United States Office of Water EPA-822-R-07-004
Environmental Protection Office of Science and Technology September 2007
Agency Washington, DC 20460 www.epa.gov
Nutrient Criteria
Technical Guidance Manual
Wetlands
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DISCLAIMER
This manual provides technical guidance to States, Authorized Tribes, Territories and other
authorized jurisdictions to establish water quality criteria and standards under the Clean Water
Act (CWA), in order to protect aquatic life from acute and chronic effects of nutrient over-
enrichment. Under the CWA, States and Authorized Tribes are directed to establish water quality
criteria to protect designated uses. States and Authorized Tribes may use approaches for
establishing water quality criteria that differ from those recommended in this guidance. This
manual constitutes EPA's scientific recommendations regarding the development of numeric
criteria reflecting ambient concentrations of nutrients that protect aquatic life. However, it does
not substitute for the CWA or EPA's regulations; nor is it a regulation itself. Thus, it cannot
impose legally binding requirements on EPA, States, Authorized Tribes, or the regulated
community, and might not apply to a particular situation or circumstance. Further, States and
Authorized Tribes may choose to develop different types of criteria for wetlands protection,
including narrative criteria. EPA may change this guidance in the future.
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TABLE OF CONTENTS
CONTRIBUTORS vii
ACKNOWLEDGMENTS viii
LIST OF FIGURES ix
LIST OF TABLES x
LIST OF INTERNET LINKS/REFERENCES xi
EXECUTIVE SUMMARY 1
Chapter 1 Introduction 5
1.1 INTRODUCTION 5
1.2 WATER QUALITY STANDARDS AND CRITERIA 6
1.3 NUTRIENT ENRICHMENT PROBLEMS 8
1.4 OVERVIEW OF THE CRITERIA DEVELOPMENT PROCESS 11
1.5 ROADMAP TO THE DOCUMENT 12
Chapter 2 Overview of Wetland Science 15
2.1 INTRODUCTION 15
2.2 COMPONENTS OF WETLANDS 17
2.3 WETLAND NUTRIENT COMPONENTS 22
Chapters Classification of Wetlands 30
3.1 INTRODUCTION 30
3.2 EXISTING WETLAND CLASSIFICATION SCHEMES 31
3.3 SOURCES OF INFORMATION FOR MAPPING WETLAND CLASSES 43
3.4 DIFFERENCES IN NUTRIENT REFERENCE CONDITION OR SENSITIVITY TO NUTRIENTS
AMONG WETLAND CLASSES 46
3.5 RECOMMENDATIONS 47
Chapter 4 Sampling Design for Wetland Monitoring 51
4.1 INTRODUCTION 51
4.2 CONSIDERATIONS FOR SAMPLING DESIGN 52
4.3 SAMPLING PROTOCOL 57
4.4 SUMMARY 63
Chapter 5 Candidate Variables for Establishing Nutrient Criteria 65
5.1 OVERVIEW OF CANDIDATE VARIABLES 65
5.2 SUPPORTING VARIABLES 67
5.3 CAUSAL VARIABLES 70
5.4 RESPONSE VARIABLES 76
Chapter 6 Database Development and New Data Collection 82
6.1 INTRODUCTION 82
6.2 DATABASES AND DATABASE MANAGEMENT 82
6.3 QUALITY OF HISTORICAL AND COLLECTED DATA 86
6.4 COLLECTING NEW DATA 89
6.5 QUALITY ASSURANCE / QUALITY CONTROL (QA/QC) 91
Chapter 7 Data Analysis 92
7.1 INTRODUCTION 92
7.2 FACTORS AFFECTING ANALYSIS APPROACH 92
7.3 DISTRIBUTION-BASED APPROACHES 94
7.4 RESPONSE-BASED APPROACHES 95
7.5 PARTITIONING EFFECTS AMONG MULTIPLE STRESSORS 97
7.6 STATISTICAL TECHNIQUES 98
7.7 LINKING NUTRIENT AVAILABILITY TO PRIMARY PRODUCER RESPONSE 102
Chapters Criteria Development 104
IV
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8.1 INTRODUCTION 104
8.2 METHODS FOR DEVELOPING NUTRIENT CRITERIA 105
8.3 EVALUATION OF PROPOSED CRITERIA 111
REFERENCES 113
APPENDIX A. ACRONYM LIST AND GLOSSARY 155
ACRONYMS 155
GLOSSARY 157
APPENDIX B. CASE STUDY: DERIVING A PHOSPHORUS CRITERION FOR THE FLORIDA
EVERGLADES 161
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VI
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CONTRIBUTORS
Nancy Andrews (U.S. Environmental Protection Agency)
Mark Clark (University of Florida)
Christopher Craft (University of Indiana)
William Crumpton (Iowa State University)
Ifeyinwa Davis (U.S. Environmental Protection Agency)
Naomi Detenbeck (U.S. Environmental Protection Agency)
Paul McCormick (U.S. Geological Survey)
Amanda Parker (U.S. Environmental Protection Agency)*
Kristine Pintado (Louisiana Department of Environmental Quality)
Steve Potts (U.S. Environmental Protection Agency)
Todd Rasmussen (University of Georgia)
Ramesh Reddy (University of Florida)
R. Jan Stevenson (Michigan State University)
Arnold van der Valk (Iowa State University)
*Principal Author
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ACKNOWLEDGMENTS
The authors wish to acknowledge the efforts and input of several individuals. These include
members of our EPA National Nutrient Team: Jim Carleton, Lisa Larimer, and Robert Cantilli;
members of the EPA Wetlands Division: Kathy Hurld, Chris Faulkner and Donna Downing;
members of the Office of Research and Development and their Office of Science Policy: Valerie
Chan, Joseph Schubauer-Berigan, Charles Lane, John Morrice, Christine Weilhoefer, Tony
Olsen, and Walt Nelson; the Office of General Counsel: Leslie Darman. We also want to thank
Kristine Pintado (DEQ, Louisiana) for her contributions and her careful review and comments.
This document was peer reviewed by a panel of expert scientists. The peer review charge
focused on evaluating the scientific validity of the processes and techniques for developing
nutrient criteria described in the guidance. The peer review panel comprised Dr. Robert H.
Kadlec, Dr. Lawrence Richards Pomeroy, Dr. Eliska Rejmankova and Dr. Li Zhang. Edits and
suggestions made by the peer review panel were incorporated into the final version of the
guidance.
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LIST OF FIGURES
Figure 1.1 Flowchart providing the steps of the process to develop wetland nutrient
criteria
Figure 2.1 Schematic of nutrient transfer among potential system sources and sinks
Figure 2.2 Relationship between water source and wetland vegetation. Modified from
Brinson(1993)
Figure 2.3 Schematic showing basic nutrient cycles in soil-water column of a wetland
Figure 2.4 Range of redox potentials in wetland soils
Figure 2.5 Schematic of the nitrogen cycle in wetlands
Figure 2.6 Schematic of the phosphorus cycle in wetlands
Figure 3.1 Map of Omernik aquatic ecoregions
Figure 3.2a Map of Bailey ecoregions with coastal and estuarine provinces
Figure 3.2b Legend (of Map of Bailey ecoregions with coastal and estuarine provinces)
Figure 3.3 Examples of first four hierarchical levels of Ecological Units
Figure 3.4 (Top) Cowardin hierarchy of habitat types for estuarine systems
Figure 3.5 Dominant water sources to wetlands, from Brinson 1993
Figure 3.6 Dominant hydrodynamic regimes for wetlands based on flow pattern
Figure 3.7 Interaction with break in slope with groundwater inputs to slope wetlands
(Bottom) Palustrine systems, from Cowardin et al., 1979
Figure 5.1 Conceptual model of causal pathway between human activities and ecological
attributes
Figure 7.1 Biological condition gradient model describing biotic community condition as
levels of stressors increase
Figure 8.1 Use of undisturbed wetlands as a reference for establishing criteria versus an
effects-based approach
Figure 8.2 Tiered aquatic life use model used in Maine
Figure 8.3 Percent calcareous algal mat cover in relation to distance from the P source
showing the loss of the calcareous algal mat in those sites closer to the source
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LIST OF TABLES
Table 1 Observed consequences of cultural eutrophication in freshwater wetlands
Table 2 Comparison of landscape and wetland classification schemes
Table 3 Features of the major hydrogeomorphic classes of wetlands that may
influence background nutrient concentrations, sensitivity to nutrient loading,
nutrient storage forms and assimilative capacity, designated use and choice
of endpoints
Table 4 Comparison of Stratified Probabilistic, Targeted, and BACI Sampling Designs
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LIST OF INTERNET LINKS/REFERENCES
Chapter 1 http ://www. epa. gov/waterscience/criteri a/nutrient/guidance/index.html
http ://www. epa. gov/owow/wetlands
http://www.epa.gov/waterscience/criteria/nutrient/strategy.html.
http ://www. epa. gov/owow/wetlands/initiative
http://www.dep.state.fl.us/legal/Rules/shared/62-302/62-302.pdf
Chapter 2 http://www.arl.noaa.gov/research/programs/airmon.html
http://nadp.sws.uiuc.edu/
Chapter 3 http ://www. epa. gov/emap/remap/index.html
http ://www. epa. gov/bioindicators/
http ://www. epa. gov/waterscience/standards/nutrient.html
http://el.erdc.usace.army.mil/wetlands/pdfs/wrpde9.pdf
http://water.usgs.gov/GIS/metadata/usgswrd/XML/ecoregion.xml
http ://www.nwi .fws. gov
http://www.wes.army.mil/el/wetlands
http://www.epa.gov/waterscience/criteria/wetlands/7Classification.pdf
http://www.epa.gov/waterscience/criteria/wetlands/17LandUse.pdf
Chapter 4 http ://www. epa. gov/waterscience/criteria/wetlands/index.html
http ://www. epa. gov/owow/wetlands/bawwg/case/me.html
http ://www. epa. gov/owow/wetlands/bawwg/case/mtdev.html
http ://www. epa. gov/owow/wetlands/bawwg/case/wa.html
http ://www. epa. gov/owow/wetlands/bawwg/case/fl 1 .html
http ://www. epa. gov/owow/wetlands/bawwg/case/fl2.html
http ://www. epa. gov/owow/wetlands/bawwg/case/oh 1 .html
http ://www. epa. gov/owow/wetlands/bawwg/case/mn 1 .html
http ://www. epa. gov/owow/wetlands/bawwg/case/or.html
http://www.epa.gov/owow/wetlands/bawwg/case/wi 1 .html
Chapter 5 http://www.epa.gov/waterscience/criteria/wetlands/10Vegetation.pdf
http ://www. epa. gov/waterscience/criteria/wetlands/11 Algae.pdf
http://www.epa.gov/waterscience/criteria/wetlands/9Invertebrate.pdf
http://www.epa.gov/waterscience/criteria/wetlands/16Indicators.pdf
Chapter 6 http://www.nps.ars.usda.gov/programs/nrsas.htm
http://www.fs.fed.us/research/
http://www.usbr.gov
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Chapter 7 http://el.erdc.usace.army.mil/wrap/wrap.html
http://firehole.humboldt.edu/wetland/twdb.html
http://www.socialresearchmethods.net/
http://www.math.yorku.ca/SCS/
http://calculators.stat.ucla.edu/powercalc/
http://www.surveysystem.com/sscalc.htm
http://www.health.ucalgary.ca/~rollin/stats/ssize/index.html
http ://www. stat. ohi o-state. edu/~j ch/ssinput.html
http ://www. stat.uiowa. edu
http ://www. epa. gov/waterscience/criteria/wetlands
Chapter 8 http://www.epa.gov/waterscience/biocriteria/modules/wetl01-05-alus-
monitoring.pdf
http ://www. epa. gov/owow
http://www.wetlandbiogeochemistry.lsu.edu/
http://data.lca.gov/Ivan6/app/app c ch9.pdf
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EXECUTIVE SUMMARY
The purpose of this document is to provide scientifically defensible guidance to assist States,
Authorized Tribes, Territories, and other authorized jurisdictions—hereafter referred to as States
—in assessing the nutrient status of their wetlands, and to provide technical assistance for
developing numeric nutrient criteria for wetland systems in an eco-region. The development of
nutrient criteria is part of an initiative by the U.S. Environmental Protection Agency (USEPA) to
address the problem of cultural eutrophication, i.e., nutrient pollution caused by human activities
(USEPA 1998a). Cultural eutrophication is not new; however, traditional efforts at nutrient
control have been only moderately successful. Specifically, efforts to control nutrients in water
bodies that have multiple nutrient sources (point and nonpoint sources) have been less effective
in providing satisfactory, timely remedies for enrichment-related problems. Development and
adoption of numeric criteria into water quality standards aids nitrogen and phosphorus pollution
control efforts by providing clear numeric goals for water quality protection. Furthermore,
numeric nutrient criteria provide specific water quality goals that will assist researchers in
designing improved best management practices.
In 1998, the USEPA published a report entitled, National Strategy for the Development of
Regional Nutrient Criteria (USEPA 1998a). This report outlines a framework for development
of waterbody-specific technical guidance that can be used to assess nutrient status and develop
region-specific numeric nutrient criteria. The document presented here is the wetland-specific
technical guidance for developing numeric nutrient criteria. The Nutrient Criteria Technical
Guidance Manuals for Rivers and Streams (USEPA, 2000b), Lakes and Reservoirs (USEPA,
2000a) and Estuarine and Coastal Marine Waters (USEPA, 2001) have been completed and are
available at: http://www.epa.gov/waterscience/criteria/nutrient/guidance/index.html.
Section 303(c) of the Clean Water Act directs States to adopt water quality standards for
waters that are "waters of the United States," including wetlands that are waters of the
United States.1 A water quality standard consists of three main elements: (1) one or more
designated uses of each of the State's waters, such as recreation or propagation offish;
(2) criteria expressed as pollutant concentration levels or narrative statements
representing a quality of water that supports a designated use; and, (3) an anti-
degradation policy to protect existing uses and high quality waters.
1 For further information regarding the scope of 'waters of the U.S.' in light of the U.S. Supreme Court's 2006
decision in Rapanos v. United States, see "Clean Water Act Jurisdiction Following the U.S. Supreme Court's
Decision in Rapanos v. United States & Carabell v. United States," which was jointly issued by the U. S.
Environmental Protection Agency and the Army Corps of Engineers and is available at:
http ://www. epa. gov/o wow/wetlands/.
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SEPTEMBER 2007 Executive Summary
The information used in developing the technical approaches in this document came from
references about studies of wetlands in a wide range of conditions, but not wetlands with
a high degree of modification (e.g., wetlands that are considered "prior converted
cropland" or artificial wetlands specifically engineered to protect or improve downstream
water quality). This guidance is to assist States in developing numeric nutrient criteria for
wetlands, should they choose to do so. States may choose to develop different types of
criteria for wetlands protection, including site-specific or narrative criteria for wetlands
protection, as long as they are scientifically defensible and protective of the designated
uses (40 CFR § 131.11). This Guidance Manual includes chapters dealing with the
following topics:
CLASSIFICATION OF WETLANDS
Classification strategies for nutrient criteria development include:
• physiographic regions
• hydrogeomorphic class
• water depth and duration
• vegetation type or zone
Choosing a specific classification scheme will likely depend on practical considerations, such as:
whether a classification scheme is available in mapped digital form or can be readily derived
from existing map layers; whether a hydrogeomorphic or other classification scheme has been
refined for a particular region and wetland type; and, whether classification schemes are already
in use for monitoring and assessment of other waterbody types in a State or region.
SAMPLING DESIGN
Three sampling designs for new wetland monitoring programs are described:
• probabilistic sampling
• targeted/tiered approach
BACI (Before/After, Control/Impact)
These approaches are designed to obtain a significant amount of information for statistical
analyses with relatively minimal effort. Sampling efforts should be designed to collect
information that will answer management questions in a way that permits robust statistical
analysis. In addition, site selection, characterization of reference sites or systems, and
identification of appropriate index periods are all of particular concern when selecting an
appropriate sampling design. Careful selection of sampling design will allow the best use of
financial resources and result in the collection of high quality data for evaluation of the wetland
resources of a State.
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SEPTEMBER 2007 Executive Summary
CANDIDATE VARIABLES FOR ESTABLISHING NUTRIENT CRITERIA
Candidate variables to use in determining nutrient condition of wetlands and to help identify
appropriate nutrient criteria for wetlands consist of supporting variables, causal variables, and
response variables. Supporting variables provide information useful in normalizing causal and
response variables and categorizing wetlands. Causal variables are intended to characterize
nutrient availability (or assimilation) in wetlands and could include nutrient loading rates and
soil nutrient concentrations. Response variables are intended to characterize biotic response and
could include community structure and composition of macrophytes and algae. Recommended
variables for wetland nutrient criteria development described in this chapter are:
1. Causal variables - nutrient loading rates, land use, extractable and total soil nitrogen (N) and
phosphorus (P), water column N and P;
2. Response variables - nutrient content of wetland vegetation (algal and/or higher plants),
aboveground biomass and stem height, macrophyte, algal, and macroinvertebrate community
structure and composition; and,
3. Supporting variables - hydrologic condition/balance, conductivity, soil pH, soil bulk density,
soil organic matter content.
DATABASE DEVELOPMENT AND NEW DATA COLLECTION
A database of relevant water quality information can be an invaluable tool to States as they
develop nutrient criteria. In some cases, existing data are available and can provide additional
information that is specific to the region where criteria are to be set. However, little or no data
are available for most regions or parameters, and creating a database of newly gathered data is
strongly recommended. In the case of existing data, the data should be geolocated, and their
suitability (type and quality and sufficient associated metadata) ascertained.
DATA ANALYSIS
Data analysis is critical to nutrient criteria development. Proper analysis and interpretation of
data determine the scientific defensibility and effectiveness of the criteria. Therefore, it is
important to evaluate short and long-term goals for wetlands of a given class within the region of
concern. The purpose of this chapter is to explore methods for analyzing data that can be used to
develop nutrient criteria consistent with these goals. Techniques discussed in this chapter
include:
• Distribution-based approaches that examine distributions of primary and supporting
variables (i.e., the percentile approach);
• Response-based approaches that develop relationships between measurements of nutrient
exposure and ecological responses (i.e., tiered aquatic life uses);
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SEPTEMBER 2007 Executive Summary
• Partitioning effects of multiple stressors;
• Statistical techniques;
• Multi-metric indices; and,
• Linking nutrient availability to primary producer response.
CRITERIA DEVELOPMENT
Several methods can be used to develop numeric nutrient criteria for wetlands.They include, but
are not limited to, criteria development methods that are detailed in this document:
• Comparing conditions in known reference systems for each established
wetland type and class based on best professional judgment (BPJ) or
identifying reference conditions using frequency distributions of empirical
data and identifying criteria using percentile selections of data plotted as
frequency distributions;
• Refining classification systems using models, and/or examining system
biological attributes in comparison to known reference conditions to
assess the relationships among nutrients, vegetation or algae, soil, and
other variables and identifying criteria based on thresholds where those
response relationships change; and,
• Using or modifying published nutrient and vegetation, algal, and soil
relationships and values to identify appropriate criteria.
A weight of evidence approach with multiple attributes that combine one or more of the
development approaches will generally produce criteria of greater scientific validity.
The purpose of this document is to provide guidance on developing numeric nutrient criteria in a
scientifically valid manner, and is not intended to address the multiple, complex issues
surrounding implementation of water quality criteria and standards. Implementation will be
addressed in a different process and additional implementation assistance will also be provided
through other technical assistance projects provided by EPA. For issues specific to constructed
wetlands, States should refer to http://www.epa.gov/owow/wetlands/watersheds/cwetlands.html.
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SEPTEMBER 2007 Chapter 1. Introduction
Chapter 1 Introduction
1.1 INTRODUCTION
PURPOSE
The purpose of this document is to provide technical guidance to assist States in assessing the
nutrient status of their wetlands by considering water, vegetation, and soil conditions, and to
provide technical assistance for developing regionally-based, scientifically defensible, numeric
nutrient criteria for wetlands. In this document, the term "wetlands" or "wetland systems" refers
to wetlands that are considered as "waters of the United States." However, States may, at their
discretion, use this document to develop water quality criteria and standards for wetlands that are
considered waters of the State.
EPA's development of recommended nutrient criteria is part of an initiative by the U.S.
Environmental Protection Agency (USEPA) to address the problem of cultural eutrophication. In
1998, the EPA published a report entitled, National Strategy for the Development of Regional
Nutrient Criteria (USEPA 1998a). The report outlines a framework for EPA's development of
waterbody-specific technical guidance that can be used to assess nutrient status and develop
region-specific numeric nutrient criteria. This document is the technical guidance for developing
numeric nutrient criteria for wetlands. Approaches to nutrient criteria development are similar
for freshwater and tidal wetlands, however, this document has a freshwater emphasis. EPA
recognizes that wetlands are different from the other types of waters of the U.S. in that they
frequently do not have standing or flowing water, and the soils and vegetation components are
more dominant in these systems than in the other waterbody types (lakes, streams, estuaries).
Additional, more specific information on sampling wetlands is available at:
www.epa.gov/waterscience/criteria/nutrient/guidance/index.html.
BACKGROUND
Cultural eutrophi cation (human-caused inputs of excess nutrients in waterbodies) is one of the
primary causal factors that impair surface waters in the U.S. (USEPA 1998a). Both point and
nonpoint sources of nutrients contribute to impairment of water quality. Point source discharges
of nutrients are relatively constant and are controlled by the National Pollutant Discharge
Elimination System (NPDES) permitting program. Nonpoint source pollutant inputs have
increased in recent decades, resulting in degraded water quality in many aquatic systems.
Nonpoint sources of nutrients are most commonly intermittent and are usually linked to runoff,
atmospheric deposition, seasonal agricultural activity, and other irregularly occurring events
such as silvicultural activities. Control of nonpoint source pollutants typically focuses on land
management activities and regulation of pollutants released to the atmosphere (Kronvang et al.,
2005; Howarth et al., 2002; Carpenter et al., 1998).
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SEPTEMBER 2007 Chapter 1. Introduction
The term eutrophication was coined in reference to lake systems. The use of the term for
wetlands can be problematic due to the confounding nature of hydrodynamics, light, and the
differences in the responses of algae and vegetation. Eutrophication in this document refers to
human-caused inputs of excess nutrients and is not intended to indicate the same scale or
responses to eutrophi cation found in lake systems and codified in the trophic state index for
lakes (Carlson 1977). This manual is intended to provide guidance for identifying deviance from
natural conditions with respect to cultural eutrophication in wetland systems. Hydrologic
alteration and pollutants other than excess nutrients may amplify or reduce the effects of nutrient
pollution, making specific responses to nutrient pollution difficult to quantify. EPA recognizes
these issues, and presents recommendations for analyzing wetland systems with respect to
nutrient condition for development of nutrient criteria in spite of these confounding factors.
Cultural eutrophication is not new; however, traditional efforts at nutrient control have been only
moderately successful. Specifically, efforts to control nutrients in waterbodies that have multiple
nutrient sources (point and nonpoint sources) have been less effective in providing satisfactory,
timely remedies for enrichment-related problems (Azzellino et al., 2006; Merseburger et al.,
2005; Carpenter et al., 1998). Development and adoption of numeric nutrient criteria into water
quality standards aid State nutrient pollution control efforts by providing clear numeric goals for
nutrient concentrations. Furthermore, numeric nutrient criteria provide specific water quality
goals that will assist researchers in designing improved best management practices.
1.2 WATER QUALITY STANDARDS AND CRITERIA
States are responsible for setting water quality standards to protect the physical, biological, and
chemical integrity of their waters. "Water quality standards (WQS) are provisions of State or
Federal law which consist of a designated use or uses and water quality criteria for such waters
to protect such uses.2 Water quality standards are to protect public health or welfare, enhance the
quality of the water, and serve the purposes of the Act (40 CFR 131.2 and 131.3(1))" (USEPA
1994). A water quality standard defines the goals for a wetland by: 1) designating its specific
uses, 2) setting criteria to protect those uses, and, 3) establishing an antidegradation policy to
protect existing water quality.
Designated uses are a State's concise statements of its goals and expectations for each of the
individual surface waters under its jurisdiction. With designated uses, States can work with their
publics to identify a collective goal for their waters that they intend to strive for as they manage
water quality. EPA encourages States to evaluate the attainability of these goals and expectations
2 EPA published guidance on water quality standards for wetlands in 1990 (USEPA, 1990c).
Examples of different state approaches for standards can be found at:
http ://www. epa. gov/owow/wetlands/initiatives/.
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SEPTEMBER 2007 Chapter 1. Introduction
to ensure they have designated the appropriate uses. Generally, the effectiveness of designated
uses in guiding water quality management programs is greater if they:
a Identify specific expectations based on as much data as possible to reduce ambiguity.
a Recognize and accommodate inherent natural differences among surface water types.
a Acknowledge certain human caused conditions that limit the potential to support uses.
Designated uses may involve a spectrum of expectations, depending on the type of wetland and
associated hydropatterns, where the wetland is situated with respect to natural landscape features
and human activity, and the historical and anticipated future functions that the wetland provides.
Criteria to protect specific uses, in turn, should reflect these differing expectations where
appropriate. The information used in developing the technical approaches in this document was
drawn from references about studies of wetlands in a wide range of conditions, but not wetlands
with a high degree of modification (e.g., wetlands that are considered "prior converted cropland"
or artificial wetlands specifically engineered to protect or improve downstream water quality).
Water quality criteria may be expressed as numeric values or narrative statements. As of this
writing, most of the Nation's waterbodies do not have numeric nutrient criteria, but instead rely
on narrative criteria that describe the desired condition. Narrative criteria are descriptions of
conditions necessary for a water to attain the designated uses. An example of a narrative criterion
for nutrients is shown below:
In no case shall nutrient concentrations of a body of water be altered so as to
cause an imbalance in natural populations of aquatic flora or fauna.
Numeric criteria, on the other hand, are values assigned to measurable components of water
quality to protect designated uses, such as the concentration of a specific constituent that is
present in the water column. An example of a numeric criterion for specific waters is shown
below:
(4) Phosphorus Criterion.
(a) The numeric phosphorus criterion for Class III waters shall be a long-term
geometric mean of 10 ppb, but shall not be lower than the natural conditions of
the Class II waters, and shall take into account spatial and temporal variability.
Achievement of the criterion shall be determined by the methods in this
subsection. Exceedences of the provisions of the subsection shall not be
considered deviations from the criterion if they are attributable to the full range of
natural spatial and temporal variability, statistical variability inherent in sampling
and testing procedures, or higher natural background conditions.
In addition to narrative and numeric criteria, some States use numeric translator mechanisms—
mechanisms that translate narrative (qualitative) standards into numeric (quantitative) values for
use in evaluating water quality data. Translator mechanisms may be useful internally by the State
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SEPTEMBER 2007 Chapter 1. Introduction
agency for water assessment and management and serve as an intermediate step between
numeric and narrative criteria.
Numeric criteria provide distinct interpretations of acceptable and unacceptable conditions, form
the foundation for measurement of environmental quality, and reduce ambiguity for management
and enforcement decisions. The lack of numeric nutrient criteria in State water quality standards
for most of the Nation's waterbodies makes it difficult to assess the condition of waters of the
U.S. with respect to nutrients, and thus hampers the water quality manager's ability to protect
designated uses and improve water quality. EPA encourages States to adopt numeric nutrient
criteria into their water quality standards (USEPA 2007b).
Many States have adopted some form of nutrient criteria for surface waters related to
maintaining natural conditions and avoiding nutrient enrichment. Most States with nutrient
criteria in their water quality standards have broad narrative criteria for most waterbodies and
may also have site-specific numeric criteria for certain waters of the State. Established criteria
most commonly pertain to phosphorus (P) concentrations in lakes. Nitrogen (N) criteria, where
they have been established, are usually protective of human health effects or relate to toxic
effects of ammonia and nitrates. In general, levels of nitrate (10 ppm [mg/L] for drinking water)
and ammonia high enough to be problematic for human health or toxic to aquatic life (1.24 mg
N/L at pH = 8 and 25°C) will also cause problems of enhanced algal growth (USEPA 1986).
Numeric nutrient criteria can provide a variety of benefits and may be used in conjunction with
State and Federal biological assessments, Nonpoint Source Programs, Watershed
Implementation Plans, and in development of Total Maximum Daily Loads (TMDLs) to improve
resource management and support watershed protection activities at local, State, and national
levels. Information obtained from compiling existing data and conducting new surveys can
provide water quality managers and the public a better perspective on the condition of State
waters. The compiled information can be used to most effectively budget personnel and financial
resources for the protection and restoration of State waters. In a similar manner, data collected in
the criteria development and implementation process can be compared before, during, and after
specific management actions. Analyses of these data can determine the response of the wetland
and the effectiveness of management endeavors.
1.3 NUTRIENT ENRICHMENT PROBLEMS
Water quality can be affected when watersheds are modified by alterations in vegetation,
sediment transport, fertilizer use, industrialization, urbanization, or conversion of native forests
and grasslands to agriculture and silviculture (Turner and Rabalais 1991; Vitousek et al., 1997;
Carpenter et al., 1998). Cultural eutrophication, one of the primary factors causing impairment of
U.S. surface waters (USEPA 1998a), results from point and nonpoint sources of nutrient
pollution. Nonpoint source pollutant inputs have increased in recent decades and have degraded
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SEPTEMBER 2007 Chapter 1. Introduction
water quality in many aquatic systems (Carpenter et al., 1998). Control of nonpoint source
pollutants focuses on land management activities and regulation of pollutants released to the
atmosphere (Carpenter et al., 1998).
Nutrient enrichment frequently ranks as one of the top causes of water resource impairment.
EPA reported to Congress that of the waterbodies surveyed and reported impaired, 20 percent of
rivers and 50 percent of lakes were listed with nutrients as the primary cause of impairment
(USEPA 2000c). Few States currently include wetland monitoring in their routine water quality
monitoring programs (only eleven States reported attainment of designated uses for wetlands in
the National Water Quality Inventory 1998 Report to Congress (USEPA 1998b) and only three
States used monitoring data as a basis for determining attainment of water quality standards for
wetlands); thus, the extent of nutrient enrichment and impairment of wetland systems is largely
undocumented. Increased wetland monitoring by States will help define the extent of nutrient
enrichment problems in wetland systems.
The best-documented case of cultural eutrophication in wetlands is the Everglades ecosystem.
The Everglades ecosystem is a wetland mosaic that is composed primarily of oligotrophic
freshwater marsh. Historically, the greater Everglades ecosystem included vast acreage of
freshwater marsh, small stands of custard apple and some cattail south of Lake Okeechobee, and
Big Cypress Swamp, which eventually drains into Florida Bay. Lake Okeechobee was diked to
reduce flooding. The area directly south of Lake Okeechobee was then converted into
agricultural lands for cattle grazing and row crop production. The cultivation and use of
commercial fertilizers in the area now known as the "Everglades Agricultural Area" have
resulted in release of nutrient-rich waters into the Everglades for more than thirty years. The
effects of the nutrient-rich water, combined with coastal development and channeling to supply
water to communities on the southern Florida coast, have significantly increased soil and water
column phosphorus levels in naturally oligotrophic areas. In particular, nutrient enrichment of
the freshwater marsh has resulted in an imbalance in the native vegetation. Cattail is now
encroaching in areas that were historically primarily sawgrass; calcareous algal mats are being
replaced by non-calcareous algae, changing the balance of native flora that is needed to support
vast quantities of wildlife. Nutrient enriched water is also reaching Florida Bay, suffocating the
native turtle grass as periphyton covers the blades (Davis and Ogden 1994; Everglades Interim
Report 1999, 2003; Everglades Consolidated Report 2003). Current efforts to restore the
Everglades are focusing on nutrient reduction and better hydrologic management (Everglades
Consolidated Report 2003).
Monitoring to establish trends in nutrient levels and associated changes in biology has been
infrequent for most wetland types as compared to studies in the Everglades or examination of
other surface waters such as lakes. Noe et.al., (2001) have argued that phosphorus
biogeochemistry and the extreme oligotrophy observed in the Everglades in the absence of
anthropogenic inputs represents a unique case. Effects of cultural eutrophication, however, have
been documented in a range of different wetland types. Existing studies are available to
document potential impacts of anthropogenic nutrient additions to a wide variety of wetland
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Chapter 1. Introduction
types, including bogs, fens, Great Lakes coastal emergent marshes, and cypress swamps. The
evidence of nutrient effects in wetlands ranges from controlled experimental manipulations, to
trend or empirical gradient analysis, to anecdotal observations. Consequences of cultural
eutrophication have been observed at both community and ecosystem-level scales (Table 1).
Changes in wetland vegetation composition resulting from cultural eutrophication of these
systems have been demonstrated in bogs (Kadlec and Bevis 1990), fens (Guesewell et.al., 1998,
Bollens and Ramseier 2001, Pauli et.al., 2002), meadows (Finlayson et.al., 1986), marshes
(Bedford et.al., 1999) and cypress domes (Ewel 1976). Specific effects on higher trophic levels
in marshes seem to depend on trophic structure (e.g., presence/absence of minnows, benthivores,
and/or piscivores, Jude and Pappas 1992, Angeler et.al., 2003) and timing/frequency of nutrient
additions (pulse vs. press; Gabor et.al., 1994, Murkin et.al., 1994, Hann and Goldsborough 1997,
Sandilands et.al., 2000, Hann et.al., 2001, Zrum and Hann 2002).
Table 1. Observed consequences of cultural eutrophication in freshwater wetlands.3
Observed impact
Loss of submerged aquatic plants that have high
light compensation points
Shifts in vascular plant species composition due to
shifts in competitive advantage
Increases in above-ground production
Decreases in local or regional biodiversity
Increased competitive advantage of
aggressive/invasive species
(e.g., Typhaglauca, T. latifolia and Phalaris
arundinacea)
Loss of nutrient retention capacity (e.g., carbon and
References
Phillips et.al., 1978
Stephenson et.al., 1980
Galatowitsch and van der Valk 1996
Wentz 1976
Verhoeven et.al., 1988
Ehrenfeld and Schneider 1993
Gaudet and Keddy 1995
Koerselman and Verhoeven 1995
Barko 1983
Bayley et.al., 1985
Barko and Smart 1986
Vermeer 1986
Mudroch and Capobianco 1 979
Guntenspergen et al., 1980
Lougheed et.al., 2001
Balla and Davis 1995
VanGroenendael et.al., 1993
Bedford et.al., 1999
Woo and Zedler 2002
Svengsouk and Mitsch 2001
Green and Galatowitsch 2002
Maurer and Zedler 2002
Nichols 1983
1 Similar impacts in tidal and estuarine wetlands have been documented, but are not included in this table.
10
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SEPTEMBER 2007
Chapter 1. Introduction
nitrogen storage, changes in plant litter
decomposition)
Major structural shifts between "clear water"
macrophyte dominated systems to turbid
phytoplankton dominated systems or metaphyton-
dominated systems with reduced macrophyte
coverage
Shifts in macroinvertebrate composition along a
cultural eutrophication gradient
Davis and van der Valk 1983
Rybczyk et.al., 1996
McDougal et.al., 1997
Angeler et.al., 2003
Chessman et.al., 2002
The cycling of nitrogen (N) and phosphorus (P) in aquatic systems should be considered when
managing nutrient enrichment. The hydroperiod of wetland systems significantly affects nutrient
transformations, availability, transport, and loss of gaseous forms to the atmosphere (Mitsch and
Gosselink, 2000). Nutrients can be re-introduced into a wetland from the sediment, or by
microbial transformation, potentially resulting in a long recovery period even after pollutant
sources have been reduced. In open wetland systems, nutrients may also be rapidly transported
downstream, uncoupling the effects of nutrient inputs from the nutrient source, and further
complicating nutrient source control (Mitsch and Gosselink, 2000; Wetzel 2001). Recognizing
relationships between nutrient input and wetland response is the first step in mitigating the
effects of cultural eutrophication. When relationships are established, nutrient criteria can be
developed to manage nutrient pollution and protect wetlands from eutrophication.
1.4 THE CRITERIA DEVELOPMENT PROCESS
The National Strategy for the Development of Regional Nutrient Criteria (USEPA 1998a)
describes the principal elements of numeric nutrient criteria development. This document can be
downloaded in PDF format at the Web site:
http://www.epa.gov/waterscience/criteria/nutrient/strategy.html. The Strategy recognizes that a
prescriptive, one-size-fits-all approach is not appropriate due to regional differences that exist
and the scientific community's current technical understanding of the relationship between
nutrients, algal and macrophyte growth, and other factors (e.g., flow, light, substrata). The
approach chosen for criteria development therefore may be tailored to meet the specific needs of
each State. The
EPA Strategy envisions a process by which State waters are initially monitored, reference
conditions are established, individual waterbodies are compared to known reference waterbodies,
and appropriate management measures are implemented. These measurements can be used to
document change and monitor the progress of nutrient reduction activities and protection of
water quality.
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SEPTEMBER 2007 Chapter 1. Introduction
The National Nutrient Program represents an effort and approach to criteria development that, in
conjunction with efforts made by State water quality managers, will ultimately result in a
heightened understanding of nutrient-response relationships. As the proposed process is put into
use to set criteria, program success will be gauged over time through evaluation of management
and monitoring efforts. A more comprehensive knowledge-base pertaining to nutrient, and
vegetation and/or algal relationships will be expanded as new information is gained and
obstacles overcome, justifying potential refinements to the criteria development process.
The overarching goal of developing and adopting nutrient criteria is to protect and maintain the
quality of our national waters. Protecting and maintaining water quality may include restoration
of impaired systems, conservation of high quality waters, and protection of systems at high risk
for future impairment. The specific goals of a State water quality program may be defined
differently based on the needs of each State, but should, at a minimum, be established to protect
the designated uses for the waterbodies within State lands. In addition, as numeric nutrient
criteria are developed for the nation's waters, States should revisit their goals for water quality
and revise their water quality standards as needed.
1.5 ROADMAP TO THE DOCUMENT
As set out in Figure 1.1, the process of developing numeric nutrient criteria begins with defining
the goals of criteria development and water quality standards adoption. Those goals are pertinent
to the classification of systems, the development of a monitoring program, and the application of
numeric nutrient criteria to permit limits and water quality protection. These goals therefore
should be determined with the intent of revising and adapting them as new information is
obtained and the paths to achieving those goals are clarified. Defining the goals for criteria
development is the first step in the process. The summaries below describe each chapter in this
document. The document is written to provide recommendations for a stepwise procedure for
criteria development. Some chapters contain information that is not needed by some readers; the
descriptions below should serve as a guide to the most relevant information for each reader.
Chapter Two describes many of the functions of wetland systems and their role in the landscape
with respect to nutrients. This chapter is intended to familiarize the reader with some basic
scientific information about wetlands that will provide a better understanding of how nutrients
move within a wetland and the importance of wetland systems in the landscape.
Chapter Three discusses wetland classification and presents the reader with options for
classifying wetlands based on system characteristics. This chapter introduces the scientific
rationale for classifying wetlands, reviews some common classification schemes, and discusses
their role in establishing nutrient criteria for wetlands. The classification of these systems is
important to identifying their nutrient status and their condition in relation to similar wetlands.
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SEPTEMBER 2007 Chapter 1. Introduction
Chapter Four provides technical guidance on designing effective sampling programs for State
wetland water quality monitoring programs. Most States should begin wetland monitoring
programs to collect water quality and biological data in order to develop nutrient criteria
protective of wetland systems. The best monitoring programs are designed to assess wetland
condition with statistical rigor and maximize effective use of available resources. The sampling
protocol selected, therefore, should be determined based on the goals of the monitoring program,
and the resources available.
Chapter Five gives an overview of candidate variables that could be used to establish nutrient
criteria for wetlands. Primary variables are expected to be most broadly useful in characterizing
wetland conditions with respect to nutrients, and include nutrient loading rates, soil nutrient
concentrations, and nutrient content of wetland vegetation. Supporting variables provide
information useful for normalizing causal and response variables. The candidate variables
suggested here are not the only parameters that can be used to determine wetland nutrient
condition, but rather identify those variables that are thought to be most likely to identify the
current nutrient condition and of the greatest utility in determining a change in nutrient status.
A database of relevant water quality information can be an invaluable tool to States as they
develop nutrient criteria. If little or no data are available for most regions or parameters, it may
be necessary for States to create a database of newly gathered data. Chapter Six provides the
basic information on how to develop a database of nutrient information for wetlands, and
supplies links to ongoing database development efforts at the State and national levels.
The purpose of Chapter Seven is to explore methods for analyzing data that can be used to
develop nutrient criteria. The quality of the analysis and interpretation of data generally
determines whether the criteria will be scientifically defensible and effective. This chapter
describes recommended approaches to data analysis for developing numeric nutrient criteria for
wetlands. Included are techniques to evaluate metrics, to examine or compare distributions of
nutrient exposure or response variables, and to examine nutrient exposure-response
relationships.
Chapter Eight describes the details of establishing scientifically defensible criteria in wetlands.
Several approaches are presented that water quality managers can use to derive numeric criteria
for wetland systems in their State waters. They include: (1) the use of the reference conditions
concept to characterize natural or minimally impaired wetland systems with respect to causal and
response variables; (2) applying predictive relationships to select nutrient concentrations that
will protect wetland function; and, (3) developing criteria from established nutrient exposure-
response relationships (as in the peer-reviewed, published literature). This chapter provides
recommendations regarding how to determine the appropriate numeric criterion based on the
data collected and analyzed.
The appendices include a glossary of terms and acronyms and case study examples of wetland
nutrient enrichment and management.
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Chapter 1. Introduction
Monitor
Identify
Goals
Classify
Wetlands
Select
Variables
Determine
Sampling
Design
Build
Database
Analyze
Data
Develop
Criteria
Figure 1.1 Flowchart identifying the steps of the recommended process to develop wetland
nutrient criteria.
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SEPTEMBER 2007 Chapter 2. Overview of Wetland Science
Chapter 2 Overview of Wetland Science
2.1 INTRODUCTION
Wetlands exist at the interface between terrestrial and aquatic environments. They serve as
sources, sinks, and transformers of materials. (Figure 2.1) Wetlands serve as sites for
transformation of nutrients such as nitrogen (N) and phosphorus (P). Dissolved inorganic forms
of N and P are assimilated by microorganisms and vegetation and incorporated into organic
compounds. Nitrate in surface- and ground-water is reduced to gaseous forms of N (NO, N2O,
N2) by microorganisms, a process known as denitrification, and returned to the atmosphere.
Phosphorus undergoes a variety of chemical reactions with iron (Fe), aluminum (Al), and
calcium (Ca) that depend on the pH of the soil, availability of sorption sites, redox potential, and
other factors. These biogeochemical reactions are important in evaluating the nutrient condition
(oligotrophic, mesotrophic, eutrophic) of the wetland and its susceptibility to nutrient
enrichment.
Wetlands also generally are sinks for sediment, and wetlands that are connected to adjacent
aquatic ecosystems (e.g., rivers, estuaries) may trap more sediment as compared to wetlands that
lack such connectivity (Fryirs et.al., 2007; Mitsch and Gosselink, 2000; Dunne and Leopold
1978). Wetlands also may be sources of organic carbon (C) (Bouchard 2007; Raymond and
Bauer 2001) and nitrogen (N) (Mitsch and Gosselink 2000; Mulholland and Kuenzler 1979) to
aquatic ecosystems. Production of plant biomass (leaves, wood, and roots) from riparian,
alluvial, and floodplain forests and from fringe wetlands such as tidal marshes and mangroves
provide organic matter to support heterotrophic foodwebs of streams, rivers, estuaries, and
nearshore waters (Mitsch and Gosselink 2000; Day et.al., 1989).
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Chapter 2. Overview of Wetland Science
I Atmospheric Inputs
Atmospheric Outputs
Surface Water Inflows
Ground water Inflows
,1. Groundwater Outflows
,1, Surface Water Outflows
Figure 2.1. Schematic of nutrient transfer among potential system sources and sinks.
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SEPTEMBER 2007 Chapter 2. Overview of Wetland Science
2.2 COMPONENTS OF WETLANDS
Wetlands are distinguished by three primary components: hydrology, soils, and vegetation.
Wetland hydrology is the driving force that determines soil development, the assemblage of
plants and animals that inhabit the site, and the type and intensity of biochemical processes.
Wetland soils may be either organic or mineral, but share the characteristic that they are
saturated or flooded at least some of the time during the growing season. Wetland vegetation
consists of many species of algae, rooted plants that may be herbaceous and emergent, such as
cattail (Typha sp.) and arrowhead (Saggitaria sp.), or submergent, such as pondweeds
(Potamogeton sp.), or may be woody such as bald cypress (Taxodium distichum) and tupelo
(Nyssa aquatica). Depending on the duration, depth, and frequency of inundation or saturation,
wetland plants may be either obligate (i.e., species found almost exclusively in wetlands) or
facultative (i.e., species found in wetlands but which also may be found in upland habitats). The
discussion that follows provides an overview of wetland hydrology, soils, and vegetation, as well
as aspects of biogeochemical cycling in these systems.
HYDROLOGY
Hydrology is characterized by water source, hydroperiod (depth, duration, and frequency of
inundation or soil saturation), and hydrodynamics (direction and velocity of water movement).
The hydrology of wetlands differs from that of terrestrial ecosystems in that wetlands are
inundated or saturated long enough during the growing season to produce soils that are at least
periodically deficient in oxygen. Wetlands differ from other aquatic ecosystems by their shallow
depth of inundation that enables rooted vegetation to become established, in contrast to deep
water aquatic ecosystems, where the depth and duration of inundation can be too great to support
emergent vegetation. Anaerobic soils promote colonization by vegetation adapted to low
concentrations of oxygen in the soil.
Wetlands primarily receive water from three sources: precipitation, surface flow, and
groundwater (Figure 2.2). The relative proportion of these hydrologic inputs influences the plant
communities that develop, the types of soils that form, and the predominant biogeochemical
processes. Wetlands that receive mostly precipitation tend to be "closed" systems with little
exchange of materials with adjacent terrestrial or aquatic ecosystems. Examples of precipitation-
driven wetlands include "ombrotrophic" bogs and depressional wetlands such as cypress domes
and vernal pools. Wetlands that receive water mostly from surface flow tend to be "open"
systems with large exchanges of water and materials between the wetland and adjacent non-
wetland ecosystems. Examples include floodplain forests and fringe wetlands such as lakeshore
marshes, tidal marshes, and mangroves. Wetlands that receive primarily groundwater inputs tend
to have more stable hydroperiods than precipitation- and surface water-driven wetlands, and,
depending on the underlying bedrock or parent material, high concentrations of dissolved
inorganic constituents such as calcium (Ca) and magnesium (Mg). Fen wetlands and seeps are
examples of groundwater-fed wetlands.
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Chapter 2. Overview of Wetland Science
0%A 100%
£
100%
33%
67%
100%
SURFACE FLOW
Figure 2. Relationship between water source and wetland
vegetation. Modified from Brinson (1993).
Hydroperiod is highly variable depending on the type of wetland. Some wetlands that receive
most of their water from precipitation (e.g., vernal pools) have very short duration hydroperiods.
Wetlands that receive most of their water from surface flooding (e.g., floodplain swamps) often
are flooded longer and to a greater depth than precipitation-driven wetlands. Fringe wetlands
such as tidal marshes and mangroves are frequently flooded (up to twice daily) by astronomical
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SEPTEMBER 2007 Chapter 2. Overview of Wetland Science
tides but the duration of inundation is relatively short. In groundwater-fed wetlands, hydroperiod
is more stable and water levels are relatively constant as compared to precipitation- and surface
water-driven wetlands, because groundwater provides a less variable input of water throughout
the year.
Hydrodynamics is especially important in the exchange of materials between wetlands and
adjacent terrestrial and aquatic ecosystems. In fact, the role of wetlands as sources, sinks, and
transformers of material depends, in large part, on hydrodynamics. For example, many wetlands
are characterized by lateral flow of surface- or ground-water. Flow of water can be unidirectional
or bidirectional. An example of a wetland with unidirectional flow is a floodplain forest where
surface water spills over the river bank, travels through the floodplain, and re-enters the river
channel some distance downstream. In fringe wetlands such as lakeshore marshes, tidal marshes,
and mangroves, flow is bidirectional as wind-driven or astronomical tides transport water into,
then out of the wetland. These wetlands have the ability to intercept sediment and dissolved
inorganic and organic materials from adjacent systems as water passes through them. In
precipitation-driven wetlands, flow may occur more in the vertical direction as rainfall percolates
through the wetland soils to underlying aquifers or nearby streams. Wetlands with lateral surface
flow may be important in maintaining water quality of adjacent aquatic systems by trapping
sediment and other pollutants. Surface flow wetlands also may be an important source of organic
C to aquatic ecosystems as detritus, paniculate C, and dissolved organic C are transported out of
the wetland into rivers and streams down gradient or to adjacent lakes, estuaries, and nearshore
waters.
SOILS
Wetland soils, also known as hydric soils, are defined as "soils that formed under conditions of
saturation, flooding, or ponding long enough during the growing season to develop anaerobic
conditions in the upper part" (NRCS 1998). Anaerobic conditions result because the rate of
oxygen diffusion through water is approximately 10,000 times less than in air. Wetland soils
may be composed mostly of mineral constituents (sand, silt, clay) or they may contain large
amounts of organic matter. Because anaerobic conditions slow or inhibit decomposition of
organic matter, wetland soils typically contain more organic matter than terrestrial soils of the
same region or climatic conditions. Under conditions of near continuous inundation or
saturation, organic soils (histosols) may develop. Histosols are characterized by high organic
matter content, 20-30% (12-18% organic C depending on clay content) with a thickness of at
least 40 cm (USDA 1999). Because of their high organic matter content, histosols possess
physical and chemical properties that are very different from mineral wetland soils. For example,
organic soils generally have lower bulk densities, higher porosity, greater water holding
capacity, lower nutrient availability, and greater cation exchange capacity than many mineral
soils.
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SEPTEMBER 2007 Chapter 2. Overview of Wetland Science
Mineral wetland soils, in addition to containing greater amounts of sand, silt, and clay than
histosols, are distinguished by changes in soil color that occur when elements such as Fe and
manganese (Mn) are reduced by microorganisms under anaerobic conditions. Reduction of Fe
leads to the development of grey or "gleyed" soil color as oxidized forms of Fe (ferric Fe, Fe3+)
are converted to reduced forms (ferrous Fe, Fe+2). In sandy soils, development of a dark-colored,
organic-rich surface layer is used to distinguish hydric soil from non-hydric (terrestrial) soil. An
organic-rich surface layer, indicative of periodic inundation or saturation, is not sufficiently thick
(<40 cm) to qualify as a histosol, which forms under near-continuous inundation.
Wetland soils serve as sites for many biogeochemical transformations. They also provide long
and short term storage of nutrients for wetland plants. Wetland soils are typically anaerobic
within a few millimeters of the soil-water interface. Water column oxygen concentrations are
often depressed due to the slow rate of oxygen diffusion through water. However, even when
water column oxygen concentrations are supported by advective currents, high rates of oxygen
consumption lead to the formation of a very thin oxidized layer at the soil-water interface.
Similar oxidized layers can also be found surrounding roots of wetland plants. Many wetland
plants are known to transport oxygen into the root zone, thus creating aerobic zones in
predominantly anaerobic soil. The presence of these aerobic (oxidizing) zones within the
reducing environment in saturated soils allows for the occurrence of oxidative and reductive
transformations to occur in close proximity to each other. For example, ammonia is oxidized to
nitrate within the aerobic zone surrounding plant roots in a process called nitrification. Nitrate
then readily diffuses into adjacent anaerobic soil, where it is reduced to molecular nitrogen via
denitrification or may be reduced to ammonium in certain conditions through dissimilatory
nitrate reduction (Mitsch and Gosselink 2000; Ruckauf et al., 2004; Reddy and Delaune, 2005).
The anaerobic environment hosts the transformations of N, P, sulfur (S), Fe, Mn, and C. Most of
these transformations are microbially mediated. The oxidized soil surface layer also is important
to the transport and translocation of transformed constituents, providing a barrier to translocation
of some reduced constituents. These transformations will be discussed in more detail below in
Biogeochemical Cycling.
VEGETATION
Wetland plants consist of macrophytes and microphytes. Macrophytes include free-floating,
submersed, floating-leaved, and rooted emergent plants. Microphytes are algae that may be free
floating or attached to macrophyte stems and other surfaces. Plants require oxygen to meet
respiration demands for growth, metabolism, and reproduction. In macrophytes, much (about
50%) of the respiration occurs below ground in the roots. Wetland macrophytes, however, live in
periodically to continuously-inundated and saturated soils and, therefore, use specialized
adaptations to grow in anaerobic soils (Cronk and Fennessy 2001). Adaptations consist of
morphological/anatomical adaptations that result in anoxia avoidance, and metabolic adaptations
that result in true tolerance to anoxia. Morphological/anatomic adaptations include shallow roots
systems, aerenchyma, buttressed trunks, pneumatophores (e.g., black mangrove (Avicennia
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SEPTEMBER 2007 Chapter 2. Overview of Wetland Science
germinans)), and lenticles on the stem. These adaptations facilitate oxygen transport from the
shoots to the roots where most respiration occurs. Many wetland plants also possess metabolic
adaptations, such as anaerobic pathways of respiration, that produce non-toxic metabolites such
as malate to mitigate the adverse effects of oxygen deprivation, instead of toxic compounds like
ethanol (Mendelssohn and Burdick 1988).
Species best adapted to anaerobic conditions are typically found in areas inundated for long
periods, whereas species less tolerant of anaerobic conditions are found in areas where
hydroperiod is shorter. For example, in southern forested wetlands, areas such as abandoned
river channels (oxbows) are dominated by obligate species such as bald cypress (Taxodium
distichuni) and tupelo gum (Nyssa aquaticd) (Wharton et.al., 1982). Areas inundated less
frequently are dominated by hardwoods such as black gum (Nyssa sylvatica\ green ash
(Fraxinuspennsylvanicus), and red maple (Acer rubrum), and the highest, driest wetland areas
are dominated by facultative species such as sweet gum (Liquidambar styraciflud) and sycamore
(Platanus occidentalis) (Wharton et.al., 1982). Herbaceous-dominated wetlands also exhibit
patterns of zonation controlled by hydroperiod (Mitsch and Gosselink 2000).
In estuarine wetlands such as salt- and brackish-water marshes and mangroves, salinity and
sulfides also adversely affect growth and reproduction of vegetation (Webb and Mendelssohn
1996; Mitsch and Gosselink 2000). Inundation with seawater brings dissolved salts (NaCl) and
sulfate. Salt creates an osmotic imbalance in vegetation, leading to desiccation of plant tissues.
However, many plant species that live in estuarine wetlands possess adaptations to deal with
salinity (Winchester et al., 1985; Whipple et al., 1981; Zheng et.al., 2004). These adaptations
include salt exclusion at the root surface, salt secreting glands on leaves, schlerophyllous (thick,
waxy) leaves, low transpiration rates, and other adaptations to reduce uptake of water and
associated salt. Sulfate carried in by the tides undergoes sulfate reduction in anaerobic soils to
produce hydrogen sulfide (H2S) that, at high concentrations, is toxic to vegetation. At sub-lethal
concentrations, H2S inhibits nutrient uptake and impairs plant growth.
SOURCES OF NUTRIENTS
Point Sources
Point source discharges of nutrients to wetlands may come from municipal or industrial
discharges, including stormwater runoff from municipalities or industries, or in some cases from
large animal feeding operations. Nutrients from point source discharges may be controlled
through the National Pollutant Discharge Elimination System (NPDES) permits, most of which
are administered by States authorized to issue them. In general, point source discharges that are
not stormwater related are fairly constant with respect to loadings.
Nonpoint Sources
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SEPTEMBER 2007 Chapter 2. Overview of Wetland Science
Nonpoint sources of nutrients are commonly discontinuous and can be linked to seasonal
agricultural activity or other irregularly occurring events such as silviculture, non-regulated
construction, and storm events. Nonpoint nutrient pollution from agriculture is most commonly
associated with row crop agriculture and livestock production that tend to be highly associated
with rain events and seasonal land use activities. Nonpoint nutrient pollution from urban and
suburban areas is most often associated with climatological events (rain, snow, and snowmelt),
when pollutants are most likely to be transported to aquatic resources.
Urban and agricultural runoff is generally thought to be the largest source of nonpoint source
pollution; however, growing evidence suggests that atmospheric deposition may have a
significant influence on nutrient enrichment, particularly from nitrogen (Jaworski et.al., 1997).
Gases released through fossil fuel combustion and agricultural practices are two major sources of
atmospheric N that may be deposited in waterbodies (Carpenter et.al., 1998). Nitrogen and
nitrogen compounds formed in the atmosphere return to the earth as acid rain or snow, gas, or
dry particles. Atmospheric deposition, like other forms of pollution, may be determined at
different scales of resolution. More information on national atmospheric deposition can be found
at: http://www.arl.noaa.gov/research/programs/airmon.html and http://nadp.sws.uiuc.edu/. These
national maps may provide the user with information about regional areas where atmospheric
deposition, particularly of nitrogen, may be of concern. However, these maps are generally low
resolution when considered at the local and site-specific scale and may not reflect areas of high
local atmospheric deposition, such as local areas in a downwind plume from an animal feedlot
operation.
Other nonpoint sources of nutrient pollution may include certain silviculture and mining
operations; these activities generally constitute a smaller fraction of the national problem, but
may be locally significant nutrient sources. Control of nonpoint source pollutants focuses on land
management activities and regulation of pollutants released to the atmosphere (Carpenter et.al.,
1998).
2.3 WETLAND NUTRIENT COMPONENTS
NUTRIENT BUDGETS
Wetland nutrient inputs mirror wetland hydrologic inputs (e.g., precipitation, surface water, and
ground water), with additional loading associated with atmospheric dry deposition and nitrogen
transformation (Figures 2.5 and 2.6). Total atmospheric deposition (wet and dry) may be the
dominant input for precipitation-dominated wetlands, while surface- or ground-water inputs may
dominate other wetland systems.
The total annual nutrient load (mg-nutrients/yr) into a wetland is the sum of the dissolved and
particulate loads. The dissolved load (mg-nutrients/s) can be estimated by multiplying the
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SEPTEMBER 2007 Chapter 2. Overview of Wetland Science
instantaneous inflow (L/s) by the nutrient concentration (mg-nutrients/L). EPA recommends
calculating the annual load by the summation of this function over the year—greater loads may
be found during periods of increased flow and EPA recommends monitoring during these
intervals. Where continuous data are unavailable, average flows and concentrations may be used
if a bias factor (Cohn et al., 1989) is included to account for unmeasured loads during high
flows. Particulate loads (mg-nutrients/yr) can be estimated using the product of suspended and
bedload inputs (kg-sediments/yr) and the mass concentrations (mg-nutrients/kg-sediment).
Surface-water nutrient inputs are associated with flows from influent streams, as well as diffuse
sources from overland flow through the littoral zone. Ground-water inputs can also be
concentrated at points (e.g., springs), or diffuse (such as seeps). The influence of allochthonous
sources is likely to be greatest in those zones closest to the source.
Because wetlands generally tend to be low-velocity, depositional environments, they often
sequester sediments and their associated nutrients. These sediment inputs generally accumulate
at or near the point of entry into the wetland, forming deltas or levees near tributaries, or along
the shoreline for littoral inputs. Coarser fractions (e.g., gravels and sands) tend to settle first; the
finer fractions (silts, clays, and organic matter) tend to settle further from the inlet point.
Particulate input from ground-water sources can usually be neglected, while particulate inputs
from atmospheric sources may be important if local or regional sources are present.
Wetland nutrient outputs again mirror hydrologic outputs (e.g., surface- and ground-water), and
loads are again estimated as the product of the flow and the concentration of nutrients in the
flow. While evaporation losses from wetlands may be significant, there are no nutrient losses
associated with this loss. Instead, loss of nutrients to the atmosphere may occur as a result of
ammonia volatilization, as well as N2O losses from incomplete denitrification. Because sediment
outputs from wetlands may be minor, nutrient exports by this mechanism may not be important.
Nutrient accumulation in wetlands occurs when nutrient inputs exceed outputs. Net nutrient
loads can be estimated as the difference between these inputs and outputs. It is important,
therefore, to have some estimate of net accumulation by taking the difference between upstream
and downstream loads. Sampling ground-water nutrient concentrations in wells located upstream
and downstream of the wetland can provide some sense of net nutrient sequestration, while
sampling wetland nutrient inflows and outflows is needed for determining the additional
sequestration for this pathway.
BlOGEOCHEMICAL CYCLING
Biogeochemical cycling of nutrients in wetlands is governed by physical, chemical, and
biological processes in the soil and water column. Biogeochemical cycling of nutrients is not
unique to wetlands, but the aerobic and anaerobic interface generally found in saturated soils of
wetlands creates unique conditions that allow both aerobic and anaerobic processes to operate
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SEPTEMBER 2007 Chapter 2. Overview of Wetland Science
simultaneously. The hydrology and geomorphology of wetlands (Johnston et.al., 2001)
influences biogeochemical processes and constituent transport and transformation within the
systems (e.g., water-sediment exchange, plant uptake, and export of organic matter).
Interrelationships among hydrology, biogeochemistry, and the response of wetland biota vary
among wetland types (Mitsch and Gosselink, 2000; Reddy and Delaune, 2005).
Biogeochemical processes in the soil and water column are key drivers of several ecosystem
functions associated with wetland values (e.g., water quality improvement through
denitrification, long-term nutrient storage in the organic matter) (Figure 2.3). The hub for
biogeochemistry is organic matter and its cycling in the soil and water column. Nutrients such as
N, P, and S are primary components of soil organic matter, and cycling of these nutrients is
always coupled to C cycling. Many processes occur within the carbon, nitrogen, phosphorus, and
sulfur (C, N, P, or S) cycles; microbial communities mediate the rate and extent of these
reactions in soil and the water column.
Aerobic-anaerobic interfaces are more common in wetlands than in upland landscapes and may
occur at the soil-water interface, in the root zones of aquatic macrophytes, and at surfaces of
detrital tissue and benthic periphyton mats. The juxtaposition of aerobic and anaerobic zones in
wetlands supports a wide range of microbial populations and associated metabolic activities,
with oxygen reduction occurring in the aerobic interface of the substrate, and reduction of
alternate electron acceptors occurring in the anaerobic zone (D'Angelo and Reddy, 1994a or b).
Under continuously saturated soil conditions, vertical layering of different metabolic activities
can be present, with oxygen reduction occurring at and just below the soil-floodwater interface.
Substantial aerobic decomposition of plant detritus occurs in the water column; however, the
supply of oxygen may be insufficient to meet demands and drive certain microbial groups to
utilize alternate electron acceptors (e.g., nitrate, oxidized forms of iron (Fe) and manganese
(Mn), sulfate, and bicarbonate
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SEPTEMBER 2007
Chapter 2. Overview of Wetland Science
Submerged
macrophyte
Emergent
macrophyte
Periphyton
"Water
Bioavailable
nutrients
Figure 2.3 Schematic showing basic nutrient cycles in soil-water column of a wetland.
Soil drainage adds oxygen to the soil, while other inorganic electron acceptors may be added
through hydraulic loading to the system. Draining wetland soil accelerates organic matter
decomposition due to the introduction of oxygen deeper into the profile. In many wetlands, the
influence of NOs and oxidized forms of Mn and Fe on organic matter decomposition is minimal.
This is because the concentrations of these electron acceptors are usually low as a result of the
fact that they have greater reduction potential than other alternate electron acceptors, so they
generally are depleted rapidly from systems. Long-term sustainable microbial activity is then
supported by electron acceptors of lower reduction potentials (sulfate and HCOs).
Methanogenesis is often viewed as the terminal step in anaerobic decomposition in freshwater
wetlands, whereas sulfate reduction is viewed as the dominant process in coastal wetlands.
However, both processes can function simultaneously in the same ecosystem and compete for
available substrates (Capone and Kiene 1988).
A simple way to characterize wetlands for aerobic and anaerobic zones is to determine the
oxidation-reduction potential or redox potential (Eh) of the soil-water column (Figure 2.4).
Redox potential is expressed in units of millivolts (mV) and is measured using a voltmeter
coupled to a platinum electrode and a reference electrode. Typically, wetland soils with Eh
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SEPTEMBER 2007
Chapter 2. Overview of Wetland Science
values >300 mV are considered aerobic and typical of drained soil conditions, while soils with
Eh values <300 mV are considered anaerobic and are devoid of molecular oxygen (Figure 2.4).
-3
Ana
DIL [
prnhic 4
H'9h|y Reduced
Reduced
1 1 1 1
Moderately
Reduced
fc Aorohic
Oxidized
I I I I I I I
I
00 -100 0 100 300 500 700
Oxidation-Reduction Potential (mV)
Figure 2.4. Range of redox potentials in wetland soils (Reddy and Delaune 2007).
Wetlands, as low-lying areas in the landscape, receive inputs from all hydrologically connected
uplands. Many wetlands are open systems receiving inputs of carbon (C) and nutrients from
upstream portions of the watershed that can include agricultural and urban areas.
Prolonged nutrient loading to wetlands can result in distinct gradients in water and soil. Mass
loading and hydraulic retention time determine the degree and extent of nutrient enrichment.
Continual nutrient loading to an oligotrophic wetland can result in a zone of high nutrient
availability near the input, and low nutrient availability and possibly nutrient limiting conditions
further from the input point. This enrichment effect can be seen in many freshwater wetlands,
most notably in the sub-tropical Everglades where light is abundant and temperatures are high
(Davis, 1991; Reddy et al., 1993; Craft and Richardson, 1993 a, b; DeBusk et al., 1994), and in
some estuarine marshes (Morris and Bradley 1999). Between these two extremes, there can exist
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SEPTEMBER 2007
Chapter 2. Overview of Wetland Science
a gradient in quality and quantity of organic matter, nutrient accumulation, microbial and
macrobiotic communities, composition, and biogeochemical cycles.
Compared to terrestrial ecosystems, most wetlands show an accumulation of organic matter, and
therefore wetlands function as global sinks for carbon. Accumulation of organic C in wetlands is
primarily a result of the balance of C fixation through photosynthesis and losses through
decomposition. Rates of photosynthesis in wetlands are typically higher than in other ecosystems,
and rates of decomposition are typically lower due to anaerobic conditions, hence organic matter
tends to accumulate. In addition to maintaining proper functioning of wetlands, organic matter
storage also plays an important role in regulating other ecosystems and the biosphere. For example,
organic matter contains substantial quantities of N, P, and S; therefore, accumulation of organic
matter in wetlands decreases transport of these nutrients to downstream aquatic systems.
NITROGEN (N):
Nitrogen enters wetlands in organic and inorganic forms, with the relative proportion of each
depending on the input source. Organic forms are present in dissolved and particulate fractions,
while inorganic N (NFL^N, NOs-N and NO2-N) is present in dissolved fractions (Figure 2.5) or
bound to suspended sediments (NH4-N). Particulate fractions are removed through settling and
burial, while the removal of dissolved forms is regulated by various biogeochemical reactions
functioning in the soil and water column. Relative rates of these processes are affected by
physico-chemical and biological characteristics of plants, algae, and microorganisms.
Atmospheric
Deposition
Plant biomass
NH3
N2 N2O
inflow
Outflow
Litterfall
Volatilization
Plant ^A^;
Denitrification
Microbial
Organic N •**• Biomass N Adsorbed NH4+
Soil - ANAEROBIC
— N2. N20 (g)
Figure 2.5. Schematic of the nitrogen cycle in wetlands.
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SEPTEMBER 2007 Chapter 2. Overview of Wetland Science
Nitrogen reactions in wetlands effectively process inorganic N through nitrification and
denitrification, ammonia volatilization, and plant uptake. These processes aid in lowering levels
of inorganic N in the water column. A significant portion of dissolved organic N assimilated by
plants is returned to the water column during breakdown of detrital tissue or soil organic matter,
and the majority of this dissolved organic N is resistant to decomposition. Under these
conditions, water leaving wetlands may contain elevated levels of N in organic form. Exchange
of dissolved nitrogen species between soil and water column support several nitrogen reactions.
For example, nitrification in the aerobic soil layer is supported by ammonium flux from the
anaerobic soil layer. Similarly, denitrification in the anaerobic soil layer is supported by nitrate
flux from the aerobic soil layer and water column. Relative rates of these reactions will,
however, depend on the environmental conditions present in the soil and water column (Reddy
and Delaune 2007).
PHOSPHORUS (P):
Phosphorus retention by wetlands is regulated by physical (sedimentation and entrainment),
chemical (precipitation and flocculation), and biological mechanisms (uptake and release by
vegetation, periphyton, and microorganisms). Phosphorus in the influent water is found in
soluble and particulate fractions, with both fractions containing a certain proportion of inorganic
and organic forms. Relative proportions of these pools depend on the input source. For example,
municipal wastewater may contain a large proportion (>75%) as inorganic P in soluble forms, as
compared to effluents from agricultural watersheds where a greater percentage of P loading may
be in the particulate fraction.
Phosphorus forms that enter a wetland are grouped into: (i) dissolved inorganic P (DIP); (ii)
dissolved organic P (DOP); (iii) particulate inorganic P (PIP); and, (iv) particulate organic P
(POP) (Figure 2.6). The particulate and soluble organic fractions may be further separated into
labile and refractory components. Dissolved inorganic P is generally bioavailable, whereas
organic and particulate P forms generally must be transformed into inorganic forms before
becoming bioavailable. Both biotic and abiotic mechanisms regulate relative pool sizes and
transformations of P compounds within the water column and soil. Alterations in these fractions
can occur during flow through wetlands and depend on the physical, chemical, and biological
characteristics of the systems. Thus, both biotic and abiotic processes should be considered when
evaluating P retention capacities of wetlands. Biotic processes include assimilation by
vegetation, plankton, periphyton, and microorganisms. Abiotic processes include sedimentation,
adsorption by soils, precipitation, and exchange processes between soil and the overlying water
column (Reddy et.al., 1999, 2005; Reddy and Delaune, 2007). The processes affecting
phosphorus exchange at the soil/sediment water interface include: (i) diffusion and advection due
to wind-driven currents; (ii) diffusion and advection due to flow and bioturbation; (iii) processes
within the water column (mineralization, sorption by particulate matter, and biotic uptake and
release); (iv) diagenetic processes (mineralization, sorption, and precipitation dissolution) in
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SEPTEMBER 2007
Chapter 2. Overview of Wetland Science
bottom sediments; (v) redox conditions (C>2 content) at the soil/sediment-water interface; and,
(vi) phosphorus flux from water column to soil mediated by evapotranspiration by vegetation.
Atmospheric
Deposition
Plant biomass P
Water Column
Soil - AEROBIC
s " Ty\ ^ R1 — *
| vftv Peat
mo • > / ^^V accretion
\ ^/m v
\> - POP' — > n(
OOP"- '
1 / [Fe, Al or
Pip Ca-bound
^ P]
J Adsorbed $
DP |p
So/7 - ANAEROBIC
Figure 2.6. Schematic of the Phosphorous cycle in wetlands.
The key biogeochemical services provided by wetlands include nutrient transformation and
removal by decreasing concentrations of nutrients and other contaminants, and sequestration of
carbon and nutrients into stable pools (Kadlec and Knight 1996). The biogeochemical processes
regulating water quality improvement are well established, and are made use of in treatment
wetlands. Increased nutrient loading to oligotrophic wetlands results in increased primary
productivity and nutrient enrichment. This resulting eutrophication can have both positive and
negative impacts to the environment. Higher rates of primary productivity increase rates of
organic matter accumulation, thus increasing carbon sequestration. However, eutrophication
may lead to increased periodic and episodic export of DIP (Kadlec and Knight 1996; Reddy
et.al., 1995, 1996, 2005; Reddy and Delaune 2007)).
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SEPTEMBER 2007 Chapter 3. Classification of Wetlands
Chapter 3 Classification of Wetlands
3.1 INTRODUCTION
Developing individual, site-specific nutrient criteria is not practical for every wetland. Instead,
criteria for groups of similar wetlands in a region are needed. To this end, a means of grouping
or classifying wetlands is required. This chapter introduces the scientific rationale for classifying
wetlands, reviews some common classification schemes, and discusses their implications for
establishing nutrient criteria for wetlands. Use of a common scheme across State boundaries
should facilitate collaborative efforts in describing reference condition for biota or water quality
and in developing assessment methods, indices of biotic integrity (IBI) (USEPA 1993b,
http://www.epa.gov/emap/remap/index.html), nutrient-response relationships, and nutrient
criteria for wetlands. This chapter describes a series of national classification systems that could
be used to provide a common framework for development of nutrient criteria for wetlands, and
suggests ways in which these classification schemes could be combined in a hierarchical fashion.
Many existing classification schemes may be relevant and should be considered for use or
modification, even if they were not originally derived for wetland nutrient criteria because: 1)
they incorporate key factors that control nutrient inputs and cycling; 2) they have already been
mapped; and, 3) they have been incorporated into sampling, assessment, and management
strategies for wetland biology or for other surface water types, thus facilitating integration of
monitoring strategies. Adoption of any classification scheme should be an iterative process,
whereby initial results of biological or water quality sampling are used to test for actual
differences in reference condition for nutrients or nutrient-response relationships among
proposed wetland classes. Wetland classes that behave similarly can be combined, and apparent
outliers in distributions of nutrient concentrations from reference sites or in nutrient-response
relationships can be examined for additional sources of variability that may need to be
considered. In addition, new classification schemes can be derived empirically through many
multivariate statistical methods designed to determine factors that can discriminate among
wetlands based on nutrient levels or nutrient-response relationships.
The overall goal of classification is to reduce variability within classes due to differences in
natural condition related to factors such as geology, hydrology, and climate. This will minimize
the number of classes for which reference conditions must be defined. For example, we would
expect different conditions for water quality or biological community composition for wetland
classes in organic soils (histosols), compared to wetlands in mineral soils. In assessing impacts to
wetlands, comparing a wetland from within the same class would increase the precision of
assessments, enable more sensitive detection of change, and reduce errors in characterizing the
status of wetland condition.
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SEPTEMBER 2007 Chapter 3. Classification of Wetlands
REFERENCE CONCEPT
Reference conditions "describe the characteristics of waterbody segments least impaired by
human activities and are used to define attainable biological or habitat conditions" (USEPA
1990, Stoddard et.al., 2006). At least two general approaches have been defined to establish
reference condition—the site-specific and the regional (U.S. EPA 1990b,
http://www.epa.gov/bioindicators/). The current approach to developing water quality criteria for
nutrients also emphasizes the identification of expected ranges of nutrients by waterbody type
and ecoregion for the least-impaired reference conditions (U.S. EPA 1998,
http ://www. epa. gov/waterscience/standards/nutrient.html).
Although different concepts of reference condition have been used in other programs (e.g., for
evaluation of wetland mitigation projects (Smith et.al., 1995;
http://el.erdc.usace.army.mil/wetlands/pdfs/wrpde9.pdf)), for the purposes of this document, the
term "reference condition" refers to wetlands that are minimally or least impacted by human
activities. Most, if not all, wetlands in the U.S. are affected to some extent by human activities
such as acid precipitation, global climate change, or other atmospheric deposition of nitrogen
and mercury, and changes in historic fire regime. "Minimally impacted" is therefore
operationally defined by choosing sites with fewer stressors or fewer overall impacts as
described by indicators of stressors, such as land-use or human activities within the watershed or
buffer area surrounding a wetland and source inputs. Identifying reference wetlands in areas of
high local or regional atmospheric deposition of nitrogen should also be carefully considered
because indicators such as local land use activities may not be sufficient to indicate nutrient
enrichment from dry or wet air deposition.
3.2 EXISTING WETLAND CLASSIFICATION SCHEMES
There are two different approaches for classification of aquatic resources. One is geographically-
based, and the other is independent of geography but relies on environmental characteristics that
determine aquatic ecosystem status and vulnerability at the region-, watershed-, or ecosystem-
scale (Detenbeck et.al., 2000). Ecoregions (including "nutrient ecoregions") and Ecological
Units represent geographically-based classification schemes that have been developed and
applied nation-wide (Omernik 1987, Keys et.al., 1995). The goal of geographically-based
classification schemes is to reduce variability in reference condition based on spatial co-variance
in climate and geology, along with topography, vegetation, hydrology, and soils.
Geographically-independent or environmentally-based classification schemes include those
derived using watershed characteristics such as land-use and/or land-cover (Detenbeck et.al.,
2000), hydro geomorphology (Brinson 1993), vegetation type (Grossman et.al., 1998), or some
combination of these (Cowardin et.al., 1979). Both geographically- and environmentally-based
schemes have been developed for wetland classification. These approaches can be applied
individually or combined within a hierarchical framework (Detenbeck et.al., 2000).
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SEPTEMBER 2007 Chapter 3. Classification of Wetlands
GEOGRAPHICALLY-BASED CLASSIFICATION SCHEMES
Regional classification systems were first developed specifically for the United States by land
management agencies. The U.S. Department of Agriculture (USD A) has described a hierarchical
system of Land Resource Regions and Major Land Resource Areas based mainly on soil
characteristics for agricultural management (USDA SCS 1981). Ecoregions were then refined for
USDA and the U.S. Forest Service based on a hierarchical system in which each of several
environmental variables such as climate, landform, and potential natural vegetation were applied
to define different levels of classification (Bailey 1976). Subsequently, Omernik and colleagues
developed a hierarchical, nationwide ecoregion system to classify streams using environmental
features they expected would influence aquatic resources, as opposed to terrestrial resources
(Hughes and Omernik 1981, Omernik et.al., 1982). The latter was based on an overlay of
"component maps" for land use, potential natural vegetation, land-surface form, and soils, along
with a subjective evaluation of the spatial congruence of these factors as compared to the
hierarchical approach used by Bailey, which relied only on natural features (not land-use).
Omernik has produced a national map of 84 ecoregions defined at a scale of 1:7,500,000 (Figure
3.1; Omernik 1987, http://water.usgs.gov/GIS/metadata/usgswrd/XML/ecoregion.xml). More
detailed, regional maps have been prepared at a scale of 1:2,500,000 in which the most "typical"
areas within each ecoregion are defined. Cowardin et.al., (1979) have suggested an amendment
to Bailey's ecoregions to include coastal and estuarine waters (Figure 3.2a). In practice,
Omernik's scheme has been more widely used for geographic classification of aquatic resources
such as streams, but few examples to verify the appropriateness of this grouping to wetland
nutrients are available.
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SEPTEMBER 2007
Chapter 3. Classification of Wetlands
Figure 3.1 Map of Omernik aquatic ecoregions.
PROVINCE
SECTION
5. WEST
INDIAN
BOUNDARIES OF
10 MARINE AMD ESTUflRINE
PROVINCES
Figure 3.2a. Map of Bailey ecoregions with coastal and estuarine provinces
(Cowardin et al., 1979).
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SEPTEMBER 2007
Chapter 3. Classification of Wetlands
Figure 3.2b. Legend
"Domains, Divisions, Provinces, and Sections used on Bailey's (1976) map and described in detail in Bailey
(1978). Highland ecoregions are designated M mountain, P plateau, and A altiplano.
1000 Polar
1200 Tundra
1210 Arctic Tundra
1220 Bering Tundra
M1210 Brooks Range
1300 Subarctic
1310 Yukon Parkland
1320 Yukon Forest
M1310 Alaska Range
2000 Humid Temperate
2100 Warm Continental
2110 Laurentian Mixed Forest
2111 Spruce-Fir Forest
2112 Northern Hardwoods-Fir Forest
2113 Northern Hardwoods Forest
2114 Northern Hardwoods-Spruce Forest
M2110 Columbia Forest
M2111 Douglas-fir Forest
M2112 Cedar-Hemlock-Douglas-fir Forest
2200 Hot Continental
2210 Eastern Deciduous Forest
2211 Mixed Mesophytic Forest
2212 Beech-Maple Forest
2213 Maple-Basswood Forest + Oak Savanna
2214 Appalachian Oak Forest
2215 Oak-Hickory Forest
2300 Subtropical
2310 Outer Coastal Plain Forest
2311 Beech-Sweetgum-Magnolia-Pine-Oak
2312 Southern Floodplain Forest
2320 Southeastern Mixed Forest
2400 Marine
2410 Willamette-Puget Forest
M2410 Pacific Forest (in conterminous U.S.)
M2411 Sitka Spruce-Cedar-Hemlock Forest
M2412 Redwood Forest
M2413 Cedar-Hemlock-Douglas-fir Forest
M2414 California Mixed Evergreen Forest
M2415 Silver fir-Douglas-fir Forest
M2410 Pacific Forest (in Alaska)
2500 Prairie
2510 Prairie Parkland
2511 Oak-Hickory-Bluestern Parkland
2512 Oak + Bluestem Parkland
2520 Prairie Brushland
2521 Mesquite-Buffalo Grass
2522 Juniper-Oak-Mesquite
2523 Mesquite-Acacia
2530 Tall-Grass Prairie
2531 Bluestem Prairie
2532Whestgrass-Bluestem-Needlegrass
2533 Bluestem-Gamma Prairie
2600 Mediterranean (Dry-summer Subtropical)
2610 California Grassland
M2610Sierran Forest
M2620 California Chaparral
3000 Dry 3100 Steppe
3110 Great Plains-Shortgrass Prairie
3111 Gramma-Needlegrass-Wheatgrass
3112 Wheatgrass-Needlegrass
3113 Grama-Buffalo Grass
M3110 Rocky Mountain Forest
M3111 Grand-fir-Douglas-fir Forest
M3112 Douglas-fir Forest
M3113 Ponderosa Pine-Douglas-fir Forest
3120 Palouse Grassland
M3120 Upper Gila Mountains Forest
3130 Intermountain Sagebrush
3131 Sagebrush-Wheatgrass
3132 LahontanSaltbush-Greasewood
3133 Great Basin Sagebrush
3134 Bonneville Saltbush-Greasewood
3135 Ponderosa Shrub Forest
P3130 Colorado Plateau
P3131 Juniper-Pinyon Woodland + Sagebrush Saltbush Mosaic
P3132 Grama-Galleta Steppe + Juniper-Pinyon Woodland Mosaic
3140 Mexican Highland Shrub Steppe
A3140 Wyoming Basin
A3141 Wheatgrass- Need legrass-Sagebrush
A3142 Sagebrush-Wheatgrass
3200 Desert 3210 Chihuahuan Desert
3211 Grama-Tobosa
3212Tarbush-CreosoteBush
3220 American Desert
3221 Creosote Bush
3222 Creosote Bush-Bur Sage
4000 Humid Tropical
4100 Savanna
4110 Everglades
4200 Rainforest
M4210 Hawaiian Islands
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SEPTEMBER 2007 Chapter 3. Classification of Wetlands
Finally, an attempt has been made to integrate approaches across Federal agencies to produce
regional boundaries termed Ecological Units (Keys et.al., 1995). Information has been combined
on climate, landform, geomorphology, geology, soils, hydrology, and potential vegetation to
produce a nested series of boundaries for the eastern U.S. Different combinations of
environmental parameters are emphasized at each hierarchical level of classification. This
scheme was developed to explain variation in both terrestrial and aquatic systems, and is
consistent with a more comprehensive strategy to classify lotic systems down to the level of
stream reaches (Maxwell et.al., 1995). The mapped system for the eastern U.S. includes
classification at the following levels:
domain (n=2) > divisions (n=5) > provinces (n=14) > sections (n=78) > subsections (n=xxx),
where Sections are roughly half the size of Omernik ecoregions (Figure 3.3). For lotic systems,
additional spatial detail can be added by defining watersheds (at the level of land type
associations), subwatersheds (at the level of land types), valley segments, stream reaches, and,
finally, channel units (Maxwell et.al., 1995). In reality, not all watersheds nest neatly within
subsections, and may cross-subsection boundaries.
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SEPTEMBER 2007
Chapter 3. Classification of Wetlands
a. Domain
b. Division
231 Southeastern
Mixed Fccest
231A. Southern
Appalachian Piedmon
e. Province
d. Section
Figure 3.3 Examples of first four hierarchical levels of Ecological Units:
domain, division, province, and section, from USEPA Environmental
Atlas.
Some States have chosen to refine the spatial resolution of Omernik's ecoregional boundaries for
management of aquatic resources (e.g., Region 3 and Florida). For example, the State of Florida
has defined subecoregions for streams based on analysis of macroinvertebrate data from 100
36
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SEPTEMBER 2007 Chapter 3. Classification of Wetlands
minimally-impacted sites. Efforts are currently underway to define ecoregions for Florida
wetlands based on variables influencing the water budget and plant community composition
(Dougherty et.al., 2000, Lane 2000).
ENVIRONMENTALLY-BASED CLASSIFICATION SYSTEMS
Wetland habitat types are described very simply but coarsely by Shaw and Fredine (1956,
Circular 39), ranging from temporarily-flooded systems to ponds. A more refined hierarchical
classification system is available based on vegetation associations; for example, the system
developed by the Nature Conservancy for terrestrial vegetation includes some wetland types
(Grossman et.al., 1998). Vegetation associations have also been used to classify Great Lakes
coastal wetlands within coastal geomorphic type (Michigan Natural Features Inventory 1997).
COWARDIN CLASSIFICATION SYSTEM
The Cowardin classification system (Cowardin et.al., 1979) was developed for the U.S. Fish and
Wildlife Service (FWS) as a basis for identifying, classifying, and mapping wetlands, special
aquatic sites, and deepwater aquatic habitats. The Cowardin system combines a number of
approaches incorporating landscape position, hydrologic regime, and habitat (vegetative) type
(http://www.nwi.fws.gov) (Figure 3.4). Wetlands are categorized first by landscape position
(tidal, riverine, lacustrine, and palustrine), then by cover type (e.g., open water, submerged
aquatic bed, persistent emergent vegetation, shrub wetlands, and forested wetlands), and then by
hydrologic regime (ranging from saturated or temporarily-flooded to permanently flooded).
Modifiers can be added for different salinity or acidity classes, soil type (organic vs. mineral), or
disturbance activities (impoundment, beaver activity). Thus, the Cowardin system includes a
mixture of geographically-based factors, proximal forcing functions (hydrologic regime, acidity),
anthropogenic disturbance regimes, and vegetative outcomes. In practice, the Cowardin system
can be aggregated by combination of hydrogeomorphic (HGM) type and predominant vegetation
cover if digital coverages are available (Ernst et.al.,1995).
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SEPTEMBER 2007
Chapter 3. Classification of Wetlands
UIW »*1tl
b SFftSfKUUlY^ FtHOWO
I SEMPEHHAMEHTLY FLDODEQ
1 SATURATED
Figure 3.4. (Top) Cowardin hierarchy of habitat types for estuarine systems;
(Bottom) Palustrine systems, from Cowardin et.al., 1979.
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SEPTEMBER 2007
Chapter 3. Classification of Wetlands
HYDROGEOMORPfflC CLASSIFICATION SYSTEM(S)
Brinson (1993) has defined a hydrogeomorphic classification system for wetlands based on
geomorphic setting, dominant water source (Figure 3.5), and dominant hydrodynamics (Figure
3.6; http://www.wes.army.mil/el/wetlands). Seven classes have been described: depressional,
lacustrine fringe, tidal fringe, slope, riverine, mineral soil flats, and organic soil flats (Smith
et.al., 1995). Also see Hydrogeomorphic Classification in
http://www.epa.gov/waterscience/criteria/wetlands/7Classification.pdf
(o)
' PRtClPlTATlOM •"••,„;
(b)
>nr\
'...=» - *}
".I',. -(I *C_
^W-V.K'AU '' . ' '''.'•-
Figure 3.5. Dominant water sources to wetlands, from Brinson 1993.
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SEPTEMBER 2007
Chapter 3. Classification of Wetlands
(a)
VERTICAL
S-LUCIUATIONS
UNIDIRECTIONAL
FLOW
BIDIRECTIONAL
FLOW
Figure 3.6. Dominant hydrodynamic regimes for wetlands based on flow pattern (Brinson 1993).
Depressional systems, as the name implies, are located in topographic depressions where surface
water can accumulate. Depression wetlands can be further classified based on presence of inlets
or outlets and primary water source as closed, open/groundwater, or open/surface water
subclasses.
Lacustrine fringe wetlands are located along lake shores where the water elevation of the lake
determines the water table of the adjacent wetland. Great Lakes coastal wetlands represent one
important region of lacustrine fringe wetlands. These coastal systems are strongly influenced by
coastal forming processes, and, as such, have been further classified by geomorphic type through
various schemes (Jaworski and Raphael 1979, and others summarized in Michigan Natural
Features Inventory 1997). These geomorphic coastal positions will further influence the
predominant source of water and the degree and type of energy regime (riverine vs. seiche and
wave activity). Tidal fringe wetlands occupy a similar position relative to marine coasts and
estuaries, where water level is influenced by sea level. Tidal fringe wetlands can be broken down
further based on salinity into euhaline vs. mixohaline subclasses. Slope wetlands occur on slopes
where groundwater discharges to the land surface, but typically do not have the capacity for
surface water storage (Figure 3.7). Riverine wetlands are found in floodplains and riparian zones
associated with stream channels. Riverine systems can be broken down based on watershed
position (and, thus, hydrologic regime) into tidal, lower perennial, upper perennial, and
nonperennial subclasses. Mineral soil flats are in areas of low topographic relief (e.g.,
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SEPTEMBER 2007
Chapter 3. Classification of Wetlands
interfluves, relic lake bottoms, and large floodplain terraces) with precipitation as the main
source of water. The topography of organic soil flats (e.g., peatlands), in contrast, is controlled
by the vertical accretion of organic matter.
LAKE SURFACE
a. Seepage race where grourxtoalftr flow Imersecls [he land surg
SEEPAGE AT BASE
^Ti ^\ a g
LINES OF EQUAL o o ° ^^f( -j
HY3RAULK HEAD ^^^r' \
~\ \
b Seepage in the lov/ere ota portion of the break
Figure 3.7. Interaction with break in slope with groundwater inputs to slope wetlands (Brinson
1993).
The HGM classification system is being further refined to the subclass level for different regions
or States and classes (Cole et.al., 1997, http://www.wes.army.mil/el/wetlands). In addition to the
classification factors described above, Clairain (2002) suggests using parameters such as the
degree of connection between the wetland and other surface waters (depressional wetlands),
salinity gradients (tidal), degree of slope or channel gradient (slope and riverine wetlands),
position in the landscape (riverine, slope), and a scaling factor (stream order, watershed size or
floodplain width for riverine subclasses). In some cases, existing regional schemes have been
used as the basis for subclass definition (e.g., Stewart and Kantrud 1971, Golet and Larson 1974,
Wharton et.al., 1982, Weakley and Schafale 1991, Keough et.al., 1999).
The HGM classification system has been applied primarily to assess wetland functions related to
hydrology, biological productivity, biogeochemical cycling, and habitat (Smith et.al., 1995,
http://www.wes.army.mil/el/wetlands/pdfs/wrpde9.pdf). The same environmental parameters
that influence wetland functions also determine hydrologic characteristics and background water
quality, which in turn drive wetland habitat structure and community composition and the timing
of biotic events. Thus, the HGM classification system can serve as a basis for partitioning
variability in reference trophic status and biological condition, as well as defining temporal
strategies for sampling.
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SEPTEMBER 2007 Chapter 3. Classification of Wetlands
COMPARISON OF ENVIRONMENTALLY-BASED CLASSIFICATION SYSTEMS
If an integrated assessment of aquatic resources within a watershed or region is desired, it may
be useful to consider intercomparability of classification schemes for wetlands, lakes, and
riverine systems to promote cost-effective sampling and ease of interpretation. The HGM
approach could integrate readily with a finer level of classification for lake type because lentic
systems are separated out as lacustrine fringe or depressional wetlands based on lake or pond
size and influence of water level on the adjacent wetland. Lacustrine classification systems for
water quality have included geography (climate + bedrock characteristics, Gorham et.al., 1983)
or hydrologic setting (Winter 1977, Eilers et.al., 1983) as factors for categorization. McKee
et.al., (1992) suggest a modification of Cowardin's system for Great Lakes coastal wetlands
incorporating landscape position (system), depth zone (littoral vs. limnetic subsystems),
vegetative or substrate cover (class and subclass), and modifiers of ecoregions, water level
regimes, fish community structure, geomorphic structure, and human modification. In contrast,
the Michigan Natural Features Inventory (1997) categorizes Great Lakes coastal wetlands by
Great Lake, then nine unique geomorphic types within lakes, then vegetative association.
For lotic systems, Brinson et.al., (1995) describes an approach to further classify riverine classes
into subclasses based on watershed position and stream size/permanence. This strategy is
consistent with current monitoring efforts to develop stream IBIs (Indices of Biotic Integrity),
which typically use stream order as a surrogate for watershed size in explaining additional
background variation in IBI scores (USEPA 1996). A more detailed classification of stream
reach types, based on hydrogeomorphic character, is described by Rosgen (1996). This
classification scheme has been predominantly applied to assessments of channel stability and
restoration options, and not to development of criteria. Gephardt et.al., (1990) described a cross-
walk between riparian and wetland classification and description procedures.
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SEPTEMBER 2007 Chapters. Classification of Wetlands
COMBINATIONS OF GEOGRAPHIC AND ENVIRONMENTALLY-BASED APPROACHES
It is possible to combine geographically-based classification with hydrogeomorphic and/or
habitat-based approaches. For example, a scheme could be defined that nests Cowardin
(Cowardin et.al., 1979) vegetative cover class within HGM class within ecoregion. Maxwell
et.al., (1995) have defined a scheme for linking geographically-based units based on geoclimatic
setting (domains => divisions => provinces => sections => subsections) to watersheds and
subwatersheds, and thus to riverine systems composed of valley segments, stream reaches, and
channel units, or to lacustrine systems composed of lakes, lake depth zones, and lake
sites/habitat types.
Maxwell et.al., (1995) also define a series of fundamental hydrogeomorphic criteria for
classifying wetlands based on Brinson (1993) and Winter (1992), including physiography
(landscape position), water source, hydrodynamics, and climate. The first three of these are
similar to the HGM classification system (see summary tables in Keys et.al., 1995). Finer scale
variation in landforms is also discussed and may be of use in determining the dominance of
different hydrogeomorphic classes of wetlands and associated surface waters (lakes and rivers).
Characteristics and relative advantages and disadvantages of different classification systems are
summarized in Table 3.2.
3.3 SOURCES OF INFORMATION FOR MAPPING WETLAND CLASSES
In order to select wetlands for sampling in a random- or random-stratified design (described in
Chapter 4), it is important to have a record of wetland locations to choose from, preferably
categorized by the classification system of interest. For some, but not all portions of the country,
wetlands have been mapped from aerial photography through the National Wetlands Inventory
(NWI) maintained by the U.S. Fish and Wildlife Service (http://www.fws.gov/nwi/: Dahl 2005).
In other cases, individual States have developed inventories, or researchers have developed lists
for specific types of wetlands within a given region, e.g., Great Lakes coastal wetlands
(Herdendorf et.al., 1981). In order to sample these mapped wetland areas in a random fashion, it
is important to have a list of each wetland that occurs within each class and its associated area. A
geographic information system (GIS) allows one to automatically produce a list of all wetland
polygons by type within a specified geographic region. Sources of digital information for
mapping and/or classifying wetlands in a GIS are presented in the Land-Use Characterization for
Nutrient and Sediment Risk Assessment Module
(http://www.epa.gov/waterscience/criteria/wetlands/17LandUse.pdf).
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SEPTEMBER 2007
Chapter 3. Classification of Wetlands
Table 2. Comparison of landscape and wetland classification schemes.
Classification
scheme
Bailey's ecoregions
Omernik ecoregions
Ecological units
(Maxwell et.al., 1995)
USAGE
Hydrogeomorphic
Classes
Rosgen channel
types
Scale
Nationwide
Nationwide
Nationwide
Nationwide at
class level;
regionalized at
subclass level
Nationwide
Hierarchical?
Yes
No
Yes
Yes - limited
Yes
Levels of strata
Domains
Divisions
Provinces
Sections
Ecoregions
Subecoregions
Domain
Divisions
Provinces
Sections
Subsections
Class
Subclass
Level I
Level II
Advantages
Only natural
attributes
included
Digital maps
Digital maps
Digital maps
Specific for
wetlands
Captures
differences
in hydrologic
regime for
riverine
wetlands
Disadvantages
Terrestrial basis
Untested for wetlands
No hydrology
Combines land-use
with natural
attributes
Untested for most
wetlands
No hydrology
Greater number of
strata and units
than for ecoregions
Untested for wetlands
Subclasses not
comparable across
different regions
More focused on
instream channel
form than riparian
characteristics
Riverine only
Not mapped
Potential links with other schemes
Could form first strata for any of the
schemes below ecological units
Could form first strata for any of the
schemes below ecological units
Could form first strata for any of the
schemes below ecological units
Ties to classification schemes
already defined within
hydrogeomorphic types
Intermediate strata between
geographic and habitat-scale
Intermediate strata between hydro-
geomorphic type and habitat-
scale
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SEPTEMBER 2007
Chapter 3. Classification of Wetlands
Table 2. Comparison of landscape and wetland classification schemes.
Classification
scheme
Anderson land-cover
classes
Circular 39 classes
National Wetland
Inventory
Vegetation
associations
Scale
Nationwide
Nationwide
Nationwide
International
Hierarchical?
Yes
No
Yes
Yes
Levels of strata
Level 1
Level II
Level III
Class
System
Subsystem
Class
Subclass
Hydrologic
modifier
Other modifiers
System
Formation class
Formation
subclass
Formation group
Formation
subgroup
Formation
alliance
Association
Advantages
Common basis
for land-
use/land-
cover
mapping
Popular
recognition
Digital maps
available for
much of
nation (but
smallest
wetlands
omitted)
Consistency
across
terrestrial
and aquatic
systems
Disadvantages
Not functionally based
Mixture of criteria used
to distinguish
classes
Not mapped
Inconsistencies in
mapping water
quality modifiers
Limited consideration
of
hydrogeomorphic
type
Not functionally based
No digital maps
Taxa specific
Potential links with other schemes
Cross-walk w NWI system possible
Strata below geographic but
contains mixture of
hydrogeomorphic type and
habitat type
Strata below geographic
Hydrogeomorphic class could be
improved by linkw HGM system
Could be used as lowest level within
other schemes
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SEPTEMBER 2007 Chapters. Classification of Wetlands
In areas for which digital NWI maps do not yet exist, potential wetland areas can be mapped
using GIS tools to predict relative wetness (e.g., Phillips 1990) or soil survey maps with hydric
soil series can be used. It should be noted that in areas in which hydrology has been significantly
altered (e.g., through ditching, tiling, or construction of urban stormwater systems), areas of
potential wetlands could have been removed already. Similarly, although there are no current
maps of wetlands by hydrogeomorphic class, these could be derived through GIS techniques
using a combination of wetland coverages, hydrography (adjacency to large lakes and rivers),
and digital elevation models to derive landforms (mineral and organic soil flats) and/or
landscape position (slope and depressional wetlands).
3.4 DIFFERENCES IN NUTRIENT REFERENCE CONDITION OR SENSITIVITY
TO NUTRIENTS AMONG WETLAND CLASSES
Very few studies to verify classification systems for wetland nutrient monitoring have been
completed, although a number of monitoring strategies have been implemented based on pre-
selected strata. Monitoring efforts to develop or assess biological criteria generally have used a
combination of geographic region and hydrogeomorphic class or subclass (e.g., Cole et.al., 1997,
Bennett 1999, Apfelbeck 1999, Michigan Natural Features Inventory 1997). Analysis of plant
associations has been used to derive empirical classifications based on factors such as landscape
position, water source, climate, bedrock, and sediment hydraulic conductivity (Weakley and
Schafale 1991, Nicholson 1995, Halsey et.al., 1997, Michigan Natural Features Inventory 1997).
Only one case of classification based on wetland macroinvertebrate composition was found. For
Australian wetlands, wetland classes grouped by macroinvertebrate communities were
distinguished by water chemistry extremes (low pH, high salinity), degree of nutrient
enrichment, and water color (Growns et.al., 1992).
In some cases (e.g., northern peatlands) classification criteria derived on the basis of plant
associations are less powerful in discriminating among nutrient regimes (e.g., Nicholson 1995);
this may be particularly true where variation in vegetation type is related to differences in major
ion chemistry and pH, rather than nutrients. The same is true in southern pocosins, where short
and tall pocosins differ in seasonal hydrology but not soil chemistry. However, when contrasting
pocosins and swamp forests, soil nutrients differed strongly (Bridgham and Richardson 1993).
For some potential indicators of nutrient status such as vegetation nitrogen to phosphorus ratios,
indicator thresholds will be consistent across species (Koerselman and Meuleman 1996), while
response thresholds for other indicators of plant nutrient status vary across functional plant
groupings with different life history strategies. These differences may indicate potential
differences in sensitivity to excess nutrient loading (McJannet et.al., 1995). Thus, vegetation
community types are not always a good predictor of background nutrient concentrations
(reference condition) or sensitivity to nutrient loading.
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SEPTEMBER 2007 Chapters. Classification of Wetlands
Sensitivity to nutrient loading (as evidenced by differences in nutrient cycling and availability)
may also be related to differences in hydroperiod among wetlands. Wetland mesocosms exposed
to pulse discharges had higher nutrient loss from the water column than those exposed to
continuous flow regimes (Busnardo et.al., 1992). Depending on the predominant mechanism for
nutrient loss (e.g., plant uptake versus denitrification), nutrient-controlled primary production
could be either stimulated or reduced. Mineralization rates of carbon, nitrogen, and phosphorus
differ significantly among soils from northern Minnesota wetlands, related to an ombrotrophic to
minerotrophic gradient (i.e., degree of groundwater influence), and aeration status (Bridgham
et.al., 1998).
In general, very few definitive tests of alternative classification schemes for wetlands are
available with respect to describing reference condition for either nutrient criteria or biocriteria.
However, evidence from the literature suggests that in many cases both geographic factors (e.g.,
climate, geologic setting) and landscape setting (hydrogeomorphic type) are expected to affect
water quality and biotic communities.
3.5 RECOMMENDATIONS
Classification strategies for nutrient criteria development should incorporate factors affecting
background nutrient levels and wetland sensitivity to nutrient loading at several spatial scales.
• Classification of physiographic regions eliminates background variation in lithology and
soil texture (affecting background nutrient levels and sorption capacity), in climate
(affecting seasonality, productivity, decomposition, and peat formation), and in
landforms, which determines the predominance of different hydrogeomorphic classes.
• Classification by hydrogeomorphic class reduces background variation in predominant
water and nutrient sources, water depth and dynamics, hydraulic retention time,
assimilative capacity, and interactions with other surface water types (Table 3).
• Classification by water depth and duration (which may or may not be incorporated into
hydrogeomorphic classes) helps to explain variation in internal nutrient cycling,
dissolved oxygen level and variation, and the ability of wetlands to support some higher
trophic levels such as fish and amphibians.
• Classification by vegetation type or zone, whether to inform site selection or to determine
sampling strata within a site, helps to explain background variation in predominant
primary producer form (which will affect endpoint selection), as well as turnover and
growth rates (which will affect rapidity of response to nutrient loadings).
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SEPTEMBER 2007 Chapters. Classification of Wetlands
In general, the choice of specific alternatives among the classification schemes listed above
depends on their intrinsic value as well as practical considerations, e.g., whether a
classification scheme is available in mapped digital form or can be readily derived from
existing map layers, whether a hydrogeomorphic or other classification scheme has been
refined for a particular region and wetland type, and whether classification schemes are
already in use for monitoring and assessment of other waterbody types in a State or region.
Revisiting classification decisions once data from a sufficient number of sites have been
sampled may be useful to ensure the original classification was correct.
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SEPTEMBER 2007
Chapter 3. Classification of Wetlands
Table 3. Features of the major hydrogeomorphic classes of wetlands that may influence background nutrient concentrations, sensitivity
to nutrient loading, nutrient storage forms and assimilative capacity, designated use and choice of endpoints.
HGM Class
Predominant
Nutrient Source(S)
Landscape
Position
Hydrologic Regime
Hydraulic
Retention Time
Nutrient
Assimilation
Capacity
Organic Flats
Atmospheric
Deposition
Saturated, Little
Standing Water
Decades
Low
Mineral Flats
Atmospheric
Deposition,
Groundwater
Saturated, Little
Standing Water
Decades
High Sorption
Capacity
Depressional
Runoff (Particulate
and Dissolved),
Surface and
Groundwater
Depth and
Duration Varyfrom
Saturated to
Temporary to
Seasonal to Semi-
Permanent to
Permanent
Inundation
Varies With
Inflows/Outflows,
Landscape
Position
High Sorption,
Plant Uptake,
(Limited) Sediment
Storage
Riverine
Runoff
(Particulate),
Overbank Flooding
(Particulate,
Dissolved)
Adjacent to Rivers
Depth, Duration
Vary With River
Flooding Regime
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SEPTEMBER 2007
Chapter 3. Classification of Wetlands
Table 3 cont'd.
HGM Class
Predominant
Vegetation Growth
Form
Top Trophic Level
Commercially-
Important
Fish/Wildlife
Recreational Use
Likely
Drinking Water
Source
Downstream
Organic Flats
Mosses
Sedges
Mammals
Birds
Amphibians
Invertebrates
Mineral Flats
Sedges
Mammals
Birds
Amphibians
Invertebrates
Depressional
Varies With Zone
And Duration of
Flooding:
Wooded
Grass/Sedge
Emergents
Submerged
Aquatics*
Mammals
Birds
Mudminnows
Amphibians
Invertebrates
Waterfowl
Yes
Possible
Riverine
Wooded,
Emergent
Vegetation
Submerged
Aquatics*
Fish
Birds
Mammals
Fish*
Yes
Likely
Fringe
Varies With Zone:
Grass/Sedge
Emergents
Submerged
Aquatics*
Fish
Birds
Mammals
Waterfowl
Fish*
Yes
Possible
Slope
Wooded
Grasses
Sedges
Mammals
Birds
Amphibians
Invertebrates
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SEPTEMBER 2007 Chapter 4. Sampling Design of Wetland Monitoring
Chapter 4 Sampling Design for Wetland Monitoring
4.1 INTRODUCTION
This chapter provides technical guidance on designing effective sampling programs for State
wetland water quality monitoring programs. EPA recommends that States begin wetland
monitoring programs to collect water quality and biological data in order to characterize the
condition of existing wetlands as they develop nutrient criteria that will protect their wetlands.
The best monitoring programs are designed to assess wetland conditions with statistical rigor
while maximizing available resources.
At the broadest level, monitoring data should:
1. Detect and characterize the condition of existing wetlands.
2. Describe whether wetland conditions are improving, degrading, or staying the same.
3. Define seasonal patterns, impairments, and deviations in status of wetland conditions.
Water quality monitoring programs should collect a sufficient number of samples over time and
space to identify changes in system condition or estimate average conditions with statistical
rigor. Three approaches to study design for assessing water quality and biological and ecological
condition, and identifying degradation in wetlands are described in this chapter. Specific issues
to consider in designing monitoring programs for wetland systems are also discussed in this
chapter. The study designs presented here can be tailored to fit the goals of specific monitoring
programs.
The three approaches described below (Section 4.3) (probabilistic sampling, targeted/tiered, and
Before/After-Control/Impact [BACI]), present study designs that allow one to obtain a
significant amount of information with relatively minimal effort. Probabilistic sampling begins
with a large-scale, random monitoring design that is reduced as the wetland system conditions
are characterized. This approach is used to find the average condition of each wetland class in a
specific region. Probabilistic sampling design is frequently used for new large-scale monitoring
programs at the State and Federal level (e.g., Environmental Monitoring and Assessment
Program (EMAP), Regional Environmental Monitoring and Assessment Program (REMAP),
State programs [e.g., Maine, Montana, Wisconsin]). The tiered or targeted approach to
monitoring begins with coarse screening and proceeds to more detailed monitoring protocols as
impaired and high-risk systems are identified and targeted for further investigation. Targeted
sampling design provides a triage approach to more thoroughly assess condition and diagnose
stressors in wetland systems in need of restoration, protection, and intensive management.
Several State pilot projects use this method or a modification of this method for wetland
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SEPTEMBER 2007 Chapter 4. Sampling Design of Wetland Monitoring
assessment (e.g., Florida, Ohio, Oregon, and Minnesota). The synoptic approach described in
Kentula et.al., (1993) uses a modified targeted sampling design. The BACI design and its
modifications are frequently used to assess the success of restoration efforts or other
management experiments. BACI design allows for comparisons in similar systems over time to
determine the rate of change in relation to the management activity, e.g., to assess the success of
a wetland hydrologic restoration. The BACI design, in particular, is included to assist States in
evaluating ongoing management actions, and may provide less statistical rigor if adopted as a
general monitoring program design. This design, however, is of considerable value in assessing
restoration success and has been included at the request of States with ongoing wetland
restoration. Detenbeck et.al., (1996) used BACI design for monitoring water quality of wetlands
in the Minneapolis/St. Paul, Minnesota metro area.
Monitoring programs should be designed to describe what the current conditions are and to
answer under what conditions impairment may occur. A well-designed monitoring program can
contribute to determining those conditions.
Sampling design is dependent on the management question being asked. Sampling efforts
should be designed to collect information that will answer the management question. For
example, probabilistic sampling might be good for ambient (synoptic) monitoring programs,
BACI for evaluating management actions such as restoration, and targeted sampling/stratified
and random sampling for developing index of biotic integrity (IBIs) or nutrient criteria
thresholds. In practice, some State programs likely will need to use a combination of approaches.
4.2 CONSIDERATIONS FOR SAMPLING DESIGN
DESCRIBING THE MANAGEMENT QUESTION
Clearly defining the question being asked (identifying the hypothesis) encourages the use of
appropriate statistical analyses, reduces the occurrence of Type I (false positive) errors, and
increases the efficient use of management resources (Suter 1993; Leibowitz et al., 1992; Kentula
et al., 1993). Beginning a study or monitoring program with carefully defined questions and
objectives helps to identify the statistical analyses most appropriate for the study and reduces the
chance that statistical assumptions will be violated. Management resources are optimized
because resources are directed at monitoring that which is most likely to answer management
questions. In addition, defining the specific hypotheses to be tested, carefully selecting reference
sites, and identifying the most useful sampling interval can help reduce the uncertainty
associated with the results of any sampling design and further conserve management resources
(Kentula et al., 1993). Protecting or improving the quality of a wetland system often depends on
the ability of the monitoring program to identify cause-response relationships, for example, the
relationship of nutrient concentration (causal variable) to nutrient content of vegetation or
vegetation biomass (response variable). Cause-response relationships can be identified using
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SEPTEMBER 2007 Chapter 4. Sampling Design of Wetland Monitoring
large sample sizes and systems that span the gradient (low to high) of wetland quality. All ranges
of response should be observed along the causal gradient from minimally disturbed to high levels
of human disturbance.
Monitoring efforts often are prioritized to best utilize limited resources. For example, the Oregon
case study chose not to monitor depressional wetlands due to funding constraints. They further
tested the degree of independence of selected sites (and thus the need to monitor all of those
sites) using cluster analysis and other statistical tests
(http://www.epa.gov/owow/wetlands/bawwg/case/or.html). Frequency of monitoring should be
determined by the management question being asked and the intensity of monitoring necessary
to collect enough information to answer the question. In addition, monitoring should identify the
watershed level activities that are likely to result in ecological degradation of wetland systems
(Suteretal., 1993).
SITE SELECTION
Site selection is one of many important tasks in developing a monitoring program (Kentula et.al.,
1993). Site selection for a monitoring program is based on the need to sample a sufficiently large
number of wetlands to establish the range of wetland quality in a specific regional setting.
Wetland monitoring frequently includes an analysis of both watershed/landscape characteristics
and wetland specific characteristics (Kentula et al., 1993; Leibowitz et al., 1992). Therefore,
wetland sampling sites should be selected based on land use in the region so that watersheds
range from minimally impaired with few expected stressors to high levels of development (e.g.,
agriculture, forestry, or urban) with multiple expected stressors (see the Land-Use
Characterization for Nutrient and Sediment Risk Assessment, Wetland module #17). There is
often a lag in time between the causal stress and the response in the wetland system. This time
lag between stress and response and the duration of this lag depends on many factors, including
the type of stressor, climate, and system hydrology; these factors should be considered when
selecting sites to establish the range of wetland quality within a region.
LANDSCAPE CHARACTERIZATION
The synoptic approach described in Liebowitz et.al., (1992) provides a method of rapid
assessment of wetlands at the regional and watershed levels that can help identify the range of
wetland quality within a region. Liebowitz et.al., (1992) recommend an initial assessment for site
selection based on current knowledge of watershed and landscape level features; modification of
such an assessment can be made as more data are collected. Assessing watershed characteristics
through aerial photography and the use of geographical information systems (GIS) linked to
natural resource and land-use databases can aid in identifying reference and degraded systems
(see the Land-Use Characterization for Nutrient and Sediment Risk Assessment, Wetland
module #17); Johnston et al., 1988, 1990; Gwin et al., 1999; Palik et al., 2000; Brown and Vivas
2004). Some examples of watershed characteristics which can be evaluated using GIS and aerial
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SEPTEMBER 2007 Chapter 4. Sampling Design of Wetland Monitoring
photography include land use, land cover (including riparian vegetation), soils, bedrock,
hydrography, and infrastructure (e.g., roads or railroads). Changes in point sources can be
monitored through the NPDES permit program (USEPA 2000). Changes in nonpoint sources can
be evaluated through the identification and tracking of wetland loss and/or degradation,
increased residential development, urbanization, increased tree harvesting, shifts to more
intensive agriculture with greater fertilizer use or increases in livestock numbers, and other land
use changes. Local planning agencies should be informed of the risk of increased anthropogenic
stress and encouraged to guide development accordingly.
IDENTIFYING AND CHARACTERIZING REFERENCE WETLANDS
The term "reference" in this document refers to those systems that are least impaired by
anthropogenic effects. The use of the term reference is confusing because of the different
meanings that are currently in use in different classification methods, particularly its use in
hydrogeomorphic [HGM] wetland classification. A discussion of the term reference and its
multiple meanings is provided in Chapter 3.
Watersheds with little or no development that receive minimal anthropogenic inputs could
potentially contain wetlands that may serve as minimally impaired reference sites. Watersheds
with a high percentage of the drainage basin occupied by urban areas, agricultural land, and
altered hydrology are likely to contain wetlands that are impaired or could potentially be
considered "at risk" for developing problems. Wetland loss in the landscape also should be
considered when assessing watershed characteristics for reference wetland identification.
Biodiversity can become impoverished due to wetland fragmentation or decreases in regional
wetland density even in the absence of site-specific land-use activities. Reference wetlands may
be more difficult to locate if fragmentation of wetland habitats is significant and may no longer
represent the biodiversity of minimally disturbed wetlands in the region. The continued high rate
of wetland loss in most States dictates that multiple reference sites be selected to ensure some
consistency in reference sites for multiple year sampling programs (Liebowitz et al., 1992;
Kentula et al., 1993). Once the watershed level has been considered, a more site-specific
investigation can be initiated to better assess wetland condition.
The ideal reference site will have similar soils, vegetation, hydrologic regime, and landscape
setting to other wetlands in the region (Adamus 1992; Liebowitz et al., 1992; Kentula et al.,
1993; Detenbeck et al., 1996). Classification of wetlands, as discussed in Chapter 3, may aid in
identifying appropriate reference wetlands for specific regions and wetland types. Wetland
classification should be supplemented with information on wetland hydroperiod to assure that
the selected reference wetlands are truly representative of wetlands in the region, class, or
subclass of interest. Reference wetlands may not be available for all wetland classes. In that case,
data from systems that are as close as possible to the assumed unimpaired state of wetlands in the
wetland class of interest should be sought from States within the same geologic province.
Development of a conceptual reference may be important if appropriate reference sites cannot be
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found in the local region or geologic province. Techniques for defining a conceptual reference
are discussed at some length in Harris et.al., (1995), Trexler (1995), and Toth et.al., (1995).
Reference wetlands should be selected based on low levels of human alteration in their
watersheds (Liebowitz et.al., 1992; Kentula et.al., 1993; USEPA 2000). Selecting reference
wetlands usually involves assessment of land-use within watersheds and visits to individual
wetland systems to ground-truth expected land-use and check for unsuspected impacts. Ground-
truthing visits to reference wetlands are crucial for identification of ecological impairment that
may not be apparent from land-use and local habitat conditions. Again, sufficient sample size is
important to characterize the range of conditions that can be expected in the least impacted
systems of the region (Detenbeck et.al., 1996). Reference wetlands should be identified for each
ecoregion or geological province in the State lands and then characterized with respect to
ecological integrity. A minimum of three low impact reference systems is recommended for each
wetland class for statistical analyses. However, power analysis can be performed to determine
the degree of replication necessary to detect an impact to the systems being investigated
(Detenbeck et.al., 1996; Urquhart et.al., 1998). Highest priority should be given to identifying
reference systems for those wetland types considered to be at the greatest risk from
anthropogenic stress.
WHEN TO SAMPLE
Sampling may be targeted to the periods when effects are most likely to be detected - the index
period. The appropriate index period should be defined by what the investigator is trying to
investigate and what taxonomic assemblage or parameters are being used for that investigation
(Barbour et.al., 1999). For example, increased nutrient concentrations and sedimentation from
non-point sources may occur following periods of high runoff during spring and fall, while point
sources of nutrient pollutants may cause plankton blooms and/or increased water and soil
nutrient concentrations in wetland pools during times of low rainfall. Hence, different index
periods may be needed to detect effects from point source and nonpoint source nutrients,
respectively. Each taxonomic assemblage studied also should have an appropriate index period—
usually in the growing season (see assemblage methods in the Maine case study:
http ://www. epa. gov/waterscience/criteria/wetlands/index.html).
The index period window may be early in the growing season for amphibians and algae. Other
assemblages, such as vegetation and birds, may benefit from a different sampling window for the
index period; see the assemblage specific modules for recommendations. Once wetland
condition has been characterized, one-time annual sampling during the appropriate index period
may be adequate for multiple year monitoring of indicators of nutrient status, designated use, and
biotic integrity. However, criteria and ecological indicator development may benefit from more
frequent sampling to define conditions that relate to the stressor or perturbor of interest (Karr and
Chu 1999; Stevenson 1996; Stevenson 1997). Regardless of the frequency of sampling, selection
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of index periods and critical review of the data gathered and analyzed should be done to
scientifically validate the site characterization and index periods for data collection.
Ideally, water quality monitoring programs produce long-term data sets compiled over multiple
years to capture the natural, seasonal, and year-to-year variations in biological communities and
constituent concentrations (e.g., Tate 1990; Dodds et.al., 1997; McCormick et.al., 1999; Craft
2001; Craft et al., 2003; Zheng et al., 2004). Multiple-year data sets can be analyzed with
statistical rigor to identify the effects of seasonality and variable hydrology. Once the pattern of
natural variation has been described, the data can be analyzed to determine the ecological state of
the wetland. Long-term data sets have also been important in influencing management decisions
about wetlands, most notably in the Everglades, where long-term data sets have induced Federal,
State, and Authorized Tribal actions for conservation and restoration of the largest wetland
system in the U.S. (see Davis and Ogden 1994; Everglades Interim Report, South Florida Water
Management District [SFWMD, 1999]; Everglades Consolidated Report [SFWMD, 2000, 2001];
1994 Everglades Forever Act, Florida Statute § 373.4592).
In spite of the documented value of long-term data sets, there is a tendency to intensively study a
wetland for one year before and one year after treatment. A more cost-effective approach may be
to measure only the indices most directly related to the stressor of interest (i.e., those parameters
or indicators that provide the best information to answer the specific management question), but
to double or triple the monitoring period. Multiple years (two or more) of data are often needed
to identify the effects of years with extreme climatic or hydrologic conditions. Comparisons over
time between reference and at risk or degraded systems can help describe biological response
and annual patterns in the presence of changing climatic conditions. Multi-year data sets also can
help describe regional trends. Flooding or drought may significantly affect wetland biological
communities and the concentrations of water column and soil constituents. Effects of uncommon
climatic events can be characterized to discern the overall effect of management actions (e.g.,
nutrient reduction, water diversion) if several years of data are available to identify the long-term
trends.
At the very minimum, two years of data before and after specific management actions, but
preferably three or more each, are recommended to evaluate the cost-effectiveness of
management actions with some degree of certainty (USEPA 2000). If funds are limited,
restricting sampling frequency and/or numbers of indices analyzed should be considered to
preserve a longer-term data set. Reducing sampling frequency or numbers of parameters
measured will allow for effectiveness of management approaches to be assessed against the high
annual variability that is common in most wetland systems. Wetlands with high hydrological
variation from year to year may benefit from more years of sampling both before and after
specific management activities to identify the effects of the natural hydrologic variability
(Kadlec and Knight 1996).
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CHARACTERIZING PRECISION OF ESTIMATES
Estimates of cause-response relationships, nutrient and biological conditions in reference
systems, and wetland conditions in a region are based on sampling; hence, precision should be
assessed. Precision is defined as the "measure of the degree of agreement among the replicate
analyses of a sample, usually expressed as the standard deviation" (APHA 1999). Determining
precision of measurements for one-time assessments from single samples in a wetland is often
important. The variation associated with one-time assessments from single samples can be
determined by re-sampling a specific number of wetlands during the survey. Measurement
variation among replicate samples then can be used to establish the expected variation for one-
time assessment of single samples. Re-sampling does not establish the precision of the
assessment process, but rather identifies the precision of an individual measurement (Kentula
et.al., 1993).
Re-sampling frequency is often conducted for one wetland site in every block of 10 sites.
However, investigators should adhere to the objectives of re-sampling (often considered an
essential element of QA/QC) to establish an assessment of the variation in a one-time/sample
assessment. Often, more than one in 10 samples should be replicated in monitoring programs to
provide a reliable estimate of measurement precision (Barbour et.al., 1999). The reader should
understand that this is a very brief description of the concerns about precision, and that any
monitoring program or study involving monitoring should include consultation with a
professional statistician before the program begins and regularly during the course of the
monitoring program to assure statistical rigor.
4.3 SAMPLING PROTOCOL
APPROACHES TO SAMPLING DESIGN
The following sections discuss three different approaches to sampling design, probabilistic,
targeted, and BACI. These approaches have advantages and disadvantages that under different
circumstances warrant the choice of one approach over the other (Table 4). The decision as to
the best approach for sample design in a new monitoring program should be made by the water
quality resource manager or management team after careful consideration of the different
approaches. For example, justification of a dose-response relationship is confounded by lack of
randomization and replication and should be considered in choosing a sampling design for a
monitoring program.
PROBABILISTIC SAMPLING DESIGN FOR ASSESSING CONDITION
Probabilistic sampling - a sampling process wherein randomness is requisite (Hayek 1994) - can
be used to characterize the status of water quality conditions and biotic integrity in a region's
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wetland system. This type of sampling design is used to describe the average conditions of a
wetland population, identify the variability among sampled wetlands, and help determine the
range of wetland system conditions in a region. Data collected from a probabilistic random
sample design generally will be characteristic of the dominant class or type of wetland in the
region, but rare wetlands may be under-represented or absent from the probabilistically sampled
wetlands. Additional sampling sites may need to be added to precisely characterize the complete
range of wetland conditions and types in the region.
Probabilistic designs are often modified by stratification (such as classification). Stratified
random sampling is a type of probabilistic sampling where a target population is divided into
relatively homogenous groups or classes (strata) prior to sampling based on factors that influence
variability in that population (Hayek 1994). Stratification by wetland size and class or types
ensures more complete information about different types of wetlands within a region. Sample
statistics from random selection alone would be most characteristic of the dominant wetland type
in a region if the population of wetlands is not stratified.
Many State 305(b) and watershed monitoring programs utilize stratified random sampling
designs, and we will further discuss this type of probabilistic sampling. Pilot projects in Maine,
Montana, and Wisconsin all use stratified random sampling design. Details of these monitoring
designs can be found in the Case Studies module #14 and on the Web at
http ://www. epa. gov/waterscience/criteria/wetlands/index.html.
Stratification is based on identifying wetland systems in a region (or watershed) and then
selecting an appropriate sample of systems from the defined population. The determination of an
appropriate sample population usually is dependent on the management questions being asked. A
sample population of isolated depressional wetlands could be identified as a single stratum, but
investigations of these wetlands would not provide any information on riparian wetlands in the
same region. If the goal of the monitoring program is to identify wetland condition for all
wetland classes within a region, then a sample population of wetlands should be randomly
selected from all wetlands within each class. In practice, most State programs stratify random
populations by size, wetland class (see Chapter 3), and landscape characteristics or location (see
http://www.epa.gov/waterscience/criteria/wetlands/index.html, module #14).
Once the wetlands for each stratum have been identified, the list of wetlands can be used to
select a spatially-balanced stratified random sample. Spatial-balance will ensure spatial coverage
over the assessment region, usually increase the types of wetlands sampled (assuming classes of
wetlands vary spatially), and reduce spatial autocorrelation among the sampled wetlands. For
example, EMAP implements spatially-balanced samples using Generalized Random Tessellation
Stratified (GRTS) designs applied to GIS coverages of wetlands within the assessment region.
GRTS using a hierarchical grid randomization process to ensure the sites are spatially distributed
(Paulsen et.al., 1991; Stevens and Olsen 2004). Estimates of ecological conditions from these
kinds of modified probabilistic sampling designs can be used to characterize the water quality
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conditions and biological integrity of wetland systems in a region, and over time, to distinguish
trends in ecological condition within a region. (See
http://www.epa.gov/owow/wetlands/bawwg/case/mtdev.html and
http://www.epa.gov/owow/wetlands/bawwg/case/fl 1 .html).
TARGETED DESIGN
A targeted approach to sampling design may be more appropriate when resources are limited
(Stern 2004). The example of targeted sampling described here involves defining a gradient of
impairment. Once the gradient has been defined and systems have been placed in categories of
impairment, investigators focus the greatest efforts on identifying and characterizing wetland
systems or sites likely to be impacted by anthropogenic stressors, and on relatively undisturbed
wetland systems or sites (see Identifying and Characterizing Reference Systems, Chapter 3), that
can serve as regional, sub-regional, or watershed examples of natural biological integrity. Florida
Department of Environmental Protection (FL DEP) uses a targeted sampling design for
developing thresholds of impairment with macroinvertebrates
(http://www.epa.gov/owow/wetlands/bawwg/case/fl2.html). Choosing sampling stations that
best allow comparison of ecological integrity at reference wetland sites of known condition can
conserve financial resources. A sampling design that tests specific hypotheses (e.g., the FL DEP
study tested the effect of elevated water column phosphorus on macroinvertebrate species
richness) generally can be analyzed with statistical rigor and can conserve resources by
answering specific questions. Furthermore, identification of systems with problems and
reference conditions eliminates the need for selecting a random sample of the population for
monitoring.
Targeted sampling assumes some knowledge of the systems sampled (Stern 2004; Kentula et.al.,
1993). Systems based on independent variables with evidence of degradation are compared to
reference systems that are similar in their physical structure (i.e., in the same class of wetlands).
Wetland systems should be viewed along a continuum from reference to degraded. An impaired
or degraded wetland is a system in which anthropogenic impacts exceed acceptable levels or
interfere with beneficial uses. Comparison of the monitoring data to that collected from reference
wetlands will allow characterization of the sampled systems. Wetlands identified as "at risk"
should be evaluated through a sampling program to characterize the degree of degradation. Once
characterized, the wetlands should be placed in one of the following categories:
1. Degraded wetlands—wetlands in which the level of anthropogenic perturbance interferes
with designated uses.
2. High-risk wetlands—wetlands where anthropogenic stress is high but does not
significantly impair designated uses. In high-risk systems, impairment is prevented by
one or a few factors that could be changed by human actions, though characteristics of
ecological integrity are already marginal.
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3. Low-risk wetlands—wetlands where many factors prevent impairment, stressors are
maintained below problem levels, and/or no development is contemplated that would
change these conditions.
4. Reference wetlands—wetlands where the ecological characteristics most closely
represent the pristine or minimally impaired condition.
Once wetland systems have been classified based on their physical structure (see Chapter 3) and
placed into the above categories, specific wetlands need to be selected for monitoring. At this
point, randomness is introduced; wetlands should be randomly selected within each class and
risk category for monitoring. An excellent example of categorizing wetlands in this manner is
given in the Ohio Environmental Protection Agency's (OH EPA) case study, available at:
http://www.epa.gov/owow/wetlands/bawwg/case/oh 1 .html. They used the Ohio Rapid
Assessment Method to categorize wetlands by degree of impairment. The Minnesota Pollution
Control Agency (MPCA) also used a targeted design for monitoring wetlands
(http://www.epa.gov/owow/wetlands/bawwg/case/mnl.html). They used the best professional
judgment of local resource managers to identify reference sites and those with known
impairment from identified stressors (agriculture and stormwater runoff).
Targeted sampling design involves monitoring identified degraded systems and comparable
reference systems most intensively. Low risk systems are monitored less frequently (after initial
identification) unless changes in the watershed indicate an increased risk of degradation.
Activities surrounding impaired wetland systems may be used to help identify which actions
negatively affect wetlands, and therefore may initiate more intensive monitoring of at-risk
wetlands. Monitoring should focus on factors likely to identify ecological degradation and
anthropogenic stress and on any actions that might alter those factors. State water quality
agencies should encourage adoption of local watershed protection plans to minimize ecological
degradation of natural wetland systems. Development plans in the watershed should be evaluated
to identify potential future stressors. Ecological degradation often gradually increases due to
many growing sources of anthropogenic stress. Hence, frequent monitoring may be warranted
for high-risk wetlands if sufficient resources remain after meeting the needs of degraded
wetlands. Whenever development plans appear likely to alter factors that maintain ecological
integrity in a high-risk wetland (e.g., vegetated buffer zones), monitoring should be initiated at a
higher sampling frequency in order to enhance the understanding of baseline conditions (USEPA
2000).
BEFORE/AFTER, CONTROL/IMPACT (BACI) DESIGN
An ideal before/after impact survey has several features: 1) the type of impact, time of impact,
and place of occurrence should be known in advance; 2) the impact should not have occurred
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yet; and, 3) control areas should be available (Green 1979). The first feature allows the surveys
to be efficiently planned to account for the probable change in the environment. The second
feature allows a baseline study to be established and extended as needed. The last feature allows
the surveyor to distinguish between temporal effects unrelated to the impact and changes related
to the impact. In practice however, advance knowledge of specific impacts is rare, and the ideal
impact survey is rarely conducted. BACI designs modified to monitor impacts during or after
their occurrence still can provide information, but there is an increase in the uncertainty
associated with the results and the likelihood of finding a statistically significant change due to
the impact is less probable. In addition, other aspects of survey design are dependent on the
study objectives, e.g., the sampling interval, the length of time the survey is conducted (i.e.,
sampling for acute versus chronic effects), and the statistical analyses appropriate for analyzing
the data (Suter 1993).
The best interval for sampling is determined by the objectives of the study (Kentula et.al., 1993).
If the objective is to detect changes in trends (e.g., regular monitoring for detection of changes in
water quality or biotic integrity), regularly spaced intervals are preferred because the analysis is
easier. On the other hand, if the objective is to assess differences before and after impact, then
samples at random time points are advantageous. Random sample intervals reduce the likelihood
that cyclic differences unforeseen by the sampler will influence the size of the difference before
and after the impact. For example, surveys taken every summer for a number of years before and
after a clear-cut may show little difference in system quality; however, differences may exist that
can only be detected in the winter and therefore may go undetected if sampling occurs only
during summer.
The simplest impact survey design involves taking a single survey before and after the impact
event (Green 1979). This type of design has the obvious pitfall that there may be no relationship
between the observed event and the changes in the response variable—the change may be
entirely coincidental. This pitfall is addressed in BACI design by comparing before and after
impact data to data collected from a similar control system nearby. Data are collected before and
after a potential disturbance in two areas (treatment and a control), with measurements on
biological and environmental variables in all combinations of time and area (Green 1979). We
will use a clear-cut adjacent to a wetland as an example to illustrate the BACI design. The
sampling design is developed to identify the effects of clear-cutting on adjacent wetland systems.
In the simplest BACI design, two wetlands would be sampled. One wetland would be adjacent to
the clear-cut (the treatment wetland); the second wetland would be adjacent to a control site that
is not clear-cut. The control site should have characteristics (soil, vegetation, structure,
functions) similar to the treatment wetland and is exposed to climate and weather similar to the
first wetland. Both wetlands are sampled at the same time points before the clear-cut occurs and
at the same time point after the clear-cut takes place. This design is technically known as an
area-by-time factorial design. Evidence of an impact is found by comparing the control site
samples (before and after) with the treatment site before and after samples. Area-by-time
factorial design allows for both natural wetland-to-wetland variation and coincidental time
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effects. If there is no effect of the clear-cut, then change in system quality between the two time
points should be the same. If there is an effect of the clear-cut, the change in system quality
between the two time points should be different.
CONSIDERATIONS FOR BACI DESIGN
There are some potential problems with BACI design. First, because the control and impact sites
are not randomly assigned, observed differences between sites may be related solely to some
other factor that differs between the two sites. One could argue that it is unfair to ascribe the
effect to the impact (Hurlbert 1984; Underwood 1991). However, as pointed out by Stewart-
Oaten et.al., (1986), the survey is concerned about a particular impact in a particular place, not in
the average of the impact when replicated in many different locations. Consequently, it may be
possible to detect a difference between these two specific sites. Even so, if there are no
randomized replicate treatments, the results of the study cannot be generalized to similar events
at different wetlands. In any case, the likelihood that the differences between sites are due to
factors other than the impact can be reduced by monitoring several control sites (Underwood
1991) because multiple control sites provide some information about potential effects of other
factors.
The second and more serious concern with the simple Before-After design with a single
sampling point before and after the impact is that it fails to recognize that there may be natural
fluctuations in the characteristic of interest that are unrelated to any impact (Hurlbert 1984;
Stewart-Oaten 1986). Single samples before and after impact would be sufficient to detect the
effects of the impact if there were no natural fluctuations over time. However, if the population
also has natural fluctuations over and above the long-term average, then it is impossible to
distinguish between cases where there is no effect from cases where there is an impact.
Consequently, measured differences in system quality may be artifacts of the sampling dates and
natural fluctuations may obscure differences or lead one to believe differences are present when
they are not.
The simple BACI design was extended by Stewart-Oaten et.al., (1986) by pairing surveys at
several selected time points before and after the impact to help resolve the issue of
psuedoreplication (Hulbert 1984). This modification of the BACI design is referred to as BACI-
PS (Before-After, Control-Impact Paired Series design). The selected sites are measured at the
same time points. The rationale behind this paired design is that repeated sampling before the
impact gives an indication of the pattern of differences of potential change between the two sites.
BACI-PS study design provides information both on the mean difference in the wetland system
quality before and after impact and on the natural variability of the system quality measurements.
The resource manager has detected an effect if the changes in the mean difference are large
relative to natural variability. Considerations for sampling at either random or regularly spaced
intervals also apply here. Replication of samples should also be included if resources allow in
order to improve certainty of analytical results.
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Violation of the BACI assumptions may invalidate conclusions drawn from the data. Enough
data should be collected before the impact to identify the trends in the communities of each
sampling site if the BACI assumptions are to be met. Clearly defining the objectives of the study
and identifying a statistically testable model of the relationships the investigator is studying can
help resolve these issues (Suter 1993).
The designs described above are suitable for detecting longer-term chronic effects in the mean
level of the variable of interest. However, the impact may have an acute effect (i.e., effects only
last for a short while) or may change the variability in response (e.g., seasonal changes become
more pronounced) in some cases. The sampling schedule can be modified so that it occurs at two
temporal scales (enhanced BACI-PS design) that encompass both acute and chronic effects
(Underwood 1991). The modified temporal design introduces randomization by randomly
choosing sampling occasions in two periods (Before and After) in the control or impacted sites.
The two temporal scales (sampling periods vs. sampling occasions) allow the detection of a
change in mean and of a change in variability after impact. For example, groups of surveys could
be conducted every year with five surveys one week apart randomly located within each group.
The analysis of such a design is presented in Underwood (1991). Again, multiple control sites
should be used to counter the argument that detected differences are specific to the sampled site.
The September 2000 issue of'the Journal of'Agricultural, Biological, and Environmental
Statistics discusses many of the advantages and disadvantages of the BACI design and provides
several examples of appropriate statistical analyses for evaluation of BACI studies.
4.4 SUMMARY
State monitoring programs should be designed to assess wetland condition with statistical rigor
while maximizing available management resources. The three approaches described in this
module—probabilistic sampling, targeted/tiered approach, and BACI (Before/After,
Control/Impact)—present study designs that allow one to obtain a significant amount of
information for statistical analyses. The sampling design selected for a monitoring program
should depend on the management question being asked. Sampling efforts should be designed to
collect information that will answer management questions in a way that will allow robust
statistical analysis. In addition, site selection, characterization of reference sites or systems, and
identification of appropriate index periods are all of particular concern when selecting an
appropriate sampling design. Careful selection of sampling design will allow the best use of
financial resources and will result in the collection of high quality data for evaluation of the
wetland resources of a State. Examples of different sampling designs currently in use for State
wetland monitoring are described in the Case Study module #14 on the Web site:
http://www.epa.gov/waterscience/criteria/wetlands/index.html. Well-designed monitoring
programs tend to produce data that managers can use in nutrient criteria development, such as in
developing reference networks or utilizing distribution-based approaches.
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Chapter 4. Sampling Design for Wetland Monitoring
Table 4. Comparison of Probabilistic, Targeted, and BACI Sampling Designs
Probabilistic
Targeted
BACI
Random selection of wetland
systems from entire population
within a region.
This design requires minimal
prior knowledge of wetlands
within the sample population
for stratification.
This design may use more
resources (time and money) to
randomly sample wetland
classes because more wetlands
may need to be sampled.
System characterization for a
class of wetlands is more
statistically robust.
Rare wetlands may be under-
represented or absent from the
sampled wetlands.
This design is potentially best
for regional characterization of
wetland classes, especially if
water quality conditions are
not known.
Targeted selection of wetlands
based on problematic (wetland
systems known to have
problems) and reference
wetlands.
This design requires prior
knowledge of wetlands within
the sample population.
This design utilizes fewer
resources because only
targeted systems are sampled.
System characterization for a
class of wetlands is less
statistically robust, although
characterization of a targeted
wetland may be statistically
robust.
This design may miss
important wetland systems if
they are not selected for the
targeted investigation.
This design is potentially best
for site-specific and
watershed-specific criteria
development when water
quality conditions for the
wetland of interest are known.
Selection of wetlands based on
a known impact.
This design requires
knowledge of a specific
impact to be analyzed.
This design may use fewer
resources because only
wetlands with known impacts
and associated control systems
are sampled.
Characterization of the
investigated systems is
statistically robust.
The information gained in this
type of investigation is not
transferable to wetland
systems not included in the
study.
This design is potentially best
for monitoring restoration or
creation of wetlands and
systems that have specific
known stressors.
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Chapter 5 Candidate Variables for Establishing Nutrient
Criteria
5.1 OVERVIEW OF CANDIDATE VARIABLES
This chapter provides an overview of candidate variables that could be used to establish nutrient
criteria for wetlands. A more detailed discussion of sampling methods and laboratory analysis
with useful references can be found in the Methods for Evaluating Wetland Condition module
series for sampling wetlands4'5 at:
http ://www. epa. gov/waterscience/criteria/wetlands/index.html.
A good place to start with selecting candidate variables is by developing a conceptual model of
how human activities affect nutrients and wetlands. These conceptual models may vary from
complex to very simple models, such as relating nitrogen concentrations in sediments and plant
biomass or species composition. Conceptual models establish the detail and scope of the project
and the most important variables to select. In addition, they define the cause-effect relationships
that should be documented to determine whether a problem occurs and what is causing the
problem.
In general, for the purposes of numeric nutrient criteria development, it is helpful to develop an
understanding of the relationships among human activities, nutrients and habitat alterations, and
attributes of ecosystem structure and function to establish a simple causal pathway among three
basic elements in a conceptual model. These three basic groups of variables are important to
distinguish because we use them differently in environmental management (Stevenson et.al.,
2004a). A fourth group of variables is important in order to account for variation in expected
condition of wetlands due to natural variation in landscape setting.
The overview of candidate variables in this chapter follows the outline provided in the
conceptual model in Figure 5.1. Historically, variables in conceptual models have been grouped
many ways with a variety of group names (Paulsen et.al., 1991; Stevenson 1998; Stevenson
2004a, b). In this document, three groups and group names are used to emphasize cause-effect
relationships, simplify their presentation and discussion for a diversity of audiences, and
maintain some continuity between their use in the past and their use here. The three groups are:
supporting variables, causal variables, and response variables.
Supporting variables provide information useful in normalizing causal and response variables
and categorizing wetlands. (These are in addition to characteristics used to define wetland
4 EPA is developing and revising additional modules as a part of the Methods for Evaluating Wetland Conditions
Module series; Biogeochemical Indicators, Wetland Hydrology, and Nutrient Loading Estimation.
5 The references for these modules can be found in the Supplementary References following the References section.
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SEPTEMBER 2007 Chapter 5. Candidate Variables for Establishing Nutrient Criteria
classes as described in Chapter 3 ) Causal variables characterize pollution or habitat
alterations. Causal variables are intended to characterize nutrient availability in wetlands and
could include nutrient loading rates and soil nutrient concentrations. Response variables are
direct measures or indicators of ecological properties. Response variables are intended to
characterize biotic response and could include community structure and composition of
vegetation and algae. The actual grouping of variables is much less important than understanding
relationships among variables.
It is important to recognize the complex temporal and spatial structure of wetlands when
measuring or interpreting causal and response variables with respect to nutrient condition. The
complex interaction of climate, geomorphology, soils, and internal interactions has led to a
diverse array of wetland types ranging from infrequently flooded, isolated depressional wetlands
such as seasonal prairie potholes and playa lakes, to very large, complex systems such as the
Everglades and the Okefenokee Swamp. In addition, most wetlands are complex temporal and
spatial mosaics of habitats with distinct structural and functional characteristics illustrated most
visibly by patterns in vegetation structure.
Horizontal zonation is a common feature of wetland ecosystems, and in most wetlands, relatively
distinct bands of vegetation develop in relation to water depth. Bottomland hardwood forests and
prairie pothole wetlands provide excellent illustrations of zonation in two very divergent wetland
types. However, vegetation zones are not static. Seasonal and long-term changes in vegetation
structure are a common characteristic of most wetland ecosystems. Wetlands may exhibit
dramatic shifts in vegetation patterns in response to changes in hydrology, with entire wetlands
shifting between predominantly emergent vegetation to completely open water within only a
year or two. Such temporal patterns in fact are important features of many wetlands and should
be considered in interpreting any causal or response variable. For example, seasonal cycles are
an essential feature of floodplain forests, which are typically flooded during high spring flows
but dry by mid to late summer. Longer-term cycles are similarly essential features of prairie
pothole wetlands, which exhibit striking shifts in vegetation in response to water level
fluctuations over periods of a few years in smaller wetlands to decades in larger, more permanent
wetlands (van der Valk 2000). Vegetation patterns can significantly affect the physical and
chemical characteristics of sediments and overlying waters and are likely to control major
aspects of wetland biogeochemistry and trophic dynamics (Rose and Crumpton 1996).
The complex temporal and spatial structure of wetlands should influence the selection of
variables to measure and methods for measuring them. Most wetlands are characterized by
extremely variable hydrologic and nutrient loading rates and close coupling of soil and water
column processes. As a result, estimates of nutrient loading may prove more useful than direct
measurements of water column nutrient concentrations as causal variables for establishing the
nutrient condition of wetlands. In addition, soil nutrients that integrate a wetland's variable
nutrient history over a period of years may provide the most useful metric against which to
evaluate wetland response.
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Chapter 5. Candidate Variables for Establishing Nutrient Criteria
Fig 5.1
This conceptual model illustrates
the causal pathway between
human activities and valued
ecological attributes. It includes
the role of nutrients in a broader
context that includes natural
variation among wetlands. The
relationship between different
approaches of grouping variables
is illustrated to emphasize the
importance of cause-effect
relationships. Here, natural factors
and human activities regulate the
physical, chemical and biological
attributes of wetlands. Some
wetland attributes are more valued
than others and provide the
endpoints of assessment and
management. Some physical,
chemical, and biological attributes
are stressors, i.e. contaminants
and habitat alterations caused by
human activities that negatively
affect valued ecological attributes.
The overview of variables in
Chapter 5 is organized in three
sections: supporting, causal, and
response variables. Supporting
variables are natural landscape-
level factors that classify expected
condition of wetlands. Causal
factors "cause" effects in response
variables.
Natural Factors
Climate
Geology
Topography
Human Activities
Agricult
»
Ripar
jre Urban Dev. C
\s<
an Buffers
No-till Rov
Channelization
i/ Crops
T
Stressors: Contaminants & Habitat Alterations
Nitrogen
X
Phosphorus
/ X
Invasive Species
Hydrologic
Alterations
T
Responses: Valued Ecological Attributes
Ecosystem Structure
•Biomass
•Biodiversity
Flora & Fauna
Ecosystem Function
•Productivity
•Nutrient Retention
•Hydrologic Regulation
5.2 SUPPORTING VARIABLES
Supporting variables are not intended to characterize nutrient availability or biotic response but,
rather, to provide information that can be useful in normalizing causal and response variables.
Below is a brief overview of supporting variables that might be useful for categorizing wetlands
and for normalizing and interpreting causal and response variables.
CONDUCTIVITY
Conductivity (also called electrical conductance or specific conductance) is an indirect measure
of total dissolved solids. This is due to the ability of water to conduct an electrical current when
there are dissolved ions in solution—water with higher concentrations of dissolved inorganic
compounds have higher conductivity. Conductivity is commonly measured in situ using a
handheld probe and conductivity meter (APHA 1999) or using automated conductivity loggers.
Because the conductivity changes with temperature, the raw measurement should be adjusted to
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a reference temperature of 25°C. A multiplier of 0.7 is commonly applied to estimate the total
dissolved solids concentration (mg/L) in fresh water when the conductivity is measured in units
of microSiemens per centimeter (jiS/cm), although this multiplier varies with the types of
dissolved ions and should be adjusted for local chemical conditions.
Conductivity is a useful tool for characterizing wetland inputs and interpreting nutrient condition
because of its sensitivity to changes in these inputs. Rainfall tends to have lower conductivity
than surface water, with ground water often having higher values due to the longer residence
time of water in the subsurface. Coastal and marine waters—as well as water in terminal lakes
and wetlands—have even higher conductivity due to the influence of salinity. Municipal and
industrial discharges often have higher conductivity than their intake waters due to the addition
of soluble wastes. Wetland hydrologic inputs can be identified by comparing the measured input
conductivity with the conductivity of potential local sources.
SoiLPH
Soil pH can be important for categorizing wetland soils and interpreting soil nutrient variables.
The pH of wetland soils and water varies over a wide range of values. Many ombrotrophic
organic wetland soils (histosols) such as bogs and non-limestone based wetlands are often
acidic, and mineral wetland soils are frequently neutral or alkaline. Flooding a soil results in
consumption of electrons and protons. In general, flooding acidic soils results in an increase in
pH, and flooding alkaline soils decreases pH (Mitsch and Gosselink 2000). The increase in pH of
low pH (acidic) wetland soils is largely due to the reduction of iron and manganese oxides.
However, the initial decrease in pH of alkaline wetland soils is due to rapid decomposition of
soil organic matter and accumulation of CC>2. The decrease in pH that generally occurs when
alkaline soils are flooded results from the buildup of CO2 and carbonic acid. In addition, the pH
of alkaline soils is highly sensitive to changes in the partial pressure of CC>2. Carbonates of iron
and manganese also can buffer the pH of soil to neutrality. Soil pH determinations should be
made on wet soil samples. Once the soils are air-dried, oxidation of various reduced compounds
results in a decrease in pH and the values may not represent ambient conditions.
Soil pH is measured using commercially available combination electrodes on soil slurries. If air
dry or moist soil is used, a 1:1 soil to water ratio should be used. For details on methodology, the
reader is referred to Thomas (1996).
Soil pH can explain the availability and retention capacity of phosphorus. For example,
phosphorus bioavailability is highest at soil pH near neutral conditions. For mineral soils,
phosphorus adsorption capacity has been directly linked to extractable iron and aluminum. For
details, the reader is referred to Supplementary References.
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SOIL BULK DENSITY
Soil bulk density is the mass of dry solids per unit volume of soil, which includes the volume of
solids plus air- and water-filled pore space. Bulk density is a useful parameter for expressing the
concentration of nutrients on a volume basis, rather than mass basis. For example, concentration
of nutrients in organic wetland soils can be high when expressed on a mass basis (mg/kg or |ig/g
of dry soil), as compared to mineral wetland soils. However, the difference in concentration may
not be as high when expressed on a volume (cm3) basis, which is calculated as the product of
bulk density and nutrient concentration per gram of soil. Expressing soil nutrient concentrations
on a volume basis is especially relevant to uptake by vegetation since plant roots explore a
specific volume, not mass, of soil. Expressing nutrients on a volume basis also helps in
calculating total nutrient storage in a defined soil layer.
Bulk density is measured by collecting an intact soil core of known volume at specific depths in
the soil (Blake and Hartge, 1986). Cores are oven-dried at 70°C and weighed. Bulk density is
calculated as follows:
Bulk density (dry) (g/cm3) = mass dry weight (grams)/volume (cm3)
Bulk densities of wetland organic soils range from 0.1 to 0.5 g/cm3, whereas bulk densities of
mineral wetland soils range from 0.5 to 1.5 g/cm3. Soil bulk densities are directly related to soil
organic matter content, as bulk densities decrease with increases in soil organic matter content.
SOIL ORGANIC MATTER CONTENT
Soil organic matter can be important for categorizing wetland soils and interpreting soil nutrient
variables. Wetland soils often are characterized by the accumulation of organic matter because
rates of primary production often exceed rates of decomposition. Some wetlands accumulate
thick layers of organic matter that, over time, form peat soil. Organic matter provides nutrient
storage and supply, increases the cation exchange capacity of soils, enhances adsorption or
deactivation of organic chemicals and trace metals, and improves overall soil structure, which
results in improved air and water movement. A number of methods are now routinely used to
estimate soil organic matter content expressed as total organic carbon or loss on ignition (APHA,
1999; Nelson and Sommers, 1996).
Soil organic matter content represents the soil organic carbon content of soils. Typically, soil
organic matter content is approximately 1.7 to 1.8 times that of total organic carbon. The carbon
to nitrogen and carbon to phosphorus ratios of soils can provide an indication of nutrient
availability in soils.
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HYDROLOGIC CONDITION
Wetland hydrologic condition is important for characterizing wetlands and for normalizing many
causal and response variables. Hydrologic conditions can directly affect the chemical and
physical processes governing nutrient and suspended solids dynamics within wetlands (Mitsch
and Gosselink, 2000). Detailed, site-specific hydrologic information available is best, but at a
minimum, some estimate of water level fluctuation should be made. A defining characteristic of
wetlands is oxygen deficiency in the soil caused by flooding or soil saturation. These conditions
influence vegetation dynamics through differential growth and survival of plant species and also
exert significant control over biogeochemical processes involved in carbon flow and nutrient
cycling within wetlands. Spatial and temporal patterns in hydrology can create complex patterns
in soil and water column oxygen availability, including alternating aerobic and anaerobic
conditions in wetland soils, with obvious implications for plant response and biogeochemical
process dynamics. Water levels in wetlands can be determined using a staff gauge when surface
water is present. A staff gauge measures the depth of surface flooding relative to a reference
point such as the soil surface. Other methods to assess past water levels when standing water is
not present include moss collars, staining, and cypress knee heights. While surface flooding may
be rare or absent in a wetland, high water tables may still cause soil saturation in the rooting
zone. In wetlands where soils are saturated, water level can be measured with a small diameter
perforated tube installed in the soil to a specified depth (Amoozegar and Warrick 1986).
Automated water level recorders using floats, capacitance probes, or pressure transducers are
suitable for measuring water levels both above- and below-ground. The reader is referred to the
Supplementary References for details.
5.3 CAUSAL VARIABLES
Causal variables are intended to characterize nutrient availability in wetlands. Most wetlands are
characterized by extremely variable nutrient loading rates and close coupling of soil and water
column processes. As a result, estimates of nutrient loading and measurements of soil nutrients
may prove more useful than direct measurements of water column nutrient concentrations as
causal variables for establishing the nutrient condition of wetlands. Nutrient loading history and
soil nutrient measures can integrate a wetland's variable nutrient history over a period of years
and may provide especially useful metrics against which to evaluate nutrient condition. Wetlands
exhibit a high degree of spatial heterogeneity in chemical composition of soil layers, and areas
impacted by nutrients may exhibit more variability than unimpacted areas of the same wetland.
Thus, sampling protocols should capture this spatial variability. Developing nutrient criteria and
monitoring the success of nutrient management programs involves important considerations for
sampling designed to capture spatial and temporal patterns.
Below is a brief overview of the use of nutrient loading and soil and water column nutrient
measures for estimating nutrient condition of wetlands. Please refer to Supplementary
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References for a list of references on both nutrient load estimation and biogeochemical
indicators, with a focus on soil and water column nutrient measures.
NUTRIENT LOADING
External nutrient loads to wetlands are determined primarily by surface and subsurface transport
from the contributing landscape, and vary significantly as a function of weather and landscape
characteristics such as soils, topography, and land use. Most wetlands are characterized by
extremely variable hydrologic and nutrient loading rates, which present considerable obstacles to
obtaining adequate direct measurement of nutrient inputs. Adequate measurement of loads may
require automated samplers capable of providing flow-weighted samples when loading rates are
highly variable. In many cases, nonpoint source loads simply may not be adequately sampled.
The more detailed the loading measurements the better, but it is not reasonable to expect
adequate direct measurement of loads for most wetlands. In the absence of sufficient, direct
measurements, it may be possible to estimate nutrient loading using an appropriate loading
model or at least to provide a relative ranking of wetlands based on expected nutrient load. One
advantage of loading models is that nutrient loading can be integrated over the appropriate time
scale for characterizing wetland nutrient condition and, in some cases, historical loading patterns
can be reconstructed. Loading models also can provide hydrologic loading rates to calculate
critical supporting variables such as hydroperiod and residence times.
Loading function models are based on empirical or semi-empirical relationships that provide
estimates of pollutant loads on the basis of long-term measurements of flow and contaminant
concentration. Generally, loading function models contain procedures for estimating pollutant
load based on empirical relationships between landscape physiographic characteristics and
phenomena that control pollutant export. McElroy et.al., (1976) and Mills (1985) described
loading functions employed in screening models developed by the USEPA to facilitate
estimation of nutrient loads from point and nonpoint sources. The models contain simple
empirical expressions that relate the magnitude of nonpoint pollutant load to readily available or
measurable input parameters such as soils, land use and cover, land management practices, and
topography. Preston and Brakebill (1999) described a spatial regression model that relates the
water quality conditions within a watershed to sources of nutrients and to those factors that
influence transport of the nutrients. The regression model, Spatially-Referenced Regressions on
Watersheds (SPARROW), involves a statistical technique that utilizes spatially referenced
information and data to provide estimates of nutrient load (Smith et al., 1997; Smith et al., 2003;
http://water.usgs.gov/nawqa/sparrow/).
In general, the SPARROW methodology was designed to provide statistically based
relationships between stream water quality and anthropogenic factors such as contaminant
sources within the contributing watersheds, land surface characteristics that influence the
delivery of pollutants to the stream, and in-stream contaminant losses via chemical and
biological process pathways. The Generalized Watershed Loading Functions (GWLF) model
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(Haith and Shoemaker, 1987; Haith et al., 1992) uses daily time steps, and to some extent, both
can be used to examine seasonal variability and the response to landscape characteristics of
specific watersheds. The GWLF model was developed to evaluate the point and nonpoint
loading of nitrogen and phosphorus in urban and rural watersheds. The model enhances
assessment of effectiveness of certain land use management practices and makes extensive use of
readily available watershed data. The GWLF also provides an analytical tool to identify and rank
critical areas of a watershed and evaluate alternative land management programs.
Process-oriented simulation models attempt to explicitly represent biological, chemical, and
physical processes controlling hydrology and pollutant transport. These models are at least partly
mechanistic in nature and are built from equations that contain directly definable, observable
parameters. Examples of process-oriented simulation models that have been used to predict
watershed hydrology and water quality include the Agricultural Nonpoint Source model
(AGNPS), the Hydrologic Simulation Program-Fortran (HSPF), and the Soil and Water
Assessment Tool (SWAT). AGNPS (Young et. al., 1987) is a distributed parameter, event-based
and continuous simulation model that predicts the behavior of runoff, sediment, nutrients, and
pesticide transport from watersheds that have agriculture as the primary land use. Because of its
simplicity and ease of use, AGNPS is probably one of the most widely used hydrologic and
water quality models of watershed assessment. HSPF (Johansen et al., 1984; Bicknell et al.,
1993; Donigian et al., 1995a) is a lumped parameter, continuous simulation model developed
during the mid-1970s to predict watershed hydrology and water quality for both conventional
and toxic organic pollutants. HSPF is one of the most comprehensive models available for
simulating nonpoint source nutrient loading. The capability, strengths, and weaknesses of HSPF
have been demonstrated by its application to many urban and rural watersheds and basins (e.g.,
Donigian et al., 1990; Moore et al., 1992; and Ball et al., 1993). SWAT (Arnold et al., 1995) is a
lumped parameter, continuous simulation model developed by USD A-Agricultural Research
Services that provides long-term simulation of impact of land management practices on water,
sediment, and agricultural chemical yields in large complex watersheds. Because of its lumped
parameter nature, coupled with its extensive climatic, soil, and management databases, the
SWAT model is one of the most widely used hydrologic and water quality models for large
watersheds and basins, and the model has found widespread application in many modeling
studies that involve systemic evaluation of impact of agricultural management on water quality.
These loading models address only gross, external nutrient inputs. It is important to consider the
overall mass balance for the receiving wetland in developing measures of nutrient loading
against which to evaluate wetland nutrient condition. This requires some estimate of nutrient
export, storage, and transformation. In the absence of sufficient, direct measurements from
which to calculate nutrient mass balance, it may be possible to estimate nutrient mass balances
using an appropriate wetland model. Strictly empirical, regression models can be used to
estimate nutrient retention and export in wetlands but these regressions are of little value outside
the data domain in which they are developed. When developed for a diverse set of systems, the
scatter in these regressions can be quite large. In contrast to strictly empirical regressions, mass
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balance models incorporate principles of mass conservation. These models integrate external
loading to the wetland, nutrient transformation and retention within the wetland, and nutrient
export from the wetland. Mass balance models allow time varying hydrologic and nutrient inputs
and can provide estimates of spatial nutrient distribution within the wetland. The most difficult
problem is developing removal rate equations which adequately represent nutrient
transformation and retention across the range of conditions for which estimates are needed.
LAND USE
Identifying land uses in regions surrounding wetlands is important for characterizing reference
condition, identifying reference wetlands, and providing indicators of nutrient loading rates for
criteria development. Most simply, the percentage of natural area or the percentage of
agricultural and urban lands can be used to characterize land uses around wetlands. More
detailed quantitative data can be gathered from GIS analysis, which provides higher resolution
identification of land use types such as pastures, row crops, and confined animal feeding
operations for agriculture. Ideally these characterizations should be done for the entire
sourceshed, including both air and water, in the regions around wetlands. Air-sheds should
incorporate potential atmospheric sources of nutrients, and watersheds should incorporate
potential aquatic sources. However, in practice, land use around wetlands is typically used for
defining reference wetlands and also in most nutrient loading models to characterize
groundwater and surface water sources. Land use in buffer zones, one kilometer zones around
wetlands and wetland watersheds (delineated by elevation), has been used to characterize human
activities that could be affecting wetlands (Brooks et.al., 2004).
EXTRACTABLE SOIL NITROGEN AND PHOSPHORUS
Ammonium is the dominant form of inorganic N in wetland soils, and unlike total soil N (Craft
et.al., 1995, Chiang et.al., 2000), soil extractable NH4-N increases in response to N loadings.
Enrichment leads to enhanced cycling of N between wetland biota (Valiela and Teal 1974,
Broome et.al., 1975, Chalmers 1979, Shaver et.al., 1998), greater activity of denitrifying bacteria
(Johnston 1991, Groffman 1994, White and Reddy 1999), and accelerated organic matter andN
accumulation in soil (Reddy et.al., 1993, Craft and Richardson 1998). In most cases, extractable
soil N should be measured in the surface soil where roots and biological activity are
concentrated.
Extractable N is measured by extraction of inorganic (NH4-N) N with 2 M KC1 (Mulvaney
1996). Ten to twenty grams of field moist soil is equilibrated with 100 ml of 2 M KC1 for one
hour on a reciprocating shaker, followed by filtration through Whatman No. 42 filter paper.
Ammonium-N in soil extracts is determined colorimetrically using the phenate or salicylate
method (APHA 1999, Method 350.2, USEPA, 1993a).
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Extractable P is often a reliable indicator of the P enrichment of soils, and in wetlands,
extractable P is strongly correlated with surface water P concentration and P enrichment from
external sources (Reddy et.al., 1995, 1998). Selected methods used to extract P are described
below (Kuo 1996). Many soil testing laboratories perform these analyses on a routine basis.
Historically, these methods have been used to determine nutrient needs of agronomic crops, but
the methods have been used more recently to estimate P impacts in upland and wetland soils
(Sharpley et.al., 1992; Nair et.al., 1995; Reddy et.al., 1995, 1998).
The Mehlich I method is typically used in the Southeast and Mid-Atlantic regions on mineral
soils with pH of < 7.0 (Kuo 1996). The extractant consists of dilute concentrations of strong
acids. Many plant nutrients such as P, K, Ca, Mg, Fe, Zn, and Cu extracted with Mehlich I
methods have been calibrated for production of crops in agricultural ecosystems. This solvent
extracts some Fe and Al- bound P, and some Ca-bound P. Soil (dry) to extractant ratio is set at
1:4, for mineral soils, while wider ratios are used for organic soils. Soil solutions are equilibrated
for a period of five minutes on a mechanical shaker and then filtered through a Whatman No. 42
filter. Filtered solutions are analyzed for P and other nutrients using standard methods (Method
365.1,USEPA, 1993a).
The Bray P-l method has been widely used as an index of available P in soils (Kuo 1996). The
combination of dilute concentration of strong acid (HC1 at 0.025 M) and ammonium fluoride
(NH4F at 0.03 M) is designed to easily remove acid extractable soluble P forms such as Ca-
bound P, and some Fe and Al-bound P. Soil (dry) to extractant ratio is set at 1:7 for mineral soils
with wider ratios used for highly organic soils, then shaken for five minutes and filtered through
a Whatman No. 42 filter. Filtered solutions are analyzed for P and other nutrients using the same
methods used for the Mehlich I extraction (Method 365.1, USEPA 1993a).
Bicarbonate Extractable P is a suitable method for calcareous soils. Soil P is extracted from the
soil with 0.5 M NaHCOs at a nearly constant pH of 8.5 (Kuo 1996). In calcareous, alkaline, or
neutral soils containing Ca-bound P, this extractant decreases the concentration of Ca in solution
by causing precipitation of Ca as CaCOs. As a result, P concentration in soil solution increases.
Soil (dry) to extraction ratio is set at 1:20 for mineral soils and 1:100 for highly organic soils.
Soil solutions are equilibrated for a period of 30 minutes on a shaker, filtered through a
Whatman No. 42 filter paper, and analyzed for P using standard methods (Method 365.1,
USEPA, 1993a).
TOTAL SOIL NITROGEN AND PHOSPHORUS
Nutrient enrichment leads to enrichment of total soil P (Craft and Richardson 1993, Reddy et.al.,
1993, Bridgham et al., 2001). In contrast, soil total N usually does not increase in response to
nutrient enrichment (Craft et.al., 1995, Chiang et.al., 2000). Rather, enrichment leads to
enhanced cycling of N between wetland biota that is reflected in greater N uptake and net
primary production (NPP) of wetland vegetation (Valiela and Teal 1974, Broome et.al., 1975,
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Chalmers 1979, Shaver et.al., 1998), greater activity of denitrifying bacteria (Johnston 1991,
Groffman 1994, White and Reddy 1999), and accelerated organic matter and N accumulation in
soil (Reddy et.al., 1993, Craft and Richardson 1998). In most cases, total N and P should be
measured in at least the surface soil where most roots and biological activity are concentrated.
Since ammonium N is the dominant form of inorganic nitrogen in saturated wetland soils with
very little nitrate (NO3) present, total Kjeldahl nitrogen (TKN) can generally be taken as a
measure of total N in such soils. The difference between TKN and ammonium N provides
information on soil organic N. The soil organic carbon to soil organic nitrogen ratio can provide
an indication of the soil's capacity to mineralize organic N and provide ammonium N to
vegetation. TKN in soils is determined by converting organic forms of N to NH4-N by digestion
with concentrated H2SO4 at temperatures of 300-350 ° C (Bremner 1996). The NH4-N in digested
samples is analyzed using colorimetric (e.g., phenate, salicylate) methods (APHA 1999,
Mulvaney 1996).
Total P in soils is determined by oxidation of organic forms of P and acid (nitric-perchloric acid)
dissolution of minerals at temperatures of <300°C (Kuo 1996). Digested solutions are analyzed
for P using colorimetric methods (e.g., ascorbic acid-molybdate) (APHA 1999, Kuo 1996).
Many laboratories may not have access to perchloric acid fume-hoods. Alternatively, soil total
phosphorus can be determined using the ashing method (Anderson, 1976). Results obtained from
this method are reliable and comparable to total phosphorus measurements made using
perchloric acid digestion method.
WATER COLUMN NITROGEN AND PHOSPHOROUS
Nutrient inputs to wetlands are highly variable across space and time, hence, single
measurements of water column N and P represent only a "snap-shot" of nutrient condition and
may or may not reflect the long-term pattern of nutrient inputs that alter biogeochemical cycles
and affect wetland biota. The best use of water column N and P concentrations for nutrient
criteria development will be based on frequent monitoring of nutrient concentrations over time
(e.g., weekly or monthly measurements). Of course, in wetlands that are seldom flooded,
measurements of water column N and P may not be practical or even relevant for assessing
impacts. Whenever water samples are obtained, it is important that the water depth is recorded
because nutrient concentration is related to water depth. In the case of tidal estuarine or
freshwater wetlands, it is also important to record flow and the point in the tidal cycle that the
samples were collected.
Methodologies to monitor N in surface waters are well developed for other ecosystems and can
be readily adopted for wetlands. The most commonly monitored N species are total Kjeldahl
nitrogen (TKN), ammonium N, and nitrate plus nitrite N (APHA 1999). The TKN analysis
includes both organic and ammonium N, but does not include nitrate plus nitrite N. Organic N is
determined as the difference between TKN and NH4-N. Forms of N in surface water are
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measured by standard methods, including phenol-hypochlorite for ammonium N, cadmium
reduction of nitrate to nitrite for nitrate N, and Kjeldahl digestion of total N to ammonium for
analysis of total N (APHA 1999). Dissolved organic N is primarily used by heterotrophic
microbes, whereas plants and various microorganisms take up inorganic forms of N (ammonium
N and nitrate N) to support metabolism and new growth.
Methodologies to monitor P in surface waters are well developed for aquatic ecosystems and can
be readily adopted for wetlands (APHA 1999). The most commonly measured forms of P in
surface water are total P, dissolved inorganic P (i.e., PO/t-P), and total dissolved P. To trace the
transport and transformations of P in wetlands, it might be useful to distinguish four forms of P:
(i) dissolved inorganic P (DIP, also referred to as dissolved reactive P (DRP) or soluble reactive
phosphorous (SRP)); (ii) dissolved organic P (DOP); (iii) particulate inorganic P (PIP); and, (iv)
particulate organic P (POP). Dissolved inorganic P (PCVP) is considered bioavailable (e.g.,
available for uptake and use by microorganisms, algae, and vegetation), whereas organic and
particulate P forms generally must be transformed into inorganic forms before being considered
bioavailable. In P limited wetlands, a significant fraction of DOP can be hydrolyzed by
phosphatases and utilized by bacteria, algae, and macrophytes.
5.4 RESPONSE VARIABLES
Biotic measures that can integrate a wetland's variable nutrient history over a period of months
to years may provide the most useful measures of wetland response to nutrient enrichment.
Microorganisms, algae, and macrophytes respond to nutrient enrichment by: (1) increasing the
concentration of nutrients (P, N) in their tissues; (2) increasing growth and biomass production;
and, (3) shifts in species composition. The biotic response to nutrient enrichment generally
occurs in a sequential manner as nutrient uptake occurs first, followed by increased biomass
production, followed by a shift in species composition as some species disappear and other
species replace them. Macroinvertebrates respond to nutrient enrichment indirectly as a result of
changes in food sources, habitat structure, and dissolved oxygen. Because of their short life
cycle, microorganisms and algae respond more quickly to nutrient enrichment than macrophytes.
However, biotic measures that can integrate a wetland's variable nutrient history over a period of
months to years may provide the most useful measures of wetland response.
Below is a brief overview of the use of macrophytes, algae, and macroinvertebrates to assess
nutrient condition of wetlands. Please refer to the relevant modules in the EPA series "Methods
for Evaluating Wetland Condition" for details on using vegetation
(http://www.epa.gov/waterscience/criteria/wetlands/16Indicators.pdf;
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http://www.epa.gov/waterscience/criteria/wetlands/10Vegetation.pdf), algae;
(http://www.epa.gov/waterscience/criteria/wetlands/llAlgae.pdf): and, macroinvertebrates
(http://www.epa.gov/waterscience/criteria/wetlands/9Invertebrate.pdf) to assess wetland
condition, including nutrients.
MACROPHYTE NITROGEN AND PHOSPHORUS
Wetland macrophytes respond to nutrient enrichment by increasing uptake and storage of N and
P (Verhoeven and Schmitz 1991, Shaver et.al., 1998, Chiang et.al., 2000). In wetlands where P is
the primary limiting nutrient, the P content of vegetation increases almost immediately (within a
few months) in response to nutrient enrichment (Craft et.al., 1995). Increased P uptake by plants
is known as "luxury uptake" because P is stored in vacuoles and used later (Davis 1991). Like P,
leaf tissue N may increase in response to N enrichment (Brinson et.al., 1984, Shaver et.al.,
1998). However, most N is directly used to support new plant growth so that luxury uptake of N
is not usually observed (Verhoeven and Schmitz 1991). Tidal marsh grasses, however, do appear
to store nitrogen in both living and dead tissues that can be accessed by living plant tissue. A
discussion of conservation and translocation of N in saltwater tidal marshes can be found in
Hopkinson and Schubauer (1980) and Thomas and Christian (2001).
Nutrient content of macrophyte tissue holds promise as a means to assess nutrient enrichment of
wetlands. However, several caveats should be kept in mind when using this diagnostic tool
(Gerloff 1969, Gerloff and Krombholz 1966, EPA 2002c).
1. The most appropriate plant parts to sample and analyze should be determined. It is
generally recognized that the plant or plant parts should be of the same physiological age.
2. Samples from the same species should be collected and analyzed. Different species
assimilate and concentrate nutrients to different levels.
3. Tissue nutrient concentrations vary with (leaf) position, plant part, and age. It is
important to sample and analyze leaves from the same position and age (e.g., third leaf
from the terminal bud on the plant) to ensure comparability of results from sampling of
different wetlands.
4. Tissue P may be a more reliable indicator of nutrient condition than N. This is because N
is used to increase production of aboveground biomass, whereas excess P is stored via
luxury uptake.
Another promising macrophyte-based tool is the measurement of nutrient resorption of N and P
prior to leaf senescence and dieback. Nutrient resorption is an important strategy used by
macrophytes to conserve nutrients (Hopkinson and Schubauer 1984; Shaver and Melillo 1984).
In nutrient-poor environments, macrophytes resorb N and P from green leaves prior to
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senescence, leading to low concentrations of N and P in senesced leaves. In nutrient-rich
environments, resorption becomes less important so that senesced leaves retain much of the N
and P that was present when the leaves were green.
Nitrogen and phosphorus should be measured in green leaves of the same approximate age
collected from the dominant wetland plant species. Samples also should be collected throughout
the wetland to account for spatial variability. If an environmental gradient is known or suspected
to exist within the wetland, then sites along this gradient should be sampled separately. At each
sampling location, approximately five green leaves are collected from each of the dominant plant
species. Leaves are collected from the middle portion of the stem, avoiding very young leaves at
the top of the stem and very old leaves at the bottom of the stem. At each location, leaf samples
by species are combined for analysis, oven-dried at 70°C, and ground.
Nitrogen is measured by dry combustion using a CHN analyzer. Phosphorus is measured
colorimetrically after digestion in strong acid (H2SO4-H2O2) (Allen et.al., 1986). Many land-
grant universities, State agricultural testing laboratories, and environmental consulting
laboratories perform these analyses. Contact your local U.S. Department of Agriculture office or
land-grant agricultural extension office for information on laboratories that perform plant tissue
nutrient analyses.
Please see the EPA module #16, Vegetation-based Indicators of Wetland Nutrient Enrichment
(http://www.epa.gov/waterscience/criteria/wetlands/16Indicators.pdf) for a detailed description
of indicators derived from N and P content of macrophytes.
ABOVEGROUND BIOMASS AND STEM HEIGHT
Wetland macrophytes also respond to nutrient enrichment by increased net primary production
(NPP) and growth if other factors such as light are not limiting growth (Chiang et.al.,2000). Net
primary production is the amount of carbon fixed during photosynthesis that is incorporated into
new leaves, stems, and roots. Most techniques to measure NPP focus on aboveground biomass
and discount root production because it is difficult to measure, even though root production may
account for 50% of NPP. The simplest way to measure aboveground biomass is by harvesting all
of the standing material (biomass) at the end of the growing season (Broome et al., 1986). The
harvest method is useful for measuring NPP of herbaceous emergent vegetation, especially in
temperate climates where there is a distinct growing season. If root production desired, it can be
determined by sequentially harvesting roots at monthly intervals during the year (Valiela et. al,
1976).
Enhanced NPP often is reflected by increased height and, sometimes, stem density of herbaceous
emergent vegetation (Broome et. al., 1983). Because increased stem density may reflect other
factors like vigorous clonal growth, it is not recommended as an indicator of nutrient enrichment.
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Aboveground biomass of herbaceous vegetation may be determined by end-of-season harvest of
aboveground plant material in small 0.25 m2 quadrats stratified by macrophyte species or
inundation zone (Broome et.al., 1986). Stem height of individuals of dominant species is
measured in each plot. Height of the five to 10 tallest stems in each plot has been shown to be a
reliable indicator of NPP (Broome et.al., 1986) that saves time as compared to height
measurements of all stems in the plot. Aboveground biomass is clipped at the end of the growing
season, in late summer or fall. Clipped material is separated into live (biomass) versus dead
material, then dried at 70°C to a constant weight. For stem height and biomass sampling, five to
10 plots per vegetation zone are collected. In forested sites, biomass production is defined as the
sum of the leaf and fruit fall and aboveground wood production (Newbould, 1967). Please see
the EPA module Vegetation-based Indicators of Wetland Nutrient Enrichment
(http://www.epa.gov/waterscience/criteria/wetlands/16Indicators.pdf) for a detailed description
of sampling aboveground biomass in wetlands.
ALGAL NITROGEN & PHOSPHORUS
In some cases, measurements of algal N and P can provide a useful complement to vegetation
and soil nutrient analyses that integrate nutrient history over a period of months in the case of
vegetation (Craft et.al., 1995), to years in the case of soils (Craft and Richardson 1998, Chiang
et.al., 2000). Nutrient concentrations in algae can integrate variation in water column N and P
bioavailability over a time scale of weeks, potentially providing an indication of the recent
nutrient status of a wetland (Fong et al., 1990; Stevenson et.al., 2001). Caution is warranted for
this method because it is not useful in all wetlands; for example, in wetlands where surface
inundation occurs intermittently or for short periods of time, where the water surface is severely
shaded as in some forested wetlands, or under other circumstances where unrelated
environmental factors exert primary control over algal growth.
Algae should be sampled by collecting grab samples from different locations in the wetland to
account for spatial variability in the wetland. If an environmental gradient is known or suspected
(i.e., decreasing canopy or impacted land uses) or exists within the wetland as a result of specific
source discharges, then sites along this gradient should be sampled separately. Comparisons
among wetlands or locations within a wetland should be done on a habitat-specific basis (e.g.,
phytoplankton vs. periphyton). Samples are processed in the same manner as wetland plants to
determine N and P content. Nitrogen is determined using a CHN analyzer, whereas P is
measured colorimetrically after acid digestion.
Please see the EPA module Using Algae to Assess Environmental Conditions in Wetlands
(http://www.epa.gov/waterscience/criteria/wetlands/llAlgae.pdf) for a detailed description of
indicators derived from to N and P content of algae.
MACROPHYTE COMMUNITY STRUCTURE AND COMPOSITION
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The composition of the plant community and the changes that result from human activities can
be used as sensitive indicators of the biological integrity of wetland ecosystems. In particular,
aggressive, fast-growing species such as cattail (Typha spp.), giant reed (Phragmites communis),
reed canarygrass (Phalaris arundincea), and other clonal species invade and may eventually
come to dominate the macrophyte community. Data collection methods and analyses for using
macrophyte community structure and composition as an indicator of nutrient enrichment and
ecosystem integrity for wetlands are described in Vegetation-based Indicators of Wetland
Nutrient Enrichment (http://www.epa.gov/waterscience/criteria/wetlands/16Indicators.pdf) and
Using Vegetation to Assess Environmental Conditions in Wetlands
(http://www.epa.gov/waterscience/criteria/wetlands/10Vegetation.pdf), respectively.
ALGAL COMMUNITY STRUCTURE AND COMPOSITION
Algae can be used as a valuable indicator of biological and ecological condition of wetlands.
Structural and functional attributes of algae can be measured including diversity, biomass,
chemical composition, productivity, and other metabolic functions. Species composition of
algae, particularly of the diatoms, is commonly used as an indicator of biological integrity and
physical and chemical conditions of wetlands. Discussions of sampling, data analyses, and
interpretation are included in Using Algae to Assess Environmental Conditions in Wetlands
(http://www.epa.gov/waterscience/criteria/wetlands/llAlgae.pdf).
INVERTEBRATE COMMUNITY STRUCTURE AND COMPOSITION
Aquatic invertebrates can be used to assess the biological and ecological condition of wetlands.
The approach for developing an Index of Biological Integrity (IBI) for wetlands based on aquatic
invertebrates is described in Developing an Invertebrate Index of Biological Integrity for
Wetlands (http://www.epa.gov/waterscience/criteria/wetlands/9Invertebrate.pdf).
5.5 SUMMARY
Candidate variables to use in determining nutrient condition of wetlands and to help identify
appropriate nutrient criteria for wetlands consist of supporting variables, causal variables, and
response variables. Supporting variables provide information useful in normalizing causal and
response variables and categorizing wetlands. Causal variables are intended to characterize
nutrient availability (or assimilation) in wetlands and could include nutrient loading rates and
soil nutrient concentrations. Response variables are intended to characterize biotic response and
could include community structure and composition of macrophytes and algae.
The complex temporal and spatial structure of wetlands will influence the selection of variables
to measure and methods for measuring them. The information contained in this chapter is a brief
summary of suggested analyses that can be used to determine wetland condition with respect to
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nutrient status. The authors recognize that the candidate variables and analytical methods
described here will generally be the most useful for identifying wetland nutrient condition, while
other methods and analyses may be more appropriate in certain systems.
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Chapter 6 Database Development and New Data
Collection
6.1 INTRODUCTION
A database of relevant water quality information can be an invaluable tool to States as they
develop nutrient criteria. In some cases, existing data are available and can provide additional
information that is specific to the region where criteria are to be set. However, little or no data
are available for most regions or parameters and creating a database of newly gathered data is
strongly recommended. In the case of existing data, the data should be located and their
suitability (type and quality and sufficient associated metadata) ascertained. It is also important
to determine how the data were collected to ensure that future monitoring efforts are compatible
with earlier approaches.
Databases operate much like spreadsheet applications but have greater capabilities. Databases
store and manage large quantities of data and allow viewing and exporting of data sorted in a
variety of ways, while spreadsheets analyze and graphically display small quantities of data.
Databases can be used to organize existing information, store newly gathered monitoring data,
and manipulate data for water quality criteria development. Databases can sort data for export
into statistical analyses programs, spreadsheets, and graphics programs. This chapter will discuss
the role of databases in nutrient criteria development and provide a brief review of existing
sources of nutrient-related water quality information for wetlands.
6.2 DATABASES AND DATABASE MANAGEMENT
A database is a collection of information related to a particular subject or purpose. Databases are
arranged so that individual values are kept separate, yet can be linked to other values based on
some common denominator (such as association of time or location). Geographic Information
Systems (GIS) are geo-referenced relational databases that have a geographical component (i.e.,
spatial platform) in the user interface. Spatial platforms associated with a database allow
geographical display of sets of sorted data. GIS platforms such as Arc View™, Arclnfo™, and
Maplnfo™ are frequently used to integrate spatial data with monitoring data for watershed
analysis. Data stored in simple tables, relational databases, or geo-reference databases can also
be located, retrieved, and manipulated using queries. A query allows the user to find and retrieve
only the data that meets user-specified conditions. Queries can also be used to update or delete
multiple records simultaneously and to perform built-in or custom calculations of data. Data in
tables can be analyzed and printed in specific layouts using reports. Data can be analyzed or
presented in a specific way in print by creating a report. The most effective use of these tools
requires a certain amount of training, expertise, and software support, especially when using geo-
referenced data.
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To facilitate data storage, manipulation, and calculations, it is highly recommended that
historical and present-day data be transferred to a relational database (i.e., Access™). Relational
databases store data in tables as sets of rows and columns and are powerful tools for data
manipulation and initial data reduction. They allow selection of data by specific, multiple criteria
and definition and redefinition of linkages among data components. Data queries can also be
exported to GIS, provided that the data is related to some geo-referenced coordinate system.
POTENTIAL DATA SOURCES
EPA Water Quality Data
STORET
EPA has many programs of national scope that focus on collection and analysis of water quality
data. The following presents information on several of the databases and national programs that
may be useful to water quality managers as they compile data for criteria development.
STORET STOrage and RETrieval system (STORET) is EPA's national database for water
quality and biological data.
Environmental Monitoring and Assessment Program (EMAP)
The Environmental Monitoring and Assessment Program is an EPA research program designed
to develop the tools necessary to monitor and assess the status and trends of national ecological
resources (see EMAP Research Strategy on the EMAP Web site: www.epa.gov/emap). EMAP's
goal is to develop the scientific understanding for translating environmental monitoring data
from multiple spatial and temporal scales into assessments of ecological condition and forecasts
of future risks to the sustainability of the Nation's natural resources. Data from the EMAP
program can be downloaded directly from the EMAP Web site (www.epa.gov/emap/. The
EMAP Data Directory contains information on available data sets, including data and metadata
(language that describes the nature and content of data). Current status of the data directory, as
well as composite data and metadata files, are available on this Web site.
U.S. Geological Surve) (USGS) Water Data
The USGS has national and distributed databases on water quantity and quality for waterbodies
across the nation. Much of the data for rivers and streams are available through the National
Water Information System (NWIS). These data are organized by State, Hydrologic Unit Codes
(HUCs), latitude and longitude, and other descriptive attributes. Most water quality chemical
analyses are associated with an instantaneous streamflow at the time of sampling and can be
linked to continuous streamflow to compute constituent loads or yields. The most convenient
method of accessing the local databases is through the USGS State representative. Every State
office can be reached through the USGS home page at: http://www.usgs.gov.
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HBN and NASQAN
USGS data from several national water quality programs covering large regions offer highly
controlled and consistently collected data that may be particularly useful for nutrient criteria
analysis. Two programs, the Hydrologic Benchmark Network (HBN) and the National Stream
Quality Accounting Network (NASQAN), include routine monitoring of rivers and streams over
the past 30 years. The HBN consists of 63 relatively small, minimally disturbed watersheds.
HBN data were collected to investigate naturally-induced changes in streamflow and water
quality and the effects of airborne substances on water quality. The NASQAN program consists
of 618 larger, more culturally influenced watersheds. NASQAN data provides information for
tracking water-quality conditions in major U.S. rivers and streams. The watersheds in both
networks include a diverse set of climatic, physiographic, and cultural characteristics. Data from
the networks have been used to describe geographic variations in water-quality concentrations,
quantify water-quality trends, estimate rates of chemical flux from watersheds, and investigate
relations of water quality to the natural environment and anthropogenic contaminant sources.
WEBB
The Water, Energy, and Biogeochemical Budgets (WEBB) program was developed by USGS to
study water, energy, and biogeochemical processes in a variety of climatic/regional scenarios.
Five ecologically diverse watersheds, each with an established data history, were chosen. This
program may prove to be a rich data source for ecoregions in which the five watersheds are
located. Many publications on the WEBB project are available. See the USGS Web site for more
details (http://water.usgs.gov/nrp/webb/about.html).
US Department of Agriculture (USDA)
Agricultural Research Service (ARS)
The USDA ARS houses the Natural Resources and Sustainable Agricultural Systems Scientific
Directory (http://hydrolab.arsusda.gov/arssci.html), which has seven national programs to
examine the effect of agriculture on the environment. The program on Water Quality and
Management addresses the role of agriculture in nonpoint source pollution through research on
Agricultural Watershed Management and Landscape Features, Irrigation and Drainage
Management Systems, and Water Quality Protection and Management Systems. Research is
conducted across the country and several models and databases have been developed.
Information on research and program contacts is listed on the Web site
(http://www.nps.ars.usda.gov/programs/nrsas.htm).
Forest Service
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The Forest Service has designated research sites across the country, many of which are Long
Term Ecological Research (LTER) sites. Many of the data from these experiments are available
in the USFS databases located on the Web site (http://www.fs.fed.us/research/). Most of the data
are forest-related but may be of use for determining land uses and questions on silviculture
runoff.
National Science Foundation (NSF)
The National Science Foundation (NSF) funds projects for the Long Term Ecological Research
(LTER) Network. The Network is a collaboration of over 1,100 researchers investigating a wide
range of ecological topics at 24 different sites nationwide. The LTER research programs are not
only an extremely rich data source, but also a source of data available to anyone through the
Network Information System (NTS), the NSF data source for LTER sites. Data sets from sites are
highly comparable due to standardization of methods and equipment.
U.S. Army Corps of Engineers (COE)
The U.S. Army Corps of Engineers (COE) is responsible for many federal wetland jurisdiction
issues. Although a specific network of water quality monitoring data does not exist, specific
studies on wetlands by the COE may provide suitable data. The COE focuses more on water
quantity issues than on water quality issues. As a result, much of the wetland system data
collected by the COE does not include nutrient data. Nonetheless, the COE does have a large
water sampling network and supports USGS and EPA monitoring efforts in many programs. A
list of the water quality programs that the COE actively participates in can be found at
http://www.usace.army.mil/public.html.
U.S. Department of the Interior, Bureau of Reclamation (BuRec)
The Bureau of Reclamation of the U.S. Department of the Interior manages many irrigation and
water supply reservoirs in the West, some of which may have wetland applicable data available.
These data focus on water supply information and limited water quality data. However, real time
flow data are collected for rivers supplying water to BuRec, which may be useful if a flow
component of criteria development is chosen. These data can be gathered on a site-specific basis
from the BuRec Web site: http://www.usbr.gov.
State Monitoring Programs
Some States may have wetland water quality data as part of a research study, use attainability
analysis (UAA), or to assess mitigation or nutrient related impacts. Most of this data is collected
by State natural resources or environmental protection agencies, or by regional water
management authorities. Data collected by State water quality monitoring programs can be used
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for nutrient criteria development and may provide pertinent data sources, although they may be
regionally limited. These data should be available from the agencies responsible for monitoring.
Volunteer Monitoring Programs
State and local agencies may use volunteer data to screen for water quality problems, establish
trends in waters that would otherwise be unmonitored, and make planning decisions. Volunteers
benefit from learning more about their local water resources and identifying what conditions or
activities might contribute to pollution problems. As a result, volunteers frequently work with
clubs, environmental groups, and State or local governments to address problem areas. The EPA
supports volunteer monitoring and local involvement in protecting our water resources.
Academic and Literature Sources
Most of the data available on water and soil quality in wetlands is the result of research studies
conducted by academic institutions. Much of the research conducted by the academic
community, however, was not conducted for the purpose of spatial or long-term biogeochemical
characterization of the nation's wetlands; instead, water quality information was often collected
to characterize the environmental conditions under which a particular study or experiment was
conducted. Infrequently, spatial studies of limited extent or duration were conducted. Data
collected from these sources, therefore, may not be sufficiently representative of the population
of wetlands within an ecoregion. However, this limited data may be the only information
available and therefore could be useful for identifying reference conditions or determining where
to begin a more comprehensive survey to support development of nutrient criteria. Academic
research data is available from researchers and the scientific literature.
6.3 QUALITY OF HISTORICAL AND COLLECTED DATA
The value of older historical data is a recurrent problem because data quality is often unknown.
Knowledge of data quality is also problematic for long-term data repositories such as STORET
and long-term State databases, where objectives, methods, and investigators may have changed
many times over the years. The most reliable data tend to be those collected by a single agency
using the same protocol. Supporting documentation should be examined to determine the
consistency of sampling and analytical protocols. The suitability of data in large, heterogeneous
data repositories for establishing nutrient criteria are described below. These same factors need
to be taken into account when developing a new database such that future investigators will have
sufficient information necessary to evaluate the quality of the database.
LOCATION
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Geo-referenced data is extremely valuable in that it allows for aggregating and summarizing data
according to any GIS coverage desired, whether the data was historically related to a particular
coverage theme or not. However, many studies conducted prior to the availability and accuracy
of hand held Global Positioning System (GPS) units relied on narrative and less definitive
descriptions of location such as proximity to transportation corridor, county, or nearest municipal
center. This can make comparison of data, depending upon desired spatial resolution, difficult.
Knowledge of the rationale and methods of site selection from the original investigators may
supply valuable information for determining whether inclusion of the site or study in the
database is appropriate based on potential bias relative to overall wetland data sources. STORET
and USGS data associated with the National Hydrography Dataset (NHD) are geo-referenced
with latitude, longitude, and Reach File 3 (RF3) codes (http://nhd.usgs.gov/). In addition,
STORET often contains a site description to supplement location information. Metadata of this
type, when known, is frequently stored within large long-term databases.
VARIABLES AND ANALYTICAL METHODS
Each separate analytical method yields a unique variable. For example, five ways of measuring
TP result in five unique variables. Data generated using different analytical methods should not
be combined in data analyses because methods differ in accuracy, precision, and detection limits.
Data generated from one method may be too limited, making it important to select the most
frequently used analytical methods in the database. Data that were generated using the same
analytical methods may not always be obvious because of synonymous names or analytical
methods. Consistency in taxonomic conventions and indicator measurements is likewise
important for biological variables and multimetric indices comparisons. Review of recorded data
and analytical methods by knowledgeable personnel is important to ensure that there are no
problems with data sets developed from a particular database.
LABORATORY QUALITY CONTROL (QC)
Data generated by agencies or laboratories with known quality control/quality assurance
protocols are most reliable. Laboratory QC data (blanks, spikes, replicates, known standards) are
infrequently reported in larger data repositories. Records of general laboratory quality control
protocols and specific quality control procedures associated with specific data sets are valuable
in evaluating data quality. However, premature elimination of lower quality data can be
counterproductive because the increase in variance caused by analytical laboratory error may be
negligible compared to natural variability or sampling error, especially for nutrients and related
water quality parameters. However, data of uncertain and undocumented quality should not be
accepted.
Water column nutrient data can be reported in different units, e.g., ppm, mg/L, mmoles.
Reporting of nutrient data from other strata such as soils, litter, and vegetation can further
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expand the list of reporting units (e.g., mg/kg, g/kg, %, mg/cm3). In many instances, conversion
of units is possible; however, in other instances unit conversion is not possible or is lacking
support information for conversion. Consistency in reporting units and the need to provide
conversion tables cannot be overemphasized.
DATA COLLECTING AGENCIES
Selecting data from particular agencies with known, consistent sampling and analytical methods
and known quality will reduce variability due to unknown quality problems. Requesting data
review for quality assurance from the collecting agency will reduce uncertainty about data
quality.
TIME PERIOD
Long-term records are critically important for establishing trends. Determining if trends exist in
the time series database is also important for characterizing reference conditions for nutrient
criteria. Length of time series data needed for analyzing nutrient data trends is discussed in
Chapter 7.
INDEX PERIOD
An index period—the time period most appropriate for sampling—for estimating average
concentrations can be established if nutrient and water quality variables were measured through
seasonal cycles. The index period may be the entire year or the summer growing season. The
best index period is determined by considering wetland characteristics for the region, the quality
and quantity of data available, and estimates of temporal variability (if available). Consideration
of the data available relative to longer-term oscillations in environmental conditions (e.g., dry
years, wet years) should also be taken into account such that the data is representative and
appropriate. Additional information and considerations for establishing an index period are
discussed in Chapter 7.
REPRESENTATIVENESS
Data may have been collected for specific purposes. Data collected for toxicity analyses, effluent
limit determinations, or other pollution problems may not be useful for developing nutrient
criteria. Further, data collected for specific purposes may not be representative of the region or
wetland classes of interest. The investigator should determine if all wetlands or a subset of the
wetlands in the database are representative of the population of wetlands to be characterized. If a
sufficient sample of representative wetlands cannot be found, then a new survey is strongly
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6.4 COLLECTING NEW DATA
New data should be collected when no data presently exist or the data available are not suitable,
and should be gathered following the sampling design protocols discussed in Chapter 4. New
data collection activities for developing nutrient criteria should focus on filling in gaps in the
database and collecting spatially representative regional monitoring data. In many cases, this
may mean starting from scratch because no data presently exists or the data available are not
suitable. Data gathered under new monitoring programs should be imported into databases or
spreadsheets and, if comparable, merged with existing data for criteria development. It is best to
archive the data with as much data-unique information (meta-data) as possible. It is always
possible to aggregate at a later time, but impossible to separate lumped data without having the
parameter needed to partition the data set. Redundancy may also be a problem but can more
easily be avoided when common variables or parameters are kept in each database (i.e., dates
may be very important). The limitations and qualifications of each data set should be known and
data 'tagged', if possible, before combining them. The following five factors should be
considered when collecting new data and before combining new data with existing data sets:
representativeness, completeness, comparability, accuracy, and precision.
REPRESENTATIVENESS
Sampling program design (when, where, and how you sample) should produce samples that are
representative or typical of the regional area being described and the classes of wetlands present.
Sampling designs for developing nutrient criteria are addressed in Chapter 4. Databases
populated by data from the literature or historical studies will not likely provide sufficient spatial
or class representation of a region. Data interpretation should recognize these gaps and be
limited until gaps are filled using additional survey information.
COMPLETENESS
A QA/QC plan should describe how to complete the data set in order to answer questions posed
(with a statistical test of given power and confidence) and the precautions being taken to ensure
that completeness. Data collection procedures should document the extent to which these
conditions have been met. Incomplete data sets may not invalidate the collected data but may
reduce the rigor of statistical analyses. Precautions to ensure completeness may include
collecting extra samples, having back-up equipment in the field, copying field notebooks after
each trip, and/or maintaining duplicate sets of data in two locations.
COMPARABILITY
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In order to compare data collected under different sampling programs or by different agencies,
sampling protocols and analytical methods should demonstrate comparable data. The most
efficient way to produce comparable data is to use sampling designs and analytical methods that
are widely used and accepted and examined for compatibility with other monitoring programs
prior to initiation of a survey. Comparability should be assessed for field sample collection,
sample preservation, sample preparation and analysis, and among laboratories used for sample
analyses.
ACCURACY
To assess the accuracy of field instruments and analytical equipment, a standard (a sample with a
known value) should be analyzed and the measurement error or bias determined. Internal
standards should periodically be checked with external standards provided by acknowledged
sources. At Federal, State, and local government levels, the National Institute of Standards and
Technology (NIST) provides advisory and research services to all agencies by developing,
producing, and distributing standard reference materials for vegetation, soils, and sediments.
Standards and methods of calibration are typically included with turbidity meters, pH meters DO
meters, and DO testing kits. The U.S. EPA, USGS, and some private companies provide
reference standards or QC samples for nutrients.
VARIABILITY
The variability in field measurements and analytical methods should be demonstrated and
documented to identify the source and magnitude of variability when possible. EPA QA/QC
guidance provides an explanation and protocols for measuring sampling variability (USEPA
1998c).
DATA REDUCTION
For data reduction, it is important to have a clear idea of the analysis that will be performed and
a clear definition of the sample unit for analysis. For example, a sample unit might be defined as
"a wetland during July- August." For each variable measured, a mean value would then be
estimated for each wetland during the July-August index period on record. Analyses are then
conducted on the observations (estimated means) for each sample unit, not with the raw data.
Steps recommended for reducing the data include:
1. Selecting the long-term time period for analysis;
2. Selecting an index period;
3. Selecting relevant variables of interest;
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4. Identifying the quality of analytical methods;
5. Identifying the quality of the data recorded; and,
6. Estimating values for analysis (mean, median, minimum, maximum) based on the
reduction selected.
6.5 QUALITY ASSURANCE / QUALITY CONTROL (QA/QC)
The validity and usefulness of data depend on the care with which they were collected, analyzed,
and documented. EPA provides guidance on data quality assurance (QA) and quality control
(QC) (USEPA 1998c) to assure the quality of data. Factors that should be addressed in a QA/QC
plan are elaborated below. The QA/QC plan should state specific goals for each factor and
should describe the methods and protocols used to achieve the goals.
1. Who will use the data?
2. What the projecf s goals/objectives/questions or issues are?
3. What decision(s) will be made from the information obtained?
4. How, when, and where project information will be acquired or generated?
5. What possible problems may arise and what actions can be taken to mitigate their impact
on the project?
6. What type, quantity, and quality of data are specified?
7. How "good" those data have to be to support the decision to be made?
8. How the data will be analyzed, assessed, and reported?
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Chapter 7 Data Analysis
7.1 INTRODUCTION
Data analysis is critical to nutrient criteria development. Proper analysis and interpretation of
data determine the scientific defensibility and effectiveness of the criteria. Therefore, it is
important to evaluate short- and long-term goals for wetlands of a given class within the region
of concern. These goals should be addressed when analyzing and interpreting nutrient and
response data. Specific objectives to be accomplished through use of nutrient criteria should be
identified and revisited regularly to ensure that goals are being met. The purpose of this chapter
is to explore methods for analyzing data that can be used to develop nutrient criteria consistent
with these goals. Included are techniques to evaluate metrics, to examine or compare
distributions of nutrient exposure or response variables, and to examine nutrient exposure-
response relationships.
Statistical analyses are used to interpret monitoring data for criteria development. Statistical
methods are data-driven and range from very simple descriptive statistics to more complex
statistical analyses. Generally, the type of statistical analysis used for criteria development is
determined by the source, quality, and quantity of data available.
7.2 FACTORS AFFECTING ANALYSIS APPROACH
Wetland systems should be appropriately classified a priori for nutrient criteria development to
minimize natural background variation (see Chapter 3). This section discusses some of the
factors that should be considered when classifying wetland systems and in determining the
choice of predictor (causal) and response variables to include in the analysis.
Wetland hydrogeomorphic type http://el.erdc.usace.army.mil/wrap/wrap.html may determine the
sensitivity of wetlands to nutrient inputs, as well as the interaction of nutrients with other driving
factors in producing an ecological response. Hydrogeomorphic types differ in landscape
position, predominant water source, and hydrologic exchanges with adjacent water bodies
(Brinson 1993). These factors, in turn, influence water residence time, hydrologic regime, and
disturbance regime. In general, isolated depressional wetlands will have greater residence times
than fringe wetlands, which, in turn, will have greater residence times than riverine wetlands.
Systems with long residence times are likely to behave more like lakes than flow-through
systems and may show a greater response to cumulative loadings. Thus, nutrient loading rates or
indicators thereof are likely to be a more sensitive predictor of ecological effects for depressional
wetlands, while nutrient water column or sediment concentrations are likely to be a more
sensitive predictor of responses for riverine wetlands. Water column concentrations will
influence the response of algal communities, while macrophytes derive nutrients from both the
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water column and sediments. Fringe wetlands are likely to be influenced both by concentration
of nutrients in the adjacent lake or estuary as well as the accumulation of nutrients within these
systems from groundwater inflow and, in some cases, riverine inputs. The relative influence of
these two sources will depend on the exchange rate with the adjacent lake, e.g., through seiche
activity (Keough et al., 1999; Trebitz et al., 2002). In practice, it is difficult to measure loadings
from multiple sources including groundwater and exchange with adjacent water bodies. If
sediment concentrations are shown to be a good indicator of recent loading rates, then sediment
concentrations might be the best predictor to use across systems.
It may be important to control for ancillary factors when teasing out the relationship between
nutrients and vegetation community response, particularly if those factors interact with nutrients
in eliciting responses. For example, riverine and fringe wetlands differ from basin wetlands in
the frequency and intensity of disturbance from flooding events or ice. Day et. al. (1988)
describe a fertility-disturbance gradient model for riverine wetlands describing how the relative
dominance of plant guilds with different growth forms and life history strategies depends on the
interactive effects of productivity, fertility, disturbance, and water level. In depressional
wetlands, the model could be simplified to include only the interaction of fertility with the
hydrologic regime. Disturbance regimes and water level could be incorporated into analysis of
cause-effect relationships either as categorical factors or as covariates.
The selection of assessment and measurement of response attributes for determining ecological
response to nutrient loadings should depend, in part, on designated uses assigned to wetlands as
part of standards development. Designated uses such as recreation (aesthetics and contact) or
drinking water are not typically assigned to wetlands; thus, defining nuisance algal blooms in
terms of taste or odor problems or aesthetic considerations may not be appropriate for wetlands.
Guidance for the definition of aquatic life use is currently being refined to describe six stages of
impact along a human disturbance gradient, from pristine reference condition to heavily
degraded sites (Figure 7.1, Stevenson and Hauer 2002, Davies and Jackson 2006). The relative
abundance of sensitive native taxa is expected to shift with relatively minor impacts, while
organism condition or functional attributes are relatively robust to altered loadings. However, if
maintenance of ecological integrity of sensitive downstream systems is of concern, then it may
be important to measure some functional attributes related to nutrient retention. Stevenson and
Hauer (2002) have suggested a series of "resource condition tiers" analogous to those defined for
biological condition but related to ecosystem functions. Tier 1 requirements are proposed as:
"Native structure and function of the hydrologic and geomorphic regimes and processes are in
the natural range of variation in time and space." Thus maintenance of structure and function of
upstream processes should be protective of downstream biological conditions.
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c
o
c.
o
o
_o
o
m
BCG Model: Snap Shot
Natural structure & function of biotic community maintained
Minimal changes in structure & function
Evident changes in structure and
minimal changes in function
Moderate changes in structure &
minimal changes in function
Major changes in structure .
moderate changes in function
Severe changes in structure & function
Increasing Levels of Stressors
Figure 7.1. Biological condition gradient model describing biotic community condition as levels
of stressors increase.
7.3 DISTRIBUTION-BASED APPROACHES
Frequency distributions can aid in the setting of criteria by describing central tendency and
variability among wetlands. Approaches to numeric nutrient criteria development based on
frequency distributions do not require specific knowledge of individual wetland condition prior
to setting criteria. Criteria are based on and, in a sense, developed relative to the conditions of
the population of wetlands of a given class.
The simplest statistic describing the shape of distributions refers to quartiles, or the 25th and the
75th percentile. These can be defined as the observation which has 25% of the observations on
one side and 75% on the other side in the case of the first quartile (25th percentile), or vice versa
in the case of the third quartile (75th percentile). In the same manner, the median is the second
quartile or the 50th percentile. Graphically, this is depicted in boxplots as the box length, the
lower extreme represents the first quartile, and the upper extreme represents the third quartile,
the area inside the box encompassing 50% of the data.
Distributions of nutrient exposure metrics or response variables can be developed to represent
either an entire population of wetlands or only a subset of those considered to be minimally
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impacted. In either case, a population of wetlands should be defined narrowly enough through
classification so that the range in attributes due to natural variability does not equal or exceed the
range in attributes related to anthropogenic effects. The effects of natural variability can be
minimized by classifying wetlands by type and/or region. Nutrient ecoregions define one
potential regional classification system (USEPA 2000). Alternatively, thresholds in landscape or
watershed attributes defining natural breakpoints in nutrient concentrations can be determined
objectively through procedures such as classification and regression tree (CART) analysis
(Robertson et. al., 2001). If a distribution-based approach is used, periodic reviews using
empirical data that relate a measured value to an ecological attribute or ecosystem function can
validate the assumptions of the chosen percentiles.
7.4 RESPONSE-BASED APPROACHES
Indicators characterized as "response" or "condition" metrics should be distinguished from
"stressor" or "causal" indicators, such as nutrient concentrations (Paulsen et al., 1991; USEPA
1998a; Stevenson 2004a). While both "response" and "causal" indicators could be used in a
single multimetric index, it is recommended that separate multimetric indices be used for
"response" and "causal" assessment. Distinguishing between "response" and "causal" indices
can be accomplished utilizing a risk assessment approach with separate hazard and exposure
assessments that are linked to response-stressor relationships (USEPA 1996, 1998a; Stevenson
1998; Stevenson et al., 2004a, b). A multimetric index that specifically characterizes "responses"
can be used to clarify goals of management (maintenance or restoration of ecological attributes)
and to measure whether goals have been attained with nutrient management strategies.
Response-based multimetric indices can also be used more directly for natural resource damage
assessments than multimetric indices with response and causal variables.
Factors that should be considered in selecting indicators include conceptual relevance (relevance
to the assessment and ecological function), feasibility of implementation (data collection
logistics, information management, quality assurance, cost), response variability (measurement
error, seasonal variability, interannual variability, spatial variability, discriminatory ability), and
interpretation and utility (data quality objectives, assessment thresholds, link to management
actions) (Jackson et al., 2000). Of these factors, cost, response variability, and ability to meet
data quality objectives can be assessed through quantitative methods. An analytical
understanding of the factors that affect wetlands the most will also help States develop the most
effective monitoring and assessment strategies.
Designated uses such as contact recreation and drinking water may not be applicable to
wetlands, hence, it may not be readily apparent what the relative significance of changes in
different primary producers is for organisms at higher trophic levels. Wetland food webs have
traditionally been considered to be detritus-based (Odum and de la Cruz 1967; Mann 1972,
1988). However, more recent research on wetland food webs utilizing stable isotope analysis
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have identified the importance of phytoplankton, periphyton, or benthic algae as the base of the
food chain for higher trophic levels (Fry 1984, Kitting et al., 1984, Sullivan and Moncreiff 1990,
Hamilton et al., 1992, Newell et al., 1995, Keough et al., 1996); in these cases, it would be
particularly important to monitor shifts in algal producers.
Empirical relationships can be derived directly between water quality parameters such as total P
or transparency and wetland biological responses. Unlike lakes or streams, the level of algal
biomass corresponding to aesthetic problems or ecological degradation in wetlands is not readily
defined, so that defining a TP-chlorophyll a relationship based on water column measurements is
not likely to be useful. However, in some wetlands such as coastal Great Lakes, the loss of
submerged aquatic vegetation biomass and/or diversity with increased eutrophication provides
an ecologically significant endpoint (Lougheed et al., 2001). Reductions in submerged plant
species diversity was associated with increases in turbidity, total P, total N, and chlorophyll a,
suggesting that a trophic state index incorporating multiple parameters might be a better
predictor than a single variable such as total P (Carlson 1977).
Models describing empirical relationships can include linear or nonlinear univariate forms with a
single response metric, multivariate with multiple response metrics, a series of linked
relationships, and simulation models. The simplest forms of linear univariate approaches are
correlation and regression analyses; these approaches have the advantage that they are simple to
perform and transparent to the general public. When assessment thresholds can be determined
based on severity of effect or difference from reference conditions such that associated exposure
criteria can be derived, linear forms should be adequate. In the case of nonlinear relationships,
data can generally be transformed to linearize the relationship. However, if it is desired to
identify the inflection point in a curvilinear relationship as an indicator of rapid ecological
change, alternative data analysis methods are available, including changepoint analysis
(Richardson and Qian 1999) and piecewise iterative regression techniques (Wilkinson 1999).
Multivariate models are useful for relating nutrient exposure metrics to community-level
responses. Both parametric and nonparametric (nonmetric dimensional scaling orNMDS)
ordination procedures can be used to define axes or gradients of variation in community
composition based on relative density, relative abundance, or simple presence-absence measures
(Gauch 1982, Beals 1984, Heikkila 1987, Growns et al., 1992). Ordination scores then can be
regressed against nutrient exposure metrics as an indicator of a composite response (McCormick
et al., 1996). Direct gradient analysis techniques such as canonical correspondence analysis can
be used to determine which combination of nutrient exposure variables predict a combination of
nutrient response variables as a first step in deriving multimetric exposure and response variables
(Cooper et al., 1999). Indicator analysis can be used to determine which subset of species best
discriminate between reference sites with low nutrient loadings versus potentially impacted sites
with high loadings, or weighted averaging techniques can be used to infer nutrient levels from
species composition (McCormick et al., 1996, Cooper et al., 1999, Jensen et al., 1999). In the
latter case, paleoecological records can be examined to infer historic changes in total P levels
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from macrophyte pollen or diatom frustrules, which will be particularly valuable in the absence
of sites representing reference condition (Cooper et al., 1999, Jensen et. al., 1999).
Some ecohydrological models have been derived that incorporate the effect of multiple stressors
(hydrology, eutrophication, acidity) on wetland vegetation, thus providing a link between
process-based models and community level response (see Olde Venterink and Wassen 1997 for
review). These models are based on: 1) a combination of expert opinion to estimate species
sensitivities, supplemented by multivariate classification of vegetation and environmental data to
determine boundaries of species guilds; or, 2) field measurements used to derive logistic models
to quantify dose-response. These approaches could be used to derive wetland nutrient criteria for
the U.S. provided that models could be calibrated using species and response curves developed
using data for the U.S. Most multiple-stressor models for wetland vegetation have been
calibrated using data from Western Europe (Olde Venterink and Wassen 1997). Latour and
colleagues (Latour and Reiling 1993, Latour et al., 1994) have suggested a mechanism for
setting nutrient standards using the occurrence probability of species along a trophic gradient to
extrapolate maximum tolerable concentrations that protect 95% of species.
A series of linked empirical relationships for wetlands may be most effective for developing
nutrient criteria. Linked empirical relationships may be most useful in cases where integrative
exposure measurements such as sediment nutrient concentrations are more sensitive predictors of
shifts in community composition, or algal P limitation, or other ecological responses
(phosphatase enzyme assays; Qian et al., 2003) than are spatially and temporally heterogeneous
water column nutrient concentrations. In these cases, it may be important to develop one set of
relationships between nutrient loading and exposure indicators for a subset of sites at which
intensive monitoring is done, and another set of relationships between nutrient exposure and
ecological response indicators for a larger sample population (Qian et al., 2003).
7.5 PARTITIONING EFFECTS AMONG MULTIPLE STRESSORS
Changes in nutrient concentrations within or loadings to wetlands often co-occur with other
potential stressors such as changes in hydrologic regime and sediment loading. In a few cases,
researchers have been able to separate the simple effects of nutrient addition through
manipulations of mesocosms (Busnardo et al., 1992, Gabor et.al., 1994, Murkin et al., 1994,
McDougal et al., 1997, Hann and Goldsborough 1997), segments of natural systems (Richardson
and Qian 1999, Thormann and Bayley 1997), or whole wetlands (Spieles and Mitsch 2000). In
other cases, both simple and interactive effects have been examined experimentally, e.g., to
separate effects of hydrologic regime from nutrient loading (Neill 1990a, b; Neill 1992, Bayley
et al., 1985). If nutrient effects are examined by comparing condition of natural wetlands along a
loading or concentration gradient, effects of other driving factors can be minimized by making
comparisons among wetlands of similar hydrogeomorphic type and climatic regime within a
well-defined sampling window. In addition, multivariate techniques for partitioning effects
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among multiple factors can be used, such as partial CCA or partial redundancy analysis (Cooper
et al., 1999, Jensen et al., 1999).
7.6 STATISTICAL TECHNIQUES
Quantitative methods can be used to assess metric cost, evaluation, response variability, and
ability to meet data quality objectives. The most appropriate method varies with respect to the
indicator or variable being considered. In general, statistical techniques are aimed at making
conjectures or inferences about a population's values or relationships between variables in a
sample randomly taken from the population of interest. In these terms, population is defined as
all possible values that a certain parameter may take. For example, in the case of total
phosphorus levels present in marsh sediments in nutrient ecoregion VII, the total population
would be determined if all the marshes in that ecoregion were sampled, which would negate the
need for data analysis. Practically, a sample is taken from the population and the characteristics
associated with that sample (mean, standard deviation) are "transferred" to the entire population.
Many of the basic statistical techniques are designed to quantify the reliability of this transferred
estimate by placing a confidence interval over the sample-derived parameter. More complex
forms of data analysis involve comparisons of these parameters from different populations (for
example, comparison between sites) or the establishment of complex data models that are
thought to better describe the original population structure (for example, regression). They are
still basic inference techniques that utilize sample characteristics to make conjectures about the
original population.
A basic and typical issue facing any type of sampling design is the number of samples that
should be taken to be confident in the translation from samples to population. The degree of
confidence required should be defined as data quality objectives by the end-user and identify the
expected statistical rigor for those objectives to be met. There are extensive texts on types and
manners of sampling schemes; these will not be discussed here. This section is geared to
determining the minimum data set recommended to work with subsequent sections of the data
analysis chapter. In interpreting the results of various forms of data analysis, an acceptable level
of statistical error is formulated; this is called Type I error, or alpha (a). Type I error can be
defined as the probability of rejecting the null hypothesis (Ho) when this is actually true. In
setting the Type I error rate, the Type II error rate is also specified. The Type II error rate, or
beta (|3), is defined as failing to reject the null hypothesis when it is actually false, i.e., declaring
that no significant effect exists when in reality this is the case. In setting the Type I error rate, an
acceptable level of risk is recommended; the risk of concluding that a significance exists when
this is not the case in reality, i.e., the risk of a "false positive"(Type I error) or "false negative"
(Type II error). The concepts of Type I and Type II errors are introduced in Chapter 4 with
reference to sampling design and monitoring, and more fully discussed in Chapter 8 with
reference to criteria development.
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In experimental or sampling design, of greater interest is a statistic associated with beta (P),
specifically 1 - P, which is the power of a statistical test. Power is the ability of the statistical test
to indicate significance based on the probability that it will reject a false null hypothesis.
Statistical power depends on the level of acceptable statistical significance (usually expressed as
a probability 0.05 - 0.001 (5% -1%) and termed the a level); the level of power dictates the
probability of "success," or identifying the effect. Statistical power is a function of three factors:
effect size, alpha (a), and sample size, the relationship between the three factors being relatively
complex.
1. Effect size is defined as the actual magnitude of the effect of interest. This could be the
difference between two means or the actual correlation between the variables. The
relationship between the effect size and power is intuitive; if the effect size is large (for
example, a large difference between means) this results in a concomitantly large power.
2. Alpha is related to power; to achieve a higher level of significance, power decreases if
other factors are kept constant.
3. Sample size. Generally, this is the easiest factor to control. If the two preceding factors
are set, increased sample sizes will always result in a greater power.
As indicated before, the relationship between these three factors is complex and depends on the
nature of the intended statistical analysis. An online guide for selecting appropriate statistical
procedures is available at: http://www.socialresearchmethods.net/. Software packages for
performing power analysis have been reviewed by Thomas and Krebs (1997). Online power
calculations have been made available by several statistical faculty and are available at these
Web sites: http://www.math.yorku.ca/SCSA http://calculators.stat.ucla.edu/powercalc/,
http://www.survevsystem.com/sscalc.htm,
http://www.health.ucalgary.ca/~rollin/stats/ssize/index.html, http://www.stat.ohio-
state.edu/~jch/ssinput.html, and http://www.stat.uiowa.edu. Additional Web sites are listed in
Chapter 4 that emphasize designs for monitoring with statistical rigor.
Metric response variability can be evaluated by examining the signal to noise ratio along a
gradient of nutrient concentrations or loading rates (Reddy et.al., 1999). The power of regression
analyses can be determined using the power function for a t-test. Optimization of the design,
such as the spacing, number of levels of observations, and replication at each level, depend on
the purpose of the regression analysis (Neter et.al., 1983).
Multiple correlation analysis can compound uncertainty and in some instances misidentify
correlations due to chance as relevant. Appropriate corrections (e.g., Bonferroni) should be
applied to avoid these errors (Rice 1989).
MULTIMETRIC INDICIES
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Multimetric indices are valuable for summarizing and communicating results of environmental
assessments. Use of multimetric indices is one approach in developing criteria. Furthermore,
preservation of the biotic integrity of algal assemblages, as well as fish and macroinvertebrate
assemblages, may be an objective for establishing nutrient criteria. Multimetric indices for
stream macroinvertebrates and fish are common (e.g., Kerans and Karr 1994, Barbour et.al.,
1999), and multimetric indices with benthic algae have recently been developed and tested on a
relatively limited basis (Kentucky Division of Water 1993; Hill et.al., 2000). Efforts are
underway to develop multi-metric indices of biotic integrity for wetlands, and methods modules
are available for characterizing wetland algal, plant, macroinvertebrate, amphibian, and bird
communities (http://www.epa.gov/waterscience/criteria/wetlands/). Methods for multi-metric
indices are well developed for streams and are readily transferable to wetlands. However, higher
trophic levels do not often directly respond to nutrients and therefore may not be as sensitive to
relatively small changes in nutrient concentrations as algal assemblages. It is recommended that
relations between biotic integrity of algal or vegetation assemblages and nutrients be defined and
then related to biotic integrity of macroinvertebrate and fish assemblages in a stepwise,
mechanistic fashion. The practitioner should realize, however, that wetlands with a history of
high nutrient loadings have often lost the most sensitive species and in these cases higher trophic
level species may prove to be the best indicators of current nutrient loadings and wetland
nutrient condition.
This section provides an overview for developing a multimetric index that will indicate shifts in
primary producers that are associated with trophic status in wetlands. The first step in developing
a multimetric index of trophic status is to select a set of ecological attributes that respond to
human changes in nutrient concentrations or loading. Attributes that respond to an increase in
human disturbance are referred to as metrics. Six to 10 metrics should be selected for the index
based on their sensitivity to human activities that increase nutrient availability (loading and
concentrations), their precision, and their transferability among regions and habitat types.
Selected metrics also should respond to the breadth of biological responses to nutrient conditions
(see discussion of metric properties in McCormick and Cairns 1994).
Effects of nutrients on primary producers and effects of primary producers on the biotic integrity
of macroinvertebrates and fish should be characterized to aid in developing nutrient criteria that
will protect designated uses related to aquatic life (e.g., Miltner and Rankin 1998, King and
Richardson 2002).
Another approach for characterizing biotic integrity of assemblages as a function of trophic
status is to calculate the deviation in species composition or growth forms at assessed sites from
composition in the reference condition. Similarity or dissimilarity indices can be used for the
determining the differences in biotic integrity of a wetland in comparison to the reference
condition. Multivariate similarity or dissimilarity indices need to be calculated for multivariate
attributes such as taxonomic composition (Stevenson 1984; Raschke 1993) as defined by relative
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abundance of different growth forms or species, or species presence/absence. One standard form
of these indices is percent community similarity (PSC, Whittaker 1952):
PSC =Si=i,s min(ai,bi)
Here a; is the percentage of the ith species in sample a, and b; is the percentage of the same ith
species in a subsequent sample, sample b.
A second common community similarity measurement is based on a distance measurement
(which is actually a dissimilarity measurement, rather than similarity measurement, because the
index increases with greater dissimilarity, Stevenson 1984; Pielou 1984). Euclidean distance
(ED) is a standard distance dissimilarity index, where:
Log-transformation of species relative abundances in these calculations can increase precision of
metrics by reducing variability in the most abundant taxa. However, the practitioner should also
be aware that transformation, while reducing variability, often decreases sensitivity and the
ability to distinguish true fine scale changes in community and species composition.
Theoretically and empirically, we expect to find that multivariate attributes based on taxonomic
composition more precisely and sensitively respond to nutrient conditions than do univariate
attributes, for instance multimetric algal assemblages (see discussions in Stevenson and Pan
1999).
To develop the multimetric index, metrics should be selected and their values normalized to a
standard range such that they all increase with trophic status. Criteria for selecting metrics can be
found in McCormick and Cairns (1994) or many other references. Basically, sensitive and
precise metrics should be selected for the multimetric index and selected metrics should
represent a broad range of impacts and, perhaps, designated uses. Values can be normalized to a
standard range using many techniques. For example, if 10 metrics are used and the maximum
value of the multimetric index is defined as 100, all 10 metrics should be normalized to the range
of 10 so that the sum of all metrics would range between 0 and 100. The multimetric index is
calculated as the sum of all metrics measured in a system. A high value of this multimetric index
of trophic status would indicate high impacts of nutrients and should be a robust (certain and
transferable) and moderately sensitive indicator of nutrient impacts in a stream. A 1-3-5 scaling
technique is commonly used with aquatic invertebrates (Barbour et.al., 1999; Karr and Chu
1999) and could be used with a multimetric index of trophic status as well. Using the 95th
percentile when developing metrics is an approach that may decrease the influence of outliers
(Mack 2004).
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7.7 LINKING NUTRIENT AVAILABILITY TO PRIMARY PRODUCER RESPONSE
When evaluating the relationships between nutrients and primary producer response within
wetland systems, it is important to first understand which nutrient is limiting. Once the limiting
nutrient is defined, critical nutrient concentrations can be specified and nutrient-response
relationships developed.
DEFINING THE LIMITING NUTRIENT
The first step in identifying nutrient-producer relationships should be to define the limiting
nutrient. Limiting nutrients will control biomass and productivity within a system. However,
non-limiting nutrients may have other impacts, e.g., toxicological effects related to ammonia
concentrations in sediments or effects on competitive interactions that determine vegetation
community composition (Guesewell et.al., 2003). A review of fertilization studies indicated that
vegetation N:P mass ratios are a good predictor of the nature of nutrient limitation in wetlands,
with N:P ratios > 16 indicating P limitation at a community level, and N:P ratios < 14 indicative
of N limitation (Koerselman and Meuleman 1996). Guesewell et.al., (2003) found that
vegetation N:P ratios were a good predictor of community-level biomass response to fertilization
by N or P, but for individual species were only predictive of P-limitation and could not
distinguish between N-limitation, co-limitation, or no limitation. Likewise, N, P, and K levels in
wet meadow and fen vegetation were found to be correlated with estimated supply rates or
extractable fractions in soils (Odle Venterink et.al., 2002). A survey of literature values of
vegetation and soil total N:P ratios by Bedford et.al., (1999) indicated that many temperate North
American wetlands are either P-limited or co-limited by N and P, especially those with organic
soils. Only marshes have N:P ratios in both soils and plants indicative of N limitation, while soils
data suggest that most swamps are also N-limited.
Many experimental procedures are used to determine which nutrient (N, P, or carbon) limits
algal growth. Algal growth potential (AGP) bioassays are very useful for determining the
limiting nutrient (USEPA 1971). Yet, results from such assays usually agree with what would
have been predicted from N:P biomass ratios, and in some cases N:P ratios in the water. Limiting
nutrient-potential biomass relationships from AGP bottle tests are useful in projecting maximum
potential biomass in standing or slow-moving water bodies. However, they are not as useful in
fast-flowing, and/or gravel or cobble bed environments. Also, the AGP bioassay utilizes a single
species, which may not be representative of the response of the natural species assemblage.
Limitation may be detected by other means, such as alkaline-phosphatase activity, to determine
if phosphorus is limiting. Alkaline phosphatase is an extracellular enzyme excreted by some
algal species and from roots in some macrophytes in response to P limitation. This enzyme
hydrolyzes phosphate ester bonds, releasing orthophosphate (PO4) from organic phosphorus
compounds (Mullholland et.al., 1991). Therefore, the concentration of alkaline phosphatase in
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the water can be used to assess the degree of P limitation. Alkaline phosphatase activity,
monitored over time in a wetland, can be used to assess the influence of P loads on the growth
limitation of algae (Richardson and Qian 1999).
There have been no empirical relationships published relating nutrient concentrations or inputs
to wetland chlorophyll a or productivity levels as there have been for streams and lakes. This is
likely due to the large number of factors interacting with nutrients that determine net ecological
effects in wetlands. For example, eutrophication of Great Lakes coastal wetlands and increases
in agricultural area in upstream watersheds have been correlated with decreases in diversity of
submerged aquatic vegetation, yet researchers were unable to uncouple the effects of nutrients
from those of turbidity (Lougheed et.al., 2001). Even in experimentally controlled settings,
where it is possible to separate increased suspended solids loadings from nutrient loadings,
effects of nutrients depend heavily on other factors such as periodicity of nutrient additions
(pulse vs. press loadings; Gabor et.al., 1994, Murkin et al., 1994, Hann and Goldsborough 1997,
McDougal et.al., 1997), water regime (Neill 1990a, b; Thormann and Bayley 1997), food web
structure (Goldsborough and Robinson 1996), and time lags (Neill 1990a, b). It is important in
experimental settings to utilize adequate controls for water additions that may accompany
nutrients (Bayley et.al., 1985); in empirical comparisons from field data, it may be difficult if not
impossible to separate out these effects. Day et.al., (1988) propose a general conceptual model
describing responses of different wetland plant guilds in riverine wetlands based on a
combination of disturbance regime, hydrologic regime, and nutrients. In the latter case, proper
classification of sites based on disturbance and hydrologic regime prior to describing reference
condition help to adequately separate out nutrient-related effects and explain differences in
response.
The significance of food web structure in determining nutrient effects does not preclude deriving
predictive nutrient-primary producer relationships or minimize the importance of describing
significant impacts. However, it does highlight the importance of adequately characterizing the
trophic structure of wetlands prior to comparison, especially the number of trophic levels (e.g.,
presence or absence of planktivorous fish), and examining interactive effects on multiple classes
of primary producers: phytoplankton, epipelon, epiphytic algae, metaphyton, and macrophytes
(Goldsborough and Robinson 1996, McDougal et al., 1997). In some cases, addition of nutrients
may have little or no effect on some components such as benthic algae, but can create significant
shifts in primary productivity among others, such as a loss of macrophytes and associated
epiphytes with an increase in inedible filamentous metaphyton and shading of the water column
(McDougal et al., 1997).
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Chapter 8 Criteria Development
8.1 INTRODUCTION
This chapter describes recommendations for setting scientifically defensible criteria for nutrients
in wetlands by using data that address causal and biotic response variables. Causal variables
(external nutrient loading, soil extractable P, soil extractable N, total soil N and P, and water
column N and P), and biotic response variables (vegetation N and P, biomass, species
composition, and algal N and P) and the supporting variables (hydrologic condition,
conductivity, soil pH, soil bulk density, particle size distribution, and soil organic matter), as
described in Chapter 5 provide an overview of environmental conditions and nutrient status of
the wetland; these parameters are considered critical to nutrient assessment in wetlands. Several
recommended approaches that water quality managers can use to derive numeric criteria in
combination with other biological response variables are presented. These recommended
approaches can be used alone, in combination, or may be modified for use by State water quality
managers to derive criteria for wetlands that are scientifically defensible and protective of the
designated use. Criteria developed from multiple lines of evidence using combined approaches
will provide the greatest scientific defensibility. Recommended approaches for numeric nutrient
criteria development presented here include:
• the use of reference conditions to characterize natural or minimally impaired wetland
systems with respect to causal and exposure indicator variables;
• applying predictive relationships to select nutrient concentrations that will protect
wetland structure and/or function; and,
• developing criteria from established nutrient exposure-response relationships (as in the
peer-reviewed published literature).
The first approach is based on the assumption that maintaining nutrient levels within the range of
values measured for reference systems will maintain the biological integrity of wetlands. This
presumes that a sufficient number of reference systems can be identified. The second two
approaches are response-based; hence, the level of nutrients associated with biological
impairment should be used to identify criteria. Ideally, both kinds of information (background
variability and exposure-response relationships) will be available for criteria development.
Recommendations are also presented for deriving criteria based on the potential for effects to
downstream receiving waters (i.e., the lake, reservoir, stream, or estuary influenced by
wetlands). States should consider relating these measures to metrics of ecological integrity and
periodically assessing measures to verify assumptions made in criteria development. The chapter
concludes with a recommended process for evaluating proposed criteria, suggestions of how to
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SEPTEMBER 2007 Chapter 8. Criteria Development
interpret and apply criteria, considerations for sampling for comparison to criteria, potential
modifications to established criteria, and adoption of criteria into water quality standards.
The RTAG is composed of State and Regional specialists who will help the Agency and States
establish nutrient criteria for adoption into their water quality standards. Expert evaluations are
important throughout the criteria development process. The data upon which criteria are based
and the analyses performed to arrive at criteria should be assessed for veracity and applicability.
8.2 METHODS FOR DEVELOPING NUTRIENT CRITERIA
The following discussions focus on three general methods that can be used in developing
nutrient criteria. First, identification of reference or control systems for each established wetland
type and class should be based on either best professional judgment (BPJ) or percentile
selections of data plotted as frequency distributions. The second method uses refinement of
classification systems, models, and/or examination of system biological attributes to assess the
relationships among nutrients, vegetation or algae, soil, and other variables. Finally, the third
method identifies published nutrient and vegetation, algal, and soil relationships and values that
may be used (or modified for use) as criteria. A weight of evidence approach with multiple
attributes that combines one or more of these three approaches should produce criteria of
greater scientific validity.
USING REFERENCE CONDITION TO ESTABLISH CRITERIA
One approach to consider in setting criteria is the concept of reference condition. This approach
involves using relatively undisturbed wetlands as reference systems to serve as examples for the
natural or least disturbed ecological conditions of a region. These approaches are most useful for
estimating reference conditions appropriate to the specific designated use for a class of wetlands.
Three recommended ways of using reference condition to establish criteria are:
1. Characterize reference systems for each class within a region using best professional
judgment and use these reference conditions to define criteria.
2. Identify the 75th to 95th percentile of the frequency distribution for a class of reference
wetlands as defined in Chapter 3 and use this percentile to define the criteria.
3. Calculate a 5th to 25th percentile of the frequency distribution of the general population of
a class of wetlands and use the selected percentile to define the criteria.
Defining the nutrient condition of wetlands within classes will allow the manager to identify
protective criteria and determine which systems may benefit from management action. Criteria
that are identified using reference condition approaches may require comparisons to similar
systems in other States that share the ecoregion so that reference condition and developed
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SEPTEMBER 2007 Chapter 8. Criteria Development
criteria can be validated. Furthermore, the 95th percentile of the reference population and the 5th
percentile of the general population are best used to define the criteria when there is great
confidence that the group of reference waters truly reflects reference conditions as opposed, for
example, to best available condition.
Reference wetlands should be identified for each class of wetland within a State or ecoregion
and then characterized with respect to external nutrient loading, water column N and P, biotic
response variables (macrophytes, algae, soils) and supporting environmental conditions.
Wetlands classified as reference quality should be verified by comparing the data from the
reference systems to general population data for each wetland class. Reference systems should
be minimally disturbed and should have biotic response values that reflect this condition.
Conditions at reference sites may be characterized using either of two frequency distribution
approaches (see 2 and 3 above). In both approaches, an optimal reference condition value is
selected from the distribution of an available set of wetland data for a given wetland class. This
approach may be of limited value at this time because few States currently collect wetland
monitoring data. However, as more wetlands are monitored and more data become available, this
approach may become more viable.
In the first frequency distribution approach, a percentile (75th - 95th is recommended) is selected
from the distribution of causal and biotic response variables of reference systems selected a
priori based on very specific criteria (i.e., highest quality or least impacted wetlands for that
wetland class within a region). The values for variables at the selected quartile may be used as
the basis for nutrient criteria. The selection of a specific percentile as the basis for the criterion
should be determined by the uses designated for that water.
If reference wetlands of a given class are rare within a given region or if inadequate information
is available to assign wetlands with historic nutrient data as "reference" versus "impacted"
wetlands, another approach may be appropriate. The second frequency distribution approach
involves selecting a percentile of: (1) all wetland data in the class (reference and non-reference);
or, (2) a random sample distribution of all wetland data within a particular class. Due to the
random selection process, a lower percentile should be selected because the sample distribution
is expected to contain some degraded systems. This option is most useful in regions where the
number of legitimate "natural" reference wetlands is usually very small, such as in highly
developed land use areas (e.g., the agricultural lands of the Midwest and the urbanized east or
west coasts). EPA's recommendation in this case is the 5th to 25th percentile depending upon the
number of "natural" reference systems available. If almost all systems are impaired to some
extent, then a lower percentile, generally the 5th percentile, is recommended for selection of
reference wetlands.
Both the 75th percentile for the subset of reference systems and the 5th to 25th percentile from a
representative random sample distribution are only recommendations. The actual distribution of
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Chapter 8. Criteria Development
the observations should be the major determinant of the threshold point chosen. For example, a
bi-modal distribution of sediment or water-column nutrients might indicate a natural breakpoint
between reference and enriched systems. To illustrate, Figure 8.1 shows both options and
illustrates the presumption that these two alternative methods should approach a common
reference condition along a continuum of data points. In this illustration, the 75th percentile of
the reference data distribution produces an extractable soil P reference condition that
corresponds to the 25th percentile of the random sample distribution.
75th percentile of
reference population is
the starting point for
Concentration
o
£
LU
.a
ro
Effects thresholds
can help justify
criterion value.
Concentration
Nutrient data from reference waters (blue) or
from all waters (gold) similar physical
characteristics.
Paired nutrient and effects data from waters
with similar physical characteristics.
Figure 8.1 Use of frequency distributions of nutrient concentration for establishing criteria (left
graphic), and use of effects thresholds with nutrient concentration for establishing criteria (right
graphic).
The choice of a distribution cut-off to define the upper range of reference wetland nutrient levels
is analogous to defining an acceptable level of Type I error, the frequency for rejecting wetlands
as members of the "unimpacted" class when in fact they are part of the reference wetland
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SEPTEMBER 2007 Chapter 8. Criteria Development
population (a false designation of impairment). If a distribution cut-off of 25% is chosen, the rate
of falsely designating wetlands as impaired will be higher than if a distribution cutoff of 5% is
chosen; however, the frequency of committing Type II errors (failing to identify
anthropogenically-enriched wetlands) will be lower. As described in Chapter 7, there is a trade-
off between Type I and Type II errors. When additional information is available, it may be
possible to justify a range of values that are representative of least-impaired wetlands that would
reduce Type I errors on a system by system basis.
State water quality managers also may consider analyzing wetlands data based on designated use
classifications. Using this approach, frequency distributions for specific designated uses, as
opposed to frequency distributions of reference or general populations, could be examined and
criteria proposed based on maintenance of high quality systems that are representative of each
designated use. For example, one criterion could be derived that protects superior quality
wetland habitat (SWLH), and a second criterion could be identified that maintains good quality
wetland habitat (function maintained but some loss of sensitive species (Figure 8.2); see Office
of Water tiered aquatic life use training module:
(http://www.epa.gov/waterscience/biocriteria/modules/wetl01-05-alus-monitoring.pdf). This
recommended approach is designated as the Tiered Aquatic Life Use (TALU) and is being
developed by the EPA Office of Water in a more detailed publication. Using this approach, a
criterion range is created and a greater number of wetland systems will likely be considered
protective of the designated use. In this case, emphasis may be shifted from managing wetland
systems based on a central tendency,toward more pristine systems associated with Tiers I and II.
This approach also will aid in prioritizing systems for protection and restoration. Subsequent
management efforts using this approach should focus on improving wetland conditions so that,
over time, plots of wetland data shift to the left (i.e., improved nutrient condition) of their initial
position.
p.p
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SEPTEMBER 2007
Chapter 8. Criteria Development
Native or natural condition
1
MAINE TALU
Minimal loss of species; some
Natural
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SEPTEMBER 2007
Chapter 8. Criteria Development
[http://www.wetlandbiogeochetnistry.lsu.edu/] and also in interagency efforts through the Los
Angeles Department of Natural Resources) to assess coastal area ecology.
rhttp://data. 1 ca. gov/Ivan6/app/app c ch9.pdfl
Multimetric indices are a special form of indicators of biological condition in which several
metrics are used to summarize and communicate in a single number the state of a complex
ecological system. Multimetric indices for macroinvertebrates and fish are used successfully to
establish biocriteria for aquatic systems in many States, and several States are developing
multimetric indices for wetlands (see http://www.epa.gov/owow Web site).
Another recommended approach is to identify threshold or non-linear biotic responses to nutrient
enrichment. Some biological attributes respond linearly with increasing nutrient concentrations,
whereas some attributes change in a non-linear manner. Non-linear changes in metrics indicate
thresholds along environmental gradients where small changes in environmental conditions
cause relatively great changes in a biological attribute. In an example from the Everglades, a
specific level of P concentration and loadings was associated with a dramatic shift in algal
composition and loss of the calcareous algal mats typical of this system (Figure 8.3). Overall,
metrics or indices that change linearly (typically higher-level community attributes such as
diversity or a multimetric index) provide better variables for establishing biocriteria because they
respond to environmental change along the entire gradient of human disturbance. However,
metrics that change in a non-linear manner along environmental gradients are valuable for
determining where along the environmental gradient the physical and chemical criteria should be
set and, correspondingly, how to interpret other biotic response variables of interest (Stevenson
et.al., 2004a).
fc
6
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. f*i
0?
90
SO
70
60
50
40
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20
10
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. . • * t * * * .
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.* * *
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^ * •
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6 8 10 12 14
Distance from Point Source (km)
no
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SEPTEMBER 2007 Chapter 8. Criteria Development
Figure 8.3. Percent calcareous algal mat cover in relation to distance from the P source showing
the loss of the calcareous algal mat in those sites closer to the source (Stevenson et.al., 2002).
USING DATA PUBLISHED IN THE LITERATURE
Values from the published literature may be used to develop nutrient criteria if a strong rationale
is presented that demonstrates the suitability of these data to the wetland of interest (i.e., the
system of interest should share the same characteristics with the systems used to derive the
published values). Published data, if there is enough of it, could be used to develop criteria for:
(1) reference condition; (2) predictive (cause and effect) relationships between nutrients and
biotic response variables; (3) tiered criteria; or, (4) criteria that exhibit a threshold response to
nutrients. However, published data from similar wetlands should not substitute for collection and
analysis of data from the wetland or wetlands of interest.
CONSIDERATIONS FOR DOWNSTREAM RECEIVING WATERS
More stringent nutrient criteria may be appropriate for wetlands that drain into lentic or standing
waters. For example, it is proposed that 35 ug/L TP concentration and a mean concentration of 8
ug/L chlorophyll a constitute the dividing line between eutrophic and mesotrophic lakes (OECD
1982). Natural nutrient concentrations in some wetlands may be higher than downstream lakes.
In addition, assimilative capacity for nutrients without changes in valued attributes may also be
higher in wetlands than lakes. Nutrient criteria for wetlands draining into lakes may need to be
lower than typically would be set if only effects on wetlands were considered. This is because
EPA's regulations require States to take into consideration the water quality standards of
downstream waters when designating uses of a water body and adopting appropriate criteria to
protect those uses. (See 40 CFR 131.10(b).) Therefore, when adopting nutrient criteria for
wetlands draining into lakes, States should take into account the protection of the downstream
waters of receiving lakes in addition to wetlands.
8.3 EVALUATION OF PROPOSED CRITERIA
Following criteria derivation, an expert assessment of the proposed criteria and their
applicability to all wetlands within the class of interest is encouraged. Criteria should be verified
in many cases by comparing criteria values for a wetland class within an ecoregion across State
boundaries. In fact, development of interstate criteria should be an integral part of a State's water
quality standards program. In addition, prior to recommending any proposed criterion, it is
recommended that States take into consideration the water quality standards of downstream
waters to ensure that their water quality standards provide for attainment and maintenance of the
water quality standards of downstream waters, (see 40 CFR 131.10(b)). Load estimating models,
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SEPTEMBER 2007 Chapter 8. Criteria Development
such as those recommended by EPA (USEPA 1999), can assist in this determination (see
External Nutrient Loading in Chapter 5.3). Water quality managers responsible for downstream
receiving waters also should be consulted.
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SEPTEMBER 2007 REFERENCES
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Hydrocomp, Inc. 1977. Hydrocomp Water Quality Operations Manual. Palo Alto, CA:
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Manguerra, H. B. and B. A. Engel. 1998. Hydrologic parameterization of watershed for runoff
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SEPTEMBER 2007 APPENDIX A: ACRONYM LIST AND GLOSSARY
APPENDIX A. ACRONYM LIST AND GLOSSARY
ACRONYMS
ACOE/ACE/COE - Army Corps of Engineers
AGNPS - Agricultural Nonpoint Source Pollution model
ARS - Agricultural Research Service
BACI - Before/After, Control/Impact
BMP - Best Management Practice
BuRec - Bureau of Reclamation
CCC - Commodity Credit Corporation
CENR - Committee for the Environment and Natural Resources
CGP - Construction General Permit
CHN - Carbon-Hydrogen-Nitrogen
CPGL - Conservation of Private Grazing Land
CPP - Continuing Planning Process
CREP - Conservation Reserve Enhancement Program
CRP - Conservation Reserve Program
CSO - Combined Sewer Overflow
CWA-Clean Water Act
CZARA - Coastal Zone Act Reauthorization Amendment
DIP - Dissolved inorganic phosphorus
DO - Dissolved oxygen
DOP - Dissolved organic phosphorus
DRP - Dissolved reactive phosphorus
ECARP - Environmental Conservation Acreage Reserve Program
ED AS - Ecological Data Application System
Eh - Redox potential
EMAP - Environmental Monitoring and Assessment Program
EQIP - Environmental Quality Incentive Program
FDEP - Florida Department of Environmental Protection
FIP - Forestry Incentive Program
GIS - Geographic Information System
GPS - Geospatial Positioning System
GWLF - Generalized Watershed Loading Function
HEL - Highly credible land
HGM - Hydrogeomorphic approach
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SEPTEMBER 2007 APPENDIX A: ACRONYM LIST AND GLOSSARY
HSPF - Hydrologic Simulation Program - Fortran
MPCA - Minnesota Pollution Control Agency
NAAQS - National Ambient Air Quality Standard
NASQAN - National Stream Quality Assessment Network
NAWQA - National Water Quality Assessment
NIS - Network Information System
NIST - National Institute of Standards and Technology
NOAA - National Oceanic and Atmospheric Administration
NPDES - National Pollution Discharge Elimination System
NPP - Net primary production
NRCS - Natural Resources Conservation Service
NSF - National Science Foundation
NWI - National Wetlands Inventory
OH EPA - Ohio EPA
ONRW - Outstanding Natural Resource Waters
PCB - Polychlorinated biphenyls
PCS - Permit Compliance System
PIP - Paniculate inorganic phosphorus
POP - Paniculate organic phosphorus
PSA - Particle size analysis
QA/QC - Quality Assurance/Quality Control
QC - Quality Control
REMAP - Regional Environmental Monitoring and Assessment Program
RF3 - Reach File 3
SCS - Soil Conservation Service
SPARROW - Spatially Referenced Regressions on Watersheds
SRP - Soluble reactive phosphorus
STORET - Storage and Retrieval System
SWAT - Soil and Water Assessment Tool
TKN - Total Kjeldahl Nitrogen
TMDL - Total Maximum Daily Load
TP - Total Phosphorus
TWINSPAN -
USD A - United States Department of Agriculture
USEPA - United States Environmental Protection Agency
USFWS - United States Fish and Wildlife Service
USGS - United States Geological Survey
WEBB - Water, Energy, and Biogeochemical Budgets
WHIP - Wildlife Habitat Incentive Program
WLA - Wasteload Allocation
WQBEL - Water Quality Based Effluent Limit
WQS - Water Quality Standard
WRP - Wetlands Reserve Program
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SEPTEMBER 2007 APPENDIX A: ACRONYM LIST AND GLOSSARY
GLOSSARY
biocriteria
(biological criteria) Narrative or numeric expressions that describe the desired biological condition of aquatic
communities inhabiting particular types of waterbodies and serve as an index of aquatic community health. (USEPA
1994).
cluster analysis
An exploratory multivariate statistical technique that groups similar entities in an hierarchical structure.
criteria
Elements of State water quality standards, expressed as constituent concentrations, levels, or narrative statements,
representing a quality of water that supports a particular use. When criteria are met, water quality will generally
protect the designated use (40 CFR 131.3(b)).
designated use(s)
Uses defined in water quality standards for each waterbody or segment whether or not the use is being attained
(USEPA 1994).
detritus
Unconsolidated sediments comprised of both inorganic and dead and decaying paniculate organic matter inhabited
by decomposer microorganisms (Wetzel 1983).
ecological unit
Mapped units that are delineated based on similarity in climate, landform, geomorphology, geology, soils,
hydrology, potential vegetation, and water.
eco region
A region defined by similarity of climate, landform, soil, potential natural vegetation, hydrology, and other
ecologically relevant variables.
emergent vegetation
"Erect, rooted herbaceous angiosperms that may be temporarily to permanently flooded at the base but do not
tolerate prolonged inundation of the entire plant; e.g., bulrushes (Scirpus spp.), saltmarsh cordgrass" (Cowardin
etal., 1979).
eutrophic
Abundant in nutrients and having high rates of productivity frequently resulting in oxygen depletion below the
surface layer (Wetzel 1983).
eutrophication
The increase of nutrients in [waterbodies] either naturally or artificially by pollution (Goldman and Home 1983).
GIS (Geographical Information Systems)
A computerized information system that can input, store, manipulate, analyze, and display geographically
referenced data to support decision-making processes. (NDWP Water Words Dictionary)
HGM, hydrogeomorphic
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SEPTEMBER 2007 APPENDIX A: ACRONYM LIST AND GLOSSARY
Land form characterized by a specific origin, geomorphic setting, water source, and hydrodynamic (ND WP Water
Words Dictionary)
index of biotic integrity (IBI)
An integrative expression of the biological condition that is composed of multiple metrics. Similar to economic
indexes used for expressing the condition of the economy.
interfluve
An area of relatively unchannelized upland between adjacent streams flowing in approximately the same direction.
lacustrine
"Includes wetlands and deepwater habitats with all of the following characteristics: (1)
situated in a topographic depression or a dammed river channel; (2) lacking trees, persistent emergents, emergent
mosses or lichens with greater than 30% areal coverage; and, (3) total area exceeds 8 ha (20 acres). Similar wetland
and deepwater habitats totaling less than 8 ha are also included in the Lacustrine System if an active wave-formed
or bedrock shoreline feature makes up all or part of the boundary, or if the water depth in the deepest part of the
basin exceeds 2 m (6.6 feet) at low water...may be tidal or nontidal, but ocean-derived salinity is always less than
0.5%" (Cowardinet.al., 1979).
lentic
Relatively still-water environment (Goldman and Home 1983).
limnetic
The open water of a body of fresh water.
littoral
Region along the shore of a non-flowing body of water.
lotic
Running-water environment (Goldman and Home 1983).
Macrophyte
(Also known as S AV-Submerged Aquatic Vegetation) Larger aquatic plants, as distinct from the microscopic
plants, including aquatic mosses, liverworts, angiosperms, ferns, and larger algae as well as vascular plants; no
precise taxonomic meaning (Goldman and Home 1983).
micrograms per liter, 10"6 grams per liter
mg/L
milligrams per liter, 10"3 grams per liter
mineral soil flats
Level wetland landform with predominantly mineral soils
minerotrophic
Receiving water inputs from groundwater, and thus higher in salt content (major ions) and pH than ombrotrophic
systems.
mixohaline
Water with salinity of 0.5 to 30%, due to ocean salts.
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M
Molarity, moles of an element as concentration
multivariate
Type of statistics that relates one or more independent (explanatory) variables with multiple dependent (response)
variables.
nutrient ecoregion
Level II ecoregions defined by Omernik according to expected similarity in attributes affecting nutrient supply (
http ://www. epa. gov/OST/standards/ecomap. html).
oligotrophic
Trophic status of a waterbody characterized by a small supply of nutrients (low nutrient release from sediments),
low production of organic matter, low rates of decomposition, oxidizing hypolimnetic condition (high DO) (Wetzel
1983).
palustrine
"Nontidal wetlands dominated by trees, shrubs, persistent emergents, emergent mosses orlichens, and all such
wetlands that occur in tidal areas where salinity due to ocean-derived salts is below 0.5%. It also includes wetlands
lacking such vegetation, but with all of the following four characteristics: (1) area less than 8 ha (20 acres); (2)
active wave-formed or bedrock shoreline features lacking; (3) water depth in the deepest part of basin less than 2 m
at low water; and, (4) salinity due to ocean-derived salts less than 0.5%" (Cowardin etal., 1979).
peatland
"A type of wetland in which organic matter is produced faster than it is decomposed, resulting in the accumulation
of partially decomposed vegetative material called Peat. In some mires peat never accumulates to the point where
plants lose contact with water moving through mineral soil. Such mires, dominated by grasslike sedges, are called
Fens. In other mires peat becomes so thick that the surface vegetation is insulated from mineral soil. These plants
depend on precipitation for both water and nutrients. Such mires, dominated by acid forming sphagnum moss, are
called Bogs." (NDWP Water Words Dictionary)
periphyton
Associated aquatic organisms attached or clinging to stems and leaves of rooted plants or other surfaces projecting
above the bottom of a waterbody (USEPA 1994).
pocosin
Evergreen shrub bog, found on Atlantic coastal plain.
riverine wetland
A hydrogeomorphic class of wetlands found in floodplains and riparian zones associated with stream or river
channels.
slope wetland
A wetland typically formed at a break in slope where groundwater discharges to the surface. Typically there is no
standing water.
trophic status
Degree of nutrient enrichment of a waterbody.
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SEPTEMBER 2007 APPENDIX A: ACRONYM LIST AND GLOSSARY
waters of the U.S.
Waters of the United States is defined at 40 CFR § 230.3(s)) as including:
a. All waters that are currently used, were used in the past, or may be susceptible to use in interstate or foreign
commerce, including all waters that are subject to the ebb and flow of the tide;
b. All interstate waters, including interstate wetlands; and,
c. All other waters such as interstate lakes, rivers, streams (including intermittent streams), mudflats, sandflats,
wetlands, sloughs, prairie potholes, wet meadows, playa lakes, or natural ponds the use, degradation, or destruction
of which would affect or could affect interstate or foreign commerce including any such waters:
1 That are or could be used by interstate or foreign travelers for recreational or other purposes;
2 From which fish or shellfish are or could be taken and sold in interstate or foreign
commerce; or,
3 That are used or could be used for industrial purposes by industries in interstate
commerce;
d. All impoundments of waters otherwise defined as waters of the United States under this definition;
e. Tributaries of waters identified in paragraphs (a) through (d) of this definition;
f. The territorial sea; and,
g. Wetlands adjacent to waters (other than waters that are themselves wetlands) identified in paragraphs (a) through
(f) of this definition.
For further information regarding the scope of 'waters of the U.S.' in light of the U.S. Supreme Court's 2006
decision in Rapanos v. United States, see "Clean Water Act Jurisdiction Following the U.S. Supreme Court's
Decision in Rapanos v. United States & Carabell v. United States," which was jointly issued by the U. S.
Environmental Protection Agency and the Army Corps of Engineers and is available at:
http ://www. epa. gov/o wow/wetlands/.
wetland(s)
Those areas that are inundated or saturated by surface or groundwater at a frequency and duration sufficient to
support, and that under normal circumstances do support, a prevalence of vegetation typically adapted for life in
saturated soil conditions [EPA, 40 CFR§ 230.3 (t)/USACE,33 CFR § 328.3 (b)].
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SEPTEMBER 2007 APPENDIX B: CASE STUDIES
APPENDIX B. CASE STUDY: DERIVING A PHOSPHORUS CRITERION FOR THE
FLORIDA EVERGLADES
INTRODUCTION
The Everglades (Figure B 1.1) is the largest subtropical wetland in North America and is widely
recognized for its unique ecological character. It has been affected for more than a century by
rapid population growth in south Florida. Roughly half of the ecosystem has been drained and
converted to agricultural and urban uses. Among other changes, the conversion of 500,000 acres
of the northern Everglades to agriculture (the Everglades Agricultural Area or EAA) and the
subsequent diking of the southern rim of Lake Okeechobee eliminated the normal seasonal flow
of water southward from Lake Okeechobee. Furthermore, the construction of a complex network
of internal canals and levees disrupted the natural sheetflow of water through the system and
created a series of impounded wetlands known as "Water Conservation Areas" or WCAs. This
conversion from a hydrologically open to a highly managed wetland occurred gradually,
beginning with the excavation of four major canals during the 1900-1910 period and culminating
with the construction of the Central and South Florida Flood Control Project (CSFFCP) during
the 1950s and 60s (Light and Dineen 1994).
The remnant Everglades is managed for multiple and often conflicting uses including water
supply, flood control, and the hydrologic needs of the natural ecosystem. Water management
operations have altered the quantity, quality, timing, and delivery of flows to the Everglades
relative to the pre-disturbance system; some parts of the system have been damaged by
overdrainage, excessive flooding in other areas has stressed native vegetation communities.
Changes to the seasonal pattern of flooding and drying have influenced many ecological
processes, including changes in the dominant micro- and macro-phytic vegetation, declines in
critical species, and the nesting success of wading bird populations that rely on drawdowns
during a narrow window of time to concentrate fish prey. Canal inputs containing runoff from
agricultural and urban lands contribute roughly 50% of flows to the managed system and have
increased loads of nutrients and contaminants. In particular, phosphorus (P) has been identified
as a key limiting nutrient in the Everglades and increased inputs of this nutrient have been
identified as a significant factor affecting ecological processes and communities.
The primary source of P to the pre-disturbance Everglades was rainfall, although seasonal flows
from Lake Okeechobee likely contributed significant P to the northern fringe of the wetland.
Prior to the implementation of P control efforts in the late 1990s, canal flows were estimated to
contribute more than half of the P load to the managed Everglades (SFWMD 1992). Discharge
from the EAA is the main source of water to the Everglades, with approximately 500,000 acres
of farmland draining southward via SFWMD canals, and is the major source of anthropogenic P.
Significant inputs also come from Lake Okeechobee, a naturally mesotrophic lake that has also
been enriched by agricultural runoff. Several other agricultural and urban catchments contribute
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SEPTEMBER 2007
APPENDIX B: CASE STUDIES
Appendix Bl. Figure Bl.l. Major hydrologic units of the remnant Florida
Everglades (shaded region) including (from north to south) the A.R.M.
Loxahacthee National Wildlife Refuge (LNWR), Water Conservation Area
(WCA) 2A, WCA 3 A, and Everglades National Park. Shaded lines represent the
regional canal and levee system that conveys water southward from Lake
Okeechobee and the Everglades Agricultural Area to the Everglades and urban
areas along the coast.
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SEPTEMBER 2007 APPENDIX B: CASE STUDIES
smaller amounts of P via canal discharges into various parts of the Everglades. However, in
general, canal P concentrations and loads (and associated wetland concentrations) decline from
north to south.
The history of P enrichment and associated ecological impacts is not well documented but
probably occurred at a limited scale for much of the last century. Early reports by the South
Florida Water Management District (e.g., Gleason et.al., 1975, Swift and Nicholas 1987) showed
an expansion of cattail and changes in the periphyton community in portions of the northern
Everglades receiving EAA runoff. The severity and extent of P impacts were more fully
recognized by 1988 when the Federal Government sued the State of Florida for allowing P-
enriched discharges and associated impacts to occur in the Everglades. Settlement of this lawsuit
eventually resulted in the enactment of the Everglades Forever Act by the Florida Legislature in
1994, which required the Florida Department of Environmental Protection (FDEP) to derive a
numeric water quality criterion for P that would "prevent ecological imbalances in natural
populations of flora or fauna" in the Everglades. These legal and legislative events provided the
basis for numerous research and monitoring efforts designed to better understand the effects of P
enrichment and to determine levels of enrichment that produced undesirable ecosystem changes.
Research and monitoring were initiated by the State of Florida (the Florida Department of
Environmental Protection and the South Florida Water Management District) and other
university research groups (e.g., Duke University, Florida International University, University of
Florida) to better understand ecological responses to anthropogenic P inputs and to identify a P
concentration or range of concentrations that result in unacceptable degradation of the
Everglades ecosystem. This case study reviews research and monitoring conducted by the State
to derive a P criterion for the Everglades. This criterion was proposed by the FDEP in 2001 and
approved in 2003. This process is divided into three parts:
1. Define the reference (i.e., historical) conditions for P and the oligotrophic ecology of the
Everglades;
2. Determine the types of ecological impacts caused by P enrichment; and,
3. Identify wetland P concentrations that produce these impacts,and determine a
criterion that will protect the resource from those impacts.
DEFINING THE REFERENCE CONDITION
Several sources of information were used to characterize reference conditions across the
Everglades. Sampling in minimally impacted locations (i.e., reference sites) believed to best
reflect historical conditions provided the quantitative basis for establishing reference conditions
with respect to P concentrations and associated ecological conditions. Where possible, this
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SEPTEMBER 2007 APPENDIX B: CASE STUDIES
characterization was augmented by historical evidence. Written accounts of surveys conducted
during the 1800s and early 1900s provided useful qualitative data on past ecological conditions.
Early scientific literature contained substantial information on large-scale vegetation patterns
(e.g., Davis 1943, Loveless 1959). Paleoecological assessments, including the dating and
analysis of soil cores with respect to nutrient content and preserved materials such as pollen
provided, further information (e.g., Cooper and Goman 2001, Willard et.al., 2001).
Predisturbance Everglades exhibited significant spatial and temporal variation, and, while its
conversion to a smaller, more managed wetland resulted in the loss of some of this
heterogeneity, the legacy of past variations in hydrology, chemistry, and biology remain in many
areas. Legislation mandating the development of a P criterion stipulated that natural variation in
P concentrations and ecological conditions within the remnant ecosystem be considered. This
required that sampling efforts encompass the expected range of background variability in the
remnant ecosystem. To ensure that spatial variation in P conditions were considered, sampling
was conducted in all four major hydrologic units: The Loxahatchee National Wildlife Refuge
(LNWR), WCA-2A, WCA-3A, and Everglades National Park (see Figure Bl.l).
Water Column Phosphorus
Nutrient inputs to the Everglades were historically derived primarily from atmospheric
deposition (rainfall and dry fallout), which is typically low in P. Historical loading rates have
been estimated from annual atmospheric P inputs in south Florida and reconstructions of P
accumulation in Everglades soils and probably averaged less than 0.1 g P m^y"1 (SFWMD
1992). Atmospheric inputs of P were augmented by inflows from Lake Okeechobee, which was
connected by surface-water flows to the northern Everglades during periods of high water
(Parker et.al., 1955). While inflows from this historically eutrophic lake were undoubtedly
enriched in P compared with the Everglades, the influence of these inputs were likely limited to
wetlands along the lake's southern fringe (Snyder and Davidson 1994) as is demonstrated by the
limited extent of pond apple and other vegetation that require more nutrients for growth than the
sawgrass (Cladium jamaicense) that dominates most of the Everglades.
Interior areas of the Everglades generally retain the oligotrophic characteristics of the
predrainage ecosystem and, thus, provide the best contemporary information on historical P
concentrations. Water chemistry data were available for several interior locations that had been
sampled by the State for many years. Median water-column TP concentrations at these stations
ranged between 4 and 10 jig L"1, with lowest concentrations occurring in southern areas that
have been least affected by anthropogenic P loads (Figure B1.2). Phosphorus concentrations >10
jig L"1 were measured periodically at many of these sites. Isolated high P concentrations at
reference stations were attributed to P released as a result of oxidation of exposed soils,
increased fire frequency during droughts, and difficulties in collecting water samples that are not
contaminated by flocculent wetland sediments when water depths are low. Data from reference
sites may represent an upper estimate of historical TP concentrations in the Everglades since
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SEPTEMBER 2007 APPENDIX B: CASE STUDIES
several stations are located in areas that either have been overdrained, a condition which
promotes soil oxidation and P release, or so heavily exposed to canal inflows (e.g., WCA 2A)
that some P inputs have likely intruded even into interior areas. However, in the absence of
reliable historical data these values were deemed as best available for defining reference
condition.
Soil Phosphorus
Extensive soil mapping projects across interior portions of the central and northern Everglades
indicate a reference range for soil TP in the surface 0-10 cm of soil of between 200 and 500 mg
kg"1 on a mass basis (DeBusk et.al., 1994, Reddy et.al., 1994a, Newman et.al., 1997, Richardson
et.al., 1997a, Newman et.al., 1998). Fewer data are available from ENP, but available evidence
indicates background concentrations of < 400 mg kg"1 (Doren et.al., 1997). Soil P content also
varies volumetrically as a function of changing soil bulk density. The typical bulk density of
flooded Everglades peat soils is approximately 0.08 g cm"3, whereas soils that have been
subjected to extended dry out and oxidation can have bulk densities greater than 0.2 g cm"3
(Newman et.al., 1998). Increases in volumetric nutrient concentrations resulting from increased
bulk density can have a stimulatory effect on plant growth even in the absence of external P
inputs (see Chapter 2). Following correction for the varying bulk densities in the peat soils of
the Everglades, a historical TP concentration of <40 jig cm"3 may be applicable for most regions
(DeBusk et.al., 1994, Reddy et.al., 1994a, Newman et.al., 1997, Newman et.al., 1998, Reddy
et.al., 1998). In the LNWR, most of the interior area has soil TP < 20 jig TP cm"3 (Newman
et.al., 1997).
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APPENDIX B: CASE STUDIES
1000
O)
3.
100 -J
£
i
10
O
±
LNWR WCA2A WCA3A
Hydrologic Unit
ENP
Appendix Bl. Figure B1.2. Box plots showing surface-water P concentrations at
long-term monitoring stations in each major hydrologic unit that illustrate the
minimally impacted (i.e., reference) condition of the Everglades with respect to P.
The top, mid-line, and bottom of each box represents the 75th, 50th (median), and
25th percentile of data, respectively; the error bars represent the 90th and 10th
percentiles; open circles are data outside the 90th percentile; the dashed line is the
analytical limit for TP (4 jig L"1).
REFERENCE ECOLOGICAL CONDITIONS
The Everglades is perhaps the most intensively studied wetland in the world and, therefore, the
ecological attributes that defined the predisturbance structure and function of this ecosystem are
well understood compared with most wetlands. Clearly, not all of the valued ecological attributes
of this or any other wetland are affected directly by P enrichment. Thus, in order to define the
reference condition of the ecosystem with respect to the role of P, this assessment focused on
those processes and communities that are most sensitive to P enrichment. Based on available
information and preliminary scoping studies, five ecological features were selected as biotic
response variables. These features included three indicators of ecosystem structure, one indicator
of ecosystem function, and one indicator of landscape change. Structural indicators included the
periphyton community, dominant macrophyte populations, and the benthic macroinvertebrate
community. Diel fluctuations in water column DO provided an important indicator of shifts in
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SEPTEMBER 2007 APPENDIX B: CASE STUDIES
aquatic metabolism. The landscape indicator of change was the loss of open-water slough-wet
prairie habitats—areas of high natural diversity and productivity.
Periphyton
Aquatic vegetation and other submerged surfaces in the oligotrophic Everglades interior are
covered with periphyton, a community of algae, bacteria and other microorganisms. Periphyton
accounts for a significant portion of primary productivity in sloughs and wet prairies (Wood and
Maynard 1974, Browder et.al., 1982, McCormick et.al., 1998), and floating and attached
periphyton mats provide an important habitat and food source for invertebrates and small fish
(Browder et.al., 1994, Rader 1994). These mats store large amounts of P (approaching 1 kg TP
m"2 in some locations) and, thus, may play a critical role in maintaining low P concentrations in
reference areas (McCormick et.al., 1998, McCormick and Scinto 1999). Periphyton biomass and
productivity peak towards the end of the wet season (August through October) and reach a
minimum during the colder months of the dry season (January through March). Periphyton
biomass in open-water habitats can exceed 1 kg m"2 during the wet season (Wood and Maynard
1974, Browder et.al., 1982, McCormick et.al., 1998) when floating mats can become so dense as
to cover the entire water surface. Aerobic conditions in slough-wet prairie habitats is maintained
by the high productivity of this community and the capacity of dense algal mats to trap oxygen
released during photosynthesis (McCormick and Laing 2003).
Two types of periphyton communities occur in reference areas of the Everglades. Mineral-rich
waters, such as those found WCA 2A and Taylor Slough (ENP), support a periphyton
assemblage dominated by a few species of calcium-precipitating cyanobacteria and diatoms,
while the soft-water interior of LNWR contain a characteristic assemblage of desmid green algae
and diatoms. Waters across much of the southern Everglades (WCA-3A and portions of ENP)
tend to be intermediate with respect to mineral content and contain some taxa from both
assemblages.
The chemical composition of periphyton in the oligotrophic Everglades is indicative of severe P
limitation. Periphyton samples from reference areas of major hydrologic units within the
Everglades are characterized by an extremely low P content (generally <0.05%) and extremely
high N:P ratios (generally >60:1 w:w). This observational evidence for P limitation is supported
by experimental fertilization studies that have shown that: 1) periphyton responds more strongly
to P enrichment than to enrichment with other commonly limiting nutrients such as nitrogen
(Scheldt et.al., 1989, Vymazal et.al., 1994); and, 2) periphyton changes in response to
experimental P enrichment mimic those that occur along field nutrient gradients (McCormick
and O'Dell 1996). Thus, it is well-established that periphyton is strongly P-limited in reference
areas of the Everglades.
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SEPTEMBER 2007 APPENDIX B: CASE STUDIES
Dissolved Oxygen
Interior Everglades habitats exhibit characteristic diel fluctuations in water-column dissolved
oxygen (DO), although aerobic conditions are generally maintained throughout much or all of
the diel cycle (Belanger et.al., 1989, McCormick et.al., 1997, McCormick and Laing 2003). High
daytime concentrations in open-water habitats (i.e., sloughs, wet prairies) are a product of
photosynthesis by periphyton and other submerged vegetation. These habitats may serve as
oxygen sources for adjacent sawgrass stands, where submerged productivity is low (Belanger
et.al., 1989). Oxygen concentrations decline rapidly during the night due to periphyton and
sediment microbial respiration and generally fall below the 5 mg L"1 standard for Class III
Florida waters (Criterion 17-302.560(21), F.A.C.). However, these diurnal excursions are
characteristic of reference areas throughout the Everglades (McCormick et.al., 1997) and are not
considered a violation of the Class III standard (Nearhoof 1992). In fact, a site specific criterion
for DO has been adopted by the State; a copy of the technical support document (Weaver 2004)
can be found at:
http://www.dep.state.fl.us/water/wqssp/everglades/docs/DOTechSupportDOC2004.pdf.
Vegetation
The vegetation communities characteristic of the pristine Everglades are dominated by species
adapted to low P, seasonal patterns of wetting and drying, and periodic natural disturbances such
as fire, drought, and occasional freezes (Duever et.al., 1994, Davis 1943, Steward and Ornes
1983, Parker 1974). Major aquatic vegetation habitats in oligotrophic areas include sawgrass
wetlands, wet prairies, and sloughs (Loveless 1959, Gunderson 1994). The spatial arrangement
of these habitats is dynamic and controlled by environmental factors such as fire, water depth,
nutrient availability, and local topography (Loveless 1959).
Sawgrass (Cladium jamaicense) is the dominant macrophyte in the Everglades, and stands of this
species compromise approximately 65 to 70% of the total vegetation cover of the Everglades
(Loveless 1959). Wet prairies include a collection of low-stature, graminoid communities
occurring on both peat and marl soils (Gunderson 1994). Dominant macrophyte taxa in these
habitats include Rhynchospora, Panicum, and Eleocharis (Loveless 1959, Craighead 1971).
Sloughs are deeper water habitats that remain wet most or all of the year and are characterized
by floating macrophytes such as fragrant white water lily (Nymphaea odorata), floating hearts
(Nymphoides Aquaticum), and spatterdock (Nuphar advend) (Loveless 1959, Gunderson 1994).
Submerged aquatic plants, primarily bladderworts (Utriculariafoliosa and U. purpurea in
particular), also can be abundant in these habitats and, in the case of U. purpurea, provide a
substrate for the formation of dense periphyton mats.
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SEPTEMBER 2007 APPENDIX B: CASE STUDIES
Several studies have concluded that macrophyte communities in the Everglades are P-limited.
Sawgrass is adapted to the low-P conditions indicative of the pristine Everglades (Steward and
Ornes 1975b, Steward and Ornes 1983). During field and greenhouse manipulations, sawgrass
responded to P enrichment either by increasing the rate of growth or P uptake (Steward and
Ornes 1975a, Steward and Ornes 1983, Craft et.al., 1995, Miao et.al., 1997, Daoust and Childers
1999). Furthermore, additions of N alone had no effect on sawgrass or cattail growth under low-
P conditions (Steward and Ornes 1983, Craft et.al., 1995). Recent experimental evidence in the
Everglades National Park (Daoust and Childers 1999) has shown that other native vegetation
associations such as wet prairie communities are also limited by P.
Historically, cattail (Typha spp.) was one of several minor macrophyte species native to the
Everglades (Davis 1943, Loveless 1959). In particular, cattail is believed to have been associated
largely with areas of disturbance such as alligator holes and recent burns (Davis 1994). Analyses
of Everglades peat deposits reveal no evidence of cattail peat, although the presence of cattail
pollen indicates its presence historically in some areas (Gleason and Stone 1994, Davis et.al.,
1994, Bartow et.al., 1996). Findings such as these confirm the historical presence of cattail in the
Everglades but provide no evidence for the existence of dense cattail stands covering large areas
(Wood and Tanner 1990) as now occurs in the northern Everglades. In contrast, sawgrass and
water lily peats have been major freshwater Everglades soils for approximately 4,000 years
(McDowell et.al., 1969).
Macroinvertebrates
Aquatic invertebrates (e.g., insects, snails, and crayfish) represent a key intermediate position in
energy flow through the Everglades food web as these taxa are the direct consumers of primary
production and, in turn, are consumed by vertebrate predators. Invertebrates occupy several
functional niches within the Everglades food web; however, most taxa are direct consumers of
periphyton and/or plant detritus (e.g., Rader and Richardson 1994, McCormick et.al., 2004).
Rader (1994) sampled both periphyton and macrophyte habitats in this same area and, based on
the proportional abundance of different functional groups, suggested that grazer (periphyton) and
detrital (plant) pathways contributed equally to energy flow in low-nutrient areas of the
Everglades.
The macroinvertebrate fauna of the Everglades is fairly diverse (approximately 200 taxa
identified) and is dominated by Diptera (49 taxa), Coleoptera (48 taxa), Gastropoda (17 taxa),
Odonata (14 taxa), and Oligochaeta (11 taxa) (Rader 1999). Most studies have focused on a few
conspicuous species (e.g., crayfish and apple snails) considered to be of special importance to
vertebrate predators, and relatively little is known about the distribution and environmental
tolerances of most taxa. An assemblage of benthic microinvertebrates (meiofauna) dominated by
Copepoda and Cladocera is also present in the Everglades (Loftus et.al., 1986), but even less is
known about the distribution and ecology of these organisms.
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SEPTEMBER 2007 APPENDIX B: CASE STUDIES
Invertebrates are not distributed evenly among Everglades habitats but, instead, tend to be
concentrated in periphyton-rich habitats such as sloughs. In an early study, Reark (1961) noted
that invertebrate densities in ENP were higher in periphyton habitats compared with sawgrass
stands. Rader (1994) reported similar findings in the northern Everglades and found mean annual
invertebrate densities to be more than six-fold higher in sloughs than in sawgrass stands.
Invertebrate assemblages in sloughs were more species-rich and contained considerably higher
densities of most dominant invertebrate groups. Functionally, slough invertebrate assemblages
contained similar densities of periphyton grazers and detritivores compared with a detritivore-
dominated assemblage in sawgrass stands. Higher invertebrate densities in sloughs were
attributed primarily to abundant growths of periphyton and submerged vegetation, which provide
oxygen and a source of high-quality food.
QUANTIFYING P IMPACTS
A targeted design (see Chapter 4) was used to quantify changes in key ecological attributes in
response to P enrichment. Discharges of canal waters through fixed water-control structures are
the primary source of anthropogenic P for the Everglades and produce P gradients that extend
several kilometers into the wetland in several locations. These gradients have existed for several
decades and provided the clearest example of the long-term ecological impacts associated with P
enrichment. Monitoring was conducted along gradients in different parts of the Everglades to
assess ecological responses to P enrichment. Fixed sampling stations were located along the full
extent of each gradient to document ecological conditions associated with increasing levels of P
enrichment. Intensive monitoring was performed along gradients in two northern Everglades
wetlands, WCA 2A and the LNWR. WCA 2A is a mineral-rich, slightly basic peatland and
contains the most pronounced and well studied P gradient in the Everglades, whereas LNWR is a
soft-water, slightly acidic peatland. These two wetlands represent the most extreme natural water
chemistry conditions in the Everglades and support distinct periphyton assemblages and
macrophyte populations while sharing dominant species such as sawgrass and water lily. Less
intensive sampling along gradients in other parts of the Everglades (WCA 3 A and ENP) to
confirm that P relationships were consistent across the wetland.
Chemical and biological conditions were measured at each sampling station along the two
intensively sampled gradients. Repeated sampling, sometimes over several years, was performed
to ensure that temporal variation in each metric was considered in the final data analysis.
Monthly surface-water sampling and less frequent soil sampling were performed to quantify P
gradients in each area. Diel DO regimes, periphyton, and benthic macroinvertebrates were
sampled quarterly when surface water was present. Macrophyte sampling included ground-based
methods to document shifts in species composition and remote sensing to determine changes in
landscape patterns. The hydrology of each site was characterized to determine whether P
gradients were confounded with hydrologic gradients, which can also exert a strong influence on
ecological patterns.
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SEPTEMBER 2007 APPENDIX B: CASE STUDIES
Numerous field experiments have been conducted to quantify ecological responses to P
enrichment and to better understand how interactions between P enrichment and other factors
such as hydrology may affect these responses. The design of these experiments varied in
complexity with respect to size and dosing regime depending on the specific objective of each
study and has included enclosed fertilizer plots (e.g., Craft et.al., 1995), semi-permeable
mesocosms receiving periodic P additions to achieve fixed loading rates in the form of periodic
additions (e.g., McCormick and O'Dell 1996), flumes receiving semi-continuous enrichment at a
fixed rate (Pan et.al., 2000), and flumes receiving flow-adjusted dosing to achieve constant
inflow concentrations (Childers et.al., 2002). These experiments were useful in establishing the
causal nature of responses to P enrichment documented along the P gradients described above.
GRADIENT P CONCENTRATIONS
Strong gradients in P concentrations were documented downstream of canal discharges into most
Everglades wetlands (Figure B1.3). Inflow TP concentrations in from 1996-1999 have averaged
as high as 100 jig L"1 as compared with reference and pre-disturbance concentrations < 10 jig L"1
. The degree and spatial extent of P enrichment varies among areas depending on the source and
magnitude of inflows. The most extensive enrichment has occurred in the northern Everglades
near EAA inflows, while southern areas (e.g., ENP) have been relatively less affected. The most
extensive enrichment has occurred in WC A-2 A, which, unlike other areas, receives most of its
water from canal discharges. Soil TP was strongly correlated with surface-water concentrations
and exceeded 1500 mg kg"1 at the most enriched locations as compared with concentrations <
500 mg kg"1 in reference areas. In general, this enrichment effect is limited to the surface 30 cm
of soil depth (Reddy et.al., 1998).
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SEPTEMBER 2007
APPENDIX B: CASE STUDIES
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Appendix Bl. Figure B1.3. Mean water-column TP concentrations (1996-1999)
at long-term monitoring stations downstream of canal discharges in two northern
Everglades wetlands, WCA 2A (circles connected by solid line) and LNWR
(squares connected by dashed line). Error bars are + 1 SE.
ECOLOGICAL RESPONSES TO P ENRICHMENT
Periphyton
Periphyton responses to P enrichment include changes in productivity, biomass, and species
composition. Periphyton rapidly accumulates P from the water (McCormick et.al., 2001, Noe
et.al., 2003), and, thus, a strong relationship between P concentrations in the water and
periphyton is maintained along the P gradients (Grimshaw et.al., 1993, McCormick et.al., 1996).
In fact, increases in periphyton P may provide one of the earliest signals of P enrichment (e.g.,
Gaiser et.al., 2004). Rapid increases in periphyton photosynthetic activity and growth rates occur
in response to P enrichment (e.g., Swift and Nicholas 1987, McCormick et.al., 1996, McCormick
et.al., 2001). All of these responses are consistent with the P-limited nature of Everglades
periphyton.
Paradoxically, these physiological responses are associated with sharply lower periphyton
biomass in P-enriched areas due to the loss of the abundant community of calcareous
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SEPTEMBER 2007
APPENDIX B: CASE STUDIES
cyanobacteria and diatoms that is indicative of mineral-rich reference areas. This community is
replaced by a eutrophic community of filamentous cyanobacteria, filamentous green algae, and
diatoms in areas having even slightly elevated P concentrations. For example, McCormick and
O'Dell (1996) found that the calcareous assemblage that existed at low water-column P
concentrations (TP = 5 to 7 jig L"1) was replaced by a filamentous green algal assemblage at
moderately elevated concentrations (TP = 10 to 28 jig L"1) and by eutrophic cyanobacteria and
diatoms species at even higher concentrations (TP = 42 to 134 jig L"1). These results are
representative of those documented by other investigators (e.g., Swift and Nicholas 1987, Pan
et.al., 2000). Taxonomic changes in response to controlled P enrichment in field experiments
have been shown to be similar to those documented along field enrichment gradients (Figure
B1.4), thereby providing causal evidence that changes in the periphyton assemblage were largely
a product of P enrichment (McCormick and O'Dell 1996, Pan et.al., 2000).
100
Mesocosms
Transects
Loading rate
(g P nY2 yr'1)
Water Column P
(M9 TP L1)
Appendix Bl. Figure B1.4. Changes in percent biomass (as biovolume) of major
algal groups in field enclosures dosed weekly with different P loads (left panel)
and along a P enrichment gradient downstream of canal discharges (right panel)
in WCA 2A. From McCormick and O'Dell (1996).
Community metabolism and dissolved oxygen concentrations
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SEPTEMBER 2007 APPENDIX B: CASE STUDIES
Phosphorus enrichment causes a shift in the balance between autotrophy and heterotrophy in the
water column as a result of contrasting effects on periphyton productivity and microbial
respiration. Rates of aquatic primary productivity (P) and respiration (R) are approximately
balanced (P:R ratio =1) across the diel cycle in minimally impacted sloughs throughout the
Everglades (Belanger et al., 1989; McCormick et al., 1997). In contrast, respiration rates exceed
productivity by a considerable margin (P:R ratio « 1) at enriched locations. This change is
related primarily to a large reduction in areal periphyton productivity as a result of shading by
dense stands of cattail (Typha domingensis) that form a nearly continuous cover in the most
enriched areas (McCormick and Laing, 2003). Increased cattail production also stimulates
microbial respiration (e.g., sediment oxygen demand) (e.g., Belanger et.al., 1989) due to an
increase in the quantity and decomposability of macrophyte litter.
The shift towards dominance of heterotrophic processes with P enrichment, in turn, affects
dissolved oxygen (DO) concentrations in enriched areas. For example, DO concentrations at an
enriched site in WCA 2A rarely exceeded 2 mg L"1 compared with concentrations as high as 12
mg L"1 at reference locations (McCormick et al., 1997). Depressed water-column DO
concentrations have subsequently been documented in enriched areas of WCA 2A and the
LNWR (Figure B1.5) and confirmed in experimental P-enrichment studies (McCormick and
Laing 2003). Declines in DO along field P gradients were steepest within a range of water-
column TP concentrations roughly between 10 and 30 jig L"1. Lower DO in enriched areas are
associated with other changes including an increase in anaerobic microbial processes and a shift
in invertebrate species composition toward species tolerant of low DO, described later in this
study.
Macrophytes
Nutrient enrichment initially stimulates the growth of existing vegetation as evidenced by
increased plant P content, photosynthesis, and biomass production, as it does for periphyton.
Persistent enrichment eventually produces a shift in vegetation composition toward species
better adapted to rapid growth and expansion under conditions of high P availability. Two major
shifts in Everglades plant communities have been documented along P gradients, including: 1)
the replacement of sawgrass stands by cattail; and, 2) the replacement of slough-wet prairie
habitat by cattail.
Sawgrass populations in the Everglades have life-history characteristics indicative of plants
adapted to low-nutrient environments (Davis 1989, Davis 1994, Miao and Sklar 1998). Sawgrass
responses to P enrichment include an increase in tissue P, plant biomass, P storage, annual leaf
production and turnover rates, and seed production (e.g., Davis 1989, Craft and Richardson
1997, Miao and Sklar 1998). Cattail is characterized by a high growth rate, a short life cycle,
high reproductive output, and other traits that confer a competitive advantage under enriched
conditions (Davis 1989, Davis 1994, Goslee and Richardson 1997, Miao and Sklar 1998).
174
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SEPTEMBER 2007
APPENDIX B: CASE STUDIES
WCA-2A
LNWR
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Appendix Bl. Figure B1.5. Relationship between water-column DO metrics and
TP concentration at several stations and time intervals along P gradients
downstream of canal discharges into two northern Everglades wetlands (see
Figure 1 for map). Total P concentrations are mean values for all samples (n = 3
to 6) collected during the three-month period preceding DO measurements, which
were typically collected over 3-4 diel cycles using dataloggers. Correlation
coefficients are Spearman rank coefficients based on all data in the plot. Adapted
from McCormick and Laing (2003).
175
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SEPTEMBER 2007
APPENDIX B: CASE STUDIES
Measurements and controlled enrichment experiments have shown that cattail growth rates
exceed those of sawgrass under enriched conditions (Davis 1989, Newman et.al., 1996, Miao
and DeBusk 1999). The replacement of sawgrass by cattail in P enriched areas may be facilitated
by disturbances such as flooding or severe fires that weaken or kill sawgrass plants and create
openings. Consequently, sawgrass distributional patterns were not as clearly related to P
gradients as were other ecological indicators of enrichment.
Sloughs and wet prairies appear to be particularly sensitive to replacement by cattail under P-
enriched conditions, possibly due to the sparser vegetation cover in these habitats. The process
of slough enrichment and replacement by cattail as shown in satellite imagery is supported by
ground-based sampling methods (McCormick et.al., 1999) that documented changes in slough
vegetation and encroachment of these habitats by cattail in areas where soil TP concentrations
averaged between 400 and 600 mg kg"1 and water-column TP in recent years
averaged > 10 jig L"1. Eleocharis declined in response to increased soil P, and Nymphaea was
stimulated by enrichment and was dominant in slightly enriched sloughs. Increased occurrence
of cattail in sloughs was associated with a decline in Nymphaea, probably as a result of increased
shading of the water surface. These findings are consistent with those of Vaithiyanathan et.al.,
(1995) who documented a decline in slough habitats along this same nutrient gradient and the
loss of sensitive taxa such as Eleocharis at locations where soil TP exceeded 700 mg kg"1. As
discussed by McCormick et.al., (2002), loss of these open-water areas is a sensitive landscape
indicator of P enrichment (Figure B 1.6).
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Figure B1.6. Changes in the percentage of open-water (i.e., sloughs, wet prairies,
or other opening caused by natural disturbance or airboats) cover at 94 locations
along a P enrichment gradient in WCA 2A as determined using aerial
176
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SEPTEMBER 2007 APPENDIX B: CASE STUDIES
photography. Gray line shows the mean (+ 1 SE) water-column TP concentration
(1996-1999) at 15 long-term monitoring stations along the gradient.
Benthic Macroinvertebrates
Macroinvertebrates are the most widely used biological indicator of water quality impacts, and
several changes that occur in this community along P enrichment gradients in the Everglades are
similar to those documented in response to eutrophication in other aquatic ecosystems. Several
studies have documented an overall increase in macroinvertebrate abundance with increasing P
enrichment (Rader and Richardson 1994, Trexler and Turner et.al., 1999, McCormick et.al.,
2004). However, differences in sampling methodology have apparently produced conflicting
results with respect to changes in species richness and diversity. For example, Rader and
Richardson (1994) documented an increase in both macroinvertebrate species richness and
diversity with P enrichment in open-water (i.e., low emergent macrophyte cover) habitats and
concluded that enrichment had not impacted this community. McCormick et.al., (2004),
however, using a landscape approach that involved habitat-weighted sampling, found little
change in either species richness or diversity in response to enrichment. This latter study
accounted for the decline in the cover of habitats such as sloughs and wet prairies, which contain
the most diverse and abundant macroinvertebrate communities (Rader 1994). McCormick et.al.,
(2004) also documented a pronounced shift in community composition with increasing P
enrichment as taxa characteristic of the oligotrophic interior of the wetland are replaced by
common pollution-tolerant taxa of oligochaetes and chironomids. These changes were indicative
of habitat degradation as determined using biotic indices derived by the Florida DEP to assess
stream condition based on macroinvertebrate composition (results available at
http ://www. epa. gov/owow/wetlands/bawwg/case/fl2.html).
As for many other P-induced biological changes, the greatest change in the macroinvertebrate
community occurred in response to relatively small increases in P concentration. Along field
enrichment gradients, community shifts were associated with increases in water-column TP
above approximately 10 ug L"1 (McCormick et.al., 2004). Similarly, Qian et.al., (2004)
documented several shifts in community structure and function in response to long-term
experimental dosing at average concentrations of approximately 10-15 ug L"1.
ESTABLISHING A P CRITERION
The FDEP was charged with reviewing and analyzing available P and ecological data collected
throughout the Everglades to establish a numeric P criterion. A brief summary of this process is
provided here, and more detailed information can be found in Payne et al., (2000, 2001a,b;
available at http://www.dep.state.fl.us/water/wqssp/everglades/pctsd.htm: and, 2002, 2003,
available at http://www.sfwmd.gov/sfer/previous ecr.html).
The narrative nutrient standard for Class III Florida waters such as the Everglades states that "in
no case shall nutrient concentrations of a body of water be altered so as to cause an imbalance in
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SEPTEMBER 2007 APPENDIX B: CASE STUDIES
natural populations of aquatic flora or fauna." The FDEP approach to detecting violations of this
standard with respect to surface-water P concentrations in the Everglades was to test for
statistically significant departures in ecological conditions from those at reference sites (i.e.,
interior sampling locations with background P concentrations). Biological and chemical data
collected along anthropogenic P gradients throughout the Everglades were analyzed to determine
P concentrations associated with such departures. Results showed that sampling sites with
average (geometric mean) surface-water TP concentrations significantly greater than 10 ppb
consistently exhibited significant departures in ecological condition from that of reference sites.
A key finding supporting this concentration as the standard was the fact that multiple changes in
each of the major indicator groups—periphyton, dissolved oxygen, macrophytes, and
macroinvertebrates—all occurred at or near this same concentration (e.g., Payne et.al., 2001).
Data from field and laboratory experiments conducted by various research groups provided
valuable supporting information for understanding responses to P enrichment. While such
experiments were not used directly to derive the P criterion, they established cause-effect
relationships between P enrichment and ecological change that supported correlative
relationships documented along field P gradients. For example, McCormick and O'Dell (1996)
and Pan et.al., (2000) showed that major shifts in periphyton species composition documented
along field P gradients matched those elicited by controlled P dosing in field enrichment
experiments. McCormick and Laing (2003) confirmed that controlled P enrichment produced
declines in water-column DO similar to those measured along the gradients. Macroinvertebrate
community changes were documented experimentally, Qian et.al., (2004).
While the criterion established a surface-water concentration of 10 ug L"1 TP as protective of
native flora and fauna, the methodology used to measure compliance with the criterion needed to
normalize background fluctuations in concentration. Additional analyses of P data collected over
several years at reference sites was used to set both a longer-term average concentration and a
shorter-term maximum concentration for each site. Based on these analyses, the FDEP
concluded that annual maximum concentrations at a given sampling location should not exceed
15 ug L"1 TP over the long-term, while five-year average concentrations should not exceed 10 ug
L"1 TP. These limits would be applied to reference areas to ensure no further degradation and to
areas already impacted by P enrichment to gauge the rate and extent of recovery in response to a
suite of P control measures, including agricultural BMPs and the construction of treatment
wetlands to remove P from surface runoff prior to being discharged into the Everglades.
Additional information on Florida's progress in assessing and implementing the adopted
standard can be found on the South Florida Water Management District Web site:
www.sfwmd.gov.
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