United States Office of Water
Environmental Protection Agency 4304T
EPA-822-B-08-001
June 2008
Nutrient Criteria
Technical Guidance Manual
Wetlands
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U.S. Environmental Protection Agency
Nutrient Criteria
Technical Guidance Manual
Wetlands
June 2008
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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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CONTENTS
Disclaimer i
List of Figures iv
List of Tables iv
List of Internet Link References v
Contributors vii
Acknowledgments vii
Executive Summary ix
CHAPTER 1. Introduction 1-1
1.1 Introduction 1-1
1.2 Water Quality Standards and Criteria 1-2
1.3 Nutrient Enrichment Problems 1-3
1.4 Overview of the Criteria Development Process 1-6
1.5 Roadmap to the Document 1-6
CHAPTER 2. Overview of Wetland Science 2-1
2.1 Introduction 2-1
2.2 Components of Wetlands 2-2
2.3 Wetland Nutrient Components 2-5
CHAPTER 3. Classification of Wetlands 3-1
3.1 Introduction 3-1
3.2 Existing Wetland Classification Schemes 3-2
3.3 Sources of Information for Mapping Wetland Classes 3-10
3.4 Differences in Nutrient References Condition or Sensitivity to
Nutrients Among Wetland Classes 3-10
3.5 Recommendations 3-11
CHAPTER 4. Sampling Design for Wetland Monitoring 4-1
4.1 Introduction 4-1
4.2 Considerations for Sampling Design 4-2
4.3 Sampling Protocol 4-5
4.4 Summary 4-9
CHAPTER 5. Candidate Variables for Establishing Nutrient Criteria 5-1
5.1 Overview of Candidate Variables 5-1
5.2 Supporting Variables 5-3
5.3 Casual Variables 5-5
5.4 Response Variables 5-9
5.5 Summary 5-12
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CONTENTS (continued)
CHAPTER 6. Database Development and New Data Collection 6-1
6.1 Introduction 6-1
6.2 Databases and Database Management 6-1
6.3 Quality of Historical and Collected Data 6-4
6.4 Collecting New Data 6-6
6.5 Quality Assurance / Quality Control 6-7
CHAPTER?. Data Analysis 7-1
7.1 Introduction 7-1
7.2 Factors Affecting Analysis Approach 7-1
7.3 Distribution-based Approaches 7-2
7.4 Response-based Approaches 7-3
7.5 Partitioning Effects Among Multiple Stressors 7-5
7.6 Statistical Techniques 7-5
7.7 Linking Nutrient Availability to Primary Producer Response 7-8
CHAPTERS. Criteria Development 8-1
8.1 Introduction 8-1
8.2 Methods for Developing Nutrient Criteria 8-1
8.3 Evaluation of Proposed Criteria 8-6
References R-l
Supplementary References R-21
Appendix A. Acronym List and Glossary A-l
Acronyms A-l
Glossary A-2
Appendix B. Case Study: Deriving a Phosphorus Criterion for the Florida Everglades B-l
Literature Cited L-l
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LIST OF FIGURES
FIGURE 1.1 Flowchart providing the steps of the process to develop wetland nutrient criteria 1-8
FIGURE 2.1 Schematic of nutrient transfer among potential system sources and sinks 2-1
FIGURE 2.2 Relationship between water source and wetland vegetation. Modified from Brinson (1993) 2-2
FIGURE 2.3 Schematic showing basic nutrient cycles in soil-water column of a wetland 2-7
FIGURE 2.4 Range of redox potentials in wetland soils 2-8
FIGURE 2.5 Schematic of the nitrogen cycle in wetlands 2-9
FIGURE 2.6 Schematic of the phosphorus cycle in wetlands 2-10
FIGURE 3.1 Map of Omernik aquatic ecoregions 3-3
FIGURE 3.2A Map of Bailey ecoregions with coastal and estuarine provinces 3-3
FIGURE 3.2B Legend (of Map of Bailey ecoregions with coastal and estuarine provinces) 3-4
FIGURE 3.3 Examples of first four hierarchical levels of Ecological Units 3-5
FIGURE 3.4A Cowardin hierarchy of habitat types for estuarine systems 3-6
FIGURE 3.4B Cowardin hierarchy of habitat types for Palustrine systems 3-7
FIGURE 3.5 Dominant water sources to wetlands, from Brinson 1993 3-8
FIGURE 3.6 Dominant hydrodynamic regimes for wetlands based on flow pattern 3-8
FIGURE 3.7 Interaction with break in slope with groundwater inputs to slope wetlands (Bottom)
Palustrine systems, from Cowardin et al. 1979 3-8
FIGURE 5.1 Conceptual model of causal pathway between human activities and ecological attributes 5-2
FIGURE 7.1 Biological condition gradient model describing biotic community condition as levels of
stressors increase 7-1
FIGURE 8.1 Use of undisturbed wetlands as a reference for establishing criteria versus an effects-based
approach 8-3
FIGURE 8.2 Tiered aquatic life use model used in Maine 8-4
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 8-5
LIST OF TABLES
TABLE 1 Observed consequences of cultural eutrophication in freshwater wetlands 1-5
TABLE 2 Comparison of landscape and wetland classification schemes 3-12
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 3-13
TABLE 4
Comparison of Stratified Probabilistic, Targeted, and BACI Sampling Designs 4-10
IV
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LIST OF INTERNET LINKS/REFERENCES/GLOSSARY/APPENDIX
INTERNET LINKS
EXECUTIVE SUMMARY http://www.epa.gov/waterscience/criteria/nutrient/guidance/index.html
http://www.epa.gov/owow/wetlands/
http://www.epa.gov/owow/wetlands/watersheds/cwetlands.html
CHAPTER 1
http://www.epa.gov/waterscience/criteria/nutrient/guidance/index.html
http://www.epa.gov/owow/wetlands/initiative
http://www.epa.gov/waterscience/criteria/nutrient/strategy
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
CHAPTER 4
http ://www. epa. gov/owow/wetlands/bawwg/case/or.html
http://www.epa.gov/waterscience/criteria/wetlands/
http ://www. epa. gov/waterscience/criteria/wetlands/1 TLandUse .pdf
http ://www. epa. gov/owow/wetlands/bawwg/case/mtdev.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/mnl.html
http://www.epa.gov/waterscience/criteria/wetlands/
CHAPTER 5
http ://www. epa. gov/waterscience/criteria/wetlands/
http://water.usgs.gov/nawqa/sparrow/
http ://www. epa. gov/waterscience/criteria/wetlands/16Indicators
http://www.epa.gov/waterscience/criteria/wetlands/10Vegetation.pdf
http://www.epa.gov/waterscience/criteria/wetlands/HAlgae.pdf
http://www.epa.gov/waterscience/criteria/wetlands/9Invertebrate.pdf
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CHAPTER 6
http://www.epa.gov/emap/html/data/index.html
http ://www. epa.gov/emap
http://www.usgs.gov
http ://water.usgs .gov/nrp/webb/about.html
http://hydrolab.arsusda.gov/arssci.html
http://www.nps.ars.usda.gov/programs/nrsas.htm
http://www.fs.fed.us/research/
http://www.usace.army.mil/public.html
http ://www.usbr.gov
http://nhd.usgs.gov
CHAPTER 7
CHAPTER 8
REFERENCES
GLOSSARY
APPENDIX B
http: //el. erdc .usac e. army.mil/wrap/wrap .html
http://www.socialresearchmethods.net/
http://www.yorku.ca/isr/scs/
http://www.surveysystem.com/sscalc.htm
http://www.stat.ohio-state.edu/~jch/ssinput.html
http ://www. stat.uiowa. edu
http://www.epa.gov/waterscience/criteria/wetlands
http://www.epa.gov/waterscience/biocriteria/modules/wetl01-05-alus-monitoring.pdf
http://www.wbi.lsu.edu/wbi/web-content/index.html
http://data.lca.gov/Ivan6/app/app _c_ch9.pdf
http ://www. epa.gov/owow
http ://www. dep. state. fl .us/lab s/library/index .htm
http://www.epa.gov/owow/wetlands/pdf/RapanosGuidance6507.pdf
http://www.epa.gov/waterscience/criteria/nutrient/policy20070525.pdf
http ://www. wwwalker.net/dmsta
http://www.epa.gov/waterscience/criteria/nutrient/ecoregions/index.html
http://www.epa.gov/owow/wetlands/pdf/RapanosGuidance6507.pdf
http://www.epa.gov/owow/wetlands/
http://www.dep.state.fl.us/water/wqssp/everglades/docs/DOTechSupportDOC2004.pdf
http://www.epa.gov/owow/wetlands/bawwg/case/fl2.html
http://www.dep.state.fl.us/water/wqssp/everglades/pctsd.htm
http ://www.www. sfwmd.gov
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)
Todd Rasmussen (University of Georgia)
Ramesh Reddy (University of Florida)
R. Jan Stevenson (Michigan State University)
Arnold van der Valk (Iowa State University)
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, Steve Potts, 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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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 . 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.
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:
1For 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/owow/wetlands/.
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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.
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), above
ground 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.
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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 meta data) 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);
• 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 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/c wetlands. html.
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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: http://www.epa.gov/waterscience/criteria/nutrient/guidance/index.html.
BACKGROUND
Cultural eutrophication (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).
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 eutrophication 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-
Nutrient Criteria-Wetlands 1-1
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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(i))" (USEPA 1994). A water quality standard defines the goals for a wetland
by: designating its specific uses, setting criteria to protect those uses, and, 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 to ensure they have designated the appropriate uses.
Generally, the effectiveness of designated uses in guiding water quality management programs is greater if
they:
• Identify specific expectations based on as much data as possible to reduce ambiguity;
• Recognize and accommodate inherent natural differences among surface water types; and
• 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.
2EPA 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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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 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
Nutrient Criteria-Wetlands 1-3
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and have degraded 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 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).
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,
1-4 Nutrient Criteria-Wetlands
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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.
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., Typha glauca, T. latifolia and Phalaris arundinacea)
Loss of nutrient retention capacity (e.g., carbon and 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
Phillips et al. 1978
Stephenson et al. 1980
Galatowitsch and van der Valk 1996
Wentz 1976
Verhoeven et al. 1988
Ehrenfeld and Schneider 1 993
Gaudet and Keddy 1995
Koerselman and Verhoeven 1995
Barko 1983
Bayleyetal. 1985
Barko and Smart 1986
Vermeer 1986
Mudroch and Capobianco 1979
Guntenspergen et al. 1980
Lougheed et al. 2001
Balla and Davis 1995
VanGroenendael et al. 1993
Bedford etal. 1999
Woo and Zedler 2002
Svengsouk and Mitsch 200 1
Green and Galatowitsch 2002
Maurer and Zedler 2002
Nichols 1983
Davis and van der Valk 1983
Rybczyketal. 1996
McDougal et al. 1997
Angeler et al. 2003
Chessman et al. 2002
Table 1: Observed consequences of cultural eutrophication in freshwater wetlands.3
3Similar impacts in tidal and estuarine wetlands have been documented, but are not included in this table.
Nutrient Criteria-Wetlands
1-5
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1.4 OVERVIEW OF 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. 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.
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
1-6 Nutrient Criteria-Wetlands
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wetlands. The classification of these systems is important to identifying their nutrient status and their
condition in relation to similar wetlands.
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.
Nutrient Criteria-Wetlands 1-7
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MONITOR
IDENTIFY
GOALS
CLASSIFY
WETLANDS
SELECT
VARIABLES
DETERMINE
SAMPLING
DESIGN
BUILD
DATABASE
ANALYZE
DATA
DEVELOP
CRITERIA
Figure 1.: Flowchart identifying the steps of the recommended process to develop wetland nutrient
criteria.
1-8
Nutrient Criteria-Wetlands
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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).
Atmospheric Inputs
Atmospheric Outputs I
., • . «•
Surface Water Inflows
NI Ground Water Inflows
Ground Water Outflows
Surface Water Outflows
Figure 2.1: Schematic of nutrient transfer among potential system sources and sinks.
Nutrient Criteria-Wetlands
2-1
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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.
0%A100%
BOGS,
POCOSINS
GROUND WATER ^^^^^^^^^^^ PRECIPITATION
47%
RIVERINE,
FRINGE,
TIDAL
kO%
33% 67% 100%
SURFACE FLOW te-
Figure 2.2: Relationship between water source and wetland vegetation. Modified from Brinson (1993)
2-2 Nutrient Criteria-Wetlands
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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 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, particulate 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.
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, Fe2+). 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
Nutrient Criteria-Wetlands 2-3
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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 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 distichum) and tupelo gum (Nyssa aquatica) (Wharton et al. 1982).
Areas inundated less frequently are dominated by hardwoods such as black gum (Nyssa sylvatica), green ash
(Fraxinus pennsylvanicus), and red maple (Acer rubrum), and the highest, driest wetland areas are dominated
by facultative species such as sweet gum (Liquidambar styraciflua) 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.
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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
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 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.
Nutrient Criteria-Wetlands 2-5
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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.
BIOCHEMICAL 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 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
2-6 Nutrient Criteria-Wetlands
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Emergent
macrophyte
Submerged
macrophyte
"Water"
Soil
Bioavailable
nutrients
Figure 2.3: Schematic showing basic nutrient cycles in soil-water column of a wetland.
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 (HCO3)).
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 NO3 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 HCO3). 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 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).
Nutrient Criteria-Wetlands
2-7
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Flooded Soil
Anaerobic
Drained Soil
Aerobic
Highly
Reduced
Reduced
Moderately
Reduced
Oxidized
-300
-100 0 100 300 500
Oxidation-Reduction Potential (mV)
700
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 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.
2-8
Nutrient Criteria-Wetlands
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Atmospheric
Deposition
Plant biomass
/NH3
Jtterfall
Volatilization
N2 N2O
Inflow
Nitrogen
Fixation
Mineralization ..... + .... =—,
Organic -^—•—^^- NH4 Water Column
Soil-AEROBIC
Peaf
accretion
N03"
Denitrification
Microbial
Organic N •**• Biomass N Adsorbed NH4+
^— N2, N20 (g)
Figure 2.5: Schematic of the nitrogen cycle in wetlands.
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 (NH4-N,
NO3-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.
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.
Nutrient Criteria-Wetlands
2-9
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Plant biomass P
Inflow
Atmospheric
Deposition
//f^\L\tteria\\
-4h-
Outflow
PIP
Water Column
Soil-AEROBIC
OOP
Adsorbed
IP
[Fe, Al or
Ca-bound
P]
Soil - ANAEROBIC
Figure 2.6: Schematic of the phosphorous cycle in wetlands.
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 bottom sediments; (v) redox conditions
(O2 content) at the soil/sediment-water interface; and, (vi) phosphorus flux from water column to soil mediated
by evapotranspiration by vegetation.
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).
2-10
Nutrient Criteria-Wetlands
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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.
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
Nutrient Criteria-Wetlands 3-1
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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).
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 (USDA) 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.
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),
3-2 Nutrient Criteria-Wetlands
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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.
Figure 3.1: Map of Omernik aquatic ecoregions.
5. WEST
INDIAN
BOUNDARIES OF
10 MARINE AND ESTUARINE
PROVINCES
Figure 3.2a: Map of Bailey ecoregions with coastal and estuarine provinces. (Cowardin et al. 1979).
Nutrient Criteria-Wetlands
3-3
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a 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 Harwoods-Spruce Forest
M2110 Columbia Forest
M2 111 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-Bluestem 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
2532 Whestgrass-Bluestem-Needlegrass
2533 Bluestem-Gamma Prairie
2600 Mediterranean (Dry-summer Subtropical)
2610 California Grassland
M2610 Sierran Forest
M2620 California Chaparral
3000 Dry
3100 Steppe
3110 Great Planins-Shortgrass Prairie
3111 Gramma-Needlegrass-Wheatgrass
3112 Wheatgrass-Needlegrass
3113 Grama-Buffalo Grass
M3110 Rocky Mountain Forest
M3 111 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 Lahontan Saltbush-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-Needlegrass-Sagebrush
A3142 Sagebrush-Wheatgrass
3200 Desert 3210 Chihuahuan Desert
3211 Grama-Tobosa
3212 Tarbush-Creosote Bush
3220 American Desert
3221 Creosote Bush
3222 Creosote Bush-Bur Sage
4000 Humid Tropical
4100 Savanna
4110 Everglades
4200 Rainforest
M4210 Hawaiian Islands
Figure 3.2b: Legend for Bailey ecoregion map shown in Figure 3.2a.
3-4
Nutrient Criteria-Wetlands
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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 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).
Nutrient Criteria-Wetlands
3-5
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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
(F WS) 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).
UPLAND
ESTUARINE
UPLAND
ESTUARINE
IMTERTIDAL SUBTIDAL IWTERTIDAL
C Iff *f* *
D
<
cc
LJ
CL
D
LJ
D
_i
O
O
CL
D
LJ
00
DC
UJ
Q.
irjTERTIDAL
SUETIDAL
LJ
D
a
LU
Q
O
•
^- LJ -
3 g <
5 oo £
CS
<
D
LJ
LU
4 IRREGULARLY FLOODED
tREGULARLYFOODED
<: IRREGULARLY EXPOSED
J SUBTIDAL
LJ
LJ
cc
D
O
O
O
Figure 3.4a: Cowardin hierarchy of habitat types for estuarine systems; from Cowardin et al. 1979.
3-6
Nutrient Criteria-Wetlands
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UPLAND PALUSTRINEUPLAND
PALUSTRINE
PALUSTRINE
UPLAND
SEEPAGE ZONE
a TEMPORARILY FLOODED
b SEASONALLY FLOODED
c SEMIPERMANENTLY FLOODED
d INTERMrTTTENTLY FLOODED
c PERMANENTLY FLOODED
f SATURATED
HIGH WATER
AVERAGE WATER
LOW WATER
Figure 3.4b: Cowardin hierarchy of habitat types for Palustrine systems; from Cowardin et al. 1979.
HYDROGEOMORPHIC 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.
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., 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.
Nutrient Criteria-Wetlands
3-7
-------
„.«.
Figure 3.5: Dominant water sources to
wetlands, fromBrinson 1993. Cowardin
hierarchy of habitat types for estuarine
systems.
IMS
VERTICAL
[-LUC1UATIOWS
UMCHRECTIONA.
FLOW
tSOtRtCTlONA.
FLOW
Figure 3.6: Dominant hydrodynamic
regimes for wetlands based on flow
pattern (Brinson 1993).
FACE
«(N» »*»• » «»
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
3-8
Nutrient Criteria-Wetlands
-------
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.
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.
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 2.
Nutrient Criteria-Wetlands 3-9
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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).
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.
Sensitivity to nutrient loading (as evidenced by differences in nutrient cycling and availability) may also be
3-10 Nutrient Criteria-Wetlands
-------
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 etermine
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).
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.
Nutrient Criteria-Wetlands 3-11
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Bailey's ecoregions
Omernik ecoregions
Ecological units
(Maxwell et al. 1995)
USAGE
Hydrogeomorphic
Classes
Rosgen channel types
Anderson land-cover
classes
Circular 39 classes
National Wetland
Inventory
Vegetation
associations
Nationwide
Nationwide
Nationwide
Nationwide
at class level;
regionalized
at subclass
level
Nationwide
Nationwide
Nationwide
Nationwide
International
Yes
No
Yes
Yes - limited
Yes
Yes
No
Yes
Yes
Domains
Divisions
Provinces
Sections
Ecoregions
Subecoregions
Domain
Divisions
Provinces
Sections
Subsections
Class
Subclass
Level I
Level II
Level I
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
Only natural
attributes included
Digital maps
Digital maps
Digital maps
Specific for
wetlands
Captures
differences in
hydrologic regime
for riverine
wetlands
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
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
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
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
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 link w HGM system
Could be used as lowest level
within other schemes
Table 2: Comparison of landscape and wetland classification schemes.
3-12
Nutrient Criteria-Wetlands
-------
Predominant Nutrient
Source(S)
Landscape Position
Hydrologic Regime
Hydraulic Retention
Time
Nutrient Assimilation
Capacity
Predominant
Vegetation Growth
Form
Top Trophic Level
Commercially-
Important Fish/
Wildlife
Recreational Use
Likely
Drinking Water Source
Downstream
Atmospheric
Deposition
Saturated,
Little
Standing
Water
Decades
Low
Mosses
Sedges
Mammals
Birds
Amphibians
Invertebrates
Atmospheric
Deposition,
Groundwater
Saturated, Little
Standing Water
Decades
High Sorption
Capacity
Sedges
Mammals
Birds
Amphibians
Invertebrates
Runoff
(P articulate
and Dissolved),
Surface and
Groundwater
Depth and
Duration Vary
from Saturated
to Temporary
to Seasonal to
Semi-Permanent
to Permanent
Inundation
Varies With
Inflows/Outflows,
Landscape
Position
High Sorption,
Plant Uptake,
(Limited)
Sediment Storage
Varies With Zone
And Duration of
Flooding:
Wooded
Grass/Sedge
Emergents
Submerged
Aquatics*
Mammals
Birds
Mudminnows
Amphibians
Invertebrates
Waterfowl
Yes
Possible
Runoff
(P articulate),
Overbank Flooding
(P articulate,
Dissolved)
Adjacent to Rivers
Depth, Duration
Vary With River
Flooding Regime
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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 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
Nutrient Criteria-Wetlands 4-1
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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 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 (Suter et al. 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). 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
4-2 Nutrient Criteria-Wetlands
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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);
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 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 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
Nutrient Criteria-Wetlands 4-3
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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/).
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 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.
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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).
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 Quality
Assurance/Quality Control (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.
PROBALISTIC 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 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.
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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/, http://www.epa.gov/waterscience/criteria/wetlands/17LandUse.pdf).
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
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/fll.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 (FDEP) 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
FDEP 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.
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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.
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/ohl.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 yet; and, (3) control areas
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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 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.
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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.
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.
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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/. 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.
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.
Table 4: Comparison of Probabilistic, Targeted, and BACI Sampling Designs.
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CHAPTER 5: CANDIDATE VARIABLES FOR ESTABLISHING NUTRIENT CRI-
TERIA
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/.
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 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.
4EPA is developing and revising additional modules as a part of the Methods for Evaluating Wetland Conditions Module Series-Biogeo-
chemical Indicators, Wetland Hydrology, and Nutrient Loading Estimation.
5The references for these modules can be found in the Supplementary References following the References section.
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STRESSORS: CONTAMINANTS a HABITAT ALTERATIONS
T
RESPONSES; VALUED ECOLOGICAL ATTRIBUTES
Ecosystem Structure
Biomass
Biodiversit
"' ra& Fauna
Ecosystem Function
Productivity
Nutrient Retention
Hydrologic Regulatio
This conceptual model illustrates the casual 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 conditions of wetlands. Causal factors "cause"
effects in response variables.
Figure 5.1: Conceptual model of causal pathway between human activities and ecological attributes
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).
5-2
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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.
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 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 (ja,S/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.
SOIL pH
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 CO2. 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 CO2. 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.
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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.
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 ug/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.
HYDROLIC 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
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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 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
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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 (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 USDA-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 balance models
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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 source
shed, 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 and N 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
20 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).
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).
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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 NaHCO3 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 CaCO3.
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; 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 PHOSPHORUS
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.
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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 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., PO4-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: (1) dissolved inorganic P (DIP, also referred to as
dissolved reactive P (DRP) or soluble reactive phosphorous (SRP)); (2) dissolved organic P (DOP); (3) particulate
inorganic P (PIP); and, (4) particulate organic P (POP). Dissolved inorganic P (PO4-P) 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/15Indicators.pdf;
http://www.epa.gov/waterscience/criteria/wetlands/16Vegetation.pdf), algae (http://www.epa.gov/waterscience/
criteria/wetlands/11 Algae.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).
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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 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, 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.
ABOVE GROUND 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
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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.
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 ten 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 ten 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 AND 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/1 lAlgae.pdf) for a detailed description of indicators derived from to N and
P content of algae.
MACROPHYTE COMMUNITY STRUCTURE AND COMPOSITION
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/lOVegetation.pdf), respectively.
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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/HAlgae.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 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 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 ArcView™,
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.
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.
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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: http://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 (http://www.
epa.gov/emap/html/data/index.html). 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 Survey (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.
HBNandNASQAN
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).
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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/nr sas. htm).
Forest Service
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 (NIS), 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 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.
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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
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
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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
Data generated by agencies or laboratories with known quality control/quality assurance protocols are most
reliable. Laboratory Quality Control (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 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 recommended.
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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
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.
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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;
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
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 and quality control (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 project'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.
BCG MODEL: SNAP SHOT
z
o
F
5
z
O
u
u
o
o
o
m
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.
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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 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
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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.
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 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 (USEPA2000). 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.
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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 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 or NMDS) 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 from macrophyte pollen or diatom frustrates, 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
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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 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
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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 (P), 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.
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.yorku.ca/isr/scs/, http://www.surveysystem.com/sscalc.htm,
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 INDICES
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
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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 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= 2j=i,smin(aj,bi)
Here aj 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
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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).
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.
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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 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 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 Regional Technical Assistance Group (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 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
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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 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 to 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
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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 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.
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 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.
75th percentile of
reference population is
the starting point for
criteria.
Concentration
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).
Nutrient Criteria-Wetlands
8-3
-------
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 (PDF): (http://www.epa.gov/
waterscience/biocriteria/modules/wetlOl-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.
APPLYING PREDICTIVE RELATIONSHIPS
Two fundamental reasons are commonly considered for using biological attributes in developing nutrient
criteria. The concepts basically promote the use of biotic responses or biocriteria to nutrient enrichment.
i.e., both rationales support evaluation of physical and chemical conditions in conjunction with biological
parameters when establishing water quality criteria. The first reason is that the primary goal of environmental
assessment and management is to protect and restore ecosystem services and ecological attributes, which are
often closely related to biological features and functions in ecosystems. Therefore, it is the effects of nutrients
on the living components of ecosystems that should become the critical determinant of nutrient criteria, rather
than the actual nutrient concentrations. The second reason for using biocriteria is that attributes of biological
MAINE TALU
Native or natural condition
NATURAL
o
13
O
u
_o
"o
DEGRADED
Minimal loss of species; some
density changes may occur
Some replacement of
sensitive-rare species;
functions fully
maintained
Some sensitive species
maintained; altered
distributions; functions
largely maintained
Tolerant species show
increasing dominance;
sensitive species are rare;
functions altered Severe alteration of
structure and function
LOW Increasing Effects of Stressors HIGH
Figure 8.2: Tiered Aquatic Life Use model used in Maine.
8-4
Nutrient Criteria-Wetlands
-------
assemblages usually vary less in space and time than most physical and chemical characteristics measured
in environmental assessments. Thus, fewer mistakes in assessment may occur if biocriteria are employed in
addition to physical and chemical criteria. In those environments where biological attributes change fairly
rapidly, such as in Louisiana's coastal wetland environment where salinity can vary dramatically in response
to wet versus drought years, other techniques will need to be developed. Information on some other techniques
can be found at The Louisiana State University School of the Coast and Environment (http://www.wbi.lsu.edu/
wbi/web-content/index.html) and also in interagency efforts through the Los Angeles Department of Natural
Resources) to assess coastal area ecology. (http://data.lca.gov/Ivan6/app/app_c_ch9.pdf).
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).
) Mat Cover
i fin
90
80
70
60
50
40
^n
jit
20
10
1
(
I
*.•'£'•*• v
*J... . ,T. ...*...* ....
. . " * **• *
• •
" * * • * •
i i ••*
i 8 10 12
distance Irom Point Source
•
•
-
1
(km
4
)
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).
Nutrient Criteria-Wetlands
8-5
-------
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, 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.
8-6 Nutrient Criteria-Wetlands
-------
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APPENDIX A.
ACRONYM LIST AND GLOSSARY
ACRONYM LIST
ACOE/ACE/COE - Army Corps of Engineers
AGNPS - Agricultural Nonpoint Source Pollution
model
AGP - Algal Growth Potential
ARS - Agricultural Research Service
BACI - Before/After, Control/Impact
BMP - Best Management Practice
BPJ - Best Professional Judgement
BuRec - Bureau of Reclamation
CART - Classification and Regression Tree
CCC - Commodity Credit Corporation
CENR - Committee for the Environment and Natural
Resources
CGP - Construction General Permit
CHN - Carbon-Hydrogen-Nitrogen
COE - U.S. Army Corps of Engineers
CPGL - Conservation of Private Grazing Land
CPP - Continuing Planning Process
CREP - Conservation Reserve Enhancement Program
CRP - Conservation Reserve Program
CSFFCP - Central Florida Flood Control Project
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 - Euclidean Distance
EDAS - Ecological Data Application System
Eh - Redox potential
EMAP - Environmental Monitoring and Assessment
Program
EPA - U.S. Environmental Protection Agency
EQIP - Environmental Quality Incentive Program
FDEP - Florida Department of Environmental
Protection
FIP - Forestry Incentive Program
GIS - Geographic Information System
GPS - Geospatial Positioning System
GRTS - Generalized Random Tessellation Stratified
GWLF - Generalized Watershed Loading Function
HBN - Hydrologic Benchmark Network
HEL - Highly erodible land
HGM - Hydrogeomorphic approach
HSPF - Hydrologic Simulation Program - Fortran
HUC - Hydrologic Unit Codes
IBI - Index of Biotic Integrity
ICI - Invertebrate Community Index
LNWR - Loxahachee National Wildlife Refuge
LTER - Long Term Ecological Research
MPCA - Minnesota Pollution Control Agency
N - Nitrogen
NAAQS - National Ambient Air Quality Standard
NASQAN - National Stream Quality Assessment
Network
NAWQA - National Water Quality Assessment
NHD - National Hydrology Dataset
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
NWIS - National Water Information Systems
OH EPA - Ohio EPA
ONRW - Outstanding Natural Resource Waters
P - Phosphorus
PCB - Polychlorinated biphenyls
PCS - Permit Compliance System
PIP - Particulate inorganic phosphorus
POP - Particulate organic phosphorus
PSA - Particle size analysis
PSc - Percent Community Similarity
QA - Quality Assurance
QA/QC - Quality Assurance/Quality Control
QC - Quality Control
REMAP - Regional Environmental Monitoring and
Assessment Program
RF3 - Reach File 3
RTAG - Regional Technical Assistance Group
SCS - Soil Conservation Service
Nutrient Criteria-Wetlands
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SPARROW - Spatially Referenced Regressions on Watersheds
SRP - Soluble reactive phosphorus
STORET - Storage and Retrieval System
SWAT - Soil and Water Assessment Tool
SWLH - Superior Quality Wetland Habitat
TALU - Tiered Aquatic Life Use
TKN - Total Kjeldahl Nitrogen
TMDL - Total Maximum Daily Load
TP - Total Phosphorus
UAA - Use Attainability Analysis
USDA - United States Department of Agriculture
USEPA - United States Environmental Protection Agency
USFWS - United States Fish and Wildlife Service
USGS - United States Geological Survey
WCA - Water Conservation Area
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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GLOSSARY
aquatic ecoregion
Level II ecoregions defined by Omernik according to expected similarity in attributes affecting nutrient supply.
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.
(USEPA1994).
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
Uses defined in water quality standards for each waterbody or segment whether or not the use is being attained
(USEPA1994).
detritus
Unconsolidated sediments comprised of both inorganic and dead and decaying particulate 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.
ecoregion
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)
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HGM, hydrogeomorphic
Land form characterized by a specific origin, geomorphic setting, water source, and hydrodynamic (NDWP 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%" (Cowardin et 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 SAV-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.
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mixohaline
Water with salinity of 0.5 to 30%, due to ocean salts.
molarity
Molarity, moles of an element as concentration
multivariate
Type of statistics that relates one or more independent (explanatory) variables with multiple dependent (response)
variables.
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 et al. 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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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 wet lands; 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/
owow/wetlands/pdf/RapanosGuidance6507.pdf, http://www.epa.gov/owow/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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APPENDIX B.
CASE STUDY: DERIVING A PHOSPHORUS CRITERION FOR THE FLORIDA
EVERGLADES
INTRODUCTION
The Everglades (Figure Bl.l) 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 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
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FLORIDA
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 3A, 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.
B-2
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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 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 m2 yl (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.
Nutrient Criteria-Wetlands B-3
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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 ug I/1, with lowest concentrations
occurring in southern areas that have been least affected by anthropogenic P loads (Figure B1.2). Phosphorus
concentrations >10 ug L ' 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 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 cm3, whereas soils that have
been subjected to extended dry out and oxidation can have bulk densities greater than 0.2 g cm3 (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 ug cm3 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 ug TP cm3
(Newman etal. 1997).
Water-column TP (ug/L)
0 I
O O t
8
$
£_
§
a
I
s
LNWR
WCA2A WCA3A
Hydrologlc Unit
8
t
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 ug I/1).
B-4
Nutrient Criteria-Wetlands
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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 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.
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
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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 ' 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
PDF 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 advena) (Loveless 1959; Gunderson 1994).
Submerged aquatic plants, primarily bladderworts (Utricularia foliosa 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.
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
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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.
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 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 3A
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.
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 regimen
Nutrient Criteria-Wetlands B-7
-------
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 PHOSPOROUS 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 jo,g L ' as
compared with reference and pre-disturbance concentrations < 10 jo,g L ' . 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 WCA-2A, 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' 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
(Reddyetal. 1998).
Ecological Responses to Phosphorous 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
150
120 -
C
E
_3
O
u
1_
OJ
*-«
re
2 4 6 8 10 12
Distance from canal (km)
14
16
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.
B-8
Nutrient Criteria-Wetlands
-------
(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 photo synthetic
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 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 (o,g I/1) was replaced by a filamentous green algal
assemblage at moderately elevated concentrations (TP = 10 to 28 jo,g I/1) and by eutrophic cyanobacteria and
diatoms species at even higher concentrations (TP = 42 to 134 jo,g I/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).
COMMUNITY METABOLISM AND DISSOLVED OXYGEN CONCENTRATIONS
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 ' compared with concentrations as high as 12 mg L ' 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 jo,g I/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
Nutrient Criteria-Wetlands B-9
-------
s,
a.
°
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).
^ WCA-2A LNWR
inimum DO (mg/L) Frequency <1 mg/L
:> ro -£t oioooro ^01 o
Mean DO (mg/L) M
o s s a i e
8 r2 = 0.712
p < 0.001
&
%°0
&
°/ °
°i$^ ;„ - °o
r^ 0.615
p < 0.001
9j
0
tf
^g%Jw* rfb
r2 = 0.692
0 p < 0.001
o
o°8° * o
*» 0"
0 o
o° o °
o o
o r2 = 0.314
00 P = °-OM
0° °
n
-------
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).
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 jo,g I/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~l. As discussed by McCormick et al., (2002), loss of these open-water areas
is a sensitive landscape indicator of P enrichment (Figure B1.6).
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 jo,g I/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 jo,g
L"1.
Nutrient Criteria-Wetlands B-11
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ESTABLISHING A PHOSPHOROUS 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 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 jo,g L ' 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 jo,g L ' TP over the long-term, while five-year average concentrations should not
exceed 10 jo,g L ' 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.
B-12 Nutrient Criteria-Wetlands
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0)
TS
C
0)
Q.
O
"c
0)
O
0)
Q.
4 6 8 10 12
Distance from canal (km)
14
16
c
E
_3
O
O
<5
Appendix Bl. 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
Nutrient Criteria-Wetlands
B-13
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