United States
Environmental Protection
kl M m Agency
EP A/600/R-16/3 7 2
February 2017
www, epa. eov/ncea/isa
Integrated Science Assessment
for Oxides of Nitrogen, Oxides of
Sulfur, and Particulate Matter—
Ecological Criteria
(First External Review Draft)
National Center for Environmental Assessment-RTP Division
Office of Research and Development
U.S. Environmental Protection Agency
Research Triangle Park, NC
-------
Disclaimer
This document is an external review draft, for review purposes only. This information is
distributed solely for predissemination peer review under applicable information quality
guidelines. It has not been formally disseminated by EPA. It does not represent and
should not be construed to represent any Agency determination or policy. Mention of
trade names or commercial products does not constitute endorsement or recommendation
for use.
February 2017
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Contents
INTEGRATED SCIENCE ASSESSMENT TEAM FOR OXIDES OF NITROGEN, OXIDES OF
SULFUR, AND PARTICULATE MATTER—ECOLOGICAL CRITERIA xxix
AUTHORS, CONTRIBUTORS, AND REVIEWERS xxxi
CLEAN AIR SCIENTIFIC ADVISORY COMMITTEE OXIDES OF NITROGEN, OXIDES OF
SULFUR, AND PARTICULATE MATTER—ECOLOGICAL CRITERIA NAAQS
REVIEW PANEL xxxv
ACRONYMS AND ABBREVIATIONS xxxvii
PREFACE xlvii
Legislative Requirements for the Review of the National Ambient Air Quality Standards xlvii
Overview and History of the Reviews of the Secondary National Ambient Air Quality Standards
for Nitrogen Dioxide, Sulfur Dioxide, and Particulate Matter xlviii
Nitrogen Dioxide Secondary National Ambient Air Quality Standards xlviii
Sulfur Dioxide Secondary National Ambient Air Quality Standards xlix
Particulate Matter Secondary National Ambient Air Quality Standards liii
Most Recent Combined Review of the Oxides of Nitrogen and Oxides of Sulfur
National Ambient Air Quality Standards Ivi
EXECUTIVE SUMMARY lix
Purpose and Scope of the Integrated Science Assessment lix
Figure ES-1 Schematic of the integrated science assessment linking
atmospheric concentrations and deposition, soil and aquatic
biogeochemistry, and biological effects Ixi
Emissions, Ambient Air Concentrations, and Deposition Ixi
Ecological Effects Ixiii
Table ES-1 Causal determinations for relationships between criteria
pollutants and ecological effects from the 2008 and current
draft Integrated Science Assessment. Ixv
Gas-Phase Direct Phytotoxic Effects Ixvii
Nitrogen and Sulfur Deposition: Terrestrial Ecosystems Ixviii
Soil Biogeochemistry Ixviii
Biological Effects Ixx
Nitrogen and Acidifying Deposition: Freshwater Ixxii
Aquatic Biogeochemistry Ixxiii
Biological Effects Ixxiv
Nitrogen Deposition: Estuarine Ixxvii
Aquatic Biogeochemistry Ixxviii
Biological Effects Ixxix
Nitrogen Deposition: Wetlands Ixxx
Soil/Sediment Biogeochemistry Ixxx
Biological Effects Ixxx
Sulfur Deposition: Wetlands and Freshwater Ixxxi
CHAPTER 1 INTEGRATED SYNTHESIS 1-1
1.1 Introduction to this ISA 1-1
1.1.1 Purpose 1-1
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1.1.2 Process and Development 1-3
Figure 1-1 Workflow for collecting relevant literature for the 2017
Integrated Science Assessment for Oxides of Nitrogen, Oxides
of Sulfur, and Particulate Matter—Ecological Criteria 1-4
1.1.3 Organization 1-5
1.1.4 Main Findings 1-6
Figure 1-2 Overview of atmospheric chemistry, deposition, and ecological
effects of emissions of oxides of nitrogen, oxides of sulfur, and
reduced nitrogen. 1-7
Table 1-1 Causal determinations for relationships between criteria
pollutants and ecological effects from the 2008 and current
draft Integrated Science Assessment. 1-9
1.2 Emissions and Atmospheric Chemistry 1-11
1.2.1 Sources and Atmospheric Transformations 1-12
1.2.2 Measurement and Modeling Techniques 1-13
1.2.3 Spatial and Temporal Variability in Deposition 1-14
Figure 1-3 Three-year (2011 to 2013) average annual dry + wet
deposition of total oxidized nitrogen and reduced nitrogen
species in kilograms of nitrogen per hectare per year. 1-15
Figure 1-4 Total deposition of total oxidized nitrogen, reduced nitrogen,
and oxidized sulfur expressed as H+ equivalents per hectare
per year over the contiguous U.S. 2011-2013. 1-17
1.3 Core Ecological Concepts 1-18
1.3.1 Ecosystem Scale, Structure and Function 1-18
1.3.2 The Importance of Biodiversity 1-20
1.3.3 Critical Loads as an Organizing Principle 1-21
Figure 1-5 An example of the matrix of information considered in defining
and calculating critical loads (see discussion in text). Note that
multiple alternative biological indicators, critical biological
responses, chemical indicators, and critical chemical limits
could be used. 1-22
1.3.4 Source apportionment of N and S to Ecosystems 1-23
1.3.5 Reduced Versus Oxidized Nitrogen Effects Across Ecosystems 1-24
1.4 Gas-phase Direct Phytotoxic Effects 1-24
1.4.1 Sulfur Dioxide 1-25
1.4.2 Nitrogen Oxide, Nitrogen Dioxide, and Peroxyacetyl Nitrate 1-26
1.4.3 Nitric Acid 1-26
1.5 Terrestrial Ecosystem Nitrogen Enrichment and Acidification 1-26
1.5.1 Soil Biogeochemistry 1-28
Table 1-2 Summary of key soil geochemical processes and indicators
associated with eutrophication and acidification. 1-29
1.5.2 Biological Effects of Terrestrial Nitrogen Enrichment 1-34
Figure 1-6 Summary of critical loads in the U.S. for shrubs and
herbaceous plants (yellow), trees (blue), lichens (green), and
mycorrhizae (grey). 1-44
1.5.3 Biological Effects of Acidification 1-44
Figure 1-7 Forest ecosystem critical loads for soil acidity related to base
cation soil indicators. 1-48
1.6 Freshwater Ecosystem Nitrogen Enrichment and Acidification 1-48
1.6.1 Freshwater Biogeochemistry 1-49
Table 1-3 Summary of key aquatic geochemical processes and indicators
associated with eutrophication and acidification. 1-51
1.6.2 Biological Effects of Freshwater Acidification 1-57
Figure 1-8 Surface water critical loads for acidity in the U.S. 10th
percentile aggregation for 36 km2 grids with S and N. 1-61
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1.6.3 Biological Effects of Freshwater Nitrogen Enrichment 1-63
1.7 Estuarine and Near-Coastal Ecosystem Nitrogen Enrichment and Acidification 1-66
1.7.1 Estuary and Near-Coastal Biogeochemistry 1-67
1.7.2 Biological Effects of Nitrogen Enrichment 1-69
1.7.3 Biological Effects of Ocean Acidification 1-72
1.7.4 National-Scale Sensitivity and Critical Loads 1-72
1.8 Wetland Ecosystem Nitrogen Enrichment and Acidification 1-74
1.8.1 Wetland Biogeochemistry 1-74
1.8.2 Biological Effects of Wetland Nitrogen Enrichment/Eutrophication 1-76
1.8.3 National Sensitivity and Critical Loads for Wetlands 1-77
1.9 Nonacidifying Sulfur Enrichment 1-78
1.9.1 Biogeochemistry 1-79
1.9.2 Biological Effects of Nonacidifying Sulfur 1-80
1.9.3 National-Scale Sensitivity and Critical Loads 1-83
1.10 Recovery 1-83
1.11 Climate Modification of Ecosystem Response 1-84
1.12 Ecosystem Services 1 -85
CHAPTER 2 SOURCE TO DEPOSITION 2-1
2.1 Introduction 2-1
2.2 Sources of Nitrogen and Sulfur Compounds to the Atmosphere 2-3
Table 2-1 Emissions of NOx (nitric oxide + nitrogen dioxide), sulfur
dioxide, and ammonia by source category for 2014
(Teragrams3 N, S/yr). 2-4
2.3 Atmospheric Chemistry of Nitrogen and Sulfur Species 2-7
Figure 2-1 Schematic diagram showing pathways for reactive nitrogen
species in ambient air. 2-8
Table 2-2 Henry's law coefficients for selected reactive nitrogen species
at 25°C in water. 2-9
2.3.1 Sulfur Oxides 2-11
Figure 2-2 Rate of conversion of sulfur (IV) to sulfur (VI) by different
oxidation paths as a function of pH. 2-13
2.3.2 Organic Nitrogen and Sulfur 2-15
2.3.3 Organic Acids 2-16
2.4 Atmospheric Transport of Nitrogen and Sulfur Species 2-16
Figure 2-3 The diurnal evolution of the planetary boundary layer when
high pressure prevails over land. Three major layers exist (not
including the surface layer): a turbulent mixed layer; a less
turbulent residual layer, which contains air formerly in the
mixed layer; and a nocturnal, stable boundary layer, which is
characterized by periods of sporadic turbulence. 2-18
Figure 2-4 Locations of low-level jet occurrences in decreasing order of
prevalence (most frequent, common, observed). These
locations are based on 2-year radiosonde data obtained over
limited areas. 2-19
Figure 2-5 Idealized flow pattern around a Bermuda High. 2-20
Figure 2-6 Transport by conveyor belts associated with a frontal system
shown as heavy black lines. 2-21
2.5 Techniques for Measuring Nitrogen and Sulfur Species in the Atmosphere 2-22
2.5.1 Measurements of Nitric Oxide and Nitrogen Dioxide 2-22
2.5.2 Measurements of Total Oxidized Nitrogen Compounds in the Atmosphere 2-24
2.5.3 Nitric Acid and Particulate Nitrate 2-25
Figure 2-7 Clean Air Status and Trends Network filter pack. 2-26
2.5.4 Ammonia 2-27
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2.5.5 Sulfur Dioxide
2-30
Figure 2-8 Comparison between weekly average measurements of sulfur
dioxide using the Clean Air Status and Trends Network filter
pack and the trace ultraviolet pulsed fluorescence monitor in
2014. 2-32
Table 2-3 Sources of uncertainty for individual Ozone Monitoring
Instrument measurements in the study of Nowlan et al. (2014). 2-33
2.5.6 Methods for Measuring Nitrate and Sulfate in Other Networks 2-33
2.6 Geographic Distributions of Species Relevant for Deposition 2-36
Figure 2-9 Distribution of annual average total oxidized nitrogen species
for 2011 simulated by Community Multiscale for Air Quality
modeling system. 2-36
2.6.1 Nitrogen Dioxide 2-37
2.6.2 Nitric Acid 2-37
2.6.3 Particulate Nitrate 2-37
Figure 2-10 Seasonal average surface nitrogen dioxide mixing ratios
in parts per billion for winter (upper panel) and summer (lower
panel) derived by Ozone Monitoring Instrument/GEOS-Chem
for 2009-2011. Ozone Monitoring Instrument has overpass at
approximately 1:30 p.m. local standard time. 2-38
Figure 2-11 Three-year average (2011 -2013) surface concentrations of
nitric acid based on monitoring data obtained at Clear Air
Status and Trends Network sites (black dots). 2-39
Figure 2-12 Three-year average (2011-2013) surface concentrations of
particulate nitrate based on monitoring data obtained at Clear
Air Status and Trends Network sites (black dots). 2-40
Figure 2-13 Average (2012) surface concentration of ammonia obtained by
the Ambient Ammonia Monitoring Network at select Clear Air
Status and Trends Network sites. Concentrations of ammonia
(|jg/m3) can be can be converted to mixing ratios (parts per
billion) to rough approximation at normal temperature and
pressure by multiplying by 1.4. 2-41
Figure 2-14 Three-year average (2011-2013) surface concentrations of
particulate ammonium (|jg/m3) based on monitoring data
obtained at Clear Air Status and Trends Network sites (black
dots). 2-42
2.6.4 Ammonia 2-42
2.6.5 Particulate Ammonium 2-43
2.6.6 Sulfur Dioxide 2-43
2.6.7 Particulate Sulfate 2-43
Figure 2-15 Three-year average (2011 -2013) surface concentrations of
sulfur dioxide obtained by fusion of monitoring data obtained at
Clear Air Status and Trends Network sites (black dots) and
Community Multiscale for Air Quality model system results.
Concentrations (|jg/m3) can be can be converted to mixing
ratios (parts per billion) at normal temperature and pressure) to
rough approximation by multiplying by 0.37. 2-44
Figure 2-16 Three-year average (2011-2013) surface concentrations of
particulate sulfate based on monitoring data obtained at Clear
Air Status and Trends Network sites (black dots). 2-45
2.7 Deposition 2-45
Figure 2-17 Schematic diagram showing mechanisms for transferring
pollutants from the atmosphere to the surface. 2-46
2.7.1 Wet Deposition 2-46
2.7.2 Dry Deposition 2-48
Table 2-4 Average dry deposition velocities (cm/s) for a number of gases
over land surfaces. 2-53
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Table 2-5 Deposition velocity (cm/s) for sulfur dioxide averaged over
different land use types for summer and winter. 2-53
Figure 2-18 Relationships among particle diameter, flux, and deposition
velocity for particles measured in ambient air in Chicago, IL. 2-55
Figure 2-19 Modeled and measured deposition velocities over grass (left
figure) and coniferous forest canopies (right figure) for particles
of density 1 gm/cm3 depositing under similar friction velocity
(35 < U' < 56 cm/s). 2-56
2.7.3 Occult Deposition in Clouds and Fogs 2-57
2.7.4 Deposition of Nitrogen Species in the Forest Canopy and Throughfall 2-58
Figure 2-20 Schematic of the interactions involved in the exchange of
nitrogen oxides between the atmosphere and the forest canopy
as identified by Min et al. (2014). 2-60
2.8 Geographic Distribution of Deposition of Nitrogen and Sulfur Species 2-61
2.8.1 Distribution of Deposition Derived Using Surface Measurements and
Chemistry Transport Models 2-62
Figure 2-21 Total (wet + dry) deposition of nitrogen (kg N/ha/yr) over the
contiguous U.S. 2011 -2013. 2-63
Figure 2-22a Percent of total nitrogen deposition as reduced inorganic
nitrogen over the contiguous U.S. 2011-2013. 2-64
Figure 2-22b Percent of total nitrogen deposition as oxidized nitrogen over
the contiguous U.S. 2011-2013. 2-64
Figure 2-23a Total reduced inorganic nitrogen deposition over the
contiguous U.S. 2011 -2013. 2-65
Figure 2-23b Total oxidized nitrogen deposition over the contiguous U.S.
2011 -2013. 2-65
Figure 2-24 Three-year average percentage of total nitrogen deposition by
species (i.e., those species that are not measured in the
networks) simulated by the Community Multiscale for Air
Quality modeling system. 2-67
Figure 2-25 Total deposition of Sulfur (kg S/ha/yr) over the contiguous U.S.
2011 -2013. 2-68
Figure 2-26 Percentage of deposition of total sulfur as dry deposition over
the contiguous U.S. 2011-2013. 2-69
2.8.2 Changes in Deposition since 2000 Based on Modeling and Measurements 2-69
2.8.3 Long-Term Changes in Wet Deposition 2-71
Figure 2-27 (Left) pH of rainwater, 1989-1991; (Right) pH of rainwater,
2011 -2013. 2-71
Figure 2-28 Difference in wet deposition of ammonium (kg N/ha/yr) over
the contiguous U.S. between 1989 to 1991 and 2012 to 2014. 2-73
Figure 2-29 Difference in wet deposition of nitrate (kg N/ha/yr) over the
contiguous U.S. between 1989 to 1991 and 2012 to 2014. The
range of positive values is smaller than that for negative
values. 2-74
Figure 2-30 Difference in wet deposition of sulfate (kg S/ha/yr) over the
contiguous U.S. between 1989 to 1991 and 2012 to 2014. The
range of positive values is much smaller than for negative
values. 2-75
Figure 2-31 Difference in wet deposition of nitrate, ammonium and sulfate
expressed as hydrogen ion equivalents (eq/ha/yr) over the
contiguous U.S. between 1989 to 1991 and 2012 to 2014. 2-76
Figure 2-32 Wet deposition of ammonium + nitrate (kg N/ha/yr) over the
contiguous U.S. in two, 3-year periods, 2012 to 2014 and 1989
to 1991. Also shown are active National Trends Network sites
in either period. 2-77
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2.8.4 Distributions of Dry Deposition of Nitrogen Dioxide and Sulfur Dioxide
Derived Using Satellite-Based Measurements and Chemistry Transport
Models 2-78
Figure 2-33 Top panel: Modeled deposition velocities for nitrogen dioxide
and sulfur dioxide for 2005 to 2007; Middle panel
Satellite-model estimates of annual mean dry deposition fluxes
of nitrogen dioxide and sulfur dioxide; Bottom panel:
Uncertainties in estimates. 2-79
2.9 Transference Ratios Relating Deposition to Ambient Oxidized Nitrogen Species and
Sulfur Oxides. 2-80
Figure 2-34 Scatterplots showing transference ratios for oxidized nitrogen
and sulfur oxides comparing Community Multiscale for Air
Quality model to Comprehensive Air Quality Model with
Extensions in (a) and (c) and comparing 2005 to 2014 in (b)
and (d). 2-82
2.10 Background Sources of Oxidized and Reduced Nitrogen and Oxidized Sulfur Species 2-83
Figure 2-35 Contributions to oxidized and reduced nitrogen deposition from
U.S. anthropogenic (top), foreign anthropogenic (middle) and
natural sources (bottom). 2-84
2.11 Summary 2-86
CHAPTER 3 DIRECT PHYTOTOXIC EFFECTS OF GASEOUS OXIDIZED NITROGEN AND
SULFUR ON VEGETATION 3-1
3.1 Introduction 3-1
Figure 3-1 The microarchitecture of a dicot leaf. While details among
species vary, the general overview remains the same. Light
that drives photosynthesis generally falls upon the upper
(adaxial) leaf surface. Carbon dioxide, sulfur oxides, oxides of
nitrogen, and ozone gases generally enter by diffusion through
the guard cells (or stomata) on the lower (abaxial) leaf surface,
while water vapor exits through the stomata (transpiration). 3-3
3.2 Direct Phytotoxic Effects of Sulfur Dioxide on Vegetation 3-3
3.3 Direct Phytotoxic Effects of Nitric Oxide, Nitrogen Dioxide, and Peroxyacetyl Nitrate 3-6
3.4 Direct Phytotoxic Effects of Nitric Acid 3-11
3.5 Summary 3-13
3.5.1 Sulfur Dioxide 3-13
3.5.2 Nitrogen Oxide, Nitrogen Dioxide, and Peroxyacetyl Nitrate 3-14
3.5.3 Nitric Acid 3-14
CHAPTER 4 SOIL BIOGEOCHEMISTRY 4-1
4.1 Introduction 4-1
4.2 Nitrogen and Sulfur Sources to Soil 4-1
Figure 4-1 Dominant sources of nitrogen across the U.S. at 8-digit
Hydrologic Unit Codes. 4-3
Figure 4-2 Percentage of nitrogen input from nitrogen deposition at 8-digit
Hydrologic Unit Codes. 4-3
4.3 Soil Pools and Processes 4-4
Table 4-1 Summary of key soil geochemical processes and indicators
associated with eutrophication and acidification. 4-5
4.3.1 Nitrogen Pathways and Pools 4-6
Table 4-2 Pathways and pools. 4-7
4.3.2 Nitrogen Accumulation, Saturation, and Leaching 4-9
Figure 4-3 Hypothesized temporal patterns of response of forest
ecosystem properties to continuing nitrogen additions. 4-12
Figure 4-4 A hypothetical model to account for the effects of nitrogen
supply on plant nitrogen uptake and belowground carbon
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allocation, microbial production of inorganic nitrogen, and
nitrogen leaching. 4-13
Table 4-3 Nitrogen accumulation, saturation, and leaching. 4-13
4.3.3 Sulfate Accumulation, Adsorption, and Leaching 4-19
Table 4-4 Sulfate adsorption and leaching. 4-20
4.3.4 Base Cations 4-22
Table 4-5 Base cations. 4-23
4.3.5 Aluminum 4-25
4.3.6 Nitrification and Denitrification 4-26
Figure 4-5 Effects of nitrogen addition on biogenic nitrous oxide emission. 4-28
Figure 4-6 The weighted response ratio for the responses to nitrogen
addition for fluxes and pools related to the ecosystem nitrogen
cycle in agricultural (open bars) and nonagricultural (closed
bars) ecosystems. 4-29
Table 4-6 Nitrification and denitrification. 4-30
4.3.7 Decomposition 4-35
Table 4-7 Decomposition. 4-37
4.3.8 Nitrogen Mineralization 4-43
Figure 4-7 The effects of nitrogen inputs on soil carbon, carbon:nitrogen
ratio, and minimum nitrogen in forest floors (panels A-C) and
mineral soils (panels D-F). 4-45
Table 4-8 Nitrogen mineralization. 4-46
4.3.9 Dissolved Organic Carbon Leaching 4-47
Figure 4-8 Conceptual diagram of positive (solid arrows) and negative
(dashed arrows) fluxes in nitrogen pools (squares) and carbon
pools (ovals) and the biological processes (no border) that are
affected by experimental nitrogen deposition. 4-49
Table 4-9 Terrestrial dissolved organic carbon leaching. 4-50
4.3.10 Belowground Carbon Pools 4-51
Figure 4-9 Estimation of the changes in carbon budget of terrestrial
ecosystem under nitrogen. 4-52
4.3.11 New Biogeochemical Indicators 4-53
Table 4-10 New biogeochemistry indicators. 4-53
4.3.12 Disturbance and Stand Age Effects on Nitrogen Retention 4-54
4.4 Soil Monitoring and Databases 4-55
Table 4-11 Biogeochemistry monitoring and databases. 4-56
4.5 Models 4-58
4.5.1 Updates to Key Previously Identified Models 4-59
4.5.2 New Models (Published since 2008) 4-65
4.6 National-Scale Sensitivity 4-66
4.6.1 Acidification Recovery 4-67
4.6.2 Critical Loads 4-69
Figure 4-10 Forest ecosystem critical loads for soil acidity related to base
cation soil indicators. 4-70
Figure 4-11 Map of critical loads for nitrate leaching by ecoregion in the
U.S. 4-72
4.7 Summary 4-72
4.7.1 Sources 4-72
4.7.2 Soil Processes and Indicators 4-73
Table 4-12 Summary of key soil geochemical processes and indicators
associated with eutrophication and acidification. 4-74
4.7.3 Monitoring 4-79
4.7.4 Models 4-80
4.7.5 National-Scale Sensitivity 4-83
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CHAPTER 5 BIOLOGICAL EFFECTS OF TERRESTRIAL ACIDIFICATION
5-1
5.1
Introduction
5.2
5.3
5.4
5.5
5.6
Table 5-1
Figure 5-1
Mode of action for acidifying nitrogen and sulfur deposition.
Diagram based on Fenn et al. (2006) showing indicators of
forest physiological function, growth, and structure that are
linked to biogeochemical cycles through processes that control
rates of calcium supply. Calcium affects plant physiological
processes that influence growth rates and the capacity of
plants to resist environmental stresses, such as extremes of
temperature, drought, insects, and diseases. Therefore,
acidifying deposition, which can deplete soil calcium or
interfere with calcium uptake through mobilization of soil
aluminum, can affect forest health.
Table 5-2 Relationships between soil chemistry indicators and biological
endpoints that have been evaluated in the literature since the
2008 Integrated Science Assessment.
Effects on Terrestrial Organisms and Ecosystems
5.2.1 Trees and Forests
Table 5-3 Summary of calcium addition studies in North America.
Figure 5-2 Relationship between the proportion of seedlings that were
sugar maple and soil base saturation in the upper B-horizon._
Forest Understory and Grassland Species
Lichens
5.2.2
5.2.3
5.2.4
5.2.5
Characteristics, Distribution, and Extent of Sensitive Ecosystems
Application of Terrestrial Acidification Models
Soil Biota_
Fauna
Levels of Deposition at Which Effects Are Manifested
5.5.1
5.5.2
Impacts of Elevated Nitrogen and Sulfur Deposition
Table 5-4 Impacts of acidifying nitrogen and sulfur deposition.
Impacts of Ambient Deposition
Table 5-5 Results of Spearman's rank correlation analysis comparing
growth versus critical load exceedance by species for the
forested plots in the northeastern U.S. [from Duarte et al.
(2013)]. Modeled sulfur and nitrogen deposition on the plots
ranged from 242 to 1,154 eq/ha/yr and 256 to 920 eq/ha/yr,
respectively. Correlations shown here are significant at
a = 0.05.
Table 5-6 Results of Spearman's rank correlation analyses comparing
tree vigor, crown density and dieback, and canopy
transparency versus critical load exceedance by species for
the forested plots in the northeastern U.S. [from Duarte et al.
(2013)]. Modeled sulfur and nitrogen deposition on the plots
ranged from 242 to 1,154 eq/ha/yr and 256 to 920 eq/ha/yr,
respectively. Correlations shown here are significant at
a = 0.05.
5.5.3 Critical Loads and Exceedances
Summary
5.6.1 Physiology and Growth
5.6.2 Biodiversity
5.6.3 National-Scale Sensitivity and Critical Loads
5-1
5-3
5-9
10
12
12
14
5-18
5-25
5-26
5-27
5-29
5-30
5-34
5-35
5-35
5-38
5-43
5-44
5-45
5-47
5-54
5-54
5-56
5-57
CHAPTER 6
TERRESTRIAL ECOSYSTEMS: NITROGEN ENRICHMENT EFFECTS ON
ECOLOGICAL PROCESSES
6.1 Linking Nitrogen Deposition to Changes in Physiology, Growth, and Productivity in
Terrestrial Ecosystems
6-1
6-1
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6.1.1 Introduction
6.1.2 Mechanisms Operating across Terrestrial Ecosystems
6.1.5
6.1.6
Figure 6-1
Figure 6-2
Table 6-1
6.1.3 Forests
Table 6-2
Table 6-3
Effects of nitrogen additions on plant growth and net primary
productivity.
Effects of added nitrogen on ecosystem carbon pools and
fluxes.
Changes in terrestrial ecological and biogeochemical
endpoints caused by different forms of inorganic nitrogen in
meta-analyses.
6-1
6-3
6-6
6-8
6-11
6-15
Growth, productivity, and carbon cycle responses of
ectomycorrhizal fungi to nitrogen added via atmospheric
deposition or experimental treatments. 6-23
Growth, productivity, and carbon cycle responses of arbuscular
mycorrhizal fungi to nitrogen added via atmospheric deposition
or experimental treatments. 6-26
Table 6-4
Table 6-5
Figure 6-3
Abundance and carbon cycle responses of forest soil
microorganisms to nitrogen added in experimental treatments.
Growth and physiology responses of forest epiphytic lichens to
nitrogen added via atmospheric deposition or experimental
treatments.
Studies reporting the response of forest (A) aboveground
biomass carbon sequestration and (B) ecosystem carbon
sequestration to nitrogen deposition or long-term nitrogen
additions.
6.1.4 Arctic and Alpine Tundra and Grasslands_
Alpine and Arctic tundra plant producitivity and physiology
responses to nitrogen added via atmospheric deposition or
experimental treatments.
Alpine and Arctic tundra lichen growth and physiology
responses to nitrogen added via atmospheric deposition or
experimental treatments.
Growth and biodiversity responses of ericoid mycorrhizal fungi
to nitrogen added in experimental treatments.
Table 6-6
Table 6-7
Table 6-8
Table 6-9
Grasslands
Table 6-10 Grassland microbial biomass responses to experimental
nitrogen additions.
Arid and Semiarid Ecosystems
Table 6-11 Arid and semiarid ecosystem plant producitivity and physiology
responses to nitrogen added in experimental treatments.
Table 6-12 Arid and semiarid microbial biomass responses to
experimental nitrogen additions.
Physiology, Growth, and Productivity Summary
Alpine and Arctic tundra microbial biomass responses to
experimental nitrogen additions.
6.1.7
6.2 Relationships between Nitrogen Deposition and Terrestrial Species Composition,
Species Richness, and Biodiversity
6.2.1 Introduction
6.2.2 Mechanisms Operating across Terrestrial Ecosystems
6.2.3 Forests
Table 6-13
Table 6-14
Table 6-15
Forest plant diversity responses to nitrogen added via
atmospheric deposition or experimental treatments.
Forest microbial biodiversity responses to experimental
nitrogen additions.
6-30
6-35
.6-41
6-42
.6-44
.6-58
.6-61
.6-62
.6-64
.6-69
.6-71
.6-76
.6-82
.6-83
.6-85
.6-85
.6-87
.6-90
.6-92
6-96
Ectomycorrhizal biodiversity responses to nitrogen added via
atmospheric deposition or experimental N additions.
6-101
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Table 6-16 Arbuscular mycorrhizal responses to nitrogen added via
atmospheric deposition or experimental treatments. 6-103
Table 6-17 Arthropod responses to experimental nitrogen additions. 6-106
6.2.4 Alpine and Arctic Tundra 6-108
Table 6-18 Alpine and Arctic tundra plant diversity responses to nitrogen
added via atmospheric deposition or experimental treatments. 6-111
Table 6-19 Alpine and Arctic tundra microbial diversity responses to
nitrogen added via experimental treatments. 6-114
6.2.5 Grasslands 6-115
Table 6-20 Grassland microbial diversity responses to nitrogen added via
experimental treatments. 6-122
6.2.6 Arid and Semiarid Ecosystems 6-122
Table 6-21 Arid and semiarid ecosystem plant diversity responses to
nitrogen added via atmospheric deposition or experimental
treatments. 6-126
Table 6-22 Arid and semiarid ecosystem microbial diversity responses to
nitrogen added via experimental treatments. 6-129
6.2.7 Lichens 6-130
Table 6-23 Lichen biodiversity responses to nitrogen added via
atmospheric deposition or experimental treatments. 6-131
6.2.8 Biodiversity Summary 6-134
6.3 Most Sensitive and Most Affected Terrestrial Ecosystems and Regions 6-137
6.4 Critical Loads 6-138
6.4.1 Mycorrhizal Fungi 6-140
Figure 6-4 Map of critical loads for mycorrhizal fungi by ecoregion in the
U.S. 6-141
Table 6-24 Mycorrhizal critical loads. 6-142
6.4.2 Lichens and Bryophytes 6-142
Figure 6-5 Map of critical loads for lichens by ecoregion in the U.S. 6-145
Table 6-25 Lichen critical loads. 6-146
6.4.3 Herbaceous and Shrub Species 6-148
Figure 6-6 Map of critical loads for herbaceous plants and shrubs by
ecoregion in the U.S. 6-150
Figure 6-7 Nitrogen deposition (gray scale) and critical loads for nitrogen
deposition based on total graminoid plus forb species richness
(colored symbols). 6-151
Table 6-26 Summary of U.S. critical loads for nitrogen and corresponding
herbs and shrubs. 6-152
6.4.4 T rees 6-154
Figure 6-8 Map of critical loads for forest ecosystems by ecoregion in the
U.S. 6-155
Table 6-27 Tree critical loads. 6-156
6.4.5 National-Scale Exceedance Studies 6-156
6.4.6 Critical Loads Summary 6-157
Table 6-28 Critical loads for nitrogen by Pardo et al. (2011c) with newer
information on thresholds. 6-158
CHAPTER 7 AQUATIC BIOGEOCHEMISTRY 7-1
7.1 Introduction 7-1
7.2 Freshwater 7-2
7.2.1 Nitrogen Sources to Freshwater 7-3
Table 7-1 Summary of recent studies quantifying nitrogen deposition
contribution to total nitrogen loading in freshwater systems. 7-5
7.2.2 Sulfur Sources to Freshwater 7-8
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7.2.3 Chemical Processes and Effects Indicators 7-9
Table 7-2 Commonly used geochemical indicators of freshwater nutrient
enrichment and acidification caused by nitrogen and sulfur
deposition that were identified by the 2008 Integrated Science
Assessment for Oxides of Nitrogen and Sulfur—Ecological
Criteria. 7-10
Figure 7-1 Nitrogen cycle in freshwater ecosystem (U.S. EPA, 2008a). 7-13
7.2.4 Monitoring Data 7-27
Table 7-3 Monitoring and resurvey results of aquatic acidification and/or
chemical recovery since the 2008 Integrated Science
Assessment for Oxides of Nitrogen and Sulfur-Ecological
Criteria. 7-30
7.2.5 Freshwater Modeling 7-41
Table 7-4 Model projections of surface water sulfate and associated acid
neutralizing capacity, shown as changes between dates, for
Adirondack and Shenandoah streams. 7-44
Table 7-5 Recent process-based model estimates of surface water
acidification and chemical recovery in the U.S. 7-46
7.2.6 Water Quality Criteria 7-50
Table 7-6 Water quality criteria for rivers/streams by state (all values in
mg/L, shaded by criteria level). 7-52
Table 7-7 U.S. Environmental Protection Agency aggregate Level III
ecoregion nutrient criteria (all values in mg/L and shaded by
criteria level; U.S. Environmental Protection Agency
ecoregional nutrient criteria documents for rivers and streams). 7-53
Figure 7-2A Total nitrogen criterion values by ecoregion. 7-54
Figure 7-2B Chlorophyll a criterion values by ecoregion. 7-54
7.3 Estuaries and Near-Coastal Areas 7-55
7.3.1 Nitrogen Sources to Estuarine and Near-Coastal Areas 7-56
Figure 7-3 Chemical nitrogen cascade in the Chesapeake Bay Watershed
(metric tons/year). 7-58
Table 7-8 Summary of studies quantifying atmospheric nitrogen
contribution to total nitrogen in coastal areas via watersheds
and/or direct deposition to estuary surface waters. 7-59
7.3.2 Chemical Effects and Processes in Estuaries and Near-Coastal Areas 7-62
Figure 7-4 Schematic diagram illustrating sources, transformations and
fate of nitrogen along the estuary-to-ocean continuum.
Surface, subsurface, and atmospheric pathways of externally
supplied or new nitrogen inputs attributable to anthropogenic
activities are shown as internal nitrogen cycling. The combined
anthropogenic nitrogen inputs are shown as a thick arrow
(upstream), which decreases in thickness downstream as a
portion of the nitrogen inputs settles to the bottom sediments
and is buried and/or denitrified. Nitrogen (N2) fixation is a
biologically mediated new nitrogen input. The linkage of
anthropogenically enhanced nitrogen inputs to accelerated
primary production or eutrophication and its trophic and
biogeochemical fate are also shown. 7-64
7.3.3 Modeling Estuaries and Near-Coastal Areas 7-68
7.4 Summary 7-72
7.4.1 Freshwater Biogeochemistry Summary 7-72
7.4.2 Estuary and Near-Coastal Biogeochemistry Summary 7-77
CHAPTER 8 BIOLOGICAL EFFECTS OF FRESHWATER ACIDIFICATION 8-1
8.1 Introduction 8-1
8.2 Chronic versus Episodic Acidification and Biological Response 8-3
8.3 Aquatic Organisms Impacted by Acidifying Deposition 8-4
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.3.1 Plankton 8-5
.3.2 Periphyton 8-8
.3.3 Benthic Invertebrates 8-8
Figure 8-1 Total macroinvertebrate species (community) richness as a
function of median pH in 36 streams sampled in the western
Adirondack Mountains of New York, 2003-2005; the four
standard (New York State) impact categories for species
richness are defined. 8-10
Table 8-1 Thresholds of biological response to changes in water acidity
in benthic invertebrates published since the 2008 Integrated
Science Assessment for Oxides of Nitrogen and
Sulfur-Ecological Criteria. 8-11
8.3.4 Bacteria, Macrophytes, and Bryophytes 8-12
8.3.5 Amphibians 8-13
8.3.6 Fish 8-14
Figure 8-2 Relationship between pH (a) or gill aluminum (b) and
physiological response factor of Atlantic salmon (Salmo salar)
smolts in five study sites and two trials. 8-17
Figure 8-3 Relationship between (a) cationic aluminum (labile aluminum
and inorganic monomeric aluminum) and gill aluminum for parr
and smolt. (b) Relationship between acid neutralizing capacity
and gill aluminum. 8-19
Figure 8-4 Critical aquatic pH ranges for fish species. 8-21
Table 8-2 pH thresholds in fish published since the 2008 Integrated
Science Assessment for Oxides of Nitrogen and Sulfur-
Ecological Criteria. 8-23
Figure 8-5 Number of fish species per lake verses acidity status,
expressed as acid neutralizing capacity, for Adirondack lakes. 8-24
Table 8-3 Expected ecological effects and concern levels in freshwater
ecosystems at various levels of acid neutralizing capacity. 8-26
Table 8-4 Threshold values of aluminum for various fish species and
effects. 8-28
Figure 8-6 Relationship between (a) pH, (b) cationic aluminum, (c) acid
neutralizing capacity and (d) gill aluminum and accumulated
mortality of smolt. 8-32
8.3.7 Fish-Eating Birds 8-33
8.3.8 Aquatic Assemblages 8-33
Figure 8-7 Species richness of biotic groups in 30 Adirondack study lakes
relative to midsummer epilimnetic pH in the sample years. 8-35
Figure 8-8 Structure of diatom assemblage in 20 streams across a pH
gradient of 4.5-8.5. (a) Species richness (log-io-transformed
numbers of diatom species per stream), (b) total abundance of
diatoms (log-io-transformed numbers of individuals per m2),
(c) chlorophyll a concentration (mg chlorophyll a per m2), as a
measure of algal biomass. 8-36
Figure 8-9 Macroinvertebrate community composition in 20 streams
across a pH gradient. Taxon richness (total number of primary
consumer taxa; left panel) and benthic density [number of
individuals logio(x+ 1)-transformed; right panel] plotted against
stream pH, all primary consumers (a, b), shredders (excluding
Leuctridae and Nemouridae) (c, d), herbivore-detritivores
(Leuctridae and Nemouridae) (e, f), collectors (g, h) and
grazers (i, j). 8-37
8.4 Documentation of Biological Recovery 8-38
8.4.1 Phytoplankton Recovery 8-39
Table 8-5 Paleolimnological responses to changing lake chemistry
published since the 2008 Integrated Science Assessment for
Oxides of Nitrogen and Sulfur-Ecological Criteria. 8-41
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8.4.2 Zooplankton Recovery 8-42
Figure 8-10 (A) Midsummer (sulfate) concentration in the epilimnion of
Brooktrout Lake (o) and in annual wet deposition (•) at local
National Atmospheric Deposition Program/National Trends
Network Station NY52 from 1984-2012. (B) Midsummer
epilimnetic concentrations of inorganic monomeric aluminum
(~) and [hydrogen ion] (¦) in Brooktrout Lake from 1984-2012.
(C) Midsummer phytoplankton (A) and total plankton
(phytoplankton, rotifers, crustaceans) (A) species richness in
Brooktrout Lake from 1984-2012. 8-44
Table 8-6 Midsummer values and productivity analytes in the epilimnion
of Brooktrout Lake in the Adirondack Park from the 1980s
through 2010-2012a. 8-45
8.4.3 Benthic Invertebrate Recovery 8-47
8.4.4 Fish Recovery 8-49
8.4.5 Bird Recovery 8-50
8.4.6 Mitigation 8-51
8.5 Levels of Deposition at Which Effects Are Manifested 8-51
8.5.1 Most Sensitive and Most Affected Ecosystems and Regions 8-51
Figure 8-11 Map of landscape sensitivity to acidic deposition for the
northeastern and Mid-Atlantic U.S. Stippled areas were not
considered. 8-52
8.5.2 Extent and Distribution of Sensitive Ecosystems/Regions 8-53
Figure 8-12 A synoptic illustration of surface water sensitivity to acid
deposition in the conterminous U.S. based on surface water
measurements of acid neutralizing capacity <100 peq/L from
water quality data since 1984. 8-54
Figure 8-13 (a) Minimum critical loads of surface water acidity for nitrogen
and sulfur. Grids represent the minimum calculated critical load
from all data within the 36 * 36-km grid cell. The critical
chemical criterion used was an acid neutralizing capacity of
50 peq/L. (b) Mean critical loads of surface water acidity. Grids
represent the average calculated critical load from all data
within the 36 km * 36 km grid cell. The critical chemical
criterion used was an acid neutralizing capacity 50 peq/L. 8-55
8.5.3 Deposition, Water Quality, and Biological Change 8-56
8.5.4 U.S. Critical Loads 8-56
8.5.5 Empirical Critical Loads 8-57
8.5.6 Modeled Critical Loads 8-58
Table 8-7 Recent empirical critical loads to protect against aquatic
acidification in U.S. ecosystems. 8-59
Table 8-8 Recent aquatic critical load and target load modeling studies in
the U.S. to protect against aquatic acidification. 8-61
Figure 8-14 Target loads for sulfur deposition in the Adirondack Park to
protect lake acid neutralizing capacity at 50 peq/L in the year
2010 (left map) and their exceedance (right map). 8-65
8.5.7 International Critical Loads 8-67
8.6 Aquatic Acidification Summary and Causal Determinations 8-68
Table 8-9 Ecological indicators and thresholds for aquatic acidification. 8-70
8.6.1 Phytoplankton 8-70
8.6.2 Zooplankton 8-71
8.6.3 Benthic Invertebrates 8-71
8.6.4 Fish 8-72
8.6.5 Thresholds of Response 8-73
Table 8-10 Results of recent biological effects studies in surface waters
indicative of thresholds of biological response to changes in
water acidity. 8-74
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8.6.6 Biological Recovery 8-74
8.6.7 Most Sensitive and Most Affected Regions 8-75
8.6.8 Critical Loads 8-75
CHAPTER 9 BIOLOGICAL EFFECTS OF FRESHWATER NITROGEN ENRICHMENT 9-1
9.1 Introduction to Nitrogen Enrichment and Eutrophication in Freshwater Systems 9-1
Figure 9-1 Conceptual model of the influence of atmospheric nitrogen
deposition on freshwater nutrient enrichment [modified from
Baron et al. (2011 b)]. 9-2
9.1.1 Shifting Perspectives of the Role of Nitrogen in Freshwater Eutrophication 9-3
9.1.2 Nitrogen Sources and Biogeochemical Cycling in Freshwater 9-3
Figure 9-2 Nitrogen cycle in freshwater ecosystems (U.S. EPA, 2008a). 9-4
9.1.3 Characteristics of Freshwater Systems Sensitive to Atmospheric Deposition 9-5
9.1.4 Shifts from Predominantly Nitrogen Limitation to Phosphorus Limitation in
High Alpine Lakes 9-6
Figure 9-3 Phytoplankton responses to nitrogen and/or phosphorus
enrichment for Rocky Mountain lakes receiving low or high
atmospheric nitrogen deposition, given as the ratio of final
chlorophyll concentration in the enriched treatment
(+phosphorus, +nitrogen, or+nitrogen + phosphorus) to the
chlorophyll concentration in the unenriched control. 9-7
9.1.5 Inconclusive Studies on Nutrient Limitation Shift in High Alpine Lakes 9-9
9.2 Biological Indicators 9-9
9.2.1 Chlorophyll a 9-10
9.2.2 Periphyton/Microbial Biomass 9-12
9.2.3 Diatoms 9-13
Table 9-1 Summary of studies using diatoms as biological indicators of
nitrogen enrichment evaluated in the literature since the 2008
Integrated Science Assessment for Oxides of Nitrogen and
Sulfur-Ecological Criteria. 9-14
9.2.4 Trophic Status Indices 9-17
Table 9-2 Summary of additional evidence for nitrogen limitation on
productivity of freshwater ecosystems that has been evaluated
since the 2008 Integrated Science Assessment for Oxides of
Nitrogen and Sulfur-Ecological Criteria. 9-19
9.2.5 Potential Biological Indicators 9-21
9.3 Biodiversity 9-23
9.3.1 Phytoplankton Diversity 9-23
9.3.2 Benthic Algal Diversity 9-26
9.3.3 Freshwater Invertebrate Diversity 9-28
9.3.4 Macrophytes 9-29
9.3.5 Amphibians 9-30
9.3.6 Fish 9-30
Table 9-3 Summary of studies on nitrogen effects on species
composition and biodiversity that have been evaluated in the
literature since the 2008 Integrated Science Assessment for
Oxides of Nitrogen and Sulfur-Ecological Criteria 9-31
9.4 Animal Behavior and Disease 9-34
9.4.1 Behavior 9-34
9.4.2 Disease 9-34
9.5 Nitrate Toxicity 9-35
9.5.1 Macroinvertebrates 9-36
9.5.2 Amphibians 9-36
9.5.3 Fish 9-37
9.6 Extent and Distribution of Sensitive Ecosystems/Regions 9-37
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9.7 Summary of the Levels of Deposition at Which Effects are Manifested and/or Critical
Loads 9-38
Table 9-4 Summary of critical loads for nitrogen eutrophication for
surface water in the U.S. [adapted from Pardo et al. (2011c)
with newer studies added], 9-39
Table 9-5 Nutrient enrichment inflection points for nitrogen deposition in
western regions of the U.S. [from Baron etal. (2011b)]. 9-41
9.8 Summary and Causal Determination 9-41
CHAPTER 10 BIOLOGICAL EFFECTS OF NITROGEN ENRICHMENT IN ESTUARIES AND
NEAR-COASTAL SYSTEMS 10-1
10.1 Introduction 10-1
Figure 10-1 Eutrophication can occur when the concentration of available
nutrients increases above normal levels. 10-3
10.1.1 Nitrogen Sources to Estuaries and Coasts 10-4
10.1.2 Nitrogen Transformations and Fate in Estuaries 10-4
Figure 10-2 Schematic diagram illustrating sources, transformations, and
fate of nitrogen along the estuary to ocean continuum. 10-5
10.1.3 Nitrogen Limitation 10-6
10.1.4 Characteristics of Coastal Systems Sensitive to Eutrophication 10-7
10.2 Indicators of Nutrient Enrichment 10-9
Table 10-1 Indicators of Estuarine Eutrophication. 10-10
Figure 10-3 Biological indicator responses to nutrient enrichment. 10-11
10.2.1 Chlorophyll a 10-11
Table 10-2 Chlorophyll a thresholds used in methods to evaluate the
status of phytoplankton in U.S. coastal and estuarine water
bodies. 10-12
10.2.2 Harmful/Nuisance/Toxic Algal Blooms 10-14
Table 10-3 Levels and forms of nitrogen at which effects on phytoplankton
are manifest in U.S. coastal waters evaluated in the literature
since the 2008 Integrated Science Assessment for Oxides of
Nitrogen and Sulfur-Ecological Criteria. 10-17
10.2.3 Macroalgal Abundance 10-21
10.2.4 Dissolved Oxygen 10-22
Figure 10-4 The range of ecological impacts exhibited as dissolved oxygen
levels drop from saturation to anoxia. 10-24
10.2.5 Submerged Aquatic Vegetation 10-26
Table 10-4 Nitrogen loading thresholds from multiple watershed sources
versus eelgrass loss. 10-28
Figure 10-5 Extent of submerged aquatic vegetation in the Chesapeake
Bay 1978-2015. 10-29
10.2.6 Indices of Estuarine Condition 10-30
10.3 Effects on Biodiversity 10-32
10.3.1 Paleontological Diversity 10-32
10.3.2 Phytoplankton Biodiversity 10-33
10.3.3 Biodiversity of Phytoplankton in Reduced versus Oxidized Nitrogen 10-34
10.3.4 Biodiversity of Bacteria and Archaea 10-35
10.3.5 Benthic Biodiversity 10-35
10.3.6 Fish Biodiversity 10-37
10.3.7 Trophic Interactions 10-38
10.3.8 Models Linking Indicators to Nitrogen Enrichment 10-39
Figure 10-6 Forecasting curves for effects on total nitrogen loadings on
(A) chlorophyll and (B) dissolved oxygen (mean and 95%
confidence interval) for selected estuaries demonstrating the
full range of sensitivity to relative total nitrogen loading. 10-40
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10.4 Animal Behavior and Disease 10-41
10.4.1 Behavior 10-41
Figure 10-7 The pathway of effects of eutrophication on different
reproductive behaviors and selection forces in Gasterosteus
aculeatus. 10-42
10.4.2 Disease 10-43
10.5 Nutrient Enhanced Coastal Acidification 10-44
Figure 10-8 Pathway of nutrient enhanced coastal acidification from
nitrogen loading to biological effects. Both microbial respiration
of organic matter and increasing atmospheric carbon dioxide
lower pH of coastal waters. 10-45
10.6 Extent and Distribution of Sensitive Ecosystems/Ecoregions 10-46
10.6.1 Eutrophication 10-46
Figure 10-9 Overall eutrophication condition on a national scale. 10-48
10.6.2 Coastal Acidification 10-49
10.7 Summary of Thresholds and Levels of Deposition at Which Effects Are Manifested 10-50
10.8 Summary and Causal Determinations 10-51
10.8.1 Nitrogen Enrichment 10-51
10.8.2 Nutrient-Enhanced Coastal Acidification 10-55
CHAPTER 11 NITROGEN EUTROPHICATION EFFECTS IN WETLANDS 11-1
11.1 Introduction 11-1
Table 11-1 Wetland classification used in the Integrated Science
Assessment. 11-2
11.2 Regional Sensitivity 11-4
11.3 Soil Biogeochemistry 11-4
11.3.1 Nitrogen Pools and Processes 11-5
Table 11-2 New studies on nitrogen addition effects on nitrogen cycling in
wetlands. 11-9
11.3.2 Soil Carbon Cycling 11-11
Table 11-3 Loading effects upon belowground carbon cycling. 11-15
Table 11-4 Nitrogen loading effects upon methane emissions. 11-19
11.4 Production and Aboveground Biomass 11-19
11.4.1 Salt Marsh 11-20
11.4.2 Freshwater Tidal Marsh 11-21
11.4.3 Mangrove 11-22
11.4.4 Bog and Fen 11-22
11.4.5 Summary Table 11-23
Table 11-5 Nitrogen loading effects upon production and biomass. 11-23
11.5 Plant Stoichiometry and Physiology 11-27
11.5.1 Salt Marsh 11-28
11.5.2 Mangrove 11-28
11.5.3 Freshwater Marsh 11-28
11.5.4 Riparian Wetland 11-30
11.5.5 Bog and Fen 11-30
11.5.6 Summary Table 11-33
Table 11-6 Nitrogen loading effects upon plant stoichiometry and
physiology. 11-33
11.6 Plant Architecture 11-38
11.6.1 Salt Marsh 11-39
11.6.2 Mangrove 11-39
11.6.3 Freshwater Tidal Marsh 11-39
11.6.4 Riparian Wetland 11-39
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11.6.5 Summary Table 11-40
Table 11-7 Nitrogen loading effects upon architecture. 11-40
11.7 Demography 11-41
11.7.1 Mangrove 11-42
11.7.2 Riparian Wetland 11-42
11.7.3 Summary Table 11-43
Table 11-8 Nitrogen loading effects upon demography. 11-43
11.8 Biodiversity/Community 11-43
11.8.1 Plants 11-44
Table 11-9 Nitrogen loading effects upon plant biodiversity and
communities. 11-46
11.8.2 Phytoplankton 11-48
11.8.3 Consumer 11-49
11.9 Critical Loads 11-50
11.9.1 Freshwater Wetland 11-50
11.9.2 Intertidal Wetlands 11-51
11.9.3 Comparison to Critical Loads from Europe 11-51
11.10 Summary 11-52
11.10.1 Causality across Wetland Types 11-53
Figure 11-1 Summary of the levels of nitrogen addition where a change to
nitrogen cycling is first observed. 11-54
Figure 11-2 Summary of new literature of nitrogen addition effects on
belowground and aboveground C cycling. 11-55
Figure 11-3 Summary of the level of nitrogen addition that caused a
change in the response variables of plant stoichiometry and
physiology in wetlands. 11-57
Figure 11-4 Summary of nitrogen addition studies on wetland biodiversity.
Numbers indicate the lowest addition level in which change is
observed. 11-60
11.10.2 Freshwater and Intertidal 11-60
Figure 11-5 Summary of field nitrogen addition studies for coastal wetlands
versus critical loads. 11-61
Figure 11-6 Summary of field nitrogen addition studies for freshwater
wetlands as well as current critical loads. Values indicate biotic
or chemical changes observed in response to experimental
nitrogen addition. 11-63
CHAPTER 12 NONACIDIFYING SULFUR EFFECTS 12-1
12.1 Introduction 12-2
Figure 12-1 Effects of sulfur oxide deposition upon chemical (blue boxes),
biological (green boxes), and atmospheric (yellow boxes)
indicators of ecosystem change, as documented by the
previous Integrated Science Assessment and more recent
research. 12-3
12.2 Ecosystem Effects of Altered Sulfur Cycling 12-4
12.2.1 The Sulfur Cycle 12-4
Figure 12-2 Sulfur cycle in terrestrial, forested ecosystems. 12-4
12.2.2 Deposition and Sulfur Stores 12-8
Table 12-1 New studies on nonacidifying sulfur effects on sulfur cycling. 12-9
12.2.3 Sulfide Phytotoxicity 12-9
Figure 12-3 Schematic from Minnesota Pollution Control Agency that
illustrates the mitigating effect of iron upon toxicity of sulfide,
and the stimulatory effect that organic carbon has on sulfide
production. "These processes form the basis for the state's
proposed sulfate standard for wild rice water bodies." 12-11
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12.2.4 Internal Eutrophication 12-12
Figure 12-4 Mechanisms of linked sulfur, iron, and phosphorus cycling in
wetland waters and soils. 12-13
12.2.5 Sulfur Effects on Methane Emissions 12-14
Table 12-2 New studies on nonacidifying sulfur effects on methane
emissions. 12-17
12.3 Mercury Transformations 12-18
12.3.1 Microbial Mercury Transformation 12-19
Table 12-3 New studies on nonacidifying sulfur effects on microbial
communities. 12-22
12.3.2 Zones of High Methylmercury Fractions across the Landscape 12-23
12.3.3 Methylmercury in Periphyton 12-24
12.3.4 Other Factors that Control Methylmercury Production 12-26
12.4 Sulfur Manipulation Studies of Methylmercury 12-33
12.4.1 Ecosystem Scale and Field Mesocosm Studies 12-33
Figure 12-5 Total methylmercury mass in water at Little Rock Lake,
Wisconsin, annually (a), and in relationship to annual
mercury (b) or sulfur (c) deposition. 12-38
Table 12-4 New studies on nonacidifying sulfur effects on mercury cycling. 12-40
12.4.2 Laboratory Manipulation Studies 12-42
Table 12-5 New studies on sulfur addition effects on methylmercury. 12-44
12.5 Sulfur Oxides Deposition Effects on Methylmercury 12-44
12.5.1 Summary Table 12-46
Table 12-6 New studies on sulfur deposition effects on methylmercury. 12-47
12.6 Relationships between Sulfate and Methylmercury in Natural Waters 12-47
12.6.1 Lakes 12-48
Table 12-7 New studies on nonacidifying sulfur effects on mercury cycling
in lakes. 12-49
12.6.2 Wetlands 12-50
Figure 12-6 The relationship between surface water sulfate and
methylmercury concentrations in the Florida Everglades. 12-51
Table 12-8 New studies on nonacidifying sulfur effects on mercury in
wetlands. 12-52
12.6.3 Streams and Rivers 12-53
Figure 12-7 The relationship between surface water sulfate and total
mercury or methylmercury fraction in river-leaf litter
mesocosms. 12-54
Figure 12-8 Methylmercury concentrations as a function of sulfate
concentrations at inlet and outlet streams of Sunday and
Arbutus Lakes, and at lake surface water samples from
Arbutus Lake. 12-55
Table 12-9 New studies on nonacidifying sulfur effects on mercury in
streams and rivers. 12-56
12.6.4 Coastal Marshes and Estuaries 12-57
12.6.5 Rice in the San Joaquin Delta, California 12-57
12.7 Sulfur Impacts on Mercury in Wildlife 12-59
Figure 12-9 Bioconcentration and biomagnification result in methylmercury
concentrations about 1 million times higher in predator fish
than in stream water. 12-60
Figure 12-10 Tissue mercury concentrations as a function of surface water
sulfate concentrations (n = 2,360 surface water samples) in the
Everglades Protection Area. 12-63
12.7.1 Summary Table 12-65
Table 12-10 New studies on nonacidifying sulfur effects on mercury in
wildlife. 12-65
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12.8 Extent and Distribution of Sensitive Ecosystems 12-66
Figure 12-11 Fish mercury concentrations across the U.S. 12-68
12.9 Summary of Nonacidifying Sulfur Effects 12-68
12.9.1 Terrestrial Sulfur Cycling 12-69
12.9.2 Aquatic Sulfur Cycling 12-69
12.9.3 Sulfide Toxicity 12-70
Figure 12-12 Thresholds of sulfate or sulfide concentrations in water which
cause biological and chemical effects in ecosystems. 12-71
12.9.4 Internal Eutrophication 12-71
12.9.5 Effects on Methane Production 12-71
12.9.6 The Role of Microbes in Mercury Methylation 12-72
Figure 12-13 Linear relationships between sulfate and methylmercury
concentrations in published studies. 12-74
12.9.7 Impacts of Sulfur upon Mercury Cycling 12-75
Figure 12-14 Thresholds of sulfate addition or deposition from published
studies which affect chemical or biological changes in
ecosystems. 12-76
12.9.8 Sensitive Ecosystems 12-76
12.9.9 Mercury Effects on Animal Species 12-77
12.9.10 SummaryTable 12-78
Table 12-11 Summary of quantitative effects of non-acidifying sulfur. 12-78
CHAPTER 13 CLIMATE MODIFICATION 13-1
13.1 Excerpt from Greaver et al. (2016) 13-1
13.1.1 Nitrogen Cycling: Transport and Transformation 13-1
Figure 13-1 Summary of key interactions among nitrogen,
anthropogenic-driven climate change, and hydrology. 13-2
13.1.2 Carbon Cycling, Acidification, and Biodiversity 13-5
Figure 13-2 The effects of increased nitrogen, temperature, and
precipitation upon terrestrial carbon pools (left panel) and
fluxes (right panel) from published meta-analyses. 13-7
13.2 Estuaries 13-13
CHAPTER 14 ECOSYSTEM SERVICES 14-1
14.1 Ecosystem Services Frameworks 14-1
14.1.1 U.S. Applications 14-3
Figure 14-1 Economic nitrogen cascade in the Chesapeake Bay
Watershed. 14-5
Figure 14-2 Summary of beneficiaries of ecosystem services related to
nitrogen addition. 14-6
14.1.2 European and Canadian Applications 14-8
Figure 14-3 Benefits and costs associated with the 25% decline in nitrogen
deposition in the U.K. since 1990. 14-10
14.1.3 Global Perspective 14-10
14.2 Ecosystem Service Profiles of Select Species 14-11
14.2.1 Balsam Fir 14-11
14.2.2 Eel Grass 14-13
14.2.3 Green Turtle 14-14
14.2.4 White Ash 14-15
14.2.5 Lace Lichen 14-17
14.3 Summary 14-18
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APPENDIX A. MAPS OF DEPOSITION CHANGE THROUGH TIME A-1
Figure A-1 Wet plus dry deposition of total nitrogen over 3-year periods.
Top: 2000-2002; Bottom: 2011-2013. A-2
Figure A-2 Wet deposition of total nitrogen over 3-year periods. Top:
2000-2002; Bottom: 2011-2013. A-3
Figure A-3 Dry deposition of total nitrogen over 3-year periods. Top:
2000-2002; Bottom: 2011-2013. A-4
Figure A-4 Percent of total nitrogen as dry deposition over 3-year periods.
Top: 2000-2002; Bottom: 2011-2013. A-5
Figure A-5 Wet plus dry deposition of oxidized nitrogen over 3-year
periods. Top: 2000-2002; Bottom: 2011-2013. A-6
Figure A-6 Percent of total nitrogen as oxidized nitrogen over 3-year
periods. Top: 2000-2002; Bottom: 2011-2013. A-7
Figure A-7 Dry deposition of oxidized nitrogen over 3-year periods. Top:
2000-2002; Bottom: 2011-2013. A-8
Figure A-8 Percent of total nitrogen dry deposited as oxidized nitrogen
over 3-year periods. Top: 2000-2002; Bottom: 2011-2013. A-9
Figure A-9 Combined dry deposition of nitric acid and particulate nitrate
over 3-year periods. Top: 2000-2002; Bottom: 2011-2013. A-10
Figure A-10 Dry deposition of nitric acid over 3-year periods. Top:
2000-2002; Bottom: 2011-2013. A-11
Figure A-11 Dry deposition of particulate nitrate over 3-year periods. Top:
2000-2002; Bottom: 2011-2013. A-12
Figure A-12 Dry deposition of modeled (unmeasured) nitrogen species over
3-year periods. Top: 2000-2002; Bottom: 2011-2013. A-13
Figure A-13 Percent of total nitrogen as modeled (unmeasured) species
over 3-year periods. Top: 2000-2002; Bottom: 2011-2013. A-14
Figure A-14 Wet plus dry deposition of reduced (inorganic) nitrogen over
3-year periods. Top: 2000-2002; Bottom: 2011-2013. A-15
Figure A-15 Percent of total nitrogen deposition by reduced (inorganic)
nitrogen over 3-year periods. Top: 2000-2002; Bottom:
2011-2013. A-16
Figure A-16 Dry deposition of ammonia over 3-year periods. Top:
2000-2002; Bottom: 2011-2013. A-17
Figure A-17 Dry deposition of particulate ammonium over 3-year periods.
Top: 2000-2002; Bottom: 2011-2013. A-18
Figure A-18 Dry deposition of reduced (inorganic) nitrogen over 3-year
periods. Top: 2000-2002; Bottom: 2011-2013. A-19
Figure A-19 Percent of total nitrogen deposition by dry reduced (inorganic)
nitrogen over 3-year periods. Top: 2000-2002; Bottom:
2011-2013. A-20
Figure A-20 Wet plus dry deposition of total sulfur over 3-year periods. Top:
2000-2002; Bottom: 2011-2013. A-21
Figure A-21 Wet deposition of total sulfur over 3-year periods. Top:
2000-2002; Bottom: 2011-2013. A-22
Figure A-22 Dry deposition of total sulfur over 3-year periods. Top:
2000-2002; Bottom: 2011-2013. A-23
Figure A-23 Percent of total sulfur deposition by dry deposition over 3-year
periods. Top: 2000-2002; Bottom: 2011-2013. A-24
Figure A-24 Dry deposition of sulfur dioxide over 3-year periods. Top:
2000-2002; Bottom: 2011-2013. A-25
Figure A-25 Dry deposition of particulate sulfate over 3-year periods. Top:
2000-2002; Bottom: 2011-2013. A-26
APPENDIX B. MERCURY CYCLING B-1
B.1. Transfer of Mercury from the Atmosphere to Terrestrial Ecosystems B-1
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B.2. Transfer of Mercury from Terrestrial to Aquatic Ecosystems _
B.3. Transfer of Mercury from Atmosphere to Aquatic Ecosystems_
B.4. Methylmercury Cycling
BAA.
B.4.2.
B.4.3.
Transfer of Methylmercury from Terrestrial to Aquatic Ecosystems
Transfer of Methylmercury from Wetlands to Aquatic Ecosystems
Methylmercury Cycling in Aquatic Ecosystems—Lake Onondaga, New York
Figure B-1 Mercury and methylmercury mass balance cycle in Lake
Onondaga in 1992. The quantities of mercury in each flux are
indicated in parentheses by (kg total Hg/yr, kg MeHg/yr), from
Henry et al. (1995).
B.4.4.
B.4.5.
B.4.6.
Methylmercury in Sediments and Water Column—Lakes
Methylmercury in Sediments and Water Column—Wetlands
Methylmercury in Sediments and Water Column—Estuarine and Marine
Ecosystems
_ B-2
_ B-3
_ B-3
_ B-3
_ B-4
B=4
B-5
B-6
B-7
B-8
APPENDIX C. CASE STUDIES
C.1. Northeastern U.S. Case Study: Acadia National Park, Hubbard Brook Experimental
Forest, and Bear Brook Watershed
C.1.1. Background
Figure C-1
Locations of northeastern U.S. case study areas and nearby
human population centers.
C.1.2.
Table C-1
Figure C-2
Table C-2
Figure C-3
Table C-3
Table C-4
Deposition_
Figure C-4
Figure C-5
Selected characteristics of northeastern case study areas.
Site map of Hubbard Brook Experimental Forest in the White
Mountains of New Hampshire.
Land use/land cover for northeastern case study areas.
Land cover in the Northeast case study region.
Literature cited by northeast U.S. case study area.
Key recent research literature focused on the case study
region.
Total nitrogen deposition (A) and percent oxidized nitrogen
deposition (B) for the northeast case study area estimated by
the National Atmospheric Deposition Program Total Deposition
Science committee.
Total sulfur deposition (A) for the northeast case study area
estimated by the National Atmospheric Deposition Program
Total Deposition Science committee. Time series of wet
deposition (B) from the National Atmospheric Deposition
Program/National Trends Network in the Hubbard Brook
Experimental Forest, New Hampshire.
C.1.3. Critical Loads and Other Dose-Response Relationships
Table C-5
Table C-6
Figure C-6
Table C-7
Figure C-7
Terrestrial empirical and modeling research on the response of
nitrogen and sulfur deposition for the northeastern U.S.
Empirical critical loads for nitrogen in Acadia National Park, by
receptor, from Pardo et al. (2011c).
Annual stream calcium and magnesium export (paired bars),
and cumulative excess export in West Bear Brook compared to
East Bear Brook (line), over the study period 1989-2000 at the
Bear Brook Watershed experiment.
C-1
_C-1
_C-1
_C-2
_C-2
_C-4
_C-7
_C-7
C-8
.11
12
C-13
14
15
C-16
C-19
C-21
Critical loads of nutrient nitrogen for the Northern Forests
ecoregion. C-22
Conceptual diagram showing the direct and indirect effects of
changes in temperature and precipitation on biogeochemical
processes in forests and on the services forests provide. Also
shown are feedbacks that further influence climatological
effects. C-24
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Table C-8 Aquatic empirical research on the response of nitrogen and
sulfur deposition forthe northeastern U.S. C-25
Table C-9 Critical and target load and exceedance modeling studies in
the northeastern U.S.C-29
Table C-10 Empirical and modeled nitrogen critical loads applicable to the
northeastern U.S. C-31
C.1.4. Long-Term Ecological Monitoring C-32
Table C-11 Summary table of observed terrestrial and aquatic acidification
long-term trends in Hubbard Brook Experimental Forest and
Bear Brook Watershed. C-33
Table C-12 Example surface water acidification chemistry studies in the
northeast case study region. C-36
Table C-13 Summary of observed terrestrial and aquatic nutrient
enrichment long-term responses in Acadia National Park,
Hubbard Brook Experimental Forest, Bear Brook Watershed,
and other northeastern regions. C-39
C.1.5. Recovery C-42
C.2. Southeastern Appalachia Case Study C-44
C.2.1. Background C-44
Table C-14 Species in the southeast case study region that are listed as
threatened or endangered or as species of concern. C-48
Figure C-8 Land cover in the southern Appalachian Mountains case study
region. C-51
C.2.2. Deposition C-51
Figure C-9 Deposition over Great Smoky Mountain National Park. C-52
Figure C-10 Trends in wet deposition of nitrogen and sulfur in Great Smoky
Mountain National Park, 1990-2014. C-53
Figure C-11 Maps showing total nitrogen deposition on left, total sulfur
deposition on right, forthe 3-yr average, 2011-2013. C-54
Figure C-12 Modeled sulfur and nitrogen deposition to the Great Smoky
Mountain National Park for the year 2000. C-55
C.2.3. Critical Loads and Other Dose-Response Relationships C-55
C.2.4. Characterization and Long-term Monitoring C-58
Table C-15 Example soil, terrestrial biota, and surface water acidification
characterization and long-term monitoring studies in the
southern Appalachian Mountains region. C-59
C.3. Tampa Bay Case Study C-62
C.3.1. Background C-62
Figure C-13 Tampa Bay mainstem segments and watershed. Also shown
are the National Atmospheric Deposition (NADP) National
Trends Network wet deposition monitoring site FL41 at Verna
Wellfield in Sarasota county and the NADP Atmospheric
Integrated Research Monitoring Network site FL 18 in
Hillsborough County. C-63
Figure C-14 Tampa Bay overview map highlighting watershed development
and land use. C-66
C.3.2. Deposition C-67
Figure C-15 Annual wet deposition of ammonium, nitrate, sulfate, and
acidity at the National Atmospheric Deposition National Trends
Network monitoring site closest to the Tampa Bay case study
area. Source: National Center for Environmental Assessment,
U.S. EPA. C-67
Figure C-16 Estimated annual loads of total nitrogen from various sources
to Tampa Bay summarized from 1976 to 2011. C-68
Figure C-17 A. Wet and dry nitrogen deposition in Tampa Bay and the
surrounding area. B. Percent oxidized nitrogen deposition in
Tampa Bay and the surrounding area. C-70
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C.3.3. Long-Term Ecological Monitoring C-70
Figure C-18 Seagrass Loss in Tampa Bay. Red indicates area of seagrass
lost from 1950 to 1990. C-72
Figure C-19 Comparison of observed chlorophyll a and that predicted from
the total nitrogen load—chlorophyll a relationships for all four
mainstem Tampa Bay segments, for 1986-1998 and
1999-2007. C-73
Figure C-20 Total seagrass coverage in Tampa Bay circa 1950 through
2014. C-75
Figure C-21 Trend in hydrologically normalized total nitrogen load to Tampa
Bay relative to population increases in the Tampa Bay
metropolitan area. C-76
C.3.4. Nitrogen Management in Tampa Bay C-76
Table C-16 Numeric nutrient criteria for chlorophyll a for the four mainstem
segments of Tampa Bay adopted by the Florida Department of
Environmental Protection. C-77
Table C-17 Numeric nutrient criteria for total nitrogen for the four mainstem
segments of Tampa Bay. C-78
C.4. Rocky Mountain National Park Case Study C-80
C.4.1. Background C-80
Figure C-22 Rocky Mountain National Park ecosystems. C-82
Figure C-23 Rocky Mountain National Park land coverage using the land
cover classifications as mapped by the National Land Cover
Dataset. Percent cover shown for the four dominant cover
types. C-84
Figure C-24 Rocky Mountain National Park hydrologic unit code 12
watersheds. C-85
C.4.2. Deposition C-85
Figure C-25 Spatial patterns of atmospheric nitrogen and sulfur deposition
in the Rocky Mountain National Park region based on TDEP
calculations averaged from 2011 -2013 (see Chapter 2) and
long-term trends in wet atmospheric deposition from the
Beaver Meadows National Atmospheric Deposition Program
Monitoring site within Rocky Mountain National Park. C-87
Figure C-26 Spatial patterns of in the percentage of atmospheric nitrogen
deposited in oxidized forms and through wet deposition in the
Rocky Mountain National Park region based on TDEP
calculations averaged from 2011-2013 (see Chapter 2). C-88
Figure C-27 Rocky Mountain National Park nitrogen cycle. C-89
Figure C-28 Total wet and dry deposition of nitrogen components measured
at Rocky Mountain National Park from November 2008 to
November 2009, including organic nitrogen and particulate
organic nitrogen. C-90
C.4.3. Critical Loads and Other Dose-Response Relationships C-90
Table C-18 Terrestrial empirical critical loads of nutrient nitrogen for the
Northwestern Forested Mountains ecoregion. C-91
Table C-19 Montane forest and alpine ecosystem critical loads for nitrogen
deposition research published since the critical load
assessment by Pardo et al. (2011c). C-93
Table C-20 Hindcast absolute and percent changes in species abundance
between 1900 and 2010 in response to historical
reconstructions of nitrogen deposition (Sullivan et al., 2005)
and historical climate change (IPCC, 2007b). C-95
Table C-21 Critical loads for nitrogen for eutrophication for surface water
(high elevation lakes) in the Rocky Mountains. C-97
Table C-22 Lake water nitrate concentrations in nitrogen deposition studies
observing phytoplankton responses. C-99
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Table C-23
Table C-24
Paleolimnological biological responses in Rocky Mountain
lakes exposed to anthropogenic nitrogen deposition.
C-100
Critical loads of nitrogen or sulfur for surface water acidification
Rocky Mountain National Park and other high-elevation lakes
in the Rocky Mountains.
C.4.4.
C.4.5.
.C-101
Figure C-29 The continuum of ecological sensitivity to nitrogen deposition. C-104
Figure C-30 Critical load thresholds for current and possible future
biogeochemical and biological effects of nitrogen deposition. C-105
Highlights of Additional Research Literature and Federal Reports Since
January 2008 C-105
Table C-25 Summary of freshwater eutrophication studies in the Rocky
Mountains since 2008. C-107
Rocky Mountain National Park Initiative C-108
Figure C-31 Rocky Mountain National Park Initiative glidepath and current
wet nitrogen deposition at Loch Vale in Rocky Mountain
National Park.
Figure C-32 Rocky Mountain National Park Initiative accomplishment
timeline.
C.5.
C.4.6. Interactions between Nitrogen Deposition,
Ecological Disturbances
Southern California
C.5.1.
Climate Change, and Large-Scale
Background
Figure C-33 Map of the distribution of vegetation types and land cover in
California.
Figure C-34 Southern California case study region showing locations of
human population centers.
Table C-26
C-109
.C-110
.C-110
.C-111
.C-111
_C-114
C-117
Land coverages of Sequoia, Kings Canyons, and Joshua Tree
national parks.
C.5.2. Deposition_
Figure C-35 Patterns and temporal trends of nitrogen and sulfur deposition
in Joshua Tree National Park and surrounding region in
California. A and B 3-yr average total deposition of nitrogen
and sulfur for 2011 -2013
_C-118
CC-118
C-120
Figure C-36 Patterns and temporal trends of nitrogen and sulfur deposition
in Joshua Tree National Park and surrounding region in
California. A shows the partitioning between oxidized and
reduced nitrogen; B and C show the 3-yr average total percent
wet deposition of nitrogen and sulfur for 2011 -2013.
C-121
Figure C-37 Patterns and temporal trends of nitrogen and sulfur deposition
in Joshua Tree National Park and surrounding region in
California. The 25-yrtime series for wet deposition of nitrate,
ammonium, sulfate, and hydrogen ion obtained from the
National Atmospheric Deposition Program/National Trends
Network monitoring site CA 67.
C-122
Figure C-38 Patterns and temporal trends of nitrogen and sulfur deposition
of Sequoia and Kings Canyons National Parks and
surrounding region in California. A and B show the 3-yr
average total deposition of nitrogen and sulfur for 2011-2013. C-123
Figure C-39 Patterns and temporal trends of nitrogen and sulfur deposition
of Sequoia and Kings Canyons National Parks and
surrounding region in California. A. shows the partitioning
between oxidized and reduced nitrogen, indicated as the
fraction of total nitrogen which is oxidized; B and C show the 3-
yr average total percent wet deposition of nitrogen and sulfur
for 2011-2013. C-124
Figure C-40 Patterns and temporal trends of nitrogen and sulfur deposition
of Sequoia and Kings Canyons National Parks and
surrounding region in California. A and B show w the 25-yr
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time series for wet deposition of nitrate, ammonium, sulfate,
and hydrogen obtained from the National Atmospheric
Deposition Program/National Trends Network monitoring sites
CA 99 and CA 75m; G shows percent oxidized nitrogen. C-125
C.5.3. Critical Loads and Other Dose-Response Relationships C-126
Table C-27 Summary of recent empirical dose-response and critical load
studies focused on the southern California case study area and
published since Pardo et al. (2011c). C-128
Figure C-41 Composite critical load exceedance maps for all seven
vegetation types included in the study of Fenn et al. (2010)
showing the combined exceedance areas and the level of
exceedance (kg N/ha/yr). C-130
Table C-28 Terrestrial critical and target load and exceedance modeling
studies in southern California. C-131
Table C-29 Example surface water acidification studies in Sequoia and
Kings Canyons National Parks and other Sequoia and Kings
Canyons National Parks-relevant areas in the southern
California case study region. C-135
C.5.4. Highlights of Additional Research Literature and Federal Reports since
January 2008 C-140
Table C-30 Key recent research literature focused on the case study
region. C-140
C.5.5. Summary C-142
Figure C-42 Continuum of critical loads in southern California case study
area and relevant surrounding region. C-143
APPENDIX D. OTHER ECOLOGICAL EFFECTS OF PARTICULATE MATTER D-1
D.1. Introduction D-1
D.2. Direct Effects of Particulate Matter on Radiative Flux D-2
D.3. Particulate Matter Deposition to Ecosystems D-3
D.3.1. Metals D-4
D.3.2. Organics D-4
D.4. Effects of Particulate Matter on Vegetation D-5
D.4.1. Vegetative Surfaces D-5
D.4.2. Foliar Uptake of Particulate Matter D-7
D.4.3. Particulate Matter Impacts on Gas Exchange Processes D-8
D.4.4. Plant Physiology D-9
D.4.5. Uptake of Particulate Matter by Plants from Soils D-9
D.4.6. Effects on Plant Growth D-10
D.4.7. Vegetation as Bioindicators D-11
D.5. Effects of Particulate Matter on the Soil Environment D-11
D.5.1. Bioavailability in Soils D-11
D.5.2. Soil Nutrient Cycling D-12
D.5.3. Soil Community Effects D-14
D.5.4. Soil Microbe Interactions with Plant Uptake of Particulate Matter D-17
D.5.5. Effects of Particulate Matter on Physical Properties of Soils D-18
D.6. Effects of Particulate Matter on Fauna D-19
D.6.1. Laboratory Bioassays D-19
D.6.2. Wildlife as Biomonitors of Particulate Matter D-21
D.6.3. Biomagnification D-22
D.7. Effects of Particulate Matter on Ecological Communities and Ecosystems D-23
D.7.1. Gradient Effects near Smelters D-23
D.7.2. Urban Environments D-25
D.7.3. Aquatic Ecosystems D-25
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D.7.4. Experimental Microecosystems DD-26
D.8. Summary of Ecological Effects of Particulate Matter 26
REFERENCES R-1
February 2017 xxviii DRAFT: Do Not Cite or Quote
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INTEGRATED SCIENCE ASSESSMENT TEAM FOR
OXIDES OF NITROGEN, OXIDES OF SULFUR, AND
PARTICULATE MATTER—ECOLOGICAL CRITERIA
Executive Direction
Dr. John Vandenberg (Director, RTP Division)—National Center for Environmental
Assessment—RTP Division, Office of Research and Development, U.S. Environmental
Protection Agency, Research Triangle Park, NC
Ms. Debra Walsh (Deputy Director, RTP Division)—National Center for Environmental
Assessment—RTP Division, Office of Research and Development, U.S. Environmental
Protection Agency, Research Triangle Park, NC
Dr. Reeder Sams II (Acting Deputy Director, RTP Division)—National Center for
Environmental Assessment—RTP Division, Office of Research and Development,
U.S. Environmental Protection Agency, Research Triangle Park, NC
Dr. Steven J. Dutton (Branch Chief)—National Center for Environmental Assessment,
Office of Research and Development, U.S. Environmental Protection Agency, Research
Triangle Park, NC
Dr. Ellen Kirrane (Acting Branch Chief)—National Center for Environmental Assessment,
Office of Research and Development, U.S. Environmental Protection Agency, Research
Triangle Park, NC
Scientific Staff
Dr. Tara Greaver (Assessment Lead)—National Center for Environmental Assessment,
Office of Research and Development, U.S. Environmental Protection Agency, Research
Triangle Park, NC
Dr. Emmi Felker-Quinn—National Center for Environmental Assessment, Office of
Research and Development, U.S. Environmental Protection Agency, Research Triangle
Park, NC
Dr. Jeffrey D. Herrick—National Center for Environmental Assessment, Office of Research
and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC
Dr. Meredith Lassiter—National Center for Environmental Assessment, Office of Research
and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC
Dr. Joseph P. Pinto—National Center for Environmental Assessment, Office of Research
and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC
Technical Support Staff
Ms. Marieka Boyd—National Center for Environmental Assessment, Office of Research and
Development, U.S. Environmental Protection Agency, Research Triangle Park, NC
Mr. Kenneth J. Breito—Senior Environmental Employment Program, National Center for
Environmental Assessment, Office of Research and Development, U.S. Environmental
Protection Agency, Research Triangle Park, NC
February 2017
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Ms. Eleanor Jamison—Senior Environmental Employment Program, National Center for
Environmental Assessment, Office of Research and Development, U.S. Environmental
Protection Agency, Research Triangle Park, NC
Mr. Ryan Jones—National Center for Environmental Assessment, Office of Research and
Development, U.S. Environmental Protection Agency, Research Triangle Park, NC
Ms. Connie Meacham—National Center for Environmental Assessment, Office of Research
and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC
Ms. Olivia Philpott—Senior Environmental Employment Program, National Center for
Environmental Assessment, Office of Research and Development, U.S. Environmental
Protection Agency, Research Triangle Park, NC
Mr. Samuel S. Thacker—National Center for Environmental Assessment, Office of Research
and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC
Mr. Richard N. Wilson—National Center for Environmental Assessment, Office of Research
and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC
February 2017
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AUTHORS, CONTRIBUTORS, AND REVIEWERS
Authors
Dr. Tara Greaver (Assessment Lead)—National Center for Environmental Assessment,
Office of Research and Development, U.S. Environmental Protection Agency, Research
Triangle Park, NC
Ms. Marion Deerhake*—RTI International, Research Triangle Park, NC
Dr. Emmi Felker-Quinn—National Center for Environmental Assessment, Office of
Research and Development, U.S. Environmental Protection Agency, Research Triangle
Park, NC
Dr. Jeffrey D. Herrick—National Center for Environmental Assessment, Office of Research
and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC
Dr. Meredith Lassiter—National Center for Environmental Assessment, Office of Research
and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC
Dr. Stephen McDow—National Center for Environmental Assessment, Office of Research
and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC
Dr. Jennifer Phelan*—RTI International, Research Triangle Park, NC
Dr. Joseph P. Pinto—National Center for Environmental Assessment, Office of Research
and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC
Dr. Timothy J. Sullivan*—E&S Environmental Chemistry, Inc., Corvallis, OR
Dr. Alan Talhelm—Oak Ridge Institute for Science and Education, National Center for
Environmental Assessment, Office of Research and Development, U.S. Environmental
Protection Agency, Research Triangle Park, NC
* Under contract with RTI International
Contributors
Mr. Adam Benson—Oak Ridge Institute for Science and Education, National Center for
Environmental Assessment, Office of Research and Development, U.S. Environmental
Protection Agency, Research Triangle Park, NC
Dr. Mary C. Barber*—RTI International, Washington, DC
Ms. Tamara Blett—National Park Service, Lakewood, CO
Dr. Jana Compton—National Health and Environmental Effects Research Laboratory, Office
of Research and Development, U.S. Environmental Protection Agency, Corvallis, OR
Dr. Christopher M. Clark—National Center for Environmental Assessment, Office of
Research and Development, U.S. Environmental Protection Agency, Washington, DC
Dr. Linda Geiser—Air Resource Management National Program Leader, USDA Forest
Service, Washington, DC
Dr. Alan Knapp—Department of Biology, Colorado State University, Fort Collins CO
February 2017
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Dr. Jason Lynch—Office of Air and Radiation, Office of Atmospheric Programs, U.S.
Environmental Protection Agency, Washington, DC
Ms. April Maxwell—Oak Ridge Institute for Science and Education, National Center for
Environmental Assessment, Office of Research and Development, U.S. Environmental
Protection Agency, Research Triangle Park, NC
Dr. Stephen McDow—National Center for Environmental Assessment, Office of Research
and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC
Ms. Margaret O'Neil*—RTI International, Research Triangle Park, NC
Ms. Jennifer Richkus*—RTI International, Research Triangle Park, NC
Ms. Elizabeth Sullivan*—RTI International, Research Triangle Park, NC
Dr. George L. Van Houtven*—RTI International, Research Triangle Park, NC
* Under contract with RTI International
Reviewers
Mr. Barry P. Baldigo, Water Science Center, U.S. Geological Survey, Troy, NY
Ms. Tamara Blett—National Park Service, Lakewood, CO
Dr. Michael Bell—National Park Service, Lakewood, CO
Ms. Patricia Brewer—National Park Service, Lakewood, CO
Dr. Suzanne Bricker—National Oceanic and Atmospheric Administration, Washington, DC
Mr. Jim Cheatham—National Park Service, Lakewood, CO
Dr. Christopher M. Clark—National Center for Environmental Assessment, Office of
Research and Development, U.S. Environmental Protection Agency, Washington, DC
Dr. Christopher B. Craft—Indiana University, Bloomington, IN
Dr. Eric Davidson—University of Maryland, Appalachian Laboratory, Frostburg, MD
Ms. Christine Davis—Office of Air and Radiation, Office of Air Quality Planning and
Standards, U.S. Environmental Protection Agency, Research Triangle Park, NC
Dr. Jean-Jacques Dubois—North Carolina State University, Raleigh, NC
Dr. Eric Edgerton—Atmospheric Research and Analysis, Cary, NC
Ms. Candace Edwards—Oak Ridge Institute for Science and Education, National Center for
Environmental Assessment, Office of Research and Development, U.S. Environmental
Protection Agency, Research Triangle Park, NC
Ms. Charlene Finley—Oak Ridge Institute for Science and Education, National Center for
Environmental Assessment, Office of Research and Development, U.S. Environmental
Protection Agency, Research Triangle Park, NC
Ms. Elizabeth Gatling—Oak Ridge Institute for Science and Education, National Center for
Environmental Assessment, Office of Research and Development, U.S. Environmental
Protection Agency, Research Triangle Park, NC
Dr. Cynthia Gilmour—Smithsonian Environmental Research Center, Edgewater, MD
February 2017
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Mr. William Grffin—Oak Ridge Institute for Science and Education, National Center for
Environmental Assessment, Office of Research and Development, U.S. Environmental
Protection Agency, Research Triangle Park, NC
Dr. David Grantz—College of Natural and Agricultural Sciences, Air Pollution Research
Center, University of California Riverside, Parlier, CA
Dr. Scot Haggerthey—National Center for Environmental Assessment, Office of Research
and Development, U.S. Environmental Protection Agency, Washington, DC
Dr. Meredith K. Hastings—Earth, Environmental, and Planetary Sciences, Brown
University, Providence, RI
Dr. Laszlo Horvath—Plant Ecology Research Group, Szent Istvan University, Hungary
Dr. Robert Hetes—Office of Air and Radiation, Office of Air Quality Planning and
Standards, U.S. Environmental Protection Agency, Research Triangle Park, NC
Mr. James Hou—Office of the Regional Administrator, Region 8, U.S. Environmental
Protection Agency, Denver, CO
Dr. Bryan Hubbel—Office of Air Quality Planning and Standards, Office of Air and
Radiation, U.S. Environmental Protection Agency, Research Triangle Park, NC
Mr. Saturo Ito—Oak Ridge Institute for Science and Education, National Center for
Environmental Assessment, Office of Research and Development, U.S. Environmental
Protection Agency, Research Triangle Park, NC
Mr. Ryan Jones—National Center for Environmental Assessment, Office of Research and
Development, U.S. Environmental Protection Agency, Research Triangle Park, NC
Dr. James Kaldy—National Health and Environmental Effects Research Laboratory, Office
of Research and Development, U.S. Environmental Protection Agency, Corvallis, OR
Mr. Matt Kulp—National Park Service, Gatlinburg, TN
Ms. Emily Lau—Oak Ridge Institute for Science and Education, National Center for
Environmental Assessment, Office of Research and Development, U.S. Environmental
Protection Agency, Research Triangle Park, NC
Dr. Jason Lynch—Office of Air and Radiation, Office of Atmospheric Programs, U.S.
Environmental Protection Agency, Washington, DC
Mr. Ihab Mikati—Oak Ridge Institute for Science and Education, National Center for
Environmental Assessment, Office of Research and Development, U.S. Environmental
Protection Agency, Research Triangle Park, NC
Ms. Danielle Moore—Oak Ridge Institute for Science and Education, National Center for
Environmental Assessment, Office of Research and Development, U.S. Environmental
Protection Agency, Research Triangle Park, NC
Ms. Kristi Morris—National Park Service, Lakewood, CO
Dr. Kristopher Novak—National Center for Environmental Assessment, Office of Research
and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC
Dr. Caroline Nowlan—Harvard-Smithsonian Center for Astrophysics, Harvard University,
Cambridge, MA
February 2017
xxxiii
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Mr. Kyle Painter—Oak Ridge Institute for Science and Education, National Center for
Environmental Assessment, Office of Research and Development, U.S. Environmental
Protection Agency, Research Triangle Park, NC
Ms. Rebecca Perrin—Office of the Regional Administrator, Region 8, U.S. Environmental
Protection Agency, Denver, CO
Mr. Jim Renfro—National Park Service, Gatlinburg, TN
Dr. Jennifer Richmond-Bryant—National Center for Environmental Assessment, Office of
Research and Development, U.S. Environmental Protection Agency, Research Triangle
Park, NC
Ms. Kristin Riha—Office of Air and Radiation, Office of Air Quality Planning and
Standards, U.S. Environmental Protection Agency, Research Triangle Park, NC
Ms. Alexandra Ross—Oak Ridge Institute for Science and Education, National Center for
Environmental Assessment, Office of Research and Development, U.S. Environmental
Protection Agency, Research Triangle Park, NC
Dr. Donald Scavia—University of Michigan, Ann Arbor, MI
Ms. Vicki Sandiford—Office of Air and Radiation, Office of Air Quality Planning and
Standards, U.S. Environmental Protection Agency, Research Triangle Park, NC
Dr. Bret Schichtel—National Park Service, Fort Collins, CO
Dr. Erika Sasser—Office of Air and Radiation, Office of Air Quality Planning and
Standards, U.S. Environmental Protection Agency, Research Triangle Park, NC
Dr. J. Travis Smith—Office of Air and Radiation, Office of Air Quality Planning and
Standards, U.S. Environmental Protection Agency, Research Triangle Park, NC
Ms. Ginger Tennant—Office of Air and Radiation, Office of Air Quality Planning and
Standards, U.S. Environmental Protection Agency, Research Triangle Park, NC
Dr. Barbara J. Turpin—Gillings School of Global Environmental Health, University of
North Carolina, Chapel Hill, NC
Dr. Rich Scheffe—Office of Air Quality Planning and Standards, U.S. Environmental
Protection Agency, Research Triangle Park, NC
Mr. Randy Waite—Office of Air and Radiation, Office of Air Quality Planning and
Standards, U.S. Environmental Protection Agency, Research Triangle Park, NC
Dr. John T. Walker—National Risk Management Research Laboratory, Office of Research
and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC
Dr. Christopher Weaver—National Center for Environmental Assessment, Office of
Research and Development, U.S. Environmental Protection Agency, Washington, DC
Ms. Karen Wesson—Office of Air and Radiation, Office of Air Quality Planning and
Standards, U.S. Environmental Protection Agency, Research Triangle Park, NC
February 2017
xxxiv
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CLEAN AIR SCIENTIFIC ADVISORY COMMITTEE
OXIDES OF NITROGEN, OXIDES OF SULFUR, AND
PARTICULATE MATTER—ECOLOGICAL CRITERIA
NAAQS REVIEW PANEL
Chair of Review Panel
Dr. Ivan J. Fernandez**—Distinguished Maine Professor, School of Forest Resources and
Climate Change Institute, University of Maine, Orono, ME
Review Panel Members
Dr. Edith Allen—Professor of Plant Ecology, Department of Botany and Plant Sciences,
University of California Riverside, Riverside, CA
Dr. Praveen Amar—Independent Consultant, Environment, Energy, and Climate Strategies,
Lexington, MA
Dr. James Boyd—Senior Fellow and Director, Center for the Management of Ecological
Wealth, Resources for the Future, Washington, DC
Dr. Elizabeth W. Boyer—Associate Professor of Water Resources, Department of
Ecosystem Science and Management, Pennsylvania State University, University Park, PA
Dr. Douglas Burns—Research Hydrologist, New York Water Science Center, U.S.
Geological Survey, Troy, NY
Ms. Lauraine Chestnut—Managing Economist, Stratus Consulting Inc., Boulder, CO
Dr. Charles T. Driscoll, Jr.—Distinguished Professor and University Professor of
Environmental Systems Engineering, Department of Civil and Environmental
Engineering, College of Engineering and Computer Science, Syracuse University,
Syracuse, NY
Dr. Mark Fenn—Research Plant Pathologist, Pacific Southwest Research Station, USDA
Forest Service, Riverside, CA
Dr. James Galloway—Sidman P. Poole Professor of Environmental Sciences, Department of
Environmental Sciences, University of Virginia, Charlottesville, VA
Dr. Frank Gilliam, Professor—Department of Biological Sciences, Marshall University,
Huntington, WV
Dr. Robert A. Goldstein—Senior Technical Executive for Water and Ecosystems, Electric
Power Research Institute, Palo Alto, CA
Dr. Daven Henze—Assistant Professor and Charles C. Gates Faculty Fellow, Department of
Mechanical Engineering, University of Colorado, Boulder, CO
Dr. Robert W. Howarth—David R. Atkinson Professor of Ecology & Environmental
Biology, Department of Ecology and Evolutionary Biology, Cornell University, Ithaca,
NY
Dr. Donna Kenski—Data Analysis Director, Lake Michigan Air Directors Consortium,
Rosemont, IL
February 2017
XXXV
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Dr. William McDowell—Professor of Environmental Science, Department of Natural
Resources and the Environment, University of New Hampshire, Durham, NH
Dr. Erik Nelson—Assistant Professor, Department of Economics, Bowdoin College,
Brunswick, ME
Dr. Hans Paerl—Kenan Professor of Marine and Environmental Sciences, Institute of
Marine Sciences, University of North Carolina—Chapel Hill, Morehead City, NC
Mr. Richard L. Poirot—Air Quality Planning Chief, Air Quality and Climate Division,
Vermont Department of Environmental Conservation, Montpelier, VT
Dr. Armistead (Ted) Russell—Howard T. Tellepsen Chair and Regents Professor of Civil
and Environmental Engineering, Department of Civil and Environmental Engineering,
Georgia Institute of Technology, Atlanta, GA
Dr. Stephen E. Schwartz—Senior Scientist, Environmental and Climate Sciences
Department, Brookhaven National Laboratory, Upton, NY
Dr. Kathleen Weathers—Senior Scientist, Cary Institute of Ecosystem Studies, Millbrook,
NY
**Member of the statutory CASAC appointed by the U.S. EPA Administrator
Science Advisory Board Staff
Dr. Thomas Armitage—Designated Federal Officer, U.S. Environmental Protection Agency,
Science Advisory Board (1400R), 1200 Pennsylvania Avenue, NW, Washington, D.C.
20460-0001, Phone: 202-564-2155, Fax: 202-565-2098, (Armitage.thomas@epa.gov)
February 2017
xxxvi
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ACRONYMS AND ABBREVIATIONS
Acronym/Abbreviation Meaning
ACCENT Atmospheric Composition
Change: the European Network
of excellence
AIRMoN Atmospheric Integrated
Research Monitoring Network
AIRS Atmospheric Infrared Sounder
(instrument)
A1 aluminum
Al3+ aluminum ion
Ali inorganic aluminum
Al2+ aluminum ion
Alo organic aluminum
Al(OH)3 aluminum hydroxide
ALSC Adirondack Lake Survey
Corporation
ALTM Adirondack Long Term
Monitoring
AMD acid mine drainage
ANC acid neutralizing capacity
ANPP aboveground net primary
production
AOD aerosol optical depth
AOSR Athabasca oil sands region
AQCD Air Quality Criteria Document
AQEG Air Quality Expert Group
AQI Air Quality Index
AQS Air Quality System (database)
Ar argon
ARS Agricultural Research Service
As arsenic
ASI Acid Stress Index
asl above sea level
ATMOS Atmospheric Trace Molecule
Spectroscopy
ATTILA type of Lagrangian model
AUSPEX Atmospheric Utility Signatures,
Predictions, and Experiments
AVIRIS Airborne Visible and Infrared
Imaging Spectrometer
Acronym/Abbreviation Meaning
Ba barium
BBW Bear Brook Watershed
BBWM Bear Brook Watershed, Maine
Be or BC base cation
BCE exchangeable base cations
BCS base-cation surplus
BCw base cation weathering
BGC Biogeochemical (model)
B-IBI benthic index of biological
integrity
BMPs best management practices
BNF biological nitrogen fertilization
Br bromine
Br~ bromide ion
Bn molecular bromine
BrCl bromine chloride
BrO bromine mooxide
BUV Backscatter Ultraviolet
Spectrometer
BUVD Beneficial Use Values Database
C carbon; concentration
12C carbon-12, stable isotope of
carbon
13C carbon-13, stable isotope of
carbon
Ca ambient air concentration
Ca calcium
Ca2+ calcium ion
CAA Clean Air Act
CAAA Amendments to the Clean Air
Act
CAAAC Clean Air Act Advisory
Committee
CaCk calcium chloride
CaCCb calcium carbonate
CALIPSO Cloud-Aerosol Lidar and
Infrared Pathfinder Satellite
Observation (satellite)
Ca(NC>3)2 calcium nitrate
February 2017
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Acronym/Abbreviation
Meaning
Acronym/Abbreviation
Meaning
Ca(OH>
calcium hydroxide
CINO2
nitryl chloride
CAPMoN
Canadian Air and Precipitation
Monitoring Network
CMAQ
Community Multiscale Air
Quality (modeling system)
CaS04-2H20
CASTNet
gypsum
Clean Air Status and Trends
Network
CMSA
CO
consolidated metropolitan
statistical area
carbon monoxide
CB4
Carbon Bond 4 (model)
CO2
carbon dioxide
Cd
cadmium
CO3-
carbonate
CEC
cation exchange capacity
CONUS
continental U.S.
CENTURY
model that simulates carbon,
nitrogen, phosphorus, sulfur, and
water dynamics in the soil-plant
system at monthly intervals over
time scales of centuries and
millennia
CPUE
CRREL
CS
catch per unit effort
U.S. Army Cold Regions
Research and Engineering
Laboratory
Consumer surplus
CFCs
chlorinated fluorocarbons
CS2
carbon disulfide
CG
cloud-to-ground (lightning flash)
CSS
coastal sage scrub (ecosystem)
Chi a
chlorophyll a
CTM
chemical transport model
CH4
methane
Cu
copper
C2H4
ethene
CV
contingent valuation
C2U6
ethane
CVM
contingent valuation method
CsRs
isoprene
A, 5
delta, difference; change
CH3CHO
CH3C(0)
CH3C(0)00
CH2I2
acetaldehyde
acetyl radical
acetyl peroxy radical
diiodomethane
DayCent
DayCent-Chem
model for daily biogeochemistry
for forest, grassland, cropland,
and savanna systems
combination of DayCent-Chem
and PHREEQC models
CH-20
formaldehyde
DC
dichotomous choice
CH300H
methyl hydroperoxide
DDRP
Direct Delayed Response Project
CH3-S-CH3
dimethylsulfide, DMS
DDT
Damage Delay Time
CH3-S-H
(CH3)2SO
CH3S03H
CH3-S-S-CH3
Ci
CL
CI
methyl mercaptan
dimethyl sulfoxide, DMSO
methanesulfonic acid
dimethyl disulfide, DMDS
interstitial air concentration
critical load
chlorine
DECOMP
DEP
DIC
DIN
DMDS
decomposition model based on
soil-plant system dynamics
Department of Environmental
Protection
dissolved inorganic carbon
dissolved inorganic nitrogen
dimethyl disulfide,
CH3-S-S-CH3
cr
chloride ion
DMS
dimethyl sulfide, CH3-S-CH3
C12
molecular chlorine
DMSO
dimethylsulfoxide
CLaMS
type of Lagrangian model
DNDC
Denitrification-Decomposition
(model)
dissolved oxygen
CloudSat
NASA Earth observation
satellite
DO
February 2017 xxxviii DRAFT: Do Not Cite or Quote
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Acronym/Abbreviation Meaning
DOC dissolved organic carbon
DON dissolved organic nitrogen
EBB East Bear Brook
EC elemental carbon
EEAs Essential Ecological Attributes
ELA Experimental Lakes Area
ELS Eastern Lakes Survey
EMAP Environmental Monitoring and
Assessment Program
EMEFS Eulerian Model Evaluation Field
Study
EMEP Co-operative Programme for
Monitoring and Evaluation of
the Long-range Transmission of
Air Pollutants in Europe
EMF ectomycorrhizal fungi
EOS Earth Observation System
U.S. EPA U.S. Environmental Protection
Agency
eq equivalents
ER ecosystem respiration
EPT Ephemeroptera-Plecoptera-
Tricoptera (index)
ERP Episodic Response Project
ESA European Space Agency
EVRI Environmental Valuation
Reference Inventory
F flux
F~ fluoride ion
FAB First-order Acidity Balance
model
FACE free-air CO2 enrichment (studies)
Fe iron
FeP04 iron phosphate
FeS iron sulfide
F-factor fraction of the change in mineral
acid anions that is neutralized by
base cation release
FHM Forest Health Monitoring
FIA Forest Inventory and Analysis
(program)
FISH Fish in Sensitive Habitats
(project)
Acronym/Abbreviation
Meaning
FLEXPART
type of Lagrangian model
ForSAFE
three-component model using
nitrogen, carbon cycling, and
soil chemistry
FRM
Federal Reference Method
FTIR
Fourier Transform Infrared
Spectroscopy
FW2
black carbon soot
Fx
flux
YN2O5
uptake coefficient for N2O5 on
particles
GAW
Global Atmospheric Watch
(program)
GCE
Goddard Cumulus Ensemble
(model)
GDP
gross domestic product
GEOS
Goddard Earth Observing
System
GEOS-Chem
Goddard Earth Observing
System (with global chemistry
transport model)
GEOS-IDAS
Goddard Earth Observing
System Data Assimilation
System
GFED
Global Fire Emissions Database
GHG
greenhouse gas
GOES
Geostationary Operational
Environmental Satellites
GOME
Global Ozone Monitoring
Experiment
GPP
gross primary productivity
gs
stomatal conductance
GtC
gigaton carbon
Gton
gigaton
GWP
global warming potential
H
hydrogen; hydrogen atom
2H
hydrogen-2, deuterium, stable
isotope of hydrogen
H+
proton, hydrogen ion; relative
acidity
ha
hectare
HAPs
hazardous air pollutants
HBEF
Hubbard Brook Experimental
Forest
February 2017
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Acronym/Abbreviation Meaning
HBES
Hubbard Brook Ecosystem
Study
HBN
Hydro logic Benchmark Network
HC
hydrocarbon
HCHO
formaldehyde
HC1
hydrochloric acid
HC03~
bicarbonate
Hg
mercury
HNCh, HONO
nitrous acid
HNO3, HOONO
nitric acid
HNO4
pernitric acid
HO2
hydroperoxyl radical
H2O2
hydrogen peroxide
HO2NO2
peroxynitric acid
HOBr
hypobromous acid
HOC1
hypochlorous acid
HOX
hypohalous acid
HP
hedonic pricing
HSO3-
bisulfate ion
HSO4-
sulfuric acid ion
H2S
hydrogen sulfide
H2SO3
sulfurous acid
H2SO4
sulfuric acid
HUC-8s
8 digit Hydrologic Unit Codes
hv
photon with energy at
wavelength v
I
iodine
I2
molecular iodine
IA
Integrated Assessment
IADN
Integrated Atmospheric
Monitoring Deposition Network
IC
intracloud (lightning flash)
ILWAS
Integrated Lake-Watershed
Acidification Study
IPC
International Cooperative
Programme
IEc
Industrial Economicsym
IIASA
International Institute for
Applied Systems Analysis
IMPROVE
Interagency Monitoring of
Protected Visual Environments
February 2017 xl
Acronym/Abbreviation Meaning
INOs
iodine nitrate
INTEX-NA
Intercontinental Chemical
Transport Experiment—North
America
IO
iodine oxide
IPCC
Intergovernmental Panel on
Climate Change
IPCC-AR4
Intergovernmental Panel on
Climate Change 4th Assessment
Report
IPCC-TAR
Intergovernmental Panel on
Climate Change 3rd Assessment
Report
IQR
interquartile range
IR
infrared
ISA
Integrated Science Assessment
J
flux from a leaf, deposition flux
(g/cm/second)
JK
Joyce Kilmer
JPL
Jet Propulsion Laboratory
JRGCE
Jasper Ridge Global Climate
Change Experiment
K
potassium
K+
potassium ion
Ka
dissociation constant
Kb
dissociation constant
KH
Henry's Law constant in M/atm
(M-atnT1)
kmol
kilomole
KNOs
potassium nitrate
Kw
ion product of water
LAF
Lake Acidification and Fisheries
LAR
leaf-area ratio
LB
laboratory bioassay
LC0.01
lethal concentration at which
0.01% of exposed animals die
LD33
lethal dose at which 33% of
exposed animals die
LDH
lactic acid dehydrogenase
LG
Linville Gorge
LIDAR
Light Detection and Ranging
(remote sensing system)
LIF
laser-induced fluorescence
DRAFT: Do Not Cite or Quote
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Acronym/Abbreviation Meaning Acronym/Abbreviation Meaning
LIMS
Limb Infrared Monitor of the
MOZAIC
Measurement of Ozone and
Stratosphere
Water Vapor by Airbus
LMCO
Lacasse-like multicopper
In-Service Aircraft
oxidase
MOZART
Model for Ozone and Related
LOD
limit of detection
Chemical Tracers
LP
long-path
MPAN
peroxymethacrylic nitrate
LRTAP
Long Range Transport of Air
MPCA
Minnesota Pollution Control
Pollution
Agency
LTER
Long-Term Ecological Research
MSA
metropolitan statistical area
(program)
Mt
million, or mega tons
LTM
Long-Term Monitoring (project)
N
nitrogen
M
air molecule
N, n
number of observations
MA
Millennium Ecosystem
14N
nitrogen-14, stable isotope of
Assessment
nitrogen
MAGIC
Model of Acidification of
15N
nitrogen-15, stable isotope of
Groundwater in Catchments
nitrogen
(model)
N2
molecular nitrogen; nonreactive
MAHA
Mid-Atlantic Highlands
nitrogen
Assessment of streams
N14C
plant soil N and C cycling model
MAQSIP
Multiscale Air Quality
Simulation Platform (model)
NA
not available; insufficient data
MAT
moist acidic tundra
Na
sodium
MAX-DO AS
multiple axis differential optical
Na+
sodium ion
absorption spectroscopy
NAAQS
National Ambient Air Quality
MBC
microbial biomass carbon
Standards
MBL
marine boundary layer
NaCl
sodium chloride
MDN
Mercury Deposition Network
NADP
National Atmospheric
MeHg
Methylmercury
Deposition Program
model ensemble mean
Na2Mo04
sodium molybdate
MEM
NAMS
National Air Monitoring Stations
Heq
Microequivalent
Mg
Magnesium
NANI
Net anthropogenic nitrogen
inputs
Mg2+
magnesium ion
NAPAP
National Acid Precipitation
MIMS
membrane inlet mass
Assessment Program
spectrometry
NASQAN
National Stream Quality
MM5
National Center for Atmospheric
Accounting Network
Research/Penn State Mesoscale
NARSTO
program formerly known as
Model, version 5
North American Regional
Mn
Manganese
Strategy for Atmospheric Ozone
MOBILE6
Highway Vehicle Emission
NAS
National Academy of Sciences
Factor Model
NASA
National Aeronautics and Space
MODIS
Moderate Resolution Imaging
Administration
Spectroradiometer
Na2S04
sodium sulfate
MOPITT
Measurement of Pollution in the
NASQAN
National Stream Quality
Troposphere (satellite
Accounting Network
instrument)
February 2017
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Acronym/Abbreviation Meaning
NATTS National Air Toxics Trends
(network)
NAWQA National Water Quality
Assessment (program)
NCore National Core Monitoring
Network
N_dep nitrogen deposition
NEE net ecosystem exchange
NEG/ECP New England Governors and
Eastern Canadian Premiers
NEI National Emissions Inventory
NEON National Ecological Observatory
Network
NEP net ecosystem productivity
N-fert nitrogen-fertilization
N-fix nitrogen-fixing vegetation
NFI net factor income
NH3 ammonia
NH2 amino (chemical group)
NH4+ ammonium ion
NH4CI ammonium chloride
NH4NO3 ammonium nitrate
(NH4)2S04 ammonium sulfate
NHx category label for NH3 plus
NH4+
NHy total reduced nitrogen
Ni nickel
NILU Norwegian Institute for Air
Research
NITREX Nitrogen saturation Experiments
nitro-PAH nitro-polycyclic aromatic
hydrocarbon
NLCD National Land Cover Data
Nmin nitrogen mineralization
NMOC nonmethane organic compound
NO nitric oxide
NO2 nitrogen dioxide
NO2- nitrite
MV nitrate
N2O nitrous oxide
N2O5 dinitrogen pentoxide
Acronym/Abbreviation Meaning
NOAA
U.S. National Oceanic and
Atmospheric Administration
NOAA-ARL
U.S. National Oceanic and
Atmospheric Administration Air
Resources Laboratory
NOAEL
no-observed-adverse-effect level
NOEC
no-observed-effect concentration
NOx
sum of NO and NO2
NOy
sum of NOx and NOz; odd
nitrogen species; total oxidized
nitrogen
NOz
sum of all inorganic and organic
reaction products of NOx
(HONO, HNO3, HNO4, organic
nitrates, particulate nitrate,
nitro-PAHs, etc.)
NPOESS
National Polar-orbiting
Operational Environmental
Satellite System
NPP
net primary production
NPS
National Park Service
Nr
reactive nitrogen
NRC
National Research Council
NS or n.s.
nonsignificant
NSF
National Science Foundation
NSS
National Stream Survey
Nss
nonsea salt
NSTC
National Science and
Technology Council
NSWS
National Surface Water Survey
NTN
National Trends Network
NuCM
nutrient cycling model
O2
molecular oxygen
O3
ozone
16o
oxygen-16, stable isotope of
oxygen
18o
oxygen-18, stable isotope of
oxygen
19o
oxygen-19, radioactive isotope
of oxygen
OC
organic carbon
O-CN
terrestrial biosphere model
OCO
Orbiting Carbon Observatory
OCS
carbonyl sulfide
February 2017
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Acronym/Abbreviation Meaning
O('D)
electronically excited oxygen
atom
OH
hydroxyl radical
OM
organic matter
OMI
Ozone Monitoring Instrument
0(3P)
ground-state oxygen atom
P
phosphorus
P,P
probability value
Pi
1 st percentile
P5
5th percentile
P95
95th percentile
P99
99th percentile
PAHs
polycyclic aromatic
hydrocarbons
PAMS
Photochemical Assessment
Monitoring Stations
PAN
peroxyacetyl nitrate
PANs
peroxyacyl nitrates
PARASOL
Polarization and Anisotropy of
Reflectances for Atmospheric
Sciences coupled with
Observations from a Lidar
(satellite instrument)
Pb
lead
PBL
planetary boundary layer
PC
payment card
PCBs
polychlorinated biphenyl
compounds
PH
relative acidity
P(HN03)
production of nitric acid
PHREEQC
model for soil and water
geochemical equilibrium
PIRLA
Paleocological Investigation of
Recent Lake Acidification
(projects)
pKa
dissociation constant
PM
particulate matter
PM2.5
particulate matter with
aerodynamic diameter of #2.5
(rm
PM10
particulate matter with
aerodynamic diameter #10 jim
February 2017 xliii
Acronym/Abbreviation Meaning
PMlO-2.5
particulate matter with
aerodynamic diameter between
10 and 2.5 |im
PM-CAMx
Comprehensive Air Quality
Model with extensions and with
particulate matter chemistry
PnET
Photosynthesis and
EvapoTranspiration (model)
PnET-BGC
Photosynthesis and
EvapoTranspiration-
Biogeochemical (model)
PnET-CN
Photosynthesis and
EvapoTranspiration model of C,
water, and N balances
PnET-N-DNDC
Photosynthesis and
EvapoTranspiration-
Denitrification-Decomposition
(model)
pNOs"
particulate nitrate
P(03)
production of O3
PO,f, PO43-
phosphate
POPs
persistent organic pollutants
Ppb
parts per billion
PPN
peroxypropionyl nitrate
Ppt
parts per trillion
PRB
policy relevant background
PRE-STORM
Preliminary Regional
Experiment for STORM
PROFILE
model using soil mineralogy as
input
PS
producer surplus
pS042~
particulate sulfate
P(so42-)
production of sulfate
Q
flow rate; discharge
Q10
temperature coefficient
QAPP
Quality Assurance Project Plan
R
generic organic group attached
to a molecule
R2
coefficient of determination
r2
correlation coefficient
Ra
aerodynamic resistance
Raboveground
aboveground respiration
Rautotrophic
soil autotrophic respiration
Rb
boundary layer resistance
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Acronym/Abbreviation Meaning
Rc internal resistance
RADM Regional Acid Deposition Model
RAMS Regional Atmospheric Modeling
System
RAPS Regional Air Pollution Study
RCOO-s strongly acidic organic anions
RC(0)00 organic peroxy radical
RDT Recovery Delay Time
REMAP Regional Environmental
Monitoring and Assessment
Program
RH relative humidity
RLTM Regional Long-Term Monitoring
Rmicrobiai microbial respiration
RMCC Research and Monitoring
Coordinating Committee
RMSE root mean squared error
RO2 organic peroxyl; organic peroxy
RONO2 organic nitrate
RO2NO2 peroxynitrate
ROS rain on snow
RP revealed preferences
RRx lognormal-transformed response
ratio
response ratio
Rsoil total soil respiration
RuBisCO ribulose-l,5-bisphosphate
carboxylase/oxygenase
s second
S sulfur
32S sulfur-32, stable isotope of sulfur
34S sulfur-34, stable isotope of sulfur
35S sulfur-35, radioactive isotope of
sulfur
SAA sum of mineral acid anion
concentrations
SAFE Soil Acidification in Forest
Ecosystems (model)
SAMAB Southern Appalachian Man and
the Biosphere (program)
SAMI Southern Appalachian
Mountains Initiative
Acronym/Abbreviation Meaning
SAO Smithsonian Astrophysical
Observatory
SAPRAC Statewide Air Pollution Research
Center
SBC sum of base cation
concentrations
SBUV Solar Backscatter Ultraviolet
Spectrometer
SC safe concentration
SCAQS Southern California Air Quality
Study
SCIAMACHY Scanning Imaging Absorption
Spectrometer for Atmospheric
Chartography
Se selenium; standard error
SEARCH Southeastern Aerosol Research
and Characterization Study
(monitoring program)
Si silicon
SIP State Implementation Plan
SJAQS San Joaquin Valley Air Quality
Study
SLA specific leaf area
SLAMS State and Local Air Monitoring
Stations
SMART Simulation Model for
Acidification's Regional Trends
(model)
SMB Simple Mass Balance (model)
SMBE steady-state mass-balance
equations
SO sulfur monoxide
502 sulfur dioxide
503 sulfur trioxide
S032~ sulfite
S042~ sulfate ion
S2O disulfur monoxide
SOM soil organic matter
SONEX Subsonics Assessment Ozone
and Nitrogen Oxides Experiment
SOS Southern Oxidant Study
SOS/T State of Science/Technology
(report)
SOx sulfur oxides
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Acronym/Abbreviation Meaning
SP
stated preferences
SPARROW
SPAtially Referenced
Regressions on Watershed
SR
Attributes (model)
Shining Rock
Sr
strontium
86 Sr
strontium-86, stable isotope of
strontium
87Sr
strontium-87, stable isotope of
strontium
SRB
sulfate-reducing bacteria
SRP
soluble reactive phosphorus
SSWC
Steady State Water Chemistry
(model)
STA
Soil Texture Approximations
(model)
STE
strata spheric-tropo spheric
exchange
STN
Speciation Trends Network
SUM06
seasonal sum of all hourly
average concentrations
>0.06 ppm
SVOC
semivolatile organic compound
SWAS
Shenandoah Watershed Study
T, T
tau, atmospheric lifetime
T
time; duration of exposure
TAF
Tracking and Analysis
Framework (model)
Tair
air temperature
TAMM
Timber Assessment Market
Model
TAR
Third Assessment Report
TC
total carbon; travel cost
TCM
travel cost method
TDLAS
Tunable Diode Laser Absorption
Spectrometer
Tg
teragram
TIME
Temporally Integrated
Monitoring of Ecosystems
(program)
TN
total nitrogen
TOC
total organic carbon
TOMS
Total Ozone Mapping
Spectrometer
Acronym/Abbreviation Meaning
TOR tropospheric ozone residual
TP total phosphorus
TRACE-P Transport and Chemical
Evolution over the Pacific
TSI timber-stand improvement
TSS total suspended solids
Twater water temperature
UAN urea and ammonium nitrate
fertilizer
UMD-CTM University of Maryland
Chemical Transport Model
UNECE United Nations Economic
Commission for Europe
USDA U.S. Department of Agriculture
USFS U.S. Forest Service
USGS U.S. Geological Survey
UV ultraviolet
UV-A ultraviolet radiation of
wavelengths from 320 to 400 nm
UV-B ultraviolet radiation of
wavelengths from 280 to 320 nm
Vd deposition rate, deposition
velocity (cm/s)
VOC volatile organic compound
VSD Very Simple Dynamic (soil
acidification model)
VTSSS Virginia Trout Stream
Sensitivity Study
WARMS Waterfowl Acidification
Response Modeling System
WATERSN Watershed Assessment Tool for
Evaluating Reduction Scenarios
for Nitrogen
WBB West Bear Brook
WEBB Water, Energy, and
Biogeochemical Budgets
WFPS water-filled pore space
WGE Working Group on Effects
WLS Western Lakes Survey
WMO World Meteorological
Organization
WMP W atershed Manipulation Proj ect
WSA Wadeable Stream Assessment
(survey)
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Acronym/Abbreviation
wt %
WTA
WTP
XNOs
XO
yr
Zn
ZnO
Meaning
percent by weight
willingness-to-accept
willingness-to-pay
nitrate halogen-X salt
halogen-X oxide
year
zinc
zinc oxide
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PREFACE
Legislative Requirements for the Review of the National Ambient
Air Quality Standards
Two sections of the Clean Air Act (CAA) govern the establishment, review, and revision
of the National Ambient Air Quality Standards (NAAQS). Section 108 [42 U.S. Code
(U.S.C.) 7408] directs the Administrator to identify and list certain air pollutants and then
to issue air quality criteria for those pollutants. The Administrator is to list those air
pollutants that in their "judgment, cause or contribute to air pollution which may
reasonably be anticipated to endanger public health or welfare," "the presence of which
in the ambient air results from numerous or diverse mobile or stationary sources," and
"for which ... [the Administrator] plans to issue air quality criteria ..." [42 U.S.C.
7408(a)(1); (CAA. 1990a)1. Air quality criteria are intended to "accurately reflect the
latest scientific knowledge useful in indicating the kind and extent of all identifiable
effects on public health or welfare, which may be expected from the presence of [a]
pollutant in the ambient air ..." [42 U.S.C. 7408(b)]. Section 109 [42 U.S.C. 7409;
(CAA. 1990b) I directs the Administrator to propose and promulgate "primary" and
"secondary" NAAQS for pollutants for which air quality criteria are issued.
Section 109(b)(1) defines a primary standard as one "the attainment and maintenance of
which in the judgment of the Administrator, based on such criteria and allowing an
adequate margin of safety, are requisite to protect the public health."1 A secondary
standard, as defined in Section 109(b)(2), must "specify a level of air quality the
attainment and maintenance of which, in the judgment of the Administrator, based on
such criteria, is requisite to protect the public welfare from any known or anticipated
adverse effects associated with the presence of [the] air pollutant in the ambient air."2
In setting standards that are "requisite" to protect public health and welfare as provided in
Section 109(b), the U.S. EPA's task is to establish standards that are neither more nor less
stringent than necessary for these purposes. In so doing, the U.S. EPA may not consider
the costs of implementing the standards.3 Likewise, "[a]ttainability and technological
1 The legislative history of Section 109 indicates that a primary standard is to be set at"... the maximum permissible
ambient air level ... which will protect the health of any [sensitive] group of the population," and that for this
purpose "reference should be made to a representative sample of persons comprising the sensitive group rather than
to a single person in such a group" S. Rep. No. 91:1196, 91st Cong., 2d Sess. 10 (1970).
2 Section 302(h) of the Act [42 U.S.C. 7602(h)] provides that all language referring to effects on welfare includes,
but is not limited to, "effects on soils, water, crops, vegetation, man-made materials, animals, wildlife, weather,
visibility and climate, damage to and deterioration of property, and hazards to transportation, as well as effects on
economic values and on personal comfort and well-being ..." (CAA. 20051.
3 See generally, Whitman v. American Trucking Associations, 531 U.S. 457, 465-472, 475-476 (2001).
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feasibility are not relevant considerations in the promulgation of national ambient air
quality standards."4
Section 109(d)(1) requires that "not later than December 31, 1980, and at 5-year intervals
thereafter, the Administrator shall complete a thorough review of the criteria published
under Section 108 and the national ambient air quality standards ... and shall make such
revisions in such criteria and standards and promulgate such new standards as may be
appropriate ...Section 109(d)(2) requires that an independent scientific review
committee "shall complete a review of the criteria ... and the national primary and
secondary ambient air quality standards ... and shall recommend to the Administrator any
new ... standards and revisions of existing criteria and standards as may be
appropriate ...Since the early 1980s, this independent review function has been
performed by the Clean Air Scientific Advisory Committee (CASAC).5
Overview and History of the Reviews of the Secondary National
Ambient Air Quality Standards for Nitrogen Dioxide, Sulfur
Dioxide, and Particulate Matter
NAAQS are defined by four basic elements: indicator, averaging time, level, and form.
The indicator defines the pollutant to be measured in the ambient air for the purpose of
determining compliance with the standard. The averaging time defines the time period
over which air quality measurements are to be obtained and averaged or cumulated,
considering evidence of effects associated with various time periods of exposure. The
level of a standard defines the air quality concentration used (i.e., an ambient
concentration of the indicator pollutant) in determining whether the standard is achieved.
The form of the standard defines the air quality statistic that is compared to the level of
the standard in determining whether an area attains the standard. The Administrator
considers these four elements collectively in evaluating the protection to public welfare
provided by the secondary NAAQS.
Nitrogen Dioxide Secondary National Ambient Air Quality
Standards
The first air quality criteria and standards for oxides of nitrogen were issued in 1971
KU.S. EPA. 1971). 36 FR 8186], Both the primary and secondary standards were set at
0.053 parts per million (ppm), as an annual arithmetic mean (36 FR 8186). In 1982, the
4 Sqq American Petroleum Institute v. Costle, 665 F. 2d at 1185.
5 Lists of chartered CASAC members and of members of the CASAC Panels are available at:
http://vosemite.epa.gov/sab/sabproduct.nsfAVebCASAC/CommitteesandMembership7QpeiiDocument.
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U.S. EPA published Air Quality Criteria for Oxides of Nitrogen (U.S. EPA. 1982a).
which updated the scientific criteria upon which the initial standards were based. On
February 23, 1984, the U.S. EPA proposed to retain these standards (49 FR 6866). After
taking into account public comments, the U.S. EPA published the final decision to retain
the existing standards on June 19, 1985 (50 FR 25532).
In November 1991, the U.S. EPA initiated another review and released an updated draft
air quality criteria document (AQCD) for review and comment by CASAC and the public
(56 FR 59285). The final AQCD was released later in 1993 (U.S. EPA. 1993). Staff of
the Office of Air Quality Planning and Standards (OAQPS) prepared a draft Staff Paper
that summarized and integrated the key studies and scientific evidence contained in the
revised air quality criteria document and identified the critical elements to be considered
in the review of the NO2 NAAQS. The Staff Paper was reviewed by the CASAC and the
public in December 1994, and in September 1995, the U.S. EPA finalized the Staff Paper
(U.S. EPA. 1995b). On October 2, 1995, the Administrator announced her proposed
decision not to revise either the primary or secondary NAAQS for NO2 based on the
information available in this review (60 FR 52874; October 11, 1995). After
consideration of public comments, the Administrator made a final determination that
revisions to neither the primary nor the secondary NAAQS for NO2 were appropriate at
that time (61 FR 52852; October 8, 1996).
The most recent review of the secondary NAAQS standards for oxides of nitrogen was
performed jointly with a review of the secondary NAAQS for oxides of sulfur beginning
in 2005 (described below).
Sulfur Dioxide Secondary National Ambient Air Quality
Standards
Based on the 1969 sulfur oxides criteria document (HEW. 1969). the U.S. EPA
promulgated the initial primary and secondary NAAQS for SO2 on April 30, 1971 (36 FR
8186). The secondary standards were 0.02 ppm as an annual arithmetic mean and
0.5 ppm as a maximum 3-hour, not to be exceeded more than once per year. These
secondary standards were established on the basis of vegetation effects evidence
described in the 1970 criteria document. Based on additional data available in 1973,
revisions were made to Chapter 5 "Effects of Sulfur Oxide in the Atmosphere on
Vegetation" of the Air Quality Criteria for Sulfur Oxides (U.S. EPA. 1973). which led the
U.S. EPA to propose (38 FR 11355) and then finalize a revocation of the annual mean
secondary standard (38 FR 25678). At that time, the U.S. EPA additionally considered
welfare effects related to effects on materials, visibility, soils, and water. However, the
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U.S. EPA concluded that either protection from such effects was afforded by the primary
standard or that sufficient data were not then available to develop criteria for standards
based on these effects (38 FR 25680).
In 1980, the U.S. EPA released a combined AQCD for sulfur oxides and particulate
matter for CASAC review. Following its review of a draft revised criteria document in
August 1980, the CASAC concluded that acidic deposition was atopic of extreme
scientific complexity, noting that a fundamental problem of addressing acid deposition in
a criteria document is that acidic deposition is produced by several pollutants, including
oxides of sulfur, oxides of nitrogen, and the fine particulate fraction of suspended
particles KU.S. EPA. 1982b). pp. 125-126], Following CASAC closure on the criteria
document in December 1981, the U.S. EPA released a final AQCD (U.S. EPA. 1982b).
and the OAQPS prepared a Staff Paper that was released in November 1982 (U.S. EPA.
1982c). The issue of acidic deposition was not, however, assessed directly in the OAQPS
Staff Paper because the U.S. EPA followed the guidance given by CASAC.
In response to CASAC recommendations for a separate comprehensive discussion of
acidic deposition as part of the criteria documents, the U.S. EPA subsequently prepared
the following documents: The Acidic Deposition Phenomenon and Its Effects: Critical
Assessment Review Papers, Volumes I and II (U.S. EPA. 1984a. b) and The Acidic
Deposition Phenomenon and Its Effects: Critical Assessment Document I (Bennett et al..
1985); 53 FR 14935-14936], Although these documents were not considered criteria
documents and had not undergone CASAC review, they represented the most
comprehensive summary of relevant scientific information completed by the U.S. EPA at
that point (58 FR 21355).
At about the same time in 1980 as the CASAC recommendation for a comprehensive
assessment of acidic deposition, Congress created the National Acid Precipitation
Assessment Program (NAPAP). During the 10-year course of this program, a series of
reports were issued and a final report was issued in 1990 (NAPAP. 1991).
On April 26, 1988, the U.S. EPA proposed not to revise the existing primary and
secondary standards. This proposal regarding the secondary SO2 NAAQS was due to the
Administrators conclusions that (1) based upon the then-current scientific understanding
of the acidic deposition problem, it would be premature and unwise to prescribe any
regulatory control program at that time and (2) when the fundamental scientific
uncertainties had been reduced through ongoing research efforts, the U.S. EPA would
draft and support an appropriate set of control measures (53 FR 14926). Subsequent to
proposal, Congress took up consideration of acidic deposition.
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On November 15, 1990, Amendments to the CAA were passed by Congress and signed
into law by the President. In Title IV of these Amendments, Congress included a
statement of findings that had led them to take this action, including that: "(1) the
presence of acidic compounds and their precursors in the atmosphere and in deposition
from the atmosphere represents a threat to natural resources, ecosystems, materials,
visibility, and public health; (2) the problem of acid deposition is of national and
international significance; and that (3) current and future generations of Americans will
be adversely affected by delaying measures to remedy the problem..." The goal of Title
IV was to reduce emissions of SO2 by 10 million tons and oxides of nitrogen emissions
by 2 million tons from 1980 emission levels in order to achieve reductions over broad
geographic regions/areas. In envisioning that further action might be necessary in the
long term, Congress included Section 404 of the 1990 Amendments. This section requires
the U.S. EPA to conduct a study on the feasibility and effectiveness of an acid deposition
standard or standards to protect "sensitive and critically sensitive aquatic and terrestrial
resources" and at the conclusion of the study, submit a report to Congress. Five years
later, the U.S. EPA submitted to Congress its report titled Acid Deposition Standard
Feasibility Study: Report to Congress (U.S. EPA. 1995a) in fulfillment of this
requirement. The Report to Congress concluded that establishing acid deposition
standards for sulfur and nitrogen deposition might at some point in the future be
technically feasible although appropriate deposition loads for these acidifying chemicals
could not be defined with reasonable certainty at that time.
The 1990 Amendments also added new language to sections of the CAA that pertain to
the scope or application of the secondary NAAQS designed to protect the public welfare.
Section 108 (g) specified that "the Administrator may assess the risks to ecosystems from
exposure to criteria air pollutants (as identified by the Administrator in the
Administrator's sole discretion)." The definition of public welfare in Section 302 (h) was
expanded to state that the welfare effects identified should be protected from adverse
effects associated with criteria air pollutants ".. .whether caused by transformation,
conversion, or combination with other air pollutants."
In response to these legislative initiatives, the U.S. EPA and other federal agencies
continued research on the causes and effects of acidic deposition and related welfare
effects of SO2 and implemented an enhanced monitoring program to track progress (58
FR 21357). In 1993, the U.S. EPA announced a decision not to revise the secondary
standard, concluding that revision to address acidic deposition and related SO2 welfare
effects was not appropriate at that time (58 FR 21351). In reaching this decision, the
U.S. EPA took into account the significant reductions in SO2 emissions, ambient SO2
concentrations and ultimately deposition expected to result from implementation of the
Title IV program, which was expected to significantly decrease the acidification of water
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bodies and damage to forest ecosystems and to permit much of the existing damage to be
reversed with time (58 FR 21357). While recognizing that further action might be needed
to address acidic deposition in the longer term, the U.S. EPA judged it prudent to await
the results of the studies and research programs then underway, including those assessing
the comparative merits of secondary standards, acidic deposition standards, and other
approaches to control of acidic deposition and related effects, and then to determine
whether additional control measures should be adopted or recommended to Congress (58
FR 21358).
In 2000, the U.S. EPA announced receipt of two items related to acidic deposition and the
NAAQS (65 FR 48699). The first was a petition submitted to the U.S. EPA in 1999 by
representatives of seven northeastern states for the promulgation of revised secondary
NAAQS for the criteria pollutants associated with the formation of acid rain (including
NO2, SO2, and fine particulate matter [PM2 5]). The petition states that the language in
Section 302(h) of the CAA "clearly references the transformation of pollutants resulting
in the inevitable formation of sulfate and nitrate aerosols and/or their ultimate
environmental impacts as wet and dry deposition, clearly signaling Congressional intent
that the welfare damage occasioned by sulfur and nitrogen oxides be addressed through
the secondary standard provisions of Section 109 of the Act." The petition further stated
that "recent federal studies, including the NAPAP Biennial Report to Congress: An
Integrated Assessment, document the continued—and increasing—damage being
inflicted by acid deposition to the lakes and forests of New York, New England, and
other parts of our nation, demonstrating that the Title IV program had proven
insufficient." The petition also listed other adverse welfare effects associated with the
transformation of these criteria pollutants, including visibility impairment, eutrophication
of coastal estuaries, global warming, tropospheric ozone, and stratospheric ozone
depletion.
The second item was a related request from the U.S. Department of Interior (DOI) that
the U.S. EPA address many of the same adverse environmental effects associated with
the same types of air pollutants and with ozone that the DOI asserted were occurring in
national parks and wilderness areas (65 FR 48699). Included among the effects of
concern identified in the request were acidification of streams, surface waters and/or
soils, eutrophication of coastal waters, visibility impairment, and foliar injury from ozone
(65 FR 48701). The U.S. EPA requested comment on the issues raised by these requests,
stating that it would consider any relevant comments and information submitted, along
with the information provided by the petitioners and DOI, before making any decision
concerning a response to these requests for rulemaking, which if commenced would
include opportunity for public review and comment (65 FR 48701).
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Particulate Matter Secondary National Ambient Air Quality
Standards
The U.S. EPA first established NAAQS for particulate matter (PM) in 1971 (36 FR 8186,
April 30, 1971) based on the original AQCD (NAPCA. 1969). The AQCD assessed the
evidence for a variety of PM-associated welfare effects, including visibility impairment
and materials damage (e.g., soiling, corrosion). Based on evidence for such effects, the
secondary standards were set at 150 (ig/m3 for the 24-hour average not to be exceeded
more than once per year and 60 |ig/m3 for the annual geometric mean. The federal
reference method (FRM) specified for determining attainment of the original standards
was the high-volume sampler, which collects PM up to a nominal size of 25 to
45 micrometers (|im: referred to as total suspended particulates or TSP).
In October 1979 (44 FR 56730; October 2, 1979), the U.S. EPA announced the first
periodic review of the air quality criteria and NAAQS for PM. Revised primary and
secondary standards were promulgated in 1987 (52 FR 24634; July 1, 1987). In the 1987
decision, the U.S. EPA changed the indicator for particles from TSP to PMio to focus on
the subset of inhalable particles small enough to penetrate to the thoracic region of the
respiratory tract (including the tracheobronchial and alveolar regions) referred to as
thoracic particles.6 The level of the 24-hour standards (primary and secondary) was set at
150 |ig/m3. and the form was one expected exceedance per year, on average, over 3 years.
The level of the annual standards (primary and secondary) was set at 50 |ig/m3. and the
form was annual arithmetic mean averaged over 3 years.
In April 1994, the U.S. EPA announced its plans for the second periodic review of the air
quality criteria and NAAQS for PM, and in 1997, the U.S. EPA promulgated revisions to
the NAAQS (62 FR 38652, July 18, 1997). In the 1997 decision, the U.S. EPA
determined that the fine and coarse fractions of PMio should be considered separately.
This determination was based on evidence that serious health effects were associated with
short- and long-term exposures to fine particles in areas that met the existing PMio
standards. The U.S. EPA added new standards using PM2 5 as the indicator for fine
particles (with PM2 5 referring to particles with a nominal mean aerodynamic diameter
less than or equal to 2.5 |im). These new standards were as follows: (1) an annual
standard with a level of 15.0 |ig/m3 based on the 3-year average of annual arithmetic
mean PM2 5 concentrations from single or multiple community-oriented monitors and
(2) a 24-hour standard with a level of 65 |ig/m3 based on the 3-year average of the 98th
6 PMio refers to particles with a nominal mean aerodynamic diameter less than or equal to 10 |im. More specifically,
10 |im is the aerodynamic diameter for which the efficiency of particle collection is 50%. Larger particles are not
excluded altogether but are collected with substantially decreasing efficiency while smaller particles are collected
with increasing efficiency.
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percentile of 24-hour PM2 5 concentrations at each monitor within an area. Also, the
U.S. EPA established a new reference method for the measurement of PM2 5 in the
ambient air and adopted rules for determining attainment of the new standards. To
continue to address the coarse fraction of PM10 (referred to as thoracic coarse particles or
PM10-2.5; generally including particles with a nominal mean aerodynamic diameter
greater than 2.5 |im and less than or equal to 10 |im). the U.S. EPA retained the annual
PM10 standard and revised the form of the 24-hour PM10 standard to be based on the 99th
percentile of 24-hour PM10 concentrations at each monitor in an area. The U.S. EPA
revised the secondary standards by setting them equal in all respects to the primary
standards.
Following promulgation of the 1997 PM NAAQS, petitions for review were filed by a
large number of parties, addressing a broad range of issues. In May 1999, the U.S. Court
of Appeals for the District of Columbia Circuit (D.C. Circuit) upheld the U.S. EPA's
decision to establish fine particle standards, holding that "the growing empirical evidence
demonstrating a relationship between fine particle pollution and adverse health effects
amply justifies establishment of new fine particle standards." American Trucking
Associations v. EPA, 175 F. 3d 1027, 1055-56 (D.C. Cir., 1999). The D.C. Circuit also
found "ample support" for the U.S. EPA's decision to regulate coarse particle pollution,
but vacated the 1997 PM10 standards, concluding that the U.S. EPA had not provided a
reasonable explanation justifying use of PM10 as an indicator for coarse particles (175 F.
3d at 1054-55). Pursuant to the D.C. Circuit's decision, the U.S. EPA removed the
vacated 1997 PM10 standards, and the pre-existing 1987 PM10 standards remained in
place (65 FR 80776, December 22, 2000). The D.C. Circuit also upheld the U.S. EPA's
determination not to establish more stringent secondary standards for fine particles to
address effects on visibility (175 F. 3d at 1027).
The D.C. Circuit also addressed more general issues related to the NAAQS, including
issues related to the consideration of costs in setting NAAQS and the U.S. EPA's
approach to establishing the levels of NAAQS. Regarding the cost issue, the court
reaffirmed prior rulings holding that in setting NAAQS the U.S. EPA is "not permitted to
consider the cost of implementing those standards" (Id. at 1040-41). Regarding the levels
of NAAQS, the court held that the U.S. EPA's approach to establishing the level of the
standards in 1997 (i.e., both for PM and for the ozone NAAQS promulgated on the same
day) effected "an unconstitutional delegation of legislative authority" (Id. at 1034-40).
Although the court stated that "the factors U.S. EPA uses in determining the degree of
public health concern associated with different levels of ozone and PM are reasonable," it
remanded the rule to the U.S. EPA, stating that when the U.S. EPA considers these
factors for potential nonthreshold pollutants "what U.S. EPA lacks is any determinate
criterion for drawing lines" to determine where the standards should be set.
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The D.C. Circuit's holding on the cost and constitutional issues were appealed to the U.S.
Supreme Court. In February 2001, the Supreme Court issued a unanimous decision
upholding the U.S. EPA's position on both the cost and constitutional issues. Whitman v.
American Trucking Associations, 531 U.S. 457, 464, 475-76. On the constitutional issue,
the Court held that the statutory requirement that NAAQS be "requisite" to protect public
health with an adequate margin of safety sufficiently guided the U.S. EPA's discretion,
affirming the U.S. EPA's approach of setting standards that are neither more nor less
stringent than necessary.7
In October 1997, the U.S. EPA published its plans for the third periodic review of the air
quality criteria and NAAQS for PM (62 FR 55201; October 23, 1997). On September 21,
2006, the U.S. EPA announced its final decisions to revise the primary and secondary
NAAQS for PM to provide increased protection of public health and welfare,
respectively (71 FR 61144; October 17, 2006). With regard to the primary and secondary
standards for fine particles, the U.S. EPA revised the level of the 24-hour PM2 5 standards
to 35 |ig/m3. retained the level of the annual PM2 5 standards at 15.0 (ig/m3, and revised
the form of the annual PM2 5 standards by narrowing the constraints on the optional use of
spatial averaging. With regard to the primary and secondary standards for PM10, the
U.S. EPA retained the 24-hour standards, with levels at 150 |ig/m3. and revoked the
annual standards.8 The Administrator judged that the available evidence generally did not
suggest a link between long-term exposure to existing ambient levels of coarse particles
and health or welfare effects. In addition, a new reference method was added for the
measurement of PM10-2.5 in the ambient air, in order to provide a basis for approving
federal equivalent methods (FEMs) and to promote the gathering of scientific data to
support future reviews of the PM NAAQS.
Several parties filed petitions for review following promulgation of the revised PM
NAAQS in 2006. These petitions addressed the following issues: (1) selecting the level of
the primary annual PM2 5 standard; (2) retaining PM10 as the indicator of a standard for
thoracic coarse particles, retaining the level and form of the 24-hour PM10 standard, and
7 The Supreme Court remanded the case to the Court of Appeals for resolution of any remaining issues that had not
been addressed in that court's earlier rulings (Id. at 475-76). In a March 2002 decision, the Court of Appeals
rejected all remaining challenges to the standards, holding that the U.S. EPA's PM2.5 standards were reasonably
supported by the administrative record and were not "arbitrary and capricious" American Trucking Associations v.
EPA, 283 F. 3d 355, 369-72 (D.C. Cir. 2002).
8 In the 2006 proposal, the U.S. EPA proposed to revise the 24-hour PM10 standard in part by establishing a new
PM10-2.5 indicator for thoracic coarse particles (i.e., particles generally between 2.5 and 10 |im in diameter). The
U.S. EPA proposed to include any ambient mix of PM10-2.5 that was dominated by resuspended dust from high
density traffic on paved roads and by PM from industrial and construction sources. The U.S. EPA proposed to
exclude any ambient mix of PMi 0-2.5 that was dominated by rural windblown dust and soils and by PM generated
from agricultural and mining sources. In the final decision, the existing PM10 standard was retained, in part due to an
"inability.. .to effectively and precisely identify which ambient mixes are included in the [PMi0-2.5] indicator and
which are not" (71 FR 61197; October 17, 2006).
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revoking the PMio annual standard; and (3) setting the secondary PM2 5 standards
identical to the primary standards. On February 24, 2009, the U.S. Court of Appeals for
the District of Columbia Circuit issued its opinion in the case American Farm Bureau
Federation v. EPA, 559 F. 3d 512 (D.C. Cir. 2009). The court remanded the primary
annual PM2 5 NAAQS to the U.S. EPA because the U.S. EPA failed to adequately explain
why the standards provided the requisite protection from both short- and long-term
exposures to fine particles, including protection for at-risk populations {American Farm
Bureau Federation v. EPA, 559 F. 3d 512, 520-27; D.C. Cir. 2009). With regard to the
standards for PM10, the court upheld the U.S. EPA's decisions to retain the 24-hour PM10
standard to provide protection from thoracic coarse particle exposures and to revoke the
annual PM10 standard (American Farm Bureau Federation, 559 F. 2d at 533-38). With
regard to the secondary PM2 5 standards, the court remanded the standards to the
U.S. EPA because the Agency failed to adequately explain why setting the secondary PM
standards identical to the primary standards provided the required protection for public
welfare, including protection from visibility impairment (American Farm Bureau
Federation, 559 F. 2d at 528-32). The U.S. EPA responded to the court's remands as
part of the next review of the PM NAAQS, which was initiated in 2007.
In June 2007, the U.S. EPA initiated the fourth periodic review of the air quality criteria
and the PM NAAQS by issuing a call for information in the Federal Register (72 FR
35462; June 28, 2007). In December 2012, the U.S. EPA announced its final decisions
with regard to the secondary PM standards, the U.S. EPA retained the 24-hour and annual
PM2 5 standards and the 24-hour PM10 standard to address visibility and nonvisibility
welfare effects. On judicial review, the revised standards were upheld in all respects
{NAMv EPA, 750 F.3d 921; D.C. Cir. 2014).
Most Recent Combined Review of the Oxides of Nitrogen
and Oxides of Sulfur National Ambient Air Quality
Standards
In 2005, the U.S. EPA initiated a joint review of the air quality criteria for oxides of
nitrogen and sulfur and the secondary NAAQS for NO2 and SO2. In so doing, the
U.S. EPA assessed the scientific information, associated risks, and standards relevant to
protecting the public welfare from adverse effects associated jointly with oxides of
nitrogen and sulfur. Although the U.S. EPA has historically adopted separate secondary
standards for oxides of nitrogen and oxides of sulfur, the U.S. EPA conducted a joint
review of these standards because oxides of nitrogen and sulfur and their associated
transformation products are linked from an atmospheric chemistry perspective, as well as
from an environmental effects perspective. The joint review was also responsive to the
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National Research Council (NRC) recommendation for the U.S. EPA to consider
multiple pollutants, as appropriate, in forming the scientific basis for the NAAQS (NRC.
2004).
The review was initiated on December 13, 2005 with a call for information (70 FR
73236) for the development of a revised ISA. A draft Integrated Review Plan (IRP) was
released in October 2007, reviewed by CASAC; the final IRP was released in December
2007 ("U.S. EPA. 2007). The first and second drafts of the ISA were released in
December 2007 and August 2008 (73 FR 10243), respectively, for CASAC and public
review. The final ISA(U.S. EPA. 2008a) was released in December 2008 (73 FR 75716).
Based on the scientific information in the ISA, the U.S. EPA developed a Risk and
Exposure Assessment (REA) to further assess the national impact of the effects
documented in the ISA. The Draft Scope and Methods Plan for Risk/Exposure
Assessment: Secondary NAAQS Review for Oxides of Nitrogen and Oxides of Sulfur
outlining the scope and design of the future REA was released in March 2008 (73 FR
10243). A first and second draft of the REA were released (August 2008 and June 2009)
for CASAC review and public comment. The final REA (U.S. EPA. 20090) was released
in September 2009. Drawing on the information in the final REA and ISA, a first draft,
second draft, and final Policy Assessment (PA) were released in March 2010, September
2010, and January 2011, respectively (U.S. EPA. 2011a).
On August 1, 2011, based on consideration of the scientific information and quantitative
assessments, the U.S. EPA published a proposal to (1) retain the existing NO2 and SO2
secondary standards, (2) add secondary standards identical to the NO2 and SO2 primary
1-hour standards, and (3) not set a new multipollutant secondary standard in this review.
After consideration of public comments on the proposed standards and on design of a
new field pilot program to gather and analyze additional relevant data, the Administrator
signed a final decision in this rulemaking on March 20, 2012. The Administrator's
decision was that, while the current secondary standards were inadequate to protect
against adverse effects from deposition of oxides of nitrogen and sulfur, it was not
appropriate under Section 109(b) to set any new secondary standards at this time due to
the limitations in the available data and uncertainty as to the amount of protection the
metric developed in the review would provide against acidification effects across the
country (77 FR 20281). In addition, the Administrator decided that it was appropriate to
retain the current NO2 and SO2 secondary standards to address direct effects of gaseous
NO2 and SO2 on vegetation. Thus, taken together, the Administrator decided to retain and
not revise the current NO2 and SO2 secondary standards: an NO2 standard set at a level of
0.053 ppm as an annual arithmetic average, and an SO2 standard set at a level of 0.5 ppm
as a 3-hour average, not to be exceeded more than once per year (77 FR 20281).
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The U.S. EPA's decision to not set a secondary NAAQS for oxides of nitrogen and sulfur
even though the Administrator had concluded that the existing standards are not adequate
to protect against the adverse impacts of aquatic acidification on sensitive ecosystems
was challenged by the Center for Biological Diversity and other environmental groups.
The petitioners argued that having decided that the existing standards were not adequate
to protect against adverse public welfare effects such as damage to sensitive ecosystems,
the Administrator was required to identify the requisite level of protection for the public
welfare and to issue a NAAQS to achieve and maintain that level of protection. The D.C.
Circuit disagreed, finding that the U.S. EPA acted appropriately in not setting a
secondary standard given the U.S. EPA's conclusions that "the available information was
insufficient to permit a reasoned judgment about whether any proposed standard would
be 'requisite to protect the public welfare . . (Center for Biological Diversity, et al. v.
EPA, 749 F.3d 1079, 1087; 2014). In reaching this decision, the court noted that the
U.S. EPA had "explained in great detail" the profound uncertainties associated with
setting a secondary NAAQS to protect against aquatic acidification.
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EXECUTIVE SUMMARY
Purpose and Scope of the Integrated Science Assessment
This Integrated Science Assessment (ISA) for Oxides of Nitrogen, Oxides of Sulfur, and
Particulate Matter—Ecological Criteria provides a comprehensive evaluation and
synthesis of the most policy-relevant science aimed at characterizing the ecological
effects caused by these criteria pollutants.9 These criteria pollutants are reviewed here
together because they all contribute to nitrogen (N) and sulfur (S) deposition, which
causes substantial ecological effects. In this document, the terms "oxides of nitrogen"
refer to total oxidized N (NOy), including NO and NO2, and all other oxidized N
containing compounds formed from NO and NO2.10 Oxides of sulfur (SOx) are defined
here to include sulfur monoxide (SO), sulfur dioxide (SO2), sulfur trioxide (SO3), disulfur
monoxide (S2O), and sulfate (SO42 ). However, SO, SO3, and S2O will not be discussed
further because they occur at much lower ambient levels than SO2 and SO42 . Particulate
matter is composed of some or all of the following components: nitrate (NO3 ), SO42 .
ammonium (NH/), metals, minerals (dust), and organic and elemental carbon.
Thus, this ISA serves as the scientific foundation for the review of the ecological effects
associated with the secondary (welfare-based) National Ambient Air Quality Standards
(NAAQS) for oxides of nitrogen, oxides of sulfur, and particulate matter. The health
effects of these criteria pollutants are considered in separate assessments as part of the
review of the primary (health-based) NAAQS for oxides of nitrogen (U.S. EPA. 2016b).
oxides of sulfur (U.S. EPA. 2016a). and particulate matter (U.S. EPA. 2009a).11 The
Clean Air Act definition of welfare effects includes, but is not limited to, effects on soils,
water, wildlife, vegetation, visibility, weather, and climate, as well as effects on man-
made materials, economic values, and personal comfort and well-being.
The current secondary NAAQS for oxides of nitrogen and oxides of sulfur were set to
protect against direct damage to vegetation by NO2 or SO2. The secondary NAAQS for
NO2 is identical to the primary standard set in 1971: an annual average not to exceed
9 The general process for developing an ISA, including the framework for evaluating weight of evidence and
drawing scientific conclusions and causal judgments, is described in a companion document, Preamble to the
Integrated Science Assessments (U.S. EPA. 2015e\ www.epa.gov/isa.
10 This ISA reserves the abbreviation NOx strictly as the sum of NO and NO2—consistent with its use in the
atmospheric science community—and uses the term "oxides of nitrogen" to refer to the broader list of oxidized
nitrogen species. Oxides of nitrogen refers to NOy as the total oxidized nitrogen in both gaseous and particulate
forms. The major gaseous and particulate constituents of NOy include nitric oxide (NO), nitrogen dioxide (NO2),
nitric acid (HNO3), peroxyacetyl nitrate (PAN), nitrous acid (HONO), organic nitrates, and particulate nitrate (NO3).
This ISA uses the definitions adopted by the atmospheric sciences community.
11 In this ISA, the blue electronic links can be used to navigate to cited materials as well as chapters, sections, tables,
figures, and studies from this ISA.
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0.053 ppm nitrogen dioxide. The secondary NAAQS for SO2, set in 1973, is a 3-hour
average of 0.5 ppm SO2, not to be exceeded more than once per year. The current
secondary standards for PM are intended to address PM-related visibility and non-
visibility welfare effects. These standards are a 3-year annual mean PM2 5 concentration
of 15 |ig/m3. with the 24-hour average PM2 5 and PM10 set at concentrations of 35 |ig /m3
and 150 |ig/m3. respectively.
This ISA updates the 2008 ISA for Oxides of Nitrogen and Oxides of Sulfur—Ecological
Criteria [hereafter referred to as 2008 ISA (U.S. EPA. 2008a)l. as well as the ecological
portion of the 2009 ISA for Particulate Matter (U.S. EPA. 2009a') with studies and reports
published from January 2008 through December 2015. The U.S. EPA conducted in-depth
searches to identify peer-reviewed literature on relevant topics. Subject-area experts and
the public were also able to recommend studies and reports during a kick-off workshop
held at the U.S. EPA in March 2014 for oxides of nitrogen and oxides of sulfur, and June
2016 for particulate matter. To fully describe the state of available science, the U.S. EPA
also carried over the most relevant studies from previous assessments to include in this
ISA.
This ISA determines whether oxides of nitrogen, oxides of sulfur, and particulate matter
concentrations in the air or depositing from the air cause ecological effects. The
ecological effects of deposition are grouped into three main categories: (1) N
enrichment/N-driven eutrophication (caused by NOy, and particulate forms of N), (2)
acidification (caused by NOy, SOx, and particulate forms of N and S), and (3) S
enrichment (caused by SOx and particulate forms of S). Ecological effects are further
subdivided into terrestrial, wetland, freshwater, and estuarine/near-coastal ecosystems.
These ecosystems and effects are linked by the connectivity of terrestrial and aquatic
habitats through biogeochemical pathways of N and S. A schematic of the document
organization is given by Figure ES-1. Chapter 2 characterizes the sources, atmospheric
processes involving NOy, SOx, and PM, and trends in ambient concentrations and
deposition. Chapter 3 describes direct effects of gas-phase NOy and SOx on plants and
lichens. Chapter 4-Chapter 6 describe N and S deposition effects on terrestrial
biogeochemistry, and the biological effects of terrestrial acidification and terrestrial N
enrichment, respectively. Chapter 7 describes N and S deposition effects on aquatic
biogeochemistry. Chapter 8~Chapter 10 characterize the biological effects of freshwater
acidification, freshwater N enrichment, and marine eutrophication. Chapter 11 describes
effects of N deposition on wetlands. Chapter 12 characterizes the ecological effects of S
as a nutrient. Chapter 13 discusses the climate modification of ecosystem response to N,
and Chapter 14 presents information on ecosystem services. There are also four
appendices. Appendix A provides additional maps of deposition to augment the
information in Chapter 2. while Appendix B provides additional information on mercury
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cycling that is introduced in Chapter 12. Five locations in the U.S. were selected as case
study areas that are candidates for additional analysis of risk and exposure because they
have abundant data on ecological effects; however, the air quality data available varies
among the case studies. These case studies are presented in Appendix C. In addition, the
ecological effects of forms of PM, which are not related to N or S deposition, are
included in Appendix D. The nonecological welfare effects associated with PM, such as
visibility, climate, and materials effects, are considered as part of a separate review of
PM (81 FR 8 793 3, December 6, 2016).
Deposition of
N and S
(Chapter 2)
ISA
schematic
Exposure
Terrestrial Ecosystem
Directto organism/ ambient air concentrations
Exposure/soil and aquatic biogeochemical
pathways
Terrestrial Ecosystems
Directto organism/deposition
Directto soil, effects on soil biogeochemistry (Chapter 4)
Wetland Ecosystems
Directto soil and surface water, runoff from soil
Wetland biogeochemistry (Chapters 11&12)
Freshwater Ecosystems
Directto surface water, runoff from soil, effects on
freshwater biogeochemistry (Chapter 7)
HI
Estuaries Ecosystems
Directto water, transport from watershed runoff, effects on
biogeochemistry along the freshwater to ocean continuum
[Chapter 7)
Biological effects
SOj, N02, NO, PAN, hno3
(Chapter 3)
Plant foliar and lichen Injury
Biological effects of
acidification (NOX+ NHX +SOX)
N enrichment/eutrophication (NOX +NHX)
S-nutrient (SOX)
Terrestrial Ecosystems
Acidification (Chapter 5)
N enrichment/eutroohication (Chapter 61
Wetlands Ecosystems
N enrichment/eutrophication (Chapter 11)
S-nutrient (Chapter 12)
Freshwater Ecosystems
Acidification (Chapter 8)
N enrichment/eutrophication (Chapter 9)
S-nutrient (Chapter 12)
Estuarine Ecosystems
N-nutrient/ eutrophication (Chapter 10)
N-enhanced ocean acidification (Chapter 10)
Climate modification of ecosystem response to N
(Chapter 13)
Ecosystem Services
(Chapter 14)
Appendices
ISA = Integrated Science Assessment; HN03 = nitric acid; N = nitrogen; NHX =reduced nitrogen; NO = nitric oxide; N02 = nitrogen
dioxide; NOx = NO + N02; PAN = peroxyacetyl nitrate; S = sulfur; S02 = sulfur dioxide; SOx = sulfur oxides.
Figure ES-1 Schematic of the integrated science assessment linking
atmospheric concentrations and deposition, soil and aquatic
biogeochemistry, and biological effects
Emissions, Ambient Air Concentrations, and Deposition
The main findings of this ISA are related to N and S deposition; therefore, this summary
of atmospheric chemistry focuses on the deposition of gaseous and particulate forms of N
and S species (including XII ), which primarily result from the atmospheric
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transformations of NOx(NO + N02 ), NHx (reduced N), and SOx emissions. Numerous
factors cause uncertainty in estimating N and S deposition. Oxides of nitrogen and oxides
of sulfur occur in the atmosphere with a variety of other gases and particles, which
together undergo complex chemical and physical interactions to form transformation
products (Section 2.3). Particulate matter originates from a variety of anthropogenic
stationary and mobile sources, as well as from natural sources. Particles may be emitted
directly, or formed in the atmosphere by transformations of gaseous emissions such as
SO2, NOx, ammonia (NH3), and volatile organic compounds (VOC). The chemical and
physical properties of PM vary greatly with time, region, meteorology, and source
category. Details regarding the emissions, formation, composition, and deposition of
particulate matter are described in the 2009 ISA for Particulate Matter (U.S. EPA.
2009a).
Emissions of SO2, NO, and NO2 have declined dramatically since the passage of the
Clean Air Act amendments in 1990 (Section 2.8); these compounds are the main
precursors forming sulfuric acid (H2SO4) and nitric acid (HNO3), which acidify
precipitation. As detailed in the 2016 NOx Health ISA (U.S. EPA. 2016b). NOx
emissions in the U.S. from highway vehicles and fuel combustions declined 49% between
1990 and 2013, while nationwide annual average NO2 concentrations decreased by 48%
from 1990 to 2012. Total emissions of SO2 decreased by 72% in the 1990 to 2011 period
(U.S. EPA. 2016a).
Transfer of nitrate (NO3 ) and SO42 from the air to the surface by wet deposition in
precipitation and by dry deposition (i.e., transfer of species from the air to the surface by
atmospheric turbulence) has declined substantially in the eastern U.S (Section 2.8.3).
However, the declines in the deposition of N as NO3 (Figure A-5) have been largely
offset by increases in deposition of NH4+, mainly in the central U.S. and in smaller areas,
which have increased fertilizer use and livestock-related emissions (Figure 2-28. Figure
A-14. Figure A-15).
Over a third of the U.S. receives over 10 kg N/ha/yr wet + dry deposition, with some
areas (such as the San Joaquin Valley, CA; Logan, UT; northern Iowa; eastern North
Carolina) receiving more than 15 kg N/ha/yr (Figure 2-21). The spatial extent of areas
with substantial deposition and the overall amount of N deposited are likely
underestimated because reduced organic N species (Section 2.3.2) are not included in
these estimates. Although declines in sulfur deposition have been most pronounced in the
Northeast, parts of Ohio, Pennsylvania, and West Virginia still receive deposition of S
ranging between 15 and 20 kg S/ha/yr (Figure 2-25).
In addition to representing deposition of N and S as a mass flux, their deposition can also
be combined to give total acid deposition expressed in units of H+ equivalents (eq;
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Section 2.8). Total (wet + dry) deposition fluxes of N + S as H+ eq ranged from a few
hundred H+ eq/ha/yr over much of the western U.S. to over 1,500 H+ equivalents/ha/yr in
a broad swath encompassing the Midwest and the Mid-Atlantic regions (Figure 1-4).
High acid deposition rates (> -1,500 H+ eq/ha/yr) are also found in smaller areas
dominated by high emissions of NH3, presumably due to agricultural activities, such as
eastern North Carolina; Logan, UT; and the San Joaquin Valley, CA. Large urban areas
such as Los Angeles, CA experience high rates. Areas like northern New England are
affected by rates roughly one-third or less of those found in areas of high acid deposition.
These rates should be examined with the understanding that rates and patterns of
deposition are continually changing due to ongoing implementation of control measures
and shifting patterns of population growth, industrial activity, and agricultural activities.
Estimates of total deposition are based on the fusion of measurements from the National
Atmospheric Deposition Program National Trends Network monitoring sites and
chemical-transport model (CTM) estimates for dry deposition (Section 2.8). The limited
number of monitoring sites in many locations across the country results in gaps in data
for deposition in a large number of potentially sensitive areas. CTMs help fill in these
data gaps and suggest that local and even regional areas of high ambient concentration
and deposition exist where measurements are unavailable, as in the central U.S. and other
areas where there is extensive agricultural activity. CTMs consider interactions among
pollutants, their transport and transformations, resulting atmospheric concentrations, and
deposition to the surface. Although considerable progress has been made in the
development of CTMs, they are still subject to considerable uncertainty in their treatment
of major physical and chemical processes determining the transport, transformations, and
fate of atmospheric pollutants.
National-scale networks routinely monitoring ambient concentrations and deposition of N
do not measure or fully characterize all the chemical species of reduced and oxidized N
that contribute to N deposition (Section 2.5). Substantial uncertainty also exists in the
ability of current models to determine rates of dry deposition and to characterize the
spatial variability in dry deposition across the U.S. (Section 2.7).
Ecological Effects
It is clear that current atmospheric concentrations of NOy, SOx, and PM contribute to N
and S deposition, which cause declines in biodiversity in many ecosystems in the U.S.
Declines in biodiversity mean that some species become relatively less abundant and may
be locally extirpated. The current period in Earth's history is the Anthropocene. A
defining attribute of the Anthropocene is global human-driven mass extinctions of
species. The biodiversity loss reported in this assessment contributes to the Anthropocene
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loss of biodiversity. In addition to the loss of unique living species, the decline in total
biodiversity is harmful because biodiversity is an important determinant of the stability of
ecosystems and the ability of ecosystems to provide services to humanity.
In this ISA, information on ecological effects from controlled exposure studies, field
addition studies, gradient studies, and toxicological studies are integrated to form
conclusions about the causal nature of relationships between NOy, SOx, and PM related
to N and S deposition and ecological effects. Ecological effects are considered in relation
to a range of ambient concentration and deposition loads that are within one to two orders
of magnitude of current conditions [Preamble (U.S. EPA. 20156). Section 5c]. A
consistent and transparent framework [Preamble (U.S. EPA. 2015e). Table II] is applied
to classify the ecological effects evidence according to a five-level hierarchy:
1. Causal relationship
2. Likely to be a causal relationship
3. Suggestive of, but not sufficient to infer, a causal relationship
4. Inadequate to infer a causal relationship
5. Not likely to be a causal relationship
The conclusions presented in Table ES-1 are informed by recent findings integrated with
information from the 2008 ISA (U.S. EPA. 2008a). Important considerations include
judgments of error and uncertainty, as well as the coherence of findings integrated across
studies underlying geochemical and biological mechanisms. There are 19 causality
statements in this ISA. Fourteen are causal relationships repeated from the 2008 ISA or
modified from the 2008 ISA to include specific endpoints. Five are new endpoint
categories not evaluated in the 2008 ISA: three with causal relationships, one with a
likely causal relationship, and one suggestive of a causal relationship.
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Table ES-1 Causal determinations for relationships between criteria pollutants
and ecological effects from the 2008 and current draft Integrated
Science Assessment.
Causal Determination
Effect Category
2008 ISA
Current Draft ISA
Gas-Phase Direct Phototoxic Effects
Gas-phase SO2 and injury to vegetation
Causal relationship
Causal relationship
Section 3.5.1
Gas-phase NO, NO2, and PAN and injury to vegetation
Causal relationship
Causal relationship
Section 3.5.2
Gas-phase HNO3 and injury to vegetation3
Causal relationship
Causal relationship
Section 3.5.3
N and Acidifying Deposition to Terrestrial Ecosystems
N and S deposition and alteration of soil biogeochemistry
in terrestrial ecosystems3
Causal relationship
Causal relationship
Section 4J.
N deposition and the alteration of the physiology and
growth of terrestrial organisms and the productivity of
terrestrial ecosystems'5
Not included
Causal relationship
Section 6.1.7
N deposition and the alteration of species richness,
community composition, and biodiversity in terrestrial
ecosystems'5
Causal relationship
Causal relationship
Section 6.2.8
Acidifying N and S deposition and the alteration of the
physiology and growth of terrestrial organisms and the
productivity of terrestrial ecosystems0
Not included
Causal relationship
Section 5.6.1
Acidifying N and S deposition and the alteration of species
richness, community composition, and biodiversity in
terrestrial ecosystemsd
Causal relationship
Causal relationship
Section 5.6.2
N and Acidifying Deposition to Freshwater Ecosystems
N and S deposition and alteration of freshwater
biogeochemistrye
Causal relationship
Causal relationship
Section 7.4.1
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Table ES-1 (Continued): Causal determinations for relationships between criteria
pollutants and ecological effects from the 2008 and
current draft Integrated Science Assessment.
Causal Determination
Effect Category
2008 ISA
Current Draft ISA
Acidifying N and S deposition and changes in biota
including physiological impairment and lateration of
species richness, community composition, and
biodiversity in freshwater ecosystems'
Section 8,6
Causal relationship
Causal relationship
N deposition and changes in biota including altered
growth, species richness, community composition, and
biodiversity due to N enrichment in freshwater
ecosystems9
Section 9J3
Causal relationship
Causal relationship
N Deposition to Aquatic Estuarine Ecosystems
N deposition and alteration of biogeochemistry in
estuarine and near-coastal marine systems
Section 7.4.2
Causal relationship
Causal relationship
N deposition and increased nutrient-enhanced coastal
acidification
Section 7.4.2
Not included
Likely to be a causal
relationship
N deposition and changes in biota including altered
growth, species richness, community composition, and
biodiversity due to N enrichment in estuarine
environments11
Section 10.8
Causal relationship
Causal relationship
N deposition and changes in biota including altered
physiology, species richness, community composition,
and biodiversity due to nutrient-enhanced coastal
acidification
Section 10.8.2
Not included
Suggestive of a causal
relationship
N Deposition to Wetland Ecosystems
N deposition and the alteration of biogeochemical cycling
in wetlands
Section 11.10.1
Causal relationship
Causal relationship
N deposition and the alteration of species physiology,
species richness, community composition, and
biodiversity in wetlands
Section 11.10.1
Causal relationship
Causal relationship
S Deposition to Freshwater and Wetland Ecosystems
S deposition and increased methylation of Hg in wetland
and aquatic ecosystems where the value of other factors
is within adequate range for methylation'
Causal relationship
Causal relationship
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Table ES-1 (Continued): Causal determinations for relationships between criteria
pollutants and ecological effects from the 2008 and
current draft Integrated Science Assessment.
Causal Determination
Effect Category
2008 ISA Current Draft ISA
Section 12.9
S deposition and changes in biota due to sulfide Not included Causal relationship
phytotoxicity including alteration of species physiology,
species richness, community composition, and
biodiversity in wetland ecosystems
Section 12.9.3
Hg = mercury; HN03 = nitric acid; ISA = Integrated Science Assessment; N = nitrogen; NO = nitric oxide; N02 = nitrogen dioxide;
PAN = peroxyacetyl nitrate; S = sulfur; S02 = sulfur dioxide
aThe 2008 ISA causality statements for gas phase HN03 was phrased as, "changes in vegetation."
bThe 2008 ISA included two causality statements for terrestrial biogeochemistry phrased as, "relationship between acidifying
deposition and changes in biogeochemistry" and "relationship between N deposition and the alteration of biogeochemical cycling
of N."
The 2008 ISA causality statement for biological effects of N enrichment in terrestrial ecosystems was phrased as, "relationship
between N deposition and the alteration of species richness, species composition and biodiversity."
dThe 2008 ISA causality statement for biological effects of acidifying deposition in terrestrial ecosystems was phrased as,
"relationship between acidifying deposition and changes in terrestrial biota."
eThe 2008 ISA included three causality statements for freshwater biogeochemistry phrased as, "relationship between acidifying
deposition and changes in biogeochemistry related to aquatic ecosystems," "relationship between N deposition and the alteration
of biogeochemical cycling of N," and "relationship between N deposition and the alteration of biogeochemical cycling of C."
'The 2008 ISA causality statement for biological effects of acidifying deposition in freshwater ecosystems was phrased as,
"relationship between acidifying deposition and changes in aquatic biota."
9The 2008 ISA causality statement for biological effects of N deposition in freshwater ecosystems was phrased as, "relationship
between N deposition and the alteration of species richness, species composition and biodiversity in freshwater aquatic
ecosystems."
hThe 2008 ISA causality statement for biological effects of N deposition to estuaries was phrased as, "relationship between N
deposition and the alteration of species richness, species composition and biodiversity in estuarine ecosystems."
'The 2008 ISA causality statement for biological effects of S deposition effects on ecosystems was phrased as, "relationship
between S deposition and increased methylation of Hg, in aquatic environments where the value of other factors is within
adequate range for methylation."
Gas-Phase Direct Phytotoxic Effects
New evidence supports the causal determinations made in the 2008 ISA regarding gas-
phase effects on vegetation and there are no new causal statements for gas-phase effects
As in the 2008 ISA, the current ISA concludes that there are causal relationships between
SO2, NO2, NO, peroxyacetyl nitrate (PAN), HNO3, and injury to vegetation (Table ES-l).
This determination is based on consistent, coherent, and biologically plausible evidence
that acute and chronic exposures to SO2 have phytotoxic effects on vegetation, which
include foliar injury, decreased photosynthesis, and decreased growth (Section 3.2).
Acute exposures to NO2, NO, PAN, and HNO3 cause foliar injury and decreased growth
(Sections 33 and 3.4). Studies also indicate that HNO3 pollution in southern California
may have contributed to the local extirpation of a lichen species. The clearest evidence
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for these conclusions across pollutants comes from studies available at the time of the
2008 ISA. There have been some additional studies since the 2008 ISA, particularly on
the recovery of tree growth with decreasing SO2 emissions and additional studies on
HNO3 effects on vegetation in southern California, that are consistent with earlier studies.
The majority of evidence on the direct effects of gaseous NOy and SOx comes from
controlled exposure studies across many species of vegetation. Additionally, there is a
smaller base of evidence from the field studies using data on pollutant changes over time
and space. The majority of controlled exposure studies over the past several decades used
concentrations of gas-phase NOy and SOx above current ambient conditions observed in
the U.S. Relevant information is lacking on exposures and effects reflecting the more
recent lower pollutant conditions. Therefore, little evidence is available to inform
whether current monitored concentrations of gas-phase NOy and SOx are high enough to
injure vegetation.
Nitrogen and Sulfur Deposition: Terrestrial Ecosystems
For terrestrial ecoystems, new evidence reinforces causal findings from the 2008 ISA and
provides the basis for two new causal statements that reflect a more comprehensive
understanding of how N and acidifying deposition alter terrestrial ecosystems (Table ES-
1). As in the 2008 ISA, the current ISA concludes that N and acidifying deposition alter
terrestrial soil biogeochemistry, causing soil N enrichment and/or soil acidification. As in
the 2008 ISA, the current ISA concludes that the biological effects of N enrichment
caused by N deposition alters species richness, community composition, and biodiversity
in terrestrial ecosystems. New causal statemements have been added to reflect the
evidence base for effects of N deposition on physiology and growth of terrestrial
organisms, and the productivity of terrestrial ecosystems.. For acidification, new studies
since the 2008 ISA indicate that there remain widespread areas of ongoing acidification
in forest soils in the northeastern U.S., despite recent decreases in acid deposition and the
recovery of some surface waters. In the 2008 ISA, the causality statement for the
biological effects of acidifying deposition was "effects on biota." The current ISA
specifies these effects with more detail to reflect the breadth of available evidence. The
new causality determinations state causal relationships between acidifying deposition and
the alteration of the physiology and growth of terrestrial organisms, the productivity of
terrestrial ecosystems, species richness, community composition, and biodiversity.
Soil Biogeochemistry
The atmospheric deposition of N and S onto terrestrial ecosystems can cause both soil
nutrient enrichment and soil acidification. Soil acidification is a natural process that can
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be accelerated by atmospheric deposition (Section 4.3). Where acidifying inputs exceed
the supply of base cations supplied via atmospheric deposition and soil weathering, the
pool of base cations such as calcium (Ca2+) and magnesium (Mg2+) is depleted and
becomes increasingly dominated by hydrogen (H+) and aluminum (Al3+). These shifts
alter soil biogeochemistry and can change water chemistry in receiving water bodies
(Chapter 7). Deposition of HNO3 and H2SO4 directly acidifies soils, but deposition of
reduced forms of N (e.g., NHx) can also cause soil acidification by stimulating
nitrification. A number of soil geochemical processes and indicators are associated with
soil acidification (Table 4-12). There are several widely used biogeochemical models for
predicting soil acidification. Data recently published by the U.S. Geological Survey allow
for some soil acidification models to be applied across broader geographic regions
(Section 4.5).
Nitrogen enrichment is indicated by some of the same soil processes and chemical
indicators associated with acidification (Table 4-12). In the process of N enrichment, the
added N often accumulates in the soil, altering microbial transformation of N and
resulting in increased rates of nitrification and denitrification and altered rates of
decomposition. The accumulation of deposited N in the soil continues until biotic and
abiotic uptake processes are kinetically saturated, at which point the surplus N leaches as
N03 into adjacent waters. Much of the new work since 2008 focuses on the effects of N
deposition, with comparatively less new research on S deposition. There is new
information to better characterize soil pools and microbial transformations of N via
mineralization, nitrification, and denitrification (Section 4.3. Table 1-1. Table 4- 12V
New molecular ecology and ecophysiological research has provided a more mechanistic
understanding of how added N alters belowground C cycling (Section 4.3V Since 2008,
biogeochemical models used to evaluate responses to deposition have improved, with
most of these models applicable at watershed scales.
Soil nitrogen enrichment and soil acidification occur in sensitive ecosystems across the
U.S. at present levels of deposition. Ecosystem vulnerability to N accumulation in soils
caused by N deposition is ubiquitous across the U.S. (Section 4.6.2.2 and Table 4- 12V
Total N deposition rates are relatively unchanged across much of the contiguous U.S.
(CONUS; Section 1.2.3V there is no available evidence of recovery from N enrichment.
Soil vulnerability to acidifying deposition depends on local geology; high-elevation areas
are more vulnerable to acidification, especially in the eastern U.S where there have been
higher levels of deposition during the last century (Section 4J) and Figure 4-10).
Decreasing SOx emissions have led to early signs of recovery from acidification in some
northeastern watersheds; however watersheds in the Southeast do not yet show signs of
decreased acidification despite lower S emissions.
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Biological Effects
The changes in soil biogeochemistry caused by atmospheric deposition have
consequences for biological processes in terrestrial ecosystems because N and base
cations such as Ca2+ and Mg2+ are essential nutrients for plants and other organisms,
while A1 and acidity can be toxic (Section 5.1. Section 6.2). These changes in soil
biogeochemistry alter physiological processes and growth, with effects that differ among
species (Section 5.2. Section 6.2.1V Ultimately, these species-specific responses to N and
acidifying deposition change interactions between species, leading to altered community
composition and biodiversity of terrestrial communities (Section 5.2. Section 6.2.2V
Individual chemical forms of reactive N can have different effects on biogeochemical
processes such as soil N leaching and denitrification, but most terrestrial biological
processes appear to respond similarly to various forms of N (Section 6.2.1). Notably,
there is new national-scale evidence of interaction between acidification and N deposition
wherein soil pH modulates the effect of N deposition on plant species richness
(Section 6.3).
The effects of N deposition on growth, physiology, and biodiversity have been
consistently documented in terrestrial ecoregions across the U.S. for hundreds of species,
including plants, microorganisms, and organisms at higher trophic levels. New
information since the 2008 ISA further strengthens and quantifies these effects. Epiphytic
lichens and mycorrhizae (a plant-fungal symbiosis at the tips of plant roots) are the
organisms that are most sensitive to atmospheric N deposition and acidifying deposition.
Lichen physiology, abundance, and community composition have been documented to
change in response to atmospheric N deposition rates as low as 1 kg N/ha/yr (Section
6.4.2) and S deposition rates as low as 7 kg S/ha/yr (Section 5.5). Although lichens
typically are only a small portion of terrestrial vegetation biomass, these changes in
lichen communities are meaningful because lichens provide food and habitat for insects,
birds, and mammals; contribute to nutrient and hydrologic cycling; have many traditional
human uses; and have considerable potential for pharmaceutical use (Section 6.2.7).
Changes in the community composition of mycorrhizal fungi and declines in mycorrhizal
abundance have been observed in the U.S. at rates of atmospheric N deposition of 5-10
kg N/ha/yr (Section 6.4.1). These fungi are important for supplying nutrients to plants,
controlling soil C sequestration, and producing fruiting bodies (mushrooms) used by
humans and wildlife.
Nitrogen deposition and acidifying deposition alter the physiology of vascular plants
(e.g., grasses, shrubs, and trees). There is new information since the 2008 ISA further
strengthening and quantifying these effects. The accumulation of N in the soil increases
the availability of N, a nutrient that is in short supply for plants in most ecosystems
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(Section 6.2.1). Overall, meta-analyses have observed that N additions increase
ecosystem-level plant productivity by 20-30% in grasslands, forests, tundra, and
wetlands (Section 6.2.1). The physiological effects of acidification inhibit growth and
decrease plant health. Acidifying deposition can decrease membrane stability and
freezing tolerance in young red spruce needles. For many species, Ca depletion from the
soil and A1 mobilization cause decreased root uptake of Ca and disrupt fine root
physiological functions. Reduced availability of cations in the soil can also make trees
more vulnerable to other stresses, such as damage from insects and other pathogens.
The effects of N deposition and acidifying deposition on tree growth are well
documented. In new analyses in the northeastern U.S. and western Europe, N deposition
has been correlated with increases in aboveground tree growth for most tree species.
These observations of increased tree growth in forest inventories, combined with
observations of greater soil C storage, are consistent with evidence from other types of
research studies that N deposition increases ecosystem C storage in temperate and boreal
forests (Section 6.1.3.4). However, N deposition can decrease growth and increase
mortality in some tree species, particularly conifers. Within the eastern U.S., the
physiological effects of acidifying deposition have been well documented for several tree
species (Section 5.2). particularly sugar maple (Acer saccharum), red spruce (Picea
rubens), and to a lesser extent, flowering dogwood (Cornus florida). Evidence available
before and since the 2008 ISA show that there is consistent and coherent evidence among
these species that soil acidification and base cation depletion can decrease foliar cold
tolerance, increase rates of crown dieback, decrease tree growth, suppress seedling
regeneration, and increase mortality rates. Studies since the 2008 ISA in the northeastern
U.S. have shown that Ca addition can alleviate many of these effects.
The effects of N deposition and acidifying deposition on grass and forb growth and
species diversity are well documented for both open-canopy ecosystems (grasslands,
tundra, etc.) and in forest understory plant communities. Acidifying deposition has been
linked to changes in forest understory plant community composition in the northeastern
U.S., grass and forb biodiversity in eight ecoregions across the U.S., and decreased
grassland plant species richness in Europe.
The factors that govern the vulnerability of terrestrial ecosystems across the landscape to
nutrient enrichment from N deposition include the degree of N limitation, historical rate
ofN deposition, current rate ofN deposition, elevation, species composition, length of
growing season, and soil N retention capacity. At the time of the 2008 ISA, relatively
little research was available on critical load (CL) thresholds for biological effects
resulting from N deposition (Section 6.4). However, numerous CL studies have been
published since 2008 for a variety of ecosystems and biota, including a national-scale
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synthesis published by the U.S. Department of Agriculture's Forest Service. Among U.S.
ecoregions, CLs for changes in composition or abundance range from 1.5-9 kg N/ha/yr
for lichens, 5-12 kg N/ha/yr for mycorrhizal fungi, 4-33 kg N/ha/yr for herbaceous
plants and shrubs, and 3-26 kg N/ha/yr for forests (Table 6-28. Figure I -6).
CLs are deposition thresholds for the onset of ecological change. Across regions, critical
loads are higher where N deposition rates are higher because current conditions represent
a change from more pristine historical conditions. Alpine ecosystems in the western U.S.
are among the most sensitive ecosystems to atmospheric N deposition (Section 6.2.3).
Alpine ecosystems in the Colorado Front Range (Section CA), Sierra Nevada
(Section C.5). Cascades, and northern Utah receive N deposition from adjacent urban and
agricultural centers. Changes in plant and microbial community composition in alpine
ecosystems have been documented in response to N deposition. Likewise, there is
widespread evidence that N deposition has dramatically altered some semiarid and arid
ecosystems, such as those in southern California (Section 6.1.6; Section 6.2.6). Within
these dry-land systems, N deposition promotes the growth of exotic annual plants and
creates a more continuous fuel bed that allows wildfires to spread more easily. Because
the native plant species are not adapted to frequent wildfires, this change has dramatically
altered plant communities in some areas. The dramatic shifts in vegetation are of
particular concern in coastal sage-scrub and chaparral ecosystems in southern California.
These ecosystems are hotspots for biodiversity, have restricted spatial distributions, and
are also threatened by land use change.
Terrestrial areas most sensitive to effects from acidifying deposition include montane
forests in the Northeast, New England, and the central and southern Appalachians
(Section 5.3). Despite decreases in acid deposition, there continues to be evidence that
acidification of forest soils is ongoing across much of the northeastern U.S. New CL
estimates for acidification are reported for some sensitive areas of the U.S.
Nitrogen and Acidifying Deposition: Freshwater
For freshwater systems, new evidence reinforces causal findings from the 2008 ISA
(Table ES-1). New evidence also expands the scope of exisiting causal findings to
include additional biota affected by N enrichment and acidifying deposition, and supports
quantification of these effects with new critical loads. As in the 2008 ISA, the current
ISA concludes that there is a causal relationship between N and S deposition and the
alteration of freshwater biogeochemistry. Deposition of N and S alters aquatic
biogeochemistry through either N nutrient enrichment or acidification. Nutrient
enrichment of freshwater systems can cause eutrophication, a process of increased growth
of algae and other primary producers that decreases water clarity and sometimes also
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causes low dissolved oxygen (DO) concentrations. Increased acidity of surface waters
may occur in response to deposition of N, S, or both N and S. Freshwater N enrichment
and acidification occur in sensitive ecosystems across the U.S. at present levels of
deposition. For the biological effects of N enrichment, the 2008 ISA concluded there is a
causal relationship between N deposition and species richness, species composition, and
biodiversity. The current causal statement has been expanded to incorporate effects of N
on growth of primary producers. In acidified waters, consistent and coherent evidence
from multiple studies spanning several decades shows that changes in surface water
chemistry can cause the loss of acid-sensitive species. The 2008 ISA concluded there is a
causal relationship between acidifying deposition and changes in freshwater biota. The
current causal statement has been expanded to include specific endpoints of physiological
impairment, and alteration of species richness, community composition, and biodiversity.
Chemical recovery corresponding to decreased acidifying deposition, especially S
deposition, has been observed in some previously acidified water bodies, while evidence
for biological recovery is limited.
Aquatic Biogeochemistry
Deposition of N and S to watersheds influences freshwater biogeochemistry, either by
direct deposition to the water surface or by transport from terrestrial ecosystems via
runoff or leaching. Nitrogen enrichment/eutrophication and acidification are two
biogeochemical processes that can occur in freshwater as a result of atmospheric
deposition. The N added to streams, lakes, and rivers increases the productivity of algae
and/or aquatic plants. Deposition of N, S, or N + S can increase the acidity of surface
waters. At the time of the 2008 ISA, it was known that N deposition can alter the pools
and fluxes of the C, N, and phosphorus (P) cycles, particularly nitrification and
denitrification. Deposition of S directly adds SO42 to soil leachate and surface waters,
increasing acidity. The extent of N enrichment/eutrophication and acidification can be
described by changes in chemical indicators (Section 7.2). Surface water NO3
concentration can indicate both eutrophication and acidification. Water pH, acid
neutralizing capacity (ANC), and the concentrations of SO42 . inorganic Al, and base
cations are indicators of acidification. These processes and chemical indicators were well
characterized at the time of the 2008 ISA, and newer studies have further described and
quantified some of these relationships.
At the time of the 2008 ISA, N in excess of ecosystem requirements was known to alter
biogeochemical processes and nutrient ratios in receiving water bodies. The contribution
of N deposition to total N loading varies among freshwater systems. Atmospheric
deposition is the main source of new N to most headwater streams, high-elevation lakes,
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and low-order streams far from the influence of other N sources such as agricultural
runoff and wastewater effluent. The productivity of many freshwater systems is N
limited. Thus, even small amounts of N can shift nutrient ratios and affect the trophic
status of lakes and streams. Many new studies have addressed the relative importance of
N versus P loading in controlling eutrophication processes. It was well understood at the
time of the 2008 ISA that headwater streams play a disproportionately large role in N
transformation and N cycling and that streams can transform nutrients, store nutrients for
the short term, or serve as a sink for N loss from the watershed. As reported in the 2008
ISA and newer studies, a shift from N limitation, to either colimitation by N and P or
limitation by P has been observed in some alpine lakes in the U.S. and other countries,
with these shifts correlated with elevated N deposition.
Acid-sensitive freshwater systems can either be chronically acidified or subject to
occasional episodes of decreased pH and ANC and increased inorganic A1 concentration.
Episodic acidification is associated with precipitation or snowmelt events that transport
accumulated deposition from soils or snowpack to water bodies. Long-term monitoring of
lakes and streams shows some recovery of surface water chemistry with decreasing
deposition, especially in the northeastern U.S. Surface water SO42 has generally declined
in response to decreasing SOx deposition, while lake and stream pH and ANC values
have shown modest increases in some acid-sensitive lakes and streams throughout the
eastern U.S, indicating some chemical recovery in these systems. In most regions, the
rate of decrease for base cations have been similar to decreases in SO42 plus NO.? . with
the exception of streams in western Virginia and in the Shenandoah National Park, which
are strongly affected by SO42 adsorption on soils.
Models of acidification and eutrophication have been widely applied to lakes, rivers, and
streams (Section 7.2) to characterize biogeochemical change attributed to deposition.
Most available models reviewed in the 2008 ISA considered effects of N or N + S
deposition at the watershed scale. Since the 2008 ISA, additional models have been
developed including those applied at the regional spatial scale.
Biological Effects
Biological effects in freshwaters attributed to N and S deposition include changes in
essential nutrient ratios and toxic effects of altered surface water chemistry. To the extent
that N is the growth-limiting nutrient, N deposition can stimulate growth of primary
producers, which in turn may alter algal species assemblages and cause eutrophication of
aquatic ecosystems. In remote nutrient-poor lakes and streams where atmospheric
deposition is the dominant source of N, even small inputs of N can increase nutrient
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availability or alter the balance ofN and P. Biological indicators ofN enrichment include
chlorophyll a, phytoplankton (free-floating algae) biomass, periphyton (algae attached to
a substrate) biomass, diatoms (major algal group with cell walls made of silica), and
trophic status indices (Section 9.2).
As reported in the 2008 ISA and further strengthened with new evidence in this review,
there is consistent and coherent evidence that increased N availability can change species
composition and reduce biodiversity, especially for primary producers from
high-elevation lakes in the western U.S. (Section 9.3). The taxonomic groups most
affected by increased nutrient inputs are phytoplankton (Section 9.3). Diatom species
such as Asterionella formosa and Fragilaria crotonensis generally prefer high
concentrations ofN and are used as indicators of diatom assemblage shifts. Biological
responses to N enrichment from atmospheric deposition at higher trophic levels have not
been as thoroughly researched in remote freshwater systems as those of primary
producers; however, atmospheric N can potentially alter food web interactions and
contribute to invertebrate declines.
Changes in biota due to acidification from N and S deposition have been described for
several decades and are linked to changes in surface water chemistry, including
concentrations of SO42 , NO3 . inorganic Al, Ca2+, pH, sum of base cations, ANC, and
base cation surplus. Low pH and ANC and elevated inorganic Al concentration are
commonly used indicators of biological response in chronically or episodically acidified
waters. Observations reported in the 2008 ISA and recent research show consistent and
coherent evidence of toxic effects associated with acidity in freshwater organisms
including algae, zooplankton, benthic invertebrates, and fish (Section 8.3). Possible
mechanisms for zooplankton sensitivity to low pH and ANC include ion regulation
failure, decreased oxygen uptake, inability to reproduce, and inorganic Al toxicity. In
invertebrates, H+ and Al can be directly toxic, causing disruption of ion regulation and
reduced reproductive success. Further characterization of physiological responses (ion
regulation, stress responses, gill Al accumulation) to acidification in fish
(Section 8.3.6.1). mostly trout and other salmonids, adds to the existing information on
sublethal effects on individual fish species. Many of the newer studies are conducted
in situ and report varying sensitivity of different lifestages. These recent findings are
consistent with physiological alterations in fish and other organisms reported in the 2008
ISA.
There is consistent and coherent evidence from multiple studies of many aquatic species
that acidification of freshwaters can cause the loss of acid-sensitive species and that more
species are lost with greater acidification, which can lead to effects at higher levels of
biological organization. Effects of acidification on freshwater biodiversity are observed at
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virtually all trophic levels in sensitive ecosystems, and these responses have been well
characterized for several decades (Section 8.3V Biological effects of episodic
acidification may include fish kills, changes in species composition, and declines in
aquatic species richness across multiple taxa. Acid-sensitive species are often absent in
chronically acidified waters. Declines in zooplankton, macroinvertebrate, and fish species
richness are primarily attributable to low pH and high inorganic A1 concentration. Fish
populations in acidified lakes and streams in the U.S. have declined and some
populations have been eliminated as a result of acidifying deposition and the resulting
changes insurface water chemistry. Characterization of ANC and its levels of concern
have not changed appreciably with the newly available information. Few or no fish
species are found in lakes and streams that have very low ANC (near zero), and low pH
(near 5.0) and the number of fish species generally increases with higher ANC and pH
(Section 8.3). Although acidifying deposition, especially S deposition, is decreasing,
recent studies suggest biological recovery of previously acidified systems is limited
despite evidence for chemical recovery (Section 8.4). Modeling studies for these regions
indicate aquatic ecosystems may not be able to recover completely from the effects of
acidifying deposition under current and future deposition scenarios.
Regional sensitivity across U.S. freshwater systems is heterogeneous. Biological effects
of N nutrient enrichment from atmospheric deposition are most likely to occur in
high-elevation lakes, headwaters, and first-order streams with low primary productivity
and low nutrient levels located far from other pollution sources. Freshwater systems in
the U.S. sensitive to N nutrient enrichment include those in the Rocky Mountains and the
Sierra Nevada (Section 9.6). For acidification, many of the surface waters most sensitive
to acidification in the U.S. are found in the Northeast, the Southeast, and the mountainous
West (Section 8.5). In the West, acidic surface-waters are rare and are of limited extent to
date. Watershed sensitivity to acid inputs depends on characteristics such as underlying
geology (Chapter 4 and Chapter 7) and the sensitivity of species in the local biological
community. Regional heterogeneity in levels of deposition that causes effects are due, in
part, to historic exposure and climate. In the East, especially the southern Appalachian
Mountains and the Adirondacks, the effects of acidifying deposition have been studied
for several decades. Variation in ANC is associated with water constituents that
contribute to or ameliorate acidity-related stresses, in particular pH, Ca2+, and inorganic
A1 concentration. Areas with lower ANC (<100 |icq/L) across the U.S. are generally the
most sensitive to acidifying deposition (Figure 8-12).
Since the 2008 ISA, considerable critical loads research for acidifying deposition has
been conducted in the U.S. (Section 8.5). New empirical critical loads include
8 kg N/ha/yr in the Northeast and 4 kg N/ha/yr in the West for high elevation lakes. In
addition, modeled critical loads of N and S are available for several locations in the East
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and West. In many regions sensitive to either acidification or N enrichment, current
levels of atmospheric deposition generally exceed critical loads for many species of
concern. Modeled steady-state and dynamic critical loads and target loads for sensitive
regions of the U.S. including the Adirondacks, Smoky Mountains, and the Appalachians
show that biological and chemical recovery from acidification may not be attainable in all
water bodies.
As reported in the 2008 ISA, shifts in diatom community composition in the Rocky
Mountains have been observed at N deposition loads of approximately 1.5 to 2 kg
N/ha/yr. New critical loads from the western U.S. continue to report effects of N nutrient
enrichment within the range of 1.0 to 3.0 kg N/ha/yr (Section 9.7). A critical load ranging
from 3.5 to 6.0 kg N/ha/yr has been identified for high elevation lakes in the eastern U.S.
based on increases in NOs concentrations from N deposition.
Nitrogen Deposition: Estuarine
For estuaries, causal determinations from the 2008 ISA are further supported and
strengthened by additional studies, and there are two new causal statements on the
emerging topic of nutrient enhanced coastal acidification (Figure ES-1). As in the 2008
ISA, which reported effects of N deposition on biogeochemical cycling of both N and C,
the current ISA concludes that there is a causal relationship between N deposition and the
alteration of biogeochemistry in estuarine and near-coastal marine systems. In estuaries
(where freshwater from rivers meets the saltwater of the ocean), atmospheric deposition
typically constitutes less than half of the total N supply, although it can be higher in some
locations (Section 7.3). The additional N from atmospheric and nonatmospheric sources
may increase water N concentrations leading to alteration of biogeochemical processes
and N cycling. Seawater contains high concentrations of SO42 so atmospheric inputs of S
are unlikely to contribute substantially to biogeochemistry or biological effects in coastal
areas. Estuary eutrophication is indicated by water quality deterioration, including
development of hypoxic zones, species mortality, and formation of harmful algal blooms.
As in the 2008 ISA, the current ISA concludes that there is a causal relationship between
N deposition and species richness, community composition, and biodiversity due to N
enrichment in estuarine and near-coastal systems. The current causal statement also
includes altered growth as an additional effect of N loading in coastal environments.
For the new causal statements, N has been recognized as a possible contributing factor to
ocean water acidification because the CO2 produced by organic matter decomposition in
eutrophic waters can contribute CO2 to the water column, decreasing the pH. The current
ISA concludes there is a likely causal relationship between N deposition and increased
nutrient-enhanced coastal acidification. Evidence that organisms producing calcium
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carbonate shells are effected by increasing acidification of waters is suggestive of a
causal relationship between N deposition and changes in biota, including altered
physiology, species richness, community composition, and biodiversity in coastal waters
due to nutrient-enhanced coastal acidification.
Aquatic Biogeochemistry
Atmospheric N deposition to watersheds along with other sources of N affects
biogeochemistry along the freshwater-to-ocean continuum. In the previous 2008 ISA,
there was a strong scientific consensus that N is the principal cause of coastal
eutrophication in the U.S. Some of the key processes that influence N cycling in estuaries
and other coastal areas include hypoxia (low DO), nitrification, denitrification,
decomposition, and other sediment-associated processes (Section 7.3.2). The rate of
nutrient delivery, especially N, to coastal waters is strongly correlated to primary
production and phytoplankton biomass. The role of N inputs from upstream and the
connectivity between freshwater and receiving estuaries and coastal waters have led to
recommendations to decrease both N and P in upstream waters. The most widespread
chemical indicator of eutrophication in estuarine and marine ecosystems is DO.
Specifically, DO decreases as decomposition of organic matter associated with increased
algal abundance consumes DO. Areas of low DO (<2 mg/L) can become uninhabitable
for aquatic life (hypoxic zones). Coastal acidification may be exacerbated by eutrophic
conditions (Section 7.3.2.3). The largest zone of hypoxic coastal water in the U.S. is in
the northern Gulf of Mexico on the Louisiana-Texas continental shelf. Long Island Sound
and Chesapeake Bay also experience periodic low DO. In other U.S. coastal systems,
incidence of hypoxia is increasing; however, the severity of DO effects are variable and
relatively limited temporally and spatially.
Since the 2008 ISA, additional models and tools (Section 7.3) have been applied to assess
atmospheric contributions of N to estuaries, both from the landscape to the coastal zone
and direct inputs of N to the estuary surface from the atmosphere. Other models have
predicted coastal ecosystem responses to N loading. These have included studies that
focused primarily on N cycling, hypoxia, and harmful algal blooms. For coastal
acidification, models show that while the effect of each acidification pathway (N
enrichment and atmospheric CO2 dissolution) may be moderate, the combined effect of
the two may be much larger than would be expected from the simple additive effects of
each pathway.
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Biological Effects
Widely used biological indicators of N nutrient enrichment in estuaries include decreases
in the presence and extent of submerged aquatic vegetation, increases in chlorophyll a
concentration (measure of primary production), and increases in the occurrence and
abundance of algal blooms and macroalgae (Section 10.2 and Table 10-1). In general, the
growth of autotrophic species in estuaries are N limited; however, conditions are highly
variable in estuarine environments. Increased algal biomass associated with nutrient over
enrichment leads to increased decomposition of organic matter which decreases DO. Fish
and benthic invertebrates have reduced survival in hypoxic conditions. Macroalgal
growth may block sunlight and outcompete submerged aquatic vegetation. Release of
toxins during harmful algal blooms can affect aquatic biota and be transferred throughout
the food web. The combined effect of atmospheric CO2 and nutrient-enhanced coastal
acidification and hypoxia may exacerbate coastal acidification and affect organisms with
calcium carbonate shells such as oysters, clams, and coral. Decreased saturation rates of
aragonite and calcite, two minerals needed in shell formation, are observed in acidic
conditions.
In the current ISA, the role of nutrients and the form of N in algal bloom formation and
phytoplankton community dynamics has been further characterized, reinforcing the
causal determination from the 2008 ISA (Table ES-1). Increasing N enrichment can lead
to a cascade of biological effects including shifts in phytoplankton community
composition, and loss of biodiversity (Section 10.3). Macroinvertebrate community
structure and biodiversity is affected by duration and severity of hypoxia. Loss of
submerged aquatic vegetation affects other marine organisms that use the plants for
habitats and nursery grounds. In shallow estuaries in New England, markedly decreased
eelgrass coverage was observed at N loading rates (a portion of which is atmospheric)
above 100 kg N/ha/yr, and levels above 50 kg N/ha/yr were likely to affect habitat extent
(Section 10.2).
Regional sensitivity ofN enrichment varies across U.S. coastal areas (Section 10.6).
Factors that influence sensitivity to estuarine eutrophication include the flushing rate and
dilution capacity of the watershed, which reflect the volume of water available to dilute
added N, human population, agricultural production, and the size of the estuary relative to
its drainage basin. In the 2008 ISA, nearly two-thirds of the estuaries in the U.S. had
moderate-high to high eutrophic conditions and received relatively high N loads from
both atmospheric and nonatmospheric sources (Figure 10-8). In a national assessment of
estuarine eutrophication reported in the 2008 ISA, the most eutrophic estuaries in the
U.S. were in the mid-Atlantic region, and the estuaries with the lowest degree of
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eutrophication were in the North Atlantic. While seagrass coverage is improving in some
estuaries, such as Tampa Bay, many areas continue to see declines in seagrass extent.
Nitrogen Deposition: Wetlands
New evidence from wetlands, including new critical loads, supports and strengthens the
causal findings from the 2008 ISA (Table ES-1). As in the 2008 ISA, there is a causal
relationship between N deposition and the alteration of biogeochemical cycling in
wetlands. The body of evidence is sufficient to infer a causal relationship between N
deposition and the alteration of species physiology, species richness, community
composition, and biodiversity in wetlands. N deposition in North American wetlands
causes eutrophication. In the U.S., neither N nor S deposition have documented
acidification effects in wetlands because the levels of organic acidity are naturally high
from peat in permanent wetlands. S deposition effects in wetlands and freshwater aquatic
systems are addressed below, in the S deposition section.
Soil/Sediment Biogeochemistry
Indicators of altered biogeochemical cycling of N in wetlands include increases in NOs
leaching, denitrification rates, and emissions of nitrous oxide from wetland waters and
sediments (Section 11.3.1). Indicators of altered biogeochemical cycling of C in wetlands
include increases in methane and carbon dioxide emissions from wetland waters and
sediments (Section 11.3.2). Regional sensitivity of wetlands to N deposition is related to
the fraction of N deposition of total N loading. For example, freshwater wetlands
(particularly bogs and fens) are typically more sensitive because they receive a higher
fraction of their N supply from deposition than do downstream riparian, estuarine, and
coastal wetlands (Section 11.2). Biogeochemical critical loads have been established for
wetlands since the 2008 ISA. The critical load for freshwater wetlands based on
alterations to primary productivity and peat accumulation is between 2.7 and 13 kg
N/ha/yr. The critical load for coastal wetlands is based upon multiple endpoints,
including biogeochemistry, and is in the range of 63-400 kg N/ha/yr (Section 11.9).
Biological Effects
Wetlands provide habitat to a disproportionally high number of rare plants given they are
less common than terrestrial ecosystems in the landscape. Increasing N deposition can
alter plant community composition, decreasing the cover of N-sensitive species such as
mosses and insectivorous plants, while increasing the cover of N-tolerant species,
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including non-native invasive species. Most studies evaluate the effects of N addition
directly on plants/autotrophs, rather than linking the effects of deposition to a soil or
water indicator. N addition levels in studies are typically much higher than the loading
that would occur via N deposition. Indicators of altered biota in wetlands that occur at
addition levels close to current deposition rates in the U.S. primarily occur in bogs and
include changes in plant tissue nutrient concentrations (Section 11.5). decreases in plant
retention of nutrients (Section 11.5). changes in plant cover and relative abundance of
plant species (Section 11.8.1). and changes in plant reproduction and mortality
(Section 11.7). Biodiversity critical loads have been established for wetlands since the
2008 ISA. Critical loads for sustainable populations of pitcher plants in bogs are 6.8-14
kg N/ha/yr (Section 11.9). The critical load for coastal wetlands (63-400 kg N/ha/yr),
which are less sensitive to deposition because N deposition supplies only a fraction of
total N load, includes protection for biodiversity endpoints of plant community
composition and microbial activity.
Sulfur Deposition: Wetlands and Freshwater
New evidence from wetland and freshwater aquatic ecosystems strengthens and extends
the causal findings of the 2008 ISA regarding nonacidifying sulfur effects, and also
provides the basis for a new caual determination (Table ES-1). As in the 2008 ISA, the
evidence is sufficient to infer a causal relationship between S deposition and increased
methylation of Hg in wetland and aquatic ecosystems where the value of other factors is
within adequate range for methylation (Section 12.9.7). The evidence is sufficient to infer
a causal relationship between S deposition and changes in biota due to sulfide
phytotoxicity including alteration of species physiology, species richness, community
composition, and biodiversity in wetland ecosystems (Section 12.2.3). This new causal
statement reflects new research on sulfide phytotoxicity in North American wetlands, as
the 2008 ISA described sulfide phytoxicity only in European systems.
SOx deposition increases SO42 concentration in surface waters, which can stimulate the
microbial transformation of inorganic Hg into methylmercury (MeHg; Section 12.3.1).
MeHg is the most persistent and toxic form of Hg that affects animals in the natural
environment. Indicators of S deposition effects upon Hg methylation include increases in
MeHg concentrations or fraction of total Hg in water, sediments, and peat (Section 12.4).
as well as increases in MeHg concentrations in periphyton (Section 12.3.3). submerged
aquatic plants (Section 12.3.3). invertebrates (Section 12.7). and fish (Section 12.7). New
evidence confirms the relationship between aqueous concentrations of SO42 and MeHg,
and broadens our understanding of where methylation occurs from the wetlands and lakes
reported in the 2008 ISA to include rivers, reservoirs, and streams (Section 12.6). Hg
methylation occurs at anoxic-oxic boundaries in wetland and lake sediments, in peat
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moss, in periphyton, and in estuarine and marine sediments (Section 12.3). There are
published quantitative relationships between surface water SO42 concentrations and
MeHg concentrations in lakes, peatlands, and rivers. Results from empirical studies in
bogs indicate significant increases in concentrations of MeHg and total Hg in water, as
well as Hg load in larval mosquitoes, when S deposition increased in a range of 8.3 to
32 kg/ha/yr (Section 12.9). An empirical study across an S deposition gradient found
significant increases in largemouth bass Hg load when S deposition was 11.9 kg/ha/yr
(Section 12.5V Water quality thresholds of 1 mg SO42 /L have been proposed to protect
water quality and fish in the Florida Everglades (Section 12.9). There is also evidence
that decreasing sulfur deposition (observational studies of SOx deposition, experimental
studies of simulated SOx wet deposition) results in decreasing concentrations of MeHg in
water, invertebrates, and fish (Section 12.5).
Current levels of S deposition are causing sulfide toxicity in wetland plants. Indicators of
sulfide phytotoxicity caused by S deposition include increases in water or sediment
sulfide concentrations. Sulfide negatively effects growth, competition, and persistence in
several wetland species, including the economically important species wild rice, and the
keystone sawgrass species in the Everglades marshes (Section 12.2.3). The Minnesota
Pollution Control Agency has developed a model that calculates protective levels of
water SO42 concentrations given iron and DOC concentrations in water bodies. There are
no published studies that establish regional sensitivities to sulfide phytotoxicity, although
studies have observed its effects in New York, Minnesota, and Florida freshwater
marshes. Ambient sulfide concentrations are high in saltwater systems, and S deposition
is unlikely to alter sulfide phytotoxicity in these systems. There are no deposition-based
critical loads for sulfide phytotoxicity, although 0.165 mg sulfide/L has been proposed as
a water quality standard in Minnesota to protect wild rice populations (Section 12.2.3).
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CHAPTER 1
INTEGRATED SYNTHESIS
1.1 Introduction to this ISA
1.1.1 Purpose
The Integrated Science Assessment (ISA) is a comprehensive evaluation and synthesis of
the policy-relevant science "useful in indicating the kind and extent of all identifiable
effects on public health or welfare which may be expected from the presence of [a]
pollutant in the ambient air," as described in Section 108 of the Clean Air Act (CAA.
1990a).12 This ISA for Oxides of Nitrogen, Oxides of Sulfur, and Particulate
Matter—Ecological Criteria provides a comprehensive evaluation and synthesis of the
most policy-relevant science aimed at characterizing ecological effects caused by these
three criteria pollutants. Oxides of nitrogen, oxides of sulfur, and particulate matter (PM)
are reviewed here together because they are interrelated through complex chemical and
physical atmospheric processes and because they all contribute to nitrogen (N) and sulfur
(S) deposition, which in turn contributes to well-documented ecological effects. In this
document, the term "oxides of nitrogen" refers to all forms of oxidized nitrogen (N)
compounds, including NO, NO2, and all other oxidized N containing compounds formed
from NO and NO2.13 Oxides of sulfur14 are defined here to include sulfur monoxide (SO),
sulfur dioxide (SO2), sulfur trioxide (SO3), disulfur monoxide (S2O), and sulfate (SO42 ).
However, SO, SO3, and S2O are present at much lower ambient levels than SO2 and SO42
and are therefore not discussed further. Particulate matter is composed of some or all of
the following components: nitrate (NO3 ). SO42 . ammonium (NH4+), metals, minerals
(dust), and organic and elemental carbon (C).
This ISA communicates critical science judgments of the ecological criteria for oxides of
nitrogen, oxides of sulfur, and particulate matter. As such, this ISA serves as the
12The general process for developing an ISA, including the framework for evaluating weight of evidence and
drawing scientific conclusions and causal judgments, is described in a companion document, Preamble to the
Integrated Science Assessments (U.S. EPA. 2015e').
13 This ISA reserves the abbreviation NOx strictly as the sum of NO and NO2—consistent with its use in the
atmospheric science community—and uses the term "oxides of nitrogen" to refer to the broader list of oxidized
nitrogen species. Oxides of nitrogen refers to NOy as the total oxidized nitrogen in both gaseous and particulate
forms. The major gaseous and particulate constituents of NOy include nitric oxide (NO), nitrogen dioxide (NO2),
nitric acid (HNO3), peroxyacetyl nitrate (PAN), nitrous acid (HONO), organic nitrates, and particulate nitrate (NO3).
This ISA uses the definitions adopted by the atmospheric sciences community.
14 Oxides of sulfur refers to the criteria pollutant category.
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scientific foundation for the review of the ecological effects of the current secondary
(welfare-based) National Ambient Air Quality Standards (NAAQS) for oxides of
nitrogen, oxides of sulfur, and particulate matter. The human health effects for oxides of
nitrogen, oxides of sulfur, and particulate matter are evaluated in separate assessments
conducted as part of the review of the primary (human health-based) NAAQS for oxides
of nitrogen (U.S. EPA. 2016b). oxides of sulfur (U.S. EPA. 2016a). and particulate
matter (U.S. EP A. 2009a). The Clean Air Act definition of welfare effects includes, but is
not limited to, effects on soils, water, wildlife, vegetation, visibility, weather, and climate,
as well as effects on man-made materials, economic values, and personal comfort and
well-being. The nonecological welfare effects associated with particulate matter, such as
climate and visibility, are considered as part of a separate, ongoing review of PM that is
outlined in the "Integrated Review Plan for the National Ambient Air Quality Standards
for Particulate Matter (IRP)" (81 FR 87933, December 6, 2016).
This ISA updates the 2008 Integrated Science Assessment for Oxides of Nitrogen and
Sulfur—Ecological Criteria [hereafter referred to as the 2008 ISA (U.S. EPA. 2008a)l. as
well as the ecological portion of the Integrated Science Assessment for Particulate Matter
(U.S. EPA. 2009a'). with studies and reports published from January 2008 through
December 2015. Thus, this ISA updates the state of the science that was available for the
2008 ISA, which informed decisions on the secondary oxides of nitrogen and oxides of
sulfur NAAQS in the review completed in 2012. The Administrator signed a final
decision in this rulemaking on March 20, 2012. The Administrator's decision was that,
while the current secondary standards were inadequate to protect against adverse effects
from deposition of oxides of nitrogen and oxides of sulfur, it was not appropriate under
Section 109(b) to set any new secondary standards at this time due to the limitations in
the available data and uncertainty as to the amount of protection the metric developed in
the review would provide against acidification effects across the country (77 FR 20281).
In addition, the Administrator decided that it was appropriate to retain the current
nitrogen dioxide (NO2) and sulfur dioxide (SO2) secondary standards to address direct
effects of gaseous NO2 and SO2 on vegetation. Thus, taken together, the Administrator
decided to retain and not revise the current NO2 and SO2 secondary standards: an NO2
standard set at a level of 0.053 ppm, as an annual arithmetic average, and an SO2 standard
set at a level of 0.5 ppm, as a 3-hour average, not to be exceeded more than once per year
(77 FR 20281). The current secondary standards for PM are intended to address PM-
related visibility and non-visibility welfare effect. These standards are a 3-year annual
mean PM2 5 concentration of 15 (ig/m3, with the 24-hour average PM2 5 and PM10 set at
concentrations of 35 |ig /m3 and 150 |ig/m3. respectively.
This new review of the secondary oxides of nitrogen, oxides of sulfur, and particulate
matter NAAQS is guided by several policy-relevant questions that are identified in The
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Integrated Review Plan for the Secondary National Ambient Air Quality Standard for
Nitrogen Oxides, Sulfur Oxides, and Particulate Matter (U.S. EPA. 2016b). To address
these questions, this ISA aims to characterize the evidence for ecological effects
associated with total oxidized N (NOy), the major gaseous and particulate constituents of
NOy, including NO, NO2, HNO3, PAN, HONO, organic nitrates, and NO3 : SOx, the
major gaseous and particulate constituents of which are SO2 and SO42 : and PM by:
• Integrating findings across scientific disciplines and across related ecological
outcomes.
• Considering important uncertainties identified in the interpretation of the scientific
evidence, including the role of NOy, SOx, and PM contribution to N and S
deposition within the broader ambient mixture of pollutants.
• Assessing policy-relevant issues related to quantifying ecological risks, such as
ambient air concentrations, deposition, durations, and patterns associated with
ecological effects; the relationship between ambient air concentrations, deposition,
and ecological response and the existence of thresholds below which effects do
not occur; and species and populations potentially at increased risk of ecological
effects.
The information summarized in this ISA will serve as the scientific foundation for
assessing the current secondary oxides of nitrogen, oxides of sulfur, and particulate
matter NAAQS.
1.1.2 Process and Development
The U.S. EPA uses a structured and transparent process to evaluate scientific information
and determine the causality of relationships between air pollution and ecological effects
[see Preamble (U.S. EPA. 20156)1. The ISA development includes approaches for
literature searches, criteria for selecting and evaluating relevant studies, and a framework
for evaluating the weight of evidence and forming causal determinations. As part of this
process, the ISA is reviewed by the Clean Air Scientific Advisory Committee (CASAC),
which is a formal independent panel of scientific experts, and by the public. This ISA
informs the review of the secondary oxides of nitrogen, oxides of sulfur, and particulate
matter NAAQS. It therefore integrates and synthesizes information characterizing NOy,
SOx, and PM air concentrations and deposition, and relationships of these substances
with ecological effects. Relevant studies include those examining atmospheric chemistry,
spatial and temporal trends, and deposition, as well as U.S. EPA analyses of air quality
and emissions data. Relevant ecological research includes geochemistry, microbiology,
physiology, toxicology, population biology, and community ecology. The research
includes laboratory and field additions, as well as gradient studies.
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The U.S. EPA conducted literature searches to identify relevant peer-reviewed studies
published since the previous ISA (i.e., from January 2008 through December 2015;
Figure 1-1).
Excluded
(not relevant)
Considered
Manual screening
for pertinence
(title)
Manual screening for
pertinence
(abstract/full text)
Topic-specific
keyword searches
by authors
Cited in first draft of 2016 ISA
(availableon HERO project page)
References from 2008 ISA and other sources
2203 references
Relevant Literature for
each topic
43,000 references
Sorted by automated topic
classification of abstracts,
OR
Ranked based on numbers of
citations of 2008 ISA references
Keyword searches
OR
Citation searches
of Web of Science
for peer-reviewed papers
published 01/01/2008-12/31/2015
198,000 references
HERO = Health and Environmental Research Online; ISA = Integrated Science Assessment
Figure 1-1 Workflow for collecting relevant literature for the 2017 Integrated
Science Assessment for Oxides of Nitrogen, Oxides of Sulfur, and
Particulate Matter—Ecological Criteria
Multiple search methods were used in the Web of Science database [Preamble (U.S.
EPA. 2015e). Chapter 21. including searches by keyword and by citations of 2008 ISA
references. Subject-area experts and the public were also permitted to recommend studies
and reports during kick-off workshops held at the U.S. EPA in March 2014 for oxides of
nitrogen and oxides of sulfur and in February 2015 for particulate matter. The new
references were sorted by automated methods into topic areas based on wording in the
publication's abstract or numbers of citations of 2008 ISA references, and the resultant
relevant literature was reviewed by the ISA authors. Studies were screened based on the
title first and then by the abstract; studies that did not address a relevant research topic
based on this screening were excluded. The U.S. EPA also identified studies from
previous assessments as definitive works on particular topics to include in this ISA. The
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HERO project page for this ISA (http://hero. epa.gov/heronet/NOxSOxPMEco) contains
the references that are cited in the ISA and electronic links to bibliographic information
and abstracts.
The Preamble to the Integrated Science Assessments (U.S. EPA. 2015e) describes the
general framework for evaluating scientific information, including criteria for assessing
study quality and developing scientific conclusions. For ecological studies, emphasis is
placed on studies that characterize quantitative relationships between criteria pollutants
and ecological effects that occur at concentration and deposition levels relevant to current
levels in the U.S. However, experimental studies with higher exposure concentrations are
included if they contribute to an understanding of mechanisms.
This ISA draws conclusions about relationships between NOy, SOx, and PM and
ecological effects by integrating information across scientific disciplines and related
ecological outcomes and synthesizing evidence from previous and recent studies.
Determinations are made about causation, not just association, and are based on
judgments of consistency, coherence, and scientific plausibility of observed effects as
well as related uncertainties. The ISA uses a formal causal framework [Table II of the
Preamble (U.S. EPA. 2015eYI which is based largely on the aspects for causality
proposed by Sir Bradford Hill to classify the weight of evidence according to the
five-level hierarchy summarized below.
• Causal relationship
• Likely to be a causal relationship
• Suggestive of, but not sufficient to infer, a causal relationship
• Inadequate to infer the presence or absence of a causal relationship
• Not likely to be a causal relationship
1.1.3 Organization
This ISA includes the Preface (legislative requirements and history of the secondary
oxides of nitrogen, oxides of sulfur, and particulate matter NAAQS), Executive
Summary. 14 chapters, and 4 appendices. The general process for developing an ISA is
described in a companion document, Preamble to the Integrated Science Assessments
(U.S. EPA. 20156). Chapter 1 synthesizes the scientific evidence that best informs
policy-relevant questions that frame this review. Chapter 2 characterizes the sources,
atmospheric processes, and the trends in ambient concentrations and deposition of NOy,
SOx, and PM. Chapter 3 describes direct effects of NOy and SOx gases on plants and
lichens. Chapter 4-Chapter 6 describe N and S deposition effects on terrestrial
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biogeochemistry, and the terrestrial biological effects of terrestrial acidification and N
enrichment. Chapter 7 describes the effects of N and S deposition on aquatic
biogeochemistry. Chapter 8-Chapter 10 characterize the biological effects of freshwater
acidification, freshwater N enrichment, and N enrichment in estuaries and near-coastal
systems. Chapter 11 describes the effects of N deposition on wetlands, and Chapter 12
characterizes the ecological effects of S as a nutrient. Chapter 13 presents information on
ecosystem services, while the climate modification of ecosystem response to N is
discussed in Chapter 14. Additional supporting material is presented in the Appendices.
Appendix A provides maps of deposition to augment the information in Chapter 2. while
Appendix B provides additional information on mercury cycling that is introduced in
Chapter 12. The case studies are five locations in the U.S. (Southern California,
Northeastern U.S., Rocky Mountain National Park, Southeastern Appalachia, Tampa
Bay) where data are sufficient to well characterize the ecological effects of N and S
deposition. These sites would therefore make good candidates for further place-based risk
and exposure assessments (Appendix C). In addition, the ecological effects of forms of
PM, which are not related to N or S deposition, are included in Appendix D.
1.1.4 Main Findings
In this ISA, although scientific material is divided into separate chapters for atmospheric
science and the multiple ecological effects, there are strong links between the atmosphere
and terrestrial and aquatic systems (Figure 1-2). Emissions of NOy, SOx, and PM cause
an accumulation of N and S in the environment that creates a multitude of effects on
terrestrial, wetland, and aquatic ecosystems. Nitrogen is a vital component of all
biological systems, serving as an essential element to molecules such as amino acids and
nucleic acids, which are among the biochemical building blocks of life. As an organizing
concept to understand the effects of N within the environment, the sequence of transfers,
transformations, and environmental effects has been described as the "N cascade"
(Gallowav and Cowling. 2002). The concept of cascading effects also applies to S, which
is also an essential macronutrient.
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Sunlight
NO,
Effects on productivity
and biodiversity
Oxidation Dissolution
S02 ~ H2S04 *¦ 2H* +SO«2"
NO, ~HNO3 ~ H*+N03-
Dry deposition §02
NO„ NH„ SO, NO
Wet Deposition
H*. NH4\ NOj , S042-
N20 NO,
GHGs
Acidification of water + Eutrophication
A
Deposition
Ambient Air
Concentration
Ecological
Effect
Ca2+ = calcium ion; GHG = greenhouse gas; H* = hydrogen ion; HN03 = nitric acid; H2S04 = sulfuric acid; Mg2+ = magnesium ion;
N = nitrogen; N20 = nitrous oxide; NH3 = ammonia; NH4+ = ammonium; NHX = NH3 + NH4+ + reduced organic nitrogen compounds;
NO = nitric oxide; N02 = nitrogen dioxide; N03~ = nitrate; NOx = NO + N02; PAN = peroxyacetyl nitrate; PM = particulate matter;
S02 = sulfur dioxide; S042" = sulfate; SOx = S02 + S042"; VOC = volatile organic compounds.
The sum of reactive oxidized nitrogen species is referred to as NOY (NOY = NO + N02 + HN03 + 2N205 + HONO + N03" + N20
PAN + other organic nitrates). VOC refers to volatile organic compounds.
Although not explicitly indicated, wet and dry deposition of PM components (e.g., metals, minerals and secondary organic aerosol
also occur and contribute to ecological effects).
Source: (U.S. EPA. 2008a)
Figure 1-2 Overview of atmospheric chemistry, deposition, arid ecological
effects of emissions of oxides of nitrogen, oxides of sulfur, and
reduced nitrogen.
1.1.4.1 New Evidence and Causal Determinations
1 There are 19 causality statements in this ISA (Table 1-1). Fourteen are causal
2 relationships repeated from the 2008 ISA or modified from the 2008 ISA to include
3 specific endpomts. Five are new endpoint categories not evaluated in the 2008 ISA: three
4 with causal relationships, one with a likely causal relationship, and one suggestive of a
5 causal relationship.
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The current NO2 and SO2 secondary NAAQS are based on plant foliar injury. Research
continues to support causal relationships between SO2, NO2, NO, peroxyacetyl nitrate
(PAN), HNO3, and injury to vegetation (Table 1-1). but research that tests plant response
to the lower exposure levels that represent current atmospheric NOy and SOx
concentrations is limited. Therefore, little evidence is available to inform whether current
monitored concentrations of gas-phase NOy and SOx are high enough to injure
vegetation.
It is clear that NOy, SOx, and PM contribute to total N and S deposition, which alters the
biogeochemistry and the physiology of organisms, resulting in harmful declines in
biodiversity (Section 1.3.2). Decreases in biodiversity mean that some species become
relatively less abundant and may be locally extirpated. The current period in Earth's
history is the Anthropocene. A defining attribute of the Anthropocene is global human-
driven mass extinctions of species. The biodiversity loss reported in this assessment
contributes to the Anthropocene loss of biodiversity (Rockstrom et al.). In addition to the
loss of unique living species, the decline in total biodiversity is harmful because
biodiversity is an important determinant of the stability of ecosystems and the ability of
ecosystems to provide services to humanity.
Since the 2008 ISA, the largest increase in evidence is for terrestrial N enrichment effects
(Sections 1.5.1 and 1.5.2V This new research has greatly improved understanding of the
mechanistic links that inform causal determinations between N deposition,
biogeochemistry, and biota in terrestrial ecosystems (Table 1-1). Further, there is now
stronger empirical evidence from across most regions of the U.S. to evaluate the effects
of N deposition on biodiversity of lichens and grasses/forbs. A critical load (CL) is the
level of a pollutant below which no harmful ecological effect occurs (Section 1.3.3). To a
lesser extent, there is new evidence to evaluate CLs across much of the U.S. for nitrate
leaching, tree survivorship, and mycorrhizal biodiversity. The effects of N deposition on
terrestrial ecosystems have been the most comprehensively documented in forests and in
high-elevation ecosystems (e.g., alpine tundra) because these ecosystems are considered
strongly N limited, have historically experienced higher rates of N deposition, and
contain sensitive taxa such as lichens, forbs, and mycorrhizal fungi. Changes in
biodiversity caused by N deposition are also well documented in grasslands and arid
ecosystems. New evidence to characterize terrestrial acidification across large regions of
the U.S. is also available; in particular, new modeling work has improved calculation of
CLs for soil acidification (Section 1.5.3).
New evidence for freshwater acidification to characterize CLs across the U.S. builds on
several decades of research documenting freshwater acidification effects on aquatic biota
and confirms the causal relationships determined in the 2008 ISA (Table 1-1). New
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1 research has helped partition the role of atmospheric N deposition from agricultural and
2 wastewater N sources in contributing to N driven eutrophication of freshwaters, estuaries,
3 and wetlands. In freshwater systems where atmospheric deposition is the primary source
4 of N, such as in high alpine watersheds, new CLs support previous findings that
5 atmospheric N inputs are associated with increased primary productivity (a
6 community-scale metric of plant growth) and changes in biodiversity (Section 1.6). New
7 evidence also supports clear links between aqueous sulfur concentrations in aquatic
8 systems and both mercury methylation and sulfide toxicity; however, quantitatively
9 linking these outcomes to atmospheric deposition remains a challenge (Section 1.9).
Table 1-1 Causal determinations for relationships between criteria pollutants
and ecological effects from the 2008 and current draft Integrated
Science Assessment.
Causal Determination
Effect Category
2008 ISA
Current Draft ISA
Gas-Phase Direct Phototoxic Effects
Gas-phase SO2 and injury to vegetation
Causal relationship
Causal relationship
Section 3.5.1
Gas-phase NO, NO2, and PAN and injury to vegetation
Causal relationship
Causal relationship
Section 3.5.2
Gas-phase HNO3 and injury to vegetation3
Causal relationship
Causal relationship
Section 3.5.3
N and Acidifying Deposition to Terrestrial Ecosystems
N and S deposition and alteration of soil biogeochemistry in
terrestrial ecosystems3
Section 4J.
Causal relationship
Causal relationship
N deposition and the alteration of the physiology and growth
of terrestrial organisms and the productivity of terrestrial
ecosystems'5
Not included
Causal relationship
Section 6.1.7
N deposition and the alteration of species richness,
community composition, and biodiversity in terrestrial
ecosystems'5
Causal relationship
Causal relationship
Section 6.2.8
Acidifying N and S deposition and the alteration of the
physiology and growth of terrestrial organisms and the
productivity of terrestrial ecosystems0
Not included
Causal relationship
Section 5.6.1
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Table 1-1 (Continued): Causal determinations for relationships between criteria
pollutants and ecological effects from the 2008 and current
draft Integrated Science Assessment.
Causal Determination
Effect Category
2008 ISA
Current Draft ISA
Acidifying N and S deposition and the alteration of species
richness, community composition, and biodiversity in
terrestrial ecosystemsd
Causal relationship
Causal relationship
Section 5.6.2
N and Acidifying Deposition to Freshwater Ecosystems
N and S deposition and alteration of freshwater
biogeochemistrye
Causal relationship
Causal relationship
Section 7.4.1
Acidifying N and S deposition and changes in biota including
physiological impairment and alteration of species richness,
community composition, and biodiversity in freshwater
ecosystems'
Causal relationship
Causal relationship
Section 8,6
N deposition and changes in biota including altered growth,
species richness, community composition, and biodiversity
due to N enrichment in freshwater ecosystems9
Causal relationship
Causal relationship
Section 9J3
N Deposition to Estuarine Ecosystems
N deposition and alteration of biogeochemistry in estuarine
and near-coastal marine systems
Causal relationship
Causal relationship
Section 7.4.2
N deposition and increased nutrient-enhanced coastal
acidification
Not included
Likely to be a causal
relationship
Section 7.4.2
N deposition and changes in biota including altered growth,
species richness, community composition, and biodiversity
due to N enrichment in estuarine environments11
Causal relationship
Causal relationship
Section 10.8
N deposition and changes in biota including altered
physiology, species richness, community composition, and
biodiversity due to nutrient-enhanced coastal acidification
Not included
Suggestive of a causal
relationship
Section 10.8.2
N Deposition to Wetland Ecosystems
N deposition and the alteration of biogeochemical cycling in
wetlands
Causal relationship
Causal relationship
Section 11.10.1
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Table 1-1 (Continued): Causal determinations for relationships between criteria
pollutants and ecological effects from the 2008 and current
draft Integrated Science Assessment.
Causal Determination
Effect Category 2008 ISA Current Draft ISA
N deposition and the alteration of species physiology, Causal relationship Causal relationship
species richness, community composition, and biodiversity
in wetlands
Section 11.10.1
S Deposition to Wetland and Freshwater Ecosystems
S deposition and increased methylation of Hg in wetland Causal relationship Causal relationship
and aquatic ecosystems where the value of other factors is
within adequate range for methylation'
Section 12.9
S deposition and changes in biota due to sulfide Not included Causal relationship
phytotoxicity including alteration of species physiology,
species richness, community composition, and biodiversity
in wetland ecosystems
Section 12.9.3
C = carbon; Hg = mercury; HN03 = nitric acid; ISA = Integrated Science Assessment; N = nitrogen; NO = nitric oxide; N02 = nitrogen
dioxide; PAN = peroxyacetyl nitrate; S = sulfur; S02 = sulfur dioxide.
The 2008 ISA causality statements for gas phase HN03 was phrased as, "changes in vegetation."
bThe 2008 ISA included two causality statements for terrestrial biogeochemistry phrased as, "relationship between acidifying deposition
and changes in biogeochemistry" and "relationship between N deposition and the alteration of biogeochemical cycling of N."
The 2008 ISA causality statement for biological effects of N enrichment in terrestrial ecosystems was phrased as, "relationship between
N deposition and the alteration of species richness, species composition and biodiversity."
dThe 2008 ISA causality statement for biological effects of acidifying deposition in terrestrial ecosystems was phrased as, "relationship
between acidifying deposition and changes in terrestrial biota."
eThe 2008 ISA included three causality statements for freshwater biogeochemistry phrased as, "relationship between acidifying deposition
and changes in biogeochemistry related to aquatic ecosystems", "relationship between N deposition and the alteration of biogeochemical
cycling of N", and "relationship between N deposition and the alteration of biogeochemical cycling of C."
The 2008 ISA causality statement for biological effects of acidifying deposition in freshwater ecosystems was phrased as, "relationship
between acidifying deposition and changes in aquatic biota."
The 2008 ISA causality statement for biological effects of N deposition in freshwater ecosystems relationship between N deposition and
the alteration of species richness, species composition and biodiversity in freshwater aquatic ecosystems."
The 2008 ISA causality statement for biological effects of N deposition to estuaries was phrased as, "relationship between N deposition
and the alteration of species richness, species composition and biodiversity in estuarine ecosystems."
'The 2008 ISA causality statement for biological effects of S deposition effects on ecosystems was phrased as, "relationship between S
deposition and increased methylation of Hg, in aquatic environments where the value of other factors is within adequate range for
methylation."
1.2 Emissions and Atmospheric Chemistry
The atmospheric chemistry from emission to deposition for NOy
(NOy = NO + NO2 + HNO3 + 2N2O5 + HONO + N03 + peroxyacetyl nitrate
[PAN] + other organic nitrates), SOx (SOx = SO2 + SO42 ) and NHx
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(NHx = NH3 + NH4+) is included in this ISA.15 A wide variety of N containing
compounds (oxidized + reduced, and organic + inorganic) contribute to wet and dry
deposition (Section 2.1). Wet deposition occurs via precipitation, and dry deposition
transfers gaseous and particulate pollutants from the atmosphere to the surface by
impaction through turbulence and gravitational settling.
Atmospheric processes of PM are also addressed in this ISA because the PM components
relevant to acid and nutrient deposition are NOy, SOx, or NHx. The major components of
particulate matter in the U.S. are NO3 , SO42 , NH4+, organic carbon, and elemental
carbon. Of these, NO3 , SO42 . and NH4+ usually have a strong influence on acid
deposition, and NO3 and NH4+, and in some cases organic nitrogen (organic nitrates and
reduced organic N), make a substantial contribution to N deposition. Because all of these
contributors are included in definitions of NOy, SOx, or NHx, a discussion of
atmospheric processes of NOy, SOx, or NHx also functions as an effectively complete
discussion of atmospheric PM processes relevant to the impacts investigated in this ISA.
Since the 2008 ISA, there have been a number of new developments including:
• expansion of monitoring networks to include NH3 and NOy at selected sites, and
comparisons of monitoring methods with research-grade instruments
(Section 2.5);
• adoption of new methods, such as data-model fusion, to integrate deposition
information across the U.S. (Section 2.8);
• incorporation of bidirectional exchange into models of dry deposition
(Section 2.7.2): and
• improvements in techniques using satellite-based measurements and
chemistry-transport model simulations to estimate emissions, concentrations, and
dry deposition of NO2, SO2, and NH3 (Section 2.8).
1.2.1 Sources and Atmospheric Transformations
Both gaseous and particulate forms of N and S contribute to atmospheric deposition. The
main contributors to acidifying precipitation are H2SO4 and HNO3, which are formed
from precursor emissions of SO2 and NOx (NO + NO2) (Section 2.2). Gaseous emissions
ofNH3 and S02are each dominated by a single source: agriculture (fertilizer application
and animal waste) for NH3 and electricity generating units (EGUs) for SO2. Notably, SO2
emissions from EGUs have been decreasing. NOx, emissions have a wider distribution of
15The term concentration is used throughout the ISA to denote either a mass per unit volume or a mixing ratio. The
use of concentration to denote abundance expressed as mixing ratio is so firmly entrenched in the literature that it is
retained here, despite being technically incorrect.
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sources, with substantial contributions from highway and off-highway vehicles, lightning,
and EGUs.
Major components of particulate N and S include NH4+, NO;, . and SO42 , which are
primarily derived from gaseous precursors NH3, NOx, and SO2 (Section 2.3) Formation
of particulate N and S is described in the 2009 ISA for Particulate Matter (U.S. EPA.
2009a).
In general, inorganic SO2, NO, NO2, and NH3 are the most abundant atmospheric
gas-phase species, and inorganic NO3 , SO42 . and NH4 are the main PM components
that have a role in acid or N deposition. An understanding of the sources, chemistry, and
atmospheric processes for these gas-phase and PM species provides a background for
understanding acidifying and N deposition.
1.2.2 Measurement and Modeling Techniques
Monitoring networks across the U.S. measure NOy, SOx, and NHx species involved in
deposition (Section 2.5). The National Acid Deposition Program/National Trends
Network (NADP/NTN) has monitored precipitation chemistry for several decades at
many U.S. sites. The Clean Air Status and Trends Network (CASTNET) has monitored
concentrations of inorganic gas and particulate-phase N and S species since 1990.
Concentrations are combined with measurements of micrometeorology and surface
characteristics to infer dry deposition. Monitoring of NH3 (Section 2.5.3) in the Ammonia
Monitoring Network (AMoN), part of the NADP network, was initiated at a subset of
CASTNET sites in 2007. The Interagency Monitoring of Protected Visual Environments
(IMPROVE) network and the Chemical Speciation Network (CSN) measure PM and PM
components including NH4+, NO3 . and SO42 . although these data are not used to
estimate deposition rates (Section 2.5.6).
Atmospheric N deposition rates are calculated from measurements and models. Direct
measurement of NO2 has limited utility for quantifying NOy deposition rates. Because
NOy is composed of diverse chemical species with a wide range of deposition velocities
and compensation points, unmeasured component species of NOy and concentrations of
all NOy species in data-sparse regions must be provided by regional models in
conjunction with satellite data (Section 2.5.1.1).
Estimates of dry deposition (Section 2.7.2) over the contiguous U.S. (CONUS) are
inferred by atmospheric models, either regional-scale chemical transport models (CTMs)
or local-scale micrometeorological models, using CASTNET data. Both types of models
are subject to uncertainties in their treatment of small-scale turbulence and surface
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interactions. Consequently, dry deposition rates (and ratios of wet-to-dry deposition)
continue to be highly uncertain.
1.2.3 Spatial and Temporal Variability in Deposition
Emissions of SO2 and NOx (NO + NO2) have declined dramatically since the passage of
the Clean Air Act Amendments in 1990. Emissions of NOx in the U.S. from highway
vehicles and fuel combustion declined 49% between 1990 and 2013, while nationwide
annual average NO2 concentrations decreased by 48% from 1990 to 2012 ISA (U.S. EPA.
2016b). Total emissions of SO2 decreased by 72% from 1990 to 2011.
Overall deposition of total N (oxidized + reduced N) has not decreased over the past
25 years (Section 2.8.3). Although NOx emissions have declined in the CONUS,
emissions of NH3 have increased in many areas. The large spatial variability in N
deposition is evident in the map (Figure 1-3) of average (2011 to 2013) annual dry + wet
deposition of NOy and NHx over the CONUS estimated using the TDEP (Total
Deposition) modeling approach (Section 2.8). which combines output from the
Community Model for Air Quality (CMAQ) system with wet deposition from the
NADP/NTN (Schwede and Lear. 2014b).
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Total deposition of nitrogen 1113
Soilrt-e: CASTNTTTAHMAQA~T\7AMON/SE AR C H TTSEPA KVle/14
ha = hectare; kg = kilogram; N = nitrogen.
Figure 1-3 Three-year (2011 to 2013) average annual dry + wet deposition of
total oxidized nitrogen and reduced nitrogen species in kilograms
of nitrogen per hectare per year.
According to TDEP estimates for 2011-2013 (Section 2.8.1.1). at least one-third of the
CONUS is estimated to receive at least 10 kg N/ha/yr dry +wet deposition, with some
areas receiving more than 15 kg N/ha/yr. It is likely that estimates for the spatial extent of
the areas receiving at least 10 kg N/ha/yr of deposition and the overall amount of N
deposited are too low because reduced organic N species are not routinely monitored or
considered in air quality models such as CMAQ.
In general, wet deposition of reduced N exceeds that of oxidized N across the CONUS.
Nationwide, deposition of N occurs mainly by dry deposition of HNOb and NH3 (with
NH3 dominant), according to estimates based on CASTNET and NADP data and CMAQ
modeling results (Figure A-4). Hybrid satellite/modeling and CMAQ results indicate that
dry deposition of NO2 is also a nontrivial source of deposited N in many areas. Over the
past 25 years, NADP/NTN data show that wet deposition of inorganic N
(oxidized + reduced) decreased in areas such as the Northeast, but remained constant or
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increased in areas such as the central U.S. (see Figure 2-32 in Section 2.8.3). Wet
deposition of total inorganic N has not tracked declines in NOx emissions over the past
25 years, indicating that wet deposition of reduced inorganic N has increased in this
period.
For S deposition, wet deposition tends to dominate over dry deposition in large areas of
the CONUS. Dry deposition of particulate SO42 is only a minor source of S.
Anthropogenic emissions of S and subsequent deposition have declined markedly since
the 1990s, with the most pronounced declines in the eastern U.S. Currently, the highest
values of total (wet + dry) SOx deposition in the U.S. are in parts of the Ohio Valley
region, and range between 15 to 20 kg S/ha/yr (Figure A-20).
Both N and S deposition contribute to acidification of ecosystems. The pH of rainwater
has increased markedly across the U.S. since 1990, coincident with decreases in the wet
deposition of nitrate and sulfate. However, there are still widespread areas affected by
acidifying precipitation, mainly in the eastern U.S. (see Section 2.8). Total acidifying
deposition (wet + dry N + S, expressed as H+ equivalents) fluxes for 2011 to 2013 ranged
from a few hundred H+ equivalents/ha/yr over much of the western U.S. to over 1,500 H+
equivalents/ha/yr in a broad swath encompassing the Midwest and the Mid-Atlantic
regions, and in other isolated hotspots surrounding areas of concentrated industrial or
agricultural activity (Figure 1-4).
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H+ Equivalents of Total Nitrogen and Sulfur Deposition
Eq.= equivalents; H+ = hydrogen ion; ha = hectare; yr = year.
Source: NCEA using data from TDEP.
Figure 1-4 Total deposition of total oxidized nitrogen, reduced nitrogen, and
oxidized sulfur expressed as H+ equivalents per hectare per year
over the contiguous U.S. 2011-2013.
1 Dry deposition rates are a strong function of surface characteristics, which modify the
2 structure of surface layer turbulence and the resistance to uptake by vegetation
3 (Section 2.7.2). As a result, spatially aggregated estimates of dry deposition fluxes are
4 subject to sizable uncertainty, in addition to inherent uncertainties in the measurement of
5 species concentrations and in the inference of dry fluxes. Wet fluxes are not directly
6 influenced by surface characteristics (although orography affects transport and
7 precipitation) but are subject to smaller uncertainties in the measurement of rainfall and
8 chemistry.
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1.3 Core Ecological Concepts
This synthesis of current scientific knowledge, which draws on many methodological
approaches and disciplines, relies on the ecological concepts of ecosystem scale,
structure, and function and CL. Ecosystem structure comprises both biodiversity and
geography. Biodiversity encompasses many quantitative measures of the abundance and
distribution of organisms within a defined area (for a more explicit definition, see
Section 1.3.1). Ecosystem function refers to processes that control fluxes and pools of
matter and energy in the ecosystem (Section 1.3.1). The loss of biodiversity is a key
consequence of the air pollutants discussed in this ISA. The importance of preserving
biodiversity and ecosystem function contributes to the sustainability of ecosystem
service, services that ecosystems provide to benefit human welfare and society
(Section 1.3.2 and Chapter 14).
In human health assessments, dose-response relationships are used to identify
quantitative relationships between chemical concentrations (dose) and health outcomes
(response), with emphasis on identifying thresholds, the lowest doses at which negative
health outcomes are observed. In ecology, CLs provide a similar quantitative relationship
between chemical dose (e.g., deposition) and specific, quantitative changes in ecological
properties or processes (Section 1.3.3). Use of CLs in evaluating the effects of deposition
upon ecosystems must consider how deposition compares to other anthropogenic and
ambient sources of N and S to these ecosystems (Section 1.3.4). as well as the
heterogeneous sensitivities of organisms and ecosystems to different chemical forms of
deposition (Section 1.3.5).
1.3.1 Ecosystem Scale, Structure and Function
For this assessment, an ecosystem is defined as the interactive system formed from all
living organisms (biota) and their abiotic (chemical and physical) environment within a
given area (IPCC. 2007a). Ecosystem boundaries are somewhat arbitrary, depending on
the focus of interest or study. Thus, the extent of an ecosystem may range from very
small, well-circumscribed systems such as a small pond, to biomes at the continental
scale, or the entire globe (U.S. EPA. 2008a). Ecosystem scale does not always correlate
with complexity. A small pond may be a complex system with multiple trophic levels
ranging from phytoplankton to invertebrates to several feeding guilds of fish. A large
lake, on the other hand, may be a very simple ecosystem, such as the Great Salt Lake in
Utah that covers approximately 1,700 square miles but contains only bacteria, algae,
diatoms, and two invertebrate species (U.S. EPA. 2013b). All ecosystems, regardless of
size or complexity, share the commonality of multiple interactions between biota and
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abiotic factors, and a reduction in entropy through energy flow from autotrophs to top
predators. Ecosystems include both structural (geography and biodiversity; e.g., soil type
and food web trophic levels) and functional (flow of energy and matter; e.g.,
decomposition, nitrification) attributes. Ecosystem changes are often considered
undesirable if important structural or functional components of the ecosystems are altered
following pollutant exposure (U.S. EPA. 2013b. 1998a).
Ecosystems are most often defined by their structure. Structure includes biodiversity.
Biodiversity comprises quantitative measurements, including abundance, richness,
distribution, evenness, and composition, measured at the population, species, community,
ecosystem or global scale. A eukaryotic species is defined by a common morphology,
genetic history, geographic range of origin, and ability to interbreed and produce fertile
offspring. Populations consist of interbreeding groups of individuals of thesame species
that occupy a defined geographic space. Interacting populations of different species
occupying a common spatial area form a community (Bamthouse et al.. 2008).
Community composition may also define an ecosystem type, such as a pine forest or a
tall grass prairie. Pollutants can affect the ecosystem structure at any of these levels of
biological organization (Suter et al.. 2005). Individual plants or animals may exhibit
changes in metabolism, enzyme activities, hormone function, or may suffer gross lesions,
tumors, deformities, or other pathologies. However, only some organism-level endpoints
such as growth, survival, and reproductive output have been definitively linked to effects
at the population level and above (U.S. EP A. 2013b). Population-level effects of
pollutants include changes over time in abundance or density (number of individuals in a
defined area), age or sex structure, and production or sustainable rates of harvest
(Bamthouse et al.. 2008). Community-level attributes affected by pollutants include
species richness, species abundance, composition, evenness, dominance of one species
over another, or size (area) of the community (U.S. EPA. 2013b). Pollutants may affect
communities in ways that are not observable in organisms or populations (Bartell. 2007).
including: (1) effects resulting from interactions between species, such as altering
predation rates or competitive advantage; (2) indirect effects, such as reducing or
removing one species from the assemblage and allowing another to emerge (Petraitis and
Latham. 1999); and (3) alterations in trophic structure.
Alternatively, ecosystems may be defined on a functional basis. "Function" refers to the
suite of processes and interactions among the ecosystem components that involve energy
or matter. Examples include water dynamics and the flux of trace gases such as rates of
photosynthesis, decomposition, nitrification, or carbon cycling. Pollutants may affect
abiotic conditions (e.g., soil chemistry), which indirectly influences biotic structure and
function (Bartell. 2007).
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Some ecosystems, and some aspects of particular ecosystems, are less vulnerable to
long-term consequences of pollutant exposure. Other ecosystems may be profoundly
altered if a single attribute is affected. Thus, spatial and temporal definitions of
ecosystem structure and function become an essential factor in defining impacted
ecosystem services and CLs of particular pollutants, either as single pollutants or in
combination with other stressors.
1.3.2 The Importance of Biodiversity
There are causal relationships between N and/or S and biodiversity loss in terrestrial,
freshwater, wetland, and estuarine ecosystems in the U.S. (Table 1-1). What does it mean
to affect biodiversity? Biodiversity loss not only represents the extirpation of unique
living species; several decades of research link biodiversity to ecosystem function and
ecosystem services in a wide variety of natural systems (Hooper et al.. 2012; Balvanera et
al.. 2006; Tilman. 2000). Numerous studies demonstrate that the number and diversity of
organisms in a system control the abundance of habitat for other species, the
biogeochemical cycling of nutrients and carbon, and the efficiency at which biotic
systems are able to transform limited resources into biomass (Cardinale et al.. 201IV
Among plant communities, higher biodiversity leads to higher overall plant productivity
and greater retention of soil nutrients (Reich et al.. 2012; Tilman. 2000). In multitrophic
systems, higher prey diversity leads to both higher predator growth rates and a smaller
impact of predation on prey abundance (Duffv et al.. 2007). Positive impacts of
biodiversity on ecosystem services have been documented in forests (Gamfeldt et al..
2013; Zhang et al.. 2012b). grasslands (Tilman et al.. 2012). arid and semi arid
ecosystems (Maestre et al.. 2012). and marine systems (Gamfeldt et al.. 2015; Worm et
al.. 2006) and include effects such as greater carbon storage, fruit production, wood
production, and nutrient cycling. In marine ecosystems, biodiversity loss has been linked
to increased rates of resource collapse and exponential decreases in water quality through
metrics such as higher numbers of beach closures and harmful algal blooms [HABs;
(Worm et al.. 2006)1. Notably, HABs are linked to increased disease prevalence among
humans, domestic animals/pets, and aquatic organisms (Johnson et al.. 2010). In addition
to the relationship between HABs and disease, there is now empirical evidence from
many ecosystems of a broader link between declines in biodiversity and increased
transmission and severity of disease (Johnson et al.. 2015b) caused by plant, wildlife, and
human pathogens. As a whole, these decades of research have produced an overwhelming
body of evidence indicating that the loss of biodiversity risks a deterioration of the
ecosystem goods and services that humanity depends upon (Gamfeldt et al.. 2015;
Cardinale et al.. 2012).
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One of the most important consensus observations in biodiversity research is that
ecosystem processes are more stable (have less temporal variability) at higher levels of
diversity (Cardinale et al.. 2012; McCann. 2000; Naeem and Li. 1997; Til man and
Downing. 1994). This stability occurs because species respond differently to
environmental variation. In diverse communities, is it more likely that declines in the
growth of one species caused by an environmental change will provide more resources
for competing species (Cardinale et al.. 2012; Tilman. 2000). This property was predicted
by economists and is similar to how more diversified investment portfolios provide
enhanced stability under fluctuating market conditions (Doak et al.. 1998; Tilman et al..
1998). Notably, there is also consensus that the impact of biodiversity on ecosystem
processes is nonlinear, wherein declines in ecosystem processes accelerate as the number
of species in a system declines (Cardinale et al.. 2012). Accelerating ecosystem service
declines in response to species loss may be due to multifunctionality, which suggests that
different ecosystem functions require the presence of different sets of species (Isbell et
al.. 2015; Reich et al.. 2012; Zavaleta et al.. 2010). The increased stability of diverse
ecosystems makes these systems less vulnerable to environmental change and less
vulnerable to collapse caused by external forces such as drought or human disturbance
(Isbell et al.. 2015; Tilman et al.. 2012; Isbell et al.. 2011; Worm et al.. 2006). For
example, coastal systems with higher species diversity had lower rates of fishery collapse
and extinction for commercially important fish and invertebrate species, and large marine
ecosystems with higher fish diversity recovered more quickly from collapse (Worm et al..
2006). Thus, there is strong evidence that high biodiversity helps sustain ecosystem
services and also makes these ecosystem services more resilient to environmental change.
1.3.3 Critical Loads as an Organizing Principle
Throughout this ISA, the CL concept is used as an organizing principle to relate
atmospheric deposition to ecological endpoints that indicate impairment. The generally
accepted definition of a CL of atmospheric pollutant deposition as a level of a pollutant
below which no harmful ecological effect. The development of a quantitative critical load
estimate requires a number of steps. An illustrative example of the eight general steps is
shown in Figure 1-5.
It is important to recognize that there is no single "definitive" critical load for an
ecological effect. Critical loads estimates reflect the current state of knowledge and the
selected limits, indicators, and responses. Changes in scientific understanding may
include, for example, new dose-response relationships, better resource maps and
inventories, larger survey data sets, continuing time-series monitoring, and improved
numerical models.
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1) Disturbance
Acidification
Eutrophication
2) Receptor
Forest
Lake
Grassland
Lake
3) Biological
indicator
Sugar
Maple
Norway
Spruce
Brook trout
Fish species
richness
Species
diversity
Primary
productivity
4) Critical
biological
response
Failure to
reproduce
Seedling
death
Presence
absence
Species
loss
Species
loss
Excess
productivity
5) Chemical
indicator
Soil % Base
Saturation
Soil Ca/AI
ratio
Lakewater
ANC
Lakewater
ANC
Soil C/N
ratio
Lakewater
no3
8) Critical
chemical
limit
10%
1.0
0 peq/L
50 peq/L
20
10 peq/L
7) Atmospheric
pollutant
S04, no3,
NH,
so4< no3.
nh4
so4, no3,
nh4 "
so4, no3,
nh4
no3. nh4
no3! wh4
8) Critical
pollutant load
??? ???
??7
???
???
???
Al = aluminum; ANC = acid neutralizing capability; C = carbon; Ca = calcium; L = liter; |jeq = microequivalents; N = nitrogen;
NH4 = ammonium; N03 = nitrate; S04 = sulfate.
Source= U.S. EPA (2008a)
Figure 1-5 An example of the matrix of information considered in defining
and calculating critical loads (see discussion in text). Note that
multiple alternative biological indicators, critical biological
responses, chemical indicators, and critical chemical limits could
be used.
This procedure could require calculating multiple critical loads for a given pollutant at a
single location. The multiple solutions derive from the nested sequence of disturbances,
receptors, and biological indicators considered for a given pollutant. Multiple critical load
values may also arise from an inability to agree on a single definition of "harm."
Calculation of critical loads for multiple definitions of "harm" may be deemed useful in
subsequent discussions of the analysis and in the decision-making steps that may follow
critical load calculation.
Finally, there is the inescapable heterogeneity of all natural environments, which can
affect responsiveness of ecosystems to both deposition load (Section 1.5.1.1) and
chemical form (Section 1.3.5). As an example, the high spatial variability of soils almost
guarantees that for any reasonably sized soil-based "receptor" that might be defined in a
CL analysis, there will be a continuum of CL values for any indicator chosen. The range
of this continuum of values might be narrow enough to be ignored; nevertheless, there is
an a priori expectation in any critical load analysis that multiple values (or a range of
values) will result from the analysis. Given the heterogeneity of ecosystems affected by N
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and S deposition, published critical load values for locations in the U.S. vary widely
depending on both biological and physical factors.
1.3.4 Source apportionment of N and S to Ecosystems
The contribution of atmospheric deposition to total loading for N and S varies within and
among terrestrial, wetland, freshwater, and estuarine ecosystems.
In the 2008 ISA, atmospheric deposition was identified as the main source of
anthropogenic N to unmanaged terrestrial ecosystems. This has been confirmed by new
studies on N sources to lands and waterways, which find human-mediated watershed N
inputs that range from <1.0 to 34.6 times the rate of background N input (Section 4.2).
Across all watersheds, atmospheric N deposition is the second largest overall
human-mediated N source and the largest N source to 33% of watersheds. There is no
new information published on nonatmospheric sources of S in terrestrial ecosystems
(Section 4.2); S inputs from the atmosphere are discussed in Chapter 2.
In the 2008 ISA, atmospheric deposition was also identified as the main source of N to
some freshwater ecosystems, including headwater streams, high-elevation lakes, lower
order streams in undisturbed areas and freshwater wetlands (e.g., bogs and fens).
Evidence for the influence ofN deposition on water chemistry has been further supported
by new studies that quantify the contribution of N deposition to total N loading in
freshwater lakes and streams, and which quantify atmospheric contributions during storm
events (Table 7-1). As shown in these studies, deposition can represent a substantial
portion of total N loading to surface waters. However, other nonpoint and point sources
of N dominate N inputs to high-order streams.
In fresh surface waters and wetlands, sources of S that contribute to enrichment effects
are the same sources of S that induce acidifying effects, and include weathering of
minerals in sediments and rocks, leaching from terrestrial S cycling, internal cycling, and
direct atmospheric deposition. The 2008 ISA showed that drought can release S stored in
wetlands or lake sediments, as bound sulfide (S2 ) is exposed to atmospheric oxygen and
oxidized to sulfate. Model of Acidification of Groundwater in Catchments (MAGIC)
modeling showed that variable water levels due to climate change-induced droughts can
increase water sulfate concentrations, and observational research showed that drought
increased lake S load by 5 kg S/ha/yr. New evidence confirms that fluctuating water
levels in wetlands increase SO42 concentration in pulses following water level recovery.
Sources of N in coastal areas may include direct deposition to the water surface, coastal
upwelling from oceanic waters, and transport from watersheds. Freshwater inflows to
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estuaries may contain N from agriculture, urban, wastewater and atmospheric deposition
sources. Atmospheric deposition constitutes less than half of the total N supply in most,
but not all estuaries (Table 7-6). Both point sources and nonpoint sources (including
runoff, as well as atmospheric deposition) have been identified as targets for mitigation of
N loading in coastal areas. The importance of atmospheric deposition as a cause of
estuarine eutrophication is determined by the relative contribution of the atmospheric
versus nonatmospheric sources of N input. Seawater contains high concentrations of
S042 so atmospheric inputs of S are unlikely to contribute substantially to
biogeochemistry or biological effects in coastal areas.
1.3.5 Reduced Versus Oxidized Nitrogen Effects Across Ecosystems
Individual biochemical and geochemical processes involve specific chemical forms of N,
suggesting that there may be consequences in many ecosystems from the ongoing trend
of decreasing NOy deposition and increasing NHx deposition (Section 1.2.3). The largest
body of evidence that the effects of reduced versus oxidized N may have different
consequences for ecological structure and function is for coastal ecosystems. For
instance, the growth of some species of phytoplankton (Section 10.2.2) and macroalgae
(seaweed; Section 10.2.3) appear to be related to the form of N. However, in many
estuaries, inputs of NH3/NH44" are unlikely to be attributed solely to atmospheric sources
due to the large contribution of N from wastewater, agriculture, and other sources. Inputs
of NH3/NH44" selectively favor species associated with HABs, and shifts in phytoplankton
community composition to species that respond strongly to reduced N have been
observed in some coastal regions (Section 10.3.2). There is also increasing evidence in
freshwater systems for the importance of N in HABs, and several studies have shown that
the form of N influences freshwater algal species composition (Section 9.2.5). In
terrestrial systems, redox status of inorganic N seems to have little influence on the
biological responses to N deposition (Table 6-1). Different responses to individual forms
ofN have been observed for some biogeochemical processes, but terrestrial flora rarely
respond differentially at currently observed levels because plant uptake of N is mediated
by soil biogeochemical cycles that often rapidly transform N between oxidized and
reduced forms (Section 6.1.2).
1.4 Gas-phase Direct Phytotoxic Effects
New evidence supports the causal determinations made in the 2008 ISA regarding
gas-phase effects on vegetation, and there are no new causal statements for gas-phase
effects. As in the 2008 ISA, the current ISA concludes that there are causal relationships
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between SO2, NO2, NO, PAN, HNO3, and injury to vegetation. This determination is
based on consistent, coherent, and biologically plausible evidence (Sections 32, 33, and
3.4; Table 1-1). The clearest evidence for these conclusions across pollutants comes from
studies available at the time of the 2008 ISA. There have been some additional studies
since the 2008 ISA. The majority of evidence on the direct effects of gaseous NOy and
SOx comes from controlled exposure studies across many species of vegetation. The
majority of controlled exposure studies over the past several decades have used
concentrations of gas-phase NOy and SOx above current ambient conditions observed in
the U.S. Relevant information is lacking on exposures and effects reflecting the more
recent lower pollutant conditions. Therefore, there is little evidence available to inform
whether current monitored concentrations of gas-phase NOy and SOx are high enough to
injure vegetation.
1.4.1 Sulfur Dioxide
In the 2008 ISA, evidence was sufficient to infer a causal relationship between exposure
to SO2 and injury to vegetation. The current secondary standard for SO2 is a 3-hour
average of 0.50 ppm, which is designed to protect against acute foliar injury in
vegetation. There has been limited research on acute foliar injury since the 1982 PM-SOx
Air Quality Criteria Document (AQCD), and there is no clear evidence of acute foliar
injury below the level of the current standard. The limited new research since 2008 adds
more evidence that SO2 can have acute negative effects on vegetation but does not
change conclusions from 2008 ISA regarding the causal relationship between SO2
exposure and vegetation damage or the SO2 levels producing these effects (see
Section 3.1). Consistent with the 2008 ISA, the body of evidence is sufficient to infer a
causal relationship between gas-phase SO2 and injury to vegetation.
Increased SO2 exposure concentrations and longer exposure times are associated with
decreases in plant growth and yield. The 1982 PM-SOx AQCD concluded that more
definitive concentration-response studies were needed before useable exposure metrics
could be identified. However, very few studies of the effects of SO2 on growth of
vegetation in the U.S. have been conducted since 1982. Recent studies from Eastern
Europe indicate recovery of tree growth in response to decreases in SO2 concentrations
since the 1980s and that annual SO2 concentrations of 4 ppb decreased silver fir (Abies
alba) growth. In West Virginia, the growth of eastern redcedar (Juniperus virginiana)
trees increased with declines in SO2 emissions since the 1980s.
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1.4.2
Nitrogen Oxide, Nitrogen Dioxide, and Peroxyacetyl Nitrate
In the 2008 ISA, evidence was sufficient to infer a causal relationship between exposure
to NO, NO2, and PAN and injury to vegetation. It is well known that in sufficient
concentrations, NO, NO2, and PAN can have phytotoxic effects on plants through
decreased photosynthesis and induction of visible foliar injury. However, the 1993
Oxides of Nitrogen AQCD concluded that concentrations of NO, NO2, and PAN in the
atmosphere are rarely high enough to have phytotoxic effects on vegetation (U.S. EPA.
1993). and very little new research has been performed at concentrations currently
observed in the U.S. (see Section 3.3). Thus, consistent with the previous 2008 ISA, the
body of evidence is sufficient to infer a causal relationship between gas-phase NO,
NO2, and PAN and injury to vegetation.
1.4.3 Nitric Acid
In the 2008 ISA, evidence was sufficient to infer a causal relationship between exposure
to HNO3 and changes to vegetation. The 2008 ISA reported experimental exposure to
HNO3 resulted in damage to the leaf cuticle of pine and oak seedlings, which may
predispose those plants to other stressors such as drought, pathogens, and other air
pollutants. Since the 2008 ISA, Padgett et al. (2009b) investigated dry deposition of
HNO3 on the foliage in a fumigation study and confirmed the earlier research. The 2008
ISA also reported several lines of evidence that past and current HNO3 concentrations
may be contributing to the decline in lichen species in the Los Angeles basin. Subsequent
studies conducted in the Los Angeles basin since the 2008 ISA provide further evidence
of the impacts (see Section 3.4). These new studies continue to support the causal
findings of the 2008 ISA, such that the body of evidence is sufficient to infer a causal
relationship between gas-phase HNO3 and changes to vegetation.
1.5 Terrestrial Ecosystem Nitrogen Enrichment and Acidification
For terrestrial ecosystems, new evidence reinforces causal findings from the 2008 ISA
and provides the basis for two new causal statements that reflect a more comprehensive
understanding of how N and acidifying deposition alter terrestrial ecosystem biota (Table
1-1). In general, N deposition may cause soil N enrichment and stimulate the growth of
opportunistic species. However, in sensitive soils, deposition of N and/or S can cause soil
acidification, which may decrease growth and cause mortality among sensitive plant
species. Atmospheric deposition ofN and S alter the species composition of terrestrial
systems by one of four mechanisms: (1) nutrient enrichment (eutrophication; Chapter 4
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and Chapter 6). (2) acidification (Chapter 4 and Chapter 5). (3) direct damage (Chapter
3), and (4) secondary effects (Section 6.2.1V Ecosystems and communities may be
simultaneously affected by one or more mechanisms depending on the sensitivity of
environmental and biological properties to each mechanism.
N deposition is considered nutrient enrichment because, despite the abundance of N in
the environment, plants are unable to directly access the large pools of N contained in the
atmosphere as N2 gas and in the soil as large organic molecules. Consequently, the
limited availability of reactive N often constrains biological activity in terrestrial all
ecosystems. In general, N addition stimulates plant growth and productivity (cumulative
growth of all vegetation within a community), which has been recognized since the
second half of the 19th century. In comparison, the biological influence of acidifying
deposition is less ubiquitous and largely constrained to ecosystems that have historically
experienced high rates of deposition and are predisposed to vulnerability by factors such
as geology and climate. While S is also an essential macronutrient, less S is required for
growth than N, and areas affected by acidifying deposition typically receive S at rates
that greatly exceed biotic demand. Instead, the impact of acidifying deposition stems
from the disruptions to biochemical processes caused by decreased pH and shifts in soil
physiochemical processes that decrease the supply of other essential nutrients (e.g., Ca,
Mg) and increase the mobilization of toxic forms of Al.
Current knowledge of soil biogeochemistry indicates soil N enrichment and soil
acidification occur in sensitive ecosystems across the U.S. at present levels of deposition.
Newly published work indicates decreasing SO2 emissions and S deposition have led to
early signs of recovery from acidification in some Northeastern watersheds, but areas in
the Southeast do not show recovery (Chapter 4). There are many well-defined soil
indicators that are related to the biological effects of acidifying (N + S) deposition. New
evidence uses these indicators to describe the status of ecosystems, either by empirical
observation or models. Soil indicators for acidification are more typically modeled than
those for eutrophication effects. There is an abundance of new information on
biogeochemical pools and processes, including a new conceptual framework for the N
saturation of terrestrial ecosystems.
The enrichment of terrestrial ecosystems by N deposition often increases plant
productivity and causes changes in physiology and growth rates that vary among species.
This has been observed for herbaceous plants and trees across ecoregions. The changing
growth rates transform competitive interactions between species, and as a consequence
lower species diversity is often observed with increasing N deposition within terrestrial
communities. The relationship between N deposition and community composition is
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often derived empirically as critical loads. There are many new critical loads available
since the 2008 ISA for lichens, herbaceous plants, and mycorrhizae.
The process of terrestrial acidification has been well understood and documented for
decades. Recent research, since the 2008 ISA, has confirmed and strengthened this
understanding and provided more quantitative information, especially across
regional-scale landscapes. A number of studies have evaluated the relationships between
soil chemistry indicators of acidification and ecosystem biological endpoints (see Table
5-1) and some models are well established. There have been new advances in the
parameterization of acidification models to U.S. soils since the 2008 ISA (Section 4.5)
resulting in better certainty of critical loads. Biological endpoints included in the
evaluations include physiological and community responses of trees and other vegetation
(such as lichens), soil biota, and fauna.
The following section summarizes the main effects of N and S deposition on terrestrial
ecosystems.
1.5.1 Soil Biogeochemistry
In the 2008 ISA, evidence was sufficient to infer causal relationships between acidifying
deposition and changes in terrestrial biogeochemistry and between N deposition and
terrestrial biogeochemical cycling of N. There is new evidence of how deposition
contributes to total loading in ecosystems, as well as new information from addition,
gradient, and time-series studies characterizing how deposition affects soil pools and
processes. Much of the new work focuses on the effects of N deposition, with relatively
little work focusing on S deposition. Soil N enrichment and soil acidification occur in
sensitive ecosystems across the U.S. at present levels of deposition. Decreasing S
emissions have led to early signs of recovery from acidification in some Northeastern
watersheds, but areas in the Southeast do not show recovery. Because deposition rates of
total N (NOy + NHx) are relatively unchanged across much of the CONUS
(Section 1.1.1). there are no signs of recovery from N enrichment effects. Critical load
determinations have been made at the ecoregion scale for NOs leaching. Critical loads
for biological effects are summarized below (Sections 1.5.1.2 and 1.5.3.3). The body of
evidence is sufficient to infer a causal relationship between N and S deposition and
alteration of soil biogeochemistry in terrestrial ecosystems, which is consistent with
the conclusions of the 2008 ISA.
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1.5.1.1
Soil Processes and Indicators
Deposition ofN or N + S alters soil chemistry, which can have cascading effects on
aquatic ecosystems (Chapter 7-Chaptcr 10). Soil acidification is a natural process that
can be accelerated by N or S deposition. Deposition in the forms of HNO3 and H2SO4 can
directly acidify soils; however, deposition of reduced forms of N (e.g., NHx) can also
cause soil acidification by releasing hydrogen ions (H+) during the microbial oxidation of
NH4+ to NO3 . There are a number of soil geochemical processes associated with
acidification (Table 1-2). Base cations counterbalance acid anions. Base cations are
added to the soil solution by weathering and atmospheric deposition and are removed by
leaching and biological uptake. Where acidifying deposition rates are high relative to
base cation input, this deposition can deplete exchangeable base cation pools in soils.
There are several useful indicators of soil acidification (Table 1-2) that have quantitative
relationships to biological responses (Chapter 5).
Table 1-2 Summary of key soil geochemical processes and indicators
associated with eutrophication and acidification.
Endpoint
N-Driven
Nutrient
Enrichment
Acidification
The Effect of Deposition
PROCESS
N saturation
X
X
New empirical evidence suggests revising the N saturation
concept, specifically it is now observed that NO3" leaching
can occur even if the ecosystem N capacity to retain N has
not yet been saturated.
Soil N accumulation
X
X
New meta-analysis across ecosystem types confirms
inorganic soil NO3" concentration increases with N addition.
New gradient study confirms that N concentration increases
with N deposition. New addition study confirms increased
soil N accumulation.
NO3" Leaching
X
X
New meta-analysis confirms leaching increases with N
additions. Regional-scale gradient analyses: <8 kg N/ha/yr
onset of leaching; <1 kg N/ha/yr in European forests; in the
NE U.S., 90% retention for sites receiving 7 kg N/ha/yr to
60% retention for sites receiving 11 kg N/ha/yr.
New addition study: 9-14 kg N/ha/yr increase in inorganic N
concentrations.
New USFS critical loads for the onset of leaching: 8-10 kg
N/ha/yr in eastern and western U.S., 17 kg N/ha/yr in the
Sierra Nevada and San Bernardino Mountains.
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Table 1-2 (Continued): Summary of key soil geochemical processes and
indicators associated with eutrophication and
acidification.
N-Driven
Nutrient
Endpoint Enrichment Acidification The Effect of Deposition
S accumulation and X Some soils (notably in many watersheds in the SE U.S.)
adsorption have the capacity to adsorb substantial quantities of S, with
essentially no acidification of drainage water. Nevertheless,
S adsorption capacity is finite, and under continual high S
deposition loading, the adsorptive capacity of soil will
eventually be exceeded.
New studies of 27 watersheds in the SE indicate most will
begin releasing SO42" in the next two decades; NE
watersheds show a net loss of S from soils now in response
to decreased levels of atmospheric S deposition.
SC>42"leaching X Atmospheric S deposition generally increases leaching of
SO42" to surface waters. The amount of deposition that
causes the onset of leaching varies across the landscape.
Base cation X Base cation (Ca, Mg, K, Na) release from soil particles to the
release/depletion soil solution occurs in response to the input of acid anions
(SO42" and NO3") from deposition.
New studies confirm base cation depletion continues to
occur in the Rocky Mountains (threshold 28 kg N/ha/yr) and
in U.K grasslands, while in a NE forest, 17 years of N
addition did not cause further depletion. A meta-analysis
suggests cation depletion early after increased deposition of
acid anions, but this depletion tapers off with time.
Al mobilization X The threshold for inorganic Al mobilization from soil is
<15-20% soil base saturation. This is an extremely
important effect of acidifying deposition because inorganic
monomeric Al is toxic to biota (Chapter 4 and Chapter 8).
Inorganic Al is minimally soluble at pH 6.0, but solubility
increases steeply at pH below 5.5.
There have been no new studies on Al mobilization.
Nitrification X X Nitrification releases 2 mol hydrogen ion (H+) per mol NhV
converted to NO3", acidifying soils. As soil inorganic N
accumulates, net nitrification rates often increase, and NO3"
can leach from the ecosystem.
New N gradient and meta-analysis studies confirm N
addition increases nitrification.
Denitrification X Denitrification is the microbial reduction of NO3" to NO2",
NO, the greenhouse gas N2O, and N2, which occurs under
anaerobic conditions. In Europe, soil switched from a source
to a sink after two decades of N deposition exclusion. New
meta-analysis confirms N addition increases denitrification
rates.
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Table 1-2 (Continued): Summary of key soil geochemical processes and
indicators associated with eutrophication and
acidification.
Endpoint
N-Driven
Nutrient
Enrichment
Acidification
The Effect of Deposition
DOC Leaching
X
X
Acidity of some surface waters is partly regulated by DOC
concentrations. Soil acidification can suppress the natural
production of DOC. In recent years, the DOC concentration
of some lakes and streams has risen, with adjacent
terrestrial ecosystems as the DOC source.
New studies include a meta-analysis and field addition
studies.
Decomposition
X
X
The addition of N can stimulate the breakdown of labile
compounds that degrade during the initial stages of
decomposition, but added N can suppress the
decomposition of more recalcitrant material.
There are new addition studies and meta-analysis on
mechanisms and response trends.
INDICATOR
Soil [N]
X
X
This is a result of increasing soil N accumulation and
indicates N in soils that may be assimilated by organisms or
mobilized via leaching.
Soil C:N Ratio
X
X
Decreasing soil C:N linked to changes in decomposition and
increases in nitrification and NO3" leaching.
<20-25 causes increased nitrification and elevated risk of
NO3" leaching in the U.S. and <25-30 for increased NO3"
leaching in Europe.
Soil base saturation
X
Increasing N + S deposition decreases the soil pool of
exchangeable base cations.
<15-20% exchange ion chemistry is dominated by inorganic
Al and mav cause iniurv to veaetation (see Chapter 5).
Soil Bc:AI ratio
X
Increasing N + S deposition decreases the soil pool of
exchangeable base cations, often decreasing the Ca:AI
ratio.
Ca:AI <1.0 causes physiological stress, decreased growth,
and mortality of sensitive plant species (see Chapter 5).
Fungi-to-bacteria ratio
X
New indicator: Increasing N deposition decreases the
fungi-to-bacteria ratio and causes a transition from N to C
limitation among soil food webs.
Al = aluminum; Al3+ = aluminum(lll); Be = base cations; C = carbon; Ca = calcium; DOC = dissolved organic carbon; H+ = hydrogen
ion; ha = hectare; K = potassium; kg = kilogram; Mg = magnesium; N = nitrogen; N2 = molecular (atmospheric) nitrogen;
N20 = nitrous oxide; Na = sodium; NE = northeastern; NH4+ = ammonium; NO = nitric oxide; N02" = nitrite; N03" = nitrate;
S = sulfur; SE = southeastern; S042" = sulfate; U.S. = United States; USFS = U.S. Forest Service; U.K. = United Kingdom;
yr = year.
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Some of the same processes and indicators associated with acidification are also
associated with the N enrichment of soils in response to the input of exogenous N
(Section 4.3V The 2008 ISA documented that the increase in global reactive N (defined
as NOy + NHx + organic N) that occurred over the previous century was largely due to
three main causes: (1) widespread cultivation of crops that promote conversion of N2 gas
to organic N through biological N fixation, (2) fossil fuel combustion converting
atmospheric N2 and fossil N to NOx, and (3) the Haber-Bosch process, which converts
nonreactive N2 to reactive N to sustain food production and some industrial activities
(Gallowav et al.. 2003; Gallowav and Cowling. 2002).
The 2008 ISA documented that often soils contain >85% of the total ecosystem N,
primarily as organic matter. Atmospheric deposition can increase soil N. Soil N
accumulation is linked to increased N leaching and decreased retention of N. Critical
loads for the onset of elevated NO3 leaching are given in Section 4.6.2.2.
The 2008 ISA described the conceptual model of N saturation, which occurs when N
input rates to terrestrial ecosystems exceed the uptake capacity of the soils and biota, and
is indicated by the onset of increased soil N leaching. However, more recent work has
revised the N saturation model in response to observations where N leaching resulted
from N input rates that are faster than vegetation and soil uptake rates, thus distinguishing
capacity N saturation and kinetic N saturation. Budgets from 83 forested watersheds in
the northeast U.S. show that N retention averages 76% of the incoming atmospheric N
deposition and decreases from 90% retention at 7 kg N/ha/yr of deposition to 60%
retention at 11 kg N/ha/yr of deposition.
The 2008 ISA documented that N enrichment is associated with changes in microbially
mediated biogeochemical processes, including nitrification, denitrification, and
decomposition (Section 4.3). The 2008 ISA also documented that the addition ofN can
increase nitrification (the microbial conversion of NH4+ to NO3 ), which contributes to
soil acidification. Nitrification is often stimulated in soils with a C:N ratio below
approximately 20 to 25, which can be decreased by N deposition. The NO.? created by
nitrification may be leached or denitrified. Denitrification is the microbial reduction of
N03 to NO2 , NO, the greenhouse gas N2O, and N2, which occurs under anaerobic
conditions. Several syntheses have been published since 2008 evaluating N addition
effects on denitrification and nitrification in terrestrial ecosystems. A new meta-analysis
shows N addition substantially increases denitrification from many types of ecosystems
(e.g., coniferous forest, deciduous forest, tropical forest, wetland, grassland), except
heathlands. Among five chemical forms of N studied, NO3 showed the strongest
stimulation of N2O emission. Using data extracted from 206 peer-reviewed papers, a
second meta-analysis observed that the largest changes in the ecosystem N cycle caused
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by N addition were increased nitrification (154%), N2O emissions (134%), and
denitrification (84%).
About one-half of C fixed annually during photosynthesis by terrestrial vegetation is
allocated to belowground C processes; therefore, it is important to understand how N
affects belowground C to better understand changes in plant physiology, plant growth,
and ecosystem C cycling (Chapter 6). Many studies have shown that changes in
belowground C cycling do not always parallel shifts in aboveground C cycling, making
extrapolation from aboveground responses to belowground processes inappropriate. New
studies published since 2008 (Section 4.3.10) have found that generally, N addition
increases aboveground litter inputs (+20%), inhibits CO2 loss via microbial respiration
(-8%), and decreases microbial biomass carbon (-20%). Dissolved organic carbon
concentrations increased (+18%), suggesting C leaching loss may increase. The addition
of N increased the C pool size within the soil organic horizon (+17%), attributed to both
increased litter input and decreased decomposition (inferred from the lower microbial
respiration rates).
The effect of N on organic matter decomposition is an active area of research
(Section 4.3.9). Decomposition primarily occurs through the leaching of soluble
chemicals, the depolymerization of complex biomolecules by microbial extracellular
enzymes, and the microbial assimilation of nutrients. Bacteria and fungi are the primary
microbial decomposers of organic matter. Both microbial community composition (see
Chapter 6) and microbial enzyme activity can respond dynamically to shifts in inorganic
N and substrate availability. Within the literature, litter decay rates have long been
correlated with the ratio of N to C or lignin in litter. Based on these observations, it could
be assumed that added N would stimulate decomposition and the loss of C from soil
pools. However, the stimulatory effects of N on decomposition are limited to the early
stages of mass loss and the addition of N slows the later stages of decomposition that are
controlled by the degradation of recalcitrant compounds. In general, N additions decrease
respiration from soil heterotrophs, but do not necessarily decrease total soil respiration
because heterotrophic respiration accounts for only a portion of the soil CO2 efflux.
1.5.1.2 National-Scale Sensitivity and Critical Loads
As of the 2008 ISA, the regions of the U.S. with abundant acid-sensitive soils had been
well delineated. These acid-sensitive ecosystems are generally located in mountainous
terrain in the eastern U.S. and are underlain by bedrock that is resistant to weathering.
However, a similar delineation of the areas sensitive to the eutrophication effects of N
had not yet been completed. There is strong evidence demonstrating that biogeochemical
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sensitivity to deposition-driven eutrophication and acidification is the result of historical
loading, geologic/soil conditions (e.g., mineral weathering and S adsorption), and/or
natural sources of N and S loading to the system. There is no single deposition level
applicable to all ecosystems in the U.S. that will mark the onset of eutrophication or
acidification.
Several new publications comment on recovery from terrestrial acidification (NAPAP.
2011). specifically in the northeastern U.S. and the lack of recovery in the southern
Appalachian Mountains. New ecoregion-scale terrestrial critical loads for NO3 leaching
were published in 2011 and have been updated by more recent published work. However,
the most recent national-scale assessment of soil acidification was published in 2007.
1.5.2 Biological Effects of Terrestrial Nitrogen Enrichment
The enrichment of terrestrial ecosystems by N deposition often increases plant
productivity and causes changes in physiology and growth rates that vary among species.
This combination of effects can alter the composition and decrease diversity of terrestrial
communities by transforming competitive interactions between species and changing the
availability of other essential resources, including light, water, and nutrients. Because N
deposition can cause both eutrophication and acidification and these processes can occur
simultaneously, the relationship between N deposition and community composition has
often been derived empirically. Many of the effects of N deposition are similar across
ecosystems and life forms because N is an essential macronutrient, but the composition
and magnitude of how these effects are expressed within an ecosystem can differ as a
result of biotic and abiotic influences. Consequently, as with the 2008 ISA, we have
grouped the effects of N deposition on physiology and biodiversity by biome (e.g., forest,
tundra, grassland, and arid lands), with further framing by life form (e.g., plants,
microorganisms) and functional groups (e.g., trees, herbaceous plants). In comparison,
the broadest CLs created by the scientific community are at the ecoregion level, which
typically subdivide biomes based on ecological, climatological, and geological
differences.
The 2008 ISA documented consistent evidence that N additions increased plant
productivity across a wide range of terrestrial ecosystems. Since 2008, a large body of
new research on the biological effects of added N in terrestrial ecosystems has been
published from investigations of plant and microbial physiology, long-term
ecosystem-scale N addition experiments, regional and continental-scale monitoring
studies, and syntheses. These studies have been conducted in ecosystems representing
biomes in the U.S., including tundra, grasslands, arid and semiarid lands, and tropical,
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temperate, and boreal forests. As a consequence of the breadth of this research, there is a
strong mechanistic and empirical understanding for many of the biological effects of
added N. This body of evidence is sufficient to infer a causal relationship between N
deposition and the alteration of the physiology and growth of terrestrial organisms
and the productivity of terrestrial ecosystems.
The varying effects of N deposition on the growth and physiology of individual species
have consequence for biodiversity. In the 2008 ISA, evidence was sufficient to infer a
causal relationship between N deposition and the alteration of species richness, species
composition, and biodiversity in terrestrial ecosystems. The 2008 ISA documented
consistent evidence of reduced species richness and altered community composition from
N addition studies in the U.S. and N deposition gradient studies in Europe for grassland
plant diversity, forest understory plants, and forest mycorrhizal fungi. There was also
consistent evidence of altered plant and mycorrhizal community composition from N
addition studies in arid and semiarid ecosystems, particularly in southern California.
There was little evidence of changes in forest overstory tree composition. Since the 2008
ISA, new research techniques have been developed to understand community
composition, a larger number of communities have been surveyed, and new regional and
continental-scale studies have made it possible to isolate the influence of N deposition
from other environmental factors. This new research has provided more extensive and
mechanistic evidence, and combined with the findings of the 2008 ISA, this body of
evidence is sufficient to infer a causal relationship between N deposition and the
alteration of species richness, community composition, and biodiversity in
terrestrial ecosystems.
1.5.2.1 Physiology and Biodiversity
At the time of the 2008 ISA, terrestrial ecologists had used meta-analyses to broadly
quantify the effects N deposition can have on the growth of terrestrial plants, concluding
that N additions stimulated plant productivity by 20-30% in grasslands, forests, tundra,
and wetlands, increased aboveground productivity in herbaceous plant communities,
altered plant tissue chemistry, decreased biomass of mycorrhizal fungi, and altered litter
decomposition (Section 6.1. IV Recent research has provided further coherent and
consistent evidence that N additions stimulate plant growth and productivity, but this
research is still dominated by studies of temperate ecosystems and aboveground plant
responses (Figure 6-1 and Figure 6-2).
In the 2008 ISA, the positive plant growth response to N deposition was attributed to
higher rates of photosynthesis. However, evidence for this is mixed: increases in
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photosynthesis following N additions have been observed across a variety of plant
functional types, but higher rates of photosynthesis have not been consistently observed
in response to chronic N additions meant to simulate atmospheric deposition. There is
new support for another mechanism that would increase aboveground growth: decreases
in the quantity of C allocated by plants to roots, mycorrhizae, and root exudation. There
was evidence in the 2008 ISA that N additions increase aboveground biomass more than
belowground biomass, raising the shoot-to-root ratio among plants, but evidence is now
more consistent and widespread. Plants invest substantial amounts of C to support
mycorrhizal fungi, but there is evidence that this investment declines when N is added to
terrestrial ecosystems. Similarly, there is mounting evidence that plants can increase root
exudation as N availability decreases.
Evidence that biodiversity change can be a consequence of N deposition has accumulated
since 2008 and includes new information for major taxonomic groups including
herbaceous plants, overstory trees, and two groups of symbionts: lichens and
mycorrhizae. There is now more widespread evidence of decreases in lichen species
richness as the result of N deposition in the U.S. There are direct observations that N
deposition in the U.S. is changing mycorrhizal community composition and altering
herbaceous plant species richness across a broad range of ecosystems, including forests,
grasslands, arid and semiarid ecosystems, and alpine tundra. In addition, based on
changes in mortality and growth rates of dominant tree species, there is also strong
indirect evidence that N deposition is altering overstory tree community composition.
A substantial body of research linking changes in biodiversity to shifts in N availability
has been developed. Within this body of research, there is evidence that (1) rare species
are particularly vulnerable to loss and (2) organisms with specific traits will have either
positive or negative responses in growth and survival when N is added. Both mechanisms
can operate simultaneously and both mechanisms tie the changes in physiology, growth,
and productivity caused by increased N availability to declines in biodiversity.
As noted in Chapter 4. soil microorganisms have important roles in regulating N and C
cycling. There are several mechanisms to alter soil microbial biomass and physiology,
including changes in soil pH, increases in inorganic N availability, shifts in soil food
webs, and changes in the quantity and quality of available C. There were some
observations in the 2008 ISA that added N decreases microbial biomass, but there is now
more coherent evidence that added N broadly decreases microbial biomass, microbial
biomass C, and microbial biomass N (Table 6-4).
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1.5.2.1.1 Forests
Forests occur within every U.S. state, but are most abundant in the eastern U.S., montane
and coastal portions of the western U.S., and Alaska. The distribution of forests is bound
by water availability, cold temperatures, and land management. In the 2008 ISA, there
was consistent evidence that N additions stimulated forest productivity, but these
responses varied widely and included both neutral and negative effects of N additions on
tree growth. However, there had been no empirical analyses of how atmospheric N
deposition altered forest productivity in the U.S.at broad scales. There was no
information regarding whether N deposition had any impact on the diversity and
composition of forest overstory trees as of the 2008 ISA, but there was evidence for
changes in the composition of herbaceous vegetation, epiphytic lichens, and microbial
communities. The addition of new research since the 2008 ISA provides coherent
evidence that N deposition alters the physiology, growth, and community composition of
overstory trees, understory plants, lichens, mycorrhizal fungi, soil microorganisms, and
arthropods.
As of the 2008 ISA, most long-term N addition experiments were located in temperate
forests in the northeastern U.S. or in temperate or boreal forests in Europe. In these
studies, conifer species were less likely than broadleaf species to exhibit positive growth
responses to added N and more frequently exhibited increased mortality and decreased
growth. Since the 2008 ISA, a number of new observations from experiments, forest
inventory studies, model simulations, and data synthesis efforts have been published
quantifying increases in forest net primary productivity (NPP), net ecosystem
productivity (NEP), and ecosystem C storage (Section 6.1.2; Figure 6-3). Overall, there is
consistent evidence that N deposition increases forest ecosystem C storage, including
specific evidence that current rates of N deposition in the northeastern U.S. broadly
stimulate aboveground forest productivity.
Many of the observations in the 2008 ISA about how long-term N additions affected
forest mortality and aboveground productivity were reinforced by more recent research,
including long-term forest inventory data collected from across the eastern U.S. and in
Europe. Growth and mortality responses have apparent links to plant functional traits; for
example, several conifer species common to the northeastern U.S. exhibited negative
growth responses in both long-term N addition experiments and in an analysis of forest
inventory data. Tree species hosting arbuscular mycorrhizal fungi also showed increased
growth in response to N additions and N deposition.
Analyses of forest inventory analyses from the eastern U.S. have not directly assessed
changes in overstory tree composition, but the evidence of species-specific effects on
growth and mortality observed in these studies suggest that changes in community
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composition are occurring. This represents an advance in our understanding from the
time of the 2008 ISA, when the impact of N deposition on the composition of forest
overstory trees was unclear.
In comparison, there is direct evidence that N deposition is altering the composition of
forest understory plant communities. The evidence for altered forest understory plant
communities (also known as herbaceous layer or groundcover vegetation) comes from
both the 2008 ISA and from the more recent literature. Changes in understory plant
communities have been observed in monitoring plots along atmospheric N deposition
gradients in the U.S. and in Europe. In Europe, forest understory plant communities have
shifted toward more nutrient-demanding and shade-tolerant plant species.
Higher rates of aboveground tree growth in response to N deposition might be due to
shifts in C allocation away from belowground processes. Changes in C allocation in
response to additional N have been accompanied by decreases in the abundance of
mycorrhizal fungi and changes in mycorrhizal community composition (Table 6-2. Table
6-14). Evidence for composition change is particularly abundant in ectomycorrhizal
fungal communities (Table 6-14); there are fewer observations of how arbuscular
mycorrhizal fungal communities change in response to N additions (Table 6-3; Table
6-16). There are also numerous observations of altered total microbial (including
bacterial) biomass and community composition. For microbial biomass, most studies
identified since 2008 observed either negative or neutral effects ofN additions, consistent
with results of syntheses published before the 2008 ISA (Table 6-4). Changes in soil
microbial community composition were identified along an N deposition gradient in
Europe and in all three N addition studies. The effects of N additions on individual
microbial taxonomic groups (bacteria, archaea, fungi, etc.) have been less consistent
(Table 6-15). Overall, there is coherent evidence thatN additions decrease total microbial
biomass and alter microbial communities in forest soils.
Within soil food webs, soil microorganisms have both direct and indirect links to
arthropods. Because arthropods feed upon both microorganism and litter, they can be
important regulators of decomposition, nutrient cycling, and forest productivity. Several
studies have examined the response of forest arthropod communities to added N,
including a group of studies on insect herbivores conducted in southern California (Table
6-17). There is coherent evidence that N additions can alter forest arthropod
communities.
Epiphytic lichens have long been recognized as sensitive to air pollution. Although these
organisms often make up a small portion of forest biomass, they have important roles in
hydrologic cycling, nutrient cycling, and as sources of food and habitat for other species.
New research on lichen community composition identified since the 2008 ISA has further
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added to the consistent and coherent evidence that lichen communities in the U.S. and
Europe are sensitive to current levels of atmospheric N deposition (Section 6.2.6; Table
6-23). In particular, there are abundant data from the U.S. Forest Service's Forest
Inventory and Analysis Program on the abundance of lichens throughout the U.S. Shifts
in lichen community composition that are clearly attributable to atmospheric N pollution
have been observed in forests throughout the West Coast, in the Rocky Mountains, and in
southeastern Alaska. Shifts in epiphytic lichen growth or physiology have been observed
along atmospheric N deposition gradients in the highly impacted area of southern
California, but also in more remote locales such as Wyoming and southeastern Alaska,
(Table 6-5). A number of experimental N studies have also created more detailed insight
into changes in lichen physiology processes. Overall, there is widespread evidence from
forests that N deposition can alter the growth, physiology, and biodiversity of trees,
herbaceous plants, lichens, soil microorganisms, and arthropods.
1.5.2.1.2 Tundra
Within the U.S., tundra ecosystems are limited to Arctic ecosystems in Alaska and to
relatively isolated, high elevation sites in the West. Although these ecosystems tend to be
remote, the influence of atmospheric N deposition is distinct and there was evidence in
the 2008 ISA indicating that alpine tundra plant communities were sensitive to
atmospheric N deposition. Organisms there may be more sensitive to N deposition
because of the unique nature of N cycling in these ecosystems, which tend to have limited
inorganic N availability. Since the 2008 ISA, numerous studies of tundra physiological,
productivity, and community composition responses to added N have been published,
providing further evidence that N deposition alters the growth and physiology of alpine
plant communities, including vascular plants (herbaceous and woody), bryophytes, and
lichens (Section 6.1.3). as well as evidence of altered soil microbial communities (Table
6-19; Table 6-8).
As in forests, increases in foliar N content in response to additional N are widespread in
tundra plant communities (Table 6-5; Table 6-6). Higher tissue N concentrations in
response to added N were observed in multiple studies for vascular plants, bryophytes,
and lichens. The 2008 ISA noted that plant growth and biomass responses tended to be
species specific. Subsequent studies have confirmed this result (Table 6-6). showing
varying responses to added N among ecosystem types, plant functional groups, and
species. Whereas vascular plants tend to show a positive response to added N, both
bryophytes and lichens tend to decrease in biomass and cover (Table 6-5; Table 6-6).
Given the varying effects of N addition on species physiology and growth, it is
unsurprising that there have also been numerous observations of N addition impacts on
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species richness, species diversity, and community composition among vascular plants,
bryophytes, and lichens in alpine and Arctic tundra ecosystems (Section 6.2.3; Table
6-18). Within the U.S., these observations included effects of N additions on plant
community composition in Colorado and Washington. In northern Europe, decreases in
plant species richness along atmospheric N deposition gradients have been documented.
Overall, this new research has provided further evidence that experimental N additions
can alter plant biodiversity in alpine and Arctic tundra ecosystems and has provided new
evidence that current rates of atmospheric N deposition in Europe are associated with a
loss of plant species richness in these ecosystems.
There are relatively few observations regarding the effect of N additions on total
microbial biomass or the biomass response of individual microbial taxonomic groups in
tundra ecosystems; these results have also been largely inconsistent. However, new
research has provided coherent evidence that N additions can alter microbial community
composition in alpine tundra ecosystems (Table 6-19; Table 6-8).
1.5.2.1.3 Grasslands
Grasslands are most prevalent in the central U.S., but are widely distributed across the
U.S. in areas where woody vegetation is excluded by environmental factors or
management. There was widespread evidence at the time of the 2008 ISA that the
growth, physiology, and productivity of grassland plants could be altered by N
deposition. In addition, there were multiple lines of evidence in the 2008 ISA that plant,
mycorrhizal, and microbial communities were sensitive to N inputs. Combined with
subsequent research, there is clear evidence that physiology, growth, and community
composition of plants, mycorrhizae, soil microorganisms, and arthropods are sensitive to
N inputs.
Although NPP can be limited by multiple factors (e.g., water, herbivores, other nutrients)
in all ecosystems, these other limitations tend to be more marked in grasslands than
forests, making it harder to understand and predict the effects of increased N availability.
However, the general response is similar (Section 6.1.4): N additions stimulate NPP and
increase foliar N, and increase allocation to aboveground biomass (increased ratio of
shoot:root mass).
Evidence from the U.S. of grassland plant community composition change in the 2008
ISA was based on N addition studies in Mediterranean grasslands in California and
northern prairie ecosystems. However, large-scale assessments of biodiversity across
observed atmospheric N deposition gradients were restricted to Europe. Recent research
provides further evidence that N deposition reduces grassland biodiversity in the U.S. and
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Europe (Section 6.2.4). Since 2008, there have been direct observations of reduced
species richness along atmospheric N deposition gradients for grasslands in the U.S. and
Europe. These gradient studies have documented an interaction with soil pH, noting that
N deposition causes a greater loss of species richness and a shift in community
composition at sites with lower pH. Together, these findings from deposition gradients in
the U.S. and Europe provide coherent evidence that N deposition causes shifts in plant
community composition and the loss of plant species richness through mechanisms of
both acidification and eutrophication. Experimental studies published since 2008 have
provided more insight into the mechanisms linking changes in plant and microbial
community composition to increased N availability, providing evidence that declines in
species richness increase with time and that competition for resources such as water may
exacerbate the effects of N addition on diversity.
Overall, the additional studies in grassland ecosystems have confirmed that many of the
responses observed in the older N addition studies also occur at present rates of
atmospheric N deposition. These changes include losses in forb species richness (which
make up the majority of grassland biodiversity), greater growth of grass species (which
make up the majority of grassland biomass), changes in reproductive rates, as well as
shifts in mycorrhizal, soil microbial (Table 6-16; Table 6-20). and arthropod populations.
In total, it appears that due to the ubiquity of N limitation in grasslands and the
dominance by fast-growing species that can shift in abundance rapidly (in contrast to
forest trees), grasslands are especially sensitive to N input rates comparable to N
deposition across much of the contiguous U.S.
1.5.2.1.4 Arid and Semiarid
Arid and semiarid ecosystems are abundant in areas of the western U.S. where climate or
orography create conditions that are annually or seasonally dry. At the time of the 2008
ISA, there was a large amount of information available on how N deposition impacted
the growth and physiology of plants and microorganisms in arid and semiarid
ecosystems, and there was coherent evidence that plant communities in these ecosystems
could be altered by the added N. Evidence for these effects was particularly strong in
coastal sage scrub (CSS), chaparral, and Mojave Desert ecosystems in southern
California. Within the CSS ecosystems, N deposition has been linked to increased
mortality in native shrubs, decreased abundance of arbuscular mycorrhizal fungi, higher
cover of invasive annual plants, and increased wildfire activity. Similar increases in
invasive annual plant cover and fire frequency have also been attributed to N deposition
in areas of the Mojave Desert downwind of urban centers in southern California.
Research since 2008 has further documented these effects, with consistent evidence that
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N deposition can impact the physiology, growth, and community composition of plants
and soil microorganisms in arid and semiarid systems.
The impacts of N deposition on physiological and biogeochemical processes in arid and
semiarid ecosystems are even more clearly dependent on moisture availability than in
grasslands (Section 6.1.4V In these ecosystems, inorganic N often accumulates in the soil
during dry periods, and growth and physiological responses to additional N are only
observed when and where sufficient moisture is available. There are two additional
important effects of aridity: (1) higher soil base saturation and pH that buffer these
systems from the acidification effects of N deposition, and (2) spatially patchy nutrient
availability that develops beneath isolated shrub canopies. One important effect of N
deposition on arid and semiarid ecosystems is to decrease the patchiness of nutrient
availability, which promotes the growth of invasive annual plants in the spaces between
the isolated shrubs. The growth of these annual plants creates a more continuous fuel bed
for wildfires, increasing the prevalence of fire and shifting plant community composition
toward more fire-adapted plant species.
Since 2008, there have been observations of increases in aboveground plant biomass or
plant cover observed in the U.S. in the Mojave and Sonoran Deserts, and in southern
California chaparral, and internationally in China and Spain (Section 6.1.5V Given the
linkage to fire, it is notable that there have been multiple observations of increased annual
plant growth in the Mojave Desert in response to added N.
New research has also provided further evidence that N deposition alters plant
communities in arid and semiarid ecosystems, particularly in southern California, but also
in other locations (Section 6.2.5). Many of these studies documented changes in plant
community composition, with fewer observations of plant species loss or changes in plant
diversity. Overall, this body of research has provided consistent and coherent evidence
that N deposition is altering the growth, physiology, and community composition of
plants in arid and semiarid ecosystems. Relative to plants, there are fewer studies of
microbial communities (Table 6-12; Table 6-22). but these studies provided wide
evidence that N additions can alter the abundance, physiology, and community
composition of soil microorganisms in arid and semiarid ecosystems.
1.5.2.2 National-Scale Sensitivity and Critical Loads
The 2008 ISA documented that the most sensitive ecosystems to N nutrient enrichment
from atmospheric N deposition are those that receive high rates of N deposition, are N
limited, or contain species that have evolved in nutrient-poor environments. However,
there had been little quantification of the extent and distribution ofN deposition-sensitive
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terrestrial ecosystems in the U.S. It is now more clear that the factors that govern the
vulnerability of terrestrial ecosystems to N deposition include the degree of N limitation,
rates of N deposition, elevation, species composition, length of growing season, and soil
N retention capacity.
In the 2008 ISA, the effects on individual plant species had not been well studied in the
U.S. More was known about the sensitivity of particular plant communities, based largely
on results obtained in more extensive studies conducted in Europe. Since the 2008 ISA,
substantial work has been done on N CLs for U.S. ecoregions. In the 2008 ISA, there was
no published U.S. national CL assessment. A large body of work has been published on
critical loads for N since the 2008 ISA. The most notable new work is the U.S.
Department of Agriculture-Forest Service (USDA-FS) Assessment of Nitrogen
Deposition Effects and Empirical Critical Loads (Pardo et al.. 201 la). That assessment
was organized by Level 1 ecoregions, and where data were available, CLs calculations
were made for individual ecosystem types (e.g., forests within the Mediterranean
California ecoregion) and life forms (i.e., lichens, mycorrhizal fungi). This ISA largely
follows that structure, reporting terrestrial N CLs for life forms (e.g., herbaceous plants)
within each ecoregion, which are geographically defined areas that divide broader biomes
(e.g., forests) based on distinct physical and biological features (e.g., Northwest Forested
Mountains, Eastern Temperate Forests, etc.).
In general, higher N CLs were often reported for regions with higher ambient N
deposition. One explanation for this pattern is that when ecosystems experience elevated
N deposition, the current condition already represents a change from the condition prior
to elevated N deposition (i.e., a pristine or near-pristine state). This pattern would explain
why the empirical CL is often above the ambient deposition even as that deposition
increases in the same ecosystem type across a region (Pardo etal.. 2011a).
Newer CLs studies are presented in tandem with the CLs reported by Pardo etal. (201 la)
in Table 6-26 and Figure 1-6. The majority of values for new CLs are within the range of
CLs identified by Pardo etal. (201 la). Notably, Simkin et al. (2016) identified a new
lower range of 7.9 kg N/ha/yr, and new lower CLs are denoted for alpine ecosystems in
the Northwest Forested Mountains ecoregion. There are also new CLs for herbaceous
species in two ecoregions that previously had no CL ITable 6-28. (Simkin et al.. 2016)1.
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Temperate Sierras
«-< Mediterranean California
~|j 7.8-9.2 O
j QCB-84
c
North American Deserts
O 5-25 O
Great Plains
Marine West Coast Forest
Eastern Temperate Forests
North(East) Forest
(DO 4-10 O
O
O 4-17
2.5- CD
5-10
•
^ 5 °
U 2.7-9.2
b
o o
17.5
>3 O
4-8
>3 O
|
10 20 30 40 50
kg N/ha/yr
CL = critical load; ha = hectare; kg = kilogram; N = nitrogen; yr = year.
The rectangles indicate the range of CLs designated by Pardo et al. (2011a); the circles indicate new papers that have specified
CLs; data from Table 6-28.
Figure 1-6 Summary of critical loads in the U.S. for shrubs and herbaceous
plants (yellow), trees (blue), lichens (green), and mycorrhizae
(grey).
1.5.3 Biological Effects of Acidification
1 Since publication of the 2008 ISA, the overarching understanding of terrestrial
2 acidification has not appreciably changed. Recent research has confirmed and
3 strengthened this understanding and provided more quantitative information, especially
4 across regional-scale landscapes. A number of studies have evaluated the relationships
5 between soil chemistry indicators of acidification and ecosystem biological endpoints
6 (see Table 5-1). Soil chemistry indicators examined in recent literature include
7 exchangeable base cations, soil pH, exchangeable acidity (H+ and Al), exchangeable
8 Ca:Al ratio, base saturation, and Al concentrations. Biological endpoints included in the
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evaluations consisted of physiological and community responses of trees and other
vegetation, lichens, soil biota, and fauna.
1.5.3.1 Physiology and Growth
In the 2008 ISA, evidence was sufficient to infer a causal relationship between acidifying
deposition and changes in terrestrial biota; the evidence included changes in plant
physiology, plant growth, and terrestrial biodiversity. The physiological effects of
acidification on terrestrial ecosystems in the U.S. were well characterized at the time of
the 2008 ISA and included slower growth and increased mortality among sensitive plant
species. Consistent and coherent evidence from multiple species and studies in 2008
showed that the biological effects of acidification on terrestrial ecosystems were
generally attributable to physiological impairment caused by A1 toxicity and decreased
ability of plant roots to take up base cations (Section 3.2.2.3 of the 2008 ISA). Much of
the new evidence for the negative effects of acidifying deposition comes from Ca
addition experiments, in which the addition of Ca has alleviated many of the negative
plant physiological and growth effects. Consistent with the findings of the 2008 ISA, the
body of evidence is sufficient to infer a causal relationship between acidifying N and
S deposition and the alteration of the physiology and growth of terrestrial organisms
and the productivity of terrestrial ecosystems.
In the 2008 ISA, acidifying deposition, in combination with other stressors, was found to
be a likely contributor to physiological effects that led to the decline of sugar maple (Acer
saccharum) trees occurring in portions of the eastern U.S. with base-poor soils. Studies
since the 2008 ISA support these findings (see Section 5.2.1.1). For example, recent field
studies demonstrated relationships between soil chemical indicator threshold values and
tree responses. Substantial declines in sugar maple regeneration were found at soil base
saturation levels <20%, which is consistent with the range reported in the 2008 ISA. In
new studies, sugar maple showed positive growth and regeneration responses to
increasing exchangeable base cations, base saturation, and soil pH, and negative
relationships with increasing exchangeable Al. In other studies, the growth, regeneration,
and physiological responses of sugar maple to the soil conditions created by acidifying
deposition were reversed or ameliorated by Ca additions. Similarly, the 2008 ISA
reported that processes associated with soil acidification contributed to physiological
stress, high mortality rates, and decreasing growth trends of red spruce (Picea rubens)
trees. New evidence from Ca addition studies provides further support for these
mechanisms (see Section 5.2.1.2). Added Ca reversed or ameliorated many of the
physiological responses to acidification.
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In the 2008 ISA, there was limited information on the effects of acidification on other
tree species. Since the 2008 ISA, research has observed varying physiological sensitivity
to soil acidification among eight eastern U.S. tree species. New studies since the 2008
ISA have also added new information about the effects of acidifying deposition on forest
understory vegetation, grasslands, lichens, and higher trophic level organisms (snails and
salamanders) that support the terrestrial acidification conclusions of the 2008 ISA.
The 2008 ISA noted strong evidence that acidifying deposition could alter terrestrial
community composition and cause a loss of terrestrial biodiversity. The physiological and
growth effects of acidifying deposition are not uniform across species, resulting in altered
species composition and decreased biodiversity whereby sensitive species are replaced by
more tolerant species. For example, increasing soil base cation availability was tied to
greater sugar maple growth and seedling colonization, whereas American beech (Fagus
grandifolia) was relatively more dominant on soils with lower base cation availability
(see Section 5.2.1.3.1). Measurements of soil acid-base chemistry have been used as a
predictor of understory species composition, with 50 understory species associated with
high soil base cation status. In another set of studies, soil acid-base chemistry was
correlated with soil biodiversity and community composition. For example, addition of
Ca resulted in changes in soil bacterial community composition and bacterial community
structure that were correlated with soil exchangeable Ca, pH, and P (see Section 5.2.4).
Based on research included in the 2008 ISA and these new studies, the body of evidence
is sufficient to infer a causal relationship between acidifying N and S deposition and
the alteration of species richness, community composition, and biodiversity in
terrestrial ecosystems.
The sensitivity of soils to acidifying deposition is discussed in detail in Chapter 4. In
general, surficial geology is the principal factor governing the sensitivity of terrestrial
ecosystems soil to acidification from S and N deposition. Other factors that contribute to
the sensitivity of soils to acidifying deposition include topography, soil chemistry, and
land use. Several widely accepted models are currently used in the U.S. to assess the
terrestrial effects of S and N deposition (Section 4.5). These models are typically used to
evaluate acidification effects on biota by assigning a value of a soil parameter that relates
to the onset of a harmful biological effect. Since the 2008 ISA, estimates of base cation
weathering (BCw), which are input to soil acidification models, have improved for
1.5.3.2
Biodiversity
1.5.3.3
National-Scale Sensitivity and Critical Loads
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application in the U.S. yielding new critical loads. Forests of the Adirondack Mountains
of New York, Green Mountains of Vermont, White Mountains of New Hampshire, the
Allegheny Plateau of Pennsylvania, and mountain tops and ridges forest ecosystems in
the southern Appalachians are the regions that are most sensitive to terrestrial
acidification from atmospheric deposition (Section 3.2.4.2 of the 2008 ISA).
Models used to determine critical loads of acidifying deposition included SMB, STA,
MAGIC, ForSAFE-VEG, and empirical models. Several models and extrapolation
methods to estimate BCw rates were also investigated. The PROFILE model was
evaluated as a model to estimate soil BCw rates to support estimates of SMB critical
loads in the U.S. (see Section 4.5). In general, recently published models used soil
solution Bc:Al ranging from 1.0 to 10.0 as an indicator to estimate CLs in North
America.
Ecosystem sensitivities to ambient N and S deposition were also characterized by
developing CLs and exceedances (see Section A5_, Figure 4-10. and Section 5.5).
Calculated CLs for forest plots based on the soil solution Bc:Al of 10.0 in the
northeastern U.S. ranged from 11 to 6,540 eq/ha/yr (eq quantifies the supply of available
H+ ions, combining the acidifying effects of N and S deposition), and 15-98% of these
plot-level CLs were exceeded by N and S deposition. In this region, correlation analyses
showed that the growth of 17 tree species were negatively correlated with CL
exceedance. In Pennsylvania, CLs based on the soil solution Bc:Al of 10.0 for hardwood
forests ranged from 4 to 10,503 eq/ha/yr and were exceeded by estimated N and S
deposition in the year 2002 in 53% of the plots. Several studies found that CL and
exceedance determinations could be influenced by BCw rates, soil chemical indicators, N
retention, tree species-specific base cation uptake, and/or bulk (i.e., wet) versus total
deposition on CL estimates.
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Forest Ecosystems Critical Loads for Acidity
S + N eq/ha/yr
m 170-1,000
HI 1,001-2,000
" ! 2,001-4,000
] 4,001-6,000
i 6,001-8,800
- States
No Data
eq = equivalent; ha = hectare; yr = year.
(A.) McNultv et al. (2007) critical loads are mapped at 1 km2 grids (center map). For uncertainty, see Li and McNultv (2007).
(B.) Duarte et ai. (2013) critical loads are mapped at 4 km2 grids; (C. and D.) Phelan et ai. (2014) critical loads are mapped for each
sampling site (Pennsylvania). McDonnell et al. (2014b): Sullivan et al. (2011b): Sullivan et al. (2011 at critical loads are mapped as a
single point at the center point of the watershed (New York and North Carolina).
Source: http://nadp.sws.uiuc.edu/committees/clad/db/NCLDMapSummarv 2015.pdf
Figure 1-7 Forest ecosystem critical loads for soil acidity related to base
cation soil indicators.
1.6 Freshwater Ecosystem Nitrogen Enrichment and
Acidification
1 For freshwater systems, new evidence reinforces causal findings from the 2008 ISA
2 (Table 1-1). New evidence also expands the scope of existing causal findings to include
3 additional biota affected by N enrichment and acidifying deposition, and supports
4 quantification of these effects with new critical loads. Freshwater systems include lakes
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(lentic systems) and rivers and streams (lotic systems). In freshwater ecosystems, N may
cause N enrichment/eutrophication. Aquatic eutrophication occurs as increased
productivity of algae and aquatic plants, altered nutrient ratios, and sometimes decreased
oxygen levels. Deposition ofN, S, orN + S can cause acidification, which affects
watershed biogeochemical processes and surface water chemistry. Freshwater N
enrichment and acidification take place in sensitive ecosystems across the U.S. at present
levels of deposition and may occur simultaneously in some water bodies. New studies
have added to the body of evidence in the 2008 ISA that N nutrient enrichment and
acidifying deposition alter freshwater biogeochemistry and subsequent biological effects.
Both N enrichment/eutrophication and acidification can impact physiology, survival, and
biodiversity of sensitive aquatic biota. The 2008 ISA and new studies provide examples
of lakes and streams that show signs of eutrophication, especially increased algal growth
and shifts in algal biodiversity, in response to N addition. The current causal statement
for nutrient enrichment effects of N deposition now includes altered algal growth as well
as the endpoints of species richness, species composition, and biodiversity reported in the
2008 ISA (Table 1-1). For biological effects of aquatic acidification, the current causal
statement has been expanded from the 2008 ISA to include the specific endpoints of
physiological impairment, alteration of species richness, community composition, and
biodiversity (Table 1-1). New studies also show that despite reductions in acidifying
deposition, many aquatic ecosystems across the U.S. are still experiencing changes in
ecological structure and functioning at multiple trophic levels. Although there is evidence
for chemical recovery in many previously acidified ecosystems, biological recovery has
been limited.
1.6.1 Freshwater Biogeochemistry
In the 2008 ISA, the body of evidence was sufficient to infer a causal relationship
between N deposition and the alteration of biogeochemical cycling of N in freshwater
aquatic ecosystems. N is deposited directly to the surface water of aquatic ecosystems or
is leached from terrestrial ecosystems. As supported by the 2008 ISA and newer studies,
fate and transport of deposited N depend on characteristics of the catchment and the
receiving waters. Atmospheric deposition of N affects freshwater chemical processes
such as nitrification and denitrification. Chemical indicators of deposition include NOs,
and dissolved inorganic nitrogen (DIN) concentrations in surface waters.
In the 2008 ISA, the evidence was sufficient to infer a causal relationship between N
deposition and the alteration of biogeochemical cycling of C in freshwater systems. N
deposition can fertilize aquatic systems to increase the productivity of photosynthesizing
organisms, resulting in a larger pool of fixed C. Indicators of productivity effects of
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deposition include nutrient ratios and the chl a-to-total phosphorus (P) ratio. N deposition
is commonly the main source of N enrichment to lower order streams and high-elevation
lakes in nonagricultural ecosystems. Recent evidence supports algal growth responses
with N addition.
In the 2008 ISA, the evidence was sufficient to infer a causal relationship between
acidifying deposition (N and S) and changes in biogeochemistry related to aquatic
ecosystems. Acidifying deposition in terrestrial soils affects water chemistry and
biological functioning of hydrologically-connected surface waters, which also receive
deposition directly from the atmosphere. Deposited N and S interact with the aquatic
sediments via oxidation and reduction reactions as well as with biota via biological
uptake. Well-established indicators for acidification of surface water include
concentrations of SO42 , NO3 . and inorganic Al, the sum and surplus of base cations,
acid neutralizing capability (ANC), and pH.
Long-term monitoring studies published since the 2008 ISA detected temporal trends in
surface water chemistry and biological responses. In addition, new laboratory studies and
nutrient bioassays have added to the body of evidence that N nutrient enrichment and
acidifying deposition alter freshwater biogeochemistry and subsequent biological effects.
Recent research on denitrification indicates this process plays a greater role in freshwater
N cycling than was previously recognized. New studies confirm evidence that dissolved
organic carbon (DOC) constrains ANC and pH in some systems, affecting recovery from
acidification. New studies indicate that declining S emissions made S already stored in
ecosystems increasingly influential on aquatic biogeochemistry. New information on
biogeochemical cycling of N and S, acidifying deposition effects on biogeochemical
processes, and changes to chemical indicators of surface water chemistry associated with
acidification and N nutrient enrichment is consistent with the conclusions of the 2008
ISA, and the body of evidence is sufficient to infer a causal relationship between
N and S deposition and the alteration of freshwater biogeochemistry.
1.6.1.1 Freshwater Processes and Indicators
Key processes and geochemical indicators of freshwater N enrichment and acidification
(Table 1-3) link to biological effects. Surface water chemistry integrates the sum of soil
and water processes that occur upstream within a watershed. There are several key
biogeochemical processes that cause or contribute to surface water eutrophication and
acidification, and these processes have been the focus of substantial research over the last
three decades. New studies since the 2008 ISA have further investigated the cycling of S,
N, C, and base cations; these studies substantiate and further quantify earlier findings.
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Nitrogen is deposited as NO3 , NH4 . NH3, and/or organic N. Inorganic N is leached from
terrestrial ecosystems mainly as NO3 . In freshwater ecosystems deposited NH4+ is taken
up by biota or nitrified to NO3 . Elevated NO3 concentrations in lakes and streams are a
biogeochemical indicator that a freshwater system is receiving excess N which will cause
acidification or eutrophication. Qualitatively, northeastern U.S. spatial patterns in surface
waters NO3 concentrations suggest influence by atmospheric N deposition. However,
considerable variation in the relationship between stream chemistry and deposition was
associated with land use and watershed attributes. Glaciers in alpine watersheds of the
western U.S. raise NO3 concentrations in high-elevation lake ecosystems. The higher
concentration of NO3 in glacial meltwater relative to seasonal snowpack meltwater was
attributed to reduced contact with watershed soils and thus to low biological uptake by
microbial communities (Saros et al.. 2010).
Sulfur is deposited mainly as SO42 , which is a mobile anion in many acid-sensitive
watersheds (Chapter 4). Deposition is not the only source of SO42 to drainage waters.
Geologic sources of S, including iron sulfide minerals, can also contribute SO42 to
surface waters. The 2008 ISA found that S deposition alters soil and drainage water
chemistry through sustained leaching of SO42 , associated changes in soil chemistry, and
accumulation of S in the soil through adsorption and biological assimilation.
Table 1-3 Summary of key aquatic geochemical processes and indicators
associated with eutrophication and acidification.
Endpoint
N-Driven
Nutrient
Enrichment
Acidification
The Effect of Deposition
PROCESS
NO3-
Leaching into
water bodies
X
X
See NO3 Leachinq in Table 1-2. Leachinq from terrestrial ecosystems
is an important source of NO3" in freshwater ecosystems
so42~
leaching into
water bodies
X
See SO42" Leachinq in Table 1-2. Leachinq from terrestrial ecosystems
is an important source of SO42" in freshwater ecosystems
Nitrification
X
X
Nitrification is an acidifying process, releasing 2 mol hydrogen ion (H+)
per mol NhV converted to NO3". As the N cycle becomes enriched
through cumulative N addition, net nitrification rates often increase,
and NCVconcentrations increase.
Denitrifi cation
X
Denitrification is the microbial process that transforms NO3" by
anaerobically reducing it to NO2", NO, N2O, and N2.
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Table 1-3 (Continued): Summary of key aquatic geochemical processes and
indicators associated with eutrophication and
acidification.
Endpoint
N-Driven
Nutrient
Enrichment
Acidification
The Effect of Deposition
DOC
Leaching into
water bodies
X
X
See DOC Leachina in Table 1-2. DOC contributes to aciditv of fresh
water ecosystems.
INDICATOR
Surface
water [NO3"]
X
X
Increased N deposition (to surface waters or to terrestrial watershed,
see Table 1-2) increases the water NOa" concentration.
High concentrations of NO3" in lakes and streams, indicative of
terrestrial ecosystem N saturation, have been found at a variety of
locations throuahout the U.S. (U.S. EPA. 2006c: Stoddard. 1994).
Comparison of preindustrial to modern estimates suggested elevated
concentrations in water bodies as a result of N deposition (Fenn et al..
2011b).
Surface
water DIN
X
Increased N deposition increases DIN in most fresh water aquatic
environments, largely as NO3"
Surface
water N:P
ratios
X
Increased N deposition can alter the ratio of N to P in freshwater
systems. Freshwater biota have different nutrient requirements and
changes in nutrient ratios may alter species richness, community
structure, and biodiversity, especially primary producers.
Surface
water [SO42"]
X
Increased S deposition (to surface waters or to terrestrial watershed,
see Table 1-2) increases the water SO42" concentration.
Comparison of preindustrial to modern estimates suggested elevated
concentrations in water bodies as a result of S deposition.
Surface
water [base
cation]
X
Several studies in the eastern U.S. suggested that base cation
concentrations in surface waters increased during the initial phases of
acidification into the 1970s. This trend reversed, and base cations
have decreased in response to decreasing SO42" and NO3"
concentrations. Many base cations (especially Ca2+) are important
nutrients for aquatic biota.
Surface
water ANC
X
Increased N and S deposition decrease ANC. Surface water ANC
correlates with other biologically influential chemical metrics, including
pH, inorganic Al concentration, Ca concentration, and organic acidity.
ANC <50-100 peq/L typically poses a risk for species survival, species
richness, and biodiversity.
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Table 1-3 (Continued): Summary of key aquatic geochemical processes and
indicators associated with eutrophication and
acidification.
Endpoint
N-Driven
Nutrient
Enrichment
Acidification
The Effect of Deposition
Surface
water pH
X
Surface water pH is a common alternative to ANC as an indicator of
acidification, but ANC is a better indicator at pH >6.0, and is less
sensitive to dissolved CO2. N and S deposition are associated with
decreasing pH in surface waters. Increasing pH trends in surface
waters in the northeastern U.S. were common through the 1990s up to
2004, but the rates of change have been small [Driscoll et al. (2001b),
Driscoll et al. (2001a), and Driscoll et al. (2007a)l.
Surface
Water
Inorganic Al
X
Acidifying N and S deposition increase mobilization of inorganic Al
from terrestrial ecosystems into surface water, increasing surface
water concentrations. Inorganic Al in surface waters is (1) widely toxic
and (2) leaches from terrestrial ecosystems only in response to acidic
conditions. Earlier studies demonstrated reduced growth and survival
of various species offish at inorganic Al concentrations between
approximately 2 and 7.5 pmol/L. Most recently, 20% mortality of
young-of-the year brook trout was documented in situ during a 30-day
period with a median inorganic Al concentration of 2 pmol/L.
Al = aluminum; ANC = acid neutralizing capacity; Ca = calcium; C02 = carbon dioxide; DIN = dissolved inorganic nitrogen;
DOC = dissolved organic carbon; H+ = hydrogen ion; ha = hectare; kg = kilogram; L = liter; |jeq = microequivalents;
|jmol = micromole; N = nitrogen; N2 = molecular (atmospheric) nitrogen; N20 = nitrous oxide; NE = northeast; NH4+ = ammonium;
NO = nitric oxide; N02 = nitrogen oxide; N03" = nitrate; P = phosphorus; S = sulfur; S042" = sulfate; U.S. = United States;
USFS = U.S. Forest Service; yr = year.
The 2008 ISA found evidence that nitrification and denitrification occur in both terrestrial
and aquatic environments, and respond to atmospheric inputs of oxidized and reduced N.
New research has substantiated these earlier findings and suggests that denitrification
can, in some situations and locations, play a larger role in removing N from an aquatic
ecosystem than was previously recognized (see Section 1.233).
1.6.1.1.1 Acidification
The acidifying effects of N and S deposition in U.S. waters have been well characterized
for several decades. As reported in the 2008 ISA, acidification occurs as a chronic or
episodic condition. Driscoll et al. (2001b) characterized chronically acidic lakes and
streams by ANC of <0 (j,eq/L throughout the year, while episodic acidification occurs
when ANC falls below 0 (j,eq/L only for hours to weeks. Chronic acidification refers to
average conditions and is often measured as summer and fall chemistry for lakes and as
spring baseflow chemistry for streams. Episodic acidification is associated with
precipitation or snowmelt events when high volumes of drainage water enter watersheds.
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Episodes generally cause changes in at least two of the following chemical parameters:
ANC, pH, base cations, SO42 concentration, NO3 concentration, inorganic A1
concentration, organic acid anions, or DOC. New studies show that both N and S
contributed to episodic acidification over a 20-year period at Bear Brook, Maine (see
Section 7.2.4.3).
The most widely used measure of surface-water acidification is ANC. As reported in the
2008 ISA and newer studies, ANC is the primary chemical indicator of historic
acidification and for predicting the recovery expected from decreasing atmospheric
deposition. As reported in the 2008 ISA, ANC <50-100 (ieq/L typically poses a risk for a
decline in biodiversity (U.S. EPA. 2008a; Driscoll et al. 2001b). ANC correlates with the
surface water constituents (pH, Ca2+, and inorganic Al concentration) that contribute to or
ameliorate acidity effects in biota. Biological indicators of acidification, such as fish
species richness, are presented in Section 8.3.
Surface water pH is another indicator of acidification. It also correlates with surface
water chemical constituents with biotic effects (inorganic Al, Ca2+, and organic acids).
The 2008 ISA included the scientific consensus that low pH can have direct toxic effects
on aquatic species (U.S. EPA. 2008a; Driscoll et al.. 2001b). A pH value of 6.0 is the
level below which biota are at increased risk from acidification (Section 8.3). The 2008
ISA noted increasing trends in pH (decreasing acidification) through the 1990s and up to
2004 in surface waters in the northeastern U.S.
As stated in the 2008 ISA, the concentration of inorganic Al in surface waters is an
especially useful indicator of acidifying deposition because (1) it is toxic to many aquatic
species and (2) it leaches from soils only under acidic conditions including acidifying
deposition, acid mine drainage or from rare geologic deposits. Inorganic Al has
well-documented effects on aquatic biota at specific thresholds (Section 8.3) and is often
the greatest threat to aquatic biota below pH 5.5. The 2008 ISA noted that concentrations
of inorganic Al decreased slightly in some surface waters in the northeastern U.S. in
response to decreased levels of acidifying deposition (U.S. EPA. 2008a). and this trend
has generally continued (Section 7.2.3.10).
Assessments of acidifying deposition effects dating from the 1980s and reported in the
2008 ISA showed SO42 to be the primary acidifying ion in most acid-sensitive waters in
the U.S. The 2008 ISA, presented temporal data that showed a trend of increasing
concentrations of SO42 in surface waters before the period of peak S emissions in the
early 1970s. After the peak SO42 surface water concentrations have decreased in a
widespread trend. The rate of recovery varies by ecosystem and new studies indicate that
as atmospheric S deposition has declined, soils with large stores of historically deposited
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S (e.g., the Blue Ridge Mountain region) have begun releasing this adsorbed S to
drainage water, (Chapter 4) preventing or slowing aquatic recovery.
Change in base cation supply with surface water acidification was highlighted in the
assessment of Charles and Christie (1991) and in the 2008 ISA. Base cations increase in
watersheds via mineral weathering and atmospheric deposition and decrease as a result of
leaching and biotic uptake. Acidification increases base cation leaching from soil and
increases surface water base cation concentrations. In some acidified watersheds, soil
concentrations of Ca2+ and other base cations are substantially reduced from likely
preindustrial levels by historic acidification. This base cation depletion in watersheds
constrains ANC and pH recovery of surface waters. New studies of base cations
corroborated earlier findings and included experiments, modeling, and gradient studies.
A relatively new area of research pertaining to recovery from surface water acidification
has been the observed increase in DOC concentration in many surface waters. Any
changes in DOC concentration or properties will impact the acid-base chemistry of
surface waters. The 2008 ISA reported increasing concentrations of DOC in surface
waters across North America and Europe and concluded that these increases were partly
related to changes in atmospheric deposition of S and N. New research on this topic
suggests that the strength of this response and magnitude of DOC change plays a greater
role in modulating surface water chemistry that was previously understood
(Section 7.2.3.11).
1.6.1.1.2 Nitrogen Enrichment/Eutrophication
Atmospheric N deposition can shift the ratios of essential nutrients in freshwater
ecosystems and alter productivity. The long-held paradigm that freshwaters are P limited
has been replaced by an understanding that both N and P can be limiting, and that
limitation can be dynamic and transient. N deposition in some high deposition lakes has
changed the nutrient status of these lakes from a more-or-less balanced (mainly N
deficient) state to more consistently P limited conditions (see Section 7.2.3.4).
Trophic status is a way of describing freshwater ecology in terms of productivity and
indicates eutrophication, and in some aquatic systems, changes in biodiversity.
Freshwater trophic status indices in the 2008 ISA include ratios comprised of biologically
reactive forms of N or P, or chlorophyll a concentrations (which are a proxy for biomass
of planktonic primary production). New studies showed a shift from N to P limitation of
productivity when the DIN:TP mass ratio increased from 1.5 to 3.4. High DIN:TP,
indicative of P limitation, was found in alpine lakes that received low to moderate N
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deposition and in boreal lakes that received high N deposition (>13 kg N/ha/yr; see
Section 7.2.3.4V
1.6.1.2
Models
Models used to assess the effects of N and S deposition on U.S. ecosystems were
reviewed in the 2008 ISA (Annex A). Several of the models used for terrestrial
ecosystems (see Section 1.5.3.3 such as MAGIC and PnET/BGC are also applicable to
aquatic systems. Both of these models have been widely applied, mainly to relatively
small, upland watersheds. Three other models, Spatially Referenced Regressions on
Watershed Attributes (SPARROW), Watershed Assessment Tool for Evaluating
Reduction Scenarios for Nitrogen (WATERS-N), and Surface Water Assessment Tool
(SWAT) have been used to evaluate N loading to mixed-use watersheds in larger river
systems. A model that has been applied to the analysis of nutrient enrichment in aquatic
systems is AQUATOX, which simulates nutrient dynamics and effects on aquatic biota.
Few new freshwater acidification or eutrophication models have been developed and
published since 2008. A new national water quality modeling system (Hydrologic and
Water Quality System, HAWQS) is under development by Texas A&M University and
USDA for the U.S. EPA's Office of Water (https: //epahawqs .tamu .cdu/). The model is
intended to assist resource managers and policy makers in evaluating the effectiveness of
water pollution control efforts. Freshwater eutrophication and acidification models are
described in greater detail in Section 7.2.5.
In the last NAAQS review of oxides of nitrogen and oxides of sulfur, an aquatic
acidification index (AAI) was developed (1) to relate atmospheric concentrations of SOx
and NOy + NHy to N and S deposition levels using transference ratios (Chapter 2) and
(2) to relate deposition to ANC values, using a modified SSWC model (Chapter 4) and
water chemistry for over 6,000 sites in the U.S. The ANC values where grouped by site
into ecoregions and evaluated by considering the distribution of predicted ANC values
(Scheffe et al.. 2014; U.S. EPA. 201 laV
Sensitivity of lakes, streams, and rivers to biogeochemical changes associated with N and
S deposition varies across the U.S. The biogeochemical sensitivity to acidifying
deposition will be discussed together with biological sensitivity in Section 1.6.2.2.
Sensitivity to N enrichment will be discussed with biological sensitivity in
Section 1.6.3.2.
1.6.1.3
National-Scale Sensitivity
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1.6.2
Biological Effects of Freshwater Acidification
The 2008 ISA found evidence sufficient to infer a causal relationship between acidifying
deposition and changes in aquatic biota, including strong evidence that acidified aquatic
habitats had lower species richness among fishes, macroinvertebrates, and phytoplankton.
The effects of acidifying deposition on aquatic ecosystems also include physiological
impairment or mortality of sensitive species and shifts in biodiversity of both flora and
fauna. Organisms at all trophic levels are affected by acidification, with clear linkages to
chemical indicators for effects on algae, benthic invertebrates, and fish (Table S-IO).
Biological effects are primarily attributable to low pH and high inorganic A1
concentration. ANC integrates chemical components of acidification (Table 1-2). and
surface water acidification models project ANC rather than pH and inorganic A1
concentrations. However, ANC does not directly alter the health of biota.
Effects of acidification on fish species are especially well characterized and many species
are harmed. Both in situ and lifestage experiments in fish support thresholds of chemical
indicators for biological effects. Most of these effects were documented in a rigorous
review of acidification effects on aquatic biota that was included in the 2008 ISA.
Fundamental understanding of mechanisms and biological effects has not changed, and
new studies support findings of the 2008 ISA. New studies also show that despite
reductions in acidifying deposition, alterations in aquatic biodiversity and ecosystem
functioning caused by acidification persist. Although there is evidence for chemical
recovery in many ecosystems, biological recovery has been limited (Section 1.6.2.2V
New research is consistent with the causal determination in the 2008 ISA and has
strengthened the evidence base for these effects. The current causal statement has been
expanded to include specific endpoints of physiological impairment, as well as effects at
higher levels of biological organization (Table 1-1). The body of evidence is sufficient
to infer a causal relationship between acidifying deposition and changes in biota
including physiological impairment and alteration of species richness, community
composition, and biodiversity in freshwater ecosystems.
1.6.2.1 Physiology and Biodiversity Effects
The deterioration in water quality caused by acidification affects the physiology,
survivorship, and biodiversity of many species from several taxonomic groups and at
multiple trophic levels. As stated in the 2008 ISA, biological effects are primarily
attributable to low pH (or ANC) and high inorganic A1 concentrations under chronic or
episodic acidic conditions. During acidification episodes, water chemistry may exceed
the acid tolerance of resident aquatic biota, with effects that include fish mortalities,
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changes in species composition, and declines in species richness across multiple taxa.
New effects thresholds have been identified for aquatic organisms consistent with
observations in the 2008 ISA (Table 8-10). New evidence is congruent with findings in
the 2008 ISA that high levels of acidification (to pH values below 5 and ANC lower than
the range of 50 to 100 |icq/L) eliminate sensitive species from freshwater streams. This
information is reviewed below.
1.6.2.1.1 Primary Producers
Phytoplankton, or suspended algae, play an important role in freshwater systems as
primary producers in the aquatic food web. These photosynthetic organisms vary in
tolerance of acidic conditions and include diatoms, cyanobacteria, dinoflagellates, and
other algal groups. The 2008 ISA reported reduced species richness of freshwater
plankton in response to acidification-related decreases in pH and increases in inorganic
Al. Effects were most prevalent when pH decreased to the pH 5 to 6 range. Since the
2008 ISA, several paleolimnological and field studies have further linked phytoplankton
community shifts to chemical indicators of acidification (Section 8.3.IV For example,
Lacoul etal. (2011) reviewed information on the effects of acidification and observed
that the largest declines in phytoplankton species richness occur over a pH range of 4.7 to
5.6 in Atlantic Canada.
1.6.2.1.2 Zooplankton
Zooplankton comprise many groups of freshwater unicellular and multicellular organisms
including protozoans, rotifers, cladocerans, and copepods. Decreases in ANC and pH and
increases in inorganic Al concentration were shown to contribute to the loss of
zooplankton species or abundance in lakes. In the 2008 ISA, thresholds for zooplankton
community alteration were between pH 5 and 6. In the Adirondacks, a decrease in pH
from 6 to 5 decreased zooplankton richness in lakes, and at ANC <0, zooplankton
richness was only 45% of richness in unacidified lakes. Newer studies support effects in a
similar pH range (see Section 8.3.1.2).
1.6.2.1.3 Benthic Invertebrates
Acidification has strong impacts on aquatic invertebrates, as H+ and Al are directly toxic
to sediment-associated invertebrates such as bivalves, worms, gastropods, and insect
larvae. In the 2008 ISA and in new studies in Section 8.3.3. decreases in ANC and pH
and increases in inorganic Al concentration contribute to declines in abundance or
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extirpation of benthic invertebrate species in streams. Acidification to pH values below 5
eliminates mayflies (Ephemeroptera), a taxa indicative of stream water quality, along
with other aquatic organisms. Since the 2008 ISA, a survey of benthic macroinvertebrates
by Baldigo et al. (2009) in the Adirondack Mountains indicated that macroinvertebrate
communities were intact at pH above 6.4, with moderate acidification effects at pH 5.1 to
5.7, and severe acidification effects at pH less than 5.1. Thresholds of pH 5.2 to 6.1 were
identified for sensitive invertebrates from Atlantic Canada.
1.6.2.1.4 Fish
The effects of low pH and ANC and of high inorganic Al concentrations have been well
characterized in fish for many decades (Section 8.3.6). The 2008 ISA reported that
acidification impairs gill function and can cause respiratory and circulatory failure in fish.
Sensitivity to pH and inorganic Al varies among fish species, and among lifestages within
species, with early lifestages more sensitive to acidification. The most commonly studied
species were brown trout (Salmo trutta), brook trout (Salvelinus fontinalis), and Atlantic
salmon {Salmo salar). Studies published since the 2008 ISA add to the existing
information on sublethal effects confirming variation in sensitivity among lifestages
(Section 8.3.6.IV Since 2008, new studies include acidification effects upon migratory
activities and upon behavior. For example, a recent study assessed smolts moving
downstream in well-buffered and acid-impacted migration corridors in the northeastern
U.S. In the acid-impacted river basin, fish had elevated gill Al and lower gill
Na/K-ATPase activity indicating physiological impairment. New studies on fish show
behavioral effects at pH <6.6 (Section 8.3.6.5).
As summarized in Baker etal. (1990a) and the 2008 ISA, fish populations in acidified
streams and lakes of Europe and North America have declined, and some have been
eliminated as a result of atmospheric deposition of N and S and the resulting changes in
pH, ANC, and inorganic Al concentrations in surface waters. There is often a positive
relationship between pH and the number of fish species, particularly between pH 5.0 and
6.5. Additional pH thresholds published since the 2008 ISA (Table 8-2) support this
range, and several new studies consider the role of DOC in controlling pH and
subsequent effects on biota. In the 2008 ISA and in new research, few or no fish species
are found in lakes and streams that have very low ANC (near zero; Figure 8-6 and Table
8-3) and low pH (near 5.0). The number of fish species generally increases at higher
ANC and pH values. Al is very toxic to fish and thresholds to elevated concentrations of
this metal in acidified waters are summarized in Table 8-5.
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1.6.2.2
National-Scale Sensitivity, Biological Recovery, and Critical Loads
The extent and distribution of sensitive freshwater ecosystems and sensitive regions in
the U.S. were well known at the time of the 2008 ISA. Surface waters in the U.S. that are
most sensitive to acidification are largely found in the Northeast, southern Appalachian
Mountains, Florida, the Upper Midwest, and the mountainous West (Figure 1-8). Levels
of acidifying deposition in the West are low in most areas, acidic surface waters rare, and
the extent of chronic surface water acidification to date has been very limited. However,
episodic acidification occurs in both the East and West at sensitive locations. In the
eastern U.S., acid-sensitive ecosystems are generally located in upland, mountainous
terrain underlain by weathering-resistant bedrock. Some of the most in-depth studies of
the effects of acid stress on fish were conducted in streams in Shenandoah National Park
in Virginia and in lakes in the Adirondack Mountains of New York. Effects on fish have
also been documented in acid-sensitive streams of the Catskill Mountains of southeastern
New York, and the Appalachian Mountains from Pennsylvania to Tennessee and South
Carolina.
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Surface Water Critical Loads for Acidity
S+N meq/m2/yr - 10th Percentile v \
12-50 \
H 51 - 100 \
101 -200 I
201-4,215 Conditions:
Mn Data (1) ANC threshold: East = 50 peq/L, West = 20 peq/L
(2) Negative Critical Loads = 0.1 meq/m2/yr
States (3) NCLD v2.5 - 3/17/2015
ANC = acid neutralizing capacity; meq=milliequivalent yr = year.
Source: http://nadp.sws.uiuc.edu/committees/clad/db/NCLDMapSummary 2015.pdf
Figure 1-8 Surface water critical loads for acidity in the U.S. 10th percentile
aggregation for 36 km2 grids with S and N.
1 Biological recovery can occur only if chemical recovery (Chapter 7) is sufficient to allow
2 growth, survival, and reproduction of acid-sensitive plants and animals. Surface water
3 chemistry recovery varies by region with the strongest evidence for improvement in the
4 Northeast and little or no recovery in central Appalachian streams. As reported in the
5 2008 ISA and in new studies, biological recovery lags behind chemical recovery in many
6 systems (see Section 8.4). and the time required for biological recovery is unknown. In
7 general, recovery of plankton and other invertebrates is observed before fish population
8 recovery, although most biological communities studied to date have not returned to
9 pre-acidification conditions. The 2008 ISA indicated a lag time of 1 to 6 years for
10 zooplankton recovery m the experimentally acidified Little Rock Lake in Wisconsin, and
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zooplankton recovery occurred at pH 6.1 in an experimentally acidified lake in Canada.
Newer studies from the Sudbury Lakes region of Canada indicate recovery of copepods
and cladocerans at pH 5.5 and higher (Section 8.4.2). New studies assess recovery of
benthic organisms, although most of this research has been conducted in Canadian and
European waters (Section 8.4.3 and Table 8-6). There is some evidence for recolonization
by fish and community shifts in recovering lakes (Section 8.4.4). Several long-term
studies find limited biological recovery despite substantial improvements in water
chemistry, while other studies show more evidence for repopulation by biota. When
biological recovery is observed, the recovered ecosystem may host different species from
those present before acidification.
Since the 2008 ISA, considerable CL research has focused on aquatic acidification in the
U.S. New empirical CLs include 8 kg N/ha/yr in the Northeast and 4 kg N/ha/yr in the
West to prevent episodic acidification in high-elevation lakes and to maintain an ANC of
74 eq/ha/yr in high-elevation lakes of the Sierra Nevada ITable 8-81. Several modeled
steady-state CLs have been derived since the 2008 ISA (Table 8-9). Steady-state CLs of
acidifying deposition for lakes in the Adirondack Mountains (1,620 eq/ha/yr) and for the
central Appalachian streams (3,700 eq/ha/yr) were calculated to maintain a surface water
ANC of 50 (.ieq/L on an annual basis (NAPAP. 2011). CL values of less than
500 eq/ha/yr were calculated for one-third of streams in the Blue Ridge ecoregion, to
maintain stream ANC at 50 (ieq/L. For lakes in class I and II wilderness areas in the
Sierra Nevada, CLs for acidifying deposition in 2008 were estimated at ANC values of 0,
5, 10, and 20 (j,eq/L, which span the range of minimum ANC values observed in Sierra
Nevada lakes. The median CL for granitic watersheds based on a critical ANC limit of
10 (ieq/L was 149 eq/ha/yr. Slightly more than one-third of these lakes had estimated
rates of acidifying deposition higher than their CL.
In addition to the steady-state and empirical loads described above, CL estimates have
been derived from dynamic modeling (Table 8-9). For example, there is new work on
simulated past and future effects of N and S on stream chemistry of 12 watersheds in the
Great Smoky Mountain National Park. Target levels of ANC to protect aquatic life were
used and ranged from minimal (0 j^ieq/L) to considerable protection (50 j^ieq/L). For the
12 study streams, target levels of NO3 + SO42 deposition ranged from 270 to
3,370 eq/ha/yr to reach an ANC of 0 (j,eq/L by 2050, and 0-1,400 eq/ha/yr to reach an
ANC of 50 |icq/L by 2050. However, the majority of streams could not achieve the ANC
target of 50 (ieq/L. Modeling also suggests that complete recovery from acidification may
not be possible by the year 2100 at all sites in the southern Blue Ridge region (Sullivan et
al.. 2011b) even if S emissions cease entirely. In Shenandoah National Park, MAGIC
modeling based on simulations of 14 streams identified a target load of about 3 kg
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S/ha/yr to achieve an ANC = 50 j^icq/L (preindustrial level based on hindcast simulations)
in 2100 in sensitive streams.
In the Adirondacks, target loads were calculated for two time periods (2050, 2100) and
three levels of protection (ANC = 0, 20, 50 (ieq/L). About 30% of the lakes in the region
had a target load <500 eq/ha/yr to protect lake ANC to 50 j^ieq/L (Sullivan et al.. 2012a).
Future decreases in SO42 deposition are suggested to be more effective in increasing
Adirondack lake water ANC than equivalent decreases in NO3 deposition. In another
modeling study of 20 Adirondack watersheds. Estimates of preindustrial ANC for the
study lakes ranged from 18 to 190 (ieq/L, and simulations estimate that lake ANC have
decreased by 26 to 100 j^icq/L as a legacy of acidification.
1.6.3 Biological Effects of Freshwater Nitrogen Enrichment
In the 2008 ISA, evidence was sufficient to infer a causal relationship between N
deposition and the alteration of species richness, species composition, and biodiversity in
freshwater ecosystems. The freshwater systems most affected by nutrient enrichment due
to atmospheric deposition of N were remote high-elevation lakes with low N retention
capacity. In these ecosystems, N changes biota, especially increasing algal growth and
shifting algal communities. Freshwater organism responses to N enrichment can be
assessed through biological indicators, including chlorophyll a, phytoplankton and
periphyton (algae attached to a substrate) biomass, diatoms, and trophic status. The
current causal statement has been expanded to include effects on algal growth (Table
1-1). New evidence since 2008 of N enrichment includes paleolimnology, phytoplankton
community dynamics, macroinvertebrate response, and indices of biodiversity. This new
evidence is consistent with the conclusions and strengthens the evidence base of the 2008
ISA, and together, the body of evidence is sufficient to infer a causal relationship
between N deposition and changes in biota including altered growth, species
richness, community composition, and biodiversity due to N enrichment in
freshwater ecosystems.
1.6.3.1 Physiology and Biodiversity Effects
Inputs of N to freshwater systems stimulate algal growth, which leads to a cascade of
effects on algal community composition and biodiversity. Algal species have differential
responses to N loading and shifts in nutrient ratios, so dominant species may change in
response to N enrichment. As reported in the 2008 ISA, shifts in nutrient limitation from
N limitation to colimitation by N and P, or to P limitation, have been observed in some
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alpine lakes. Bergstrom (2010) identified a lake response when DIN:TP mass ratios
increased from 1.5 to 3.4, of phytoplankton shifting from clear N limitation to clear P
limitation. New biodiversity studies are summarized in Table 9-3.
1.6.3.1.1 Primary Producers
In remote freshwater systems where atmospheric deposition is a dominant N source, the
strongest body of evidence is for biological effects of N enrichment upon primary
producers. Algae are the base of the freshwater food web. The majority of studies focused
on phytoplankton, although several new studies indicate that both benthic and pelagic
primary producers respond to N inputs (Section 9.3.2). The 2008 ISA and new studies
include lake surveys, fertilization experiments, and nutrient bioassays that show a
relationship between increased N concentrations and increased pelagic and benthic algal
productivity (measured by chlorophyll a concentration). An increase in lake
phytoplankton biomass with increasing N deposition was reported in the Snowy Range in
Wyoming and in Europe. New studies in the Colorado Rocky Mountains, where
atmospheric deposition ranged from 2 to 7 kg N/ha/yr, finds correlations between higher
chlorophyll a and higher rates of deposition.
The 2008 ISA and newer studies (Table 9-1 and Section 9.3.1) show a general shift in
algal dominance from chrysophytes that dominate low N lakes to cyanophytes and
chlorophytes in higher N lakes. Two nitrophilous species of diatom, Asterionella formosa
and Fragilaria crotonensis serve as indicators of N enrichment in lakes. New studies
show that glacial meltwater has higher NCh relative to snow meltwater with different
influences on algal community composition (Section 9.3.1.1). In a comparison of lakes
with different meltwater sources, fossil diatom richness in snowpack-fed lakes was at
least double the richness of lakes with both glacial and snow meltwater inputs. Some
shifts in algal biodiversity observed in high-elevation waters are attributed to climate
change or nutrient effects and climate as costressors (Chapter 13).
Few studies in the U.S. have considered effects of atmospheric deposition on aquatic
macrophytes, although declines in macrophyte occurrence were noted in a new survey of
Lake Tahoe comparing lake biota to a survey conducted in the 1960s (Caires et al. 2013).
Atmospheric N contributions are a substantial portion (approximately 57%) of the total N
loading to Lake Tahoe.
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1.6.3.1.2
Zooplankton
Compared to changes in primary producers, biological responses to N deposition at
higher trophic levels are not well characterized, but atmospheric N can alter food web
interactions (see Section 9.3.3.1). A few studies in the 2008 ISA showed declines in
zooplankton biomass in response to N related shifts in phytoplankton biomass toward less
palatable taxa with higher C:P ratios.
1.6.3.1.3 Higher Invertebrates
Only a limited number of studies published since the 2008 ISA have linked atmospheric
N deposition to taxonomic shifts and declines in invertebrates. These studies do not
attribute shifts in the abundance of higher invertebrates to N deposition alone, as there are
interactions with climate and invasive species. New studies provide additional evidence
that trophic interactions may moderate algal growth following nutrient loading
(Section 9.3.3.2V A study in Banff National Park, Canada indicated that grazing by fairy
shrimp (Crustacea: Anostraca) consumed additional biomass stimulated by nutrient
enrichment effects on primary producers (Vinebrooke et al.. 2014). In Lake Tahoe, which
receives 57% of N inputs from atmospheric sources, endemic invertebrate taxa have
declined 80 to 100% since the 1960s due to nutrient inputs and invasive species.
1.6.3.1.4 Higher Trophic Levels
Toxic effects due to increased NOs in surface waters occur in amphibians and fish at
much higher concentrations than would commonly be attributable to atmospheric
deposition. Emerging research on disease in biota (Section 9.4.2) has suggested that N
enrichment may affect host susceptibility to parasites and pathogens.
1.6.3.2 National-scale Sensitivity and Critical Loads
New data have not appreciably changed the identification of sensitive lakes and streams
in the U.S. Nutrient enrichment effects from N most likely occur in undisturbed,
low-nutrient surface waters at higher elevations in the western U.S. (Section 9.6).
including the Snowy Range in Wyoming, the Sierra Nevada, and the Colorado Front
Range. The responses of high-elevation lakes vary with catchment characteristics
(Section 9.1.3). In these systems, even low inputs of atmospheric N can shift N limitation
to colimitation by N and P, or to P limitation (Section 9.1.4). altering algal species
composition and productivity. Data are limited for biological effects of N enrichment in
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other regions of the U.S. A new study showed a positive relationship between lake
DIN:TP and N deposition in the Adirondack region.
In the 2008 ISA, diatom assemblage shifts were reported at N deposition rates as low as
1.5 kg/N/yr. Additionally, a hindcasting exercise in Rocky Mountain National Park lakes
associated algal changes between 1850 and 1964 with an increase in wet N deposition of
1.5 kg N/ha/yr. Additional CLs have been identified since the 2008 ISA for eastern Sierra
Nevada lakes, the greater Yellowstone ecosystem, and Hoh Lake in Olympic National
Park (Table 9-4). The identified CL values fall within the range of 1.0 to 3.0 kg N/ha/yr
for lakes in the western U.S. and from 3.5 to 6.0 kg N/ha/yr for lakes in the northeastern
U.S.
1.7 Estuarine and Near-Coastal Ecosystem Nitrogen Enrichment
and Acidification
For estuaries (areas where freshwater from rivers meets the salt water of oceans), causal
determinations from the 2008 ISA are further supported and strengthened by additional
studies, and there are two new causal statements on the emerging topic of nutrient
enhanced coastal acidification (Table 1-1). Estuaries support a large biodiversity of flora
and fauna and play a role in nutrient cycling. N from atmospheric and other sources
contributes to increased primary productivity, leading to eutrophication (Figure 10-1).
Source apportionment data in the 2008 ISA and newer studies indicate that atmospheric
contributions to estuarine N are heterogeneous across the U.S., ranging from <10% to
approximately 70% of total estuary N inputs (Table 7-6). In estuaries, increasing nutrient
over-enrichment leading to eutrophication is indicated by water quality deterioration,
resulting in numerous harmful effects, including areas of low dissolved oxygen (DO)
concentration (hypoxic zones), species mortality, and harmful algal blooms (HABs). New
studies support the 2008 ISA's causal findings that increased N loading to coastal areas
can alter biogeochemical processes and lead to shifts in community composition, reduced
biodiversity, and mortality of biota. The current causal statement of biological effects of
N enrichment in estuarine ecosystems has been expanded to include altered growth
(Table 1-1). Since the 2008 ISA, it has been suggested that, in addition to atmospheric
sources of CO2, nutrient-enhanced productivity may contribute to acidification of coastal
waters. New causal determinations have been added to the current ISA on N deposition
and increased nutrient enhanced coastal acidification and associated biological effects
(Table 1-1). Increased ocean acidification interferes with the ability of some organisms to
build shells, although the contribution of nutrient-enhanced coastal acidification is not yet
understood.
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1.7.1
Estuary and Near-Coastal Biogeochemistry
In the 2008 ISA, evidence was sufficient to infer a causal relationship between N
deposition and the biogeochemical cycling of both N and C in estuarine ecosystems. The
rate of nutrient delivery, especially N, to coastal waters correlates with primary
production and phytoplankton biomass (Paerl and Piehler. 2008). The influence of N
inputs from upstream freshwater ecosystems has led to recommendations to decrease
both atmospheric N deposition and N loading activities upstream (Paerl et al.. 2014;
Con lev et al.. 2009; Paerl. 2009). A variety of empirical and modeling studies published
since the 2008 ISA have provided additional data on N and C cycling, hypoxia, HABs,
and spatial variation in DIN export. There is new information on benthic ammonia
oxidizers which play a key role in N cycling. New research further supports conclusions
of the 2008 ISA, and the body of evidence is sufficient to infer a causal relationship
between N deposition and the alteration of biogeochemistry in estuarine and
near-coastal marine systems.
Ocean acidification is already occurring from dissolution of rising atmospheric CO2. In
eutrophic zones of high primary productivity, decomposition and respiration of fixed C
releases additional CC^to the water column. This hypoxic zone alters C cycling and
lowers pH. The body of evidence is sufficient to infer a likely causal relationship
between N deposition and increased nutrient-enhanced coastal acidification.
1.7.1.1 Nitrogen Enrichment
As reported in the 2008 ISA, estuaries are generally N limited, and have received
sufficiently high levels of N input from human activities (including deposition,
agricultural runoff, and wastewater) to cause eutrophication. Highly variable
environments within estuaries are characterized by a gradient of increasing salinity
toward the ocean. As N moves downstream, some fraction is taken up by phytoplankton
or removed by microbial denitrification. Key processes that influence N cycling include
hypoxia, nitrification, denitrification, and decomposition. Indicators of nutrient
enrichment in coastal areas include DIN, dissolved inorganic phosphorus (DIP; Chapter
7) water clarity, and DO.
Decreasing DO can create hypoxic (<2 mg/L of dissolved O2) or anoxic zones inimical to
fish and other aerobic life forms. Organic particles in coastal regions sink to the
sediment-water interface, where they accumulate and decompose. Decomposition of
these organic particles transforms nutrients and depletes O2 in the water. This can result
in seasonal hypoxia in shallow coastal regions, particularly those that receiving high
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inputs of nutrients from coastal rivers. Development of hypoxia is increasingly a concern
in estuaries across the U.S.
The 2008 ISA, along with new research from North America and Europe, describe the
importance of nitrification and denitrification to N cycling in estuarine and near-coastal
marine ecosystems. (Section 7.3.2.IV Nitrification—the oxidation of NH4+ to
N03—largely controls the relative abundance of oxidized and reduced DIN. The
efficiency of estuarine denitrification depends on the extent and type of habitats, with
oyster reefs and seagrass beds providing especially high rates of N removal per unit
estuary area.
Nitrogen removal from the estuary is also influenced by faunal as well as microbial
communities. Sediment-burrowing macrofauna (molluscs, worms, crustaceans) stimulate
nitrification and denitrification in the sediment. These N cycling processes facilitate
removal of N from the estuary system to coastal waters or the atmosphere. Until recently,
it was generally believed that NH3 oxidation was accomplished only by Proteobacteria in
marine environments. New research discovered that some archaea can also oxidize NH3.
These ammonia-oxidizing archaea are dominant in some estuaries, while
ammonia-oxidizing bacteria are more important in others.
Since the 2008 ISA, N enrichment has been recognized as a potential contributing factor
to acidification of coastal waters (Section 10.5). Dissolution of atmospheric
anthropogenic CO2 into the ocean has led to long-term decreases in pH. With increasing
N inputs to coastal waters, decomposition of excess organic matter associated with
eutrophication adds CO2 to the water column (Sunda and Cai. 2012; Cai etal.. 2011c;
Howarth et al.. 2011). Models show that while the impact of each acidification pathway
(N enrichment or atmospheric CO2 dissolution) may be moderate, the combined effect
may be much larger than would be expected from the additive effects of each pathway
(Sunda and Cai. 2012; Cai et al.. 2011c').
Models of estuarine eutrophication focus on N load apportionment, or on relationships
between N loads and ecological endpoints. Since the 2008 ISA, SPARROW has been
used to estimate total N loads within watersheds to determine sources of N to streams and
rivers; it has also been applied at regional and national scales. Additional models and
tools that include the contribution of N directly from the atmosphere have been applied to
1.7.1.2
Nutrient-Enhanced Coastal Acidification
1.7.1.3
Models
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U.S. estuaries, including the Watershed N Loading Model (NLM) and the Watershed
Deposition Tool (WDT). The latter was developed by the U.S. EPA to map atmospheric
deposition estimates to watersheds using wet and dry deposition data from CMAQ
(Schwede et al.. 2009). This tool links air and water quality modeling data for use in
Total Maximum Daily Load (TMDL) determinations and analysis of nonpoint-source
impacts. New model applications include studies that focused primarily on endpoints of
N cycling, hypoxia, and HABs. These studies show seasonal and spatial patterns of DIN
export influence coastal eutrophication impacts, including incidence of HABs and the
development of seasonal hypoxic zones. Models of coastal eutrophication are described
in greater detail in Section 7.3.3.
1.7.1.4 National-Scale Sensitivity
Sensitivity of estuaries to biogeochemical changes associated with N enrichment varies
across the U.S. The biogeochemical sensitivity of estuaries and near coastal areas will be
discussed together with biological sensitivity to N enrichment in Section 1.7.4.
1.7.2 Biological Effects of Nitrogen Enrichment
In the 2008 ISA, evidence was sufficient to infer a causal relationship between N
deposition and the alteration of species richness, species composition, and biodiversity in
estuarine ecosystems. Since 2008, new paleontological studies, observational studies, and
experiments have further characterized the effects of N on phytoplankton growth and
community dynamics, macroinvertebrate response, and other indices of biodiversity. This
new research strengthens the evidence base and is consistent with the 2008 ISA (Table
1-1) that the body of evidence is sufficient to infer a causal relationship between N
deposition and changes in biota including altered growth, species richness,
community composition, and biodiversity due to N enrichment in estuarine
environments.
Indicators of altered biodiversity due to coastal eutrophication include chlorophyll a,
HABs, macroalgal (seaweed) abundance, DO concentrations, and changes in submerged
aquatic vegetation (SAV; rooted vascular plants that do not emerge above the water
I Table 10-11). Some indicators, such as chlorophyll a, are directly linked to nutrient
enrichment and provide evidence of early ecosystem response; other indicators, such as
low DO and decreases in SAV, indicate more advanced eutrophication.
New studies support the 2008 ISA's conclusions that increased N loading to coastal areas
can shift community composition, reduce biodiversity, and cause mortality. N inputs
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increase the dominance of faster growing benthic or pelagic macroalgae to the exclusion
of other species. Increased productivity of floating algae can block the penetration of
sunlight to SAV. Release of toxins during HABs can be harmful to fish and shellfish, and
these toxins may be transferred to higher trophic levels (Section 10.2.2V Hypoxia and
anoxia caused by decomposition of increased primary production can be fatal to
immobile aerobic organisms (Section 10.2.4 and Figure 10-4) and reduce faunal
diversity. New studies emphasize that N inputs interact with physical and hydrologic
factors to increase primary productivity and eutrophication in coastal areas.
1.7.2.1 Primary Producers
Algae are the base of the coastal food web, and the 2008 ISA showed that changes in
chemical composition of N inputs can shift the algal community and cascade up the food
web. Community composition changes as algal species have differential responses to
shifts in nutrient ratios (Section 10.3.2). Studies in the 2008 ISA suggested that large
diatoms dominate coastal waters when NO, is supplied, and the increased NH/ relative
to N03 in the eastern U.S. favors small diatoms. Newer studies support these
observations of NO3 and NH4+ and diatom species distribution (Section 10.3.3). New
studies also show that NH3/NH4 inputs selectively favor HAB species such as toxic
cyanobacteria and dinoflagellates (Table 10-3). and that some macroalgae have greater
assimilation and growth rates with NH44" than with NO3 (Section 10.2.3).
Algal community composition also changes in response to total N loading as some
species are more responsive to N inputs. Shifts in phytoplankton community structure
occur in estuaries with elevated N inputs. In Chesapeake Bay, sediment core analyses
show decreases in biodiversity and a shift to a primarily planktonic food web
corresponding to increased N flux and higher sediment inputs (Sowers and Brush. 2014;
Brush. 2009; Cooper and Brush. 1993). The dominance shifted from diatoms to
nonsilicate nanoplankton coincident with increased nutrient loading in Skidaway River
estuary, Georgia.
In the 2008 ISA, nutrient enrichment in coastal water bodies was linked to increased
HAB outbreaks. Of the 81 estuary systems for which data were available for the National
Estuarine Eutrophication Assessment (NEEA), 26 exhibited a moderate or high symptom
expression for nuisance or toxic algae (Bricker et al.. 2007). Since the 2008 ISA, HAB
bloom conditions and effects of HAB toxins on wildlife have been further characterized
(Section 10.2.2). There is consistent and coherent evidence that the incidence of HAB
outbreaks is increasing in both freshwater and coastal areas.
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Macroalgae (seaweed) growth is also stimulated by increased N inputs. Increased
abundance of macroalgae can block light to the lower water column, reducing the growth
and biomass of SAV. The 2008 ISA reported correlations between increased N loading
and declines in SAV abundance and newer studies have further characterized this
relationship. In a survey of southern New England estuaries, reduced eelgrass extent was
observed at increased watershed N loading. SAV declines can lead to a cascade of
ecological effects as many species are dependent upon seagrasses for cover from
predation and as breeding or nursery grounds. New studies have characterized the role of
invertebrate mesograzers, such as small crustaceans and gastropods, in controlling algal
growth, potentially buffering eutrophication effects on seagrass communities
(Section 10.3.7).
1.7.2.2 Bacteria and Archaea
Ammonia-oxidizing prokaryotes carry out nitrification in estuarine waters.
Ammonia-oxidizing archaea are relatively recently described, and several studies since
the 2008 ISA have considered community responses of ammonia-oxidizing bacteria and
ammonia-oxidizing archaea. Community structure of ammonia-oxidizers is related to
nutrient inputs and affected by the form of available N (Section 10.3.4).
1.7.2.3 Invertebrates
Invertebrate community structure changes in response to hypoxia (Section 10.3.6). The
community of benthic organisms shifts toward shorter life spans and smaller body size in
coastal areas with severe seasonal hypoxia. Reduced species density and diversity in the
northern Gulf of Mexico are linked to persistent hypoxic events.
Shifts in algal composition and productivity can affect growth of shellfish that feed on
phytoplankton. Shellfish contribute to N and C cycling and can improve water quality
and recent research has explored the use of these organisms for coastal N remediation.
Harvest of shellfish for human consumption removes nutrients from estuaries. The form
of N present has been shown to affect molluscan taxonomic assemblages (Atalah and
Crowe. 2012V
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1.7.2.4 Fish
Fish biodiversity is altered by increased N inputs and resulting changes in biological and
chemical indicators. Many fish are unable to persist at DO below 2 mg/L (Figure 10-4).
Recent studies in the southern Gulf of Saint Lawrence have linked SAV loss to declines
in fish biodiversity, although organisms did not change positions within food webs. In
laboratory conditions, turbidity associated with eutrophication alters fish reproductive
behaviors. Hypoxia has also recently been shown to affect reproduction in fish. For
example, hypoxia acts as an endocrine disruptor in Atlantic croaker (Micropogonias
undulatus; Section 10.2.4).
1.7.3 Biological Effects of Ocean Acidification
Newer studies show that organisms that produce calcium carbonate shells are impacted
by increasing acidification of ocean waters (Section 10.5). Decreased concentration of
carbonate ions (which organisms such as calcareous plankton, oysters, clams, sea urchins,
and coral take up to build shells) are observed in acidic conditions. Documented declines
of oyster production on the U.S. west coast are linked to ocean acidification. Nutrient
enhanced coastal acidification and hypoxia may exacerbate acidification from
atmospheric CO2 (Section 7.3.2.3). The body of evidence is suggestive of a causal
relationship between N deposition and changes in biota including altered
physiology, species richness, community composition, and biodiversity due to
nutrient-enhanced coastal acidification.
1.7.4 National-Scale Sensitivity and Critical Loads
The NEEA, the most recent comprehensive survey of eutrophic conditions in U.S.
estuaries conducted by the National Oceanic and Atmospheric Administration, defined
eutrophication susceptibility as the natural tendency of an estuary to retain or flush
nutrients (Bricker et al.. 2007). In estuaries that have longer water residence times,
nutrients are more likely to lead to eutrophic conditions (Section 10.1.4). As reported in
the 2008 ISA and newer studies, nutrient loading accelerates hypoxia, which is more
likely in marine waters with limited water exchange, water column stratification, and
high production and settling of C to bottom waters. Other factors identified in the 2008
ISA that increase estuary sensitivity to eutrophication include human population,
agricultural production, and the size of the estuary relative to its drainage basin.
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The NEEA reported that the most eutrophic estuaries in the U.S. occur in the
mid-Atlantic region, and the estuaries with the lowest degree of eutrophication are in the
North Atlantic (Figure 10-8). Estuaries identified in the 2008 ISA as susceptible to
eutrophication include the Chesapeake Bay, Pamlico Estuary in North Carolina, Long
Island Sound, as well as along the continental shelf adjacent to the Mississippi and the
Atchafalaya River discharges to the Gulf of Mexico. New research at the regional scale
includes long-term studies of several coastal systems on trends in coastal water quality
and chemistry. A 23-year study of the Chesapeake Bay concluded that water quality has
decreased and chlorophyll a levels have increased since 1986, in part due to long-term
climate trends (see Section 7.3.2V
The 2008 ISA reported that the largest zone of hypoxic coastal water in the U.S. was the
northern Gulf of Mexico on the Louisiana-Texas continental shelf. This hypoxic area
continues to be the largest in the U.S. and the second largest in the world, forming
annually between May and September (Dale et al.. 2010; Jewett et al.. 2010).
Atmospheric deposition to watersheds in the Mississippi/Atchafalaya River Basin
contributes approximately 16% to 26% of the total N load to the Gulf of Mexico
(Robertson and Saad. 2013; Alexander et al.. 2008). The midsummer bottom-water
hypoxia area averaged approximately 8,500 km2 (5,300 mi2) between 1985 and 2014.
Long Island Sound also experiences anoxia, and between 1987 and 2014, the average
maximum extent was 98 km2 (61 mi2). In other U.S. coastal systems, hypoxia incidence
is increasing, but DO impacts are relatively limited temporally and spatially. The NEEA
suggested that only a small fraction of the estuary systems evaluated reported moderate to
high SAV loss (Bricker et al.. 2007). mostly in the mid-Atlantic region. While seagrass
coverage is improving in some estuaries, such as Tampa Bay (Tampa Bay Case Study,
Appendix C). many estuaries continue to see declines in seagrass extent.
No CLs for N in coastal waters were identified in the recent review of the literature,
although the critical load for coastal wetlands includes eelgrass population as an endpoint
(Section 1.9.3). There are thresholds of response identified for some biological and
chemical indicators of N enrichment. Chlorophyll a is an indicator of phytoplankton
biomass, and thus, a proxy for assessing estuarine nutrient enrichment. In general,
0-5 (ig/L chlorophyll a is considered to be good condition, concentrations between 5 and
20 (ig/L are classified as fair condition, and concentrations of >20 |_ig/L indicate poor
conditions in estuaries (Table 10-2). A new response threshold of tidal-averaged total N
concentration of <0.34 mg/L has been identified for healthy eelgrass in Massachusetts
waters. Markedly decreased eelgrass coverage is observed atN loading rates >100 kg
N/ha/yr, and levels above 50 kg N/ha/yr are likely to impact SAV habitat extent in
shallow New England estuaries ITable 10-4; (Benson et al.. 2013; Latimer and Rego.
2010)1. In terms of DO, concentrations of 0 mg/L are anoxic, 0-2 are indicative of
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hypoxic conditions, and 2-5 mg/L are biologically stressful conditions (Devlin et al..
2011; Bricker et al.. 2007).
The indicators of nutrient enrichment in coastal areas (chlorophyll a, HABs, macroalgal
abundance, DO, SAV, and benthic diversity) have been incorporated into indices of
coastal eutrophication. In the 2008 ISA, the Assessment of Estuarine Tropic Status
(ASSETS) categorical Eutrophication Condition index (ECI) developed for the NEEA
was used as an assessment framework for coastal U.S. estuaries (Bricker et al.. 2007).
Additional indices of estuarine functioning that incorporate biological indicators have
since been developed both in the U.S. and internationally (Section 10.2.6). Comparisons
of these frameworks have identified robust methods to measure estuarine response, such
as incorporation of annual data, frequency of occurrence, spatial coverage, secondary
biological indicators, and a multicategory rating scale.
1.8 Wetland Ecosystem Nitrogen Enrichment and Acidification
New evidence, including new critical loads, supports and strengthens the causal findings
from the 2008 ISA regarding N enrichment effects in wetlands (Table 1-1). New research
together with the information included in the 2008 ISA shows that the body of evidence
is sufficient to infer a causal relationship between N deposition and alteration of
biogeochemical cycling in wetlands. The body of evidence is sufficient to infer a causal
relationship between N deposition and changes in biota, including alteration of species
physiology, species richness, community composition, and biodiversity in wetlands. In
freshwater and coastal wetland ecosystems, deposition of N and S do not tend to cause
acidification-related effects at levels common in the U.S. (U.S. EPA. 2008a. in Annex B).
However, the 2008 ISA documented that wetlands can be sensitive to N enrichment and
eutrophication effects. Newer studies have characterized N effects on biogeochemistry,
physiology, biodiversity, national sensitivity, and critical loads for freshwater and coastal
wetlands; the latter are typically adapted to much higher N loading.
1.8.1 Wetland Biogeochemistry
In the 2008 ISA, evidence was sufficient to infer a causal relationship between N
deposition and the alteration of wetland biogeochemical cycling. Although sources and
rates of N inputs vary widely among wetlands, N deposition contributes substantially to
total loading in many wetlands. This additional N alters multiple aspects of
biogeochemistry, including C cycling, N cycling, methane flux, and nitrous oxide flux.
New research on wetland biogeochemistry since 2008, includes a synthesis of wetland
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improvements to water quality through denitrification and biological uptake, a
meta-analysis of N addition effects on methane and nitrous oxide fluxes, and multiple
observations of changes in belowground C cycling in response to added N. New research
together with the information included in the 2008 ISA shows that the body of evidence
is sufficient to infer a causal relationship between N deposition and the alteration of
biogeochemical cycling in wetlands.
The 2008 ISA found that N enrichment altered N cycling in wetland ecosystems.
Chemical indicators of wetland N cycling are similar to terrestrial indicators, and include
rates of NO, leaching, N mineralization, and denitrification. A wetland can act as a
source, sink, or transformer of atmospherically deposited N, and these functions vary
with season and hydrological conditions. Vegetation type, physiography, local hydrology,
and climate all influence source/sink N dynamics in wetlands. A new synthesis of global
wetland data showed that wetland reactive N removal and water quality improvement is
proportional to reactive N load and removal efficiency is 26% higher in nontidal than
tidal wetlands. There are also new studies that evaluate the effects of N addition on
endpoints related to N cycling in salt marsh, mangrove, peat bog, and riparian wetlands.
The endpoints evaluated include tidal export, mineralization, denitrification, and bacterial
community composition. These studies are summarized in Figure 11-1.
The 2008 ISA found that N enrichment altered C cycling in wetlands. N limitation of
productivity varies considerably among wetlands and determines the degree to which N
deposition alters C cycling. There are several new studies evaluating N addition effects
on belowground C cycling in wetlands, including assessments of changes in root biomass
and soil respiration (Figure 11-2). Several more studies have evaluated aspects of
aboveground C cycling, such as plant production and total plant biomass (Figure 11-2).
An important impact of altered wetland C and N cycling is the increase in emissions of
two powerful greenhouse gases (GHGs): nitrous oxide (N2O) and methane (CH4). Each
gas traps radiation in the atmosphere more efficiently than CO2, and each gas can be
produced or consumed by soil microorganisms. For N2O, a meta-analysis of 19 N
addition observations (N addition ranged from 15.4 to 300 kg N/ha/yr) found that N
enrichment increased wetland emissions by 207%. For CH4, the same meta-analysis
included 17 N addition observations (N addition 30 to 240 kg N/ha/yr) and found that N
addition increased methane emissions from wetlands and grasslands by 115%.
Subsequent research has found further evidence that N additions increase methane
production from wetland soils.
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1.8.2
Biological Effects of Wetland Nitrogen Enrichment/Eutrophication
In the 2008 ISA, evidence was sufficient to infer a causal relationship between N
deposition and the alteration of species richness, species composition, and biodiversity in
wetlands. New evidence is presented in the following sections regarding the effects of N
upon wetland plant physiology, architecture, demography, and biodiversity. The body of
evidence is sufficient to infer a causal relationship between N deposition and the
alteration of species physiology, species richness, community composition, and
biodiversity in wetlands.
1.8.2.1 Physiology
The effects of N additions on plant stoichiometry and chemistry were not addressed in the
2008 ISA, but information regarding these effects is summarized in Section 11.5 (Figure
11-3). Plant stoichiometry theory connects the relative concentrations of multiple
chemical elements in living tissues to changes in physiological function. Among N
addition studies in wetlands, most new data of N addition effects on physiology and
stoichiometry are for bogs and freshwater marshes. In bogs, N addition typically causes
increased plant tissue N concentrations, decreased N use efficiency, decreased N
resorption efficiency during senescence, and increased plant productivity in vascular
plants. After several years of exposure to high rates of N loading, bog plants may
experience leaf N saturation and limitation by other nutrients (e.g., P and K, indicated by
increasing reabsorption efficiencies), resulting in leaf damage and biomass loss in
sensitive species. There are several new studies that indicate plants in freshwater marshes
respond similarly to those found in bogs, such that N addition increases plant tissue N
concentrations and increases net primary production.
Plant architecture and demography were not addressed in the 2008 ISA. Aboveground,
plant architecture includes branching patterns, as well as the size, shape, and position of
leaves and flower organs. New studies find N enrichment affects plant architecture in a
salt marsh, in mangroves, in freshwater tidal marshes, and in a riparian wetland
(Section 11.6). For plant demography, N addition has mixed effects upon reproduction of
West Coast salt marsh plant species, while N addition increased mortality across the
global distribution of mangrove species (Section 11.7).
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1.8.2.2
Biodiversity
In the 2008 ISA, evidence was sufficient to infer a causal relationship between N
deposition and the alteration of species richness, species composition, and biodiversity in
wetlands. Notably, the 2008 ISA cited 4,200 native plant species in U.S. wetlands, 121 of
which are federally endangered. Given their relative area, wetlands provide habitat to a
disproportionally high number of rare plants. Many wetland species have evolved under
N limited conditions, including endangered species in the genera Isoetes (3 endangered
species) and Sphagnum (15 endangered species), as well as charismatic insectivorous
plants such as endangered pitcher plants (Sarracenia oreophila) and sundews (Drosera
rotundifolia).
The 2008 ISA documented evidence from Canadian and European peatlands that N
deposition had negative effects on Sphagnum bulk density and mixed effects on
Sphagnum productivity depending on history of deposition. Coastal wetlands responded
to N enrichment with increased primary production, changing microbial and plant
communities, and altered pore water chemistry, although many of these studies used high
N enrichment levels more similar to N loading from wastewater than from atmospheric
deposition. Publications since 2008 provide consistent and coherent evidence that N is an
important factor shaping wetland plant diversity (Section 11.8). including field N
addition studies that have observed altered biodiversity in bogs, freshwater marshes, and
coastal marshes (Figure 1 1-4). Together with information from the 2008 ISA, the body of
evidence is sufficient to infer a causal relationship between N deposition and the
alteration of species richness, community composition, and biodiversity in wetlands.
1.8.3 National Sensitivity and Critical Loads for Wetlands
Freshwater and coastal wetlands tend to have different sensitivity to added N. Broadly,
wetlands that receive a larger fraction of their total water budget in the form of
precipitation are more sensitive to the effects of N deposition. For example, bogs
(70-100% of hydrological input from rainfall) are more sensitive to N deposition than
fens (55-83% as rainfall), which are more sensitive than intertidal wetlands (10-20% as
rainfall).
Since the 2008 ISA, N CLs for U.S. coastal wetlands have been established. The CLs are
based on several different ecological endpoints, including eelgrass population (50-100 kg
N/ha/yr) and plant community composition, microbial activity, and biogeochemistry
(63-400 kg N/ha/yr). Figure 11-5 shows a comparison of N CLs for wetlands with
studies published after 2011 (Section 11.10.2).
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Since the 2008 ISA, N CLs for U.S. freshwater wetlands have been established. The CL
for altered peat accumulation and NPP is between 2.7 and 13 kg N/ha/yr The upper end
of this critical load range is based on measurements of wet deposition only (10 to 13 kg
N/ha/yr) and therefore does not reflect total N loading. There is evidence showing that N
deposition alters both the morphology and population dynamics of the purple pitcher
plant (Sarraceniapurpurea). The empirical evidence suggests a critical load to protect
the population of purple pitchers of 10-14 kg N/ha/yr, while matrix modeling to forecast
long-term population sustainability based on observations of population demographics
suggests a lower value of 6.8 kg N/ha/yr. A comparison of these CLs to more recently
published data on N addition levels (16-500 kg N/ha/yr) and associated effects is given
in Figure 11-6 (Section 11.10.2).
1.9 Nonacidifying Sulfur Enrichment
New evidence from wetland and freshwater aquatic ecosystems strengthens and extends
the causal findings of the 2008 ISA regarding nonacidifying sulfur effects, and provides
the basis for a new causal determination (Table 1-1). New research together with the
information included in the 2008 ISA shows that the evidence is sufficient to infer a
causal relationship between S deposition and increased methylation of Hg where the
value of other factors is within adequate range for methylation in wetland and aquatic
ecosystems. New evidence is sufficient to infer a new causal relationship between S
deposition and changes in biota due to sulfide phytotoxicity, including alteration of
species physiology, species richness, community composition, and biodiversity in
wetland ecosystems.
SOx deposition can have chemical and biological effects other than acidification,
particularly in flooded wetland soils and aquatic ecosystems. The 2008 ISA described
qualitative relationships between sulfate deposition and a number of ecological
endpoints, including altered S cycling, sulfide phytotoxicity, internal eutrophication of
aquatic systems, altered methane emissions, increased mercury (Hg) methylation, and
increased Hg loading in animals, particularly fish. Table 12-11 summarizes chemical
concentrations that alter ecological endpoints and the quantitative relationships
describing effects of sulfate deposition. Recent research supports these relationships
between S deposition and ecological endpoints and provides the basis for SOx deposition
levels, water column sulfate concentrations, and water column sulfide concentrations
protective of plants and animals.
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1.9.1
Biogeochemistry
SOx deposition alters biogeochemical processes via S enrichment including S cycling, P
cycling, and Hg cycling.
The primary chemical indicator for nonacidifying effects of S in wetland and aquatic
ecosystems is surface water sulfate concentration, as it is for acidifying effects. There are
also indicators unique to nonacidifying effects, including methylmercury (MeHg), sulfate
reduction rates, sulfide, and phosphate. MeHg is produced by microbial sulfate reduction,
and is the most persistent and toxic form of Hg in the natural environment. MeHg is
measured in surface water or aquatic sediments (MeHg concentration or % MeHg of total
Hg) to predict its effects upon biota. Several new studies demonstrate significant positive
relationships between surface water SO42 concentrations and water or sediment MeHg
concentrations (Figure 12-13).
The 2008 ISA reported that chemical reduction of sulfate was an important indicator of
SOx effects on water chemistry, as the process generates ANC. New research finds a
positive relationship between increasing chemical sulfate reduction rates and increasing
water SO42 concentrations. The product of sulfate reduction, sulfide (measured as
surface water or sediment pore water S2 concentrations) is also a water quality indicator
of deposition effects upon biota. Sulfide may also react with iron bound to phosphates in
the sediment to release phosphate into the water column, increasing primary productivity;
new research documents this process, referred to as internal eutrophication
(Section 12.2.4).
There are few national-scale studies of nonacidifying S effects. There are national
assessments of Hg burdens in sampled fish, but these assessments do not consider
relationships between S deposition, water sulfate, and Hg loads. The U.S. EPA-OAQPS
found that fish tissue Hg loads were higher in the eastern U.S. The U.S. EPA national
stream surveys found that fish MeHg levels were highest in streams in watersheds with
considerable wetland area, and the highest fish MeHg concentrations in the U.S. were in
the Southeast.
1.9.1.1
Indicators and Processes
1.9.1.2
National-Scale Sensitive Ecosystems
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1.9.2 Biological Effects of Nonacidifying Sulfur
Nonacidifying S effects upon biota include plant toxicity and changes in plant
biodiversity, increased mercury methylation, and increased Hg concentrations in biota.
The toxicological effects of Hg accumulation in animals were documented in the 2008
ISA and newer studies.
Plants and other organisms require S as an essential nutrient. The deposition of S can
affect plant protein synthesis by affecting S availability for S containing amino acids,
which in turn will affect N uptake. The 2008 ISA documented the effects of sulfate
toxicity on plant development and reproduction at very high S loads. There is no new
evidence of S deposition effects upon plant S nutrition or sulfate toxicity. The product of
sulfate reduction, sulfide, is an important plant toxin, and the 2008 ISA documented
sulfide phytotoxicity in European systems. Together with new research showing sulfide
phytotoxicity in North American wetlands, the body of evidence is sufficient to infer a
causal relationship between S deposition and changes in biota due to sulfide
phytotoxicity including alteration of species physiology, species richness, community
composition, and biodiversity in wetland ecosystems.
The 2008 ISA documented that sulfide toxicity decreased biomass of wetland plants and
aquatic macrophytes in mesocosms under aquatic S concentrations higher than U.S.
concentrations. New research has demonstrated sulfide phytotoxicity effects at current
ambient sulfide concentrations in multiple ecosystems within the U.S. (Section 12.2.3V
Sulfide decreased total plant cover and cover of dominant species in a New York fen, and
decreased the growth rate of Cladium jamaicense (sawgrass), a keystone species in the
Florida Everglades. The Minnesota Pollution Control Agency is working on a sulfide
standard to protect the economically and culturally important species wild rice, and has
also developed a model that calculates protective levels of water SO42 concentrations,
given iron and DOC concentrations in water bodies.
Sulfate deposition can shift microbial community composition and activity, resulting in
lower methane emissions. The 2008 ISA documented the suppression of methane
emissions in wetland soils by sulfate addition in several studies and noted that 15 kg
S/ha/yr (the lowest S load in experimental treatments) suppressed methane emissions to
1.9.2.1
Sulfur Nutrient and Toxicity to Plants
1.9.2.2
Sulfur Effects on Methane Production
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the same extent as higher S loads. Recent research has confirmed that sulfate deposition
increases the abundance or metabolic activity of SRP. Under conditions favorable to
SRP, competing methanogens decline, resulting in suppressed methane emissions
(Section 12.2.4).
1.9.2.3 Sulfur Effects on Mercury Methylation
In the 2008 ISA, evidence was sufficient to infer a causal relationship between S
deposition and increased methylation of Hg, in aquatic environments where the value of
other factors is within adequate range for methylation. In the 2008 ISA, sulfur-reducing
bacteria (SRB) were identified as the organisms responsible for Hg methylation, and
anoxic wetland and lake-bottom sediments were identified as habitat for these
microorganisms. New evidence shows the ability to methylate Hg is more broadly
distributed phylogenetically, including both bacteria and archaea, which is why this
document refers to mercury methylators as SRP rather than the SRB described in the
previous ISA (Section 12.3.IV Recent research shows that the microbial communities
responsible for Hg methylation are more widely distributed in the environment than the
freshwater lake or wetland bottom sediments identified in the 2008 ISA. Additional
aquatic environments for Hg methylation include within Sphagnum peat, within
periphyton, and in marine ecosystems (Section 12.3 and Appendix B). Between the 2008
ISA and new research, the body of evidence is sufficient to infer a causal relationship
between S deposition and increased methylation of Hg in wetlands and aquatic
ecosystems where the value of other factors is within adequate range for
methylation.
As a microbial process, Hg methylation is determined not just by sulfate and Hg
concentrations, but by other environmental and nutritional requirements of SRP,
including pH, DOC concentrations, temperature, water quality parameters, and C supply.
(Section 12.3.4). Sulfate addition increases MeHg concentrations in the environment and
in biota by stimulating the activity of SRPs, some of which possess a gene pair conferring
the ability to methylate inorganic Hg. New research demonstrates that Hg methylation
occurs at ambient sulfate concentrations within U.S. water bodies. Multiple lines of
evidence support a relationship between sulfate surface water concentrations and MeHg
concentration or production in various freshwater systems, including wetlands. Linear
relationships between sulfate concentrations and MeHg concentrations were observed in
sediments of the South River, Virginia; across peat bogs in Minnesota and Ontario; and
across prairie pothole lakes in Saskatchewan (Section 12.5 and Figure 12-13). There is
also supporting evidence from S addition experiments in peat bogs in Minnesota and in
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Sweden showing that increasing S loads increased Hg mobility and MeHg fractions and
concentrations in peat (Section 12.4.1 and Figure 12-14).
In the freshwater marshes of the Everglades, recent work sets a target concentration of
1 mg/L sulfate to keep water MeHg low (Section 12.6.2). which is also a sulfate
concentration that will protect fish from elevated Hg burdens in that system (Figure
12-12). There are also studies in Little Rock Lake, Wisconsin and in watersheds in the
Adirondacks that show relationships between increasing MeHg and removal by microbial
S reduction of sulfate in the water column (Section 12.6).
1.9.2.4 Sulfur, Mercury, and Animal Species
Mercury is a developmental, neurological, endocrine, and reproductive toxin across
animal species. The 2008 ISA documented Hg accumulation in fish, songbirds, four turtle
species, insectivorous passerine birds, and the common loon (Gavia immer). Recent
research also documented Hg accumulation in insectivore songbirds, bats, and fish in
agricultural wetlands. The 2008 ISA reported that 23 states had issued fish advisories by
2007 in response to the U.S. EPA's fish tissue criterion of 0.3 (.ig MeHg/g fish (0.3 ppm),
set to protect human health. The 2008 ISA reported on the negative impacts of Hg on the
development, morphology, survival, or reproduction in the following fish species:
walleye (Stizostedion vitreum), grayling (Thymallus thymallus), mummichog (Fundulus
heteroclitus), rainbow trout (Oncorhynchus mykiss), fathead minnows (Pimephales
promelas), and zebrafish (Danio rerio). However, a recent report on Hg in streams of the
U.S. by the USGS summarizes current research indicating that birds, fish, and fish-eating
wildlife experience negative effects of Hg at lower concentrations than the 0.3 ppm
criterion set to protect human health on the basis of fish consumption (Wentz et al..
2014).
The 2008 ISA documented a link between decreased S deposition and decreased fish
MeHg concentrations. Recent research in Voyageurs National Park (a Class I Area)
supports this finding. There is also supporting evidence from fish surveys of Texas
reservoirs across regions with different S deposition loads, and from a S addition
experiment in a peat bog in the Marcell Experimental Forest in northern Minnesota,
where increased S loading increased Hg concentrations in larval Culex spp. (mosquitoes),
which are an important food source for both aquatic and terrestrial species (Section 12.6
and Figure 12-14). In addition to the studies that consider S deposition, there are recent
studies that consider sulfate concentrations in water in relation to fish Hg concentrations
in six lakes in South Dakota, and in the marshes of the Everglades (Section 12.6).
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1.9.3
National-Scale Sensitivity and Critical Loads
The 2008 ISA identified ecosystems in the Northeast as particularly sensitive to Hg
methylation in response to S deposition, as many watersheds in this region have abundant
wetlands and freshwater water bodies with high DOC and low pH. The U.S. EPA
national stream surveys found that MeHg in predator fish exceeded the Hg criterion in a
quarter of stream miles and half the lakes surveyed. Fish MeHg levels were highest in
streams in watersheds with considerable wetland area, and surveys showed highest fish
MeHg concentrations in the southeastern U.S., suggesting that ecosystems sensitive to
SOx deposition effects upon Hg methylation extend beyond the Northeast. Recent studies
confirm that Hg methylation is more widespread than was documented at the time of the
2008 ISA. New research conducted in agricultural wetlands in California suggests Hg
methylation in these systems may provide a route to animal and human Hg exposure
through food, specifically MeHg concentrations in rice seeds.
1.10 Recovery
Evidence from across the U.S. of ecosystem recovery from N nutrient enrichment and
acidification corresponding to long-term trends in N and S emissions is variable. Overall
N deposition has been relatively steady, and consequently, there has been little research
on N enrichment recovery. Some estuaries have shown improvements in biological
indicators, such as increases in the extent of submerged aquatic vegetation, in response to
decreases in N inputs from atmospheric deposition and in wastewater and agricultural
runoff. For an example, see the Tampa Bay case study (Appendix C).
Total acidifying deposition has decreased in the eastern U.S. in recent decades. However,
the southeastern U.S. shows minimal to no recovery. There are early signs of recovery in
some northeastern U.S. watersheds where soils are less weathered and have smaller stores
of historically-deposited S. In addition to decreased acidification, a few studies report
declines in methylmercury concentrations in biota or water in response to decreasing S,
which is suggestive of ecosystem recovery (Section 12.5).
Long-term monitoring has been very important in tracking the ecological response to N
and acidifying deposition. The historical focus on aquatic acidification has resulted in
more data to evaluate recovery. Fewer studies have tracked the potential recovery of
terrestrial ecosystems since the 1980s (Section 4.6.1). largely because the impacts of
terrestrial acidification were not well understood at that time. Since the early 1990s,
evidence has accumulated that soils in the most sensitive regions continue to acidify in
response to deposition.
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In areas where N and S deposition has decreased, chemical recovery must first create
physical and chemical conditions favorable for growth, survival, and reproduction in
order for biological recovery to occur (Driscoll et al.. 2001b). Recovery is not expected to
recreate historical freshwater biological communities because of differences in the rate of
recovery of aquatic organisms, the permanent loss of some acid-sensitive species, and the
irreversible chemical and physical alterations to aquatic environments (NAPAP. 2011V
New studies continue to support findings in the 2008 ISA that biological response to
water chemistry recovery varies among taxa and among water bodies, and that most
biological communities studied have not returned to pre-acidification conditions, even
after recovery of chemical parameters (Section 8.4V Recent research has described an
ecosystem recovery response to decreasing SOx deposition that was not included in the
2008 ISA—increases in soil DOC leaching and surface water DOC concentrations (Table
1-2. Table 1-3. Section 7.2.3.11). Elevated DOC constrains the extent of ANC and pH
recovery, but also decreases the toxicity of dissolved Al to aquatic organisms. Overall,
DOC increases are inconsistent across surface waters.
The northeastern U.S. and Southern Appalachians are two regions of the U.S. where a
large body of research has evaluated recovery (see Chapter 8 and Appendix C). In the
Northeast, evidence for chemical recovery is primarily from soils (Section 4.6.1) and
freshwater lakes and streams (Section 7.2). In regards to biological recovery
(Section 8.4). newer studies have documented some evidence for zooplankton recovery
and the successful reintroduction of brook trout in previously acidified Adirondack water
bodies or recolonization of previously acidic lakes from refugia.
In contrast to the northeastern U.S., there is little evidence for recovery in the southern
Appalachian Mountain region (see Appendix C). This area is characterized by an
abundance of low-ANC streams situated on acidic, highly weathered soils. Streams in
western Virginia and in Shenandoah National Park are strongly affected by SO42
adsorption on soils, and long-term monitoring studies suggest that soil base cation
depletion has prevented chemical recovery (Section 7.2.4.4). Biogeochemistry modeling
scenarios suggest that even with large decreases in SO42 deposition, it may take decades
for soil base cation levels to recover in this region.
1.11 Climate Modification of Ecosystem Response
Deposition of N and/or S occurs in many ecosystems concurrently experiencing multiple
stressors, including climate change. Recent work has focused on the effects of
anthropogenic N on Earth's radiative forcing and how temperature and precipitation alter
ecological responses to N exposure. The first draft ISA excerpts text from Greaver et al.
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(2016). a review of how climate (e.g., temperature and precipitation) modifies terrestrial
and freshwater response to N, and includes a brief summary of climate and N interactions
in estuaries. Climate effects on ecosystems is a rapidly expanding field. However, for
many pools and processes, there is not yet sufficient empirical evidence to accurately
model the effects of climate on ecosystem N cycling and ecosystem responses to
exogenous N. The incorporation of N and C cycle interaction into recent Earth systems
models used to model global climate is summarized in Chapter 6.
1.12 Ecosystem Services
Ecosystem services are often affected as a result of N or S deposition. Since the 2008
ISA, several new ecosystem services frameworks and classification system have been
published, including the U.S. EPA Final Goods and Services Classification System
(FEGS-CS).
Since the 2008 ISA, several qualitative and quantitative assessments ofN or N and S
deposition effects on ecosystem services have been conducted across Europe and Canada.
Some of the qualitative and conceptual assessments provided descriptions of the complex
and diverse impacts of N deposition on ecosystems. However, most quantitative
assessments were simplified to focus on some or all of the ecosystem services that had
been identified in the 2008 ISA due to uncertainty regarding the physical, biological, or
economic effects on other ecosystem services.
There is a new evaluation of the impact of humans on the global N cycle and how these
impacts relate to changes in ecosystem services. This evaluation includes the negative
impacts of excess N on human health, but also notes that N can increase crop production,
which can support undernourished populations and help fight disease. The paper
concludes that better quantitative relationships need to be established between N and the
effects on human health and ecosystems at smaller scales, including a better
understanding of how N shortages can affect individual populations.
Several species profiles have been created for the current ISA to better characterize the
ecosystem services affected by N and S deposition. The biological species included here
as examples are all threatened and endangered species for which N deposition has been
identified as a contributing stressor (Hernandez et al.. 2016). The species are: balsam fir
(Abies balsamea), eelgrass (Zostera marina), green turtle (Chelonia mydas), white ash
(Fraxinus americana), and lace lichen (Ramalina menziesii). These profiles identify the
geographic distribution of sensitive species within the U.S., ecological function,
threatened and endangered status, Class I areas, FEGS, and cultural importance.
Information on economic valuation is presented when available.
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CHAPTER 2
SOURCE TO DEPOSITION
2.1 Introduction
This chapter provides fundamental and applied atmospheric science information to
support the assessment of the environmental exposures and effects associated with the
deposition of nitrogen (N) and sulfur (S) species. More specifically, these data relate to N
and S emissions sources and rates of atmospheric transformation and transport, total
atmospheric loadings, measurement and modeling techniques, and deposition issues
relevant to this review of the National Ambient Air Quality Standards (NAAQS). This
information serves as prologue for the detailed descriptions of the evidence of
environmental effects from oxidized and reduced N and oxidized S that follow in later
chapters.
Oxidized nitrogen species considered here range from nitrogen oxide (NO) and nitrogen
dioxide (NO2; collectively referred to as NOx) to higher order organic and inorganic
oxidation products, collectively referred to as NOz. NOz is especially relevant when
considering nutrient addition to ecosystems and the acidification of surface waters. NOx
is grouped together with its oxidation products, NOz, as NOy (i.e., NOx + NOz = NOy).
Although nitrous oxide (N2O) is an oxide of nitrogen, it is not a member of the NOy
family and is not considered as this chapter is focused on NOy and reduced nitrogen
(NHx). N2O does not contribute to or contributes very little to, N deposition. It is an
intermediate product in denitrification and nitrification in soils and in the oceans, which
can escape to the atmosphere. N2O is basically inert in the troposphere, but in the
stratosphere it decomposes and contributes to stratospheric ozone depletion. It is a
greenhouse gas and as such contributes to climate forcing as described in the fifth IPCC
Assessment Report [AR5 (IPCC. 2013)1.
Ammonia (NH3) is included in this ISA because of its key role in a number of
atmospheric and aquatic processes. It is the precursor for the ammonium ion (NH4+),
which plays a key role in neutralizing acidity in ambient particles produced from NO2
and sulfur dioxide (SO2) oxidation and in cloud, fog, and rain water. NH3 and NH44" are
conventionally grouped together under the category label NHx (i.e., NH3 + NH4+ = NHx).
However, once deposited on the surface, NH4 can contribute to acidification and nutrient
enrichment/eutrophication. Excess NH3 is also an actor in nitrification of aqueous and
terrestrial ecosystems, participating alone and together with NOy in the N cascade
(Gallowav et al.. 2003). Additionally, NH? is involved in new particle formation in the
atmosphere and reacts with gas-phase nitric acid (HNO3) to form ammonium nitrate
(NH4NO3), a major component of N deposition in many areas of the U.S. For this
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assessment, NOy and NHx are grouped together as total reactive nitrogen, Nr
(i.e., NOy + NHx = Nr). Note that for practical reasons (i.e., a lack of data), this
approximation to the definition of Nr does not include nitrous oxide and reduced organic
nitrogen compounds (which are distinct from oxidized organic species such as
peroxyacyl nitrates and isoprene- and monoterpene-derived nitrates that are components
of NOy). However, to the extent it is available, information on the sources, abundances,
and fate of reduced organic nitrogen is included in the sections to follow.
SO2 is the only oxidized, gas-phase sulfur compound considered here because it is
present in the lower troposphere at concentrations most relevant for environmental
considerations. Moreover, SO2 interacts with particles and cloud drops and is oxidized to
sulfate. Hence, particulate-phase S compounds are also assessed here. SO2 and sulfate
(SO42 ) are conveniently grouped together as SOx (i.e., SO2 + SO42 = SOx).
Sulfuric acid (H2SO4) and HNO3 have been long established as the major species
contributing to acid rain. For this reason, much of the discussion in sections dealing with
chemistry, measurement, and deposition (both wet and dry) focus on these species. Other
N and S species that either hydrolyze to form acids and organic acids are also included, to
the extent they contribute substantively to acidification of terrestrial and aquatic
environments, as are N and S species that contribute to nutrient
enrichment/eutrophication.
Nitrogen and sulfur species of interest occur in both gaseous and particulate forms.
Particles can either be transferred directly to the ground or vegetation directly or be taken
up by cloud droplets and then deposited in precipitation. Major forms in particulate
matter include NH44", nitrate (NO;, ) and SO42 . These components are primarily derived
from gaseous precursors NH3, NOx and SO2 either through chemical reactions occurring
in particles or by condensation of gas phase reaction products. Either they or their
precursors are involved in reactions with PM components such as transition metals and
minerals, or with the formation of secondary organic aerosol, as described in the 2009
ISA for Particulate Matter (U.S. EPA. 2009a').
Section 22 considers sources and emissions of N and S compounds to the atmosphere.
Section 23 summarizes the atmospheric chemical transformations that occur during
transport from sources to deposition to the surface, and Section 2 A discusses the relevant
features of atmospheric transport of these emissions. Section 25_ describes methods used
to measure concentrations of relevant species in the Clean Air Status and Trends Network
(CASTNET), the Interagency Monitoring of Protected Visual Environments (IMPROVE)
network and the Chemical Speciation Network (CSN). Section 2A shows the geographic
distributions of atmospheric concentrations of N and S species involved in acidification
and eutrophication measured by CASTNET and the National Acid Deposition Program
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(NADP). Section 2/7 discusses forms of deposition for both gases and particles and
Section 2J. presents information on the geographical distribution of wet and dry
deposition and on changes in these forms of deposition since 2000 and on longer term
changes in wet deposition across the continental U.S. Section Z9 provides a brief
description of transference ratios, which have been proposed as a means of relating
ambient concentrations to deposition. Section 2.10 considers sources of background N-S
deposition as a means of distinguishing between sources that can be controlled as
opposed to those that cannot be controlled by U.S. regulatory actions. Finally, main
points are summarized and conclusions are given in Section 2.11.
2.2 Sources of Nitrogen and Sulfur Compounds to the
Atmosphere
N and S containing compounds contributing to deposition can be either primary
(i.e., directly emitted from sources) or secondary (i.e., produced from atmospheric
reactions involving precursor species directly emitted from sources). Major primary
species include NOx, SO2, NH3, and reduced organic nitrogen (RON).
Table 2-1 shows nationwide emissions of NOx, SO2, and NH3 by source category
compiled from the 2011 National Emissions Inventory (NEI), and other sources. Updates
to emissions for point source to the 2011 NEI reflecting 2014 have also been included.
Emissions estimates are not available for RON. The NEI is a national compilation of
annually averaged emissions sources collected from state, local, and tribal air agencies, as
well as emission estimates developed by U.S. EPA from measurements by source sector.
For most sources, estimates are generally available for all 50 states and the District of
Columbia.
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Table 2-1 Emissions of NOx (nitric oxide + nitrogen dioxide), sulfur dioxide,
and ammonia by source category for 2014 (Teragrams3 N, S/yr).
NOx
SO2
NHs
Highway vehicles
1.2
0.0
0.081
Off-highway
0.74
0.05
<0.01
Utilities (fuel combustion)
0.49
1.5
0.019
Other stationary (fuel combustion)
0.50
0.41
0.059
Industrial and other processes
0.35
0.27
0.076
Agriculture
0.0
0.0
1.8
Wild, prescribed, agricultural fires
0.53
0.089
0.15
Biogenic
0.28
b
0.08c
Lightning
0.69d
—
-
Total
4.8
2.3
2.3
N = nitrogen; NH3 = ammonia; NOx = the sum of nitric oxide and nitrogen dioxide; S = sulfur; S02 = sulfur dioxide; yr = year.
a1 Teragram = 1 x 109 kg.
b~ = not applicable.
°Bouwman et al. (1997).
dMurrav et al. (2012).
Source: httDs://www.eDa.aov/air-emissions-inventories/air-Dollutant-emissions-trends-data update except as noted.
Table 2-1 shows that NOx, SO2, and NH3 each are for the most part emitted by different
sources. The source categories used in Table 2-1 represent groups of similar NEI source
sectors. Highway Vehicles comprise all on-road vehicles, including light duty as well as
heavy duty vehicles, both gasoline and diesel powered, and represents the largest source
category for NOx emissions. Off-Highway vehicles and engines include aircraft,
commercial marine vessels, locomotives, and nonroad equipment. Utilities (Fuel
Combustion), or electric power generating units (EGUs), include contributions from
combustion of coal (85%) with the remainder from natural gas. Other Stationary (Fuel
Combustion) includes commercial/institutional, industrial, and residential combustion of
biomass, coal, natural gas, oil, and other fuels. Industrial and Other Processes include a
variety of different industries, including chemical manufacturing, cement manufacturing,
and oil and gas production. The other processes included in this category consist of a
number of miscellaneous sectors, including gasoline stations and terminals, commercial
cooking, road and construction dust, solvent use, and waste disposal. More than half of
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NOx emissions in the NEI are from transportation-related sources, including Highway
and Off-Highway vehicles and engines, with about one fourth from Utilities, Fuel
Combustion-Other and Industrial Processes.
Atmospheric measurements made during recent field studies have been used to evaluate
NEI estimates. For example, Anderson et al. (2014). based on analysis of aircraft
measurements made during DISCOVER-AQ and modeling results, estimated that NOx
emissions from mobile sources have been overestimated by -50 to 75% in the 2005 NEI
and perhaps by a larger amount in the 2011 NEI. Travis et al. (In Press) suggested that
the NEI for NOx in the U.S. is likely too high on a nationwide basis by -50%, based on
wet deposition of NO3 , satellite measurements of NO2, and measurements of NOx
oxidation products made during the Studies of Emissions and Atmospheric Composition,
Clouds and Climate Coupling by Regional Surveys (SEAC4RS). NOx emissions from
point sources are better known because continuous emissions monitoring systems are
used in many facilities (e.g., EGUs) for which accurate production records need to be
kept. This would imply that emissions of NOx from other sources in the inventory
(e.g., mobile sources) are being overestimated. Although these studies were conducted in
specific regions (the Mid-Atlantic and the Southeast) for limited time spans, they
nonetheless raise concerns that overall source strengths may be overestimated in the NEI.
In contrast to NOx, SO2 emissions are dominated by stationary sources burning fossil
fuels, particularly EGUs, which contribute about 70% of total nationwide SO2 emissions.
As a result, most SO2 emissions originate from point sources having well-known
locations and identifiable fuel streams. Uncertainties in annual emissions were estimated
to range from 4 to 9% for SO2 and slightly larger for NOx from the same point sources
identified in the 1985 NAPAP inventories for the U.S. (Placet et al.. 1990). However, the
fractional contribution of NOx from large point sources is much smaller than for SOx,
implying a much larger contribution from more disperse and more uncertain area sources
for NOx as mentioned above. Emissions factors for easily measured fuel components that
are released completely or almost completely during combustion (e.g., CO2, SO2) should
be the most reliable (Placet et al.. 2000). As described in the previous ISA for Oxides of
Nitrogen and Sulfur-Ecological Criteria (U.S. EPA. 2008a). SO2 emissions densities in
most counties east of the Mississippi River are larger than in most counties in the West.
Agriculture includes both fertilizer application and livestock waste emissions. Fires
include wildfires, prescribed fires, and agricultural field burning.
The biogenic category includes emissions from vegetation and soil. Both nitrifying and
denitrifying organisms in the soil can produce NOx, mainly in the form of NO.
Nationwide, about 60% of the total NOx emitted by soils is estimated to occur in the
central Corn Belt of the U.S. Spatial and temporal variability in soil NOx emissions leads
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to considerable uncertainty in emissions estimates. Soil emissions occur mainly during
summer and occur across the entire country, including areas where anthropogenic
emissions are low. Emission rates depend primarily on fertilization amount, soil
temperature, and moisture. Models of NOx emissions from soils (e.g., Hudman et al.
(2012) include these dependencies, but most measurements on which they are based are
made at temperatures <30°C. However, in agricultural areas subjected to very high
temperatures (>40°C) like the Imperial Valley, CA, emissions factors for NO following
fertilizer application ranged from 1.8 to 6.6%, as compared to estimates of typically ~1 to
2% (Oikawa etal.. 2015). Oikawa et al. (2015) also suggest that in many areas of the
Southwest, the NEI overestimates anthropogenic emissions at the expense of soil
emissions and that these soil emissions have a noticeable effect on ozone formation.
Travis et al. (In Press) estimate that combustion accounts for 68% of NOx emissions in
the Southeast in summer—with the remainder from soils. These results indicate that soil
emissions need to be better understood.
NH3 originates mainly from agriculture, which accounts for -80% of its emissions
nationwide. Agriculturally related sources consist of livestock, including confined animal
feeding operations, and soils after addition of N containing fertilizers. Fertilizer
application occurs mainly during spring and summer. In addition to NH3, reduced organic
compounds such as urea and a wide range of proteins and other biological components
are also emitted as the result of agricultural activity. As described in Section 2/7, NO2 and
NH3 can be both emitted from and deposited to soils, water, or vegetation depending on
their atmospheric concentrations and characteristics of the underlying surface. Activity
rates and uncertainties for a number of very disperse fugitive sources (e.g., NH3) are
difficult to quantify, and estimates have yet to be made for reduced organic nitrogen.
Although lightning is shown as a relatively modest source (-13%) of NOx, most
production by lightning occurs during the summer and is highest in the south-central and
southwestern U.S. (Zhang et al. 2012a). Fang et al. (2010) estimated that -98% of
lightning-generated NOx is formed in the free troposphere where it is oxdized to species
such as nitric acid and peroxy acetyl nitrate. The remaining 2% is formed within the
planetary boundary layer.
The entries in emissions inventories are typically obtained using a bottom-up approach,
in which entries are based on emissions factors, activity rates, and control device
efficiency for various source types. This contrasts to a top-down approach in which
measurements of pollutant concentrations from satellites, aircraft, or surface monitors are
used to constrain a priori estimates of emissions using a chemistry-transport model
(CTM). The emissions in the CTM are optimized by minimizing a cost function
containing contributions from the difference between model predictions and observations.
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Other terms such as the difference between the bottom-up (emissions inventory) and the
optimized inventory can also be added. As an example of this methodology, Paulot et al.
(2014) derived optimized NH3 emissions for the CONUS of 2.8 MT N/yr based on
inversion of wet deposition data from the NADP/NTN. Note however that model
estimates of dry deposition of NH3, which have their own set of uncertainties, were used.
The use of remotely sensed data for measurements of pollutants for this and other
applications is further discussed in Section 25_.
2.3 Atmospheric Chemistry of Nitrogen and Sulfur Species
The atmospheric chemistry of N and S species relevant for the production of ecosystem
nutrients and acidic species was extensively reviewed in the previous ISA for Nitrogen
and Sulfur Oxides (U.S. EPA. 2008a'). The main findings from that review and key
findings from more recent studies and reviews are included here. NOx (NO + NO2) is the
precursor for oxidized nitrogen species that contribute to acidic deposition. NOx, its
oxidation products, and NH3 also serve as nutrients to many ecosystems. More specific
details on the chemistry and transformation of NOx can be found in the 2016 ISA for
Oxides of Nitrogen-Health Criteria (U.S. EPA. 2016b) and for SOx in the 2008 ISA for
Sulfur Oxides (U.S. EPA. 2008c). Hence, those topics are only briefly recounted here
with special reference to the secondary NOx and SOx NAAQS.
Oxidized nitrogen species (NOy) are introduced into the atmosphere as NOx, mainly
from fossil fuel combustion as summarized in Section 7J1. Figure 2-1 summarizes the
atmospheric reactions of NOx, showing rapid inter-conversion of NO and NO2 in
sunlight, with slower formation of more oxidized organic and inorganic products (NOz).
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NO
NO
NO
ORGANIC
PRODUCTS
PAN
INORGANIC
PRODUCTS
>no3-^hno3
HO;
hv
NH
RO;
NO
NO
' > f
deposition
deposition
emissions
Ca2+ = calcium ion; HN03 = nitric acid; H02 = hydroperoxy radicals; hi/ = solar photon; Mg2+ = magnesium; NH3 = ammonia;
NH4+ = ammonium; NO = nitric oxide; N02 = nitrogen dioxide; N03" = nitrate ion; N0X = the sum of NO and N02; NOz = oxidation
products of NOx; NOY = NOx + NOz; 03 = ozone; PAN = peroxyacetyl nitrate; R02 = organic peroxy radicals.
Note: The inner shaded box contains NOx (NO + N02). The outer box contains other species (NOz) formed from reactions of NOx.
All species shown in the outer and inner boxes are collectively referred to as NOY by the atmospheric sciences community.
Source: NCEA.
Figure 2-1 Schematic diagram showing pathways for reactive nitrogen
species in ambient air.
1 A large number of oxidized nitrogen species in the atmosphere are formed from the
2 oxidation of NO and NO2 (shown in the inner box). These include nitrate radicals (NO3),
3 nitrous acid (HONO), nitric acid (HNO3), dinitrogen pentoxide (N2O5), nitryl chloride
4 (CINO2), peroxynitric acid (HNO4), peroxyacetyl nitrate (PAN) and its homologues
5 (PANs), other organic nitrates, such as isoprene- and monoterpene-derived nitrates, and
6 particulate nitrate (pNO, ). These species (and NH3) are characterized by large
7 differences in their solubility (Table 2-2). which determines their ability to be taken up by
8 cloud droplets, airborne particles, and moist surfaces.
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Table 2-2 Henry's law coefficients for selected reactive nitrogen species at
25°C in water.
Compound
Coefficient [mol/kg/bar]
HNOs
2.6 x 10®
HONO
49
NO
0.0019
NO2
0.012
PAN
4.1
NHs
61
1 bar = 105 Newtons/m2; C = Celsius; HN03 = nitric acid; HONO = nitrous acid; NH3 = ammonia; NO = nitric oxide; N02 = nitrogen
dioxide; PAN = peroxyacetyl nitrate.
Source: Adapted from Sutton et al. (2011).
Reactions producing more oxidized forms of nitrogen (NOz) involve mainly O3, OH, and
organic radicals with NO and NO2. Reaction of NO2 with OH leads directly to HNO3:
NO2 + OH + M HNOs
Equation 2-1
Reaction ofN02 with O3 produces nitrate radical (NO3), which reacts further to form
dinitrogen pentoxide (N2O5), and ultimately also produces HNO3:
NO2 + O3 NO3 + O2
Equation 2-2
NO2 + NO3 N2O5 (equilibrium)
Equation 2-3
N2O5 + H2O 2 HNOs
Equation 2-4
The relative importance of these two paths for producing HNO3 is strongly location and
seasonally dependent, with the first path dominating when OH radicals are abundant
(during the day) and the second during the night and under cold conditions. Warneck
(1999) estimated that most HNO3 is formed in the sunlit portions of clouds by the
reaction of NO2 with OH, with much smaller amounts from the pathway involving N2O5
hydrolysis. As it is highly soluble, HNO3 is taken up by particles or cloud droplets to
form N03 and is also deposited onto moist surfaces, such as on vegetation. HNO3 also
recycles back to NO2 in the gas phase by photolysis and reaction with OH radicals, but on
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timescales longer than that for uptake by cloud droplets, particles, and the surface.
Whereas photolysis of HNO3 is slow (x ~ 106 s) in the gas phase, it can be two orders of
magnitude faster on moist surfaces (Ye et al.. 2016). releasing NO2 and/or HONO back to
the atmosphere.
NO2 reacts with organic peroxy radicals to form organic nitrates such as peroxyacetyl
nitrate (PAN) and its homologues as shown on the right side of Figure 2-1; other RO2NO2
compounds are much less stable than PANs. NO and NO3 radicals also react with organic
radicals produced by the oxidation of isoprene and monoterpenes to form a wide range of
organic nitrates. Considering the troposphere as a whole, most of the mass of NOz shown
in Figure 2-1 is in the form of PAN and HNO3. However, organic nitrates such as
isoprene- and monoterpene-derived nitrates increase in importance in the planetary
boundary layer (PBL), and are likely to be dominant in vegetated areas (Kim et al.. 2015;
Min et al.. 2014).
In forested areas, the initial step in the production of isoprene nitrates (INs) is most often
the reaction of isoprene with OH radicals to produce isoprene peroxy radicals. These can
react with HO2 radicals, other RO2 radicals, or isomerize to produce a variety of organic
compounds. They can also react with NO to produce multifunctional organic nitrates.
Lifetimes on the order of one to a few hours can be estimated for these first generation
INs based on their reactions with OH radicals and O3 (Lockwood et al.. 2010; Paulot et
al.. 2009). The reaction products can further react with NO (after internal rearrangement)
to form secondary organic nitrates such as ethanal nitrate, methacrolein nitrate,
propanone nitrate, and methyl vinyl ketone nitrate. The second-generation organic
nitrates are more stable than the first-generation INs because they lack a double carbon
(C = C) bond. Obviously, the relative importance of pathways forming nitrates or other
products depends on the ambient concentrations of NO and other oxides of nitrogen for
which many key experimental details are still lacking. During the SEAC4RS
measurement campaign, which took place in the summer of 2013 in the southeastern
U.S., Travis et al. (In Press) found that these two pathways were of comparable
importance.
In addition to oxidation initiated by OH radicals, isoprene is also oxidized by NO3
radicals. Rollins et al. (2009) determined a yield of first-generation carbonyl nitrates of
70% based on experiments in large reaction chambers. These first generation nitrates can
further react with NO, leading to the production of second-generation organic (alkyl)
nitrates. Mao et al. (2013) estimated that the global mean lifetime is ~5 days for these
second-generation organic nitrates. Mao et al. (2013) also suggested that the export of
INs and other organic nitrates followed by their decomposition is potentially a larger
source of NOx to the boundary layer of the western North Atlantic Ocean than the export
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of PANs. It should also be noted that some INs are low enough in volatility that they can
partition to the particle phase [e.g., Rollins et al. (2009)1. Once in the particle phase, the
INs hydrolyze to form HNO3 and an alcohol, with a rate constant that correlates strongly
with the acidity of the particles (Rindelaub et al.. 2015; Jacobs et al.. 2014).
In addition to considering the chemistry of isoprene-derived nitrates during SEAC4RS,
Fisher et al. (2016) considered the formation of organic nitrates derived from the
oxidation of monoterpenes with either one or two double bonds. Their modeling results
suggest that isoprene- and monoterpene-derived nitrates account for 25 to 50% and -10%
of total organic nitrates and that production of isoprene- and monoterpene-derived
nitrates account for -20% of the net loss of NOx emitted in the Southeast during summer.
Fisher et al. (2016) also note that production of organic nitrates involving biogenic VOCs
is the dominant NOx sink only in areas where elevated levels of biogenic VOCs coincide
with low NOx levels (otherwise the major sink would be formation of HNO3). As a
result, these processes will represent only a minor pathway for NOx loss. In any event, as
with isoprene-derived nitrates, monoterpene-derived nitrates are also mainly taken up by
particles with formation of HNO3. Uptake by particles was estimated by Fisher etal.
(2016) to account for -60% of the removal of gas-phase organic nitrates, with -20%
recycled back to NOx and another 15% deposited to the surface.
As the most common soluble base in the atmosphere, NH3 plays a key role in neutralizing
the acidity in ambient particles and in cloud, fog, and rainwater resulting from dissolution
of H2SO4 and HNO3, and the weak acidity due to organic acids. The atmospheric lifetime
of NH3 with respect to oxidation by OH radicals is -2 months [based on
OH = 106 molec/cm3 and rate coefficient =1.6/ 10 'VcmVmolcc/s: (Sander et al..
2011)1. As a result, uptake by cloud droplets, particles, and the surface is favored over
reaction with OH radicals. Xu and Penner (2012) estimate a globally averaged lifetime
for NH3 of -11 hours as a result of these processes, implying strong spatial and temporal
variability of NH3 concentrations.
2.3.1 Sulfur Oxides
SO2 is the only gas phase form of SOx (SO2 + SO42 ) emitted in the tropospheric
boundary layer at concentrations of concern for environmental exposures (U.S. EPA.
2008c). It reacts in both the gas phase and in aqueous solution in clouds and particles to
form SO42 . As described in the previous ISA for Oxides of Nitrogen and
Sulfur-Ecological Criteria (U.S. EPA. 2008a). the steps involved in aqueous-phase
oxidation of SO2 begins with dissolution of SO2 following Jacobson (2002):
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S02(g) S02(aq)
Equation 2-5
and is followed by formation and dissociation of H2SO3:
S02(aq) + H2O H2S03(aq) H+ + HSOs" 2H+ + SOs2"
Equation 2-6
Dissolved SO2 thus rapidly partitions into four forms with the same oxidation state, with
their relative concentrations dependent on pH:
S(IV) = S02(aq) + H2S03(aq) + HSOs"(aq) + SOs2"(aq)
Equation 2-7
S(IV) is then oxidized to SO42 in cloud water primarily by either H2O2, O3, and O2 in the
presence of dissolved Fe(III). Reaction with H2O2 is most important at pH less than about
5.3, and reaction with either dissolved O3 or with O2 catalyzed by Fe(III), becomes most
important at pH greater than about 5.3, as shown in Figure 2-2 (Seinfeld and Pandis.
1998V
The remaining SO2 is oxidized to H2SO4 in the gas phase with a characteristic time scale
of -10 days [based on OH = 106/cm3 and rate coefficient = 1.3 x 10 l2/cm7molcc/s:
(Sander et al.. 2011)1 following a multistep process:
SO2 + OH + M HSOs + M
Equation 2-8
HSOs + O2 ^ SOs + HO2
Equation 2-9
and/or by
SO2 + sCI -> SO3 + products
Equation 2-10
where sCI is a stabilized Criegee intermediate (Bemdt et al. 2012; Mauldin et al.. 2012;
Welz et al.. 2012) and products refer to other organic radicals. Criegee radicals are
produced by the reaction of alkenes with O3 during both night and day. The relative
importance of the OH and sCI pathways depends in large measure on the local
concentration of alkenes, in particular biogenic alkenes. Welz et al. (2012) also raised the
possibility that Criegee radicals might be important for the oxidation of NO2 to form
nitrate radicals. SO3 produced by either path further reacts to form gas-phase H2SO4 via
SOs + H2O ^ H2SO4
Equation 2-11
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aq = aqueous; Fe(lll) = iron (oxidation number III); H202 = hydrogen peroxide; Mn(ll) = mangnanese (oxidation number II);
N02 = nitrogen dioxide; 03 = ozone; S(IV) = sulfur (oxidation number IV); S02 = sulfur dioxide.
Concentrations assumed are: [S02(g)] = 5 ppb; [N02(g)] = 1 ppb; [H202(g)] = 1 ppb; [03(g)] = 50 ppb; [Fe(lll)(aq)] = 0. 3 |jM;
[Mn(ll)(aq>] = 0.03 |jM.
Source:Seinfeld and Pandis (1998).
Figure 2-2 Rate of conversion of sulfur (IV) to sulfur (VI) by different
oxidation paths as a function of pH.
Because H2SO4 is extremely soluble, it is removed rapidly by transfer to the aqueous
phase of particles and cloud droplets. Sulfuric acid can be partly or totally neutralized by
NH3. Seinfeld and Pandis (1998) define two regimes: (1) ammonia poor [TA] <2 [TS]
and (2) ammonia rich [TA] >2 [TS], where TA and TS refer to total ammonia,
ammonium and sulfate concentrations in gas, aqueous, and solid forms. In the 1st regime,
there is partial neutralization; sulfate is in the form of (NH4)HS04, the vapor pressure of
NH3 is very low, equilibrium favors formation of ammonium sulfate over ammonium
nitrate, any nitrate is driven to the gas phase, and ammonium nitrate levels are low (or
even zero). In the 2nd regime, sulfate is in the form of (NH^SO-i, and any NH3 left over
could react with HNO3 to form NH4NO3. However, this conceptual model neglects
interactions with organic compounds. Analysis of data by Kim et al. (2015) from the
SEAC4RS field study and the Chemical Speciation Network (CSN) during
August-September of 2013 indicates that the extent of neutralization of sulfuric acid and
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acidic sulfate by ammonium was incomplete in the Southeast despite an excess of
atmospheric NH3. Kim et al. (2015) suggested that uptake of NH3 is inhibited by organic
compounds in particles. This suggestion is in accord with laboratory studies of Liggio et
al. (2011) who found that organic compounds, especially terpenes and «-alkanes on
particle surfaces are effective in inhibiting NH3 uptake by particles.
NH4NO3 is in thermodynamic equilibrium with gas-phase NH3 and HNO3. The
equilibrium constant is extremely sensitive to variations in relative humidity and
temperature such that it varies over several orders of magnitude depending on
atmospheric conditions, but in general, lower temperature and higher relative humidity
(e.g., during winter) shifts the equilibrium towards NH4NO3. The effects on phase
partitioning are pronounced because of the large variation in the equilibrium constant, K,
(—10—103 ppb2) between summer and winter conditions in many locations. Also, as noted
by Malm et al. (2016). NH4NO3 can volatilize and reform multiple times during transport
away from sources of NH3 and HNO3. Because the atmospheric lifetimes of NH3, HNO3,
and NH4NO3 differ substantially from each other, local conditions of temperature and
relative humidity, by implication, control how far these species can travel.
Although the above considerations apply to particles in general, it should be remembered
that the mass of airborne particles is present in two distinct size fractions each with its
own characteristic composition [see U.S. EPA (2009aYI. These differences determine the
size fraction in which pNCh will be found. Because sulfate is found mainly in the fine
particle mode these considerations tend to apply more to the atmospheric fine mode.
Displacement of HC1 (and other hydrohalic acids) from marine aerosol (found typically
in the coarse mode) by gas-phase HNO3 has long been known to occur, resulting in
particulate nitrate (pNCh ) being associated with sodium in the coarse mode in many
coastal areas. Brimblecombe and Clegg (1988) provide a detailed evaluation of the
thermodynamic data and a discussion of this process. Wolff (1984) found that
coarse-mode pNChis formed by adsorption of HNO3 on basic soil particles (i.e., those
containing Ca2+ and Mg2+). These distinctions between the behavior of pNCh in the fine
and coarse modes are important as deposition rates for these two size modes can differ
appreciably and there can be appreciable differences in the ratio of fine to coarse pNO,
as shown in Section 2.7.
The composition of rainwater and of particles is strongly affected by pH. As described
above, the pH of cloud water determines the distribution of S(IV) species in rainwater
and the aqueous phase of particles and their oxidation processes (as described above), and
in turn the solubility of trace metals, and the partitioning of weak acids among other
factors. As the most abundant base in the atmosphere, NH3 has a strong influence on pH
of cloud water. However, the role of NH3 as a base is limited to atmospheric processes.
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Once deposited in soil, oxidation of NH3 and NH4+ to NO3 (during nitrification)
produces an amount of H+ equivalent to HNO3 deposition I Scheffe et al. (2014) and
references therein].
2.3.2 Organic Nitrogen and Sulfur
In addition to deposition of NOy and NHx, deposition of other nitrogen compounds, in
particular dissolved organic nitrogen (DON) consisting of proteins, amino acids, urea,
and amines, for example, must be considered. These compounds can contribute to
acidification in soils and be an important source of nutrients to terrestrial and aquatic
environments (Jickells et al. 2013; Cape etal.. 2011; Cornell. 2011b; Sutton et al. 2011).
The content of organic nitrogen in particles and rainwater can be characterized in two
ways. In the first, it can be calculated as the difference between total N as measured by
total elemental analysis [see e.g., Bronk et al. (2000)1 minus NO3 and NH44". In the
second way, the content of organic nitrogen in particles and rainwater can be
characterized by measuring the concentrations of individual species. However, the
number of species constituting DON at a particular location can be quite large. For
example, Altieri et al. (2009a) detected several thousand organic N containing species in
precipitation samples collected in New Jersey and found the overall composition was
consistent with oligomerization of amino acids; in most compounds, N was in reduced
form.
Cornell (201 la) estimated on the basis of measurements reported in 58 published studies
that organic N constitutes 35% of total N in rainwater in North America. Jickells et al.
(2013) estimated on the basis of data from a number of measurement sites
(n = 115 globally), that average DON in rainwater contributes -25% of the flux of total
nitrogen. They also reasoned that because it is correlated with total nitrogen in rainwater
(If = 0.57), which has a large anthropogenic component, DON might also have a large
anthropogenic component. Further description of DON measured at sites in the CONUS
are deferred to Section Z8.
A large number of organosulfates (R-O-SO3H) have been detected in rainwater samples
(Altieri et al.. 2009b). However, their abundances could not be determined. Tolocka and
Turpin (2012) estimated that organic sulfates could contribute up to 5 to 10% of organic
mass on average to particle mass based on measurements taken at 12 sites across the U.S.
Liao et al. (2015) found that organic sulfates contributed a few percent to particulate
sulfate, mainly from the two most abundant forms, isoprene epoxydiol sulfate and
glycolic acid sulfate. Organic sulfates such as these have low pKa's and are expected to
act as singly charged species.
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Phytoplankton emit copious amounts of dimethyl sulfide which can be oxidized to sulfur
dioxide and to methane sulfonic acid. The SO2 that is formed can then be a source of
H2SO4 in coastal areas.
2.3.3 Organic Acids
The effects of deposition of acidic sulfur and nitrogen should be considered in the context
of a more complete description of the composition of rainwater, including organic acids.
However, organic acids are not routinely measured by monitoring networks because they
are unstable with respect to microbial degradation following collection. As a result, data
for organic acids in rainwater are sparse. Formic and acetic acids are typically the most
abundant organic acids found in rainwater in the U.S. (Willev et al.. 2011; Avery et al..
2006; Talbot et al.. 1990). They are largely secondary in origin (i.e., produced in the
atmosphere by the photochemical oxidation of biogenic and anthropogenic
hydrocarbons). Paulot et al. (2011) suggest that isoprene oxidation is the largest global
source of formic and acetic acids. These acids are also produced by the oxidation of
ethane and propylene emitted in automobile exhaust. Their abundances in rainwater and
their effects on pH are not negligible. For example, Willev et al. (2011) found that formic
acid (pKa = 3.75) and acetic acid (pKa = 4.76) were the major organic acids present and
contributed -22 and 5% of free acidity (mean pH = 4.65) in rainwater samples collected
at Wilmington, NC in 2008. In addition, other organic acids (e.g., oxalic acid, lactic acid)
have been found to be present at much lower levels at this site (Avery et al.. 2006). Vet et
al. (2014) note that organic acids should be monitored in areas where the concentration of
H+ is <5 |icq/L (or pH > 5.3). As will be seen in Section 2.8. this condition is met in areas
like the Northwest where concentrations of NO, and SO42 in rainwater are low. Even in
areas where the effects of organic acid neutralization by NFU+ might be small, the vapor
pressures of some organic acids (e.g., oxalic acid) would be reduced by orders of
magnitude, resulting in increased uptake of the organic acid from the gas phase and
growth of particles (Ortiz-Montalvo et al.. 2014; Paciga et al.. 2014).
2.4 Atmospheric Transport of Nitrogen and Sulfur Species
A variety of mechanisms operating over a wide range of spatial and temporal scales
transport heat, water, and pollutants horizontally and vertically through the atmosphere.
These mechanisms range from local-scale circulations (e.g., urban heat islands) to
hemispheric-scale transport by the jet stream. Long-range transport of pollutants in the
lower free troposphere associated with large-scale synoptic systems is possible because
flows are largely uncoupled from surface friction. Flows in the upper planetary boundary
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layer (PBL), especially during the day, might not be as effective for transporting
pollutants over long distances because air can be mixed down to the surface by
turbulence. If these pollutants react with surface material or are taken up by vegetation,
they can be removed within a relatively short distance from their sources.
In the nocturnal residual layer, low level jets (LLJs) can rapidly transport pollutants
across hundreds of km. Deep convection and the air streams within mid-latitude cyclones
transport air from the boundary layer to the upper troposphere, where winds are much
stronger, resulting in effective regional- to hemispheric-scale transport. The latter
processes involving moist convection are more strongly associated with precipitation than
are phenomena, such as LLJs or large-scale circulations around a high pressure system,
such as the Bermuda High.
In addition to wind velocity, the distance scale for transport of a pollutant that is
relatively stable in the troposphere with respect to gas-phase reactions (i.e., chemical
lifetime > a few days) depends strongly on the pollutant's interactions with solid and
liquid surfaces and subsequent chemical transformations. Because NO and NO2 are only
slightly soluble, they can be transported over longer distances in the gas phase than can
more soluble species, like HNO3 (and its anhydride, N2O5) and NH3 that are depleted by
deposition to moist surfaces or taken up more readily on aqueous surfaces of particles or
on cloud drops. For example, measurements of the ratio of NH3 to CH4 in the San
Joaquin Valley indicate substantial loss of NH3 to the surface within a few km of sources
of these gases (Miller et al.. 2015). consistent with an NH3 lifetime of minutes to a few
hours in this environment. On the other hand, GEOS-Chem modeling results over the
eastern U.S. indicate an atmospheric lifetime for SO2 of 13 hours in summer increasing to
48 hours in winter, compared to lifetimes of 19 ± 7 hours in summer increasing to
58 ± 20 hours in winter based on analysis of in situ measurements (Lee et al.. 2011)
indicating the potential for much longer range transport of SO2.
In many areas in the U.S., LLJs transport pollutants, such as SO2 and NOx emitted by
EGUs, over hundreds of km overnight [for example, see Husar et al. (1978)1. The
evolution of LLJs is shown schematically in Figure 2-3; areas where they occur most
frequently are shown in Figure 2-4. As can be seen from Figure 2-4. LLJs tend to form to
the east of mountain ranges, such as the Rockies and the Appalachians.
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Free Atmosphere
Cloud Layer
Cloud Layer
Residual Layer
U)
Mixed
Layer
Mixed
Layer
C Low Level Jet
Stable Nocturnal Boundary Layer
0-
Surface Layer
Afternoon
Sunset
Midnight
Sunrise
Noon
Source: Adapted from Stull (1988) Figures 1.7 and 12.1.
Figure 2-3 The diurnal evolution of the planetary boundary layer when high
pressure prevails over land. Three major layers exist (not
including the surface layer): a turbulent mixed layer; a less
turbulent residual layer, which contains air formerly in the mixed
layer; and a nocturnal, stable boundary layer, which is
characterized by periods of sporadic turbulence.
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Most
Frequent
Arrows indicate the direction of flow.
Source:Bonner (1968).
Figure 2-4 Locations of low-level jet occurrences in decreasing order of
prevalence (most frequent, common, observed). These locations
are based on 2-year radiosonde data obtained over limited areas.
1 Large-scale synoptic systems (e.g., the Bermuda High) are very efficient in transporting
2 pollutants over the continental scale and pollutants are also transported offshore. Figure
3 2o shows a schematic of the Bermuda High, which is a dominant climatological feature
4 controlling the weather pattern in the eastern U.S. during summer. Figure 2-5 also
5 illustrates the interaction between the Bermuda High and the track of a hurricane or a
6 lesser tropical disturbance. Air to the left of the high is transported northward and
7 eastward around the high, and oxidation products of NOx and SO2 emitted in the Ohio
8 Valley affect the Adirondacks and New England. There is also the potential for recycling
9 of air pollutants back into the U.S. through the Gulf of Mexico.
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40
TlO °W 100 "W 90 'W 80 'W 70 °W 60 °W 50 'W 40 'W
©The COMET Program
Source: meted.ucar.edu.
Figure 2-5 Idealized flow pattern around a Bermuda High.
Dickerson et al. (1987) documented the importance of deep convective transport of
boundary layer pollutants to the upper troposphere. Once pollutants are lofted to the
middle and upper troposphere, they typically have a much longer chemical lifetime and,
with the generally stronger winds at these altitudes, can be transported long distances
from their source regions. Thunderstorm updraft regions, which contain copious amounts
of water, are places where efficient scavenging of soluble species can occur and be rained
out.
In advancing frontal systems (e.g., a cold front), air rising along the front brings
pollutants along with it, and at high enough altitudes, water condenses and falls as rain
bringing with it soluble pollutants. Basically, this transport occurs over the length of the
frontal system, which can be on the order of a thousand km. This system of transport is
like a conveyor belt transporting air, water, and pollutants northward and eastward
between continents (Cooper et al.. 2002). Thus, mechanisms transporting pollutants into
the free troposphere are generally more effective for long-range transport than those
involving near-surface winds.
Transport of surface emissions associated with the passage of a frontal system, which
typically might follow the Bermuda High, is shown in Figure 2-6. The overall airflow
pattern is complex and composed of several air streams, often referred to as conveyor
belts: WCB = warm conveyor belt; CCB = cold conveyor belt; DA = dry airstream; and
PCFA = post cold front airstream. Values on the CCB and WCB air streams refer to
pressure levels (in hPa) reached by these air streams as the weather system moves and
evolves over the course of several hours. Because the warm conveyor belt involves rising
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motions, condensation of water vapor followed by rain occurs. The form of the WCB
implies that the system can entrain pollutants that can then undergo aqueous-phase
chemistry in cloud droplets and be transported to the north and east and mixed along the
length of the cold front, which can extend over a distance of the order of a thousand km.
The cold conveyor belt also represents rising motion that can lead to cloud formation and
precipitation. The dry air stream represents cold air descending from the upper
troposphere and the stratosphere; values indicate the pressure at the bottom of the dry air
stream. The post cold frontal air stream represents transport of cold, dry surface air
following the passage of a cold front.
PC FA \ AO?
WCB
CCB = cold conveyor belt; DA = dry airstream; WCB = warm conveyor belt; PCFA = post cold front airstream.
Values Indicate pressure in hectopascals as air moves pollutants with altitude (see text).
Source: Adapted from Cooper et al. (2002).
Figure 2-6 Transport by conveyor belts associated with a frontal system
shown as heavy black lines.
Air (and pollutants) lifted from the polluted boundary layer to the free troposphere by the
warm conveyor belt can be transported rapidly by the jet stream between continents.
These pollutants can then be delivered to the surface by subsidence, especially around
long-lived high pressure systems, for example, the leading edge of the Bermuda High (for
the Atlantic Ocean) or the Central Pacific High (for the eastern Pacific Ocean and
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western North America). As a result, nitrate is delivered to the open oceans and pollutants
are transported from Asia to North America and from North America to Europe.
Intercontinental transport of O3 and PM has been the focus of efforts by the Task Force
on Hemispheric Transport of Air Pollution (HTAP). To the extent that N and S species
are transported along with O3 and PM, they also contribute to deposition following
subsidence to the surface. Further details on the contribution of foreign emissions to
deposition in the contiguous U.S. are given in Section 2.10.
2.5 Techniques for Measuring Nitrogen and Sulfur Species in the
Atmosphere
An extensive review of techniques for measuring NOx, NOz, NOy, NHx, and SOx
appeared in the previous ISA for Oxides of Nitrogen and Sulfur-Ecological Criteria (U.S.
EPA. 2008a). Updates to techniques for measuring NOx, NOy, and SOx species can be
found in the latest ISA for Oxides of Nitrogen (U.S. EPA. 2016b) and for Sulfur Oxides
(U.S. EPA. 2008c) to which the reader is referred for details. Only brief summaries are
presented here. Most relevant for the current review are NOy, and SOx because they have
been recommended as indicator species of the Nitrogen and Sulfur Oxides Secondary
NAAQS following the U.S. EPA's Science Advisory Board Integrated Nitrogen
Committee (U.S. EPA. 201 lb). Methods for measuring major constituents of NOy and
NHx are also included because of their involvement with acidification and eutrophication.
All of the species discussed in this section are measured either in the CASTNET and/or
NCore networks. Species measured in CASTNET include: O3, SO2, HNO3 in the gas
phase and SO42 , NO3 . NH4+, Ca2+, Mg2+, K+, Na+, and Cl~ in particles. CASTNET
consists of 261 sites and NCore consists of 76 sites across the CONUS. Most NCore sites
are located in urban areas with only several collocated with CASTNET sites. Maps
showing the locations of CASTNET sites and measured species concentrations can be
found in Section 2J>- In addition to CASTNET, several other monitoring networks are
operated either by the U.S. EPA or jointly with other federal agencies; species measured
and other details for networks making measurements relevant for deposition are shown in
Naess (2016).
2.5.1 Measurements of Nitric Oxide and Nitrogen Dioxide
Measurements of NO and NO2 are considered first because the accepted method for
measuring NOy is based on the Federal Reference Method (FRM) for measuring NO and
NO2. Nitric oxide (NO) is routinely measured using the chemiluminescence induced by
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the compound's reaction with O3 at low pressure. The FRM for NO2 makes use of this
technique of NO detection with a prerequisite step that is meant to reduce NO2 to NO on
the surface of a molybdenum oxide (MoOx) substrate heated to between 300 and 400°C.
Because the FRM monitor cannot detect NO2 directly, the concentration of NO2 is
determined as the difference between the NO in the air stream passed over the heated
MoOx substrate and the NO in the air stream that has not passed over the substrate.
However, the reduction of NO2 to NO on the MoOx catalyst substrate also reduces other
oxidized nitrogen compounds (i.e., NOz compounds shown in the outer box of Figure
2-1) to NO. This interference by NOz compounds has long been recognized following
Winer et al. (1974) who found over 90% conversion of PAN, ethyl nitrate, ethyl nitrite,
and «-propyl nitrate and 6-7% conversion of nitroethane to NO with a MoOx converter.
HNO3 also produced a response, but its form could not be determined. As a result of their
experiments, Winer et al. (1974) concluded that, "the NOx mode of commercial
chemiluminescent analyzers must be viewed to a good approximation as measuring total
gas phase 'oxides of nitrogen,' not simply the sum of NO and NO2." Numerous later
studies, as noted in the ISA for Oxides of Nitrogen (U.S. EPA. 2016b). have confirmed
this conclusion.
NO2 is not currently monitored in the Clean Air Status and Trends Network (CASTNET)
network, and estimates of its concentration for use in calculations of dry deposition in the
U.S. are currently derived mainly by the Community Multiscale for Air Quality (CMAQ)
model. However, NO2 is sampled at sites of the European Measurement and Evaluation
Program (EMEP) on glass fiber filters impregnated with sodium iodide and sodium
hydroxide. In this method, NO2 is reduced to nitrite and is determined photometrically by
the Griess method (Sutton et al.. 2011). Twenty-four-hour samples are collected for NO2
in the range from -0.2 ppb to 20 ppb, with a sampling volume of 0.7 m3 and an extraction
volume of 4 mL. The collection efficiency of PAN (peroxyacetyl nitrate) is -20% and
could cause positive interference in areas where PAN, and perhaps other organic nitrates
are an appreciable fraction of NO2.
2.5.1.1 Remote Sensing of Nitrogen Dioxide
Remote sensing by satellites is an approach that could be especially useful in areas where
surface monitors are sparse. Retrieving NO2 column abundances from satellite data
typically involves three steps: (1) determining the total NO2 integrated line-of-sight
(slant) abundance by spectral fitting of measurements of backscattered solar radiation,
(2) removing the stratospheric contribution by using data from remote regions where the
tropospheric column abundance is small, and (3) applying an air mass factor to convert
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tropospheric slant columns into vertical columns. The retrieval uncertainty is largely
determined by Steps 1 and 2 over remote regions where there is little tropospheric NO2,
and by Step 3, over regions of elevated tropospheric NO2 (Boersma et al. 2004; Martinet
al.. 2002). Satellite retrievals are largely limited to cloud fractions <20%. Some
algorithms for obtaining NO2 columns such as the Berkeley High-Resolution product
(Russell etal.. 2011). which has shown that higher resolution input fields (topography,
albedo, and NO2 vertical profile shape) in the retrievals can reduce the uncertainty in the
measurements.
A hybrid approach using data for NO2 tropospheric column abundances obtained by the
Ozone Monitoring Instrument (OMI) on the Aura satellite coupled with results from the
GEOS-Chem, global-scale, three-dimensional, chemistry-transport model has been
developed by Lamsal et al. (2008) with updates by Lam sal et al. (2010). In this approach,
the surface mixing ratio divided by the column abundances calculated by the
GEOS-Chem model are used as the scaling factors to derive surface mixing ratios from
satellite-measured column abundances. This method provides estimates of surface NO2
concentrations that are especially useful in data-sparse regions. The algorithm used to
derive the tropospheric columns of NO2 is given in Bucsela et al. (2013). Note that this
algorithm was recently shown to produce NO2 column abundances that are too high by
-20% (Marchenko et al.. 2015).
2.5.2 Measurements of Total Oxidized Nitrogen Compounds in the
Atmosphere
Gold-catalyzed CO or H2 reduction, or conversion on heated MoOx, have been used for
many years to reduce total NOy to NO before detection by chemiluminescence [CL;
(Croslev. 1996; Fehsenfeld et al.. 1987)1. Both techniques offer generally reliable
measurements, with linear dynamic range demonstrated in field intercomparisons from
-10 ppt to 10s of ppb. Under some conditions, hydrogen cyanide (HCN), NH3, alkyl
nitrates (RNO2), and acetonitrile (CH3CN) can be converted to NO; but at normal
atmospheric concentrations and relative humidity, and when converter temperature is
closely monitored, these are minor interferents. Thermal decomposition followed by
laser-induced fluorescence (LIF) has also been used for NOy detection. In field
comparisons, instruments based on these two principles generally showed good
agreement (Dav et al.. 2002). with experimental uncertainty estimated to be on the order
of 15 to 30%.
Commercially available NOx monitors have been converted to NOy monitors by moving
the MoOx converter to interface directly with the sample inlet. Because of losses on inlet
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surfaces and differences in the efficiency of reduction of NOz compounds on the heated
MoOX substrate, NOx concentrations cannot be considered as a universal surrogate for
NOy. However, near sources of fresh combustion emissions, such as highways, most of
the NOy is present as NOx. To the extent that all the major oxidized nitrogen species can
be reduced quantitatively to NO, measurements of NOy concentrations should be more
reliable than those for NOx concentrations, particularly at typical ambient levels of NO2.
Exceptions might apply in locations near NOx sources, where NOx measurements are
likely to be less biased and confidence in measurement accuracy increases.
Alternatively, multiple methods for observing components of NOy have been developed
and evaluated in some detail. As a result of these methods, as applied in the field and the
laboratory, knowledge of the chemistry of odd-N species has evolved rapidly. Recent
evaluations of methods can be found in Arnold et al. (2007) for HNO3; Wooldridge etal.
(2010) for speciated PANs; and Pinto et al. (2014) for HONO. However, it is worth
reiterating that the direct measurements of NO are still the most reliable of all. Reliable
measurements of NOy and NO2 concentrations, especially at the low concentrations
observed in many areas remote from sources, are also crucial for evaluating the
performance of three-dimensional, chemical transport models of oxidant and acid
production in the atmosphere. To meet this goal, NOy monitors have been installed at six
sites in CASTNET as part of the NCore program. Note that neither PANs, NO2, nor
HONO are measured in CASTNET.
2.5.3 Nitric Acid and Particulate Nitrate
HNO3 samples are collected on nylon filters in the CASTNET filter pack shown in Figure
2=7.
In principle, particles of all sizes are collected on the open-face Teflon filter with very
high efficiency. Filter extracts are analyzed by ion chromatography (IC) for the species
identified in Figure 2-7. Nitric acid sampling on nylon filters has been used over the past
four decades and there have been a number of studies evaluating this method.
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Figure 1-4 Three-Stage Filter Pack
Cellulose (2)
Nylon
Teflon®
Gaseous
Gaseous
Particulate
•S03
• HNO, • S03
• so* • no3 • nh; • K*
• Ca2* • Mg2* • Na* • CP
Quick Disconnect
Two
Cellulose Nylon Teflon*
Filters Filter Filter
Shipping Cap
(removed during sampling)
Direction of Ar Flow
Teflon* Spacers
Ca2+ = calcium ion; CI" = chloride; HN03 = nitric acid; K+ = potassium ion; Mg2+ = magnesium ion; Na+ = sodium ion:
NH4+ = ammonium; N03" = nitrate; S02 = sulfur dioxide; S042- = sulfate.
Air flows from right to left.
Source: (MACTEC. 2010).
Figure 2-7
Clean Air Status and Trends Network filter pack.
Identified artifacts include:
1. Volatilization of NH4NO3 collected on the Teflon (pre-) filter leading to an
overestimation in the concentration of HNO3 and NH3, if it is also collected
downstream (Hering et al.. 1988).
2. Reactions of O3 with particles (containing organic nitrogen) on the nylon filter
or on the substrate itself forming HNO;; (Talbot et al.. 1990).
3. Scavenging of HNO3 by alkaline particles collected on the Teflon filter
(Laverv et al.. 2009).
4. Adsorption of HNO3 on sampler surfaces (Babich et al.. 2000). Babich et al.
(2000) suggest putting the Teflon and nylon filters in a single filter holder to
minimize contact with sampler surfaces.
The first two are positive artifacts and the third and fourth are negative artifacts in the
measurement of HNO3; the converse is true for measurements of pNO.i
Much of the following discussion focuses on the results of intercomparisons in which
CASTNET measurement techniques are compared to other methods as a means of
providing perspective on relative measurement capabilities of the techniques used in the
network. Three semicontinuous methods for detecting HNO3 were tested against an
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annular denuder system (ADS) consisting of base- and acid-coated annular denuders
followed by a Teflon-nylon filter pack at the Tampa Bay Regional Atmospheric
Chemistry Experiment (BRACE) Sydney research station -20 km downwind of the
Tampa, FL urban core (Arnold et al.. 2007). The semicontinuous instruments included
two slightly differing implementations of the NOy~NOy* (total oxides of nitrogen minus
NOy denuded of HNO3) denuder difference technique: one from the NOAA Air
Resources Lab (ARL), and one from Atmospheric Research and Analysis, Inc. (ARA).
the parallel plate wet diffusion scrubber online IC technique from Texas Tech University
(TTU); and the chemical ionization mass spectrometer (CIMS) from the Georgia Institute
of Technology (GIT) were also included. Integrated 12-hour ADS samples were collected
by the University of South Florida (USF). Results for 10-minute samples computed from
the various higher sampling frequencies of each semicontinuous instrument showed good
agreement (It2 > 0.7) for afternoon periods of the highest production and accumulation of
HNO3. Further, agreement was within ±30% for these instruments even at HNO3
concentrations <0.30 ppb. However, the USF ADS results were biased low by 44%, on
average, compared to the aggregated 12-hour means from the semicontinuous methods,
and by >600% for the nighttime samples; ADS results were below the ensemble mean
maximum HNO3 concentration by >30% as well. The four instruments using
semicontinuous methods, by contrast, were all within 10% of each other's 12-hour mean
mixing ratios. While only ARA employed a formal minimum detection limit at
0.050 ppb, error analysis with the other techniques established that, at the same level of
precision, TTU's effective limit was approximately the same as ARA's, and that ARL's
limit was 0.030 ppb. Analysis for GIT showed no apparent effective limit at the levels of
HNO3 encountered in this field study.
Because of artifacts mentioned above in measuring HNO3 and pNCh . the sum of the two
species is reported by CASTNET. Filter Pack Total NO3 (HNO3 + pNO, ) at CASTNET
sites can be compared to collocated NOy measurements. Ratios of NOy to total NO3
varied from 4.1 at the Bonville, IL site (BVL 130) to 9.7 at the Beltsville, MD site (BEL
116). It is clear that other oxidized nitrogen components, such as NOx and organic
nitrates make up the difference. Their relative proportions depend on proximity to their
sources.
2.5.4 Ammonia
The National Atmospheric Deposition Program (NADP) deployed an NH3 monitoring
network (AMoN) using Radiello® passive samplers starting in the fall of 2007 at 16 sites:
currently there are more than sixty active AMoN sites, two-thirds of which are located at
CASTNET sites. The passive sampling method relies on diffusion across a membrane
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onto an absorbing substrate, which for NH3 is H3PO3. The sampling period in AMoN is
2 weeks. Puchalski et al. (2011) compared the results from three passive samplers with
annular denuder systems (taken to be the reference method). The median relative percent
difference between the Radiello passive samplers and the denuder systems was -37% and
the coefficient of variation among triplicate Radiello samplers was 10%. Puchalski et al.
(2015) further compared 2-week samples collected at five sites over the course of a year
by Radiello passive samplers with collocated annular denuder systems (ADS) with
different configurations. The mean relative percent difference between the ADS and
AMoN samplers was -9% to be compared to a precision of 5% for both the ADS and
AMoN samplers.
Ambient instruments with much higher time resolution were compared by Schwab et al.
(2007) and von Bobrutzki et al. (2010). Schwab et al. (2007) conducted a
laboratory-based intercomparison of ambient NH3 instruments with seven instruments
using six methods sampling from a common manifold, including tunable diode laser
(TDLAS) absorption spectrometer, wet scrubbing long-path absorption photometer
(LOPAP), wet effusive diffusion denuder (WEDD), ion mobility spectrometer (IMS),
Nitrolux laser acousto-optical absorption analyzer, and a modified CL analyzer. Schwab
et al. (2007) reported that all instruments agreed to within -25% of the expected
calibration value, with the exception of the CL analyzer which suffered from problems
related to its MoOx conversion of NOz to NO.
von Bobrutzki et al. (2010) conducted a field intercomparison of ambient NH3
measurements with eleven instruments using eight methods including: three wet
techniques (annular rotating batch denuders, one with offline analysis and two with
online analysis [AMANDA, AiRRmonia]), two Quantum Cascade Laser Absorption
Spectrometers (c-QCLAS, DUAL-QCLAS), two photo-acoustic spectrometers, a cavity
ring down spectrometer, a chemical ionization mass spectrometer, an ion mobility
spectrometer, and an open-path Fourier transform infrared spectrometer. This study was
unique in that the surrounding field was fertilized with urea halfway through the
campaign to increase average concentrations of NH3 from 10 to 100 ppb. Overall, If was
>0.84 with respect to the ensemble mean for all instruments over the entire range of
concentrations (<120 ppb), with slopes ranging from 0.67 to 1.13. Higher variability was
found at lower concentrations (<10 ppb) with R2 > 0.52 and slopes ranging from 0.42 to
1.15. Perhaps the most consistent agreement between two instruments was found for the
c-QCLAS and AiRRmonia (R2 = 0.91, slope = 0.86, intercept = 0.84 ppb for NH3
<10 ppb; and R2 = 0.91, slope = 0.83, intercept = 0.34 ppb over the entire range of NH3
concentrations).
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Nitrolux-100 denuders were used both in the intercomparison study of von Bobrutzki et
al. (2010) and in the one by Puchalski et al. (2011). Compared to the ensemble mean, the
slope was 0.97, the intercept was 1.86 ppb, and R2 = 0.98 over the entire concentration
range. As noted by von Bobrutzki etal. (2010). comparisons of this sort only show
relative performance of the instruments and not a functional relationship to a standard.
2.5.4.1 Remote Sensing of Ammonia
In addition to these in situ techniques, remote sensing techniques have also been used to
measure NH3. The Tropospheric Emission Spectrometer (TES) on the Aura satellite
rShephard et al. (2011). and references therein; (Beer et al.. 2008)1 and the Infrared
Atmospheric Sounding Interferometer (IASI) on the MetOp-A satellite (Van Damme et
al.. 2014) measure spectral features in the v2 vibrational band centered at around 950/cm
(the so-called atmospheric window in the infrared). Operating specifications for TES
(spectral resolution, 0.06/cm; footprint 5.3 x 8.3 km2; 0.15-0.20 K noise) are generally
better than for IASI (spectral resolution, 0.50/cm; footprint 12 x 12 km2; 0.15-0.20 K
noise). Although TES has higher spectral resolution, it has less dense spatial coverage.
Unlike satellite detection of atmospheric molecules by backscattered solar radiation
(e.g., NO2 and SO2), NH3 is detected in the thermal infrared spectral range, so data for
both day and night can be obtained (satellite overpasses at the Equator at approximately
1:30 a.m. and 1:30 p.m. for TES and 9:30 a.m. and 9:30 p.m. for IASI). The sensitivity of
the IR sounding technique for NH3 increases with the thermal contrast between the
surface and the temperature of the air in the lower troposphere, and thus the daytime
crossing allows for increased detectability of NH3 (Clarisse et al.. 2010). NH3 is confined
largely to the planetary boundary layer (PBL) with much lower concentrations aloft in the
free troposphere and TES retrievals are most sensitive to NH3 between 700 and 900 hPa.
The TES level of detectability for NH3 is given by a profile with a peak concentration of
1 ppbv, or equivalently a constant mixing ratio of 0.4 ppbv distributed over the pressure
range of maximum sensitivity, provided there is substantial thermal contrast.
Pinder et al. (2011) found that TES retrievals of NH3 in the PBL captured the spatial and
seasonal variability of NH3 over eastern North Carolina measured by surface
observations. Similarly, Sun et al. (2015a) found that column abundances measured by
TES over the San Joaquin Valley agreed with those measured by upward looking
instruments at the surface to within 2% and to within 6% for aircraft measurements. TES
columns were also shown to be reasonably well correlated (R2 = 0.67) with median NH3
measured at the surface by quantum cascade laser, thereby demonstrating the ability of
the satellite-based measurements to capture spatial variability in NH3 between individual
pixels.
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Alvarado et al. (2011) derived emissions factors for NH3 in biomass burning plumes over
Canada using data from TES. Using data from IAS I R'Honi et al. (2013) found total
column abundances for NH3 in the plumes of Russian wildfires during the summer of
2010 that were two orders of magnitude larger than background values.
2.5.5 Sulfur Dioxide
Currently, ambient SO2 is measured using instruments based on pulsed UV fluorescence
in the SLAMS network. This technique is a Federal Equivalence Method (FEM). The UV
fluorescence technique is subject to both positive and negative interference. Luke (1997)
reported the positive artifacts of a modified pulsed fluorescence (PF) detector generated
by the coexistence of NO, CS2, and a number of highly fluorescent aromatic HCs such as
benzene, toluene, o-xylene, m-xylcnc, /^-xy lene, m-cthyltolucnc. ethylbenzene, and
1,2,4-trimethylbenzene. NO at 35 ppb induces an instrumental response equivalent to
1 ppb SO2. Concentrations of hydrocarbons in urban air would have to be much higher
than those of NO to produce noticeable interference in the PF detector. Collisional
quenching of excited SO2 molecules can occur from collisions with common molecules
in air, including N2, O2, and H2O. During collisional quenching, the excited SO2 molecule
transfers energy, kinetically allowing the SO2 molecule to return to the original lower
energy state without emitting a photon. Collisional quenching results in a decrease in the
SO2 fluorescence and results in the underestimation of SO2 concentration in the air
sample. Luke (1997) reported that the response of the PF detector could be reduced by
about 7 and 15% at water vapor mixing ratios of 1 and 1.5 mole percent (RH = 35 to
50%) at 20-25°C and 1 atm for a modified pulsed fluorescence detector.
The nominal LOD for a nontrace level SO2 analyzer is 10 ppb (U.S. EPA. 2006b).
However, most commercial analyzers report operational detection limits of ~3 ppb.
Current requirements are documented in 75 FR 35597-35601 (22 June 2010), "the
ultraviolet fluorescence (UVF)—FRM must meet the following performance
requirements: a detection limit of 1 part per billion by volume (ppbv), maximum
interference less than ±5 ppbv SO2 equivalent, and 12- and 24-hour zero drift less than
±5 ppbv SO2 equivalent." The bottom-line is many SO2 analyzers are not appropriate for
measurement of SO2 in remote areas.
Luke (1997) tested the response of modified pulsed fluorescence detector to measure low
levels of SO2 and found the PF detector could detect SO2 down to 30 ppt, with an
estimated uncertainty of the measurements approaching ±100%. At SO2 levels more
representative of clean rural areas, long (>30-minute) measurement times and frequent
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zeroing intervals were judged to be necessary for maximizing precision and accuracy and
minimizing detection limits.
As can be seen in Figure 2-8. SO2 is measured by the CASTNET filter pack by IC
analysis of extracts from the cellulose filters. Because the nylon filter adsorbs some of the
SO2 (Sickles et al.. 1999; Sickles and Hodson. 1999). SO42 is also measured on nylon
and added to the SO2 (expressed as SO42 ) collected on the backup cellulose-fiber filters.
Results of an intercomparison of weekly average SO2 data (ppbv) collected by the
CASTNET filter pack and trace level SO2 monitors during all of 2014 at Bondville, IL
and Beltsville. MD are shown in Figure 2-8. (AMEC Environment & Infrastructure.
2015V
2.5.5.1 Remote Sensing of Sulfur Dioxide
In addition to the above in situ methods, satellite-based measurements have also been
used to measure tropospheric SO2 and to infer surface SO2 concentrations with the aid of
the GEOS-Chem chemistry-transport model (Nowlan et al.. 2014; Lee et al.. 2011).
Tropospheric column abundances of SO2 are obtained by the Ozone Monitoring
Instrument (OMI) on the Aura satellite or the Scanning Imaging Absorption Spectrometer
for Atmospheric Chartography (SCIAMACHY) on Envisat and are combined with results
from the GEOS-Chem, global-scale, three-dimensional, chemistry-transport model to
derive surface concentrations of SO2 (as they are for NO2). Lee et al. (2011) associated
annual mean surface mixing ratios of SO2 derived from the hybrid satellite/model
technique with ambient measurements of SO2, (R2 = 0.66 and 0.74, slope = 0.70 and 0.93,
n = 121 and 115, for OMI and SCIAMACHY, respectively).
The algorithms used to derive vertically integrated SO2 abundances in the troposphere
undergo continuing refinement. For example, Thevs et al. (2015) applied an algorithm
based on differential optical absorption spectroscopy (Piatt and Stutz. 2008) combined
with a radiative transfer model. Li et al. (2013) developed an algorithm based on
principal components analysis, which has replaced the earlier standard algorithm
developed by Krotkov et al. (2008). The methods applied by Thevs et al. (2015) and Li et
al. (2013) are designed to be operational for retrieving SO2 in the PBL with an estimated
detection limit of ~0.5 Dobson units (1 DU = 2.69 x 1016 molec/cm2 corresponding to a
concentration of ~3 ppb if SO2 is well mixed in a 2-km deep, mixed layer), or about half
that in the older standard method. Table 2-3 summarizes sources of uncertainty for
individual OMI measurements of NO2 and SO2.
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Trace UV Fluorescence S02
0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5
Trace UV Fluorescence SC^
Filter Pack vs Trace U V Fluorescence S02
Beltsville, MD
±0.05
Filter Pack vs Trace UV Fluorescence S02
Bondville, IL
±0.07
S02 = sulfur dioxide; UV = ultraviolet.
Results for Beltsville, MD are shown in the upper panel and results for Bondville, IL are shown in the lower panel.
Figure 2-8 Comparison between weekly average measurements of sulfur
dioxide using the Clean Air Status and Trends Network filter pack
and the trace ultraviolet pulsed fluorescence monitor in 2014.
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Table 2-3 Sources of uncertainty for individual Ozone Monitoring Instrument
measurements in the studv of Nowlan et al. (2014).
Source
NO2
SO2
OMI Fitting Error
~1015 molec/cm2
~1016 molec/cm2
Air Mass Factor
20%
15-45%
Stratospheric Correction
2 x 1014 molec/cm2
N/A
SO2 Offset Correction
N/A
2 x 1014 molec/cm2
Profile Shape
30%
10%
molec = molecules; N/A = not applicable; N02 = nitrogen dioxide; OMI = Ozone Monitoring Instrument; S02 = sulfur dioxide.
Source:Nowlan et al. (2014).
The errors in the column measurements result mainly from uncertainties in the vertical
profiles of NO2 and SO2, cloud fraction, cloud pressure, surface reflectivity, and particles
used in the calculation of air mass factor. A correction is required to account for NO2 in
the stratosphere (produced from N2O oxidation and cosmic ray interactions dissociating
with N2). The SO2 offset correction refers to a global background correction arising from
issues in spectral fitting, such as spectral correlations with O3 and stray light within the
instrument.
2.5.6 Methods for Measuring Nitrate and Sulfate in Other Networks
In addition to CASTNET, pSCU2 and pNO, are monitored in the Chemical Speciation
Network (CSN), and the Interagency Monitoring of Protected Visual Environments
(IMPROVE) network. pNH4 measurements are reported for the CSN but not for the
IMPROVE network. Estimates of pNH4+ for the IMPROVE network are reported based
on the assumption of complete neutralization of measured sulfate and nitrate (Solomon et
al.. 2014). In both the latter networks, particulate matter is collected by filtration in
parallel sampling channels with several different filter media suited to the various groups
of species analyzed. Samples are collected once every 3 or 6 days for the CSN and once
every 3 days for IMPROVE (Solomon et al.. 2014). Analysis is by either energy
dispersive x-ray fluorescence (XRF) or ion chromatography. There are some important
differences in sampling and analytical procedures between the two networks, and these
have been recently described in detail (Solomon et al.. 2014).
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In energy dispersive x-ray fluorescence spectrometry, a beam of x-ray photons from an
external excitation source is applied to a filter sample of particulate matter, causing
ejection of inner shell electrons from elements in the sample. Because inner shell
electrons have higher electron binding energies than outer shell electrons, the ejection of
the inner shell electron induces an energetically favorable electronic transition of an outer
shell electron to replace the ejected electron. The release of electromagnetic radiation as a
result of an electronic transition is defined as fluorescence. Fluorescence energies
associated with electronic transitions depend on atomic structure and vary among
elements. As a result, XRF energy is uniquely characteristic of an element, and x-ray
intensity at a given energy provides a quantitative measurement of elemental
concentration in the sample. The x-rays are detected by passing them through a
semiconductor material, resulting in an electrical current that depends on the energy of
the x-ray.
In ion chromatography, filter extracts are injected into a liquid eluent, which flows
through a chromatographic column. Analytes are retained in the stationary phase ionic
functional groups at the surface of a column by ionic interactions. The strength of the
ionic interactions with the stationary phase determines the mobility and retention time of
the analytes as they elute through the column, resulting in a clean separation of analytes
for quantitative analysis with a conductivity detector.
In the IMPROVE network, pSCU2 is measured by collecting particulate matter on Teflon
filters, and analyzing the filter by XRF for elemental S. pSOr concentrations are
estimated from elemental S loadings by assuming all elemental S is present in the form of
pSOr . In the IMPROVE network pNOs is collected on a nylon filter in a separate
channel, extracted in deionized water at room temperature, and analyzed by ion
chromatography; pNH4+ is not analyzed in the IMPROVE network.
In the CSN, pS042~, pNOs . and pNH/ are all analyzed from samples collected on nylon
filters and extracted in deionized water at a temperature lower than used in IMPROVE.
This is done to limit volatilization of species like NH4NO3. However, high extraction
efficiencies for NH4+ and NO3 have been reported for both networks (Solomon et al..
2014). Extracts are analyzed separately for anions (including SO42 and NO3 ) and cations
(including NH44") by ion chromatography. In both networks, nylon filters are used to
avoid loss of pNOs, during sampling that can occur with Teflon and other filter media
(Hering and Cass. 1999).
Because nylon filters are efficient sampling media for collection of gas phase HNO3
(Appel et al.. 1980). they were first used as after-filters for collection of HNO3 volatilized
from particulate matter collected on upstream Teflon filters (Appel et al.. 1981). When
the IMPROVE network was established, nylon filters were used directly for collection of
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PM rather than as an after-filter for correction. Any HNO3 formed during sampling is still
retained on the filter, and loss of gas-phase HNO3 produced by reactions or changes in
equilibrium is avoided. However, there is potential for greater loss of NH3 from nylon
filters than other filters, leading to possible negative artifacts for pNH/ (Yu et al.. 2006).
Consequently, use of pNH/ in IMPROVE samples has been discouraged and is no
longer reported.
While nylon filters effectively eliminate loss of pNCh during sampling, their use can
also lead to positive bias in pNOs measurement due to efficient collection of
atmospheric gas-phase HNO3 (Appel et al.. 1981; Appel et al.. 1980V To a lesser extent,
gas-phase SO2 can also be collected on nylon filters and converted to pSCU2 during
sampling (Japar and Brachaczek. 1984). Collection of these acidic gases is avoided by
placing a diffusion denuder upstream of the filter. A diffusion denuder is a coated tube,
network of concentric tubes, or an arrangement of parallel channels upstream of the filter
that makes use of the large difference in diffusion rates between more rapidly diffusing
gases and more slowly diffusing particles. The tube diameter or channel width and the
sampling flow rate are optimized to efficiently remove the rapidly diffusing gases while
promoting efficient penetration of the more slowly diffusing particles. Denuder walls are
coated with a material that causes the gas to stick. Na2CC>3 (IMPROVE) or MgO (CSN)
are used as denuder coatings to remove gas-phase HNO3 upstream of the nylon filter.
In the CSN, two Teflon filter channels are used, one for XRF and another for ion
chromatography analysis. pSO/~, pNO? . and pNH4 are all analyzed by ion
chromatography. In the IMPROVE network, there is only one Teflon filter channel,
which is used for XRF analysis. Only PM from nylon filters in the IMPROVE network is
analyzed by ion chromatography and only pNO;, concentrations are based on ion
chromatography analysis. pS042 is also analyzed on nylon filters in the IMPROVE
network as a quality assurance check for elemental S analysis, and good agreement has
been reported (Yu et al.. 2005). However, reported concentrations are based on elemental
S analysis because of concerns of gas phase SO2 adsorption on nylon filters.
In both networks, samples for ion chromatography analysis are allowed to equilibrate to
room temperature, and extracted with deionized water after collection. An alternative
approach using a NaHC03/Na2C03 mixture has been explored because HNO3 is
potentially more easily removed in basic solution, but this approach prevents analysis of
Na in the extract. Yu et al. (2005) demonstrated that extraction efficiencies between
deionized water extraction and the NaHC03/Na2C03 mixture are equivalent.
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2.6
Geographic Distributions of Species Relevant for Deposition
Maps of the average distribution of atmospheric species are presented in this section.
Different sources are used depending on the availability of data. For example, the
distribution of NOy is shown in Figure 2-9. However, because NQy is only measured at a
small number of sites, this figure is based solely on CMAQ model output. The
distribution of NO2 (shown in Figure 2-10) is derived from satellite data (OMI) and
output from the GEOS-Chem model using the method outlined in Section 2.5.1. The
distribution of NFb was obtained from the Ammonia Monitoring Network (AMoN).
Distributions of HNO3, pNCh , pNFU+, SO2, and pSO r are based on data from the
CASTNET. Note, however, that because of artifacts relating to measurement of HNO3
and pNO ; described in the preceding section, the measurement of total nitrate
(TN = HNO3 + pNO, ) is judged to be more reliable than measurements of its
components.
NOY
• 33-86
NOy = oxidized nitrogen species.
Source: U.S. EPA/OAQPS.
Figure 2-9 Distribution of annual average total oxidized nitrogen species for
2011 simulated by Community Multiscale for Air Quality modeling
system.
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As seen in the figure, highest values are found in and around urban areas. In general,
much broader areas of high concentrations (>~5 ppb) are found in the eastern U.S., with
many areas in the western U.S. subjected to concentrations <1 ppb. Note that because
NOy refers to the sum of oxidized N species, this implies that concentrations of
components that might pose a hazard are also lower than 1 ppb.
2.6.1 Nitrogen Dioxide
Figure 2-10 shows seasonal average NO2 concentrations derived using the hybrid
(OMI-satellite/GEOS-Chem- model) approach described in Section 2.5.1.
Large variability in NO2 concentrations is apparent in Figure 2-10. As expected, the
highest NO2 concentrations are seen in large urban regions, such as in the Northeast
Corridor, and lowest values are found in sparsely populated regions located mainly in the
West. Minimum hourly values can be less than -10 ppt, leading to a large range between
maximum and minimum concentrations. Although overall patterns of spatial variability
are consistent with the current understanding of the behavior of NO2, not much
confidence should be placed on values <~100 ppt due to limitations in the satellite
retrievals. Surface NO2 concentrations tend to be higher in January than in July, largely
reflecting lower planetary boundary layer heights in winter. Such seasonal variability is
also evident on a local scale, as measured by surface monitors. For example, in Atlanta,
GA, NOx measurements also exhibited higher concentrations in winter and lower
concentrations in summer, when NOx is more rapidly removed by photochemical
reactions. For example, see U.S. EPA (2008b).
2.6.2 Nitric Acid
As can be seen from Figure 2-11. elevated concentrations of HNO3 are notable in
southern California, the Midwest, the south-central U.S., and the Mid-Atlantic states.
Conversion of NO2 to HNO3 takes place over a time scale of 1 to several hours, during
which time appreciable transport can occur.
2.6.3 Particulate Nitrate
Figure 2-12 shows 3-year average concentrations of particulate nitrate (pNOs ) across the
CONUS.
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OMI-derived surface N02 (ppb)
I
I
7.00
6.22
5.44
4.67
3.89
3.11
2.34
1.56
0.78
0.01
JJA
DJF = December, January, February; JJA = June, July, August; N02 = nitrogen dioxide; OMI = Ozone Monitoring Instrument.
Note: Images shown were constructed by Dr. Lok Lamsal of Universities Space Research Association from data obtained by the
OMI instrument on the Aura satellite (http://aura.asfc.nasa.qov/scinst/omi.html) using the algorithm described in Bucsela et al.
(2013'. Output from the GEOS-Chem, global-scale, three-dimensional, chemistry-transport model to derive surface concentration
fields from the satellite data as described in Lamsal et al. (2008) and Lamsal et al. (2010).
Top panel (winter; December, January, February). Lower panel (summer; June, July, August).
Figure 2-10 Seasonal average surface nitrogen dioxide mixing ratios in parts
per billion for winter (upper panel) and summer (lower panel)
derived by Ozone Monitoring Instrument/GEOS-Chem for
2009-2011. Ozone Monitoring Instrument has overpass at
approximately 1:30 p.m. local standard time.
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HN03
(ptg/m3)
=-0.0
Source: CASTNET USEPA/CAMD 10/09/14
.'Ha B TT-'.^T tn ^fpn P.1' 111 J/Jmo3_C-i 113
HN03 = nitric acid; Concentrations of nitric acid (|jg/m3) can be converted to mixing ratios (parts per billion) to rough approximation
at normal temperature and pressure by multiplying by 0.38.
Source: CASTNET/U.S. EPA-CAMD 10/09/14.
Figure 2-11 Three-year average (2011-2013) surface concentrations of nitric
acid based on monitoring data obtained at Clear Air Status and
Trends Network sites (black dots).
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N03-
(ftg/m3)
—-0.0
Source: CASTNET USEPA/CAMD 10(09/14
jr/castiietfciig/l 11 113
N03" = nitrate.
Source: CASTNET/U.S. EPA-CAMD 10/09/14.
Figure 2-12 Three-year average (2011-2013) surface concentrations of
particulate nitrate based on monitoring data obtained at Clear Air
Status and Trends Network sites (black dots).
Average pNO < concentrations were highest in the upper Midwest with a notable
maximum at the junction of Iowa, Wisconsin, Missouri, and Illinois. The high values in
the upper Midwest are expected to be found during winter for reasons noted in
Section 2.3. Elevated levels were also observed in central California in the San Joaquin
Valley, central Pennsylvania, central Florida, and through much of the Midwest. Based
on IMPROVE and CSN monitoring network data, ammonium nitrate concentrations are
highest in California and the Midwest (Hand et al.. 2012c). It is worth noting that at
several monitoring sites in the central and northern Great Plains, nitrate and sulfate are
increasing at a rate of over 5% per yr (Hand et al.. 2012a). Hand et al. (2012a) suggested
that this increase might be related to oil and gas exploration and production in the region,
transport from oil and gas fields in Alberta, and also to expansion of EGUs to meet the
demands of population growth.
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Figure 2-13 and Figure 2-14 show maps for the reduced inorganic nitrogen species, NH3
and pNFU4
Ambient Ammonia Monitoring Network (AMoN)
0.68; >
2012
Average Ambient
Ammonia Concentration
nh3
Concentration
(MSJ/m3)
O * 0.40
O 0.40 - 0.80
O 0.80-1,20
O 1.20-1.60
O 1.60-2.00
O 2.00-2.40
O > 2.40
AMoN = Ambient Ammonia Monitoring Network; NH3 = ammonia.
Source: CASTNET/U.S. EPA-CAMD 10/09/14.
Figure 2-13 Average (2012) surface concentration of ammonia obtained by the
Ambient Ammonia Monitoring Network at select Clear Air Status
and Trends Network sites. Concentrations of ammonia (pg/m3)
can be can be converted to mixing ratios (parts per billion) to
rough approximation at normal temperature and pressure by
multiplying by 1.4.
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Souice: CASTNET
USEPA/CAMD 10/09/14
B a csstrvWpTlg/ 1113/nh4_c-1113
NH/ = ammonium.
Source: CASTNET/U.S. EPA-CAMD 10/09/14.
Figure 2-14 Three-year average (2011-2013) surface concentrations of
particulate ammonium (pg/m3) based on monitoring data obtained
at Clear Air Status and Trends Network sites (black dots).
2.6.4 Ammonia
Highest concentrations of NH? were measured in Salt Lake City, UT at 15.07 (.ig/m3. All
other annual average concentrations for 2012 were lower than 5 |.ig/m3. The Salt Lake
City site is located near feed lots, perhaps explaining in large part why levels were much
higher there than at other sites. In general, areas of highest NH3 concentration correspond
well with areas of highest ML emissions, as shown in the 2008 ISA for Oxides of
Nitrogen (U.S. EPA. 2008b). Note that confidence in the magnitude and inter-monitor
precision of NFL measurements has increased since the 2008 ISA for Oxides of Nitrogen
and Sulfur-Ecological Criteria (U.S. EPA. 2008a) also see Section 2.5.4. However,
sparseness of the monitoring network still presents uncertainty in describing the
nationwide distribution of NH3 concentrations.
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2.6.5
Particulate Ammonium
Particulate NH4+ concentrations were highest in Illinois-Indiana-western Ohio, along with
high values in central Pennsylvania and central California. These locations correspond
generally to highest concentrations of pNOs and moderate-to-high concentration
locations for NH3. In addition, some of the areas with high NH3 concentrations, such as
southern Wisconsin or Salt Lake City, do not appear to have elevated pNH4+.
2.6.6 Sulfur Dioxide
Figure 2-15 and Figure 2-16 show the distribution of atmospheric concentrations of gas
phase SO2 and particulate phase SO42 .
Elevated SO2 concentrations persist along the Ohio River Valley and western Virginia,
but concentrations have decreased substantially over the last decade throughout the
eastern U.S. Comparison between the national SO2 distributions (Figure 2-15) for
2011-2013 and the ones for 1989-1991 and 2003-2005 presented in the 2008 ISA for
Oxides of Nitrogen and Sulfur (U.S. EPA. 2008a') demonstrated continual decreases in
SO2 concentrations across the nation.
2.6.7 Particulate Sulfate
Both concentrations and seasonal variability of sulfate are substantially higher in the
eastern U.S. than in the West (Hand et al.. 2012c). Based on air pollution monitoring
network data (IMPROVE and CSN), sulfate concentrations on a national scale are
steadily decreasing across the U.S. Between 1992 and 2010, annual mean sulfate
concentrations at rural sites decreased fairly consistently at a rate of-2.7% per year. This
decline has become even steeper more recently, with annual mean concentrations
decreasing by an average of-4.6% per year from 2002 to 2010. The decrease appears to
be due to decreasing SO2 emissions from power plants (Hand et al.. 2012b). While the
nationwide trend is for a reduction in sulfate concentrations, there are seasonal and
regional increasing trends, specifically in the central and northern Great Plains in winter,
and in the western U.S. in spring (Hand et al.. 2012a). Both sulfate and nitrate are
increasing at a rate of over 5% per year at several monitoring sites in the central and
northern Great Plains (Hand et al.. 2012c).
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Source: CASTNET
USEPA/CAMD 10/09/14
fditta/mdaasaiet/jmgfl 113,'io2_c-l 113
S02 =sulfur dioxide.
Source: CASTNET/U.S. EPA-CAMD 10/09/14.
Figure 2-15 Three-year average (2011-2013) surface concentrations of sulfur
dioxide obtained by fusion of monitoring data obtained at Clear
Air Status and Trends Network sites (black dots) and Community
Multiscale for Air Quality model system results. Concentrations
(pg/m3) can be can be converted to mixing ratios (parts per
billion) at normal temperature and pressure) to rough
approximation by multiplying by 0.37.
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S042 = sulfate.
Source: CASTNET/U.S. EPA-CAMD 10/09/14.
Figure 2-16 Three-year average (2011-2013) surface concentrations of
particulate sulfate based on monitoring data obtained at Clear Air
Status and Trends Network sites (black dots).
Source: CASTNET
USEPA/CAMD 10/09/14
/datafarc/ai stnet/jaigfl. 113/io4_c-l 113
2.7 Deposition
1 Detailed mechanisms by which pollutants are transferred from the atmosphere to the
2 earth's surface have been treated in a number of texts, for example Moller (2014) and
3 Seinfeld and Pandis (1998). Only brief background will be presented here. Figure 2-17
4 (Moller. 2014) illustrates the pathways that transfer gaseous and particulate pollutants
5 from the atmosphere to the surface by deposition. As can be seen from Figure 2-17. wet
6 deposition occurs when particulate and gaseous species are removed via uptake by cloud
7 drops (rainout) and also via impaction by falling precipitation (washout). Occult
8 deposition (Pollard et al.. 1983). which results from the impaction of droplets in fogs or
9 clouds with vegetation is not shown in the figure. Occult deposition is especially
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important in coastal and inland areas where there are mountain ranges. Note also that
cloud drops evaporate, leaving behind aerosol components which can then be involved in
repeated cycles of condensation and evaporation. Dry deposition refers to the transfer of
gaseous and particulate pollutants from the atmosphere to the surface by turbulent
motions and gravitational settling of large particles.
Source: Moller (2014).
Figure 2-17 Schematic diagram showing mechanisms for transferring
pollutants from the atmosphere to the surface.
Wet deposition results from the incorporation of atmospheric particles and gases into
cloud droplets and their subsequent precipitation as rain or snow, or from the scavenging
of particles and gases by raindrops or snowflakes as they fall (Lovctt. 1994). Wet
deposition of a pollutant is estimated as the product of pollutant concentration in
precipitation and precipitation depth (e.g., in rain or snow). Wet deposition is currently
measured by the National Atmospheric Deposition Program/National Trends Network
(NADP/NTN) across a national network of sites using a standard precipitation collector.
The sample is collected in a bucket with a lid that includes an electronic moisture sensor
to retract the lid from the sample bucket during a rain event. Each site is equipped with a
scavenging
particles
heterogeneous
scavenging
cloud \
(in-cloud
scavenging)
homogeneous
nucleation
scavenging
^precipitation
¦w (sub-cloud
\ scavenging)
scavenging
sedimentation dry deposition
wet deposition
2.7.1 Wet Deposition
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rain gage to record precipitation amounts. Week-long samples are collected, weighed,
and sent to the NADP Central Analytical Laboratory in Champaign, IL, where H+, SO42 .
NO3 , NH4+, Ca2+, Mg2+, K+, Na+, CI", and Br" are analyzed by ion chromatography.
As noted by Moller (2014). the measurement of wet deposition is relatively
straightforward, but the interpretation of measurements is not, due to the complex
processes occurring in going from emission to deposition. In other words, at the point of
precipitation and its sampling, long-range transport of precursors in air, atmospheric
aerosol, and clouds with a complex physical-chemical history determines the composition
in the precipitating clouds (in-cloud scavenging) and local processes determines the
below-cloud scavenging. These processes can lead to very substantial variations between
precipitation events, causing large uncertainties in terms of both spatial and temporal
interpolation and extrapolation. Uncertainties exist regarding sampling artifacts and the
effects of taking week-long average samples. Individual rainfall samples collected in the
field will mix because of the once-per-week sample collection schedule in NADP. As a
result individual rain drops or samples with different acidity/alkalinity will have been
mixed with those from other rainfall events, resulting in acid-base reactions and a shifting
liquid-gas equilibrium with a new reference point with an averaged "final" acidity.
Receptor (i.e., vegetation) surface properties have little effect on wet deposition, although
leaves can retain liquid and solubilized PM. In terrain containing extensive vegetative
canopies, any material deposited via precipitation to the upper stratum of foliage is likely
to be intercepted by several foliar surfaces before reaching the soil. This allows such
processes as foliar uptake, chemical transformation, and resuspension into the atmosphere
to occur.
Landscape characteristics can affect wet deposition via orographic effects and by the
closer aerodynamic coupling to the atmosphere of tall forest canopies as compared to the
shorter shrub and herbaceous canopies. Following wet deposition, humidity and
temperature conditions further affect the extent of drying by concentrating solutions on
foliar surfaces, thereby influencing the rate of metabolic uptake of surface solutes
(Swietlik and Faust. 1984). van Hove et al. (1989) found that leaf surfaces might work
like capacitors for NH3 and SO2 uptake. This capacitance increases with humidity
(i.e., higher humidity leads to greater storage on leaf surfaces). This transport to leaf
surfaces is independent of solar radiation, and in contrast to the uptake through stomata,
also takes place at night. The interaction, or codeposition between NH3 and SO2 in which
deposition of one enhances the other is explicitly accounted for in the EMEP MSC-W
chemistry-transport model (Simpson et al.. 2012).
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2.7.2
Dry Deposition
Methods for estimating dry deposition fall into two major categories: surface analysis
methods, which include all types of estimates of contaminant accumulation on surfaces of
interest, and atmospheric deposition rate methods, which use measurements of
contaminant concentrations in the atmosphere and micrometeorological measurements of
atmospheric turbulence. Emphasis here is placed on the latter class of methods as the
accumulation methods are subject to limitations such as the site specificity of the
measurements and the restriction to elements that are largely conserved within the
vegetative system. Surrogate surfaces used for collection have not been found that can
adequately replicate essential features of natural surfaces and therefore do not produce
reliable estimates of particle deposition to the landscape. These methods have been
described in the previous ISA for Oxides of Nitrogen and Sulfur (U.S. EPA. 2008a').
Measurements of dry deposition fluxes of gaseous compounds and particulate species
have been made using the eddy covariance technique from towers or aircraft (Weselv and
Hicks. 2000). In this technique, the high frequency deviations in vertical wind and
species concentrations from mean conditions are measured; this technique measures
vertical fluxes due to turbulence in the atmospheric surface layer directly. In the
aerodynamic gradient method, measurements of concentration gradients along with
vertical eddy transfer coefficients are used (Mvles et al.. 2012). Dynamic chambers
(Breuninger et al.. 2012) are also used. Dynamic chamber methods are useful in
determining process-level fluxes, but often shelter the surrounding environment, making
it difficult to extrapolate fluxes to an ecosystem level (Almand-Hunter et al.. 2015).
The net, vertical flux of a species is given by the covariance of fluctuations of vertical
wind speed and species concentrations, averaged over some time interval (Garratt. 1994)
given by
Fluxq =(pw)'q' ~pw'q' ~ w'c'
Equation 2-12
where Fluxq refers to the vertical flux of q, and primes (') refer to instantaneous
deviations from the mean (denoted by the overbar, typically -30 minutes) of the vertical
velocity (w), the species mass mixing ratio (q) and to the species concentration (c).
Measurements of the above quantities are made in the eddy covariance technique. The
eddy covariance technique requires fast response measurements typically made at >1 Hz.
Instrumentation required for measuring surface layer fluxes of heat and momentum by
eddy covariance has been available for the past several decades. The eddy covariance
technique has been applied to a wide variety of species such as CH4, CO2, O3, particles,
and various N and S species. However, molecules such as HNO3 and NH3 are "sticky"
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and subject to interactions with inlet surfaces. Their stickiness has limited the potential
for flux determinations to be made by eddy covariance. Roscioli et al. (2016) developed a
method to passivate inlet surfaces thereby overcoming this difficulty and thus allowing
for more rapid response measurements to be made. Min et al. (2014) determined the net
flux of NO and NO2 (at a frequency of 5 Hz) over a forest with estimated total systematic
uncertainties of <8 and <6%, and random errors of <25 and <21%, respectively.
Measurements of the vertical gradient of the species of interest are also used in field
studies to measure net fluxes. In this approach, the depositional flux is given by Equation
2-13.
Flu x=-pA^
Equation 2-13
where ~p is the mean density of moist air, Kq the turbulent diffusivity for the substance
(typically set equal to that for heat or for water vapor) and q the mean (mass) mixing
ratio at heights of the sensors, typically a few meters apart in the surface layer. By
measuring the vertical heat flux using eddy covariance and then making use of the
principle that eddy transfer coefficients for scalar quantities are equal, Kq in Equation
2-13 is obtained. This approach is often used in field studies using the gradient method
[e.g., Mvles et al. (2012)1 to measure the deposition of species for which measurements
by eddy correlation are not feasible.
As part of a series of measurements to be tested at several CASTNET sites, Rumsev and
Walker (2016) evaluated the ability of the MARGA 2S (Monitoring for AeRosols and
GAses) system to measure fluxes using the aerodynamic gradient method. Measurements
were made during a 3-week period in fall of 2012 over an unfertilized grass field in Duke
Forest, in central North Carolina. In this technique, two different sampling systems
operating simultaneously collect gas (wet-rotating denuder) and aerosol components
(steam jet aerosol collector) at 1-h temporal resolution with analysis by a single ion
chromatography system to eliminate inter-instrument bias. Simultaneous measurements
of the NH3 HNO3 NH4NO3 triad allow for an assessment of the errors due to instability
of the particle phase. Simultaneous measurements of SO2 and SO42 allow for
investigation of ammonium sulfate neutralization and codeposition between SO2 and
NH3. Over the range of meteorological conditions observed during a 3-week sampling
period in fall of 2012, median flux uncertainty was found to range from ~3 1 % for NH3 to
~ 121% for NH4+. Further evaluation and field studies are underway and/or planned at
several CASTNET sites.
Note that either the gradient or eddy covariance methods implicitly take into account the
bidirectionality of exchange as the flux can be either positive (upward) or negative
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(downward). In principal, the eddy covariance method can provide a spatially
representative sample of an ecosystem by measuring exchange across an extended
footprint, depending on the horizontal length scale of the eddies being sampled [which
could be hundreds of meters; (Schmid. 1994)1. Note, however, that changes in surface
roughness cause large changes in boundary layer flows that could seriously compromise
flux estimates by either technique. The eddy covariance technique measures the flux up
to measurement height and the gradient technique up to the height of the lowest sensor.
The interpretation of results becomes difficult if there are sources and sinks operating in
the air space between the surface and height of the sensors.
In practice, measurements using the eddy covariance and aerodynamic gradient
techniques are not used in monitoring networks because of cost and logistics. Instead, dry
deposition fluxes of gases and particles are estimated in CASTNET and by
chemistry-transport models, such as CMAQ, by an inferential technique. In the inferential
model approach, the deposition of a pollutant is accomplished by introducing a resistance
component to account for the individual chemical and biological processes that control
pollutant adsorption and capture at natural surfaces (Hicks et al.. 1987). Ambient
pollutant concentrations of O3, SO42 , NO3 , NH4 , SO2, and HNO3 are routinely collected
at CASTNET dry deposition sites. The temporal resolution for the ambient concentration
measurements is hourly for O3 and weekly for the other species (Clarke et al.. 1997).
Deposition velocities based on local meteorological measurements were calculated using
the Multi-Layer Model (MLM) at U.S. EPA-sponsored CASTNET sites until 2010, when
meteorological measurements were discontinued at all but five U.S. EPA CASTNET
sites. Dry deposition fluxes are still reported at sites with discontinued meteorological
measurements using historical average values for deposition velocities (Vd).
Measurements of meteorological parameters are still made at National Park
Service-sponsored CASTNET sites.
In the application of the inferential technique, the dry deposition process is thought of
consisting of three consecutive steps: turbulent transport through the atmospheric surface
layer; molecular diffusion through the quasi-laminar-sublayer immediately adjacent to
the surface; and uptake by the surface. The general approach used to estimate Ki is the
resistance-in-series method in which each step is parameterized by a resistance that is
based on analogy with electrical circuits as shown in Equation 2-14.
Vd = l/(Ra + Rb+Rc)
Equation 2-14
where Ra represents the resistance due to atmospheric turbulence, Rb represents the
resistance due to molecular diffusion in the quasi-laminar sublayer adjacent to the
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elements of surface, and Rc represents the resistance to uptake by the surface itself. The
flux to the surface is then given by
Flux = —C(Zrd) X Vd
Equation 2-15
where C(zief) is the concentration measured or determined at some reference height,
usually a few meters above the surface (fluxes are defined as positive upward). In the
derivation of the resistance model, the flux is expressed in terms of its gradient using
parameters from Monin-Obukhov similarity theory (Hicks et al.. 1987).
This approach might be appropriate for substances (e.g., O3 and HNO3) whose surface
concentrations are equal to zero (i.e., Rc = 0) and for meteorological conditions for which
similarity theory (relating fluxes to gradients through a mixing length) is applicable.
However, it is inappropriate for species with substantial re-emission from the surface or
for species whose surface concentrations are not equal to zero (i.e., Rc 4- 0), or for
strongly stable or unstable meteorological conditions. Until recently, CASTNET inferred
dry deposition using the Multi-Layer Model (MLM) for calculating Vd (Meyers et al..
1998). The model separates the vegetative canopy into 20 layers with resistances
calculated for each layer. The MLM uses locally determined meteorological data
(temperature, wind speed, relative humidity) and surface data including type and quantity
of vegetation and leaf area index [LAI; (Clarke etal.. 1997)1 to calculate deposition
velocities at hourly resolution. Currently semiempirical deposition velocities for a wide
range of species are calculated by three-dimensional chemistry-transport models (CTMs)
such as CMAQ and CAMx. However, CTM calculations use fields that are averaged over
a grid cell that could contain a mixture of land use types and topography.
A major shortcoming of using Equation 2-15 based on the MLM is that this and similar
models do not consider the bidirectional exchange of gases, which has been shown to be
important for NH3 and NO2; it is the net flux that is of interest for determining the overall
budget of a pollutant to an ecosystem. Note, however, that this shortcoming is shared by a
number of CTMs. A compensation point can be defined when the downward and upward
fluxes are equal and the net flux is zero. For ambient concentrations larger than the
compensation point, the flux is into the receptor; however, at lower ambient
concentrations, the flux is into the atmosphere. Serious errors can result if the
bidirectional exchange of gases is not considered. In its simplest form, the net
bidirectional exchange of a gas can be expressed as
Flux = ~(C[Zref] - C[cp\)/(Ra + fib)
Equation 2-16
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where C(zref) is the concentration at some reference height and C(a>) is the
compensation-point concentration Farquhar et al. (1980). As seen in Equation 2-14
above, for VL\, the term (It, + Rb) in the denominator corresponds to Ki when Rc (the
surface resistance) equals zero and the flux reduces to that given in Equation 2-15.
Note that deposition velocities can be derived from fluxes determined by either the flux
gradient or the eddy covariance method as shown in Equation 2-17.
Vd = -F\uxq/p q
Equation 2-17
The calculation of fluxes by either the (aerodynamic) resistance model (It,) or the
aerodynamic gradient method requires an expression relating fluxes to gradients. For
slightly and moderately stable and unstable conditions, this linkage is provided by
Monin-Obukhov similarity theory, which relies on an empirically determined stability
function,
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Deposition velocities of other species are also expected to be spatially and temporally
variable.
Table 2-4
Average dry deposition velocities (cm/s) for a number of gases over
land surfaces.
Substance
so2
NO
NO2
HNOs
Os
H2O2
CO
NHs
Vd
0.8
<0.02
0.02
3
0.6
2
<0.02
1
CO = carbon monoxide; H202 = hydrogen peroxide; HN03 = nitric acid; NH3 = ammonia; NO = nitric oxide; N02 = nitrogen dioxide;
03 = ozone; s = second; S02 = sulfur dioxide; Vd = deposition velocities.
Source: Moller (2014).
Table 2-5 Deposition velocity (cm/s) for sulfur dioxide averaged over different
land use types for summer and winter.
Farmland
Grassland
Dec. Forest
Con.
Forest
Urban
Water
Su
Wi
Su
Wi
Su
Wi
Su
Wi
Su
Wi
Su
Wi
Wet
1.0
1.0
1.0
1.0
3.0
1.5
2.0
2.0
1.0
1.0
0.5
0.5
Dry
0.7
0.5
0.6
0.4
1.5
0.5
0.7
0.5
0.1
0.1
0.5
0.5
Snow
-
0.
-
0.1
-
0.2
-
0.2
-
0.1
-
0.1
Con = coniferous; Dec = deciduous; Su = summer; Wi = winter.
Source: Moller (2014).
The strong dependence of dry deposition on surface characteristics, which are highly
spatially variable, causes in situ measurements to be limited in applicability, especially in
areas of high topographic relief [e.g., Weathers et al. (2006)1. The lifetime in the
boundary layer (~1 km depth) for rapidly depositing species (i.e., those with Fj ~ 1 cm/s)
is ~1 day, implying that distances from source to deposition are relatively short and that
the deposition flux depends strongly on the nature and strength of nearby sources. In
addition, Vj also shows strong temporal variability on time scales ranging from diurnal to
seasonal, as do wind regimes affecting a particular site. Day-night variability in V\\ is
especially pronounced as it is due to the variability of turbulent transport in the surface
layer (e.g., ranging from strong vertical mixing during the afternoon to strongly stable
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conditions before dawn). Because the depositing species may be positively or negatively
correlated with Ki during the diel (24-h) cycle, errors can result when averages are taken
over time scales longer than those for variability in Vd.
Nowlan et al. (2014) used satellite-based measurements to infer global-scale dry
deposition of NO2 and SO2 (see Section 2.8.4 for values). Data obtained at spatial
resolution of 0.1 x 0.1° by the Ozone Monitoring Instrument (OMI) on the Aura satellite
was combined with modeled NO2 and SO2 surfaces and vertically integrated
concentrations and deposition velocities to estimate deposition fluxes. Nowlan etal.
(2014) relied on the GEOS-Chem three-dimensional, global-scale, chemistry-transport
model to provide Ki and surface layer concentrations. Uncertainties in depositional flux
estimates in this approach result from the combined uncertainties in the satellite-derived
surface concentrations and model-derived deposition velocities used in the flux
calculations; average relative uncertainties are estimated to be -30 % for both NO2 and
SO2 over land.
2.7.2.1 Dry Deposition of Particulate Matter
In the size range of -0.1 to 1.0 ^m (aerodynamic diameter) for atmospheric particles, Ki
is controlled by roughness of the surface and by the stability and turbulence of the
atmospheric surface layer. Impaction and interception dominate over diffusion as dry
deposition processes, and Ki is considerably lower than for particles that are either
smaller or larger than this size range [e.g., Seinfeld and Pandis (1998)1. Deposition of
particles between 1 and 10 |im aerodynamic diameter is strongly dependent on particle
size due to gravitational settling [e.g., Seinfeld and Pandis (1998)1. Figure 2-18 shows an
example of the experimentally determined mass-size distribution of ambient and
deposited particles and their dry deposition velocities as a function of particle size on the
roof of a building in Chicago (Lin et al.. 1994). Deposition velocities for each of 15 size
bins were calculated using the relation Vd = Flux/concentration for each size bin. As can
be seen from the figure, deposition velocities increase rapidly with particle size. This
increase is due in large measure to gravitational settling. The distance particles can travel
from their sources depends strongly on their size. For example, assuming a mixing layer
height of 1 km leads to an atmospheric lifetime with respect to settling of -2 hours for
10 (mi particles compared to -4 months for 1 |im particles. This result implies that dry
deposition limits how far coarse-mode particles can be transported and is likely to be the
dominant removal mechanism for coarse particles. Conversely, wet deposition is likely to
be a more important loss mechanism for accumulation-mode particles. This also implies
that fine (accumulation-mode) particles can travel long distances (perhaps 1,000s of km),
especially if they are lofted above cloud tops. Because pNCV, in the eastern U.S. at least,
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is found mainly in the coarse mode, it would likely not travel as far from its source as
would pSO.r~, which occurs mainly in smaller particles.
5 io"
io r
iu
10
-fi—
n - Flu* • : Mass
v ; Calculated deposition
vtlosily - to' S"
\
J ....
o.i
1 10
Portltlf diameter. jmn
100
<0! |
10
l J
I li
-------
A
~
O
o
grass (Chamberlain 67)
grass (WT) "
sticky grass (WT) "
grass (WT) (Clough 75)
moorland (Gallagher 88)
moorland (Nemitz02)
semi arid savannah (Lamaud 94)
Davidson 82 u*=45cm.s~1
Legg 79-Aylor 82 "
Wiman 85 "
Slinn 82 "
Zhang 01 "
• Spruce (Beswick 91)
® Spruce (Bleyl 01)
O Pine (Lorenz 89)
~ Pine (Buzorius 00)
O Pine (Gaman 04)
v Pine (Lamaud 94)
b Pine (Gronholm 07)
A Fir (Gallagher 97)
Forest
dp (n™)
0.001
100
0.001
Grass
Cp{nm)
dp = aerodynamic diameter of particle; Vdc = deposition velocity; Ws = Stokes settling velocity.
Notes: (Gronholm et al.. 2007: Gaman et al.. 2004: Nemitz et al.. 2002: Zhang et al.. 2001: Buzorius et al.. 1998: Gallagher et al..
1997: Lamaud et al.. 1994a: Lamaud et al.. 1994b: Beswick et al.. 1991: Lorenz and Murphy. 1989: Gallagher et al.. 1988: Wiman
and Agren. 1985: Avlor. 1982: Davidson et al.. 1982: Legg and Powell. 1979: Clough. 1975: Chamberlain. 1967).
Closed symbols correspond to wet or sticky surfaces or liquid particles; open symbols to dry surfaces or solid particles.
Source: Petroff et al. (2008).
Figure 2-19 Modeled and measured deposition velocities over grass (left
figure) and coniferous forest canopies (right figure) for particles
of density 1 gm/cm3 depositing under similar friction velocity
(35 < u* < 56 cm/s).
1 Schwede et al. (2011) found (with reference to the Multi-Layer Model and the Routine
2 Deposition Model used in CAPMoN) that "given consistent meteorological inputs and
3 site characterization (e.g., vegetation type, LAI, canopy height, surface roughness), the
4 median hourly Ki and, therefore, the flux can be a factor of 2 to 3 different depending on
5 the choice of deposition velocity model/' In particular, the median increase in Va for SO2
6 in the CAPMoN model was 49.3% over that in the CASTNET model. Flechard et al.
7 (2011) inter-compared results from four dry deposition models across the 55 sites of the
8 NitroEurope network. They found differences of factors of 2 to 3 in Nr dry deposition
9 across the models. They noted that the main differences across the models were in
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parameterizations of stomatal conductance and nonstomatal resistance. Interestingly,
Schwede et al. (2011) also identified nonstomatal resistance as the main source of
differences in the results of their intercomparison. The importance of incorporating
bidirectional exchange should not be underestimated. For example, Li et al. (2016) found
a much larger depositional flux of NH3 (median ratio of 1.9 at 35 sites on an annual basis)
calculated using the MLM than the model including bidirectional exchange. Li et al.
(2016) also considered uncertainties in the models for HNO3 dry deposition and
concluded that the dry component of N deposition is much more uncertain than the wet
component. Finally, as noted by Vet et al. (2014). ".. .the estimation of dry deposition
remains highly uncertain because dry deposition velocities are not validated by direct flux
measurements."
2.7.3 Occult Deposition in Clouds and Fogs
Although most effort has been placed on large scale monitoring networks and models to
extend and interpret the data for wet and dry deposition, these efforts are most suited for
rather flat, homogeneous, open terrain. However, occult deposition can be the dominant
form of delivery of water and chemical species to vegetation in mountainous terrain both
in coastal and inland areas (e.g., Hutchings et al.. 2009; Anderson et al. 2006; Weathers
et al.. 2000). Essentially, occult deposition refers to the impaction of cloud droplets
(whose aerodynamic diameters are on the order of several |im) on vegetation.
Concentrations of dissolved ionic species can be much higher in cloud water than in
precipitation (e.g., Vong et al.. 1991; Weathers et al.. 1988). As a result, mountain
systems like the Adirondacks that are located downwind of major pollution sources are
subject to high levels of acid deposition. The rate of deposition to vegetation in cloud/fog
droplets is a function of wind speed, droplet size, concentration, and number density of
droplets. Because wind speeds can be considerably higher on mountain tops than at lower
elevations, much higher rates of deposition onto vegetated surfaces can result.
Measurements of cloud water chemistry and occult deposition have been made as part of
the Mountain Acid Deposition Program (MADPro). The longest lived (1994-2011)
sampling location was at Clingmans Dome in the Great Smoky Mountains National Park,
although there were several other sites operating earlier in the program. Cloud deposition
at Clingmans Dome was modeled using the approach described in Lovett (1984) and was
estimated to be the largest component of deposition, ranging from 90% of total in 1993 to
70% in 2011. Aleksic et al. (2009) analyzed samples of cloud water and rainwater
collected separately at two sites on Whiteface Mountain from 1994 through 2006 and
found that cloud deposition was between 14 and 28 times greater than wet deposition.
Measurements made on Mount Washington from 1984 to 2011 indicate that cloud
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deposition of acidifying species can be more than twice as high as wet deposition but also
showed a decline in the acidity of cloud water (Murray et al.. 2013). Some distinction
must be made between this measurement programs and those of the other studies, in that
the latter sampled only nonprecipitating clouds. Not all cloud water is strongly acidic; pH
values ranged from 5.12 to 6.66 in nonprecipitating clouds sampled at the summit of Mt.
Elden, near Flagstaff, AZ, during the summers of 2005-2007, showing evidence of acid
neutralization by crustal material. Major cations were NH4+ and Ca2+ and major anions
were NO, and SO42 . There was some evidence of missing anions, such as HCO , .
HCOO , and CH3COO .
2.7.4 Deposition of Nitrogen Species in the Forest Canopy and Throughfall
Wet, dry, and occult deposition all contribute N and S species to the forest canopy in
varying proportions. Deposited species can react on surfaces within the canopy, be taken
up by vegetation through stomata, be resuspended during stormy weather, or simply pass
through the canopy to the forest floor. The rainwater that passes directly through a
canopy or is initially intercepted by above ground vegetative surfaces and subsequently
drips from the canopy is measured as throughfall. The fraction of the precipitation that
drains from outlying leaves and branches and is channeled to the stem of plants is
classified as stemflow. Throughfall and stemflow inputs constitute the majority of
incident precipitation in forests and can account for 70 to 90% of incoming precipitation
in most cases, with the remainder lost to interception within the canopy (Lcvia and Frost.
2003). Compared to wet deposition measurements in the open, the magnitude of
deposition from throughfall and stemflow can either be smaller (e.g., from evaporation
from canopy surfaces) or larger (e.g., from resuspension of previously deposited
material). The type of vegetation is important for characterizing throughfall. For example,
Templer et al. (2015a) found that the cycling of N, particularly the rate of throughfall for
NH4+, is significantly different in conifer compared to deciduous forest sites.
Rainfall introduces new material and also redistributes previously dry-deposited particles
throughout the canopy (Peters and Eiden. 1992). The concentrations of suspended and
dissolved materials are typically highest at the onset of precipitation and decline with
duration of individual precipitation events (Hansen et al.. 1994). Sustained rainfall
removes much of the accumulation of dry-deposited particles from foliar surfaces,
reducing direct foliar effects, and combining the associated chemical burden with the
wet-deposited material (Lovett. 1994) for transfer to the soil. Intense rainfall may
contribute substantial total particulate inputs to the soil, but it also removes bioavailable
or injurious pollutants from foliar surfaces. This washing effect, combined with
differential foliar uptake and foliar leaching of different chemical constituents from
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particles, alters the composition of the rainwater that reaches the soil and the pollutant
burden that is taken-up by plants. Low intensity precipitation events, in contrast, may
deposit substantially more particulate pollutants to foliar-surfaces than high intensity
precipitation events. Additionally, low-intensity events could enhance foliar uptake
through the hydration of previously dry-deposited particles (U.S. EPA. 2004).
Several Nr species are deposited to vegetation, among them HNO3, NO2, PAN (and other
RONO2), and NH3. Some species, most prominently HNO3, can be characterized by
uni-directional exchange, whereas bidirectional exchange is more appropriate for most
other species. A two-pathway process description can be used to describe bidirectional
exchange in a forest canopy (see e.g., Fowler et al.. 2009; Loubet et al.. 2001): (1) a
stomatal pathway, which is bidirectional and modeled using a stomatal compensation
point and (2) a plant surface pathway, which denotes exchange with water surfaces or
waxes on the plant surface.
Field observations demonstrate that deposition of HNO3 is rapid and is constrained only
by the rate of transfer by atmospheric turbulence (Weselv and Lcsht. 1989). Surface
resistance to HNO3 uptake by vegetation is negligible. Its deposition rate is independent
of leaf area or stomatal conductance, implying that deposition occurs to branches, soil,
and the leaf cuticle as well as leaf surfaces. Ki for HNO3 typically exceeds 1 cm/s and
exhibits a diel pattern characterized by a maximum in turbulent transfer around
mid-afternoon and lower values at night in the more stable boundary layer.
NO2 exchange with foliage (J) can be related to the stomatal conductance (g.s) and a
concentration gradient between the ambient air NO2 concentration (Ca) and interstitial air
NO2 concentration (C) in the leaf (Ca ~ G) as depicted in Equation 2-18.
/ = gs(ca ~ Ct)
Equation 2-18
This approach best describes results for exchange with individual foliage elements and is
expressed per unit leaf or needle area. While this approach provides linkage to leaf
physiology, it is not easily scaled up from the leaf to the ecosystem. However,
compensation points are not fixed but rather vary by plant species, plant life cycle, and
environmental conditions; compensation points are typically reported to be in the range
of -0.05 to 3 ppb [see e.g., Raivonen et al. (2009)1. Given the variability of NO2 levels
found in the atmosphere, this range suggests that NO2 can either be taken up by the
canopy near NO2 sources (e.g., near urban areas) or be emitted in remote regions where
NO2 levels are low.
Understanding the exchange of reactive nitrogen species in the forest canopy has always
been challenging. One of the most comprehensive studies focusing on this question has
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been the Biosphere Effects on AeRosols and Photochemistry Experiment (BEARPEX)
conducted in 2009 (Min et al.. 2014) that examined fluxes and transformations of NOx
within a forest canopy on the western slope of the Sierra Madre range in 2009. The
study's results, shown schematically in Figure 2-20. indicate the existence of active
chemical interactions within the forest canopy in which NO emitted from soil or
transported from elsewhere is oxidized to NO2 and then to peroxy and alkyl nitrates and
HNO3. These pathways represent alternative mechanisms to plant uptake that have the
net effect of reducing the soil NO that escapes the forest canopy as NOx is converted to
peroxy nitrates and alkyl nitrates that can be transported to the atmosphere above the
canopy on very short time scales (~100s of seconds). The fraction of NO emitted by soil
that can be lost to the atmosphere above the canopy depends on the relative time scales
for transport through the canopy versus chemical transformation and foliar uptake.
Likewise, NO or NO2 transported form elsewhere can also be oxidized to organic nitrates
within the canopy. The organic nitrates formed can either be taken up within the canopy
or be transported upward through the forest canopy to act as reservoirs of NOx that can
reform downwind.
NO;
hv
RO
OH
RONO;
HNO;
NO
NO;
_ Tl"rA _]
(~100s seel
NO
N02
RONO;
HNO;
uptake
uptake
uptake
OH
RO
canopy reduction
emission
deposition
deposition
HNO3 = nitric acid; hv = soiar photon; OH = hydroxyl radical; NO = nitric oxide; N02 = nitrogen dioxide; NOx = sum of NO and N02;
03 = ozone; RO = aikoxy radicals; R02 = organic peroxy radicals: RON02 = alkyl nitrates; R02N02 =peroxy nitrates.
Bold arrows in blue (downward) and red (upward) represent the direction of the flux of each species across the canopy surface. Red
thin arrows within canopy indicate the nitrogen oxides removal processes within the canopy in addition to plant uptake.
Source: Min et al. (2014).
Figure 2-20 Schematic of the interactions involved in the exchange of
nitrogen oxides between the atmosphere and the forest canopy
as identified by Min et al. (2014).
The organic nitrates consist in large measure of isoprene- and monoterpene-derived
nitrates. Nauven et al. (2015) measured fluxes of organic nitrates on a tall tower in the
Talladega National Forest (AL) in June 2013 as part of the Southern Oxidant and Aerosol
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Study (SOAS). They found that fluxes of organic nitrogen formed by reactions of
nitrogen oxides (NO, NO2, NO3) with isoprene and monoterpene oxidation products
constituted -15% of the flux of oxidized N to the forest canopy, with most of the rest
from HNO3. Interaction of HNO3 with inlet surfaces required correction of the HNO3
fluxes, which were increased by a factor of 1.62 based on degrading of the signal from
species that do not stick to inlet surfaces.
2.8 Geographic Distribution of Deposition of Nitrogen and Sulfur
Species
Schwede and Lear (2014a) developed an approach that combines measured and modeled
values for producing spatially aggregated maps of wet, dry, and total (wet plus dry)
deposition of nitrogen and sulfur species across the U.S. Wet deposition is based on
concentrations measured in rainwater collected at NADP/NTN monitoring sites
combined with precipitation estimates interpolated by PRISM (Parameter-elevation
Regression Slopes Model). In their approach to dry deposition, measured values of
species concentrations in air are used at monitoring site locations, and bias-corrected
modeling results from CMAQ (currently at 12-km horizontal resolution) are used to fill
in gaps between sites and to provide composition and deposition information for species
not measured (PANs, NO2, and HONO) in the routine monitoring networks. Distributions
of species that undergo dry deposition are derived mainly by fusion of data from the
Clean Air Status and Trends Network (CASTNET), the National Atmospheric Deposition
Program (NADP), Ammonia Monitoring Network (AMoN), and the Southeastern
Aerosol Research and Characterization (SEARCH) network. Note however that the
sampling artifacts mentioned in Section 2^5 should be considered. Parameterizations in
CMAQ are used to calculate deposition velocities for gases and particles (Pleim and Ran.
2011). Note that CMAQ includes bidirectional exchange for NH3 (Bash et al.. 2012). but
not for other species such as NO2. Dry deposition fluxes are then combined with wet
fluxes to estimate total deposition.
Efforts have also been made to achieve greater consistency by relying more heavily on
WRF/CMAQ simulations for estimating wet deposition. Effects of biases in CMAQ wet
deposition are corrected by adjusting the modeled wet deposition by the ratio of observed
precipitation interpolated by PRISM to WRF precipitation. In this approach, it is assumed
that the ratio of observed to modeled precipitation is well correlated with the ratio of
observed to modeled wet deposition, but not (necessarily) that wet deposition scales
linearly with precipitation Appel et al. (2011). Likewise, estimates of dry deposition
could be obtained using CMAQ evaluated by comparison with monitoring results.
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Maps providing estimates of continuous spatial and temporal coverage of wet and dry
deposition (beginning in 2000) for nitrogen and sulfur species and documentation of the
process used to generate these maps as part of the total deposition activity (TDEP) are
posted on the NADP website at http://nadp.isws.illinois.edu/tdepmaps. These maps are
shown also in Appendix A for two, 3-year periods, 2000-2002 and 2011-2113 as Figure
A-1 to Figure A-25. These additional maps are meant to provide an indication of changes
in various parameters between these periods. Although instructive, it should be
remembered when viewing these maps that model estimates are subject to uncertainty,
and for many parameters, comparison to observations is still needed.
The TDEP values shown on the maps are derived from NADP/NTN wet deposition
measurements at 4 km resolution coupled with CMAQ results for dry deposition at
12 km. Weathers et al. (2006) found evidence for substantial spatial variability in
deposition with altitude, generally at smaller scales than used for TDEP. In particular,
they found evidence for factors of 4-6 variability in N and S deposition throughout
Acadia NP (121 km2) and Great Smoky Mountains NP (2,074 km2); deposition rates
averaged over the two parks were -70% higher than inferred using only in situ point
measurements. As might be expected, deposition increased with elevation because of the
increased importance of cloud deposition and dry deposition (due to higher winds and
hence increased turbulence).
Distributions of dry deposition of NO2 and SO2 from satellite-based measurements of
tropospheric vertical column abundance and model input derived by Nowlan et al. (2014)
are also shown in Section 2.8.4.
2.8.1 Distribution of Deposition Derived Using Surface Measurements and
Chemistry Transport Models
Fluxes are based on the method developed by Schwede and Lear (2014a) as outlined
above and are given in terms of kg (N or S)/ha/yr.
2.8.1.1 Deposition of Nitrogen
Figure 2-21 shows total deposition of N, which as noted earlier in Section 2J_ is given by
the sum of all NOy and NHx species considered by CMAQ.
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Total deposition of nitrogen 1113
TTSEPA irvib/14
Source: CASTNFT/C:MAQ/NT\7Atv10N/SF.ARCH
Jtal N
(kg-N/ha)
N = nitrogen; Nr = reactive nitrogen.
Source: CASTNET/CMAQ/NTN/AMON/SEARCH.
Figure 2-21 Total (wet + dry) deposition of nitrogen (kg N/ha/yr) over the
contiguous U.S. 2011-2013.
As can be seen from Figure 2-21. highest deposition of nitrogen occurs in a broad swath
across the Midwest, and in more localized patches across the U.S. Inspection of Figure
2-22a and Figure 2-22b shows that many of these areas are dominated either by
deposition of NHx emitted mainly by agriculture (e.g., California's Central Valley, Upper
Midwest), or NO , resulting from oxidation of nitrogen oxides emitted mainly by
combustion sources (e.g., the Northeast, Southwest). As might be expected when
considering all forms of NOy, total deposition tends to be much higher near urban and
suburban areas. Note also that deposition of Nr, based on the hybrid
measurements/modeling approach, is dominated by reduced forms across the CONUS as
a whole. Alternatively, Figure 2-23a and Figure 2-23b show the depositional flux of NHx
and NOy over the CONUS 2011-2013 to facilitate comparison with critical loads.
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Pet of total N as reduced N 1113
USEPA 10/16/1-1
Source: CASTNET/CMAQ/NTN/AMON7SEARCII
Total reN
(Pet of Total)
reN = reduced nitrogen.
Source: CASTNET/CMAQ/NT N/AM ON/SEARCH.
Figure 2-22a Percent of total nitrogen deposition as reduced inorganic
nitrogen over the contiguous U.S. 2011-2013.
Total oxN
(Pet of Total)
-60
IT70
¦-80
1-90
B->100
Pet of total N as oxidised N 1113
USEPA 10/16/14
Soiree: CASTNET'/CMAQ/NTN/AMQN/SEARCH
oxN = oxidized nitrogen.
Source: CASTNET/CMAQ/NTN/AMON/SEARCH.
Figure 2-22b Percent of total nitrogen deposition as oxidized nitrogen over the
contiguous U.S. 2011-2013.
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Total deposition of reduced N 1113
USEFA 10/16/14
Total reN
(kg-N/^a)
reN = reduced nitrogen.
Source: CASTNET/CMAQ/NTN/AMON/SEARCH.
Figure 2-23a Total reduced inorganic nitrogen deposition over the contiguous
U.S. 2011-2013.
Total deposition of oxidized N LI 13
USEPA 10/16/14
Source: €IASTNKT/CMAQ/NTN/AMON/SBAROI
Total oxN
(kg-N/ha)
oxN = oxidized nitrogen.
Source: CASTNET/CMAQ/NTN/AMON/SEARCH
Figure 2-23b Total oxidized nitrogen deposition over the contiguous U.S.
2011-2013.
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Dry deposition of gas-phase N (as HNO3 and NH3) dominates over particulate forms
(pNC>3~, NH4+) over most of the CONUS according to the hybrid method. Overall,
deposition of N is mainly as reduced forms, with a maximum over the north-central U.S.
The Central Valley of California, northern Utah, and eastern North Carolina are among
other areas of high deposition of reduced N. In general, dry deposition of N, in either
oxidized or reduced form, exceeds wet deposition across the CONUS. However, based on
discussions in earlier sections, uncertainties for dry deposition are likely much larger than
for wet deposition.
In constructing Figure 2-20 through Figure 2-23. the assumption was made that 80% of
pNOs is in the fine mode and 20% is in the coarse mode. Note also, the monitors in
CASTNET do not use size-selected inlets. As shown in Figure 2-19. the deposition
velocity of particles increases dramatically with particle size due to gravitational settling,
resulting in higher deposition rates than calculated if pNO? were found mainly in the fine
mode. However, to the extent there is displacement of HNO3 by acid sulfur species in
fine particles as occurs in the eastern U.S. due to much higher emissions of SO2 than in
the western U.S. [e.g., Wolff (1984); especially in coastal areas where displacement of
Cr in marine aerosol occurs], higher levels of pNOs would be found in coarse mode
particles (see Section 2.3). During the Tampa Bay Study, measured and modeled (using
CMAQ) concentrations of HNO3 and pNOs, in PM10-2.5 were much higher than pNOs in
PM2 5. Wolff (1984) found that most pNOs (as NH4NO3) is found in the fine mode in
Denver but in the coarse mode (associated with Ca2+ and Mg2+) in measurements made in
Detroit and rural South Dakota, Louisiana, and Virginia. Blanchard et al. (2013) found a
range of 32 to 63% for the fraction of pNO;, in PM10-2.5 versus PM2 5 particles in the
Southeast: Lee et al. (2008) found that most pNO? was in the coarse mode at Grand
Canyon and Great Smoky Mountains, corroborating earlier findings at Yosemite and Big
Bend national Parks. They also found that both coarse and fine mode pNOs were
important at Brigantine National Wildlife Refuge, NJ and San Gorgonio Wilderness
Area, CA. Lefer and Talbot (2001) also found that NO? sampled at Harvard Forest, MA
between March and October was mainly found in the coarse mode with a mass median
diameter of 4.8 ±1.5 (jm. These results indicate considerable regional variability in the
ratio of pNOs, in the fine and coarse modes and consequently additional uncertainty in
estimates of pNOs deposition.
Studies at individual sites (e.g., on the North Carolina Coast) have shown that about 30%
of wet deposition of N consisted of organic N, 20-30% of which was then available to
primary producers on time scales of hours to days (Peierls and Paerl. 1997). In addition,
Benedict et al. (2013) found that wet deposition of organic nitrogen contributed 18% of
total quantified reactive nitrogen deposition and 25% of wet nitrogen deposition at Rocky
Mountain National Park between November 2008 and November 2009.
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3
As mentioned earlier, several species potentially important for deposition are not
measured in CASTNET. Figure 2-24 shows dry deposition for oxidized nitrogen species
(e.g.. PAN, other organic nitrates, HQNO) calculated by CMAQ.
Pet of total N as unmeasured species 1113
USEPA 10/16/14
Source: CASIWI/CM AQ/TCIN/AMO.N/SEARCH
Other N
(PctofTotal)
N = nitrogen.
Source: CASTNET/CMAQ/NTN/AMON/SEARCH.
Figure 2-24 Three-year average percentage of total nitrogen deposition by
species (i.e., those species that are not measured in the
networks) simulated by the Community Multiscale for Air Quality
modeling system.
4 As seen in Figure 2-24. deposition of these species can contribute substantially to
5 nitrogen deposition, especially near strong sources, in particular large urban areas.
2.8.1.2 Deposition of Sulfur Oxides
6 Figure 2-25 shows wet plus dry deposition of SOx (SO2 + SOr ) over the CONUS.
7 Maximum deposition occurs over the Ohio River Valley (southeastern Ohio, West
8 Virginia, and western Pennsylvania). Figure 2-26 shows a good deal of spatial variability
9 in the percentage of dry deposition across the CONUS. In the area of highest total
10 deposition in the Mid-Atlantic States, dry deposition of SO2 is dominant and dry
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deposition of pSOa2 is very minor component of dry deposition of SOx. Wet deposition
dominates in the Pacific Northwest, northern New England and in general in the central
U.S. Note that deposition of organic sulfur species (e.g., methane sulfonic acid) or SO2
and/or SO42 produced by the oxidation of organic S species is not included.
TomJ iteposition cf sulfur 1113
HSlil'A mill'14
Si urn =: (:ASTN I T.t ?V1 AQ.'NTN/AM()N .SI lARCIt
Total S
(kg-S/Ha)
S = sulfur.
Source: CASTNET/CMAQ/NTN/AMON/SEARCH.
Figure 2-25 Total deposition of Sulfur (kg S/ha/yr) over the contiguous U.S.
2011-2013.
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due mainly to large decreases in dry deposition of total nitrate (TNO3 = HNO3 + pNO, :
see Figure A-9). The decreases in total nitrate across the CONUS are generally due to
decreases in HNO3 (see Figure A-10). Decreases in dry deposition of pNCh have
generally been smaller, reflecting the smaller contribution of pNO, to TNO3. Exceptions
include areas such as Florida, Texas, and southern California where dry deposition of
pNCh has been much greater than HNO3 in the earlier period and has decreased
substantially (see Figure A-I I). Other N species, mainly N02 also show large decreases
(see Figure A-12 and Figure A-13). especially near urban source areas. Using OMI data,
krotkov et al. (2016) found decreases in column (vertically integrated) abundances of
NO2 of -40% from 2005 to 2014 over the U.S.
In contrast to deposition of oxidized N, deposition of reduced inorganic N has seen large
increases (see Figure A-14 and Figure A-15). Several hotspots (the San Joaquin Valley,
southern Idaho, and several areas in the central and eastern U.S.) have increased
markedly in size (see Figure A-14) between the two periods. Dry deposition of NH3 has
been the major contributor to the increase (see Figure A-16). while dry deposition of
pNH4+ has largely decreased between the two periods (see Figure A-17). Between the two
periods, emissions ofNOxhave decreased resulting in lower formation rates of HNO3
that could react with NH3 to form PNH4NO3.
Deposition of oxidized and reduced N have undergone geographic shifts with
corresponding shifts in the contributions of each to total N deposition on regional and
smaller scales (compare Figure A-5 and Figure A-6 to Figure A-14 and Figure A-15). For
example, deposition of oxidized N in the Northeast has decreased substantially, but
deposition of reduced N has increased substantially in the central U.S. Sizable shifts are
also seen in the fractional contributions of total N deposition as dry deposition of both
oxidized and reduced forms (compare Figure A-4 and Figure A-19).
Substantial declines in the deposition of S have occurred over the past 15 years,
particularly in the Ohio River Valley (see Figure A-20). with generally much smaller
declines in wet deposition (see Figure A-21) than for dry deposition (see Figure A-22).
Despite these declines, S deposition is still highest in the Ohio River Valley. Except for
small shifts in several areas, the proportion of S dry deposited has been rather similar (see
Figure A-23). Dry deposition of SO2 is still dominant over pSOr in eastern Ohio and
central Pennsylvania (compare Figure A-23 and Figure A-24 to Figure A-25). These
decreases are consistent with those derived by krotkov et al. (2016) who detected
decreases in the column (vertically integrated) abundance of SO2 of -75 % for the period
2005 to 2014 over the Ohio River Valley and southwestern Pennsylvania. These
decreases reflect reductions in emissions mandated by the Clean Air Act Amendments
and other regulatory requirements.
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As noted earlier, these estimates of change in deposition were derived from CMAQ
output and data from measurement networks. Each of these components has its own set
of uncertainties, and the estimates of deposition and the changes over time should be
viewed in this light.
2.8.3 Long-Term Changes in Wet Deposition
Longer term changes than those described above can only be assessed based on wet
deposition data collected by the NADP/NTN. Changes in the pH of rainwater over the
CONUS between the two periods 1989 to 1991 and 2011 to 2013 are shown in Figure
2-27.
(pH Units)
—- 4.2
NADT
IftvEFAXAMD »OWI'
Source: NADP/U.S. EPA/CAMD.
Figure 2-27 (Left) pH of rainwater, 1989-1991; (Right) pH of rainwater,
2011-2013.
As shown in Figure 2-27. substantial improvement in the quality of rainwater in terms of
pH has occurred from the earlier to the later period. However, there are areas, especially
in the eastern U.S. near the upper Ohio River Valley, where the pH of rainwater is still
much lower than the reference pH of -5.65 (for equilibrium with CO2) that has often
been used as a benchmark when characterizing the excess acidity of rainwater. (Note that
the reference CO2 concentration used to determine this value is 316 ppm, atmospheric
CO2 concentrations are now over 400 ppm, resulting in a lowering of pH by -0.05 units).
As noted by Galloway et al. (1976 the major contributors to free acidity in rainwater for
pH <5.6 are the strong mineral acids HNO3 and H2SO4. However, weak acids
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(e.g., organic acids) can contribute substantively to free acidity at pH levels seen
throughout much of the U.S. For example, concentrations of formic acid and acetic acid
(pKa = 3.75, 4.76) measured in rainwater at pH ~5 by Avery et al. (2006) are of the order
of 10 |iM. which is comparable to concentrations of NOs and SO42 measured in
rainwater. Additionally, in areas like the Northwest where the pH of stream water can be
around or even larger than 5.6, acidification of streams by CO2 might also need to be
considered (Qu et al.. 2015).
Differences in wet deposition of NFU+, NO3 . and SO42 and N + S expressed as H+
equivalents between the two, 3-yr periods 1989-1991 and 2012-2014 across the U.S.
based on data obtained by the NADP/NTN are shown in Figure 2-28 through Figure
2-31. These maps were constructed by summing gridded values and then taking the
difference between the two, 3-year averages using data from the NADP website.
Although instructive, these results should be viewed with some caution, as errors are
incurred because development of a map spanning the CONUS requires extensive
interpolation in-between monitoring sites, which are often distant from each other. As
noted by the NADP, uncertainty within maps of wet deposition varies geographically and
has not been quantified. These maps are meant to provide a general indication of large
scale features in the patterns and long-term changes in deposition.
Figure 2-28 shows large increases in wet deposition of NFU+ centered in eastern North
Carolina and throughout the North Central U.S. and decreases in the Gulf States. The
situation is more nuanced than shown in that some sites show small increases and others
small decreases. In general, large-scale increases in wet deposition of NH/, rather than
decreases, are seen across the U.S. in agreement with the analysis of Li et al. (2016).
Figure 2-29 shows that most locations in the U.S. show decreases in wet deposition of
NC>3~, which are associated with NOx emissions control measures since the passage of
the 1990 Clean Air Act amendments. However, some areas, located mainly in the
Intermountain West show increases. As noted earlier, Hand et al. (2012a) suggest that
this increase might be related to oil and gas exploration and production in the region,
transport from oil and gas fields in Alberta and also to expansion of motor vehicles and
EGUs to meet the demands of population growth. The large area with the strongest
increases in the North-Central U.S. corresponds to oil and gas operations in the Bakken
Shale.
Figure 2-30 shows that the pattern for changes in wet deposition of SO42 is similar to
that for N03 with strongest decreases in the East, but with many areas in the western
U.S. showing some increase. Reasons for this increase are similar to those for NO3 as
noted by Hand et al. (2012a).
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between (1989-1991) and (2012-2014)
Change in NH4+ Wet Deposition in the U.S.
Change in NIV (Kg N/ha/yr) for 3-Yr. Avgs. Between 1989-1991 and 2012-2014
y #v
vo' kP
v v
^ JV ^
<&• \* v v
' «0 wO *0 -7
.1p V 0- <5 *
-------
Change in N03~ Wet Deposition in the U.S.
between (1989-1991) and (2012-2014)
Change in N03 (Kg N/ha/yr) for 3-Yr. Avgs. Between 1989-1991 and 2012-2014
" I I I I
a? J ^ ^ ^
t' _«s>' ,*?' n-° O0 *
_ "V" • V ,V "N 'X "L, ^m
^ N.^ CS- rvO' ^ 0 400 800 ^
*v * * * * Source: NADP NTN Annual Gradients
N = nitrogen; N03" = nitrate.
Figure 2-29 Difference in wet deposition of nitrate (kg N/ha/yr) over the
contiguous U.S. between 1989 to 1991 and 2012 to 2014. The
range of positive values is smaller than that for negative values.
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Change in S042' Wet Deposition in the U.S.
between (1989-1991) and (2012-2014)
Change in S042' (Kg S/ha/yr) for 3-Yr. Avgs. Between 1989-1991 and 2012-2014
Kilometers
0 400 800 A.
Source: NADP NTN Annual Gradients
S = sulfur; S042 = sulfate.
Figure 2-30 Difference in wet deposition of sulfate (kg S/ha/yr) over the
contiguous U.S. between 1989 to 1991 and 2012 to 2014. The
range of positive values is much smaller than for negative values.
1 The increases in wet deposition of SO42 in the North-Central U.S. correspond to those
2 for NO; and are in the immediate vicinity of the Bakken Shale. There is a high degree of
3 interannual variability in deposition in some areas, especially those showing increases
4 (e.g., Logan UT/Idaho, making source attribution difficult. The change in acid loading
5 (H+ equivalents) due to deposition of nitrate, ammonium and sulfate ions in precipitation
6 is shown in Figure 2-31. Substantial decreases in acid loading are seen in the eastern U.S.
7 with areas in the central and western U.S. showing smaller positive or negative changes
8 or essentially no change. In viewing maps such as these it should be borne in mind that
9 the rates and patterns of deposition are continually changing due to ongoing
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implementation of control measures and shifting patterns of population growth, and
industrial and agricultural activities.
Change in Nitrogen and Sulfur Wet Deposition from Nitrate, Ammonium,
and Sulfate in the U.S. between 1989 to 2014
Change in N and S Deposition (Eq. H*/ha) for 3-Yr. Avgs. Between 1989-1991 and 2012-2014
Kilometers
0 400 800 ^
Source: NADP NTN Annual Gradients
H+ = hydrogen ion; eq = H+ equivalent.
Figure 2-31 Difference in wet deposition of nitrate, ammonium and sulfate
expressed as hydrogen ion equivalents (eq/ha/yr) over the
contiguous U.S. between 1989 to 1991 and 2012 to 2014.
3 Figure 2-32 shows total wet deposition of N (NH4 + NOa ) binned in increments of 2 kg
4 N/ha/yr for comparison to critical loads estimates. Although it is apparent that N wet
5 deposition has decreased overall across the U.S., there are areas showing increases. Also
6 shown are NTN sites active during either period.
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Sum NO3' and NH4+ Wet Deposition by 3-Yr. Averages
2012 - 2014
t
• •
JT^l
1989 - 1991
Kg NI ha /yr • • ^
~ <2
> 2 to 4
^] > 4 to 6
| > 6 to 8
| > 8 to 10
¦¦ > 10
• Active NTN Sites '89-'91 or ,12-'14
0 500 1.000 ^
Source: NADP NTN Annual Gradients
NTN = National Trends Network: N = nitrogen; NH/ = ammonium; N03" = nitrate.
Figure 2-32 Wet deposition of ammonium + nitrate (kg N/ha/yr) over the
contiguous U.S. in two, 3-year periods, 2012 to 2014 and 1989 to
1991. Also shown are active National Trends Network sites in
either period.
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2.8.4 Distributions of Dry Deposition of Nitrogen Dioxide and Sulfur Dioxide
Derived Using Satellite-Based Measurements and Chemistry Transport
Models
Figure 2-33 shows the annual average dry deposition velocities and fluxes of NO2 and
SO2 for 2005 to 2007 and their estimated uncertainties derived by Nowlan et al. (2014)
using data derived from the Ozone Monitoring Instrument (OMI) on board the Aura
satellite and model parameters from the GEOS-Chem three-dimensional,
chemistry-transport model.
As shown in Figure 2-33. higher fluxes for both NO2 and SO2 occur in the East than in
the West. In particular, there is a band of high dry deposition for NO2 and SO2 along the
Ohio River. High depositional fluxes for NO2 are also seen along the Northeast Corridor
and in scattered locations throughout the East. In addition, there is a noticeable plume of
SO2 over the western Atlantic Ocean. Average, relative uncertainty in the flux estimates
for both NO2 and SO2 are -30% over land and are not much higher over the Atlantic
Ocean south of Massachusetts and Nova Scotia. Increased SO2 deposition, especially
near shore, is expected based on the likelihood of off-shore transport of SO2 and NO2
along with other pollutants by synoptic weather systems (see Section 2.4). Note that
bidirectional exchange for NO2 (and a number of other gases) has not been implemented
yet in GEOS-Chem or in CMAQ. Note also that in this study, older algorithms have been
used for derivation of NO2 and SO2 columns than more recent ones with lower detection
limits. These results, however, do illustrate the potential of the hybrid, satellite/model
approach for mapping deposition at the continental scale.
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NO Dry Deposition Velocity [cm s ' J
SO Dry Deposition Velocity [cms1]
0 0.2 0.4 0.6 0.8 >1 0 2 4 6 8 >10
NO Dry Deposition Flux [kg N ha"1 yr'1 ] SO Dry Deposition Flux [kg S ha'1 yr"']
0 0.1 0.2 >0.3 0 1 2 3 4 >5
NO, Dry Deposition Uncertainty [kg N ha"1 yr'1] S02 Dry Deposition Flux Uncertainty [kg S ha'' yr"']
N = nitrogen; N02 = nitrogen dioxide; S = sulfur; S02 = sulfur dioxide.
Source: Nowlan et al. (2014).
Figure 2-33 Top panel: Modeled deposition velocities for nitrogen dioxide and
sulfur dioxide for 2005 to 2007; Middle panel Satellite-model
estimates of annual mean dry deposition fluxes of nitrogen
dioxide and sulfur dioxide; Bottom panel: Uncertainties in
estimates.
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2.9 Transference Ratios Relating Deposition to Ambient Oxidized
Nitrogen Species and Sulfur Oxides.
Ratios of modeled or measured concentrations of SOx and NOy to their deposition, or
transference ratios (TRatio—SOx, NOy) were proposed by Scheffe et al. (2011) as a
means to link ambient air quality to deposition. Transference ratios for NOy and SOx are
given by:
• TRatio—NOy = (annual wet + dry deposition of NOyVannual average ambient
concentration of NOy
• TRatio—SOx = (annual wet + dry deposition of SOx)/annual average ambient
concentration of SOx
and can be extended to NHx:
• TRatio—NHx = (annual wet + dry deposition of NHx)/annual average ambient
concentration of NHx
These ratios are expressed in units of distance/time (like a velocity) and can be multiplied
by measured ambient concentrations of NOy and SOx to give a flux.
In practice, a regional modeling approach using a modeling system such as CMAQ or
CAMx is used in the calculation of transference ratios by simulating the relevant
transport processes discussed in Section 2 A because these models incorporate a
self-consistent approach to calculating all of the parameters involved in deposition and
generate deposition rates of all species that constitute NOy. In contrast, CASTNET
reports concentrations of HNO3, pNOs , SO2, and pS042 and their dry deposition using
locally inferred values. Mass conservation is another issue to consider when combining
measurements with model output. Sickles and Shadwick (2013) and Sickles et al. (2013)
estimated that TRatio—SOx and TRatio—NOy could be given to within 25-35% of
observed values using CMAQ. Model-derived transference ratios can then be multiplied
by measured ambient concentrations to derive total deposition for NOy and SOx.
koo et al. (2012) and koo et al. (2015) raised the issue of model dependence on the
calculation of depositing species and transference ratios, koo et al. (2012) compared
model results for concentrations of SO2, SO42 . HNO3, and NO3 and corresponding dry
deposition fluxes from CMAQ and CAMx to those measured at CASTNET sites. They
also compared model results for wet deposition to NADP/NTN measurements. On an
annualized basis, mean normalized errors (MNEs) in gas-phase concentrations ranged
from -25 to -100%. MNEs in dry deposition were much larger and ranged from -50 to
>300% and MNE in wet deposition ranged from -40 to -100% with no clear preference
for one model over another. MNE for NH4+ in dry and wet deposition ranged from -35 to
70%. koo et al. (2012) also found evidence for spatial variability in TR;il,„—SOx and
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TRatio—NOy across the U.S. and within selected ecosystems (roughly a few hundred km
across). The transport processes described in Section 2 A imply that wet deposition should
not necessarily be well correlated with surface concentrations because of differences in
the direction or spatial extent of transport in the boundary layer compared to cloud levels.
Dry deposition fluxes are more directly related to surface concentrations. However,
bidirectional exchange will modify the association between ambient concentrations and
dry deposition fluxes thereby introducing additional uncertainty into the calculation of
transference ratios.
Koo et al. (2015) compared simulations of transference ratios computed using CMAQ
and CAMx for two model years, 2005 and 2014, (see Figure 2-34) and found that
TRatio—SOx was much higher in CMAQ than in CAMx: however, differences were much
smaller for TRatm—NOy. R2 values for TRatio—NOy between the two models was 0.37 for
2005 and 0.33 for 2014. For TRatio—SOx, R2 was 0.073 for 2005 and 0.072 for 2014.
Note that each point shown in Figure 2-34 represents the average over 365 x 24 model
entries and are dissimilar to measurement artifacts. The outlying point (in the lower right)
is from the Weminuche Wilderness IMPROVE site (WEMI) in the Rockies and likely is
the result of the difficulty mesoscale models have in simulating precipitation and flow
patterns in areas of high relief and indicates further work is needed in this regard. Note
that the disagreement in TRatio—SOx by CMAQ is mostly due to an error in CMAQ
emissions of SO2 that has since been corrected. There is no consistent geographic pattern
of agreement or disagreement between the two simulations.
A more complete understanding of the causes of differences between model simulations
requires understanding the differences in how major chemical and physical processes
have been parameterized, thus underscoring the importance of accurately representing
emissions, transport, chemistry and deposition. Both models used different modules to
represent these processes. In addition, these results might imply that metrics used need
further scrutiny. Note again that the results shown in Koo et al. (2012) and Koo et al.
(2015) were obtained using older versions of CMAQ and CAMx and that CTMs are
continually undergoing improvement. In this regard, detailed comparisons with
observations and intercomparisons between the most current versions of these models
might help explain these findings.
Koo et al. (2015) also found very small differences between simulations for model years
2005 and 2014 from either CMAQ or CAMx for both NOy and SOx indicating ratios are
relatively invariant at least over an annual time scale. This result is not surprising.
Because of the long averaging time, concentrations and deposition rates can better track
emissions changes.
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o 2005
+ 2014
o CAMx
+ CMAQ
o CAMx
+ CMAQ
2005
(a) TRJtj0 SOx {CMAQ vs. CAMx)
3.5
CAMx
(c) TRatio NOy (CMAQ vs. CAMx)
0 0.2 0.4 0.6 0.8 1 1.2 1.4
CAMx
{b) TRatlo SOx (2014 vs. 2005)
(d) TRitto NOy (2014 vs. 2005)
—T I I I I
0.4 0.6 0.8 1 1.2
2005
CAMx = Comprehensive Air Quality Model with Extensions; CMAQ = Community Multiscale for Air Quality; NOY = oxides of
nitrogen; SOx = sulfur oxides; TRatio = transference ratio.
Source: Adapted from Koo et al. (2015).
Figure 2-34 Scatterplots showing transference ratios for oxidized nitrogen
and sulfur oxides comparing Community Multiscale for Air
Quality model to Comprehensive Air Quality Model with
Extensions in (a) and (c) and comparing 2005 to 2014 in (b) and
(d).
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2.10
Background Sources of Oxidized and Reduced Nitrogen and
Oxidized Sulfur Species
As defined in other ISAs, background refers to those concentrations or fluxes that do not
result from U.S. anthropogenic emissions. Background sources of N include natural
sources like lightning, wildfires, and emission from soils as well as anthropogenic
sources from outside the U.S. Background sources of SOx include natural sources, such
as volcanos or oxidation of reduced sulfur species (H2S,[CH3]2S) emitted in anaerobic
environments, and anthropogenic sources from outside the U.S. Background levels so
defined facilitate separation of pollution levels that can be controlled by U.S. regulations
(or through international agreements with neighboring countries) from levels that are
generally uncontrollable by the U.S.
Kim et al. (2014a) found increases in nitrate concentrations in the mixed layer of the
North Pacific Ocean, extending to near-shore areas off the west coast of the U.S., with
attendant changes in the status of N limitation. Because NH3 and NH44" are so highly
soluble, they are likely to be removed in rain during ascent before trans-Pacific transport.
Because SO2 is much less soluble than NH3, it can be transported to the free troposphere
by the warm conveyor belt system (see Section 2.4) before it is oxidized to SO42 in cloud
droplets or on the surfaces of mineral dust particles. The survivability of nitrate is
intermediate, depending on the form the nitrate takes.
Zhang et al. (2012a) computed N deposition rates from background sources and from
domestic anthropogenic sources using GEOS-Chem. According to their estimates, most
of the eastern U.S. and parts of states along the Pacific Coast received >10 kg/ha/yr N
deposition. The version of GEOS-Chem used (8.2.3) is the same as described in Zhang et
al. (2011a) and used in the 2013 ISA for Ozone and Other Photochemical Oxidants (U.S.
EPA. 2013c). Figure 2-35 shows contributions from domestic anthropogenic, foreign
anthropogenic, and natural emissions to total (wet + dry) annual nitrogen deposition over
the CONUS for 2006 calculated by Zhang et al. (2012a) using the GEOS-Chem global
scale CTM with a horizontal resolution of 1/2° by 2/3°.
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Nitrogen deposition enhancement Percentage contribution
US
anthropogenic
Foreign
anthropogenic
Natural
0.1 0,3 1 2 3 6 8 12 16 0 5 10 20 30 50 70 90 [%]
[kg Nha'a']
Source; Zhang et al. (2012a).
Figure 2-35 Contributions to oxidized and reduced nitrogen deposition from
U.S. anthropogenic (top), foreign anthropogenic (middle) and
natural sources (bottom).
The upper panel of Figure 2-35 shows that highest values from U.S. anthropogenic
sources are found in the eastern U.S. in and downwind of the Ohio River Valley and in
and around urban areas. The middle panel of Figure 2-35 shows highest contributions
from foreign anthropogenic sources is largest in regions of the CONUS bordering Canada
and Mexico. Note the band of highest contribution in upper New York State as a result of
emissions in southern Canada. There is also some indication in the Pacific Northwest of
smaller contributions due to transport from Eurasia. The pattern of N deposition in the
simulation for natural sources in Figure 2-35 (bottom panel), however, shows maximum
deposition throughout the Central U.S. with the highest values over the Midwest,
reflecting a combination of NOy emissions from lightning in the south-central U.S.,
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biomass burning throughout the Southeast, and soils mainly in the Midwest. The
background contribution to N deposition is typically <30% over the eastern U.S. and
typically 30 to 50% in the western U.S. where N deposition is already lower. Overall,
according to these simulations, U.S. anthropogenic emissions account for 78% of Nr
deposition over the CONUS. Foreign anthropogenic emissions and natural emissions
account for 6 and 16% respectively of total N deposition in this model simulation.
Background concentrations of SO2 were calculated using the MOZART-2 global model
of tropospheric chemistry (Horow itz et al.. 2003) and were presented in the 2008 ISA for
Sulfur Oxides (U.S. EPA. 2008c). Background SO2 concentrations are estimated to be
below 10 parts per trillion (ppt) over much of the U.S. Maximum background
concentrations of SO2 of -30 ppt are found in the western U.S. In the Northwest, where
there are large geothermal sources of SO2, the contribution of background sources to total
SO2 is 70 to 80%; however, absolute SO2 concentrations are still on the order of ~2 ppb
or less. With the exception of the West Coast, where volcanic SO2 emissions cause high
background concentrations, background sources contribute 20% because of the geothermal
sources of SO2 and oxidation of DMS in surface water of the eastern Pacific. In
comparison, values observed at several relatively remote sites cited in the ISA for Sulfur
Oxides (U.S. EPA. 2008c) ranged from 20 to 40 ppt.
As noted earlier, volcanic sources of SO2 in the U.S. are found in the Pacific Northwest,
Alaska, and Hawaii. The greatest potential domestic effects from volcanic SO2 occur on
the island of Hawaii. Nearly continuous venting of SO2 from Mauna Loa and Kilauea
produces SO2 in high concentrations of ~5 ppm lasting for periods of up to 1 hour [see
Figure 2-34 and Figure 2-35 in the 2008 ISA for Sulfur Oxides; (U.S. EPA. 2008c)l at
two National Park sites near the Kilauea caldera and the nearby east rift zone. The latter
emits several times as much SO2 as the Kilauea caldera. The two measurement sites
within the National Park are <3 km from the summit emission source and ~10 km from
the east rift source and are affected by the two sources during southerly and easterly
winds. A number of communities and population centers are within the same distance
from the east rift gas source that affects these two monitoring sites. When the normal
trade wind flows are disrupted, emissions from the sources can be brought directly to
these various communities. Because these communities are located at a similar distance
from the large east rift emission source as the National Park monitoring stations, it is
probable that these communities are subjected to SO2 concentrations as high as those
measured within Hawaii Volcanoes National Park.
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Global scale modeling results reported in the last ISA for Oxides of Nitrogen and Sulfur
(U.S. EPA. 2008a') and in the latest ISAs for Oxides of Nitrogen (U.S. EPA. 2016b) and
Sulfur Oxides (U.S. EPA. 2008c) indicate that intercontinental transport of oxidized and
reduced nitrogen, SO2, and SO42 are likely minor background sources of these species.
Of greater importance are localized emissions from natural sources. These include
emissions of NO from soils and lightning and emissions of SO2 from geothermal and
biogenic sources.
Just as pollutants can be transported into the U.S., they can also be transported outward.
For example, wet deposition of pollutants emitted in eastern North America occurs over
the North Atlantic Ocean. Deposition of N species is an important source of nutrients to
the western North Atlantic (Zamora et al.. 2011). Dennis et al. (2013). based on CMAQ
modeling results, estimated that -1/3 of oxidized N emissions and slightly less than 1/3
of NH3 emissions in the U.S. are transported out over the North Atlantic Ocean. Although
the average pH of rainwater at Bermuda is ~5, reflecting deposition of acidic species
emitted in North America, this additional source of acidity is at most only -2% of that
due to anthropogenic CO2 (Bates and Peters. 2007).
2.11 Summary
H2SO4 and HNO3 have been long established as the major species contributing to acid
rain. Precipitation chemistry has been monitored at a large number of sites across the
U.S. for several decades as part of the National Acid Deposition Program (NADP).
Concentrations of inorganic gas and particulate phase N and S species have been
monitored across the U.S. since 1990 by the Clean Air Status and Trends Network
(CASTNET). These concentrations are then used to infer dry deposition (i.e., the transfer
of gaseous and particulate pollutants from the atmosphere to the surface by impaction
through turbulent motions and gravitational settling). Starting in 2007, monitoring of NH3
was initiated at a subset of CASTNET sites. Cloud deposition, which can account for the
bulk of deposition at high elevations in many mountainous areas, was monitored at
several sites in the Appalachian Range until 2001 by the Mountain Acid Deposition
Program (MADPro) but now is only measured at Whiteface Mountain and Mount
Washington on a regular basis. However, there have also been shorter term field studies
examining the composition of clouds and fogs conducted in various locations in the U.S.
Although the pH of rainwater has increased noticeably across the U.S., coincident with
notable decreases in the wet deposition of nitrate and sulfate since 1990, there are still
widespread areas, mainly in the eastern U.S. affected by acid precipitation. Deposition of
total nitrogen has not reflected the continuing decrease in NOx emissions, largely because
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emissions and concentrations of NH3 have increased in many areas. Large areas, at least
one-third of the CONUS are estimated to receive at least 10 kg/ha/yr wet + dry deposition
of reactive nitrogen species with some areas receiving more than 10 kg/ha yr. This
estimate is likely too low because reduced organic nitrogen species are not measured by
the routine monitoring networks or considered in air quality models such as CMAQ.
Since the last ISA for Oxides of Nitrogen and Sulfur, there have been a number of new
developments. They include methods, such as data-model fusion to integrate information
for deposition across the U.S.; the use of chemistry-transport models linking deposition to
ambient air quality; the expansion of CASTNET monitoring to include NH3 and NOy at
selected sites and intercomparisons of monitoring methods with research grade
instruments; and advances being made in satellite-based measurements in conjunction
with chemistry-transport model simulations of tropospheric NO2, SO2, and NH3 that will
allow mapping of dry deposition over remote areas with spatial resolution of
~10 km x 10 km. A number of intercomparisons between CASTNET measurements and
other instruments have been carried out. Comparison of CASTNET filter pack
measurements of SO2 with trace-level pulse fluorescence monitors (a Federal Equivalent
Method) indicate relatively good agreement on annual time scales.
Major sources of the precursors (NOx, SO2) to the formation of HNO3 and H2SO4 include
on- and off-highway vehicles and electricity-generating units (EGUs). Atmospheric
measurements made during recent field studies have been used to evaluate National
Emissions Inventory estimates. Results suggest that emissions of NOx are overestimated.
Although conducted in specific regions for limited periods of time, these studies
nonetheless raise concerns that overall source strengths may be overestimated in the NEI.
In contrast, anthropogenic emissions of SO2 are much better known because SO2 is
emitted mainly by large stationary sources that require continuous emissions monitoring
systems.
SO2 is oxidized to H2SO4 either in the gas phase by reaction with OH radicals or
stabilized Criegee bi-radicals, and in cloud water, primarily by either H2O2, O3, or O2 in
the presence of dissolved Fe(III). Reaction with H2O2 is most important at pH less than
about 5.3, and reaction with either dissolved O3, or with O2 catalyzed by Fe(III), becomes
most important at pH greater than about 5.3. NO2 is oxidized to HNO3 by reaction with
OH radicals in the gas phase or by reaction with NO3 radicals to form N2O5, which can
then undergo hydrolysis to yield HNO3. NH3 and HNO3 interact to form NH4NO3, which
depending on local conditions of temperature and humidity can exhibit semivolatile
behavior which in turn can substantially alter the distance over which NH3 and HNO3 can
travel. Reduced organic nitrogen species, which could have large agricultural sources can
constitute a substantial fraction of N delivered to ecosystems by precipitation. Although
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not measured in the routine monitoring networks, organic acids, most notably formic,
acetic, and oxalic acids can be major contributors to the acidity of rainwater in areas
where rainwater pH is greater than about 4.5.
The currently used chemiluminescent method of determining ambient NOx and then
reporting NO2 concentrations by subtraction of NO is subject to positive interference by
NO2 oxidation products, chiefly HNO3, PAN, and other oxidized N containing
compounds. However, measurements of these higher order oxidation products are sparse.
Within the urban core of metropolitan areas where many of the ambient monitors are
sited (i.e., near strong NOx sources such as motor vehicles on busy streets and highways),
these positive artifacts due to NO2 oxidation products are much smaller on a relative basis
(typically <10% of measured NO2) than outside the urban core. Conversely, the positive
artifacts are larger in locations more distant from NOx sources where NO2 concentrations
are lowest and can exceed 50% of measured NO2. Therefore, variable, positive artifacts
from measuring NO2 using the FRM severely hamper this method's ability to serve as an
accurate and precise indicator of NO2 concentrations at the typical ambient levels
generally encountered in areas outside of urban cores. These are the areas that are most
relevant for the environmental exposures of concern to a secondary NAAQS. However,
high sensitivity NOy monitors as deployed at several CASTNET sites are not subject to
these artifacts. Because NOy is composed of a large number of species characterized by a
wide range of deposition velocities and compensation points, regional models, perhaps in
conjunction with satellite data, must be used to provide information on component
species not measured at these sites and to provide information for the distributions of all
species in data-sparse areas.
A wide variety of N containing compounds, consisting of oxidized and reduced organic
and inorganic species contribute to wet and dry deposition. In general, deposition of
reduced (organic + inorganic) N exceeds that of oxidized N across the CONUS.
Nationwide, deposition of N species occurs mainly by dry deposition of HNO3 and NH3
according to estimates based on CASTNET and NADP data and CMAQ modeling
results. The pattern is more complex for S in that for large areas, mainly in the central
U.S., wet deposition tends to dominate over dry deposition. Dry deposition of particulate
S042 is a minor source of S to the surface, largely due to the low deposition velocities of
fine-mode particles.
Unlike the inferential models, which treat deposition by analogy to multiple resistances in
series, the eddy covariance technique measures fluxes directly. The eddy covariance
technique can be used on towers or aircraft, thereby extending the length scale of the flux
measurements. Issues in applying the eddy covariance technique to measurement of
HNO3 and NH3, which stick to inlet surfaces, are largely resolved by developing
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techniques to passivate inlet surfaces. However, care must be taken to insure that
conditions satisfying requirements for application of the eddy covariance technique are
met. Fast response measurement techniques are not yet available for many species, but
measurements of the species' vertical gradient coupled with measurements of the heat
flux by eddy correlation can be used in a semidirect approach. Unfortunately, these
approaches are too demanding of resources to be widely used in a nationwide network.
Estimates of dry deposition over the CONUS are inferred by atmospheric models, either
regional scale chemistry-transport models (CTMs) or local-scale micrometeorological
models using data collected at CASTNET sites. Although very useful, each model is
subject to its own set of uncertainties in the treatment of small-scale turbulence and
surface interactions. An intercomparison of two widely used micrometeorological models
for calculating dry deposition in North America (i.e., the Multi-layer Model [MLM] and
the Big Leaf Model [BLM]) found differences of factors of 2 to 3 in median hourly
deposition velocity using consistent meteorological inputs and site characterization
(e.g., vegetation type, leaf area index, canopy height, surface roughness). It is difficult to
judge which of the two models is the more accurate, although the MLM is newer than the
BLM and contains additional features, because these models are not evaluated by
comparison to direct flux measurements. As a result, dry deposition rates (and hence
ratios of wet to dry deposition) will continue to remain highly uncertain. The importance
of including bidirectional exchange into models for dry deposition is becoming apparent.
For example, excluding bidirectional exchange of NH3 led to much higher estimates of
dry deposition fluxes of NH3 in the Multi-Layer Model than when the exchange was
included.
Although orography certainly influences (open) wet deposition, wet deposition to the top
of a forest canopy, for example, does not depend directly on surface characteristics.
However, the distribution of deposition within the canopy depends strongly on
throughfall and stemflow. In contrast, the nature of the surface strongly influences dry
deposition because it affects the structure of the turbulence in the surface layer and the
resistance to uptake by surface vegetation. Thus, spatially aggregated estimates of dry
deposition fluxes are subject to considerable uncertainty that should be considered in
addition to inherent uncertainties in measuring species concentrations and in inferring dry
fluxes. Wet fluxes are subject to uncertainty in the measurement of rainfall and analytical
uncertainty in measurement of species. These sources of error are much smaller than
those affecting dry fluxes. However, artifacts during the collection period, storage and
transport that can influence concentrations of reactive N species, and presence of organic
acids need to be considered. Errors in spatial extrapolation of wet deposition
measurements need to be considered also.
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At Tampa Bay and some other NADP sites, dry fluxes are directed upward in CMAQ,
due to the implementation of bidirectional exchange of NH3. (However, the net flux of
NHx in CMAQ is still directed downward from wet deposition.) Bidirectional exchange
of other species, such as NO2, are not yet considered in CMAQ.
Because of the rural bias in the placement of monitoring sites in CASTNET,
concentrations of species that could be important for deposition (e.g., NO2, PAN), are not
measured in more populated areas, where their concentrations are likely to be highest.
However, CMAQ and OMI/GEOS-Chem modeling results indicate that dry deposition of
NO2 is a nontrivial source of N to the surface in many areas. For example, the 3-year
average contribution of NO2 (almost exclusively dry deposition) to total deposition of
oxidized nitrogen is typically several percent. In addition, regional scale variability in the
partitioning of pNO, between the fine and coarse modes of ambient PM results in
increased spatial variability and higher dry deposition fluxes of pNO, that may not be
appropriately accounted for in the measurement networks or in CTMs. Neither the wet
nor dry deposition networks monitor reduced organic nitrogen compounds, which consist
largely of biologically derived material and are estimated to contribute up to 30% of wet
N deposition.
Transport and mixing lead to some degree of association between concentrations and
deposition on the regional scale depending on the transport pathways leading to dry or
wet deposition of a particular species. The degree of association can be assessed using
CMAQ or other regional models. Output from regional model simulations have been
used to derive the ratio of wet and dry deposition of NOy and SOx to their ambient
concentrations. These ratios obtained as an annual average (i.e., transference ratios) are
then combined with measured ambient NOy and SOx, or if not available, model-derived
values. The transport processes described in Section 2 A imply that wet deposition should
not necessarily be well correlated with surface concentrations because of differences in
directions of transport in the boundary layer compared to cloud levels. Dry deposition
fluxes are more directly related to surface concentrations. However, bidirectional
exchange will modify the association between ambient concentrations and dry deposition
fluxes. In addition, these ratios have been shown to be strongly model dependent based
on comparison between calculation of the ratios by the CMAQ and CAMx modeling
platforms (R2 < 0.4 for NOy and <0.1 for SOx).
Background contributions to deposition of Nr over the CONUS are -20% overall, but
typically <30% over the eastern U.S. and typically 30 to 50% in the western U.S. (where
Nr deposition is already lower). For SOx, background contributions are typically <10%
overall but can be much higher in areas with geothermal activity, mainly in the Northwest
and on Hawaii.
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CHAPTER 3 DIRECT PHYTOTOXIC EFFECTS OF
GASEOUS OXIDIZED NITROGEN
AND SULFUR ON VEGETATION
This chapter provides a brief overview of the exposure and phytotoxic effects of gaseous
forms of oxidized nitrogen (N) and sulfur (S) compounds on vegetation. The purpose is
to recognize that the focus of this ISA is understanding the ecological impact of oxidized
N and S and that the major effects of these compounds on ecosystems are through
acidifying deposition and N deposition. However, direct effects of gaseous oxidized N
and S could augment the effects of deposition on vegetation, and direct effects of gaseous
N and S may be apparent in some areas. The effect of sulfur dioxide (SO2) gas on
vegetation is discussed in Section 32. Section 33 discusses nitric oxide (NO), nitrogen
dioxide (NO2), peroxyacetyl nitrate (PAN) effects on vegetation. Lastly, Section 3.4.
presents information on direct effects of HNO3 vapor on vegetation, including lichens. A
summary section with causal determinations based on a synthesis of the body of
information on the biological effects of exposure to these gases is presented in
Section 3.5.
3.1 Introduction
The effects of gaseous pollutants such as SO2, NO2, NO, HNO3, and ozone (O3) on
vegetation have been studied since at least the early 19th century (Holmes et al.. 1915;
Havwood. 1905). Methodologies have been developed to study the effects of gaseous
exposures to these pollutants in the lab, greenhouse, and in the field. The methodologies
to study the effects of gaseous pollutants on vegetation have been recently reviewed in
the 2013 Ozone ISA and 2006 Ozone AQCD [Air Quality Criteria Document (U.S. EPA.
2013c. 2006a)]. A thorough description of the methodologies used to expose vegetation
to gaseous pollutants can be found in Section 9.2 of the 2013 Ozone ISA (U.S. EPA.
2013c). AX9.1 of the 2006 Ozone AQCD (U.S. EPA. 2006a) and Section 9.2 in the 1993
Oxides of Nitrogen AQCD (U.S. EPA. 1993).
Uptake of gaseous pollutants in a vascular plant canopy is a complex process involving
adsorption to surfaces (leaves, stems, and soil) and absorption into leaves. These
pollutants penetrate into leaves primarily in gaseous forms through the stomata. The
surface cuticle provides a protective barrier to gaseous pollutant exposure, although there
is evidence for limited uptake across the cuticle (Zhang et al.. 2003; Kerstiens et al..
1992). Pollutants must be transported from the bulk air to the leaf boundary layer to reach
the stomata. The transport of pollutants through a boundary layer into the stomatal region
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is by diffusion. Studies of transport through the boundary layer are based on aerodynamic
concepts and usually relate to smooth surfaces that are not typical of leaf-surface
morphology (Gates. 1968). Once through the boundary layer, the gas enters the leaf
through the stomata. The entry of gases into a leaf is dependent upon gas-phase chemical
processes and physical characteristics of surfaces, including stomatal aperture. The
aperture of the stomata is controlled largely by the prevailing environmental conditions,
such as humidity, temperature, light intensity, and water availability. When the stomata
are closed, as occurs under dark or drought conditions, resistance to gas uptake is very
high and the plant has a very low degree of susceptibility to injury (Figure 3-1). The
stomatal control of uptake of gaseous pollutants is described in more detail in AX9.2 of
the 2006 Ozone AQCD (U.S. EPA. 2006a) and Section 9.3.1.5 of the 1993 Oxides of
Nitrogen AQCD (U.S. EPA. 1993). Note that unlike vascular plants, mosses and lichens
do not have a protective cuticle barrier to gaseous pollutants, which is a major reason for
their sensitivity to gaseous S and N.
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Light
03, N0X, S0X
Cuticle
Epidermis
Pallisade
Mesophyll
Spongy
Mesophyll
Epidermis
Cuticle
^^c, = [CQ^
Guard Cell
H20
c0= [C02]
*
Guard Cell
03, NOx, SOx
Vascular
System
Abbreviations: Ci = internal C02 in leaf; C0 = C02 of the atmospheric air; C02 = carbon dioxide; SOx = sulfur oxides; NOx = oxides of
nitrogen; 03 = ozone.
Figure 3-1 The microarchitecture of a dicot leaf. While details among species
vary, the general overview remains the same. Light that drives
photosynthesis generally falls upon the upper (adaxial) leaf
surface. Carbon dioxide, sulfur oxides, oxides of nitrogen, and
ozone gases generally enter by diffusion through the guard cells
(or stomata) on the lower (abaxial) leaf surface, while water vapor
exits through the stomata (transpiration).
3.2 Direct Phytotoxic Effects of Sulfur Dioxide on Vegetation
1 It has been known since the early 1900s that exposure to SO2 can cause plant damage and
2 death (Wislicenus. 1914). The large sources of historic SO2 emissions were ore smelters.
3 Sulfides m the ore were oxidized during smelting and resulted in large releases of SO2.
4 Emissions from large ore smelters in the U.S. and Canada resulted in large areas denuded
5 of vegetation surrounding these facilities (Thomas. 1951; Swain. 1949). Much of the
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damage to the vegetation was due to acute effects of high concentrations of SO2.
However, as early as 1923, researchers recognized that SO2 might decrease plant growth
without producing acute symptoms of foliar injury (Stoklasa. 1923). In the 1950s through
the early 1980s, there was much research on the effects of SO2 on vegetation, as well as
the interaction with pollutants such as O3 and NO2. Since then, there has been much less
research on the effects of SO2 on vegetation, especially in the U.S., due to the decreasing
ambient concentrations of SO2 (U.S. EPA. 2012a). The effects of SO2 on vegetation are
summarized below.
Currently, SO2 is the only criteria pollutant with a secondary NAAQS distinct from the
primary standard. This standard is to protect acute foliar injury resulting from SO2
exposure. The standard is a 3-hour average of 0.50 ppm and was promulgated in 1971 to
protect against the adverse effects of acute foliar injury in vegetation. The 1982 AQCD
for ecological effects of particulate matter and sulfur oxides concluded that controlled
experiments and field observations supported retaining this secondary standard (U.S.
EPA. 1982b. d. 1971).
Acute foliar injury usually occurs within hours of exposure, involves a rapid absorption
of a toxic dose and collapse or necrosis of plant tissues. Another type of visible injury is
termed chronic injury and is usually a result of variable SO2 exposures over the growing
season. After entering the leaf, SO2 is converted to sulfite (SO32 ) and bisulfite (HSO3 )
ions, which may be oxidized to sulfate (SO42 ). Sulfate is about 30 times less toxic than
sulfite and bisulfite. The conversion of sulfite and bisulfite to sulfate results in net H+
production in the cells. Kropff (1991) proposed that the appearance of SO2 induced leaf
injury was likely due to a disturbance of intra-cellular pH regulation. Kropff (1991)
pointed out several studies in which the pH of homogenates of leaf cells only shifted
towards greater acidity when plants were lethally damaged from long-term SO2
exposures (Jager and Klein. 1977; Grill. 1971; Thomas et al.. 1944). The appearance of
foliar injury can vary significantly among species and growth conditions (which affect
stomatal conductance). Currently, there is no regular monitoring for SO2 foliar injury
effects in the U.S.
Besides foliar injury, long-term lower SO2 concentrations can result in decreased
photosynthesis, growth, and yield of plants. These effects are cumulative over the
growing season and are often not associated with visible foliar injury. As with foliar
injury, the effects of these injuries vary among species and growing environment. The
1982 Particulate Matter and Oxides of Sulfur (PM-SOx) AQCD summarized the
concentration-response information available at the time (U.S. EPA. 1982b). Effects on
growth and yield of vegetation were associated with increased SO2 exposure
concentration and time of exposure. However, that document concluded that more
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definitive concentration-response studies were needed before useable exposure metrics
could be identified. Because of falling ambient SO2 concentrations and focus on O3
vegetation effects research, relatively few studies have emerged to better inform a metric
and levels of concern for effects of SO2 on growth and productivity of vegetation.
SO2 is considered to be the primary factor causing the death of lichens in many urban and
industrial areas, with fruticose lichens being more susceptible to SO2 than many foliose
and crustose species (Hutchinson etal.. 1996). Damage to lichens in response to SO2
exposure includes reduced photosynthesis and respiration, damage to the algal
component of the lichen, leakage of electrolytes, inhibition ofN fixation, reduced K+
absorption, and structural changes (Hutchinson et al.. 1996; Belnap et al.. 1993; Farmer et
al.. 1992). Significant reductions in lichen photosynthesis have been measured at
concentrations as low as 91 ppb over 2-4 hours (Sanz et al.. 1992; Huebert et al.. 1985).
Damage to the algal component of the thallus is evidenced by its discoloration. The entire
thallus dies soon after algal cells are damaged (Hutchinson et al.. 1996). At higher
concentrations, SO2 deactivates enzymes by chemical modification, leading to reduced
metabolic activity and loss of membrane integrity (Nieboer et al.. 1976; Ziegler. 1973). In
addition, SO2 binds to the central metal atoms of enzymes, adversely affecting membrane
function and cell osmolality. SO2 also competitively inhibits bicarbonate (HCO, ) and
dihydrogen phosphate (H2PO4 ) interactions with enzymes (Hutchinson et al.. 1996).
Low pH increases the toxicity of SO2 action (Farmer et al.. 1992). The toxic effects of
atmospheric deposition of SO2 are lessened when lichen are attached to a substrate,
typically bark or rock, that has high pH or superior buffering capacity (Richardson and
Cameron. 2004). van Herk (2001) evaluated relationships between bark pH and air
pollution levels as two significant variables affecting epiphytic lichen composition and
concluded that bark pH was the primary factor regulating the distribution of acidophilic
species in the Netherlands. In studies of unpolluted areas, differences in bark chemistry
also affect the presence and distribution of epiphytes (Farmer et al.. 1992). Indirect
changes to bark pH, caused by acidification and high SO2 concentrations, also affect
lichen distribution (Farmer et al.. 1992).
More recent research has been performed in areas of Europe where ambient SO2
concentrations are generally higher than in the U.S. Since the 2008 ISA, several studies
in Germany and some eastern European countries have indicated that direct effects of
SO2 caused growth reductions in trees in those countries during the last century (Cavlovic
et al.. 2015; Haiick et al.. 2012; Rvdval and Wilson. 2012; Elling et al.. 2009). Elling et
al. (2009) evaluated a large database providing long-term growth of 1,010 silver firs
(Abies alba) from 51 sites, long-term climate records, and long-term air pollution data in
southern Germany. In this analysis, silver fir growth was influenced by SO2 pollution
more than any other factor in the second half of the last century. They also reported an
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almost immediate increase in growth in response to falling SO2 emissions in the 1980s.
This rapid response indicates a direct effect of gaseous SO2 rather than an indirect effect
of soil acidification, which would have a longer response time. Annual average
concentrations above 10 p.g SCh/m3 (approximately 4 ppb) appeared to reduce growth of
silver fir. (See Figure 2-15 for recent concentrations in the continental U.S.). In a later
publication, Boselaetal. (2014) argued a combination of SO2 and NOx gas emissions has
historically reduced growth in silver fir in the western Carpathian Mountains of the
Czech Republic.
A similar gaseous SO2 effect on tree growth may have been occurring with trees in the
eastern U.S. Using tree ring analysis, Thomas et al. (2013) reported significant growth
increases in old-growth eastern redcedar (Juniperus virginiana) in West Virginia
following decreases in SO2 emissions since 1980. Growth continued to increase as SO2
emissions further declined in the 1990s and 2000s. Thomas et al. (2013) also found
evidence of physiological changes in response to SO2 emissions. The authors attributed
the growth response to an indirect effect decreasing acidifying deposition and thus,
recovery from soil acidification. However, a historical record of acidifying deposition
was not available. As in Europe, the trees studied in West Virginia also had a relatively
rapid recovery in response to declining SO2 emissions that could indicate the effects were
from direct exposure to gases in the atmosphere rather than soil acidification. Further, a
response to this study from other researchers pointed out that the eastern redcedars in the
West Virginia study were found on a limestone outcrop that could be well buffered from
soil acidification (Schaberg et al.. 2014V This study may indicate that gaseous SO2 alone
or in combination with other gases may have inhibited redcedar growth. See
Section 5.2.1.3 for further discussion of this study.
3.3 Direct Phytotoxic Effects of Nitric Oxide, Nitrogen Dioxide,
and Peroxyacetyl Nitrate
In sufficient concentrations, nitric oxide (NO) and nitrogen dioxide (NO2) can have
phytotoxic effects on plants by decreasing photosynthesis and inducing visible foliar
injury (U.S. EPA. 1993). The 1993 Oxides of Nitrogen AQCD concluded that
concentrations of NO2 or NO in the atmosphere are rarely high enough to have
phytotoxic effects on vegetation (U.S. EPA. 1993). Since the 1993 Oxides of Nitrogen
AQCD, very little new research has been done on these phytotoxic effects to alter this
conclusion (Bender and Weigel. 2011). However, it is known that these gases alter the N
cycle in some ecosystems, especially in the western U.S., and contribute to N saturation
(Sparks. 2009; Fenn et al.. 2003a; Bvtnerowicz and Fenn. 1996). See Section 6J_ for a
discussion of the nutrient effects of N.
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In general, NO and NO2 enters leaves through the stomata (Saxe. 1986). However, it has
also been shown that the leaf cuticle could be an important receptor for NO2, and there is
evidence of transport of NO and NO2 across isolated cuticles (Lcndzian and Kerstiens.
1988). Several studies have demonstrated that plant canopies can directly assimilate N in
the form of NO2, but canopy uptake of NO2 is generally small relative to total plant
uptake (Vallano and Sparks. 2008; Ammann et al.. 1995; Niissbaum et al.. 1993;
Segschneideretal.. 1993; von Ball moos et al.. 1993; Hanson et al.. 1989). After entering
the leaves, NO2 dissolves in the extracellular water of the substomatal cavity to form
HNO2 and HNO3, which then dissociate to form NO2 . NO3 . and H+ (Bvtnerowicz et al..
1998). Both cell and tonoplast membranes contain ATP-dependent H+ pumps and the
tonoplast pumps are strongly inhibited by NO3 (Bvtnerowicz et al.. 1998). If extra
protons are deposited in vacuoles of the plant cells during normal cellular regulation, then
additional acidity will occur in combination with additional NO3 . This combination can
cause disruptions in cellular control (Tavlor and MacLean. 1970). NO? and nitrite
(NO2 ) are metabolized to amino acids and proteins through a series of enzymatic
reactions mainly involving NO? and nitrite reductases (Amundson and MacLean. 1982).
The ability of plants to reduce NO3 and NO2 to amino acids and proteins determines the
potential of the plant to detoxify NO and NO2 (Wcllburn. 1990). Reduction of NO3 takes
place outside of the chloroplast while the reduction of NO2 is coupled with the light
reactions of photosynthesis. Therefore, when leaves are exposed to NO and NO2 in the
dark, highly phytotoxic levels of NO2 accumulate and may lead to greater toxicity to NO
and NO2 at night (Amundson and MacLean. 1982). Exposure to NO produces both NO?
and N02~ in the leaves, but the rate of NO? accumulation is much slower than NO2 .
Thus, plants exposed to high NO could be at risk to elevated concentrations of NO2
(Wcllburn. 1990). More detailed information on the cellular effects of NO and NO2 can
be found in the 1993 Oxides of Nitrogen AQCD.
The functional relationship between ambient concentrations of NO or NO2 and a specific
plant response, such as foliar injury or growth, is complex. Factors such as inherent rates
of stomatal conductance and detoxification mechanisms and external factors, including
plant water status, light, temperature, humidity, and the particular pollutant exposure
regime, all affect the amount of a pollutant needed to cause symptoms of foliar injury.
Plant age and growing conditions, and experimental exposure techniques also vary
widely among studies quantifying the response of plants to NO2. An analysis conducted
in the 1993 Oxides of Nitrogen AQCD of over 50 peer-reviewed reports on the effects of
NO2 on foliar injury indicated that plants are relatively resistant to NO2, especially
compared to foliar injury caused by exposure to O3 (U.S. EPA. 1993). With few
exceptions, visible injury has not been reported at concentrations below 0.20 ppm, and
these exceptions occurred when the cumulative duration of exposures extended to
100 hours or longer. At 0.25 ppm, increased leaf abscission was reported on navel orange
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trees (Citrus sinensis), but only after exposures in excess of 1,000 hours (Thompson et
aL 1970). Green bean (Phaseolus vulgaris) plants used as bioindicators of NO2 injury in
Israel developed foliar injury symptoms when ambient concentrations exceeded 0.5 ppm
(Donagi and Goren. 1979). In most plants, injury occurred in less than 1 day only when
concentrations exceeded 1 ppm (U.S. EPA. 1993). In recent years (2011-2013), ambient
hourly. NO2 concentrations in the U.S. have been well below the exposures in the above
studies with maximum highest 1-hour daily concentrations less than 0.075 ppm [see
Section 2.5.2 of U.S. EPA (2016b)l.
Decreased rates of photosynthesis have been recorded in experimental exposures of
plants to both NO and NO2, but usually at concentrations significantly higher than would
normally be encountered in ambient air. For example, Sabaratnam et al. (1988) reported
that soybeans (Glycine max) exposed 7 hours/day for 5 days showed an increase in
photosynthesis at a concentration of 0.2 ppm but a decrease in net photosynthesis at a
concentration of 0.5 ppm. Short-term exposures of soybean to 0.6 ppm NO2 for 2 to
3 hours also had no effect on net photosynthesis (Carlson. 1983). Most plants appear to
be more susceptible to NO than to NO2, as shown by Saxe (1986). who exposed a variety
of horticultural plants raised in greenhouses (species of Heciera. Ficus, Hibiscus,
Nephrolepis, and Dieffenbachia) to both NO and NO2. Saxe (1986) reported that
decreases in net photosynthesis occurred at doses of NO that were 22 times less than that
for NO2. However, these decreases in net photosynthesis required concentrations as high
as 1 ppm NO for 12 hours to elicit a response in these plants.
In the 1970s and 1980s, hundreds of studies were conducted on the effects of NO2 on
growth and yield of plants. These studies varied widely in plant species, growing
conditions, exposure equipment, concentrations, durations, exposure regimes, and
environmental conditions during exposures. No clear dose-response relationships for
exposure to NO2 and reductions in growth and/or yield of plants emerged from these
experiments. Readers are referred to the analysis of over 100 studies conducted in the
1993 Oxides of Nitrogen AQCD. A few key studies are highlighted in this section. The
growth of several plant species appears to be susceptible to concentrations of NO2 less
than 0.2 ppm, particularly when exposure occurs during low-light conditions. For
example, nearly continuous exposure to 0.1 ppm NO2 for 8 weeks significantly reduced
growth of Kentucky blue grass [Poa pratensis (Whitmore and Mansfield. 1983;
Ashenden. 1979)1. Eight species of tree seedlings were exposed to 0.1 ppm NO2 for
6 hours/day for 28 days, resulting in reduced shoot or root growth in two species, white
ash (Fraxinus americana) and sweetgum (Liquidambar styraciflua), reduced height
growth in two clones of loblolly pine (Pinus taeda), and no effects on the other species
(Kress and Skellv. 1982). No effects of NO2 at 0.1 ppm or lower were observed on
numerous other species, including potato (Solanum tuberosum), black poplar (Populus
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nigra), radish (Raphanus sativus), soybean, or peas [Pisum sativum (U.S. EPA. 1993)1.
No effects of NO2 were observed on soybeans grown in field plots subjected to a series of
10 episodic exposures averaging 0.4 ppm for 2.5 or 3 hours (Irving et al.. 1982).
Numerous studies have reported negative effects on growth of a variety of plants exposed
to 0.5 ppm NO2 and above (U.S. EPA. 1993). but these concentrations are very high
relative to current ambient levels of NO2 (see Section 2.6.1).
The 1993 Oxides of Nitrogen AQCD reviewed the extensive literature on the effects of
NO2 in combination with other gaseous air pollutants, particularly SO2 and O3, and
concluded that combinations of pollutants can cause foliar injury or decreases in
photosynthesis at concentrations lower than those associated with NO2 acting alone.
However, the plant responses occur at concentrations much higher than are typically
found in ambient air in the U.S. (U.S. EPA. 1993). In addition, the presence of in studies
combining other gases did not produce symptoms different from those caused by the
dominant pollutant, either SO2 or O3, such that a plant response produced by
combinations of NO2 with other air pollutants in the field would be difficult, if not
impossible, to distinguish from those of the other single pollutants (U.S. EPA. 1993).
Since the 1993 Oxides of Nitrogen AQCD was completed, most new research on NO2
exposure to vegetation has taken place in Europe and other areas outside the U.S. For
example, foliar NO3 reductase activity was increased in Norway spruce (Picea abies)
trees growing near a highway in Switzerland with average exposures of about 0.027 ppm
compared to trees growing 1,300 m away from the highway with NO2 exposures less than
0.005 ppm (Ammann et al.. 1995). This result was consistent with other studies on
Norway spruce in the field and laboratory (von Ball moos et al.. 1993; Thoene et al..
1991). Muller et al. (1996) found that the uptake rate of NO? by roots of Norway spruce
seedlings was decreased by the exposure to 0.1 ppm of NO2 for 48 hours. Similarly,
soybean plants grown in Australia had decreased NO3 uptake by roots and reduced
growth of plants exposed to 1.1 ppm of NO2 for 7 days (Qiao and Murray. 1998). In a
Swiss study, poplar (Populus x euramericana) cuttings exposed to 0.1 ppm of NO2 for
approximately 12 weeks resulted in decreased stomatal density and increased specific
leaf weight, but did not result in other effects such as leaf injury or a change in growth
(Giinthardtgoerg et al.. 1996). However, NO2 enhanced negative effects of ozone on
poplars, including leaf injury, when the pollutants were applied in combination
(Giinthardtgoerg et al.. 1996).
Since the 2008 ISA for Oxides of Nitrogen and Oxides of Sulfur- Ecological Criteria
[hereafter referred to as the 2008 ISA (U.S. EP A. 2008a)l. very few studies have been
published on the direct effects of NO and NO2 on vegetation. Hu et al. (2015b) exposed
clonal hybrid poplar (Populus alba it Populus berolinesis) saplings to 4 ppm of NO2. The
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authors reported significant declines in photosynthesis and dark respiration with
exposures of 48 hours. They also reported stomatal dysfunction at this level of exposure
resulting in partial stomatal closure and a decline in stomatal conductance. However,
4 ppm of NO2 is very high relative to current ambient levels of NO2 in the U.S. (see
Section 2.6.1). These results are consistent with past studies with relatively high NO2
exposure to plants.
As part of a broad study of N deposition of a native serpentine grassland in California,
Vallano et al. (2012) exposed five native grasses and forbs (Plantago erecta, Layia
gaillardioides, Lasthenia californica, Vulpia microstachys, and Cryptantha flaccida) and
the most common invasive grass Lolium multiflorum to NO2 and soil N addition. The
plants were exposed in a growth chamber to very low levels of NO2 (0.03 ppm) to
simulate recent ambient air concentrations for this ecosystem. At this relatively low NO2
exposure, no significant effects were found on shoot biomass, root biomass,
photosynthesis, or stomatal conductance. The authors reported that despite not finding
species responses to NO2 exposure, the additive effects of NO2 combined with soil N on
plant performance indicate that uptake of NO2 may play a role in species responses to
increasing N deposition. The authors found that the combined NO2 and N addition
resulted in a strong positive growth and competitive response in the invasive Lolium. This
result is consistent with previous findings that low levels of NO2 that are not phytotoxic
to plants can add to the N load to an ecosystem from uptake through leaves (Sparks.
2009).
Peroxyacetyl nitrate (PAN) is a well-known photochemical oxidant that often co-occurs
with O3 during high photochemical episodes and that has been shown to cause injury to
vegetation (See reviews by, Cape. 2003; Kleindienst. 1994; Temple and Tavlor. 1983).
Acute foliar injury symptoms resulting from exposure to PAN are generally characterized
as a glazing, bronzing, or silvering of the underside of the leaf surface; some sensitive
plant species include spinach, Swiss chard, lettuces, and tomatoes (Temple and Tavlor.
1983). Petunias (Petunia hybrida) have also been characterized as sensitive to PAN
exposures and have been used as bioindicators in areas of Japan (Nouchi etal.. 1984).
Controlled experiments have also shown significant negative effects on the net
photosynthesis and growth of petunia and kidney bean (Phaseolus vulgaris) after
exposure of 30 ppb of PAN for 4 hours on each of 3 alternate days (Cape. 2003; Izuta et
al.. 1993). As mentioned previously, it is known that oxides of N, including PAN, could
be altering the N cycle in some ecosystems, especially in the western U.S., and
contributing to N saturation (Fenn et al.. 2003a; Bvtnerowicz and Fenn. 1996). Although
PAN continues to persist as an important component of photochemical pollutant
episodes, there is little evidence in recent years to suggest that PAN poses a significant
risk to vegetation in the U.S.
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3.4
Direct Phytotoxic Effects of Nitric Acid
Relatively little is known about the direct effects of HNO3 vapor on vegetation. The
deposition velocity of HNO3 is very high compared to other pollutants (see Table 2-2)
and HNO3 may be an important source of N for plants (Hanson and Garten. 1992;
Hanson and Lindberg. 1991; Yose and Swank. 1990V This deposition could contribute to
N saturation of some ecosystems close to sources of photochemical smog (Fenn et al..
1998). For example, in mixed conifer forests of the Los Angeles basin mountain ranges,
HNO3 has been estimated to provide 60% of all dry deposited N (Bvtnerowicz et al..
1998). Since the 2008 ISA, a controlled exposure study (Padgett et al.. 2009a') reported
that 10 to 60% of the HNO3 retained by foliage was incorporated into the biologically
active N pool. The remainder of the HNO3 was bound to foliar surfaces. This new study
provides further evidence for HNO3 as a contributor of biologically available N to
southern California forests.
Norbv et al. (1989) reported that exposure of 75 ppb of HNO3 for 1 day increased nitrate
reductase activity in red spruce (Picea rubens) foliage. In another study, foliar nitrate
reductase activity was also increased in California black oak (Quercus kelloggi), canyon
live oak (Quercus chrysolepis), and ponderosa pine (Pinus ponderosa) seedlings with
exposure to 65 to 80 ppb of HNO3 for 24 hours (Krvwult and Bvtnerow icz. 1997).
Because the induction of nitrate reductase activity is a step in a process leading to the
formation of organic N compounds (amino acids), the nitrate from HNO3 could function
as an alternative source of N for vegetation (Calanni etal. 1999). However, in plants
under stress, the reduction of nitrate to amino acids consumes energy needed for other
metabolic processes.
At high ambient concentrations, HNO3 can cause vegetation damage. Seedlings of
ponderosa pine and California black oak subjected to short-term exposures from
50-250 ppb of HNO3 vapor for 12 hours showed deterioration of pine needle cuticle at
50 ppb in light (Bvtnerow icz et al.. 1998). Oak leaves appeared to be more resistant to
HNO3 vapor, however, with 12-hour exposures in the dark at 200 ppb producing damage
to the epicuticular wax structure (Bvtnerowicz et al.. 1998). The observed changes in wax
chemistry caused by HNO3 and accompanying injury to the leaf cuticle (Bvtnerow icz et
al.. 1998) may predispose plants to various environmental stresses such as drought,
pathogens, and other air pollutants. Because elevated concentrations of HNO3 and ozone
co-occur in photochemical smog (Solomon et al.. 1988). synergistic interactions between
the two pollutants are possible (Bvtnerow icz et al.. 1998). However, it should be noted
that the experiments described above were observed at relatively short-term exposures at
above ambient concentrations of HNO3. Studies of long-term effects of lower air
concentrations that more closely approximate ambient HNO3 are needed.
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Since the 2008 ISA, Padgett et al. (2009b) investigated dry deposition of HNO3 on the
foliage of ponderosa pine, white fir {Abies concolor), California black oak, and canyon
live oak that occur in southern California. Using a chamber system within a greenhouse,
leaves and needles were exposed to control (0 |_ig/m3 HNO3), moderate (30 to 60 (.ig/nr'
peak HNO3) and high (95 to 160 (ig/m3 peak HNO3) concentrations. The high
concentrations represented a high ambient concentration that occurs periodically in
California. The experimental exposures resulted in a suite of damage symptoms that
intensified with increasing exposure. The exposures caused substantial perturbations to
the epicuticular surfaces of foliage of all four tree species studied. The damage caused by
dry deposition may leave foliage more vulnerable to other copollutants such as ozone.
It has been suspected that HNO3 may have caused a dramatic decline in lichen species in
the Los Angeles basin (Nash and Sinai. 1999). The suggestion was strengthened by
transplant of Ramalina lichen species from clean air habitats (Mount Palomar and San
Nicolas Island) to analogous polluted habitats in the Los Angeles basin and observing
death of the lichens over a few weeks in the summer (Boonpragob and Nash. 1991).
Associated with this death was a massive accumulation of H+ and NO3 by the lichen
thalli (Boonpragob et al.. 1989). Riddel 1 et al. (2008) exposed healthy Ramalina menziesii
thalli to moderate (8-10 ppb) and high (10-14 ppb) HNO3 in month-long fumigations
and reported a significant decline in chlorophyll content and carbon exchange capacity
compared to thalli in control chambers. Thalli treated with HNO3 showed visual signs of
bleaching and by Day 28 were clearly damaged and dead. The damage may have
occurred through several mechanisms including acidification of pigments and cell
membrane damage (Riddell et al.. 2008). The authors concluded that Ramalina menziesii
has an unequivocally negative response to HNO3 concentrations common to ambient
summer conditions in the Los Angeles air basin. They believed it was very likely that
HNO3 contributed to the disappearance of this sensitive lichen species from the Los
Angeles air basin, as well as other locations with arid conditions with high HNO3
deposition loads (Riddell et al.. 2008).
Since the 2008 ISA, there have been more studies published on HNO3 effects on lichen in
the Los Angeles Basin. Riddell et al. (2012) studied six lichen species with differing
morphology and physiology that were collected near the Los Angeles Basin. All were
found to be sensitive to HNO3 exposures (daily peak levels near 50 ppb) in controlled
chambers. Measurements of effects included decreased chlorophyll content and
chlorophyll fluorescence, decreased photosynthesis and respiration, and increased
electrolyte leakage. The species showed differential sensitivity to the HNO3 exposures
(Riddell et al.. 2012). In the same study, lichens were not reported to be sensitive to
ozone exposure. This study adds to evidence that the main agent of decline of lichen in
the Los Angeles basin is HNO3 exposure.
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In another study, Riddel 1 etal. (2011) resampled 18 plots from a 1976-1977 study in the
Los Angeles basin. The 1976-1977 study (Sinai and Nash. 1983) had documented an air
pollution related 50% decline of lichens described and collected in the same region in the
early 1900s (Hasse. 1913). In the 2008 resampling, Riddel 1 et al. (2011) found
community shifts, declines in the most pollutant-sensitive lichen species, and increased
abundance of nitrogen-tolerant lichen species compared to 1976-1977. The authors also
reported that these lichen communities have not recovered from the damaged state of the
late 1970s and the 2008 survey data suggests that lichen communities are further
degrading. This recent observational field study further supports the evidence air
pollutants such as HNO3 may be causing declines in lichens in the Los Angeles basin.
3.5 Summary
3.5.1 Sulfur Dioxide
The current secondary standard for SO2 is a 3-hour average of 0.50 ppm, which is
designed to protect against acute foliar injury in vegetation. There has been limited
research on acute foliar injury since the 1982 PM-SOx AQCD, and there is no clear
evidence of acute foliar injury below the level of the current standard. The limited new
research since 2008 adds more evidence on acute effects of SO2 on vegetation, but does
not change conclusions from 2008 ISA on the levels producing effects.
Effects on growth and yield of vegetation are associated with increased SO2 exposure
concentration and time of exposure. The 1982 PM-SOx AQCD concluded that more
definitive concentration-response studies were needed before useable exposure metrics
could be identified. Very few studies have been reported on the effects of SO2 on growth
of U.S. vegetation since the 1982 PM-SOx AQCD. Recent studies from eastern Europe
indicate recovery of tree growth correlated to falling SO2 concentrations since the 1980s.
Elling et al. (2009) reported that annual SO2 concentrations of 4 ppb appeared to reduce
silver fir (Abies alba) growth. There may be similar effects of SO2 emissions on trees in
West Virginia (Thomas et al.. 2013). but more research is needed to further investigate
the mechanisms of the apparent recovery of tree growth in order to link this phenomenon
with declines in ambient SO2 that have occurred since the 1980s.
Limited new evidence from 2008 to the present continue to support the causal findings of
the 2008 ISA. As a whole, the body of evidence is sufficient to infer a causal
relationship between gas-phase SO2 and injury to vegetation.
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3.5.2
Nitrogen Oxide, Nitrogen Dioxide, and Peroxyacetyl Nitrate
It is well known that in sufficient concentrations, NO, NO2 and PAN (peroxyacetyl
nitrate) can have phytotoxic effects on plants through decreasing photosynthesis and
induction of visible foliar injury (U.S. EPA. 1993). However, the 1993 Oxides of
Nitrogen AQCD concluded that concentrations of NO, NO2, and PAN in the atmosphere
are rarely high enough to have phytotoxic effects on vegetation (U.S. EPA. 1993). Since
the 1993 Oxides of Nitrogen AQCD, very little new research has been performed on
these phytotoxic effects at concentrations currently observed in the U.S.
Since the 2008 ISA (U.S. EPA. 2008a'). very few studies have been published on the
direct effects of NO and NO2 on vegetation; thus, the body of evidence is sufficient to
infer a causal relationship between gas-phase NO, NO2, and PAN and injury to
vegetation.
3.5.3 Nitric Acid
The 2008 ISA reported experimental exposure of HNO3 resulted in damage to the leaf
cuticle of pine and oak seedlings which could predispose those plants to other stressors
such as drought, pathogens, and other air pollutants (U.S. EPA. 2008a'). Since the 2008
ISA, Padgett et al. (2009b) investigated dry deposition of HNO3 on the foliage, with
findings that supported the earlier research. The 2008 ISA also reported several lines of
evidence in lichen studies, including transplant and controlled exposure studies,
indicating that past and current HNO3 concentrations contributed to the decline in lichen
species in the Los Angeles basin (U.S. EPA. 2008a). Since the 2008 ISA, there have been
more exposure and field survey studies published on HNO3 effects on lichen in the Los
Angeles basin (Riddel 1 et al. 2012; Riddel 1 et al.. 2011). These new studies continue to
support the causal findings of the 2008 ISA. As a whole, the body of evidence is
sufficient to infer a causal relationship between gas-phase HNO3 and changes to
vegetation.
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CHAPTER 4
SOIL BIOGEOCHEMISTRY
This chapter characterizes how nitrogen (N) and sulfur (S) deposition contribute to total
loading of N and S in nonagricultural terrestrial ecosystems (Section 4.2). the effects of N
and S on soil pools and processes (Section 4.3). soil monitoring and databases
(Section 4.4). soil models (Section 4.5). national-scale soil sensitivity to N and S
deposition (Section 4.6). and summary (Section 4.7).
4.1 Introduction
The 2008 ISA for Oxides of Nitrogen and Oxides of Sulfur—Ecological Criteria
(hereafter referred to as the 2008 ISA) documented that the main effects of N and S
deposition on terrestrial soils were N enrichment and acidification. Since the 2008 ISA,
there is new evidence on how deposition contributes to total loading in ecosystems, as
well as the effects of deposition on soil pools and processes. This evidence is from
addition, gradient, and time-series studies. Much of the new work focuses on the effects
of N deposition, with relatively little work focusing on S deposition. There are improved
models to evaluate ecosystem responses to deposition; most of these models are
applicable at watershed scales, while some models may be applied regionally. Soil N
enrichment and soil acidification occur in sensitive ecosystems across the U.S. at present
levels of deposition. Decreasing emissions of S have led to early signs of recovery from
acidification in some northeastern watersheds; however, areas in the Southeast do not
show recovery. There are no signs of recovery of N enrichment effects. Critical loads
(CL) determinations for soils have been made at the ecoregion scale for NO;, leaching
and some soil acidification indicators. The body of evidence is sufficient to infer a
causal relationship between N and S deposition and alteration of soil
biogeochemistry in terrestrial ecosystems, which is consistent with the conclusions of
the 2008 ISA.
4.2 Nitrogen and Sulfur Sources to Soil
The 2008 ISA documented that atmospheric deposition is the main source of
anthropogenic N to nonagricultural terrestrial ecosystems and headwater streams. The
global pool of reactive N (Nr) increased over the past century, largely due to three main
causes: (1) widespread cultivation of legumes, rice, and other crops that support bacteria
capable of converting N2 gas to organic N through biological N fixation; (2) fossil fuel
combustion converting atmospheric N2 and fossil N to NOy; and (3) the Haber-Bosch
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process, which converts nonreactive N2 to Nr for N fertilizer production and some
industrial activities (Gallowav et al.. 2003; Gallowav and Cowling. 2002) . Food
production accounts for much of the conversion from N2 to Nr, and accounts for
geographic redistribution of N as food is shipped to meet population demands and often
returned to the environment via wastewater. Nr accumulates in the environment on local,
regional, and global scales (Gallowav et al.. 2003; Gallowav and Cowling. 2002;
Gallowav. 1998). This accumulation occurs in the atmosphere, soil, and water (Gallowav
and Cowling. 2002). with a multitude of effects on humans and ecosystems (Townsend et
al.. 2003; Rabalais. 2002; van Egmond et al.. 2002; Gallowav. 1998). The sequence of
transfers, transformations, and environmental effects is referred to as the "N cascade"
(Gallowav et al.. 2003; Gallowav and Cowling. 2002).
Although we were unable to identify any new studies on S sources to ecosystems, there
have been several new studies published since the 2008 ISA on the source of N inputs to
ecosystems. Sobota et al. (2013) quantified sources and fluxes of reactive N inputs to
U.S. lands and waterways and found human-mediated N inputs are spatially
heterogeneous across the country, ranging up to 34.6 times the background N input
across all of the 8-digit Hydrologic Unit Codes (HUC-8s). Across the contiguous U.S.
(CONUS), synthetic N fertilizer and atmospheric N deposition are the largest and
second-largest overall human-mediated N inputs to ecosystems, and the single largest
sources in 41% and 33% of HUC-8s, respectively (Figure 4-1 and Figure 4-2).
At the global scale, Fowler et al. (2013) estimated the relative contributions of five
sources of N that contribute to emissions and deposition, all of which are predicted to
change through the end of this century. Two new studies have confirmed that geologic N
from the weathering of sedimentary and metasedimentary rock can be a source of N to
some ecosystems (Montross et al.. 2013; Morford et al.. 2011). although Sobota etal.
(2013) suggest that anthropogenic sources of N are more significant at the landscape
scale.
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Largest human-mediated
N source
Synthetic fertilizer
Atmospheric N deposition
| Agricultural BNF
| Confined feedlot manure
| Centralized sewage
Most: Synthetic fertilizer (886 HUC-8s)
Least: Centralized sewage (32 HUC-8s)
8-digit USGS Hydrologi
USGS = U.S. Geologic Survey; HUC-8 = 8-digit Hydrologic Unit Code; N = nitrogen; BNF = biological nitrogen fixation.
Source: map presented in Sobota et al. f2013).
Figure 4-1 Dominant sources of nitrogen across the U.S. at 8-digit
Hydrologic Unit Codes.
Atmospheric N deposition, circa 2000
Proportion of total N input
N = nitrogen.
Source: modified from data presented in Sobota et al. (2013V
Figure 4-2 Percentage of nitrogen input from nitrogen deposition at 8-digit
Hydrologic Unit Codes.
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4.3
Soil Pools and Processes
Eutrophication and acidification are two biogeochemical processes that can occur from N
and S deposition. These processes can alter the biogeochemistry in terrestrial ecosystems
and they may occur either in sequence or simultaneously in a given geographic area. N
driven eutrophication is typically indicated by N accumulation (e.g., increased soil N
concentrations or decreased C:N ratios). These indicators of N accumulation are directly
linked to biological effects in the soil, including changes in microbial-mediated
decomposition and nitrification. N added to terrestrial ecosystems can also be lost
through leaching from the soil, typically as nitrate (NOs ), or through emissions to the
atmosphere, primarily via denitrification (Gallowav et al.. 2003; Gallowav and Cowling.
2002). Denitrification is a microbial process that reduces NOs, to either unreactive N2
gas, nitrogen oxide (NO), or the potent greenhouse gas nitrous oxide (N2O). S addition to
an ecosystem typically causes S accumulation and leaching from the soil, which in turn
leads to acidification because demand for S as a nutrient is low compared to soil stores of
organic and inorganic S.
Soil acidification results from the accumulation of hydrogen ions (H+) and occurs
naturally through the production of carbonic acid and organic acids, as well as plant
cation uptake (Charles and Christie. 1991; Turner et al.. 1991). However, NOy and SOx
air pollution increase the rate of soil acidification through the deposition of the inorganic
acids HNO3 and H2SO4. In addition, NHx deposition contributes to soil acidification by
stimulating nitrifying bacteria that derive energy by oxidizing the NH4+ to NO, . A
byproduct of nitrification is the production of an H+ ion, but whether there is a net effect
on soil acidity depends upon the fate of the NO3 . If the NO, is leached with a base
cation, then the H+ is left behind and the soil become more acidic. If, however, the NO,
is denitrified, then the H+ from nitrification is neutralized by OH generated by
denitrification. Likewise, if NO, is taken up by a plant root, the root will exude an OH
in exchange.
Decreases in soil pH attributable to acid deposition have been documented throughout the
U.S. (Sullivan et al.. 2006b; Bailey et al.. 2005; Johnson et al.. 1994b; Johnson et al..
1994a). Inorganic and organic acids can be neutralized by soil weathering or base cation
exchange in the soil. However, because soils vary in their capacity to neutralize incoming
acidity, the effects of acidification have been heterogeneous across the U.S. In addition,
pollutant loadings vary across the U.S. The primary effects of acidification in soils
include the loss of important base cation nutrients such as Ca and Mg, as well as the
mobilization of aluminum (Al3+) cations, which are toxic to many organisms. The loss of
base cations through leaching, a decrease in base saturation, and decreased soil solution
Ca:Al ratios all serve as indicators of soil acidification.
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1 Studies published since the 2008 ISA augment our knowledge of previously identified
2 effects of N addition on soils. The following sections document the empirical evidence of
3 N effects on multiple pools, processes, and indicators associated with the general effect
4 of N enrichment and eutrophication (Table 4-1). These sections summarize the empirical
5 effects of N and S addition on soil biogeochemistry, often from addition or gradient
6 studies. The publications present information on multiple processes and indicators so
7 individual papers are often discussed in more than one section.
Table 4-1 Summary of key soil geochemical processes and indicators
associated with eutrophication and acidification.
Endpoint
N-Driven Nutrient
Enrichment
Acidification
Section of ISA that Discusses
Each Endpoint
PROCESS
N saturation
X
X
4.3.2
Soil N accumulation
X
X
4.3.2
NO3" leaching
X
X
4.3.2
S accumulation and adsorption
X
4.3.3
SC>42"leaching
X
4.3.3
Base cation release/depletion
X
4.3.4
Al mobilization
X
4.3.5
Nitrification
X
X
4.3.6
Denitrifi cation
X
4.3.6
DOC leaching
X
X
4.3.9
Decomposition/mineralization
X
X
4.3.7 and 4.3.8
INDICATOR
Soil [N]
X
X
4.3.2
Soil C:N ratio
X
X
4.3.6 and 4.3.7
Soil base saturation
X
4.3.4
Soil BcAl ratio
X
4.3.5
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Table 4-1 (Continued): Summary of key soil geochemical processes and
indicators associated with eutrophication and
acidification.
N-Driven Nutrient
Section of ISA that Discusses
Endpoint
Enrichment
Acidification
Each Endpoint
Fungi-to-bacteria ratio
X
4.3.11
Al = aluminum; Be = base cation; C = carbon; DOC = dissolved organic carbon; ISA = Integrated Science Assessment;
N = nitrogen; N03" = nitrate; S = sulfur; S042" = sulfate.
4.3.1 Nitrogen Pathways and Pools
The 2008 ISA documented that N is stored primarily in the soil in forest ecosystems, and
soil N often exceeds 85% of the total ecosystem N (Cole and Rapp. 1981; Bormann et al..
1977). Experimental 15N-addition studies showed that trees typically take up only a small
fraction of added 15N; most is retained in the soil pool (Providoli et al.. 2005; Templeret
al.. 2005; Nadelhoffer et al.. 1999a; Tietema et al.. 1998). However, these experiments
were criticized for applying 15N directly to the soil surface, thereby precluding direct
canopy uptake of N from wet or dry deposition and limiting inference for N deposition
effects (Sievering et al.. 2000; Sievering. 1999). Forest canopies take up an average of
16% of total atmospheric N input (Lovett. 1992). but this uptake could be considerably
higher (up to 90%) in some N limited forests with large epiphyte loads (klopatek et al..
2006). It was unclear how much of the N from deposition retained by vegetation was
used in photosynthetic enzymes and would thus contribute to increased productivity
(Bauer etal. 2004).
Most soil N is contained in organic matter, typically bound in organo-mineral complexes
or large-molecular-weight organic compounds (Schmidt et al.. 2011; Schimel and
Bennett. 2004) These pools of N are not directly available for uptake by plants or
microbes, and the relative immobility of these compounds means they contribute less to
the leaching loss of N into ground or surface waters. To enter the actively cycling portion
of the ecosystem N pool, recalcitrant organic N must be converted into inorganic forms
(e.g., NC>3~, NH4+) or small-molecular-weight organic compounds (e.g., amino acids,
amino sugars), typically through the activity of extracellular enzymes produced by soil
microorganisms. The size of this N pool often controls net primary productivity (NPP;
see Chapter 6). but plants compete with microorganisms for this pool of available N.
Since 2008 there is new research using 15N to trace pathways and pools in ecosystems
(Table 4-2). including a new paper confirming the previous conclusion that ecosystem N
is primarily stored in forest mineral soil (Perakis et al.. 2011). There is also new evidence
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that litter is the largest sink for added N in grasslands, shrublands, and wetlands (Templer
et al.. 2012).
There are new studies tracing pathways of N in ecosystems through time. In Swiss
grasslands, N addition increased ecosystem N storage in plant biomass, both in living
plant biomass as well as litter, but did not affect soil N (Bassin et al.. 2015). In a
temperate forest ecosystem in Switzerland, application of 15N tracer in a solution to
simulate wet deposition showed increased dissolved organic N and enrichment of soil
microbes and plant roots within the first day. When plots were resampled a year later,
litter and soil pools, particularly soil organic matter, were enriched with the N tracer
(Morier et al.. 2008). These results confirm that deposited N is incorporated rapidly into
ecosystem pools and is stored primarily in litter and recalcitrant organic matter in the soil.
Table 4-2
Pathways and pools.
Process/
Type of Deposition
Addition
Reference
Indicator
Ecosystem Region (kg/ha/yr)
(kg/ha/yr)
Effect of Deposition
HERO ID
Pools and
Subalpine Alp Flix, a 4
0, 5, 10,
Plant N pools increased
Bassin et al.
pathway N
(seminatural) high
25, and 50
by 30-40% after N
(2015)
uptake
pasture plateau
as
addition, while soil pools
near Sur,
NH4NO3
remained unaffected
Grosons,
Switzerland
Not Not 5 as Model was developed Diikstra (2009)
specified specified NH4NO3 for N cycling using
observations of 15N. The
temporal dynamics of
15N fractions (labeled-N
fractions) in plant and
microbial biomass are
closely tied to the
turnover time of these N
pools
A meta-analysis of Templer et al
studies at 48 sites (2012)
across four continents.
The largest sinks for 15N
tracers among
ecosystem types were
organic soil in forests
(35.5%, n = 31) and
foliage in tundra (12.1%,
n = 3). While litter was
the largest sink in
grasslands (25.5%,
n = 9), shrublands
(33.8%, n =6), and
wetlands (34.1%, n =2).
N turnover times Semiarid
grassland
N pools Soil 15N Global Varied Varied
across 48 across 48
studies studies
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Table 4-2 (Continued): Pathways and pools.
Process/ Type of Deposition Addition
Indicator Ecosystem Region (kg/ha/yr) (kg/ha/yr)
Effect of Deposition
Reference
HERO ID
N pools Temperate Oregon
forest Coast
Range
2.0 None Mineral soil accounted
for 96-98% of total
ecosystem N. Soil water
15N03" patterns
suggested a shift in
relative N losses from
denitrification to NO3"
leaching as N
accumulated, and
simulations identified
NO3" leaching as the
primary N loss pathway
that constrains
maximum N
accumulation.
Perakis et al.
(2011)
N pools
Temperate
hardwood
forest
Swiss
Prealps
16
After 1 day, the litter
layer retained
approximately 19-28%
of the 15N tracer.
Authors concluded that
the processes relevant
for the fate of
atmospherically
deposited N take place
rapidly and that N
recycling within the
microbe-plant-soil
organic matter system
prevents further losses
in the long term.
Morier et al.
(2008)
N pools
Common Denmark
13 to 19 for
Tree species influenced
(Callesen et al..
garden
broadleaf
N cycling and 15N
2013)
experiment,
forest
patterns through
five
18 to 26 for
multiple species-specific
broadleaved
Norway
Spruce
traits. The type of
tree species
mycorrhiza association,
light climate, and
ground vegetation
differed between ash
and sycamore and
beech, lime, oak, and
Norway spruce.
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Table 4-2 (Continued): Pathways and pools.
Process/ Type of Deposition Addition
Indicator Ecosystem Region (kg/ha/yr) (kg/ha/yr)
Effect of Deposition
Reference
HERO ID
N pathway
Spruce
plantation
Hoglwald,
Bavaria,
Germany
45
Following two to three
decades of chronically
high loads of
atmospheric N
deposition, a new
equilibrium was
reached, characterized
by substantial losses of
N to the groundwater
(approximately 20 kg
NO3") and to the
atmosphere (16 kg N in
form of N2O, NO, and
N2). Ecosystem N
retention is dominated
by microbial
immobilization, which
was about a factor of
three higher than plant
N uptake.
Kreutzer et al.
(2009)
15N = Nitrogen-15; N = nitrogen; NO = nitric oxide; N20 = nitrous oxide; N02 = nitrogen dioxide, N03 = nitrate;
15N03" = Nitrogen-15-labeled nitrate; NH4NO3 = ammonium nitrate; yr = year.
4.3.2 Nitrogen Accumulation, Saturation, and Leaching
In the 2008 ISA, a documented indicator of terrestrial N driven eutrophication was the
accumulation of N in soils. Atmospherically deposited N can accumulate in soil as
inorganic N or by incorporating N into organic matter. The ability of atmospheric N
pollution to cause an accumulation of N in soil is indicated by a positive correlation
between atmospheric deposition rates and total N concentration in the Oa soil horizon
observed at sites in New York, Vermont, New Hampshire, and Maine (Driscoll et al..
2001b). Accumulation of soil N as a result of N deposition has been either documented or
suggested to occur across large areas of the U.S. (Aber et al.. 2003). There is also
evidence for soil N accumulation from mass-balance studies of experimental N additions
(Campbell et al.. 2004b'). Further evidence that atmospheric deposition increased the
availability of N in soil is provided by the strong negative correlation between
atmospheric N deposition and the decreasing C:N ratio of the Oa soil horizon across the
northeastern U.S. (Aber etal.. 2003). Soil N accumulation is linked to increased N
leaching and decreased N retention.
New studies (Table 4-3) confirm that, across terrestrial ecosystem types, N addition
increases soil concentrations. For instance, Lu et al. (2011a) conducted a meta-analysis of
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N cycle responses to N additions using data from 206 peer-reviewed studies and observed
a mean increase in inorganic soil NOs concentrations of 429% (inorganic soil NO3 .
429%). In semiarid shrublands in southern California, Vourlitis and Fernandez (2012)
observed that N additions increased soil N.
Thresholds between N deposition and the onset of elevated leaching have been previously
identified. Atmospheric deposition of 8 to 10 kg N/ha/yr resulted in the onset of NO3
leaching to waters in the eastern U.S. Slightly lower N deposition levels (5-10 kg
N/ha/yr) led to NO3 leaching in the Rocky Mountains due to colder temperatures, shorter
growing season, slow soil development, extensive exposed bedrock, and rapid melting of
large snowpacks (Williams and Tonnessen. 2000; Williams et al.. 1996c; Baron etal..
1994). Lastly, deposition loads of 17 kg N/ha/yr led to the onset of NO3 leaching in the
Sierra Nevada and San Bernardino mountains.
The 2008 ISA documented that N saturation occurred when the input of N to the
terrestrial ecosystem exceeds the uptake capacity of the soils and biota, causing a large
fraction of the incoming N to leach from soils to surface waters (Stoddard. 1994; Aberet
al.. 1989). N saturation had been observed or suggested to occur across large areas of the
U.S. (Adams et al.. 2000; Aber et al.. 1998; Adams et al.. 1997; Peteriohn et al.. 1996;
Cook et al.. 1994; Edwards and Helvev. 1991; Aber etal.. 1989).
New evidence (Table 4-3) from an N tracer study confirms N retention varies across
ecosystem types and is highest in shrublands (89.5%) and wetlands (84.8%), followed by
forests (74.9%), and grasslands [51.8%; (Tempter et al.. 2012)1. Other significant factors
affecting long-term 15N recovery (a proxy for N retention in N tracer studies) were
mycorrhizal association (ericoid > ecto- > arbuscular), plant growth form, and site history
(less retention on former agricultural sites). Where 15N tracer studies were conducted as
part of N addition experiments, the N additions decreased 15N retention. In 15N studies
with multiple N addition treatments, there was a negative correlation between retention
and the rate of N additions. The influence of biotic processes on N retention is also
evident at smaller scales. Among nine forested sites along an urban-to-rural landscape
gradient in the Boston, Massachusetts area, throughfall inorganic N deposition increased
with proximity to the urban core, with inorganic N deposition rates positively correlated
with rates of soil inorganic N leaching across the sites (Rao et al.. 2014). Measurements
of S15N and 8180 in the soil leachate NO3 indicated no clear relationship between
microbial nitrification and proximity to the urban core—evidence that factors other than
N availability influenced N processing. Overall, it is clear from recent research that N
retention is strongly influenced by biotic factors (e.g., mycorrhizae, plant growth form,
ecosystem) and environmental conditions (e.g., precipitation), while ecosystems
experiencing high rates of added N tend to retain less N. In Europe, Disc et al. (2009)
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documents approximately 95% of forests receiving less than 8 kg N/ha/yr still have
leaching, typically less than 1 kg N/ha/yr. Additional work on monitoring data in Sweden
by khalili et al. (2010) showed a clear sudden increase in NCh leaching in regions where
N deposition exceeded 7.5 kg/ha/yr (Section 4.4).
N leaching is an indicator of ecosystem N saturation. New work (Table 4-3) suggests
revising the N saturation concept (Aber et al.. 1998) in response to observations of N
cycling in temperate forests (Lovett and Goodale. 2011) and chaparral (Homvak et al..
2014). Lovett and Goodale (2011) proposed a model of N saturation that distinguished
capacity N saturation, in which the vegetation and soil sinks for N have been filled, from
kinetic N saturation, in which the plant and soil sinks are accumulating N, but the rate of
N accumulation is slower than the N input rate. One implication of this new model is that
N03 leaching occurs even if the ecosystem N retention capacity has not yet been
saturated, as is observed at many sites (e.g., Homvak et al.. 2014; Talhelm et al.. 2012;
Lovett and Goodale. 2011). New information confirms the applicability of the capacity N
saturation concept in Northwest forests (Perakis and Sinkhorn. 2011). although the new
idea of kinetic N saturation is particularly useful in describing N cycling processes in
California chaparral (Homvak et al.. 2014). At chaparral sites N added during the dry
season is lost from the ecosystem, while N added during the growing season is retained in
plant biomass (Vourlitis and Pasquini. 2009; Grulke et al.. 2005). In these systems, water
scarcity limits plant productivity, microbial C availability, and denitrification, all of
which cause NO, to be flushed from surface soils in large precipitation events (Menonet
al.. 2010). Large leaching losses of N in arid ecosystems which do not indicate N demand
by biota are evidence for kinetic saturation.
New research identifies the role of microbial community in N saturation. Kopacek et al.
(2013) developed a conceptual model that asserts N saturation is associated with shifts in
the microbial community, namely a decrease in the fungi-to-bacteria ratio, and a
transition from N to C limitation. In N enriched systems, three mechanisms could lead to
lower amounts of bioavailable dissolved organic C (DOC) for the microbial community
and to C limitation: (1) lower plant allocation to roots in response to increased nutrient
availability, leading to a decrease in plant exudates; (2) chemical suppression of DOC
solubility by soil acidification; and (3) enhanced bacterial mineralization of DOC due to
increased abundance of electron acceptors in the form of NO3 in anoxic soil. In support
of this model, recent studies indicate that N retention in semiarid shrublands is driven
more by spatial and temporal variations in labile C availability than exceedance of N
storage capacity (Vourlitis and Fernandez. 2015). Furthermore, Hogberg et al. (2013)
found that forest soils with low concentrations of NO;, and Al3+ had a higher fungi:
bacteria ratio compared with stands with higher concentrations of NO;, and Al (negative
correlation, r = -0.857). Fungi: bacteria ratio, and a second indicator, stem growth,
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explained 70% of the variation in N and A1 leaching (see broader discussion of N effects
on microbial community composition in Chapter 6).
Foliar N
N Mineralization
200
NPP
100
CnrAl And
Mg:N Ratios
Nitrification
1
2
3
0
Stage
N = nitrogen; NPP = net primary productivity; Ca = calcium; Al = aluminum; Mg = magnesium.
Source: Aber et al. (1998).
Figure 4-3 Hypothesized temporal patterns of response of forest ecosystem
properties to continuing nitrogen additions.
Hogberg et al. (2013) propose a hypothetical model to account for the effects of N supply
on plant N uptake and belowground C allocation, microbial production of inorganic N,
and N leaching (Figure 4-4). Shifts in N mineralization, nitrification, and leaching from
forests might occur in response to N loading as a result of decreasing tree allocation of C
to belowground roots, and ultimately, to ectomycorrhizal fungi and other C limited soil
microbes. When N supply increases, ectomycorrhizal fungi and other rhizosphere
microbes become progressively more C limited, and their abundance and activity decline.
Microbial assimilation of N diminishes, and N mineralization increases, whereas the
fungi: bacteria ratio decreases. Increasing ammonium levels and decreasing organic C
supply both stimulate autotrophic nitrification, nitrate leaching, and denitrification.
Increasing N loading can alter plant C allocation, causing shifts in microbial activity and
community composition that in turn increase NO;, leaching from the ecosystem (Figure
4-4).
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f§ supply to plant® and microbes
Decreasing increasing
Plant N
uptake
X- -s
Below-
N teaching
C = carbon; N = nitrogen.
Thick arrows indicate an increasing rate whereas thin arrows mean decreasing rate. Nitrogen supply increases are indicated by
black arrows.
Source: (Hoaberg et al.. 2013).
Figure 4-4 A hypothetical model to account for the effects of nitrogen supply
on plant nitrogen uptake and belowground carbon allocation,
microbial production of inorganic nitrogen, and nitrogen leaching.
Table 4-3 Nitrogen accumulation, saturation, and leaching.
Process/
Indicator
Type of
Ecosystem
Region
Deposition
(kg/ha/yr)
Addition
(kg/ha/yr)
Reference
Effect of Deposition HERO ID
N export
Forest
Ontario,
Canada
Not reported Not applicable
Isotope: ROS, as it
passes through the
ecosystem, has a
higher concentration
of NOs"
(throughfall/snowmelt
average = 498 pg/L)
compared with
baseflow
(average = 7.3 |jg/L;
average = 41 pg/L)
and as a result,
throughfall and
snowmelt contribute
the majority of NO3" N
export
(average = 62%)
during ROS events
Casson et
al.
(2014b)
February 2017
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Table 4-3 (Continued): Nitrogen accumulation, saturation, and leaching.
Process/
Type of
Deposition
Addition
Reference
Indicator
Ecosystem
Region
(kg/ha/yr)
(kg/ha/yr)
Effect of Deposition
HERO ID
N leaching
48 sites
Global
Varied across
Varied across
Meta-analysis: of
Templer et
across four
48 studies
48 studies
studies at 48 sites
al. (2012)
continents
across four
Grassland,
continents. The
Forest,
greatest recoveries of
Wetland,
ecosystem 15N tracer
Shrubland
occurred in
shrublands (mean,
89.5%) and wetlands
(84.8%) followed by
forests (74.9%) and
grasslands (51.8%)
N leaching
Forest
248 sites (plot Varied
Not reported Gradient: The most
and
consistent indicators
catchment
of N leaching were
scale) from 15
throughfall N
countries in
deposition, organic
northern,
horizon C:N ratio, and
eastern, and
mean annual
central
temperature. Sites
Europe
receiving low levels of
N deposition
(8 kg N/ha/yr) showed
very low output fluxes
of N. In general, the
models successfully
predicted N leaching
(mean
of ±5 kg N/ha/yr
between observed
and predicted) from
forests at early to
intermediate stages of
N saturation but not
from N saturated sites
Pise et al.
(2009)
Soil N, C:N
Chaparral and
CSS
shrublands
Southern
California
6-8.1
56 to 58 Addition: In this
6-year field
experiment, chaparral
and CSS are found to
have the capacity to
immobilize 6.2 and
11.9 g N/m2/yr,
respectively.
Vourlitis
and
Fernandez
(2012)
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Table 4-3 (Continued): Nitrogen accumulation, saturation, and leaching.
Process/
Indicator
Type of
Ecosystem
Region
Deposition
(kg/ha/yr)
Addition
(kg/ha/yr)
Effect of Deposition
Reference
HERO ID
Soil extractable N
increased significantly
after 7-10 g/m2 of
cumulative N
exposure, resulting in
a simultaneous
increase in the N
concentration and a
decline in the C:N
ratio of shrub tissue.
Similar results were
observed for the
surface litter pool and
litter production but at
a higher cumulative N
exposure.
N
accumulation
Semiarid
chaparral and
CSS
Santa
Margarita
Ecological
Reserve and
the Sky Oaks
Field Station.
6 to 8
50
Vourlitis
and
Fernandez
Addition: N
enrichment
significantly increased
N accumulation but (2015)
not microbial
respiration.
Net primary
productivity/
aboveground:
large
herbivores
biomass
Boreal and
temperate
forest
Global
0.5 to 10
Studies
included one
site of up to
90
Synthesis:
Increasing N
deposition shifts
producer nutrient
composition towards
highertissue N:P and
lower tissue C:N
ratios. Herbivores
feeding on these
primary producers
generally benefit from
this change.
However, primary
consumers shift from
large to small insects,
from cladocerans to
copepods, and from
trichopterans to
chironomids and
gastropods; these
changes could have a
negative effect on a
number of secondary
consumers, such as
birds and fish.
Meunier et
al. (2016)
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Table 4-3 (Continued): Nitrogen accumulation, saturation, and leaching.
Process/
Indicator
Type of
Ecosystem
Region
Deposition
(kg/ha/yr)
Addition
(kg/ha/yr)
Effect of Deposition
Reference
HERO ID
N saturation/ Forest
White
6.6 to 6.7 N
Not applicable Isotope: There was
nh4+, no3- ,
Mountains
8.1 to 8.5
no significant
total inorganic
National
SO42"
biological production
N, and
Forest,
of NO3" via
so42"-s
Crawford
nitrification in the
Notch, NH;
canopy. NO3"
Lye Brook, VT
concentrations in
in southern
streams were low and
Green
had natural 1sO
Mountain
abundances
National
consistent with
Forest
microbial production,
Templer et
al. (2015b)
demonstrating that
atmospheric N is
being biologically
transformed while
moving through these
watersheds and that
these forested
watersheds are
unlikely to be N
saturated.
N saturation
Oak forest
Southeastern 9
100 NH4NO3
Conceptual Model:
Lovett and
New York
(1996-1999)
50 NH4NO3
(2000-2006)
of N saturation based
Goodale
State, U.S.
on an N addition
study of an oak forest
in southeastern New
York State, U.S.
(2011)
N saturation
None
(theoretical)
None
(theoretical)
Not specified None
Conceptual Model:
N addition alleviates
N limitation, and
together with SO42"
deposition, causes
soil acidification and
increases availability
of electron acceptors
for soil microbial
processes. Increasing
N and SO42"
decreases fungal
biomass, increases
bacterial DOC
mineralization, and
decreases DOC
leaching.
Kopacek
et al.
(2013)
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Table 4-3 (Continued): Nitrogen accumulation, saturation, and leaching.
Process/
Indicator
Type of
Ecosystem
Region
Deposition
(kg/ha/yr)
Addition
(kg/ha/yr)
Reference
Effect of Deposition HERO ID
Soil [NO3-]
Soil [Al]
Fungi-to-
bacteria ratio
19 Picea South
abies (L.) Sweden
Karst. Stands
Throughfall N
includes wet
and dry inputs
and ranged
from 2.7 to 19
Ammonium
NOs" at 20
Addition: Microbial
community
composition in the
organic horizon and
soil solution chemistry
below the rooting
zone was highly
correlated. Stands
with low
concentrations of
NO3" and Al had
higher fungi-bacteria
ratio compared with
stands with higher
concentrations of
NO3" and Al.
Microbial community
composition in the soil
was more closely
related to the soil
solution than to the
soil chemistry. Study
found a significant
negative correlation
between the
fungi-bacteria ratio in
the soil and NO3" and
Al in soil solution
(r= -0.533 and
-0.857, respectively).
Hoqberq
et al.
(2013)
N saturation
N
accumulation
N
mineralization
nitrification
Douglas-fir
forest
Oregon Coast
Range
2.0
and
Sinkhorn
(2011)
None Gradient: test of the Perakis
N saturation theory
along a natural N
gradient. Higher N
content of surface
(0-10 cm) soil was
linearly related to
higher net N
mineralization. Lower
pH was related to
lower nitrification. The
ratio of netgross N
mineralization to
higher nitrification
increased along the
gradient, indicating
progressive saturation
of microbial N
demands.
February 2017
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Table 4-3 (Continued): Nitrogen accumulation, saturation, and leaching.
Process/
Indicator
Type of
Ecosystem
Region
Deposition
(kg/ha/yr)
Addition
(kg/ha/yr)
Reference
Effect of Deposition HERO ID
N leaching
Douglas-fir
forest
Oregon Coast 2.0
Range
None Gradient: Hydrologic Perakis
N losses were and
dominated by Sinkhorn
dissolved organic N at (2011)
low-N sites, with
increased nitrate loss
causing a shift to
dominance by nitrate
at high-N sites,
particularly where net
nitrification exceeded
plant N demands.
N
accumulation
N leaching
Mesic desert
Spanish
Spring Valley,
Nevada
Not specified None
Field Experiment:
Assessed factors
contributing to NO3"
accumulation in mesic
desert vadose zones.
Concluded that soil
resources (water and
organic C) are rare.
Leaching events are
the primary factors
that lead to
accumulation of NO3"
in this region. Unused
NO3" from low
biological demand is
transported and
accumulated in the
deeper vadose zone
with occasional deep
leaching events.
Menon et
al. (2010)
NO3 leaching
Urban
gradient
Urban sites
12.3 and
nonurban 5.7
Gradient: Five of
nine sites had
N03"leached that
came almost entirely
from nitrification,
indicating that the
NCVin leachate came
from biological
processes rather than
directly passing
through the soil. A
significant proportion
(17-100%) of
NCVIeached from the
other four sites came
directly from the
atmosphere.
Rao et al.
(2014)
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18
19
20
Table 4-3 (Continued): Nitrogen accumulation, saturation, and leaching.
Process/
Indicator
Type of
Ecosystem
Region
Deposition
(kg/ha/yr)
Addition
(kg/ha/yr)
Reference
Effect of Deposition HERO ID
Decomposition Deciduous
forests
Catskills
Mountains of
southeastern
New York,
U.S.
9.0
50 (NH4NO3)
N addition: NO3"
leaching increased
markedly in response
to the N addition in all
species, indicating
that the addition rate
of N exceeded the N
retention capacity of
vegetation and soils
in these plots.
Lovett et
al. (2013)
Al = aluminum; C = carbon; cm = centimeter; CSS = coastal sage scrub; DOC = dissolved organic carbon; g= gram; ha = hectare;
kg = kilogram; L = liter; m = meter; N = nitrogen; NH4+ = ammonium; N03" = nitrate; P = phosphorus; NH4NO3 = ammonium nitrate;
r = correlation coefficient; ROS = rain-on-snow; S042" = sulfate; yr = year.
4.3.3 Sulfate Accumulation, Adsorption, and Leaching
The 2008 ISA showed that SOx deposition may be assimilated by vegetation or microbes,
accumulate in the soil, or act as a mobile ion and leach out of the soil to aquatic
ecosystems. Plant demand for S is typically low, particularly in comparison to the large
pools of S stored in the soil in recalcitrant, organic compounds; consequently almost all S
deposited in terrestrial ecosystems enters soil rather than plant pools. At many locations
in the U.S. that receive high levels of S deposition, notably the glaciated Northeast and
Upper Midwest, much of the deposited S leaches through soils into streams and lakes.
The physical process of charge balance pairs sulfate (SO42 ) leaching with leaching of
countercharged base cations from the soil matrix, and this process contributes to
acidification of soil, soil water, and surface water. As the base cations become depleted in
the soil matrix, charge balance in the soil is maintained by an increase in acidic cations
(H+ and inorganic Al), sometimes resulting in toxic conditions for plant roots and aquatic
organisms (Charles and Christie. 1991; Turner et al.. 1991).
In the 2008 ISA, regional trends of SO42 soil accumulation and leaching were identified
in the U.S. In the Southeast, accumulation of atmospherically deposited S in soil resulted
from S042 adsorption to soil particles as well as incorporation of S into soil organic
matter through biological assimilation. Accumulated S is slowly released from soil pools
into drainage water, and this process can temporarily delay ecosystem recovery in
response to decreases in S deposition (Sullivan et al.. 2004; Elwood et al.. 1991; Turner
et al.. 1991). In the Northeast, there was a demonstrated accumulation of S deposition in
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soil (Driscoll et al.. 2001a). Two new studies on SO42 accumulation, leaching, and
adsorption are described below (Table 4-4).
The net loss of S from soils is occurring in a number of northeastern watersheds in
response to decreased levels of atmospheric S deposition. In a new study evaluating
watersheds in the Northeast, Mitchell and Likens (2011) calculate that the annual
discrepancies in the watershed S budgets (SO42 flux in drainage waters minus total
atmospheric S deposition) have become more negative, indicating the increasing
importance of the release of S from internal ecosystem sources. The release of S from
forest soils is controlled (57%) by water flux and soil moisture. In the southeastern U.S.,
Rice et al. (2014) calculated SO42 mass balances for 27 forested, unglaciated watersheds
from Pennsylvania to Georgia by using total atmospheric deposition (wet plus dry) as
input. Unlike their counterparts in the northeastern U.S. and southern Canada, many of
these watersheds still retain SO42 . Rice et al. (2014) predicted that many of the
watersheds in the study will begin releasing SO42 over the next two decades. The
specific years when the watersheds cross over from retaining to releasing SO42
correspond to a general geographical pattern from north to south of later net watershed
release. For instance, the three watersheds in West Virginia have crossover years that
ranged from 2006 to 2011, and crossover years for five of the watersheds in Virginia
range from 2012 to 2021. The runoff ratio, computed as the ratio of annual mean
discharge to annual mean precipitation, was the single best watershed-scale predictor of
the crossover year (r2 = 0.72). Watersheds with higher runoff ratio tend to convert sooner
from net retention to net release of SO42 Rice et al. (2014).
Table 4-4 Sulfate adsorption and leaching.
Process/ Type of
Indicator Ecosystem
Deposition Addition
Region (kg/ha/yr) (kg/ha/yr) Effect of Deposition
Reference
HERO ID
Sulfate
Upland forests, Athabasca oil Not
low-lying areas sands region specified
and wetlands. (AOSR) in
None Coarse-textured soils in Jung et al.
adsorption
Cation
leaching
Alberta,
Canada
the AOSR are sensitive (2011)
to acidification because
of their low cation
exchange capacity and
thus low buffering
capacity. SO42"
adsorption capacity was
relatively low (50 to 500
mg S042"/kg) in both
watersheds as compared
to other acid-sensitive
soils in eastern North
America.
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Table 4-4 (Continued): Sulfate adsorption and leaching.
Process/ Type of Deposition Addition
Indicator Ecosystem Region (kg/ha/yr) (kg/ha/yr)
Effect of Deposition
Reference
HERO ID
S budget Varied
15 sites
southeastern
Canada and
northeastern
U.S.
-0.1 to 14
Long-term Deposition:
The net annual fluxes of
SO42" showed a strong
relationship with
hydrology; the sensitivity
of S budgets is likely to
be greatest in
watersheds with the
greatest wetland area,
which are particularly
sensitive to drying and
wetting cycles.
Mitchell et al.
(2011)
Sulfate Forest HBEF in the ~7 to 20 None Long-term Deposition: Mitchell and
accumulation White S released from internal Likens (2011)
and leaching Mountains of sources is increasing
New overtime. Watershed
Hampshire wetness, as a function of
Iog10 annual water flux
explained 57% (n = 157)
of the annual variation for
four watersheds. The
biogeochemical control of
annual SO42" export in
streamwater of forested
watersheds has shifted
from atmospheric S
deposition to climatic
factors by affecting soil
moisture.
SO42" Watersheds 27 forested, Not None Long-term Deposition: Rice et al.
leaching ranging from unglaciated specified Calculated SC>42"mass (2014)
Pennsylvania watersheds balances for 27
to Georgia watersheds showed that
over the next two
decades, many of the
study's watersheds will
begin releasing
S042"The single most
important variable that
explained the crossover
year was the runoff ratio,
defined as the ratio of
annual mean stream
discharge to
precipitation.
AOSR = Athabasca oil sands region; S042" = sulfate; kg = kilogram; HBEF = Hubbard Brook Experimental Forest; S = sulfur;
yr = year.
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28
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32
33
34
4.3.4
Base Cations
In the 2008 ISA, it was known that acidifying deposition decreases concentrations of
exchangeable base cations in soil because the deposition accelerates natural rates of
base-cation leaching (Lawrence et al.. 1999; Cronanetal.. 1978). Base cations are
essential plant nutrients and the loss of exchangeable base cations from the soil may have
adverse effects on flora. When SO42 and NO3 leaching occur in equal magnitude to base
cation leaching, the drainage water is not acidified. However, in the process of
neutralizing the acidity of drainage water, base cation release from soil causes depletion
of the base saturation of the soil. Soil base saturation expresses the concentration of
exchangeable bases (Ca, Mg, potassium [K], sodium [Na]) as a percent of the total cation
exchange capacity (which includes exchangeable H+ and inorganic Al).
Under conditions of low soil base saturation (<20%) and elevated concentrations of
strong acid anions, Al is mobilized from soil to drainage water (Cronan and Schofield.
1990; Reuss. 1983). with potentially harmful consequences for sensitive terrestrial plants
and aquatic organisms throughout the food web. Leaching of base cations associated with
acidifying deposition was documented in sensitive regions in the U.S. including the
Adirondack Mountains, New England, Catskill Mountains, and northwestern
Pennsylvania (U.S. EPA. 2008a). Base cation loss increases the sensitivity of the
watershed to further acidifying deposition. Watersheds that were capable of fully
neutralizing a particular level of acidifying deposition in the past may no longer be
capable of fully neutralizing that level today or in the future due to the cumulative effect
of acidifying deposition on soil base saturation.
New publications further support findings from the 2008 ISA that N and S deposition
cause base cation depletion from soils (Table 4-5). In the Rocky Mountains, Lieb et al.
(2011) observed that soil acid buffering capacity decreased as N inputs increased (40%
decrease at highest N input). An acidification threshold is calculated for significant loss
of soil acid buffering capacity of around 28 kg N/ha/yr. Base cation depletion was shown
to increase with N addition over a 10-year period in grasslands located one of the most N
and acid rain polluted regions of the U.K., leading to a loss of 23% to 35% of total
available bases (Ca2+, Mg2+, K+, and Na+) from the soil and acidifying it by 0.2 to 0.4 pH
units (Horswill et al.. 2008). In one eastern U.S. forest, long-term trends in base cation
depletion at Bear Brook watershed, ME, showed N addition over a 17-year time period
(while S deposition was simultaneously decreasing) resulted in little evidence of
continued soil exchangeable base cation concentration depletion or recovery [expected
because of decreasing S deposition (SanClements et al.. 2010)1. Two field studies in
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2
international locations, Italy and Mongolia, further confirm that N deposition/N addition
lowers soil pH and decreases base cations (Chen et al.. 2015; Ferretti et al.. 2014V
3 A meta-analysis of 107 studies found N addition alters the availability of base cations in
4 terrestrial and aquatic ecosystems (Lucas etal.. 2011): although short-term N and S
5 deposition cause base cation depletion, long-term trends across all studies are unclear and
6 may be affected by confounding disturbances. Evaluating the strength of these results is
7 difficult because they are based on averages from various biome types and there are few
8 long-term studies.
Table 4-5 Base cations.
Process/ Type of Deposition Addition Reference
Indicator Ecosystem Region (kg/ha/yr) (kg/ha/yr) Effect of Deposition HERO ID
pH Forest soils Italy 4.5 to 28.8 Not Gradient: Exchangeable Ferretti et
Base cations throughfall applicable base cations and pH al. (2014)
N (NO3" + decreased with increasing N
NH4+) deposition, and foliar nutrient
N ratios (especially N:P and
N:K) increased. Comparison
between bulk openfield and
throughfall data suggested
possible canopy uptake of N,
levelling out for bulk
deposition >4-6 kg/ha/yr.
pH Semiarid Mongolia Not
30jl |\| grassland specified
Base cations
Fungi:bacteria
ratio
Belowground
biomass
Microbial
community
Structure
0, 17.5, 52.5, Addition: Soil pH decreased Chen et al.
105.0,175, across the N addition (2015)
and 280 gradient by 0.3-1.8 units in
NH4NO3 2010 and by 0.1-1.7 units in
fertilizer 2011. Decreased
concentrations of mineral
cations Ca2+, Mg2+, and Na+
were observed. The
observed increases in
above- and belowground
biomass and changes in
plant community structure
were mainly (57-69%)
attributed to the increase in
soil N availability and
changes in soil base cations.
N addition increased the
fungi:bacteria ratio by
5-18% in 2010 and by
2-10% in 2011.
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Table 4-5 (Continued): Base cations.
Process/
Indicator
Type of
Ecosystem
Region
Deposition
(kg/ha/yr)
Addition
(kg/ha/yr)
Effect of Deposition
Reference
HERO ID
Base cation
depletion
Critical Load
Forest Niwot 8 to 15 20,40,60 Addition: Soil acid buffering
stands with Ridge in capacity decreased with
mature white southern increasing N inputs (40%
ash Rocky decrease at highest input),
Mountains and was associated with a
decrease in pH, loss of
extractable Mg2+ and
increases in Mn and Al3+.
The threshold at which
acidification occurred was
around 28 kg N//ha/yr.
Lieb et al.
(2011)
Base cation
depletion
Soil pH
Soil [Al], [Fe],
[Mg]
Grasslands
Peak
District
National
Park,
England,
Not
specified
Plots treated
for 8 to 10
years with
0, 35, or 140
as NH4NO3
Addition: treatments Horswill et
caused the grassland soils al. (2008)
to lose 23 to 35% of their
total available bases (Ca2+,
Mg2+, K+, and Na+), and they
became acidified by 0.2 to
0.4 pH units. Al, Fe, and Mn
were mobilized and taken up
by limestone grassland forbs
and were translocated down
the acid grassland soil.
Mineral N availability
increased in both grasslands
and many species showed
foliar N enrichment. N
deposition depletes base
cations from grassland soils.
Base cation
Boreal
107 sites
Not
Median N
Meta-analysis of 107
Lucas et al.
depletion
forest,
globally
specified
addition
independent studies to
(2011)
temperate
across the
determine if N fertilization
forest,
studies was
alters the availability of base
tropical
38, and 71%
cations (BC) in terrestrial
forest, and
of the
and stream ecosystems.
grassland
studies
Results suggest N
added 70 or
fertilization may accelerate
less
BC loss from terrestrial
ecosystems overtime
periods less than five years.
Base cation
Hardwood
Eastern
28.8 S and
Addition: Compared treated
SanClemen
depletion
forest
U.S., Bear
25.2 as
and untreated watersheds
ts et al.
Book
(NH4)2S04
within the system after N
(2010)
watershed,
and S manipulation over a
Maine
17-year time period. Found
little evidence of continued
soil exchangeable base
cation concentration
depletion or recovery,
possibly because a 1998 ice
storm increased litterfall and
accelerated mineralization,
obscuring temporal trends in
soil chemistry.
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Table 4-5 (Continued): Base cations.
Process/
Indicator
Type of
Ecosystem
Region
Deposition
(kg/ha/yr)
Addition
(kg/ha/yr)
Effect of Deposition
Reference
HERO ID
Base cation Jack pine Athabasca Not 30 N, 30 S Addition: No evidence of N
leaching (Pinus oil sands specified (2006 saturation in the studied
banksiana) region forAOSR through forest ecosystem after 4 yr
and aspen (AOSR), 2009) of N and S additions. No
(Populus Alberta, long-term increase of
tremuloides) Canada inorganic N concentrations
in upland in the soil; leaching of N
forests and beyond the main rooting
black spruce zone in the soil profile was
(Picea minimal, and tree growth
mariana) in was increased by N addition,
low-lying all indications of N limitation
areas and in the studied forest stand,
wetlands. However, exchangeable
Ca2+ and Mg2+
concentrations in the surface
mineral soil layer were found
to be reduced by N and S
additions because of
increased cation leaching
associated with increased
SO42" leaching caused by S
addition and increased
nutrient uptake associated
with increased tree growth
resulting from N addition.
Jung and
Chang
(2012)
Al = aluminum; AOSR = Athabasca oil sands region; BC = base cations; BCE = exchangeable base cations; Ca2+ = calcium;
Fe = iron; g = gram; ha = hectare; K+ = potassium; kg = kilogram; m = meter; Mg2+ = magnesium; N = nitrogen; Na+ = sodium;
NH4+ = ammonium; NH4NO3 = ammonium nitrate; (NH4)2S04 = ammonium sulfate; N03 = nitrate; S = sulfur; S042" = sulfate;
yr = year.
4.3.5 Aluminum
The 2008 ISA documented that when soil base saturation is 15 to 20% or lower,
acidifying deposition can mobilize inorganic Al, which can lead to the leaching into soil
solution and into surface waters (Cronan and Schofield. 1990; Reuss and Johnson. 1985;
Reuss. 1983). This is an extremely important effect of acidifying deposition because
some forms of inorganic monomeric Al, including Al3+ and various hydroxide species,
are toxic to tree roots, fish, algae, and aquatic invertebrates (Chapter 5 and Chapter 8).
Increased concentrations of exchangeable inorganic Al in the soil have been identified
through repeated sampling in the U.S. and Europe over periods ranging from 17 to
41 years in studies by Billett et al. (1990). Falkengren-Grerup and Eriksson (1990).
Bailey et al. (2005). and Lawrence et al. (1995).
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Base saturation values less than 10% predominate in the soil B-horizon in the areas in the
U.S. where soil and surface water acidification from acidifying deposition have been
most pronounced, including conifer and hardwood forests in the Adirondack Mountains
(Sullivan et al.. 2006b'). red spruce forests throughout the Northeast (David and
Lawrence. 1996). hardwood forests in the Allegheny Plateau (Bailey et al.. 2004). and
conifer and hardwood forests in the southern Appalachian Mountains (Sullivan et al..
2003). In a study of sugar maple decline throughout the Northeast, Bailey et al. (2004)
found threshold relationships between base cation availability in the upper B soil horizon
and sugar maple mortality at Ca saturation less than 2%, and Mg saturation less than
0.5% (Bailey et al.. 2004). The authors concluded that base saturation varied as a function
of topography, geologic parent material, and acidifying deposition.
The negative effect of Al mobilization on Ca uptake by tree roots was proposed by
Shortle and Smith (1988). Substantial evidence of this relationship has accumulated
through field studies (Kobe et al.. 2002; Minocha et al.. 1997; Shortle et al.. 1997;
McLaughlin and Tioelker. 1992; Schlegel etal. 1992) and laboratory studies (Cronan
and Grigal. 1995; Sverdrup and WarfVinge. 1993). These studies make clear that high
inorganic Al concentration in soil water can be toxic to plant roots. The toxic response is
often related to the concentration of inorganic Al relative to the concentration of Ca,
expressed as the molar ratio of Cato inorganic Al in soil solution. From an exhaustive
literature review, Cronan and Grigal (1995) estimated a 50% risk of adverse effects on
tree growth if the molar ratio of Ca to Al in soil solution was as low as 1.0. They
estimated a 100% risk for adverse effects on growth at a molar ratio value below 0.2 in
soil solution and minimal to no risk is thought to occur at <10.
In this review, no new studies have been identified on aluminum leaching nor calcium to
aluminum ratio in soils.
4.3.6 Nitrification and Denitrification
The 2008 ISA documented that nitrification is the microbial oxidation of ammonia or
ammonium to form nitrite followed by the oxidation of the nitrite to NO.? . The oxidation
of ammonia into nitrite is performed by two groups of organisms,
ammonia-oxidizing bacteria and ammonia-oxidizing archaea. The rate of nitrification is
controlled by numerous factors, including substrate availability (presence of NH44"),
aeration (availability of O2), well-drained soils with <60% soil moisture, and pH (near
neutral). N addition may increase nitrification, which is often stimulated in soils with a
C:N ratio below about 20 to 25 (Ross et al.. 2004; Aber et al.. 2003). The microbial
process of autotrophic nitrification is an acidifying process, releasing 2 moles of
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hydrogen ion (H ) per mole NH4 converted to NO? (Reuss and Johnson. 1986). As the
N cycle becomes enriched through cumulative N addition, N becomes more abundant,
competition among organisms for N decreases, net nitrification rates often increase, and
N03 can leach from the soil (Aber et al.. 2003; Aber et al.. 1989V
Soils with a C:N ratio below about 20 to 25 is associated with stimulated mineralization,
nitrification, and cation leaching (Ross et al.. 2004; Aber et al.. 2003). This observation
makes the C:N ratio an especially useful field measurement that provides a relative index
rather than a quantitative rate of N leaching (Ross et al.. 2004). C:N ratios in the forest
floor are inversely related to acidifying deposition levels, although the relationship is
stronger for hardwood stands than conifer stands (Aber et al.. 2003). The C:N ratio a
reliable and relatively straightforward measure for identifying forest ecosystems that may
be experiencing soil acidification and base leaching as a result of N input and increased
nitrification.
The 2008 ISA documented that denitrification is the microbial process that transforms
N03 by anaerobically reducing it to nitrite (NO2 ), nitric oxide (NO), the greenhouse gas
nitrous oxide (N2O) and N2. In terrestrial ecosystems, denitrification mainly occurs in
soils, groundwater, and riparian zones. Soil pH has a marked effect on denitrification,
with lower rates in acidic than alkaline conditions (Yamulki et al.. 1997). Soil
denitrification and N2O production and consumption are extremely variable in time and
space (McClain et al.. 2003).
New information published since 2008 is summarized in Table 4-6. Several new
syntheses evaluate N addition effects on denitrification and nitrification in terrestrial
ecosystems (Bouwman et al.. 2013; Luetal.. 2011a; Liu and Greaver. 2009). Globally,
denitrification removes more N from terrestrial ecosystems than from groundwater or
riparian zones (Bouwman et al.. 2013). Liu and Greaver (2009) show that N addition
significantly increased denitrification from all ecosystems tested (coniferous forest,
deciduous forest, tropical forest, wetland, grassland) except heathland. Among the five
chemical forms of N fertilizer added to ecosystems in studies, NO3 showed the strongest
stimulation of N2O emission (Figure 4-5). Lu et al. (2011a) further confirm that N
addition stimulates nitrification and denitrification (Figure 4-6). Using data extracted
from 206 peer-reviewed papers, the meta-analysis showed that among the largest changes
caused by N addition in the ecosystem N cycle were increased nitrification (154%),
nitrous oxide emission (134%), and denitrification (84%).
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(a) aii
Mean (155)
-//
(b) Vegetation
Agriculture (aerobic) (33)
Agriculture (anaerobic) (IB) I—
Oooitefous (33) I—*
Deciduous (15) |—
Tropical forest (11)
Wfelland (19) I—
Grassland (IB)
Heathland (3)
(c) W form
NH4M03 (44)
NH,* (23)
NO," {24)
Urea (32)
UAfJ (23)
(d) Experimental length
Short term (61)
Long term {90)
(e) N addition level
<55 (35)
55-150(20)
>150 (51)
I—*
V>r-
3 4 5 6 7 6 9 15 18 20
Response ratio
N = nitrogen; NH4N03 = ammonium nitrate; NH4+ = ammonium; N03 = nitrate; UAN = urea and ammonium nitrate fertilizer.
The data are expressed as the mean response ratio with 95% confident intervals. The numbers of studies included are indicated in
parentheses.
Source: Liu and Greaver (2009).
Figure 4-5 Effects of nitrogen addition on biogenic nitrous oxide emission.
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a
Leaf N
Aboveground plant N
Belowg round plant N
Litter N
Microbial N
Organic horizon N
Soil N
DON
Soil inorganic N
N mineralization
Immobilization
Nitrification
Denitrification
Leaching ¦
0.0 0.4 0.8 1.2 1.6 2.0
Weighted response ratio (RFL,.)
N = nitrogen; N20 = nitrous oxide; RR = response ratio.
Bars represent RR++ ± SE. The vertical line is drawn at logeRR = 0. The sample size for each variable is shown next to the bar.
Source: Lu et al. (2011a).
Figure 4-6 The weighted response ratio for the responses to nitrogen
addition for fluxes and pools related to the ecosystem nitrogen
cycle in agricultural (open bars) and nonagricultural (closed bars)
ecosystems.
1 New empirical work on an N deposition gradient in Oregon found that nitrification
2 increased with increasing N deposition (Pcrakis and Sinkhorn. 2011); likewise,
3 denitrification increased with N deposition in northeastern forests (Morse et al.. 2015a).
4 In a deposition exclusion study in Europe, after two decades of deposition exclusion, net
5 nitrification and NO;, concentration in soils were not detectible, and in fact, the soil
6 switched from a net source of NOy to a next sink (Eickcnscheidt and Brumme. 2012).
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1 There is a growing body of information that increased N deposition also alters the soil
2 microbial community (Frccdman et al.. 2013). Additional discussion is provided in
3 Chapter 6. Marusenko et al. (2013) explore the role of fungi in NO? and N2O production
4 in soils from regions across the southwestern U.S. and found fungi are significant sources
5 of N2O production in soils in semiarid grasslands and deserts. High soil organic matter is
6 associated with increased rates of nitrification in forest watersheds in North America,
7 Europe, and Japan (Mitchell. 2011). However, Russow et al. (2008) found that soils with
8 high soil organic matter adsorbed added NH/, making it difficult to determine microbial
9 activity.
Table 4-6 Nitrification and denitrification.
Ambient N/S N/S
Process Type of Deposition Addition Reference
Endpoint Ecosystem Region (kg/ha/yr) (kg/ha/yr) Effect of Deposition HERO ID
Nitrification Deciduous and Ontario, 3 sites along Not Gradient: N gas flux Morse et al
denitrification coniferous Canada, a gradient: applicable increased (2015a)
forests New 4.5, 7, and 11 systematically with
Hampshire; natural N enrichment
and Maine from soils with high
nitrification rates.
Results suggest that N
gas fluxes are linked to
patterns of N
availability in forests,
they do not suggest
that these fluxes
respond to increases in
atmospheric N
deposition at the study
sites.
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Table 4-6 (Continued): Nitrification and denitrification.
Process
Endpoint
Type of
Ecosystem
Region
Ambient N/S
Deposition
(kg/ha/yr)
N/S
Addition
(kg/ha/yr)
Effect of Deposition
Reference
HERO ID
Nitrification
Mixed
hardwood
forested
headwater
catchments
South-
central
Ontario,
Canada
Average NO3
N deposition
2.78 ± 1.22;
average NH4
N deposition
3.90 ± 1.39
Not Time Series: seasonal Casson et al.
applicable differences in (2014a)
nitrification were
largely driven by
temperature, soil
moisture, and
inorganic N
concentration in soil.
Annual nitrification
fluxes were almost two
orders of magnitude
greater than N
deposition or NO3"
leaching. Nitrification
rates scaled up to
annual
catchment-scale
production of NO3"; the
resulting fluxes are
64.9 ± 8.7 and
59.7 ± 3.1 kg N/ha/yr,
which greatly exceed
seasonal inputs in
deposition.
Rates of nitrification
and mineralization
were similar, indicating
that almost all
mineralized N is
converted to NO3" N in
both soil types (ranging
from 71 to 99%).
Nitrification
Common
garden
experiment,
five
broadleaved
tree species
Denmark
13 to 19 for
broadleaf
forest;
18 to 26 for
Norway
spruce
Litter 815N and 15N
enrichment factor
(615Nlitter - 815Nsoil)
were positively
correlated with N
status based on
nitrification, as well as
other factors. Linear
relationship between
fungal mycelia
production vs. net
nitrification rate in lab
incubations from soils
collected in the field.
(Callesen et
al.. 2013)
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Table 4-6 (Continued): Nitrification and denitrification.
Process
Endpoint
Type of
Ecosystem
Region
Ambient N/S
Deposition
(kg/ha/yr)
N/S
Addition
(kg/ha/yr)
Effect of Deposition
Reference
HERO ID
Nitrification
Spruce
plantation
Hoglwald,
Bavaria,
Germany
30
(two decades)
None Time-series: Highly
dynamic internal N
cycle within the soil,
driven by growth and
death of the microbial
biomass, which turns
over approximately
seven times each year.
Although input and
output fluxes are of
high environmental
significance, they are
low compared to the
internal fluxes
mediated by microbial
activity.
Kreutzer et al.
(2009)
Denitrification Northern HBEF, 6 to 8 None Method Comparison:
hardwood White Both isotopic tracer
forest Mountain and gas-flow soil core
National method indicate that
Forest, denitrification is higher
New and N20:N2 ratios are
Hampshire lower (< 0.02) than
previously thought in
the northern hardwood
forest and that
short-term abiotic and
biotic transformations
of atmospheric N
deposition to gas are
significant in this
ecosystem.
Kulkarni et al.
(2014)
Denitrification
Agricultural
crop, forest,
grassland,
wetland,
tundra,
heathland, and
desert
Global
Not specified 10 to 562
Liu and
G re aver
Meta-analysis:
Analysis of 313
observations across all (2009)
ecosystems show N
addition increased N2O
emission by 216%.
Denitrification Forested Pond 10 ±4 None Isotopic tracer:
watershed Branch in Spatial and temporal
Maryland, extrapolations of
U.S. measured rates
suggest that a
minimum of 16-27% of
atmospheric N
deposition is lost to
denitrification.
Duncan et al.
(2013)
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Table 4-6 (Continued): Nitrification and denitrification.
Process
Endpoint
Type of
Ecosystem
Region
Ambient N/S
Deposition
(kg/ha/yr)
N/S
Addition
(kg/ha/yr)
Effect of Deposition
Reference
HERO ID
Nitrification Agriculture and Not Mean = 105
Denitrification nonagriculture. specified Tg N/yr
0 to > 100 Meta-analysis of 206
papers for responses
of 15 variables
associated with
ecosystem N cycle
caused by N addition.
Increases in
nitrification (154%),
N2O emission (134%),
and denitrification
(84%) were found.
Increased N2O
emissions and N
leaching under N
addition tended to
export the N out of the
systems rather than
benefit plant uptake
over the long term,
suggesting a leaky
terrestrial N system.
Lu et al.
(2011a)
Fungal
nitrification and
denitrification
Semiarid
grasslands
Arizona and
New
Mexico
Not specified
10 g soil to
a 100 mL
solution of
50 mmol/L
(NH4)2S04,
0.2 mol/L
K2HPO4,
and 0.2
mol/L
KH2PO4,
with a pH of
7.2.
Moisture X biocide:
Fungi are significant
sources of N2O
production in soils from
semiarid grasslands
and deserts,
expanding evidence in
support of that fungi
play a vital role in the
N cycle of arid lands.
Marusenko et
al. (2013)
Denitrification Agricultural
land and
natural
ecosystems
Global 24 to 46 Tg Not Model: N2 production
N/yr from applicable from denitrification
1900-2050. increased from 52 to
96 Tg/yr between 1900
and 2000, and N2O
emissions increased
from 10 to 12 Tg N/yr.
The scenarios foresee
a further increase to
142 Tg N2 and
16 Tg N20-N/yr by
2050. Riparian buffer
zones are an important
source of N2O,
contributing an
estimated
0.9 Tg N20-N/yr in
2000.
Bouwman et
al. (2013)
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Table 4-6 (Continued): Nitrification and denitrification.
Process
Endpoint
Type of
Ecosystem
Region
Ambient N/S
Deposition
(kg/ha/yr)
N/S
Addition
(kg/ha/yr)
Effect of Deposition
Reference
HERO ID
Nitrification
and
denitrification
Agricultural
black earth
soils (haplic
chernozem);
two sites: high
and normal
SOM
Central
Germany
Not specified
81.3
(KNOs,
Ca(N03)2);
80 kg
(NH4)2S04
Isotopic tracer:
Addition of 15N
revealed denitrification
of NO3" represents the
main pathway of soil
N2O release. On
average, 76% and
54% of N2O was
emitted during
denitrification from
soils with high and
normal SOM content,
respectively.
Denitrification
contributed, on
average, only 17% and
12% of released NO
from soil with high and
normal SOM content,
respectively.
Russow et al.
(2008)
Nitrification
and
denitrification
Microbial
community
Sugar maple
dominated
northern
hardwood
forest
Upper
Michigan
15 to 20
30 kg N in
the form of
NaNOs
pellets
delivered to
the forest
floor over
the growing
season
Addition: NO3"
addition to forest
stands across a
500-km climatic
gradient decreased the
abundance and
richness of key
protein-coding genes
in archaea and
bacteria responsible
for N fixation,
ammonifi cation,
denitrification, and
assimilatory NO3"
reduction; the same
was true for bacterial
genes mediating
nitrification and
dissimilatory NO3"
reduction.
Freedman et
al. (2013)
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Table 4-6 (Continued): Nitrification and denitrification.
Process
Endpoint
Type of
Ecosystem
Region
Ambient N/S
Deposition
(kg/ha/yr)
N/S
Addition
(kg/ha/yr)
Effect of Deposition
Reference
HERO ID
Nitrification
and
denitrification
Microbial N
demand
Temperate
hardwood and
conifer forests
(unfertilized)
9 sites in
North
Central
Oregon
Coast
Range,
U.S.
Not specified None
Soil and foliar N
gradient: As future
reductions in
deposition to polluted
sites occurs,
symptoms of N
saturation are most
likely to persist where
soil N content remains
elevated. Temperate
and hardwood forests
of north-central Oregon
Coast Range. The ratio
of netgross N
mineralization and
nitrification increased
along the gradient,
indicating progressive
saturation of microbial
N demands at high soil
N.
Perakis and
Sinkhorn
(2011)
Ca(N03)2 = calcium nitrate; g = gram; HBEF = Hubbard Brook Experimental Forest; K2HP04 = dipotassium phosphate;
KH2P04 = monopotassium phosphate; KN03 = potassium nitrate; L = liter; mL = milliliter; mmol = millimole; mol = mole;
N = nitrogen; N2 = molecular nitrogen; N20 = nitrous oxide; N20-N = nitrogen from nitrous oxide; NaN03 = sodium nitrate;
NH4+ = ammonium; (NH4)2S04 = ammonium sulfate; NO = nitric oxide; N03" = nitrate; SOM = soil organic matter; Tg = teragram
yr = year.
4.3.7 Decomposition
Decomposition is a general term that refers to the breakdown of organic matter.
(Schlesinger. 1997). The 2008 ISA documented that the soil microbial community
(bacteria and fungi) are the main decomposers of organic matter. Both the microbial
community composition (Compton et al.. 2004) and microbial enzyme activity can
dynamically respond to shifts in inorganic nutrient and substrate availability (Carreiro et
al.. 2000). reflecting the nutrient and energy limitation of the microbial community. Litter
decay rates are also well established to correlate with ratios of C:N, lignin:N, or
lignin:cellulose in litter (Hobbie. 2008; Aerts. 1997; Melillo et al.. 1982). These chemical
traits are strong predictors of litter decay, accounting for over 73% of the variation in
litter decomposition rates worldwide (Zhang et al.. 2008).
The 2008 ISA documented that N addition accelerates decomposition of low-lignin litter
(Fog. 1988). Lignin is an organic polymer, particularly important in cell wall formation
of vascular plants. In contrast, decomposition may not be affected or decelerated in high
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lignin litter, N saturation, and mature forest. A shift can occur from stimulation to
depression of decomposition in N addition studies lasting longer than 2 years (Knorret
al.. 2005). CO2 is often measured as an indication of soil respiration, which includes both
autotrophic (root) biomass and heterotrophic (microbial) activity. More information is
necessary to attribute the autotrophic or heterotrophic source apportionment. There have
been numerous studies published since 2008 on how N addition affects the
decomposition of organic C and N (Table 4-7).
There is new field work supporting that N deposition suppresses decomposition (Rings et
al.. 2015; Zak et al.. 2008). In a meta-analysis evaluating the central tendencies of N
addition effects on belowground C cycling, Janssens et al. (2010) found that N additions
decreased soil respiration from roots and heterotrophs. This is a different result than Liu
and Greaver (2010). who found that only the microbial respiration decreased, while total
soil respiration did not. The different result in the two meta-analysis reflects slightly
different selection criteria by the authors on which studies to include in the analyses.
Notably, Janssens et al. (2010) found that mature forests are more sensitive to N addition,
decreasing soil respiration.
Zhou et al. (2014) conducted a meta-analysis of 295 published results and found N
addition significantly increased soil respiration by 2.0% across all biomes but decreased
respiration by 1.44% in forests and increased respiration by 7.84% and 12.4% in
grasslands and croplands, respectively. Differences in soil respiration may largely result
from stimulation of autotrophic respiration to N addition among croplands and grasslands
compared with no significant change in forests. Heterotrophic respiration exhibited a
negative response to N addition among biomes, with the exception of croplands, tropical
forests, and boreal forests. N addition largely altered root and microbial biomass and soil
C content, the likely mechanisms behind the altered soil respiration.
There is new evidence to support that lignolytic enzyme activity decreases under N
addition (Keeler et al.. 2009; Manning et al.. 2008). The most likely explanation for this
effect was increased soil enzyme activity for enzymes that are known to breakdown
cellulose. This trend is also supported by a new meta-analysis by Whittinghill et al.
(2012). who found N addition decreased lignin decomposition rates by 30% and
increased cellulose decomposition by 9%. Fine roots are likely the dominant source of
difficult-to-decompose plant carbon fractions entering the soil. Xia et al. (2015)
determined this pattern appears to be widespread in boreal and temperate forests.
There are cases in which N addition causes no change in enzyme activity of microbes in
response to N addition; for example, the hardwood and softwood forests growing in the
Bear Brook Watershed in Maine (Mineau et al.. 2014). Another study in the Catskill
Mountains of New York State identifies that patterns in microbial community structure
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and function (detected by enzyme activity) were more strongly influenced by tree species
than by fertilization (Weand et al.. 2010).
There may also be a temporal component to microbial response to N addition. Within the
organic layer, Hobbie et al. (2012) suggest N deposition in forest ecosystems may
decrease mean residence times of active fractions in fresh litter, while increasing those of
more slowly decomposing fractions, including more processed litter. In boreal forests,
Talbot and Treseder (2012) found a transition over time from competition among
decomposers to high cellulase activity and suppressed lignin loss under N fertilization.
The trend suggests that, in N limited systems, N fertilization may alter decomposer
community structure by favoring a shift toward cellulose- and mineral-N users.
Eisenlord et al. (2013) measured the richness and diversity of microbial gene expression.
They found that experimental N deposition significantly decreased the richness and
diversity of microbial genes involved in the depolymerization of starch (12%),
hemicellulose (16%), cellulose (16%), chitin (15%), and lignin (16%).
Table 4-7 Decomposition.
Process/
Indicator
Type of
Ecosystem
Region
Deposition
(kg/ha/yr)
Addition
(kg/ha/yr)
Effect of Deposition
Reference
HERO ID
Soil respiration Multiple
biomes
Global
Varied Meta-analysis: N
addition significantly
increased soil
respiration by 2.0%
across all biomes but
decreased respiration
by 1.44% in forests and
increased it by 7.84%
and 12.4% in
grasslands and
croplands, respectively
(p< 0.05).
The response ratios of
soil respiration to N
addition were positively
correlated with mean
annual temperature,
most significant when
MAT was less than
15°C. N addition largely
altered root and
microbial biomass and
soil C content, which
are likely the
mechanisms behind the
altered soil respiration.
Zhou et al.
(2014)
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Table 4-7 (Continued): Decomposition.
Process/
Indicator
Type of
Ecosystem
Region
Deposition
(kg/ha/yr)
Addition
(kg/ha/yr)
Effect of Deposition
Reference
HERO ID
Soil respiration Forest
Global
Varied Meta-analysis: N
additions decreased
root respiration,
heterotrophic
respiration, and soil CO2
but had no effect on
litter decomposition.
Janssens et
al. (2010)
Meta-analysis: N Liu and
additions decreased G re aver
heterotrophic respiration (2010)
but had no effect on
total soil respiration,
boreal forest,
tropical forest,
grassland,
wetland,
tundra,
desert, and
Arctic
Soil respiration Temperate Global Varied
broadleaf and
mixed forest,
Temperate
conifer forest
Mineralization
Soil N
SOM
Simulated
northern
hardwood
forest
Michigan,
Great Lakes
region
7 to 12
30
N addition: N addition Zak et al.
significantly increase (2008)
the N concentration
(+19%) and N content
(+24%) of canopy
leaves. A decade of
experimental NO3"
deposition significantly
increased amounts of
organic matter (+12%)
and N (+9%) in forest
floor and mineral soil,
despite no increase in
detritus production.
Tracing 15NC>3~ revealed
that N accumulated in
soil organic matter by
first flowing through soil
microorganisms and
plants, and that the
shedding of 15N-labeled
leaf litter enriched soil
organic matter.
February 2017
4-38
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Table 4-7 (Continued): Decomposition.
Process/
Indicator
Type of
Ecosystem
Region
Deposition
(kg/ha/yr)
Addition
(kg/ha/yr)
Effect of Deposition
Reference
HERO ID
Decomposition
Northern
hardwood
forest
Michigan
6.8 to 11.8 30
N addition: The
increase in surface soil
C storage was
apparently driven by
altered rates of organic
matter decomposition,
rather than an increase
in detrital inputs to soil.
The accumulation of C
in the top 10 cm of soil
in the NO3" deposition
treatment appears to be
driven by the direct
suppression of the soil
enzymes responsible for
litter degradation when
litter has a higher N
concentration.
Preqitzer et
al. (2008)
Decomposition
Enzymes
Northern
hardwood
forest
Upper
Michigan
15 to 20
30
N addition: caused
slower organic matter
decay and altered
microbial community
composition and
function. Observed a
decrease in the
abundance and
richness of key
protein-coding genes in
archaea and bacteria
responsible for N
fixation, ammonification,
denitrification, and
assimilatory NO3"
reduction; the same was
true for bacterial genes
mediating nitrification
and dissimilatory NO3"
reduction.
Freedman
et al. (2013)
Decomposition Deciduous
Catskill 9.0
50 mg N/ha/
N addition: N addition
Lovett et al.
forests
Mountains of
yr N
caused decrease in
(2013)
southeastern
(NH4NO3)
mineralization and
New York,
nitrification and an
U.S.
increase in forest floor C
pools and C:N,
indicating that N
addition increased C
sequestration in the
organic horizons ofthe
soil, most significantly in
hemlock plots.
February 2017
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Table 4-7 (Continued): Decomposition.
Process/
Indicator
Type of
Ecosystem
Region
Deposition
(kg/ha/yr)
Addition
(kg/ha/yr)
Effect of Deposition
Reference
HERO ID
Decomposition Northern Upper
Enzymes hardwood Michigan
forest
15 to 20
30 as six
equal
applications
of NaNOs
pellets
delivered to
the forest
floor over the
growing
season
N addition: Observed
that atmospheric N
deposition increases
saprotrophic bacterial
Lacasse-like
multicopper oxidases
(LMCOs). These results
suggest represents a
plausible mechanism by
which anthropogenic N
deposition has reduced
decomposition,
increased soil C
storage, and
accelerated phenolic
DOC production.
Freedman
and Zak
(2014)
Decomposition
fungal residue
Forest
Switzerland Not specified
7 (NH4NO3-
70
(NH4NO3-)
N addition: promoted
the production of new
fungal residues but
slowed the
decomposition of old
residues in forest soil
fractions. Preservation
of old microbial residues
could be due to
decreased N limitation
of microorganisms and
therefore a reduced
dependence on organic
N sources.
Griepentroa
etal. (2014)
Decomposition Grassland
Minnesota,
Nebraska,
Iowa,
Kansas;
Colorado
3.1 to U
100
N addition: decreased
microbial respiration of
OM by as much as 29%
relative to control plots,
and consequently,
decreased C loss from
this pool.
Riggs et al.
(2015)
Enzyme activity
Decomposition
Forest and
grasslands
U.S.
None None Data from 28
ecosystems shows
resources to produce
the enzymes phenol
oxidase and
b-1,4-glucosidase are
uncoupled. This
indicates that the
increasing recalcitrance
of organic matter
decreases C and
nutrient availability and
slows microbial growth
Sinsabaugh
and Shah
(2011)
February 2017
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Table 4-7 (Continued): Decomposition.
Process/ Type of Deposition Addition Reference
Indicator Ecosystem Region (kg/ha/yr) (kg/ha/yr) Effect of Deposition HERO ID
Decomposition Forest Great Lakes 6.8 to 11.8 30 as N addition Fine root Xia et al.
region NaNC>3 biochemistry was less (2015)
responsive than leaf
litter to long-term
simulated N deposition.
Fine roots were the
dominant source of
difficult-to-decompose
plant C fractions
entering the soil.
When combined with
litter production,
simulated N deposition
increased N flux through
leaf litter by an average
of 29%, but did not
affect fine root N flux.
N addition: generally Keeler et al.
stimulated activities of (2009)
cellulose degrading
enzymes in litter and
soil, but had no effect
on lignin degrading
enzyme activity. N
addition had a negative
or neutral effect on litter
and SOM
decomposition in the
same sites, with no
correspondence
between effects of N on
enzyme activity and
decomposition across
sites.
Growth Chamber: Manning et
Evidence to support that al. (2008)
N deposition increased
soil enzyme activity
known to breakdown
cellulose
(cellobiosidase, (3-
glucosidase and
p-xylosidase).
Enzyme activity Forests Central Not specified 100
Decomposition grasslands Minnesota (NH4NO3)
Enzyme activity Eight annual Controlled 2.0 and 44.0
Decomposition herb species ecosystem
(litter bags
placed in
annual herb
based
microcosm
ecosystems)
February 2017
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Table 4-7 (Continued): Decomposition.
Process/
Type of
Deposition
Addition
Reference
Indicator
Ecosystem
Region
(kg/ha/yr)
(kg/ha/yr)
Effect of Deposition
HERO ID
Enzyme activity
Sugar maple
Michigan
Not specified
30
Meta-analysis: N
Whittinahill
Decomposition
forests
addition increases
etal. (2012)
cellulose decomposition
by 9% and decreases
lignin decomposition
rates by 30%. Overall, N
increases the amount of
litter mass entering the
humus pool that leads
to increases in soil C
storage under
experimental N
deposition.
Enzyme activity
Northern
Bear Brook
25.5
N addition: After 22
Mineau et
hardwood and
Watershed
years of N addition, N
al. (2014)
softwood
(BBWM),
enrichment had little
forest
Maine, U.S.
effect on microbial
enzyme activity in
terrestrial
compartments, even
across varying degrees
of organic matter
recalcitrance.
Enzyme activity
Northern
Catskill
50 (NH4NO3)
N addition: Identifed
Weand et
hardwood
Mountains of
that patterns in
al. (2010)
forest
New York,
U.S.
microbial community
structure and function
were more strongly
influenced by tree
species than by
fertilization.
Enzyme activity
Northern
Minnesota
N addition: accelerated
Hobbie et
Decomposition
hardwood
the initial decomposition
al. (2012)
forest
rate. Faster initial
decomposition rates
corresponded to higher
activity of
polysaccharide-
degrading enzymes and
greater relative
abundances of
Gram-negative and
Gram-positive bacteria.
Later in decomposition,
externally supplied N
slowed decomposition,
increasing the fraction
of slowly decomposing
litter, reducing
lignin-degrading
enzyme activity, and
relative abundances of
Gram-negative and
Gram-positive bacteria.
February 2017
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Table 4-7 (Continued): Decomposition.
Process/
Type of
Deposition
Addition
Reference
Indicator
Ecosystem
Region
(kg/ha/yr)
(kg/ha/yr)
Effect of Deposition
HERO ID
Decomposition
Sugar maple
Bear Brook
1,800
N + S addition: caused
Hunt et al.
hardwood
Watershed
eq/ha/yr of
increased N
(2008)
forest
in Eastern
(NH4)2S04
concentration in leaves
Maine
and faster short-term
decomposition.
Decomposition
Mature black
Central
Not specified
Yr
N addition: N
Talbot and
Enzymes
spruce forest
Alaska
2009 = 200
fertilization may alter
Treseder
in upland
(NH4NO3)
decomposer community
(2012)
boreal
Yr
structure by favoring a
ecosystem
2010 = 100
shift toward cellulose-
(NH4NO3)
and mineral-N users.
Cellulose degrading
microbes
(decomposers) were
competitively dominant
under N fertilization.
Decomposition
Sugar maple
Michigan
5.8 to 7.3
30
N addition:
Eisenlord et
Enzymes
forests
(1) significantly altered
al. (2013)
the composition of
actinobacterial and
fungal genes mediating
plant and fungal cell
wall depolymerization.
(2) significantly
decreased the richness
and diversity of genes
involved in the
depolymerization of
starch (-12%),
hemicellulose (-16%),
cellulose (-16%), chitin
(-15%), and lignin
(-16%) (3) resulted in
small changes in
community composition
(25% difference in fungi;
18% in actinobacteria).
BBWM = Bear Brook Watershed; C = carbon; DOC = dissolved organic carbon; ha = hectare; kg = kilograms;
LMCO = Lacasse-like multicopper oxidase; mg = milligrams; N = nitrogen; 15N = nitrogen-15: NaN03 = sodium nitrate;
NH4NO3 = ammonium nitrate; (NH4)2S04 = ammonium sulfate; N03" = nitrate; 15N03" = nitrogen-15-labeled nitrate; OM = organic
matter; S = sulfur; SOM = soil organic matter; yr = year.
4.3.8 Nitrogen Mineralization
Mineralization is a more specific term of decomposition that refers to processes that
release carbon as CO2 and nutrients in inorganic form. Nitrogen mineralization is the
process by which organic N is converted to plant-available inorganic forms. The 2008
February 2017
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1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
ISA documented that N availability to plants in soil is largely controlled by the process of
N mineralization. The rate of mineralization may be influenced by numerous factors
including C:N soil organic matter, soil pH, and the microbial community. N
mineralization has been shown to increase with increasing N addition (Aberetal.. 1998).
often by 0.3 to 1.6 times the control (Gundersen et al.. 1998).
New publications (Table 4-8) support that soil N mineralization increases with N
addition across terrestrial ecosystems (Lu et al.. 2011a) and specifically in temperate
forests (Nave et al.. 2009a). likely due to increases in DON, size of the N pool in the soil,
and decreases in C:N ratios. The forest floor responds differently than the deeper mineral
soil layer I Figure 4-7; (Lovett et al.. 2013; Nave et al.. 2009a)I.
In forests, Casson et al. (2014a) found that almost all mineralized N is converted to NO,
(ranging from 71 to 99%) in catchments they studied. While Bade et al. (2015) found in
old-growth spruce forest, lower N mineralization occurred in the more open than the
closed patches. Possible reasons are reduced litter supply and lower canopy N
interception in gaps in this forest under exposure to high N deposition. Further studies in
other old-growth forests are needed to better understand the mechanisms causing
long-term change in N cycling with forest development.
In grasslands, Rao et al. (2009) found N deposition may increase production and/or alter
litter C:N ratios that increases soil C. There was an inverse relationship between the C:N
ratio and total N mineralized, yet a positive relationship between organic C and total N
with mineralization. These results appear to support that microbial activity in low
productivity arid land soils is primarily limited by C and secondarily limited by N.
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SolC
C/N
Forest floor
~vera
N-ftx
N-fert
N-dep
Mineral soil
Overall
N-fert
N-dep
(45)
(47)
(87)
-«o- 1161
N,
* /
mm
/
JB1)
(37)
—tfet
<42)
(21
(5)
-40 -20 0 20 40 60
-20 -15 -10 -5 0 5
Change with N inputs (%)
|80'}
A '
(51)
-*—
(24)
0 100 400 600
C = carbon; C/N = carbon-to-nitrogen ratio; N-dep = nitrogen deposition; N-fert = nitrogen-fertilization; N-fix = nitrogen-fixing
vegetation; Nmin = nitrogen mineralization.
Points are means ± bootstrapped 95% confidence intervals, with number of studies in parentheses. Groups with confidence
intervals overlapping the dotted reference line (0% change) show no significant effects of N addition. Soil carbon responses to
nitrogen inputs are shown separately for pool sizes (filled symbols) and concentrations (open symbols). For each response
parameter, the effects of nitrogen inputs are shown overall, and for individual modes of nitrogen addition, including the
establishment of nitrogen-fixing vegetation, large-dose nitrogen-fertilization, and simulated chronic nitrogen deposition. Note that
points plotted in panels C and F have 95% confidence intervals with upper-bounds beyond the x-axis maximum.
Source: (Nave et al.. 20093).
Figure 4-7 The effects of nitrogen inputs on soil carbon, carbon:nitrogen
ratio, and minimum nitrogen in forest floors (panels A-C) and
mineral soils (panels D-F).
February 2017
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Table 4-8
Nitrogen mineralization.
Process
Ambient N/S
Reference
Type of
Deposition
N/S Addition
Effect of
Endpoint
Ecosystem
Region
(kg/ha/yr)
(kg/ha/yr)
Deposition
HERO ID
Net N
Mixed
Muskoka-
NO3-
Not applicable
In all seasons, rates
Casson et
mineralization
hardwood
Haliburton
deposition
of nitrification were
al. (2014a)
and nitrification
forested
district of
2.78 ± 1.22;
similar to rates of
rates/NH4+ N,
headwater
south-central
NH4+
total mineralization,
soil NO3",
catchments
Ontario,
deposition
indicating that
stream NO3"
Canada
3.90 ± 1.39
almost all
mineralized N is
converted to NO3" in
both soil types
(ranging from 71 to
99%).
N
Natural
Harz
27 (open
Not applicable
Net N mineralization
Bade et al.
mineralization,
(unmanaged)
National
areas)
(and ammonification)
(2015)
ammonifi cation,
old-growth
Park in
47 (closed
rates were higher in
nitrification/NC>3"
Norway
Central
forest)
the closed stands of
spruce forest
Germany
the optimum and
overmature stages
than in the more
open decay and
regeneration stages.
Only a small
proportion of NH4+
was oxidized to
NO3" in the acidic
soils.
N mineralization
Desert
Joshua Tree
2.7 to 14.4
Calculated soil N
Rao et al.
National
from deposition was
(2009)
Park
directly correlated
with measured soil C
and N and
decreasing C:N
ratios.
N mineralization
Temperate
Northeastern
Varies
Varies
Meta-analysis:
Nave et al.
forests.
U.S.
Overall, N inputs
(2009a)
increased soil C
(+7.7%) and N
mineralization
(+62%), while
decreasing C:N
(-4.9%).
N mineralization Forest
50 (6 years of
N addition: There
Lovett et
N addition)
was a significant
al. (2013)
decline in potential N
mineralization and
nitrification rates in
the mineral horizon
but not in the forest
floor.
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Table 4-8 (Continued): Nitrogen mineralization.
Process
Ambient N/S
Reference
Type of
Deposition N/S Addition
Effect of
Endpoint
Ecosystem
Region
(kg/ha/yr) (kg/ha/yr)
Deposition
HERO ID
N mineralization
Terrestrial
Varies Varies
Meta-analysis: N
Lu et al.
ecosystems
addition increased
(2011a)
mineralization rates.
Mineralization
Mixed
Adirondack
Not specified None
Ca gradient: The
Paae and
soil [N]
hardwood
Mountains,
exchangeable Ca
Mitchell
soil [Ca]
stands
New York,
coupled with soil
(2008)
U.S.
moisture, soil
organic matter, and
ambient temperature
accounted for 61%
of the variability in
extractable inorganic
N across 11 sites.
The influence of Ca
on soil inorganic N
may be through
interactions between
soil Ca
concentrations and
species composition,
which in turn affect
the quality of litter
available for N
mineralization.
N mineralization
Douglas-fir
Oregon
2.0 None
Aboveground N
Perakis
forest
Coast Range
uptake by plants
and
increased
Sinkhorn
asymptotically with
(2011)
net N mineralization
to a peak
35 kg N/ha/yr
Decomposition
Spruce forest
Germany
8.5
N exclusion: Some
Enowashu
Enzyme
N cycling enzymes
et al.
activities
increased activities,
(2009)
whereas others
decreased under
reduced N
treatment.
C = carbon; Ca = calcium; ha = hectare; kg = kilogram; N = nitrogen; NH4+ = ammonium; N03 = nitrate; yr = year.
4.3.9 Dissolved Organic Carbon Leaching
The 2008 ISA documented that chronically high N deposition influences soil DOC
production and transportation. The many carboxylic groups of DOC make it chemically
interact like a weak acid and affect pH levels. Acidity of some surface waters is partly
February 2017
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1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
regulated by the concentration of DOC. Acidification caused by human activity that
lowers pH to 5 suppresses the production of natural DOC. In recent years, the DOC of
some lakes and streams has risen, with the source likely from the adjacent terrestrial
watershed. However, the mechanism causing this increase in unclear. The increase may
be due to soil recovery from acidification (Haaland et al.. 2010) or changes in climate or
land use. There are new publications attempting to define background levels of DOC
(Erlandsson et al.. 2011). For a discussion of DOC in surface water see Chapter 7.
A second mechanism that may cause increasing DOC is N deposition effects on rates of
decomposition. Increases in DOC concentrations were observed in both experimental
sites which received chronic N addition (Adams et al.. 2005; Pregitzer et al.. 2004;
Sinsabaugh et al.. 2004) and natural ecosystems which experienced high rates of N
deposition, such as Hudson River and several European peatlands (Bragazza et al.. 2006;
Findlav. 2005). N deposition may increase DOC export by increasing litter input and
decreasing DOC degradability (Roulet and Moore. 2006). However, the mechanism
behind the association between N deposition and DOC production is not yet well
understood (DeForest et al.. 2005; Findlav. 2005; Pregitzer et al. 2004).
New publications on how N addition affects DOC leaching report mixed results (Evans et
al.. 2008). either increasing it (Liu and Greaver. 2010). showing no significant effect or
decreased it (Hagedorn et al.. 2012). Mechanisms for how N addition affects DOC were
explored by Kopacek et al. (2013) and Freedman and Zak (2014).
Freedman and Zak (2014) reported that atmospheric N deposition led to less diverse,
significantly altered bacterial and LMCO gene assemblages, with taxa implicated in
organic matter decay accounting for the majority of compositional changes. These results
suggest that experimental N deposition favors bacteria in the forest floor that harbor the
LMCO gene and represents a plausible mechanism by which anthropogenic N deposition
has reduced decomposition, increased soil C storage, and accelerated phenolic DOC
production (Figure 4-8). Kopacek et al. (2013) observed that N addition, together with
S042 deposition, increases the availability of electron acceptors for soil microbial
processes. The chemical and microbial responses include an increase in bacterial
mineralization creating DOC, increased N mineralization where N availability increases
(with an increase in bacterial uptake of DOC), chemical suppression of DOC solubility
and bioavailability in the progressively acidifying soils, and finally, the C limitation of
microbial metabolism. Bacterial assimilation of NO3 , which depends on the
stoichiometric NO3 to DOC ratio in the substrate, may initially increase with increasing
N03 concentrations, but then decrease due to a lower pool of bioavailable DOC.
In a meta-analysis of forest ecosystem (Liu and Greaver. 2010). the central tendency is
that N addition increases short-term belowground C storage by increasing C content of
February 2017
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1
2
3
4
5
6
7
8
9
10
organic layer. N addition increased DOC concentration (+18%); and increased C content
of the organic soil layer (+17%) but not the mineral soil layer (Liu and Greaver. 2010). In
a field study, Hagedorn et al. (2012) observed that N addition did not affect DOC
leaching from the litter layer, but DOC fluxes from the near-surface mineral soils
decreased by 17%. Less than 15% of the DOC flux from the mineral soil was derived
from fresh litter, regardless of the N additions. Thus, it is likely that the suppression of
DOC leaching from the mineral soil by the N addition causes decreased mobilization of
"older" (nonlitter) DOC. The decline in DOC was attributed to an alteration of soil
solution chemistry by the NH4NO3 treatment, specifically increased ionic strength and
acidification.
Extracellular Enzyme Activity
Pe»tij(idase3 and Phenol OxkJase
BaslcKW»yc«ts 4. AKomycew Funai
Incomplete Lignin Decay
N in Plant Litter
Inorganic N
In Soil Solution
Atmospheric N Deposition
Bacterial Metabolism of Lignin and Humics
LMCO-flaibtmng Bacteria &
CDecomposition Organic Matter
Rates *"--.__Accumulation
N = nitrogen; LMCO = Lacasse-like multicopper oxidase.
Source: Freedman and Zak (2014).
Figure 4-8 Conceptual diagram of positive (solid arrows) and negative
(dashed arrows) fluxes in nitrogen pools (squares) and carbon
pools (ovals) and the biological processes (no border) that are
affected by experimental nitrogen deposition.
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Table 4-9 Terrestrial dissolved organic carbon leaching.
Ambient
N/s
Type of Deposition N/S Addition Reference
Process Ecosystem Region (kg/ha/yr) (kg/ha/yr) Effect of Deposition HERO ID
DOC leaching
mineralization
DOC
reduce leaching of older
DOC from mineral soil. N
addition did not
significantly affect annual
C losses through
mineralization, but
altered the temporal
dynamics in litter
mineralization.
Beech forest Swiss Jura Not 5.5 (NH4NO3) N addition was found to Haaedorn et
stands on mountain specified alter mineralization al. (2012)
calcareous range dynamics of 13C-depleted
soils leaf and twig litter and
DOC leaching Temperate 410
Microbial
activity
indicated as
biomass C,
respiration
Soil
respiration
mixed and
conifer
forests, boreal
forests,
grasslands,
tropical
forests, arctic,
wetlands,
desert, and
tundra
observations
globally
Not 10 to 650 N addition will increase
specified short term belowground
C storage by increasing
C content of organic
layer. N addition;
increased DOC
concentration (+18%);
and increased C content
of the organic soil layer
(+17%) but not the
mineral soil layer.
Liu and
G re aver
(2010)
Mineralization
Nitrification
DOC
None-
theoretical
None-
theoretical
Not
specified
Not specified
N addition increases
mineralization causing
the pool of bioavailable
DOC to decrease.
Consequently, relatively
less bioavailable DOC
remains for NH4+
assimilation and
immobilization in
microbial biomass,
leaving more NhV for
nitrifiers. As a result,
internal NO3" production
increased. The higher
bacterial demand for
DOC under elevated
availability of N and
electron acceptors
comes into conflict with
increasing chemical
suppression of DOC
solubility and
bioavailability in the
progressively acidifying
soils and finally results in
the C limitation of
microbial metabolism.
Kopacek et
al. (2013)
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2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
Table 4-9 (Continued): Terrestrial dissolved organic carbon leaching.
Ambient
N/s
Type of Deposition N/S Addition Reference
Process Ecosystem Region (kg/ha/yr) (kg/ha/yr) Effect of Deposition HERO ID
Mineralization Northern
Enzymes hardwood
Microbial
community
forest
Upper
Michigan
15 to 20 kg
N/ha/yr
30 (as six
equal
applications
of NaNOs
pellets
delivered to
the forest
floor over the
growing
season)
N deposition reduced
decomposition, increased
soil C storage, and
accelerated phenolic
DOC production.
Observations suggest
that future rates of
atmospheric N deposition
could fundamentally alter
the physiological
potential of soil microbial
communities.
Freedman
and Zak
(2014)
13C = carbon-13; C = carbon; DOC = dissolved organic carbon; ha = hectare; kg = kilogram; N = nitrogen; NaN03 = sodium nitrate;
NH4+ = ammonium; NH4N03 = ammonium nitrate; N03" = nitrate; S = sulfur; yr = year.
4.3.10 Belowground Carbon Pools
In general, N enrichment influences C flux, C partitioning, and the amount of C
sequestered by ecosystems. A number of studies have suggested that C sequestration
increases with increasing N supply based on the changes in aboveground net primary
production [ANPP; (LcBauer and Treseder. 2008; Xia and Wan. 2008)1. However, about
half of C fixed annually by terrestrial vegetation is allocated to belowground pools. Many
studies have shown that the belowground C cycle does not always mirror the
aboveground cycle. For example, elevated CO2 and N both have been shown to increase
aboveground biomass production (LcBauer and Treseder. 2008). However, increases in
aboveground plant production and greater aboveground litter inputs do not necessarily
increase mineral soil C storage (Talhelm et al.. 2009; Gielen et al.. 2005; Lichter et al..
2005). and increases in soil C do not necessarily result from greater aboveground litter
inputs (Pregitzer et al.. 2008). This disparity indicates that it is inappropriate to
extrapolate from aboveground responses to belowground processes. Aboveground plant
biomass, once dropped from the canopy, is one of the major contributors to soil organic
matter accumulation (Sullivan et al.. 2007a). ANPP generally increases with increasing N
supply (LcBauer and Treseder. 2008; Xia and Wan. 2008). However, this increase in C
input may not cause an increase in belowground ecosystem C storage. This is because the
output of C from the soil may be stimulated by N induced alteration of plant tissue
chemistry or the ratio of root: shoot, each of which will change the rate of decomposition
(see Section 4.3.7). Since the 2008 ISA was published there have been several new
meta-analyses on the effects of N addition on belowground carbon pools (Janssens et al..
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2010; Liu and Greaver. 2010). each integrating information from numerous pools to
improve the understanding of how N addition alters the carbon cycle below ground.
Liu and Greaver (2010) synthesized data from multiple terrestrial ecosystems to quantify
the response of belowground C cycling under N addition (Figure 4-9). N addition
increased aboveground litter inputs (+20%), but fine roots litter inputs were unchanged.
N addition inhibited microbial activity, as indicated by a reduction in microbial
respiration (-8%) and microbial biomass carbon (-20%). Although soil respiration was
not altered by N addition, dissolved organic carbon concentration increased (+18%),
suggesting C leaching loss may increase. N addition increased the C content of the soil
organic horizon (+17%) but not the mineral soil. The increase in organic horizon C was
attributed to both increased litter input and decreased decomposition [inferred from the
lower microbial respiration rates (Liu and Greaver. 2010)1.
GPP (?)
ER (?)
tANPP (+29%)
RatoegroufiiJ (?)
§
'Root biomass (+23%)
: i ; Pine root Morruns |n.s.)
w
Hoot exudation (?)
~Mycorrhiza (-15%)
'autotrophic
(?)
MBC (-20%)
Mineral soil layer
(n.s.)
fWn-s.)
1 microbial
(~a%)
DOC (+18%)
ANPP = aboveground net primary production; DOC = dissolved organic carbon; ER = ecosystem respiration; GPP = gross primary
productivity; MBC = microbial biomass carbon; n.s. = nonsignificant; Raboveground = aboveground respiration; RautotroPhic = soil
autotrophic respiration; Rmio-obiai = microbial respiration; Rsoii = total soil respiration,
f data from LeBauer and Treseder (2008); * data from Xia and Wan (2008); =t= data from Treseder (2004).
Source: Liu and Greaver (2010)
Figure 4-9 Estimation of the changes in carbon budget of terrestrial
ecosystem under nitrogen.
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Field studies provide additional support for the finding that soil carbon responds
differently to N addition with increasing depth. In four northern hardwood forests spread
across Michigan that received experimental N deposition (additional 30 kg N/ha/y) for
10 years, Pregitzer et al. (2008) and Zak et al. (2008) reported significant increases in soil
C, particularly within the soil organic horizon. These increases occurred despite no
increase in aboveground litter production or root turnover. A ' "NO, -labeling experiment
revealed that N accumulated in SOM by first flowing through soil microorganisms to
plants, which then shed the leaves back to the detrital layer. In a meta-analysis including
data from 72 north temperate forests, Nave et al. (2009a) found N addition increased soil
C (+7.7%). The forest floor responded differently than the deeper mineral soil layer (5 to
100 cm depth) as increased soil C storage occurred only in the mineral soil (+12.2%), in
contrast to the findings of Liu and Greaver (2010) and Pregitzer et al. (2008).
4.3.11 New Biogeochemical Indicators
In this section, we report on new biogeochemical indicators reported in the literature
since the 2008 ISA. Recent literature offering potential new indicators of biogeochemical
change due to N and/or S deposition included fungal to bacterial ratio (Hogberg et al..
2013) and syntaxonomic associations KWamelink et al.. 2011) Table 4-101.
Table 4-10 New biogeochemistry indicators.
Nutrient Description/Direct Effect
Enrichment Acidification Deposition Addition of Soil/Water Endpoint Reference
Indicator Indicator (kg/ha/yr) (kg/ha/yr) On Biological Effect HERO ID
Endpoint
N leaching
X Throughfall 20 Microbial community Hogberg et
N includes (NH4NO3) composition in the mor al. (2013)
wet and dry layer of spruce forests and
inputs and soil solution chemistry
ranged from below the rooting zone
2.7 to 19 was highly correlated.
Stands with low
concentrations of NO3"
and Al were fungi
dominated and had a
higher fungi:bacteria ratio
compared with stands with
high concentrations of
these leachates. Leaching
stands had higher
abundance of
gram-positive bacteria.
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Table 4-10 (Continued): New biogeochemistry indicators.
Endpoint
Nutrient Description/Direct Effect
Enrichment Acidification Deposition Addition of Soil/Water Endpoint Reference
Indicator Indicator (kg/ha/yr) (kg/ha/yr) On Biological Effect HERO ID
Vegetation
health
X
X
Not specified None
Acknowledge the
approach is not yet
possible to directly
estimate ranges for
syntaxa for pH and NO3"
on a large scale; however,
indirectly estimated soil
pH and NO3"
concentrations are
sufficiently available to
derive ranges for many
associations.
Wamelink et
al. (2011)
Al = aluminum; ha = hectare; kg = kilogram; N = nitrogen; NH4NO3 = ammonium nitrate; N03 = nitrate; yr = year.
Hogberg et al. (2013) proposed soil microbial community indices as predictors of soil
solution chemistry and N leaching in Picea abies (L.) Karst spruce forests in Southern
Sweden. Stands with low concentrations of NO3 and Al3+ had higher fungi:bacteria
ratios compared with stands with higher concentrations of NO3 and Al. They identified
three promising microbial community indices as indicators of N leaching from forests;
the soil fungi:bacteria ratio was the most important.
In a study in the Netherlands, Wamelink et al. (2011) examined whether the abiotic
ranges of syntaxonomic units (associations) in terms of pH and NO3 concentration can
be estimated and then, in principle, used to estimate critical loads for acid and N
deposition. They used splines to estimate abiotic ranges of syntaxonomic units on the
basis of measured soil pH and NO3 concentration and vegetation releves. They
acknowledge it is not yet possible to directly estimate ranges for syntaxa for pH and NO3
on a large scale using this approach; however, indirectly estimated soil pH and NO3
concentrations are sufficiently available to derive ranges for many associations.
4.3.12 Disturbance and Stand Age Effects on Nitrogen Retention
The 2008 ISA reported that varying degrees ofN assimilation, leaching, and microbial
transformation often reflect differences in N status among treatment sites. These
variations have most often been attributed to disturbance history, dating back a century or
more (Goodale and Aber. 2001). Sites that have undergone disturbances that cause loss of
soil N, such as logging, fire, and agriculture, tend to be most effective at retaining
atmospheric and experimental inputs of N. Fire causes substantial N losses from
ecosystems. Timber harvest contributes to nutrient removal from the ecosystem via
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biomass export and acceleration of leaching losses (Mann et al. 1988; Bormann et al..
1968). In particular, logging contributes to loss of N and Ca2+ from the soil (Lattv et al..
2004; Tritton et al.. 1987). N retention capability often decreases with stand age,
suggesting that older forests are more susceptible than younger forests to becoming N
saturated (Hedin et al.. 1995).
One new study has been published since 2008 on how disturbance affects N retention
(Vourlitis and Pasquini. 2008). Fire did little to alter patterns of soil N enrichment from
atmospheric N deposition; however, periodic fires have important implications for the
structure and function of chaparral shrublands and their propensity to become N saturated
under current and future N deposition and fire regimes.
4.4 Soil Monitoring and Databases
There are several new studies using long-term monitoring data sets in the U.S. and
Europe (Table 4-11). New studies in the U.S., including an analysis of 45 years of
biogeochemical monitoring data (Yanai et al.. 2013) and sulfur accumulation (Mitchell
and Likens. 2011) at the Hubbard Brook Experimental Forest LTER, New Hampshire
and at the Niwot Ridge LTER, Colorado Lieb et al. (2011). identify the effects of a
decade of simulated N deposition in the southern Rocky Mountains.
Yanai et al. (2013) evaluated 45 years of biogeochemical monitoring data at the Hubbard
Brook Experimental Forest LTER, New Hampshire, U.S. Since 1992, the ecosystem
shifted to a net N sink ~8 kg N/ha/yr. There are several possible explanations: (1) gaseous
N fluxes from the ecosystem, (2) a budget discrepancy in the net error of the other
measured and estimated stocks and fluxes, and/or (3) N is accumulating in the ecosystem.
As discussed in Section 4.3.3. Mitchell and Likens (2011) examined the sulfur
accumulation observed in over four decades of continuous long-term records for four
watersheds in Hubbard Brook Experimental Forest, New Hampshire and found that as S
deposition has declined, soil moisture has become a more powerful control on S release
from soils than is deposition.
At the southern Rocky Mountains Niwot Ridge LTER, Colorado, U.S., Lieb etal. (2011)
found a decade of simulated N deposition to alpine ecosystems caused ongoing changes
in diversity and soil biogeochemistry, including lower soil acid buffering capacity,
decreased concentrations of base cation Mg2+, and increased concentrations of the
potentially toxic cations Mn2+ and Al3+. Their results suggested an N deposition threshold
of 28 kg N/ha/yr.
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There are new studies evaluating long-term monitoring in Europe, including S dynamics
in England (Lchmann et al. 2008) and N and S dynamics in Switzerland (Pannatieret al..
2011). In Sweden, khalili et al. (2010) examined N and C interactions between boreal
soils and lakes. Lchmann et al. (2008) found that a soil ecosystem response to SO2
emissions was a shift to more oxidized organic S that proceeded much more rapidly than
the reversal after reductions of atmospheric emissions and deposition. Pannatier et al.
(2011) examined monitoring at Swiss Long-Term Forest Ecosystem Research sites.
Results suggested that the fluxes of BC, SO42 , and inorganic N in soil solution reacted
very little to the changes in atmospheric deposition. A stronger reduction in base cations
compared to Al3+ was detected at two sites, which might indicate that acidification of the
soil solution was proceeding faster at these sites than the other sites. In Sweden, Khalili et
al. (2010) examined samples that were collected in selected years between 1993 and
2005. Although, they found a significant relation between C:N ratios of the organic soil
layer and lake waters, the large-scale variations in soil C content were not directly linked
to C concentrations in lake waters. Soil N seems to have leached in small amounts from
the soils directly into the lakes in the form of NO, . Relating latitude and longitude to
NO, leaching showed a clear sudden increase in NO, leaching in regions where N
deposition exceeded 7.5 kg/ha/yr.
Table 4-11 Biogeochemistry monitoring and databases.
Process/
Type of
Deposition
Addition
Reference
Indicator
Ecosystem
Region
(kg/ha/yr)
(kg/ha/yr)
Effects
HERO ID
Base cation
Alpine soils
Niwot Ridge
6 to 8
8, 28, 48,
Addition: Results are
Lieb et al.
(BC) release
in the
(10 years)
and 68
ongoing but include
(2011)
Soil [Al]
southern
(NH4NO3)
changes in diversity,
Soil [Mn]
Rocky
lower soil acid buffering
Soil pH
Mountains,
Colorado,
U.S.
capacity, decreased
concentrations of base
cation Mg2+, and
increased
concentrations of the
potentially toxic cations
Mn2+ and Al3+. Results
suggested an N
deposition threshold of
28 kg N/ha/yr.
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Table 4-11 (Continued): Biogeochemistry monitoring and databases.
Process/ Type of Deposition Addition
Indicator Ecosystem Region (kg/ha/yr) (kg/ha/yr)
Effects
Reference
HERO ID
Sulfate leaching
[S0421
Northeastern
forest
HBEF, New
Hampshire,
U.S.
Not specified None
Monitoring: Over four
decades of data were
used to evaluate S
budgets. Current
declining inputs of
atmospheric S and the
higher outputs of SO42"
in drainage waters
relative to precipitation
inputs are driven by the
S stored in the soil. This
climatic change will
potentially increase
SO42" mobilization and
hence could slow the
resultant recovery from
acidification.
Mitchell and
Likens
(2011)
N accumulation
Northern
HBEF, New
~7 None
Since 1992, the
Yanai et al.
C:N soil [N]
hardwood
forest
Hampshire,
U.S.
(since 1992)
ecosystem shifted to a
net N sink, either storing
or denitrifying
~8 kg N/ha/yr.
(2013)
NO3" leaching
Boreal soils
Sweden
<3 to 17 None
Gradient: Significant
Khalili et al.
C:N (lake)
and lakes
relation found between
(2010)
C:N (mineral
C:N ratios of the organic
soil layer)
soil layer and the ones
TOC:TN
of lake waters. Evidence
found of N deposition
having depressed the
C:N ratios of lake
waters more than the
ones of organic soil
layers. Clear sudden
increase seen in NO3"
leaching in regions
where N deposition
exceeded 7.5 kg/ha/yr.
Oxidation of
organic S in
humic soils due
to S dep
Ratio of reduced
to oxidized
organic S
Grassland.
Rothamsted
Park Grass
Experiment,
Herfordshire,
England
Not specified None
Effects of atmospheric Lehmann et
SO2 emissions since the al. (2008)
late 1800s considered.
Acidification led to a
depletion of
exchangeable Ca and
Mg and an eightfold
increase in
exchangeable Al.
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Table 4-11 (Continued): Biogeochemistry monitoring and databases.
Process/ Type of
Indicator Ecosystem
Deposition Addition
Region (kg/ha/yr) (kg/ha/yr)
Effects
Reference
HERO ID
BC, N, and Forest,
SO42" flux including
soil solution [Al] beech and
soil solution BC Norway
soil solution spruce
[Inorganic N]
soil solution
Mountains in 2007, mean
southern (-0.02 to
Alps. The 1.99
forests were kmol/ha/yr)
not managed
during the
whole
observation
period.
Switzerland
Jura
Between None
2000 and
A decade (1995-2007) Pannatier et
of monitoring data al. (2011)
indicates acidifying
deposition significantly
decreased at three out
of the nine study sites
due to a decrease in
total N deposition. In the
soil solution, no trend in
concentrations and
fluxes of BC, SO42", and
inorganic N were found
at most soil depths at
five out of the seven
sites, suggesting that
the soil solution reacted
very little to the changes
in atmospheric
deposition.
[S042"]
molar BC/AL in
soil solution
Al = aluminum; BC = base cation; C = carbon; Ca = calcium; ha = hectare; HBEF = Hubbard Brook Experimental Forest;
kg = kilogram; kmol = kilomole; Mg = magnesium; Mn = manganese; N = nitrogen; NH4NO3 = ammonium nitrate; N03" = nitrate;
S = sulfur; S02 = sulfur dioxide; S042" = sulfate; TN = total nitrogen; TOC = total organic carbon; yr = year.
The most commonly used ecosystem models in the U.S. were described in the 2008 ISA
(Section A.3 of the 2008 ISA). The focus of Section 4v5 is to update available
information on several primary models that are currently being used in the U.S. to assess
the effects of S and N deposition on terrestrial ecosystems. One important input to these
models are estimates of base cation weathering (BCw), and there are new updates on two
methods to estimate this parameter: Soil Texture Approximations (STA) and PROFILE.
Steady state models include steady-state mass-balance equations (SMBE). Dynamic
models include: the Very Simple Dynamic (VSD) soil acidification model, MAGIC,
NuCM, PnET/BGC, and DayCent-Chem.
4.5 Models
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4.5.1
Updates to Key Previously Identified Models
4.5.1.1 Estimating Base Cation Weathering: Soil Texture Approximation and
PROFILE
Base cation weathering (BCw) rate is one of the most influential yet difficult to estimate
parameters in the calculation of critical acid loads of nitrogen (N) and sulfur (S)
deposition for terrestrial systems. As discussed in Section 43 acidifying deposition
causes base cation leaching from soil. The supply of base cations is replenished by base
cation weathering of minerals from rock within the ecosystems. Obtaining accurate
estimates of weathering rates is difficult because weathering is a process that occurs over
very long periods of time, and estimates on an ecosystem's ability to buffer acid
deposition rely on accurate estimates of weathering. There is some new work on
estimating BCw, including a study on the clay correlation-substrate method to PROFILE
(Koseva et al.. 2010). a new application of PROFILE in the U.S. (Phelan et al.. 2014).
and an evaluation of uncertainty in estimating BCw (Futter et al.. 2012).
The clay correlation-substrate method, also called clay-based Soil Texture
Approximation (STA), is an empirical steady-state model that has been used to estimate
BCw rates for forest ecosystems in the U.S. because it is simple and has low data
requirements. The STA method has an empirical function that was first developed for
European soils and later adapted to soils in Canada and the U.S. The method estimates
total base cation weathering rates (BCw, sum of Ca2+, Mg2+, Na+, and K+), based on the
relationship between established weathering classes and clay content of soils for different
acidity classes—acidic, intermediate, and basic. An alternate steady-state model,
PROFILE (Sverdrup and Warfvinge. 1993). may offer an improved method to estimate
BCw rates. It is a transferable, process-based model that simulates the weathering rates of
groups of minerals. PROFILE was developed in Sweden and is a mechanistic,
steady-state kinetics model that calculates the weathering of Ca2+, Mg2+, K+, and Na+ in
each horizon within a soil profile based on mineral specific chemical dissolution rates
and site and soil conditions. Because PROFILE is a steady-state model, weathering rates
calculated by PROFILE can be used with the SMB critical acid load model. One of the
main limitations that has discouraged the wider adoption of PROFILE for BCw rate
determinations in the U.S. is the data requirements of the model (koseva et al.. 2010).
koseva et al. (2010) reported on their evaluation and revision of the STA model for use
in Canadian forests. The authors compared the performance of the STA model to
PROFILE weathering estimates for soils at 75 sites in Canada. The relative ability of the
STA and PROFILE models to provide reasonable weathering rates was evaluated using
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base cation mass balances at a subset of sites in Ontario (n = 19). Mineral weathering
rates calculated with the STA method at 75 sites in Canada (6-367 eq/ha/yr) were up to
38 times lower (7 times on average) than rates estimated with PROFILE
(143-2,119 eq/ha/yr,/? < 0.0001). Despite deviations from the 1:1 line, weathering
estimates obtained using the STA method were significantly correlated with PROFILE
weathering estimates (p < 0.05). The authors concluded that the "revised" STA model
they used may be more widely applicable in Canada, but may not necessarily be suited to
all regions. The uncertainty of the model is largely unknown, and due to its empirical
nature, the three equations of the clay correlation-substrate method require recalibration
or revision when transferred to new locations. In addition, the STA equations were
produced for young soils that developed following the Late Wisconsin glaciation (Koseva
et al.. 2010). the clay correlation-substrate model that is based on clay content and parent
material acidity may not be suitable for older, more weathered soils that were not
impacted by the most recent glaciation and which cover the majority of the U.S. (U.S.
EPA. 2009c).
PROFILE requires over 26 time series or site parameters as model inputs. The U.S.
Geological Survey (USGS) recently completed a soil geochemical and mineralogical
survey of the U.S. as part of the North American Soil Geochemical Landscapes Project.
This project, hereafter referred to as the USGS Landscapes Project, included mineralogy
analyses conducted on soil samples collected from 4,871 evenly spaced sites across the
U.S. (Smith et al.. 2013). These new data enable the application of the PROFILE model
at a larger and potentially national scale. Phelan et al. (2014) evaluated PROFILE using
national data sets as a method to estimate BCw rates for forests in the U.S., focusing on
Pennsylvania as the first test state. The model paired with national data sets was
successfully applied at 51 forested sites across Pennsylvania. Weathering rates ranged
from 119 to 9,245 eq ha/year and were consistent with soil properties and regional
geology. The authors suggest the method should be applied to other locations for further
evaluation of the performance of the model.
A data set of published BCw rates was evaluated by Futter et al. (2012). The data set
included 394 individual silicate mineral weathering rate estimates from 82 poorly
buffered, silicate-mineral-dominated locations across the world where at least three
published estimates of BCw were available. The researchers found the estimated
contribution of model parameter uncertainty to overall variability related to PROFILE
and MAGIC was relatively small ranging from 1.7 to 2.1 for the two models,
respectively. The two models have been most widely used to make assessments of
weathering rates for environmental decision making, and each represents the landscape
differently. PROFILE provides estimates for shallow one-dimensional soil, whereas
MAGIC integrates weathering processes for the whole catchment, including deep soil
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weathering. Therefore, lower weathering rate estimates are shown from PROFILE in
comparison to MAGIC, considering that deep soil weathering could constitute an
important source of BC in catchment weathering (Futter et al.. 2012).
The 2008 ISA documented a model to assess CLs for acidification in forest soils based on
simple mass-balance equations [SMBE; (McNultv et al.. 2007)1. This study estimated
critical acid load and exceedance in soils at a 1-km2 spatial resolution across the U.S. A
second publication discussed the uncertainties associated with this model and
national-scale assessment (Li and McNultv. 2007). The authors quantified uncertainty
under natural variability in 17 model parameters and determined the relative
contributions of each in predicting critical loads. Results indicated that uncertainty in the
CLs came primarily from components of base cation weathering (BCw; 49%) and acid
neutralizing capacity (46%), whereas the most critical parameters were BCw base rate
(62%), soil depth (20%), and soil temperature (11%). The authors concluded that
improvements in estimates of these factors are crucial to reducing uncertainty and
successfully scaling up SMBE for national assessments. This work remains the best
national-scale estimate of terrestrial soil acidification in the U.S. (see Section 4.6). New
work by Posch etal. (2011) is a regional application of SMB models, while several other
studies using SMB have been published to determine acidification critical loads based on
critical limits of BC/A1 and ANC (Phelan et al.. 2014; Duarte et al.. 2013; Jung et al..
2013; Whitfield and Watmough. 2012; Forsius et al.. 2010; McNultv and Boggs. 2010;
Nasr et al.. 2010). The biological implications of these critical loads are discussed in
Chapter 5 and a summary of SMB CLs in the U.S. is presented in Section 4.6.
Posch etal. (2011) published an article outlining SMB models for use in N deposition on
ecosystem biodiversity. This approach has the well-established benefit of easy regional
applicability, while incorporating specified critical chemical criteria to protect specified
receptors. Rather than an upper limit for deposition (i.e., critical load), linked nutrient
nitrogen and acidity chemical criteria for plant occurrence result in an "optimal" nitrogen
and sulphur deposition envelope. This method is similar to the methods developed in the
2010 Oxides of N and S Policy Assessment.
The VSD model is the simplest extension of the steady-state SMB model into a dynamic
model. It does this by including cation exchange and time-dependent N immobilization
4.5.1.2
Steady-State Mass Balance
4.5.1.3
The Very Simple Dynamic Soil Acidification Model
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(accumulation). The VSD model is designed for sites with few data available and
applications on a large regional or continental scale. The model has short execution time
that allows rapid scenario analyses and the calculation of target loads (i.e., deposition
targets), which result in a desired chemical condition in the soil (solution) in a specified
year. Posch and Reinds (2009) have developed a version of the VSD for steady-state
critical load applications at the regional scale. Although simpler than other widely used
models (such as MAGIC and SAFE), VSD contains the basic physical and chemical
relationships common to all these models. However, the model's simplicity also means
that some processes have either been left out altogether (e.g., SO42 sorption) and others
strongly simplified (e.g., N processes). As a consequence VSD is not best suited for sites
where SO42 adsorption is important. Furthermore, the simple description of N processes
does not allow simulating decreasing soil N pools (and increasing C:N ratios) under
reduced N inputs.
4.5.1.4 The Soil Acidification in Forest Ecosystems
The ForSAFE model (Wallman et al.. 2005) is the biogeochemical simulator platform
that simulates the cycles of carbon, nitrogen, base cations (Be), and water in a forest
ecosystem, including simulation of soil chemistry, tree growth, and soil organic matter
accumulation or depletion. ForSAFE requires site-specific inputs of the physical
properties of the soil (including mineralogy, hydrological parameters, density, depth, and
stratification), tree type, and time series of atmospheric deposition and climatic data
(temperature, light, and precipitation). The model gives monthly estimates of weathering
rates, soil moisture, soil solution concentrations, uptake fluxes of N and Be, litterfall,
decomposition and mineralization, as well as photosynthesis and growth rates.
ForSAFE-VEG is a composite model, in which the Veg module (Sverdrup et al.. 2007).
reads a set of five drivers (soil solution pH, Be concentration, N concentration, ground
level light, soil moisture) from ForSAFE, in addition to air temperature, and uses them to
estimate the relative abundance of a set of indicator plants at the site. The result is a
model chain that can link changes in atmospheric deposition, climatic conditions, and
land use to responses in the biogeochemistry and plant community composition at the site
level, both historically and in the future. A new study by Belvazid et al. (201 la) revealed
limitations in the model simulation of N concentrations in soil solution. The authors
concluded that the biogeochemical model platform must be improved to simulate N
processes more accurately before it is used to calculate CL for N deposition. The model
overestimated the actual N concentrations in the soil solution. Several new applications
of ForSAFE-VEG have been published (Sverdrup et al.. 2012; Belvazid et al.. 201 la),
and the results are discussed in Chapter 5 and Chapter 6.
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4.5.1.5
Model of Acidification of Groundwater in Catchment
MAGIC (Cosbv et al.. 1985a; C'osbv et al.. 1985c; Cosbv et al.. 1985b) is one of the most
well-known dynamic models of aquatic acidification. It is a lumped-parameter model of
soil and surface water acidification in response to atmospheric deposition based on
process-level information about acidification. "Lumped-parameter" refers to the extent
that spatially distributed physical and chemical processes in the catchment are averaged
or lumped together without affecting the model's reproduction of catchment response.
Process-level information refers to how the model characterizes acidification into (1) a
section in which the concentrations of major ions are assumed to be governed by
simultaneous reactions involving SO42 adsorption, cation exchange,
dissolution-precipitation-speciation of aluminum, and dissolution-speciation of inorganic
carbon and (2) a mass balance section in which the flux of major ions to and from the soil
is assumed to be controlled by atmospheric inputs, chemical weathering, net uptake and
loss in biomass, and losses to runoff. At the heart of MAGIC is the size of the pool of
exchangeable base cations in the soil. As the fluxes to and from this pool change over
time due to changes in atmospheric deposition, the chemical equilibria between soil and
soil solution shift to give changes in surface water chemistry. The degree and rate of
change of surface water acidity thus depend both on flux factors and the inherent
characteristics of the affected soils. The data requirements required to run dynamic
models, such as MAGIC, are greater. The equations that characterize the chemical
composition of soil water in MAGIC contain 33 variables and 21 parameters. Data
required to conduct dynamic modeling are not as available in many places as the data
required to conduct steady-state modeling.
Oulehle et al. (2012) presented a new formulation of the acidification model MAGIC that
uses decomposer dynamics to link N cycling to C turnover in soils. In comparisons with
earlier versions, the new formulation more correctly simulates observed short-term
changes in NO3 leaching, as well as long-term retention of N in soils. The authors state
that the new formulation gives a more realistic simulation of observed changes in N
leaching. The new formulation also provides a reasonable simulation of the long-term
changes in C and N pools (and C:N ratio) with SOM.
4.5.1.6 Photosynthesis and EvapoTranspiration-Biogeochemical
PnET-BGC is an integrated forest-soil-water model that has been used to assess the
effects of air pollution and land disturbances on forest and aquatic ecosystems (Gbondo-
Tugbawa et al.. 2001). The model was developed by linking two submodels: PnET-CN
[PnET-carbon and nitrogen; (Aberet al.. 1997)1 and BGC (Gbondo-Timbawa et al..
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2001). The main processes in the model include tree photosynthesis, growth and
productivity, litter production and decay, mineralization of organic matter,
immobilization of nitrogen, nitrification (Aber et al.. 1997). vegetation and organic
matter interactions of major elements, abiotic soil processes, solution speciation, and
surface water processes (Gbondo-Timbawa et al.. 2001). The hydrologic algorithms used
in PnET-BGC are summarized by Aber and Federer (1992) and Chen and Driscoll
(2005). PnET-BGC has the capability of using multiple soil layers (Chen and Driscoll.
2005) to model seasonal variations in soil parameters and chemistry.
No new literature (2008-2015) has been identified to update of this model.
4.5.1.7 No New Literature (2008-2015) Has Been Identified to Update of This
Model Nutrient Cycle Model
The Nutrient Cycling Model (NuCM) was developed to synthesize current understanding
of nutrient cycling in forests and to predict how forests respond to changing S and N
atmospheric deposition rates. The NuCM model links soil-solution chemical components
with traditional conceptual models of forest nutrient cycling on a stand level (Liu et al.
1991).
No new literature (2008-2015) has been identified to update of this model.
4.5.1.8 Comparative Analyses
Tominaga et al. (2009) used HBEF, New Hampshire, U.S., as the setting to evaluate the
performance of three uncalibrated process-oriented models. They performed a Monte
Carlo multiple-model evaluation framework of the dynamic models: MAGIC, SAFE, and
VSD. The greatest differences in model outputs were attributed to the cation exchange
submodel, with Gapon-exchange based models retaining more base cations on the
exchange complex and releasing less into solution, resulting in lower soil solution ANC
values. Given the same deposition scenario, the three models (without calibration)
simulate changes in soil and soil solution chemistry differently, but the basic patterns
were similar.
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4.5.2 New Models (Published since 2008)
4.5.2.1
Soil Organic Matter
The SOM model was developed as an alternative decomposition model of the PnET
model of northeastern forests. It relies on empirical representations of litter
decomposition and soil C turnover rates, and explicitly represents multiple soil horizons.
Tonitto et al. (2014) examined the effect of N addition on SOM dynamics. Their model
simulations suggested that ambient atmospheric N deposition at the forest has led to an
increase in cumulative 0-, A-, and B-horizons C stocks of 211 g C/m2 (3.9 kg C/kg N)
and 114 g C/m2 (2.1 kg C/kg N) for hardwood and pine standards, respectively. They
concluded that the model proved largely able to simulate soil C and N dynamics at their
study site under control conditions and that field observations, mechanistic experiments,
and model simulations suggest that addition of N to forest ecosystems could have a
substantial effect on forest soil C accumulation via suppression of organic matter
decomposition.
O-CN is a terrestrial biosphere model which has been developed from the land surface
model ORCHIDEE and describes the N and C fluxes and stocks of vegetation and SOM
for 10 natural plant functional types, as well as C3 and C4 croplands at a half hourly time
scale. Zaehle (2013) state that the estimate of the process-based O-CN model applied
here is somewhat lower than earlier studies based on simple biogeochemical models and
upscaling of field-based C sequestration estimates, which have estimated C sequestration
based on N deposition estimates as 0.4-0.7 Pg C/yr in 1990. The O-CN results were
within the range of model simulations with the current generation of C-N cycle models
(0.2-0.6 Tg N/yr). The authors believe the study provides an advance over previous
assessments because it relies on a process-based ecosystem model that integrates the key
C-N cycle interactions and their coupling to biogeophysical processes, while considering
the impacts of atmospheric (climate, CO2) and land cover changes. Key uncertainties in
the modeling include (1) the response of canopy-level photosynthesis to N additions,
(2) changes in the allocation patterns (root: shoot ratio), and (3) the competition of plants
and soil microbes for the added (or reduced) amount of N.
4.5.2.2
ORCHIDEE-Carbon-Nitrogen
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4.5.2.3
Dynamic Model N14C
Dynamic model N14C is a plant-soil N and C cycling model that simulates terrestrial
ecosystem responses to atmospheric N deposition (Tipping et al.. 2012). The model
includes four plant functional types: broadleaved and coniferous trees, herbs, and dwarf
shrubs. It simulates net primary production (NPP); C and N pools; leaching of DOC and
DON, and inorganic N; denitrification; and the radiocarbon contents of organic matter on
an annual time step. The model simulates annual plant growth and turnover and soil C
and N cycling and is reasonably successful at reproducing average results. However, for
individual sites, there are no significant correlations for C pools (r2 - 0.05) or C:N ratios
(r2 - 0.08) and only weak relationships for N pools (r2 = 0.05) and inorganic N leaching
(r2 = 0.31). Inorganic leaching has traditionally been considered one of the main
indicators of N saturation (however, see new studies in Section 4.3.2) and therefore an
important goal of N14C is to simulate its response to N enrichment.
Perakis and Sinkhorn (2011) reported 515N constraints on long-term N balances in
temperate forests using a dynamic simulation model of ecosystem N and S15N. Their
model evaluated which combination of N input and loss pathways could produce a range
of high ecosystem N contents characteristic of forests in the Oregon Coast Range, U.S.
Ecosystem S15N displayed a curvilinear relationship with ecosystem N content and
largely reflected mineral soil, which accounted for 96-98% of total ecosystem N. Model
simulations of ecosystem N balances parameterized with field rates of N leaching
required long-term average N inputs that exceed atmospheric deposition and asymbiotic
and epiphytic N2-fixation, and that were consistent with cycles of post-fire N2-fixation by
early successional red alder. Soil water 5l5NO;, patterns suggested a shift in relative N
losses from denitrification to NOs leaching as N accumulated, and simulations identified
NO3 leaching as the primary N loss pathway that constrains maximum N accumulation.
The 2008 ISA documented that by the end of the 1980s, after nearly a decade of intensive
research performed under the original NAPAP, the regions of the U.S. with many
acid-sensitive waters and ecosystems were well recognized. These acid-sensitive
ecosystems are generally located in upland, mountainous terrain in the eastern U.S. and
are underlain by bedrock that is resistant to weathering, such as granite or quartzite
sandstone. However, a similar map for areas sensitive to the eutrophication effects of
4.5.2.4
Dynamic Simulation Model of Ecosystem Nitrogen
4.6 National-Scale Sensitivity
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nitrogen were not available. There is strong evidence demonstrating that biogeochemical
sensitivity to deposition-driven eutrophication and acidification is the result of historical
loading, geologic/soil conditions (e.g., mineral weathering and S adsorption), and
nonanthropogenic sources of N and S loading to the system. There is no single deposition
level applicable to all ecosystems in the U.S. that will describe the onset of eutrophication
or acidification. There are two new publications commenting on recovery from terrestrial
ecosystems at either the national scale (NAPAP. 2011) or specifically in the Northeast
(Lawrence et al.. 2015a). There is one new paper evaluating national-scale terrestrial
critical loads for nitrate leaching (Pardo et al.. 201 lb), but work on national-scale soil
acidification published in 2007 remains the most recent national assessment of this effect
(McNultv et al.. 2007).
4.6.1 Acidification Recovery
The National Acid Precipitation Assessment Program (NAPAP) report to Congress was
published in 2011 (NAPAP. 2011). NAPAP is a cooperative federal program first
authorized in 1980 to coordinate acid rain research and report the findings to Congress.
The research, monitoring, and assessment efforts by NAPAP and others in the 1980s
culminated in Title IV of the 1990 Clean Air Act Amendments (CAAA), also known as
the Acid Deposition Control Program. Title IV includes a market-based program that
provides economic incentives for controlling emissions of sulfur dioxide from electricity
generating facilities. Title IX of the CAAA reauthorized NAPAP to conduct acid rain
research and monitoring and to periodically assess the costs, benefits, and effectiveness
of Title IV. The NAPAP member agencies are the U.S. Environmental Protection
Agency, the U.S. Department of Energy, the U.S. Department of Agriculture, the
U.S. Department of Interior, the National Aeronautics and Space Administration, and the
National Oceanic and Atmospheric Administration.
The report notes, few studies have tracked the status and potential recovery of terrestrial
ecosystems during the period of decreasing acid deposition since the 1980s. This is due in
part to the historical focus on aquatic acidification and a lack of understanding of the
terrestrial impacts of acidification at the time that the Clean Air Act was amended in
1990. Since the early 1990s, scientific understanding of terrestrial ecosystem effects of
acid deposition has increased greatly, and studies indicate continued degradation of soil
base status (calcium and magnesium). The report concludes few studies have evaluated
terrestrial ecosystem health relative to acidification effects over time, and soils in the
most acid-sensitive regions continue to acidify.
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Since the publication of the NAPAP (2011). there has been a new study that observes the
beginning of a reversal of the forest-soil acidification in the Northeastern U.S. (Lawrence
et al.. 2015a). In this study, resampling of soils in eastern Canada and the northeastern
U.S. was done at 27 sites exposed to reductions in wet SO42 deposition of 5.7-76%, over
intervals of 8-24 year. Increases in pH were seen at most sites. Reductions in SO42
deposition were positively correlated with ratios of base saturation and negatively
correlated with exchangeable Al ratios.
A study by McDonnell et al. (2013) used the MAGIC model to evaluate soil BC status
for a group of 65 streams and their watersheds in the southern Blue Ridge physiographic
province of the southern Appalachian Mountains, U.S. Future S deposition reduction
scenarios (6, 58, 65, and 78% reduction), and various changes in timber harvest,
temperature, and precipitation were modeled. Each of the scenario projections indicated
that median year 2100 soil exchangeable Ca will be at least 20% lower than preindustrial
values. The simulations suggested that substantial mass loss of soil BC has already
occurred since preindustrial times. Soil BC pools in the study region are expected to
remain significantly below preindustrial conditions for more than 100 years into the
future, regardless of changes in climate, S deposition, or timber harvest.
Elliott et al. (2008) used NuCM to model three S deposition simulations: current, 50%
decrease, and 100% increase, at Joyce Kilmer (JK), Shining Rock (SR), and Linville
Gorge (LG) wilderness areas in the southern Appalachian Mountains, North Carolina,
U.S. Low Ca:Al ratios results suggest that forests at SR and LG are significantly stressed
under current conditions. The authors' results suggest that SO42 retention is low, perhaps
contributing to the high degree of acidification. The soils are very acidic and low in
weatherable minerals. Even with large reductions in SO42 and associated acid deposition,
it may take decades before these systems recover from depletion of exchangeable Ca,
Mg, and K. Due to the complexity of biogeochemical cycling processes, predicting the
susceptibility to (and recovery from) changes in long-term chronic or acute deposition
requires a modeling approach that is sufficiently mechanistic to represent the interactions
among vegetation, soils, and hydrologic fluxes.
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4.6.2
Critical Loads
4.6.2.1 Soil Acidification
The 2008 ISA included McNultv et al. (2007) a national assessment of soil critical loads
for acidification calculated by a SMBE technique (see Section 4.5.1.8. Table 4-10). No
new publications are identified in this review on the subject of national-scale sensitivity.
The uncertainty associated with the SMBE technique was discussed in a second
publication (Li and McNultv. 2007). In general, the SMBE predicted that 26% of U.S.
forest soils have critical loads less than 1,000 eq/ha/yr. Low critical loads outside of New
England, New York, and the Appalachian Mountain region are not necessarily
problematic to forest health because acid deposition is much lower across most of the
U.S. compared to these areas. Unfortunately, mountainous terrain comprises much of the
area with very low forest soil critical loads. Mountain forests receive some of the highest
local rates of acidic deposition.
Figure 4-10 is a map of soil CLs presented by McNultv et al. (2007) and updated with
newer SMB modeling, where it is available (McDonnell et al.. 2014b; Phelan et al. 2014;
Duarte et al.. 2013; Sullivan et al.. 201 lb; Sullivan et al.. 201 la). Duarte et al. (2013) is a
new evaluation of critical loads for terrestrial acidification in New England, U.S. The
steady-state mass balance method is applied at over 4,000 plots. The acceptable ANC
leaching rate, was calculated based on the critical chemical criteria of no change in base
saturation. Over 80% of the critical loads were between 850-2,015 eq/ha/yr. Phelan et al.
(2014) evaluated PROFILE using national data sets as a method to estimate BCw rates
for forests in the U.S., focusing on Pennsylvania as the first test state. The model paired
with national data sets was successfully applied at 51 forested sites across Pennsylvania.
The soil critical loads were evaluated using a Bc/Al value of 10.0. The CL values ranged
from 4 to 10,503 eq/ha/yr. Sullivan et al. (201 la) used the dynamic model MAGIC to
model terrestrial soil acidification in the Adirondacks, New York. Simulations were
based on one driver of acidic deposition (S) and included evaluation of CLs for soil
solution molar Bc/Al and Ca/Al ratio, two critical threshold levels (1 and 10), and two
endpoint years of model simulation (2050 and 2100). Statistically selected lakes (n = 44)
were modeled to represent a population of 1,320 sites. Nearly all (>93%) had a very low
TL (<25 eq/ha/yr for the year 2100) when the protection threshold is set to BC:A1 =10,
and the majority (>60%) had a high TL of (>100 eq/ha/yr for the year 2100) to achieve
Bc/AL = 1. Sullivan et al. (201 lb) calculated surface water CLs for 66 sites in the Blue
Ridge mountains (North Carolina, Tennessee and South Carolina). CL were reported for
surface waters; however, the MAGIC model was parameterized for all 66 sites including
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1 terrestrial geochemistry. McDonnell et al. (2014b , studied acidification in the Southern
2 Appalachians from northern Georgia to southern Pennsylvania, and from eastern
3 Kentucky and Tennessee to central Virginia and western North Carolina. Although soil
4 critical loads were not reported in the publication, soil solution data are reported in Figure
5 4-10.
Forest Ecosystems Critical Loads for Acidity
S + N eq/ha/yr
IH 170- 1,000
HI 1,001-2,000
~| 2,001-4,000
4,001-6,QQ0
6,001-8,800
States
No Data
eq = equivalent; ha = hectare; yr = year.
(A.) McNultv et al. (2007) critical loads are mapped at 1 km2 grids (center map). For uncertainty, see Li and McNultv (2007). (B.)
Duarte et al. (2013) critical loads are mapped at 4 km2 grids; (C. and D.) Phelan et al. (2014) critical loads are mapped for each
sampling site (Pennsylvania). McDonnell et al. (2014b); Sullivan et al. (2011b); Sullivan et al. (2011a) critical loads are mapped as a
single point at the center point of the watershed (New York and North Carolina).
Source: http://nadp.sws.uiuc.edu/committees/clad/db/NCLDMapSummarv 2015.pdf
Figure 4-10 Forest ecosystem critical loads for soil acidity related to base
cation soil indicators.
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4.6.2.2
Nitrate Leaching
Pardo etal. (201 lb) documented the threshold N deposition value which caused
increased NCh leaching from forest ecosystems into surface water was 8 to
25 kg N/ha/yr. This information is summarized by ecoregion (Omernick Level 1) in
Figure 4-11. At 4 kg N/ha/yr, increasing NOs was reported in the organic horizon in the
Colorado Front Range, which suggests incipient N saturation. In the northeastern U.S., N
budgets from 83 forested watersheds show that N retention averages 76% of incoming
atmospheric-N deposition and decreases from 90% retention for sites receiving
7 kg N/ha/yr to 60% retention for sites receiving 11 kg N/ha/yr (Aber etal.. 2003). The
highest critical loads were reported for Mediterranean California mixed-conifer forests.
Since the publication of Pardo etal. (201 lb), new work has been published on nitrate
leaching (see Section 4.3.2. New evidence from Europe by Disc et al. (2009) shows
approximately 95% of forests receiving less than 8 kg N/ha/yr have leaching of less than
1 kg N/ha/yr. In Sweden, Khalili et al. (2010) showed a clear sudden increase in NO?
leaching in regions where N deposition exceeded 7.5 kg/ha/yr.
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Empirical CL of N (kg ha1 y"1)
4-17 Northwest Forested Mountains
8 Northern Forests: Eastern Temperate Forests
| 10-17 Mediterranean California
10-25 Great Plains
CL = critical load; ha = hectare; kg = kilogram; N = nitrogen; yr = year.
The range of critical loads based on increased nitrate leaching for each ecoregion. The hatch marks indicate increasing level of
uncertainty: no hatch marks for the most certain "reliable" category and single hatching for the "fairly reliable" category. White areas
lack data for critical loads determination for nitrate leaching.
Source: Pardo et al. (2011b).
Figure 4-11 Map of critical loads for nitrate leaching by ecoregion in the U.S.
4.7 Summary
4.7.1 Sources
1 The effects of N and S deposition on soil biogeochemistry cause cascading effects on the
2 biological species. These effects are discussed in Chapter 5 and Chapter 6. In the 2008
Uncertainty
~ Reliable
[\^| Fairly Reliable
[t^>| Expert Judgment
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ISA, atmospheric deposition was identified as the main source of anthropogenic N to
nonmanaged terrestrial ecosystems. This has been confirmed by new studies on N
sources to U.S. lands and waterways, which find human-mediated N inputs are spatially
heterogeneous across the country, ranging from <1.0 to 34.6 times the rate of background
N input across the conterminous U.S. Synthetic N fertilizer and atmospheric N deposition
are the largest and second largest overall human-mediated N sources (the single largest
sources in 41 and 33% of HUC-8s, respectively). There is no new information published
on nonair sources of S in terrestrial ecosystems, S inputs from emissions to the
atmosphere are discussed in Chapter 2.
4.7.2 Soil Processes and Indicators
Soil N enrichment and soil acidification are occuring in senstitive ecosystems across the
U.S. at current levels of deposition. Soil acidification is a natural process that can be
accelerated by N and/or S deposition. There are a number of soil geochemical processes
associated with acidification (Section 43 and Table 4-12). Base cations counterbalance
acid anions. Base cations are added to a watershed by weathering and atmospheric
deposition and are removed by leaching and (perhaps temporarily) by uptake into
growing vegetation. Acidifying deposition can deplete exchangeable base cation pools in
soils where acid deposition is high relative to base cation input. The limited mobility of
anions associated with naturally derived acidity (organic acids and carbonic acid)
controls the rate of base cation leaching from soil where rates of atmospheric deposition
of S and N are low. Because inputs of S and N in acidifying deposition provide anions
that are more mobile in the soil environment than anions of naturally derived acids, these
inorganic acid anions accelerate rates of base cation leaching. In addition, the deposition
of reduced forms ofN (e.g., NHx) can stimulate nitrification, which is the microbial
oxidation of NH/ to NO, . This oxidation process acidifies soils because 2 moles of
hydrogen ion (H+) are released per mole of NH44" converted to NO? . Therefore, both
chemically reduced and oxidized forms of N and S deposition contribute to terrestrial
acidification. There are several useful indicators of soil acidification (Table 4-12).
including indicator thresholds related to biological responses, the biological basis of
which are discussed in Chapter 5.
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Table 4-12 Summary of key soil geochemical processes and indicators
associated with eutrophication and acidification.
Endpoint
N-Driven Nutrient
Enrichment
Acidification
The Effect of Deposition
PROCESS
N saturation
X
X
New empirical evidence suggests revising the N
saturation concept, now observed NO3" leaching can
occur even if the ecosystem N retention capacity has not
yet been saturated.
Soil N accumulation
X
X
New meta-analysis across ecosystem types confirms
inorganic soil NO3" concentration increases with N
addition. New gradient study confirms that N
concentration increases with N deposition. New addition
study confirms increased soil accumulation.
NO3" leaching
X
X
New meta-analysis confirms leaching increases with N
addition.
New regional-scale gradient analyses: <8 kg N/ha/yr
onset of leaching <1 kg N/ha/yr in European forests.
Second study suggests <7.5 kg N/ha/yr increases
leaching in Swedish forests.
New addition Study: 9 to 14 kg N/ha/yr increase in
inorganic N concentrations.
New USFS critical loads for the onset of leaching: 8 to
10 kg N/ha/yr in eastern and western U.S., 17 kg N/ha/yr
in the Sierra Nevada and San Bernardino Mountains.
S accumulation and
adsorption
X
Some soils (notably in many watersheds in the SE U.S.)
have the capacity to adsorb substantial quantities of S,
with essentially no acidification of drainage water.
Nevertheless, S adsorption capacity is finite and under
continual high S deposition loading, the adsorptive
capacity of soil will eventually be depleted.
New studies of 27 watersheds in the SE indicates most
will begin releasing SC>42"in the next two decades, and
northeastern watersheds show a net loss of S from soils
now in response to decreased levels of atmospheric S
deposition.
SO42" leaching
X
Atmospheric S deposition generally increases leaching of
SO42" to surface waters. The amount of deposition that
causes the onset of leaching varies across the landscape.
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Table 4-12 (Continued): Summary of key soil geochemical processes and
indicators associated with eutrophication and
acidification.
Endpoint
N-Driven Nutrient
Enrichment
Acidification
The Effect of Deposition
Base cation
release/depletion
X
Base cation (Ca, Mg, K, Na) release occurs in response to
the input of acid anions (SO42" and NO3") from deposition.
This proportional change in base cations relative to acid
anions from N and S deposition is called the F-factor.
New studies confirm base cation depletion continues to
occur in the Rocky Mountains (threshold 28 kg N/ha/yr)
and in U.K grasslands, while in a northeastern forest, 17
years of N addition did not cause further depletion. A
meta-analysis indicates cation depletion occurs early after
increased deposition of acid anions, which tapers off with
time.
Al mobilization X
<15 to 20% soil base saturation is the threshold for
inorganic Al mobilization from soil. This is an extremely
important effect of acidifying deposition because inorganic
monomeric Al, including Al3+ and various hydroxide
species, is toxic to biota (Chapter 5). Inorganic Al is
minimally soluble at pH about 6.0, but solubility increases
steeply at pH values below about 5.5.
There have been no new studies on Al mobilization.
Nitrification X X Nitrification releases 2 mol hydrogen ion (H+) per mol
NH4+ converted to NO3", acidifying soils. As soil inorganic
N accumulates, net nitrification rates often increase, and
NO3" can leach from the ecosystem.
New N gradient and meta-analysis studies confirm N
addition increases nitrification.
Denitrification X Denitrification is the microbial reduction of NO3" to nitrite
(NO2"), nitric oxide (NO), the greenhouse gas nitrous
oxide (N2O) and N2, which occurs under anaerobic
conditions. In Europe, soil switched from a source to a
sink after two decades of N deposition exclusion.
New meta-analysis confirms N addition increases
denitrification rates.
DOC leaching X X Acidity of some surface waters is partly regulated by DOC
concentrations. Soil acidification can suppress the natural
production of DOC. In recent years, the DOC
concentration of some lakes and streams has risen, with
adjacent terrestrial ecosystems as the DOC source.
However, the mechanism for this increase is unclear. It
may be due to soil recovery from acidification or N
deposition effects on decomposition.
New studies include a meta-analysis and field addition
studies.
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Table 4-12 (Continued): Summary of key soil geochemical processes and
indicators associated with eutrophication and
acidification.
Endpoint
N-Driven Nutrient
Enrichment
Acidification
The Effect of Deposition
Decomposition/
mineralization
X
X
Decomposition rates correlate with ratios of C:N, lignin:N,
or lignin:cellulose in litter. The addition of N can stimulate
the decomposition of labile compounds that degrade
during the initial stages of decomposition, but added N
can suppress the decomposition of more recalcitrant
material. Evidence for this is widespread in forests, but
has not yet been well documented in grasslands and other
ecosystems.
There are new addition studies and meta-analysis to
better understand the mechanisms and response trends.
INDICATOR
Soil [N]
X
X
Increasing N deposition increases concentration of N in
soil and reflects soil N accumulation that may be
assimilated by organisms or mobilized via leaching.
Soil C:N ratio
X
X
Increasing N deposition decreases the C:N in plant tissue,
causing cascading effects during decomposition on
microbial transformation, especially nitrification, leading to
increased NO3" leaching.
THRESHOLD: <20 to 25 associated with elevated rates of
nitrification and elevated risk of nitrate leaching in the U.S.
and <25 to 30 for increased NO3" leaching in Europe.
Soil base saturation
X
Increasing N + S deposition decreases the soil pool of
exchangeable base cations.
THRESHOLD: <15 to 20% is the value at which exchange
ion chemistry is dominated by inorganic Al and may cause
iniurv to veaetation (see Chapter 5).
Soil Bc:AI ratio
X
Increasing N + S deposition decreases the soil pool of
exchangeable base cations, often decreasing the Ca:AI
ratio.
THRESHOLD: Ca:AI <1.0 to 10 causes physiological
stress, decreased growth and survival of sensitive plant
species (see Chapter 5).
Fungi-to-bacteria
ratio
X
New indicator since 2008 ISA: Increasing N deposition
decreases the fungi-to-bacteria ratio and causes a
transition from N to C limitation among soil food webs.
Al = aluminum; Be = base cation; C = carbon; Ca = calcium; DOC = dissolved organic carbon; H+ = hydrogen ion; ha = hectare;
K = potassium; kg =kilogram; Mg = magnesium; N = nitrogen; N2 = molecular nitrogen; N20 = nitrous oxide; NE = northeast;
NH4+ = ammonium; NO = nitric oxide; N02" = nitrite; N03" = nitrate; S = sulfur; SE = southeast; yr = year.
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It is clear from Table 4-12 that some of the same processes and indicators associated
with acidification are also associated with N enrichment. The N enrichment of terrestrial
soils occurs in response to the input of exogenous N. The new studies on N deposition
contribution to total N loading in terrestrial U.S. ecosystems are discussed in Section 42.
The 2008 ISA documented that the increase in global Nr over the previous century was
largely due to three main causes: (1) widespread cultivation of crops that promote
conversion of N2 gas to organic N through biological N fixation; (2) fossil fuel
combustion converting atmospheric N2 and fossil N to NOy; and (3) synthetic N fertilizer
production via the Haber-Bosch process, which converts nonreactive N2 to Nr to sustain
food production and some industrial activities (Galloway et al.. 2003; Gallowav and
Cowling. 2002).
The 2008 ISA documented that most N, often more than 85% of the total ecosystem N, is
stored in the soil in temperate forest ecosystems. Soil N is primarily contained in organic
matter, typically bound in humic material or organic-mineral complexes that are resistant
to microbial degradation. There is new evidence that litter is the largest N pool in
grasslands, shrublands, and wetlands (Section 4.3.1). The ability of atmospheric
deposition to increase soil N is indicated by a positive correlation between atmospheric
deposition levels and total N concentration in the upper soil horizon. Soil N accumulation
is linked to increased N leaching and decreased N retention (Section 4.3.2). Thresholds of
N deposition that are associated with the onset of elevated NO.? leaching are discussed in
Section 4.6.2.2 and summarized in Table 4-12.
The 2008 ISA documented the conceptual model of N saturation, which occurs when N
input to terrestrial ecosystems exceeds the uptake capacity of the soils and biota, with the
onset of increased soil N leaching indicating an inability of an ecosystem to retain N and
the state ofN saturation. However, more recent work suggests thatN leaching from soil
can precede the complete saturation of the biotic and abiotic processes that retain N,
indicating that the conceptual model of N saturation needs to be revised (Section 4.3.2).
Lovett and Goodale (2011) proposed a model of N saturation that distinguished capacity
N saturation from kinetic N saturation. In capacity N saturation, the vegetation and soil
sinks for N have been filled. In kinetic N saturation, the plant and soil sinks are
accumulating N but the rate of N accumulation is slower than the N input rate. One
implication of this new model is that NO3 leaching can occur even if the ecosystem N
retention capacity has not yet been saturated, as is observed at many sites and supported
by several new studies. Although N leaching may occur prior to saturation, N budgets
from 83 forested watersheds in the northeastern U.S. show that N retention averages 76%
of incoming N deposition. Nitrogen retention decreases from 90% retention for sites
receiving 7 kg N/ha/yr to 60% retention for sites receiving 11 kg N/ha/yr, suggesting a
range of response in which leaching is exacerbated in this region (Aberetal.. 2003).
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The 2008 ISA documented that N enrichment alters rates of microbial transformation of
chemicals in the soil, such as increased rates of nitrification and denitrification, and
altered rates of decomposition. The addition of N to terrestrial ecosystems can increase
nitrification, an important process for soil acidification and the production of NO, . The
rate of nitrification is controlled by numerous factors including: substrate availability
(presence of NH4+), aeration (availability of O2), and pH (near neutral). Nitrification is
often stimulated in soils with a C:N ratio below approximately 20 to 25, and N deposition
often causes the ratio to fall to these values. The NO3 created by nitrification may be
leached or denitrified. In terrestrial ecosystems, denitrification of NO3 mainly occurs in
soils, groundwater, and riparian zones. Soil denitrification is extremely variable in time
and space due to variability of N substrates and oxygen. Several syntheses have been
published since 2008 evaluating N addition effects on denitrification and nitrification in
terrestrial ecosystems (Section 4.3.6). A new meta-analysis shows N addition
significantly increases denitrification from many types of ecosystems (coniferous forest,
deciduous forest, tropical forest, wetland, grassland), except heathlands. Among the five
chemical forms of N fertilizer, NO3 showed the strongest stimulation of N2O emission, a
product of denitrification. A second meta-analysis, using data extracted from 206
peer-reviewed papers, confirms N addition stimulates nitrification (154%), N2O
emissions (134%), and denitrification (84%).
There have been several new meta-analyses published since 2008 on N addition effects
on belowground carbon cycling (Section 4.3.10). The meta-analyses integrate
information from numerous pools to improve the understanding of how N addition alters
the belowground carbon cycle. About half of C fixed annually by terrestrial vegetation is
allocated to belowground C pools; therefore, it is important to understand how N affects
belowground C to better understand changes in plant physiology, plant growth, and
ecosystem C cycling (Chapter 6). Many studies have shown that the belowground C cycle
does not always match the aboveground C cycle. The disparity between aboveground and
belowground processes indicates that it is inappropriate to extrapolate from aboveground
responses to belowground processes. In general, N addition increases aboveground litter
inputs (+20%), inhibits CO2 loss via microbial respiration (-8%), and decreases
microbial biomass carbon (-20%). However, dissolved organic carbon concentrations
increase (+18%), suggesting C leaching loss may increase. The addition of N increases
the C pool size within the soil organic horizon (+17%). This increase is attributed to both
increased litter input and decreased decomposition (inferred from the lower microbial
respiration rates).
The effects of N on decomposition, which is the breakdown of organic matter, is an
active area of research (Section 4.3.7V Within the soil microbial community, bacteria and
fungi are the primary decomposers of organic matter. Both microbial community
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composition (see Chapter 6) and microbial enzyme activity can respond dynamically to
shifts in inorganic nutrient and substrate availability, reflecting the nutrient and energy
limitation of the microbial community. Litter decay rates are also well established to
correlate with ratios of C:N, lignin:N, or lignin:cellulose in litter. These chemical traits
have been shown to account for over 73% of the variation in litter decomposition rates
worldwide. Based on these observations, it could be assumed that added N would
stimulate decomposition and the loss of C from soil pools. However, there is now
widespread evidence that the stimulatory effects of N on decomposition are limited to the
early stages of mass loss, when more labile compounds are degraded. During the later
stages of decomposition when the rates of mass loss are slow and controlled by the
degradation of recalcitrant compounds, the addition of N slows decomposition. This
slowing of decomposition appears to be a consequence of decreases in the production of
some extracellular enzymes by fungi. It is clear that N additions generally decrease
respiration from soil heterotrophs, but this may not decrease total soil respiration because
heterotrophic respiration accounts for only a portion of soil CO2 efflux.
4.7.3 Monitoring
Several new studies use long-term monitoring data sets. There are new analysis of
45 years of biogeochemical monitoring data (Yanai etal.. 2013) and Sulfur accumulation
(Mitchell and Likens. 2011) at the Hubbard Brook Experimental Forest LTER New
Hampshire, U.S. At the southern Rocky Mountains Niwot Ridge LTER, Colorado, U.S.,
Lieb etal. (2011) identify the effects of a decade of simulated N deposition.
Yanai et al. (2013) evaluated 45 years of biogeochemical monitoring data at the Hubbard
Brook Experimental Forest LTER, New Hampshire, U.S. Since 1992, the ecosystem
shifted to a net N sink of ~8 kg N/ha/yr. Mitchell and Likens (2011) examines sulfur
accumulation observed in over four decades of continuous long-term record for four
watersheds (reported in Section 4.3.3). At the Niwot Ridge LTER, Colorado, U.S., Lieb
et al. (2011) found that a decade of simulated N deposition to alpine ecosystems caused
ongoing changes in diversity and soil biogeochemistry, including lower soil acid
buffering capacity, decreased concentrations of Mg2+, and increased concentrations of the
potentially toxic cations Mn and Al3+. Their results suggested an N deposition threshold
of 28 kg N/ha/yr.
There are new studies on long-term monitoring in Europe, including investigations of S
dynamics in England (Lehmann et al.. 2008) and N and S dynamics in Switzerland
(Pannatier et al.. 2011). In Sweden, khalili et al. (2010) examined N and C interactions
between boreal soils and lakes. Lehmann et al. (2008) found that a soil response to SO2
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emissions was to shift to more oxidized organic S. This reaction proceeded much more
rapidly than did the reverse reaction when atmospheric emissions and deposition were
reduced. Pannatier et al. (2011) examined monitoring at Swiss Long-Term Forest
Ecosystem Research sites and found BC, SO42 , and inorganic N in soil solution reacted
very little to the changes in atmospheric deposition. A stronger reduction in base cations
compared to Al3+ was detected at two sites, which might indicate that acidification of the
soil solution was proceeding faster at these sites. In Sweden, Khalili et al. (2010) found a
significant relation between C:N ratios of the organic soil layer and C in lake waters, and
a clear sudden increase in NO3 leaching regions where N deposition exceeded
7.5 kg N/ha/yr.
4.7.4 Models
The most commonly used ecosystem models in the U.S. were described in the 2008 ISA.
Here we focus on the several primary models that are currently being used in the U.S. to
assess the effects of S and N deposition on terrestrial ecosystems. One important input to
these models are estimates of base cation weathering (BCw). There are new updates on
two methods to estimate this parameter: Soil Texture Approximations (STA) and
PROFILE. Steady state models include steady-state mass balance equations (SMBE),
while dynamic models include the Very Simple Dynamic (VSD) soil acidification model,
MAGIC, NuCM, PnET/BGC, and DayCent-Chem.
Base cation weathering rate is one of the most influential yet difficult to estimate
parameters in the calculation of critical acid loads of nitrogen (N) and sulfur (S)
deposition for terrestrial systems. As discussed in Section 4.3. acidifying deposition
causes base cation leaching from soil. The supply of base cations is replenished by base
cation weathering of minerals from rock within the ecosystems. Obtaining accurate
estimates of weathering rates is difficult because weathering is a slow process estimates
on an ecosystem's ability to buffer acid deposition rely on accurate estimates of
weathering. Commonly used models include STA, a simple empirical steady-state model
with low data requirements, and PROFILE, a mechanistic, steady-state kinetics model
that requires 26 input parameters. There is some new work on estimating BCw. koseva et
al. (2010) confirm that the STA equations were produced for young soils that developed
following the Late Wisconsin glaciation. The clay correlation-substrate model that is
based on clay content and parent material acidity may not be suitable for older, more
weathered soils that were not impacted by the most recent glaciation and which cover the
majority of the U.S. (U.S. EPA. 2009c). The larger data set required to run PROFILE
prohibits applying the model to many parts of the U.S. However, a recent soil
geochemical data set compiled by the USGS has made it possible to apply PROFILE in
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the U.S. The initial application in 51 forested sites across Pennsylvania indicates this
technique may be appropriate for applications across the U.S. (Phelan et al.. 2014). The
uncertainty associated with the calculation of BCw has recently been evaluated by Futter
et al. (2012). who found that estimated contribution of model parameter uncertainty to
overall variability related to PROFILE and MAGIC (a dynamic model that typically uses
PROFILE for initial estimates of BCw) were relatively small, ranging from 1.7 to 2.1,
and that lower weathering rate estimates are shown from PROFILE in comparison to
MAGIC. This is expected because PROFILE provides estimates for a shallow
one-dimensional soil whereas MAGIC integrates weathering processes for the whole
catchment including deep soil weathering.
Estimates of BCw are input parameters in soil acidification models. The simplest are the
steady-state mass balance models. The 2008 ISA documented a model based on simple
mass-balance equations (SMBE) to assess critical loads for acidification in forest soils
(McNultv et al.. 2007). This study estimated critical acid load and exceedance for forest
soils at a 1-km2 spatial resolution across the conterminous U.S. A second publication
discussed the uncertainties associated with this model and national-scale assessment (Li
and McNultv. 2007). The authors quantified uncertainty under natural variability in
17 model parameters and determined the relative contributions in predicting critical
loads. The results indicated that uncertainty in the critical load came primarily from
components of BCw (49%) and acid neutralizing capacity (46%), whereas the most
critical parameters were BCw base rate (62%), soil depth (20%), and soil temperature
(11%). The authors concluded that improvements in estimates of these factors are crucial
to reducing uncertainty and successfully scaling up SMBE for national assessments.
Posch etal. (2011) discusses a regional application of SMB models, while several other
studies using SMB have been published to determine acidification critical loads based on
critical limits of BC:AL and ANC leaching (Phelan et al.. 2014; Duarte et al.. 2013; Jung
et al.. 2013; Whitfield and Watmough. 2012; Forsius et al.. 2010; McNultv and Boggs.
2010; Nasretal.. 2010). These critical loads are discussed in Chapter5.
Dynamic models are typically applied to much smaller spatial areas than steady-state
models because they require more data and parameterization. The VSD model is the
simplest extension of the steady-state SMB model into a dynamic model, which is done
by including cation exchange and time-dependent N immobilization (accumulation). The
VSD model is designed for sites with few data available and applications on a large
regional or continental scale. The model has a short execution time that allows rapid
scenario analyses and the calculation of target loads (i.e., deposition targets), which result
in a desired chemical condition in the soil (solution) in a specified year. Posch and Reinds
(2009) have developed a version of the V SD for steady-state critical load applications at
the regional scale. Although simpler than other widely used models, such as MAGIC and
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SAFE, VSD contains the basic physical and chemical relationships common to all these
models. However, the model's simplicity also means that some processes have either
been left out altogether (e.g., SO42 sorption) and others strongly simplified (e.g., N
processes). As a consequence, VSD is not suited for sites where SO42 adsorption is
important. Furthermore, the simple description of N processes does not allow simulating
decreasing soil N pools (and increasing C:N ratios) under reduced N inputs.
The ForSAFE model (Wallman et al.. 2005) simulates the cycles of carbon, nitrogen,
base cations (Be), and water in a forest ecosystem, while simultaneously simulating soil
chemistry, tree growth, and soil organic matter accumulation or depletion. ForSAFE
requires site-specific inputs of the physical properties of the soil (including mineralogy,
hydrological parameters, density, depth and stratification), tree type, and time series of
atmospheric deposition and climatic data (temperature, light, and precipitation). The
model gives monthly estimates of weathering rates, soil moisture, soil solution
concentrations, uptake fluxes of N and Be, litterfall, decomposition and mineralization, as
well as photosynthesis and growth rates. ForSAFE-VEG is a composite model in which
the VEG module (Sverdrup et al.. 2007) reads a set of five drivers (soil solution pH, Be
concentration, N concentration, ground level light, soil moisture) from ForSAFE, in
addition to air temperature, and uses them to estimate the relative abundance of a set of
indicator plants at the site. The result is a model chain that can link changes in
atmospheric deposition, climatic conditions, and land use to responses in the
biogeochemistry and plant community composition at the site level, both historically and
in the future. The new study published in this area is Belvazid et al. (201 la), which
revealed limitations in the model simulation of nitrogen concentrations in soil solution.
The authors conclude the biogeochemical model platform must be improved to simulate
N processes more accurately before being applied to calculate critical loads. The model
overestimated the actual N concentrations in the soil solution. Several new applications
of ForSAFE-VEG were published l( McDonnell et al.. 2013; Sverdrup et al.. 2012;
Belvazid et al.. 201 la); Results discussed in Chapter 5 and Chapter 61.
MAGIC (Cosbv et al.. 1985a; Cosbv et al.. 1985c; Cosbv et al.. 1985b) is one of the most
well-known dynamic models of aquatic acidification. It is a lumped-parameter model of
soil and surface water acidification in response to atmospheric deposition based on
process-level information about acidification. The data requirements required to run
MAGIC are high. The equations that characterize the chemical composition of soil water
in MAGIC contain 33 variables and 21 parameters. Data required to conduct dynamic
modeling are not available for as many places as the data required to conduct steady-state
modeling. An update to MAGIC by Oulehle et al. (2012) presented a new formulation
that uses decomposer dynamics to link N cycling to C turnover in soils. In comparisons
with earlier versions, the new formulation more correctly simulates observed short-term
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changes in NCh leaching, as well as long-term retention of N in soils. The authors state
that the new formulation gives a more realistic simulation of observed changes in N
leaching. The new formulation also provides a reasonable simulation of the long-term
changes in C and N pools (and C:N ratio) with SOM.
PnET-BGC is an integrated forest-soil-water model that has been used to assess the
effects of air pollution and land disturbances on forest and aquatic ecosystems. The
Nutrient Cycling Model (NuCM) was developed to synthesize current understanding of
nutrient cycling in forests and to predict how forests respond to changing S and N
atmospheric deposition rates. No revisions to these models have been identified.
4.7.4.1 Comparative Analyses
Tominaga et al. (2009) used HBEF, New Hampshire, U.S., as the setting to evaluate the
performance of three uncalibrated process-oriented models. They performed a Monte
Carlo multiple-model evaluation framework of the dynamic models: MAGIC, SAFE, and
VSD. The greatest differences in model outputs were attributed to the cation exchange
submodel, with Gapon-exchange based models retaining more base cations on the
exchange complex and releasing less into solution, resulting in lower soil solution ANC
values. Given the same deposition scenario, the three models (without calibration)
simulate changes in soil and soil solution chemistry differently, but the basic patterns
were similar.
4.7.5 National-Scale Sensitivity
The 2008 ISA documented that by the end of the 1980s, after nearly a decade of intensive
research performed under the original NAPAP, the regions of the U.S. with many
acid-sensitive waters and ecosystems were well recognized. These acid-sensitive
ecosystems are generally located in upland, mountainous terrain in the eastern U.S. and
are underlain by bedrock that is resistant to weathering, such as granite or quartzite
sandstone. However, a similar work characterizing areas sensitive to the eutrophication
effects of nitrogen is not available. Typically, all terrestrial ecosystems are sensitive to N
deposition.
There is strong evidence to show that biogeochemical sensitivity to deposition-driven
eutrophication and acidification is the result of historical loading, geologic/soil conditions
(e.g., mineral weathering and S adsorption), and nonanthropogenic sources of N and S
loading to the system. There is no single deposition level applicable to all ecosystems in
the U.S. that will describe the onset of eutrophication or acidification, ecosystem
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sensitivity is heterogeneous. There are three new publications commenting on recovery of
terrestrial ecosystems from acidification at the national scale (NAPAP. 2011).
specifically in the Northeast (Lawrence et al.. 2015a). and the lack of recovery in the
southern Appalachian Mountains (McDonnell et aL 2013). Work on national-scale soil
acidification published in 2007 remains the most recent national assessment of this effect
(McNultv et al.. 2007). however, Figure 4-10 is a map of soil CLs which updates
McNultv et al. (2007) with newly available modeling (McDonnell et al.. 2014b; Phelan et
al.. 2014; Duarte et al.. 2013; Sullivan et al.. 201 lb; Sullivan et al.. 201 la).
A new critical loads for nitrate leaching in forest ecosystems by Pardo et al. (2011b)
ranges from 8 to 25 kg N/ha/yr across ecoregions (Omernick Level 1) in the U.S. (Figure
4-11). At 4 kg N/ha/yr, increasing NO, was reported in the organic horizon in the
Colorado Front Range, which suggests incipient N saturation. In the northeastern U.S., N
budgets from 83 forested watersheds show that N retention averages 76% of incoming
atmospheric-N deposition and decreases from 90% retention for sites receiving
7 kg N/ha/yr to 60% retention for sites receiving 11 kg N/ha/yr (Aber etal.. 2003). The
highest critical loads were reported for Mediterranean California mixed-conifer forests.
Since the publication of Pardo etal. (2011b). new work has been published on nitrate
leaching (see Section 4.3.2). New evidence from Europe by Disc et al. (2009) shows
approximately 95% of forests receiving less than 8 kg N/ha/yr have leaching of less than
1 kg N/ha/yr. In Sweden, Khalili et al. (2010) showed a clear sudden increase in NO?
leaching in regions where N deposition exceeded 7.5 kg/ha/yr.
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CHAPTER 5 BIOLOGICAL EFFECTS OF
TERRESTRIAL ACIDIFICATION
This chapter characterizes the biological effects of acidifying deposition of nitrogen (N)
and sulfur (S) to terrestrial ecosystems. Section 52, discusses effects on trees and forests
(Section 5.2.1). understory plants and grasslands (Section 5.2.2). lichens (Section 5.2.3).
soil biota (Section 5.2.4). and fauna (Section 5.2.5). The characteristics, distribution and
extent of sensitive ecosystems is presented in Section 53. Next, Section 54 presents the
application of terrestrial acidification models. Finally, levels of deposition at which
effects are manifested is discussed in Section 5^5, including a discussion of critical loads
(Section 5.5.3). A summary section with causal determinations based on a synthesis of
new information and previous evidence of biological effects of terrestrial acidification is
presented in Section 5JS.
5.1 Introduction
Changes in biogeochemical processes caused by acidifying deposition of N and S to
terrestrial systems (Chapter 4) are linked to changes in terrestrial biota and have
significant ramifications for biological functioning of these ecosystems. In the 2008 ISA
for Oxides of Nitrogen and Oxides of Sulfur—Ecological Criteria (hereafter referred to as
the 2008 ISA), the evidence was sufficient to infer a causal relationship between
acidifying N and S deposition and changes in terrestrial biota. The strongest evidence for
a causal relationship comes from studies of terrestrial systems exposed to elevated levels
of acidifying deposition that show decreased plant health, reduced plant vigor, and/or loss
of terrestrial biodiversity. In multiple studies, consistent and coherent evidence has
shown that acidifying deposition can affect terrestrial ecosystems by causing direct
effects on plant foliage and indirect effects associated with changes in soil chemistry
(Section 3.2.2.3 of 2008 ISA). Biological indicators with reported responses to acidifying
deposition and conditions created by acidifying deposition include forest trees, shrubs,
lichens, grasslands, and Arctic and alpine tundra.
Acidifying deposition can affect terrestrial ecosystems via direct effects on plant foliage
and indirect effects associated with changes in soil chemistry (Figure 5-1). Biological
effects of acidification on terrestrial ecosystems are generally attributable to aluminum
(Al) toxicity and decreased ability of plant roots to take up base cations (especially
calcium |Ca|) and water from the soil (Cronan and Grigal. 1995). Acidifying deposition
to acid-sensitive soils can cause soil acidification, increased mobilization of Al from soil
to drainage water, and depletion of the pool of exchangeable base cations in the soil.
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Effects on the soil and direct effects of acidifying deposition on foliage can influence the
response of plants to climatic stresses such as drought and cold temperature. The effects
of acidifying deposition can also influence the sensitivity of plants to other stresses,
including insect pests and disease (Joslin et al.. 1992).
Since publication of the 2008 ISA, the overarching understanding of terrestrial
acidification has not appreciably changed. More recent research has confirmed and
strengthened this understanding and provided more quantitative information, especially
across the regional landscape. This chapter highlights findings from the literature after
the completion of the 2008 ISA. A number of studies have evaluated the relationships
between soil chemistry indicators of acidification and ecosystem biological endpoints
(Table 5-1). Soil chemistry indicators examined in recent literature include exchangeable
base cations, soil pH, exchangeable acidity (hydrogen ions [H+] and Al), exchangeable
Ca:Al ratio, base saturation, and Al concentrations. Biological endpoints evaluated
included physiological responses of trees and other vegetation, lichens, soil biota, and
fauna. Trees and other vegetation included sugar maple (Acer saccharum), red spruce
(Picea rubens), yellow birch (Betula alleghaniensis), American beech (Fagus
grandifolia), American basswood (Tilia americana), black cherry (Prunus seritona),
eastern hophornbeam (Ostrya virginiana), white ash (Fraxinus americana), hickories
(Carya spp.), northern red oak (Quercus rubra), and forest understory, grassland, and
alpine plant species. Table 5-2 provides a summary of the soil chemistry
indicator-biological endpoint relationships that have been evaluated in the literature since
the 2008 ISA. The 2008 ISA only considered changes in vegetation in the analysis of
how acid deposition affected terrestrial ecosystems. More recent research has quantified
effects on fauna (e.g., birds, snails) and soil biota (Section 5.2.5V
Together with the information available in the 2008 ISA, this body of evidence is
sufficient to infer a causal relationship between acidifying N and S deposition and
the alteration of the physiology and growth of terrestrial organisms and the
productivity of terrestrial ecosystems. Further,the body of evidence is sufficient to
infer a causal relationship between acidifying N and S deposition and the alteration
of species richness, community composition, and biodiversity in terrestrial
ecosystems.
February 2017
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Table 5-1 Mode of action for acidifying nitrogen and sulfur deposition.
Ecosystem
Reference Type/Region Species
N and S
Deposition/
Additions
Soil Indicator
Description
Bardhan et al.
(2012)
Forest
Great Smoky
Mountain
National Park,
TN, NC
Soil
microbes
(bacteria)
6 to 41 kg S/ha/yr
modeled
deposition classes
(Weathers et al..
2006)
Soil pH and
exchangeable Ca
and Al, CEC and
base saturation
(O-, A-, and
B-horizons)
Only minor differences in bacterial diversity among sites; the bacterial
community did not change along the gradients of S deposition, soil pH, or
exchangeable Ca:AI ratio. High elevation sites remain acidic and have not
yet reached a threshold suitable for nonacidophilic bacterial communities.
Beier et al.
(2012)
Forest
Adirondack
Mountains, NY
(12 upland
hardwood
forests)
NA 14.57 to 19.7
kg/ha/yr as wet
NOs"; 17.44 to
29.09 kg/ha/yr as
wet SO42",
modeled (Ito et
al.. 2002)
1990-1999
Exchangeable Ca
and pH (Oa- and
B-horizons)
Increasing trends in snail community richness and abundance, live
biomass of redback salamanders, and canopy tree basal area with
increasing soil Ca. Land snail species richness and abundance were
positively correlated with Oa-horizon Ca and negatively related to SO42"
deposition. Salamander communities changed continuously along the Ca
gradient. Several known calciphilic species of snails and plants were
found only at the highest Ca sites. The proportion of basal area attributed
to standing dead trees decreased significantly with Oa-horizon Ca.
Bilodeau-
Gauthier et al.
(2011)
Forest
Quebec lakes
network,
Quebec,
Canada
(6 watersheds)
Sugar
maple
NA
Soil pH, base
saturation,
exchangeable
Ca:AI ratio,
exchangeable Al,
Ca, Mg, Mn, and K
(forest floor and 0
to 15 cm of
B-horizon)
Tree growth was positively correlated to concentrations of base cations
(Ca, K, and Mg) in wood and soil, and negatively correlated to
concentrations of acidic metals in wood (Al, Mn, and Cd) and soil (H+ and
exchangeable Al). Percentage base saturation was the best predictor of
BAI (nonlinear) and explained 43% of variance. Multifactorial
relationships indicated that tree age and soil exchangeable Al accounted
for 51% and tree age and log of the ratio of base cations (Ca + Mg + K): Al
in the soluble (water and acid soluble wood extracts) fractions accounted
for 46% of the variation in sugar maple BAI.
February 2017
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Table 5-1 (Continued): Mode of action for acidifying nitrogen and sulfur deposition.
Reference
Ecosystem
Type/Region
Species
N and S
Deposition/
Additions
Soil Indicator
Description
Chen et al.
(2013)
Grassland
Mongolian
steppe, China
Soil
microbes
(bacteria,
fungi, and
nematodes)
Seven treatments
of S additions as
sulfuric acid (0,
2.76, 5.52, 8.28,
11.04, 13.8, and
16.56 mol H+/m2)
as three additions
(2009-2010)
Soil pH and
extractable cations
(Al, Ca, Mg, and
NA; Oto 15 cm)
Fungal fatty acids were increased by 49% and fungi:bacteria ratio
increased by up to 120% by the H2SO4 additions, relative to the controls.
The H2SO4 treatments decreased total and bacterial fatty acids by up to
47 and 40%, respectively. These responses were attributed to soil pH
and Al3+ concentrations. High Al3+ concentrations (51 to 83 mg/kg) were
associated with decreased total fatty acids and decreases in bacterial and
increases in fungal fatty acids. Soil nematode numbers were initially
increased by the H2SO4 treatments followed by changes in the nematode
community. The shifts in the nematode community were attributed to
decreased soil pH and changes in soil moisture.
Cleavitt et al.
(2014)
Forest
Hubbard Brook
Experimental
Forest, NH
Sugar
maple
NA
Exchangeable Ca
(top 5 cm of
B-horizon)
Soil Ca concentration exhibited a ninefold change across the study sites
and was positively correlated to sugar maple abundance and initial
seedling densities. However, soil Ca concentration was not a significant
predictor of first-year mortality, nor was it a factor that distinguished
among the three main site types.
Duchesne
and Ouimet
(2009)
Forest
southern
Quebec,
Canada
(426 monitoring
plots)
Sugar
maple and
American
beech
NA
Soil pH,
exchangeable K,
Ca, Mg, H and Al
(upper B-horizon)
The basal area of sugar maple in the sapling stratum was positively
correlated with soil exchangeable Ca and Mg. Basal area of American
beech in the sapling stratum was negatively correlated with exchangeable
Ca and Mg. However, the basal area of sugar maple in the sapling
stratum was positively correlated with both the relative basal area of dead
sugar maple and sugar maple in the tree stratum. The basal area of
American beach was also positively correlated with the relative basal
area of American beech in the tree stratum.
Elias et al.
Forest
Hardwood NA
Soil pH, base
Found that hickories were the only species to be in significantly lower
(2009)
Monongahela
National Forest,
and conifer
saturation,
numbers on sites with base saturation below 20 (A-horizon) and 2.5%
tree species
exchangeable
(B-horizon). Percent of dead northern red oak was highest on sites with
WV (FIA plots)
Ca:AI (A- and
A-horizon Al concentrations above 43 cmolc/kg of soil. Soil exchangeable
B-horizons)
Ca:AI and sum of base cations in the B-horizon were highest in stands
that experienced the lowest species turnover rates (1989-2000). Periodic
mean annual volume increment (whole stand) was positively correlated
with A-horizon base saturation (range of 5 to 77%), Ca concentrations,
and exchangeable Ca:AI (range of 0.17 to 10.2) and B-horizon pH. The
exchangeable Ca:AI of the A-horizon accounted for over 30% of the
variation in the periodic mean annual volume increment.
February 2017
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Table 5-1 (Continued): Mode of action for acidifying nitrogen and sulfur deposition.
Reference
Ecosystem
Type/Region
Species
N and S
Deposition/
Additions
Soil Indicator
Description
Gilliam et al.
(2011b)
Forest
Fernow
Experimental
Forest, WV
Soil
microbes
(bacteria
and fungi)
NA
Soil pH (5 cm) Fungi were dominant at the most weathered, low NO3" site, while
Gram-negative bacteria were significantly higher at the less weathered,
moderate and high NO3" sites. Accordingly, the fungi:bacteria ratio
increased in the direction of the low NO3" plots in ordination space.
Correlations between the soil parameters and PLFA results suggest that
low soil pH and NO3" concentrations supported fungal dominance,
although other factors including differences in plant community and clay
and organic matter content may have also influenced the soil microbial
community.
Horslev et al.
(2008)
Forest
Pennsylvania,
New York, New
Hampshire, and
Vermont
(86 northern
hardwood
stands)
234 forest
understory
species
NA
Found that a base cation-acid cation nutrient gradient accounted for
71.9% (in NH and VT) and 63% (in PA and NY) of the variation in the
nonmetric multidimensional scaling ordination analyses of plant
community composition. Sugar maple foliar Mg and Ca had the strongest
association with the base end of the gradient. Exchangeable Al (in NH
and VT) and foliar Mn (in PA and NY) were strongly associated with the
acid end of the gradient. A total of 50 of the 234 understory species were
associated with the base end of the base cation-acid cation nutrient
gradient.
Long et al. Forest Sugar
(2009) Pennsylvania, maple and
New York, New black cherry
Hampshire, and
Vermont
(76 sites)
NA
Soil Ca:AI
(threshold of 0.03;
upper B-horizon)
Exchangeable Ca, Mg, and pH in upper B-horizon were positively
correlated with sugar maple BAI growth in 1987-1996. Generally, in
long-term trends (1937-1996), sugar maple in stands with
below-threshold amounts of foliar Ca or Mg and above-threshold amounts
of Mn had decreasing BAI trends, while stands with above-threshold Ca
and Mg and below-threshold Mn showed a leveling off of the BAI. Black
cherry consistently showed greater growth on stands with
below-threshold foliar Ca and Mg compared with above-threshold stands.
Black cherry BAI was also greater in stands with below-threshold Ca:AI
molar ratios in the upper B-horizon.
Lucash et al.
(2012)
Forest
19 sites in
northeastern
U.S. (New York
and New
Hampshire)
Hardwood NA
and conifer
tree species
Exchangeable Ca,
Mg, and Al (Oie,
Oa 0 to 10 cm, 10
to 30 cm and
30 cm to top of
C-horizon)
Concentrations of Ca and Mg in foliage were correlated with
exchangeable Ca and Mg concentrations in the upper mineral soil; for
most tree species they were also correlated to acid-extractable Ca and
Mg in the parent material (C-horizon). Foliar Al was insensitive to soil Al
concentrations.
February 2017
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Table 5-1 (Continued): Mode of action for acidifying nitrogen and sulfur deposition.
Reference
Ecosystem
Type/Region
Species
N and S
Deposition/
Additions
Soil Indicator
Description
McEathron et
Forest
Sugar
NA
Soil pH and
Evaluated the relationships between species-specific basal area and soil
al. (2013)
Ha-De-Ron-
maple,
exchangeable Ca
and stream water chemistry. Sugar maple basal area was positively
Dah Wilderness
black
and Al (0 to 10 cm
correlated with mineral soil pH, and yellow birch basal area was positively
Area in
cherry,
mineral soil
correlated with mineral soil exchangeable Ca. Sugar maple basal area
Adirondack
American
horizon)
was also negatively correlated with stream water DOC.
Mountains, NY
beech, red
(seven
maple, and
subwatersheds)
yellow birch
Pabian and Forest
Brittinqham
(2012)
NA
NA
Pennsylvania
(14 forest sites)
Exchangeable Ca
and pH
(Oa-horizon).
Mean soil
exchangeable Ca
and pH for the
14 study sites
ranged from 5.28
to 23.5 meq/100 g
and 3.6 to 5.1,
respectively.
Bird community composition (species richness and species abundances)
varied with soil Ca and pH, with 10 bird species having the highest
abundances in forests with high-Ca soils, and 5 species having the
highest abundances with low-Ca soils. Bird species associated with
low-Ca soils were associated with high densities of acid-loving mountain
laurel (Kalmia latifolia) and five tree species with basal area explained by
low soil pH and Ca, whereas bird species associated with high-Ca soils
were associated with high densities of saplings and high basal area of
acid-sensitive tree species.
Paae and
Forest
Sugar NA
Exchangeable Ca,
Evaluated the relationships between exchangeable soil Ca
Mitchell
Adirondack
maple,
exchangeable
concentrations and tree basal area. There were no observed trends
(2008)
Mountains, NY
American
Ca:AI (forest floor
relating total basal area to mineral soil (0 to 10 cm) exchangeable Ca
(11 sites)
beech,
and upper [0 to
concentrations; however, the relative basal areas of sugar maple and
American
10 cm] mineral
American basswood were positively correlated with mineral soil
basswood,
soil)
exchangeable Ca, and relative basal area of American beech was
and white
negatively correlated. Relative basal area of white ash was not related to
ash
soil exchangeable Ca.
Perakis et al.
(2013)
Forest
Oregon
(coastal range)
Douglas fir NA
(plantations)
None
Nitrate leaching (at 20 and 100 cm) increased, soil pH declined (from 5.8
to 4.2), and exchangeable soil Ca, Mg, and K decreased (10-fold
declines) along the soil N gradient. Exchangeable Ca and Mg (in both 0
to 20 cm and 0 to 100 cm) and K (0 to 20 cm) declined with increasing
nitrate leaching. Mean soil profile pH declined logarithmically with nitrate
leaching at 20 and 100 cm. The sum of exchangeable Ca, Mg, and K was
positively correlated with soil pH at 20 and 100 cm. Aboveground tree
biomass contained an increasing percentage of total ecosystem Ca, Mg,
and K as soil N increased.
February 2017
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Table 5-1 (Continued): Mode of action for acidifying nitrogen and sulfur deposition.
Reference
Ecosystem
Type/Region
Species
N and S
Deposition/
Additions
Soil Indicator
Description
Pitel and
Yanai (2014)
Forest
Massachusetts,
Vermont, and
New York
Sugar
maple
NA
Soil pH,
exchangeable
Ca:AI, Al, and
cations (Ca, Mg,
K), cation (Ca, Mg,
K, and total)
saturation, and
effective CEC (A-
and upper
B-horizons)
Evaluated the mortality of dominant and codominant sugar maple in
47 stands that had experienced defoliation by native forest tent caterpillar
(Malacosoma disstria). Mortality was found to be highest in stands with
the greatest amount of crown diebackthe previous year. Drought, cold
winter temperatures, concave microrelief and soil base cation availability
were also significant predictors of mortality. Concentrations of
exchangeable Ca, Mg, and K in the upper B soil horizon were inversely
correlated with sugar maple mortality, with exchangeable K having the
strongest relationship with mortality. Site with above-average sugar
maple mortality (>3 or 4%) occurred on soils with low concentrations of
exchangeable Ca (0.31 to 0.46 cmolc/kg), Mg (0.06 to 0.10 cmolc/kg), and
K (0.03 to 0.05 cmolc/kg). Stands defoliated in 2005 that had low Mg
saturation (A-horizon) suffered higher rates of mortality, suggesting an
interaction between low base cations and defoliation events.
Sridevi et al.
(2012)
Forest
Hubbard Brook
Experimental
Forest, NH
Soil
microbes
(bacteria)
NA
Soil pH,
exchangeable
cations, Al, Fe, P,
Mn, Zn,
exchangeable
acidity, and CEC
(0 to 15 cm)
Ca additions of 1,000 kg Ca/ha applied in 1999. The bacterial community
structure in the Ca treated and nontreated reference soils was found to
be significantly different, with differences among communities being more
pronounced in the mineral soils. Calcium additions resulted in a change in
bacterial community composition of 23% in the organic and 22% in the
mineral soil horizons. Numbers of detectable taxa in some families were
lower in the Ca amended soils, while some families were higher.
Analyses of relationships between soil chemistry and the bacterial
communities indicated that only Ca, pH, and P were significantly
correlated with bacterial community structure.
Stevens et al.
(2010b)
Grassland
U.K. (68 sites)
Grassland
species
6.2 to 36.3 kg
N/ha/yr
Centre for
Ecology and
Hydrology (CEH)
National
Atmospheric
Deposition Model
Ellenburg R
(reaction-soil pH)
and N (soil
nutrient) scores
Data from a national survey were used to evaluate species richness of
68 U.K. grasslands along an N deposition gradient. The results suggest
that soil acidification (instead of eutrophication) was contributing to
changes in species diversity and composition. Soil acidification may have
led to reduced nutrient availability and increased Al solubility preventing
the "fertilizing" effects of N addition from being apparent.
February 2017
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Table 5-1 (Continued): Mode of action for acidifying nitrogen and sulfur deposition.
Reference
Ecosystem
Type/Region
Species
N and S
Deposition/
Additions
Soil Indicator
Description
Sullivan et al.
(2013)
Forest
Adirondack
Mountains, NY
(50 plots in
20 small
watersheds
with sugar
maple
overstory)
Sugar 75 to
maple 112 meq/m2/yr as
N + S
NADP (wet
deposition);
CASTNET (dry
deposition)
2000-2004
(average)
Soil pH,
exchangeable Ca,
exchangeable Mg,
and base
saturation (forest
floor, A- and upper
B- (0 to 10 cm)
horizons)
The study found that plots with lower soil base saturation did not have
sugar maple regeneration (these same plots also received higher N and
S deposition levels); proportion of sugar maple seedlings dropped
substantially at base saturation levels less than 20%. Canopy vigor was
positively correlated with soil pH and exchangeable Ca and Mg. Mean
growth rates (BAI) were positively correlated with exchangeable Ca and
base saturation at the watershed level.
Basto et al.
(2015b)
Grassland
Peak District
National Park,
U.K.
261 NA
grassland
species;
seed bank
Soil pH (gradient
with soil pH range
of 3.5 to 6.5)
Studied seed bank and seed germination, viability, and damage (through
seed burial experiment conducted with Scabiosa columbaria, Hypericum
pulchrum, and Campanula rotundifolia) along a natural pH gradient from
acidic to calcareous grasslands. Increasing soil pH was found to be
correlated with decreases in total and grass seed abundance, declines in
the persistence of H. pulchrum seed, and declines in damage to C.
rotundifolia seed. Seed germination was not influenced by pH. In soil with
pH higher than 5.6, indirect effects of pH (through increased fungal
pathogens) appeared to decrease the persistence of the seed of all three
grassland species. This study suggested that: acidic soils are associated
with increased seed persistence; the longevity and size of grassland seed
banks decline as soil pH increases; and that pH indirectly influences seed
persistence.
Al = aluminum; BAI = basal area increment; Ca = calcium; CASTNET = Clean Air Status and Trends Network; Cd = cadmium; CEC = cation exchange capacity; CEH = Centre for
Ecology and Hydrology; cm = centimeter; DOC = dissolved organic compound; Fe = iron; FIA = Forest Inventory and Analysis; g = grams; H+ = hydrogen; ha = hectare;
K = potassium; kg = kilograms; m = meter; meq = milliequivalent; mg = milligrams; Mg = magnesium; Mn = manganese; mol = mole; N = nitrogen; NA = not applicable;
NADP = National Acid Deposition Program; P = phosphorus; PLFA = phospholipid fatty acid: N03" = nitrate; S = sulfur; S042" = sulfate; yr = year; Zn = zinc.
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FUNCTION
Membrane integrity
Stomatal regulation
Enzyme activation
Carbohydrate metabolism
Cold hardiness
Defense/chemical-physical
I
GROWTH
Cell division
Cell wall synthesis
Stress tolerance
1
STRUCTURE
Canopy integrity
Leaf form
Wood quality
Tree height
Root distribution
Transpiration
Foliar
Ca
Uptake
Exchange
Forrest Floor
Soil
Reserves
Mineral
Pool
H'J
Deposition
Cytoplasm
Cell Wall
Cal
Leaching
Throughfall
, , Root xylem and cortex
'OHor,
s In
X
lCa. Al
Soil 1
Solution
Ca, Al
Leaching
Physiological Processes
Ca Supply Rate
«
Biogeochemical Processes
Al = aluminum; Ca = calcium; H = hydrogen; H20 = water; S = sulfur.
Source: (Fenn et al., 2006)
Figure 5-1 Diagram based on Fenn et al, (20061 showing indicators of forest
physiological function, growth, and structure that are linked to
biogeochemical cycles through processes that control rates of
calcium supply. Calcium affects plant physiological processes
that influence growth rates and the capacity of plants to resist
environmental stresses, such as extremes of temperature,
drought, insects, and diseases. Therefore, acidifying deposition,
which can deplete soil calcium or interfere with calcium uptake
through mobilization of soil aluminum, can affect forest health.
February 2017 5-9 DRAFT: Do Not Cite or Quote
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Table 5-2 Relationships between soil chemistry indicators and biological endpoints that have been evaluated
in the literature since the 2008 Integrated Science Assessment.
Taxa
Exchangeable Base
Cations
PH
Exchangeable
Acidity
Exchangeable
Ca:AI Ratio
Exchangeable Al or
Base Saturation Al Concentrations
Sugar maple
Beieretal. (2012):
Bilodeau-Gauthier et al.
(2011):
Lona et al. (2009):
Paae and Mitchell
(2008):
Sullivan et al. (2013):
Cleavitt et al. (2014):
Duchesne and Ouimet
(2009):
Pitel and Yanai (2014)
Lona et al. (2009):
McEathron et al.
(2013): Sullivan et
al. (2013):
Miller and
Watmouah (2009)
Bilodeau-Gauthier
et al. (2011)
Bilodeau-Gauthier Bilodeau-Gauthier et
etal. (2011): al. (2011)
Sullivan et al.
(2013)
Yellow birch
McEathron et al. (2013)
-
-
-
-
American beech
Paae and Mitchell
(2008):
Duchesne and Ouimet
(2009)
American basswood
Paae and Mitchell
(2008):
Beieretal. (2012)
-
-
-
-
Black cherry
-
-
-
Lona et al.
(2009)
-
Eastern hophornbeam
Beieretal. (2012)
-
-
-
-
Hickories
-
-
-
-
Elias et al. (2009) -
Northern red oak
-
-
-
-
Elias et al. (2009)
February 2017
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Table 5-2 (Continued): Relationships between soil chemistry indicators and biological endpoints that have been
evaluated in the literature since the 2008 Integrated Science Assessment.
Taxa
Exchangeable Base
Cations
PH
Exchangeable
Acidity
Exchangeable
Ca:AI Ratio
Exchangeable Al or
Base Saturation Al Concentrations
Forest understory plant
species
Horslev et al. (2008)
Horslev et al.
(2008)
Horslev et al.
(2008)
-
Horslev et al. (2008)
Grassland plant species
-
Pannek et al.
(2015)
-
-
-
Lichens
-
Cleavitt et al.
(2011a)
-
-
-
Soil biota
Sridevi etal. (2012):
Ohta etal. (2014)
Chen etal. (2013):
Rousk et al. (2009):
Gilliam et al.
(2011b):
Sridevi etal. (2012)
Chen etal. (2013):
Rousk et al. (2009)
Fauna
Beier et al. (2012):
Pabian and Brittinaham
(2012)
Pabian and
Brittinaham (2012)
-
Al = aluminum; Ca = calcium.
Note: only soil chemistry indicators with a reported significant relationship (positive or negative) with a biological endpoint is indicated in this table. See Table 5-1 for a listing of soil
chemical indicators included in each study.
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1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
5.2 Effects on Terrestrial Organisms and Ecosystems
5.2.1 Trees and Forests
Both coniferous and deciduous forests throughout the eastern U.S. have been
experiencing gradual losses of base cation nutrients from the soil due to accelerated
leaching from acidifying deposition. This change in base cation nutrient availability can
reduce the quality of forest nutrition over the long term in sensitive areas of low
base-cation soils. Evidence suggests that red spruce and sugar maple in some areas in the
eastern U.S. have experienced declining health as a consequence of acidifying deposition.
The 2008 ISA reported several indicators of stress to forest trees (Table 3-3 in 2008 ISA),
including percent dieback of canopy trees, dead tree basal area (as a percentage), crown
vigor index, and fine twig dieback. Biological effects of acidification on terrestrial
ecosystems were generally attributed to A1 toxicity, decreased ability of plant roots to
take up nutrient cations (due to leaching of base cations from soil and interference with
uptake), and elevated leaching of Ca2+ from conifer needles. The Ca:Al ratio in soil
solution is a chemical indicator of the negative impacts of soil acidification on terrestrial
vegetation (Cronan and Grigal. 1995). As tree species have shown similar sensitivities to
Ca:Al and base cation (Bc):Al soil solution ratios, the Bc:Al ratio was used to represent
the Ca:Al ratio and is the most commonly used indicator in the simple mass balance
(SMB) model to estimate critical acid loads in the European Union, Canada, and the U.S.
(McNultv et al.. 2007; Ouimet et al.. 2006; Spranger et al. 2004).
Sverdrup and Warfvinge (1993). in a meta-analysis of laboratory, greenhouse, and field
studies, reported that the critical Be: Al ratios for a large variety of tree species ranged
from 0.09 to 20.0, although the Bc:Al ratio range reported for tree species native to North
American was 0.09 to 2.0. This range is similar to that described by Cronan and Grigal
(1995) for Ca:Al. In their meta-analysis, assessment of studies examining sensitivities to
the Ca:Al ratio, plant toxicity, or nutrient antagonism was reported to occur at Ca:Al
ratios ranging from 0.2 to 2.5. The meta-analysis by Sverdrup and Warfvinge (1993)
explored the relationship between Bc:Al ratios in soil solution and tree growth. They
reported the Bc:Al ratios at which growth was reduced by 20% relative to control trees. A
Bc:Al ratio of 1 is often applied to protect forested systems of Europe, particularly
conifers, (Spranger et al.. 2004) and a Bc:Al ratio of 10 has been identified for forests in
North America , particularly to protect deciduous forests (McNultv et al.. 2007; Ouimet
February 2017
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1
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et al.. 2006). The higher ratio provides more protection for various conditions and
possible episodic acidification events.
The tree species most commonly studied in North America and used in the 2008 ISA to
assess the impacts of acidification due to total nitrogen and sulfur deposition include red
spruce and sugar maple, although other tree species like flowering dogwood (Cornus
florida) can also be sensitive to conditions created by acidifying deposition. New
information regarding the effects of acidifying deposition on the commonly studied sugar
maple and red spruce, as well as other tree species, understory species, and grassland
species is summarized below.
5.2.1.1 Sugar Maple
Among broadleaf tree species in the northeastern U.S., sugar maple is the species most
commonly associated with adverse acidification-related effects resulting from S and N
deposition, although other base cation accumulating hardwoods may also be at risk
(Driscoll et al.. 2001b). Sugar maple is distributed from Missouri and Minnesota in the
northcentral U.S. eastward to Maine and the central Appalachian Mountain region, and
the species is a dominant component of the northern hardwood forest type (Braun. 2001).
Within this range, soil acidification is widespread throughout the northeastern U.S. and
within many portions of the Appalachian Mountains (Warbv et al.. 2009).
The 2008 ISA reported that acidifying deposition, in combination with other stressors, is
a likely contributor to the decline of sugar maple trees (Section 3.2.2.3 of 2008 ISA).
Sugar maple decline has been noted to occur in some portions of the eastern U.S., on base
cation-poor soils developed from parent material dominated by sandstone or other base
cation-poor substrates. Sugar maple appears to be particularly sensitive to reduced Ca and
magnesium (Mg) availability caused by acidifying deposition. Based on the results from
a compilation of laboratory studies, sugar maple growth can be reduced by approximately
20% at a Bc:Al soil solution ratio of 0.6 (Sverdrup and WarfVinge. 1993).
The more recent literature on sugar maple is consistent with the 2008 ISA. In these
studies, sugar maple was sensitive to soil conditions and chemistries associated with
acidifying deposition (Section 5.2.1.1.1). Soil chemical indicators that were evaluated
included exchangeable base cations, soil pH, exchangeable acidity (H+ and Al),
exchangeable Ca:Al ratios, base saturation, and Al concentrations. Measured sugar maple
responses included changes in basal area, growth, regeneration success, and foliar
nutrient concentrations and chemistry (Table 5-1). In addition, several studies evaluated
physiological mechanisms that could explain the response of sugar maple to changes in
soil chemistry induced by acidifying deposition (Table 5-3).
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Table 5-3 Summary of calcium addition studies in North America.
Reference Region
Species
Additions
(Ca and/or Al)
Description
Battles et al.
(2014)
New
Hampshire
Sugar maple,
American
beech, yellow
birch, red
spruce, and
balsam fir
Approximately
1,000 kg Ca/ha
(applied in 1999)
Ca additions resulted in the recovery of tree biomass increments, higher aboveground NPP,
and increased photosynthetic surface area. Sugar maple exhibited the largest cumulative
change in biomass, while American beech showed a negative cumulative change in
biomass.
Bovce et al.
(2013)
New
Hampshire,
Vermont
Red spruce
and balsam fir
Total of 38 g Ca/m2
and/or 10.8 g Al/m2
Trends toward greater foliar Ca and Ca:AI ratios and lower Al concentrations across the
treatment gradient. Ca availability appeared to enhance the ability of red spruce and balsam
fir to repair oxidative stress damage.
Cleavitt et
al. (2011b)
New
Hampshire
Sugar maple
Approximately
1,000 kg Ca/ha
(applied in 1999)
Masting events were not influenced by the Ca treatment. Seeds from the Ca treated sites
had lower concentrations of Al, K, and Mg and significantly higher concentrations of Si (but
no differences in Ca concentrations). Seeds from the Ca treated sites had higher
percentage of seedling emergence and higher seedling survival for the first 3 years.
Halman et
al. (2008)
New
Hampshire
Red spruce
Approximately
1,000 kg Ca/ha
(applied in 1999)
Foliar Ca and total sugar concentrations were significantly higher in trees in the Ca addition
watershed. Cold tolerance of foliage was significantly greater in trees in the Ca addition
watershed.
Halman et
al. (2013)
New
Hampshire
Sugar maple
Total of 38 g Ca/m2
and/or 10.8 g Al/m2
Ca additions were found to increase C allocation to sugar maple growth. Al additions
increased root Al concentrations, root cell membrane disturbance, and ascorbate
peroxidase and glutathione reductase activity, and reduced foliar reflush following frost
injury and the number of viable seeds.
Halman et
al. (2015)
New
Hampshire
Sugar maple
and American
beech
Annual application of
CaCb (2.5 g/m2) and
AlCb (0.9 g/m2) from
1995-1999;
Wollastonite (38 g/m2)
was applied in 1999 a
single dose
The Al and Ca treatments did not affect beech foliar chemistry. Ca additions resulted in
significantly higher Ca concentrations in both dominant and nondominant sugar maple trees.
By 2008, the growth of American beech was higher than that of sugar maple on the control
plots and Al treated plots, and nondominant sugar maple growth was greater than that of
American beech and dominant sugar maple on the Ca treated plots. Increases in tree
mortality on the Al treated plots may have released surviving American beech and increased
their growth.
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Table 5-3 (Continued): Summary of calcium addition studies in North America.
Reference
Region
Species
Additions
(Ca and/or Al)
Description
Minocha et
al. (2010)
New
Hampshire
Sugar maple,
yellow birch,
and American
beech
Approximately
1,000 kg Ca/ha
(applied in 1999)
Foliar soluble Ca increased significantly in all species at mid and high elevations at Ca
supplemented watershed. Sensitivity to Ca limitation increased with elevation.
Moore et al.
(2012)
Quebec,
Canada
Sugar maple
8 dolomite lime
addition rates—0, 0.5,
1, 2, 5, 10, 20 and
50 megatonnes/ha
(applied in 1994)
Foliar Ca and Mg concentrations were found to be higher for treated trees relative to the
control trees. Mean crown dieback of trees decreased and seedling density increased with
the lime rate. The stem basal area increment for maple trees and proportion of the sugar
maple seedlings was increased with lime treatment.
Schabera et
al. (2011)
New
Hampshire
Red spruce
Approximately
1,000 kg Ca/ha
(applied in 1999)
Trees from the Ca addition watershed had higher estimated levels of foliar biomass. Ca
addition increased the stress tolerance of red spruce foliage during the cold season,
resulting in greater crown mass.
Smith et al.
(2009)
New York,
Vermont
Red spruce
Total of 160 kg Ca/yr
(1992-1995)
Greater amounts of Ca were found in the wood from the high-Ca location than from the
low-Ca location. Ca concentration was greater in wood formed in the 1970s than for wood
formed in the 1980s, and Ca treatments resulted in increased concentration of Ca in both
the 1970s and 1980s decadal bands of wood. Foliar concentrations ofCa oxalate were also
higher on the high-Ca site.
Sridevi et al.
(2012)
New
Hampshire
Soil microbes
(bacteria)
Approximately
1,000 kg Ca/ha
(applied in 1999)
Bacterial community structure in the Ca treated and nontreated reference soils was found to
be significantly different, with differences among communities being more pronounced in the
mineral soils.
Al = aluminum; AICI3 = aluminum chloride; C = carbon; Ca = calcium; CaCI2 = calcium chloride; g = gram; ha = hectare; K = potassium; kg = kilograms; m = meter; Mg = magnesium;
NPP = net primary production; Si = silicon; yr = year.
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5.2.1.1.1
Soil Chemical Indicators for Sugar Maple
Soil Exchangeable Base Cations
Sugar maple basal area and growth were responsive to soil exchangeable base cation
concentrations in several studies in the northeastern U.S. In the Adirondack Mountains of
New York, Beier et al. (2012) reported sugar maple basal area was positively related to
forest floor and mineral soil (B-horizon) exchangeable soil Ca on sites that ranged in soil
Ca from 1.83 to 53.89 cmolc/kg (in Oa-horizon) and 0.28 to 7.73 cmolc/kg in the
B-horizon (see Figure 3-2 in 2008 ISA for a description of soil horizons). Similar results
were reported in Quebec, Canada by Bilodeaii-Gauthier et al. (2011) who found that
sugar maple basal area growth was positively correlated to concentrations of base cations
(Ca, potassium [K], and Mg) in wood and mineral soil (B-horizon), and Long et al.
(2009) who reported that sugar maple basal area increment (BAI) was positively
correlated with exchangeable Ca and Mg in the upper B-horizon in the northeastern U.S.
Page and Mitchell (2008) also found that the relative basal area of sugar maple was
positively correlated with mineral soil (0-10 cm) exchangeable Ca in the Adirondack
Mountains. In the same region, Sullivan et al. (2013) determined that sugar maple canopy
vigor was positively correlated with soil exchangeable Ca and Mg, and mean growth
rates (measured as BAI) were positively correlated with exchangeable Ca at the
watershed level.
Relationships between soil exchangeable base cations and sugar maple regeneration (the
growth and abundance of seedlings and saplings) have also been demonstrated. Cleavitt
et al. (2014) evaluated sugar maple seedling survival and cause of death across 22 sites in
New Hampshire that varied in soil Ca and topographic position. Soil Ca concentration
exhibited a ninefold change across the study sites and was positively correlated to
increases in sugar maple abundance and initial seedling densities. However, soil Ca
concentration was not a significant predictor of first-year mortality, nor was it a factor
that distinguished among the three main site types. In a study in Quebec, Canada,
Duchesne and Ouimet (2009) explored relationships between soil chemistry and sugar
maple in the sapling stratum and found that the basal area of sugar maple was positively
correlated with soil exchangeable Ca and Mg.
Pitel and Yanai (2014) evaluated the abiotic and biotic factors influencing the mortality
of dominant and codominant sugar maple trees in 47 stands in Massachusetts, Vermont,
and New York that had experienced defoliation by native forest tent caterpillars
(Malacosoma disstria) between 2002 and 2007. A total of 54 predictive variables
(defoliation year, stand and site characteristics, and soil chemistry variables) were
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evaluated through multiple linear regression followed by stepwise regression to produce
the best predictive models of sugar maple mortality from 2006 to 2008. Mortality was
highest in stands with the greatest amount of crown dieback the previous year, and
drought, cold winter temperatures, concave micro-relief, and soil base cation availability
were significant predictors of mortality. Concentrations of exchangeable Ca, Mg, and K
in the upper B soil horizon were inversely correlated with sugar maple mortality, with
exchangeable K showing the strongest relationship. Sites with above average sugar maple
mortality (>3 or 4%) were found to occur on soils with low concentrations of
exchangeable Ca (0.31-0.46 cmolc/kg), Mg (0.06-0.10 cmolc/kg), and K
(0.03-0.05 cmolc/kg). There was also an interaction between defoliation and soil base
cation availability: stands defoliated in 2005 that had low soil (A-horizon) Mg saturation
suffered higher rates of mortality.
Soil Exchangeable Acidity and pH
Bilodeau-Gaiithier et al. (2011) found that sugar maple tree growth was negatively
correlated to soil exchangeable acidity (H+ and exchangeable Al), and through a
multifactor analysis, showed that tree age and soil exchangeable Al accounted for 51% of
the variation in sugar maple BAI. Positive correlations between mineral soil pH and sugar
maple basal area growth have also been reported by Long et al. (2009) and McEathron et
al. (2013). Sullivan et al. (2013) found that sugar maple canopy vigor was positively
correlated with soil pH.
One study reported a relationship between sugar maple foliar chemistry and
exchangeable soil chemistry. Miller and Watmough (2009). in their evaluation of
hardwood plots along air-pollution (N, S, and ozone), soil-acidity, and climate gradients
in Ontario, Canada, showed that foliar Ca and Mg content was positively correlated and
foliar manganese (Mn) content was negatively correlated with soil A-horizon pH.
Soil Base Saturation
An investigation of every relationship between sugar maple BAI and soil variables
revealed that base saturation was the best predictor of BAI (nonlinear) and explained
43% of variance (Bilodeau-Gaiithier et al.. 2011). Similarly, Sullivan et al. (2013) found
that soil base saturation was related to sugar maple regeneration and growth. Plots with
lower soil base saturation did not have sugar maple regeneration; the proportion of sugar
maple seedlings dropped substantially at base saturation levels less than 20% (Figure
5-2). Mean growth rates were positively correlated with soil base saturation at the
watershed level.
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C
o
tr
o
Q.
o
OT
E
d>
a>
CO
(/)
1~
0.8
0.6
0.4
0.2 -
0
0
w i
CO I
o"
Oil
COl
CQ.
%
¦<9
Ł
20
40 60
BS in Upper B Horizon (%
—I
80
100
BS = base saturation; SM = sugar maple.
Note: Plots were rank ordered based on soil base saturation, and a 5-plot rolling average was applied to both the soil base
saturation and the seedling proportion data. Reference lines are added at base saturation values of 12 and 20%, indicating break
points in the sugar maple seedling proportion-response function.
Source: Sullivan et al. (2013)
Figure 5-2 Relationship between the proportion of seedlings that were sugar
maple and soil base saturation in the upper B-horizon.
Soil Exchangeable Calcium:Aluminum Ratio
The relationship between sugar maple BAI and a soil exchangeable Ca:Al threshold of
<0.03 was evaluated by Long et al. (2009) through an analysis of a regional network of
76 forest sites that spanned Pennsylvania, New Hampshire, New York, and Vermont.
However, a repeated measures analysis did not reveal statistically significant effects of
the Ca:Al soil ratio threshold on BAI.
5.2.1.1.2 Physiological Mechanisms for Sugar Maple
A number of studies were also conducted to determine the potential mechanisms
underlying the sensitivity of sugar maple to the soil conditions created by acidifying
deposition. These studies evaluated the influence of Ca additions on sugar maple
physiology, growth, seeds, and seedlings (Table 5-3). In Hubbard Brook Experimental
Forest (HBEF), NH, one study involved the addition of a total of approximately 1,000 kg
Ca/ha as pelletized wollastonite (CaSiCh) in October 1999 to a watershed (Battles et al..
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2014). This treatment resulted in increases in: soil pH (in Oie-horizon) from 4.29 to 5.45;
base saturation from 9.6 to 78.6% (in Oie layer), 56% (in Oa-horizon), and 14.3% (in
upper mineral soil); and soil solution Ca:Al (inorganic monomeric Al) from 1.6 to 6.4 (in
Oa-horizon) and from 0.97 to 3.8 (in the mineral soil). As part of this study, Battles et al.
(2014) evaluated the effects of the Ca additions on tree growth and found that sugar
maple in the treated watershed exhibited the largest increase in cumulative biomass
relative to other species. Another study at the same experiment reported that sugar maple
seedlings were 50% larger in the treated watershed and mycorrhizal colonization of
seedlings was much higher in the treated watershed (22.47% of root length) as compared
with the reference watershed [4.4% (Juice et al.. 2006)1. Mycorrhizal colonization also
increased in mature sugar maple in the treated watershed (56%) compared to the
reference watershed [35% (Juice et al.. 2006)1. In contrast to sugar maple, American
beech showed a negative cumulative change in biomass. Minocha et al. (2010) examined
the effects of the Ca addition treatment on foliar chemistry and found that sugar maple
had increased foliar concentrations of Ca, which were accompanied by increases in
soluble phosphorous (P), chlorophyll, and two amino acids, glutamate, and glycine. The
authors also reported decreases in known metabolic indicators of physiological stress
(i.e., arginine and y-aminobutyric acid, as well as putrescine, a diamine). Sugar maple
also exhibited a decrease in foliar putrescine at higher elevations in the watershed,
indicating possible remediation from Ca deficiency. Cleavitt et al. (201 lb) evaluated
sugar maple seed production, seed chemistry, seedling growth (lifestage), and seedling
survival on the Ca treated watershed and found that seeds from the Ca treated sites had
lower concentrations of Al, K, and Mg and significantly higher concentrations of silicon
(Si) than seeds from the reference watershed. Percent seedling emergence was also
higher, average lifestage was more significantly advanced, and seedling survival was
greater on the Ca treated watershed.
In a second study (NuPert Study) conducted at HBEF, Halman et al. (2013) evaluated the
impacts of Ca (380 kg/ha) and Al (108 kg/ha) additions on sugar maple physiology. The
Ca additions increased the proportion of carbon allocated to sugar maple growth. In
contrast, Al additions increased root Al concentrations and root cell membrane
disturbance, increased ascorbate peroxidase (APX) and glutathione reductase (GR)
activity, reduced foliar reflush following frost injury, and reduced the number of viable
seeds. Ascorbate peroxidase and GR are antioxidant enzymes that target reactive oxygen
species generated by environmental stresses, such as photo-oxidative stress damage at
low temperatures. Elevated APX and GR activity are indicators of increased oxidative
stress. Several years later, Halman et al. (2015) re-evaluated the NuPert study to
determine the long-term and contrasting responses of sugar maple and American beach to
the Ca and Al treatments following a major ice storm in 1998. The Al and Ca treatments
did not affect beech foliar chemistry. However, Ca additions significantly increased Ca
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concentrations in both dominant and nondominant sugar maple trees, relative to the trees
treated with Al. Interestingly, for all treatments, foliar A1 concentrations were higher in
the nondominant than dominant sugar maple trees, and the opposite was found for foliar
Ca concentrations. By 2008 (11 years after the ice storm), the growth of American beech
was higher than that of sugar maple on the control plots and Al treated plots, and
nondominant sugar maple growth was greater than that of American beech and dominant
sugar maple on the Ca treated plots. These differential growth responses emerged within
2 to 11 years following the ice storm, depending on the treatment and species. Although
plots were mainly composed of sugar maple, American beech experienced the greatest
growth on Al treated plots. Increases in overstory tree mortality on the Al treated plots
may have increased light availability, released surviving American beech, and increased
beech growth.
Moore et al. (2012) evaluated soil chemistry and sugar maple status 15 years after
treatment with dolomite lime (0 to 50 megatonnes/ha) to a hardwood forest in Quebec,
Canada, and found results similar to those in HBEF. Foliar Ca and Mg concentrations
were higher for treated trees relative to the control trees, and mean crown dieback of trees
decreased quadratically with the lime addition rate, from 39% for the control trees to a
value of 1 to 3% for the lime rates of 5 megatonnes/ha and higher. In addition, sugar
maple BAI for the limed trees was nearly double that of the nonlimed trees. The lime
application was also beneficial to the sugar maple regeneration. The overall sugar maple
seedling density increased with the lime rate, nearly doubling in the 50 megatonnes /ha
(32 seedlings/m2) compared with the controls (16 seedlings/m2). The proportion of the
sugar maple seedlings to all of the other species increased quadratically from 22% in
controls to more than 55% in the 5 to 50 megatonnes /ha treatments. In contrast, the
proportion of competitive species decreased quadratically with the lime rate, including
American beech, for which the proportion in the treated plots (24%) was nearly half the
proportion observed in the controls (46%).
5.2.1.2 Red Spruce
Red spruce is a conifer that occurs mainly in the northeastern U.S. and at scattered
high-elevation sites (e.g., mountain and ridge tops) in the Appalachian Mountains. Red
spruce dieback or decline has been observed across high elevation landscapes of the
northeastern, and to a lesser extent, southeastern U.S. At high elevations in the
Adirondack Mountains in New York and the Green Mountains in Vermont, more than
50% of the canopy red spruce trees died during the 1970s and 1980s. In the White
Mountains in New Hampshire, about 25% of the canopy spruce died during that same
period (DeHaves etal.. 1999). Dieback of red spruce has also been observed in mixed
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hardwood-conifer stands at relatively low elevations in the western Adirondack
Mountains, an area that receives high inputs of acidifying deposition (Shortle et al..
1997); acidifying deposition has been implicated as a causal factor (DeHaves et al..
1999).
The 2008 ISA reported that changes in soil chemistry (e.g., depletion of soil base cations,
Al toxicity to tree roots, leaching of base cations into drainage water) have contributed to
high mortality rates and decreased growth of red spruce trees in some areas of the eastern
U.S. over the past three decades. Studies evaluating the physiologic basis behind the
responses of red spruce to acidifying deposition have attributed the reduced vigor of the
species to increased sensitivity to frost injury and cold temperatures. The frequency of
freezing injury to red spruce needles had increased during a period in the latter half of the
20th century that coincided with increased emissions of S and N oxides and increased
acidifying deposition (DeHaves et al.. 1999).
Since the 2008 ISA, research evaluating the sensitivity of red spruce to soil indicators of
acidifying deposition have mainly focused on the potential mechanisms underlying the
sensitivity of the species to acidic soil conditions. These studies have examined the
physiological response of red spruce to Ca additions (Table 5-3).
In the HBEF study that involved the addition of approximately 1,000 kg Ca/ha, Halman
et al. (2008) and Schaberg et al. (2011) evaluated the response of red spruce foliar
chemistry. Halman et al. (2008) reported significantly higher foliar Ca and total sugar
(fructose and glucose) in the Ca addition watershed than in trees in the reference
watershed. Foliar APX activity was also higher in trees in the Ca addition watershed
during winter. Cold tolerance of foliage was significantly greater in trees in the Ca
addition watershed than in trees in the reference watershed. Schaberg et al. (2011)
measured concentrations of foliar polyamines and free amino acids, foliar chlorophyll,
and sapwood area (as a proxy for foliar biomass) in Ca treated and nontreated trees.
Foliar polyamines (putrescine and spermidine) and free amino acids (alanine,
aminobutyric acid [GABA]) are putative stress protection compounds that may directly
protect or provide other benefits to foliage that increase stress tolerance. The Ca additions
increased November concentrations of alanine, GABA, putrescine, and spermidine
relative to foliage from the reference watershed. Consistent with increased stress
protection indicated by the elevated polyamine and free amino acids, foliage from the Ca
addition watershed had higher total chlorophyll concentrations than foliage from the
reference watershed. In contrast, foliage from the reference watershed had significantly
higher alanine:glutamic acid ratios which have been attributed to cold sensitivity or
damage in other species. In addition to concentration-based differences in foliar
compounds, trees from the Ca addition watershed had higher estimated levels of foliar
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biomass than trees from the reference watershed. These findings suggest that Ca addition
increased the stress tolerance and productive capacity of red spruce foliage during the
cold season and resulted in greater crown mass compared to trees growing on nontreated
soils.
Similar findings were reported by Bovce etal. (2013). who examined the influence of Ca
and A1 on the physiology of red spruce and balsam fir (Abies balsamea) in three different
locations that varied in soil nutritional status. Processes known to be Ca sensitive (root
and foliar cation concentrations, chlorophyll fluorescence, soluble sugar concentrations,
and the activities of APX and GR in current-year foliage) were measured, and the results
from the study suggest that Ca availability enhanced the ability of red spruce and balsam
fir to repair oxidative stress damage, including photo-oxidation.
Concentrations of Ca in sapwood and accumulations of Ca oxalate in foliage have been
used as markers of environmental change due to acidic deposition or forest management
practices. Smith et al. (2009) compared the effects of different Ca fertilization treatments
(approximately 178 kg Ca/ha/yr during 1992-1995) on Ca concentrations in wood and
Ca and oxalate (Ox) concentrations in red spruce foliage at two locations with different
initial concentrations of Ca in the soil (6.4 cmolc/kg vs. 13.7 cmolc/kg). Greater amounts
of Ca were found in the wood from the high-Ca location than from the low-Ca location.
Foliar concentrations of Ca oxalate were higher on the high-Ca site than on the low-Ca
site and increased in response to Ca additions.
5.2.1.3 Other Tree Species
In the 2008 ISA, there was some information regarding the effects of acidification on
dogwood (Cornus) species. Loss of base cations, specifically Ca2+, had been implicated
in increased susceptibility of flowering dogwood to dogwood anthracnose, its most
destructive disease. Susceptibility to the disease and disease severity in stands appeared
dependent on several factors, including acid deposition and various edaphic
characteristics and meteorological conditions. Studies pointed to greater vulnerability of
dogwoods to anthracnose under simulated acid rain treatments (Britton et al.. 1996) and
under Ca2 deficiency KHolzmueller et al.. 2007) Section 3.2.2.3 of 2008 ISA],
Since the 2008 ISA, no further research on dogwood has been published. However, other
tree species have been evaluated in studies relating soil chemistry to tree physiology,
including yellow birch, white ash, American beech, black cherry, northern red oak,
hickories, American basswood, and eastern hophornbeam. These species were reported to
vary in their sensitivities to soil conditions associated with acidifying deposition (Table
5zi).
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In a recent study in West Virginia, Thomas et al. (2013) used dendroisotopic techniques
to show the recovery of eastern redcedar (Juniperus virginiana) trees from decades of S
pollution using an analysis of a tree ring chronology from 1909 to 2008. Growth,
measured as BAI, in eastern redcedar old-growth stands (118-480 years old) increased
significantly since 1970. A multivariate correlation analysis using historical climate
variables, atmospheric CO2 concentrations, and U.S. SO2 and NOx emissions estimates
showed that the growth of cedar trees over the 100-year chronology is explained best by
increases in atmospheric CO2 and NOx emissions, and decreases in SO2 emissions.
Through carbon isotope (13C) analyses, the researchers were able to show that the stomata
of cedar may be more sensitive to SO2 emissions than to increasing atmospheric CO2. A
breakpoint in the 100-year S13C tree ring chronology occurred around 1980, as SO2
emissions declined, indicating a gradual increase in stomatal conductance and a
concurrent increase in photosynthesis related to decreasing SO2 emissions and increasing
atmospheric CO2. After 1990, calculated stomatal conductance increased more than
photosynthesis. These patterns in physiology led to changing trends in intrinsic water use
efficiency (/WUE; the ratio of photosynthesis to water loss through stomatal
conductance). The calculated /'WUE generally increased from the 1940s to 1990 mainly
because of SO2 emission effects on stomatal conductance, and then /'WUE began to
decrease after 1990 because SO2 emissions no longer constrained stomatal function.
Through S isotope analysis (tree ring S34S), the study showed a synchronous change in
the sources of S used at the whole-tree level that indicated a reduced anthropogenic
influence. The increase in growth and the S13C and S34S trends in the tree ring chronology
of these Juniperus trees provide evidence for a distinct physiological response to changes
in atmospheric SO2 emissions since 1980. The authors attributed the changes since 1980
to an indirect effect of decreases in acid deposition. However, the exact mechanism is
unclear because the 100-year chronology could only be correlated to estimated SO2
emissions because acidifying deposition measurements were not available. Other
researchers have pointed out that the trees in the Thomas et al. (2013) study were
growing on a limestone outcrop that could be well buffered from soil acidification
(Schaberg et al.. 2014). Further, the rapid recovery of tree growth could also point to a
direct effect of gaseous SO2 rather than an indirect effect of soil acidification, which
would have a longer response time to decreases in emissions. See Section 3^2 for further
discussion of direct gaseous SO2 effects on vegetation.
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5.2.1.3.1
Soil Chemical Indicators for Other Tree Species
Soil Exchangeable Base Cations
Several studies reported on the relationships between species-specific basal area and
growth and soil exchangeable base cations. In the Adirondack Mountains, McEathron et
al. (2013) evaluated the relationships between basal area and soil chemistry and reported
that yellow birch basal area was positively correlated with mineral soil exchangeable Ca.
Similarly, Page and Mitchell (2008) compared the basal areas of American basswood,
American beech, and white ash with mineral soil (0-10 cm in depth) exchangeable Ca
concentrations and found exchangeable Ca had a positive correlation with relative basal
area of American basswood, a negative correlation with the relative basal area of
American beech, and no correlation with relative basal area of white ash. The positive
relationship between American basswood and soil exchangeable Ca is consistent with
other studies. Beier et al. (2012). in their evaluation of vegetation communities across
northern hardwood sites that ranged in exchangeable Ca concentrations from 1.83 to
53.89 cmolc/ha (in Oa-horizon) and 0.28 to 7.73 cmolc/ha (in B-horizon), reported that
American basswood and eastern hophornbeam were only found on the sites with the
highest exchangeable Ca concentrations. Similarly, negative relationships between
American beech and soil exchangeable Ca have been reported elsewhere. Duchesne and
Qui met (2009) found that basal area of American beech in the sapling stratum in sugar
maple-dominated forests was negatively correlated with exchangeable Ca and Mg. Soil
concentrations of Ca and Mg on sites colonized by American beech were, on average,
roughly half those on sites where American beech was absent, thereby suggesting that
beech effectively colonizes sites with low base status. These findings are also consistent
with the responses of American beech to the Ca addition studies described earlier (Battles
et al.. 2014; Moore et al.. 2012).
Soil Base Saturation
One study of 30 forest plots within Monongahela National Forest, WV reported on the
relationship between soil base saturation and tree abundance. Elias et al. (2009) evaluated
relationships between tree growth parameters and soil indicators of acidifying deposition
and found that hickories were the only species (out of 4 within-species comparisons) to
have significantly lower numbers on sites with base saturation below 20% (A-horizon)
and 2.5% (B-horizon). They also found that the percentage of dead northern red oak was
highest on sites with Al concentrations (A-horizon) above 43 cmolc/kg. The authors
reported that sites in the year 2000 with subsurface base saturation above 10% had more
unique species.
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Soil Exchangeable Calcium:Aluminum Ratio
A study of 76 hardwood stands across the northeastern U.S. noted the relationship
between exchangeable Ca:Al ratios and BAI. Long et al. (2009) found that, unlike sugar
maple, black cherry BAI was greater in stands with exchangeable Ca:Al ratios
(B-horizon) below the <0.03 threshold adopted by the study.
5.2.2 Forest Understory and Grassland Species
The 2008 ISA did not specifically assess the effect of acidification on forest understory
species due to the lack of studies. Also, the 2008 ISA reported that grasslands were
thought to be less sensitive to acidification than woodlands (kocln and Wilson. 2001;
Blake et al.. 1999). and grasslands with calcareous soils will be less sensitive than those
with acidic soils (Bobbink et al.. 1998).
Since the 2008 ISA, several studies have evaluated the relationships between soil
chemistry indicators of acidification and forest understory and grassland species (Table
5zi).
5.2.2.1 Soil Chemical Indicators for Forest Understory and Grassland Species
Soil pH, Exchangeable Base Cations, and Exchangeable Acidity
One study examined the relationship between soil chemistry indicators of acidification
and forest understory species. Horslev et al. (2008) evaluated 35 soil chemistry, stand,
and climatic variables as predictors of understory plant species composition in northern
hardwood stands, and found that a base cation-acid cation nutrient gradient accounted for
71.9% (in New Hampshire and Vermont) and 63% (in Pennsylvania and New York) of
the variation in the nonmetric multidimensional scaling ordination analyses of plant
community composition. Soil Ca, Mg, and pH formed the base end and Al, Mn, K, soil
acidity, and organic matter represented the acid end of the gradient. Based on results from
McNemars' exact test, a total of 50 of the 234 understory species were associated with
the base end of the base cation-acid cation nutrient gradient. These species have value as
indicators of sites at the high end of the base cation nutrient gradient in northern
hardwoods, sites that would be suitable for acid-sensitive species such as sugar maple.
In the U.K., Stevens et al. (2010b) used data from a national survey to evaluate the
species richness of 68 grasslands along an N deposition gradient. Ellenberg R
(reaction-soil pH) and N (soil nutrient) scores and an index of soil acidity preference
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were used as the metrics to characterize the plant diversity responses to the soil chemistry
conditions created by N deposition. Although the study did not find any significant
relationships between the Ellenberg and soil acidity index values and N deposition, there
was evidence that soil acidification was contributing to changes in species diversity and
community composition. Soil acidification may have led to decreased nutrient
availability and increased A1 solubility, thus masking the effects of increased soil N
availability (see also Section 6.2.1 for N discussion).
A similar analysis along an N deposition gradient (2.4 kg N/ha/yr to 43.5 kg N/ha/yr) was
conducted by Pannek et al. (2015) using a vegetation data set from 153 seminatural acidic
grasslands in northwestern Europe. Species frequency in response to N and other factors
including soil (0-10 cm) P, pH, NH4+, and NOs and geographical, climatic, and
management factors were evaluated. A second set of data from acidic grasslands in
Germany (392 plots) and the Netherlands (144 plots) containing plots from different time
periods were also included in the analyses to determine whether the results of the spatial
gradient approach coincided with temporal changes in the abundance of species. Out of
44 species included in the study, 16 were found to be affected by N deposition, with 12 of
them exhibiting a decreased abundance response. Soil pH and P influenced 24 and
14 species, respectively, predominantly increasing abundance. Change of species over
time was unrelated to their responses to pH. However, species were found to significantly
decline over time in both Germany and the Netherlands in response to N deposition, soil
P, and NC>3~. These results show the influence of N deposition in a decline for many plant
species in seminatural acidic grasslands, although impacts of N deposition on pH did not
appear to be the mechanism of plant responses (see also Section 6.2.1 for N discussion).
5.2.3 Lichens
In the 2008 ISA it appeared that lichen populations were affected in areas with acidifying
deposition (Davies et al.. 2007). However, it was not clear whether effects were due to
direct effects of SO2, N effects, or acidifying deposition.
We have not identified any new studies published since the 2008 ISA that evaluated the
relationships between conditions created by acidifying deposition and lichen physiology.
However, in Acadia National Park, Cleavitt et al. (201 la) evaluated the interactions
among N and S deposition, tree type, and epiphytic lichen and bryophyte diversity,
biomass, and abundance to (1) document any differences in the depositional
environments (throughfall and cloud water) of red spruce and red maple (Acer rubrum)
trees, (2) relate deposition differences to both chemistry of the bark and corresponding
epiphyte biomass and composition on the bark, and (3) describe any species-specific
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relationships that emerged between the epiphytes and bark chemistry (Table 5-1).
Throughfall N and S deposition were higher under spruce trees than under maple trees,
and average S concentrations in cloud water were negatively correlated with bark Ca and
bark Mg. Epiphytic lichen richness was higher on maple trees than spruce trees, and tree
species differed in the number of rare epiphytic species. Several pollution-sensitive
epiphytes were restricted to the maples: the cyanolichens Leptogium cyanescens
(bipartite) and Lobariapulmonaria (tripartite), the large ruffle lichen Parmotrema
crinitum, and the moss Zygodon viridissimus var. rupestris. Cyanolichens only occurred
on maple bark and did not occur on any bark with a pH below 5.02. Apparent overlap
between the bark chemistry of spruce and maple, particularly for samples from higher on
maple boles, suggest a reduction in the area of chemically suitable substratum for
epiphytes.
5.2.4 Soil Biota
Soil biota were not specifically addressed in the 2008 ISA. Since the 2008 ISA, several
studies have evaluated the relationships between soil chemistry indicators of acidification
and soil biota (Table 5-1).
5.2.4.1 Soil Chemical Indicators for Soil Biota
Soil pH and Exchangeable Calcium:Aluminum Ratio
Bardhan et al. (2012) evaluated the relationships between soil chemistry and bacterial
diversity in 30 plots along a soil chemistry and deposition gradient in high-elevation
spruce-fir forests in the Great Smoky Mountain National Park (GSMNP). Modeled S
deposition ranged from 6 to 41 kg S/ha/yr, measured soil pH ranged from 3.0 to 4.6, and
measured CEC ranged from 1.3 to 23.1 (soil samples pooled from the 0-, A-, and
B-horizons). However, bacterial diversity and community composition did not change
along the gradients of S deposition, soil pH, or exchangeable Ca:Al ratio.
Soil pH and Aluminum Concentrations
Chen et al. (2013) evaluated the impacts of S additions on soil microbial and nematode
communities in a grassland system of Inner Mongolia. Seven treatments of 28 to 166 mol
H+/ha were applied in three doses in the form of sulfuric acid (H2SO4) from 2009 to 2010.
The authors found that the proportions of soil bacteria, fungi, and nematodes were altered
by the treatments, and the responses were related to soil pH and Al concentrations.
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Increases in fungal fatty acids (49% increase) and fungi:bacteria ratio (120% increase)
and decreases in total and bacterial fatty acids (40-47% decrease) relative to the controls
were attributed to soil pH and A1 concentrations. High A1 concentrations (51 to
83 mg/kg) were associated with decreases in total fatty acids and bacterial fatty acids and
increases in fungal fatty acids. These results are consistent with a study of an agricultural
soil gradient that showed that at soil pH below 4.5, microbes (bacteria and fungi) are
decreased due to increased A1 solubility (Rousk et al.. 2009). and that fungi are often
more dominant in acidic soils. Chen et al. (2013) also reported that acid additions also
impacted the soil nematode community by initially increasing the total number of soil
nematodes and then altering nematode community composition: bacterivorous and
fungivorous nematodes increased, but plant-feeding and omnivorous and carnivorous
nematodes decreased. The shifts in the nematode community were attributed to decreased
soil pH and changes in soil moisture.
Soil pH and Exchangeable Calcium
One study also investigated the influence of Ca addition (-1,000 kg Ca/ha/yr in 1999) on
the soil bacterial community in a northeastern hardwood forest (Sridevi et al.. 2012V The
study detected 1,756 taxa spanning 42 phyla, 53 classes, 127 orders, and 154 families in
the Ca treated and reference watersheds. Bacterial community structure was significantly
different between the Ca treated and nontreated reference soils, with differences among
communities being more pronounced in the mineral soils. Calcium additions resulted in
significant changes in bacterial community composition in the organic and in the mineral
soil horizons. The numbers of detectable taxa in families such as Acidobacteriaceae,
Comamonadaceae, and Pseudomonadaceae were lower in the Ca amended soils, while
Flavobacteriaceae and Geobacteraceae were higher. Analyses of relationships between
soil chemistry and the bacterial communities indicated that only exchangeable Ca, pH,
and P were significantly correlated with bacterial community structure.
Soil pH
Gilliam et al. (201 lb) evaluated the microbial community across a soil weathering
gradient in a northern hardwood forest in West Virginia. Microbial community
composition, characterized through phospholipid fatty acid (PLFA) analysis, varied
among sites. Fungi were dominant at the most weathered, low NO, -production site,
while Gram-negative bacteria were significantly higher at the less weathered, moderate
and high NO, -production sites. Accordingly, the fungi:bacteria ratio increased in the
direction of the low NO, -production plots in ordination space. Correlations between the
soil parameters and PLFA results suggest that low soil pH and NO, concentrations
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supported fungal dominance, although other important factors including differences in
plant community and clay and organic matter content may have also influenced the soil
microbial community.
Soil Exchangeable Calcium
A study in Japan evaluated the relationship between forest type and soil invertebrate
communities in evergreen broad-leaved forests versus Japanese cedar (Cryptomeria
japonica) plantation forests (Ohta et al.. 2014). Exchangeable Ca was found to be
significantly higher in soil from the Japanese cedar plantations than the evergreen forest.
The invertebrate community composition also differed significantly between the two
forest types and was best explained by exchangeable Ca concentrations. Two major taxa
of soil crustaceans, Talitridae and Ligidium japonicum, were only found in the Japanese
cedar plantations. In contrast, millipedes (Paradoxosomatidae) and beetles were relatively
abundant in the evergreen plots.
5.2.5 Fauna
Fauna were not specifically assessed in the 2008 ISA. Since the 2008 ISA, two studies
were found that evaluated the relationships between soil chemistry indicators of
acidifying deposition and fauna (Table 5-1).
5.2.5.1 Soil Chemical Indicators for Fauna
Soil Exchangeable Calcium
Beier etal. (2012) characterized the variation in gastropod, salamander, and vegetation
communities among northern hardwood forests attributable to soil exchangeable Ca. The
sites represented the variability in soil Ca in the Adirondack Mountains, ranging from
1.83 to 53.89 cmolc/kg (Oa-horizon) and 0.28 to 7.73 cmolc/kg (B-horizon). Snail
community richness and the abundance and live biomass of redback salamanders
(Plethodon cinereus) were all positively correlated with soil Ca. Land snail species
richness and abundance were positively correlated with Oa-horizon Ca and negatively
related to SO42 deposition and site elevation (and NO3 deposition for snail abundance).
Salamander communities were dominated by mountain dusky salamanders
(Desmognathus ochrophaeus) at Ca poor sites, with composition continuously shifting
toward dominance by redback salamanders as Ca availability increased. Several known
calciphilic species of snails (Paravitrea multidentata, Gastrocopta pentodon, and
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Euconolus polygyratus) were found only at the highest-Ca sites. Some of the
observations (e.g., decreasing snail abundance) were confounded by a strong positive
correlation between elevation and estimated acid deposition. However, although the
underlying mechanisms require further study, these findings indicate that Ca availability,
which is shaped by geology and acidic deposition inputs, influences northern hardwood
forest ecosystems at multiple trophic levels.
Soil Exchangeable Calcium and pH
Pabian and Brittingham (2012) determined the relationships between soil (Oa-horizon)
chemistry and forest bird community composition, abundance, and diversity, and
evaluated potential mechanisms responsible for the relationships in oak and red
maple-dominated forests in Pennsylvania. Mean soil exchangeable Ca and pH for the
14 forest sites ranged from 5.28 to 23.5 meq/100 g and 3.6 to 5.1 meq/100 g,
respectively. Bird community composition (species richness and species abundances)
varied with soil Ca and pH, with 10 bird species having the highest abundances in forests
with high-Ca soils, and 5 species having the highest abundances with low-Ca soils. Five
species were classified as "generalists" because they had high abundances and were
present at all forest sites. Bird species associated with low-Ca soils were associated with
high densities of mountain laurel (Kalmia latifolia) and five tree species whose basal
areas were explained by low soil pH and Ca. Bird species associated with high-Ca soils
were associated with high densities of saplings and high basal areas of acid-sensitive tree
species (17 species whose basal areas were, in part, explained by high Ca and soil pH).
All environmental and soil variables explained 37.8% if the variation in bird species
abundance data, with environmental variables explaining 36.0%, soils explaining 0.5%,
and 1.3% being explained by both. Most (67%) of the variation in the bird abundance
data explained by soils was also explained by the vegetation and invertebrate variables,
thereby supporting the hypothesis that the environmental variables were responsible for
the soil-bird relationships.
5.3 Characteristics, Distribution, and Extent of Sensitive
Ecosystems
In the 2008 ISA, it was known that geology (particularly surficial geology) is the
principal factor governing the sensitivity of terrestrial and aquatic ecosystems to
acidification from S and N deposition. Geologic formations with low base cation supply
(e.g., sandstone, quartzite), due mainly to low weathering, generally underlie the
watersheds of acid-sensitive lakes and streams. Bedrock geology has been considered in
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numerous acidification studies (Sullivan et al.. 2007b; Vertucci and Eilers. 1993; Stauffer
and Wittchen. 1991; Stauffer. 1990; Bricker and Rice. 1989). Other factors contribute to
the sensitivity of soils and surface waters to acidifying deposition, including topography,
soil chemistry, land use, and hydrologic flowpath.
Forests of the Adirondack Mountains of New York, Green Mountains of Vermont, White
Mountains of New Hampshire, the Allegheny Plateau of Pennsylvania, and mountain
tops and ridges forest ecosystems in the southern Appalachians are the region's most
sensitive to terrestrial acidification from atmospheric deposition (Section 3.2.4.2 of 2008
ISA). Recent decreases in acid deposition had been linked to improvements in surface
water chemistry (Chapter 7). However, there remains widespread measurements of
ongoing depletion of exchangeable base cations in forest soils in the northeastern U.S
(Chapter 4).
At the time of the 2008 ISA, there had been no systematic national survey to determine
the extent and distribution of terrestrial ecosystem sensitivity to the effects of acidifying
deposition. However, one preliminary national evaluation by McNultv et al. (2007) used
a simple mass balance model and available national databases to estimate forest soil
critical acidifying deposition loads (for wet and dry deposition of S and N) and
exceedances. They found that approximately 15% of forest soils in the U.S. receive
acidifying deposition that exceeds the estimated critical load of wet and dry deposition of
S and N by more than 250 eq/ha/yr (McNultv et al.. 2007). The areas where exceedances
reach this level could be considered to represent those areas that are likely most sensitive
to continued high levels of acidifying deposition. Alternatively, or in addition to
sensitivity distributions based on critical load evaluations, it might be possible to identify
forest areas that are sensitive to acidifying deposition by mapping the distribution of acid
sensitive species like red spruce and sugar maple.
Since the 2008 ISA, a series of studies have evaluated the characteristics, distribution,
and/or sensitivity of ecosystems to acidifying N and S deposition. For descriptions of
studies that characterized ecosystem sensitivity through critical load and critical load
exceedance determinations, see Section 5.5.
Rov et al. (2012) conducted a life cycle impact assessment (LCIA) to derive spatially
explicit soil sensitivity factors (SFs) for terrestrial acidification at a global scale, which
included the U.S. The four different soil chemistry indicators assessed were: Bc:Al,
Al:Ca, soil solution pH, and dissolved Al concentrations. These factors were calculated
using the PROFILE model and a global set of regional soil parameters. The Bc:Al and
Al:Ca indicators were unable to provide a sufficient level of discrimination. Soil solution
pH was found to be the best SF, as it was less influenced by input parameter
uncertainties. The highest pH-based SFs (i.e., greatest sensitivity to changes in soil pH in
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response to N and S deposition) were found in Canada, Scandinavia, the Amazon, central
Africa, and East and Southeast Asia. However, a Monte Carlo analysis showed that input
parameter variability may cause SF variations greater than six orders of magnitude for
certain indicators.
In a second study, Rov et al. (2014) conducted a life cycle analysis (LCA) to quantify and
compare the influence of spatial variability and statistical uncertainty in characterization
factors (CFs) for acidifying pollutants on a global scale. CFs were calculated based on
atmospheric fate (relationship between N and S emission and deposition locations), soil
sensitivity (ability of receiving location to withstand changes in soil pH in response to N
and S deposition and function of soil properties and environmental conditions of
receiving location), and effect (potential loss of plant community biodiversity due to
changes in soil pH). The CFs for terrestrial acidification were defined as a change in the
potentially not occurring fraction of vascular plant species (PNOF) summed over the
receiving areas due to marginal change(s) in the emission of acidifying substance at the
source location. Spatial variability in the CFs was found to be much larger than statistical
uncertainty (i.e., six orders of magnitude vs. two orders of magnitude). Spatial variability
was largely drive by the atmospheric fate and soil sensitivity factors, while the ecological
effect factor was the main source of statistical uncertainty. In general, emission locations
with the highest atmospheric fate factors were located on the western coasts of the
different continents and are globally consistent with the worldwide north-east dominant
winds. Cells with soils and vegetation types that were particularly sensitive to acidifying
deposition (e.g., northern Canada and Scandinavia) had high CF scores.
Two studies were conducted in Canada to evaluate the sensitivity of forest soils to
deposition based on an emissions management framework [EMF (Whitfield et al.. 2010b;
Whitfield et al.. 2009)1. The EMF uses modeled changes in soil base saturation and soil
solution Bc:Al relative to site-specific, policy-relevant thresholds. EMFs are calculated as
half the change between the estimated preindustrial condition and a fixed endpoint for
base saturation (10%) and soil solution Bc:Al of 2. In the first study, Whitfield et al.
(2009) predicted the impacts of increased S emissions and deposition (from 1900-2100)
on 11 jack pine stands with acid-sensitive soils in the Athabasca oil sands region in
Alberta, Canada using the MAGIC model and the EMF. MAGIC model simulations were
conducted for a historical period (1900-2006) and a future period (2006-2100) under
two different scenarios: (1) base case (2006 deposition constant from 2006 to 2100), and
(2) double S (S deposition doubled linearly from 2006 to 2020 and remaining constant
thereafter). Model simulations during the 105-year hindcast period (1900-2005) showed
limited changes in base saturation, but considerable decreases in soil solution Bc:Al rates.
Similarly, the future S deposition scenarios resulted in no or small changes in base
saturation and additional declines in Bc:Al ratios. Declines in the Bc:Al ratios were
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greatest in response to the double S scenario, which was consistent with S deposition
exceeding base cation deposition, predicted retention of base cations on the soil exchange
complexes, and the limited ability of upland soils to retain S. Although the site-specific
critical thresholds for base saturation and Bc:Al ratio varied widely, none of the 11 sites
were predicted to reach the EMF thresholds for base saturation by 2100. In contrast,
under the base-case scenario, modeled Bc:Al ratios were predicted to reach the chemical
threshold at two and three sites within 15 and 30 years. Under conditions of double S
deposition, seven sites were predicted to be at the EMF threshold levels within 30 years.
However, the site-specific thresholds were found to be stringent relative to chemical
thresholds and associated criteria (e.g., Bc:Al of 10) used elsewhere and the impacts of S
deposition in the region were anticipated to be minimal.
In a second study, Whitfield et al. (2010b) evaluated the need for emission control
policies in the Athabasca oil sands region of Alberta, Canada by simulating the impacts
of historical and future deposition in 50 lake catchments (forest soil chemistry was
modeled on 28 catchments). The MAGIC model was calibrated to forest soils (plot-level)
and whole catchments, and sensitivity to deposition was evaluated based on an EMF.
Similar to the earlier Whitfield et al. (2009) study, simulations were conducted for a
historical period (1900-2005) and a future period (2006-2035) under two future
scenarios: (1) base case (2005 deposition constant from 2006 to 2035) and (2) double
acid (S and N deposition doubled linearly from 2005 to 2020 and remaining constant
thereafter). Model simulations during the 105-year hindcast period (1900-2005) showed
limited changes in base saturation, although base saturation values varied considerably
across the sites. Limited changes in base saturation were attributed to base cation
deposition, which offset increases in SO42 deposition. Across the southern region of the
study area, base cation deposition averaged 70-80% of SO42 deposition. Similarly,
neither future scenario out to 2035 resulted in large changes to base saturation. Under
elevated acid deposition (double acid scenario), base saturation only decreased by an
average of 0.1% by 2035. In contrast, soil solution Bc:Al responses were highly variable
and dependent on base cation weathering (BCw) rates (generated by the PROFILE
model). Comparison of model simulations with the thresholds of tolerable change
specified under the EMF indicated that many sites within the study area could reach a
Bc:Al below 2 under both future deposition scenarios. However, in general, the modeled
2005 Bc:Al remained well above 2, suggesting limited historical impact of N and S
deposition.
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5.4 Application of Terrestrial Acidification Models
The models that were used in recent studies to evaluate terrestrial acidification and its
components included the simple mass balance [SMB (Phelan et al.. 2014; Duarte et al..
2013; Jung et al.. 2013; Whitfield and Watmough. 2012; Forsius et al.. 2010; McNultv
and Boggs. 2010; Nasr et al. 2010)1. soil texture approximation [STA (Whitfield et al..
2010c)], MAGIC (Sullivan etal.. 2011a; Whitfield et al.. 2010b; Whitfield et al.. 2009).
ForSAFE-Veg (McDonnell et al.. 2014a; Sverdrup et al.. 2012). and empirical models
outlined by the Spranger et al. (2004) (Krzvzanowski. 2011). See Section 4 A for a review
of models.
Phelan et al. (2014) applied the PROFILE model to estimate BCw to support SMB
critical load estimates for 51 hardwood forest sites in Pennsylvania. The rates of BCw
ranged from 119 to 9,245 eq/ha/yr, and were consistent with soil properties and regional
geology. Critical loads ranged from 4 to 10,503 eq/ha/yr. These estimates were three
times larger than those reported for the same sites by McNultv et al. (2007) who used the
clay correlation-substrate method and SMB models to estimate BCw rates and critical
loads, respectively. Base cation weathering rates estimated by PROFILE were, on
average, almost three times larger than those estimated by the clay correlation-substrate
method. These results suggest that the hardwood sites in Pennsylvania may not be as
sensitive to acidifying deposition as previously estimated. However, as the study only
tested and compared the PROFILE model in Pennsylvania, the researchers recommended
applying PROFILE in different regions and ecosystems in the U.S. to gain a better
understanding of the model performance and the degree to which BCw rates estimated by
PROFILE differ from those estimated using the clay correlation-substrate model.
Several studies were also conducted in Canada that evaluated models and methods to
estimate and extrapolate BCw rates. Whitfield et al. (2010c) calculated critical loads and
exceedances for 333 sites in the Athabasca oil sands region of Alberta, Canada using the
SMB model and a soil solution Bc:Al ratio of 10 as the chemical criterion and threshold
value, respectively. Rates of BCw were determined using the PROFILE and STA (based
on percent clay content) models. At 43 sites, the STA model was recalibrated based on a
stepwise regression using clay and loss-on-ignition (LOI) as the model parameters, and
the recalibrated model was applied to the 290 remaining sites. The BCw rate estimate
were similar in the two models (0 to 72 meq/m2/yr for STA and 1.6 to 74 meq/m2/yr for
PROFILE) and low, resulting in very low critical loads that averaged 580 meq/ha/yr
under the assumption of complete N retention and 400 meq/ha/yr when all deposited N
was leached from the soil rooting zone.
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Base cation weathering rates and SMB critical loads of S were calculated for upland
forest sites in Saskatchewan, Canada using a new method to approximate BCw rates for
the region: empirical regression approximation [ERA (Whitfield and Watmough. 2012)1.
This new method was developed by forward stepwise multiple regression of soil and site
properties with BCw rates calculated by the PROFILE model at 35 sites with detailed
physicochemical data. Sand content, soil moisture, and latitude were important prediction
variables in the ERA. The BCw rates varied widely across the study area (0.1 to
8,000 mmolc/m3/yr), which was consistent with the contrasting soil properties. Sites with
very low BCw rates had quartz-dominated mineralogy and coarse-textured soils with
very low surface areas. Critical loads varied by ecoregion, with medians ranging from
140 to 1,120 mmolc/ha/yr.
5.5 Levels of Deposition at Which Effects Are Manifested
Since the 2008 ISA, several studies have evaluated the relationships between N and S
deposition and the growth and physiology of terrestrial organisms and ecosystem
function. In addition, numerous studies have used estimates of critical load exceedances
caused by historic, current, and future N and S deposition levels to characterize the
impacts of acidifying deposition. In this section, these relationships are described as
(1) impacts of elevated N and S deposition, (2) impacts of ambient levels of N and S
deposition, and (3) critical loads and exceedances.
5.5.1 Impacts of Elevated Nitrogen and Sulfur Deposition
A number of studies published since the 2008 ISA have evaluated the impacts of elevated
N and S deposition on trees, herbaceous species, and soil biota (Table 5-4). "Elevated" N
and S deposition in this section refers to additions of N and S above current atmospheric
deposition.
In Bear Brook Watershed, ME, Bothers et al. (2009) investigated the effects of
chronically elevated N and S deposition (i.e., 25.2 kg N/ha/yr and 28.8 kg S/ha/yr
additions since 1989) on growth, foliar nutrients, and photosynthetic capacity of sugar
maple saplings. Sugar maple saplings in the treated watershed had higher foliar Al
(+56%), N (+15%), P (+10%), and K (+15%) and lower foliar Ca (-25%) compared to
nontreated watershed, presumably through influences on soil chemistry. The treated
saplings also had lower photosynthetic capacity, high N:P ratios, negative correlations
between leaf N and electron transport capacity, and reduced carboxylation capacity,
which suggest nutrient imbalances induced by the elevated N and S deposition. However,
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sapling growth was unaffected by the treatments. In another study conducted in Quebec,
Canada, Moore and Houle (2013) observed similar results in their evaluation of the
effects of 8 years of NH4NO3 additions (26 kg N/ha/yr and 85 kg N/ha/yr applied from
2001-2008) on sugar maple physiology and soil chemistry. Foliar Ca in the high N
treatment decreased by 79% compared to the control and reached 0.24%, the lowest foliar
Ca concentration ever reported for sugar maple. The treatments did not significantly alter
dieback rate or basal area growth. These results corresponded to changes in soil
chemistry; the treatments significantly decreased exchangeable Ca, Mg, Mn, and K in at
least one of the top organic soil layers. The largest differences were observed for
exchangeable Ca between the control and the high N treatment, with the L and the H
layers of the soil organic horizon showing exchangeable Ca decreases of 29 and 72%,
respectively. These results suggest that increased N deposition can strongly affect Ca
nutrition of sugar maple at sites with low base cation saturation.
In West Virginia, Jensen et al. (2014) examined long-term impacts of relatively high N
and S additions (22 years of 169 kg/ha/yr (NH^SC^) on black cherry and yellow poplar
(Liriodendron tulipifera) bole wood Ca, Mg, and Mn concentrations; tree growth; and
basal area. Bole wood Ca concentrations were lower and Mn concentrations higher in
both species on the treated versus nontreated watershed. Growth responses, measured
through relative growth rates of cored trees and changes in basal area, were not
conclusively affected by the treatment.
Jung and Chang (2012) evaluated the impacts of 4 years of elevated N and S deposition
(30 kg N/ha/yr, 30 kg S/ha/yr, and 60 kg N + S/ha/yr additions from 2006 to 2009) on a
forest composed of trembling aspen (Populus tremuloides), white spruce (Picea glauca),
balsam fir, black spruce (Picea mariana), and paper birch (Betula papyrifera) in the
Athabasca oil sands region of Alberta, Canada. None of the treatments influenced the
growth of the understory plants or soil microbial biomass; understory and microbial
community composition were not measured. However, N increased tree growth in the N
and N + S treatments, indicating N limitation. Nitrogen and S additions decreased soil
exchangeable Ca2+ and Mg2+, and these decreases were attributed to a combination of
increased tree uptake to support greater growth and increased leaching with SO42 .
Bowman et al. (2012) evaluated the impacts of 3 years of elevated N deposition (5, 10,
and 30 kg N/ha/yr from 2006 to 2009) on alpine vegetation and soils in Rocky Mountain
National Park, CO. The study found that species richness and diversity did not change,
but the cover of Carex rupestris increased from 34 to 125%. No changes in soil pH or
extractable cations were detected. Therefore, changes in plant species composition was
most likely due to N enrichment.
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Guv et al. (2013) conducted a greenhouse experiment to assess the potential effects of
acidic deposition on the root system morphology of three endemic species that grow on
sand dunes in the Athabasca oil sands region of Alberta, Canada: Armeria maritime,
Deschampsia mackenzieana, and Stellaria arenicola. Plants were exposed to three pH
treatments (pH 5.6, 5.0, and 4.2) together with additions of 2.61 to 4.67 mg/L of SOr
and 1.95 to 3.51 mg/L NOs, for 55-60 days. There were no statistically significant
differences in plant survival, root length, root surface area, or root tip numbers between
acid treatments. Therefore, current rates of acidifying N and S deposition are not likely a
threat to these species.
Since the 2008 ISA, three studies were identified on the impacts of N and/or S deposition
on soil biota. Payne et al. (2010) examined the impacts of elevated SO42 deposition on
the microbial community in a Scottish peatland and showed that additions of 95 kg
SO42 /ha/yr applied over 18 months decreased the concentrations and percentages of live
amoebae. Abundances of Trimena lineare, Corythion dubium, and Euglypha rotunda
were also significantly reduced. These results suggest the potential importance of SO42
deposition in influencing testate amoebae communities in the peatland soils. In another
study, Chen et al. (2013) evaluated the impacts of S additions on soil microbial and
nematode community composition in an Inner Mongolian grassland in China. Seven
treatments of 28 to 166 mol H+/ha were applied in three doses in the form of sulfuric acid
(H2SO4) from 2009 to 2010. Fungal fatty acids were increased by 49% and fungi:bacteria
ratio increased by up to 120% by the acid additions. Total and bacterial fatty acids were
decreased by the S treatments by up to 47 and 40%, respectively. Acid additions also
impacted the soil nematode community by initially increasing the total number of soil
nematodes, then altering community composition; bacterivorous and fungivorous
nematodes increased, while plant-feeding and omnivorous and carnivorous nematodes
decreased. Hu et al. (2013) examined the impacts of N and S additions on soil microbial
biomass and function in a boreal mixed-wood forest in the Athabasca oil sands region of
Alberta, Canada. Five years of N and S additions (30 kg N/ha/yr and/or 30 kg S/ha/yr)
did not influence soil microbial biomass C and N. However, activities of some
extracellular enzymes in the soil were decreased by the treatments, with greater
(3-glucosidase activity in the N + S treatment than in the S treatment and decreased soil
arylsulfatase activity in the S addition treatment. Thus, the additions of N and/or S
strongly affected soil microbial community functions and enzymatic activities without
changing soil microbial biomass in this boreal forest.
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Table 5-4 Impacts of acidifying nitrogen and sulfur deposition.
Reference
Ecosystem Type/Region
Species
Nitrogen and Sulfur
Deposition/Additions
Description
Bardhan et al. (2012)
Forest/Great Smoky
Mountain National Park,
TN, NC
Soil microbes (bacteria) 6 to 41 kg S/ha/yr (modeled)
Soil analyses indicated only minor
differences in bacterial diversity among
sites; the bacterial community did not
change along the gradients of S deposition.
Bethers et al. (2009)
Forest/Bear Brook
Watershed, ME
Sugar maple
Ambient: 8.4 kg N/ha/yr; 14.4 kg
S/ha/yr; elevated: 25.2 kg N/ha/yr and
28.8 kg S/ha/yr
Treated watershed had a 56% increase in
foliar Al, a 25% reduction in foliar Ca, N
(+15%), P (+10%), and K (+15%). The
treated saplings had lower photosynthetic
capacity, high N:P ratios, and negative
correlations between leaf N and electron
transport capacity, which may indicate
nutrient imbalance.
Bowman et al. (2012)
Dry meadow
community/Rocky
Mountain National Park,
CO
Alpine meadow species
Ambient: 4 kg N/ha/yr; elevated: 5,
10, and 30 kg N/ha/yr
Found that species richness and diversity
did not change, but Carex rupestris cover
increased from 34 to 125%. Changes in
species composition most likely attributable
to N enrichment.
Chen et al. (2013)
Grassland/Mongolia,
China
Soil microbes, bacteria,
fungi, and nematodes
Sulfuric acid (0, 2.76, 5.52, 8.28,
11.04, 13.8 and 16.56 mol H+/m2)
Fungal fatty acids were increased by 49%
and fungi:bacteria ratio increased by up to
120% by the acid additions relative to the
controls. Total and bacterial fatty acids
were decreased by the S treatments by up
to 47 and 40%, respectively. In the
treatments, bacterivorous and fungivorous
nematodes increased, while plant-feeding
and omnivorous + carnivorous nematodes
decreased.
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Table 5-4 (Continued): Impacts of acidifying nitrogen and sulfur deposition.
Reference
Ecosystem Type/Region
Species
Nitrogen and Sulfur
Deposition/Additions
Description
Cleavitt et al. (2011a) Forest/Acadia National
Park, ME
Epiphytic lichens
12 to 18 kg S/ha/yr
Throughfall chemistry influenced bark pH
and the suitability of tree boles as habitat
for lichen; epiphytic lichen species richness
and presence of pollution-sensitive
epiphytes were greater on red maple trees,
which have a higher pH in the bark relative
to red spruce trees.
Dietze and Moorcroft
(2011)
Forest/eastern and central
portions of the U.S.
267 tree species
organized into 10 PFTs
6 to 16 kg/ha/yr as NO3 ; 4 to
30 kg/ha/yr as S042" (NADP wet)
Mean sensitivity by covariate and PFTs
showed that overall tree mortality was most
sensitive to atmospheric pollutants, with
acid deposition (SO42") showing the highest
sensitivity and N deposition the third
highest sensitivity. Stand DBH showed the
second highest sensitivity.
Duarte et al. (2013) Forest/northeastern U.S. 21 tree species
256 to 920 eq/ha/yr of N; 242 to
1,154 eq/ha/yr of S (modeled)
Statistically significant negative correlations
between critical load exceedance and
growth (17 species), and crown density
(4 species) were determined. Positive
correlations between critical load
exceedance and declining vigor
(4 species), crown dieback (4 species), and
crown transparency (7 species) were
determined. Species that were most
negatively affected by N and S deposition
included balsam fir, red spruce, quaking
aspen, and paper birch.
Guv et al. (2013)
Sand dunes/Athabasca oil
sands region in Alberta,
Canada
Armeria maritima,
Stellaria arenicola, and
Deschampsia
mackenzieana
2.61 to 4.67 mg/L of SO4 and 1.95 to
3.51 mg/L NO3 (additions)
In a greenhouse experiment, there were no
significant differences in survival, root
length, surface area, or tip numbers among
acid treatments.
Hu et al. (2013)
Forest/Alberta, Canada
Soil microbes
30 kg N/ha/yr as NH4NO3; 30 kg
S/ha/yr as Na2SC>4 (additions)
Five years of N and S additions did not
influence soil microbial biomass C and N.
However, soil microbial community-level
physiological profiles were significantly
impacted.
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Table 5-4 (Continued): Impacts of acidifying nitrogen and sulfur deposition.
Reference
Ecosystem Type/Region
Species
Nitrogen and Sulfur
Deposition/Additions
Description
Jensen et al. (2014)
Forest/Fernow
Experimental Forest, WV
Yellow poplar and black 169 kg/ha/yr of (NhU^SCM (addition)
cherry
Bole wood Ca concentrations were lower
and Mn concentrations were higher in both
species on the treated watershed. Growth
responses were not conclusive and
appeared to differ by species.
Jung and Chang
(2012)
Forest/Alberta, Canada
Trembling aspen, white
spruce, balsam fir, black
spruce, and paper birch
30 kg N/ha/yr, 30 kg S/ha/yr, and
60 kg N + S/ha/yr (additions)
Nitrogen addition increased tree growth in
the N and N + S treatments. None of the
treatments affected understory growth or
soil microbial biomass. Annual leaching
losses of SO42" were increased by S and
S + N additions. Leaching of base cations
showed a similar trend to SO42" leaching.
Miller and Watmough Forest/southern Ontario, Sugar maple
(2009) Canada
9 to 12.8 kg N/ha/yr; 7.6 to 14.8 kg
S/ha/yr (ambient)
Sugar maple foliar S and N contents were
positively correlated with modeled N and S
deposition. Foliose lichen species richness
was negatively correlated with modeled air
pollution levels (S deposition, N deposition,
and atmospheric ozone).
Moore and Houle
(2013)
Forest/Lake Clair
Watershed, Quebec,
Canada
Sugar maple
26 kg N/ha/yr; 85 kg N/ha/yr
(additions)
Foliar Ca and Mn concentrations
decreased with increasing levels of N
addition, while foliar N increased. Foliar Ca
in the high N treatment decreased by 79%
compared to the control and reached
0.24%. No significant treatment effects
were observed for dieback rate or basal
area growth, although mean dieback rate of
sugar maple in the high N treatment was
43% higher than in the control.
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Table 5-4 (Continued): Impacts of acidifying nitrogen and sulfur deposition.
Reference
Ecosystem Type/Region
Species
Nitrogen and Sulfur
Deposition/Additions
Description
Pannek et al. (2015)
Acidic grassland/Atlantic
biogeographic region of
Europe
44 grassland species
within the Violion
caninae alliance
2.4 to 43.5 kg N/ha/yr (ambient)
Out of 44 species studied, 16 were affected
by N deposition, with 12 ofthem exhibiting
a negative response. Soil pH and P
influenced 24 and 14 species, respectively,
predominantly positively. Species that were
negatively affected by high N deposition
and/or high soil P also showed a negative
temporal trend characterized by short
stature and slow growth.
Payne et al. (2010) Peatland/Scotland
Soil microbes (testate
amoebae)
Ambient: 5 kg SO42 /ha/yr; elevated:
95 kg S042"/ha/yr
Analysis showed that the SO42" treatment
reduced the concentrations and
percentages of live amoebae, suggesting a
less active community as a result of the
treatment. In addition, abundances of
Trimena linear, Corythion dubium, and
Euglypha rotunda were significantly
reduced.
Quesnel and Cote
(2009)
Forest/boreal region of
Canada
White spruce
NA
Meta-analysis of foliar results (nutrient
concentrations) from 23 white spruce
forests (natural and nonfertilized plantation
forests) revealed that N deficiencies
occurred in less than 10% of the sites.
Base cation deficiencies identified were
attributed to removals with harvest, higher
requirements of white spruces for K and
Ca, and nutrient deficiencies/imbalances
induced by N additions/deposition.
Soule (2011)
Forest/Grandfather
Mountain, NC
Red spruce
NA
Radial growth rates of red spruce increased
through time, and growth rates were
significantly related to temperature
(positive), days with precipitation
(negatively), atmospheric CO2 (positively),
and emissions of SOx and NOx
(negatively).
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Table 5-4 (Continued): Impacts of acidifying nitrogen and sulfur deposition.
Reference
Ecosystem Type/Region
Species
Nitrogen and Sulfur
Deposition/Additions
Description
Sullivan et al. (2013)
Forest/Adirondack
Mountains, NY
Sugar maple
750 to 1,120 eq/ha/yr as N + S
(NADP wet, CASTNET dry)
Found that plots without sugar maple
seedlings had higher rates of atmospheric
N + S deposition.
Thomas et al. (2013)
Forest/Appalachian
Mountains, WV
Eastern redcedar
NA
Dendroisotopic techniques showed the
recovery of eastern redcedar trees from
decades of S pollution. Analysis provided
evidence for a distinct physiological
response to changes in atmospheric SO2
emissions since 1980.
Cleavitt et al. (2015)
Forest/VT, NH, ME
Lichens
3 to 8 kg N/ha/yr and 4.5 to 5.2 kg
S/ha/yr
Annual mean and cumulative N deposition
was strongly correlated with decreases in
lichen species richness, decreases in N
sensitive species, and poorer thallus
condition. Cumulative dry deposition of S
had the best fit to decreases in thallus
condition, poorer community-based S index
values, and the absence of many S
sensitive species.
Al = aluminum; C = carbon; Ca = calcium; CASTNET = Clean Air Status and Trends Network; C02 = carbon dioxide; DBH = diameter at breast height; eq = equivalents;
H+ = hydrogen ion; ha = hectare; K = potassium; kg = kilogram; L = liter; m = meter; mg = milligram; MN = manganese; mol = mole; N = nitrogen; NA = not applicable;
Na2S04 = sodium sulfate; NADP = National Acid Deposition Program; NH4N03 = ammonium nitrate; (NH4)2S04 = ammonium sulfate; N03~ = nitrate; NOx = the sum of nitric oxide and
nitrogen dioxide; P = phosphorus; PFT = plant functional types; S = sulfur; S02 = sulfur dioxide; S042" = sulfate; SOx = sulfur oxides; yr = year.
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5.5.2
Impacts of Ambient Deposition
Five studies that were published since the 2008 ISA have been identified that
documented the impacts of current rates of ambient N and S deposition on terrestrial
biological endpoints, including tree species, tree species grouped into plant functional
types (PFTs), lichens, and soil biota (Table 5-4). "Ambient" N and S deposition in this
section refers to the levels of atmospheric N and S deposition experienced during the time
of the specified study.
Dietze and Moorcroft (2011) conducted a large-scale analysis of central and eastern U.S.
that investigated 13 covariates (including climate, air pollutants [N deposition, acid
deposition, and ozone], topography, and stand characteristics) as predictors of individual
tree mortality. Tree species (267 species) were grouped into 10 PFTs based on
hardwoods/softwoods, latitude, successional phase (early, mid, and late successional),
and hydrological soil status (i.e., hydric). The researchers found that tree mortality was
most sensitive to stand characteristics and air pollutants. Nine PFTs had decreased
mortality with increased N deposition, and only the northern mid-successional hardwoods
showing the opposite pattern (i.e., increased mortality with increased N deposition).
Seven PFTs showed large increases in mortality with acid deposition (as SO42 ). with
only late successional conifers showing the inverse (i.e., a weak decline in mortality with
increased acid deposition). Mean sensitivity by covariate and PFT showed that overall
tree mortality was most sensitive to atmospheric pollutants, with acid deposition (SO42 )
showing the highest sensitivity and N deposition the third highest sensitivity. Individual
tree DBH showed the second highest sensitivity.
Duarte et al. (2013) evaluated the responses of tree species in 4,057 forest plots in the
northeastern U.S. to the exceedance of critical loads of N and S deposition. Modeled S
and N deposition ranged from 242 to 1,154 eq/ha/yr and 256 to 920 eq/ha/yr,
respectively. Critical loads were exceeded in 45% (calculated using midpoint weathering
rates) of the plots. See Section 5.5.3 for a greater description of critical loads and
exceedances from this study. Results from Spearman's rank correlation analyses showed
that the growth of 17 species and crown density of 4 species were negatively correlated
with critical load exceedance (Table 5-5). Positive correlations between critical load
exceedance and declining vigor (three species), crown dieback (four species), and crown
transparency (seven species) were also found (Table 5-6). Crown dieback was considered
the most reliable indicator of forest health. Based on this metric, balsam fir, red spruce,
quaking aspen, red maple, and paper birch were identified as the species most negatively
impacted by N and S deposition.
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Table 5-5 Results of Spearman's rank correlation analysis comparing growth
versus critical load exceedance by species for the forested plots in
the northeastern U.S. [from Duarte et al. (2013)1. Modeled sulfur and
nitrogen deposition on the plots ranged from 242 to 1,154 eq/ha/yr
and 256 to 920 eq/ha/yr, respectively. Correlations shown here are
significant at a = 0.05.
Species
Correlation Coefficient
Sample Size (n)
Black spruce (Picea mariana)
-0.44
41
Balsam fir (Abies balsamea)
-0.33
499
Chestnut oak (Quercus prinus)
-0.28
238
Paper birch (Betula papyrifera)
-0.27
574
Scarlet oak (Quercus coccinea)
-0.26
170
Bigtooth aspen (Populus grandidentata)
-0.25
280
Eastern white pine (Pinus alba)
-0.19
1,464
Black oak (Quercus velutina)
-0.18
257
White ash (Fraxinus americana)
-0.18
1,256
Sweet birch (Betula lenta)
-0.12
460
Yellow birch (Betula alleghaniensis)
-0.12
669
Northern red oak (Quercus rubra)
-0.11
1,533
Red maple (Acer rubrum)
-0.11
3,861
Red spruce (Picea rubens)
-0.09
616
American beech (Fagus grandifolia)
-0.08
1,449
Black cherry (Prunus serotina)
-0.07
1,026
Eastern hemlock (Tsuga canadensis)
-0.07
1,055
Pignut hickory (Carya glabra)
0.44
31
Norway spruce (Picea abies)
0.38
148
Yellow-poplar (Liriodendron tulipifera)
0.35
47
White spruce (Picea gluaca)
0.24
97
eq = equivalents; ha = hectare; yr = year.
Source: Duarte et al. (2013)
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Table 5-6 Results of Spearman's rank correlation analyses comparing tree
vigor, crown density and dieback, and canopy transparency versus
critical load exceedance by species for the forested plots in the
northeastern U.S. [from Duarte et al. (2013)1. Modeled sulfur and
nitrogen deposition on the plots ranged from 242 to 1,154 eq/ha/yr
and 256 to 920 eq/ha/yr, respectively. Correlations shown here are
significant at a = 0.05.
Vigor
Crown Density
Crown Dieback
Canopy Transparency
Species
Correlation
Coefficient
Sample
Size (n)
Correlation Sample
Coefficient Size (n)
Correlation Sample
Coefficient Size (n)
Correlation
Coefficient
Sample
Size (n)
American
beech
0.13
433
0.12 502
0.30
502
Ash
0.22
189
Balsam
fir
-0.23 161
0.56 161
0.18
161
Black
Cherry
0.33
47
Eastern
hemlock
0.36 82
-0.24 148
Fir
-0.36
33
Northern
red oak
0.27
208
Paper
birch
-0.29 125
0.13 300
Quaking
aspen
-0.56 61
0.44 61
0.40
61
Red
maple
-0.16 337
0.10 767
0.19
767
Red
spruce
0.20 115
0.43 168
0.61
168
Sugar
maple
0.06
3,408
-0.04 3,466
0.12
3,467
White
ash
-0.32
49
eq = equivalents; ha = hectare; yr = year.
Source: Duarte et al. (2013)
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Sullivan et al. (2013) evaluated relationships between deposition and sugar maple
regeneration in the Adirondack Mountains. Total N and S deposition ranged between 750
and 1,120 eq/ha/yr, and plots that received higher rates of N (median of approximately
560 eq/ha/yr), S (median of approximately 480 eq/ha/yr), and N + S (median of
approximately 1,040 eq/ha/yr) deposition had no sugar maple seedlings.
Soule (2011) sampled red spruce trees within a high elevation red spruce/Fraser fir (Abies
fraseri) forest on Grandfather Mountain, NC between 2006 and 2008, and used
dendrochronology to evaluate the influences of climate (precipitation, temperature, and
CO2 concentrations) and emissions of SOx and NOx on growth. Radial growth rates of
red spruce increased through time and were positively related to temperature and
atmospheric CO2, but were negatively related to emissions of SOx and NOx and number
of days with precipitation in a year.
Miller and Watmough (2009) evaluated hardwood plots along air pollution (N, S, and
ozone), soil acidity, and climate gradients in Ontario, Canada, and found that foliose
lichen species richness was negatively correlated with modeled air pollution levels (S
deposition, N deposition, and atmospheric ozone). In the same study, however, no
relationship was seen in canopy condition and ground vegetation richness and diversity.
Bardhan et al. (2012) evaluated bacterial diversity along a soil and S deposition gradient
in high elevation spruce-fir forests in GSMNP. Modeled S deposition ranged from 6 to
41 kg S/ha/yr. However, neither bacterial diversity nor community composition changed
along the gradient of S deposition. The bacterial community on all sites was dominated
by members of phylum Actinobacteria, Acidobacteria, Planctomycetes, Proteobacteria,
and Chloroflex. Species from these phyla are often found in highly acidic environments
such as acid-mine drainage and sphagnum bogs. Therefore, these analyses suggested that
despite reductions in acid deposition, the soil conditions in these GSMNP sites were still
acidic and had not yet reached a threshold suitable for nonacidophilic bacterial
communities.
Pannek et al. (2015) used a data set from seminatural grasslands found on acidic soils
along an N deposition gradient (2.4 kg N/ha/yr to 43.5 kg N/ha/yr) in northwestern
Europe to examine the response of species frequency to N and other factors including soil
(0-10 cm) P, pH, NH4+, and NO3 and geographical, climatic, and management factors.
Out of 44 studied species, 16 were affected by N deposition, with 12 of them exhibiting a
negative response.
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5.5.3
Critical Loads and Exceedances
Since the 2008 ISA, critical load evaluations have been conducted in the northeastern
forests of the U.S., hardwood forests in Pennsylvania, forests in western Canada, and
arctic, subarctic, alpine, subalpine, and boreal systems. Studies also simulated target
loads and critical loads and exceedances into the future under different deposition and
climate scenarios, and evaluated the sensitivity of critical load estimates to varying
environmental conditions and forest management and uncertainties in critical load
estimates.
Duarte et al. (2013) calculated critical loads of N and S for 4,057 forested plots in the
northeastern U.S. using the steady-state SMB model and soil solution Bc:Al of 10.0 as
the chemical indicator and threshold. In addition, the study evaluated the influence of
three different BCw rates on critical loads: minimum, midpoint, and maximum. These
BCw rates were determined using the clay correlation-substrate method and the range of
U.S. Department of Agriculture (USDA) Natural Resources Conservation Service
(NRCS) Soil Survey Geographic Database (SSURGO) values for each soil series. Critical
loads using the mid-point weathering rates were found to range from 11 to 6,540 eq/ha/yr
(over 80% within the range of 850-2,050 eq/ha/yr), and in comparisons with deposition
estimated using the ClimCalc model, were exceeded in 98% (calculated using minimum
weathering rates), 45% (calculated using midpoint weathering rates), and 15% (calculated
using maximum weathering rates) of plots. Similarly, Phelan etal. (2014) calculated
critical loads of N and S deposition for 51 hardwood forests in Pennsylvania using the
SMB model, soil solution Bc:Al of 10.0 as the chemical indicator, and the PROFILE
model to estimate BCw rates. They found that critical loads ranged from 4 to
10,503 eq/ha/yr, and that critical loads at 53% of the sites were exceeded by the 2002 N
and S deposition.
Multiple critical load studies were conducted in western Canada. In the Athabasca oil
sands region of Alberta, Jung et al. (2013) calculated critical loads (based on S
deposition) using the SMB model and soil solution Bc:Al of 10.0 as the chemical
indicator for two boreal forest sites dominated by jack pine (Pinus banksiana) and
trembling aspen. The goal of the study was to understand the influence of two different
methods to estimate base cation deposition (bulk deposition [i.e., wet] vs.
bulk + interception [i.e., total deposition]) and two time frames (short term vs. long term)
on critical loads and exceedances. Species-specific base cation uptake was included in the
calculation of short-term critical loads, but was assumed to be minimal in determination
of long-term critical loads. Long-term critical loads ranged from 223 to 711 molc/ha/yr
based on bulk deposition, loads that were similar but lower than loads based on total
deposition. These differences indicate that exceedances based on bulk deposition could
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potentially underestimate the risk of soil acidification. The short-term critical loads were
lower than the long-term loads and varied by species: 256 to 260 molc/ha/yr for jack pine
and 45 to 59 molc/ha/yr for trembling aspen. Short-term critical loads were exceeded in
the aspen forests. Similarly, Whitfield et al. (2010c) calculated critical loads and
exceedances for 333 sites in the Athabasca oil sands region using the SMB model and a
soil solution Bc:Al ratio of 10.0 as the chemical criterion and threshold value,
respectively. Critical loads averaged 580 eq/ha/yr under the assumption of complete N
retention and 40 eq/ha/yr when all deposited N was leached from the soil rooting zone.
Corresponding exceedance calculations indicated that the critical loads were exceeded by
the 2006 deposition for 34% of sites under the N retention scenario and for 62% of sites
under the N leaching scenario. Thus, Whitfield et al. (2010c) concluded that
acid-sensitive soils in the region are at risk of acidification due to pressures from
industrialization associated with fossil fuel extraction.
Whitfield and Watmough (2012) used the SMB model to calculate critical loads of S for
upland forest sites in Saskatchewan, Canada. Critical loads were found to vary by
ecoregion, with medians ranging from 140 to 1,120 mmolc/ha/yr.
Krzvzanowski (2011) modeled deposition and soil acidification critical loads in
northeastern British Columbia, Canada using empirical methods described in the
Spranger et al. (2004). Slow weathering of shale- and mudstone-derived feldspars, micas,
and quartz placed the soils of the study area in the "high-sensitivity" class of critical
loads. Soil acidification critical load was estimated to be 200 eq/ha/yr. Neither S nor N
deposition exceeded this critical load. The combined S and N deposition at the dominant
point of reception (i.e., near Blueberry River First Nation) was estimated to be
73.5 eq/ha/yr.
Estimates of S and N critical loads and exceedances for upland soils were generated for
the Georgia Basin in British Columbia, Canada using the SMB model and zero base
cation depletion as the chemical criterion and threshold (Nasr et al. 2010). The objective
of the study was to evaluate critical load and exceedance calculations in the context of
sustainable forest and soil management policies by using "no further changes in soil base
saturation" as the critical load criterion. Critical loads were found to range between 140
and 4,000 eq/ha/yr, and were generally lowest on ridge tops and increased towards the
valleys. Critical load exceedance ranged from 13% of the basin when exposed to wet
deposition to 32% under modeled total (wet and dry) deposition. With continued N and S
deposition, significant portions of the basin were predicted to experience
exceedance-enhanced base cation depletion rates greater than 200 eq/ha/yr.
Forsius et al. (2010) determined critical loads and exceedances for terrestrial ecosystems
in the arctic and subarctic regions (with latitudes north of 60°) for 1990, 2000, 2010, and
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2020 using the SMB model and two different chemical indicators (soil solution Al:Bc of
1.0 and ANCle of 0.0). The Al:Bc indicator was hypothesized to protect against fine root
damage, and the ANCle indicator was hypothesized to preserve existing soil base cation
pools. The 2020 deposition scenario was based on the maximum feasible reduction
(MFR) emissions for 2020. Critical load estimates were generally comparable among the
three main regions (northern Europe, Russia, and North America) and were influenced by
the chemical indicator and associated threshold. The Al:Bc of 1.0 was less stringent than
ANCle of 0.0, with the median critical loads for the two indicators being 700 eq/ha/yr
and 300 eq/ha/yr, respectively. In North America, the lowest critical loads occurred in
eastern Canada above latitudes north of 60°. In general, low critical loads were found in
areas with low weathering rates associated with coarse soils on acidic parent material.
Critical loads in North America (above latitudes north of 60°) were not exceeded by any
of the deposition levels for any of the years: The lowest critical load was 130 eq/ha/yr,
while the maximum rates of N and S deposition in North America were estimated to be
30 to 40 eq/ha/yr.
Critical loads for subalpine vegetation in the Rocky Mountain National Park were
estimated by Bowman et al. (2012) through changes in species composition in response
to elevated N deposition (total of 5 to 30 kg N kg N/ha for 3 years). Species richness and
diversity did not change, but Carex rupestris cover increased from 34 to 125%. The study
determined N critical loads of 3 kg N/ha/yr for vegetation, and recommended critical
loads under 10 kg N/ha/yr to prevent acidification.
5.5.3.1 Target and Future Critical Loads/Critical Load Exceedances
Target loads of S deposition were calculated for 44 watersheds and extrapolated to
1,320 acid-sensitive watersheds in the Adirondacks using MAGIC and different soil
chemical indicator and thresholds of base saturation (5 and 10%), soil solution Bc:Al, and
Ca:Al [1.0 and 10.0 (Sullivan etal.. 2011 a) I. In acomparison of target loads (out to years
2050 and 2100) and the 2002 deposition, only 11.6 to 13.5% of the watersheds were
simulated to be in exceedance of target loads to protect soil base saturation to 5%. For
target loads to protect soils to a base saturation of 10%, 79.7 to 87.5% of the watersheds
were in exceedance. For soil solution Bc:Al, 7.8 and 98.1% of watersheds were exceeded
by the 2002 deposition for target loads to protect soil solution ratios of 1.0 and 10.0,
respectively. For soil solution Ca:Al, 44.1 to 58.2% of watersheds experienced
exceedances of target loads associated with a soil solution ratio of 1.0, and 98.1% of
watersheds with target loads to protect Ca:Al ratios of 10.0 were exceeded. Further
investigations revealed that 58.2, 85.7, and 93.6% of watersheds could not obtain
threshold values of 10% base saturation, Bc:Al = 10, or Ca:Al = 10, respectively, even if
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acidic deposition was held at zero, thereby demonstrating that these chemical indicator
threshold values were not useful for target load calculations using MAGIC in the
Adirondack Mountains.
Sverdrup et al. (2012) and McDonnell et al. (2014a) used the ForSAFE-Veg model to
evaluate potential long-term effects of climate change and atmospheric N deposition on
alpine/subalpine ecosystems. Critical loads in both studies were defined as the amount of
N deposition to protect against a change in plant biodiversity of 5 to 10 Mondrian (M)
units (i.e., 5-10% change in plant species cover). Sverdrup et al. (2012) focused on a
"generalized" alpine/subalpine site in the Rocky Mountain National Park, and simulated
plant responses to a future climate (IPCC scenario A2) and four levels of N and S
deposition (preindustrial background, Clean Air Act (CAA) controls, no CAA controls,
and no CAA controls + high deposition). Soil base saturation decrease to less than 1%
and soil solution Bc:Al were predicted to be less than 10.0 after year 2100, with the
futures of no CAA emission controls and no CAA controls + high deposition (indicating
soil acidification). Future plant species coverages were predicted to change in
successively greater amounts in response to the altered climate, CAA emission controls,
no CAA emission controls, and no CAA emission controls + high deposition. Critical
loads of N deposition were calculated (based on a change of 5 M) to be 1 kg N/ha/yr.
Critical loads related to S deposition were not discussed. All future N deposition
scenarios (except preindustrial background N) were simulated to result in critical load
exceedance. McDonnell et al. (2014a) found similar results in their study that evaluated
the response of plants on a site in the Loch Vale watershed, Colorado to 100 different
scenario combinations of N deposition, precipitation, and temperature. The estimated
critical load ofN to protect against future (average of 2010-2100) change in biodiversity
(10 M) was estimated to be between 1.9 and 3.5 kg N/ha/yr, depending on the
temperature increase scenario. Current deposition levels were found to exceed the critical
load. Future increases in temperature were forecasted to substantially impact plant
community composition beyond the predicted changes in response to N alone; N
deposition was forecasted to result in approximately a 10- to 25-M change by 2100,
whereas a +4.6°C increase in temperature was forecasted to result in approximately a
38- to 48-M change by 2100. In both studies, plant community response appeared to be
attributed to N enrichment or eutrophication, as McDonnell et al. (2014a) stated that the
critical load adopted in their study was much lower than critical loads to protect against
N03 leaching and soil acidification determined by other studies.
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5.5.3.2 Sensitivity of Critical Load Estimates to Forest Management and
Environmental Stresses
Influences of Forest Management
Removal of N and base cations with tree harvesting can be included in the calculation of
critical loads. Several recent studies evaluated the amounts of base cations removed
through different harvesting practices and determined that base cation removal can be
substantial and contribute to site acidification.
Duchesne and Houle (2008) determined base cation budgets in a managed boreal balsam
fir forest in Quebec, Canada according to six different scenarios, including two
harvesting scenarios (whole-tree and stem-only harvesting), and three scenarios of
mineral weathering. Whole-tree harvesting was found to remove twice as much Ca (1,358
vs. 664 mol/ha) and K (483 vs. 200 mol/ha) as stem only. In contrast to Ca and Mg,
immobilization of K within tree biomass (69 mol/ha/yr) was the main pathway of K
losses from the soil exchangeable reservoir, being five times higher than losses via soil
leaching (14 mol/ha/yr). The amounts of K contained within the aboveground biomass
and the exchangeable soil reservoir were 3.3 kmol/ha and 4.2 kmol/ha, respectively.
Whole-tree harvesting was estimated to remove 44% of the K that was readily available
for cycling in the short term.
Similar results were found by Iwald et al. (2013) in their evaluation of the removal of
base cations with the harvesting of tree stumps and logging residues for biofuels in
Sweden. Their study evaluated three levels of harvesting intensity that varied in the
amounts of stump and logging residues left on site (0-40%). Results from the study
indicated that harvesting of stumps and logging residues constituted 13 to 24% and 27 to
45% of total (stumps + stem wood + logging residues) base cation extraction,
respectively, depending on harvest intensity and tree species. The higher acidifying effect
of logging residue removal was explained by the higher contents of base cations in
needles and branches compared to stem wood. In a comparison between total net cation
extraction by tree harvesting and maximum levels of current acid deposition, the
acidifying effect of pine harvesting was found to be 57 to 108% of that of acid
deposition, the acidifying effect of spruce harvesting was 114 to 263%, and the acidifying
effect of birch harvesting was 60 to 171%.
In the northeastern U.S., Lucas et al. (2014) evaluated base cation extractions under three
different management scenarios that varied in management intensity and conservation
focus. The MaxGrowth management option, which involved site scarification, intensive
fertilization, and short rotation lengths (60-100 years), resulted in roughly 50 to 100%
greater base cation removal than that associated with the other three management
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scenarios. Additionally, removal of tree tops, branches, and stumps consistently resulted
in removal rates of Ca, Mg, and K three to four times greater than conventional stem-only
harvests.
Johnson et al. (2015a) used mass balance calculations to evaluate the impact of
harvesting on ecosystem balances of Ca, Mg, K, and acidification of forest soils at
40 sites in Ireland. Three harvesting scenarios were evaluated: stem-only harvest (SOH),
stem plus branch harvest (SBH), and whole-tree harvest (WTH). Mass balances for Ca,
Mg, and K were determined based on the difference between long-term inputs
(atmospheric deposition plus mineral weathering) and outputs (biomass removal plus
leaching losses). Soil acidification was calculated using a simplified acidity balance of
inputs (base cation and Na deposition and base cation weathering) and outputs (base
cation uptake, S deposition, and CI" deposition). Under the SOH and SBH management,
inputs of Ca, Mg, and K were predicted to be sufficient to meet outputs. Atmospheric
deposition was the most important source of Ca and Mg input. For K, inputs from soil
weathering were as important as deposition. Under the WTH scenario, Ca output
exceeded input at 19 of the 40 study sites. However, the differences were small relative to
the sizes of the Ca pools; at the 19 sites, exchangeable pools could support Ca removal
with WTH for a median of 220 years. Mg and K removal with WTH was balanced by
inputs through deposition and soil weathering. In contrast, for soil acidification budgets,
base cation removal with all scenarios of harvesting was much greater than that generated
by soil weathering, suggesting that soils will become acidified over the long term.
However, there was considerable uncertainty around the calculation of base cation fluxes.
For Ca balances, confidence intervals spanned positive and negative values at so many
sites that it was not possible to predict the balance of Ca budgets. In addition, uncertainty
in flux calculations was particularly important for K, as soil exchangeable pools were
small and could be depleted within one or two rotations.
Zetterberg et al. (2014) evaluated the long-term effects of whole-tree harvest (WTH) on
soil and stream water acidity in three forested catchments dominated by Norway spruce
in Sweden. Potential influences of varying the amounts of logging residues, Ca
concentrations in tree biomass, and site productivity on the model predictions were also
evaluated through a sensitivity analysis. The MAGIC model was used to simulate
changes in forest soil exchangeable Ca pools and stream water ANC from 1850 to 2100,
with WTH occurring in 2020. Large depletions in soil Ca supply and a reversal of the
positive trend in stream ANC were predicted for all three catchments sites after WTH.
However, the magnitude of impact on stream ANC varied depending on site and the
concentrations of mobile strong acid anions. Varying the tree biomass Ca concentrations
was found to have the largest impacts on modeled soil and stream chemistry. Site
productivity was the second most influential variable, and changing the amount of
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harvest residues left on site only marginally affected soil exchangeable Ca and stream
water ANC. The results from this study suggest that future research should concentrate
on minimizing uncertainties in tree biomass Ca concentrations and performing studies on
biological feedback mechanisms that can increase Ca availability in the soils.
Influences of Environmental Stresses
Climate and other environmental stresses may also directly or indirectly alter ecosystem
parameters that are used in the SMB model to determine critical loads. The potential
influences of climate were examined by McNultv and Bonus (2010) in their case-study
evaluation of red spruce stands in western North Carolina that were experiencing low
versus high rates of mortality associated with a pine beetle outbreak. There were positive
relationships between site fertility (forest floor and soil measurements, foliar N
concentrations, and Mg:N ratios) and red spruce mortality. Annual basal area growth of
red spruce on more fertile plots was more sensitive to drought than on less fertile sites.
Based on these observations, critical loads of acidity could change as a result of episodic
stress (e.g., drought, insect infestations, frost injury, cold tolerance, etc.), and increased
growth due to higher fertility and/or nutrient imbalances caused by acidifying deposition
may make red spruce more susceptible to environmental stresses. Critical loads of N and
S, therefore, might be lower when environmental stresses are present.
5.5.3.3 Uncertainties in Critical Load Estimates
Reinds and de Vries (2010) evaluated the uncertainties in critical and target loads of S
and N for 182 European forest soil plots using the very simple dynamic (VSD) model.
Target loads were defined as the deposition that leads to a desired chemical state of the
ecosystem in a given future year. The VSD model was calibrated using Bayesian prior
probability functions for model parameters based on literature data, data from 200 Dutch
forest sites and from simulated denitrification rates from a detailed ecosystem model,
which improved the model fit to observed soil measurements. Critical loads determined
by the calibrated model varied by chemical criterion. Minimum critical loads of N ranged
between 181 eq/ha/yr (5th percentile) and 1,606 eq/ha/yr (95th percentile), maximum
critical loads ofN ranged between 502 eq/ha/yr (5th percentile) and 31,247 eq/ha/yr
(95th percentile), and maximum critical loads of S ranged between 4 eq/ha/yr
(5th percentile) and 9,670 eq/ha/yr (95th percentile), with the critical loads based on
Al:Bc = 1 being higher than those determined using the ANC = 0 eq/ha/yr criterion.
Uncertainty analysis also showed that the main drivers of uncertainty were largely
dependent on the chemical criterion used in the critical and target load calculations. Base
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cation weathering, deposition, and the parameters describing the H-Al equilibrium in the
soil solution were the main sources of uncertainty in the estimates of maximum critical
loads for S (CLmax[S]) based on the Al:Bc criterion of 1.0, and uncertainty in CLmax(S)
based on ANC was completely determined by base cation inputs. The denitrification
fraction was the most important source of uncertainty for the maximum critical loads of
N (CLmax[N]). Calibration of VSD reduced the levels of uncertainty for all critical loads
and criteria. After calibration, the coefficient of variation (CV) for CLmax(S) was below
0.4 for almost all plots, and target loads were not needed in any of the simulations for
40% of the plots. According to the noncalibrated model, there was a positive probability
for the need of a target load for almost all plots.
5.6 Summary
Since publication of the 2008 ISA, the overarching understanding of terrestrial
acidification has not appreciably changed. More recent research has confirmed and
strengthened this understanding and provided more quantitative information, especially
across the regional landscape. A number of studies have evaluated the relationships
between soil chemistry indicators of acidification and ecosystem biological endpoints
(see Table 5-1). Soil chemistry indicators examined in recent literature include
exchangeable base cations, soil pH, exchangeable acidity (H+ and Al), exchangeable
Ca:Al ratio, base saturation, and Al concentrations. Biological endpoints included in the
evaluations consisted of physiological and community responses of trees and other
vegetation, lichens, soil biota, and fauna.
5.6.1 Physiology and Growth
The physiological effects of acidification on terrestrial ecosystems in the U.S. were well
characterized at the time of the 2008 ISA. Consistent and coherent evidence from
multiple species and studies in 2008 showed that the biological effects of acidification on
terrestrial ecosystems were generally attributable to physiological impairment caused by
Al toxicity and decreased ability of plant roots to take up base cations (Section 3.2.2.3 of
2008 ISA). Acid deposition can also leach membrane associated stores of Ca from young
red spruce needles, which affects membrane stability and freezing tolerance. New
information since the 2008 has supported these conclusions (Section 5.2). including
further studies on the impact of acidifying deposition on sensitive tree species, such as
sugar maple and red spruce. Much of the new evidence for the negative effects of
acidifying deposition on these species comes from Ca addition experiments, in which the
addition of Ca has alleviated many of the negative plant physiological and growth effects.
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Consistent with the findings of the 2008 ISA, the body of evidence is sufficient to infer
a causal relationship between acidifying N and S deposition and the alteration of the
physiology and growth of terrestrial organisms and the productivity of terrestrial
ecosystems.
In the 2008 ISA, acidifying deposition, in combination with other stressors, was found to
be a likely contributor to physiological effects that led to the decline of sugar maple trees
living at higher elevation in some portions of the eastern U.S. that have geologies
dominated by sandstone or other base-poor substrate, and that have base-poor soils.
Studies since the 2008 ISA support these findings (See Section 5.2.1.1). For example,
recent field studies demonstrated relationships between soil chemical indicator threshold
values and tree responses. Substantial declines in sugar maple regeneration were found at
soil base saturation levels <20% which is consistent the range reported in the 2008 ISA.
In new studies, sugar maple showed positive growth and regeneration responses to
increasing exchangeable base cations, base saturation and soil pH, and negative
relationships with increasing exchangeable Al. Additional studies indicated that growth,
regeneration and physiological responses of sugar maple to soil conditions created by
acidifying N and S deposition were reversed or ameliorated by Ca additions. The
responses to Ca additions responses included increased growth and regeneration,
decreased crown dieback, increased foliar chlorophyll, and decreases in foliar metabolic
indicators of physiological stress.
The 2008 ISA reported that changes in soil chemistry, such as depletion of soil base
cations, increasing Al concentration, and leaching of base cations into drainage water,
have contributed to physiological stress, high mortality rates, and decreasing growth
trends of red spruce trees. New information since the 2008 ISA from Ca addition studies
supports the conclusion that depletion of base cations contributed to these effects in trees
(Section 5.2.1.2). Foliar biomass and physiological responses of red spruce to soil
conditions created by acidifying N and S deposition were reversed or ameliorated by Ca
additions. The responses included higher foliar antioxidant activity in the winter,
significantly greater foliar cold tolerance, and higher levels of foliar metabolic
compounds that indicate an increased tolerance of environmental stresses. (Schaberg et
al.. 2011; Halman et al.. 2008).
In the 2008 ISA, there was a limited amount of information on acidification effects on
flowering dogwood. Since the 2008 ISA, no additional information on dogwood has been
published; however, other tree species that have been evaluated in studies relating soil
chemistry to tree physiology include yellow birch, white ash, American beech, black
cherry, northern red oak, hickories, American basswood, and eastern hophornbeam.
These species were reported to vary in their sensitivities to soil conditions associated with
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acidifying deposition. Data are insufficient to draw general conclusions for other species.
New information was also published on the recovery of eastern redcedar since the 1980s
as SO2 emissions declined. However, it is unclear whether this recovery was from acid
deposition, direct SO2 effects, or a combination of each (Section 5.2.1.3).
New studies since the 2008 ISA have also added new information about acidifying
deposition on forest understory vegetation, grasslands, lichen communities, and higher
trophic-level organisms (snails and salamanders). These studies are not as numerous as
those from the decades of tree research; however, results of these studies support the
conclusions of the 2008 ISA regarding the effects of acid deposition on terrestrial
ecosystems.
5.6.2 Biodiversity
Consistent with the findings of the 2008 ISA, the body of evidence is sufficient to infer
a causal relationship between acidifying N and S deposition and the alteration of
species richness, community composition, and biodiversity in terrestrial ecosystems.
The physiological effects of acidifying deposition can result in changes in species
composition and biodiversity whereby sensitive species are replaced by more tolerant
species. For example, sugar maple was found to have greater growth and seedling
colonization with increasing soil cation availability, and American beech was more
prevalent on soils with lower levels of cations—locations where sugar maple does less
well (Section 5.2.1.3.1). As noted above, studies have found increased regeneration of
sugar maple with Ca additions and less regeneration with increasing exchangeable Al.
Soil acid-base chemistry was found to be a predictor of understory species composition.
Fifty understory species associated with the basic end of a soil pH gradient, and these
species could have value as indicators of sites with high base cation status and potentially
suitable habitat for acid-sensitive species like sugar maple. In another set of studies, soil
acid-base chemistry predicted and was correlated with soil biota diversity and community
composition. Proportions of soil bacteria, fungi, and nematodes were found to be related
to soil pH and Al concentrations. Fungi and nematodes were more abundant in acidic
soils. Ca additions resulted in a change in soil bacterial community composition, and the
bacterial community structure was found to be significantly correlated with soil
exchangeable Ca, pH, and P (Section 5.2.4).
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5.6.3
National-Scale Sensitivity and Critical Loads
Sensitivity of soils to acidifying deposition is discussed in detail in Chapter 4 and
summarized in Section 1.5. In general, surficial geology is the principal factor governing
the sensitivity of terrestrial ecosystems soil to acidification from S and N deposition.
Other factors contribute to the sensitivity of soils to acidifying deposition, including
topography, soil chemistry, and land use. Forests of the Adirondack Mountains of New
York, Green Mountains of Vermont, White Mountains of New Hampshire, the Allegheny
Plateau of Pennsylvania, and mountain top and ridge forest ecosystems in the southern
Appalachians are the regions most sensitive to terrestrial acidification from atmospheric
deposition (Section 3.2.4.2 of 2008 ISA). Sensitive ecosystems can also be characterized
by presence of acid-sensitive soils and plant species (Section 5.3).
Models used to determine critical loads of acidifying deposition included: SMB, STA,
MAGIC, ForSAFE-VEG, and empirical models. Several models and extrapolation
methods to estimate BCw rates were also investigated. The PROFILE model was
evaluated as a model to estimate soil BCw rates to support estimates of SMB critical
loads in the U.S. In general, recently published models used soil solution Bc:Al of 10.0 as
an indicator to estimate critical loads in North America. These models are described in
more detail in Section 4.5.
Sensitivities of ecosystems to ambient N and S deposition were also characterized
through critical loads and exceedances (Section 5.5). Calculated critical loads for forest
sites based on the soil solution Bc:Al of 10.0 in the northeastern U.S. ranged from 11 to
6,540 eq/ha/yr (eq quantifies the supply of H+ ions available for acid-base reaction,
allowing the acidifying effects of N and S deposition to be combined into the same unit),
and 15-98% of these critical loads were exceeded by N and S deposition. In this region,
correlation analyses showed that the growth of 17 species and crown density of 4 species
were negatively correlated with critical load exceedance. In Pennsylvania, critical loads
based on the soil solution Bc:Al of 10.0 for hardwood forests ranged from 4 to
10,503 eq/ha/yr and were exceeded by the 2002 N and S deposition in 53% of the plots.
In comparison, critical loads for terrestrial ecosystems in the arctic and subarctic regions
of North America were not exceeded by estimated deposition in the years 1900, 2000,
2010, and 2020. For these high latitude ecosystems, the lowest critical load was
130 eq/ha/yr, while the maximum N and S deposition was 30 to 40 eq/ha/yr.
In western Canada, critical loads ranged from 40 to 4,000 eq/ha/yr depending on the
study and location. Several studies evaluated the influence of BCw rates, soil chemical
indicators and thresholds, N retention, tree species-specific base cation uptake, and/or
bulk (i.e., wet) versus total deposition on critical load estimates. All of these parameters
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1 were found to influence critical load and exceedance determinations, thereby
2 demonstrating the uncertainties and sensitivities associated with critical load estimates.
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CHAPTER 6 TERRESTRIAL ECOSYSTEMS:
NITROGEN ENRICHMENT EFFECTS
ON ECOLOGICAL PROCESSES
This chapter characterizes the biological effects of nitrogen (N) enrichment in terrestrial
ecosystems that can be caused by atmospheric N deposition. The chapter is composed of
three major portions: effects on growth and physiology (Section 6.1). changes in
biodiversity and community composition (Section 6.2). sensitive areas and critical loads
(Section 63 and Section 6.4). Each of these portions of text are divided into subsections
based on ecosystem type (e.g., forests, grasslands, etc.) or functional group (e.g., lichens,
trees, herbaceous plants). The first two portions begin with an introduction (Section 6.1.1
and Section 6.2.1) that review the previous casual determination and present the current
casual determination. Following these introductions, an overview of the mechanisms that
operate across ecosystems to link N enrichment to biological change is presented
(Section 6.1.2 and Section 6.2.2). All three major portions end with a summary that
provides a synthesis of the new information generated since the 2008 ISA for Oxides of
Nitrogen and Sulfur-Ecological Criteria (hereafter referred to as the "2008 ISA").
6.1 Linking Nitrogen Deposition to Changes in Physiology,
Growth, and Productivity in Terrestrial Ecosystems
6.1.1 Introduction
Nitrogen (N) is a key element required by all organisms in order to build amino acids and
nucleic acids, the basic biochemical subunits needed to synthesize the proteins, enzymes,
RNA, and DNA that sustain all biological processes. By the second half of the 19th
century, before these biochemical pathways had been identified, it was already
understood that N was a component of plant and animal tissues and that a supply of N
was essential for plant growth (Gallowav et al.. 2004). Indeed, the ability of added N to
stimulate plant growth had been recognized by science (and commerce) for over a
century (Gallowav et al.. 2004; Gallowav and Cowling. 2002) prior to the 2008 ISA. By
2008, it was already clear that N availability broadly limited productivity in terrestrial
ecosystems and that changes in N availability could alter the composition and function of
terrestrial ecosystems from molecular to global scales.
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In the 2008 ISA, evidence was sufficient to infer a causal relationship between N
deposition and the alteration of the terrestrial carbon (C) and N biogeochemical cycles.
These effects included changes in soil C and N pools and fluxes (described in Chapter 4).
but also significant alterations of plant and microbial growth and physiology. The 2008
ISA built upon the conclusions of the 1993 Oxides of Nitrogen Air Quality Criteria
Document. By 1993, a series of hypotheses regarding the effects of chronic N deposition
on northern temperate forests had already been developed from early field observations
(Aberetal.. 1989). Briefly, N deposition was expected to increase tree growth in most
forests, but once plant demand for N had been satisfied (biological and physical sinks had
reached "N saturation"), further N deposition could lead to nitrification, soil cation
leaching, acidification, nutrient deficiencies, and decreased tree growth (Aber et al..
1989). A revised form of these N saturation hypotheses (Aberetal.. 1998) provided
much of the conceptual foundation in the 2008 ISA for understanding how N deposition
influenced plant physiology, growth, and ecosystem productivity.
Because of the fundamental role ofN in biological processes across terrestrial
ecosystems, the effects of N deposition on terrestrial ecological processes have been
widely studied since 2008. Research on N deposition has continued in North America and
Europe, but a significant new body of research has developed in the boreal, arid, and
subtropical ecosystems of Asia, particularly in China [e.g., (Zhang et al.. 2015e; Du et al..
2014a; Du et al.. 2014b; Du and Fang. 2014; Sun et al.. 2014)1. With the increasing
volume of research, a number of new studies have been conducted using meta-analysis to
synthesize published observations or using continental or global data sets to understand
broad-scale patterns. These new analyses have provided a more detailed understanding of
how added N affects productivity responses in different biomes (LcBauer and Treseder.
2008). growth among plant functional types (Xia and Wan. 2008). growth of individual
plant parts (Xia and Wan. 2008). root growth (Li et al.. 2015). and ecosystem C storage
(Liu and Greaver. 2009). while other broad-scale analyses have examined changes in
plant N concentrations (Xia and Wan. 2008). microbial biomass (Treseder. 2008). and
belowground C cycling (Liu and Greaver. 2010). This expanded body of research has
created a better understanding of how N influences processes at molecular to global
scales. Together with the information available in the 2008 ISA, this body of evidence is
sufficient to infer a causal relationship between N deposition and the alteration of
the physiology and growth of terrestrial organisms and the productivity of
terrestrial ecosystems.
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6.1.2
Mechanisms Operating across Terrestrial Ecosystems
The 2008 ISA evaluated a large number of studies assessing how N deposition changed
terrestrial C cycling and found an array of ecological responses. The most extensive
evidence on the effect of N deposition on C cycling was available for forests in North
America and Europe. In experimental N addition studies, moderate to high additions of N
led to either no significant change in tree growth rates or transient growth increases
(generally at deposition rates lower than 10 kg N/ha/yr), followed by increased mortality,
especially at higher rates of N addition. This group of studies showed coherence in
effects and indicated the presence of a biological gradient in responses with increasing N
deposition.
Some of the broad-scale changes caused by N additions to terrestrial ecosystems had
been quantified by meta-analysis, a data synthesis tool that started to become commonly
used in ecological research beginning in the late 1990s (Gu rev itch et al.. 2001). Using
this tool to understand the effects of N additions on herbaceous plant communities,
Gough et al. (2000) found that N additions stimulated aboveground plant productivity by
an average of 53%. In a broader synthesis, Elser et al. (2007) conducted a meta-analysis
of N addition effects on plant community productivity and observed average increases in
productivity of 20-30% in grasslands, forests, tundra, and wetlands. In addition to
changes in plant growth, koricheva et al. (1998) identified via meta-analysis that added
N could alter the chemistry of plant tissues, including increasing tissue concentrations of
N and free amino acids, while decreasing concentrations of starch and C based secondary
compounds (important for defense against herbivores), including phenylpropanoid
compounds. Belowground, Treseder (2004) found in a meta-analysis that N additions
decreased both the abundance of mycorrhizal fungi and the percentage of plant roots
colonized by mycorrhizal fungi. In addition, there were multiple lines of evidence that N
deposition increases the performance of insect herbivores, and potentially insect
populations (Throop and Lcrdau. 2004). In a synthesis of 500 observations of the effect
of N on litter decomposition rates, Knorretal. (2005) found that added N stimulated
decomposition at sites with low rates of ambient N deposition (<5 kg N/ha/yr), but
slowed decomposition at sites with moderate rates of N deposition [5-10 kg N/ha/yr;
(Knorr etal.. 2005)1 and that N additions at rates from 2 to 20 times ambient N
deposition inhibited decomposition by 8 to 16%. These changes in themselves can cause
a cascade of ecological consequences. For instance, the inhibition of decomposition can
increase soil C content, but the accumulation of plant litter on the soil surface can inhibit
the establishment of some plant species (Patterson et al.. 2012; Cleavitt et al.. 201 lb;
Xiong and Nilsson. 1999; Facelli and Pickett. 1991). In this way, it was recognized in the
2008 ISA that the effects of N deposition on biological and ecological processes in
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terrestrial ecosystems were pervasive, complex, and difficult to fully understand and
predict.
Although some coherence had developed in plant productivity responses to N deposition
as of the 2008 ISA, the extent to which N increased forest C content in C budget
measurements (quantified input and output of C to the ecosystem) was uncertain. A
prominently reported estimate of >600 kg C sequestered per kg of N deposited to forests,
which was based on a regional gradient technique (Magnani et al.. 2007). was widely
criticized. Subsequent reassessments of these data suggested that forest C sequestration
was an order of magnitude lower (Sutton et al.. 2008). Liu and Greaver (2009) found in a
meta-analysis that N additions ranging from 25.5 to 200 kg N/ha/yr increased forest
ecosystem C content (+6%).
In the western U.S., Fenn et al. (2003a) suggested that the growth increase caused by N
deposition could increase plant litter accumulation, increasing the susceptibility of forests
and other wildlands to severe wildfires. Nitrogen deposition also affects the patterns of C
allocation because most of the additional plant growth occurs aboveground. This
increases the shoot-to-root ratio, which can be detrimental to plants because of decreased
resistance to environmental stressors, such as drought and wind (Braun et al.. 2003;
Krupa. 2003; Minnich et al.. 1995; Fangmeier et al.. 1994).
However, less had been reported regarding the effects of N deposition on the
eutrophication of nonforested ecosystems. Mack et al. (2004) examined C and N pools in
a long-term N addition experiment at the Arctic Long-Term Ecological Research site near
Toolik Lake, Alaska. Plant growth increased as a result of N additions, but the N
additions enhanced decomposition of belowground C pools in deep soil layers more than
it increased primary production, leading to a substantial net loss of C from this
ecosystem. More broadly, Liu and Greaver (2009) conducted a meta-analysis of 16
observations from nine publications to evaluate the relationship between N addition (16
to 320 kg N/ha/yr) and C sequestration in nonforest ecosystems and did not find a
significant effect on net ecosystem exchange (NEE, kg C/ha/yr).
Xia and Wan (2008) identified nearly 1,600 observations of plant biomass growth in
response to N additions, excluding agricultural and horticultural species (Figure 6-1 A).
Overall, plant biomass increased by 54%, with a larger gain in seeded plants (+55%) than
spore plants (+21%; not shown). Among the seeded plants, grasses showed the largest
biomass response, followed by trees, forbs, and shrubs. Annual herbs (+92%) showed a
stronger response than perennial herbs (+56%). Overall, biomass responses to N
increased linearly with mean annual precipitation (MAP). The studies included in the
analysis had addition rates ranging from 10 kg N/ha/yr to 1,000 kg N/ha/yr. When the N
additions were divided into low (<100 kg N/ha/yr) and high (>100 kg N/ha/yr) groups,
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there were only a few differences among functional groups. The response of woody
species was lower than for herbaceous species at the low addition rate (+25 vs. +51%),
but the groups had similar responses at the high N addition rate. Among herbaceous
plants, both legumes and nonlegumes had positive responses to low rates of N additions
(19 and 23%, respectively), while the high rate of N additions increased nonlegume
biomass (+43%), but did not significantly affect legume growth, also examined how these
responses varied in response to the rate of N additions. The N addition studies were also
divided into 50 kg N/ha/yr increments from 0 to 300 kg N/ha/yr, but aside from
increasingly positive growth responses for trees and woody plants with greater N
additions, there were few apparent trends and sample sizes were inconsistent.
In their analysis, Xia and Wan (2008) separated plant growth data into aboveground
(887 observations) and belowground (340 observations) components. Across almost all
functional groups, there were greater increases in biomass in aboveground than
belowground components (Figure 6-1 A). In a subsequent meta-analysis of plant C pools,
Lu et al. (201 lb) also found that N additions to plants in nonagricultural systems
stimulated shoot C by 28.5% (n = 146) and root C by 20% (n = 77). These results
indirectly suggest that plant C allocation changes in response to N addition, but this
changes was confirmed by a more direct analysis of a much smaller meta-analysis data
set (n = 15), where Li et al. (2015) observed a significant 11% decrease in the root:shoot
biomass ratio. Together, these results provide further support to the conclusion in the
2008 ISA that N additions can alter plant C allocation and result in elevated shoot:root
ratios. Further, Lu etal. (201 lb) analyzed the response of some individual plant parts to
added N and observed a 1.6% increase in leaf C mass.
Belowground processes are important components of terrestrial ecosystems. As detailed
in Chapter 5. soils are often the largest ecosystem pools of both C and N, soil respiration
can be the largest ecosystem efflux of CO2, and soils can be important sources and sinks
for the greenhouse gases N2O and CH4. Biologically, the large C fluxes that plants
allocate belowground for root exudation, the growth and maintenance of roots, and the
support of mycorrhizal fungi, combine with inputs of aboveground detritus to support
complex belowground foodwebs host diverse microbial and arthropod communities.
Relative to aboveground plant responses, there is less information available about
belowground responses to N additions. However, Li et al. (2015) recently conducted a
meta-analysis of how root traits respond to N additions. Notably, Li et al. (2015) found
that although total root biomass increased (+20%; n = 74), fine root biomass declined
(-13%; Figure 6-2B). This discrepancy is apparently accounted for by an increase in the
biomass of coarse roots (+57%; n = 7), which are typically structural and conductive
tissues. Morphological traits of fine roots such as length (n = 25), diameter (n = 10), and
specific root length (n = 22) were unaffected by N additions. Fine root turnover rate was
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21% higher (n = 12), but fine root production was not significantly affected by the N
additions [n = 22; (Li et al.. 2015)1.
Aboveground net primary productivity (NPP), which measures aboveground plant growth
at the community scale, was less responsive on average (+29%) than individual plant
growth to N additions KLeBauer and Treseder. 2008); Figure 6-IB and Figure 6-2A1.
Consistent with the plant functional group analysis conducted by Xia and Wan (2008).
LeBauer and Treseder (2008) observed a large stimulation of aboveground NPP in
grass-dominated ecosystems such as temperate grasslands (+53%), tropical grasslands
(+26%), and tundra (+35%), whereas temperate forest NPP increased only 19%. There
were also significant NPP increases in tropical forests and wetlands. Added N did not
significantly increase NPP in deserts, but the analysis only included three observations.
LeBauer and Treseder (2008) had a considerably smaller data set (n = 126) than Xia and
Wan (2008) and did not find that MAP, mean annual temperature (MAT), or latitude had
significant overall influences on responsiveness of NPP to added N. However, within
individual biomes, forests and tundra NPP responses to N increased with MAT and
forests also became more responsive with greater MAP.
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Overall Temperate Tropical
Forest Forest
Tundra Tropical Temperate Wetland Desert
Grassland Grassland
NPP = net primary productivity.
Notes: (A) Mean change in plant biomass growth in response to N additions from Xia and Wan (2008'i. with blue bars representing
the overall response, orange bars representing aboveground growth, and grey bars representing belowground growth. Vertical grey
lines identify different ways the data were parsed (i.e., all seeded plants; woody vs. herbaceous plants, etc.) (B) Mean change in net
primary productivity, from LeBauer and Treseder (2008). Error bars represent the 95% confidence interval. Numbers above the error
bars indicate the number of observations included in the analysis.
Figure 6-1 Effects of nitrogen additions on plant growth and net primary
productivity.
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Liu and Greaver (2009) had smaller data sets, with 16 observations of net ecosystem
exchange (NEE; all in nonforested systems) and 17 observations of ecosystem C content
(Figure 6-2). There were no significant effects of added N on NEE overall or within the
individual biomes included in the analysis (grasslands, wetlands, tundra). However,
added N did increase forest ecosystem C content by 6%. Belowground NPP responses
have not been synthesized, at least in part because of lack of data (Lc Bauer and Treseder.
2008).
In terms of altered physiology, there is also widespread evidence that N additions
increase plant tissue N concentrations. The meta-analysis by Xia and Wan (2008)
included changes in plant N concentrations overall, aboveground, and belowground.
Overall, N additions increased plant N concentrations by an average of 28.5% (Xia and
Wan. 2008). Although there was significant variation among plant functional groups, the
average increase in tissue N concentration among seeded plants was much more similar
across functional groups than the biomass growth response, ranging only from +24 to
+35% once legumes (+7%) and the two broader functional groups containing legumes
(forbs, +14%; perennial herbs: +22%) were excluded. Likewise, belowground and
aboveground plant tissues had a similar change in N concentration, in contrast to the
varying biomass growth responses to N (Xia and Wan. 2008). Li et al. (2015) also
observed that N additions significantly increased root N concentrations in a root trait
meta-analysis (+18%; n = 84).
The 2008 ISA linked enhanced terrestrial productivity to increases in photosynthesis and
gross primary productivity. Gross primary productivity can increase either as a result of a
greater amount of photosynthetic tissue (more light absorption) or a higher rate of
photosynthesis per leaf. There is a strong mechanistic and conceptual link between
greater foliar N concentrations, higher leaf concentrations of the C assimilating enzyme
Rubisco (Evans. 1989). and greater maximum rates of leaf-level photosynthesis in
vascular plants (Wright et al.. 2004). Consequently, the increase in foliar N caused by N
additions has been linked to increases in the leaf-level rate of photosynthesis for decades
[e.g., (Teskev et al.. 1994) and references therein]. Alternately, evidence cited in the 2008
ISA suggests that much of the increased foliar N observed when N is added may be
physiologically inactive because it manifests as an increase in storage compounds such as
free amino acids (Bauer et al.. 2004). While increases in photosynthesis in response to N
additions have been observed in trees, grasses, and shrubs, these increases have not been
consistent [e.g., (Talhelm et al.. 2011; Elvir et al.. 2006; Chen et al.. 2005b; Newman et
al.. 2003; Laitha and Whitford. 1989; Gulmon and Chu. 1981)1 and there do not appear to
be any meta-analysis or other synthesis on the response of leaf-level photosynthesis or
GPP (Figure 6-2B) to N additions. Similarly, there is a strong fundamental relationship
between tissue N concentration and respiration rates in plants (Reich et al.. 2008; Reich et
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al.. 2006; RvanetaL 1996), such that this relationship is used to model respiration rates
|e.g.. (Hanson et al.. 2004; Amthor. 2000)1. However, there is evidence that this
relationship can breakdown in N addition studies [e.g., (Burton et al.. 2012; Drake et al.
2008; Schaberg et al.. 1997)1. and there are currently no broad analyses on the effects of
N additions on ecosystem or plant-scale autotrophic respiration (Figure 6-2B).
60
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Net Ecosystem
F|ux Input and
Output
Fluxes
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Total
Plant
Fluxes
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No No
AnalysisAnalysis
No No
AnalysisAnalysis
Below
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No
GPP R_
_ Above Below
Ground Ground
NPP NPP
Decomposition
Analysis ^
autotroph
^KXl
htmuuuph
NEE
DOC = dissolved organic C, NEE = net ecosystem exchange, GPP = gross primary production, Recosystem = ecosystem respiration,
NPP = net primary production; Recosystem autotroph = plant respiration, Rsom = soil respiration, Rsom heterotroph = heterotroph soil respiration.
Notes: Mean effect sizes from meta-analyses of N addition experiments on ecosystem, plant, and soil pools ([a] top panel) and
fluxes ([b] bottom panel). Error bars represent 95% confidence intervals. Numbers above the bars are the sample sizes for each
analysis. Letter with each bar denote the data source. No Analysis denotes a pool or flux that has not yet been meta-analyzed.
Data sources: (A) Liu and Greaver (2009). (B) Xia and Wan (2008). (C) Lu et al. (2011b): (D) Li et al. (2015): (E) Liu and Greaver
(20101. (F) Treseder (2004): (G) LeBauer and Treseder (2008): (H) Knorr et al. (2005)"
Figure 6-2
Effects of added nitrogen on ecosystem carbon pools and fluxes.
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The 2008 ISA noted some observations of decreased microbial biomass as a result of
added N, particularly among mycorrhizal fungi KTreseder. 2004); Figure 6-2B1.
However, it has become clear in more recent analyses that N deposition can greatly
impact microbial communities, which often includes a decrease in microbial biomass.
Meta-analyses conducted across all ecosystem types have found that N additions can
decrease microbial biomass (Treseder. 2008). microbial biomass C (Liu and Greaver.
2010). and microbial biomass N (Luetal.. 2011b) and that the effects of added N on
microbial biomass increase with the duration of N additions and the total amount of N
added (Treseder. 2008). These changes are noteworthy given the diverse role of
microorganisms in nutrient cycling, greenhouse gas fluxes, and other ecosystem services.
Although N additions frequently decrease microbial biomass, the results are not always
consistent (Liu and Greaver. 2010; Treseder. 2008). The effects of N were not significant
at the level of individual microbial domains (bacteria, fungi), although there were trends
toward increasing negative effects of N additions on fungal biomass as duration and
cumulative N load increased (Treseder. 2008). Recently, Li et al. (2015) provided a new
meta-analysis of N addition effects on mycorrhizal colonization of fine root tips and
observed an overall 19% decline (n = 21). While this reinforces the conclusions of an
earlier meta-analysis by Treseder (2004). there are important qualifiers to this finding: the
sample only included observations from forests and grasslands in temperate and
subtropical climates; significant decreases were only observed in forests, temperate
ecosystems, after more than 3 years of N additions, or at N addition rates
>100 kg N/ha/yr (Li et al.. 2015). Changes in mycorrhizae are notable given the role of
mycorrhizae in plant nutrition, biogeochemical cycling, and shaping plant community
composition. For instance, Van Per Heiiden et al. (2008) found that N additions
(100 kg N/ha/yr) had a smaller impact on plant community composition in dune grass
mesocosms inoculated with arbuscular mycorrhizal fungi than in mesocosms that had not
received the fungal inoculum and the plant communities in the inoculated mesocosms had
greater evenness among functional groups. In addition, mycorrhizal fungi carry a
significant cost to plants; in exchange for nutrients and water from the fungus, the plant
provides C from photosynthesis (Hogberg et al.. 2010; Rillig. 2004). Thus, plants that
make fewer mycorrhizal associations under higher N availability benefit from the
physiological advantages that accompany an alleviation of N limitation (e.g., increases in
photosynthesis, changes in plant chemistry), and from incurring a lower C cost for
mycorrhizae (Johnson et al.. 2008). Thus, the shift in C allocation away from
mycorrhizae may be a mechanism supporting increased plant productivity in situations
where plants do not show gains in photosynthesis [e.g., (Talhelm et al.. 2011)1.
There are numerous mechanisms through which N deposition could impact microbial
biomass, including changes in soil chemistry, changes in the rates of aboveground and
belowground plant C inputs (including litter production, root exudates, and C supplied to
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mycorrhizal fungi), and changes in plant tissue chemistry (Treseder. 2008). Nitrogen
additions can change the chemistry of litter inputs by altering the tissue composition of
plant species (Throop and Lcrdau. 2004) or by changing the composition of plant
communities contributing to the ecosystem flux of plant litter [e.g., (Manning et al..
2008)1. Within a particular species, N additions can cause changes in both of the
dominant forms of plant litter: leaf litter and fine roots [e.g., (Xia etal.. 2015)1. These
changes can be relatively direct, such as increases in tissue concentrations of inorganic
and organic forms of N [e.g., (Bauer et al.. 2004; koricheva et al.. 1998)1. While leaf
litter N concentrations are not as widely measured as green leaf N, increases in leaf litter
N concentrations due to added N are also likely to be widespread because increased N
availability often either decreases or has no effect on the fraction of N plants absorb from
leaves during senescence (Aerts. 1996). Other changes in litter chemistry, such as
increases in condensed tannins, soluble phenolics, and nonstructural carbohydrates (Xia
et al.. 2015). likely involve more complex biological mechanisms.
In a litter decomposition meta-analysis, Knorr et al. (2005) also observed that the effects
of added N also differed based on the length of the study and the initial litter lignin
content; added N stimulated decomposition in studies lasting less than 2 years, but
reduced decomposition in studies lasting more than 2 years; high lignin litter decomposed
more slowly, but low lignin litter decomposed faster. Because lignin concentrations tend
to increase during litter decomposition, both of these results were considered to be
consistent with earlier evidence that increased N supplies stimulate microbial activity
responsible for the decomposition of labile litter constituents such as lignin, while
suppressing the microbial production of extracellular enzymes responsible for the
degradation of lignin (Knorr et al.. 2005). In a subsequent meta-analysis, Liu and Greaver
(2010) found that although N additions increased aboveground litter production (+20%;
n = 37; not shown) across all biomes and N addition rates, there were no significant
overall changes in either total soil respiration (Figure 6-2B) or heterotrophic soil
respiration (Figure 6-2B). In fact, both forms of soil respiration tended to decline.
Currently, no similar cross-biome analysis has been conducted for changes in autotrophic
soil respiration (respiration from roots and mycorrhizal fungi), but Janssens etal. (2010)
noted in a meta-analysis that autotrophic respiration was suppressed by N additions in
forests.
Because some biological and biogeochemical processes involve specific chemical forms
of N (e.g., denitrification, ammonium toxicity), there is the potential that ecological
responses to N deposition (or N addition) could depend on whether the dominant form of
deposited N was oxidized (NOy) or reduced (NHx). A number of studies have specifically
addressed this issue, either by conducting experiments that directly test additions of
different forms of N or indirectly through syntheses that compare the effects of NOy and
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NHx in different experiments. One direct test occurred in the Front Range of the Rocky
Mountains in Colorado, where Ramirez et al. (2010a) investigated whether soil microbes
respond differently to additions of NH4+ versus NOs and found that the total amount of
N added was correlated with a decrease in soil respiration, not the form of the N (NH/
vs. NO? ). Similarly, Jovan et al. (2012) found that total N deposition, rather than the
deposition or atmospheric concentration of specific chemical forms of N, was the best
predictor of the abundance of eutrophic lichens in the Los Angeles Basin in southern
California. A more comprehensive understanding is available by reviewing the results of
meta-analyses that have compared the responses of N addition experiments conducted
with different forms of N (Table 6-1). Different responses to individual forms of N were
observed for some biogeochemical processes, such as increases in dissolved organic C,
decreases in ecosystem N retention, and increases in soil N2O emissions (Yue et al..
2016; Tempter et al.. 2012; Liu and Greaver. 2010. 2009). However, differences caused
by N forms in plant and microbial biomass or productivity responses to added N were
rarely observed and tended to occur where sample sizes were small [e.g., belowground C
pools in Yue et al. (2016)1.
Table 6-1 Changes in terrestrial ecological and biogeochemical endpoints
caused by different forms of inorganic nitrogen in meta-analyses.
Reference
Endpoint
Effect of NOy vs. NHx Forms
LeBauer and Treseder (2008)
Aboveground plant
productivity
Not significant
Yue et al. (2016)
Aboveground plant
productivity
Not significant
Yue et al. (2016)
Aboveground plant C pool
Not significant
Liu and Greaver (2010)
Leaf litter production
Insufficient data
Yue et al. (2016)
Leaf litter production
Insufficient data
Liu and Greaver (2010)
Fine root litter production
Not significant
Yue et al. (2016)
Belowground plant C pool
Increase with NhV, NH4NO3 and NO3" not significant
Treseder (2004)
Mycorrhizal abundance
Not significant
Treseder (2008)
Microbial biomass
Not significant
Liu and Greaver (2010)
Microbial biomass C
Not significant
Yue et al. (2016)
Microbial biomass C
Not significant
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Table 6-1 (Continued): Changes in terrestrial ecological and biogeochemical
endpoints caused by different forms of inorganic nitrogen
in meta analyses.
Reference
Endpoint
Effect of NOy vs. NHx Forms
Treseder (2008)
Fungal biomass
Not significant
Treseder (2008)
Bacteria biomass
Not significant
Liu and Greaver (2010)
Soil respiration
Increase with NhV, NH4NO3 and NO3" not significant
Yue etal. (2016)
Soil respiration
Not significant
Knorretal. (2005)
Litter decomposition
Not significant
Yue etal. (2016)
Litter decomposition
Not significant
Liu and Greaver (2010)
Microbial respiration
Not significant
Yue etal. (2016)
Microbial respiration
Not significant
Liu and Greaver (2009)
Soil organic C
Not significant
Yue etal. (2016)
Soil organic C
Not significant
Liu and Greaver (2010)
Mineral soil C
Not significant
Yue etal. (2016)
Mineral soil C
Not significant
Liu and Greaver (2010)
Soil organic horizon C
Not significant
Yue etal. (2016)
Soil organic horizon C
Increase with NH4NO3, NO3" not significant
Liu and Greaver (2010)
Dissolved organic C
Increase with NO3", NHV, and NH4NO3 not significant
Yue etal. (2016)
Dissolved organic C
Increase with NO3", NhV, and NH4NO3 not significant
Liu and Greaver (2009)
Ecosystem C content
Not significant
Templer et al. (2012)
Ecosystem 15N recovery
Less recovery of NO3" than NhV
Liu and Greaver (2009)
Methane emission
Not significant
Liu and Greaver (2009)
Methane uptake
Not significant
Liu and Greaver (2009)
N2O emission
Larger increase with NO3" than NhV or NH4NO3
C = carbon; 15N = tracer isotope of nitrogen; N20 = nitrous oxide; NH4+ = ammonium; NH4N03 = ammonium nitrate; NHX = sum of
reduced forms of N; N03" = nitrate; NOY = the sum of oxidized forms of nitrogen.
Note: Only statistically significant differences are noted.
1 Prior to the 2008 ISA, neither terrestrial N cycling nor anthropogenic N deposition had
2 been widely incorporated into the Earth systems models (ESMs) used to understand and
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forecast global climate and biogeochemical cycling. Thornton et al. (2007) made the first
effort to understand how both coupled C and N cycling and anthropogenic N deposition
would impact ESM predictions for terrestrial C uptake by inserting a new land
biogeochemistry model into a coupled climate system model. In the resulting model
output, N limitation greatly decreased the amount of terrestrial C uptake predicted from
future increases in atmospheric CO2 and decreased the sensitivity of terrestrial C
sequestration to increases in temperature and precipitation (Thornton et al.. 2007). The
inclusion of N deposition within the model directly increased terrestrial C uptake and also
indirectly increased terrestrial C uptake by removing some of the N limitation predicted
to occur under increased atmospheric CO2 (Thornton et al.. 2007). Subsequently, efforts
to model biogeochemical processes at regional and global scales have expanded (Thomas
et al.. 2015; Zaehle and Dalmonech. 2011). Although the integration of terrestrial N
cycling into ESMs remains relatively weak, more ESMs are incorporating the coupling of
terrestrial C and N cycling as overall model development and sophistication advances
(Thomas et al.. 2015; Arora et al.. 2013; Zaehle and Dalmonech. 2011; Bonan and Levis.
2010; Gerber et al.. 2010). Consistent with the findings of Thornton et al. (2007).
inclusion of coupled C-N cycling in ESMs has two primary effects: decreasing the
stimulatory effects of elevated atmospheric CO2 on terrestrial productivity and decreasing
the sensitivity of terrestrial C sequestration to climate warming because increased soil N
mineralization stimulates plant productivity (Arora et al.. 2013; Zaehle and Dalmonech.
2011; Zhang et al.. 201 lb; Arneth et al.. 2010; Bonan and Levis. 2010; Gerber et al..
2010; Yang et al.. 2010; Zaehle et al.. 2010; Thornton et al.. 2009). However, the ESMs
that do include basic terrestrial C-N coupling lack more recently identified interactions
such as plant organic N uptake, soil priming (root exudation), and the suppression of litter
decomposition at high soil N availability, all of which could increase terrestrial C uptake
to varying extents (Thomas et al.. 2015; Zaehle and Dalmonech. 2011). In addition, the
interactions between and net effects of N, precipitation, and temperature on ecosystem C
response in soils is unknown in many cases (see Section 13.1.2.1).
In the few ESMs that have directly included the effects of N deposition, the additional N
increased terrestrial C uptake and increased the extent to which elevated atmospheric CO2
stimulates terrestrial C uptake (Devaraiu et al.. 2016; Bonan and Levis. 2010; Yang et al..
2010). In addition, N deposition in the Northern Hemisphere (particularly in the U.S.)
apparently compounded the increase in C sequestration caused by the regrowth of
secondary forests during the late 20th century following agricultural abandonment and
timber harvest (Gerber et al. 2013; Yang et al.. 2010). However, it should be noted that
although N deposition and the overall anthropogenic production of reactive N increases
terrestrial C sequestration, this is not the only influence of anthropogenic N on global
climate. It is difficult to quantify the overall climate impact of anthropogenic N
[e.g., (Pinder et al.. 2013)1 because reactive N can change the planetary albedo by
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enhancing aerosol formation, stimulate the production of biogenic greenhouse gases, alter
the production and destruction of methane and tropospheric ozone in the atmosphere, and
indirectly decrease terrestrial productivity due to the phytotoxic effects of ozone (Lu and
Tian. 2013; Pinder et al.. 2013; Pinder et al.. 2012; Arneth et al.. 2010; Zaehle et al..
2010). Many of these impacts are discussed further in the atmospheric chemistry and
terrestrial biogeochemistry portions of this ISA (see Chapter 2 and Chapter 4).
In addition to the global-scale analyses conducted using ESMs, biogeochemical process
models have been used to assess the impact of N deposition on terrestrial productivity
and C sequestration at national and regional scales. Tian et al. (2012) used the Dynamic
Land Ecosystem Model (DLEM) to model the influence of climate, tropospheric ozone,
fertilizer use, land-use/land-cover change, atmospheric CO2, and N deposition on
terrestrial C storage over the 20th century in the southeastern U.S. (encompassing Texas
and Oklahoma to Florida and Virginia). Terrestrial C storage increased from 1951-2007,
with the model identifying atmospheric CO2 and N deposition as the environmental
factors responsible for the increase in C sequestration (Tian et al.. 2012). In China, a
series of papers has been published using biogeochemical process models to identify how
this same set of environmental factors influenced terrestrial C cycling in that country.
Rates of N deposition in China grew rapidly during the late 20th century and were
considerably higher than in the U.S. by the early 21st century, with nationwide average
rates of approximately 20 kg N/ha/yr and rates in southeast China averaging
35-40 kg/ha/yr (Lu and Tian. 2013; Lu et al.. 2012). Tian et al. (2011) applied the
Terrestrial Ecosystem Model and the DLEM model to China from 1961-2005. In both
models, China was a C sink during this time period, with the combination of N deposition
and agricultural fertilizer use accounting for 61% of the increase in C sequestration.
Notably, the responsiveness of terrestrial C sequestration to N deposition has declined
since the 1980s as N deposition in China increased, evidence that that terrestrial
ecosystems are becoming less N limited in China (Tian etal.. 2011). Lu et al. (2012)
conducted a similar analysis, using DLEM to understand how multifactor environmental
change influenced terrestrial C sequestration in China from 1901-2005. Like Tian et al.
(2011). Lu et al. (2012) observed that N deposition increased terrestrial C sequestration in
China throughout much of the late 20th century, but that the responsiveness of terrestrial
C sequestration to N deposition has declined since the 1980s. Moreover, Lu et al. (2012)
reported that all areas of China, aside from some shrublands and portions of western
China, are becoming N saturated.
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6.1.3
Forests
6.1.3.1 Aboveground Processes
The 2008 ISA noted a wide range of forest productivity responses to added N. Responses
to low levels of N were often positive because N availability tends to limit growth in
terrestrial ecosystems (LcBauer and Treseder. 2008). However, forest productivity
responses to higher rates of N addition were neutral or negative [e.g., (Magill et al..
2004)1. The effects of N deposition were variable across species. Conifer species,
particularly at high elevations, were more likely to exhibit negative growth responses or
mortality in response to added N. Conifer species were less likely to demonstrate
increased growth in response to additional N and more often exhibited decreased growth
and increased mortality [e.g., (McNultv et al.. 2005; Beieret al.. 1998; Boxman et al..
1998)1. Differences between broadleaf and conifer species were especially clear in
long-term N addition experiments: Elvir et al. (2003) observed increased sugar maple
(Acer saccharum) basal area growth in response to long-term (NEL^SC^ (25 kg/ha/yr for
11 years) additions, but red spruce (Picea rubens) growth was unchanged. At Harvard
Forest, oak (Quercus velutina, Q. rubra) increased growth in response to chronic N
additions (50 or 150 kg/ha/yr for 15 years), while red pine (Pinus resinosa) growth
slowed and mortality increased (Magill et al.. 2004). Most empirical observations of the
effects on atmospheric N deposition on forest productivity came from chronic N addition
experiments in temperate forests in the U.S. [e.g., (Pregitzer et al.. 2008; Magill et al..
2004; Elvir et al.. 2003; McNultv et al.. 1996; Aber et al.. 1995)1 and temperate and
boreal forests in Europe (Hvvonen et al.. 2008; Hogberg et al.. 2006; Beier et al.. 1998;
Boxman et al.. 1998). Empirical analyses of the effects of atmospheric N deposition on
forest productivity in the U.S. were lacking.
Research published since 2008 have reinforced many of the ideas in the 2008 ISA. There
is considerable evidence from deposition gradient studies, forest modeling, and long-term
N addition experiments that N deposition broadly stimulates tree growth and the
productivity of forested ecosystems. Using forest inventory data from the early 1980s
through the mid-1990s for 23 species growing in a region stretching from Ohio to Maine,
Thomas et al. (2010) found that N deposition accelerated growth in 11 species, including
3 of the 4 most abundant species ([red maple [Acer rubrum\, sugar maple, and northern
red oak [Quercus rubra]). There were negative effects on growth in three species, all of
which were evergreen conifers (red pine [Pinus resinosa], red spruce, northern
white-cedar [Thuja occidentalism). All five of the arbuscular mycorrhizal tree species
included in the analysis exhibited increased growth. Notably, although Xia and Wan
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(2008) observed positive effects of added N on growth for both broadleaf and coniferous
trees in a meta-analysis, broadleaf trees (+73%) were more responsive than conifers
(+37%). Eight species exhibited higher mortality rates with increasing N deposition in the
Thomas et al. (2010) analysis, notably several oak species, including northern red oak.
Only three species showed increased survival. In a broader analysis of forest inventory
data from across the entire eastern U.S. from the 1970s through early 2000s, Dietze and
Moorcroft (2011) found that N deposition was linked to decreased tree mortality in 9 of
10 plant functional types and increased mortality only in the northern mid-successional
hardwoods functional type. Across a smaller gradient within the Adirondacks, Bedison
and McNeil (2009) found a significant positive overall effect of N deposition on tree
growth from 1984-2004, but positive growth effects only for red maple, balsam fir
(Abies balsamea), and red spruce at the species level. Thus, it appears from these
inventory analyses that while tree growth has generally been enhanced by N deposition
over the last several decades, individual species have exhibited variable responses to N
deposition in mortality and growth.
Many of the species exhibiting notable responses in the broad northeastern U.S. inventory
analysis have also been included in long-term simulated N deposition experiments, but
the results in these studies have not always been consistent with the observations of
Thomas et al. (2010). Overstory sugar maple trees increased growth in response to added
N in Michigan KPregitzer et al. 2008); N added at 30 kg/ha/yr] and Maine KElvir etal..
2003); 25 kg/ha/yr], but mature sugar maple and red maple did not respond in the
Catskills I(Lovett et al.. 2013); 50 kg/ha/yr]. Northern red oak increased growth at
Harvard Forest KFrev et al.. 2014); 50 and 150 kg/ha/yr] and showed no growth response
at two sites in New York state I (Wallace et al.. 2007); 75 kg/ha/yr, (Lovett et al.. 2013);
50 kg/ha/yr], with increased mortality at one of the New York sites (Wallace et al.. 2007).
A 13-year study in a young forest in West Virginia included the two species with the
most positive growth responses in the Thomas et al. (2010) analysis and observed that N
addition (35 kg N/ha/yr of [NFL^SC^) increased growth of black cherry (Prunus
serotina), but decreased growth of tuliptree (Liriodendron tulipifera). Red pine at
Harvard Forest exhibited decreased growth and higher mortality in response to chronic N
additions KFrev et al.. 2014); 50 and 150 kg/ha/yr], while red spruce showed no growth
response in Maine KElvir etal. 2003); 25 kg/ha/yr]. Notably, the rates ofN additions in
these studies are often considerably greater than the rates of N deposition observed in the
U.S.
The effects of N deposition on tree growth and mortality in U.S. forests have been
similarly mixed in other contexts. At the same sites in Michigan where long-term N
additions increased growth of mature sugar maple (Pregitzer et al.. 2008). N additions
decreased the growth and survival of sugar maple saplings (Talhelm et al.. 2013;
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Patterson et al.. 2012). Notably, this negative effect occurred without increase in
overstory leaf area that would reduce light availability or a change in soil pH (Talhelm et
al.. 2013). Likewise, N deposition appears to be decreasing growth among northern red
oak saplings in the Chicago area, potentially contributing to the inability of this species to
regenerate in that region (Bassirirad et al.. 2015). In Vermont, 2 years of N addition at
150 kg/ha/yr increased growth in four hardwood species (including sugar maple and
northern red oak), decreased growth in one conifer, and had no effect on two other
hardwoods (Finzi. 2009). Allison et al. (2010) observed a 2.5-fold increase in
aboveground net primary productivity in response to several years of N additions
(100 kg/ha/yr) in central Alaska in a recently burned boreal forest. At two mixed conifer
forests in the Sierra Nevada, 2 years of N additions (12 or 24 kg/ha/yr) had a positive
effect on herb community biomass at one site (24 kg N/ha/yr) and a negative effect at the
other site (12 kg N/ha/yr); shrub biomass was unaffected (Hurteau and North. 2008).
Modeling 50 years into the future based on these results, a lower rate of N deposition
(12 kg N/ha/yr) was expected to increase herb biomass, while the high rate of N
deposition led only to a small increase in shrub biomass. In combination with a wetter
precipitation regime, both N deposition rates were predicted to increase shrub and herb
biomass (Hurteau et al.. 2009). In a greenhouse study, using N additions of up to
120 kg/ha/yr had no effect on the N fixing tree black locust (Robinia pseudoacacia) when
grown in a monoculture or in competition with the sawtooth oak (Quercus acutissima),
but N additions increased the height and total biomass of the sawtooth oak when grown
in competition with black locust (Luo et al.. 2014).
A number of studies on the effects on N deposition or chronic N additions have been
conducted in temperate and boreal forests in Europe and these studies have more
consistently found positive effects of N on tree growth. Solberg et al. (2009) studied tree
growth on 363 forest inventory monitoring plots across western and northern Europe.
Variation in tree volume increment was positively related to N deposition and summer
temperature, particularly for pine (Pinus) and spruce (Picea). Similar, but weaker,
relationships were apparent for beech (Fagus) and oak (Quercus). A positive effect of N
deposition on tree growth was also found on 135 Swiss long-term observation plots for
mature beech and spruce from the mid-1980s through late 2000s (Braun et al.. 2010).
However, further N additions decreased tree growth at three of seven experimental sites,
with these changes linked to phosphorus deficiencies (Braun et al.. 2010). Eastaugh et al.
(2011) took a more complex approach to understand growth trends of Norway spruce
(Picea abies) in the Austrian National Forest Inventory from 1960-2008. Using the
Biome-BGC model to isolate growth trends from variation in climate, the authors found a
positive relationship between tree growth and N deposition. Using data from long-term N
addition experiments in Norway spruce and Scots pine (Pinus sylvestris) forests
throughout Sweden and Finland, Hwonen et al. (2008) found increased tree growth at 11
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of 12 sites. The effects of added N on forest productivity appear to persist for decades
and carry over through major ecosystem disturbances. From et al. (2015) studied young
Norway spruce and Scots pine forests planted in the late 1990s after the original forests
were clear-cut. The original forests had received N additions of 150 kg N/ha/yr (as
NH4NO3) either twice (in 1977 and 1985), once (1985), or never. Tree height growth of
the young forests was positively related to the amount of previous N additions, with
significantly greater height growth in the forests that had received two N additions. Foliar
N concentrations were also significantly higher in the forests that had received N
additions (From et al.. 2015).
The 2008 ISA tied greater tree growth and forest productivity to increases in foliar N,
photosynthesis, and gross primary productivity. In addition, foliar N was identified as a
sensitive indicator of changes in forest N availability (Aber et al.. 1989). Since the 2008
ISA, increases in foliar N continue to have been linked to N deposition in forests in the
U.S., Europe, and Asia in pollution gradient studies (Talhelm et al.. 2012; Jones et al..
2011; Cox et al.. 2010; Thimonier et al.. 2010; Fenn et al.. 2008) and long-term N
addition experiments (Fowler et al.. 2015; Du and Fang. 2014; Lovett et al.. 2013;
Talhelm et al.. 2013; Lovett and Goodale. 2011; Talhelm et al.. 2011; Braun et al.. 2010).
For instance, Cox et al. (2010) observed a 40% increase in foliar N (from 15 mg/g to
21 mg/g) in Scots pine forests in Germany and the U.K. along an N deposition gradient of
4.6 to 28 kg N/ha/yr. In addition to trees, forest bryophytes and lichens also show
increased tissue N concentrations when exposed to additional N (McMurray et al.. 2015;
McMurray et al.. 2013; Gundale et al.. 2011; Fenn et al.. 2008; Glavich and Geiser.
2008). Increased foliar N is not universally observed in N addition studies [e.g., (Zhang et
al.. 2015c; Lovett et al.. 2013)1 or along N deposition gradients (Watmough and
Meadows. 2014). but a meta-analysis found that N additions generally increase foliar N
in trees (Luetal.. 2011b).
Although there are clear links between N deposition and increased foliar N and between
higher foliar N and increased photosynthesis, there is only somewhat limited evidence
that chronic N deposition increases leaf-level photosynthesis in forests. For instance, in
long-term simulated N deposition experiments in Massachusetts and Maine, only one of
four species exhibited increased photosynthesis with N additions (Elvir etal.. 2006;
Bauer et al.. 2004). Research on photosynthesis since the 2008 ISA has been similarly
mixed. Talhelm et al. (2011) did not observe a significant increase in either
photosynthesis or canopy leaf area in mature sugar maple trees at four sites in Michigan
in response to N additions (30 kg N/ha/yr as NaNC>3 for 14 years). Using a canopy
applied N treatment at two Swiss forests, Wortman et al. (2012) found that N additions
improved photosynthetic processes in oak at one site, but did not significantly influence
photosynthetic parameters in spruce or beech at the other site. At a broader scale,
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Fleischer et al. (2013) analyzed the effect of N deposition on photosynthesis using
observations from 80 forest eddy covariance C flux measurement sites predominantly
located in the eastern U.S. and western Europe. In this data set, canopy photosynthetic
capacity was positively correlated to N deposition for conifer forests when N deposition
was below an observed critical load of approximately 8 kg N/ha/yr (Fleischer et al..
2013). However, there was little to no influence of N deposition in broadleaf forests or
forests in the temperate climate zones, with most of the stimulus provided by N
deposition occurring in boreal forests (Fleischer et al.. 2013). Leonardi et al. (2012)
compiled a global data set of published tree ring 13C chronologies and found that the rate
of N deposition had a significant linear effect on intrinsic water-use efficiency (iWUE)
and 13C discrimination (A13C) in conifers and a quadratic effect in angiosperms. This
change in 13C suggests that the additional N either stimulated photosynthesis or
stimulated growth to the extent that the trees became more water limited.
The disconnect between the wide observations that N deposition can increase both tree
growth and foliar N concentrations and the inconsistent effects of N deposition on
leaf-level photosynthesis could be explained by two other physiological responses to N.
First, plants can store excess N in foliage as free amino acids and other physiologically
inactive forms of N (Bauer et al.. 2004). Increases in foliar amino acid concentrations,
particularly arginine, have been observed in forests in chronic N addition experiments
(Bauer etal.. 2004) and along N deposition gradients (Braun et al.. 2010). In these cases,
the added foliar N would have no impact on photosynthesis. Second, plants can respond
to added N by altering C allocation. As noted in the 2008 ISA, higher N availability often
causes trees to allocate less photosynthate to roots and belowground processes and more
photosynthate toward aboveground growth (Vicca et al.. 2012; Hogberg et al.. 2010;
Janssens et al.. 2010; Litton et al.. 2007; Aerts and Chapin. 1999; Minnich et al.. 1995).
Research since the 2008 ISA has provided further evidence that N deposition is likely
capable of causing such a shift in forests. In a greenhouse experiment, N additions (2, 5,
and 10 kg N/ha/yr) resulted in more biomass allocated to leaves than to roots at all four N
addition levels for oak and black locust trees. At the same Michigan sites where Talhelm
et al. (2011) observed that chronic N additions had no effect on leaf-level photosynthesis
or stand leaf area, the combination of increased aboveground growth, no change in root
production or respiration, and decreased mycorrhizal abundance led the authors to
conclude that a change in C allocation away from mycorrhizae was the likely cause for
enhanced tree growth. More broadly, Vicca et al. (2012) found that across 49 forest sites,
higher site fertility increased both the fraction of biomass that was allocated aboveground
and the fraction of photosynthate that was allocated toward biomass production. The
increase in C allocated to biomass production was thought to most likely result from less
C being allocated to root symbionts such as mycorrhizae (Vicca etal.. 2012). Likewise,
Janssens et al. (2010) conducted a meta-analysis of 20 forest N addition experiments and
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found that N additions decreased the fraction of C allocated to belowground processes
but did not affect root biomass. As an example of this, Hogberg et al. (2010) conducted a
short-term (~2 hour) 13CC>2 canopy labeling experiment in a young Scots pine forest in
northern Sweden in order to determine how N additions (two 100 kg N/ha additions over
2 years) altered the allocation of recent photosynthate belowground. In the 3 weeks
following the canopy labeling, the total soil respiratory efflux of the 13C label was 62%
lower in the plots that had received the N additions.
The effects of N addition on forest productivity have the potential to be moderated by
increases in herbivory, particularly among insects (Throop and Lerdau. 2004). For
instance, Andersen et al. (2010) observed that N additions increased foliar N and
photosynthetic rates within a tropical forest in Panama, but that tree growth rates were
unaffected because of increased herbivory. In a Pennsylvania common garden experiment
with northern red oak, saplings receiving N additions (200 kg N/ha/yr) tended to have
greater herbivore damage, but the effects of N addition on herbivory and the link between
herbivory and decreased growth both varied by the type of herbivore, the tree lineage
(breeding family), and the study location (Cha et al.. 2010). Similarly, Jones et al. (2008)
and Jones et al. (2011) observed that the most abundant herbivore of bracken fern
(Pteridium aquilinum) and a beetle herbivore of California black oak (Quercus kellogii)
were increased by N addition at a heavily polluted site, but not at a drier, less polluted
site. However, there was a positive correlation between leaf NO, concentrations and the
abundance of several groups of black oak herbivores.
6.1.3.2 Belowground Processes
The 2008 ISA analysis of how belowground processes in forests reacted to N deposition
focused on fine root dynamics, aboveground litter inputs, decomposition, soil respiration,
and soil C. Johnson (2001) had found a significant increase in forest soil C in response to
N additions as part of a meta-analysis, but only a single long-term N addition field study
had observed a significant increase in forest soil C KPregitzer et al.. 2008); see Chapter
4]. For fine roots, Nadelhoffer (2000) hypothesized that N deposition would decrease
biomass, but stimulate turnover and production. The 2008 ISA found little evidence with
which to evaluate this hypothesis. There was more available research on N effects on
decomposition and soil respiration. As noted earlier, Knorr et al. (2005) observed in a
meta-analysis that N additions increased decomposition at sites receiving low rates of
ambient N deposition (<5 kg/ha/yr), but N additions suppressed decomposition at sites
receiving moderate rates of N deposition (5-10 kg/ha/yr). Compared to aboveground
forest processes, the 2008 ISA suggested that there was a less advanced understanding of
how belowground processes in forests respond to added N.
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Research completed since the 2008 ISA has advanced our understanding of how N
affects belowground processes in forests. In two meta-analyses, Liu and Greaver (2010)
did not find a consistent effect of N additions on forest fine root production, while Li et
al. (2015) observed a decrease (-13.5%) in forest fine root biomass. Broadly, some of the
results discussed in the 2008 ISA that appeared inconsistent at the time were likely a
reflection of how N additions interacted with other ecological processes. In young,
rapidly expanding forests, N addition may increase root biomass as a consequence of an
overall enhancement of plant growth (Janssens et al.. 2010). For instance, N additions
(150 kg N/ha/yr for 3 years) to a young bamboo forest increased fine root growth by
>30%, even though this forest already received high rates of atmospheric N deposition
[95 kg N/ha/yr of wet deposition; (Tu et al.. 2015)1. However, as noted in the
"Aboveground Processes" section (Section 6.1.3.1). increases in N deposition tend to
decrease the proportion of C allocated to roots relative to aboveground growth (Li et al..
2015; Vicca et al.. 2012; Janssens et al.. 2010; Litton et al.. 2007; Minnich etal.. 1995).
Thus, in more mature forests, root biomass and production are not consistently affected
by N deposition. For instance, there were no effects of chronic N additions on fine root
biomass in four mature hardwood forests in Michigan [30 kg N/ha/yr for over 15 years;
(Burton et al.. 2012)1 and in the two mature mixed oak (Quercus) stands at Harvard
Forest [50 or 150 kg N/ha/yr for over 20 years; (Frev et al.. 2014)1. Likewise,
50 kg N/ha/yr did not cause significant changes in root biomass in a Puerto Rican tropical
forest (C'usack et al.. 2010). In contrast with the mixed oak stands, fine root biomass
decreased in two red pine stands at Harvard Forest [50 or 150 kg N/ha/yr for over
10 years; (Frev et al.. 2014)1.
Observations of how other belowground processes respond to N additions provide further
evidence of an increase in the ratio of tree C allocated to aboveground growth and
productivity versus the C allocated belowground. In a meta-analysis of forest soil
respiration responses to N addition, Janssens et al. (2010) noted that N additions
decreased soil respiration overall, with a portion of this effect caused by a decrease in
autotrophic respiration. Within forests, autotrophic respiration may make up more than
50% of total soil respiration (Hasselquist et al.. 2012). Much this autotrophic respiration
is mycorrhizal respiration, with the C allocated to and respired by mycorrhizae estimated
to account for 9 to 34% of forest soil respiration (Hasselquist et al.. 2012; Heinemever et
al.. 2007).
Mycorrhizal fungi have long been observed to be sensitive to increased forest N
availability, particularly ectomycorrhizae because these fungi have direct roles in plant N
acquisition, and their production of aboveground fruiting bodies (sporocarps) makes it
easier to observe changes in abundance (Treseder. 2004; Lillcskov et al.. 2002; Wallenda
and Kottke. 1998). In a meta-analysis, Li et al. (2015) found that N additions decreased
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mycorrhizal colonization of fine root tips by 19% (n = 12). In contrast to the widespread
increases in aboveground tree growth, studies of ectomycorrhizal growth and
productivity responses to added N have documented nearly universally negative or
neutral effects on metrics such as mycorrhizal root colonization, sporocarp abundance,
and the abundance of the fungal lipid biomarker 18:2co6,9 in the soil (Table 6-2).
Although this research is consistent, these studies have limitations because all of this
research has been conducted on conifer species and most of the negative effects occur in
studies using unrealistically high rates of N addition (>100 kg N/ha/yr). However, two
studies of ectomycorrhizae in Norway spruce forests in Europe have documented
significant declines along gradients of ambient N deposition (Bahr et al. 2013; ki oiler et
al.. 2012). In particular, ki oiler et al. (2012) observed an 80 and 90% decrease in
ectomycorrhizal root tip abundance and mycelial production, respectively, across a
canopy throughfall N deposition gradient of 27 to 43 kg N/ha/yr in Denmark. Parrent and
Vilgalvs (2009) took a notably different approach, studying expression of plant genes for
monosaccharide transport (MST; three genes) and ammonium transport (AMT; two
genes) and fungal 18S ribosomal RNA in tree roots in a North Carolina loblolly pine
(Pinus taeda) forest that received N additions of 112 kg N/ha/yr for a single year. The
MST genes are involved in supplying monosaccharides to plant and fungal cells and the
genes are upregulated in ectomycorrhizal symbiosis; AMT genes have been linked to the
uptake of NH4+ from mycorrhizal fungi; 18S rRNA expression is an index of mycorrhizal
activity. Although the effects were not statistically significant, the N additions
consistently decreased in the three MST genes and both AMT genes.
Given these decreases in ectomycorrhizal growth and productivity in response to added
N, it is not surprising that researchers have found that the amount of C allocated
belowground by plants to mycorrhizae can be sensitive to N availability. Hogberg (2012)
twice added N (100 kg N/ha) over a period of two growing seasons to boreal Scots pine
forests in Sweden as part of a short (~2 hour) 13C canopy labeling experiment. In the
5 weeks following the labeling, 48% less of the 13C label was found in an
ectomycorrhizal fungal lipid biomarker in the soil of the N amended plots. Hasselquist et
al. (2012) found that in Scots pine forests in northern Sweden, 6 years of N additions at a
rate of 100 kg N/ha/yr decreased respiration from ectomycorrhizae by 40%, but N
additions at a rate of 20 kg N/ha/yr increased this respiration by 120%. However, the low
N addition did not change the fractional contribution of ectomycorrhizae to total soil
respiration. The low N addition treatment also had no effect on ectomycorrhizal
sporocarp production, but the high N addition treatment nearly eliminated sporocarp
production [99% decrease; (Hasselquist et al.. 2012)1. The availability of N also appears
to influence the transfer of N from mycorrhizal fungi to plants. In a boreal Scots pine
forest in Sweden, Nasholm et al. (2013) observed that a single N dose (100 kg N/ha)
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shifted the dominant sink for a 15N tracer added two weeks later from the cytoplasm of
ectomycorrhizal fungi and other soil microorganisms to the pine foliage.
Table 6-2 Growth, productivity, and carbon cycle responses of ectomycorrhizal
fungi to nitrogen added via atmospheric deposition or experimental
treatments.
Study
Reference Location
Ambient
Deposition
Vegetation or Addition
Nitrogen
Addition
Rate Duration
(kg N/ha/yr) (yr)
Effect of
Additional
Endpoint Nitrogen
Gillet et al. (2010) Switzerland Norway Addition 150 12 Sporocarp Decrease
spruce abundance
(Picea
abies)
Hasselauist and Sweden
Hogberg (2014)
Scots pine Addition
(Pinus
sylvestris)
110 20; 15 yr Sporocarp Not
recovery abundance significant
Allison et al. (2008) Alaska
Black Addition
spruce
(Picea
mariana)
140
Sporocarp
abundance
Decrease
Hasselquist et al. Sweden Scots pine Addition 20,100 6 Sporocarp Low dose:
(2012) (Pinus abundance not
sylvestris) significant
high dose:
decrease
Hasselquist and Sweden Scots pine Addition 20,100 6 Sporocarp Low dose:
Hoqberq (2014) (Pinus abundance not
sylvestris) significant
high dose:
decrease
Hasselguist and Sweden
Hogberg (2014)
Scots pine Addition 35, 70
(Pinus
sylvestris)
40, 2 yr Sporocarp Decrease
recovery abundance
for 70-kg
treatment
Ki0ller et al. (2012) Denmark Norway Ambient 27-43 n/a Root Decrease
spruce colonization (%)
(Picea
abies)
Garcia et al. (2008) North Loblolly Addition 112 2 Root Increase
Carolina pine (Pinus colonization (%)
taeda)
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Table 6-2 (Continued): Growth, productivity, and carbon cycle responses of
ectomycorrhizal fungi to nitrogen added via atmospheric
deposition or experimental treatments.
Reference
Study
Location
Ambient
Deposition
Vegetation or Addition
Nitrogen
Addition
Rate
(kg N/ha/yr)
Duration
(yr)
Endpoint
Effect of
Additional
Nitrogen
Diaz etal. (2010)
Spain
Aleppo pine Addition
(Pinus
halepensis)
35, 60,
120 mg/plant
1
Root
colonization (%)
Decrease
Kou etal. (2015)
China
Slash pine
(Pinus
elliottii)
Addition
40, 120
2
Root
colonization (%)
Low dose:
not
significant
hiah dose:
increase
Nasholm et al.
(2013)
Sweden
Scots pine
(Pinus
sylvestris)
Addition
100
0 Fine root chitin
(2 weeks) concentration
Not
significant
Pritchard et al.
(2014)
North
Carolina
Loblolly
pine (Pinus
taeda)
Addition
112
6
Mycorrhizal root
tip production
Decrease
Pritchard et al.
(2014)
North
Carolina
Loblolly
pine (Pinus
taeda)
Addition
112
6
Deep soil
mycorrhizal root
tip survival
Increase
Bahretal. (2013)
Sweden
Norway
spruce
(Picea
abies)
Ambient
0.9-24.6
n/a
Mycelium
production
Decrease
Ki0ller et al. (2012)
Denmark
Norway
spruce
(Picea
abies)
Ambient
27-43
n/a
Mycelium
production
Decrease
Bahretal. (2015)
Sweden
Norway
spruce
(Picea
abies)
Addition
200 (once)
1
Mycelium
production
Decrease
Vallack et al. (2012)
Sweden
Scots pine
(Pinus
sylvestris)
Addition
100
2
Mycorrhizal
respiration
Decrease
Hasselquist et al.
(2012)
Sweden
Scots pine
(Pinus
sylvestris)
Addition
20, 100
6
Mycorrhizal
respiration
Low dose:
increase
hiah dose:
decrease
Hoabera et al.
(2011)
Sweden
Scots pine
(Pinus
sylvestris)
Addition
120
20; 15 yr
recovery
EM biomarker
18:2(jo6,9
Not
significant
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Table 6-2 (Continued): Growth, productivity, and carbon cycle responses of
ectomycorrhizal fungi to nitrogen added via atmospheric
deposition or experimental treatments.
Reference
Study
Location
Ambient
Deposition
Vegetation or Addition
Nitrogen
Addition
Rate
(kg N/ha/yr)
Duration
(yr)
Endpoint
Effect of
Additional
Nitrogen
Hoabera et al.
(2011)
Sweden
Scots pine
(Pinus
sylvestris)
Addition
30, 70
35
EM biomarker
18:2(jo6,9
Decrease
Nasholm et al.
(2013)
Sweden
Scots pine
(Pinus
sylvestris)
Addition
100
0 (2
Weeks)
13C labeling of
EM biomarker
PLFA 18:2(jo6,9
Not
significant
Hoabera et al.
(2010)
Sweden
Scots pine
(Pinus
sylvestris)
Addition
100
2
13C labeling of
EM biomarker
PLFA 18:2(jo6,9
Decrease
Parrent and Vilaalvs
(2009)
North
Carolina
Loblolly
pine (Pinus
taeda)
Addition
112
1
EM 18S RNA
Expression
Not
significant
Parrent and Vilaalvs
(2009)
North
Carolina
Loblolly
pine (Pinus
taeda)
Addition
112
1
Root ammonium
transport gene
expression
Not
significant
Parrent and Vilaalvs
(2009)
North
Carolina
Loblolly
pine (Pinus
taeda)
Addition
112
1
Root
monosaccharide
transport gene
expression
Not
significant
EM = ectomycorrhizal fungi; ha = hectare; kg = kilogram; N = nitrogen; n/a = not applicable; PLFA = phospholipid fatty acids;
RNA = ribonucleic acid; yr = year.
Note: Single studies are reported more than once if multiple endpoints are measured. Only statistically significant effects are listed
as increases or decreases.
Although ectomycorrhizae are important in many high latitude and temperate
ecosystems, particularly forests, most species of terrestrial plants form arbuscular
mycorrhizae (Rillig. 2004). The impact of N deposition on arbuscular mycorrhizae has
received less research attention, perhaps partly because these fungi are best known for
their role in plant phosphorus acquisition (Rillig. 2004). Arbuscular mycorrhizae
community composition and production can be sensitive to added N lYvan Diepen et al..
2010; Egerton-Warburton and Allen. 2000); Table 6-31. but these effects may not be
consistent, van Diepen et al. (2010) reviewed eight previous studies of how intra-radicle
(within root) and extra-radicle arbuscular mycorrhizal biomass responded to N additions,
predominantly in forests, and found inconsistent effects. Intra-radical biomass
significantly declined in response to N in three studies and increased in two studies,
including in the work of Garcia et al. (2008). In comparison, extra-radical biomass was
either unresponsive or declined (van Diepen et al.. 2010). Aside from the work of Garcia
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et al. (2008). other researchers since 2008 have found either neutral or negative effects on
metrics of arbuscular mycorrhizal biomass and abundance (Table 6-3). Notably, the
arbuscular mycorrhizal species studied by Garcia et al. (2008) were all understory or
subdominant canopy species growing beneath ectomycorrhizal loblolly pines. The
increased growth of these larger trees in response to added N may have imposed other
resource limitations on the arbuscular mycorrhizal plant species. Although this more
recent research has generally shown negative or neutral effects, the overall inconsistency
of arbuscular mycorrhizal responses to N that was documented by van Diepen et al.
(2010) is in contrast to the universally positive aboveground growth responses of
arbuscular mycorrhizal tree species to N deposition observed by Thomas et al. (2010).
Further research is needed to quantify how C fluxes to arbuscular mycorrhizae change in
response to added N.
Table 6-3 Growth, productivity, and carbon cycle responses of arbuscular
mycorrhizal fungi to nitrogen added via atmospheric deposition or
experimental treatments.
Reference
Study
Location
Vegetation
Ambient
Deposition
or
Addition
Nitrogen
Addition
Rate
(kg N/ha/yr)
Duration
(yr)
Endpoint
Effect of
Additional
Nitrogen
Garcia et al. (2008)
North
Carolina
Loblolly pine
(Pinus
taeda)
Addition
100
1-2
Root
colonization (%)
Increase
Mandvam and
Jumpponen (2008)
Kansas
C3 and C4
grasses
Addition
100
3
Root
colonization (%)
Not
significant
Camenzind et al.
(2014)
Ecuador
Evergreen
tropical
forest
Addition
50
3
Root
colonization (%)
Decrease
Van Der Heiiden et
al. (2008)
Holland
Dune
grasses
Addition
100
1
Root
colonization (%)
Decrease
Chen et al. (2014)
China
Steppe
grassland
Addition
100
6
Root
colonization (%)
Not
significant
van Diepen et al.
(2010)
Michigan
(four sites)
Sugar maple
(Acer
saccharum)
Addition
30
13
Intra-radical
biomass
(16:1 oj5c
abundance)
Decrease
van Diepen et al.
(2010)
Michigan
(four sites)
Sugar maple
(Acer
saccharum)
Addition
30
13
Extra-radical
biomass
(16:1 oj5c
abundance)
Decrease
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11
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16
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18
19
20
21
22
Table 6-3 (Continued): Growth, productivity, and carbon cycle responses of
arbuscular mycorrhizal fungi to nitrogen added via
atmospheric deposition or experimental treatments.
Reference
Study
Location
Vegetation
Ambient
Deposition
or
Addition
Nitrogen
Addition
Rate
(kg N/ha/yr)
Duration
(yr)
Endpoint
Effect of
Additional
Nitrogen
van Diepen et al.
(2010)
Michigan
(four sites)
Sugar maple
(Acer
saccharum)
Addition
30
13
Extra-radical
biomass
production
Decrease
Chen et al. (2014)
China
Steppe
grassland
Addition
100
6
Hyphal length
Decrease
Garcia et al. (2008)
North
Carolina
Loblolly pine
(Pinus
taeda)
Addition
100
1-2
Soil glomalin
content
Not
significant
ha = hectare; kg = kilogram; N = nitrogen; yr = year.
Note: Single studies are reported more than once if multiple endpoints are measured. Only statistically significant effects are listed
as increases or decreases.
Aside from mycorrhizal respiration, the other dominant component of autotrophic soil
respiration is root respiration. Although Janssens et al. (2010) observed a decrease in
autotrophic soil respiration in the presence of N, this decrease was not apparently related
to changes in root respiration. In a long-term N addition experiment (30 kg N/ha/yr for
+15 years) in four northern hardwoods forests, Burton et al. (2012) found that although
root N concentration was a strong predictor of the root respiration rate and N additions
had increased root N concentrations, N additions had not increased root respiration
because the added N changed the relationship between root N and respiration. Drake et
al. (2008) made a similar observation in loblolly pine forests in North Carolina: N
additions (100 kg N/ha/yr for 2 years) increased fine root N concentrations but did not
impact fine root respiration rates, resulting in an altered tissue N respiration relationship.
Frev et al. (2014) also reported that root respiration was unresponsive to long-term N
additions (50 or 150 kg N/ha/yr) in oak forests and pine forests in Massachusetts.
However, Hasselquist et al. (2012) found that a relatively modest N addition rate
(20 kg N/ha/yr for 6 years) increased both root and mycorrhizal respiration in a boreal
forest in Sweden that received relatively low rates of ambient N deposition
(<5 kg N/ha/yr). Thus, it appears that C allocation to mycorrhizae is more sensitive to N
availability than C allocation to root respiration.
In a meta-analysis of the effects of N additions on microbial biomass, Treseder (2008)
found that changes in soil respiration were significantly and positively correlated with the
response of microbial biomass. Mycorrhizal fungi are major components of forest soil
microbial communities, with Hogberg et al. (2010) estimating that ectomycorrhizal
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mycelium made up 39% of total soil microbial biomass in a Swedish boreal forest. Given
the widespread negative effects of added N on mycorrhizal fungi, the results of Treseder
(2008)'s meta-analysis and the broadly negative or neutral effects of N additions on
microbial biomass in the studies published since 2008 are unsurprising (Table 6-4).
However, soil microbial communities are taxonomically and functionally diverse and
have exhibited varying responses to added N in forests (Zhang et al.. 2015c; Treseder.
2008). For instance, Wang et al. (2015a) added N (0, 50, 100, or 150 kg N/ha/yr for
9 years) to pine, broadleaf, and mixed pine-broadleaf forests in southern China; the 50 kg
N treatment increased microbial biomass C in the pine forests and the 150 kg N treatment
decreased microbial biomass C in the broadleaf forests, but there were no other
significant treatment effects. The addition of 100 kg N/ha/yr to a regenerating Alaskan
boreal forest decreased the microbial biomass and the C:N ratio of microbial biomass
(Allison et al.. 2010; Allison et al.. 2008). In England, Bebberetal. (2011) observed that
simulated N deposition (2.8 kg N/ha/yr) had no effect on the mycelial growth of
wood-decomposing fungi within a beech forest. In Michigan, long-term (+15 years) N
additions (30 kg N/ha/yr) to northern hardwood forests decreased the abundance of
actinobacteria in the surface mineral soil, but not in the soil organic horizon (Eisenlord
and Zak. 2010). Relative to mycorrhizal fungi, there is less information available
regarding the growth and biomass responses of individual domains and other taxonomic
groupings within microbial communities (Table 6-4). Of this finer scale information,
most observations are for fungi (sometimes including mycorrhizal fungi), with positive,
neutral, and negative effects of added N.
Atmospheric N deposition may affect forest microbial communities and litter
decomposition by altering litter chemistry through shifts in forest community
composition, increasing litter N concentrations, or changing the secondary chemistry of
litter. The two dominant forms of forest plant litter, leaves and fine roots, can each be
altered by N additions (Xia etal.. 2015). As noted in the aboveground processes section
of this chapter, there is abundant evidence that N deposition can increase foliar N
concentrations in trees and there is also a large body of research that the increase in foliar
N concentrations will result in increased leaf litter N concentrations (Aerts. 1996). Since
the 2008 ISA, there have been new observations of increased leaf litter N concentrations
both in long-term N addition experiments (van Diepen et al.. 2015; Xia et al.. 2015; Zak
et al.. 2008) and along an N deposition gradient [6.8-11.8 kg N/ha/yr; (Talhelm et al..
2012)1. Increases in leaf litter N concentrations with greater N deposition are not
universal [e.g., (Watmough and Meadows. 2014)1. but in a meta-analysis, van Diepen et
al. (2015) observed a >20% increase in tree leaf litter N concentrations in response to N
additions. Other changes in forest litter chemistry likely involve changes in more
complex physiological and biogeochemical mechanisms (Du and Fang. 2014). In an old
growth boreal forest in China, N additions (20, 50, or 100 kg N/ha/yr for 3 years)
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decreased leaf litter phosphorus concentrations, an effect that could have been caused by
changes in either physiological or biogeochemical processes (Du and Fang. 2014). In a
meta-analysis, van Diepen et al. (2015) found that simulated N deposition significantly
decreased leaf litter concentrations of phosphorus, calcium, manganese, aluminum, and
zinc, but did not find significant changes in concentrations of potassium, magnesium,
boron, iron, or copper. It is not entirely understood how all of these changes in elemental
composition impact the composition and function of soil microbial communities, but
manganese and calcium are needed for the production of extracellular enzymes that
degrade lignin (van Diepen et al.. 2015).
There is a large volume of research about how major biochemical constituents of plant
litter such as lignin, cellulose, condensed tannins, and phenolics impact leaf litter
decomposition, but less information about how N additions change the abundance of
these compounds. Xia et al. (2015) researched the effects of long-term N additions
(30 kg N/ha/yr for +15 years) on sugar maple leaf litter and fine root chemistry in four
mature northern hardwood forests in Michigan. The N additions increased concentrations
of condensed tannins in leaf litter and in fine roots. At three of the four sites, N additions
increased the fraction of nonstructural cell wall material and decreased both cellulose and
lignin in leaf litter. On an ecosystem basis, N additions decreased total annual litter
(leaf + fine root) fluxes of condensed tannins and soluble protein and increased the fluxes
of nonstructural carbohydrates (sugars + starch) and N (Xia etal.. 2015). Based on broad
decomposition chemistry patterns observed elsewhere, these changes in litter chemistry
were expected to increase initial rates of litter decomposition, which contrasts with the
decrease in litter turnover rates observed at these sites (Xia et al.. 2015). However,
changes in tissue chemistry are not ubiquitous, such as in Griepentrog et al. (2015). who
observed that the abundance and composition of fatty acids in leaf and root tissues in
spruce and beech trees in Switzerland were not influenced by added N (70 kg N/ha/yr).
Further, while N additions can change plant tissue chemistry, links between litter
chemistry and microbial abundance and microbial function are complex [e.g., (Baumann
etal.. 2009)1.
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Table 6-4 Abundance and carbon cycle responses of forest soil
microorganisms to nitrogen added in experimental treatments.
Reference
Ambient Nitrogen
Deposition Addition
Study or Rate Duration
Location Vegetation Addition (kg N/ha/yr) (yr)
Endpoint
Effect of
Additional
Nitrogen
Treseder (2008) Meta- Mostly Addition
analysis boreal and
temperate
forests
1-600
0.5-57
Microbial
biomass
Decrease
Treseder (2008) Meta- Mostly Addition
analysis boreal and
temperate
forests
1-600
0.5-57
Fungal
biomass
Not
significant
Treseder (2008) Meta- Mostly Addition
analysis boreal and
temperate
forests
1-600
0.5-57
Bacterial
biomass
Not
significant
Allison et al. (2008)
Alaska
Boreal forest
Addition
140
5
Microbial
Not
(Picea
biomass
significant
mariana)
Allison et al. (2010)
Alaska
Boreal forest
Addition
114
7
Microbial
Decrease
(Picea
biomass C
mariana)
van Diepen et al.
Michigan (Ml
Northern
Addition
30
12
Microbial
Decrease
(2010)
gradient)
hardwood
biomass
forests (Acer
saccharum)
Hobbieet al. (2012)
Minnesota
Oak and
Addition
100
5
Microbial
Not
(Cedar
pine forests
biomass
significant
Creek)
(Quercus
ellipsoidalis,
Pinus
strobus)
Keeler et al. (2009)
Minnesota
Temperate
Addition
100
5
Microbial
Not
(Cedar
forests
biomass
significant
Creek)
(Quercus
ellipsoidalis,
Pinus
strobus) and
Grassland
Zhao et al. (2014a)
China
Spruce-fir
Addition
250
4
Microbial
Decrease
(Tibetan
(Picea
biomass
plateau)
asperata,
Abies
faxoniana)
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Table 6-4 (Continued): Abundance and carbon cycle responses of forest soil
microorganisms to nitrogen added in experimental
treatments.
Reference
Study
Location
Vegetation
Ambient
Deposition
or
Addition
Nitrogen
Addition
Rate
(kg N/ha/yr)
Duration
(yr)
Endpoint
Effect of
Additional
Nitrogen
Wanqetal. (2015a)
China
(southern)
Subtropical
pine forest
(Pinus
massoniana)
Addition
50, 100
8
Microbial
biomass C
Low dose:
increase;
hiah dose:
not
significant
Wanqetal. (2015a)
China
(southern)
Subtropical
pine-
broadleaf
forest (Pinus
massoniana)
Addition
50, 100
8
Microbial
biomass C
Not
significant
Wanqetal. (2015a)
China
(southern)
Subtropical
broadleaf
forests
Addition
50, 100,
150
8
Microbial
biomass C
Low. mid
dose: not
significant;
hiah dose:
decrease
Zhao etal. (2014a)
China
(Tibetan
plateau)
Spruce-fir
(Picea
asperata,
Abies
faxoniana)
Addition
250
4
Bacterial
biomass
Decrease
Hesse etal. (2015)
Michigan (Ml
gradient)
Northern
hardwood
forests (Acer
saccharum)
Addition
30
16
Bacterial
biomass
Not
significant
Hesse etal. (2015)
Michigan (Ml
gradient)
Northern
hardwood
forests (Acer
saccharum)
Addition
30
16
Fungal
biomass
Not
significant
Zhao etal. (2014a)
China
(Tibetan
plateau)
Spruce-fir
(Picea
asperata,
Abies
faxoniana)
Addition
250
4
Fungal
biomass
Decrease
Enowashu et al.
(2009)
Germany
Norway
spruce
(Picea
abies)
Subtraction
9.7 (-21)
16
(recovery)
Fungal
biomass
(ergosterol)
Increase
van Diepen et al.
(2010)
Michigan (Ml
gradient)
Northern
hardwood
forests (Acer
saccharum)
Addition
30
12
Saprotrophic
fungal
biomass
Not
significant
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Table 6-4 (Continued): Abundance and carbon cycle responses of forest soil
microorganisms to nitrogen added in experimental
treatments.
Reference
Study
Location
Vegetation
Ambient
Deposition
or
Addition
Nitrogen
Addition
Rate
(kg N/ha/yr)
Duration
(yr)
Endpoint
Effect of
Additional
Nitrogen
Bebberet al. (2011)
U.K.
Broadleaf
temperate
forest
(Fraxinus-
Acer, Fag us)
Addition
2.8
1
Fungal
mycelium
growth
Not
significant
Allison et al. (2008)
Alaska
Boreal forest
(Picea
mariana)
Addition
140
5
Fungal
sporocarp
biomass
Decrease
Gillet et al. (2010)
Switzerland
Norway
spruce
(Picea
abies)
Addition
150
12
Saprobic
fungal
sporocarp
abundance
Increase
and
decrease
(N x yr)
C = carbon; ha = hectare; kg = kilogram; N = nitrogen; yr = year.
Note: Single studies are reported more than once if multiple endpoints are measured. Only statistically significant effects are listed
as increases or decreases.
6.1.3.3 Forest Lichens
Lichens are widely used as indicators of N deposition impacts on ecosystems, particularly
in forests. However, lichens also are important for ecosystem function. For insects, birds,
and mammals, lichens represent camouflage, building materials for nests, and a source of
food or prey (Brodo et al.. 2001). Lichens absorb N, S, and other elements from
atmospheric deposition and throughfall, and lichens that host cyanobacteria can add
significantly to ecosystem N inputs, providing N to other plants (kobvlinski and Fredeen.
2015). In addition, lichens also have a role in hydrologic cycling, have many traditional
human uses, and have high potential for pharmaceutical use (McCune and Geiser. 1997).
Lichens are symbioses comprised of fungi (mycobiont) and a green alga and/or
cyanobacterium [photobiont; (Sundberg et al.. 2001; Palmqvist. 2000)1. Much of the
lichen biomass is comprised of fungal (mycobiont) tissue, but the photobiont synthesizes
organic compounds, supplying the energy and structural C needed for growth of the
lichen. Both the photobiont and the mycobiont require N for growth (Palmqvist. 2000).
but the supply of C and N must be must be coordinated for the development of lichen
thalli (Sundberg et al.. 2001). Lichens with a cyanobacterial photobiont are N fixing, but
those with a green algal photobiont depend on atmospheric deposition for N.
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Lichens can be classified based on their response to N pollution. Lichens occurring in
areas that receive high N deposition are considered nitrophytic or eutrophic; lichens
common in areas receiving low N input are designated acidophytic or oligotrophic (Gaio-
Oliveira et al. 2005; van Herk. 2001). Atmospheric N deposition can impact lichens
through changes in physiological function caused by an increased supply of N or by
altering the pH of tree bark hosting the lichen (Jovan. 2008). Although lichens with a
green algal photobiont depend on atmospheric deposition as a source of N, these lichens
can also be negatively impacted by N deposition via the accumulation of toxic
concentrations of NH4 within the thallus. Cyanobacteria can grow on either NO3 or
NH4+ sources when administered at nontoxic concentrations, but more rapid growth has
been observed with NH4 than NO3 (Von Riickert and Giani. 2004). Ammonium is more
easily assimilated by lichens; both NO3 and nitrite must first be reduced to NH4 before
assimilation (Von Riickert and Giani. 2004). The 2008 ISA noted that lichens with a
cyanobacterial photobiont appear to be more sensitive to adverse effects from
atmospheric N deposition than most other lichens (Dahlman et al.. 2002; Hallingback and
Kellner. 1992; Hallingback. 1991). In part, the sensitivity of lichens to increasing N
deposition is a function of the mechanisms with which that lichen can respond to high N
supply, such as decreasing N uptake or assimilating N into nontoxic forms such as
arginine (Gaio-Oliveira et al.. 2005; Dahlman et al.. 2002).
Since the 2008 ISA, new research on the impact of N deposition on the growth and
physiology of forest lichens has both confirmed that lichen abundance is sensitive to N
deposition and provided further insight on the growth and physiological changes that
occur when lichens are exposed to exogenous N (Table 6-5). For example, previous
research had suggested that lichens were most sensitive to N as ammonia (Sheppard et
al.. 2011; Jovan. 2008). However, a study of lichen communities on California black oak
(Quercus kellogii) forests at 22 sites in the Los Angeles Basin in California, Jovan et al.
(2012) found that the abundance of eutrophic lichen species was only weakly related to
gaseous NH3 concentrations. Instead, the strongest N pollution-related predictor of
eutrophic lichen abundance was total N deposition (as canopy throughfall). Further, at the
relatively neutral bark pHs in the Los Angeles Basin, there was no influence of pH on the
abundance of eutrophic lichen species. The abundance of eutrophic lichens was also best
correlated with total throughfall N deposition in southeast Alaska (Schirokauer et al..
2014a). This research provides strong evidence that total N deposition, not the deposition
of a particular form of N, is the primary driver of changes in the growth, physiology, and
composition of epiphytic lichens.
Increases in lichen thalli N concentrations in response to added N have been widely
observed in the U.S. and Europe (Table 6-5). even at relatively low rates of atmospheric
N deposition. For instance, McMurray et al. (2013) measured throughfall N deposition
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and sampled lichen thalli N concentrations at sites near the Bridger-Teton Wilderness that
were at increasing distances downwind of a major oil and natural gas production field.
Although the observed rates of N deposition were only 0.8 to 4.1 kg N/ha/yr along this
gradient, thalli N concentrations in Usnea lapponica approximately doubled from ~1.2 to
2.4%. In southeastern Alaska, Schirokauer et al. (2014a) found increases in thalli N
concentrations along an even smaller range of N deposition (0.05 to 1.05 kg N/ha/yr), a
pollution gradient attributed to cruise ship emissions.
Also in southern California, Riddel 1 et al. (2008) transplanted thalli from the oligotrophic
lichen Ramalina menziesii from relatively unpolluted sites into fumigation chambers
under moderate and high HNO3 concentrations (19.9-25 (ig/m3 and 26.4-35.3 (ig/m3,
respectively). The HNO3 fumigation caused significant declines in chlorophyll content
and C exchange capacity compared to thalli in control chambers. This research was later
expanded to six species known to vary in sensitivity to N pollution (Riddel 1 et al.. 2012).
Fumigation with HNO3 (daily peaks near 50 ppb) decreased chlorophyll content,
chlorophyll fluorescence, gross photosynthesis, dark respiration, in three of the five N
sensitive species; while only photosynthesis declined in the other two N sensitive species.
Four of the N sensitive species were tested for fumigation effects on cell membrane ion
leakage; overall ion leakage, and specifically K+ ion leakage, were both increased by
HNO3 fumigation in all species.
Johansson and colleagues conducted a series of experiments in Sweden intended to
understand the physiological responses of epiphytic lichens to added N (Johansson et al..
2012; Johansson et al.. 2011; Johansson et al.. 2010). In a whole-tree N addition
experiment in a spruce forest in boreal Sweden, low rates of N addition (6,
12.5 kg N/ha/yr for 3 years) increased total lichen abundance, but higher N addition rates
(25, 50 kg N/ha/yr) decreased total lichen abundance (Johansson et al.. 2012V However,
within the lichen community there was considerable variation among species in the N
addition treatment rate that resulted in optimal growth. For two of the lichen species in
that experiment, Alectoria sarmentosa and Platismatia glauca, Johansson et al. (2010)
quantified physiological responses to N additions. Thalli N concentrations increased in
both species at the two highest N addition rates (25, 50 kg N/ha/yr) and there was a
significant positive relationship between cumulative N dose and chlorophyll content, but
the N additions did not affect thalli phosphorus concentrations. In a separate experiment
with a single much higher N addition rate (300 kg N/ha/yr for one season), Johansson et
al. (2011) examined the physiological and growth responses of three lichen species. All
three lichen species exhibited increased tissue N concentrations, increased chlorophyll
concentrations, increased photosynthesis, and increased growth of the photobiont.
However, mycobiont growth decreased in two species and was unchanged in the third
and total biomass changes among the three species were positive, neutral, and negative.
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In another experiment in Scandinavia, lichens collected from Sweden and Norway were
exposed to added N (50 kg N/ha/yr for one season) in order to understand whether this
altered concentrations of the C based secondary compounds (CBSCs) thought to protect
lichens from herbivores and whether this affected feeding preferences of gastropod
herbivores (Asplund et al.. 2010; Nvbakken et al.. 2009). The N additions decreased the
concentrations of CBSCs in one species, but had no effect on the other three lichen
species (Nvbakken et al.. 2009). For three of the four species, the gastropod herbivores
preferred to feed on lichens from control treatment, but the thalli from the N addition
treatment were preferred as food for the fourth lichen species (Asplund et al.. 2010).
Notably, the species exhibiting the decrease in CBSCs was not the species that was more
preferable to herbivores in the N addition treatment. Together, these results suggest that
N deposition may alter lichen community composition by shifting herbivore feeding
preferences.
Table 6-5
Growth and physiology responses of forest epiphytic lichens to
nitrogen added via atmospheric deposition or experimental
treatments.
Reference
Study
Location
Vegetation
Ambient
Deposition
or
Addition
Nitrogen
Addition
Rate (kg
N/ha/yr)
Duration
(yr)
Endpoint
Effect of
Additional
Nitrogen
Johansson et al.
(2012)
Sweden
Norway
spruce
(Picea
abies)
Addition
6, 12.5, 25,
50
4
Lichen
abundance
Six and
12.5
doses:
Increase;
25 and 50
doses:
decrease
Will-Wolf et al.
(2015)
Northeastern
U.S.
Forests
Ambient
Not stated
n/a
Lichen
abundance
Decrease
Strenabom and
Nordin (2008)
Sweden
Boreal
forest
Addition
150 (twice)
Additions
22 and
30 yr
prior to
surveys
Lichen
abundance
Decrease
February 2017
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Table 6-5 (Continued): Growth and physiology responses of forest epiphytic
lichens to nitrogen added via atmospheric deposition or
experimental treatments.
Ambient
Nitrogen
Deposition
Addition
Effect of
Study
or
Rate (kg
Duration
Additional
Reference
Location
Vegetation Addition
N/ha/yr)
(yr)
Endpoint Nitrogen
Johansson et al. Sweden Boreal Addition 300 1 Thallus growth One
(2011) forest species:
increase;
one
species:
not
significant;
one
species:
decrease
Thallus growth Three
species:
increase;
one
species:
not
significant
Johansson et al.
(2011)
Sweden
Boreal
forest
Addition
300
1
Photobiont
growth
Increase
Johansson et al.
(2011)
Sweden
Boreal
forest
Addition
300
1
Mycobiont
growth
One
species:
decrease;
two
species:
not
significant
Riddell et al.
(2008)
California
(Los Angeles
Basin)
Oak forests
(Quercus
douglasii)
HNO3 gas
fumigation
0, 15, 30
mg/m3
0.08
Photosynthesis
Decrease
Johansson et al.
(2011)
Sweden
Boreal
forest
Addition
300
1
Photosynthesis
Increase
Riddell et al.
(2008)
California
(Los Angeles
Basin)
Oak forests
(Quercus
douglasii)
HNO3 gas
fumigation
0, 15, 30
mg/m3
0.08
Respiration
Decrease
Johansson et al.
(2011)
Sweden
Boreal
forest
Addition
300
1
Chlorophyll
content
Increase
Johansson et al.
(2010)
Sweden
Norway
spruce
(Picea
abies)
Addition
6, 12.5, 25,
50
3
Chlorophyll
content
Increase
Nvbakken et al. Sweden and Boreal Addition 50
(2009) Norway forest
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Table 6-5 (Continued): Growth and physiology responses of forest epiphytic
lichens to nitrogen added via atmospheric deposition or
experimental treatments.
Reference
Study
Location
Vegetation
Ambient
Deposition
or
Addition
Nitrogen
Addition
Rate (kg
N/ha/yr)
Duration
(yr)
Endpoint
Effect of
Additional
Nitrogen
Nvbakken et al.
(2009)
Sweden and
Norway
Boreal
forest
Addition
50
1
Chlorophyll
content
Three
species:
increase;
one
species:
not
significant
Riddell et al.
(2008)
California
(Los Angeles
basin)
Oak forests
(Quercus
douglasii)
HNO3 gas
fumigation
0, 15, 30
mg/m3
0.08
Chlorophyll
content
Decrease
Root et al. (2013)
Western
North
America
Forests
Ambient
0.1-39.3
n/a
Thalli N %
Increase
McMurrav et al.
(2013)
Wyoming
Conifer
forests
Ambient
0.8-4.1
n/a
Thalli N %
Increase
McMurrav et al.
(2015)
Idaho,
Wyoming,
Montana
Conifer
forests
Ambient
0.5-4.3
n/a
Thalli N %
Increase
Boltersdorf et al.
(2014)
Germany
Forests
Ambient
2.2-9.5
n/a
Thalli N %
Increase
Schirokauer et al.
(2014a)
Alaska
(southeast)
Conifer
forests
Ambient
0.05-1.05
n/a
Thalli N %
Increase
Johansson et al.
(2010)
Sweden
Norway
spruce
(Picea
abies)
Addition
6, 12.5, 25,
50
3
Thalli N %
Six and
12.5
doses: not
significant;
25 and 50
doses:
increase
Johansson et al.
(2011)
Sweden
Boreal
forest
Addition
300
1
Thalli N %
Increase
Johansson et al.
(2011)
Sweden
Boreal
forest
Addition
300
1
Thalli P %
Two
species:
increase;
one
species:
not
significant
Johansson et al.
(2010)
Sweden
Norway
spruce
(Picea
abies)
Addition
6, 12.5, 25,
50
3
Thalli P %
Not
significant
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Table 6-5 (Continued): Growth and physiology responses of forest epiphytic
lichens to nitrogen added via atmospheric deposition or
experimental treatments.
Ambient
Nitrogen
Deposition
Addition
Effect of
Study
or
Rate (kg
Duration
Additional
Reference
Location
Vegetation
Addition
N/ha/yr)
(yr)
Endpoint
Nitrogen
Riddell et al.
California
Oak forests
HNO3 gas
0, 15, 30
0.08
Membrane ion
Increase
(2008)
(Los Angeles
(Quercus
fumigation
mg/m3
leakage
Basin)
douglasii)
Nvbakken et al.
Sweden and
Boreal
Addition
50
1
C-based
Three
(2009)
Norway
forests
secondary
species:
compounds
not
significant;
one
species:
decrease
Asplund et al.
Sweden and
Boreal
Addition
50
1
Gastropod
Three of
(2010)
Norway
forests
feeding
four lichen
preference
species:
decrease;
one
species:
increase
C = carbon; ha = hectare; HN03 = nitric acid; kg = kilogram; m = meter; mg = milligram; N = nitrogen; n/a = not applicable;
P = phosphorus; yr = year.
Note: Single studies are reported more than once if multiple endpoints are measured. Only statistically significant effects are listed
as increases or decreases.
6.1.3.4 Net Ecosystem Production and Carbon Sequestration Response
The 2008 ISA concluded that N deposited onto terrestrial ecosystems increased net
primary productivity (NPP) and ecosystem C storage (kg C/ha). However, the extent to
which this additional N stimulates forest C sequestration was atopic of debate [e.g., (De
Schriiver et al.. 2008; de Vries et al.. 2008; Sutton et al.. 2008; Magnani et al.. 2007;
Nadclhoffcr et al.. 1999b) I. Magnani et al. (2007) correlated net ecosystem production
(NEP; kg C/ha/yr) with estimated rates of N deposition for 20 forested sites in North
America and Europe, which resulted in an estimate of 725 kg C sequestered per kg of
added N (i.e., kg C/kg N). However, this estimate was widely criticized and a reanalysis
of these data produced an estimate of C sequestration more than an order of magnitude
lower [68 kg C/kg N; (Sutton et al.. 2008)1. Since the 2008 ISA, there have been several
new syntheses and a number of field experiments and modeling studies that have
provided further evidence that N deposition increases NPP, NEP, and ecosystem C
content and more tightly constrained estimates of the response of plant, soil, and
ecosystem C content to N deposition.
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Nave et al. (2009b) estimated that up to 15% of the N needed to support NPP in a
northern Michigan aspen forest was supplied by atmospheric N deposition. In China, N
additions of 20, 50, or 100 kg N/ha/yr to an old growth boreal forest stimulated
aboveground tree productivity by 5, 7, and 23% during the 2nd and 3rd years of the
experiment (Du and Fang. 2014). Chen etal. (2011) found that a Douglas-fir stand in the
Pacific Northwest increased NEP by 2,500 kg/ha (+83%) in the 1st year after receiving
200 kg N/ha of urea, both from decreased respiration (930 kg/ha) and increased gross
primary production (157 kg/ha). Increases in ecosystem C content have been noted in
long-term N addition experiments in Massachusetts (Frev et al.. 2014). Michigan
(Pregitzer et al. 2008). and New York (Lovett et al.. 2013). Using a process model that
neglected changes in stand ontogeny, disturbances, and shifts in forest management, de
Vries and Posch (2011) concluded that N deposition was a dominant determinant of
European forest productivity throughout the 20th century. Since the 2008 ISA, a variety
of techniques have been used to quantify the C sequestration response of forests to N
deposition, particularly in Europe (Frev et al.. 2014). Using a 15N-labeling technique,
Gundale et al. (2014) observed a linear relationship between C sequestration and N
additions of up to 50 kg N/ha/yr that had a slope of 16 kg C/kg N in a Swedish boreal
forest. Hyvonen et al. (2008) synthesized soil and plant C sequestration data from
15 long-term (14-30 year) N addition experiments in boreal (Picea abies, Pinus
sylvestris) forests in Sweden and Finland and estimated that C sequestration averaged
23 kg C/kg N for Picea and 30 kg C/kg N for Pinus, with an additional 11 kg C/kg N
within the soil. Also in Sweden, Eliasson and Agren (2011) applied an ecosystem model
to Scots pine (Pinus sylvestris) forests and estimated that ecosystem C stocks increased
by 24,123 kg/ha in response to a cumulative 224 kg N/ha added over a century
(108 kg C/kg N). Based on the stimulation of photosynthesis and assumptions about the
fraction of photosynthate that is ultimately transformed into tree biomass, Fleischer et al.
(2013) estimated that N deposition stimulates C sequestration by 25 kg C/kg N.
Forest inventory studies typically make use of one or more decades of tree growth data
from national or continental monitoring networks and relate the variation in this growth
to differences in N deposition and other environmental factors. Across western and
northern Europe, Solberg et al. (2009) found that variation in tree volume increment was
positively related to N deposition and summer temperature, particularly for pine {Pinus)
and spruce {Picea), with similar, but weaker, relationships for beech {Fagus) and oak
{Quercus). The overall model estimated C sequestration was 19 kg C/kg N. Eastaugh et
al. (2011) analyzed Norway spruce {Picea abies) growth data from the Austrian National
Forest Inventory and estimated thatN deposition sequestered 21.6 kg C/kg N in
aboveground tree biomass during the latter half of the 21st century. Etzold et al. (2014)
and Ferretti et al. (2014) took similar approaches with 18 inventory plots in Switzerland
and 25 inventory plots in Italy, respectively. Both studies found a positive relationship
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between N deposition and NPP, but were unable to isolate NPP effects from other
environmental factors. Within the U.S., the analysis of forest inventory data in the
northeastern U.S. by Thomas et al. (2010) estimated that N deposition increased
aboveground tree biomass at 61 kg C/kg N; a rough estimate including belowground C
increased this to 73:1. Pinder et al. (2012) modified the estimates of Thomas et al. (2010).
using alternate values for N deposition, more complex belowground biomass estimates,
and changes in soil C pools, producing an enhancement of 65 kg C/kg N. A critique of
the inventory and modeling studies is that they match variation in growth only to current
levels of N deposition, neglecting the contribution of N deposition in previous to N cycle
at that site. Thus, the influence of current N deposition may be exaggerated (Hogberg.
2012).
In the long-term N addition experiment at Harvard Forest (Frev et al.. 2014). the C
response to N deposition ranged from -2 to 30 kg C/kg N among the four treatment types
(50 or 150 kg N/ha/yr; Pinus or Quercus forests). Notably, the amount of C sequestered
in the soil was equal to or greater than the amount of C sequestered in trees. Similar
results showing more C sequestration in the soil than in trees were found in N addition
experiments at four Michigan forests (23 kg C/kg N soil vs. 17 kg C/kg N tree; (Pregitzer
et al.. 2008) and in the Catskills (Lovett et al.. 2013). Several syntheses of forest C
sequestration changes in response to N deposition have been conducted (Frev et al.. 2014;
Pinder et al.. 2013; Pinder et al.. 2012; Butterbach-Bahl et al.. 2011; Janssens et al.. 2010;
Liu and Greaver. 2009). producing estimates of 12-41 kg C/kg N. Often these synthesis
studies are meta-analyses; however, de Vries et al. (2014a) took a novel approach of
combining estimates of ecosystem N retention with N allocation and C:N ratios to
develop stoichiometric estimates of N deposition for tropical, temperate, and boreal
ecosystems. Although this approach involves a number of important assumptions about
biogeochemistry and tree physiology, estimates for tree and soil C sequestration response
rates were similar to values from other syntheses (Figure 6-3).
Variation in these estimates is likely influenced by the research approach. For instance,
the model used by Eliasson and Agren (2011) predicted almost no N losses from the
forests due to leaching or denitrification, which are both widely reported at high rates of
N deposition. However, environmental and ontological factors also appear to influence
the sensitivity of forest C sequestration to N deposition. Using the G'DAY model, Dezi et
al. (2010) found recent forest harvests, shifts in plant C allocation away from roots, and
canopy N uptake all increased the C sequestration response to N deposition. Among the
15 experiments synthesized by Hwonen et al. (2008). the amount of C sequestered
ranged from -0.8 to 61 kg C/kg N, with greater increases in kg C/kg N at lower N doses.
The amount of additional tree C sequestered was small in plots that had low soil
O-horizon C:N ratios (near 25) and the amount of C sequestered by added N increased
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1 with O-horizon C:N until C:N reached 35. Among Picea forests, young stands were more
2 responsive than old stands, but no such effect was apparent for Pinus. In addition, C
3 sequestration increased more in plots simultaneously supplied with potassium and
4 phosphorus (Hwonen et al.. 2008). Janssens ct al. (2010 acknowledged the role of stand
5 age in altering the dynamic of C cycling, explicitly removing young, rapidly expanding
6 forests from some portions of the meta-analysis.
Aboveground
<9
orest Biomass
dO o
Modeling
00 o
1 oaO o o o
«Ox>
inventory
Experimental
i
%
Wamalink at al. 2009b
f lent her etal. 2013
oeVneiet >1.2006
Thomas ct al. 2010
UfUut»etaL2011
Solberg et >1.2009
laubhannetal. 2009
H*d«lhoffcret»l. 1999
HoctKfjctJJ, 2006
Hyvonen et al. 2008
Prefitieret *1-2006
Lovett at al. 2013
Frey et al. 2014
GundaJeetal. 2014
Fw»»r »t *1.2015
•O
*
Synthesis
30
50
Ecosystem Cart
Response Ratio (kg C kg"1 N)
a>0 o
¦—o—
Modeling
Butt»(b*h-8»hl at it. 2011
da Vrin at *1. 2014
daVneietal. 2014
da VfMM at *1.2014
levy et at. 2004
Sutton «ai. 2008
Sutton et »i. 2008[one titej
Wamelink et al. 2009b
Warns link at al. 2009a
Elusion ft Agren 2011
Inventory
de Vrin at a(. 2006
Sutton et a). 2008 [Mapvani
) oO
o
o
Opt
o O <
""i~
o
oo Q> o
O O
O 0
0 _ o
o
o o
Experimental
-L-
Synthesir-
Nad*lhcflarat»1.19W
Hojbefj et al. 2006
Hyvonen et al. 2008
Pragitser at al. 2006
lovatt atal. 2013
Frey etaL 2014
Gundaile etai.2014
fowler et al. 2015
Liu & Graavar 2009
Buttert»ch^ahl et al. 2011
de Vrieset al. 21X14
d« Vnei et aL 2014
dm Vriai at aL 2014
-30 0 30 60 90
Response Ratio (kg C kg'1 N)
C = carbon; kg = kilogram; N = nitrogen.
Notes: Studies grouped by research approaches, including process modeling, forest inventory analyses, long-term N addition
experiments, or data syntheses. The citations to the right represent studies that quantified at least one of three aspects of forest C
sequestration responses to N (forest biomass, soil C, or ecosystem C). Studies that quantified (A) forest biomass and (B) ecosystem
carbon are shown in black text; N deposition C sequestration studies that quantified other C pools are shown in grey. The large
orange circles represent the mean response for each study and the smaller blue circles represent individual estimates (replicate
plots, study sites, or model simulations). The colored boxes bound the range of mean responses.
Source: Adapted from Frev et al. (2014).
Figure 6-3 Studies reporting the response of forest (A) aboveground
biomass carbon sequestration and (B) ecosystem carbon
sequestration to nitrogen deposition or long-term nitrogen
additions.
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6.1.4
Arctic and Alpine Tundra and Grasslands
Tundra areas in the U.S. are concentrated in high-elevation alpine areas in the western
U.S. and high-latitude areas in Alaska. The western U.S. contains extensive land areas
that receive low levels of atmospheric N deposition, interspersed with hot spots of
relatively higher N deposition downwind of large metropolitan centers and agricultural
areas (Fenn et al.. 2003b'). Alpine tundra ecosystems occur in some of the western areas
that receive elevated atmospheric N deposition, such as those located in the central and
southern portions of the Sierra Nevada in California, the Front Range in Colorado, the
Wasatch Mountains in Utah, and the Cascade Mountains in Washington. Although alpine
ecosystems are limited in their spatial extent, these ecosystems are important components
of many national parks (e.g., Rocky Mountain, Yosemite, Sequoia-Kings Canyon, Mount
Rainier) and other Class I areas within these regions. Further, alpine tundra ecosystems
are significant as headwaters for aquatic systems and as unique sites for biodiversity.
Nitrogen deposition rates in Arctic tundra areas are generally low, but there is a distinct
impact of anthropogenic pollution on N cycling that could increase with further industrial
development at high latitudes (Holtgrieve et al.. 201IV
For Arctic tundra ecosystems, the 2008 ISA identified a single N addition experiment and
cited two studies from the 1980s on the effects of decreased N availability. The two
studies on plants grown under conditions of low N availability found that tundra plants
responded by increasing root growth (Bloom et al.. 1985) or increasing N use efficiency
(Chapin. 1980V The N addition (50 or 100 kg/ha/yr) experiment began in 1981 and
caused changes in plant community composition (Shaver et al.. 2001). increases in
aboveground plant growth, but losses in soil C pools that resulted in decreased ecosystem
C content (Mack et al.. 2004).
The 2008 ISA reported that alpine plant species are often sensitive to N enrichment
because many are adapted to low nutrient availability (Bowman et al.. 2006) and that N
deposition may increase alpine plant productivity and alter plant community composition
(Neff et al.. 2002; Seastedt and Vaccaro. 2001; Bowman et al.. 1995). Some alpine plants
in the southern Rocky Mountains exhibit greater growth in response to increased N, but
this species-specific growth response to N deposition is one of the mechanisms that
results in changes in community composition (Bowman et al.. 1993). Many of the
dominant plant species do not respond to additional N supply with increased production.
Rather, many subdominant species increase in abundance when the N supply is increased
(Fenn et al.. 2003a). The 2008 ISA also noted that the effects of N deposition can be
spatially heterogeneous in alpine tundra ecosystems, with areas that accumulate
wind-blown snow receiving higher rates of winter N deposition (Bowman and Steltzer.
1998). Further, the 2008 ISA also cited evidence that chronic N additions to alpine
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ecosystems can accelerate the decomposition of some soil C fractions, while preserving
other C fractions (Neff et al. 2002).
Research since 2008 on the effects of added N on alpine and Arctic ecosystems has
included broad syntheses, a number of experiments in both Europe and Asia, and
additional research in North America. Bouskill et al. (2014) conducted a meta-analysis of
high-latitude N addition experiments and compared these results with model simulations
from the Community Land Model (CLM), the land component of the Community ESM
(CESM). Bouskill et al. (2014) identified 37 N addition field experiments from 14 sites in
North America and Europe. In this synthesis, N additions significantly stimulated gross
primary production (GPP; +44 ± 7%, mean ± standard error), while soil respiration
declined by 12 ± 7%. Total aboveground plant biomass was not significantly affected by
N additions (increase of 15 ± 22%), but vascular plant biomass increased by 33 ± 8%.
Notably, the modeled responses produced from CLM matched observations only for two
parameters: soil organic matter and GPP and only under the lowest rates of N addition
(<1 kg/ha/yr), suggesting that N cycling processes or parameters are not well
characterized in tundra ecosystems.
Three multiyear experiments span the period before and after the 2008 ISA was
published (Table 6-6). In a subalpine shrub heathland in Scotland, Britton and Fisher
(2007) examined the effects on plant communities of burning, clipping, and N additions
of 0, 10, 20, or 50 kg N/ha/yr as NH4NO3 for 5 years. Since the 2008 ISA was published,
Britton et al. (2008) observed that N additions increased shoot N concentration in the
dominant shrub Calluna vulgaris, with significant increases only at the two highest levels
of N addition. In assessing plant growth, Britton and Fisher (2008) found increased
growth of the dominant alpine shrub Calluna vulgaris and increased growth of Vaccinium
vitis-idaea with N additions of 20 and 50 kg N/ha/yr, but no effect of 10 kg N/ha/yr and
no effect of N at any level on three other shrub species. In a second study within
Scotland, Britton and Fisher (2010) found that N additions of 7.5. 12.5. and
22.5 kg N/ha/yr increased thallus N concentration three of four alpine lichen species, but
decreased growth of two species and did not significantly affect growth in three other
species.
February 2017
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Table 6-6 Alpine and Arctic tundra plant producitivity and physiology
responses to nitrogen added via atmospheric deposition or
experimental treatments.
Nitrogen
Ambient
Addition
Effect of
Study
Deposition
Rate (kg
Duration
Additional
Reference
Location
Vegetation
or Addition
N/ha/yr)
(yr)
Endpoint
Nitrogen
Bouskill et al.
North
Arctic and
Addition
Average:
Meta-
Gross
Increase
(2014)
America and
high latitude
72 range:
analysis
primary
Europe
1-100
productivity
Bouskill et al.
North
Arctic and
Addition
Average:
Meta-
Above-
Not significant
(2014)
America and
high latitude
72
analysis
ground
Europe
range:
plant
1-100
biomass
Bouskill et al.
North
Arctic and
Addition
Average:
Meta-
Above-
Increase
(2014)
America and
high latitude
72
analysis
ground
Europe
range:
plant
1-100
biomass
(vascular)
Arens et al.
Greenland
Dwarf-
Addition
5, 10, 50
3
NEE
Low dose: not
(2008)
shrub/herb
significant;
tundra (Salix
mid and hiah
arctica, Carex
dose:
rupestris,
decrease
Dryas
integrifolia)
Volketal. (2011)
Switzerland
Subalpine
Addition
10, 50
4
Net
Low dose: not
grassland
ecosystem
significant;
(Nardis
production
hiah dose:
stricta, Carex
decrease
semper-
virens,
Festuca spp.)
Arens et al.
Greenland
Dwarf-
Addition
5, 10, 50
3
Gross
Increase
(2008)
shrub/herb
ecosystem
tundra (Salix
production
arctica, Carex
rupestris,
Dryas
integrifolia)
Volketal. (2011)
Switzerland
Subalpine
Addition
10, 50
4
Gross
Not significant
grassland
primary
(Nardis
production
stricta, Carex
semper-
virens,
Festuca spp.)
February 2017
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Table 6-6 (Continued): Alpine and Arctic tundra plant producitivity and
physiology responses to nitrogen added via atmospheric
deposition or experimental treatments.
Nitrogen
Ambient Addition Effect of
Study Deposition Rate (kg Duration Additional
Reference Location Vegetation or Addition N/ha/yr) (yr) Endpoint Nitrogen
Arens et al. Greenland Dwarf- Addition 5,10,50 3 Ecosystem Increase
(2008) shrub/herb respiration
tundra (Salix
arctica, Carex
rupestris,
Dryas
integrifolia)
Volk et al. (2011) Switzerland Subalpine Addition 10,50 4 Ecosystem Not significant
grassland respiration
(Nardis
stricta, Carex
semper-
virens,
Festuca spp.)
Arens et al.
(2008)
Greenland
Dwarf-
shrub/herb
tundra (Salix
arctica, Carex
rupestris,
Dryas
integrifolia)
Addition
5, 10, 50
Below-
ground
respiration
Low and high
dose: not
significant;
mid dose:
increase
Farrer et al.
(2015)
Colorado
(Niwot
Ridge)
Moist alpine
meadow
(Deschamp-
sia cespitosa,
Geum rossii)
Addition
229
Net
primary
productivity
Not significant
Volk et al. (2011) Switzerland
Subalpine
grassland
(Nardis
stricta, Carex
semper-
virens,
Festuca spp.)
Addition
5, 10, 25,
50
Above-
ground
plant
biomass
Low dose: not
significant;
other doses:
increase
Volk et al. (2014) Switzerland Subalpine Addition 5,10,25, 7 Above- Increase
grassland 50 ground
(Nardis plant
stricta, Carex biomass
semper-
virens,
Festuca spp.)
Gill (2014) Utah Subalpine Addition
meadow
(Achnath-
erum
lettermanii,
Artemisia
michauxiana)
70
Above-
ground
plant
biomass
Increase
February 2017
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Table 6-6 (Continued): Alpine and Arctic tundra plant producitivity and
physiology responses to nitrogen added via atmospheric
deposition or experimental treatments.
Nitrogen
Ambient
Addition
Effect of
Study
Deposition
Rate (kg Duration
Additional
Reference
Location
Vegetation
or Addition
N/ha/yr) (yr)
Endpoint
Nitrogen
Sona and Yu
China
Alpine
Addition
3.75, 15, 75 8
Above-
Low and mid
(2015)
(Tibetan
meadow
ground
dose: not
Plateau)
(Kobresia
plant
significant;
humilis,
biomass
hiqh dose:
Elymus
increase
nutans, Stipa
aliena,
Festuca
ovina)
Bowman et al.
Colorado
Dry sedge
Addition
5,10,30 4
Above-
Not significant
(2012)
(Rocky
meadow
ground
Mountain
(Kobresia
plant
National.
myosuroides,
biomass
Park)
Carex
rupestris)
Farrer et al.
Colorado
Moist alpine
Addition
229 7
Above-
Deschampsia:
(2015)
(Niwot
meadow
ground
increase;
Ridge)
(Deschamp-
plant
Geurrr.
sia cespitosa,
biomass
Decrease
Geum rossii)
Zamin et al.
Northwest
Shrub tundra
Addition
10, 100 8
Above-
Low dose: not
(2014)
Territories
(Vaccinium
ground
significant;
(Canada)
vitis-idaea,
plant
hiqh dose:
Rhododen-
biomass
decrease
dron
subarcticum,
Andromeda
polifolia)
Kellev and
Alaska
Tundra
Addition
100 3
Above-
Not significant
Epstein (2009)
meadow
ground
(Dryas
plant
integrifolia,
biomass
Eriophorum
vaginatum,
Carex spp.)
Blanke et al.
Switzerland
Subalpine
Addition
50 3
Above-
Increase
(2012)
grassland
ground
(Festuca
plant
rubra, F.
biomass
Nardus
stricta, Carex
semper-
virens)
February 2017
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Table 6-6 (Continued): Alpine and Arctic tundra plant producitivity and
physiology responses to nitrogen added via atmospheric
deposition or experimental treatments.
Reference
Study
Location
Vegetation
Ambient
Deposition
or Addition
Nitrogen
Addition
Rate (kg
N/ha/yr)
Duration
(yr)
Endpoint
Effect of
Additional
Nitrogen
Blanke et al.
(2012)
Switzerland Subalpine
grassland
(Festuca
violacea,
Leontodon
helveticus,
Carex
semper-
virens,
Trifolium
alpinum)
Addition
50
Above-
ground
plant
biomass
Festuca'.
increase;
Leontodon,
Carex,
Trifoliunr. not
significant
Bassin et al.
(2012)
Switzerland Subalpine
grassland
{Carex
semper-
virens)
Addition
50
Above-
ground
plant
biomass
Increase
Onipchenko et
al. (2012)
Russia
(Caucasus
Mountains)
Lichen heath
(Cetraria
islandica)
Addition
90
Above-
ground
plant
biomass
Increase
Onipchenko et
al. (2012)
Russia Alpine
(Caucasus grassland
Mountains) (Festuca
varia)
Addition
90
Above-
ground
plant
biomass
Not significant
Onipchenko et
al. (2012)
Russia
(Caucasus
Alpine
meadow
Mountains) (Geranium
gymnocau-
lon)
Addition
90
Above-
ground
plant
biomass
Not significant
Onipchenko et
al. (2012)
Russia Alpine
(Caucasus snowbeds
Mountains) (Sibbaldia
procumbens)
Addition
90
Above-
ground
plant
biomass
Not significant
Blanke et al.
(2012)
Switzerland
Subalpine
grassland
(Festuca
rubra, F.
violacea,
Nardus
stricta, Carex
semper-
virens)
Addition
50
Above- Grasses:
ground increase;
plant forbs. sedges.
biomass legumes: not
(functional significant
group)
February 2017
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Table 6-6 (Continued): Alpine and Arctic tundra plant producitivity and
physiology responses to nitrogen added via atmospheric
deposition or experimental treatments.
Reference
Study
Location
Vegetation
Ambient
Deposition
or Addition
Nitrogen
Addition
Rate (kg
N/ha/yr)
Duration
(yr)
Endpoint
Effect of
Additional
Nitrogen
Bassin et al.
(2013)
Switzerland
Subalpine
grassland
(Nardis
stricta, Carex
sempervir-
ens, Arnica
montana,
Gentiana
acaulis)
Addition
5, 10, 25,
50
Above- Sedge, grass:
ground increase;
plant forbs.
biomass legumes: not
(functional significant
group)
Wardle et al.
(2013)
Sweden
Tundra
meadow
(Deschamp-
sia flexuosa,
Empetrum
hermaphrodi-
tum,
Vaccinium
spp.)
Addition
50
21 Vascular Increase
plant cover
Armitage et al.
(2014)
Europe
(North
Atlantic)
Alpine Ambient
heathlands
0.6-39.6
n/a
Plant cover
(functional
group)
Shrubs:
decrease;
forbs: not
significant;
graminoids:
increase
Bishop et al.
(2010)
Washington
(Mt. St.
Helens)
Primary
successional
alpine
meadow
Addition
78
Plant cover Forbs:
(functional
group)
increase;
graminoids:
not significant;
legumes:
decrease
Bishop et al.
(2010)
Washington
(Mt. St.
Helens)
Primary
successional
alpine
meadow
Addition
78
Plant cover Increase
Wardle et al.
(2013)
Sweden
Tundra
meadow
(Deschamp-
sia flexuosa,
Empetrum
hermaphrodi-
tum,
Vaccinium
spp.)
Addition
50
21 Bryophyte Decrease
cover
February 2017
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Table 6-6 (Continued): Alpine and Arctic tundra plant producitivity and
physiology responses to nitrogen added via atmospheric
deposition or experimental treatments.
Nitrogen
Ambient
Addition
Effect of
Study
Deposition
Rate (kg
Duration
Additional
Reference
Location
Vegetation
or Addition
N/ha/yr)
(yr)
Endpoint
Nitrogen
Armitaae et al.
U.K.
Bryophyte
Ambient
Reciprocal
2
Bryophyte
Decrease
(2011)
heathlands
transplant
biomass
(Ranicomi-
(7.2 with
(R.
trium
8.2-32.9)
Ianugino-
lanuginose-
sum)
um)
Armitaae et al.
Europe
Alpine
Ambient
0.6-39.6
n/a
Bryophyte
Decrease
(2012)
(North
heathlands
cover(R.
Atlantic)
(Rani com it-
Ianugino-
rium
sum)
lanuginose-
um)
Armitaae et al.
U.K.
Bryophyte
Ambient
Reciprocal
2
Bryophyte
Increase
(2011)
heathlands
transplant
growth (R.
(Rani com it-
(7.2 with
Ianugino-
rium
8.2-32.9)
sum)
lanuginose-
um)
Armitaae et al.
Europe
Alpine
Ambient
0.6-39.6
n/a
Bryophyte
Increase
(2012)
(North
heathlands
growth (R.
Atlantic)
(Rani com it-
Ianugino-
rium
sum)
ianuginosum)
Britton and
Scotland
Shrub
Addition
10, 20, 50
5
Shoot
Low dose: not
Fisher (2008)
heathland
growth
significant;
(Caiiuna
(Caiiuna
mid and hiah
vulgaris)
vulgaris)
dose: increase
Britton and
Scotland
Shrub
Addition
10, 20, 50
5
Shoot
Low dose: not
Fisher (2008)
heathland
growth
significant;
(Caiiuna
(Vaccinium
mid and hiah
vulgaris)
vitis-idaea)
dose: increase
Britton and
Scotland
Shrub
Addition
10, 20, 50
5
Shoot
Not significant
Fisher (2008)
heathland
growth
(Caiiuna
(Empetrum
vulgaris)
hermaph-
roditum,
Arctosta-
phylos
uvaursi,
Vaccinium
myrtillus)
February 2017
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Table 6-6 (Continued): Alpine and Arctic tundra plant producitivity and
physiology responses to nitrogen added via atmospheric
deposition or experimental treatments.
Nitrogen
Ambient
Addition
Effect of
Study
Deposition
Rate (kg
Duration
Additional
Reference
Location
Vegetation
or Addition
N/ha/yr)
(yr) Endpoint
Nitrogen
Zamin and
Northwest
Shrub tundra
Addition
10, 100
7 Above-
Low dose: not
Groaan (2012)
Territories
(Betula
ground
significant;
(Canada)
glandulosa,
plant
hiah dose:
Vaccinium
growth
increase
vitis-idaea,
(Betula)
Rhododen-
dron
subarcticum)
Blanke et al. Switzerland Subalpine Addition
(2012) grassland
(Festuca
violacea,
Leontodon
helveticus,
Carex
sempervir-
ens, Trifolium
alpinum)
Volk et al. (2014) Switzerland Subalpine Addition
grassland
(Nardis
stricta, Carex
sempervir-
ens, Festuca
spp.)
Zamin and
Groaan (2012)
Northwest
Territories
(Canada)
Shrub tundra
(Betula
glandulosa)
Addition
10, 100
7
Inflore-
scence
production
Not significant
Aerts (2009)
Sweden
Tundra
Addition
75
10
Inflore-
Decrease
meadow
scence
(Betula nana)
production
Aerts (2009)
Sweden
Tundra
meadow
(Empetrum
hermaphrod-
itum,
Andromeda
polifolia,
Betula nana,
Eriophorum
vaginatum)
Addition
75
10
Leaf
production
Andromeda'.
increase;
other three
species: not
significant
50
Below-
ground
plant
biomass
Festuca:
increase;
Leontodorr.
decrease;
Carex.
Trifoliunr. not
significant
10, 50 7 Below- Increase
ground
plant
biomass
February 2017
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Table 6-6 (Continued): Alpine and Arctic tundra plant producitivity and
physiology responses to nitrogen added via atmospheric
deposition or experimental treatments.
Reference
Study
Location
Vegetation
Ambient
Deposition
or Addition
Nitrogen
Addition
Rate (kg
N/ha/yr)
Duration
(yr)
Endpoint
Effect of
Additional
Nitrogen
Aerts (2009)
Sweden
Tundra
meadow
(Empetrum
hermaphrodi-
tum,
Andromeda
polifolia,
Eriophorum
vaginatum)
Addition
75
10
Leaf
survival
Andromeda
and
Eriophorum'.
decrease;
Empetrum'.
not significant
Farrer et al.
(2013)
Colorado
(Niwot
Ridge)
Moist alpine
meadow
(Geum rossii)
Addition
288
11
Plant
nonstruct-
ural carbo-
hydrate
pools
Decrease
Bassin et al.
(2009)
Switzerland
Subalpine
grassland
(Festuca
rubra, Nardus
stricta, Carex
semper-
virens)
Addition
50
Specific
leaf area
One species:
increase;
two species:
decrease;
eight species:
not significant
Bassin et al.
(2009)
Switzerland
Subalpine
grassland
(Festuca
rubra, Nardus
stricta, Carex
semper-
virens)
Addition
50
Leaf mass Three
(per leaf) species:
increase;
seven
species: not
significant
Bassin et al.
(2012)
Switzerland Subalpine
grassland
(Carex
semper-
virens)
Addition
50
Leaf length
(C.
semper-
virens)
Increase
Bassin et al.
(2009)
Switzerland
Subalpine
grassland
(Festuca
rubra, Nardus
stricta, Carex
semper-
virens)
Addition
50
Leaf Nine species:
chlorophyll increase;
concentra- one species:
tion not significant
Southon et al.
(2013)
U.K.
Heathlands
(Caiiuna
vulgaris)
Ambient
5.9-32.4
n/a
Foliar N %
(Caiiuna
vulgaris)
Not significant
February 2017
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Table 6-6 (Continued): Alpine and Arctic tundra plant producitivity and
physiology responses to nitrogen added via atmospheric
deposition or experimental treatments.
Nitrogen
Ambient Addition Effect of
Study Deposition Rate (kg Duration Additional
Reference Location Vegetation or Addition N/ha/yr) (yr) Endpoint Nitrogen
Britton et al. Scotland Shrub Addition
(2008) heathland
(Calluna
vulgaris)
10,20,50 5 Foliar N% Low dose: not
(Calluna significant;
vulgaris) mid and high
dose: increase
Kellev and Alaska Tundra Addition 100 3 Foliar N % Increase
Epstein (2009) meadow
(Dryas
integrifolia,
Eriophorum
vaginatum,
Carex spp.)
Bowman et al.
Colorado
Dry Sedge
Addition
5,10,30 4
Foliar N %
Not significant
(2012)
(Rocky
meadow
Mountain
(Kobresia
National
myosuroides,
Park)
Carex
rupestris)
Churchland et al.
Northwest
Shrub tundra
Addition
100 1
Plant
Increase
(2010)
Territories
(Betula
tissue N %
(Canada)
glandulosa,
Vaccinium
vitis-idaea,
Rhododen-
dron
subarcticum)
Bishop et al.
Washington
Primary
Addition
78 4
Foliar N %
Aarostis\
(2010)
(Mount. St.
successional
increase;
Helens)
alpine
Lupinus'.
meadow
decrease
(Agrostis
pallens,
Lupinus
lepidus)
Blanke et al.
Switzerland
Subalpine
Addition
50 3
Foliar N %
Grasses:
(2012)
grassland
(functional
increase;
(Festuca
group)
forbs. sedaes:
rubra, F.
not significant
violacea,
Nardus
stricta, Carex
semper-
virens)
February 2017
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Table 6-6 (Continued): Alpine and Arctic tundra plant producitivity and
physiology responses to nitrogen added via atmospheric
deposition or experimental treatments.
Nitrogen
Ambient
Addition
Effect of
Study
Deposition
Rate (kg
Duration
Additional
Reference
Location
Vegetation
or Addition
N/ha/yr)
(yr)
Endpoint
Nitrogen
Bassin et al.
Switzerland
Subalpine
Addition
50
3
Foliar N %
Six species:
(2009)
grassland
increase;
(Festuca
two species:
rubra, Nardus
not significant;
stricta, Carex
semper-
virens)
Bassin et al.
Switzerland
Subalpine
Addition
50
2
Foliar N %
Increase
(2012)
grassland
(C.
(Carex
semper-
semper-
virens)
virens)
Armitaae et al.
U.K.
Bryophyte
Ambient
Reciprocal
2
Bryophyte
Increase
(2011)
heathlands
transplant
tissue N %
(Rani com i-
(7.2 with
(R.
trium
8.2-32.9)
lanugino-
lanuginosum)
sum)
Armitaae et al.
Europe
Alpine
Ambient
0.6-39.6
n/a
Bryophyte
Increase
(2012)
(North
heathlands
tissue N %
Atlantic)
(Ranicomi-
(R.
trium
lanugino-
lanuginosum)
sum)
Armitaae et al.
Europe
Alpine
Ambient
0.6-39.6
n/a
Bryophyte
Increase
(2012)
(North
heathlands
tissue P %
Atlantic)
(Ranicomi-
(R.
trium
lanugino-
lanuginosum)
sum)
ha = hectare; kg = kilogram; N = nitrogen; n/a = not applicable; NEE = net ecosystem exchange; yr = year.
Note: Single studies are reported more than once if multiple endpoints or ecosystems are measured. Only statistically significant
effects are listed as increases or decreases.
1 In subalpine tundra in Sweden, a long-term experiment was started in 1989 in order to
2 understand how alleviating nutrient limitations altered ecological processes, including
3 productivity, decomposition, and the development of plant communities (Wardle et al..
4 2013; Nilsson et al.. 2002). The experimental design includes six treatments, including
5 additions of NOs and NH4NO3 at rates of 50 kg N/ha/yr. After the first 9 years, there
6 were negative effects of both NO3 and NH4NO3 on the percent cover of the dominant
7 ericaceous shrub Empetrum hermaphroditum, but increased cover of two ericaceous
8 Vaccinium shrub species (Nilsson et al.. 2002). An even stronger positive response was
9 exhibited by the bunchgrass Deschampsia flexuosa, which became the dominant plant in
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plots receiving N additions. The N additions also had varying effects on the cover of the
dominant bryophyte species: Dicranum spp. decreased in cover in response to added N
and Pleurozium schreberi disappeared entirely from some N addition plots, while Polia
spp., Bryum spp. and Barbilophozia lycopodioides were not significantly affected by N
additions. The dominant lichen, Cladina spp., decreased in response to added N (Nilsson
et al.. 2002). The N addition treatments did not impact vascular plant diversity, but moss
species richness was decreased by NH4NO3 and lichen species richness was decreased by
NC>3~. Decomposition of pine needles in litterbags was followed for 4 years, but no
significant effects of the N addition treatments were observed (Nilsson et al.. 2002). In
2010, Wardle et al. (2013) reassessed the changed in plant cover caused by the N addition
treatments. The N addition treatments increased cover of vascular plants, but decreased
bryophyte cover and lichen cover. Specifically, N additions repeatedly increased cover of
Deschampsia and decreased cover of Empetrum, although these changes were not always
significant. Within the soil microbial community, NH4NO3 additions decreased the
abundance of fungal phospholipid fatty acids (PLFAs; a marker of microbial abundance),
while bacterial PLFAs were increased by NO3 additions. However, NO3 and NH4NO3
each decreased the fungal-to-bacterial PLFA ratio in the soil. Humus mass and C content
were increased by NH4NO3 additions, but not significantly affected by NO3 .
Also spanning the period before and after the 2008 ISA was a 7-year N deposition study
in a subalpine grassland in the Swiss Alps, with rates of N addition of 0, 5, 10, 25, or
50 kg N/ha/yr (as NH4NO3). The initial analysis of the first three years of data found that
N additions increased aboveground plant productivity (Bassin et al.. 2007). Among
functional groups, sedge growth was consistently stimulated, forb growth increased
strongly in the 1st year of the experiment, and grasses and legumes were unresponsive to
N. Species richness was not influenced by the N additions, but N did alter the relative
abundance of the 11 most frequently occurring species. A subsequent analysis of this
experiment (Bassin et al.. 2009) focused on the physiological responses of these
11 species to the 50 kg N/ha/yr treatment. The N addition treatment increased leaf
concentrations ofN and chlorophyll in 9 of the 11 species. Notably, the species
exhibiting the largest growth response (Carex sempervirens) also showed the largest
increase in foliar concentrations of N and chlorophyll. Four years into the experiment,
Yolk et al. (2011) measured changes in ecosystem C fluxes in response to the 10 and
50 kg N/ha/yr treatments. Although aboveground plant growth increased, there were no
significant changes in gross primary productivity or ecosystem respiration. Net
ecosystem production was unaffected by the lower rate of N addition, but declined with
the 50 kg N/ha/yr treatment, which suggests decreases in belowground C pools.
Bassin et al. (2013) and Yolk et al. (2014) reassessed this Swiss Alps grassland N
addition experiment after 7 years when the experiment concluded. Yolk et al. (2014)
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observed that N additions had a strong positive effect on aboveground productivity,
ranging from a 31% stimulation caused by 5 kg N/ha/yr to a 60% increase caused by
50 kg N/ha/yr. Effects on belowground biomass were smaller, ranging from a 19%
increase for the 5 kg N treatment to a 24% increase for the 50 kg N treatment. Thus, N
additions increased the ratio of shoot to root biomass (Yolk et al. 2014). This is
consistent with a 15N tracer study at the site, in which the N addition treatment increased
the proportion of the 15N tracer found in aboveground biomass (Bass in et al.. 2015).
However, the stimulation of plant N pools was relatively similar among aboveground
biomass (+31%), roots (+31%), necromass (+41%), and litter [+30%; (Bassin et al..
2015)1. Among functional groups, the longer-term results were both similar and different
than the results observed after the initial 3 years (Bassin et al.. 2013). The effects of N
addition on sedge biomass increased through time, with the highest rate of N addition
(50 kg N/ha/yr) increasing sedge biomass by 360%. In this same treatment, grass biomass
increased by 14%, forb biomass was unchanged, and legume biomass decreased by 43%.
Unsurprisingly, these changes resulted in more sedge-dominated plant communities. Two
aspects of this community change are notable: (1) changes were largely complete after
4-5 years, and (2) the lowest rate ofN addition was sufficient to cause significant
changes (Bassin et al.. 2013). This experiment also included an ozone fumigation
treatment, but there were no interactions between ozone and added N for productivity or
community composition (Yolk et al.. 2014; Bassin et al.. 2013; Bassin et al.. 2007) and
few N x ozone interactions for leaf physiological traits (Bassin et al.. 2009). Two related
studies on alpine grasslands have also been conducted in the Swiss Alps by members of
the same research group. At 10 sites, Bassin et al. (2012) found that grassland
aboveground productivity increased 30% with 2 years of NH4NO3 additions of
50 kg N/ha/yr. Blanke et al. (2012) planted seedlings of four local plant species into
intact grass/soil monoliths excavated from the same Swiss alpine grassland site as Bassin
et al. (2013). Bassin et al. (2009). and Bassin et al. (2007). Nitrogen addition
(50 kg N/ha/yr) treatments increased overall biomass of the unplanted vegetation in the
monoliths. Among the planted species, N additions increased biomass of the grass and
decreased biomass of the forb, but had no effect on the sedge or legume. Roots of the
grass, forb, and legume were colonized by arbuscular mycorrhizal (AM) fungi; N
addition increased root colonization by AM fungi for the grass (Blanke et al.. 2012).
As in other environments, the plant growth response to N additions in alpine and Arctic
ecosystems varies among taxonomic groups. For example, in the Swiss subalpine
grassland experiment, Bassin et al. (2013) noted that within plant communities, sedge
(Cyperaceae) species tend to show especially strong positive responses to N additions.
Within a dry meadow in Rocky Mountain National Park in Colorado, N additions of 5,
10, and 30 kg N/ha/yr increased cover of the sedge Carex rupestris from 34 to 125%
(Bowman et al.. 2012). Within the northern Caucasus Mountains of Russia, Qnipchenko
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et al. (2012) examined the response of four different alpine plant communities to
90 kg N/ha/yr for 5 years. The N additions increased vascular plant biomass in a lichen
heath community, but not in grassland, meadow, or snowbed communities. Within these
communities, the response of individual plant functional groups to N varied. The N
additions increased sedge biomass in the lichen heath, increased forbs and sedges in the
meadow, increased grasses in the grassland, and decreased legumes in the lichen heath
and meadow. Shrubs were not significantly affected by N additions. This variation among
plant species was also observed in two long-term N addition experiments in moist alpine
meadows at the Niwot Ridge Long-Term Ecological Research site in Colorado, wherein
N additions (averaging either 229 or 288 kg N/ha/yr) for 7 or 11 years increased growth
of the grass Deschampsia cespitosa, but decreased growth of the perennial forb Geum
rossii (Farrer et al.. 2015; Farrer et al.. 2013). The decrease in Geum abundance was not
necessarily due to competitive exclusion: Geum decreased even in study plots where
Deschampsia had been removed (Farrer et al.. 2013). Instead, Geum showed effects of
physiological stress with N additions, with less C allocation to storage organs and lower
concentrations of nonstructural carbohydrates (Farrer et al.. 2013).
In addition to the research on alpine tundra in Colorado, there have been several other
recent publications on the effect of N additions on plant productivity in tundra
ecosystems in North America. Additions of 70 kg N/ha/yr for 3 years plots in a central
Utah alpine meadow increased aboveground plant production by 10-20%, but did not
significantly impact soil respiration or soil C content (Gill. 2014). Given the large
contribution of root and mycorrhizal respiration to soil respiration, this suggests a change
in C allocation toward aboveground growth. In shrub tundra in the Northwest Territories
of Canada, 8 years of N additions of 10 kg N/ha/yr had no effect on overall aboveground
plant biomass or the biomass of the dominant plant (Betula), but each of these metrics
was increased by N additions at a rate of 100 kg N/ha/yr (Zamin et al.. 2014; Zamin and
Grogan. 2012). Inflorescence production in Betula was unaffected at both N addition
rates. Elsewhere in the Northwest Territories, Churchland et al. (2010) observed that a
single year of N additions (100 kg N/ha/yr) increased foliar N concentrations in shrub
tundra plants. In an Alaskan tundra meadow, kellev and Epstein (2009) found that N
additions (100 kg N/ha/yr for 3 years) increased foliar N concentrations but had no effect
on aboveground plant growth. Together, the results of these studies in North America are
consistent with the overall body N addition research in tundra ecosystems (Table 6-6).
The influence of N additions on tundra plant biomass and productivity has also been
assessed since 2008 in other portions of the world. In the Tibetan Plateau in China, N
additions of 75 kg N/ha/yr over 8 years increased plant biomass in an alpine meadow by
about 20% regardless of the form of N added (NaNC>3, [NFLJ2SO4, NH4NO3), but lower
rates of N addition (3.75 or 15 kg N/ha/yr) had no effect (Song and Yu. 2015). In an
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Arctic shrub ecosystem in Greenland, Arens etal. (2008) studied the effects of N
additions at 5, 10, and 50 kg N/ha/yr over 3 years on ecosystem C fluxes and community
composition. Net ecosystem productivity (NPP), gross primary production (GPP), and
ecosystem respiration (ER) all increased in response to N additions, but these responses
saturated beyond 10 kg N/ha/yr. The smallest rate of N addition caused both GPP and ER
to nearly double. However, soil respiration was not significantly affected by the N
addition treatments. Dominant vascular plant cover was highest in the 10 kg N/ha/yr
treatment. Nitrogen additions increased the cover of subdominant vascular plants from
3% in control plots to 8% in the highest N treatment. There were also other changes in
the cover of plant functional groups, including a 41% increase in deciduous shrubs lowest
N addition plots, a doubling of graminoid biomass in the moderate N treatment relative to
control, and large increases in forb biomass in the moderate and high N addition
treatment.
As in forests, lichens are an important component of plant communities and a significant
contributor to ecosystem function in Arctic and alpine tundra ecosystems. Since 2008,
there have been numerous observations of how lichens have responded to added N in
these systems (Table 6-7) and these responses are broadly similar to those observed in
forests. Nielsen et al. (2014) studied the tissue N concentration of the lichen Cladonia
portentosa at five heathland sites in Denmark in local areas with NH3 emissions rates
varying from 5 to 19 kg N/ha/yr. The lichen tissue N concentrations were strongly related
(r2 = 0.97) to annual average NH ? concentrations at the sites. Britton and Fisher (2010)
also observed increased tissue N concentrations in three of four lichen species from
Scottish heathlands over the course of a growing season with N additions of 2.5 to
22.5 kg N/ha/yr. Hogan et al. (2010b) collected lichens from 27 heathland sites in the
U.K. along a wet N deposition gradient (2-33 kg N/ha/yr) and observed increased thalli
N concentrations, decreased thalli P concentrations, and increased phosphomonoesterase
activity, an enzyme important for P acquisition. Hogan et al. (2010a) found similar results
in an N addition study. Armitage et al. (2014) observed a decline in lichen cover in alpine
heathland sites across an N deposition gradient of 0.6 to 39.6 kg N/ha/yr in the North
Atlantic region of Europe. Similarly, there were decreases in lichen biomass or lichen
cover with additional N in studies in Scotland (Britton and Fisher. 2010). Sweden
(Wardle et al.. 2013). Alaska (Kellev and Epstein. 2009). and Canada (Zamin et al..
2014).
Because of the often sparse cover of vascular plants in tundra ecosystems, bryophytes are
often relatively larger components of plant communities than in other terrestrial systems.
As with lichens, bryophyte physiology and growth in tundra ecosystems can be impacted
by added N. Armitage et al. (2012) conducted an analysis of the tissue chemistry, growth,
and cover of the bryophyte Racomitrium lanuginosum in alpine heathlands at 36 sites in
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Great Britain, Iceland, Faroe Islands, and Norway. Estimated N deposition at these sites
ranged from ~ 1 kg/ha/yr to nearly 40 kg/ha/yr. Among environmental variables that
included temperature, precipitation, and grazing, N deposition was the largest influence
on tissue N and P concentrations. Notably, tissue N concentration increased rapidly with
N deposition rates up to 5 kg/ha/yr, then increased at a slower rate with higher levels of N
deposition. Tissue N concentration was positively related to moss shoot growth, but also
positively related to shoot turnover and negatively related to moss mat depth. These
effects were nonlinear and especially pronounced at high tissue N concentrations. Among
other plant functional types at these sites, shrub growth decreased with greater N
deposition, graminoid growth increased, and forbs were not significantly affected
(Armitage etal.. 2014). In related work using a subset of these sites, Armitage et al.
(2011) conducted a 2-year transplant experiment that moved Racomitrium between
10 sites receiving higher N deposition (8.2-32.9 kg/ha/yr) and a cleaner site
(7.2 kg/ha/yr). When the authors transplanted Racomitrium from elevated N deposition
sites to low N deposition sites and vice versa, tissue N concentration remained higher in
the plants from higher N sites, whereas moss moved from lower N to higher N sites
increased tissue N to nearly match levels in the moss natural to the site. Armitage et al.
(2011) also observed that moss at high N sites had higher shoot growth, whereas moss
transplanted to lower N sites increased in biomass due to decreasing tissue C:N and
slowing decomposition (Armitage et al.. 2011).
Table 6-7 Alpine and Arctic tundra lichen growth and physiology responses to
nitrogen added via atmospheric deposition or experimental
treatments.
Reference
Study
Location
Vegetation
Ambient
Deposition
or Addition
Nitrogen
Addition
Rate (kg
N/ha/yr)
Duration
(yr) Endpoint
Effect of
Additional
Nitrogen
Zamin et al.
Northwest
Shrub tundra
Addition
10, 100
8 Lichen biomass
Low dose:
(2014)
Territories
(Vaccinium
not
(Canada)
vitis-idaea,
significant;
Rhododendron
hiah dose:
subarcticum,
decrease
Andromeda
polifolia)
Britton and
Fisher (2010)
Scotland
Heathlands
(Calluna
vulgaris)
Addition
2.5, 7.5,
12.5, 22.5
0.25 Lichen thalli
mass
Three
species: not
significant;
two
species:
decrease
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Table 6-7 (Continued): Alpine and Arctic tundra lichen growth and physiology
responses to nitrogen added via atmospheric deposition
or experimental treatments.
Nitrogen
Ambient
Addition
Effect of
Study
Deposition
Rate (kg
Duration
Additional
Reference
Location
Vegetation
or Addition
N/ha/yr)
(yr) Endpoint
Nitrogen
Wardle et al.
Sweden
Tundra
Addition
50
21 Lichen cover
Decrease
(2013)
meadow
(Deschampsia
flexuosa,
Empetrum
hermaphrodi-
tum, Vaccinium
spp.)
Kellev and
Alaska
Tundra
Addition
100
3 Lichen cover
Decrease
Epstein (2009)
meadow
{Dryas
integrifolia,
Eriophorum
vaginatum,
Carex spp.)
Armitaae et al.
Europe
Alpine
Ambient
0.6-39.6
n/a Lichen cover
Decrease
(2014)
(North
heathlands
Atlantic)
Britton and
Scotland
Heathlands
Addition
2.5, 7.5,
0.25 Thalli N %
Three
Fisher (2010)
(Calluna
12.5, 22.5
species:
vulgaris)
increase;
one
species: not
significant
Nielsen et al.
Denmark
Heathlands
Ambient
5-19
n/a Thalli N %
Increase
(2014)
(Calluna
vulgaris)
Hoaan et al.
U.K.
Heathland
Addition
8, 24, 56
4 Thalli N %
Increase
(2010a)
lichen
(Cladonia
portentosa)
Hoaan et al.
U.K.
Heathland
Ambient
2.32-32.8
n/a Thalli N %
Increase
(2010b)
lichen
(Cladonia
portentosa)
Hoaan et al.
U.K.
Heathland
Ambient
2.32-32.8
n/a Thalli N %
Increase
(2010b)
lichen
(Cladonia
portentosa)
Hoaan et al. U.K. Heathland Ambient 2.32-32.8 n/a Thalli P % Decrease
(2010b) lichen
(Cladonia
portentosa)
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Table 6-7 (Continued): Alpine and Arctic tundra lichen growth and physiology
responses to nitrogen added via atmospheric deposition
or experimental treatments.
Reference
Study
Location
Vegetation
Ambient
Deposition
or Addition
Nitrogen
Addition
Rate (kg
N/ha/yr)
Duration
(yr)
Endpoint
Effect of
Additional
Nitrogen
Hoaan et al.
(2010a)
U.K.
Heathland
lichen
(Cladonia
portentosa)
Addition
8, 24, 56
4
Phosphomono-
esterase activity
Increase
Hoaan et al.
(2010b)
U.K.
Heathland
lichen
(Cladonia
portentosa)
Ambient
2.32-32.8
n/a
Phosphomono-
esterase activity
Increase
ha = hectare; kg = kilogram; N = nitrogen; n/a = not applicable; P = phosphorus; yr = year.
Note: Single studies are reported more than once if multiple endpoints or ecosystems are measured. Only statistically significant
effects are listed as increases or decreases.
In high-latitude and high-elevation ecosystems such as tundra, heathlands, and boreal
forests, plants in the Ericaceae family are often abundant. Notable members of the
Ericaceae family include blueberries and cranberries (both Vaccinium). Ericaceous plants
are unique in that they host ericoid mycorrhizae, which are distinct from ectomycorrhizae
and arbuscular mycorrhizae. Ericoid fungi are recognized for their ability to decompose
large organic molecules and absorb organic forms of soil N (Read et al.. 2004). This
specialization in organic N uptake could make these mycorrhizae more vulnerable to
increased inorganic N availability. However, only a relatively small number of N addition
studies have quantified changes in mycorrhizal growth or physiology in ecosystems
supporting plants that host ericoid mycorrhizae (Table 6-8). Ishida and Nordin (2010)
added 12.5 or 50 kg N/ha/yr for 4 or 12 years to boreal forests in Sweden and observed
no change in the percentage of Vaccinium myrtillus roots colonized by ericoid
mycorrhizae, the number of ericoid fungal species per root tip, or ericoid community
composition, and observed mixed effects on ericoid species richness. Dean et al. (2014)
studied the response of root-associated fungi in alpine tundra in Colorado to 8 years of N
additions (29 kg N/ha/yr). Ericoid fungi abundance decreased and the overall community
composition of root-associated fungi changed, including a reduction in diversity and
richness. Further research is needed to understand the response of ericoid mycorrhizae to
added N.
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Table 6-8 Growth and biodiversity responses of ericoid mycorrhizal fungi to
nitrogen added in experimental treatments.
Reference
Study
Location
Vegetation
Ambient
Deposition
or Addition
Nitrogen
Addition
Rate (kg
N/ha/yr)
Duration
(yr)
Endpoint
Effect of
Additional
Nitrogen
Ishida and
Nordin (2010)
Sweden
Vaccinium
myrtillus roots in
Picea abies
forests and Pinus
sylvestris forests
Addition
12.5, 50
12
(Picea),
4 (Pinus)
Root
colonization
(%)
Not significant
Ishida and
Nordin (2010)
Sweden
Vaccinium
myrtillus roots in
Picea abies
forests and Pinus
sylvestris forests
Addition
12.5, 50
12
(Picea),
4 (Pinus)
Ericoid species
per root tip
Not significant
Ishida and
Nordin (2010)
Sweden
Vaccinium
myrtillus roots in
Picea abies
forests and Pinus
sylvestris forests
Addition
12.5, 50
12
(Picea),
4 (Pinus)
Ericoid species
richness
Pinus\
increase;
Picea\ not
significant
Ishida and
Nordin (2010)
Sweden
Vaccinium
myrtillus roots in
Picea abies
forests and Pinus
sylvestris forest
Addition
12.5, 50
12
(Picea),
4 (Pinus)
Ericoid
community
composition
Not significant
Dean et al.
(2014)
Colorado
(Niwot
Ridge)
Alpine tundra
(Geum rossii,
Deschamp-sia
cespitosa)
Addition
28.8
8
Root-
associated
fungal diversity
and richness
Deschampsia'.
decrease;
Geum\
increase
Dean et al.
(2014)
Colorado
(Niwot
Ridge)
Alpine tundra
(Geum rossii,
Descham-psia
cespitosa)
Addition
28.8
8
Root-
associated
fungal
community
composition
Change
Dean et al.
(2014)
Colorado
(Niwot
Ridge)
Alpine tundra
(Geum rossii)
Addition
28.8
8
Ericoid fungal
abundance
Decrease
ha = hectare; kg = kilogram; N = nitrogen; yr = year.
Note: Single studies are reported more than once if multiple endpoints are measured. Only statistically significant effects are listed
as increases or decreases.
1 Although Bouskill et al. (2014) observed that N additions increased fungal biomass in a
2 meta-analysis of high-latitude N addition experiments, other studies of fungal biomass in
3 tundra ecosystems have found negative (Farreret al.. 2013; Wardle et al.. 2013) or
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neutral responses (Sundqvist et al.. 2014). Bouskill et al. (2014) did not find a significant
effect of added N on total microbial biomass in their meta-analysis, with individual
studies reporting a negative effect (Farrer et al.. 2015) or no effect (Churchland et al..
2010). In a meta-analysis, Treseder (2008) found that N additions decreased bacterial
biomass in tundra ecosystems, but this analysis included only two studies. Of the three
subsequent studies of bacterial biomass, N additions had no effect in two and a negative
effect in a third (Table 6-9). Notably, Bouskill et al. (2014) observed that microbial
biomass responses were positive under relatively low rates of N addition, but became
negative as N addition rates exceeded -50 kg N/ha/yr). Belowground respiration showed
a similar response, but lower threshold (-25 kg N/ha/yr) at which the response switched
from positive to negative.
To examine the influence of added N on organisms at higher trophic levels, Bishop et al.
(2010) studied the effects of N additions (78 kg N/ha/yr for 5 years) on plant and
arthropod communities in alpine meadows that were primary successional ecosystems on
recently formed volcanic substrates on Mount St. Helens in Washington. The N additions
increased foliar N concentration in the dominant graminoid, but decreased foliar N
concentration in the dominant legume. The N additions also increased both plant species
diversity and plant cover, although in the final year of the experiment, increased
browsing by small mammals negated the effect of the N additions. There was no effect on
total arthropod abundance (individuals per m2), but the number of Orthoptera
approximately doubled. Overall, total arthropod abundance was strongly positively
related to both plant diversity and plant cover, with arthropod abundance among
individual orders both positively and negative related to plant diversity and plant cover.
Table 6-9 Alpine and Arctic tundra microbial biomass responses to
experimental nitrogen additions.
Reference
Study
Location
Vegetation
Ambient
Deposition
or Addition
Nitrogen
Addition
Rate (kg
N/ha/yr)
Duration
(yr)
Endpoint
Effect of
Additional
Nitrogen
Bouskill et al.
North
Arctic and high-
Addition
Average:
Various
Microbial
Not
(2014)
America
latitude meta-
72; range:
biomass
significant
and Europe
analysis
1-100
Farrer et al.
(2015)
Colorado
(Niwot
Ridge)
Moist alpine
meadow
(Deschampsia
cespitosa, Geum
rossii)
Addition
229
7
Microbial
biomass
Decrease
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Table 6-9 (Continued): Alpine and Arctic tundra microbial biomass responses to
experimental nitrogen additions.
Nitrogen
Ambient
Addition
Effect of
Study
Deposition
Rate (kg
Duration
Additional
Reference
Location
Vegetation
or Addition
N/ha/yr)
(yr)
Endpoint
Nitrogen
Churchland et
Northwest
Shrub tundra
Addition
100
1
Microbial
Not
al. (2010)
Territories
(Betula
biomass C
significant
(Canada)
glandulosa,
Vaccinium vitis-
idaea,
Rhododendron
subarcticum)
Bouskill et al.
North
Arctic and high-
Addition
Average:
Various
Fungal
Increase
(2014)
America
latitude meta-
72; range:
biomass
and Europe
analysis
1-100
Sundqvist et
Sweden
Tundra meadow
Addition
100
3
Fungal
Not
al. (2014)
(Deschampsia
biomass
significant
flexuosa,
Anthoxanthum
alpinum)
Farrer et al.
Colorado
Moist alpine
Addition
288
11
Fungal
Decrease
(2013)
(Niwot
meadow
biomass
Ridge)
(Deschampsia
cespitosa, Geum
rossii)
Wardle et al.
Sweden
Tundra meadow
Addition
50
21
Fungal
Decrease
(2013)
(Deschampsia
biomass
flexuosa,
Empetrum
hermaphroditum,
Vaccinium spp.)
Treseder
Tundra
Meta-analysis
Addition
Various
Bacterial
Decrease
(2008)
biomass
Sundqvist et
Sweden
Tundra heath
Addition
100
3
Bacterial
Not
al. (2014)
(Vaccinium vitis-
biomass
significant
idaea, Vaccinium
uiiginosum,
Betula nana)
Farrer et al.
Colorado
Moist alpine
Addition
288
11
Bacterial
Decrease
(2013)
(Niwot
meadow
biomass
Ridge)
(Deschampsia
cespitosa, Geum
rossii)
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Table 6-9 (Continued): Alpine and Arctic tundra microbial biomass responses to
experimental nitrogen additions.
Nitrogen
Ambient Addition Effect of
Study Deposition Rate (kg Duration Additional
Reference Location Vegetation or Addition N/ha/yr) (yr) Endpoint Nitrogen
Wardle et al. Sweden Tundra meadow Addition 50 21 Bacterial Not
(2013) (Deschampsia biomass significant
flexuosa,
Empetrum
hermaphroditum,
Vaccinium spp.)
C = carbon; ha = hectare; kg = kilogram; N = nitrogen; yr = year.
Note: Single studies are reported more than once if multiple endpoints or ecosystems are measured. Only statistically significant
effects are listed as increases or decreases.
6.1.5 Grasslands
The 2008 ISA contained limited information regarding the effects on N deposition on
productivity and related aspects of eutrophication in grasslands. That assessment included
the work of Neff et al. (2002). who examined the long-term effects (+10 years) of N
deposition (10 kg N/ha/yr) in an alpine meadow, where N additions stimulated
aboveground NPP by 47%. Factors affecting productivity in grasslands are similar in
many ways to forests, with N availability limiting primary production. Grasslands
dominate largely in places where forests cannot grow because of low moisture
availability, high disturbance rates (such as from fire or grazing), and/or cold
temperatures and shorter growing seasons [such as at high latitudes and elevations;
(Chapin et al.. 2002; Knapp et al.. 1998)1. However, because of the commonality of N
limitation to primary production (Vitousek and Howarth. 1991). many of the processes
that occur when N is added to forests also occur when N is deposited onto grasslands.
These include increases in primary production and foliar N, increases in allocation to
aboveground biomass (increased shoot:root ratio), decreased levels of light reaching the
ground surface, elevated litter inputs, and changes in the soil biota (Aerts and Chapin.
1999; Knapp et al.. 1998). which are described further below.
Since the 2008 ISA, further advancements in our understanding of the effects of N
deposition on grasslands have occurred. A meta-analysis estimated that N additions
increased grassland aboveground NPP by 53% (LcBauer and Treseder. 2008). Increased
plant growth, NPP, or plant biomass in response to added N has been observed in prairies
in Wyoming, Kansas, and Minnesota (Henry et al.. 2015; Farrior et al.. 2013; Isbell et al..
2013; Hillerislambers et al.. 2009; Johnson et al.. 2008). in temperate grasslands in
Ontario (Vankoughnett and Henry. 2014; Hutchison and Henry. 2010) and Michigan
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(Grman and Robinson. 2013). and in Mediterranean grasslands in California (Borer et al..
2014; Vallano et al.. 2012). Although the response to N enrichment is variable among
species in many terrestrial ecosystems, the comparatively rapid turnover rate of plant
biomass in grasslands means that wide differences in the response of individual species to
N deposition are frequently observed even in short-term studies (Hautier et al.. 2014;
Vankoughnett and Henry. 2014; Grman and Robinson. 2013; Isbell et al. 2013; Bradford
et al.. 2012; Vallano et al.. 2012; Skogen etal.. 2011). Three new syntheses of grassland
responses to N additions or N deposition have been published since the 2008 ISA.
Stevens et al. (2015) used data from a network of 42 grassland sites on four continents
and found that estimated rates of atmospheric N deposition were the strongest predictor
of aboveground NPP in these ecosystems. On average, aboveground NPP increased 3%
for every 1 kg N/ha/yr increase in N deposition and N deposition explained 16% of the
variance in productivity in these systems (Stevens et al.. 2015). implying that much of the
variation in NPP was not understood. Yue et al. (2016) conducted a meta-analysis of N
addition studies and found a 50.4% stimulation of grassland aboveground NPP, similar to
the estimate of LcBauer and Treseder (2008). Aboveground and belowground plant C
were stimulated by an average of 30.5 and 28%, respectively, in the Yue et al. (2016)
analysis, whereas Li et al. (2015) did not observe a significant change in grassland fine
root biomass.
The differences in how individual plant species respond to added N may in part be due to
variation in functional traits, including the ability to change plant C allocation. In a
common garden experiment, Johnson et al. (2008) grew plants that were among the most
positively and negatively responsive to long-term N additions at the Cedar Creek and
Konza Prairie LTER sites. The plants that were most positively affected by N additions
allocated more biomass to shoots than roots and formed fewer associations with
mycorrhizal fungi. Likewise, Grman and Robinson (2013) also found that N additions
increased aboveground biomass and decreased the relative allocation of C to
mycorrhizae. Of the two grass species studied, the species that more strongly decreased
allocation to mycorrhizae as N availability increased also showed a greater aboveground
biomass response to added N. Bradford et al. (2012) documented a somewhat different
functional response, finding that increasing rates of N additions favored the species that
showed greater leaf trait plasticity in response to the N additions. Earlier studies
suggested leaf plasticity was an important determinant of plant growth responses to added
N, and that the ability of a species to upregulate production if nutrients were abundant
was an advantage (Knops and Reinhart. 2000). Hillerislambers et al. (2009) observed that
N amendments (40 kg N/ha/yr) had similar effects on grasses within the same functional
groups: C3 grasses tended to increase aboveground biomass and decreased seed
production, while C4 grasses increased seed production and decreased aboveground
biomass. In a survey of 44 species in 153 acidic grassland sites across northern and
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western Europe, Pannek etal. (2015) found that species with high relative growth rates
tended to show beneficial responses to N deposition.
In multiyear studies, responses to N enrichment often varied through time. For instance,
over a 7-year period of N addition, Henry et al. (2015) found that the stimulation of
aboveground biomass ranged approximately 10 to nearly 100%. Working at a long-term
biodiversity and N deposition experiment at Cedar Creek in Minnesota that used seven
different N addition rates from 10 to 270 kg N/ha/yr, Isbell et al. (2013) initially observed
that N additions increased grassland productivity, with higher rates of N addition causing
greater increases in productivity. Although N additions continued to stimulate
productivity, productivity decreased in plots that lost the most species over time. In a
large synthesis, Hautier et al. (2014) used data from studies of 41 experimental grassland
communities on five continents and found grassland communities had greater annual
variability in plant productivity (less stability) as the N input rate increased. Under
ambient conditions, annual variability in plant productivity is limited by asynchronous
productivity among different species, wherein slower growth by some species is balanced
by more rapid growth of neighboring species. In these unmanipulated systems, the
stability of plant productivity is positively associated with plant diversity (Hautier et al..
2014; Til man et al.. 2001; Tilman et al.. 1997). With added N, the increase in annual
variability in productivity could not be linked to a loss of species richness, but was
instead caused by a decrease in the asynchrony of productivity among individual plant
species.
Nitrogen enrichment can also cause variation in plant chemistry, particularly increases in
tissue N concentrations (Reich et al.. 2003). Bradford et al. (2012) conducted a
greenhouse experiment with several grass and forb species and observed increases in
shoot N concentrations, but root C:N and root mass N were not consistently affected by N
additions. In a greenhouse experiment conducted by Jamieson et al. (2012). N addition
had no effect on the concentration of a defensive compound in shoots, whereas
concentrations decreased in flowers by -35%. As in other terrestrial ecosystems, these
increases in shoot N concentrations can lead to an increase in leaf-level photosynthesis
where other resources are not limiting [e.g., (Reich et al.. 2003; Lee et al.. 2001)1.
However, these increases in photosynthesis vary among species and can vary temporally
(Reich et al.. 2003; Lee et al.. 2001). Within a U.K. grassland exposed to N additions of
35 or 140 kg N/ha/yr for 11 years, Arroniz-Crespo et al. (2008) observed decreases in
cover of two bryophyte species as well as a decrease in chlorophyll fluorescence in both
species (despite an increase in chlorophyll content in one species). Both bryophyte
species exhibited increased activity of an enzyme involved in P acquisition
(phosphomonoesterase) and decreased nitrate reductase enzyme activity, but only one of
the two bryophyte species exhibited increased tissue N concentrations and N:P ratios.
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Several experiments in Ontario, Canada have examined the response of old field
grasslands to the interaction between N additions and climate change in the form of
altered snowpack, soil freezing, or warming. Vankoughnett and Henry (2014) found that
N additions of 20 or 60 kg N/ha/yr increased aboveground production, but this varied by
species. In the first year of the experiment, plant production showed a stronger response
to N in plots where snow had been experimentally removed, but this interaction did not
occur in subsequent years. Although the extent of the effect varied by year, Henry et al.
(2015) found that 7 years of N additions at a rate of 60 kg N/ha/yr increased aboveground
biomass and showed no interaction with experimental warming.
Effects of water availability were also observed in grassland studies by Friedrich et al.
(2012). Jamieson et al. (2013). and Farrior et al. (2013). In a greenhouse experiment with
a grass native to German grasslands, Friedrich et al. (2012) found that N additions of
48 kg N/ha/yr increased aboveground biomass by 500%. However, plants receiving N
were more likely to suffer dieback when N additions were combined with drought.
Nitrogen enrichment in a Wyoming prairie increased the production of a defensive
chemical compound in an invasive plant by 37% under ambient conditions, but decreased
the production of this compound by 25% when water availability was reduced (Jamieson
et al.. 2013). At Cedar Creek in Minnesota, Farrior et al. (2013) found complex responses
to changes in N and water availability: N enrichment increased shoot biomass regardless
of water availability, fine root biomass declined when availability of both water and N
was high, and higher water availability increased fine root biomass only at low rates of N
addition.
There has been less research on the effects on N enrichment on belowground C cycling in
grasslands than in forests (Yue et al.. 2016; Li et al.. 2015; Liu and Greaver. 2010). In a
meta-analysis, Liu and Greaver (2010) found that N additions to grasslands increased
aboveground litter inputs, but did not significantly affect soil respiration, microbial
respiration, or soil C. In part, the lack of an overall effect on these processes could be due
to the combination of high variability among grasslands and the small samples size for
the meta-analysis, as only approximately six studies were available for the Liu and
Greaver (2010) analysis. However, a more recent meta-analysis of N addition
experiments by Yue et al. (2016) that had larger sample sizes found somewhat similar
results: belowground plant C was stimulated by 24.2%, but there were no significant
effects on soil respiration, microbial respiration, litter decomposition rates, soil organic
C, or microbial biomass. This last result contradicts Liu and Greaver (2010). who found
that N enrichment decreased microbial biomass C.
The conflicting meta-analytic results for changes in grassland soil microbial biomass
could be caused by differences in analyses or data sets, or could reflect ecological
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complexities that require more nuanced understanding, such as the influence of
phosphorus availability (Johnson et al.. 2008). For instance, Chung et al. (2009) found
that N additions (40 kg N/ha/yr as NH4NO3) decreased fungal biomass via phospholipid
fatty acid analyses at Cedar Creek in Minnesota, while Liang et al. (2015) did not find
any significant changes in fungal lipid biomass caused by N additions (70 kg N/ha/yr) at
Jasper Ridge in the San Francisco Bay Area. However, Liang et al. (2015) also measured
changes in the abundance of individual amino sugars that indicated decreases in total
microbial biomass and fungal biomass, but increases in bacterial biomass. In the over
150-year Park Grass Experiment, Zhalnina et al. (2015) observed that NaNO? additions
had no effect on bacterial and archaeal biomass as assessed by 16S ribosomal RNA
abundance, but (NFL^SC^ additions decreased on bacterial and archaeal biomass. Li et
al. (2015) found no effect of N additions on fine root biomass or mycorrhizal
colonization of root tips in a meta-analysis of grassland experiments, but again had small
sample sizes (four biomass studies, nine mycorrhizal studies). There have been a number
of studies of the effects of N additions on mycorrhizal abundance in grasslands (Table
6-3). Grassland plants predominantly host arbuscular mycorrhizal fungal associations. As
with arbuscular mycorrhizal responses observed in forests [e.g., (van Diepen et al..
2010)1. arbuscular mycorrhizal responses to added N in grasslands have been
inconsistent, with a similar number of studies showing no response (Liang etal.. 2015;
Chen et al.. 2014; Mandvam and Jumpponen. 2008) and studies showing a negative effect
on colonization or growth [e.g., (Chen et al.. 2014; Johnson et al.. 2008; Van Per Heiiden
et al.. 2008)1.
Most studies of grassland soil microbial responses to N deposition (Table 6-10) have
focused on free-living soil heterotrophs or mycorrhizal fungi, but Weese et al. (2015)
examined the response of N fixing rhizobial bacteria in clover (Trifolium) as part of a
22-year chronic N addition (123 kg N/ha/yr as NH4NO3) experiment in a Michigan
grassland. Clover inoculated with rhizobial bacteria from soil or bacterial strains that
were collected from the long-term N addition experiment exhibited lower chlorophyll
content and decreased plant biomass, including fewer leaves and stolons. These patterns
were consistent across all three clover species used in the experiment. Notably, these
changes did not result from a shift in the community composition of the rhizobial
bacteria, but instead resulted from the evolution of new strains of the bacteria Rhizobium
leguminosarum that were less symbiotic and less cooperative in the exchange of C for N.
A similar change toward less mutualistic interactions in response to N additions have
been observed for mycorrhizae in grasslands (Johnson. 1993). It is unclear if these
evolutionary changes are reversible or how long this reversion would take (Weese et al..
2015).
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Zehnder and Hunter (2008) performed a plant density manipulation experiment to
examine the effect of N deposition on the interaction between a host plant from the
southeastern U.S., Asclepias tuberosa, and its herbivore, Aphis nerii. Added N increased
aphid population growth, plant foliar N concentrations, and plant biomass. In southern
California coastal grasslands, Borer et al. (2014) observed that N additions (40 or
100 kg N/ha/yr as Ca|NO,|2) increased plant biomass, but only in the absence of
herbivores (pocket gophers, Thomomys bottae).
The high spatial and temporal variability inherent in grassland structure and function that
is a product of the multiple limiting factors such as precipitation and phosphorus, as well
as the large influence of herbivores and fire, makes all but the most general predictions of
responses to increased N deposition a challenge. Although grassland ecosystems are
sensitive to shifts in N availability, forecasting the magnitude of increase in NPP with
increased N deposition is limited to broad generalizations based on meta-analyses
(30-60%; [e.g., (Yue et al.. 2016; Liu and Greaver. 2010; LcBauer and Treseder. 2008)1.
Thus, although there is wide variation among grasslands, the general response is similar,
with N addition leading to increases in NPP and foliar N, increases in allocation to
aboveground biomass (increased ratio of shoot:root), elevated litter inputs, and changes
in the populations of soil biota and their associations with plants.
Table 6-10 Grassland microbial biomass responses to experimental nitrogen
additions.
Ambient Nitrogen
Deposition Addition Effect of
Study or Rate (kg Additional
Reference Location Vegetation Addition N/ha/yr) Duration (yr) Endpoint Nitrogen
Ramirez et al. Minnesota Temperate Addition
(2010b) (Cedar grasslands
Creek)
30, 60,
100,
160,
280,
500, 800
27
Microbial
biomass
Not
significant
Eisenhauer et al.
(2013)
Minnesota Prairie
(Cedar
Creek)
Addition
40
14
Microbial
biomass
Not
significant
Wei et al. (2013)
China Steppe Addition
grassland
5.6,
11.2,
22.4,
39.2,
56
Microbial
biomass
Lowest
dose: not
significant;
other
doses:
decrease
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Table 6-10 (Continued): Grassland microbial biomass responses to experimental
nitrogen additions.
Ambient Nitrogen
Deposition Addition Effect of
Study or Rate (kg Additional
Reference Location Vegetation Addition N/ha/yr) Duration (yr) Endpoint Nitrogen
Liana et al. (2015) California Annual Addition 70 9 Microbial Not
(northern) grassland biomass significant
(Avert a
barbata, A.
fatua)
Liana et al. (2015) California Annual Addition 70 9 Bacterial Not
(northern) grassland biomass significant
(Avert a
barbata, A.
fatua)
Wei et al. (2013) China Steppe Addition 5.6, 4 Bacterial Lowest
grassland 11.2, biomass dose: not
22.4, significant;
39.2, 56 other
doses:
decrease
Wei et al. (2013) China Steppe Addition 5.6, 4 Fungal Three
grassland 11.2, biomass lowest
22.4, doses: not
39.2, 56 significant;
two
highest
doses:
decrease
Liang et al. (2015) California Annual Addition 70 9 Fungal Not
(northern) grassland biomass significant
(Avert a
barbata, A.
fatua)
Liang et al. (2015)
California
(northern)
Annual
grassland
(Avert a
barbata, A.
fatua)
Addition
70
9
Saprotrophic
fungal
biomass
Not
significant
Eisenhauer et al.
(2012)
Minnesota
(Cedar
Creek)
Prairie C3
and C4
grasses,
forbs,
legumes
Addition
40
14
Amoeba and
flagellate
abundance
Not
significant
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Table 6-10 (Continued): Grassland microbial biomass responses to experimental
nitrogen additions.
Study
Ambient Nitrogen
Deposition Addition
or Rate (kg
Effect of
Additional
Endpoint Nitrogen
Reference Location Vegetation Addition N/ha/yr) Duration (yr)
Kastl et al. (2015) Germany Temperate Addition
(green- grasses
house) (Dactylis
50, 100, 0.12
200
Archaeal Achaea:
and not
bacterial significant;
amoA (NH3 Bacteria:
mono- increase
oxygenase)
gene
abundance
glomerata,
Festuca
rubra)
ha = hectare; kg = kilogram; N = nitrogen; yr = year.
Note: Single studies are reported more than once if multiple endpoints or ecosystems are measured. Only statistically significant
effects are listed as increases or decreases.
Large portions of the western U.S. are covered by arid and semiarid ecosystems. While
many of these ecosystems receive little anthropogenic N deposition compared to the
eastern U.S., some areas downwind of agricultural and metropolitan centers receive high
levels of atmospheric N deposition (Form et al.. 2003b'). In addition, the unique nutrient
cycling processes in these systems can intensify the influence of N deposition on
ecosystem processes I Homvak et al. (2014); see Chapter 41.
The lack of moisture in arid and semiarid climates changes the nature of how N
deposition impacts biological communities in these ecosystems compared to more mesic
ecosystems such as tallgrass prairies and forests. First, the strong moisture constraint on
productivity limits the influence of increased N availability on plant communities [e.g.,
(Rao and Allen. 2010)1. with shifts in community composition less likely to occur
without sufficient moisture [e.g., (Concilio and Loik. 2013)1. Second, the lack of strong
biological demand for N during periods of moisture limitation, combined with infrequent
soil leaching and runoff events, leads to the accumulation of inorganic N in surface soils,
intensifying the effects of N deposition on soil N concentrations when moisture is
available [e.g., (Homvak et al.. 2014)1. Broadly, soil base saturation and pH increase as
the climate becomes more arid (Schlesinger. 2005). buffering dryland ecosystems from
the acidification-driven losses in biodiversity that are observed along N deposition
gradients [e.g., (Simkin et al.. 2016)1. Finally, the patchy vegetation that often develops
in deserts tends to create isolated islands of fertility, wherein nutrients (including N) are
concentrated beneath shrub canopies (Titus et al.. 2002; Schlesinger and Pilmanis. 1998).
Under these circumstances, anthropogenic N deposition can increase N availability in the
6.1.6 Arid and Semiarid Ecosystems
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interspaces between shrubs, allowing the growth of annual grasses and forbs, which can
grow and reproduce during the brief seasonal periods with adequate moisture availability
(Brooks. 2003). In particular, there have been numerous observations from semiarid and
arid ecosystems that N deposition can increase the productivity and dominance of
invasive grasses [e.g., (Brooks. 2003; Fenn et al.. 2003a; Padgett and Allen. 1999)1. This
phenomenon provides a more continuous fuel bed for wildfires, increasing fire frequency
and shifting plant community composition away from species that are not fire adapted
(Padgett and Allen. 1999; Allen et al.. 1998).
There was already a large amount of information available on how N deposition impacted
arid and semiarid ecosystems at the time of the 2008 ISA, especially in areas around
southern California downwind of Los Angeles, where dry N deposition can be
>30 kg N/ha/yr (Bvtnerowicz and Fenn. 1996). In particular, the 2008 ISA described
results from several N deposition studies in this region, which showed increased biomass
of invasive species, high mortality of native shrubs in heavily polluted areas, and
increased fire risk (Padgett and Allen. 1999; Allen et al.. 1998). These experiments were
primarily conducted in coastal sage scrub (CSS) ecosystems or in the Mojave Desert.
The amount of land area covered by CSS in southern California has greatly declined in
the past 60 years due to changes in land use, grazing, and increased wildfire frequency
(Allen et al.. 1998). In addition, native CSS vegetation has been replaced in many areas
by annual grasses from the Mediterranean region (Padgett et al.. 1999; Padgett and Allen.
1999; Allen et al. 1998). In the mid-1990s, N deposition had been implicated as a
contributor to this ecosystem alteration because it decreased the growth of native shrubs
and increased the growth of invasive grasses, with the secondary effect of increasing fire
frequency (Padgett et al.. 1999; Padgett and Allen. 1999; Allen et al.. 1998). There was
also evidence that the N assisted conversion from CSS to invasive annual grasses had
altered the hydrology of these ecosystems (Wood et al.. 2006). The loss of native
vegetation in the CSS and chaparral ecosystems in southern California is particularly
notable because these ecosystems are unique within the U.S., are limited in their spatial
extent, and are important global and national hotspots for biodiversity.
Similar effects of N deposition on plant communities had also been observed at the time
of the 2008 ISA further east, in the Mojave Desert. Brooks (2003) documented that
NH4NO3 additions (32 kg N/ha/yr) increased the biomass of invasive annual grasses and
forbs by more than 50%. The increased growth of the invasive plants suppressed the
growth of native annual plants. In particular, N additions stimulated the growth of
Bromus madritensis beneath the dominant native shrub Larrea tridentata, while the
invasive grasses in the genus Schismus and the invasive forb Erodium cicutarium had
enhanced growth in the interspaces between shrubs. This spatial nature of these effects is
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important because as in the CSS, the spatially continuous fuel beds created by high grass
biomass have been associated with increased fire frequency in the Mojave Desert (Brooks
et al.. 2004; Brooks and Esque. 2002; Brooks. 1999). This effect is stronger at higher
elevation, likely because the higher precipitation stimulates grass productivity. Fire was
relatively rare in the Mojave Desert until the past two decades, but now fire occurs
frequently in areas that have experienced invasion of exotic grasses (Brooks. 1999V The
comparatively unresponsive nature of native Mojave vegetation to N deposition was also
observed elsewhere. For instance, 3 years of N additions [40 kg N/ha/yr as Ca(NC>3)2] had
almost no impact on leaf-level photosynthetic or hydraulic performance in Larrea
tridentata growing north of Las Vegas, NV (Barker et al.. 2006).
At the time of the 2008 ISA, N deposition effects on belowground processes in arid and
semiarid lands were not well understood. In a Chihuahuan Desert grassland in New
Mexico, 10 years of N additions (10 kg N/ha/yr) increased the activity of extracellular
glucosidase enzymes important in the breakdown of carbohydrates, but decreased the
activity of extracellular aminopeptidase enzymes important in the decomposition of
proteins and peptides (Stursova et al.. 2006). In contrast, there were no differences in C
mineralization (decomposition) in soils collected at a similar southern California gradient
of CSS sites [4 to 23 kg N/ha/yr; (Vourlitis and Zorba. 2007)1. Along a CSS N deposition
gradient in the Los Angeles area, arbuscular mycorrhizal (AM) fungi associated with the
dominant sagebrush shrub declined with increasing N pollution and also in response to N
additions (60 kg N/ha/yr; 4-5 years) at a relatively unpolluted site (Sigiienza et al.. 2006).
There was conflicting evidence about whether these changes in AM fungi influenced the
plant growth response to N deposition. An earlier study suggested that differences in
mycorrhizal colonization were not responsible for the effects ofN deposition on CSS
plant growth in this region (Yoshida and Allen. 2001). However, a subsequent study
found that sagebrush inoculated with AM from a high N deposition site grew more
slowly than those with inoculum from a low N deposition site (Sigiienza et al.. 2006). In
addition, grasses in semiarid ecosystems in New Mexico and Colorado grew slower when
inoculated with mycorrhizae from sites that had received N additions than from sites
without N additions (Corkidi et al.. 2002).
Research published since 2008 has continued to concentrate on CSS and Mojave Desert
ecosystems in the southern California, but new studies in southern California chaparral
ecosystems, the Sonoran Desert of Arizona, and elsewhere have been published. Most
studies investigating the effects of N deposition in arid and semiarid environments
published since the 2008 ISA have further emphasized that the impacts of increased N are
heavily dependent on water availability (Rao et al.. 2015; Homvak et al.. 2014;
Newingham et al.. 2012; Ochoa-Hueso and Manrique. 2010; Rao and Allen. 2010). The
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high dependence on precipitation is consistent with ecosystem models for C cycling in
desert systems (Shen et al.. 2008).
For instance, Rao and Allen (2010) investigated how productivity in Joshua Tree
National Park annuals is altered by increasing N supply under a range of water
availabilities (Table 6-11). Using a 5-year field N addition experiment and N additions of
up to 12.4 kg N/ha/yr, the authors observed the greatest production of invasive grasses
and native forbs under the highest soil N and highest watering regime. Similarly,
(Newingham et al.. 2012) found that N additions of 10 or 40 kg N/ha/yr as Ca(NO?): in
the Mojave Desert increased branch production in creosote (Larrea tridentata) only
during a wet year, whereas the addition of water and N significantly increased the amount
of rodent herbivory.
A similar interaction between N and water was found in the Sonoran Desert in and
around Phoenix. Hall etal. (2011) added 60 kg N/ha/yr and found little or no increase in
production among herbaceous annuals in low precipitation years, moderate N responses
with average rainfall, and strong increases in biomass with added N during above-normal
rainfall seasons. However, no increases in productivity were observed in the dominant
shrub Larrea tridentata, even during above-normal rainfall. This contrasts with the
ecosystem modeling for this same study system conducted by Shen et al. (2008). which
suggests that observed rates of N deposition in the Phoenix region would increase Larrea
productivity by more than an order of magnitude in wet years. Mosses in this region also
appear to be influenced by N deposition, with lower moss abundance and higher tissue N
concentrations at urban study sites that receive higher N deposition (Ball and Guevara.
2015).
Other studies document the overall effect of N deposition on vegetation communities. At
Joshua Tree National Park in the Mojave desert of California, non-native grass biomass
increased significantly at three of the four study sites that received 30 kg N/ha/yr for
2 years, but there was no change with 5 kg N/ha/yr of added N (Allen et al.. 2009). There
was no clear response of native species to N addition, but these plants made up a small
fraction of community biomass. Rao et al. (2015) tried to model the effects of N
deposition on the biomass of invasive annual grasses and the occurrence of wildfire in the
Mojave Desert of California, but were unable to effectively disentangle the effects of N
deposition on fire from factors such as precipitation, distance from roads, and firefighting
resources. Also in the Mojave Desert, Stark etal. (2011) investigated the effects of 10 or
40 kg N/ha/yr N addition on the dominant biological crust moss (Syntrichia caninervis)
for a period of 5 years. Interestingly, the lower rate of N application had negative effects
on the amount dead chlorotic tissue in shoots and crust regeneration, higher rates of N
addition only negatively impacted apical meristem growth. Additionally, Wissinger et al.
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(2014) observed higher seed production in areas of the Mojave with higher atmospheric
N deposition (up to 16 kg N/ha/yr).
There are very few field studies of how N enrichment impacts belowground C cycling in
desert systems (Liu and G reaver. 2010). In a meta-analysis of these studies, Liu and
Greaver (2010) found no consistent effect of N enrichment on soil respiration. Verburg et
al. (2013) quantified the effects of increased summer precipitation and N deposition on
fine root dynamics in a Mojave Desert ecosystem during a 2-year field experiment.
Increased summer precipitation and 40 kg N/ha/yr N additions did not have an overall
significant effect on any of the measured root parameters. Within the Sonoran Desert near
Phoenix, Marusenko etal. (2015) observed that N additions (60 kg N/ha/yr for 8 years)
increased the abundance of the a mo A gene, which is needed for ammonia oxidation, in
both Archaea and Bacteria. Sinsabaugh et al. (2015) conducted a meta-analysis of soil
microbial responses to N additions (5 to 560 kg N/ha/yr; 0.3 to 10 years) in arid
ecosystems and identified only 8 studies of various microbial biomass responses and 10
studies of various microbial metabolic responses. Broadly, both metrics increased with
the addition of low amount of N, but responses became negative once threshold N
addition rates (kg N/ha/yr: 88 for biomass, 70 for metabolism) or cumulative loads
(kg N/ha: 159 for biomass, 114 for metabolism) had been reached.
Vourlitis (2012) measured the aboveground biomass and litter production of a post-fire
chaparral and a mature CSS stand in southern California over an 8-year period. Nitrogen
additions decreased NPP in the chaparral during the first 3 years of the study, but
increased NPP during the last 3 years of the experiment. In the coastal sage scrub, the
effect of added N positively correlated with precipitation and was only significant in the
high rainfall years. The authors suggest that N enrichment (50 kg N/ha/yr) may increase
the productivity, but that temporal patterns may take years to emerge and be dependent
on water availability. In contrast, shorter experiments conducted by Vourlitis and
Fernandez (2012) and Vourlitis et al. (2009) in chaparral and coastal sage scrub
ecosystems in southern California found that 4 years of dry season N addition at
50 kg N/ha/yr increased litter N and plant tissue, but had no effect on ecosystem
productivity or ecosystem N storage. Another study using the same N deposition gradient
in the CSS as Padgett and Allen (1999). found decreased lower soil C content at high
deposition sites (Liu and Crowlev. 2009). Further, experimental N additions
[50 kg N/ha/yr as Ca(NC>3)2] decreased soil C content at the low deposition site.
However, there were no clear changes in microbial community composition along the
deposition gradient or as a result of the N additions.
A study by Vourlitis and Pasquini (2008) analyzed pre- and post-fire nutrient and soil
dynamics of three southern California chaparral stands exposed to varying levels ofN
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1 deposition and determined that periodic fire may not reduce N enrichment from decades
2 of N deposition. In a subsequent study, Pasquini and Vourlitis (2010) exposed chaparral
3 stands to different levels ofN deposition over the first 3 years of post-fire succession.
4 High N deposition was associated with a lower relative abundance of A. fasciculatum and
5 a higher relative abundance of other shrub and herbaceous species. However, overall
6 aboveground net productivity was not related to N deposition.
Table 6-11 Arid and semiarid ecosystem plant producitivity and physiology
responses to nitrogen added in experimental treatments.
Ambient
Nitrogen
Deposition
Addition
Effect of
Study
or
Rate (kg
Duration
Additional
Reference
Location
Vegetation
Addition
N/ha/yr)
(yr)
Endpoint
Nitrogen
Wana et al.
China
Arid
Addition
100
4
Net
Increase
(2015b)
(north, Jilin)
grassland
ecosystem
(Leymus
exchange
chinensis)
Wana et al.
China
Arid
Addition
100
4
Ecosystem
Increase
(2015b)
(north, Jilin)
grassland
respiration
(Leymus
chinensis)
Wana et al.
China
Arid
Addition
100
4
Gross
Increase
(2015b)
(north, Jilin)
grassland
ecosystem
(Leymus
production
chinensis)
Ochoa-
Spain
Shrubland
Addition
10, 20,
3
Plant biomass
Not
Hueso and
(Quercus
50
significant
Stevens
coccifera,
(2015)
Rosmarinus
officinalis,
Lithodara
fruticosa)
Zhana et al.
China
Alkaline
Addition
100
4
Plant
Increase
(2015b)
(north,
grassland
aboveground
Songnen)
(Leymus
biomass
chinensis,
Kaiimeris
integrifoiia)
Wana et al.
China
Arid
Addition
100
4
Plant
Increase
(2015b)
(north, Jilin)
grassland
aboveground
(Leymus
biomass
chinensis)
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Table 6-11 (Continued): Arid and semiarid ecosystem plant producitivity and
physiology responses to nitrogen added in experimental
treatments.
Reference
Study
Location
Vegetation
Ambient
Deposition
or
Addition
Nitrogen
Addition
Rate (kg
N/ha/yr)
Duration
(yr)
Endpoint
Effect of
Additional
Nitrogen
Sun et al.
(2014)
China
(north,
Songnen)
Shrubland
(Leymus
chin en sis,
Artemisia
scoparia)
Addition
23, 46,
69, 92
3
Plant
aboveground
biomass
Low dose:
not
significant
other
doses:
increase
Rao and
Allen
(2010)
Garden
(California,
Mojave)
Invasive
grass
(Bromus
madritensis),
native forb
(Amsinckia
tessellata)
Addition
5, 30
1
Aboveground
plant biomass
Forb:
increase;
arass:
increase
Rao and
Allen
(2010)
California
(Mojave)
Larrea
tridentata or
Juniperus
caiifornica,
Pinus
monophyiia
Addition
2, 5, 30
5
Grass and
forb biomass
Increase
Allen et al.
(2009)
California
(Joshua
Tree NP;
four sites)
Creosote
bush scrub
(Larrea
tridentata);
Pinyon-
juniper
woodland
(Pinus
monophyiia,
Juniperus
caiifornica)
Addition
5, 30
2
Invasive
grass
biomass
Low dose:
not
significant;
hiah dose:
increase at
3/4 sites
Rao et al.
(2015)
California
(Mojave)
Desert wash,
desert scrub,
desert
succulent
cover types
Ambient
0.4-15.3
n/a
Biomass of
annual plants
Increase
Rao et al.
(2009)
California
(Joshua
Tree NP)
Creosote
bush (Larrea
tridentata) or
Pinyon-
juniper
woodland
(Pinus
monophyiia,
Juniperus
caiifornica)
Ambient
2.7-14.4
n/a
Biomass of
annual plants
Not
significant
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Table 6-11 (Continued): Arid and semiarid ecosystem plant producitivity and
physiology responses to nitrogen added in experimental
treatments.
Ambient Nitrogen
Deposition Addition
Effect of
Study
or Rate (kg
Duration
Additional
Reference
Location
Vegetation
Addition N/ha/yr)
(yr)
Endpoint
Nitrogen
Allen et al.
California
Creosote
Addition 5, 30
2
Native and
Low dose:
(2009)
(Joshua
bush scrub
exotic plant
not
tree NP;
(Larrea
cover
significant;
four sites)
tridentata);
hiqh dose:
Pinyon-
not
juniper
significant
woodland
at three
(Pinus
sites,
monophylla,
increased
Juniperus
native
californica)
cover at
one site
Hall et al.
Phoenix,
Creosote and
Addition 60
5
Herbaceous
Increase
(2011)
AZ
bursage
annual plant
shrublands
production
(Larrea
tridentata,
Ambrosia
spp.)
Hall et al.
Phoenix,
Creosote and
Addition 60
5
Shrub
Not
(2011)
AZ
bursage
biomass
significant
shrublands
production
(Larrea
tridentata,
Ambrosia
spp.)
Zhana et al.
China
Alkaline
Addition 100
4
Plant
Increase
(2015b)
(north,
grassland
belowground
Songnen)
(Leymus
biomass
chin en sis,
Kaiimeris
integrifoiia)
Wissinaer
California
Creosote and
Ambient 2-12
n/a
Shrub seed
Increase
et al.
(Mojave)
bursage
production
(2014)
shrublands
(Larrea
tridentata,
Ambrosia
dumosa)
Pasauini
California
Chaparral
Ambient 8.1, 11.9,
n/a
Growth rate
Increase
and
(southern;
(Adenostoma
18.4
per shrub
Vourlitis
three sites)
fascicuiatum,
(2010)
Ceanothus
spp.)
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Table 6-11 (Continued): Arid and semiarid ecosystem plant producitivity and
physiology responses to nitrogen added in experimental
treatments.
Reference
Study
Location
Vegetation
Ambient
Deposition
or
Addition
Nitrogen
Addition
Rate (kg
N/ha/yr)
Duration
(yr)
Endpoint
Effect of
Additional
Nitrogen
Pasquini
and
Vourlitis
(2010)
California
(southern;
three sites)
Chaparral
(Adenostoma
fasciculatum,
Ceanothus
spp.)
Ambient
8.1, 11.9,
18.4
n/a
Shrub density
(Plants/ha)
Decrease
Newinaham
et al.
(2012)
Nevada
(Mojave)
Creosote
bush (Larrea
tridentata)
Addition
10, 40
6
Larrea branch
elongation
Not
significant
Newinaham
et al.
(2012)
Nevada
(Mojave)
Creosote
bush (Larrea
tridentata)
Addition
10, 40
6
Larrea branch
number
Increase
Newinaham
et al.
(2012)
Nevada
(Mojave)
Creosote
bush (Larrea
tridentata)
Addition
10, 40
6
Larrea leaf
production
Not
significant
Newinaham
et al.
(2012)
Nevada
(Mojave)
Creosote
bush (Larrea
tridentata)
Addition
10, 40
6
Larrea seed
production
Not
significant
Belnap et
al. (2008)
Utah
(Canyon-
lands NP)
Biological soil
crusts
Addition
Not
stated
1
Photosyn-
thetic
pigments
Decrease
Sinsabauah
et al.
(2015)
Nevada
(Mojave)
Creosote and
bursage
shrublands
(Larrea
tridentata,
Ambrosia
dumosa)
Addition
7, 15
1
Shrub foliar
element %
(including N,
P)
Not
significant
Wissinaer
et al.
(2014)
California
(Mojave)
Creosote and
bursage
shrublands
(Larrea
tridentata,
Ambrosia
dumosa)
Ambient
2-12
n/a
Shrub foliar N
%
Not
significant
Hall et al.
(2011)
Phoenix,
AZ
Creosote and
bursage
shrublands
(Larrea
tridentata,
Ambrosia
spp.)
Addition
60
5
Shrub foliar N
%
Larrea and
herbs:
increase;
Ambrosia:
not
significant
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3
4
5
6
7
8
9
10
11
12
Table 6-11 (Continued): Arid and semiarid ecosystem plant producitivity and
physiology responses to nitrogen added in experimental
treatments.
Reference
Study
Location
Vegetation
Ambient
Deposition
or
Addition
Nitrogen
Addition
Rate (kg
N/ha/yr)
Duration
(yr)
Endpoint
Effect of
Additional
Nitrogen
Zhang et al.
(2015a)
Beijing,
China
Shrubland
(Vitex
negundo)
Addition
20, 50,
100
Foliar N %
Low dose:
not
significant;
med. dose:
increase in
1 of 4
species;
high dose:
increase in
3/4 species
Zhang et al.
(2015a)
Beijing,
China
Shrubland
(Spirea
trilobata)
Addition
20, 50,
100
Foliar N %
Not
significant
Zhang et al. China Shrubland
(2015a) (north, (Vitex
Songnen) negundo)
Addition
20, 50,
100
Leaf litter N %
Low dose:
not
significant;
med. dose:
increase in
1 of 4
species;
high dose:
increase
Zhang et al.
(2015a)
China
(north,
Songnen)
Shrubland
(Spirea
trilobata)
Addition
20, 50,
100
Leaf litter N % Not
significant
ha = hectare; kg = kilogram; N = nitrogen; n/a = not applicable; NP = national park; P = phosphorus; yr = year.
Note: Single studies are reported more than once if multiple endpoints or ecosystems are measured. Only statistically significant
effects are listed as increases or decreases.
There were also numerous studies conducted on dryland ecosystems outside of the U.S.,
including in China. Huang et al. (2015) conducted a 3 year N x water experiment focused
on soil microbial community composition and function in a desert steppe ecosystem in
northwestern China that receives 25 kg N/ha/yr of ambient deposition. The N addition
treatment (50 kg N/ha/yr as NH4NO3) did not have consistent effects, increasing
microbial respiration in the interplant zone between shrubs in the 1st year of the
experiment, while decreasing microbial respiration, microbial biomass C, and the
microbial biomass C:N ratio beneath the shrubs in the abnormally dry 2nd year of the
experiment. The N addition effects differed between interplant and beneath shrub sites. In
the interplant spaces, N additions tended to increase overall microbial abundance, with
significant increases in bacteria and total microbial PLFA biomass in all 3 years and an
increase in actinobacteria in the last 2 years of the experiment, whereas beneath the
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shrubs, N additions decreased bacteria biomass, fungal biomass, and total PLFA in
2 years and decreased actinobacteria biomass in all 3 years (Table 6-12). Microbial
respiration, C content, and N content were each positively related to soil moisture, but not
soil inorganic N pools. Soil moisture also tended to have larger effects on soil microbial
community composition. In a semiarid steppe grassland in northeastern China, 4 years of
N additions (100 kg N/ha/yr as NH4NO3) increased belowground biomass in each year of
the experiment, but effects on aboveground biomass were only significant in 2 of the
4 years (Zhang et aL 2015d). However, the stimulation of aboveground biomass (+20%)
was larger than the stimulation of belowground biomass (+6.1%). In another semiarid
steppe grassland in northeastern China, 4 years of N additions (50 kg N/ha/yr as urea)
increased plant density (plants per m2), aboveground biomass, and belowground biomass
in the final 3 years of the experiment (Wang et al.. 2015b). As in the Zhang et al. (2015d)
study, the stimulation of aboveground biomass (+102%) was much larger than the
stimulation of belowground biomass (+41%). The N addition treatment increased NEE
(+53.8%), ER (+47.6%), and GEP (+47.9%) in all 3 years. In a third N addition
experiment in the semiarid steppe grassland in northeastern China, Sun et al. (2014)
observed that N additions of 23, 46, 69, and 92 kg N/ha/yr (3 years, as urea) caused
proportional increases in both plant aboveground productivity and soil microbial
biomass. Elsewhere in China, 2 years of N additions (20, 50, or 100 kg N/ha/yr as urea)
to a semiarid shrub steppe increased leaf N concentrations and decreased the amount of N
resorbed during leaf senescence in seven perennial grass, sedge, and shrub species
(Zhang et al.. 2015a). In a steppe ecosystem in northern China, Li et al. (2014) found that
the dominant grass Leymus chinensis responded positively to one season of N additions
of between 20 and 300 kg N/ha, with shifts in plant allocation toward decreased root to
shoot ratios at higher N addition rates. Zhang et al. (2015c) studied how N added
(eight levels from 10 to 500 kg N/ha/yr as NH4NO3) frequently (12 doses/yr) or
infrequently (2 doses/yr) over 5 years influenced plant productivity in a steppe grassland
in the Inner Mongolia region of China. The higher doses of N increased aboveground
NPP regardless of how frequently the N was added. However, the authors pointed to a
group of similar studies that had shown small frequent N doses caused more, less, or
similar growth responses relative to large infrequent N doses. As in other semiarid
systems, the authors noted greater productivity responses to N in years with higher annual
precipitation. Although the N additions increased ecosystem aboveground NPP, some
individual species were less productive with added N. Notably, increasing N doses were
related to decreased soil water content, temperature, and pH, and higher soil NO3 and
NH4 (Zhang etal.. 2015e).
In a greenhouse study of plants collected from a semiarid ecosystem in Spain, Ochoa-
Hueso and Manrique (2010) found that grass biomass was relatively unresponsive to N
enrichment of up to 50 kg N/ha, even when provided with increased water. However,
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1 forb biomass and community biomass approximately tripled when both water and N were
2 enriched. In a related field experiment in central Spain, Ochoa-Hueso and Stevens (2015)
3 added N (0, 10, 20, or 50 kg N/ha/yr as NH4NO3) to a semiarid shrubland ecosystem for
4 6 years. The effects on plant productivity varied by time. After 2.5 years, N additions
5 decreased the biomass of the dominant forbs species. After 5.5 years, N additions
6 increased the biomass of plants in the Cruciferae family, but only in areas where there
7 was sufficient soil P available. The authors noted that each of the biomass assessments
8 occurred in years with above-average precipitation.
Table 6-12 Arid and semiarid microbial biomass responses to experimental
nitrogen additions.
Reference
Study
Location
Vegetation
Ambient
Deposition
or
Addition
Nitrogen
Addition
Rate (kg
N/ha/yr)
Duration
(yr)
Endpoint
Effect of
Additional
Nitrogen
Sinsabauah
etal. (2015)
Global
Arid lands
meta-analysis
Addition
5-560
0.3-10
Microbial
biomass
Low dose:
increase; high
dose: decrease
Sinsabauah
etal. (2015)
Global
Arid lands
meta-analysis
Addition
5-560
0.3-10
Microbial
metabolism
Low dose:
increase;
hiah dose:
decrease
Sinsabauah
etal. (2015)
Nevada
(Mojave)
Creosote and
bursage
shrublands
(Larrea
tridentata,
Ambrosia
dumosa)
Addition
7, 15
1
Microbial
biomass
Not significant
Treseder
(2008)
Desert
Meta-analysis
Addition
Microbial
biomass
Increase
Huana et al.
(2015)
China
Desert shrubs
(Haloxylon
ammodendron)
Addition
50
3
Microbial
biomass C
Not significant
Sun et al.
(2014)
China
(north,
Songnen)
Shrubland
(Leymus
chin en sis,
Artemisia
scoparia)
Addition
23, 46, 69,
92
3
Microbial
biomass C
Hiqhest dose:
increase;
other doses: not
significant
C = carbon; ha = hectare; kg = kilogram; N = nitrogen; yr = year.
Note: Single studies are reported more than once if multiple endpoints or ecosystems are measured. Only statistically significant
effects are listed as increases or decreases.
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23
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25
26
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6.1.7
Physiology, Growth, and Productivity Summary
At the time of the 2008 ISA, there was evidence sufficient to infer a causal relationship
between N deposition and the alteration of the biogeochemical cycling of C in terrestrial
ecosystems. This evidence included observations that added N increased plant
productivity across a broad range of terrestrial ecosystems, but there was no explicit
statement regarding the effects of N deposition on physiology, growth, and productivity.
Since the 2008 ISA, a more mechanistic understanding of how N deposition impacts
terrestrial organisms and ecosystems has been developed, the effects of N deposition in
terrestrial ecosystems in North America and Europe have been more widely documented,
and a significant new body of research has observed N deposition impacts in Asia
(particularly China). These efforts have provided further evidence that added N alters
plant physiological processes, stimulates the growth of most plants, and broadly increases
productivity (Liu and Greaver. 2010; Lc Bauer and Treseder. 2008; Xia and Wan. 2008).
There is also widespread evidence that N additions affect soil microbial physiology and
biomass (see Chapter 4 for soil extracellular enzyme responses), particularly by
decreasing the abundance of symbiotic mycorrhizal fungi (Li et al.. 2015; Treseder.
2008). There have also been numerous observations that additional N can alter arthropod
performance and abundance among both detritivores and herbivores KThroop and
Lcrdau. 2004); Table 6-171. Thus, it is apparent that plants, microorganisms, and
ecosystem-scale productivity are sensitive to N availability. This body of evidence is
sufficient to infer a causal relationship between N deposition and the alteration of
the physiology and growth of terrestrial organisms and the productivity of
terrestrial ecosystems.
Although plants are broadly sensitive to added N, it is clear that the effects of N on plant
growth and productivity vary considerably among plant tissues (Li et al.. 2015; Xia and
Wan. 2008). individual species and functional types (Xia and Wan. 2008). and biomes
(LeBauer and Treseder. 2008). In a meta-analysis of 1,600 observations, short-lived plant
functional types tended to have stronger relative responses than long-lived plants;
herbaceous plants responded more than woody plants and annual herbs responded more
than perennial herbs lYXia and Wan. 2008); Figure 6-11. Shrubs were notably less
responsive than trees (Figure 6-1). but this may have been related to prevalence of shrubs
in more arid environments; overall, biomass responses increased linearly with mean
annual precipitation (Xia and Wan. 2008). There is also now more consistent and
widespread evidence that N additions increase aboveground biomass more than
belowground biomass, raising the shoot:root ratio among plants (Li et al.. 2015; Lu et al..
201 lb).
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The increase in aboveground growth of individual plant species is the best documented
response of plants to N, with fewer studies documenting belowground growth responses
and more complex physiological and ecosystem-scale responses (e.g., Figure 6-1. and
Figure 6-2). LeBauer and Treseder (2008) found that N additions stimulated aboveground
productivity, but the relative stimulation was smaller the response of individual plants
identified by Xia and Wan (2008). Belowground net primary productivity responses to
added N have not yet been synthesized because of lack of data (LeBauer and Treseder.
2008). Liu and Greaver (2009) did not find a significant effect on net ecosystem
exchange, but forest ecosystem C content was increased by 6%.
In the 2008 ISA, the increase in plant growth and terrestrial productivity was attributed to
increases in foliar N content and related increases in photosynthesis. As noted earlier,
increases in plant N concentrations are widespread (Koricheva et al.. 1998). particularly
in the foliage, koricheva et al. (1998) had previously quantified increases in foliar N
concentrations among woody plants; Xia and Wan (2008) expanded this analysis to other
plant functional groups, with an overall stimulation of +28.5%. Aside from smaller
responses among legumes and broader functional groups containing legumes, there was a
relatively narrow range of responses across functional groups (+24-34%). Root N
concentrations show similar responses (Li et al.. 2015; Xia and Wan. 2008). Given the
mechanistic and empirical relationships between greater foliar N concentrations, higher
leaf concentrations of the C assimilating enzyme Rubisco (Evans. 1989). and greater
maximum rates of leaf-level photosynthesis in vascular plants (Wright et al.. 2004). the
increases in foliar N observed with greater N supply have been linked to higher rates of
leaf-level photosynthesis [e.g., (Teskev et al.. 1994)1. Alternately, there was evidence in
the 2008 ISA that much of the additional foliar N could be physiologically inactive
(Bauer etal. 2004). consistent with the significant increase in free amino acids observed
by koricheva et al. (1998). Increases in photosynthesis following N additions have been
observed across a variety of plant functional types, but higher rates of photosynthesis
have not been universally observed in long-term experiments [e.g., (Talhelm et al.. 2011;
Elvir et al.. 2006; Chen et al.. 2005b; Newman et al.. 2003; Laitha and Whitford. 1989;
Gulmon and Chu. 1981)1 and there have not been any broad syntheses or meta-analyses
of either leaf-level photosynthesis or gross primary productivity. There is a similar
mechanistic and empirical relationship between tissue N concentrations and respiration
rates, but this relationship has shifted in long-term N addition studies, providing further
evidence that much of the additional tissue N is physiologically inactive [e.g., (Burton et
al.. 2012; Drake et al.. 2008)1.
Alternately, decreases in the quantity of C allocated belowground to roots, mycorrhizae,
and root exudation could provide a mechanism that increases aboveground plant growth
in plants and ecosystems that do not show gains in photosynthesis [e.g., (Talhelm et al..
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2011)1. Plants provide mycorrhizal fungal symbionts with C in exchange for nutrients
and the abundance of mycorrhizal fungi and the rates at which these fungi colonize roots
declines when N is added to terrestrial ecosystems (Treseder. 2004). a finding that has
since been repeated (Li et al.. 2015; Treseder. 2008). The decrease is particularly well
documented for ectomycorrhizal fungi (Table 6-2). but can also occur with arbuscular
mycorrhizal fungi as well lYvan Diepen et al.. 2010); Table 6-31.
Nitrogen deposition can affect the physiology and abundance of soil microorganisms
through decreases in soil pH, increases in inorganic N availability, changes in soil food
webs, and shifts in the quantity and quality of available C (Xia etal.. 2015; Manning et
al.. 2008; Treseder. 2008; koricheva et al.. 1998). There were some observations in the
2008 ISA that added N decreased microbial biomass. There is now more abundant
evidence that N deposition can greatly impact microbial communities. In meta-analyses,
N additions have been shown to decrease microbial biomass (Treseder. 2008). microbial
biomass C (Liu and Greaver. 2010). and microbial biomass N (Luetal.. 2011b). In a
meta-analysis, Treseder (2008) found that the negative effects of added N on microbial
biomass increased in magnitude with the duration of the N additions and the cumulative
amount of added N. Notably, these observations of soil microbial biomass would include
the hyphal biomass of mycorrhizal fungi. There are fewer observations of N addition
effects at the level of individual microbial domains (e.g., bacteria, fungi), functional
groups (e.g., saprotrophic vs. mycorrhizal fungi), or higher-level taxonomic groups, and
aside from the aforementioned decreases in mycorrhizal fungi, effects at these scales
appear to be less consistent (Table 6-4).
Notably, the form of inorganic N added to terrestrial ecosystems seems to have little
influence on the biological responses (Table 6-1). Based on this evidence, the effects of
oxidized and reduced forms of N on terrestrial eutrophication appear to be broadly
similar.
6.2 Relationships between Nitrogen Deposition and Terrestrial
Species Composition, Species Richness, and Biodiversity
6.2.1 Introduction
Given the enormous role of N in biogeochemical cycling (Chapter 4). soil acidification
(Chapter 5). and the growth and physiology of terrestrial organisms (Section 6.1). it is
unsurprising that N availability exerts a strong control on community composition.
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Because of functional differences among organisms, the changes in community
composition and diversity caused by N deposition have both direct and indirect
implications for the provisioning of ecosystem goods and services (Mace et al.. 2012). In
the 2008 ISA, the evidence was sufficient to infer a causal relationship between N
deposition on the alteration of species richness, species composition, and biodiversity in
terrestrial ecosystems. In the 2008 ISA, the most sensitive terrestrial taxa were lichens.
Empirical evidence indicated that lichens in the U.S. are adversely affected by deposition
levels as low as 3 kg N/ha/yr. Alpine ecosystems were also found to be sensitive to N
deposition, changes in an individual species were estimated to occur at deposition levels
near 4 kg N/ha/yr, and modeling indicated that deposition levels near 10 kg N/ha/yr alter
plant community assemblages.
Since 2008, there have been a large number of studies that have quantified plant, animal,
and microbial populations and communities in order to understand the relationship
between increased atmospheric N deposition and biodiversity, species richness,
community composition, the abundance of N sensitive species, the presence non-native
species, and community stability. The effects of N deposition on diversity have been
observed in all major biomes (Bobbink et al.. 2010) and changes in biological
communities have been found across a wide range of taxonomic and functional
classifications, including trees, shrubs, grasses, forbs, bryophytes, fungi (including
mycorrhizae), bacteria, and arthropods. Among these effects, N deposition has been
identified as a threat to 12 terrestrial plant or animal species that are listed or candidates
for protection under the federal Endangered Species Act (Hernandez et al.. 2016).
A number of global, continental, and regional syntheses have compiled information about
changes in biodiversity as a result of N deposition. Some of these studies predate the
2008 ISA and served as part of the basis for the conclusions in that assessment [e.g.,
(Phoenix et al.. 2006; Pennings et al. 2005; Sliding et al.. 2005; Stevens et al.. 2004;
Bobbink et al.. 2003; Matson et al.. 2002; Gough et al.. 2000; Wallenda and kottke.
1998; Vitousek et al.. 1997)1. More recent assessments have reinforced the conclusion
that N deposition is a major cause of species loss in ecosystems around the world [e.g.,
(Phoenix et al.. 2012; De Schrijver et al.. 2011; Pardo et al.. 2011a; Bobbink et al..
2010)1. Further, these new assessments have provided a more detailed understanding of
both vulnerable and heavily impacted species, ecosystems, and biomes and created a
more precise understanding of the mechanisms linking species loss to N deposition. This
new research, combined with information from the 2008 ISA, creates a body of evidence
sufficient to infer a causal relationship between N deposition and the alteration of
species richness, community composition, and biodiversity in terrestrial ecosystems.
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6.2.2
Mechanisms Operating across Terrestrial Ecosystems
Broadly, the effects of N deposition on the diversity and composition of terrestrial
ecosystems stem from four mechanisms [sensu Bobbink et al. (2010)1: (1) eutrophication,
(2) acidification, (3) direct toxicity and damage, and (4) increased susceptibility to
secondary stress. Within a particular community or ecosystem, it is likely that multiple
mechanisms operate simultaneously to alter diversity. As described in Chapter 5. N
deposition may lead to soil acidification, which can have negative effects on plants and
microorganisms as base cation nutrients are lost to leaching and toxic metals such as Al
become more available in the soil solution. Direct toxicity and damage from N deposition
often comes from an accumulation of NH4+ in soils and plant tissues, wherein high
concentrations can be toxic. Vulnerability to secondary stressors includes effects such as
greater impacts of pathogens (Bobbink et al.. 2010) and shifts in herbivory as a result of
altered tissue chemistry (Throop and Lcrdau. 2004). Among these four major
mechanisms, eutrophication is perhaps the most complex because it can change the
physiology of individual organisms, alter the relative growth and abundance of species,
transform relationships among species, and indirectly affect the availability of other
essential resources such as light, water, and nutrients [see Section 6.1; Chapter 4;
(Hautier et al. 2009; Clark et al.. 2007; Sliding et al.. 2005)1. Given these complexities, it
is difficult to develop mechanistic models that can accurately predict shifts in the
composition of ecological communities as a result of N deposition. Consequently,
assessments of how N deposition alters species diversity, species richness, and changes in
community composition predominately rely on experimental manipulations and empirical
relationships developed across large spatial and temporal scales [e.g., (Simkin et al..
2016; Verheven et al.. 2012; Clark et al.. 2007; Sliding et al.. 2005)1.
Much of the ecological theory regarding the loss of species richness with N enrichment
has been developed from observations of changes in plant species abundance in
grasslands and other nonforest ecosystems [e.g., (Pennings et al.. 2005; Sliding etal..
2005; Gough et al.. 2000)1. Many investigators have found a unimodal relationship
between plant species richness and aboveground primary productivity, such that there is a
negative relationship between productivity and local-scale plant species richness in
terrestrial ecosystems that takes effect once an initial threshold for minimum productivity
has been reached (Sliding et al.. 2005; Gough et al.. 2000; Gross et al.. 2000; Grime.
1973). In a synthesis of long-term (>4 years) N addition experiments
(90-130 kg N/ha/yr) in open-canopy ecosystems (grasslands, tundra, etc.), Gough et al.
(2000) found that as the relative stimulation of aboveground primary productivity by the
N additions increased, there was a greater relative loss of species richness. Thus, there
was a direct linkage between the stimulation of productivity by added N and the loss of
plant species richness.
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Two meta-analyses published in 2005 synthesized data from nonforested N addition
experiments across North America to understand the role of plant functional traits versus
random effects in determining changes in community diversity (Pennings et al.. 2005;
Sliding et al.. 2005). The random-loss hypothesis of biodiversity decline suggests that
rare species are most vulnerable to disappearance as increased competition for resources
such as light eliminates less successful individuals, whereas the functional trait
hypothesis predicts that organisms with particular traits will become more successful or
vulnerable when N is added; these mechanisms could operate simultaneously (Sliding et
al.. 2005). In this synthesis, N additions increased primary production and decreased
species richness in all terrestrial ecosystems (Sliding et al.. 2005). There was also support
for random loss of species: the rarest species had a >60% chance of disappearance, while
the chance of disappearance for the most abundant species was 10%. This suggests
ecosystems with many rare species that experience increases in competition after N
additions are especially vulnerable to species loss. There was also support for the
functional trait hypothesis: N fixing forbs, shorter-statured species, and perennial plants
were more likely to be lost, although there was variation among the sites in which traits
made species the most vulnerable. Pennings et al. (2005) took a somewhat different
approach, following the fate of 20 individual species across experiments. There were
consistent responses in 10 of the 20 species, but for all but 2 species, these responses
were dependent on the combination of site productivity, species richness, functional
traits, and initial abundance (Pennings et al.. 2005). In a related synthesis of these data to
understand the environmental and experimental factors associated with the loss of species
richness, Clark et al. (2007) observed that several individual factors were almost equally
correlated to the loss of species richness, including aboveground plant production
(r = -0.50), lower soil cation exchange capacity (r = 0.48), and length of the experiment
(r = -0.57). Overall, a full multifactor structural equation model indicated that increased
risk of species loss among the study sites was tied to lower average annual minimum
temperature, low soil cation exchange capacity, and larger productivity responses to N
additions (Clark et al.. 2007). This suggests that high latitude or high elevation
ecosystems, with low cation exchange capacity (often associated with traits such as sandy
soils, low pH, low organic matter content, and highly weathered soils), and productivity
that is strongly limited to N, would be the most vulnerable to plant species loss—traits
common in alpine and Arctic tundra, among other ecosystems.
More recently, De Schriiver et al. (2011) conducted a meta-analysis of plant species
richness responses in N addition experiments conducted in forests (understory plants
only), heathlands, grasslands, tundra, and wetlands. Additions of N increased graminoid
biomass, decreased bryophyte biomass, and decreased the biomass of understory plants in
forests. The addition of N decreased species richness when analyzed across experiments;
within individual ecosystems the effect was only significant in grasslands and heathlands,
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while other ecosystems had negative effects but small sample sizes. The loss of species
richness increased with higher cumulative N loads.
A new analysis by Simkin et al. (2016) has dramatically increased our understanding of
how N deposition is altering plant biodiversity in the continental U.S. Here, Simkin et al.
(2016) gathered data on herbaceous species richness from more than 15,000 study plots
in a variety of habitats. There was a strong effect of N deposition on species richness, but
this effect differed between closed canopy and open ecosystems (i.e., forests and
nonforest). In nonforested ecosystems (grasslands, deserts, shrublands, subalpine
ecosystems), there was a positive relationship between N deposition and herbaceous
species richness at low rates of N deposition, then a decrease in species richness with
higher rates of N deposition once a threshold of 8.7 kg N/ha/yr. The effect was notably
stronger at low pH. In forests, the relationship between N deposition and herbaceous
species richness was similar, but more complex. In acidic soils, the relationship was
similar to open canopy systems. In neutral or basic soils, the relationship between N
deposition and species richness was consistently positive. Overall, these national-scale
results are consistent with the relationship between productivity and species richness
suggested by ecological theory [e.g., (Clark et al.. 2007; Sliding et al.. 2005)1 and also
provide evidence that N deposition is decreasing species richness in the U.S. via
acidification.
There are few direct analyses comparing the impacts of oxidized and reduced forms of N
deposition on biodiversity. Because NOs tends to be more readily lost to both leaching
and denitrification than NH4 (Brady and Weil. 1999). it is possible that this form of N is
less likely to accumulate in the soil and cause fewer changes in plant and microbial
communities. However, two regional-scale plant biodiversity studies in Europe found
stronger relationships between species richness and total N deposition than with NHx or
NOy deposition (Stevens et al.. 2006; Stevens et al.. 2004). Similarly, Jovan et al. (2012)
observed that lichen communities in the Los Angeles basin were best predicted by total N
deposition (as throughfall) than the deposition or gaseous concentrations of any particular
form of N. The national-scale analysis of herbaceous species richness completed by
Simkin et al. (2016) only evaluated total N deposition, not individual forms of deposition.
Thus, the existing literature supports the idea that at least vascular plant and lichen
composition are most tightly linked to total N deposition rather than the deposition of a
particular form of N, which is consistent with numerous observations across
meta-analyses that individual forms of inorganic N have similar effects on biological
processes (Table 6-1).
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6.2.3 Forests
6.2.3.1
Overstory Trees
The 2008 ISA reported that there was very little information on the effect of N deposition
on the biodiversity of overstory trees in the U.S. However, the altered growth rates
caused by N enrichment have the potential to affect forest structure and biodiversity. The
life span of many trees is 100 years or more; therefore, it is difficult to observe how
changes in growth or mortality affect biodiversity within established forests. The 2008
ISA cited evidence for boreal forest encroachment into grasslands under increased N
deposition (kochv and Wilson. 2001). Since the 2008 ISA, little new direct information
is available on the effect of N deposition on the biodiversity of overstory trees in the U.S.
or Europe. In subtropical forests in China along a rural to urban N deposition gradient of
30 to 43 kg N/ha/yr across four sites, Huang et al. (2012) found a decrease in tree
diversity with increasing N deposition, but there were also differences in management
regimes, elevation, and dominant vegetation among the study sites. There is widespread
evidence of species-specific effects of N deposition on tree growth and mortality in the
U.S. [e.g., (Dietze and Moorcroft. 2011; Thomas et al.. 2010)1. but this information has
not yet been transformed into a quantitative assessment of changes in tree community
composition. A broad-scale analysis of changes in overstory community composition as a
result of N deposition remains as a research need.
Compared to overstory trees, there was more information available in the 2008 ISA
regarding the effects of N deposition on understory plants. A major influence on the 2008
ISA was a review by Gilliam (2006). who identified nine studies on N deposition effects
on forest understory plant communities, all within the U.S. and Europe. All of the North
American studies cited by Gilliam (2006) were N addition experiments within temperate
forests in the northeastern U.S.; two of these studies found no significant changes in
community composition (Gilliam et al.. 2006; Gilliam et al.. 1994). In Sweden, there
were documented shifts in understory plant community composition along two forest N
deposition gradients that ranged from 6 to 20 kg N/ha/yr (Brunet et al.. 1998) and from 3
to 12 kg N/ha/yr (Strengbom et al.. 2001).
Many of the mechanisms through which N additions alter plant community composition
and species richness in other terrestrial ecosystems also function in forest understory
6.2.3.2
Understory Plants
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environments, including shifts in mycorrhizal communities, competitive exclusion,
increases in herbivory, and species-specific growth responses to increased N availability
(Gilliam. 2006). However, resource heterogeneity in forests can be especially high and
limited light availability can constrain the effects of competitive exclusion (Simkin et al..
2016). Since the 2008 ISA, a number of new studies of N addition and ambient
deposition effects on understory plant diversity have been conducted in temperate and
boreal forests in the U.S. and Europe, as well as in subtropical forests in China (Table
6-13). In a national-scale analysis of herbaceous species richness, Simkin et al. (2016)
found that the effect of N deposition on forest understory species richness was highly
dependent on soil pH. At all soil pH values, low rates of N deposition (~5 kg N/ha/yr)
had neutral or positive effects on species richness. At a low pH (4.5), species richness
declined at N deposition rates >11.6 kg N/ha/yr, but among neutral and basic soils there
was no point in the data set at which N deposition had a negative effect on species
richness (the analysis included deposition values up to -20 kg N/ha/yr). However, Simkin
et al. (2016) also analyzed smaller regional forest gradients dominated by maple-birch
(Acer-Betula), white oak (Quercus alba), or Douglas-fir (Pseudotsuga menziesii) trees.
At this scale, the threshold for negative deposition effects tended to be lower
(7.5-9.5 kg N/ha/yr) and the negative effects of N deposition were greatest when
temperature and precipitation were high. In a similar study that synthesized data from
>1,200 forest understory vegetation plots in northern and central Europe, Verheven et al.
(2012) did not find a significant effect of increasing N deposition on species richness.
However, the amount of N deposition received by the forests in this study was much
higher, ranging from 8.3 to 35.7 kg N/ha/yr. Further, although understory plant species
richness did not change, community composition shifted significantly away from
light-demanding species and toward nutrient-demanding species. In another study of
forest understory vegetation plots at 28 sites across Europe, Pirn bock et al. (2014) also
found that although understory plant species richness was not affected by N deposition,
plant communities became more strongly dominated by both more nutrient-demanding
species and more shade-tolerant species as N deposition rates increased beyond identified
critical loads.
There is also evidence for shifts in plant communities across local and regional N
deposition gradients. Huang et al. (2012) observed that understory plant species richness
was negatively correlated with N deposition along a rural to urban gradient (30 to
40 kg N/ha/yr) of four subtropical forests in China. At a network of 40 sugar maple forest
monitoring sites in Ontario, McPonough and Watmough (2015) observed that most of
the variability in understory plant community composition could be explained by climate
and soil factors, but that N deposition (8 to 12.9 kg N/ha/yr) explained a statistically
significant portion of the variability. However, there was no effect on understory species
richness over this relatively narrow range ofN deposition.
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Understory plant species richness was also not affected in several N addition studies in
temperate forests in the U.S. (Chapman et al.. 2016; Talhelm et al.. 2013; Jones and
Chapman. 2011). In an oak forest in the Philadelphia, PA area, Jones and Chapman
(2011) found that native understory plant diversity and richness were negatively
correlated with soil inorganic N, but not significantly impacted by N additions
(13 kg N/ha/yr). In a follow up at the same site, Chapman et al. (2016) used higher rates
of N additions (100 or 200 kg N/ha/yr as NH4NO3 for 4 years). Changes in total, native,
or invasive species cover were not detected, but N additions increased invasive species
richness in some years. Similar to the two N deposition-gradient monitoring studies in
Europe, Talhelm et al. (2013) found that although N additions did not alter understory
plant species richness, community composition was altered. Tree sapling communities
were apparently more resistant, as neither species richness nor community composition
changed in response to N additions (Talhelm et al.. 2013).
The effects of N additions on forest understory plant communities can be long lasting.
Strengbom and Nordin (2008) found significant differences in understory plant
communities in recently-harvested regenerating Swedish forests as a result of two single
additions of 150 kg N/ha 22 years and 30 years earlier. The forests that received N
decades earlier had denser understory vegetation, much less shrub cover, and much more
herb and graminoid cover. The abundance of individual species, including
ground-dwelling bryophytes and lichens, differed by as much as 20 times due to the N
additions (Strengbom and Nordin. 2008). In a related study, Hedwall et al. (2013) found
that the amount of change in understory plant community composition in regenerating
forests caused by N additions was negatively correlated with the rate of N deposition
along a Swedish deposition gradient of 4.4 to 16.1 kg N/ha/yr.
Table 6-13 Forest plant diversity responses to nitrogen added via atmospheric
deposition or experimental treatments.
Reference Location
Study
Nitrogen
Ambient Addition
Deposition Rate Duration
Vegetation or Addition (kg N/ha/yr) (yr)
Effect of
Additional
Endpoint Nitrogen
Simkin et al.
Contiguous Forests
Ambient 1.3-17.9 n/a
Understory Low soil
species pH:
(2016)
U.S.
richness decrease;
high soil
2H:
increase
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Table 6-13 (Continued): Forest plant diversity responses to nitrogen added via
atmospheric deposition or experimental treatments.
Reference
Study
Location
Vegetation
Ambient
Deposition
or Addition
Nitrogen
Addition
Rate
(kg N/ha/yr)
Duration
(yr)
Endpoint
Effect of
Additional
Nitrogen
Verheven et al.
(2012)
Central and
northern
Europe
Temperate
deciduous
forests
Ambient
8.3-35.7
n/a
Understory
species
richness
Not
significant
Dirnbock et al.
(2014)
Europe
Boreal,
temperate, and
Mediterranean
forests
Ambient
0.6-20.2
n/a
Understory
species
richness
Not
significant
McDonouah and
Watmouah
(2015)
Ontario,
Canada
Northern
hardwood
(Acer
saccharum)
Ambient
8.3-12.9
n/a
Understory
species
richness
Not
significant
Jones and
Chapman
(2011)
Pennsylvania
Mixed oak
(Quercus)
Addition
13
1
Understory
species
richness
Not
significant
Talhelm et al.
(2013)
Michigan (four
sites)
Northern
hardwood
(Acer
saccharum)
Addition
30
+ 10
Understory
species
richness
Not
significant
Chapman et al.
(2016)
Pennsylvania
Mixed oak
(Quercus)
Addition
100, 200
4
Understory
species
richness
Not
significant
Huana et al.
(2012)
China
(southern
tropical)
Moist
subtropical
evergreen
broadleaf
forests
Ambient
30.1-43.1
n/a
Understory
species
richness
Decrease
Lu et al.
(2011c)
China
(southern
tropical)
Pine and
broadleaf
(Pinus
massoniana,
Schima
superba)
Addition
50, 100 (40
ambient)
6
Understory
species
richness
Not
significant
Lu et al. (2010)
China
(southern
tropical)
Evergreen
tropical moist
forest
Addition
50, 100, 150
(35 ambient)
6
Understory
species
richness
Decrease
Huana et al.
(2012)
China
(southern
tropical)
Moist
subtropical
evergreen
broadleaf
forests
Ambient
30.1-43.1
n/a
Overstory
species
richness
Decrease
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Table 6-13 (Continued): Forest plant diversity responses to nitrogen added via
atmospheric deposition or experimental treatments.
Reference
Study
Location
Vegetation
Ambient
Deposition
or Addition
Nitrogen
Addition
Rate
(kg N/ha/yr)
Duration
(yr)
Endpoint
Effect of
Additional
Nitrogen
Talhelm et al.
(2013)
Michigan (four
sites)
Northern
hardwood
(Acer
saccharum)
Addition
30
+ 10
Tree
sapling
species
richness
Not
significant
Verheven et al.
(2012)
Central and
northern
Europe
Temperate
deciduous
forests
Ambient
8.3-35.7
n/a
Understory
community
composition
Change
Dirnbock et al.
(2014)
Europe
Boreal,
temperate, and
Mediterranean
forests
Ambient
0.6-20.2
n/a
Understory
community
composition
Change
McDonouah and
Watmouah
(2015)
Ontario,
Canada
Northern
hardwood
(Acer
saccharum)
Ambient
8.3-12.9
n/a
Understory
community
composition
Change
Hedwall et al.
(2013)
Sweden
Norway spruce
(Picea abies)
Ambient
4.4-16.1
n/a
Understory
community
composition
Change
Chapman et al.
(2016)
Pennsylvania
Mixed oak
(Quercus)
Addition
100, 200
4
Understory
community
composition
Not
significant
Strenabom and
Nordin (2008)
Sweden
Scots pine,
Norway
spruce, birch
(Pinus
sylvestris,
Picea abies,
Betuia)
Addition
150 (twice)
Additions
22 and
30 years
prior to
surveys
Understory
community
composition
Change
Talhelm et al.
(2013)
Michigan (four
sites)
Northern
hardwood
(Acer
saccharum)
Addition
30
+ 10
Understory
plant
community
composition
Change
Talhelm et al.
(2013)
Michigan (four
sites)
Northern
hardwood
(Acer
saccharum)
Addition
30
+ 10
Tree
sapling
community
composition
Not
significant
Jones and
Chapman
(2011)
Pennsylvania
Mixed oak
(Quercus)
Addition
13
1
Understory
species
diversity
Not
significant
Talhelm et al.
(2013)
Michigan (four
sites)
Northern
hardwood
(Acer
saccharum)
Addition
30
+ 10
Understory
species
diversity
Not
significant
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Table 6-13 (Continued): Forest plant diversity responses to nitrogen added via
atmospheric deposition or experimental treatments.
Reference
Study
Location
Vegetation
Ambient
Deposition
or Addition
Nitrogen
Addition
Rate
(kg N/ha/yr)
Duration
(yr)
Endpoint
Effect of
Additional
Nitrogen
Strenabom and
Nordin (2008)
Sweden
Scots pine,
Norway
spruce, birch
(Pinus
sylvestris,
Picea abies,
Betula)
Addition 150 (twice)
Additions
22 and
30 years
prior to
surveys
Understory
species
diversity
Decrease
ha = hectare; kg = kilogram; N = nitrogen; n/a = not applicable; yr = year.
Note: Single studies are reported more than once if multiple endpoints are measured. Only statistically significant effects are listed
as increases or decreases.
6.2.3.3 Mycorrhizal and Microbial Diversity
Soils contain a high amount of microbial diversity (Lvnch et al. 2012). but this diversity
may not be evenly distributed among phylogenetic groups. For instance, using 97%
sequence identity to cluster operational taxonomic units (OTUs) from 16S rRNA
pyrosequencing, Turlapati et al. (2013) observed that 2% of the OTUs observed in
surface soils at Harvard Forest contained >50% of the total sequences, while about 10%
of total sequences contained 80% of the OTUs. This suggests that many of the individual
soil microbes are either from the same or closely related taxonomic groups and that there
a large number of relatively rare taxonomic groups. However, in reanalyzing these data
with a more detailed oligotype sequence clustering approach, Turlapati et al. (2015)
found that microbial taxonomic groups were more evenly distributed in terms of
population structure.
Of the forests studies quantifying overall microbial community composition that were
identified, all four observed shifts in response to N added experimentally or via
atmospheric deposition (Table 6-14). Much of the available information about changes in
microbial community composition published since 2008 has been about changes in
fungal communities, including mycorrhizal species. Seven studies that quantified the
response of forest fungal communities to N additions were identified for this assessment;
one study had site-specific results, but N additions changed community composition in
four of the remaining six studies (Table 6-14). Among studies of ectomycorrhizal fungi,
N additions caused changes in six out of seven studies, including in four studies along
ambient N deposition gradients (Table 6-15). There is less information about N additions
change arbuscular mycorrhizal communities (Table 6-16). with only two experiments,
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one in Ecuador (Camenzind et al.. 2014) that observed no effect of added N
(50 kg N/ha/yr for 3 years) on community composition and another in northern hardwood
forests in Michigan where the effect of added N (30 kg N/ha/yr for +12 years) on
community composition was dependent on the measurements technique (van Diepen et
al.. 2013; van Diepen et al.. 2011). Although shifts in fungal community composition are
widely reported, these shifts are not necessarily the same, even in similar ecosystems.
Allison et al. (2010) conducted an N addition experiment in a recently burned boreal
forest in Alaska. Here, the forest microbial community is dominated by fungi in the
Ascomycota and N additions increased the abundance of Ascomycota. In contrast,
Allison et al. (2008) conducted a similar experiment in a mature boreal forest in Alaska
and observed that the microbial community was dominated by Basidiomycota and N
additions did not change the overall abundance of fungi in this phyla. However, in both
ecosystems, N additions greatly changed the relative abundance of individual taxa (orders
and families) within these phyla (Allison et al.. 2010; Allison et al.. 2008). Individual
components of microbial communities also appear to react to N additions at different
speeds. In a long-term forest N addition in Switzerland, Gillet et al. (2010) observed that
both ectomycorrhizal and saprobic fungal communities responded to an increase in soil N
input, but the ectomycorrhizal community rapidly decreased in species richness, whereas
the saprobic community was less affected. The response was highly species specific,
especially for the saprobic community. As with lichens and plants, the sensitivity of
ectomycorrhizal fungi appears to vary taxonomically, with these taxonomic differences
apparently related to differences in functional traits such as organic N acquisition
(Lilleskov et al.. 2011).
Table 6-14 Forest microbial biodiversity responses to experimental nitrogen
additions.
Ambient Nitrogen
Deposition Addition Effect of
Study or Rate (kg Duration Additional
Reference Location Vegetation Addition N/ha/yr) (yr) Endpoint Nitrogen
Zechmeister- Europe Conifer and Ambient 2-40 n/a Microbial Change
Boltenstern et broadleaf community
al. (2011) forests composition
Hobbie et al. Minnesota
(2012) (Cedar Creek)
Oak and pine Addition 100
forests
(Quercus
ellipsoidalis,
Pinus
strobus)
5 Microbial Change
community
composition
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Table 6-14 (Continued): Forest microbial biodiversity responses to experimental
nitrogen additions.
Reference
Study
Location
Vegetation
Ambient
Deposition
or
Addition
Nitrogen
Addition
Rate (kg
N/ha/yr)
Duration
(yr)
Endpoint
Effect of
Additional
Nitrogen
Zhao et al. China (Tibetan Spruce-fir
(2014a) Plateau) (Picea
asperata,
Abies
faxoniana)
Addition
250
Microbial
community
composition
Change
van Diepen et
al. (2010)
Michigan (Ml
gradient)
Northern
hardwood
forests (Acer
saccharum)
Addition
30
12
Microbial
community
composition
Change
Hesse et al.
(2015)
Michigan (Ml
gradient)
Northern
hardwood
forests (Acer
saccharum)
Addition
30
16
Bacterial
community
composition
Not
significant
Turlapati et al.
(2013)
Massachusetts Temperate
(Harvard oak forest
Forest) (Quercus
rubra, Q.
velutina)
Addition
50, 150
22
Bacterial
community
composition
Change
Turlapati et al.
(2015)
Massachusetts Temperate
(Harvard oak forest
Forest) (Quercus
rubra, Q.
velutina)
Addition
50, 150
22
Bacterial
community
composition
Change
Krumins et al.
(2009)
Florida and
New Jersey
Scrub oak
forests
(Quercus
myrtifolia, Q.
ilicifolia)
Addition
35, 70
Bacterial
community
composition
Not
significant
Eisenlord et al. Michigan (Ml
(2013) gradient)
Northern
hardwood
forests (Acer
saccharum)
Addition
30
16
Actinobacterial
community
composition
Three sites:
change;
one site:
not
significant
Edwards et al.
(2011)
Michigan (Ml
gradient)
Northern
hardwood
forests (Acer
saccharum)
Addition
30
14
Fungal
community
composition
Not
significant
Eisenlord et al.
(2013)
Michigan (Ml
gradient)
Northern
hardwood
forests (Acer
saccharum)
Addition
30
16
Fungal
community
composition
Two sites:
decrease;
two sites:
change
Hesse et al.
(2015)
Michigan (Ml
gradient)
Northern
hardwood
forests (Acer
saccharum)
Addition
30
16
Fungal
community
composition
Change
February 2017
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Table 6-14 (Continued): Forest microbial biodiversity responses to experimental
nitrogen additions.
Reference
Study
Location
Vegetation
Ambient
Deposition
or
Addition
Nitrogen
Addition
Rate (kg
N/ha/yr)
Duration
(yr)
Endpoint
Effect of
Additional
Nitrogen
Allison et al.
(2008)
Alaska
Boreal forest
(Picea
mariana)
Addition
140
5
Fungal
community
composition
Change
Allison et al.
(2010)
Alaska
Boreal forest
(Picea
mariana,
Festuca
altaica)
Addition
114
7
Fungal
community
composition
Change
Krumins et al.
(2009)
Florida and
New Jersey
Scrub oak
forests
(Quercus
myrtifolia, Q.
ilicifolia)
Addition
35, 70
1
Fungal
community
composition
Not
significant
Gillet et al.
(2010)
Switzerland
Norway
spruce (Picea
abies)
Addition
150
12
Saprobic fungal
community
composition
Change
Zechmeister-
Boltenstern et
al. (2011)
Europe
Conifer and
broadleaf
forests
Ambient
2-40
n/a
Bacterial/fungi
ratio
Increase
Allison et al.
(2008)
Alaska
Boreal forest
(Picea
mariana)
Addition
140
5
Fungal diversity
Not
significant
Eisenlord et al.
(2013)
Michigan (Ml
gradient)
Northern
hardwood
forests (Acer
saccharum)
Addition
30
16
Actinobacterial
gene diversity
Two sites:
decrease;
two sites:
not
significant
Eisenlord et al.
(2013)
Michigan (Ml
gradient)
Northern
hardwood
forests (Acer
saccharum)
Addition
30
16
Actinobacterial
gene functional
richness
Two sites:
decrease;
two sites:
not
significant
Eisenlord et al.
(2013)
Michigan (Ml
gradient)
Northern
hardwood
forests (Acer
saccharum)
Addition
30
16
Fungal gene
diversity
Two sites:
decrease;
two sites:
not
significant
Eisenlord et al.
(2013)
Michigan (Ml
gradient)
Northern
hardwood
forests (Acer
saccharum)
Addition
30
16
Fungal gene
functional
richness
Two sites:
decrease;
two sites:
not
significant
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9
10
11
12
13
14
Table 6-14 (Continued): Forest microbial biodiversity responses to experimental
nitrogen additions.
Reference
Study
Location
Vegetation
Ambient
Deposition
or
Addition
Nitrogen
Addition
Rate (kg
N/ha/yr)
Duration
(yr)
Endpoint
Effect of
Additional
Nitrogen
Gillet etal.
(2010)
Switzerland
Norway
spruce (Picea
abies)
Addition
150
12
Saprobic fungal
species
richness
Decrease
Krumins et al.
(2009)
Florida and
New Jersey
Scrub oak
forests
(Quercus
myrtifolia, Q.
ilicifolia)
Addition
35, 70
Fungal
morphotype
richness
Not
significant
Turlapati et al. Massachusetts Temperate Addition
(2013) (Harvard oak forest
Forest) (Quercus
rubra, Q.
velutina)
50, 150 22 Bacterial Increase
richness
Hesse et al. Michigan (Ml Northern Addition 30 16 Bacterial Not
(2015) gradient) hardwood richness significant
forests (Acer
saccharum)
Hesse et al. Michigan (Ml Northern Addition 30 16 Fungal richness Not
(2015) gradient) hardwood significant
forests (Acer
saccharum)
ha = hectare; kg = kilogram; N = nitrogen; yr = year.
Note: Single studies are reported more than once if multiple endpoints are measured. Only statistically significant effects are listed
as increases or decreases.
Decreases in taxonomic richness among ectomycorrhizal fungi appear to be less common
than changes in community composition. Of the ten identified studies, decreases in
richness were observed only in six studies (Table 6-15). Only two studies of taxonomic
richness in overall fungal communities were identified for this assessment: one study saw
changes at two of four study sites (Eisenlord et al.. 2013). while the other study saw no
effect (Krumins et al.. 2009).
In Scotland, Jarvis et al. (2013) analyzed fungal communities from 15 seminatural Scots
pine (Pinus sylvestris) forests and found changes in abundance of Cortinarius species at
higher N deposition (9.8 kg N/ha/yr). Krumins et al. (2009) evaluated the effects of N
addition on soil bacteria and fungi in two similar scrub oak forests (Florida and New
Jersey). Bacterial colony type richness responded differently to N treatment in the
different sites, but ectomycorrhizal morphotype richness was not affected by N or
location. Results imply that bacterial communities may be more sensitive than fungi to
intense pulses of N in sandy soils.
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7
8
9
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20
21
22
23
kjoiler et al. (2012) observed changes in the ectomycorrhizal community composition
and a loss of ectomycorrhizal species richness across an N deposition gradient in
Denmark from 27 to 43 kg N/ha/yr at the edge of a spruce forest. In Scotland, Jarvis et al.
(2013) analyzed ectomycorrhizal fungal communities from 15 seminatural Scots pine
forests and found changes in abundance of Cortinarius species at higher N deposition
(9.8 kg N/ha/yr). In red spruce-dominated forests in the northeastern U.S., Lilleskov et al.
(2008) observed changes in ectomycorrhizal communities over a much lower N
deposition gradient, ranging from 2.8 to 7.9 kg N/ha/yr of wet deposition. Nitrogen
deposition was positively related to fine root N concentrations and those root N
concentrations had positive relationships with the abundance of three of the
ectomycorrhizal fungal morphotypes, negative relationships with three morphotypes, and
ambiguous relationships with three other morphotypes. In Scots pine (Pinus sylvestris)
forests in Germany and the U.K. arrayed along an N deposition gradient ranging from 4.6
to 28.6 kg N/ha/yr, Cox et al. (2010) used DNA extracted from fine roots and group
sequences at 97% similarity to assess changes in ectomycorrhizal community
composition. Similar to Lilleskov et al. (2008). N deposition was positively correlated to
foliar N concentrations and then foliar N was linked to shifts in mycorrhizal community
structure. In particular, foliar N concentrations were significantly negatively correlated to
ectomycorrhizal richness. Of the 35 taxa that occurred widely across the gradient, 11
showed significant responses to increased N availability: 6 taxa increased and 5 taxa
decreased with greater N availability (Cox et al.. 2010). Thus, the effects ofN deposition
on ectomycorrhizal community composition observed by Lilleskov et al. (2008) and Cox
et al. (2010) were indirect.
February 2017
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Table 6-15 Ectomycorrhizal biodiversity responses to nitrogen added via
atmospheric deposition or experimental N additions.
Reference
Study
Location
Vegetation
Ambient
Deposition
or Addition
Nitrogen
Addition
Rate (kg
N/ha/yr)
Duration
(yr)
Endpoint
Effect of
Additional
Nitrogen
Ki0ller et al.
(2012)
Denmark
Norway
spruce (Picea
abies)
Ambient
27-43
n/a
Community
composition
Change
Jarvis et al.
(2013)
Scotland,
U.K.
Scots pine
(Pinus
sylvestris)
Ambient
3.1-9.9
n/a
Community
composition
Change
Lilleskov et al.
(2008)
Northeastern
U.S.
Red spruce
(Picea
rubens)
Ambient
2.8-7.9 (wet
only)
n/a
Community
composition
Change
(indirect)
Cox et al. (2010)
Germany,
U.K.
Scots pine
(Pinus
sylvestris)
Ambient
4.6-28.6
n/a
Community
composition
Change
(indirect)
Wriaht et al.
(2009)
British
Columbia,
Canada
Western
hemlock
(Tsuga
heterophylla)
Addition
300 (once)
7 yr
recovery
Community
composition
Not
significant
Avis et al. (2008)
Illinois
Oak
(Quercus
alba, Q.
rubra)
Addition
21
4
Community
composition
Change
Gillet et al.
(2010)
Switzerland
Norway
spruce (Picea
abies)
Addition
150
12
Sporocarp
community
composition
Change
Suz et al. (2014)
Europe (nine
countries)
Oak
(Quercus
robur, Q.
petraea)
Ambient
5.1-35.5
n/a
Community
evenness
Decrease
Cox et al. (2010)
Germany,
U.K.
Scots pine
(Pinus
sylvestris)
Ambient
4.6-28.6
n/a
Taxonomic
richness
Decrease
(Indirect)
Ki0ller et al.
(2012)
Denmark
Norway
spruce (Picea
abies)
Ambient
27-43
n/a
Species
richness
Decrease
Suz et al. (2014)
Europe (nine
countries)
Oak
(Quercus
robur, Q.
petraea)
Ambient
5.1-35.5
n/a
Species
richness
Decrease
February 2017
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Table 6-15 (Continued): Ectomycorrhizal biodiversity responses to nitrogen
added via atmospheric deposition or experimental N
additions.
Reference
Study
Location
Vegetation
Ambient
Deposition
or Addition
Nitrogen
Addition
Rate (kg
N/ha/yr)
Duration
(yr)
Endpoint
Effect of
Additional
Nitrogen
Jarvis et al.
(2013)
Scotland,
U.K.
Scots pine
(Pinus
sylvestris)
Ambient
3.1-9.9
n/a
Species
richness
Not
significant
Wriaht et al.
(2009)
British
Columbia,
Canada
Western
hemlock
(Tsuga
heterophylla)
Addition
300 (once)
7 yr
recovery
Species
richness
Not
significant
Avis et al. (2008)
Illinois
Oak
(Quercus
alba, Q.
rubra)
Addition
21
4
Species
richness
Decrease
Krumins et al.
(2009)
Florida and
New Jersey
Scrub oak
forest
(Quercus
myrtifolia, Q.
ilicifolia)
Addition
35, 70
1
Morphotype
richness
Not
significant
Gillet et al.
(2010)
Switzerland
Norway
spruce (Picea
abies)
Addition
150
12
Sporocarp
richness
Decrease
Hasselquist and
Hoabera (2014)
Sweden
Scots pine
(Pinus
sylvestris)
Addition
35, 70
40, 2 yr
recovery
for 70 kg
treatment
Sporocarp
richness
Decrease
Hasselquist and
Hoabera (2014)
Sweden
Scots pine
(Pinus
sylvestris)
Addition
110
20; 15 yr
recovery
Sporocarp
richness
Not
significant
Hasselauist and
Hoabera (2014)
Sweden
Scots pine
(Pinus
sylvestris)
Addition
20, 100
6
Sporocarp
richness
Not
significant
at 20;
decrease at
100
Ha = hectare; kg = kilogram; N = nitrogen; n/a = not applicable; yr = year.
Note: Single studies are reported more than once if multiple endpoints are measured. Only statistically significant effects are listed
as increases or decreases.
1 In two oak (Quercus) forests near Chicago, Avis et al. (2008) quantified changes in
2 ectomycorrhizal community composition in response to N additions (21 kg N/ha/yr
3 beginning in 2003) from 2004 to 2006 using morphological and molecular techniques.
4 The N additions did not impact ectomycorrhizal taxonomic richness when expressed at
5 the soil core or root sampling scale, but significantly decreased taxonomic richness at the
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stand scale. In particular, these differences in richness were the result of a loss in rare
taxa. Also in oak forests, Krumins et al. (2009) evaluated the effects of N addition on soil
bacteria and fungi in two similar scrub oak forests (Florida and New Jersey). Bacterial
colony type richness responded differently to N treatment in the different sites, but
ectomycorrhizal morphotype richness was not affected by N or location.
Overall, less is known about how forest bacterial community composition responds to N
additions, with only a few identified studies since 2008 (Table 6-14). At the Harvard
Forest long-term N addition study in Massachusetts (50 and 150 kg N/ha/yr), Turlapati et
al. (2015); (Turlapati et al.. 2013) used molecular techniques to assess changes in
bacterial community composition. Using a 97% sequence identity approach to clustering
OTUs, Turlapati et al. (2013) found the chronic N additions caused major changes in the
bacterial phyla of Acidobacteria, Proteobacteria, and Verrucomicrobia. Using the more
detailed oligotype sequence clustering approach, Turlapati et al. (2015) observed five
genera that exclusively appeared in N treated soils (Aquabacterium, Nitrosospira,
Yersinia, Legionella, and Niabella) and eight genera that were present only in the control
plots (Comamonas, Microbacterium, Mycetocola, Brochothrix, Flavobacterium,
Pedobacter, Sphingobacterium, and Terrimonas). However, the N addition treatments
also caused shifts in community structure within most genera. As with Fiereretal.
(2012). microbial communities in the mineral soil were less affect by the N additions than
communities in the organic soil.
Table 6-16
Arbuscular mycorrhizal responses to nitrogen added via
atmospheric deposition or experimental treatments.
Reference
Study
Location
Vegetation
Ambient
Deposition
or Addition
Nitrogen
Addition
Rate (kg
N/ha/yr)
Duration
(yr)
Endpoint
Effect of
Additional
Nitrogen
van Diepen et al.
(2011)
Michigan
(four sites)
Sugar maple
(Acer
saccharum)
Addition
30
13
Community
composition
Change
van Diepen et al.
(2013)
Michigan
(four sites)
Sugar maple
(Acer
saccharum)
Addition
30
14
Community
composition
Not
significant
Camenzind et al.
(2014)
Ecuador
Evergreen
tropical forest
Addition
50
3
Community
composition
Not
significant
February 2017
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Table 6-16 (Continued): Arbuscular mycorrhizal responses to nitrogen added via
atmospheric deposition or experimental treatments.
Reference
Study
Location
Vegetation
Ambient
Deposition
or Addition
Nitrogen
Addition
Rate (kg
N/ha/yr)
Duration
(yr)
Endpoint
Effect of
Additional
Nitrogen
van Diepen et al.
(2011)
Michigan
(four sites)
Sugar maple
(Acer
saccharum)
Addition
30
13
Taxonomic
diversity
Three sites:
not
significant;
one site:
decrease
van Diepen et al.
(2013)
Michigan
(four sites)
Sugar maple
(Acer
saccharum)
Addition
30
14
Taxonomic
richness
Decrease
Camenzind et al.
(2014)
Ecuador
Evergreen
tropical forest
Addition
50
3
Taxonomic
richness
Decrease
Chen et al. (2014) China
Steppe
grassland
Addition
100
Soil Decrease
microbial
phylotype
richness
Chen et al. (2014) China
Steppe Addition 100
grassland
Soil Not
microbial significant
phylotype
diversity
Chen et al. (2014) China
Steppe Addition 100
grassland
Plant- Not
associated significant
microbial
phylotype
richness
Chen et al. (2014) China
Steppe Addition 100
grassland
Plant- Not
associated significant
microbial
phylotype
diversity
ha = hectare; kg = kilogram; N = nitrogen; yr = year.
Note: Single studies are reported more than once if multiple endpoints are measured,
as increases or decreases.
Only statistically significant effects are listed
6.2.3.4 Arthropod Diversity
1 Arthropods can be key components of forest productivity and nutrient cycling because
2 they can feed on living plant tissues, plant litter, or on litter-degrading fungi, and
3 arthropod communities can be directly or indirectly altered by changes in plant
4 productivity and chemistry (Gan et al.. 2014; Throop and Lcrdau. 2004). Consequently,
5 recent research has quantified the response of arthropods to added N (Table 6-17). Both
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21
22
23
24
25
26
27
28
29
before and after the 2008 ISA, Eatough Jones and colleagues published a series of studies
on how N air pollution altered plant-associated insect communities in mixed conifer
forests outside Los Angeles, California (Jones etal.. 2011; Jones et al.. 2008; Jones and
Paine. 2006; Jones et al.. 2004). Jones et al. (2008) found that insect herbivore
communities on California black oak (Quercus kellogii) trees did not change in response
to several years of N additions (150 kg N/ha/yr) at a relatively unpolluted and dry site,
but were altered by N additions at a wetter site that received more ambient N deposition.
Jones et al. (2011) found a similar response for insect herbivore communities associated
with bracken fern plants at these sites, with no change in insect taxonomic richness at the
dry and low-deposition site and increased richness at the wetter, higher deposition site.
This contrasts with earlier research at these sites on bark beetle activity, which was
stimulated by N additions at the low deposition site and suppressed by N additions at the
high-deposition site (Jones et al.. 2004). Notably, as with plant productivity responses in
grassland and arid environments, the effects of added N on insect abundance and
diversity appeared to be strongly dependent on climate (Jones et al.. 2011).
Gan etal. (2013) and Gan et al. (2014) quantified changes in the abundance and
community composition of soil microarthropods and trophic position of soil-dwelling
oribatid mites at the same four northern hardwoods forests in which Talhelm et al. (2013)
quantified changes in understory plant composition. The overall abundance of
microarthropods declined by approximately 45% in response to N additions, a change
that was attributed to changes in soil food webs as a consequence of previously
documented decreases in litter decomposition (Zak et al.. 2008). decreases in mycorrhizal
productivity (van Diepen et al.. 2010). and shifts in the microbial community
composition (van Diepen et al.. 2013; Edwards et al.. 2011; van Diepen et al.. 2011).
More specifically, Gan etal. (2013) observed decreases in two orders of detritivores
(Oribatida, Collembola) and one order of predaceous mites (Mesostigmata), with the
largest decline in the oribatid mites. The decrease in oribatid mites did not affect species
richness or their trophic position, but there was a shift in the community composition
(Gan et al.. 2014. 2013).
February 2017
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Table 6-17 Arthropod responses to experimental nitrogen additions.
Nitrogen
Ambient
Addition
Effect of
Study
Deposition
Rate (kg
Duration
Additional
Reference Location
Vegetation
or Addition
N/ha/yr)
(yr)
Endpoint
Nitrogen
Gan et al. (2013) Michiaan (four
Northern
Addition
30
18
Soil oribatid
Not
sites)
hardwoods
mite species
significant
forests (Acer
richness
saccharum)
Jones et al. (2011) California
Bracken fern
Addition
150
3
Insect
Low deD
(southern CA,
(Pteridium
herbivore
site: not
two sites)
aquilinum) in
taxonomic
significant;
mixed conifer
richness
hiah deD
forests
site:
increase
Jones et al. (2008) California
California
Addition
150
3-4
Insect
Low deD
(southern CA,
black oak
herbivore
site: not
two sites)
(Quercus
community
significant;
kellogii) in
composition
hiah deD
mixed conifer
site: chanae
forests
Gan et al. (2013) Michiaan (four
Northern
Addition
30
18
Soil oribatid
Change
sites)
hardwoods
mite
forests (Acer
community
saccharum)
composition
Jones et al. (2011) California
Bracken fern
Addition
150
3
Insect
Low deo
(southern CA,
(Pteridium
herbivore
site: not
two sites)
aquilinum) in
abundance
significant;
mixed conifer
hiah deo
forests
site:
decrease
Gan et al. (2013) Michiaan (four
Northern
Addition
30
18
Soil oribatid
Decrease
sites)
hardwoods
mite
forests (Acer
abundance
saccharum)
Gan et al. (2014) Michiaan (four
Northern
Addition
30
18
Soil oribatid
Not
sites)
hardwoods
mite trophic
significant
forests (Acer
position
saccharum)
Wissinaer et al.
California
Creosote and Ambient
2-12
n/a
Harvester ant Increase
(2014)
(Mojave)
bursage
(Messor
shrublands
pergandei)
(Larrea
nest density
tridentata,
Ambrosia
dumosa)
February 2017
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Table 6-17 (Continued): Arthropod responses to experimental nitrogen additions.
Nitrogen
Ambient
Addition
Effect of
Study
Deposition
Rate (kg
Duration
Additional
Reference
Location
Vegetation
or Addition
N/ha/yr)
(yr)
Endpoint
Nitrogen
Wissinaer et al.
California
Creosote and
Ambient
2-12
n/a
Harvester ant
Decrease
(2014)
(Mojave)
bursage
(Messor
shrublands
pergandei)
(Larrea
nest size
tridentata,
Ambrosia
dumosa)
Bishop et al.
Washington
Primary
Addition
78
3
Total arthropod Not
(2010)
(Mt. St.
successional
abundance
significant
Helens)
alpine
meadow
Bishop et al.
Washington
Primary
Addition
78
5
Orthoptera
Increase
(2010)
(Mt. St.
successional
abundance
Helens)
alpine
meadow
Eisenhauer et al.
Minnesota
Prairie
Addition
40
14
Nematode
Three auilds:
(2013)
(Cedar Creek)
abundance
not
significant;
one quild:
increase;
one quild:
decrease
Eisenhauer et al.
Minnesota
Prairie C3
Addition
40
14
Mesofauna
Not
(2013)
(Cedar Creek)
and C4
abundance
significant
grasses,
(arthropods—
forbs,
five orders)
legumes
Eisenhauer et al.
Minnesota
Prairie C3
Addition
40
14
Nematode
Not
(2013)
(Cedar Creek)
and C4
richness
significant
grasses,
forbs,
legumes
Eisenhauer et al.
Minnesota
Prairie C3
Addition
40
14
Mesofauna
Not
(2013)
(Cedar Creek)
and C4
diversity
significant
grasses,
(arthropods—
forbs,
five orders)
legumes
Eisenhauer et al.
Minnesota
Prairie C3
Addition
40
14
Microarthropod Decrease
(2012)
(Cedar Creek)
and C4
richness
grasses,
forbs,
legumes
February 2017
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Table 6-17 (Continued): Arthropod responses to experimental nitrogen additions.
Reference
Study
Location
Vegetation
Ambient
Deposition
or Addition
Nitrogen
Addition
Rate (kg
N/ha/yr)
Duration
(yr)
Endpoint
Effect of
Additional
Nitrogen
Cesarz et al.
(2015)
Minnesota
(Cedar Creek)
Prairie C3
and C4
grasses,
forbs,
legumes
Addition
40
14
Nematode
community
composition
Change
Zehnder and
Hunter (2008)
Georgia
Milkweed
(Asclepias
tuberosa)
Addition
25, 40
0.1
Aphid
population
growth rate
Increase
Zehnder and
Hunter (2008)
Georgia
Milkweed
(Asclepias
tuberosa)
Addition
25, 40
0.1
Aphid carrying
capacity
Increase
Pavne et al.
(2012)
U.K.
Heathland
(Calluna
vulgaris)
Addition
10, 20, 40,
80, 120
11,
21
Enchytraeid
worm
abundance
Not
significant
Cha et al. (2010)
Pennsylvania
Northern red
oak (Quercus
rubra)
Addition
200
1
Deer browsinq One site:
herbivory increase;
one site:
decrease
Cha et al. (2010)
Pennsylvania
Northern red
oak (Quercus
rubra)
Addition
200
1
Chewing insect Increase
herbivory
Cha et al. (2010)
Pennsylvania
Northern red
oak (Quercus
rubra)
Addition
200
1
Galling insect
herbivory
Not
significant
ha = hectare; kg = kilogram; N = nitrogen; yr = year.
Note: Single studies are reported more than once if multiple endpoints are measured. Only statistically significant effects are listed
as increases or decreases.
6.2.4 Alpine and Arctic Tundra
1 There was consistent and coherent evidence in the 2008 ISA indicating that alpine plant
2 communities are among the terrestrial communities most sensitive to atmospheric N
3 deposition. The previous assessment identified a number of factors that made these
4 ecosystems vulnerable to N deposition, including low rates of primary production, short
5 growing seasons, low temperature, and low rates of N mineralization (Bowman and Fisk.
6 2001; Bowman and Steltzer. 1998; Fisk et al.. 1998; Bowman. 1994; Bowman et al..
7 1993). Alpine plants are broadly N limited and increased N inputs have been observed to
8 cause changes in alpine growth and species composition (Bowman et al.. 2006; Bowman
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and Steltzer. 1998; Vitousek et al.. 1997). Alpine plant communities have also developed
under conditions of low nutrient supply, in part because soil-forming processes are poorly
developed, and this was also thought to contribute to their N sensitivity.
Many of the alpine tundra ecosystems in the U.S. are found in the western U.S.,
particularly in the Rocky Mountains, Cascade Mountains, and the Sierra Nevada.
Atmospheric deposition tends to be low in the western U.S., but high elevation areas can
be hot spots for N deposition. In several studies, the capacity of Colorado Rocky
Mountain alpine catchments to sequester N was exceeded at input levels of 10 kg N/ha/yr
or less [e.g., (Baron et al.. 1994)1. Similarly, relatively low N addition rates can cause
shifts in alpine plant communities. Bowman et al. (2006) estimated that changes in the
abundance of Carex rupestris occurred at deposition rates of 4 kg N/ha/yr and changes
alpine tundra community composition occurred at deposition rates of approximately
10 kg N/ha/yr. In Europe, critical loads for alpine plant communities were estimated to be
between 5 and 15 kg N/ha/yr (Bobbink et al.. 2003).
Since 2008, there was further research in the U.S. on the effects of added N on plant
communities in Colorado at the Niwot Ridge Long-Term Ecological Research Site and in
Rocky Mountain National Park (RMNP), as well as on Mount St. Helens in Washington
(Table 6-18). In RMNP, Bowman et al. (2012) conducted a 4-year study in a dry alpine
meadow ecosystem where N was added at rates of 5, 10 and 30 kg N/ha/yr, while
ambient N deposition was 4 kg N/ha/yr. No shifts in species richness or diversity were
observed in response to the N additions; however, Carex rupestris increased in cover
from 34 to 125% in response to the treatments. More broadly, McDonnell et al. (2014a)
used the ForSAFE-VEG model to assess changes in vegetation cover in subalpine
ecosystems in RMNP since 1900 and forecast the changes through the end of the
21st century as a result of N deposition and climate change scenarios. Based on the model
output, plant community composition changed by 10% over the past 100 years as a result
of increases in N deposition, with increases in graminoid species and decreases in forb
species. Over the next 100 years, forecasted changes in N deposition and climate factors
are predicted to increase tree cover. Plant diversity increased with N additions
(78 kg N/ha/yr for 5 years) on Mount St. Helens, but this plant community was growing
on very N poor soils formed following the volcanic eruption there in 1980 (Bishop et al..
2010).
Internationally, plant diversity research has been conducted in Arctic ecosystems in
Scandinavia and north Atlantic Europe (Greenland, Iceland, northern Great Britain, etc.)
and in alpine ecosystems in Switzerland and China. In a subalpine grassland in the Swiss
Alps, Bassin et al. (2013) observed that 7 years of N additions of 5 to 50 kg N/ha/yr
decreased plant diversity and changed plant community composition. Arens et al. (2008)
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found no effects of N additions (5, 10, or 50 kg N/ha/yr) on plant community
composition over three years in dwarf shrub/herb tundra ecosystems in Greenland. In
Sweden, Sundqvist et al. (2014) did not observe any change in plant species diversity or
plant species richness as a result of three years of N additions (100 kg N/ha/yr) to a
tundra heath and a tundra meadow. Elsewhere in Sweden, Wardle et al. (2013) found that
two decades ofN additions (50 kg N/ha/yr) to a tundra meadow decreased both plant
species richness and plant community diversity. Because of the similarities in soil and
plant community properties, heathlands have also been included in the tundra section.
Southon et al. (2013) quantified plant species richness at heathland sites in the U.K. along
an N deposition gradient (5.9-32.4 kg N/ha/yr) and observed declines in both vascular
plant species richness and bryophyte species richness. Similarly, Armitage et al. (2014)
observed changes in plant community composition and decreases in plant species
richness in alpine heathlands along an N deposition gradient of 0.6 to 39.6 kg N/ha/yr
across the northern U.K., Iceland, Norway, and the Faroe Islands. Three studies
quantified changes in lichen species richness in alpine tundra ecosystems along
atmospheric N deposition gradients in northern Europe; two observed significant declines
with increases in N deposition.
In China, Song and Yu (2015) examined how different rates (3.75, 15, or 75 kg N/ha/yr)
and chemical forms ofN ([NELJ2SO4, NaNC>3, or NH4NO3) additions over 8 years
influenced plant diversity and the stability of plant communities in alpine plant
communities on the Tibetan Plateau in China. Throughout the experiment, there were no
effects ofN form. The highest rate ofN addition decreased community stability (mean
biomass/mean temporal standard deviation), species richness, and the dominance of
community composition by individual species; other rates ofN did not affect these
metrics. Broadly, added N also increased the temporal synchrony of species cover,
meaning that there were stronger correlations among species and functional groups in
year-to-year variation in cover. This suggests that N additions can decrease compensatory
effects within plant communities, wherein one species or functional group increases in
cover during periods when others are exhibiting decreased growth. Instead, the high N
treatment increased the abundance of both the two dominant grass species. Song and Yu
(2015) suggested that the reduction in compensatory growth could result from decreased
competition for N. As expected, there was a strong correlation between log-transformed
species variance in abundance and log-transformed mean abundance, meaning that more
abundant species were also more variable in their abundance; this relationship was not
affected by N additions. Notably, there was no relationship between community stability
and species richness. Although this is unusual among studies of community stability and
richness [e.g., (Loreau and de Mazancourt. 2013; Til man et al.. 2006; Steineret al.. 2005;
Tilman. 1996)1. the high rate ofN addition caused the loss of only 2 of 20 species within
these communities; neither was a dominant species in the community.
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Table 6-18 Alpine and Arctic tundra plant diversity responses to nitrogen added
via atmospheric deposition or experimental treatments.
Nitrogen
Ambient
Addition
Effect of
Study
Deposition
Rate (kg
Duration
Additional
Reference
Location
Vegetation
or Addition
N/ha/yr)
(yr)
Endpoint
Nitrogen
Sona and Yu
China
Alpine meadow
Addition
3.75, 15, 75
8
Plant
Change
(2015)
(Tibetan
(Kobresia
community
Plateau)
humilis, Elymus
composition
nutans, Stipa
aliena, Festuca
ovina)
Arens et al. Greenland Dwarf-shrub/herb Addition
(2008) tundra (Salix
arctica, Carex
rupestris, Dryas
integrifolia)
5, 10, 50
Plant Not
community significant
composition
Armitaae et
al. (2014)
Europe (North
Atlantic)
Alpine
heathlands
Ambient
0.6-39.6
n/a
Plant
community
composition
Change
Bassin et al.
(2013)
Switzerland
Subalpine
grassland
Addition
5, 10, 25,
50
7
Plant
community
composition
Change
Bowman et al.
(2012)
Colorado
(Rocky
Mountain
National Park)
Dry sedge
meadow
(Kobresia
myosuroides,
Carex rupestris)
Addition
5, 10, 30
4
Plant
species
diversity
Not
significant
Farrer et al.
(2015)
Colorado
(Niwot Ridge)
Moist alpine
meadow
(Deschampsia
cespitosa, Geum
rossii)
Addition
229
7
Plant
species
diversity
Decrease
Bishop et al.
(2010)
Washington
(Mt. St.
Helens)
Primary
successional
alpine meadow
Addition
78
5
Plant
species
diversity
Increase
Sundqvist et
al. (2014)
Sweden
Tundra meadow
(Deschampsia
flexuosa,
Anthoxanthum
alpinum)
Addition
100
3
Plant
species
diversity
Not
significant
Sundqvist et
al. (2014)
Sweden
Tundra heath
(Vaccinium vitis-
idaea, Vaccinium
uiiginosum,
Betuia nana)
Addition
100
3
Plant
species
diversity
Not
significant
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Table 6-18 (Continued): Alpine and Arctic tundra plant diversity responses to
nitrogen added via atmospheric deposition or
experimental treatments.
Nitrogen
Ambient
Addition
Effect of
Study
Deposition
Rate (kg
Duration
Additional
Reference
Location
Vegetation
or Addition
N/ha/yr)
(yr)
Endpoint
Nitrogen
Wardle et al.
Sweden
Tundra meadow
Addition
50
21
Plant
Decrease
(2013)
(Deschampsia
species
flexuosa,
diversity
Empetrum
(vascular)
hermaphroditum,
Vaccinium spp.)
Bassin et al.
Switzerland
Subalpine
Addition
5, 10, 25,
7
Plant
Decrease
(2013)
grassland
50
species
diversity
Sona and Yu
China
Alpine meadow
Addition
3.75, 15, 75
8
Plant
Not
(2015)
(Tibetan
(Kobresia
species
significant
Plateau)
humilis, Elymus
evenness
nutans, Stipa
aliena, Festuca
ovina)
Sona and Yu
China
Alpine meadow
Addition
3.75, 15, 75
8
Plant
Low and
(2015)
(Tibetan
(Kobresia
species
mid dose:
Plateau)
humilis, Elymus
richness
not
nutans, Stipa
significant;
aliena, Festuca
hiah dose:
ovina)
decrease
Bowman et al.
Colorado
Dry sedge
Addition
5, 10, 30
4
Plant
Not
(2012)
(Rocky
meadow
species
significant
Mountain
(Kobresia
richness
National Park)
myosuroides,
Carex rupestris)
Armitaae et
Europe (North
Alpine
Ambient
0.6-39.6
n/a
Plant
Decrease
al. (2014)
Atlantic)
heathlands
species
richness
Sundavist et
Sweden
Tundra meadow
Addition
100
3
Plant
Not
al. (2014)
(Deschampsia
species
significant
flexuosa,
richness
Anthoxanthum
alpinum)
Sundavist et
Sweden
Tundra heath
Addition
100
3
Plant
Not
al. (2014)
(Vaccinium vitis-
species
significant
idaea, Vaccinium
richness
uliginosum,
Betula nana)
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Table 6-18 (Continued): Alpine and Arctic tundra plant diversity responses to
nitrogen added via atmospheric deposition or
experimental treatments.
Reference
Study
Location
Vegetation
Ambient
Deposition
or Addition
Nitrogen
Addition
Rate (kg
N/ha/yr)
Duration
(yr)
Endpoint
Effect of
Additional
Nitrogen
Wardle et al. Sweden
(2013)
Tundra meadow Addition
(Deschampsia
flexuosa,
Empetrum
hermaphroditum,
Vaccinium spp.)
50
21
Plant
species
richness
(vascular)
Decrease
Southon et al. U.K.
(2013)
Heathlands Ambient
(Calluna vulgaris)
5.9-32.4 n/a Plant Decrease
species
richness
(vascular)
ha = hectare; kg = kilogram; N = nitrogen; n/a = not applicable; yr = year.
Note: Single studies are reported more than once if multiple endpoints are measured. Only statistically significant effects are listed
as increases or decreases.
Among studies of microbial diversity (Table 6-19). two studies (Farrer et al.. 2013;
Nemergut et al.. 2008) investigated the effect of N additions in the Rocky Mountains.
Farrer et al. (2013) asked whether soil microbial changes were significant to the
demonstrated decline in the abundance of the plant Geum rossi under increased N
deposition. Microbial community composition changed, but the influence of this change
on G. rossi was unclear. However, there was evidence that N additions imposed a
stronger physiological C limitation on G. rossi. Nemergut et al. (2008) also found shifts
in fungal and bacterial soil communities with chronic N additions (10 to 25 kg N/ha/yr
for >10 years). The fungal community shifted in response to N amendments, with a
decrease in the relative abundance of basidiomycetes. Bacterial community composition
also shifted in the N amended soil, with increases in the relative abundance of sequences
related to the Bacteroidetes and Gemmatimonadetes, and decreases in the relative
abundance of the Verrucomicrobia and considered the point at which such changes might
affect ecologically relevant processes.
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Table 6-19 Alpine and Arctic tundra microbial diversity responses to nitrogen
added via experimental treatments.
Reference
Study
Location
Vegetation
Ambient
Deposition
or
Addition
Nitrogen
Addition
Rate (kg
N/ha/yr)
Duration
(yr) Endpoint
Effect of
Additional
Nitrogen
Farrer et al.
Colorado
Moist alpine
Addition
288
11 Microbial
Change
(2013)
(Niwot
meadow
community
Ridge)
(Deschampsia
composition
cespitosa, Geum
rossii)
Tundra meadow Addition 50 21 Microbial Change
(Deschampsia community
flexuosa, composition
Empetrum
hermaphroditum,
Vaccinium spp.)
Nemeraut et al.
(2008)
Colorado
(Niwot
Ridge)
Dry alpine
meadow
(Kobresia
myosuroides)
Addition
11.5
10
Microbial
community
composition
Change
Nemeraut et al.
(2008)
Colorado
(Niwot
Ridge)
Dry alpine
meadow
(Kobresia
myosuroides)
Addition
11.5
10
Fungal
community
composition
Change
Pavne et al.
(2012)
U.K.
Heathland
(Caiiuna vulgaris)
Addition
10,
80,
20, 40,
120
11,
21
Amoeba
community
composition
Change
Pavne et al.
(2012)
U.K.
Heathland
(Caiiuna vulgaris)
Addition
10,
80,
20, 40,
120
11,
21
Amoeba
species
diversity
Decrease
Pavne et al.
(2012)
U.K.
Heathland
(Caiiuna vulgaris)
Addition
10,
80,
20, 40,
120
11,
21
Amoeba
species
richness
Not
significant
Pavne et al.
(2012)
U.K.
Heathland
(Caiiuna vulgaris)
Addition
10,
80,
20, 40,
120
11,
21
Amoeba
species
richness
Not
significant
ha = hectare; kg = kilogram; N = nitrogen; yr = year.
Note: Single studies are reported more than once if multiple endpoints are measured. Only statistically significant effects are listed
as increases or decreases.
Wardle et al. Sweden
(2013)
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6.2.5
Grasslands
In the 2008 ISA, there was consistent and coherent evidence suggesting that N additions
reduced plant biodiversity in grasslands in the U.S. and Europe. In the U.S., Clark and
Tilman (2008) evaluated the effects of chronic N addition over 23 years in Minnesota
prairie grasslands and found species numbers declined at the lowest addition level
(10 kg N/ha/yr added to 6 kg N/ha/yr of ambient deposition). In the San Francisco Bay
area of California, which receives N deposition levels of 10 to 15 kg N/ha/yr, exotic
nitrophilous grasses have displaced native grass species, likely due to greater N
availability from deposition and from the cessation of grazing, which previously exported
N out of the ecosystem (Form et al.. 2003b; Weiss. 1999).
In Europe, there were observations of N deposition-related declines in grassland plant
diversity in a variety of environments, including calcareous, neutral, and acidic soils,
species-rich heaths, and montane-subalpine grasslands (Stevens et al.. 2004; Bobbink et
al.. 1998; Bobbink et al.. 1992). In a transect of 68 acidic grasslands across Great Britain
that covered a broad range of ambient N deposition (5 to 35 kg N/ha/yr), chronic N
deposition significantly decreased plant species richness (Stevens et al.. 2004). Species
richness declined as a linear function of the rate of inorganic N deposition, with a
reduction of one species per 4-m2 quadrant for every 2.5 kg N/ha/yr of chronic N
deposition (Stevens et al.. 2004).
Although there were only a few studies that had examined low levels of N inputs to
grasslands in the U.S. as of 2008, there were many that added higher levels of N (Clark et
al.. 2007; Bradley et al.. 2006; Sliding et al.. 2005; Gough et al.. 2000) and examined how
N enrichment interacted with other factors such as fire, elevated atmospheric CO2,
species diversity, and climate change (Zavaleta et al.. 2003; Reich et al.. 2001; Collins et
al.. 1998). These studies were not necessarily designed to simulate N deposition, rather
their focus was on nutrient limitation and what happened following the alleviation of this
limitation. Recent studies using low level N addition rates verify that the direction of
effect between low and high N input rates (as well as from gradient studies) are similar.
This suggests that although the magnitude of effect depends on the level of input, the
direction of effect may not, and that nutrient enrichment in grasslands follows a general
response. This response includes increases in aboveground production, decreases in light
availability at the soil surface, changes in soil fauna, and increases in litter buildup, all of
which can lead to competitive displacement of slower growing and shorter plant species
from either shading and/or reduced recruitment and regrowth (Hautier et al.. 2009;
Bobbink et al.. 1998; Tilman. 1993. 1987).
In total, prior to 2008 large-scale biodiversity assessments across gradients of
atmospheric N deposition were restricted to Europe (Stevens et al.. 2004). Although there
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was wide evidence in the U.S. linking the composition of plant and microbial
communities to N availability, most of these experiments had been conducted using N
additions rates considerably exceeding observed atmospheric N deposition rates in the
U.S. [e.g., (Bradley et al.. 2006; Sliding et al.. 2005)1. Experiments demonstrating the
sensitivity of grassland community composition to lower rates of N deposition were more
limited, with evidence for Mediterranean grasslands (Weiss. 1999) and a northern prairie
ecosystem (Clark and Tilman. 2008).
Since the 2008 ISA, research on the impacts of anthropogenic N on biodiversity in
grassland ecosystems has expanded to include a wider range of organisms and
ecosystems and a further understanding of how added N (particularly at more realistic N
input rates) alters biodiversity, including the species and functional groups most
susceptible to increased N availability. Much of this new research has been conducted in
the U.S. (particularly at Cedar Creek in Minnesota) and in western Europe, but China has
also emerged as a center for research on the effects of excess N on grasslands.
As noted earlier, Simkin et al. (2016) quantified the effect of N deposition on species
richness in the continental U.S. using data from over 15,000 plots, including grassland
ecosystems. While Europe has several large-scale continental studies on the effects from
N deposition (Stevens et al.. 2010a; Stevens et al.. 2004). this is the first study of its size
in the U.S. and provides a unique insight on the impacts from N deposition on U.S.
grassland ecosystems. In their analysis, Simkin et al. (2016) observed that at very low
rates of N deposition, increases in N deposition were associated with higher plant species
richness in open canopy ecosystems (e.g., grasslands, shrublands, and woodlands), but
species richness declined atN deposition rates above 8.7 kg N/ha/yr (5th-95th percentile:
6.4-11.3 kg N/ha/yr). Levels causing a decline in species richness are common across
much of the eastern and central U.S. and also occur near urban and intensive agricultural
areas in the west. Evidence of increases at low N input rates had not been observed across
N deposition gradients in Europe, likely due to higher historical deposition rates. Simkin
et al. (2016) also reported that the loss of species was strongly contingent on soil pH,
with more losses occurring in more acidic soils. Notably, Simkin et al. (2016) reported
that approximately 40% of grassland plots used for the study received N deposition at
rates above the threshold for declines in species richness.
A number of studies in Europe have built upon the work of Stevens et al. (2004) in
documenting N deposition impacts on grassland plant communities over long time
periods and/or large geographic areas, with these studies consistently indicating changes
in plant community composition and decreases in diversity as a result of N deposition.
Changes grassland plant diversity in the U.K. from N deposition have been particularly
well documented. Stevens et al. (2010b) and Maskell et al. (2010) built on the work of
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Stevens et al. (2004) in the U.K., trying to identify whether changes in plant community
composition caused by N deposition were the result of acidification or eutrophication.
Stevens et al. (2010b) worked from the same 68 acidic grasslands in Great Britain as
Stevens et al. (2004). but included more detailed information about soil pH and the
sensitivity of individual plant species to pH and N availability. Based on these data,
Stevens et al. (2010b) observed that N deposition mostly caused a shift toward more
acid-tolerant species rather than nitrophilic species, suggesting that acidification is the
primary impact of N deposition on acidic grassland plant communities. A broader
analysis of Maskell et al. (2010). which expanded the work of Stevens et al. (2004) and
Stevens et al. (2010b) beyond acidic grasslands to also include calcareous grasslands,
heathlands, and mesotrophic grasslands and also included direct soil measurements at a
subset of these sites, also found that the primary link between N deposition and species
loss in acidic grasslands and heathlands was acidification. However, eutrophication was
the primary link between species loss and N deposition in calcareous grasslands (Maskell
et al.. 2010). Notably, species losses along the deposition gradient were smaller in
calcareous ecosystems than in acidic ecosystems Henrys et al. (2011) used data from two
national observation networks over Great Britain and found clear negative trends in plant
species prevalence to increasing N in all acidic grassland habitats. Field et al. (2014) also
expanded on the work of Stevens et al. (2004) by surveying a broader range of ecosystem
types across the U.K.: acidic grasslands, bogs, upland and lowland heaths, and sand
dunes. Higher N deposition was associated with decreases in species richness and
changes in community composition across all ecosystem types. Among functional
groups, N deposition decreased the diversity of mosses, lichens, forbs, and graminoids,
but generally increased the cover of graminoids (Field et al.. 2014).
Similar results were observed at broader scales in Europe. Several studies surveyed
153 acidic grassland sites across northern and western Europe (Pannek et al.. 2015;
Stevens et al.. 201 la; Stevens et al.. 201 lb. 2010a). These sites spanned a deposition
gradient of 2 to 44 kg N/ha/yr, but the decreases in plant species richness were not linear
and the highest rate of species loss occurred at deposition rates <20 kg N/ha/yr (Stevens
et al.. 2010a). Across the gradient, most of the decline in species richness was caused by
a loss of forb species, but grass and bryophyte species also declined (Stevens et al..
2010a). As a fraction of total species richness, grass species richness increased and forb
species richness declined with increasing N deposition (Stevens et al.. 201 lb). Notably,
these changes occurred without consistent effects of N deposition on soil NO;, . soil
NH4+, or tissue N concentrations in broadly sampled forb (Galium saxatile) and grass
(Agrostis capillaris) species, but both soil C:N and the foliar N concentration of a
bryophyte (Rhytidiadelphus squarrosus) were positively correlated with N deposition
(Stevens et al.. 201 lb). Stevens et al. (201 lb) were able to explain 24% of the total
variation in plant species composition using climate, soil, and atmospheric deposition
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metrics. Among this 24% of the total variation, soil variables (pH, aluminum
concentrations, C and N content) explaining 38% of the variation and deposition
represented about 10% of this variation (Stevens et al.. 201 la). This influence of
deposition on community composition was notably weaker than the relationship to
changes in species richness. A survey of 44 species in these grasslands found that the
presence of 16 species responded to N deposition, with 12 of these 16 species responding
negatively (Pannek et al.. 2015). In the Atlantic region of France, Gaudnik et al. (2011)
observed that N deposition was one of the primary determinants of community
composition in acidic grasslands, even though the observed range of N deposition was
much smaller than in Stevens et al. (2004). Dupre et al. (2010) examined plant
community composition change in acidic grasslands in north-central Europe and the U.K.
over 70 years, dating back to 1939. Vegetation communities were differentiated
predominately according to soil pH, soil N availability, cumulative N deposition and S
deposition, and sampling date. Plot species richness declined through time for both
vascular plants and bryophytes, with cumulative N deposition identified as the primary
determinant of species loss.
While these N deposition gradient studies have provided strong documentation that
anthropogenic N pollution is altering biodiversity in grasslands in North America and in
Europe, experimental N addition studies have provided new information about the
mechanisms linking N deposition to shifts in community composition. For instance, using
grassland mesocosms in Switzerland receiving 150 to 200 kg N/ha/yr, Hautier et al.
(2009) conducted a unique experiment to understand the role of light competition in the
loss of species under conditions of high N availability. The addition of N increased
aboveground productivity and decreased both light availability near the ground surface
and species richness. An experimental increase in light availability caused by the use of
plant growth lights beneath the grassland canopy further increased productivity, but also
prevented the loss of plant species richness.
At Cedar Creek in Minnesota, Reich (2009) conducted a 10-year experiment where
grassland assemblages of 16 perennial species were grown under factorial combinations
of ambient and elevated CO2 and ambient and elevated N. Increased N (40 kg N/ha/yr)
reduced species at both ambient and elevated CO2, by 16 and 8%, respectively. The
reduced losses of biodiversity at higher CO2 levels remains an active area of research but
is thought to be caused by greater soil water availability at higher CO2 levels (from
reduced stomatal conductance) that reduced the competitive displacement with N
addition. An even longer experiment, 25 years, conducted at Cedar Creek and analyzed
by Isbell et al. (2013) also demonstrated that N enrichment decreased the number of plant
species, and that over time, this effect became increasingly negative at all rates of N
addition. Moreover, species losses were nonrandom, with initially dominant native
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perennial grasses becoming less dominant and then lost, and non-native perennial C3
grasses becoming increasingly dominant. Plot composition changed from a
high-diversity, native-dominated state (C4 grasses) to a low-diversity, non-native
dominated state (C3 grasses). Several earlier studies at this site also reported this general
effect (Clark and Tilman. 2008; Tilman. 1987). Nine native species were particularly
susceptible to becoming locally extinct under chronic nutrient enrichment, including
initially dominant and initially rare species. All of the findings from this seminal
experiment in Cedar Creek, Minnesota, are representative of terrestrial eutrophication as
opposed to acidification, because these soils were limed to maintain a constant pH
(Tilman. 1987). However, there were no lime additions in the experiment conducted at
this site by Reich (2009). indicating that both terrestrial eutrophication and acidification
could be occurring in that experiment.
Lan et al. (2015) examined how N deposition altered spatial patterns in biodiversity and
species-area relationships by measuring plant species loss and species richness in a
grassland in Inner Mongolia in 14 different plot sizes ranging from 1 m2 to 25 m2. The
experiment included five levels of N addition between 17.5 and 280 kg N/ha/yr
(NH4NO3) for 10 years. Except for the 17.5 kg N/ha/yr treatment, N additions decreased
species richness. The absolute number of species lost versus the control group increased
rapidly as plot size increased from 1 to 8 m2, but then stayed the same (high N doses) or
decreased (low N doses). However, the proportional loss of species decreased as plot size
increased, which allowed for predictions of critical loads for species loss at different plots
sizes: 11.4 kg N/ha/yr at 5 m2 and 17.4 kg N/ha/yr at 25 m2. A previous study at these
sites using 0.5 m2 plots found a critical load of 8.5 kg N/ha/yr, indicating that species loss
as a consequence of N additions is sensitive to survey design.
Ecological theory suggests that plant diversity can be maintained by several factors,
including disturbance [e.g., (Davis et al. 2000; Mack et al.. 2000; Hobbs and Huenneke.
1996)]. Among grasslands, the managed reintroduction of some disturbances has been
proposed as a way of maintaining plant diversity in eutrophic ecosystems. In a California
serpentine grassland, Pasari et al. (2014) examined the interactive effects of grazing and
simulated N deposition (80 kg N/ha total over 4 years) on native and exotic species
dynamics. With N additions, grazing helped maintain native species richness. High
grazing intensity decreased exotic plant cover, but only under ambient conditions (Pasari
et al.. 2014). In a southern California coastal grassland, Borer et al. (2014) conducted
several nutrient enrichment experiments, two of which involved the addition of N (40 and
100 kg N/ha/yr). At the higher N level, species richness (forbs primarily) was reduced by
one species per 0.5 m2 after 2 years. However, unlike in the work of Pasari et al. (2014).
this change in diversity was not affected by the presence of pocket gophers (Thomomys
bottae), a keystone herbivore that eliminated the effect of N on plant productivity. In an
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annually burned Kansas tallgrass prairie, McLauchlan et al. (2014) analyzed a 27-year
record of plant community composition and N cycling. Despite rates of N deposition
(average 7 kg N/ha/yr) that were persistently within the range of critical loads for
temperate grasslands in the region, there was no evidence for increases in plant N
concentrations, decreases in forb diversity, or shifts in the relative abundance of dominant
grass species. Further, McLauchlan et al. (2014) suggest that losses of N through frequent
burning or grazing are sufficient to prevent grassland eutrophication at low rates of N
deposition.
There is also new evidence that N additions can alter flowering, seed production, and
seed abundance in grasslands. In Minnesota, Hillerislambers et al. (2009) developed a
statistical model to determine the effects of multiple global change factors, including N
deposition, on inflorescence mass. The effects of N deposition on seed production were
similar within functional groups and negatively correlated with aboveground
productivity: C3 grasses increased aboveground biomass and decreased seed production,
while C4 grasses decreased aboveground biomass and increased seed production. In
addition to seed production, the abundance of seed in soil seed banks is important
because seed banks help in revegetation following disturbances and help maintain plant
diversity, especially in small and isolated ecosystems (Piessens et al.. 2004). However, N
impacts on grassland seed banks are not necessarily directly related to changes in plant
cover or flowering. Basto et al. (2015a) found that 13 years of simulated N deposition at
rates of 35 or 140 kg N/ha/yr decreased cover and flowering in only one species
(Potentilla erecta) in an acidic grassland in England, but total seed bank abundance
declined by 34 and 61% in the low and high N treatments, respectively. Further, seed
bank species richness declined by 29 and 41% in these treatments. Among taxa, there
were decreases of >50% in the seed bank abundance of forbs, sedges, and grasses with
the high N dose, but only a significant decrease (34%) in grass seed bank abundance at
the lower N dose. Seed banks were quantified again 4 years after the cessation of N
additions, but did not significantly recover in any metric of abundance, richness, or
composition.
The Park Grass Experiment in England is the longest ecological experiment in the world
and has examined the effect of various soil amendments, including N (96 kg N/ha/yr) as
(NH4)2S04 or NaNC>3, on grassland productivity and composition since 1856. Zhalnina et
al. (2015) conducted 16S ribosomal RNA sequencing of soil samples from this
experiment in order to assess bacterial and archaeal community composition (Table
6-20). Soil nitrate concentrations were positively correlated with the abundance of
Thaumachaeota and Nitrospirae DNA, whereas total soil N was negatively correlated
with Firmicutes, Verrucomicrobia, and Chloroflexi. Multivariate analyses of community
composition found that the primary determinants of microbial community composition
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were soil pH and C:N. Soil C:N was negatively correlated with Thaumachaeota,
Nitrospirae, and Gemmatimonadetes, but positively correlated with Acidobacteria and
Chlamydiae. Changes in soil pH were a much larger control on microbial abundance,
with significant correlations with 17 of the 37 most abundant soil microbial genera. The
two different forms of N had different effects on pH, and unsurprisingly, different effects
on microbial community composition. Amendments of (NEL^SC^ decreased the phyla
Verrucomicrobia and Chloroflexi and the genera Bradyrhizobium, Paenibacillus, and
Geobacter, while NaNC>3 increased the abundance of the phyla Thaumarchaeota and
Nitrospirae and the genera Geobacter, Candidatus Nitrososphaera, Nitrospira, and
Methylibium. In comparison, 27 years of N additions at Cedar Creek in Minnesota
changed bacterial composition (Fierer et al.. 2012; Ramirez et al.. 2010b). but had no
effect on bacterial diversity I (Fierer et al.. 2012); Table 6-201.
Relative to forests, there is comparably little information on how N additions shift the
composition of mycorrhizal communities in grasslands (Table 6-16). In steppe grassland
in China, Chen etal. (2014) observed that six years of N additions (100 kg N/ha/yr)
decreased the richness of arbuscular mycorrhizal phylotypes found in the soil, but did not
affect the diversity of soil phylotypes nor alter the richness or diversity of phylotypes
observed in plant roots.
Similar to forests, there is also some information available regarding the effects ofN
additions on soil fauna (Table 6-17). In particular, several studies have been conducted
on soil fauna and their role in soil food webs at Cedar Creek in Minnesota (C'esarz et al..
2015; Eisenhauer et al.. 2013; Eisenhauer et al.. 2012). Eisenhauer et al. (2012) observed
that the N deposition treatment at Cedar Creek (40 kg N/ha/yr) significantly altered the
abundance of 5 of 14 groups of soil biota. Simulated N deposition decreased predaceous
nematode abundance by 62%, but increased fungal feeding nematodes by 206%.
Nematode taxon richness and microarthropod taxon richness declined by 7% and 15%
under added N (Eisenhauer et al.. 2012). A more detailed analysis by C'esarz et al. (2015)
found that N enrichment increased the density of the plant-feeding Longidoridae
nematode family by 148% and increased the density of rapidly growing guilds of
fungal-feeding and bacterial-feeding nematodes, a slower-growing guild of predaceous
nematodes declined (C'esarz et al.. 2015). Overall, N additions increased nematode
community composition toward nematode guilds favored by decomposition pathways
dominated by fungi and away from bacterial-dominated decomposition pathways (C'esarz
et al.. 2015; Eisenhauer et al.. 2012). However, while simulated N deposition had
significant effects on soil food webs, these influences were weaker than the direct effects
caused by differences in plant diversity (Eisenhauer et al.. 2013).
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Table 6-20 Grassland microbial diversity responses to nitrogen added via
experimental treatments.
Reference
Study
Location
Vegetation
Ambient
Deposition
or Addition
Nitrogen
Addition
Rate (kg
N/ha/yr)
Duration
(yr)
Endpoint
Effect of
Additional
Nitrogen
Fiereret al. (2012)
Minnesota
(Cedar
Creek)
Temperate
grassland
Addition
34, 272
27
Bacterial
diversity
Not
significant
Fiereret al. (2012)
Minnesota
(Cedar
Creek)
Temperate
grassland
Addition
34, 272
27
Bacterial
community
composition
Low dose:
not
significant;
hiah dose:
change
Ramirez et al.
(2010b)
Minnesota
(Cedar
Creek)
Temperate
grassland
Addition
30, 60, 100,
160, 280,
500, 800
27
Bacterial
community
composition
Change
Zhalnina et al.
(2015)
U.K.
Temperate
grassland
Addition
96
153
Microbial
community
composition
Change
ha = hectare; kg = kilogram; N = nitrogen; yr = year.
Note: Single studies are reported more than once if multiple endpoints are measured. Only statistically significant effects are listed
as increases or decreases.
6.2.6 Arid and Semiarid Ecosystems
As of the 2008 ISA, there was consistent and coherent evidence of altered plant
communities in N addition experiments in arid and semiarid ecosystems, particularly
within coastal sage scrub (CSS) and chaparral ecosystems along the southern California
coast and in portions of the Mojave Desert near large population centers. There was
further additional evidence about shifts in plant and microbial community composition
from N addition experiments in the Mojave, Chihuahuan, Sonoran, and Great Basin
Deserts. Although many of these ecosystems are relatively remote and lightly impacted
by anthropogenic N deposition, the previous ISA noted that deposition to some arid and
semiarid ecosystems can be high downwind of major urban and agricultural areas,
reaching more than 30 kg N/ha/yr in areas of southern California (Fenn et al. 2003^.
Like other terrestrial ecosystems, there was widespread evidence that N additions altered
plant communities by causing a differential stimulation of growth among plant species
(Baez et al.. 2007; Inouve. 2006). such as by favoring rapidly growing nitrophilous
species (Form et al.. 2003b). In addition to these effects on plant communities, Egerton-
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Warburton and Allen (2000) found a shift in arbuscular mycorrhizal community
composition with decreased species richness and diversity along an N deposition gradient
among CSS ecosystems in southern California (2 to 57 |ig N/g as soil NO, ). These shifts
in mycorrhizal fungal communities may facilitate replacement of native plant
communities by exotic annual grasslands.
There are two ecological interactions that are particularly important controlling how N
deposition influences plant community composition in arid and semiarid ecosystems: (1)
the strong dependence of biological responses on an adequate water supply and (2) the
ability of N deposition to promote the growth of exotic plants [particularly annual
grasses; (Brooks. 2003)1. which can dramatically alter the fire cycle by providing a more
spatially continuous fuel supply (Brooks et al.. 2004). The fire cycle impacts of increased
invasive grass biomass were particularly apparent in southern California in CSS
ecosystems near the coast and in Mojave Desert ecosystems inland (Brooks et al.. 2004;
Brooks and Esque. 2002; Cione et al.. 2002; Yoshida and Allen. 2001; Brooks. 1999;
Eliason and Allen. 1997). Fire was relatively rare in the Mojave Desert until the past two
decades, but fire now occurs frequently in areas that have experienced invasion of exotic
grasses (Brooks. 1999). These interactions are apparent in an NH4NO3 addition
(32 kg N/ha/yr) study in the Mojave Desert of southern California conducted by Brooks
(2003). In the 2nd and wetter year of the experiment, N additions decreased species
richness among native annual plants (Brooks. 2003). Overall, N additions increased the
growth of the invasive grass compact brome (Bromus madritensis) beneath the dominant
native shrub creosote bush (Larrea tridentata) and increased the growth of invasive
grasses in the genus Schismus and the invasive forb Erodium cicutarium in the
interspaces between Larrea shrubs, creating a more continuous fuel bed.
Since the 2008 ISA, a number of new N addition experiments and ambient N deposition
gradient studies on shifts in plant community composition and diversity have been
conducted, primarily in California and in arid portions of China (Table 6-21). Broadly,
while some of these studies found decreases in plant species richness [e.g., (Sun etal..
2014; Allen et al. 2009)1. there were more frequent observations of changes in plant
community composition. This disparity may be a function of both the relative brevity of
these experiments (mostly 2-4 years) and the strong moisture limitation that constrains
biological responses to added N in these ecosystems.
Within southern California, there was a continued research focus on how N deposition
alters the abundance of invasive annual plants (particularly grasses) in CSS, chaparral,
and Mojave Desert ecosystems (Cox et al.. 2014; Pasquini and Vourlitis. 2010; Allen et
al.. 2009; Rao et al.. 2009; Vourlitis and Pasquini. 2009; Talluto and Suding. 2008).
Among inland ecosystems, Allen et al. (2009) added N (5 and 30 kg N/ha/yr for 2 years)
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to four sites at Joshua Tree National Park (JOTR) in California and found that the effects
of added N on native plant diversity depended on the abundance of invasive grasses. At
one site where invasive grass biomass (primarily Bromus madritensis) was high and
responded positively to added N, N additions decreased native forb species richness; at a
site where invasive grasses were a small component of the plant community, N additions
increased native forb cover and species richness. Given that Rao et al. (2009) found
greater invasive annual grass cover at sites with higher N deposition across a 16-site N
deposition gradient in the JOTR area, the results of Allen et al. (2009) imply that N
deposition may be decreasing native forb richness across broad areas in the JOTR area.
Near the southern California coast, Vourlitis and Pasquini (2009) investigated the effects
of dry-season N addition in chaparral (dominated by the shrubs Adenostoma fasciculatum
and Ceanothus greggii) and CSS (dominated by the shrubs Artemisia californica and
Salvia mellifera) stands over a 5-year period. The additional N (50 kg N/ha/yr)
significantly altered the community composition of CSS, but not chaparral. The
differences in CSS community composition were due to changes in the relative
abundance of dominant shrubs, not herbaceous plant species. This is not necessarily
consistent with previous research, including observations that although both native shrubs
and invasive annual plants both can exhibit faster growth rates with added N, high N
availability can cause mortality in native shrubs (Allen et al.. 1998). Talluto and Sliding
(2008) revisited 232 plots in southern California that had been dominated by CSS
vegetation during a 1930s vegetation survey and found that CSS cover had declined by
49% and only 15% of the 1930s CSS plots lacked invasive annual grasses. At a landscape
scale, the conversion of CSS to invasive-dominated land was positively related to N
deposition rates and fire frequency, which itself has been linked to N deposition. In
another landscape-level analysis of vegetation change in CSS ecosystems over the years
1930 to 2009, Cox et al. (2014) observed that CSS converted to non-native grasslands
when N deposition was greater than 11 kg N/ha/yr, more consistent with the previous
results. Also in southern California, Pasquini and Vourlitis (2010) found evidence that N
deposition caused changes in chaparral plant community composition in recently burned
ecosystems, but the influence of N deposition in this study was confounded by changes in
other environmental factors across the three-site N deposition gradient (8.1 to
18.4 kg N/ha/yr) used for this research.
Elsewhere in California, Concilio and Loik (2013) studied the effects of added N
(50 kg N/ha/yr for 4 years) on sagebrush steppe ecosystems in the eastern Sierra Nevada
where the invasive annual grass Bromus tectorum was beginning to establish. Although N
addition treatments increased plant available N and total N, no changes were observed in
cover, community composition or richness of native or invasive species. Bromus
tectorum cover was inversely related to native forb species richness, but increased N
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deposition did not affect plant diversity. However, Concilio and Loik (2013) cautioned
that precipitation was below average during the study and N additions may have different
effects when moisture availability is greater.
Among the N addition studies conducted in the arid steppe grassland and shrubland
ecosystems in northern and western China, there have been several notable experiments.
Zhang et al. (2014) studied whether the frequency of additions (12 doses/yr vs.
2 doses/yr) altered effect of added N on plant diversity in a steppe grassland in the Inner
Mongolia region of China (eight levels from 10 to 500 kg N/ha/yr as NH4NO3 for
5 years). Species richness declined by about 50% as N additions rates increased; plant
diversity also decreased more with higher N addition rates. Zhang et al. (2014) noted that
the declines in diversity and richness were smaller with the smaller frequent N doses than
with the large infrequent doses, and suggested that this implied that some N addition
studies may be overestimating the negative effects on plant biodiversity. However, at the
lower N addition rates (10, 20, and 30 kg N/ha/yr) that are more relevant to N deposition
levels in the U.S., the effects of dose frequency were not consistently observed; species
richness was sometimes (nonsignificantly) higher with the large infrequent doses at these
N addition rates. The frequency of N additions did not impact the rate of species loss in
perennial forbs, but did affect the rate of species loss in grasses and annual and biennial
forbs. Notably, N additions were associated with significant decreases in soil
temperature, soil moisture, and soil pH and increases in NH44" and NO3 . All of these soil
changes were correlated with each other and the proportional changes in each of these
variables were correlated with the proportional loss in species richness. Among these soil
traits, higher N addition frequency increased NH4 . but had no other significant effects.
A recent study by Tian et al. (2016) examined how N addition at several rates affected
grassland structure and function in the temperate steppe of China (0, 20, 40, 80, 160,
320 kg N/ha/yr). They found that N addition led to increases in aboveground biomass,
and shifts in relative abundance from forbs to grasses even at the lowest input rate, as
reported in other studies. However, they reported a novel mechanism related to
manganese (Mn) toxicity to explain reductions in forb diversity that had not been
demonstrated before, but had been reported in forestry literature (St.Clair et al.. 2008;
St.Clair and Lvnch. 2005). They reported that forbs were much more prone to Mn
toxicity than grasses following N addition because of physiological differences in root
enzymes associated with metal uptake. Manganese accumulated much more in forbs than
grasses, which led to decreased forb photosynthetic rates and shifts in relative
abundances towards grasses. It is unknown whether this mechanism is operating in other
grassland systems.
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Table 6-21 Arid and semiarid ecosystem plant diversity responses to nitrogen
added via atmospheric deposition or experimental treatments.
Nitrogen
Ambient Addition Effect of
Study Deposition Rate (kg Duration Additional
Reference Location Vegetation or Addition N/ha/yr) (yr) Endpoint Nitrogen
Concilio and Loik
(2013)
California Cheatgrass
(Great (Bromus
Basin)
tectorum) in
sagebrush
(.Artemesia
tridentata)
steppe
Addition
50
Plant Not
community significant
composition
Vourlitis and California Coastal sage Addition
Pasauini (2009) (southern scrub
coastal) (Artemisia
californica,
Salvia
mellifera)
50
Plant Change
community
composition
Vourlitis and
Pasauini (2009)
California Chaparral
(southern (Adenostoma
coastal) fasciculatum,
Ceanothus
greggii)
Addition
50
Plant Not
community significant
composition
Ochoa-Hueso and Spain
Stevens (2015)
Shrubland Addition
(Quercus
coccifera,
Rosmarinus
officinalis,
Lithodara
fruticosa)
10, 20, 50
Plant Change
community
composition
Pasquini and California Chaparral Ambient
Vourlitis (2010) (southern; (Adenostoma
three fasciculatum,
sites) Ceanothus
spp.)
8.1, 11.9, n/a Plant Change
18.4 community
composition
Cox etal. (2014)
California Coastal sage
(southern scrub
coastal)
Ambient 5.7-23.8 n/a Plant More
community invasive
composition grasses
when N
deposition
>11 kg
N/ha/yr
Zhang etal. (2015b)
China
(north,
Songnen)
Alkaline
grassland
(,Leymus
chinensis,
Kalimeris
integrifolia)
Addition
100
Plant Change
community
composition
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Table 6-21 (Continued): Arid and semiarid ecosystem plant diversity responses to
nitrogen added via atmospheric deposition or
experimental treatments.
Nitrogen
Ambient
Addition
Effect of
Study
Deposition
Rate (kg
Duration
Additional
Reference
Location
Vegetation
or Addition
N/ha/yr)
(yr)
Endpoint
Nitrogen
Zhana et al. (2015b)
China
Alkaline
Addition
100
4
Plant
Not
(north,
grassland
community
significant
Songnen)
(Leymus
evenness
chinensis,
Kalimeris
integrifolia)
Zhana et al. (2015b)
China
Alkaline
Addition
100
4
Plant
Decrease
(north,
grassland
species
Songnen)
(Leymus
diversity
chinensis,
Kalimeris
integrifolia)
Ochoa-Hueso and
Spain
Shrubland
Addition
10, 20, 50
3
Plant
Not
Stevens (2015)
(Quercus
species
significant
coccifera,
diversity
Rosmarinus
officinalis,
Lithodara
fruticosa)
Zhana et al. (2014)
China
Alkaline
Addition (2 or
10, 20, 30,
5
Plant
Decrease
(north,
grassland
12
50, 100,
species
(stronger
inner
(Leymus
additions/yr)
150, 200,
richness
decrease
Mongolia)
chinensis,
500
with two
Stipa grandis)
additions/yr)
Zhana et al. (2014)
China
Alkaline
Addition (2 or
10, 20, 30,
5
Plant
Decrease
(north,
grassland
12
50, 100,
species
(stronger
inner
(Leymus
additions/yr)
150, 200,
diversity
decrease
Mongolia)
chinensis,
500
with two
Stipa grandis)
additions/yr)
Vourlitis and
California
Coastal sage
Addition
50
5
Plant
Not
Pasauini (2009)
(southern
scrub
species
significant
coastal)
(.Artemisia
richness
californica,
Salvia
mellifera)
Vourlitis and
California
Chaparral
Addition
50
5
Plant
Not
Pasauini (2009)
(southern
(.Adenostoma
species
significant
coastal)
fasciculatum,
richness
Ceanothus
greggii)
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Table 6-21 (Continued): Arid and semiarid ecosystem plant diversity responses to
nitrogen added via atmospheric deposition or
experimental treatments.
Nitrogen
Ambient
Addition
Effect of
Study
Deposition
Rate (kg
Duration
Additional
Reference
Location
Vegetation
or Addition
N/ha/yr)
(yr)
Endpoint
Nitrogen
Concilio and Loik
California
Cheatgrass
Addition
50
4
Plant
Not
(2013)
(Great
(Bromus
species
significant
Basin)
tectorum) in
richness
sagebrush
(Artemesia
tridentata)
steppe
Sun et al. (2014)
China
Shrubland
Addition
23, 46, 69,
3
Plant
Low dose:
(north,
(Leymus
92
species
not
Songnen)
chinensis,
richness
significant
Artemisia
other doses:
scoparia)
decrease
Zhana et al. (2015b)
China
Alkaline
Addition
100
4
Plant
Decrease
(north,
grassland
species
Songnen)
(Leymus
richness
chinensis,
Kaiimeris
integrifoiia)
Allen et al. (2009)
California
Creosote Bush
Addition
5, 30
2
Native plant
Low dose:
(Joshua
(Larrea
species
not
Tree NP;
tridentata)
richness
significant;
four sites)
scrub; pinyon-
hiqh dose:
juniper
not
woodland
significant at
(Pinus
two sites,
monophyiia,
increase at
Juniperus
one site,
californica)
decrease at
one site
Rao et al. (2009)
California
Creosote bush
Ambient
2.7-14.4
n/a
Invasive
Increase
(Joshua
(Larrea
annual
Tree NP)
tridentata) or
grass cover
pinyon-juniper
woodland
(Pinus
monophyiia,
Juniperus
californica)
ha = hectare; kg = kilogram; N = nitrogen; n/a = not applicable; NP = national park; yr = year.
Note: Single studies are reported more than once if multiple endpoints are measured. Only statistically significant effects are listed
as increases or decreases.
1 In an arid steppe grassland in northeastern China, Sun et al. (2014) observed that N
2 additions of 23, 46, 69, and 92 kg N/ha/yr (3 years, as urea) caused proportional
3 decreases in forb species richness, but that added N caused soil bacterial communities to
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become more diverse except at the highest N dose (Table 6-22). Huang et al. (2015)
conducted a 3-year N x water experiment focused on soil microbial community
composition in a desert steppe ecosystem in northwestern China that receives
25 kg N/ha/yr of ambient deposition. The N addition treatment (50 kg N/ha/yr as
NH4NO3) effects on microbial composition differed between interplant and beneath shrub
sites. In the interspaces, N additions increased the portion of bacteria in total microbial
biomass in all 3 years and increased actinobacteria in the last 2 years of the experiment.
Beneath the shrubs, N additions broadly suppressed microorganisms in all domains. In
the Sonoran Desert near Phoenix, Marusenko et al. (2015) found that although N
additions (60 kg N/ha/yr for 8 years) increased the abundance of the a mo A gene (needed
for ammonia oxidation) in both archaea and bacteria, the community composition of
ammonia oxidizing microorganisms was unaffected.
Table 6-22 Arid and semiarid ecosystem microbial diversity responses to
nitrogen added via experimental treatments.
Reference
Ambient
Study Deposition
Location Vegetation or Addition
Nitrogen
Addition
Rate (kg
N/ha/yr)
Duration
(yr) Endpoint
Effect of
Additional
Nitrogen
Sun et al. (2014)
China Shrubland
(north, (Leymus
Songnen) chinensis,
Artemisia
scoparia)
Addition
23, 46, 69, 92 3
Soil
bacterial
diversity
Increase
Sun et al. (2014)
China Shrubland
(north, (Leymus
Songnen) chinensis,
Artemisia
scoparia)
Addition
23, 46, 69, 92 3
Soil
bacterial
community
composition
Change
Huang et al. (2015) China
Desert shrubs Addition
(Haioxyion
ammodendron)
50
Microbial Change
community
composition
Marusenko et al. Phoenix, Creosote and Addition
(2015) AZ bursage
shrublands
(Larrea
tridentata,
Ambrosia spp.)
60
Archaeal
and
bacterial
amoA (NH3
mono-
oxygenase)
gene
abundance
Increase
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20
21
22
Table 6-22 (Continued): Arid and semiarid ecosystem microbial diversity
responses to nitrogen added via experimental treatments.
Reference
Study
Location
Vegetation
Ambient
Deposition
or Addition
Nitrogen
Addition
Rate (kg
N/ha/yr)
Duration
(yr)
Endpoint
Effect of
Additional
Nitrogen
Marusenko et al.
(2015)
Phoenix,
AZ
Creosote and
bursage
shrublands
(Larrea
tridentata,
Ambrosia spp.
Addition
60
Archaeal
and
bacterial
amoA (NH3
mono-
oxygenase)
community
composition
Not
significant
ha = hectare; kg = kilogram; N = nitrogen; yr = year.
Note: Single studies are reported more than once if multiple endpoints are measured. Only statistically significant effects are listed
as increases or decreases.
6.2.7 Lichens
In the 2008 ISA, there was consistent and coherent evidence indicating that lichen
communities were affected by current levels of N deposition. Lichen community
composition is highly sensitive to atmospheric pollution from N and S (Jovan. 2008).
Based on the widely recognized sensitivity of lichen species to air pollution, Geiser and
Neitlich (2007) developed a model to assess local air quality in Pacific Northwest forests
based on lichen community composition. In addition to being good subjects for
biomonitoring, lichens constitute important components of the forest ecosystem by
contributing to biodiversity, regulating nutrient and hydrological cycles, and providing
habitat elements for wildlife (McCune and Geiser. 1997). The composition of the lichen
community is important because individual species have different physical and
physiological traits, and thus particular contributions to the provisioning of ecosystem
services.
Lichens that contain a cyanobacterial photobiont appear to be more sensitive to adverse
effects from atmospheric N deposition than most other lichens (Hallingback and Kellner.
1992; Hallingback. 1991). In central Europe, Haiick and Wirth (2010) analyzed
514 lichen species and found that shade adapted lichen species are nearly universally
intolerant of high rates of N deposition. Nearly all of these shade-tolerant and pollution
sensitive species are crustose lichens (Hauck and Wirth. 2010). The decline of lichens
containing cyanobacteria in parts of northern Europe has been associated with N
deposition in the range of 5 to 10 kg N/ha/yr (Bobbink et al.. 1998). In the U.S., lichen
species are negatively affected by N inputs as low as 3 to 8 kg N/ha/yr (Fenn et al..
2003a).
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In the San Bernardino Mountains, CA, up to 50% of lichen species that occurred in the
region in the early 1900s have disappeared (Fenn et al.. 2003a; Nash and Sigal. 1999). In
mixed conifer forests in California, the critical load for lichen communities has been
estimated at 3.1 kg N/ha/yr (Fenn et al.. 2008). Compared to California, air pollution has
historically been less problematic in the Pacific Northwest and this region still has large
populations of pollution-sensitive lichens (Jovan. 2008; Fenn et al.. 2003a'). Jovan (2008)
reported that hotspots for lichen diversity in the U.S. include Klamath-Siskiyou region
along the Oregon-California border, the Okanogan highlands region in northeastern
Washington, and the Blue Mountains in eastern Oregon—all areas that are relatively
distant from large human population centers and industrial centers. However, lichen
communities in the Pacific Northwest are beginning to show evidence of changes in
response to increased N pollution, including decreased distribution of sensitive lichen
taxa and their replacement with nitrophilous species (Geiser and Neitlich. 2007).
Table 6-23
Lichen biodiversity responses to nitrogen added via atmospheric
deposition or experimental treatments.
Reference
Study
Location
Vegetation
Ambient
Deposition
or Addition
Nitrogen
Addition
Rate (kg
N/ha/yr)
Duration
(yr)
Endpoint
Effect of
Additional
Nitrogen
Jovan (2008)
California,
Oregon,
Washington
Forest
Ambient
0.5-21
n/a
Community
composition
Change
Jovan et al.
(2012)
California
(Los
Angeles
Basin)
Oak forests
(Quercus
kelloggii)
Ambient
6.1-71.1
n/a
Community
composition
Change
McMurrav et al.
(2015)
Idaho,
Wyoming,
Montana
Conifer forests
Ambient
0.5-4.3
n/a
Community
composition
Change
Schirokauer et al
(2014b)
Alaska
(southeast)
Conifer forests
Ambient
0.05-1.05
n/a
Community
composition
Change
Geiser et al.
(2010)
Oregon and
Washington
Conifer forests
Ambient
0.8-8
n/a
Community
composition
Change
Roaers et al.
(2009)
Utah and
Idaho
Aspen forests
(Populus
tremuloides)
Ambient
(NH3 gas)
7.3-92.2
|jm/m3
n/a
Community
composition
Change
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Table 6-23 (Continued): Lichen biodiversity responses to nitrogen added via
atmospheric deposition or experimental treatments.
Nitrogen
Ambient
Addition
Effect of
Study
Deposition
Rate (kg
Duration
Additional
Reference
Location
Vegetation or Addition
N/ha/yr)
(yr)
Endpoint Nitrogen
Gibson et al. Nova Scotia Northern Ambient 0.01-0.35 ppb n/a Community Change
(2013) (Canada) hardwood (NO2 gas) composition
forests (Acer
saccharum,
Betula
alleghaniensis)
Johansson et al. Sweden Norway spruce Addition 6,12.5,25,50 4 Community Change
(2012) (Picea abies) composition
Gibson et al. Nova Scotia Northern Ambient 0.01-0.35 ppb n/a Species Decrease
(2013) (Canada) hardwood (NO2 gas) richness
forests (Acer
saccharum,
Betula
alleghaniensis)
Will-Wolf et al.
(2015)
Northeastern
U.S.
Forests
Ambient
Not stated
n/a
Species
richness
Decrease
McDonouah and
Watmouah (2015)
Ontario,
Canada
Sugar maple
forests (Acer
saccharum)
Ambient
8.3-12.9
n/a
Species
richness
Not
significant
Southon et al.
(2013)
U.K.
Heathlands
(Calluna
vulgaris)
Ambient
5.9-32.4
n/a
Species
richness
Decrease
Armitaae et al.
(2014)
Europe
(North
Atlantic)
Alpine
heathlands
Ambient
0.6-39.6
n/a
Species
richness
Not
significant
Field et al. (2014)
U.K.
Heathlands
Ambient
5.4-32.4
n/a
Species
richness
Decrease
Johansson et al.
(2012)
Sweden
Norway spruce
(Picea abies)
Addition
6, 12.5, 25, 50
4
Species
richness
6 and 12.5
doses:
increase;
25 and 50
doses:
decrease
ha = hectare; kg = kilogram; N = nitrogen; n/a = not applicable; NH3 = ammonia; N02 = nitrogen dioxide; ppb = parts per billion;
yr = year.
Note: Single studies are reported more than once if multiple endpoints are measured. Only statistically significant effects are listed
as increases or decreases.
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Research on lichens since 2008 continues to indicate that lichen communities change in
response to increased atmospheric N, in both U.S. and Europe. Unlike most other N
deposition biodiversity studies, lichen research has been dominated by studies using
measurements along ambient N deposition gradients rather than using experimental N
additions (Table 6-23). Within the U.S., there are numerous examples of shifts in lichen
community composition along gradients of atmospheric N deposition. Lichen community
composition has been quantified in many parts of the U.S. as part of the U.S. Department
of Agriculture Forest Service's Forest Inventory and Analysis (FIA) program. Jo van
(2008) reported the results from surveys of almost 800 plots conducted from 1998 to
2003 in California, Washington, and Oregon, documenting clear shifts in lichen
community composition in forests in and around areas of intensive agricultural and
industrial production in the Central Valley of California, the Willamette Valley in
Oregon, and the Puget Trough (Seattle/Tacoma/Olympia) in Washington. In the
northeastern U.S., Will-Wolf et al. (2015) analyzed approximately 600 plots of survey
data collected in the 1990s and 2000s as part of the FIA program and from other sources.
Within these data, there were strong relationships between total N deposition and
decreased lichen abundance, reduced species richness, and altered community
composition, but the very strong overlap between N deposition and acidifying deposition
in this region makes it difficult to discern the primary influence on lichen biodiversity.
There are also other surveys of lichen community composition in the U.S. that document
changes even at relatively low rates of N deposition. For instance, lichen community
composition in southeast Alaska shifted toward more eutrophic species along an N
deposition gradient of 0.05 to 1.05 kg N/ha/yr Schirokauer et al. (2014b). In the northern
Rockies, McMurray et al. (2015) observed a shift in lichen community composition at
deposition rates greater than 4.0 kg N/ha/yr. In montane aspen forests in the Utah-Idaho
border region, Rogers et al. (2009) observed a shift in lichen community composition
away from nitrophilous species along a NH3 concentration gradient away from urban and
agricultural sources. In the Los Angeles Basin area of California, Jovan et al. (2012)
documented increases in the abundance of eutrophic lichen species along a gradient of N
deposition. In coniferous forests in the Pacific Northwest, shifts in lichen community
composition and declines in oligotrophic lichen species were observed as N deposition
increased to levels from 3 to 9 kg N/ha/yr range (Geiser et al.. 2010; Glavich and Geiser.
2008).
Outside of the U.S., changes in lichen community composition have been observed in
Canada and in Europe. In the U.K., Southon et al. (2013) and Field et al. (2014) observed
decreased lichen species richness in over 50 heathland survey locations along an N
deposition gradient of 5.4 to 32.4 kg N/ha/yr. However, Armitage etal. (2014) did not
find a significant change in lichen species richness along an N deposition gradient of 0.6
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to 39.4 kg N/ha/yr in alpine heathlands in the North Atlantic region of Europe. In
Sweden, Johansson et al. (2012) found that in old growth boreal spruce forests, additions
of 6 kg N/ha/yr changed the species composition of epiphytic lichen communities and
reduced species richness. Gibson et al. (2013) also noted that in Cape Breton Highlands
National Park in Nova Scotia, the number of pollutant-intolerant lichen species decreased
from 10 to 5 when summer and winter atmospheric NO2 concentrations increased to 0.46
and 0.15 ppb, respectively. McDonough and Watmough (2015) were unable to detect an
influence of N deposition on epiphytic foliose lichen species richness across a network of
40 sugar maple forest monitoring plots across Ontario, Canada. However, study sites in
areas with a history of intense industrial activity tended to have very low epiphytic
foliose lichen species richness.
6.2.8 Biodiversity Summary
The 2008 ISA found evidence sufficient to infer a causal relationship between deposition
and the alteration of species richness, species composition, and biodiversity in terrestrial
ecosystems. Since 2008, there is now more widespread documentation of decreases in
lichen species richness as the result of N deposition in the U.S. [e.g., (Geiseret al.. 2010;
Jovan. 2008)1. and there are now direct observations that (1) N deposition in the U.S. is
altering herbaceous plant species richness across a broad range of ecosystems, including
forests, grasslands, arid and semiarid ecosystems, and alpine tundra [e.g., (Simkin et al..
2016)1; and (2) N deposition in the U.S. is changing mycorrhizal community composition
[e.g., (Allen et al.. 2016; Lillcskov et al.. 2008)1. Further, based on changes in mortality
and growth rates of overstory tree species, there is also now strong indirect evidence that
N deposition is altering overstory tree community composition [e.g., (Dietze and
Moorcroft. 2011; Thomas et al. 2010)1. The body of evidence is sufficient to infer a
causal relationship between N deposition and the alteration of species richness,
community composition, and biodiversity in terrestrial ecosystems.
Broadly, the mechanisms through which N deposition alters the composition of
ecological systems can be grouped into four categories: (1) eutrophication,
(2) acidification, (3) direct damage, and (4) secondary effects. Individual ecosystems and
communities may be simultaneously affected by one or more mechanisms depending on
the environmental and biological properties and the mechanisms may operate
independently or interactively [sensu (Bobbink et al. 2010)1. Eutrophication can alter the
physiology of individual organisms, change relative growth rates, transform fundamental
relationships between species, and affect the availability of essential resources such as
light or water (Hautier et al.. 2009; Clark et al.. 2007; Sliding et al.. 2005). Because
eutrophication can have complex effects and these effects can occur simultaneously with
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other mechanisms, the full impact of N deposition on community composition has often
been derived through empirical analyses of plant communities and microbial
communities.
In forests, research since 2008 has provided evidence of altered understory plant, soil
microbial, arbuscular and ecto-mycorrhizal, and arthropod communities. Two new
assessments using forest inventory plots from the eastern U.S. have observed effects on
growth and mortality that likely impact forest overstory tree composition [e.g., (Dietze
and Moorcroft. 2011; Thomas et al.. 2010)1. However, these data sets and analyses have
not directly been applied to assess changes in forest overstory composition either in
North America or Europe. Evidence for altered forest understory plant communities (also
known as herbaceous layer or groundcover vegetation) come from both the 2008 ISA and
the literature published since 2008. Gilliam (2006) reviewed nine studies on the effects of
N deposition on forest understory plant communities in North America and Europe,
including two European studies that documented shifts in understory plant community
composition along N deposition gradients (Strengbom et al.. 2001; Brunet et al.. 1998). In
a major new analysis of understory plant community composition, Simkin et al. (2016)
observed that N deposition increased herbaceous plant species richness where soil pH
was neutral or basic, but that N deposition above 11.6 kg N/ha/yr decreased herbaceous
species richness on acidic soils. Similar studies of plant community composition have
been conducted across N deposition gradients in Europe, with both Verheven et al.
(2012) and Dirnbock et al. (2014) finding shifts in plant community composition toward
more nutrient-demanding and shade-tolerant plant species, but no loss of species
richness. For soil microbial communities, Zechmeister-Boltenstem et al. (2011) observed
shifts in soil microbial community composition along an N deposition gradient in Europe
and all three N addition studies that were identified since 2008 observed changes in
microbial community composition (Zhao et al.. 2014a; Hobbie et al.. 2012; van Diepen et
al.. 2010). Among studies of how N additions affect forest ectomycorrhizal fungal
communities, there were changes in community composition caused by N additions in six
out of seven studies. This included four studies where shifts in community composition
could be directly or indirectly linked to N deposition gradients in the U.S. or Europe
(Table 6-15).
Since 2008, new studies have quantified the impact of N additions on species richness,
species diversity, and community composition among vascular plants, bryophytes,
lichens, and soil microorganisms in alpine and Arctic tundra ecosystems in North
America, Europe, and Asia. Within the U.S., several N addition studies have documented
changes in plant community composition, including experiments in Colorado (Farrer et
al.. 2015; Bowman et al.. 2012) and Washington (Bishop et al.. 2010). In the North
Atlantic region of Europe, Armitage et al. (2014) observed shifts in community
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composition and decreases in plant species richness among alpine heathlands located
along an N deposition gradient. Similarly, Southon et al. (2013) found decreasing
vascular plant species richness with increasing N deposition in heathlands in the U.K.
Arens et al. (2008) did not observe changes in community composition as a result of N
additions in Greenland, but shifts in plant community composition were observed in
longer (7-8 years) experiments in tundra ecosystems in China (Song and Yu. 2015).
Switzerland (Bassin et al.. 2013). and Sweden (Wardle et al.. 2013). Shifts in microbial
community composition were observed in several N addition experiments in Colorado
(Dean et al.. 2014; Farreretal.. 2013; Nemergut et al.. 2008).
New research on lichens has added further evidence that lichen communities in the U.S.
and Europe are sensitive to current levels of atmospheric N deposition. Shifts in lichen
community composition attributable to atmospheric N pollution have been observed in
forests throughout the west coast (Jovan et al.. 2012; Geiser et al.. 2010; Jovan. 2008). in
the Rocky Mountains (McMurray et al.. 2015; Rogers et al.. 2009). and in southeast
Alaska (Schirokauer et al.. 2014b). Outside of the U.S., changes in lichen community
composition have been observed with increased atmospheric NO2 concentrations in Nova
Scotia, Canada (Gibson et al.. 2013) and experimental N additions in Sweden (Johansson
et al.. 2012).
Since 2008, there have been direct observations of reduced species richness along
atmospheric N deposition gradients for grasslands in the U.S. (Simkin et al.. 2016) and in
Europe (Pannek et al.. 2015; Field et al.. 2014; Gaudnik et al.. 2011; Stevens et al..
2011a; Stevens et al.. 201 lb; Dupre et al.. 2010; Stevens et al.. 2010b; Stevens et al..
2010a). Studies in both the U.S. and in Europe have found that the effects of N deposition
on grassland communities are often dependent on soil pH [e.g., (Simkin et al.. 2016;
Stevens et al.. 201 la; Maskell et al.. 2010; Stevens et al.. 201 Ob)I. Information about
changes in mycorrhizal communities was limited and provided mixed results (Chen et al..
2014). while the relatively few studies that addressed overall soil microbial communities
consistently observed shifts in composition.
Research since 2008 from N deposition gradient studies and N addition experiments has
been dominated by research from southern California, which has provided evidence that
higher N availability alters plant community composition through an increase in invasive
annual plants (Cox et al.. 2014; Allen etal.. 2009; Rao et al.. 2009). Many of these
studies documented changes in plant community composition, with fewer observations of
plant species loss. Evidence for shifts in plant community composition is particularly
strong for coastal sage scrub (CSS) and chaparral ecosystems near the southern California
coast and in areas of the Mojave Desert downwind of major southern California
population centers. An important effect of N deposition in arid ecosystems is an increase
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in N availability in the interspaces between shrubs, allowing the growth of annual grasses
and forbs, which can grow and reproduce during the brief seasonal periods with adequate
moisture availability (Brooks. 2003). This phenomenon provides a more continuous fuel
bed for wildfires, increasing fire frequency and shifting plant community composition
away from species that are not fire-adapted (Padgett and Allen. 1999; Allen et al.. 1998).
Relative to plants, there are fewer studies of shifts in microbial communities, but these
studies provided consistent and coherent evidence that N additions can alter microbial
communities in arid and semiarid ecosystems.
6.3 Most Sensitive and Most Affected Terrestrial Ecosystems and
Regions
The 2008 ISA reported that the most responsive ecosystems to N enrichment from
atmospheric N deposition were those that receive high levels of N loading, are N limited,
or contain species that have evolved in nutrient-poor environments. Species adapted to
low N supply are readily outcompeted by species that have higher N demand when the
availability of N is increased (krupa. 2003; Tilman and Wedin. 1991; Aerts et al.. 1990).
As a consequence, some native species can be eliminated by N deposition (Stevens et al..
2004; Falkengren-Grerup. 1989. 1986; Roelofs. 1986; Ellenberg. 1985).
Unlike the situation for determining the extent of terrestrial impacts of acidifying
deposition wherein ecosystem vulnerability is principally tied to underlying geology,
most terrestrial ecosystems are N limited and, therefore, sensitive to perturbation caused
by N additions (LcBauer and Treseder. 2008). Consequently, little was known in the
2008 ISA about the full extent and distribution of the terrestrial ecosystems in the U.S.
that were most sensitive to adverse impacts caused by atmospheric N deposition. Effects
were most likely to occur where areas of relatively high atmospheric N deposition
intersect with N limited plant communities. The factors that govern the vulnerability of
terrestrial ecosystems to nutrient enrichment from N deposition include the degree of N
limitation, rates of N deposition, elevation, species composition, length of growing
season, and soil N retention capacity. Thus, ecosystems such as alpine tundra, which are
typically strongly N limited, contain vegetation adapted to low N availability, often have
thin soils with limited N retention capacity, and have short growing seasons, can be
particularly vulnerable to N deposition. Similarly, the ability of atmospheric N deposition
to override the natural spatial heterogeneity in N availability in arid ecosystems such as
the Mojave Desert and coastal sage scrub ecosystems in southern California that then
makes these ecosystems much more prone to wild fires, makes these systems uniquely
sensitive to N deposition.
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In the 2008 ISA, effects on individual plant species had not been well studied in the U.S.
More was known about the sensitivity of particular plant communities, based largely on
results obtained in more extensive studies conducted in Europe, which included
hardwood forests, alpine meadows, arid and semiarid lands, and grassland ecosystems.
Among communities sensitive to N deposition, lichens and ectomycorrhizal fungi have
particularly low thresholds for impacts (see Section 6.4.1 and Section 6.4.2'). Thus, the
ecosystems that contain a large number and/or diversity of these organisms, such as
temperate and boreal forests and alpine tundras, could be considered particularly sensitive
to N deposition. More broadly, there has been substantial work on critical loads for N in
U.S. ecoregions since the 2008 ISA (see Section 6.4). which has created an improved
understanding of which processes, taxa, and regions are sensitive to N deposition
impacts.
6.4 Critical Loads
As discussed elsewhere in this ISA (e.g., Chapter 1. Chapter 4. Chapter 5). critical loads
(CLs) are a determination of how much atmospheric deposition can be tolerated by an
environmental system before a significant change occurs. Most commonly, this approach
defines a level of deposition associated with an adverse geochemical or biological
response within an ecoregion. As of the 2008 ISA, most of the critical loads that had been
developed for North American ecosystems were for aquatic ecosystems (lakes and
streams) in Canada and the northeastern U.S. Among terrestrial ecosystems in North
America, the 2008 ISA identified efforts to develop empirical CLs for western
ecosystems in the U.S., particularly alpine and arid ecosystems. The reported effect levels
ranged from 4 to 5 kg N/ha/yr for changes in the abundance of individual sensitive alpine
plant species, to 20 kg N/ha/yr for community level changes in alpine plant communities.
Clark and Til man (2008) calculated the CL for the onset of reduced relative species
number in grasslands to be 5.3 kg N/ha/yr with a 95% inverse prediction interval of
1.3-9.8 kg N/ha/yr. A CLof 3.1 kg N/ha/yr was considered protective of lichen
communities in the western U.S. (Form et al.. 2008). However, as of 2008, there was no
published CL assessment that spanned the U.S.
A large body of work has been published on CLs for N since the 2008 ISA. Most notably,
the U.S. Department of Agriculture (USDA)-Forest Service (FS) created a detailed
national assessment of empirically developed CLs for the U.S. (Pardo etal.. 2011c).
which has also been summarized into a refereed manuscript (Pardo et al.. 201 la). This
national CLs document, Assessment of Nitrogen Deposition Effects and Empirical
Critical Loads (Pardo etal.. 2011c). reports CLs for various biological and
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biogeochemical endpoints in 15 terrestrial ecoregions and, therefore, represents a
significant advance in the understanding of CLs for atmospheric N deposition.
As with many published CL estimates, most of the CLs reported in the USDA-FS
assessment were based on ecological changes observed along atmospheric N deposition
gradients or in response to experimental additions of N at rates near ambient deposition.
Where ecological responses to N deposition could be clearly delineated, the deposition
level that corresponded to a departure from a background "pristine" state was used. An
important advantage of empirical CLs is that they are based on measured (vs. modeled)
changes in ecological processes in response to N inputs. Consequently, the links between
N deposition and the measured response variable are direct and a full process-level
knowledge is not required. However, the use of empirically derived CLs is not without
disadvantages. The lack of a full process-based understanding makes it difficult to
extrapolate observed results across space and time. Spatially, variation in biological and
biogeochemical processes imposed by climate, geology, biota, and other environmental
factors may alter the observed deposition-response relationship. This is particularly
problematic in areas where N deposition has received sparse research attention. Pardo et
al. (201 lc) reported that for some ecoregions, a single study or very few studies were
available. If the variability of ecosystem response to N deposition across an ecoregion is
not available, the estimated CL for N may be relevant for only a single ecosystem type or
a single subregion within the ecoregion. Temporally, whereas atmospheric deposition
responds dynamically to shifts in emissions and weather patterns, ecological processes
react to environmental stress at a variety of timescales. Further, because ecological
changes can be dependent on a series of underlying processes, there can be a time lag
between deposition and ecological responses. Finally, reference plots or low end of the
deposition gradient may already have been altered from a "pristine" condition, which can
bias CL estimates upwards. This shift from a background state can be particularly
problematic for highly sensitive indicators, as well as in regions such as the northeastern
U.S. that have long and geographically extensive histories of elevated N deposition. In
the USDA-FS assessment, Pardo et al. (2011c) reported CLs that tended to be higher in
regions that experienced greater rates of N deposition.
Because environmental factors are large influences on both biogeochemical cycling and
biological processes (Pardo etal.. 2011c). the discussion of terrestrial biological CLs in
this ISA focuses largely on research conducted in North America. Notably, Pardo et al.
(201 lc) reported that CLs developed for Europe and China both tended to be higher than
those reported in the U.S., likely because of the higher rates of N deposition in these
regions. Further, because a large portion of the variation in CLs is a function of particular
ecological receptors (Pardo et al.. 2011c'). the analysis of CL research presented here
compares observations for key receptors (e.g., mycorrhizal fungi, lichens, herbaceous
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plants) across ecoregions, focusing on the estimates created by Pardo etal. (2011c) and
other CL research published since 2008.
6.4.1 Mycorrhizal Fungi
Mycorrhizal fungi are symbiotic organisms hosted on the roots of many plant species that
have important roles in plant nutrient acquisition, belowground C cycling, and as food
sources for other organisms. As noted in Section 6J_ and Section 6.2. mycorrhizal fungi
can be sensitive to added N, responding through changes in physiology and growth
(Table 6-2. Table 6-3. and Table 6-8). as well as shifts in species richness and community
composition (Table 6-15 and Table 6-16). Pardo etal. (2011c) documented that N
deposition in the range of 5 to 10 kg N/ha/yr can significantly alter ectomycorrhizal fungi
community composition and decrease species richness in N limited conifer forests
(Lilleskov et al.. 2008; Dighton et al.. 2004; Lilleskov et al.. 2002; Lilleskov et al.. 2001;
Lilleskov. 1999). Similarly, N deposition levels of 7.8 to 12 kg N/ha/yr can lead to
arbuscular mycorrhizal community changes, declines in spore abundance and root
colonization, and changes in community function. Based on additional analysis, Pardo et
al. (2011c) suggested that the threshold for N effects on mycorrhizae are even lower
because high background deposition precludes consideration of sites receiving deposition
at or near preindustrial levels. The provisional expert judgment was that CLs for
mycorrhizal diversity for sensitive ecosystem types are 5 to 10 kg N/ha/yr. Pardo et al.
(2011c) indicated there is high uncertainty in this estimate because few studies had been
conducted at low rates of N deposition (Figure 6-4).
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Uncertainty
| Reliable
~ Fairly Reliable
Expert Judgement
Empirical Critical Load of
N (kg/ha/yr)
5 Marine West Coast Forests
5 - 7 Northern Forest, Taiga
5-10 Northwest Forested Mountains
2 .7 -12 Marine West Coast Forests
| 7,8 - 9,2 Mediterranean California
| 12 Great Plains
CL = critical load; ha = hectare; kg = kilogram; N = nitrogen; yr = year.
Notes: The range of CLs reported for mycorrhizal fungi is shown for each ecoregion. The hatch marks indicate increasing level of
uncertainty: no hatch marks for the most certain "reliable" category, single hatching for the "fairly reliable" category, and double
hatching for the "expert judgment" category. The color sequence moves from green toward blue and violet as the CL increases. As
the range of the CL gets broader, the saturation of the color decreases. White areas lack data for CLs determination for mycorrhizal
fungi.
Source: (Pardo et al... 2011c).
Figure 6-4 Map of critical loads for mycorrhizal fungi by ecoregion in the
U.S.
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Since the publication of USDA-FS assessment by Pardo et al. (2011c). there has been one
additional study on CLs for mycorrhizae in the U.S. In that study, Allen etal. (2016)
estimated an N deposition CL of 10-12 kg N/ha/yr for mycorrhizal biodiversity in
southern California coastal sage scrub ecosystems (Table 6-24).
Table 6-24 Mycorrhizal critical loads.
Type of
Ecosystem
Critical Load
(kg N/ha/yr)
Biological and Chemical
Effects
Study Species
Reference
California
10-11
Rapid decline in
Arbuscular mycorrhizal
Allen etal. (2016)
coastal sage
mycorrhizal biodiversity
fungi
scrub
Sensitive
ecosystem
types in the
U.S.
5-10
Diversity
Mycorrhizal
Pardo etal. (2011c)
Scots pine 5-10 Community composition Ectomycorrhizal fungi Jarvis et al. (2013)
forest in
Scotland
ha = hectare; kg = kilogram; N = nitrogen; yr = year.
6.4.2 Lichens and Bryophytes
Lichens are symbioses between fungi and algae or cyanobacteria and are important
components of plant communities in forests, tundra, and some arid ecosystems. Lichens
are important contributors to ecosystem function, such through providing wildlife food
and habitat and contributing to nutrient and hydrologic cycling. Like mycorrhizae, the
growth, physiology, and community composition of lichens is sensitive to atmospheric N
deposition (Table 6-5. Table 6-7. and Table 6-23). The 2008 ISA documented
observations that N deposition altered lichen community composition at deposition rates
of 3 to 8 kg N/ha/yr (Fenn et al.. 2003a). In the San Bernardino Mountains in southern
California, up to 50% of lichen species that occurred in the region in the early 1900s had
disappeared by the 1990s (Fenn et al.. 2003a; Nash and Sigal. 1999). The CL has been
calculated for lichen communities in mixed conifer forests in California at 3.1 kg N/ha/yr
(Fenn et al.. 2008). In the Pacific Northwest, lichen communities have shown evidence of
changes in response to increased N pollution, including decreases in the distribution of
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sensitive lichen taxa and the replacement of these taxa with nitrophilous species (Geiser
and Neitlich. 2007).
Since the 2008 ISA, it has become clear that although simple N deposition CL estimates
for changes in lichen community composition can be constructed I(McMurray et al..
2013; Fenn et al.. 2008); Table 6-251. accounting for the effects of climate and other
environmental factors can improve lichen CL estimates (Blett et al.. 2014; Pardo et al.
2011c; Geiser et al.. 2010). providing more refined estimates of CL variability and
exceedance. As noted in Section 6.1.3.3. changes in lichen growth are best correlated
with integrated measures of total N deposition rather with the deposition of a single
chemical species such as HNO3 or NH4+. Lichen responses to N deposition such as
increases in thalli N concentration and shifts in community composition have been most
tightly correlated with colocated canopy throughfall measurements of N-NO3 + N-NH4
(Mc Murray et al.. 2013; Root et al.. 2013; Jovan et al.. 2012; Fenn et al.. 2007) and
ambient N concentrations in fine particulates of [NFL^SC^ and NH4NO3 measured by
IMPROVE (Root et al.. 2015; Geiser et al.. 2010). CMAQ total deposition can also be
closely correlated to lichen response in regions of the country with short precipitation
gradients and moderate to long N deposition gradients.
Lichen community composition and lichen thallus N concentrations shift continuously
with all increments of N addition and the response is generally unimodal. In the latter
case, the fastest rate of change occurs with the earliest increments of N addition and
slows as only tolerant species are left in the community. As N deposition increases
dominance of lichen communities shift from oligotrophic to eutrophic species (i.e., the
number of oligotrophs decrease and the number of eutrophs increase). At very high
deposition levels, total biodiversity decreases.
There are some challenges associated with developing CLs for lichens. First, because
responses are continuous, there is no obvious cut off between adverse and nonadverse
effects. Individual author groups have selected different response thresholds including:
deposition values associated with thallus N concentrations above the 97% distribution
quantile observed for clean sites (Fenn et al.. 2008). community composition shifts from
oligotroph to eutroph dominance (Fenn et al.. 2008). low probability of detecting
regionally distributed sensitive species (Root et al. 2015; Geiser et al.. 2010). or
extirpation of oligotrophs (Fenn et al.. 2008). Secondly, clean site data can be lacking in
some ecoregions. For example, few empirical data are available for sites in the eastern
U.S. with deposition rates <4 kg N/ha/yr, making it impossible to quantify shifts in lichen
physiology or community composition that may have occurred in this region at
deposition rates of 1-4 kg N/ha/yr. Lastly, accurate deposition data are lacking in some
ecoregions where lichens are abundant, such as the southwestern U.S. and areas of the
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intermountain West where CMAQ data tends to overestimate deposition at wet sites and
underestimate deposition at very clean sites (Root et al.. 2015; Mc Murray et al.. 2013).
In the USDA-FS CL assessment, Pardo et al. (2011c) determined an N CL for lichens of
1 to 9 kg N/ha/yr (Figure 6-5. Table 6-25). This CL was based on the shift in community
composition toward eutrophic lichen species and away from oligotrophs. The certainty
associated with the lichen CL estimates for each ecoregion varied considerably, in part
because of differences in sampling scheme and intensity. There were highly reliable
critical N load estimates in the Pacific Northwest and California, where sampling
intensity was high and the linkages between N deposition and lichen community
composition have been well documented. Assessments in the eastern U.S. are more
problematic, due to historical and contemporary S emissions and acidifying deposition.
Historical information necessary to identify a "pristine" or "clean" state has been lacking,
making it difficult to determine the N CL, and the resulting confidence associated with
the CL was low.
In addition to the USDA-FS assessment by Pardo etal. (2011c). there have been a
number of N deposition CL studies for lichens published since 2008, including research
in the northeastern U.S. (Cleavitt et al.. 2015; Will-Wolf et al.. 2015). California (Fenn et
al.. 2010; Fenn et al.. 2008). the Pacific Northwest (Root et al.. 2015; Geiser et al.. 2010;
Glavich and Geiser. 2008). and the Rocky Mountains (McMurray et al.. 2013).
In the northeastern U.S., Cleavitt et al. (2015) studied four Class I areas and found annual
mean and cumulative deposition of N were strongly negatively correlated with lichen
species richness, the abundance of N sensitive species, and thallus condition. The work
by Cleavitt et al. (2015) supported the CL of 4-6 kg N/ha/yr of total N deposition for
epiphytic lichens in the Northern Forest Ecoregion created by Pardo etal. (2011c).
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Empirical Critical Load VSpk
of N (kg/ha/yr) ™ \
11 - 3 Tundra, Taiga \ 1
J 1.2 - 3.7 Northwest Forested Mountains, Alaska
Uncertainty
n Reliable
4 - 7 Temperate Sierras
4 - 8 Eastern Temperate Forests
2.5 - 7.1 Northwest Forested Mountains ~ Fairly Reliable
2.7 - 9.2 Marine West Coast Forests Expert Judgement
3 North American Deserts
3.1-6 Mediterranean California
4 - 6 Northern Forests
CL = critical loads; ha = hectare; kg = kilogram; N = nitrogen; yr = year.
Notes: The range of critical loads reported for lichens is shown for each ecoregion. The hatch marks indicate increasing level of
uncertainty: no hatch marks for the most certain "reliable" category, single hatching for the "fairly reliable" category, and double
hatching for the "expert judgment" category. White areas lack data for CLs determination for lichens.
Source: Pardo et al. (2011cV
Figure 6-5 Map of critical loads for lichens by ecoregion in the U.S.
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Based on sampling in mixed conifer forests in the Sierra Nevada and San Bernardino
Mountains in California, Fenn et al. (2008) developed a CL estimate of 3.1 kg N/ha/yr for
throughfall N deposition based on increases in thallus N concentration for the lichen
Letharia vulpina. Above this CL, there were shifts in lichen community composition
away from acidophytic lichen species and toward lichen species that were considered to
be neutrophytic and nitrophytic. Fenn et al. (2010) later applied these and other
previously published CL values for lichens in California to estimate that 53 and 41% of
the chaparral and oak woodland ecosystems in the state received N deposition in excess
of lichen CLs of 3.1-8 kg N/ha/yr. In comparison, Pardo etal. (2011c) determined the
CL for lichens in the chaparral and oak woodlands of California to be 5.5 kg N/ha/yr.
In the Wind River Range in western Wyoming, McMurrav et al. (2013) developed a
lichen CL based on study sites adjacent to the Bridger Wilderness, a Class I area
downwind of an area experiencing intensive oil and gas production. Above a threshold of
4.0 kg N/ha/yr of throughfall N deposition, McMurrav et al. (2013) observed a
degradation of lichen communities in this area that included necrotic and bleached thalli
and decreased growth.
Table 6-25 Lichen critical loads.
Type of
Ecosystem
Critical Load
(kg N/ha/yr)
Biological and
Chemical
Effects
Study Site
Study Species
Reference
U. S. and Canada
Forest
0.26 to 0.33 kg
inorganic
N/ha/yr and
0.044-0.055
mg/L of
ammonium wet
deposition
Declines in
presence and
abundance of
sensitive lichen
communities
Western Oregon
and Washington
Lichens
Glavich and Geiser
(2008)
Temperate forest
3-9
Sensitive species
declines of
20-40%
Western Oregon
and Washington
Epiphytic
lichens
Geiser et al. (2010)
Various
1-9
Lichen health and
community
composition
U.S. national
Epiphytic
lichens
Pardo etal. (2011c)
Mixed conifer
forests
3.1
Enhanced lichen
tissue N
concentrations
California
Epiphytic
lichens
Fenn et al. (2008)
Fenn etal. (2010)
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Table 6-25 (Continued): Lichen critical loads.
Type of
Ecosystem
Critical Load
(kg N/ha/yr)
Biological and
Chemical
Effects
Study Site Study Species
Reference
Mixed conifer
forests
5.2
Lichen
community
shifted from
acidophyte
dominance to
neutrophyte
dominance
California
Epiphytic
lichens
Fenn et al. (2008)
Fenn et al. (2010)
Mixed conifer 10.2 Lichen species California Epiphytic Fenn et al. (2008)
forests classified as lichens Fenn et al (2010)
acidophytes were
extirpated
Chaparral and oak 5.5 Shift to nitrophyte California Epiphytic Pardo et al. (2011c)
woodland dominance in the lichens Fenn et al (2010)
lichen community
Relating total N in Southern CA, Epiphytic Jovan et al. (2012)
throughfall to north of Los lichens
lichen biodiversity Angeles. Under etal. (2013)
Forest <4.1 Poorer thallus
condition
Wind River Epiphytic McMurrav et al.
Range, WY, lichens (2013)
including the
Class I Bridger
Wilderness
Forest 4 Degradation to Northern Rocky Epiphytic McMurrav et al
lichen Mountains lichens (2015)
communities
Forest 4-6 for total N
deposition
Decreases in Northeastern
lichen species U.S. Class I
richness and N areas
sensitive species,
and poorer
thallus condition
Epiphytic Cleavitt et al. (2015)
lichens
Forest 1.54 and
2.51 kg N/ha/yr
of through-fall
dissolved
inorganic N
deposition
Lichen Pacific Northwest
communities and
lichen N
concentration
Epiphytic Root et al. (2015)
lichens
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Table 6-25 (Continued): Lichen critical loads.
Biological and
Type of
Critical Load
Chemical
Ecosystem
(kg N/ha/yr)
Effects
Study Site
Study Species
Reference
Forest
Continuous
The continuous
Northeastern
141-165 lichen
Will-Wolf et al.
change dose
gradient of
U.S., 218-250
taxa
(2015)
response,
Pollution Index
plot surveys
lowest N dep
values suggests
was 6.3
the cleanest
areas may have
air pollution
above a CL to
fully protect
lichen
communities
CL = critical load; ha = hectare; kg = kilogram; N = nitrogen; yr = year.
6.4.3 Herbaceous and Shrub Species
Herbaceous species and shrubs are found in grasslands, shrublands, forests, deserts, and
wetlands, and comprise the majority of the roughly 26,600 vascular plant species found
in North America north of Mexico (NRC'S. 2009). In forests, herbaceous-layer
(understory) vegetation can be important contributors to ecosystem processes such as
litter production and N cycling (Talhelm et al.. 2013). and can comprise up to 90% of
forest plant biodiversity, including endangered or threatened species (Gilliam. 2007). As
described in Section 6.2.3.2. there is abundant evidence that forest understory vegetation
composition can be sensitive to N deposition (Table 6-13). No broad N deposition CL
values were available for herbaceous and shrub vegetation the U.S. as of the 2008 ISA. In
the USDA-FS assessment, Pardo et al. (201 lc) reported N deposition CLs for herbaceous
species and shrubs across all ecoregions of 3 to 33 kg N/ha/yr (Figure 6-6; Table 6-26).
Among the new research published since the USDA-FS assessment was completed by
Pardo etal. (201 lc). Simkin et al. (2016) examined the influence of N deposition on
species richness of grasses and forbs in over 15,000 plots located across the continental
U.S. Notably, Simkin et al. (2016) found different relationships between N deposition
and species richness in open canopy and closed canopy ecosystems, likely a function of
different species loss mechanisms (Section 6.2.2) operating in these systems. In open
canopy systems (e.g., grasslands, shrublands, and woodlands), N deposition above an
average of 8.7 kg N/ha/yr led to a reduction in species richness (5th-95th percentile:
6.4-11.3 kg N/ha/yr). These rates of N deposition are common across much of the
eastern and central U.S., as well as areas in the western U.S. that are downwind of major
urban and agricultural areas (Figure 6-7). Average CLs for grasses and forbs did not
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differ widely among the grassland, shrubland, and woodland ecosystems (8.9, 8.5, and
8.5 kg N/ha/yr). The calculated CL for closed canopy systems was considerably higher:
13.4 kg N/ha/yr (5th-95th percentile: 6.8-22.2 kg N/ha/yr). At higher levels of N input,
processes such as competitive exclusion and soil acidification occur, decreasing species
richness. There are two important observations from this analysis. First, increases in N
deposition below the CL levels could increase species richness, particularly in
open-canopy ecosystem. Second, the effects of N deposition on species richness were
often pH dependent (see Section 6.2.2). Simkin et al. (2016) also developed more
localized CL estimates. In forests, these ranged from a low of 7.9 kg N/ha/yr in open
canopy eastern forests to a high of 15.3 kg N/ha/yr in northwestern forest mountains. In
the Great Plains region, Simkin et al. (2016) estimated CLs for grasses and forbs of
8.3-9.8 kg N/ha/yr in the open canopy systems to 11.3-19.6 kg N/ha/yr in closed canopy
systems. In arid ecosystems, Simkin et al. (2016) estimated a CL of 8.3-9.9 kg N/ha/yr
for open canopy ecosystems and 13.5-17 kg N/ha/yr for closed canopy ecosystems.
Within the Colorado Rocky Mountains, there were several efforts to develop CLs based
on both empirical and modeled data. In the Rocky Mountain National Park, Bowman et
al. (2012) calculated an empirical CL of 3 kg N/ha/yr to protect natural community cover
based on large increases in the abundance of the sedge Carex rupestris in response
additional N deposition. McDonnell et al. (2014a) applied the ForSAFE-VEG model to
develop a long-term CL estimate aimed at avoiding future (2010-2100) changes in
subalpine plant biodiversity in Rocky Mountain National Park of more than 10%. The
estimated CL to protect future plant diversity was 1.9-3.5 kg N/ha/yr, a value that was
already exceeded in the study area. Notably, the CL estimates to protect future
biodiversity were lower under scenarios that did not include climate warming. Sverdrup
et al. (2012) also used ForSAFE-VEG model to understand how long-term CLs would be
influenced by climate change, but worked from a synthetic alpine and subalpine
vegetation dataset developed from observations at national parks the northern and central
Rocky Mountains region of the U.S. Here, CL values to protect against a future change in
plant diversity of 5-20% were 1 to 2 kg N/ha/yr.
In addition to the Simkin et al. (2016) CL estimates for plant species richness, two other
CL estimates have been developed for arid and semiarid ecosystems. Pardo et al. (201 lc)
determined a CL of 3-8.4 kg N/ha/yr for North American deserts based on a decrease in
native forbs. Rao et al. (2010) developed unique CL estimates for the rate ofN deposition
needed to increase vegetation productivity in two arid ecosystems within Joshua Tree
National Park in southern California above a threshold of 1,000 kg/ha, which would
increase the risk of wildfire spread. To do this, Rao et al. (2010) applied the DayCent
model. Fire risk increased rapidly above CLs of 2.2 and 3.6 kg N/ha/yr for the two
ecosystem types. Fire risk stopped increasing when N deposition levels reached 5.5 and
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8.8 kg N/ha/yr for the two ecosystem types. Notably, contemporary rates of N deposition
at sites were 3 to 8 kg N/ha/yr. In southern California, Coxet al. (2014) modeled the
influence of environmental factors such as climate, land use, and N deposition on the
conversion of coastal sage scrub (CSS) ecosystems to exotic annual grasslands from 1930
to 2009. Here, conversion of CSS to exotic grasslands was more likely to occur if N
deposition exceeded 11 kg N/ha/yr. This CL estimate was similar to a CL of
10 kg N/ha/yr for CSS developed by Pardo et al. (2011c).
-S -1 i
Empirical CL of N (kg ha yr )
1 - 3 Tundra
3-8.4 NcftiAneiican Desert
i - 1D Nortfiwe® Forced Mountains
5 - 25 Great Plains
6 Taiga
6 - 33 Mediterranean California
--7 - --21 Northern Forests
<17.5 EsfiKn Temperate Forests
Uncertainty
^ P.e ac e
^ Fally Rellasie
e\| Expert Judipem
CL = critical load; ha = hectare; kg = kilogram; N = nitrogen; yr = year.
Notes: The range of CLs reported for herbaceous plants and shrubs is shown for each ecoregion. The hatch marks indicate
increasing level of uncertainty: no hatch marks for the most certain "reliable" category, single hatching for the "fairly reliable"
category, and double hatching for the "expert judgment" category. White areas lack data for CLs determination for herbaceous
species and shrubs.
Source: (Pardo et al.. 2011c).
Figure 6-6 Map of critical loads for herbaceous plants and shrubs by
ecoregion in the U.S.
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N Deposition Critical Load
(kg/ha/yr)
I 10-5
J 5-9
J 9-11
¦ 11 -13
¦ 13-15
¦ 15-63
(kg/ha/yr)
Closed Op«n
• 7.4-9 A
9-11 A
11 -13
13-15
• 15-19.6
250 500
i i I
1.000 Kilometers
i
ha = hectare; kg = kilogram; N = nitrogen; yr = year.
Notes: The 3,317 open sites (combined grassland, shrubland, and woodland vegetation types) are portrayed with triangles, and the
11,819 closed canopy sites (deciduous, ever-green, and mixed forests) are portrayed with circles. Background deposition values are
the average of 27 yr of wet deposition (NADP 1985-2011) plus the average of 10 yr of dry deposition (CMAG 2002-2011). Other
variation in CLs is due to the other predictor variables (soil pH, temperature, and precipitation).
Source: (Simkin et al.. 2016).
Figure 6-7 Nitrogen deposition (gray scale) and critical loads for nitrogen
deposition based on total graminoid plus forb species richness
(colored symbols).
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Table 6-26 Summary of U.S. critical loads for nitrogen and corresponding herbs
and shrubs.
Type of
Ecosystem
Critical Load
(kg N/ha/yr)
Biological and
Chemical Effects
Study Site
Study Species
Reference
Addition studies
Alpine tundra
3.0
Protection of
natural community
cover
Rocky Mountain
National Park
Alpine grasses
and forbs
Bowman et al.
(2012)
Modeled
Alpine and
subalpine
ground
vegetation
1 to 2
ForSAFE-VEG
Declines in plant
biodiversity
Northern and
central Rocky
Mountains
Alpine and
subalpine
ground
vegetation
SverdruD et al.
(2012)
Subalpine
1.9 to 3
ForSAFE-VEG
Changes of more
than 10% to
biodiversity
Rocky Mountain
National Park
Subalpine
ground
vegetation
McDonnell et al.
(2014a)
Desert
2.2 and 3.6
DayCent: biomass
exceeds the fire
threshold of
1,000 kg/ha
Southern CA
Joshua Tree
National Park
Various
Rao et al. (2010)
North American
desert
Open: 8.3-9.9
(mean = 9.2,
n = 240)
Closed:
13.5-17.0
(mean = 16.5,
n = 32)
Decreasing
species richness
grasses and forbs
Ecoregion
Various
Simkin et al. (2016)
Semiarid coastal
sage scrub
<11
Conversion to
exotic grasslands
Riverside County,
California
Various
Cox et al. (2014)
Northern forests Open: 8.0-9.8 Decreasing Ecoregion Various Simkin et al. (2016)
(mean = 8.9, species richness
n = 75) grasses and forbs
Closed: 8.0-18.9
(mean = 13.8,
n = 1,955)
Eastern
Open: 6.6-9.7
Decreasing Ecoregion
Various
Simkin et al. (2016)
temperate
(mean = 7.9,
species richness
forests
n = 947)
Closed: 7.8-19.3
(mean = 12.5,
n = 7,378)
grasses and forbs
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Table 6-26 (Continued): Summary of U.S. critical loads for nitrogen and
corresponding herbs and shrubs.
Type of Critical Load Biological and
Ecosystem (kg N/ha/yr) Chemical Effects Study Site Study Species Reference
Northwestern
Open: 8.0-10.2
Decreasing
Ecoregion
Various
Simkin et al. (2016)
forested
(mean = 9.1,
species richness
mountains
n = 1,429)
grasses and forbs
Closed:
10.8-19.6
(mean = 15.3,
n = 2,113)
Marine west
Open: no data
Decreasing
Ecoregion
Various
Simkin et al. (2016)
coast forests
Closed:
species richness
10.4-15.0
grasses and forbs
(mean = 12.8,
n =24)
Temperate
Open: 8.6-8.7
Decreasing
Ecoregion
Various
Simkin et al. (2016)
sierras
(mean = 8.65,
species richness
n = 3)
grasses and forbs
Closed:
14.8-14.8
(mean = 14.8,
n =42)
Great Plains
Open: 8.3-9.8
Decreasing
Ecoregion
Various
Simkin et al. (2016)
(mean = 9.3,
species richness
n =618)
grasses and forbs
Closed:
11.3-19.6
(mean = 16.6,
n = 274)
Dry and neutral
8.0
Plant biodiversity
The Netherlands
Dry and neutral
De Vries et al.
grasslands
loss as predicted
grasslands
(2010)
by SMART2
Semidry
12.4
Plant biodiversity
The Netherlands
Semidry
De Vries et al.
calcareous
loss as predicted
calcareous
(2010)
grasslands
by SMART2
grasslands
Moist and wet
12.6
Plant biodiversity
The Netherlands
Moist and wet
De Vries et al.
oligotrophic
loss as predicted
oligotrophic
(2010)
grasslands
by SMART2
grasslands
Boreal forests
0.9-7.8
Plant biodiversity
Sweden
Forest
De Vries et al.
loss predicted by
understory
(2010)
ForSAFE-VEG
plants
Subalpine
1.9-3.5
ForSAFE-VEG
Rocky Mountain
Forest
McDonnell et al.
vegetation
modeled changes
National Park
understory
(2014a)
of more than 10%
plants
to biodiversity
Beech and 5-11 Plant biodiversity Aeshau, Forest Belvazid et al.
fir/spruce forest loss predicted by Switzerland understory (2011b)
ForSAFE-VEG plants
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1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
Table 6-26 (Continued): Summary of U.S. critical loads for nitrogen and
corresponding herbs and shrubs.
Type of
Ecosystem
Critical Load
(kg N/ha/yr)
Biological and
Chemical Effects
Study Site
Study Species
Reference
Spruce forest
10-16
Plant biodiversity
loss predicted by
ForSAFE-VEG
Bachtel,
Switzerland
Forest
understory
plants
Belvazid et al.
(2011b)
Pine forest
4-6
Plant biodiversity
loss predicted by
ForSAFE-VEG
Sostared, Sweden
Forest
understory
plants
Belvazid et al.
(2011b)
Spruce forest
1-2
Plant biodiversity
loss predicted by
ForSAFE-VEG
Hogbranna,
Sweden
Forest
understory
plants
Belvazid et al.
(2011a)
Forest
16.8
Plant biodiversity
loss as predicted
by SMART2
The Netherlands
EUNIS classes
De Vries et al.
(2010)
EUNIS = European Nature Information System; ForSAFE-VEG = a dynamic forest ecosystem model; ha = hectare; kg = kilogram;
N = nitrogen; SMART2 = a simple soil acidification and nutrient-cycling model; yr = year.
6.4.4 Trees
As noted in Section 6.2.3.1. there are relatively few direct observations of overstory tree
community composition change, likely because it is difficult to observe changes for
long-lived organisms in slowly developing communities. However, there is more
abundant evidence of changes in tree growth, mortality, and physiology (Section 6.1.3.1V
Notably, critical loads for trees due to N + S deposition are presented in Chapter 5.
In the USDA-FS assessment, Pardo etal. (2011c) reported that N CLs for forest
ecosystems ranged from 4 to 39 kg N/ha/yr (Figure 6-8). Estimates of 3-26 kg N/ha/yr
for declining forest growth and increased mortality were based on the forest inventory
data analysis conducted by Thomas et al. (2010) and a chronic N addition experiment
conducted in red spruce forests in the northeastern U.S. (McNultv et al.. 2005). In
Mediterranean California mixed conifers, Pardo etal. (2011c) reported a CL of
17 kg N/ha/yr for decreased fine root biomass and 39 kg N/ha/yr for forest sustainability,
both developed from observations reported by Fenn et al. (2008).
There have been several new studies on CLs for trees. Fleischer et al. (2013) reported that
greater rates of N deposition increased canopy photosynthetic capacity in evergreen
needleleaf forests below a CL threshold of 8 kg N/ha/yr (Table 6-27). while several
modeling studies have been used to estimate changes in forest biodiversity. For example,
ForSAFE-VEG, both McDonnell et al. (2014a) and Belvazid et al. (201 la) have
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published a CL for tree species in Rocky Mountain National Park and
Switzerland/Sweeden, respectively (Table 6-26).
>
Empirical CL of N (kg ha"1 yr'1}
>3-8 Eastern Ternperafe Forests
>3 - <2S Northern Forests
4 - XT Northwest Forested Mountains
<5 -10 Tropical and Subtropical Hianid Forests
5 Marine West Coast Forests
17-30 Medteiranean Calfbma
Uncertainty
Relink?
|\.J Fairly Reliaee
Expert Judgment
CL = critical load; ha = hectare; kg = kilogram; N = nitrogen; yr = year.
Notes: The range of CLs reported for forest ecosystems is shown for each ecoregion; this map does not include the responses of
mycorrhizal fungi, lichens, or understory herbaceous plants already represented. The hatch marks indicate increasing level of
uncertainty: no hatch marks for the most certain "reliable" category, single hatching for the "fairly reliable" category, and double
hatching for the "expert judgment" category. White areas lack data for CLs determination for forest ecosystems.
Source: (Pardo et al... 2011c).
Figure 6-8 Map of critical loads for forest ecosystems by ecoregion in the
U.S.
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1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
Table 6-27 Tree critical loads.
Type of
Ecosystem
Critical Load
(kg N/ha/yr)
Biological and Chemical
Effects
Study Site
Study
Species
Reference
Evergreen
forest
~8
Saturation of
photosynthetic capacity of
the canopy
32 forest sites
around the globe
Conifer
Fleischer et al.
(2013)
Models
Forest
Dose response
reported
Tree growth and survival
Central northern
U.S.
25 tree
species
Thomas et al.
(2010)
EUNIS = European Nature Information System; ha = hectare; kg = kilogram; N = nitrogen; yr = year.
6.4.5 National-Scale Exceedance Studies
In the USDA-FS assessment of N deposition CLs, Pardo etal. (2011c) evaluated the CL
exceedances for mycorrhizal fungi, lichens and bryophytes, herbaceous plants and
shrubs, and forests using N deposition estimates produced by the CMAQ model v.4.3.
This CMAQ model used data reported in 2001 for the simulations of wet plus dry N
deposition. Pardo etal. (2011c) concluded that large parts of the eastern U.S., as well as
localized areas in the West, experience rates of N deposition that exceed the CL for
sensitive ecosystem components. In this assessment, Pardo et al. (2011c) determined that
the resources most threatened by elevated N deposition included freshwater diatoms,
lichens, bryophytes, and herbaceous plants.
In addition to Pardo etal. (2011c). several studies have quantified N deposition CL
exceedance at the regional scale for herbaceous plants. In the Simkin et al. (2016)
analysis of herbaceous species richness in over 15,000 plots over the continental U.S.,
approximately 41% of grassland plots were experiencing N deposition in exceedance of
the CL for plant species richness. Clark et al. (2013) used 26 years (1985-2010) of N
deposition data with ecosystem-specific functional responses from local field
experiments and a national CLs database to generate estimates of herbaceous species
loss. In scenarios using the low end of the CL range, N deposition exceeded CLs over
0.38, 6.5, 13.1, 88.6, and 222.1 million ha for the Mediterranean California, North
American Desert, Northwestern Forested Mountains, Great Plains, and Eastern Forest
ecoregions, respectively, with corresponding species losses ranging from <1 to 30%.
When scenarios assumed less sensitivity (using a common CL of 10 kg N/ha/yr, and the
high end of the CL range) minimal losses were estimated. The large range in projected
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1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
impacts among scenarios highlights the uncertainty in current CLs estimates for plant
diversity in the U.S.
McLauchlan et al. (2014) analyzed a 27-year record of ecophysiological, community, and
ecosystem metrics for an annually burned Kansas tallgrass prairie. Despite observed rates
of atmospheric N deposition (7 kg N/ha/yr from 2002 to 2009) that exceed the minimum
estimated CL for herbaceous plants in tallgrass prairie of the Great Plains of North
America [5-15 kg N/ha/yr (Pardo et al.. 201 lcVI. there were no observations of plant
community composition change or effects on plant physiology that signaled an obvious
influence ofN deposition: plant N concentrations and plant N availability did not
increase, aboveground NPP was unchanged, forb diversity did not decline, and the
relative abundance of dominant grasses did not shift toward more eutrophic species.
Thus, current rates of N deposition do not appear to be altering ecosystem function in this
grassland, even though these rates exceed minimum CLs.
6.4.6 Critical Loads Summary
The 2008 ISA documented efforts to develop CL efforts in the U.S. However, the CLs for
changes in terrestrial ecology available in 2008 were for a subset of western ecosystems.
There were no published assessments of N deposition CLs that spanned ecosystems
across the U.S. Since the 2008 ISA, there has been substantial work on CLs for N for
U.S. ecoregions. A large body of work has been published on CLs for N since the 2008
ISA. Notably, the USDA-FS published Assessment of Nitrogen Deposition Effects and
Empirical Critical Loads (Pardo et al.. 201 lc). which reports CLs for various biological
and biogeochemical endpoints in terrestrial ecoregions (Omernick Level 1) in the U.S.
Most of the published CLs in the U.S. that were included in the Pardo etal. (201 lc)
assessment or subsequently published have covered lichens, mycorrhizae, and herbaceous
and understory plant species. There are still relatively few observations of CLs for
overstory tree species. There do not appear to have been any CLs published for birds,
mammals, or arthropods in terrestrial ecosystems. In general, CLs were higher in regions
that experienced greater rates of ambient N deposition. In part, these higher critical loads
may represent previous ecological change caused by historical N deposition. This pattern
would explain why the empirical CL is often above the ambient deposition even as that
deposition increases in the same ecosystem type across a region (Pardo et al.. 2011c'). The
CLs published since the publication of the USDA-FS assessment by Pardo etal. (201 lc)
often fall into the range of CLs identified by Pardo etal. (201 lc). particularly if these
CLs assess similar ecological endpoints. The new information is presented in tandem
with the CLs by Pardo et al. (201 lc) in Table 6-28.
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Table 6-28 Critical loads for nitrogen by Pardo et al. (2011c) with newer
information on thresholds.
Critical Load
(kg N/ha/yr)
Pardo et al. (2011c)
New
Type of
Ecosystem
Biological and
Study
Species
Ecoregion (Level 1)
Lower CL Upper CL
' Critical Load
(kg N/ha/yr)
Chemical
Effects
Reference
Mycorrhizal fungi
Northern (eastern)
forest
5
7
n/a
Eastern temperate
forests
5
12
n/a
Marine west coast
forest
5
n/a
n/a
Northwest forested
mountains
5
10
n/a
Great Plains
12
n/a
n/a
North American
deserts
n/a
n/a
n/a
Mediterranean
California
7.8
9.2
10-11
California
coastal sage
scrub
Rapid decline
in mycorrhizal
biodiversity
Arbuscular
mycorrhizal
fungi
Allen et al.
(2016)
Temperate sierras
n/a
n/a
n/a
Southern semiarid
highlands
n/a
n/a
n/a
Lichens
Continuous
change dose
response,
lowest N dep
was 6.3
Northern (eastern) 4
6
4-6
Northeastern
Decreases in
Epiphytic
Cleavitt et
forest
U.S. Class I
species
lichens
al. (2015)
areas
richness and N
sensitive
species, and
poorer thallus
condition
Eastern temperate 4
8
n/a
forests
Northeastern Species 141-165 Will-Wolf et
U.S. 218-250 richness lichen taxa al. (2015)
plot surveys
February 2017
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Table 6-28 (Continued): Critical loads for nitrogen by Pardo et al. (2011b) with
newer information on thresholds.
Critical Load
(kg N/ha/yr)
Pardo et al. (2011c)
New
Critical Load
(kg N/ha/yr)
Type of
Ecosystem
Biological and
Chemical
Effects
Study
Species
Ecoregion (Level 1)
Lower CL Upper CL
Reference
Marine west coast
forest
2.7
9.2
1.54 and 2.51
Pacific
Northwest
Lichen
communities
and lichen N
concentration
Root et al.
(2015)
4
Northern
Rocky
Mountains
Degradation to
lichen
communities
Epiphytic
lichens
McMurrav et
al. (2015)
Northwest forested
mountains
2.5
7.1
<4.1
Wind River
Range, WY,
including the
Class I
Bridger
Wilderness
Poorer thallus
condition
Epiphytic
lichens
McMurrav et
al. (2013)
Great Plains
n/a
n/a
n/a
North American
deserts
3
n/a
n/a
Mediterranean
California
3.1
6
n/a
Temperate sierras
4
7
n/a
Southern semiarid
highlands
n/a
n/a
n/a
Herb and shrub
Northern (eastern)
forest
7
21
Open:
8.0-9.8
(mean = 8.9,
n = 75)
Closed:
8.0-18.9
(mean = 13.8,
n = 1,955)
Ecoregion
Decreasing
species
richness
Grasses
and forbs
Simkin et al.
(2016)
Eastern temperate
forests
n/a
17.5
Open:
6.6-9.7
(mean = 7.9,
Ecoregion
Decreasing
species
richness
Grasses
and forbs
Simkin et al.
(2016)
n = 947)
Closed:
7.8-19.3
(mean = 12.5,
n = 7,378)
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Table 6-28 (Continued): Critical loads for nitrogen by Pardo et al. (2011b) with
newer information on thresholds.
Critical Load
(kg N/ha/yr)
Pardo et al. (2011c)
Ecoregion (Level 1) Lower CL Upper CL
New
Critical Load
(kg N/ha/yr)
Biological and
Type of Chemical Study
Ecosystem Effects Species
Reference
Marine west coast
forest
n/a
n/a
Open:
8.0-10.2
(mean = 9.1,
n = 1,429)
Closed:
10.8-19.6
(mean = 15.3,
n = 2,113)
Ecoregion
Decreasing
species
richness
Grasses
and forbs
Open:
8.0-10.2
(mean = 9.1,
n = 1,429)
Closed:
10.8-19.6
(mean = 15.3,
n = 2,113)
Ecoregion
Decreasing
species
richness
Grasses
and forbs
3.0
1.9-3
Alpine
Protection of
natural
community
cover
Grasses
and forbs
Subalpine
ForSAFE-VEG
Changes of
more than 10%
to biodiversity
Simkin et al.
(2016)
Simkin et al.
(2016)
Bowman et
al. (2012)
McDonnell
et al.
(2014a)
Northwest forested
mountains
10
1-2
Alpine and
subalpine
ForSAFE-VEG
Declines in
plant
biodiversity
Ground
vegetation
Sverdrup et
al. (2012)
Great Plains
25
Open:
8.3-9.8
(mean = 9.3,
n = 618)
Closed:
11.3-19.6
(mean = 16.6,
n = 274)
Ecoregion
Decreasing
species
richness
Grasses
and forbs
Simkin et al.
(2016)
Open:
8.3-9.9
(mean = 9.2,
n = 240)
Closed:
13.5-17.0
(mean = 16.5,
n = 32)
Ecoregion
Decreasing
species
richness
Grasses
and forbs
Simkin et al.
(2016)
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Table 6-28 (Continued): Critical loads for nitrogen by Pardo et al. (2011b) with
newer information on thresholds.
Critical Load
(kg N/ha/yr)
Pardo et al. (2011c)
New
Critical Load
(kg N/ha/yr)
Type of
Ecosystem
Biological and
Chemical
Effects
Study
Species
Ecoregion (Level 1)
Lower CL Upper CL
Reference
North American
deserts
-3"
00
CO
3.2 and 3.9
Southern
California
Joshua Tree
National Park
DayCent:
biomass
exceeds the
fire threshold
of 1,000 kg/ha
Creosote
bush and
pinon
juniper
Rao et al.
(2010)
Mediterranean
California
6 33
<11 kg/ha/yr
Semiarid
coastal sage
scrub, CA
Conversion to
exotic
grasslands
Cox et al.
(2014)
Temperate sierras n/a n/a Open: Ecoregion Decreasing Grasses Simkin et al.
8.6-8.7 species and forbs (2016)
(mean = 8.65, richness
n = 3)
Closed:
14.8-14.8
(mean = 14.8,
n = 42)
Southern semiarid
highlands
n/a
n/a
n/a
Forest
8
32 forest sites
around the
globe
Saturation of
photosynthetic
capacity of the
canopy
Conifer
Fleischer et
al. (2013)
Northern (eastern)
forest
3
26
Dose-
response
reported
Tree growth
and survival
Tree
species
Thomas et
al. (2010)
8
32 forest sites
around the
globe
Saturation of
photosynthetic
capacity of the
canopy
Conifer
Fleischer et
al. (2013)
Eastern temperate
forests
3
8
Dose-
response
reported
Tree growth
and survival
Tree
species
Thomas et
al. (2010)
Marine west coast
forest
5
n/a
n/a
8
32 forest sites
around the
globe
Saturation of
photosynthetic
capacity of the
canopy
Conifer
Fleischer et
al. (2013)
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Table 6-28 (Continued): Critical loads for nitrogen by Pardo et al. (2011b) with
newer information on thresholds.
Critical Load
(kg N/ha/yr)
Pardo et al. (2011c)
New
Critical Load
(kg N/ha/yr)
Type of
Ecosystem
Biological and
Chemical
Effects
Study
Species
Ecoregion (Level 1)
Lower CL Upper CL
Reference
Northwest forested
mountains
4
17
1.9-3.5
Subalpine
Rocky
Mountain
National Park
ForSAFE-VEG
modeled
changes of
more than 10%
to biodiversity
Abies
lasiocarpa
as part of a
community
McDonnell
et al.
(2014a)
Great Plains
n/a
n/a
n/a
North American
deserts
n/a
n/a
n/a
Mediterranean
California
17
39
10-11
California
coastal sage
scrub
Rapid decline
in mycorrhizal
biodiversity
Arbuscular
mycorrhizal
fungi
Allen et al.
(2016)
Temperate sierras
n/a
n/a
n/a
Southern semiarid
highlands
n/a
n/a
n/a
CL = critical load; ForSAFE-VEG = a dynamic forest ecosystem model; ha = hectare; kg = kilogram; N = nitrogen; yr = year.
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7
8
9
10
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22
23
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25
26
27
28
29
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31
32
CHAPTER 7
AQUATIC BIOGEOCHEMISTRY
This chapter summarizes recent advancements in understanding the effects of nitrogen
(N) and sulfur (S) deposition on aquatic biogeochemical processes in freshwater systems
(Section 7.2). and estuaries (where fresh water from rivers meets the salt water of oceans)
and other near-coastal areas such as lagoons and open ocean areas near coastlines
(Section 7.3). The freshwater section is further subdivided into N sources (Section 7.2.1).
S sources (Section 7.2.2). chemical processes and indicators of eutrophication and
acidification (Section 7.2.3). monitoring data (Section 7.2.4). modeling of
biogeochemical responses (Section 7.2.5). and water quality criteria (Section 7.2.6). N
sources to estuaries and near-coastal environments are discussed in Section 7.3.1.
followed by chemical effects and processes (Section 7.3.2) and modeling (Section 7.3.3)
in these areas. A summary of aquatic biogeochemistry as it relates to these topic areas
including causal determinations are in Section 1A_.
7.1 Introduction
Changes in major biogeochemical processes in response to S and N deposition have
ramifications for the chemistry and biological functioning of surface waters. As described
in the 2008 Integrated Science Assessment for Oxides of Nitrogen and Sulfur-Ecological
Criteria (2008 ISA), the most common and well-documented aquatic effects are
acidification and eutrophication which may occur simultaneously in water bodies.
Acidification of freshwater ecosystems occurs in response to either S or N deposition
alone or in combination. This is because both N and S deposition can act as acidifying
agents. Acidification is characterized by ecological effects that are distinct from
eutrophication (Chapter 8). Eutrophication is due to N and phosphorus (P)
over-enrichment of freshwater and marine/estuarine systems that leads to increased
production of primary producers (Chapter 9 and Chapter 10). while S over-cnrichment
contributes to biological effects mediated by S reducing prokaryotes (Chapter 12). P
over-enrichment is not specifically addressed in this assessment. Recently, elevated
nutrient loading to coastal areas and subsequent eutrophication has been hypothesized to
contribute to coastal acidification. Ocean acidification is already occurring from
dissolution of rising atmospheric CO2. CO2 produced from decomposition of algal
biomass associated with eutrophication may also decrease the pH of coastal waters. The
geochemical processes and associated chemical indicators discussed in the following
sections can be considered to indicate or suggest eutrophication or acidification. Some of
the biogeochemical alterations associated with N and S deposition link directly to biotic
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effects; others do not cause direct biological effects but are precursory steps to
subsequent changes in soil or water chemistry that can cause biological effects.
A separate chapter addresses the biogeochemistry of terrestrial responses to nutrient and
acidic additions (Chapter 4). Aquatic and terrestrial systems are interconnected and many
of the biogeochemical processes discussed herein bridge the transitions between these
two environmental compartments. Atmospherically deposited N to watersheds, along
with other nonatmospheric sources of N, influence processes that operate from the
freshwater to ocean continuum.
7.2 Freshwater
In the 2008 ISA, the body of evidence was sufficient to infer a causal relationship
between N deposition and the alteration of biogeochemical cycling of N in freshwater
ecosystems. Freshwater systems of the U.S. include lakes (lentic systems), rivers and
streams (lotic systems), and wetlands. The latter, including bogs, fens, marshes, and
swamps, are discussed in Chapter 11 and Chapter 12. As reviewed in the 2008 ISA and
supported by newer studies, fate and transport of deposited N is influenced by
characteristics of the catchment and the receiving waters. Atmospheric deposition of N
affects the chemistry and biology of freshwater ecosystems including processes such as
nitrification and denitrification. N is deposited directly to the surface water of aquatic
ecosystems, or may be intercepted by terrestrial ecosystems and then leached from the
soil to surface waters. Chemical indicators of deposition identified by the 2008 ISA were
nitrate (NO, ) and dissolved inorganic nitrogen (DIN) concentrations in surface waters.
The 2008 ISA found the evidence sufficient to infer a causal relationship between N
deposition and the alteration of biogeochemical cycling of C in freshwater systems. N
deposition can act as a fertilizer in aquatic systems and increase the productivity of
photosynthesizing organisms, resulting in a larger pool of fixed C in aquatic systems.
Indicators of productivity effects of deposition include nutrient ratios and the chlorophyll
a:total phosphorus (P) ratio. In terms of freshwater eutrophication, N deposition is
commonly the main source of N enrichment to lower order streams and high elevation
lakes in nonagricultural ecosystems. Recent evidence provides examples of lakes and
streams that are limited by N and show signs of eutrophication in response to N addition.
In the 2008 ISA, the evidence was sufficient to infer a causal relationship between
acidifying deposition (N and S) and changes in biogeochemistry related to aquatic
ecosystems. Acidifying deposition effects on biogeochemical processes in terrestrial soils
(Chapter 4) have significant ramifications for the water chemistry and biological
functioning of associated surface waters. Surface water chemistry integrates direct
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air-to-water deposition as well as deposition impacts upon soil chemistry of
hydrologically connected terrestrial ecosystems within the watershed. Deposited N and S
interact with the sediments of terrestrial and aquatic ecosystems via oxidation and
reduction reactions as well as biological uptake and microbially mediated processes. The
strongest evidence for a causal relationship between acidifying deposition and ecosystem
impacts comes from studies of changes in surface water chemistry, including
concentrations of sulfate (SO42 ). NO3 . inorganic aluminum (Al), calcium (Ca), sum and
surplus of base cations, acid neutralizing capacity (ANC), and surface water pH. Data
from long-term monitoring, nutrient addition and modeling studies provide consistent and
coherent evidence for biogeochemical changes associated with acidifying N and S
deposition.
New information on biogeochemical cycling of N and S, acidifying deposition effects on
biogeochemical processes and changes to chemical indicators of surface water chemistry
associated with acidification and N nutrient enrichment is consistent with the conclusions
of the 2008 ISA and the body of evidence is sufficient to infer a causal relationship
between N and S deposition and the alteration of freshwater biogeochemistry.
7.2.1 Nitrogen Sources to Freshwater
In the 2008 ISA, it was known that reactive N from fossil fuel combustion converts
atmospheric N2 and fossil N to nitrogen oxides (NOx). Widespread cultivation of crops
promotes conversion of N2 gas to organic N through biological N fixation, and synthetic
N fertilizer production via the Haber-Bosch process accumulates N in the environment on
local, regional, and global scales (Gallowav et al.. 2003; Galloway and Cowling. 2002;
Gallowav. 1998). This N accumulation occurs in the atmosphere, soil, and water
(Galloway and Cowling. 2002). with a multitude of effects on humans and ecosystems
(Townsend et al.. 2003; Rabalais. 2002; van Egmond et al.. 2002; Galloway. 1998). The
sequence of transfers, transformations, and environmental effects is called the "N
cascade" (Gallowav et al.. 2003; Gallowav and Cowling. 2002).
Several new studies published since the 2008 ISA quantified N sources, including
atmospheric contribution, to lakes and streams (Table 7-1). Sobota et al. (2013)
synthesized data on N inputs to lands and waterways throughout the U.S. They found that
human-caused N inputs are ubiquitous, but are spatially heterogeneous. The highest N
loads occurred in the Midwest, Mid-Atlantic region, central California, and portions of
the Columbia River Valley. Synthetic fertilizer was estimated to be the single largest
source of human-caused N inputs to 41% of the water resource units analyzed, followed
by atmospheric deposition (33%) and biological N fixation (22%). In a U.S. Geological
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Survey (USGS) National Water Quality Assessment (NAWQA) report on occurrence and
distribution of nutrients in streams and groundwater (based on water quality assessments
conducted from 1992 to 2001), atmospheric deposition was identified as the largest
nonpoint source of N in the less developed watersheds (areas dominated by forest or
rangeland with <5% urban and <25% agricultural land) in the eastern part of the country
where deposition rates are highest, in areas near the Great Lakes, and the mountainous
west (Dubrovskv et al.. 2010). Atmospheric sources have also been shown to be
quantitatively important (>33% of total input) to Lake Tahoe, CA/NV (Sahoo et al..
2013; Dolislager et al.. 2012). Flat Head Lake, MT (Ellis et al.. 2015). and Nine Mile
Run in Pittsburgh, PA (Divers et al.. 2014). Even in lowland lakes, N from atmospheric
sources has been shown to contribute appreciably to the total input of N. In a recent study
of nutrient sources to Saginaw Bay, MI, N deposition was estimated to comprise 10 to
11% of the total N input from 1987 to 2002 (He et al.. 2014).
Atmospheric N is deposited directly as wet or dry deposition to surface water or is
deposited on land and then leached from the soil to surface water. Nitrogen is deposited
as NC>3~, ammonium (NH4 ). ammonia (NH3) and/or organic N. Inorganic N leaches
mainly as NO3 . In the soil or water, much of the deposited NH4 is either taken up by
biota or nitrified to NO3 . Surface waters and soils have some capacity to remove N via
uptake into vegetation and via the microbial process of denitrification (which returns
biologically available N to the atmosphere). These processes occur across the watershed
along the freshwater to ocean continuum (Seitzinger et al.. 2006).
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Table 7-1 Summary of recent studies quantifying nitrogen deposition
contribution to total nitrogen loading in freshwater systems.
Region
Total N Loading Due to Atmospheric
Deposition
Method
Reference
Lake Tahoe, CA
Approximately 57%, NH3 as the dominant
component and nitric acid and NO3" representing
a smaller but not insignificant proportion of total N
Field data and
Lake Tahoe
Watershed model
Sahoo et al. (2013)
Dolislaaer et al.
(2012)
Flathead Lake, MT Atmospheric loading of NhU"1" averaged 44% of Field data and Ellis et al. (2013)
total load between 1985 and 2004 and was the statistical analysis,
primary form of N in deposition linear regression
Saginaw Bay, Ml N deposition was estimated to be 10 to 11% of Multiple databases He et al. (2014)
total N from 1987-2002. of land use/cover,
hydrography,
animal production,
fertilizers,
combined
wastewater
overflows
St Lawrence River,
Quebec City
Atmospheric N contributed about 0 to 4% of total
N load in the summer; in the spring this source
represented 4 to 11% of total N.
Isotopic analysis Thibodeau et al.
(2013)
Quinnipiac River,
CT
Atmospherically deposited NO3" represented
<6% of N loading; however, during storm events,
atmospheric deposition represented up to 50% of
stream NO3" but varied widely by site.
Stable isotope
ratios
Anisfeld et al. (2007)
Baltimore Long Atmospheric contributions ranged from 5 to 94%
Term Ecological during storm flow conditions and represented
Research site approximately 50% of the highest NO3" loads
during storms.
N watershed mass
balances and
stable isotopes
Kaushal et al. (2011)
Nine Mile Run in 34% of NO3" in stream water was atmospheric in
Pittsburgh, PA origin during storm events while 94% of stream
water NO3" was from sewage sources during
baseflow conditions.
Stable isotope
ratios
Divers et al. (2014)
Key Pre-2008 Literature
16 northeastern Approximately 70% of the N in headwater
watersheds streams was from N deposition and the net
transport of N from headwater streams was
between 40 and 65% of total N.
SPARROW
Alexander et al.
(2002);
Alexander et al.
(2007)
N = nitrogen; NH3 = ammonia; NH4+ = ammonium; N03 = nitrate; SPARROW = Spatially Referenced Regressions on Watershed
Attributes.
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Long-range atmospheric transport of N can affect remote freshwater catchments far from
pollutant sources. As identified in the 2008 ISA, atmospheric deposition is the main
source of N to remote lower order streams and high elevation lakes. Moving from lower
order streams to higher order streams, atmospheric N from direct deposition, runoff, and
leaching from terrestrial ecosystems combines with other diffuse and point sources of N.
In the 2008 ISA, the difficulty in determining the percent of atmospheric N in lowland
waters was noted because there are so many other point and nonpoint sources of N to
drainage waters (U.S. EPA. 2008a'). Although the proportion of total N load from
atmospheric sources decreases in a downstream direction, N deposition may be an
important source to higher order streams. Apportionment of N sources to identify the
contribution of atmospherically derived N was described in a few studies in the 2008 ISA
(U.S. EPA. 2008a'). In Spatially Referenced Regressions on Watershed Attributes
(SPARROW) modeling studies, approximately 70% of the N in headwater streams in the
northeastern U.S. was from N deposition, and first-order headwaters contributed 65, 55,
and 40% of the total N flux to 2nd-, 4th-, and higher ordered catchments, respectively
(Alexander et al.. 2007; Alexander et al.. 2002).
Although overall, atmospheric deposition of total N has not changed appreciably,
atmospheric deposition of reduced N has increased relative to oxidized N in parts of the
U.S. including the East and Midwest in the last few decades (Chapter 2) and this trend is
expected to continue in the future under existing emissions controls (Pinder et al.. 2008;
U.S. EPA. 2008a'). As described in the 2008 ISA, a large fraction of atmospheric N
deposition is retained in most terrestrial ecosystems (U.S. EPA. 2008a'). Nevertheless, the
fraction that does leach to streams can make a substantial contribution to total N inputs to
downstream waters, especially in the eastern U.S. (Driscoll et al.. 2003c'). Nitrogen
retention varies among watershed types such that similar amounts of deposition can result
in different rates of N leaching, depending upon catchment characteristics (Bergstrom.
2010). The concentration of NO3 in surface water can serve as a chemical indicator of N
input in excess of ecosystem requirements (Section 7.2.3).
Additional information is available on atmospheric contribution of reduced versus
oxidized N in lakes since the 2008 ISA. In Lake Tahoe, where a total maximum daily
load (TMDL) allocation was adopted in 2011 by California and Nevada to reduce
nutrient loading, atmospheric N represented approximately 57% of the total N loading to
the lake (Sahoo et al.. 2013). In this large alpine lake in the Sierra Nevada mountain
range, an estimated 185 metric tons of N was directly deposited from the atmosphere,
with NH3 as the dominant component and nitric acid and NO3 representing a smaller, but
not insignificant, proportion of total N (Dolislager et al.. 2012). In Flathead Lake, MT,
atmospheric loading of NH44" averaged 44% of the total load between 1985 and 2004 and
was the primary form of N in atmospheric deposition (Ellis et al.. 2013). The molar ratio
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of the aerosol loading TN:TP increased significantly over this time period with an
increase in atmospheric loading of NO3 + NCh (48%) and NH44" (198%) and decrease in
total P loading (-135%). NCh was the primary form of N in tributary surface water
loading to the lake.
Nitrogen deposition to snow and glaciers is an important source of N to alpine lakes and
streams which are fed by meltwaters. Recent studies indicate that glacial meltwater has
higher NCh than snowmelt water. This may influence interpretation of biological data
from high altitude lakes and streams (Slemmons et al.. 2015; Slemmons et al.. 2013;
Saros et al.. 2010; Baron et al.. 2009). Williams et al. (2007) found that in the Colorado
Front Range rock/glacier outflow had NCh concentrations of 69 |icq/L compared to
snow with 7 |icq/L. In two proximal lakes in the Central Rocky Mountains, NCh
concentration from glacier-fed Jasper Lake, was 2 (j,eq/L compared to the snowpack-fed
Lake Albino where NO? concentration was only 0.03 (.ieq/L (Slemmons et al.. 2015).
In the studies reviewed in the 2008 ISA, the role of atmospheric deposition in
downstream urban and residential water bodies was rarely addressed (U.S. EPA. 2008a).
New studies using stable isotope ratios to quantify N loading in streams have been used
to characterize the contribution of atmospheric N. Several of these studies have shown
shifts from lower to higher atmospheric N contributions to total N loading during storm
events. In the Quinnipiac River in Connecticut which drains into Long Island Sound,
atmospherically deposited NCh averaged <6% of average N loading during baseflow
conditions; however, during storm events, atmospheric deposition represented up to 50%
of stream NCh but the amount varied widely by site (Anisfeld et al.. 2007). In the St.
Lawrence River outlet at Quebec City, Canada, isotopic analysis of N inputs indicated
that atmospheric N contributed about 0 to 4% of total N load in the summer, while in the
spring this source was 4 to 11% of total N (Thibodeau et al.. 2013). In forested,
agricultural and urban watersheds at the Baltimore Long Term Ecological Research site,
atmospheric N contributions ranged from 5 to 94% during storm flow conditions and
represented approximately 50% of peak storm NCh (Kaushal et al.. 2011). In Nine Mile
Run in Pittsburgh, PA, 34% of this NCh in stream water was atmospheric in origin
during storm events whereas during baseflow conditions, 94% of stream water NCh was
from sewage sources (Divers et al.. 2014). In another study in Pennsylvania, stream water
from Spring Creek was monitored at sites from upstream to downstream during storm
flow events to assess changes in N sources (Buda and DeWalle. 2009). For the forested
upstream site, the atmospheric contribution varied by storm size, while in the downstream
urbanized watershed atmospheric NCh was an important N source at peak flow,
especially during short-duration storms when overland flow was prevalent. Burns et al.
(2009) applied dual isotope analysis of NO3 to determine the dominant sources and
processes that affect NCh concentrations in six streams on different land uses in New
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York. The dual isotope data revealed varying sources and processes that affect NO,
concentration among the six stream watersheds. The suburban watershed with no septic
or wastewater influence showed NCh concentrations only slightly higher than those
observed in two forested watersheds. Overall, these recent studies have better
characterized the atmospheric contribution in water bodies with multiple sources of N.
7.2.2 Sulfur Sources to Freshwater
The 2008 ISA reported that there were both depositional and geological sources of SO42
in aquatic ecosystems. SOx deposition to ecosystems is primarily in the chemical form
SO42 , which is a highly mobile anion in the soil solution and surface water of many
acid-sensitive watersheds. Other major sources of SO42 in ecosystems include
mineralization of S from organic matter and weathering of geologic sources of S,
including pyrite minerals. Anthropogenic soil and rock disturbance in the form of road
cuts or mine tailings can increase geological contributions to soil or surface water SO42
by exposing S bearing minerals to oxygen (O2), promoting mineral oxidation and the
release of SO42 . Acid mine drainage is one result of this process, and is prevalent in
many parts of the Appalachian Mountain region. New published evidence regarding the
influence of geologic sources of S or acid mine drainage on stream chemistry has not
been reviewed for this ISA.
The 2008 ISA described how SOx deposition causes release of S from terrestrial soil into
aquatic ecosystems via SO42 leaching, and changes surface water chemistry by
increasing SO42 concentrations. At that time, acidification of surface waters at most
locations in the U.S. where acidification has been documented in response to deposition
was caused mainly by SO42 (Driscoll et al.. 2001b; Sullivan. 2000). This was partly due
to the mobility of SO42 in waters draining from terrestrial ecosystems to aquatic
ecosystems. It was also known that the mobility of SO42 varies geographically, with S
adsorption on soils most significant in regions that were unglaciated during the most
recent glaciation. This includes many acid-sensitive watersheds in the southeastern U.S.
In the most recently glaciated Northeast and Upper Midwest, the majority of
atmospherically deposited S accumulates in organic pools in soil, although microbial
mineralization can transform this S back into SO42 . Some of the SO42 leached from
terrestrial soil, as well as the SOx deposited directly into surface water, is reduced and
retained in aquatic sediments, especially in wetlands. However, S stored in sediments can
be subsequently reoxidized for down-gradient transport as SO42 during periods of high
discharge, particularly following periods of drought. The leaching of SO42 contributes to
a variety of ecological effects (Chapter 8 and Chapter 12). When SO42 is released from
catchment soils to drainage water, it is accompanied by an equivalent amount of cationic
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counter-charge in the form of acidic (H+, Al3+) or basic (Ca2+, Mg2+, K+, and Na+) cations
(U.S. EPA. 2008a'). There are no new studies evaluating sources of S to freshwater
systems.
7.2.3 Chemical Processes and Effects Indicators
Commonly reported biogeochemical indicators of freshwater nutrient enrichment and
acidification from the 2008 ISA are summarized in Table 7-2 along with thresholds of
associated biological effects. N and S deposition impacts on aquatic ecosystems can be
described by changes in chemical indicators including SO42 concentration, NO3
concentration, inorganic A1 concentration, base cation concentrations, pH, and ANC.
Surface water NO3 concentration can indicate both eutrophication and acidification.
Water pH and the concentrations of ANC, SO42 . base cations, and inorganic A1 are
indicators of acidification (U.S. EP A. 2008a').
New information on these biogeochemical indicators and processes is presented in the
following sections, along with summaries of information from the 2008 ISA. As reported
in the 2008 ISA and summarized in Figure 7-1. the biogeochemical cycles of N, P, and C
are linked in freshwater ecosystems. N deposition can alter the pools and fluxes of the C,
N, and P cycles, particularly nitrification and denitrification. S deposition directly adds
S042 to soil solutions and to surface waters with effects on ecosystems (Chapter 12). but
many ecological effects are mediated through the indirect effects of SO42 on acidic and
basic cations. The chemical indicators of deposition discussed below also link to
biological effects of acidifying deposition (Chapter 8) and freshwater eutrophication
(Chapter 9).
7.2.3.1 Nitrogen Uptake, Storage, and Retention
A number of studies since 2008 have focused on improving understanding of aquatic
acidification and eutrophication processes. Many of these have focused on pathways of
pollutant and other constituent movement within ecosystems, including monitoring
studies of various kinds (Section 7.2.4). Long-term monitoring databases have been very
important in quantifying the recovery of aquatic ecosystems from damages caused by
atmospheric deposition of nutrients and acid-precursors.
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Table 7-2 Commonly used geochemical indicators of freshwater nutrient enrichment and acidification caused
by nitrogen and sulfur deposition that were identified by the 2008 Integrated Science Assessment for
Oxides of Nitrogen and Sulfur—Ecological Criteria.
Endpoint
Nutrient Enrichment
Indicator
Acidification
Indicator
Deposition Effect on Water Chemistry Endpoint
Relationship with Biological Effects
[NO3-]
X
X
Increased N deposition increases the water NO3"
concentration.
High concentrations of NO3" in lakes and streams,
indicative of terrestrial ecosystem N saturation, have been
found at a variety of locations throughout the U.S. (U.S.
EPA. 2006c: Stoddard. 1994).
Comparison of preindustrial to modern estimates
suggested elevated concentrations in water bodies as a
result of N deposition.
>20 peq/L-degraded aquatic ecosystem
(Fenn etal.. 2011b)
DIN
X
Increased N deposition increases DIN in most freshwater
environments, largely as NO3".
N:P ratios
X
Increased N deposition can alter the ratio of N to P in
freshwater systems.
Suggestion of N limitation vs. P limitation,
which can influence nutrient enrichment
[S0421
X
Increased S deposition increases the water SO42"
concentration.
Comparison of preindustrial to modern estimates
suggested elevated concentrations in water bodies as a
result of S deposition.
No direct biological effects in aquatic
ecosystems
[base cation]
X
The results from several studies in the eastern U.S.
suggested that base cation concentrations in surface
waters increased during the initial phases of acidification
into the 1970s. This trend reversed, and base cations
decreased in response to decreasing SO42" and NO3"
concentrations.
Many base cations (especially Ca2+) are
important nutrients.
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Table 7-2 (Continued): Commonly used geochemical indicators of freshwater nutrient enrichment and
acidification caused by nitrogen and sulfur deposition that were identified by the 2008
Integrated Science Assessment for Oxides of Nitrogen and Sulfur—Ecological Criteria.
Nutrient Enrichment Acidification
Endpoint Indicator Indicator
Deposition Effect on Water Chemistry Endpoint
Relationship with Biological Effects
[base cation
surplus]
X Increased N and S deposition cause decreased base
cation surplus, defined as the difference between the
summed concentrations of base cations (Ca2+, Mg2+, Na+,
K+) and acidic inorganic anions (SO42", NO3", CI"), plus an
estimate of the strongly acidic organic anions estimated
from dissolved organic C and an assumed charge density.
BCS less than zero suggests mobilization
of inorganic Al which is toxic at levels
generally above about 2 pmol/L.
ANC
X Increased N and S deposition cause decreased ANC.
Titrated ANC is useful because it reflects the ANC of the
complete chemical system, which is typically decreased
by acidic deposition in acid-sensitive landscapes.
Surface water ANC correlates with other
biologically important components of
surface water acid-base chemistry,
including pH, inorganic Al concentration,
Ca concentration, and organic acidity. ANC
<50-100 peq/L typically poses a risk for
biological impairment.
PH
X Surface water pH is a common alternative to ANC as an
indicator of acidification. However, at pH values above
about 6.0, pH is not a good indicator of either sensitivity to
acidification or level of effect. In addition, pH
measurements (especially at these higher values) are
sensitive to levels of dissolved CO2 in the water. N and S
deposition are associated with decreasing pH (increasing
hydrogen ion concentration) in surface waters. Increasing
pH trends in surface waters in the northeastern U.S. were
common through the 1990s up to 2004, but the rates of
change have been small. Driscoll et al. (2001b), Driscoll et
al. (2001a). and Driscoll et al. (2007a) attributed the
limited pH recovery of lakes in acid-sensitive regions to
three factors: (1) the levels of acid-neutralizing base
cations in surface waters have decreased because of
base cation depletion from the soil, and to a lesser extent,
a reduction in atmospheric inputs of base cations; (2) as
forests mature, their requirements for N decrease, and
they are expected to increasingly leach NO3" as forests
develop; and (3) sulfur has accumulated in the soil under
previous conditions of high atmospheric S deposition and
is now being gradually released to surface water as
SO42", even though S deposition has decreased.
Low pH can have direct toxic effects on
aquatic species (Driscoll et al.. 2001b). In
general, low pH can disturb normal ion
osmoregulation in aquatic biota. A pH value
of 6.0 is often considered the level below
which biota are at risk from acidification.
Generally, below a pH of 5.5 inorganic Al
becomes the greater threat.
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Table 7-2 (Continued): Commonly used geochemical indicators of freshwater nutrient enrichment and
acidification caused by nitrogen and sulfur deposition that were identified by the 2008
Integrated Science Assessment for Oxides of Nitrogen and Sulfur—Ecological Criteria.
Nutrient Enrichment Acidification
Endpoint Indicator Indicator
Deposition Effect on Water Chemistry Endpoint
Relationship with Biological Effects
Surface water
inorganic Al
X N and S deposition are associated with increased
mobilization of inorganic Al from terrestrial ecosystems
that leach into surface water, increasing surface water
concentrations.
Earlier studies demonstrated reduced
growth and survival of various species of
fish (Baker et al.. 1996: Baker and
Schofield, 1982) at inorganic Al
concentrations between approximately 2
and 7.5 pmol/L. Most recently, 20%
mortality of young-of-the year brook trout
was documented in situ during a 30-day
period with a median inorganic Al
concentration of 2 pmol/L (Baldiqo et al..
2007). This study estimated that 90%
mortality would occur over 30 days with a
median inorganic Al concentration of
4.0 |jmol/L.
Al mobilization from soil to aquatic
ecosystems is an important consequence
of acidification of lakes and streams. Gills,
skeleton, kidney, liver and muscles are the
main target organs for Al toxicity. The
concentration of inorganic Al in surface
waters is an especially useful indicator of
acidifying deposition effects because (1) it
is widely toxic (e.g., respiratory,
osmoregulatory and circulatory
impairment), and (2) it generally does not
leach from the terrestrial soils to surface
waters in the absence of acidifying
deposition.
Al >2 pmol/L is toxic to aquatic biota (Fenn
et al.. 2011b).
Al = aluminum; ANC = acid neutralizing capacity; BCS = base cation surplus; Ca = calcium; CI = chloride; C02 = carbon dioxide; DIN = dissolved inorganic nitrogen; K = potassium;
L = liter; |jeq = microequivalent; |jmol = micromole; Mg = magnesium; N = nitrogen; Na = sodium; N03" = nitrate; P = phosphorus; S = sulfur; S042" = sulfate.
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CCL
Terrestrial input
O
Is
Q_
CO
<1)
deposition
~
P
L respiration photosynthesis
Grazers,
predators
and viruses
! I
u
Sediments
CO,
deposition
N fixation
water surface
uptake
producers
excretion
excretion «
decomposition
Detritus
C cycle
N cycle
P cycle
Benthic
decomposition
C = carbon; C02 = carbon dioxide; N = nitrogen; P = phosphorus.
Figure 7-1 Nitrogen cycle in freshwater ecosystem (U.S. EPA, 2008a).
Reactive N that is not lost to drainage or denitrification can be taken up by terrestrial and
aquatic biota or stored in soils and/or sediments. Typically, a rather large percentage of
the N deposition to a given watershed is taken up or stored and is not available for
leaching to surface waters. This stored N does not contribute directly to water
acidification or eutrophication and represents a significant portion of the incoming N
deposition to forested ecosystems in the U.S. The portion of the N deposition that is not
retained or lost to denitrification can contribute to water acidification or eutrophication,
both on a chronic and especially an episodic basis.
It was well understood at the time of the 2008 ISA that streams can transform nutrients,
store them for the short term, or serve as a sink for N loss from the watershed through
denitrification. It is important to consider the balance between how much and how long
streams retain elements versus transport them downstream. This balance is key to
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modeling watershed nutrient export. Hydrologic processes influence nutrient cycling,
including within the full spatial extent of the stream that extends beyond the main
channel. Hydrologic exchange between the streams and the groundwater increases the
travel time of water down-gradient and puts the stream water in contact with biofilms that
are attached to alluvial sediments and buried organic materials. This hyporheic exchange
can contribute to N retention in streams because it promotes denitrification associated
with anoxic flow paths through organic stream bottom substrates. Recent studies have
added more quantitative context to this understanding. For example, Hall et al. (2009b)
used a 15N-tracer addition of NOs to measure N uptake, storage, and export during
snowmelt flood periods and during baseflow in a stream in the Sawtooth Mountains of
Idaho. N was preferentially exported during high flow periods. However, the snowmelt
floods exhibited enhanced demand for NO3 because of hyporheic exchange. Residence
times were relatively long in fine detritus, insects, and particulate N that accumulated in
the hyporheic zone. Results of this study suggested that assimilation and hydrologic
storage can be important for retaining N at the watershed scale. Hydrologic exchange
between the stream and its valley is an important storage mechanism for N. Thus, the
study stream was not solely a conduit for nutrients at high flow. It had as high an uptake
velocity for N during the snowmelt flood as during summer baseflow.
Headwater streams can be especially important locations for nutrient transport. They
often comprise most of the total stream length in a given drainage network. These small
streams can play a disproportionately large role in N transformation and N cycling in
aquatic ecosystems. They are important to predicting effects ofN loading on downstream
ecosystems (Lawrence et al.. 2015b). Headwater streams often have increased water
residence time and solute retention due to increased interactions between surface and
groundwater in the hyporheic zone. Hubbard et al. (2010) characterized NO? uptake
lengths in a small headwater stream in the Rocky Mountains using '"N-NO, addition
tracer tests. They calculated and compared NO, uptake parameters derived from
background chemistry and isotopic injection and investigated the impacts of man-made
and beaver dams on hyporheic exchange and on N cycling. Dams influenced stream
water geochemistry because a portion of the stream water flow was diverted into the
more reactive hyporheic zone. Highly oxic and anoxic regions of the streambed
developed around the more permanent structures. This enhanced N cycling in the
hyporheic zone and increased the potential for denitrification and NO, uptake.
Some work has been conducted regarding the biological impacts of changes in N
retention. Heini et al. (2014) examined chlorophyll a at various depths in a lake in
southern Finland, and found that algae and cyanobacteria were at least partly responsible
for the observed variability in water chemistry in the surface layer of the lake.
Differences in phytoplankton strongly affected observed short-term differences in
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chemical properties. The chemical conditions in the deeper waters during summer were
generally more stable than in the layers near the surface of the lake. In Flathead Lake,
MT, which is colimited by N and P, an average of 3.7% of carbon production in the lake
from 1984 to 2004 was attributed by Ellis et al. (2015) to N inputs from atmospheric
deposition. During years of high atmospheric inorganic N loading, N deposition
accounted for up to 6.9% of organic carbon production in the lake (Ellis et al. 2015). The
long-term range in inorganic N deposition (wet plus dry) to the lake was 3 to
13 gN/ha/day (1.1-4.7 kg/ha/yr) with a mean of 7.6 g N/ha/day (2.8 kg N/ha/yr). During
years that received high atmospheric N loading, deposition accounted for up to 7% of
organic carbon production in the lake.
7.2.3.2 Surface Water Nitrate
As summarized in the 2008 ISA, high concentrations of NO3 in lakes and streams,
indicative of terrestrial ecosystem N saturation, have been found at a variety of locations
throughout the U.S. (Table 7-2). Surface water NCh is a chemical indicator for both
eutrophication and acidification. NOs contributes to the acidity of many lakes and
streams in the eastern U.S. that have been affected by acidifying deposition, especially
during spring months and under high-flow conditions. Nevertheless, in the 2008 ISA
there was little or no apparent relationship between recent temporal trends (decreases) in
N deposition and trends in NO3 concentrations in surface waters in the eastern U.S. This
observation is in sharp contrast to observed relationships between S deposition and SO42
concentrations in surface waters, especially in the northeast (Section 7.2.3.6'). These
results likely reflect the complexities of N cycling within terrestrial and aquatic
ecosystems (U.S. EPA. 2008a'). Key processes include vegetative uptake and
denitrification. The former removes bioavailable N; the latter results in N transport back
to the atmosphere. Uptake by plants and microorganisms in the terrestrial environment of
atmospherically deposited N precludes drainage water acidification and base cation
leaching that would occur if excess N leached as NO3 from the terrestrial to aquatic
ecosystems. While great uncertainty exists and the timescales of N saturation may be
longer than previously considered (e.g., centuries rather than decades), the long-term
retention of N deposited to forested regions and consequent dampening of deposition
effects on surface waters is unlikely to continue indefinitely (Aber etal.. 2003).
Moreover, spatial patterns in NO3 concentrations in surface waters across the
northeastern U.S. are qualitatively consistent with atmospheric N deposition although
there is considerable variation in these relationships, and that variation appears to be
associated in large part with land use and watershed attributes. In the Western U.S.
Rocky Mountains there is a strong positive correlation between surface water NO3
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concentrations and atmospheric N deposition (Elser et al.. 2009b; Bergstrom and Jansson.
2006V
Studies of several types have been conducted in recent years to elucidate processes
affecting surface water NOs . including experimental studies, isotopic analyses,
monitoring, and observational studies. Seasonality in surface water chemistry can be
caused, in part, by differential hydrologic flows from watershed seeps and glaciers. These
flows can influence NO? leaching to surface waters. O'Driscoll and DeWalle (2010)
showed that seeps are generally NO, sinks with NO3 concentrations decreasing
downslope from seep locations in Baldwin Creek in southwestern Pennsylvania. During
cold and wet periods, however, the seeps frequently acted as NO3 sources to the stream.
These locations where upwelling groundwater saturates the surface for most of the year
and excess groundwater can be delivered to the stream channel via surface flow paths
may provide seasonally linked water quality functions that can modify the effects of N
deposition.
In snow-influenced ecosystems, the hydrology of snowmelt can affect N cycling. Since
the 2008 ISA, new research on characterization of NO3 in glacial- and snowpack-fed
lakes indicates that effects of N deposition may be modified by glacial and snowpack
melting influence. In two sets of high-elevation lakes in the western U.S.: those fed by
snowpack melt alone and those fed by both glacial and snowpack meltwaters, the NOs
concentrations in the glacially influenced lakes were one to two orders of magnitude
higher than in the lakes that were fed only by snowmelt (Saros et al.. 2010V A
comparison of nutrient concentrations, water transparency, algal biomass, and fossil
diatom species richness in the lakes suggested that the presence of glaciers in alpine
watersheds of the western U.S. more strongly influences NO3 concentrations in
high-elevation lake ecosystems than other geomorphic or biogeographic characteristics.
The higher concentration of NO? in glacial meltwater relative to seasonal snowpack
meltwater was attributed, at least in part, to reduced contact with watershed soils where
microbial communities could rapidly assimilate the available N. This contrasts with
snowmelt watersheds where the meltwater typically percolates through soils before
reaching the streams (Saros et al.. 2010).
Three new additional studies highlighted the use of stable isotopes for improving
understanding of NO3 in N cycling. Curtis et al. (2012) used the dual isotope technique
at four moorland watersheds in Great Britain to investigate NO3 production in surface
waters. An estimated 79-98% of the annual median NOs had been microbially produced
indicating that both reduced and oxidized N deposition may cycle through the microbial
flora and contribute similarly to NO3 leaching. This is important because atmospheric
deposition of NH44" has been increasing in many areas while deposition of oxidized N
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forms (NOy) has decreased (Chapter 2). Goodale et al. (2009) characterized the amount,
form, isotopic composition (15N and 180), and seasonality of stream N in subwatersheds
of the Susquehanna River. Atmospheric deposition contributed substantial N to this river,
which provides two-thirds of the annual N load to Chesapeake Bay. Retention of
atmospherically deposited N in the watershed was estimated to be higher than 95%.
Nevertheless, stream NO;, patterns exhibited substantial seasonality. Peak values of
N03 (14-96 (j,eq/L) were reached during summer. Lowest values (<1 |icq/L) occurred in
October. The summer season increase in net soil nitrification and in-stream heterotrophic
N uptake in response to litterfall during autumn were identified as likely important
drivers of the observed NO;, seasonality. Using stable isotope analysis, atmospheric
deposition was identified as an important source of stream NOs, concentration at a
Iow -NOb site at Fernow Experimental Forest, West Virginia (Rose et al.. 2015b). Based
on more than 30 years of monitoring data, three hardwood watersheds appeared to be less
responsive to changes in N deposition than the one study watershed that had coniferous
vegetation. The percentage of stream NO, concentration contributed by atmospheric
deposition in the study watersheds increased during high-flow periods.
7.2.3.3 Dissolved Inorganic Nitrogen
DIN is the sum of the concentrations of NO; . NH3 and nitrite in a water body. In the
2008 ISA, a study evaluating the relationship between wet deposition and DIN
concentration in 4,296 lakes across Canada, Europe, and the U.S. showed a significant
correlation between increases in DIN concentration and increasing N wet deposition
(Bergstrom and Jansson. 2006). The DIN:TP ratio was demonstrated to be a better
indicator of N or P limitation than the TN:TP ratio r(Bergstrom. 2010); Section 7.2.3.51.
7.2.3.4 Nitrification and Denitrification
It was well known at the time of the 2008 ISA that nitrification and denitrification
(discussed in Chapter 4) are quantitatively important portions of the N cycle and that
these processes can be influenced by atmospheric inputs of oxidized and reduced N.
More recent research has further substantiated these earlier findings and provided
additional quantitative context. Most of the deposited NH4+ that is not taken up by
vegetation is quickly nitrified to NOs in soils and drainage water. At some locations,
new research suggests that denitrification may play a larger role than was previously
recognized.
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Deposited NH44" is often either taken up by vegetation or nitrified to NO? . which is more
mobile in soils than NH4+. The NOs . in turn, can be leached to drainage water or
denitrified and released back to the atmosphere as gaseous N2O. The process of
denitrification is important because it effectively removes deposited N from aquatic and
terrestrial ecosystems, reducing the potential for acidification or eutrophication, but
facilitating redeposition at other locations. During the nitrification process, NH4+ is
oxidized to NO3 and the NO3 that is produced can contribute to acidification of soil and
drainage waters. The 2008 ISA concluded that nitrification in soil solution is stimulated
at soil C:N ratios less than about 20 to 25. Excess N supply reduces competition among
plants and microbes for available NH4+ to the point that net nitrification occurs (U.S.
EPA. 2008a; Aberet al.. 2003). Since the 2008 ISA additional isotope, modeling,
observational, and experiment studies have further characterized denitrification
processes.
Nitrous oxide (N2O), which is emitted to the atmosphere during the process of
denitrification, is a potent greenhouse gas. Beaulieu et al. (2011) presented results of 15N
tracer addition to 72 headwater streams draining multiple land uses across the U.S.
Denitrification in the streams produced N2O at rates that increased with stream NO3
concentration. The study streams were mostly sources of N2O to the atmosphere.
Estimation of N2O emissions from streams in this study were three times higher than
those estimated by the Intergovernmental Panel on Climate Change. Thus, results of this
study suggested that the process of denitrification may be quantitatively more important
than has been widely recognized. In another new isotopic study, Mulholland et al. (2009)
measured denitrification rates using 15N tracer addition to 49 streams, including
reference, agricultural-impacted, and suburban-urban streams. The fraction of total NO3
removed from stream water by denitrification ranged from 0.5 to 100%, with a median of
16%. It was related to NH4+ concentrations and ecosystem respiration rate. Although the
areal denitrification rate increased with increasing NO3 concentration, the efficiency of
N03 removal from water via denitrification declined. This resulted in a smaller
proportion of stream water NO3 load removed over a given length of stream at higher N
loading.
A new study by Bellinger et al. (2014) showed that bacterially mediated denitrification in
lake sediments can partly ameliorate the effects of N loading from the atmosphere by
permanently removing some of the N inputs. They modeled sediment nitrification and
denitrification in a large embayment of western Lake Superior. Rates of nitrification and
denitrification were inversely related, suggesting that these processes may be decoupled
in sediments. McCrackin and Elser (2012) also measured denitrification in sediments, in
this case from lakes in the Colorado Rocky Mountains. The study lakes received either
elevated (5-8 kg N/ha/yr) or low (<2 kg N/ha/yr) inputs of atmospheric N deposition.
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The NOs -N concentration was significantly higher in high-deposition lakes
(0.1582 mg/L) compared to low deposition lakes (0.0462 mg/L). The researchers
concluded that the sampled lakes were capable of removing a significant portion of N
inputs via denitrification in the lake sediment. They found no difference between
high- and low-deposition lakes in the extent to which chronic N loading has altered
sediment denitrification capacity. The abundance of denitrifying bacteria in this study
was largely related to light availability. Results of this new research by McCrackin and
Elser (2012) support growing evidence that lakes can play important roles in N removal
although current levels of N deposition have not altered the abundance of denitrifying
bacteria or saturated the capacity for sediment denitrification in Rocky Mountain lakes.
An earlier study by McCrackin and Elser (2010) measured rates of denitrification and
N2O production during denitrification in the sediments of 32 Norwegian lakes at the high
and the low ends of a gradient of atmospheric N deposition. They also found that
denitrification varied with N loading. Denitrification and N2O production rates averaged
41.7 and 1.1 |imol N/m2/h, respectively, for the lakes that received relatively high levels
of N input. There was no detectable denitrification or N2O production in the low
atmospheric N deposition lakes. Experimental NO3 additions stimulated denitrification
in the sediments of all lakes regardless of the N deposition level. These findings
suggested that lake sediments can efficiently remove NO3 from lake water. This capacity
does not appear to have been saturated under conditions of moderate chronic N loading.
The findings also suggested that lake sediments may be an important source of N2O
emissions, which play a role in climate warming, particularly in areas that are subject to
elevated N deposition levels.
7.2.3.5 Trophic Status Indices
Trophic status is a way of characterizing bodies of water in terms of their productivity.
Nutritional responses of aquatic ecosystems to atmospheric N deposition are heavily
dependent on surface water P concentrations. Thus, various chemical ratios of N to P can
be useful as indices of trophic status, especially in evaluating eutrophication potential. In
the 2008 ISA, various trophic status indices were described, including total N to total P
(TN:TP), DIN:TP, DIN to total dissolved P (DIN:TDP), DIN to soluble reactive P
(DIN:RP), and dissolved inorganic N to the ratio of chlorophyll a to total P
(DIN: [chlorophyll a:TP]). Algal growth has been reported to be limited at DIN:TP values
between about 5 and 20 (Bergstrom and Jansson. 2006; Downing and McC'aulev. 1992;
Morris and Lewis. 1988; Grimm and Fisher. 1986; Schindler. 1980). When DIN:TP ratios
are high, growth stimulation, N and P colimitation, or P limitation commonly occurs
(Sickman et al.. 2003). In a Swedish lake survey reviewed in the 2008 ISA, N limitation
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occurred in lakes where the DIN:TP ratio was less than 7 (DIN concentrations <33 (j,M
N/L). Colimitation ofN and P was found in lakes with DIN:TP ratio between about 8 and
10, and P limitation at DIN:TP values greater than 10 (Berestrom et al.. 2005). Other
thresholds for N limitation were reported in the literature to occur at DIN:RP ratios <4
(Lohman and Priscu. 1992) and <10 (Wold and Hershev. 1999). Berestrom et al. (2005)
reported an index, (DIN: [chlorophyll a:TP]) to assess the eutrophication of lakes in
response to N deposition.
Many new studies have been conducted in recent years that have addressed nutrient
limitation in aquatic ecosystems and the relative importance of N versus P loading in
controlling eutrophication processes. The earlier paradigm that freshwaters are typically
P limited has now been replaced by a general understanding that both N and P can be
important. Nutrient limitation can be a dynamic and transient process. Conditions can
vary among water bodies and within a given water body over time. A wide range of
studies of a variety of types have been conducted since the 2008 ISA that address N and
P stoichiometry, suggest other trophic status indices, and elucidate associated biological
responses. Studies that address biological responses to changes in trophic status indices
are discussed further in Chapter 10.
Gibson and O'Reilly (2012) used ecological stoichiometric theory to couple the cycles of
N and P in a headwater stream in southern New York by investigating relationships
between N and P uptake and the extent to which organic matter stoichiometry was related
to nutrient uptake. Higher ecosystem respiration was associated with higher NH/ and P
uptake. Relative nutrient uptake and the ratio of NH4 to soluble reactive P uptake was
strongly predicted by organic matter stoichiometry in the stream. Seasonal input of leaf
litter that had a low N:P ratio contributed to enhanced NHV uptake. Gibson and O'Reilly
(2012) concluded that integrating stoichiometry with metabolic controls can inform
nutrient dynamics and frame the cycles of N and P in streams.
As reported in Chapter 10 and summarized here, Berestrom et al. (2008) evaluated
phytoplankton responses to N and P enrichment in unproductive Swedish lakes along a
gradient of atmospheric N deposition. They found that regional and seasonal patterns in
nutrient limitation were related to the level of N deposition. In the south, high N
deposition was accompanied by high lake DIN concentrations during early summer, with
subsequent P limitation. Later in the summer, DIN concentrations declined and lakes
switched to N and P colimitation, and then to N limitation. Berestrom et al. (2008)
concluded that N limitation is probably the natural state of these unproductive lakes. P
limitation has been induced by increased N availability caused by atmospheric N
deposition. This has important implications for the trophic status of surface waters in the
U.S., especially as atmospheric N deposition continues to decline.
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The 2008 ISA reported several studies that investigated relationships between freshwater
N concentration and primary production (Bergstrom and Jansson. 2006; Bergstrom et al..
2005; Fenn et al.. 2003a'). Primary production was reflected in such variables as
chlorophyll a concentration and the DIN:TP ratio. In a follow-up study, Bergstrom
(2010) documented how N:P ratios (TN:TP and DIN:TP) vary in oligotrophic lakes
located in northern Europe and the Rocky Mountains. Nutrients (N, P, N + P, control)
were added to water from 28 unproductive lakes. More than half (54%) of the
oligotrophic study lakes had TN:TP mass ratio <25. The DIN:TP ratio was a better
indicator than the TN:TP ratio for nutrient limitation of phytoplankton because TN may
include a large fraction of biologically unavailable N. A shift was observed from N to P
limitation when the DIN:TP mass ratio increased from 1.5 to 3.4. High DIN:TP,
indicating P limitation, was generally found in alpine lakes with low to moderate N
deposition and in boreal lakes with high N deposition (>13 kg N/ha/yr).
In the northeastern U.S., Crowlev et al. (2012) investigated patterns of nutrient limitation
relative to N deposition. In this study, N deposition appeared to be insufficient to drive
nutrient limitation from N towards P. However, patterns differed in the Adirondack
subregion, which might provide an early warning indication of increasing P limitation
caused by N addition. Results of this new study by Crowlev et al. (2012) suggested that
foliar chemistry of dominant tree species in northeastern forests may serve as a predictor
of regional lake chemistry in the Northeast. This was attributed to the fact that increased
atmospheric N loading makes reactive N available for uptake into plant tissues as well as
increasing N leaching to surface waters. Foliar N increased with increasing N deposition
for each of the most frequently observed tree species. Effects of N deposition on foliar N
were evident independent of relationships between precipitation or average temperature
and foliar N. Foliar N increased with increasing N deposition beginning at N deposition
of 9-10 kg N/ha/yr for most tree species. There was an apparent peak in foliar N at N
deposition about 12 kg N/ha/yr. In Adirondack lakes, and also in lakes across the
northeastern region, lake DIN increased with N deposition.
A recent study by Elser et al. (2009b) showed that concentrations of chlorophyll,
indicative of primary production, were twice as high in high-elevation lakes in Colorado
that received relatively high atmospheric N deposition as compared with low-deposition
lakes. High-deposition lakes had an increased frequency of primary P limitation and a
decreased frequency and magnitude of response to N and to combined N + P enrichment.
This research further supported the hypothesis that N deposition has likely shifted
nutrient supply from a relatively balanced but mainly N deficient state to more
consistently P limited conditions.
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7.2.3.6
Sulfate Concentrations
The 2008 ISA documented some declines in surface water SO42 in response to
decreasing SOx deposition over previous decades. Measurements of SO42 concentration
in surface waters provide important information regarding the extent of cation leaching in
soils and how SO42 concentrations relate to ambient levels of atmospheric S deposition.
Assessments of acidifying deposition effects reported in the 2008 ISA dating from the
1980s showed SO42 to be the primary strong acid anion in most, but not all,
acid-sensitive waters in the U.S. (Webb et al. 2004; Driscoll et al.. 2001b; Driscoll et al..
1988; Driscoll and Newton. 1985). At the time of the 2008 ISA, available data indicated
that before the peak of S emissions in the 1970s, SO42 in surface waters increased in
response to S deposition. After the emissions peak, there were regional decreasing trends
in S042 surface water concentrations in the 1980s and 1990s, particularly in the
Northeast. In some regions, particularly the Blue Ridge Mountain region in Virginia,
surface water SO42 remained high even as emissions declined, due to the release of
historically deposited S from soils into surface water. The rate of surface water response
was variable by watershed, and some model results suggested that recovery may be
delayed as accumulated S leaches from watersheds, even as emissions and deposition
decline.
Studies of S cycling reported in the 2008 ISA emphasized the importance of S adsorption
and desorption and their interactions with soil pH (see Chapter 4). In addition, internal
watershed sources of SO42 (e.g., S mineralized from soil organic matter), which were
previously relatively minor sources to surface water in the northeastern U.S., have
become proportionately more important as S deposition has declined (see Chapter 4).
Both chronic and episodic leaching of SO42 from terrestrial ecosystems influence surface
water acidification. The literature reviewed in the 2008 ISA did not address how
terrestrial S cycling affects water sulfate concentrations, and there are no new studies that
use S042 concentration as an indicator of surface water acidification.
7.2.3.7 Base Cation Concentrations
Quantitatively, the most important component of the overall surface water acidification
and chemical recovery responses has been change in base cation supply (Charles and
Christie. 1991). As stated in the 2008 ISA, decreases in base cation concentrations in
surface waters in the eastern U.S. over the past two to three decades have been ubiquitous
and closely tied to trends in SO42 concentrations in surface waters. In most regions, rates
of decrease for base cations have been similar to those for SO42 plus NO3 , with the
exception of streams in western Virginia and in the Shenandoah National Park, which are
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strongly affected by SO42 adsorption on soils. The 2008 ISA concluded that acidifying
deposition has been an important cause of decreasing amounts of exchangeable base
cations on soils. This influences base cation leaching to surface waters and soil buffering
of deposition acidity. Surface water base cation concentrations increase with acidification
and generally decrease under reduced levels of acidic deposition. However, in some
watersheds that have acidified, concentrations of Ca2+ and other base cations have
become substantially reduced from likely preindustrial levels, in response to depletion by
many years of acidic deposition. This base cation depletion constrains surface water ANC
and pH recovery. This was described in the 2008 ISA. Recent results have further
corroborated these earlier findings. More recent studies have included experiments
(liming), modeling, and gradient studies with a geographical focus on the southern
Appalachian Mountains, Colorado, and the Hubbard Brook Experimental Forest (HBEF)
in New Hampshire.
Base cations are contributed to soils and surface waters through weathering and
atmospheric base cation deposition (Chapter 4). Estimates of base cation weathering
(BC„) largely control simulated base cation concentrations in drainage water and are
needed for evaluating critical loads (CLs) of surface water acidity using steady state
models (Chapter 8). McDonnell et al. (2012) developed an approach for regionalizing
BC„ using regionally specific empirical relationships. The dynamic model MAGIC was
used to calibrate BCW in 92 watersheds distributed across the southern Appalachian
Mountains. About one-third of the study region had BC„ estimates that were less than
100 meq/m2/yr, with lowest values for watersheds located in national parks and
wilderness areas.
Increased atmospheric transport of dust enriched with nutrients, metals, and base cations
to alpine watersheds in the western U.S. has been shown to alter lake biogeochemical
processes. Ballantvne et al. (2011) examined temporal trends in dust deposition from
sediment cores from two lakes in Colorado with distinct physical and chemical
properties. Recent increases in dust deposition and its enrichment in various elements,
including Ca, has contributed base cations to drainage water and altered the
biogeochemistry of the two study lakes. Liming studies confirm ecosystem responses
when depleted base cation pools in soils are restored by addition of base cations
experimentally or for management purposes. Cho et al. (2012) treated Watershed 1 (Wl)
at HBEF with 45,000 kg of calcium silicate (wollastonite, CaSiCh) in an experiment to
assess the role of Ca supply in supporting the structure and function of base-poor forested
ecosystems. About 2% of the added Ca was exported from Wl in stream water during the
first 6 years after treatment. The study authors documented increases in the
concentrations of Ca and decreases in the concentrations of H+ and inorganic aluminum
in stream water. Stream ANC increased. Cho et al. (2012) concluded that the treatment
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appeared to be effective in mitigating the acidifying impacts of acidic deposition,
although most of the added Ca remained in the organic soil horizon.
7.2.3.8 Surface Water Acid Neutralizing Capacity
The most widely used measure of surface-water acidification is ANC. It is often
determined by Gran titration (titrated ANC) or calculated from the charge balance. As
described in the 2008 ISA, this measurement is the primary chemical indicator for
assessing past effects of acidifying deposition and the recovery expected from decreasing
atmospheric deposition (Aber et al.. 2003; Bulger et al. 2000). Titrated ANC is useful
because it reflects the ANC of the complete chemical system, which is typically
decreased by acidic deposition in acid-sensitive landscapes. The ANC is associated with
the surface water constituents that directly contribute to or ameliorate acidity-related
stress, in particular pH, Ca2+ and inorganic Al concentrations. The ANC is generally more
stable than pH and it reflects sensitivity and effects of acidification in a linear fashion
across the full range of ANC values. Therefore, ANC is usually the preferred indicator
for assessment of surface water acidification and recovery. Both titrated and calculated
ANC values are commonly determined in studies aimed at resource characterization or
long-term monitoring. They can differ greatly, depending on the amount of organic
acidity in the water. Information on biological indicators of acidification such as fish
species richness that are associated with changes in ANC are presented in Chapter 8.
7.2.3.9 Surface Water pH
Surface water pH is also commonly used as an indicator of acidification. This was the
case in the 2008 ISA and nothing has changed in that regard in more recent years. It
correlates with other biologically important components of surface water acid-base
chemistry, including organic acidity and concentrations of inorganic Al and Ca2+. Low
pH can have direct toxic effects on aquatic species (U.S. EPA. 2008a; Driscoll et al..
2001b), and this was widely understood at the time of the 2008 ISA. Low pH can disturb
normal ion osmoregulation in aquatic biota. Threshold pH levels for adverse biological
effects are described in Chapter 8 and summarized briefly here. A pH value of 6.0 is
often considered the level below which biota are at increased risk from acidification.
Below pH 5.5, inorganic Al often becomes the greatest threat to aquatic biota. In the 2008
ISA, increasing trends in pH in surface waters in the northeastern U.S. were common
through the 1990s up to 2004. Rates of change have generally been small.
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Acidification may occur as a chronic or an episodic condition. The 2008 ISA defined
chronic acidification by reference to annual average conditions, often quantified as
summer and fall chemistry for lakes and as spring baseflow chemistry for streams.
Episodic acidification refers to conditions during rainstorms or snowmelt when water has
a relatively short residence time in soil before entering surface water. During these
stormflow events, proportionately more water drains through upper soil horizons,
providing less neutralization of atmospheric acidity compared with flow through deeper
soil horizons. Episodes of acidification are typified by lower pH, lower ANC, and higher
inorganic A1 concentration in surface water than during baseflow conditions. The
short-term change in chemical conditions has important effects on aquatic biota. Episodic
acidification that is toxic or lethal to fish and/or other aquatic biota may occur in streams
which under average conditions are capable of supporting biota (Chapter 8). Episodic
declines in pH and ANC are nearly ubiquitous in drainage waters throughout the eastern
U.S. (Wigington et al.. 1992V They are caused partly by acidifying deposition (SO42 ,
NO3 ) and partly by natural processes.
Surface water pH (and other parameters) is sensitive to hydrological conditions at the
time of sampling. Burns et al. (2008b) sampled 12 Catskill mountain streams within the
Neversink River watershed in New York for stream chemistry. The measured pH values
in 2003 were generally lower than those in 1987 and this was attributed to higher stream
flow during summer of 2003, rather than to chronic acidification during the intervening
period. There were no significant differences in biota observed between 1987 and 2003.
Surface water pH is a common alternative to ANC as an indicator of acidification.
However, at pH values above about 6.0, pH is of less value as an indicator of either
sensitivity to acidification or level of effect. In addition, pH measurements (especially at
these higher values) are sensitive to levels of dissolved CO2 in the water. There is no new
information regarding the use of pH as an indicator of surface water acidification.
7.2.3.10 Surface Water Aluminum
As stated in the 2008 ISA, the concentration of inorganic Al in surface waters is an
especially useful indicator of acidifying deposition effects because (1) it is toxic to many
species of aquatic biota (Chapter 8). and (2) it generally does not leach from soils to
surface waters in the absence of acidifying deposition (Lawrence et al.. 2007; Driscoll et
al.. 1988). with exceptions such as in the presence of acid mine drainage or relatively rare
geologic deposits. It has well-documented effects on aquatic biota at specific thresholds
(Chapter 8). There is no new information regarding the utility of inorganic Al
concentration as an acidification indicator. In the 2008 ISA, limited data suggested that
some acid-sensitive surface waters in acid-sensitive regions of the northeastern U.S. have
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elevated inorganic A1 concentrations, which have been induced by years of acidifying
deposition and pose threats to aquatic life. The 2008 ISA concluded that inorganic A1 has
well-documented effects on aquatic biota at specific thresholds. Concentrations of
inorganic A1 have decreased slightly in some surface waters in the northeastern U.S. in
response to decreased levels of acidifying deposition (U.S. EPA. 2008a) and have
generally continued to decrease.
7.2.3.11 Surface Water Dissolved Organic Carbon Concentration
An especially important, and relatively new, area of research focus in the context of
recovery from surface water acidification has been the observed increase in dissolved
organic carbon (DOC) concentration in many surface waters recovering from
acidification. This has implications with respect to water toxicity and cycling of C and N.
The 2008 ISA reported widely observed increased concentrations of DOC in surface
waters across North America and Europe and that these increases in DOC were at least
partly related to changes in atmospheric deposition of S and N. Thus, it has been
recognized for several decades that surface water DOC concentrations have decreased to
some extent with water acidification and, therefore, would likely increase with recovery.
However, the strength of this response and the magnitude of DOC change were perhaps
under-appreciated at the time of the 2008 ISA. More recent research on this topic has
been diverse and has included experiments, observation, isotope studies, and synthesis
and integration work. Overall, they illustrate relatively large increases in DOC with
acidification recovery in some aquatic systems. This response constrains the level of
ANC, and especially pH, recovery, but decreases the toxicity of dissolved A1 by
converting some of it from inorganic to organic forms (Lawrence et al.. 2013). As a result
of this widely observed pattern, surface water DOC concentration has become a more
important indicator of acidification and chemical recovery since the 2008 ISA. DOC is
comprised of a diverse mix of organic matter and functional groups. Wood et al. (2011)
noted that dark, aromatic-rich organic matter of allochthonous origin, and with relatively
high humic content, may be more effective in ameliorating metal bioavailability and
toxicity than other organic materials. In addition, part of the protection provided by DOC
may involve physiologic mechanisms other than metal complexation (Wood etal.. 2011).
Soil mechanisms that contribute to higher DOC in surface waters are discussed in
Chapter 4.
DOC effects on N cycling have been further elucidated since the 2008 ISA. Fork and
Heffernan (2014) investigated how DOC derived from terrestrial ecosystems affects the
rate of denitrification in river sediments. They examined the extent to which higher
concentrations of DOC in black water rivers stimulate or inhibit denitrification. Results
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supported the hypothesis that terrestrially derived DOC indirectly inhibits denitrification
via a decrease in autochthonous production. Therefore, changes in DOC concentration
might reduce the ability of inland waterways to remove reactive N from the aquatic
ecosystem. Results of this study further suggested that the indirect effects of DOC on
light will be important in determining how N cycling responds to increasing
concentrations of DOC in surface waters. This may have consequences for eutrophication
of downstream ecosystems.
7.2.4 Monitoring Data
Monitoring data provide temporal trends of biogeochemical processes and indicators
associated with eutrophication and acidification. These data document and quantify
changes that occur in response to environmental stressors, including S and N deposition,
and ecosystem sensitivities. Many monitoring studies have been ongoing for one or two
decades, in some cases longer. Such data were available and incorporated into the 2008
ISA. Since that time, nearly a decade's worth of additional data has been added to some
of these databases. This is noteworthy because temporal variability often obfuscates
documentation of trends over time where and when changes are relatively small. The
availability of these additional data facilitates trend detection now, compared with 2008.
Since the early 2000s, U.S. EPA, together with the states, tribes, and other entities and
individuals, have collaborated on a series of statistically representative surveys (National
Aquatic Resource Surveys [NARS]) of the nation's waters, including surveys of lakes
(U.S. EPA. 200%). streams (U.S. EPA. 2016d). wetlands (U.S. EPA. 20166). and coastal
waters (U.S. EPA. 2016c). Based on standard sampling and analysis protocols and
consistent quality assurance, these surveys periodically assess the magnitude and spatial
extent of water quality issues and concerns across the U.S. Additional long-term
monitoring surveys in the U.S. include the USGS NAWQA and U.S. EPA's Temporally
Integrated Monitoring of Ecosystems (TIME) and the Long-Term Monitoring (LTM)
program.
7.2.4.1 Eutrophication Monitoring
A number of monitoring studies have been conducted or continued in recent years that
have documented the effects of N input on the NO.? flux or trophic state of freshwaters.
Monitoring studies published since the 2008 ISA are highlighted in this section.
Monitoring data have been applied to infer the N saturation status of watersheds in
forested ecosystems using NO? leaching to surface waters. Eshleman et al. (2013)
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evaluated changes in the concentrations of NO, in streams impacted by atmospheric N
deposition in the Appalachian Mountains during the period 1986-2009. Regional NOx
emissions progressively decreased during the study period. Decreases in the annual
surface water NOs concentration and the NO.? yield were observed over the study
period, which corresponded to generally comparable declines in annual wet N deposition.
They applied a kinetic N saturation model that suggested that all nine of their forested
study watersheds exhibited signs of N saturation, indicated by limited N demand and that
the study watersheds would be responsive to changes in atmospheric N inputs. Based on
trends observed in their analysis, Eshleman et al. (2013) concluded that further reductions
in N deposition might be expected to produce additional reductions in stream water N
loads. An early sign of recovery from N saturation in these watersheds is a decrease in
N03 concentration in stream water during the vegetation dormant period. The most
highly N saturated watersheds were located in western Maryland where atmospheric N
deposition has historically been relatively high; the least N saturated forests were located
in the southernmost portion of the study region where N deposition has been lower.
Long-term monitoring of nutrient dynamics has also been conducted in the western U.S.
Mast et al. (2014) measured long-term changes in stream NO3 concentration over three
decades at the Loch Vale watershed in Rocky Mountain National Park. The
concentrations of NO3 in stream water increased during the early 1990s, peaked in the
mid-2000s, and then declined by more than 40%. The recent decreases corresponded with
decreases in NOx emissions and N deposition. As was found by Eshleman et al. (2013) in
Maryland, similarities in the timing and magnitude of NO3 concentrations in stream
water and N deposition suggested that stream chemistry is responding to changes in
atmospheric deposition of N. However, the response was complicated in this case by a
drought in the early 2000s that enhanced N export for several years. Results presented by
Mast et al. (2014) illustrated that stream chemistry can respond rapidly to changes in N
deposition in high-elevation western watersheds, but the dynamics of this response can be
complicated by changes in weather or climate.
Generally comparable results have been found in Europe. For example, Sponseller et al.
(2014) evaluated the importance of ecosystem characteristics, pollution input gradients,
and aquatic habitat variables to patterns in NO3 concentration at 115 stream monitoring
sites across Sweden. Surface water NOs concentration trends corresponded with
gradients in N inputs, including the amount of agricultural land use. Concentrations of
inorganic N in streams were seasonal, with peaks during winter dormant periods. In
contrast, organic N showed limited seasonality, although the summertime increases in
N03 suggested the importance of soil organic N production and export, which are
influenced by temperature. Sponseller et al. (2014) concluded that N trends were linked
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to changes in terrestrial ecosystem characteristics, variation in N inputs, and the structure
of the aquatic environment.
7.2.4.2 Acidification Monitoring
A number of freshwater monitoring studies have been conducted using data collected
over the previous one to three decades that have documented ecosystem chemical damage
and recovery caused by acidifying deposition of S and/or N. Many of these studies have
been conducted in the U.S., especially in the Northeast and the southern Appalachian
Mountains (Table 7-3). including studies since 2008. Studies conducted in Canada and
Europe further corroborated these findings. As reported in the 2008 ISA, lake and stream
ANC values decreased throughout much of the 20th century in a large number of
acid-sensitive lakes and streams throughout the eastern U.S. This effect has been well
documented in monitoring programs, paleolimnological studies, and model simulations.
Since about 1990, the ANC values of many previously acidified lakes and streams have
shown some increases, but such increases have been relatively modest in most cases.
Chemical recovery in previously acidified surface water is required to support subsequent
biological recovery. In general, biological recovery has lagged behind chemical recovery
in previously acid-impacted surface waters (Chapter 9).
Two surface water chemistry monitoring programs that have been especially useful to
inform the assessment of aquatic ecosystem responses to changes in acidic atmospheric
deposition are TIME (Stoddard et al.. 1996) and LTM (Stoddard et al.. 1998; Ford et al..
1993). These U.S. EPA monitoring efforts focus on portions of the U.S. most affected by
the acidifying influence of S and N deposition, including lakes in the Adirondack
Mountains of New York and in New England, and streams in the Northern Appalachian
Plateau and the Blue Ridge physiographic provinces in Virginia and West Virginia. Both
projects are operated cooperatively with numerous collaborators in state agencies,
academic institutions and various federal agencies, kahl et al. (2004) summarized
20 years of chemical monitoring data from regional U.S. EPA programs in the northern
and eastern U.S. Surface water chemistry improved over the 20-year period in many
lakes and streams; specifically, moderate but significant increases in ANC and pH were
observed. More recent monitoring studies are highlighted below and in Table 7-3.
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Table 7-3 Monitoring and resurvey results of aquatic acidification and/or chemical recovery since the 2008
Integrated Science Assessment for Oxides of Nitrogen and Sulfur-Ecological Criteria.
Ambient
Nutrient
N/S
N/S
Acidification Enrichment Type of
Time
Deposition
Addition
Process
Indicator Indicator Ecosystem
Region
Period
(kg/ha/yr)
(kg/ha/yr)
Effect of Deposition
Publication
Chemical
pH, ANC, N/Ap 12 streams
Adirondack
1980s-
Variable
N/Ap
On average, pH increased
Lawrence et al. (2011)
recovery
S042", DOC
Mts.
2008
by 0.28; ANC increased
13 peq/L; rate of decrease
in stream SO42"
concentration was
2 pmol/L/yr between 1999
and 2008 at a high-DOC
stream and 0.73 pmol/L/yr
at a low-DOC stream.
Chemical
ANC, DOC NO3- TIME lakes
Adirondack
1991-
Variable
N/Ap
Percent acidic lakes
Waller et al. (2012)
recovery
Mts.
2007
decreased from 15.5 to
8.3%; calculated ANC
increased at more than
twice the rate as Gran
ANC, which was attributed
to increase in DOC.
Chemical
S042", DOC N/Ap 9 lakes
Maine
1993-
Wet
N/Ap
Decreases in lake SO42"
SanClements et al.
recovery
2009
S = 6.2
correlated with increases in
(2012)
(1980) to
DOC and a shift from
1.5 (2010)
microbial to terrestrially
N = 3
derived organic matter.
Chemical
NO3" NO3" Lakes
Adirondack
2000-
N/Av
N/Ap
Lake NO3" concentrations
Strock et al. (2014)
recovery
Mts. and
2010
declined at rate of
New
-0.05 peq/L/yr and there
England
was a shift to nontoxic
(organic) Al.
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Table 7-3 (Continued): Monitoring and resurvey results of aquatic acidification and/or chemical recovery since
the 2008 Integrated Science Assessment for Oxides of Nitrogen and Sulfur-Ecological
Criteria.
Ambient
Nutrient
N/S
N/S
Acidification
Enrichment
Type of
Time
Deposition
Addition
Process Indicator
Indicator
Ecosystem
Region Period
(kg/ha/yr)
(kg/ha/yr)
Effect of Deposition
Publication
Chemical
recovery
Ali
N/Ap Resurvey of NE U.S. 1986- N/Av N/Ap In 2001, only 7 lakes,
113 lakes 2001 representing 130 lakes in
population, had Ali
>2 pmol/L (toxic threshold
to brook trout), compared
with 20 sampled lakes
(representing 449 lakes in
population) in 1986.
Warbv et al. (2008)
Chemical
recovery
S042"
NOs"
ANC
NO3" 2 streams Western 1990- N/Av N/Ap Concentrations of SO42" in
Maryland 2005 stream water decreased at
a rate of about 3 peq/L/yr in
response to 34% reduction
in wet S deposition. Trends
in stream NO3" appeared
to be related to watershed
factors, especially forest
disturbance. Rate of ANC
increase during the period
1996-2005 was about half
the rate of the entire study
period, suggesting that
chemical recovery may be
slowing or coming to an
end.
Eshleman et al. (2008)
Chemical
recovery
Ca2+, Mg2+,
SO42"
NO3" 2 streams Bear Brook, 1988- Wet S = 6 N/Ap Concentrations of Ca and
(manipulated Maine 2006 (1987) to Mg in stream water
and control) 2.3(2006) decreased more than
SO42" concentration,
causing stream
acidification in control
stream.
Navratil etal. (2010)
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Table 7-3 (Continued): Monitoring and resurvey results of aquatic acidification and/or chemical recovery since
the 2008 Integrated Science Assessment for Oxides of Nitrogen and Sulfur-Ecological
Criteria.
N/S
Addition
(kg/ha/yr) Effect of Deposition Publication
Ambient
Nutrient N/S
Acidification Enrichment Type of Time Deposition
Process Indicator Indicator Ecosystem Region Period (kg/ha/yr)
Chemical ANC N/Ap 64 streams Western 1987- Wet S = 9
recovery Virginia 2011 (1980) to
S SCM2" NOs" Stream
adsorption watershed
N/Ap
3.7 (2010)
Wet N = 4.7
(1980) to
3.0 (2010)
Noland 1991- S = 28 N/Ap
Divide, 2006
GSMNP,
Tennessee
At most sites underlain by Robison et al. (2013)
base-poor bedrock, ANC
decreased despite
reductions in S deposition.
This response was related
to depletion of base
cations.
Sulfur adsorption on soil is Cai et al. (2010)
important on average.
During large precipitation
events, SO42" was more
mobile and caused stream
acidification.
Pyrite SO42" N/Ap High Colorado 1985- N/Av N/Ap Lake SO42" concentration Mast et al. (2011)
weathering elevation 2008 decreased at a rate of
lakes -0.12 to -0.27 peq/L/yr.
Climate warming appears
to have affected pyrite
weathering and lake SO42"
concentration.
Al = aluminum; ANC = acid neutralizing capacity; Ca2+ = calcium; DOC = dissolved organic carbon; GSMNP = Great Smoky Mountain National Park; ha = hectare; kg = kilograms;
L = liter; ^eq = microequivalent; jimol = micromole; Mg2+ = magnesium; N = nitrogen; N/Av = not available; N/Ap = not applicable; NE = northeastern; N03" = nitrate; S = sulfur;
S042" = sulfate; yr = year.
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In 2007, the U.S. EPA conducted the NLA, a collaborative survey of lakes in the U.S. as
a component of the National Aquatic Resource Surveys [NARS; (U.S. EPA. 2009b) I.
More than 1,000 lakes, ponds, and reservoirs (representing nearly 50,000 water bodies)
were sampled for their water quality and biological and habitat conditions using generally
comparable field and laboratory protocols. Although the survey was not specifically
focused on acid-base chemistry, ANC and pH were among the chosen chemical
indicators used to assess biological integrity. However, due to logistical considerations,
included sites were restricted to lakes larger than 10 acres (4 ha). This constraint
eliminated many of the most acid-sensitive and acid-impacted lakes. Therefore, results of
the NLA are not necessarily reflective of acid-base status across the spectrum of lake
sizes. The NLA concluded that lake acidification was not a widespread problem, but that
there were "hot spots" of acidification stress at some locations.
The U.S. EPA also conducted a National Rivers and Streams Assessment (NRSA) during
the period 2008-2009 (U.S. EPA. 2016d). Nearly 2,000 perennial river and stream sites
were sampled, representing nearly 1.2 million miles of stream reach. Stream size ranged
from very small headwaters to very large rivers. The NRSA reported four chemical
stressors: total N, total P, salinity, and acidification. Acidification was found to be a
problem in less than 1% of the stream and river length in the U.S. (U.S. EPA. 2016d).
The USGS has several long-term monitoring programs, including the NAWQA Program
that was created in 1991 to assess the nation's water quality in 51 study units defined
primarily by major drainage divides. These units comprise approximately 50% of the
conterminous U.S. Major objectives of the NAWQA program have been to determine the
condition of the nation's streams, rivers, and groundwater; whether these conditions are
changing over time; and how these conditions are affected by natural features and human
activities. The major priority of the NAWQA program since its inception has been the
study of watersheds that have experienced impacts from agriculture and various forms of
development. The location of sites, sampling frequency, and types of measurements all
reflect this priority. Additional USGS monitoring programs have included: the
Hydrologic Benchmark Network (discontinued in 1997), the New York District of the
USGS for the water supply watershed for New York City (in the Catskill Mountain
region), and a monitoring project in the Adirondack Mountains at Buck Creek, NY.
Since 2008, these and other studies (Table 7-3) have documented and quantified the
responses of surface waters to changes in acidic deposition and other ecosystem drivers.
They have included long-term monitoring of lake or stream acid base chemistry and
resurvey of surface waters that had been previously sampled. Although these programs
were in existence at the time of the 2008 ISA, and were considered in that analysis, more
recent publications include data from the longer period of monitoring record and
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strengthen previous conclusions. These chemical indicators are reflective of biologically
relevant water chemistry.
Shorter-term studies to characterize acid-base chemistry have also provided information
on surface water quality and biogeochemistry. Kang and Mitchell (2013) studied spatial
and temporal variation in the quantity and quality of DOC, N, and S in Adirondack
Mountain surface waters over a 14-month period. This investigation included the
sampling of two upland streams, two wetland-influenced streams, and one lake outlet
(Arbutus Lake). The DOC and DON concentrations increased as water was transported
through wetland areas. Results highlighted the value of applying multiple approaches for
understanding the biogeochemistry of dissolved organic matter (DOM). The researchers
used multiple methods to characterize the DOM heterogeneity. The acid-base chemistry
of DOC has been further investigated in several other studies. Porcal et al. (2009)
confirmed that DOC concentrations in lakes and streams throughout much of Europe and
North America have increased over the last three decades. Possible reasons for this
change proposed by Porcal et al. (2009) included increased atmospheric CO2
concentration, climate warming, decreased S deposition (and associated changes in water
pH and ionic strength), and hydrologic changes caused by drought and precipitation. Any
changes in DOC concentration or properties will impact the acid-base chemistry of
surface waters and perhaps the composition of aquatic biota. In a laboratory study, Al-
Reasi et al. (2013) performed titrations for a range of freshwater DOM isolates to
elucidate mechanism of protection to organisms. In general, the proton site density (Lt)
exhibited maxima near proton binding constants (pKa) values of 3.5 and 10, reflecting the
presence of both strong and weak organic acids. The Proton Binding Index parameter was
described to summarize the chemical reactivity of DOM based on the pKa values and the
Lt. Results of this study provided a rationale for describing the protection provided by
DOM against metal, including inorganic Al, toxicity. Recent additional research has also
focused on improving scientific understanding of variation in the importance of organic
versus mineral acids in controlling the acidity of soil water and surface water. Chapman
et al. (2008) analyzed seasonality in soil water and surface water chemistry in two U.K.
headwater watersheds. Strong seasonal patterns were observed for both ANC and DOC.
Acidic deposition controlled acidity during winter, whereas organic acids were more
important during summer. The observed increase in DOC concentration in drainage water
over the previous two decades was attributed mainly to climate warming, increased CO2,
and/or decreased acidic deposition.
The amount and composition of DOC mobilized from upland soils to surface waters is an
important link in the global C cycle. The relationship between ultraviolet (UV)
absorbance and DOC concentration has been shown to reflect changes in the proportion
of DOC that is hydrophobic (aromatic, recalcitrant) and thus resistant to biodegradation.
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Dawson et al. (2009) reported a change in correspondence between UV absorbance and
DOC concentration over a period of 22 years at two moorland watersheds in Scotland.
The DOC concentration has increased over time, while the proportion of hydrophobic
DOC has decreased. A model analysis by Dawson et al. (2009) suggested that S
deposition was the only factor that could reasonably explain the observed long-term DOC
trend at both sites.
7.2.4.3 Northeastern U.S.
Taken together, results of recent acid-base chemistry studies in the northeastern U.S.
(mostly in the Adirondack Mountains), confirmed the previously observed pattern of
gradual ANC and pH recovery, in some cases, more marked decrease in inorganic Al
concentrations, and important interactions with DOC. At the time of the 2008 ISA, the
region of the U.S. most thoroughly studied to ascertain changes in acid-base surface
water chemistry over time was the Adirondack Mountains. This has not changed. Several
new studies are highlighted here that focused on Adirondack surface waters, three on
lakes and one on streams, The Adirondack Lakes Survey Corporation (ALSC) has been
monitoring Adirondack lakes for about 30 years. This work has mainly focused on
acid-base chemistry, but has also involved some fish monitoring and measurement of
parameters relevant to nutrient enrichment. Monitoring data have shown some chemical
recovery from lake acidification, as increased pH and ANC and decreased inorganic Al
concentrations.
Mitchell et al. (2013) studied 16 of the original Adirondack Long-Term Monitoring lakes
that were monitored between 1984 and 2010. There were significant declines in total S
deposition to all of the study lake watersheds during the monitoring period.
Correspondingly, significant decreases were observed overtime (-2.14 (j,mol/L/yr) in
lake S042 concentrations. They observed discrepancies in the calculated S mass balances
that were associated with discharge. These results suggested that internal S sources have
become more important to the watershed S budget as atmospheric S deposition has
decreased. The watershed supply of SO42 was lower in those watersheds that contained
lakes that had lower ANC. Limited contributions from internal sources of SO42 to the
low-ANC lakes will allow ANC recovery. Mitchell et al. (2013) further concluded that
the effects of future increases in precipitation might become more important in regulating
the amount of SO42 mobilized from internal watershed sources.
Surface water ANC and pH recovery have been documented by Lawrence et al. (2013)
and Lawrence et al. (2011) in studies of Adirondack streams and lakes. Lawrence et al.
(2011) reported results of Adirondack Mountain stream monitoring from the early 1980s
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to 2008. During that period, there was an approximate 50% reduction in atmospheric
deposition of S in the Adirondack region. On average, the pH increased by only 0.28 pH
units and ANC by 13 (j,eq/L in 12 streams that were monitored over a period of 23 years.
Larger increases in ANC and pH occurred in the monitored streams that had lower initial
ANC. In the north tributary of Buck Creek that had a relatively high DOC concentration,
the S042 concentration decreased between 1999 and 2008 at a rate of 2 (imol/L/yr. In the
adjacent south tributary, which had a lower DOC concentration, the decrease in SO42
concentration was substantially smaller, only 0.73 (imol/L/yr.
Chemical recovery from surface water acidification, and associated CL exceedance, in
the Adirondack Mountains have been accompanied by increasing concentrations of DOC
and organic acids. This has complicated and restricted recovery from acidification.
Lawrence et al. (2013) reported the chemistry of 42 Adirondack lakes from samples
collected between 1994 and 2011. They evaluated long-term changes in DOC and base
cation surplus (which calculates the ANC and includes an adjustment for strong organic
acid anions). Increases in DOC concentration during the study period contributed to
organic complexation of Al. This reduced the fraction of monomeric Al that was in the
inorganic (and potentially toxic) form from 57% in 1994 to 23% in 2011. Thus, the
higher DOC found during the latter sampling period increased the organic acidity of the
lake water and limited ANC recovery, but at the same time it decreased the toxicity of
dissolved Al to aquatic biota. Similarly, St rock et al. (2014) reported trends in recovery
from acidification of northeastern U.S. surface waters associated with Al chemistry. They
analyzed recent trends in lake chemistry using long-term data from lakes in the
Adirondack Mountains and New England. During the 2000s, the wet depostion of NO3
declined more than 50%. The lake NO3 concentration, which showed no trend prior to
2000, declined subsequent to 2000 at a rate of-0.05 (ieq/L/yr. There was a shift to
nontoxic (organic) forms of Al. Despite the Al recovery, both the ANC and pH in the
study lakes failed to show evidence of appreciable chemical recovery; rather, the lakes
continued to exhibit variable trends in ANC and pH.
Waller et al. (2012) also evaluated the response of lake watersheds in the Adirondack
Mountains to changes in SO2 and NOx emissions and deposition, in this case using data
from the TIME monitoring program collected during the period 1991 to 2007. The
percentage of Adirondack lakes that were acidic decreased from an estimated 15.5 to
8.3%. Decreases in lake water SO42 , and to a lesser extent NO3 , concentrations
generally were accompanied by increases in lake ANC. However, the calculated ANC
increased more than twice as much as the Gran titrated ANC. This discrepancy is
important for assessing lake recovery from acidification. It appeared to be due mainly to
increases in DOC (and organic anions) that accompanied decreases in concentrations of
the strong mineral acid anions, SO42 and NO3 . The difference between calculated ANC
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and Gran titrated ANC was generally consistent with trends of increasing DOC. Waller et
al. (2012) concluded that assessments of surface water recovery from previous
acidification should consider differences in DOC concentration and in the manner in
which ANC is calculated and quantified.
Interpretation of long-term trends in Adirondack surface water chemistry, as summarized
above, has also been augmented by results of the repeated survey of chemistry of lakes
initially surveyed several decades previously. Warbv et al. (2008) resurveyed 113 lakes
throughout the Northeast in 2001 that had previously been sampled by the U.S. EPA in
1986 to assess chemical recovery from lake acidification. Decreases in total Al and
inorganic Al concentrations were widespread, and were largest in the Adirondack
Mountains (-2.59 to -4.60 (imol/L). In 2001, only 7 study lakes (representing 130 lakes
in the population) had inorganic Al concentrations above a toxic limit of 2 |imol/L.
compared with 20 sampled lakes (representing 449 lakes in the population) in 1986.
Thus, it was estimated that in 2001 more than 300 northeastern lakes no longer had
summer inorganic Al concentrations at levels considered harmful to aquatic biota.
Although the Adirondack region has been the major area of geographic focus for
long-term monitoring studies of surface water recovery from acidification, the Bear
Brook Watershed in Maine, including monitoring of the East Bear Brook reference
tributary stream, has been the subject of paired watershed experimental manipulation and
monitoring since the 1980s. At the reference watershed, mean annual SOr concentration
in precipitation decreased between 1988 and 2006, while wet deposition of NOydeclined
slightly. Navratil et al. (2010) reported that high flow conditions during the winter-spring
period of November-May tended to be dominated by water chemistry indicative of
shallow hydrologic flow paths. During these times, the stream exhibited lower pH and
higher Al and DOC concentrations. Concentrations of Ca and Mg in stream water
declined over time at a faster rate than the SO42 concentration. This was reflected in
water acidification, as indicated by lower pH and higher inorganic Al concentrations.
Depletion of Ca and Mg in the manipulated (ammonium sulfate addition) watershed
(West Bear Brook) caused stream base cation concentrations to decrease to
premanipulation values over a period of nearly three decades. In a summary of 20 years
of data from whole-watershed acidification experimentation at Bear Brook, Norton et al.
(2010) observed decreases in pH, base cation concentrations, and ANC, and increases in
inorganic Al concentration in the East Bear reference watershed indicative of
acidification even as the SO42 concentrations have declined. The West Bear (acid
addition) tributary acidified more rapidly than the East Bear control tributary.
Nevertheless, the SO42 concentrations in West Bear Brook have not increased to a new
steady-state condition, and this was attributed by Norton et al. (2010) to increased SO42
adsorption accompanying soil acidification. The concentration of dissolved Al increased
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during the study period in West Bear Brook. Nitrogen retention in West Bear Brook
remained at over 80% despite more than 20 years of N addition. Laudon and Norton
(2010) analyzed 212 hydrological episodes in Bear Brook using the ANC Dilution Model
(ADM) of Laudon and Bishop (1999). Results showed that 18 years of experimental
addition of N and S to the West Bear Brook watershed had not altered the natural causes
of episodic stream acidification: base cation dilution, processes associated with
deposition of marine sea salts and contributions of organic acidity during rain and
snowmelt events. Results indicated that the contributions of SO42 to the observed ANC
decreases in West Bear Brook during episodes increased steadily since the beginning of
experimental watershed treatment. In contrast, the role of NO, in episodic acidification
events remained relatively constant after an early increase.
SanC'lements et al. (2012) used a chemical signature of terrestrial DOM to investigate the
extent to which increased DOC concentrations in surface water since about 1993 in the
northeastern U.S. have been driven by decreasing acidic deposition and increasing
solubility of soil organic matter. They used fluorescence spectroscopy to characterize the
quality of DOM in stored samples that had been collected from nine acid-sensitive lakes
in Maine. Decreases in lake water SO42 concentration were associated with increases in
DOC concentration and a shift during ecosystem recovery from microbial to terrestrially
derived DOM. Changes in the quality or quantity of DOM can affect aquatic ecosystem
functions. Dissolved organic matter is important for providing food to microbes,
attenuating light, buffering pH, binding Al, and controlling the cycling of nutrients
(SanC'lements et al.. 2012).
7.2.4.4 Central and Southern Appalachian Mountains
A second region of focus for monitoring and modeling studies of aquatic ecosystem
acidification and recovery prior to and since 2008 in the U.S. has been the southern
Appalachian Mountain region. New studies have been conducted of stream acid-base
chemistry throughout this region, as described below, in West Virginia, Maryland,
Virginia, and Tennessee. This region is important because it contains an abundance of
low-ANC streams situated on base-poor geology, atmospheric S and N deposition have
been high, S adsorption on soils complicates acidification/recovery responses, and much
of the acid-sensitive landscape is managed as national park and wilderness area.
Results of these monitoring studies suggested that the rate of stream ANC recovery may
be slowing (Eshleman et al.. 2008) and that base cation depletion has contributed to
further acidification or less recovery despite reductions in S deposition (Robison et al..
2013; Cai et al.. 2010). Eshleman et al. (2008) used data from two long-term monitoring
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stations in western Maryland to assess the recovery of stream water ANC due to declines
in acidic deposition. Stream water SO42 concentration declined at the two study sites
between 1990 and 2005 by about 3 (j,eq/L/yr in response to a 34% reduction in wet
atmospheric S deposition. However, trends in NO3 concentration were more strongly
related to watershed factors, especially forest disturbance. Although ANC increased
throughout the study, the rate of increase between 1996 and 2005 was only about half as
large as the rate of increase in ANC over the entire study period. This result might
suggest a slowing of chemical recovery from previous acidification (Eshleman et al..
2008). This supposition was further substantiated by Robison et al. (2013). who analyzed
the chemistry of stream samples collected quarterly from 1987 to 2011 at 64 sites in the
southern Appalachian Mountains of western Virginia. At most of the study streams, the
pH increased overtime. However, at most sites underlain by base-poor bedrock, ANC
decreased even though S deposition decreased. These decreases in stream ANC were
associated with depletion of base cations.
Base cation depletion was also a focus of new work by Cai et al. (2010). They used
long-term monitoring data to generate an input-output budget to identify processes that
have influenced stream pH and ANC at the Noland Divide watershed in Great Smoky
Mountains NP during the period 1991-2006. The majority (about 61%) of the net SO42
entering the watershed was retained, confirming that S adsorption on soil is an important
biogeochemical process in this watershed. However, during large precipitation events,
S042 in wet deposition moved more directly and rapidly to streams, contributing to
episodic stream acidification. Cai et al. (2010) concluded that base cation depletion from
soils could limit chemical recovery from acidification of streams in this watershed.
7.2.4.5 Western U.S.
In the western U.S., only limited long-term acid-base surface water chemistry monitoring
has been conducted before or after the 2008 ISA. One new study was published. Mast et
al. (2011) examined trends in precipitation chemistry and other factors that influence
long-term changes in chemistry of high-elevation lakes in three Colorado wilderness
areas during the years 1985 through 2008. Sulfate concentrations in precipitation
decreased at rates of-0.15 to -0.55 (j,eq/L/yr at 10 monitoring stations in Colorado. In
lakes where SO42 was primarily derived from atmospheric sources, the lake SO42
concentrations decreased by -0.12 to -0.27 (ieq/L/yr. In lakes where SO42 likely
originated primarily from watershed sources, the SO42 concentrations in lake water
increased from 1985 to 2008. Annual air temperature has increased by 0.45 to 0.93°C per
decade throughout mountainous areas in Colorado, and climate may be a cause of these
differences in S dynamics. Isotopic data presented by Mast et al. (2011) indicated that the
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S042 in these lakes that showed increasing trends is likely derived largely from pyrite.
This may indicate that climate warming is increasing the pyrite weathering, and therefore,
the concentrations of SO42 in those lakes that are most influenced by geological sources
of S.
7.2.4.6 Canada
Monitoring has also been conducted in Ontario, Canada, to document aquatic ecosystem
recovery from acidification. Molot and Dillon (2008) estimated export rates of base
cations from forested watersheds during the period 1975-2005 in an acid-sensitive region
of central Ontario. Concentrations of base cations in lake water suggested that the
dynamics were associated with three primary time periods. The period from 1975-1976
to 1982-1983 coincided with relatively high runoff and high concentrations of Ca, Mg,
and K in lake water. This was followed by a 10-year period characterized by fluctuations
in base cation concentrations. Finally, the base cation concentrations remained 5 to 20%
below long-term mean values through 2005. kothawala et al. (2011) reported a decrease
in NO3 deposition during the latter part of a 28-year monitoring period in southcentral
Ontario. Average stream NO.? concentrations and export decreased at 6 out of 11 study
streams that drain upland-dominated catchments. The five study streams that drain
primarily wetland-dominated watersheds showed lower levels of NO3 and no decreasing
trend over time. Kothawala et al. (2011) concluded that upland forest ecosystems that did
not show evidence of progressing towards N saturation may exhibit a relatively rapid
response to decreases in NO3 deposition.
7.2.4.7 Europe
Monitoring results from Europe in recent years have further substantiated findings from
North America. Relatively modest increases over time in pH and ANC were commonly
observed in response to decreased levels of acidic deposition. Burton and Aherne (2012)
resurveyed 60 small Irish lakes in 2007 that were relatively remote from emissions
sources and had initially been surveyed in 1997. During the intervening decade, S
deposition decreased about 36%; SO42 and base cation concentrations decreased. Lake
ANC increased, reflecting chemical recovery from acidification, but there were no
changes in pH. The lake DOC increased at the higher elevation sites, as it has in the
northeastern U.S. Hruska et al. (2009) reported high DOC in two watersheds in the
western Czech Republic: 18.8 mg/L and 20.2 mg/L at the acidic and base-rich
watersheds, respectively. Between 1993 and 2007, the concentrations of DOC in stream
water increased by about 65% at both streams. Increases in stream water DOC were
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associated with small increases in stream pH, but large decreases in ionic strength due to
declining acidic atmospheric deposition. Although neither of the catchments showed
changes in the pH of soil water, DOC concentrations in soil water tripled. Hruska et al.
(2009) concluded that the changes in ionic strength of soil water and stream water, rather
than acidity, was the major cause of increased stream water DOC. Changes in
temperature, precipitation, and discharge during the study suggested that climate change
may be an important control of DOC dynamics.
Two new long-term trend studies were reported from Sweden. Loferen et al. (2011)
evaluated how decreases in S deposition have affected the chemistry of surface water and
groundwater in four watersheds. Trends in water chemistry from 1996 through 2009 were
only weakly associated with decreases in S deposition. Other factors, including marine
influence and catchment features, seemed to be just as important as changes in acidic
deposition. Lucas et al. (2013) documented two decade patterns in base cation
concentrations at 60 stream monitoring sites. Long-term trends were variable and differed
among geographical regions. Concentrations of Ca2+, Mg2+, K+, and Na+ in stream water
all decreased in southern Sweden since 1990, and this response was related to concurrent
declines in SO42 concentrations. In contrast, the concentrations of the four base cations
in stream water in northern Sweden, where acidic deposition has been much less
pronounced, did not exhibit significant long-term trends. Rather, base cation dynamics in
the north were characterized by high inter-annual variability that was most closely linked
to climate. Lucas et al. (2013) suggested that interactions between climate variability and
acidic deposition collectively influenced base cation patterns across streams.
7.2.5 Freshwater Modeling
Models used to assess effects of N deposition on U.S. ecosystems were reviewed in the
2008 ISA (Annex A). The most frequently used ecosystem models for aquatic systems
have included the Model of Acidification of Groundwater in Catchments (MAGIC) and
the Photosynthesis and Evapotranspiration-Biogeochemical (PnET/BGC) model (U.S.
EPA. 2008a). Both have been widely applied, mainly to relatively small, upland
watersheds. Three other models, SPARROW, Watershed Assessment Tool for Evaluating
Reduction Scenarios for Nitrogen (WATERS-N), and Surface Water Assessment Tool
(SWAT) have been used to evaluate N loading to large river systems.
There have been few new freshwater acidification or eutrophication models developed
and published since 2008. The Watershed Analysis Risk Management Framework
(WARMF) is a model for evaluating point and nonpoint pollution, including N fate and
transport (Davvani et al.. 2013; Herr and Chen. 2012). A new national water quality
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modeling system (Hydrologic and Water Quality System, HAWQS) is under
development by Texas A&M University and USDA for U.S. EPA's Office of Water
(https://cpaha\vqs.tamu.edu/). The model is intended to assist resource managers and
policy makers in evaluating the effectiveness of water pollution control efforts. HAWQS
will support application of SWAT and SPARROW and will include simulations of
nutrients and other pollutants.
Other models have been used for assessment of nutrient loading to freshwater systems.
SWAT has been adopted as part of U.S. EPA's Better Assessment Science Integrating
Point and Nonpoint Sources (BASINS) platform in support of TMDL development
(Gassman et al.. 2007). Another model that has been applied to analysis of nutrient
enrichment in aquatic systems is AQUATOX (Carleton et al.. 2009). which simulates
nutrient dynamics and effects on aquatic biota. Such models were earlier summarized in
Table A-8 in the 2008 ISA (U.S. EPA. 2008a).
7.2.5.1 Freshwater Nutrient Cycling Models
Watershed N budgets and empirical models can be useful for assessing the relative
magnitude of N inputs and losses via riverine export. A variety of computational
approaches can be used. To determine the influence of assumptions and methodologies
on the effectiveness of using estimated N input for predicting riverine N export, a new
study by Han and Allan (2008) compared N budgets for 18 study watersheds located in
the vicinity of Lake Michigan. Nitrogen input estimation approaches that considered
detailed information on agricultural practices yielded the best predictions of riverine N
export. This was likely because agricultural sources of N dominated in many of the study
watersheds. The average riverine export of N ranged from less than 300 kg N/km2/yr in
forested watersheds to more than 800 kg N/km2/yr in agricultural watersheds and
1,580 kg N/km2/yr in small urban watersheds. The most robust model suggested that
riverine N exports explained about 21% of N inputs. The improved ability to predict N
export using methods that incorporated description of agricultural N sources was
particularly noticeable when applied to watersheds that had pronounced diversity of land
use and geology.
The controls on NOs leaching from soil waters to surface waters are still not well
understood. Three new European studies provide some additional perspective. Futter et
al. (2009) reported results of experimental N addition at Gardsjon, Sweden in a project
focused on mechanisms that regulate NO3 leaching to drainage water. The Integrated
Catchments model for Nitrogen (INCA-N) was used to simulate responses to N addition
which began in 1991. The model successfully reproduced stream and soil water N
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behavior before and during the experiment. Simulations were controlled mainly by
hydrology and vegetation dynamics, and secondarily by soil processes. Futter et al.
(2009) suggested that future modeling efforts should focus on improving representation
of soil processes and N uptake and on linking C and N dynamics.
Model simulations have also reported N fluxes in large river systems. Calculations by
Hagg et al. (2012) suggested that about one-fourth of the regional human-caused N input
is exported by rivers to the Baltic Sea. Minimally disturbed watersheds in northern
Sweden were not simulated to have high riverine N export. In northern and western
Sweden, N export was controlled by the hydraulic load, which was expressed as
discharge normalized by the water surface area. Forest cover also affected N export,
mainly in the northern and western portions of Sweden. Nitrogen fertilizer was important
to predictions of N export, due to high N export from agricultural watersheds in southern
Sweden. Agricultural N sources have also been shown to be important in Denmark
(Hinsbv et al.. 2012). The poor ecological status of the majority of Danish coastal waters
is largely attributable to nutrient contributions from intensive agriculture in Denmark.
Nevertheless, atmospheric deposition contributes additional nutrients to these waters.
Freshwater nutrient cycling studies have also focused some attention on N fixation. In
Waco Reservoir, TX, Scott et al. (2008) measured N fixation over a 19-month period and
linked these data with nutrient-loading estimates derived from a physically based
watershed model. Readily available topographic, soil, land cover, effluent discharge, and
climate data were used in the SWAT model in order to derive estimates of nutrient
loading from the watershed to the reservoir. Results suggested that human activities in the
watershed can exert significant control over planktonic N fixation.
7.2.5.2 Freshwater Acidification Models
The two principal process-based biogeochemical models that have commonly been used
in the U.S. in recent years to assess the acidifying effects of S and N deposition on
terrestrial and freshwater ecosystems have been MAGIC and PnET-BGC. Model
projections of past and future changes in surface water chemistry using these models in
response to changes in acidic deposition are summarized in Table 7-4. These models use
biogeochemical principles to hindcast and forecast the acid-base chemistry and N
responses of soils and surface waters.
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Table 7-4 Model projections of surface water sulfate and associated acid
neutralizing capacity, shown as changes between dates, for
Adirondack and Shenandoah streams.
Region
Water
Bodies
Dates
Model
Pollution
Scenario
Change in
Median
Surface
Water SO42"
((jeq/L)
Change in
Median
Surface
Water ANC
((jeq/L)
Reference
HINDCASTS
Adirondacks,
New York
38 lakes
1850 to
2003
PnET-
BGC
+72.9
-39.9
Zhai et al. (2008)
Adirondacks,
New York
37 lakes
1850 to
1984
PnET-
BGC
+ 107
-77.8
Chen et al.
(2005a)
Adirondacks,
New York
44 potentially
acid-sensitive
lakes
1850 to
1990
MAGIC
+77.8
-38.3
Sullivan et al.
- C9nnfiai
PnET-
BGC
+57.3
-29.5
FORWARD PROJECTIONS
Shenandoah
NP, Virginia
5 streams on
siliciclastic
bedrock
1990 to
2040
MAGIC
Constant
deposition
+ 13
-11.6
Sullivan et al.
(2008)
Mild reduction
-21
+6.2
Medium
reduction
-23
+7.2
Strong
reduction
-40
+24.2
Very strong
reduction
-44
+27.2
Shenandoah
NP, Virginia
4 streams on
granitic
bedrock
1990 to
2040
MAGIC
Constant
deposition
+22
-8
Sullivan et al.
(2008)
Mild reduction
+ 11
-5
Medium
reduction
+ 11
-5
Strong
reduction
+3
-2
Very strong
reduction
+2
-2
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Table 7-4 (Continued): Model projections of surface water sulfate and associated
acid neutralizing capacity, shown as changes between
dates, for Adirondack and Shenandoah streams.
Region
Water
Bodies
Dates
Model
Pollution
Scenario
Change in
Median
Surface
Water SO42"
((jeq/L)
Change in
Median
Surface
Water ANC
(Heq/L)
Reference
Shenandoah
NP, Virginia
5 streams on
basaltic
bedrock
1990 to
2040
MAGIC
Constant
deposition
+33
-5
Sullivan et al.
(2008)
Mild reduction
+ 12
0
Medium
reduction
+ 11
+ 1
Strong
reduction
-4
+5
Very strong
reduction
+6
Adirondacks, 44 potentially 1990 to MAGIC Current and -42.4 +5.89 Sullivan et al
New York acid-sensitive 2050 expected (2006a)
lakes controls
Moderate -58.9 +18.6
emissions
controls
Aggressive -64.6 +22.6
emissions
controls
Adirondacks, 44 potentially 1990 to MAGIC Current and -18 -3.7 Sullivan et al.
New York acid-sensitive 2050 expected (2006a)
lakes controls
Moderate -32.2 +1.8
emissions
controls
Aggressive -38.3 +9.3
emissions
controls
ANC = acid neutralizing capacity; L = liter; |jeq = microequivalent; MAGIC = Model of Acidification of Groundwater in Catchments;
PnET-BGC = Photosynthesis and Evapotranspiration-Biogeochemical; S042" = sulfate.
Source: U.S. EPA (2008a).
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Table 7-5 Recent process-based model estimates of surface water acidification
and chemical recovery in the U.S.
Model
Nutrient
Enrichment
Acidification
Type of
Ecosystem
Region
Model Application and
Findings
Publication
PnET-
X
44
Adirondack
Larger historical lake
Zhai et al. (2008)
BGC
representative
Mtns.
acidification in lakes having
watersheds
lower ambient ANC
MAGIC
X
66 stream
watersheds
Southern
Blue Ridge
Mtns.
All modeled streams had
preindustrial ANC
>30 peq/L. Median stream
lost about 25 peq/L of ANC
between 1860 and 2005.
Sullivan et al.
(2011b)
PnET-
BGC
X 128 Adirondack Of 128 acid-impaired lakes
acid-impaired Mtns. that were modeled, 97 had
lakes ambient ANC below target
of 20 peq/L and 83 were
below target of 11 peq/L.
TMDL corresponding to a
moderate emissions
control scenario (60%
decrease in S deposition)
was 7.9 meq/m2/yr.
Fakhraei et al.
(2014)
PnET-
BGC
X Streams, HBEF, NH Simulations under Pourmokhtarian
watershed changing climate reflected et al. (2012)
later snowpack
development, earlier spring
snowmelt, greater ET, and
slight increase in water
yield. Net soil
mineralization and
nitrification caused
simulated soil and water
acidification.
PnET-
BGC,
SAFE,
VSD,
MAGIC
Inter-model HBEF, NH Hindcast and forecast
comparison projections were
qualitatively similar, but
temporal patterns of
simulated change in
chemistry differed
substantially among
models.
Tominaqa et al.
(2010)
PnET-
BGC
X Three Adirondack Predicted ANC recovery Wu and Driscoll
multipollutant Mtns. closely related to percent (2009)
scenarios of watershed in conifers,
elevation, and lake area.
ANC = acid neutralizing capacity; ET = evapotranspiration; HBEF = Hubbard Brook Experimental Forest; L = liter; m = meter;
jieq = microequivalent; meq = milliequivalent; MAGIC = Model of Acidification of Groundwater in Catchments;
PnET-BGC = Photosynthesis and Evapotranspiration-Biogeochemical; S = sulfur; SAFE = Soil Acidification in Forest Ecosystems;
TMDL = total maximum daily load; VSD = Very Simple Dynamic; yr = year.
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The Very Simple Dynamic (VSD) soil acidification model is used in Europe to simulate
acidification effects in soils when observed data are sparse. It has not been used widely in
the U.S. There are other process-based models of acid-base chemistry, but those models
have also been used less often for these purposes in the U.S. Table 7-5 summarizes recent
process-based model estimates of surface water acidification and chemical recovery in
the U.S.
Several studies have been conducted to model surface water acidity recovery responses in
the northeastern U.S., including studies in the Adirondack Mountains of New York and at
HBEF. Fakhraei et al. (2014) used PnET-BGC to evaluate decreases in atmospheric S
and N deposition as causes of changes in lake water chemistry in the Adirondack
Mountains. The two targets of ANC that were selected for the study were 11 and
20 (ieq/L. Of the 128 lakes that were judged to be acid impaired, 97 had ambient ANC
values below the target value of 20 |icq/L: 83 had ANC below the target value of
11 |icq/L. A moderate emissions control scenario (60% decrease from the ambient
atmospheric S deposition) was projected to recover the ANC of lakes by 0.18 and
0.05 (j,eq/L per year on average during the periods 2022 to 2050 and 2050 to 2200,
respectively. The TMDL of S acidity corresponding to this moderate emissions control
scenario was estimated to be 7.9 meq S/m2/yr, a 60% reduction, which included a 10%
safety margin. The ANC target of 11 |icq/L was proposed to protect arctic char
(,Salvelinus alpinus), which represents a similar niche to brook trout (S. fontinalis), the
most important fishery in the Adirondack Mountains. The ANC target of 20 (j,eq/L was
intended to protect brook trout against adverse impacts associated with elevated
concentrations of inorganic Al. Model results suggested that controlling S deposition of
Adirondack lake watersheds was more effective as a means to recover acidic lakes than
was controlling N deposition. For about 40% of the study lakes, it was projected that
ANC would not recover to 20 (ieq/L by the year 2200. This was mainly because most of
these lakes were naturally low in ANC.
Another new study in the Adirondack Mountains by Wu and Driscoll (2009) applied the
PnET-BGC model to predict the responses of lake ANC during the period 2001 to 2050.
Based on three multipollutant scenarios, predicted ANC recovery was associated with
elevation, lake area, and the percentage of watershed area in coniferous vegetation. A
geographic weighted regression model was used to evaluate patterns in predicted lake
ANC. The variables lake depth and the square of the lake elevation explained 40% of the
variation in predicted lake water ANC. Even under the most aggressive air pollution
control scenario considered, not all of the Adirondack lakes were simulated to recover to
ANC above 50 |icq/L by the year 2050. This lack of recovery to a selected ANC target
can be further compounded by geology or disturbance. Inamdar and Mitchell (2008)
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found that geological sources of S can be important in New York and can cause some
watersheds to respond slowly to decreased atmospheric S deposition.
Two new acid-base chemistry modeling studies were conducted at HBEF.
Pourmokhtarian et al. (2012) used the PnET-BGC model to consider effects of potential
future changes in temperature, precipitation, solar radiation, and atmospheric CO2 on the
behavior of major elements at HBEF. Climate projections indicated that the average air
temperature will likely increase at HBEF by 1.7 to 6.5°C over the 21st century. It has
been estimated that annual average precipitation might increase by 4 to 32 cm. Model
simulations under the expected future climate showed later development of snowpack,
earlier snowmelt, higher evapotranspiration, and increased water yield. The simulations
suggested that net soil N mineralization and nitrification will increase in response to
higher temperature. This could result in acidification of soil and stream water.
In a model comparison study at HBEF, Tominaga et al. (2010) evaluated the performance
and uncertainty of the MAGIC, PnET-BGC, SAFE (Soil Acidification in Forest
Ecosystems), and VSD watershed acidification models. They applied each of the models
to long-term records of precipitation and stream chemistry. The calibrated models were
used to assess likely responses of soil and stream chemistry to reduced future
atmospheric S deposition. Tominaga et al. (2010) noted hindcast (1850-1992) and
forecast (2005-2100) projections were qualitatively similar across the models, although
projected stream ANC and soil base saturation differed substantially through time. The
authors recommended use of multiple models to reduce uncertainty.
A new empirical modeling study by Robinson et al. (2008) reported base flow water
chemistry at 90 streams in Great Smoky Mountains National Park during the years
1993-2002. Stepwise multiple linear regression modeling analyzed long-term trends in
pH, ANC, S, and N. There were significant decreasing trends in stream pH and SO42 at
lower elevation sites over time, but no long-term trends in stream NO3 or ANC. An
estimated 30% of the sample sites were simulated to decrease pH to less than 6 within
10 years. The models explained 71% of the variability in pH and 86% of the variability in
ANC. Soil retention of SO42 and assimilation of NO3 into plants were important
biogeochemical processes regulating stream chemistry. The stream pH at base flow has
not yet shown signs of recovery in response to recent decreases in acidic deposition. The
model developed for elevations between 305 and 1,070 m predicted that median pH
values will decrease below 6 within 34 years if the observed statistical trends continue.
Recent acid-base chemistry modeling studies in Canada have focused on quantification of
weathering rates and on surface water acidification responses in the oil sands region of
western Canada. Watmough and Aherne (2008) estimated calcium weathering in the
watersheds of 550 lakes in south central Ontario. Because Ca weathering at the
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130 low-Ca (<75 (imol/L) sites was primarily dominated by silicate minerals such as
plagioclase and hornblende, Watmough and Aherne (2008) used Ca:Na ratios in lake
water to estimate the rates of Ca weathering in soil, which ranged from 0.04 to
0.24 kmol/ha/yr (median 0.09 kmol/ha/yr). These estimates generally corresponded with
the range obtained using the steady state water chemistry model (0.06 to
0.24 kmol/ha/yr). Watmough and Aherne (2008) estimated that Ca concentrations at
steady state in study lakes would likely decline by 10 to 40% compared with ambient
values. Dynamic model projections using the MAGIC model suggested that lake Ca
concentrations will be considerably lower than the steady-state predictions if timber
harvesting continues. Houle et al. (2012) also estimated weathering, but they used the
steady-state soil chemistry PROFILE model. Their study focused on 21 watersheds
located within the temperate and boreal forests of the Canadian Shield. Spatial variations
in PROFILE weathering estimates were in general agreement with the soil mineralogy.
The estimated weathering rates for Ca and Mg were significantly (r = 0.80 and 0.64,
respectively) correlated with base cation concentrations in lake water. It was concluded
that the PROFILE model could reproduce spatial gradients in weathering rates of Ca and
Mg in this application, but not as reliably for Na. These weathering rates could be used as
inputs to steady-state CL models. Weathering is the largest source of uncertainty in such
modeling.
The MAGIC model was applied by Whitfield et al. (2010a) to two watersheds in the
Athabasca oil sands region of Alberta to project watershed responses to changes in S and
N deposition. Simulation results suggested limited risk of acidification for these lakes
because of high S retention in soils of the study watersheds. Whitfield et al. (2010a)
developed an approach for regional application of MAGIC. Because simulations of
charge balance ANC of the lakes in 50 long-term monitoring watersheds suggested very
small decreases since industrialization, the researchers judged that there was limited
potential for acidification impacts to these lakes.
Studies of surface water chemical recovery from acidification in Europe have
complemented studies conducted in North America. Kohler etal. (2011) reported results
from application of the MAGIC model to simulate the acidification of four forested
catchments in Sweden acidified by varying amounts. Modeled mass balance uncertainties
were connected with assumptions about S adsorption on soils and soil mass. Results
suggested that predicted values of pH and ANC at these sites using MAGIC had
precisions about equal to 0.3 pH units and 20 |icq/L. respectively.
Acid-base chemistry modeling is generally conducted in a given study for individual
discrete watersheds. Resulting model output informs understanding of processes that
occur in the watershed(s) that were modeled. However, information developed by
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monitoring and site-specific modeling must be extrapolated to the broader landscape in
order to enhance scientific and policy utility. Evans et al. (2010) proposed an approach
for upscaling model outputs to long-term monitoring sites in the U.K. Acid Waters
Monitoring Network. Standardized concentrations (z scores) for ANC and other acid-base
chemical parameters showed high correspondence among sites. This allowed the mean
solute concentrations at a new site to be predicted from observations or model
simulations at other sites.
Some modeling studies since the 2008 ISA have included focus on DOC dynamics,
which has emerged as an important area of research focus since the 2008 ISA.
Fluctuations in the concentrations of TOC in runoff at the small headwater catchment,
Storgama, in southern Norway were related to climate and changes in acidic deposition.
A 20-year increase in TOC was associated with reductions in S deposition.
Multiple-regression modeling described long-term trends and seasonal variability and
projected the future concentrations of NO;, and TOC, given scenarios of future climate
change and continued decreases in acidic deposition. All scenarios considered in the
study suggested that there would be increased fluxes in TOC in the future. Similarly,
Erlandsson et al. (2010) modeled effects of increasing lake water DOC in southern
Sweden on the recovery of 66 lakes from acidification between 1990 and 2008. Results
of the modeling study suggested that recent increases in DOC have reduced recovery
from acidification by 0.13 pH units (median across all study lakes) and by more than a
full pH unit for some individual lakes. The MAGIC model was used by Hruska et al.
(2014) to simulate preindustrial and future stream acid-base chemistry for a small
acidified stream in the Czech Republic. Three scenarios assumed varying levels of DOC
concentrations and sources. Results indicated large effects on stream pH based on
different levels of DOC.
In the 2008 secondary NAAQS review for oxides of N and S, an aquatic acidification
index (AAI) was developed to relate (1) atmospheric concentrations of SOx and
NOy + NHy to N and S deposition levels using transference ratios (Chapter 2). and (2) to
relate deposition to ANC values, using a modified Steady-state Water Chemistry (SSWC)
model (Chapter 4) and water chemistry for over 6,000 sites in the U.S. The ANC values
where grouped by site into ecoregions and evaluated by considering the distribution of
predicted ANC values (Scheffe et al.. 2014).
7.2.6 Water Quality Criteria
The term "water quality criteria" is used in two sections of the Clean Water Act:
Section 304(a)(1) and Section 303(c)(2). The term has a different impact in each section.
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In Section 304, the term refers to a scientific assessment of ecological and human health
effects that U.S. EPA recommends to states and authorized tribes for establishing water
quality standards that ultimately provide a basis for controlling discharges or releases of
pollutants or related parameters. Ambient water quality criteria associated with specific
water body uses when adopted as state or tribal water quality standards under Section 303
define the level of a pollutant (or, in the case of nutrients, a condition) necessary to
protect designated uses in specific water bodies.
U.S. EPA develops Water Quality Criteria (WQC) using the latest scientific knowledge
to determine when water is unsafe for people and wildlife. These criteria are developed as
recommendations. State and tribal governments may adopt these criteria or use them as
guidance in developing their own. U.S. EPA bases aquatic life criteria on how much of a
chemical can be present in surface water before it is likely to harm plant and animal life.
WQC are determined for aquatic life, biology, human health, microbial/recreational, and
sediment. For aquatic life, the criteria are designed to protect both freshwater and
saltwater organisms from short-term and long-term exposure to pollutants. Biological
criteria indicate the health of water bodies based on how many and what kinds of
organisms are present. More details about the scientific basis for these criteria may be
found at https://www.epa.gov/wqc/basic-information-water-qualitv-criteria.
The U.S. EPA is working with the states to develop numeric nutrient criteria to better
define levels of N and P that affect U.S. waters. The numeric values include both
causative (N and P) and response (chlorophyll a, turbidity) variables. The U.S. EPA's
National Nutrient Program developed recommended nutrient criteria for rivers and
streams in 14 ecoregions of the U.S. (based on Omernik Level III ecoregions) for the
states to use as a starting point for states to develop their own criteria (U.S. EPA. 1998b).
WQC indicators related to N are available for Oregon, California, Arizona, Colorado,
Montana, Utah, and Mississippi. These criteria may include a variety of N species and
chlorophyll a (Table 7-6). For Washington and Louisiana, which lack explicit numeric
criteria, U.S. EPA aggregate Level III ecoregion nutrient criteria for rivers and streams
were used (Table 7-6; http://www2.epa.gov/nutrient-policv-data/ecoregional-criteria-
documents').
The compiled state WQC vary greatly in spatial resolution and N species addressed.
Mississippi applies only one species criterion to the entire state. By contrast, California
has a patchwork of criteria designated by regional water boards.
U.S. EPA Aggregate Level III Omernik Ecoregion Nutrient Criteria for Rivers and
Streams (from U.S. EPA Ecoregional Nutrient Criteria Documents for Rivers and
Streams; available at http://www2.epa.gov/nutrient-policv-data/ecoregional-nutrient-
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1 criteria-documents-rivers-and-streams) were developed for states to provide a more
2 spatially even set of standards for TN and chlorophyll a (Table 7-7). The aggregate
3 ecoregion criteria are mapped in Figure 7-2A and Figure 7-2B.
4 Since the 2008 ISA, the ambient water quality criteria for NH3 was recently updated to
5 reflect the sensitivity of freshwater unionoid mussels to this nutrient (U.S. EPA. 2013a).
6 The acute criterion is 17 mg total ammonia nitrogen (TAN)/L, and the chronic criterion is
7 1.9 TAN/L at pH 7 and temperature 20°C.
Table 7-6 Water quality criteria for rivers/streams by state (all values in mg/L,
shaded by criteria level).
State
Subregion
TN
Nitrate
(as N)
Nitrite
(as N)
Nitrate +
Nitrite
(as N)
Ammonia
(NHs)
Chlorophyll a
Oregon
10
-
0.015
Washington
Ecoregion 1
0.31
-
0.0018
Washington
Ecoregion 2
0.12
-
0.00108
Washington
Ecoregion 3
0.38
-
0.00178
California
SWRCB3
Region 1
-
45
-
California
SWRCB3
Region 2
-
45
-
California
SWRCB3
Region 3
-
45
-
California
SWRCB3
Region 4
-
8
1
10
-
California
SWRCB3
Region 5
0.31
-
0.0018
California
SWRCB3
Region 6
0.38
-
0.00178
California
SWRCB3
Region 7
45
-
10
-
California
SWRCB3
Region 8
0.38
45
-
0.00178
Arizona
2
10
1
-
Colorado
South Platte Basin
-
-
0.5
-
Colorado
Remainder of state
-
10
0.05
-
0.02
-
Montana
1
-
1
-
Utah
10
-
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Table 7-6 (Continued): Water quality criteria for rivers/streams by state (all values
in mg/L, shaded by criteria level).
State
Subregion
TN
Nitrate
(as N)
Nitrite
(as N)
Nitrate +
Nitrite Ammonia
(as N) (NHs)
Chlorophyll a
Louisiana
Ecoregion 9
-
0.69
-
0.00093
Louisiana
Ecoregion 10
-
0.76
-
0.0021
Mississippi —
10
-
Florida
Panhandle West
0.67
-
-
-
-
Florida
Panhandle East
1.03
-
-
-
-
Florida
North Central
1.87
-
-
-
-
Florida
Peninsular
1.54
-
-
-
-
Florida
West Central
1.65
-
-
-
-
Florida
South Florida
Narrative
-
-
-
-
L = liter; mg = milligram; N = nitrogen; NH3 = ammonia; TN = total nitrogen.
aState Water Resources Control Board.
Table 7-7 U.S. Environmental Protection Agency aggregate Level III ecoregion
nutrient criteria (all values in mg/L and shaded by criteria level;
U.S. Environmental Protection Agency ecoregional nutrient criteria
documents for rivers and streams).
Ecoregion
TN
Chlorophyll a
1
0.31
0.0018
2
0.12
0.00108
3
0.38
0.00179
4
0.56
0.0024
5
0.88
0.003
9
0.69
0.00093
10
0.76
0.0021
11
0.31
0.00161
12
0.9
0.0004
TN = total nitrogen.
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EPA Ecoregions by Nutrient Level
Nutrient Criteria: Total Nitrogen
Criteria (mg/L) | | o 39-0 58
I I 0,12 lU 0 57-0.90
~ 0.13-0 36 0 91 - 218
d y
L = liter; mg = milligram.
Figure 7-2A Total nitrogen criterion values by ecoregion.
Criteria (mg/L) LJ| oooiosi-0002100
^ 0.00M00- 0.000630 ¦ 0.002101 -0.003000
| j 0.000631 -0.001080 ¦ 0.003001 -0 003750
EPA Ecoregions by Nutrient Level
Nutrient Criteria: Chlorophyll-a
L = liter; mg = milligram.
Figure 7-2B Chlorophyll a criterion values by ecoregion.
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7.3
Estuaries and Near-Coastal Areas
In the 2008 ISA, the evidence was sufficient to infer a causal relationship between
reactive N deposition and alterations in the biogeochemical cycling of N in estuarine and
near-coastal marine systems. Estuary eutrophication is indicated by water quality
deterioration, including development of hypoxic zones, species mortality, and formation
of harmful algal blooms (HABs; Chapter 10). The most widespread chemical indicator of
eutrophication in estuarine and marine ecosystems is dissolved oxygen (DO),
specifically, decreases in DO. Widely used biological indicators of N nutrient enrichment
discussed in Chapter 10 include decreases in the presence and extent of submerged
aquatic vegetation (SAV), increases in chlorophyll a concentration (measure of primary
production), and increases in the occurrence and abundance of algal blooms and
macroalgae. Evidence reviewed in the 2008 ISA along with new studies indicate elevated
N inputs to coastal areas can alter the biogeochemistry of these ecosystems and cause
increased primary production. N from both atmospheric and nonatmospheric sources
contribute to the total N loading of coastal waters. The contribution of atmospheric N
deposition to overall N loading varies among estuaries, and the extent to which N
deposition controls eutrophication varies accordingly. Key processes affected by N
loading include nitrification and denitrification. As stated in the 2008 ISA, many
estuaries currently receive high N input from human activities (e.g., atmospheric
deposition, agricultural runoff, wastewater, and other sources), and because production in
these systems tends to be N limited (Elser et al.. 2007). eutrophication is the result
(Howarth et al.. 1996; Vitousek and Howarth. 1991). Nearly two-thirds of the estuaries in
the U.S. assessed by Bricker et al. (2007) in the National Estuarine Eutrophication
Assessment (NEEA) conducted by the National Oceanic and Atmospheric
Administration (NOAA) and summarized in the 2008 ISA had moderate to high
eutrophic conditions and received relatively high N loads from both atmospheric and
nonatmospheric sources. New information is consistent with the conclusions of the 2008
ISA that the body of evidence is sufficient to infer a causal relationship between N
deposition and the alteration of biogeochemistry in estuarine and near-coastal
marine systems.
Since the 2008 ISA, there is new evidence that N loading, a portion of which is
atmospheric in origin, can contribute to acidification of coastal waters (Figure 10-8).
Some acidification of water bodies occurs naturally as atmospheric carbon dioxide (CO2)
diffuses into the water body, forms carbonic acid, and then dissociates into carbonate ions
and hydrogen ions. N loading increases acidification when algal biomass from increased
primary production sinks out of surface waters and then decomposes, and the CO2
produced by decomposition undergoes dissociation and production of hydrogen ions
(Howarth et al.. 2011; Orr et al. 2005). Models show that while the impact of each
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acidification pathway (N enrichment and atmospheric CO2 dissolution) may be moderate,
the combined effect of the two may be much larger than would be expected by just
adding the effects of each pathway together (Sunda and Cai. 2012; Cai etal.. 2011c). The
body of evidence is sufficient to infer a likely causal relationship between N
deposition and increased nutrient-enhanced coastal acidification.
The sections below describe chemical indicators and processes. This section is divided
into three parts. Section 7.3.1 is focused on sources of N to estuaries and near-coastal
marine waters, including both point and nonpoint sources. Typically, atmospheric
deposition constitutes less than half of the total N supply to estuaries in the continental
U.S. Section 7.3.2 addresses chemical effects and processes, with special attention given
to nitrification, denitrification, hypoxia, and increased production of CO2 leading to
coastal acidification. Model projections of responses of estuarine and near-coastal waters
to N addition are addressed in Section 7.3.3. A summary of aquatic biogeochemistry as it
relates to these topic areas including causal determinations are in Section 7.4.
7.3.1 Nitrogen Sources to Estuarine and Near-Coastal Areas
N sources to near-coastal ecosystems include direct deposition to the water surface as
well as deposition to the watershed and all other N sources upstream of receiving
estuaries and coastal waters. In estuaries adjacent to areas of coastal upwelling such as
some locations along the Pacific coast of the U.S., oceanic inputs of nutrients can also
represent an important source of N (Brown and Ozretich. 2009). The 2008 ISA identified
various N sources, both point (coming from a single outfall or discharge point) and
diffuse or nonpoint sources (U.S. EPA. 2008a). Since the 1972 Clean Water Act, point
sources of N such as wastewater treatment plants and some industries have been
regulated, and nutrient discharges from these sources have declined. Releases of N from
agricultural, urban, and mixed land uses comprise a significant portion of the nonpoint
sources in many watersheds (Birch et al.. 2011; Alexander et al.. 2008). The Chesapeake
Bay is an example of a well-studied coastal system in which N fluxes have been
relatively well characterized (Figure 7-3).
In many places, nonpoint sources are now the dominant sources of N to water bodies
(Howarth et al.. 2002). Atmospheric deposition typically constitutes less than half of the
total N supply to estuaries; however, atmospheric inputs are heterogeneous across the
U.S. ranging from <10 to approximately 70% of the N inputs (Table 7-8). In management
of coastal eutrophication, both point and nonpoint sources have been identified as targets
for control of N inputs (Stephenson et al.. 2010; Paerl et al.. 2002). Nonpoint sources are
more difficult to control and include agricultural runoff and wet and dry deposition from
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the atmosphere. Increased respiration caused by N enrichment may exacerbate coastal
ocean acidification through alteration of the carbon cycle.
The importance of atmospheric deposition as a cause of estuarine eutrophication is
determined by the relative contribution of the atmospheric versus nonatmospheric sources
of N input (U.S. EPA. 2008a'). Atmospherically deposited N from combustion of fossil
fuels (NOy), agricultural sources (NH3, NH4+) and organic N combine with N from other
anthropogenic and natural sources to contribute varying total N inputs in coastal regions.
It is the cumulative effect from multiple sources that contributes to ecosystem enrichment
(Paerl et al.. 2002). Although overall, atmospheric deposition of total N has not changed
appreciably, atmospheric deposition of reduced N has increased relative to oxidized N in
parts of the U.S. including the East and Midwest in the last few decades (Chapter 2). and
this trend is expected to continue in the future under existing emissions controls (Pinder
et al.. 2008; U.S. EP A. 2008a'). Thus, the form of inorganic N input to coastal areas is
changing overtime. Deposition of oxidized and reduced forms ofN are detailed in
Chapter 2.
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Chemical Nitrogen Cascade: Chesapeake Bay Watershed
NOx Emissions
1
Utilities
52,000
Industry
43,000
Mobile Sources
170,000
Other Sources
14,000
NHj Emissions
Non-Agriculture 22,000
N Additions to Water
Point Sources 26,000
22.000
N Additions to I.and
Agriculture 370,000
Urban and Mixed Open
Land Uses 62,000
H 26,000
Arrow width indicates size of flux.
Arrow color indicates origin of
nitrogen flux
* Red-Air
* Green - Land
* Blue - Water
All estimates are in metric tonnes N
per yeaT
N.E. = No Estimate Available
Atmosphere
¦
I
110,000
¦
Agriculture and
Forestry Nil.
Emissions to
Air
Terrestrial 1
System J
... J
6,200 i
Deposition
to Land
Deposition
to Land
52.000
Fertilizer
N,0
Emissions
Leaching
to Streams
Leaching
to Streams
¦ 1
1 90,000 I I 29
000 |
Freshwater
System
I 90^0 I 1 29^00 |
1 1
Delivered to
Bay
24,000
Delivered to
Bay
| 69
,000 1
Delivered to
Bay
23,000
Streams
N,0
from
Bay
hstuarine
System
Source: Birch et al. (2011)
Figure 7-3
Chemical nitrogen cascade in the Chesapeake Bay Watershed
(metric tons/year).
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Table 7-8 Summary of studies quantifying atmospheric nitrogen contribution
to total nitrogen in coastal areas via watersheds and/or direct
deposition to estuary surface waters.
Region
Total N loading due to atmospheric deposition
Model
Reference
U.S. coastal areas
N deposition to land surfaces that is subsequently
exported from watersheds to the coastal zone is
responsible for 17-21% of the total N input.
NEWS
SPARROW
McCrackin et al.
(2013)
Gulf of Mexico in the Atmospheric deposition contribution, which may SPARROW Robertson and
Mississippi/Atchafalaya include volatilized losses from natural, urban, and Saad (2013)
river basin agricultural sources, was estimated to be 26% of
total N transported to the Gulf of Mexico.
Northeast and Identified deposition to the watershed as the SPARROW Moore et al.
mid-Atlantic coastal dominant source of N to the estuaries of the (2011)
region Connecticut, Kennebec, and Penobscot Rivers, but
the third largest source (20%) for the region as a
whole, after agriculture (37%) and sewage and
population-related sources (28%).
Narragansett Bay Combined direct atmospheric deposition to the Vadeboncoeur et
estuary and atmospheric deposition to the al. (2010)
watershed were responsible for 20% of N loading to
the Bay.
Small-to-medium sized Direct atmospheric deposition to estuary surface NLM
estuaries of southern averaged 37%, and indirect atmospheric deposition
New England via the watershed averaged 16% of total N loading,
although the percentage varied widely for each
individual estuary.
Latimer and
Charpentier
(2010)
Tampa Bay
Direct and indirect atmospheric loading were
estimated to be 30% and 41%, respectively, of total
N loading to the Bay.
WDT
Poor et al.
(2013b)
Tampa Bay Direct and indirect atmospheric loading were CMAQ modified Poor et al.
estimated to be 17 and 40%, respectively, of total N with University of (2013a)
loading to the Bay. California Davis
aerosol module
Chesapeake Bay Atmospheric loading is 24% of total N loading. Birch et al.
(2011)
Chesapeake Bay
Half of the atmospheric source of N to the watershed
Chesapeake Linker etal.
originates outside of the watershed; indirect loading
Airshed Model. (2013)
of atmospheric N via watershed inputs are larger
combining CMAQ
than direct loading to tidal waters.
and regression
model for wet
deposition
Gulf of Mexico in the Atmospheric deposition to watersheds in the basin SPARROW Alexander et al
Mississippi/Atchafalaya contributed about 16% of the total N load, second to (2008)
river basin corn and soybean production (52%).
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Table 7-8 (Continued): Summary of studies quantifying atmospheric nitrogen
contribution to total nitrogen in coastal areas via
watersheds and/or direct deposition to estuary surface
waters.
Region
Total N loading due to atmospheric deposition Model
Reference
Key Pre-2008 Literature
34 Atlantic and Gulf
coast estuaries
The contribution of atmospheric deposition WATERS-N
(including directly onto the water surface and onto
the watershed) was 7-72% of the total N.
Castro et al.
(2001);Castro et
al. (2003)
Chesapeake Bay
Atmospheric deposition makes a substantial
contribution (about 25%) to the overall N budget.
Bover et al.
(2002);Howarth
(2007)
16 northeastern river
basins
Atmospheric deposition averaged 31% of total N
inputs; estimated riverine export of N amounted to
25% of total N inputs.
Bover et al.
(2002)
Based on 34 Atlantic
and Gulf coast
estuaries
In systems with watershed area to estuarine surface
area ratios greater than 15, N deposition is not as
important (comprising less than 25% total N input)
as in estuaries that are large relative to their
watershed.
Castro et al.
(2001)
CMAQ = Community Multiscale Air Quality; N = nitrogen; NEWS = Nutrient Export from Watersheds; NLM = Nitrogen Loading
model; SPARROW = Spatially Referenced Regressions on Watershed Attributes; WATERS-N = Watershed Assessment Tool for
Evaluating Reduction Scenarios for Nitrogen; WDT = Water Deposition Tool.
As reported in the 2008 ISA (U.S. EPA. 2008a'). the shape and extent of the airshed is
different from that of the watershed. In a watershed, everything that falls within its area,
by definition, flows into a single collection point in a body of water. An airshed, by
contrast, is a theoretical concept that defines the area containing the emissions
contributing a given level, often 75%, of the deposition in a particular watershed or to a
given water body based on results of atmospheric modeling (U.S. EPA. 2008a').
Estimates of atmospheric deposition to the overall estuary N load exhibit wide variability
due in part to the difficulty associated with quantifying multiple agricultural and mobile
and stationary fuel combustion emissions sources and N transformations and losses as the
N moves from the terrestrial watershed to the estuary (U.S. EPA. 2008a; NRC. 2000).
Despite high variability, it appears that atmospheric sources of N loading to estuaries can
be quantitatively important, based on studies reviewed in the 2008 ISA. For example,
atmospheric N loads to estuaries in the U.S. were estimated to range from 2-8% for
Guadalupe Bay, TX, on the lowest end to as high as 72% for St. Catherine's-Sapelo
estuary, GA (Castro et al.. 2003). In another study considering atmospheric deposition of
N to the East Coast and Gulf of Mexico, direct deposition of N was estimated to
contribute from 10 to over 40% of N loading to estuarine, coastal, and open marine
waters (Paerl et al.. 2002). In Chesapeake Bay, studies reviewed in the 2008 ISA
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indicated that atmospheric deposition makes a substantial contribution (about 25%) to the
overall N budget (Howarth. 2007; Boveretal.. 2002).
In a series of studies reviewed in the 2008 ISA, the model WATERS-N estimated that the
contribution of atmospheric deposition (including directly onto the water surface and
indirectly onto the watershed) was 7-60% of the total N input to 34 Atlantic and Gulf
coast estuaries (Castro et al.. 2003; Castro et al.. 2001). Nitrogen deposition contributed
20-86% (average = 48%) of the total N input to 22 watersheds having watershed area to
estuarine surface area ratio less than 15. In systems with a ratio greater than 15, N
deposition is not as important, comprising less than 25% of total N input across
12 systems (Castro et al.. 2001).
Since the 2008 ISA, additional modeling studies have estimated the amount and
proportion of current and future N loading expected to result from atmospheric
deposition. The Nutrient Export from Watersheds (NEWS) and SPARROW models
agreed that 62-81% of N delivered to the coastal zone in the continental U.S. is
anthropogenic in source (McCrackin et al.. 2013). Model results showed that atmospheric
N deposition that is subsequently transported to estuaries represents 17-21% of the total
N exported to the coastal zone (McCrackin et al.. 2013; Moore etal.. 2011). One model
(SPARROW) found atmospheric N deposition to be the dominant source of delivered N
to estuaries along the Atlantic Coast and the Gulf of Mexico (McCrackin et al. 2013).
Using SPARROW, the atmospheric deposition contribution (which may include
volatilized losses from natural, urban and agricultural sources) was estimated to be 26%
of total N transported to the Gulf of Mexico in the Mississippi/Atchafalaya river basin
(Robertson and Saad. 2013). Moore etal. (2011) found that SPARROW identified
atmospheric deposition to watersheds as the dominant source of N to the estuaries of the
Connecticut, Kennebec, and Penobscot rivers, but the third largest source (20%) for the
Northeast and mid-Atlantic coastal region as a whole, after agriculture (37%) and sewage
and population-related sources (28%).
A modeling study conducted by Vadeboncoeur et al. (2010) estimated that the third
largest source of the N loading (via the watershed and directly to the water body) to
Narragansett Bay in the year 2000 was atmospheric deposition (20%). Future scenarios
suggested that very aggressive reductions in both fertilizer use and atmospheric
deposition would be needed for Narragansett Bay to return to early twentieth century
levels of N loading (Vadeboncoeur et al.. 2010). Latimer and Charpentier (2010) applied
the NLM to small- to medium-sized estuaries of southern New England. Direct
atmospheric deposition to the water surface made up an average of 37% of the N input,
although the percentage varied widely for individual estuaries (Latimer and Charpentier.
2010). Indirect deposition via the watershed averaged 16% of N loading. Using WDT,
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Poor et al. (2013b) estimated direct atmospheric loading of 1,080 metric tons of N and
1,490 metric tons of N from indirect atmospheric loading (assuming a watershed-to-bay
transfer rate of 18%) for Tampa Bay using data from 2002. Thus, atmospheric sources
were an estimated 71% of the total N loading. Key studies from the 2008 ISA on
atmospheric N loading to estuaries are summarized in Table 7-8. along with newer
estimates.
Near NH3 emission sources, such as large mammal and poultry livestock operations, N
deposition is expected to increase 10-40% by 2020 according to different regulation and
reduction scenarios (Pinder et al.. 2008). Many of the agricultural emissions sources are
located in sensitive watersheds such as the Chesapeake Bay and Pamlico Sound, NC
(Pinder et al.. 2008). Birch et al. (2011) estimated that 24% of the reactive N that reached
Chesapeake Bay originated as emissions to the atmosphere that were then deposited in
the watershed to land and water; 57% came from terrestrial N additions from nonpoint
source runoff; the remaining 19% was estimated to come from direct discharges of N to
freshwater ecosystems. Results of a modeling study that integrated the airshed,
watershed, and estuary indicated that atmospheric deposition represented one of the
largest inputs of N to the Chesapeake Bay watershed, and about half of it originated
outside the watershed (Linker et al.. 2013). Atmospheric N loading to tidal waters was
included in the Chesapeake Bay 2010 TMDL, the first time that atmospheric deposition
has been included in a plan for nutrient load reduction (U.S. EPA. 2010a). The explicit
TMDL N allocation was determined to be 7.1 million kg per year of total N atmospheric
deposition loads directly to Chesapeake Bay and tidal tributary surface waters. It was
based on the 2020 CMAQ N deposition scenario described by Linker et al. (2013).
The role of large coastal rain events in causing N inputs to coastal areas has been further
characterized since the 2008 ISA. In an isotopic study conducted from rain samples
collected during Hurricane Irene in coastal North Carolina, the majorN source prior to
hurricane landfall was lightning (Felix et al.. 2015). As the hurricane moved inland, the N
isotopic composition in rainfall shifted to indicate more terrestrial sources. These
included vehicle emissions and power plants. Chapter 2. "Nitrogen Source to
Deposition," provides more detailed discussion of N source apportionment.
7.3.2 Chemical Effects and Processes in Estuaries and Near-Coastal Areas
Human activities have altered the loading of N and P to estuary systems throughout the
U.S. (Paerl et al.. 2014). In addition, climatic changes increase variability in freshwater
discharge, and therefore, change nutrient loading and biogeochemistry (Chapter 13).
More severe storms and more intense droughts interact with nutrient inputs and modify
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the magnitude and relative proportion of N and P loading. A number of studies have been
conducted in recent years that further characterize the use of estuarine and near-coastal
marine indicators of eutrophication. These have included experimental, observational,
paleolimnological, and synthesis studies.
In general, estuaries tend to be N limited (Elser et al.. 2007). and many have received
sufficiently high levels of N input from human activities (including deposition,
agricultural runoff and wastewater) to cause eutrophication (Howarth et al.. 1996;
Vitousek and Howarth. 1991). Some of the key processes that influence N cycling in
near-coastal environments include hypoxia, nitrification, denitrification, decomposition,
and other sediment-associated processes.
Atmospherically deposited N, along with other sources of N to coastal systems, influence
processes that operate along the freshwater to ocean continuum I (Paerl and Piehler.
2008); Figure 7-41. These heterogeneous environments are characterized by gradients of
salinity. At the upstream end of an estuary, the water is primarily fresh much of the time.
Nonpoint source runoff of N from the land surface, only a part of which is of atmospheric
origin (mainly deposition to land and subsequently leached to the river water), dominates
new N inputs. Downstream, freshwater inflows gradually mix with salt water to form
mesohaline segments of the estuary. Further along the salinity gradient, much of the
terrestrial N load is assimilated by phytoplankton and benthic flora or removed by
microbes in the process of denitrification (Paerl et al.. 2002). Direct atmospheric N inputs
also impact the lower estuary, although the relative importance of N deposition in this
zone is uncertain (Paerl et al.. 2002). In many estuary and sound ecosystems, primary
production and phytoplankton biomass are highest at mid-estuary locations, where N
loads and decreasing rates of flushing (increasing residence times) overlap. A high level
of chlorophyll a is characteristic of estuaries in which the residence time is sufficiently
long to allow periodic phytoplankton blooms to accumulate.
Estuarine eutrophication can be reflected in increasing concentrations of N in the
sediment or water. In many estuaries this occurs with a simultaneous increase in P.
Runoff N and P contributions are often coupled, especially where agricultural or human
waste sources dominate. Increases in N concentration can have direct effects on the
physiology of aquatic organisms and biodiversity (Chapter 10).
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Atmospheric
Urban/
Coastal
Ocean
Open
Ocean
Estll4ry/ Sou nit
Industrial
Runoff [Aquaculturc
(Jrouritlwaler
ledimenltUiun
Chi a = chlorophyll a; DNF = denitrified; N = nitrogen; N2 = nitrogen; NF = nitrogen (N2) fixation.
Source: From Paerl and Piehler. 2008.
Figure 7-4 Schematic diagram illustrating sources, transformations and fate
of nitrogen along the estuary-to-ocean continuum. Surface,
subsurface, and atmospheric pathways of externally supplied or
new nitrogen inputs attributable to anthropogenic activities are
shown as internal nitrogen cycling. The combined anthropogenic
nitrogen inputs are shown as a thick arrow (upstream), which
decreases in thickness downstream as a portion of the nitrogen
inputs settles to the bottom sediments and is buried and/or
denitrified. Nitrogen (N2) fixation is a biologically mediated new
nitrogen input. The linkage of anthropogenically enhanced
nitrogen inputs to accelerated primary production or
eutrophication and its trophic and biogeochemical fate are also
shown.
7.3.2.1 Nitrification and Denitrification
1 Nitrification and denitrification can be key aspects of N cycling in estuarine and
2 near-coastal marine ecosystems. Nitrification is the microbially mediated conversion of
3 NH4+ to NO;, . The process includes NH3 oxidation to nitrite (NO: ). followed by NO:
4 oxidation to NO3 . The first step is typically rate limiting (Damashek et al.. 2015). This
5 importance was well-known at the time of preparation of the 2008 ISA. More recent
6 research has provided additional quantitative context, including new studies in North
7 America and Europe. The oxidation of NH4 to form NO: largely controls the relative
8 abundance of oxidized and reduced DIN.
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Smyth et al. (2013) measured the N2 fluxes in five major estuarine habitat types in Bogue
Sound, southeastern North Carolina: salt marshes, seagrass beds, oyster reefs, and
inter-tidal and subtidal flats. Based on the distribution of habitats across the study
estuary, it was estimated that about 76% of the watershed N load was removed by
denitrification in the estuary each year. Results suggested that the amount of N removed
by denitrification from an estuary depends on the amount and type of habitats located in
that estuary. Each habitat had a characteristic impact on N cycling in the sediment. Smyth
et al. (2013) concluded that oyster reefs and seagrass beds provided especially high N
removal per unit estuary area. N removed from the estuary is also influenced by benthic
fauna. Stief (2013) reviewed the contributions of benthic macrofaunato the turnover ofN
and to the emissions of greenhouse gasses such as nitrous oxide from the estuary to the
atmosphere. Sediment-burrowing macrofauna stimulated nitrification and denitrification
in the sediment. Together these facilitate removal of N from the estuary system. Benthic
macrofauna intensify the coupling among water, benthos, and atmosphere by enhancing
turnover and transport of N.
In the eutrophic Baltic Sea, denitrification in sediments is important for partially
mitigating the adverse effects of eutrophication. Jantti and Hietanen (2012) demonstrated
that dissimilatory NO3 reduction controlled the overall NO3 reduction under conditions
of low O2. Barnes and Upstill-Goddard (2011) reported measurements of dissolved
nitrous oxide (N2O), inorganic N, O2, and turbidity in six estuaries in the U.K. Results
suggested that the main source of N2O was nitrification; denitrification did not appear to
be a significant NO3 sink in that ecosystem.
Much of the N contributed to riverine estuaries by atmospheric deposition and other
nonpoint and point sources of N is removed from the aquatic ecosystem by either
denitrification or the anaerobic oxidation of NH ? (anammox; Damashek et al.. 2015;
Ward. 2013; Bovnton and Kemp. 2008). These processes predominate in the anoxic
sediments if the water body is well mixed.
Prior to the 2000s, it was generally believed that NH3 oxidation was accomplished only
by Proteobacteria (Damashek et al.. 2015; Kowalchuk and Stephen. 2001). Complexity
increased with the discovery that some Archaea (also called Thaumarchaeota), a
primitive life form separate from bacteria, can also oxidize NH? (Brochier-Armanet et al..
2008; Konneke et al.. 2005). These ammonia-oxidizing Archaea (AOA) are dominant in
some estuaries (Moin et al.. 2009). Ammonia-oxidizing bacteria (AOB) are important in
others (Abell et al.. 2010). These two life forms can vary spatially in importance in still
other estuaries (Damashek et al.. 2015; Zheng et al.. 2014). Benthic NH? oxidizers may
be able to oxidize a significant quantity of NH4+ in NH4 -rich systems, such as the
Sacramento River (Damashek et al.. 2015). Several studies that have examined changes
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in AOA and AOB relative abundance and community structure associated with N loading
are reviewed in Section 10.3.4.
7.3.2.2 Sediment Processes and Dissolved Oxygen
In the 2008 ISA, DO was identified as a useful chemical indicator of eutrophic conditions
in estuaries. It was also included as an indicator in the NEEA (Bricker et al.. 2007). The
decomposition of organic matter associated with increased algal abundance consumes
DO and can reduce concentrations in eutrophic waters to levels that cannot support
aquatic life. Decreased DO can lead to development of hypoxic (<2 mg/L of dissolved
O2) or anoxic zones that are inhospitable to fish and other life forms. The threshold of
dissolved O2 in estuarine bottom waters used in the National Coastal Condition
Assessment (U.S. EPA. 2016c) were as follows: good condition, >5 mg/L; fair condition,
2-5 mg/L; poor condition, <2 mg/L.
Biogeochemical processes that occur in the sediment of estuarine and near-coastal
ecosystems are important to the cycling of N that is deposited or transported to estuarine
ecosystems. Development of seasonal hypoxia is common in shallow coastal regions that
receive high inputs of nutrients, including N, from coastal rivers. Development of
hypoxia is increasingly becoming a concern throughout the U.S. and internationally.
Climate change may intensify this phenomenon (Chapter 13).
Processes that govern hypoxia at or near the sediment-water interface have been
investigated in a new study in Chesapeake Bay by Testa and Kemp (2012). They
investigated interactions between hypoxia and nutrient cycling in the bay, based on
analysis of long-term monitoring data collected during two time periods: 1965 to 1980
and 1985 to 2007. They found that bottom water in the upper Bay region, where seasonal
hypoxia first develops, was enriched in NH4 and PO4 relative to other regions of the
bay. This might help explain the occurrence of extensive and persistent hypoxia during
the month of June even during years of lower N loading.
The potential effects of sustained hypoxia using sediment that had been collected from
the southern North Sea were measured by Neubacher et al. (2013) in mesocosms. The
focus of this research was partly on the consumption and penetration of O2 into the
sediment. Exchange ofN03 NO2 , and NH4 between the sediment and water was erratic
in the early days of the experiment. However, once a steady state was established after
10 days, the sediment acted as either a sink for fixed N under hypoxia or as a source of
fixed N under higher O2 levels in the controls. Under sustained hypoxic conditions,
production of N2 gas increased by 72% relative to controls. It appeared that hypoxia
could increase the removal of fixed N by denitrification and anammox.
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Organic particles that are formed in nutrient-enriched coastal regions often settle to the
bottom where they accumulate and decompose at or above the sediment-water interface.
Decomposition of these organic particles removes O2 and transforms nutrients in the
water. N dynamics at the sediment water interface were examined by Gardner and
McCarthy (2009) in four regions of Florida Bay, and they provided estimates of sediment
O2 demand and the fluxes of nutrients. Florida Bay differs from many other estuarine and
marine systems in that N tends to be relatively high, and P (rather than N) often limits
biological production. Reduced forms of inorganic N in this bay are commonly as
abundant or more abundant than NO3 . The high availability of NH44" and organic N can
promote development of HABs in the water column, and loss of seagrass beds from
shallow areas. High salinity, temperature, and the availability of organic C might
exacerbate the effects of nutrient inputs to this bay, including N, while maintaining
bioavailable N as NH4+ or NO2 rather than removal from the system by denitrification or
anammox. Results of this study suggested that there is an important linkage between the
dynamics of N and O2, with both being affected by estuarine eutrophication.
Since the 2008 ISA, additional studies focused on marine biogeochemistry and DO have
further characterized ecosystem responses. Rabalais et al. (2010) provided a synthesis of
knowledge regarding hypoxia in coastal waters. Hypoxic water masses (less than
approximately 30% saturation) are more likely to occur in marine waters where and when
water residence time is long, water exchange is limited, the water column stratifies, and
the production and movement of C to bottom waters are relatively high. It is well known
that the development and continuation of hypoxia in estuary and marine systems can be
accelerated by increased nutrient (N, P) loading. In locations where coastal upwelling can
be a large source of nutrient loads such as the Pacific Northwest, advection of upwelled
water can introduce hypoxic water into estuaries that is not related to anthropogenic
eutrophication (Brown and Power. 2011; Brown and Ozretich. 2009).
Climate change and associated thermal stratification of the water column will further
complicate biogeochemical processes that regulate natural and human-caused hypoxia
(Chapter 13). Increased thermal stratification will worsen hypoxia where it already occurs
and will facilitate its formation at other locations (Rabalais et al.. 2010). Increased
precipitation in some areas will increase freshwater discharge and the flux of nutrients
from terrestrial to estuary ecosystems. This is expected to result in increased primary
production in the receiving waters, at least in the short term. The interactions between
increased nutrient loading and thermal stratification will accelerate hypoxia. Middelburg
and Levin (2009) provided a review of coastal hypoxia and linkages with
biogeochemistry. Changes in bottom water O2 concentrations influence chemical
exchange between sediment and bottom water.
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Low DO is a major contributor to loss of biodiversity and ecosystem functioning in
coastal ecosystems. Despite extensive restoration efforts in the Chesapeake Bay
watershed, water quality indicators (chlorophyll a, DO, and Secchi depth) and biotic
metrics of ecological condition have shown little improvement during a 23-year period
Williams et al. (2010) The one exception to the pattern of no improvement in water
quality was an observed increase in the amount of SAV. Overall, water quality has
decreased and chlorophyll a levels have increased since 1986. Climate is related to the
observed patterns. Nutrient inputs associated with higher-than-average annual discharge
in the estuary after 1992 contributed to this response. Biological responses to hypoxia are
addressed in greater detail in Chapter 10.
7.3.2.3 Nutrient-Enhanced Coastal Acidification
Dissolution of atmospheric anthropogenic CO2 into the ocean has led to long-term
decreases in pH. With increasing inputs of N and other nutrients to coastal waters, CO2 is
produced from decomposition of excess organic matter associated with eutrophication.
This additional CO2 further acidifies marine waters as it dissociates into carbonate ions
and hydrogen ions (Sunda and Cai. 2012; Cai etal.. 2011c; Howarth et al.. 2011).
Estuarine acidification was detected in eutrophic zones of estuaries of Narragansett Bay,
Long Island Sound, Jamaica Bay, and Hempstead Bay during late summer and early fall
(Wallace et al.. 2014; Orr et al.. 2005). Biogeochemical modeling of eutrophically driven
ocean acidification coupled to data collected from the Gulf of Mexico, the Baltic Sea, and
the East China Sea predicted that eutrophication would cause a 0.24 to 1.1 unit decrease
in pH of bottom waters, and also found that increasing atmospheric CO2 will
synergistically amplify eutrophically driven acidification (Sunda and Cai. 2012; Cai et
al.. 2011c).
7.3.3 Modeling Estuaries and Near-Coastal Areas
7.3.3.1 Models
There are models that track the sources and movement of N through the landscape and
stream network to estuary and near-coastal marine ecosystems. These models vary in
scope, level of spatial and temporal resolution, forms of N considered, model complexity,
and empirical versus deterministic construction (Alexander et al.. 2008). They can be
structured as statistical models (Howarth et al.. 2012; Peierls et al.. 1991). empirical
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models (C'araco and Cole. 1999). export coefficient models (Johnes. 1996). deterministic
models such as SWAT (Gassman et al.. 2007; Nietsch et al.. 2002) and Generalized
Watershed Loading Function [GWLF; (Haith and Shoenaker. 1987)1. and hybrid
approaches (SPARROW, NEWS). The principal ecosystem models applied to U.S.
waters to assess N enrichment were reviewed in Annex 3 of the 2008 ISA and are briefly
summarized here (U.S. EPA. 2008a).
Several models have been applied at national or large regional scales to examine N
loading to rivers and the coastal zone. SPARROW is a hybrid statistical-mechanistic
model that can attribute pollutant sources and contaminant transport to surface waters
(Smith et al.. 1997). SWAT is a mechanistic model developed by the U.S. Department of
Agriculture, Agricultural Research Service (Gassman et al.. 2007; N ietsch et al.. 2002).
WATERS-N is a mass balance model that has been used to evaluate N inputs to estuaries
(Castro et al.. 2003; Castro et al.. 2001).
Since the 2008 ISA, there have been new applications of SPARROW and SWAT, as well
as development and application of new models and approaches such as NEWS and Net
Anthropogenic Nitrogen Inputs (NANI). SPARROW has been used to estimate total N
loads within watersheds to determine sources of N to streams and rivers. It has also been
applied at regional and national scales (Schwarz et al.. 2011; Alexander et al.. 2008).
SPARROW operates on an annual time step, usually integrating multiple years of data to
develop load relationships and then simulating conditions for 1 year. NEWS is a similar
hybrid model. It has been used to estimate the magnitudes and sources of different forms
of N (particulate, dissolved inorganic, and organic) to coastal waters (Glibcrt et al..
2010a). Recent work with NEWS included a global, seasonal version (McCrackin et al..
2014). It has been used for scenario comparisons, including predictions about reductions
in air deposition resulting from CAA regulations (McCrackin et al.. 2015). NANI is a
simple model that takes information about inputs and outputs of nitrogen within a basin
and estimates the riverine flux from the landscape to the ocean (Howarth et al.. 2012).
Deterministic models of N flux are based on mechanistic relationships that simulate N
transformations, transport, and removal, often at relatively fine temporal and spatial
resolution. SWAT has been recently applied at the regional scale of the Mississippi River
Basin (Santhi et al.. 2014). It allows examination of the effects of changes in cropland
management on delivery of N to coastal waters. Recent SWAT publications do not
explicitly include atmospheric deposition as a source of N, but have produced similar
overall results as SPARROW and NEWS in terms of load and attribution to agriculture in
the Mississippi River basin (-54-61%; White et al.. 2014; McCrackin et al.. 2013).
The watershed models described above route N from the landscape to estuaries and the
coastal zone, but generally do not model the contribution of N directly to the estuary
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surface from the atmosphere. These models also deal with the freshwater components of
watersheds and do not predict N fate within estuaries or N effects on estuarine processes
or functions. The following sections describe new applications of several models that
operate within estuaries.
Additional models and tools that have been applied to assess atmospheric contributions of
N to U.S. estuaries since the 2008 ISA included the watershed N Loading Model [NLM;
(Latimer and Charpentier. 2010)1 and the Watershed Deposition Tool [WDT; (PooretaL
2013b)]. The latter was developed by the U.S. EPA to map atmospheric deposition
estimates to watersheds using wet and dry deposition data from the Community
Multiscale Air Quality Model [CMAQ; (Schwede et al.. 2009)1. This tool links air and
water quality modeling data for use in total maximum daily load (TMDL) determinations
and analysis of nonpoint-source impacts. The NLM has been used for New England
estuaries to estimate total N loading and the relative contributions of the various N
sources. Across all of the studied estuaries in New England, direct atmospheric
deposition to the estuary represented about 37% of the total N inputs, while wastewater
represented 36% of the total N inputs. Indirect atmospheric deposition within the
watershed was estimated to be 16% and the fertilizer component was 12%. The relative
magnitudes of these source types varied across estuaries. The N loading estimates were
used to develop load response relationships among N inputs and ecological responses
related to seagrass extent (Latimer and Rego. 2010).
Hinsbv et al. (2012) evaluated the N and P concentrations of groundwater and surface
water in a coastal watershed in Denmark. Calculations using empirical models and a
hydrological model of the catchment suggested that the N and P loads should be reduced
to levels corresponding to about 52 and 56% of ambient loads of N and P, respectively, in
order to restore ecological status.
7.3.3.2 Predicted Response to Nitrogen Loading
Many of the models that estimate N loads to the coastal zone from the landscape and
freshwater inflow have been compared, and there is a good deal of knowledge about their
limitations and uncertainties (McC'rackin et al . 2013: Alexander et al.. 2008). In a 2000
National Research Council review, it was determined that these models are
hydrodynamically complex and tend to be specific to particular sites. Thus, they are
difficult to apply broadly (NRC. 2000).
The range of coastal ecosystem responses to changing N loads reflect changes in DO,
productivity, SAV cover, and impacts on other organisms. Water residence time can
influence the response of estuaries to nutrient loading because of the effects of flushing
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on nutrients, water temperature, plankton, and light penetration. Capturing these
dynamics in a model is challenging (Swanev et al.. 2008).
A recent review of hypoxia modeling described trade-offs between details of complex
models and the need for simpler, more broadly applicable models (Pena et al.. 2010).
Greene et al. (2009) developed a set of multiple regression models to simulate
relationships between river loads and concentrations of N and P compared with the extent
of hypoxic bottom water. A Bayesian approach was used in combination with a model of
hypoxia to project the O2 demand and extent of hypoxia (Liu et al.. 2010). Estuarine
models have been important to policy decision making and formulation of nutrient
reduction goals (Scavia et al.. 2006; Scavia et al.. 2004). There is an increased interest in
developing coupled models that connect physical-chemical-biological nutrient loading
and fate models (Fennel et al.. 2011) and to connect chemical eutrophication models to
fisheries response models (Cerco et al. 2010).
A number of new studies have been conducted since the 2008 ISA to quantify or model
eutrophication processes in estuaries and near-coastal marine ecosystems. These have
included studies that focused primarily on N cycling, hypoxia, and HABs.
The responses of estuaries to N loading is partly determined by environmental
characteristics. Nutrient-phytoplankton-zooplankton (NPZ) models examine biological
responses including the effects of nutrient limitation and zooplankton predation on
phytoplankton dynamics and fish production. The NPZ model described by Swanev et al.
(2008) can assess complex responses of estuaries to different climate variables, land use,
atmospheric loading, and other stressors.
New studies have focused on increasing understanding of spatial variation in DIN export
from the watershed to coastal zones. Seasonal patterns of DIN export influence impacts
of coastal eutrophication, including HABs and the development of seasonal hypoxic
zones. McCrackin et al. (2014) predicted seasonal TIN export to coastal regions, using
the NEWS2 model calibrated to measured DIN yield in 77 rivers distributed globally.
The DIN transport efficiency was positively correlated with runoff and negatively
correlated with temperature. McCrackin et al. (2014) concluded that because of landscape
N attenuation, a better representation of land-to-river N transfers, in particular, might
improve models of nutrient cycling.
Eldridge and Morse (2008) developed a combined water-column and sediment model to
investigate sediment and water-column metabolism and their impacts on development of
hypoxia on the Louisiana shelf. They found that sediment O2 demand was the primary
sink for O2 at the beginning and end of a hypoxic event. Once hypoxia has developed,
however, sediments became isolated from 02-rich upper waters.
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Key drivers of hypoxia in coastal waters include nutrient loading, mainly from
anthropogenic sources, and processes that contribute to thermal stratification. Complex
hypoxia models are difficult to validate, however, and this limits the confidence that can
be placed on simulation results. Eldridge and Roelke (2011) recommended the use of
multiple models and identification of similarities in qualitative model behavior. They
provided a brief overview of recent hypoxia models, and identified the need for a
meta-analysis of simulations produced by these models in search of qualitative
similarities. They concluded that there is a need for development of more complex
models of hypoxia that include three-dimensional hydrology. Sturdivant et al. (2013)
developed a model of hypoxia impact on macrobenthic production in the lower
Rappahannock River, a tributary of the Chesapeake Bay that experiences seasonal
hypoxia. Simulation results suggested that macrobenthic biomass was strongly linked
with dissolved O2 concentration. Biomass fluctuations reflected the duration and severity
of hypoxia. Results suggested that hypoxia had a negative effect on biomass, with longer
duration and greater severity resulting in increased loss of biomass.
Glibert et al. (2010a) reviewed modeling approaches to improve understanding of HABs
and their relationship with nutrient inputs. They recommended that predictive capabilities
will likely improve if a suite of modeling approaches is used. This might include
site-specific loading models of nutrient sources and models that couple nutrient discharge
to biological responses.
Dale etal. (2011) investigated biogeochemical processes that affect N cycling in the
sediment of Eckernforde Bay in the southwestern portion of the Baltic Sea, where severe
bottom water hypoxia (and sometimes anoxia) commonly occurs during late summer.
Sediments acted as net sinks for NO3 . of which three-fourths was characterized as
derived from reduction of NO3 to NH4 . The other 25% was characterized as derived
from denitrification of NO, to NO2 . The NH4 flux was high (1.74 mmol/m2/day), in
response to degradation of organic N at the sediment interface, and was directed out of
the sediment.
7.4 Summary
7.4.1 Freshwater Biogeochemistry Summary
In the 2008 ISA, the body of evidence was sufficient to infer a causal relationship
between N and S deposition and the alteration of biogeochemical cycling of N and C in
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freshwater ecosystems, and between acidifying deposition and changes in
biogeochemistry of freshwaters. The strongest evidence for causal relationships between
N and S deposition and biogeochemistry of receiving water bodies typically derives from
studies of changes in surface water chemistry. These studies use approaches such as
monitoring, modeling, and/or experimental manipulation. As reviewed in the 2008 ISA
and newer studies, biogeochemical processes and surface water chemistry are influenced
by characteristics of the catchment and the receiving waters. Atmospheric deposition
affects the chemistry, and often also the biology, of each type of freshwater environment.
Increased acidity of water bodies due to N + S deposition—evaluated by chemical
indicators such as SO42 , NO3 . pH, Ca2+, alkalinity, ionic metals (especially inorganic
Al) and ANC—may result in loss of acid-sensitive biota. These waters may be
chronically acidified or subject to occasional episodes of decreased pH, decreased ANC
and increased inorganic Al concentration. Increased N deposition to freshwater systems
via runoff or direct atmospheric deposition, especially to N limited and N and phosphorus
(P) colimited systems, can stimulate primary production. Eutrophication is the process of
over-enrichment of a water body with nutrients resulting in increased production of algae
and/or aquatic plants, and sometimes also decreased O2 levels. Monitoring data from
studies ongoing for decades provide a temporal context for biogeochemical processes and
indicators of ecosystem changes associated with eutrophication and acidification. New
information on biogeochemical cycling of N and S, acidifying deposition effects on
biogeochemical processes and changes to chemical indicators of surface water chemistry
associated with acidification and N nutrient enrichment is consistent with the conclusions
of the 2008 ISA, and the body of evidence is sufficient to infer a causal relationship
between N and S deposition and the alteration of freshwater biogeochemistry.
Indicators of altered N cycling include changes in the concentrations of NO3 , DIN, and
indicators of trophic status such as N and P ratios. It was well known at the time of the
2008 ISA that key processes such as nitrification and denitrification are quantitatively
important portions of the N cycle and that they can be influenced by atmospheric inputs
of oxidized and reduced N. More recent research has further substantiated these earlier
findings and provided additional quantitative context. Some new research suggests that
denitrification may, in some situations, produce more N2O in relationship to surface
water nitrate concentration than was previously recognized. The quantity and timing of
N03 leaching into surface waters is an indicator of terrestrial N cycling in the associated
watershed. The concentration of NO, in drainage water provides an index of the balance
between removal and addition of N to terrestrial ecosystems. Studies of several types
have been conducted in recent years to elucidate these processes, including experimental
studies, isotopic analyses, monitoring, and observational studies.
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The dynamic nature of N and P bioavailability and their influence on nutrient limitation
in producers have been important avenues of recent research. Studies have included
ecosystem experiments, gradient studies, monitoring, and observation. The ratio of N:P in
aquatic ecosystems can provide information on N cycling and its behavior in aquatic
ecosystems. Many studies have been conducted in recent years on the topics of nutrient
limitation in aquatic ecosystems and the relative importance of N versus P loading in
controlling eutrophication processes. The long-held paradigm that freshwaters are
typically P limited has been replaced by an understanding that both N and P can limit
primary production, and that nutrient limitation can be a dynamic and transient process.
N deposition can act as a fertilizer in aquatic systems and increase the production of
photosynthesizing organisms, resulting in a larger pool of fixed C in aquatic systems.
Indicators of production effects of deposition include nutrient ratios. Recent research has
shown increased primary production in alpine lakes that receive relatively high
atmospheric N deposition (>6 kg N/ha/yr) as compared with lakes that received low
deposition [<2 kg N/ha/yr; (Elser et al.. 2009bVI. High-deposition lakes showed an
increased frequency of P limitation and a decreased frequency and magnitude of response
to N and to combined N:P enrichment. It appears thatN deposition has changed the
nutrient supply to these lakes from a more or less balanced (mainly N deficient) state to
more consistently P limited conditions. Bergstrom (2010) documented variation in N:P
ratios (TN:TP and DIN:TP) in oligotrophic lakes located in northern Europe and the
Rocky Mountains region of the U.S. More than half (54%) of the oligotrophic lakes had
TN:TP mass ratio <25. The DIN:TP ratio was found to be a better indicator of nutrient
limitation of phytoplankton growth than the TN:TP ratio. A change was observed by
Bergstrom (2010) from N to P limitation when the DIN:TP mass ratio increased from 1.5
to 3.4. High DIN:TP, indicative of P limitation, was found in alpine lakes that received
low to moderate N deposition and in boreal lakes that received high N deposition
(>13 kg N/ha/yr). The relative ratios of N and P are a sensitive indicator of N deposition
effects upon freshwater primary producers.
The changes in major biogeochemical processes and soil conditions caused by acidifying
deposition (Chapter 4) have significant ramifications for the water chemistry and
biological functioning of associated surface waters. Because surface water chemistry
integrates the sum of soil and water processes that occur upstream within a watershed, it
also reflects the results of watershed-scale terrestrial effects. Deposited S and N interact
with the sediments of these environments via oxidation and reduction reactions, and are
immobilized and mineralized by biota. The strongest evidence for a causal relationship
between acidifying deposition and aquatic biogeochemistry comes from studies of
changes in surface water chemistry, including concentrations of SO42 , NO3 . inorganic
Al, Ca, sum and surplus of base cations, ANC, and surface water pH. Data from
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long-term monitoring, nutrient addition and modeling studies provide consistent and
coherent evidence for biogeochemical changes associated with N and S deposition.
Monitoring data have proven to be a reliable means with which to confirm environmental
models and evaluate damage/recovery of ecosystems in response to changes in acidic
atmospheric deposition. A number of freshwater monitoring studies have documented
ecosystem damage and recovery caused by acidifying deposition of S and/or N. Many of
these studies have been conducted in the U.S., especially in the northeast and the
Appalachian Mountains and Bear Brook watershed in Maine. Studies conducted in
Canada and Europe further corroborate findings in the U.S. Since 2008, TIME, LTM, and
other long-term studies have documented and quantified the responses of surface waters
to changes in acidic deposition and other ecosystem drivers. Although many of these
monitoring programs were in existence at the time of the 2008 ISA and were considered
in that analysis, more recent publications reflect the longer period of monitoring record
and strengthen previous conclusions.
Bear Brook watershed in Maine has been the site of an ongoing experimental N and S
addition since 1989. A recent study evaluated hydrological and chemical data from
212 high flow events in paired (N + S, control) watersheds to determine the
environmental factors responsible for episodic acidification in surface waters. Ambient
drivers of episodic acidification at this site included deposition of marine salts,
contributions of organic acidity from primary producers, and base cation dilution, and
experimental N + S additions did not alter these natural causes. However, S addition
decreased ANC during high flow events in the experimentally acidified watershed, and
the effect of SO42 upon ANC grew stronger over time. NO, contributed to decreases in
ANC, but its effect upon ANC remained about the same magnitude over the
approximately two decades of the experiment. Thus, both NO3 and SO42 contributed (in
addition to natural processes) to episodic acidification, but their relative roles changed
over the course of the experimental ammonium sulfate addition (Laudon and Norton.
2010V
Reductions in SOx deposition have resulted in changes in lake water sulfate
concentrations, although S stored in watershed soil still affects water quality. Decreases
in lake SO42 concentrations were documented (-2.14 (imol/L/yr) in 16 Adirondack
Long-Term Monitoring lakes that were sampled between 1984 and 2010 (Mitchell et al..
2013). Sulfur mass balance discrepancies were linked with discharge, and suggested that
internal S sources have become increasingly important as atmospheric S inputs have
declined. With long-term decreases in atmospheric S deposition, the effects of future
increases in precipitation will likely become increasingly important in regulating the
amount of SO42 mobilized from internal watershed sources. A number of S cycling
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studies (Rice et al.. 2014; Mitchell et al.. 2013) have emphasized the importance of S
adsorption and desorption and their interactions with soil pH. In addition, internal
watershed sources of S, which were earlier believed to be relatively minor in the
northeastern U.S., have and will likely continue to become proportionately more
important as S deposition continues to decline.
Reductions in SOx deposition have not consistently resulted in increases of base cation
supply in soils or ANC in surface water. The quantitatively most important component of
the overall surface water acidification and chemical recovery responses has been change
in base cation supply. This was highlighted in the assessment of Charles and Christie
(1991) and in the 2008 ISA. Base cations are added to watershed soils by weathering of
minerals and atmospheric deposition, and are removed by uptake into growing vegetation
or by leaching. Acidic deposition increased leaching of base cations, as SO42 leaching
into soil solution from soil particles carried along base cations as a function of charge
balance. In watersheds with historical acidic deposition, current concentrations of Ca2+
and other base cations are substantially reduced from likely preindustrial levels, having
been depleted by many years of acidic deposition. This base cation depletion constrains
ANC and pH recovery of surface waters. This was described in the 2008 ISA. Recent
results have further corroborated earlier findings and have included experiments,
modeling, and gradient studies.
Recent research has described an ecosystem recovery response to decreasing SOx
deposition that was not a focus of the 2008 ISA: DOC increases in surface water. It has
been recognized for several decades that surface water DOC concentrations had
decreased to some extent as a result of SOx acidification, and that DOC would likely
increase with recovery. However, the strength of this response and the magnitude of
DOC change have exceeded scientific predictions. Research on this topic has been
diverse and has included experiments, observation, isotope studies, and synthesis and
integration work. Overall, these studies illustrate large increases in DOC with
acidification recovery in some aquatic systems. Increases in DOC constrain the extent of
ANC and pH recovery, but decrease the toxicity of dissolved Al by converting some of it
from inorganic to organic forms (Lawrence et al.. 2013).
Changes in DOC are not indicative only of ecosystem response to SOx deposition, and
should be interpreted with caution. The concentrations of DOC in lakes and streams
throughout much of Europe and eastern North America have increased over the last three
decades (Porcal et al.. 2009). Such changes have been attributed to increased atmospheric
CO2 concentration, climate warming, decreased S deposition with associated changes in
water pH and ionic strength, and hydrologic changes associated with drought and
precipitation. Although not all increases in DOC are directly caused by decreases in
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acidifying deposition, any changes in DOC concentration or properties can impact the
acid-base chemistry of surface waters and perhaps the composition of aquatic biota.
It is important to recognize that recent changes in atmospheric S and N deposition,
although substantial in many areas of the U.S., have not occurred in a vacuum. Other
important ecosystem drivers have also changed, and these changes have varied by region.
The potential importance of these factors was known at the time of preparation of the
2008 ISA. More recent work has further confirmed the importance of these linkages,
especially those related to climate (Chapter 13).
7.4.2 Estuary and Near-Coastal Biogeochemistry Summary
In the 2008 ISA, the evidence was sufficient to infer a causal relationship between
reactive N deposition and biogeochemical cycling in estuarine and near-coastal marine
systems. Evidence reviewed in the 2008 ISA along with new studies indicate elevated N
inputs to coastal areas can alter key processes that influence C and N cycling in
near-coastal environments. These processes, including hypoxia, nitrification,
denitrification, and decomposition, have been further characterized since the 2008 ISA.
New studies and evidence reviewed in the 2008 ISA continue to show that many coastal
areas, atmospheric deposition typically constitutes less than half of the total N supply;
however, atmospheric inputs are heterogeneous across the U.S. ranging from <10 to
approximately 70% of the N inputs. As stated in the 2008 ISA, estuaries tend to be N
limited (Elser et al.. 2007). and many currently receive high N loads from human
activities (e.g., atmospheric deposition, agricultural runoff, wastewater, and other
sources), which can cause eutrophication (Howarth et al.. 1996; Vitousek and Howarth.
1991). In new research as well as in studies reviewed in the 2008 ISA, both point and
nonpoint sources have been identified as targets for control of N inputs (Stephenson et
al.. 2010; Paerl et al.. 2002). Nearly two-thirds of the estuaries in the U.S. assessed by
Bricker et al. (2007) in the NEEA conducted by NOAA and summarized in the 2008 ISA
had moderate to high eutrophic conditions and received relatively high N loads from both
atmospheric and nonatmospheric sources. New information is consistent with the
conclusions of the 2008 ISA that the body of evidence is sufficient to infer a causal
relationship between N deposition and the alteration of biogeochemistry in estuarine
and near-coastal marine systems.
Several studies suggest that N loading, a portion of which is atmospheric in origin, can
contribute to the process of acidification in estuaries via decomposition of increased
primary production into CO2 (Wallace et al.. 2014; Orr et al.. 2005). The CO2 produced
in eutrophic estuarine waters combines with water molecules, producing carbonic acid,
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1 which makes the water more acidic (Sunda and Cai. 2012; Cai et al.. 2011c; Howarth et
2 al.. 201 1). Modeling of coastal acidification via N enrichment and atmospheric CO2
3 dissolution suggests that the combined effects of these two pathways are synergistic. The
4 body of evidence is sufficient to infer a likely causal relationship between N
5 deposition and increased nutrient-enhanced coastal acidification.
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CHAPTER 8 BIOLOGICAL EFFECTS OF
FRESHWATER ACIDIFICATION
This chapter characterizes the biological effects of acidifying deposition of nitrogen (N)
and sulfur (S) in freshwater systems. Chemical indicators of surface water chemistry are
linked to biological endpoints (Section 8.1) in freshwater systems experiencing either
chronic or episodic acidification (Section 8.2). Affected biota include plankton,
invertebrates, fish, and other organisms (Section 8.3). Next, documentation of biological
recovery in previously acidified systems (Section 8.4) is reviewed. Section 8J includes
levels of deposition at which effects are manifested and empirical and modeled critical
loads for acidifying deposition. A summary section with causal determinations based on a
synthesis of new information and previous evidence of biological effects of aquatic
acidification is presented in Section 8.6.
8.1 Introduction
In the 2008 Integrated Science Assessment for Oxides of Nitrogen and Sulfur-Ecological
Criteria (2008 ISA), the body of evidence was sufficient to infer a causal relationship
between acidifying deposition and changes in freshwater biota. Changes in
biogeochemical processes and water chemistry caused by deposition of N and S to
surface waters and their watersheds (Chapter 7) have been well characterized for several
decades and have ramifications for biological functioning of freshwater ecosystems. The
2008 ISA and studies since have shown that acidification from acid deposition can result
in the loss of acid-sensitive organisms, population declines, and decreased species
richness. This evidence is consistent and coherent across multiple species. More species
are lost with greater acidification, providing evidence of a biological gradient in effects.
Studies indicate that aquatic biota have been affected by acidification at virtually all
trophic levels in sensitive aquatic ecosystems. New information is consistent with the
conclusions of the 2008 ISA that the body of evidence is sufficient to infer a causal
relationship between acidifying deposition and changes in biota including
physiological impairment and alteration of species richness, community
composition, and biodiversity in freshwater ecosystems.
As reported in the 2008 ISA, effects of acidifying deposition on biotic integrity of
freshwater organisms can be linked to changes in several key chemical effects indicators,
including pH, dissolved inorganic aluminum (Al) concentration, and acid neutralizing
capacity (ANC). Biological effects are primarily attributable to low pH and high
inorganic Al concentration. ANC, a measure of the overall buffering capacity against
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acidification, is also used because it integrates overall acid status and because surface
water acidification models do a better job projecting ANC than pH and inorganic A1
concentrations. However, ANC does not relate directly to the health of biota. The
usefulness of ANC lies in the association between ANC and the surface water
constituents that directly contribute to or ameliorate acidity-related stress, in particular
inorganic Al, calcium (Ca), and H+ (measured as pH).
Chemical factors such as pH, Ca, alkalinity, ionic metals and dissolved organic carbon
(DOC) can profoundly affect the structure and function of biological communities in
lakes and streams. Inorganic Al is minimally soluble at soil or surface water pH of about
6.0, but solubility increases steeply as pH values drop below about 5.5. Low
concentrations of base cations like Ca enable low pH and high concentrations of
inorganic Al to occur (Baker et al.. 1990b). However, DOC can bind to inorganic Al ions
and reduce their bioavailability and toxic impact on aquatic biota. The base cation surplus
(BCS) is an alternate index that also describes acid-base status of surface waters
(Lawrence et al.. 2007). BCS is based on a measurement of ANC (calculated from the
charge balance of ionic concentrations in water) and also accounts for the influence of
natural organic acidity.
Acid-sensitive freshwater systems can either be chronically acidified or subject to
occasional episodes of decreased pH, decreased ANC, and increased inorganic Al
concentration (Chapter 7). Changes to flow and surface water chemistry characteristic of
these events reflect the influence of acidic inputs from precipitation, gases, and particles,
as well as the local geology and soil. As stated in the 2008 ISA, surface water chemistry
is a good indicator of the effects of acidification on the biotic integrity of freshwater
ecosystems because it integrates the sum of soil and water processes that occur within a
watershed. The surface water chemistry also reflects and integrates the biogeochemical
processes occurring in the watershed, including N saturation, forest decline, soil
acidification, and land use (U.S. EPA. 2003).
Acidification studies reviewed in the 2008 ISA included laboratory experiments,
bioassays, mesocosms, field observations, and whole ecosystem acidification studies.
Baker et al. (1990a) conducted a rigorous review of the effects of acidification on aquatic
biota for the 1990 National Acid Precipitation Assessment Program (NAPAP) State of
Science/Technology reports. In this report hundreds of laboratory, in situ bioassay, field
surveys, whole-system field experiments, and mesocosm studies on the effects of
acidification on aquatic biota were evaluated. The findings in that report along with
literature published after 1990 up to December 2007 were assessed in the 2008 ISA.
Measures of health, vigor, reproductive success, and biodiversity of aquatic biota were
identified in the 2008 ISA as being affected by acidified waters from acidifying
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deposition. Effects have been most clearly documented for fish, aquatic invertebrates, and
algae.
Since publication of the 2008 ISA, the overarching understanding of aquatic acidification
has not changed appreciably. More recent research has confirmed and strengthened this
understanding and provided more quantitative information, especially across the regional
landscape. This chapter highlights post-2007 research literature findings.
8.2 Chronic versus Episodic Acidification and Biological
Response
Acidification may occur as a chronic or an episodic condition. As defined in the 2008
ISA a chronic condition refers to annual average conditions, which are often represented
as summer and fall chemistry for lakes and as spring baseflow chemistry for streams.
Episodic condition refers to conditions during rainstorms or snowmelt when
proportionately more drainage water is routed through upper soil horizons, which tend to
provide less neutralization of atmospheric acidity as compared with deeper soil horizons.
Surface water chemistry exhibits lower pH and acid neutralizing capacity (ANC) during
episodic than baseflow conditions. Driscoll et al. (2001b) defined that chronically acidic
lakes and streams maintain an ANC of <0 (ieq/L throughout the year, while ANC during
episodic events may fall below 0 |icq/L only for a few hours to weeks.
A large portion of the available data reported in the 2008 ISA focused on lakes and
streams in the Northeast and the southern Appalachian Mountains (U.S. EPA. 2008a')
because these systems have been the most impacted by acidifying deposition in the past
and have the best available surface water monitoring information. Since completion of
the literature review for the 2008 ISA, considerable research has been conducted on
changes in chronic surface water chemistry in the U.S. in response to changing levels of
acidic deposition (Chapter 7). Many of these studies have further documented chemical
recovery as S and N deposition continue to decline in most areas in the U.S. Biological
recovery has been observed in some of those systems, but data generally indicate that it
lags behind chemical recovery (Section 8.4).
Many streams that exhibit chemical conditions during base flow that are suitable for
aquatic life are subject to occasional episodic acidification that may exceed the acid
tolerance of many aquatic species. Episodic events vary in timing, duration, and intensity.
Episodic acidification is most common in the early spring and late fall, and least common
in summer, when high flows tend to be infrequent (Driscoll et al.. 2001b). This
seasonality of episodic events reflects the influence of deposition accumulating in the
landscape that is flushed out during precipitation or snowmelt events. Episodic processes
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are mostly natural, but SO42 and NO3 influxes due to atmospheric deposition play
important roles in the episodic acidification of some surface waters.
As reported in the 2008 ISA, episodes are generally accompanied by changes in two or
more of the following chemical parameters: ANC, pH, concentration of base cations,
SO42 , NO3 , aluminum ions, organic acid anions, and DOC (Sullivan. 2000). During
such short-term episodes (hours or days), both flow and water chemistry can change
markedly. Biological effects of episodes sometimes include fish mortalities, changes in
species composition, and declines in aquatic species richness across multiple taxa,
ecosystems, and regions. The U.S. EPA's Episodic Response Project (ERP) in the 1980s
confirmed the chemical and biological effects of episodic pH depressions in lakes and
streams in parts of the U.S. (Wigington et al.. 1993). In this report, streams having acidic
episodes showed long-term effects on fish populations compared with streams where
ANC remains above 0 (j,eq/L. Results reported in the 2008 ISA from in situ bioassay
studies from across the eastern U.S. show that acidic episodes (with associated low pH
and elevated inorganic Al concentrations and high stream-water discharge) caused rapid
fish mortality under some conditions (Driscoll et al.. 2001b; Bulger et al.. 1999; Baker et
al.. 1996). Baker et al. (1990a) concluded that episodes are most likely to affect biota if
the episode occurs in waters with pre-episode pH above 5.5 and minimum pH during the
episode of less than 5.0. In a later study, acid episodes reduced the size of fish
populations and eliminated acid-sensitive species if median high-flow pH was less than
5.2 and inorganic Al concentration exceeded 3.7 |imol (100 (ig/L), despite the relatively
short duration of the episodes studied (Baker et al.. 1996). Research from several regions
in the U.S. indicates that acidifying deposition likely has increased the magnitude,
frequency, and biological effects of episodic acidification events.
8.3 Aquatic Organisms Impacted by Acidifying Deposition
Section 8.3.1 to Section 8.3.8 describe effects of acidification on phytoplankton,
zooplankton, benthic invertebrates, fish, birds, and other biota. Changes in biota are
linked to chemical indicators (Chapter 7) in surface water. In the 2008 ISA biological
effects were divided into two major categories: effects on health, vigor, and reproductive
success and effects on biodiversity. The first category included changes at the species
level of biological organization such as cumulative sublethal physiological effects
(individual condition factor) and recruitment success. Effects on biodiversity included
changes in community structure, species composition, and taxonomic richness. Studies
reviewed in the 2008 ISA showed earlier lifestages were particularly sensitive to
acidification.
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In Section 8.3.1 to Section 8.3.8 findings from the 2008 ISA are summarized for each
major taxonomic group followed by a review of new literature including studies that
report physiological alterations, changes in the abundance or presence of taxa,
community shifts, and other biological responses associated with acidifying conditions.
Effects on organisms at lower trophic levels, such as plankton and invertebrates, are
discussed first followed by observations in fish and other vertebrates. Ecological
thresholds of chemical indicator(s) associated with the observed responses are included,
when available, from the reviewed studies. Section 84 considers the evidence for
biological recovery in different taxa.
8.3.1 Plankton
8.3.1.1 Phytoplankton
Phytoplankton or suspended algae, play an important role in freshwater systems as
primary producers in the aquatic food web. These photosynthetic organisms
encompassing diatoms, cyanobacteria, dinoflagellates, and other groups of algae vary in
tolerance of acidic conditions. Studies reviewed in the 2008 ISA reported reduced species
richness of phytoplankton with decreases in pH and increases in inorganic A1
concentrations associated with acid-affected surface waters (U.S. EPA. 2008a'). There
was also a shift in the composition of dominant taxa, but species composition shifts could
not be accurately predicted. This effect was most prevalent in the pH 5 to 6 range (Baker
etal.. 1990a). It appeared that phytoplankton community restructured as their water
become acidified. However, the response of phytoplankton communities often vary, with
some lakes increasing other decreasing, or yet others having no change in phytoplankton
biomass (Baker etal.. 1990a). Lcavitt et al. (1999) suggested that the complex
interactions between pH, DOC, and light explain the high variability in the
phytoplankton-biomass-acidification relationship. In most lakes, acidification has a
negligible effect on primary productivity.
More recent studies of the responses of phytoplankton to changes in surface water acidity
have been limited. Lacoul et al. (2011). reviewed information on the effects of
acidification on plankton and other organisms in Atlantic Canada and observed that the
greatest changes in phytoplankton species richness occur over a pH range of 4.7 to 5.6,
just beyond the interval (pH 5.5 to 6.5) where bicarbonate becomes rapidly depleted in
the water. In acidifying conditions, phytoplankton communities shifted from dominance
by chrysophytes, other flagellates, and diatoms to larger dinoflagellates. However,
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biomass and productivity were not much affected. Algal biomass in five Pennsylvania
streams decreased with severity of episodic acidification (MacDoimall et al.. 2008).
Although no significant trends were observed for taxon richness or diversity, the degree
of acidification during episodes appeared to affect the quantity of algae in the streams.
Bloch and Wevhenmever (2012) evaluated physical and chemical time series data for
13 nutrient-poor Swedish lakes across a latitudinal gradient. Phytoplankton biomass and
species richness showed only weak relations with water chemistry. The only significant
association observed across seven of the surveyed lakes was the number of chlorophyte
taxa and changes in water temperature and color.
As stated in the 2008 ISA, diatoms, which comprise an important component of the
phytoplankton, are excellent biological indicators of environmental change in aquatic
ecosystems, being sensitive to changes in acidity, nutrient status, salinity, and climate
(Stoermer and Smol. 1999; Sullivan and Charles. 1994). Since the 2008 ISA, studies have
further linked phytoplankton community shifts to acidification using paleolimnological
analysis of fossil diatoms or long-term sampling of phytoplankton from the water
column. Most of these studies have documented phytoplankton recovery in historically
acidified lakes (Section 8.4.1). Stratigraphy of sediment chrysophyte remains in
Brooktrout Lake in the Adirondack Mountains revealed shifts in Mallomonas spp. and
Synura spp., with some species declining and others increasing. After the 1950s,
Fragilariforma acidobiontica, a diatom that is often abundant at pH <5.0, was present in
lake sediments. These observations in Brooktrout Lake correspond to historical
acidification which was most severe during the 1970s and 1980s (Sutherland et al.. 2015).
Over time, phytoplankton assemblages in Swedish lakes recovering from acidification
become more similar to reference lakes (Johnson and Angeler. 2010). In a recent analysis
of diatom fossils from 10 lakes located about 80-250 km east and northeast of the oil
sands development near Fort McMurray and Fort Mackay, northwestern Saskatchewan,
Laird etal. (2013) observed increases in scaled chrysophytes and diatom flux rates in
post-1980 sediments potentially related to atmospheric deposition from the oil sands
region. A slight decrease (0.25 pH unit) in diatom-inferred pH occurred in one study site
closest to the development, but there was no evidence of widespread acidification.
8.3.1.2 Zooplankton
Zooplankton, the animal forms of plankton, comprise many groups of freshwater
unicellular and multicellar organisms including protozoans, rotifers, cladocerans, and
copepods. In studies reviewed in the 2008 ISA, decreases in ANC and pH and increases
in inorganic Al concentration were shown to contribute to the loss of zooplankton species
or decreased abundance in lakes (Keller and Gunn. 1995; Schindleret al.. 1985). A
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decrease in pH from 6 to 5 reduced species richness in zooplankton communities in lakes
(Holt et al.. 2003; Holt and Yan. 2003; Locke and Sprules. 1994). Sullivan et al. (2006a)
found that zooplankton communities varied with ANC levels in Adirondack lakes with
lower taxonomic richness (number of species of crustaceans, rotifers, and total
zooplankton) in lakes with lower ANC levels. In general, lake-water ANC explained
nearly half of the variation in total zooplankton and crustacean taxonomic richness, but
less for rotifer richness. Extremely low richness of zooplankton communities occurs
when ANC levels are below 0 (j,eq/L (15 species in highly acidic lakes compared to 35 at
the highest values of ANC in the study [near 200 |icq/L|). Observations from in situ
enclosure studies at Emerald Lake in the Sierra Nevada showed shifts in zooplankton
community with decreased pH (Barmuta et al.. 1990). Daphnia rosea and Diaptomus
signicauda were eliminated below pH 5.0 while other species such as Bosmina
longirostris and Keratella taurocephala become more abundant. Possible mechanisms for
zooplankton sensitivity to low pH and ANC include ion regulation failure, reduced
oxygen uptake, inability to reproduce, and Al toxicity (U.S. EPA. 2008a).
A number of studies have been conducted on the response of zooplankton to lake
acidification since the 2008 ISA. Highlighted here are several studies conducted in the
U.S. and Canada. Many of these studies indicate multiple factors could influence
zooplankton community changes. Vinebrooke et al. (2009) reported variations in
phytoplankton and zooplankton communities during a whole-lake experimental
acidification of Lake 302S in the Experimental Lakes Area in Ontario. There was a
negative effect on zooplankton species richness as pH decreased from 6.8 to 4.5.
However, no correlation was found between functional properties (productivity or net
total biomass) and species richness with this pH change, indicating other factors such as
multiple stressor interactions, species occurrences, and altered trophic interactions might
also influence zooplankton community change. In northwest boreal shield lakes
downwind of N emissions from the Athabasca oil sands extraction in Saskatchewan,
Canada, zooplankton community structure was influenced by local environmental factors,
including acidity, predation, and lake productivity. The role of regional atmospheric
deposition on zooplankton community composition could not be distinguished from
natural variability due to a lack of baseline data prior to oil extraction operations (Anas et
al.. 2014). Thus, the role of acidic deposition in driving changes in zooplankton
community composition was not clear.
Acidification often reduces Ca availability in lake water, which may impact invertebrates
that require Ca for growth such as Daphnia spp. and crayfish (Section 8.4.3). Jeziorski et
al. (2012b) examined the growth and survival of daphnid species across a Ca gradient in
central Ontario soft-water lakes (from 50 to 150 (ieq/L). Considerable variability in
growth and survival was observed within the Daphnia pulex species complex, and the
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variation across the entire cladoceran genera was best explained by pH and lake depth.
This research adds support to the previous observation that among the cladocerans,
daphnids are especially sensitive to decreases in Ca which leads to declines in their
growth and survival as lake water acidifies with inputs of acidifying deposition.
8.3.2 Periphyton
Periphyton mats are biofilms of algae, cyanobacteria, fungi, microinvertebrates, organic
detritus, inorganic particles, and heterotrophic microbes imbedded within a matrix and
attached to submerged substrates in aquatic systems (e.g., stream or lake bottoms).
Periphyton is an important food source for invertebrates, tadpoles, and some fish. As
reported in the 2008 ISA acidification impacts periphyton species differently, with some
being excluded from impacted water bodies while others become dominant, which
decreases species richness and alters community structure (U.S. EPA. 2008a'). For
example, many of the brown algae and blue-green bacterial periphyton species cannot
tolerate acidic conditions, causing their abundance to decline along with pH, while green
algae, particularly the filamentous Zygnemataceae, increase in relative abundance at
lower pH (Baker et al.. 1990a). Unlike for phytoplankton, there is evidence that the
biomass of attached periphyton increases at lower pH. No new studies of acidifying
effects on periphyton were identified for this review.
8.3.3 Benthic Invertebrates
Benthic invertebrates live in freshwater sediments and include groups such as bivalves,
worms, gastropods and insect larvae. As reviewed in the 2008 ISA, acidification as
measured by decreases in ANC and pH and increases in inorganic Al concentration has
been shown to contribute to the loss or decline in abundance of benthic invertebrate
species in streams. The Ephemeroptera (mayflies)-Plecoptera (stoneflies)-Tricoptera
(caddisflies; EPT) Index is a common measure of stream macroinvertebrate community
integrity. The EPT metric is the total number of families present in those three insect
orders. Mayflies tend to be the most sensitive of the three, and stoneflies tend to be the
least sensitive (Peterson and Van Eeckhaute. 1992). The mayfly order is often selected
for study because it includes a number of genera and species having varying degrees of
sensitivity to acidification, including some that are highly sensitive (Sullivan et al.. 2003).
Typically, pH values below 5 result in the virtual elimination of all mayflies along with
other aquatic organisms from some streams (U.S. EPA. 2008a; Baker and Christensen.
1991). These benthic invertebrates are impacted by acidification because H+ and Al can
be directly toxic, causing disruption of their ion regulation, and reproductive success.
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Work since the 2008 ISA by Baldigo et al. (2009) assessed effects of acidification on
benthic macroinvertebrate community dynamics in the southwestern Adirondack
Mountains. Water chemistry and benthic macroinvertebrates were surveyed in 36 streams
with different level of acidity to characterize community response and identify thresholds
of biological effects Figure 8-1). In the study streams, macroinvertebrate assemblages
were severely impacted at pH <5.1, moderately impacted at pH from 5.1 to 5.7, slightly
impacted at pH from 5.7 to 6.4 and usually unaffected above pH 6.4. Inorganic Al
concentrations reached potentially toxic levels in two-thirds of the study streams. The
authors developed a new index (Acid Biological Assessment Profile [acidBAP]) based on
percent mayfly richness and percent acid-tolerant macroinvertebrate taxa. This index was
strongly correlated with pH, ANC, BCS, and the concentration of inorganic Al, indicating
the loss of mayflies in the stream as the surface waters pH declines from pH 7.0 to 4.2. A
loss of about 12 total species occurred between streams with a pH of 7 and 4.2, and
regression across all 36 streams shows a loss of 4.6 species per unit pH (Figure 8-1).
Inorganic Al toxicity is likely the cause of the loss of macroinvertebrates and Al
concentration is strongly correlated to surface water pH and acid-base balanced as
measured by BCS.
Several pH thresholds for aquatic invertebrate response have been published since the
2008 ISA (Table 8-1). Lacoul et al. (2011) reviewed available information on the effects
of water acidification on aquatic organisms in Atlantic Canada. The median pH for
sensitive invertebrate species occurrence was between 5.2 and 6.1, below which species
are absent. For example, several species of Ephemeroptera and most gastropods are
intolerant of acidity and only occur at pH >5.5 and >6, respectively. In six humic (mean
total organic carbon [TOC] 10-18 mg/L) streams in central Sweden, Andren and
Wiklund (2013) evaluated acute and sublethal toxicity of macroinvertebrate salmonid
prey items exposed to episodes of acidity during spring snowmelt. The threshold for
mortality was pH <5.7 and inorganic Al >20 (ig/L for mayflies (Baetis rhodani) and
pH <6.0 and inorganic Al >15 (ig/L for the freshwater amphipod Gammarus pulex.
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non-impacted
slight impact •
• •
moderate impact
O 10
severe impact
4.0
4.5
5.0
5.5
6.0
6.5
7.0
7.5
Median pH
Source: Modified from Baldiqo et al. (2009).
Figure 8-1 Total macroinvertebrate species (community) richness as a
function of median pH in 36 streams sampled in the western
Adirondack Mountains of New York, 2003-2005; the four standard
(New York State) impact categories for species richness are
defined.
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Table 8-1 Thresholds of biological response to changes in water acidity in
benthic invertebrates published since the 2008 Integrated Science
Assessment for Oxides of Nitrogen and Sulfur-Ecological Criteria.
Life Forms Region
Potential
Thresholds
Reference
Sensitive invertebrates Atlantic Canada
present
pH 5.2 to 6.1
Lacoul et al. (2011)
Littoral macroinvertebrates Northern Europe
pH 5.8 to 6.5
Schartau et al. (2008)
Stream macroinvertebrates Southwestern Adirondacks
Mountains
pH 5.1 to 5.7
Baldiao etal. (2009)
Stream macroinvertebrates Sweden
pH 5.7 to 6.0
(Andren and Wiklund, 2013)
Several European studies published since the 2008 ISA have evaluated the use of benthic
invertebrates as a biological metric to classify the ecological status of water bodies. These
studies have developed or applied indices to predict the dose-response relationship
between macroinvertebrate communities and water chemistry. One study by Schartau et
al. (2008) applied existing macroinvertebrate metrics developed for river acidification to
lakes and also developed and tested new species-based indicators of lake acidification
based on 668 samples of littoral macroinvertebrates taken from 427 lakes across Sweden,
the U.K., and Norway. Although there was high variation in the data, a response
threshold between pH 5.8 and 6.5 was identified for littoral macroinvertebrate
communities suggesting they could be used to assess ecological quality of lakes. Using
macroinvertebrate monitoring data (1,462 samples) from Northern Europe Moe et al.
(2010) tested new and existing acidification metrics with the aim of selecting a common
metric to assess pH effects on biota in this region. Most investigated metrics responded to
pH, with most of the variance explained by a few variables, including the number of
Ephemeroptera families and the proportion of sensitive Ephemeroptera. Most biological
metrics were higher (less impacted) in humic than in clear waters, suggesting smaller
acidification effects in humic waters. Murphy et al. (2013) described an approach for
developing diagnostic indices for assessing acidity in British streams that could be useful
in the U.S. Variation in macroinvertebrate assemblages in 76 test sites was quantified
with a 197-site calibration set. The Acid Water Indicator Community Index expressed at
the species level was related to base-flow pH and to storm-flow pH and ANC, accounting
for 38 to 56% of the variation in acid condition.
Traister et al. (2013) investigated shifts in macroinvertebrate communities and food webs
in nine small forested streams in the Czech Republic across a pH gradient from 4.0 to 7.7.
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Acidification was related to reduced taxon richness and reduced Ephemeroptera family
richness and lower population densities.
8.3.4 Bacteria, Macrophytes, and Bryophytes
At the time of the 2008 ISA, most observations of biological effects of acidification were
in phytoplankton (Section 8.3.1.1). benthic invertebrates (Section 8.3.3). and fish
(Section 8.3.6). and relatively little information was available regarding the response of
other biological taxato surface water acidification. This has not changed appreciably. A
few studies have been conducted on bacteria, macrophytes, and bryophytes, as described
below.
Percent et al. (2008) assessed bacterioplankton community diversity and structure in
18 Adirondack lakes across a range of acid-base chemistry using sequencing and
amplified ribosomal DNA restriction analysis of constructed rRNA gene libraries. Based
on principal components analysis, pH was positively correlated with bacterioplankton
community richness and diversity. Several bacterial classes, including
Alphaproteobacteria, were directly correlated with pH. However, other environmental
factors, such as lake depth, hydraulic retention time, dissolved inorganic C, and nonlabile
(organically bound) monomeric Al, were also important in explaining bacterioplankton
community richness and diversity, indicating that acidity is only one factor in controlling
community composition.
Studies that look at macrophytes provide additional information on the biological
responses to acidic conditions. For example, a pH threshold for the absence of sensitive
macrophytes was determined to be 5.5 in Atlantic Canada lakes by Lacoul et al. (2011).
In addition, Pulido et al. (2012). examined the health and survival of isoetid macrophytes
under different conditions of alkalinity and SO42 concentration. Changes in the
concentration of surface water SO42 and alkalinity can stimulate mineralization in lake
sediments, contributing to anoxic lake conditions. This can have adverse impacts on the
health and survival of isoetid macrophytes, including Lobelia dortmanna, a flowering
plant occurring in shallow waters. Pulido et al. (2012) exposed this species to elevated
alkalinity and a combination of elevated alkalinity and SO42 concentrations in aquaria.
At the end of 3 months, the combination of SO42 and alkalinity significantly increased
macrophyte mortality, lowered areal biomass, and reduced photosynthetic efficiency.
In an analysis of factors affecting distribution of aquatic macrophytes in lakes in the
Pyrenees Mountains of southern Europe, Pulido et al. (2015) constructed statistical
models to predict optimum ranges and ecological niches of 11 aquatic macrophyte
species. Macrophytes were most suited to lakes with low water concentrations of NO,
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and SO42 in vegetated watersheds at low elevations. It was possible to delineate
individual species ranges along gradients of specific conductance and water pH.
Bryophytes, most notably mosses and liverworts, are nonvascular plants that are often an
important component of the biodiversity and productivity in low-order streams. Tessler et
al. (2014) assessed bryophyte assemblages in southeastern New York streams and found
that some species like Hygrohypnum eygyrium and Codriophorus aduncoides were
generalists and able to tolerate pH in a range from approximately 4 to 7, while others
were limited by pH. For example, H. ochraceum occurred only at circumneutral pH of
around 6.5, while Andreaea rothii was restricted to low pH values of <5. Stream pH and
amount of bedrock substrate were identified in this study as the primary determinates of
byrophyte assemblage composition.
8.3.5 Amphibians
Amphibians such as frogs, newts, toads and salamanders have an aquatic lifestage and
may be in contact with acidified waters in areas affected by acidifying deposition. In the
2008 ISA, there was no evidence to suggest that acidic deposition is a factor that impacts
the health and abundance of amphibian communities (U.S. EPA. 2008a). There are both
acid-sensitive and acid-tolerant amphibians. Examples of acid-sensitive amphibians in
Baker et al. (1990a) include the spotted salamander (Ambystoma maculatum) and
Jefferson salamander (Ambystoma jeffersonianum). Jefferson salamanders were absent
from ponds with pH values <4.5 (Freda and Dunson. 1986). Based on transplant studies
into ponds or to the laboratory, embryos of this species did not hatch in water with pH
less than about 4.5. Acid-tolerant embryos such as the Pine Barrens treefrog (Hyla
andersoni) may hatch at a pH of 3.7 (Freda and Dunson. 1986). Toxicity is not solely a
matter of pH, but is also influenced by Ca2+, inorganic Al, and DOC concentrations,
lifestage, and water temperature (Baker et al.. 1990a). Large-scale amphibian extinctions
in any geographic region due to acidifying deposition have not been detected (Baker et
al.. 1990a).
Studies published since the 2008 ISA continue to indicate that amphibian species are
relatively tolerant of acidifying conditions. In a review of toxicity data from amphibian
species found in Atlantic Canada, Lacoul et al. (2011) indicated that some amphibians
can survive even to pH 3.5 to 4.0. Chambers et al. (2013) explored the relationship
between pH and hormonal response in salamanders. In their field studies with Jefferson
salamander larvae from eight natural breeding populations and a mesocosm experiment
with varying pH, they observed an increase in baseline corticosterone concentration with
lower pH (in the range of 5 to 5.8). Elevation of baseline corticosterone level is a
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physiological alteration associated with stress response. In contrast, no significant
relationship was observed between corticosterone and pH in adult Allegheny Mountain
dusky salamanders (Desmognathus ochrophaeus) living in nine streams in the Central
Appalachian Ecoregion with differing pH (Woodlev et al.. 2014). Three-week laboratory
exposures with the same species showed that low pH (3.5) decreased locomotory activity
but had no effect on plasma corticosterone levels.
8.3.6 Fish
Physiological and population-level responses associated with exposure to acidified waters
have been well characterized in fish for many decades. As summarized in the NAPAP
report by Baker et al. (1990a) and studies reviewed in the 2008 ISA, fish populations in
acidified streams and lakes of Europe and North America have declined, and some have
been eliminated due to atmospheric deposition of acids and the resulting decrease in pH
and ANC and increase in inorganic Al concentrations in surface waters. By 1990, it was
well established that freshwater acidification could cause significant adverse biological
effects in fish, although the effects were not uniform across species. Summary
information from the 2008 ISA for pH, ANC, and Al and effects on fish are presented in
Section 8.3.6.1 to Section 8.3.6.5 along with new studies. In general, understanding of the
effects of acidification on fish has not changed since the 2008 ISA.
Responses among fish species and lifestages within species to pH and Al in surface
waters are markedly variable. In general, early lifestages are more sensitive to acidic
conditions than the young-of-the-year, yearlings, and adults (Baker et al.. 1990a; Johnson
et al.. 1987; Baker and Schofield. 1985). Some of the most commonly studied species are
brown trout (Salmo trutta), brook trout (Salvelinus fontinalis), and Atlantic salmon
(Salmo salar). Among these three species, Giedrem and Rosseland (2012) recently
showed substantial additive genetic variation in tolerance to acidic water, with
heritabilities (h[2]) ranging from 0.09 to 0.27 for dead-eyed-eggs (a development period
that is highly sensitive to low pH [4.7 to 5.2]).
Atlantic salmon are anadromous and they are susceptible to physiological effects of
acidification as they develop and move to different habitats. The salmon start their life
cycle in freshwater then migrate to the ocean, returning to freshwater to spawn. In rivers,
eggs hatch into fry which develop into parr. Before migrating to the ocean, parr start
developing into smolt, which are more sensitive to acidification than the parr lifestage
(Kroglund et al.. 2008; Monette and McCormick. 2008). Recent research has shown that
exposure to concentrations of inorganic Al that have no apparent effects in freshwater
may subsequently affect smolt survival in seawater. Thus, the timing of acidification
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episodes in relation to fish lifestage and migration from freshwater to seawater may
impact fish survival due to the delayed response to inorganic A1 exposure (kroalund et
al.. 2008; Kroglund et al.. 2007).
8.3.6.1 Physiological Responses to Acidification
The modes of action of biological impacts on fish from surface water acidification were
reasonably well known at the time of the 2008 ISA. Physiological disturbances to fish
exposed to acidic waters reported in the 2008 ISA include iono- and osmoregulatory
failure, acid-base regulatory failure, and respiratory and circulatory failure. These effects
can often be directly attributed to effects on gill function or structure. Al has been shown
to accumulate on the gill surface when fish are exposed to water having high inorganic Al
concentration. The primary mechanism for the toxic effects of low pH and elevated
inorganic Al on fish involves disruption of normal ion regulation at the gill surface,
resulting in increased rates of ion loss and inhibition of ion uptake (Bergman et al.. 1988;
Wood and McDonald. 1987; Lcivestad. 1982; McWilliams and Potts. 1978). The
disruption of salt and water balance causes red blood cells to rupture and blood viscosity
to increase (Driscoll et al.. 2003b'). Additional effects might include disruption of Ca
metabolism (Reader et al.. 1988; Gunn and Noakes. 1987; Peterson and Martin-
Robichaud. 1986) and loss of Ca from important binding sites in the gill epithelium,
which reduces the ability of the gill to control membrane permeability (Exlev and
Phillips. 1988; Havas. 1986; McDonald. 1983).
Newly available literature since the last review supports previous findings of effects of
acidification on fish physiology. Several in situ studies with brook trout in the Southeast
and New England provide additional information on sensitivity of different lifestages to
episodic acidification. Changes in native brook trout physiology were determined during
two acid runoff episodes in the Great Smoky Mountains National Park (Neff et al.. 2008).
Results of an in situ bioassay of whole-body sodium concentrations before and after
acidification showed that stream acidification negatively impacted native trout
physiology. Loss of whole-body sodium when stream pH dropped below 5.1 indicated
that trout lost the ability to osmoregulate. Stream water ANC and pH decreased
episodically during the stormflow events studied. An ANC contribution analysis
indicated that acidic deposition may have been the major cause of episodic stream
acidification; increased concentrations of organic acid anions and base cation dilution
also appeared to be important. Subsequently, Neff et al. (2009) investigated the effects of
hydrologic episodes on loss of blood plasma Na+ in native southern brook trout, a
response associated with physiological stress from acid exposure. In situ bioassays were
conducted at three sites during a two-year period. Whole-body Na+ concentrations
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decreased by 10 to 20% following acidic episodes during which 24-hour mean pH values
of 4.88, 5.09, and 4.87 and total dissolved A1 concentration of 210, 202, and 202 (ig/L
were observed.
Several new studies of Atlantic salmon provide additional information on sensitivity of
this species to acidification during different lifestages. In a combination lab and field
study designed to establish whether smolts or parr are more sensitive to short-term
acid/Al pulses, Monette and McCormick (2008) observed that compared with control
fish, smolts exposed to elevated acid/Al levels showed greater losses of blood plasma CI"
(9-14 mM) after 2 and 6 days and increases in plasma Cortisol (4.3-fold) and glucose
(2.9-fold) levels after 6 days of exposure, while parr were not affected. Gill Na+/
K+-ATPase (NKA) activity was not affected in either lifestage. Smolts were shown to be
more sensitive than parr to short-term acid/Al exposure although gill accumulation of A1
was observed in both lifestages.
McCormick et al. (2009) determined the effects of pH and A1 on survival, development
of smolts, ion regulation, and stress levels of salmon in southern Vermont. Two 6-day
field studies during the peak of smolt development (late April and early May) were
conducted in five streams having different acid-base chemistry. The researchers found
increased mortality, loss of blood plasma chloride (Cl~), altered NKA activity in the gills,
and higher gill Al in fish that were caged in streams that experienced low pH (5.4-5.6)
and high inorganic Al concentration (50-80 j^ig/L). Fish confined at sites that were less
impacted by acidification showed more moderate decrease in blood plasma Cl~ and more
moderate increase in plasma Cortisol, glucose, and gill Al.
Individual Atlantic salmon physiological responses were strongly inter-correlated, with a
single principal component axis (PCI) that comprised Cortisol, glucose, chloride, and
NKA accounting for 90% of the total variation in the physiological response variables
data set (McCormick et al.. 2009). The authors suggested that physiological impairment
was the most appropriate interpretation of PCI. In a stepwise linear regression model
using water chemistry variables only, PCI scores were best explained by low pH
(r2 = 0.53). McCormick et al. (2009) found that a third-order polynomial fitted the
relationship between pH and PCI best, with r2 = 0.80 (Figure 8-2a). Gill Al also was a
strong predictor of physiological impairment and explained 81% of the variation in PCI
scores across sites (Figure 8-2b).
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O Hoc*
O Wardabom
O Winhall
• Middle rial
# Upper 3al
Al = aluminum; PC = principal component.
Notes: The physiological response factor includes plasma chloride, Cortisol, glucose, and gill Na+/K+ - ATPase activity. The line in
panel (a) is a third-order regression (t2 = 0.80) and in panel (b) is a linear regression (t2 = 0.81).
Source: McCormick et al. (2009).
Figure 8-2 Relationship between pH (a) or gill aluminum (b) and
physiological response factor of Atlantic salmon (Salmo salar)
smolts in five study sites and two trials.
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Recent studies in salmon have examined A1 toxicity following transfer to seawater to
simulate the physiological changes associated with migration to the marine environment.
In an exposure to high acidity and inorganic A1 followed by 24-hour seawater exposure,
blood plasma Cl~ levels were higher than controls, suggesting reduced seawater tolerance
(Monette et al.. 2008). Loss of seawater tolerance was accompanied by lower levels of
gill NKA activity. Exposure to acidity and inorganic Al also caused decreased plasma
insulin-like growth factor (IGF-I) and levels of 3, 3', 5'-triiodo-L-thyronine (T-3).
Results of this research suggest that smolt development and seawater tolerance can be
affected by exposure to high acidity and inorganic Al despite an absence of detectable
impacts on blood plasma ion regulation in freshwater. In 2 and 5 day Al/acid exposures
followed by a seawater challenge test. Monette et al. (2010). showed that in Atlantic
salmon smolt seawater tolerance is reduced by prior acute exposure to acidic conditions
and low levels of Al, and that the mechanisms of blood ion regulation depend on the
extent and duration of Al exposure. In both seawater and freshwater, exposure to pH 5.3
and moderate Al levels led to accumulation of gill Al, alterations in gill morphology,
reduced gill NKA activity, and impaired ion regulation. In contrast, gill Al accumulation
was decreased, with only slight effects on gill morphology in smolts exposed to acidic
conditions and the lowest level of Al concentration.
Sockeye salmon fry were raised in freshwater for 126 days under sublethal conditions of
low pH (4.8-6.8) by Kennedy and Picard (2012). Effects on growth, stress, and seawater
tolerance were determined after smoltification. At the lower pH site (5.0), fish gained
significantly less mass (average 46% of control [pH 6.8] values), exhibited lower
condition factor, and showed lower liver somatic index values than control fish. The
concentrations of liver glycogen (49% of control values) and whole-body lipids (65% of
control values) were also significantly lower. Acid exposure caused increased stress, as
measured by increased concentrations of blood plasma Cortisol. Fish exposed to pH 5.0 in
freshwater for 30 days, and then challenged with seawater, exhibited 14% higher
mortality on average compared to control fish. They also showed osmoregulatory stress
(increased blood plasma Na+ and CI" concentrations) and lower critical swimming speed
(22% reductions compared to control fish). Results suggested that sockeye salmon are
acid sensitive and do not acclimate to low pH under chronic exposure conditions. This
sensitivity could decrease the probability of fish surviving after moving to the marine
environment.
In a synthesis of bioassay study results with Atlantic salmon in Norway, gill Al
concentration was significantly correlated to inorganic Al and ANC IFimirc 8-3;
(Kroglund et al.. 2008)1. The same authors analyzed seawater challenge tests and
reported a relationship between plasma Cl~ and mortality, indicating that the fish had
impaired hypo-osmoregulatory capacity due to inorganic Al exposure in freshwater.
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LAI
Ali
1000
750
a 500
u
250
0
0
25
50
75
100
ANC.peq L
Ali; smolt • Seasirv * Ali; parr
500
¦o 400
300
D»
200
y = 5x + 8
R1- 0.748
>•
100
Cationic Al: pg L
A! = aluminum; Al = inorganic monomeric aluminum; ANC = acid neutralizing capacity; dw = dry weight; g = gram; L = liter;
Lai = labile aluminum; |jg = microgram; seasurv = seawater survival.
Notes: Linear relationships are entered into the graphs whenever significant.
Source: Kroalund et al. (2008).
Figure 8-3 Relationship between (a) cationic aluminum (labile aluminum and
inorganic monomeric aluminum) and gill aluminum for parr and
smolt. (b) Relationship between acid neutralizing capacity and gill
aluminum.
To assess the ability of Atlantic salmon smolts to recover from acid/Al exposure, Nil sen
et al. (2013) subjected salmon for 2- and 7-day periods to low pH (5.7) and inorganic Al
(40 Lig/L). Fish were subsequently transferred to good quality water (control exposure;
pH 6.8; inorganic Al <14 j^ig/L). Accumulations of Al on fish gills measured after 2 and
7 days of acid/Al exposure were 35.3 ± 14.1 and 26.6 ± 11.8 (.ig/g (dry weight),
respectively. High gill Al decreased 2 days after moving exposed fish to control water,
but were still higher than under sustained control conditions (5-10 (.ig/L inorganic Al)
over the following 2 week period. Decreases in blood plasma Na+ levels were also
observed in both test groups and remained significantly lower than in control fish for the
2-week period after transferring fish to control water. Blood plasma Ck levels in smolts
exposed for 7 days were significantly lower than in control smolts and then remained low
in both treatments following transfer to control water. Treated smolts maintained high
blood plasma glucose levels, indicative of increased stress, after being transferred to
control water and for more than a week following exposure.
Responses of Atlantic salmon smolts to episodic pH fluctuations were assessed during
in situ experiments in rivers and streams in eastern Maine (Liebich et al . 2011). Altered
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plasma chloride and plasma glucose in Atlantic salmon smolts were strongly correlated
with pH, consistent with the laboratory findings of Monette and McCormick (2008) and
others. High DOC concentrations in streams could reduce the inorganic A1 impact by
enhancing complexation with organic ligands. However under certain episodic conditions
in eastern Maine rivers, blood plasma ions in smolts can be affected (Liebich et al..
2011V
Recently, gill Al and NKA activity was assessed in smolts migrating downstream in New
England (Kelly et al.. 2015). Smolt immigrating from the Connecticut River, where most
tributaries were well buffered, had low levels of gill Al and high levels of NKA activity.
In the Merrimack River watershed, where most tributaries are characterized by low pH
and high inorganic Al concentrations salmon smolt immigrating downstream showed
higher gill Al and lower gill NKA activity. Stocked salmon return rates are lower in the
Merrimack River watershed, and the authors suggested that episodic acidification could
be affecting salmon smolts in poorly buffered streams in New England.
8.3.6.2 Fish and pH Thresholds
The detrimental effects on fish associated with pH are closely tied to ANC
(Section 8.3.6.3) and Al [Section 8.3.6.4; (Driscoll et al.. 2001b)l. In the 2008 ISA, pH
effects on fish were well characterized. A pH range of 5.0 to 5.5 has been found to cause
the absence of several fish species (Haines and Baker. 1986). Among lakes with fish,
there was an unambiguous relationship between the number of fish species and lake pH,
ranging from about one species per lake for lakes having pH less than 4.5 to about six
species per lake for lakes having pH higher than 6.5 (Driscoll et al.. 2001b; Baker et al..
1990b). The observations from field studies of pH effects on fish are corroborated by
bioassay data (Figure 8-4). Some species and lifestages experienced significant mortality
in bioassays at relatively high pH (e.g., pH 6.0-6.5 for eggs and fry of striped bass and
fathead minnow, McCormick et al.. 1989; Buckler et al.. 1987). whereas others were able
to persist at quite low pH without adverse effects. Many minnows and dace (Cyprinidae)
are highly sensitive to acidity, but some common game species such as brook trout,
largemouth bass, and smallmouth bass are less sensitive (threshold effects at pH <5.0 to
near 5.5). In many Appalachian Mountain streams that have been acidified by acidic
deposition, brook trout is the last species to disappear; it is generally lost at pH near 5.0
(MacAvov and Bulger. 1995). which usually corresponds in these streams with ANC near
0 (ieq/L (Sullivan et al.. 2003). While brook trout and other fish species may be absent at
a pH of <5.0, detrimental effects on population size and density may occur at higher pH
values (Baker et al.. 1990a; Baker and Schofield. 1985).
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Critical pH Ranges of Fish
Central mudrninnow
YeBow perch
Brown bullhead
Pumpkir»s&ec!
Largemouth bass
Northern pike
Brook, troul
White sucker
Rock bass
Golden sinner
Arctic char
Atiantic sal men
Brown trout
Creek chub
Rainbow trout
Smalfmouth trass
Lake trout
Walleye
N rehellied dace
Slimy Bculpm
! Common shirwr
Fattiead minnow
Blackness dace
Blurtnose minnow
Biadtnosa shiner
4.0
}.o
6.0
pH
7.0
Safe range, no acid-related effects occur
Uncertain range, acid related effects may occur
> Critical range, acid-related offsets likely
Notes: Baker and Christensen (1991 generally defined bioassay thresholds as statistically significant increases in mortality or by
survival rates less than 50% of survival rates in control waters. For field surveys, values reported represent pH levels consistently
associated with population absence or loss.
Source: Fenn et al. (2011b) based on Baker and Christensen (1991).
Figure 8-4 Critical aquatic pH ranges for fish species.
1 Studies in the Adirondack Mountains reviewed in the 2008 ISA demonstrated the effect
2 of acidification on fish species richness. Of the 53 fish species recorded in Adirondack
3 lakes, about half (26 species) were absent from lakes with pH below 6.0. Those
4 26 species included important recreational species plus ecologically important minnows
5 that serve as forage for sport fish (Baker etal.. 1990b). There is often a positive
6 relationship between pH and number of fish species, at least for pH values between about
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5.0 and 6.5, or ANC values between about 0 and 50 to 100 |icq/L (C'osbv et al. 2006;
Sullivan et al.. 2006a; Driscoll et al.. 2003b; Bulger etal.. 1999).
Since the 2008 review, additional pH thresholds have been published for fish species
(Table 8-2). A pH threshold of <5.9 was identified as potentially harmful to Atlantic
salmon smolts in eastern Maine (Liebich et al.. 2011). kirbv et al. (2008) show that when
streams in central Pennsylvania had pH levels below 5 because of their underlying
geology, brook trout were only in 9 of 28 streams, while all streams with pH of 6 or
greater had brook trout. This finding is consistent with previously published findings and
suggests the threshold for brook trout morality is at a pH of about 5.0.
Brown trout embryo and first-year juvenile survival in 12 streams in northern Sweden
were investigated by Serrano et al. (2008) during snowmelt using in situ bioassays. The
study streams had high DOC which causes a pH decrease, but also protects fish against
Al toxicity. High juvenile brown trout mortality was documented during the spring flood,
in association with low pH. No significant effect of inorganic Al concentration on
juvenile or embryo mortality was observed. An empirical model developed to predict
juvenile brown trout mortality in high-DOC streams suggested a critical chemical
threshold of pH in the range of 4.8-5.4. High embryo and yolk sac fry survival was
recorded, even at stream sites with pH as low as 4.0. The observed pH threshold in
DOC-rich water was lower than previously observed thresholds for low-DOC
freshwaters. First-year juveniles are likely to be most sensitive to adverse effects of low
pH in northern boreal stream ecosystems, especially during snowmelt-driven episodic pH
depressions.
Despite recent reductions in acidic deposition in northern Europe, mobilized Al remains a
threat to brown trout. Andren and Rvdin (2012) identified a threshold for healthy trout
populations by exposing yearling trout to a pH and inorganic Al gradient in humic
streams in Scandinavia. Results suggested a threshold of less than 20 (ig/L inorganic Al
and pH higher than 5.0. Toxic effects beyond these thresholds included Al accumulation
on the gills, increased hemoglobin and plasma glucose, decreased plasma chloride, and
increased mortality.
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Table 8-2 pH thresholds in fish published since the 2008 Integrated Science
Assessment for Oxides of Nitrogen and Sulfur-Ecological Criteria.
Fish Species and Effects
Region
Potential Thresholds
Reference
Atlantic salmon smolts reduction of plasma
ions
Eastern Maine
pH 5.9
Liebich et al. (2011)
Brook trout loss of whole body Na
Great Smoky
Mountains NP
pH 5.1
Neffet al. (2008)
Brook trout loss of whole-body Na of 10 to
20%
Great Smoky
Mountains NP
pH 4.9 to 5.1
Neffet al. (2009)
Juvenile brown trout mortality in high DOC
streams
Sweden
pH 4.8 to 5.4
Serrano et al. (2008)
Brown trout embryo and yolk sac fry
survival during episodes in DOC-rich lakes
Sweden
pH 4.0
Serrano et al. (2008)
Toxicity to brown trout in humic streams
Northern Europe
pH 5.0; inorganic
aluminum 20 |jg/L
Andren and Rvdin (2012)
Response of Atlantic salmon to alarm cues
after episodic exposure3
Canada
6.2
Leduc etal. (2009)
Interference of chemical alarm cues to
assess predation risk in juvenile Atlantic
salmon3
Canada
pH <6.6
Elvidae and Brown
(2014)
DOC = dissolved organic carbon; Na = sodium; NP = national park.
aBehavioral responses offish are discussed in Section 8.3.6.5. Table B-23 and Table B-24 in the 2008 ISA summarize pH
thresholds from the NAPAP report (Baker et al.. 1990a).
8.3.6.3 Fish and Acid Neutralizing Capacity Thresholds
1 ANC has been found in various studies reviewed in the 2008 ISA to be the best single
2 indicator of the biological response and health of aquatic communities in acid-sensitive
3 systems (U.S. EPA. 2008a; Sullivan et al.. 2006a'). For fish and other aquatic biota, ANC
4 is closely tied to pH effects (Section 8.3.6.2) and the bioavailability of Al
5 [Section 8.3.6.4; (Driscoll et al.. 2001 b)I. There is often a positive relationship between
6 pH and number of fish species, at least for pH values between about 5.0 and 6.5, or ANC
7 values between about 0 and 50 to 100 (.ieq/L (C'osbv et al.. 2006; Sullivan et al.. 2006a;
8 Bulger et al.. 1999). In Shenandoah National Park streams, fish species richness is lower
9 by one species on average for every 21 (j,eq/L decrease in ANC (Bulger etal.. 1999).
10 Interpretation of species richness can be difficult, however, because more species tend to
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1 occur in larger lakes and streams as compared with smaller ones, irrespective of acidity
2 (Sullivan et al.. 2003).
3 As summarized in the 2008 ISA, lakes and streams having an ANC below 0 ueq/L
4 generally do not support fish (Figure 8-5). The analysis shown in this figure suggests that
5 there could be a loss of fish species with decreases in ANC below approximately 50 to
6 100 (.ieq/L (Sullivan et al.. 2006a).
Acute
-200
-100
100 200
ANC (peq/L)
300
400
500
ANC = acid neutralizing capacity; L = liter; |jeq = microequivalent..
Notes: The data are presented as the mean (filled circles) of species richness within 10 peq/L ANC categories, based on data
collected by the Adirondacks Lakes Survey Corporation.
Source: Modified from Sullivan et al. (2006a).
Figure 8-5 Number of fish species per lake verses acidity status, expressed
as acid neutralizing capacity, for Adirondack lakes.
7 Various ecological effect criteria, including effects on fish communities, have been used
8 to classify ranges of ANC values (Table 8-3). The utility of these criteria lies in the
9 association between ANC and the surface water constituents that directly contribute to or
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ameliorate acidity-related stress, in particular pH, Ca2+, and inorganic A1 concentration.
Bulger et al. (2000) developed ANC thresholds for brook trout response to acidification
in forested headwater catchments in western Virginia. Across the eastern U.S., brook
trout are often selected as a biological indicator of acidification for aquatic biota because
they are native to many eastern streams and lakes and because residents place great
recreational and aesthetic value on this species. Note that because brook trout are
comparatively acid tolerant, adverse effects on many other fish species would be
expected at higher ANC values. Chronic ANC greater than about 50 (ieq/L is generally
considered suitable for brook trout in southeastern U.S. streams. Such streams have
sufficient buffering capacity to prevent persistent acidification from posing a threat to this
species, and there is little likelihood of lethal storm-induced acidic episodes. In such
streams, reproducing brook trout populations are expected if the habitat is otherwise
suitable (Bulger et al.. 2000). although some streams may periodically experience
episodic chemistry that affects species more sensitive than brook trout. Streams having
annual average ANC from 20 to 50 j^ieq/L may or may not experience episodic
acidification during storms that can be lethal to brook trout, as well as other fish (Bulger
et al.. 2000). Streams that are designated as episodically acidic (chronic ANC from 0 to
20 (ieq/L) are considered marginal for brook trout because acidic episodes are likely
(Hveret al.. 1995). although the frequency and magnitude of episodes vary. Streams that
are chronically acidic (chronic ANC less than 0 j^ieq/L) are not expected to support
healthy brook trout populations (Bulger et al.. 2000).
Hesthagen et al. (2008) used a regional water chemistry database to determine critical
values of pH, ANC, and inorganic Al for survival of brown trout in 790 Norwegian lakes.
The threshold value (ANCimut) to avoid fish damage was compared with that found in a
similar study conducted in 1986. In 1995, the threshold Gran ANC value to avoid toxic
effects to fish and retain unaffected fish populations was 67 |_icq/L. compared with
20 (ieq/L in 1986. The higher ANCimm found for 1995 was attributed to lower pH and
higher inorganic Al concentration at a given ANC value in 1995 than in 1986. This, in
turn, was attributed to increases in total organic carbon in these lakes.
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Table 8-3 Expected ecological effects and concern levels in freshwater
ecosystems at various levels of acid neutralizing capacity.
Category Label
ANC level
|jeq/L
Expected Ecological Effects
Low concern
(no effect)
>100
Fish species richness may be unaffected. Reproducing brook trout populations
are expected where habitat is suitable. Zooplankton communities are unaffected
and exhibit expected diversity and distribution.
Moderate concern
(minimally
impacted)
50 to 100
Fish species richness begins to decline (sensitive species are lost from lakes).
Brook trout populations are sensitive and variable, with possible sublethal
effects. Diversity and distribution of zooplankton communities begin to decline as
species that are sensitive to acid deposition are affected.
Elevated concern
(episodically acidic)
Oto 50
Fish species richness is greatly reduced (more than half of expected species are
missing). On average, brook trout populations experience sublethal effects,
including loss of health and reproduction (fitness). During episodes of high acid
deposition, brook trout populations may die. Diversity and distribution of
zooplankton communities decline.
Acute concern
<0
Near complete loss offish populations is expected. Planktonic communities have
extremely low diversity and are dominated by acid-tolerant forms. The numbers
of individuals in plankton species that are present are greatly reduced.
ANC = acid neutralizing capacity; L = liter; |jeq = microequivalent.
Based on data from Southern Appalachian steams and from Shenandoah National Park.
Source: Fenn et al. (20116).
8.3.6.4 Fish and Aluminum Thresholds
Al has no established biological function and dissolved inorganic Al can be extremely
toxic to fish and other aquatic biota. The bioavailability of Al is strongly influenced by
ANC, pH, and concentrations of organic acids (Driscoll et al.. 2001b). In the 2008 ISA,
elevated concentrations of inorganic Al associated with acidification in surface waters
were known to affect fish populations and communities in parts of the Adirondack
Mountains of northern New York (Siminon etal.. 1993; Kretser and Gallagher. 1989;
Johnson et al.. 1987; Schofield and Driscoll. 1987; Baker and Schofield. 1982). in
acid-sensitive streams of the Catskill Mountains of southeastern New York (Charles and
Christie. 1991). and the Appalachian Mountains from Pennsylvania to Tennessee and
South Carolina (Bulger et al.. 2000; Bulger etal.. 1999; SAMAB. 1996). In one study
reviewed in the 2008 ISA, 20% mortality of caged young-of-year brook trout in poorly
buffered headwater streams in the Adirondacks was documented during a 30-day period
with a median inorganic Al concentration of 2 (imol/L [54 j^ig/L; (Baldigo et al.. 2007)1.
The authors estimated that 90% mortality would occur over 30 days, with a median
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inorganic A1 concentration of 4.0 |imol/L (108 (.ig/L). Threshold values for A1 from
Baker et al. (1990a) for various species and effects were summarized in the 2008 ISA.
These values along with additional Al thresholds for various fish species and endpoints
are listed in Table 8-4.
Since the 2008 ISA, additional Al thresholds for salmonids have been published (Table
8-4). In a synthesis of 347 short term (<14 days) exposures (in tanks fed river water or in
tanks where water quality was manipulated) of salmon parr and smolt performed between
1990 and 2003 in Norway, Kroglund et al. (2008) identified dose-response relationships
for pH, inorganic Al concentration, ANC, and gill Al and time of first fish mortality over
a 10-day exposure period (Figure 8-6). Results of smolt releases were also evaluated after
pre-exposure to moderately acidic waters. All smolt survived at pH >5.8 and inorganic Al
<200 (ig/L. For parr, mortality increased at pH <5.6 or inorganic Al >45 (ig/L. In the
same study, seawater challenge tests were analyzed where smolts were pre-exposed to
sublethal concentrations of Al in freshwater and then moved to saltwater. As freshwater
pH decreased and inorganic Al concentration increased, hypo-osmoregulatory capacity
decreased, and increased mortalities were observed. Smolt exposed to >5 to <10 (ig/L
inorganic Al in freshwater and then released into seawater had a 25 to 50% reduction in
survival based on data from a sea survival program in the River Imsa in Norway
(Kroglund et al.. 2008; Kroglund et al.. 2007).
Additional studies have characterized the role of DOC in influencing Al bioavailability
and subsequent effects on fish. In a field study of Atlantic salmon smolts in streams in
eastern Maine, observations suggested that streams with moderate to high DOC
concentrations buffered the effects associated with low pH and high total Al
concentrations (Liebich et al.. 2011). Smolts exposed to high DOC waters had lower gill
Al concentrations compared to smolts in low DOC waters having similar pH and Al
concentrations.
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Table 8-4 Threshold values of aluminum for various fish species and effects.
Type of Study
Taxa
PH
AI (Jig/L)
Observed Effect
Form of AI
Country
Reference
Field study
Brook trout
(Salvelinus
fori tin alis)
4.9
286
No survival of trout stocked into
lakes with higher total AI (even
after accounting for pH effects)
Total
U.S.
Schofield and Troinar
(1980)
Laboratory
exposure
White sucker
(Catostomus
commersoni)
5.2
200
>50% larval mortality
Total
U.S.
Baker and Schofield (1982)
Laboratory
exposure
Brown trout
(Salmo trutta)
4.5-5.4
250
>50% fry mortality
Total
-
Brown (1983)
Laboratory
exposure
Atlantic salmon
(Salmo salar)
4.9-5.0
130
Significant increase in mortality
of pre-smolts
Labile
Norway
Rosseland and Skoaheim
(1984)
Laboratory
exposure
Eel (Anguilla
anguilla)
5.1
230
Significant increase in elver
mortality
Total
Norway
Fiellheimetal. (1985)
Field mesocosm
experiment
Atlantic salmon
(Salmo salar)
5.1
75
>50% mortality of smolts
Labile
Norway
Skoaheim and Rosseland
(1986)
Field survey
Brown trout
(Salmo trutta)
-
40
Fish absent or rare in streams in
Wales and England
Labile
monomeric
Wales and England
Turnpenny et al. (1987)
Laboratory
exposure
Blueback
herring (Alosa
aestivalis)
5.5-5.6
100
>50% larval mortality
Total
U.S.
Klauda and Palmer (1987)
Whole-stream
experiment
Atlantic salmon
(Salmo salar)
and brown trout
(Salmo trutta)
5.0
350
>50% mortality of young-of-the-yr
Wales
Ormerod et al. (1987)
Laboratory
exposure
Brown trout
(Salmo trutta)
5.2
30
Significant reduction in fish
growth
-
England
Sadler and Lvnam (1988)
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Table 8-4 (Continued): Threshold values of aluminum for various fish species and effects.
Type of Study
Taxa
PH
AI (Jig/L)
Observed Effect
Form of AI
Country
Reference
Laboratory
exposure
Walleye
(Stizostedion
vitreum)
4.9
50
>50% mortality of embryos to
4-days post-hatch
Total
Canada
Holtze and Hutchinson
(1989)
Laboratory
exposure
Brook trout
(Salvelinus
fori tin alis)
5.2
29
Survival of 1-yr-olds decreased
Inorganic
monomeric
U.S.
Inaersoll et al. (1990)
Laboratory
exposure
Brook trout
(Salvelinus
fon tin alis)
4.8
34
Weight of 1-yr-olds decreased
after exposure to either pH or AI
threshold
Inorganic
monomeric
U.S.
Inaersoll et al. (1990)
Laboratory
exposure
Greenback
cutthroat trout
(Oncorhynchus
clarki stomias)
5.5
100
Decreased survival of alevins
and swim-up larvae
Total
U.S.
Woodward etal. (1991)
Laboratory
exposure
Greenback
cutthroat trout
(Oncorhynchus
clarki stomias)
5.5
100
Decreased swimming activity in
swim-up larvae and alevins
Total
U.S.
Woodward etal. (1991)
Laboratory
exposure
Greenback
cutthroat trout
(Oncorhynchus
clarki stomias)
5.0
300
Decreased survival of embryos
Total
U.S.
Woodward etal. (1991)
Laboratory
exposure
Greenback
cutthroat trout
(Oncorhynchus
clarki stomias)
5.0
300
Increased loss of Na ions in
embryos
Total
U.S.
Woodward etal. (1991)
Laboratory
exposure
Greenback
cutthroat trout
(Oncorhynchus
clarki stomias)
6.0
50
Increased loss of Na, K, and Ca
ions in alevins (compared to
treatment with same pH and
without AI)
Total
U.S.
Woodward etal. (1991)
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Table 8-4 (Continued): Threshold values of aluminum for various fish species and effects.
Type of Study
Taxa
PH
AI (Jig/L)
Observed Effect
Form of AI
Country
Reference
Laboratory
exposure
Greenback
cutthroat trout
(Oncorhynchus
clarki stomias)
6.0
50
Decreased feeding strikes in
swim-up larvae (compared to
treatment with same pH and
without AI)
Total
U.S.
Woodward etal. (1991)
Laboratory
exposure
Greenback
cutthroat trout
(Oncorhynchus
clarki stomias)
6.0
50
Decreased swimming duration in
alevins (compared to treatment
with same pH and without AI)
Total
U.S.
Woodward etal. (1991)
Field study
Blacknose dace
(Rhinichthys
atratulus)
-
101
Decreased survival of adults
when exposed to threshold for
more than 6 days
Inorganic
monomeric
U.S.
Simonin et al. (1993)
Field study
Brook trout
(Salvelinus
fon tin alis)
-
225
Juvenile mortality significantly
increased (>20%) when exposed
to AI threshold for 2 or more days
Inorganic
monomeric
U.S.
Baldiao and Murdoch
(1997)
Field study
Brook trout
(Salvelinus
fon tin alis)
54/108
Correlations between low
(54 ijg/L) and high (108 pg/L)
thresholds and low (20%) and
high (50-90%) mortality
Inorganic
monomeric
U.S.
Baldiao and Murdoch
(1997)
Laboratory
exposure
Atlantic salmon
(Salmo salar)
5.0-5.4
43-68
Ion regulation, stress physiology,
gill AI accumulation
Inorganic
U.S.
Monette and McCormick
(2008)
Laboratory
exposure
Atlantic salmon
(Salmo salar)
5.4-6.3
28-64
Ion regulation, seawater
tolerance, plasma hormone
levels, stress physiology
Inorganic
U.S.
Monette et al. (2008)
Laboratory
exposure
Atlantic salmon
(Salmo salar)
5.8
40
Smolt survival
Cationic
(inorganic
aluminum)
Norway
Kroalund et al. (2008)
Laboratory
exposure
Atlantic salmon
(Salmo salar)
5.6
45
Parr survival
Cationic
(inorganic
aluminum)
Norway
Kroalund et al. (2008)
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Table 8-4 (Continued): Threshold values of aluminum for various fish species and effects.
Type of Study
Taxa
PH
AI (Jig/L)
Observed Effect
Form of AI
Country
Reference
Field bioassay
Atlantic salmon
(Salmo salar)
5.4-5.6
50-80
Survival, smolt development, ion
homeostasis, stress
Inorganic
U.S.
McCormick et al. (2009)
In situ exposure
Brown trout
(Salmon trutta)
5.0
20
Recommended threshold to
sustain healthy populations
based on gill AI, blood physiology
Inorganic
Sweden
Andren and Rvdin (2012)
Laboratory
exposure
Atlantic salmon
(Salmo salar)
5.7
40
Gill AI accumulation
Inorganic
U.S.
Nilsen et al. (2013)
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Ł
¦e
8
<
o LAI; smolt * Ali; smolt
100
90
30
70
60
50
40
30
20
10
0
Ł)_
4.
1—* 1 * i
5 5.5
o v °
6.5
pH
o LAI: smolt • Ali; smalt
100 -i
90 -
80 -
70 •
<5
60 -
Ł
50 -
40 -
3
30 -
o
o
?0 •
<
10 ¦
0 -1
-i <5 ¦
0 ft fr
0
D
0
&
*
* &
•
it**
g
0
1
M
i i* Ą
¦50 -25 0 25
ANC, pcq L'1
50
B
Ł
€
E
3
O
y
<
100
90
80
70 -
60 -
50 -
40 -
30 -
20 -
10
0
o LAI; smolt * Ali; smalt
oo . O * ¦ <5
o
Q
0
o ;~
r.\
fPrrTTTTTTTTTTn
25 50 75 100 125
Cationic Al, |jg L"1
~ LAI; smolt * Ali; smolt
R = 0.96
y = 0.2x-72
500 1000
Gill Al, pg Al g*1 dw
Al = aluminum; Ali = inorganic monomeric aluminum; ANC = acid neutralizing capacity; dw = dry weight; g = gram; L = liter;
LAI = labile aluminum; ueq = microequivalent; (jg = microgram.
Notes: Linear relationships are entered into the graph whenever significant. The dashed lines suggest dose levels separating "no
effect," "low to high" effect, and/or always "high" effect.
Source: Kroalund et al. (2008).
Figure 8-6 Relationship between (a) pH, (b) cationic aluminum, (c) acid
neutralizing capacity and (d) gill aluminum and accumulated
mortality of smolt.
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8.3.6.5 Behavioral Responses to Acidification
New studies in salmonids have also shown effects of acidification on behavioral
endpoints. Using hatchery-reared juvenile Atlantic salmon, Elvidge and Brown (2014)
conducted a tethering experiment in reaches of neutral (pH >6.6) and low pH (<6.6)
salmon nursery streams, plus one additional stream that varied between pH classes. The
researchers observed that the tethered fish in the low-pH streams were significantly more
likely to be preyed upon than fish in the neutral streams although there were fewer
predatory fish species, similar availability of physical refugia, and similar threat from
terrestrial predators. Lcduc et al. (2009) quantified alarm behavior of juvenile Atlantic
salmon exposed to chemical alarm cues in a stream before and after rainfall. Before
rainfall, fish exhibited an alarm response in the study streams. After rainfall, fish from the
higher pH (near 7.5) stream continued to respond, but those from the lower pH (near 6.2)
stream did not. The researchers suggested that episodic acidification in small nursery
streams may disrupt the chemical information mediated by chemical alarm cues and
contribute to higher fish mortality. This may be the first published study documenting the
disruption of a chemical messenger by acidification of steam water.
8.3.7 Fish-Eating Birds
The 2008 ISA reviewed the limited studies that documented effects of acidification on
birds. Acidification has been shown to disrupt food web dynamics causing alteration to
the diet, breeding distribution, and reproduction of certain species of birds. Lacoul et al.
(2011) reviewed studies of acidification on aquatic birds and noted that in the Atlantic
Canada region breeding was limited to lakes and streams that had a pH higher than 5.5. A
substantial amount of research has recently been conducted on air pollution effects on
birds, but the focus of that work has been on mercury exposure.
8.3.8 Aquatic Assemblages
In the 2008 ISA, decreases in species richness in response to surface water acidification
were reported in lakes and streams for all major trophic levels of aquatic organisms
(Baker et al.. 1990a). even after adjusting for lake size (Matuszek and Beggs. 1988;
Schofield and Driscoll. 1987; Frenette et al.. 1986; Rago and Wiener. 1986; Harvey and
Lee. 1982). Acidification was also found to cause decreases in food web complexity
(indicated by the number of trophic links or species) in Adirondack lakes (Havens and
Carlson. 1998).
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Since the 2008 ISA, several studies have considered effects of species assemblages
associated with acid-impacted water bodies. Nierzwicki-Bauer et al. (2010) presented
baseline midsummer chemistry and community composition of phytoplankton, bacteria,
rotifers, crustaceans, macrophytes, and fish in 30 lakes of the southwestern Adirondacks
(Figure 8-7). Species richness in the lakes was correlated with acid-base chemistry at all
trophic levels except bacteria.
The decrease in number of taxa per unit pH was similar among groups and ranged from
1.75 (crustaceans) to 3.96 (macrophytes). Following the 5-year experimental acidification
of Little Rock Lake in Wisconsin from pH 6.1 to 4.7, Hogsden et al. (2009) observed
greater reductions in species richness at higher trophic levels (fish and zooplankton)
compared to algae. The authors suggested that the observed asymmetrical food web
response could have implications for biological recovery of lakes. This study was limited,
however, by the fact that the experimental acidification only involved the lake and not the
watershed. Cladoceran assemblages reconstructed by Mosscrop et al. (2015) from lake
sediment cores from 30 lakes in Ontario, Canada showed that in shallow lakes, there was
no significant difference in cladoceran taxa between present-day and preindustrial
sediments, while in deeper lakes, relative abundance of cladocerans had shifted over
time. The researchers hypothesized that cladoceran assemblages in shallower lakes might
be influenced more by habitat than by water chemistry and that Ca availability may vary
spatially in shallow lake areas, or, that cladoceran species living in littoral zones may be
less sensitive to low Ca.
In an analysis of pH effects on grazing and herbivory in 20 stream food webs across the
British Isles, considerable species differences were observed across a pH gradient from
5.0 to 8.4 (Layer et al.. 2013). Three dose-response relationships were characterized for
diatom assemblages (Figure 8-8). Macroinvertebrate taxon richness and benthic density
were plotted against stream pH for all primary consumer taxa as well as by trophic group
(shredders, herbivore-detritivores, collectors, grazers; Figure 8-9). At low pH, generalist
herbivore-detritivores dominated the primary consumer assemblage. At higher pH, they
were partially replaced by specialist grazers. The researchers concluded that the ability of
acid-tolerant herbivore-detritivores to exploit food resources and the low nutritional value
of basal resources in acidified streams might decrease recolonization by specialist grazers
in streams where chemical conditions are becoming less acidic.
February 2017
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Bacteriopiankton
$
>¦=2.4972* - 0.1353
* r
~
R!=0.(M9
~
tp " a
+ ~ ¦+
~
¦
y=l.4259*- 1.9141 —
V 1
RMJ.122
w m
4,15 475 525 575 S.I5 k 75 7,25 775
Rotifers
»
25
y=3J603x- 12.249
" R--0.6863
15
0
4 75
5.23
5.75
Macrophytes
4.25
5.25
5.75
6.75
4.75
6.25
Phyloplanklon
25
jr=3,9744x - 9.0623
~ ~
5 2J
5 75
Crustaceans
25
y-1.7529*- 3.4791
RM5.5873
20
15
10
5
0
4.25
4.75
5.25
5 75
6.25
6.75
7.25
Fish
30
20
15
10
0
425
4.75
5.75
625
725
Lake pH
Notes: The y-axis denotes number of groups (bacteria), taxa (phytoplankton) or species (rotifers, crustaceans, macrophytes, fish).
The x-axis denotes the pH range that occurred in the 30 study lakes. Note: In the bacteriopiankton graph, two regressions were run
on the basis of genera (diamonds) and classes (squares).
Source: Nierzwicki-Bauer et al. (2010).
Figure 8-7 Species richness of biotic groups in 30 Adirondack study lakes
relative to midsummer epilimnetic pH in the sample years.
February 2017
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100 -1
1
Cl
« 10 H
c
|
o
Hi
CL
CO
0
O
o
o
y=5.37x-20.3;
r2=Q. 47; F=15.84;
p= 0.001*
10U
E
o
IB
t3
10 10 -
106.
o
8
o
y=2.2*1012x-1.26*1013;
r-2=0.45; F=14.49;
p=0.001*
sr
Ł
o>
§
4 -
o
4.5
PH
M = meter; mg = milligram; no = number; S = sulfur;
Notes: Statistical significance was determined using linear regression analysis. Asterisk denotes a statistically significant result at
p < 0.05.
Source: Layer et al. (2013).
Figure 8-8 Structure of diatom assemblage in 20 streams across a pH
gradient of 4.5-8.5. (a) Species richness (logio-transformed
numbers of diatom species per stream), (b) total abundance of
diatoms (logio-transformed numbers of individuals per m2),
(c) chlorophyll a concentration (mg chlorophyll a per m2), as a
measure of algal biomass.
y=1.18x-5.13;
r-'=0.41;
F=12.33;
p=0.002*
1
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a All primary consume! taxa
4 1
0 o
%
y=0.1TnOM, r=0.30, P=7.72,
p=0.012"
C Shredders
>t0.24*-0.96, r-rfi.39, F=11.30.
p=0-0(M'
S Hetbrare-desrilivores
>te-0.05:wQ.K. r-"=0.09. F= 1J6,
p=0.19 (n.B.)
<3 ® 8
o as o
o ocd o o
ooxi o o
g Collectors
>=D.1imi.10,.r»=a.14; F=2E4:
p=0.11 (n.s.)
%
6s
o o
o
i Qrazers
>t0.26*-1 .38.^=0.43. F=13.37,
p=0002'
b All primary consumer 1axa
0
>tD.37jft-0.2, P=0.24, F=5.70.
p=0.02B"
d Shredders
y=0.94y-4.G5,1^=0.67, F=3R.)
ptO.0001" O
Ł•
'(/I
6
f Herbivore-demtrrares
y=0-06*+1.1S, C=0.01. F=0.25,
p=D.63 (n.s.)
°«;o °
o
o°°
h Collectors
O
O ° O
rvS° °
03 O
w CD
JK=0.31*K)21,/^€.15; F=3-11;
p=O.P95 (n.s.)
j Grazers
y=0.T6*-3_9.rB=0.53. F=20.00.
pcD.001"
O
O
°o
pH
ri.s. = not significant; S = sulfur.
Notes: Statistical significance was determined using linear regression analysis. Asterisk denotes a statistically significant result at
p < 0.05.
Source: Layer et al. (2013).
Figure 8-9 Macroinvertebrate community composition in 20 streams across
a pH gradient. Taxon richness (total number of primary consumer
taxa; left panel) and benthic density [number of individuals
logio(x+ 1)-transformed; right panel] plotted against stream pH,
all primary consumers (a, b), shredders (excluding Leuctridae and
Nemouridae) (c, d), herbivore-detritivores (Leuctridae and
Nemouridae) (e, f), collectors (g, h) and grazers (i, j).
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Lacoul etal. (2011) reviewed available information on the effects of water acidification
on aquatic organisms and other organisms that feed on aquatic organisms in Atlantic
Canada. The pH threshold 5.0 was critical to sensitive macrophytes.
New analytical methods have recently been developed for detecting and quantifying
ecological thresholds, such as tipping points for ANC or other acid-base chemical
parameters (Baker and King. 2010). Previous methods for designating ecological
community thresholds have been based on univariate indicators or multivariate
dimension-reduction of community structure. They tend to be insensitive to the responses
of taxa that have low occurrence frequencies or highly variable abundance. The
Threshold Indicator Taxa Analysis (TITAN) statistical tool detects changes in taxa
distributions and abundances along an environmental gradient, such as ANC for example.
It uses indicator species scores to integrate occurrence, abundance, and directionality of
taxa responses by optimizing the value of a continuous variable that partitions sample
units while maximizing taxon-specific scores. It emphasizes the relative magnitude of
change and increases the contributions of taxa that have low occurrence frequencies and
high sensitivity to the gradient. As an example, Baker and King (2010) assessed
macroinvertebrate community response to a nutrient (P) gradient using TITAN. Results
supported previous threshold estimates but with lower confidence limits. Several taxa
were shown to decline at lower levels of P concentration.
In 28 subwatersheds of the Neversink River Basin in the Catskill Mountains, New York,
Harpold et al. (2013) used a simple hydrogeomorphic model as a tool to predict impacts
of acidification on biological communities. The model, which considered watershed slope
and drainage density to estimate ANC, successfully predicted several measures of
macroinvertebrate and fish community richness.
8.4 Documentation of Biological Recovery
Biological recovery can occur only if chemical recovery (Chapter 7) is sufficient to allow
growth, survival, and reproduction of acid-sensitive plants and animals (Driscol 1 et al.
2001b). In the 2008 ISA, studies of biological recovery generally indicated that the time
required for biological recovery is uncertain and that responses in biota lag behind
chemical recovery and may take decades from the onset of chemical recovery (U.S. EPA.
2008a). Literature reviewed in the 2008 ISA suggests that macroinvertebrate populations
in streams may recover more rapidly (within approximately 3 years in response to
improved chemical conditions), relative to lake populations of zooplankton (Driscoll et
al.. 2001b; Gunn and Mills. 1998). Fish populations may recover 5 to 10 years after
zooplankton recovery. Biological recovery of previously acidified surface waters can lag
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behind chemical recovery because of factors such as limits on dispersal and
recolonization (Gray and Arnott. 2011). barriers imposed by water drainage patterns
(Jackson and Harvey. 1995). the influence of predation (Lave ret al.. 2011; McNicol et
al.. 1995). and other environmental stressors (Yan et al. 1996b; Yan et al.. 1996a; Gunn
et al.. 1995; Havas et al.. 1995; Jackson and Harvey. 1995; McNicol etal.. 1995).
Biological recovery is likely to occur in stages due to differences in acid sensitivity and
the rate of recovery of affected organisms (Driscoll et al.. 2007b). In a study reviewed in
the 2008 ISA, recovery of the zooplankton community in an experimentally acidified
lake did not retrace the same trajectory as the initial deterioration due to acidification,
indicating substantial hysteresis in recovery (Frost etal.. 2006). Biological recovery
research from the Sudbury region of Canada was highlighted in the 2008 ISA. This
region, formerly impacted by smelter operations, has been important for clearly
documenting the chemical and biological effects of S deposition as well as subsequent
recovery from acidification.
New studies in multiple trophic levels continue to support findings in the 2008 ISA that
biological recovery has lagged behind chemical recovery in many systems and that the
response may vary between taxa and water bodies. Several long-term studies in water
bodies impacted by acidification indicate that biological recovery is limited despite
significant improvements in deposition and water chemistry (Battarbee et al.. 2014;
Murphy et al.. 2014; Angeler and Johnson. 2012). while others such as Honnedaga Lake
and Brooktrout Lake in the Adirondacks show more evidence for return of biota to
preacidification levels (Sutherland et al.. 2015; Josephson et al.. 2014). In Brooktrout
Lake, biological recovery of the food web structure has been observed, in part, due to
reintroduction and reestablishment of brook trout populations in the lake. Ongoing
biological recovery cannot necessarily be expected to conclude with the return of the
biological community to preacidification conditions. This is due to factors such as
differences in the rate of recovery of aquatic organisms, permanent loss of some
acid-sensitive species, and irreversible chemical and physical alterations to aquatic
environments during acidification (NAPAP. 2011).
8.4.1 Phytoplankton Recovery
In the 2008 ISA, phytoplankton recovery from experimental acidification showed an
increase in phytoplankton species richness and diversity with increased pH. In Lake 223
in the Experimental Lakes area of Ontario, there was little increase in phytoplankton
diversity as pH changed from 5.0 to 5.8 but a strong recovery of diversity at pH above 6
(Tindlav and Kasian. 1996). In Lake 302S, profound change began at pH 5.5,
phytoplankton assemblages at pH below 5.5 resembling acidified lakes. Findlav (2003)
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reported that lakes that were previously low in pH (5.0 to 5.5) and are now above pH 6
have shifted towards phytoplankton assemblages typical of circumneutral environments.
Recent studies on responses of phytoplankton to decreased acidity have been limited.
Josephson et al. (2014) reported that observed increases in chlorophyll a and decreases in
water clarity in Honnedaga Lake, New York in recent years reflect an increase in
phytoplankton abundance in association with chemical recovery from acidification.
The 2008 ISA reported results of several paleolimnological studies that used fossil
remains of diatoms or chrysophytes in lake sediments to infer lake chemistry at discrete
time periods in the past. These studies provided valuable information regarding the extent
of historical acidification, especially in the Adirondack Mountains, by using
well-established relationships between water chemistry and diatom community structure.
The studies also provided the foundation for testing the performance of process-based
dynamic models, such as Model of Acidification of Groundwater in Catchments
(MAGIC), by comparing MAGIC hindcast simulations of water chemistry with diatom
inferences of preindustrial pH and ANC (Sullivan et al. 1990).
Since the 2008 ISA, a number of additional paleolimnological studies have been
conducted that have documented historical acidification and subsequent recovery (Table
8-5); however, most of the studies have been conducted in other countries. In one study
from the U.S., diatom shifts have been linked to historical changes in pH at Brooktrout
Lake in the Adirondacks. Fragilariforma acidobiontica, a diatom that is often abundant
at pH <5.0, was present in lake sediments deposited since the 1950s and shifts in
Mallomonas and Synura were also observed (Sutherland et al.. 2015).
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Table 8-5 Paleolimnological responses to changing lake chemistry published
since the 2008 Integrated Science Assessment for Oxides of
Nitrogen and Sulfur-Ecological Criteria.
Lake(s) Sampled/Region
Observation
Reference
Brooktrout Lake Adirondacks
Fragilariforma acidobiontica, a diatom that is often
abundant at pH <5.0, was present in lake sediments
deposited since the 1950s.
Sutherland et al. (2015)
Glasgow Lake
Nova Scotia
Based on diatoms, inferred to have acidified in response
to a peak S loading of about 14 kg S/ha/yr during the
mid-1970s.
Gerber et al. (2008)
Four sampled lakes in
Nova Scotia
Decline in Daphnia beginning in the early 20th century.
Korosi and Smol (2012)
36 small headwater lakes in
the Boreal Shield of south
central Ontario
Large declines documented in relative abundances of
Ca rich Daphnia spp. and increases in the Ca poor
species Holepium glacialis.
Jeziorski et al. (2012a)
Lakes downwind of iron
sintering plant northeast of
Wawa, Ontario
Recent cladoceran sedimentary assemblages remain in
an altered state, although lakes have returned to
circumneutral pH.
Jeziorski et al. (2013)
Low-Ca lakes (mean 2 mg/L)
from the Experimental Lakes
area, Ontario
Present-day cladoceran assemblages including
Bosmina spp. and H. glacialis differed from preindustrial
assemblages.
Jeziorski et al. (2014)
Middle Lake (limed in 1973) in
the Experimental Lakes area,
Ontario
Cladoceran assemblages have not returned to
preacidification levels, and many rare species are not
present.
Labai et al. (2014)
Two boreal lakes in the
Killarney lakes region, Ontario
recovering from acidification
Cladoceran assemblages varied little from preindustrial
times to recovery. Bosmina spp. dominated in the lakes.
Labai etal. (2015)
54 lakes in the Muskota-
Haliburton region of Ontario
Numbers of planktonic diatoms such as Cyclotella
stelligera have increased with lake DOC and warming
from 1992 to present.
Hadlev etal. (2013)
Four boreal lakes recovering
from acidification and
four minimally disturbed lakes
in Sweden
Phytoplankton and littoral assemblages in acidified lakes
become more similar to reference lakes overtime.
Differences were greatest for phytoplankton
assemblages.
Johnson and Anaeler
(2010)
Ca = calcium; DOC = dissolved organic carbon; L = liter; mg = milligrams; S = sulfur.
In a lake study from Sweden, Johnson and Angeler (2010) compared phytoplankton and
littoral assemblages in four boreal lakes recovering from acidification and four minimally
disturbed reference lakes over a two-decade period. They observed that assemblages in
the previously acidified lakes became more similar to reference lakes overtime.
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Differences were greater for phytoplankton assemblages than for invertebrate
assemblages. Biological responses were correlated with inter-annual variability in
climate, in addition to decreased water acidity. Hadlev et al. (2013) conducted a resurvey
of 54 lakes in the Muskota-Haliburton region of south-central Ontario. They documented
more recent changes in chemistry and biology for the lakes using sediment cores and
diatom transfer functions. Observed pH increases were accompanied by decreases in
acidophilic diatoms, however, diatoms were moving toward a novel assemblage rather
than the preacidification assemblage. Lake DOC concentration has increased from 1992
in the lakes Hadlev et al. (2013) sampled, as have the numbers of planktonic diatoms
such as Cyclotella stelligera commonly linked to climate warming while Ca has
decreased and land use changes have further impacted the lakes. All of these factors may
be influencing diatom assemblage recovery.
Sixteen lakes in Cape Breton Highlands National Park in Nova Scotia were assessed
through sedimentary records for historical trends in water chemistry and changes in
diatom assemblages. Only one lake (Glasgow Lake) was inferred to have acidified under
peak S deposition (about 14 kg S/ha/yr) in the 1970s (Gerber et al.. 2008). Six of the
lakes, including Glasgow Lake, were modeled using the MAGIC model. The five other
lakes that were modeled showed patterns of acidification and subsequent chemical
recovery but no evidence of acidification from the diatom analysis (Gerber et al.. 2008).
The authors suggested that the diatom approach was conservative and/or that the MAGIC
model overestimated changes in acid-base chemistry.
8.4.2 Zooplankton Recovery
Several studies reviewed in the 2008 ISA reported zooplankton recovery in response to
experimental deacidification of lakes. Zooplankton recovery was observed in
experimentally acidified Lake 223 in the Experimental Lakes region in Canada as pH
increased back to 6.1 (Mallev and Chang. 1994). A lag of 1 to 6 years was observed in
recovery of zooplankton in the experimentally acidified Little Rock Lake in Wisconsin
(Frost et al.. 2006). Locke and Sprules (1994) reported that acidification below pH 5 in
the 1970s overcame the resistance stability of the zooplankton community in Ontario
Precambrian Shield lakes. The subset of study lakes that showed pH recovery from
acidification 20 years later in 1990 also showed recovery in the stability of the
zooplankton community. Holt and Yan (2003) also noted recovery in zooplankton
community composition (based on similarity to neutral lakes) in the subset of Killarney
Park (Ontario) lakes in which the pH increased to over 6 during the 1971 to 2000 study
period. They did not, however, note any time trend of increasing species richness
between the recovering lakes and nonrecovering lakes.
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Studies published since the 2008 ISA continue to provide evidence for plankton recovery.
In Brooktrout Lake in the Adirondacks, phytoplankton, and rotifer taxonomic richness
showed substantial increases (Figure 8-10) in association with pronounced decreases in
lake SO42 . H+, and inorganic A1 concentrations (Table 8-6). In contrast, species richness
of crustaceans changed little. Sutherland et al. (2015) suggested that the absence of
crustacean recovery may have been due to the severity of the initial stress and continuing
toxic pH conditions during some seasons, and/or to a large population of predatory
Chaoborus larvae present since the early 1980s when fish were absent from the lake.
Paleolimnological evidence of zooplankton responses to changing lake chemistry
published since the 2008 ISA is summarized in Table 8-5.
Evidence from newly published studies in lakes near the former smelting complexes at
Sudbury, Ontario, Canada indicate some evidence of biological recovery although the
relative recovery due to decreasing acidification versus recovery from decreased metal
emissions is not clear. In 87 lakes around the smelter area, Valois etal. (2011) surveyed
zooplankton community structure changes related to gradients of acidification, metal
contamination, trophic status and lake depth. At pH >6.0 community composition of
copepods and cladocerans did not differ substantially from reference lakes. Recovery was
evident in lakes with pH >5.5 with decreased community richness of copepod
communities in lakes with lower pH. In the lakes around Sudbury, the survival of some
zooplankton species, especially Daphnia mendotae are limited by fish populations,
notably yellow perch [Percaflavescens; (Valois et al.. 2010)1. The relative importance of
changing acidity and metal contamination in driving the observed biological responses is
not known. Nevertheless, the results suggest that the re-establishment of the zooplankton
community in lakes recovering from acid and metal stress may require improvements in
both habitat quality and the integrity of the food web. Babin-Fenske et al. (2012) reported
results of phylogenetic analyses of freshwater amphipod (Hyalella spp.) colonization in
lakes near Sudbury, Ontario. Two major groups of Hyalella were revealed, based on
mitochondrial cytochrome c oxidase I sequences. One group was associated with
recolonization of lakes that had historically been most acidified. The second group was
associated with the more peripheral, less impacted, lakes.
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160
140
- 120
s.
1100
F:
% 80
1 60
Q
-
20
0
20
18
16
!u
112
(a)
o Midsummer Epttimnet 8 § |,
•"*"* l-J
« * *
* = 0.78
(b)
a Mid-summer SpilimneBclMA (pM H|
» Mid-summerE|*i«wt#tic(H") (litq I "!
1 •
0
40
,,
( 30
j 25
120
t 15
| 10
5
0
(C)
m l
«P. i.
!¦: "m 1
t Rl = Ł
1
X *
>-"'t 4 A
4 4
A A
* & &
i & & &
A
& & & R2 - 0 60
A
& A &.Phvfop(6jr#;tDn
* Tolas Plankton
84 86 88 90- 92 94 96 98 00 02 04 06 08 10 12
Year
H =hydrogen; IMA = inorganic monomeric aluminum; |jeq = microequivalent; |jM = micromolar; m = meter; S042 = sulfate;
yr = year.
Source: Sutherland et al. (2015).
Figure 8-10 (A) Midsummer (sulfate) concentration in the epilimnion of
Brooktrout Lake (o) and in annual wet deposition (•) at local
National Atmospheric Deposition Program/National Trends
Network Station NY52 from 1984-2012. (B) Midsummer
epilimnetic concentrations of inorganic monomeric aluminum (~)
and [hydrogen ion] (¦) in Brooktrout Lake from 1984-2012.
(C) Midsummer phytoplankton (A) and total plankton
(phytoplankton, rotifers, crustaceans) (~) species richness in
Brooktrout Lake from 1984-2012.
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Table 8-6 Midsummer values and productivity analytes in the epilimnion of
Brooktrout Lake in the Adirondack Park from the 1980s through
2010-2012a.
Analyte
(a) 1980s mean (±SD)
(b) 2010-2012 mean (±SD)
[H+] (peq/L)
8.15 (2.54)
1.30 (0.26)
ANC (peq/L)
-1.90 (10.31)
11.73 (3.77)
SCM2" (peq/L)
118.18 (9.16)
52.09 (3.88)
NOs" (peq/L)
17.06 (7.36)
7.52 (2.43)
Total P (|jg/L)
3.29 (1.80)
4.00 (2.09)
DOC (mg/L)
0.71 (0.49)
2.40 (0.46)
Ca (peq/L)
68.22 (7.56)
41.65 (12.46)
Secchi (turbidity) (m)
8.89 (1.97)
5.92 (0.66)
Chi a (|jg/L)
0.85 (0.68)
1.86 (1.04)
Reactive silica (mg/L)
3.31 (0.21)
2.39 (0.28)
Total Al (|jM/L)
19.11 (7.13)
7.52 (3.10)
Labile monomeric Al (|jM/L) [IMA]
12.17 (2.93)
1.02 (0.77)
Al = aluminum; ANC = acid neutralizing capacity; Ca = calcium; Chi a = chlorophyll a; DOC = dissolved organic carbon;
H+ = hydrogen ion; IMA = inorganic monomeric aluminum; L = liter; |jeq = microequivalent; |jg =microgram; |jM = micromolar;
m = meter; mg = milligrams; N03" = nitrate; P = phosphorus; SD = standard deviant; S042" = sulfate.
aValues presented in (a) and (b) are means (± standard deviation).The 1980s samples were collected in 1984 (three dates), 1987
(four dates), and 1988 (two dates). The values presented in (b) represent 10 sampling dates during 2010-2012.
Source: Sutherland et al. (2015).
1 In a synthesis of 21 regional surveys of zooplankton recovery in lakes affected by acidic
2 deposition in North America and Europe Gray and Arnott (2009) identified the most
3 commonly used metrics and factors limiting recovery in acid-impacted lakes. In the
4 evaluated studies, species richness, indicator species, and relative species abundances
5 were commonly assessed. At pH >6.0, recovery of zooplankton was significant, although
6 often incomplete in both North American and European lakes. In their analysis, the
7 authors identified slow chemical recovery, dispersal limitation and community resistance
8 as primary factors limiting biological recovery although the relative importance varied
9 between the lakes and regions evaluated.
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Grav et al. (2012) assessed the chemical and biological recovery of 45 previously
acidified lakes in Killarney Park, Ontario. Zooplankton data were compared for the
periods 1972-1973 and 2005. Significant increases in pH overtime were documented for
the majority of the study lakes. Species richness and diversity of many acid-damaged
lakes only increased to a minor extent. They observed differing importance of biotic and
abiotic conditions and dispersal processes in determining the relative contribution of
copepod and cladoceran zooplankton in the post-recovery community structure,
suggesting different expectations for recovery among different taxonomic groups. In a
study of zooplankton communities in four of the lakes, dispersal limitation was identified
as a factor impeding biological recovery of this group (Grav and Arnott. 201IV The
researchers observed a relatively quick return of acid-sensitive zooplankton species that
disperse from streams and the egg bank in contrast to low numbers of species that depend
on overland dispersal via wind or animals.
Several studies have focused on changes in cladoceran assemblages in response to lake
chemistry. Cladocerans require relatively large amounts of available Ca for growth and
survival, which can be reduced under acidifying conditions. In a study from Nova Scotia,
cladoceran remains from three of four sampled lakes showed a decline in Daphnia
beginning in the early 20th century that suggested limnological changes in response to
acidic deposition or increased fish predation (Korosi and Smol. 2012). Following closure
of a S emitting iron sintering plant in 1998 in the region northeast of Wawa, Ontario, pH
from three previously acidified lakes returned to circumneutral conditions due to the high
buffering capacity of the local geology. However, biological recovery has lagged behind,
with no recovery observed in cladoceran sedimentary assemblages (Jeziorski et al..
2013). Analysis of sedimentary cladoceran assemblages from low-Ca lakes
(mean < 2 mg/L) in the Experimental Lakes Area of Ontario, Canada, Jeziorski et al.
(2014) indicated differences between present-day and preindustrial cladoceran
assemblages. In Middle Lake, a lake in the Experimental Lakes area that was limed in
1973, alterations in Cladoceran assemblages were assessed in the sedimentary record
(Labai et al.. 2014). Overall, the results suggested that biological recovery has not
occurred in the lake because many rare species have not yet returned to preacidification
levels. Bosminids dominated the sedimentary cladoceran assemblage from two acidified
lakes in the Killarney lake region in Ontario, and minimal shifts were observed in the
paleolimnological record from preacidification to recovery (Labai et al.. 2015). In
contrast, cladoceran abundance in acidified lakes near Sudbury, Ontario impacted by
former smelter operations experienced greater shifts in cladoceran abundance best
explained by contamination by copper (Cu) and nickel (Ni). In an earlier study, Jeziorski
et al. (2012a) documented large declines in the relative abundances of Ca rich Daphnia
spp. and increases in the Ca poor species H. glacialis in 36 small headwater lakes in the
Boreal Shield of south central Ontario having Ca concentration <3 mg/L.
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8.4.3
Benthic Invertebrate Recovery
In the 2008 ISA, few studies reported benthic recovery in previously acidified waters.
One study by Soulsbv et al. (1995) indicated recovery in some streams in Scotland with
recent ANC increases although recovery was not observed in the most severely acidified
streams.
Since the publication of the 2008 ISA, additional studies are available that assess
recovery of benthic organisms, although most of the research has been conducted in
Canadian and European waters. In a study from the Neversink River basin in the Catskill
Mountains in New York, Burns et al. (2008b) collected water chemistry data and
surveyed macroinvertebrates, fish, and periphytic diatoms from 12 streams. This survey
was conducted in 2003 and compared with a 1987 survey in the same locations.
Differences between the two surveys were not significant overall. However, a shift
toward a less acid-tolerant macroinvertebrate community in the 2003 survey in streams in
the upper river basin that were the most acidic in 1987 suggests biological changes that
are consistent with improvement in water chemistry. Further monitoring will be needed
to determine the eventual extent of biological recovery.
Crayfish and other benthic invertebrates that require large amounts of Ca for growth may
be reduced or absent in acidified water bodies where low pH decreases Ca availability
(U.S. EPA. 2008a; Baker et al.. 1990a). Hadlev et al. (2015) studied the limnological
record of four lakes in Algonquin Park, Ontario where native populations of the crayfish
Cambarus bartonii have not recovered despite improvements in pH. Cladoceran remains
were used as a proxy for historical Ca trends. Ca levels in the lakes are currently <2 mg/L
which is below the minimum requirements for crayfish (2 to 10 mg/L). Depletion of Ca
in the soils and reduced export to lakes appear to contribute to the lack of recovery of
crayfish populations in the region.
Two studies examined the response of littoral benthic macroinvertebrate community
composition to changing water chemistry in 17 lakes recovering from acidification
located on the Precambrian Shield in eastern Canada. The first study, by Lento et al.
(2008). tracked benthic invertebrate community composition over a 14-year period
(1988-2002). In these lakes there was a strong correlation between changes in chemical
variables and shifts in benthic invertebrate communities. The rate of change in
invertebrate community composition was greatest between 1993 and 1997, which
corresponded most closely with water chemistry changes. The second study, by Lento et
al. (2012). evaluated temporal trends in 15 years of data from the same lakes. In analyses
of both single and multiple lakes, decreasing proportions of Chironomidae and increasing
proportions of Ephemeroptera, Plecoptera, and Tricoptera (quantified collectively as the
EPT Index) were observed. Six of the nine lakes that showed significant recovery trends
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in more than one benthos metric exhibited a significant decrease in Chironomidae and
concurrent increase in EPT. The results of these two studies thus suggest that the benthic
macroinvertebrate communities of these study lakes changed in response to deacidifying
changes in lake chemistry by shifting towards more acid-sensitive taxa. This response
was consistent with benthic invertebrate recovery from acidification.
In a bioassessment in the Athabasca oil sands region of Alberta, Canada, Parsons et al.
(2010) sampled 32 lakes to assess potential current impacts of pollutant emissions and
acid deposition on benthic macroinvertebrate communities. Five of the lakes were
selected from an area with modeled high deposition. All of the statistical methods used
(one sample /-tests, multivariate analysis of variance, and test site analysis) showed that
assemblages differed between test lakes and reference lakes. However, results suggested
these differences were more due to intrinsic lake physicochemical factors, such as
geology and water chemistry, than to atmospheric deposition.
Several studies conducted in Europe have also considered macroinvertebrate recovery
following ongoing chemical recovery. In one of the previously most acidified areas of
Europe, Svobodova et al. (2012) compared water chemistry and macrozoobenthos
composition of the outflows from two lakes in the Bohemian Forest. The water chemistry
is now recovering in response to reduced levels of acidic deposition. Evidence of
biological recovery was found for Lake Laka (current pH ~5.2), but not for the more
strongly acidified Lake Certovo (pH ~4.6). At the Lake Laka outflow, increasing
numbers of Ephemeroptera and Tricoptera taxa were observed. Comparable changes
were not observed at the outflow for the more strongly acidified lake.
In an analysis of a 20-year data set (1988-2008) from the Acid Waters Monitoring
Network (AWMN) in the U.K., macroinvertebrate recovery was observed in 5 of the
11 stream sites and at 5 of 12 lakes (Murphy et al.. 2014). An increase in ANC over time
was observed at all 10 sites where biological recovery was evident based on trends in the
macroinvertebrate community. An additional seven sites showed ANC recovery but no
recovery of the macroinvertebrate community. The authors attributed this observation to
differences in chemical environments and/or ecological interactions that interfere with
recovery such as food-web dynamics and predation. In another 20-year data set, Angeler
and Johnson (2012) analyzed littoral invertebrates in acidified and circumneutral lakes in
Sweden. The concentration of SO42 decreased in both acidified and circumneutral lakes
but converged in the latter part of the study. Chemical recovery was generally weak in the
acidified lakes, with pH increasing by only about 0.1 to 0.2 pH units in the study lakes.
These results from Sweden suggest that because invertebrate communities respond to
complex processes, including both local and regional factors, partial recovery of water
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chemistry from acidification is at times not accompanied by observable biological
recovery, especially as related to biodiversity.
Data from two national-scale benthic macroinvertebrate surveys, the AWMN in the U.K.
and a lakes survey in Norway, were used to compare field sampling results to predictions
of maximum species richness as a function of chemical conditions in surface waters
recovering from acidification (Stockdale et al.. 2011). In general, there was good
agreement between model predictions and observed trends in EPT taxa. Biological
recovery rates for actual and predicted species richness were generally consistent with
each other, at 1.2 to 2.0 species per decade change. However, actual recovery rates in the
AWMN lakes were less than in the rivers (0.6 vs 2.0 species per decade recovery),
whereas predicted rates were similar (1.7 vs 2.0 species per decade). At sites where there
was poorer agreement between model predictions and observations, differences in water
chemistry explained some of the observed reduction in species richness. The authors
speculated that factors not included in the model, such as biotic interactions and site
conditions, could also affect species richness.
8.4.4 Fish Recovery
Evidence for recovery of fish populations following reduction of deposition or through
liming was reported in several studies reviewed in the 2008 ISA (Gunn et al.. 1988;
Kelso and Jeffries. 1988; Beggs and Gunn. 1986; Dillon et al.. 1986; Keller and Pitblado.
1986; Raddum et al.. 1986; Hultberg and Andersson. 1982). There have been additional
studies of fish response to surface water acidification and subsequent recovery since the
2008 ISA. These studies have been conducted in both North America and Europe.
Sutherland et al. (2015) documented the reintroduction and re-establishment of a
naturalized native fish species (brook trout) in an Adirondack lake (Brooktrout Lake) in
which brook trout had previously been extirpated. The historical decline in water quality
and loss of the fishery were reconstructed from available data dating back more than a
century. Lake chemistry has improved substantially in response to decreases in acidifying
deposition since the 1980s, with pronounced decreases in midsummer epilimnetic
inorganic Al and H+ concentrations. In Brooktrout Lake, the mean ANC increased from
-2 (ieq/L during the 1980s to 12 j^icq/L during the period 2010-2012. Substantial changes
were also noted for other variables, including SO42 , H+, NO3 . DOC, and inorganic Al.
In the period from 2005-2007, brook trout were reintroduced to the lake and have
subsequently survived and successfully reproduced. In 2012, young brook trout were
observed and photographed, documenting reproduction in the lake. Other acid-impacted
lakes in the Adirondacks such as Honnedaga Lake lost acid-sensitive fish species
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between 1920 and 1960 while continuing to support brook trout (Josephson et al.. 2014).
By the late 1970s, brook trout were also considered extirpated from the lake but persisted
in tributary refuges. By 2000, brook trout had recolonized the lake coincident with
reductions in surface-water SO42 . NO3 and inorganic Al concentrations.
In addition to these studies of recolonization of lakes by brook trout where acid-base
chemical conditions are improving, new reports of shifts in fish communities in response
to acidification have been published since the 2008 ISA. Warren et al. (2008) used
historical records to document a fish community shift in the upper mainstem of Hubbard
Brook in New Hampshire corresponding to chronically acidified conditions in the 1970s.
Records indicated that there were at least three fish species in the 1960s: slimy sculpin
(Cottus cognatus), blacknose dace (Rhinichthys astratulus) and brook trout. Only brook
trout were present in surveys conducted in 2005, 2006, and 2007. In an evaluation of fish
recovery in nearly 5,000 small headwater lakes in Finland where at the end of the 1980s
populations were either diminished by acid deposition or extirpated, Rask et al. (2014)
noted recovery of perch (Perca fluviatilis), an acid-tolerant species, starting in the 1990s.
The population structure has returned to normal during the monitoring period which
ended in the mid-2000s. Little or no recovery of the acid-sensitive roach (Rutilus rutilus)
was observed over the same time period.
Recovery of fish populations in streams may be affected by habitat considerations as well
as water chemistry. Warren et al. (2010) evaluated the relative influence of stream habitat
and pH on total fish biomass in 16 streams in the northeastern U.S. Physical and chemical
factors evaluated in the study included total pool area, cover, large wood frequency, and
water temperature. Both pool area and pH were most closely correlated with prediction of
fish biomass. Physical habitat is likely more important at pH >5.7 (at low flow) and
becomes less important at lower pH when conditions are too acidic to support fish.
8.4.5 Bird Recovery
Common loon (Gavia immer) breeding success was assessed from 1982 to 2007 in
38 lakes historically impacted by deposition from smelter activities in the Sudbury,
Ontario region (Alvo. 2009). No fledglings were observed on any lakes that had pH <4.4.
In two of the lakes that were previously too acidic for loon reproduction, chicks were
observed as acid conditions improved over the duration of the study. However, it was not
clear from the results whether there is a critical pH for loon fledging survival.
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8.4.6 Mitigation
Prior to the 2008 ISA, relatively few studies were conducted in the U.S. with focus on
mitigation of harm to aquatic organisms in response to acidification. Limited lake liming
had occurred in the Adirondacks in an effort to reverse the adverse effects of water
acidification (Schofield and Keleher. 1996).
Only limited additional research has been conducted on this topic in more recent years.
However, an experimental stream and watershed liming study is currently in progress in
the Adirondacks. This work is being conducted by a group of researchers under the
coordination of the U.S. Geological Survey in Troy, NY.
In an effort to mitigate Atlantic salmon population declines in Norway due to
acidification, liming was implemented in 21 impacted rivers. Hesthagen et al. (2011)
electrofished 13 rivers 1 year before and annually for 12 years after initiation of liming.
Increases in salmon parr densities were slow, and the authors estimated that it will take
more than 20 years of liming to restore lost salmon stocks. Rivers that are stocked and
those lacking hydropower developments generally had higher fry densities and faster
increase in parr densities.
Mant et al. (2013) conducted a review and meta-analysis of the impacts of liming streams
and rivers on the biological recovery of fish and aquatic invertebrates. The meta-analysis
included studies in the UK, Norway, Sweden, U.S., and Canada. On average, liming
increased the abundance and richness of acid-sensitive invertebrates and increased fish
abundance. Nevertheless, benefits were variable and did not occur in all rivers.
8.5 Levels of Deposition at Which Effects Are Manifested
8.5.1 Most Sensitive and Most Affected Ecosystems and Regions
The characteristics of acid-sensitive ecosystems were well known and summarized in the
2008 ISA. In brief, the effects of acid deposition on aquatic systems depend largely upon
the ability of the ecosystem to neutralize additional acid inputs. For this reason, not all
environments are sensitive to acidifying deposition, but more importantly, the level of
deposition and its impacts vary across the landscape. No one level of deposition can be
used to generalize the impacts of acidifying deposition across the landscape. The
principal factor governing the sensitivity of aquatic ecosystems to acidification from
acidifying deposition is geology [particularly surficial geology; (Greaver et al.. 2012)1.
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1 Geologic formations having low base cation supply, due mainly to low weathering,
2 generally underlie the watersheds of acid-sensitive lakes and streams. Figure 8-11 is a
3 map of aquatic ecosystem sensitivity in the eastern U.S. based on underlying geology in
4 unglaciated areas and ANC in the glaciated region. Other factors contribute to the
5 sensitivity of surface waters to acidifying deposition, including topography, soil
6 chemistry and physical properties, land use and history, and hydrologic flowpath.
Class 1. Most Sensitive
Class 2. Sensitive
Class 3, Marginally Sensitive
Class 4, Not Sensitive
Source: Lovett et al. (2009).
Figure 8-11 Map of landscape sensitivity to acidic deposition for the
northeastern and Mid-Atlantic U.S. Stippled areas were not
considered.
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At an ANC of 100 |icq/L or less, acid-sensitive species may be affected I Figure 8-5;
(U.S. EPA. 2008a; Sullivan et al.. 2006a; Bulger etal.. 2000; Bulger et al.. 1999)1.
Sensitive water bodies are therefore defined as those with an ANC of 100 (j,eq/L or less.
Sensitivity increases with further decreases in ANC. In general, streams in the eastern
U.S. that are sensitive tend to be headwater streams of first- to third-order. Streams and
lakes in the western U.S. tend to be headwater systems in high elevation areas. Recent
research has not changed this understanding and has served to strengthen it (Chapter 7).
8.5.2 Extent and Distribution of Sensitive Ecosystems/Regions
The 2008 ISA summarized the extent and distribution of freshwater ecosystems sensitive
to acidifying deposition. In the U.S., surface waters that are most sensitive to
acidification based on ANC and alkalinity are largely found in the Northeast, southern
Appalachian Mountains, Florida, the Upper Midwest, and the mountainous West I Figure
8-12; (McDonnell et al.. 2014b; Greaver et al.. 2012; Campbell et al.. 2004a; Driscoll et
al.. 2001b; Baker etal.. 1990b; Omernik and Powers. 1983)1. Levels of acidifying
deposition in the West are low in most areas, acidic surface waters are rare, and the extent
of chronic surface water acidification that has occurred to date has been very limited
(Charles and Christie. 1991). Episodic acidification, however, does occur in both the East
and West at some acid-sensitive locations. These areas can be identified by critical load
maps for the U.S. based on an ANC of 50 (.ieq/L I Figure 8-13; (Blett et al.. 2014)1. A
critical load (CL) is a quantitative estimate of exposure to one or more pollutants below
which significant harmful effects on specified sensitive elements of the environment do
not occur according to present knowledge (Spranger et al.. 2004; Nilsson and Grcnnfclt.
1988). Critical loads are discussed further in Section 8.5.4.
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Surface water
ANC (jeq L~1
• <0
• 0-50
• 50-100
ANC = acid neutralizing capacity; L = liter; peq = microequivalent.
Notes: Although the actual sensitivity of a water body depends on many watershed characteristics and processes; the low ANC
areas on the map indicate where sensitive surface waters are most likely to be found.
Source: Greaver et al. (2012).
Figure 8-12 A synoptic illustration of surface water sensitivity to acid
deposition in the conterminous U.S. based on surface water
measurements of acid neutralizing capacity <100 peq/L from
water quality data since 1984.
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Lege nd
Critical Load (N+S eq ha 1 yr"') T *
1 aw
2BOO 1 • 6KH
¦I «»'
¦I 12001 - 2&XC
H 30001 - A 1W*
r
i
Legend
Critical Load (N+S eq ha ' yr ')
1-1CC0
2001 - so®
6001 -13000
| 12001 -WDOOO
| 20001 - 4 I9»
SUrtiri
•4 *V •*"
/¦i: V.r
J
I .
¦ ~ ¦ _
m mjf
if > . •
¦ J1
ha = hectare; eq = equivalent; km = kilometer; L = liter; N = nitrogen; S = sulfur; [jeq = microequivalent; yr = year.
Notes: Grids represent the average calculated critical load from all data within the 36-km x 36-km grid cell. The critical chemical
criterion used was an acid neutralizing capacity of 50 peq/L.
Source: Blett et al. (2014).
Figure 8-13 (a) Minimum critical loads of surface water acidity for nitrogen
and sulfur. Grids represent the minimum calculated critical load
from all data within the 36 x 36-km grid cell. The critical chemical
criterion used was an acid neutralizing capacity of 50 peq/L.
(b) Mean critical loads of surface water acidity. Grids represent
the average calculated critical load from all data within the
36 km x 36 km grid cell. The critical chemical criterion used was
an acid neutralizing capacity 50 peq/L.
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8.5.3 Deposition, Water Quality, and Biological Change
The biological impact of acidifying deposition is mediated through changes in water
quality that in turn impact biota. Deposition of N and S can lead to a cascade of
biogeochemical changes (Chapter 7) that may induce biological effects. It is often
difficult to separate nutrient enrichment (Chapter 9) and acidification stressors, as they
act simultaneously in some water bodies. Posch et al. (2011) argued that the application
of linked nutrient and acidity chemical criteria to support plant occurrence contributes to
an optimal N and S deposition needed to sustain a prescribed biodiversity goal.
The 2008 ISA summarized findings from several national surveys on the effects of
acidifying deposition, including the National Lakes Survey and the National Streams
Survey in the mid-1980s, the Wadeable Streams Assessment (WSA) in 2004, the U.S.
EPA Long-Term Monitoring program beginning in 1983, and the Temporally Integrated
Monitoring of Ecosystems probability surveys beginning in 1991. Results of these
surveys suggested that acidifying deposition had acidified surface waters in the
southwestern Adirondacks, New England uplands, eastern portion of the upper Midwest,
forested Mid-Atlantic highlands, and Mid-Atlantic coastal plain (U.S. EPA. 2008a').
Biological change has been extensively studied in many acid-sensitive regions identified
in Section 8.5.2. Some of the most in-depth studies of the effects of acid stress on fish
(Section 8.3.6) have been conducted in streams in Shenandoah National Park, Virginia
(C'osbv et al.. 2006) and lakes in the Adirondack Mountains, New York (Sullivan. 2015).
Effects on fish have also been documented in acid-sensitive streams of the Catskill
Mountains of southeastern New York and the Appalachian Mountains from Pennsylvania
to Tennessee and South Carolina (Bulger et al.. 2000; Bulger et al.. 1999; SAMAB. 1996;
Charles and Christie. 1991). Since the 2008 ISA. several studies have documented
biological recovery that corresponds to decreasing deposition (Section 8.4).
8.5.4 U.S. Critical Loads
The 2008 ISA documented CLs developed in the U.S. CLs for surface water in the U.S.
have been reviewed by Porter et al. (2005). Burns et al. (2008a). Pardo etal. (201 la).
NAPAP (2011). Lovett (2013). and Sullivan and Jenkins (2014). Most aquatic CL studies
conducted in the U.S. have used surface water ANC as the metric of water quality change
in response to acidifying deposition. This should not be taken as an indication that ANC
should be the only environmental predictor of harm to aquatic species on which to base
CLs. Other potentially useful variables include water pH or BCS. Either or both can be
used instead of, or in addition to, ANC.
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The initial step in developing a critical load is to define a threshold for a significantly
harmful effect. This biological change can be defined for the protection of a single
species or an entire biological community, and defining varying levels of protection for
either can be achieved through different indicators of harm. Because CLs depend on what
is being protected, any given biological community requires a set of CLs. The closely
related target load (TL) estimates the reduction needed to achieve a certain condition at a
designated future time period. As described in the 2008 ISA, there are different types of
critical loads: empirical CL, modeled steady-state CL (time invariant), and modeled
dynamic CL [change through time with a specific target date, often to the year 2100 as a
management target load; (U.S. EPA. 2008a)I. Several critical loads studies were
summarized in the 2008 ISA.
As discussed in the 2008 ISA, a useful aspect of the CL approach is the calculation of
exceedance. Knowledge of where and to what extent ambient air pollutant loads exceed
levels that are sustainable without causing ecological harm can inform vulnerability
assessments (Sullivan and Jenkins. 2014).
Since 2006, the primary forum for coordination of research on CL development in the
U.S. has been the Critical Loads of Atmospheric Deposition (CLAD) Science Committee
of the National Atmospheric Deposition Program [NADP; (Blett et al.. 2014)1. Efforts are
underway in association with CLAD to collect needed data and improve methods for CL
calculations throughout the U.S.
8.5.5 Empirical Critical Loads
An empirical CL is developed from observational spatial or temporal gradient studies or
additions of pollutants to determine the deposition load at which chemical or biological
changes (e.g., changes to foliage, lichens, soil, aquatic chemistry/biota) occur in the
environment. Empirical CLs are generally applied to sites or landscapes that are
ecologically comparable to location(s) from which CLs were determined (cf. Pardo et al..
201 la). Empirical CLs for acidification are difficult to apply to sites other than those
used in defining them and to generalize across the landscape because sensitivity to
acidification is highly spatially variable (see Section 8.5.1). A given CL for acidification
often only applies to a narrow subset of environmental conditions, in many cases only to
a single water body.
At the time of the 2008 ISA, very few empirical CLs were available for U.S. freshwater
ecosystems. Rocky Mountain National Park has been the site of research addressing the
environmental effects of N deposition. Williams and Tonnessen (2000) reported ANC in
surface water <0 j^icq/L as a result of acidifying inputs of N deposition, suggesting that
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current deposition levels are having an observable impact on catchments in the Front
Range. The authors recommended a critical load of 4.0 kg N/ha/yr to prevent episodic
freshwater acidification in alpine lakes (ANC < 0 (ieq/L). However, biological changes
were not a focus of this study.
New studies from the Western U.S. have identified additional critical loads for freshwater
systems (Table 8-7). In Moat Lake in the Sierra Nevada mountains, acidic deposition
(S042 + NO3 ) equal to about 74 eq/ha/yr was correlated with the initial decline in ANC
[observed in the lake between 1920 and 1930; (Heard et al.. 2014)1. This was taken by
the authors to be the critical load to protect against acidification for Moat Lake, but the
authors did not specify the level of acidification or how the biological community would
be protected. Diatom-reconstructed ANC of Moat Lake changed from near 100 j^ieq/L
prior to 1920 to near 60 j^ieq/L during the 1970s. Reconstructed ANC patterns were not
correlated with climate, productivity, nor NOx emissions.
Baron etal. (201 lb) estimated CLs to be about 8 kg N/ha/yr in the Northeast and
4 kg N/ha/yr in the Rocky Mountains for NO3 concentrations related to episodic
acidification. Critical loads for N deposition in California were estimated based in part on
changes in NO3 leaching in stream water, which can cause or contribute to water
acidification (Fenn et al.. 2008). The empirical CL and the CL simulated by the DayCent
model for NO3 leaching were both 17 kg N/ha/yr. Nitrogen deposition exceeds that level
at some locations in California.
8.5.6 Modeled Critical Loads
Steady-state and dynamic models are used to quantify relationships between deposition
and biogeochemistry for watersheds in order to develop CL estimates (see description of
models in Chapter 7). New studies on modeled CLs for aquatic acidification are
summarized in Table 8-8.
8.5.6.1 Steady-State Critical Loads
Steady-state CLs are derived from mathematical mass-balance models under assumed or
modeled equilibrium conditions. The models used to derive steady-state CLs vary in
complexity with regard to process representation. However, a fundamental linkage
among the various modeling approaches is the solution of elemental mass balances. To
simulate the dynamic aspects of damage and recovery, a dynamic model of
hydrogeochemical processes is required.
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Table 8-7 Recent empirical critical loads to protect against aquatic acidification
in U.S. ecosystems.
Ecosystem
Site
Critical Load for N
Deposition
Response
Comments
Study
Alpine lakes
Central
Rockies/Colorado
Front Range
4.0 kg N/ha/yr
Episodic
freshwater
acidification
Survey
Williams and
Tonnessen (2000)
Mediterranean
California
stream water
California
17 kg N/ha/yr
Changes in NO3"
leaching in
stream water
Fenn et al. (2008)
High elevation
lakes
West and
Northeast
8 kg N/ha/yr
(Northeast)
4 kg N/ha/yr (West)
Episodic
freshwater
acidification
Baron et al. (2011b)
High elevation
lakes
Sierra Nevada
74 eq/ha/yr
Lake
acidification
ANC
Heard et al. (2014)
ANC = acid neutralizing capacity; eq = equivalent; ha = hectare; kg = kilograms N = nitrogen; N03 = nitrate; yr = year.
NAPAP (2011) calculated steady-state aquatic critical loads to protect southern
Appalachian Mountain streams and Adirondack Mountain lakes against the combined
load of S and N deposition below which the ANC level would still support healthy
aquatic ecosystems. Research studies have shown that surface water with ANC values
greater than 50 |icq/L tends to protect most fish (e.g., brook trout) and other aquatic
organisms [see Table 8-3. which describes these changes; (Driscoll et al.. 2001 b)I. In this
case, the CL represented the combined deposition load of S and N to which a stream and
its watershed could be subjected and still have a surface water ANC of 50 (j,eq/L on an
annual basis. On average, the NAPAP (2011) calculated CL of S and N for lakes in the
Adirondack Mountains is 1,620 eq/ha/yr, while for central Appalachian streams is
3,700 eq/ha/yr.
Sullivan et al. (2012b) developed a new approach for deriving regional estimates of base
cation weathering to support steady-state CL estimates for the protection of southern
Appalachian Mountain streams against acidification in three ecoregions of Virginia and
West Virginia. Weathering estimates at the study watersheds were developed using
MAGIC and extrapolated to the full study region using landscape characteristics
available as regional coverages. Calculated CL values were low at many locations. In the
Blue Ridge ecoregion, calculated CL values to maintain stream ANC at 50 (ieq/L were
less than 500 eq/ha/yr at one-third of the study sites. About half or more of the stream
length in the study region was in exceedance of the critical load of S for protecting
aquatic resources to an ANC level of 50 j^ieq/L over the long term.
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16
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18
19
20
21
22
23
24
25
26
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In another model simulation in Appalachian Mountain streams, McDonnell et al. (2014b)
calculated critical values, including steady-state aquatic CLs to protect streams against
acidification to ANC = 50 (ieq/L. They considered an ANC threshold of 50-100 j^icq/L to
be generally protective of ecological health (cf, U.S. EPA. 2009c; C'osbv et al.. 2006).
The study area included mainly streams in Virginia, West Virginia, North Carolina, and
Tennessee. Weathering values were calibrated using the MAGIC model and machine
learning/linear regression models, and used as inputs to the Steady State Water Chemistry
(SSWC) model to calculate regional CLs. Nearly one-third of the stream length assessed
in the study region had a CL of S deposition <500 eq/ha/yr, which was below the
estimated regional average S deposition (600 eq/ha/yr). The percentage of streams in
exceedance was highest for mountain wilderness areas and national parks and lowest for
privately owned valley bottom lands.
Shaw et al. (2014) applied two variants of the SSWC model (one based on the F-factor
approach and the other determined empirically) to estimate CLs for 2008 lakes in Class I
and II wilderness areas in the Sierra Nevada. It was estimated that slightly more than
one-third of the lakes received acidic deposition higher than the estimated CL. Lakes
included in the model runs were generally dilute, with mean ANC = 56.8 (ieq/L. Critical
loads for acid deposition were estimated at ANC values of 0, 5, 10, and 20 (ieq/L, which
span the range of minimum ANC values observed in Sierra Nevada lakes. Median CLs
were 217 (ANC = 0), 186 (ANC = 5), 157 (ANC = 10), and 101 (ANC = 20) ^leq/L. The
median CL for granitic watersheds based on a critical ANC limit of 10 j^icq/L was
149 eq/ha/yr.
8.5.6.2 Target and Dynamic Critical Loads
To simulate the dynamic aspects of damage and recovery, a dynamic model based on
hydrogeochemical processes is required. Dynamic models can be used to simulate soil or
water chemistry or biological response. Since the 2008 ISA dynamic modeling of CLs
have been focused on the Adirondacks, Appalachians, Great Smoky Mountains National
Park, Shenandoah National Park, and the Rocky Mountains/Sierra Nevada (Table 8-8).
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Table 8-8 Recent aquatic critical load and target load modeling studies in the
U.S. to protect against aquatic acidification.
Type of
Region
Model
Ecosystem
Focus
Critical Loads
Publication
Conterminous
SSWC and
Lakes and
Implementation
A consistent CL process was
Blett etal. (2014)
U.S.
empirical
streams
of a consistent
documented.
process for
calculating and
mapping
steady-state CLs
Adirondack
MAGIC and
Lakes
TL for lakes in
To achieve ANC = 50 peq/L in
Sullivan et al.
Mountains
Regional
the yr 2050 and
2100 about 30% of lakes had
(2012a)
Extrapolatio
2100
simulated TL of S deposition
n of Model
<500 eq/ha/yr. About
600 lakes were in
exceedance.
Adirondack
PnET-BGC
Lakes
TL link to fish
The magnitude of simulated
Zhou etal. (2015b)
Mountains
and zooplankton
historical acidification
richness
represented by ANC loss
ranged from about 26 to
100 peq/L. The amount of
historical acidification of the
lakes was related to the total
ambient deposition of
SO42" + NO3-, the Ca
weathering rate, and the
simulated preindustrial ANC in
the yr 1850. Adirondack lakes
have lost fish and total
zooplankton species richness
beginning with the onset of
acidic deposition. Modeling
results suggested that
complete recovery to
preindustrial conditions may
not be possible for most
acidified lake ecosystems.
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Table 8-8 (Continued): Recent aquatic critical load and target load modeling
studies in the U.S. to protect against aquatic acidification.
Region
Model
Type of
Ecosystem
Focus
Critical Loads
Publication
Adirondack PnET-BGC
Mountains.
Lake Effects of
biophysical
factors on the TL
Model simulations suggested
that future decreases in SO42"
deposition would be more
effective in increasing the lake
water ANC than equivalent
decreases in NO3" deposition.
The difference was a factor of
4.6 during the period 2040 to
2050, but decreased to a
factor of 2 by the yr 2200.
Lakes that had longer
hydrologic residence exhibited
less historical acidification and
therefore could achieve a
higher ANC in response to
chemical recovery compared
with lakes that had short
hydrologic residence times.
Zhou etal. (2015c)
Adirondack SSWC
Lakes and
Combined
To achieve ANC = 50 peq/L
Mountain
streams
deposition load
on average, critical load of
lakes and
of sulfur and
sulfur and nitrogen for lakes in
Appalachian
nitrogen to
the Adirondack Mountains is
Mountain
which a stream
1,620 eq/ha/yr, while for
streams
and its
central Appalachian streams
watershed could
is 3,700 eq/ha/yr.
be subjected
and still have a
surface water
concentration
ANC of 50 peq/L
on an annual
basis
NAPAP (2011)
NY
MAGIC and
Streams and
Development
To achieve ANC values of 50
Sullivan (2015)
Regional
lakes
and application
and 20 peq/L in the yr 2050
Extra-
of tools to
and 2100, the TL to protect
polation of
document and
against acidification of surface
Model
quantify TL and
waters was exceeded
their
throughout the Adirondack
exceedances
Mountains.
Hubbard
PnET-BGC
Stream
Importance of
Authors developed
Wu and Driscoll
Brook
incorporating
three-dimensional dynamic TL
(2010)
Experimental
base cation
surfaces as function of NO3",
Forest, NH
deposition and
S, and base cation deposition
climate in
under varying climate
calculating TLs
scenarios.
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Table 8-8 (Continued): Recent aquatic critical load and target load modeling
studies in the U.S. to protect against aquatic acidification.
Region
Model
Type of
Ecosystem
Focus
Critical Loads
Publication
VA, WV
SSWC
Streams
Estimation of CL
and exceedance
for stream
watersheds
exposed to S
deposition
To achieve ANC = 50 peq/L
one-third of the stream length
in the Blue Ridge ecoregion
had CL <500 eq/ha/yr. About
half of the stream reach in the
study region was in
exceedance under assumed N
saturation at steady state.
Sullivan et al.
(2012b)
Southern SSWC Streams Regional
Appalachian
Mountains.
To achieve ANC = 50 peq/L McDonnell et al.
nearly one-third of the stream (2014b)
length in the southern
Appalachian Mountain region
had a critical load of S
deposition <500 eq/ha/yr,
which was less than the
estimated regional average S
deposition (600 eq/ha/yr). Due
to the local geology, elevation,
and cool and moist forest
conditions, the percent of
streams in exceedance was
highest for mountain
wilderness areas and national
parks, and lowest for privately
owned valley bottom lands.
Great Smoky PnET-BGC Streams TL values for
Mountains 12 streams to
National Park achieve ANC
0, 20, and
50 peq/L by
2050
To achieve ANC values of 0, Zhou et al. (2015a)
20, and 50 peq/L, the level of
of NO3" + SO42" deposition
necessary to achieve a given
ANC target was approximately
a linear function of current
ANC. Most streams could not
achieve ANC = 50 peq/L;
some could not achieve
ANC = 20 peq/L. Simulated
mean projected stream ANC
of 71 peq/L (range 32 to
107 peq/L) prior to industrial
development (-1850)
decreases in response to
historical acidic deposition to
33 peq/L (-13 to 88 peq/L) in
2007.
Shenandoah MAGIC
(2008)
Stream TL values for To achieve ANC = 50 peq/L in Sullivan et al.
14 streams to 2100 median modeled
achieve streams located on siliciclastic
ANC = 50 peq/L geology had TL about
in 2100 3 kg S/ha/yr, substantially
lower than ambient deposition.
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Table 8-8 (Continued): Recent aquatic critical load and target load modeling
studies in the U.S. to protect against aquatic acidification.
Type of
Region
Model
Ecosystem
Focus
Critical Loads
Publication
NE, Rocky
Empirical
Lakes
CL of N for
To achieve ANC = 0 peq/L
Baron et al. (2011b)
Mountains,
acidification of
critical loads to protect against
Sierra
lakes
episodic acidification were
Nevada
4.0 kg N/ha/yr in West and
8.0 kg N/ha/yr in NE.
Sierra
SSWC
Lakes
CL of acidity for
To achieve ANC = 10 peq/L,
Shaw et al. (2014)
Nevada
208 lakes
median CL was 149 eq/ha/yr
and 16-17% of study lakes
were in exceedance.
N/A
Various
Various
Application of
A conceptual framework was
Sullivan (2012)
CLand ES
proposed that illustrates how
principles for
CL and ES can be combined,
public land
using as an example aquatic
management
acidification.
and natural
resources policy
decision making
ANC = acid neutralizing capacity; Ca = calcium; CL = critical load; eq = equivalent; ES = ecosystem service; ha = hectare;
kg = kilogram; L = liter; m = meter; |jeq = microequivalent; MAGIC = Model of Acidification of Groundwater in Catchments;
N = nitrogen; NE = northeast; N03" = nitrate; PnET-BGC = Photosynthesis and Evapotranspiration-Biogeochemical; S = sulfur;
S042" = sulfate; SSWC = Steady State Water Chemistry; TL = target load; yr = year.
1 In the Adirondacks region, the MAGIC model was used by Sullivan et al. (2012a) to
2 estimate the target load that would protect the acid-base chemistry of lakes. The target
3 loads were calculated for two time periods (2050, 2100) and three levels of protection
4 (ANC = 0, 20, 50 (ieq/L). Results of simulated target loads, and associated exceedances,
5 were extrapolated to the regional population of Adirondack lakes. About 30% of the lakes
6 had target load <500 eq/ha/yr to protect lake ANC to 50 j^icq/L. About 600 lakes received
7 S deposition in exceedance of the target load required to protect to ANC = 50 (ieq/L, in
8 some cases by more than a factor of two. Based on the model simulations, some critical
9 criteria threshold values were not obtainable, even when S deposition was decreased to
10 zero (Figure 8-14).
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ALSC Sampled Watersheds
ANC Criterion = SOfteq/L in 2100
Target Load of S (mcq'm tyt)
$~S ADK Ecorwiofl
© 25-50 c""^
O 50-75 C_| Sttto8ourd»»y
O 75-100
• >100
Exc*e4anc« of S Ta*g«i Load
O No Excetdance
r>
ADK Ecoregion
O 1.0 to 1.5 !nre» the CL
O 1.5 to 2.0 ttw CL
State Boundary
• > 2.0 limes the CL
ALSC Sampled Watersheds
ANC Criterion * 9Ofi0q/Lm21OO
ADK = Adirondack; ALSC = Adirondack Lakes Survey Corporation; ANC = acid neutralizing capacity; CL = critical load; L = liter;
meq = milliequivalent; peq = microequivalent.; S = sulfur
Source: Sullivan et al. (2012a).
Figure 8-14 Target loads for sulfur deposition in the Adirondack Park to
protect lake acid neutralizing capacity at 50 [jeq/L in the year 2010
(left map) and their exceedance (right map).
Simulations using the dynamic PnET-BGC model (Zhou et al.. 2015c) for the Constable
Pond watershed (a chronically acidified drainage area in the Adirondack region)
suggested that future decreases in SO42 deposition would be more effective in increasing
the lake water ANC than equivalent decreases in NO? deposition. Biophysical factors
that affected CLs and TLs included hydrologic residence time. Lakes with longer
hydrologic residence time exhibited less historical acidification and therefore could
achieve a higher ANC in response to chemical recovery compared with lakes that had
short hydrologic residence times. This difference was attributed to in-lake production of
ANC in the lakes having long hydrologic residence time. The model outputs further
suggested that forest cutting could enhance acidification by the removal of nutrient base
cations along with the removal of forest biomass. However, forest cutting could also
enhance retention of atmospherically deposited N in an aggrading forest ecosystem.
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In another modeling study using PnET-BCG, Zhou et al. (2015b) evaluated lake water
chemistry and the species richness of fish and total zooplankton in 20 Adirondak
watersheds in response to historical acidic deposition and under future deposition
scenarios. Historical acidification in the lakes was related to the total ambient deposition
of S042 + NO3 . the Ca weathering rate, and the simulated preindustrial ANC in the year
1850. In the modeled watersheds, changes in the concentration of Al3+ since the onset of
acidic deposition were related to the Ca weathering rate and the hindcast value of ANC in
the year 1850. Estimated preindustrial ANC for the study lakes ranged from 18 to
190 (ieq/L. Modeling results suggested that lake ANC and fish and total zooplankton
species richness would increase under hypothetical decreases in future acidic deposition.
However, biological and chemical recovery may not be attainable in all of the lakes
(Zhou et al.. 2015b).
Using the same model (PnET-BGC), Zhou et al. (2015a) simulated past and future effects
of N and S on stream chemistry of 12 watersheds in the Great Smoky Mountain National
Park. Three target levels of ANC (0, 20, and 50 |_icq/L) were based on a range of
protection of aquatic life from "minimal" to "considerable." Model simulations indicated
the level of NO3 + SO42 deposition necessary to achieve a given ANC target was
approximately a linear function of current ANC. Target loads of NO3 + SO42 deposition
for the 12 study streams ranged from 270 to 3,370 eq/ha/yr to reach an ANC of 0 |icq/L
by 2050, 0-2,340 eq/ha/yr to reach ANC of 20 (ieq/L by 2050, and 0-1,400 eq/ha/yr to
reach an ANC of 50 |icq/L by 2050. However, the majority of streams could not achieve
the ANC target of 50 |_ieq/L. This was also true to a lesser extent for the target of
ANC = 20 (ieq/L.
An important outcome of CL modeling studies is the suggestion that complete recovery
may not be possible in the Appalachians. Sullivan et al. (201 lb) applied the MAGIC
model to estimate the S target load for protecting aquatic resources in 66 stream
watersheds in the Southern Blue Ridge province of the Appalachian Mountains at
different points in the future. For some of the modeled sites, if S deposition were
decreased to zero and maintained at that level throughout the simulation, one or more of
the selected critical ANC levels (0, 20, 50, 100 j^icq/L) could not be achieved by 2100.
For other sites with large watershed acid buffering capacity even very high sustained S
deposition would not reduce stream ANC below thresholds associated with biological
harm.
MAGIC modeling based on simulations of past and future acid-base chemistry of
14 streams in Shenandoah National Park identified a target load of about 3 kg S/ha/yr in
the median modeled stream located on sensitive (siliciclastic) bedrock. This was 77%
lower than the S deposition in 1990 (Sullivan et al.. 2008). Target loads were calculated
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to achieve ANC = 50 j^icq/L in 2100. Many streams had ambient ANC <20 j^icq/L.
Hindcast simulations suggested that preindustrial ANC was above 50 |_icq/L in all of the
study streams.
8.5.7 International Critical Loads
Critical loads concepts were initially developed in Europe and more recently applied in
the U.S. and Canada. Work on CLs has continued internationally as a basis for setting
environmental policy. Some of the recent work conducted outside the U.S. is summarized
below.
Previous regional CL assessments in the U.S. and Canada have often employed an
empirical clay-based soil texture approximation to estimate weathering as input for
aquatic and terrestrial CL modeling, koseva et al. (2010) developed a generalized soil
texture approximation method at 75 sites across Canada. It was based on soil silt content,
loss-on-ignition (which represents organic matter content), and soil depth. The model's
performance (adjusted If = 0.73) suggested that it may have broad application to forest
soils in Canada. Krzvzanowski and Innes (2010) estimated steady-state CLs, using the
SSWC model, and associated exceedances for protecting freshwater ecosystems in First
Nations territory in British Columbia against water acidification. Estimates of acidic
deposition were not in exceedance of the CL at any of the study lakes.
The 1999 Gothenburg Protocol, under the Long-Range Transboundary Air Pollution
(LRTAP) Convention of the United Nations Economic Commission for Europe
(UNECE), was aimed at reducing the total area of Europe where acidic deposition
exceeded CLs. In 2007, the Coordination Centre for Effects (CCE) of the International
Cooperative Programme for Modeling and Mapping (part of the LRTAP Convention)
issued a call to European countries for results from dynamic models of soil and water
acidification. In response to this call, Norwegian scientists used the MAGIC model to
project recovery of surface waters in Norway. Larssen et al. (2010) described the results
for water quality and fish population status and considered implications for policy
options. The modeling results suggested that surface waters will continue to recover
slowly under existing legislation, but about 18% of Norway will still have lakes that
receive acidic deposition that exceeds the CL to protect against aquatic acidification and
in which water quality will continue to be insufficient to support viable populations of
fish and other aquatic organisms.
Anthropogenic acidification of surface waters is influenced by TOC concentrations in
water. Both the degree of acidification and chemical recovery are dependent on historical
TOC concentrations. Valinia et al. (2015) used visible near-infrared spectroscopy of lake
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sediments to reconstruct the reference condition TOC in Swedish lakes. Long-term
monitoring data were used to simulate recent changes in TOC and then analyzed using
two empirical models. The first predicted historical TOC trends between reference
conditions in the year 1860 and peak acidification in approximately the year 1980. The
second model predicted TOC between 1988 and 2012 in conjunction with partial
chemical recovery from acidification. The models were driven by lake and watershed
area, the amount of wetlands, historical S deposition, and current water chemistry. The
researchers estimated that the present-day TOC concentrations are similar to
reconstructed reference conditions in Swedish lakes. Thus, it was deemed unlikely that
the TOC concentrations in Swedish lakes will continue to increase with continued
controls on acidic deposition.
Bishop et al. (2008) applied the SSWC model to lakes in northern Sweden, many of
which are rich in organic matter. They argued that the SSWC model is not suitable for
judging the acidification of individual lakes in regions such as northern Sweden where
the extent of chronic acidification is relatively small and where organic influence on lake
chemistry is pronounced. A variant of the SSWC model predicted preindustrial lake
chemistry at 58 sites where paleolimnological reconstructions of lake chemistry were
available. The authors noted a large discrepancy between SSWC predictions and diatom
reconstructions, and this was attributed largely to short-term fluctuations in modern lake
chemistry.
8.6 Aquatic Acidification Summary and Causal Determinations
In the 2008 ISA, the body of evidence was sufficient to infer a causal relationship
between acidifying deposition and changes in freshwater biota. Studies indicate that
aquatic organisms have been affected by acidification at virtually all trophic levels in
sensitive ecosystems and that these responses have been well characterized for several
decades. Recent research and observations reported in the 2008 ISA show consistent and
coherent evidence for effects on aquatic biota, especially algae, benthic invertebrates, and
fish that are most clearly linked to chemical indicators of acidification (pH, ANC,
inorganic Al concentration). Effects on fish species are especially well understood, and
many species are documented to be adversely affected. Both in situ and lifestage
experiments in fish support previous thresholds of chemical indicators and biological
effects. Physiological perturbations at the organism level of biological organization can
lead to effects on reproduction, growth, and survival. More species are lost with greater
acidification, providing evidence of a biological gradient in effects. Biological shifts such
as loss of acid-sensitive organisms, population declines, and decreased species richness
have been reported from acid-sensitive regions of the U.S. and other countries. Despite
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reductions in acidifying deposition, many aquatic ecosystems across the U.S. are still
experiencing changes in ecological structure and functioning at multiple trophic levels.
New information is consistent with the conclusions of the 2008 ISA that the body of
evidence is sufficient to infer a causal relationship between acidifying deposition and
changes in biota including physiological impairment and alteration of species
richness, community composition, and biodiversity in freshwater ecosystems.
Baker et al. (1990a) conducted a rigorous review of the effects of acidification on aquatic
biota for the 1990 National Acid Precipitation Assessment Program (NAPAP) State of
Science/Technology reports. In the review, hundreds of laboratory studies, in situ
bioassays, field surveys, whole-system field experiments, and mesocosm studies were
evaluated to provide a synthesis of the effects of acidification on aquatic biota. The
findings in that report along with literature published after 1990 up to 2007 were included
in the 2008 ISA. The summaries below integrate information known at the time of the
2008 ISA with newer studies. For most topics related to aquatic acidification, the
fundamental understanding of mechanisms and biological effects has not changed; rather,
additional studies support findings from the previous ISA.
The effects of acidification on freshwaters in the U.S. and elsewhere were well
characterized at the time of the 2008 ISA. The sensitivity of a watershed depends on
watershed characteristics such as underlying geology (Chapter 7). and the sensitivity of
species that make up the local biological community. Changes in biota are linked to
chemical indicators in surface water (Chapter 7; Table 8-9). As stated in the 2008 ISA,
biological effects are primarily attributable to low pH and high inorganic Al
concentration. ANC is also used because it integrates overall acid status and because
surface water acidification models do a better job projecting ANC than pH and inorganic
Al concentrations. However, ANC does not relate directly to the health of biota. The
usefulness of ANC lies in the association between ANC and the surface water
constituents or parameters that directly contribute to or ameliorate acidity-related stress,
in particular pH, Ca, and inorganic Al.
Acid-sensitive freshwater systems can either be chronically acidified or subject to
occasional episodes of decreased pH and ANC and increased inorganic Al concentration.
Chronically acidic lakes and streams typically have an ANC of <0 |icq/L. while ANC in
freshwater systems where episodic acidification occurs may fall below 0 (j,eq/L for only a
few hours to weeks in a given year (Driscoll et al.. 2001b). During these episodes, water
chemistry may exceed acid tolerance of resident aquatic biota. Biological effects of
episodes may include fish mortality, changes in species composition, and declines in
aquatic species richness across multiple taxa. Biological effects of chronic and episodic
acidification have been most clearly documented for phytoplankton, zooplankton, aquatic
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invertebrates, and fish and can be linked to changes in the chemical indicators of aquatic
acidification (Table 8-9).
Table 8-9
Ecological indicators and thresholds for aquatic acidification.
Key Indicators
Ecological Threshold
Key References
Acid neutralizing
capacity
0 peq/L—risk for chronic acidification
20-50 peq/L—risk for episodic acidification
>100 peq/L—low risk to aquatic biota
Driscoll et al. (2001b), MacAvov and
Bulaer (1995), Baker et al. (1990a)
Base cation
surplus in soil
0 peq/L—risk of Al leaching to streams
Section 3.2.1.5 2008 Integrated
Science Assessment for Oxides of
Nitrogen and Sulfur-Ecological Criteria
U.S. EPA (2008a)
PH
<6.0—reduced number offish species
Driscoll et al. (2001b), MacAvov and
Bulaer (1995), Baker et al. (1990a)
Inorganic Al
>2 pmol/L (54 |jg/L)—toxic to aquatic biota
Baldiao et al. (2007), Driscoll et al.
(2001b), Wiainaton et al. (1996a),
MacAvov and Bulaer (1995)
Al = aluminum; L = liter; |jeq = microequivalent; |jg = microgram.
Source: modified from Fenn et al. (20116).
8.6.1 Phytoplankton
Phytoplankton, photosynthesizing forms of plankton, play an important role in freshwater
systems as primary producers in the aquatic food web. These organisms encompassing
diatoms, cyanobacteria, dinoflagellates, and other groups of algae vary in tolerance of
acidic conditions. Studies reviewed in the 2008 ISA reported reduced species richness of
plankton with the decreases in pH and increases in inorganic Al concentrations that are
associated with acid-affected surface waters (U.S. EPA. 2008a). Effects were most
prevalent in the 5 to 6 pH range (Baker et al.. 1990a). Since the 2008 ISA, several
paleolimnological and field studies have further linked phytoplankton community shifts
to chemical indicators of acidification. For example, Lacoul etal. (2011) reviewed
information on the effects of acidification on plankton in Atlantic Canada and observed
that the greatest changes in phytoplankton species richness occur over a pH range of 4.7
to 5.6, just beyond the interval (pH 5.5 to 6.5) where bicarbonate becomes rapidly
depleted in the water.
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8.6.2
Zooplankton
Zooplankton, the animal forms of plankton, comprise many groups of freshwater
unicellular and multicellular organisms including protozoans, rotifers, cladocerans, and
copepods. Decreases in ANC and pH and increases in inorganic A1 concentration were
shown to contribute to the loss of zooplankton species and/or abundance in lakes in
studies reviewed in the 2008 ISA (Keller and Gunn. 1995; Schindler et al.. 1985V
Possible mechanisms for zooplankton sensitivity to low pH and ANC include ion
regulation failure, reduced oxygen uptake, inability to reproduce, and inorganic Al
toxicity (U.S. EPA. 2008a). Reported pH thresholds for zooplankton community
alteration generally ranged from 5 to 6 in studies reviewed in the 2008 ISA. For example,
a decrease in pH from 6 to 5 caused decreased species richness in zooplankton
communities in lakes (Holt et al.. 2003; Holt and Yan. 2003; Locke and Sprules. 1994).
Newer studies support effects in a similar pH range. Vinebrooke etal. (2009) reported
variations in phytoplankton and zooplankton communities during a whole-lake
experimental acidification of Lake 302S in the Experimental Lakes Area in Ontario.
There was a negative effect on zooplankton species richness as pH decreased from 6.8 to
4.5. Acidification often reduces Ca availability in lake water and can affect growth and
survival of Daphia spp., an important prey item in many freshwater food webs (Jeziorski
et al.. 2012b). At ANC values <0, zooplankton richness was extremely low in
Adirondack lakes [15 species in highly acidic lakes compared to 35 at the highest values
of ANC in the study (near 200 (.ieq/L) (Sullivan et al.. 2006a)l.
8.6.3 Benthic Invertebrates
Sediment-associated invertebrates such as bivalves, worms, gastropods, and insect larvae
are impacted by acidification because H+ and Al can be directly toxic, causing disruption
of ion regulation and reduced reproductive success. As reviewed in the 2008 ISA,
decreases in ANC and pH and increases in inorganic Al concentration have been shown
to contribute to the decline in abundance or loss of benthic invertebrates species in
streams. Typically, pH values below 5 virtually eliminate all mayflies, a common taxa
used to assess water quality, along with other aquatic organisms from some streams (U.S.
EPA. 2008a; Baker and Christensen. 1991). Since the 2008 ISA, a survey of benthic
macroinvertebrates by Baldigo et al. (2009) in 36 streams in the southwestern
Adirondack Mountains indicates that 44 to 56% of macroinvertebrate communities were
severely impacted by acidification at pH <5.1, moderately at pH 5.1 to 5.7, and
unaffected at pH above 6.4 (Baldigo et al.. 2009). Thresholds of pH 5.2 to 6.1 were
identified for sensitive invertebrates from Atlantic Canada; below these pH values,
changes in the abundance or presence of taxa were observed (Lacoul etal.. 2011).
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8.6.4
Fish
The primary mechanism for the toxic effects of acidified waters on fish involves
disruption of normal ion regulation at the gill surface, resulting in increased rates of ion
loss and inhibition of ion uptake (Bergman et al.. 1988; Wood and McDonald. 1987;
Lcivestad. 1982; McWilliams and Potts. 1978). Additional responses to acidifying
conditions include respiratory and circulatory failure. The effects of low pH, low ANC,
and high inorganic Al concentrations have been well characterized in fish for many
decades. Responses among fish species and lifestages within species to pH and Al in
surface waters is markedly variable. In general, early lifestages are more sensitive to
acidic conditions than the young-of-the-year, yearlings, and adults (Baker et al.. 1990a;
Johnson et al.. 1987; Baker and Schofield. 1985). Some of the most commonly studied
species are brown trout, brook trout, and Atlantic salmon.
Further characterization of physiological responses (ion regulation, stress responses, gill
Al accumulation) to acidification in fish, mostly trout and salmonids, adds to the existing
information on sublethal effects on individual fish species. Many of the newer studies are
conducted in situ and report varying sensitivity of different lifestages. Findings are
consistent with physiological alterations in fish reported in the 2008 ISA. Several studies
have assessed physiological changes associated with migratory activities. For example, a
recent study assessed gill Al and NKA activity in smolts moving downsteam in
well-buffered and acid-impacted migration corridors in the northeastern U.S. (Kelly et
al.. 2015). In the acid-impacted river basin, the fish had elevated gill Al and lower gill
NKA activity.
As summarized in Baker etal. (1990a) and studies reviewed in the 2008 ISA, fish
populations in acidified streams and lakes of Europe and North America have declined,
and some have been eliminated as a result of atmospheric deposition of acids and the
resulting changes in pH, ANC, and inorganic Al concentrations in surface waters. There
is often a positive relationship between pH and number of fish species, at least for pH
values between about 5.0 and 6.5 (C'osbv et al.. 2006; Sullivan et al.. 2006a; Driscoll et
al.. 2003b; Bulger etal.. 1999). Additional pH thresholds published since the 2008 ISA
generally reinforce these ranges, and several new studies consider the role of DOC in
modulating pH and subsequent effects on biota. New studies on fish responses to
chemical alarm cues show behavioral effects at pH <6.6. Characterization of ANC and its
levels of concern have not changed appreciably with the newly available information.
Few or no fish species are found in lakes and streams that have very low ANC (near zero)
and low pH [near 5.0; (U.S. EPA. 2008a; Sullivan et al.. 2006a)l. The number of fish
species generally increases at higher ANC and pH values. ANC largely controls pH and
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the bioavailability of A1 (Driscoll et al.. 2001b). A1 is very toxic to fish, and thresholds to
elevated concentrations of this metal in acidified waters are summarized in Table 8-4.
Some of the most in-depth studies of the effects of acid stress on fish have been
conducted in streams in Shenandoah National Park, Virginia (C'osbv et al.. 2006), and
lakes in the Adirondack Mountains, New York (Sullivan. 2015). Effects on fish have also
been documented in acid-sensitive streams of the Catskill Mountains of southeastern
New York and the Appalachian Mountains from Pennsylvania to Tennessee and South
Carolina (Bulger et al.. 2000; Bulger et al.. 1999; SAMAB. 1996; Charles and Christie.
1991).
8.6.5 Thresholds of Response
As reviewed above, new thresholds have been identified in aquatic organisms (Table
8-10). However, this new information does not appreciably change the understanding of
biological effects associated with chemical indicators or the levels at which effects occur.
Evidence continues to strengthen findings in the 2008 ISA that high levels of
acidification (to pH values below 5) eliminate sensitive species from freshwater streams.
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Table 8-10 Results of recent biological effects studies in surface waters
indicative of thresholds of biological response to changes in water
acidity.
Life Forms and Effects
Region
Potential Tipping
Points
Reference
Sensitive invertebrates present
Atlantic Canada
pH 5.2 to 6.1
Lacoul et al. (2011)
Littoral macroinvertebrates
Northern Europe
pH 5.8 to 6.5
Schartau et al. (2008)
Brook trout loss of whole-body Na
Great Smoky Mountains NP
pH 5.1
Neffet al. (2008)
Brook trout loss of whole-body Na
of 10 to 20%
Great Smoky Mountains NP
pH 4.9 to 5.1
Neffet al. (2009)
Fish damage in lakes
Norway
ANC 67 peq/L
Hesthaaen et al. (2008)
Juvenile brown trout mortality in
high DOC streams
Sweden
pH 4.8 to 5.4
Serrano et al. (2008)
Embryo and yolk sac fry survival
during episodes in DOC-rich lakes
Sweden
pH 4.0
Serrano et al. (2008)
Toxicity to brown trout in humic
streams
Northern Europe
pH 5.0; inorganic
aluminum 20 |jg/L
Andren and Rvdin (2012)
Presence of macrophytes
Atlantic Canada
pH 5.0
Lacoul et al. (2011)
Aquatic bird breeding
Atlantic Canada
pH 5.5
Lacoul et al. (2011)
ANC = acid neutralizing capacity; DOC
NP = National Park.
= dissolved organic carbon; L = liter; |jeq = microequivalent; |jg = microgram; Na = sodium;
8.6.6 Biological Recovery
1 Biological recovery can occur only if chemical recovery (Chapter 7) is sufficient to allow
2 growth, survival, and reproduction of acid-sensitive plants and animals (Driscoll et al..
3 2001b'). As reported in the 2008 ISA, biological recovery lags behind chemical recovery
4 in many systems, and the time required for biological recovery after chemical recovery is
5 complete is uncertain (U.S. EPA. 2008a'). New studies continue to support these
6 observations. In general, recovery of plankton and other invertebrates is observed prior to
7 recovery of fish populations, although most biological communities studied to date have
8 not returned to preacidification conditions, even after recovery of chemical parameters. In
9 a study reviewed in the 2008 ISA, zooplankton recovery in experimentally acidified
10 Little Rock Lake in Wisconsin took one decade with approximately 40% of the
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zooplankton species experiencing a lag time of 1 to 6 years compared to the reference
basin (Frost et al.. 2006). In an experimentally acidified lake in Canada, zooplankton
species diversity partially rebounded to preacidification levels as pH returned back to 6.1,
with rotifers recovering less than crustaceans (Mailev and Chang. 1994). Newer studies
from the Sudbury Lakes region of Canada indicate substantial recovery of copepods and
cladocerans at pH 5.5 and higher in previously acidified lakes (Valois et al.. 2011). Since
the publication of the 2008 ISA additional studies are available that assess recovery of
benthic organisms although most of the research has been conducted in Canadian and
European waters.
In the 2008 ISA, recovery of fish populations following liming or reduction of deposition
was reported in several studies. Newer studies have documented successful
reintroduction of brook trout in previously acidified Adirondack water bodies (Brooktrout
Lake) or recolonization (Honnedaga Lake) by populations in tributary refuges
(Sutherland et al.. 2015; Joseph son et al. 2014). Fish community shifts from historical
acidification have been observed in the upper mainstem of Hubbard Brook (Warren et al..
2008) and other locations.
8.6.7 Most Sensitive and Most Affected Regions
The extent and distribution of sensitive ecosystems and regions in the U.S. were well
known at the time of the 2008 ISA. In the U.S., surface waters that are most sensitive to
acidification based on ANC and alkalinity are largely found in the Northeast, southern
Appalachian Mountains, Florida, the Upper Midwest, and the mountainous West
(McDonnell et al.. 2014b; Greaver et al.. 2012; Campbell et al.. 2004a; Driscoll et al..
2001b; Baker et al.. 1990b; Omernik and Powers. 1983). Levels of acidifying deposition
in the West are low in most areas, acidic surface waters rare, and the extent of chronic
surface water acidification that has occurred to date has been very limited (Charles and
Christie. 1991). Episodic acidification does occur in both the East and West at some
acid-sensitive locations.
8.6.8 Critical Loads
Since the 2008 ISA, considerable critical loads research has been conducted in the U.S.
New empirical critical loads include 8 kg N/ha/yr in the Northeast and 4 kg N/ha/yr in the
West for high elevation lakes (Baron et al.. 2011b) and an ANC of 74 eq/ha/yr in high
elevation lakes of the Sierra Nevada (Heard et al.. 2014). Several steady state critical
loads have been derived since the 2008 ISA. Steady-state critical loads of S and N for
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lakes in the Adirondack Mountains (1,620 eq/ha/yr) and for the central Appalachian
streams (3,700 eq/ha/yr) were calculated for maintaining a surface water ANC of
50 (.ieq/L on an annual basis (NAPAP. 2011). Sullivan et al. (2012b) calculated critical
load values in the Blue Ridge ecoregion, where calculated values for maintaining stream
ANC at 50 (ieq/L were less than 500 eq/ha/yr at one-third of the study sites. Observations
show that about one-half or more of the stream length in the study region was in
exceedance of the critical load of S for protecting aquatic resources to an ANC level of
50 (.ieq/L over the long term. McDonnell et al. (2014b) calculated steady-state aquatic
critical loads to protect southern Appalachian Mountain streams against acidification up
to ANC = 50 (ieq/L and other critical values. Results showed that nearly one-third of the
stream length in the study region (mainly streams in Virginia, West Virginia, North
Carolina, and Tennessee) had a critical load of S deposition <500 eq/ha/yr, which was
less than the estimated regional average S deposition (600 eq/ha/yr). Critical loads for
acid deposition lakes in Class I and II wilderness areas of the Sierra Nevada were
estimated in 2008 at ANC values of 0, 5, 10, and 20 |icq/L. which span the range of
minimum ANC values observed in those lakes. Median CLs were 217 (ANC = 0), 186
(ANC = 5), 157 (ANC = 10) and 101 (ANC = 20) |icq/L. The median CL for granitic
watersheds based on a critical ANC limit of 10 j^icq/L was 149 eq/ha/yr. It was estimated
that slightly more than one-third of the lakes received acidic deposition higher than their
critical load.
In addition to the steady-state and empirical loads described above, estimates include
additional critical load information from dynamic modeling. NOs leaching in stream
water in California was both simulated (by the DayCent model) and determined
empirically with both agreeing on 17 kg N/ha/yr (Fenn et al.. 2008). Zhou et al. (2015a)
simulated past and future effects of N and S on stream chemistry of 12 watersheds in the
Great Smoky Mountain National Park. Three target levels of ANC (0, 20, and 50 j^ieq/L)
were used based on a range of protection of aquatic life from minimal to considerable.
TLs of NO3 + S042 deposition for the 12 study streams ranged from 0.27 to
3.37 keq/ha/yr to reach an ANC of 0 (j,eq/L by 2050, 0-2.34 keq/ha/yr to reach ANC of
20 |icq/L by 2050, and 0-1.40 keq/ha/yr to reach an ANC of 50 (j,eq/L by 2050.
However, the majority of streams could not achieve the ANC target of 50 j^icq/L. This
was also true to a lesser extent for the target of ANC = 20 (ieq/L. Modeling studies also
suggest that complete recovery may not be possible in the Appalachians (Sullivan et al..
2011b). For some sites, one or more of the selected critical ANC levels (0, 20, 50,
100 |_ieq/L) could not be achieved by 2100, even if S deposition were decreased to zero
and maintained at that level throughout the simulation. MAGIC modeling based on
simulations of past and future acid-base chemistry of 14 streams in Shenandoah National
Park identified a target load of about 3 kg S/ha/yr in the median modeled stream located
on sensitive (siliciclastic) bedrock which was 77% lower than the S deposition in 1990
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(Sullivan et al.. 2008). Target loads were calculated to achieve ANC = 50 (ieq/L in 2100.
Many streams had ambient ANC <20 (ieq/L. Hindcast simulations suggested that
preindustrial ANC was above 50 j^icq/L in all of the study streams.
In the Adirondacks, target loads were calculated for two time periods (2050, 2100) and
three levels of protection (ANC = 0, 20, 50 (ieq/L). Results of simulated target loads, and
associated exceedances, were extrapolated to the regional population of lakes. About
30% of the lakes had target load <500 eq/ha/yr to protect lake ANC to 50 j^icq/L (Sullivan
et al.. 2012a). Also in the Adirondacks, Zhou et al. (2015c) ran simulations using the
PnET-BGC model which suggested that future decreases in SO42 deposition would be
more effective in increasing the lake water ANC than equivalent decreases in NO,
deposition. In another modeling study of 20 Adirondack watersheds, lake ANC and fish
and total zooplankton species richness were projected to increase under hypothetical
decreases in future acidic deposition, and model projections suggested that lake
ecosystems may not achieve complete chemical and biological recovery in the future
(Zhou et al.. 2015b). Estimates of preindustrial ANC for the study lakes ranged from 18
to 190 (ieq/L. The magnitude of simulated historical acidification represented by ANC
loss ranged from about 26 to 100 (ieq/L.
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CHAPTER 9 BIOLOGICAL EFFECTS OF
FRESHWATER NITROGEN
ENRICHMENT
This chapter characterizes the biological effects of nitrogen (N) nutrient enrichment from
atmospheric deposition to freshwater systems. In many water bodies, atmospheric
deposition constitutes only a portion of total N load; however, aquatic ecosystems where
atmospheric sources are the dominant source of N (remote headwater and lower order
streams and alpine lakes) are the focus of this chapter. Section 9.1.1 presents a brief
overview of the role N in freshwater nutrient enrichment and nutrient limitation in
freshwater systems. Sources and biogeochemistry of N in freshwater systems are
reviewed in section (Section 9.1.2 and discussed further in Chapter 7. Characteristics of
water bodies sensitive to N deposition (Section 9.1.3). along with studies that show shifts
in nutrient limitation (Section 9.1.4). indicators of biological responses to nutrient
enrichment (Section 9.2). and effects on biodiversity, ecosystem structure, and function
(Section 9.3). are described. Emerging research on links between nutrient enrichment and
animal behavior and disease are reported in Section 9.4. followed by nitrate (NO, )
toxicity data (Section 9.5). Finally, the extent and distribution of nutrient enrichment
attributed to N deposition in inland water bodies of the U.S. is characterized (Section 9.6)
along with thresholds of biological response in these systems (Section 9/7). A summary
section including causal determinations based on a synthesis of new information and
previous evidence from prior N assessments is presented in Section 9J..
9.1 Introduction to Nitrogen Enrichment and Eutrophication in
Freshwater Systems
In the 2008 Integrated Science Assessment for Oxides of Nitrogen and
Sulfur—Ecological Criteria (2008 ISA), the body of evidence was sufficient to infer a
causal relationship between N deposition and the alteration of species richness, species
composition, and biodiversity in freshwater ecosystems (U.S. EPA. 2008a). Increased N
deposition to freshwater systems via runoff or direct atmospheric deposition, especially to
N limited and N and phosphorus (P) colimited systems, can stimulate primary
productivity (Figure 9-1). Eutrophication is the process of over-enrichment of a water
body with nutrients resulting in increased productivity of algae and/or aquatic plants, and
sometimes also decreased oxygen levels. As summarized in the 2008 ISA and supported
by data in newer studies, nutrient enrichment effects on freshwater ecosystems from
atmospheric deposition of N are most likely to occur in lakes and streams that have low
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primary productivity and low nutrient levels and that are located in the most undisturbed
areas with no local pollution sources (U.S. EPA. 2008a'). Even small inputs of N in these
water bodies can increase nutrient availability or alter the balance of N and P, which can
stimulate growth of phytoplankton and lead to changes in species richness, composition,
and biodiversity. Changes in biological indicators of N enrichment including chlorophyll
a, phytoplankton (free-floating algae) biomass, periphyton (algae attached to a substrate)
biomass, diatoms (major algal group with cell walls made of silica), and trophic status
indices provide evidence for N effects. Transport of atmospheric N inputs downstream
can exacerbate eutrophic conditions in higher order streams, rivers, and lakes.
Atmospheric deposition to watersheds affects processes along the freshwater to ocean
continuum including coastal and estuarine systems (Chapter 10). New information is
consistent with the conclusions of the 2008 ISA that the body of evidence is sufficient
to infer a causal relationship between N deposition and changes in biota including
altered growth, species richness, community composition, and biodiversity due to N
enrichment in freshwater ecosystems.
Nitrogen deposition
(nitrate and ammonium\
s
%
\
Upland fertilization
Nutrient enrichment
(increased productivity)
Changes in aquatic
plant assemblages
Figure 9-1 Conceptual model of the influence of atmospheric nitrogen
deposition on freshwater nutrient enrichment [modified from
Baron et al. (2011b)l.
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9.1.1
Shifting Perspectives of the Role of Nitrogen in Freshwater
Eutrophication
With increased characterization of N fate and transport processes, N and P dynamics,
phytoplankton response, and downstream effects in coastal/estuarine systems, the
understanding of the role of N in freshwater eutrophication has evolved in recent decades.
As conveyed in the 2008 ISA, the historic focus on P as a major cause of freshwater
eutrophication was based on a number of highly influential studies in the 1960s and
1970s that focused on the role of wastewater, in particular phosphate detergents, in
causing excessive algal blooms in Lake Mendota (Wisconsin), Lake Washington
(Washington), Lake Erie, and many other locations (Edmondson. 1991; Schindler. 1974;
Schindler et al.. 1971; Edmondson. 1969; Vollenweider. 1968; Hasler. 1947). These
observations guided approaches to freshwater lake and stream ecology for many years.
Over time, an increasing recognition that N inputs can stimulate phytoplankton growth
under certain conditions, coupled with further characterization of aquatic
biogeochemistry (Chapter 7) and the connectively between freshwater and receiving
estuaries and coastal waters, has led to recommendations to consider both N and P in
nutrient reduction strategies (Lewis etal.. 2011; Scott and McCarthy. 2010; Conlev et al..
2009; Paerl. 2009; Lewis and Wurtsbaugh. 2008).
In the 2008 ISA, results from surveys, paleolimnological reconstructions, experimental
results, and meta-analyses of hundreds of studies have shown N limitation to be common
in freshwaters, especially in remote areas, and a nearly universal eutrophication response
to N enrichment in lakes and streams that are N limited (U.S. EPA. 2008a; Elser et al..
2007; Bergstrom et al.. 2005; Elser et al.. 1990). Newer studies published since the 2008
ISA add to the evidence that reservoirs, rivers, and freshwater lakes can exhibit N
limitation and N and P colimitation (Paerl et al.. 2014; Lewis etal.. 2011; Conlev et al..
2009; Sterner. 2008). N limitation appears to be increasingly common in freshwater
systems, probably because their nutrient dynamics are being altered significantly by
growing agricultural and urban P inputs (Grantz et al.. 2014; Paerl et al.. 2014; Finlav et
al.. 2013).
9.1.2 Nitrogen Sources and Biogeochemical Cycling in Freshwater
N sources to freshwater including atmospheric contributions (Table 7-1) are described in
further detail in Chapter 7. Briefly, atmospheric deposition is the main source of N to
remote headwater and lower order streams and high elevation lakes (U.S. EPA. 2008a).
Nitrogen is deposited as NO3 , ammonium (NH4 ). ammonia (NH3), or organic N. In the
soil or water, much of the deposited NIL+ is either taken up by biota or nitrified to NO3
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and leaches to water bodies mainly as NO. . Although overall, atmospheric deposition of
total N has not changed, atmospheric deposition of reduced N has increased relative to
oxidized N in parts of the U.S. including the East and Midwest in the last few decades
(Chapter 2). and this trend is expected to continue under existing emissions controls
(Pinder et al.. 2008; U.S. EPA. 2008a). Moving from lower order streams to higher order
streams, atmospheric N from direct deposition, runoff, and leaching from terrestrial
ecosystems combines with other diffuse and point sources of N. The contribution from
other terrestrial sources of N. such as fertilizer, livestock waste, septic effluent, and
wastewater treatment plant outflow often becomes much more important downstream
than in upland areas. The focus of this chapter is freshwater systems (headwater streams,
lower order streams, alpine lakes) where atmospheric deposition is the dominant source
of N, Figure 9-2 summarizes the N, P, and carbon (C) cycle in freshwater ecosystems.
Biogeochemical processes and chemical indicators associated with nutrient enrichment of
freshwaters are discussed in Chapter 7.
CO,
o
"fg
v_
Q_
CO
I
o>
~
p
*
uptake
~
<
excretion
*
respiration | photosynthesis \
uptake
Primary*
producers CPii/.
deposition
! N fixation
! i
! i
\ ! i
\ i i
\
! i
> i i
N
vj)
~I
Grazers,
predators
and viruses
%
Q>
* I
excretion /
/
/
\
Detritus
decomposition
water surface
C cycle
N cycle
P cycle
Sediments
Benthic
decomposition
C = carbon; C02 = carbon dioxide; N = nitrogen; P = phosphorus.
Figure 9-2 Nitrogen cycle in freshwater ecosystems (U.S. EPA, 2008a).
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9.1.3
Characteristics of Freshwater Systems Sensitive to Atmospheric
Deposition
As reported in the 2008 ISA, freshwater systems in which N has been observed to
influence ecological processes either received extremely high inputs [e.g., (Dumont et al..
2005)1. or had very low initial N concentrations and responded rapidly to the additional
inputs (Bergstrom and Jansson. 2006; Baron et al.. 2000). Nutrient enrichment effects on
freshwater ecosystems from atmospheric deposition of N are of great concern in lakes
and streams far from local pollution sources and which have very low nutrients and
productivity (U.S. EPA. 2008a). In highly productive freshwaters, nutrient enrichment
from N deposition usually does not stimulate primary productivity or community change
because P is more commonly the limiting nutrient. Thus, nutrient enrichment effects from
N deposition are most likely to occur in undisturbed, low-nutrient surface waters like
those found at high elevation areas in the western U.S (Section 9.6). Tropical and
subtropical lakes, and lakes having small watersheds relative to the lake surface/volume,
also tend to be N limited (Paerl and Scott. 2010; Elser et al.. 2007).
Various factors affect the sensitivity of remote water bodies to atmospheric deposition.
These factors include spatial and temporal patterns of nutrient limitation and physical and
chemical attributes of the catchment (Hundev et al.. 2014; Nanus et al.. 2012; U.S. EPA.
2008a). Thus, the same amount of N deposition can lead to different N loading depending
on the characteristics of the receiving watershed and water body (Bergstrom. 2010). In
high elevation lakes above the tree line in areas with steep slopes, sparse vegetation,
exposed bedrock, and shallow rocky soils, there is little opportunity for nutrient uptake
processes, so changes in productivity and biodiversity of algal assemblages can occur
with little or no lag time (Baron et al.. 201 lb). The hydrology of these systems is
dominated by spring snowmelt (Spaulding et al.. 2015). Seasonal meltwaters can deliver
a nutrient pulse to alpine lakes and streams, with glacial meltwater contributing more
NO? than snowmelt water does (Slemmons et al.. 2015; Slemmons et al.. 2013; Saros et
al.. 2010; Baron et al.. 2009). Other freshwater systems, such as some nonalpine
freshwater lakes, reservoirs, and rivers that exhibit N limitation and N and P colimitation,
are sensitive to additional N inputs (Paerl et al.. 2014; Lewis et al.. 2011; Conlev et al..
2009; Elser et al.. 2009b; Sterner. 2008). N from atmospheric deposition represents a
proportion of total N in these systems, although agricultural and wastewater inputs are
often predominant.
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9.1.4
Shifts from Predominantly Nitrogen Limitation to Phosphorus
Limitation in High Alpine Lakes
Elevated N concentrations from deposition and runoff can increase total nutrient
availability, altering the stoichiometric composition of water chemistry and thereby
changing the nutrient status of lakes (Chapter 7). As reported in the 2008 ISA, shifts in
nutrient limitation, from N limitation, to between N and P limitation or to P limitation,
have been observed in some alpine lakes (U.S. EPA. 2008a). In a meta-analysis reviewed
in the 2008 ISA, Elser et al. (2007) found that N limitation occurred as frequently as P
limitation in freshwater ecosystems. Nutritional responses of aquatic ecosystems to
atmospheric N deposition are heavily dependent on surface water P concentrations. Thus,
chemical ratios of N to P can be very useful in evaluating eutrophication potential
(Section 9.2.4). In studies reviewed in the 2008 ISA, atmospheric N deposition
(approximately 1 to 5 kg N/ha/yr) can cause an increase in phytoplankton and periphyton
biomass in some high alpine lakes. For example, evidence for effects on algal
productivity at 1.5 kg N/ha/yr was reported for both the Beartooth Mountains, Wyoming
and Rocky Mountains, Colorado (Baron. 2006; Saros et al.. 2003).
The 2008 ISA reported on gradient studies of undisturbed northern temperate, mountain
or boreal lakes that receive low levels of atmospheric N deposition. These studies found
strong relationships between N limitation and primary productivity where N deposition
was low and P and N + P limitations where N deposition was higher (Bergstrom and
Jansson. 2006; Bergstrom et al.. 2005; Fenn et al.. 2003a). As reviewed in the 2008 ISA,
a comprehensive survey of 42 unproductive lakes (oligotrophic lakes with total P less
than or equal to 25 (ig/L) along gradients of N deposition in Europe and North America
showed increased inorganic N concentration and productivity to be correlated with
atmospheric N deposition (Bergstrom and Jansson. 2006). Unproductive lakes receiving
low atmospheric N deposition were N limited (<2.5 kg N/ha/yr). At about 2.5 to
5 kg N/ha/yr, colimitation of N and P was observed, while at N deposition above
5 kg N/ha/yr, the lakes were P limited. Based on the study findings and paleolimnological
evidence, the authors suggested that most lakes in the northern hemisphere may have
originally been N limited and that atmospheric N deposition has changed the balance of
N and P in lakes.
Consistent with the 2008 ISA findings, research literature after 2007 indicates that N
deposition is correlated to a shift from N to P limitation in certain high elevation water
bodies. Elser et al. (2009b) conducted a nutrient limitation study across a gradient of
lakes in the Rocky Mountains of Colorado that receive low (<2 kg N/ha/yr, N = 20) and
high (>6 kg N/ha/yr, N = 16) N deposition. Nutrient enrichment bioassays indicated that
P limitation or colimitation was prevalent in the population of high-deposition lakes (9 of
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1 16 lakes) while only one of the lakes showed N limitation. In contrast, only 4 of 20
2 low-deposition lakes showed P limitation. The relative response ratio (RR; chlorophyll
3 concentration in a given treatment normalized to chlorophyll in control) of N and P
4 (RR-N:RR-P) was 0.73 in high-deposition lakes (indicative of a greater P response) and
5 1.23 in low-deposition lakes where N limitation was stronger (Figure 9-3). This data was
6 included in Elser et al. (2009a) who reported that lakes in Norway, Sweden, and
7 Colorado affected by N deposition showed a similar pattern. In high-N-deposition lakes,
8 phytoplankton was predominately P limited, while N limitation was more common in
9 low-N-deposition lakes.
CL
CL
CC
CC
P< 0.02
P < 0.06
P < 0.03
.00 —-
0.75-
Low
High Low
Atmospheric N deposition
High
N = nitrogen; P = phosphorus.
The response ratio (RR) has no units. (A) Response to P enrichment alone (RR-P); (B) response to N enrichment alone (RR-N); (C)
response to combined N and P enrichment (RR-NP); (D) relative response to N vs. P (RR-N/RR-P, equivalent to final chl N/final chl
P). For RR-N/RR-P, a value >1 indicates stronger N limitation while a value <1 indicates stronger P limitation. Error bars
indicate ± SE. The result of t tests comparing low- and high-deposition means for each parameter are given in each panel [From
Elser et al. (2009b)l.
Figure 9-3 Phytoplankton responses to nitrogen and/or phosphorus
enrichment for Rocky Mountain lakes receiving low or high
atmospheric nitrogen deposition, given as the ratio of final
chlorophyll concentration in the enriched treatment
(+phosphorus, +nitrogen, or +nitrogen + phosphorus) to the
chlorophyll concentration in the unenriched control.
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New evidence for shifts toward P limitation in the northeastern U.S. has become
available since the 2008 ISA. Using lake and foliar chemistry data from a five-state
region of the Northeast (Maine, New Hampshire, Vermont, Massachusetts, Rhode Island,
New York) and from the Adirondack subregion (New York), Crowley et al. (2012) used
N:P mass ratios to evaluate whether P limitation is increasing where N deposition is high.
Dissolved inorganic nitrogen (DIN), total phosphorus (TP), and DIN:TP ratios
(Section 9.2.4) were analyzed for 331 lake points in the northeastern U.S. and for a subset
of those points comprising 43 lakes in the Adirondack subregion. At the subregional scale
of the Adirondacks, there was a positive relationship between lake DIN: TP ratio and N
deposition. This pattern of increasing P limitation with increasing N deposition in the
Adirondack subregion was also evident in foliar N:P ratio from seven tree species
examined in the same study. Tree and lake data did not support a transition from N
toward P limitation for the entire five-state region, but that shift was supported for the
Adirondack subregion.
Based on an analysis of lake water chemistry data from 106 alpine lakes in Sweden,
Slovakia, Poland and the Rocky Mountains of Colorado and nutrient bioassays from high
mountain lakes in Sweden and the Rocky Mountains of Colorado, Bergstrom (2010)
identified a threshold for the shift of lake response from N limitation to P limitation.
When DIN:TP ratios increased from 1.5 to 3.4, the phytoplankton moved from clear N to
clear P limitation. The majority of the lakes were N limited and the shift from N to P
limitation was strongly affected by N deposition.
N-deposition gradient studies conducted in Sweden support findings of shifts from N to P
limitation in lakes. Liess et al. (2009) observed that increased atmospheric N deposition
was positively correlated with total N across a north to south gradient. In the sampled
lakes, northern lakes received 2 to 6 kg N/ha/yr while southern lakes received 10 to
12 kg N/ha/yr. Sampling of epilithic communities indicated a weakly positive correlation
of atmospheric N deposition to epilithon N:P ratios, suggesting that epilithic communities
were generally more N limited in the northern lakes and more P limited in the southern
lakes, which received higher N deposition. Bergstrom et al. (2008) concluded that N
limitation of phytoplankton was prevalent under conditions of low atmospheric N
deposition, based on lake sampling and in situ nutrient enrichment experiments. In the
southern part of the gradient where atmospheric N deposition and DIN inputs from runoff
were higher, P limitation was observed during a relatively short period in the early
summer. Later in the summer when the DIN was lower in the lakes, P limitation in these
systems switched to dual and colimitation of N and P, and to N limitation.
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9.1.5
Inconclusive Studies on Nutrient Limitation Shift in High Alpine Lakes
In an assessment of 29 alpine lakes and ponds in the Canadian Rocky Mountains (Banff
National Park, Alberta and Yoho National Park, British Columbia) certain ponds
appeared N limited while most water bodies sampled did not show evidence of N
limitation (Murphy et al.. 2010). DIN:TP ratio analysis indicated N limitation in only
14% of the sampled water bodies. N limitation was observed more frequently in shallow
ponds than lakes, and during the late summer sampling period, the ponds had a
significantly lower mean DIN:TP ratio.
In another study from the Rocky Mountains, surface sediment samples and surface water
N03 concentrations were collected from an N deposition gradient (1 to 3.2 kg Nr/ha/yr
in wet deposition) across 46 high-elevation lakes to characterize diatom community
changes (Arnett et al.. 2012). The researchers found that even in lakes with NO,
concentrations below quantification (<1 (ig/L), diatom assemblages were already
dominated by key indicator species characteristic of moderate N enrichment, and the
authors were unable to identify a threshold. They noted that small inputs of reactive N
can shift diatom species composition along the length of the NOs, gradient and that they
switch from N limited oligotrophy to P limitation.
In a study of 11 lakes in northern subarctic Sweden situated along an altitudinal/climate
gradient with low N deposition (<1 kg N/ha/yr) the lakes did not show a shift from
mainly N to mainly P limitation reported from U.S. lakes where N deposition was higher.
However, mainly P limitation was observed in high alpine lakes with rocky catchments
and high DIN:TP ratios, while mainly N and NP colimitation was occurring in subalpine
and lower mid-alpine lakes (Bergstrom et al.. 2013). The authors attributed these
observations to climate and catchment characteristics and suggested warming would have
a greater impact than N deposition on the subset of sparsely vegetated high alpine lakes,
in contrast to the majority of subarctic lakes with N or NP colimitation, where both
warming and N inputs will alter phytoplankton response.
9.2 Biological Indicators
Biological indicators of freshwater N enrichment discussed in the 2008 ISA included
chlorophyll a, phytoplankton biomass, periphyton biomass, and indices of trophic status
(U.S. EPA. 2008a). Paleolimnological records of shifts in diatom community
composition were also used to assess the effects of N deposition. These same biological
indicators are discussed further below along with new studies. Additional indicators ofN
effects on productivity in freshwater systems in the 2008 ISA included water clarity and
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chemical indicators of freshwater nutrient enrichment discussed in the Aquatic
Biogeochemistry chapter (Chapter 7). In the current review, response of microbial
enzymes to N and P and increased incidence of harmful algal blooms (HABs) in
freshwater habitats are discussed as possible biological indicators of the effects of
elevated N. Dose-response relationships between N and biological indicators were
reported in the 2008 ISA and new literature continues to support these findings.
9.2.1 Chlorophyll a
The concentration of chlorophyll a, a pigment present in all photosynthetic organisms, is
a common measure of algal productivity and is hence an easily documented biological
indicator of change in aquatic ecosystem productivity. Quantification of chlorophyll a is
one approach for estimating phytoplankton biomass. Chlorophyll a is used as the primary
indicator of trophic status in the U.S. EPA National Lakes Assessment and as a water
quality indicator in many state and federal monitoring programs (U.S. EPA. 200%).
Surveys and fertilization experiments reported in the 2008 ISA show increased inorganic
N concentration and aquatic ecosystem productivity, as quantified by chlorophyll a
concentration, to be strongly related (U.S. EPA. 2008a'). At the time of the 2008 ISA,
increases in lake phytoplankton biomass (as chlorophyll a) with increasing N deposition
were reported in several regions, including the Snowy Range in Wyoming (Lafrancois et
al.. 2003b) and across Europe (Bergstrom and Jansson. 2006). A meta-analysis of
enrichment bioassays in 62 freshwater lakes of North America reported in the 2008 ISA
found algal growth enhancement from N amendments to be common in slightly less than
half the studies (Elseret al.. 1990). There was a mean increase in phytoplankton biomass
of 79% in response to N enrichment (Elseret al.. 1990)1. This meta-analysis was
repeated, incorporating study sites from multiple countries and a much larger data set,
with similar results (Elseret al.. 2007).
Chlorophyll a continues to be a common biological indicator of N nutrient enrichment in
the research literature from 2008 to present. In the western U.S., Elser et al. (2009b)
examined chlorophyll a response in Rocky Mountain, Colorado lakes where atmospheric
deposition ranged from 2 to 7 kg N/ha/yr. Concentrations of chlorophyll were 2 to
2.5 times greater in high-deposition lakes relative to low-deposition lakes. In another
study in Colorado's Front Range in Green Lake Valley (part of the Niwot Ridge Long-
Term Ecological Research Project), Green Lake 4, a well-studied lake in the area, was
sampled weekly throughout the summer ice-free period to assess chlorophyll response
(Gardner et al.. 2008). Epilimnetic chlorophyll a concentrations peaked at 4 (ig/L in late
July. In the same study, NO;, addition to an in situ mesocosm on the lake (930 (ig/L
NOs . for a final exposure of 1,240 (ig/L NOs, given background concentrations) did not
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increase algal biomass significantly in comparison with the control, while phytoplankton
chlorophyll a increased in P and P + NOs additions, indicating the lake was P limited
during the summer.
Chlorophyll a can also be used as a bioindicator of lake response over decadal and longer
periods. Hundev et al. (2014) took sediment cores from six remote alpine lakes in Utah to
assess trends in lake productivity. In five of the six lakes, sedimentary chlorophyll a and
percentage of organic matter was observed to be relatively constant from the beginning of
the record (mid-1800s using 210Pb dating, 1200 to 1800 estimated by linear regression)
until 1940-1960 when lake production progressively increased.
As reported in the 2008 ISA and discussed further in Chapter 7. dissolved organic carbon
(DOC) is increasing in U.S. surface waters (Monteith et al. 2007; Evans et al.. 2006).
DOC affects acidity and N cycling (Chapter 7). A recent study indicated different
phytoplankton responses to N and dissolved organic matter (DOM) inputs depending
upon nutrient status of the lakes and background DOC. Daggett et al. (2015) selected a
low DOC, N and P colimited water body (Jordan Pond in Acadia National Park, Maine)
and an N limited lake with higher DOC (Sargent Lake in Isle Royale National Park,
Michigan) to assess the effects of an N gradient on algal biomass following addition of
DOM. Both of these Class I areas have a similar N deposition rates (6-7 kg total
inorganic N/ha/yr wet deposition). DOM addition stimulated phytoplankton biomass in
both lakes regardless of nutrient limitation or background DOC concentration.
Phytoplankton biomass in N limited Sargent Lake increased with both N and DOM
inputs, while in N and P colimited Jordan Pond, algae were sensitive primarily to DOM
addition.
Not all studies have shown a positive relationship between N inputs and increased
chlorophyll a. In the Canadian Rockies, Murphy et al. (2010) performed nutrient
enrichment bioassays on 29 Banff and Yoho National Park water bodies using 1 mg N/L
additions. They found that N amendment did not significantly increase final total
phytoplankton chlorophyll concentration across all of the water bodies sampled during
either early or late summer 2007. Although phytoplankton collected from ponds showed
several responses to nutrient amendment, the effect of N on total chlorophyll did not
differ significantly between pond and lake communities. Harvested final total chlorophyll
concentrations from the bioassays were significantly higher for ponds than lakes. In water
bodies in Wapusk National Park, Manitoba, a significant linear relationship occurred
between chlorophyll a and TP across all ponds but not between chlorophyll a and total N
[TN (Svmons et al.. 2012)1.
Chlorophyll a is being used as an indicator of nutrient enrichment in U.S. EPA's National
Nutrient Program KU.S. EPA. 1998b); Section 7.2.61 The U.S. EPA is working with the
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states to develop numeric nutrient criteria to better define levels ofN and P that affect
U.S. waters. The numeric values include both causative (N and P) and response
(chlorophyll a, turbidity) variables to assess eutrophic conditions. The U.S. EPA's
National Nutrient Program to reduce eutrophication in water bodies developed
recommended nutrient criteria for rivers and streams in 14 ecoregions of the U.S. for the
states to use as a starting point for states to develop their own criteria (U.S. EPA. 1998b).
Atmospheric deposition as a source of N may represent a potential target in such
remediation approaches as Total Maximum Daily Load (TMDL), nutrient budgets, and
allocations.
In addition to studies in North America, Bergstrom et al. (2008) sampled lakes across a
gradient of N deposition in Sweden from 100 to 1,000 kg N/km2/yr (1 to 10 kg N/ha/yr)
from Region 1 in the south to Region 4 in the north (12 lakes per region) during the
summers of 2004 to 2006. They observed that the phytoplankton biomass (expressed as
chlorophyll a) was generally low, with the mean decreasing from Region 1 to Region 4
(from 3.7 to 1.6 (ig/L). In regions with higher atmospheric deposition of N,
phytoplankton biomass was higher per unit P as reflected in the mean ratio of chl a:TP,
which decreased by a factor of about 2.4 from Region 1 to Region 4.
9.2.2 Periphyton/Microbial Biomass
Periphyton mats are biofilms of algae, cyanobacteria, fungi, microinvertebrates, organic
detritus, inorganic particles, and heterotrophic microbes imbedded within a matrix and
attached to submerged substrates in aquatic systems (e.g., stream or lake bottoms). In the
2008 ISA, no studies reported resource requirements for periphyton, although several
papers described stimulated growth with N amendments in ecosystems throughout the
U.S. (Annex C of the 2008 ISA), including streams in Alaska, Arizona, Iowa, Texas,
Minnesota, and Missouri, and lakes in California, Colorado, and Massachusetts (U.S.
EPA. 2008a'). Additional lake bioassay experiments that enriched the water column down
into the sediments found enhancement of periphyton growth on bioassay container walls
in experiments in California, Wyoming, and Massachusetts (Smith and Lee. 2006;
Nvdick et al.. 2004; Axler and Reuter. 1996). Strong N limitation of benthic algae has
also been inferred in streams of Arizona (Grimm and Fisher. 1986). California (Hill and
Knight. 1988). Missouri (Lohman et al.. 1991). and Montana (Lohman and Priscu. 1992).
Since the 2008 ISA, few studies on N effects on periphyton biomass have been identified.
In Ditch Creek, Wyoming, a relatively undisturbed stream with N accumulation primarily
from high N2 fixation, biofilm growth on rocks increased after snowmelt and N2 fixers
dominated the algal assemblage (kunza and Hall. 2014). A shift to non-N; fixing taxa
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was observed later in the season. In this stream with little to no anthropogenic influence,
N fixation was higher than denitrification. Burrows et al. (2015) assessed microbial
respiration and biomass using nutrient-diffusing substrata in 20 boreal streams in
Sweden. An increase in N availability led to increased microbial activity. Microbial
biomass was primarily N limited, and distinct microbial communities were associated
with inorganic N in stream water.
Microbial communities involved in plant litter decomposition in streams have been
shown to be altered by nutrient concentrations. Most studies have examined effects of N
and P in combination. However, Femandes et al. (2014) conducted a series of N addition
studies in microcosms to assess leaf litter decomposition with increasing N concentration
and temperature in streams. In general, increased temperature led to an increase in
decomposer activity and a decrease in the amount of N needed. Dunck et al. (2015)
reported decreased primary production and leaf litter decomposition in highly eutrophic
streams and streams with little human influence compared to streams that were
intermediate along the trophic gradient.
9.2.3 Diatoms
Diatoms are commonly used for monitoring of environmental conditions in water bodies
overtime. Changes in diatom species assemblages in paleolimnological studies of
mountain lakes disturbed only by atmospheric deposition and climate change were
reported in the 2008 ISA. Chlorophytes, such as Asterionella formosa and Fragilaria
crotonensis, generally prefer high concentrations of N and are able to rapidly dominate
the flora when N concentrations increase ("U.S. EPA. 2008a; Findlav et al.. 1999). These
two nitrophilous species of diatom are used as biological indicators of N impact in water
bodies. Table 9-1 summarizes diatom studies published since the 2008 ISA. The majority
of those studies highlight the observed influence of 20th century N deposition on
diatoms, with increasing nitrophilous diatoms such as A. formosa and F. crotonensis.
Section 93 considers effects of N deposition on diatom biodiversity. Thresholds of
diatom response are reported in Section 9.7.
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Table 9-1 Summary of studies using diatoms as biological indicators of nitrogen enrichment evaluated in the
literature since the 2008 Integrated Science Assessment for Oxides of Nitrogen and Sulfur-
Ecological Criteria.
Study Site
Ambient N Deposition
Diatom Response
Species
Reference
Three national parks 0.25 ±0.15 to
in Washington State 1.10 ± 0.21 kg/ha/yr
(Mt. Rainier, North
Cascades, and
Olympic)
NH4+-N; 0.34 ± 0.04 to
1.32 ± 0.19 kg/ha/yr NOs"
N; 0.59 ± 0.07 to
2.42 ± 0.27 kg/ha/yr
inorganic N
Overall, only one lake (Hoh Lake) of 10 study lakes where cores
were collected showed clear evidence of impacts from N
deposition based on changes in sediment diatom communities.
A. formosa, F.
crotonensis. And F.
ten era
Sheiblev et al.
(2014)
Western U.S.
(Glacial National
Park, Greater
Yellowstone
Ecosystem, and
eastern Sierra
Nevada)
Sierra Nevada = 2 kg/ha/yr
(current) to 4 kg/ha/yr (early
1990s) total wet inorganic N
deposition.
GNP = 0.5-1.5 kg/ha/yr
(1980-2006).
GYE = 0.5-1.1 kg/ha/yr
(1980-2006)
A critical load of 1.4 kg N/ha/yrwet deposition changed diatom
community structure in both the eastern Sierra Nevada and the
Greater Yellowstone Ecosystem although N deposition rates
between the two regions and timing of diatom community shifts
were different. No diatom community changes were observed in
Glacier National Park lakes.
A. formosa and F.
crotonesis
Saros et al. (2011)
Rocky Mountains
Central Rockies NO3 and
NhU+ = 1.4-2.5 kg Nr/ha/yr.
N. Rockies =
2.0-3.4 kg Nr/ha/yr.
Lakes fed by snowpack meltwater had greater sediment diatom
taxonomic richness over the last century (35 to 54 taxa)
compared to lakes that were fed by both glacial and snowpack
meltwater (12 to 26 taxa) which are higher in NO3".
(-50% of Glacier National Park lakes and ~ 0-20% of lakes in
central Rockies receive glacial meltwater).
Multiple
Saros et al. (2010)
Rocky Mountains
Wet deposition ranged from
0.8 to 3.2 kg N/ha/yr at
study sites.
High abundance of key indicator species of N enrichment (A.
formosa, F. crotonensis) in lakes with low to moderate NO3"
precluded an attempt to quantify the surface water NO3"
concentrations that elicit diatom community changes in
high-elevation lakes using a diatom-based transfer function.
Multiple
Arnett et al. (2012)
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Table 9-1 (Continued): Summary of studies using diatoms as biological indicators of nitrogen enrichment
evaluated in the literature since the 2008 Integrated Science Assessment for Oxides of
Nitrogen and Sulfur-Ecological Criteria.
Study Site
Ambient N Deposition
Diatom Response
Species
Reference
Rocky Mountains
>3 kg N/ha/yr
A maximum growth rate of 0.2 ± 0.04/day at 0.5 |jM N for the
diatom A. formosa was measured following N addition to identify a
NO3" threshold for this species in surface water.
A. formosa
Nanus et al. (2012)
Central Rocky
Mountains Beartooth
Mountains located
along the Montana
and Wyoming
borders
Not specified
Fossil-diatom assemblages from two lakes near each other (one
snowpack-fed and one glacial-fed) indicated greater diatom
assemblage turnover in the glacier-fed lake. The glacier-fed lake
showed evidence for mild N enrichment starting approximately
1,000 years ago, and the increase in abundances of A. formosa
and F. crotonensis occurred much earlier suggesting glacial
meltwater was a source of N.
A. formosa and F.
crotonensis
Slemmons et al.
(2015)
Central Rocky
Mountains Beartooth
Mountains located
along the Montana
and Wyoming
borders
Not specified
Diatom species richness from the top of sediment cores was 1,8x
higher in snowpack-fed lakes compared with glacial and
snowpack-fed lakes, whereas richness did not differ between core
bottoms (ca. 1850) of the lakes. Compared with snow-fed lakes, N
enriched glacial snowpack-fed lakes were dominated by A.
formosa and F. crotonensis.
A. formosa and F.
crotonensis
Slemmons and
Saros (2012)
Grand Teton
National Park
Estimated at 2.5 kg N/ha/yr
Directional change in benthic diatom assemblages after 1960 that
is correlated with atmospheric deposition.
Benthic diatoms
Spauldina et al.
(2015)
Uinta Mountains,
Utah
0.02-0.04 kg km2
Four of five lakes with recent increase in productivity (between
1940 and 1960) show comparable shifts in diatom community
composition linked to atmospheric deposition of N and P. Lake
sediment records show an increasing abundance of nitrophilous
A. formosa.
Asterionella
formosa
Hundev et al.
(2014)
U.S.
Not specified
Shifts in diatom community composition away from N intolerant Multiple
species.
Pardo et al. (2011a)
North America and
Greenland
0.8 to 2 (<50°N) to <0.5
(>50°N)
A meta-analysis of 52 alpine, Arctic, and boreal montane lakes
showed increased beta diversity in the 20th century. Observed
diatom assemblage turnover in alpine and Arctic lakes is related
to temperature changes, while in mid-latitude alpine lakes
changes are linked to N deposition.
Multiple
Hobbs et al. (2010)
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Table 9-1 (Continued): Summary of studies using diatoms as biological indicators of nitrogen enrichment
evaluated in the literature since the 2008 Integrated Science Assessment for Oxides of
Nitrogen and Sulfur-Ecological Criteria.
Study Site
Ambient N Deposition
Diatom Response
Species
Reference
Baptiste Lake,
Alberta, Canada
Not specified
Lake sediment cores indicate prevalence of diatom assemblages
that favor nutrient-rich conditions for at least the last 150 years.
From -1980 to present, a distinct increase in Stephanodiscus
hantzschii was observed.
Multiple
Adams et al. (2014)
Whitefish Bay,
Ontario, Canada,
also meta-analysis of
200 lakes in North
America and Europe
<5 to <1 kg N/ha/yr
No effects of N deposition observed on diatom community
structure in Whitefish Bay, Observed shifts in Arctic lakes (1850)
and temperate lakes (1970) were in response to climate change.
Multiple planktonic
and benthic
diatoms
Ruhland et al.
(2008)
Ha = hectare; kg = kilogram; km = kilometer; |jM = micromole; N = nitrogen; NH4+-N = nitrogen as ammonium; N03 = nitrate; P = phosphorus; yr = year.
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9.2.4
Trophic Status Indices
Trophic status is a way of characterizing bodies of water in terms of their productivity.
Nutritional responses of aquatic ecosystems to atmospheric N deposition are heavily
dependent on surface water P concentrations. Thus, various chemical ratios of N to P can
be useful as indices of trophic status, especially in evaluating eutrophication potential.
Algal species have different nutrient optima for growth and cellular uptake of N, and P
alters the elemental composition of primary producers at the base of the freshwater food
chain. Freshwater trophic status indices in the 2008 ISA included ratios of total N to total
P (TN:TP), DIN:TP, dissolved inorganic N to total dissolved P (DIN:TDP), dissolved
inorganic N to soluble reactive P (DIN:RP), and dissolved inorganic N to the ratio of
chlorophyll a to total P [DIN:(chl a:TP) (U.S. EPA. 2008a)l. In studies reviewed in the
2008 ISA, algal growth was reported to be limited at DIN:TP ratios between about 5 and
20 (Bergstrom and Jansson. 2006; Downing and McCaulev. 1992; Morris and Lewis.
1988; Grimm and Fisher. 1986; Schindler. 1980). When DIN:TP values are greater than
reference values, growth stimulation, N and P colimitation, or P limitation commonly
occur (Sickman et al.. 2003).
Studies published since the 2008 ISA have continued to evaluate eutrophication potential
of water bodies by characterizing nutrient relationships (Table 9-2). Several studies in
Section 9.1.4 published since the 2008 ISA use DIN:TP ratios to show shifts in nutrient
regime from N limitation to P limitation in high elevation lakes (Bergstrom. 2010; Elser
et al.. 2009b; Elser et al.. 2009a). Bergstrom identified a threshold using DIN:TP ratios
for lake response to phytoplankton; DIN:TP of 1.5 was indicative of an N limited lake
while a ratio of 3.4 was clearly P limited. In Green Lake in Colorado's Front Range, the
ratio of DIN: TP in the epilimnion over the course of the study was consistently above 4
and averaged 16.3 ± 2.76 suggesting the lake was P limited (Gardner et al.. 2008).
Crowley et al. (2012) used N:P and DIN: TP in a regional analysis of nutrient limitation in
Adirondack lakes. A series of nutrient addition experiments were performed on samples
collected from 21 lakes and ponds in Wapusk National Park, Canada located in the
Hudson Bay lowland to identify whether these systems were N or P limited (Svmons et
al.. 2012). In the survey, 38% of lakes were not N or P limited, 26% were colimited, 26%
were P limited and 13% were N limited. Nutrient ratios (TN:TP, DIN:TP, and NO, :TP)
were compared to nutrient bioassays to evaluate the use of these ratios in predicting the
limiting nutrient. There was agreement in 29% of bioassay results, suggesting nutrient
ratios are not the best predictor of nutrient limitation in this subarctic region. Liess et al.
(2009) compared a population of lakes in northern Sweden with lower N deposition
(N= 7) to lakes in the South with higher deposition (N= 6). Significantly lower epilithic
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N:P ratios were reported for northern Sweden lakes corresponding to lower deposition in
that region. Lakes in the north were generally more N limited compared to lakes in the
South. Atmospheric N deposition showed a strong positive correlation with TN.
Hundev et al. (2014) assessed trophic status for six remote alpine lakes in the Uinta
Mountains, Utah based on TP, TN, chlorophyll a, Secchi depth, and N:P relationships.
One of six lakes was P limited, two were N limited, one varied by month, and the
limitation was uncertain in the other two. Nutrient status was difficult to determine in
some of the lakes because the ratios were values that could indicate either N or P
limitation depending on the threshold used, and some lakes were on the boundary
between oligotrophic and mesotrophic.
In a comparison of diatom-inferred lake nutrient records and surface water monitoring
data (collected since the early 1980s) from Baptiste Lake in the Canadian Rockies,
Adams et al. (2014) found Total Kjehldahl Nitrogen (TKN) was a significant predictor of
chlorophyll a, where chlorophyll a was independent of TP. They observed that the lake
experienced eutrophic conditions for >150 years based on diatom sediment core data.
Diatom- inferred TKN data tracked current TKN dynamics measured in the water
column.
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Table 9-2 Summary of additional evidence for nitrogen limitation on productivity of freshwater ecosystems
that has been evaluated since the 2008 Integrated Science Assessment for Oxides of Nitrogen and
Sulfur-Ecological Criteria.
Region
N Deposition
N Addition
Biological Effects
Reference
Rocky Mountains, 2-7 kg N/ha
Colorado
None
Atmospheric N deposition increased the stoichiometric ratio of N and Elser et al. (2009a)
P in lakes. Phytoplankton growth in 16 high N deposition lakes (~7 kg
N/ha) was P limited whereas in 20 low-N deposition lakes (~2 kg
N/ha) growth was primarily N limited.
Rocky Mountains, High >6 kg N/ha/yr;
Colorado low <2 kg N/ha/yr
(NADP)
Enrichment of
7.5 pmol/L N (as
NH4NO3) for N, there
was also a P and
N + P treatment
Phytoplankton response to increased inputs of N was inferred from
chlorophyll changes in bioassay data from 20 low-N-deposition lakes
and 16 high-N-deposition lakes. Concentrations of chlorophyll and
seston C were 2-2.5 times higher in high-N-deposition relative to
low-N-deposition lakes, while high-deposition lakes also had higher
seston C:N and C:P (but not N:P) ratios.
Elser et al. (2009b)
Rocky Mountains, Not specified
Colorado
Added 930 pg/L NOs";
with background,
exposure was
1,240 pg NO3"; added
93 pg/L TDP
In in situ mesocosm experiments with water from Green Lake 4,
chlorophyll a did not increase significantly with addition of NO3" in
comparison with the control, while P and N + P treatments resulted in
increases.
Gardner et al. (2008)
Utah
Not specified
None
Using sediment core data from six remote alpine lakes, chl a and
percentage of organic matter are relatively constant from the
beginning of the record until 1940-1960 in five of six lakes, when
production progressively increased. The authors found limiting
nutrient difficult to identify.
Hundev et al. (2014)
Alberta, Canada Not specified
None
TKN was a significant predictor of chl a in Baptiste Lake where chl a
was independent of TP measured in the water column.
Adams et al. (2014)
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Table 9-2 (Continued): Summary of additional evidence for nitrogen limitation on productivity of freshwater
ecosystems that has been evaluated since the 2008 Integrated Science Assessment for
Oxides of Nitrogen and Sulfur-Ecological Criteria.
Region
N Deposition
N Addition
Biological Effects
Reference
Wapusk National
Park, Canada
Not specified
N (NH4NO3) and P
(KH2PO4) were added
to increase the
nutrient concentrations
by 10 times mean
ambient
concentrations
Nutrient enrichment bioassays were conducted on water samples
from 21 lakes and ponds with chl a concentrations from 1.2 to 10.8
|jg/L. In total, 13% of the lakes and ponds were found to be N limited, Svmons et al. (2012)
26% P limited, 26% colimited, and 38% did not respond to either N or
P additions.
Sweden
Gradient rates of N
dep. Ranging from 100
to 1,000 kg N/km2/yr in
4 regions during
summers of
2004-2006
N: 1 mg/L and/or the
concentrations of P by
100 |jg/L (molar N:P
ratio, 23:1)
Phytoplankton were N limited in northern lakes (low N deposition),
while in the southern lakes higher N deposition was accompanied by
increased lake DIN concentrations and a switch from N to P
limitation. N limitation was common during the summer. As summer
progressed, P limitation in these systems switched to duel and
colimitation of N and P, and to N limitation, due to exhaustion of DIN
pool in the lakes.
Berqstrom et al.
(2008)
Sweden
<1 kg N/ha/yr
Nutrients were added
to increase [N] as
NH4NO3 by 100 |jg/L
(7.2 pmol/L) and/or [P]
as KH2PO4 by 10 pg/L
(0.3 pmol/L)
In phytoplankton nutrient addition bioassays using water from
high-altitude lakes, phytoplankton was subject to P limitation, and
became increasingly N and NP colimited at lower altitude.
Chlorophyll concentrations in the bioassays were lower with
increasing altitude, and this pattern held over the whole growing
season.
Berqstrom et al.
(2013)
Sweden
2 to 12 kg/ha/yr
None
N deposition positively related to total N and total P. Highest
proportion of N fixing cyanobacteria (although only consisting of 5%
of the algal biovolume) found where N deposition was lowest.
Liess et al. (2009)
C = carbon; KH2P04 = monopotassium phosphate; N = nitrogen; NADP = National Atmospheric Deposition Program; NH4NO3 = ammonium nitrate; N03 = nitrate; P = phosphorus;
TDP = total dissolved phosphorus; TKN = Total Kjehldahl Nitrogen; TP = total phosphorus.
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9.2.5
Potential Biological Indicators
9.2.5.1 Harmful Algal Blooms
Freshwater HAB formation has become more prevalent in the U.S. in recent decades
(Lopez et al.. 2008). coinciding with increased N in surface waters. Although risk of
bloom formation remains low for high-elevation oligotrophic water bodies with
atmospheric N as the dominant source, atmospheric N may combine with other sources to
contribute to total N loading in downstream lacustrine and riverine systems. Freshwater
HABs can affect taste and odor of drinking water, lead to hypoxic conditions, impact
recreational uses of surface waters, and produce toxins harmful to humans, domestic
animals, and wildlife (Lopez et al.. 2008). The major harmful algal group in freshwater
environments are the cyanobacteria (blue-green algae). Cyanobacterial toxins are
produced by several genera including Microcystis, Anabaena, Nodularia,
Aphanizomenon, Cylindrospermopsis, and Oscillatoria. The mechanism of action of
these toxins can be hepatotoxic, such as cylindrospermopsins and microcystins;
neurotoxic, such as anatoxins and saxitoxins; or dermatoxic.
Evidence for a role for N in harmful algal blooms includes water bodies across the U.S.
In western Lake Erie, cyanobacterial growth was N limited during bloom conditions in
late summer and the N fixing cyanobacterium Anabaena become dominant following the
observed N limitation (Chaffin et al. 2013). In a survey of eutrophic midcontinent lakes,
microcystins (common cyanobacterial toxins associated with HABs), were detected in all
blooms (Graham et al.. 2010). In another U.S. survey, TN was strongly correlated to
microcystin concentration in lakes and reservoirs (Beaver et al.. 2014). The highest
cyanobacteria abundance was observed in the Midwest where agriculture is a dominant
land use, and TN concentrations are higher. Yuan et al. (2014) modeled a threshold for
probability of occurrence of Microcystis, a common non-N2-fixing cyanobacterial genera,
using data from the U.S. EPA National Lakes Assessment (U.S. EPA. 2009b). In their
analysis, the frequency of occurrence of high microcystin concentrations depended most
strongly on TN, with weaker associations to chlorophyll a. The calculated threshold is
based on the range of possible combinations of TN and chlorophyll a and the World
Health Organization drinking water provisional guideline for microcystin of 1 |ag/L
(WHO. 1998). The recommended threshold ranges to protect against frequency of
occurrence of high microcystin concentrations (0.1 MC < 1 (.ig/L) were 570 or
1,100 (ig/L TN paired with chlorophyll a concentrations of 37 and 3 (ig/L, respectively
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(Yuan et al.. 2014). Decreasing the frequency of microcystin occurrence to 5% gave TN
concentrations of 250 or 400 (ig/L paired with chlorophyll a concentrations of 14 and
1 |_ig/L. The U.S. EPA has recently provided health advisories on allowable limits of
0.3 (ig/L microcystins and 0.7 (ig/L cylindrospermopsin in drinking water over a 10-day
exposure period (U.S. EPA. 2015a. b).
Since the 2008 ISA, additional studies have indicated that the availability and form of N
influences algal bloom composition, and inputs of inorganic N selectively favor HAB
species. A recent bloom in Lake Okeechobee in Florida was dominated by Microcystis,
which depends on DIN for growth (Paerl and Scott. 2010). In nutrient amendment
experiments with water collected from Lake Agawam in New York, abundances of toxic
strains of Microcystis were enhanced more than nontoxic strains by inorganic N while
nontoxic strains responded to organic N more frequently than inorganic N (Davis et al..
2010). Microcystis populations were stimulated more frequently by N than by P in the
assays. Similarly, in a series of nutrient addition experiments using water from Sandusky
Bay, Lake Erie, bloom growth and microcystin concentrations responded more frequently
to addition of inorganic and organic forms of N than to P addition indicating that N inputs
may impact bloom size and toxicity (Davis et al.. 2015). Donald et al. (201 1) reported
differential responses of phytoplankton to various forms ofN in mesocosm experiments
in Wascana Lake, Saskatchewan. In this naturally P rich lake, addition of NH4 and urea
promoted nonheterocystous cyanobacteria and algae, while increased chlorophytes and
some cyanobacteria were observed with NO, and urea. Microcystin production increased
with added N, although the response varied by form of N and predominant algal taxon.
9.2.5.2 Enzymes
A recent study used analysis of enzyme activity to characterize nutrient limitation in
aquatic systems. Microbial enzyme response to changes in N and P was found to vary in
terrestrial and aquatic compartments in Bear Brook Watershed in Maine, the site of a
whole-watershed N enrichment experiment (Mineau et al.. 2014). Stronger effects were
typically observed in aquatic habitats. Although not explicitly the focus of the study, the
authors imply that P limitation is caused by N availability. Since 1989, ammonium
sulfate ([NLLJ2SO4) has been applied bi-monthly to the watershed by helicopter, (25.2 kg
N/ha/yr). Activity of three enzymes (b-1, 4-glucosidase [BG],
b-l,4-N-acetylglucosaminidase [NAG], acid phosphatase [AP]) in soil, leaf litter in both
terrestrial and stream habitats, and in stream biofilms were compared to a reference
watershed. In both terrestrial and aquatic habitats in the Bear Brook Watershed, BG, and
NAG activities were unaffected. Stream biofilms had fivefold higher AP activity while
stream litter had eightfold higher AP activity indicative of enhanced P limitation in the
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treated watershed. Shorter experimental P enrichments were used to characterize
potential P limitation under ambient and elevated N availability. In streams, the effects of
acute P additions were strongest with reduced AP activity and increased BG activity.
9.3 Biodiversity
Increased N deposition to water bodies, either directly, or via N leaching from soils,
increases available nutrients to aquatic biota and alters the balance of N and P. As
reported in the 2008 ISA, differences in resource requirements allow some species to gain
competitive advantage over others upon nutrient addition, causing shifts in freshwater
community composition and biodiversity (Saros et al.. 2005; Lafrancois et al.. 2004;
Wolfe et al.. 2003). Evidence for N effects on biodiversity in phytoplankton,
zooplankton, and macroinvertebrates in the 2008 ISA included observations from
paleolimnological studies, bioassays, mesocosm, and laboratory experiments.
Community shifts and decreased biodiversity of phytoplankton have been described in
multiple studies while fewer studies considered zooplankton. New literature described
below has continued to report the effects of N enrichment on algal biodiversity and
limited evidence at higher trophic levels (Table 9-3).
9.3.1 Phytoplankton Diversity
Survey data, paleolimnological studies, and fertilization experiments in the 2008 ISA
reported species changes and reductions in plankton biodiversity in sensitive high-
elevation lakes in the western U.S. in response to increased availability of N (U.S. EPA.
2008a). Available data reviewed in the 2008 ISA suggest that the increases in total N
deposition do not have to be large to elicit an ecological effect. Interlandi and kilham
(2001) demonstrated that maximum phytoplankton biodiversity was maintained at very
low N levels (<3 (.iM N) in lakes in the Yellowstone National Park region. A hindcasting
exercise determined that a change in Rocky Mountain National Park lake algae occurred
between 1850 and 1964 at only about 1.5 kg N/ha/yr wet N deposition (Baron. 2006).
Similar changes inferred from lake sediment cores of the Beartooth Mountains of
Wyoming also occurred at about 1.5 kg N/ha/yr deposition (Saros et al.. 2003).
Preindustrial inorganic N deposition is estimated to have been only 0.1 to 0.7 kg N/ha/yr
based on measurements from remote parts of the world (Holland et al.. 1999; Galloway et
al.. 1995). In the western U.S., preindustrial, or background, inorganic N deposition was
estimated by Holland et al. (1999) to range from 0.4 to 0.7 kg N/ha/yr.
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Some freshwater algae are particularly sensitive to the effects of added N and experience
shifts in community composition and biodiversity with increased N deposition. A general
shift from chrysophytes that dominate lakes with low N to cyanophytes and chlorophytes
in lakes with higher N has been observed in studies reported in the 2008 ISA (Lafrancois
et al.. 2004; Wolfe et al.. 2003; Jassbv et al.. 1994) and newer studies (Svmons et al..
2012; Pardo etal.. 2011a; Saros et al.. 2010). For example, in phytoplankton sampling
from 21 lakes and ponds in Wapusk National Park, Canada, Svmons et al. (2012)
observed that the N limited lakes had significantly different phytoplankton community
composition with more chrysophytes and Anabaena sp. compared to all other lakes.
Using data from the U.S. Geological Survey National Water Quality Assessment, (Passv.
2008) assessed responses of 2,426 benthic and 383 planktonic diatom communities from
760 and 127 distinct localities, respectively, to nutrient limitation. As more resources
(basic cations, silica, iron, NH3, NO.? . and dissolved P) became limiting, benthic diatom
richness declined while phytoplankton richness increased.
9.3.1.1 Paleolimnological Studies
In the 2008 ISA, changes in diatom species assemblages, increases in cell numbers, and
pigment-inferred increases in whole-lake primary production were reported from
paleolimnological studies of mountain lakes that have only been disturbed by
atmospheric deposition and climate change. Sediment cores in oligotrophic lakes
receiving <5 kg N/ha/yr showed diatom community shifts. As reported in the 2008 ISA
and Section 9.2.3 of this chapter, two opportunistic species of diatom, A. formosa and F.
crotonensis, now dominate the flora of at least several lakes in the Rocky Mountains
(Slemmons et al.. 2015; Arnett et al.. 2012; Saros et al.. 2010; Saros et al.. 2005; Saros et
al.. 2003; Wolfe et al.. 2003; Wolfe et al.. 2001; Interlandi andKilham. 1998). In the
southern Rocky Mountains, this shift had occurred in the 1950s in the south, with more
recent shifts (1970s) in the central region (Baron et al.. 201 lb). In most, but not all, of
these studies the observed responses in phytoplankton were concordant with effects from
increased atmospheric N deposition. In regions where there is no evidence of increased
atmospheric nutrient inputs, warming trends are observed to enhance competitiveness of
planktonic diatoms such as A. formosa, indicating that climate change (Chapter 13) has
significant direct and indirect effects on algal species composition and may enhance
effects observed in areas with nutrient increases (Rtihland et al.. 2015).
Studies available since the 2008 ISA, (summarized here and in Table 9-1) provide
additional evidence from historical records of lake sediments in assessing biological
changes associated with N enrichment over time. Sediment records from lakes in the
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Uinta Mountains, Utah showed shifts in diatom community composition and increasing
abundance of the nitrophilous diatom A. formosa linked to atmospheric deposition
(Hundev et al.. 2014). In sediment core sampling from high-altitude lakes from National
Parks in Washington, Sheiblev et al. (2014) analyzed a total of 56 sediment samples for
diatom presence and abundance over time. In the survey, over 250 diatom species were
identified; however, only Hoh Lake in Olympic National Park showed clear evidence of
impacts from N deposition based on changes in sediment diatom assemblages and
presence of A. formosa, F. crotonensis, and Fragelaria tenera. In high-altitude lakes in
the Rocky Mountains with low atmospheric deposition (<2 kg N/ha/yr) and low to
moderate surface water NO3 (<1 |_ig/L [below detection] to 30 |_ig/L). Arnctt et al. (2012)
observed diatom assemblages were already dominated by nitrophilous species like A.
formosa or F. crotonensis. Because of the abundance of species indicative of moderate N
enrichment even at NO;, concentrations below detection, it was not possible to identify a
threshold of reactive N response for diatom community change. In Baptiste Lake, in
Alberta, Canada, a general shift in diatom assemblages away from N intolerant species
and proliferation of Stephanodiscus hantzschii, a nitrophilus diatom species was observed
(Adams et al.. 2014). Paleolimnological analysis suggests that eutrophic conditions were
present in the lake for at least 150 years.
N deposition was identified as a driver of diatom compositional turnover (or beta
diversity) along with climate change in a synthesis of paleolimnological core samples of
52 Arctic, alpine, and boreal montane lakes in North America and west Greenland
(Hobbs et al.. 2010). The authors state that in all lakes, beta diversity was significantly
greater during the 20th century than the 19th century while there was only a small and
nonsignificant difference in turnover between the 19th century and the 1550-1800
intervals (p = 0.86). Relative to forested montane boreal sites, alpine, and Arctic lakes
reveal greater diatom assemblage turnover in the 20th century. In Arctic lakes,
temperature appears to be the main factor affecting diatom composition turnover, while
in temperate lakes, N deposition appears to play a larger role. A meta-analysis of
200 lakes in Europe and North America showed diatom shifts in Arctic lakes around
1850 and temperate lakes around 1970 (Riihland et al.. 2008). Observed changes were
primarily attributed to warming. The authors examined the diatom record from one lake
in detail (Whitefish Lake in Ontario), and reported that observations of diatom shifts in
this lake were not explained by N deposition but rather corresponded to temperature
changes.
New information on relative NOs inputs from glacial versus snowpack meltwaters
reported in Chapter 7 indicate water of glacial origin has higher NO3 , which may
influence interpretation of biological data from high-altitude lakes and streams
(Slemmons et al.. 2015; Slemmons et al.. 2013; Saros et al.. 2010; Baron et al.. 2009). In
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the central Rockies and Glacier National Park, fossil diatom richness in snowpack-fed
lakes, versus lakes fed by both glacial and snowpack meltwaters, was found to be higher
(Saros et al.. 2010). Diatom taxonomic richness in lakes receiving both glacial and
snowpack meltwaters ranged from 12 to 26 taxa compared to 34 to 54 taxa in
snowpack-fed lakes. In the central Rockies, N deposition was 1.4 to 2.5 kg Nr/ha/yr, and
10 to 20% of lakes receive glacial meltwater. In Glacier National Park in the northern
Rockies, approximately 50% of lakes receive glacial meltwater and deposition was
2.0 to 3.4 kg Nr/ha/yr. In another study comparing sedimentary fossil diatom
assemblages in two lakes next to each other (one glacier-fed and one snow-fed lake) in
the central Rocky Mountains, increased abundances of A. formosa, and F. crotonensis
were observed in the glacial-fed lake starting 1,000 years ago along with a decrease in
diatom species richness (Slcmmons et al.. 2015). These observations suggest increased N
inputs associated with glacial meltwater have altered the fossil algal record and continue
to affect algal communities in glacial-fed lakes.
9.3.1.2 Bioassay, Mesocosm, and Laboratory Studies
Several experimental nutrient additions (mesocosm and bioassay studies) described in
Section 9.1.4 show that N limitation is common in freshwater systems (Elser et al..
2009b; Elser et al.. 2009a; Bergstrom et al.. 2008). Since the 2008 ISA, several N
addition studies have explored the effects of increased nutrients on phytoplankton
biomass and community structure (Daggett et al.. 2015; Gardner et al.. 2008). In the
Colorado Front Range, diatom abundance increased, and phytoplankton species
composition shifted in nutrient-enriched mesocosms (Gardner et al.. 2008). Principal
component analysis suggested that 21% of the variance in phytoplankton community
composition was related to added nutrients, while 34% of the variance was due to
seasonal changes. In a bioassay comparison of phytoplankton community structure
following N and DOM addition to a low DOC and N and P colimited water body (Jordan
Pond in Acadia National Park, Maine) and an N limited lake, (Sargent Lake in Isle
Royale National Park, Michigan) Daggett et al. (2015) observed increased chlorophytes
following DOM inputs in both lakes. In the N limited lake, an increase in F. crotonensis
and Tabellaria flocculosa was observed. There was a reduced response of chlorophytes to
DOM addition when N was added to the N limited lake.
9.3.2 Benthic Algal Diversity
Several recent studies have considered the effects of N on benthic algae characteristic of
shallow lakes and littoral zones. Periphyton is typically more abundant than
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phytoplankton in shallow habitats (Vinebrooke et al.. 2014; Nvdick et al.. 2004). In a
stable isotope tracer study in Bull Trout Lake, a subalpine lake in Idaho, the largest
portion of added N was retained within the periphyton (Epstein et al.. 2012). Responses
of benthic algae to N deposition in high-altitude shallow lakes in Grand Teton National
Park were recently determined using lake sediment cores (Spaulding etal.. 2015).
Although benthic algae are less sensitive to nutrient inputs than planktonic species, the
authors report a directional change in benthic diatom species after 1960 that is correlated
with atmospheric deposition. Liess et al. (2009) conducted a survey of periphyton along
an N deposition gradient (2 to 12 kg N/ha/yr) in Sweden. Benthic algal composition in
lakes in the northern part of the country where N deposition was lower had a higher
contribution from N fixing cyanobacteria (5% of algal biovolume) than in the south.
Overall, lakes were more N limited in the North and P limited in the South. In another
study using nutrient diffusing substrata in two small Alpine lakes in the Rhone Alps,
France, N enriched substrata had a greater phytobenthic biomass, and the taxonomic
composition of the phytobenthos was different between the treatment and control (Lepori
and Robin. 2014). Grazing by macrograzers, such as benthic insects and tadpoles, had the
same effect on the biomass of the phytobenthos regardless of nutrient treatment.
In pond fertilization experiments in 12 Ashless, nonglacial ponds in Snow Pass within the
Cascade Valley catchment of Banff National Park, Alberta, periphyton outcompeted
phytoplankton for limiting nutrients, indicating the importance of considering both
benthic and pelagic primary producers (Vinebrooke et al.. 2014). In these N limited
ponds, phytoplankton biomass increased significantly only when N was applied in the
absence of fairy shrimp. High grazing pressure by fairy shrimp appeared to suppress
effects of added nutrient on algal communities suggesting that trophic interactions are
important to take into account to avoid missing effects of N in alpine waterbodies.
Algal assemblage response following 6-week nutrient amendments in Wyoming streams
indicated that both N and P altered community structure of epilithic biofilm (kunza and
Hall. 2013). Depending upon which nutrient was added, N2 fixers reacted differently than
non-N2 fixers; an increase in non-N2 fixing diatoms in the N and N + P additions was
observed compared to N2 fixer dominance in control and P treatment.
Other studies consider how changes in benthic algal biodiversity affect community
processes such as chemical uptake. NO3 -N uptake differed among benthic algal
assemblages from rocks in a stream in Boise National Forest in central Idaho (Baker et
al.. 2009). Uptake of NO? was highest in the green filamentous algae, (dominated by the
chlorophytes Spirogyra sp. And Rhizoclonium sp.), lowest in the yellow patch type
(dominated by the chlorophytes Spirogyra sp. And Bulbochaete sp.), and intermediate in
the brown patch type (dominated by the diatom including Synedra sp., Cymbella sp.,
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Fragilaria sp. And Epithemia sp.). NO3 -N uptake normalized to chlorophyll a increased
in concert with algal composition and species richness in the three patch types.
9.3.3 Freshwater Invertebrate Diversity
9.3.3.1 Zooplankton
Changes to aquatic food webs in response to N enrichment have not been as thoroughly
explored as changes to algal assemblages, but a few studies in the 2008 ISA showed
declines in zooplankton biomass (Lafrancois et al.. 2004; Paul et al.. 1995) in response to
N related shifts in phytoplankton biomass toward less palatable taxa with higher C:P
ratios (Elser et al.. 2001). New studies provide additional evidence for N deposition
effects to zooplankton through altered trophic interactions.
Nutritional status of zooplankton is influenced by the quantity and quality of food items
(Elser et al.. 2001). In lakes across an N deposition gradient in Norway, zooplankton
feeding on seston (organisms and nonliving matter in the water column) were found to be
affected by P limitation in phytoplankton (Elser et al.. 2010). The seston in lakes with
high N deposition had significantly higher C:P and N:P ratios due to phytoplankton P
limitation. Using an assay to measure alkaline phosphatase activity (APA), which is
overexpressed in animals with dietary P deficiency, Elser et al. (2010) observed that the
biomass-specific APA value differed considerably among taxa and that N deposition was
significantly associated with some species such as seston-feeding zooplankton but not
others, leading the authors to conclude that P limitation was transferred up the food chain.
A taxonomic shift from omnivorous, raptorial-feeding copepods to filter-feeding
herbivorous daphnids was observed with warming and N addition in a growth chamber
experiment (Thompson et al.. 2008). The study was conducted with water and sediment
collected from Pipit Lake in the Canadian Rocky Mountains in Banff National Park,
Alberta. While warming and N fertilization increased phytoplankton abundance,
herbivory by Daphnia middendorffiana decreased but only in the presence of sediment
(pond conditions). Findings demonstrated that the effects of warming and N differ both
among trophic levels and aquatic alpine habitats.
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9.3.3.2
Macroi invertebrates
Macroinvertebrates such as aquatic insects, crustaceans, worms, and mollusks are
commonly sampled to assess water quality in federal and state monitoring programs (U.S.
EPA. 2016d). These organisms feed on algae and organic material and are an important
food source for fish and other wildlife. Few studies have considered the effects of
atmospheric N enrichment on biodiversity of freshwater macroinvertebrates. Due to the
existence of a survey of benthic invertebrates in Lake Tahoe, Nevada conducted in the
1960s, it was possible to assess how the populations have changed with enrichment and
introduction of non-native species. In this high alpine lake, atmospheric N contributions
are a significant portion (approximately 57%) of the total N loading to the lake (Sahoo et
al.. 2013). Caires et al. (2013) resurveyed the lake in 2008-2009 and observed declines of
80 to 100% in endemic benthic invertebrate taxa, and changes to the community structure
of benthic invertebrate assemblages. Corresponding to these changes in lake biota, a
decrease in water clarity over the past 4 decades has been associated with a shift in the
bottom of the euphotic zone (1% light penetration) from 80 to 57 m (Chandra et al..
2005V
A recent study from Denmark suggests that macroinvertebrates may be poor indicators of
N enrichment. Friberg et al. (2010) measured stream macroinvertebrate occurrence along
gradients in organic pollution and eutrophication in 594 streams. They observed that
occurrence of many taxa showed a stronger relationship to habitat condition than to
chemical variables. Overall, macroinvertebrate occurrence appeared to be related
primarily to biological oxygen demand, NH4+-N, and TP rather than TN.
9.3.4 Macrophytes
No U.S. studies of N effects on macrophyte (aquatic plant) community biodiversity in
high elevation lakes and streams were identified in the recent literature, although declines
in total macrophyte occurrence were noted in a resurvey of Lake Tahoe comparing
samples to a lake survey conducted in the 1960s (Caires et al.. 2013). Benthic
invertebrate declines were most severe in sampling sites where macrophytes were present
in the 1960s but now absent, suggesting that macroinvertebrate and macrophyte
assemblages are closely associated in the lake. Barker et al. (2008) conducted a
mesocosm experiment using water and sediment from a stream in Norfork, UK.
Experimental tanks were planted with 11 macrophyte species from the local environment.
Constant P loadings were given to all tanks (50 |_ig P/L). Nitrate loading varied from 1 to
10 mg NO3 -N/L. Macrophyte species richness decreased with increasing N during the
first year of treatment, and decreased in all treatments above 1 mg NO3 -N/L during the
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second year. Barker et al. (2008) estimated a threshold of 1.5 mg N/L for maintaining a
stable species richness.
9.3.5 Amphibians
3 No studies on N enrichment effects on amphibian biodiversity were reviewed in the 2008
4 ISA or identified in the current literature. Toxicity of NO;, to amphibians is considered in
5 Section 9.5.2.
9.3.6 Fish
6 No studies of direct effects of N enrichment on freshwater fish biodiversity were
7 reviewed in the 2008 ISA. Post-2007 literature includes several behavioral endpoints in
8 fish (Section 9.4.1V
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Table 9-3 Summary of studies on nitrogen effects on species composition and biodiversity that have been
evaluated in the literature since the 2008 Integrated Science Assessment for Oxides of Nitrogen and
Sulfur-Ecological Criteria
Region
Endpoint
Deposition
(kg N/ha/yr)
N Addition
Observation
Species
Ecosystem
Type
Reference
Isle Royale Phytoplankton 6-7 kg total 0, 5, 10, 20, or Chlorophytes had a reduced
National Park, community inorganic 40 [jg/L response to DOM addition when N
Michigan and structure N/ha/yr wet was added to the N limited lake
Acadia deposition (Sargent Lake in Isle Royale
National Park. National Park). Increase in
Maine diatoms (F. crotonensis and
Tabellaria flocculosa) with DOM
addition to the lake.
Multiple
Boreal lakes
Daggett et
al. (2015)
Lake Tahoe,
California,
Nevada
Survey
Not specified None
Endemic benthic invertebrate taxa
have declined by 80 to 100%
since a survey of Lake Tahoe was
conducted in the 1960s. Changes
in the density and assemblage
structure of benthic invertebrates
mirrors increases in nutrient
enrichment and non-native
species in the lake. Macrophyte
occurrence has also declined.
Amphipods Stygobromus
lacicolus and S.
tahoensis declined
99.9%
No endemic turbellarians
but abundant in 1960s.
Endemic stonefly, Capnia
lacustra, has decreased
93.5%
Endemic ostracods
(Candona tahoensis)
density decreased 83.4%
Subalpinie,
oligotrophic
lake in
California
Caires et al.
(2013)
Ditch and
Spread Creeks
in Grand Teton
National Park,
Wyoming, and
Spring Creek
near Wilson,
Wyoming
Algal biofilm
assemblage
Not specified
0.5 M NaNOs;
0.5 M KH2PO4;
0.5 NaNOs and
0.5 KH2PO4
Nutrient additions altered algal
biofilm assemblages in the
streams. NO3" addition inhibited
N2 fixer accumulation.
Phytoplankton
Streams
Kunza and
Hall (2013)
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Table 9-3 (Continued): Summary of studies on nitrogen effects on species composition and biodiversity that have
been evaluated in the literature since the 2008 Integrated Science Assessment for Oxides
of Nitrogen and Sulfur-Ecological Criteria.
Region
Endpoint
Deposition
(kg N/ha/yr)
N Addition
Observation
Species
Ecosystem
Type
Reference
Front Range of Phytoplankton Not specified Added 930 |jg/L Diatom abundance increased, and Phytoplankton
the Colorado community NO3"; (with phytoplankton species
Rocky composition background, composition shifted in nutrient-
Mountains exposure was enriched mesocosms Principal
1,240 |jg NO3"; component analysis suggested
added 93 |jg/L that 21 % of the variance in
TDP) phytoplankton community
composition was related to added
nutrients, while 34% of the
variance was due to seasonal
changes.
Alpine lake Gardner et
al. (2008).
12 alpine
Phytoplankton 6.5-2.3 kg
ponds in Banff biomass/
National Park, community
Canadian diversity
Rockies
N/ha/yr
(2000-2010)
Highest levels
(30-90
kg N/ha/yr)
downwind of
urban and
agricultural
sources.
1 mg N/L
30 |jg P/L
Simulating
deposition =
20 kg/ha/yr
Periphyton outcompeted
phytoplankton for limiting nutrients
indicating the importance of
considering both benthic and
pelagic primary producers. High
grazing pressure by fairy shrimp
affected results predicted from
chemical inference and bioassay
results regarding effects of added
nutrients on algal communities.
Phytoplankton n grazers,
(fairy shrimp, Anostraca:
Brachinecta paludosa)
Fishless,
nonglacial
ponds located
above tree
line
Vinebrooke
et al. (2014)
Banff Phytoplankton
National Park, abundance,
Canadian effect on
Rockies zooplankton
1,200 mg/L N
added to aquaria
with and without
sediment
A taxonomic shift from
omnivorous, raptorial-feeding
copepods to more effective filter-
feeding herbivorous daphnids was
observed with warming and N
addition. Warming and N
fertilization increased
phytoplankton abundance while
herbivory by Daphnia decreased
but only in the presence of
sediment. Effects of warming and
N differ both between trophic
levels and aquatic alpine habitats.
Zooplankton: herbivorous Alpine lake
Daphnia middendorffiana
and omnivorous
Hesperodiaptomus
arcticus
Thompson
et al. (2008)
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Table 9-3 (Continued): Summary of studies on nitrogen effects on species composition and biodiversity that have
been evaluated in the literature since the 2008 Integrated Science Assessment for Oxides
of Nitrogen and Sulfur-Ecological Criteria.
Region
Endpoint
Deposition
(kg N/ha/yr)
N Addition
Observation
Species
Ecosystem
Type
Reference
Wapusk
National Park,
Canada
Phytoplankton
abundance,
effect on
zooplankton
Not specified
N (NH4NO3) and
P (KH2PO4) were
added to
increase the
nutrient
concentrations by
10 times mean
ambient
concentrations
N-limited lakes had significantly
different phytoplankton community
composition with more
chrysophytes and Anabaena sp.
compared to all other lakes.
41 phytoplankton taxa
including
Chlamydomonas spp.,
Sphaerocystis spp.,
Diatom a spp. and
Crugienella spp.
Subarctic
lakes and
ponds
Svmons et
al. (2012)
Denmark Macroinvertebr Not specified
ate occurrence
None
Macroinvertebrate communities
did not change significantly with
TN based on analysis of a large
number of concurrent samples of
macroinvertebrate communities
and chemical indicators of
eutrophication and organic
pollution (TP, TN, NH4+-N,
biological oxygen demand
[BOD5]) from 594 Danish stream
sites.
Plecopteran Leuctra Streams
Isopod Asellus aquaticus
Dipteran Chironomus
Friberq et
al. (2010)
French Alps
Phytobenthos 7
species
richness,
grazing
pressure
Nutrient-diffusing A shift in taxonomic composition Diatoms
substrata
N treatment:
N = 113 [jg/N/hr
N + P:
N = 181 [jg/N/hr
P = 13 [jg/P/hr
Alpine lakes
of phytobenthos toward green
algae (less palatable to grazers)
from cyanobacteria and diatoms
was observed with N enrichment.
Benthic grazing by
macroinvertebrates was not
reduced.
Green Algae
Cyanobacteria
Lepori and
Robin
(2014)
DOM = dissolved organic matter; KH2P04 = monopotassium phosphate; N = nitrogen; NaN03 = sodium nitrate; TN = total nitrogen; TDP = total dissolved phosphorus; TP = total
phosphorus.
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9.4
Animal Behavior and Disease
9.4.1 Behavior
Nutrient enrichment of freshwater systems has recently been shown to alter behavioral
endpoints in an invertebrate and a fish species. NO? exposure (21.4, 44.9, 81.8, 156.1
mg NO3/L) was shown to decrease velocity of movement in the aquatic snail
Potamopyrgus antipodarum (Alonso and Camargo. 2013). Reproductive impairments
(decreased number of newborns) were observed at all tested concentrations. The NO3
concentrations used in this study are much higher than typically measured in remote
freshwater catchments affected by atmospheric deposition.
In the three-spined stickleback Gasterosteus aculeatus, a fish that inhabits both
freshwater and brackish habitats, changes to water quality associated with eutrophication
(i.e., turbidity associated with algal blooms) have impacted social and reproductive
behaviors at the individual and population level. These studies are reviewed in Chapter
10.
9.4.2 Disease
The interactions of N enrichment and disease in biota is a relatively new area of research
in N impacted freshwater systems. The interactions characterized to date are complex and
involve indirect effects on host-parasite interactions (Johnson et al.. 2010; Johnson et al..
2007). In a mesocosm experiment with two treatment groups (ambient and elevated
nutrients [N + P]) density of the snail Planorbella trivolvis, a host for the trematode
parasite Ribeiroia ondatrae increased in the elevated nutrient treatment group (Johnson et
al.. 2007). This parasite sequentially infects birds, snails, and amphibian larvae,
frequently causing severe limb deformities and mortality in amphibians. An increase in
the number of parasites produced per snail was also observed in the nutrient treatment.
The increase in host population and number of parasites per snail, in turn, significantly
increased the intensity of infection in green frogs (Rana clamitans). In this study, nutrient
enrichment significantly enhanced periphyton chlorophyll a, snail egg production, and
dry mass of the snail host population. Because both N and P were added, it is not clear if
there was an N effect; however, N has been shown to increase algal production, a
condition conducive for this host-parasite interaction.
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Another host-parasite relationship potentially impacted by increased N to aquatic systems
is that of the fungal pathogen Metschnikowia bicuspidata, which is parasitic to crustacean
zooplankton Daphnia dentifera (Dallas and Drake. 2014). In a series of bioassays
designed to assess effects of N on host and pathogen, D. dentifera were exposed to six
N03 concentrations (0.4, 2, 4, 8, 16, and 32 mg NOs /L) and then inoculated withM
bicuspidata. NCh decreased D. dentifera population size and increased infection
prevalence. Next, ambient level of N (0.4 mg NO, -N/L) and a concentration
representative of a moderately polluted system (12 mg NO, -N/L) were used to test the
influence of NO3 on pathogen dose, infection prevalence, and host fitness (growth and
fecundity). No effects were observed on growth rate of D. dentifera; however, greater
infection prevalence was associated with increased NO, . and in general, host fecundity
and infection intensity both decreased with increasing pathogen dose.
9.5 Nitrate Toxicity
NO, concentrations can increase in surface water due to leaching from terrestrial
systems and biogeochemical cycling following direct deposition of N into water bodies
(Chapter 7). NO, in freshwater at extremely high concentrations can have direct adverse
effects on many lifestages of fish, as well as on invertebrates and amphibians. These
effects occur at levels that are typically more than 30 times higher than those that would
commonly be attributable to atmospheric deposition, and therefore, NO, concentration
was not defined as a primary biological indicator in the 2008 ISA (U.S. EPA. 2008a). In
eastern water bodies from West Virginia to Maine, Aber et al. (2003) identified a
threshold level of atmospheric deposition of approximately 7 to 8 kg N/ha/yr that causes
NO, release into surface water from forested watersheds in the northeastern U.S. Mean
lake N03 in sensitive high-elevation water bodies in the northeast from 1997 to 2006
was 14.4 |_iM L [0.893 mg/L (Baron et al.. 201 lb)l. In the same study, mean lake NO-,
from 1997 to 2006 was lower in western high-elevation lakes, 2.7 (.iM L (0.167 mg/L),
and 3.7 (.iM L (0.229 mg/L), respectively for Sierra Nevada mountain lakes and Rocky
Mountain lakes. High concentrations of stream water NO, have been measured
historically in the Great Smoky Mountains, North Carolina (Cook et al.. 1994) and in
mixed conifer forests in southern California (Fenn and Poth. 1999). New data on NO?
toxicity to macroinvertebrates and vertebrates is described below. Water quality criteria
incorporating NO;, and other N species are discussed in Chapter 7. including the updated
ambient water quality criteria for NH3 based on sensitivity of freshwater mussels.
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9.5.1
Macroin vertebrates
Invertebrate responses to increased nutrient enrichment reported in the 2008 ISA were
primarily NO, toxicity studies. The toxic response thresholds were typically much
higher than levels of N in surface waters that could be attributable to N deposition.
However, several toxicity studies have been conducted on invertebrates since the 2008
ISA in support of the development of water quality criteria for NOs (U.S. EPA. 201 Ob).
A lethal concentration at which 50% of the organisms did not survive (LC50) was
reported. These included 96-hour acute toxicity tests with several species of freshwater
mussels (Lampsilis siliquoidea [LC50 = 357 mg/L\, Megalonaias nervosa
[LC50 = 937 mg/L], Sphaerium simile [LC50 = 371 mg/L]), aplecopteran Amphinemura
delosa [LC50 = 456 mg/L], and an amphipod crustacean, Hyalella azteca
[LC50 = 16.4 mg/L], The acute toxicity of NO3 to the midge Chironomus dilutus
[LC50 = 278 mg/L] was assessed in a 48-hour acute test.
Since the 2008 ISA, several sublethal endpoints have been assessed in invertebrates
following exposure to NO3 . Toxicity of NO3 to the aquatic snail Potamopyrgus
antipodarum was assessed in a chronic bioassay [35 days (Alonso and Camargo. 2013)1.
The endpoints were behavior (velocity of movement) and reproduction (number of
newborns). Snails were exposed to four concentrations of NO3 (21.4, 44.9, 81.8, and
156.1 mg N-NO37L) and periodically monitored for velocity and newborn production.
Reduced velocity was observed at the three highest test concentrations and the number of
live newborns decreased in all treatments. Growth rate, molting frequency, and molting
egestion rates were measured in the amphipod Gammarus pseudolimnaeus following
exposure to 0.35 to 128 mg NO? /L for 21 days (Stelzer and Joachim. 2010). A weakly
statistically significant linear regression suggested an effect on growth rate while no
effects were observed for the other endpoints.
9.5.2 Amphibians
In amphibians, it appears that very high NO3 concentrations are required to elicit atoxic
response. Concentrations in surface waters that caused no observed effects ranged from
357 to 714 (.iM N/L (22 to 44 mg/L NO3 ) for frogs, salamanders, and the American toad
(Bufo americanus), as reported in the 2008 ISA (Romansic et al.. 2006; Johansson et al..
2001; Laposata and Dunson. 1998; Hecnar. 1995). A recent study by Meredith and
Whiteman (2008) support previous findings of tolerance of NO3 by amphibians.
Embryos of three amphibian species, Ambystoma mexicanum, Hyla chrysoscelis, and
Rana clamitans, were exposed to increasing levels (0, 5, 10, 30, 60, 100, 300, and
500 mg/L) of NO3 in laboratory static-renewal experiments. No significant mortality
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was noted among species or at any NOs concentration. The authors speculate that
invulnerability of the amphibian embryos may be due to several factors including
inability of embryos to uptake the ions, the protective role of the outer membrane in
developing embryos, and the lack of enzymes to convert NO3 to harmful NO2 . which
has been found to have lethal effects on embryos (GrifTis-kvle. 2005).
9.5.3 Fish
Toxic threshold concentrations in fish, eggs, and fry reported in the 2008 ISA are much
higher than the concentrations of NOs in surface water that would routinely be expected
to occur solely in response to atmospheric N deposition in the U.S. Additional NO3
toxicity testing was recently reported for the fathead minnow Pimephales promelas in
support of the development of water quality criteria for NO3 (U.S. EPA. 2010b). An
LC50 of 415 mg/L was reported from a 96-hour acute toxicity test. A 32-day chronic test
was also conducted with this species to assess mortality and growth effects. Lethal
concentration (LC) for survival, (LC50 = 76.8 mg/L, LC25 = 68.2 mg/L,
LC20 = 64.6 mg/L, LC10 = 55.5 mg/L) and effect concentration (EC) for growth
EC50 = 91.3 mg/L, EC25 = 65.3 mg/L, EC20 = 59.8 mg/L, EC10 = 46.7 mg/L) were
reported as well as a No Observed Effects Concentration (NOEC) of 49 mg/L and a
Lowest Observed Effect Concentration (LOEC) of 109 mg/L.
9.6 Extent and Distribution of Sensitive Ecosystems/Regions
Survey data and fertilization experiments from studies reviewed in the 2008 ISA
documented increases in algal productivity as well as species changes and reductions in
diversity at high-elevation lakes in the western U.S. in response to increased availability
of N (U.S. EPA. 2008a). In the western U.S., high-elevation lakes are considered the
aquatic ecosystems most sensitive to N deposition. Some examples include the Snowy
Range in Wyoming, the Sierra Nevada, Lake Tahoe, and the Colorado Front Range. The
responses of high-elevation lakes can vary considerably depending on catchment
characteristics and N deposition (Section 9.1.3). A portion of these lakes and streams in
the western U.S. are in Class I wilderness areas (Clow et al.. 2015; Nanus et al.. 2012).
Since the 2008 ISA, new studies quantifying the N contribution from glacial meltwater
which has higher NO3 relative to water from melting snow may alter interpretation of
biological data from high altitude lakes and streams (Slemmons et al.. 2015; Slemmons et
al.. 2013; Saros et al.. 2010). N deposition to snow and glaciers are important sources of
N to alpine lakes and streams that are fed by meltwaters. For example, approximately
50% of Glacier National Park lakes and 10-20% of central Rockies lakes receive glacial
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meltwater and diatom taxonomic richness in surface-sediment samples from glacial and
snowpack-fed lakes (higher in NOs ) were consistently low over the last century, ranging
from 12 to 26 taxa, in contrast to snow-fed lakes with 35 to 54 taxa in cores over the
same interval (Saros et al.. 2010).
In the 2008 ISA, locations with high concentrations of lake or stream water NO3 ,
indicative of ecosystem saturation, were reported at a variety of locations throughout the
U.S., including the San Bernardino and San Gabriel Mountains within the Los Angeles
Air Basin (Form et al.. 1996). the Front Range of Colorado (Williams et al.. 1996a; Baron
etal.. 1994). the Allegheny Mountains of West Virginia (Gilliam et al.. 1996). the
Catskill Mountains of New York (Stoddard. 1994; Murdoch and Stoddard. 1992). the
Adirondack Mountains of New York (Wigington et al. 1996b). and the Great Smoky
Mountains in Tennessee (Cook et al.. 1994). All of these regions, except the Colorado
Front Range, received more than about 10 kg N/ha/yr atmospheric deposition of N
throughout the 1980s and 1990s. The Front Range of Colorado received up to about
5 kg N/ha/yr of total (wet plus dry) deposition (Sullivan et al.. 2005). less than half of the
total N deposition received at many of these other locations.
Crowley et al. (2012) compared nutrient limitation patterns in lakes and tree foliage from
existing data sets from the northeast U.S. and observed a shift from N toward P nutrient
limitation in the Adirondacks subregion suggesting this area is sensitive to N enrichment.
They speculate this parallel foliar and lake pattern may be an early indicator of shifts
from N toward P limitation within the region overall, as N deposition continues to
accumulate in the system.
9.7 Summary of the Levels of Deposition at Which Effects are
Manifested and/or Critical Loads
Since the 2008 ISA, additional thresholds of response to N have been identified that are
useful for critical load development in water bodies impacted by N nutrient effects. A
critical load (CL) is a quantitative estimate of exposure to one or more pollutants below
which significant harmful effects on specified sensitive elements of the environment do
not occur according to present knowledge (Spranger et al.. 2004; Nilsson and Grcnnfclt.
1988). Critical loads for N nutrient enrichment in U.S. freshwater ecosystems are
summarized in Table 9-4.
Available data from the 2008 ISA suggests that the increases in total N deposition do not
have to be large to elicit an ecological effect. For example, a hindcasting exercise
determined that the shift in Rocky Mountain National Park lake algae composition that
occurred between 1850 and 1964 was associated with wet N deposition that was only
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1 about 1.5 kg N/ha/yr (Baron. 2006). Similar changes inferred from lake sediment cores of
2 the Beartooth Mountains of Wyoming occurred at about 1.5 kg TN/ha/yr deposition
3 (Saros et al.. 2003). The threshold level of atmospheric deposition that causes release of
4 N03 to surface waters was identified by Aber et al. (2003) as approximately 7 to
5 8 kg N/ha/yr for the northeastern U.S. In watersheds receiving N deposition above this
6 level, concentrations of NO;, in surface waters were positively correlated with
7 atmospheric deposition, whereas most watersheds with deposition less than 7 kg/ha/yr
8 had little or no NO3 (undetectable at most sites) in their surface waters (Aber et al..
9 2003).
Table 9-4 Summary of critical loads for nitrogen eutrophication for surface
water in the U.S. [adapted from Pardo et al. (2011c) with newer
studies added].
Ecosystem
Site
Critical Load for
N Deposition
(kg N/ha/yr)
Comments
Reference/
HERO ID
Alpine stream
Southern Rockies/Loch
Vale Rocky Mtn. Nat.
Park
2
Modeled
Baron et al.
(1994)
Alpine lake
Northern
Rockies/Beartooth Mtns.,
Wyoming
1.5
Paleolimnological
Saros et al.
(2003)
Eastern water
bodies
West Virginia to Maine
8
NO3" leaching to surface
water
Aber et al. (2003)
Alpine lakes
Western lakes
2
Paleolimnological
Baron (2006)
Alpine lakes
Rocky Mountains
2.5
Surveys and references
therein
Berastrom and
Jansson(2006)
Alpine lakes
Eastern Sierra Nevada
and Greater Yellowstone
Ecosystem
1.4
Paleolimnological
Saros et al.
(2011)
High-elevation
lakes of
Western and
Eastern U.S.
Rocky Mountains, Sierra
Nevada, Northeast
1.0 to 3.0 (Western
lakes)
3.5 to 6.0
(Northeastern lakes)
Based on N deposition
calculated 3 different ways
and lake NO3"
concentrations
Baron et al.
(2011b)
High-elevation
lakes
2.0 (Western lakes)
8.0 (Eastern Lakes)
Pardo et al.
(2011c)
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Table 9-4 (Continued): Summary of critical loads for nitrogen eutrophication for
surface water in the U.S. [adapted from (Pardo et al.,
2011c) with newer studies added].
Ecosystem
Site
Critical Load for
N Deposition
(kg N/ha/yr)
Comments
Reference/
HERO ID
Alpine lakes Rocky Mountain National
Park
>1.5
Based on NO3 threshold
of 0.5 |jM
(concentration which elicits
a growth effect in the
diatom A. formosa)
(2012)
Nanus et al
Alpine lake Hoh Lake, Olympic
National Park,
Washington State
1.0-1.2
Paleolimnological
Sheiblev et al.
(2014)
N = nitrogen; N03 = nitrate.
Since the release of the 2008 ISA, work has continued on identifying thresholds of
response to N deposition in sensitive freshwater systems. A DIN:TP mass ratio shift from
1.5 to 3.4 is indicative of a shift from clear N to clear P limitation in phytoplankton
(Benistrom. 2010). These values are based on analysis of lake water chemistry from
106 alpine lakes in Sweden, Slovakia, Poland, and the Rocky Mountains, Colorado and
nutrient bioassay data from high mountain lakes in Sweden and the Rocky Mountains,
Colorado. A nutrient threshold for surface water NO3 for growth of the diatom A.
formosa was developed for high-elevation lakes in the Rocky Mountains where N
deposition is prevalent (Nanus et al. 2012). The NO3 threshold of 0.5 |imol/L (31 |ig/L)
was then used to estimate areas in Rocky Mountain National Park that exceed CL values.
Additional CLs for nutrient enrichment of freshwaters developed since the 2008 ISA
include the West and Northeast U.S. Baron etal. (201 lb) found that in the western high-
altitude lakes, increased productivity and changes to algal biodiversity can occur with
only minimal inputs of N deposition. They estimated that the thresholds, or CLs, for
nutrient enrichment are 1.0 to 3.0 kg N/ha/yr for the western mountains (Sierra Nevada
and Rocky Mountains) and 3.5 to 6.0 kg N/ha/yr in minimally disturbed lakes in the
Northeast (Table 9-5). In another study from the eastern Sierra Nevada and Greater
Yellowstone Ecosystem, Saros et al. (2011) determined a CL of 1.4 kg N/ha/yr wet N
deposition by modeling wet deposition rates from the period in which diatom shifts first
occurred. The shifts were identified from sediment cores between 1960 and 1965 in the
eastern Sierra Nevada and starting in 1980 in the Greater Yellowstone Ecosystem. Using
core samples, Sheiblev et al. (2014) identified diatom changes during 1969-1975 in Hoh
Lake in Washington state that correspond to N inputs, and a CL of 1.0-1.2 ± 0.01 kg
N/ha/yr was established for the lake.
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Table 9-5 Nutrient enrichment inflection points for nitrogen deposition in
western regions of the U.S. [from Baron et al. (2011b)1.
Region
Mean
Lake
NOs"
Mean
1997-2006
NADP N
Deposition
Nutrient
Enrichment
Inflection
Point
(NADP)
Mean 1997-2006
(PRISM + NADP)
Deposition
Nutrient
Enrichment
Inflection Point
(PRISM + NADP)
2002 Total
N
Deposition
Nutrient
Enrichment
Inflection
Point (Total
N)
Sierra
Nevada
(n = 30)
2.7
(1.10)
1.5 (0.22)
1.5
2.5 (0.34)
1.5
3.4 (0.47)
2.0
Rocky
Mountains
(n = 285)
3.7
(1.90)
1.2 (0.27)
1.0
3.0 (0.28)
2.0
2.0 (0.24)
3.0
Northeast
(n = 216)
14.4
(0.76)
4.7 (0.18)
3.5
5.2 (0.18)
3.5
3.5 (0.20)
6.0
N = nitrogen; NADP = National Atmospheric Deposition Program; N03 = nitrate; PRISM = Parameter-elevation Regressions on
Independent Slopes Model; PRISM +NADP = concentrations from NADP with PRISM precipitation values.
Note: Inorganic N deposition was calculated three ways, as was described in Baron et al. (2011b) Coefficients of variation are in
parentheses.
Mean lake N03" (in micromoles per liter), inorganic nitrogen (N) deposition amounts (in Kg N/ha/yr), and nutrient enrichment
inflection points where lake N03" concentrations increase in response to increasing N deposition.
Source: Aber et al. (2003). Sickman et al. (2002). U.S. Forest Service's Air Resource Management online database
(www.fs.fed.us/ARMdata).
Pardo etal. (2011c) estimated a CL of 2.0 kg N/ha/yr for Western Lakes and
8.0 kg N/ha/yr for Eastern Lakes based on the value of N deposition at which significant
increases in surface water NO, concentrations occur. Source of uncertainty in N
deposition estimates for assessment of critical loads according to Pardo etal. (201 la)
include "(1) the difficulty of quantifying dry deposition of nitrogenous gases and particles
to complex surfaces; (2) sparse data, particularly for arid, highly heterogeneous terrain
(e.g., mountains); and (3) sites with high snowfall or high cloud water/fog deposition,
where N deposition tends to be underestimated." A review by Bowman et al. (2014) notes
that current N CLs for sensitive alpine systems may not be protective under future
climate scenarios of warmer summer temperatures and shorter duration of snow cover.
9.8 Summary and Causal Determination
In the 2008 ISA, the body of evidence was sufficient to infer a causal relationship
between N deposition and the alteration of species richness, species composition, and
biodiversity in freshwater ecosystems. New evidence from 2008 to the present, from
paleolimnological surveys, fertilization experiments, gradient studies, phytoplankton
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community responses, and indices of biodiversity continue to show effects of N loading
to sensitive freshwater systems. As summarized in the 2008 ISA and supported by data in
newer studies, nutrient enrichment effects on freshwater ecosystems from atmospheric
deposition of N are most likely to occur in lakes and streams that have low primary
productivity and low nutrient levels and that are located in the most undisturbed areas
with no local pollution sources. Even small inputs of N in these water bodies can increase
nutrient availability or alter the balance of N and P, which can stimulate growth of
phytoplankton. As reported in the 2008 ISA and further strengthened with new evidence
in this review, there is consistent and coherent evidence for species composition changes
and reductions in biodiversity, especially for primary producers from high-elevation lakes
in the western U.S., in response to increased availability of N. New information is
consistent with the conclusions of the 2008 ISA that the body of evidence is sufficient
to infer a causal relationship between N deposition and changes in biota including
altered growth, species richness, community composition, and biodiversity due to N
enrichment in freshwater ecosystems.
New data have not appreciably changed the consistent and coherent evidence at the time
of the 2008 ISA that freshwater systems likely to be most impacted by nutrient
enrichment due to atmospheric deposition of N are remote high-elevation water bodies
with no local nutrient sources and with low N retention capacity. N inputs to these
ecosystems are linked to changes in biota, especially increased algal growth and shifts in
algal communities. Freshwater systems sensitive to N nutrient enrichment include those
in the Snowy Range in Wyoming, the Sierra Nevada Mountains, and the Colorado Front
Range. A portion of these lakes and streams where effects are observed are in Class I
wilderness areas (Clow et al.. 2015; Nanus et al.. 2012).
Recent research further supports the 2008 ISA findings that N limitation is common in
oligotrophic waters in the western U.S. (Elseret al.. 2009b; Elser et al.. 2009a'). Shifts in
nutrient limitation, from N limitation, to between N and P limitation, or to P limitation,
were reported in some alpine lake studies reviewed in the 2008 ISA. Bergstrom (2010)
identified a threshold for the switch of lake response from N to P limitation. When
DIN:TP mass ratios increased from 1.5 to 3.4, the phytoplankton moved from clear N to
clear P limitation. Although there is limited data for biological effects due to atmospheric
deposition of N in other regions of the U.S., Crowlev et al. (2012) used N:P mass ratios
to show that there was a positive relationship between lake DIN:TP and N deposition in
the Adirondack subregion, although this pattern was not observed at the regional scale
across the Northeast U.S.
The body of evidence for biological effects of N enrichment and altered N:P ratios in
remote freshwater systems (where atmospheric deposition is the predominant source of
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N) is greatest for phytoplankton, the base of the freshwater food web. Lake surveys,
fertilization experiments, and nutrient bioassays reported in the 2008 ISA and in this
review show increased pelagic and benthic algal productivity (as indicated by chlorophyll
a concentration) to be strongly related to increased N concentration. An increase in lake
phytoplankton biomass with increasing N deposition was reported in several regions
including the Snowy Range in Wyoming and across Europe. New studies in the Rocky
Mountains of Colorado where atmospheric deposition ranged from 2 to 7 kg N/ha/yr
support observations from the 2008 ISA that show correlations between greater
chlorophyll a response and higher rates of deposition (Elser et al. 2009a').
Studies reported in the 2008 ISA (Lafrancois et al.. 2004; Wolfe et al.. 2003; Jassbv et al..
1994) and newer studies (Svmons et al.. 2012; Saros et al.. 2010) show a general shift
from chrysophytes that dominate lakes with low N to cyanophytes and chlorophytes in
lakes with higher N. In the 2008 ISA, diatom assemblage shifts were reported from the
literature at total N deposition as low as 1.5 kg N/ha/yr (Saros et al.. 2003). This was
further supported by a hindcasting exercise that determined the change in Rocky
Mountain National Park lake algae that occurred between 1850 and 1964 was associated
with an increase in wet N deposition that was only about 1.5 kg N/ha/yr (Baron. 2006).
Two nitrophilous species of diatom, A. formosa and F. crotonensis, are dominant in lakes
with higher N and serve as biological indicators ofN enrichment. Additional critical
loads have been identified since the 2008 ISA for Eastern Sierra Nevada lakes, Rocky
Mountain lakes, the greater Yellowstone ecosystem and Hoh Lake, Olympic National
Park I Table 9-4 (Sheiblev et al. 2014; Pardo et al.. 2011c; Saros et al.. 2011)1. The
identified values fall within the range of 1.0 to 3.0 kg N/ha/yr for western lakes (Baron et
al.. 2011b). A critical load ranging from 3.5 to 6.0 kg N/ha/yr was identified for
high-elevation lakes in the eastern U.S. based on the nutrient enrichment inflection point
[where NCh concentrations increase in response to increasing N deposition (Baron et al.
2011 b) 1. Another critical load of 8.0 kg N/ha/yr for eastern lakes based on the value of N
deposition at which significant increases in surface water NOs concentrations occur was
estimated by Pardo etal. (2011c). Some shifts in algal biodiversity observed in high
elevation waters are attributed to climate change or nutrient effects and climate as
costressors (Chapter 13).
Biological responses to N deposition at higher trophic levels have not been as thoroughly
explored in remote freshwater ecosystems as those of primary producers, but atmospheric
N can potentially alter food web interactions (Elser et al.. 2009a). A few studies in the
2008 ISA showed declines in zooplankton biomass (Lafrancois et al.. 2004; Paul et al.
1995) in response to N related shifts in phytoplankton biomass toward less palatable taxa
with higher C:P ratios (Elser et al.. 2001). Limited studies since the 2008 ISA suggest
that atmospheric N inputs are linked to taxonomic shifts and declines in some
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invertebrates, although the effects attributed to N are difficult to separate from other
stressors such as climate change and invasive species. The role of trophic interactions in
moderating algal growth following nutrient loading has been examined in several studies.
For example, a study in Banff National Park, Canada indicated that grazing pressure on
algae may have negated effects of nutrient inputs on primary producers (Vinebrooke et
al.. 2014). Limited evidence suggests a decreased rate of leaf litter decomposition by
microbial communities with N loading to streams. Few studies in the U.S. have
considered effects of atmospheric deposition on aquatic macrophytes, although declines
in macrophyte occurrence over the last four decades were noted in a resurvey of Lake
Tahoe (Caires et al.. 2013). Atmospheric N contributions are a significant portion
(approximately 57%) of the total N loading to the lake (Sahoo et al.. 2013). Toxic effects
due to increased NOs in surface waters occur in macroinvertebrates, amphibians, and
fish at much higher concentrations than would commonly be attributable to atmospheric
deposition. Emerging research on disease in biota suggest that N enrichment may modify
relationships such as host susceptibility to parasites and pathogens. Although little
research has been conducted in freshwater systems, there is evidence to suggest increased
turbidity associated with algal blooms may affect reproductive and social behaviors in
fish (Chapter 10).
New studies show consistent and coherent evidence that the N contribution from glacial
meltwater (which has higher NO3 relative to water from melting snow) affects diatom
community composition in high altitude lakes and streams (Slemmons et al.. 2015;
Slemmons et al.. 2013; Saros et al.. 2010). N deposition to snow and glaciers are
important sources of N to alpine lakes and streams that are fed by meltwaters. In a
comparison of biological response in snowpack-fed lakes versus lakes with both glacial
and snowpack meltwater, fossil diatom richness was higher in the snowpack-fed lakes
(34 to 54 taxa) compared to lakes with both glacial and snow meltwater inputs [12 to
26 taxa (Saros et al.. 2010)1.
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CHAPTER 10 BIOLOGICAL EFFECTS OF
NITROGEN ENRICHMENT IN
ESTUARIES AND NEAR-COASTAL
SYSTEMS
This chapter characterizes the biological effects of nitrogen (N) enrichment in estuaries
(areas where freshwater from rivers meets the salt water of oceans), coastal lagoons and
open ocean areas near coastlines. Included is an overview of N sources and cycling in
coastal systems and characteristics of coastal areas sensitive to N inputs (Section 10.1).
Indicators of nutrient enrichment (Section 10.2). effects of N on biodiversity and
ecosystem structure and function (Section 10.3). animal behavior and disease
(Section 10.4) and the role of N nutrient enrichment in coastal acidification
(Section 10.5) are covered in this chapter. Finally, the extent and distribution of coastal
eutrophication and acidification in the U.S. is characterized (Section 10.6) as well as
thresholds of response in these systems (Section 10.7). A summary section including
causal determinations based on a synthesis of new information and previous evidence
from prior N assessments is presented in Section 10.8.
10.1 Introduction
In the 2008 Integrated Science Assessment for Oxides of Nitrogen and Sulfur-Ecological
Criteria (2008 ISA), the body of evidence was sufficient to infer a causal relationship
between N deposition and the alteration of species richness, species composition, and
biodiversity in estuarine systems (U.S. EPA. 2008a). In estuaries, N from atmospheric
and nonatmospheric sources contributes to increased primary productivity, leading to
eutrophication (Figure 10-1). Estuary eutrophication is a process of increasing nutrient
over-enrichment indicated by water quality deterioration, resulting in numerous adverse
effects including areas of low dissolved oxygen (DO) concentration (hypoxic zones),
species mortality, and harmful algal blooms (HABs). In the 2008 ISA the strongest
evidence for a causal relationship was from changes in biological indicators of nutrient
enrichment including chlorophyll a, macroalgal "seaweed" abundance, HABs, DO, and
submerged aquatic vegetation (SAV). Biological effects of increasing nutrient enrichment
also include changes in biodiversity in these systems. New information is consistent with
the conclusions from the 2008 ISA that the body of evidence is sufficient to infer a
causal relationship between N deposition and changes in biota including altered
growth, species richness, community composition, and biodiversity due to N
enrichment in estuarine environments.
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Since the 2008 ISA, N loading has been recognized as a possible contributing factor to
acidification of coastal waters. Dissolution of atmospheric anthropogenic CO2 into the
ocean has led to long-term decreases in pH. Increased production of CO2 from
degradation of organic matter associated with eutrophication along with atmospheric
anthropogenic CO2 inputs can result in formation of carbonic acid and make the ocean
water more acidic. Organisms that produce calcium carbonate shells such as calcareous
plankton, oysters, clams, sea urchins, and coral may be affected by long-term decreases
in pH. The body of evidence is suggestive of a causal relationship between N
deposition and changes in biota including altered physiology, species richness,
community composition, and biodiversity due to nutrient-enhanced coastal
acidification.
Coastal systems are linked to terrestrial N processes along the freshwater to ocean
continuum as nutrients deposited to the watershed move downstream. Altered
biogeochemical processes associated with N loading (Chapter 7) may affect aquatic biota
in a diversity of habitats. Chapter 11 will cover wetland ecosystems, including those
located on coasts in which soils and/or sediments are periodically inundated by tides or
flooding. Habitats associated with coastal areas include shallow open waters, sandy
beaches, mud and sand flats, rocky shores, oyster reefs, mangrove forests, river deltas,
tidal pools, and sea grasses (U.S. EPA. 2016c). These systems provide breeding grounds,
nurseries, and shelter for aquatic biota.
Algae and phytoplankton at the base of the coastal food web to organisms at higher
trophic levels are affected to varying degrees by nutrient loading in coastal ecosystems.
As described in the 2008 ISA, in coastal ecosystems, the nutrients most commonly
associated with phytoplankton growth are N, phosphorus (P), and silicon (Si). The
relative proportions of these nutrients are important determinants of primary production,
food web structure, and energy flow through the ecosystem (Turner et al.. 1998; Justic et
al.. 1995b; Justic et al.. 1995a; Dortch and Whitledge. 1992). In general, estuaries tend to
be N limited KElseret al.. 2007); Section 10.1.31; however, P limitation can play an
important role, particularly seasonally if the water body has a significant freshwater
source (Kemp et al.. 2005; Malone et al.. 1996).
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Atmospheric Deposition
0
Sewage effluent
Runoff
~ -
•V
*¦ _
g Phytoplankton Bloom
thrives on nutrients
• I'
• 4 .
Dead ~
material*
settles
Dissolved Oxygen
trapped in the upper,
lower-salinity layer
Decomposition
I
. Dissolved Oxygen used up
* by microorganism respiration
1 i#
Nutrients
• i
Dissolved Oxygen
from wave action
and photosynthesis
Lower-density
surface water
Higher-density
bottom water
^ released by bottom sediments
Fish will avoid
hypoxia if possible
Dissolved Oxygen consumed
Shellfish
and other
benthic
organisms
unable
to escape
hypoxia
Decomposition of organic
matter in sediments
N = nitrogen.
Notes: Atmospheric N deposition is one of the sources of nutrient enrichment to coastal areas.
Source: modified from U.S. EPA (2012bV
Figure 10-1 Eutrophication can occur when the concentration of available
nutrients increases above normal levels.
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In the previous ISA, there was a strong scientific consensus that N is the principal cause
of coastal eutrophication in the U.S. (U.S. EPA. 2008a; NRC. 2000). On average, human
activity has likely contributed to a sixfold increase in the N flux to the coastal waters of
the U.S. over the past several decades, and N represents the most significant coastal
pollution problem (Bricker et al.. 2008; Bricker et al.. 2007; Howarth and Marino. 2006;
Bricker et al.. 2003; Howarth et al.. 2002). Many coastal areas receive high enough levels
of N input from human activities to cause eutrophication (Bricker et al.. 2007; Howarth et
al.. 1996; Vitousek and Howarth. 1991V As reported in the 2008 ISA, N driven
eutrophication of shallow estuaries has increased over the past several decades and
environmental degradation of coastal ecosystems is now a widespread occurrence
(Bricker et al. 2007; Paerl et al.. 2000). This chapter highlights post-2007 research
literature findings since the release of the 2008 ISA.
10.1.1 Nitrogen Sources to Estuaries and Coasts
N sources and deposition to coastal areas are described in detail in Chapter 7. Coastal
waters are influenced by N enrichment from upstream sources that may undergo
biogeochemical transformations along the freshwater-to-ocean continuum as well as
direct inputs from the atmosphere. In estuaries adjacent to areas of coastal upwelling such
as some locations along the Pacific coast of the U.S., oceanic inputs of nutrients may also
represent an important source of N (Brown and Ozretich. 2009). N inputs can be
attributed to point sources, coming from a single outfall or discharge point and nonpoint
sources, which are diffuse (U.S. EPA. 2008a). Both point and nonpoint sources have been
identified as targets for control of N inputs in coastal systems (Stephenson et al.. 2010;
Paerl et al. 2002). In many coastal areas, atmospheric deposition typically constitutes
less than half of the total N supply; however, atmospheric inputs are heterogeneous
across the U.S. ranging from <10 to approximately 70% of the N inputs (Table 7-8;
Chapter 7). As summarized in the 2008 ISA, although overall, atmospheric deposition of
total N has not changed appreciably, atmospheric deposition of reduced N has increased
relative to oxidized N and this trend is expected to continue in the future under existing
emission controls (Pinder et al.. 2008; U.S. EPA. 2008a).
10.1.2 Nitrogen Transformations and Fate in Estuaries
Atmospherically deposited N along with other sources of N to estuaries influence
processes from the watershed to the open ocean I (Paerl and Piehler. 2008); Figure 10-21.
These highly variable environments are characterized by an increasing gradient of
salinity. At the upstream end of an estuary, the water is primarily fresh much of the time.
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1 Nonpoint source runoff of N from the land surface, only a part of which is of atmospheric
2 origin (mainly deposition to land that is subsequently leached to the river water)
3 dominates new N inputs. Downstream, freshwater inflows gradually mix with salt water
4 to form mesohaline segments of the estuary. Further along the salinity gradient, much of
5 the terrestrial N load is assimilated by phytoplankton and benthic flora or removed by
6 microbes in the process of denitrification (Pacrl et al.. 2002). Direct atmospheric N inputs
7 also impact the lower estuary although the relative importance of N deposition in this
8 zone is uncertain (Pacrl et al.. 2002). The biogeochemical cycling of N in estuaries is
9 described in greater detail in Chapter 7.
Urbatv^
Agriculture/ ~
Industrial
Runoff [Aquaeukurc
Coastal
Ocean
Open
Ocean
Estuary/ Sound
Groundwater
SedirtienLiLion
Chi a max = chlorophyll a maximum; DNF = denitrification; N = nitrogen; NF = nitrification.
Notes: Surface, subsurface, and atmospheric pathways of externally supplied or new N inputs attributable to anthropogenic activities
are shown as internal N cycling. The combined anthropogenic N inputs are shown as a thick arrow (upstream), which decreases in
thickness downstream as a portion of the N inputs settles to the bottom sediments and is buried and/or denitrified. NF represents N2
fixation, a biologically mediated new N input. The linkage of anthropogenically enhanced N inputs to accelerated primary production
or eutrophication and its trophic and biogeochemical fate are also shown. In many estuary and sound systems, primary production
and phytoplankton biomass are maximal in mid-system locations, when adequate new N loads and decreasing rates of flushing
(increasing residence times) overlap. The resultant chlorophyll a max is characteristic on estuarine systems in which residence
times are long enough to allow periodic phytoplankton blooms to accumulate.
Source: Paerl and Piehler (2008).
Figure 10-2 Schematic diagram illustrating sources, transformations, and fate
of nitrogen along the estuary to ocean continuum.
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10.1.3 Nitrogen Limitation
As reported for several decades prior to the 2008 ISA, N enrichment of marine and
estuarine waters can alter the ratios among nutrients such as P and Si and affect overall
nutrient limitation. N is the most common limiting nutrient in estuarine and coastal
waters and continued inputs have resulted in N over enrichment and subsequent
alterations to nutrient balance in these systems (U.S. EPA. 2008a; Paerl et al.. 2000). As
described in the 2008 ISA, nutrient limitation may shift along the estuarine to ocean
continuum (U.S. EPA. 2008a'). For example, Chesapeake Bay exhibits a shift in nutrient
limitation with P most commonly limited at upstream freshwater locations and at the
transition between fresh and salt water N and P may be colimiting, whereas the saltwater
environments on the outer bay are usually N limited (Fisher et al.. 1998; Rudek et al..
1991). Levels of N limitations are affected by seasonal patterns in estuaries with N
limited conditions likely occurring during the peak of annual productivity in the summer
(U.S. EPA. 2008a).
Since the 2008 ISA, N limitation in estuarine and marine systems has been further
evaluated, along with recognition of the shifting nature of nutrient limitation based on
relative nutrient inputs and other ecosystem conditions. The rate of nutrient delivery,
especially N, to coastal waters is strongly correlated to primary production and
phytoplankton biomass (Paerl and Piehler. 2008). Strong management controls causing
low riverine P inputs have, in some cases, exacerbated N limitation downstream, with
implications for estuarine eutrophication (Paerl. 2009). Likewise, if N inputs are high
enough, some estuaries and coastal marine ecosystems can become P or Si limited
(Howarth et al.. 2011; Paerl and Justic. 2011). Under this scenario, if a system becomes P
limited, the N input may travel farther away from its sources and contribute to
eutrophication at greater distances (Howarth et al.. 2011).
The role of N inputs from upstream and the connectivity between freshwater and
receiving estuaries and coastal waters have led to recommendations to reduce both N and
P in upstream waters (Paerl et al.. 2014; Conlev et al.. 2009; Paerl. 2009). Increased N
inputs may be affecting N limitation in the open ocean as well as in near-coastal areas.
Kim et al. (2014a) reported a detectable increase in NO3 concentration in the upper
Pacific Ocean. The rate of increased N relative to P was highest near the source of
anthropogenic emissions in northeastern Asia with rates decreasing eastward across the
upper North Pacific Ocean. The authors suggest that increased N deposition may enhance
primary production and potentially lead to a shift from N to P limitation in this region.
Additional studies support observations reported in the 2008 ISA of N and P dynamics in
estuaries. P limited conditions often exist in the low salinity regions while N limitation is
more common downstream in higher salinity waters (Paerl and Otten. 2013). Studies in
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the Chesapeake Bay and in Europe have shown that the phytoplankton community in
coastal ecosystems can be P limited over several months in the spring, and can switch to
N limitation for periods of time as short as 1 week later in the season (Trommer et al..
2013; Malone et al.. 1996). In the low-nutrient waters of North Carolina's Alligator River
estuary, phytoplankton primary productivity and biomass (chlorophyll a) increased with
N additions, but both indicators showed the greatest increases after treatment with
combined N and P, indicating that this system was colimited by N and P (Rossignol et al..
2011). N additions in this region are known to lead to poor water quality and related
complications such as algal blooms, hypoxia/anoxia (water with DO that is too low to
support marine biota), and fish kills and impact ecosystem services, including fisheries
and recreation (Paerl and Piehler. 2008).
10.1.4 Characteristics of Coastal Systems Sensitive to Eutrophication
Each coastal system has site-specific characteristics that influence ecological response to
nutrient loading. A variety of factors that govern the sensitivity of estuaries and
near-coastal marine waters to eutrophication from atmospheric N deposition are
summarized in the 2008 ISA. Of critical importance is the total N input from all sources,
including both atmospheric and nonatmospheric sources (Section 10.1.1). Other key
elements include the flushing rate and dilution capacity of the watershed which reflects
the volume of water available to dilute added N. (NRC. 2000; Bricker et al.. 1999).
As described in the 2008 ISA, the principal watershed features that control the amount of
increased N flux to estuaries in the U.S. include human population, agricultural
production, and the size of the estuary relative to its drainage basin (Fisher et al.. 2006;
Caddv. 1993; Peierls et al.. 1991). A study included in the 2008 ISA reported a strong
correlation between population density (persons/km2) and the total N loading from
watershed to estuary (r2 = 0.78) for coastal watersheds in the U.S. (Turner et al.. 2001).
This finding is likely due to the prevalence of automobiles in heavily populated areas,
along with their associated N emissions and deposition, plus the myriad of
nonatmospheric sources of N from human activities, particularly wastewater discharges.
The study authors also determined that direct atmospheric deposition becomes
increasingly more important as a contributor to the total N loading to an estuary as the
water surface area increases relative to total watershed area (terrestrial plus water
surfaces). Because of human population growth and the great popularity of coastal areas,
there is substantial potential for increased N loading to coastal ecosystems from both
atmospheric and nonatmospheric sources.
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Freshwater inputs to coastal areas and subsequent response to nutrient inputs depend on
residence time of the nutrient-laden freshwater and the degree of tidal exchange within
the estuary (Zaldivar et al.. 2008). Residence time is defined by physical and hydrological
characteristics of the watershed such as surface area, volume, depth, and flushing (Paerl
et al.. 2002). In systems characterized as having a short residence time, there is little
opportunity for nutrients to be taken up and for blooms to develop (Bricker et al.. 2007).
In the National Estuarine Eutrophication Assessment (NEEA), a comprehensive survey
of eutrophic conditions in the Nation's estuaries conducted by the National Oceanic and
Atmospheric Administration (NOAA), systems with longer flushing times were
considered more susceptible to eutrophication (Bricker et al.. 2007).
In some estuaries, especially in the Pacific Northwest, nutrient inputs from local and
regional upwelling can be difficult to discern from anthropogenic sources (Brown and
Ozretich. 2009). Transfer of hypoxic water from upwelling to estuaries can also occur
(Brown and Power. 2011). Other factors within the highly variable estuarine environment
that influence the composition of biological communities include salinity, DO, and
suspended solids, which vary spatially and temporally along the estuary continuum
(Boria et al.. 2012). Mixing depth, temperature and light penetration depth also affect
biological response (Paerl et al.. 2002). A stratified water column that separates
well-oxygenated surface water from bottom water and sediments is generally required for
formation of hypoxic zones (Jewett et al.. 2010). In contrast to the seasonal or persistent
nature of hypoxic zones, diel-cycling hypoxia typically occurs over hours to days and
does not require stratification. Precipitation events such as storm and floods or drought
can also modulate nutrient effects I (Paerl and Piehler. 2008); Chapter 131.
In the 2008 ISA and NEEA, estuaries characterized as eutrophic were generally those that
had large watershed-to-estuarine surface area, high human population density, high
rainfall and runoff, low dilution, and low flushing rates (U.S. EPA. 2008a; Bricker et al..
2007). In literature reviewed for this ISA, many studies have re-emphasized the important
role that physical and hydrologic factors play in determining which estuaries and coastal
ecosystems are the most sensitive to N enrichment (Hart et al.. 2015; Wilkerson et al..
2015; Glibert et al.. 2014; Rothenberger et al.. 2014; Kennison et al.. 2011). The
hydrodynamics of a system may play a more important role in phytoplankton growth than
the availability of N. For example, in Florida's Ten Mile Creek, which drains into the
Indian River Lagoon. Yang et al. (2008) found that chlorophyll a (Section 10.2.1) was
negatively correlated with N concentrations. This result is thought to be due to the strong
influence exerted by hydrologic factors (such as freshwater inflow, salinity, pH, and
temperature), which were all positively correlated with chlorophyll a concentrations
during this study. In the subtropical well-flushed Guana Tolomato Matanzas estuary in
FL, short water residence time and degree of tidal exchange appeared to provide a level
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of resistance to eutrophication (Hart et al.. 2015). These factors that affect estuarine
response to nutrient loading should be taken into account when establishing N input
thresholds so that eutrophication can be controlled for different ecosystem types,
hydrologic conditions, and future climate scenarios (Paerl et al.. 2014).
10.2 Indicators of Nutrient Enrichment
In the complex environment of the freshwater-to-ocean continuum there are many
chemical and biological indicators of eutrophic condition. One approach is to measure
total nutrient loading and concentrations; however, this data needs to be interpreted in the
context of the physical and hydrological characteristics that determine ecosystem
response. Chemical indicators such as dissolved inorganic nitrogen (DIN) and dissolved
inorganic P (Chapter 7). additional measures of water quality (water clarity, DO) along
with biological indicators such as chlorophyll a, phytoplankton abundance, HABs,
macroalgal abundance, SAV, and fish kills can all be used to assess responses to nutrient
loading. Some biological indicators, such as chlorophyll a are directly linked to nutrient
enrichment and provide evidence of early response to added nutrients while other
indicators such as low DO and decreases in SAV indicate that the degree of
eutrophication has progressed (Boria et al.. 2012). A summary of key indicators of
estuarine eutrophication is provided in Table 10-1. and these indicators are discussed in
the following sections. The 2008 ISA used the five ecological indicators shown in Figure
10-3 (chlorophyll a, harmful/nuisance/toxic algal blooms, macroalgae, DO, and SAV)
included in the Assessment of Estuarine Tropic Status (ASSETS) categorical
Eutrophication Condition Index (ECI) in the NEEA to estimate the likelihood that an
estuary is experiencing eutrophication or will experience eutrophication (Bricker et al..
2007).
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Table 10-1 Indicators of Estuarine Eutrophication.
Indicator Description
Chlorophyll a Excess N input will stimulate primary productivity, and chlorophyll a concentration is an
indicator of phytoplankton biomass. Phytoplankton biomass is strongly controlled in
coastal waters by the availability and supply rates of nutrients, especially N (Paerl and
Piehler. 2008).
Excess N input can cause nuisance or toxic algal blooms, which release toxins in the
water that can poison aquatic animals and threaten human health (Baron et al.. 2012).
Problem occurrences of HABs increased 13% from 1997 to 2007 in mid-Atlantic
estuaries, the only region for which data were available, along with increasing N loading
(Bricker et al.. 2008).
Macroalgal abundance Macroalgal blooms can cause the loss of important submerged aquatic vegetation by
blocking sunlight and opportunistic macroalgae can outcompete many seagrass
species (Kennison et al.. 2011). Can also cause hypoxia and can smother seagrass,
coral, clams/oysters, other benthic organisms. High biomasses also cause "stinky
beach" by rafting onto beaches and decaying.
Dissolved oxygen (DO) Dissolved O2 concentration decreases with increasing algal abundance under elevated
N because microbes consume Chas they decompose dead algae. Increased
atmospheric N deposition combined with N loading from other sources will likely affect
the size, frequency, and severity of hypoxia events (Rabalais et al.. 2010). Hypoxia also
contributes to ocean acidification, which is detrimental to the growth and development
of calcifying organisms (Howarth et al.. 2011). The largest documented zone of hypoxic
coastal water in the U.S. is located in the northern Gulf of Mexico (Dale et al.. 2010).
Excess N input stimulates algal growth, and opportunistic macroalgae may block the
penetration of sunlight into the water column and outcompete seagrasses, leading to
reduced SAV coverage. Reduced extent of eelgrass was found to correspond to
increased loading of N (from wastewater, fertilizer and atmospheric deposition) to
small-to-medium shallow estuaries in New England (Latimer and Reao. 2010) and
distribution of SAV in Chesapeake Bay is used as an indicator in the EPA Report on the
Environment (U.S. EPA. 2016f).
Chi = chlorophyll; DO = dissolved oxygen; EPA = Environmental Protection Agency; HAB = harmful algal blooms; N = nitrogen;
02 = oxygen; SAV = submerged aquatic vegetation.
Harmful/nuisance/toxic
algal blooms (HABs)
Submerged aquatic
vegetation (SAV)
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S.B. Bticker el at./Harmful Algae S (200SJ 21-32
Impact: No Problem /low Moderate low Moderate Moderate high
High
o,
WPWWf'W&V
Few symptoms Symptoms occur Symptoms occur Symptoms occur Symptoms occur
occur 81 more than episodically and/or less regularly less regularty and/or periodically or
minimal levels over a small to and/or over a over a medium to persistently and/or over
medium area medium area extensive area an extensive area
IK
Key to symbols
Submerged
aquatic vegetation
Chlorophyll a
#
o
Nuisance/toxic
blooms (HAB)
Macros Igae
Dissolved oxygen
Source: Bricker et al. (2008).
Figure 10-3 Biological indicator responses to nutrient enrichment.
10.2.1 Chlorophyll a
Chlorophyll a is a photosynthesizing green pigment that can be measured to indicate the
amount of algae present (total phytoplankton biomass). Algae is the base of the coastal
food web and excess algal growth is directly linked to nutrient enrichment. Chlorophyll a
is widely used to assess eutrophic conditions because of its sensitivity to nutrient inputs
(Borja et al.. 2012) and it was one of the indicators of overall eutrophic condition of U.S.
coastal areas in the 2008 ISA (U.S. EPA. 2008a). It can signal an early stage of water
quality degradation related to nutrient loading. High concentration of chlorophyll a
suggests that algal biomass is sufficiently high, and that it might contribute to low DO
concentration due to increased decomposition of dead algae. Due to the strength of
hydrologic forces in some types of coastal systems, benthic chlorophyll a may be a more
sensitive indicator of ecosystem response to N enrichment than planktonic chlorophyll a
in well-flushed systems (Paerl and Piehler. 2008).
Chlorophyll a concentrations are commonly included in standardized frameworks of
eutrophic condition [Section 10.2.5; (Boriaet al.. 2012)1. Many of these indices define
spatial extent and temporal sampling periods and statistical measures to determine
representative concentrations. Several chlorophyll a thresholds have been identified for
U.S. water bodies (Table 10-2). The EPA National Coastal Condition Assessment
(NCCA; formally known as National Coastal Assessment) measures chlorophyll a from
an annual index period (June to October) and compares the samples to reference
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conditions to determine a rating [>20 |ig/L. poor; 5-20 |ig/L. fair; <5 |ig/L. good; (U.S.
EPA. 2016c. 2012bVI. For the NEEA ASSETS, the 90th percentile of annual values for
chlorophyll a combined with spatial coverage and frequency of occurrence of blooms are
reported for distinct salinity zones (tidal fresh 0-0.5 ppt), mixing zone (0.5 to 25 ppt),
and seawater (>25 ppt); 0-5 |ig/L is a water body with low risk of eutrophication,
5-20 (ig/L is moderate, >20 |ig/L is high (Bricker et al. 2007).
In the NEEA, high chlorophyll a concentration was the most widespread documented
symptom of eutrophication (Bricker et al.. 2007). Half of the estuaries for which data
were available exhibited high chlorophyll a concentration (Bricker et al.. 2007). In the
2008 ISA, San Francisco Bay, CA was an example of an estuary that has experienced
considerable increases in chlorophyll a concentrations in recent years.
Table 10-2 Chlorophyll a thresholds used in methods to evaluate the status of
phytoplankton in U.S. coastal and estuarine water bodies.
Chlorophyll a
Thresholds Sample
Method/ and Ranges Time
Approach (H9"-) Frame
Statistical
Measure
Other
Characteristics
Community
Composition
Indicators in
Overall
Eutrophication
Index
EPANCCA Poor >20
Fair 5-20
Good 0-5
Index
period
(June-Oct.
Concentration
percentage of
coastal area in
poor, fair, and
good condition
based on
probabilistic
sampling design
for 90% conf. in
areal result
No
Chlorophyll a,
water clarity, DO,
DIP, DIN
ASSETS
(eutrophic
condition
component
only)
Poor >20
Fair 5-20
Good 0-5
Annual
90th percentile
Chlorophyll a
concentration of
annual data
Spatial
coverage,
frequency
occurrence
Nuisance and
toxic bloom
occurrence,
frequency,
duration
Chlorophyll a,
macroalgae, DO,
seagrasses,
nuisance/toxic
algal blooms
ASSETS = Assessment of Estuarine Trophic Status; conf = confidence; DIN = dissolved inorganic nitrogen: DIP = dissolved
inorganic phosphorus; DO = dissolved oxygen; EPA = Environmental Protection Agency; L = liter; NCCA = National Coastal
Condition Assessment.
Source: Boria et al. (2012)
Phytoplankton biomass, as indicated by chlorophyll a concentration, is strongly
controlled in coastal waters by the availability and supply rates of nutrients, especially N
(Paerl and Piehler. 2008). Bioassays conducted in the low-nutrient Alligator River
estuary in North Carolina showed that N enrichment is directly related to increasing
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chlorophyll a concentration. Although the highest increase occurred in response to
addition of both N and P, DIN treatment alone stimulated chlorophyll a in some
treatments (Rossignol et al.. 2011). A 3-year data set from Raritan Bay, NJ indicates that
eutrophication contributed to high concentrations of chlorophyll a from 2010-2012
(Rothenbereer et al.. 2014). Winter and spring N loading to Mattawoman Creek estuary
and other shallow estuaries in the Chesapeake Bay region was highly correlated to
summer chlorophyll a concentrations (Bovnton et al.. 2014). However, after point source
nutrient (N and P) reductions were enacted, a decrease in chlorophyll a was observed in
Mattawoman Creek. In North Carolina's Neuse River estuary, it appears that the elevated
loading of total N (TN) contributed to higher annual average chlorophyll a values from
2000-2009 (Lebo et al.. 2012).
While recent research indicates that N loading remains a strong predictor of chlorophyll a
concentrations under most conditions, there has been increasing discussion regarding the
role of other factors in altering the strength of this relationship. The impact of nutrient
inputs can at times be overtaken by hydrologic features, seasonal variations, climatic
changes and oscillations exerting greater control over phytoplankton dynamics (Paerl et
al.. 2010). In Corpus Christi Bay, TX, rainfall events altered nutrient N:P ratios but did
not affect chlorophyll a (Turner et al.. 2015). Instead, chlorophyll a concentration in
weekly sampling mainly followed seasonal trends by increasing in spring and summer
and decreasing in fall and winter. No significant relationships were observed between
annual TN, total phosphorus (TP) load, and annual mean chlorophyll a concentrations in
the Guana Tolomato Matanzas estuary in Florida, rather phytoplankton biomass was
influenced by temperature, precipitation, water residence times and tidal exchange in this
well-flushed system (Hart et al.. 2015). Glibert et al. (2014) found significant increases in
chlorophyll a at only three out of seven study areas in the Maryland/Virginia coastal
lagoon, although regionally chlorophyll a concentrations increased due to increasing
anthropogenic nutrient loads and increased freshwater flow in the early 2000s. In San
Francisco Bay, low N uptake and rates of primary production were associated with high
freshwater flow while during conditions of low freshwater flow elevated chlorophyll a
and blooms occurred (Wilkerson et al.. 2015). The authors suggested that this results
from uptake of ambient NO, by phytoplankton enabled by increased NH4+ loads.
Using satellite and meteorological data from U.S. Atlantic coastal waters, Kim et al.
(2014b) found that precipitation events were associated with increased levels of
chlorophyll a in low nutrient areas (defined as having NO? concentrations of less than
1 |iM). but precipitation was correlated with lower chlorophyll a concentrations in high
nutrient areas (defined as having NOs concentrations greater than 1 (iM). This is likely
because in low nutrient areas, new N input from precipitation stimulated phytoplankton
growth. In areas already high in nutrients, wind associated with precipitation events may
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have deepened the mixed layer and the resulting loss of light availability caused
chlorophyll a concentrations to decline (Kim et al.. 2014b).
10.2.2 Harmful/Nuisance/Toxic Algal Blooms
Nuisance or toxic algal blooms reflect the proliferation of a toxic or nuisance algal
species that negatively affects natural resources or humans. Blooms are increasing in
outbreak frequency and extent in the U.S. and other countries and N is one of the
nutrients known to promote HAB formation (Baron et al.. 2012; Heisler et al.. 2008). A
concurrent increase in atmospheric sources of N to coastal areas and proliferation of
harmful algal bloom formation have been recognized for several decades (Paerl et al..
2002; Paerl and Whitall. 1999; Paerl. 1997V HABs caused by N enrichment can release
toxins that are harmful to fish and shellfish and that may accumulate in predators and
organisms higher in the food web (Johnson et al.. 2010). Other blooms are not toxic but
may cause low DO events due to very high biomass, or are so small they clog filter
feeders' siphons causing shellfish mortality (Gastrich and Wazniak. 2002). For example,
during blooms in Florida Bay in 2002 and 2005, Synechocococcus spp. comprised >99%
of the phytoplankton assemblage and reached 10s cells/L (FWRI. 2007; Glibert et al..
2004). Similarly, in the Chincoteague Bay, Aureococcus anophagefferens has been found
to comprise from 85 to 95% of the phytoplankton community during bloom periods [e.g.,
Wazniak and Glibert (2004)1. These species are much smaller than typical phytoplankton
that dominate estuarine environments, being less than 3 |im in size (Glibert et al.. 2010b).
In addition to effects on biota, HABs cause a range of responses in humans from direct
dermatitis, such as swimmers itch, to severe food poisoning, liver and kidney toxicity,
and paralysis (Peel et al.. 2013; Johnson et al.. 2010).
The frequency and duration of algal blooms is one of five indicators used in the NEEA
and was included as an indicator of eutrophic conditions in the 2008 ISA (U.S. EPA.
2008a; Bricker et al.. 2007). Of the 81 estuary systems for which data were available in
the NEEA, 26 exhibited a moderate or high symptom expression for nuisance or toxic
algae (Bricker et al.. 2007). In the previous 2008 ISA review, the frequency of
phytoplankton blooms and the extent and severity of hypoxia were documented to have
increased in the Chesapeake Bay (Officer et al.. 1984) and Pamlico Sound estuaries in
North Carolina (Paerl and Piehler. 2008) and along the continental shelf adjacent to the
Mississippi and Atchafalaya river discharges to the Gulf of Mexico (Eadie et al. 1994).
New tools and monitoring approaches for further characterization of HABs have become
available since the 2008 ISA. For example, Solid Phase Adsorption Toxin Tracking
(SPATT), a passive sampling tool which simulates the contamination of filter-feeding
bivalves has been used recently in the field to detect presence of algal toxins with greater
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accuracy than grab sampling methods (Gibble and kudcla. 2014; kudcla. 2011; Lane et
aL 2010). Remote sensing systems are increasing being used to forecast and monitor
HABs in coastal waters (Klemas. 2012).
Recent studies indicate that the harmful effects of HAB toxins on fish and wildlife may
persist even when the bloom conditions have passed. Wood et al. (2014) found that HAB
toxins in consumer species persisted in overwintering populations of estuarine finfish,
common wedge clam (Rangia cuneata) and blue crab (Callinectes sapidus) in the James
River estuary, Virginia although the highest tissue concentrations and greatest percent of
individuals affected were observed when toxin levels in the water column were also the
highest. The toxin was present in both muscle and viscera of blue crabs at concentrations
that have been shown to have physiological effects on other species of estuarine crab
(Wood et al.. 2014). In Monterey Bay, CA, deaths of 21 sea otters (Enhydra lutris), a
federally listed threatened species, were attributed to hepatotoxic shellfish poisoning due
to trophic transfer of microcystin, a class of toxins produced by HABs that were observed
in this study to originate from nutrient-impaired rivers (Miller et al.. 2010).
N enrichment is widely understood to be a prominent cause of the expansion and
persistence of cyanobacterial algal blooms (Paerl and Otten. 2013). Post-2007 studies
have further elucidated the role of nutrients and form of N in algal bloom formation and
occurrence. The abundance of one HAB species (Heterosigma akashiwo) was found to be
correlated with NO? levels in Raritan Bay, NJ (Rothenberger et al.. 2014). In San
Francisco Bay, a comparison ofN isotopes in cells of the HAB species Microcystis
aeruginosa with N in rivers flowing into the bay indicated the primary source of N that
supported the bloom formation was likely NHV. not NO? (Lehman et al.. 2015).
Phytoplankton community dynamics varied with the form of N in nutrient enrichment
experiments using water from the New River Estuary, NC (Altinan and Paerl. 2012).
Photopigment analysis used to identify and quantify taxonomic groups revealed that
addition of riverine dissolved organic nitrogen (DON) promoted dinoflagellates,
chloropytes, and myxoxanthophyll (cyanobacteria) while zeaxanthin (cyanobacteria) was
most frequently detected with inorganic N.
Laboratory studies with HAB species further support the role of the form of N and
growth of HABs. H. akashiwo is able to grow well with a pulsed supply of NH4, NO3 .
and urea under low light conditions and assimilate stores of N nutrients, suggesting that
this species could outcompete diatoms in silicate-limited, N enriched coastal areas (Kok
et al.. 2015). In nutrient amendment experiments with water collected from the tidally
influenced Transquaking River, which flows into Chesapeake Bay, Microcystis was
stimulated by N more frequently than P and abundances of toxic and nontoxic strains
were enhanced to different degrees by inorganic and organic N (Davis et al.. 2010).
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Response of Alexandrium fimdyense to nutrient addition varied throughout the course of
bloom events in Northport-Huntington Bay, NY (Hattcnrath et al.. 2010). Addition of
NH4+ to bloom water most frequently resulted in statistically significant increases of A
fundyense density and toxin concentration compared to other forms of N (glutamine,
N03~, and/or urea).
Modeling studies have reported on potentially altered future scenarios of HAB formation,
intensity, duration, and toxicity due to changes in N deposition (Glibcrt et al.. 201 Ob).
Pinder et al. (2008) reported on modeled scenarios that predict alterations in the
frequency, intensity, toxicity, and species composition of algal blooms due to higher rates
of N deposition and changes in the reduced-to-oxidized N ratio. Future changes in HAB
dynamics will be affected by climate change and increased N loading, and integrated
ecosystem models that couple the atmosphere, land, and coastal ocean are needed to
estimate these HAB responses (Glibcrt et al.. 2010a).
It should be noted that there has recently been some question of the strength of the link
between changing nutrient ratios (as a result of anthropogenic N inputs) and the
abundance, frequency, and toxicity of HABs (Davidson et al.. 2012). When neither
nutrient contributing to the ratio is limiting, then the value of the nutrient ratio does not
affect species competition. In their review, Davidson et al. (2012) also found that in
general, laboratory studies show that toxin production can be influenced by nutrient
ratios, but extrapolation of those results to the specific species and conditions in the field
is difficult. Long-term monitoring (1987-2005) of phytoplankton populations in the bay
of Fundy in southwestern New Brunswick, Canada did not link HABs to nutrients, rather
climate and weather patterns explain many species abundances and intensities (Martin et
al.. 2009). Vox Alexandrium fundyense there was a negative relationship with cell density
and NC>3~.
Table 10-3 summarizes new studies on levels and forms of N at which effects are
manifested in phytoplankton.
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Table 10-3 Levels and forms of nitrogen at which effects on phytoplankton are manifest in U.S. coastal waters
evaluated in the literature since the 2008 Integrated Science Assessment for Oxides of Nitrogen and
Sulfur-Ecological Criteria.
Study Site
Ambient N
Deposition
N Additions
Ecological/Biological Effects
Species
Reference
Northport-
Huntington Bay
complex, NY
Addition of NH4+
(10 |jM-40 |jM)
Addition of NhU"1" significantly increased A. fundyense
densities compared to the control. The addition of NhV
(40 |jM) yielded a significant increase in both A.
fundyense densities and toxin concentrations by fourfold
and eightfold, respectively, compared to controls.
Phytoplankton
(.Alexandrium
fundyense)
Hattenrath et al.
(2010)
Raritan Bay, NJ
Ambient levels
Multivariate analyses of a 3-yr data set indicated that
abundance of HAB species Heterosigma akashiwo is
positively associated with NO3" in Raritan Bay. Both
climatic conditions and nutrient concentrations affect
phytoplankton bloom composition in the bay.
Phytoplankton
(Heterosigma
akashiwo and
13 other HABs
identified)
Rothenberaer et
al. (2014)
Ocean surface
from 28°N to
44°N and from
the East Coast
of the U.S. to
60-70°W
Based on direct
measurements of
wet deposition along
the East Coast of
the U.S., the N
supply through wet
deposition was
estimated to be
25-45 mmol N/m2/yr
Precipitation events in coastal waters of the eastern U.S.
increased the chlorophyll a concentration up to 15% in
low-nutrient areas (<1 |jM NO3") but decreased the
chlorophyll a concentration in nutrient-replete areas
(>1 |jM NO3"). The authors suggested that in
nutrient-depleted areas (south of 36°north), the added
nutrients were a dominant factor increasing the
chlorophyll a concentration, whereas in the
nutrient-replete areas (north of 36°north), where
phytoplankton growth was light limited, reduced light
availability was the dominant factor determining reduced
chlorophyll a concentration.
Phytoplankton
Kim et al. (2014b)
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Table 10-3 (Continued): Levels and forms of nitrogen at which effects on phytoplankton are manifest in U.S.
coastal waters evaluated in the literature since the 2008 Integrated Science Assessment
for Oxides of Nitrogen and Sulfur-Ecological Criteria.
Study Site
Ambient N
Deposition
N Additions
Ecological/Biological Effects
Species
Reference
Matta woman
Creek,
Chesapeake
Bay
Used atmospheric
deposition data from
Bovnton et al.
(2008) including N
from both wet and
dry deposition
(0.81 mg N/L as an
annual average
concentration).
Direct atmospheric
deposition to surface
waters of the creek
contributed about
6,000 kg N/yror
about 16 kg N/day to
the creek system.
Strong relationships were found between N loading and
algal biomass and between algal biomass and water
clarity. Winter-spring N loading and summer chlorophyll
a were found to be highly correlated, a relationship which
appears to be linear.
Phytoplankton and
SAV
Bovnton et al.
(2014)
Tidally
influenced
Transquaking
River which
flows into
Chesapeake
Bay
20 |jM (NOs"),
20 |jM NH4+ (NH4+),
10 |jM (= 20 |jM N)
urea, 10 |jM
(= 20 |jM N),
L-glutamine (GA), P
(1.25 |jM
orthophosphate), or
a combined
treatment of NO3"
and P
Microcystis was simulated by N more frequently than P
and abundances of toxic and nontoxic strains were
enhanced to different degrees by inorganic N and
organic N. Toxic microcystis abundance increased more
with inorganic N than organic N.
Toxic and nontoxic Davis et al.
strains of Microcystis (2010)
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Table 10-3 (Continued): Levels and forms of nitrogen at which effects on phytoplankton are manifest in U.S.
coastal waters evaluated in the literature since the 2008 Integrated Science Assessment
for Oxides of Nitrogen and Sulfur-Ecological Criteria.
Study Site
Ambient N
Deposition
N Additions
Ecological/Biological Effects
Species
Reference
Maryland and
Virginia coastal
bays
Measurements of
atmospheric
deposition since
2000, based on the
NADP, suggest that
NO3" is decreasing
and NH4+ from
deposition is stable
for the coastal bays
(NADP data
http://nadp.sws.uiuc.
ed u/sites/ntn/NTNtre
nds.html?sitelD=MD
18).
Virtually all of the N in the water column is now in the
chemically reduced form, NhV or DON, resulting in
phytoplankton community shifts to those species that
can do well under such conditions. Submerged aquatic
vegetation has decreased.
Phytoplankton and
SAV
Glibert et al.
(2014)
Alligator River
estuary, NC
Potential for
atmospheric
deposition of N from
nearby farm (wet
NH4+ concentrations
increased greatly
close to farm).
DIN additions:
140 |jg N-NH4/L,
140 |jg N-NOs/L,
and 70 pg N-NH4/L
plus 70 pg N-NO3/L
Significant increase in phytoplankton biomass (chl a) and Phytoplankton
rates of primary productivity due to N enrichment. DIN
treatments alone significantly stimulated chl a in two out
of five tests for all three DIN addition treatments,
although DIN + DIP treatments provided the largest
increase in chl a.
Rossiqnol et al.
(2011)
Neuse River
Ambient, acute DIN
Study noted increase in phytoplankton bloom frequency
Phytoplankton
Paerl et al.
estuary, NC
inputs via runoff
from hydrologic
pulses (hurricanes,
tropical storms,
heavy rainfall
events)
and magnitude (indicated by increasing chl a variability)
overtime in response to acute DIN inputs from
hydrologic pulses. Control of algal bloom duration,
thresholds, taxonomic composition, and spatial extent
may be dictated by climatic changes and oscillations
instead of nutrient inputs.
(2010)
New River
N addition to
Varying the form of nutrients promoted growth of
Phytoplankton
Altman and Paerl
estuary, NC
estuary water in the
form of DIN, organic
N from river water
(with disolved
inorganic P) or urea
different phytoplankton groups based on photopigment
analysis. Dinoflagellates, chlorophytes, and
cyanobacteria responded to dissolved organic N while
cyanobacteria increases were most frequent with
inorganic N addition.
(2012)
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Table 10-3 (Continued): Levels and forms of nitrogen at which effects on phytoplankton are manifest in U.S.
coastal waters evaluated in the literature since the 2008 Integrated Science Assessment
for Oxides of Nitrogen and Sulfur-Ecological Criteria.
Ambient N
Study Site
Deposition
N Additions
Ecological/Biological Effects
Species
Reference
Ten Mile Creek,
High median
Chlorophyll a was negatively correlated with N
Phytoplankton
Yana et al.
Indian River
concentrations of
concentrations. This result is thought to be due to the
(2008)
Lagoon, FL
total N
strong influence exerted by hydrologic factors (such as
(0.988 mg/L),
freshwater inflow, salinity, pH, and temperature), which
NO3--N
were all positively correlated with chl a concentrations
(0.104 mg/L),
during this study.
NH4+-N
(0.103 mg/L),
and total Kjeldahl N
(0.829 mg/L)
Nueces Estuary
377 x 10s g N/yr
Rainfall events altered nutrient N:P ratios but did not
Phytoplankton
Turner et al.
and Corpus
deposition to the
affect chlorophyll a. Instead, chlorophyll a concentration
(2015)
Christi Bay, TX
estuary surface. (8%
in weekly sampling mainly followed seasonal trends by
of total N loadina.
increasing in spring and summer and decreasing in fall
based on data from
and winter.
Brock. 2001)
San Francisco NO3" and NhV A comparison of N isotopes in cells of the HAB species Phytoplankton Lehman et al.
Bay/estuary measured from two Microcystis aeruginosa with N in rivers flowing into the (cyanobacteria (2015)
source estuaries bay indicated the primary source of N that supported the Microcystis
bloom formation was likely NhU"1", not NO3. aeruginosa)
San Francisco
Bay/estuary
Ambient nitrate
ranged 0.19 to
0.36 mg/L. Ambient
ammonia ranged
0.02 to 0.06 mg/L.
The greatest chl a concentration and cell density
occurred in the San Joaquin River estuary which had a
high average nitrate concentration (0.36 mg/L). The
second highest chl a concentration and cell density
occurred in the Old River estuary which had relatively
low N concentration (mean 0.19 mg/L). Differences in chl
a were correlated with environmental conditions,
particularly streamflow and water temperature and
secondarily to nutrient concentrations and ratios.
Phytoplankton
(cyanobacteria
Microcystis
aeruginosa)
Lehman et al.
(2008)
DIN = dissolved inorganic nitrogen; DON = dissolved organic nitrogen; HAB = harmful algal blooms; N = nitrogen; NADP = National Atmospheric Deposition Program;
NH4+ = ammonium ion; N03" = nitrate; P = phosphorus; SAV = submerged aquatic vegetation; W = west.
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10.2.3
Macroalgal Abundance
Abundance of macroalgae generally referred to collectively as seaweed was an indicator
of eutrophic condition in the 2008 ISA (U.S. EPA. 2008a'). Macroalgae have been
combined with other indicators to classify estuarine condition (Borjaetal.. 2012). For
example, NEEA includes an assessment of macroalgae (Bricker et al.. 2007). Macroalgal
blooms can contribute to loss of important SAV by blocking the penetration of sunlight
into the water column. Although macroalgal data for estuaries in the U.S. were generally
sparse, the NEEA reported high macroalgal expression in 15 of the 64 estuaries evaluated
(Bricker et al. 2007). In other places such as lagoons with limited oceanic exchange,
macroalgae may be a more sensitive biological indicator than phytoplankton (e.g.,
McLaughlin et al.. 2014; Nobre et al.. 2005). For example, in most estuaries of the
Southern California Bight, macroalgae is the dominant primary producer and a key
indicator of eutrophication (McLaughlin et al.. 2014).
Opportunistic, fast-growing macroalgae can exhibit very high rates of N uptake during
periods of high N availability and can often outcompete or block out light for other
macrophytes when N loads are high and variable (Abreu etal.. 2011). This growth of
macroalgae can also smother corals, clams, oysters, and other biota (Bricker et al.. 2007)
and contribute to declines in seagrasses (Olvamik and Stachowicz. 2012). These
macroalgae also tend to preferentially uptake N in the form of NH4+. In a Danish study,
sea lettuce (Ulva lactuca), which is a common species of macroalgae in U.S. coastal
waters, grew faster and exhibited greater biomass when subjected to NH4+ as the N
source as compared to NOs (Ale etal.. 2011). It was thought this is due to the fact that
reduced N can be more easily assimilated and used by algae. Similarly, in experimental
manipulations with Gracilaria tenuistipitata, an opportunistic macroalgal species from
China, when both NH44" and NO, were available, NH44" was assimilated more rapidly and
algal biomass was higher than with NO3 addition alone (Wang et al.. 2014a). Growth of
Caulerpa cylindracea, an invasive macroalga in the Mediterranean Sea, was not inhibited
by high NH3, and was able to outcompete native macroalgae in experimental plots with
nutrient addition (Gennaro et al.. 2015).
Southern California estuaries, some of the most nutrient enriched in the world, have not
been well studied in the past, but recent work is providing important information about
macroalgal growth in response to N loading to these systems. Opportunistic macroalgae
(Ulva intestinalis and Ulva expansa) were shown to take up NO3 from the water very
efficiently at many concentration levels, giving these species the ability to outcompete
other algae in estuaries subject to varying nutrient loads (Kennison et al.. 2011). Algae
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that were depleted in N took up NO3 at higher rates than enriched algae, and uptake rates
slowed as the algae became saturated.
However, macroalgal abundance was not found to be directly related to water or sediment
N concentrations in southern California estuaries (Kennison and Fong. 2014). Rather,
macroalgal blooms occurred throughout the year and appeared to be influenced by the
unique physical and hydrological differences among the different estuaries. For instance,
in one estuary with high nutrient levels in both water and sediment, there was little to no
macroalgal biomass present. This was possibly due to high water velocities that
prevented young algal filaments from attaching, or perhaps due to NO3 or pesticide
toxicity, although there was not enough evidence to support the latter (Kennison and
Fong. 2014). In other estuaries, comparatively high algal biomass was found year-round
even when nutrient supplies were lower than other sites (although still N enriched),
perhaps due to low rates of tidal flushing and longer water residence times. Internal
nutrient processing, variable hydrological regimes, and multiple external nutrient sources
may all contribute to eutrophic conditions (Kennison and Fong. 2014).
10.2.4 Dissolved Oxygen
DO was included in the 2008 ISA, the NCCA and the NEEA as an indicator of eutrophic
condition (U.S. EPA. 2008a). Additional information on DO as a chemical indicator is
provided in Chapter 7. The decomposition of organic matter associated with increased
algal abundance consumes DO and can reduce DO concentrations in eutrophic waters to
levels that cannot support aquatic life (Jewett etal.. 2010). Generally, at DO levels from
3 to 4 mg/L, some biota are impacted with increasing effects observed at lower DO
concentrations (Figure 10-4). Decreased DO can lead to development of hypoxic or
anoxic zones that are inhospitable to fish and other life forms and can impact ecosystem
processes (Diaz and Rosenberg. 2008). For example, in Chesapeake Bay, macrobenthic
production was 90% lower during hypoxic conditions resulting in a biomass loss similar
to 7,320-13,200 metric tons C over an area of 7,720 km2 (Sturdivant et al.. 2014). The
authors estimated this represented a displacement of 20 to 35% of macrobenthic activity
during the summer.
In the U.S., the incidence of hypoxia has increased almost 30-fold from 1960 to 2008 and
is now reported in more than 300 systems (Jewett et al.. 2010). Eutrophication-induced
hypoxia, which has been documented globally, can be characterized by both the duration
of the event and the ecosystem response (Diaz and Rosenberg. 2008). Summer hypoxia is
most common, followed by systems that experience periodic oxygen (O2) depletion that
may occur more often than seasonally. In these hypoxic and anoxic areas ("dead zones")
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only organisms that can live with little or no O2 are present (Jewett et al.. 2010). Once an
ecosystem reaches severe seasonal hypoxia, there is a shift to benthic organisms with
shorter life spans and smaller body size (Diaz and Rosenberg. 2008).
Recent research has shown that the duration of a hypoxic event is one of the most
important factors affecting macroinvertebrate density and species composition. Baustian
and Rabalais (2009) found that hypoxia duration (the number of days during which O2
concentrations were below 1 mg/L) was highly correlated with both reduced species
density and diversity in the northern Gulf of Mexico. Very low O2 levels can be lethal to
fish with no means of escape, and it has been suggested that even sublethal hypoxia may
lower the breeding rate and affect fish populations (Moran et al.. 2010). Hypoxia has
been shown to act as an endocrine disruptor in Atlantic croaker (Micropongonias
undulatus) in laboratory studies and biomarkers of reproductive function and endocrine
disruption are observed in field-collected individuals (Murphy et al.. 2009; Thomas and
Rahman. 2009; Thomas et al.. 2007). Hypoxic conditions increase nitric oxide and super
oxide radicals in brain tissue in croakers, which causes cellular oxidative damage and
inhibited protein expression in the hypothalamus leading to neuroendocrine effects
(Rahman and Thomas. 2015).
Low O2 conditions have also been shown to alter animal behavior (Section 10.4.1). O2
content influences hatching rate and parental effort among other reproductive behaviors
in three-spined sticklebacks (Gasterosteus aculeatus), so eutrophication-induced hypoxia
may alter reproductive output in some fish populations (Candolin. 2009). However, it
does not appear that hypoxia negatively affects fisheries below what would be predicted
from N loadings alone, except in circumstances where raw sewage is released or when
critical habitat is lost for very sensitive species (Breitburg et al.. 2009).
Effects of low DO appear to be exacerbated by presence of multiple stressors. For
example, Gobler et al. (2014) examined concurrent effects of low DO and acidification
on early lifestages of bay scallops (Argopecten irradians) and hard clams (Mercenaria
mercenaria). Observations in later lifestages of clams indicated that growth rates
decreased by 40% in combined exposures to hypoxia and acidification. Additional studies
with earlier lifestages indicated effects were more severe with costressors than with either
hypoxia or acidification alone.
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100% Saturation
Mob' le Fauna Begin
to Migrate to Higher
DO Areas
Shrimp & Crabs
Absent
Burrowing Slops
Stressed Fauna
Emerge & Lay on
Sediment Surface
Mortality of Tolerant
Fauna
Avoidance by
Fishes
Fishes Absent
Fauns Unable to Escape
Initiate Survival
Behaviors
7 to 8 rog/r
Normal Activity A Behavior
3 to 4
Mortality of Sensitive
Fauna
1
Formation of Microbial
Mats
Sediment Geochemistry
Drastically Altered
Mo Mecrofauna
Survive
Hydrogen Sulfide Builds Up
In Water Column
EUr»*d on Out# artd Kotanterg (IMS) md lUtulm it iL (2031)
DO = dissolved oxygen; I = liter; mg = milligrams.
Source: Jewett et al. (20101 and based on Diaz and Rosenberg (1995) and Rabalais and Turner (2001).
Figure 10-4 The range of ecological impacts exhibited as dissolved oxygen
levels drop from saturation to anoxia.
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At the time of the last review, it was documented that the largest zone of hypoxic coastal
water in the U.S. was the northern Gulf of Mexico on the Louisiana-Texas continental
shelf (U.S. EPA. 2008a). Since the 2008 ISA observations continue to indicate a large
zone of hypoxia in the northern Gulf of Mexico during the summer months associated
with increased N loading from the Mississippi and Atchafalaya River Basins. The
northern Gulf of Mexico hypoxic zone is the largest in the U.S. and the second largest in
the world, averaging about 16,500 km2 (10,250 mi2) in size, and forms annually between
May and September (Dale et al.. 2010; Jewett et al.. 2010). The size of the midsummer
bottom-water hypoxia area (<2 mg/L DO) in the Northern Gulf of Mexico has varied
considerably since 1985, ranging from 24 km2 (15 mi2) in 1988 (a drought year in the
Mississippi Basin) to approximately 13,700 km2 (8,500 mi2) in 2002 (U.S. EPA. 2016f).
In the latest year of sampling, 2014, the hypoxic zone measured 8,100 km2 (5,050 mi2).
Over the full period of record (1985-2014), the area with DO less than 2 mg/L has
averaged approximately 8,500 km2 (5,300 mi2). Alexander et al. (2008) used the
SPARROW water quality model to show that atmospheric deposition to watersheds in the
Mississippi River Basin is the second largest source of N (16%) to the Gulf, after corn
and soybean production (52%).
The Hypoxia Task Force (Mississippi River/Gulf of Mexico Watershed Nutrient Task
Force) is a federal/state partnership (five federal agencies, the National Tribal Water
Council and 12 states bordering the Mississippi and Ohio rivers) established in 1997 with
the goal of reducing nutrient inputs and the size of the hypoxic zone in the Gulf of
Mexico (U.S. EPA. 2015c). The task force is working toward the goal of reducing the
areal extent of the Gulf of Mexico hypoxic zone to less than 5,000 km2 by 2035, with an
interim target of 20% nutrient load reduction by the year 2025. This was revised from the
2001 action plan that called for the described reductions by 2015 (U.S. EPA. 2001). Each
state in the task force has a nutrient reduction plan and progress toward stated goals are
reported in the Mississippi River/Gulf of Mexico Watershed Nutrient Task Force Report
to Congress (U.S. EPA. 2015c) as required by the Harmful Algal Bloom and Hypoxia
Research and Control Amendments Act of 2014 (HABHRC Act. 2014). Other states not
included in the Mississippi River/Gulf of Mexico Watershed Nutrient Task Force have
nutrient reduction programs in place.
Hypoxic conditions are reported from other U.S. locations. For example, in the shallow
estuary of Long Island Sound, atmospheric deposition is considered to comprise a
significant fraction of total N loading [19%; (Whitall et al.. 2004)1. and DO levels below
3 mg/L are common, with levels below 2 mg/L known to occur. During some years,
portions of the Long Island Sound bottom waters become anoxic (DO <1 mg/L),
(Latimer et al.. 2014). The maximum extent and duration of hypoxic events (<2 mg/L
DO) in Long Island Sound has varied considerably since the 1980s (U.S. EPA. 2016f).
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Between 1987 and 2014, the average annual maximum extent was 98 km2 (61 mi2). In
2014, the hypoxic area was 32 km2 (20 mi2), with the lowest DO levels occurring in the
western end of the Sound. The shortest hypoxic event occurred in 2014, lasting 2 days.
The longest hypoxic event was 71 days in 1989. Over the full period of record
(1987-2014), the average annual maximum duration was 31 days. Other estuaries
identified in the 2008 ISA where hypoxic conditions occur included Chesapeake Bay and
the Pamlico Estuary in North Carolina (U.S. EPA. 2008a).
Climate change and increasing N loading to coastal ecosystems are both expected to
widen the distribution and increase the size of areas affected by eutrophication-induced
hypoxia, while also increasing the frequency and persistence of these events KRabalais et
al.. 2010); Chapter 131.
10.2.5 Submerged Aquatic Vegetation
SAV, rooted vascular plants that grow to the surface but do not emerge from the water,
are important to the quality of coastal ecosystems because they provide habitat for a
variety of aquatic organisms, serves as nursery grounds for estuarine invertebrates and
fish, absorb excess nutrients, and trap sediments (U.S. EPA. 2008a; Handlev et al.. 2007).
The loss of SAV can, therefore, have a cascade of effects on other ecosystem
characteristics and ecosystem services. Water clarity is important for photosynthesis of
SAV (Handlev et al. 2007). Seagrass loss is occurring globally with nutrient enrichment
as a major driving factor contributing to declines in SAV coverage (Latimer and Rego.
2010; Wavcott et al.. 2009). SAV is included as a biological indicator for estuarine
condition for U.S. coastal waters in ASSETS-ECI in the NEEA and in U.S. EPA's Report
on the Environment (U.S. EPA. 2016f; Bricker et al.. 2007).
At the time of the 2008 ISA estimates of historical losses of SAV and declines in habitat
were available for some coastal regions of the U.S.; although, there were few data
documenting the long-term response of SAV to N loading. In Waquoit Bay, MA, Valiela
et al. (1992) reported a strong negative relationship between modeled N loading and
measured eelgrass (Zostera marina) area based on measurements of eelgrass coverage
from 1951 to 1990. In the NEEA report only a small fraction of the estuary systems
evaluated reported high severity of SAV loss from the 1990s to 2004 (Bricker et al..
2007). in part, because historical losses wiped out seagrasses in many estuaries, and
recent changes do not seem of high severity.
Since the 2008 ISA additional studies are available on the relationship between N loading
and SAV abundance including the development of thresholds of response to N loading in
seagrasses (Table 10-4). Orth et al. (2010) observed a consistent negative correlation
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between SAV abundance and N loading based on water quality data in Chesapeake Bay
from 1984-2006. In the Potomac River, a major tributary to Chesapeake Bay, a reduction
in total N from point and nonpoint sources was significantly correlated to increased SAV
abundance and diversity using field data from 1990 to 2007 (Ruhl and Rvbicki. 2010V
Similarly, the reduction of N and P input from point sources into Mattawoman Creek, a
tributary to Chesapeake Bay, led to large increases in SAV coverage and density
(Bovnton et al.. 2014). Benson et al. (2013) identified a tidal-averaged total N
concentration of <0.34 mg/L as a threshold for healthy eelgrass in a survey of
19 Massachusetts estuaries. Eelgrass coverage decreases markedly in shallow estuaries in
New England with N loading rates >100 kg N/ha/yr (based on nitrogen loading model
[NLM] estimates from wastewater, fertilizer, and atmospheric deposition inputs) and
levels above 50 kg/ha/yr are likely to impact habitat extent (Latimer and Rego. 2010).
These ranges were found to be comparable to loading thresholds identified in other east
coast estuaries (Table 10-4). In a modeling study using NLM applied to small-to-medium
sized estuaries of southern New England, direct atmospheric deposition to the water
surface made up an average of 37% of the N input while indirect deposition via the
watershed averaged 16% of N loading although the percentage varied widely for
individual estuaries (Latimer and Charpentier. 2010).
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Table 10-4 Nitrogen loading thresholds from multiple watershed sources versus
eelgrass loss.
Loading Threshold kg/ha/yr
Description
>20
•
Areal cover of eelgrass sharply reduced
100
•
Meadows disappeared rCape Cod estuaries, n = 10: (Bowen et
al.. 2007)1
-30
•
Substantial eelgrass loss (80-96% of bed area)
>60
•
Total disappearance TCape Cod estuaries, n = 7: (Hauxwell et
al.. 2003)1
>64a
•
Threshold based on nonparametric change-point analysis
[95% probability of change; Chesapeake Bay estuaries,
n = 101: (Li et al.. 2007)1
>52
•
Threshold based on nonparametric change-point analysis
[95% probability of change; New England estuaries, n = 57;
(Latimer and Reao. 2010)1
Consensus of Literature
Percent Eelgrass Area Loss (n = 57):
Mean
Median 25th Percentile 75th Percentile
<50
62%
73% 39% 78%
51-99
88%
89% 82% 98%
>100
93%
100% 95% 100%
aThis only includes point source inputs.
Source: Latimer and Rego (2010).
The extent of SAV in the Chesapeake Bay increased from 41,000 acres (16,600 hectares)
in 1978 to a peak of 91,000 acres (36,800 hectares) in 2015 based on data collected by
the Virginia Institute of Marine Science KVIMS. 2016); Figure 10-51 as reported in U.S.
EPA's Report on the Environment (U.S. EPA. 2016f). SAV acreage has fluctuated in the
bay since 2002, covering an estimated 60,000 acres in 2013 then increasing in the most
recent survey conducted in 2015. This estimate is based on black and white,
l:24,000-scale aerial photographs of the Chesapeake Bay. Aerial monitoring first
occurred in 1978, and has occurred annually since 1984 (except during 1988). The SAV
survey targets SAV species, which as a group are sensitive to disturbance, particularly
from eutrophication and associated reductions in light availability. Pilots follow fixed
flight routes to comprehensively photograph all tidal shallow water areas of the bay and
its tidal tributaries. Orth et al. (2010) reported a strong correlation between tributaries
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where nutrient reductions have occurred and increases in seagrass abundance; however,
further reductions are necessary to meet SAY restoration targets.
Exhibit 1. Extent of submerged aquatic vegetation (SAV) in the Chesapeake
Bay, 1978-2015
100
A
"O
s=
"3
§
so
Estimated additional acreage
| Mapped acreage
1975 1962 19E6 1990 1994 199B 2002 2006 2010 2014
Year
There were partial Bay-wide surveys from 1 979 to 1 983, and no survey in 1 9S8.
Information on the statistical significance of the trend in this exhibit is not currently available. For
more information about uncertainty, variability, and statistical analysis, view the technical
documentation for this indicator.
Data source: Chesapeake Bay Program, 2016
SAV = submerged aquatic vegetation.
Source: U.S. EPA (2016fl.
Figure 10-5 Extent of submerged aquatic vegetation in the Chesapeake Bay
1978-2015.
In Tampa Bay, FL, data on seagrass (primarily Thalassia testndimim) extent is available
as far back as the 1950s. In the 1970s and early 1980s, the bay exhibited signs of
increasing eutrophication including loss of seagrasses. Seagrass coverage has recovered
to relatively predisturbed conditions (approx. 15,380 ha) following N controls
implemented in the mid-1980s (Greening et al.. 2014; Greening et al.. 2011). Although
the nutrient-load hypothesis of Brauer et al. (2012) suggests that algae can out-compete
or block out light for other macrophytes under high or variable nutrient loads this is not
always the case. For example, in Yaquina Bay in Oregon, distribution of eelgrass has
remained stable despite high nutrient loads and algal blooms (Kaldv. 2014).
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In other U.S. coastal areas, SAV coverage has declined. SAV coverage in the coastal
lagoon of Maryland and Virginia showed an increase with time until the early 2000s, and
then declined in the past decade, likely due to increasing anthropogenic nutrient inputs
that were accelerated by increased freshwater flow over the same time period (Glibert et
al.. 2014). In an analysis of 12 years of data for eelgrass areal coverage along the
Massachusetts coastline, there was an overall decrease in seagrass abundance although
the amount of change was highly variable between individual embayments (Costello and
Kenworthv. 201IV
SAV is often at a competitive disadvantage under N enriched conditions due to the fast
growth of opportunistic macroalgae that preferentially take up NH4+ and can block light
from seagrass beds (Abreu et al.. 2011). Eelgrass from the Pacific Northwest exhibited
increased growth rates with increasing NH4+ concentrations, but growth rate was not
related to NOs concentration (Kaldv. 2014). Temperature was found to significantly
affect the response of eelgrass to nutrients but the effects were not synergistic. A
significant increase in leaf length and decreases in shoot density and aboveground and
belowground biomass in eelgrass was observed concurrent with increased shading by
algae in field studies of 12 estuaries in Atlantic Canada (Schmidt et al.. 2012V In the
same study, C and N storage (two ecosystem services provided by eelgrass) declined with
increasing eutrophication.
A modeling framework to link variable freshwater inputs with seagrass (Halodule
wrightii, Thalassia testudinum) biomass and timing of growth and chlorophyll a was
applied to the Caloosahatchee River Estuary in southwest Florida (Buzzelli et al.. 2014).
The model predicted organic N in the upper estuary, and chlorophyll a in time and space
reasonably well; however, there was more variation in NH44" while NOx" (nitrate-nitrite)
was proportional to freshwater inflow. Overall, the model reflected variations in seagrass
biomass, although timing and growth did not match the variability of field observations.
10.2.6 Indices of Estuarine Condition
Indicators may also be combined into an overall condition rating to measure ecosystem
function, structure and processes in a standardized approach (U.S. EPA. 2016c; Boriaet
al.. 2012; U.S. EPA. 2012b; Devlin et al.. 201 1; Bricker et al.. 2007). Several assessment
frameworks for eutrophic condition have been developed in the U.S. (e.g., EPA's NCCA
and the NOAA NEEA ASSETS-ECI) and other countries (e.g., Trophic State Index
[TRIX], Institut frangais de recherche pour Vexploitation de la mer [IFREMER],
transitional water quality index [TWQI]); however, the applicability of a specific
framework to areas outside of the region where they were originally developed may be
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limited (McLaughlin et al.. 2014; Borja et al.. 2012). Within the same estuary, results of
assessment of eutrophic condition may vary depending on the framework used for
evaluation and the associated chemical and biological indicators (McLaughlin et al..
2014; Garmendia et al.. 2012; Devlin et al.. 2011). In a comparison of methods to assess
nutrient enrichment impacts, Devlin et al. (2011) suggested indices that incorporate
annual data, frequency of occurrence, spatial coverage, secondary biological indicators
and a multicategory rating scale are more robust and representative. Two of these
methods that have been applied to U.S. waters are ASSETS-NCI (Bricker et al.. 2007)
and NCCA (U.S. EPA. 2016c. 2012b). ASSETS-NCI is only applied to nutrients and
focuses on response indicators rather than chemical indicators while the NCCA can be
used for assessing other stressors to coastal areas and integrates both chemical and
biological data.
The ASSETS ECI in the NEEA Bricker et al. (2007) was used to estimate of the
likelihood that an estuary is experiencing eutrophication or will experience eutrophication
based on five ecological indicators: chlorophyll a, macroalgae, DO, nuisance/toxic algal
blooms, and SAV I Figure 10-3; (Bricker et al.. 2007)1. ASSETS uses the frequency and
spatial extent of algal blooms combined with the 90th percentile of annual values for
chlorophyll a (Table 10-2). Estuaries are divided into salinity zones and ratings are
combined as an area weighted sum. Results from the NEEA were included in the 2008
ISA, and the biological indicators are the same in both reports for nutrient effects in
estuarine systems.
The NCCA reports represent collaboration among U.S. EPA, NOAA, U.S. Fish and
Wildlife Service, and coastal state agencies. The most recent sampling period was 2010
(U.S. EPA. 2016c). NCCAs use chlorophyll a DO, and three additional indicators (DIN,
DIP, water clarity) to determine a water quality index (U.S. EPA. 2016c. 2012b). The
NCCA include data on water quality, sediment quality, benthic community composition,
and fish tissue contaminants to determine the overall condition of the nation's coastal
waters.
Additional indices applied to U.S. waters include biological indicators of estuarine
condition. Fertig et al. (2014) describe a Eutrophication Index applied to Barnegat
Bay-Little Egg Harbor Estuary, New Jersey using weighted indicators of water quality
(temperature, DO, TN, TP), light availability (chlorophyll a, total suspended solids,
Secchi depth, macroalgae percent cover, percent surface light, epiphyte biomass), and
seagrass (Zostera) response (aboveground biomass, belowground biomass, density,
percent cover and length). The biological condition gradient conceptual framework
(Davies and Jackson. 2006) was applied to Greenwich Bay, RI to assess estuarine habitat
overtime (Shumchenia et al.. 2015). Biological indicators included seagrass extent,
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benthic community, primary productivity and shellfish. Additional indices used in other
countries for describing estuarine condition are reported in Zaldivar et al. (2008). Boriaet
al. (2008). Boria et al. (2012). Devlin etal. (2011). Garmendia et al. (2012). and
Andersen et al. (2014).
In an ecosystem-scale modeling and field study in 14 estuaries in Victoria, Australia,
nutrient inputs of N and P from rivers were related to indices of primary producer
communities (a demersal index and a planktonic index) and water residence times
(Woodland et al.. 2015). The demersal index was based on the coverage of macroalgae
compared to other vegetation and total area with vegetation. The plankton index to
measure total productivity was seasonally averaged chlorophyll concentration. For all
indices, DIN was the best predictor and effects were observed at approximately 5 to
10 mg/km/yr inorganic N. In contrast, results with TN- and TP-based models did not
closely predict effects on macroalgae and chlorophyll a.
10.3 Effects on Biodiversity
Increased N loading to coastal areas can lead to shifts in community composition,
reduced biodiversity, and mortality of biota. Evidence for impacts to biodiversity include
paleontological evidence (Section 10.3.1). altered phytoplankton community composition
(Section 10.3.2). the role of reduced versus oxidized nitrogen (Section 10.3.3).
bacteria/archaea diversity (Section 10.3.4). and macroinvertebrate biodiversity
(Section 10.3.5). The form of N can significantly affect phytoplankton community
composition in estuarine and marine environments (Paerl et al.. 2000; Stolte et al.. 1994).
In hypoxic areas, mortality of benthic biota and avoidance of I0W-O2 conditions by
mobile organisms lead to changes in biodiversity and loss of biomass (Diaz and
Rosenberg. 2008). Energy transfer through the food web can also be altered by a decrease
in predators and increase in microbes from oxygenated areas to anoxic zones.
10.3.1 Paleontological Diversity
Sediment records from Chesapeake Bay showed alterations in producers and consumers
correlated to land use change in the watershed (Sowers and Brush. 2014; Brush. 2009). In
this estuary, diatom community structure has shown a steady decrease in overall diversity
since 1760 as estimated by sediment core analysis (Cooper and Brush. 1993). Diatom
populations began to shift from benthic to planktonic in the early 1900s corresponding to
the increased N flux and higher sediment inputs [which decreased light penetration;
(Brush. 2009)1. Additional sediment cores from two distinct locations in the estuary show
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a shift to an estuarine food web that is predominately planktonic (Sowers and Brush.
2014). An increase in the formaminifera Ammobaculites spp. and decrease in the
polychaete Nereis spp. were observed along with the change in primary producers.
Paleontological evidence from England shows significant changes in benthic species
composition and ecosystem functioning between periods of extremely low O2 (Caswell
and Frid. 2013). The evidence suggests that normal benthic functions are maintained
during early hypoxia, but these functions collapse once thresholds of severely low O2 are
reached.
10.3.2 Phytoplankton Biodiversity
As reported in the 2008 ISA, excess N can contribute to changes in phytoplankton
species composition (U.S. EPA. 2008a). High loadings of N and P can also increase the
potential for Si limitation, with associated changes in diatoms. Such changes to the
phytoplankton community and functional groups (e.g., diatoms, dinoflagellates,
cryptomonads, cyanobacteria, chlorophytes) can also affect higher trophic levels because
these organisms are the base of the estuarine food web. Changes in phytoplankton species
abundance and diversity have been further documented through in situ bioassay
experiments, such as the results reported by Paerl et al. (2003) for the Neuse River
Estuary, North Carolina. Effects were species specific and varied dramatically depending
on whether, and in what form, N was added. The findings illustrate the potential impacts
of N additions on phytoplankton. Changing phytoplankton community composition and
structure has numerous potential ecological ramifications, including modifications to the
ecosystem food web and nutrient dynamics. For example, if the nutrient mix favors
species that are not readily grazed (e.g., cyanobacteria, dinoflagellates), trophic transfer
will be poor and relatively large amounts of unconsumed algal biomass will settle to the
bottom, which could stimulate decomposition, O2 consumption, and the potential for
hypoxia (Paerl et al.. 2003).
Several studies published since the 2008 ISA use shifts in diatoms as a measure of N
enrichment effects on biodiversity. Phytoplankton community structure was altered by
eutrophication in the Skidaway River estuary, Georgia, as evidenced by a shift away from
diatoms and towards nonsilicate nanoplankton (Verity and Borkman. 2010). There was a
strong relationship between diatom taxon distribution and TN concentrations in Charlotte
Harbor, FL (Nodine and Gaiser. 2014). Differences were noted in the phytoplankton
community structure during the time periods before, during, and after eutrophication in
the Black Sea (Mikaelvan et al. 2013). Diatoms and dinoflagellates especially were
found to be dependent on high N and N:P ratios. While nutrient ratios are known to
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influence phytoplankton community structure, Davidson et al. (2012) pointed out that
these nutrient ratios are important only when one nutrient is low enough to limit growth.
Shifts in phytoplankton community structure are known to occur in estuaries due to N
enrichment, but climatic changes may at times outweigh the impacts of eutrophication
(Paerl et al.. 2010). Thus, physical changes caused by climate change, such as water
temperature, stratification, circulation, and hydrologic variability, must be taken into
account when modeling phytoplankton community responses to N enrichment I (Paerl et
al.. 2014); Chapter 131. Likewise Glibert et al. (2014) noted changes in phytoplankton
community composition along with increased anthropogenic N input and a switch to
long-term wet conditions in the coastal lagoons area of Maryland and Virginia. A 3-year
data set from Raritan Bay indicates that climatic conditions and nutrient concentrations
both affected phytoplankton composition from 2010-2012 (Rothenberger et al.. 2014).
The abundance of flagellates in the bay over time reflects a shift in dominance away from
diatoms that is characteristic of eutrophic systems.
10.3.3 Biodiversity of Phytoplankton in Reduced versus Oxidized Nitrogen
Phytoplankton biodiversity varies with form of N and some HAB species respond
strongly to reduced N (Section 10.2.2). Some studies reviewed in the 2008 ISA suggested
that large diatoms tend to dominate coastal waters when NCh is supplied (Paerl et al..
2000; Stolte et al.. 1994). whereas smaller diatom species have a greater preference for
NH4+ uptake. A similar pattern was recently observed on the southwest Florida shelf
where more diatoms were found in the south with higher inputs of NO;, while in the
north, cyanobacteria and dinoflagellates were more common and DON inputs were
prevalent (Heil et al.. 2007). Thus, ongoing trends of decreasing NO3 deposition and
increasing NH4+ deposition might contribute to changes in species distributions and size
distributions of phytoplankton, with cascading effects on trophic structure and
biogeochemical cycling (Paerl et al.. 2000). In Maryland and Virginia coastal bays,
Glibert et al. (2014) observed a regional shift in phytoplankton community composition
to species that do well in reduced N.
Not all studies have found variation in algal response with the form of N. Esparza et al.
(2014) observed that nutrient concentrations or ratios in NH4+ impacted Suisun Bay in the
northern part of San Francisco Bay were less important than the initial species
composition of the seeding population in predicting final phytoplankton community
composition. Richardson et al. (2001) examined the effects of different forms of N
application (NO3 . NH4+, urea) on the structure and function of estuarine phytoplankton
communities in mesocosm experiments in the Neuse River Estuary, NC. Even though
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NH4+ is more readily taken up by phytoplankton in this estuary than is NO? (Twomev et
aL 2005). the results of the Richardson et al. (2001) study suggested that phytoplankton
community structure was determined more by the hydrodynamics of the system than by
the form of N available for growth. Twomev et al. (2005) measured Neuse River Estuary
phytoplankton uptake rates of NH4+, NOs . and urea. NH44" was the dominant form of N
taken up, contributing about half of the total N uptake throughout the estuary. Uptake
varied spatially; in particular, NO3 uptake declined from 33% of the total uptake in the
upper estuary to 11 and 16% in the middle and lower estuary, respectively. Urea uptake
contributed 45 and 37% of the total N uptake in the middle and lower estuary, showing
the importance of regenerated N for fueling phytoplankton productivity in the mesohaline
sections of the estuary. Therefore, N budgets based only on inorganic forms may
seriously underestimate the total phytoplankton uptake (Twomev et al.. 2005).
10.3.4 Biodiversity of Bacteria and Archaea
Since the 2008 ISA, a few studies have explored ammonia-oxidizing bacteria (AOB) and
ammonia-oxidizing archaea (AOA) community responses in relation to N in coastal
waters. These organisms play a key role in N cycling and the AOA were described
relatively recently (Konneke et al.. 2005). Bouskill et al. (2012) examined the distribution
and abundance of AOA and AOB across a variety of aquatic environments, including two
sites at different salinity levels in Chesapeake Bay. The AOB were dominate in the
freshwater end of the continuum, whereas AOA were more common in open ocean areas.
The abundance of both groups were correlated with the concentration of NH4+ in the
water, especially relative abundance of AOB. A similar pattern was observed in the
Sacramento-San Joaquin Delta where AOB were more abundant in the NH4+-rich
Sacramento River compared to the San Joaquin River and Suisun Bay where AOA were
prevalent (Damashek et al. 2015). Community structure of benthic ammonia oxidizers
differed across the region and appeared to be related to nutrient inputs.
10.3.5 Benthic Biodiversity
Invertebrates associated with bottom substrates of coastal systems are useful indicators of
biological change for impacted waters. Several indices based on benthic invertebrates,
macroinvertebrates or macrophytes have been used to assess biological condition in
response to the European Water Framework Directive (Andersen et al.. 2014; Zaldivar et
al.. 2008). A few of these indices have been tested in the U.S. waters. Boria et al. (2008)
compared the Benthic Index of Biotic Integrity (B-IBI), the AZTI Marine Biotic Index
(AMBI) and its multivariate extension the M-AMBI in Chesapeake Bay. There was
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relative agreement between methodologies and differences were related to spatial
variability and habitat type. The EPA's NCCA has developed comparable regional
benthic indices for the Northeast/Acadian, northeast Virginian, southeast Virginian,
southeast Carolinian, and Gulf Louisianan coasts (U.S. EPA. 2016c). Research and
modeling studies alike indicate that N and climate change will interact to drive losses in
biodiversity that will be more than additive compared to each independent force I (Porter
et al.. 2013); Chapter 131.
N enrichment has been shown to have significant but complex effects on
suspension-feeding macroinvertebrates in estuaries. Shellfish species can respond
positively to increased N loading and high phytoplankton biomass levels due to increased
quantity and quality of food particles (Carmichael et al.. 2004). A recent study in Long
Island's Peconic Estuary suggested that eutrophication impacts shellfish through changes
in the quality of food and not the quantity (Wall et al.. 2013). Select species (oysters
[Crassostrea virginica] and clams [Mercenaria mercenaria]) in eutrophic areas
experienced enhanced growth rates that were strongly correlated with high densities of
autotrophic nanoflagellates and centric diatoms. Other species (scallops [Argopectin
irradians] and slipper limpets) suffered negative effects and grew at the slowest rate at
the most eutrophic sites. Bay scallop growth was negatively correlated with densities of
dinoflagellates, which were more abundant at the most eutrophic site (p < 0.001) In rocky
shore environments in Ireland, similar to those of the U.S. northeastern Atlantic coast, N
enriched sites near industrial and sewage outfalls have been shown to have reduced total
abundance and number of taxa of molluscs and altered community composition
compared to control sites (Atalah and Crowe. 2012). Nitrite and NH? levels explained the
highest percentages of variation in the molluscan assemblage structure (13 and 12.5%,
respectively), owing in large part to the absence of three rare species at contaminated
sites. The observed shift in community structure caused by different levels of molluscan
tolerance to N enriched conditions has been suggested for use as a biological indicator of
eutrophication (Atalah and Crowe. 2012).
The use of shellfish for coastal N remediation has been explored due to the ability of
these organisms to modulate nutrient dynamics and water quality (Bricker et al.. 2014;
STAC. 2013; Cerco and Noel. 2007; Carmichael et al.. 2004). These filter feeders store
nutrients in shell and tissue that are permanently removed with shellfish harvest.
Biodeposits (partially digested phytoplankton expelled from suspension feeding bivalves)
may remove additional N through acceleration of denitrification processes in underlying
sediments (Pollack et al.. 2013; STAC. 2013; Stephenson et al.. 2010). For example, in
the Mission-Aransas Estuary in Texas, oyster reefs were estimated to remove 502.5 kg
N/km2 through denitrification of biodeposits and 251.3 kg N/km2 in burial of biodeposits
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to sediments (Pollack et al.. 2013). Oyster harvest in the same estuary was calculated to
remove approximately 21,665 kg N/yr.
Additional studies have reported N removal by shellfish in U.S. waters. Carmichael et al.
(2004) directly measured N removal in the oyster C. virginica in transplant studies to five
Cape Cod estuaries with different N loadings. Estimated N removal of different sources
was <15% of land-derived N loads and <1% of phytoplankton. N removal by oysters in
the Great Wicomico River, which drains into the Chesapeake Bay, was estimated to be
15.2 tons/yr [total area 2.8 x 105 m2; (C'erco. 2015)1. Based on model estimates for
Chesapeake Bay harvesting 7.7 * 10676-mm harvest-sized oysters removes 1 ton ofN
from the bay (Higgins et al.. 2011). In the same study, an offset of approximately 10 to
15% of total N load in some basins (cultivation of 200 * 106 oysters/yr) was calculated.
Holmer et al. (2015) recommended harvest of mussels within 1 year of the production
cycle for the most efficient N removal.
Over time, mussel excretion and subsequent sedimentation may lead to hypoxic
conditions and the farming operation may shift from a net sink to a net source of N.
Oyster reef restoration projects in several locations throughout the U.S. have been
evaluated for effects on N cycling; however, this process appears to be dependent on
local habitat and growing conditions and may vary by orders of magnitude (C'erco. 2015;
Smyth et al.. 2015; Kellogg et al.. 2014; Plutchak et al.. 2010). In Great Bay Estuary in
New Hampshire, eutrophication enhanced oyster feeding rates and enhanced biodeposit
quality indicating that oyster-mediated ecosystem services may be expected to vary with
environmental conditions (Hoellein et al.. 2015).
Recent evaluation of oysters in Chesapeake Bay for inclusion in total maximum daily
load (TMDL) reductions reported enhanced denitrification in association with oyster
reefs; however, the effect was highly variable and not reliable unless direct measurements
were conducted on individual reefs (STAC. 2013). The potential for shellfish aquaculture
to be included in proposed nutrient trading markets for achieving pollution control under
the Clean Water Act is being evaluated in Chesapeake Bay (Stephenson et al.. 2010).
Some recent modeling studies show that mean N removal by shellfish aquaculture
compares favorably to reported N removal effectiveness of agricultural best management
practices and stormwater control measures (Rose et al.. 2015a; Rose et al.. 2014).
10.3.6 Fish Biodiversity
A few studies have recently reported effects on fish biodiversity in nutrient-impacted
estuaries. In an estuary in the southern Gulf of St. Lawrence in Canada, loss of eelgrass
was linked to declines in fish biodiversity but did not change the positions of organisms
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within the food chain (Schein et al.. 2013; Schein et al.. 2012). In Prince Edward Island
estuaries, adult and young-of-the-year abundance of pollution-tolerant mummichogs
(Fundulus heteroclitus) increased in estuaries with greater intensity of N loading from
agricultural land use (Finlev et al.. 2013). In this study, eutrophication was associated
with changes in habitat variables, which were linked to mummichog abundance.
10.3.7 Trophic Interactions
Since the 2008 ISA, studies have further characterized the effects of nutrient enrichment
on trophic interactions. In the Skidaway River estuary, Georgia, increasing nutrient
concentrations and changes in nutrient ratios lead to increases in eukaryotic organisms
(heterotrophic and mixotrophic flagellates, dinoflagellates, ciliates, and metazoan
zooplankton) but not diatoms, potentially altering food web predator-prey relationships
(Verity and Borkman. 2010). In an experimental study in Chesapeake Bay, Reynolds et
al. (2014) demonstrated that reduction of crustacean grazers controlling algal growth on
seagrasses resulted in 65% reduced seagrass biomass and nearly sixfold increased
epiphytic algae. In experimental plots where grazers were removed, aboveground
eelgrass biomass was reduced following fertilization. In the presence of grazers, eelgrass
biomass increased with fertilization. When predators were excluded, mesograzers were
able to limit ephiphyte growth even when nutrients were added. Based on these findings,
the researchers suggested that it is unlikely that reducing nutrient pollution alone would
restore seagrass meadows where alterations to food webs have already reduced
populations of algae-feeding mesograzers. Similar results were reported in McSkimming
et al. (2015) from Posidonia angustifolia meadows in Australia where mesograzers
responded to nutrient addition by increasing grazing per capita resulting in greater
consumption of epiphytic algae.
Newer literature has provided evidence for complex interactions between eutrophication
and other stressors and subsequent effects on trophic interactions. For example, Burnett et
al. (2013) used mesocosms to demonstrate the effect of eutrophic conditions on
plant-herbivore grazing interactions between the sea urchin Amblypneustes pallidas and
the seagrass Amphibolis antartica affected by warming and acidification. Nutrient
enrichment offset increased grazing associated with acidification and warming; however,
it did not fully counter the additive effects of these two stressors.
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10.3.8
Models Linking Indicators to Nitrogen Enrichment
1 Process-oriented models such as nutrient-phytoplankton-zooplankton (NPZ) models are
2 used to predict the response of organisms such as HABs to various known and/or
3 predicted nutrient conditions (Swanev et al.. 2008). A nutrient-driven phytoplankton
4 model developed by Scavia and Liu (2009) was expanded by Evans and Scavia (2013) to
5 test the sensitivity of the response of chlorophyll a levels and DO levels to N enrichment.
6 Results indicated that separate processes control chlorophyll a and DO sensitivity
7 (estuary flushing time and relative mixing depth, respectively), and that these sensitivities
8 vary among estuaries (Figure 10-6).
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IthwIHIl B
O- Paiuxcnt R
-*— Penobscot B
-O— Potomac R
-X— St, Marys R and Cumberland S
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0 0.2 0.4 0.6 0.8 1
% TN
Chl = chlorophyll; DO = dissolved oxygen; TN = total nitrogen.
The x-axis shows river total nitrogen load relative to the 1992 SPARROW total nitrogen load for each estuary. In the figure legend,
R = river, B = bay, and S = sound.
Source: Evans and Scavia (2013).
Figure 10-6 Forecasting curves for effects on total nitrogen loadings on
(A) chlorophyll and (B) dissolved oxygen (mean and 95%
confidence interval) for selected estuaries demonstrating the full
range of sensitivity to relative total nitrogen loading.
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10.4 Animal Behavior and Disease
10.4.1 Behavior
Turbidity caused by excess algae in the water, a secondary effect of eutrophication, has
been shown in laboratory studies to potentially alter some fish behaviors, with
implications for mate selection and offspring survival rates. It is not known whether some
of these behavior changes will be adaptive or if they will have positive or negative effects
on the fish populations. For instance, when the strength of sexual selection on several
traits is relaxed, the relative importance of survival selection may increase (Candolin.
2009). The color contrast created by increased turbidity may lead to a heightened feeding
response in some fish larvae such as California yellowtail (Seriola lalandi), which
exhibited elevated growth and survival rates compared to larvae raised in clear
(oligotrophic) water (Stuart and Drawbridge. 2011).
Several studies of the three-spined sticklebacks (Gasterosteus aculeatus) indicate that
observed alterations of reproductive behaviors are linked to eutrophic conditions (Figure
10-7).
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Eutrophication
- filamentous algae
- water turbidity
Territory
and nest
Courtship
Sneaking
choice
Reproductive
success
1
Sexual selection
Parental
1
Population
demography
I
Survival selection
Source: Candolin (2009).
Figure 10-7 The pathway of effects of eutrophication on different reproductive
behaviors and selection forces in Gasterosteus aculeatus.
Laboratory manipulations suggest that turbidity caused by eutrophication may affect mate
selection and breeding success in this euryhaline fish species (Heuschele et al.. 2012;
Heuschele and Candolin. 2010). When given the choice between dense or sparse algae,
male sticklebacks preferred to nest in dense algae (which simulated eutrophic conditions).
The nests of those males were more likely to be parasitized by other males; however, the
males nesting in dense algae also acquired more eggs, and thus, had a higher probability
of reproduction (Heuschele and Candolin. 2010). This may be because reduced visibility
leads to reduced mate selectivity searching by females, although it is unknown whether
these behavior changes would have positive or negative impacts on the population
(Heuschele et al.. 2012). Simulated turbidity has also been shown to impair visual mate
choice in an eastern Atlantic species of marine pipefish, Syngnathns typhle (Sundin et al..
2010). In the same species, the latency period between courting and copulation was
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prolonged in I0W-O2 conditions, although other measures of reproductive behavior (total
time spent courting, probability of mating, dancing, male pouch-flap behavior) were
unaffected (Sundin et al.. 2015).
Other types of fish mating behaviors are also affected by eutrophication. Male
sticklebacks engage in an opportunistic mating behavior called "sneaking" which is less
successful under more turbid (eutrophic) conditions (Vlieger and Candolin. 2009).
Eutrophication has so far been found to have conflicting impacts on nest building
behavior in male sticklebacks, with varying implications for the survival rate of
stickleback offspring. Male sticklebacks built smaller nests with wider openings during
eutrophic (algal bloom) conditions (Wong et al.. 2012). These males also took longer to
complete the nest than did males that built during nonbloom conditions. However, under
normal water conditions in a laboratory setting, male sticklebacks that had been collected
from eutrophic waters built their nests faster than those collected from noneutrophic
waters, although the nests did not differ in structure or composition between the two
groups (Tuomainen and Candolin. 2013). In European sand gobies (Pomatoschistus
minutus), another species that exhibits paternal care of eggs, algal turbidity altered male
behaviors (Jarvenpaa and Lindstrom. 2011). Males spent more time away from the nest,
and exhibited less fanning of the eggs with their pectoral and tail fins. Goby egg survival
rates were actually found to be higher under turbid conditions. Although the mechanism
for this outcome is unknown, it was proposed that males may have increased other forms
of care in the presence of eutrophic conditions, leading to higher egg survival.
Under normal conditions, it is beneficial for sticklebacks to live in larger groups where
they gain protection from predators, are able to forage more efficiently, and are able to
find a mate more easily than in smaller groups. However, in eutrophic (turbid) water,
sticklebacks did not show a preference for joining a larger shoal as they did under normal
conditions (Fischer and Frommen. 2013V This lack of exhibited shoal preference under
turbid conditions could eventually reduce individual stickleback fitness. In addition,
sticklebacks changed shoals less frequently in turbid water than observed under normal
conditions, which leads to a decrease in the transfer of important social information, such
as the location of foraging routes. Therefore, increased turbidity may reduce social
learning opportunities for sticklebacks, which may in turn impair their foraging efficiency
(Fischer and Frommen. 2013).
10.4.2 Disease
Diel-cycling hypoxia in estuaries is a natural phenomenon that can be exacerbated by
increased biomass and productivity associated with anthropogenic nutrient loadings
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(Tvler et al.. 2009). Tvler et al. (2009) observed that upper areas of four Delaware
estuaries experienced increased incidence of severe hypoxia (DO <2 mg/L) where
nutrient loading was greater. The duration and spatial extent of diel-cycling hypoxia in
the estuaries were primarily associated with water temperature, previous day's insolation,
hours of morning ebb tide, and daily streamflow. Oysters (C. virginica) exposed to
periods of diel-cycling hypoxia were demonstrated to have increased incidence and
progression of Perkinsus marinus infection (Dermo) in field and laboratory experiments
(Breitburg et al.. 2015). Field experiments were conducted in Chesapeake Bay. The
authors suggest that the likely mechanism is negative effects of hypoxia on host immune
response.
10.5 Nutrient Enhanced Coastal Acidification
Since the 2008 ISA, several studies have suggested that the increased respiration caused
by N enrichment may exacerbate coastal ocean acidification through alteration of the
carbon cycle (Chapter 7). Dissolution of atmospheric anthropogenic carbon dioxide
(CO2) into the ocean has caused increasing acidification of coastal waters, resulting in
long-term decreases in pH (Wallace et al.. 2014; Orr et al.. 2005). N enrichment is
expected to worsen this acidification because degradation of excess organic matter then
produces CO2 in the water column, which in turn can make the water more acidic I Figure
10-8; (Sunda and Cai. 2012; Cai etal.. 2011c; Howarth et al.. 2011)1. Ocean
acidification, which can be exacerbated by elevated N input, is projected to impact a wide
range of marine ecosystems (Sunda and Cai. 2012; Donev et al. 2009).
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Increasing
atmospheric
CO,
Loading
Algal blooms
from nutrient
inputs >
Adverse
biological
impacts
Increasing \
[C02]/lower pH
as regulated by
s,temperature and
x salinity y
Microbial
respiration of
organic
v matter /
Lower 02/
hypoxia
C02=carbon dioxide; N = nitrogen; 02=oxygen.
Modified from: Sunda and Cai (2012).
Figure 10-8 Pathway of nutrient enhanced coastal acidification from nitrogen
loading to biological effects. Both microbial respiration of organic
matter and increasing atmospheric carbon dioxide lower pH of
coastal waters.
1 Acidification of coastal waters may cause varying degrees of harm to marine organisms
2 that produce calcium carbonate shells or skeletons, including oysters, clams, sea urchins,
3 shallow water corals, and calcareous plankton (Pfister et al.. 2014; Kroeker et al. 2013;
4 Sunda and Cai. 2012). The acidifying process decreases the saturation state of the two
5 mineral forms (aragonite and calcite) that most bivalves use to form their shells (Barton
6 et al.; Barton et al.. 2012). Already, there are declines in oyster production on the U.S.
7 West Coast due to the inability of oysters to create shells due to acidification (Barton et
8 aL; Hettinger et al.. 2012). However, other factors can confound the response of these
9 sensitive organisms, and more research is needed to accurately determine the interactions
10 and combined impact of ocean acidification and N enrichment on U.S. ecosystems such
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as coral reefs (found in southern Florida) and estuaries with sensitive shellfish
populations (kroekeret al.. 2013).
Models show that while the impact of each acidification pathway (N enrichment and
atmospheric CO2 dissolution) may be moderate, the combined effect of the two may be
much larger than would be expected by just adding the effects of each pathway together
(Sunda and Cai. 2012; Cai et al.. 2011c). These models, which incorporate the expected
future higher atmospheric CO2 levels and current levels of eutrophication, show dramatic
increases in acidification of coastal waters below the pycnocline. Model predictions
agreed well with pH data from hypoxic zones in the northern Gulf of Mexico and both
the modeled and the measured decreases in pH are well within the range shown to impact
marine fauna (Sunda and Cai. 2012V Data from the northern Gulf of Mexico revealed a
significant positive correlation between subsurface water pH and O2 concentration,
linking acidification to low O2 due to organic matter decomposition (Cai etal.. 2011c').
The increase in atmospheric CO2 dissolution is also expected to alter the N cycle in the
ocean, with implications for the entire ecosystem. Acidification will result in decreased
rates of nitrification which, combined with expected increasing N deposition, is expected
to cause the NH44" concentration of the water to rise (Lefebvre et al.. 2012). A study of the
coccolithophore Emiliania huxleyi, which plays a major role in the global carbon cycle by
regulating the exchange of CO2 across the ocean-atmosphere interface, found that higher
levels ofNH4+ can affect the morphology and calcification of the coccolithophore. The
combined effect of higher NH4+ levels and greater acidification could reduce calcification
rates, suggesting a greater alteration to the ocean's carbon cycle due to the combined
effect of increased NH4 /NO3 and acidification (Lefebvre et al.. 2012).
10.6 Extent and Distribution of Sensitive Ecosystems/Ecoregions
10.6.1 Eutrophication
The NEEA defined susceptibility as an estimate of the natural tendency of an estuary to
retain or flush nutrients (Bricker et al.. 2007). In estuaries that have longer residence
times, nutrients are more likely to be taken up by algae and lead to eutrophic conditions
(Section 10.1.4). In the NEEA assessment, the most eutrophic estuaries in the U.S.
occurred in the mid-Atlantic region and the estuaries with the lowest degree of
eutrophication were in the North Atlantic (Figure 10-9).In the Pacific Northwest, coastal
upwelling can be a large source of nutrient loads and advection of upwelled water can
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introduce hypoxic water into estuaries that is not related to anthropogenic eutrophication
(Brown and Power. 2011; Brown and Ozretich. 2009).
In the U.S., Chesapeake Bay is perhaps the best-documented case study of the effects of
human activities on estuarine eutrophication. Human disturbances, such as landscape
changes, have exacerbated the negative impacts of N deposition by reducing N removal
and retention in the upper watershed region. Anthropogenic N inputs have substantially
altered the trophic condition of Chesapeake Bay over the last 50 to 100 years. Signs of
eutrophication in the bay include high algal production, low biodiversity, and large
hypoxia and anoxia zones. Eutrophication has been implicated in declines of SAV,
striped bass (Morone saxatilis) and blue crab (C. sapidus) in the Chesapeake Bay (Kemp
et al.. 2005). Other estuaries identified in the 2008 ISA where the extent of hypoxia and
algal blooms have increased included Long Island Sound, the Pamlico Estuary in North
Carolina, and along the continental shelf adjacent to the Mississippi and the Atchafalaya
River discharges to the Gulf of Mexico (U.S. EPA. 2008a). In the NEEA, 65% of
assessed systems had moderate to high overall eutrophic conditions KBricker et al..
2007); Figure 10-91.
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s
o
0
°i>
a» 40
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HM
t/>
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II
14 15
JL
f
~
Low Moderate Moderate Moderate High
low high
400
Kilometers
J Miles
100 200
N
sO.
%
High: symptoms occur periodically or persistently and/or over an extensive area
Moderate high: symptoms occur less regularly and/or over a medium to extensive area
I Moderate: symptoms occur less regularly and/or over a medium area
Moderate low: symptoms occur episodically and/or over a small to medium area
I Low: few symptoms occur at more than minimal levels
Unknown: insufficient data for analysis.
Source: Bricker et al. (2007).
Figure 10-9 Overall eutrophication condition on a national scale.
Post-2007 literature includes additional information on the extent and severity of
eutrophication in sensitive regions. Murphy et al. (2011 \ analyzed a 60-year record of
Chesapeake Bay hypoxic zone volumes and found a slight but significant decreasing
trend in late summer hypoxia, which aligns with the decrease in N loading due to
management controls. This analysis also showed a correlation between N loading and the
duration of summer hypoxia events (Murphy et al.. 2011). Bricker et al. (2014) evaluated
N inputs to the Potomac River Estuary and found that despite some improvements in the
upper estuary (i.e., increased DO and decreased chlorophyll a in the tidal fresh zone;
continued regrowth of sea grasses), eutrophic conditions have worsened in the lower
estuary since the early 1990s. Eutrophic conditions in the Potomac were found to be
representative of the Chesapeake Bay region and other U.S. estuaries, with
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moderate-to-high levels of nutrient-related degradation particularly compared to similar
river-dominated low-flow systems (Bricker et al.. 2014). These river-dominated
watersheds with low flow (>10 days residence time), high population density
(i.e. >100 people/km2), and >40% of land use classified as urban and/or agriculture were
predicted to be likely impacted by eutrophication. Modeling studies show that oyster
aquaculture could alleviate some eutrophication impacts from the Potomac River Estuary
(Bricker et al. 2014).
In a regional survey of estuaries in southern California, 78% of estuaries were rated
"moderate" or "worse" based on macroalgae, 39% based on phytoplankton, and 63%
based on DO using the European Union Water Framework Directive (McLaughlin et al..
2014). With the ASSETS framework, 53% of surveyed areas were identified as impaired.
The specific characteristics of each estuary play an important role in determining its
susceptibility to N enrichment. Scavia and Liu (2009) evaluated a nutrient-driven
phytoplankton model and their model analysis provides a first-order screening tool for
estuarine susceptibility classification. Using data from 75 estuaries, they found that the
susceptibility of an estuary to nutrient loading could be estimated based on the ratio of
river inflow (Q) to estuarine volume (V). In this analysis, efficiency appeared to decrease
roughly with the inverse square root of QIV: s = 0.908(6>/F) l,47(/^2 = 0.53), where 8
represents mean values arising from the 75 estimated normal distributions. Model results
showed that estuaries with a Q:V value greater than 2.0/yr are less susceptible to nutrient
loads, and those with Q:V between 0.3 and 2.0/yr are moderately susceptible. Case
studies showed that Q:V—and thus estuarine sensitivity to nutrient loading—can vary
between seasons and with storm events due in part to fluctuations in river inflow.
10.6.2 Coastal Acidification
The geographic extent of acidification is being assessed in some U.S. coastal regions. In a
series of sampling cruises and analysis of water sampling data, Wallace et al. (2014)
identified concurrent low pH conditions and declining DO in four northeast estuaries
(Long Island Sound, NY; Jamaica Bay, NY; Narragansett Bay, RI; Hempstead Bay, NY).
Observed conditions in eutrophic estuaries during late summer were such that marine
biota, especially calcifying organisms, may be affected (Section 10.5). Analysis of
historical (from the late 1960s to 2010) alkalinity and pH data from bays along the
northwestern coast of Texas indicated most of the bays in this region have experienced
long-term acidification (Hu et al.. 2015a).
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10.7 Summary of Thresholds and Levels of Deposition at Which
Effects Are Manifested
Studies linking changes in estuary nutrient status to atmospheric deposition have been
limited, although some states are addressing atmospheric inputs as part of their
development of TMDLs (Linker et al. 2013). Since the 2008 ISA additional thresholds of
response to N have been identified for biological indicators. In general, identification and
application of indicators and thresholds to assess eutrophication in coastal areas is more
highly developed in Europe than in the U.S. due to the implementation of the Water
Framework Directive (Zaldivar et al.. 2008). Here we limit discussion to indicators and
thresholds that have been applied to U.S. water bodies.
For chlorophyll a, both NEEA ASSETS and EPA NCCA have a similar range for
categorization of eutrophic conditions; however, ASSETS uses the 90th percentile
chlorophyll concentration of annual data and EPA NCCA uses growing season
(June-October) values RBoria et al.. 2012); Table 10-21. For ASSETS, 0-5 (ig/L is a
water body with low risk of eutrophication, 5-20 |ig/L is moderate, >20 |ig/L is high with
>60 (ig/L indicating hypereutrophic conditions. NCCA identified chlorophyll
concentration of >20 |ig/L as an indicator of an estuary in poor condition. Chlorophyll
concentrations between 5-20 |ig/L are classified as fair and chlorophyll concentration
0-5 (ig/L was good for sites located in the Northeast, Southeast, Gulf, West Coast, and
Alaska (U.S. EPA. 2012b). Values were lower for sites in Hawaii, Puerto Rico, U.S.
Virgin Islands, American Samoa, and Florida Bay (0.5 |ig/L good, 0.5-1 |ig/L fair,
>1 (ig/L, poor).
For DO, ASSETS uses the 10th percentile of annual data. Concentrations of 0 mg/L are
anoxic, 0-2 mg/L are indicative of hypoxic conditions and 2-5 mg/L are biologically
stressful conditions (Devlin et al.. 2011; Bricker et al.. 2007). Spatial coverage (range of
0-10% [low] to >50% [high]) and frequency of occurrence (persistent, periodic,
episodic) are also included in determining reference thresholds for DO with ASSETS.
For EPA NCCA, the cut point used for poor DO condition is <2 mg/L in bottom waters
(U.S. EPA. 2016c. 2012b). Because many states use higher concentrations, the NCCA
considers concentrations between 2 and 5 mg/L as fair, and >5 mg/L as good.
Under the U.S. Clean Water Act, states are in the process of developing numeric nutrient
criteria to better define levels of N and P that affect estuaries and coastal marine waters.
The numeric values include both causative (N and P) and response (chlorophyll a,
biocriteria) variables to assess eutrophic conditions. For progress toward state
development of numeric criteria for nitrogen see (http: //cfbub .epa. gov/wq sits/nnc-
development/). Florida and Hawaii have estuary or embayment-specific numeric nutrient
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criteria while several other states including Massachusetts and California have partial
criteria for N. Atmospheric deposition as a source of N may represent a potential target
for remediation such as TMDL, nutrient budgets and allocations.
The Chesapeake Bay 2010 TMDL load reductions include atmospheric deposition, the
first time atmospheric N loads to tidal waters have been included in a TMDL for
reduction (U.S. EPA. 2010a). For Chesapeake Bay, a numerical chlorophyll criteria
ranging from 1.4 to 15 mg/m3 (|ig/L) based on seasonal mean across salinity zones was
proposed as a restoration goal with 90th percentile compliance limits ranging from 4.3 to
45 mg/m3 [fig/L; (Harding et al.. 2014)1. These values were based on relationships of
chlorophyll a concentrations to DO, water clarity and toxic algae. Chlorophyll a ranges
of 7.2 to 11 mg/m3 (|ig/L: May-August mean) in the bay and 9 to 14 mg/m3 (|ig/L:
annual mean) in the tributaries would be protective of low DO conditions. For SAV
growth, a mean chlorophyll a concentration of 7.9-12 mg/m3 (|ig/L) with a threshold of
19-28 mg/m3 (|ig/L) during the growing season would allow for sufficient light
conditions. For decreased risk for toxic cyanobacteria, a mean summer chlorophyll a
concentration of 15 mg/m3 and a threshold of 25 mg/m3 (fig/L) was recommended.
For seagrasses in New England estuaries a threshold of N loading (N export of
wastewater, fertilizer, and atmospheric deposition from the watershed combined with
direct atmospheric deposition to waters) >100 kg N/ha/yr was identified where essentially
no eelgrass is present and levels above 50 kg N/ha/yr are likely to impact habitat extent
I Table 10-4; (Latimer and Rego. 2010)1. These values were based on literature threshold
values from Bowen and Valiela (2001). Hauxwell et al. (2003). Li et al. (2007). and
Latimer and Rego (2010).
10.8 Summary and Causal Determinations
10.8.1 Nitrogen Enrichment
In the 2008 ISA, the body of evidence was sufficient to infer a causal relationship
between N deposition and the alteration of species richness, species composition, and
biodiversity in estuarine systems (U.S. EPA. 2008a). Physiological perturbations at the
organism-level of biological organization can lead to effects on reproduction, growth, and
survival. These endpoints may impact population dynamics and lead to the changes in
biodiversity described above from the 2008 ISA. New evidence from 2008 to present
from paleontological studies, phytoplankton community dynamics, experiments
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characterizing effects of forms of N on biodiversity, macroinvertebrate response, and
indices of biodiversity support the findings in the 2008 ISA of N nutrient enrichment
effects on biota. New information summarized below is consistent with the 2008 ISA that
the body of evidence is sufficient to infer a causal relationship between N deposition
and changes in biota including altered growth, species richness, community
composition, and biodiversity due to N enrichment in estuarine environments.
Algae are the base of the coastal food web and changes to these primary producers
associated with increased N can lead to a cascade of direct and indirect effects at higher
trophic levels. Algal species have differential responses to N and shifts in nutrient ratios,
which in turn influence community composition. As described in the 2008 ISA, in
general, estuaries tend to be N limited. In many coastal areas, atmospheric deposition
typically constitutes less than half of the total N supply; however, atmospheric inputs are
heterogeneous across the U.S. ranging from <10 to approximately 70% of the N inputs
(Table 7-8) so deposition may play a significant role in altering nutrient dynamics in
some coastal systems. The ratio of reduced-to-oxidized N deposition has shifted toward
increased NH4+ relative to NCh in coastal areas especially in the eastern U.S. Large
diatoms are more efficient in using NO? than NH4+, and the increased NH4+ relative to
NO? in the eastern U.S. favors small diatoms (Paerl et al.. 2000; Stolte et al.. 1994V This
alters the foundation of the food web. Some newer studies support these observations of
N03 and NH4 and diatom species distribution (Heil et al.. 2007).
Chlorophyll a is an indicator of phytoplankton biomass and is used as a proxy for
assessing effects of estuarine nutrient enrichment. It has been used in national-scale
assessments including EPA's NCCA and the NEEA. In general, 0-5 |ig/L chlorophyll is
considered to be good, chlorophyll concentrations between 5-20 (ig/L are classified as
fair, and >20 |ig/L as an indicator of an estuary in poor condition. Shifts in phytoplankton
community structure are known to occur in estuaries with elevated N inputs. Sediment
core analysis of diatom diversity show an overall decrease in biodiversity, shift to a
primarily planktonic food web, and a population shift corresponding to increased N flux
and higher sediment inputs in Chesapeake Bay (Sowers and Brush. 2014; Brush. 2009;
Cooper and Brush. 1993). Phytoplankton community structure was altered by
eutrophication in the Skidaway River estuary in Georgia, specifically a shift from
diatoms to nonsilicate nanoplankton was observed (Verity and Borkman. 2010). These
changes at the base of the food chain can lead to growth effects in shellfish which feed on
phytoplankton (Wall et al.. 2013). The role of shellfish in N and C cycling and their
ability to modulate water quality has significant implications for estuarine functioning
(Rose et al.. 2015a; Bricker et al.. 2014; Rose et al.. 2014; STAC. 2013; Carmichael et
al.. 2012; Cerco and Noel. 2007). The harvest of shellfish permanently removes nutrients,
and biodeposits may remove additional N (Pollack etal.. 2013; STAC. 2013; Stephenson
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et al.. 2010). Although availability of N is an important factor for productivity in
estuaries, many newer studies have emphasized the role of physical and hydrologic
factors in growth of chlorophyll a and other indicators of N enrichment (Hart et al. 2015;
Turner et al.. 2015; Wilkerson et al.. 2015; Glibert et al.. 2014; Kennison and Fong. 2014;
Rothenberger et al.. 2014; Paerl et al.. 2010; Yang et al.. 2008).
In the previous assessment nutrient enrichment in coastal water bodies was linked to
increased HAB outbreaks, a problem that has been recognized for several decades (U.S.
EPA. 2008a; Bricker et al.. 2007; Paerl et al.. 2002; Paerl and Whitall. 1999; Paerl.
1997). Of the 81 estuary systems for which data were available in the NEEA reported in
the 2008 ISA, 26 exhibited a moderate or high symptom expression for nuisance or toxic
algae (Bricker et al.. 2007). HAB bloom conditions and effects of HAB toxins on coastal
biota have been further characterized since the 2008 ISA (Wood et al.. 2014; Miller et al..
2010). Newer studies continue to show that NH3/NH4 inputs selectively favor HAB
species including toxic cyanobacteria and dinoflagellates (Lehman et al.. 2015; Paerl and
Otten. 2013; Hattenrath et al.. 2010). while others have identified other factors such as
initial species in the seeding population as more important than the form of N (Esparza et
al.. 2014). Incidence of HAB outbreaks is increasing in both freshwater and coastal areas.
In addition to phytoplankton, seaweed growth is also stimulated by increased N inputs.
Macroalgal blooms can smother benthic organisms and corals and contribute to loss of
important SAV by blocking the penetration of sunlight into the water column. Studies
published since the 2008 ISA indicate that macroalgae have shown greater assimilation
and growth rates with NH44" than with NO3 (Wang et al.. 2014a; Ale et al.. 2011). Under
conditions of increased nutrient enrichment, opportunistic macroalgae can block light,
altering growth and reducing biomass of SAV (Schmidt et al.. 2012; Abreu etal.. 2011).
Correlations between N loading and SAV loss were reported in the 2008 ISA. Loss of
SAV habitat can lead to a cascade of ecological effects because many organisms are
dependent upon seagrasses for cover, breeding and as nursery grounds. Recent studies in
the southern Gulf of Saint Lawrence have linked SAV loss to declines in fish biodiversity
but no changes were observed in the positions of organisms within the food chain (Schein
et al.. 2013; Schein et al.. 2012). The NEEA suggested only a small fraction of the
estuary systems evaluated reported high severity of SAV loss (Bricker et al.. 2007). Most
of those that did report moderate or high loss were located in the Mid-Atlantic region.
Since the 2008 ISA, additional studies are available on the relationship between N
loading and SAV abundance (Bovnton et al.. 2014; Orth et al.. 2010; Ruhl and Rvbicki.
2010). and several studies have identified specific regional thresholds (a tidal-averaged
total N concentration of <0.34 mg/L for healthy eelgrass; markedly decreased eelgrass
coverage at N loading rates (>100 kg N/ha/yr, and levels above 50 kg/ha/yr were likely to
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impact habitat extent) for SAV response in Massachusetts estuaries (Benson et al. 2013;
Latimer and Rego. 2010). While seagrass coverage is improving in some estuaries, such
as Tampa Bay, many areas continue to see declines in seagrass extent.
Increased algal biomass associated with nutrient over-enrichment leads to increased
decomposition of organic matter which decreases DO. A variety of ecological impacts
are associated with low DO (Figure 10-4) and this indicator has been used in national
assessments of coastal condition including EPA's NCCA and the NEEA. Concentrations
of 0 mg/L are anoxic, 0-2 mg/L are indicative of hypoxic conditions and 2-5 mg/L are
biologically stressful conditions (Devlin et al.. 201 1; Bricker et al.. 2007). For example,
many fishes are absent at DO below 2 mg/L, and mortality of tolerant organisms can
occur at approximately 0.5 mg/L. Hypoxia has recently been shown to affect reproductive
parameters in fish by increasing nitric oxide and super oxide radicals in fish, which may
lead to effects at the population level. For example, hypoxia has been shown to act as an
endocrine disruptor in Atlantic croaker (Thomas and Rahman. 2010. 2009; Thomas et al..
2007). and sublethal hypoxia may lower the breeding rate in three-spined sticklebacks
(Moran et al.. 2010). In laboratory conditions, increased turbidity associated with
eutrophic conditions has been demonstrated to alter fish reproductive behaviors
(Candolin. 2009). Macroinvertebrate community structure is also affected by duration
and severity of hypoxia. A shift to benthic organisms with shorter life spans and smaller
body size has been observed in coastal areas that experience severe seasonal hypoxia
(Diaz and Rosenberg. 2008). Reduced species density and diversity in the northern Gulf
of Mexico are linked to the duration of hypoxic events (Baustian and Rabalais. 2009).
In the 2008 ISA, the largest zone of hypoxic coastal water in the U.S. was the northern
Gulf of Mexico on the Louisiana-Texas continental shelf (U.S. EPA. 2008a). This area
continues to be the largest in the U.S. and the second largest in the world, averaging
about 16,500 km2 (10,250 mi2) in size, forming annually between May and September
(Dale et al.. 2010; Jewett et al.. 2010). Atmospheric deposition from watersheds in the
Mississippi/Atchafalaya river basins contributes approximately 16 to 26% of the total N
load in the Gulf of Mexico (Robertson and Saad. 2013; Alexander et al.. 2008). Although
the size of the midsummer bottom-water hypoxia area (<2 mg/L DO) varies annually, the
area with DO less than 2 mg/L has averaged approximately 8,500 km2 (5,300 mi2)
between 1985-2014. Long Island Sound also experiences periods of anoxia in some
years. Between 1987 and 2014, the average annual maximum extent was 98 km2 (61 mi2).
In other U.S. coastal systems, incidence of hypoxia is increasing; however, the severity of
DO impacts are relatively limited temporally and spatially (Jewett et al. 2010; U.S. EPA.
2008a; Bricker et al.. 2007).
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The indicators described above (chlorophyll a, HABs, macroalgal abundance, DO, SAV,
and benthic diversity) have been incorporated into indices that describe eutrophic
conditions in coastal areas. In the 2008 ISA, the ASSETS ECI developed for the NEEA
was used as an assessment framework for eutrophic condition in coastal U.S. estuaries
(Bricker et al. 2007). The NCCA incorporates indicators including chlorophyll a and DO
to assess U.S. waters (U.S. EPA. 2016c. 2012b). Additional indices of overall condition
of estuarine functioning that incorporate biological indicators of eutrophication have
since been developed both in the U.S. and other countries (Boria et al.. 2012; Devlin et
al.. 2011; Boria et al.. 2008). Comparisons of these frameworks have led to identification
of more robust and representative methods to measure estuarine response such as
incorporation of annual data, frequency of occurrence, spatial coverage, secondary
biological indicators, and amulticategory rating scale (Devlin etal.. 2011).
10.8.2 Nutrient-Enhanced Coastal Acidification
The body of evidence is suggestive of a causal relationship between N deposition and
changes in biota including altered physiology, species richness, community
composition, and biodiversity due to nutrient enhanced coastal acidification. Since
the 2008 ISA, N enrichment has been recognized as a possible contributing factor to
increasing acidification of marine environments. Dissolution of atmospheric
anthropogenic CO2 into the ocean has led to long-term decreases in pH (Wallace et al..
2014; Orr et al.. 2005). With increasing N inputs to coastal waters CO2 in the water
column is produced from degradation of excess organic matter which in turn can make
the water more acidic (Sunda and Cai. 2012; Cai etal.. 2011c; Howarth et al.. 2011).
Models show that while the impact of each acidification pathway (N enrichment and
atmospheric CO2 dissolution) may be moderate, the combined effect of the two may be
much larger than would be expected by just adding the effects of each pathway together
(Sunda and Cai. 2012; Cai et al.. 2011c).
Newer studies show that organisms that produce calcium carbonate shells are impacted
by increasing acidification of waters (Barton et al.; Kroeker et al.. 2013; Barton et al..
2012; Hettinger et al.. 2012). Affected organisms may include calcareous plankton,
oysters, clams, sea urchins, and coral. Decreased saturation rates of aragonite and calcite,
two minerals needed in shell formation, are observed in acidic conditions. These
physiological responses to acidifying conditions in coastal waters may lead to impacts at
the population level. There are already documented declines of oyster production on the
U.S.'s west coast linked to ocean acidification.
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CHAPTER 11 NITROGEN EUTROPHICATION
EFFECTS IN WETLANDS
This chapter describes the effects of N deposition upon wetland ecosystems. The
introduction contains an overview of the relationship between N deposition and wetland
endpoints, as well as the wetland classification system used in this chapter (Section 11.1).
Regional sensitivity in wetlands is related to position within the watershed (Section 11.2).
N deposition causes changes to biogeochemical pools and processes in wetlands,
specifically, to N cycling (Section 11.3.1) and C cycling (Section 11.3.2). Nitrogen
eutrophication affects wetland primary producers via alteration of aboveground plant
biomass (Section 11.4). alteration of plant stoichiometry and physiology (Section 11.5).
alteration of plant architecture (Section 11.6). alteration of plant demography
(Section 11.7). and alteration of community composition (Section 11.8.1). Nitrogen
eutrophication also alters wetland biodiversity via changes to phytoplankton communities
(Section 11.8.2) and changes to consumer communities (Section 11.8.3). There are a
number of critical loads published for wetland ecosystems (Section 11.9).
11.1 Introduction
The 1993 Oxides of Nitrogen Air Quality Criteria Document and the 2008 ISA for
Oxides of Nitrogen and Sulfur—Ecological Criteria (hereafter referred to as the 2008
ISA) evaluated the effects of nitrogen deposition on wetland ecosystems. The
1993 AQCD found that the three main ecological effects of N deposition on wetland
ecosystems were reduced biodiversity, modified microbial processes, and increased
primary production. The 2008 ISA supported and extended the conclusions in the
1993 AQCD, especially with regard to the effects of N deposition on species diversity,
and also found evidence for alterations of ecosystem nitrogen and carbon cycling. The
2008 ISA found that the evidence was sufficient to infer a causal relationship between N
deposition to wetland ecosystems and the alteration of biogeochemical cycling, as well as
the alteration of species richness, species composition, and biodiversity. New evidence
published between 2008-2015 from observational studies, experimental N additions in
the field and in mesocosms, and reanalysis of large data sets supports and extends the
conclusions of the 2008 ISA. The body of evidence is sufficient to infer a causal
relationship between N deposition and the alteration of biogeochemical cycling in
wetlands. In addition to new information on species biodiversity, there is recently
published evidence of N deposition effects on endpoints not covered in the 2008 ISA,
including alterations to plant physiology and plant architecture. The body of evidence is
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sufficient to infer a causal relationship between N deposition and the alteration of
species physiology, species richness, community composition, and biodiversity in
wetlands.
Wetland vegetative communities are adapted to high levels of natural organic acidity, so
S and N deposition are unlikely to cause any acidification-related effects at levels of
acidic deposition commonly found in the U.S. (U.S. EPA. 2008a. in Annex B).
Sensitivity of wetlands to N deposition as a nutrient are well documented in the 2008 ISA
(Section 11.2). Hydrologic pathways are often the same pathways of N input; therefore,
they are useful for discussing the N sources and sensitivity to atmospheric N deposition.
In general, wetland types (Table 11-1) that receive most of their total N input from the
atmosphere are most sensitive to atmospheric deposition. Nearly all new N comes from
atmospheric deposition in ombrotrophic bogs because these wetlands only receive water
inputs via precipitation. They develop where precipitation exceeds evapotranspiration and
where there is some impediment to drainage of the surplus water (Mitsch and Gosselink.
1986). Fens, marshes, and swamps are characterized by ground and surface water inputs
that are often on the same order of magnitude as precipitation (Koerselman. 1989).
Lastly, intertidal wetlands receive water from precipitation, ground/surface water, and
marine/estuarine sources. Therefore bogs and fens are among the most vulnerable
wetlands to the nutrient-enrichment effects of N deposition (Krupa. 2003).
Table 11-1 Wetland classification used in the Integrated Science Assessment.
Wetland term Definition (adapted from, Wakelev. 2002: Mitsch and Gosselink. 2000: Cowardin et aL 19791
Soil-based classification
Peat
Substrate consisting of partially decomposed plant litter. In bryophyte-dominated wetlands (bogs
and fens), this layer is composed of dormant or dead moss. In marshes and swamps, peat consists
of dead litter, including plant leaves, stems, and roots, as well as undifferentiated soil organic
matter and sediments.
Peatland
Any wetland that accumulates or has historically accumulated organic C stores in the substrate.
Net primary productivity and accumulation of fixed C exceed decomposition rates. In Europe, the
synonymous term 'mire' is used.
Hydrology-based classification
Permanent
Wetland where a zone of the soil profile or peat profile remains saturated with water. The deeper
wetland
soil profile is typically saturated, anoxic, and often has a high percentage of organic matter.
Intermittent
Wetland where soils are saturated with water for short periods of time, annually or every few years;
wetland
soils tend to have higher mineral contents than do permanent wetland soils.
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Table 11-1 (Continued): Wetland classification used in the Integrated Science
Assessment.
Wetland term Definition (adapted from, Wakelev. 2002: Mitsch and Gosselink. 2000: Cowardin et aL 19791
Intertidal Wetlands where soils or sediments are inundated with water at high tide, and are exposed to air at
wetland low tide. This includes salt marshes, mangroves, and unvegetated mudflats.
Soil, hydrology, and vegetation-based classification
Bog or peat Defined by vegetation. A wetland dominated by acidophilic mosses, particularly Sphagnum
bog mosses. Ericaceous shrubs and certain graminoids are also particularly adapted for bog
conditions.
Ombrotrophic
or oligotrophic
bog
A peatland dominated by acidophilic mosses, particularly Sphagnum mosses. Water is derived
entirely from precipitation, with high [DOC], low pH, and low nutrient concentrations.
Mesotrophic, A peatland that supports herbaceous and woody plant species with a wetland surface composed of
poor, or moss species. Water sources include precipitation, surface water, and groundwater. Water pH
intermediate (acidic to circumneutral) and nutrient concentrations are intermediate between ombrotrophic bog
fen and minerotrophic fen.
Minerotrophic, A peatland dominated by herbaceous graminoid species typical of marshes, with a mat composed
rich, eutrophic, of moss species. Water sources include precipitation, surface water, and groundwater. Water has
or calcareous higher pH (circumneutral to alkaline), as well as higher concentrations of calcium ions and other
fen nutrients, than other bog types.
Swamp Defined by vegetation. A wetland dominated by woody plants, particularly tree and woody species
with physiological adaptations to occasional or constant soil inundation.
Mangrove An intertidal swamp. A subtropical or tropical swamp dominated by halophytic trees and shrubs.
Tidal inundation by ocean or estuarine waters is frequent. In the U.S., dominant species are trees
in the Avicennia and Rhizophora genera. Mangroves are important nursery habitats for marine
animal species.
Marsh Defined by vegetation. A wetland dominated by herbaceous plants with physiological adaptations
to occasional or constant soil inundation.
Freshwater Marsh dominated by herbaceous plant community composed of species with physiological
marsh adaptations to soil inundation. Includes marshes in lakes, rivers, and nonsaline regions of
estuaries. Salt- and sulfide-intolerant marsh plant species are common. Soils may be peat or
mineral sediments.
Pothole A type of freshwater marsh. A shallow pond with herbaceous and submerged aquatic vegetation,
common in the prairie ecosystems of the Dakotas and central Canadian plains. A pothole is often
not connected by surface water flow to its watershed; water sources include precipitation and
groundwater.
Tidal marsh An estuarine marsh. Used in this document to describe estuarine marshes in which water level
fluctuates in response to ocean tides but marsh water has low or no salinity (i.e., water sources are
freshwater). Depending on physical location in the estuary, occasional saltwater intrusion may alter
biogeochemistry and plant community. A mix of saline-tolerant and saline-intolerant plant species
is common.
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Table 11-1 (Continued): Wetland classification used in the Integrated Science
Assessment.
Wetland term Definition (adapted from, Wakelev. 2002: Mitsch and Gosselink. 2000: Cowardin et aL 19791
Salt or An intertidal marsh. Halophytic herbaceous species are dominant. Tidal inundation by ocean water
intertidal marsh structures the plant community, which typically forms zones of single species monocultures or
low-diversity communities of plants with similar tolerances for salt and water stress. Plant roots trap
alluvial sediments to build and maintain the elevation of the marsh surface, or platform. Salt
marshes are important nursery habitats for marine animal species.
Intermittent Defined by hydrology and vegetation. Wetland where soils are saturated, with soil processes
typical of aquatic sediments, for short periods annually or every few years; inundation occurs with
sufficient frequency to prevent persistence of flooding-intolerant plant species.
Vernal pool An area with mineral soils which is flooded by rainwater or rising water tables and then isolated
from surface water flow as it slowly dries up. These seasonally inundated areas are important
nursery habitat for a number of invertebrate and vertebrate species.
Riparian An area with mineral soils, and a high water table due to close proximity to a river, stream, or lake,
wetland Periodic inundation occurs when water levels rise. Vegetation is a mix of terrestrial plants and
plants with physiological adaptations to occasional soil inundation.
C = carbon; DOC = dissolved organic carbon.
11.2 Regional Sensitivity
There is no new information on regional sensitivity of wetlands to N deposition. In the
2008 ISA, wetlands were described in order of sensitivity to N deposition. Bogs are
among the most sensitive wetland ecosystems to N deposition. In the U.S., peat-forming
bogs and fens are most common in glaciated areas, especially in portions of the Northeast
and Upper Midwest (U.S. EPA. 1993). N input and output rates of freshwater or riparian
marshes and swamps are intermediate between bogs and coastal marshes. N deposition
increased primary productivity 30% and increased methane emissions. N deposition was
projected to drastically change species composition based on experimental results in
European fens (Pauli et al.. 2002; Aerts and de Caluwe. 1999). Atmospheric N inputs
contribute to eutrophication problems in coastal marshes at many locations. However,
marine inputs of N are typically higher than direct atmospheric input. Models of sources
of N to wetland ecosystems are not yet available.
11.3 Soil Biogeochemistry
The 2008 ISA described the relationship between N deposition and the alteration of
biogeochemical cycling in wetlands. N deposition alters N cycling (Section 11.3.1) and C
cycling (Section 11.3.2) in wetlands. N deposition alters N cycling by altering microbial
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communities, the rates at which they transform N between pools, ecosystem retention or
release of transformed N, and the emissions of the greenhouse gas nitrous oxide. N
deposition alters C cycling by altering soil processes such as decomposition and
respiration (resulting in emissions of the greenhouse gases carbon dioxide and methane),
as well as by altering soil pools such as belowground biomass and soil organic matter.
There is new evidence since 2008 of N deposition effects upon biogeochemical cycling
across wetlands, as well as in salt marshes, mangroves, bogs, and riparian wetlands. The
body of evidence is sufficient to infer a causal relationship between N deposition and
the alteration of biogeochemical cycling in wetlands.
11.3.1 Nitrogen Pools and Processes
Water table depth tends to fluctuate more in wetlands than terrestrial ecosystems. The
variable depth creates dynamic anoxic-oxic boundaries and many varied niches for
different microbial communities. As a result, wetlands are important disproportionate to
their spatial area on the landscape (i.e., hotspots) for the microbial transformation of
nitrogen between oxidized and reduced forms. These nitrogen transformations can
improve water quality of downstream streams, lakes, and estuaries by removing N in the
soil or water of an ecosystem into the atmosphere. However, these transformations can
result in emissions of the potent greenhouse gas nitrous oxide. Alteration to N cycling or
N cycling microbial endpoints indicate changes to the important wetland function of
improving water quality.
N deposition contributes to total N load in wetlands. The chemical indicators that are
typically measured include NOs leaching, N mineralization, and denitrification rates. N
dynamics in wetland ecosystems are variable in time and among types of wetlands and
environmental factors, especially water availability (Howarth et al.. 1996). A wetland can
act as a source, sink, or transformer of atmospherically deposited N (Devito et al.. 1989).
and these functions can vary with season and hydrological conditions. Vegetation type,
physiography, local hydrology, and climate all play significant roles in determining
source/sink N dynamics in wetlands (Mitchell et al.. 1996; Arheimer and Wittgren. 1994;
Koerselman et al.. 1993; Devito et al.. 1989).
N mineralization (microbial transformation of organic N to inorganic forms of N) has
been shown to increase with N addition, and this can cause an increase in wetland N
export to adjacent surface water (Groffman. 1994). In general, ecosystem leaching losses
ofNCV from wetlands to downstream aquatic systems are often small, as anoxic wetland
zones are favorable for microbial denitrification of N from NO3 to gaseous N forms.
Elevated N inputs to wetlands will often increase the rate of denitrification (Cooper.
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1990; Broderick et al.. 1988; Dierberg and Brezonik. 1983). This mitigates environmental
effects associated with increased N supply to soils and drainage waters; however,
increased denitrification may also increase the emissions of greenhouse gases (e.g., N2O)
to the atmosphere. Denitrification appears to be negligible in wetland environments that
are typically nutrient (including N) poor, such as some bogs and fens (Morris. 1991).
New studies summarized below in salt marsh, mangrove, peat bog, and riparian wetlands
have evaluated the effects of N loading/N addition on endpoints related to N cycling. In
addition, there is a new study on wetland N removal, synthesizing information across
wetland types.
11.3.1.1 Across Wetlands
N removal, defined as the sum of denitrification, plant uptake, and burial in sediments,
was evaluated by analyzing data from 109 wetlands distributed globally, including
agricultural wetlands, freshwater marshes, freshwater swamps, and coastal marshes
(Jordan et al.. 2011). Total N loads to these wetlands ranged from 0.2-90,480 kg N/ha/yr;
however, the sources of reactive N were not identified by the authors. Across this global
data set, wetland N removal as measured in outflow is proportional to wetland N load. N
removal efficiency was 26% higher in nontidal wetlands than in tidal wetlands.
The 2008 ISA found evidence that N deposition alters the emission of nitrous oxide
(N2O) and methane (CH4), which contribute to global warming. A meta-analysis of 19 N
addition observations (N addition 15.4 to 300 kg N/ha/yr) found that N enrichment
increased wetland N2O emissions by 207% (Liu and Greaver. 2009).
11.3.1.2 Salt Marsh
New studies have evaluated the effects of N loading/N addition on tidal export, N
mineralization, nitrification, and microbial community structure in salt marshes. Tidal
export of N from salt marshes was studied in a long-term (>30 years) fertilization
experiment in Massachusetts (Brin et al.. 2010) in which tidal export of N increased with
increasing N load. Tidal export of ammonia increased linearly with increasing annual N
load, and tidal export of nitrate increased exponentially with increasing annual load (see
Table 11-2 for equations). Likewise, a linear relationship was documented between
increasing N and decreasing potential N mineralization after 7 months of N addition to
three salt marshes in California [see Table 11-2 for equation (Vivanco et al.. 2015)1. In
this same study, there was no relationship between N addition and net nitrification rates;
however, the nitrification rates differed among the marsh sites.
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Increasing reactive N may change the diversity and composition of microbial
communities responsible for denitrification and nitrification. Change in the microbial
communities could change the rate of the chemical reactions that microbes perform in the
wetland. Increasing N loads alter the abundance of denitrifying bacteria. In the long-term
marsh fertilization experiment in a salt marsh in Massachusetts, nirS DNA sequences
were amplified to assess denitrifying bacteria (Bowen et al.. 2013). The plots sampled
were fertilized with sewage sludge, which contained other nutrients, metals, and organic
material in addition to N, and N addition rates were 221, 655, or 1,966 kg N/ha/yr. With
the addition of N, denitrifying bacteria communities became more dissimilar, as widely
distributed bacteria declined, and abundance and richness of unique denitrifiers increased
(Bowen et al.. 2013). Lage et al. (2010) sampled sediments associated with Spartina
patens in a New England salt marsh. This study used the amoA DNA sequence in
sediments to sample the ammonia-oxidizing bacteria, which produce nitrites from
ammonia in the first step of nitrification. The majority of species affected by N addition
were within a clade of Nitrosospira-like sequences found in other salt marshes. N
addition decreased evenness of distribution and altered composition, specifically the
relative abundance of taxa within the marine and estuarine Nitrosospira-like clade,
suggesting that there are fine-scale genetic differences to the bacteria's ability to use
nitrogen.
11.3.1.3 Mangrove
In mangrove ecosystems, N addition suppressed N fixation and increased denitrification
(Whigham et al.. 2009). Lab incubations showed that the denitrification rate was 15 times
higher in soils that had received 100 kg N/ha/yr than in control soils (N load on N
deposition in control soils not reported). However, field measurements of N2O emissions
were 5.6 times higher in fertilized than in control soils, indicating incomplete
denitrification in fertilized soils. Nitrogen fixation rates were suppressed by 88% in
fertilized plots (Whigham et al. 2009).
11.3.1.4 Riparian Wetland
New studies on riparian wetlands include N addition relationships to denitrification rates
and bacterial community composition. In a riparian wetland in Durham, NC, wetland
species' potential denitrification activity increased linearly with increasing soil total
inorganic N [see Table 11-2 for equation (McGill et al. 2010)1. In freshwater riparian
wetlands along the James River, Virginia, soils were collected and incubated with added
nitrogen. Nitrogen addition increased the abundance of denitrifying bacteria—quantified
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as copies of the nirS sequence—by 541% when labile organic matter was also added
(Morrissev et al.. 2013). When N addition occurred simultaneously with the addition of
recalcitrant organic matter, denitrifying bacterial abundance decreased 96% with
increased N. Community composition of denitrifying bacteria shifted in response to N
addition, as did the composition of bacteria capable of dissimilatory nitrate reduction to
ammonia [quantified as copies of nrfA sequence (Morrissev et al.. 2013)1.
In riparian forests, increased N loads altered the symbiotic association between A In us
incana ssp. tenuifolia (grey alder, hereafter A tenuifolia) and Frankia (actinorhizal, N
fixing bacteria). N addition of 100 kg N/ha/yr decreased the density of Frankia- hosting
root nodules by 62% compared to nodules from unamended control plots. Nodule
respiration rates were 28% lower under N fertilization, indicating lower rates of Frankia
metabolism, and N fixation in nodules was 31% lower than in controls (Ruess etal..
2013).
11.3.1.5 Bog
In peat bog ecosystems, N addition altered N cycling by decreasing the N retention
efficiency of the ecosystem, as measured by the recovery of a 15N tracer. When N was
added at the rate of 16 kg N/ha/yr from 2000-2007, a pulse of added 15N was recovered
at lower rates from fertilized plots than from unamended control plots (N deposition was
8 kg N/ha/yr), indicating a 71% reduction in average retention efficiency across biomass
pools (Xing etal.. 2011).
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11.3.1.6 Summary Table
l
Table 11-2 New studies on nitrogen addition effects on nitrogen cycling in
wetlands.
Additions or
Type of
Load
Biological and Chemical
Ecosystem
(kg N/ha/yr)
Effects
Study Site
Study Species
Reference
Agricultural
0.02-90,480 kg
Removal: Wetland N
Global
Reanalysis of data
Jordan et al.
wetlands;
N/ha/yr as N load,
removal is proportional to
from 109 global
(2011)
intertidal
mean load for
N load: log (N
wetlands
marshes;
each wetland
removal) = 0.943(log [N
freshwater
class: agricultural:
load]) - 0.033. N removal
bogs and
426, intertidal:
efficiency is 26% higher in
marshes;
211, freshwater
nontidal than tidal
freshwater
bogs and
wetlands.
swamps;
marshes: 890,
other
freshwater
wetlands
swamps: 69,
other: 280 kg
N/ha/yr
Deposition =
not reported
Wetlands
N addition
N addition increases N2O
Global
Meta-analysis of
Liu and
(natural and
experiments, N
emissions 207% across
data collected from
G re aver
agricultural)
addition of 15.4 to
wetlands (n = 19).
North America,
(2009)
300 kg N/ha/y
South America,
Europe, and Asia
Deposition = not
reported
Salt marsh
Addition = 180 kg
Tidal export: of N
Great
Spartina
Brin et al.
N/ha/yr (as
increases with increasing
Sippewissett
alterniflora,
(2010)
Milorganite, NPK
N addition.
Marsh,
Spartina patens,
10-6-4), 520 kg
For NH4+ export: Tidal
Massachusetts
and Distichlis
N/ha/yr (as urea
export NH4+
spicata
or as Milorganite),
(kg N/season) = 0.00083
1,560 kg N/ha/yr
(annual load) + 0.4326.
(as Milorganite)
For NO3" export: Tidal
export NO3
(kg N/season) =
0 1226~'0018(anr|ual l°ad)
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Table 11-2 (Continued): New studies on nitrogen addition effects on nitrogen
cycling in wetlands.
Type of
Ecosystem
Additions or
Load
(kg N/ha/yr)
Biological and Chemical
Effects Study Site Study Species
Reference
Salt marsh
Addition = 0,100,
200, 400, 800,
1,600,
3,200 kg N/ha/yr
as urea
N deposition =
3-5 kg N/ha/yr as
reported in
Tonnesen et al.
(2007)
Mineralization: Potential
net N mineralization
decreases in a linear
response to N; N
mineralization = -0.0015x
(g N added/m2/yr) +
0.022.
Nitrification: no significant
relationship.
Morro Bay
National
Estuary,
Carpinteria Salt
Marsh Reserve,
Tijuana River
Reserve
Estuary,
California
Salicornia
depressa Standi.
(Salicornia
virginica) stands
Vivanco et al.
(2015)
Salt marsh
Addition =
1,630 kg N/ha/yr
as NH4NO3
Deposition =
not reported
Bacterial community:
N addition decreases
evenness of
ammonia-oxidizing
bacterial community and
changes community
composition (p = 0.017).
Scarborough
Marsh, Maine
p-proteobacteria
containing amoA
gene in sediments
associated with
Spartina patens
Laqe et al.
(2010)
Salt marsh Addition = sewage Bacterial community:
sludge. Low
fert = 221 kg
N/ha/yr, high
fert = 655 kg
N/ha/yr, very high
fert = 1,966 kg
N/ha/yr
Deposition =
not reported
Ubiquitous nirS
sequences declined with
increasing N addition
(higher abundance and
richness of unique
denitrifying species in
higher N treatments).
Great
Sippewissett
Marsh,
Falmouth,
Massachusetts
Denitrifying
bacteria in
sediment
(community)
Bowen et al.
(2013)
Mangrove
Addition = 100 kg
N/ha/yr
Deposition =
not reported
Denitrification:
Denitrification rate (lab
incubation) was 15 times
faster in N addition
sediments.
Indian River Avicennia
Lagoon, Florida germinans and
(Impoundment associated
SLC-24) sediments
Whiqham et
al. (2009)
Riparian
wetland
Addition = n/a
Deposition =
not reported
Denitrification: Potential
denitrification activity in
spring increases with total
inorganic N in soil
(y = 6.96x+ 20.52).
Durham, North 1, 4, or 8 species
Carolina from Carex crinita,
Carex lurida,
Scirpus cyperinus,
Juncus effusus,
Panicum virgatum,
Chasman-thium
latifolium,
Eupatorium
fistulosum, Veronia
novebora-censis,
Asclepias,
incarnata, and
Lobelia cardinalis.
McGill et al.
(2010)
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Table 11-2 (Continued): New studies on nitrogen addition effects on nitrogen
cycling in wetlands.
Type of
Ecosystem
Additions or
Load
(kg N/ha/yr)
Biological and Chemical
Effects Study Site Study Species
Reference
Riparian
floodplain
successional
forest
Addition = 100 kg
N/ha/yr
Deposition = not
reported
Frankia nodule densities
decreased 62%. Nodule N
fixation declined 31% and
nodule respiration
declined 28%.
Bonanza Forest
LTER, Alaska
Alnus incana ssp.
tenuifolia (or A.
tenuifolia) and
associated Frankia
strains
Ruess et al.
(2013)
Riparian
wetland
Addition = Soil
incubations with
0.5, 2, 4 mg N/g
wet sediment as
KNOs
Deposition = not
reported
Nitrate addition increased
DNF (copies nirS)
abundance 541 % when
labile OM was present
and decreased DNF
abundance 96% when
recalcitrant OM was
present. Community
composition of DNF and
DNRA shifted in response
to nitrate addition.
James River,
Charles City
County, Virginia
Soil microbial
communities
involved in
denitrification
(DNF, gene nirS)
or dissimilatory
nitrate reduction to
NH4+ (DNRA, gene
nrfA)
Morrissev et
al. (2013)
Ombro-
Addition = 16 kg
Retention efficiency: N
Mer Bleue Bog,
Bog plant
Xina et al.
trophic peat
N/ha/yr as
addition decreased the
Ontario, Canada
community: dwarf
(2011)
bog
NH4NO3 N
retention efficiency of
(measured
shrub species and
deposition =
ecosystem N pools (15N
2007)
mosses:
8 kg N/ha/yr as
tracer) by 71%.
Sphagnum
quantified by
magellanicum,
Turunen et al.
Sphagnum
(2004)
capillifolium, and
Polytricum strictum
DNF = denitrification; DNRA = dissimilatory nitrate reduction to ammonium; fert = fertilizer; ha = hectare; kg = kilogram;
KN03 = potassium nitrate; LTER = Long-Term Ecological Research; N = nitrogen; NH4+ = ammonium; NH4N03 = ammonium
nitrate; NPK = nitrogen, phosphorus, potassium; S = sulfur; yr = year.
11.3.2 Soil Carbon Cycling
Wetlands can be hotspots for emissions of carbon dioxide and methane. High water levels
in wetland soils prevent the rapid decomposition of dead roots and fallen stems by
aerobic bacteria or fungi. Over long time periods (decades, centuries, or millennia), this
results in large stores of carbon belowground in wetland systems. Methanogens are able
to decompose some of these anaerobic, saturated carbon stores to produce methane, and
in severe droughts, a larger microbial community can produce large pulses of carbon
dioxide by decomposing freshly aerated older organic carbon. Endpoints of methane and
carbon dioxide emissions have important implications for the wetland function of
long-term carbon storage, as well as obvious feedbacks for climate change
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A meta-analysis that included wetlands with other nonforest ecosystems indicated no
effect of N deposition on overall net ecosystem exchange of carbon (see
Section 11.3.2.2.1). In other words, any gain in carbon capture by photosynthesis was
offset by ecosystem respiration and C leaching. There were not enough studies to
evaluate wetlands as a separate category.
11.3.2.1 Belowground Decomposition, Respiration, and Biomass
Respiration includes the release of carbon dioxide that can be measured in the air. Soil
respiration may be the result of root or microbial activity. The process of decomposition
often releases carbon dioxide from organic matter. Decomposers feed on dead organic
matter, breaking it down into its simplest components: carbon dioxide or methane, water,
and nutrients. Nitrogen may change the rate of respiration and decomposition.
Low decomposition in wetlands results in the buildup of dead plant material in the soil. In
relatively closed systems, such as rain-fed bogs, a nutrient-poor, high-organic-acid
ecosystem is produced. In open systems where flowing surface water supplies additional
nutrients and sediments, the growth of new root systems on top of undecomposed roots
can trap sediment and increase the height of the soil surface. This accretion of new
wetland soil depends on both plant growth and maintenance of old carbon stored in soil
organic matter. Wetland existence depends on the sum of these processes: if the sum of
new plant growth does not exceed the decomposition of the soil organic matter, the
wetland may subside until water levels rise above the soil surface. In this case, the
drowned wetland area converts to an aquatic system. Wetland accretion is particularly
important in estuarine and marine systems, where wave action and tides regularly wash
sediment and dead plant material out of the wetland into aquatic systems, where they
nourish aquatic food webs. Belowground endpoints, such as bulk density, soil organic
matter, and root and rhizome production, are all indicators of wetland health and
continued existence (Table 11-3).
11.3.2.1.1 Across Wetlands
A new study of 90 wetlands around the Gulf Coast from Florida to Texas found that
higher N in the soil correlated with lower soil bulk density [see Table 11-3 for equation,
(Nestlerode et al.. 2014)1. Wetlands included both tidal and nontidal marshes and
swamps. Reactive N or atmospheric N deposition loads were not quantified. This result
suggests that higher N in wetlands correlates with a reduction in wetland soil stability,
making wetlands more susceptible to erosion.
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11.3.2.1.2
Salt Marsh
A new study confirms N loading increases carbon dioxide production from salt marsh
soils. The new study uses an older model developed by Wigand et al. (2003). the
Nitrogen Loading Model (NLM) for wetlands and estuaries of Narragansett Bay, Rhode
Island, to determine annual N loads for different watersheds (sum of Nr from runoff,
deposition, and municipal waste, 10.3-6,727 kg N/ha/yr) within the bay. Sampling of
cordgrass marshes [Spartina alterniflora and Spartinapatens (Wigand et al.. 2009)1
within these watersheds showed that soil respiration of CO2 increased linearly and at
similar rates with increasing annual N load in stands of S. alterniflora and S. patens.
Decreases in sediment soil %C and %N and in belowground biomass were also observed
as soil respiration increased (Wigand et al.. 2009). Two additional experiments evaluated
how N addition affects soil respiration (Anisfeld and Hill. 2012) and general CO2 (see.
Wigand et al. 2015a). In both cases, N addition increased these rates; however, the
amount of N was over 1,000 kg/ha/yr, too high a level to evaluate the effects of N
deposition.
In the Great Sippewissett Marsh fertilization experiment, fertilization with 520 kg N
decreased long-term carbon storage in substrates by 31% (Turner et al.. 2009). The
stability of the marsh substrate decreased (measured as the physical resistance to force
decreased) 60% in urea-only fertilized plots. In contrast, N addition to S. alterniflora
marshes located in Cocodrie, LA did not affect the physical resistance of the surface
marsh substrate, and no changes at any profile were detected with the addition of
1,200 kg N/ha/yr (Turner. 2011). At much higher rates of N addition, substrate depths of
60-100 cm, physical resistance decreased by 37% of unamended marsh with 2,300 or
4,700 kg N/ha/yr added, decreased 38% at 9,300 kg N/ha/yr, and decreased 42% at
18,600 kg N/ha/yr (Turner. 2011).
Each year, marsh plants produce a new set of fine roots to acquire nutrients from the
sediment and pore water. In Kirkpatrick Marsh, vegetation consisted of Schoenoplectus
americanus, Spartina patens, and Distichlis spicata. N addition alone (250 kg N/ha/yr,
ambient CO2) decreased fine root production by 42% and 84% compared to control plots
in the 3rd and 4th years of the experiment (Langlev and Megonigal. 2012. 2010). In an
experiment at Goat Island, SC, addition of 4,200 kg N/ha/yr over 12 years decreased fine
root mass 39% in the top 10 cm of sediments (Davev et al.. 2011).
In marshes, coarse roots and rhizomes are produced by plants to serve as physical
supports and as storage organs for nutrients and carbohydrates. In a freshwater tidal
marsh dominated by Zizaniopsis miliacea in the Altamaha River Estuary, Georgia,
addition of 500 kg N/ha/yr decreased the biomass of live rhizomes by 71%, and the mass
of macro-organic matter (living + dead roots) decreased 33% (Ret et al.. 2011). In
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contrast, higher levels of N addition in coastal salt marshes had opposite effects on
belowground biomass. At Goat Island, SC, addition of 4,200 kg N/ha/yr increased the
total volume of coarse roots in the top 10 cm of sediments by 63% (Wigand et al..
2015a). increased peat as fraction of total mass by 28% (Davev et al.. 2011). and
increased root and rhizome mass fraction by 58% over unamended marsh (along with
changes to root structure, see Section 11.6). In a larger soil profile, 0-21 cm depth,
organic matter increased 20% (Wigand et al.. 2015b).
11.3.2.1.3 Bog
In the 2008 ISA, soil respiration in bogs had been studied in European countries under a
natural gradient of atmospheric N deposition from 2 to 20 kg N/ha/yr. Studies found
enhanced decomposition rates for material accumulated under higher atmospheric N
supplies resulted in higher carbon dioxide emissions. There are two new studies on bogs
located in Ontario.
The Mer Bleue Bog in Ontario is the site of two concurrent fertilization experiments. In
one experiment, treatments were initiated in 2000 with nitrogen addition of 16 kg
N/ha/yr. The second experiment was initiated in 2005 in separate plots, where
nitrogen-only treatments of 32 kg N/ha/yr and 64 kg N/ha/yr were applied. Each
experiment had separate control plots. N addition at the rate of 16 kg N/ha/yr decreased
the concentrations of CO2 in peat substrate in the 8th year of N addition (2007),
decreasing CO2 by 19% at 5 cm depth and 14% at 25 cm depth (Wendel et al. 2011). N
addition at the rate of 64 kg N/ha/yr did not significantly alter ecosystem respiration
when assessed 7 years after fertilization started (2011), but due to declines in cover and
changes in photosynthesis (see Section 11.5.6 and Section 11.8.1.4). net ecosystem
exchange in the growing season was 46% lower than in unamended bog plots (Larmola et
al.. 2013).
In the Mer Bleue ombrotrophic peat bog, 16 kg N/ha/yr added from 2000 to 2007
increased peat biomass 17% in the top 10 cm of the substrate. In addition, median
temperature at 5 cm depth in the peat was 19% lower in plots which received
16 kg N/ha/yr than in control plots (Wendel et al.. 2011). which the authors posited was
due to increased shading by increasingly productive shrub species. In contrast, soil
temperatures were elevated deeper in the peat substrate; at 20 cm depth, average daily
temperature was 0.6°C higher in plots with 16 kg N/ha/yr added than in control plots
(Wendel etal.. 2011).
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11.3.2.1.4 Summary Table
i
Table 11-3 Loading effects upon belowground carbon cycling.
Type of
Ecosystem
Additions or
Load (kg
N/ha/yr)
Biological and Chemical
Effects
Study Site Study Species Reference
Estuarine marsh,
N dep = not
Soil total N increased
90 Gulf Coast
Marsh
Nestlerode et
estuarine shrub
reported
(In-transformed) as soil
wetlands,
community, soil
al. (2014)
swamp,
S dep = not
reported
bulk density decreased,
T exas to
and pore water
palustrine marsh,
(in soil %
Florida
chemistry
palustrine
N) = -1.9233 x (density,
swamp
g/cc) + 0.4165.
Salt Marsh
Watershed total
N load (10.3,
11.5, 27.4, 37.4,
2,729.9, 3,661,
and 6,727 kg
N/ha/yr) using
nitrogen loading
model in Wiqand
et al. (2003)
N dep = not
reported
S dep = not
reported
In S. alterniflora stands,
soil respiration increased
linearly with N loading
(y= 0.0006X+ 2.04). Soil
%C and %N decreased as
soil respiration increased.
Narragansett
Bay, Rhode
Island
Bare sediments Wiqand et al.
in Spartina
patens and
Spartina
alterniflora
stands ,
additional S.
patens marshes
from Wiqand
(2008): Wiqand
et al. (2003)
(2009)
Estuarine salt
marsh
250 kg N/ha/yr
N dep = not
reported
S dep = not
reported
Total fine root production Kirkpatrick
decreased by 42% and
84% in the third and fourth
years; under elevated CO2
and N, fine roots
decreased by 54% and
46% in the 3rd and 4th
years.
Schoenoplectus Lanqlev and
Marsh,
Maryland
(measured in
third and fourth
years,
2008-2009)
americanus
(C3), Spartina
patens (C4),
and Distichlis
spicata (C4)
Meqoniqal
(2012. 2010)
Salt Marsh
520 kg N/ha/yr in
U (N as urea
treatment), UP
(urea + 208 kg
P/ha/yr as
phosphate), and
HF (Milorganite,
10-6-4 NPK)
plots, as reported
by Brin et al.
(2010)
N dep = not
reported
S dep = not
reported
Fertilization decreased the
organic:inorganic ratio by
31% in older, deeper
(pre-1963) marsh
substrate, and decreased
the physical resistance of
the marsh substrate
(shear vane strength) by
60% in U plots, 36% in UP
plots, and 35% in HF
plots.
Great
Sippewissett
Marsh,
Massachusetts
Spartina
alterniflora,
Spartina patens,
and Distichlis
spicata
Turner et al.
(2009)
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Table 11-3 (Continued): Loading effects upon belowground carbon cycling.
Type of
Ecosystem
Additions or
Load (kg
N/ha/yr)
Biological and Chemical
Effects
Study Site Study Species Reference
Salt marsh
Addition:
1,050 kg N/ha/yr
(low) as NaNC>3,
2,100 kg N/ha/yr
(medium) as
NH4NO3 or
NaNOs, 4,200 kg
N/ha/yr (high) as
NH4NO3 in same
plots in over
several years
N dep = not
reported
S dep = not
reported
Medium N increased
annual sediment
respiration
(g C/m2/yr) by 53%.
Hoadley Creek
Marsh,
Guilford,
Connecticut
Spartina
alterniflora
Anisfeld and
Hill (2012)
Coastal salt
marsh
Addition:
4,200 kg N/ha/yr
as NH4NO3 or
(NH4)2S04
N dep = not
reported
S dep = not
reported
N addition increased
coarse root volume 63% in
the top 10 cm, or 61 % in
the top 20 cm of sediment.
Organic matter increased
20% in the top 21 cm of
sediment. CO2 emission
increased 41%.
Goat Island,
South Carolina
(measured
2008)
Spartina
alterniflora and
associated
sediments
Wiqand et al.
(2015a)
Salt Marsh
4,200 kg N/ha/yr N addition increased peat Goat Island,
Spartina
as NH4NO3
N dep = not
reported
S dep = not
reported
mass fraction by 28% and
root/rhizome mass fraction
by 58% in wet shallow
(<10 cm) sediments. Fine
root mass decreased 39%
in shallow sediments.
South Carolina alterniflora
(measured
2008)
Davev et al.
(2011)
Freshwater
marsh
500 kg N/ha/yr as Addition of 500 kg N/ha/yr Altamaha
NH4CI or urea
N dep = not
reported
S dep = not
reported
decreased the biomass of Estuary,
live rhizomes by 71%, and Georgia (2007,
the mass of macro-organic 2008)
matter (living + dead
roots) decreased 33%.
Zizaniopsis
miliacea,
Pontederia
cordata, and
Sagittaria
lancifolia
Ket et al.
(2011)
Ombrotrophic
peat bog
16 (low), 32
(medium), or 64
(high) kg N/ha/yr
as N (NH4NO3) or
NPK(NH4N03
and KHPO4)
S dep = not
reported
N dep = 8 kg
N/ha/yr
Medium and high NPK
increased ecosystem
respiration in 8th year by
24% and 32%
respectively, and
decreased surface
temperature by 11% and
13% respectively. In high
NPK, the water table was
42% closer to peat
surface.
Mer Bleue
Bog, Ontario,
Canada
Bog plant
community:
dwarf shrub
species and
mosses
Sphagnum
magellanicum,
Sphagnum
capillifolium,
and Polytricum
strictum
Juutinen et al.
(2010)
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Table 11-3 (Continued): Loading effects upon belowground carbon cycling.
Type of
Ecosystem
Additions or
Load (kg
N/ha/yr)
Biological and Chemical
Effects
Study Site Study Species Reference
Ombrotrophic
peat bog
Addition: 16 kg
N/ha/yr as
NH4NO3
N dep = 8 kg
N/ha/yr as
quantified by
Turunen et al.
(2004)
N addition lowered
substrate temperature at
5 cm depth, decreasing
median temperature by
19% and increased
substrate temperature at
20 cm depth, by an
average of 0.6°C.
N addition decreased CO2
concentrations in
substrate by 19% at 5 cm
depth and by 14% at
25 cm depth.
N addition increased peat
biomass 17%.
Mer Bleue
Bog, Ontario,
Canada
(measured
2007)
Bog plant
community:
dwarf shrub
species and
mosses
Sphagnum
magellanicum,
Sphagnum
capillifolium,
and Polytricum
strictum
Wendel et al.
(2011)
Ombrotrophic
peat bog
16 (low), 32
(medium), or 64
(high) kg N/ha/yr
as N (NH4NO3) or
NPK(NH4N03
and KHPO4)
Under high N, growing
season net ecosystem
exchange declined by
46%.
Mer Bleue
Bog, Ontario,
Canada
Shrub species
(Vaccinium
myrtilloides,
Ledum
groenlandicum,
Chamaedaphne
calyculata) and
mosses
(Sphagnum
magellanicum,
Sphagnum
capillifolium,
Polytricum
strictum)
Larmola et al.
(2013)
ANPP = aboveground net primary productivity; C = carbon; cm = centimeter; C02 = carbon dioxide; dep = deposition; g = gram;
ha = hectare; kg = kilogram; m = meter; N = nitrogen; NaN03 = sodium nitrate; NH4CI = ammonium chloride; NH4NO3 = ammonium
nitrate; (NH4)2S04 = ammonium sulfate; NPK = nitrogen, phosphorus, potassium; S = sulfur; yr = year.
11.3.2.2 Methane Emissions
1 Methane (CH4) is an important greenhouse gas that is over 20 times more effective at
2 trapping heat than carbon dioxide. The primary biological source of methane is microbial
3 (methanogens in the domain Archaea), as is the primary biological sink (methanotrophs
4 among the Bacteria and Archaea). Therefore, understanding the controls on these
5 microorganisms is important for predicting methane flux from ecosystems, especially in
6 the face of global change drivers such as nitrogen enrichment. In terms of carbon
7 emissions, the 2008 ISA reported that N deposition alters CH4 flux in wetland and
8 forested ecosystems. A meta-analysis of 25 N addition observations (N addition 30 to
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240 kg N/ha/yr) found that N addition increased CH4 emissions by 95% from wetlands
and grasslands [see Table 11-4 for non-significant results; Liu and Greaver (2009)1.
There is new evidence that N loading increases methane production in soils. In the N
addition experiments replicated in three California marshes (Vivanco et al. 2015; Irvine
et al.. 2012). field-measured methane flux from soils increased linearly with increasing N
load (0, 100, 200, 400, 800, 1,600, 3,200 kg N/ha/yr), such that CH4 flux from soils
increased by 1.23 |ig CH4/m2/d for each 10 kg N/ha/yr added R2 = 0.23 and P = 0.025
(Vivanco et al.. 2015; Irvine et al.. 2012). Methane flux increased from low or nearly
negative to net positive values above -100 kg N/ha/yr, showing that the effect of added N
on methanogenesis, the final step in anaerobic decomposition, offset any increase in
methanotrophy. Differential effects of N on both methanogenesis and methanotrophy
have been documented in other ecosystems (Irvine et al.. 2012; Liu and Greaver. 2009).
The linearity of the trend becomes less robust when the exposure time increases to
14 months.
Soils were collected from the Tijuana River Reserve near the sites used in Vivanco et al.
(2015) and incubated in a laboratory microcosm experiment with factorial C and N
additions (Irvine et al.. 2012). Adding C and N together increased methane production by
44% above controls (Irvine et al.. 2012). suggesting that N loading will increase
microbial methane production disproportionally when accompanied by pulses of labile C.
The authors conclude temperate salt marshes generally emit low levels of methane, but
these values are also highly spatially and seasonally variable (Cheng et al.. 2010;
Magenheimer et al.. 1996; Bartlett et al.. 1985; King and Wiebe. 1978). Despite the high
variability observed, however, the field experiment suggests that increased N availability
stimulates methanogenesis and increases methane emissions in southern California salt
marshes, as in other ecosystems (Liu and Greaver. 2009).
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11.3.2.2.1
Summary Table
Table 11-4 Nitrogen loading effects upon methane emissions.
Type of
Ecosystem
Additions or
Load (kg
N/ha/yr)
Biological and Chemical Effects Study Site Study Species Reference
Wetlands
(natural and
agricultural)
N addition
experiments, N
addition of 10
to 562 kg
N/ha/y
Deposition =
not reported
No effect across wetlands (n = 6) Global
of N addition on net ecosystem
exchange.
N addition increased ChU
emissions by 95% across
grass + wetland + anaerobic
agricultural systems (n = 25).
Meta-analysis of
data collected
from North
America, South
America, Europe,
and Asia
Liu and
G re aver
(2009)
No effect across drained wetlands
of N addition (n = 6) upon
biological CH4 uptake.
Salt Marsh 100,200,400,
Methane flux increased linearly
Morro Bay,
Marsh dominated
Irvine et al.
800, 1,600,
with N addition: y (mg CH4/m2/d) =
Carpinteria
by Salicornia
(2012)
and 3,200 kg
0.00123x (g N/m2/yr) - 0.0122.
Salt Marsh,
depressa
N/ha/yr as
Tijuana
(formerly
granular urea
River
Reserve,
California
Salicornia
virginica)
Salt Marsh 0,100,200,
CH4 flux from soils increased by
Morro Bay
Stands of
Vivanco et al.
400, 800,
1.23 |jg CH4/m2/d for each
National
Salicornia
(2015)
1,600,
10 kg N/ha/yr added
Estuary,
depressa
3,200 kg
Carpinteria
(formerly
N/ha/yr as
Salt Marsh
Salicornia
urea
Reserve,
Tijuana
virginica)
N
River
Reserve
dep = 3-5 kg
N/ha/y as
Estuary,
California
reported in
Tonnesen et
al. (2007)
11.4 Production and Aboveground Biomass
Aboveground biomass is a measure of how much carbon is fixed by wetland plants.
Changes in this endpoint can affect food webs within the wetland, including dependent
migratory species. Changes in aboveground biomass will also be important for food webs
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in rivers, lakes, or estuaries connected by surface water flow, as plant litter from wetlands
is an important base for food webs downstream. The new studies published from
2008-2015 include work on tidal marsh, mangroves, and ombrotrophic bogs.
11.4.1 Salt Marsh
In the 2008 ISA, primary production of plant species in intertidal wetlands typically
increased with N addition; however, most studies apply fertilizer treatments that are
several orders of magnitude larger than atmospheric deposition (Darby and Turner. 2008;
Tvleret al.. 2007; Wigand et al.. 2003; Mendelssohn. 1979). N fertilization experiments
in salt marsh ecosystems show biomass stimulation from 6 to 413% with application rates
ranging from 7 to 3,120 kg N/ha/yr (U.S. EP A. 1993). A number of new studies have
evaluated N effects on production and biomass in intertidal wetlands.
In Elkhorn Slough, the largest coastal marsh in California, addition of 150 kg N/ha/yr
increased S. pacifica biomass in two of the six experimental sites (Goldman Martone and
Wasson. 2008). a 36% increase over unamended plots occurred in a site with unrestricted
tidal flow, and a 53% increase occurred in a marsh where impoundments restricted
regular tidal exchange. Darby and Turner (2008) reported on a nitrogen addition
experiment at Cocodrie, LA, in which five loads of nitrogen were applied to S.
alterniflora marshes. Aboveground biomass increased linearly with increases in N load,
although the regressions were not reported. Additions of 230 and 465 kg N/ha/yr did not
significantly raise aboveground (AG) biomass above unamended marsh biomass, but
930 kg N increased AG biomass 122%, 1,860 kg N increased AG biomass 124%, and
3,720 kg N/ha/yr increased AG biomass 141%. A nitrogen addition experiment with
seven different N loads (0, 100, 200, 400, 800, 1,600, and 3,200 kg N/ha/yr) was
replicated at three different California estuarine reserves [Morro Bay, Carpinteria Salt
Marsh, and Tijuana River Marsh Reserve (Vivanco et al.. 2015)1. Aboveground biomass
of existing S. depressa increased linearly in response to N addition across all three
marshes and N addition levels starting at 100 kg N/ha/yr (see Table 11-5 for equation,
R2 = 0.58). When harvested plots were resampled, the regrowth of aboveground biomass
increased in a saturating response to increasing N load, with no significant increases in
biomass in response to N above 1,600 kg N/ha/yr (Table 11-5 for equation). Similar
saturation of plant response occurred in N tissue (see Section 11.5).
Several other studies have evaluated N addition levels over 1,000 kg N/ha/yr; in all cases,
N addition increased biomass, but the high levels of experimental N addition
exponentially exceed N loading from deposition, limiting the scope of inference from this
literature (Anisfeld and Hill. 2012; Nelson and Zavaleta. 2012; Ryan and Bover. 2012).
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The Kirkpatrick Marsh in Maryland is the site of a factorial elevated CO2 by nitrogen
fertilization experiment in a tidal marsh community consisting of Schoenoplectus
americanus, Spartina patens, and Distichlis spicata. Over the 4 years of the experiment,
nitrogen addition (and ambient CO2) of 250 kg N/ha/yr increased total aboveground
biomass by 47-79% (Langlev and Megonigal. 2010; Langlev et al.. 2009). When the
biomass response was partitioned by carbon fixation mechanism (C3 or C4 plants),
biomass of C3 plants declined with N addition to 81% in the third year and 55% in the
fourth year of initial fertilized S. americanus biomass. Biomass of C4 plants S. patens
and D. spicata increased 2-51 times the control over the 4 years of the experiment (see
Section 11.8.1). or increased 129% in the 4th year over initial fertilized C4 biomass.
Langlev and Megonigal (2010) suggest that the effects of N upon community
composition (decline in C3 plants, increased C4 biomass) will prevent the plant
community from increasing productivity in response to increased CO2, because increases
in CO2 alone enhanced total aboveground biomass, while increases in CO2 combined
with N addition decreased total aboveground biomass.
11.4.2 Freshwater Tidal Marsh
In a freshwater tidal marsh on the Tchefuncte River, Louisiana, Graham and
Mendelssohn (2010) conducted an N loading experiment that added 50, 200, or 1,200 kg
N/ha/yr to a plant community dominated by Sagittaria lancifolia, Eleocharis fallax, and
Persicaria punctata (formerly Polygonum punctatum). The aboveground net primary
productivity of the community increased with increasing N in a negative quadratic
function, with ANPP not increasing above 200 kg N/ha/yr (Graham and Mendelssohn.
2010).
There are several other new studies on the effects of N loading on aboveground biomass
of freshwater tidal ecosystems, but the addition rates are 500 kg N/ha/yr or greater. At the
Altamaha River Estuary, Georgia, N addition experiments were conducted in tidal
freshwater marshes dominated by giant cutgrass Zizaniopsis miliacea. Addition of 500 kg
N/ha/yr increased aboveground biomass 1.4-3.8 times control biomass in the
2nd through 5th years of fertilization (Ket et al.. 2011; Frost etal.. 2009). A nitrogen
experiment conducted in intertidal marshes and swamps on the Nanticoke River in the
Chesapeake Bay found that while an added load of 670 kg N/ha/yr did not significantly
change total herbaceous plant community aboveground biomass, it did increase biomass
of Typha spp. by 47% (Baldwin. 2013).
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11.4.3 Mangrove
Mangrove ecosystems are ecologically and economically important because they provide
habitat not just to a diversity of resident species but also serve as nurseries to the juvenile
lifestages of many marine fish species. As slow-growing tree species, mangroves are
rarely destructively sampled in order to estimate productivity and aboveground biomass.
The mangroves at Indian River Lagoon are the site of several nitrogen addition
experiments. Whigham et al. (2009) added 100 kg N/ha/yr to plots of dwarf Avicennia
germinans, black mangrove, which increased productivity by increasing the number of
new branches 150% above control plots.
There are several other new studies on the effects of N loading on aboveground biomass
of freshwater tidal ecosystems; however, the addition rates are 500 kg N/ha/yr or greater.
In a long-term (since 1997) N addition experiment that added approximately
11,200 kg N/yr to each tree, growth rate of Rhizophora mangle quantified by measuring
shoot elongation rates increased 290% in the shoreline fringe zone and increased 1,340%
in the interior scrub zone (Feller et al.. 2009). At Merritt Island National Wildlife Refuge,
N addition of 1,400 kg N/ha/yr in the ecotone where mangroves and cordgrasses grow in
competition increased A germinans seedlings' production of new leaves by 42%, which
increased total leaf biomass by 72% over unamended trees (Simpson et al.. 2013) and
altered above- and belowground stoichiometry (see Section 11.5.2).
11.4.4 Bog and Fen
In Sphagnum-dominated ombrotrophic bogs, higher N deposition resulted in higher tissue
N concentrations and greater NPP (Aldous. 2002a). but lower bulk density. A study of
23 ombrotrophic peatlands in Canada with deposition levels ranging from 2.7 to 8.1 kg
N/ha/yr showed peat accumulation increases linearly with N deposition; however, in
recent years, this rate has begun to slow indicating limited capacity for N to stimulate
accumulation (Turunen et al.. 2004). Soil respiration had been studied in European
countries under a natural gradient of atmospheric N deposition from 2 to 20 kg N/ha/yr.
The authors found that enhanced decomposition rates for material accumulated under
higher atmospheric N supplies resulted in higher carbon dioxide emissions.
In the Mer Bleue ombrotrophic peat bog, 8 years of N addition at the rate of
16 kg N/ha/yr increased biomass of mosses (Sphagnum magellanicum, Sphagnum
capillifolium, and Polytrichum strictum) by 30% of moss biomass in control plots (Xing
et al.. 2011). Relative changes in biomass can lead to plant community succession. Model
results from Logofet and Alexandrov (1984) suggest 7 kg N/ha/yr is the threshold for an
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oligotrophic bog to become a mesotrophic bog dominated by trees, as found in the 1993
Oxides of Nitrogen AQCD.
In freshwater-rich fens in Gogebic County, Michigan, N addition of 60 kg N/ha/yr
increased productivity of dominant grass Calamagrostis canadensis, which increased the
species' biomass to 600% over its biomass in unamended fen plots (Iversen et al.. 2010).
In oligotrophic bogs in Gogebic County, Michigan, N addition of 60 kg N/ha/yr increased
total plant community productivity by 82% over unamended plot productivity, which
resulted in 2.6 times as much biomass in fertilized plots as biomass in unamended plots
(Iversen et al.. 2010). The plant community trends reflected the responses of the
dominant vascular shrub Chamaedaphne calyculata, which increased its productivity by
87%, increasing C. calyculata biomass in N addition plots 105% over its biomass in
control plots (Iversen et al.. 2010).
11.4.5 Summary Table
Table 11-5 Nitrogen loading effects upon production and biomass.
Additions or
Type of Load (kg Biological and
Ecosystem N/ha/yr) Chemical Effects
Study Site
Study Species Reference
Coastal high Addition: At two sites with
marsh 150 kg N/ha/yr unrestricted and
as urea restricted tidal flow,
Six sites at Marsh community Goldman
Elkhorn Slough, dominated by Martone and
Watsonville, Sarcocornia pacifica, Wasson
California also contains Jaumea (2008)
N dep = not
reported
fertilization increased S.
pacifica biomass by 36
and 53%, respectively.
carnosa, Frankenia
salina, Spergularia
salina, Distichlis
spicata, and Atriplex
californica/
triangularis
Estuarine salt Addition: 100,
marsh 200, 400, 800;
Aboveground biomass Morro Bay Salicornia depressa Vivanco et al
increases in a linear National Estuary, Standi. (Salicornia (2015)
response to N addition, Carpinteria Salt virginica) stands
biomass = 0.001 * Marsh Reserve,
(g N/m2/yr) + 1.117 Tijuana River
(R2 = 0.58), while Reserve Estuary,
biomass regrowth California
increases in a saturating
response to N, biomass
regrowth =
-1.16 x e("001 a
N/m2/y) + -| Q9.
1,600,
3,200 kg
N/ha/yr as
urea
N
dep = 3-5 kg
N/ha/yr as
reported in
Tonnesen et
al. (2007)
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Table 11-5 (Continued): Nitrogen loading effects upon production and biomass.
Additions or
Type of
Load (kg
Biological and
Ecosystem
N/ha/yr)
Chemical Effects
Study Site
Study Species
Reference
Estuarine
Addition:
In S. pacifica, biomass
China Camp
Sarcocornia pacifica
Rvan and
marsh
1,337 kg
increased 54-185%
State Park,
dominant (C3
Bover (2012)
N/ha/yr as
across habitats.
California
succulent shrub),
urea.
Distichlis spicata (C4
S dep = not
grass), and Jaumea
reported
carnosa (C3
N dep = not
semisucculent forb)
reported
Coastal salt
Addition:
AG biomass increased
Elkhorn Slough,
Sarcocornia pacifica
Nelson and
marsh
3,000 kg
28 and 216% in
Monterey Bay,
dominant, Distichlis
Zavaleta
N/ha/yr as
successive summers,
California
spicata, Frankenia
(2012)
NH3NO3
and increased
saiina, and Jaumea
S dep = not
shoot-to-root ratio 249%.
carnosa
reported
N dep = not
reported
Coastal salt
230, 465, 930,
AG biomass increased
LUMCON,
Spartina aiternifiora
Darbv and
marsh
1,860, or
linearly with N load
Cocodrie,
Turner (2008)
3,720 kg
(regression not given).
Louisiana
N/ha/yr as
Aboveground live
(NH4)2S04
biomass increased
S dep = not
122%, 124%, and 141%
reported
in response to 930,
1,860, and 3,720 kg N.
N dep = not
reported
Coastal salt
1,050 kg
ANPP increased by
Hoadley Creek
Spartina aiternifiora
Anisfeld and
marsh
N/ha/yr (low)
132% in low, 130% in
Marsh, Guilford,
Hill (2012)
as NaNOs,
medium, and 120% in
Connecticut
2,100 kg
high N treatments.
N/ha/yr
(medium) as
NH4NO3 or
NaNOs,
4,200 kg
N/ha/yr (high)
as NH4NO3 in
same plots in
over several
years
S dep = not
reported
N dep = not
reported
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Table 11-5 (Continued): Nitrogen loading effects upon production and biomass.
Type of
Ecosystem
Additions or
Load (kg
N/ha/yr)
Biological and
Chemical Effects
Study Site
Study Species
Reference
Estuarine salt
marsh
Addition:
250 kg N/ha/yr
S dep = not
reported
N dep = not
reported
In ambient but not
elevated CO2, S.
americanus aboveground
biomass decreased by
19% and 45% in the 3rd
and 4th years,
respectively.
Kirkpatrick
Marsh, Maryland
(measured in
third and fourth
years,
2008-2009)
Schoenoplectus
americanus (C3),
Spartina patens (C4),
and Distichlis spicata
(04)
Lanqlev and
Meaoniaal
(2012. 2010)
Biomass of S. patens
and D. spicata increased
129% in the 4th year
over initial fertilized C4
biomass.
Estuarine salt
marsh
Addition:
250 kg N/ha/yr
S dep = not
reported
N dep = not
reported
In the first two growing
seasons, fertilization
increased productivity in
ambient and elevated
(ambient + 342 ppm)
CO2 treatments,
increasing aboveground
biomass in the second
season by 57% under
ambient CO2 and 70%
under elevated CO2.
Kirkpatrick
Marsh, Maryland
(measured in first
and second
years,
2006-2007)
Schoenoplectus
americanus, Spartina
patens, and Distichlis
spicata
Lanqlev et al.
(2009)
Mangrove/
marsh
ecotone
Addition:
1,400 kg
N/ha/yr
S dep = not
reported
N dep = not
reported
Mangrove leaf production
increased by 42% and
leaf biomass increased
by 72%.
Merritt Island
National Wildlife
Refuge, Florida
(Impoundment
T9)
Avicennia germinans
Simpson et al.
(2013)
Mangrove
Addition:
1,400 kg
N/ha/yr
S dep = not
reported
Fertilization increases
growth rate (shoot
elongation) by 290% in
the fringe zone and by
1,340% in the scrub
zone.
Indian River
Lagoon, Florida
(Impoundment
MI23)
Rhizophora mangle
Feller et al.
(2009)
N dep = not
reported
Mangrove
100 kg N/ha/yr
N addition increased the
number of new branches
150% in Avicennia.
Indian River
Lagoon, Florida
(Impoundment
SLC-24)
Avicennia germinans
and associated
sediments
Whiaham et
al. (2009)
Estuarine
tidal marsh
Addition:
670 kg N/ha/yr
S dep = not
reported
Typha spp. biomass
increased by 95%.
Nanticoke River,
Maryland and
Delaware
Plant community
Baldwin
(2013)
N dep = not
reported
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Table 11-5 (Continued): Nitrogen loading effects upon production and biomass.
Additions or
Type of
Load (kg
Biological and
Ecosystem
N/ha/yr)
Chemical Effects
Study Site
Study Species
Reference
Freshwater
50, 200, or
Community ANPP
Tchefuncte
Oligohaline plant
Graham and
estuarine
1,200 kg
increased with medium N
River,
community dominated
Mendelssohn
marsh
N/ha/yr as
load, ANPP = -0.00165
Madisonville,
by Sagittaria
(2010)
Nutralene
x (kg N/ha/yr)2 + 2.5091
Louisiana
lancifolia, Eleocharis
methylene
x (kg N/ha/yr) + 1270.3.
fall ax, and
urea
Polygonum
S dep = not
punctatum
reported
N dep = not
reported
Freshwater
500 kg N/ha/yr
N addition increased
Altamaha River,
Zizaniopsis miliacea
Frost et al.
tidal marsh
as NH4CI or
aboveground biomass by
Georgia
(2009)
urea
140% and plant height by
32% in Z. miliacea. N
addition decreased leaf
[N] by 99% and leaf [P]
by 25%.
Freshwater 500 kg N/ha/yr In Z. miliacea,
marsh
as NH4CI or
urea
N dep = not
reported
S dep = not
reported
aboveground biomass
increased by 2.9-3.8
times the control, as leaf
number increased 52%
and plant height
increased 25-40%.
Altamaha
Estuary, Georgia
Zizaniopsis miliacea, Ket et al.
Pontederia cordata,
and Sagittaria
land folia
(2011)
Ombrotrophic
peat bog
16 (low), 32
(medium), or
64 (high)
kg N/ha/yr as
N (NH4NO3) or
NPK(NH4N03
and KHPO4)
In high NPK, shrub
biomass increased, with
40% higher leaf biomass,
and 86% higher woody
biomass.
Mer Bleue Bog,
Ontario, Canada
Bog plant community:
dwarf shrub species
and mosses
Sphagnum
magellanicum,
Sphagnum
capillifolium, and
Polytricum strictum
Juutinen et al.
(2010)
Ombrotrophic
peat bog
Addition: 16 kg
N/ha/yr as
NH4NO3
N dep = 8 kg
N/ha/yr as
quantified by
Turunen et al.
(2004)
N addition decreased
aboveground moss
biomass by 30%.
Mer Bleue Bog,
Ontario, Canada
(measured 2007)
Bog plant community:
dwarf shrub species
and mosses
Sphagnum
magellanicum,
Sphagnum
capillifolium, and
Polytricum strictum
Xing et al.
(2011)
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Table 11-5 (Continued): Nitrogen loading effects upon production and biomass.
Type of
Ecosystem
Additions or
Load (kg
N/ha/yr)
Biological and
Chemical Effects
Study Site
Study Species
Reference
Rich fen and 60 kg N/ha/yr In Chamaedaphne
Gogebic County,
ombrotrophic as urea calyculata, fertilization Michigan
bog increased productivity by
S dep = not 87% and biomass by
reported 105%.
In Calamagrostis
N dep = not canadensis, biomass
reported increased 600% over
unamended fen plots.
Plant community
consisting of
Sphagnum spp.,
ericaceous shrubs,
dominant vascular
plants Carex
oligosperma and
Chamaedaphne
calyculata
Iversen et al.
(2010)
The entire plant
community responded to
N addition with increases
in productivity (82%) and
biomass (160%).
AG = aboveground; ANPP = aboveground net primary productivity; C02 = carbon dioxide; dep = deposition; ha = hectare;
kg = kilogram; N = nitrogen; NaN03 = sodium nitrate; NH4CI = ammonium chloride; NH4N03 = ammonium nitrate;
(NH4)2S04 = ammonium sulfate; S = sulfur; yr = year.
11.5 Plant Stoichiometry and Physiology
N addition alters the stoichiometry of plant tissue. When inorganic N stores increase in
the soil matrix due to N deposition, one of the first plant responses may be to increase N
uptake and the storage of N in plant tissues. As a result, the concentration of N in plant
tissue (often reported as [N] or %N) is one of the earliest indicators of changing
bioavailability of N within an ecosystem. Plants may store the additional N in proteins,
use it for further growth if other nutrients and abiotic conditions are not limiting, or
curtail growth of belowground, nutrient-acquiring roots. Plant tissue [N] also has
important implications for consumers, as many insect and vertebrate consumers
preferentially graze on high N tissues, and plant [N] can also affect decomposition rates.
In systems in which N availability increases while other nutrient cycles are unaltered,
such as nutrient-poor bogs, nutrient imbalances develop and plant [K] and [P] decline.
This section will consider the effects ofN deposition upon plant tissue [N] as a sensitive
indicator of plant response, as well as the effects of N deposition upon other elements in
plant tissue, which would indicate more detrimental effects of increased N availability
upon plant growth.
Plant stoichiometry theory considers the balance of multiple chemical elements in living
tissues. The stoichiometry of plant tissue is often connected to its physiological function.
Most new studies on physiology and stoichiometry are for bogs and freshwater marshes.
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There are a few studies on salt water marshes and fens. The new literature is summarized
in the following sections.
11.5.1 Salt Marsh
There are several studies on the effects of N addition on salt marsh plant stoichiometry.
In three California salt marshes, N addition at seven different levels (0, 100, 200, 400,
800, 1,600, and 3,200 kg N/ha/yr) showed that succulent forb Salicornia depressa
increased leaf %N in a saturating response, with no significant increases in response
above 800 kg N/ha/yr (Vivanco et al.. 2015). There are several N addition studies at
addition levels greater than 500 kg N/ha/yr I (Baldwin. 2013; Nelson and Zavaleta. 2012;
Rvan and Bover. 2012); see Table 11-61.
11.5.2 Mangrove
The N addition levels in all new studies on mangroves are generally higher (greater than
500 kg N/ha/yr) than would be relevant to the effects of N deposition. As perennial
plants, mangroves respond to increasing N loads by altering tissue storage of N as well as
by increasing productivity (Section 11.4.3). In salt-marsh mangrove ecotone, Avicennia
germinans seedlings responded to addition of 1,400 kg N/ha with 62% higher leaf tissue
%N, as well as increased N in belowground biomass (Simpson et al.. 2013). In more
mature mangrove ecosystems receiving higher N loads (11,200 kg N/yr per tree), N
addition decreased the efficiency with which Rhizophora mangle resorbed N from
senescing leaves by 7%, which resulted in 39% higher %N in senesced leaves than in
unfertilized trees (Feller etal.. 2009).
11.5.3 Freshwater Marsh
N addition is documented to alter plant stoichiometry and physiology in freshwater
marshes. This topic was not addressed in the 2008 ISA. There are five new studies
published since 2008.
In freshwater marsh mesocosms planted with wetland obligate graminoid Bolboschoenus
maritimus [cosmopolitan bulrush, multiple synonyms including Schoenoplectus
maritimus, listed as Special Concern by Connecticut and Rhode Island, and as
endangered by Illinois, New Jersey, and New York (USDA. 2015b)I N addition increased
N stored in plant tissues. Aboveground tissue %N increased 31-114% of %N in control
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plants with increasing N loads (32, 65, 108 kg N/ha/yr) added in fall 2009, and increased
33-67% with increasing N loads (59, 119, 198 kg N/ha/yr) added in the summer and fall
of 2010 (Dimuma and Walton. 2014). N addition also increased tissue N in belowground
tissues. In fall 2009, addition of 32 kg N/ha/yr did not affect BG %N, but addition of
65 kg N/ha/yr increased BG %N by 26%, and addition of 108 kg N/ha/yr increased BG
%N by 126% to 1.29% tissue N. In summer and fall 2010, addition of 119 and 198 kg
N/ha/yr increased BG %N 47% and 37%, with a tissue N value of 1.34 and 1.25% N,
respectively (Dimuma and Walton. 2014V
In tidal freshwater marshes of the Tchefuncte River, Louisiana, experimentally added N
loads of 50, 200, 1,200 kg N/ha/yr did not alter the relative dominance of Sagittaria
lancifolia, but did alter N storage in plant tissues. Plant tissue N (mg N/g leaf) increased
0.02 mg for every 10 kg N/ha/yr of N load, which shifted the N:P ratio, 0.04 N: 1 P
increase for every additional 10 kg N/ha/yr (Graham and Mendelssohn. 2010). N addition
also decreased the efficiency with which plants resorbed nutrients from senescing leaves
for use in future growth. N addition decreased N resorption efficiency (%) by 0.1% for
every additional 10 kg N/ha/yr, and decreased P resorption efficiency (%) by 0.09% for
every additional 10 kg N/ha/yr (Graham and Mendelssohn. 2010).
In marsh mesocosms at the Smithsonian Environmental Research Center (SERC), native
and introduced haplotypes of graminoid Phragmites australis were grown under a
factorial elevated CO2 and nitrogen addition experiment. The species Phragmites
australis includes haplotypes (genetic lineages) native to North America, as well as
invasive haplotypes capable of forming monocultures that exclude native plant species.
Nitrogen fertilization of 250 kg N/ha/yr increased the construction cost (grams of glucose
invested in synthesizing a gram ofbiomass) of leaves for the native F haplotype of P.
australis by 5% under ambient or elevated CO2 (Caplan et al.. 2014V Nitrogen addition
alone did not significantly alter construction costs of the invasive M haplotype [listed as a
noxious weed, banned invasive, or plant pest by Alabama, Connecticut, Massachusetts,
South Carolina, Vermont, and Washington (USDA. 2015b)l. but the combined N and
elevated [CO2] treatment increased leaf construction costs by 6% (Caplan et al.. 2014).
These results suggest that under current conditions, N enrichment favors the invasive
haplotype over the native haplotype and may facilitate invasion.
In tidal freshwater marshes in the Altamaha River Estuary, Georgia, N addition of 500 kg
N/ha/yr in the second year stimulated productivity (Section 11.4.2) to the extent of
diluting N and phosphorus (P) in plant tissues, decreasing leaf N (%) by 22% and
decreasing leaf P (jxg/g) by 25% (Frost et al.. 2009). In later years of the experiment, N
addition increased leaf N (%) above control plot leafN by 25-43% (Ret et al.. 2011). and
this altered leaf nutrient ratios, decreasing leaf C:N 18-28% and increasing leaf N:P
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25-61% over leaves from control plots. The increases in productivity combined with
alterations in leaf tissue nutrients altered total nutrient pools stored in aboveground
biomass, increasing total aboveground N by 236% and increasing total aboveground P by
169% (Ret et al.,2011).
11.5.4 Riparian Wetland
In developing riparian forests at Bonanza Forest LTER, Alaska, N addition of 100 kg
N/ha/yr increased leafN 10% in tree species Alnus tenuifolia growing in late successional
riparian forest, but not in recently colonized or mid-successional sand bars (Ruess et al..
2013). N addition also altered A tenuifolia's internal P cycling efficiency, decreasing
resorption of P from senescing leaves by 21% in mid-successional forest (Ruess et al..
2013).
11.5.5 Bog and Fen
Research conducted in European fens and reviewed in the 2008 ISA has shown that N
addition favors the growth of grass and sedge species over peat-forming moss species
(U.S. EPA. 2008a). New research suggests that North American sedge and grass species
experience positive effects of N loading, and that their responses can alter N dynamics of
North American bogs and fens. In a bog in Gogebic County, Michigan, where sedge
Carex oligosperma [listed as Special Concern in Connecticut, threatened in Ohio and
Pennsylvania, and endangered in Illinois, Massachusetts, and North Carolina, (USDA.
2015b)] was dominant in the plant community, the obligate wetland species responded to
60 kg N/ha/yr addition by decreasing N use efficiency by 89% and N response efficiency
by 84% (Tversen et al.. 2010). The response of the sedge altered ecosystem responses in
the bog, increasing plant community N uptake by 125% over uptake in unamended plots
(Tversen et al.. 2010). This increased N stored in biomass pools 171% above biomass N in
control plots, and increased the concentration of N in vascular plant tissues by 19%
(Iversen et al.. 2010). Similarly, the grass Calamagrostis canadensis [classified as
wetland facultative or obligate in different U.S. regions by (USDA. 2015b) I which was
dominant in a closely adjacent rich fen, responded to N addition of 60 kg N/ha/yr by
increasing N uptake. Along with increased productivity (Section 11.4.5). this response
expanded the total pool of N stored in biomass by 300% (Iversen et al.. 2010).
In the same set of experiments in Gogebic County, Michigan, woody plants increased
their productivity in response to N loading, but their efficiency in using N declined,
suggesting a mechanism by which N loading lowers N retention of bogs and fens
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(Section 11.3.1.5). The wetland obligate shrub Chamaedaphne calyculata (threatened in
Illinois and Maryland) responded to 60 kg N/ha/yr addition by increasing plant N uptake
by 75%, which increased productivity (Section 11.4) and increased the pool of N stored
in aboveground biomass by 100%. However, nitrogen addition decreased the efficiency
of photosynthesis and metabolism in C. calyculata, as N use efficiency was 81% lower
and N response efficiency was 91% lower in fertilized plots (Iversen et al.. 2010). In an
intermediate fen, tree species A Inns incana ssp. rugosa, speckled alder [hereafter referred
to as A. rugosa, endangered in Illinois, (USDA. 2015b)l. responded to an added 60 kg
N/ha/yr with a 45% decline in N response efficiency [net primary productivity relative to
available soil N (Iversen et al.. 2010)1.
A long-term fertilization experiment at the Mer Bleue Bog in Ontario, Canada, has
documented the effect of more than a decade of elevated N inputs on the same species in
an ombrotrophic peat bog. Chamaedaphne calyculata responded to 32 g N/ha/yr by
increasing P resorption by 42%, and responded to 64 kg N/ha/yr by increasing P
resorption by 33% (Wang et al. 2014b). In year 6, 64 kg N/ha/yr decreased leaf calcium
22% (Wang et al.. 2014b). and in year 9, leaf Ca was 34% lower in C. calyculata from
plots that received 16 kg N/ha/yr than in leaves from control plots (Bubier et al.. 2011).
After 9 years of N addition at Mer Bleue, leaf C:N ratios were 15% lower in C.
calyculata leaves that received 16 kg N/ha/yr than in leaves from control plots, with
dependent increases in leaf alanine and y-aminobutyric acid (GABA; see Table 11-6 for
equations), amino acid pools which indicate N saturation in the plant (Bubier et al..
2011). Leaf aluminum concentrations were 44% lower in these leaves than in leaves from
control plots (Bubier et al.. 2011). In plots that received 64 kg N/ha, there was no change
in leaf C:N, but there were increases in proteins indicative of increased plant N uptake. C.
calyculata leaf total chlorophyll was 84% higher than in control leaves, and there were
115% increases in leaf alanine and 94% increases in leaf GABA, indicating N saturation.
Leaf manganese was 45% lower in these leaves than in control plot C. calyculata,
indicating that shrub productivity may be limited by micronutrients in a N fertilized bog
(Bubier et al.. 2011).
At Mer Bleue, the wetland obligate shrub Rhododendron groenlandicum (synonym:
Ledum groenlandicum, rare in Pennsylvania, threatened in Connecticut, and endangered
in Ohio) responded to 4 years of 64 kg N/ha/yr with a 16% increase in leaf N and a
dependent increase in leaf glutamic acid (Bubier etal.. 2011). Leaf P declined by 54% of
control leaf P after 4 years of 64 kg N/ha/yr (Bubier etal.. 2011). After 7 years of 64 kg
N/ha/yr R. groenlandicum responded with a 23% decrease in leaf magnesium (Mg) and
186% decrease in Mg resorption from senescing leaves (Wang et al.. 2014b). indicating
increasing limitation by magnesium which could negatively affect photosynthesis and
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enzyme activity within the plant. After 7 years of 32 and 64 kg N/ha/yr addition, R.
groenlandicum increased P and K resorption from senescing leaves; P resorption
increased 12-12.2 times the rate of resorption in leaves from unamended plots, and
increased K resorption by 92-123% (Wang etal.. 2014bV
In the same experiment, after 7 years, N addition shifted the seasonality of gross
photosynthesis, with 64 kg N/ha/yr reducing C uptake 29-45% of control rates in early
summer (May-July), and increasing C uptake 25% above rates in control plots in
September (Larmola et al.. 2013). After 9 years of 16 kg N/ha/yr addition R.
groenlandicum exhibited altered leaf physiology, doubling maximum carboxylation
capacity (Vcmax) on a per-leaf-mass basis (Bubieret al.. 2011). There was no significant
effect of 4 years of 64 kg N/ha/yr upon Vcmax measured during the same growing season
(2008). The study authors posited that plants responded to this level of N availability with
a stress response, allocating N to storage in glutamic acid (nmol glutamic acid/g
leaf = 37.914 + 252.2 x leaf %N) instead of using it in photosynthetic enzymes (Bubieret
al.. 201 1).
At Mer Bleue, the wetland facultative shrub Vaccinium myrtilloides (designated sensitive
in Washington, special concern in Connecticut, threatened in Ohio and Iowa, and
endangered in Indiana) responded to nitrogen addition with declines in other leaf
nutrients. Leaf calcium declined 23% in response to 9 years of 16 kg N/ha/yr and
declined 56% in response to 4 years of 64 kg N/ha/yr (Bubier et al.. 2011). indicating that
increasing N will increasingly limit leaf Ca and by extension decrease signaling and
structural integrity of plant tissues. Leaf P decreased by 55% after 9 years of 16 kg
N/ha/yr and by 68% after 4 years of 64 kg N/ha/yr. Leaf manganese (Mn) decreased 57%
under 64 kg N/ha/yr (Bubier et al.. 2011). which could affect photosynthesis or N
assimilation because Mn is a component of enzymes involved in these processes. V.
myrtilloides leaf potassium also declined: 47% in response to 9 years of 16 kg N/ha/yr
and 34% in response to 4 years of 64 kg N/ha/yr (Bubier et al.. 2011). Leaf potassium
regulates stomatal movement, activates enzymes, and balances electrical charges
associated with ATP production, so K deficiency can decrease photosynthesis and slow
growth. Leaf aluminum decreased 45% of control leaf aluminum concentrations in plots
receiving 64 kg N/ha/yr for 4 years (Bubier et al.. 2011).
The wetland obligate pitcher plants have previously been shown to experience
detrimental impacts ofN deposition at physiological and population levels KGotelli and
Ellison. 2002) in 2008 ISA], Bott et al. (2008) reciprocally transplanted Sarracenia
purpurea ssp. purpurea [listed as exploitably vulnerable in New York, threatened in New
York, and endangered in Georgia and Illinois (USDA. 2015b)1 between ombrotrophic
Sapa bog and the rich Cedarburg fen, both in Wisconsin. Leaf %N was positively and
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linearly correlated with surface water NO, concentration at the site where the plants
were transplanted (Leaf %N = 0.9581 + 0.1667 x |iM NO3 ). confirming Gotelli's
designation of pitcher plants as sensitive indicators of N deposition (Bott et al.. 2008).
Fritz et al. (2014) performed a peat mesocosm study to test how a history of atmospheric
N deposition alters the N uptake rates of Sphagnum magellanicum, a widely distributed
peat-forming species. The researchers collected blocks of living S. magellanicum from a
pristine bog in Argentina which received an annual load of 1-2 kg N/ha/yr, and also from
a polluted bog in the Netherlands which received an annual load of 20-30 kg N/ha/yr.
Under controlled conditions, nitrogen solutions of 1, 10, or 100 (j,mol N/L were added to
the block. Rates of N uptake were significantly different among bog samples (Argentine
or Dutch) for the 10 or 100 |imol solutions, with the pristine (Argentine) Sphagnum
absorbing nitrogen at 1.4-2.6 times the rate of the uptake rate of the Dutch bog, which
receives a higher annual N load (Fritz et al.. 2014).
11.5.6 Summary Table
Table 11-6 Nitrogen loading effects upon plant stoichiometry and physiology.
Additions or
Type of Load (kg
Ecosystem N/ha/yr)
Biological and Chemical
Effects
Study Site Study Species Reference
Coastal salt
marsh
Addition: 100, Salicornia leaf %N increases
200, 400, 800, in a saturating response to N
1,600,3,200 kg Leaf N=-0.73 x
N/ha/yr as urea g(-o.o24g N/m2/yr) + 2 99
N dep = 3-5 kg
N/ha/yr as
reported in
Tonnesen et al.
(2007)
Morro Bay Salicornia Vivanco et
National depressa al. (2015)
Estuary, Standi.
Carpinteria (Salicornia
Salt Marsh virginica) stands
Reserve,
Tijuana River
Reserve
Estuary,
California
Coastal salt
marsh
3,000 kg
N/ha/yr as
NH3NO3
Plant [N] increased by 224%
and 33%, and N pools in AG
vegetation increased by 60%
and 84% in successive
Slough, pacifica Zavaleta
Monterey Bay, dominant, (2012)
California Distichlis
Elkhorn Sarcocornia Nelson and
N dep = not
reported
S dep = not
reported
summers.
spicata,
Frankenia
salina, and
Jaumea
carnosa
February 2017
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Table 11-6 (Continued): Nitrogen loading effects upon plant stoichiometry and
physiology.
Type of
Ecosystem
Additions or
Load (kg
N/ha/yr)
Biological and Chemical
Effects
Study Site Study Species Reference
Estuarine salt
marsh
1,337 kg
In S. pacifica, tissue N
China Camp Sarcocornia
N/ha/yr as urea increased 28-46%. D. spicata State Park,
N dep = not tissue N increased 19%. J. California
reported
S dep = not
reported
carnosa tissue N increased by
54%.
pacifica
dominant,
Distichlis
spicata, and
Jaumea
carnosa
Ryan and
Bover (2012)
Mangrove/ salt
marsh ecotone
1,400 kg
N/ha/yr
N dep = not
reported
S dep = not
reported
Mangrove leaf production Merritt Island
increased by 42%. Leaf tissue National
%N increased 62%. Root %N Wildlife
increased 9% and root C:N Refuge,
decreased 25%. Florida
Avicennia
germinans
Simpson et
al. (2013)
Mangroves
No areal rate
reported;
11,200 kg N/yr
per tree
N dep = not
reported
S dep = not
reported
Fertilization increases growth
rate (shoot elongation) by
290% in the fringe zone and
by 1,340% in the scrub zone.
In the fringe zone, fertilization
decreases resorption
efficiency of N from dying
leaves by 7%, resulting in
senesced leaves containing
39% more N than control
senesced leaves.
Indian River
Lagoon,
Florida
Rhizophora
mangle
Feller et al.
(2009)
Freshwater
marsh
Fall 2009: 32
(low), 65
(medium), 108
(high) kg
N/ha/yr as
(NH4)2S04;
summer 2010:
59 (low), 119
(medium), or
198 (high) kg
N/ha/yr as
(NH4)2S04
N addition increased S.
maritimus %N of aboveground
tissue 31-114% in 2009 and
33-67% in 2010. N addition
(medium, high) increased S.
maritimus %N of belowground
tissue 26-126% in 2009 and
37-47% in 2010.
Mesocosms at
UC Riverside
research
station,
California
Schoenopiectus
maritimus,
Cuiex tarsaiis,
and Anopheles
hermsi
Duauma and
Walton
(2014)
N dep = not
reported
S dep = not
reported
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Table 11-6 (Continued): Nitrogen loading effects upon plant stoichiometry and
physiology.
Type of
Ecosystem
Additions or
Load (kg
N/ha/yr)
Biological and Chemical
Effects
Study Site Study Species Reference
Freshwater tidal 250 g N/ha/yr
marsh (growth as NH4CI
chamber) solution
N dep = not
reported
S dep = not
reported
Nitrogen increases
construction cost of leaves by
5% in native Phragmites.
Nitrogen under elevated [CO2]
increases construction costs
by 6% in invasive Phragmites.
Mesocosms at
Smithsonian
Environmental
Research
Center,
Maryland
Phragmites Caplan et al.
australis (native (2014)
F haplotype and
invasive M
haplotype)
Freshwater tidal 500 kg N/ha/yr
marsh as NH4CI or
urea
N addition decreased leaf [N]
by 99% and leaf [P] by 25%.
Altamaha Zizaniopsis Frost et al.
River, Georgia miliacea (2009)
Freshwater
marsh
500 kg N/ha/yr
as NH4CI or
urea
N dep = not
reported
S dep = not
reported
In Z. miliacea, leaf %N
increased 25-43% so that leaf
C:N decreased 18-28% and
leaf N:P increased 25-61%.
Total N and total P in
aboveground pools increased
236% and 169%, respectively.
Altamaha
Estuary,
Georgia
Zizaniopsis
miliacea,
Pontederia
cord at a, and
Sagittaria
land folia
Ket et al.
(2011)
Freshwater tidal
marsh
50, 200, or
1,200 kg
N/ha/yr as
Nutralene
methylene urea
N dep = not
reported
S dep = not
reported
In S. lancifolia, N addition
increased plant tissue [N],
[N] = 0.00226 x (kg
N/ha/yr) + 23.271; and N:P
ratio, N:P = 0.00404 x (kg
N/ha/yr) + 16.853.
In S. lancifolia, resorption
efficiencies declined with
increasing N addition, for
nitrogen: NRE = -0.01048 x
(kg N/ha/yr) + 31.796, for
phosphorus: PRE = -0.00915
x (kg N/ha/yr) + 62.778.
Tchefuncte
River,
Madisonville,
Louisiana
Oligohaline
plant
community
dominated by
Sagittaria
lancifolia,
Eleocharis
fall ax, and
Polygonum
punctatum
Graham and
Mendelssohn
(2010)
Freshwater tidal
marsh
Addition
N/ha/yr
S dep = not
reported
N dep = not
reported
670 kg
Foliar N increased in A.
calamus (by 23%) and Typha
spp. (by 47%).
Nanticoke
River,
Maryland and
Delaware
Plant
community
Baldwin
(2013)
Riparian
100 kg N/ha/yr
Specific leaf mass decreased
Bonanza
Alnus incana
Ruess et al.
floodplain
N dep = not
reported
by 12% and 11% in early and
Forest LTER,
ssp. tenuifolia
(2013)
successional
late successional forest. Leaf
Alaska
(or A. tenuifolia)
forest
N increased 10% in late
and associated
S dep = not
reported
successional forest. Leaf P
Frankia strains
resorption decreased 21%.
February 2017
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Table 11-6 (Continued): Nitrogen loading effects upon plant stoichiometry and
physiology.
Type of
Ecosystem
Additions or
Load (kg
N/ha/yr)
Biological and Chemical
Effects
Study Site Study Species Reference
Ombrotrophic
peat bog
16 (low), 32
(medium), or 64
(high)
kg N/ha/yr as N
(NH4NO3) or
NPK(NH4N03
and KHPO4)
N dep = 8 kg
N/ha/yr
S dep = not
reported
In R. groenlandicum, leaf %N
increased by 25% (low N) and
16% (high N), and leaf C:N
ratios decreased by 19% (low
N) and 15% (high N). Leaf P
declined by 54% (high N). In
low N addition, R.
groenlandicum V cmax increased
by 76% on a per-area basis or
doubled on a per-mass basis.
In C. calyculata, leaf C:N ratios
decreased by 15% (low N) and
33% (high N), and total
chlorophyll increased by 84%
(high N), just as
concentrations of leaf alanine
increased 115% (high N) and
GABA increased 94% (high
N). Leaf Ca declined 34% (low
N) and 17% (high N), leaf Mn
declined 45% (high N), and
leaf Al declined 44% (low N).
In V. myrtilloides, leaf Ca
declined 23% (low N) and 56%
(high N), leaf P declined by
55% (low N) and 68% (high
N), leaf Mn declined 57%, leaf
K declined 47% (low N) and
34% (high N), and leaf Al
declined 45% (high N). Amino
acid leaf concentrations
(nmol/g) increased with leaf
%N: in R. groenlandicum,
glutamic acid increased
y = 252.2x+ 37.914; in C.
calyculata, alanine increased
y = 221.07*- 52.931, and
GABA increased
y = 276.82x-98.682.
Mer Bleue
Bog, Ontario,
Canada
Three
ericaceous
shrubs:
Vaccinium
myrtilloides,
Rhododendron
groenlandicum
(formerly
Ledum
groenlandicum),
and
Chamaedaphne
calyculata
Bubier et al.
(2011)
Ombrotrophic
peat bog
16 (low), 32
Under high N, gross PSN
Mer Bleue
Shrub species
(medium), or 64
declined 29-45% in May-July,
Bog, Ontario,
(Vaccinium
(high) kg
but increased 25% in Sept.
Canada
myrtilloides,
N/ha/yr as N
Ledum
(NH4NO3) or
groenlandicum,
NPK(NH4N03
Chamaedaphne
and KHPO4)
calyculata) and
mosses
(Sphagnum
magellanicum,
Sphagnum
capillifolium,
Polytricum
strictum)
Larmola et
al. (2013)
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Table 11-6 (Continued): Nitrogen loading effects upon plant stoichiometry and
physiology.
Type of
Ecosystem
Additions or
Load (kg
N/ha/yr)
Biological and Chemical
Effects
Study Site Study Species Reference
Ombrotrophic
peat bog
16 (low), 32
(medium), or 64
(high) kg
N/ha/yr as N
(NH4NO3) or
NPK(NH4N03
and KHPO4)
N dep = 5-6 kg
N/ha/yr
S dep = not
reported
High N decreased leaf Ca
(mg/cm2) by 22% in C.
calyculata and decreased leaf
Mg (mg/cm2) by 23% in R.
groenlandicum. In C.
calyculata, medium N
increased P resorption by 42%
as high N increased it by 33%.
In R. groenlandicum, N
addition (medium N, high N)
increased P resorption by
12-12.2 times, and increased
K resorption by 92-123%.
High N decreased Mg
resorption 186% in R.
groenlandicum.
Mer Bleue
Bog, Ontario,
Canada
Chamaedaphne
calyculata and
Rhododendron
groenlandicum
(formerly
Ledum
groenlandicum)
Wang et al.
(2014b)
Rich fen and
No addition
Leaf % N was positively
Cedarburg fen
Sarracenia Bott et al.
ombrotrophic
N dep = not
reported
correlated with surface water
and Sapa bog,
purpurea subsp. (2008)
bog
NO3" concentration
Wisconsin
Purpurea
(y= 0.1667X+ 0.9581)
S dep = not
reported
Bog
Laboratory
incubation.
Moss from
Argentina
(54.75°S,
68.33°W) and
Netherlands
(52.82°N,
2.42°E)
N uptake of 10 and 100 pmol
N/L solutions was 40-160%
more rapid by Sphagnum from
the pristine (Argentinian) bog
than the Dutch bog.
Laboratory
incubation of
moss from
pristine site in
Argentina and
N polluted site
in Netherlands
Sphagnum
magellanicum
Fritz et al.
(2014)
Pristine site
(Argentina): 1-2
kg N/ha/yr, N
polluted site
(Netherlands):
20-30 kg
N/ha/yr
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Table 11-6 (Continued): Nitrogen loading effects upon plant stoichiometry and
physiology.
Type of
Ecosystem
Additions or
Load (kg
N/ha/yr)
Biological and Chemical
Effects
Study Site Study Species Reference
Ombrotrophic 60 kg N/ha/yr In Chamaedaphne calyculata,
bog as urea fertilization increases plant N
uptake by 75%, N stored in
S dep = not biomass by 100%, productivity
reported by 87%.
Fertilization decreases C.
N dep = not calyculata N use efficiency by
reported g-|o/0 anc| ^ response
efficiency by 91%.
In Carex oligosperma,
fertilization decreases N use
efficiency by 89% and N
response efficiency by 84%.
The entire plant community
responded to N addition with
increases in N uptake (125%),
N stored in biomass (171%),
productivity (82%), and [N] in
new tissue (19%).
Gogebic
County,
Michigan
Plant
community
consisting of
Sphagnum
spp.,
ericaceous
shrubs,
dominant
vascular plants
Carex
oligosperma
and
Chamaedaphne
calyculata
Iversen et al.
(2010)
Fen
60 g N/ha/yr as In A. rugosa, fertilization
urea decreases N response
N dep = not efficiency by 45%.
reported
S dep = not
reported
Gogebic
County,
Michigan
Dominant
vascular plants
Calamagrostis
canadensis and
Alnus rugosa
Iversen et al.
(2010)
AG = aboveground; Al = aluminum; ANPP=aboveground net primary productivity; C = carbon; Ca = calcium; cm = centimeter;
C02 = carbon dioxide; dep = deposition; GABA = gamma-Aminobutyric acid; ha = hectare; K = potassium; kg = kilogram;
KHP04 = potassium phosphate; L = liter; LTER = Long Term Ecological Research; |jmol = micromole; mg = milligram;
Mn = manganese; N = nitrogen: NH4CI = ammonium chloride; NH4NO3 = ammonium nitrate; (NH4)2S04 = ammonium sulfate;
N03" = nitrate; NPK= nitrogen, phosphorus, potassium; NRE = nitrogen resorption efficiency; P = phosphorus; PRE = phosphorus
resorption efficiency; S = sulfur; yr = year.
11.6 Plant Architecture
1 Plant architecture (plant height, branching) in wetlands is an important endpoint because
2 the architecture of the dominant plants determines the availability of nesting habitats or
3 refugia from flooding and predators. Plant architecture is defined as the
4 three-dimensional organization of the plant body. For the parts of the plant that are
5 aboveground, this includes the branching pattern, as well as the size, shape, and position
6 of leaves and flower organs (Table 11-7). The 2008 ISA did not have sufficient data on N
7 addition effects on wetland plant architecture to consider plant architecture as a specific
8 endpoint.
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11.6.1
Salt Marsh
There are several new studies on salt marsh plant architecture. Darbv and Turner (2008)
report that for Spartina alterniflora, stem height increased linearly with N load starting at
230 kg N/ha/yr, although regression equations were not included. Stem density was
significantly higher than in unamended plots only for the highest N load, 3,720 kg
N/ha/yr, which increased stem density by 43%. There are two other addition studies with
N addition rates above 500 kg N/ha/yr evaluated effects in U.S. salt marshes (Ryan and
Bover. 2012; Davev et al.. 2011).
11.6.2 Mangrove
In Florida mangroves, Whigham et al. (2009) added 100 kg N/ha/yr to plots of dwarf
Avicennia germinans, black mangrove, which increased the number of new branches
produced 150% above control plots.
11.6.3 Freshwater Tidal Marsh
There are several new studies on freshwater tidal wetlands. In freshwater tidal marshes of
Altamaha River Estuary, Georgia, N addition (500 kg N/ha/yr) increased the number of
leaves per m2 52% and increasing plant height by 25-40% over the course of the 5-year
experiment (Ket et al.. 2011). Duguma and Walton (2014) constructed freshwater
wetland mesocosms at UC Riverside, planting Bolboschoenus maritimus (formerly
Schoenoplectus maritimus), alkali bulrush, and monitoring plant responses as well as use
of mesocosms by mosquito species (Section 11.8.3). N addition of 32 kg N/ha/yr
increased plant height 23% with no effect upon plant height when 65 or 108 kg N/ha/yr
were added in 2009. However, in 2010 when the experiment was initiated earlier in the
year (5 August start date in 2009, 22 March start date in 2010), all N addition levels (59,
119, 198 kg N/ha/yr) increased plant height 28-44% above control plants (Duguma and
Walton. 2014).
11.6.4 Riparian Wetland
In developing riparian forests at Bonanza Forest LTER, AK, N addition of
100 kg N/ha/yr altered leaf structure of the tree species Alnus incana ssp. tenuifolia
[hereafter A. tenuifolia (Ruess et al.. 2013)1. In the mostly recently colonized sand bars,
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N addition decreased specific leaf mass (SLM) of A tenuifolia 12%, and in
mid-successional riparian forest SLM decreased 11% with N addition.
11.6.5 Summary Table
Table 11-7 Nitrogen loading effects upon architecture.
Type of Additions or Load
Ecosystem (kg N/ha/yr)
Biological and
Chemical Effects
Study Site Study Species
Reference
Coastal salt 4,200 kg N/ha/yr as N addition increased Goat Island,
marsh
NH4NO3
S dep = not
reported
N dep = not
reported
rhizome diameter by 1%
in shallow and 5% in
deep (10-20 cm)
sediments.
South
Carolina
Spartina
alterniflora
Davev et al. (2011)
Coastal salt
marsh
230, 465, 930,
1,860, or 3,720 kg
N/ha/yr as
(NH4)2S04
S dep = not
reported
N dep = not
reported
Stem density and stem
height increased linearly
with N load (regressions
not given). Stem
densities increased
43% in response to
3,720 kg N.
LUMCON,
Cocodrie,
Louisiana
Spartina
alterniflora
Darby and Turner
(2008)
Estuarine
marsh
Addition: 1,337 kg
N/ha/yr as urea.
S dep = not
reported
N dep = not
reported
In S. pacifica, height China Camp Sarcocornia Ryan and Bover
increased 207%,
number of branches
increased 135-283%. J.
carnosa height
increased 504%.
State Park,
California
pacifica
dominant (C3
succulent
shrub),
Distichlis
spicata (C4
grass), and
Jaumea
carnosa (C3
semisucculent
forb)
(2012)
Mangrove 100 kg N/ha/yr
N addition increased the
number of new
branches 150% in
Avicennia.
Indian River
Lagoon,
Florida
(Impoundment
SLC-24)
Avicennia
germinans and
associated
sediments
Whiqham et al.
(2009)
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Table 11-7 (Continued): Nitrogen loading effects upon architecture.
Type of
Ecosystem
Additions or Load
(kg N/ha/yr)
Biological and
Chemical Effects
Study Site Study Species
Reference
Freshwater
marsh
Fall 2009: 32 (low),
65 (medium), 108
(high) kg N/ha/yr
as (NH4)2S04;
Summer 2010: 59
(low), 119
(medium), or 198
(high) kg N/ha/yr
as (NH4)2S04
N dep = not
reported
S dep = not
reported
N addition increased S.
maritimus height 23% in
2009 (low N), and
28-44% in 2010.
Mesocosms at Schoenoplectus Duauma and
UC Riverside
research
station,
California
maritimus,
Culex tarsalis,
and Anopheles
hermsi
Walton (2014)
Tidal
500 kg N/ha/yr as
In Z. miliacea, leaf
Altamaha
Zizaniopsis
Ket et al. (2011)
freshwater
NH4CI or urea
number increased 52%
Estuary,
miliacea,
marsh
and plant height
increased 25-40%.
Georgia
Pontederia
cordata, and
Sagittaria
lancifolia
Riparian
100 kg N/ha/yr
Specific leaf mass
Bonanza
Alnus incana
Ruess et al. (2013)
floodplain
N dep = not
reported
S dep = not
reported
decreased by 12% and
Forest LTER,
ssp. tenuifolia
successional
11% in early and late
Alaska
and associated
forest
successional forest.
Frankia strains
Ombrotrophic
peat bog
16 (low), 32
(medium), or 64
(high) kg N/ha/yr
as N (NH4NO3) or
NPK (NH4NO3 and
KHPO4)
S dep = not
reported
N dep = 8 kg
N/ha/yr
In medium and high
NPK treatments, shrub
canopies grew 72% and
82% taller than controls.
There were no
significant effects of
medium or high N on
shrub canopies.
Mer Bleue
Bog, Ontario,
Canada
Bog plant
community:
dwarf shrub
species and
mosses
Sphagnum
magellanicum,
Sphagnum
capillifolium,
and Polytricum
strictum
Juutinen et al.
(2010)
AG = aboveground; ha = hectare; kg = kilogram; KHP04 = potasium phosphate; LTER = Long Term Ecological Research;
LUMCON = Louisiana Universities Marine Consortium; N = nitrogen; NH4CI = ammonium chloride; NH4NO3 = ammonium nitrate;
(NH4)2S04 = ammonium sulfate; P = phosphorus; S = sulfur; yr = year.
11.7 Demography
Plant demography is the change in plant population size and structure through time.
Changes to plant demography will determine the long-term stability of wetlands.
Information on the effect of N loading on wetland plant demography, including
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establishment, survival, and reproduction is sparse. Evidence from salt marsh ecosystems
shows mixed responses to N loading: two pre-2008 studies found negative effects of N
addition upon reproduction in invasive Spartina foliosa and Spartina hybrids (Tvler et al..
2007). and a positive effect upon reproduction of native Salicornia bigloveii (Bover and
Zedler. 1999). Work reviewed in the 2008 ISA on Sarraceniapurpurea, or northern
pitcher plant, found that increases in N deposition also increased population extinction
risk (Gotelli and Ellison. 2006. 2002). and serves as the scientific basis for the wetland
critical load values (Section 11.9). The sections below describe two new studies which
find negative impacts of high N upon the demography of wetland plants.
11.7.1 Mangrove
Lovelock et al. (2009) considered a global data set of mangrove responses to N
fertilization experiments conducted for 3-12 years. N addition (900-2,700 kg N/tree/y)
decreased survival probability by 10%, with trees growing on the land side in hypersaline
conditions particularly vulnerable when rainfall was low.
11.7.2 Riparian Wetland
The Great Salt Lake is an inland salt lake ecosystem that provides an important food
source for migrating bird species as well as an economically important fishing industry
by providing habitat for Artemia franciscana, brine shrimp. Carling et al. (2013) studied
impounded and floodplain wetlands along the rivers that feed into the GSL, and found
that increasing nitrate and nitrite concentrations in water flowing through the wetlands
decreased reproduction of the submerged aquatic plants Ruppia cirrhosa and Stuckenia
spp. (equations in Table 11-8).
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11.7.3 Summary Table
Table 11-8
Nitrogen loading effects upon demography.
Type of
Additions or
Biological and Chemical
Study
Study
Ecosystem
Load (kg N/ha/yr)
Effects
Site
Species
Reference
Mangrove
No areal rate
Mangrove survival probability
12 global
Mangrove
Lovelock et al.
given; 900 kg/yrto
decreased 10% with N addition.
sites,
species
(2009)
2,700 kg N/yr per
including
tree as urea
Indian
River
Lagoon,
Florida
Riparian
Not reported
Reproduction declines with
Great
Submerged
Carlina et al. (2013)
wetlands
increasing surface water nitrate
Salt
aquatic
and
(g/m2 drupelets = -4.15 ln[mg/L
Lake,
vegetation:
Floodplain
N03] + 4.03, R2 = 0.51) and
Utah
Ruppia
wetlands
increasing surface water NO2"
cirrhosa and
(g/m2 drupelets = -13.43 ln[mg/L
Stuckenia
NO2-] - 25.27, R2 = 0.54)
spp.
concentrations.
AG = aboveground; g = gram; ha = hectare; kg = kilogram; L = liter; LTER = Long Term Ecological Research; m = meter;
mg = milligram; N = nitrogen; NH3N03 = ammonium nitrate; N02" = nitrite; N03" = nitrate; P = phosphorus; S = sulfur; yr = year.
11.8 Biodiversity/Community
High biodiversity is a characteristic of wetlands. Fluctuating water levels in open systems
such as riparian strips and tidal marshes create zones with distinct abiotic characteristics
and multiple niches for microbes, plants, and animals with different biotic and abiotic
requirements. More closed systems such as bogs and fens, nutrient-poor, high-organic
acid ecosystems are uniquely adapted and rare plant communities including carnivorous
plants, ericaceous plants, and bryophytes characterized by low growth rates. Most
wetlands contain communities with a balance of species, and one result of eutrophication
is to shift the composition and relative abundance of species so that nitrogen-tolerant
species become more common as species adapted to low nitrogen availability become
less common or disappear from the system. Thus, plant cover (% of the total wetland area
occupied by a particular species) is an important metric of biodiversity. Similarly,
communities of aquatic producers contain both nitrogen-tolerant and
low-nitrogen-adapted species, and changes in phytoplankton species composition
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represents a change in biodiversity important for dependent food webs. Changes in the
abundance of herbivorous, omnivorous, or predatory invertebrates are indicative of
alterations to trophic interactions and effects which could cascade up the food web
towards economically or culturally important fish, bird, and mammal species.
The 2008 ISA found that the evidence was sufficient to infer a causal relationship
between N deposition and the alteration of species richness, species composition, and
biodiversity in wetland ecosystems. The 2008 ISA noted there are 4,200 native plant
species in U.S. wetlands, 121 of which are federally endangered. Wetlands provide
habitat to a disproportionally high number of rare plants given their relative area; for
example, fens occupy 0.01% of the land area of northeast Iowa, yet contain 17% of the
endangered, threatened, or listed species of concern in the area. Wetland species have
evolved under N limited conditions, including endangered species in the Isoetes (three
endangered species) and Sphagnum (15 endangered species) genera, as well as the
endangered insectivorous plants Sarracenia oreophila and Drosera rotundifolia.
In the 2008 ISA, evidence from Canadian and European peatlands showed that N
deposition had negative effects on Sphagnum bulk density and mixed effects on
Sphagnum productivity, depending on history of deposition. In Canadian ombrotrophic
peatlands experiencing deposition of 2.7-8.1 kg N/ha/yr, peat accumulation increased
with N deposition, but accumulation rates had slowed by 2004, indicating a degree of N
saturation. Sarracenia oreophila responded to N deposition with changes in morphology
and projected population extinction under N deposition levels of 4.5-6.8 kg N/ha/yr.
There was only one study on N enrichment in riparian systems at the time of the 2008
ISA, and N levels were meant to mimic wastewater effluent, not the lower amounts of N
typical of atmospheric deposition. Coastal wetlands responded to N enrichment with
increased primary production, shifting microbial and plant communities and altering pore
water chemistry, although many of the studies in coastal wetlands used N enrichment
levels more similar to wastewater than atmospheric deposition.
11.8.1 Plants
11.8.1.1 Salt Marsh
Nitrogen was an important factor driving plant diversity in a study on the Patuxent River,
where marsh soil NO3 -N and pore water salinity best explained the variation in plant
species richness out of all factors considered, with NO3 -N accounting for 26% of the
variation in the richness of all species. Presence-absence data for all species were used to
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determine the geographic range for each species, and the 50% of species per river with
the smallest range was designated as a "restricted-range" subset. On the Patuxent River,
the best model of variation in species richness of restricted range species contained only
soil NOs -N as an explanatory variable, with a positive relationship between NO.? -N and
species richness [see Table 11-9; (Sharpe and Baldwin. 2013)1.
Several new field addition studies further confirm N addition alters plant community
composition in salt marshes. In Kirkpatrick Marsh, Maryland, a limited plant community
allowed researchers to measure the biomass of plots as a proxy for plant cover. C4 plants
Spartina patens and Distichlis spicata plot cover increased over the course of the 4-year
fertilization experiment so that C4 biomass was 129% higher in the fourth year than in
the first year of receiving 250 kg N/ha/yr, while C4 biomass in the control plots remained
unchanged over 4 years. The C3 plant species Schoenoplectus americanus declined in
biomass in the control plots by 8-22% of that produced in the first year, but decreased to
a greater extent in N addition plots, declining after 4 years by 52% compared to the first
year plot biomass (Langlev and Megonigal. 2010). Langlev and Megonigal (2010)
suggest that the effects of N upon community composition (decline in C3 plants,
increased C4 biomass) will prevent the plant community from increasing productivity in
response to increased CO2, because increases in CO2 alone enhanced total aboveground
biomass, while increases in CO2 combined with N addition decreased total aboveground
biomass. In Elkhorn Slough, California, marsh community was assessed at six sites. At
one site, where impoundment restricted tidal exchange, N addition of 150 kg N/ha/yr
altered community composition, decreasing cover of native marsh plants by 52% and
increasing cover of non-native upland plants by 80% (Goldman Martonc and Wasson.
2008). There are two studies with N addition above 500 kg N/ha/yr (Baldwin. 2013; Ryan
and Bover. 2012). but this N addition level is not useful in inferring effects of N
deposition upon ecosystems.
11.8.1.2 Freshwater Tidal Marsh
In a freshwater tidal marsh on the Tchefuncte River, Louisiana, N addition shifted the
relative dominance of the perennial wetland-obligate monocots dominant at the site
(Graham and Mendelssohn. 2010). Increasing N loads increased the relative dominance
of Persicariapunctata (formerly Polygonumpunctatum) with a 0.13% increase (% total
biomass consisting of P. punctata) for every 10 kg N/ha/yr added. Increasing N loads
decreased the relative dominance of Eleocharis fallax, with a 0.08% decrease (% total
biomass consisting of E. fallax) for every 10 kg N/ha/yr added (Graham and
Mendelssohn. 2010). N loading did not affect the relative dominance of Sagittaria
lancifolia, but did alter its storage of N in plant tissues (Section 11.5).
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11.8.1.3 Bog
In Mer Bleue Bog, Ontario, N addition decreased the dominance of Sphagnum mosses in
the northern ombrotrophic peat bog. After 4 years of N fertilization at the rate of 64 kg
N/ha/yr, cover of Sphagnum species (of Sphagnum magellanicum and Sphagnum
capillifolium) in fertilized plots was 43% of Sphagnum cover in control plots (Juutinen et
al.. 2010). At Year 12, cover of Sphagnum species in 16 kg N/ha/yr fertilized plots was
64% of cover in control plots (Larmola et al.. 2013). Plots measured in the same growing
season (2011) which had received 7 years of elevated N at higher N addition rates also
experienced declines in Sphagnum cover, 26% decline in cover at 32 kg N/ha/yr and 54%
decline in cover at 64 kg N/ha/yr (Larmola et al.. 2013). These declines in peat-forming
species corresponded to changes in ecosystem C fluxes (Section 11.3.2).
11.8.1.4 Summary Table
Table 11-9 Nitrogen loading effects upon plant biodiversity and communities.
Type of
Ecosystem
Additions
or Load (kg
N/ha/yr)
Biological and Chemical
Effects
Study Site Study Species
Reference
Coastal high
marsh
Addition:
150 kg
N/ha/yr as
urea
S dep = not
reported
N dep = not
reported
At a site where tidal inflow Six sites at
was restricted, fertilization Elkhorn
increased cover of Slough,
non-native upland plants by Watsonville,
80% and decreased cover of California
native marsh plants by 52%.
Marsh community
dominated by
Sarcocornia pacifica,
also contains Jaumea
carnosa, Frankenia
salina, Spergularia
salina, Distichlis
spicata, and Atriplex
caiifornica/trianguiaris
Goldman
Martone and
Wasson (2008)
Estuarine salt
marsh
Addition:
1,337 kg
N/ha/yr as
urea
S dep = not
reported
N dep = not
reported
S. pacifica cover increased China Camp
at 6.2 times the rate of State Park,
increase in control. J. California
carnosa cover declined 5.4
times as fast as in control.
Sarcocornia pacifica
dominant (C3
succulent shrub),
Distichlis spicata (C4
grass), and Jaumea
carnosa (C3
semisucculent forb)
Ryan and Bover
(2012)
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Table 11-9 (Continued): Nitrogen loading effects upon plant biodiversity and
communities.
Additions
Type of or Load (kg Biological and Chemical
Ecosystem N/ha/yr) Effects
Study Site Study Species
Reference
Estuarine salt
marsh
Addition:
250 kg
N/ha/yr
S dep = not
reported
N dep = not
reported
In ambient but not elevated
CO2, S. americanus
aboveground biomass
decreased by 19% and 45%
in the 3rd and 4th years,
respectively.
Kirkpatrick
Marsh,
Maryland
(measured in
3rd and 4th
years,
2008-2009)
Schoenoplectus
americanus (C3),
Spartina patens (C4),
and Distichlis spicata
(04)
Lanqlev and
Meaoniaal
(2012. 2010)
Estuarine tidal
marsh
Addition:
none
S dep = not
reported
N dep = not
reported
On the Patuxent River, pore Nanticoke
water NCV-N and salinity River and
best explained plant species Patuxent
richness (model R2 = 0.67), River,
with NC>3"-N accounting for Chesapeake
26% of variation in the full Bay,
data set and for 5% of Maryland
variation in widely distributed and
species. In species with Delaware
more restricted geographic
ranges, NCV-N alone best
predicted plant species
richness (positive
relationship, model
R2 = 0.71).
Plant community
Sharpe and
Baldwin (2013)
Estuarine tidal Addition: Typha spp. cover increased
marsh 670 kg by 120%.
N/ha/yr
S dep = not
reported
N dep = not
reported
Nanticoke Plant community Baldwin (2013)
River,
Maryland
and
Delaware
Freshwater
estuarine
marsh
50, 200, or
1,200 kg
N/ha/yr as
Nutralene
methylene
urea
S dep = not
reported
N dep = not
reported
N addition decreased the
dominance (percent
biomass) of Eleocharis
fallax, % mass = -0.00812 *
(kg N/ha/yr) + 15.410.
Addition increased the
dominance (percent
biomass) of P. punctatum, %
mass = 0.03144 * (kg
N/ha/yr) + 9.353
Tchefuncte
River,
Madisonville,
Louisiana
Oligohaline plant
community dominated
by Sagittaria
lancifolia, Eleocharis
fallax, and Polygonum
punctatum
Graham and
Mendelssohn
(2010)
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Table 11-9 (Continued): Nitrogen loading effects upon plant biodiversity and
communities.
Additions
Type of or Load (kg Biological and Chemical
Ecosystem N/ha/yr) Effects
Study Site Study Species
Reference
Ombrotrophic
peat bog
16 (low), 32
(medium), or
64 (high)
kg N/ha/yr
as N
(NH4NO3) or
NPK
(NH4NO3
and KHPO4)
S dep = not
reported
N dep = 8 kg
N/ha/yr
In high N treatment,
Sphagnum cover declined
by 57%.
In all NPK treatments,
Sphagnum cover declined
over 8 years to 1-25% of
control, as Polytrichum cover
increased by 5-10 times
control and then declined.
Mer Bleue Bog plant community:
Bog, dwarf shrub species
Ontario, and mosses:
Canada Sphagnum
magellanicum,
Sphagnum
capillifolium, and
Polytricum strictum
Juutinen et al.
(2010)
Ombrotrophic 16 (low), 32
After 12 yr of low N,
Mer Bleue
Shrub species
Larmola et al.
peat bog (medium), or
Sphagnum cover decreased
Bog,
(Vaccinium
(2013)
64 (high) kg
36%. After 5 yr of medium
Ontario,
myrtilloides, Ledum
N/ha/yr as N
and high N, Sphagnum
Canada
groenlandicum,
(NH4NO3) or
cover decreased 26% and
Chamaedaphne
NPK
54%, respectively.
calyculata) and
(NH4NO3
mosses(Sphagnum
and KHPO4)
magellanicum,
Sphagnum
capillifolium,
Polytricum strictum)
C02 = carbon dioxide; dep = deposition; ha = hectare; kg = kilogram; KHP04 = potassium phosphate; N = nitrogen;
N03"-N = nitrogen as nitrate; NH4N03 = ammonium nitrate; NPK= nitrogen, phosphorus; potassium; PSN = photosynthesis;
S = sulfur; yr = year.
11.8.2 Phytoplankton
N loading alters abundance and community structure of phytoplankton in wetlands;
however, the experimental N additions in the relevant studies are above 500 kg N/ha/yr
and are more typical of anthropogenic N wastewater than of N deposition loads. In
Yaquina Bay, OR, addition of 4,056 kg N/ha/yr increased the relative abundance of the
diatom Navicula gregaria by 91% in surface sediments of the tidal marsh, although this
did not alter measures of diatom community diversity (Hankin et al.. 2012). A higher rate
of N addition, at 16,250 kg N/h/yr, decreased the abundance of surface sediment diatom
N. phyllepta by 67% and decreased diatom community richness by 12%. Both these
changes resulted in a 14% decline in species diversity (evenness + richness) as measured
by the Shannon index (H'). The highest rate of N addition in this study, 40,560 kg
N/ha/yr, altered both species abundance and community composition. At this higher rate
of N loading, N. gregaria, which had responded positively to lower N addition rates,
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decreased in abundance to 24% of relative abundance in unamended sediments, while N.
phyllepta decreased in relative abundance to 25% of control. At the same time, diatoms in
the genus Amphora increased in abundance to 20 times their abundance in unamended
plots. Diatom richness also declined to 86% of control richness, which in combination
with changes in the abundance of certain species lowered the Shannon Index of diversity
to 76% of unamended diatom community of surface sediments (Hankin et al.. 2012).
Alterations to the phytoplankton community were also observed at an N addition
experiment conducted in restored salt marshes of the Tijuana River National Estuarine
Research Reserve, California. In this experiment, phytoplankton abundance was assessed
by measuring the concentrations of different forms of chlorophyll specific to different
groups of plankton in both the water column and the surface sediment. N addition of
600 kg N/ha/yr increased the total abundance of the total algal community in the water
column (based on concentrations of chlorophyll a) by 54%, and in particular increased
the abundance of diatoms (chl c) by 29%. In surface sediments, 600 kg N/ha/yr increased
the abundance of photosynthetic diatoms by 47%.
11.8.3 Consumer
Increased reactive N can alter dynamics among consumers in wetlands. There are studies
showing increasing N load increases parasitism, decreases overall health condition, and
increases abundance of mosquitos (vectors for zoonotic diseases). There is also a new
meta-analysis evaluating consumer behavior in coastal wetlands. He and Silliman (2015)
conducted a meta-analysis of herbivory in globally distributed coastal wetlands (marshes
and mangroves) and found that N and N + P additions generally increased herbivore
abundance and herbivory across salt marsh studies, but not across mangrove studies.
In a survey of the native mud snail Illyanassa obsoleta collected from 15 New England
salt marshes, increased N correlated with increasing parasitism of I. obsoleta. Sediment N
correlated positively with parasitic trematode prevalence (If = 0.41) and with infection
by the parasitic flatworm Stephanostomum spp. (If = 0.42).
Wigand et al. (2010) developed a metric for marsh condition using the Nitrogen Loading
Model (Wigand et al.. 2003) and data collected on abundance and richness of plants,
invertebrates, and soil conditions of 10 coastal marshes in Narragansett Bay, Rhode
Island. Marsh condition declined as annual N load to the marsh increased.
laleggio and Nyman (2014) collected plants dominant in freshwater (Panicum
hemitomon), freshwater-brackish (Sagittaria lancifolia), and brackish (Spartian patens)
marshes, fertilized the plants with 619 kg N/ha/yr in mesocosms, and then offered the
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plants along with unfertilized controls in feeding trials to the introduced aquatic rodent
Myocastor coypus, nutria. Fertilization increased plant tissue N by 140%, from 0.9% N to
2.2% N by mass, and nutria preferentially fed on fertilized plants. N loading increased
plant mass loss due to nutria herbivory by 750% (laleggio and Nvman. 2014).
N addition increases the abundance of mosquito species Culex tarsalis and Anopheles
hermsi, which act as vectors for zoonotic diseases. Duguma and Walton (2014)
constructed freshwater wetland mesocosms at UC Riverside, planting Schoenoplectus
maritimus in all mesocosms and monitoring plant growth as well as colonization of
mesocosms by mosquito species. N loads were 0, 32, 65, and 108 kg N/ha/yr in 2009, and
0, 59, 119, and 198 kg N/ha/yr in 2010. Sampling retrieved elevated numbers of Culex
tarsalis (western encephalitis mosquito) larvae and pupae in elevated nitrogen treatments
in both 2009 and 2010, and of Anopheles hermsi in 2010. In 2009, immature mosquito
counts were 56-100% higher in fertilized treatments than in control treatments, but there
were no differences among differentN loads in mosquito counts. In 2010, total mosquito
counts were similar in unenriched mesocosms and in mesocosms receiving 59 kg
N/ha/yr, but increased by 64% with 119 kg N/ha/yr, and by 129% with 198 kg N/ha/yr
(Duguma and Walton. 2014).
11.9 Critical Loads
In the 2008 ISA, no critical loads studies had been published. Since then, critical loads
have been published for wetlands in the U.S. (Greaver et al.. 2011).
11.9.1 Freshwater Wetland
Greaver et al. (2011) determined that the critical load for altered peat accumulation and
NPP is between 2.7 and 13 kg N/ha/yr, based on observations from Aldous (2002a).
Moore et al. (2004). Rochefort et al. (1990). and Vitt et al. (2003). The upper end of this
critical load range is based on measurements of wet deposition only [10 to 13 kg N/ha/yr
(Aldous. 2002a. b)] and therefore does not reflect total N loading from all sources. There
is evidence showing that N deposition alters both the morphology and population
dynamics of the purple pitcher plant. The empirical evidence suggests a critical load to
protect the population of purple pitchers of 10-14 kg N/ha/yr (Gotelli and Ellison. 2006).
while matrix modeling to forecast long-term population sustainability based on
observations of population demographics suggests a lower value of 6.8 kg N/ha/yr
(Gotelli and Ellison. 2002).
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11.9.2
Intertidal Wetlands
Greaver et al. (2011) conclude that the critical load range for atmospheric deposition is
difficult to establish for intertidal wetlands because these ecosystems have open nutrient
cycles that are often strongly affected by N loading sources other than atmospheric
deposition. Typically, the amount of N added in experimental treatments simulates total
N input and therefore far exceeds the amount that U.S. intertidal wetlands would receive
by atmospheric deposition. Only two studies had addition levels below 100 kg N/ha/yr.
Based on the results of Wigand et al. (2003). a critical load to protect the community
structure of salt marshes is likely to be 63 to 400 kg N/ha/yr. Caffrev et al. (2007) provide
additional evidence that 80 N/ha/yr alters microbial activity and biogeochemistry.
Latimer and Rego (2010) found that eelgrass coverage started to decrease rapidly at N
loading higher than 50 kg N/ha/yr, with no eelgrass at loading levels higher than 100 kg
N/ha/yr. Note that these values are the total N loading to salt marshes, including N
deposition directly to the marsh surface, as well as N deposited indirectly to the
watershed, surface or groundwater, and runoff from agriculture, urban areas, and other
sources. Additional experimental evidence on ecosystem response to N loads that are
similar to the amount of loading due to N deposition is needed to improve the critical
load calculation for intertidal wetlands in the U.S.
11.9.3 Comparison to Critical Loads from Europe
The most recent assessment of N critical loads in Europe was published in 2003 and
designated critical loads for multiple types of wetlands, including raised and blanket
bogs, poor fens, rich fens, mountain rich fens, and intertidal wetlands (Bobbink et al..
2003). There are numerous publications on N effects to wetlands in Europe compared to
the U.S. In general, documented responses include effects on growth and species
composition, competition among species, peat and peat water chemistry, decomposition,
and nutrient cycling. A brief summary of the European critical loads for wetlands is
presented here.
Bobbink et al. (2003) assigned a critical load of 5 to 10 kg N/ha/yr for bog ecosystems,
based on plant community and species responses to N deposition, and indicated that
precipitation and P limitation should be used to assign critical loads to individual sites.
The observed changes in the plant communities of ombrotrophic bogs included the
replacement of Sphagnum-form i ng species with nitrophilous moss species [20 to
40 kg N/ha/yr in Dutch bogs (Greven. 1992)1; the absence of characteristic Sphagnum
species in British bogs [30 kg N/ha/yr (Lee and Studholme. 1992)1; and reduction in the
growth survivorship of characteristic bog species roundleaf sundew [10 kg N/ha/yr in
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Swedish bogs (Bobbink et al.. 2003; Redbo-Torstensson. 1994)1. The European critical
load is similar to the range of critical loads suggested for freshwater wetlands in the U.S.
It is unclear how European critical loads for poor fens, rich fens, and montane rich fens
relate to the critical loads for similar wetlands in North America because the impacts of N
loads have not been studied in the U.S. European poor fens have a critical load of 10 to
20 kg N/ha/yr based on increased sedge and vascular plants and negative effects on peat
mosses. The critical load for rich fens in Europe is 15 to 35 kg N/ha/yr based on
increased tall graminoids and decreased diversity. The critical load for montane rich fens
in Europe was 15 to 25 kg N/ha/yr based on increased vascular plants and decreased
bryophytes. Note that changes in the vegetation composition and structure likely affect
fauna species assemblages, such as ground-breeding birds and spiders and beetles, living
in the originally open bog vegetation. Increased nutrient availability results in an increase
of the nutrient content of plant material (Limpens et al.. 2003a; Tomassen et al.. 2003)
and algal growth (Limpens et al.. 2003b; Gulati and Demott. 1997). which affects
herbivorous, detritivorous, and carnivorous invertebrates (van Du inert et al.. 2004).
The European critical load for salt marshes, based on expert judgment, is 30 to
40 kg N/ha/yr (Bobbink et al.. 2003). but studies of European salt marshes are limited.
High levels of N input (65 to 70 kg N/ha/yr) significantly increased biomass production
in the Netherlands (van Wiinen and Bakker. 1999); however, no changes in species
composition and in diversity have been observed for the current deposition of 15 to
25 kg N/ha/yr at sites in the Netherlands and Germany (Bobbink et al.. 2003). The critical
load for North American intertidal ecosystems may be closer to these values than to the
high levels of N input previously studied.
11.10 Summary
There are chemical and biological effects of N deposition in wetlands. Wetland
vegetative communities are adapted to high levels of natural organic acidity, so it is
unlikely that S or N deposition would cause any acidification-related effects at levels of
acidic deposition commonly found in the U.S. (U.S. EPA. 2008a. in Annex B). Wetlands
can be sensitive to eutrophication caused by N deposition. These effects were
documented in the 2008 ISA. In this chapter, new information published since 2008 is
integrated with the information published in the 2008 ISA. Synthesis is made across
wetland types for causality statements. Information is also synthesized for freshwater and
intertidal wetlands, because saltwater/intertidal wetlands are typically adapted to much
higher N loading.
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11.10.1 Causality across Wetland Types
New studies published between 2008-2015 support and extend the findings of the 2008
ISA. As in the 2008 ISA, the body of evidence is sufficient to infer a causal
relationship between N deposition and biogeochemistry (alterations to N and C
cycling, including increases in methane and nitrous oxide emissions). There is new
evidence of N deposition changes to plant physiology, which was not included in the
2008 ISA as an endpoint due to lack of evidence. This expands our understanding of the
causal relationship between N deposition and species diversity. The body of evidence is
sufficient to infer a causal relationship between N deposition and the alteration of
species physiology, species richness, community composition, and biodiversity in
wetlands.
N deposition contributes to total N loading in wetlands, with the relative contribution of
deposition to total loading variable among wetland types. Chemical indicators of N
deposition in wetlands include NO3 leaching, N mineralization, and denitrification rates.
A wetland can serve as a source, sink, or transformer of atmospherically deposited N
(Devito et al.. 1989). Source/sink N dynamics in wetlands vary with season, hydrological
conditions, vegetation type, climate, and surface geology (Mitchell etal.. 1996; Arheimer
andWittgren. 1994; Koerselman et al.. 1993; Devito et al.. 1989).
Several new studies provide evidence of N deposition alterations to biogeochemical
cycling of N within a wetland ecosystem (Section 11.3). A synthesis study of multiple
wetland types across the globe shows wetland N removal is proportional to N load (log
[N removal] = 0.943[log(N load)] - 0.033 N) and removal efficiency is 26% higher in
nontidal than tidal wetlands (Jordan et al.. 2011). Meta-analysis of 19 N addition
observations (N addition 15.4 to 300 kg N/ha/yr) found that N enrichment increased
wetland N2O emissions by 207% (Liu and Greaver. 2009). The emission factor for the
amount of N added to a wetland that is converted to N2O ranges between 0.007-0.07 (Liu
and Greaver. 2009).There are also new studies that evaluate the effects of N loading/N
addition on other endpoints related to N cycling in salt marsh, mangrove, peat bog, and
riparian wetlands. The endpoints evaluated include tidal export of N, mineralization,
denitrification, and bacterial community composition in wetland soils. The results of
these studies are summarized in Figure 11-1.
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ao
o
CO
\1/ N retention efficiency
16
Q.
DC
\1/ BNF rates, sUN-fixing symbionts
100
'T* Denitrification rate
100
\1/ N mineralization
o
u \1/ N retention tidal N export)
100
180
100 200 300
N addition (kg N/ha/yr)
400
500
BNF =biological nitrogen fixation; ha = hectare; kg = kilogram; N = nitrogen.
A = Xing et al. (2011) B = Ruess et al. (2013). C = Whiaham et al. (2009). D = Vivanco et al. (2015). E = Brin et al. (2010).
Figure 11-1 Summary of the levels of nitrogen addition where a change to
nitrogen cycling is first observed.
There is also new information on how N deposition alters biogeochemical cycling of C in
wetlands. In a study of 90 wetlands around the Gulf Coast from Florida to Texas,
Nestlerode et al. (2014) found that higher N in the soil correlated with lower bulk density
([In soil %N] = -1.9233 x [g/cc] + 0.4165) which indicates that the marsh is less resilient
to physical stresses from tidal or storm flooding, and the marsh platform is more likely to
shear off or wash away. Significant effects of N addition upon biogeochemical cycling of
C (in which the N addition was 500 kg N/ha/yr or lower) are summarized in Figure 11-2.
This figure also includes responses of aboveground plant biomass and productivity to N
addition. N addition alters belowground and aboveground pools of carbon, and also
increases wetland methane emissions, as summarized by meta-analysis in the 2008 ISA
and published in Liu and Greaver (2009).
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Q)
LI—
o3
M
O
CQ
AG: 'T* 30% biomass of moss community A
BG: 'T* 17% biomass in top 10 cm peat B
BG: altered peat temperature, \|/ peat [C02] B
AG: 'T* 105% biomass C. calyculata (STE) c
AG: 'T* 600% biomass C. oligosperma (STE) c
AG: 'T* 2.6 times productivity plant community c
BG: \1/ 46% net ecosystem C exchange D
ANPP responsive to N E
BG: \1/ 71% rhizome biomass F
BG: \1/ 33% macro-organic matter F
AG: ^l.4-3.8 times biomass Z. miliacea (STE) F
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added N on methanogenesis, the final step in anaerobic decomposition, offset any
increase in methanotrophy. Differential effects of N on both methanogenesis and
methanotrophy have been documented in other ecosystems (Irvine et al.. 2012; Liu and
Greaver. 2009V
N addition effects on plant stoichiometry were not addressed in the 2008 ISA. Plant
stoichiometry theory considers the balance of multiple chemical elements in living
tissues. The stoichiometry of plant tissue is often connected to the tissue's physiological
function. Most new studies on physiology and stoichiometry are for bogs and freshwater
marshes. There are a few studies on salt water marshes and fens. In bogs, N addition
typically causes an increase in N content, a decrease in N use efficiency and resorption,
and an increase in plant production. After several years of exposure, plants may
experience leaf N saturation, and micronutrient limitation (e.g., P and K, indicated by
increasing reabsorption efficiencies; see Figure 11 -3). Sensitive plant species show leaf
damage (Bubier et al.. 2011; Xing etal.. 2011). There are several new studies that
indicate species in freshwater marshes function similarly to the species found in bogs; N
addition increases the N concentration in plant tissue with a cascading effect that
increases primary production. There was no evidence of decreased production.
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4/ 15% leaf C:N, 4/ 34% leaf Ca, ^ amino acids in shrub C. calyculata (STE)
HH
4* 23% leaf Ca, 4/ 55% P, 4' 47% K in shrub V. myrtilloides (STE)
0
^ 100% Vcmax in shrub R. groenlandicum (STE)
4^29-62% N uptake in moss S. magellanicum
0
i" 42% P resorption in shrub C. calyculata (STE)
0
^12 times P resorption, "f 92-123% K resorption in R. groenlandicum (STE)
0
c
d)
4^ 81% NUE, 4^ 91% NRE in shrub C. calyculata (STE)
0
o3
00
4/ 89% NUE, 4/ 84% NRE in sedge C. oligosperma (STE)
0
o
CO
'T N uptake by grass C. canadensis
4/45% NRE in tree A. rugosa
^ 16% leaf N, 4^ 54% leaf P, f glutamic acid, in shrub R. groenlandicum (STE)
4' 23% leaf Mg, 4/ 186% Mg resorption in R. groenlandicum (STE)
84% leaf chlorophyll, 'T amino acids in shrub C. calyculata (STE)
1s P resorption 33%, 4' 22% leaf Ca, 4/ 45% Mn in shrub C. calyculata (STE)
Shift in bog seasonal gross PSN: 4/ summer PSN, ^ fall PSN
0
0
0
0
0
0
0
Riparian
"T 10% leaf N , 4- 21% P resorption in tree A. tenuifolia
M
1" AG plant tissue [N], in sedge B. maritimus (STE)
0
JZ
plant tissue N, ^ plant N:P, 4/ NRE, 4/PRE in forb S. lancifolia
0
CTJ
E
T" 26% BG plant tissue [N] in sedge B. maritimus (STE)
0
5
LL.
'V 5% leaf construction cost in native haplotype of grass P. australis
-t 25-43% leaf N, ^ 18-28% leaf C:N, ^ 25-61% leaf N:P in tidal FW marsh
[ho]
fsool
Coastal
Marsh
f leaf N in succulent forb S. depressa
M
C
) 100
200 300
kg N/ha/yr
400
500
AG = aboveground; BG = belowground; C = carbon; Ca = calcium; FW = freshwater; K = potassium; Mg = magnesium;
Mn = manganese; N = nitrogen; NRE = nitrogen resorption efficiency; NUE = nutrient use efficiency; P = phosphorus; PP = primary
productivity; PRE = phosphorus resorption efficiency; PSN = photosynthesis; STE=state-listed threatened or endangered species;
Vcmax = maximum velocity of carboxylation.
Figure 11-3 Summary of the level of nitrogen addition that caused a change in
the response variables of plant stoichiometry and physiology in
wetlands.
1 Plant architecture was not addressed in the 2008 ISA. Plant architecture is defined as the
2 three-dimensional organization of the plant body. For the parts of the plant that are
3 aboveground, this includes the branching pattern, as well as the size, shape, and position
4 of leaves and flower organs. There are several new studies on plant architecture. Two
5 studies in freshwater marshes that increase the number of leaves and plant height
6 (Duguma and Walton. 2014; Ket et al.. 2011). There was one study in mangroves in
7 which N addition of 100 kg/ha/yr increased the number of branches for A germincms.
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Finally, one study in a riparian wetland found that N addition of 100 kg/ha/yr decreased
the SLM of leaves in A. tenuifolia (Ruess et al.. 2013).
Plant demography was not addressed in the 2008 ISA. Plant demography is the change in
plant population size and structure through time. N addition caused negative reproductive
effects in invasive Spartina foliosa and Spartina hybrids (Tvler et al.. 2007). and a
positive effect of Salicornia bigloveii (Bover and Zedler. 1999).
The 2008 ISA found that the evidence was sufficient to infer a causal relationship
between N deposition and the alteration of species richness, species composition, and
biodiversity in wetland ecosystems. The 2008 ISA noted that there are 4,200 native plant
species in U.S. wetlands, 121 of which are federally endangered. Wetlands provide
habitat to a disproportionally high number of rare plants given their relative area; for
example, fens occupy 0.01% of the land area of northeast Iowa yet contain 17% of the
endangered, threatened, or listed species of concern in the area. Wetland species have
evolved under N limited conditions, including endangered species in the Isoetes
(3 endangered species) and Sphagnum (15 endangered species) genera, as well as the
endangered insectivorous plants Sarracenia oreophila and Drosera rotundifolia.
In the 2008 ISA, evidence from Canadian and European peatlands showed that N
deposition had negative effects on Sphagnum bulk density and mixed effects on
Sphagnum productivity depending on the history of deposition. In Canadian
ombrotrophic peatlands experiencing deposition of 2.7-8.1 kg N/ha/yr, peat
accumulation increased with N deposition, but accumulation rates had slowed by 2004,
indicating a degree of N saturation. Sarracenia oreophila responded to N deposition with
changes in morphology and projected population extinction under N deposition levels of
4.5-6.8 kg N/ha/yr. There was only one study on N enrichment in riparian systems at the
time of the 2008 ISA, and the N levels in the study were meant to mimic wastewater
effluent, not the lower amounts of N typical of atmospheric deposition. Coastal wetlands
responded to N enrichment with increased primary production, shifting microbial and
plant communities, and altering pore water chemistry. However, many of these studies of
coastal wetlands used N enrichment levels more similar to wastewater than atmospheric
deposition.
Publications since 2008 confirm nitrogen is an important factor driving plant diversity. A
study on the Patuxent River found marsh soil NO;, -N and pore water salinity best
explained variation in plant species richness out of all factors considered (R2 = 0.67), with
NO3-N accounting for 26% of the variation in the richness of all species.
Presence-absence data for all species were used to determined geographic range for each
species, and the 50% of species per river with the smallest range were designated as a
"restricted-range" subset. On the Patuxent River, the best model of variation in species
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richness of restricted range species contained only soil NO3 -N as an explanatory
variable, with a positive relationship between NO3 -N and species richness [i?2 = 0.71
(Sharpe and Baldwin. 2013)1.
There are several field addition studies to support the causal relationship between N
addition and altered biodiversity (Figure 11-4). In Mer Bleue Bog, Ontario, N addition
decreased the dominance of Sphagnum mosses in the northern ombrotrophic peat bog
(Larmola et al.. 2013; Juiitinen et al.. 2010). In a freshwater tidal marsh on the
Tchefuncte River, Louisiana, N addition shifted the relative dominance of the perennial
wetland-obligate monocots dominant at the site (Graham and Mendelssohn. 2010). In salt
marshes in Maryland and California, N addition was shown to alter the relative
abundance of species (Langlev and Megonigal. 2010; Goldman Martonc and Wasson.
2008).
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aa
o
CO
<4, 36% cover of mosses S. magellanicum arid S.
capillifolium (12yr Ex)A
4, 26% cover of mosses S. magellanicum arid S.
capillifolium (7 yr Ex)A
si/ 57% cover of mosses S. magellariicm arid S.
capillifolium (4 yr Ex)B
si/ 54% cover of mosses S. magellanicum and S.
capillifolium (7 yr Ex) A
sj/ relative dominance of sedge E. fallaxc
relative dominance of forb P. punctata c
16
32
64
64
50
50
80% cover of non-native upland plant species '
150
o
u
si/ 52% cover of native marsh plant species D
i" 129% cover of C4 grasses S. patens and D.
spicata E
si/ 52% cover of C3 sedge S. americanus E
150
250
250
100
200 300
kg N/h/yr
400
500
Ex=experimental exposure length; FW = freshwater; h =hectare; kg = kilogram; N = nitrogen; yr = year.
A = Larmola et al. (2013). B = Juutinen et al. (2010). C = Graham and Mendelssohn (2010). D = Goldman Martone and Wasson
(2008). E = Lanalev and Meaoniaal (2010).
Figure 11-4 Summary of nitrogen addition studies on wetland biodiversity.
Numbers indicate the lowest addition level in which change is
observed.
11.10.2 Freshwater and Intertidal
Freshwater and intertidal wetlands tend to have different sensitivity to N
deposition/addition. The effect of N deposition on wetland ecosystems depends on the
fraction of rainfall in its total water budget, and the sensitivity to N deposition has been
suggested as bogs (70-100% rainfall) >fens (55-83% rainfall) >intertidal wetlands
[10-20% rainfall (Morris. 1991)1.
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1 Greaver et al. (2011) suggest N critical loads CLs for U.S. intertidal wetlands based on
2 eel grass population (50-100 kg N/ha/yr) and community composition, microbial
3 activity, and biogeochemistry (63-400 kg N/ha/yr). A comparison of those critical loads
4 with data on N addition levels (15-500 kg N/ha/yr) and associated effects, published
5 since the CLs for wetlands were set, is given in Figure 11-5.
O
U
u (TJ
±± ~o
ra +-»
u ° Ł
cc —1 +-»
I- !=
(J
AG: 'T* biomassA. germinans
'T* Denitrification rate
'T* methane emissions
\1/ N mineralization
'T* leaf N in succulent forb S. depressa
AG: 'T* biomass of S. depressa
AG: 'T* biomass ofS. pacifica
'T* cover of non-native upland plant species
\1/ cover of native marsh plant species
\1/ N retention tidal N export)
BG: \1/ fine root production
AG: 'T* biomass of C4 plants S. patens and D. spicata
AG: \1/ biomass of C3 S. americanus
AG: 'T* plant community biomass
'T* cover of C4 grasses S. patens and D. spicata
\1/ cover of C3 sedge S. americanus
loss of eel grass
Salt marsh community structure, microbial activity
and biogeochemistry
11001
11001
11001
11001
11001
11001
1150 I
EH1
115oJ
fl80
250
2§
2§
250
2§
12501
150-1001
63-400
100 200 300
kg N/ha/yr
400 500
AG = aboveground; BG = belowground; CH4 = methane; GTR = general technical report; N = nitrogen.
Figure 11-5 Summary of field nitrogen addition studies for coastal wetlands
versus critical loads.
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Greaver et al. (2011) determined that the critical load for altered peat accumulation and
NPP is between 2.7 and 13 kg N/ha/yr, based on observations from Aldous (2002a).
Moore et al. (2004). Rochefort et al. (1990). and Vitt et al. (2003). The upper end of this
critical load range is based on measurements of wet deposition only [10 to 13 kg N/ha/yr
(Aldous. 2002a. b)] and therefore does not reflect total N loading. There is evidence that
N deposition alters both the morphology and population dynamics of the purple pitcher
plant. The empirical evidence suggests a critical load to protect the population of purple
pitchers of 10-14 kg N/ha/yr (Gotelli and Ellison. 2006). while matrix modeling to
forecast long-term population sustainability based on observations of population
demographics suggests a lower value of 6.8 kg N/ha/yr (Gotelli and Ellison. 2002). A
comparison of those CLs to data on N addition levels (16-500 kg N/ha/yr) and associated
effects, published since the CLs for wetlands were set, is given in Figure 11-6.
There is information on the relationship between N addition and numerous endpoints. At
the lowest addition level (16 kg N/ha/yr), there are observations of decreases in moss
cover, increased peat biomass, decreased N retention efficiency, and altered/damaged leaf
stoichiometry in vascular plants.
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Vcmax in shrub R. groenlandicum (STE) ED
AG: 'T" biomass of moss community
BG:1^ biomass in top 10 cm peat [IT)
4, N retention efficiency of bog
BG: altered peat temperature, 4/ peat [C02]
4^cover of mosses S. magellanicum and capillifolium(12 yr Ex)
-i- N uptake in moss S. magellanicum 1701
'V P resorption in shrub C. calyculata (STE) ED
"T-P resorption, "T- K resorption in R. groenlandicum (STE) 11? |
4- cover of mosses S. magellanicum and capillifolium (7 yr Ex) ED
4- NUE, 4- NRE in shrub C. calyculata (STE) [eo]
i2! 4» NUE, 4' NRE in sedge C. oligosperma (STE) |eo|
08 '—'
^ N uptake by grass C. canadensis |eo |
slz NRE in tree A. rugosa |eo|
AG: f - biomass of grass C. calyculata (STE) |fio|
AG; biomass of sedge C. oligosperma (STE)
AG: 'f productivity plant community [go]
't4 leaf N, 4,P, 'f glutamic acid, in R. groenlandicum (STE) ED
4/ leaf Mg, xj/ Mg resorption in R. groenlandicum (STE) [m]
T* leaf chlorophyll, 'f amino acids in shrub C. calyculata (STE) ED
P resorption, 4> leaf Ca, 4- Mn in shrub C. calyculata (STE)
4> cover of mosses S. magellanicum and capillifolium (4 yr Ex) 0
Shift in bog seasonal gross PSN: 4- summer PSN, -T fall PSN |641
BG: 4/ net ecosystem C exchange
c leaf N , 4- P resorption in tree A. tenuifolia | too |
.52 I I
4/ SLM in tree A. tenuifolia 11001
01 4'BNFrates, 4'N-fixing symbionts 11001
"T AG plant tissue [N], in sedge B. maritimus (STE) ED
¦f larval and pupal mosquito abundance
T plant tissue N, T N:P, 4- NRE, 4-PRE «n forb S. lancifolia
-i- relative dominance of sedge E. fallax [so]
i4- relative dominance of forb P. punctata
-jjj *T BG plant tissue [N] in sedge B. maritimus (STE) ED
5 total mosquito abundance |i!91
^ ANPP responsive to N
leaf construction cost of grass P. australis | ?S01
T- leaf N, 4- leaf C:N, T leaf N:P in tidal FW marsh
BG: 4' rhizome biomass |soo|
BG: 4, macro-organic matter
AG: -t biomass Z, miliacea (STE)
: $ -o
300 400
kg N/ha/yr
, tj 5 peat accumulation and NPP (2.713|
°i * 1 1
1 5 Pitcher plant community change |6.8-14|
AG = aboveground; ANPP = aboveground net primary productivity; BG = belowground; BNF = biological nitrogen fixation;
C = carbon; Ca = calcium; C02 = carbon dioxide; Ex = experimental exposure length; FW = freshwater; GTR = general technical
report; K = potassium; Mg = magnesium; Mn = manganese; N = nitrogen; NPP = net primary productivity; NRE = nitrogen resorption
efficiency; NUE = nutrient use efficiency; P = phosphorus; PRE = phosphorus resorption efficiency; PSN = photosynthesis;
SLM = specific leaf mass; STE = state-listed threatened or endangered species; Vcmax = maximum carboxylation velocity; yr = year.
Figure 11-6 Summary of field nitrogen addition studies for freshwater
wetlands as well as current critical loads. Values indicate biotic or
chemical changes observed in response to experimental nitrogen
addition.
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CHAPTER 12 NONACIDIFYING SULFUR EFFECTS
Chapter 12 summarizes research on the nonacidifying impacts of S deposition on
ecosystems, synthesizing literature published since the 2008 ISA for Oxides of Nitrogen
and Sulfur- Ecological Criteria (hereafter referred to as the 2008 ISA) with earlier key
studies. The causal statements are presented in the Introduction (Section 12.1).
Section 12.2 discusses effects of sulfur (S) deposition upon S storage and cycling in
ecosystems, sulfide phytotoxicity in wetlands, S upon internal eutrophication in
freshwater aquatic systems, S upon methane emissions from wetlands and lakes, and S
upon the microbial communities responsible for methanogenesis.
In Section 12.3. increasing bioavailability of mercury (Hg) due to S addition is a major
focus, and Hg sources, pools, and fluxes in terrestrial and aquatic ecosystems are briefly
described. This section also includes a discussion of the current understanding about the
distribution of Hg methylation potential across the prokaryotic domains, and the key role
of sulfur-reducing prokaryotes (SRPs). Because methylation rates are highly
heterogeneous across time and space, this section also contains a discussion of the
particular locations and temporal conditions of mercury methylation. Mercury
methylation occurs in lakes in shallow sediments or below the oxycline; in peat wetlands,
at the interface with upland areas and generally near the water surface in peat; in
periphyton; and in estuarine and marine sediments. In freshwater systems, methylation is
strongly seasonal, peaking in summer, with methylmercury (MeHg) concentrations
peaking in summer or fall. A number of chemical constituents other than sulfate also
control MeHg production and concentrations, including pH, organic matter, iron, and
nitrate.
In Section 12.4. multiple lines of evidence are presented establishing the relationship
between SOx deposition and increases in bioavailable Hg in the environment, including
experimental S addition experiments and their effects on MeHg and laboratory studies in
which sulfate is added to sediments collected from aquatic ecosystems. Section 12.5
considers observational evidence of the correlation between SOx deposition and Hg
burdens in fish. Section 12.5 also presents the results of observational studies in prairie
pothole wetlands, peat bogs, freshwater marshes, streams, and rivers that find positive
correlations between sulfate concentrations and MeHg concentrations in water and
sediment samples. Section 12.6 describes studies that find higher Hg burdens in
mosquitos and fish from ecosystems with increased experimental or anthropogenic S
loading. Ecosystems especially sensitive to the effects of S deposition are described in
Section 12.7. Section 12.8 is a summary including causal determinations based on the
synthesis of new information and previous evidence.
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12.1
Introduction
In the 2008 ISA, the evidence was sufficient to infer a causal relationship between S
deposition and increased methylation of Hg in aquatic environments where the value of
other factors was within adequate range for methylation. Direct atmospheric deposition of
S to wetland and aquatic systems, as well as sulfate leaching from terrestrial systems with
current or historical S deposition, alters biology and chemistry of these systems.
Nonacidifying effects of S deposition in these nonterrestrial systems include toxicity to
wetland plants, increased phosphorus (P) availability leading to internal eutrophication,
altered methane emissions, and increased Hg methylation and Hg concentration in biota.
As in the 2008 ISA, the body of evidence is sufficient to infer a causal relationship
between S deposition and increased methylation of Hg in wetland and aquatic
ecosystems where the value of other factors is within adequate range for
methylation. The 2008 ISA described sulfide phytoxicity in European systems, but there
is more recent research demonstrating sulfide phytotoxicity under current conditions in
North American wetlands. The body of evidence is sufficient to infer a causal
relationship between S deposition and changes in biota due to sulfide phytotoxicity
including alteration of species physiology, species richness, community composition,
and biodiversity in wetland ecosystems.
S deposition contributed to Hg accumulation by stimulating the activity of
anoxic-sediment-dwelling sulfur-reducing bacteria (SRB), which convert inorganic Hg to
MeHg in the course of metabolism. The 2008 ISA described the activity of SRB, but
more recent research indicates that S reducing archaea are also active in wetland
sediments, which is why this document will use the broader term sulfur-reducing
prokaryotes (SRPs) to denote both bacteria and archaea involved in S reduction.
Laboratory and mesocosm-scale experiments reviewed in the 2008 ISA established that
only trace amounts of MeHg could be produced in the absence of sulfate. These results
were confirmed with larger-scale observational studies. MeHg enters the food chain and
bioaccumulates in higher trophic levels, and research summarized in the 2008 ISA
suggested that numerous wild populations of fish, birds, and mammals experienced
MeHg exposures high enough to cause substantial reproductive, behavioral, or health
impairment.
At the time of the 2008 ISA, dose-response relationships between S deposition and
Hg-methylation rates had not been established, in part because oxygen content,
temperature, pH, and labile carbon supply also control the rates of the activity of SRB in
aquatic environments. Watersheds with conditions known to be conducive to Hg
methylation were found in the northeastern U.S. and southeastern Canada, although
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1 significant biotic Hg accumulation had been observed in other regions that had not been
2 studied as extensively. The U.S. EPA set the fish tissue criterion in 2001 for MeHg at
3 300 ng/g fish tissue (reported as 0.3 mg/kg) for the protection of human health, which
4 resulted in 2,436 fish consumption advisories for Hg in 2004, 2,682 in 2005, and 3,080 in
5 2006. Forty-eight states, one territory, and two tribes had issued Hg fish-consumption
6 advisories at the time of the 2008 ISA.
7 Chapter 12 summarizes research on the nonacidifying impacts of S deposition on
8 ecosystems, synthesizing literature published since the 2008 ISA with earlier, key studies
9 (Figure 12-1).
Atmospheric inputs/indicators
Biological indicators
Chemical indicators
Increased Hg
in mosquito
Increased Hg
in birds
Increased Hg
in fish
Increased Hg
in rice
Internal
Eutrophication
P release from Fe complexes
Decreased CH4
emissions
Increased sulfide in
water column or soils
Increased sulfide
phytotoxicity in plants
Decreased methanogen
abundance/activity
SOx deposition
Increased sulfur-reducing
proka ryote abundance/activity
Increased [SCU] in water column
or porewater of soil
Increased [MeHg] or
%MeHg in water column,
sediments, or periphyton
Food web
CH4 = methane; Fe = iron; Hg = mercury; MeHg = methylmercury; P = phosphorus; S04 = sulfate; SOx = sulfur oxides.
Figure 12-1 Effects of sulfur oxide deposition upon chemical (blue boxes),
biological (green boxes), and atmospheric (yellow boxes)
indicators of ecosystem change, as documented by the previous
Integrated Science Assessment and more recent research.
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12.2
Ecosystem Effects of Altered Sulfur Cycling
This section provides background on the sulfur cycle (Section 12.2.1). It describes effects
of S enrichment (SOx deposition or experimental S amendments) upon aquatic S cycling
(Section 12.2.1). sulfide toxicity upon wetland plants (Section 12.2.2). S enrichment upon
phosphate cycling in aquatic ecosystems and upon uptake of toxic elements by aquatic
plants (Section 12.2.3). and S enrichment in altering microbial competition and
methanogenesis (Section 12.2.4).
12.2.1 The Sulfur Cycle
S cycling in terrestrial ecosystems is relatively well-characterized compared to S cycling
in aquatic systems. Sulfate is the dominant S source in supplying plant nutrient S
demand, and due to its size and polar charge, it is very mobile within the soil solution.
Sulfate in the soil solution, whether its source was weathering of sulfur-containing
minerals, mineralization of internal ecosystem S, or atmospheric deposition of SOx, has
several possible routes through the S cycle (Figure 12-2).
Wet
Deposition
Dry
Deposition
Uptake
Litter
Inputs
Organic
Sulfur
Immobilization
Minera ization
Adsorbed Sulfate
Weathering
Su fur
Minera s
Leaching to
Surface Waters
Adsorption
Desorption
Source: Adapted from Mitchell et al. (2011).
Figure 12-2 Sulfur cycle in terrestrial, forested ecosystems.
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Sulfate can be immobilized by incorporation into living cells (microbes, fungi, plants),
and ultimately end up in the organic soil S pool. In most North American terrestrial
ecosystems, total S pools in soil greatly exceed S stored in living biota (Figure 12-2).
with soil S in organic or inorganic molecules. The largest pool of S in soil is organic,
typically comprising more than 95% of total soil S in temperate ecosystem soils (Wang et
al.. 2006; Solomon et al.. 2001). although in drained wetland soils of the Florida
Everglades Agricultural Area (EAA) the organic fraction was quantified as 87% of total
S (Ye et al.. 2010V Organic S pools in grassland soils are negatively correlated with mean
annual temperature in the North American Great Plains, indicating that climate is a strong
control on S cycling (Wang et al.. 2006). Organic soil S is found in ester-bound forms
(produced via microbial activity) or bound directly to carbon (C) in organic compounds
of varying sizes [the ultimate source was found to be plant roots or litter, (Edwards.
1998)1. Organic soil S cannot be taken up by plants directly, but organic S compounds
are mineralized back to sulfate by soil microbes under favorable moisture, temperature,
and oxic conditions (Wang et al.. 2006). Organic S pools can be indirectly enhanced by
SOx deposition via microbial and plant incorporation, as indicated by measures of soil
[S] and S isotopes. Sulfate in the soil solution can remain in the soil S pool in its
inorganic form as it adsorbs to hydrated soil particles. Soil adsorption of sulfate generally
results in a smaller S pool than soil organic matter, but this pool can be directly enhanced
by SOx deposition and associated acidification. Acidification may increase the storage
capacity of soils for sulfate. In the case of nonspecific adsorption, increasing acidity and
more H+ held in colloidal suspension create more sulfate binding capacity in soil, while
ecosystem recovery towards a more neutral pH may cause desorption of sulfate and
higher sulfate concentrations in the soil solution. In the case of specific adsorption,
sulfate binds with metal atoms in mineral particles; sulfate specific adsorption to soil also
increases with lower pH. However, the rate at which sulfate bound to soil particles is
released from adsorption in the soil solution as the ecosystem recovers (see Chapter 4)
towards a more neutral pH will heavily depend upon soil factors such as clay type, soil
age and weathering, calcium availability, and glaciation history. Inorganic S storage
within terrestrial soils can be directly affected by SOx deposition, as indicated by
measures of sulfate concentrations in soil fractions and soil solution.
Sulfate in the soil solution may be transported out of the terrestrial ecosystem if it leaches
to surface water and into downstream wetland and aquatic ecosystems. Sulfate
concentrations in surface water are often measured as an indicator of S fluxes from small
terrestrial watersheds. Freshwater aquatic S cycling is not as well described in the
scientific literature as is terrestrial soil S cycling. The preponderance of evidence is
concerned with the locations of redox S reactions within these aquatic systems. Sulfate
leached from terrestrial ecosystems, as well as sulfate from direct deposition to surface
water, is transformed in aquatic systems under particular conditions. High oxygen levels
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in the water column or inundated sediments of a wetland, lake, or stream favor S in
oxidized form as sulfate. Sulfate in anoxic (very low O2) waters or sediments is
transformed into more reduced forms such as sulfide or elemental S, which are less
soluble and may precipitate into sediments. Sulfur-reducing prokaryotes (SRPs) couple
their metabolism to the transformation of sulfate into these reduced forms. SRPs are
obligate anaerobes but require sulfate for metabolism, and as a result they are often
present and active at oxic-anoxic boundaries in aquatic environments. In shallow lakes,
this boundary (and the majority of sulfate reduction) occurs at the water-sediment
interface, in the top 1-2 cm of sediment (Rudd et al.. 1986; kellv and Rudd. 1984). In
deeper lakes that experience seasonal stratification, the water column may account for up
to 15% of sulfate reduction (Ingvorsen and Brock. 1982). and the anoxic boundary may
occur in the flocculant (suspended sediment), for example, 10 cm above the sediment in
Little Rock Lake, Wisconsin (Sherman et al.. 1994). In wetlands, particularly in peat bogs
that depend entirely upon precipitation as their water supply, the anoxic-oxic boundary
often coincides with the water table and can be much more dynamic. Finally, recent
research suggests that periphyton occupying high-oxygen waters can create anoxic
microenvironments that promote the growth and activity of SRPs (see Section 12.3.3).
The location and activity of SRPs are important environmentally because some SRPs
couple sulfate reduction with Hg methylation (see Section 12.3.IV The transformation of
S between reduced and oxidized forms in aquatic and wetland ecosystems occurs in
particular locations within these ecosystems but can have broader impacts on chemistry
and biota.
Pools of S in freshwater systems (lakes, rivers, streams, and wetlands) and residence
times of S in ecosystem pools are addressed in only a few ecological studies. S cycling in
lakes removes sulfate from the water column and stores reduced S in sediments. An early
study by Rudd et al. (1986) developed a budget for reduction-oxidation cycling of S
based on Adirondack lakes. Sulfate in the water column diffuses into sediments where it
binds to particulate matter or is incorporated by microbes. About 47% of water column
sulfate is reduced (by chemical or biological processes) and released into the sediments
as sulfide, which can bind to iron and precipitate, or as elemental S, which can precipitate
directly. The release of reduced S into the water column is responsible for some of the
other nonacidifying effects of S deposition, including internal eutrophication and
protective effects against certain heavy metals (see Section 12.2.4). The rest of the S
originally taken up by microbes as sulfate is incorporated into organic compounds. The
growth and activity of SRPs are responsible for Hg methylation in many sediments (see
Section 12.3). About one third of the reduced inorganic S and 57% of the organic S are
buried in lake sediments annually, or about 47% of the total sulfate input. The remaining
reduced sulfur, 53% of the original sulfate input, is oxidized by chemical reaction with
water molecules (Bates et al.. 2002) and returns to the S cycle (Rudd et al. 1986). This
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suggests that changes in S inputs to lakes—for example, reductions in SOx
deposition—could rapidly reduce sulfate concentrations in the water column, assuming
other environmental factors remain steady (see below for climatic influences on S
cycling).
Wetland S budgets resemble lake budgets in S reduction and burial of reduced S in
sediments, but also may include plant uptake and S export if hydrology allows. Sulfur
budgets have also been determined for the peat soils and freshwater marshes of the
Florida Everglades. The EAA has large impacts on S cycling in freshwater marshes in the
surrounding designated Water Conservation Areas (WCA), which serve as a water
quality buffer around Everglades National Park, a Class I area. In the EAA, addition of
elemental S as an agricultural soil amendment increased sulfate in the soil from 13 to
19% of total soil S, although at the end of the growing season sulfate was 1% of total S,
due to uptake by growing sugarcane (Ye et al.. 2010) and runoff into surrounding canals
and wetlands (Bates et al.. 2002). In an early study quantifying S budgets in the
Everglades WCA, Bates et al. (2002) determined that most of the sulfate in the system
has its source in S agricultural amendments applied in the EAA. In these wetland
systems, the pool of S in organic matter is high, and additional sulfate could be rapidly
incorporated into organic matter or exported in surface water, in addition to the reduction
or burial, which occurs in other aquatic systems.
Weather and climatic factors can disrupt S storage in more stable pools within aquatic
and wetland systems. In smaller stratified lakes, sulfate transfer from the epilimnion into
lower layers occurs slowly by diffusion between the stable water layers, while in larger
lakes, the layers are more prone to perturbation by wind and allow larger transfers of
sulfate to zones where SRPs are active (Ingvorsen and Brock. 1982). Sulfur cycling, like
most microbially driven processes, is seasonal; sulfate fluxes to the sediment are 10 times
higher in the summer than in winter (Sherman et al.. 1994). and the growing season
coincides with peak sulfate reduction in many freshwater systems (see Section 12.3.4.1).
In the Experimental Lakes Area (ELA) in Ontario, 10-39% of reduced S ended the
summer as sulfide dissolved in the hypolimnion, and this S was reoxidized to sulfate
when circulation occurred in the fall (Kelly etal.. 1982). In winter, O2 can penetrate
deeper into sediments or peat, reoxidizing sulfide (Sherman et al.. 1994). This reoxidation
can also occur in water bodies where water levels are controlled by humans, for example
in reservoirs (Ecklev et al.. 2015). Extreme events like droughts can also result in
reoxidation of reduced S (Wasik et al.. 2015) and can contribute to Hg methylation
hotspots upon re wetting and restoration of anaerobic aquatic conditions.
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12.2.2
Deposition and Sulfur Stores
In terrestrial ecosystems, atmospheric deposition of S at levels below amounts that trigger
acidification may still induce biochemical effects. These effects were described in the
2008 ISA including nutrient enrichment of plants, increased S storage in soils, and
elevated sulfate concentrations in water leaching from soils. New information regarding
the effects of S deposition upon terrestrial biogeochemical cycling is sparse, but can be
found in Chapter 4. Terrestrial plant productivity is commonly limited by N, so SOx
deposition at levels low enough to provide S enrichment without associated acidification
effects is unlikely to have significant effects upon terrestrial plant productivity. Instead,
the nonacidifying effects of SOx deposition are strongest in freshwater systems such as
wetlands and lakes, where hydrology controls storage and release of S.
Changes in water availability and water levels in aquatic systems alter the S cycle, and
may release additional S to the aquatic environment from storage in sediment. During a
drought at Little Rock Lake in Wisconsin, lake sulfate concentrations increased
0.18 mg/L/yr, from 1.5 mg/L in 1998 to 2.9 mg/L in 2006 ("Watras and Morrison. 2008).
During this time period, lake water volume decreased only 30%, which would not
account for the 93% increase in water sulfate concentration, suggesting that drought
released additional S stored in lake sediment or biomass into the water column. Watras
and Morrison (2008) calculated that an additional load of 5 kg S/ha/yr from internal
ecosystem sources of S would account for the increase of S in Little Rock Lake,
Wisconsin. In the S addition experiment at the S6 bog in Marcell Experimental Forest,
Minnesota (see Section 12.4.1). rewetting of the bog after a drought released a pulse of
sulfate into surface water in both control and experimental S addition plots. In plots to
which 32 kg S/ha/yr had been added, concentrations of sulfate in peat pore water after the
drought were 438% higher than in control plots (Wasik et al.. 2012). indicating that S
addition decreases the retention of S in drought-stressed wetlands (Table 12-1). This is
particularly important as intensification of drought frequency and severity is one of the
possible effects of climate change, and suggests that climate change and SOx deposition
may synergistically contribute to increased sulfate concentrations in surface water and
associated water quality impairment.
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12.2.2.1 Summary Table
Table 12-1 New studies on nonacidifying sulfur effects on sulfur cycling.
Type of
Ecosystem
Additions or Load
(kg S/ha/yr)
Biological and
Chemical Effects
Study Site Study Species Reference
Bog Ambient S deposition:
5.5 kg/ha/yr (mid 2000s) as
quantified at NADP site
MN16
S addition: 32 kg S/ha/yr
dissolved in pond water and
delivered by sprinklers
(mimics 4x the 1990s
deposition rate)
Following 2007
drought, pore water
SO4 concentrations
were 438% higher in
experimental
treatment.
S6 peatland,
bog section,
Marcell
Experimental
Forest,
Minnesota
Wasik et al.
Pore water,
peat, and Culex (2012)
spp.(mosquito)
larvae
ha = hectare; kg = kilogram; NADP = National Atmospheric Deposition Program; S = sulfur; S04 = sulfate; yr = year.
12.2.3 Sulfide Phytotoxicity
Wetland ecosystems are characterized by occasional or total soil inundation, and typically
include water and sediment zones with low oxygen levels. Under low-oxygen conditions,
sulfate can be used as an electron acceptor by a number of microorganisms during
decomposition of organic C, and is quickly converted to sulfide. Sulfide inhibits plant
root nutrient uptake at high levels [>34.1 mg/L or >1 mM; Koch et al. (1990)1. and
sulfide toxicity due to increased sulfate loads was documented by the 2008 ISA and
references therein for wetland plants including Carex spp., Juncus acutiflorus (not native
to or documented in North America), Galium palustre (endangered in Ohio, special
concern in Tennessee), Gramineae, as well as the aquatic macrophytes Stratiotes aloides
(listed as an Class C noxious weed in Alabama, Class 1 prohibited aquatic plant in
Florida) and Elodea nuttallii (threatened in Kentucky, special concern in Tennessee).
More recent research confirms sulfide toxicity in wetland habitats, and suggests that
sulfide toxicity can determine plant community composition in freshwater wetlands. A
recent study sampled pore water chemistry and plant community composition in Junius
Pond Fen, Seneca County, New York, and found that sulfide concentrations (range: not
detectable to 5.73 mg/L or 168 |iM H2S) had negative effects on the plant community.
Sulfide concentration was negatively correlated with total plant cover, and had strong
effects on the cover of the dominant plants in the fen (Simkin et al.. 2013). In models,
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high sulfide concentrations decreased cover of the moss species Campylium stellatum,
decreased cover of the monocot and USDA-classified (USDA. 2015b) wetland obligate
Eleocharis rostellata (endangered in Florida and Pennsylvania; threatened in Illinois,
Minnesota, and Wisconsin; sensitive or special concern in Rhode Island and
Washington), and decreased cover of obligate monocot Cladium mariscoides
(endangered in Pennsylvania). Sulfide concentrations also correlated negatively with
dicot diversity (Simkin et al.. 2013). This study shows that sulfide toxicity effects on
sensitive plant species can cascade to affect plant community composition in fens.
Sulfide toxicity has been proposed as an important causal factor in the expansion of
Typha domingensis (southern cattail) in the Florida Everglades. Southern cattail is
displacing the historically dominant sawgrass, Cladium jamaicense, which is the
keystone species in the Everglades sawgrass prairies and which has minor agricultural
importance as a food source for small mammals and water birds (reported in. Everitt et
al.. 1999). In a hydroponic greenhouse study of both species, cattails had a higher
tolerance for sulfide in all plant metrics measured. Sulfide concentrations in growth
media were 0, 7.5, 15.7, 23.5, 31.4 mg/L sulfide (reported as 0, 0.22, 0.46, 0.69, or
0.92 mM). At 7.5 mg/L sulfide, sawgrass leaf elongation rates decreased 49%, at
15.7 mg/L sulfide net photosynthetic rate decreased 34%, and at 23.5 mg/L, sawgrass
biomass in different compartments decreased 29-41% (Li et al.. 2009). Cattails
experienced sulfide toxicity effects on leaf elongation rates at 23.5 mg/L sulfide (38%
decrease) and on photosynthesis at 31.4 mg/L sulfide (22% decrease), and there were no
effects of sulfide upon biomass at any concentration (Li et al.. 2009). Together, these
results suggest that sulfide toxicity is shifting the competitive balance between these
species away from the dominant species in the Everglades. However, studies that
assessed cattail and sawgrass growth in mesocosms placed across the naturally occurring
sulfate-sulfide gradient in the Everglades (DeBusk et al.. 2015) or in mesocosms with
added sulfate (Li et al.. 2009) have not found effects of sulfide toxicity upon sawgrass.
Under controlled conditions, sulfide toxicity favors cattails over keystone Everglades
species sawgrass, but evidence from field studies in the Everglades ecosystem suggests
that geological or ecological factors not reproduced in the greenhouse may mitigate
sulfide toxicity.
Recent work by the Minnesota Pollution Control Agency (MNPCA) proposes to
incorporate geological and biological factors into water quality regulation in order to
prevent sulfide toxicity to an economically important species. Wild rice (Zizania
palustris) has been protected by the state of Minnesota as ecologically important as food
for waterfowl and economically important as a foraged crop (MPCA. 2015a). The state
first set a standard to protect wild rice in 1973, when the water quality standard was set at
10 mg sulfate/L. In 2011, the state began collecting field samples, conducting
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experiments in hydroponics and mesocosms, and modeling environmental and
experimental data in order to revise the standard. The previous standard of
10 mg sulfate/L would only protect 58% of current wild rice sites from sulfide toxicity
(MPCA. 2015a). In March 2015, the Minnesota Pollution Control Agency (MPCA)
released its recommendations ( IPC A. 2015a). Based on the new analyses, the MPCA set
a sulfide concentration threshold of 0.165 mg sulfide/L in sediment pore water to protect
wild rice, based on 2011-2013 monitoring of 112 Minnesota water bodies in which this
level of sulfide corresponded to a 10% decrease in the probability of the species being
present (MPCA. 2015b). Sulfide is the end product of microbial sulfate reduction, which
is heavily dependent upon other environmental factors, particularly DOC, and sulfide
phototoxicity depends upon its residence time as a free ion in water, which depends upon
iron concentrations (see Figure 12-3). As a result, the MPCA did not set a single value of
sulfate as a standard to protect wild rice.
High iron levels
in sediment
High organic
-vs_ carbon levels in
sediment
IE
1
organic carbon
bacteria
* ' *
SSjH
sulfide :
>CB>,
Iron in sediment binds to sulfide
and neutral izes it. making it
nontoxic to m Id rice.
Bacteria
In the
sediment
concert
sulfate to
sulfide.
Sulfide is
toxic to
wild rce.
organic carbon
V bacteria
a
sulfide
Oganiccarbon in sediment is
food forthe bacteria^ causing
more sulfide to be produced.
Source: From MPCA (201513).
Figure 12-3 Schematic from Minnesota Pollution Control Agency that
illustrates the mitigating effect of iron upon toxicity of sulfide, and
the stimulatory effect that organic carbon has on sulfide
production. "These processes form the basis for the state's
proposed sulfate standard for wild rice water bodies."
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Instead, MPCA established a formula that would allow protective sulfate thresholds to be
calculated for all wild rice-producing water bodies based on sediment organic carbon and
sediment iron concentrations in each water body [Source: (MPCA. 2015b)I:
Sulfate = 0.0000136 x Organic Carbon-1-410 x Iron1956
Equation 12-1
The range in sulfate values that protect wild rice from sulfide toxicity in Minnesota water
bodies is from 0.4 to >200 mg sulfate/L. This proposed standard will require large-scale
sediment sampling to determine sediment pore water DOC and Fe concentrations in
Minnesota water bodies, and is still under review. These regulatory efforts determine
protective surface water sulfate concentrations on the basis of a sulfide phytotoxicity
threshold protective of wild rice.
Sulfide phytotoxicity as a result of SOx deposition alters freshwater wetlands and lakes,
but is unlikely to affect coastal wetlands. Seawater contains high concentrations of sulfate
[1 ppt seawater contains 750 (.iM or 72 mg/L sulfate according to Hackney and Avery
(2015)1. and as a recent study in the Cape Fear Estuary, North Carolina, demonstrates,
seawater intrusion and sulfate-reducing conditions structure the distribution of tidal
marsh and tidal swamp zones in the estuary. Specifically, tidal marsh plants are salt- and
sulfide-tolerant, and occur in the Estuary in areas where sulfate reduction is the dominant
microbial mineralization process more than 50% of the time (Hackney and Avery. 2015).
Tidal swamp plants were sensitive to and negatively affected by saltwater intrusion over
the decade-long course of the study. This study suggests a biologically plausible link
between sulfide increases caused by SOx deposition and tidal marsh intrusion upon tidal
swamp zones. However, the authors did not consider sulfate as originating from any
source other than seawater, so the effect of salinity could not be separated from the effect
of sulfate reduction and resultant sulfide phytotoxicity. There is no evidence of SOx
deposition contributing to sulfide phytotoxicity in wetland and aquatic ecosystems with
significant seawater contributions.
12.2.4 Internal Eutrophication
Internal eutrophication occurs in saturated soils in freshwater wetlands and lakes when
sulfate addition results in the release of bioavailable phosphate from soil forms that are
not bioavailable. Additional sulfate in surface waters can increase P mobility and cause
internal eutrophication of the recipient ecosystem; farmers growing sugarcane in the
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oxidized peatland soils of the Florida EAA use S as a soil amendment for this reason (Ye
et al.. 2010).
Wetland and aquatic systems often retain phosphate in Fe(PC>4)3. When sulfate is
reduced, the resultant sulfide binds with iron to create FeS, which precipitates out of
solution, releasing 3 molar equivalents of P for each S added (Figure 12-4). This internal
eutrophication can alter plant community composition (U.S. EPA. 2008a). or can speed
the accretion of organic matter and infilling of the wetland, reducing wetland habitat
(Kleeberg et al.. 2016). Water and sediment mesocosms of samples collected from Lake
Moshui in China showed that sodium sulfate addition to raise sulfate concentrations to
500 mg/L also raised peak [P] by 180% in the water column, and by 210% in the
sediment pore water, above unamended control mesocosms, and the peak [P] with sulfate
addition occurred a week later than in control mesocosms (Yu et al.. 2015). Sulfate
addition can alter P dynamics and cause eutrophication in freshwater systems.
edu*00
sulfate
oxidation
reduction
sulfide
Fe(ll) = iron (II); Fe(lll) = iron (III); FeSx = iron-sulfide complexes; P043 = phosphate.
Open boxes indicate pore water components, and shaded boxes indicate solid phase chemistry. Reduction reactions are indicated
by solid arrows, oxidation reactions are indicated by dotted lines, and phase changes (precipitation or dissolution) are indicated by
dashed lines.
Source: From Simkin et al. (2013).
Figure 12-4 Mechanisms of linked sulfur, iron, and phosphorus cycling in
wetland waters and soils.
Surface water sulfate may decrease heavy metal bioaccumulation in plants, but the
implications of this process for impacts of SOx deposition may be limited. Sulfate
addition can decrease the accumulation of toxic elements in aquatic plants. In separate
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soil, S addition decreased dissolved arsenic (As) concentrations in soil solution, but
increased As(III):As(V), although the researchers suggested that the formation of
As-Fe-sulfide minerals prevented plant As uptake. In microbially spiked soil mesocosms,
the addition of SRB had a stronger stimulatory effect on As(III):As(V) than did S
addition. In rice mesocosms, S addition decreased As concentrations in rice roots and in
the iron plaques on roots (Jia etal.. 2015). In laboratory mesocosms, accumulation of
selenium (Se) in aquatic plants was a function of both sulfate and Se concentrations in
water, but increasing sulfate concentrations decreased Se concentrations in both Lemna
minor (aquatic macrophyte) and Pseudokrichneriella subcapitata [unicellular green alga
(Lo et al.. 2015)1. Sulfate in surface waters may slow bioaccumulation of heavy metals in
biota by forming relatively insoluble S-metal complexes and preventing metal uptake by
aquatic plants. However, these findings may have limited applicability to SOx deposition.
If there is a common source of both SOx and heavy metal deposition to an aquatic
environment, it is unlikely that deposition will correlate with decreasing metal
bioavailability. Also, mercury is a focus of research into heavy metal environmental
transformations and bioavailability, and SOx deposition is linked instead to increased
bioaccumulation of Hg (see Section 12.3 to Section 12.7). There is no research on how
SOx deposition affects Se or As accumulation in plants growing under field conditions.
12.2.5 Sulfur Effects on Methane Emissions
The 2008 ISA documented the suppression of methane emissions from aquatic and
wetland ecosystems in response to increases in sulfate concentrations. When sulfate is
added to freshwater systems, SRPs outcompete methanogens, and methane emissions are
suppressed. The activity and environmental preferences of SRPs are key to understanding
the effects of SOx deposition upon methane and MeHg production. Under anaerobic
conditions, SRPs and methanogens compete for organic C as a metabolic substrate, and
the reactions of sulfate reduction coupled with organic C oxidation are
thermodynamically favored over the reactions of methanogenesis (Paulo et al.. 2015).
However, in many anaerobic environments, sulfate is in short supply, and methanogens
are more active than SRPs in mineralizing organic C. Sulfate addition may swing the
competitive balance back towards SRPs, decreasing methane production in saturated soils
and surface waters.
The relative primacy of methanogens versus SRB in oxidizing carbon is one of the
factors which distinguishes freshwater from coastal wetlands and water bodies. Older
literature suggests that when SOx deposition is not a factor, methanogens dominate
anaerobic decomposition in freshwater systems (including wetlands), with
methanogenesis responsible for 72-82% of organic C mineralization at the ELA, Ontario
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(Rellv and Rudd. 1984). and methanogenesis responsible for 4 times the electron flow
and organic C mineralization of sulfate reduction in Lake Mendota, Wisconsin
(Ingvorsen and Brock. 1982). In estuarine and marine ecosystems, on the other hand,
SRPs are the dominant anaerobic decomposers. In the saltwater marshes at Kirkpatrick
Marsh, Maryland, methanogenesis is <10% of C mineralization, and sulfate reduction is
responsible for 45-85% of total C mineralization in the summer, and 5-25% of C
mineralization in the fall (Mitchell and Gilmour. 2008). Older research suggests that in
pristine ecosystems, methanogens dominate anaerobic C mineralization in freshwater
systems.
New research on microbial communities in saturated sediments contributes to the
biological plausibility of the reduction in methanogenesis established by the 2008 ISA
(see Table 12-2). Adding sulfate to freshwater systems can depress methanogenesis
because anaerobic C mineralization by SRPs is energetically favored when sulfate and
acetate are available at the sediment surface (Urban etal.. 1994). Newer work also
supports this finding. Twitchell Island is a restored wetland in the San Joaquin delta,
California, where researchers sampled sediments and water along a gradient of
decreasing riverine S load (14-8 mg sulfate/L in February) from the wetland inlet to a
transitional site to an interior marsh site. In summer, sulfate was 60% lower and methane
emissions were 110% higher at the interior site than at the inlet, and 16S rRNA
sequencing confirmed that relative SRP abundance was negatively correlated with
methanogen abundance [r = -0.67, r2 = 0.45 (He et al.. 2015)1. In the Everglades WCA,
Florida, there are similar gradients of S loading from agricultural runoff in the freshwater
marsh, and sampling at sites F4 (7.1 mg/L or 74 (jM sulfate in pore water), U3 (3.7 mg/L
or 39 |iM sulfate), and W3 (<0.4 mg/L or <4 (j,M sulfate), found effects of sulfate upon
SRB (sulfur-reducing archaea were not sampled) and methanogens (Bae et al.. 2015).
SRB abundance increased with increasing sulfate pore water concentrations across the
three sites, and was 6.9 times higher at U3 and 16.8 times higher at F4 than at W3.
Sulfate also affected the competitive interaction between SRB and methanogens, which
had equal abundances at the most pristine W3 site. At the sites with higher S loads, SRB
were 60-80% more abundant than methanogens. The relative abundance of methanogens
was determined by copy number of the mcrA gene in environmental samples, which
correlated positively with methane production rates and mRNA (Bae et al. 2015). so
sulfate loading alterations to the microbial community in the Everglades WCA may also
be lowering methane emissions. Sampling from natural microbial communities confirms
that sulfate favors SRB over methanogens.
A laboratory study with controlled redox conditions and microbial communities suggests
that even when SRB and methanogens are not in direct competition for anaerobic C,
methanogen activity will increase when sulfate concentrations decrease. In an incubation
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of water and sediment collected from oligotrophic Lake Stechlin, Germany, researchers
were able to create fluctuating redox conditions while continuously sampling the water
column. When the system was reduced, expression of the dsrB gene (present in SRB)
increased, and sulfide concentrations increased, indicating that SRB abundance and
activity increased in response to anoxic conditions in the water column (Frindte et al..
2015). Methane also increased in the water column, indicating no competition between
SRB and methanogens in this system. Over time, dsrB diversity decreased, and
expression ofpmoA (present in methanogens) increased (Frindte et al.. 2015). indicating
that although there was no competition between SRB and methanogens, methanogens
were able to persist after SRB had exhausted the available sulfate and diminished in
abundance. Active methanogenesis occurs when SRB activity is constrained by low
sulfate availability. Reductions in SOx deposition could increase methanogen activity
typical of wetland and aquatic sediments.
As with sulfide phytotoxicity, impacts of SOx deposition upon methanogenesis may be
present in freshwater but not marine ecosystems, as the high endogenous concentration of
sulfate in seawater is likely to overwhelm the impact of anthropogenic S. In marine
sediments, sulfate reduction accounts for 50-100% of anaerobic carbon mineralization
(Urban et al.. 1994); methanogenesis often persists at depths in organic sediments below
the depth to which sulfate can diffuse. In estuarine wetlands in the Cape Fear River
system in North Carolina, Hackney and Avery (2015) stated that in vertical soil profiles,
a concentration of 28 mg/L (300 (jM) sulfate was the threshold where S reduction
switched to methanogenesis as the dominant form of C mineralization. This study also
determined that in estuaries, the transition from methanogenic to S reducing conditions
occurs when more than 25% of tidal flooding carries more than 1 ppt of seawater
(Hackney and Avery. 2015). In a study of the Min River Estuary in China, there was no
relationship between methane emissions and pore water sulfate, but dominant plant
species did affect microbial communities, with lower relative abundance of both
methanogens (84% decrease) and SRPs (73% decrease) in Spartina alterniflora
sediments than in Phragmites australis-associated sediments (Tong et al.. 2015). Both of
these species are dominant plants in North American eastern coastal marshes, and this
result suggests plant community may be more important than sulfate deposition in
determining methane emissions in coastal marshes. SOx deposition is unlikely to affect
methane emissions from coastal marshes and water bodies.
Sulfate addition may also result in lower methane emissions by stimulating microbial
methane oxidation. In marine sediments, this occurs in syntrophic associations
(associations among heterotrophs dependent on the metabolic byproducts of other
microbes) between anaerobic methanotrophic archaea and SRB, which pair anaerobic
oxidation of methane with sulfate reduction, or in a clade (monophyletic group) of
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anaerobic methanotrophs capable of both sulfate reduction and methanotrophy (Jove.
2012). However, these processes have been observed only in marine deep-sea sediments,
and it is not yet clear how widely distributed or important they are in other systems.
12.2.5.1 Summary Table
Table 12-2 New studies on nonacidifying sulfur effects on methane emissions.
Type of Additions or Load Biological and Chemical
Ecosystem (kg S/ha/yr) Effects Study Site
Study Species
Reference
Restored
peatland
island in
river
River water is the
source of the S
load, more interior
sites have lower S
load, as reflected
by Feb. sediment
surface
measurements:
Inlet [S042"]
14 mg/L;
Transitional [SO42"]
11.5 mg/L;
Interior [SO42"]
8 mg/L
SRP abundance decreases
with increasing methanogen
abundance (r= -0.67).
Denitrifier abundance
decreases with increasing
methanogen abundance
(r= -0.64).
In August, sulfate decreases
60% from inlet to interior, and
methane emissions increases
110%.
SRP relative abundance
increases with sulfate
concentration (r= 0.96).
Twitchell
Island, San
Joaquin
delta,
California
Island covered with
Typhus spp. and
Schoenoplectus
acutus, sampled at
inlet, transitional,
and interior marsh
sites
Microbial community
quantified by 16S
rRNA sequencing of
peat sample
He et al.
(2015)
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Type of Additions or Load Biological and Chemical
Ecosystem (kg S/ha/yr) Effects Study Site Study Species Reference
Coastal salt Total load = not
marsh measured
Deposition = not
measured
No significant correlation
between potential methane
emissions and pore water
S042", NOs", and Fe3+.
Shanyutan, Zones of Chinese Tonq et al.
Min River native Phragmites (2015)
Estuary, australis, Chinese
China invasive (American
Methanogen abundance is
84% lower in S. alterniflora
than in P. australis marsh.
native) Spartina
alterniflora, and
Cyperus
malaccensis
(subtropical species
not present in U.S.)
SRP abundance is 73% lower
in S. alterniflora than in P.
australis marsh.
Methanogenic
archaea quantified
using 16S rRNA
Methanogen abundance
increases with pore water
NO3" concentrations:
Methanogens (1,000 gene
copies/g
soil) = 0.3468 + 0.8149
(|jM NOs").
SRPs are quantified
using dsrA gene
16S rRNA = 16S ribosomal ribonucleic acid Fe3+ = iron; g = gram; ha = hectare; kg = kilogram; L = liter; |jM = micromolar;
mg = milligram; N03" = nitrate; S = sulfur; S042" = sulfate; SRPs = sulfur-reducing prokaryotes; yr = year.
The 2008 ISA found the evidence was sufficient to infer a causal relationship between S
deposition and increased methylation of Hg, in aquatic environments where the value of
other factors was within adequate range for methylation. Recent research as well as key
early papers on the microbial methylation of mercury are summarized in this section.
New evidence is consistent with the 2008 ISA in identifying sulfur-reducing bacteria as a
biotic link between increased SOx deposition and increased MeHg concentrations in the
environment and in biota. New developments since 2008 include identification of
microbial genes linked to mercury methylation, and the identification of methylation
capability in certain archaeal strains (Section 12.3.1).
Ecosystem areas with high MeHg fractions (as a fraction of total Hg) are considered to
indicate active microbial methylation, as well as places where primary producers and
animals are at an elevated risk of MeHg accumulation. An active area of research is in
identifying areas or zones of ecosystems where %MeHg is elevated (Section 12.3.2V
Background information on deposition and biogeochemical cycling of Hg, with particular
emphasis on identifying hotspots of mercury methylation, is presented in Appendix B.
12.3 Mercury Transformations
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Mercury methylation is a microbial process carried out by a subset of prokaryotes that are
active under reducing environmental conditions (anoxic water or sediments) while
requiring oxidized sulfur and organic C as substrates. As a result, Hg methylation rates
are heterogeneous across time and the landscape. Transformation by bacteria and archaea
from inorganic Hg2+ to organic MeHg occurs in wetland soils; in Sphagnum mats of
wetlands; and at the oxic-anoxic boundary in lakes, estuaries, and the Arctic water
column. Hg methylation by SRB embedded in periphyton is a new topic that was not
covered in the 2008 ISA (Section 12.3.3). Evidence of MeHg production in periphyton
has important implications for aquatic MeHg concentrations, as periphyton may extend
throughout water columns and are more connected to aquatic and terrestrial food chains
than are Hg methylation hotspots in sediment or peat. Regardless of their location within
the ecosystem, microbial Hg methylators have specific environmental requirements
which affect their rates of Hg methylation (Section 12.3.4). New evidence is consistent
and coherent with the conclusions of the 2008 ISA that the body of evidence is
sufficient to infer a causal relationship between S deposition and increased
methylation of Hg in wetland and equatic ecosystems where the value of other
factors is within adequate range for methylation.
12.3.1 Microbial Mercury Transformation
The 2008 ISA attributed Hg methylation to sulfur-reducing bacteria, and there is new
evidence of the link between microbial sulfate reduction and Hg methylation. New (and
key older) studies include experimental inhibition of different microbial groups in order
to demonstrate microbial mechanisms, molecular sequencing techniques to identify
potential microbial Hg methylating strains, and sequencing of environmental or
experimental samples to determine microbial dynamics of Hg methylation. These studies
were conducted with samples from rivers, lakes, wetlands, and laboratory mesocosms
(Table 12-3).
Increasing SOx in the microbial environment increases the metabolic activity and growth
of sulfate reducers, and one of the metabolic activities that can be stimulated is the
methylation of Hg. Sulfate-reducing prokaryotes (SRPs; bacteria and archaea) and
iron-reducing prokaryotes are primarily responsible for Hg methylation in natural
ecosystems. On a broad scale, these bacteria metabolize organic C by pairing its
oxidation with the reduction of sulfate and/or Fe3+. The sulfide produced by the reduction
of SOx can act as a negative feedback on SRP activity and Hg methylation. SRPs that
have demonstrated environmentally significant Hg methylation rates are obligate
anaerobes, meaning that they are active only in low-oxygen environments. This limits the
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presence and activity of SRPs within wetland and freshwater ecosystems to zones with
low oxygen availability.
Specific inhibition of SRPs using molybdate (M0O42 ) is a common tool in studies that
determine the contribution of SRPs to Hg methylation. An older study of acidic Dickie
Lake in Ontario used different microbial inhibitors to determine whether SRPs or
methanogens within the sediments were responsible for Hg methylation. Molybdate
inhibited sulfate reduction and decreased %MeHg by 75% of production in controls,
while 2-bromo-ethanesulfonate (BESA), an inhibitor of methanogens, did not
significantly decrease MeHg production (Kerry et al.. 1991). Researchers inferred that
SRPs, not methanogens, were responsible for methylation in the lake, and sulfate
reduction rates increased 0.35 mg sulfate reduced/L/day with a 1 mg/L increase in sulfate
addition. However, additions of sulfate to concentrations of 5-25 mg sulfate/L in
sediment slurries did not affect %MeHg, which was 0.20-0.25% MeHg/g sediment
(Kerry et al.. 1991). A similar relationship between MeHg and sulfate reduction was
demonstrated using molybdate inhibition in coastal Georgia marsh soils, where Mo
addition decreased sulfate reduction by 90% and decreased MeHg production by 85%
(Kina et al.. 1999). indicating that SRPs were involved in both processes.
An early laboratory study cultivated strains of a SRB, a methanogen, or an acetogen with
an Hg spike. The SRB was the only species that methylated added Hg, and it did so at a
rate that resembled the rate in aquatic sediments, while molybdate inhibited MeHg
production and demethylation of added MeHg (Pak and Bartha. 1998). In a more recent
study, incubations of St. Lawrence River sediments with different inhibitors showed that
molybdate inhibited sulfate reduction completely, but did not affect methane production
(Avramescu et al.. 2011). indicating that methanogens did not play an important role in
reducing S. Moreover, sulfate reduction rates were strongly positively correlated with
potential Hg methylation rates (r2 = 0.98). However, when methanogens were inhibited,
methylation of Hg increased 16% (Avramescu et al.. 2011). indicating that methanogens
compete with SRPs and can depress Hg methylation. In Everglades, Florida sediment
incubations, molybdate decreased MeHg production by 90% (Gilmour et al.. 1998). In
incubations of Sphagnum sampled from Sunday Lake, New York, molybdate decreased
MeHg production by 44% (Yu et al.. 2010). In core incubations from lakes in Wisconsin,
including both basins of Little Rock Lake, molybdate reduced MeHg production by 50%
(Gilmour et al.. 1998).
The identification of the gene pair conferring the ability to methylate Hg occurred
recently, after the 2008 ISA. No ecological or evolutionary advantage of the ability to
methylate Hg has been established (Kerin et al.. 2006; Benoit et al.. 2003). and it appears
to be an inadvertent transformation by a corrinoid-dependent protein produced by
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prokaryotes for a different metabolic pathway (Gilmour et al.. 2013). Recent
phylogenetics work indicates that the gene pair hgcAB confers the ability to methylate
Hg, and that the gene pair and Hg methylation are present in some but not all species
within the SRB, iron-reducing bacteria, syntrophic sulfur reducers in the
Syntrophobacterales, methanogens in the Archaea, and bacteria in the Clostridia
(Gilmour et al.. 2013). The confirmed and predicted Hg methylators from this study
occur across alkaline, neutral, or acidic environments, and are mostly heterotrophs that
use sulfate, iron, and CO2 as terminal electron acceptors.
MeHg production rates vary among species, and even among strains within species (Shao
et al.. 2012). A recent study of hgcAB in the freshwater marshes of the Florida Everglades
showed that syntrophs dominated the microbial methylators (49-65% of sequences) and
also were the dominant sulfate reducers, as shown by dsrB mRNA quantification
(75-89%) of sediments sampled within the water conservation areas (Bae et al.. 2014). In
a recent study of methylation using a strain of Desulfovibrio dechloroacetivorans,
expression of the hgcAB gene did not correlate with methylation capacities of pure
cultures, which supports the supposition that Hg methylation is not the main purpose of
the proteins encoded by hgcAB. However, during the exponential growth phase of the
cultures, addition of 2,900 mg/L (30 mM) sulfate increased net MeHg production by 50%
(Goni-Urriza et al.. 2015).
Demethylation is also an important microbial Hg transformation to consider in natural
ecosystems. The capacity to transform MeHg to inorganic Hg (elemental Hg or Hg2+) is
widely distributed and occurs by different mechanisms in different microbial groups.
Microbial demethylation by aerobic and facultative Hg-resistant microbes possessing the
mer operon break MeHg into methane and Hg° via reductive degradation, whereas
methanogens, SRPs, and other prokaryotes break MeHg into carbon dioxide, methane,
and Hg2+ via oxidative demethylation. A recent study of St. Lawrence River, Ontario,
Canada sediments showed that methane production in sediment slurries correlated
positively with demethylation rates (r2 = 0.61), and direct inhibition of methanogens
decreased demethylation by 83% (Avramescu et al.. 2011). An earlier study tested a pure
culture of the archaea Methanococcus maripaludis and found that it demethylated added
MeHg despite no observed methylation potential (Pak and Bartha. 1998).
Microbial demethylation also occurs in the same prokaryotes that methylate Hg; a
laboratory incubation of pure cultures demonstrated that Desulfovibrio desulfricans (an
SRB that methylates Hg) demethylated added MeHg at rates similar to those of incubated
aquatic sediments (Pak and Bartha. 1998). In the same study of sediments of the St.
Lawrence River, Ontario, inhibition of both SRPs and methanogens decreased
demethylation of Hg by 96% (Avramescu et al.. 2011). indicating that while
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1 methanogens are responsible for the bulk of demethylation in these sediments, SRPs are
2 involved in demethylation.
3 New evidence of the genetic basis of Hg methylation and the activity of microbial
4 methylators in the environment and in the lab is consistent with the 2008 ISA's link
5 between sulfate-reduction and Hg methylation.
12.3.1.1 Summary Table
Table 12-3 New studies on nonacidifying sulfur effects on microbial
communities.
Type of
Ecosystem
Additions or
Load (kg
S/ha/yr)
Biological and Chemical Effects Study Site
Study
Species
Reference
Freshwater W3 pore water SRB abundance was 6.9x higher F4, U3, and W3 Methanogens Bae et al.
marsh
[SO42 ] 24 |jM in U3 than W3 and 16.8x higher in sites in Water as quantified (2015)
U3 pore water
[SO42"] is 39 |jM
F4 pore water
[SO42"] is 74 |jM
Deposition = not
measured
F4.
In W3, abundance of SRB and
methanogens are not significantly
different. In U3, SRB abundance is
80% higher than methanogen
abundance. In F4, SRB
abundance is 60% higher than
methanogens.
mcrA copy number correlates
positively with mRNA and methane
production rates.
Conservation
Area,
Everglades,
Florida
by mcrA
copies
Sulfur-
reducing
bacteria as
quantified by
dsrB copies
Acetotrophic methanogens are
dominant at W3, while at high S
U3 and F4 sites, hydrogenotrophic
methanogens are dominant.
Marine Lab cultures with
different C
sources
(pyruvate,
fu ma rate,
lactate, ethanol,
or malate),
control and
additional sulfate
(30 mM)
Methylation increases with
increasing bacterial biomass
(r= 0.83).
During exponential growth phase,
S addition increases net MeHg
production by 50%.
hgcAB expression levels do not
correlate with methylation
capacities.
Lab cultures
Sediments from
Berre Lagoon,
France
Desulforibrio
dechloroaceti
vorans, strain
BerOCI from
sediments
Goni-Urriza
et al. (2015)
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Additions or
Type of Load (kg Study
Ecosystem S/ha/yr) Biological and Chemical Effects Study Site Species Reference
C = carbon; ha = hectare; kg = kilogram; MeHg = methylmercury; mM = millimolar; |jM = micromolar; S = sulfur; S042" = sulfate;
SRB = sulfur-reducing bacteria; yr = year.
12.3.2 Zones of High Methylmercury Fractions across the Landscape
The 2008 ISA described watersheds with low pH waters and high wetland cover as
sensitive to Hg methylation, but did not describe MeHg fraction in the environment as an
indicator of Hg methylation. MeHg is bioavailable and bioaccumulates within organisms
due to the strong complexes it forms with thiosulfate groups in organic molecules. The
fraction of total Hg which is in the form of MeHg (or %MeHg) is used as an indicator of
bioavailable Hg within an ecosystem. New studies (as well as key older studies) of MeHg
fractions in watersheds, streams, lakes, and wetlands show the link between S deposition
and MeHg fraction in water and sediments, and confirm the importance of wetlands and
nonurban watersheds as sources of MeHg to aquatic ecosystems.
Aquatic and wetland ecosystems which have received high loads of S generally have
higher MeHg fractions. In sampling of Little Rock Lake and four nearby lakes in
Wisconsin, MeHg fractions in lake water ranged from 6-25% MeHg, with no
relationship to pH (Bloom et al.. 1991). Nutrient availability—the relative availability of
nitrogen (N) and P as well as of S—can impact MeHg fraction, with low or intermediate
levels of nutrients most conducive to higher MeHg across two very different nutrient
gradients. In seven wetlands across a nutrient gradient in Sweden, total Hg was
113-287 ng/g in soils, and MeHg was 3.5-21 ng/g in soils, and the highest MeHg
fraction was 16%. Potential methylation rate constants and MeHg fractions were highest
at wetlands with an intermediate nutrient status (Tierngren et al.. 2012). In the Florida
Everglades WCA, a gradient of nutrient eutrophication (N, P, and S) from agricultural
runoff runs from northeast to southwest across the WCA, with sulfate concentrations
around 4.8 mg/L (reported as 50 (j,M) in southern, less disturbed sites (Gilmour et al..
1998). Sediment Hg increased from north to south by a factor of 3-4, and MeHg
sediment concentrations increased across the same gradient by a factor of 25 (Gilmour et
al.. 1998V
Two studies that sampled MeHg fractions at different locations within the U.S. provide
information at the landscape level about factors that increase probability of detrimental
effects upon wildlife due to Hg availability. There is large variability across systems in
MeHg fraction. In a study of five forested watersheds distributed across the U.S. (in
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Vermont, Wisconsin, Colorado, Georgia, and Puerto Rico), total Hg flux out of the
watershed in the streams was highest at Rio Icacos, Puerto Rico (54,400 ng Hg/m2/yr,
reported as 54.4 |ig Hg/m2/yr) and lowest at Allequash Creek, Wisconsin
[250 ng Hg/m2/yr or 0.25 |ig Hg/m2/yr (Shanlev et al. 2008)1. MeHg fraction was highest
at Allequash Creek (14.8% of total Hg) and lowest at Rio Icacos (0.7%), indicating that
watershed flux of total Hg does not directly indicate risk to organisms (Shanlev et al..
2008). In a study of eight streams in Oregon, Wisconsin, and Florida, MeHg fractions and
concentrations (range: <0.01-17.8 ng/g sediment) in streambed sediments were higher in
nonurban than in urban streams (Marvin-PiPasquale et al.. 2009).
Wetlands tend to have higher MeHg fractions than other water bodies at similar locations
and order within watersheds. In the watershed around Sunday Lake in the Adirondack
Mountains, New York, sampling of soils and substrates (upland, riparian, open water,
peat bog) at different points in the watershed found that the highest MeHg fraction was in
Sphagnum mats (Yu et al.. 2010). In a survey that included 21 freshwater, brackish, and
marine wetlands and lakes in the Mississippi River delta near Lake Pontchartrain,
Louisiana, MeHg levels in wetlands were higher than in nearby rivers or lakes with
similar salinity levels. In brackish and freshwater wetlands, total MeHg concentrations
(ng/L) and MeHg fraction (MeHg/total Hg) were twice or three times as much as in
brackish or freshwater rivers (Hall et al.. 2008).
12.3.3 Methylmercury in Periphyton
The 2008 ISA did not address the role that periphyton play in hosting SRPs and boosting
Hg methylation rates within the oxic water column of aquatic and wetland ecosystems.
This section summarizes new (and key older) papers that demonstrate that SRB in
periphyton methylate Hg in South American lakes as well as North American lakes and
wetlands. Periphyton are ecologically important as they form the basis of the aquatic food
web for many invertebrates and vertebrates. Periphyton mats are biofilms of algae,
bacteria, fungi, microinvertebrates, organic detritus, and inorganic particles, embedded in
a polysaccharide matrix, typically attached to a substrate of sediments or submerged
macrophytes. The microbial communities embedded within the periphyton can be quite
complex and diverse, including autotrophs and heterotrophs, SRB and S oxidizing
bacteria, and methanogens; periphyton microbial composition and microbial activity
depend on site conditions (Correia et al.. 2012). The polysaccharide matrix slows
exchange with the water column while intense aerobic metabolism at the matrix surface
quickly consumes oxygen diffusing into the periphyton, creating anoxic, reducing
microenvironments in the interior of periphyton where anaerobes including SRPs thrive.
In the case of periphyton attached to macrophytes, plant exudates are an important source
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of carbon for periphyton microbes, boosting activity above rates of activity of similar
microbes residing in sediments.
SRPs embedded in periphyton are more efficient in methylating Hg than are SRPs in
sediments. Much of the research demonstrating Hg methylation by periphyton has
occurred in South America, in tropical lakes where the genus Eichhornia (water
hyacinth) is native, and where ambient temperatures can support high levels of bacterially
mediated Hg methylation (Guimaraes et al.. 2006). Eichhornia crassipes is a wetland
plant present in 24 states, and is listed as a noxious or invasive weed by 7 states (USDA.
2015b). Closely related Eichhornia azurea is currently present only in Florida, and is
listed by the Animal and Plant Health Inspection Service of the U.S. Department of
Agriculture (USDA-APHIS) as a noxious weed (USDA. 2015b). In incubations of
chopped Eichhornia crassipes roots spiked with 203HgCl2, net MeHg production was
high, 1.6-30.2% of total Hg (Guimaraes et al.. 2006). Other studies have shown a
similarly wide range of methylation by periphyton, with high rates exceeding sediment
methylation rates. Intact crassipes periphyton incubations had potential methylation of
12.1-25.2% of added Hg, and periphyton isolated from Polygonum densiflorum
[hereafter called by its current accepted scientific name Persicaria glabra; a wetland
obligate plant also native to the U.S., classified as endangered in Maryland and New
Jersey, (USDA. 2015bYI had potential methylation rates of 0.2-36.1 %; by comparison,
sediment from the same tropical lakes produced 6.4-12.5% MeHg in incubations
(Correia etal. 2012).
Mo inhibition of sulfate reduction also inhibits MeHg production in periphyton,
confirming that SRPs are responsible for a significant portion of Hg methylation within
these complex microbial communities. Recently, Acha et al. (2011) and Correia etal.
(2012) collected macrophyte samples from oxbow lakes in the Bolivian Amazon for
inhibition experiments. Incubations with an array of guild-specific inhibitors show the
relative contribution of different microbes to Hg methylation. One set of incubations of
periphyton associated with the roots of E. crassipes or P. glabra suggested that SRB were
the most important component of the periphyton in producing MeHg. Molybdate, an
inhibitor of sulfate reduction, decreased MeHg production by 30% fori?, crassipes and
by 60% for P. glabra (Acha etal.. 2011). indicating that in intact periphyton, SRB alone
are responsible for 30-60% of Hg methylation. Quantitative PCR of bacterial genes
indicated that 3.34% of the total bacterial community in the periphyton belonged to the
SRB families Desulfovibrionaceae and Desulfobacteraceae, and MeHg fraction was
positively correlated with relative abundance of Desulfobacteraceae in P. glabra
periphyton (Acha et al.. 2011). A second set of incubations of six tropical macrophyte
species-associated periphyton confirmed that inhibition of sulfate reduction and SRB
using molybdate decreased MeHg production, but showed that inhibiting both SRB and
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methanogens resulted in a 90% reduction of MeHg production across sediments and
periphyton (Correia et al.. 2012). Algaecide or fungicide additions significantly inhibited
MeHg formation in some but not all incubations, indicating that the microbial
composition or activity varied across periphyton samples, even when they were collected
from the same site or from the same species grown at different sites (Correia et al.. 2012).
Together, these studies show that SRB are important in producing MeHg within
periphyton, but that other microbes residing in the periphyton contribute through poorly
understood mechanisms to total MeHg production.
Mercury methylation by periphyton has also been documented within North American
ecosystems. In an older study in Dickie Lake in Ontario, measured Hg concentrations in
periphyton were 56.5 ng/g, 22 times higher than Hg concentrations in sediments (Kerry et
al.. 1991). A more recent study of periphyton growing in the epilimnion of boreal Lake
Croche in Quebec demonstrated that Hg methylation rates are faster in periphyton,
reaching steady-state in 12 hours, than the 4-8 days to steady state of MeHg production
in sediments (Desrosiers etal.. 2006). MeHg production by periphyton in the boreal lake
was dependent on SRB as well as on photosynthesizers, as demonstrated by inhibition
experiments. Despite the lower temperatures of incubations to reflect the lower
temperatures of the boreal lake, potential MeHg production was 16.6-18.5% (Desrosiers
et al.. 2006). similar to MeHg production in tropical periphyton.
In the Florida Everglades, periphyton are the base of the aquatic food web. In an older
study, incubation of periphyton collected from different sites along the eutrophic gradient
between the EAA to the north and Everglades National Park to the south found MeHg
production in periphyton from all sites, although rates varied widely (Cleckner et al..
1999). MeHg potential production rates were highest in periphyton collected at the
northern, eutrophic site, and MeHg production correlated positively with both S reduction
and S oxidation by photosynthesizing purple S bacteria (Cleckner et al.. 1999).
Periphyton may be an important direct source of MeHg to the food web in the Florida
Everglades.
12.3.4 Other Factors that Control Methylmercury Production
The 2008 causality statement linked S to increased Hg methylation when other conditions
are favorable, with a particular emphasis on dissolved organic carbon (DOC) as a control
on Hg methylation (U.S. EPA. 2008a). This section is an overview of factors other than S
that control Hg methylation. There are seasonal patterns of Hg methylation and transport
of Hg in many systems which can affect MeHg accumulation. There are also a number of
chemical constituents that stimulate or inhibit Hg methylation. Given our limited
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understanding of the microbial mechanisms of Hg transport and methylation, and the
complexity and diversity of aquatic environments, chemical controls on MeHg processes
are not fully established. This section is meant to lend context to the description of how S
deposition affects methylation, but is not a complete review of the chemical controls on
biological Hg methylation in natural environments.
12.3.4.1 Seasonality and Temperature
The 2008 ISA did not describe temperature or seasonal effects on Hg methylation. This
section presents information from key older papers and recent research on temperature
effects in lakes, wetlands, and watersheds. As a microbial process, Hg methylation is
temperature dependent. In Lake Clara, Wisconsin, incubation at in situ temperatures of
seasonally sampled sediment cores from a lake depth of 10.5 m showed that Hg
methylation increased slowly from near 0% in April to peaks of 1% methylation in
August and September, with temperature accounting for 30% of methylation rate
variation (Korthals and Winfrcv. 1987). Demethylation was also measured in incubations
and displayed slightly different seasonal variation; it increased sharply from 1% in May
to 4% in early July, then fell sharply to 1% in late July, staying low for the rest of the
sampling year. As a result, the methylation:demethylation ratio (a predictor of MeHg
concentrations in water) rose above 1 in late July through August, and then again in late
September (Korthals and Winfrey. 1987). Timing of methylation and demethylation
peaks were similar in sediments sampled from a lake depth of 1.0 m, although gross
methylation and demethylation rates were slightly higher (Korthals and Winfrey. 1987V
Sampling across the ELA in Ontario suggests that seasonal patterns of methylation in
lakes are due to seasonal shifts in oxygen availability, as locations and depths within the
lake where methylation was documented in the summer had no methylation potential
when resampled in the fall following turnover (Ecklev and Hintelmnnn. 2006V
Fall mixing of stratified lakes can have significant effects on total MeHg in lake food
chains. In all years of sampling at Lake Onondaga, New York, there was a significant
peak in MeHg concentrations and in MeHg:total Hg ratios in the epilimnion in the fall
following turnover (Todorova et al.. 2014). In Little Rock Lake, Wisconsin, researchers
inferred that considerable demethylation occurred in the fall following mixing because
high MeHg in the summer water column did not accumulate in sediments and was not
reflected in low spring MeHg water column concentrations ("Watras et al.. 2006). Short
weather events can also affect Hg exchange. During the fall of 2006, regular weekly
sampling in Lake Onondaga, New York, captured the effects of strong winds and heavy
rains mixing the stratified layers of the lake upon MeHg dynamics. Dissolved oxygen
values dropped in the sampled surface waters, and MeHg concentrations rose 23% to
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0.236 ng/L in surface waters, even as MeHg concentrations dropped in the hypolimnion
(Todorova et al.. 2014).
There are seasonal patterns of Hg methylation in wetlands as well. In peatlands of
Allequash Creek watershed, Wisconsin, MeHg concentrations and MeHg fraction
(percentage of total Hg) peak in early fall (Creswell et al.. 2008). In freshwater marshes
in the Yolo Bypass, California, seasonal wetland export of MeHg occurs during the
winter as well as the summer. In the summer, newly methylated MeHg is drawn into the
root zone of the sediment by plant transpiration, and in winter, diffusion releases MeHg
from the sediment into the water column (Bachand et al.. 2014). Seasonal changes have
also been documented in the salt and freshwater marshes at Kirkpatrick Marsh on the
Chesapeake Bay, Maryland, with higher MeHg concentrations and higher methylation
rates in summer than in fall (Mitchell and Gilmour. 2008). and temperature effects have
been experimentally demonstrated in Georgia coastal marshes, where the methylation
rate was 2 times higher at 25°C than at 4°C, and was 30 times higher at 35°C than at 4°C
(king et al.. 1999). Seasonal patterns are even observed in the Florida Everglades, where
December potential methylation rates were lower than March or July rates, although
water temperatures at midday in December were 18°C (Gilmour et al.. 1998).
In addition to affecting Hg methylation rates, seasonal changes in hydrology can alter
fluxes of Hg in watersheds. In the Marcell Experimental Forest, Minnesota, water flow
during snowmelt over 2 weeks in spring is 30 or 41% of total annual discharge from two
wetland catchments (Mitchell et al.. 2008c). and 26 or 39% of total annual Hg export
from the catchment occurred during that time. The majority of MeHg within the
catchments (79 or 95% of total catchment MeHg) was in the wetlands and exported in
high amounts during snowmelt, about 22-23% of annual MeHg export from the
catchments (Mitchell et al.. 2008c).
12.3.4.2 Total Mercury Concentration
The 2008 ISA did not present information on how total Hg concentration affects rates of
MeHg production, in part because there is no consensus across studies as to whether there
is a linear relationship between total Hg and MeHg. In part this is because most reported
MeHg rates are potential rates determined by experimental incubations with added Hg,
and methylation rates have been shown to be dependent on initial concentrations of Hg
(King et al.. 1999; Gilmour et al.. 1992). Additionally, different chemical forms of
inorganic Hg vary in bioavailability and affect methylation rates (kucharzvk et al.. 2015;
Graham et al.. 2012).
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The relationship between Hg and MeHg concentrations may depend heavily on the type
and salinity of water body. A recent report on Hg concentrations in streams across the
U.S. found no relationship between Hg and MeHg across sites (Wentz et al.. 2014). This
is in contrast to an earlier review of Hg methylation and demethylation dynamics found
that across studies, there is a positive correlation between Hg and MeHg in estuaries
(r2 = 0.78), and weaker positive correlations in rivers (r2 = 0.68) and lakes (r2 = 0.64), but
no correlation in wetlands (Benoit et al.. 2003). In a recent study of eight highly
Hg-contaminated (up to 226,000 ng Hg/g sediment, reported as 226 |ig Hg/g sediment)
lakes and water bodies in Sweden, more than 55% of the variation in sediment MeHg was
explained by total sediment Hg in three estuary sites, but there was no correlation in the
remaining freshwater sites (Drott et al.. 2008). In the freshwater sites, MeHg was instead
strongly correlated with potential methylation rates [r2 > 0.85 (Drott et al.. 2008)1.
12.3.4.3 pH
The 2008 ISA described the state of knowledge current at the time, that lower pH waters
had higher MeHg production, which was assumed to be a causal relationship. However,
laboratory body of evidence suggests that if all other factors are held equal, methylation
is highest near neutral pH, and drops with increasing acidity. The apparent discrepancy is
due to the fact that SOx deposition causes both elevated sulfate concentrations and
acidification in aquatic ecosystems.
Studies from the early 1980s assumed that acidification, not sulfate concentration, was
the causal factor in observed increases of MeHg in water and increased Hg burdens in
fish in response to SOx deposition. For example, samples from circumneutral lakes at the
ELA in Ontario that were experimentally acidified with H2SO4 had increased methylation
and decreased demethylation, so that methylation:demethylation rates were 2.9-4 times
higher at pH 5.1 than at pH 7.1 (Xun et al.. 1987; Ramial etal.. 1985).
Recent research on the role of S reducing bacteria in methylating Hg (Section 12.3.1)
suggests reinterpretation of an acid pH-MeHg relationship. Controlled laboratory
experiments showed that it was the added sulfate, not pH, that increased Hg methylation
rates in these lakes. Slurries with sediments from Lake Clara, Wisconsin, were made with
added H2SO4 or a molar equivalent amount of sulfate as Na2S04. Acidification from
neutral slurries to pH 4.5 with H2SO4 decreased methylation by 65%, while an equivalent
addition of Na2S04 did not alter methylation rates; acidification to pH 3.0 almost entirely
inhibited methylation (Steffan et al.. 1988). This study also measured demethylation over
a range of pH 2.0-8.0: demethylation was higher than 2% from pH 4.4-8, while
methylation rose above 2% from pH 6.0-8.0, and both processes slowed with increasing
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acidity and decreasing pH (Steffan et al.. 1988). The 2008 ISA correctly identified the
correlation between acidic surface water and high rates of MeHg, but the two factors
share a common cause, increased surface water sulfate concentrations, rather than a direct
causal relationship.
12.3.4.4 Organic Matter in Water and Sediments
The 2008 ISA described some of the complex qualitative relationships (stimulatory
and/or inhibitory) between DOC and rates of Hg methylation. DOC and sediment organic
matter encompass a wide range of organic chemicals in the environment; they affect
MeHg production through effects on inorganic Hg ion chemistry and availability to
microbes, and by serving as a metabolic substrate for SRPs. New studies from lakes,
rivers, wetlands, and estuaries have found positive relationships between a range of lower
DOC concentrations and MeHg production or concentrations. However, the chemical
form of DOC or salinity of water body can alter DOC and MeHg relationships.
Certain forms of DOC may serve as a metabolic substrate that increases SRP activity and
by extension, Hg methylation. In wetlands in the Arbutus Lake watershed, New York,
there were strong correlations (r2 = 0.58 or 0.60) between Hg and total carbon in the
upper 30 cm of peat (Selvendiran et al.. 2008b). In northern Wisconsin lakes, the quantity
of DOC derived from wetlands is the strongest (>80% variance) predictor of MeHg
(Watras et al.. 2006). In Canadian boreal lakes, there was a positive relationship between
methylation rates and DOC (r2 = 0.62). In Little Rock Lake, Wisconsin, DOC and S
reduction had a complex relationship: between 3.6-7.6 mg C/L (reported as
300-600 (imol/L), sulfide (a proxy for S reduction) increased linearly with DOC
concentration, while S reduction did not occur at DOC less than 3.6 mg C/L, and S
reduction did not increase at DOC concentrations above 7.6 mg C/L (Watras et al.. 2006).
Sediment organic matter may also increase microbial Hg methylation. At another
watershed in the Adirondacks, Sunday Lake, New York, the highest MeHg
concentrations were in samples that were more than 20% organic material (Yu et al..
2010). In prairie potholes in Saskatchewan, surface water [MeHg] increased in a linear
relationship with the sediment percentage of organic matter (OM), with a 2.65 ng/L
increase in MeHg for every 10% increase in the percentage of OM (Hoggarth et al..
2015).
In wetlands, rivers, and lakes of the Mississippi River delta, Louisiana, total Hg dissolved
in surface water was positively correlated with DOC concentrations, but negatively
correlated with sulfate concentrations. However, this correlation is confounded by
ecosystem salinity, as mean sulfate concentrations in surface water were 16 mg/L in
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freshwater wetlands, 63 mg/L in brackish wetlands, and 909 mg/L in marine wetlands
(Hall et al.. 2008). Also, dissolved MeHg in surface water increased linearly with the
hydrophobic organic acid fraction of DOC, with dissolved MeHg increasing 1 ng/L
(0.000001 mg/L) for each increase of 0.048 mg organic acid/L (Hall et al.. 2008). The
hydrophobic organic acid fraction represents a recalcitrant source of aromatic carbon
such as what would be found in peat, and would account for the high amounts of MeHg
in these wetlands. Another recent study used controlled incubations of an SRP strain,
varying concentrations of Hg, and two we 11-characterized forms of DOC to quantify the
effects of DOC upon methylation. DOC typical of terrestrial sources (high aromatic
fraction, high molecular weights) increased MeHg production by 10-40-fold above
unamended controls, while aquatic DOC (high aliphatic fraction, low molecular weights)
doubled MeHg production (Graham et al.. 2012). The authors hypothesize that DOC
increases MeHg production by slowing the growth of Hg-S particles, increasing Hg-S
residence time in the water and enhancing Hg bioavailability (Graham et al.. 2012). The
stronger effects of terrestrial DOC on MeHg may explain why MeHg production is
particularly high in wetlands, recently flooded reservoirs, and periodically flooded river
plains (Benoit et al.. 2003). In estuarine and marine sediments of the Chesapeake Bay,
Maryland, organic C in the sediments had a strong positive correlation (r = 0.96) with
sediment MeHg concentrations (Hollwcg et al.. 2010). In coastal marshes of the
Chesapeake such as Kirkpatrick Marsh, Maryland, there was also a significant positive
relationship (r2 = 0.478) between Hg methylation rate and mineralization of organic C, a
metric of cellular metabolism within the sediment (Mitchell and Gilmour. 2008).
Organic matter in surface water can increase the amount of Hg transported throughout a
watershed, as well as MeHg production at the watershed scale. Dissolved organic carbon
(DOC) can form complexes with Hg ions that facilitate their transport. In Arbutus Lake
watershed in Adirondack Mountains, New York, the flux of Hg and DOC in streams was
correlated (r2 = 0.80) across seasons, and the highest fluxes were in June and July
(Selvendiran et al.. 2008a). In a study of five watersheds across the U.S., MeHg
concentrations in catchment outflows correlated positively with particulate organic matter
(POC) in Sleepers River, Vermont (r2 = 0.93), and in Rio Icacos, Puerto Rico [r2 = 0.83
(Shanlev et al.. 2008)1.
DOC affects the partitioning of inorganic Hg between sediment and water, and hence the
bioavailability of inorganic Hg to methylating organisms (Hsu-Kim et al.. 2013; Marvin-
Pi Pasquale et al.. 2009; Benoit et al.. 2003). In Kirkpatrick Marsh on the Chesapeake
Bay, Maryland, linear relationships between methylation rates and absorbance values
indicated that Hg methylation rates were higher when the DOC was composed of high
molecular weight, aromatic organic compounds (Mitchell and Gilmour. 2008). There
were no correlations between DOC characterization and measures of microbial activity,
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so authors suggested that the form of DOC (size and aromaticity of compounds) controls
Hg bioavailability rather than serving as a metabolic substrate powering MeHg
production (Mitchell and Gilmour. 2008). However, the relationship between DOC and
Hg partitioning is complex [reviewed in Hsu-Kim et al. (2013)1. and in an extensive
survey of the Alabama River basin around Mobile, AL, there was no relationship across
52 sampling sites between DOC and Hg fractions [total, aqueous, particulate (Warneret
al.. 2005)1.
12.3.4.5 Iron
The 2008 ISA briefly identified iron (Fe) as a surface water component that can alter the
relationship between SOx deposition and MeHg production (as it also interacts with
sulfide phytotoxicity and internal eutrophication, see Section 12.2.3 and Section 12.2.4).
Iron can alter the rates of Hg methylation via abiotic and biotic mechanisms. Iron binds
with sulfide produced by SRPs during methylation to precipitate out of solution (Hellal et
al.. 2015). preventing the negative feedback of sulfide on sulfate reduction. Iron oxides
form complexes with inorganic Hg, which decrease Hg bioavailability. However, sulfide
released by SRPs can react with Fe-Hg complexes to release Hg into the water column
(Hellal et al.. 2015). Iron can increase methylation rates directly, by stimulating the
activity of iron-reducing bacteria capable of Hg methylation, including Geobacter spp. In
laboratory incubations mimicking freshwater sediments, iron reduction and sulfate
reduction co-occurred in time but at different zones in the sediment (Hellal et al.. 2015).
Iron and S reduction also co-occurred in wetlands of the Yolo Bypass, California (see
Section 12.6.5).
In Kirkpatrick Marsh on the Chesapeake Bay, Maryland, there was a positive relationship
(r2 = 0.478) between Hg methylation rate and mineralization of organic C and an equally
strong positive relationship between Hg methylation rate and the pool of Fe2+ [r2 = 0.478
(Mitchell and Gilmour. 2008)1. Although Fe precipitation with Hg-S has been posited as
one of the mechanisms by which Hg is buried in sediments, there was no relationship
between iron concentration and partitioning of Hg between water and soil.
12.3.4.6 Nitrate
The 2008 ISA did not address the effect of nitrate upon MeHg production. Nitrate ions
are energetically favored over sulfate in redox reactions, so N addition can depress Hg
methylation by shifting the energetic advantage from SRPs to denitrifiers (Dev et al..
2015). In Florida Everglades sediment incubations, addition of NO3 to incubations
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decreased MeHg production by 70% (Gilmour et al.. 1998). In Onondaga Lake, New
York, the Syracuse water treatment plant incorporated year-round nitrification in 2004,
doubling the nitrate concentrations measured annually in May before the lake stratified
(Todorova et al.. 2009). MeHg concentrations decreased exponentially with increasing
NO3 concentrations (estimated pseudo-r2 = 0.61) in the 2-3 years following the change in
water treatment. This change in N load reduced MeHg accumulation in the hypolimnion
by 50% in 2006, and by 93% in 2007 compared to MeHg measured earlier, in 1982,
1992, and 2002 (Todorova et al.. 2009).
12.4 Sulfur Manipulation Studies of Methylmercury
12.4.1 Ecosystem Scale and Field Mesocosm Studies
The 2008 ISA found that experimental S addition to aquatic and wetland ecosystems
increased MeHg concentrations in surface water (and Hg concentrations in biota, see
Section 12.7). Key studies supporting this finding focused on the long-term S
acidification (1984-1989) and recovery (1990-present) experiment at Little Rock Lake,
Wisconsin and the relatively recent (initiated in 2001) experimental S addition
experiment at Bog Lake Fen in the Marcell Experimental Forest, Minnesota. This section
integrates older published reports and recent papers from S addition experiments that
presented quantitative relationships between S addition and Hg mobilization,
methylation, and MeHg concentrations in surface water. There is new evidence from the
S addition experiment at Bog Lake Fen and from an S addition by warming experiment in
a Swedish bog that confirms the relationship reported in the 2008 ISA between increased
S loading and environmental increases in MeHg. There is also new evidence that
decreases in S addition allow recovery of MeHg toward control conditions, as well as
new evidence that climate change (drought, warming) will increase S cycling and
increase MeHg concentrations (Table 12-4).
As reported in the 2008 ISA, experimental S addition increases MeHg production in lake
ecosystems, and cessation of S addition results in reductions in MeHg production in
lakes. Little Rock Lake, Wisconsin was an S addition experiment that ran from
1985-1991, in which the north and south basins of the lake were artificially isolated by a
plastic barrier, and then annual S additions were used to acidify the northern basin, while
the unamended south basin served as a control. In 1993, after S addition had ceased but
sulfate concentrations in the north treatment basin (4.8 mg/L or 50 (j,M) were still twice
that of the reference basin (2.4 mg/L or 25 (j,M), potential methylation rate was 220%
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higher in the treatment basin (Gilmour and Riedel. 1995). In June 1993, when MeHg
fractions were at their highest, the MeHg fraction of total Hg was 30% higher in the
treatment basin (Gilmour and Riedel. 1995). Mercury and S cycling were monitored in
the lake through 2003, and elevated sulfate concentrations and acidification persisted in
the lake through 1996; the lake was considered recovered from 1998-2003. During
acidified years, 25% more of annual Hg2+ inputs were transformed into water column
MeHg than in recovery years (Watras et al.. 2006). Net methylation during the summer
was 70% higher in acidified than in recovery years, and summertime MeHg accumulation
was 75% higher in the whole lake in acidified years (Watras et al.. 2006). There was a
strong positive correlation between summer MeHg accumulation (1990-2003) and the
interaction of epilimnion sulfate concentration and epilimnion Hg2+ concentration. The
hypolimnion or the anoxic-oxic boundary were likely the sites of Hg methylation, as the
hypolimnion, which was less than 5% of the lake volume, accumulated more than 70% of
the total MeHg mass of the lake in acidified years (Watras et al.. 2006). Hypolimnion
MeHg was associated with hypolimnion S reduction, as there was a 10.8 ng MeHg/L
(0.0000108 mg MeHg/L) increase for each 1 mg/L increase in hydrogen sulfide (H2S;
reported as 1.71 pmol/L increase in MeHg for each 1 (imol/L increase in H2S; r2 = 0.65).
Experimental S addition substantially increases MeHg in wetlands. The ELA in Ontario
has been the subject of considerable research in Hg cycling (see Appendix B). An early
experiment added pulses of sulfate to peat inside collars installed in a poor fen, and
monitored changes in MeHg concentrations over 4 days. In one experiment, addition of
14 kg sulfate/ha increased MeHg pore water concentrations (ng/L) at the water table
surface 30% above the highest measured MeHg concentrations in the control plot, with a
100% increase in MeHg above control plot concentrations at 10-cm depth in the water
table (Branfireun et al.. 1999). Following a second 14 kg sulfate/ha addition, MeHg at
5 cm depth in the peat water table increased to 130% above maximum MeHg in the
control plot. Four days after the first S addition, MeHg at the 5-cm depth remained
elevated at 250% above maximum measured MeHg in control plots (Branfireun et al..
1999). In an experiment the following year, one sulfate addition equivalent to
2.8 kg sulfate/ha was added. After 24 hours, this S addition had increased MeHg pore
water concentrations at the water table surface 100% above maximum measured MeHg in
the control plot, and at the 10-cm depth below the water table, MeHg increased 20%.
This MeHg increase did not persist to 48 hours after addition (Branfireun et al.. 1999).
There is new evidence that addition of labile DOC typical of leachate from a forested
watershed enhanced the stimulatory effect of S addition upon MeHg concentrations in
wetlands. At the Marcell Experimental Forest, Minnesota, field mesocosms were initiated
in Bog Lake Fen to test the effects of S and carbon addition on Hg cycling in an
ombrotrophic peat bog. Mesocosms received experimentally added loads of
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8.3 kg S/ha/yr or 20.7 kg S/ha/yr, alone or in combination with additions of organic
carbon in different forms (Mitchell et al.. 2008a'). S addition increased peat pore water
concentrations of MeHg 219-246% above MeHg levels in unamended control plots with
no significant difference between net methylation under 8.3 versus 20.7 kg S/ha addition
(Mitchell et al.. 2008a'). Adding 20.7 kg S/ha/yr to mesocosms increased the fraction of
the total Hg pool that took the form of MeHg, with MeHg 117% higher than in control
plots (Mitchell et al.. 2008a'). The combined addition of sulfate and organic carbon (as
glucose, acetate, or leachate from coniferous leaf litter) increased methylation rates
(reported in pg MeHg/L/day) by 163% and increased the fraction of MeHg (%MeHg) by
152% over rates measured in mesocosms that received only S addition (Mitchell et al..
2008a'). This study showed that S addition will increase MeHg in surface water in bogs,
particularly when combined with labile C inputs. These results coincide with findings
presented elsewhere in the ISA that DOC concentrations are increasing in surface waters
(Chapter 7) as terrestrial ecosystems recover from acidification.
A decade of research at Bog Lake Fen in Minnesota shows that additional S increases
MeHg production in this wetland, with consequences for water quality and also for
resident organisms (see Section 12.7). Bog Lake Fen is the site of a long-term S addition
experiment in which entire sections of the Sphagnum peat wetland have received
additional S loading in simulated wet deposition. As reported in the 2008 ISA, S addition
began in 2001 at a rate of 32 kg S/ha/yr, and increased the levels of MeHg in the bog by
40-190% in the first summer, and increased the MeHg export from the bog by 144% in
2002 (Jeremiason et al.. 2006). More recent sampling has confirmed the relationship
between S addition and elevated MeHg production and concentrations in the wetland. In
peat pore water sampled 5 cm below the water table for 2 weeks after S addition events, S
addition increased MeHg concentrations by 880-1,790% in 2006 (0.2-0.3 ng MeHg/L in
control, 2.9-4.2 ng/L in S addition plots), and increased MeHg concentrations
340-1,170% in 2008 (Wasik et al.. 2012). Pore water MeHg fraction (percentage of total
Hg in MeHg form) increased 610-1,340% over control levels in 2006 and increased
390-1,160% over control levels in 2008 (Wasik et al.. 2012). Researchers also sampled
surface peat and found that S addition altered MeHg concentrations in peat. MeHg
concentrations (ng/L) and MeHg fraction (percentage of total Hg as MeHg) were
4-9 times higher in S addition plots than in control plots, although there was no effect of
S addition on total Hg in plots (Wasik etal.. 2012). The elevated MeHg in water and peat
had consequences for the food chain (see Section 12.7).
There is also evidence of the link between S addition and MeHg production from a
European wetland experiment. Degero Stormyr in Sweden is the site of an experiment
that addresses the effects of S and N deposition as well as warming due to climate
change. Plots received S loads of 10 kg S/ha/yr or 20 kg S/ha/yr, and a subset of plots
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was enclosed by greenhouses to raise air temperature by about 4°C and peat temperature
(at the 20-cm depth) by about 2°C. Four years after the 1995 initiation of the experiment,
Bergman et al. (2012) measured MeHg production in control and 20-kg-S/ha/yr plots.
After 4 years of treatment, S addition increased mean growing season peat pore water
MeHg concentrations 117% over MeHg concentrations in control plots (Bergman et al..
2012). There was higher variation in MeHg in S addition plots (20 kg S/ha/yr), as the
range of measured concentrations was 4.3 times the range of measured MeHg in control
plots (Bergman et al.. 2012). The experiment was resampled 12 years after initiation, and
the Hg methylation constant was 71% higher in methylation hotspots (hotspot
experimentally defined as the point in each sampled peat profile with the highest Hg
methylation rate constant) under addition of 10 kg S/ha/yr compared to control plots,
while MeHg concentrations were 22% lower than in control hotspots (Akerblom et al..
2013). These seemingly contradictory results (higher production, lower concentration)
may indicate increased mobilization of MeHg from methylation hotspots (see below) or
increased microbial demethylation rates, which were not tested. Under higher S addition
of 20 kg S/ha/yr, the Hg methylation rate constant was 400% higher than in control plots,
while the MeHg concentrations were 74% higher than in control plots (Akerblom et al..
2013). Together, these results indicate that an S addition of 10 or 20 kg/ha/yr increase
microbial MeHg production, and an S addition of 20 kg/ha/yr increases MeHg
concentrations, in wetlands.
S addition also increases the mobilization and transport of Hg and MeHg from peat
methylation hotspots into the water column, increasing bioavailability. After 4 years of S
addition at Degero Stormyr in Sweden, plots that received 20 kg S/ha/yr had 133% higher
total Hg levels in the top 5 cm of peat than control plots (Bergman et al.. 2012). After
12 years, sampling of Hg methylation hotspots in plots with 10-kg-S/ha/yr addition found
total Hg was 25% lower per peat mass or 31% per peat volume than in control plots
(Akerblom et al.. 2013). These results indicate that S addition mobilizes Hg stored in
deeper parts of the peat profile, resulting in Hg transport to more accessible parts of the
peat profile.
Recent work from the experiment at Bog Lake Fen also provides evidence that reduction
of experimental S addition to wetlands results in reductions of MeHg concentrations in
wetlands. In 2006 after 5 years of elevated S levels, a recovery treatment was initiated in
the S6 bog experiment, where S addition was halted in recovery plots. Following the
cessation of S addition, pore water MeHg (ng/L) declined by 32% between 2006 and
2008, and peat MeHg concentration and peat MeHg fraction declined by 62 and 76%,
respectively (Wasik et al.. 2012).
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12.4.1.1
Climate Change
Recent evidence from experiments in lakes and bogs allows evaluation of how climate
change will affect the relationship between SOx deposition and MeHg production.
Climate change will affect aquatic and wetland ecosystems via warming temperatures
and increasing fluctuations in water tables due to changes in the timing and magnitude of
precipitation (IPC'C. 2013). Microbial activity is strongly dependent upon temperature,
and in general microbial activity increases with temperature. It is biologically plausible
that warming could increase MeHg via stimulation both of decomposer guilds of
microbes producing DOC and of SRPs actively methylating Hg, but it is also plausible
that warming will increase the activity of microbes that demethylate MeHg. IPCC (2013)
projected that heavy precipitation events will increase in number and strength due to
climate change, which can lead to rapid changes in water table level in wetlands and
lakes. These changes in water level can move pulses of labile carbon and sulfate into the
anoxic zones of the water, sediment, and periphyton where SRPs are active, and flooding
or rewetting of previously dry zones can create new environments favorable for SRPs.
The following studies suggest that drought and warming increase S cycling and Hg
cycling. Drought, but not warming, increases MeHg production in lakes and wetlands.
As reviewed in the 2008 ISA, recovery in Little Rock Lake, Wisconsin, has been
monitored because it was experimentally acidified for 5 years (1984-1989). Drought
affected sulfate and MeHg concentrations in Little Rock Lake, Wisconsin, which is
rain-fed. During the drought years of 1998-2006, MeHg increased 0.004 ng/L/yr,
although high variation among samples made this trend marginally significant \p = 0.06
(Watras and Morrison. 2008)1. MeHg increased from 0.04 ng/L in 1997 to 0.07 ng/L in
2006, a 75% increase, which is more than can be attributed to evapoconcentration from
the lake's 30% decrease in volume (Watras and Morrison. 2008). During this time period,
there were no significant changes in total Hg deposition; although between 1988 and
2006, the total Hg concentration in Little Rock Lake has declined 0.04 ng/L/yr (Watras
and Morrison. 2008). During the drought, between 2000 and 2004, total MeHg mass in
the north basin of the lake was positively correlated with higher Hg and S deposition in
precipitation (Figure 12-5).
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1/1
ro
E
CuO
CD
Q)
C.
i_
O
_Q
L_
CD
+-»
ro
2000 2001 2002 2003 2004
Year
r = 0.8
70 80 90 100110 4 6 8 10
HgT (mg ¦ ha"1) S04 (kg ¦ ha"1)
Atmospheric deposition rate
ha = hectare; HgT = total mercury deposition kg = kilogram; MeHg = methylmercury; mg = milligram; S04 = sulfate.
Source: Adapted from Watras and Morrison (2008).
Figure 12-5 Total methylmercury mass in water at Little Rock Lake,
Wisconsin, annually (a), and in relationship to annual mercury (b)
or sulfur (c) deposition.
1 Total MeHg in Little Rock Lake, Wisconsin increased 14.4 mg (or 14,400,000 ng) for
2 every 1 kg/ha increase in sulfate deposition (Watras and Morrison. 2008). Total Hg in the
3 epilimnion from 1988-2004 did not differ between treatment and control basins, but
4 there were differences in MeHg associated with experimental Hg treatment: MeHg was
5 30% higher on average in epilimnion from 1983-1996 (Watras et al.. 2006).
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Wetlands are characterized by fluctuating water tables, and microbial communities in
wetlands are adapted to respond rapidly to changes in substrate and oxygen availability.
This is particularly true for SRPs, which methylate Hg in geographic and temporal
pulses, resulting in hotspots of high MeHg concentrations within wetlands where Hg is
actively methylated (Appendix B). Fluctuations in water tables caused by periods of
drought and periods of flooding can create pulses of SRP activity and hotspots of Hg
methylation, raising MeHg concentrations in the environment. The following studies
present evidence that climate change (through drought and warming) will interact with S
addition to change MeHg and Hg dynamics in wetlands.
Drought and rewetting increased MeHg in Bog Lake Fen, and S addition treatments
enhanced this effect. A 9-month drought from the summer of 2006 to the spring of 2007
resulted in a pulse of reduced S when the water levels rose again, and the sulfate
concentrations were 147% higher in the S addition treatment, and 78% higher in the
recovery treatment, than in the control wetland (Wasik et al.. 2015). Sulfate pulses
resulted in proportional increases in Hg methylation, with peak MeHg fraction 150%
higher in the S addition and 60% higher in the recovery treatment (Wasik et al.. 2015).
The peat experienced drought conditions in summer 2007 as well, and pulses of sulfate in
the experimental treatments that fall (165% higher in S addition, 14% higher in recovery
wetland than in control wetlands) resulted in higher peak MeHg fractions in fall and the
following spring in both the S addition and recovery treatments. Experimental
manipulation of water levels in the different wetland treatments showed that higher water
levels raised sulfate, total Hg, and MeHg in S addition wetland, but did not affect these
parameters in control and recovery wetland (Wasik et al.. 2015). In the recovery
treatment, S and MeHg pulses were higher than in control plots, indicating persistent
effects of S addition several years after addition ceased. However, because
experimentally raising water levels did not alter S or Hg chemistry in control or recovery
wetlands, the recovery wetland was returning to S and Hg processes more similar to
control plots.
Warming may ameliorate the effect of S upon MeHg production in wetlands, but
experimental evidence suggests that it will also increase sulfate and MeHg export from
peatlands into downstream aquatic ecosystems. Degero Stormyr in Sweden is the site of a
wetland experiment that addresses the effects of S and N deposition as well as warming
due to climate change. Warming altered the S and Hg dynamics under S deposition at
Degero Stormyr. Total Hg (per mass of peat) was 19% lower in 20 kg S/ha/yr + warming
plots than in S only plots, indicating increased mobilization or volatilization of Hg from
the peat. The Hg methylation constant in S + warming was similar to the rate in
unamended control plots, much lower than the rate in S only plots (Akerblom et al..
2013). MeHg concentrations in the S and warming treatment were lower than in any
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1 other treatment, 73% lower in the 20 kg S/ha/yr + warming treatment than in the
2 20 kg S/ha/yr treatment, and were 54% lower than in the control treatment (Akerblom et
3 al.. 2013). This last result suggests that the combination of warming and S addition
4 increases MeHg mobility beyond current ambient rates. Given the decreases in both total
5 Hg and MeHg, it appears that all forms of Hg were mobilized and either exported or
6 volatilized by the warming + S addition treatment, despite decreases in Hg methylation
7 rate.
12.4.1.2 Summary Table
Table 12-4 New studies on nonacidifying sulfur effects on mercury cycling.
Type of
Ecosystem
Additions or Load
(kg S/ha/yr)
Biological and Chemical Effects
Study Site
Study
Species
Referenc
Peat fen Ambient S
deposition:
3 kg S/ha/yr
S addition: low S
(7 kg S/ha/yr added
for total load of
10 kg S/ha/yr) or
high S
(17 kg S/ha/yr
added for total load
of 20 kg S/ha/yr) as
Na2SC>4, with 0 or
30 kg N/ha/yr as
NH4NO3
At 30-cm depth, total Hg (per peat mass)
in warming + high S was 19% lower than
in high S plots.
Low S decreased total Hg in peat
methylation hotspots by 25 or 31% on a
per-mass or per-volume basis.
The Hg methylation rate constant
increased by 71% in low S and by 400%
in high S.
Peat MeHg concentrations decreased by
22% in low S and increased by 74% in
high S.
Degero
Stormyr,
Sweden (64°
09' N, 20°
22' E),
measured in
2007 and
2008
Peat
samples
Akerblom
et al.
(2013)
Peat fen Ambient S
deposition:
3 kg S/ha/yr
S addition: high S
(17 kg S/ha/yr
added for total load
of 20 kg S/ha/yr)
S addition increased pore water MeHg Degero
concentrations by 117%. S addition Stormyr,
increased the range of MeHg Sweden (64°
concentrations by 4.3x, and the variance 11'N, 19°
by 22.2x the control variance. 33' E),
measured in
With S addition, MeHg increased with 1999
higher groundwater levels, although
there was no relationship in ambient
plots.
Pore water Bergman
in peat et al.
(2012)
Total Hg in the top 5 cm of peat
increased by 133% with S addition.
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Table 12-4 (Continued): New studies on nonacidifying sulfur effects on mercury
cycling.
Type of
Ecosystem
Additions or Load
(kg S/ha/yr)
Biological and Chemical Effects
Study Site
Study
Species
Referenc
e
Peatland
(poor fen)
Experimental
treatment, addition
of 32 kg/ha/yr in 3
simulated rainfall
events, 2001-2008
Recovery
treatment,
32 kg/ha/yr
2001-2006, no
added S
2006-2008
Deposition =
5.5 kg S/ha/yr
(NADP site MN16)
Mesocosms
installed in ambient,
added S, and
recovery zones of
marsh, pulse of
130 mg Na2SC>4
added
In Spring 2005, S addition increased
%MeHg 387% over control wetland. In
Fall 2005, S addition increased %MeHg
275%.
Following a 9-month drought, Spring
2007 rewetting released internally stored
S, the pulse of SO42" was 78% higher in
recovery and 147% higher in
experimental than in control wetlands.
Following a 9-month drought and
rewetting in Spring 2007, peak [MeHg]
was 75% higher in recovery and 120% in
experimental wetland. Peak %MeHg was
60% higher in recovery and 150% in
experimental wetland.
Following summer-long drought and
rewetting in fall 2007, [SO42"] was 14%
higher in recovery and 165% higher in
experimental wetland.
Following summer-long drought, the Fall
2007 peak [MeHg] was 102% higher in
recovery and 301% higher in the
experimental wetland. Peak %MeHg was
150% higher in recovery and 350%
higher in the experimental wetland.
Following summer-long drought, the
spring 2008 peak [MeHg] was 62%
higher in recovery and 133% higher in
the experimental wetland. Peak %MeHg
was 146% higher in recovery and 262%
higher in the experimental wetland.
Experimental water level rise in
mesocosms does not affect chemical
constituents in control and recovery
wetlands, but increases total Hg, SO42",
MeHg, and %MeHg in the experimental
wetland. DOC decreases in the
experimental wetland mesocosm.
S6 peatland
in Marcell
Experimental
Forest,
Minnesota
Sphagnum
spp.,
herbaceous
forbs,
ericaceous
shrubs,
spruce, and
tamarack
Coleman
Wasik et
al. (2015)
Bog Ambient S load:
2.07 kg S/ha/yr as
quantified by NADP
S addition:
8.28 kg S/ha/yr
(low), or
20.7 kg S/ha/yr
(high) as SO4
solution
S addition increased pore water MeHg
concentrations 219-246%.
High S increased MeHg fraction
(MeHg/total Hg) by 117%.
Labile organic C and S additions
increased methylation rates (pg
MeHg/L/day) by 163% and rates of
increasing MeHg fraction (%MeHg/day)
by 152% over rates for S-only addition.
Bog Lake
Fen, Marcell
Experimental
Forest,
Minnesota
Peat pore
water
Mitchell
et al.
(2008a)
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Table 12-4 (Continued): New studies on nonacidifying sulfur effects on mercury
cycling.
Type of
Ecosystem
Additions or Load
(kg S/ha/yr)
Biological and Chemical Effects
Study Site
Study
Species
Referenc
e
Bog Ambient S
deposition:
5.5 kg/ha/yr (mid
2000s) as
quantified by NADP
site MN16
S addition:
32 kg S/ha/yr
dissolved in pond
water and delivered
by sprinklers
(mimics 4* the
1990s deposition
rate)
In pore water, MeHg (ng/L) was
increased by 8.8-17.9x control levels in
2006 and 3.4-11.7* control levels in
2008. MeHg fraction (MeHg/total Hg)
was increased by 6.1-13.4-fold in 2006
and 3.9-11.6-fold in 2008.
S6 peatland, Pore water, Wasik et
bog section,
Marcell
Experimental
Forest,
Minnesota
In solid peat, MeHg concentrations and
MeHg fraction were 4-9x higher than in
controls or5-6x higher when accounting
for annual variability.
3 yr after SCU treatment cessation
(recovery treatment), pore water MeHg
declined 32%, peat MeHg declined (ng/L)
by 62%, and peat MeHg fraction (%)
declined 76%.
peat, and
Culex spp.
(mosquito)
larvae
al. (2012)
Lakes:
rain-fed
LRL, DL
drains
stream fed
by wetland
LRL: [S042"] =
2.5 mg/L, DL:
[S042"] = 2.8 mg/L,
stream feeding DL
[S042"] = 1.6 mg/L
S deposition not
reported
In LRL during drought years, lake SO42"
concentrations increased 0.18 mg/L/yr,
as MeHg concentrations increased
0.004 ng/L/yr.
In stratified basin of LRL, total MeHg
increased with increasing S deposition:
mg MeHg = 14.368 * (kg S/ha) - 18.494.
Little Rock
Lake (LRL)
and Devils
Lake (DL),
¦ Wisconsin
Lake water Watras
and
Morrison
(2008)
C = carbon; cm = centimeter; DL = Devils Lake; Ha = hectare; Hg = mercury; kg = kilogram; L = liter; LRL = Little Rock Lake;
MeHg = methylmercury; mg = milligram Na2S04 = sodium sulfate; NADP = National Atmospheric Deposition Program;
ng = nanogram; NH4N03 = ammonium nitrate; S = sulfur; S042" = sulfate; yr = year.
12.4.2 Laboratory Manipulation Studies
Laboratory studies support field research in demonstrating that under controlled
conditions, sulfate additions could increase Hg methylation in environmental samples.
The 2008 ISA reported evidence of Hg methylation in lake water and sediment samples
in response to experimental sulfate addition. In slurries of sediment collected from
Quabbin Reservoir, Massachusetts, adding 4.8 mg/L (reported as 50 (iM) sulfate to the
slurry (ambient lake water sulfate = 5.8-7.7 mg/L or 60-80 (j,M) increased potential
MeHg production 150%, 9.6 mg/L sulfate (100 (iM) increased MeHg production 160%,
and 19.2 mg/L sulfate (200 (j,M) sulfate addition increased MeHg 410% above ambient
lake water MeHg (Gilmouret al.. 1992). Slurries can overestimate the potential rates of
MeHg production, so this study also incubated intact sediment cores with sulfate
concentrations from 0.3-110 mg/L (reported as 3-1,140 (jM). Peak potential MeHg
production was at 11 mg/L sulfate (110 (j,M), where MeHg was 8.6 ng MeHg/g, a 200%
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increase from MeHg production at 0.3 mg/L sulfate [3 (j,M (Gilmour et al.. 1992)1. In
longer incubations of sediment cores from 2 lakes in Wisconsin, including Little Rock
Lake, adding 5.8-23 mg/L sulfate (60-240 |iM) changed sediments from net
demethylating (-100 ng MeHg/m2/day or -0.1 |ig MeHg/m2/day) to net methylating
(5,500 ng MeHg/m2/day or 5.5 j.ig MeHg/m2/day) environments (Gilmour and Riedel.
1995).
Since the 2008 ISA, several new studies have provided experimental evidence of sulfate
stimulation of Hg methylation in a broader range of aquatic freshwater environments
(Table 12-5). Laboratory experiments using samples from wetlands at Sunday Lake in the
Adirondack Mountains of New York were conducted to determine potential Hg
methylation rates. When slurried peat-and-water samples from a floating fen (bog mat
composed of Sphagnum spp. and ericaceous shrubs) received an addition of sulfate to
raise the concentration of sulfate by 190 mg/L (initial sulfate concentration not given),
Hg methylation rates (%MeHg/day) were 2.1 times higher than unamended samples (Yu
et al.. 2010). This result is consistent with evidence from observational (Section 12.6) and
S addition studies (Section 12.4) in peat bogs that sulfate stimulates Hg methylation in
these wetland systems.
There are two new studies that demonstrate sulfate stimulation of water and sediment Hg
methylation in samples taken from rivers. Slurried sediments collected in 2010 from the
South River, Virginia, were spiked with sulfate to raise sulfate levels from average
ambient levels of 19.2 mg/L to 38.2 or 96.1 mg sulfate/L. Sulfate addition significantly
increased the potential methylation rate of Hg (%/day), with methylation rates 1.6-2.6
times higher in sulfate-spiked sediments than in sediments with ambient sulfate
concentrations (Yu et al.. 2012). There was a significant difference in methylation rates
between the low and high S addition treatments in only one of three sampled river
sediments, where methylation was higher in the sediment where sulfate levels were
96.1 mg/L (Yu et al.. 2012). In microcosm slurries composed of water and sediment
samples from the Wupper River in Germany, higher MeHg in water correlated weakly
(If = 0.28, both variables ln-transformed) with higher sulfate concentrations, with mean
pore water sulfate of 32.2 mg/L, range 2-223 mg/L (Frohne et al.. 2012). Higher total Hg
concentrations in water correlated weakly (If = 0.20) with higher sulfate, although DOC
was a stronger predictor of total Hg [i?2 = 0.53 (Frohne et al.. 2012)1. This evidence of
sulfate stimulation of Hg methylation in river ecosystems is consistent with observational
studies of positive correlations between sulfate and Hg methylation in rivers and streams
(Section 12.6.3).
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12.4.2.1
Summary Table
Table 12-5
New studies on sulfur addition effects on methylmercury.
Type of
Additions or Load
Biological and Chemical
Study
Ecosystem
(kg S/ha/yr)
Effects
Study Site
Species Reference
River S deposition not
reported
Soil: 2.0-2.6 mg S/g soil
[SO42"] pore water in
Microcosm:
2.2-223 mg/L, mean
32.0 mg/L
Total Hg and MeHg were
positively correlated with
sulfate concentrations: In
THg =2.956 + 0.697 * (In
S04), In
MeHg =4.962 + 0.473 * (In
SO4).
Wupper River,
Germany
Sediment Frohne et
pore water al. (2012)
Floating 2.0 mM (190 mg/L)
bog sulfate added to slurried
samples
Potential Hg methylation rates Sunday Lake,
(%MeHg/day) were 2.1 * Adirondack
higher with SO4 amendment. Mountains, New
York
Sphagnum Yu et al.
spp. (2010)
River Ambient concentration
in water is 200 pM
(19.2 mg/L) sulfate
Sediment MeHg (ng/g)
increased linearly with pore
water sulfate (pM)
concentrations in the river,
MeHg = 0.61 x ([SO4]) - 0.08.
South River,
Virginia
Addition of 400 pM
(38.4 mg/L) or 1,000 pM
(96.1 mg/L) sulfate in
anoxic sediment slurries
SO4 addition in slurries
increased potential
methylation rates by
1.6-2.6-fold.
In-channel Yu et al.
surface (2012)
sediments
g = gram; ha = hectare; Hg = mercury; kg = kilogram; L = liter; MeHg = methylmercury; mg = milligram; mM = millimolar;
|jM = micromolar; ng = nanogram; S = sulfur; S04 = sulfate; THg = total mercury; yr = year.
12.5 Sulfur Oxides Deposition Effects on Methylmercury
At the time of the 2008 ISA, there was only a single paper that considered links between
measures of SOx deposition and MeHg concentrations in ecosystems. Two additional
papers have been published since then which document effects of SOx deposition upon
Hg levels in water or fish (Table 12-6). The large scale and scope of these studies include
confounding and interacting environmental factors such as correlated Hg deposition and
variations in wetland cover, the full effects of which researchers are unable to fully
quantify. Despite this limitation, each of these papers show evidence of temporal or
spatial correlations between SOx deposition and MeHg concentrations in fish or water.
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A study of fish and SOx deposition sediment records at Isle Royale in Lake Superior
indicated that there is a temporal relationship in this remote location between S
deposition and Hg loads in fish. Isle Royale is a Class I area and contains several lakes
impacted by S and Hg deposition. Between 1981 and 2006, S deposition in the region fell
40-60% (from about 10 kg S/ha/yr in 1981 to about 6 kg S/ha/yr in 2006 atNADP site
MN18 in mainland Minnesota), while Hg deposition remained stable. S deposition on the
island between 1985 and 2006 was in the range of 2.3 to 7 kg S/ha/yr with a trend
(p = 0.09) toward a decline in deposition over that time period (Drevnick et al.. 2007).
Fish collections were conducted in eight Isle Royale lakes in 1995-1996 and again in
2004-2006. In six lakes, 1995 collections of northern pike (Esox lucius) exceeded the
U.S. EPA fish tissue Hg limit (0.3 |ig Hg/g wet weight). When these lakes were
resampled in 2004-2006, northern pike mean Hg levels were below the U.S. EPA limit,
which the authors attributed to a decline in SOx deposition despite steady Hg deposition.
This study also used museum collections of fish from Isle Royale (collected in 1905,
1929, 1966) and analysis of lake sediment cores to test the relationship between historical
S loads and fish Hg burdens. The chromium-reducible sulfur (CRS) fraction in sediment
cores was determined to closely track known patterns of S deposition since monitoring
began in 1985, allowing the inference of S loads to island lakes since the Industrial
Revolution in the late nineteenth century. The historical S load data were compared to Hg
loads in both the historical and recent fish collections from Isle Royale lakes. The CRS
fraction explained 79% of variation in Hg concentration of northern pike fish fillets.
There were similar correlations between sediment reduced S and Hg burden in other fish
species, but sample sizes for those species were low and correlations were not statistically
significant (Drevnick et al.. 2007). DOC and pH were not directly tested for their
relationship with Hg levels in fish, but the authors note that there are no significant trends
in DOC or pH in these lakes from 1980-2006. This study showed that Hg fish burdens
increased in Isle Royale lakes with increasing SOx deposition in the twentieth century,
and that Hg fish burdens declined in response to reductions in SOx deposition since the
1990s.
A 12-year study of MeHg and fish Hg in Voyageurs National Park found that declines in
SOx deposition have resulted in MeHg declines only in lakes where DOC has remained
stable. In lakes in Voyageurs National Park, Minnesota, a Class I area, researchers
measured MeHg in the epilimnion of four lakes between 2000 and 2012, and compared
trends in lake water Hg concentrations with trends of measured Hg and S deposition
(Brigham et al.. 2014). S deposition to the region decreased 48% between 1998 and 2012
based on regression analysis of data measured at National Atmospheric Deposition
Program (NADP) stations MN16 and MN18, and Hg deposition decreased 32%. In two
lakes, MeHg surface water concentrations decreased over 12 years of measurement, 50%
in Peary Lake and 43% in Ryan Lake (Brigham et al.. 2014). and fish Hg concentrations
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followed suit (see Section 12.7). In contrast, Brown Lake MeHg concentrations increased
85% over the same time period, which the authors ascribed to increasing inputs from
upstream methylating aquatic environments. An alternative explanation may be in
differences among lakes in dissolved organic carbon (DOC) concentrations; in Peary and
Ryan Lakes, DOC concentrations remained flat over the decade in which MeHg
concentrations decreased, while in Brown Lake, DOC concentrations increased 30%
(Brigham et al.. 2014). Perca flavescens (yellow perch) were collected between 2000 and
2012 to determine fish Hg levels in comparison with Hg lake water trends and S
deposition. Between 2000 and 2012, P. flavescens Hg concentrations decreased 37% in
Peary Lake and 32% in Ryan Lake, just as S deposition and lake MeHg declined
(Brigham et al.. 2014). In Brown Lake, where DOC increased 30% over the same time
period, P. flavescens Hg increased 80% (Brigham et al.. 2014). In Voyageurs National
Park, lakes with stable DOC responded to decreased S deposition with decreasing MeHg
in water and Hg concentrations in fish.
A study that compiled data from reservoir fish sampling in Texas found correlations
between geographic variations in SOx deposition and average fish Hg burden over
25 years. Largemouth bass (Micropterus salmoides) were collected between 1985 and
2009 with heavy sampling between 2004 and 2008 (45% of the samples) from
145 reservoirs in eastern Texas. Samples were grouped and analyzed by Level 3
ecoregions which received varying amounts of Hg and S deposition, increasing from the
westernmost Cross Timber region where S deposition was 7.7 kg/h to the easternmost
South Central Plains region where S deposition was 11.9 kg/h (Premier et al.. 2011). The
South Central Plains region received high deposition of SOx and Hg, and also had the
highest percentage of land area as wetlands (12%) and the lowest percentage of land area
in agriculture of the four regions, all of which are conducive to high methylation rates in
aquatic ecosystems. Mean Hg levels in sampled largemouth bass were 61-89% higher in
the South Central Plains than in other eastern Texas regions (Premier et al.. 2011). which
has regional implications because the South Central Plains ecoregion extends into
Arkansas, Louisiana, and Oklahoma. This study showed that within Texas, the
geographic region with the most wetlands and the highest SOx deposition also had fish
with the highest Hg burden.
12.5.1 Summary Table
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Table 12-6 New studies on sulfur deposition effects on methylmercury.
Type of
Additions or
Biological and Chemical
Ecosystem
Load (kg S/ha/yr)
Effects
Study Site
Study Species
Reference
Lakes
6.44 kg S/ha in
As SOX deposition
Voyageurs
Surface water
Briaham et al.
1998, 3.35 kg S/ha
decreased 48% in
National Park,
and Perca
(2014)
in 2012 as
1998-2012, water MeHg
Minnesota
flavescens
quantified by
decreased 50% in Peary
(yellow perch)
NADP sites MN16
Lake and 43% in Ryan Lake.
and MN18
In Brown Lake, water MeHg
increased 85% in
1998-2012.
Between 2000 and 2012, Hg
concentration in P.
flavescens decreased 37% in
Peary Lake and 32% in Ryan
Lake, and increased 80% in
Brown Lake.
Reservoir
NADP quantifies S
Mean Hg fish levels were
145 reservoirs
Micropterus
Drenner et al.
deposition in 2008
61-89% higher in the SCP
in four Level 3
salmoides
(2011)
at CT: 7.7 kg
region (highest S and Hg
ecoregions of
(largemouth
S04/ha, TBP:
deposition) than in other
eastern Texas:
bass)
8.1 kg SCM/ha,
regions.
CT, TBP,
ECTP: 8.1 kg ECTP, SCTP
S04/ha, SCTP:
11.9 kg S04/ha
CT = Cross Timber; ECTP = East Central Texas Plains; ha = hectare; kg = kilogram; MeHg = methylmercury; NADP = National
Atmospheric Deposition Program; S = sulfur; SCTP = South Central Texas Plains; S04 = sulfate; SOx = sulfur oxides;
TBP = Texas Blackland Prairie; yr = year.
12.6 Relationships between Sulfate and Methylmercury in Natural
Waters
The 2008 ISA presented evidence that elevated sulfate concentrations in aquatic and
wetland ecosystems increased MeHg concentrations in ecosystems. At the time, most
studies documenting this relationship were conducted in lakes and wetlands, and sulfate
was often added experimentally to test the mechanisms of the relationship. Since then, a
number of new studies have shown that increases in ambient sulfate concentrations can
produce increased MeHg concentrations in surface water and sediments in lakes and
wetlands (as well as increased Hg in wildlife, see Section 12.7). In addition, there is new
evidence that increased sulfate in rivers, streams, and watersheds increased Hg
methylation. Not all studies include information about the form or relative contribution of
S sources in these ecosystems, but the studies provide evidence that current
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concentrations of surface water sulfate contribute to Hg methylation in a broad range of
American aquatic and wetland ecosystems.
12.6.1 Lakes
There is evidence from recent research that higher sulfate concentrations correspond to
higher MeHg concentrations and sulfate reduction rates in these water bodies (Table
12-7). Prairie potholes are shallow wetlands and lakes in depressions created by
glaciation, which depend upon snowmelt and precipitation for their water supply, and
tend to be hydrologically isolated. A survey of prairie pothole wetlands and lakes in
Saskatchewan measured Hg levels in water. Surface water MeHg correlated positively
with sulfate concentrations, and negatively with conductivity and specific ultraviolet
absorbance (SUVA; an indicator of aromatic fraction of DOM), such that surface water
MeHg increased 0.03 ng/L for each mg/L increase in sulfate concentrations, when all
other factors remained constant (Hall et al.. 2009a). In the St. Denis National Wildlife
Area in Saskatchewan, Canada, prairie potholes vary in sulfate concentrations in relation
with geology and position in the landscape. In a study of water MeHg, five upland ponds
had average sulfate concentrations of 1,490 mg/L (S sources are geologic), and four
lowland ponds had average sulfate concentrations of 14 mg/L (Hoggarth et al.. 2015).
MeHg fraction was 185% higher in surface water and 205% higher in sediments in the
upland ponds than in the lowland ponds, which had lower sulfate concentrations
(Hoggarth et al.. 2015). In a similar study of depressional freshwater wetlands in two
lakes in Germany, sulfate reduction rate was 2.5-7.9 times higher annually in the high
sulfate lake (22.7 mg sulfate/L) than in the low sulfate lake (9.0 mg/L), although Hg
cycling was not quantified (Kleeberg et al.. 2016).
Highly elevated sulfate concentrations, as can result from agricultural runoff, can depress
SRP activity and Hg methylation, as sulfide produced by SRPs accumulates and
downregulates SRP activity. In a sampling study of the Amistad International Reservoir
on the Texas-Mexico border, Hg pools in sediment, water, and largemouth bass (for more
on this endpoint, see Section 12.7) were quantified and compared between the Rio
Grande and Devils River branches of the reservoir. The Rio Grande branch had sulfate
concentrations an order of magnitude higher (site with highest sulfate concentration:
230 mg/L sediment pore water), as well as 40% higher total Hg pools in sediments, than
did the Devils River branch [site with highest sulfate concentrations: 23 mg/L (Becker et
al.. 2011)1. However, total Hg and sulfate were negatively correlated with MeHg, and
SRB (researchers used techniques to detect bacterial but not archaeal sulfur reducers)
were present at all sites. Hg methylation in this system was not limited by Hg supply or
biota, and was not stimulated by the Rio Grande's high sulfate levels, originating from
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1 agricultural land use in the watershed. The Devils River branch had 65% higher MeHg
2 concentrations in sediments, and a 230% higher proportion of total sediment Hg in the
3 form of MeHg (Becker et al.. 2011). Becker etal. (2011) posited that the higher MeHg in
4 Devils River sediments was due to higher DOC in this area of the reservoir and to sulfate
5 concentrations (in sediment pore water, 2.5-23 mg/L) being optimal for the metabolism
6 ofSRB.
12.6.1.1 Summary Table
Table 12-7 New studies on nonacidifying sulfur effects on mercury cycling in
lakes.
Type of
Ecosystem
Additions or
Load (kg
S/ha/yr)
Biological and Chemical Effects Study Site
Study
Species
Reference
Lakes and Not reported Surface water MeHg was positively
wetlands correlated with sulfate
concentrations:
ng MeHg/L = -2.94 - 0.44
(conductivity) + 0.303(SC>4) - 0.268
(aromatic fraction of DOM).
49 lakes and
wetlands,
prairie pothole
region,
Saskatchewan,
Canada
Lake water Hall et al.
(2009a)
Prairie
potholes
(shallow
freshwater
marsh)
Lowland ponds,
average [SO42"]
is 14 mg/L
Upland ponds,
average [SO42"]
is 1,490 mg/L
Deposition not
reported
In July, surface water [MeHg] was
290% higher in upland ponds than in
lowland ponds. In August, surface
water [MeHg] was 233% higher in
upland ponds.
Surface water %MeHg was 185%
higher in upland ponds, and
sediment %MeHg was 205% higher
in upland ponds.
Surface water [MeHg] increases with
sediment organic matter: MeHg
(ng/L) = -2.26 + 0.265 (percent
OM).
St Denis
National
Wildlife Area,
Saskatchewan,
Canada
4 lowland
ponds with
high SO42"
5 upland
ponds with
low SO42"
Hoqqarth et
al. (2015)
River and S addition or Sediment MeHg (ng/g) correlated
reservoir deposition not negatively with pore water sulfate
reported concentrations.
Becker et al.
(2011)
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Table 12-7 (Continued): New studies on nonacidifying sulfur effects on mercury
cycling in lakes.
Additions or
Type of Load (kg Study
Ecosystem S/ha/yr) Biological and Chemical Effects Study Site Species Reference
[S042"] in Rio
RG had 40% higher THg than DR.
Grande: pore
water: (means)
74-230 mg/L;
deep water:
(range)
152-342 mg/L
Rio Grande
Sediment,
(RG) and
pore water,
Devils River
and deep
(DR) branches
water;
[SO42"] in Devils
of Amistad
Micropterus
salmoides
DR sediment MeHg was 65% higher
International
River: pore
water: (means)
than in RG sediment, and DR
sediment %MeHg was 65% than in
Reservoir,
Texas
(largemouth
bass)
74-230 mg/L;
RG sediment.
deep water:
(range)
15-168 mg/L
DOM = dissolved organic matter; DR = Devils River; g = gram; ha = hectare; kg = kilogram; L = liter; MeHg = methylmercury;
mg = milligram; ng = nanogram; OM = organic matter; RG = Rio Grande; S = sulfur; S042" = sulfate; THg = total mercury;
yr = year.
12.6.2 Wetlands
Sampling at small scales within peatlands has shown positive relationships between
sulfate concentrations and MeHg concentrations (Table 12-8). In two peatlands at the
Marcell Experimental Forest, Minnesota, researchers monitored water quality at the
upland-peatland interface, hypothesized to be an important zone for methylation due to
labile carbon inputs in runoff from terrestrial communities to the peatland microbial
community. Sulfate peat pore water concentrations ranged from 0-20 mg sulfate/L, and
MeHg concentrations increased 0.037 ng/L for each 1 mg/L increase in sulfate (Mitchell
et al.. 2009). The relationship between sulfate and MeHg is also significant at a larger
spatial scale in the same region. Across four peatlands at the temperate-boreal boundary
in Minnesota and Ontario, MeHg was positively correlated with sulfate in peat pore water
(Spearman's R = 0.237) as well as with pH during the growing season of 2005 (Mitchell
et al.. 2008b). The range of median sulfate levels in these peat bogs during the course of
the study was 0.01-3 mg/L, while the range of MeHg concentrations was 0.35-0.62 ng
MeHg/L (Mitchell et al.. 2008b).
In the Water Conservation Areas outside Everglades National Park, Florida (Class I area),
sulfate concentrations were as high as 48 mg/L near the EAA, whereas in pristine areas
distant from the EAA, sulfate concentrations were less than 0.5 mg/L. Previous studies
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noted that Hg methylation was highest in areas of the wetland where sulfate
concentrations ranged from 0.7 to 1.9 mg sulfate/L (Bates et al.. 2002; Gilmour ct al..
1998). More recently, a study by Corrales et al. (2011). quantified the S budget and
determined that atmospheric deposition of S is 15 kg S/ha/yr, 4% of the total S load in the
WCAs. MeHg concentrations in surface water in the Florida Everglades increase when
sulfate concentrations increase above 1 mg/L, which Corrales et al. (2011) recommended
as a target for sulfate reduction efforts (Figure 12-6).
U)
c
o
(C
U
r
o
o
o
Q>
E
>>
5
1
Threshold
~ % A ~. •
2 4 6 8
Sulfate concentration (mg L-i)
10
L = liter; mg = milligram; ng = nanogram.
Source: Adapted from Corrales et al. (2011).
Figure 12-6 The relationship between surface water sulfate and
methylmercury concentrations in the Florida Everglades.
Microbial sulfate reduction has a negative feedback from its product, sulfide. Orem et al.
(2011) suggested that at high surface water sulfate (>20 mg/L) concentrations in the
Florida Everglades, sulfide accumulates and inhibits methylation. In treatment wetlands
that collect stormwater runoff from the EAA, the concentrations of sulfate are so high
that sulfide inhibition of MeHg may occur at the higher end of the sulfate range. Zheng et
al. (2013) reported on the water quality parameters, total Hg, and MeHg in the inflow and
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outflow waters of a constructed treatment wetland in the Everglades WCAs. The wetland
was a net source of MeHg to surface water between 2000 and 2004, and during this time,
total Hg and MeHg concentrations in water exiting the wetland were negatively
correlated with sulfate concentrations of water flowing into the wetland (Zheng et al..
2013). The range of sulfate concentrations of inflow was 39-110 mg/L sulfate, with
mean sulfate of 59.5 mg/L. Zheng et al. (2013) also constructed multivariate models for
total Hg and MeHg, and even with other factors such as DOC, pH, and chloride in the
model, inflow sulfate remained a strong and negative correlate of outflow Hg
concentrations. The positive relationship between sulfate and MeHg in the Florida
Everglades is significant only at low sulfate (in this study, 39 mg SO42 /L)
concentrations.
12.6.2.1 Summary Table
Table 12-8 New studies on nonacidifying sulfur effects on mercury in wetlands.
Type of Additions or Load
Ecosystem (kg S/ha/yr)
Biological and Chemical
Effects
Study
Study Site Species Reference
Surface
water
Ambient S deposition:
15 kg S/ha/yr as
MeHg surface water Everglades Surface and Corrales et
concentration rises above Agricultural groundwater al. (2011)
suggested threshold level of Area (EAA), FL
1 mg/L sulfate in
groundwater (Figure 12-6).
quantified by U.S. EPA
CASTNET (FL11 and
FL99)
Total S load is
110,303 metric tons/yr,
atm dep is 4% of total
Bogs
Peatland pore water
median [SO42"]: 0.1,
0.4, 0.6, 3.0 mg/L
S addition or
deposition not reported
Pore water [SO42"] (mg/L)
was positively correlated
with pore water MeHg
(Spearman R = 0.237) and
total Hg (Spearman
R = 0.576).
Four peatlands: Pore water Mitchell et al.
two in Marcell in peat (2008b)
Experimental
Forest, MN; two
in Experimental
Lakes Area,
Ontario
Upland- S deposition not
peatland reported
interface
(opearman k = u.o»):
rso7l = 0-20 mg/L n9 MeHg/L = 0.037 * (mg
S042"/L) + 0.58.
MeHg was positively
correlated with sulfate
(Spearman R = 0.39):
S2 and S6 Peat pore Mitchell et al.
peatlands, water (2009)
Marcell
Experimental
Forest, MN
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Type of
Ecosystem
Additions or Load
(kg S/ha/yr)
Biological and Chemical
Effects
Study Site
Study
Species
Reference
Constructed
wetlands
S load in surface water
as [S042"]:
39.3-110.1 mg/L
(mean 59.5 mg/L)
S deposition not
reported
Between 2000-2004, total
Hg and MeHg wetland
export were negatively
correlated to inflow [SO42"].
THg: (log ng
THg/L) = -1.22 * (log mg
S0427L) + 2.40; MeHg: (log
ng MeHg/L) = -1.91 x (log
[SO42"]) + 3.02.
Between 2000-2011, sulfate
was negatively correlated
with THg and MeHg as one
variable in multivariate
models.
Western Palm Surface Zheng et al.
Beach County, water (2013)
FL
atm = atmospheric; CASTNET = Clean Air Status and Trends Network; dep = deposition; EEA = Everglades agricultural area;
ha = hectare; Hg = mercury; kg = kilogram; L = liter; MeHg = methylmercury; mg = milligram; ng = nanogram; S = sulfur;
S042" = sulfate; THg = total mercury; yr = year.
12.6.3 Streams and Rivers
Positive relationships between sulfate and MeHg in streams and rivers indicate that
increasing sulfate increases Hg methylation in these ecosystems (Table 12-9). Tsui et al.
(2008) constructed mesocosms to mimic leaf decomposition in the hyporheic zone of
Minnesota streams and rivers, where conditions are hypothesized to be favorable for the
SRB that methylate inorganic Hg. Water samples were collected from seven streams or
rivers in Minnesota, with sulfate levels at collection of 4.0-26.2 mg sulfate-S/L (with an
ultrapure water sample as a control, 0.0 mg S/L), and incubated with Acer sp. (maple)
leaves. After 66 days of decomposition, the total Hg released from the decomposing litter
into solution as dissolved Hg increased with initial sulfate concentration (R2=0.541,
p=0.038), and the fraction of total Hg that had been transformed to MeHg increased in a
power law dependence upon initial sulfate concentration [R2=0.572, p=0.030, see Figure
12-7. (Tsui etal. 2008)1.
The South River in Waynesboro, VA, was contaminated by historical (1929-1950)
textile industrial use and release of Hg. Sediments were collected within the channel at
ten study sites at increasing distances downstream of the historic Hg source in 2008.
MeHg concentrations in the sediment increased linearly with increasing sediment pore
water sulfate concentrations, with a 0.06 ng increase in MeHg per gram of sediment for
every 1 mg/L increase in sulfate pore water concentration, with mean pore water sulfate
concentrations ranging from 2-16 mg/L (Yu et al.. 2012).
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35
f2 = 0,572
30
25
20-
15 ¦
5 -
0 ¦
Eh- %MeHg
m
0
0
10 20
DS04 (mg S L"1)
30
%MeHg = methylmercury fraction; DHg = mercury dissolved in mesocosm water; DS04 = sulfate dissolved in mesocosm water;
L = liter; mg = milligram; ng = nanogram; S = Sulfur; THg = total mercury.
Source: Figure 2A in Tsui et al. (2008).
Figure 12-7 The relationship between surface water sulfate and total mercury
or methylmercury fraction in river-leaf litter mesocosms.
Chemical constituents measured at watershed outflows represent the cumulative
microbial and abiotic chemical transformations within the watershed. A watershed in
which SRB are present will therefore have higher MeHg and lower sulfate concentrations
in its outflow than an adjacent watershed without active SRPs that experiences the same
S and Hg deposition loads. Many of the following studies document negative
relationships between sulfate concentrations and MeHg concentrations at streams or
rivers that drain entire watersheds, outflows where sulfate and Hg concentrations reflect
upstream sulfate stimulation of SRPs and Hg methylation. In a tributary stream draining a
wetland in Wisconsin, there were seasonal trends in sulfate and MeHg concentrations
indicative of wetland Hg methylation. Sulfate in the stream declined 290% between April
and June 2003, indicative of S immobilization or reduction in the wetland during the
early summer, and MeHg increased 69% over the same time period (Watras and
Morrison. 2008). This increase in MeHg and simultaneous decrease in sulfate in stream
water concentrations suggests upstream activity of SRB in Hg methylation.
In streams draining wetlands in the Archer Creek watershed in the Adirondack
Mountains, New York, water sulfate concentrations were lower than in streams upstream
of wetlands (Selvendiran et al.. 2008a). Wetlands retained or reduced sulfate in microbial
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processes that methylated Hg during the growing season, which would account for the
elevated MeHg concentrations in wetland-draining streams compared to upland streams.
There was a negative correlation between sulfate concentrations and MeHg
concentrations in streams draining the wetlands where Hg methylation occurred, with a
0.11 ng/L increase in MeHg concentrations in the stream for each mg/L sulfate removed
from surface water (Selvendiran et al.. 2008a). Selvendiran et al. (2009) measured and
calculated Hg budgets for the adjacent watersheds of Arbutus Lake and Sunday Lake in
the Adirondacks, New York, measuring inlet and outlet streams at both water bodies as
well as lake surface water at Arbutus. Across both watersheds, MeHg concentrations
were negatively correlated with sulfate concentrations (Figure 12-8).
Sunday Lake
Arbutus Lake
r = 0.49;/j< 0,0001; 131
0.8
O
0.6
0.4
0.0
2
3
4
5
6
7
Sulfate (mg S04' L 1)
L = liter; MeHg = methylmercury; mg = milligram; ng = nanogram; S042" = sulfate.
Source: From Selvendiran et al. (2009).
Figure 12-8 Methylmercury concentrations as a function of sulfate
concentrations at inlet and outlet streams of Sunday and Arbutus
Lakes, and at lake surface water samples from Arbutus Lake.
This pattern was driven by the concentrations measured in the streams in Sunday Lake,
which drains a watershed that is approximately 20% wetlands (Selvendiran et al.. 2009).
indicating that SRB in upstream wetlands may have been reducing sulfate and
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1 methylating Hg to impact the measured stream surface water. Arbutus Lake drains a
2 watershed of which wetlands comprise only 4% of surface area, which may explain the
3 relatively higher sulfate concentrations and the lower mean and variability of MeHg
4 (Selvendiran et al.. 2009). In watersheds where S and Hg deposition rates do not differ
5 spatially, negative correlations between sulfate concentrations and MeHg show the link
6 between sulfate reduction and Hg methylation.
12.6.3.1 Summary Table
Table 12-9 New studies on nonacidifying sulfur effects on mercury in streams
and rivers.
Type of
Additions or Load
Biological and
Ecosystem
(kg S/ha/yr)
Chemical Effects
Study Site
Study Species Reference
Streams
S deposition not
During the growing
Archer Creek,
Stream water Selvendiran et
reported
season, MeHg increased
Adirondacks,
al. (2008a)
monthly [SO42"]
with decreasing sulfate
New York
means in streams:
concentrations: ng
4-8 mg/L
MeHg/L = -0.11 x (mg
S042"/L) + 0.88.
Streams and
lakes
Not reported
MeHg was negatively
correlated with water
sulfate concentrations:
ng MeHg/L = 6.67 * (mg
S042"/L) -2.40.
Arbutus Lake
and Sunday
Lake,
Adirondacks,
New York
Stream and
lake surface
water
Selvendiran et
al. (2009)
Fluvial zones S deposition not
(streams and
rivers)
reported
Initial water SO42
concentrations
(mg/L): range
4.0-26.2, mean
median 6.1
9. 2,
Following aquatic anoxic Mesocosms Acer sp. and Tsui et al.
decomposition of leaf
litter, total dissolved Hg
increases in decreasing
proportion to initial SO42"
concentration. Dissolved
%MeHg increases in
decreasing proportion to
initial SO42"
concentration.
constructed with
samples from
Cedar Creek
LTER (leaf litter)
and 7 streams
or rivers (water),
Minnesota
stream
microbial
communities
(2008)
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Table 12-9 (Continued): New studies on nonacidifying sulfur effects on mercury in
streams and rivers.
Type of
Ecosystem
Additions or Load
(kg S/ha/yr)
Biological and
Chemical Effects
Study Site Study Species Reference
Lakes:
rain-fed LRL,
DL drains
stream fed
by wetland
S deposition not
reported
LRL:
[S042"] = 2.5 mg/L,
DL:
[S042"] = 2.8 mg/L,
stream feeding DL
[SO42"] = 1.6 mg/L
In stream draining
wetland, SO42"
decreased 290% as
MeHg increased 69%
over the course of spring
and summer.
Little Rock Lake
(LRL) and
Devils Lake
(DL), Wisconsin
Lake water
Watras and
Morrison
(2008)
DL = Devils Lake; ha = hectare; kg = kilogram; L = liter; LRL = Little Rock Lake; LTER = Long Term Ecological Research;
MeHg = methylmercury; mg = milligram; ng = nanogram; S = sulfur; S042" = sulfate; yr = year.
12.6.4 Coastal Marshes and Estuaries
Mercury methylation occurs in estuarine and marine ecosystems (Lchnherr et al.. 2011;
Benoitetal.. 1998). but sulfate concentrations in saline water are generally so high that
direct deposition of SOx is unlikely to alter existing MeHg dynamics. An early study on
coastal marshes in Georgia showed that both sulfate reduction and MeHg production
were at their highest rates in the top 4 cm of the marsh soil (King et al.. 1999). An older
study of Hg dynamics in the Patuxent River estuary, Maryland, where sulfate
concentrations range from 150 to 1,200 mg/L, found no correlation between sediment
pore water sulfate concentrations and MeHg fraction in sediments (Benoitetal.. 1998V
There was a peak in surface water MeHg fraction of 25% at the mouth of the river, which
authors speculated was due to mixing by wind of stratified anoxic water from the
Chesapeake Bay with the river water (Benoitetal.. 1998). MeHg sediment fraction
across the Patuxent River, Maryland, was negatively correlated with sulfide sediment
concentrations, presumably because Hg bound to sulfide is unavailable to methylating
bacteria (Benoitetal.. 1998).
12.6.5 Rice in the San Joaquin Delta, California
There is evidence from the California Central Valley that microbial Hg methylation
occurs in managed agricultural wetlands that produce rice, which suggests a route to
MeHg exposure for humans and wildlife. California (particularly the Central Valley
where these studies were conducted) is the second largest producer of rice in the U.S., as
well as an important stop along a major bird migratory route. The USGS coordinated an
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intensive research effort on Hg cycling and methylation of Hg in wetlands of the Central
Valley of California, focusing on the Yolo Bypass Wildlife Area, located in the northwest
region of the San Francisco Bay delta. There are permanent wetlands dominated by
Typha spp. (cattails) and Scirpus spp. (tule), and also agricultural wetlands where Oryza
sativa (white rice) and Zizania palustris (wild rice) are cultivated. Rice fields go through
annual drying and rewetting cycles: flooded in the summer, drained for fall harvesting,
and flooded in the winter to speed decomposition of rice straw and organic residue.
In the Yolo Bypass, California, permanent and agricultural wetlands were sampled over
the course of a growing season, June 2007-April 2008. About 10% of the 105 water
samples taken over that time period exceeded the U.S. EPA Hg water quality criterion of
50 ng total Hg/L, and total Hg was higher in the center and outflow of agricultural
wetlands than in permanent wetlands (Alpers et al.. 2014).
Across the wetlands, all of the water samples taken for MeHg determination exceeded the
San Joaquin delta regulatory total maximum daily load (TMDL) limit of
0.06 ng MeHg/L. In fact, MeHg concentrations in all water samples exceeded 1 ng/L,
with maximum measured water MeHg of 37 ng/L at the outlet of wild rice fields during
harvest. Water MeHg concentrations were significantly higher, about twice as high in the
agricultural fields, as in the permanent wetlands (Alpers etal.. 2014). and sediment
MeHg concentrations were also higher in the agricultural wetlands (Marvin-DiPasquale
et al.. 2014). The water MeHg fraction ranged from 1-80%, with a median value of
6.4%, and there were seasonal variations in agricultural but not permanent wetlands. In
agricultural wetlands, MeHg fraction increased 20-fold between June and August in
fields where white or wild rice was grown, and MeHg fraction increased 5-fold in fallow
fields over the same time period (Alpers et al.. 2014).
Hg methylation in the permanent and agricultural wetlands of the Yolo Bypass,
California correlated with S, Fe, and manganese (Mn) reduction. The strongest
correlations of MeHg fraction in the wetlands were with metrics of Mn, not Fe or S,
reduction (Alpers et al.. 2014V Sulfate was not a limiting factor of Hg methylation in the
wetlands, although 834S and sulfate:CI in outlet waters indicated that sulfate reduction
occurred in the wetlands, with at least 20% of sulfate in the water column reduced
(Alpers et al.. 2014). In agricultural wetland sediments, mineralization of C by iron
reduction was 2.4 times the mineralization of C by sulfate reduction, indicating that Fe
reduction was more important than S reduction in terms of anaerobic decomposition
(Marvin-DiPasquale etal.. 2014). Furthermore, addition of sulfate fertilizer in rice fields
did not raise measured sulfate reduction rates to the higher levels observed in fallow,
unfertilized fields, indicating that sulfate was not a limiting factor on anaerobic microbial
activity in the agricultural wetlands (Alpers et al.. 2014; Marvin-DiPasquale et al.. 2014).
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In the Yolo Bypass, California, seasonal wetland export of MeHg occurs during the
winter as well as the summer. In the summer, newly methylated MeHg is drawn into the
root zone of the sediment by plant transpiration, and in winter, diffusion releases MeHg
from the sediment into the water column (Bachand et al.. 2014). The short-term storage
of MeHg in wetland soils decreases MeHg exports from the wetland, but increases
exposure of wetland fish to MeHg (Windham-Myers et al.. 2014b). Also, MeHg in rice
seeds were correlated with root MeHg (r = 0.90), suggesting that MeHg from the root
zone may be transported through the plant to tissues that are consumed by migrating
waterfowl (Windham-Myers et al.. 2014a). MeHg in rice fields and in rice grains may be
an important pathway to human and wildlife Hg exposure via rice consumption.
Evidence from fish Hg levels in different wetland types suggests that fluctuating water
levels in the agricultural fields, as well as high levels of organic carbon from winter
decomposition of rice straw, raise Hg methylation rates in the rice fields above rates in
the permanent wetlands. Mercury concentrations of penned Gambusia affinis
(mosquitofish) rose 12.1 times over initial concentration in white rice fields, 5.8 times in
wild rice fields, and 2.9 over initial fish Hg concentration in the permanent wetlands
(Ackerman and Eagles-Smith. 2010). and these trends were echoed by Hg concentrations
in wild mosquitofish and Menidia audens (Mississippi silversides) caught in the
wetlands. However, trends of Hg concentrations in macroinvertebrates did not follow
trends in fish. There was no difference by wetland type (permanent, white rice, wild rice)
in Hg concentrations of collected water boatmen, Corisella spp., which feed on plant and
algal biomass. Hg concentrations in collected backswimmers, Notonecta spp., which are
predatory, were higher in collections from permanent wetlands than in collections from
cultivated rice wetlands (Ackerman et al.. 2010).
12.7 Sulfur Impacts on Mercury in Wildlife
Mercury has no known beneficial property in living cells. MeHg is bioconcentrated by
living cells, in which it forms strong bonds with thiosulfate groups in organic
compounds. It is common for MeHg to be present at progressively higher concentrations
up the trophic level of food chains, as MeHg consumed is remarkably persistent (Figure
12-9). A recent report by the USGS reviews the known effects of Hg on wildlife. Fish
and birds experience negative physiological and reproductive effects at Hg levels below
the 0.3 ppm tissue level set by the U.S. EPA to protect human health (Wentz et al.. 2014).
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r Top ^
predator fish
Algae and other
microorganisms
Water
USEPA fish tissue mercury criterion - 0.3 parts per million
0.001
Ł¦ 0.0001
>- 0.00001
0.000001
0.0000001
0.00000001
Increasing trophic level
Forage
Note logarithmic scale of y-axis. The top and bottom of each circle represent the range of measured methylmercury concentrations
from streams in Oregon, Wisconsin, and Florida sampled during 2002-2006, and in New York and South Carolina sampled during
2007-2009.
Source: From Wentz et al. (2014).
Figure 12-9 Bioconcentration and biomagnification result in methylmercury
concentrations about 1 million times higher in predator fish than
in stream water.
1 S deposition affects the production and net amount of MeHg in water bodies, increasing
2 accumulation of Hg up the food chain (Table 12-10). but will not affect the rates at which
3 Hg is transferred between trophic levels. Early work by Bloom et al. (1991) in seepage
4 lakes of varying pH in the Northern Highland Lake District, Wisconsin, considered
5 whether varying deposition would affect the rates at which MeHg accumulates in biota.
6 The authors sampled five lakes with common geology but a range of pH (5.1-7.2,
7 including the experimentally acidified north basin of Little Rock Lake), which the
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authors ascribed to varying acidic deposition loads. The fraction of Hg was higher in
Perca flavescens, yellow perch, than in seston, reflecting bioaccumulation of MeHg at
higher trophic levels, but there was no detected effect of pH (and by extension, S
deposition load) upon relative bioaccumulation across lakes (Bloom et al.. 1991). In
Dickie Lake, Ontario, early studies documented the biomagnification of Hg in higher
trophic levels of the lake. MeHg concentrations were 0.2 ng/g in sediments; Hg
concentrations were 56.5 ng/g in periphyton, 143 ng/g in P. flavescens, and 703 ng/g in
Micropterus spp. [largemouth and smallmouth bass, (Kerry et al.. 1991)1. Sulfate effects
on biomagnification were not documented in these studies, although sulfate was
measured at 6-8 mg/L in lake water, and microbial sulfate reduction and Hg methylation
within the lake sediments were demonstrated with sediment slurry incubations (Kerry et
al.. 1991).
Experimental S addition studies demonstrate that S addition increases Hg burdens in
different trophic levels. Little Rock Lake, Wisconsin was the site of a multiyear
(1985-1990), progressively acidic S addition study, in which the basins of this lake were
separated by a plastic barrier, allowing the north half to be experimentally acidified while
the southern half served as a control. Abiotic compartments and biota of the lake were
intensively sampled during the course of the experiment. Aqueous MeHg concentrations
were 2 times higher in the treatment basin, while zooplankton MeHg concentrations
(ng/g) were 1.8 times higher and microseston MeHg concentrations were 2.75 times
higher in the treatment than the control basin (Frost et al.. 1999; Watras and Bloom.
1992). S amendment also affected MeHg in Perca flavescens (yellow perch): MeHg
concentrations were 12-100% higher in 1-year-old yellow perch from the treatment
basin, and the annual mean burden (fig MeHg/fish) was 16-214% higher in the treatment
basin over 5 of the 6 years of the experiment (Frost et al.. 1999; Wiener et al.. 1990).
Decreasing S loads result in decreased Hg burdens in biota. The S addition experiment at
the Marcell peat bog also shows the effects of S addition upon Hg burdens in an animal
on a lower trophic level. In the S addition and S recovery experiments at the S6 peat bog,
Marcell Experimental Forest, Minnesota, elevated S increased Hg levels in sampled
Culex spp. (mosquito) larvae. Mosquito larvae are important to consider as a food source
because they are widely consumed by invertebrate predators, fish, amphibians, and birds.
In spring 2009, mosquito larvae Hg was 126% higher in plots which had received
32 kg S/ha/yr addition for 9 years than in mosquito larvae from control plots (Wasik et
al.. 2012). Recovery plots received 32 kg S/ha/yr from 2001-2006 and no S addition after
2006, and when these plots were sampled in 2009, Culex spp. (mosquito) larvae had Hg
levels 34% higher in recovery plots than in control plot mosquitoes, indicating legacy
effects of past S addition. However, recovery plot mosquito Hg concentrations were 41%
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lower than in mosquitoes from plots still receiving S additions, indicating that decreases
in S addition will decrease biotic Hg concentrations (Wasik et al.. 2012V
In stormwater treatment wetlands draining the EAA in Florida, sulfate concentrations are
elevated by agricultural runoff, and ranged from 39-110 mg/L between 2000 and 2007.
Under these very high sulfate surface water concentrations, Hg levels (mg Hg/kg fish) in
bioindicator fish species Gambusia holbrooki (mosquitofish) were negatively correlated
with inflow water sulfate concentrations (Feng et al.. 2014) because the higher end of the
sulfate concentration range reached levels inhibitory to SRPs. In the Everglades
Protection Area, where water sulfate concentrations were lower and ranged from
0-60 mg/L in surface water, relationships between sulfate and fish Hg levels were more
complicated. Gambusia spp. (mosquitofish), Lepomis spp. (sunfish), and largemouth bass
were sampled annually between 1998 and 2009 (Gabriel et al.. 2014). In all three fishes,
fish Hg increased between 0-1 mg sulfate/L, and reached highest levels of tissue Hg
concentration between 1 and 12 mg sulfate/L (see Figure 12-10). Based on these
relationships, Gabriel et al. (2014) recommended a sulfate water standard of 1 mg/L. Two
papers challenged this analysis and interpretation of the sulfate and fish Hg data. In a
commentary, Julian et al. (2015) suggested that the variability in fish Hg was too high to
correlate with sulfate concentrations, and in analyses of largemouth bass collected
between 2005-2011, Hg concentrations in fish correlated with alkalinity, pH, and
specific conductance as well as sulfate (Julian and Gu. 2015). Gabriel et al. (2015)
responded to Julian's commentary by highlighting the similarity of fish Hg patterns to
documented MeHg water column concentrations in the Florida Everglades, and suggested
that sulfate reductions are the most efficient way to reduce Hg loads in fish because about
60% of the Everglades area has sulfate concentrations exceeding 1 mg/L (Orem et al..
2011). Using structural equation modeling, Pollman (2014) showed that sulfate was
second only to periphyton MeHg concentrations in predicting Hg burdens in
mosquitofish in the Everglades, although the relationships among predictive factors were
complex and involved both direct and indirect effects.
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0.35
0.30 -
0.25 -
o> 0.20 -|
Ł 0.15 -|
o
=3
tn 0.10 -I
O
0.05 -
0.00 -
• running average
• •
••• •
•i
• •••J • • ^ . \ * •
D
t——i
I |fcl M4
hm 1—i—i i i ii 11111 ii mi 1—i—i i i i i m 1111111 m 1—i—i i i i 111 mi
0.006
running average
E 0.005
o>
~ 0.004
o) 0.002
X
^ 0.001
3
cn
0.000
running average
a> 0.2
10 20 30 40 50
Surface water sulfate (mg/L)
m
TF
¦++*-
ft
I ' • I !• I'
i i i i ii 1111 ii in i 1—i—i i i i i 1111 ii in ii
0.1 1 10
Surface water sulfate (mg/L)
i i Milium'
L = liter; kg = kilogram; mg = milligram; mm = millimeter; THg = total mercury.
Panels A-C show the running average of mercury concentrations in (A) Gambusia spp. (n = 484), (B) Lepomis spp. (n = 2,559), and
(C) Micropterus salmoides (n = 679). Panels D-F show the same data with sulfate transformed to a log scale to better illustrate the
peak in fish Hg concentrations that approximately corresponds to sulfate concentrations of 1-10 mg/L. Samples were collected from
12 fish and 12 sulfate stations within the Everglades, between 1998-2009,
Source: Figure 3 in Gabriel et al. (2014).
Figure 12-10 Tissue mercury concentrations as a function of surface water
sulfate concentrations (n = 2,360 surface water samples) in the
Everglades Protection Area.
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A number of studies document Hg burdens in fish without also quantifying contributions
of S to methylation, but other relationships between S and MeHg documented in the 2008
ISA suggest that the findings of these studies may be relevant (U.S. EPA. 2008a). In the
Alabama River basin around Mobile, AL, there was no relationship across 52 sites in the
watershed between Hg burdens in largemouth bass and MeHg fractions in sediments or
water (Warner et al. 2005V However, a subset of seven of the sites were downstream of
wetlands, and in these sites the bass Hg burden was positively correlated with watershed
area (r2 = 0.71), indicating that wetlands may contribute to higher Hg burdens in fish as
well as to higher MeHg concentrations in water (Warner et al.. 2005). In a study of Hg
burdens in South Dakota, Stone etal. (2011) analyzed water quality and fish samples
from one impoundment and five natural lakes, and found a positive correlation
(If = 0.928) between water sulfate measurements and Hg in piscivorous Sander vitreus
(walleye). However, sulfate concentrations were not reported, and sulfate measurements
and fish samples were not collected simultaneously, with a gap of up to 3 years between
collection of fish and water samples. In the Amistad International Reservoir, Texas,
elevated MeHg in sediments of one branch of the reservoir correlated with Hg
accumulation in young (age: 0-3 years) largemouth bass. The Devils River area had
elevated sediment MeHg compared to the Rio Grande area of the reservoir (see
Section 12.6.1). and the length-standardized mean of muscle Hg was 38% higher in
Devils River than in Rio Grande bass (Becker etal.. 2011). Of 138 largemouth bass (age
>3 years) line-caught at the reservoir in April 2007, 77% exceeded the U.S. EPA
recommended human consumption value of 0.3 mg Hg/kg (or 0.3 ppm), and mean fish
Hg was 0.51 mg/kg fish, although fishing site data for these samples were unavailable,
preventing assessment of connections between sediment MeHg and Hg levels in these
large fish (Becker etal.. 2011).
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12.7.1
Summary Table
Table 12-10 New studies on nonacidifying sulfur effects on mercury in wildlife.
Type of
Ecosystem
Additions or Load
(kg S/ha/yr)
Biological and
Chemical Effects
Study Site Study Species Reference
River S addition or
deposition not
reported
[SO42"] in Rio
Grande: pore water:
(means)
74-230 mg/L; deep
water: (range)
152-342 mg/L
[SO42"] in Devils
River: pore water:
(means)
74-230 mg/L; deep
water: (range)
15-168 mg/L
M. salmoides muscle Hg
(mg/fish kg) was 38%
higher in DR than RG.
Rio Grande
(RG) and Devils
River (DR)
branches of
Amistad
International
Reservoir,
Texas
Sediment, pore Becker et al.
water, and
deep water;
Micropterus
salmoides
(largemouth
bass)
(2011)
Constructed
S load as [SO42 ] in
Fish Hg (Y = log mg
Western Palm
Gambusia
Fena et al.
wetlands
wetland inflow:
Hg/kg G. holbrooki) was
Beach County,
holbrooki
(2014)
39-110 mg/L
negatively correlated with
Florida
(eastern
water sulfate (X = log mg
mosquitofish)
SC>42"/L) concentrations
and surface
in 3 treatment wetlands:
water
Y = -2.09X + 2.60;
Y = -3.17X + 3.80;
Y = -1.09X- 0.01.
Wetlands
S load as [SO42"] in
Fish Hg (mg Hg/kg or mg
Everglades
Gambusia spp.
Gabriel et al.
and canals
surface water:
Hg/kg/mm for Lepomis)
protection area,
(mosquitofish),
(2014)
0-60 mg/L
increased over 0-1 mg/L
Florida
Lepomis spp.
SO42", reached peak
(sunfish), and
levels at 1-12 mg/L
Micropterus
SO42", and decreased
salmoides
over 12-25 mg/L SO42",
(largemouth
to remain flat at SO42"
bass)
concentrations
25-60 mg/L.
Lakes
Not reported
Fish Hg is positively
1 impoundment
Sander vitreus
Stone et al.
correlated (r2 = 0.928)
and 5 natural
(walleye)
(2011)
with lake water SO4
lakes, South
(mg/L).
Dakota
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Table 12-10 (Continued): New studies on nonacidifying sulfur effects on mercury
in wildlife.
Type of
Ecosystem
Additions or Load
(kg S/ha/yr)
Biological and
Chemical Effects
Study Site Study Species Reference
Bog Ambient S deposition:
5.5 kg/ha/yr (mid
2000s) as quantified
by NADP Station
MN16
S addition:
32 kg S/ha/yr
dissolved in pond
water and delivered
by sprinklers (mimics
4x the 1990s
deposition rate)
Hg levels in Culex spp. S6 peatland,
increased 126%.
Culex spp. Hg was 41%
lower in recovery
treatment than under
SO4 treatment, but still
34% higher than control.
bog section,
Marcell
Experimental
Forest,
Minnesota
Pore water,
peat, and
Culex
spp.(mosquito)
larvae
Wasik et al.
(2012)
DR = Devils River; ha = hectare; Hg = mercury; kg = kilogram; L = liter; mg = milligram; NADP = National Atmospheric Deposition
Program; RG = Rio Grande; S = sulfur; S04 = sulfate; yr = year.
12.8 Extent and Distribution of Sensitive Ecosystems
Reservoirs in which water levels fluctuate enough to expose sediments may be
particularly susceptible to S deposition effects on MeHg production because mud flats are
directly exposed to the atmosphere and then flooded to create conditions favorable to Hg
methylation by SRPs. Older work in the ELA, Ontario, showed that reservoir creation
leads to a pulse of MeHg production. A small watershed was flooded in 1993, and Hg
and MeHg fluxes were measured over the next decade (St.Louis et al.. 2004). Before
flooding, 90% of the annual total Hg input and 130% of the annual MeHg was retained
by the wetland. In the first 3 years following flooding, 100-170% of the annual total Hg
input was exported annually; and in Years 5-9, 69-79% of the annual total Hg input was
exported annually. MeHg was high following flooding, 60-80% in water, and 300-860%
of the annual MeHg input was exported annually from the reservoir (St.Louis et al..
2004). The reservoir creation also affected Hg in the food web: MeHg in zooplankton
was 7-10 times higher in the first 3 years of flooding, and 14-30 times higher Years 4-9,
than MeHg in preflood zooplankton (St.Louis et al.. 2004). Researchers stocked finescale
dace (current scientific name, Chrosomus neogaeus) annually, and found that their Hg
body burden increased 306% following a year in the reservoir (St.Louis et al.. 2004).
More recently, at the Cottage Grove Reservoir, Oregon, elevated MeHg concentrations in
the fall outflow (4-13% MeHg fraction compared to 0.5-7% MeHg in the river flowing
into the reservoir) were linked to seasonal water fluctuations (Ecklev et al.. 2015). The
reservoir water level is lowered from September to February to allow the dam to catch
and regulate spring flooding, and so 50% of the reservoir area is exposed mud flats in the
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winter. Sulfate was below detection limits (0.005 mg sulfate/g sediment, reported as
5 jxg/g) in permanently inundated reservoir sediments, but was 0.0011 mg sulfate/g
sediment (11 jxg/g) in mudflat sediment. MeHg concentrations were higher at sediment
surfaces than in the sediment profile at seasonally inundated sites, indicating that MeHg
production was occurring there; in contrast, [MeHg] was constant across sediment depths
in the permanently inundated sites, indicating that settling of MeHg into sediments was
the only process occurring there (Ecklev et al.. 2015).
The National-Scale Assessment of Mercury Risk to Populations with High Consumption
of Self-Caught Freshwater Fish of 2011 (U.S. EPA. 201 lc) compiled fish Hg load data
on a national scale, which can be considered a county-wide sampling of ecosystems
where Hg loads in fish are high. The assessment did not directly quantify or analyze
sulfate effects, but it considered patterns of Hg deposition and Hg concentrations in
freshwater fish caught between 2005-2009 by state regulatory agencies, and modeled the
extent to which reductions in Hg deposition would affect subsidence-level human
consumers of fish from U.S. water bodies. Fish collections showed that there were
elevated fish Hg levels in water bodies across the country, although high fish Hg
concentrations were more common in the eastern U.S. [see Figure 12-11 (U.S. EPA.
20Uc)]. In this study, 5% of total Hg deposition was attributed to coal and oil-fired
electric utility steam generating units (EGUs), but EGUs contributed 9% to fish tissue
levels of Hg.
The 2014 USGS's report on mercury in streams (Wentz et al.. 2014) suggests that eastern
water bodies, watersheds with high wetland cover, and watersheds with low population
densities are linked to higher MeHg concentrations in streams and in stream biota.
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Fish Tissue Mercury Data
(HUC12-level 75th percentile values, ppm)
* 0.000000 - 0.1 09143
* 0.1091 44 - 0.1 95000
* 0195001 - 0 300000
* 0.300001 - 0.479000
* 0.479001 - 6.605000
HUC12 = 12-digit hydrologic unit code.
Source: U.S. EPA (2011c)
Figure 12-11 Fish mercury concentrations across the U.S.
12.9 Summary of Nonacidifying Sulfur Effects
Sulfate deposition has a number of effects beyond acidification in ecosystems. In the
2008 ISA, the evidence was sufficient to infer a causal relationship between S deposition
and increased methylation of Hg, in aquatic environments where the value of other
factors was within adequate range for methylation. The 2008 ISA surveyed literature
from approximately 1980 to 2008 and described the qualitative relationships between
sulfate deposition and a number of ecological endpoints, including altered S cycling,
sulfide phytotoxicity, internal eutrophication of aquatic systems, altered methane
emissions, increased Hg methylation, and increased Hg loading in animals, particularly
fish. Key findings from the 2008 ISA and new literature are summarized below for
nonacidifying effects of sulfate deposition. Table 12-11 summarizes recent thresholds
and quantitative relationships describing effects of sulfate deposition. This new
information strengthens the weight of evidence presented in the 2008 ISA and the body
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of evidence is sufficient to infer a causal relationship between S deposition and
increased methylation of Hg in wetland and aquatic ecosystems where the value of
other factors is within adequate range for methylation.
12.9.1 Terrestrial Sulfur Cycling
The 2008 ISA noted that S is an essential plant nutrient, and that S deposition can affect
plant protein synthesis by affecting S availability for S containing amino acids as well by
affecting N uptake. Sulfate can be taken up directly by plant roots as well as by soil
microbes, or it can adsorb to soil particles. The 2008 ISA reported that watersheds in the
Southeast, which retained more S than was deposited during high S loading in the 1980s,
experienced reduced S loads in the 1990s but continued to export historically deposited
sulfate in streams. In the Northeast, budgets of sites from the 1980s indicated that high S
deposition caused high sulfate export in streams. On a national level, S deposition
resulted in increased S content in organic matter in soils, and studies suggested that
mineralization of this stored S may contribute to elevated sulfate-leaching for decades
after reductions in S deposition. More recent research confirms that watersheds in the
Northeast continue to leach more S than they received from S deposition, as much as
24-45% more S than S deposition load (Mitchell et al. 2011).
12.9.2 Aquatic Sulfur Cycling
The 2008 ISA reported that nonacidifying effects of S in freshwater systems will be
affected by water residence times, with larger lakes and beaver ponds providing ample
opportunity for SRPs to reduce sulfate and generate acid-neutralizing capacity (ANC).
Early work showed that a 1 mg/L increase in sulfate concentration in Dickie Lake,
Ontario, increased S reduction rates 0.35 mg S/L/day (Kerry et al.. 1991).
The 2008 ISA reported the role of wetlands in removing sulfate from surface water and
storing it in sediments or biomass, but also highlighted the way drought reverses this
capacity, to make wetlands sources of S to downstream waters. Specifically, studies
reviewed in the 2008 ISA demonstrated that under drought conditions, sulfide in
previously saturated moss or sediments is exposed to atmospheric oxygen and reoxidized
to sulfate. This resulted in high sulfate concentrations in surface water when the water
table rose to its former level, and MAGIC modeling showed that variable water levels
due to climate change-induced droughts would delay ANC recovery in the Plastic Lake
watershed, New York (Aheme et al.. 2004). In Little Rock Lake, Wisconsin, water level
fluctuation due to drought added an additional 5 kg S/ha/yr from internal ecosystem S
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stores to the lake (Watras and Morrison. 2008). Recent work confirmed that periods of
drought result in elevated water sulfate concentrations during the recovery period
following the drought (Wasik et al.. 2012).
12.9.3 Sulfide Toxicity
In aquatic systems or in saturated soils, SRPs convert sulfate into sulfide, which inhibits
nutrient uptake in freshwater aquatic and wetland plant species. The 2008 ISA showed
that sulfide toxicity reduced biomass of wetland plants and aquatic macrophytes in
mesocosms under aquatic S concentrations higher than those that occur in U.S. regions
with high S deposition. Recent research has shown sulfide phytotoxicity occurs at
ambient aquatic S concentrations within multiple ecosystems in the U.S. (Figure 12-12).
Sulfide decreases total plant cover and cover of dominant species in a New York fen
(Simkin et al.. 2013) and decreases the growth rate of Everglades, Florida, keystone
species Cladium jamaicense (sawgrass) at surface water concentrations of 7.5 mg
sulfide/L (Li et al.. 2009). The state of Minnesota is also working on a sulfide standard to
protect the economically and culturally important Zizania palustris (wild rice), and has
proposed a water standard of 0.165 mg sulfide/L to protect the species (MPCA. 2015a).
This new information shows that sulfide toxicity occurs in North American wetlands
under current deposition conditions, and the evidence is sufficient to infer a causal
relationship between S deposition and changes in biota due to sulfide phytotoxicity
including alteration of species physiology, species richness, community composition,
and biodiversity in wetland ecosystems.
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Water quality thresholds for non-acidifying S effects
¦ Increase in MeHg concentrations in surface water of Everglades
1 mg sulfate/L |ncrease jn mosquitofish, sunfish, and largemouth bass Hg load in Everglades
I 7.5 mg sulfide/L Decrease in saw8rass
growth rate in Everglades
| 0.165 mg sulfide/L Decline in populations of wild rice in MN
0 2 4 6 8
mg/L
L = liter; Hg = mercury; MeHg = methylmercury; mg = milligram; S = sulfide.
Figure 12-12 Thresholds of sulfate or sulfide concentrations in water which
cause biological and chemical effects in ecosystems.
12.9.4 Internal Eutrophication
1 The 2008 ISA described the contribution of S deposition to internal eutrophication in
2 aquatic systems. In wetland and lake waters, sulfate is reduced to sulfide, which reacts
3 with Fe to form insoluble iron sulfide complexes. In many ecosystems, the iron in this
4 reaction is provided by Fe(P04)3, and each mole of S removed from the water column
5 releases three molar equivalents of P, thus contributing to downstream eutrophication.
6 More recently, internal eutrophication caused by sulfate addition was observed in
7 mesocosms of samples collected from Lake Moshui, China (Yu et al.. 2015).
12.9.5 Effects on Methane Production
8 Sulfate deposition can shift microbial community interactions, resulting in lower methane
9 emissions. The 2008 ISA documented the suppression of methane emissions in wetland
10 soils by sulfate addition in several studies and noted that 15 kg S/ha/yr (the lowest S load
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in experimental treatments) suppressed methane emissions to the same extent as higher S
loads (Gauci et al.. 2004). Recent research has confirmed the underlying microbial
mechanisms of this process. Sulfate deposition increases the abundance or metabolic
activity of SRPs. In many freshwater water bodies, including wetlands, low primary
productivity limits microbially available, labile C during the growing season when higher
temperatures favor microbial activity. Recent research documents competition among
microbial guilds for labile C, and when SRPs are favored, competing methanogens
decline, resulting in suppressed methane emissions (Bae et al.. 2015; He et al.. 2015;
Paulo et al.. 2015).
12.9.6 The Role of Microbes in Mercury Methylation
The 2008 ISA identified sulfur-reducing bacteria as responsible for Hg methylation, and
identified anoxic wetland and lake bottom sediments as their location within watersheds.
More recent research confirms that SRB in these locations methylate Hg, but also shows
that the ability to methylate Hg is more broadly distributed in the prokaryotic taxa and
across the environment.
Recent research suggests that the hgcAB gene pair confers the ability to methylate
inorganic Hg. HgcAB has been sequenced in lineages within bacteria and archaea, which
is why this document refers to mercury methylators as SRPs rather than the SRB
described in the previous ISA (Gilmour et al.. 2013). Experimental work has shown that
MeHg production rates vary among prokaryotic strains (Shao et al.. 2012). but confirmed
that sulfate addition causes Hg methylation in the Everglades (Goni-Urriza et al.. 2015).
as abundant syntrophs (heterotrophs dependent on the metabolic byproducts of other
microbes) were responsible for both Hg methylation and sulfate reduction (Bae et al..
2014).
Recent research shows that the microbial communities responsible for Hg methylation
are more widely distributed than the freshwater lake or wetland bottom sediments
described in the 2008 ISA (Figure 12-13). The Sphagnum (moss) mat of wetlands was the
most efficient retention site of deposited Hg in a forested watershed in the Adirondacks
(Selvendiran et al. 2008b). as well as an important location of mercury methylation
within peat wetlands in New York and Wisconsin (Yu et al.. 2010; C re swell et al.. 2008;
Selvendiran et al. 2008b). Experiments using samples from rivers or streams in Virginia,
Minnesota, or Germany showed that higher sulfate concentrations increased methylation
rates or [MeHg] (Frohne et al.. 2012; Yu et al.. 2012; Tsui et al.. 2008). with 0.06 ng/L
increase in MeHg per gram of sediment for every 1 mg/L increase in sulfate pore water
concentration in South River, Virginia (Yu et al.. 2012). New research shows that SRPs
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actively methylate Hg within periphyton, the aquatic biofilms attached to substrate or
macrophytes in oxic freshwater environments (Correia etal.. 2012; Achaetal.. 2011).
MeHg production has also been documented in estuarine and marine sediments of the
Chesapeake Bay (Hollweg et al.. 2009) and in the marine water columns sampled at
20-327-m depths in the Canadian Arctic Archipelago (Lchnherr et al.. 2011).
As a microbial process, Hg methylation is determined not just by sulfate and Hg
concentrations, but by other environmental and nutritional requirements of SRPs: pH,
temperature, and water quality parameters, and carbon supply. The 2008 ISA identified
pH and dissolved organic carbon (DOC) major controls on Hg production, with low pH
and moderately high DOC correlating with high fish MeHg in lakes. The 2008 ISA also
identified wetland area or density as an important determinant of MeHg bioaccumulation
and export in watersheds. Recent research presented in Section 12.3.4 evaluates
temperature, total Hg concentration, pH, organic matter in water and sediments, iron, and
nitrate for their influence on Hg methylation rates.
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10
SK lakes (ng/L)
MN peatlands
• (ng/L)
so
VA river
(ng/g sediment)
-10
o
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Surface water sulfate (mg/L)
C = carbon; cm = centimeter: DOM = dissolved organic matter; g = gram; L = liter; MeHg = methylmercury; mg = milligram;
mS = millisiemens; ng = nanogram; SK = Saskatchewan; S04 = sulfate.
Note: A study of prairie lakes and wetlands in Saskatchewan found that conductivity, aromatic DOM, and sulfate concentrations
correlate with water MeHg (ng MeHg/L) = -2.94 - 0.44 (conductivity, mS/cm) + 0.303 (mg SO4/L) - 0.268 (aromatic fraction of
DOM, L/mg C/cm). Simple linear regressions relate MeHg to water sulfate concentrations in Minnesota peatlands (water
ng MeHg/L = 0.58 + 0.037 mg SO4/L) and in South River, Virginia (riverbed ng MeHg/g sediment = -0.08 + 0.059 mg S04/L).
Figure 12-13 Linear relationships between sulfate and methylmercury
concentrations in published studies.
1 The 2008 ISA identified organic C as an important control on microbial sulfate reduction
2 and Hg methylation, and recent research has quantified this relationship. In Little Rock
3 Lake, Wisconsin, DOC concentrations had to be at least 3.6 mg C/L to allow microbial
4 sulfate reduction, and microbial sulfate reduction increased linearly with C increase only
5 when DOC was in the range of 3.6-7.6 mg C/L (Watras et al.. 2006). Across prairie
6 potholes in Saskatchewan, surface water [MeHg] increased 2.65 ng/L for every 10%
7 increase in percent organic matter in underlying sediment (Hoggarth et al.. 2015). In
8 wetlands, rivers, and lakes of the Mississippi River delta, Louisiana, there was a
9 1 ng MeHg/L increase in surface water for each additional 0.048 mg hydrophobic organic
10 acid fraction (aromatic carbon typical of peat) of DOC/L (Hall et al.. 2008).
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12.9.7
Impacts of Sulfur upon Mercury Cycling
Based on experimental evidence, the 2008 ISA identified maximum MeHg production
occurring at sulfate concentrations of 200-400 (j,eq sulfate/L, and noted that waters under
S deposition in the U.S. have sulfate concentrations in the range of 60-200 (j,eq sulfate/L.
There was a positive relationship between sulfate reduction and concentrations of MeHg
in the hypolimnion of Little Rock Lake, Wisconsin, with a 10.8 ng MeHg/L increase for
each mg S/L reduced (Watras et al. 2006). There was also a positive relationship at this
site between total lake MeHg and annual SOx deposition, with a 14.4 mg MeHg/lake
increase for every 1 kg S/ha/yr increase in SOx deposition (Watras and Morrison. 2008).
There are multiple lines of evidence of a positive relationship between sulfate surface
water concentrations and MeHg concentration or production in multiple freshwater
systems. Both experimental manipulations and observational studies show that higher
sulfate concentrations in peat wetlands increase MeHg concentrations (Figure 12-14).
Experimental addition of sulfate to Bog Lake Fen in Minnesota showed that 8.3 kg S/ha
increased pore water [MeHg] (Mitchell et al.. 2008a). and 32 kg S/ha/yr increased pore
water [MeHg] as well as MeHg fraction of total Hg, or %MeHg (Jeremiason et al.. 2006).
In other bogs sampled in the same region of Minnesota and Ontario, [MeHg] in water
increased 0.037 ng/L for each 1 mg sulfate/L increase (Mitchell et al.. 2009). These
results were confirmed in a peatland S addition experiment in Sweden, which found that
20 kg S/ha/yr addition to the peat increased [MeHg] (Akerblom et al.. 2013; Bergman et
al.. 2012).
Recent work also established positive relationships between sulfate and MeHg in
ecosystems other than peat wetlands. In prairie potholes in the West (Hoggarth et al..
2015). with surface water MeHg increasing 0.3 ng/L for each additional mg sulfate/L
where conductivity and aromatic DOC remain constant (Hall et al.. 2009a). In a
freshwater marsh in the Everglades, water [MeHg] concentrations increased when sulfate
concentrations exceeded 1 mg sulfate/L (Corrales et al. 2011). which is also an important
threshold value for fish in the Everglades (see below). There are also recent
ecosystem-scale studies that show that sulfate reduction and MeHg can be correlated at
the landscape level. At the watershed level in the Adirondacks, [MeHg] in stream
outflows was negatively correlated with sulfate concentration (Selvendiran et al.. 2009).
with a 0.11 ng/L increase in stream [MeHg] for each mg sulfate/L removed from surface
water (Selvendiran et al.. 2008a).
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Deposition thresholds for non-acidifying S effects
Increase in porewater %MeHg in MN bog
Increase in mosquito Hg load in MN bog
20 Increase in porewater [Hg] in MN bog
11.7 Increase in largemouth bass Hg load in TX reservoirs
8.3 Increase in porewater [MeHg] in MN bog
0
5
10
15 20 25 30
35
kg S/ha/yr
ha = hectare; Hg = mercury; kg = kilogram; MeHg = methylmercury; S = sulfur; yr = year.
Figure 12-14 Thresholds of sulfate addition or deposition from published
studies which affect chemical or biological changes in
ecosystems.
12.9.8 Sensitive Ecosystems
The 2008 ISA identified ecosystems in the Northeast as particularly sensitive to Hg
methylation in response to S deposition, as many watersheds there have abundant
wetlands and freshwater water bodies with high DOC and low pH. Recent analyses
confirm that ecosystems east of the Mississippi tend to have higher Hg concentrations in
fish (Wcntz etal.,2014; U.S. EPA. 2011c).
Recent research in the Yolo Bypass Wildlife Area, California, indicates that Hg
methylation occurs in both permanent and agricultural wetlands, and was higher in the
agricultural wetlands where rice is grown (Alpers et al.. 2014; Marvin-PiPasqualc ct al..
2014). Hg methylation in this system was associated with Mn reduction, and then to a
lesser extent with Fe reduction, and was only marginally associated with S reduction;
sulfate addition did not affect Hg methylation (Alpers et al.. 2014; Marvin-Pi Pasqualc ct
al.. 2014). However, MeHg produced in the sediments where rice grew was highly
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correlated with MeHg concentrations in rice seeds (Windham-Mvers et al.. 2014a').
suggesting a route to human exposure, and there were higher MeHg burdens in several
animal species collected from agricultural wetlands than from permanent marshes (see
below).
12.9.9 Mercury Effects on Animal Species
Mercury is a developmental, neurological, endocrine, and reproductive toxin across
animal species. It is transformed by SRPs from inorganic Hg into methylmercury
(MeHg), which forms strong complexes with thiosulfate groups of organic molecules.
This bound MeHg accumulates in biota in successively higher concentrations at
ascending trophic levels. The 2008 ISA documented Hg accumulation in four turtle
species, songbirds, insectivorous passerines, and the common loon (Gavia immer). A
recent report by the USGS notes that Hg accumulation has also been documented in
insectivorous songbirds and bats (Wentz et al.. 2014). In recent research conducted in the
Yolo Bypass, California, higher water [MeHg] in agricultural rice-producing wetlands
than in permanent marshes led to higher MeHg concentrations in mosquitofish
(Gambusia affinis) and Mississippi silversides (Menidia audens) from the agricultural
wetland than from the permanent marshes (Ackerman and Eagles-Smith. 2010).
The 2008 ISA reported that 23 states issued fish advisories by 2007 in response to the
U.S. EPA's fish tissue criterion set to protect human health of 0.3 |ig MeHg/g fish, or
0.3 ppm. The 2008 ISA reported on the negative impacts of Hg on development,
morphology, survival, or reproduction in the following fish species: walleye (Stizostedion
vitreum), grayling (Thymallus thymallus), mummichog (Fundulus heteroclitus), rainbow
trout (Oncorhynchus mykiss), fathead minnows (Pimephales promelas), and zebrafish
(Danio rerio). However, a recent report on Hg in streams of the U.S. by the USGS
summarizes current research that birds, fish, and fish-eating wildlife experience negative
effects of Hg at lower concentrations than the 0.3 ppm criteria (Wentz et al.. 2014).
The 2008 ISA reviewed two studies that considered the link between S deposition and Hg
levels in fish (Drevnick et al.. 2007; Hrabik and Watras. 2002); both studies showed that
decreases in S deposition resulted in decreases in fish MeHg levels. Recent research
supports this finding in Voyageurs National Park (a Class I area) in Ryan Lake between
1998-2012 (Brigham et al.. 2014). when decreasing S deposition correlated with
decreasing fish Hg. In addition, a survey of fish caught in Texas reservoirs found that fish
in the highest deposition region (11.7 kg S/ha/yr) had significantly higher mean Hg levels
than fish from other regions (Premier et al.. 2011). Experimental S addition to the
Marcell peat bog in Minnesota demonstrated that 32 kg S/ha/yr increased the Hg
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1 concentrations in larval Culex spp. (mosquitoes), which are an important food source for
2 both aquatic and terrestrial species (Wasik et al.. 2012).
3 In addition to the studies that consider S deposition, there are recent studies that consider
4 sulfate concentrations in water in relation to fish Hg concentrations. A study of fish from
5 six lakes in South Dakota found a positive correlation between sulfate water
6 concentrations and walleye Hg concentrations (Stone etal.. 2011). The marshes of the
7 Everglades receive high S loading as agricultural runoff, and recent analysis of Hg loads
8 in mosquitofish, sunfish (Lepomis spp.), and largemouth bass (Micropterus salmoides)
9 collected 1998-2009 showed that Hg levels in fish were highest when sulfate
10 concentrations were between 1 and 12 mg sulfate/L; the researchers proposed 1 mg
11 sulfate/L as a water standard (Gabriel et al.. 2014).
12.9.10 Summary Table
Table 12-11 Summary of quantitative effects of non-acidifying sulfur.
Section of
Nonacidifying Sulfur
Effects Chapter
Threshold, Critical Level, or Quantitative Relationship
Reference
12.2.3
<7.5 mg/L sulfide to preserve growth rate of Cladium
jamaicense, sawgrass, in Everglades
Li et al. (2009)
12.2.3
0.165 mg sulfide/L to protect Zizania palustris, wild rice
MPCA (2015a. 2015b)
12.9.2
Sulfate reduction rates increase 0.35 mg (sulfate
reduced)/L/day with a 1 mg/L increase in sulfate addition
Kerrvetal. (1991)
12.3.4.4
<3.6 mg C/L as dissolved organic carbon, microbial sulfate
reduction did not occur
3.6-7.6 mg C/L of DOC, microbial sulfate reduction increases
linearly with C increase
>7.6 mg C/L, microbial sulfate reduction rate does not change
Watras et al. (2006)
12.3.4.4
2.65 ng/L increase in MeHg for every 10% increase in percent
organic matter
Hoaaarth et al. (2015)
12.3.4.4
1 ng MeHg/L increase for each increase of 0.048 mg
hydrophobic organic acid fraction of DOC/L
Hall et al. (2008)
12.4.1
<8.3 kg S/ha addition for pore water MeHg in peatlands
Mitchell etal. (2008a)
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Table 12-11 (Continued): Summary of quantitative effects of non-acidifying sulfur.
Section of
Nonacidifying Sulfur
Effects Chapter
Threshold, Critical Level, or Quantitative Relationship
Reference
12.4.1
<32 kg S/ha/yrto control pore water MeHg concentrations and
fraction of total Hg in peatlands
Jeremiason et al. (2006)
12.4.1
<20 kg S/ha/yr to control pore water total Hg concentrations and
MeHg concentrations in peatlands
Beraman et al. (2012)
12.4.1
10.8 ng MeHg/L increase for each 1 mg/L increase in H2S in
lake water.
Watras et al. (2006)
12.4.1.1
14.4 mg total lake MeHg increase for every 1 kg/ha increase in
SOx deposition
Watras and Morrison
(2008)
12.5
11.7 kg S deposition/ha/yr increases Hg levels in largemouth
bass in Texas
Drenneretal. (2011)
12.6.1
When conductivity and aromatic DOC remain constant, surface
water MeHg increases 0.3 ng/L for each mg/L increase in
sulfate concentrations
Hall et al. (2009a)
12.6.2
MeHg concentrations increased 0.037 ng/L for each 1 mg/L
increase in sulfate in pore water in peatlands
Mitchell et al. (2009)
12.6.2
1 mg/L sulfate in surface water to keep MeHg concentrations
low in Everglades surface water
Corrales et al. (2011)
12.6.3
0.06 ng increase in MeHg per gram of sediment for every
1 mg/L increase in sulfate pore water concentration in South
River, Virginia
Yu et al. (2012)
12.6.5
50 ng total Hg/L, the U.S. EPA water quality criterion
Alpers et al. (2014)
12.7
<32 kg S/ha/yr, for Hg load in larval Culex spp. (mosquitoes) in
peatlands
Wasiketal. (2012)
12.7
1 mg/L sulfate in surface water to keep Hg concentrations low in
fish: Gambusia spp., Lepomis spp., and Micropterus salmoides,
in the Everglades
Gabriel et al. (2014)
C = carbon; DOC = dissolved organic carbon; H2S = hydrogen sulfide; ha = hectare; Hg = mercury; kg = kilogram; L = liter;
MeHg = methylmercury; mg = milligram; ng = nanogram; S = sulfur; yr = year.
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CHAPTER 13 CLIMATE MODIFICATION
The scope of this chapter is to identify key papers describing how climate alters
ecosystem response to nitrogen (N) and sulfur (S) addition. Nitrogen and S loading
occurs in many ecosystems concurrently experiencing multiple stressors, including
human-driven climate change. Anthropogenic emissions of greenhouse gases are likely to
cause a global-average temperature increase of 1.5 to 4.0°C and a significant shift in the
amount and distribution of precipitation by the end of the 21st century (Collins et al..
2014). Recent work has focused on the effects of anthropogenic N on the Earth's
radiative forcing (Pinder et al.. 2012) and how temperature and precipitation alter
ecological responses to N exposure (Greaver et al.. 2016). Most work is conducted on the
effects of climate and N or acidifying deposition (N + S), relatively little work is
conducted on how climate modifies ecosystem response to S.
For the first draft ISA we have excerpted text from Greaver et al. (2016). a current review
of how climate (e.g., temperature and precipitation) modifies ecosystem response to N
that focuses on empirical observations. Climate effects on ecosystems is a rapidly
expanding field, however, for many biogeochemical pool and processes, data is
insufficient to quantify either the direction or magnitude of how climate may alter
ecosystem response to N with certainty. There are some global-scale earth systems
models now incorporating interactions between N and carbon (C) in ecosystems that are
summarized in Chapter 6. Greaver et al. (2016) includes information on terrestrial and
surface water ecosystems; however, it does not include information on estuaries. A brief
summary of climate modification of estuary response to N is also included in
Section 13.2.
13.1 Excerpt from Greaver et al. (2016)
13.1.1 Nitrogen Cycling: Transport and Transformation
Although global N cycling is complex, the movement of N through the biosphere can
largely be explained by describing a few key transformations (Figure 13-1). Atmospheric
N2 is converted into reactive N by lightning or by specialized bacteria capable of
biological N fixation, in addition to the human activities that create reactive N.
Organisms use reactive N to produce proteins and other essential compounds. Dead
organic matter is decomposed by microbial enzymes, producing smaller N containing
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1 organic molecules such as amino acids. This organic N is largely converted to mineral
2 forms that are readily assimilated by plants and microorganisms. Where reactive N is
3 present under aerobic conditions, some microorganisms convert ammonium (NHU) to
4 nitrate (Nth ). a process termed nitrification. Nitrate is mobile in soils and often leaches
5 into aquatic systems and groundwater. In anaerobic conditions, microorganisms can
6 convert NO; to gaseous N via denitrification, emitting N back to the atmosphere.
Spatial and temporal alteration of snow melt, precipitation and evapotranspiration
I
Spatial and temporal alteration of landscape-level wetness and hydrologic flow
I
Key mechanisms of nitrogen cycling altered due to changes in hydrology
Drier conditions
(-) Nitrogen flushing is likely to
increase N accumulation in
ecosystems, with large N pulses
exported during rainfall events.
(-} Dentrification will generally
decrease with drying, leading to
accumulation of N within the
ecosystem.
(-) Mineralization will generally
decrease under dry conditions.
(-) Nitrogen uptake by vegetation
caused by drought-stress in
vegetation as water becomes the
most limiting factor for growth.
(+) Drought-related plant infestation
and disease will generally decrease
under dry conditions.
(+) Fire will release ecosystem N into
the air and increase N available as
throughflow.
N = nitrogen.
Source Greaver et al. (2016)
Figure 13-1 Summary of key interactions among nitrogen,
anthropogenic-driven climate change, and hydrology.
Wetter conditions
(+) Nitrogen flushing increases export
from 'upstream' ecosystem and
loading to the 'downstream'
ecosystem.
(+) Denitrification will generally occur
in wetter areas, increased
denitrification will cause more N in
the ecosystem to be lost via the
gas-phase.
(+) Mineralization will generally
increase under wet conditions.
(+) Moisture-related plant infestation
and disease will generally increase
under wet conditions.
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In nonagricultural terrestrial ecosystems, atmospheric deposition is the dominant source
of anthropogenic N. Through changes in precipitation, shifts in atmospheric circulation,
and temperature-related effects on the stability of N compounds, climate change is
expected to alter the relative contribution of wet and dry forms of N deposition and shift
the spatial distribution of N deposition (Engardt and Langner. 2013; Tagaris et al.. 2008).
Local N deposition rates are generally predicted to change by 0-20% (Engardt and
Langner. 2013; Tagaris et al.. 2008).
The influence of N addition on reactive N availability within terrestrial and aquatic
ecosystems is mediated by microbial transformations and transport within and between
ecosystems. Climate change is expected to strongly affect these processes through
increasing temperature and through temporal and spatial shifts in temperature and
precipitation (Baron et al.. 2012). Warming directly increases the metabolic biokinetics of
enzyme activity necessary for microbial N transformation until a temperature optima is
reached. Climate change is also expected to cause numerous modifications of the
hydrologic cycle, and moisture availability regulates the biokinetic temperature response
(Borken and Matzner. 2009; Rustad et al.. 2001) because water is needed to transport
enzymes and substrates and water influences oxygen availability. Warming is predicted
to intensify the hydrologic cycle, with heavy rainfall events expected to become more
frequent and intense, along with the potential for deepening and lengthening of dry
periods, as well as altered snow accumulation and melt and changes in evapotranspiration
(Collins et al.. 2014; Jimenez Cisneros et al.. 2014). These changes may cause soil
conditions for microbial activity to shift between optimal and inhibitory (Morse et al..
2015b). modifying the link between climate warming and the rate of microbial N
transformations such as decomposition, mineralization, nitrification, denitrification, and
biological N fixation. Of these transformations, the rates of N fixation may be the most
uncertain part of the N cycle (Vitousek et al.. 2013). altering N supply and influencing
the C cycle (Welter et al.. 2015).
Climate-driven changes to the hydrologic cycle will also alter the quantity of N
transported through a system via waterborne transport and soil water content-mediated N
cycling (Billen et al.. 2013). Alteration of N retention in the soil due to changes in
moisture and flushing may be significant enough to determine whether an ecosystem is
an N source versus N sink (Boulton. 2007; Band et al.. 2001). Greater precipitation
generally increases water flow, which may (1) increase leaching/export of N through
terrestrial landscapes, (2) increase terrestrial N inputs to streams and rivers, and
(3) increase N transport rates through streams and rivers (Whitehead et al.. 2009).
although adaptation by microbes and plants may increase their ability to retain N as
flushing increases, thereby potentially limiting some of the overall impact of increased
precipitation and flow.
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Under dry conditions, landscapes can become more hydrologically disconnected and N
retentive, which can increase N concentrations in subsequent flushing events (Goodridge
and Melack. 2012; kaushal et al.. 2008). Drought can inhibit nitrification and cause N to
accumulate in the soil; once precipitation occurs it often results in a pulse of nitrification
that produces nitrate and subsequent nitrate leaching (Lamersdorf et al.. 1998). For
example, the 2012 droughts in the midwestern U.S. were followed during the spring 2013
by extremely high river nitrate concentrations (Beeman. 2013). Likewise, longer periods
between wet cycles lead to accumulation of nitrate and other acidifying solutes in the
soil, causing less frequent, yet more extreme acidification events (Bavlev et al.. 1992).
Beyond simply the total volume, precipitation intensity influences the rate of N flow
through ecosystems. Increased precipitation intensity of cold season frontal storm
systems and warm season convective storms would likely increase the frequency of
high-N-loading events to aquatic systems. Due to the limited capacity for instream
removal of N during high flow pulse events, most N is transported downstream (Kaushal
et al.. 2014).
Such hydrologic cycle changes are also expected to affect the timing of N transport.
Changes in the seasonality of precipitation, and in particular snowmelt, will tend to alter
the timing of N flushing through the ecosystem. There has already been widespread
earlier snowmelt and increased winter thaws associated with warming over the last few
decades (Collins et al.. 2014). but implications for the timing of N export have been
assessed in only a few sites (Casson et al.. 2012). Timing changes ultimately can alter the
magnitude of N export to downstream water bodies, particularly if the timing of flushing
changes relative to the timing of biologically mediated uptake in either terrestrial or
aquatic ecosystems (Baron et al.. 2009). Thus, it is possible to have a modification in
sink/source behavior in regions where annual or seasonal patterns of water-filled pore
space shift with climate change.
The rate at which denitrification returns reactive N to the atmosphere varies across space
and time, with landscape- to micro-scale denitrification hot spots or moments that depend
on interactions with hydrologic flow paths, the persistence and variability of low oxygen
conditions, and the residence time of water and N, all of which are likely to respond to
climate-driven changes in the hydrologic cycle (Anderson et al. 2015; Weier et al..
1993). Generally, warmer and wetter conditions under climate change would facilitate
greater rates of denitrification, whereas warmer and drier areas might experience
decreased denitrification or concentrate "hot spots" into smaller areas with higher soil
moisture, substrate concentrations, and fluxes (Duncan et al.. 2013). Alternating wet and
dry states may promote coupled nitrification/denitrification processes or build-up and
flushing of mobile N depending on the ratio of transport to reaction rates. These are
general trends associated with moisture availability and transport. Carbon substrate
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availability and other controls on microbial processes, however, will also be influenced
by climate change (discussed below) and can mediate these hydrologic effects.
13.1.2 Carbon Cycling, Acidification, and Biodiversity
The climate-driven changes in N cycling discussed above may alter the N supply in terms
of quantity and timing of N available for uptake by biota and whether the source is
directly from deposition or indirectly from leachate into a water body. Alteration of N
availability relative to a given organism's life cycle or physiological thresholds may alter
overall ecosystem function. These effects may be further modified when temperature and
precipitation cause direct stress to biota. In the following sections we describe how
temperature and precipitation interact with two important mechanisms affected by N
availability to taxa: (1) nitrogen-driven eutrophication, which will stimulate the growth of
opportunistic plant and animal species, and (2) acidification, which may decrease growth
and cause mortality among sensitive species. We describe how these changes in growth
will alter C cycling and biodiversity.
13.1.2.1 Nitrogen, Climate, and Carbon Cycling
Changes in N supply alter plant growth and C cycling. The addition of N to terrestrial and
aquatic ecosystems can cause eutrophication, a state of high nutrient availability that
alters ecosystem function. Autotrophs (plant/algae) capture CO2 through photosynthesis,
storing C in biomass until it is oxidized through respiration or combustion and released
back to the atmosphere. In terrestrial systems, N addition usually stimulates autotrophic
growth until biotic N demand has been satisfied, although high rates of N addition may
increase the concentration of acid anions, which often decreases plant growth (see
acidification discussion below). At certain sites, N additions have uneven effects,
stimulating growth of some tree species, while impairing the health and growth of others
(Thomas et al.. 2010V When considering the net effects on multiple tree species, growth
in most forests is stimulated. This additional growth increases the overall amount of C
stored in plant biomass; one unit of N input may cause an additional 24.5 to 177 units of
forest C uptake (de Vries et al.. 2014a; Liu and Greaver. 2009).
A number of published meta-analyses evaluate the response of C pools and fluxes to
single stressors ofN, precipitation, or temperature. To gain insight on stressor
interactions from single stressor response studies, we have synthesized existing
meta-analyses of terrestrial ecosystem response to additions ofN, precipitation, and
temperature (Figure 13-2). A recent correlation analysis of growth (in terms of net
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primary production [NPP]) for 1,247 woody plant communities across global climate
gradients confirms that NPP increases with higher temperature and precipitation (Chu et
al.. 2016). However, ecological changes along broad natural gradients may differ from
the response of ecosystems to comparatively rapid environmental change caused by
human activities (Chu et al.. 2016). This latter process may be more accurately
characterized by addition experiments, such as those summarized by meta-analysis. Our
synthesis of existing meta-analyses indicates that aboveground NPP is highly responsive
to N addition and enhanced precipitation, while temperature rise does not increase
aboveground NPP. This result is consistent with the basic biokinetic effects of warming
on enzyme activity, which would have the counteracting effects of stimulating both plant
C capture (photosynthesis) and plant C release (autotrophic respiration). Although there
are no meta-analyses on warming and whole-ecosystem autotrophic respiration, Lu et al.
(2013) observed in a meta-analysis that temperature increased gross ecosystem
production, a metric that does not subtract respiration from gross production
(photosynthesis). Therefore, temperature may have larger effects on plant C fluxes than
on NPP. Note that precipitation-induced changes in NPP may vary depending on whether
there is sufficient enhancement of precipitation to offset increased evapotranspiration in a
warmer climate (Bachelet et al. 2001).
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Carbon pools
Carbon fluxes
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30
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Ecosystem C
31 ? ?
N T P
GEP
? 34 48
rnT1
N TP
60-
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NS NS
NEE R(
31 34 48 ? 34 48
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N T P
Above-ground biomass
37 34 48
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N T P
Foliage biomass
34 ? ?
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Root biomass
37 34 48
N T P
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a
Fine root biomass
? 99 ?
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Above-ground NPP Below-ground NPP Below-ground Raj*,,,^
97 48 48 ? 48 48 ? 34 100
60
N T P
Hwsn
N T P
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IL
N T P
N T P
Organic layer
36 34 ?
36 34 ?
Dissolved organic C Microbial C Myrcorrhiza
36 34 ? 36 34 ? 38 ? ?
60
Decomposition
98 34 ?
~r i
60"
30-
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EX
60-
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MS.
36 34 100
36 34 ion
C = carbon; CI = confidence interval; GEP = gross ecosystem photosynthesis; N = nitrogen; NEE = net ecosystem C exchange;
NPP = net primary production; ns = nonsignificant effects; P = precipitation; RaUtotrophs = plant/autotroph respiration;
Recosystem = ecosystem respiration; Rheterotrophs = heterotroph respiration; Rsoj| = soil respiration; T = temperature; ?= an effect that has
not been assessed by meta-analytic review.
Note: Bars indicate response ratios (treatment/control x 100) and error bars represent 95% confidence intervals for the response.
Orange bars indicate the magnitude of response to nitrogen enrichment, blue bars show response to temperature increase, white
bars show response to precipitation increase. Blue zone indicates ecosystem carbon inputs and outputs, green zone indicates plant
responses, and brown zone indicates soil and microbial responses. The upper confidence interval for the precipitation effect on net
ecosystem C exchange is 124.6 and beyond the scale of the chart. The response of above ground net primary production to
warming was stated to be nonsignificant (Wu et a!., 2011), but no effect size was given.
Source: Greaver et al. (2016) The number above each bar indicates the published source of the effect size as follows: 1. LeBauer
and Treseder (2008): 2. Wu et al. (2011): 3. Lu et al. (2013): 4. Liu and Greaver (2009): 5. Liu and Greaver (2010): 6. Xia and Wan
(2008): 7. Knorr et al. (2005 : 8. Dieleman et al. (2012 : 9. Treseder (2004): 10. Lu et al. (2011b): 11. Liu et al. (2016).
Figure 13-2 The effects of increased nitrogen, temperature, and precipitation
upon terrestrial carbon pools (left panel) and fluxes (right panel)
from published meta-analyses.
1 Belowground, initial findings are that N addition tends to increase the C stored in the soil
2 organic layer and in root biomass (Liu and Greaver. 2010; Xia and Wan. 2008). while it
3 tends to decrease mycorrhizae/microbial abundance and heterotrophic respiration (Liu
4 and Greaver. 20.10; Treseder. 2004). This offset may result in no net change in soil
5 respiration (Liu and Greaver. 2010); however, this is an active area of research.
6 Consistent with the biokinetic effects of warming, long-term data and meta-analyses
7 show that soil respiration, including decomposition and microbial respiration, is
8 stimulated by increasing temperature (Lu et al.. 2013; Bond-Lambertv and Thomson.
9 2010; Rustad et al.. 2001). Most empirical studies show rising temperature stimulates N
10 release by mineralization (Churkina et al.. 2010). which may be driven more by
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temperature effects on moisture (Einmett et al.. 2004). In some dynamic land models, the
additional N from mineralization will stimulate C uptake by plants even more than
current N deposition (Burd et al.. 2016). At the same time, increased N from
mineralization may cause N induced inhibition of decomposition, a feedback mechanism
that might decrease the amount of N released that is currently considered by few models
(Gerber et al.. 2010). The mechanisms causing N driven reduction in decomposition are
not well understood, but are thought to result from changes in microbial community
composition and their production of decomposition enzymes, as well as possible changes
in the character and degradability of soil organic matter (Conant et al.. 2011; Janssens et
al.. 2010). Climate change could also affect decomposition rates by altering both
available soil moisture and microscale connectivity among microorganisms, water, and
nutrients within the soil matrix that in turn may alter microbial processes (Xiang et al..
2008). Although there is no consensus about how dissolved organic carbon (DOC) in
surface water is regulated overall, increasing N and temperature increase DOC
concentrations (Laudon et al.. 2012). While few meta-analyses examine precipitation
effects on the soil C cycle, precipitation tends to increase the root C pool (Figure 13-2).
Overall ecosystem C balance is assessed by summing measurements of individual pools
to quantify ecosystem carbon (EC) content or by measuring C fluxes to quantify the net
ecosystem exchange (NEE) of C. The meta-analysis we identified indicated that
temperature did not increase NEE lYLu et al.. 2013) positive NEE indicates ecosystem C
gain], and as previously mentioned this is likely because the biokinetic effects of
warming stimulate respiration that offsets the C capture via stimulation of primary
production. Increased precipitation tends to increase NEE (Wuetal.. 2011). likely
because water availability increases photosynthesis, while not increasing plant respiratory
losses. A meta-analysis of N addition studies indicates that adding N to grasslands had no
effect on NEE, but that N addition increased forests EC (Liu and Greaver. 2009). There
may be differences between grasslands and forests in terms of the extent that C gain
simulated by N is offset by heterotrophic and autotrophic respiration. Increasing
temperature may decrease C storage if the warming causes inhibition of photosystems, or
enhances evaporation and reduces water availability. A better understanding of these and
other contributing processes is needed.
Traditionally, primary production in freshwater systems was thought to be phosphorous
(P) limited, but recent data have shown an increase of limitation by N or colimitation by
N and P (Elser et al.. 2007). In N limited freshwaters, N addition enhances rapid growth
of nitrophilic algae. This is an important food source to consumer species in the trophic
cascade; however, it is unclear if this is an important source of long-term C storage.
Sediments are estimated to be the largest pool of long-term C storage (Cole et al.. 2007).
and N stimulates the production of terrestrial biomass that may be transported to aquatic
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sediments. Nitrogen also stimulates primary production of aquatic algae which contribute
to C in sediments (kastowski et al.. 2011). although few studies have examined this
effect. Gudasz et al. (2010) found a strong positive relationship between increasing
temperature and organic C mineralization. They conclude future organic C burial in
boreal lakes could decrease 4-27% under scenarios of warming due to enhanced
temperature-dependent microbial activities. We were unable to identify studies
examining precipitation effects, or the combined effects of N, temperature, and
precipitation effects, on C storage in freshwater ecosystems. A discussion of biodiversity
associated with eutrophication of freshwaters is included in the biodiversity section.
13.1.2.2 Nitrogen, Climate, and Acidification
Atmospheric deposition of acidic N and sulfur (S) compounds (e.g., HNO3, H2SO4) has
directly caused widespread acidification of terrestrial and freshwater ecosystems in many
industrial areas. More broadly, other forms of atmospheric N deposition (e.g., NHx) can
indirectly cause acidification by increasing inorganic N availability enough to induce
nitrification. Freshwater and terrestrial ecosystem acidification is well studied and is
characterized by decreased pH and elevated aluminum (Al) concentrations/mobility in
soils and surface waters that cause plant physiological changes (Schaberg et al.. 2002).
tree mortality (McNultv et al.. 2007). aquatic fauna mortality, and decreased aquatic
biodiversity (Driscoll et al.. 2001b). Acidification driven by N (as opposed to N + S)
occurs at higher levels of N addition than for initial changes to the C cycle. Often N
saturation of the terrestrial ecosystem and subsequent leaching into adjacent aquatic
systems is observed in the process of aquatic acidification (Aber et al.. 1998). The
threshold for the onset of acidification changes across the landscape, depending on
geochemical sensitivity and historical loading of acidifying deposition. Although recent
declines in emissions of SOx and NOx in eastern North America and throughout Europe
(NAPAP. 2011) have led to many improvements in acid-base balances in acid sensitive
ecosystems in recent decades, it is unclear whether sensitive ecosystems will continue to
improve as emissions decline or whether secondary processes will promote, arrest, or
reverse ecosystem recovery as climate changes.
Potential future changes in the quantity and temporal distribution of precipitation and
temperature (and their interactions) is expected to alter the wet-dry cycles that govern the
timing and amount of acidic inputs in precipitation, microbial transformation in the soil,
and the flush of acid anions from soils to surface waters. If acid anions build up in soil
during periods of drought, the eventual flushing likely causes a more potent acidification
event (Moslev. 2015; Whitehead et al.. 2009). If the acidification event occurs during a
time when sensitive biota or lifestages of biota are present, acidification may cause more
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adversity to these populations (kowalik et al.. 2007). Increases in storm frequency
associated with global climate change (Collins et al.. 2014) could increase the frequency
and severity of acidification driven by high levels of sea salt deposition in coastal regions
(Wright and Schindler. 1995). Although the mechanisms of interaction are unclear,
increases in DOC concentrations in aquatic ecosystems across Europe and the U.S. have
been linked to acidification, N cycling, and climate change, with important implications
for water quality and ecosystem function (Evans et al.. 2008).
As previously mentioned, warmer temperatures increase decomposition and nitrification.
Nitrification will also increase with increased N supply caused by increased weathering
or decomposition (Booth et al.. 2005). The process of nitrification generates protons that
increase the rate of nitrate and base cation leaching to drainage waters (Murdoch et al..
1998). The combined increase of NO3 leaching and loss of base cations has the potential
to magnify acidification in forest soils (Fernandez et al.. 2003). Soil weathering is
typically the key buffer to acidic deposition (Li and McNultv. 2007). and while
weathering is increased by both soil temperature and soil moisture (Gwiazda and
Broecker. 1994). it is unclear whether any future change in the magnitude of temperature
and precipitation will be enough to alter base cation supply or influence the acid-base
balance of sensitive ecosystems. Furthermore, it is unclear whether increased supply of N
in soils from either deposition, increased decomposition, or increased nitrogen fixation
may negate the ameliorative effect of enhanced weathering. Some studies show that
climate change will mitigate acidification through increased weathering (Belvazid et al..
2011a). while others show that climate change will aggravate acidification although
increased nitrification outpacing enhanced weathering (Wu and Driscoll. 2010). In
general, increased temperature and precipitation will likely enhance inputs of buffering
agents from weathering and deposition, but also increase inputs of acidifying agents from
deposition and enhanced N cycling. The relative sensitivity of these opposing processes
to a given change in climate remains unresolved.
Climate change may alter the sensitivity of biota to acidification, creating the need to
adapt to a combination of acidity and climate change stresses. For example, the suitable
habitat for brook trout in the Catskills and Adirondack mountains of the northeastern U.S.
may be constrained as climate change increases downstream water temperatures,
reducing downstream range where the trout can survive, while upstream migration is
limited in part by acid conditions in the headwaters. In another example, Al is toxic to
many fish and known to be mobilized during acidification events. It is known that the
mortality rate of Atlantic salmon exposed to Al increases at higher temperatures (ABS
and Muniz. 1993); it is unclear how many other aquatic species would experience
temperature-dependent toxicity, which could make them more vulnerable to acidification
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in a warming climate. Overall, there is little knowledge of how the biological thresholds
to acidity will be affected by climate change.
13.1.2.3 Nitrogen, Climate, and Biodiversity
Biodiversity, which contributes to the structure and function of ecosystems, is declining
globally (Rockstrom et al.. 2009). Decades of study show that added N reduces
autotrophic diversity in terrestrial and aquatic systems, fungal biodiversity in soils, and,
although less studied, animal diversity in terrestrial and aquatic systems (Howarth et al..
2011; Bobbink et al.. 2010). As previously mentioned, two mechanisms that contribute to
altered biodiversity are eutrophication and acidification. Eutrophication often causes N
stimulated growth for opportunistic species, which may cause competitive exclusion of
poorer competitors and soil acidification driving cation imbalances and physiological
stresses, suppressing seed germination and seedling regeneration (Sullivan et al.. 2013;
Roem et al.. 2002). In addition, N may alter physiology and/or community properties,
increasing the risk to secondary factors such as pests, fire, frost, and drought (Bobbink et
al.. 2010). Lastly, direct damage to vegetation from ammonia (NH3), nitrogen dioxide
(NO2), nitrogen monoxide (NO), peroxyacetyl nitrate (PAN), and nitric acid (HNO3)
exposure is known to occur, but most likely occurs in highly polluted areas and in close
proximity to high emission sources (Greaver et al.. 2012). In terrestrial ecosystems, all
processes generally reduce local autotroph diversity and homogenize habitats into
communities with small numbers of generally fast-growing or acid-tolerant autotrophic
species. These changes propagate through the food web, leading to increases of generalist
pests, herbivores, and parasitic soil bacteria, and decreases in specialist herbivores and
beneficial microbial communities that occur belowground (de Sassi et al.. 2012).
Biodiversity responses on land may be moderated by the type of climate change
occurring and the mechanism of N response. In terrestrial systems that get warmer and
wetter, eutrophication may be amplified if endogenous N sources are low or dampened if
endogenous sources are high/more liberated to meet community demand. The response of
the acidification pathway may depend on whether the change in net fluxes of cations
from climate change exceeds the net fluxes of N [i.e., from enhanced deposition of
cations and N, decomposition or weathering, and leaching (Howarth et al. 2011; Roem et
al.. 2002)1. Many of these processes may be dampened in terrestrial systems that are
anticipated to get warmer and drier (e.g., southwestern U.S.) due to the drier conditions
reducing biological activity (Bobbink et al.. 2010). Colder regions such as montane,
alpine, and tundra systems are often strongly N limited and poorly buffered; thus, an
extended growing season under climate change will lead to greater opportunities for all
operating processes. Climate change may also magnify the effects of secondary stressors
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in several ways, including increased pest populations under warmer wetter conditions, as
well as increasing fire potential and drought vulnerability as more aboveground plant
tissue is produced under elevated N (Pise et al.. 2011). Nonetheless, field evidence for
interactions between N and climate change under controlled conditions is scarce. The few
existing studies find additive effects in Mediterranean California (Zavaleta et al.. 2003).
and no interactive effects of precipitation and N addition in Minnesota (Reich et al..
2014; Reich. 2009). Not all terrestrial ecosystems are anticipated to be equally sensitive
to these pressures. In grasslands, many forbs and slow-growing species such as native C4
grasses appear especially vulnerable to added N (Clark and Tilman. 2008; Zavaleta et al..
2003). In a study of northeastern forests, all three tree species with negative growth
responses to N deposition were evergreen conifers (e.g., Pinus resinosa, Picea rubens,
Thuja occidentalis), while all five tree species with positive growth responses were
broadleaf species with arbuscular mycorrhizal associations [e.g., Acer rubrum, A.
saccharum, Fraxinus americana, Liriodendron tulipifera, and Prunus serotina (Thomas
et al.. 2010)1. However, contingent factors underly these general patterns, as there were
tree species from each group that did follow these generalities.
In aquatic systems, elevated temperatures and N inputs from increased rain and glacial
retreat will likely magnify changes in algal assemblages that can propagate through the
food web (Hobbs et al.. 2010; Elser et al.. 2009a). In freshwater aquatic biodiversity
research, there is a substantial amount of work on lakes investigating the effects of
warming via gradient studies (latitude or altitude), warming experiments, time-series, and
palaeoecology (Jeppesen et al.. 2014). Fish community assemblages, size, structure, and
dynamics are likely to change with continued global warming, and in some cases the
elevated temperatures that have already occurred in the past decades. Fish cannot
thermoregulate, but only physically move to areas with appropriate temperatures, if those
are accessible. In general, changes in fish composition, particularly in shallow lakes, are
characterized by a decline in abundance of several cold-stenothermal species (Kangur et
al.. 2013; Winfield et al.. 2010) and in increase in eurythermal species, which exhibit a
wide range of thermal tolerance (Jeppesen et al.. 2012). Many fish species are also
adapted to specific oxygen concentrations; when temperature increases, oxygen may drop
to critical levels as warm water holds less oxygen and the respiration rates increase.
Warming effects on the biodiversity of grazing macroinvertebrates and zooplankton is
mixed across studies (Qzen et al.. 2013; Bummer et al.. 2007). Warming is shown to
increase cyanobacteria biomass (kosten et al.. 2012) and biofilm biomass (Williamson et
al.. 2016). while warming effects on phytoplankton show mixed results (Meerhoff et al..
2012; Feuchtmavr et al.. 2009).
Warming may cause increases in evaporation that will lower water level and increase
salinity (Williams. 2001). Increasing salinity of freshwater systems tends to have a
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negative effect on phytoplankton, zooplankton, macroinvertebrates, and fish (Jeppesen et
al.. 2007). Climate change will alter the transport, availability, and timing of N in
ecosystems, and recent data indicates an increase of primary production limitation by N
or colimitation by N and P (Elser et al.. 2009a). In N limited freshwaters, N enrichment
enhances rapid growth of nitrophilic algae that outcompete other populations for light and
resources such as P and silicon (Si), leading to dominance by a few algal species and a
reduction in the nutritional quality of invertebrates as food for fish (Baron et al.. 2012;
Hobbs et al.. 2010; Elser et al.. 2009a'). The combination of increasing both N and
temperature may be synergistic and sometimes difficult to uncouple (Kangur et al..
2013). as both may stimulate hypoxic conditions, consequently altering community
structure (Ozen et al.. 2013; Feuchtmavr et al.. 2009) and the frequency, intensity, extent,
and duration of harmful algal blooms (Paerl etal.. 2011).
Presently, there are at least 78 listed or candidate species for threatened or endangered
status in North America that have N impacts identified as a primary contributor, and an
estimated 15-37% of species may be at risk from climate change (Hernandez et al.
2016). In total, there are numerous pathways whereby these dominant global change
factors can interact to impact biodiversity, and it is likely, although not definitive, that N
and climate often have additive and potentially amplifying effects on decreasing
biodiversity in many systems.
13.2 Estuaries
In addition to terrestrial and freshwater systems described above, climate change
modifies key processes in estuarine and near-coastal systems linked to nutrient inputs.
Atmospheric deposition may represent more than 40% of N in coastal water bodies
(Chapter 7). N sources to near-coastal ecosystems include direct deposition to the water
surface and all other N sources upstream. Coastal eutrophication is a process of
increasing nutrient over-enrichment indicated by water quality deterioration, resulting in
numerous adverse effects including hypoxic zones (water with dissolved oxygen that is
too low to support marine life), species mortality, proliferation of phytoplankton and
macroalgae (including harmful algal blooms), and decreased coverage of submerged
aquatic vegetation KBricker et al.. 2007); Chapter 101. These indicators of nutrient
enrichment may be affected by climate-related changes in estuaries including
temperature, precipitation, wind patterns, stronger estuary stratification, increased
metabolism and organic production, and sea-level rise (Altieri and Gedan. 2015; Statham.
2012; Rabalais et al. 2009). For example, eutrophic conditions and the extent and
duration of hypoxia are predicted to increase with changes in temperature and
precipitation (Altieri and Gedan. 2015; Rabalais et al.. 2009; Boesch et al.. 2007). Donev
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et al. (2012) reviewed effects of climate change, including coastal hypoxia, on marine
biodiversity and reported population-level shifts. In estuaries affected by nutrient
enrichment and climate-associated alterations described above, conditions favor a shift in
phytoplankton toward greater abundance and distribution of toxic cyanobacteria
associated with increased prevalence of harmful algal blooms (Paerl et al.. 2016). In a
meta-analysis of temperature effects on benthic macrofauna, survival times significantly
decreased in hypoxic conditions under warmer temperatures (Vaquer-Siinver and Duarte.
2011). Decreases in estuarine biodiversity associated with N loading can be magnified by
hydrologic factors. Glibcrt et al. (2014) observed a regional change in phytoplankton
community composition and decreased coverage of submerged aquatic vegetation
following a shift from long-term dry to long-term wet conditions in the early 2000s in
shallow coastal lagoons along the coast of Maryland and Virginia. Shifts in
phytoplankton community structure are known to occur in estuaries due to N enrichment,
but climate changes may at times outweigh the impacts of eutrophication (Paerl et al..
2010). Thus, physical changes caused by climate change should be considered when
modeling phytoplankton community response to N enrichment (Paerl et al.. 2014).
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CHAPTER 14 ECOSYSTEM SERVICES
This chapter is a review of the recent literature (published from 2008-present) written
within the context of what was known in the 2008 Integrated Science Assessment for
Oxides of Nitrogen and Sulfur-Ecological Criteria (hereafter referred to as the 2008 ISA)
about the links between emissions of these criteria pollutants and the provision of
ecosystem services.
14.1 Ecosystem Services Frameworks
In the 2008 ISA, several ecosystem services frameworks were documented. These
frameworks were used to identify, through qualitative and/or quantitative metrics, the
services that ecosystems provide to benefit human welfare and society (WRI. 2000;
Costanza et al.. 1997; Daily. 1997; Pimentel etal.. 1997). Although some goods and
services have explicit market value, the value of other services are more difficult to
assess (U.S. EPA. 2008a; Goulder and Kennedy. 1997). The most accepted framework
for ecosystem services identified by the 2008 ISA was the 2005 Millennium Ecosystem
Assessment (MEA) by Hassan et al. (2005).
Since the 2008 ISA, several new ecosystem services frameworks and classification
systems have been published. These include The Economics of Ecosystems and
Biodiversity [TEEB (Sukhdev et al. 2014)1. the Common International Classification of
Ecosystem Services [CICES (Haines-Young and Potschin. 2011)1. and U.S. EPA Final
Goods and Services Classification System [FEGS-CS (Landers and Nahlik. 2013)1. A
commonly accepted system may be necessary for ecosystem services to be incorporated
into everyday decision making and economic accounting systems.
Within each of the existing classification frameworks, the approach to classifying
biodiversity differs slightly, and there is still debate over exactly how it fits within an
ecosystem services framework. In the MEA framework specifically, biodiversity is not
considered to be a service, but rather the foundation for all ecosystem services. In
contrast, The Economics of Ecosystems and Biodiversity (TEEB), an initiative born from
a report of the same name published by the United Nations Environmental Program, was
created from an explicit desire to make a strong economic argument for biodiversity
(Sukhdev et al. 2014). The goal of the TEEB initiative is to demonstrate the economic
value of services provided by species and ecosystems and then capture the value of these
services through market- or policy-based approaches (Sukhdev et al.. 2014). The TEEB
initiative uses four primary categories of ecosystems services. Three categories are from
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the MEA (provisioning, regulating, and cultural services). However, TEEB replaces the
MEA's "supporting services" with "habitat services," which emphasizes the provisioning
of species and genetic diversity.
Developed in part as reaction to the increasingly diverse ways that ecosystem services
were being discussed, categorized, and assessed by different organizations around the
world, the CICES program has as a primary goal to create a more uniform approach to
assessing ecosystem services (Haines-Young and Potschin. 2011). This desire was
motivated by the increasing difficulty in making comparisons between assessments and
the challenges in sharing and transferring data between assessments and studies that had
taken different approaches. The classification approach CICES developed recognizes
only final outputs from ecosystems, in other words, "products" that are directly consumed
or used by people (Haines-Young and Potschin. 2011).Thus, the concept of "supporting
services" identified by the MEA was dropped under the assumption that these functions
would be recognized for their role in facilitating the final outputs. To provide flexibility
and transferability, CICES developed a hierarchical structure for assessing ecosystem
services, beginning with the three broad categories (provisioning, regulating, and
cultural), which were broken down into 23 "service groups" and then 59 "service types"
(Haines-Young and Potschin. 201IV
The FEGS-CS approach defines and classifies 338 Final Ecosystem Goods and Services
(FEGS), each defined and uniquely numbered by a combination of environmental class or
subclass and a beneficiary category or subcategory. This systematic approach is intended
to minimize double counting and relates each FEGS to a defined beneficiary, thus linking
it specifically to human well-being. This approach is expected to facilitate increased
communication about FEGS among a wide-ranging group of scientists, practitioners, and
communities of all types interested in quantifying ecosystem services (Landers and
Nahlik. 2013).
The National Ecosystem Services Classification System (NESCS) was developed by the
U.S. EPA to analyze the human welfare impacts of policy-induced changes to ecosystems
(U.S. EPA. 2015d). The goal of NESCS is to support analysis of changes from baseline
conditions, such as cost-benefit analysis, and support systematic accounting of changes in
ecosystem services. In economics literature, services are typically viewed as "flows"
from the provider to the consumer that are measured over time. The NESCS structure
defines categories and numeric codes that are designed to help identify flows of services
from ecosystems to human beings, while distinguishing between the producers
(i.e., "supply-side") and users (i.e., "demand-side") of the service.
When natural ecosystems are altered as a result of changes in nitrogen (N) or sulfur (S)
inputs, their ability to provide these services is often affected.
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In the 2008 ISA, the ecological effects were binned into the following categories [defined
by Hassan et al. (2005)1:
• Supporting (e.g., nutrient cycling, biodiversity)
• Provisioning (e.g., forest yields, fishing yields in estuaries)
• Regulating (e.g., water quality, air quality, climate regulation, fire frequency and
intensity, disease resistance)
• Cultural (e.g., swimming, boating, recreation, biodiversity)
Chestnut and Mills (2005) compare the actual benefits of reducing emissions of NOx and
SOx in Title IV of the Clean Air Act Amendments (CAAA) by the estimate of benefits
made in 1990. They conclude that quantitative assessment is problematic due to a lack of
units of measure to gauge changes in the quality and quantity of ecosystem services and a
lack of dose-response relationships to indicate how quality and quantity may change as a
function of changes in pollution exposures. They note a different approach is exemplified
by a study documenting that New York households are willing to pay an average of $45
to $100 annually to reduce the number of acidified lakes by 40% and improve forest
health in the Adirondacks (Banzhaf et al. 2004). The 40% reduction in acidified lakes is
an estimate of what would be achieved with an additional reduction in power plant
emissions by an amount similar to the Title IV reductions. The biggest challenges with
this approach are that the nature and implications of the ecosystem injury have to be
explained and understood by respondents and that values need to be determined for
incremental improvements.
Several other studies calculated monetary quantification of the value of emission
reductions. In 1990, the estimates of total annual value for improvements in recreational
fishing were $12 million to $24 million (NAPAP. 1991). These estimates were improved
with updated economics studies and new models for estimating the changes in fish stocks
and catch rates as a function of changes in emissions. U.S. EPA (1999) reported estimates
of annual value of improvements in conditions for recreational fishing in the Adirondacks
of about $65 million for the reductions in acid deposition as a result of the 1990 CAAA,
primarily Title IV.
14.1.1 U.S. Applications
Since the 2008 ISA, several comprehensive studies have been published on the
costs/benefits of ecosystems services related to N pollution that focused on U.S.
economic markets and ecosystems. These include an evaluation of multiple N inputs
(including N deposition) to the Chesapeake Bay (Birch et al.. 2011). Incorporating values
presented in Birch et al. (2011). Compton et al. (2011). and Compton et al. (2013)
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presented a synthesis of the cost/benefits on N loading across the nation for services that
included coastal fish harvests, recreational uses of inland and coastal waters, lakefront
property values, and water treatment and human health costs. Further expanding on this
work, Sobota et al. (2015) calculated the amount of N loading from human activity that is
leaked into adjacent ecosystems and thereby causes alteration of ecosystem services. This
work specifically identified the costs of the atmospheric portion of total N loading. Rea et
al. (2012) observed how atmospheric NOx and SOx causes damage to services in the
Adirondacks. (Baron et al.. 2012) evaluated the interactions between climate and N,
identifying some key services in which a changing climate will modify the response to N.
These studies are discussed in more detail below. Lastly, NAPAP (2011) concluded that
the greatest challenge in developing specific data on the economic benefits of emission
reductions lies with the availability of comprehensive scientific evidence that defines the
extent and magnitude of the adverse effects that can be directly attributed to acid
deposition from among multiple ecosystem stressors.
Understanding economic damages that occur from the release of N, has been the major
focus of attempts to restore the Chesapeake Bay. Birch et al. (2011) examined the spatial
and temporal movement of reactive N through multiple ecosystems and media in the
Chesapeake Bay watershed and estimated damage costs in several categories (Figure
14-1). The largest quantified damage impacts are associated with human health through
air exposures. Recreation and commercial fishing are the main specifically noted
ecosystem system service impacts; however, the quantification of these impacts is very
limited due to data limitations. The analysis finds that, although atmospheric releases of
N are lower than direct releases to land and water, their total damages are larger yet have
associated abatement costs that are relatively low.
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Chemical Nitrogen Cascade: Chesapeake Bay Watershed
Umlwkita
Uttttes
Irrticuy
U.OQH
Vlifeik Fk iii ucs
i Tft.nori
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14.HW
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Load Lies 62,000
I 52.030 | I IftOM I
terrestrial 1
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N \dditii>** to Water ! ., f -,
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ilcrn rmn In
Arrow uidifi irxikalcs s.i*c of flia.
Amy*- co Idc imiscair* origin or
mrtrugjen flux
* Red - Air
* Gtwii - Land
* ntue - Water
All estimates arc m metric tonne* N
per year
IjtLllBrilM1
Sy*tena
l m.kb I \ 1 I L'Jd;
PsJ'I. - No fcctimafie Available
FIGURE 1. Chemical Nitrogen Cascade in ike Chesapeake Eny Watershed |boai»ewyear). See SI tor soirees and calcaiaboH.
N = nitrogen; N.E. = no estimate available; N20 = nitrous oxide; NH3 = ammonia; N0X = nitrogen oxide.
Source: Birch et al. (2011).
Figure 14-1 Economic nitrogen cascade in the Chesapeake Bay Watershed.
The Compton et al. (2011) review and synthesis compared estimates of the average
damage costs per unit of N across a range of affected services. In general, the highest
damage costs are associated with respiratory health effects due to air emissions of NOv.
Per unit damages related to terrestrial and freshwater acidification and freshwater
eutrophication are generally much smaller or not quantified in monetarily, whereas those
associated with coastal eutrophication range between $6/kg and $56/kg.
Sobota et al. (2015) estimated the effects of N leaked to the environment (air/deposition,
surface freshwater, groundwater, and coastal zones) on services by multiplying
watershed-level N inputs (8-digit U.S. Geologic Survey Hydrologic Unit Codes;
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|HUC8s |) with published coefficients describing nutrient uptake efficiency, leaching
losses, and gaseous emissions. The general relationships between N addition to
ecosystems and beneficiaries is illustrated in Figure 14-2.
Beneficiaries
Stratospheric
Ozone (UV)
Particulate
matter
effects
Troposphenc
Ozone
A Humans
Greenhouse
Gas
Recreational
Transportational
N source
All Humans
Farmers
Natural
effects
Recreational
Non-use
Agroecosystem
effects
Coastal & Ocean
effects
Water
Surface water
effects
Commercial
Groundwater
effects
Residential
N20 = nitrous oxide; NH3 = ammonia; N03 = nitrate; NOx = nitrogen oxide.
Source: Sobota et al. (2015).
Figure 14-2 Summary of beneficiaries of ecosystem services related to
nitrogen addition.
Sobota et al. (2015) applied a per-unit damage cost values ($/N) for a wide variety of
health and ecological effects (based on estimates from various sources) to these leakage
estimates. Annual damage costs associated with anthropogenic N leakage range from
$1.94 to $2,255 per hectare per year. Nationally, the total quantifiable damages were
estimated to be between $81-$ 144 billion per year. Between 14-24% of the potential
damage costs were associated with fossil fuel combustion. Areas with the largest damage
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costs corresponded to areas with the largest N inputs and leakages, such as the upper
Midwest and central California.
Rea etal. (2012) described how economic valuation was used in the review process for
the secondary NOx-SOx NAAQS, highlighting the advantages and challenges of
quantifying ecosystem service impacts. The ecosystem services affected range from
recreational, subsistence, and commercial fishing to timber production and aesthetic and
nonuse values. Rea et al. (2012) used two different benefit transfer approaches to
estimate ecosystem service values for a scenario in which the impacts of acidic
deposition on lakes in New York's Adirondack Park were remediated. A benefit transfer
approach based on a stated preference study, which captures ecosystem service values as
a whole, estimated total values ranging from $547 million to $1 billion per year. In
contrast, an approach based on a revealed preference study, which only captures
recreation fishing values, estimated benefits ranging from $7 million to $9 million per
year.
Some work has discussed the implications of climate change and N loading on ecosystem
services such as fish harvests, property values, water treatment, human and wildlife
health, ocean acidification, and freshwater diversity (Baron et al.. 2012). The combined
effect of N loading and climate change on the economic value of water resources and
related products has yet to be evaluated, and even the separate economic effects of N
loading or climate change are difficult to determine. However, climate change will
modify the effects of N loading on some key ecological services. Porter etal. (2013) and
Compton et al. (2013) also identified some effects on the interactions between nitrogen
and climate, which include:
• As eutrophication increases with warmer water temperatures, there will be costs
associated with upgrades of municipal drinking water treatment facilities, the
purchase of bottled water, and the health costs of NO3 in drinking water leading
to toxicity and disease (Compton et al.. 2011).
• The U.S. will increasingly rely on groundwater for drinking water under future
climate change scenarios (U.S. Global Change Research Program. 2009). creating
a strong potential for increased costs for treating exposure to NO, -stimulated
disease.
• Increasingly, N enrichment is correlated in waters with pathogen abundance and
human and wildlife diseases (Johnson et al.. 2010). Climate warming opens the
possibility for more vector-transmitted diseases to migrate to higher latitudes,
where N loading may enhance their success (Johnson et al.. 2010).
• Acidification causes direct harm to calcifying shellfish and crustaceans (Howarth
et al.. 2012). Changes in climate and the N cycle will intensify ocean acidification,
and there are feedbacks from acidification to N cycling (Donev et al.. 2009).
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14.1.2
European and Canadian Applications
Since the 2008 ISA, several qualitative and quantitative assessments of either N
deposition or the combination ofN and S deposition have been conducted in the U.K.
(Jones et al.. 2014). across Europe (dc Vries et al.. 2014b; de Vries et al.. 2014c; Van
Grinsven et al. 2013). and Canada (Aheme and Posch. 2013). Although these
assessments have varied considerably in their approaches, all have used simplified
approaches that intentionally omitted much of the mechanistic and spatial complexity in
how deposition affects ecosystem services. Some of the qualitative and conceptual
assessments provided descriptions of impacts of N deposition on ecosystems (de Vries et
al.. 2014b; de Vries et al.. 2014c; Jones et al.. 2014). Most quantitative assessments
focused on some or all of the ecosystem services that had been identified in the 2008 ISA
as vulnerable to N deposition because there was too much uncertainty regarding the
physical, biological, or economic impacts on other ecosystem services (Aheme and
Posch. 2013; Van Grinsven et al.. 2013).
In Canada, (Aheme and Posch. 2013) examined critical load exceedances to assess the
impacts of N and S deposition on water quality (eutrophication), soil quality
(acidification), and plant species diversity. The approach was quantitative, but did not
assign values for ecosystem services. Instead, the analysis focused on the sources of these
emissions and understanding what regions within Canada faced a loss of these
ecosystems because critical loads had been exceeded. Based on modeled 2006 deposition
rates, large portions of the country were at risk for soil quality degradation and a loss of
species diversity as a result of atmospheric deposition.
In a European assessment of the effects of N deposition on ecosystem services, de Vries
et al. (2014b) developed a long list of ecosystem services for which N deposition is
known to have a positive or negative impact, including forest productivity, agricultural
productivity (crop and livestock), water quantity and quality, wild plant and animal
products, biodiversity, GHG emissions, nutrient cycling, recreation, and tourism. For a
subset of these impacts (plant diversity, water NCh and Al, soil base cations and Al, and
GHG emissions), the effects of N deposition were modeled using the Very Simple
Dynamic soil model (de Vries et al.. 2014c). The model quantified changes in these
services for the 2000-2050 period using three emissions scenarios: 1980 emissions,
current legislation, and a scenario where deposition does not exceed critical loads for any
ecosystem. The biggest differences between the emision scenarios were that regulations
imposed since the 1980s created significant decreases in areas receiving critical N loads
for water NCh and Al, but also likely decreased CO2 uptake by -20%.
Likewise, the two economic analyses of ecosystem services in Europe have also found
that N deposition has both positive and negative effects on the provisioning of ecosystem
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services. Although not explicitly discussed as "ecosystem services," Van Grinsven et al.
(2013) conducted economic analysis of the influence ofN cycling in Europe and found
that most economic impacts were related to atmospheric N emissions. Although there
were positive impacts on agricultural production from fertilization, there were large
negative impacts of atmospheric N emissions on human health and ecosystem function.
Overall, the costs of added reactive N (atmospheric and agricultural) in the European
Union were between 75 and 485 billion Euros per year. Within the U.K., Jones et al.
(2014) conducted a quantitative analysis that focused on six main ecosystem service
impact pathways (Figure 14-3): timber production, livestock production, carbon
sequestration, greenhouse gas (GHG) emissions, recreational fishing and biodiversity
appreciation. For the first three pathways, declining N deposition is estimated to result in
ecosystem service losses of Ł27.2 million/year, due to decreased fertilization of
woodlands, grasslands, and heathland. For the other three pathways, declining deposition
is estimated to result in ecosystem service gains totaling Ł93 million/year, due to
decreased GHG emissions, improved water quality for recreational fishing, and enhanced
nonuse values for biodiversity through habitat protection. The estimated net gains to U.K.
society are therefore Ł65.8 million/year, with a 95% confidence interval of
15.1-123.2 million pounds per year. Because of the large number of assumptions and
simplifications, both economic analyses were presented as broad conceptual analyses
demonstrating the potential of ecosystem services to quantify the impacts of reactive N in
ways that could be valuable for policymakers, rather than as definitive assessments.
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Benefltsfcosts from declining nitrogen deposition, 19B7-20Q7
200
C 150
M
> 2 100
3 5
Biodiversity
¦ Recr. fishing
N20 emissions
¦ C02 sequestration
¦ Livestock
¦ Timber
-100
Lower bound Central estimate Upper bound
estimate
estimate
C02 = carbon dioxide; N20 = nitrous oxide; recr = recreational.
Source: Jones et al. (2014).
Figure 14-3 Benefits and costs associated with the 25% decline in nitrogen
deposition in the U.K. since 1990.
14.1.3 Global Perspective
There is one new stud}' on ecosystem services with a global perspective, published since
2008 and one study published in 2005, however, not included 2008 ISA. Alcamo et al.
(2005) modeled global and regional impacts of stressors that included critical load
exceedance for acidification and eutrophication on provisioning, regulating, supporting,
and cultural ecosystem services. However, these impacts represent the combined effects
of eight drivers (including climate change, land use change, mineral extractions, and N
fertilizer use). Consequently, the analysis does not define ecosystem service changes that
are specifically attributable to changes in N or S deposition
Erisman et al. (2013) examined the impact of humans on the global N cycle and how
these impacts relate to changes in ecosystem services. They group services into the
following categories:
• Drinking water (nitrates),
• Air pollution effects on human health,
• Air pollution effects on crops (due to ozone),
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• Freshwater eutrophication (defined as areas where the concentration of nitrate
exceeds 1 mg NO.? -N/L (UNEP. 2007; Camargo and Alonso. 2006; Vorosmartv
et al.. 2005).
• Biodiversity loss (they identify the global critical load for biodiversity loss as
5-10 kg/ha/yr (Bobbink et al.. 2010).
• Stratospheric ozone depletion,
• Changes in climate, and
• Coastal dead zones.
It is especially noteworthy that the authors selected thresholds indicating the level of N
addition to an ecosystems that begins to cause adverse effects. The authors discussed the
negative impacts of excess N on human health, but also noted that N can positively
impact nutrition through increased crop supply, which can support undernourished
populations and help fight the spread of disease. The paper concludes that better
quantitative relationships need to be established between N and the effects on ecosystems
at smaller scales, including a better understanding of how N shortages can affect certain
populations.
14.2 Ecosystem Service Profiles of Select Species
Several species profiles have been created to better characterize the ecosystem services
provided by species affected by NOy and SOx. The species included here are identified as
threatened and endangered with N identified as a contributing stressor (Hernandez et al..
2016). The species are: Balsam Fir (Abies balsamea), Eelgrass (Zostera marina), Green
Turtle (Chelonia mydas), White Ash (Fraxinus americana), and Lace lichen (Ramalina
menziesii). These profile identify the geographic distribution within the U.S., ecological
function, Class I areas, FEGS, and cultural importance; information on economic
valuation is presented when available.
14.2.1 Balsam Fir
Scientific Name: Abies balsamea.
• Family: Pinaceae (pine).
Symbolic Role: N/A.
Federal or State Threatened or Endangered Species Listing Status: Endangered
species in Connecticut.
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Geographic Range/Distribution:
• Native and Current Range: The range of balsam fir is North America, including
most of eastern Canada. In the U.S., it extends from Minnesota to Maine and
south into central Pennsylvania and the mountains of Virginia and West Virginia.
Of the two main varieties—balsamea and phanerolepis—it is the latter that is
found in Virginia and West Virginia.
Overlap with Class I Areas:
• http://www.epa.gov/visibilitv/maps.html.
• http://www.epa. gov/ttn/oarpg/t 1 /fr noticcs/classimp.gif.
Habitat: Grows best in areas characterized by cool temperatures and moist soils. In the
U.S., it is most commonly found in mixed stands, where associates include red spruce,
black spruce, paper birch, aspen, and red maple (Ucln til. 1991; USDA. 1990b).
Primary Threats:
• Related to N or S deposition:
• Other: Balsam fir are particularly vulnerable to insect damage from spruce
budworms (Uchvtil. 1991) and from decay caused by the red heart fungus
[Haematostereum sanguinolentum (USDA. 1990b) I.
Ecosystem Role and Function:
• Nutrition: Provides some nutrition for mice, voles, red squirrel, and grouse
(USDA. 1990b).
• Cover: Provides winter cover to ungulates, including white-tailed deer and
moose, and to grouse and songbirds (Uchvtil. 1991). Also provides cover for
small mammals including martens and snowshoe hares (Darveau et al.. 2001; de
Bellefeuille et al.. 2001; Darveau et al.. 1998).
• Other: As with other tree species in general, balsam fir trees provide a number of
other intermediate ecosystem services that are indirectly valued by humans
including nutrient cycling, carbon sequestration, soil stabilization and erosion
control, water regulation and filtration, and air pollutant filtration (Krieger. 2001).
Final Ecosystem Services:
• Direct Human Uses:
• Raw material in wood products and other industries: Used as pulpwood
and lumber for a variety of products. Oleoresin from balsam fir bark blisters
has various uses including as a medium for mounting microscopic specimens
and cement for optical systems (USDA. 1990b). It is also used in developing
fragrances (Zerbe et al.. 2012).
• Energy/Fuel Source: Wood wastes for producers using balsam fir wood or
pulp are sometimes used for energy (USDA. 1990b).
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• Cultural and human health. Balsam fir are commonly grown and used as
Christmas trees and as material for wreath-making. In 2009 they accounted
for 7% of Christmas tree sales in the U.S. (USDA. 2010). A large number of
ethnobotanical uses of balsam fir by Native Americans has also been
documented. The Native American Ethnobotany database maintained by
University of Michigan (2015) references documents citing 87 specific uses
by 13 different tribes, including a wide variety of medicinal uses
(e.g., dermatological and venereal aid; cold and cough remedy) and uses as a
material for rugs and bedding, sewing, and canoe waterproofing.
14.2.2 Eel Grass
Scientific Name: Zostera marina (Zosteraceae).
Federal or State Threatened or Endangered Species Listing Status: Listed as a
conservation species of least concern.
Geographic Range/Distribution:
• Native Range: Eelgrass is native to coastal regions of both the Pacific and
Atlantic Oceans along the coast of North America.
• Current Range: Eelgrass is currently found in coastal regions coastal regions in
the Pacific Ocean along the western U.S. and Canada. It is also found along the
east coast of North America from Canada to the Mid-Atlantic region in the U.S.
(USDA. 2015a). Seagrasses have been disappearing from their native range at an
average rate of 110 km2/year since 1980 (Wavcott et al.. 2009) and are especially
sensitive to changes in temperature along the southern limits of their current range
in North America (Kaldv. 2014).
Overlap with Class I Areas:
• http://www.epa.gov/visibilitv/maps.html.
• http://www.epa.gov/ttn/oarpg/t 1 /fr noticcs/classimp.gif.
Habitat: Coastlines in both the Atlantic and Pacific oceans. It can be found in bays,
estuaries, lagoons and beaches.
Primary Threats:
• Related to N or S deposition: (Hernandez et al.. 2016).
• Other: Threats to eelgrass include dredging for coastal development, overfishing
of predator species that lead to losses of herbivores that clean the leaves, and
sediment and nutrient loading from coastal development (Wavcott et al.. 2009;
Orth et al.. 2006). More broad changes in climate, such as temperature and
sea-level rise also contribute to the loss of seagrasses (Kaldv. 2014; Douglass et
al.. 2010V
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Ecosystem Role and Function: Eelgrass are an important marine species for primary
productivity (Duarte. 2013). Eelgrass also provides a suitable reproductive habitat and
nursery grounds for many species of fish and shellfish (Barbier et al.. 201IV Birds,
invertebrates, green turtles, and manatees use eelgrass as a food source. Some
commercially viable fish species like pacific salmon, pacific herring, and Dungeness crab
rely on eelgrass to provide cover and habitat (Plummer et al.. 2013; Orth et al.. 2006).
Another function of eelgrass is its ability to improve water quality through nutrient
uptake and particle deposition. Eelgrass is an important species for coastal erosion
protection because it helps control wave attenuation (Barbier et al.. 201IV Eelgrass also
provides indirect human benefits through carbon sequestration, because it uses dissolved
carbon in seawater to grow, and at the end of its lifecycle, the carbon is buried and stored
as detritus (Barbier et al.. 201IV
Ecosystem Services:
• Direct Human Uses:
• Cultural: Native Americans used dried eelgrass to bake into cakes and also
for smoking deer meat (Felger and Moser. 1985). Native Americans also
consume the roots of the plant or use it to flavor other foods (University of
Michigan. 2015).
• Raw Material: Eelgrass is used to pack crabs to keep them moist during
transport in the Mid-Atlantic region of the U.S. (Barbier et al.. 2011).
14.2.3 Green Turtle
Scientific Name: Chelonia mydas (Cheloniidae).
Symbolic Role: Green sea turtles are symbols of guidance and protection in Hawaiian
culture.
Federal or State Threatened or Endangered Species Listing Status: Listed as an
endangered species (Seminoff. 2004).
Geographic Range/Distribution:
• Native Range: Green sea turtles have distinct native populations in both the
Pacific and Atlantic oceans.
• Current Range: In the North American Atlantic, nesting sites are found in
coastal regions in Florida, as well as Georgia, South Carolina, and North Carolina
(USFWS). In the Pacific, green turtles nest along the French Frigate Shoals in the
Northwestern Hawaiian Islands (NQAA Fisheries Pacific Islands Regional Office.
2015a).
Overlap with Class I Areas:
• http://www.epa.gov/visibilitv/maps.html.
• http://www.epa.gov/ttn/oarpg/t 1 /fr notices/classimp.gif.
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1 Habitat: Mature green sea turtles are found in shallow coastal regions with large
2 seagrass beds such as bays, reefs, and inlets. Green turtles nest on open beaches with
3 minimal disturbance (USFWS).
4 Primary Threats:
5 • Related to N or S deposition: (Hernandez et al.. 2016).
6 • Other: Other major threats to green sea turtles include entanglement in fishing
7 gear, incidental by catch, and collisions with fishing boats or jet skis. Green turtles
8 also face threats from illegal human harvesting and habitat loss and degradation
9 due to human development along coastal areas and reefs (Malama na Honu.
10 2015V
11 Ecosystem Role and Function: Green sea turtles are herbivores that mostly feed on
12 seagrasses and algae in near-shore marine ecosystems. Green sea turtle eggs are a food
13 source for many coastal species like ghost crabs or marine birds, as well as other
14 scavenging animals. Tiger sharks are the only nonhuman predator for large juvenile and
15 mature turtles (NOAA Fisheries Pacific Islands Regional Office. 2015b). Green sea
16 turtles are valued for their natural beauty, and several conservation groups are dedicated
17 to increasing sea turtle populations (komoroske et al.. 2011). Turtles can also be a source
18 of ecotourism (Campbell. 2002).
19 Ecosystem Services:
20 • Direct Human Uses:
21 • Cultural: Some native Hawaiians consider the green turtle to be a personal
22 or family deity which should not be harmed. The green turtle is featured in
23 Hawaiian culture through depictions in petroglyphs (NOAA Fisheries Pacific
24 Islands Regional Office. 2015a).
14.2.4 White Ash
25 Scientific Name: Fraxinus americana.
26 • Family: Oleaceae (olive).
27 Symbolic Role: N/A.
28 Federal or State Threatened or Endangered Species Listing Status: No special status.
29 Geographic Range/Distribution:
30 • Native Range: Most of eastern North America from southern Canada to northern
31 Florida and as far west as Minnesota (Griffith. 1991).
32 • Current Range: In addition to its native range, white ash is cultivated in other
33 areas, including Hawaii (Griffith. 1991).
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Overlap with Class I Areas:
• http://www.epa.gov/visibilitv/maps.html.
• http://www.epa.gov/ttn/oarp g/t 1 /fr noticcs/classimp.gif.
Habitat: Usually found mixed with other hardwoods (not the dominant species) in
various topographic conditions. It can grow in a wide variety of soil types but does best
in soils with high nitrogen and calcium content, as well as moist and well-drained soils
(USD A. 1990a).
Primary Threats:
• Related to N or S deposition: (Hernandez et al.. 2016).
• Other: White ash has experienced extensive dieback and mortality in its native
range since the 1920s, due to a variety of factors, including ash yellows (AshY
phyotplasma), canker fungi, viruses, drought (Hibben and Silverborg. 1978). and
more recently, invasions of the emerald ash borer [Agrilus planipennis; (Poland
and McC'ulloiigh. 2006)1. White ash has also been found to be sensitive to ground
level ozone exposures (Chappelka et al. 1988).
Ecosystem Role and Function:
• Nutrition: Samaras (seeds) are good forage for wood ducks, northern bobwhites,
purple finches, pine grosbeaks, fox squirrels, mice, and many other birds and
small mammals. It is browsed by white-tailed deer and cattle, and its bark is
occasionally used as food by beaver, porcupine, and rabbits (Griffith. 1991).
• Cover: It provides cover to primary cavity nesters, such as red-headed,
red-bellied, and pileated woodpeckers, and to secondary nesters such as wood
ducks, owls, nuthatches, and gray squirrels (Griffith. 1991).
• Other: As with other hardwood tree species in general, white ash trees provide a
number of other intermediate ecosystem services that are indirectly valued by
humans, including nutrient cycling, carbon sequestration, soil stabilization and
erosion control, water regulation and filtration, and air pollutant filtration
(Krieger. 2001).
Final Ecosystem Services:
• Direct Human Uses (Final Ecosystem Services).
• Raw material in wood products and related industries: White ash trees
provide a dense, shock resistant, and durable wood that is used in a variety of
products, including baseball bats, tool handles, furniture, cabinets, canoe
paddles, snowshoes, and railroad ties (USDA NRCS).
• Energy/Fuel Source: Used for fuel wood (USDA NRCS).
• Human health: Leaves from the white ash have reported beneficial uses,
including the relief of swelling and itching from mosquito bites and
prevention of snake bites (Griffith. 1991).
February 2017
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• Cultural. A large number of ethnobotanical uses of white ash by Native
Americans has been documented. The Native American Ethnobotany
database maintained by University of Michigan (2015) references documents
citing 38 specific uses by 9 different tribes, including a wide variety of
medicinal uses (e.g., gastrointestinal, dermatological, and gynecological aids)
and uses as a material for snow gear, basketry, furniture, canoes, and hunting
and finishing.
• Aesthetic: Provides attractive and vivid fall foliage, including combinations
of orange, yellow, maroon, and purple. For landscaping uses, it is also
considered to be a good and relatively quick-growing shade tree (University
of Kentucky. 2015).
• Nonuse Value: Survey-based economic studies have found evidence of
nonuse values among the general population for protecting white ash from air
pollution in the Adirondacks region (Banzhaf et al.. 2006).
14.2.5 Lace Lichen
Scientific Name: Ramalina menziesii (Ramalinaceae).
Federal or State Threatened or Endangered Species Listing Status: Listed as a
conservation species of least concern.
Geographic Range/Distribution:
• Native Range: Lace lichen is native to the west coast of North America; in the
past it was found in the San Jacinto Mountains near Los Angeles and on the
surrounding coastal plain but now only grows at elevations above the smog layer
(Hastings Reserve. 2015).
• Current Range: Lace lichen grows along the Pacific Coast of North America
from Alaska to Baja California. It grows at elevations up to 3,500 feet (Worth and
Sork. 2008).
Overlap with Class I Areas:
• http://www.epa.gov/visibilitv/maps.html.
• http://www.epa.gov/ttn/oarpg/t 1 /fr noticcs/classimp.gif.
Habitat: Grows on tree species in coastal areas with enough moisture from fog and
strong winds (Egan and Holzman. 2003).
Primary Threats:
• Related to N or S deposition: (Hernandez et al.. 2016).
• Other: Other threats to lace lichen include changes in climate. This species
requires a good amount of moisture and a temperate climate to survive; it is absent
from drier areas within its range (Egan and Holzman. 2003).
February 2017
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Ecosystem Role and Function: Lace lichen has a mutualistic relationship with its host
tree species. Three common host species in California are the valley oak, blue oak, and
coastal live oak (Worth and Sork. 2008). The lichen benefits from the microclimate and
structure provides by the host tree and it benefits the tree by capturing wind-borne
nutrients and moisture and depositing them back to the surrounding soil (Knops et al..
1996). This species is particularly useful in the Santa Lucia Mountains where nitrogen
limits plant growth (Hastings Reserve). Lace lichen is a food source for browsing animals
like deer and cows. It is also used as a nesting material for hummingbirds and orioles
(Hastings Reserve). Lace lichen has also been found to contribute to the global uptake of
sulfur dioxide, an airborne pollutant (Gries et al.. 1997V
Ecosystem Services:
• Direct Human Uses
• Aesthetic: Lace lichen has a unique morphology that adds to the natural
beauty of coastal woodlands along the Pacific Coast (Hastings Reserve.
2015V
• Education/Research: Lace lichen is very sensitive to air pollution, including
exposure to nitric acid (Riddell et al.. 2008) and can be used as an indicator
species to measure air quality (Geiser et al.. 2010). New growth of lichen can
also indicate improved air quality conditions.
14.3 Summary
When natural systems are altered as a result of changes in N or S inputs, their ability to
provide ecosystem services is often affected. Since the 2008 ISA, several new ecosystem
services frameworks and classification systems have been published, including The
Economics of Ecosystems and Biodiversity [TEEB (Sukhdev et al.. 2014)1. the Common
International Classification of Ecosystem Services [CICES (Haines-Young and Potschin.
2011)1. and U.S. EPA Final Goods and Services Classification System [FEGS-CS
(Landers and Nahlik. 2013)1.
In the 2008 ISA, there were no publications specifically evaluating the effects of N and S
deposition on ecosystem services. To connect services to N and S deposition, within the
2008 ISA, the ecological effects were binned into categories defined by Hassan et al.
(2005). Since 2008, several comprehensive studies, focused on U.S. economic markets
and ecosystems, have been published on the costs/benefits of ecosystems services related
to N pollution. These include an evaluation of multiple N inputs (including N deposition)
to the Chesapeake Bay (Birch et al.. 2011). Incorporating values presented in Birch et al.
(2011). Compton et al. (2011). and Compton et al. (2013) presented a synthesis of the
cost/benefits on N loading across the nation for services including: coastal fish harvests,
recreational uses of inland and coastal waters, lakefront property values, water treatment,
and human health costs. Further expanding on this work, Sobota et al. (2015) calculated
February 2017
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the amount of N loading from human activity, which is leaked from the target process,
into adjacent ecosystems and thereby causes alteration of ecosystem services. This work
specifically identifies the costs of atmospheric components of N loading. Rea et al.
(2012) also looked closely at how atmospheric NOy and SOx cause damage to services in
the Adirondacks. Lastly, some key services in which a changing climate will modify the
response to nitrogen have been identified (Baron et al.. 2012).
In the time since the 2008 ISA, several qualitative and quantitative assessments of either
N deposition or the combination of N and S deposition have been conducted in the U.K.
(Jones et al.. 2014). across Europe (de Vries et al.. 2014b; de Vries et al.. 2014c; Van
Grinsven et al.. 2013). and Canada (Aheme and Posch. 2013). Although these
assessments have varied considerably in their approaches, all were intentionally
simplified to neglect much of the mechanistic and spatial complexity on how N
deposition affects ecosystem services. Some of the qualitative and conceptual
assessments provided descriptions of the complex and diverse impacts of N deposition on
ecosystems (de Vries et al.. 2014b; de Vries et al.. 2014c; Jones et al.. 2014).
At the global scale, Erisman et al. (2013) examined the impact of humans on the global N
cycle and how these impacts related to changes in ecosystem services. It is especially
noteworthy that the authors selected thresholds indicating the level of N addition to an
ecosystems that begins to cause adverse effects. The authors discuss the negative impacts
of excess N on human health but also note that N can positively impact nutrition through
increased crop supply, which can support undernourished populations and help fight the
spread of disease. The paper concludes that better quantitative relationships need to be
established between N and the effects on human health and ecosystems at smaller scales,
including a better understanding of how N shortages can affect certain populations.
Several species profiles have been created for this ISA to better characterize the
ecosystem services provided by species affected by N and S deposition. The species
included here as examples are all identified as threatened and endangered, with nitrogen
identified as a contributing stressor (Hernandez et al.. 2016). The species are: Balsam Fir
(Abies balsamea), Eelgrass (Zostera marina), Green Turtle (Chelonia mydas), White Ash
(Fraxinus americana) and Lace lichen (Ramalina menziesii). These profile identify the
geographic distribution within the U.S., ecological function, threatened and endangered
status, Class I areas, FEGS and cultural importance, information on economic valuation
is presented when available.
February 2017
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APPENDIX A. MAPS OF DEPOSITION CHANGE
THROUGH TIME
This appendix contains maps of deposition referred to in Section 2.8.2.
February 2017
A-l
DRAFT: Do Not Cite or Quote
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Total deposition of nitrogen 0002
USEPA 10/16/1-1
u w / y\> i
Source: CAS'IMCT/CMAQ/NTN/AMON/SiiAiiCil
Total N
(kg-N/haj
[!
-e
Total deposition of nitrogen 1113
IIKIPA
Somra: CASTNinWMAQWTT^/AMONjStiARCII
Total N
(kg-N/ha)
[I
-8
N = nitrogen.
Source: CASTNET/CMAQ/NTN/AMON/SEARCH.
Figure A-1 Wet plus dry deposition of total nitrogen over 3-year periods. Top:
2000-2002; Bottom: 2011-2013.
February 2017
A-2
DRAFT: Do Not Cite or Quote
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WetN
(kg-N/ha)
Wet N deposition 0002
USfcFA 1UH6/14
Sotuce: CASTOKrCMAQ/MWAMONSEARCH
Wet N deposition 1113
USiKPA KYlli/M
Snturs: CASTNJH'/CMAQ/NTN/AM()N«IiARCI I
WetN
(kg-N/ha)
N = nitrogen.
Source: CASTNET/CMAQ/NTN/AMON/SEARCH.
Figure A-2 Wet deposition of total nitrogen over 3-year periods. Top:
2000-2002; Bottom: 2011-2013.
February 2017
A-3
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Dry N deposition 0002
USEPA 10/16/1 i
Soilire: CAS'I "NUT/CMAQ/NTN/AMON/SHARCII
Dry N
(kg-N/ha)
-0
Source: CASTftliT/CMAQ/NTN/AMON/SEARCH
Dry N deposition 1113
USliTA 10/16/1-1
Dry N
(kg-N/ha)
-5
-6
-7
-8
- 9
y
-10
-11
¦
->12
N = nitrogen.
Source: CASTNET/CMAQ/NTN/AMON/SEARCH.
Figure A-3 Dry deposition of total nitrogen over 3-year periods. Top:
2000-2002; Bottom: 2011-2013.
February 2017
A-4
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SniircsiCAS'IKirr/CMAQ/NTO/AMON/SliAUt:!!
Dry N
(Pet of Total)
H
P
-0
-10
-20
J
-30
-40
-50
-60
-70
I
-60
-
-90
a
->100
Pet of total N as dry deposit ion 0002
llSIil'A KYI6/1-1
Dry N
(Pet ot Total)
>100
Pet of total N as dry deposition 1113
Source: CASTNEDCMAQWIW/AMON/SEARCH USBPA 10/1 fi/H
1
N = nitrogen.
Source: CASTNET/CMAQ/NTN/AMON/SEARCH
Figure A-4 Percent of total nitrogen as dry deposition over 3-year periods.
Top: 2000-2002; Bottom: 2011-2013.
February 2017
A-5
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Total deposition of oxidized N 0002
USBPA 10/lti/l i
Source: CAS'I"NKf/CMAQ/NTN/AM()N/SI .AltCI I
Total OXN
(kg-N/ha)
Source: CASmrrtyCMAQ/NTN/AMON/SKARa!
Total deposition of oxidized N 1113
USBPA 10/16/1I
Total oxN
(kg-N/ha)
oxN = oxidized nitrogen.
Source: CASTNET/CMAQ/NTN/AMON/SEARCH.
Figure A-5 Wet plus dry deposition of oxidized nitrogen over 3-year periods.
Top: 2000-2002; Bottom: 2011-2013.
February 2017
A-6
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Sourr.?.: CASTNIiT/C:MAQ/N'I'N/AM( )N/SHARC:iI
Pet of total N as oxidized N 0002
LJSrJ'A 10/16/11
-60
Ito
-60
¦-90
H_>ioo
I
0
-30
-40
Total oxN
(Pet of Total)
Source: C.-Vi'INEr/tMAQ/NTN'/IMGN/SEARCH
-50
-60
(70
80
90
>100
Pet of total N as oxidized N 111 3
USBPA 10/16/14
Total oxN
(Pel of Total)
oxN = oxidized nitrogen.
Source: CAST NET/CM AQ/NTN/AM ON/SEARCH.
Figure A-6 Percent of total nitrogen as oxidized nitrogen over 3-year periods.
Top: 2000-2002; Bottom: 2011-2013.
February 2017
A-7
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Dry oxN
(kg-N/ha)
Dry deposition of oxidized N 0002
USEPA I(Vlft/lI
SouiTft: C:AS*I"Ni:r/C:rv1AQ/NTN/AM()N/SliAR(:i I
Souirft: CASTN IiT/C!MAQ/NTN/AMCJN/SIJARClI
Dry deposition of oxidized N 1113
USEPA 1 (VI6/1-1
Dry oxN
(kg-N/ha)
[i
oxN = oxidized nitrogen.
Source: CASTNET/CMAQ/NTN/AMON/SEARCH.
Figure A-7 Dry deposition of oxidized nitrogen over 3-year periods. Top:
2000-2002; Bottom: 2011-2013.
February 2017
A-8
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Pet of total N as dry oxidized N 0002
USOPA 10/16/11
yr60
il70
U-80
1-90
B_>ioo
Source: CASTNEIVCMAQ/NT'N /AMON/SEAROI
Dry oxN
(Pet of Total)
-0
Pet of total N as dry oxidized N 1113
USHl'A IC/lti/M
t— GO
70
80
90
>100
Source: CASTN UT/CM AQ/NTN /AM UN /SliARCl 1
Dry oxN
(Pet of Total)
¦
-0
-10
-20
-30
-40
oxN = oxidized nitrogen.
Source: CASTNET/CMAQ/NTN/AMON/SEARCH.
Figure A-8 Percent of total nitrogen dry deposited as oxidized nitrogen over
3-year periods. Top: 2000-2002; Bottom: 2011-2013.
February 2017
A-9
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TNOs
(kg-N/ha)
—-0.0
Diy deposition of HN03 + pN03 0002
Source: CASTN HT/CiMAQ/NTN/AMUN /SKA&CH USEPA 10/16/14
-3.0
(kg-N/ha)
fo.o
,,
2,0
Soiur e: tASTNLT/CMAQ/N'l'N/AMON/SJiAKCll
Dry deposition of HN03 + pN03 1113
USEPA 10/16/11
-4.0
15.0
>60
TN03 = nitric acid and particulate nitrate.
Source: CAST NET/CMAQ/NT N/AM ON/SEARCH.
Figure A-9 Combined dry deposition of nitric acid and particulate nitrate over
3-year periods. Top: 2000-2002; Bottom: 2011-2013.
February 2017
A-10
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h
HN03
(kg-N/ha)
-3.0
Dry deposition of nitric acid 0002
11 si • PA 10/16/14
Soiuta: CASTN I? 1VCM AQ/NTN/AM ON /SI lARCI I
-4.0
L
®->6.0
Souirft: CASTNTTT/CMAQ/NTN,/AM ON/SFAR CTI
Dry deposition of nitric acid 1113
TJSEPA 10/16/1 I
HNO3
(kg-N/ha)
-0.0
HNO3 = nitric acid.
Source: CASTNET/CMAQ/NTN/AMON/SEARCH.
Figure A-10 Dry deposition of nitric acid over 3-year periods. Top: 2000-2002;
Bottom: 2011-2013.
February 2017
A-11
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Source: CASXNElTCMAQ/mWAMCWSBWCH
Dry deposition of particle nitrate 0002
USEPA 10/16/14
PNO3
(kg-N/ha)
_-0.0
-0.2
-0.4
-0.6
-0.8
-1.0
-1.2
-1.4
p.
¦->2.0
SouiCft: C:AS'min/C:MAQ/N'rN/A!VK)N/SI';AR(:i I
Dry deposition of particle nitrate 1113
USRPA 10/16/1-1
-1.2
-1.4
t
¦->2.0
pN03 = particulate nitrate.
Source: CASTNET/CMAQ/NTN/AMON/SEARCH.
Figure A-11 Dry deposition of particulate nitrate over 3-year periods. Top:
2000-2002; Bottom: 2011-2013.
February 2017
A-12
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Source; c astn t "i ycmaq/ntn/am< )n/si :akci i
Dry deposition of unmeasured N species 0002
USEPA10/16/14
-3.5
lr40
-4.5
¦->5.0
-2.5
-3.0
Other N
(kg-N/ha)
¦
-0.0
-0.5
-1.0
-1.5
-2.0
Source: CASTN LT/CMAQ/NTN/AMON/SiZARCli
Dry deposition of unmeasured N species 1113
usni'A lO/16/i-i
Other N
(kg-N/ha)
[0.0
0.5
,0
1.5
-2.0
-2.5
-3.0
t-3.5
4.0
4.5
>5.0
N = nitrogen.
Source: CASTNET/CMAQ/NTN/AMON/SEARCH.
Figure A-12 Dry deposition of modeled (unmeasured) nitrogen species over
3-year periods. Top: 2000-2002; Bottom: 2011-2013.
February 2017 A-13 DRAFT: Do Not Cite or Quote
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OtherN
(Pet of Total)
Pet of total N as unmeasured species 0002
USBPA 10A6/M
Soiiirft: CASTNl!T/CMAQ/NTNMJVK>N/S!lAKCll
Pet of total N as unmeasured species 1113
USBPA I (VI6/1-1
SouiTftr CASTN I Cl'/C!MAQ/N'I'N/AM( JN/SKARCM I
Other N
(Pet of Total)
N = nitrogen.
Source: CASTNET/CMAQ/NTN/AMON/SEARCH.
Figure A-13 Percent of total nitrogen as modeled (unmeasured) species over
3-year periods. Top: 2000-2002; Bottom: 2011-2013.
February 2017
A-14
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Total deposition of reduced N 0002
IJSEPA 10/16/tJl
Same*: CASTNKnCMAQWTN/AMUN/SKARCH
Total reN
(kg-N/ha)
Srairc«:C:ASTNtsT«:MAQ/N'ra/AMONySUARCII
Total deposition ofreducedN 1113
USHI'A 10,'lfi/M
Total reN
(kg-N/ha)
i
reN = reduced nitrogen.
Source: CASTNET/CMAQ/NTN/AMON/SEARCH.
Figure A-14 Wet plus dry deposition of reduced (inorganic) nitrogen over
3-year periods. Top: 2000-2002; Bottom: 2011-2013.
February 2017
A-15
DRAFT: Do Not Cite or Quote
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Pet of total N as reduced N 0002
US EPA 10/1 fi/M
Source: ClASTNiriVCMAQ/NTN/AMON^l ARCl I
Total reN
(Petal Total)
_ 0
-
-10
-20
-30
-40
-50
-60
-70
-80
-90
I
->100
Total reN
(Pet of Total)
Pet. of total N as reduced N 1 113
US!(PA KYI6/1 I
Source: CASWiriyCMAQ/NTN/AMON/SI-ARCI I
reN = reduced nitrogen.
Source: CASTNET/CMAQ/NT N/AM ON/SEARCH.
Figure A-15 Percent of total nitrogen deposition by reduced (inorganic)
nitrogen over 3-year periods. Top: 2000-2002; Bottom:
2011-2013.
February 2017
A-16
DRAFT: Do Not Cite or Quote
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Soiuca: CAS minVCMAQ/mw/AMON/SIiARC'l I
Dry deposition of ammonia 0002
USEPA 10/16/11
NH3
(kg-N/ha)
l
-4
source: c :astnht/c:maq/ntn/amc >N/SHARCI I
Dry deposition of ammonia 1113
USEPA 10/16/1 i
NHa
(kg-N/ha)
I:
NH3 = ammonia.
Source: CASTNET/CMAQ/NTN/AMON/SEARCH.
Figure A-16 Dry deposition of ammonia over 3-year periods. Top: 2000-2002;
Bottom: 2011-2013.
February 2017
A-17
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Samrat: CASTNI T/CMAQ/NTN/AMONySlJARCU
Dry deposition of particle ammonium 0002
USHPA 10/16/1-1
(kg-N/ha)
(0.0
O.Z
0.4
0.6
-0.8
Soiuvs: CASTNIfl'/t:MAQ/N"('N/AMON/SIJAI4C:il
Dry deposition of particle ammonium 1113
US8PA 10/1644
pNH4
(kg-N/ha)
¦
-0.0
-0.2
-0.4
-0.6
-0.8
pNH4 = particulate ammonium.
Source: CASTNET/CMAQ/NTN/AMON/SEARCH.
Figure A-17 Dry deposition of particulate ammonium over 3-year periods. Top:
2000-2002; Bottom: 2011-2013.
February 2017 A-18 DRAFT: Do Not Cite or Quote
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Dry deposition of reduced N 0002
USEPA 10/16/14
Sou ice: CASTNFT/CMAQ/NTN/AM ON /SEAR CH
Dry reN
(kg-N/ha)
fi
-4
Source: CASTNKI7CM AQ/NTN /AMON/SIiARCU
Dry deposition of reduced N 1113
USlii'A 10/16/11
Dry reN
(kg-N/ha)
reN = reduced nitrogen.
Source: CASTN ET/CMAQ/NT N/AM ON/SEARCH.
Figure A-18 Dry deposition of reduced (inorganic) nitrogen over 3-year
periods. Top: 2000-2002; Bottom: 2011-2013.
February 2017
A-19
DRAFT: Do Not Cite or Quote
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Pet of total N as dry reduced N 0002
U&EPA 10/16/11
Dry reN
(Pet of Total)
¦
r°
M0
Lao
1
-30
-40
-50
-60
-70
-SO
Lgo
I
->100
Souice r CASTN Ul'/CMAQ/NTN /AM UN /SJEARC11
Source: CASTNUl'/CMAQ/NTN /AMON/SEARC1I
Pet of total N as diy reduced N 1113
USEPA10/16/1-'l
Dry reN
(Pet ol Total)
¦
r°
r 1°
L20
|
-30
-40
-50
-60
-70
-SO
L 90
I
L>ioo
reN = reduced nitrogen.
Source: CASTN ET/CMAQ/NT N/AM ON/SEARCH.
Figure A-19 Percent of total nitrogen deposition by dry reduced (inorganic)
nitrogen over 3-year periods. Top: 2000-2002; Bottom:
2011-2013.
February 2017
A-20
DRAFT: Do Not Cite or Quote
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Total deposition of sulfur 0002
USEPA 10/16/14
Snarl): t:AS'I"NlTl/CMAQ/NTN/>UWION/SKARC:i I
Source: C:ASTNiayc:MAq/NTN/AM()WSIiARC:il
Total deposition of sulfur 1113
USI-l'A 10/16/1-1
(kg-S/ha)
Total S
S = sulfur.
Source: CASTNET/CMAQ/NTN/AMON/SEARCH.
Figure A-20 Wet plus dry deposition of total sulfur over 3-year periods. Top:
2000-2002; Bottom: 2011-2013.
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Source: CASTNlHVCMAQ/mWAMt >N/5l>ARC:i t
Wet S deposition 0002
USEPA 10/16/1'1
Wats
(kg-S/ha)
WetS
(kg-S/tia)
Wet S deposition 1113
Soira;e: CASTNET/CMAQrfNTN/AMQN/SEARCH tlSEPA 10/16/14
S = sulfur.
Source: CASTNET/CMAQ/NTN/AMON/SEARCH.
Figure A-21 Wet deposition of total sulfur over 3-year periods. Top:
2000-2002; Bottom: 2011-2013.
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Dry S deposition 0002
Dry S
(kg-Stfia)
Snuira: CASWl-MMAQ/OTN/AMON/SItARCH tJSEPA 10C16/1'!
Dry S
(kg-sma)
I!
Dry S deposition 1 i 13
Somcft: CASTNinX-'MAQ/N-m/AMON/SHAKCil IJSKPA KV16/14
S = sulfur.
Source: CASTNET/CMAQ/NTN/AM O N/S E ARC K
Figure A-22 Dry deposition of total sulfur over 3-year periods. Top:
2000-2002; Bottom: 2011-2013.
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Dry S
(Pet of Total)
Pet of total S as dry deposition 0002
Sontrj: CAS'lWn'/CMAQ/NTN'AMON/SEARCH USEPA 10/lS/l-l
Dry S
(Pet of Total)
Pet of total S as dry deposition 1113
Source: CASTNRT/CMAQ/fTI'N/AMONVSRARCH ttSEPA 10/16/M
S = sulfur.
Source: CASTNET/CMAG/NTN/AMON/SEARCH
Figure A-23 Percent of total sulfur deposition by dry deposition over 3-year
periods. Top: 2000-2002; Bottom: 2011-2013.
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Souice: CASTN F'lVC :M AQ/NTN/AM C)N/SKARCH
Diy deposition of sulfur dioxide 0002
USEPA 1CV16/14
S02
(kg-S/ha)
Dry deposit ion of sulfur dioxide 1113
USEPA 10/16/1-1
Somrrt: CASTNEI7CM AQ/N" IWAM C)N/SIIARCI I
S02
(kg-S/ha)
S02 = sulfur dioxide.
Source: CAST NET/CMAQ/NT N/AM ON/SEARCH.
Figure A-24 Dry deposition of sulfur dioxide over 3-year periods. Top:
2000-2002; Bottom: 2011-2013.
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Dry deposition of particle sulfate 0002
USEPA 1CV16/M
Source: C:ASTN I iT/CM AQ/m WAMON/SEARCI I
pS04
(kg-S/ha)
[0,0
0.2
0.4
0.6
-0.8
Dry deposition of particle sulfate 1113
USIilPA 10/16/M
Souirft: CASTNI nYCMAQ/NTN/AIW)N/St ARCi t
pS04
(kg-S/ha)
¦
-0.0
-0.2
-0.4
-0.6
-0.8
pS04 = particulate sulfate.
Source: CASTNET/CMAQ/NTN/AMON/SEARCH.
Figure A-25 Dry deposition of particulate sulfate over 3-year periods. Top:
2000-2002; Bottom: 2011-2013.
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APPENDIX B. MERCURY CYCLING
This appendix describes the deposition and cycling of mercury within North American
ecosystems. Connections to sulfur cycling are emphasized where such information is
available. This appendix provides background information and context for the discussion
of nonacidifying sulfur stimulation of mercury methylation in wetland and aquatic
ecosystems (Chapter 12).
B.1. TRANSFER OF MERCURY FROM THE ATMOSPHERE TO
TERRESTRIAL ECOSYSTEMS
Mercury enters most natural terrestrial and aquatic ecosystems in the United States via
atmospheric deposition, although both active and historic mining and industrial sites have
contaminated soil and water in many ecosystems. Sources and atmospheric processes
governing Hg deposition are covered more exhaustively elsewhere (Wentz et al.. 2014;
Pirrone et al.. 2010). For the purposes of this section, we will focus on the deposition of
reactive Hg, which is deposited into ecosystems in the form of free Hg(II),
particulate-bound Hg, or as MeHg. In a jack pine/birch forest in the ELA sampled
1998-1999, wet deposition was 71,000,000 ng/ha/yr (reported as 71 mg total Hg/ha/yr),
with dry deposition estimated at 9,000,000 ng/ha/yr [reported as 9 mg/ha/yr in St Louis et
al. (2001)1.
Foliage is an important Hg pool in both forested and wetland ecosystems, since it can
directly absorb Hg deposition as well as store Hg taken up by plant roots. In the Arbutus
Lake watershed in the Adirondack Mountains, Hg in the AI mis and Betula overstory was
3,080 ng Hg/m2 (3.08 (ig Hg/m2), and was 9,480 ng/m2 (9.48 (ig/m2) in the Sphagnum
mat of the wetlands (Selvendiran et al.. 2008b'). In a 3-year long Hg tracer isotope annual
addition experiment at ELA, upland canopy and ground vegetation retained 40% of
added Hg. In a wetland ecosystem, vegetation retained 80% of added Hg (Harris et al..
2007). Although the wetland ecosystems exported Hg and MeHg to an adjacent lake in
the watershed during the course of the study, it was Hg from older sources than the
experiment, indicating that Hg storage in wetland vegetation may have a residence time
greater than one year (Harris et al.. 2007).
Foliage also represents an important flux of Hg: following senescence, leaf litter becomes
the substrate for microbial decomposition, and Hg moves out of plant biomass and into
microbial biomass, soil, or water. Flux of total Hg from litter in the ELA, Ontario, was
twice that of wet deposition in litter from upland trees, and was of a similar magnitude to
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deposition in litter from wetland shrubs and trees [72,000,000 ng/ha/yr or 72 mg
Hg/ha/yr, and 88,000,000 ng/ha/yr or 88 mg/ha/yr; (St Louis et al.. 2001)1. The organic
horizon of the soil, where litter and microbial communities are concentrated, was a major
sink of Hg within the forested and wetland ecosystems for the 20 years preceding this
study, with annual Hg accumulation rates of 130,000,000 ng Hg/ha/yr (reported as
130 mg Hg/ha/yr) for ridgetop soils (160% of total annual deposition),
200,000,000 ng/ha/yr (200 mg/ha/yr) for upland forest (250% of deposition), and
590,000,000 ng/ha/yr (590 mg/ha/yr) in wet soils supporting Sphagnum mosses
[7.4 times annual deposition; (St Louis et al.. 2001)1. In forest catchments, much of the
Hg deposition is retained in soil (St Louis et al.. 2001; St. Louis et al.. 1996). as
confirmed by the Hg tracer isotope addition experiment in ELA, which found that after
3 years of Hg addition, 58% of the added Hg was retained in soil in the upland forest
catchment (Harris et al.. 2007). The length of residence within the soil for Hg likely
depends on the same factors that control the storage of organic matter, such as soil
structure, temperature, precipitation, and timing of disturbances, particularly of wildfire.
B.2. TRANSFER OF MERCURY FROM TERRESTRIAL TO
AQUATIC ECOSYSTEMS
When Hg is released from plant tissue, detritus, or soil particles into surface water or the
soil solution, it becomes available for transport into aquatic systems. In five boreal forest
catchments in the ELA, Ontario, measured during the period 1990-1993, the flux of total
Hg from the forest into waterbodies was estimated to be 14,000,000-21,000,000 ng/ha/yr
(reported as 14-21 mg/ha/yr 28-42% of annual Hg input), in response to approximately
47,000,000 ng/ha/yr (47 mg/ha/yr) wet + dry deposition of Hg, and estimated
contributions from weathering of granite of as much as 3,000,000 ng/ha/yr [reported as
3 mg/ha/yr in St. Louis et al. (1996)1. On Isle Royale, a large island in Lake Superior and
a Class I Area, researchers estimated that lakes received one third of their annual Hg load
directly from atmospheric deposition, and the remaining two thirds of annual Hg load
was mobilized from soils in the watersheds (Drevnick et al. 2007). In aquatic
environments, specialized microbes (SRPs; as well as iron-reducing bacteria) in anoxic
zones can methylate inorganic Hg, transforming it into the toxic, persistent MeHg.
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B.3. TRANSFER OF MERCURY FROM ATMOSPHERE TO
AQUATIC ECOSYSTEMS
Total Hg deposited directly to lakes is rapidly incorporated into Hg cycling in abiotic and
biotic pools. In a Hg isotope addition experiment at the ELA, Ontario, a spike of isotope
202Hg was added directly to the lake annually over the course of three years. The 202Hg
was detected in the anoxic hypolimnion within days of addition, and in bottom sediments
of the lake within four weeks (Harris et al.. 2007). and methylated 202Hg was detected in
zooplankton, benthic amphipod Hyallela Azteca, and fish species within 2 months of
addition (Harris et al.. 2007). indicating that Hg methylation and movement of MeHg
within the food web can occur within a single season in aquatic ecosystems. Estimated
residence time of atmospherically deposited Hg2+ in the water column of Little Rock
Lake, Wisconsin, was 150 days (Watras et al.. 2006).
B.4. METHYLMERCURY CYCLING
Methylmercury (MeHg) is produced by sulfur-reducing prokaryotes (SRPs) in the course
of sulfate reduction. It is toxic to humans and vertebrate animals, particularly because it
biomagnifies up the food chain and bioaccumulates within organisms. The following
sections describe transfer of MeHg between ecosystem compartments, as well as
characteristics of zones of high MeHg production within the landscape.
B.4.1. Transfer of Methylmercury from Terrestrial to Aquatic Ecosystems
MeHg is a very small component (1%) of Hg atmospheric deposition to ecosystems
(Wentz et al.. 2014); most MeHg in ecosystems is microbially produced from inorganic
Hg. Much of our knowledge about Hg cycling in natural ecosystems comes from the
Experimental Lakes Area (ELA) in northwestern Ontario, Canada, which receives low
Hg deposition [47,000,000 ng/ha/yr or 47 mg/ha/yr in 1990-1993; 80,000,000 ng/ha/yr
or 80 mg/ha/yr in 1998-1999 (St Louis et al.. 2001; St. Louis et al.. 1996)1. A small
portion of total Hg deposition in the ELA is in the form of MeHg, 900,000 ng/ha/yr
(reported as 0.9 mg/ha/yr, or <1.5% of total Hg deposition). MeHg cycles through the
terrestrial ecosystem as total Hg does. Leaf litter represents a significant flux of MeHg
from the living canopy in upland forest to the detrital food web of 800,000 ng
MeHg/ha/yr (reported as 0.8 mg MeHg/ha/yr), a flux of a similar magnitude to
atmospheric deposition (St Louis et al.. 2001). In the 20 years preceding the study,
600,000 ng MeHg/h/yr (reported as 0.6 mg/h/yr of MeHg) were annually stored in the
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organic soil pool, and on average 100,000 ng MeHg/ha/yr (reported as 0.1 mg
MeHg/ha/yr) was exported from the catchment in stream flow (St Louis et al.. 2001).
In five boreal forest catchments at the ELA, St. Louis et al. (1996) assumed a background
MeHg deposition rate of <500,000 ng MeHg/ha/yr (reported as <0.5 mg MeHg/ha/yr). A
catchment consisting only of upland forests exported 18% of estimated annual MeHg
deposition, indicating that terrestrial ecosystems retain MeHg (St. Louis et al.. 1996). and
that aquatic MeHg is produced endogenously.
B.4.2. Transfer of Methylmercury from Wetlands to Aquatic Ecosystems
At the landscape level, MeHg export from wetlands in streams and rivers is correlated
with wetland cover in watersheds. In the ELA in Ontario, a catchment with valley bottom
wetlands exported 73% of deposited MeHg in a dry year, but 158-200% of deposited
MeHg in a wet year, indicating that the wetlands produced MeHg in wet years. MeHg
export was high in catchments with other types of wetlands as well; a catchment with
riverine wetland (peatland fed by surface water flow) exported 120-130% of annually
deposited MeHg in dry and wet years, and a catchment containing a basin wetland
exported 213% MeHg in a dry year and 500-719% annually deposited MeHg in wet
years, indicating a strong source of MeHg within the watershed, presumably in the
wetlands (St. Louis et al.. 1996). More recent work in the watershed of Arbutus Lake,
New York measured Hg and MeHg in streams draining upland and wetland areas; MeHg
was 1.7-3.0% of total Hg in upland streams, and 7.8% of total Hg in a similarly low
order stream that drained a wetland. In downstream peatlands, MeHg was 5.4-9.5% of
total Hg (Selvendiran et al.. 2008a). and the beaver meadow peatland exported 623% of
total MeHg input annually, while the riparian wetland exported 8% of total MeHg input
(Selvendiran et al. 2008b). Wetlands, with high dissolved organic carbon and fluctuating
water levels and anoxic zones, are areas of high MeHg production within watersheds, and
will affect MeHg concentrations in water and biota downstream.
B.4.3. Methylmercury Cycling in Aquatic Ecosystems—Lake Onondaga, New
York
Lake Onondaga, New York was the subject of a Hg budget project in 1992, as the
eutrophic lake received high Hg loads through the late 1970s from industry I Figure B-l;
(Henry etal.. 1995)1.
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Volatilization
(0. 016, 0)
Outlet
(2.8, 0.24)
Net Methylailon
(0. 0.63)
Net Uptake by Fishes
(0J20, 0J0)
Gross
Sedimentation
(13.7, 0.73)
Dissolved Flux
(0.056, 0.017)
Remineralization (2.6, 0.26)
Net Sedimentation
(11.3, 0.62)
Tributaries
and Metro
(13,6, 0,26)
Aim o spheric
Deposition
(0,44, 0.006)
^ Groundwater
Inflow
(0.02. 0,001)
Hg = mercury; kg = kilogram: MeHg = methylmercury; yr = year.
Figure B-1 Mercury and methylmercury mass balance cycle in Lake
Onondaga in 1992. The quantities of mercury in each flux are
indicated in parentheses by (kg total Hg/yr, kg MeHg/yr), from
Henry et al. (1995).
In 1992, 14.1 kg of total Hg entered the lake, 96% of which was carried into the lake by
tributaries, including one that drained a former chlor-alkali plant. The largest sink for Hg
within the lake was through sedimentation, which accounted for 11.1 kg of total Hg. In
that same year, 2.8 kg of total Hg flowed out of the lake downstream and 0.20 kg Hg
(0.1% of total annual Hg load) was incorporated into fish biomass (Henry et al.. 1995).
A budget for Hg methylation was also constructed for the lake, and differs front total Hg
in several important points (Figure 12-4). First, only 29% of the annual lake MeHg load
of 0.88 kg entered the lake via tributaries (compared to nearly the entire total Hg load).
The water column, particularly deep, anoxic water, contributed 0.60 kg or 68% of the
annual MeHg load of the lake (Henry et al.. 1995). More than half (about 0.47 kg) of the
annual MeHg load was incorporated into sediments, and while sedimentation rates were
high, about one- to two-thirds of MeHg in sediments was released back into the water
column. Since most of the total Hg in fish is in the form of MeHg, the model calculated
that the MeFIg in fish biomass was the same amount as total Fig in fish biomass, 0.20 kg,
although this constituted a much higher portion of the annual MeHg load [23% of annual
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MeHg; (Henry et al.. 1995)1. This early study showed that the majority of MeHg in Lake
Onondaga was produced within the lake itself, specifically in the anoxic zone, and that
MeHg cycled between the sediments and water column, with a significant amount stored
in fish tissue.
Lake Onondaga was resampled in 2006, 2007, and 2009, following industrial remediation
projects and incorporation of nitrification treatment in the municipal wastewater plant
discharging into the lake (Todorova et al. 2014). In 2006-2009 sampling, MeHg
concentrations in the epilimnion were significantly lower than in 1992, and total Hg in
the epilimnion was half of the tHg concentrations measured in 1992 (Todorova et al..
2014). However, in all years there was a significant peak in MeHg concentrations and in
MeHg:tHG ratios in the epilimnion in the fall following turnover (Todorova et al.. 2014).
indicating that this seasonal event will have significant effects on total MeHg in the food
chain of the lake.
BAA. Methylmercury in Sediments and Water Column—Lakes
The sediments under shallow, oxygenated lake waters are an important site of Hg
methylation. Early literature showed that Hg methylation rates are higher in shallow
organic sediments than in deep clay-rich sediments in Southern Indian Lake in Manitoba,
Canada, and that the ratio of methylation:demethylation was also higher in organic
sediments (Ramlal et al.. 1986). In the Quabbin Reservoir, Massachusetts, MeHg
fractions in sediments were 3.1-16.3% at 1 m depth, and decreased with increasing lake
depth to 0.1-0.2% at 22-23 m depth (Gilmour et al.. 1992). At Lake Clara, Wisconsin,
Hg methylation rates were sampled in the water column, flocculant surface sediments,
and deeper sediments at water depths of 1-10.5 m (Korthals and Winfrey. 1987). At all
sampling depths, methylation and demethylation were detectable in the water column and
in the surface sediments. Gross Hg methylation rates were highest in surficial sediments
sampled at depths of 5-7.5 m, but the methylation:demthylation ratio was highest
(5.5-5.8) in surficial sediments at depths of 1-2 m (Korthals and Winfrey. 1987).
Larger, deeper lakes stratify during the summer; waters near the surface (epilimnion) of
the lake are high in oxygen and primary productivity, while deeper waters (hypolimnion)
have low oxygen, lower primary productivity, and high rates of S reduction and MeHg
production. In the experimentally acidified Little Rock Lake, Wisconsin, MeHg was low
(less than 0.1 ng/L) in surface waters during the summer months, but increased at anoxic
depths below 4-6 m to 1 ng/L in June, 3 ng/L in July, and 3.5 ng/L in August (Bloom et
al.. 1991). In stratified Lake Onondaga, New York, the water column, particularly deep,
anoxic water, contributed 0.60 kg or 68% of the annual MeHg load of the lake (Henry et
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al.. 1995). Sampling in Pallette Lake, Wisconsin, showed that the oxic-anoxic boundary
was at 12 m depth in this stratified lake, which was also the location of the sulfate-sulfide
transition (Watras etal.. 1995). There were peaks in both sulfate reduction and Hg
methylation from 12-13 m depth, right at the top of the hypolimnion, which was
enriched in MeHg (20-30%) compared to the epilimnion (5-10% MeHg). There was no
sulfate reduction detected in the profundal sediments or deep layers of the hypolimnion.
MeHg was transported from the oxic-anoxic boundary and hypolimnion where it was
produced to the epilimnion, and the flux of MeHg from the hypolimnion
(3,400,000-6,800,000 ng/day, reported as 3.4-6.8 mg/day) was much larger than the flux
of MeHg into the epilimnion from the atmosphere [10,500 ng MeHg/day, or 0.0105 mg
MeHg/day; (Watras et al.. 1995)1. Ecklev and Hintelmann (2006) showed that in boreal
Canadian lakes, potential methylation is highest approximately 1 m below the oxycline,
and this methylation zone moves up the water column as the oxycline rises due to oxygen
depletion at depth in the summer (Ecklev and Hintelmann. 2006).
B.4.5. Methylmercury in Sediments and Water Column—Wetlands
In wetlands at Bog Lake Fen in the Marcell Experimental Forest, Minnesota, the highest
levels of MeHg production occurred at the upland-peatland interface. When mesocosms
installed in the bog interior received additions of labile C and sulfate, MeHg
concentrations were similar to MeHg concentrations from the upland-peatland interface,
indicating that upland inputs of C may contribute to high methylation rates in the
peatland (Mitchell et al.. 2008a). A larger study that sampled peatlands within the
Marcell Experimental Forest, Minnesota, as well as at the ELA in Ontario found that
%MeHg was highest within 5-10 m of the upland-peatland interface across wetlands, and
that sulfate and pH were higher at the interface, and DOC was lower at the interface, than
in the interior of the peatlands (Mitchell et al.. 2008a). In peatlands in the Arbutus Lake
watershed in the Adirondack Mountains, New York, MeHg and total Hg were higher in
pore water near the top of the peat profile, at 20-40 cm depth, than at 80-100 cm depth
(Selvendiran et al. 2008a). and the total Hg and MeHg were highest in both peat and
pore water in the top 15 cm of the peat (Selvendiran et al.. 2008a). The Hg in the top
15 cm of peat was estimated to be about 27% of the total Hg, and MeHg in the top 15 cm
was 30% of the total MeHg in a riparian peatland and 50% of the total MeHg in a beaver
meadow (Selvendiran et al. 2008a). In freshwater Sphagnum peatlands of the Allequash
Creek watershed in the Northern Highland Lake District of Wisconsin, reducing
conditions exist below 2 cm depth in the peat, and MeHg concentrations peak at 7 cm
depth in the peat (C re swell et al.. 2008).
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In wetlands not dominated by Sphagnum, Hg methylation occurs in sediments and in
periphyton (see Section 12.3. In the freshwater marshes of the Florida Everglades, where
periphyton and flocculation often extend the sediment-water interface, methylation rates
were highest in the top 6 cm of sediments (Gilmour et al.. 1998). In coastal marsh
sediments, such as at Kirkpatrick Marsh on the Chesapeake Bay, MeHg was highest in
the top 6 cm of sediment, although total Hg was highest at 12-15 cm depth in the
sediments (Mitchell and Gilmour. 2008). and in coastal Georgia marshes, sediment core
incubations showed that MeHg production was highest in the top 4 cm of the marsh
sediments (King et al.. 1999).
B.4.6. Methylmercury in Sediments and Water Column—Estuarine and Marine
Ecosystems
Research shows that Hg methylation occurs in estuaries and in marine sediments.
Incubations of samples collected in the Patuxent River and Estuary, Maryland, showed
that net MeHg production in sediments was four times the rate of MeHg accumulation in
sediments, suggesting that MeHg in estuary surface waters comes from estuarine
sediment sources as well as sources upstream in the watershed (Benoit et al.. 1998).
MeHg comprised 5% of surface water particulate Hg (unclassified compounds large
enough to be removed by filtration) and 2% of total Hg in surface water, and 0.3% of Hg
in estuarine sediments (Benoit et al.. 1998). More recently, surface sediments were
sampled from the Chesapeake Bay, from four locations in the main channel, two
locations on the continental shelf, and one location on the slope of the continental shelf.
Total Hg in the upper Bay ranged from 50 to 171 ng Hg/g sediment (reported as
250-850 pmol/g), in the lower Bay and continental shelf ranged from 2.0 to 20 ng Hg/g
sediment (10-100 pmol/g), and at the single continental slope site was 50-70 ng Hg/g
sediment (250-350 pmol Hg/g); (Hollweg et al.. 2009). MeHg was 0.2-1.5% in 0-12 cm
sediments across sites, and bottom water salinity was strongly correlated with %MeHg
[r = 0.814; (Hollweg et al.. 2009)1. suggesting that MeHg was produced in marine
sediments.
An incubation study of water samples collected at depths of 20-327 m in the ocean
around the Canadian Arctic Archipelago found measurable rates of Hg methylation at all
depths from all 5 sites sampled. Methylation of inorganic Hg accounted for 47% of the
MeHg present in the water column at these locations, and demethylation was also widely
observed, indicating that marine MeHg represents marine production of MeHg, not
merely transport of MeHg from other systems (l.elinlierr et al.. 2011).
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APPENDIX C. CASE STUDIES
This appendix includes five case studies which are meant to identify the ecological
effects of nitrogen (N) and sulfur (S) with a specific focus on National Parks and areas
with long-term research. The locations of these case studies were chosen because they are
areas for which a substantial amount of published work on ecological response to N
and/or S deposition is available. The locations include the Northeastern U.S.,
Southeastern Appalachia, Tampa Bay, Rocky Mountain National Park and Southern
California. These case studies identify current acidification and nutrient status, as well as
empirical and modeled critical loads. The scientific characterizations of ecological
responses to N and S in these case studies set the scientific foundation for further analysis
of risk and exposure.
C.1. NORTHEASTERN U.S. CASE STUDY: ACADIA NATIONAL
PARK, HUBBARD BROOK EXPERIMENTAL FOREST, AND
BEAR BROOK WATERSHED
C.1.1. Background
This case study is meant to identify effects of nitrogen (N) and sulfur (S) in the
northeastern U.S., with a specific focus on National Parks and areas with long-term
research. This case study identifies current acidification and nutrient status and empirical
and modeled critical loads (CLs). The 2008 NOx-SOx ISA included a case study of
acidification in the Adirondak region of New York [Section 3.2.2.4 of 2008 ISA (U.S.
EPA. 2008a) I. This case study is considered as a supplement to that earlier case study.
Further information about the Adirondak region can be found in Chapter 4 and Chapter 5.
C.1.1.1. Description of Case Study Region
Acadia National Park (ACAD) in coastal Maine, the Hubbard Brook Experimental Forest
(HBEF) in the White Mountains of New Hampshire, and the Bear Brook Watershed
(BBW) in southeastern Maine were chosen for this case study to represent northeastern
U.S. ecosystems known historically to be sensitive to acidification and nutrient
enrichment from atmospheric S and N deposition (Figure C-l. Table C-l). In this case
study, we highlight multiple decades of research and monitoring at these locations to
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provide insights into the ecosystems" responses to S and N deposition and look for any
indications of recovery.
Bear Brook Experimental
Watershed
Hubbard Brook
Experimental Fores
Northeast Case
Study Region
Caw Study Locations
Native American
Reservation!
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C.1.1.1.1.
Acadia National Park
Acadia National Park is located at the interface between northern coniferous forests and
temperate deciduous woods and hosts plant species from two distinct regions
(http://www.acadiacentennial2016.org/visit-acadia/acadias-treasures/). ACAD
encompasses 45,000 acres on two islands and a mainland peninsula on Maine's coast. It
receives about 140 cm/yr of rainfall (Nielsen and Kahl. 2007). Geologically, the park
consists of granite mountains with surrounding sedimentary and metamorphic rock. The
soils have low buffering capacity, and steep slopes at high elevations make soil and
runoff susceptible to acidification. The park's ecosystems include alpine heath, stunted
growth woodlands, jack pine forests that include pitch pine, rocky woodlands of black
spruce and heaths, mature spruce, and fir. Red spruce and sugar maple are the
predominant tree species in ACAD.
Eighty freshwater plant species have been documented in ACAD with another
12 semiaquatic shorelines species. Seven of the aquatic and semiaquatic plants are listed
or proposed for inclusion on Maine's List of Endangered and Threatened Species.
Another 30 of these species are considered "locally rare"
(https://www.nps.gov/acad/learn/natiire/plants.htm).
Hubbard Brook Experimental Forest is located in the southern portion of the White
Mountain National Forest in central New Hampshire (Figure C-2). The Atlantic Ocean is
about 116 km to the southeast. Most of the surrounding land is in the National Forest.
The area is hilly and steep in places with coarse-textured acidic soils. The bedrock is
dominated by metamorphosed igneous and sedimentary rocks. Bedrock is covered by
about 2 m of glacial till.
C.1.1.1.2.
Hubbard Brook Experimental Forest
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/ —. Mt. Cushman
W» m
2 vYF:
*x«l5\4 \A}*A
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Bird Transect Ares \ v 'X° \
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Mirror I
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1015 m \
« / \ ° I
/ \ i V"""\ / ;
(\ ° ^ g 6, I /
i, „ \ 8 : „ 9 /
f *?Ł >
Legend
to '
* v'
° Rain gage
Stream
Gaged Watershed
HBEF Boundary
N
A
213 m
White Mm
Sail, tores!
3 km
New
Hampshire
FS = Forest Service; HBEh = Hubbard Brook Experimental Forest; km = kilometer; m = meter; Mt = mount; Mtn = mountain;
Natl = national.
Shown are the network of rain gages, experimental watersheds, and Mirror Lake.
Source: Campbell et al. (2007).
Figure C-2 Site map of Hubbard Brook Experimental Forest in the White
Mountains of New Hampshire.
Northern hardwood forests occupy lower elevation slopes with spruce-fir occurring on
upper elevation slopes. Annual average precipitation is about 140 cm (one-third to
one-quarter of which falls as snow; http://hubbardbrookfoundation.org/wD-
contcnt/uploads/2010/12/1 onu term effects.pdf).
Glacier-deposited materials vary greatly in degree of sorting and grain size. Glacial
deposits" thicknesses are zero on ridgetops and in stream valleys and 50 m near Mirror
Lake. Principal soils are acidic (pH about 4.5 or less) and relatively infertile. The 20- to
200-mm thick forest floor allows rapid infiltration of water and insulates against soil
freezing before snow accumulates. Streams vary from small ephemeral channels to as
large as perennial 5th order. Up to about 60 to 80% of storm precipitation flows by
stream. HBEF is entirely forested, predominately with deciduous northern hardwoods
including sugar maple (Acer sctcchanim), beech (Fagns grandifolia), and yellow birch
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(Betula allegheniensis). High-elevation conifers include red spruce (Picea rubens),
balsam fir (Abies balsamea), and white birch (Betula papyrifera). Logging operations
ended approximately 1915 to 1917. The second-growth forest is about 80 to 90%
hardwoods and 10 to 20% conifers. HBEF hosts more than 90 species of birds, snowshoe
hare, moose, fox, black bear, beaver, and white-tailed deer are present
(http: //www .hubbardbrook.org/overview/sitede scription. shtml).
HBEF ornithological studies have found that the abundance of birds decreased from more
than 200 individuals per 10 ha in the early 1970s to 70 to 100 per 10 ha during the period
from the early 1990s to the present. This decrease is unexplained (R.T. Holmes
publications—Bird Abundances—http://www.hubbardbrook.org/data/dataset.php'.>id=8 1
and http://hubbardbrookfoundation.org/wp-
contentAiploads/2010/12/long term effects.pdf).
C. 1.1.1.3. Bear Brook Watershed
The BBW hosts a long-term, gaged, forested, first-order paired stream watershed. It is
located about 40 km from the Atlantic Ocean on the southeast slope of Lead Mountain. It
has a total relief of 210 m and a maximum elevation of 450 m. Two nearly perennial, low
dissolved organic carbon (DOC), low acid-neutralizing-capacity (ANC) streams (East
and West Bear Brook [EB and WB]) drain 10.3 and 11.0 ha contiguous watersheds,
respectively. BBW is covered predominantly by hardwoods (Fagus grandifolia, Acer
rubrum, Acer saccharum, Betula alleghaniensis, Betula papyrifera, and Acer
pensylvaticum) and red spruce. Soils are coarse, loamy, mixed, frigid Typic Haplorthods
developed on till averaging 1 m in thickness. Bedrock is mainly quartzites and
metapelites with local granitic intrusions
(https://iimaine.edu/bbwm/aboiit-bbwm/site-description-2/).
West Bear Brook has received bimonthly additions of ammonium nitrate since November
1989 (-1,800 eq/ha/yr—a 300% increase over ambient N deposition at the beginning of
the study). East Bear Brook has received no additions and serves as a reference [see
Norton etal. (1999)1. BBW has been a research site for 3 decades with a focus on
increasing decadal-scale understanding about northern forested ecosystems' response to
chemical and physical change, including whole ecosystem acidification, nitrogen
enrichment, and climate change. BBW research has focused on: alterations to nitrogen
dynamics, base cation decline, carbon cycling, phosphorus controls on nitrogen cycling,
response to decreasing ambient sulfate deposition, sustained elevated experimental
sulfate deposition, and changes in forest growth
(https://iimaine.edii/bbwm/research/environmental-research/).
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C.1.1.2. Class I Areas
In an effort to preserve pristine atmospheric conditions, the Clean Air Act (42 USC 7470)
authorized Class I areas to protect air quality in national parks over 6,000 acres in size
and national wilderness areas over 5,000 acres.
Class I areas are subject to the "prevention of significant deterioration (PSD)" regulations
under the Clean Air Act. (42 USC 7470). PSD preconstruction permits are required for
new and modified existing air pollution sources, and air regulatory agencies are required
to notify federal land managers (FLMs) of any PSD permit applications for facilities
within 100 km of a Class I area.
ACAD is a PSD Class I Area. HBEF is not in a Class I area, but is near two New
Hampshire Class I areas, the Great Gulf and the Presidential Range-Dry River
Wilderness Areas. BBW is located southwest of the Moosehorn Wilderness Area in
Maine.
C.1.1.3. Regional Land Use and Land Cover
No large population centers are located near HBEF or BBW. Several small towns are
interspersed with ACAD lands, including Bar Harbor (pop. 5,235), Southwest Harbor
(pop. 1,765), and Trenton (pop. 1,481). The populations of these towns increase
substantially with tourists during summer. Bangor (pop. 32,000) lies about 40 miles north
from Mount Desert Island. All three study areas are mostly forested, as is much of the
Northeast region (Table C-2. Figure C-3).
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Table C-2 Land use/land cover for northeastern case study areas.
Area Covered (km2)
ACAD
HBEF
BBW
Developed and barren
83.82
2.96
0.00
Hardwood forest
76.84
159.53
6.64
Conifer forest
592.56
61.88
0.60
Mixed forest and shrubland
300.27
111.49
2.53
Meadow/herbaceous
26.33
0.50
0.00
Wetland
137.05
1.47
0.16
ACAD = Acadia National Park; BBW = Bear Brook Watershed; HBEF = Hubbard Brook Experimental Forest; km = kilometer.
okhvpen men
Mh-i-slu'cl
Acadia National
Park
Atlantic Ocean
Northeast Case Study
Region: Land Cover
! Cis« Study Locations
Native America n
Reservations
D*v*loped Land {increasing intensity}
Barren Land
1 Deciduous Forest
m Evergreen Forest
Mixed Forest
Shrub/Scrub
Grassland/Herbaceous
H Cultivated Crops
¦ Water/Wetlands
Figure C-3
February 2017
Land cover in the Northeast case study region.
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C.1.1.4. Organization of This Case Study
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Table C-3 Literature cited by northeast U.S. case study area.
Variable
Acadia
BBW
HBEF Northeast Regional
Summary of studies from NE case study for acidification
Base cation
Elvir et al. (2006)
BAI
SanClements et al.
(2010)
Mineralization
Fernandez et al.
(2003)
Stream dissolved
S042",
pH, ANC,
Al+
Norton et al. (2004)
Base Cation, Ca, Mg
Norton et al. (2004)
Gbondo-Tuabawa
and Driscoll (2003),
Gbondo-Tuabawa
and Driscoll (2002)
Summary of studies from NE case study for nutrient status
Aquatic N cycling
Mineau et al. (2014),
Simon et al. (2010)
Soil N cycling
Mineau et al. (2014)
Jefts et al. (2004)
Ca addition
Battles et al. (2014)
February 2017 C-8 DRAFT: Do Not Cite or Quote
Because this case study addresses the condition of three discrete locations in the
Northeast (ACAD, HBEF, and BBW), we developed Table C-3 to summarize the
primary post-2000 research reported in the case study. In addition, we cite relevant
research in other areas of the northeastern region. Section C.1.2 presents information
about N and S deposition in the Northeast. Discussions of critical load or dose-response
research (Section C.1.3) are each organized around the three case study areas and the
Northeast Region. Section C.1.4 presents information available on long-term ecological
monitoring and Section C.1.5 contains information on the current status and forecasts for
recovery in the case study areas. Key research literature since January 2008 is highlighted
in Table C-4.
-------
Table C-3 (Continued): Literature cited by northeast U.S. case study area.
Variable
Acadia BBW
HBEF
Northeast Regional
N addition
Bethers et al. (2009)
Hunt et al. (2008)
N
retention + multiple
disturbances
Aber et al. (2002)
N retention
climate/freezing
Groffman et al.
(2011). Judd etal.
(2011). Campbell et
al. (2010)
N retention and fire
Nelson etal. (2007)
Campbell et al.
(2004b)
N dep effect on
wetlands
Calhoun etal. (1994)
N loading to coastal
waters
Nielsen and Kahl
(2007)
N addition to lakes
Saros (2014)
Summary of studies from NE case study for terrestrial critical load or dose-response
Dose-response
trees
Ellis et al. (2013) Elvir et al. (2006). Elvir
et al. (2003)
Pardo et al. (2011c).
Thomas et al. (2010),
McNultv et al. (2005)
Does-response
herbs
Pardo etal. (2011c)
Hurd etal. (1998)
Dose-response soil
SanClements et al.
(2010) Fernandez et
al. (2003)
Gbondo-Tuabawa
and Driscoll (2002)
Pardo etal. (2011c)
Dose-response
surface water
Gbondo-Tuabawa
and Driscoll (2002)
Modeling climate,
acid-base chemistry,
changes in plants
Phelan etal. (2016)
Phelan etal. (2016)
Campbell et al.
(2009)
Summary of studies from NE case study for aquatic critical load or dose-response
Macroinvertebrate
production
Chadwick and Hurvn
(2005)
Shift from deposition
to climate influence
Mitchell and Likens
(2011)
Flow volume and
peak flows
Kim etal. (2010)
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Table C-3 (Continued): Literature cited by northeast U.S. case study area.
Variable
Acadia
BBW
HBEF
Northeast Regional
NO3" concentration
Aber et al. (2003)
N limitation
Baron et al. (2011a)
NO3" leaching
Driscoll et al. (2003a)
DOC
SanClements et al.
(2012)
Climate effects on
pools,
concentrations, and
fluxes of major
elements
Pourmokhtarian et al.
(2012)
PH
Ouimet et al. (2006),
Dupont et al. (2005),
Ouimet et al. (2001)
ANC
Sutherland et al. (2015).
Nierzwicki-Bauer et al.
(2010), Tominaaa et al.
(2010), Ouimet et al.
(2006), Dupont et al.
(2005). Ouimet et al.
(2001)
Al+ = aluminum; ANC = acid neutralizing capacity; BAI = basal area increment; BBW = Bear Brook Watershed; Ca = calcium;
DOC = dissolved organic carbon; HBEF = Hubbard Brook Experimental Forest; Mg = magnesium; N = nitrogen;
NE = northeastern; N03" = nitrate; S042" = sulfate.
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Table C-4 Key recent research literature focused on the case study region.
Publication
Focus
Baron et al. (2011a)
Regional patterns in N limitation
Battles et al. (2014)
Ca addition at HBEF
Bethers et al. (2009)
Effects of S and N on sugar maple foliar chemistry
Campbell et al. (2009)
Influence of climate on biogeochemical cycling
Campbell et al. (2010)
Monitoring of climate conditions at HBEF
Cho et al. (2009)
Response of stream high-flow chemistry to Ca addition at HBEF
Ellis et al. (2013)
Empirical critical loads
Elviret al. (2010)
Tree growth and foliar chemistry at BBW
Fernandez and Norton (2010)
Overview of BBW study
Fernandez et al. (2010)
Responses to experimental acidification at BBW
Groffman et al. (2011)
Soil freezing at HBEF
Hunt et al. (2008)
N and P content of leaves
Judd et al. (2011)
Soil freezing at HBEF
Kim et al. (2010)
Stream flow at BBW
Laudon and Norton (2010)
Episodic stream chemistry at BBW
Lawrence et al. (2012)
Recovery of soil base status
Lona et al. (2009)
Sugar maple decline
Mineau et al. (2014)
Enzyme activity in soil and leaf litter
Mitchell and Likens (2011)
S budget at HBEF
Mitchell et al. (2011)
S mass balances for HBEF and BBW
BBW = Bear Brook Watershed; Ca = calcium; HBEF = Hubbard Brook Experimental Forest; N = nitrogen; P = phosphorus; S = sulfur.
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C.1.2.
Deposition
Characteristics of nitrogen and sulfur deposition affecting the ACAD, HBEF, and BBW
in the study area are shown in Figure C-4 and Figure C-5. Figure C-4A and Figure C-5A
show 3-year average total deposition of N and S for 2011-2013; Figure C-4B shows the
partitioning between oxidized and reduced N; Figure C-5 B shows the 25-year-long time
series for wet deposition for NOs . NH4+, SO42 and H+ obtained at the NADP/NTN
(National Atmospheric Deposition Program/National Trends Network) monitoring site at
HBEF (NH02). Surrounding areas in Maine and New Hampshire and inserts showing the
coterminous U.S. (CONUS) are shown to place the depositional environment in context.
Other maps showing the contributions of individual species to dry and/or wet deposition
are given in Appendix A.
Data shown in the map Figure C-4 and Figure C-5 A were obtained from the hybrid
modeling/data fusion product, TDEP (Total Deposition,
http://nadp.sws.uiuc.edu/committees/tdep/tdepmaps/ and described in Chapter 2.
Section 2.8). However, the time series of wet deposition is taken directly from data on the
NADP/NTN (Figure C-5B). This was done to track changes in deposition since the
passage of the Clean Air Act Amendment (CAAA) because the Community Multiscale
Air Quality (CMAQ) model simulations used in TDEP extend back only to 2000.
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I Kilometers
N Deposition (Kg-N/ha)
Kdometefs
O Monitor NH# 02
O Monitor ME #98
0 Monitor Locations
Northeast Study Area
National
Park
Bear
Brook
Acadia
Bear
Brook
Brook
-------
Bear
Brook
Acadia
National
Park
S Deposition (kg-S/ha)
Hubbard
Brook
Kitomelers
(J Monitor NH# 02
I \ O Monitor ME #98
9 Monitor Locations
Northeast Study Area
600
Annual Wet Deposition and 3-Year Moving Average at
Site NH02: 1990 - 2014
rl
L
soo
>-
.c
400
0
E
J00
c
0
in
200
O
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Comparison of Figure C-4A and Figure C-5A indicates that the general pattern of
deposition ofN and S is broadly similar; deposition tends to be higher near the coast and
decreases inland. Deposition at ACAD is an exception, with lower values along the coast
than found elsewhere. As seen in Figure C-4A. total deposition of N is relatively uniform
within the three portions of the study area. In addition, the area surrounding the three
sites shows a high degree of regional homogeneity but with higher values in New
Hampshire. Deposition of N is not as high as in many areas of the central U.S. or the rest
of the Northeast. Deposition of S is considerably lower than along the Ohio River Valley.
Figure C-4B shows that the deposition of nitrogen is estimated to be mostly in oxidized
form throughout the entire domain. Although most of the area is subject to N deposition
in oxidized form with highest percentages surrounding ACAD and BBW, there are areas,
principally in central Maine, where N is deposited mostly in reduced form. In Figure C-
5B, wet deposition of all species shows that downward trends in NO? . NH4. SO42 and
H+ are consistently found over the past 25 yr, although the rate of decrease was variable.
In general, wet deposition typically exceeds dry deposition of N and S in this case study
area.
C.1.3. Critical Loads and Other Dose-Response Relationships
C.1.3.1. Terrestrial Critical Loads and Dose-Response Relationships
This section presents post-2000 ACAD, HBEF, and BBW findings on the dose-response
relationships of N and S to terrestrial ecology, as well as the critical N and S loads for
maintaining ecosystem health. Additional relevant information for the northeastern region
is summarized. The section presents findings on both empirical research and modeling
analyses.
C.1.3.1.1. Empirical Studies
Post-2000 findings from empirical studies of terrestrial dose-response relationships and
critical loads are summarized in this section. Table C-5 summarizes the body of empirical
and modeling research identified.
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Table C-5 Terrestrial empirical and modeling research on the response of
nitrogen and sulfur deposition for the northeastern U.S.
Variable
Species
Response
Deposition/
Addition
(kg N/ha/yr)
Years
Site
Reference
Primary
productivity
NA
PnET-BGC
Model.
Predicted
increase due to
future longer
growing season
Not specified
1999-2099 HBEF Campbell et
al. (2009)
Base Cation NA PnET-BGC
Ca and Mg Model. Historical
depletion forest cutting
had little impact
on
exchangeable
cation soil pools
Not specified
1850-1995 HBEF Gbondo-
Tuabawa
and Driscoll
(2003)
Base cation
Sugar
maple,
American
beech, red
spruce
American beech
and red spruce
had lower foliar
Ca, Mg, Zn
concentrations;
nutrient
imbalance may
offset potential
photosynthesis
benefits
N addition: 8.4
(wet + dry)
(NH4)2SC>4 addition: WB
25.2
1989-2003 BBW Elvir et al.
(2006)
Sugar maple
higher
photosynthesis
rates no
decrease in Ca,
Mg, Zn
concentrations
Tree growth Northern + 8.4 N (wet + dry)/+25 1989-2002 BBW Pardo et al.
hardwoods (NH4)?SC>4 (2011c)
Mortality ND
Foliar %N +
Foliar %Ca 0
NOs" +
leaching
Cation loss +
Soil C:N 0
N +
mineralization
Nitrification _
Soil 0
respiration
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Table C-5 (Continued): Terrestrial empirical and modeling research on the
response of nitrogen and sulfur deposition for the
northeastern U.S.
Variable
Species
Response
Deposition/
Addition
(kg N/ha/yr)
Years
Site
Reference
Microbial
biomass
0
Tree growth
Red
0
8.4 N (wet + dry)/ +25 kg
¦ (NH4)2S04
1989-2002
BBW
Pardo et al.
(2011c)
Mortality
' spruce
ND
Foliar %N
+
Foliar %Ca
-
NOs"
leaching
+
Cation loss
+
Soil C:N
-
N
mineralization
+
Nitrification
+
Soil
respiration
ND
Microbial
biomass
ND
Base cation
Sugar
maple
Little evidence
of BC depletion
but confounded
by ice storm
litter
mineralization
8.4 N (wet + dry)/ + 25 kg
(NH4)2S04
Not
specified
BBW
SanClements
et al. (2010)
Mineralization
Not
specified
Storm caused
increased
litterfall,
accelerated
mineralization,
and obstructed
temporal trends
in soil chemistry
(17 yr)
8.4 (wet + dry)/ +25
(NH4)2S04
1989-1998
BBW
Fernandez et
al. (2003)
Soil base
saturation
Not
specified
ForSAFE-VEG
model.
Expected future
climate change
was simulated
to cause
increase,
especially at
BBW.
Not specified
Not
specified
BBW
and
HBEF
Phelan et al.
(2016)
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Table C-5 (Continued): Terrestrial empirical and modeling research on the
response of nitrogen and sulfur deposition for the
northeastern U.S.
Variable
Species
Response
Deposition/
Addition
(kg N/ha/yr)
Years
Site
Reference
Soil
acid-base
chemistry
Not
specified
ForSAFE-VEG
model. Climate
had a lesser
effect on
simulated at
HBEF, likely due
to the
overwhelming
influences of
high S and N
deposition.
Not specified
Not
specified
BBW
and
HBEF
Phelan et al.
(2016)
Plant
communities
and N
enrichment
Not
specified
ForSAFE-VEG
model. Climate
futures
predicted by the
IPCC of
increased
temperature and
precipitation will
change plant
communities
and N
enrichment,
counteracting
the acidifying
impacts of S
and N
deposition on
soil acid-base
chemistry.
Not specified
Not
specified
Phelan et al.
BBW
and (2016)
HBEF
NOs"
leaching
NA
PnET-BGC
Model. Increase
due to
enhanced net
mineralization
and nitrification
Not specified
1999-2099 NE
Campbell et
al. (2009)
Mineral
weathering
NA
PnET-BGC
Model. Slight
decrease due to
reduced
simulated soil
moisture
(negative effect)
and increased
temperature
(positive effect)
Not specified
1999-2099 NE
Campbell et
al. (2009)
BBW = Bear Brook Watershed; BC = base cation; C = carbon; Ca = calcium; ForSAFE-VEG = Soil Acidification in Forest
Ecosystems; ha = hectare; HBEF = Hubbard Brook Experimental Forest; IPCC = Intergovernmental Panel on Climate Change;
kg = kilogram; Mg = magnesium; N = nitrogen; NA = not applicable; ND = no data; NE = northeastern; (NH4)2S04 = ammonium
sulfate; N03" = nitrate; PnET-BGC = Photosynthesis and Evapotranspiration-Biogeochemical; S = sulfur; WB = West Bear Brook;
yr = year; Zn = zinc.
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C.1.3.1.1.1. Acadia National Park
Ellis et al. (2013) estimated the CL exceedance for nutrient-N deposition to protect the
most sensitive ecosystem receptors in 45 national parks, based on CL ranges compiled by
Pardo etal. (201 lc). Ellis et al. (2013) estimated the N CL for ACAD in the range of
3-8 kg N/ha/yr to protect hardwood forests and a similar range to protect lichens.
Pardo etal. (201 lc) estimated that ambient N deposition in parts of ACAD was higher
than estimated empirical CL values. Thus, these data suggest the possibility of
exceedance of nutrient-N CL in ACAD (see Table C-6).
Table C-6 Empirical critical loads for nitrogen in Acadia National Park, by
receptor, from Pardo et al. (2011c).
Critical Load (kg/ha/yr)
NPS
Unit
Ecoregion
N Deposition
(kg/ha/yr)
Mycorrhizal
Fungi Lichen
Herbaceous
Plant Forest
Nitrate
Leaching
Acadia
NP
Eastern Temperate
Forests
5.2
5 to 12 4 to 8
17.5 3 to 8
8
ha = hectare; kg = kilogram; N = nitrogen; NP = national park; NPS = National Park Service; yr = year.
Ambient N deposition reported by Pardo et al. (20110) is compared to the lowest critical load for a receptor to identify potential
exceedance. A critical load exceedance suggests that the receptor is at increased risk for harmful effects.
C.1.3.1.1.2. Hubbard Brook Experimental Forest
Gbondo-Tuabawa and Driscoll (2002) used the PnET-BGC model to simulate the
responses of soil and surface water chemistry at the reference watershed at HBEF to
future emissions controls. Model performance was assessed using the normalized mean
absolute error and the efficiency as objective statistical criteria. The focus was on
comparing simulated chemistry with observed values between 1980 and 1998. Results
showed good agreement for stream Ca and SOr . However, stream NOs and Al
concentrations and soil solution Ca:Al ratios were over-predicted after 1990. Simulation
results suggested that emissions controls required by the CAAA will likely not result in
substantial changes in the future in "critical indicators such as soil base saturation, soil
solution Ca:Al, or stream ANC and Al concentrations."
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C.1.3.1.1.3. Bear Brook Watershed
Elvir et al. (2006) investigated the effects of increased N deposition on photosynthesis
and foliar nutrient content of sugar maple, American beech, and red spruce at the BBW.
Trees in the treated WB watershed (an addition of 25 kg N/ha/yr as (NEL^SC^) had
higher foliar N concentrations than EB reference trees. American beech and red spruce
displayed significantly lower foliar concentrations of Ca, Mg, and Zn. Sugar maple did
not show decreases in these nutrients and was the only species to have significantly
higher photosynthetic rates in the treated watershed as compared with the reference. This
result suggested that nutrient imbalances in American beech and red spruce in the
treatment watershed may have offset any potential photosynthetic benefits to these
species from higher N availability (Elvir et al.. 2006).
During the first 7 years of treatment at WB, sugar maple basal area increment (BAI) was
higher in WB compared with EB. After 8 years of treatment, however, the initial higher
sugar maple growth rate in WB decreased (Elvir et al.. 2010).
In the WB catchments, the BAI of sugar maple was enhanced 13 to 104% by the addition
of 25 kg N/ha/yr as (NEL^SC^. The BAI of red spruce was not significantly affected
(Elvir et al.. 2003).
Fernandez et al. (2003) reported results of quantitative soil excavations in 1998 that
measured soil pools of exchangeable base cations after 9 years of treatment at WB. The
treated watershed had lower concentrations of exchangeable Ca and Mg in all soil
horizons, with greater nutrient cation depletion in the O-horizon as compared with the
mineral soil. Depletion was also greater in conifer, as opposed to hardwood, stands. The
importance of treatment-caused base cation depletion was reinforced by MAGIC model
simulations. Estimates of watershed-wide exchangeable Ca and Mg (66 and 27 kg/ha)
were roughly comparable to the total cumulative excess stream Ca and Mg export in WB
after 9 years of treatment (55 and 11 kg/ha, respectively; Figure C-6).
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DX
O
c.
*
<3
C u ni illative
East Bear
West Bear
Ca = calcium; ha = hectare; kg = kilogram; Mg = magnesium; yr = year.
Source: Fernandez et al. (2003).
Figure C-6 Annual stream calcium and magnesium export (paired bars), and
cumulative excess export in West Bear Brook compared to East
Bear Brook (line), over the study period 1989-2000 at the Bear
Brook Watershed experiment.
C.1.3.1.1.4. Other Northeast Regions
1 (Pardo et al.. 2011c) compiled data on empirical CLs for protecting sensitive resources in
2 Level I ecoregions across the CONUS against nutrient enrichment effects caused by
3 atmospheric N deposition. Available data on empirical CL of nutrient-N in the Northeast
4 suggested that the lower end of estimates of the CL for resource protection, 3 kg N/ha/yr
5 (Table C-7). Values at or above this level of deposition loading are considered to be
6 potentially problematic for mycorrhizal fungi, lichens, and forest vegetation. Keeping
7 levels below this value also helps prevent NGaT leaching into drainage water.
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Table C-7 Critical loads of nutrient nitrogen for the Northern Forests ecoregion.
Critical load or
Ecosystem N deposition
Component (kg/ha/yr) Reliability Response Comment Reference
Tree >3 # Decreased growth of None Thomas et al.
red pine, and decrease (2010)
survivorship of yellow
birch, scarlet and
chestnut oak, quaking
aspen, and basswood
Lichens
4 to 6
(#)
Community
composition shift
Application of model
developed for Marine
West Coast Forest to
Northern Forests
Geiser et al.
(2010)
Ectomychorrizal
fungi
5 to 7
#
Change in fungal
community structure
None
Lilleskov et al.
(2008)
Herbaceous
species cover
>7 and <21
#
Loss of prominent
species
Response observed in
low-level fertilization
experiment
Hurd et al.
(1998)
Northern
hardwood and
coniferous forest
8
##
Increased surface
water NO3" leaching
None
Aber et al.
(2003)
Tree growth and
mortality
>10 and <26
#
Decreased growth
and/or induced
mortality
Response observed in
low-level fertilization
experiment in
old-growth montane
red spruce
McNultv et al.
(2005)
Arbuscular
mycorrhizal fungi
<12
(#)
Biomass decline and
community
composition change
Observed along a
Michigan N gradient
Pardo et al.
(2011c)
ha = hectare; kg = kilogram; N = nitrogen; N03" = nitrate; yr = year.
Reliability rate: ## reliable; # fairly reliable; (#) expert judgment.
Source: Pardo et al. (20110).
1 Thomas et al. (2010) analyzed Forest Inventory Analysis (FIA) data in the Northeast to
2 determine tree growth in response to a gradient of atmospheric N deposition from about
3 3 to 11 kg N/ha/yr. Some tree species showed increased growth across the N input
4 gradient (yellow poplar [Liriodendron tulipifera], black cherry [Prunus serotina], and
5 white ash [Fraxinus Americana]). Some showed highest growth at intermediate levels of
6 N deposition (quaking aspen [Populus tremuloides] and scarlet oak [Quercus coccinea]).
7 Red pine (Pinus resinosa) exhibited growth decline across the gradient of increasing N
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deposition (Thomas et al.. 2010). Thus, it appeared that N deposition at ambient levels
can have both positive and negative effects on tree growth, depending on species and
deposition level.
In a high-elevation red spruce-balsam fir (Abies balsamea) forest in the Northeast, N
fertilization over 14 years led to a decrease in live basal area (LBA) with increasing N
additions. In control plots, LB A increased by 9% over the course of the study, while LB A
decreased by 18 and 40% in plots treated with 15.7 kg N/ha/yr and 31.4 kg N/ha/yr,
respectively (McNultv et al.. 2005).
There is little information available regarding the effects of N deposition on herbaceous
plants within northern hardwood forests in the Northeast. However, Hurd et al. (1998)
reported the results of experimental studies that added N at two and four times the
ambient N deposition level at several sites in the Adirondack Mountains. Herbaceous
plant coverage decreased after 3 years of fertilization, largely in response to shading
caused by enhanced growth of ferns. Additionally, information has been recently
published by Simkin et al. (2016) and is discussed in Section 6_2 of this ISA.
C.1.3.1.2. Modeling Studies
Evidence from research in northeastern forests indicates that direct and indirect effects of
climate change will cause changes in N and other biogeochemical cycling by altering
plant physiology, forest productivity, and soil processes. Campbell et al. (2009) reviewed
these relationships (Figure C-7) and applied the PnET-BGC model in a northern
hardwood forest ecosystem at HBEF to test assumptions about interactions regarding
climate change. Model results suggested an increase in primary productivity due to a
longer growing season in the future, an increase in NO;, leaching due to enhanced net
mineralization and nitrification, and a slight decrease in mineral weathering due to
reduced simulated soil moisture (negative effect) and increased temperature (positive
effect).
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Temperature, Precipitation,
and Extremu Weather Hvents
Indirect Effects
FSre
Insects-pathogens
Invasive species
A fores! composition
We! deposition
\
Dry deposition
/
Mi
Canopy
exchange
m
i
ThroughfaH
& stemllow
4
jf Litterfall Trace gases
• Uptake, ; •' , y V- ':
' Soil abiotic process ™ ™' ¦ Soil biotic processes
Ion exchange Redox reactions Decomposition
Adsorption-desorption Mineralization
Weathering Stream export Immobilization
Solute transport 1 Respiration
Feedbacks
Soil trace gas fluxes
Plant respiration
Deforestation
Transpiration
Evaporation
Albedo
Ecosystem Services
Water quality and quantity
Carbon sequestration
Economics (wood products,
tourism, maple sugar)
¦Recreation and aesthetics
NPP = net primary production.
Source: Campbell et al. (2009).
Figure C-7 Conceptual diagram showing the direct and indirect effects of
changes in temperature and precipitation on biogeochemical
processes in forests and on the services forests provide. Also
shown are feedbacks that further influence climatological effects.
C.1.3.2. Aquatic Critical Loads and Dose-Response Relationships
1 This section presents post-2000 research findings at ACAD, HBEF, and BBW on the
2 dose-response relationships of N and S to aquatic ecology, as well as the critical N and S
3 loads for maintaining ecosystem health. Additional relevant information for the Northeast
4 region is summarized. Both empirical and modeling studies of aquatic dose-response
5 relationships and critical loads are included in this section.
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C.1.3.2.1. Empirical Studies
1 Post-2000 findings from empirical studies of aquatic dose-response relationships and
2 critical loads are summarized in this section. Table C-8 compiles the body of empirical
3 research identified.
Table C-8 Aquatic empirical research on the response of nitrogen and sulfur
deposition for the northeastern U.S.
Variable
Response
Deposition
Addition
Years
Site
Reference
Fish
Shift in the upper
Not specified
0
1960S-2007
HBEF
Warren et al.
community
mainstem of HBEF
(2008)
including
from the presence of
brook trout
at least three fish
(Salvelinus
species to only brook
fori tin alis)
trout (Salvelinus
fontinalis)
S042
W6 had a 32%
Not specified
0
1963-1994
HBEF
Driscoll et al.
decline in the annual
(2001b)
volume-weighted
Likens et al. (2001)
concentration
(-1.1 [jeq/L/yr)
SO42" + NO3-
W6 had declines in
Not specified
0
1963-1994
HBEF
Driscoll et al.
stream
(2001b)
concentrations of
strong acids
(-1.9 [jeq/L/yr)
Sum of base
-1.6 [jeq/L/yr
Not specified
0
1963-1994
HBEF
Driscoll et al.
cations
(2001b)
PH
Small but significant
Not specified
0
1963-1994
HBEF
Driscoll et al.
increases In stream
(2001b)
pH, from 4.8 to 5.0
S042"
Biogeochemical
Not specified
0
1965-2008
HBEF
Mitchell and Likens
control of SO42"
(2011)
export from forested
watersheds has
shifted from
atmospheric S
deposition to climatic
factors that regulate
soil moisture.
pH and ANC Decrease Not specified 1,800 eq/ha/yr 7 yr BBW Norton et al. (2004)
(NH4)2S04 acidification
treatment
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Table C-8 (Continued): Aquatic empirical research on the response of nitrogen
and sulfur deposition for the northeastern U.S.
Variable
Response
Deposition
Addition
Years
Site
Reference
Stream
dissolved
S042"
Decreased
Not specified
1,800 eq/ha/yr
(NH4)2S04
1989-2007
BBW
Norton et al. (2004)
Fatemi etal. (2012)
Base cations
Decreased
Not specified
1,800 eq/ha/yr
(NH4)2S04
1989-2007
BBW
Norton et al. (2004)
Fatemi etal. (2012)
Al+
Increased
Not specified
1,800 eq/ha/yr
(NH4)2S04
1989-2007
BBW
Norton et al. (2004)
Fatemi etal. (2012)
ANC
Regional surface
water ANC did not
change significantly in
New England during
the 1990s
Not specified
0
NA
NE
U.S. EPA (2003)
Evans and
Monteith (2001)
Release of S
from internal
storage pools
to drainage
water
Increased
Not specified
0
1965-2008
General
Mitchell and Likens
(2011)
Al+ = aluminum; ANC = acid neutralizing capacity; BBW = Bear Brook Watershed; ha = hectare; HBEF = Hubbard Brook
Experimental Forest; kg = kilogram; L = liter; |jeq = microequivalents; eq = equivalents; NE = northeastern;
(NH4)2S04 = ammonium sulfate; N03" = nitrate; S = sulfur; S042" = sulfate; W6 = Watershed 6; yr = year.
C.1.3.2.1.1. Acadia National Park
No empirical aquatic critical loads or dose-response studies have been identified in the
literature for the ACAD case study area since 2000.
C.1.3.2.1.2. Hubbard Brook Experimental Forest
The cycling of N, S, and other elements in the Northeast is closely linked with aspects of
climate. Many recent studies have explored some of those linkages, and many of the
empirical studies of aquatic dose-response relationships have included aspects of climate
change. The potential for a shift from atmospheric deposition to climatic regulation of
watershed S biogeochemistry at HBEF was examined by Mitchell and Likens (2011).
More than four decades of continuous long-term data collected from four watersheds
were used to evaluate S budgets. "Analyses focused on the role of changing water
availability in affecting the amount of S mobilized from internal watershed sources and
the resultant changes in the S budget discrepancies over time.... The biogeochemical
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controls on annual SO42 export in stream water [appear to have] shifted from
atmospheric S deposition to climatic factors that affect soil moisture."
With declining inputs of atmospheric S, the higher outputs of SO42 in drainage waters
relative to precipitation inputs appear to be driven by the S stored in the soil. These
biogeochemical responses at the HBEF might be amplified with further climate change,
resulting in greater annual stream discharge and watershed wetness. Such climatic change
will potentially increase SO42 mobilization and hence may slow the recovery of both
aquatic and terrestrial ecosystems from acidification.
C.1.3.2.1.3. Bear Brook Watershed
Chadwick and Hurvn (2005) assessed effects of N additions on secondary stream
macroinvertebrate production in BBW. Production did not vary between streams
(reference and treatment) but was 35% higher for both streams in the second year of the
study. Results suggested that patterns of litter input and channel drying, rather than N
input, controlled secondary production in these intermittent streams by altering resource
availability and invertebrate community structure. It appeared that these variables
overrode the effects of N supply, perhaps because N is not limiting.
Ongoing climate change will likely affect a wide range of biogeochemical processes in
northeastern forested ecosystems. Of particular interest are the effects on flow volumes
and peak flows. Kim et al. (2010) analyzed a nearly two-decades-long stream flow record
at EB and a longer record for the Narraguagus River (a proximate watershed to the
BBW). The focus was on improving understanding of high flow events that have a
disproportionate impact on biogeochemical processes and fluxes. A moving window
analysis to evaluate the changing flood potential over time suggested upward trends in
the occurrence of high flow events during recent decades.
C.1.3.2.1.4. Other Northeastern Regions
Considering trends across the Northeast, Aber et al. (2003) found that surface water NO3
concentrations exceeded 1 (j,eq/L mainly in northeastern watersheds receiving more than
about 9 to 13 kg N/ha/yr deposition. Above this range, mean NO3 export increased
linearly with increasing deposition at a rate of about 0.85 kg NO3 "N/ha/yr for every
1 kg N/ha/yr increase in deposition, although at higher rates of deposition there was
considerable variability in N retention among watersheds (Aber et al.. 2003).
N limitation across the Northeast was evaluated by Baron etal. (2011a) who estimated
that 34% of 4,361 New England lakes represented in the Eastern Lakes Survey were
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likely to be N limited, based on having dissolved inorganic N (DIN):total P (TP) ratio (by
weight) less than 4. Although eutrophication is a concern, there is no published evidence
that eutrophication is occurring to any appreciable extent in the lakes in ACAD.
Dissolved organic matter (DOM) is important to a range of processes critical to aquatic
ecosystem functioning, including providing a microbial food source, attenuating light,
buffering pH, binding metals, and controlling the cycling of C, N, Hg, and P. Shifts in the
quality of DOM may affect aquatic ecosystem functioning. A chemical signature of
terrestrial DOM was used by SanClements et al. (2012) to support the hypothesis that
increased dissolved organic carbon (DOC) concentrations in surface water in the
Northeast since about 1993 have been driven mainly by decreasing acidic deposition and
increasing solubility of soil organic matter. Fluorescence spectroscopy was used to
characterize the quality of DOM of archived samples from nine acid-sensitive lakes in
Maine. Decadal decreases in SO42 in lake water were correlated with increased DOC
concentrations and a shift from microbial to terrestrially derived DOM during ecosystem
recovery from prior acidification.
Aquatic biota in the Northeast have been affected by acidification at virtually all levels of
the food web. Some species and some lifestages are especially sensitive. Decreases in
ANC and pH and increases in inorganic Al concentration contributed to declines in
species richness and abundance of zooplankton, macroinvertebrates, and fish as
documented in the Adirondacks (Sutherland et al.. 2015; Nierzwicki-Bauer et al.. 2010;
Keller and Gunn. 1995; Schindler et al.. 1985). Although some species are favored by
increased acidity, the overall species richness typically decreases as surface water acidity
increases.
C. 1.3.2.2. Modeling Studies
Post-2000 findings from modeling studies of aquatic dose-response relationships and
critical loads are summarized in this section. Table C-9 compiles the body of research
identified.
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Table C-9 Critical and target load and exceedance modeling studies in the
northeastern U.S.
Reference
Location
Model
Focus
Dupont et al. (2005)
NE region
SSWC
CLs for acidity to protect aquatic biota to
pH 6.0
SanClements et al. (2010)
BBW
PnET-BGC
Interactions between climate change
parameters and atmospheric deposition
Phelan etal. (2016)
BBW and HBEF
ForSAFE-VEG
Atmospheric deposition to northern
hardwood forests
Tominaaa et al. (2010)
HBEF
MAGIC, PnET-BGC,
SAFE, VSD
Model output comparison
Pourmokhtarian etal. (2012)
HBEF
PnET-BGC
N cycling and climate change
BBW = Bear Brook Watershed; CL = critical load; ForSAFE-VEG = Soil Acidification in Forest Ecosystems; HBEF = Hubbard
Brook Experimental Forest; MAGIC = Model of Acidification and Groundwater in Catchments; N = nitrogen; NE = northeastern;
PnET-BGC = Photosynthesis and Evapotranspiration-Biogeochemical; SAFE = Soil Acidification in Forest Ecosystems;
SSWC = Steady State Water Chemistry; VSD = Very Simple Dynamic.
C. 1.3.2.2.1. Acadia National Park
No modeling studies on aquatic critical loads for ACAD have been identified in the
literature.
C.1.3.2.2.2. Hubbard Brook Experimental Forest
Tominaga et al. (2010) evaluated the performance and prediction uncertainty of four
dynamic process-based watershed acidification models: MAGIC, PnET-BGC, SAFE, and
VSD. Model output was assessed by systematically applying each of the models to data
from the HBEF. The models were used to assess future soil and stream chemistry
response to reduced levels of atmospheric S deposition. Both hindcast and forecast
predictions were qualitatively similar across the four models. Nevertheless, the temporal
patterns of projected stream ANC and soil base saturation differed. Tominaga et al.
(2010) concluded that these differences can be accommodated by employing multiple
models. Nevertheless, these results have implications for individual model applications.
Pourmokhtarian et al. (2012) used "the PnET-BGC model to evaluate the effects of
potential future changes in temperature, precipitation, solar radiation, and atmospheric
CO2 on the pools, concentrations, and fluxes of major elements at the HBEF." The
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climate projections were based on downscaled climate output from atmospheric-ocean
general circulation models. These climate projections indicated that the average air
temperature will likely increase at the HBEF site by 1.7° to 6.5°C over the 21st century,
with simultaneous increase in annual average precipitation ranging from 4 to 32 cm
above the long-term mean. The PnET-BGC model simulations under expected future
climate showed shifts in hydrology from later snowpack development, earlier snowmelt,
increased evapotranspiration, and a slight increase in the annual water yield. The model
results suggested that net soil N mineralization and nitrification will markedly increase
under elevated temperature. This increase resulted in simulated acidification of soil and
stream water, altering the quality of water draining from the forested watershed.
C.1.3.2.2.3. Bear Brook Watershed
No aquatic critical loads modeling studies have been identified for BBW in the literature
since 2000.
C.1.3.2.2.4. Other Northeastern Region
Studies in the Northeastern region have used a variety of steady-state and dynamic
modeling approaches. The Conference of the New England Governors and Eastern
Canadian Premiers (NEG/ECP) sponsored a modeling assessment of steady-state CLs for
protection of forest soils and lakes against acidification in the Northeast region and in
eastern Canada (Ouimet et al.. 2006; Dupont et al.. 2005; Qui met et al.. 2001). Dupont et
al. (2005) reported the SSWC steady-state aquatic CLs of acidity and associated
exceedances for lakes. Atmospheric acid loads were assessed based on atmospheric
deposition of both S and N, using a critical limit of pH 6 to protect aquatic biota. This pH
level approximately corresponds with ANC = 40 (.icq/L in this region (Small and Sutton.
1986). Estimated S critical loads were exceeded in 2002 for 12.3% of all studied lakes.
Lakes having lowest calculated CLs included many in southern Vermont, eastern and
northern Maine, northern New Hampshire, and Cape Cod. Exceedances of CLs, based on
estimated acidic deposition in 2002, were highest in central and coastal Massachusetts,
southern Vermont, much of Maine, and portions of New Hampshire. Eastern Maine and
southern Vermont were notable "hot spots" where ambient S + N deposition exceeded
CLs by more than 10 meq/m2/yr (Dupont et al.. 2005).
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C. 1.3.3. Integration
1 Table C-10 contains a list of northeastern U.S. critical load determinations by multiple
2 researchers, ranging from 3-8 kg N/ha/yr (forests) to 17.5 kg N/ha/yr (herbaceous
3 plants).
Table C-10 Empirical and modeled nitrogen critical loads applicable to the
northeastern U.S.
Critical Load
(kg N/ha/yr)
Ecosystem
Component
Response
N Deposition
(kg/ha/yr)
Site
Reference
5 to 12
Eastern
temperate
forest
Mycorrhizal
Fungi
5.2
ACAD
Pardo et al.
(2011c)
4 to 8
Lichens
Epiphytic lichen community
change
5.2
ACAD
Pardo et al.
(2011c)
17.5
Herbaceous
Species
Increases in nitrophilic species,
declines in species-richness
5.2
ACAD
Pardo et al.
(2011c)
3 to 8
Hardwood
forest
Not specified
5.2
ACAD
Pardo et al.
(2011c)
Ellis et al. (2013)
8
Eastern
hardwood
forests
Increased surface water NO3"
leaching
5.2
ACAD
Pardo et al.
(2011c)
Ellis et al. (2013)
ANC crucial
concentration
= 20 |jeq/L
Not specified
Current legislated emissions
(= 13% reduction of SO42" by
2015) results in limited response
recovery
Not specified
HBEF
Tominaaa et al.
(2010)
Soil base
saturation
critical level of
10%
Maximum feasible technology
reductions (= 78% reduction of
SO42" by 2015) results in a more
rapid and greater extent of
chemical recovery
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Table C-10 (Continued): Empirical and modeled nitrogen critical loads applicable
to the northeastern U.S.
Critical Load
Ecosystem
N Deposition
(kg N/ha/yr)
Component
Response
(kg/ha/yr) Site
Reference
CO2
Not specified
N cycling and climate change.
Not specified HBEF
Pourmokhtarian
fertilization
"Under elevated temperature, net
(year
etal. (2012)
plateau of
soil N mineralization and
2070-2100)
600 ppm
nitrification markedly increase,
resulting in acidification of soil and
stream water.... Invoking CO2
fertilization effect on vegetation
under climate change
substantially mitigates watershed
N loss....Showed recovery of up
to 1 pH unit (assuming pH of 6.0
as steady state value) and...ANC
of 6.9 to 15.5 peq/L in comparison
to -3.4 peq/L mean annual
measured values (1988-2000)."
Not specified
Eastern
Interactions among climate
Not specified BBW
SanClements et
temperate
change parameters and
al. (2010)
forest
atmospheric deposition
Not specified
Eastern
Atmospheric deposition to
Not specified BBW and
Phelan et al.
temperate
northern hardwood forests
HBEF
(2016)
forest
Not specified
NE
Surface water NO3"
9 to 13 NE
Aber et al. (2003)
watersheds
concentrations exceeded 1 peq/L
and mean NO3" export increased
linearly with increasing deposition
<20 kg/ha/yr
Aquatic biota
Protect aquatic biota to pH 6.0
Not specified NE
Dupont et al.
S + N (= 9.6 kg
(2005)
SOVha/yr)
ACAD = Acadia National Park; ANC = acid neutralizing capacity; BBW = Bear Brook Watershed; C02 = carbon dioxide;
ha = hectare; HBEF = Hubbard Brook Experimental Forest; kg = kilogram; L = liter; |jeq = microequivalents; N = nitrogen;
NE = northeastern; N03" = nitrate; ppm = parts per million; S = sulfur; S04 = sulfate; yr = year.
C.1.4. Long-Term Ecological Monitoring
1 This section summarizes research on the long-term effects of S and N deposition in the
2 case study areas. The focus is primarily on research published since about the year 2000.
3 The acidification and nutrient enrichment subsections are each organized by three case
4 study areas followed by relevant information for the overall Northeast region. Key
5 publications are summarized in Table C-ll.
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Table C-11 Summary table of observed terrestrial and aquatic acidification
long-term trends in Hubbard Brook Experimental Forest and Bear
Brook Watershed.
Variable
Species
Response
Deposition
(kg/ha/yr)
Addition
(kg/ha/yr)
Site
Reference
C:N
NA
Significant increase over
25 yr
Not
specified
Not
specified
HBEF
Campbell et al.
(2007)
Biomass
Sugar
maple
Decrease
Not
specified
Not
specified
HBEF
Campbell et al.
(2007)
Al+
NA
Decrease
Not
specified
Not
specified
HBEF
Campbell et al.
(2007)
Base cation
Ca and Mg
depletion
NA
Historical forest cutting had
little impact on
exchangeable cation soil
pools"
Not
specified
Not
specified
HBEF
Gbondo-
Tuabawa and
Driscoll (2003)
SO42
NA
Watershed 6, had a 32%
decline in the annual
volume-weighted
concentration
(-1.1 [jeq/L/yr)
Not
specified
Not
specified
HBEF
1963-1994
Driscoll et al.
(2001b)
Likens et al.
(2001)
S042" + NO3-;
NA
Declines in stream
concentrations of strong
acids
(-1.9 [jeq/L/yr)
Not
specified
Not
specified
HBEF
1963-1994
Driscoll et al.
(2001b)
Sum of base
cations
NA
-1.6 [jeq/L/yr
Not
specified
Not
specified
HBEF
1963-1994
Driscoll et al.
(2001b)
PH
NA
Small but significant
increases in stream pH,
from 4.8 to 5.0
Not
specified
Not
specified
HBEF
1963-1994
Driscoll et al.
(2001b)
Fish
Slimy
Shift in the upper mainstem
Not
Not
HBEF
Warren et al.
community
sculpin
of Hubbard Brook from the
specified
specified
(1960S-2007)
(2008)
(Cottus
presence of at least three
cognatus),
fish species (slimy sculpin
blacknose
[Cottus cognatus],
dace
blacknose dace
(Rhinichthys
[Rhinichthys atratulus], and
atratulus),
brook trout [Salvelinus
and brook
fontinalis]) to only brook
trout
trout
(Salvelinus
fori tin alis)
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Table C-11 (Continued): Summary table of observed terrestrial and aquatic
acidification long term trends in Hubbard Brook
Experimental Forest and Bear Brook Watershed.
Deposition
Addition
Variable Species
Response
(kg/ha/yr)
(kg/ha/yr) Site
Reference
Base cation Sugar
American beech and red
8.4 N
WB BBW
Elvir et al.
maple
spruce lower foliar Ca, Mg,
(wet + dry)
25.2 kg
(2006)
American
Zn concentrations, nutrient
N/ha/yr
beech red
imbalance may offset
(NH4)2S04
spruce
potential photosynthesis
WB
benefits
28.8 S
Sugar maple higher
photosynthesis rates/ no
decrease in Ca, Mg, Zn
concentrations
Base cation
Sugar
maple
American
beech red
spruce
Little evidence of BC
depletion but confounded
by ice storm litter
mineralization
18.5 (1980) WB
4.74(2010) 25.2 kg
Wet S042"
2.8
Inorganic N
BBW
(NH4)2S04
WB
28.8 S
SanClements
etal. (2010)
Mineralization Sugar Storm caused increased
maple litterfall accelerated
American mineralization obstructing
beech red temporal trends in soil
spruce chemistry (17 yr)
Not
specified
WB
25.2 kg
N/ha/yr
(NH4)2S04
WB
28.8 S
BBW
Fernandez et
al. (2003)
pH and ANC NA
Decrease
Not
specified
WB
25.2 kg
N/ha/yr
(NH4)2S04
WB
28.8 S
BBW
Norton et al.
(2004)
Stream
dissolved
S042"
NA
Decrease
Not
specified
WB
25.2 kg
N/ha/yr
(NH4)2S04
WB
28.8 S
BBW
Norton et al.
(2004)
Fatemi et al.
(2012)
Base cation NA Increased BC export. Not
export in Export rated declined after specified
runoff 7 yr treatment.
WB
25.2 kg
N/ha/yr
(NH4)2S04
WB
28.8 S
BBW
Norton et al.
(2004)
Fatemi et al.
(2012)
Al+
NA
Increase
Not
specified
WB
25.2 kg
N/ha/yr
(NH4)2S04
WB
28.8 S
BBW
Norton et al.
(2004)
Fatemi et al.
(2012)
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10
11
Table C-11 (Continued): Summary table of observed terrestrial and aquatic
acidification long term trends in Hubbard Brook
Experimental Forest and Bear Brook Watershed.
Variable
Species
Deposition Addition
Response (kg/ha/yr) (kg/ha/yr)
Site
Reference
Release of S
from internal
storage pools
to drainage
water
NA
Increased
Not specific 0
General
(1972-2008)
Mitchell and
Likens (2011)
SO42" NA Biogeochemical control of
SO42" export from forested
watersheds in HBEF has
shifted from atmospheric S
deposition to climatic
factors that regulate soil
moisture.
Not specific 0
General
Mitchell and
Likens (2011)
Critical loads Varied
Varied
Not Not NE
specified specified
Pardo et al.
(2011c)
ANC
NA Regional surface water
ANC did not change
significantly in New
England during the decade
of the 1990s
Not
specified
0
NE
U.S. EPA
(2003)
Al+ = aluminum; ANC = acid neutralizing capacity; BC = base cation; BBW = Bear Brook Watershed; C = carbon; Ca = calcium;
ha = hectare; HBEF = Hubbard Brook Experimental Forest; kg = kilogram; L = liter; |jeq = microequivalents; Mg = magnesium;
N = nitrogen; NA = not applicable; NE = northeastern; (NH4)2S04 = ammonium sulfate; N03" = nitrate; S = sulfur; S042" = sulfate;
W6 = Watershed 6; WB = West Bear Brook; yr = year; Zn = zinc.
Acadia National Park is not a federally funded long-term monitoring study area.
C.1.4.1. Long-Term Monitoring of Acidification
Acidic deposition has been shown to be an important factor causing decreases throughout
much of the Northeast region in concentrations of exchangeable base cations in soils,
which were naturally low historically. Base saturation values less than 12% predominate
in the B-horizon in portions of the region where soil and surface water acidification from
acidic deposition have been most pronounced (Sullivan et al.. 2006a; Bailey et al.. 2004;
David and Lawrence. 1996).
Mitchell et al. (2011) evaluated S mass balances for 15 watersheds in the northeastern
U.S. and southeastern Canada, including watersheds at HBEF, BBW, and Cone Pond in
New Hampshire, for the period 1985 to 2002. Most study watersheds showed evidence of
internal watershed sources of SO42 . likely from mineralization of organic S stored from
decades of high S deposition. Mobilization of the mineralized S contributed an estimated
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1-6 kg S/ha/yr to the stream fluxes of SO42 . This has affected the observed rates of
recovery from acidification as S deposition has declined.
Surface water chemistry in the Northeastern U.S. has been characterized, surveyed,
resurveyed, and monitored in many studies conducted over the last several decades
(Table C-12).
Table C-12 Example surface water acidification chemistry studies in the
northeast case study region.
Time
Focus
Results
Deposition
Addition
Period
Site
Reference
N export
Unburned study watershed
Not
Not applicable
Pre- vs.
ACAD
Nelson et
exported 10 to 20 times more
specified
post-1947
al. (2007)
inorganic N than the burned
fire
watershed plus retention of
inorganic N was 96% in the
burned watershed vs. 72% in
the unburned watershed.
N export
Total N + P exported by
Not
Not applicable
Not
ACAD
Nelson et
watersheds entirely within
specified
specified
al. (2007)
ACAD were significantly lower
than exports in watersheds that
were partly or completely
outside the park.
Reference
Decline in stream SO42"
Not
Not specified
1963-1994
HBEF
Driscoll et
stream
(-1.1 [jeq/L/yr)
specified
al. (2001b)
chemistry
Decline in SO42" + NO3" in
stream (-1.9 peq/L/yr)
S budget
Biogeochemical control of
Not
Not specified
1965-2008
HBEF
Mitchell
SO42" export has switched
specified
and Likens
from atmospheric deposition to
(2011)
climate factors that regulate
soil moisture.
Stream
Stream dissolved SO42",
Not
1,800 eq/ha/yr
1987-2000
BBW
Norton et
trends for
pH, and ANC decrease
specified
(NH4)2S04
al. (2004)
reference
Base cation and Al+ increase
and
treatment
catchments
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Table C-12 (Continued): Example surface water acidification chemistry studies in
the northeast case study region.
Time
Focus Results Deposition Addition Period Site Reference
Low flow Base cation, NH4+and CI" Not 1,800 eq/ha/yr 1987-2006 BBW Navratil et
and high unchanged specified (NhU^SCM al. (2010)
flow stream
chemistry
of reference
and
treatment
catchments
Chronic
stream
chemistry
for
reference
and
treatment
catchments
Increased BC export; declined Not
after 7 yr treatment. specified
Decrease pH and alkalinity
Increased dissolved Al+, NO3",
SO42"
1,800 eq/ha/yr 1987-2007 BBW Norton et
(NH4)2S04 aL (201°)
Episodic "18 yr of N and S addition have
stream not affected the natural drivers
chemistry of episodic acidification. The
for contribution of SO42" to the
reference ANC decline in WB has been
and increasing linearly since the
treatment beginning of watershed
catchments treatment while the role of
NO3" has remained relatively
constant after an initial
increase."
Not 1,800 eq/ha/yr 1988-2006 BBW
specified (NH4)2S04
Laudon and
Norton
(2010)
Lake Ubiquitous decreases in the Not Not specified 1986 and NE region Warbv et
resurvey concentration of inorganic Al specified 1998 al. (2009)
across the region.
Organic monomeric Al also
declined region-wide in New
England.
In 2001, only 7 study lakes
(representing 130 lakes in the
Northeast region) that had AN
above the toxic threshold of
2 |jM, compared with
20 sampled lakes (representing
449 lakes in the population) in
1986.
Chronic
and
episodic
lake and
stream
chemistry
Rates of change for individual Not
water bodies ranged from specified
about -1.5 to -3 peq/L/yr.
Not specified 1990-2000 NE and
U.S. EPA
Appalachian (2003)
Mtns.
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4
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6
7
8
9
10
11
12
Table C-12 (Continued): Example surface water acidification chemistry studies in
the northeast case study region.
Time
Focus Results Deposition Addition Period Site Reference
Regional NO3" concentrations in New Not Not specified 2000-2010 New Strock et al
lake trends England and the Adirondack specified England and (2014)
Mountains, which had no trend Adirondacks
prior to 2000, declined at a rate
of -0.05 [jeq/L/yr
Response Oa-horizon BS decreased from Not
to 56.2 to 33.0% and almost specified
deposition equivalent changes in carbon
reduction l-normalized exchangeable Ca
and exchangeable Al
Not specified
1984 to
2001
NE region
Warbv et
al. (2009)
Suggested a nascent recovery Not Not specified 1992-1993 General Lawrence
of soil acid-base chemistry at specified vs. et al.
some locations in the 2003-2004 (2012)
Northeast where six red spruce
stands sampled.
Exchangeable Al in the
Oa-horizons decreased
(p < 0.05) by 20 to 40% at all
New England sites.
Evidence of base cation
depletion and decreased Ca:AI
ratio
ACAD = Acadia National Park; Al = aluminum; ANC = acid neutralizing capacity; BBW = Bear Brook Watershed; BC = base cation;
BS = base saturation; Ca = calcium; CI" = chloride; ha = hectare; HBEF = Hubbard Brook Experimental Forest; kg = kilogram;
L = liter; |jeq = microequivalents; |jM = micromole; N = nitrogen; NE = northeastern; NH4+ = ammonium; (NH4)2S04 = ammonium
sulfate; N03" = nitrate; Oa = well decomposed humus; P = phosphorus; S = sulfur; S042" = sulfate; WB = West Bear Brook;
yr = year.
These studies have focused on both chronic and episodic responses of reference and (in
the case of BBW and HBEF) experimentally treated catchments.
The U.S. EPA's Long-Term Monitoring (LTM) Program has been collecting monitoring
data since the early 1980s for many lakes and streams in acid-sensitive areas of the U.S.,
including within the Northeast region. These data allow evaluation of trends and
variability in key components of lake and stream water chemistry prior to, during, and
subsequent to 1990 CAAA Title IV implementation. Throughout the Northeast region,
the concentration of SO42 in surface waters has decreased substantially, often by
one-third to one-half, subsequent to the 1990 CAAA. These declines in lake and stream
S042 concentrations were considered consistent with observed declines in S wet
deposition and were corroborated by other studies that showed that SO42 concentrations
in northeastern lakes have decreased steadily since about the late 1970s [e.g., Driscoll et
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al. (1995). U.S. EPA (2003)1. Regional surface water ANC did not change significantly
in New England during the 1990s (U.S. EPA. 2003).
The impact of the 1990 CAAA relevant to aluminum releases to surface waters was
assessed by Warbv et al. (2008) who surveyed 113 lakes in the Northeast that were
sampled in 1986 and again in 2001. They "found ubiquitous decreases in the
concentration of inorganic Al across the region." In 2001, there were only 7 study lakes
(representing 130 lakes in the Northeast region) that had inorganic Al above the toxic
threshold of 2 (j,M, compared with 20 sampled lakes (representing 449 lakes in the
population) in 1986.
St rock et al. (2014) analyzed recent trends in wet deposition and lake chemistry using
long-term monitoring data for lakes in New England and the Adirondack Mountains.
From 2000 to 2010, lake NO, concentrations decreased at a rate of-0.05 (j,eq/L/yr (no
trend before 2000). There was a shift to nontoxic organic Al. Both ANC and pH
exhibited variable trends.
Table C-13 complies the effects of N deposition on watershed nutrient in the three case
studies and relevant Northeastern regional studies.
Table C-13 Summary of observed terrestrial and aquatic nutrient enrichment
long-term responses in Acadia National Park, Hubbard Brook
Experimental Forest, Bear Brook Watershed, and other northeastern
regions.
C.1.4.2. Long-Term Monitoring of Nitrogen Enrichment
Variable
Species
Response
Deposition Addition
(kg/ha/yr) (kg/ha/yr) Site Reference
N export
Not specified Unburned study Wet
Wet
Not ACAD Nelson et
specified (pre_ vs al. (2007)
post-1947
watershed exported 10 to deposition
20 times more inorganic only (value
N than the burned not specified)
watershed.
fire)
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Table C-13 (Continued): Summary of observed terrestrial and aquatic nutrient
enrichment long-term responses in Acadia National Park,
Hubbard Brook Experimental Forest, Bear Brook
Watershed, and other northeastern regions.
Deposition
Addition
Variable
Species
Response
(kg/ha/yr)
(kg/ha/yr) Site
Reference
N mass balance
Sugar maple,
Stream water export
~7 N
0 HBEF
Yanai et
American
decrease from 4 to
al. (2013)
Beech,
1 kg N/ha/yr
yellow birch
Shift to a net N sink
storing ~8 kg N/ha/yr.
unclear whether N is
accumulating or being
lost through
denitrification.
DIN loss
Sugar maple,
In W6, "losses were
"0.13 g/m2/yr
0 HBEF
Aber et al.
American
elevated in 1960s by a
is 20% of
(2002)
Beech,
combination of recovery
wet + dry
yellow birch
from extreme drought and
deposition"
a significant defoliation
event. N deposition
alone, in the absence of
other disturbances would
have increased DIN
losses by 0.35 g N/m2/yr."
Biogeochemical Sugar maple, Modeled soil freeze-thaw Not specified 0 HBEF Campbell
process American to year 2100. "Shortened et al.
Beech, frost covered period has (2010)
yellow birch biogeochemical process
implications."
Biogeochemical Sugar maple, "A relatively mild freezing Not specified 0 HBEF Groffman
process American event induced significant et al.
Beech, increases in N (2011)
yellow birch mineralization and
nitrification rates, solute
leaching, and soil N2O
production and caused
significant decreases in
soil methane uptake. Soil
freezing events may be
major regulators of soil
biogeochemical
processes and solute
delivery to streams in
forested watersheds."
NO3 export in
Sugar maple,
NO3" retention greater
~6 kg N 0
HBEF
Judd et al.
2006
American
than expected. "Changes
(1999-2008)
(2011)
Beech,
over last 5 decades have
yellow birch
reduced impacts of frost
events on watershed
NO3" export."
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Table C-13 (Continued): Summary of observed terrestrial and aquatic nutrient
enrichment long-term responses in Acadia National Park,
Hubbard Brook Experimental Forest, Bear Brook
Watershed, and other northeastern regions.
Deposition Addition
Variable Species Response (kg/ha/yr) (kg/ha/yr) Site Reference
NPP and Sugar maple, Ca nutrition promoted Not specified 0 HBEF Battles et
photosynthetic American higher above-ground (15-yr study) al- (2014)
surface area Beech, NPP and increased
yellow birch photosynthetic surface
area
Nitrification Showed greatest 8.4 N WB 25.2 kg BBW Jefts et al.
response to N treatments (wet + dry) N/ha/yr (2004)
(NH4)2S04
WB 28.8 S
(3-1,4
glucosidase
(3-1,4-N-
acetylglucos-
aminidase
Sugar maple, "Greatest leaf N + P
American
beech, Red
spruce
Not specified 25.2 N
BBW
contents can increase
short-term
decomposition,
accelerate production of
more humic-like water
extractable organic
matter and thereby
potentially influence the
distribution of organic
matter within the soil C
pool."
since 1989
Hunt et al.
(2008)
Mineau et
al. (2014)
Not affected by long-term
N enrichment in aquatic
and terrestrial habitats
WB vs. EB Not specified Little difference found
streams: Leaf
breakdown
Not specified Not BBW Simon et
specified al. (2010)
WB vs. EB Not specified "Virtually identical"
streams:
Invertebrate
production
Not specified Not BBW Simon et
specified al. (2010)
WB vs. EB NA N uptake responsive
streams:
Nutrient uptake
Not specified Not BBW Simon et
specified al. (2010)
Base cation
Sugar maple, American beech and red 8.4 N
American spruce lower foliar Ca,
beech, red Mg, Zn concentrations,
spruce nutrient imbalance may
offset potential
photosynthesis benefits
(wet + dry)
WB 25.2 kg
N/ha/yr
(NH4)2S04
WB 28.8 S
BBW
Elvir et al.
(2006)
Sugar maple higher
photosynthesis rates; no
decrease in Ca, Mg, Zn
concentrations
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Table C-13 (Continued): Summary of observed terrestrial and aquatic nutrient
enrichment long-term responses in Acadia National Park,
Hubbard Brook Experimental Forest, Bear Brook
Watershed, and other northeastern regions.
Variable Species Response
Watershed N Varied Varies widely. Not directly
retention related to N loading.
Deposition Addition
(kg/ha/yr) (kg/ha/yr) Site Reference
Wet 0 Mid-Atlantic Campbell
deposition 1.8 and NE et al.
to 5.5 NOs" forests (2004b)
0.9 to
2.4 NH4+
Net nitrification Picea rubens Picea rubens density
influences net nitrification
Not specified 0
NE: Ranch
Brook
Watershed,
Vermont
Ross and
Wemple
(2011)
BAI
Sugar maple,
black cherry
Varied species with acid
deposition impact on soil
nutrient status
Not specified Not
specified
NE (7 sites) Long et al.
(1937-1996) (2009)
Maple responds (growth)
to lime (Ca) addition
SOC response Hardwood Increased cumulative O-, 0.9 g N/m2/yr 5 to 15 g NE: Tonitto et
red pine A"> and B-horizons C N/m2/yr Harvard al. (2014)
stocks of 211 g C/m2 Forest
ACAD = Acadia National Park; BAI = Basal Area Increment; BBW = Bear Brook Watershed; C = carbon; Ca = calcium;
DIN = Dissolved inorganic nitrogen; EB = East Bear Brook; g = gram; ha = hectare; HBEF = Hubbard Brook Experimental Forest;
kg = kilogram; m = meter; Mg = magnesium; N = nitrogen; N20 = nitrous oxide; NA = not applicable; NE = northeastern;
NH4+ = ammonium; (NH4)2S04 = ammonium sulfate; N03" = nitrate; NPP = net primary production; P = phosphorus; S = sulfur;
SOC = soil organic carbon; W6 = Watershed 6; WB = West Bear Brook; yr = year; Zn = zinc.
C.1.5. Recovery
Research to measure and predict recovery in the Northeast indicates that while emission
control legislation has resulted in reduced S and N emissions from some stationary and
mobile sources, recovery of sensitive northeastern watersheds, including those located at
HBEF, BBW, and ACAD, has been limited. From 2000 to 2010, lake NO-,
concentrations in New England and the Adirondack Mountains, which had no trend prior
to 2000, declined at a rate of-0.05 (.ieq/L/yr (Strock et al.. 2014). Research by Warbv et
al. (2008) in the Northeast suggested a nascent recovery of soil acid-base chemistry at
some locations where red spruce stands were sampled. In BBW, SanClements et al.
(2010) found little evidence of continued depletion or recovery of soil exchangeable base
cations. Mitchell and Likens (2011) observed that with declining inputs of atmospheric S,
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the higher outputs of SO42 in drainage waters relative to precipitation inputs appear to be
driven by the S stored in the soil.
To simulate the future responses of soil and surface water chemistry to potential future
emissions controls at the reference watershed at HBEF, Gbondo-Timbawa and Driscoll
(2002) used the PnET-BGC (Photosynthesis and Evapotranspiration-Biogeochemical)
model. Simulation results suggested that emissions controls required by the CAAA will
likely not result in substantial future changes in critical indicators, such as soil base
saturation, soil solution Ca:Al, or stream ANC and A1 concentrations. Tominaga et al.
(2010) assessed model outputs of four ecosystem models by systematically applying each
of the models to data from the HBEF. They predicted that current legislated emissions
reductions (13% reduction of SO42 by 2015) would result in limited recovery and that
maximum feasible technology reductions (78% reduction of SO42 by 2015) would result
in a more rapid and greater extent of chemical recovery.
The recovery of sensitive northeastern watersheds appears to be influenced by climate
change, which has become increasingly important to consider in understanding the
potential for recovery from decades of S and N deposition. For example, climatic change,
which increases annual stream discharge and watershed wetness, will potentially increase
S042 mobilization and hence may slow the recovery of both aquatic and terrestrial
ecosystems from acidification (Mitchell and Likens. 2011). Predictive modeling of
recovery should, therefore, consider climate change. Two modeling studies reported in
this case study are noteworthy for improving scientific understanding of recovery in the
Northeast. To test assumptions about interactions that are influenced by climate change,
Campbell et al. (2009) applied the PnET-BGC model in a northern hardwood forest
ecosystem at HBEF. Results suggested an increase in primary productivity due to a
longer growing season in the future, an increase in NO3 leaching due to enhanced net
mineralization and nitrification, and a slight decrease in mineral weathering. In addition,
this warmer climate has contributed to significant declines in snow depth, snow-water
equivalents, and snow cover duration. This change has important implications for forest
ecosystem processes, such as tree phenology and growth, hydrological flow paths during
winter and spring, and soil biogeochemistry. Expected future climate change was also
simulated using ForSAFE-VEG (Soil Acidification in Forest Ecosystems model) and was
found to cause an increase in soil base saturation, especially at BBW (Phelan et al..
2016). The authors observed that climate had a lesser effect on simulated soil acid-base
chemistry at HBEF, likely due to the overwhelming influences of high S and N
deposition. They suggested that climate futures predicted by the Intergovernmental Panel
on Climate Change (IPCC) of increased temperature and precipitation will change plant
communities and N enrichment, counteracting the acidifying impacts of S and N
deposition on soil acid-base chemistry.
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Finally, increasing attention is being given to developing and implementing practices to
restore forest productivity lost to impacts from acidification. Practices such as calcium
addition may increase recovery rates in northeastern forests. For example, Battles et al.
(2014) added calcium silicate to the HBEF paired watershed to determine whether Ca lost
from leaching due to acidification can be restored. Their results suggested tree biomass
recovery and reversal of forest decline through greater above-ground net primary
production and increased photosynthetic surface area. CO2 fertilization associated with
climate change is also being evaluated for its role in helping mitigate N loss in
watersheds (Pourmokhtarian et al.. 2012).
C.2. SOUTHEASTERN APPALACHIA CASE STUDY
C.2.1. Background
This case study focuses on the Great Smoky Mountain National Park and on several
closely located Class I areas in North Carolina (Joyce Kilmer Forest, Linville Gorge,
Shining Rock). These areas are representative of the Southern Appalachian region and
also have been the focus of research on the ecological impacts of historical and current
NOx and SOx deposition. The case study summarizes literature published since 2008,
although older studies are included when relevant (e.g., conducted in Class I areas for the
purpose of investigating critical loads). The Southern Appalachians are in the Eastern
Temperate Forests ecoregion, so critical loads for the broader Level I ecoregion are also
presented.
C.2.1.1. Description of Case Study Region
This case study focuses on the southern Appalachian Mountains, with special emphasis
on Great Smoky Mountains National Park (GRSM), located on the border between
eastern Tennessee and western North Carolina. The park consists of 2,100 km2 of
mountain ridges and valleys and ranges over an elevation of 267 to 2,025 m (Thornberrv-
Ehrlich. 2008). with peaks at the highest elevations in the eastern U.S. The range in
elevation and annual precipitation [140 cm in valleys and 215 cm on ridges and peaks,
(Thomberrv-Ehrlich. 2008)1 within the park has allowed distinct terrestrial and aquatic
communities to form at different elevations.
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Geologically, the park is in the Blue Ridge physiographic province, where Cambrian
crystalline quartzite forms ridges, and Precambrian metamorphic rocks underlie the
valleys, particularly in the eastern part of the park. Carbonates and shales of the Valley
and Ridge province underlie valleys in the western part of the park where deposits of
dolomite provide substantial base cations to drainage water. The Anakeesta Formation
sits at the highest elevation of the Great Smoky Group, which forms the crest of the
mountains. The Anakeesta Formation contains iron sulfide minerals that contribute to soil
solution and surface water sulfate; it has outcropppings at Clingmans Dome, Newfound
Gap, and Chimney Tops, as well as at other high elevation locations in the north-central
section of the park.
Soils of the Blue Ridge tend to be thin and shallow, overlying steep terrain (Thornberrv-
Ehrlich. 2008). Park soils are highly weathered and, particularly on mountain tops and
ridges, have substantial soil S adsorption capacity and limited base cation supply
(Elwood. 1991).
There are 3,200 km of streams within the park's boundaries (Nichols and Langdon.
2007). Streams in the park are first through sixth order, and their chemistry is strongly
influenced by geology and storm events, as well as by acidic deposition. In 2006,
Tennessee listed 12 streams (67 km stream length) within GRSM as impaired under the
Clean Water Act section 303d, because mean stream pH was below 6.0 (Fakhraei et al..
2016). Streams in GRSM that have ANC between 50 and 200 (ieq/L (41%) are mostly
influenced by limestone weathering and tend to be located in the western portion of the
park (Neff et al.. 2009). Most stream ANC's in the park (54.2%) are in the 0-50 j^icq/L
range. Streams that have ANC near or below 0 j^icq/L (2.4%) are influenced by Anakeesta
weathering and are mainly located in the north-central portion of the park (Neff etal..
2009; Flum and Nodvin. 1995). Within the park, hindcasting by PnET-BGC model
simulations suggested that ANC in park streams in 1850 ranged from 28 to 107 |icq/L.
with lower ANC at higher elevations (Zhou et al.. 2015a). In the broader Southern Blue
Ridge province, MAGIC model simulations hindcasted to 1860 suggested that
66 modeled streams had preindustrial ANC > 30 |icq/L: in 2005, 30% of the streams had
ANC below that level (Sullivan et al.. 201 lc). Streams in the Blue Ridge region with
ANC < 20 (j,eq/L were underlain by siliceous bedrock, including sandstone and quartzite
(Sullivan et al.. 2007b).
Storm events cause episodic acidification in streams, with decreases in pH of 0.5 to
1.6 pH units in streams with ANC of <20 (j,eq/L under high flow conditions (Lawrence et
al.. 2015b; Devton et al.. 2009). Stream chemistry responses to storm events varies by
elevation within the park. At high elevations, stream pH decreased by as much
0.5-2.0 pH units during storm events in 1990-2008 (Neff et al.. 2009; Cook et al.. 1994).
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and streams above 975 m had significantly lower pH and ANC and higher nitrate
concentrations during storm events than did lower elevation streams (Neff et al.. 2013).
High elevation streams (823-966 m elevation) in the Little Pigeon River watershed had
lower ANC and pH during storm events and higher sulfate, nitrate, and organic acid
anion concentrations than at low flow (Devton et al.. 2009). Streams in watersheds
influenced by the Anakeesta Formation also had significantly lower pH and higher Al
concentrations during storm flow (Neff et al.. 2013).
GRSM historically received some of the highest deposition loads of NOx and SOx in the
U.S. In the late 1980s, a monitor at 1,740 m elevation within the park estimated S
deposition of approximately 2,200 kg S/ha/y, about half of which was occult deposition
(DW and SE. 1992); long-term trends in deposition from a monitor placed at a lower
elevation within the park are shown in Figure C-9 and Figure C-10. Much of the
historically deposited N and S remains stored within park ecosystems, with N stored in
soils, biomass, and coarse woody debris (Cai et al.. 2011b; Creed et al.. 2004). and S
adsorbed to soil (Fakhraei et al.. 2016; Cai et al.. 201 lb). The capacity of these
compartments for storing N and S are not infinite, and the capacity to retain N has been
exceeded in some areas (ecosystems have reached N saturation), as evidenced by
increased nitrate leaching and acidification of some surface waters. This suggests that
ecosystems are impaired by N deposition, and that there may be a lag time in ecosystem
recovery if deposition is reduced (Fakhraei et al.. 2016; Cai etal.. 201 la).
The range of elevation and precipitation within the park has allowed distinct terrestrial
and aquatic communities to form at different elevations, making the park one of the most
biologically diverse areas in North America. Furthermore, because the park remained
unglaciated during recent ice ages, it served as a refugium for northern plant and animal
species, as well as an evolutionary generator of new species. The All Taxa Biodiversity
Initiative is an ongoing project that seeks to document all species within the parks'
boundaries, and as of March 2016, there were 19,260 species across all domains
documented within the park (https://www.dlia.org/smokies-species-tallv).
Land cover in this case study region is mostly hardwood forest; coniferous forest occurs
primarily at the higher elevations in and around GRSM (Figure C-8). Distributed in
elevational zones from highest elevation to lowest, forest types in the park include
spruce-fir forest, beech-yellow birch forest, pine-oak forest, hemlock forest, and cove
hardwood forest. Different forest types may support endemic animal, plant, fungal, and
lichen species, as well as more broadly distributed species. There are 831 species of
lichens documented within the park (https://www.dlia.org/smokies-species-tally); lichens
are some of the most sensitive organisms in terrestrial ecosystems to atmospheric
deposition (see Section 6.1.3.3). and work in Eastern Temperate forests (Cleavitt et al..
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2015; Will-Wolf et al.. 2015) suggests that high atmospheric deposition can negatively
impact their condition, species richness, and community composition. The forests in the
park support rich understory plant communities, which are sensitive to deposition effects
such as shifts in mycorrhizal communities, competitive exclusion, and increases in
herbivory, all of which can lead to declines in herbaceous species richness (Simkin et al..
2016V
A number of threatened and endangered species occur within the park (Table C-14). A
national analysis of federally listed species identified 49 aquatic and 4 terrestrial
threatened or endangered species impacted by anthropogenic N in Fish &Wildlife Service
Region 4, which encompasses ten southeastern states, including Tennessee and North
Carolina (Hernandez et al.. 2016). The park's high biodiversity has been recognized by
its designation as a UNESCO World Heritage Site and International Biosphere Reserve.
The Tennessee-Cumberland region contains the highest diversity of freshwater mussel
and crayfish species and the highest levels of aquatic species endemism in North America
(Abell et al.. 1999). GRSM is a key preserve for North American amphibian species
(Nickerson et al.. 2002; Hyde and Simons. 2001). including salamander species whose
North American populations have declined over the past half century (Caruso and Lips.
2013).
There are a number of disturbances in the park that can interact with acidic deposition to
affect biodiversity. Invasive species alter the distribution of native species within the
park; for example, the invasive balsam woolly adelgid (Adelges piceae) has killed mature
Fraser fir {Abies fraseri) stands which historically dominated the highest elevations of the
park, resulting in a young forest of Fraser fir and red spruce (Picea rubens) at the highest
elevations (Van Miegroet et al. 2007). Ongoing damage from the invasive hemlock
woolly adelgid (Adelges tsugae) may kill the mature hemlock (Tsuga spp.) stands which
grow along streams in the park and which regulate stream temperature by the dense
shading they provide (Martin and Goebel. 2012).
Climate change may alter temperature and precipitation in the park, and some
temperature changes have already occurred in the southern Blue Ridge region. At
Grandfather Mountain, North Carolina, summer temperature increased by more than
1.4°C between 1956 and 2011 (Soule. 2011). Changes in temperature may alter species
distributions within the park. For example, native brook trout inhabit about 970 km of
stream length in GRSM, most of which is above 900 m elevation (Neff et al.. 2009).
Brook trout have disappeared from six high elevation streams in the Little Pigeon River
watershed (Devton et al.. 2009; Neff et al.. 2009). Simulation modeling by McDonnell et
al. (2015) showed that acidification of streams may hinder the movement of Southern
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Appalachian aquatic species (including brook trout) to colder, higher elevation habitats as
climate warms.
Table C-14 Species in the southeast case study region that are listed as
threatened or endangered or as species of concern.
Threatened and endangered species known or believed to occur in Great Smoky Mountains NP
Mammals
•
Myotis septentrionalis, northern long-eared bat—threatened
•
Myotis sodalis, Indiana bat—endangered
•
Glaucomys sabrinus coloratus, Carolina northern flying squirrel—endangered
Birds
•
Picoides borealis, red-cockaded woodpecker—endangered
Fish
•
Etheostoma sitikuense, Citico darter—endangered
•
Noturus baileyi, smoky madtom—endangered
•
Noturus flavipinnis, yellowfin madtom—threatened
Arthropods
•
Microhexura montivaga, spruce-fir moss spider—endangered
Plants
•
Geum radiatum, spreading avens—endangered
•
Spiraea virginiana, Virginia spiraea—threatened
•
Gymnoderma lineare, rock gnome lichen—endangered
Species believed to have been extirpated from the park
•
Canis lupus, gray wolf—endangered mammal
•
Canis rufus, red wolf—endangered mammal
•
Felis concolor couguar, eastern puma or cougar—endangered mammal
•
Erimonax monachus, spotfin chub—threatened fish
Federal Species of Concern found in the park
Mammals
•
Myotis leibii, eastern small-footed bat
•
Sorex palustris, water shrew
•
Sylvilagus obscurus, Appalachian cottontail
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Table C-14 (Continued): Species in the southeast case study region that are listed
as threatened or endangered or as species of concern.
Threatened and endangered species known or believed to occur in Great Smoky Mountains NP
Birds
•
Ammodramus henslowii, Henslow's sparrow
•
Contopus cooperi, olive-sided flycatcher
•
Dendroica cerulean, cerulean warbler
•
Loxia curvirostra, red crossbill
•
Poecile atricapillus, black-capped chickadee
•
Sphyrapicus varius, yellow-bellied sapsucker
•
Vermivora chrysoptera, golden-winged warbler
Amphibians
•
Cryptobranchus alleganiensis, eastern hellbender
•
Desmognathus aeneus, seepage salamander
•
Eurycea junaluska, Junaluska salamander
Fish
•
Percina squamata, olive darter
•
Phoxinus tennesseensis, Tennessee dace
Plants
• Abies fraseri, Fraser fir
• Calamagrostis cainii, Cain's reed-bent grass
• Cardamine clematitis, mountain bittercress
• Glyceria nubigena, Smoky Mountain manna grass
• Silene ovata, Blue Ridge catchfly
NP = National Park.
Source: National Park Service https://home.nps.gov/qrsm/learn/nature/te-species.htm.
C.2.1.2. Legal authorities
1 GRSM is a Prevention of Significant Deterioration (PSD) Class I Area. The CAA
2 (42 USC 7470) authorized Class I areas to protect air quality in national parks over
3 6,000 acres and national wilderness areas over 5,000 acres in an effort to preserve pristine
4 atmospheric conditions and air quality related values (AQRVs).
5 Wilderness areas in North Carolina located in the vicinity of GRSM that have also been
6 designated PSD Class I include Shining Rock, Linville Gorge, and Joyce Kilmer
7 Memorial Forest. All are managed by the USDA's US Forest Service. Shining Rock
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consists of 74 km2 of high elevation (1,450-1,550 m) hardwood forests dominated by
yellow birch and red maple on gneiss parent material. Linville Gorge is 43.9 km2 of
acidic cove and slope forests at intermediate elevations (1,090-1,160 m) dominated by
chestnut oak and red maple on quartzite parent material. Joyce Kilmer Memorial Forest is
68.1 km2 of low elevation (250-450 m) cove hardwoods, dominated by tulip poplar,
oaks, and eastern hemlock stands, on metasandstone parent material. Additional
information on these three wilderness areas is in Elliott et al. (2008).
Class I areas are subject to the PSD regulations under the CAA. PSD preconstruction
permits are required for new and modified existing air pollution sources. Air regulatory
agencies are required to notify federal land managers (FLMs) of any PSD permit
applications for facilities within 100 km of a Class I area.16 The FLMs are entitled to
review and comment on PSD Class I permit applications with the authorized permitting
agency. Information on air quality monitoring by NPS within GRSM is available at the
GRSM Air Quality website (https://www.nps.gov/grsm/learn/nature/air-qualitv.htm').
C.2.1.3. Regional Land Use and Land Cover
Land cover in this case study region is mostly hardwood forest; coniferous forest occurs
primarily at the higher elevations in and around GRSM (Figure C-8). Although located
generally downwind of populous areas, GRSM has only a few human population centers
of any magnitude nearby (Figure C-9). They include Knoxville, TN, 30 mi from the park
(pop. 181,000); Asheville, NC, 30 mi (pop. 87,000); Johnson City, TN, 70 mi (pop.
64,000); and Greenville, SC, 90 mi (pop. 61,188).
16 littp:/Avcbcam. srs.fs.fed.us/psd.
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Southern Appalachian Case
Study Region: Land Cover
Case Study Locations
Native American
Reservations
Developed Land (increasing intensity)
| Barren Land
| Deciduous forest
H Evergreen Forest
j Mixed Forest
~ Shrub/Scrub
I Grassland/Herbaceous
HH Cultivated Crops
^ Water/Wetlands
'eatSmlikyjSloii Bta i 11
E^ESaWarS
Figure C-8 Land cover in the southern Appalachian Mountains case study
region.
C.2.2. Deposition
1 The highest elevations of the park have received some of the highest rates of acidic
2 deposition in the U.S. (Weathers et al.. 2006; Herlihy et at.. 1993) due largely to the
3 location of upwind power plants, major agricultural regions, and the substantial amount
4 of annual precipitation.
5 Charactenstics of nitrogen and sulfur deposition affecting the Great Smoky Mountains
6 Study Area are shown in Figure C-9-Figure C-12. Data shown in Figure C-9-Figure C-
7 11 were obtained from the hybrid modeling/data fusion product, TDEP,
8 http://nadp.sws.uiuc.edu/committees/tdep/tdepmaps/ and described earlier in Section 2.8.
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However, the time series of wet deposition is taken directly from data on the NADP/NTN
website. This was done to use the long term record of wet deposition to illustrate trends
in deposition since the passage of the Clean Air Act Amendment, as the CMAQ dry
deposition simulations involved in estimating TDEP total deposition extend back only to
2000. Figure C-9 shows the 25-yr-long time series for wet deposition for NO ; . NH^
SO : \ and H measured at the NADP/NTN monitoring site Great Smoky Mountain NP
(TN11), as well as the partitioning between oxidized and reduced N Deposition of
nitrogen is estimated to be mostly in oxidized form in the study area. Although most of
the area in Figure C-9 is subject to N deposition in oxidized fonn, there are areas,
principally in northern Georgia, where N is deposited mainly in reduced form. The graph
of wet deposition of all chemical species shows that downward trends in N(Xr, NH/,
SO : . and H+ are consistently found over the past 25 yr, although the rate of decrease
was irregular, with occasional increases.
Annuil Wet Deposition and 3-Year Moving Average at
SateTNll: 1990-2014 I .«,<
WW
>
t
E
P
0
-
1
Oi
•rub
t • • * * • rk» .
m m m
m mi m
Veu
*
KenlucfcjL.
^ Knoxvllto, JN
O Monitor TW #11
# Mornio' Lomiiiw
Study Ant
• * yjf
«f «*i
U
% H Ompcmrtfsci
f f f f
» ^ jf »
~ # #v
H+ = hydrogen ion; ha = hectare; mol = mole; N = nitrogen; NH4+ = ammonium; N03 = nitrate; S042 = sulfate; yr = year.
On the left, trends in wet deposition, 1990-2014. On the right, partitioning between reduced and oxidized forms of N in deposition in
2011-2013.
Source: NCEA based on data from TDEP.
Figure C-9 Deposition over Great Smoky Mountain National Park.
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Figure C-10 shows the 25-yr-long time series for wet deposition of N and S in terms of
units commonly used to determine critical loads within GSMNP. Critical loads for
eutrophication are commonly expressed in terms of kg N/ha/yr. Critical loads for
acidification are commonly expressed in terms of kg S/ha/yr, or because both N and S
deposition can contribute to acidification, in terms of eq/ha/yr.
t
2 «
3
8
Annual Wet Deposition and 3-Year Moving
Average at Site TN11:1990 - 2014
• Ml.'
• IfllonMa1,
_ \ ry.
• #v* W \
• / \ I »
1 v " V*\ •
Annual Wet Deposition and 3-Year Moving
Average at Site TNU: 1990 - 2014
. « n
- V * / • X
\ / *
. \
V > * a
i / . W \
V *
•
10 JOM
Year
eq = H+ equivalents; ha = hectare; kg = kilogram; N = nitrogen; NH4+ = ammonium; N03 = nitrate; S = sulfur; S042 = sulfate;
yr = year.
On the left, N and S deposition are shown in units of kg/ha/yr of N or S. On the right, N and S deposition are combined into units of
acidifying deposition, eq/ha/yr of S + N.
Source: NADP/NTN.
Figure C-10 Trends in wet deposition of nitrogen and sulfur in Great Smoky
Mountain National Park, 1990-2014.
Figure C-ll shows the 3-yr average total deposition of N and S for 2011-2013.
Surrounding areas in southern states and inserts showing the coterminous U.S. are shown
to place the depositional environment in context. Comparison of maps indicates that the
general pattern of deposition of N and S is broadly similar, with higher values within the
study area than outside of it. Current rates of deposition of S are considerably lower than
along the Ohio River Valley, which might be expected given that the Ohio River Valley
is a major industrial region, and GRSM is a national park. Wet and dry deposition of S
were roughly equal across the study area. Other maps showing the contributions of
individual species to dry and/or wet deposition, based on TDEP are given in Appendix A.
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Jk
JtjrftaeW
Timnw*
w
• ~
~ Knoivflc. TN
O Mon-lor TN » 11
# Monitor Locations
AppstecltMt Study Art*
Mfirtf- _
GnM9"
i
m'9
•n
r— > N* ^
^ " % KV .•>
#
>
Kentucky,
• *
~ Kno*vi»». TH
O Mojito# TN « 11
0 Monitor Locations
App*l*chi« Study Aw*
mz)
Wort1* ^
C»fo"M *
~0»o*8**
ha = hectare; kg = kilogram; N = nitrogen; S = sulfur.
Figure C-11 Maps showing total nitrogen deposition on left, total sulfur
deposition on right, for the 3-yr average, 2011-2013.
The Great Smoky Mountain National Park NADP/NTN monitoring site (TNI 1) was
chosen to characterize long-term wet deposition of N and S species in the stud}' area.
Figure C-9-Figure C-11 are based on data for wet deposition from the TN11 monitor,
which is located in low-elevation hardwood forest within the park. Weathers et al. (2006)
mapped deposition in 2000 in the park at a finer scale and showed that deposition rates at
higher elevations (see Figure C-12) were roughly two to five times higher than at the
low-elevation NADP monitor site.
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10 km
Deposition in 6RSM,
2000 {kg ha-1 -yr1)
Suffur Nitrogen
I 4.8-10.0
6,5-13.5
13.5-20.2
20.2-26.9
26.9-33.6
33.6—41.5
10.0-15.0
15.0-20.0
20.0-25.0
25.0-30.9
GRSM = Great Smoky Mountain National Park; ha = hectare; kg = kilogram; yr = year.
Figure from Weathers et aL (2006).
Figure C-12 Modeled sulfur and nitrogen deposition to the Great Smoky
Mountain National Park for the year 2000.
C.2.3. Critical Loads and Other Dose-Response Relationships
1 The following sections describe critical loads determined for the Great Smoky Mountains
2 National Park, for the larger Southern Appalachian region, or for the Level I ecoregion in
3 which the park resides, the Eastern Temperate Forests.
C.2.3.1. Empirical Studies
4 Thresholds of deposition are quantified for GRSM and the broader region. Sampling of
5 soil and streams at high elevations in the park in the mid-1990s found elevated
6 extractable inorganic N concentrations at high elevations (Garten. 2000). as well as
7 substantial nitrate leaching in streams from these watersheds (Van Miegroet et al.. 2001).
8 Because NQx deposition was determined by Van Miegroet et al. (2001) in the watersheds
9 to be 32 kg N/ha/yr, Gilliam et al. (201 la) stated that the nitrate leaching critical load
10 would be <32 kg N/ha/yr. Additional water quality critical loads for the park are based on
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models (see below). The comparable critical load set for leaching in the Eastern
Temperate Forests is 8 kg N/ha/yr, which is lower than the Gilliam et al. (201 la) value.
This critical load is set to protect hardwood forest soils from NO;, leaching to surface
water and is based on a synthesis of data across northeastern forests (Aber et al.. 2003).
This quantity is in agreement with an earlier recommendation for Class I wildernesses in
the Forest Service's eastern region, that N deposition should not exceed 5-8 kg N/ha/yr
to protect terrestrial biota (Adams et al.. 1991). That report also recommended an annual
load for total sulfur deposition not to exceed 5-7 kg S/ha/yr to protect terrestrial biota
(Adams et al.. 1991). The critical loads set by Adams et al. (1991) were based on
observations across class I wildernesses in the Forest Service eastern region; the
deposition limits were based on the deposition loads of three Class I areas where
eutrophication and acidification were not observed.
There are a number of additional empirical critical loads set for the Eastern Temperate
Forests ecoregion based on protection of sensitive biota from effects of nitrogen
deposition (Gilliam et al.. 201 la; Pardo etal.. 2011a). A critical load of >3 kg N/ha/yr
protects growth rates or survivorship of sensitive tree species, including red pine, yellow
birch, scarlet and chestnut oaks, quaking aspen, and basswood. A critical load of
4-8 kg N/ha/yr was set for Eastern Temperate Forests based on extrapolation from data
collected in Northwest forests, to preserve sensitive lichen species and to prevent lichen
community composition shifts towards more eutrophic species. A critical load of
5-10 kg N/ha/yr protects ectomychorrizal fungi associated with coniferous tree species
from community composition change. A critical load of <12 kg N/ha/yr protects
arbuscular mycorrhizal fungi associated with hardwood tree species from decreases in
abundance and community composition change. A critical load of <17.5 kg N/ha/yr
protects forest understory communities from herbaceous species loss and shifts in plant
community composition. These critical loads (3-17.5 kg N/ha/yr) represent protection for
a broad range of sensitive terrestrial species within the Eastern Temperate Forest
ecoregion (Gilliam et al.. 201 la; Pardo etal.. 2011a).
Two more recent studies document empirical critical loads for the broad Eastern
Temperate Forest ecoregion. Cleavitt et al. (2015) conducted surveys and used FIA
assessments of lichen species in the Northeast, with particular focus on the four Class I
wilderness areas in the region (Lye Brook, VT; Great Gulf, NH; Presidential Range-Dry
River, NH; and Acadia National Park, ME). In general, cumulative N and S deposition
over the course of the modeled period (2000-2013) was a more powerful explanatory
factor than annual N or S load for the lichen data. This work determined a critical load of
4.3-5.7 kg total N (oxidized + reduced N)/ha/y based on lichen species richness, the
abundance of sensitive species (higher species richness of cyanolichens and fruticose
lichens below CL), and thallus condition. Cumulative S and N deposition were both
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equally powerfully predictors of thallus condition, but no S critical load was determined
(Cleavitt et al.. 2015V A study by Simkin et al. (2016) used FIA data to determine critical
loads for herbaceous species in a national assessment. The critical load for this analysis
was placed to prevent any loss of herbaceous species richness, and was determined to be
7.8-19.3 kg N/ha/yr for closed-canopy forest herbaceous communities in the Eastern
Temperate Forest ecoregion. The critical load determined for open-canopy (grassland,
shrubland, and woodland) herbaceous communities in this ecoregion was lower,
6.6-9.7 kg N/ha/yr (Simkin et al.. 2016). These critical load estimates may be too high
for GRSM, as Simkin et al. (2016) determined that critical loads tended to decrease under
conditions of low soil pH, high precipitation, and high temperatures, all of which affect
park ecosystems (Section 6.2.3.2).
C.2.3.2. Modeling Studies
Some of the critical loads modeled for GSMNP are aimed to protect terrestrial
ecosystems from N saturation and associated acidification. The Integrated Forest Study
sampled forests across North America, and several plots were located at high elevations
within GSMNP. A critical load of 2.5-9 kg N/ha/yr was determined for the park using
SMB modeling (OiaandArp. 1998). A decade later, Pardo and Duarte (2007) used SMB
and data from GRSM to determine critical loads for different forest types within the park.
Critical loads of 2.7-2.8 kg N/ha/yr to prevent terrestrial ecosystem eutrophication were
determined for low- and mid-elevation hardwood forests within the parks, while the
critical load for high elevation spruce-fir forests was 3.4-7 kg N/ha/yr. Pardo and Duarte
(2007) also developed critical loads to protect GSMNP forests from acidification based
on pH, Al, and base cation threshold values. In low-elevation hardwood forests, the most
protective critical load was 1,080 eq S + N/ha/yr, in mid-elevation hardwood forest the
most protective critical load was 1,650 eq S + N/ha/yr, and in high-elevation spruce-fir
forest the most protective critical load was 2,000 eq S + N/ha/yr (Pardo and Duarte.
2007).
Critical loads of N and S deposition to protect aquatic ecosystems depend upon
underlying geology, elevation, and sensitivity of streams (i.e., preindustrial ANC) in the
southern Appalachian Mountains (Sullivan et al.. 201 lb). A recent application of the
PnET-BGC model was used to determine target loads to protect aquatic ecosystems in
12 streams within GSMNP from acidification. The target load to achieve a target ANC of
50 |icq/L by 2050 was deposition of 270-1,400 eq (S + N)/ha/yr in streams at <1,000 m
elevation and which did not drain watersheds within the Anakeesta Formation (Zhou et
al.. 2015a). In an acid-sensitive, high-elevation watershed with drainage from the
Anakeesta Formation, no reduction in deposition was sufficient to reach a target of
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ANC = 50 (j,eq/L, but a target load of 270 eq (S + N)/ha/yr resulted in ANC recovery to 0
by 2050 (Zhou et al.. 2015a). More recently, Fakhraei et al. (2016) determined that in
order to protect 57% of the most sensitive GRSM streams (ANC 0-20), a critical load of
3.1 kg/ha/yr (i.e., 60% reduction from current deposition 7.8 kg/ha/yr) would be
necessary to achieve a pH >6.0 by 2080. A 60% reduction in current GRSM deposition
by 2080 would protect 71 and 87% of the most sensitive streams by 2100 and 2200.
These target loads are in good agreement with critical loads set for S only deposition
based on MAGIC and steady-state water chemistry (SSWC) modeling for the broader
Southeastern Appalachian region (McDonnell et al.. 2014b). The S only critical load was
based on achieving a target stream ANC of 50 (ieq/L, and for high elevations in the park,
the critical load was 0-250 eq S/ha/yr. Most of the low-elevation area within the park had
a critical load of 250-500 eq S/ha/yr by this method (McDonnell et al.. 2014b).
C.2.4. Characterization and Long-term Monitoring
The majority of studies conducted in this case study region have evaluated the effects of
acidification on ecosystems rather than the effects of eutrophication. Acidification has
been considered to be the dominant result of air pollution stress in the region.
Biogeochemical processes that govern watershed responses to acidification are generally
similar between the Northeast and the southern Appalachian Mountains in most respects.
The major exception is that soils in the Southern Appalachians are unglaciated and
therefore more weathered, with greater sulfate adsorption capacity, than soils in
Northeastern forests. Fakhraei et al. (2016) project that GRSM streams in watersheds
with low capacity to adsorb SO4 and low N retention will respond positively (increase
stream pH and ANC) to additional reductions in S and N deposition, while streams in
watersheds with high SO4 adsorption and low N retention (typically higher elevation
watersheds) are less responsive (or unresponsive) to reduced S and N deposition. In these
watersheds, increases in soil pH due to reduced deposition are projected to increase
desorption of accumulated SO4 from soils, resulting in a SO4 pulse to streams that will
prevent recovery of stream ANC and pH (Fakhraei et al.. 2016).
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Table C-15 Example soil, terrestrial biota, and surface water acidification
characterization and long-term monitoring studies in the southern
Appalachian Mountains region.
Study
(HERO ID)
Location
Time
Period
Focus
Results
Soil Studies
Rice et al.
(2014)
Southeastern
U.S.
2006-2021
Sulfate mass balances for
27 forested watersheds to
estimate cross-over years
(change from retaining to
releasing SO42").
Documented extensive S
adsorption on soils
Lawrence et al.
(2015b)
AT corridor,
including
through GRSM
2010-2012
Soil sampling along AT
corridor and compilation
of other existing soil
chemistry data
Documented occurrence of low
soil base saturation along the AT
corridor, including within GRSM
Cai et al.
(2011a)
Noland Divide,
GRSM
2008
Laboratory soil columns
and in situ lysimeters to
determine response of soil
solution to reduced acidic
deposition.
Recovery of soil water, as
represented by renewed Ca2+ and
Mg2+ retention, was estimated to
occur at S deposition reduction of
61% of ambient.
Cai et al.
(2012)
Noland Divide,
GRSM
2009
Four sites along
elevational gradient.
Base saturation values <7% and
Ca:AI ratio <0.01 indicated high
acid sensitivity.
Elliott et al.
(2008)
3 FS Class I
areas in North
Carolina
NuCM model
Low Ca:AI (-0.3) in A-horizon at
Shining Rock and Linville Gorge
suggested stress to forests from
soil acidification.
Terrestrial Biota Studies
Hames et al.
(2002)
Assessment of
650 study sites
across the range
of the wood
thrush in the
eastern U.S.
1995-1999
Wood thrush breeding
success
Low breeding success in the
wood thrush strongly correlated
with low soil pH
McNultv and
Boaas (2010)
Western North
Carolina
1999-2002
Red spruce and southern
pine beetle
CL for protecting forest
ecosystems may not accurately
reflect risk to ecosystem health
due to multiple stresses, including
climate change, insect infestation,
and N supply.
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Table C-15 (Continued): Example soil, terrestrial biota, and surface water
acidification characterization and long-term monitoring
studies in the southern Appalachian Mountains region.
Study
(HERO ID)
Location
Time
Period Focus
Results
Surface Water Studies
Scheffe et al.
(2014)
U.S., including
southern
Appalachian
Mts. region
Critical load by ecoregion,
as reflected in AAI
AAI model
Sullivan et al.
(2004):
Sullivan et al.
(2002)
SAMI region
MAGIC model
Streams exhibited broad range of
responses to changes in future S
deposition, including pronounced
base cation depletion. Recovery
from past acidification expected to
be slow and gradual.
Sullivan et al.
(2007b)
Southern
Appalachian
Mts.
-2,000 Delimited high-interest
area for water acidification
based on geology and
elevation, which included
almost all known low-ANC
(<20 peq/L) streams in the
region.
Lithology and elevation explained
locations of low-ANC streams.
Sullivan et al.
(2011b)
Southern
Appalachian
Mts.
MAGIC model
Estimate target loads of S
deposition to protect stream ANC
to multiple levels (0, 20, 50,
100 peq/L) at multiple points in
time (2020, 2040, 2100). TLs
ranged from 0 to values many
times higher than ambient S
deposition.
Sullivan et al.
(2011c)
Southern Blue
Ridge province
of southern
Appalachian
Mts. region
MAGIC model
Modeled 66 stream watersheds,
all of which were simulated to
have had preindustrial
ANC > 30 peq/L. In 2005, 30% of
streams had ANC below this
level. Median stream lost
25 peq/L of ANC between 1860
and 2005.
Hoos and
McMahon
(2009)
Southeastern
U.S.
SPARROW model
Examined N transport relative to
landscape characteristics. N
transport coincided with Level III
ecoregion boundaries. Lower
fraction of N input delivered to
stream at locations where primary
flow path is shallow.
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Table C-15 (Continued): Example soil, terrestrial biota, and surface water
acidification characterization and long-term monitoring
studies in the southern Appalachian Mountains region.
Study
(HERO ID)
Location
Time
Period
Focus
Results
Cai et al. Noland Divide, 1991-2007 Stream water chemistry
(2011b) GRSM trends.
Volume-weighted NO3"
concentration decreased
0.56 [jeq/L/yr; stream pH and
SO42" concentration did not
change.
Cai et al.
(2010)
Noland Divide,
GRSM
1991-2007
Developed input-output
budget.
About 61% of incoming SO42" was
retained; during rain events,
SO42" moved more readily to
streams.
Lawrence et al.
(2015b)
AT corridor,
including
through GRSM
2010-2012
Sampled more than 200
streams along the AT
corridor, including under
both high- and low-flow
conditions.
Documented wide variability in
stream ANC along the AT
corridor.
Robinson et al. Noland Divide,
(2004) GRSM
1990-1999 Developed MLR model of
water chemistry.
Showed decrease in ANC over
time.
Robinson et al. GRSM
(2008)
1993-2002
Conducted trends
analysis for 90 stream
sites, which showed
decreases in pH and
SO42" concentrations.
Extrapolation over 50 yr
suggested pH <6.0 for nearly all
study streams in the future.
Neff et al.
(2013)
GRSM
2008-2009 Examined relationships
between stream chemistry
at base flow and storm
flow vs. basin
characteristics.
Following precipitation, pH
decreased and Al increased.
Peyton et al.
(2009)
Little Pigeon
River
watersheds,
GRSM
2006-2007
Characterized chemistry
of 3 high-elevation
streams during episodes.
During storm flow, stream pH and
ANC decreased: SO42", NO3",
and organic acids increased.
AAI = Aquatic Acidification Index; Al = aluminum; ANC = acid neutralizing capacity; AT = Appalachian Trail; Ca = calcium;
CL = critical load; FS = Forest Service; GRSM = Great Smoky Mountains National Park; L = liter; |jeq = microequivalents;
MAGIC = Model of Acidification of Groundwater in Catchments; Mg2+ = magnesium; MLR = Multiple Linear Regression models;
N = nitrogen; N03" = nitrate; NuCM = Nutrient Cycling Model; S = sulfur; SAMI = Southern Appalachian Mountains Initiative;
S042 = sulfate; SPARROW = Spatially Referenced Regressions on Watershed Attributes; TL = target load; yr = year.
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C.3.
TAMPA BAY CASE STUDY
C.3.1. Background
This case study provides an overview of the Tampa Bay estuary's ecology and research
related to nutrient impairments and nitrogen (N) deposition. It also reports on the
improvements to the bay's ecology being realized from strategies to reduce nutrient
loading to the bay. Years of historical data going back to the 1950s and unique
partnerships among government, industry, and citizen groups make Tampa Bay an
interesting example of the varied issues involved in monitoring and managing water
quality and N loading in an urban estuary. During the 1970s and early 1980s eutrophic
conditions were commonly observed in Tampa Bay. Contrary to many other estuaries
suffering from eutrophication worldwide, Tampa Bay appears to be recovering since the
mid-1980s as a result of the nutrient management strategy defined by the community
(Greening et al.. 2014). These approaches have included upgraded sewage treatment,
reduction of atmospheric N emissions, and controls on stormwater and point sources.
Atmospheric deposition continues to be a source of N to Tampa Bay and, with the
decreases in N loading from point sources, represents a greater proportion of total N
loading to the bay (Greening et al.. 2014). Estimates from both modeling and
measurement indicate that direct atmospheric N deposition to Tampa Bay is between
14% and 30% while total (direct plus indirect) atmospheric deposition is between 35%
and 71% (Poor et al.. 2013b; Poor et al.. 2013a; Greening and Janicki. 2006).
Information regarding sulfur deposition is not included in this case study as N is a
primary contributor to nutrient enrichment and is the focus of the monitoring studies used
to compile this case study.
C.3.1.1. Description of Case Study Region
The Tampa Bay estuary (Figure C-13) is located on the eastern shore of the Gulf of
Mexico in Florida. At more than 1,000 km2, it is Florida's largest open water estuary,
with an average water depth of just 4 m and annual average rainfall rate of more than
125 cm (TBEP. 2015; Poor et al.. 2013a; TBEP. 2012b). It lies in the Northern Gulf of
Mexico marine ecoregion near the South Florida/Bahamian Atlantic marine ecoregion
(Wilkinson et al.. 2009). This transition zone between warm-temperate and tropical
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ecoregions, combined with its shallow waters, large size, and gradient of freshwater to
saltwater, allows the bay to support a diversity of organisms and habitats (Greening et al..
2014; USGS. 2011; USFWS.. 1990. 1988).
Hillsborough
0,d ^> M
'letrrwater Tampa
Wo* Bav |FLia-|
T— \ Gantty|
Pinellasifc^
Hillsborough
Bay
Alalia
St PaMnbutt Middle
Hft Tampa
Bo^a Bay
lower
Tampa
Bay
Manatee River
Manatee
Pasco
20
ZD Kilometers
Source: Poor et al. (2013a).
Figure C-13 Tampa Bay mainstem segments and watershed. Also shown are
the National Atmospheric Deposition (NADP) National Trends
Network wet deposition monitoring site FL41 at Verna Wellfield in
Sarasota county and the NADP Atmospheric Integrated Research
Monitoring Network site FL 18 in Hillsborough County.
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Seagrass, also known as submerged aquatic vegetation (SAV), and mangrove forests are
the most prominent estuarine habitats within Tampa Bay (TBEP. 2015). Tidal marshes
and mud flats are also found throughout the estuary (USGS. 2011). Collectively, these
habitats support a large biodiversity of flora and fauna and play a role in nutrient cycling.
Seagrasses stabilize sediments, are a food source for wildlife, provide habitat, and serve
as a nursery for large numbers of fish and shellfish species. (Greening et al.. 2014).
Mangrove roots help to stabilize the shoreline and provide nursery habitat for important
fishery species. Mud flats and salt marshes in the bay provide habitat for wading birds,
while oyster reefs near river mouths serve to naturally filter the water and attract
recreational fish species, making them popular fishing spots (TBEP. 2015). Federally
endangered West Indian manatees (Trichechus manatus), a migratory species, visit
Tampa Bay seasonally to feed in the seagrass meadows. Other endangered species in the
bay documented to be impacted by N enrichment include green turtle (Chelonia mydas)
and Atlantic sturgeon [Acipenser oxyrinchus (Hernandez et al.. 2016)1. Three national
wildlife refuges (Egmont Key, Passage Key, and Pinellas) are located in Tampa Bay and
support populations of nesting birds.
The Tampa Bay watershed, located in the Eastern Temperate Forest ecoregion, is highly
urbanized. It is now the second largest metropolitan area in Florida with a population of
over 2 million people (TBEP. 2015). Pinellas, Hillsborough, and Manatee counties border
directly on Tampa Bay while Pasco, Polk, and Sarasota counties are also within the
estuary's 6,000-km2 watershed (Poor et al.. 2013a). Activities in Tampa Bay linked to the
local and regional economy include shipping, tourism, and commercial and recreational
fishing (Poor et al.. 2013a; TBEP. 2006; Tomasko et al.. 2005). More than 80 miles of
deep-water shipping channels carry water traffic to the three seaports along the bay's
borders, in Tampa, St. Petersburg, and in northern Manatee County. The largest of these,
the Port of Tampa, consistently ranks among the busiest ports in the nation.
Mangroves, salt marshes, and SAV habitats in Tampa Bay have all experienced
significant reductions in extent since the 1950s, due to physical disturbance (dredge and
fill operations) and water quality degradation (TBEP. 2015). Excess N enrichment in the
bay is one of the main factors impacting water clarity and quality. The excess N leads to
increased algal biomass and reduced light availability for shallow-water (less than 3-m
depth) SAV (TBEP. 2015). Numerous studies have shown that the waters of Tampa Bay
are strongly N limited, due to a high concentration of phosphorus (P) from natural
leaching and from active P mining in the watershed (Greening et al.. 2014). Therefore,
the primary focus for managing eutrophication in Tampa Bay has been the reduction of N
loading to the Bay (Greening et al.. 2014).
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Tampa Bay was designated an "estuary of national significance" by Congress in 1990. In
1998, the Tampa Bay National Estuary Program (TBNEP) partnership (consisting of the
Florida Department of Environmental Protection (FDEP); the U.S. Environmental
Protection Agency; the counties of Hillsborough, Manatee, and Pinellas; the cities of
Tampa, St. Petersburg, and Clearwater; and the Southwest Florida Water Management
District) signed a formal Inter-local Agreement in support of a Comprehensive
Conservation and Management Plan (CCMP) for Tampa Bay. Upon adoption of the
Inter-local Agreement, the TBNEP became simply the Tampa Bay Estuary Program
(TBEP). TBEP continues to finance research projects in support of the CCMP and
coordinates the overall protection and restoration of the Bay with assistance and support
from its many formal and informal partners (TBEP. 2015). TBEP also coordinates the
Tampa Bay N Management Consortium (TBNMC), a public-private partnership working
to reduce nitrogen loading to the bay and whose members include local governments
(Tampa, St. Petersburg, and others) along with key industries bordering the bay, such as
electric utilities, fertilizer manufacturers, and agricultural operations.
The Tampa Bay watershed's human population is expected to increase over the next
decade and a 7% increase in N loading is projected to occur (TBEP. 2012a). To account
for these increases, the TBEP and TBNMC have adopted a new 17 ton per yr reduction
target for total N loading, to offset expected increases in total nitrogen (TN) loading and
maintain TN loading rates at average annual rates for 1992-1994.
C.3.1.2. Class I Areas
The Tampa Bay area is not a Clean Air Act Prevention of Significant Deterioration (PSD)
Class I area.
C.3.1.3. Regional Land Use and Land Cover
Land use within the Tampa Bay watershed is mixed among undeveloped, agricultural,
urban, and mining uses, including phosphate mining and fertilizer manufacturing. Figure
C-14 shows the land coverage within the bay's border communities and watershed.
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Legend
Drndgnd Navipaton ChannH
[ J TarrfM Bay V&tershed
2011 Land Use/Land Cover
¦¦ Urt»n^Op#n Land
H Mrnrg
AgriGuCura
VegeUfcon/ForwWatural
H WWand*
m wtotui
USGS Topobathymetry (m)
HQh 32 0356
Low -296312
Source: Sherwood et al. (2016)
Figure C-14 Tampa Bay overview map highlighting watershed development
and land use.
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C.3.2.
Deposition
Both direct atmospheric deposition of N to surface waters and indirect deposition to the
watershed with subsequent transport to the Tampa Bay represent important sources of N
to the case study area. In a 25-yr time series with deposition data from the nearest
National Atmospheric Deposition Program (NADP) National Trends Network (NTN)
monitoring site (Figure C-13. Verna Wellfield in Sarasota, FL), wet deposition of NO, .
NH4+, SOr and H+ show strong inter-annual variability, but downward trends in wet
deposition of all these species are consistently found over the past 25 yr (Figure C-15).
Annual Wet Deposition and 3-Year Moving Average at
Site FL41:1990-2014
400
« 350
L
300
ro
— 250
O
200
c
o
*4= 150
Q. 100
a*
Q 50
0
• A
• 4
• NIV
NO=T
H Lab
¦»"
* / * A,
* • 'V"-t * __• * -t *
19S8 1992 1996 2000 2004
Year
2008
2012
2016
H+ = hydrogen; ha = hectare; mol = mole; NH4+ = ammonium; N03 = nitrate; S042 = sulfate; yr = year.
Figure C-15
Annual wet deposition of ammonium, nitrate, sulfate, and acidity
at the National Atmospheric Deposition National Trends Network
monitoring site closest to the Tampa Bay case study area.
Source: National Center for Environmental Assessment,
U.S. EPA.
Between 2002 and 2007, U.S. EPA and Tampa Bay area scientists conducted an air
quality modeling and measurement project called the Bay Region Atmospheric
Chemistry Experiment (BRACE) in order to improve estimates of atmospheric N
deposition to Tampa Bay (Poor et al.. 2013a; Atkeson et al.. 2007). This project was also
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1 established to identify sources of N deposition in the local Tampa Bay area and assess the
2 impact of air quality regulations (Poor et al.. 2013a). Although total nitrogen (TN)
3 loading to Tampa Bay has trended downward over the past 20 yr, the percentage of N
4 from different sources has fluctuated. Direct atmospheric deposition has accounted for a
5 greater average percentage of the TN loading in recent years (from 2007-2011) than in
6 previous years r(Greening et al.. 2014; Poor et al.. 2013a); Figure C-161. Mainstem
7 segments of the bay vary widely in the percentage of total N loading attributable to direct
8 atmospheric deposition (Janicki Environmental. 2013).
Fertilizer Handling Loss
Atmospheric Deposition
Point Sources
Nonpoint Sources
Total Load
Worst case: (-1976) 1985-1989 1990-1999
Time Period
2000-2011
Source: Greening et al. (2014).
Figure C-16
Estimated annual loads of total nitrogen from various sources to
Tampa Bay summarized from 1976 to 2011.
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BRACE also investigated the primary sources of N deposition to the bay, which included
power plants and mobile sources such as cars and trucks. Power plants had recently
reduced N emissions through upgrades made as a result of TBEP's work with the
TBNMC (Poor et al.. 2013a). The sensitivity results suggested that, per unit of emission,
mobile sources had a disproportionately higher contribution than power plant sources to
atmospheric N deposition to Tampa Bay (over the watershed, the mobile NOx emissions
were responsible for four times more oxidized-N deposition than the power plant
emissions; over the Bay, the mobile NOx emissions were responsible for twice as much
oxidized-N deposition as the power plants). According to BRACE, reductions in N
emissions from mobile sources must be a part of the strategy to reduce N loading to the
Bay, and that control of atmospheric N emissions both within and outside the Tampa Bay
watershed is important to restore and maintain good water quality and a healthy
ecosystem within the bay (Poor et al.. 2013a).
The U.S. EPA recently modeled atmospheric deposition in Tampa Bay using TDEP with
monitoring data from 2000 to 2013 (see Chapter 2. Section 2.8). The general pattern of
wet + dry deposition of N (NOy and NHx) for 2011-2013 shows that fluxes are higher in
the northern half of the study area than the southern half (Figure C-17A). The deposition
of N varies by roughly a factor of two across the study area with higher deposition of N
to the north and west of Tampa Bay and a maximum in the northeast corner of the study
area. Fluxes are typically higher than those for the rest of Florida. However, they are not
as high as in many areas of the central and northeastern U.S. Dry deposition of NO2
accounts for approximately 1/6 of total deposition of oxidized N (see Appendix A). At
Tampa Bay (and some other NADP sites), dry fluxes are directed upward using the
Community Modeling for Air Quality System (CMAQ), due to the implementation of
bi-directional exchange of NH3. (However, the net flux of NHx in CMAQ is still directed
downward from wet deposition.).
Most N deposition in the case study area except the northeastern corner is estimated to be
mostly in oxidized form throughout the study area and in most of Florida, which is
consistent with many areas in the eastern and southern U.S (Figure C-17B). This is
generally in agreement with findings from BRACE modeling where oxidized forms of N
made up 60% of the total atmospheric loading to Tampa Bay, compared to 40% for
reduced forms such as ammonia [NH3 (Poor et al.. 2013a; TBEP. 2012bVI. In the study
area dry deposition dominates over wet deposition of N, which contrasts with many areas
in southern Florida where wet deposition dominates (Poor et al.. 2013a).
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A. Total Wet and Dry N Deposition
in Southern Florida 2011-2013
(12 km resolution)
B. Percent Oxidized N Deposition in
Southern Florida 2011-2013
(12 km resolution)
0 Monitor FL # 41
& Monitor Locations
1 I Tampa Bay Study Ar&a
% Oxidized N Deposition
ha = hectare; kg = kilogram; km = kilometer; N = nitrogen.
The Verna Wellfield National Atmospheric Deposition Program/National Trends Network monitoring site, FL41, was chosen to
characterize long term wet deposition of N species, because it is closest to the Tampa Bay study area. The site is located at the
southern edge of the study area in Sarasota, FL and is shown as the grey dot on the maps.
Data shown in the figures were obtained from the hybrid modeling/data fusion product, Total deposition,
http://nadp.sws.uiuc.edu/committees/tdep/tdepmaps. and described earlier in Chapter 2. Section 2ft.
Figure C-17 A. Wet and dry nitrogen deposition in Tampa Bay and the
surrounding area. B. Percent oxidized nitrogen deposition in
Tampa Bay and the surrounding area.
C.3.3. Long-Term Ecological Monitoring
Tampa Bay has been intensively studied over the years due to its significance as a natural
resource and its susceptibility to degradation due to eutrophication. There is monthly
ambient water quality data going back to 1972 (Sherwood et al . 2016). Phytoplankton
biomass and primary production have been assessed regularly in the Bay from the 1980s
N Deposition (kg-N/ha)
0 Monitor FL#41
® Monitor Locations
1 I Tampa Bay Study Area
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and benthic organisms since 1993 (Greening et al.. 2014). Aerial photography of the
Tampa Bay shoreline is available from the early 1950s showing the extent of seagrass
coverage prior to rapid human population increases in the watershed (Greening et al..
2014). A consistent monitoring program of seagrass extent (every 2 yr) was started in
1988 (Greening et al.. 2014).
Eutrophication symptoms were observed in Tampa Bay as early as the 1970s. These
included phytoplankton and macroalgal blooms and areas of low dissolved oxygen
(Greening et al.. 2014). According to Bricker et al. (2007). algal blooms were common in
the 1970s and caused foul odors and aesthetic impairment. In the late 1970s, hypoxic and
anoxic conditions along the shoreline of the most urbanized segment of Tampa Bay
caused extensive mortality of benthic organisms in the late summer months (Greening et
al.. 2014). Fish kills have also been observed in and near Tampa Bay. Historically, the
most obvious symptom of eutrophication in Tampa Bay was the loss of light at depth due
to elevated algal biomass. The loss of SAV due to reduced light availability was
dramatic. In 1950, approximately 16,000 hectares of SAV were present. By the early
1980s, over half of this area was lost I Figure C-18 (Bricker et al.. 2007; Haddad. 1989)1.
Tampa Bay is somewhat unique in that the Bay waters have historically exhibited a high
level of P due to local phosphate deposits, P mining, and fertilizer manufacturing and
shipping operations. The high phosphorus concentrations have resulted in an unusually
low N:P ratio in comparison to other estuaries, making N the limiting nutrient for
phytoplankton growth (Greening et al.. 2014; Greening and Janicki. 2006). Numerous
nutrient limitation studies using natural Tampa Bay phytoplankton populations and
cultured test organisms have confirmed N limitation (Greening et al.. 2014).
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15 iim
km = kilometer; mi = mile.
Source: Bricker et al. <2007).
Figure C-18 Seagrass Loss in Tampa Bay. Red indicates area of seagrass lost
from 1950 to 1990.
C.3.3.1. Indicators of Enrichment and Eutrophication in Tampa Bay
Indicators of historical water quality trends m the bay include chlorophyll a concentration
and seagrass coverage (Greening et al.. 2014).
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C.3.3.1.1. Chlorophyll a
1 Phytoplankton biomass as measured by chlorophyll a concentration is one of the most
2 effective indicators of eutrophication in the bay (Sherwood et al . 2016). Chlorophyll a is
3 directly linked to nutrient inputs and has been measured in the bay since 1972. Increased
4 algal biomass results in reduced light penetration in the water, thereby harming seagrass
5 and ultimately resulting in loss of SAV area.
6 The TBEP has developed water quality models to quantify linkages between N loads and
7 bay water quality. N is generally the primary limiting nutrient and chlorophyll a variation
8 in the bay responds most significantly to watershed TN loads fFigure C-19 (Greening and
9 Janicki. 2006)1.
Tampa Bay Estuary Program
Nitrogen Loading - Chlorophyll a Relationship
Comparison of Predicted and Observed Chlorophyll a Concentrations
Predicted
40
^ 86-98
°3^99-07
REF
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20
~ D O °p ft np &
' \« °Łi, f ^
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) 10 20 30
Observed
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Source: Janicki Environmental (2011).
Figure C-19 Comparison of observed chlorophyll a and that predicted from
the total nitrogen load—chlorophyll a relationships for all four
mainstem Tampa Bay segments, for 1986-1998 and 1999-2007.
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Data show that, with the exception of the Old Tampa Bay segment in 2009 and 2011,
chlorophyll a thresholds were not exceeded in all four major bay segments over the
2007-2011 period (TBEP. 2012a). The chlorophyll a threshold values are used as
indicators of impairment and vary slightly for each different segment of the bay, ranging
from 5.1 |ig/L for Lower Tampa Bay, to 8.5 |ig/L for Middle Tampa Bay, 9.3 |ig/L for
Old Tampa Bay, and 15 |ig/L for Hillsborough Bay [expressed as annual averages
(TBEP. 2012a)I.
C.3.3.1.2. Seagrass Coverage
Five species of seagrasses, turtle grass (Thalassia testudinum), manatee grass
(/Syringodiym filiforme), shoal grass {Halodule wrightii), star grass (Halophila
engelmannii), and widgeon grass (Ruppia maritima) are found in Tampa Bay (USGS.
2011). These shallow water grasses need sufficient light for photosynthesis and are
sensitive to reduced water clarity associated with increased algal growth. Scientists have
been tracking seagrass coverage as far back as the 1950s in Tampa Bay. Between the
1950s and 1980s seagrass coverage declined by about 50% or 9,000 ha in conjunction
with decreased water quality and physical impacts to the bay such as dredging and filling
(Poor etal.. 2013a; Haddad. 1989). Between 1999 and 2010, bay water clarity improved,
chlorophyll a concentrations decreased, and seagrass coverage area steadily increased,
coinciding with the reductions to N inputs to the bay I Figure C-20 (TBEP. 2015; Poor et
al.. 2013a; TBEP. 2011; Greening and Janicki. 2006)1. The most recent surveys of
seagrasses (2014) exceeded the recovery goal set in 1995 [95% of estimated seagrass
coverage of the 1950s (Sherwood et al.. 2016)1.
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o
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Seagrass Coverage Recovery Goal (-15,378 ha)
T
1950
1984 1988 1992
1996
Year
2000 2004 2008 2012
ha = hectare.
Source: Sherwood et al. (2016).
Figure C-20 Total seagrass coverage in Tampa Bay circa 1950 through 2014.
A goal to reduce N loading to 15 metric tons N/yr to maintain N loading at levels
conducive to seagrass growth was set by TBEP in the mid-1990s, a period of rapid
population growth within the watershed (Pooret al.. 2013a; Greening et al.. 2011;
Greening and Janicki. 2006). Through management actions, including an agreement with
a power company to install air pollution control systems and the completion of more than
250 projects to reduce N inputs from the watershed, TN loadings to the bay have declined
from previous annual average estimates despite an ever increasing population in the
Tampa Bay metropolitan area (Figure C-21). Data compiled by the TBNMC indicate that
continuing efforts to reduce N loading are resulting in more than sufficient water quality
for the expansion of seagrasses ( BE P. 2012a).
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J7S0
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a
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3500
32SO
3000
o
Ł 2500
Ł
1
± 2250
2000 1.5
1984 19*6 1988 1990 1992 1994 19% 1998 2000 2002 2004 2006 2008 2010 2012
Year
TN = total nitrogen; yr = year.
Source: TBEP (2012a).
Figure C-21 Trend in hydrologically normalized total nitrogen load to Tampa
Bay relative to population increases in the Tampa Bay
metropolitan area.
C.3.4. Nitrogen Management in Tampa Bay
C.3.4.1. Numeric Nutrient Criteria
1 In 1998, the U.S. EPA published the National Strategy for the Development of Regional
2 Nutrient Criteria to promote the use of nutrient concentration levels in state water quality
3 standards (U.S. EPA. 1998b). Historically, Florida had a narrative nutrient water quality
4 criterion in place to protect waters against nutrient enrichment. In 2011, the state adopted
5 the first set of statewide numeric nutrient standards for Florida's waters. Bv 2015, almost
¦ HydfO*ofticat*v Norrruiucd TN load*
—Tampa Boy Metropolitan Area Population
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all of the remaining waters in Florida had numeric nutrient standards. Numeric nutrient
criteria in Florida are established for all estuary segments, including criteria for TN, total
phosphorus (TP), and chlorophyll a. For open ocean coastal waters, numeric criteria are
derived from satellite remote sensing techniques and established for chlorophyll a only.
Numeric nutrient criteria covering all of the mainstem segments and estuarine segments
in Tampa Bay were approved by the U.S. EPA in November 2012 (U.S. EPA. 2012c). A
map of the bay segments is provided in Figure C-13. The numeric nutrient criteria for
chlorophyll a for the mainstream segments of Tampa Bay are shown in Table C-16.
Table C-16 Numeric nutrient criteria for chlorophyll a for the four mainstem
segments of Tampa Bay adopted by the Florida Department of
Environmental Protection.
Bay Segment
Chlorophyll a (jjg/L)
Old Tampa Bay
9.3 as annual mean
Hillsborough Bay
15.0 as annual mean
Middle Tampa Bay
8.5 as annual mean
Lower Tampa Bay
5.1 as annual mean
L = liter; |jg = microgram.
Modified from Sherwood et al. (2016)
Tampa Bay's numeric nutrient criteria for TN (Table C-I 7) is expressed as tons/million
cubic meters of water as an annual total not to be exceeded more than once in a 3-yr
period and represents an unorthodox approach to developing nitrogen nutrient criteria
(Florida DEP. 2016; Sherwood et al.. 2016). These values were based on previously
adopted total maximum daily loads (TMDLs) or nutrient targets developed by TBEP.
Usually, the U.S. EPA's numeric nutrient criteria are expressed as a concentration, but
TMDLs are typically expressed as loads. The N management strategy for Tampa Bay
linked seagrass growth to external N loadings based on evidence that TN loads, resultant
chlorophyll and light attenuation, and seagrass response were closely correlated
(Sherwood et al.. 2016; Janicki Environmental. 2011). The TBNMC also found that when
freshwater inputs are greater, TN moves through the system more quickly; therefore,
residence time was an important consideration. TN loads and hydrologic loads both affect
the chlorophyll within the bay, and the amount of TN delivered per unit water was used
to set the numeric nutrient criteria for Tampa Bay. The FDEP and the U.S. EPA both
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agreed that this framework, although unique for numeric nutrient criteria, would provide
reasonable assurance that the state water quality criteria would be met in Tampa Bay
(Sherwood et al.. 2016; Greening et al.. 2014).
Table C-17 Numeric nutrient criteria for total nitrogen for the four mainstem
segments of Tampa Bay.
Segment
Nitrogen Delivery Ratio Threshold (tons/million m3)
Old Tampa Bay
1.08
Hillsborough Bay
1.62
Middle Tampa Bay
1.24
Lower Tampa Bay
0.97
m = meter; TBEP = Tampa Bay Estuary Program; TN = total nitrogen.
TBEP estuarine numeric nutrient criteria expresses as nitrogen delivery ratio (tons TN per million m3 hydrologic load) based on
1992-1994 conditions.
Source: Florida PEP (2016). Janicki Environmental (2011).
C.3.4.2. Tampa Bay Nitrogen Management Consortium Efforts
The TBEP was established in 1992 as a part of the U.S. EPA's National Estuary Program
(Sherwood et al.. 2016). TBEP coordinates TBNMC, a public-private partnership
working to reduce N loading to the bay and whose members include 40+ local
governments (Tampa, St. Petersburg, and others) along with key industries bordering the
bay, such as electric utilities, fertilizer manufacturers, and agricultural operations.
In recent years, one focus of the TBNMC's strategy has been to allocate N loads for
major point and nonpoint sources in order to meet state and federal requirements. The
governments and industries participating in the TBNMC voluntarily committed to cap
their N loads at average annual levels recorded in 2003-2007, which also meets the 1998
federally recognized TMDL for N. These capped allocations have been adopted by the
state of Florida and have been incorporated into NPDES discharge permits (TBEP. 2014).
One example of the Consortium's work is the reconfiguration of coal-fired plants in the
Tampa Bay watershed to reduce NOx emissions (Poor et al.. 2013a).
Every 5 yr, the TBNMC must submit a Reasonable Assurance Update document to FDEP
for approval to document progress toward water quality and seagrass management goals.
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The most recent 2012 Reasonable Assurance Update presented data to show that there
has been reasonable progress towards the attainment of designated uses of Tampa Bay.
Based on this conclusion, FDEP upgraded Hillsborough Bay and Old Tampa Bay
segments to assessment Category 4b for nutrients (adequate management in place) from
Category 5 (impaired), and segments in Lower Tampa Bay were moved from
Category 4b to Category 2 (attains standards), signifying the state's recognition of
significant improvements in water quality and seagrass expansion (TBEP. 2014). The
consortium members share the cost of the data collection and analysis to prepare the
Reasonable Assurance Update document, and the next update will cover progress made
during the 2013-2017 time period.
C.3.4.3. Tampa Bay Response to Nitrogen Management Strategies
A recent paper reviewing the response of Tampa Bay to N management strategies
presented evidence of the ecosystem's recovery constituting a "regime shift" trajectory
(Duarte et al.. 2015; Duarte et al.. 2009). Since the mid-1980s Tampa Bay has shifted
back to a clear water seagrass system from a phytoplankton dominated system that was
characteristic of the bay under previously eutrophic conditions. Following recovery from
an El Nino heavy rainfall period (1997-1998), water clarity in Tampa Bay increased
significantly, and seagrass expanded at a rate significantly different than before the event,
suggesting a feedback mechanism as observed in just a few other systems. The authors
observed that too often these estuarine ecosystems are not able to recover even when
eutrophication stressors are mitigated because of the concurrent changes in environmental
conditions, all affecting ecosystem dynamics that occurred over the time period from the
onset of eutrophication to the reduction of nutrient levels. Greening et al. (2014) noted
four specific elements of the Tampa Bay management strategy that have resulted in a
successful recovery trajectory: (1) development of numeric water quality targets in
consultation with stakeholders, (2) citizen involvement in calling for action from
regulatory agencies, (3) collaborative actions such as the TBNMC, and (4) state and
federal regulatory programs. BRACE scientists concluded that declines in atmospheric N
deposition to the estuary and its watershed were likely part of the historical improvement
in water clarity and increases in seagrass acreage (Poor et al.. 2013a; TBEP. 2011).
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C.4.
ROCKY MOUNTAIN NATIONAL PARK CASE STUDY
C.4.1. Background
This case study describes the environment and ecology of Rocky Mountain National Park
(ROMO) and summarizes research that provides insight into the impacts of atmospheric
nitrogen and sulfur deposition on terrestrial and aquatic ecosystems in ROMO. This
includes atmospheric deposition research from within ROMO, the surrounding area of the
Rocky Mountains, as well as other portions of the Northwestern Forested Mountains
ecoregion. Although the focus is on research published since 2008, publications prior to
2008 are used to establish context and identify long-term trends.
C.4.1.1. Description of Case Study Region
Rocky Mountain National Park (ROMO) was established by Congress in 1915 and is
located in the Front Range of the Rocky Mountains in north-central Colorado, about 80
km northwest of Denver. Straddling the Continental Divide, the western side of ROMO
serves as the headwaters for the Colorado River and eastern slope feeding the South
Platte River Basin (Wolfe et al. 2003). The land within ROMO contains steep elevation
gradients and diverse ecosystem types, ranging from talus slopes at high elevations and
permanent glaciers above 4,000 m to grassy meadows at 2,400 m. Over 25% of ROMO is
above the tree line (about 3,500 m), and ROMO contains large areas of alpine tundra. In
addition, there are more than 60 peaks above 3,600 m in elevation (Porter and Johnson.
2007). Ecologically, ROMO is part of the Northwestern Forested Mountains ecoregion
(Figure C-22). The ecoregion hosts extremely diverse vegetation and well-defined
community zones along elevation gradients. More than 1,000 species of vascular plants
have been documented in ROMO (NPS. 2013). Within the alpine tundra, plant
communities contain willow (Salix spp.) and a variety of grasses, sedges, and forbs such
as alpine sunflower (Rydbergia grandiflora) and alpine forget-me-nots (Polemonium
viscosum). The subalpine zone is composed primarily of forests, dominated by
Engelmann spruce (Picea engelmannii), subalpine fir (Abies lasiocarpa), and limber pine
(Pinus flexilis), whereas forests in the montane zone vary from lodgepole pine (Pinus
contorta) at cold high elevation sites, trembling aspen (Populus tremuloides) in moist
sites, and Douglas-fir (Pseudotsuga menziesii) and ponderosa pine (Pinus ponderosd) at
more moderate and xeric sites, respectively (Beidleman et al.. 2000).
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More than 270 species of birds, including migratory species, have been reported in this
area over the last 100 yr. Many are unique to mountainous habitats—aspen, ponderosa
pine, high-elevation willow, and spruce-fir vegetation types—found in the southern
Rocky Mountains. Seven native fish and four exotic fish inhabit the aquatic systems of
ROMO. Sixty-seven mammal species are known to be native to the area, but grizzly
bears (Ursus arctos), gray wolves (Canis lupus), and bison (Bison bison) were locally
extirpated in the 19th and early 20th centuries. The lynx (Lynx canadensis) and wolverine
(Gulo gulo) are either extirpated or extremely rare. Moose (Alces alces) are now
common, but were not historically recorded as part of this area of the Rocky Mountains.
A select group of four amphibian and two reptile species survive the high elevations and
cold temperatures in ROMO. They are all considered species of concern due to apparent
low numbers, lack of information about their status, and/or declining population trends.
There are 141 confirmed species of butterflies, but arthropod (insects, spiders, centipedes,
etc.) communities in ROMO have not been as well documented as other taxonomic
groups.
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TUNDRA
There are Riparian areas l vettow) wittno eacft ecosvstefn
Source: Clarke (2013).
Figure C-22 Rocky Mountain National Park ecosystems.
The NPS maintains a list of species known to occur in ROMO that are considered
endangered, threatened, or candidates for protection by the Endangered Species Act
(NPS. 2013):
• Boreal toad (Bufo boreas boreas)—candidate
• Yellow-billed cuckoo (Coccyzus americamts)—candidate
• Canada lynx, (Lynx canadensis)—threatened
• Greenback cutthroat trout (Oncorhynchus clarki stomias)—threatened
Pardo et al. (201 lc) reported that responses to elevated N deposition in the Northwestern
Forested Mountains ecoregion include alteration of soil carbon:nitrogen (C:N) ratios,
base cation composition, and accelerated N cycling rates, including increased
mineralization and nitrification. Further, plant, lichen, and algal chemistry, surface water
chemistry (including N concentration and acid-neutralizing capacity), catchment N
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leaching rate, and changes in the community composition of plants, lichens, and
phytoplankton.
C.4.1.2. Class I Areas
Rocky Mountain National Park is designated as a federal Class I area. The Clean Air Act
(42 USC 7470) authorized these Class I areas to protect air quality in national parks over
6,000 acres and national wilderness areas over 5,000 acres in an effort to preserve pristine
atmospheric conditions. Class I areas are subject to the "prevention of significant
deterioration (PSD)" regulations under the Clean Air Act (42 USC 7470). New and
modified existing air pollution sources are required to have PSD preconstruction permits
and air regulatory agencies are required to notify federal land managers (FLMs) of any
PSD permit applications for facilities within 100 km of a Class I area.
C.4.1.3. Regional Land Use and Land Cover
The land area within the ROMO region falls predominantly into four land cover
classifications: evergreen forest, barren land, herbaceous cover, and perennial snow/ice
(Figure C-23). The remainder of the land coverage categories account for less than 7% of
the total area. The area immediately surrounding ROMO is largely forested. Regionally,
the land to the north, west, and south of ROMO is predominantly forested, with some
grasslands used as grazing land. The region to the east and southeast contains more
grassland, agricultural, and urban land use. The smaller towns of Estes Park, Allenspark,
and Grand Lake are close to the boundaries of ROMO (Figure C-24). while the larger
population centers of Fort Collins and the Denver metropolitan area are further to the east
and southeast, respectively (Figure C-23 inset).
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Rocky Mountain National Park
Case Study Location
Boulder
Jamestown
Land Cover Classification
•Evergreen Forest (S2.7%)
~
•Barren Land (13.7%)
1 1
Hay/Pasture
i i
Deciduous Forest
1 1
* Herbaceuous (13.8%)
~
Developed, Low Intensity
Open Water
Developed, Medium Intensity
1 1
"Perennial Snow/Ice (12.6%)
1 1
Developed, Open Space
1 |
Shrub/Scrub
H
Emergent Herbaceuous Wetlands
r i
Woody Wetlands
"Over 90S of coverage from
these four categories
Fort Collins
Miles
Estes Park
Denver
Lakewood
Aurora
Jackson
County
Routt National
Forest
Glen Haven
Grand Lake
Gr
Co u n
CD
Allenspark
Figure C-23 Rocky Mountain National Park land coverage using the land cover
classifications as mapped by the National Land Cover Dataset.
Percent cover shown for the four dominant cover types.
1 There are 29 total watersheds at the U.S. Geological Survey level-12 hydrological unit
2 code (HUC 12s) scale that fall completely or partially mside ROMO (Figure C-24).
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Rocky Mountain National Park
Case Study Location
HUC12 Boundaries
Inside and outside of the park boundary
County
Larimer
County
Estes Park
County
Grand Lake
BouIde r
County
Allerispark
HUC = hydrologic unit code.
Figure C-24 Rocky Mountain National Park hydrologic unit code 12
watersheds.
C.4.2. Deposition
1 Based on TDEP calculations (see Chapter 2 of the ISA), most of ROMO is estimated to
2 receive deposition between 3-9 kg N/ha/yr and 3-6 kg S/ha/yr (Figure C-25). In contrast
3 to low rates observed throughout much of the western U.S., rates of N deposition within
4 ROMO are relatively high and areas to the east of ROMO experience deposition rates
5 similar to areas in the north-central U.S. (see Figure C-25 N deposition inset). However,
6 the estimated rates of S deposition are consistent with the low rates observed elsewhere in
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1 the western U.S. and considerably lower than the S deposition rates observed within the
2 Ohio Valley. Within these TDEP estimates, the inorganic N deposition in ROMO is
3 relatively evenly balanced between oxidized and reduced forms, with the northeastern
4 portion of the region receiving predominantly reduced forms of N (Figure C-26). There
5 are three National Atmospheric Deposition Program (NADP) measurement sites within
6 ROMO (Figure C-26). including measurements stretching back more than 30 yr at the
7 Loch Vale and Beaver Meadows sites. Over the past 25 yr, sulfate (SO42 ) and hydrogen
8 ion (H+) deposition have declined slightly at the Beaver Meadows site (CO 19), whereas
9 deposition of ammonium (NH4) and nitrate (NO? ) has been relatively constant (Figure
10 C-25V
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200
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Annual Wet Deposition and 3-Year Moving Average at
Site CO!9: 1990 - 2014
• y ~ *v
• * -
H' bill
kj/"'
1988 1992 1996 2000 2004 2008
Year
2012
2016
H+ = hydrogen; ha = hectare; kg =kilogram; mol = mole; N = nitrogen; NH4+ = ammonium; N03 = nitrate; RMNP = Rocky Mountain
National Park; S = sulfur; S042" = sulfate; yr = year.
Figure C-25 Spatial patterns of atmospheric nitrogen and sulfur deposition in
the Rocky Mountain National Park region based on TDEP
calculations averaged from 2011-2013 (see Chapter 2) and
long-term trends in wet atmospheric deposition from the Beaver
Meadows National Atmospheric Deposition Program Monitoring
site within Rocky Mountain National Park.
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_Wywifa
CoiiOfa^o-
• n n
^ Oenvw.CO
O Monitor CO# 19
# Monitor Uoc»tton4
~ RMNP Study Area
tr.
% N O«pofir«n
¦f #¦%'V
N = nitrogen; RMNP = Rocky Mountain National Park.
^V*kmng
c«=*«o
- •'
~ 0*nv*r. CO
O Monitor CO# 1S
Monitor UKtfOM
Br I RMNP S4utfy Area
*1
B
% W«t H CtepooHten
//////
Figure C-26 Spatial patterns of in the percentage of atmospheric nitrogen
deposited in oxidized forms and through wet deposition in the
Rocky Mountain National Park region based on TDEP calculations
averaged from 2011-2013 (see Chapter 2).
Atmospheric N deposition generated from anthropogenic sources is a significant
influence on many ecosystems within ROMO (Wolfe et al.. 2003; Baron et ai... 2000;
Williams aad Tonnessen. 2000; Williams et al... 1996a; Caine. 1995). Because of this
influence, atmospheric N deposition has been the focus of considerable research,
including the Rocky Mountain Airborne Nitrogen and Sulfur (RoMANS) study (Beemet
al.. 2010). The RoMANS study was designed to understand the sources as well as the
transport, transformation, and deposition processes of oxidized S and oxidized and
reduced forms of N (Beem et al.. 2010).
Primary atmospheric transport to ROMO is from the west and northwest. However,
atmospheric circulation patterns along the Colorado Front Range can be complex and
significant quantities of precipitation can fall on the east side of ROMO when easterly
upslope events occur (Porter and Johnson. 2007; Mast et al.. 2003; Baron and Denning.
1993). For instance, although prevailing pattern of atmospheric circulation brings
relatively clean air from west of ROMO, anthropogenic N can be transported to ROMO
from urban and agricultural areas along the Front Range when convective heating over
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the plains produces easterly upslope winds (Figure C-27). Higher than 3,000 m above sea
level (masl), westerly air flow dominates over the upslope pollution (Sievering et al..
1996). but coal-fired power plants located in Hayden and Craig, CO approximately
150 km west of ROMO, emit NOx that may reach ROMO with prevailing westerly
winds.
Ozone
9a* and
particulate lightning
emissions
Wot Deposition
industry, power plants
Surface and Ground
Water Pollution
Soil and
Natural
Vagetation
Fertilizer and
Feedlot C hernia try
Nitrogen Sources
^^rarispor^^ranilorma^ ^^epositioi^TeedbacI^^
chemical
conversion
and dispersion
C
Particle and Gas
Transformations
HN03 = nitric acid; NH3 = ammonia; NH4+ = ammonium; NO = nitric oxide; N02 = nitrogen dioxide; N03 = nitrate; NOx = NO + NO?
Source: Clarke (2013).
Figure C-27 Rocky Mountain National Park nitrogen cycle.
Numerous organic and inorganic N species contribute to total N deposition in ROMO.
Benedict et al. (2013) conducted a year-long survey of the chemical speciation of N
deposition at ROMO (Figure C-28). Wet deposition of inorganic N, particularly NFUt,
was the dominant form of N delivered to the surface at ROMO. Wet deposition of
organic nitrogen (ON) was also a major component of deposition. Combined, reduced
forms of N (wet and dry NH4. dry NH3, ON) comprised a large majority of the total N
deposition flux in these measurements. Modeling conducted by Gebhart et al. (2011)
suggest that the majority of the ammonia measured in ROMO during the RoMANS study
was emitted from within Colorado.
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Wet NH
Wet NO.
Dry NH.
Wei ON
Dry HN0; MM
Dry NH4 V
Dry NOj ¦
Dry PON ¦
Dry N0^"> I
0 0 0.2 0.4 0 6 08 10 1.2
Total deposition (kg N/ha)
ha = hectare; HN03 = nitric acid; kg = kilogram; N = nitrogen; NH3 = ammonia; NH4 = ammonium; N02 = nitrogen dioxide;
N03 = nitrate; ON = organic nitrogen; PON = particulate organic nitrogen.
Source: Benedict et al. (2013).
Figure C-28 Total wet and dry deposition of nitrogen components measured at
Rocky Mountain National Park from November 2008 to November
2009, including organic nitrogen and particulate organic nitrogen.
C.4.3. Critical Loads and Other Dose-Response Relationships
This section focuses on studies that describe dose-response functions and/or critical loads
(CL) for atmospheric deposition effects on ecological endpoints. Terrestrial effects are
discussed first, followed by aquatic effects and a discussion on integration.
C.4.3.1. Terrestrial Critical Loads and Dose-Response Relationships
Among terrestrial ecosystems impacted by N deposition, alpine ecosystems are
particularly sensitive to increased availability of N due to inherently low rates of N
cycling, low rates of primary production, and thin, poorly weathered soils (Fcnn et al..
1998). Among taxonomic groups in this ecoregion, the impact of atmospheric deposition
on epiphytic lichens is concerning because their strong dependence on atmospheric
deposition for nutrients and unique symbiotic physiology makes them highly vulnerable
to N and S pollution and because lichens are important contributors to ecosystems
services (Brodo et al.. 2001). Among lichens, the structure and physiology of oligotrophic
species makes them especially important components of winter food webs, hydrologic
and nutrient cycles, and wildlife habitat (McCune and Geiser. 1997).
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C.4.3.1.1. Empirical Studies
In the Pardo etal. (2011c) critical loads assessment, most of the studies examining the
responses of alpine ecosystems were conducted in the Colorado Front Range of the
Rocky Mountains, either in ROMO or in adjacent ecosystems such as the Niwot Ridge
Long-Term Ecological Research site. Critical load values for these alpine ecosystems
ranged from 1.2 to >20 kg N/ha/yr, excluding two values from Fenn etal. (2008) for
southwestern forested ecosystems (Table C-18).
Table C-18 Terrestrial empirical critical loads of nutrient nitrogen for the
Northwestern Forested Mountains ecoregion.
Reliability
in Pardo
CL (kg
Deposition/
et al.
N/ha/yr)
Species
Response
Method
Addition
Site
(2011c)
Reference
1.2 to
Epiphytic
Lichen
Application
Total deposition:
Coastal
(#)
Geiser et
3.7
lichens (150
community
of western
0.8 to
Alaska
al. (2010)
species)
change in
Oregon and
8.2 kg N/ha/yr
mixed-conifer
Washington
(CMAQ)
forests
model
2.5 to
Epiphytic
Lichen
Fenn:
Fenn: Inorganic
Sierra
##
Fenn et al.
7.1
lichens
community
Empirical
N throughfall:
Nevada
(2008)
Fenn: Letharia
change in
CLs and
1.4 to 71.1
and San
Geiser et
vulpina
mixed-conifer
DayCent
kg N/ha/yr
Bernardino
al. (2010)
forests
modeling
Geiser: Total
Mountains
Geiser: 150
species
Geiser:
Application
of western
Oregon and
Washington
model
deposition: 0.8
to 8.2 kg N/ha/yr
(CMAQ)
Subalpine forest
(Englemann
spruce [Picea
englemannii])
Increase in
organic horizon
N, foliar N,
potential net N
mineralization,
and soil solution
N, initial
increases in N
leaching below
the organic
layer
Baron:
CENTURY
model
Rueth and
Baron: Field
sampling
east and
west slope
forests
Baron: modeled
total deposition:
0.2 to 16.0 kg
N/ha/yr
Rueth and
Baron: total
deposition: 3.2
to 5.5 kg N/ha/yr
(for 1992-1997)
ROMO east
and west of
Continental
Divide
##
Baron et
al. (1994)
Rueth and
Baron
(2002)
4 to 10 Alpine dry
meadow
(Carex spp.,
including Carex
rupestris)
Plant species
composition
change
N addition
experiment
Ambient:
6 kg N/ha/yr;
Addition: 20, 40,
or 60 kg N/ha/yr
Niwot
Ridge,
Colorado
##
Bowman
et al.
(2006)
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Table C-18 (Continued): Terrestrial empirical critical loads of nutrient nitrogen for
the Northwestern Forested Mountains ecoregion.
CL (kg
N/ha/yr)
Species
Response
Method
Deposition/
Addition
Site
Reliability
in Pardo
et al.
<20110
Reference
4 Carex rupestris
Increased in
N addition
Total deposition:
Niwot
##
Bowman
vegetation cover
experiment
6 kg N/ha/yr
N additions: 20,
40, or 60 kg
N/ha/yr
Ridge,
Colorado
et al.
(2006)
5 to 10 Ectomycorrhizal
Ectomycorrhizal
Expert
2002: Bulk N
Kenai
(#)
Lilleskov
fungi
fungi community
judgment
deposition
Peninsula,
(1999)
(-40 species)
structure
extrapolated
across 5
Alaska
Lilleskov
change in
from marine
sampling sites
et al.
spruce (Picea)
West Coast
ranged from
(2001)
forests
spruce forest
0.15 to
2.3 kg/ha/60
days
2008: Wet
Lilleskov
et al.
(2002)
Lilleskov
et al.
deposition 2.8 to
(2008)
7.9 kg N/ha/yr
>20
Alpine terrestrial Soil NO3" N addition
Total deposition:
Niwot #
Bowman
leaching and N
6 kg N/ha/yr
Ridge,
et al.
fluxes
N additions: 20,
40, or
60 kg N/ha/yr
Colorado
(2006)
CL = critical load; CMAQ = community multiscale air quality model; ha = hectare; kg = kilogram; N = nitrogen; N03
ROMO = Rocky Mountain National Park; yr = year.
Reliability rating: ## = highly reliable; # = fairly reliable; (#) expert judgment.
Source: Pardo et al. (2011c).
= nitrate;
Since the publication of Pardo etal. (2011c) assessment, there have been several new
studies on terrestrial CLs (Table C-19).
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Table C-19 Montane forest and alpine ecosystem critical loads for nitrogen
deposition research published since the critical load assessment by
Pardo et al. (2011c).
CL (kg
N/ha/yr)
Vegetation
Response
Method
Deposition/Addition
Site
Reference
1.0
Composite
montane plant
communities
5% change in
alpine and
subalpine plant
community
composition
ForSAFE-VEG
modeled
change in
future (to 2500)
vegetation
Deposition:
~4 kg N/ha/yr,
1 kg S/ha/yr
Northern and
central Rocky
Mountains
region
SverdruD et
al. (2012)
1.9
Salix Candida,
Carex spp.,
Abies
lasiocarpa,
Geum rossii
10% change in
treeline
(sub/alpine)
plant community
composition
ForSAFE-VEG
modeled
change in
future (to 2100)
vegetation
Deposition:
3.5 kg N/ha/yr
Loch Vale
watershed,
ROMO
McDonnell
et al.
(2014a)
3.0
Carex
rupestris
Alpine
vegetation
abundance
Field addition
study
Ambient deposition:
4 kg N/ha/yr
Addition: 5, 10, and
ROMO
Bowman et
al. (2012)
30 kg N/ha/yr.
4.0 Epiphytic Degradation of Empirical CLs 1.83 to 3.45 kg N/ha/yr Northern McMurrav
lichens lichen (CMAQ) Rocky et al. (2015)
communities Mountains
4.1
Epiphytic
lichens
L. vulpina
U. lapponica
Poorer thallus
condition
Empirical CLs
Throughfall
<0.9 to 4.1 kg N/ha/yr
Wind River
Range,
Wyoming,
including the
Class I Bridger
Wilderness
McMurrav
et al. (2013)
Forbs and
grasses—open
canopy
ecosystem
Species richness
loss
Empirical CLs
from
vegetation
surveys
1 to 19 kg N/ha/yr, wet
(NADP) + dry (CMAQ)
deposition.
Over 15,000
plots over the
continental
U.S.
Simkin et
al. (2016)
9.0
Alpine dry
meadow
Soil solution
NOs"
concentrations
Field addition
study
Ambient deposition:
4 kg N/ha/yr
Addition: 5, 10, and
30 kg N/ha/yr
ROMO
Bowman et
al. (2012)
14.0
Alpine dry
meadow
Soil dissolved
inorganic N
concentrations
Field addition
study
Ambient deposition:
4 kg N/ha/yr
Addition: 5, 10, and
30 kg N/ha/yr
ROMO
Bowman et
al. (2012)
CL = critical load; CMAQ = community multiscale air quality model; ForSAFE-VEG = a dynamic forest ecosystem model;
ha = hectare; kg = kilogram; N = nitrogen; NADP = National Atmospheric Deposition Program; N03" = nitrate; ROMO = Rocky
Mountain National Park; S = sulfur; yr = year.
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C.4.3.1.2.
Modeling Studies
Elevated lake and stream NCh concentrations have been observed in ROMO since the
mid-1980s. To understand the source of these elevated NOs concentrations and the role
of atmospheric N deposition, Baron et al. (1994) used the CENTURY terrestrial
biogeochemistry model to estimate N uptake by plants and soils in alpine forest and
subalpine tundra within the Loch Vale watershed in ROMO. Based on the model output,
N uptake in the subalpine tundra was considerably lower than in alpine forest. Increased
export of NO3 into stream water occurred at low N deposition rates (3 to 4 kg N/ha/yr)
because much of this atmospheric N was deposited in tundra or on exposed rock surface,
providing little N uptake. This work by Baron et al. (1994) was the first N deposition CL
research within the Northwestern Forested Mountains ecoregion and aside from two CL
estimates for lichens (Geiser et al.. 2010). the CL estimate produced from this research is
the lowest among the CL estimates reviewed by Pardo etal. (2011c) for this ecoregion
(Table C-18).
Terrestrial biogeochemistry models have also played a role in the development of some
CL estimates for the ROMO region published since the Pardo et al. (201 lc) assessment.
Sverdrup et al. (2012) and McDonnell et al. (2014a) used the ForSAFE-VEG model to
evaluate potential long-term effects of climate change and atmospheric N deposition on
alpine/subalpine ecosystems. Critical loads in both studies were defined as the rate of N
deposition at which plant diversity was protected from a change of 5 to 10 Mondrian
units (Mu; i.e., 5-10% change in plant species cover). Sverdrup et al. (2012) focused on a
"generalized" alpine/subalpine site, with vegetation composition constructed from plant
community data from ROMO and other national parks in the northern and central Rocky
Mountains region. Sverdrup et al. (2012) simulated plant responses to a future climate
(IPCC A2) and four levels of N and S deposition (preindustrial background, Clean Air
Act [CAA] controls, no CAA controls, and no CAA controls + high deposition). Soil
base saturation and soil solution base cation (Be) to aluminum (Al) ratios (Bc:Al) were
predicted to decrease to less than 1% and less than 10% after year 2100, respectively,
with the scenarios of no CAA emission controls and no CAA controls + high deposition
(indicating soil acidification). Future plant species coverages were predicted to change in
successively greater amounts in response to the altered climate, CAA emission controls,
no CAA emission controls, and no CAA emission controls + high deposition. Calculated
CLs (based on a change of 5 Mu) for N deposition were 1 kg N/ha/yr. Critical loads
related to S deposition were not discussed. All future N deposition scenarios (except
preindustrial background N) resulted in CL exceedance.
The approach of McDonnell et al. (2014a) was similar to that of Sverdrup et al. (2012)
because the ForSAFE-VEG model was applied to a subalpine ecosystem to determine
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CLs for long-term vegetation composition shifts caused by climate change and
atmospheric N deposition, but differed by using the Loch Vale watershed within ROMO
as the study area and also back-projecting the model to 1900. McDonnell et al. (2014a)
estimated that the N deposition CL to avert a 10% (5 Mu) change in future (2010-2100)
plant biodiversity was 1.9 to 3.5 kg N/ha/yr, which had already been exceeded. Future air
temperature increases were predicted to further change plant community composition and
exacerbate changes caused by N deposition alone. In the simulations between 1900 and
2010, the authors found that subalpine fir (Abies lasiocarpa) sapling coverage increased
by more than 25%, graminoid response was mixed, and forbs generally decreased in
abundance (Table C-20). By 2010, Geum rossii was reduced by more than 50% of its
simulated historical cover. In scenarios using ambient N deposition and x0.5 ambient N
deposition, pronounced increases in the abundance of the moss Aulacomnium palustre
would occur in 2065 and 2080, respectively, while the dominant graminoid (Carex
rupestris) decreased. They also found that higher total N deposition scenarios would
suppress moss cover near the end of the simulation period. Projected future tree responses
were similar between the lowest two and highest three total N deposition scenarios.
Future forb and Carex rupestris cover remained relatively constant under higher total N
deposition rate scenarios.
Table C-20 Hindcast absolute and percent changes in species abundance
between 1900 and 2010 in response to historical reconstructions of
nitrogen deposition (Sullivan et al.. 2005) and historical climate
change (IPCC. 2007b).
Relative Abundance %
Growth Form
Species
1900
2010
Absolute
Change
Percent
Change
Tree
Abies lasiocarpa
6.3
8.4
2.1
33.3
Shrubs
Salix Candida
15.4
25.5
10.1
65.6
Rubus parviflorus
0.0
4.4
4.4
—
Graminoids
Carex rupestris
6.8
16.4
9.6
141.2
Carex elynoides
25.1
12.8
-12.3
-49.0
Festuca ovina
1.7
3.2
1.5
88.2
Calamagrostis purpurascans
4.3
3.0
-1.4
-32.6
Poa abbreviata
3.2
2.3
-0.9
-28.1
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Table C-20 (Continued): Hindcast absolute and percent changes in species
abundance between 1900 and 2010 in response to
historical reconstructions of nitrogen deposition
(Sullivan et al., 2005) and historical climate change
(IPCC, 2007).
Relative Abundance %
Growth Form
Species
1900
2010
Absolute
Change
Percent
Change
Forbs
Geum rossii
19.7
8.9
-10.8
-54.8
Aquilegia caerulea
4.6
4.8
0.2
4.3
Antennaria rosea
1.5
2.0
0.5
33.3
Arenaria fendleri
4.7
1.8
-2.9
-61.7
Minuartia obusiloba
3.7
1.6
-2.0
-54.1
Zigadenus elegans
0.0
2.2
2.2
—
Moss
Aulacomnium palustre
3.0
2.6
-0.5
-16.7
Source: McDonnell et al. (2014a).
C.4.3.2. Aquatic Critical Loads
Nitrogen limitation of algal productivity is widespread in remote and undisturbed
freshwater lakes, such as the high elevation lakes located throughout the Rocky
Mountains (Baron et al.. 201 lb). Based on surveys conducted in the 1980s that quantified
the ratio of dissolved inorganic N to total phosphorus, alpine lakes in the Rocky
Mountains region are predominantly N limited (45% of lakes) or colimited by both N and
P [22% of lakes Pardo et al. (2011 c) I. This may underestimate the previous extent of N
limitation in these systems because lake sediment records indicate that N deposition
began impacting biogeochemistry in some alpine lakes during the 1950s (Das et al.
2005; Wolfe et al.. 2003; Wolfe et al.. 2001). Pardo et al. (201 lc) summarized CLs for
ROMO surface waters (Table C-21) with empirical and modeled CL estimates ranging
from 1.5 to 2.5 kg N/ha/yr. Within ROMO, eastern slope surface waters commonly have
higher dissolved inorganic N (DIN) than western slope surface waters (Wolfe et al..
2001; Baron et al.. 2000).
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Table C-21 Critical loads for nitrogen for eutrophication for surface water (high
elevation lakes) in the Rocky Mountains.
CL kg
N/ha/yr
Species
Response
Method
Deposition/
Addition
Site
Reference
1.5
Diatom
community
composition
Eutrophication Used exponential equations Wet deposition Southern Bowman
correlating with NOx
emissions from CO and 11
western U.S. states to
reconstruct historic N
deposition. 1950-1964 wet
N deposition correlated with
alteration of ROMO diatom
assemblages.
2.94 kg N/ha/yr;
Dry deposition
0.94 kg N/ha/yr
Rockies/
Loch Vale
ROMO
et al.
(2006)
1.5 F. crotonesis Eutrophication Paleolimnological— Not specified Northern Saros et
A formosa analyzed diatom fossil Rockies/ al. (2003)
records of 4 lakes in the Beartooth
Beartooth Mountains. Small Mountains
Fragilaria species declined
while Fragilaria crotonensis, Wyoming
Asterionella formosa, and
multiple Cyclotella species
increased
2.0
Not
applicable
Eutrophication
Used CENTURY model to
discern if high lake and
stream N measurements are
attributed to alpine tundra
and subalpine forest N
saturation
Modeled total
deposition of 0.2
to 16.0 kg
N/ha/yr
Southern
Rockies/
Loch Vale
ROMO
Baron et
al. (1994)
2.5
Chlorophyll a Eutrophication, Compared oligotrophic lake Wet DIN
N and P chemical and chlorophyll a
colimitation data in 42 European and
North American regions to
inorganic N deposition data
Rocky
Berqstrom
deposition 2.5 to
3.5 kg N/ha/yr for
regions 26 to 29
(Rocky
Mountains in
area of ROMO)
Mountains and
Jansson
(2006)
3.0 Not Increases in Compared observations of Modeled total Rocky Baron et
applicable lake nitrate nitrate concentrations in 285 deposition of 1.5 Mountains al. (2011b)
concentration lakes to observations to N to 7.5 kg N/ha/yr
deposition estimates derived
from NADP and PRISM
CL = critical load; CO = carbon monoxide; DIN = dissolved inorganic nitrogen; ha = hectare; kg = kilogram; N = nitrogen;
NADP = National Atmospheric Deposition Program; N03" = nitrate; NOx = NO + N02; P = phosphorus; PRISM = a model for
spatial climate data; ROMO = Rocky Mountain National Park; yr = year.
Source: Baron et al. (2011b). Pardo et al. (2011c). Williams and Tonnessen (2000).
1 While the majority of ROMO aquatic research since 2000 focused on eutrophication,
2 Vertucci and Corn (1996) and Wolfe et al. (2003) described the potential for aquatic
3 acidification in the Colorado Rocky Mountains. Neither Vertucci and Corn (1996) nor
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Wolfe et al. (2003) found evidence for acidification, citing the influence of catchment
sources of base cation neutralization. However, Wolfe et al. (2003) suggested that
persistent N deposition threatened to cause chronic surface water acidification,
particularly given that episodic declines of pH and acid-neutralizing capacity (ANC) have
been well documented in east slope headwaters of the Front Range (Williams and
Tonnessen. 2000; Williams et al.. 1996b). Vertucci and Corn (1996) found that although
episodic acidification occurred during snowmelt, at no point was ANC < 0 in the northern
Colorado and southern Wyoming lakes and streams that were sampled. Importantly, the
observed acidification episodes did not coincide with presence of amphibian embryos,
meaning that amphibians in the region were not threatened by acidification (including the
boreal toad, a candidate species for Endangered Species Act protection).
C.4.3.2.1. Empirical Studies
Pardo etal. (2011c) compiled a list of N deposition studies in high elevation lakes that
have observed changes in the growth, biomass, or composition of phytoplankton (Table
C-22). Within these studies, there was a relatively narrow range of lake water nitrate
concentrations at which these phytoplankton responses were observed (Table C-22). In
paleolimnological studies of alpine lakes in this region that experienced increased rates of
deposition, there were pronounced shifts in the composition and productivity of
phytoplankton communities that occurred around 1950 (Table C-23).
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Table C-22 Lake water nitrate concentrations in nitrogen deposition studies
observing phytoplankton responses.
N Cone, (mg
NO3--N/L)
Species
Response
Deposition/Addition
Site
Reference
0.9
A. formosa, F.
crotonensis
Stimulation of
A. formosa, F.
crotonensis
Wet deposition
<2 kg N/ha/yr; N addition of
18 pmol N as NaNCfe; N + P
enrichment, 18 pmol
N + 5 pmol P as NahtePCM
Beartooth
Mountains,
Wyoming
Saros et al.
(2005)
0.9
Chlorophyll a
Increasing
biomass
Wet DIN deposition 1.3 to
11 kg N/ha/yr; total N
deposition <0.1 kg N/ha/yr
to >15 kg N/ha/yr
Sweden
Berastrom et al.
(2005)
0.9
Chlorophyll a
Increasing
biomass
Wet DIN deposition 2.5 to
3.5 kg N/ha/yr for regions
26 to 29 (Rocky Mountains
in area of ROMO)
European and N.
American lakes,
including Rocky
Mountains
Berastrom and
Jansson(2006)
1.0
Chlorophyll a
Shift in species
composition
Ambient deposition not
specified; single pulse N
treatment of 1,000 pg/L
NO3--N as KNOs
Snowy Range,
Wyoming
Nvdick et al.
(2004)
1.1
Chlorophyll a
Diatom spp.
growth
stimulation
Ambient deposition of
3.5 kg N/ha/yr; N treatment
of ambient N03"-N plus
1 mg NO3--N/L
Colorado Front
Range (Loch
Vale)
Lafrancois et al.
(2003a)
Cone. = concentration; DIN = dissolved inorganic nitrogen; ha = hectare; kg = kilogram; KN03 = potassium nitrate; L = liter;
|jg = microgram; mg = milligram; N = nitrogen; NaH2P04 = monosodium phosphate; NaN03 = sodium nitrate; N03"-N = nitrate N;
P = phosphorus; ROMO = Rocky Mountain National Park; yr = year.
Source: Pardo et al. (2011c).
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Table C-23 Paleolimnological biological responses in Rocky Mountain lakes
exposed to anthropogenic nitrogen deposition.
Species
Response
Deposition/
Addition
Site
Year(s) of
Shift
Reference
A. formosa
Increased microbial activity,
greater primary production,
change in species
composition
Not specified
Colorado Rocky
Mountains
1950
Enders et al.
(2008)
A. formosa, F.
crotonensis
Greater primary production,
stimulation of A formosa
and F. crotonensis, shift in
species assemblages
Inorganic N
deposition
4 kg N/ha/yr
Eastside ROMO
lakes compared to
remote Colorado
Rocky Mountains
wilderness lake
1950
Das et al.
(2005)
A. formosa, F.
crotonensis
Greater primary production,
stimulation of A formosa
and F. crotonensis, shift in
species assemblages
Wet inorganic N
deposition 2 to
4 kg N/ha/yr;
Dry deposition:
0.9 kg N/ha/yr
Colorado Rocky
Mountains
1950
Wolfe et al.
(2001). Wolfe
et al. (2003)
A. formosa, F.
crotonensis
Greater primary production,
stimulation of A formosa
and F. crotonensis, shift in
species assemblages after
1995
Not specified
Beartooth
Mountain Range,
Wyoming
(Yellowstone NP
region)
1995
Saros et al.
(2003)
ha = hectare; kg = kilogram; N = nitrogen; NP = National Park; ROMO = Rocky Mountain National Park; yr = year.
Source: Pardo et al. (20110).
Since the Pardo etal. (2011c) CLs synthesis, Baron etal. (201 lb) synthesized aquatic N
cycling research for lakes in several regions of the U.S., including alpine lakes in the
Rocky Mountains. Using existing water chemistry measurements and modeled estimates
of wet and dry N deposition, Baron etal. (201 lb) observed that lake nitrate
concentrations increased where N deposition exceeded 2.0 kg N/ha/yr. This threshold
was similar to previous CLs of 1.5-4 kg N/ha/yr for lakes in this region (Table C-21).
Baron etal. (201 lb) also sought to develop a CL for N driven episodic aquatic
acidification, but found little data apart from that used to generate the Williams and
Tonnessen (2000) CL estimate of 4.0 kg N/ha/yr.
C.4.3.2.2. Modeling Studies
In addition to the empirical estimates of aquatic CLs, Sullivan et al. (2005) and Hartman
et al. (2007) also created modeled CL estimates for aquatic acidification in ROMO.
Sullivan et al. (2005) used the MAGIC model to evaluate the sensitivity of two water
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17
18
19
bodies in the Loch Vale watershed within ROMO—the Loch and Andrews Creek—to N
and S deposition based on ANC. Hartman et al. (2007) also modeled deposition scenarios
for changes in ANC at Andrews Creek, but used the DayCent-Chem model. Beginning
with 1996 deposition rates of 2.2 kg S/ha/yr and 4.2 kg N/ha/yr, Sullivan et al. (2005)
estimated CLs for N or S in order to reach ANC of 0, 20, or 50 |icq/L by 2046 in the
Loch and Andrews Creek, which had 1996 ANC values of 53 and 34, respectively. To
decrease ANC to 0 or 20 in either water body, Sullivan et al. (2005) estimated that S
deposition would need to more than double or N deposition would need to nearly double.
However, increasing ANC to 50 in Andrews Creek was not achievable by 2046 in any
deposition scenario considered by Sullivan et al. (2005). Hartman et al. (2007) took a
somewhat different approach, modeling 47-yr scenarios beginning in 2000 where N
deposition increased at rates that were low (+60%), moderate (+120%), and high
(+240%) relative to the contemporary deposition rate. In these scenarios, episodic
acidification (ANC = 0 |icq/L) of Andrews Creek occurred at 6.3-7.1 kg N/ha/yr.
Estimates for persistent (chronic) changes in ANC of Andrews Creek were similar to
those of Sullivan et al. (2005). within 1 kg N/ha/yr for ANC = 20 (.ieq/L and within
3 kg N/ha/yr for ANC = 0 |icq/L (Table C-24). Notably, the Loch does not represent the
most acid-sensitive lakes in the Front Range, with approximately l/5th of the alpine lakes
in the Colorado Front Range having a similar or small ANC (Eilers et al.. 1989).
Table C-24 Critical loads of nitrogen or sulfur for surface water acidification
Rocky Mountain National Park and other high-elevation lakes in the
Rocky Mountains.
CL kg/ha/yr
of N or S
Species Response
Method
Deposition/
Addition
Site
Reference
4.0 (N)
Not
Episodic
applicable freshwater
1995 synoptic survey of NADP DIN wetfall Central
91 high-elevation lakes: at 23 sites.
acidification
(ANC < 0 pmol/L)
headwater catchments
experienced episodic
acidification due to
inorganic N in wetfall
(ANC < 0 pmol/L in
surface waters during
snowmelt).
>2,500 masl: 2.5
to 3.5 kg N/ha/yr
<2,500 masl:
<2.5 kg N/ha/yr
Rockies/
Colorado
Front
Range
Williams
and
Tonnessen
(2000)
5.8 (N) Not Freshwater
applicable acidification
(ANC = 50 peq/L)
MAGIC model scenario
for 1996 to 2046
Deposition:
2.2 kg S/ha/yr,
4.2 kg N/ha/yr
The Loch
(ROMO)
Sullivan et
al. (2005)
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Table C-24 (Continued): Critical loads of nitrogen or sulfur for surface water
acidification Rocky Mountain National Park and other
high elevation lakes in the Rocky Mountains.
CL kg/ha/yr Deposition/
of N or S Species Response Method Addition Site Reference
6.3to7.1(N) Not Episodic DayCent-Chem model Deposition: Andrews Hartman et
applicable freshwater for 2000 to 2047 of four 2.7 kg S/ha/yr, Creek al. (2007)
acidification N deposition (current, 3.5 kg N/ha/yr (ROMO)
(ANC < 0 peq/L) +60% increase, +120%
increase, +240%
increase)
7.1 (N)
Not
Freshwater
DayCent-Chem model
Deposition:
Andrews
Hartman et
applicable
acidification
for 2000 to 2047 of four
2.7 kg S/ha/yr,
Creek
al. (2007)
(ANC = 20 peq/L)
N deposition (current,
3.5 kg N/ha/yr
(ROMO)
+60% increase, +120%
increase, +240%
increase)
7.8 (N)
Not
Freshwater
MAGIC model scenario
Deposition:
Andrews
Sullivan et
applicable
acidification
for 1996 to 2046
2.2 kg S/ha/yr,
Creek
al. (2005)
(ANC = 20 peq/L)
4.2 kg N/ha/yr
(ROMO)
12.2 (N)
Not
Freshwater
MAGIC model scenario
Deposition:
Andrews
Sullivan et
applicable
acidification
for 1996 to 2046
2.2 kg S/ha/yr,
Creek
al. (2005)
(ANC = 0 peq/L)
4.2 kg N/ha/yr
(ROMO)
14.7 (N)
Not
Freshwater
MAGIC model scenario
Deposition:
The Loch
Sullivan et
applicable
acidification
for 1996 to 2046
2.2 kg S/ha/yr,
(ROMO)
al. (2005)
(ANC = 20 peq/L)
4.2 kg N/ha/yr
14.6 to 15.3 Not Chronic DayCent-Chem model Deposition: Andrews Hartman et
(N) applicable freshwater for 2000 to 2047 of four 2.7 kg S/ha/yr, Creek al. (2007)
acidification N deposition (current, 3.5 kg N/ha/yr (ROMO)
(ANC < 0 peq/L) +60% increase, +120%
increase, +240%
increase)
20.6 (N)
Not
applicable
Freshwater
acidification
(ANC = 0 peq/L)
MAGIC model scenario
for 1996 to 2046
Deposition:
2.2 kg S/ha/yr,
4.2 kg N/ha/yr
The Loch
(ROMO)
Sullivan et
al. (2005)
2.8 (S)
Not
applicable
Freshwater
acidification
(ANC = 50 peq/L)
AGIC model scenario
for 1996 to 2046
Deposition:
2.2 kg S/ha/yr,
4.2 kg N/ha/yr
The Loch
(ROMO)
Sullivan et
al. (2005)
4.6 (S)
Not
applicable
Freshwater
acidification
(ANC = 20 peq/L)
MAGIC model scenario
for 1996 to 2046
Deposition:
2.2 kg S/ha/yr,
4.2 kg N/ha/yr
Andrews
Creek
(ROMO)
Sullivan et
al. (2005)
7.8 (S)
Not
applicable
Freshwater
acidification
(ANC = 20 peq/L)
MAGIC model scenario
for 1996 to 2046
Deposition:
2.2 kg S/ha/yr,
4.2 kg N/ha/yr
The Loch
(ROMO)
Sullivan et
al. (2005)
8.1 (S)
Not
applicable
Freshwater
acidification
(ANC = 0 peq/L)
MAGIC model scenario
for 1996 to 2046
Deposition:
2.2 kg S/ha/yr,
4.2 kg N/ha/yr
Andrews
Creek
(ROMO)
Sullivan et
al. (2005)
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Table C-24 (Continued): Critical loads of nitrogen or sulfur for surface water
acidification Rocky Mountain National Park and other
high elevation lakes in the Rocky Mountains.
CL kg/ha/yr
of N or S
Species
Response
Method
Deposition/
Addition
Site
Reference
11.1 (S)
Not
Freshwater
MAGIC model scenario
Deposition:
The Loch
Sullivan et
applicable
acidification
for 1996 to 2046
2.2 kg S/ha/yr,
(ROMO)
al. (2005)
(ANC = 0 peq/L)
4.2 kg N/ha/yr
ANC = acid neutralizing capacity; CL = critical load; DIN = dissolved inorganic nitrogen; ha = hectare; kg = kilogram; L = liter;
|jeq = microequivalent; |jmol = micromole; MAGIC = a biogeochemical process model; masl = meters above sea level;
N = nitrogen; NADP = National Atmospheric Deposition Program; ROMO = Rocky Mountain National Park; S = sulfur; yr = year.
C.4.3.3. Integration
Together, there is a considerable amount of research available on the effects of
atmospheric N deposition on ecological processes and characteristics within ROMO.
Assembled together, the CL estimates developed in and around ROMO (Figure C-29)
show a continuum of effects as atmospheric N loads increase from natural background
rates (0.2 kg N/ha/yr) to levels several times greater than the current estimates of
3-9 kg N/ha/yr (Figure C-25). Broadly, the chemistry and biota of aquatic systems
appear to be the most sensitive to N deposition, followed by alpine plant communities
(Figure C-29). It is notable that many of the published CLs (Table C-18. Table C-19. and
Table C-21) are near or below the rates of atmospheric N deposition currently observed
in ROMO. Thus, there is considerable evidence that current rates of atmospheric N
deposition are influencing the composition and function of aquatic and terrestrial
ecosystems within ROMO I Figure C-30; (RMNP Initiative. 2014; Porter and Johnson.
2007)1.
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I Rocky Mountain alpine lakes: shift in diatom community dominance.
. Baron et al., 2006 (ROMO) (1.5)
Baron et al., 2011 (285 RM lakes) (1.0)
Sarosetal., 2005 (other RM) (1.5)
. Baron et al., So. (RM Loch Vale ROMO) (1.5)
Diatom assemblages already dominated by species indicative of moderate N enrichment, N limited oligotrophic
lakes switch to P-limitation after receiving only modest inputs of reactive N shifting the controls on diatom
species changes along the length of the nitrate gradient
Arnett et al., 2012 46 high elevation Rocky Mountains lakes (1-3.2 wet deposition)
Eutrophication and P co-limitation lakes
• Bergstrom & Jansson, 2006 (RM lake) (2.5)
Diatom growth in A. formosa
Nanus et al., 2012 (location?) (>3)
Al pine vegetation
. Bowman et al., 2011 (ROMO) (3.0)
Increased foliar chemistry, mineralization, nitrification, and nitrate leaching
. Reuth & Baron, 2002; Reuth et al., 2003, ROMO (<4)
Alpine vegetation change (Core* rupestris indicator)
Bowman et al, 2006 Niwot Ridge (4.0)
Episodic acidification of surface waters
Baron et al., 2011 Niwot Ridge (4.0)
Williams and Tonnesson, 2000 Central Rockies, Colorado Front
Range
RR-N.RR-P ranging from 0.33 (P limitation) to 1.16 (N-P-co-
limitation) with the exception of 1 lake outlier of 1.42 (Green
Lake)
Elser et al., 2009b (>6)
>-
T3
3
Chlorophyll a concentration increase
• Elser et al., 2009a Colorado eastern lakes (2-7)
Nitrate leaching below rooting zone in alpine
Bowman et al., 2011, ROMO
Community changes in alpine vegetation
Bowman et al., 2006 South Rockies Niwot Ridge (10.0)
Nitrate increases in soil solution in alpine
. Bowman etal., 2011 ROMO (14.0)
O
10
15
20
Nitrogen deposition (kg/ha-yr)
ha = hectare; kg = kilogram; N = nitrogen; P = phosphorus; RM = Rocky Mountain; ROMO = Rocky Mountain National Park;
RR = relative response to changes in N or P; yr = year.
Figure C-29 The continuum of ecological sensitivity to nitrogen deposition.
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Chronic
acidification
J Episodic
* acidification
o
0
a:
LU
E
o
>>
m
o
o
LU
Change in alpine
plant species
Changes in soil
and foliar
chemistry
Change in
phytoplankton
composition and
abundance
Increased lako
and stream nitrate
J Potontial Future Effocts
Current Effects
N Load (kg-ha 1yr')
ha = hectare; kg = kilogram; N = nitrogen; yr = year.
Current rates of N deposition impact terrestrial and aquatic ecosystems and relatively small increases in deposition may cause
further ecological change.
Source: Porter and Johnson (2007).
Figure C-30
Critical load thresholds for current and possible future
biogeochemical and biological effects of nitrogen deposition.
C.4.4. Highlights of Additional Research Literature and Federal Reports Since
January 2008
A number of studies documenting the effects of N or S deposition on terrestrial and
aquatic systems in ROMO or the ROMO region have been published since 2008. We
discuss these studies briefly here, but refer readers to the appropriate portion of the main
body of the ISA for a more detailed review of this work.
C.4.4.1. Terrestrial
A number of the studies reviewed in Chapter 4 and Chapter 6 of the current NOx-SOx
ISA as part of the body of terrestrial N deposition research published since 2008 were
conducted in and around ROMO. Farrer et al. (2013) and Bowman et al. (2012) both
conducted N addition studies in alpine tundra ecosystems in order to understand the
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5
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7
8
9
10
11
12
13
14
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16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
response of plants to N deposition. Farrer et al. (2013) did not find an increase in net
primary productivity, but found both positive and negative effects on the aboveground
biomass of individual plant species. Bowman et al. (2012) did not find any significant
overall effect on aboveground plant biomass, plant tissue N concentration, or plant
diversity, but did the abundance of an important sedge (Carex) species almost
quadrupled. This contrasts with Farrer et al. (2015). who found that N additions
decreased plant species diversity.
There are no published CLs for changes in soil microbial communities in the ROMO
area, but several studies in alpine tundra ecosystems have quantified microbial responses
to N additions ranging from 8 to 288 kg N/ha/yr. Dean et al. (2014) observed decreased
ericoid fungi abundance and decreased richness and diversity of root-associated fungi,
while Farrer etal. (2015) observed decreased microbial biomass, fungal biomass, and
bacterial biomass, and Farrer et al. (2013) and Nemergut et al. (2008) documented shifts
in microbial community composition.
Lieb etal. (2011) found that a decade of N additions to alpine ecosystems lowered soil
acid buffering capacity, decreased concentrations of base cation Mg2+, and increased
concentrations of Mn2+ and Al3+.
C.4.4.2. Aquatic
As with terrestrial ecosystems, there have been a number of new studies quantifying the
effects of N deposition on aquatic ecosystems in the Rocky Mountains since 2008 (Table
C-25). McCrackin and Elser (2012) measured denitrification in sediments of alpine lakes
in the Colorado Rocky Mountains that received elevated (5-8 kg N/ha/yr) or low
(<2 kg N/ha/yr) N deposition inputs. In high deposition lakes, the NO, -N concentration
was significantly higher than in low deposition lakes, but there was also evidence that
denitrifying bacteria could remove a meaningful portion of N inputs to the lakes. While
current levels of N deposition have not saturated the microbial capacity for
denitrification, the abundance of denitrifying bacteria has not increased in response to
additional N.
Mast et al. (2011) examined trends in precipitation chemistry and other factors that
influence long-term changes in chemistry of high-elevation lakes in three Colorado
wilderness areas. Mast et al. (2011) observed that sulfate concentrations in precipitation
decreased at rates of-0.15 to -0.55 (j,eq/L/yr during the years 1985 through 2008 at
10 monitoring stations in Colorado. In high elevation lakes where SOr was primarily
derived from atmospheric sources, the lake SO42 concentrations decreased by -0.12 to
-0.27 (ieq/L/yr. In lakes where watershed sources were the dominant source of SO42 . the
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14
15
S042 concentrations in lake water increased during this time period. Mast et al. (2011)
attributed this trend to the effects of climate warming on pyrite weathering. Similarly,
Heath and Baron (2014) observed increases in summer (June-August) fluxes and
concentrations of cations, SiC>2, SO42 , inorganic N, and ANC in stream water from
1984-2010 within the Loch Vale watershed in ROMO and attributed these trends to
climate change effects on nitrification, mineral weathering, and the release of elements
entrained in snow and ice. In comparison, wet N deposition rates were relatively constant
and wet SO42 deposition decreased.
Nanus et al. (2012) developed a surface water NO.? threshold for growth of the diatom A.
formosa for high-elevation lakes in the Rocky Mountains. Arnett et al. (2012) tried to
develop a CL for diatom community composition change along a gradient of 46
high-elevation lakes receiving 1 to 3.2 kg N/ha/yr in wet deposition, but observed that
diatom communities were dominated by a species associated with moderate N
enrichment even in lakes where NO3 concentrations were at the detection limit
(<1 (ig/L).
Table C-25 Summary of freshwater eutrophication studies in the Rocky
Mountains since 2008.
Species
Response
Method
Deposition/
Addition
Site
Reference
Not Diatom assemblages
applicable already dominated by
species indicative of
moderate N enrichment
Diatom calibration
from surface
sediment samples
Wet deposition: 1 to
3.2 kg N/ha/yr
Arnett et al.
46
high-elevation (2012)
lakes in the
Rocky
Mountains
Not Average lake DIN:TP of Mesocosms
applicable 16.3 + 2.76, suggesting amended with
widespread N saturation, NO3", PO43", or
but unclear if this is a new PO43" + NO3"
or historical condition
Ambient deposition
not specified
Addition:
930 mg/L NOs"
Colorado
Front Range
Gardner et
al. (2008)
Chlorophyll a Greater N deposition
increased the N:P ratio in
lakes. Phytoplankton
growth P limited in high N
deposition lakes
(~7 kg N/ha/yr), but N
limited in low-N deposition
lakes (~2 kg N/ha/yr)
N and P enrichment
bioassay
experiments in
high- and
low-deposition
lakes
Deposition: 2 to
7 kg N/ha/yr
14 eastern
Colorado
alpine lakes
Elser et al.
(2009a)
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7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
Table C-25 (Continued): Summary of freshwater eutrophication studies in the
Rocky Mountains since 2008.
Deposition/
Species Response Method Addition Site Reference
Chlorophyll a Chi a conc. increase. Enrichment Wet deposition 14 eastern Elser et al.
Responses indicated a bioassay >6 kg N/ha/yr Colorado (2009b)
range from P limitation to alpine lakes
N-P colimitation with one
N limited outlier lake.
A. formosa Maximum diatom growth Growth kinetics Total deposition Rocky Nanus et al
rate at 0.5 |jM of NO3" experiments >3 kg N/ha/yr Mountains (2012)
Chi a = chlorophyll a; DIN = dissolved inorganic nitrogen; ha = hectare; kg = kilogram; L = liter; |jM = micromolar; mg = milligram;
N = nitrogen; N03" = nitrate; P = phosphorus; P043" = phosphate; TP = total phosphorus; yr = year.
C.4.5. Rocky Mountain National Park Initiative
The large body of research on the effects of atmospheric deposition on terrestrial and
aquatic ecosystems in ROMO and the relatively low CLs has led the National Park
Service (NPS) to partner with the Colorado Department of Public Health and
Environment and the U.S. EPA to develop a plan in 2005 to decrease atmospheric N
pollution within ROMO (Porter and Johnson. 2007). Formally, this collaboration is
organized as the Rocky Mountain National Park Initiative (RMNPI). The goal of the
collaboration is to understand the impacts of N deposition in ROMO and the sources of N
emissions, and resolve the N deposition issue in ROMO (RMNP Initiative. 2014). The
three agencies developed the "Nitrogen Deposition Reduction Plan," which intended to
decrease N wet deposition in ROMO from a 2006 baseline of 3.1 kg N/ha/yr to a 2032
target of 1.5 kg N/ha/yr.
The Nitrogen Deposition Reduction Plan aims for a linear decrease in deposition between
2006 and 2032, with interim milestones of 0.3 kg N/ha reductions in annual deposition
every 5 yr. In 2012, the 5-yr rolling average of wet deposition was 2.9 kg N/ha/yr, a
number that was 0.2 kg N/ha/yr above the interim milestone target, but also reflective of
a 4-yr trend toward decreased wet N deposition (RMNP Initiative. 2014V However, in the
most recent status report (Morris. 2016). the 5-yr rolling average has increased in each of
the last 2 yr and is now 3.3 kg N/ha/yr (Figure C-31). well above the intended target.
There has been no overall trend in wet N deposition or nitrate deposition since 2007, but
the ammonium concentration has increased at four of the five monitoring sites since
2009. Within the nine-county Denver Metropolitan and Northern Colorado Front Range
region, the two largest estimated sources of ammonia emissions area livestock (75% of
emissions) and fertilizer use [14% (RMNP Initiative. 2015)1. However, considerable
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1 uncertainty remains in ammonia emissions and transport estimates and the members of
2 RMNPI have dedicated resources to research ammonia in the region. The agency partners
3 within the RMNPI are working with the agricultural industry in Colorado to decrease
4 ammonia emissions through the adoption of a set of best management practices for
5 agricultural N (Figure C-32).
^—2032 GlicJepath
5-yr Rolling Average Wet M Deposition
3.30 Kg N/ha/yr* > — —
3.2
2nd Interim Milestone
(2.4 Kg N/ha/yr)
X 2 8
lit
| 2 6
_2> 2 4
S 2.2
3rd Interim Milestone
(21 kg N/fta/yr)
4th Intenm Milestone
(18 kg N/ha/yr)
1st Interim Milestone
(2 7 kg N/ha/yr)
1.2
Resource Management Goal
(1.5 kg N/ha/yr)
0.8
0.6
04
0.2
Natural Conditions
(0 2 Kg N/ha/yr)
O
o
CM
CD
O
CM
fa
8
o
O
CM
8
O
b
CM
O
Year
ha = hectare; kg = kilogram; N = nitrogen; yr = year.
Source: Morris et al. (2014).
Figure C-31 Rocky Mountain National Park Initiative glidepath and current wet
nitrogen deposition at Loch Vale in Rocky Mountain National
Park.
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RMNP INITIATIVE AC C OMPLISHMENT TIMELINE
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¦MiEPJM
Agrxanvral Prodocer Pact
Sheet Poblched
Ammonia invent an npdate
eflwt initiated (2008 dala)
Addition*] NADP L«b Vale
Monitor I mprove meat;
1W NADP Montana*;
Tread'. Report
• Critical load iBlrrm goal
to bt rtiitid with
tnped to KDRP awl CP
Ag = agriculture; APCD = Air Pollution Control District; AQ = air quality; AQCC = Air Quality Control Commission; BMP = best
management practice; CDPHE = Colorado Department of Public Health and Environment; CLA = Colorado Livestock Association;
CP = Contingency Plan; EPA = U.S. Environmental Protection Agency; NADP = National Atmospheric Deposition Program;
NPS = National Park Service; NDRP = Nitrogen Deposition Reduction Plan; RMNP = Rocky Mountain National Park;
RoMANS = Rocky Mountain Atmospheric Nitrogen and Sulfur.
Source: CDPHE (2012V https://www.colorado.gov/pacific/sites/default/files/AP PO ROMO-lnitiative-Accomplishment-TimeNne.pdf.
Figure C-32 Rocky Mountain National Park Initiative accomplishment timeline.
C.4.6. Interactions between Nitrogen Deposition, Climate Change, and
Large-Scale Ecological Disturbances
1 Most forests within ROMO are composed of lodgepole pine or a mixture of Engelmann
2 spruce and subalpine fir. Historically, these forests have been vulnerable to two natural
3 mortality agents: bark beetles and wildfire (Ehle and Baker. 2003). Bark beetles can kill
4 more than 90% of mature trees in heavily infested areas (Rhoades et al.. 2013). while
5 wildfires in these types of forests tend to burn at high intensities and kill trees across
6 large landscapes (Sibold et al.. 2006; Buechling and Baker. 2004; Veblen et al... 1994;
7 Romme and Knight. 1981). The large number of trees killed in these disturbances
8 radically alters many ecological processes, including N cycling.
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After these disturbances, there is a large decrease in the amount of N needed to support
tree growth, which results in higher levels of inorganic N in the soil and increased
concentrations of N in the leaves of surviving or recolonizing plants (Dijkstra and
Adams. 2015; Mikkelson et al.. 2013; Rhoades et al.. 2013). These changes in N cycling
are similar to those caused by N deposition (Tenn et al. 1998) and those in experiments
in and near ROMO simulating N deposition (Rueth et al.. 2003). Although these
disturbance increase N availability, beetle epidemics or wildfires in Rocky Mountain
lodgepole pine and spruce-fir forests have not historically caused large increases in soil
nitrate leaching or high concentrations of N in stream water (Dunnette et al.. 2014;
Morris et al.. 2013; Rhoades et al.. 2013). processes associated with excess N availability
and the state of "N saturation" that occurs in ecosystems receiving large amounts of N
deposition (Tenn et al.. 2003a). However, there is concern that N deposition along the
Colorado Front Range will enhance N availability to the point where disturbances will
lead to large N leaching losses (Rhoades et al.. 2013). This means that there is potential
for N deposition to interact with bark beetles and wildfire to increase stream and lake
water N content and degrade ecosystem function.
Nitrogen deposition can increase insect attack on plants (Throop and Lerdau. 2004) and
there is some evidence that bark beetle activity and the bark beetle-caused tree mortality
can be increased by N deposition (Jones et al.. 2004). Unlike in other parts of the western
U.S. where N deposition has allowed fires to occur more frequently by increasing fuels
through greater plant growth (Tenn et al.. 2003a). there is unlikely to be a large effect of
N deposition on fire occurrence in ROMO. Fires in ROMO occur mostly during extreme
weather conditions and are not as directly influenced by the amount of fuel available
(Sibold et al.. 2006). Notably, warm climate conditions increase fire frequency in
lodgepole pine and spruce-fir forests in the Rocky Mountains ("Westerling et al.. 2006)
and support bark beetle outbreaks in these forests (Bentz et al.. 2010; Hebertson and
Jenkins. 2008).
C.5. SOUTHERN CALIFORNIA
C.5.1. Background
This case study focuses on the impact of N and S deposition on aquatic and terrestrial
ecosystems in southern California. Two areas are considered that have abundant
information on ecological effects: the Sierra Nevada and southern California arid land
ecosystems. Here we focus on the national parks located in both of these ecosystems, the
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Sequoia and Kings Canyon national parks (SEKI), located in the southern Sierra Nevada
Mountains in southern California, and Joshua Tree National Park (JOTR), located in the
desert to the southeast (Figure C-33). SEKI and JOTR were selected to emphasize Class I
areas in the Sierra Nevada (SEKI) and southern California arid land ecosystems (JOTR).
In addition, research from surrounding ecoregions relevant to these ecosystems is
included because more work has been conducted within the surrounding areas than within
the park boundaries.
The majority of the information provided in this case study represents the Sierra Nevada
Mountains/SEKI. Limited research conducted in JOTR was found in the peer-reviewed
literature. Yosemite National Park (YOSE) to the north shares many commonalities with
SEKI regarding air pollution exposure, sensitivities, and impacts. Thus, research
conducted in YOSE is relevant and included here. Background information is provided
below, including a general description of the region, protected status designation
(e.g., Class I, Wilderness Area), and regional land use. This case study includes
atmospheric deposition to the parks and surrounding areas, dose-response relationships,
and critical loads.
C.5.1.1. Description of Case Study Region
Sequoia and Kings Canyon national parks are located in the Mediterranean California
ecoregion (Level I Omernick classification) and are part of the Sierra Nevada Mountains.
These parks are known for exceptionally large trees, high mountain peaks and ridges, and
deep canyons and include the highest point in the contiguous U.S. (CONUS), Mount
Whitney at 14,494 ft (4,418 m) above sea level. There are more than 200 marble caverns,
many with endemic cave invertebrates. Sequoia National Park was originally created in
1890 to protect the giant sequoia trees (Sequoiadendron giganteum) from logging. It was
the second national park and the first formed to protect a particular living organism. In
1940, Congress created the contiguous Kings Canyon National Park to include the
glacially formed Kings Canyon. These parks have increased in size to encompass
1,353 mi2 (3,504 km2); 97% is designated and managed as wilderness.
Ecosystems in SEKI include chaparral vegetation at low elevation, extending up to alpine
areas in the high mountains. Mycorrhizae, lichens, and herbaceous species communities
are susceptible to declines in species richness/biodiversity due to the effects of N
deposition. Likewise, high elevation lakes and streams as well as low-order streams are
susceptible to eutrophication and acidification driven by N deposition. Five rivers begin
in SEKI, and past and present glaciers contributed to more than 3,000 lakes (many at high
elevation) and 2,000 miles of streams, generally of low Strahler order (Boiano et al..
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2005). Landscape variation contributes to diverse habitats that contain various
assemblages of terrestrial, aquatic, and subterranean biota. As of 2005, of the more than
1,500 taxa of vascular plants in SEKI, 138 were deemed special status; 24 were listed by
the California Native Plant Society as rare, threatened, or endangered. Fifty-one taxa of
the parks' 312 terrestrial and aquatic vertebrate species had special status designations.
Five extant native vertebrate species were federally listed in 2005: Sierra Nevada bighorn
sheep (Ovis canadensis sierrae), bald eagle (Haliaeetus leucocephalus), Little Kern
golden trout (Oncorhynchus mykiss whitei), mountain yellow-legged frog (Rana
muscosa), and Yosemite toad (Anaxyrus canorus). As of 2005, the state listed the
peregrine falcon (Falco peregrinus), great gray owl (Strix nebulosa), and willow
flycatcher (Empidonax traillii) as endangered and the red fox (Vulpes vulpes), wolverine
(Gulo gulo), and Swainson's hawk (Buteo swainsoni) as threatened. Forty extant native
vertebrate species were listed as sensitive, including: white-tailed jackrabbit (Lepus
townsendii), fisher (Martespennanti), ring-tailed cat (Bassariscus astutus), Townsend's
big-eared bat (Corynorhinus townsendii), western mastiff bats (Eumops perotis), merlin
(Falco columbarius), northern harrier (Circus cyaneus), California spotted owl (Strix
occidentalis), California legless lizard (Anniella pulchra), western pond turtle (Actinemys
marmorata), Mount Lyell salamander (Hydromantes platycephalus), San Joaquin roach
fish (Lavinia symmetricus) and Kern River rainbow trout [Oncorhynchus mykiss gilberti
(Boiano et al.. 2005)1.
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Sequoia & Kin
National Pi
Joshua Tree
tonal Park (JOTR)
¦ MIXED liARDWOOD
¦ OAK WOODLAND
RIPARIAN
¦ WAT I R
WETLAND
ALPINE
CHAPARRAL
COASTAL SAGE SCRUB
DESERT
¦ GRASSLAND
- MIXED CONIFER
iiii ir— M
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1,235 mi2 (3,200 km2), more than half designated as wilderness. It straddles the San
Bernardino County/Riverside County border, including parts of two deserts: the higher
wetter Mojave Desert and the lower drier Colorado Desert. The Little San Bernardino
Mountains cross the southwestern edge of the park. JOTR is covered primarily by
semiarid and arid vegetation types, including Joshua tree (Yucca brevifolia) woodlands.
While rainfall is less than 10 cm/yr, JOTR's groundwater supplies 200 surface water
sources (e.g., springs, oases, ephemeral streams, or washes).
Joshua Tree National Park was preserved to protect the natural resources found at the
junction of three California ecosystems. The Colorado Desert is a western extension of
the Sonoran Desert. It occupies the southern and eastern portions of the park, and is
characterized by ocotillo (Fouquieria splendens) shrubs and cholla (Opuntia spp.) cacti.
The Mojave Desert crosses the northern portions of the park and contains Joshua tree
woodlands. The third ecosystem type in JOTR is a community of California juniper
(Juniperus californica) and pinyon pine (Pinus spp.) located in the westernmost portion
of the park, above 1220 m elevation, in the Little San Bernardino Mountains.
There are several threatened and endangered species found within JOTR. Plant species
include the triple-ribbed milkvetch (Astragalus tricarinatus) and Coachella Valley
milkvetch (A. lentiginosus var. coachellae), which are federally endangered; as well as
the Parish's daisy (Erigeronparishii), which is federally threatened. The desert tortoise
(Gopherus agassizii), California's state reptile, is on both California's and the federal
threatened lists. Twenty-six other species are listed as "special concern." JOTR was
originally inhabited by the Serrano, the Chemehuevi (sometimes called the Southern
Paiutes), and the Cahuilla people, and the park contains over 500 archaeological sites.
(https://www.nps.gOv/i otr/index.htm).
C.5.1.2. Class I Areas
The 1964 Wilderness Act and the NPS Organic Act are both used as tools to protect
SEKI and JOTR from air pollution impacts. SEKI and JOTR (as well as nearby YOSE)
are also Prevention of Significant Deterioration (PSD) Class I areas. They receive the
highest level of protection under the Clean Air Act (CAA) against air pollution
degradation. The CAA (42 USC 7470) authorized designation of Class I areas to protect
air quality in national parks (over 6,000 ac [2,428 hectares]) and national wilderness
areas (over 5,000 ac [2,023 hectares]) in an effort to preserve pristine atmospheric
conditions and air quality-related values (AQRVs). Class I areas are subject to the PSD
regulations under the CAA. PSD preconstruction permits are required for new and
modified existing air pollution sources. Air regulatory agencies are required to notify
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federal land managers (FLMs) of any PSD permit applications for facilities within
100 km of a Class I area.17 The FLMs are authorized to review and comment on PSD
Class I permit applications with the permitting agency.
C.5.1.3. Regional Land Use and Land Cover
Land cover in SEKI is largely forested and mountainous terrain in and near the Sierra
Nevada Mountains. The westernmost portions of the park are covered by mixed conifer
and chaparral vegetation. Further to the west is a zone of intensive agriculture (Table C-
26).
Land cover in JOTR is largely desert and semiarid land (Table C-26. Figure C-33).
Nearby human population centers (Figure C-34) include the Coachella Valley
(-350,000 people, including the cities of Palm Springs and Indio), as well as the towns of
Twentynine Palms (25,600 people) and Joshua Tree (7,400).
17http://webcam.srs.fs.fed.us/psd.
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\k*
\
s
1
/
v
T
..Sierra Naliono
Forest
Sequoia
National Park
CALIFORNIA
Kind's Canyon
National Park
Death valley
Nationaf Park
NEVADA
Los Padres
National Forest
Channel Islands National Part
Sania Monica
Mountains
IT *\
An>hp|ni Riv*
San Bernardino
National Forest
Southern California
Case Study Region
_| Case Study Areas
Native American
Reservations
USA City Populations
• 1,000,000 plus
• 500,000 - 999,999
250,000 - 499,999
• 100,000 - 249,999
20 40 60 SO
r' \
Long Be*ch
a
n
Mojave National //
Preserve I \
Joshua Tree
National Park
i,- San Dtego
ARIZONA
Figure C-34 Southern California case study region showing locations of
human population centers.
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Table C-26 Land coverages of Sequoia, Kings Canyons, and Joshua Tree
national parks.
Land Cover Category
Sequoia National Park (km2)
Joshua Tree National Park (km2)
Kings Canyon
National Park
(km2)
Developed
5
7
4
Barren land and exposed rock
416
207
690
Deciduous forest
12
0
2
Evergreen forest
736
5
519
Mixed forest
8
0
1
Shrub/scrub
390
2,936
516
Grassland/herbaceous
68
54
100
Wetland
2
0
2
km = kilometer.
C.5.2. Deposition
Characteristics of N and S deposition are shown in Figure C-35 through Figure C-37 for
JOTR and Figure C-38 through Figure C-40 for SEKI. Data shown in the figures were
obtained from the hybrid modeling/data fusion product, TDEP
(http://nadp.sws.uiuc.edu/committees/tdep/tdepmaps/). and described earlier in Chapter 2.
However, the time series of wet deposition is taken directly from data on the NADP/NTN
website. This was done to track changes in deposition since the passage of the Clean Air
Act Amendment because the CMAQ simulations involved in TDEP extend back only to
2000.
Figure C-35 indicates that the general pattern of deposition in JOTR of N and S is
broadly similar, tending to be higher near the NADP site located in the NW corner of the
study area and decreasing inland. As expected, N deposition is highest in and surrounding
Los Angeles. The park is often subject to transport of emissions from the Los Angeles
Basin. However, as can be seen from Figure C-35B. this influence decreases substantially
towards the southeast. In addition, the area surrounding JOTR shows a high degree of
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regional heterogeneity. Deposition of S is consistent with the rest of the western U.S., but
is considerably lower than in the eastern U.S.
As shown in Figure C-36A. deposition of N is estimated to be mostly in oxidized forms
in JOTR. Although there are areas principally to the south or to the west where N is
deposited mostly in reduced forms. In Figure C-37. wet deposition of NO3, NH/, SO42 .
and H+, apart from being lower than at many other sites, has not shown consistent trends
over the past 25 yr. Comparison of Figure C-35 and Figure C-36 show that dry deposition
dominates over wet deposition of N and S in the JOTR study area.
In SEKI, Figure C-38 show 3-yr average total deposition of N and S for 2011-2013;
Figure C-39 shows the partitioning between oxidized and total N; Figure C-40 shows the
25-yr time series for wet deposition of NO;, , NH4+, SO42 . and H+ obtained at the
NADP/NTN monitoring sites near SEKI.
Deposition of N is much higher in SEKI than JOTR. There is also much greater spatial
variability in N deposition in SEKI than JOTR. On the other hand, S deposition is similar
in magnitude between the two sites; S is also characterized by relatively low spatial
variability at the two sites. In contrast to JOTR, deposition of N is estimated to be mostly
in reduced forms in SEKI (see Figure C-39). This is not surprising, given the proximity
of SEKI to the San Joaquin Valley. There is considerable variability in the percentage of
N deposition as either in oxidized or reduced forms. Wet deposition of NO3 , NH4+,
SO42 . and H+ is larger over SEKI than over JOTR, but still lower than at some NADP
sites in the eastern U.S. Similar to JOTR, dry deposition dominates over wet deposition
of both N and S in SEKI.
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~
o
Lo* ArvQOl«v CA
Mon.lor CA ¦ 67
ttexiilor Location*
Jothiu Tn« Stu<*y Aim
~ lot Anfl«l«*. CA
0 Monitor CA* 17
9 Monitor Location*
Jothu* Tr*» Stutfy Are*
N DtpofUon C>(l
A > 3 •> s*> v* s*
» iV 0>
CONUS = contiguous U.S; N=riitrogen; S=sulfur; ha = hectare; kg=kilogram.
Surrounding areas in California and Nevada and inserts showing the whole CONUS are shown to place the depositional environment for both portions of the study area in context.
Other maps showing the contributions of individual species to dry and/or wet deposition are given in Appendix A.
Figure C-35
Patterns and temporal trends of nitrogen and sulfur deposition in Joshua Tree National Park and
surrounding region in California. A and B 3-yr average total deposition of nitrogen and sulfur for
2011-2013
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CONUS = contiguous U,S; N=Nitrogen, S=Sulfur.
Surrounding areas in California and Nevada and inserts showing the whole CONUS are shown to place the depositional environment for both portions of the study area in context.
Other maps showing the contributions of individual species to dry and/or wet deposition are given in Appendix A.
Figure C-36 Patterns and temporal trends of nitrogen and sulfur deposition in Joshua Tree National Park and
surrounding region in California. A shows the partitioning between oxidized and reduced
nitrogen; B and C show the 3-yr average total percent wet deposition of nitrogen and sulfur for
2011-2013.
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100
90
r*
L
>
80
*¦1
(0
70
.c
"o
60
E
50
c
o
• _
40
+-»
\n
o
30
CL
0)
20
Q
10
0
Annual Wet Deposition and 3-Year Moving Average at
Site CA67: 1990-2014
• NH4*
• NOr
• so42-
• H* Lab
Cx
• / \
/ V
* y/Nv
,-'V • x-
V
\
\
\
•>
¦
-------
CONUS = contiguous U.S.; H+ = hydrogen ion; ha = hectare; mol = mole; NH4+ = ammonium; N032 = nitrate; S042 = sulfate; yr = year.
Surrounding areas in California and Nevada and inserts showing the whole CONUS are shown to place the depositional environment for both portions of the study area in context.
Other maps showing the contributions of individual species to dry and/or wet deposition are given in Appendix A.
Figure C-38 Patterns and temporal trends of nitrogen and sulfur deposition of Sequoia and Kings Canyons
National Parks and surrounding region in California. A and B show the 3-yr average total
deposition of nitrogen and sulfur for 2011-2013.
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CONUS = contiguous U.S.; H+ = hydrogen ion; ha = hectare; mol = mole; NH4+ = ammonium; N032 = nitrate; S042" = sulfate; yr = year.
Surrounding areas in California and Nevada and inserts showing the whole CONUS are shown to place the depositional environment for both portions of the study area in context.
Other maps showing the contributions of individual species to dry and/or wet deposition are given in Appendix A.
Figure C-39 Patterns and temporal trends of nitrogen and sulfur deposition of Sequoia and Kings Canyons
National Parks and surrounding region in California. A. shows the partitioning between oxidized
and reduced nitrogen, indicated as the fraction of total nitrogen which is oxidized; B and C show
the 3-yr average total percent wet deposition of nitrogen and sulfur for 2011-2013.
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- 100
*
"I x»
g" 1*0
so
Annual Wet Deposition and 3-Year Moving Average at A
Site CA7S: 1990 - 2014
• •/*/ • ;v(''. /
^• if * • • • # _ •
tttl
MOB
ZOO
1*0
5. 1M
1
I »
I *o
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10
uo
100
Annual Wet Deposition and 3-Year Moving Average at B
Site CA99: 1990 • 2014
N UB
/\
' v
• /« »v /¦ • \ /
•. / •\ r • ! \v*
• s ! • v* v f>w
.%'V, •*V\._
IM)
Kot
»U
»U
Year
Year
CONUS = contiguous U.S.; H+ = hydrogen ion; ha = hectare; mol = mole; NH4+ = ammonium; NO32" = nitrate; S042 = sulfate; yr = year.
Surrounding areas in California and Nevada and inserts showing the whole CONUS are shown to place the depositional environment for both portions of the study area in context.
Other maps showing the contributions of individual species to dry and/or wet deposition are given in Appendix A.
Figure C-40 Patterns and temporal trends of nitrogen and sulfur deposition of Sequoia and Kings Canyons
National Parks and surrounding region in California. A and B show w the 25-yr time series for wet
deposition of nitrate, ammonium, sulfate, and hydrogen obtained from the National Atmospheric
Deposition Program/National Trends Network monitoring sites CA 99 and CA 75m; G shows
percent oxidized nitrogen.
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C.5.3.
Critical Loads and Other Dose-Response Relationships
C.5.3.1. Terrestrial
The communities of terrestrial species with well-documented effects caused by N
deposition include lichens, mycorrhizae, grasses, and trees. While well studied
ecosystems include mixed conifer forest, alpine/subalpine, and chaparral/semi-arid
shrubland.
Data on the effects of N deposition on mixed conifer forest ecosystems in the
Mediterranean California ecoregion (Omernick Level I), including the Sierra Nevada
region, are well summarized by Fenn et al. (201 lb). A more recent overview of empirical
and modeled CLs for mixed conifer forests was provided by Fenn et al. (2015). Nitrate
leaching from soil in combination with high evapotranspiration rates lead to high nitrate
concentrations in surface waters in this area.
In general, the alpine and subalpine plant communities, such as those found in SEKI and
YOSE, are sensitive to eutrophication, an observation based largely on research
conducted in alpine ecosystems in the Rocky Mountains (Bowman et al.. 2006). Alpine
and subalpine communities are high-elevation plant communities that have developed
under conditions of low nutrient supply, in part because soil-forming processes tend to be
poorly developed at high elevations. This contributes to N sensitivity. Consequently,
changes in alpine plant productivity and species composition have been reported in
response to increased N inputs (Bowman et al.. 2006; Vitousek et al.. 1997).
In chaparral and other semiarid shrublands in southern California, nitrogen enrichment
can contribute to an increase in net primary productivity; however, water availability is
often limiting to growth (Vourlitis. 2012). Arid ecosystems represent an extreme in terms
of water availability and water is the principal limiting resource. Therefore, long-term
(many years) experiments and the potential for interactions among water, fire, and
nutrient supply in governing plant responses to N additions should be considered. Based
on N addition experiments, Vourlitis and Pasquini (2009) suggested that dry-season
addition of N significantly changes the community composition of coastal sage scrub
(CSS) vegetation, but not chaparral. The impacts of such changes on the plant community
may magnify over time. It has been proposed that increases in both fire frequency and N
deposition over the last several decades in southern California may have promoted the
conversion of CSS land to non-native grasslands (Talluto and Sliding. 2008). These same
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effects may also occur in other arid ecosystems including JOTR. Both empirical and
modeling studies suggest that loss of biodiversity in response to N input and climate
change can be greater than the effects of either stressor alone (Porter et al.. 2013).
C.5.3.1.1. Empirical Studies
A number of empirical studies (N gradient and N experimental additions) have been
conducted to identify tipping points and to define areas of CL exceedance. Key studies
conducted in the southern California case study region are listed in Table C-27.
Fenn et al. (2010) reported empirical CL exceedance maps for seven major vegetation
community types in California (Figure C-41). Thirty-five percent of the land area covered
by these vegetation types (100,000 km2) was estimated to be in exceedance of the
nutrient-N CLs (3-8 kg N/ha/yr) that were estimated for mixed conifer forests, chaparral,
and oak woodlands. Nearly half of the area covered by CSS (54%) and grasslands (44%)
was judged by the authors to be in exceedance of the CLs for protecting the ecosystem
against changes associated with invasive grasses. Substantial chaparral (53%) and oak
woodland (41%) cover was estimated to be in exceedance for impacts on epiphytic
lichens. About 30% of the desert area investigated was in exceedance, based on the
presence of invasive grasses and increased fire risk. An estimated 30% of the mixed
conifer forest, based on lichens, was in exceedance of the CL. Forested and chaparral
communities were less sensitive. Only 3-15% of the forested and chaparral areas were
estimated to be in exceedance of the CL for NCh leaching. By combining the exceedance
areas of the seven vegetation types, Fenn et al. (2010) estimated that 25% of the land area
of the vegetation types included in the study were in exceedance for protecting against
nutrient enrichment.
Pardo etal. (2011c) conducted a synthesis study that evaluated published data to identify
the empirical CLs for N in Level I ecoregions across the U.S. The authors estimated CL
values as low as 3 kg N/ha/yr to protect sensitive resources in the southern California
case study area. Table C-27 lists the CLs identified by Pardo etal. (2011c) for North
American Desert and Mediterranean California ecoregions (Omernick Level I) and new
studies published after Pardo et al. (2011c). If deposition exceeds the CL, the risk of
harmful effects increases.
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Table C-27 Summary of recent empirical dose-response and critical load studies focused on the southern
California case study area and published since Pardo et al. (2011c).
Study
Terrestrial Aquatic Location
Focus
CL/Exceedance
Mediterranean California Ecoregion Level 1 (Omernick)
Pardo etal. (2011a)
• Mediterranean California
Ecoregion Level I (Omernick);
mixed-conifer forest ecosystem
Lichen chemistry and community
changes, nitrate leaching, soil
acidification, reduced fine root
biomass
3.1-39 kg N/ha/yr
The lowest critical load is 3.1 based on
lichen tissue chemistry above the clean site
threshold. Nitrate leaching and fine root
biomass critical load is 17, soil acidification
is 26 kg N/ha/yr, and susceptibility to beetle
infestation is 39 kg N/ha/yr
Pardo etal. (2011a)
• Mediterranean California
Ecoregion Level I (Omernick);
chapparal ecosystem
Nitrate leaching and changes in
the lichen community
3.1-14 kg N/ha/yr
3.1 kg N/ha/yr is a modeled value for
lichens, while 10 kg N/ha/yr is the value for
nitrate leaching
Pardo etal. (2011a)
• Mediterranean California
Ecoregion Level I (Omernick);
coastal sage scrub ecosystem
Exotic invasive grass cover, native
forb richness, arbuscular
mycorrhizal richness
7.8-10 kg N/ha/yr
Pardo etal. (2011a)
• Mediterranean California
Ecoregion Level I (Omernick);
serpentine grassland ecosystem
Annual grass invasion replacing
native herbs
6 kg N/ha/yr
Clark etal. (2013)
• Mediterranean California and
North American Desert
Loss of herbaceous plant species
Species loss 1-30%
Ellis etal. (2013)
• SEKI and YOSE
Protection of lichens
Estimated CL 2.5 to 7.1 kg N/ha/yr
Cox etal. (2014)
• Mediterranean California
Ecoregion Level I (Omernick);
coastal sage scrub ecosystem
Conversion from coastal sage
scrub to annual grassland
Estimated CL 11 kg N/ha/yr to conserve
coastal sage shrub vegetation
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Table C-27 (Continued): Summary of recent empirical dose-response and critical load studies focused on the
southern California case study area and published since Pardo et al. (2011c).
Study Terrestrial Aquatic
Location
Focus
CL/Exceedance
Bvtnerowicz et al. •
(2015)
Mediterranean California
Ecoregion Level I (Omernick);
chapparal ecosystem
Lichens in chaparral, San
Bernardino Mountains
Exceedances of CL = 5.5 kg N/ha/yr for
lichens occurred mostly in western and
northern portions of the study area
Bvtnerowicz et al. •
(2015)
Mediterranean California
Ecoregion Level I (Omernick);
mixed-conifer forest ecosystem
Mixed conifer forest
Exceedances of CL = 3.1 kg N/ha/yr for
mixed conifer forest covered much of San
Bernardino Mountains
Allen etal. (2016) ,
Mediterranean California
Ecoregion Level I (Omernick);
coastal sage scrub ecosystem
Rapid decline in mycorrhizal
biodiversity
CL = 11 kg N/ha/yr
North American Desert Ecoregion Level 1 (Omernick)
Pardo et al. (2011a) •
North American Desert
Ecoregion Level I (Omernick)
Protect herbaceous plants and
shrubs
CL 3 to 8.4 kg N/ha/yr
Simkin et al. (2016) ,
North American Desert
Ecoregion Level I (Omernick)
Grass and forb decreasing
species richness
CL open canopy: 8.3-9.9 (mean = 9.2,
n = 240)
CL closed canopy: 13.5-17.0 (mean = 16.5,
n = 32)
Clark etal. (2013) •
Mediterranean California and
North American Desert
Loss of herbaceous plant species
Species loss 1-30%
CL = critical load; ha = hectare; kg = kilogram; N =
: nitrogen; SEKI = Sequoia and Kings Canyons National Parks; YOSE = Yosemite National Park; yr = year.
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changes because the increased availability of N tends to favor invasion by non-native
grasses into arid land ecosystems.
Clark et al. (2013) estimated the loss of herbaceous plant species caused by atmospheric
N deposition based on a national CL database. Using the lower and more conservative
estimates of CLs, the ambient N deposition was judged to be in exceedance of nutrient N
CLs over extensive portions of the Mediterranean California and North American Desert
ecoregions. Estimated plant species losses ranged from less than 1 to 30%, but variability
was high and uncertainty in these estimates was substantial.
C.5.3.1.2. Modeling
Dynamic and steady-state models have been used to estimate critical or target loads in the
southern California case study region. Key studies, highlighted in Table C-28. have
focused on CLs of nutrient N and acidity.
Table C-28 Terrestrial critical and target load and exceedance modeling studies
in southern California.
Study
Location
Model
Focus
Mixed Conifer
Hurteau et al. (2009)
Teakettle
Experimental Forest
and YOSE
STELLA®7
Modeled how changing precipitation and N deposition
levels affect shrub and herb biomass production. Herb
cover growth rate greater at 12 kg N/ha/yrthan
24 kg N/ha/yr. Precipitation was more important driver for
shrub cover.
Fenn et al. (2015)
Sierra Nevada and
San Bernardino Mts.
DayCent
Modeled CLto protect against NO3" leaching; CL
ranged from 17 to 30 kg N/ha/yr.
Semiarid
Li et al. (2006)
SEKI
DayCent
Simulated N deposition of 7.7 kg N/ha/yr; increased
loss of N to NO3" export and gaseous NO.
Rao et al. (2010)
JOTR
DayCent
Effects on fire risk in creosote bush and pinyon-juniper
vegetation types. CL = 32 kg N/ha/yr (creosote bush)
and 39 kg N/ha/yr (pinyon-juniper). Wet areas having
low soil clay (6-14%) may have CL as low as
1.5 kg N/ha/yr.
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Table C-28(Continued): Terrestrial critical and target load and exceedance
modeling studies in southern California.
Study Location Model
Raoetal. (2010) jqjr DayCent
Focus
Modeled CL was determined as the N deposition load
at which fire risk began to increase exponentially above
the background fire risk. The CL for creosote bush
scrub was 2.1 kg N/ha/yr and for pinyon-juniper
woodland was 3.6 kg N/ha/yr.
CL = critical load; ha = hectare; JOTR = Joshua Tree National Park; kg = kilogram; Mts. = mountains; N = nitrogen; NO = nitric
oxide; N03" = nitrate; SEKI = Sequoia and Kings Canyons National Parks; YOSE = Yosemite National Park; yr = year.
C.5.3.1.2.1. Mixed Conifer
Hurt can et al. (2009) developed and tested a model to determine how changes in
precipitation and N deposition might affect shrub and herb biomass in mixed conifer
forests in Teakettle Experimental Forest (located abetween SEKI and YOSE) and YOSE.
They estimated the prescribed fire intervals needed to counteract high fuel loads.
Increased understory (especially grass) biomass enhances fuel connectivity and fosters
larger and more severe fires. Under a model scenario that specified higher interannual
variability in precipitation and increased N deposition, model results suggested that
implementing fire treatments at an interval approximately equivalent to the historical
range (15-30 yr) would likely be needed to maintain understory vegetation fuel loads at
levels comparable to the control.
Based on 28 streams draining California mixed conifer forests studied by Fenn and Poth
(1999). Fenn et al. (2015) estimated that peak NO? concentrations in runoff were usually
less than 14.3 |icq/L: therefore, this level of NO? leaching was identified as the likely
critical threshold value to identify watersheds that exhibit signs of N saturation. Fenn et
al. (2015) specified the empirical CL for protecting against NO3 leaching in California
mixed conifer forests equal to the N deposition level at which this identified critical
surface water NO? concentration is exceeded (Fenn et al.. 2015; Fenn et al.. 2008). The
CL was derived using linear regression of stream water NO3 concentrations and
throughfall N deposition estimated during the winter high flow period at 11 locations in
the southern Sierra Nevada and San Bernardino Mountains. The calculated CL to protect
against NO3 leaching at the sites (6-71 kg N/ha/yr deposition) was 17 kg N/ha/yr (95%
CI 15-19 kg N/ha/yr).
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C.5.3.1.2.2. Semiarid Shrublands
Li et al. (2006) used the DayCent model to quantify water, C, and N fluxes for a
chaparral ecosystem in SEKI that received about 7.7 kg N/ha/yr of atmospheric N
deposition. Simulated NOs export and gaseous N emissions (mostly as nitric oxide
[NO]) generally agreed with observations. The model projections suggested that
increased N deposition would likely increase the flux of N from terrestrial ecosystems as
N03 in streams and gaseous NO. The authors concluded that the representations within
the DayCent model of N mineralization, runoff, and NO3 export in chaparral or similar
semiarid vegetation needed improvement.
Rao et al. (2010) used DayCent to estimate CLs of N deposition in JOTR, with focus on
the effects of N input on fire risk in creosote bush (Larrea tridentata) and pinyon-juniper
vegetation communities. Fire risk was expressed as the probability that annual biomass
production would exceed the risk threshold of 1,000 kg/ha of biomass available for
burning. Critical load was calculated as the N deposition at the point along the deposition
gradient where modeled fire risk began to increase exponentially. Mean estimated CLs
across multiple soil types, receiving precipitation of less than 21 cm/yr, were 3.2 and
3.9 kg N/ha/yr for creosote bush and pinyon-juniper plant communities, respectively.
Critical loads decreased (more nutrient-sensitive) with decreasing soil clay content and
increasing precipitation. The wettest areas that had low clay content (6 to 14%) had
estimated low CLs, as low as 1.5 kg N/ha/yr (Rao et al. 2010). These values fall at the
lower end of the CL range identified by Pardo et al. (2011c) and Pardo etal. (2011a) for
herbaceous vegetation in North American Deserts. Fire risks in the two vegetation types
were highest under moderately high N deposition (9.3 and 8.7 kg N/ha/yr, respectively);
above those deposition levels, modeled fire risk was influenced more by precipitation
amount than by N supply.
C.5.3.1.2.3. Arid/Semiarid
DayCent modeling results suggested a CL less than 8.2 kg N/ha/yr for low elevation
desert containing invasive Mediterranean grass (Schismus barbatus) and less than
5.7 kg N/ha/yr at higher elevation sites containing non-native red brome (Bromus rubens;
Rao et al.. 2010). Invasive non-native grass production in JOTR was simulated under
varying levels of N input and precipitation. Results suggested changing fire frequency.
Simulated fire risk was higher when N deposition was above 3 kg N/ha/yr, but then
stabilized at N deposition above 5.7 kg N/ha/yr in pinyon-juniper and at 8.2 kg N/ha/yr in
creosote bush scrub plant communities (Rao et al.. 2010). Model results of this study also
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suggested that fire risk is controlled more by precipitation than by grass productivity
(Allen and Geiser. 201IV
C.5.3.2. Aquatic
This section highlights recent monitoring, dose-response, and critical load studies of N
and S deposition to aquatic systems in SEKI, JOTR, and similar southern California
ecosystems.
C.5.3.2.1. Acidification
In the Sierra Nevada, both S and N deposition can contribute mobile acid anions (SO42 ,
NO? ) to watershed soil solution, streams, and lakes. Many aquatic and terrestrial
ecosystems in the Sierra Nevada are generally sensitive to acidification. Lakes in these
mountains are highly sensitive to impacts from acidic deposition because of the granitic
bedrock, thin acidic soils, large amounts of precipitation, coniferous trees, and dilute
surface waters (Melack and Stoddard. 1991; Melacketal.. 1985; McColl. 1981). Because
the levels of acidic deposition at the higher elevations have been relatively low, however,
acidification effects to date have been minimal.
Many lakes in SEKI have received N deposition high enough to cause limited chronic
N03 leaching, which can contribute to both acidification and eutrophication. Widespread
chronic lake or stream acidification has not occurred to any degree, although Sullivan
(2000) concluded that some episodic acidification has likely occurred. Acid anion
concentrations (mainly SO42 and NO3 ) in most high-elevation lakes were low in surveys
conducted during summer and fall, but higher during spring when snowmelt commonly
causes pulses of high NO3 concentrations in surface waters (Melacketal. 1989).
During the fall of 1985, about one-third of the lakes sampled by the Western Lake Survey
(WLS) in and near SEKI had acid neutralizing capacity (ANC) < 50 |icq/L. and two of
the lakes in the park had ANC < 20 (j,eq/L (Landers etal.. 1987). The possibility of
recovery from lake acidification during the period 1985-1999 was evaluated by another
chemical survey conducted by the U.S. Geological Survey (USGS) during the fall of
1999 (Clow and Sueker. 2000). Clow et al. (2003) reported that the resampled lakes were
generally low in ionic strength and had pH between about 6.0 and 7.0; the median ANC
was 59 (j,eq/L in SEKI and 32 |icq/L in YOSE located to the north. The observed lake
chemistry further confirmed the high sensitivity to acidification.
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Key acidification characterization and monitoring studies conducted in the Sierra Nevada
are listed in Table C-29. None of these studies are recent (post-2008) other than the study
of Clow et al. (2010) in YOSE. The current condition of these waters is probably similar
to what was found during previous decades with no additional recovery.
Table C-29 Example surface water acidification studies in Sequoia and Kings
Canyons National Parks and other Sequoia and Kings Canyons
National Parks-relevant areas in the southern California case study
region.
Study
Location
Time
Period
Focus
Clow et al. (2003) Clow
and Sueker (2000)
National parks in western
U.S., including SEKI
1999
Resurvey of WLS lakes
Clow et al. (2003)
Sierra Nevada region
1985 and
1999
Decrease in ANC in lakes in SEKI due partly
to climatic differences at time of sampling
Clow et al. (2010)
YOSE
2003
Multiple linear regression modeling to
predict NO3" concentrations and ANC in
lakes across the park
ANC = acid neutralizing capacity; N03 = nitrate; SEKI = Sequoia and Kings Canyons National Parks; WLS = Western Lake
Survey; YOSE = Yosemite National Park.
The weight of evidence suggests that many high-elevation lakes in SEKI have in the past
received N deposition high enough to cause some chronic NO, leaching. This can
contribute to both acidification and eutrophication. Widespread chronic lake or stream
acidification has not occurred to any degree, although Sullivan (2000) concluded that
some episodic acidification has likely occurred. Acid anion concentrations (mainly SO42
and NO? ) in most high-elevation lakes were low during summer and fall, but higher
during spring when there are commonly pulses of high NO3 concentrations in surface
waters during snowmelt (Melack et al. 1989). which is seldom sampled due to logistical
and safety constraints. It is not expected that acid-base chemistry has changed
appreciably in recent years.
The hydrology of alpine and subalpine ecosystems in the Sierra Nevada is controlled by
snowmelt because more than 90% of the annual precipitation in this region falls as snow.
The relatively small loads of acidic deposition can contribute to moderately high
concentrations of SO42 and NO3 in lakes and streams during the early phase of
snowmelt (Stoddard. 1995). Potential biological effects of acidic deposition on surface
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waters in the Sierra Nevada are most likely caused by acidification attributable to high
N03 concentrations, which tend to be episodic rather than chronic ("Wigington et al..
1990).
Climatic fluctuations that control the amount and timing of precipitation, melting of the
snowpack, growth of plants, depth to groundwater, and concentration by evaporation of
constituents in solution all influence soil and surface water chemistry. These factors
regulate interactions between air pollutants and the aquatic and terrestrial biological
receptors. Because conditions vary over time, many years of data might be required to
establish the existence of trends in episodic surface water chemistry (Sullivan. 2000).
Effects of acidification on vertebrate animals in the Sierra Nevada have not been
documented. However, declines and elimination of frogs and toads due to uncertain
causes have been documented throughout the western U.S., including in the national
parks in California. Possible impacts of air pollution on aquatic amphibians is noteworthy
because amphibians are especially sensitive to environmental change or degradation
(Bradford and Gordon. 1992; B1 an stein and Wake. 1990).
Arid and semiarid ecosystems in southern California are not known to be sensitive to
acidification from either S or N deposition. Precipitation to these ecosystems is limited.
There are relatively few surface waters, and it appears that they have appreciable acid
buffering capacity.
C.5.3.2.1.1. Empirical Studies
Empirical studies have shed light on dose-response relationships in lakes and streams of
southern California. Several new studies are addressed here. Heard et al. (2014)
investigated CLs to protect against lake acidification in the Sierra Nevada. An
experimental study by Kratz et al. (1994) investigated responses of macroinvertebrates.
Earlier studies of effects of N deposition in this region (mainly before 2008) addressed
aspects of water chemistry and the response of algae to nutrient addition. More recent
publications include the reviews of Baron et al. (2011a). Pardo etal. (2011c). and Fenn et
al. (2015).
Heard et al. (2014) investigated the likelihood that paleoreconstructed changes in ANC in
lakes of the Sierra Nevada had been caused by atmospheric deposition of SOr and NO,
during the 20th century. The deposition estimates suggested that the CL at Moat Lake
was exceeded in about 1920 and the chemical recovery started in about 1970. The initial
inferred decline in the ANC of Moat Lake occurred between 1920 and 1930. This time
period corresponded with estimated acidic deposition (SO42 + NO3 ) equal to about
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74 eq/ha/yr. This was taken by Heard et al. to be the critical load (CL) to protect this lake
against acidification. Diatom-reconstructed ANC values changed from near 100 |icq/L
before 1920 to near 60 |icq/L during the 1970s. Recovery of ANC after 1970 was
attributed by Heard et al. (2014) to decreased deposition of S. In addition, during the late
20th century, warmer air temperatures may have contributed to higher ANC via increased
weathering rates.
C.5.3.2.1.2. Modeling Studies
Some limited work has been conducted on modeling of aquatic critical loads using
steady-state approaches for acidity. Data from over 12,500 streams and lakes were used
by the Critical Loads of Atmospheric Deposition (CLAD) science committee of the
NADP (http://nadp.sws.uiiic.edu/committees/clad/) to model steady-state CLs for acidity
of surface waters based on multiple approaches for estimating base cation weathering.
Shaw et al. (2014) used the Steady State Water Chemistry (SSWC) model to estimate the
steady-state CL of acidity for 208 Sierra Nevada lakes. Study lakes were generally dilute
(mean specific conductance 8 (j,S/cm) and had relatively low ANC (mean 57 |icq/L).
Most were located in Forest Service wilderness areas, some in proximity to Sierra
Nevada national parks. Using a critical ANC limit of 10 (j,eq/L to protect aquatic biota
from effects caused by water acidification, the model predicted a CL of 149 eq/ha
(14.9 meq/m2) of acidity for Sierra Nevada watersheds situated on granitic bedrock. More
than one-third of the study lakes received acidic deposition that was in exceedance of the
estimated CL. The median study lake showed a CL exceedance of about 80 eq/ha
(8 meq/m2/yr). Based on these CL calculations, Shaw et al. (2014) concluded that high
elevation lakes in the Sierra Nevada have not fully recovered from effects of acidifying
deposition despite large decreases in S and N air pollution and reduced S deposition over
the last several decades.
C.5.3.2.2. Aquatic Nutrient Enrichment
There have been several studies of water chemistry dose-response relationships that
pertain to nutrient enrichment in the Sierra Nevada case study area. These have included
studies of N retention and release, critical loads, and N saturation. A meta-analysis of
lakes from 42 regions of Europe and North America concluded that atmospheric N
deposition has caused higher concentrations of NO, in lake water and increased
phytoplankton biomass (Bergstrom and Jansson. 2006). Bergstrom et al. (2005) found N
limitation in lakes that received N deposition below approximately 2.5 kg N/ha/yr,
limitation of N and P at N deposition between -2.5 and 5.0 kg N/ha/yr, and P limitation
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in lakes that had N deposition higher than about 5.0 kg N/ha/yr. These findings may be
relevant to remote lakes in the Sierra Nevada, including those in SEKI.
Sickman et al. (2002) reported yields and retention of dissolved inorganic N (DIN) at
28 high-elevation lakes, including those within SEKI. Net DIN retention was
1.2 kg N/ha/yr, an estimated 55% of annual DIN loading. Sickman et al. (2001)
calculated that the annual yield of N from the Emerald Lake watershed varied by a factor
of 8 (0.4 to 3.2 kg N/ha/yr), which explained 89 and 74% of the variation in DIN and
organic N, respectively. The N content of runoff was higher during years that
experienced high runoff and was lower during dry years. Increases in NO;, concentration
were larger during years with deep, late-melting snowpacks. Therefore, it is expected that
climate warming, with associated earlier snowmelt, might increase N retention in
high-elevation watersheds (Sickman et al.. 2001).
Nutrient enrichment of Sierra Nevadan lakes is not solely a function of N inputs.
Atmospheric P deposition can also be important. Sickman et al. (2003) proposed that
atmospheric P deposition and enhanced cycling of P due to climate change were the most
likely sources of the observed increase in P loading to the Sierra Nevada lakes. It is not
known why atmospheric deposition of P to these lakes has increased over time.
Possibilities include increased use of organo-phosphate pesticides (Keglev et al.. 2000)
and wind-blown transport of soils and dust that are high in P from the agricultural San
Joaquin Valley to the mountains (Sickman et al. 2003; Lesack and Melack. 1996;
Bergametti etal.. 1992).
Based on results of bioassay experiments and application of coarse nutrient limitation
indices, Sickman et al. (2003) concluded that phytoplankton growth in Emerald Lake in
SEKI during the early 1980s was limited by P supply. During subsequent years, in
response to increased atmospheric P input, the nutrient balance shifted into a pattern of
colimitation by N + P, and finally N limitation. Sickman et al. (2003) observed that the
total P concentration in the lake doubled from 1983 to 1999. Particulate C concentration
in the lake in 1999 was four times higher than the average during the period 1983-1998.
Together with the observed increase in total P in lake water, this suggested that
eutrophication had occurred during that time (Sickman et al.. 2003). It was proposed that
increased P loading to Sierra Nevada lakes decreased NOs concentration in lake water
and promoted N limitation. The increased P loading may have been due to increased
emissions and deposition of P and/or accelerated internal P cycling that might be caused
by changes in climatic conditions and the timing of snowmelt and runoff (Sickman et al..
2003; Johnson. 1998; Dettinger and Cavan. 1995).
Baron etal. (2011a) synthesized CLs of N deposition for protecting against nutrient
enrichment of high-elevation lakes. Relationships between NOs concentrations and N
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deposition suggested a CL near 2 kg N/ha/yr to prevent NOs leaching to lakes in the
Sierra Nevada. Fenn etal. (201 la) also summarized data reflecting the relationship
between atmospheric N deposition and stream NOs concentration, in this case for
chaparral vegetation in the San Dimas Experimental Forest in the San Gabriel Mountains
(Meixner et al.. 2006; Riggan et al.. 1994; Riggan et al.. 1985). Devil Canyon watershed
in the western San Bernardino Mountains (Meixner and Fenn. 2004; Fenn and Poth.
1999). and Chamise Creek in SEKI (Fenn et al.. 2003a; Fenn et al.. 2003c). Stream water
N03 concentrations in streams draining chaparral vegetation were among the highest
reported in North America, with concentrations in some streams higher than 200 |icq/L
(Fenn et al.. 201 la; Fenn et al.. 2003a; Fenn et al.. 2003c; Fenn and Poth. 1999; Riggan et
al.. 1994; Riggan et al.. 1985). Evaluation of N saturation in chaparral must also consider
the prevalence of fire in this ecosystem type because the stand-replacing fire interval is
only about 40 to 60 yr (Minnich and Bahre. 1995). Much of the atmospherically
deposited N that has accumulated in the litter and aboveground vegetation over the
intervening years is released suddenly to the atmosphere during fire. In contrast, much of
the accumulated N in the mineral soil generally remains on-site after a fire (Fenn et al.
2011a). and fire contributes to increased NO.? concentrations in stream water (Riggan et
al.. 1994; Anderson and Poth. 1989).
The recent work that has been conducted on aquatic ecosystems has focused mostly on
the Sierra Nevada region. Analogous nutrient enrichment work has not been conducted in
or around JOTR, in part, because there are few surface waters in that region.
C.5.3.2.2.1. Algae
Changes in nutrient supply can affect aquatic biota at all trophic levels, but algae are
perhaps most likely to show eutrophication effects from N deposition. Studies have
shown an increase in lake phytoplankton biomass in response to increases in N deposition
in the Sierra Nevada region (Sickman et al.. 2003). Wyoming (Lafrancois et al.. 2003b).
Sweden (Bergstrom et al.. 2005). and across Europe (Bergstrom and Jansson. 2006).
Increases in algal biomass have been associated with changes in algal assemblages that
favor certain species over others. A widespread increase in the relative abundance of
Asterionella formosa and Fragilaria crotonensis occurred in oligotrophic lakes across the
western U.S.; these changes have been documented from both lake sediment cores and
limnological surveys (Saros et al.. 2003; Wolfe et al. 2001; Interlandi et al.. 1999;
Goldman. 1988). In Lake Tahoe to the north of YOSE, there has been an increase since
about 1950 in the ratio of araphidinate pennate diatoms to centric diatoms. This was
largely due to increased abundance of Fragilaria crotonensis. This change in diatom
relative abundance was associated with higher N loading to the lake (Goldman. 1988).
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Jassbv et al. (1994) showed that atmospheric deposition supplies most of the N to Lake
Tahoe.
3 Because high-elevation lakes in the Sierra Nevada tend to be highly oligotrophic, small
4 changes in nutrient supply can affect algal productivity (Sickman et al.. 2003). Chamise
5 Creek in SEKI was reported to have high NOs leaching in response to throughfall N
6 deposition near 10 kg N/ha/yr, suggesting N saturation (Fenn et al.. 2003a; Fenn et al..
7 2003c). The U.S. Forest Service has suggested a policy threshold of 2 |icq/L for stream
8 N03 concentration in N limited ecosystems in the western U.S. This load has been
9 suggested as a tipping point to trigger management concern for possible over-enrichment
10 of aquatic ecosystems with N (Fenn et al.. 2011a).
C.5.4. Highlights of Additional Research Literature and Federal Reports since
January 2008
11 Key research literature published since January, 2008 is highlighted in Table C-30.
Table C-30 Key recent research literature focused on the case study region.
Publication
Focus
Allen and Geiser(2011)
N addition experiment in JOTR
Allen et al. (2009)
Soil N along depositional gradient in JOTR
Baron et al. (2011a)
Critical load and dose-response review
Bowman et al. (2011)
Critical loads for high-elevation vegetation
Bvtnerowicz et al. (2015)
Empirical N critical loads in San Bernardino Mts.
Clow et al. (2010)
Lake acid-base chemistry characterization in YOSE
Clark etal. (2013)
Loss of herbaceous plant species in response to N deposition
Cox etal. (2014)
Conversion from coastal sage scrub to grassland
Ellis etal. (2013)
Empirical critical loads
Esque et al. (2010)
N dynamics after fire in Mojave Desert shrubs
Fenn et al. (2008)
Effects of N on epiphytic lichens
Fenn etal. (2010)
Empirical critical loads and exceedances
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Table C-30 (Continued): Key recent research literature focused on the case study
region.
Publication
Focus
Fenn et al. (2011a)
Critical loads review
Fenn et al. (2015)
Critical loads review
Geiser et al. (2010).
Effects of N on lichens
Grulke et al. (2008)
Forest susceptibility to wildfire in San Bernardino Mts.
Heard et al. (2014)
Critical loads for lakes
Hurteau and North (2009)
Effects of N on a sensitive herbaceous plant species
Johnson et al. (2011)
Soil acid-base chemistry in mixed conifer watersheds
Jovan (2008)
Response of lichens to N
Kimball et al. (2014)
Effects of water and N on CSS following fire
McCallev and Sparks (2009)
Soil temperature effects on N loss in Mojave Desert
Pardo et al. (2011c)
Critical load and exceedance for nutrient N enrichment
Pasquini and Vourlitis (2010)
Net primary production in chaparral
Rao et al. (2009)
Effects of N deposition on mineralization
Rao et al. (2010)
N and fire effects on semiarid plant communities
Rao et al. (2011)
Critical loads for desert vegetation
Shaw et al. (2014)
Critical loads for lakes in Sierra Nevada
Stark etal. (2011)
Effects of N deposition and climate on Mojave Desert vegetation
Talluto and Sudina (2008).
Conversion of CSS to grassland
Vamstad and Rotenberrv (2010)
Changes in plant species composition after fire
Vourlitis (2012)
Response of semiarid vegetation to N and climate
Vourlitis and Fernandez (2012)
N response to N input in semiarid shrublands
Vourlitis and Pasauini (2008)
C and N dynamics in pre- and post-fire chaparral
Vourlitis and Pasauini (2009)
Dry season addition of N to CSS and chaparral
C = carbon; CSS = coastal sage scrub; JOTR = Joshua Tree National Park; Mts = mountains; N = nitrogen; YOSE = Yosemite
National Park.
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C.5.5. Summary
This case study focuses the ecosystems found in two National Parks in Southern
California, SEKI and JOTR. SEKI largely consists of forested and mountainous terrain in
and near the Sierra Nevada Mountains. JOTR is covered largely by desert and semiarid
land. Both are generally downwind of air pollution (mainly N) sources. The majority of
the information provided in this case study is applicable to ecosystems found within
SEKI. Limited research conducted in JOTR was found in the peer-reviewed literature. A
summary of studies relevant to evaluating CLs is shown by Figure C-42.
The Sierra Nevada Mountains, in which SEKI is located, contain many acid-sensitive
aquatic resources. Limited monitoring studies indicated that the current condition of these
waters is probably similar to that found during previous decades with no additional
recovery. Aquatic acidification effects to date on SEKI's condition have been minimal at
higher elevations due to low acidic deposition, and widespread lake or stream
acidification has not occurred to any degree although some episodic acidification has
likely occurred. There are expectations for N retention in high-elevation watersheds as
snowmelt changes temporally due to climate warming. Small changes in nutrient supply
to high-elevation, oligotrophic lakes in the Sierra Nevada can affect algal productivity
and increase abundance of Asterionella formosa and Fragilaria crotonensis (Saros et al..
2003). Amphibian decline and the possible association with air pollution is noteworthy.
However, one of the most pronounced effects of N deposition in the Sierra Nevada has
been shown to be an alteration of the lichen community which has CLs ranging from 3.1
to 5.2 kg N/ha/yr (Bowman et al.. 2011; Fenn et al.. 2008).
JOTR's arid and semiarid ecosystems are not known to be sensitive to acidification
because there is limited precipitation, few surface waters, and high acid buffering
capacity. N deposition may increase productivity of invasive grasses after fire, and
deposition and climate change may promote an altered fire cycle that does not allow
sufficient time for Joshua tree woodlands to re-establish between fires. It has been
suggested that N deposition may have already exceeded JOTR's critical load of
8.4 kg N/ha/yr for terrestrial plant communities (Pardo et al.. 2011c).
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a>
cc
o
a.
*o
c
~a
3
| Marine West Coast Forests-lichen protection (wet depositionl-Geiser et aL, 2010
JOTR-Wetted areas with low day conterrt-Rao et al., 2010
| Sierra Nevada Mtns.-Pr event NO 3- teaching-Fenn et al.. 2011a
JOTR-Creosote bush scrub-Fenn et at., 2008,201S
SEKI and YOSE-Lie hen protection-Elks et al., 2013; Pardo et al., 2011a
California-Protection of 7 vegetation rypevFenn et al., 2010
Sierra Nevada, mainly SŁKI-Protection of mycorrhiial fungi, lichens, herbaceous plants and forest vegetation
and to limit N03- leaching-Pardo et at, 2011b
| JOTR-Lichen and herbaceous plants-Pardo et al, 201 lb
Marine Wesl Coast Forests-Lichen protection (total deposition) -Geiser
et al., 2010
Western Sierra Nevada-Epiphytic lichen shift-Bowman et al, 2011, Fenn et al., 2008
San Bernadino Mtns.-Maed conifer forest-Bynerowicz et al., 20IS
JOTR-Pinyon-jumper-Fenn et al., 2008, 2015
| San Bernadino Mtns.-Lichen protection-Bynerowiu et al.. 201S
San Bernadino Mtns -Lichen protection in chapparal eeovystems-Fenn et al, 2010
California-Lichen protection; Lichen presence at 3 of S3 lichen survey sites et al., 2011a
JOTR-Higher elevation sites containing non-native red brome-Rao et ah, 2010
JQTR-Pinyon-juniper protect*on-Rao et al., 2010
~1 SCKi-increased the losses of N as N03- In streams and gaseous NO in chapparal or
similar semi-arid vegetation-ll et al., 2006
~
~
~
~
~
~
JOTR-lnvasive grasses-Allen et al., 2009; Allen and Geiser, 2011
JOTR-Creosote bush scrub communities-Rao et al., 2010
JOTR-Low elevation desert containing invasive Mediterranean grass
Raoetal., 2010
~ N. American deserts-Fire rtslc in I vegetation type-Pardo et al,
2011a, 2011b
~
N. Amencan deserts-Fire risk In l vegetation type Pardo et
al.. 2011a, 2011b
~ Western Sierra Nevada Oligotrophy lichen elimination-
Bowman et al., 2011
~ So. California-Coastal sage scrub-Cox
et al., 2014
~ So. California -Conversion from coastal sage
scrub to annual grassland-Co* et al. 2014
YOSE-Herbaceous species Hurteau and North, 2009
Semi-arid shrub land-Shrub growth and relative abundance of
sub-dominant shrubs and herbaceous ptanls-Pasquini and
Vourlitis, 2010
~
San Bernadino Mtns.-N03- leaching in chapparal
Fenn et al., 2010
~
San Bernadino MIns.-Protection against N03- leaching in
mixed conifer forests-Bynerowia et al., 2015
Sierra Nevada and San Bernadino Mtns. Protection against
N03- leaching Fenn et al.. 2008,2015
So. California-Mixed conifer forest-Bretner, 2007
JOTR-Creosote bush-Rao et al., 2010
JOTR-Pinyon-juniper-Rao et al.,
2010
"5 1 s g nr
N deposition, Kg N/ha/yr
~n—ir
tr
14 >14
ha = hectare; JOTR = Joshua Tree National Park; kg = kilogram; Mtns. = mountains; N = nitrogen; N. = north; NO = nitric oxide;
N03" = nitrate; SEKI = Sequoia and Kings Canyons National Parks; So = southern; YOSE = Yosemite National Park; yr = year.
Figure C-42
Continuum of critical loads in southern California case study area
and relevant surrounding region.
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APPENDIX D. OTHER ECOLOGICAL EFFECTS OF
PARTICULATE MATTER
Evidence for effects of particulate matter (PM) on ecological receptors include direct
effects of airborne PM on radiative flux and both direct and indirect effects of deposited
particles. In addition to nitrogen (N) and sulfur (S) and their transformation products
(discussed in Chapter 3-Chapter 12). other PM components such as trace metals and
organics are deposited to ecosystems and may subsequently impact biota. Direct effects
include alteration of leaf processes from deposition of PM ("dust") to vegetative surfaces.
Indirect effects encompass physiological responses associated with uptake of PM
components and alterations to ecosystem structure and function. Exposures can occur
directly to surfaces of vegetation (leaves, bark, twigs), by ingestion or via soil or water
through uptake by roots or other biological tissues. Bioaccumulation and
biomagnification of PM components can lead to effects at higher trophic levels. Direct
and indirect effects of PM on vegetation, alteration of the soil environment and fauna,
and evidence for effects at higher levels of biological organization (communities,
ecosystems) from PM deposition are evaluated in the context of what was known from
previous PM assessments (U.S. EPA. 2009a. 2004) and newly available studies.
D.1. INTRODUCTION
PM-associated components include N and S and their transformation products, trace
metals, organics, base cations, and salts. The primary non-N and S components include
trace metals and organics discussed further below. Base cations (especially Ca, Mg, and
K) from atmospheric deposition can help ameliorate the effects of acidic deposition
associated with oxides of N and S, although under very high base cation deposition, plant
health can be adversely affected (U.S. EPA. 2009a'). In certain areas, salts from sea spray
are a component of PM but are not covered in this assessment because they are not
anthropogenic. However, particulate salt may be added to an ecosystem from deicing salt
(U.S. EPA. 2009a).
Effects of PM on ecological receptors can be both chemical and physical (U.S. EPA.
2009a. 2004). As described in the 2009 Integrated Science Assessment for Particulate
Matter (2009 PM ISA), particulates that elicit direct and indirect effects on ecological
receptors vary in terms of size, origin, and chemical composition. Particle composition is
attributed to ecological outcomes to a greater extent than particle size (Grantz et al..
2003). PM-associated metals and organics are linked to responses in biota; however, the
heterogeneous nature of PM composition and distribution coupled with variability
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inherent in natural environments confound assessment of the ecological effects of
particulates.
Ecological effects evaluated in the 2009 PM ISA included direct effects on metabolic
processes of plants, contribution of PM to total metal loading resulting in alteration of
soil biogeochemistry and microbiology, effects on plant and animal growth and
reproduction, and the contribution to total organics loading resulting in trophic transfer.
Evidence reviewed in the 2009 PM ISA was sufficient to infer a causal relationship is
likely to exist between deposition of PM and a variety of effects on individual organisms
and ecosystems.
Uncertainties identified in the previous review of PM regarding ecological effects
included the difficulty in quantifying relationships between ambient concentrations of
PM and ecosystem response. Some components of PM may bioaccumulate overtime
making correlations to ambient levels difficult. PM deposition varies temporally and
spatially across the landscape, thus, confounding efforts to characterize the nature and
magnitude of effects. Organisms vary in their sensitivity and responses to PM. In natural
environments, the presence of multiple stressors makes it difficult to attribute observed
effects solely to PM.
Newly available information on the ecological effects of PM published since the 2009
PM ISA is summarized in the following sections along with key studies from previous
PM assessments (U.S. EPA. 2009a. 2004). Studies conducted in the U.S. are the focus of
this review; however, research from other countries is included that has advanced the
study of PM effects on biota, such as additional physiological effects of PM toxicity, new
techniques for PM assessment, and further characterization of effects on communities and
ecosystems.
D.2. DIRECT EFFECTS OF PARTICULATE MATTER ON
RADIATIVE FLUX
Direct effects of particles suspended in the atmosphere on radiative flux and subsequent
effects on vegetation were described in previous PM assessments (U.S. EPA. 2009a.
2004). Briefly, increased atmospheric particulates and aerosols can alter radiative flux by
both radiation attenuation and by changing the efficiency of radiation interception in the
vegetation canopy through conversion of direct to diffuse radiation (Hovt. 1978). Diffuse
radiation is more uniformly distributed throughout the vegetation canopy and can reach
leaves more evenly than direct radiation, increasing canopy photosynthetic productivity.
In a study reviewed in the 2009 PM ISA, decreased crop yield in China was associated
with reduction in solar radiation attributed to regional haze (Chameides et al.. 1999).
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More recent studies provide additional evidence of the role of PM in altering radiative
flux and plant response. In an assessment of aerosol effects on plant productivity in the
eastern U.S., increased canopy photosynthesis due to increases in diffuse radiation and
despite a simultaneous decrease in direct radiation due to light scattering by aerosols,
were observed on a regional scale (Matsui et al.. 2008). Surface downwelling solar
radiation was reduced by 14.9 W/m2 in 2000 and 16.0 W/m2 in 2001, while
photosynthesis and stomatal conductance increased simultaneously. In a recent study
from Beijing, China, the expression of plant proteins important to photosynthesis were
shown to be directly impacted by presence of aerosols and PM in the air column (Yanet
al.. 2014V Expression of plant ribulose biphosphate carboxylase/oxygenase (RuBisCO), a
key enzyme involved in plant photosynthesis, increased in areas with strong diffuse solar
radiation, (identified by measurement of aerosol optical depth and particles with
diameters of 0.1 to 1.0 |im). In the same areas, light-harvesting complex II protein and
oxygen-evolving enhancer protein decreased. These enzymes play a role in plant
responses to direct solar radiation when photosynthesis capacity is exceeded.
D.3. PARTICULATE MATTER DEPOSITION TO ECOSYSTEMS
Once airborne PM is deposited to aquatic or terrestrial systems, it can elicit additional
effects on ecosystem receptors. Large particles tend to be deposited near their source such
as mining, smelting, roadsides, and other industrial operations while smaller particles can
be transported long distances (Grantz et al.. 2003). Deposition to ecosystems can be in
the form of wet, dry, or occult deposition (U.S. EPA. 2009a; Grantz et al.. 2003). Once
deposited, PM-associated components may remain on biological surfaces or be
transferred between environmental compartments (e.g., water, soil, sediment, biota).
More often the chemical constituents drive the ecosystem response to PM, rather than
size class (U.S. EPA. 2009a; Grantz et al.. 2003). Exposure to a given mass concentration
of PM may lead to widely differing phytotoxic and other environmental outcomes
depending upon the particular mix of PM constituents involved. Deposition of the metal
and organic constituents of PM are discussed below, however, a rigorous assessment of
each chemical constituent (e.g., polyaromatic hydrocarbons [PAHs], mercury [Hg],
cadmium [Cd]) is not given. An overview of trace metals and organics and their
depositional effects in ecosystems was provided in the previous PM assessments (U.S.
EP A. 2009a. 2004) and are only summarized below.
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D.3.1.
Metals
All but 10 of the 90 elements that comprise the inorganic fraction of the soil occur at
concentrations of <0.1% (1,000 jxg/g) and are termed "trace" elements or trace metals.
Trace metals with a density greater than 6 g/cm3, referred to as "heavy metals" (e.g., Cd,
copper [Cu], lead [Pb], chromium [Cr], Hg, nickel [Ni], zinc [Zn]), are of particular
interest because of their potential toxicity to plants and animals. For example, plant
toxicity to trace metals is most frequently associated with Cu, Ni, and Zn (U.S. EPA.
2004). Some metals such as Zn, manganese (Mn), Cu, and iron (Fe) play important
physiological roles in trace quantities; however, other metals such as Hg, Cd, Cr, and Pb
have no known biological function. Although some trace metals are essential for
vegetative growth or animal health, they are all toxic in large quantities. Trace metals are
naturally found in small amounts in soils, ground water, and vegetation. They may enter
the ecosystems as both fine and coarse particles. Heavy metals preferentially associate
with fine particles. Trace elements exist in the atmosphere in particulate form as metal
oxides (Ormrod. 1984). Aerosols containing trace elements derive predominantly from
industrial activities. Once deposited to biological surfaces, metals can be taken up by
biota, accumulate in tissues, and elicit toxic effects. These responses are highly variable
across organisms. Only the bioavailable fraction is available for uptake by biota. In
plants, metal uptake is generally via soil to root transfer (McBride et al.. 2013) although
recent studies reviewed in Section D.4 provide evidence for foliar transfer of metals
following atmospheric deposition. The ecological effects of atmospherically deposited
Pb, a metal associated with PM, are included in the ISA for Pb (U.S. EPA. 2013b).
D.3.2. Organics
Organic compounds can be in gas phase or associated with particles (Grantz et al.. 2003).
Organic compounds that may be associated with deposited PM include persistent organic
pollutants (POP's), pesticides, semivolatile organic compounds (SOCs), PAHs, and flame
retardants among others (U.S. EP A. 2009a). Dry deposition of organic materials is often
dominated by the course fraction, but fine PM may act as a carrier for materials such as
pesticides. PAHs are widespread in the environment. Of the anthropogenically derived
PAHs, 8 are considered carcinogenic and 16 have been classified by the U.S. EPA as
priority pollutants. In general, high molecular weight PAHs are more toxic and have a
greater tendency to be associated with PM (Mesquita et al.. 2014a). They are common air
pollutants in metropolitan areas, derived from vehicular traffic and other sources. It is
known that PAHs and other organics can be transferred to higher trophic levels. Some
atmospheric contaminants such as POPs polybrominated diphenyl ethers (PBDEs) and
other brominated flame retardants have been shown to accumulate in biota at remote
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locations such as polar regions where long-range atmospheric transport is the likely
source (U.S. EPA. 2009a'). The Western Airborne Contaminants Assessment Project
(WACAP) summarized in the 2009 PM ISA provided evidence for airborne transfer and
bioaccumulation of organics to remote national parks and Class I areas (Landers et al..
2008). Seven ecosystem compartments: air, snow, water, sediments, lichens, conifer
needles, and fish were analyzed for a suite of contaminants with the goals of determining
where the pollutants were accumulating, identifying ecological indicators and assessing
the source of the air masses most likely to have transported the contaminants to the parks.
Overall, semivolatile organic compounds and metals were detected throughout park
ecosystems and biomagnification of organics through the food web indicated
contaminants are present at multiple trophic levels.
As reviewed in previous PM assessments, vegetation itself is an important source of
hydrocarbon aerosols (U.S. EPA. 2009a. 2004). Terpenes, particularly a pinene, (3 pinene,
and limonene, released from tree foliage may react in the atmosphere to form submicron
particles. These naturally generated organic particles contribute significantly to the blue
haze aerosols formed naturally over forested areas (U.S. EPA. 2004; Geron et al.. 2000).
D.4. EFFECTS OF PARTICULATE MATTER ON VEGETATION
Particles deposited to foliar surfaces may lead to both structural and functional alterations
in plants. PM may physically obstruct processes associated with the leaf surface or be
taken up across the cuticle and into the plant tissues affecting plant metabolic activities.
This section first considers direct impacts of PM deposition to vegetative surfaces. Next,
effects following uptake of PM components into plant tissue across leaf surfaces or root
uptake via soils are described. Uptake by plants can occur at the soil/plant interface and at
the air/plant interface (Krupa et al.. 2008). Once uptake occurs plant physiological
responses may include decreased gas exchange, altered metabolism and photosynthesis,
altered pigment and mineral content, and enzyme activity (Naidoo and Chirkoot. 2004).
There is some evidence that metals affect frost hardiness and impair nutrition (Taulaviiori
et al.. 2005; Kim et al.. 2003).
D.4.1. Vegetative Surfaces
As described in the 2009 PM ISA, foliar surfaces are covered with a waxy cuticle layer
that helps reduce moisture loss and short-wave radiation stress (U.S. EPA. 2009a). This
epicuticular wax consists largely of long chain esters, polyesters, and paraffins, which
accumulate lipophilic compounds. Organic air contaminants in the particulate or vapor
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phase can be adsorbed to, and accumulate in, the epicuticular wax of leaf surfaces. Low
solubility limits foliar uptake and direct heavy metal toxicity because trace metals must
be brought into solution before they can enter leaves or bark of vascular plants (U.S.
EPA. 2009a). Particles embedded in waxes may remain for extended periods of time and
remain associated with the leaf while other particles may be removed via precipitation,
wind or leaf-fall. Particle capture efficiency varies by plant species, and the role of
vegetative surface characteristics in trapping PM, especially in polluted urban
environments, is extensively reviewed in the literature. PM trapping by vegetation
depends on leaf shape, canopy structure, leaf surface wettability, presence of hairs,
properties of the epidermal layer and phyllotaxy (Popek et al.. 2013; Saebo et al.. 2012).
The 2009 PM ISA also reviewed studies that show effects of direct deposition of
particulates to aboveground plant organs including altered plant metabolism and
photosynthesis by blocking light, obstruction of stomatal apertures, increasing leaf
temperature and leaf surface injury (U.S. EP A. 2009a; Naidoo and Chirkoot. 2004;
Grantz et al.. 2003). Leaf surface pH can be altered by deposition of alkaline particles,
which can hydrolyze epicuticular surfaces (Grantz et al.. 2003). The diverse composition
of ambient PM and effects of other air pollutants confound characterization of the direct
effects of PM on foliar surfaces (Grantz et al.. 2003).
A number of recent studies published since the 2009 PM ISA, examine effects of PM
deposition to vegetative surfaces. For example, some have further characterized the
effects of particle size and composition on leaf surface processes. Following 60-day
experimental application of urban dust collected from roadsides in India to common
annual plant species (Abelmoschus esculentus, Celosia cristata, Coleus blumei,
Cyamopsis tetragonolobus, Gompherena globosa, Impatiens balsamina, Ocimum
sanctum, Phaseolus vulgaris, Solanum melongena, Zinnia elegans), scanning electron
micrographs of leaf surfaces indicated that larger particles piled up around the stomata
while finer particles clogged the stomatal openings (Rai et al.. 2010). In the applied dust,
about 75% was in the 2.5 to 10 |im size fraction, with course particles composing
approximately 10% of PM and ultra-fines comprising 15%. Experimental application of
PM (mono-metallic PM oxides cadmium oxide [CdO], antimony trioxide [Sb2C>3], and
zinc oxide [ZnO] and process PM enriched with Pb) to cabbage (Brassica oleracea) and
spinach (Spinacia oleracea) leaves, resulted in a coverage rate of particles on the leaf
surface estimated at approximately 2% following washing (Xiong et al.. 2014). More
particles were concentrated in stomatal apertures with up to 12% of the area occupied.
Presence of PM in stomata was correlated to particle size and solubility of the associated
metal oxides. Newer studies (Qguntimehin et al.. 2010; Qguntimehin et al.. 2008) support
observations of visible foliar injury reported in previous PM assessments, and some
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suggest that drought may affect the particle capture efficiency of trees, possibly leading
to decreased drought tolerance (Burkhardt and Parivar. 2014; Rasanen et al.. 2014).
DA.2. Foliar Uptake of Particulate Matter
As reported in the 2009 PM ISA, fine PM has been shown to enter the leaf through the
stomata and penetrate into the mesophyll layers where it alters leaf chemistry and
physiology (Da Silva et al.. 2006; Naidoo and Chirkoot. 2004). Organic compounds can
be deposited as particles on the leaves or be taken up through the cuticle or stomata in the
gas phase although these pathways are not well characterized for most trace organics
(Qguntimehin et al.. 2010). As reviewed in the 2009 PM ISA, for lipophilic POPs, such
as polychlorinated dibenzodioxins (PCDDs) and polychlorinated biphenyls (PCBs), the
air/plant response route generally dominates (Lee et al.. 2003; Thomas et al.. 1998). but
uptake through above ground plant tissue also occurs. The pathways depend on the
chemical and its physical properties, such as lipophilicity, water solubility, vapor
pressure, and Henry's law constant. Environmental conditions can also be important,
including temperature and organic content of soil, plant species, and the foliar surface
area and lipid content.
Eichert et al. (2008) demonstrated hydrophilic particle penetration into the substomatal
cavity of faba bean (Vicia faba) leaves. Since the 2009 PM ISA, development and
refinement of techniques such as micro x-ray fluorescence, scanning electron microscopy
coupled with energy dispersive x-ray microanalysis, and secondary ion mass
spectrometry have been applied toward characterizing particulate transfer from foliar
surfaces to the interior of the plant (Schreck et al.. 2014; Burkhardt et al.. 2012; Schreck
et al.. 2012). Repeated deliquescence and efflorescence of soluble PM may have the
effect of slowly advancing solutes into the stomatal pore where they may become
bioavailable (Burkhardt et al.. 2012). Recently, stomatal uptake of aqueous solutions was
confirmed by environmental scanning electron microscopy (Burkhardt et al.. 2012).
Deposited aerosols on leaf surfaces may alter surface tension and hydrophobicity
enabling stomatal liquid water transport and facilitating foliar uptake. Several studies
provide additional evidence that particles enter plant tissues through stomata openings
(Schreck et al.. 2012; Uzu et al.. 2010). Schreck et al. (2014) observed particles in
stomata and damage to guard cells from Pb-rich particles from a Pb recycling factory.
Other pathways of deposited metals to vegetative surfaces may include diffusion across
the cuticle (Schreck et al.. 2012; Uzu et al.. 2010). Nonstomatal uptake of atmospheric
Hg into plant leaves has recently been demonstrated in addition to stomatal pathways
(Stamenkovic and Gustin. 2009). Biogeochemical transformations were observed to
occur in metal-rich PM at the leaf surface (Schreck et al.. 2012). The role of the
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phyllosphere (i.e., the microbial communities on foliar surfaces) on the uptake and
chemical transformation of deposited particles and in promoting plant growth is an
emerging area of study; however, interactions associated with PM are not well
characterized at this time (Wevens et al.. 2015; Xiong et al.. 2014V
D.4.3. Particulate Matter Impacts on Gas Exchange Processes
In earlier assessments of ecological effects of PM, deposition of particles to vegetation
was known to interfere with gas exchange processes such as photosynthesis, respiration,
and transpiration (U.S. EPA. 2009a. 2004V Several new studies support observations
from previous PM reviews on exchange of oxygen and carbon dioxide across the leaf
surface. Most studies focus on the application of dust to leaves. A greenhouse study with
lettuce (Lactuca serriola) leaves showed decreased gas-exchange parameters (net
photosynthetic rate and stomatal conductance) and change in transpiration rate following
PM (dust from vehicular traffic with a dominance of fine particles) application to leaves
(Pavlik et al.. 2012). Fly ash dusting of 0.5 g/m/day to 1.5 g/m/day to rice reduced
photosynthesis, stomatal conductance and transpiration (Raja et al.. 2014).
Photosynthesis, transpiration rate, and water use efficiency was decreased in peach
(Primus persica) leaves dusted with cement kiln dust, and to a lesser extent with soil
dusting (Maletsika et al.. 2015). In a study of native and non-native plant species in
Argentina, Gonzalez et al. (2014) reported that gas-exchange parameters including
maximum assimilation rate, stomatal conductance, and transpiration rate were
significantly decreased in most plant species by ambient dust accumulation on leaf
surfaces compared to that in plants for which deposited dust was removed. Similarly,
decreased photosynthesis rate, increased stomatal resistance, and lower chlorophyll
content was observed with increased PM accumulation in plant species growing in the
city center of Warsaw, Poland, compared to a moderately clean environment (Przvbvsz et
al.. 2014). The photosynthetic apparatus of the lichen species Evenia prunastri was
significantly affected by dust enriched by calcium (Ca), Fe, and titanium (Ti) near a
quarry and cement factory in Slovakia (Paoli et al.. 2015). In open-top chamber
experiments, leaf net photosynthesis rate decreased in maize (Zea mays) plants exposed
to 50 ng Hg/m3 compared to plants exposed to 2 ng Hg/m3 (Niu etal.. 2014).
Photosynthetic rate and chlorophyll content were significantly reduced in cherry tomatoes
(Lycopersicon esculentum) misted with fluoranthene for 30 days to represent atmospheric
wet deposition to the leaf surface (Omintimchin et al.. 2010).
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D.4.4.
Plant Physiology
In the 2009 PM ISA, particulates were associated with phytotoxic responses, including
induction of phytochelatins, alteration of pigments, and changes in mineral content and
enzyme activity (U.S. EPA. 2009a'). Newly available studies support these findings.
Chlorophyll content as well as specific leaf area and relative water content of selected
tree species were significantly reduced by the greater dust load associated with a polluted
site in India compared to a low pollution location (Chaturvedi et al.. 2013). Decreased
leaf chlorophyll and increased phenol content was also observed in peach leaves with
accumulated cement or soil dust (Malctsika et al. 2015). In lettuce leaves, PM
application caused a depletion in amino acids that are metabolized during photosynthesis
as well as an increase in proline (Pavlik et al.. 2012). Proline and malondialdehyde
concentrations were elevated in maize leaves treated with Hg (Niu et al.. 2014). Recently,
the use of foliar fatty acid composition as an indicator of foliar (and root) metal uptake
was demonstrated with lettuce leaves exposed to PM from smelter emissions (Schreck et
al.. 2013).
D.4.5. Uptake of Particulate Matter by Plants from Soils
Plants can also uptake PM that has been deposited to soils. As reviewed in the 2009 PM,
ISA uptake from soils varies by the PM component and plant species (U.S. EPA. 2009a).
There was some evidence that shallow rooted plant species are most likely to take up
metals from the soil (Martin and Coughtrev. 1981). The ability of plants to take up
contaminants from soil and water has been applied toward environmental cleanup efforts,
a process known as phytoremediation (Hooda. 2007; Padmavathiamma and Li. 2007;
Clemens. 2006). Plants that are hyperaccumulators of metals are especially useful in
phytoremediation efforts (Prasad and DeOliveira. 2003).
Plants respond to high concentrations of metals in soil through a variety of mechanisms
and there are substantial differences among plant species in their response to heavy metal
exposure. As reviewed in the 2009 PM ISA, mechanisms of metal tolerance included
exclusion, excretion, genetics (Yang etal. 2005; Patra et al.. 2004). mycorrhizal
interactions (Gohre and Paszkowski. 2006). storage capability and accumulation
(Clemens. 2006). various cellular detoxification mechanisms (Gratao et al.. 2005; Hall.
2002). and chelation with phytochelatins (Memon and Schroder. 2009).
Since the 2009 PM ISA, additional studies have focused on the use of vegetation to
remediate sites with both organic and inorganic contaminants and the use of mycorrhizal
fungi and bacteria to promote phytoremediation (Section D.5.4). In addition, soil-bound
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PAHs associated with soil organic matter, historically thought to be generally not easily
available for root uptake, have been shown in recent studies to be readily adsorbed to root
surfaces, with some evidence showing translocation to the shoots (Desalme et al.. 2013).
D.4.6. Effects on Plant Growth
PM effects on plant growth reviewed in the 2009 PM ISA include reduced vigor and
impaired root development (U.S. EPA. 2009a'). In general, plant biomass is negatively
correlated with organics (Desalme et al.. 2013) and metal concentrations (Audet and
Charest. 2007). Inhibition of aboveground biomass was observed in lettuce leaves with
traffic-associated PM applied directly to vegetation (Pavlik et al.. 2012). Increased trace
metal concentration along with the decrease in biomass was measured in the treated
leaves. Decreased primary root elongation and shoot and root rates were observed in
tomatoes (Solanum lycopersicum) grown for 18 days in particulate matter with a nominal
mean aerodynamic diameter less than or equal to 10 ^m (PMio) collected from an urban
background site in Italy (Daresta et al.. 2014). Decreased chlorophyll a and increased
carotenoids in the exposed plants were noted along with increased reactive oxygen
species production in roots from the PMio substrate. Phenanthrene, a common PAH in
air, applied to soils via simulated atmospheric deposition in an exposure chamber was
shown to significantly decrease root length and shoot biomass of leek (.Allium porrum)
seedlings (Desalme et al. 2012). In a similar study, shoot biomass of red clover
(Trifolium pratense) exposed to atmospheric phenanthrene decreased by around 30%
while ryegrass (Loliumperenne) was unaffected (Desalme et al.. 201 la). No effects on
root biomass were observed in either plant. With phenanthrene exposure to red clover,
more carbon (C) was retained in leaves with decreased C allocation to stems and roots
(Desalme et al.. 201 lb).
Daily application of urban dust to common annual plant species for 60 days showed
reduction in plant growth, number of leaves, and leaf area (Rai et al.. 2010). Growth and
yield of rice was significantly influenced at higher rates of fly ash deposition due to
increased heat load and reduced intracellular carbon dioxide (CO2) concentration (Raia et
al.. 2014). Following dusting of the plants by fly ash at 0.5, 1.0, and 1.5 g/m2/day, a
significant decrease in grain yield of 12.3, 15.7, and 20.2%, respectively, was observed.
Recently, the effect of air pollutants on timing and budburst of vegetation has been
assessed in several studies (Jochner et al.. 2015; kozlov et al.. 2007). Timing of full
flowering of hazel (Corylus avellana) was found to be significantly related to PM in
ambient air in urban areas of Munich, Germany (Jochner et al.. 2015).
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These effects on phenological onset were also observed with ozone (O3), nitrogen dioxide
(NO2) and nitrate (NO3) in hazel and additional tree species in the same study. In a field
and greenhouse study in Russia with mountain birch (Betula pubescens), no impacts of
air pollution on phenology were observed between trees surveyed in proximity to a Ni-Cu
smelter and trees at further distance from the emission source (kozlov et al.. 2007).
D.4.7. Vegetation as Bioindicators
There is extensive literature on the use of trees, shrubs, mosses, tree bark and lichens for
estimating deposition (biomonitors) and indicating metal and organic exposure in
ecosystems [bioindicators; (U.S. EPA. 2009a) 1. Newer studies will be evaluated during
the upcoming PM National Ambient Air Quality Standards review.
D.5. EFFECTS OF PARTICULATE MATTER ON THE SOIL
ENVIRONMENT
As described in the 2009 PM ISA, the soil environment is one of the most dynamic sites
of biological interaction in nature (U.S. EPA. 2009a). The upper soil layers where
deposited particles accumulate are typically active sites of litter decomposition and plant
root uptake. Processes associated with the rhizosphere, the soil around plant roots that
mineral nutrients must pass through, may be affected by PM components. Soil-associated
microbial communities of bacteria, and fungal phyla such as actinomycetes and
basidiomycetes break down organic matter for nutrient cycling and make elements
available for plant uptake. Soil mycorrhiza, (fungi that colonize plant roots) form a
symbiosis to provide nutrients in exchange for carbon from the plant. The effects of
PM-associated organics and metals on the soil environment is largely dictated by
bioavailability to soil microflora and plant roots.
D.5.1. Bioavailability in Soils
Soils are heterogeneous and effects of PM deposition and subsequent bioavailability of
PM components depend on soil characteristics (e.g., pH, organic content). PM-associated
organics partition between the soil and the atmosphere based upon soil properties, such as
organic matter content, moisture, porosity, texture, and structure, as well as the
physiochemical properties of the pollutant, including vapor pressure and water solubility
(U.S. EP A. 2009a). These compounds may be taken up by roots or be associated with
organic matter (Fismes et al.. 2002). For heavy metals, accumulation in soil is influenced
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by a variety of soil characteristics, including pH, Fe, and aluminum oxide content;
amount of clay and organic material; and cation exchange capacity [CEC; (Hernandez et
al.. 2003)1. Bioavailability depends on metal speciation, soil pH, and degree of binding to
dissolved organic matter [DOM; (Sauve. 2001)1.
In the 2009 PM ISA, several models, isotopic studies, and sequential extraction methods
for determining metal bioavailability in soils were reported (Feng et al.. 2005; Collins et
al.. 2003; Shan et al.. 2003). However, actual measurement of biological effects is
generally regarded as the preferred criterion to assess bioavailability (Almas et al.. 2004).
Since the 2009 PM ISA, Biomet biosensors have been used to assess bioavailability of
metals in contaminated topsoils and subsoils (Almendras et al. 2009). Biomet biosensors
use genetically engineered bacteria that give off light when exposed to heavy metals that
are bioavailable. Almendras et al. (2009) also used sequential extraction to determine
solubility. At three sites near a smelter in Chile, they found that Cu and Zn had the
greatest solubility, arsenic (As) had less solubility, and Pb and Fe were the least soluble
of those heavy metals. Further, As was determined to be the most bioavailable, while Cu
and Zn were less bioavailable. The authors were unable to determine bioavailability of Pb
using the same technique.
The mobility of heavy metals, an indicator of potential bioavailability, was determined in
surface soil using sequential extraction (Svendsen et al.. 2011). In five sites at decreasing
distances from a smelter in Norway, Cd was determined to be most mobile and Cu the
least mobile (Svendsen et al.. 2011). Zn and Pb were moderately mobile. These results
were in contrast to the results of Almendras et al. (2009).
D.5.2. Soil Nutrient Cycling
In previous PM reviews, toxicity of metals, especially Zn, Cd, and Cu, to soil microflora
was found to reduce decomposition processes in soils and interfere with nutrient cycling
(U.S. EPA. 2009a). Changes to microbial enzymatic activity, soil basal respiration rate,
and soil microbial biomass were all associated with increased metal content in soils in
previous PM reviews. Studies reviewed in the 2009 PM ISA report increased leaf litter
accumulation near point sources.
Since the 2009 PM ISA, many studies showing the deleterious effects of PM on nutrient
cycling have been published. The effect of PM on the microbial coefficient of soils
contaminated by atmospheric emissions from an active mining and smelting complex was
determined in one study. The microbial coefficient, which is the ratio of microbial
biomass carbon to total organic carbon, was negatively correlated with metal
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concentrations (Shukurov et al. 2014). The microbial coefficient gives a measure of
substrate bioavailability.
A recent study demonstrated the role of atmospheric deposition of particulate heavy
metals in inhibiting C cycling. In this study, a cropping system was exposed to
atmospheric deposition while a similar cropping system was designed to exclude it by
using a greenhouse. Total organic carbon and water soluble organic carbon increased in
the exposed plots and decreased in the greenhouse plots; slow decomposition in soils
polluted with heavy metals could have caused the increased levels of total organic carbon
and water soluble organic carbon observed in the open plots (Pandev and Pandev. 2009).
New studies show decreases in enzyme activity and varying sensitivity of enzymes to
metal pollution. Soil dehydrogenase activity was diminished in polluted soils compared
to control soils (Boiarczuk and Kieliszewska-Rokicka. 2010). High soil dehydrogenase
activity indicates the living microbial community; additionally, dehydrogenase activity
increases with microbial biomass C, organic matter levels, and basal respiration
(Boiarczuk and Kieliszewska-Rokicka. 2010). In another study, enzyme activities of
alkaline phosphatase and fluorescein diacetate were greater in greenhouse treatments than
in open treatments exposed to deposition over the study period, showing that the potential
for hydrolysis was elevated in the greenhouse treatments (Pandev and Pandev. 2009). As
a result, organic C was mineralized to carbon dioxide and released from the soil more
quickly than it was in the treatments exposed to deposition. Qu et al. (2011) found that
enzyme activity was higher at sites farther from an active mining operation than at sites
close to it. However, urease activity was more affected by heavy metals than
dehydrogenase and phosphatase activity. Dehydrogenase contributes to many oxidative
activities, which degrade soil organic matter (Qu etal.. 2011). Phosphatase conducts
hydrolysis to convert organic phosphorus compounds into inorganic phosphorus
compounds, and urease converts urea into carbon dioxide and ammonia through
hydrolysis (Ou etal.. 2011).
A new study compared soil functional activity measured by the bait-lamina assay and by
the Biolog assay. Feeding activity was increased at the less polluted site compared to the
more polluted site (Boshoff et al.. 2014). Substrate utilization rate and richness of used
substrates were decreased in the more polluted site compared to the less polluted site after
2 and 6 days. On the other hand, diversity of used substrates at all plots resembled one
another by the end of the experiment. Feeding activity, substrate utilization rate, richness
of used substrates, and diversity of used substrates all decreased as As, Cu, and Pb
concentrations increased. The Biolog assay was a better indicator of soil functional
activity than the bait-lamina assay (Boshoff et al.. 2014). The bait-lamina assay indicates
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the feeding activity of soil fauna; the Biolog assay measures the metabolic use pattern of
the culturable microbial community.
The effects of PM on microbial activity and biomass have been widely studied in the
literature since the release of the 2009 PM ISA. Respiration was reduced by addition of
Cr and Zn (Akerblom et al.. 2007). The highest concentrations of Pb and molybdenum
(Mo) decreased respiration, as did higher levels of Ni and Cd. On the other hand, low
levels of Ni and Cd increased microbial respiration. In this study, metals were added to
soil from the humus layer of a Swedish forest in low, medium, and high doses (Akerblom
et al.. 2007). Similarly, in another study, microbial activity (for all metals except Cu)
decreased with increasing metal concentrations, and a negative correlation was also
determined between metal concentrations and microbial biomass (Anderson et al..
2009a'). Notably, microbial biomass levels were all similarly reduced among
contaminated sites compared to the control site, even though metal concentrations among
the contaminated sites varied. At the same time, microbial activity and biomass increased
with increasing concentrations of physicochemical variables (such as nitrate, magnesium
[Mg], and potassium [K]). Microbial activity, indicated by the amount of carbon
substrates used, was measured using the Biolog assay (Anderson et al.. 2009a'). Using
similar methods, Anderson et al. (2009b) found that microbial activity and biomass in
polluted sites were reduced compared to activity and biomass in the control site, prior to
the experiment, which consisted of adding metals to soils from the sites. Microbial
activity and biomass were lower at all sites after metal addition (Anderson et al.. 2009b).
In Azarbad et al. (2013). basal respiration and substrate-induced respiration increased
with organic matter and pH and decreased as the toxicity index (an indicator of heavy
metal contamination) increased. The toxicity index was more important in explaining
effects of heavy metal contamination on substrate-induced respiration than basal
respiration. In the same study, microbial biomass, represented by total phospholipid fatty
acids (PLFAs), increased as toxicity index decreased (Azarbad et al.. 2013). Chodak et al.
(2013) found that microbial biomass and basal respiration were mainly affected by
environmental variables, such as total nitrogen and organic carbon, and heavy metals
impacted them much less. In another study, microbial biomass C and substrate-induced
respiration were lower in open treatments exposed to atmospheric deposition than in
greenhouse treatments as time progressed (Pandev and Pandev. 2009).
D.5.3. Soil Community Effects
At the time of the 2009 PM ISA, toxicity of heavy metals to soil-associated microbes
were well characterized in laboratory studies, but less was known about the relative
sensitivity of fungi, bacteria, and actinomycetes and community-level changes. New
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techniques described in the 2009 PM ISA, such as the use of phospholipid and
nucleic-acid biomarkers (Jovnt et al.. 2006). have enabled researchers to better
characterize microbial community composition and biodiversity. In a recent study,
tolerance of microbial communities to heavy metal PM has been shown to vary with
ecosystem type. Culturable bacterial communities in contaminated meadow soils
experienced greater tolerance to pollution, but the culturable communities in
contaminated forest soils did not (Stefanowicz et al.. 2009). The authors suggest that
similarities between the degree of heavy metal contamination in control and polluted
forest soils, caused by increased pH in polluted soils, may have contributed to the lack of
tolerance of bacterial communities in forest soils because pH influences bioavailability of
metals. Additionally, the absence of increased tolerance in forest soils might have been
caused by a lack of variation in metal sensitivity of bacterial species.
The impact of metal-associated PM on abundance of microbes has been studied in
recently published papers. Total numbers of silver birch (Betulapendula) seedling root
tips colonized by mycorrhizae decreased in seedlings grown in polluted soils relative to
those in control soil (Boiarczuk and Kieliszewska-Rokicka. 2010). In another study,
culturable bacteria were more abundant at the sites farther from an active mining
operation than at the sites close to it (On etal.. 2011). Lenart-Boron and Wolnv-koladka
(2015) found no correlation between metal concentrations and abundance of microbial
groups (mesophilic bacteria, fungi, actinomycetes, and Azotobacter spp.). The effects of
PM from heavy metals on the metabolic quotient of soils that were contaminated by an
active mining and smelting complex in Uzbekistan have been studied recently in the
literature. Metabolic quotient, an indicator of the influence of environmental variables on
microbial communities, increased with increasing heavy metal concentrations (Shukurov
et al.. 2014).
Recently published studies show that the response of soil-associated microbial
community structure and function to heavy metal PM varies. Akerblom et al. (2007)
found that most metals altered community structure in a similar way. Phospholipid fatty
acids (PLFAs) can indicate microbial community structure, and different PLFAs are
associated with different groups of microbes [e.g., fungi, bacteria; (Akerblom et al..
2007)1. Relative abundance of PLFAs associated with Gram-positive bacteria had a
positive relationship with metal concentrations, but relative abundance of PLFAs
associated with Gram-negative bacteria had a negative relationship with metal
concentrations. The relative abundance of actinomycetes PLFAs had a positive
relationship with metal concentrations. The reaction of the relative abundance of certain
PLFAs found in Gram-negative bacteria varied depending on exposure to particular
metals, and the reaction differed most between Cr and Cd. Relative abundance of a fungal
PLFA increased with increasing Cr and Zn concentrations (Akerblom et al.. 2007). Likar
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and Regvar (2009) determined that ascomycetes fungi were more common in polluted
plots, and ectomycorrhizal ascomycetes mainly comprised one taxonomic group. On the
other hand, basidiomycetes fungi were more common in control plots and in plots that
were less contaminated, and ectomycorrhizal basidiomycetes were more diverse than
ectomycorrhizal ascomycetes, comprising several taxonomic groups. Dark septate
endophytes in the ascomycete group were common in polluted plots and comprised
several taxonomic groups (Likar and Regvar. 2009). The increased number of DNA
sequences from a particular dark septate endophyte genus (Phialophora) in plots that
contained greater concentrations of Cd and Pb suggests that this genus could help goat
willow (Salix caprea) take up more nutrients under metal stress (Likar and Regvar.
2009); however, the authors did not actually measure nutrient uptake of plants in this
study. Anderson et al. (2009b) found that before the experiment, which consisted of
adding metals to soils with varying levels of initial contamination by an abandoned
smelter in Anaconda, MT, the structure and function of the microbial community from
each site differed from one another, and after the experiment, the communities remained
structurally and functionally different.
In another study, diversity and evenness of soil fungi communities in forest litter and
those of arbuscular mycorrhizal fungi communities in forest litter were lower in a site
polluted by emissions from an active copper smelter than they were in the reference site;
community structure of soil fungi in the polluted site was not similar to that in the control
site (Mikrvukov et al.. 2015). Spatial autocorrelations existed in both the control and
polluted sites for soil fungi communities, but the spatial structure of the communities in
the two sites did not resemble one another. Arbuscular mycorrhizal fungi (AMF)
community structures at control and polluted sites did resemble one another. Spatial
autocorrelation only existed in the polluted sites for arbuscular mycorrhizal fungi
communities (Mikrvukov et al. 2015). Spatial heterogeneity tends to be greater in
contaminated areas than in uncontaminated areas (Mikrvukov et al.. 2015). Qu et al.
(2011) found that microbial community diversity increased as distance from an active
mining operation increased. In a different study, ecophysiological index values at two
long-term contaminated sites were substantially high for oligotrophs and copiotrophs
(Margesin et al.. 2011). Both sites contained bacterial communities with high Shannon
diversity index values (a common index used to characterize species diversity), and the
metabolically active groups at both sites were Proteobacteria and Actinobacteria
(Margesin et al.. 2011).
Recent studies have shown the effects of environmental variables in comparison to the
effects of heavy metal associated PM. In a study by Anderson et al. (2009a). microbial
species richness was influenced by physicochemical characteristics (Mg, CEC, Ca,
ammonium [NH4]), but was not affected at all by metal concentrations; however,
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community structure in polluted sites was altered by metal concentrations compared to
control sites. In a different study, toxicity index, which represents the degree of heavy
metal pollution, had a positive impact on functional diversity of fungi, and nutrient status
had a negative impact on functional diversity of fungi (Azarbad et al.. 2013V On the other
hand, toxicity index did not influence functional diversity of bacteria, but functional
diversity increased with pH. PLFAs that represent Gram-positive bacteria increased with
toxicity index, while the PLFA associated with fungi decreased as toxicity index
increased. Organic matter and pH were factors that influenced PLFAs as well as metal
contamination (Azarbad et al. 2013). Chodak et al. (2013) determined that pH had the
largest impact on bacterial community diversity, but heavy metals also modulated
diversity. Bacterial community structure was mainly affected by pH. Although pH was
the main factor controlling microbial community structure, heavy metals also influenced
microbial community structure (Chodak et al.. 2013).
In addition to soil microbial communities, effects of metal-associated PM on other soil
fauna has been recently published. Shiikurov et al. (2014) found that abundance of
nematodes was greater at the plots further from the emission source; similarly, abundance
of nematodes, number of bacterivorous nematodes, and number of omnivorous predator
nematodes were negatively correlated with heavy metal concentrations.
The harmful effects of organic PM on soil microbes have been published in recent
studies. AMF infectivity in the top soils was reduced compared to control soils when
exposed to phenanthrene for 2 weeks (Desalme et al.. 2012). In this study, phenanthrene
was pumped into an exposure chamber containing soils to simulate atmospheric
exposure. However, in another study using a similar experimental setup, mycorrhizal
symbiosis in red clover was similar in control and polluted chambers, and mycorrhizal
symbiosis in both treatments remained efficient (Desalme et al.. 201 la). In the same
study, Rhizobium nodule (bacteria) symbiosis in clover was lower in the upper layer of
polluted soil than in the upper layer of control soil (Desalme et al.. 201 la).
D.5.4. Soil Microbe Interactions with Plant Uptake of Particulate Matter
In the 2009 PM ISA, the role mycorrhiza in modulating toxicity of deposited metals was
reported. This role includes improving nutrient uptake and decreasing metal uptake
(Vogel-Mikus et al. 2006; Nogueira et al.. 2004; Berthelsen et al. 1995) in the plant by
acting as a sink for metals (Carvalho et al.. 2006; Berthelsen et al.. 1995). often
preventing the metals in the roots from allocation to shoots (Spares and Siqueira. 2008;
Zhang et al.. 2005; kaldorf et al.. 1999). In contrast, other studies reviewed in the 2009
PM ISA showed that mycorrhizae may facilitate accumulation of metals in plants and
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enhance the translocation of metals from the root to the shoot (Zimmer et al.. 2009;
Citterio et al. 2005; Vogel-Mikus et al.. 2005). There was limited evidence for bacteria
and mycorrhiza working together to improve plant tolerance to metals (Vivas et al.. 2006;
Vivas et al.. 2003).
Since the 2009 PM ISA, additional studies show mycorrhizae modulates metal uptake in
plants. Seedlings grown in polluted soil with mycorrhizae preferentially sequestered
heavy metals (Cu and Pb) to the roots instead of the shoots (Boiarczuk and Kieliszewska-
Rokicka. 2010). The ratio of mycorrhizal fine roots to nonmycorrhizal fine roots was
lower for silver birch seedlings grown in polluted soils (mixture and fully polluted soil
near a copper foundry in Poland) than for tree seedlings grown in control soil; however,
the mycorrhizae were still able to affect metal uptake by the plants.
Nonmycorrhizal microbes (e.g., bacteria, fungal hyphae, spores from saprobes) may also
decrease metal uptake by plants. In a greenhouse experiment using soils collected at
varying distances from abandoned smelters in the U.S., wavy hairgrass (Deschampsia
flexuosa) plants grown in soils with high amounts of contamination and treated with
nonmycorrhizal microbial wash accumulated less Zn in the shoots compared to plants
without the nonmycorrhizal microbial wash (Glassman and Casper. 2012). In contrast,
although there was an AMF treatment in this experiment, AMF did not impact the
amount of Zn in the shoots of plants.
AMF and nonmycorrhizal microbes such as plant growth promoting bacteria can
contribute to phytoremediation of polluted soils; much new research on these topics has
been published since the release of the previous ISA (C'abral et al.. 2015; Meier et al..
2012; Gamalero et al.. 2009).
D.5.5. Effects of Particulate Matter on Physical Properties of Soils
PM can affect physical properties of soils, such as bulk density, porosity, and water
holding capacity. Changes in these properties can decrease plant growth and yield. This
topic was not discussed in the previous PM ISA. However, new studies on the effects of
PM on physical properties of soils have been published since the release of the previous
ISA. Pandev and Pandev (2009) found that bulk density was elevated during the study
period in an experimental cropping system open to deposition. Porosity and water
holding capacity in the open system were diminished over the same time period. The
opposite was the case for the experimental cropping system closed to deposition. The
authors suggest that the influx of deposition of particulate matter during the study period
caused a rise in bulk density, and the elevated bulk density caused the decrease in
porosity and water holding capacity (Pandev and Pandev. 2009).
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D.6.
EFFECTS OF PARTICULATE MATTER ON FAUNA
Toxicity of PM to fauna varies depending upon the PM composition, concentration,
bioaccessibility and bioavailability, biological species sensitivity, and organism lifestage.
The bioavailability or bioaccessibility of PM-associated trace metals and organics is
dependent upon the physical, chemical, and biological conditions under which an
organism is exposed at a particular geographic location. Organisms may have
detoxification mechanisms that increase tolerance to stressors. Pathways of PM exposure
to aquatic and terrestrial organisms include ingestion, absorption, and trophic transfer.
Several types of studies have been used to assess effects of PM on terrestrial and aquatic
organisms, including laboratory bioassays and field studies.
D.6.1. Laboratory Bioassays
The use of ecotoxicity assays to screen and assess PM effects on biota has expanded
considerably since the 2009 PM ISA. All but one of the new studies used PM from
outside of the U.S and the pollutant mix may, therefore, not be representative of
exposures occurring in the U.S. These studies are reported below. However, several
caveats must be noted in correlating effects in these studies to natural environments.
Extracts of PM from air filters may not be representative of exposure routes and
conditions in aquatic and terrestrial habitats (kovats et al.. 2012). Bioavailability of PM
in the natural environment is affected by many factors not represented in bioassay
techniques. Furthermore, because these studies include a mix of PM constituents, it may
be difficult to identify the active component(s). Results from toxicity assays using PM
extracts (such as dichloromethane, methanol, or water extracts) should be interpreted
with caution because additional compounds might remain unextracted, underestimating
or overestimating the whole PM toxicity to aquatic organisms (Mcsquita et al.. 2014a;
kovats et al.. 2012).
Recently the Vibrio fischeri bioluminescence inhibition test (Microtox®) has been applied
as an ecotoxicological screening tool for PM (Roig etal.. 2013; kovats et al.. 2012). In
this bioassay, the rate of inhibition of light emission from the bacteria is measured after
exposure to a pollutant. In aqueous PM extracts from air filters from urban, rural, and
industrial areas of Catalonia, Spain, no correlation was observed between inhibition of
light emission in the in vitro test and PMio concentration (Roig et al. 2013). Metals
(except Cr) and PCDD/F congeners in the samples were significantly correlated to the
bioassay results, indicating that PM composition, rather than concentration, explains the
experimental observations.
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Toxicity of PM extracts to aquatic biota have been assessed in several studies published
since the 2009 PM ISA. Acute (24-hr) toxicity of ambient PM with a nominal mean
aerodynamic diameter less than or equal to 2.5 |im (PM2 5) extracted from air filters in
Atlanta, GA to the freshwater rotifer Brachionus calyciflorus was assessed by Verma et
al. (2013). Toxicity of methanol extracts was much higher than that of water extracts, and
there were no conclusive associations of rotifer toxicity with PM chemical composition.
In zebrafish (Danio rerio) embryos exposed to organic extracts of PM samples from coal-
burning particles in a semirural area in Italy, cytochrome P4501A gene expression was
significantly induced (Olivares et al.. 2013). In another zebrafish study, urban PM had
adverse developmental effects (spinal deformations, malformation of swim bladder, etc.)
on embryos (Mesquita et al.. 2014b). These observations correlated with PAH content of
the PM samples. In a comparison of PM in rural and urban air particles collected in
Spain, induction of AhR signaling pathway correlated with PAH concentrations in all
locations (Mesquita et al.. 2015). The greatest dioxin-like activity and embryotoxicity
was observed in the finest PM fraction (<0.5 |im). During the winter, maximal assay
activity occurred in the rural samples due to biomass burning emissions.
A series of in vivo studies on effects of PM25 on the nematode Caenorhabditis elegans
have indicated a suite of responses in this organism to PM exposure. Zhao et al. (2014b).
observed altered development, lifespan, reproduction, locomotion, and defecation
behavior associated with long-term exposure to PM2 5 collected from a traffic-dense area
in Beijing, China. PM components included S, Cd, Pb, Zn, Cu, and PAHs. The insulin
signaling pathway was identified as possible a molecular target of the traffic-related
PM2 5 in nematodes (Yang et al.. 2015). In nematodes exposed to PM2 5 in coal ash,
altered functioning of neurons that control defecation behavior and gene expression
patterns required for control of oxidative stress were reported, as were effects on
development, reproduction, locomotion behavior and lifespan (Sun et al. 2015b).
Elemental analysis of the PM from coal combustion indicated Fe, Zn, and Pb were the
most common metals followed by As, Cd, Cr, Cu, and Ni. Fluoranthene, pyrene, and 12
additional PAHs were detected in the PM2 5 in the coal ash.
Earthworms often constitute a large percentage of soil animal biomass and are considered
to be relatively sensitive bioindicators of soil contamination by metals and organics.
Several studies in the 2009 PM ISA reported uptake of trace metals and organics by
earthworms (Hobbelen et al. 2006; Parrish et al.. 2006). while fewer studies reported
responses due to atmospheric deposition of PM (Massicotte et al.. 2003). Earthworms can
also modify PM bioavailability and bioaccessibility in soils through bioturbation. For
example, presence of earthworms was shown to significantly increase soil-to-plant
transfer of metals via modifications to soil and increased bioaccessibility of metals to
roots (Leveque et al.. 2014).
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In a recent study, earthworms (Eisenia andrei), directly exposed to powder from PMio
quartz filters (24.9 mg/g PMio and 14 jxg/g PAHs) in artificial soil for a range of final
concentrations from 15 jxg/g to 30 jxg/g PMio, showed genotoxic effects (Vemile et al.
2013). DNA damage measured by comet assay was observed starting at 22.5 jxg/g PMio
(0.012 jxg/g PAHs) in samples collected from an urban site in Italy.
D.6.2. Wildlife as Biomonitors of Particulate Matter
In the 2009 PM ISA, several studies were reviewed where resident biota was used to
biomonitor urban air pollution including PM. For example, snails (Helix sp.) accumulate
trace metals and agrochemicals and can be used as effective biomonitors for urban air
pollution (Renoli et al.. 2006; Viard et al.. 2004; Beebv and Richmond. 2002).
Demonstrated biological effects include oxidative stress, growth inhibition, impairment
of reproduction, and induction of metallothioneins, which are involved in metal
detoxification (Regoli et al.. 2006; Gomot-De Vaufleurv and Kerhoas. 2000).
Biomonitoring using aquatic species was also reported. For example, Coelho et al. (2006)
investigated Hg concentrations in Scrobiculariaplana, a long-lived, deposit-feeding
bivalve in southern Europe. The use of sentinel species to detect the effects of complex
mixtures of air pollutants is of particular value because the chemical constituents are
difficult to characterize, exhibit varying bioavailability, and are subject to various
synergistic effects.
New biomonitoring studies of PM effects on biota include vertebrate and invertebrate
organisms. Use of the land snail Helix aspersa as a biomonitor for PAHs associated with
atmospheric particles in Porto Alegre, Brazil indicated, in general, that higher
genotoxicity in this indicator organism was associated with PM size fractions
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metabolic rate, and the main route of exposure to urban air is through inhalation and
intake of contaminated food particles. Assay results were compared with measurements
of contaminants in the urban air (carbon monoxide [CO], PMio, NO2, O3, SO2, benzene
[CeHe], PAHs in PM2 5), and a positive correlation with PAH and protoporphyrin was
observed along with a positive correlation between O3 and DNA damage index (Sicolo et
al.. 2010; Sicolo et al.. 2009). Feathers, lung, liver, and kidney tissues were sampled from
pigeons in two urban areas in the U.S. (Glendora, CA and Midland, TX) to evaluate Hg
exposure (Cizdziel et al.. 2013); however, no significant differences were observed
between the two locations.
Several species have been evaluated as indicators of metal pollution from a long-term
monitoring site near a former Cu-Ni smelter in Haijavalta, Finland. Metal concentrations
in bird feces were quantified at the site to measure exposure via atmospheric deposition;
however, measured decreases in the excrement did not directly reflect emission patterns
(Berelund et al.. 2015). The authors suggest this is due to uptake of metals from food
items in contact with contaminated soils. Plasma carotenoid levels measured in the birds
on the site were not directly correlated to metal pollution or nesting survival (Ecva et al..
2012). Leg deformities of oribatid mites were also evaluated as a biomonitor but
determined to be an unreliable indicator of heavy metals in soil at the site (Eeva and
Penttinen. 2009).
D.6.3. Biomagnification
Biomagnification of PM-associated metals and organics was reviewed in the 2009 PM
ISA and are summarized here. The basic understanding of the process of
biomagnification has not appreciably changed since the previous assessment. As reported
in the 2009 PM ISA, biomagnification is the progressive accumulation of chemicals with
increasing trophic level (Leblanc. 1995). At the time of the 2009 PM ISA,
biomagnification had been demonstrated for a few trace metals in terrestrial and aquatic
systems (U.S. EPA. 2009a). Plant uptake is often the first step for a metals to enter higher
levels of the food web. Consumers of vegetation may often receive heavy loading of
metals from their diets. Metals may also bioaccumulate in some species, and tissue
concentrations are magnified at the higher trophic levels. Organic Hg is the most likely
metal to biomagnify, in part because organisms can efficiently assimilate methylmercury
and are slow to eliminate it I(Croteau et al.. 2005; Reinfelderet al.. 1998); Chapter 121.
There is also evidence that the trace metals Cd, Pb, Zn, Cu, and selenium (Se)
biomagnify.
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Biomagnification of organics has been extensively documented in aquatic and terrestrial
ecosystems, and these compounds are detected in biota at remote locations due to
long-range atmospheric transport processes (U.S. EPA. 2009a). Organics, such as PAHs,
can be transferred to higher trophic levels, including fish, and this transfer can be
mediated by aquatic invertebrates in the fish diet (U.S. EPA. 2009a). In high mountain
lakes, atmospheric inputs dominate as sources of contamination. In addition, such lakes
tend to have relatively simple food webs. In a study reviewed in the 2009 PM ISA, Vives
et al. (2005) investigated PAH content of brown trout (Salmo trutta) and their food items.
Total PAH concentrations tended to be highest in organisms that occupy littoral habitats,
and lowest in pelagic organisms.
The study of trophic transfer and biomagnification is limited by the difficulty in
discriminating food webs and the uncertainty associated with assignment of trophic
position to individual species (Croteau et al.. 2005). Use of stable isotopes can help to
establish linkages. However, it is difficult to determine the extent to which
biomagnification occurs in a given ecosystem without thoroughly investigating
physiological biodynamics, habitat, food web structure, and trophic position of relevant
species. Thus, developing an understanding of ecosystem complexity is necessary to
determine which species are at greatest risk from toxic metal exposure (Croteau et al..
2005).
D.7. EFFECTS OF PARTICULATE MATTER ON ECOLOGICAL
COMMUNITIES AND ECOSYSTEMS
Evidence for PM effects on higher levels of biological organization is primarily from
field studies conducted in proximity to point sources, such as smelters, mining, and other
industrial sources. These areas where PM deposition decreases from the source have been
assessed through ecological gradient studies. Several long-term monitoring studies have
been conducted on ecosystem responses to atmospheric deposition of metals, including
the Haijavalta smelter in Finland where metal-rich dust emissions have decreased by 99%
during the 23-year study period (Eeva and Lehikoinen. 2015). Additional evidence for
PM effects on ecological communities include studies from urban areas and model
microecosystems.
D.7.1. Gradient Effects near Smelters
In the 2009 PM ISA, multiple studies were reviewed that were conducted near a Cu-Ni
smelter in Haijavalta, Finland. These studies documented effects on multiple species
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operating at different trophic levels (kiikkila. 2003; Helmisaari etal.. 1999; Malkonen et
al.. 1999; Pennanen et al.. 1996). The species composition of vegetation, insects, birds,
and soil microbiota changed, and tree growth was reduced 4 km from the smelter. Within
1 km, very few organisms were documented (Kiikkila. 2003).
Since the 2009 PM ISA, additional studies have been published from the long-term
monitoring of the ecological communities near the Cu-Ni smelter site in Haijavalta,
Finland. Several studies in passerine birds (pied flycatcher [Ficedula hypoleuca\ and
great tit [Parus major]) show some biological recovery and a reduction in metal
concentration with decreased atmospheric emissions over time, even though metal levels
in tissues remain high in birds near the smelter, likely due to contamination of soils and
food items (Berglund et al.. 2012; Berglund et al.. 2011). Similarly, tissue levels in pied
flycatchers remained high near a smelter in Northern Sweden even after a 93 to 99%
reduction in metal emissions (Berglund and Nvholm. 2011). Corresponding to decreased
metal pollution at Haijavalta, breeding parameters in pied flycatchers and great tits have
improved since the 1990s. However, clutch size and fledgling number remain below
those of birds from a reference area (Eeva and Lehikoinen. 2015; Eeva et al.. 2009).
Interruption of egg laying was assessed in passerine birds at the Haijavalta Smelter site
and was attributed to both cold weather and pollution (Eeva and Lehikoinen. 2010).
These laying gaps occurred with greater frequency, and most commonly at the beginning
of the laying sequence, close to the smelter. The authors suggest that heavy metals at the
site interfere with Ca availability and metabolism during the breeding season when extra
Ca is needed for egg shell formation and growth.
Eeva et al. (2010) sampled land snail shells from pied flycatcher nests along the
Haijavalta smelter pollution gradient to assess effects of air pollution on shell mass,
abundance, and diversity of land snail communities. The snails represent an important
source of Ca for the birds, especially for egg shell formation and development of
nestlings. Shell size decreased near the smelter, indicating snail growth was also
impacted at the most highly polluted areas. The highest diversity, largest size, and
greatest abundance of snail populations were observed in the moderately polluted areas
compared to snails in the vicinity of the smelter and in remote unpolluted areas.
Recent literature continues to show a gradient of response in vegetation to trace metal
deposition from smelting operations including evidence from the U.S. The forest
surrounding two historical Zn smelters in Palmerton, PA has been used as a study site to
assess ecological response and recovery following historic emissions. A portion of this
forest includes the Appalachian National Scenic Trail, and a barren area of approximately
600 to 800 ha remains where Zn, Mn, and Cd were once emitted (Bever et al.. 2013).
Operation at the smelter ceased in 1980, but effects from the contaminated soils persist.
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In a greenhouse study using seedlings of native tree species, as little as 10% of soil
collected in proximity to the smelter site and mixed with reference soil caused reduced
growth or mortality of the tree seedings (Bever et al.. 2013). Red maple (Acer rubrum)
was most sensitive, followed by gray birch (Betulapopulifolia), northern red oak
(Quercus rubra), chestnut oak (Quercus prinus), and eastern white pine (Pinus strobus).
In a field survey relating Zn soil concentrations to forest response, canopy closure and
shrub cover was decreased to half at approximately 2,060 mg/kg Zn, while tree-seedling
density was reduced by 80% at 1,080 mg/kg Zn (Bever et al.. 2011). Vegetative
communities near the Nikel smelter in Russia near the border with Finland and Norway
showed varied response to deposition of heavy metals (Mvking et al.. 2009). Epiphytic
lichens were most affected followed by decreased abundance and species richness of
lichens and bryophytes closer to the smelter. No effects on tree crown condition or
growth were observed.
D.7.2. Urban Environments
Resident biota in urban areas are affected by PM along with other stressors associated
with the built environment such as increased temperature due to heat island effects
(Pickett et al.. 2011). McDonnell et al. (1997) observed differences in urban forest
structure and function compared to rural and suburban areas of New York. Oak forests
near the city were characterized by reduced soil fungal and invertebrate populations,
elevated soil metals (presumably from air pollution), and lower quality of leaf litter. The
removal of PM by urban vegetation to mitigate air pollution has been extensively
reviewed, but few of these studies consider ecological impacts of PM (Escobedo et al..
2011; Pataki et al.. 2011).
D.7.3. Aquatic Ecosystems
In the 2009 PM ISA, PM components in aquatic ecosystems were primarily considered in
the context of aquatic food web transfer of organic contaminants (U.S. EPA. 2009a). In
another study reviewed in the 2009 PM ISA, bioassay procedures with green algae were
used to provide an initial screening of ambient PM toxicity from two urban/industrial and
one rural site near Lake Michigan (Sheeslev et al.. 2004). Results suggested that toxicity
was not related to the total mass of PM in the extract, but to the chemical components of
the PM. In a study of the effects of contaminated tunnel wash water runoff in Norway,
growth of sea trout (Salmo trutta) was significantly reduced in the stream receiving the
wastewater (Meland et al.. 2010). The contaminated wash water had elevated
concentrations of traffic-related contaminants including metals, PAHs, and road salt from
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combustion and highway runoff. Fractionation of water samples indicated some of the
metals and PAHs were highly associated with particles. Size ratios of detected PAHs
suggested that sources included tire wear and incomplete combustion.
D.7.4. Experimental Microecosystems
Since the 2009 PM ISA, several studies have employed a microecosystem to assess
effects of air pollutants at the community level of biological organization to see how
microbial communities living on terrestrial mosses (bryophytes) respond to atmospheric
deposition of PM components (metals, PAHs, NO2). In a series of bioindicator studies
conducted in France, species-specific responses to PM components and effects on total
biomass were observed in the associated microbial communities (Meyer et al.. 2010a;
Mover et al.. 2010b). Primary producers, decomposers, and predators responded
differently to the pollutants (Meyer et al.. 2010a; Mover et al.. 201 Ob). Testate amoebae
are especially sensitive to changes in atmospheric pollution in these microsystems and
were proposed as a biomonitoring tool (Mever et al.. 2012). Total testate amoebae
abundance and abundance of five species of testate amoebae decreased with increased
deposition of the PAH phenanthrene in the experimental microecosystem (Mever et al..
2013).
D.8. SUMMARY OF ECOLOGICAL EFFECTS OF PARTICULATE
MATTER
In regards to direct effects of PM on radiative flux, newly available research links
changes in expression of proteins involved in photosynthesis to changes in radiation
associated with aerosols and PM. Although this method has not been widely applied, it
may represent an important way to study mechanistic changes to photosynthesis in
response to more diffuse radiation resulting from PM in the air column.
In general, new studies on PM deposition to vegetation support findings in previous PM
reviews on altered photosynthesis, transpiration, and reduced growth. Additional
characterization of PM effects at the leaf surface since the 2009 PM ISA has led to a
greater understanding of PM foliar uptake. Alterations in leaf fatty acid composition are
associated with metals transferred to plant tissues from PM deposition on foliar surfaces
(Schreck et al.. 2013).
Several studies published since the 2009 PM ISA show PM effects on soil physical
properties and nutrient cycling. Previous findings in the PM ISA of changes to microbial
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respiration and biomass are further supported by new studies. Microbial community
responses to PM vary in tolerance to heavy metals and organics.
In fauna, results from ecotoxicity assays with PM extracts using bacteria, rotifers,
nematodes, zebrafish, and earthworms support findings in the 2009 PM ISA that toxicity
is not related to the total mass of PM in the extract, but to the chemical components of the
PM. In nematodes exposed to PM from air filters, the insulin-signaling pathway was
identified as a possible molecular target. Use of wildlife as PM biomonitors has been
expanded to new taxa since the last PM review. Several studies in invertebrates and birds
report physiological responses to air pollutants, including PM.
For ecosystem level effects, a gradient of response with increasing distance from PM
source was reported in the 2009 PM ISA. Newly available studies from long-term
ecological monitoring sites provide limited evidence for recovery in areas such as those
around former smelters due to continued presence of metals in soils after cessation of
operations. A novel experimental microecosystem using microbial communities living in
terrestrial mosses indicate PM deposition alters responses of primary producers,
decomposers, and predators.
Since publication of the 2009 PM ISA, new literature builds upon the existing knowledge
of ecological effects associated with PM components, especially metals and organics. In
some instances, new techniques have enabled further characterization of the mechanisms
of PM on soil processes, vegetation, and effects on fauna. New studies provide additional
evidence for community-level responses to PM deposition, especially in soil microbial
communities. However, uncertainties remain due to the difficulty in quantifying
relationships between ambient concentrations of PM and ecosystem response.
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stress on land snail Helix aspersa as a sentinel organism for ecotoxicological effects of
urban pollution with heavy metals. Chemosphere 93: 1131-1138.
http://dx.doi. org/ 10.1016/i. chemosphere.2013.06.042
Abell. GCJ; Revill. AT; Smith. C; Bissett. AP; Volkman. JK; Robert. SS. (2010). Archaeal
ammonia oxidizers and nirS-type denitrifiers dominate sediment nitrifying and
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