United States 

Environmental Protection 

Agency 

Office of Water 

Office of Science and Technology 

Washington, DC 20460 

EPA-822-R-07-004 

September 2007 

www.epa.gov

 

Nutrient Criteria 

Technical Guidance Manual 

Wetlands 
ii 

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 overenrichment. Under the CWA, States and Authorized Tribes are directed to establish water quality 

criteria to protect designated uses. States and Authorized Tribes may use approaches for 

establishing water quality criteria that differ from those recommended in this guidance. This 

manual constitutes EPA’s scientific recommendations regarding the development of numeric 

criteria reflecting ambient concentrations of nutrients that protect aquatic life. However, it does 

not substitute for the CWA or EPA’s regulations; nor is it a regulation itself. Thus, it cannot 

impose legally binding requirements on EPA, States, Authorized Tribes, or the regulated 

community, and might not apply to a particular situation or circumstance. Further, States and 

Authorized Tribes may choose to develop different types of criteria for wetlands protection, 

including narrative criteria. EPA may change this guidance in the future. 
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TABLE OF CONTENTS 

CONTRIBUTORS.................................................................................................................................................... vii

ACKNOWLEDGMENTS....................................................................................................................................... viii

LIST OF FIGURES ....................................................................................................................................................ix

LIST OF TABLES .......................................................................................................................................................x

LIST OF INTERNET LINKS/REFERENCES ........................................................................................................xi

EXECUTIVE SUMMARY .........................................................................................................................................1

Chapter 1 Introduction.....................................................................................................................................5

1.1 INTRODUCTION.........................................................................................................................................5

1.2 WATER QUALITY STANDARDS AND CRITERIA ..............................................................................6

1.3 NUTRIENT ENRICHMENT PROBLEMS ...............................................................................................8

1.4 OVERVIEW OF THE CRITERIA DEVELOPMENT PROCESS........................................................11

1.5 ROADMAP TO THE DOCUMENT.........................................................................................................12

Chapter 2 Overview of Wetland Science.......................................................................................................15

2.1 INTRODUCTION.......................................................................................................................................15

2.2 COMPONENTS OF WETLANDS............................................................................................................17

2.3 WETLAND NUTRIENT COMPONENTS...............................................................................................22

Chapter 3 Classification of Wetlands............................................................................................................30

3.1 INTRODUCTION.......................................................................................................................................30

3.2 EXISTING WETLAND CLASSIFICATION SCHEMES......................................................................31

3.3 SOURCES OF INFORMATION FOR MAPPING WETLAND CLASSES.........................................43

3.4 DIFFERENCES IN NUTRIENT REFERENCE CONDITION OR SENSITIVITY TO NUTRIENTS 

AMONG WETLAND CLASSES.........................................................................................................................46

3.5 RECOMMENDATIONS............................................................................................................................47

Chapter 4 Sampling Design for Wetland Monitoring..................................................................................51

4.1 INTRODUCTION.......................................................................................................................................51

4.2 CONSIDERATIONS FOR SAMPLING DESIGN ..................................................................................52

4.3 SAMPLING PROTOCOL .........................................................................................................................57

4.4 SUMMARY....................................................................................................................................................63

Chapter 5 Candidate Variables for Establishing Nutrient Criteria...........................................................65

5.1 OVERVIEW OF CANDIDATE VARIABLES ........................................................................................65

5.2 SUPPORTING VARIABLES ....................................................................................................................67

5.3 CAUSAL VARIABLES ..............................................................................................................................70

5.4 RESPONSE VARIABLES .........................................................................................................................76

Chapter 6 Database Development and New Data Collection......................................................................82

6.1 INTRODUCTION.......................................................................................................................................82

6.2 DATABASES AND DATABASE MANAGEMENT ...............................................................................82

6.3 QUALITY OF HISTORICAL AND COLLECTED DATA ...................................................................86

6.4 COLLECTING NEW DATA.....................................................................................................................89

6.5 QUALITY ASSURANCE / QUALITY CONTROL (QA/QC) ...............................................................91

Chapter 7 Data Analysis.................................................................................................................................92

7.1 INTRODUCTION.......................................................................................................................................92

7.2 FACTORS AFFECTING ANALYSIS APPROACH ..............................................................................92

7.3 DISTRIBUTION-BASED APPROACHES ..............................................................................................94

7.4 RESPONSE-BASED APPROACHES.......................................................................................................95

7.5 PARTITIONING EFFECTS AMONG MULTIPLE STRESSORS.......................................................97

7.6 STATISTICAL TECHNIQUES....................................................................................................................98

7.7 LINKING NUTRIENT AVAILABILITY TO PRIMARY PRODUCER RESPONSE......................102

Chapter 8 Criteria Development .................................................................................................................104
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8.1 INTRODUCTION.....................................................................................................................................104

8.2 METHODS FOR DEVELOPING NUTRIENT CRITERIA ................................................................105

8.3 EVALUATION OF PROPOSED CRITERIA........................................................................................111

REFERENCES ......................................................................................................................................................113

APPENDIX A. ACRONYM LIST AND GLOSSARY.......................................................................................155

ACRONYMS .......................................................................................................................................................155

GLOSSARY.........................................................................................................................................................157

APPENDIX B. CASE STUDY: DERIVING A PHOSPHORUS CRITERION FOR THE FLORIDA 

EVERGLADES....................................................................................................................................................161
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CONTRIBUTORS 

Nancy Andrews (U.S. Environmental Protection Agency) 

Mark Clark (University of Florida) 

Christopher Craft (University of Indiana) 

William Crumpton (Iowa State University) 

Ifeyinwa Davis (U.S. Environmental Protection Agency) 

Naomi Detenbeck (U.S. Environmental Protection Agency) 

Paul McCormick (U.S. Geological Survey) 

Amanda Parker (U.S. Environmental Protection Agency)* 

Kristine Pintado (Louisiana Department of Environmental Quality) 

Steve Potts (U.S. Environmental Protection Agency) 

Todd Rasmussen (University of Georgia) 

Ramesh Reddy (University of Florida) 

R. Jan Stevenson (Michigan State University) 

Arnold van der Valk (Iowa State University) 

*Principal Author 
SEPTEMBER 2007 

viii 

ACKNOWLEDGMENTS 

The authors wish to acknowledge the efforts and input of several individuals. These include 

members of our EPA National Nutrient Team: Jim Carleton, Lisa Larimer, and Robert Cantilli; 

members of the EPA Wetlands Division: Kathy Hurld, Chris Faulkner and Donna Downing; 

members of the Office of Research and Development and their Office of Science Policy: Valerie 

Chan, Joseph Schubauer-Berigan, Charles Lane, John Morrice, Christine Weilhoefer, Tony 

Olsen, and Walt Nelson; the Office of General Counsel: Leslie Darman. We also want to thank 

Kristine Pintado (DEQ, Louisiana) for her contributions and her careful review and comments. 

This document was peer reviewed by a panel of expert scientists. The peer review charge 

focused on evaluating the scientific validity of the processes and techniques for developing 

nutrient criteria described in the guidance. The peer review panel comprised Dr. Robert H. 

Kadlec, Dr. Lawrence Richards Pomeroy, Dr. Eliska Rejmankova and Dr. Li Zhang. Edits and 

suggestions made by the peer review panel were incorporated into the final version of the 

guidance. 
SEPTEMBER 2007 

ix 

LIST OF FIGURES 

Figure 1.1 Flowchart providing the steps of the process to develop wetland nutrient 

 criteria 

Figure 2.1 Schematic of nutrient transfer among potential system sources and sinks

Figure 2.2 Relationship between water source and wetland vegetation. Modified from 

Brinson (1993) 

Figure 2.3 Schematic showing basic nutrient cycles in soil-water column of a wetland 

Figure 2.4 Range of redox potentials in wetland soils 

Figure 2.5 Schematic of the nitrogen cycle in wetlands 

Figure 2.6 Schematic of the phosphorus cycle in wetlands 

Figure 3.1 Map of Omernik aquatic ecoregions 

Figure 3.2a Map of Bailey ecoregions with coastal and estuarine provinces 

Figure 3.2b Legend (of Map of Bailey ecoregions with coastal and estuarine provinces) 

Figure 3.3 Examples of first four hierarchical levels of Ecological Units 

Figure 3.4 (Top) Cowardin hierarchy of habitat types for estuarine systems 

Figure 3.5 Dominant water sources to wetlands, from Brinson 1993 

Figure 3.6 Dominant hydrodynamic regimes for wetlands based on flow pattern 

Figure 3.7 Interaction with break in slope with groundwater inputs to slope wetlands 

 (Bottom) Palustrine systems, from Cowardin et al., 1979 

Figure 5.1 Conceptual model of causal pathway between human activities and ecological 

attributes 

Figure 7.1 Biological condition gradient model describing biotic community condition as 

levels of stressors increase

Figure 8.1 Use of undisturbed wetlands as a reference for establishing criteria versus an 

effects-based approach

Figure 8.2 Tiered aquatic life use model used in Maine 

Figure 8.3 Percent calcareous algal mat cover in relation to distance from the P source 

showing the loss of the calcareous algal mat in those sites closer to the source 
SEPTEMBER 2007 

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LIST OF TABLES 

Table 1 Observed consequences of cultural eutrophication in freshwater wetlands 

Table 2 Comparison of landscape and wetland classification schemes 

Table 3 Features of the major hydrogeomorphic classes of wetlands that may 

 influence background nutrient concentrations, sensitivity to nutrient loading, 

 nutrient storage forms and assimilative capacity, designated use and choice 

 of endpoints 

Table 4 Comparison of Stratified Probabilistic, Targeted, and BACI Sampling Designs 
SEPTEMBER 2007 

xi 

LIST OF INTERNET LINKS/REFERENCES 

Chapter 1 http://www.epa.gov/waterscience/criteria/nutrient/guidance/index.html

http://www.epa.gov/owow/wetlands

 http://www.epa.gov/waterscience/criteria/nutrient/strategy.html. 

 http://www.epa.gov/owow/wetlands/initiative 

 http://www.dep.state.fl.us/legal/Rules/shared/62-302/62-302.pdf

 

Chapter 2 http://www.arl.noaa.gov/research/programs/airmon.html

 http://nadp.sws.uiuc.edu/

Chapter 3 http://www.epa.gov/emap/remap/index.html 

 http://www.epa.gov/bioindicators/

 http://www.epa.gov/waterscience/standards/nutrient.html

 http://el.erdc.usace.army.mil/wetlands/pdfs/wrpde9.pdf 

 http://water.usgs.gov/GIS/metadata/usgswrd/XML/ecoregion.xml 

 http://www.nwi.fws.gov

 http://www.wes.army.mil/el/wetlands

 http://www.epa.gov/waterscience/criteria/wetlands/7Classification.pdf

 http://www.epa.gov/waterscience/criteria/wetlands/17LandUse.pdf

Chapter 4 http://www.epa.gov/waterscience/criteria/wetlands/index.html

 http://www.epa.gov/owow/wetlands/bawwg/case/me.html

 http://www.epa.gov/owow/wetlands/bawwg/case/mtdev.html 

 http://www.epa.gov/owow/wetlands/bawwg/case/wa.html 

http://www.epa.gov/owow/wetlands/bawwg/case/fl1.html

http://www.epa.gov/owow/wetlands/bawwg/case/fl2.html

http://www.epa.gov/owow/wetlands/bawwg/case/oh1.html

http://www.epa.gov/owow/wetlands/bawwg/case/mn1.html

http://www.epa.gov/owow/wetlands/bawwg/case/or.html

http://www.epa.gov/owow/wetlands/bawwg/case/wi1.html

Chapter 5 http://www.epa.gov/waterscience/criteria/wetlands/10Vegetation.pdf 

 http://www.epa.gov/waterscience/criteria/wetlands/11Algae.pdf

 http://www.epa.gov/waterscience/criteria/wetlands/9Invertebrate.pdf

 http://www.epa.gov/waterscience/criteria/wetlands/16Indicators.pdf

Chapter 6 http://www.nps.ars.usda.gov/programs/nrsas.htm

 http://www.fs.fed.us/research/ 

 http://www.usbr.gov
SEPTEMBER 2007 

xii 

Chapter 7 http://el.erdc.usace.army.mil/wrap/wrap.html 

http://firehole.humboldt.edu/wetland/twdb.html

 http://www.socialresearchmethods.net/

 http://www.math.yorku.ca/SCS/ 

 http://calculators.stat.ucla.edu/powercalc/

 http://www.surveysystem.com/sscalc.htm

 http://www.health.ucalgary.ca/~rollin/stats/ssize/index.html 

 http://www.stat.ohio-state.edu/~jch/ssinput.html 

 http://www.stat.uiowa.edu

 http://www.epa.gov/waterscience/criteria/wetlands 

Chapter 8 http://www.epa.gov/waterscience/biocriteria/modules/wet101-05-alusmonitoring.pdf

 http://www.epa.gov/owow

 http://www.wetlandbiogeochemistry.lsu.edu/

 http://data.lca.gov/Ivan6/app/app_c_ch9.pdf
SEPTEMBER 2007 Executive Summary 

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EXECUTIVE SUMMARY

The purpose of this document is to provide scientifically defensible guidance to assist States, 

Authorized Tribes, Territories, and other authorized jurisdictions—hereafter referred to as States 

—in assessing the nutrient status of their wetlands, and to provide technical assistance for 

developing numeric nutrient criteria for wetland systems in an eco-region. The development of 

nutrient criteria is part of an initiative by the U.S. Environmental Protection Agency (USEPA) to 

address the problem of cultural eutrophication, i.e., nutrient pollution caused by human activities 

(USEPA 1998a). Cultural eutrophication is not new; however, traditional efforts at nutrient 

control have been only moderately successful. Specifically, efforts to control nutrients in water 

bodies that have multiple nutrient sources (point and nonpoint sources) have been less effective 

in providing satisfactory, timely remedies for enrichment-related problems. Development and 

adoption of numeric criteria into water quality standards aids nitrogen and phosphorus pollution 

control efforts by providing clear numeric goals for water quality protection. Furthermore, 

numeric nutrient criteria provide specific water quality goals that will assist researchers in 

designing improved best management practices. 

In 1998, the USEPA published a report entitled, National Strategy for the Development of 

Regional Nutrient Criteria (USEPA 1998a). This report outlines a framework for development 

of waterbody-specific technical guidance that can be used to assess nutrient status and develop 

region-specific numeric nutrient criteria. The document presented here is the wetland-specific 

technical guidance for developing numeric nutrient criteria. The Nutrient Criteria Technical 

Guidance Manuals for Rivers and Streams (USEPA, 2000b), Lakes and Reservoirs (USEPA, 

2000a) and Estuarine and Coastal Marine Waters (USEPA, 2001) have been completed and are 

available at: http://www.epa.gov/waterscience/criteria/nutrient/guidance/index.html. 

Section 303(c) of the Clean Water Act directs States to adopt water quality standards for 

waters that are “waters of the United States,” including wetlands that are waters of the 

United States.1

 A water quality standard consists of three main elements: (1) one or more 

designated uses of each of the State’s waters, such as recreation or propagation of fish; 

(2) criteria expressed as pollutant concentration levels or narrative statements 

representing a quality of water that supports a designated use; and, (3) an antidegradation policy to protect existing uses and high quality waters. 

 

1

 For further information regarding the scope of ‘waters of the U.S.’ in light of the U.S. Supreme Court’s 2006 

decision in Rapanos v. United States, see “Clean Water Act Jurisdiction Following the U.S. Supreme Court's 

Decision in Rapanos v. United States & Carabell v. United States,” which was jointly issued by the U.S. 

Environmental Protection Agency and the Army Corps of Engineers and is available at: 

http://www.epa.gov/owow/wetlands/. 
SEPTEMBER 2007 Executive Summary 

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The information used in developing the technical approaches in this document came from 

references about studies of wetlands in a wide range of conditions, but not wetlands with 

a high degree of modification (e.g., wetlands that are considered “prior converted 

cropland” or artificial wetlands specifically engineered to protect or improve downstream 

water quality). This guidance is to assist States in developing numeric nutrient criteria for 

wetlands, should they choose to do so. States may choose to develop different types of 

criteria for wetlands protection, including site-specific or narrative criteria for wetlands 

protection, as long as they are scientifically defensible and protective of the designated 

uses (40 CFR § 131.11). This Guidance Manual includes chapters dealing with the 

following topics: 

CLASSIFICATION OF WETLANDS 

Classification strategies for nutrient criteria development include: 

y physiographic regions 

y hydrogeomorphic class 

y water depth and duration 

y 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: 

y probabilistic sampling 

y targeted/tiered approach 

y 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. 
SEPTEMBER 2007 Executive Summary 

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CANDIDATE VARIABLES FOR ESTABLISHING NUTRIENT CRITERIA

Candidate variables to use in determining nutrient condition of wetlands and to help identify 

appropriate nutrient criteria for wetlands consist of supporting variables, causal variables, and 

response variables. Supporting variables provide information useful in normalizing causal and 

response variables and categorizing wetlands. Causal variables are intended to characterize 

nutrient availability (or assimilation) in wetlands and could include nutrient loading rates and 

soil nutrient concentrations. Response variables are intended to characterize biotic response and 

could include community structure and composition of macrophytes and algae. Recommended 

variables for wetland nutrient criteria development described in this chapter are: 

1. Causal variables – nutrient loading rates, land use, extractable and total soil nitrogen (N) and 

phosphorus (P), water column N and P; 

2. Response variables – nutrient content of wetland vegetation (algal and/or higher plants), 

aboveground biomass and stem height, macrophyte, algal, and macroinvertebrate community 

structure and composition; and, 

3. Supporting variables – hydrologic condition/balance, conductivity, soil pH, soil bulk density, 

soil organic matter content. 

DATABASE DEVELOPMENT AND NEW DATA COLLECTION

A database of relevant water quality information can be an invaluable tool to States as they 

develop nutrient criteria. In some cases, existing data are available and can provide additional 

information that is specific to the region where criteria are to be set. However, little or no data 

are available for most regions or parameters, and creating a database of newly gathered data is 

strongly recommended. In the case of existing data, the data should be geolocated, and their 

suitability (type and quality and sufficient associated metadata) ascertained. 

DATA ANALYSIS

Data analysis is critical to nutrient criteria development. Proper analysis and interpretation of 

data determine the scientific defensibility and effectiveness of the criteria. Therefore, it is 

important to evaluate short and long-term goals for wetlands of a given class within the region of 

concern. The purpose of this chapter is to explore methods for analyzing data that can be used to 

develop nutrient criteria consistent with these goals. Techniques discussed in this chapter 

include: 

y Distribution-based approaches that examine distributions of primary and supporting 

variables (i.e., the percentile approach); 

y Response-based approaches that develop relationships between measurements of nutrient 

exposure and ecological responses (i.e., tiered aquatic life uses); 
SEPTEMBER 2007 Executive Summary 

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y Partitioning effects of multiple stressors; 

y Statistical techniques; 

y Multi-metric indices; and, 

y 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: 

y Comparing conditions in known reference systems for each established 

wetland type and class based on best professional judgment (BPJ) or 

identifying reference conditions using frequency distributions of empirical 

data and identifying criteria using percentile selections of data plotted as 

frequency distributions; 

y 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, 

y Using or modifying published nutrient and vegetation, algal, and soil 

relationships and values to identify appropriate criteria. 

A weight of evidence approach with multiple attributes that combine one or more of the 

development approaches will generally produce criteria of greater scientific validity. 

The purpose of this document is to provide guidance on developing numeric nutrient criteria in a 

scientifically valid manner, and is not intended to address the multiple, complex issues 

surrounding implementation of water quality criteria and standards. Implementation will be 

addressed in a different process and additional implementation assistance will also be provided 

through other technical assistance projects provided by EPA. For issues specific to constructed 

wetlands, States should refer to http://www.epa.gov/owow/wetlands/watersheds/cwetlands.html. 
SEPTEMBER 2007 Chapter 1. Introduction 

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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: 

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). 
SEPTEMBER 2007 Chapter 1. Introduction 

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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-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: 1) designating its specific 

uses, 2) setting criteria to protect those uses, and, 3) establishing an antidegradation policy to 

protect existing water quality. 

Designated uses are a State’s concise statements of its goals and expectations for each of the 

individual surface waters under its jurisdiction. With designated uses, States can work with their 

publics to identify a collective goal for their waters that they intend to strive for as they manage 

water quality. EPA encourages States to evaluate the attainability of these goals and expectations 

 

2

 EPA published guidance on water quality standards for wetlands in 1990 (USEPA, 1990c). 

Examples of different state approaches for standards can be found at: 

http://www.epa.gov/owow/wetlands/initiatives/.
SEPTEMBER 2007 Chapter 1. Introduction 

7 

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. 

 Acknowledge certain human caused conditions that limit the potential to support uses. 

Designated uses may involve a spectrum of expectations, depending on the type of wetland and 

associated hydropatterns, where the wetland is situated with respect to natural landscape features 

and human activity, and the historical and anticipated future functions that the wetland provides. 

Criteria to protect specific uses, in turn, should reflect these differing expectations where 

appropriate. The information used in developing the technical approaches in this document was 

drawn from references about studies of wetlands in a wide range of conditions, but not wetlands 

with a high degree of modification (e.g., wetlands that are considered “prior converted cropland” 

or artificial wetlands specifically engineered to protect or improve downstream water quality). 

Water quality criteria may be expressed as numeric values or narrative statements. As of this 

writing, most of the Nation’s waterbodies do not have numeric nutrient criteria, but instead rely 

on narrative criteria that describe the desired condition. Narrative criteria are descriptions of 

conditions necessary for a water to attain the designated uses. An example of a narrative criterion 

for nutrients is shown below: 

In no case shall nutrient concentrations of a body of water be altered so as to 

cause an imbalance in natural populations of aquatic flora or fauna. 

Numeric criteria, on the other hand, are values assigned to measurable components of water 

quality to protect designated uses, such as the concentration of a specific constituent that is 

present in the water column. An example of a numeric criterion for specific waters is shown 

below: 

(4) Phosphorus Criterion. 

(a) The numeric phosphorus criterion for Class III waters shall be a long-term 

geometric mean of 10 ppb, but shall not be lower than the natural conditions of 

the Class II waters, and shall take into account spatial and temporal variability. 

Achievement of the criterion shall be determined by the methods in this 

subsection. Exceedences of the provisions of the subsection shall not be 

considered deviations from the criterion if they are attributable to the full range of 

natural spatial and temporal variability, statistical variability inherent in sampling 

and testing procedures, or higher natural background conditions. 

In addition to narrative and numeric criteria, some States use numeric translator mechanisms—

mechanisms that translate narrative (qualitative) standards into numeric (quantitative) values for 

use in evaluating water quality data. Translator mechanisms may be useful internally by the State 
SEPTEMBER 2007 Chapter 1. Introduction 

8 

agency for water assessment and management and serve as an intermediate step between 

numeric and narrative criteria. 

Numeric criteria provide distinct interpretations of acceptable and unacceptable conditions, form 

the foundation for measurement of environmental quality, and reduce ambiguity for management 

and enforcement decisions. The lack of numeric nutrient criteria in State water quality standards 

for most of the Nation’s waterbodies makes it difficult to assess the condition of waters of the 

U.S. with respect to nutrients, and thus hampers the water quality manager’s ability to protect 

designated uses and improve water quality. EPA encourages States to adopt numeric nutrient 

criteria into their water quality standards (USEPA 2007b). 

Many States have adopted some form of nutrient criteria for surface waters related to 

maintaining natural conditions and avoiding nutrient enrichment. Most States with nutrient 

criteria in their water quality standards have broad narrative criteria for most waterbodies and 

may also have site-specific numeric criteria for certain waters of the State. Established criteria 

most commonly pertain to phosphorus (P) concentrations in lakes. Nitrogen (N) criteria, where 

they have been established, are usually protective of human health effects or relate to toxic 

effects of ammonia and nitrates. In general, levels of nitrate (10 ppm [mg/L] for drinking water) 

and ammonia high enough to be problematic for human health or toxic to aquatic life (1.24 mg 

N/L at pH = 8 and 25°C) will also cause problems of enhanced algal growth (USEPA 1986). 

Numeric nutrient criteria can provide a variety of benefits and may be used in conjunction with 

State and Federal biological assessments, Nonpoint Source Programs, Watershed 

Implementation Plans, and in development of Total Maximum Daily Loads (TMDLs) to improve 

resource management and support watershed protection activities at local, State, and national 

levels. Information obtained from compiling existing data and conducting new surveys can 

provide water quality managers and the public a better perspective on the condition of State 

waters. The compiled information can be used to most effectively budget personnel and financial 

resources for the protection and restoration of State waters. In a similar manner, data collected in 

the criteria development and implementation process can be compared before, during, and after 

specific management actions. Analyses of these data can determine the response of the wetland 

and the effectiveness of management endeavors. 

1.3 NUTRIENT ENRICHMENT PROBLEMS 

Water quality can be affected when watersheds are modified by alterations in vegetation, 

sediment transport, fertilizer use, industrialization, urbanization, or conversion of native forests 

and grasslands to agriculture and silviculture (Turner and Rabalais 1991; Vitousek et al., 1997; 

Carpenter et al., 1998). Cultural eutrophication, one of the primary factors causing impairment of 

U.S. surface waters (USEPA 1998a), results from point and nonpoint sources of nutrient 

pollution. Nonpoint source pollutant inputs have increased in recent decades and have degraded 
SEPTEMBER 2007 Chapter 1. Introduction 

9 

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 
SEPTEMBER 2007 Chapter 1. Introduction 

10 

types, including bogs, fens, Great Lakes coastal emergent marshes, and cypress swamps. The 

evidence of nutrient effects in wetlands ranges from controlled experimental manipulations, to 

trend or empirical gradient analysis, to anecdotal observations. Consequences of cultural 

eutrophication have been observed at both community and ecosystem-level scales (Table 1). 

Changes in wetland vegetation composition resulting from cultural eutrophication of these 

systems have been demonstrated in bogs (Kadlec and Bevis 1990), fens (Guesewell et.al., 1998, 

Bollens and Ramseier 2001, Pauli et.al., 2002), meadows (Finlayson et.al., 1986), marshes 

(Bedford et.al., 1999) and cypress domes (Ewel 1976). Specific effects on higher trophic levels 

in marshes seem to depend on trophic structure (e.g., presence/absence of minnows, benthivores, 

and/or piscivores, Jude and Pappas 1992, Angeler et.al., 2003) and timing/frequency of nutrient 

additions (pulse vs. press; Gabor et.al., 1994, Murkin et.al., 1994, Hann and Goldsborough 1997, 

Sandilands et.al., 2000, Hann et.al., 2001, Zrum and Hann 2002). 

Table 1. Observed consequences of cultural eutrophication in freshwater wetlands.3

Observed impact References 

Loss of submerged aquatic plants that have high 

light compensation points 

Phillips et.al., 1978 

Stephenson et.al., 1980 

Galatowitsch and van der Valk 1996 

Shifts in vascular plant species composition due to 

shifts in competitive advantage 

Wentz 1976 

Verhoeven et.al., 1988 

Ehrenfeld and Schneider 1993 

Gaudet and Keddy 1995 

Koerselman and Verhoeven 1995 

Increases in above-ground production Barko 1983 

Bayley et.al., 1985 

Barko and Smart 1986 

Vermeer 1986 

Decreases in local or regional biodiversity Mudroch and Capobianco 1979 

Guntenspergen et al., 1980 

Lougheed et.al., 2001 

Balla and Davis 1995 

VanGroenendael et.al., 1993 

Bedford et.al., 1999 

Increased competitive advantage of 

aggressive/invasive species 

(e.g., Typha glauca, T. latifolia and Phalaris

arundinacea)

Woo and Zedler 2002 

Svengsouk and Mitsch 2001 

Green and Galatowitsch 2002 

Maurer and Zedler 2002 

Loss of nutrient retention capacity (e.g., carbon and Nichols 1983 

 

3

 Similar impacts in tidal and estuarine wetlands have been documented, but are not included in this table. 
SEPTEMBER 2007 Chapter 1. Introduction 

11 

nitrogen storage, changes in plant litter 

decomposition) 

Davis and van der Valk 1983 

Rybczyk et.al., 1996 

Major structural shifts between “clear water” 

macrophyte dominated systems to turbid 

phytoplankton dominated systems or metaphytondominated systems with reduced macrophyte 

coverage 

McDougal et.al., 1997 

Angeler et.al., 2003 

Shifts in macroinvertebrate composition along a 

cultural eutrophication gradient 

Chessman et.al., 2002 

The cycling of nitrogen (N) and phosphorus (P) in aquatic systems should be considered when 

managing nutrient enrichment. The hydroperiod of wetland systems significantly affects nutrient 

transformations, availability, transport, and loss of gaseous forms to the atmosphere (Mitsch and 

Gosselink, 2000). Nutrients can be re-introduced into a wetland from the sediment, or by 

microbial transformation, potentially resulting in a long recovery period even after pollutant 

sources have been reduced. In open wetland systems, nutrients may also be rapidly transported 

downstream, uncoupling the effects of nutrient inputs from the nutrient source, and further 

complicating nutrient source control (Mitsch and Gosselink, 2000; Wetzel 2001). Recognizing 

relationships between nutrient input and wetland response is the first step in mitigating the 

effects of cultural eutrophication. When relationships are established, nutrient criteria can be 

developed to manage nutrient pollution and protect wetlands from eutrophication. 

1.4 THE CRITERIA DEVELOPMENT PROCESS 

The National Strategy for the Development of Regional Nutrient Criteria (USEPA 1998a) 

describes the principal elements of numeric nutrient criteria development. This document can be 

downloaded in PDF format at the Web site: 

http://www.epa.gov/waterscience/criteria/nutrient/strategy.html. The Strategy recognizes that a 

prescriptive, one-size-fits-all approach is not appropriate due to regional differences that exist 

and the scientific community’s current technical understanding of the relationship between 

nutrients, algal and macrophyte growth, and other factors (e.g., flow, light, substrata). The 

approach chosen for criteria development therefore may be tailored to meet the specific needs of 

each State. The 

EPA Strategy envisions a process by which State waters are initially monitored, reference 

conditions are established, individual waterbodies are compared to known reference waterbodies, 

and appropriate management measures are implemented. These measurements can be used to 

document change and monitor the progress of nutrient reduction activities and protection of 

water quality. 
SEPTEMBER 2007 Chapter 1. Introduction 

12 

The National Nutrient Program represents an effort and approach to criteria development that, in 

conjunction with efforts made by State water quality managers, will ultimately result in a 

heightened understanding of nutrient-response relationships. As the proposed process is put into 

use to set criteria, program success will be gauged over time through evaluation of management 

and monitoring efforts. A more comprehensive knowledge-base pertaining to nutrient, and 

vegetation and/or algal relationships will be expanded as new information is gained and 

obstacles overcome, justifying potential refinements to the criteria development process. 

The overarching goal of developing and adopting nutrient criteria is to protect and maintain the 

quality of our national waters. Protecting and maintaining water quality may include restoration 

of impaired systems, conservation of high quality waters, and protection of systems at high risk 

for future impairment. The specific goals of a State water quality program may be defined 

differently based on the needs of each State, but should, at a minimum, be established to protect 

the designated uses for the waterbodies within State lands. In addition, as numeric nutrient 

criteria are developed for the nation’s waters, States should revisit their goals for water quality 

and revise their water quality standards as needed. 

1.5 ROADMAP TO THE DOCUMENT 

As set out in Figure 1.1, the process of developing numeric nutrient criteria begins with defining 

the goals of criteria development and water quality standards adoption. Those goals are pertinent 

to the classification of systems, the development of a monitoring program, and the application of 

numeric nutrient criteria to permit limits and water quality protection. These goals therefore 

should be determined with the intent of revising and adapting them as new information is 

obtained and the paths to achieving those goals are clarified. Defining the goals for criteria 

development is the first step in the process. The summaries below describe each chapter in this 

document. The document is written to provide recommendations for a stepwise procedure for 

criteria development. Some chapters contain information that is not needed by some readers; the 

descriptions below should serve as a guide to the most relevant information for each reader. 

Chapter Two describes many of the functions of wetland systems and their role in the landscape 

with respect to nutrients. This chapter is intended to familiarize the reader with some basic 

scientific information about wetlands that will provide a better understanding of how nutrients 

move within a wetland and the importance of wetland systems in the landscape. 

Chapter Three discusses wetland classification and presents the reader with options for 

classifying wetlands based on system characteristics. This chapter introduces the scientific 

rationale for classifying wetlands, reviews some common classification schemes, and discusses 

their role in establishing nutrient criteria for wetlands. The classification of these systems is 

important to identifying their nutrient status and their condition in relation to similar wetlands. 
SEPTEMBER 2007 Chapter 1. Introduction 

13 

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 exposureresponse 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. 
SEPTEMBER 2007 Chapter 1. Introduction 

14 

Figure 1.1 Flowchart identifying the steps of the recommended process to develop wetland 

nutrient criteria. 
SEPTEMBER 2007 Chapter 2. Overview of Wetland Science 

15 

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). 
SEPTEMBER 2007 Chapter 2. Overview of Wetland Science 

16 

Figure 2.1. Schematic of nutrient transfer among potential system sources and sinks. 
SEPTEMBER 2007 Chapter 2. Overview of Wetland Science 

17 

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 precipitationdriven 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 nonwetland 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. 
SEPTEMBER 2007 Chapter 2. Overview of Wetland Science 

18 

GROUND WATER

PRECIPITATION

SURFACE FLOW

Riverine, 

Fringe, 

Tidal

Bogs, 

Pocosins

Fens, 

Seeps

0%

0%

0%

33%

33%

33%

67%

67%

67%

100%

100%

100%

Figure 2. Relationship between water source and wetland 

vegetation. Modified from Brinson (1993). 

 

Hydroperiod is highly variable depending on the type of wetland. Some wetlands that receive 

most of their water from precipitation (e.g., vernal pools) have very short duration hydroperiods. 

Wetlands that receive most of their water from surface flooding (e.g., floodplain swamps) often 

are flooded longer and to a greater depth than precipitation-driven wetlands. Fringe wetlands 

such as tidal marshes and mangroves are frequently flooded (up to twice daily) by astronomical 
SEPTEMBER 2007 Chapter 2. Overview of Wetland Science 

19 

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. 
SEPTEMBER 2007 Chapter 2. Overview of Wetland Science 

20 

Mineral wetland soils, in addition to containing greater amounts of sand, silt, and clay than 

histosols, are distinguished by changes in soil color that occur when elements such as Fe and 

manganese (Mn) are reduced by microorganisms under anaerobic conditions. Reduction of Fe 

leads to the development of grey or “gleyed” soil color as oxidized forms of Fe (ferric Fe, Fe3+) 

are converted to reduced forms (ferrous Fe, Fe+2). In sandy soils, development of a dark-colored, 

organic-rich surface layer is used to distinguish hydric soil from non-hydric (terrestrial) soil. An 

organic-rich surface layer, indicative of periodic inundation or saturation, is not sufficiently thick 

(<40 cm) to qualify as a histosol, which forms under near-continuous inundation. 

Wetland soils serve as sites for many biogeochemical transformations. They also provide long 

and short term storage of nutrients for wetland plants. Wetland soils are typically anaerobic 

within a few millimeters of the soil-water interface. Water column oxygen concentrations are 

often depressed due to the slow rate of oxygen diffusion through water. However, even when 

water column oxygen concentrations are supported by advective currents, high rates of oxygen 

consumption lead to the formation of a very thin oxidized layer at the soil-water interface. 

Similar oxidized layers can also be found surrounding roots of wetland plants. Many wetland 

plants are known to transport oxygen into the root zone, thus creating aerobic zones in 

predominantly anaerobic soil. The presence of these aerobic (oxidizing) zones within the 

reducing environment in saturated soils allows for the occurrence of oxidative and reductive 

transformations to occur in close proximity to each other. For example, ammonia is oxidized to 

nitrate within the aerobic zone surrounding plant roots in a process called nitrification. Nitrate 

then readily diffuses into adjacent anaerobic soil, where it is reduced to molecular nitrogen via 

denitrification or may be reduced to ammonium in certain conditions through dissimilatory 

nitrate reduction (Mitsch and Gosselink 2000; Ruckauf et al., 2004; Reddy and Delaune, 2005). 

The anaerobic environment hosts the transformations of N, P, sulfur (S), Fe, Mn, and C. Most of 

these transformations are microbially mediated. The oxidized soil surface layer also is important 

to the transport and translocation of transformed constituents, providing a barrier to translocation 

of some reduced constituents. These transformations will be discussed in more detail below in 

Biogeochemical Cycling. 

VEGETATION

Wetland plants consist of macrophytes and microphytes. Macrophytes include free-floating, 

submersed, floating-leaved, and rooted emergent plants. Microphytes are algae that may be free 

floating or attached to macrophyte stems and other surfaces. Plants require oxygen to meet 

respiration demands for growth, metabolism, and reproduction. In macrophytes, much (about 

50%) of the respiration occurs below ground in the roots. Wetland macrophytes, however, live in 

periodically to continuously-inundated and saturated soils and, therefore, use specialized 

adaptations to grow in anaerobic soils (Cronk and Fennessy 2001). Adaptations consist of 

morphological/anatomical adaptations that result in anoxia avoidance, and metabolic adaptations 

that result in true tolerance to anoxia. Morphological/anatomic adaptations include shallow roots 

systems, aerenchyma, buttressed trunks, pneumatophores (e.g., black mangrove (Avicennia 
SEPTEMBER 2007 Chapter 2. Overview of Wetland Science 

21 

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. 

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 
SEPTEMBER 2007 Chapter 2. Overview of Wetland Science 

22 

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 
SEPTEMBER 2007 Chapter 2. Overview of Wetland Science 

23 

instantaneous inflow (L/s) by the nutrient concentration (mg-nutrients/L). EPA recommends 

calculating the annual load by the summation of this function over the year—greater loads may 

be found during periods of increased flow and EPA recommends monitoring during these 

intervals. Where continuous data are unavailable, average flows and concentrations may be used 

if a bias factor (Cohn et al., 1989) is included to account for unmeasured loads during high 

flows. Particulate loads (mg-nutrients/yr) can be estimated using the product of suspended and 

bedload inputs (kg-sediments/yr) and the mass concentrations (mg-nutrients/kg-sediment). 

Surface-water nutrient inputs are associated with flows from influent streams, as well as diffuse 

sources from overland flow through the littoral zone. Ground-water inputs can also be 

concentrated at points (e.g., springs), or diffuse (such as seeps). The influence of allochthonous 

sources is likely to be greatest in those zones closest to the source. 

Because wetlands generally tend to be low-velocity, depositional environments, they often 

sequester sediments and their associated nutrients. These sediment inputs generally accumulate 

at or near the point of entry into the wetland, forming deltas or levees near tributaries, or along 

the shoreline for littoral inputs. Coarser fractions (e.g., gravels and sands) tend to settle first; the 

finer fractions (silts, clays, and organic matter) tend to settle further from the inlet point. 

Particulate input from ground-water sources can usually be neglected, while particulate inputs 

from atmospheric sources may be important if local or regional sources are present. 

Wetland nutrient outputs again mirror hydrologic outputs (e.g., surface- and ground-water), and 

loads are again estimated as the product of the flow and the concentration of nutrients in the 

flow. While evaporation losses from wetlands may be significant, there are no nutrient losses 

associated with this loss. Instead, loss of nutrients to the atmosphere may occur as a result of 

ammonia volatilization, as well as N2O losses from incomplete denitrification. Because sediment 

outputs from wetlands may be minor, nutrient exports by this mechanism may not be important. 

Nutrient accumulation in wetlands occurs when nutrient inputs exceed outputs. Net nutrient 

loads can be estimated as the difference between these inputs and outputs. It is important, 

therefore, to have some estimate of net accumulation by taking the difference between upstream 

and downstream loads. Sampling ground-water nutrient concentrations in wells located upstream 

and downstream of the wetland can provide some sense of net nutrient sequestration, while 

sampling wetland nutrient inflows and outflows is needed for determining the additional 

sequestration for this pathway. 

BIOGEOCHEMICAL 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 
SEPTEMBER 2007 Chapter 2. Overview of Wetland Science 

24 

simultaneously. The hydrology and geomorphology of wetlands (Johnston et.al., 2001) 

influences biogeochemical processes and constituent transport and transformation within the 

systems (e.g., water-sediment exchange, plant uptake, and export of organic matter). 

Interrelationships among hydrology, biogeochemistry, and the response of wetland biota vary 

among wetland types (Mitsch and Gosselink, 2000; Reddy and Delaune, 2005). 

Biogeochemical processes in the soil and water column are key drivers of several ecosystem 

functions associated with wetland values (e.g., water quality improvement through 

denitrification, long-term nutrient storage in the organic matter) (Figure 2.3). The hub for 

biogeochemistry is organic matter and its cycling in the soil and water column. Nutrients such as 

N, P, and S are primary components of soil organic matter, and cycling of these nutrients is 

always coupled to C cycling. Many processes occur within the carbon, nitrogen, phosphorus, and 

sulfur (C, N, P, or S) cycles; microbial communities mediate the rate and extent of these 

reactions in soil and the water column. 

Aerobic-anaerobic interfaces are more common in wetlands than in upland landscapes and may 

occur at the soil-water interface, in the root zones of aquatic macrophytes, and at surfaces of 

detrital tissue and benthic periphyton mats. The juxtaposition of aerobic and anaerobic zones in 

wetlands supports a wide range of microbial populations and associated metabolic activities, 

with oxygen reduction occurring in the aerobic interface of the substrate, and reduction of 

alternate electron acceptors occurring in the anaerobic zone (D’Angelo and Reddy, 1994a or b). 

Under continuously saturated soil conditions, vertical layering of different metabolic activities 

can be present, with oxygen reduction occurring at and just below the soil-floodwater interface. 

Substantial aerobic decomposition of plant detritus occurs in the water column; however, the 

supply of oxygen may be insufficient to meet demands and drive certain microbial groups to 

utilize alternate electron acceptors (e.g., nitrate, oxidized forms of iron (Fe) and manganese 

(Mn), sulfate, and bicarbonate (HCO3)). 

 
SEPTEMBER 2007 Chapter 2. Overview of Wetland Science 

25 

Figure 2.3 Schematic showing basic nutrient cycles in soil-water column of a wetland. 

Soil drainage adds oxygen to the soil, while other inorganic electron acceptors may be added 

through hydraulic loading to the system. Draining wetland soil accelerates organic matter 

decomposition due to the introduction of oxygen deeper into the profile. In many wetlands, the 

influence of 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 

Water

Soil

N C

S

P Bioavailable

nutrients

Periphyton

Emergent 

macrophyte

Submerged 

macrophyte
SEPTEMBER 2007 Chapter 2. Overview of Wetland Science 

26 

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). 

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 

-300 -100 0 300 100 500 700

Highly 

Reduced 

Reduced Moderately

Reduced

Oxidized 

Anaerobic Aerobic

Oxidation-Reduction Potential (mV) 
SEPTEMBER 2007 Chapter 2. Overview of Wetland Science 

27 

a gradient in quality and quantity of organic matter, nutrient accumulation, microbial and 

macrobiotic communities, composition, and biogeochemical cycles. 

Compared to terrestrial ecosystems, most wetlands show an accumulation of organic matter, and 

therefore wetlands function as global sinks for carbon. Accumulation of organic C in wetlands is 

primarily a result of the balance of C fixation through photosynthesis and losses through 

decomposition. Rates of photosynthesis in wetlands are typically higher than in other ecosystems, 

and rates of decomposition are typically lower due to anaerobic conditions, hence organic matter 

tends to accumulate. In addition to maintaining proper functioning of wetlands, organic matter 

storage also plays an important role in regulating other ecosystems and the biosphere. For example, 

organic matter contains substantial quantities of N, P, and S; therefore, accumulation of organic 

matter in wetlands decreases transport of these nutrients to downstream aquatic systems. 

NITROGEN (N):

Nitrogen enters wetlands in organic and inorganic forms, with the relative proportion of each 

depending on the input source. Organic forms are present in dissolved and particulate fractions, 

while inorganic N (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. 

Figure 2.5. Schematic of the nitrogen cycle in wetlands.

Organic 

Plant

uptake

Adsorbed NH4

+

NO3

-

Litterfall

Denitrification

Peat

accretion

Organic N

Nitrification Mineralization

Plant biomass 

[NH4

+

]s

NH4

+

[NH4

+

]s

NO3 NH4

NN2, N2O (g)

N2 N2O 

Microbial 

Biomass N 

NH3

Volatilization

N2

Nitrogen 

 Fixation 

Atmospheric 

Deposition 

Inflow Outflow

Water Column 

Soil - ANAEROBIC 

Soil - AEROBIC 
SEPTEMBER 2007 Chapter 2. Overview of Wetland Science 

28 

Nitrogen reactions in wetlands effectively process inorganic N through nitrification and 

denitrification, ammonia volatilization, and plant uptake. These processes aid in lowering levels 

of inorganic N in the water column. A significant portion of dissolved organic N assimilated by 

plants is returned to the water column during breakdown of detrital tissue or soil organic matter, 

and the majority of this dissolved organic N is resistant to decomposition. Under these 

conditions, water leaving wetlands may contain elevated levels of N in organic form. Exchange 

of dissolved nitrogen species between soil and water column support several nitrogen reactions. 

For example, nitrification in the aerobic soil layer is supported by ammonium flux from the 

anaerobic soil layer. Similarly, denitrification in the anaerobic soil layer is supported by nitrate 

flux from the aerobic soil layer and water column. Relative rates of these reactions will, 

however, depend on the environmental conditions present in the soil and water column (Reddy 

and Delaune 2007). 

PHOSPHORUS (P): 

Phosphorus retention by wetlands is regulated by physical (sedimentation and entrainment), 

chemical (precipitation and flocculation), and biological mechanisms (uptake and release by 

vegetation, periphyton, and microorganisms). Phosphorus in the influent water is found in 

soluble and particulate fractions, with both fractions containing a certain proportion of inorganic 

and organic forms. Relative proportions of these pools depend on the input source. For example, 

municipal wastewater may contain a large proportion (>75%) as inorganic P in soluble forms, as 

compared to effluents from agricultural watersheds where a greater percentage of P loading may 

be in the particulate fraction. 

Phosphorus forms that enter a wetland are grouped into: (i) dissolved inorganic P (DIP); (ii) 

dissolved organic P (DOP); (iii) particulate inorganic P (PIP); and, (iv) particulate organic P 

(POP) (Figure 2.6). The particulate and soluble organic fractions may be further separated into 

labile and refractory components. Dissolved inorganic P is generally bioavailable, whereas 

organic and particulate P forms generally must be transformed into inorganic forms before 

becoming bioavailable. Both biotic and abiotic mechanisms regulate relative pool sizes and 

transformations of P compounds within the water column and soil. Alterations in these fractions 

can occur during flow through wetlands and depend on the physical, chemical, and biological 

characteristics of the systems. Thus, both biotic and abiotic processes should be considered when 

evaluating P retention capacities of wetlands. Biotic processes include assimilation by 

vegetation, plankton, periphyton, and microorganisms. Abiotic processes include sedimentation, 

adsorption by soils, precipitation, and exchange processes between soil and the overlying water 

column (Reddy et.al., 1999, 2005; Reddy and Delaune, 2007). The processes affecting 

phosphorus exchange at the soil/sediment water interface include: (i) diffusion and advection due 

to wind-driven currents; (ii) diffusion and advection due to flow and bioturbation; (iii) processes 

within the water column (mineralization, sorption by particulate matter, and biotic uptake and 

release); (iv) diagenetic processes (mineralization, sorption, and precipitation dissolution) in 
SEPTEMBER 2007 Chapter 2. Overview of Wetland Science 

29 

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. 

Figure 2.6. Schematic of the Phosphorous cycle in wetlands. 

The key biogeochemical services provided by wetlands include nutrient transformation and 

removal by decreasing concentrations of nutrients and other contaminants, and sequestration of 

carbon and nutrients into stable pools (Kadlec and Knight 1996). The biogeochemical processes 

regulating water quality improvement are well established, and are made use of in treatment 

wetlands. Increased nutrient loading to oligotrophic wetlands results in increased primary 

productivity and nutrient enrichment. This resulting eutrophication can have both positive and 

negative impacts to the environment. Higher rates of primary productivity increase rates of 

organic matter accumulation, thus increasing carbon sequestration. However, eutrophication 

may lead to increased periodic and episodic export of DIP (Kadlec and Knight 1996; Reddy 

et.al., 1995, 1996, 2005; Reddy and Delaune 2007)). 

Water Column 

Soil - ANAEROBIC 

Peat

accretion

[Fe, Al or 

Ca-bound 

P] 

Adsorbed 

IP

Litterfall

DOP

Plant biomass P

DIP PIP POP

DIP

POP DOP

DOP

DIP 

DIP 

Outflow 

Periphyton 

Atmospheric 

Deposition 

Inflow 

Soil - AEROBIC 
SEPTEMBER 2007 Chapter 3. Classification of Wetlands 

30 

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. 
SEPTEMBER 2007 Chapter 3. Classification of Wetlands 

31 

REFERENCE CONCEPT

Reference conditions “describe the characteristics of waterbody segments least impaired by 

human activities and are used to define attainable biological or habitat conditions” (USEPA 

1990, Stoddard et.al., 2006). At least two general approaches have been defined to establish 

reference condition—the site-specific and the regional (U.S. EPA 1990b, 

http://www.epa.gov/bioindicators/). The current approach to developing water quality criteria for 

nutrients also emphasizes the identification of expected ranges of nutrients by waterbody type 

and ecoregion for the least-impaired reference conditions (U.S. EPA 1998, 

http://www.epa.gov/waterscience/standards/nutrient.html). 

Although different concepts of reference condition have been used in other programs (e.g., for 

evaluation of wetland mitigation projects (Smith et.al., 1995; 

http://el.erdc.usace.army.mil/wetlands/pdfs/wrpde9.pdf)), for the purposes of this document, the 

term “reference condition” refers to wetlands that are minimally or least impacted by human 

activities. Most, if not all, wetlands in the U.S. are affected to some extent by human activities 

such as acid precipitation, global climate change, or other atmospheric deposition of nitrogen 

and mercury, and changes in historic fire regime. “Minimally impacted” is therefore 

operationally defined by choosing sites with fewer stressors or fewer overall impacts as 

described by indicators of stressors, such as land-use or human activities within the watershed or 

buffer area surrounding a wetland and source inputs. Identifying reference wetlands in areas of 

high local or regional atmospheric deposition of nitrogen should also be carefully considered 

because indicators such as local land use activities may not be sufficient to indicate nutrient 

enrichment from dry or wet air deposition. 

3.2 EXISTING WETLAND CLASSIFICATION SCHEMES 

There are two different approaches for classification of aquatic resources. One is geographicallybased, and the other is independent of geography but relies on environmental characteristics that 

determine aquatic ecosystem status and vulnerability at the region-, watershed-, or ecosystemscale (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). 
SEPTEMBER 2007 Chapter 3. Classification of Wetlands 

32 

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. 
SEPTEMBER 2007 Chapter 3. Classification of Wetlands 

33 

Figure 3.1 Map of Omernik aquatic ecoregions.

Figure 3.2a. Map of Bailey ecoregions with coastal and estuarine provinces 

(Cowardin et al., 1979).
SEPTEMBER 2007 Chapter 3. Classification of Wetlands 

34 

Figure 3.2b. Legend
SEPTEMBER 2007 Chapter 3. Classification of Wetlands 

35 

Finally, an attempt has been made to integrate approaches across Federal agencies to produce 

regional boundaries termed Ecological Units (Keys et.al., 1995). Information has been combined 

on climate, landform, geomorphology, geology, soils, hydrology, and potential vegetation to 

produce a nested series of boundaries for the eastern U.S. Different combinations of 

environmental parameters are emphasized at each hierarchical level of classification. This 

scheme was developed to explain variation in both terrestrial and aquatic systems, and is 

consistent with a more comprehensive strategy to classify lotic systems down to the level of 

stream reaches (Maxwell et.al., 1995). The mapped system for the eastern U.S. includes 

classification at the following levels: 

domain (n=2) > divisions (n=5) > provinces (n=14) > sections (n=78) > subsections (n=xxx), 

where Sections are roughly half the size of Omernik ecoregions (Figure 3.3). For lotic systems, 

additional spatial detail can be added by defining watersheds (at the level of land type 

associations), subwatersheds (at the level of land types), valley segments, stream reaches, and, 

finally, channel units (Maxwell et.al., 1995). In reality, not all watersheds nest neatly within 

subsections, and may cross-subsection boundaries. 
SEPTEMBER 2007 Chapter 3. Classification of Wetlands 

36 

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 
SEPTEMBER 2007 Chapter 3. Classification of Wetlands 

37 

minimally-impacted sites. Efforts are currently underway to define ecoregions for Florida 

wetlands based on variables influencing the water budget and plant community composition 

(Dougherty et.al., 2000, Lane 2000). 

ENVIRONMENTALLY-BASED CLASSIFICATION SYSTEMS 

Wetland habitat types are described very simply but coarsely by Shaw and Fredine (1956, 

Circular 39), ranging from temporarily-flooded systems to ponds. A more refined hierarchical 

classification system is available based on vegetation associations; for example, the system 

developed by the Nature Conservancy for terrestrial vegetation includes some wetland types 

(Grossman et.al., 1998). Vegetation associations have also been used to classify Great Lakes 

coastal wetlands within coastal geomorphic type (Michigan Natural Features Inventory 1997). 

COWARDIN CLASSIFICATION SYSTEM

The Cowardin classification system (Cowardin et.al., 1979) was developed for the U.S. Fish and 

Wildlife Service (FWS) as a basis for identifying, classifying, and mapping wetlands, special 

aquatic sites, and deepwater aquatic habitats. The Cowardin system combines a number of 

approaches incorporating landscape position, hydrologic regime, and habitat (vegetative) type 

(http://www.nwi.fws.gov) (Figure 3.4). Wetlands are categorized first by landscape position 

(tidal, riverine, lacustrine, and palustrine), then by cover type (e.g., open water, submerged 

aquatic bed, persistent emergent vegetation, shrub wetlands, and forested wetlands), and then by 

hydrologic regime (ranging from saturated or temporarily-flooded to permanently flooded). 

Modifiers can be added for different salinity or acidity classes, soil type (organic vs. mineral), or 

disturbance activities (impoundment, beaver activity). Thus, the Cowardin system includes a 

mixture of geographically-based factors, proximal forcing functions (hydrologic regime, acidity), 

anthropogenic disturbance regimes, and vegetative outcomes. In practice, the Cowardin system 

can be aggregated by combination of hydrogeomorphic (HGM) type and predominant vegetation 

cover if digital coverages are available (Ernst et.al.,1995). 
SEPTEMBER 2007 Chapter 3. Classification of Wetlands 

38 

Figure 3.4. (Top) Cowardin hierarchy of habitat types for estuarine systems; 

(Bottom) Palustrine systems, from Cowardin et.al., 1979. 
SEPTEMBER 2007 Chapter 3. Classification of Wetlands 

39 

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. 

Figure 3.5. Dominant water sources to wetlands, from Brinson 1993. 
SEPTEMBER 2007 Chapter 3. Classification of Wetlands 

40 

Figure 3.6. Dominant hydrodynamic regimes for wetlands based on flow pattern (Brinson 1993). 

Depressional systems, as the name implies, are located in topographic depressions where surface 

water can accumulate. Depression wetlands can be further classified based on presence of inlets 

or outlets and primary water source as closed, open/groundwater, or open/surface water 

subclasses. 

Lacustrine fringe wetlands are located along lake shores where the water elevation of the lake 

determines the water table of the adjacent wetland. Great Lakes coastal wetlands represent one 

important region of lacustrine fringe wetlands. These coastal systems are strongly influenced by 

coastal forming processes, and, as such, have been further classified by geomorphic type through 

various schemes (Jaworski and Raphael 1979, and others summarized in Michigan Natural 

Features Inventory 1997). These geomorphic coastal positions will further influence the 

predominant source of water and the degree and type of energy regime (riverine vs. seiche and 

wave activity). Tidal fringe wetlands occupy a similar position relative to marine coasts and 

estuaries, where water level is influenced by sea level. Tidal fringe wetlands can be broken down 

further based on salinity into euhaline vs. mixohaline subclasses. Slope wetlands occur on slopes 

where groundwater discharges to the land surface, but typically do not have the capacity for 

surface water storage (Figure 3.7). Riverine wetlands are found in floodplains and riparian zones 

associated with stream channels. Riverine systems can be broken down based on watershed 

position (and, thus, hydrologic regime) into tidal, lower perennial, upper perennial, and 

nonperennial subclasses. Mineral soil flats are in areas of low topographic relief (e.g., 
SEPTEMBER 2007 Chapter 3. Classification of Wetlands 

41 

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. 

Figure 3.7. Interaction with break in slope with groundwater inputs to slope wetlands (Brinson 

1993). 

The HGM classification system is being further refined to the subclass level for different regions 

or States and classes (Cole et.al., 1997, http://www.wes.army.mil/el/wetlands). In addition to the 

classification factors described above, Clairain (2002) suggests using parameters such as the 

degree of connection between the wetland and other surface waters (depressional wetlands), 

salinity gradients (tidal), degree of slope or channel gradient (slope and riverine wetlands), 

position in the landscape (riverine, slope), and a scaling factor (stream order, watershed size or 

floodplain width for riverine subclasses). In some cases, existing regional schemes have been 

used as the basis for subclass definition (e.g., Stewart and Kantrud 1971, Golet and Larson 1974, 

Wharton et.al., 1982, Weakley and Schafale 1991, Keough et.al., 1999). 

The HGM classification system has been applied primarily to assess wetland functions related to 

hydrology, biological productivity, biogeochemical cycling, and habitat (Smith et.al., 1995, 

http://www.wes.army.mil/el/wetlands/pdfs/wrpde9.pdf). The same environmental parameters 

that influence wetland functions also determine hydrologic characteristics and background water 

quality, which in turn drive wetland habitat structure and community composition and the timing 

of biotic events. Thus, the HGM classification system can serve as a basis for partitioning 

variability in reference trophic status and biological condition, as well as defining temporal 

strategies for sampling. 
SEPTEMBER 2007 Chapter 3. Classification of Wetlands 

42 

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 crosswalk between riparian and wetland classification and description procedures. 
SEPTEMBER 2007 Chapter 3. Classification of Wetlands 

43 

COMBINATIONS OF GEOGRAPHIC AND ENVIRONMENTALLY-BASED APPROACHES

It is possible to combine geographically-based classification with hydrogeomorphic and/or 

habitat-based approaches. For example, a scheme could be defined that nests Cowardin 

(Cowardin et.al., 1979) vegetative cover class within HGM class within ecoregion. Maxwell 

et.al., (1995) have defined a scheme for linking geographically-based units based on geoclimatic 

setting (domains => divisions => provinces => sections => subsections) to watersheds and 

subwatersheds, and thus to riverine systems composed of valley segments, stream reaches, and 

channel units, or to lacustrine systems composed of lakes, lake depth zones, and lake 

sites/habitat types. 

Maxwell et.al., (1995) also define a series of fundamental hydrogeomorphic criteria for 

classifying wetlands based on Brinson (1993) and Winter (1992), including physiography 

(landscape position), water source, hydrodynamics, and climate. The first three of these are 

similar to the HGM classification system (see summary tables in Keys et.al., 1995). Finer scale 

variation in landforms is also discussed and may be of use in determining the dominance of 

different hydrogeomorphic classes of wetlands and associated surface waters (lakes and rivers). 

Characteristics and relative advantages and disadvantages of different classification systems are 

summarized in Table 3.2. 

3.3 SOURCES OF INFORMATION FOR MAPPING WETLAND CLASSES 

In order to select wetlands for sampling in a random- or random-stratified design (described in 

Chapter 4), it is important to have a record of wetland locations to choose from, preferably 

categorized by the classification system of interest. For some, but not all portions of the country, 

wetlands have been mapped from aerial photography through the National Wetlands Inventory 

(NWI) maintained by the U.S. Fish and Wildlife Service (http://www.fws.gov/nwi/; Dahl 2005). 

In other cases, individual States have developed inventories, or researchers have developed lists 

for specific types of wetlands within a given region, e.g., Great Lakes coastal wetlands 

(Herdendorf et.al., 1981). In order to sample these mapped wetland areas in a random fashion, it 

is important to have a list of each wetland that occurs within each class and its associated area. A 

geographic information system (GIS) allows one to automatically produce a list of all wetland 

polygons by type within a specified geographic region. Sources of digital information for 

mapping and/or classifying wetlands in a GIS are presented in the Land-Use Characterization for 

Nutrient and Sediment Risk Assessment Module 

(http://www.epa.gov/waterscience/criteria/wetlands/17LandUse.pdf). 
SEPTEMBER 2007 Chapter 3. Classification of Wetlands 

44 

Table 2. Comparison of landscape and wetland classification schemes. 

Classification scheme

Scale Hierarchical? Levels of strata Advantages Disadvantages 

Bailey’s ecoregions Nationwide Yes Domains 

Divisions Provinces Sections

Only natural 

attributes included 

Digital maps

Terrestrial basis Untested for wetlands No hydrology

C

Omernik ecoregions Nationwide No Ecoregions 

Subecoregions

Digital maps Combines land-use 

with natural attributes 

Untested for most 

wetlands 

No hydrology

C

Ecological units (Maxwell et.al.,1995)

Nationwide Yes Domain 

Divisions Provinces Sections Subsections

Digital maps Greater number of 

strata and units than for ecoregions 

Untested for wetlands

CT

US ACE Hydrogeomorphic Classes

Nationwide at class level; regionalized at subclass level

Yes - limited Class 

Subclass

Specific for 

wetlands

Subclasses not 

comparable across different regions

Rosgen channel types

Nationwide Yes Level I 

Level II

Captures 

differences in hydrologic regime for riverine wetlands

More focused on 

instream channel form than riparian characteristics 

Riverine only Not mapped
SEPTEMBER 2007 Chapter 3. Classification of Wetlands 

45 

Table 2. Comparison of landscape and wetland classification schemes. 

Classification scheme

Scale Hierarchical? Levels of strata Advantages Disadvantages 

Anderson land-cover classes

Nationwide Yes Level I 

Level II Level III

Common basis 

for landuse/landcover mapping

Not functionally based C

Circular 39 classes Nationwide No Class Popular 

recognition

Mixture of criteria used 

to distinguish classes 

Not mapped

S

National Wetland Inventory

Nationwide Yes System 

Subsystem Class Subclass Hydrologic modifier Other modifiers

Digital maps 

available for much of nation (but smallest wetlands omitted)

Inconsistencies in 

mapping water quality modifiers 

Limited consideration 

of hydrogeomorphic type

S

Vegetation associations 

International Yes System 

Formation class Formation subclass Formation group Formation subgroup Formation alliance Association 

Consistency 

across terrestrial and aquatic systems 

Not functionally based No digital maps Taxa specific 

C
SEPTEMBER 2007 Chapter 3. Classification of Wetlands 

46 

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 preselected 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. 
SEPTEMBER 2007 Chapter 3. Classification of Wetlands 

47 

Sensitivity to nutrient loading (as evidenced by differences in nutrient cycling and availability) 

may also be related to differences in hydroperiod among wetlands. Wetland mesocosms exposed 

to pulse discharges had higher nutrient loss from the water column than those exposed to 

continuous flow regimes (Busnardo et.al., 1992). Depending on the predominant mechanism for 

nutrient loss (e.g., plant uptake versus denitrification), nutrient-controlled primary production 

could be either stimulated or reduced. Mineralization rates of carbon, nitrogen, and phosphorus 

differ significantly among soils from northern Minnesota wetlands, related to an ombrotrophic to 

minerotrophic gradient (i.e., degree of groundwater influence), and aeration status (Bridgham 

et.al., 1998). 

In general, very few definitive tests of alternative classification schemes for wetlands are 

available with respect to describing reference condition for either nutrient criteria or biocriteria. 

However, evidence from the literature suggests that in many cases both geographic factors (e.g., 

climate, geologic setting) and landscape setting (hydrogeomorphic type) are expected to affect 

water quality and biotic communities. 

3.5 RECOMMENDATIONS 

Classification strategies for nutrient criteria development should incorporate factors affecting 

background nutrient levels and wetland sensitivity to nutrient loading at several spatial scales. 

• Classification of physiographic regions eliminates background variation in lithology and 

soil texture (affecting background nutrient levels and sorption capacity), in climate 

(affecting seasonality, productivity, decomposition, and peat formation), and in 

landforms, which determines the predominance of different hydrogeomorphic classes. 

• Classification by hydrogeomorphic class reduces background variation in predominant 

water and nutrient sources, water depth and dynamics, hydraulic retention time, 

assimilative capacity, and interactions with other surface water types (Table 3). 

• Classification by water depth and duration (which may or may not be incorporated into 

hydrogeomorphic classes) helps to explain variation in internal nutrient cycling, 

dissolved oxygen level and variation, and the ability of wetlands to support some higher 

trophic levels such as fish and amphibians. 

• Classification by vegetation type or zone, whether to inform site selection or to determine 

sampling strata within a site, helps to explain background variation in predominant 

primary producer form (which will affect endpoint selection), as well as turnover and 

growth rates (which will affect rapidity of response to nutrient loadings). 
SEPTEMBER 2007 Chapter 3. Classification of Wetlands 

48 

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. 
SEPTEMBER 2007 Chapter 3. Classification of Wetlands 

49 

Table 3. Features of the major hydrogeomorphic classes of wetlands that may influence background nutrient coto nutrient loading, nutrient storage forms and assimilative capacity, designated use and choice of endpoints.HGM Class Organic Flats Mineral Flats Depressional Riverine Fringe Predominant Nutrient Source(S)

Atmospheric Deposition

Atmospheric Deposition, Groundwater

Runoff (Particulate and Dissolved), Surface and Groundwater

Runoff (Particulate), Overbank Flooding (Particulate, Dissolved)

Adjacent LakePossible StreRiverine SourGroundwater

Landscape Position

Adjacent to Rivers Adjacent to La

Hydrologic Regime Saturated, Little 

Standing Water

Saturated, Little Standing Water

Depth and Duration Varyfrom Saturated to Temporary to Seasonal to SemiPermanent to Permanent Inundation

Depth, Duration Vary With River Flooding Regime

Standing WatEmergent and Submerged Aquatic ZoneShort-Term Fluctuation Related to SeActivity, LongTerm to Wet-DCycles

Hydraulic Retention Time

Decades Decades Varies With 

Inflows/Outflows, Landscape Position

<Day to Few Days < Day 

Nutrient Assimilation Capacity

Low High Sorption 

Capacity

High Sorption, Plant Uptake, (Limited) Sediment Storage 

High Sorption, Sediment Trapping, Plant Uptake In Floodplain

Some SedimeTrapping Nutrient Transformer
SEPTEMBER 2007 Chapter 3. Classification of Wetlands 

50 

Table 3. Features of the major hydrogeomorphic classes of wetlands that may influence background nutrient coto nutrient loading, nutrient storage forms and assimilative capacity, designated use and choice of endpoints.HGM Class Organic Flats Mineral Flats Depressional Riverine Fringe Predominant Vegetation Growth Form

Mosses Sedges

Sedges Varies With Zone 

And Duration of Flooding: Wooded Grass/Sedge Emergents Submerged Aquatics*

Wooded, Emergent Vegetation Submerged Aquatics*

Varies With ZGrass/Sedge Emergents Submerged Aquatics*

Top Trophic Level Mammals 

Birds Amphibians Invertebrates

Mammals Birds Amphibians Invertebrates

Mammals Birds Mudminnows Amphibians Invertebrates

Fish Birds Mammals

Fish Birds Mammals

CommerciallyImportant Fish/Wildlife

Waterfowl Fish* Waterfowl 

Fish*

Recreational Use Likely

Yes Yes Yes

Drinking Water Source Downstream

Possible Likely Possible

Table 3 cont’d. 
SEPTEMBER 2007 Chapter 4. Sampling Design of Wetland Monitoring 

51 

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 
SEPTEMBER 2007 Chapter 4. Sampling Design of Wetland Monitoring 

52 

assessment (e.g., Florida, Ohio, Oregon, and Minnesota). The synoptic approach described in 

Kentula et.al., (1993) uses a modified targeted sampling design. The BACI design and its 

modifications are frequently used to assess the success of restoration efforts or other 

management experiments. BACI design allows for comparisons in similar systems over time to 

determine the rate of change in relation to the management activity, e.g., to assess the success of 

a wetland hydrologic restoration. The BACI design, in particular, is included to assist States in 

evaluating ongoing management actions, and may provide less statistical rigor if adopted as a 

general monitoring program design. This design, however, is of considerable value in assessing 

restoration success and has been included at the request of States with ongoing wetland 

restoration. Detenbeck et.al., (1996) used BACI design for monitoring water quality of wetlands 

in the Minneapolis/St. Paul, Minnesota metro area. 

Monitoring programs should be designed to describe what the current conditions are and to 

answer under what conditions impairment may occur. A well-designed monitoring program can 

contribute to determining those conditions. 

Sampling design is dependent on the management question being asked. Sampling efforts 

should be designed to collect information that will answer the management question. For 

example, probabilistic sampling might be good for ambient (synoptic) monitoring programs, 

BACI for evaluating management actions such as restoration, and targeted sampling/stratified 

and random sampling for developing index of biotic integrity (IBIs) or nutrient criteria 

thresholds. In practice, some State programs likely will need to use a combination of approaches. 

4.2 CONSIDERATIONS FOR SAMPLING DESIGN 

DESCRIBING THE MANAGEMENT QUESTION

Clearly defining the question being asked (identifying the hypothesis) encourages the use of 

appropriate statistical analyses, reduces the occurrence of Type I (false positive) errors, and 

increases the efficient use of management resources (Suter 1993; Leibowitz et al., 1992; Kentula 

et al., 1993). Beginning a study or monitoring program with carefully defined questions and 

objectives helps to identify the statistical analyses most appropriate for the study and reduces the 

chance that statistical assumptions will be violated. Management resources are optimized 

because resources are directed at monitoring that which is most likely to answer management 

questions. In addition, defining the specific hypotheses to be tested, carefully selecting reference 

sites, and identifying the most useful sampling interval can help reduce the uncertainty 

associated with the results of any sampling design and further conserve management resources 

(Kentula et al., 1993). Protecting or improving the quality of a wetland system often depends on 

the ability of the monitoring program to identify cause-response relationships, for example, the 

relationship of nutrient concentration (causal variable) to nutrient content of vegetation or 

vegetation biomass (response variable). Cause-response relationships can be identified using 
SEPTEMBER 2007 Chapter 4. Sampling Design of Wetland Monitoring 

53 

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, Wetland module #17). There is 

often a lag in time between the causal stress and the response in the wetland system. This time 

lag between stress and response and the duration of this lag depends on many factors, including 

the type of stressor, climate, and system hydrology; these factors should be considered when 

selecting sites to establish the range of wetland quality within a region. 

LANDSCAPE CHARACTERIZATION

The synoptic approach described in Liebowitz et.al., (1992) provides a method of rapid 

assessment of wetlands at the regional and watershed levels that can help identify the range of 

wetland quality within a region. Liebowitz et.al., (1992) recommend an initial assessment for site 

selection based on current knowledge of watershed and landscape level features; modification of 

such an assessment can be made as more data are collected. Assessing watershed characteristics 

through aerial photography and the use of geographical information systems (GIS) linked to 

natural resource and land-use databases can aid in identifying reference and degraded systems 

(see the Land-Use Characterization for Nutrient and Sediment Risk Assessment, Wetland 

module #17); Johnston et al., 1988, 1990; Gwin et al., 1999; Palik et al., 2000; Brown and Vivas 

2004). Some examples of watershed characteristics which can be evaluated using GIS and aerial 
SEPTEMBER 2007 Chapter 4. Sampling Design of Wetland Monitoring 

54 

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 
SEPTEMBER 2007 Chapter 4. Sampling Design of Wetland Monitoring 

55 

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. Groundtruthing visits to reference wetlands are crucial for identification of ecological impairment that 

may not be apparent from land-use and local habitat conditions. Again, sufficient sample size is 

important to characterize the range of conditions that can be expected in the least impacted 

systems of the region (Detenbeck et.al., 1996). Reference wetlands should be identified for each 

ecoregion or geological province in the State lands and then characterized with respect to 

ecological integrity. A minimum of three low impact reference systems is recommended for each 

wetland class for statistical analyses. However, power analysis can be performed to determine 

the degree of replication necessary to detect an impact to the systems being investigated 

(Detenbeck et.al., 1996; Urquhart et.al., 1998). Highest priority should be given to identifying 

reference systems for those wetland types considered to be at the greatest risk from 

anthropogenic stress. 

WHEN TO SAMPLE

Sampling may be targeted to the periods when effects are most likely to be detected – the index 

period. The appropriate index period should be defined by what the investigator is trying to 

investigate and what taxonomic assemblage or parameters are being used for that investigation 

(Barbour et.al., 1999). For example, increased nutrient concentrations and sedimentation from 

non-point sources may occur following periods of high runoff during spring and fall, while point 

sources of nutrient pollutants may cause plankton blooms and/or increased water and soil 

nutrient concentrations in wetland pools during times of low rainfall. Hence, different index 

periods may be needed to detect effects from point source and nonpoint source nutrients, 

respectively. Each taxonomic assemblage studied also should have an appropriate index period—

usually in the growing season (see assemblage methods in the Maine case study: 

http://www.epa.gov/waterscience/criteria/wetlands/index.html). 

The index period window may be early in the growing season for amphibians and algae. Other 

assemblages, such as vegetation and birds, may benefit from a different sampling window for the 

index period; see the assemblage specific modules for recommendations. Once wetland 

condition has been characterized, one-time annual sampling during the appropriate index period 

may be adequate for multiple year monitoring of indicators of nutrient status, designated use, and 

biotic integrity. However, criteria and ecological indicator development may benefit from more 

frequent sampling to define conditions that relate to the stressor or perturbor of interest (Karr and 

Chu 1999; Stevenson 1996; Stevenson 1997). Regardless of the frequency of sampling, selection 
SEPTEMBER 2007 Chapter 4. Sampling Design of Wetland Monitoring 

56 

of index periods and critical review of the data gathered and analyzed should be done to 

scientifically validate the site characterization and index periods for data collection. 

Ideally, water quality monitoring programs produce long-term data sets compiled over multiple 

years to capture the natural, seasonal, and year-to-year variations in biological communities and 

constituent concentrations (e.g., Tate 1990; Dodds et.al., 1997; McCormick et.al., 1999; Craft 

2001; Craft et al., 2003; Zheng et al., 2004). Multiple-year data sets can be analyzed with 

statistical rigor to identify the effects of seasonality and variable hydrology. Once the pattern of 

natural variation has been described, the data can be analyzed to determine the ecological state of 

the wetland. Long-term data sets have also been important in influencing management decisions 

about wetlands, most notably in the Everglades, where long-term data sets have induced Federal, 

State, and Authorized Tribal actions for conservation and restoration of the largest wetland 

system in the U.S. (see Davis and Ogden 1994; Everglades Interim Report, South Florida Water 

Management District [SFWMD, 1999]; Everglades Consolidated Report [SFWMD, 2000, 2001]; 

1994 Everglades Forever Act, Florida Statute § 373.4592). 

In spite of the documented value of long-term data sets, there is a tendency to intensively study a 

wetland for one year before and one year after treatment. A more cost-effective approach may be 

to measure only the indices most directly related to the stressor of interest (i.e., those parameters 

or indicators that provide the best information to answer the specific management question), but 

to double or triple the monitoring period. Multiple years (two or more) of data are often needed 

to identify the effects of years with extreme climatic or hydrologic conditions. Comparisons over 

time between reference and at risk or degraded systems can help describe biological response 

and annual patterns in the presence of changing climatic conditions. Multi-year data sets also can 

help describe regional trends. Flooding or drought may significantly affect wetland biological 

communities and the concentrations of water column and soil constituents. Effects of uncommon 

climatic events can be characterized to discern the overall effect of management actions (e.g., 

nutrient reduction, water diversion) if several years of data are available to identify the long-term 

trends. 

At the very minimum, two years of data before and after specific management actions, but 

preferably three or more each, are recommended to evaluate the cost-effectiveness of 

management actions with some degree of certainty (USEPA 2000). If funds are limited, 

restricting sampling frequency and/or numbers of indices analyzed should be considered to 

preserve a longer-term data set. Reducing sampling frequency or numbers of parameters 

measured will allow for effectiveness of management approaches to be assessed against the high 

annual variability that is common in most wetland systems. Wetlands with high hydrological 

variation from year to year may benefit from more years of sampling both before and after 

specific management activities to identify the effects of the natural hydrologic variability 

(Kadlec and Knight 1996). 
SEPTEMBER 2007 Chapter 4. Sampling Design of Wetland Monitoring 

57 

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 onetime assessment of single samples. Re-sampling does not establish the precision of the 

assessment process, but rather identifies the precision of an individual measurement (Kentula 

et.al., 1993). 

Re-sampling frequency is often conducted for one wetland site in every block of 10 sites. 

However, investigators should adhere to the objectives of re-sampling (often considered an 

essential element of QA/QC) to establish an assessment of the variation in a one-time/sample 

assessment. Often, more than one in 10 samples should be replicated in monitoring programs to 

provide a reliable estimate of measurement precision (Barbour et.al., 1999). The reader should 

understand that this is a very brief description of the concerns about precision, and that any 

monitoring program or study involving monitoring should include consultation with a 

professional statistician before the program begins and regularly during the course of the 

monitoring program to assure statistical rigor. 

 

4.3 SAMPLING PROTOCOL 

APPROACHES TO SAMPLING DESIGN

The following sections discuss three different approaches to sampling design, probabilistic, 

targeted, and BACI. These approaches have advantages and disadvantages that under different 

circumstances warrant the choice of one approach over the other (Table 4). The decision as to 

the best approach for sample design in a new monitoring program should be made by the water 

quality resource manager or management team after careful consideration of the different 

approaches. For example, justification of a dose-response relationship is confounded by lack of 

randomization and replication and should be considered in choosing a sampling design for a 

monitoring program. 

PROBABILISTIC SAMPLING DESIGN FOR ASSESSING CONDITION

Probabilistic sampling – a sampling process wherein randomness is requisite (Hayek 1994) – can 

be used to characterize the status of water quality conditions and biotic integrity in a region’s 
SEPTEMBER 2007 Chapter 4. Sampling Design of Wetland Monitoring 

58 

wetland system. This type of sampling design is used to describe the average conditions of a 

wetland population, identify the variability among sampled wetlands, and help determine the 

range of wetland system conditions in a region. Data collected from a probabilistic random 

sample design generally will be characteristic of the dominant class or type of wetland in the 

region, but rare wetlands may be under-represented or absent from the probabilistically sampled 

wetlands. Additional sampling sites may need to be added to precisely characterize the complete 

range of wetland conditions and types in the region. 

Probabilistic designs are often modified by stratification (such as classification). Stratified 

random sampling is a type of probabilistic sampling where a target population is divided into 

relatively homogenous groups or classes (strata) prior to sampling based on factors that influence 

variability in that population (Hayek 1994). Stratification by wetland size and class or types 

ensures more complete information about different types of wetlands within a region. Sample 

statistics from random selection alone would be most characteristic of the dominant wetland type 

in a region if the population of wetlands is not stratified. 

Many State 305(b) and watershed monitoring programs utilize stratified random sampling 

designs, and we will further discuss this type of probabilistic sampling. Pilot projects in Maine, 

Montana, and Wisconsin all use stratified random sampling design. Details of these monitoring 

designs can be found in the Case Studies module #14 and on the Web at 

http://www.epa.gov/waterscience/criteria/wetlands/index.html. 

Stratification is based on identifying wetland systems in a region (or watershed) and then 

selecting an appropriate sample of systems from the defined population. The determination of an 

appropriate sample population usually is dependent on the management questions being asked. A 

sample population of isolated depressional wetlands could be identified as a single stratum, but 

investigations of these wetlands would not provide any information on riparian wetlands in the 

same region. If the goal of the monitoring program is to identify wetland condition for all 

wetland classes within a region, then a sample population of wetlands should be randomly 

selected from all wetlands within each class. In practice, most State programs stratify random 

populations by size, wetland class (see Chapter 3), and landscape characteristics or location (see 

http://www.epa.gov/waterscience/criteria/wetlands/index.html, module #14). 

Once the wetlands for each stratum have been identified, the list of wetlands can be used to 

select a spatially-balanced stratified random sample. Spatial-balance will ensure spatial coverage 

over the assessment region, usually increase the types of wetlands sampled (assuming classes of 

wetlands vary spatially), and reduce spatial autocorrelation among the sampled wetlands. For 

example, EMAP implements spatially-balanced samples using Generalized Random Tessellation 

Stratified (GRTS) designs applied to GIS coverages of wetlands within the assessment region. 

GRTS using a hierarchical grid randomization process to ensure the sites are spatially distributed 

(Paulsen et.al., 1991; Stevens and Olsen 2004). Estimates of ecological conditions from these 

kinds of modified probabilistic sampling designs can be used to characterize the water quality 
SEPTEMBER 2007 Chapter 4. Sampling Design of Wetland Monitoring 

59 

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/fl1.html). 

TARGETED DESIGN

A targeted approach to sampling design may be more appropriate when resources are limited 

(Stern 2004). The example of targeted sampling described here involves defining a gradient of 

impairment. Once the gradient has been defined and systems have been placed in categories of 

impairment, investigators focus the greatest efforts on identifying and characterizing wetland 

systems or sites likely to be impacted by anthropogenic stressors, and on relatively undisturbed 

wetland systems or sites (see Identifying and Characterizing Reference Systems, Chapter 3), that 

can serve as regional, sub-regional, or watershed examples of natural biological integrity. Florida 

Department of Environmental Protection (FL DEP) uses a targeted sampling design for 

developing thresholds of impairment with macroinvertebrates 

(http://www.epa.gov/owow/wetlands/bawwg/case/fl2.html). Choosing sampling stations that 

best allow comparison of ecological integrity at reference wetland sites of known condition can 

conserve financial resources. A sampling design that tests specific hypotheses (e.g., the FL DEP 

study tested the effect of elevated water column phosphorus on macroinvertebrate species 

richness) generally can be analyzed with statistical rigor and can conserve resources by 

answering specific questions. Furthermore, identification of systems with problems and 

reference conditions eliminates the need for selecting a random sample of the population for 

monitoring. 

Targeted sampling assumes some knowledge of the systems sampled (Stern 2004; Kentula et.al., 

1993). Systems based on independent variables with evidence of degradation are compared to 

reference systems that are similar in their physical structure (i.e., in the same class of wetlands). 

Wetland systems should be viewed along a continuum from reference to degraded. An impaired 

or degraded wetland is a system in which anthropogenic impacts exceed acceptable levels or 

interfere with beneficial uses. Comparison of the monitoring data to that collected from reference 

wetlands will allow characterization of the sampled systems. Wetlands identified as “at risk” 

should be evaluated through a sampling program to characterize the degree of degradation. Once 

characterized, the wetlands should be placed in one of the following categories: 

1. Degraded wetlands—wetlands in which the level of anthropogenic perturbance interferes 

with designated uses. 

 

2. High-risk wetlands—wetlands where anthropogenic stress is high but does not 

significantly impair designated uses. In high-risk systems, impairment is prevented by 

one or a few factors that could be changed by human actions, though characteristics of 

ecological integrity are already marginal. 
SEPTEMBER 2007 Chapter 4. Sampling Design for Wetland Monitoring 

60 

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/oh1.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/mn1.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 
SEPTEMBER 2007 Chapter 4. Sampling Design for Wetland Monitoring 

61 

yet; and, 3) control areas should be available (Green 1979). The first feature allows the surveys 

to be efficiently planned to account for the probable change in the environment. The second 

feature allows a baseline study to be established and extended as needed. The last feature allows 

the surveyor to distinguish between temporal effects unrelated to the impact and changes related 

to the impact. In practice however, advance knowledge of specific impacts is rare, and the ideal 

impact survey is rarely conducted. BACI designs modified to monitor impacts during or after 

their occurrence still can provide information, but there is an increase in the uncertainty 

associated with the results and the likelihood of finding a statistically significant change due to 

the impact is less probable. In addition, other aspects of survey design are dependent on the 

study objectives, e.g., the sampling interval, the length of time the survey is conducted (i.e., 

sampling for acute versus chronic effects), and the statistical analyses appropriate for analyzing 

the data (Suter 1993). 

The best interval for sampling is determined by the objectives of the study (Kentula et.al., 1993). 

If the objective is to detect changes in trends (e.g., regular monitoring for detection of changes in 

water quality or biotic integrity), regularly spaced intervals are preferred because the analysis is 

easier. On the other hand, if the objective is to assess differences before and after impact, then 

samples at random time points are advantageous. Random sample intervals reduce the likelihood 

that cyclic differences unforeseen by the sampler will influence the size of the difference before 

and after the impact. For example, surveys taken every summer for a number of years before and 

after a clear-cut may show little difference in system quality; however, differences may exist that 

can only be detected in the winter and therefore may go undetected if sampling occurs only 

during summer. 

The simplest impact survey design involves taking a single survey before and after the impact 

event (Green 1979). This type of design has the obvious pitfall that there may be no relationship 

between the observed event and the changes in the response variable—the change may be 

entirely coincidental. This pitfall is addressed in BACI design by comparing before and after 

impact data to data collected from a similar control system nearby. Data are collected before and 

after a potential disturbance in two areas (treatment and a control), with measurements on 

biological and environmental variables in all combinations of time and area (Green 1979). We 

will use a clear-cut adjacent to a wetland as an example to illustrate the BACI design. The 

sampling design is developed to identify the effects of clear-cutting on adjacent wetland systems. 

In the simplest BACI design, two wetlands would be sampled. One wetland would be adjacent to 

the clear-cut (the treatment wetland); the second wetland would be adjacent to a control site that 

is not clear-cut. The control site should have characteristics (soil, vegetation, structure, 

functions) similar to the treatment wetland and is exposed to climate and weather similar to the 

first wetland. Both wetlands are sampled at the same time points before the clear-cut occurs and 

at the same time point after the clear-cut takes place. This design is technically known as an 

area-by-time factorial design. Evidence of an impact is found by comparing the control site 

samples (before and after) with the treatment site before and after samples. Area-by-time 

factorial design allows for both natural wetland-to-wetland variation and coincidental time 
SEPTEMBER 2007 Chapter 4. Sampling Design for Wetland Monitoring 

62 

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 StewartOaten et.al., (1986), the survey is concerned about a particular impact in a particular place, not in 

the average of the impact when replicated in many different locations. Consequently, it may be 

possible to detect a difference between these two specific sites. Even so, if there are no 

randomized replicate treatments, the results of the study cannot be generalized to similar events 

at different wetlands. In any case, the likelihood that the differences between sites are due to 

factors other than the impact can be reduced by monitoring several control sites (Underwood 

1991) because multiple control sites provide some information about potential effects of other 

factors. 

The second and more serious concern with the simple Before-After design with a single 

sampling point before and after the impact is that it fails to recognize that there may be natural 

fluctuations in the characteristic of interest that are unrelated to any impact (Hurlbert 1984; 

Stewart-Oaten 1986). Single samples before and after impact would be sufficient to detect the 

effects of the impact if there were no natural fluctuations over time. However, if the population 

also has natural fluctuations over and above the long-term average, then it is impossible to 

distinguish between cases where there is no effect from cases where there is an impact. 

Consequently, measured differences in system quality may be artifacts of the sampling dates and 

natural fluctuations may obscure differences or lead one to believe differences are present when 

they are not. 

The simple BACI design was extended by Stewart-Oaten et.al., (1986) by pairing surveys at 

several selected time points before and after the impact to help resolve the issue of 

psuedoreplication (Hulbert 1984). This modification of the BACI design is referred to as BACIPS (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. 
SEPTEMBER 2007 Chapter 4. Sampling Design for Wetland Monitoring 

63 

Violation of the BACI assumptions may invalidate conclusions drawn from the data. Enough 

data should be collected before the impact to identify the trends in the communities of each 

sampling site if the BACI assumptions are to be met. Clearly defining the objectives of the study 

and identifying a statistically testable model of the relationships the investigator is studying can 

help resolve these issues (Suter 1993). 

The designs described above are suitable for detecting longer-term chronic effects in the mean 

level of the variable of interest. However, the impact may have an acute effect (i.e., effects only 

last for a short while) or may change the variability in response (e.g., seasonal changes become 

more pronounced) in some cases. The sampling schedule can be modified so that it occurs at two 

temporal scales (enhanced BACI-PS design) that encompass both acute and chronic effects 

(Underwood 1991). The modified temporal design introduces randomization by randomly 

choosing sampling occasions in two periods (Before and After) in the control or impacted sites. 

The two temporal scales (sampling periods vs. sampling occasions) allow the detection of a 

change in mean and of a change in variability after impact. For example, groups of surveys could 

be conducted every year with five surveys one week apart randomly located within each group. 

The analysis of such a design is presented in Underwood (1991). Again, multiple control sites 

should be used to counter the argument that detected differences are specific to the sampled site. 

The September 2000 issue of the Journal of Agricultural, Biological, and Environmental 

Statistics discusses many of the advantages and disadvantages of the BACI design and provides 

several examples of appropriate statistical analyses for evaluation of BACI studies. 

4.4 SUMMARY 

State monitoring programs should be designed to assess wetland condition with statistical rigor 

while maximizing available management resources. The three approaches described in this 

module—probabilistic sampling, targeted/tiered approach, and BACI (Before/After, 

Control/Impact)—present study designs that allow one to obtain a significant amount of 

information for statistical analyses. The sampling design selected for a monitoring program 

should depend on the management question being asked. Sampling efforts should be designed to 

collect information that will answer management questions in a way that will allow robust 

statistical analysis. In addition, site selection, characterization of reference sites or systems, and 

identification of appropriate index periods are all of particular concern when selecting an 

appropriate sampling design. Careful selection of sampling design will allow the best use of 

financial resources and will result in the collection of high quality data for evaluation of the 

wetland resources of a State. Examples of different sampling designs currently in use for State 

wetland monitoring are described in the Case Study module #14 on the Web site: 

http://www.epa.gov/waterscience/criteria/wetlands/index.html. Well-designed monitoring 

programs tend to produce data that managers can use in nutrient criteria development, such as in 

developing reference networks or utilizing distribution-based approaches. 
SEPTEMBER 2007 Chapter 4. Sampling Design for Wetland Monitoring 

64 

Table 4. Comparison of Probabilistic, Targeted, and BACI Sampling Designs 

Probabilistic Targeted BACI 

Random selection of wetland 

systems from entire population 

within a region. 

This design requires minimal 

prior knowledge of wetlands 

within the sample population 

for stratification. 

This design may use more 

resources (time and money) to 

randomly sample wetland 

classes because more wetlands 

may need to be sampled. 

System characterization for a 

class of wetlands is more 

statistically robust. 

Rare wetlands may be underrepresented 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. 
SEPTEMBER 2007 Chapter 5. Candidate Variables for Establishing Nutrient Criteria 

65 

Chapter 5 Candidate Variables for Establishing Nutrient 

Criteria 

5.1 OVERVIEW OF CANDIDATE VARIABLES 

This chapter provides an overview of candidate variables that could be used to establish nutrient 

criteria for wetlands. A more detailed discussion of sampling methods and laboratory analysis 

with useful references can be found in the Methods for Evaluating Wetland Condition module 

series for sampling wetlands4, 5 at: 

http://www.epa.gov/waterscience/criteria/wetlands/index.html. 

A good place to start with selecting candidate variables is by developing a conceptual model of 

how human activities affect nutrients and wetlands. These conceptual models may vary from 

complex to very simple models, such as relating nitrogen concentrations in sediments and plant 

biomass or species composition. Conceptual models establish the detail and scope of the project 

and the most important variables to select. In addition, they define the cause-effect relationships 

that should be documented to determine whether a problem occurs and what is causing the 

problem. 

In general, for the purposes of numeric nutrient criteria development, it is helpful to develop an 

understanding of the relationships among human activities, nutrients and habitat alterations, and 

attributes of ecosystem structure and function to establish a simple causal pathway among three 

basic elements in a conceptual model. These three basic groups of variables are important to 

distinguish because we use them differently in environmental management (Stevenson et.al., 

2004a). A fourth group of variables is important in order to account for variation in expected 

condition of wetlands due to natural variation in landscape setting. 

The overview of candidate variables in this chapter follows the outline provided in the 

conceptual model in Figure 5.1. Historically, variables in conceptual models have been grouped 

many ways with a variety of group names (Paulsen et.al., 1991; Stevenson 1998; Stevenson 

2004a, b). In this document, three groups and group names are used to emphasize cause-effect 

relationships, simplify their presentation and discussion for a diversity of audiences, and 

maintain some continuity between their use in the past and their use here. The three groups are: 

supporting variables, causal variables, and response variables. 

Supporting variables provide information useful in normalizing causal and response variables 

and categorizing wetlands. (These are in addition to characteristics used to define wetland 

 

4

 EPA is developing and revising additional modules as a part of the Methods for Evaluating Wetland Conditions 

Module series; Biogeochemical Indicators, Wetland Hydrology, and Nutrient Loading Estimation. 5

 The references for these modules can be found in the Supplementary References following the References section. 
SEPTEMBER 2007 Chapter 5. Candidate Variables for Establishing Nutrient Criteria 

66 

classes as described in Chapter 3.) Causal variables characterize pollution or habitat 

alterations. Causal variables are intended to characterize nutrient availability in wetlands and 

could include nutrient loading rates and soil nutrient concentrations. Response variables are 

direct measures or indicators of ecological properties. Response variables are intended to 

characterize biotic response and could include community structure and composition of 

vegetation and algae. The actual grouping of variables is much less important than understanding 

relationships among variables. 

It is important to recognize the complex temporal and spatial structure of wetlands when 

measuring or interpreting causal and response variables with respect to nutrient condition. The 

complex interaction of climate, geomorphology, soils, and internal interactions has led to a 

diverse array of wetland types ranging from infrequently flooded, isolated depressional wetlands 

such as seasonal prairie potholes and playa lakes, to very large, complex systems such as the 

Everglades and the Okefenokee Swamp. In addition, most wetlands are complex temporal and 

spatial mosaics of habitats with distinct structural and functional characteristics illustrated most 

visibly by patterns in vegetation structure. 

Horizontal zonation is a common feature of wetland ecosystems, and in most wetlands, relatively 

distinct bands of vegetation develop in relation to water depth. Bottomland hardwood forests and 

prairie pothole wetlands provide excellent illustrations of zonation in two very divergent wetland 

types. However, vegetation zones are not static. Seasonal and long-term changes in vegetation 

structure are a common characteristic of most wetland ecosystems. Wetlands may exhibit 

dramatic shifts in vegetation patterns in response to changes in hydrology, with entire wetlands 

shifting between predominantly emergent vegetation to completely open water within only a 

year or two. Such temporal patterns in fact are important features of many wetlands and should 

be considered in interpreting any causal or response variable. For example, seasonal cycles are 

an essential feature of floodplain forests, which are typically flooded during high spring flows 

but dry by mid to late summer. Longer-term cycles are similarly essential features of prairie 

pothole wetlands, which exhibit striking shifts in vegetation in response to water level 

fluctuations over periods of a few years in smaller wetlands to decades in larger, more permanent 

wetlands (van der Valk 2000). Vegetation patterns can significantly affect the physical and 

chemical characteristics of sediments and overlying waters and are likely to control major 

aspects of wetland biogeochemistry and trophic dynamics (Rose and Crumpton 1996). 

The complex temporal and spatial structure of wetlands should influence the selection of 

variables to measure and methods for measuring them. Most wetlands are characterized by 

extremely variable hydrologic and nutrient loading rates and close coupling of soil and water 

column processes. As a result, estimates of nutrient loading may prove more useful than direct 

measurements of water column nutrient concentrations as causal variables for establishing the 

nutrient condition of wetlands. In addition, soil nutrients that integrate a wetland’s variable 

nutrient history over a period of years may provide the most useful metric against which to 

evaluate wetland response. 
SEPTEMBER 2007 Chapter 5. Candidate Variables for Establishing Nutrient Criteria 

67 

Fig 5.1 Climate Geology

Soils

Topography

Hydrology

Agriculture Urban Dev.

No-till Row Crops

Channelization

Riparian Buffers

Nitrogen Phosphorus

Invasive Species

Hydrologic 

Alterations

Ecosystem Structure

•Biomass

•Biodiversity

Flora & Fauna

Ecosystem Function

•Productivity

•Nutrient Retention

•Hydrologic Regulation

Human Activities

Natural Factors

Stressors: Contaminants & Habitat Alterations

Responses: Valued Ecological Attributes

Supporting Causal Response

This conceptual model illustrates 

the causal pathway between 

human activities and valued 

ecological attributes. It includes 

the role of nutrients in a broader 

context that includes natural 

variation among wetlands. The 

relationship between different 

approaches of grouping variables 

is illustrated to emphasize the 

importance of cause-effect 

relationships. Here, natural factors 

and human activities regulate the 

physical, chemical and biological 

attributes of wetlands. Some 

wetland attributes are more valued 

than others and provide the 

endpoints of assessment and 

management. Some physical, 

chemical, and biological attributes 

are stressors, i.e. contaminants 

and habitat alterations caused by 

human activities that negatively 

affect valued ecological attributes. 

The overview of variables in 

Chapter 5 is organized in three 

sections: supporting, causal, and 

response variables. Supporting 

variables are natural landscapelevel factors that classify expected 

condition of wetlands. Causal 

factors “cause” effects in response 

variables.

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 
SEPTEMBER 2007 Chapter 5. Candidate Variables for Establishing Nutrient Criteria 

68 

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 (μS/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.

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. 
SEPTEMBER 2007 Chapter 5. Candidate Variables for Establishing Nutrient Criteria 

69 

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 μg/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 70oC 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. 
SEPTEMBER 2007 Chapter 5. Candidate Variables for Establishing Nutrient Criteria 

70 

HYDROLOGIC CONDITION

Wetland hydrologic condition is important for characterizing wetlands and for normalizing many 

causal and response variables. Hydrologic conditions can directly affect the chemical and 

physical processes governing nutrient and suspended solids dynamics within wetlands (Mitsch 

and Gosselink, 2000). Detailed, site-specific hydrologic information available is best, but at a 

minimum, some estimate of water level fluctuation should be made. A defining characteristic of 

wetlands is oxygen deficiency in the soil caused by flooding or soil saturation. These conditions 

influence vegetation dynamics through differential growth and survival of plant species and also 

exert significant control over biogeochemical processes involved in carbon flow and nutrient 

cycling within wetlands. Spatial and temporal patterns in hydrology can create complex patterns 

in soil and water column oxygen availability, including alternating aerobic and anaerobic 

conditions in wetland soils, with obvious implications for plant response and biogeochemical 

process dynamics. Water levels in wetlands can be determined using a staff gauge when surface 

water is present. A staff gauge measures the depth of surface flooding relative to a reference 

point such as the soil surface. Other methods to assess past water levels when standing water is 

not present include moss collars, staining, and cypress knee heights. While surface flooding may 

be rare or absent in a wetland, high water tables may still cause soil saturation in the rooting 

zone. In wetlands where soils are saturated, water level can be measured with a small diameter 

perforated tube installed in the soil to a specified depth (Amoozegar and Warrick 1986). 

Automated water level recorders using floats, capacitance probes, or pressure transducers are 

suitable for measuring water levels both above- and below-ground. The reader is referred to the 

Supplementary References for details. 

5.3 CAUSAL VARIABLES

Causal variables are intended to characterize nutrient availability in wetlands. Most wetlands are 

characterized by extremely variable nutrient loading rates and close coupling of soil and water 

column processes. As a result, estimates of nutrient loading and measurements of soil nutrients 

may prove more useful than direct measurements of water column nutrient concentrations as 

causal variables for establishing the nutrient condition of wetlands. Nutrient loading history and 

soil nutrient measures can integrate a wetland’s variable nutrient history over a period of years 

and may provide especially useful metrics against which to evaluate nutrient condition. Wetlands 

exhibit a high degree of spatial heterogeneity in chemical composition of soil layers, and areas 

impacted by nutrients may exhibit more variability than unimpacted areas of the same wetland. 

Thus, sampling protocols should capture this spatial variability. Developing nutrient criteria and 

monitoring the success of nutrient management programs involves important considerations for 

sampling designed to capture spatial and temporal patterns. 

Below is a brief overview of the use of nutrient loading and soil and water column nutrient 

measures for estimating nutrient condition of wetlands. Please refer to Supplementary 
SEPTEMBER 2007 Chapter 5. Candidate Variables for Establishing Nutrient Criteria 

71 

References for a list of references on both nutrient load estimation and biogeochemical 

indicators, with a focus on soil and water column nutrient measures. 

NUTRIENT LOADING

External nutrient loads to wetlands are determined primarily by surface and subsurface transport 

from the contributing landscape, and vary significantly as a function of weather and landscape 

characteristics such as soils, topography, and land use. Most wetlands are characterized by 

extremely variable hydrologic and nutrient loading rates, which present considerable obstacles to 

obtaining adequate direct measurement of nutrient inputs. Adequate measurement of loads may 

require automated samplers capable of providing flow-weighted samples when loading rates are 

highly variable. In many cases, nonpoint source loads simply may not be adequately sampled. 

The more detailed the loading measurements the better, but it is not reasonable to expect 

adequate direct measurement of loads for most wetlands. In the absence of sufficient, direct 

measurements, it may be possible to estimate nutrient loading using an appropriate loading 

model or at least to provide a relative ranking of wetlands based on expected nutrient load. One 

advantage of loading models is that nutrient loading can be integrated over the appropriate time 

scale for characterizing wetland nutrient condition and, in some cases, historical loading patterns 

can be reconstructed. Loading models also can provide hydrologic loading rates to calculate 

critical supporting variables such as hydroperiod and residence times. 

Loading function models are based on empirical or semi-empirical relationships that provide 

estimates of pollutant loads on the basis of long-term measurements of flow and contaminant 

concentration. Generally, loading function models contain procedures for estimating pollutant 

load based on empirical relationships between landscape physiographic characteristics and 

phenomena that control pollutant export. McElroy et.al., (1976) and Mills (1985) described 

loading functions employed in screening models developed by the USEPA to facilitate 

estimation of nutrient loads from point and nonpoint sources. The models contain simple 

empirical expressions that relate the magnitude of nonpoint pollutant load to readily available or 

measurable input parameters such as soils, land use and cover, land management practices, and 

topography. Preston and Brakebill (1999) described a spatial regression model that relates the 

water quality conditions within a watershed to sources of nutrients and to those factors that 

influence transport of the nutrients. The regression model, Spatially-Referenced Regressions on 

Watersheds (SPARROW), involves a statistical technique that utilizes spatially referenced 

information and data to provide estimates of nutrient load (Smith et al., 1997; Smith et al., 2003; 

http://water.usgs.gov/nawqa/sparrow/). 

In general, the SPARROW methodology was designed to provide statistically based 

relationships between stream water quality and anthropogenic factors such as contaminant 

sources within the contributing watersheds, land surface characteristics that influence the 

delivery of pollutants to the stream, and in-stream contaminant losses via chemical and 

biological process pathways. The Generalized Watershed Loading Functions (GWLF) model 
SEPTEMBER 2007 Chapter 5. Candidate Variables for Establishing Nutrient Criteria 

72 

(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 
SEPTEMBER 2007 Chapter 5. Candidate Variables for Establishing Nutrient Criteria 

73 

balance models incorporate principles of mass conservation. These models integrate external 

loading to the wetland, nutrient transformation and retention within the wetland, and nutrient 

export from the wetland. Mass balance models allow time varying hydrologic and nutrient inputs 

and can provide estimates of spatial nutrient distribution within the wetland. The most difficult 

problem is developing removal rate equations which adequately represent nutrient 

transformation and retention across the range of conditions for which estimates are needed. 

LAND USE

Identifying land uses in regions surrounding wetlands is important for characterizing reference 

condition, identifying reference wetlands, and providing indicators of nutrient loading rates for 

criteria development. Most simply, the percentage of natural area or the percentage of 

agricultural and urban lands can be used to characterize land uses around wetlands. More 

detailed quantitative data can be gathered from GIS analysis, which provides higher resolution 

identification of land use types such as pastures, row crops, and confined animal feeding 

operations for agriculture. Ideally these characterizations should be done for the entire 

sourceshed, including both air and water, in the regions around wetlands. Air-sheds should 

incorporate potential atmospheric sources of nutrients, and watersheds should incorporate 

potential aquatic sources. However, in practice, land use around wetlands is typically used for 

defining reference wetlands and also in most nutrient loading models to characterize 

groundwater and surface water sources. Land use in buffer zones, one kilometer zones around 

wetlands and wetland watersheds (delineated by elevation), has been used to characterize human 

activities that could be affecting wetlands (Brooks et.al., 2004). 

EXTRACTABLE SOIL NITROGEN AND PHOSPHORUS

Ammonium is the dominant form of inorganic N in wetland soils, and unlike total soil N (Craft 

et.al., 1995, Chiang et.al., 2000), soil extractable NH4-N increases in response to N loadings. 

Enrichment leads to enhanced cycling of N between wetland biota (Valiela and Teal 1974, 

Broome et.al., 1975, Chalmers 1979, Shaver et.al., 1998), greater activity of denitrifying bacteria 

(Johnston 1991, Groffman 1994, White and Reddy 1999), and accelerated organic matter 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 KCl (Mulvaney 

1996). Ten to twenty grams of field moist soil is equilibrated with 100 ml of 2 M KCl 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). 
SEPTEMBER 2007 Chapter 5. Candidate Variables for Establishing Nutrient Criteria 

74 

Extractable P is often a reliable indicator of the P enrichment of soils, and in wetlands, 

extractable P is strongly correlated with surface water P concentration and P enrichment from 

external sources (Reddy et.al., 1995, 1998). Selected methods used to extract P are described 

below (Kuo 1996). Many soil testing laboratories perform these analyses on a routine basis. 

Historically, these methods have been used to determine nutrient needs of agronomic crops, but 

the methods have been used more recently to estimate P impacts in upland and wetland soils 

(Sharpley et.al., 1992; Nair et.al., 1995; Reddy et.al., 1995, 1998). 

The Mehlich I method is typically used in the Southeast and Mid-Atlantic regions on mineral 

soils with pH of < 7.0 (Kuo 1996). The extractant consists of dilute concentrations of strong 

acids. Many plant nutrients such as P, K, Ca, Mg, Fe, Zn, and Cu extracted with Mehlich I 

methods have been calibrated for production of crops in agricultural ecosystems. This solvent 

extracts some Fe and Al- bound P, and some Ca-bound P. Soil (dry) to extractant ratio is set at 

1:4, for mineral soils, while wider ratios are used for organic soils. Soil solutions are equilibrated 

for a period of five minutes on a mechanical shaker and then filtered through a Whatman No. 42 

filter. Filtered solutions are analyzed for P and other nutrients using standard methods (Method 

365.1, USEPA, 1993a). 

The Bray P-1 method has been widely used as an index of available P in soils (Kuo 1996). The 

combination of dilute concentration of strong acid (HCl at 0.025 M) and ammonium fluoride 

(NH4F at 0.03 M) is designed to easily remove acid extractable soluble P forms such as Cabound 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, 
SEPTEMBER 2007 Chapter 5. Candidate Variables for Establishing Nutrient Criteria 

75 

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 o 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 <300o

C (Kuo 1996). Digested solutions are analyzed 

for P using colorimetric methods (e.g., ascorbic acid-molybdate) (APHA 1999, Kuo 1996). 

Many laboratories may not have access to perchloric acid fume-hoods. Alternatively, soil total 

phosphorus can be determined using the ashing method (Anderson, 1976). Results obtained from 

this method are reliable and comparable to total phosphorus measurements made using 

perchloric acid digestion method. 

WATER COLUMN NITROGEN AND PHOSPHOROUS

Nutrient inputs to wetlands are highly variable across space and time, hence, single 

measurements of water column N and P represent only a “snap-shot” of nutrient condition and 

may or may not reflect the long-term pattern of nutrient inputs that alter biogeochemical cycles 

and affect wetland biota. The best use of water column N and P concentrations for nutrient 

criteria development will be based on frequent monitoring of nutrient concentrations over time 

(e.g., weekly or monthly measurements). Of course, in wetlands that are seldom flooded, 

measurements of water column N and P may not be practical or even relevant for assessing 

impacts. Whenever water samples are obtained, it is important that the water depth is recorded 

because nutrient concentration is related to water depth. In the case of tidal estuarine or 

freshwater wetlands, it is also important to record flow and the point in the tidal cycle that the 

samples were collected. 

Methodologies to monitor N in surface waters are well developed for other ecosystems and can 

be readily adopted for wetlands. The most commonly monitored N species are total Kjeldahl 

nitrogen (TKN), ammonium N, and nitrate plus nitrite N (APHA 1999). The TKN analysis 

includes both organic and ammonium N, but does not include nitrate plus nitrite N. Organic N is 

determined as the difference between TKN and NH4-N. Forms of N in surface water are 
SEPTEMBER 2007 Chapter 5. Candidate Variables for Establishing Nutrient Criteria 

76 

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: 

(i) dissolved inorganic P (DIP, also referred to as dissolved reactive P (DRP) or soluble reactive 

phosphorous (SRP)); (ii) dissolved organic P (DOP); (iii) particulate inorganic P (PIP); and, (iv) 

particulate organic P (POP). Dissolved inorganic P (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/16Indicators.pdf; 
SEPTEMBER 2007 Chapter 5. Candidate Variables for Establishing Nutrient Criteria 

77 

http://www.epa.gov/waterscience/criteria/wetlands/10Vegetation.pdf), algae; 

(http://www.epa.gov/waterscience/criteria/wetlands/11Algae.pdf); and, macroinvertebrates 

(http://www.epa.gov/waterscience/criteria/wetlands/9Invertebrate.pdf) to assess wetland 

condition, including nutrients. 

MACROPHYTE NITROGEN AND PHOSPHORUS

Wetland macrophytes respond to nutrient enrichment by increasing uptake and storage of N and 

P (Verhoeven and Schmitz 1991, Shaver et.al., 1998, Chiang et.al., 2000). In wetlands where P is 

the primary limiting nutrient, the P content of vegetation increases almost immediately (within a 

few months) in response to nutrient enrichment (Craft et.al., 1995). Increased P uptake by plants 

is known as “luxury uptake” because P is stored in vacuoles and used later (Davis 1991). Like P, 

leaf tissue N may increase in response to N enrichment (Brinson et.al., 1984, Shaver et.al., 

1998). However, most N is directly used to support new plant growth so that luxury uptake of N 

is not usually observed (Verhoeven and Schmitz 1991). Tidal marsh grasses, however, do appear 

to store nitrogen in both living and dead tissues that can be accessed by living plant tissue. A 

discussion of conservation and translocation of N in saltwater tidal marshes can be found in 

Hopkinson and Schubauer (1980) and Thomas and Christian (2001). 

Nutrient content of macrophyte tissue holds promise as a means to assess nutrient enrichment of 

wetlands. However, several caveats should be kept in mind when using this diagnostic tool 

(Gerloff 1969, Gerloff and Krombholz 1966, EPA 2002c). 

1. The most appropriate plant parts to sample and analyze should be determined. It is 

generally recognized that the plant or plant parts should be of the same physiological age. 

2. Samples from the same species should be collected and analyzed. Different species 

assimilate and concentrate nutrients to different levels. 

3. Tissue nutrient concentrations vary with (leaf) position, plant part, and age. It is 

important to sample and analyze leaves from the same position and age (e.g., third leaf 

from the terminal bud on the plant) to ensure comparability of results from sampling of 

different wetlands. 

4. Tissue P may be a more reliable indicator of nutrient condition than N. This is because N 

is used to increase production of aboveground biomass, whereas excess P is stored via 

luxury uptake. 

Another promising macrophyte-based tool is the measurement of nutrient resorption of N and P 

prior to leaf senescence and dieback. Nutrient resorption is an important strategy used by 

macrophytes to conserve nutrients (Hopkinson and Schubauer 1984; Shaver and Melillo 1984). 

In nutrient-poor environments, macrophytes resorb N and P from green leaves prior to 
SEPTEMBER 2007 Chapter 5. Candidate Variables for Establishing Nutrient Criteria 

78 

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 70o

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 landgrant universities, State agricultural testing laboratories, and environmental consulting 

laboratories perform these analyses. Contact your local U.S. Department of Agriculture office or 

land-grant agricultural extension office for information on laboratories that perform plant tissue 

nutrient analyses. 

Please see the EPA module #16, Vegetation-based Indicators of Wetland Nutrient Enrichment

(http://www.epa.gov/waterscience/criteria/wetlands/16Indicators.pdf) for a detailed description 

of indicators derived from N and P content of macrophytes. 

ABOVEGROUND BIOMASS AND STEM HEIGHT

Wetland macrophytes also respond to nutrient enrichment by increased net primary production 

(NPP) and growth if other factors such as light are not limiting growth (Chiang et.al.,2000). Net 

primary production is the amount of carbon fixed during photosynthesis that is incorporated into 

new leaves, stems, and roots. Most techniques to measure NPP focus on aboveground biomass 

and discount root production because it is difficult to measure, even though root production may 

account for 50% of NPP. The simplest way to measure aboveground biomass is by harvesting all 

of the standing material (biomass) at the end of the growing season (Broome et al., 1986). The 

harvest method is useful for measuring NPP of herbaceous emergent vegetation, especially in 

temperate climates where there is a distinct growing season. If root production desired, it can be 

determined by sequentially harvesting roots at monthly intervals during the year (Valiela et. al, 

1976). 

Enhanced NPP often is reflected by increased height and, sometimes, stem density of herbaceous 

emergent vegetation (Broome et. al., 1983). Because increased stem density may reflect other 

factors like vigorous clonal growth, it is not recommended as an indicator of nutrient enrichment. 
SEPTEMBER 2007 Chapter 5. Candidate Variables for Establishing Nutrient Criteria 

79 

Aboveground biomass of herbaceous vegetation may be determined by end-of-season harvest of 

aboveground plant material in small 0.25 m2 quadrats stratified by macrophyte species or 

inundation zone (Broome et.al., 1986). Stem height of individuals of dominant species is 

measured in each plot. Height of the five to 10 tallest stems in each plot has been shown to be a 

reliable indicator of NPP (Broome et.al., 1986) that saves time as compared to height 

measurements of all stems in the plot. Aboveground biomass is clipped at the end of the growing 

season, in late summer or fall. Clipped material is separated into live (biomass) versus dead 

material, then dried at 70oC to a constant weight. For stem height and biomass sampling, five to 

10 plots per vegetation zone are collected. In forested sites, biomass production is defined as the 

sum of the leaf and fruit fall and aboveground wood production (Newbould, 1967). Please see 

the EPA module Vegetation-based Indicators of Wetland Nutrient Enrichment

(http://www.epa.gov/waterscience/criteria/wetlands/16Indicators.pdf ) for a detailed description 

of sampling aboveground biomass in wetlands. 

ALGAL NITROGEN & PHOSPHORUS

In some cases, measurements of algal N and P can provide a useful complement to vegetation 

and soil nutrient analyses that integrate nutrient history over a period of months in the case of 

vegetation (Craft et.al., 1995), to years in the case of soils (Craft and Richardson 1998, Chiang 

et.al., 2000). Nutrient concentrations in algae can integrate variation in water column N and P 

bioavailability over a time scale of weeks, potentially providing an indication of the recent 

nutrient status of a wetland (Fong et al., 1990; Stevenson et.al., 2001). Caution is warranted for 

this method because it is not useful in all wetlands; for example, in wetlands where surface 

inundation occurs intermittently or for short periods of time, where the water surface is severely 

shaded as in some forested wetlands, or under other circumstances where unrelated 

environmental factors exert primary control over algal growth. 

Algae should be sampled by collecting grab samples from different locations in the wetland to 

account for spatial variability in the wetland. If an environmental gradient is known or suspected 

(i.e., decreasing canopy or impacted land uses) or exists within the wetland as a result of specific 

source discharges, then sites along this gradient should be sampled separately. Comparisons 

among wetlands or locations within a wetland should be done on a habitat-specific basis (e.g., 

phytoplankton vs. periphyton). Samples are processed in the same manner as wetland plants to 

determine N and P content. Nitrogen is determined using a CHN analyzer, whereas P is 

measured colorimetrically after acid digestion. 

Please see the EPA module Using Algae to Assess Environmental Conditions in Wetlands 

(http://www.epa.gov/waterscience/criteria/wetlands/11Algae.pdf) for a detailed description of 

indicators derived from to N and P content of algae. 

MACROPHYTE COMMUNITY STRUCTURE AND COMPOSITION
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80 

The composition of the plant community and the changes that result from human activities can 

be used as sensitive indicators of the biological integrity of wetland ecosystems. In particular, 

aggressive, fast-growing species such as cattail (Typha spp.), giant reed (Phragmites communis), 

reed canarygrass (Phalaris arundincea), and other clonal species invade and may eventually 

come to dominate the macrophyte community. Data collection methods and analyses for using 

macrophyte community structure and composition as an indicator of nutrient enrichment and 

ecosystem integrity for wetlands are described in Vegetation-based Indicators of Wetland 

Nutrient Enrichment (http://www.epa.gov/waterscience/criteria/wetlands/16Indicators.pdf ) and 

Using Vegetation to Assess Environmental Conditions in Wetlands

(http://www.epa.gov/waterscience/criteria/wetlands/10Vegetation.pdf), respectively. 

ALGAL COMMUNITY STRUCTURE AND COMPOSITION

Algae can be used as a valuable indicator of biological and ecological condition of wetlands. 

Structural and functional attributes of algae can be measured including diversity, biomass, 

chemical composition, productivity, and other metabolic functions. Species composition of 

algae, particularly of the diatoms, is commonly used as an indicator of biological integrity and 

physical and chemical conditions of wetlands. Discussions of sampling, data analyses, and 

interpretation are included in Using Algae to Assess Environmental Conditions in Wetlands 

(http://www.epa.gov/waterscience/criteria/wetlands/11Algae.pdf). 

INVERTEBRATE COMMUNITY STRUCTURE AND COMPOSITION

Aquatic invertebrates can be used to assess the biological and ecological condition of wetlands. 

The approach for developing an Index of Biological Integrity (IBI) for wetlands based on aquatic 

invertebrates is described in Developing an Invertebrate Index of Biological Integrity for 

Wetlands (http://www.epa.gov/waterscience/criteria/wetlands/9Invertebrate.pdf). 

5.5 SUMMARY 

Candidate variables to use in determining nutrient condition of wetlands and to help identify 

appropriate nutrient criteria for wetlands consist of supporting variables, causal variables, and 

response variables. Supporting variables provide information useful in normalizing causal and 

response variables and categorizing wetlands. Causal variables are intended to characterize 

nutrient availability (or assimilation) in wetlands and could include nutrient loading rates and 

soil nutrient concentrations. Response variables are intended to characterize biotic response and 

could include community structure and composition of macrophytes and algae. 

The complex temporal and spatial structure of wetlands will influence the selection of variables 

to measure and methods for measuring them. The information contained in this chapter is a brief 

summary of suggested analyses that can be used to determine wetland condition with respect to 
SEPTEMBER 2007 Chapter 5. Candidate Variables for Establishing Nutrient Criteria 

81 

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 ArcViewTM, ArcInfoTM, and 

MapInfoTM 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 georeferenced data. 
SEPTEMBER 2007 Chapter 6. Database Development and New Data Collection 

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To facilitate data storage, manipulation, and calculations, it is highly recommended that 

historical and present-day data be transferred to a relational database (i.e., AccessTM). Relational 

databases store data in tables as sets of rows and columns and are powerful tools for data 

manipulation and initial data reduction. They allow selection of data by specific, multiple criteria 

and definition and redefinition of linkages among data components. Data queries can also be 

exported to GIS, provided that the data is related to some geo-referenced coordinate system. 

POTENTIAL DATA SOURCES

 

EPA Water Quality Data 

STORET 

EPA has many programs of national scope that focus on collection and analysis of water quality 

data. The following presents information on several of the databases and national programs that 

may be useful to water quality managers as they compile data for criteria development. 

STORET STOrage and RETrieval system (STORET) is EPA’s national database for water 

quality and biological data. 

Environmental Monitoring and Assessment Program (EMAP) 

The Environmental Monitoring and Assessment Program is an EPA research program designed 

to develop the tools necessary to monitor and assess the status and trends of national ecological 

resources (see EMAP Research Strategy on the EMAP Web site: www.epa.gov/emap). EMAP’s 

goal is to develop the scientific understanding for translating environmental monitoring data 

from multiple spatial and temporal scales into assessments of ecological condition and forecasts 

of future risks to the sustainability of the Nation’s natural resources. Data from the EMAP 

program can be downloaded directly from the EMAP Web site (www.epa.gov/emap/ . The 

EMAP Data Directory contains information on available data sets, including data and metadata 

(language that describes the nature and content of data). Current status of the data directory, as 

well as composite data and metadata files, are available on this Web site. 

U.S. Geological Surve) (USGS) Water Data

The USGS has national and distributed databases on water quantity and quality for waterbodies 

across the nation. Much of the data for rivers and streams are available through the National 

Water Information System (NWIS). These data are organized by State, Hydrologic Unit Codes 

(HUCs), latitude and longitude, and other descriptive attributes. Most water quality chemical 

analyses are associated with an instantaneous streamflow at the time of sampling and can be 

linked to continuous streamflow to compute constituent loads or yields. The most convenient 

method of accessing the local databases is through the USGS State representative. Every State 

office can be reached through the USGS home page at: http://www.usgs.gov. 
SEPTEMBER 2007 Chapter 6. Database Development and New Data Collection 

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HBN and NASQAN 

USGS data from several national water quality programs covering large regions offer highly 

controlled and consistently collected data that may be particularly useful for nutrient criteria 

analysis. Two programs, the Hydrologic Benchmark Network (HBN) and the National Stream 

Quality Accounting Network (NASQAN), include routine monitoring of rivers and streams over 

the past 30 years. The HBN consists of 63 relatively small, minimally disturbed watersheds. 

HBN data were collected to investigate naturally-induced changes in streamflow and water 

quality and the effects of airborne substances on water quality. The NASQAN program consists 

of 618 larger, more culturally influenced watersheds. NASQAN data provides information for 

tracking water-quality conditions in major U.S. rivers and streams. The watersheds in both 

networks include a diverse set of climatic, physiographic, and cultural characteristics. Data from 

the networks have been used to describe geographic variations in water-quality concentrations, 

quantify water-quality trends, estimate rates of chemical flux from watersheds, and investigate 

relations of water quality to the natural environment and anthropogenic contaminant sources. 

WEBB 

The Water, Energy, and Biogeochemical Budgets (WEBB) program was developed by USGS to 

study water, energy, and biogeochemical processes in a variety of climatic/regional scenarios. 

Five ecologically diverse watersheds, each with an established data history, were chosen. This 

program may prove to be a rich data source for ecoregions in which the five watersheds are 

located. Many publications on the WEBB project are available. See the USGS Web site for more 

details (http://water.usgs.gov/nrp/webb/about.html). 

US Department of Agriculture (USDA) 

Agricultural Research Service (ARS) 

The USDA ARS houses the Natural Resources and Sustainable Agricultural Systems Scientific 

Directory (http://hydrolab.arsusda.gov/arssci.html), which has seven national programs to 

examine the effect of agriculture on the environment. The program on Water Quality and 

Management addresses the role of agriculture in nonpoint source pollution through research on 

Agricultural Watershed Management and Landscape Features, Irrigation and Drainage 

Management Systems, and Water Quality Protection and Management Systems. Research is 

conducted across the country and several models and databases have been developed. 

Information on research and program contacts is listed on the Web site 

(http://www.nps.ars.usda.gov/programs/nrsas.htm). 

 Forest Service 
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The Forest Service has designated research sites across the country, many of which are Long 

Term Ecological Research (LTER) sites. Many of the data from these experiments are available 

in the USFS databases located on the Web site (http://www.fs.fed.us/research/). Most of the data 

are forest-related but may be of use for determining land uses and questions on silviculture 

runoff. 

National Science Foundation (NSF) 

The National Science Foundation (NSF) funds projects for the Long Term Ecological Research 

(LTER) Network. The Network is a collaboration of over 1,100 researchers investigating a wide 

range of ecological topics at 24 different sites nationwide. The LTER research programs are not 

only an extremely rich data source, but also a source of data available to anyone through the 

Network Information System (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 
SEPTEMBER 2007 Chapter 6. Database Development and New Data Collection 

86 

for nutrient criteria development and may provide pertinent data sources, although they may be 

regionally limited. These data should be available from the agencies responsible for monitoring. 

Volunteer Monitoring Programs 

State and local agencies may use volunteer data to screen for water quality problems, establish 

trends in waters that would otherwise be unmonitored, and make planning decisions. Volunteers 

benefit from learning more about their local water resources and identifying what conditions or 

activities might contribute to pollution problems. As a result, volunteers frequently work with 

clubs, environmental groups, and State or local governments to address problem areas. The EPA 

supports volunteer monitoring and local involvement in protecting our water resources. 

Academic and Literature Sources 

Most of the data available on water and soil quality in wetlands is the result of research studies 

conducted by academic institutions. Much of the research conducted by the academic 

community, however, was not conducted for the purpose of spatial or long-term biogeochemical 

characterization of the nation’s wetlands; instead, water quality information was often collected 

to characterize the environmental conditions under which a particular study or experiment was 

conducted. Infrequently, spatial studies of limited extent or duration were conducted. Data 

collected from these sources, therefore, may not be sufficiently representative of the population 

of wetlands within an ecoregion. However, this limited data may be the only information 

available and therefore could be useful for identifying reference conditions or determining where 

to begin a more comprehensive survey to support development of nutrient criteria. Academic 

research data is available from researchers and the scientific literature. 

6.3 QUALITY OF HISTORICAL AND COLLECTED DATA 

The value of older historical data is a recurrent problem because data quality is often unknown. 

Knowledge of data quality is also problematic for long-term data repositories such as STORET 

and long-term State databases, where objectives, methods, and investigators may have changed 

many times over the years. The most reliable data tend to be those collected by a single agency 

using the same protocol. Supporting documentation should be examined to determine the 

consistency of sampling and analytical protocols. The suitability of data in large, heterogeneous 

data repositories for establishing nutrient criteria are described below. These same factors need 

to be taken into account when developing a new database such that future investigators will have 

sufficient information necessary to evaluate the quality of the database. 

LOCATION
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Geo-referenced data is extremely valuable in that it allows for aggregating and summarizing data 

according to any GIS coverage desired, whether the data was historically related to a particular 

coverage theme or not. However, many studies conducted prior to the availability and accuracy 

of hand held Global Positioning System (GPS) units relied on narrative and less definitive 

descriptions of location such as proximity to transportation corridor, county, or nearest municipal 

center. This can make comparison of data, depending upon desired spatial resolution, difficult. 

Knowledge of the rationale and methods of site selection from the original investigators may 

supply valuable information for determining whether inclusion of the site or study in the 

database is appropriate based on potential bias relative to overall wetland data sources. STORET 

and USGS data associated with the National Hydrography Dataset (NHD) are geo-referenced 

with latitude, longitude, and Reach File 3 (RF3) codes (http://nhd.usgs.gov/). In addition, 

STORET often contains a site description to supplement location information. Metadata of this 

type, when known, is frequently stored within large long-term databases. 

VARIABLES AND ANALYTICAL METHODS

Each separate analytical method yields a unique variable. For example, five ways of measuring 

TP result in five unique variables. Data generated using different analytical methods should not 

be combined in data analyses because methods differ in accuracy, precision, and detection limits. 

Data generated from one method may be too limited, making it important to select the most 

frequently used analytical methods in the database. Data that were generated using the same 

analytical methods may not always be obvious because of synonymous names or analytical 

methods. Consistency in taxonomic conventions and indicator measurements is likewise 

important for biological variables and multimetric indices comparisons. Review of recorded data 

and analytical methods by knowledgeable personnel is important to ensure that there are no 

problems with data sets developed from a particular database. 

LABORATORY QUALITY CONTROL (QC) 

Data generated by agencies or laboratories with known quality control/quality assurance 

protocols are most reliable. Laboratory QC data (blanks, spikes, replicates, known standards) are 

infrequently reported in larger data repositories. Records of general laboratory quality control 

protocols and specific quality control procedures associated with specific data sets are valuable 

in evaluating data quality. However, premature elimination of lower quality data can be 

counterproductive because the increase in variance caused by analytical laboratory error may be 

negligible compared to natural variability or sampling error, especially for nutrients and related 

water quality parameters. However, data of uncertain and undocumented quality should not be 

accepted. 

Water column nutrient data can be reported in different units, e.g., ppm, mg/L, mmoles. 

Reporting of nutrient data from other strata such as soils, litter, and vegetation can further 
SEPTEMBER 2007 Chapter 6. Database Development and New Data Collection 

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expand the list of reporting units (e.g., mg/kg, g/kg, %, mg/cm3). In many instances, conversion 

of units is possible; however, in other instances unit conversion is not possible or is lacking 

support information for conversion. Consistency in reporting units and the need to provide 

conversion tables cannot be overemphasized. 

DATA COLLECTING AGENCIES

Selecting data from particular agencies with known, consistent sampling and analytical methods 

and known quality will reduce variability due to unknown quality problems. Requesting data 

review for quality assurance from the collecting agency will reduce uncertainty about data 

quality. 

TIME PERIOD

Long-term records are critically important for establishing trends. Determining if trends exist in 

the time series database is also important for characterizing reference conditions for nutrient 

criteria. Length of time series data needed for analyzing nutrient data trends is discussed in 

Chapter 7. 

INDEX PERIOD

An index period—the time period most appropriate for sampling—for estimating average 

concentrations can be established if nutrient and water quality variables were measured through 

seasonal cycles. The index period may be the entire year or the summer growing season. The 

best index period is determined by considering wetland characteristics for the region, the quality 

and quantity of data available, and estimates of temporal variability (if available). Consideration 

of the data available relative to longer-term oscillations in environmental conditions (e.g., dry 

years, wet years) should also be taken into account such that the data is representative and 

appropriate. Additional information and considerations for establishing an index period are 

discussed in Chapter 7. 

REPRESENTATIVENESS

Data may have been collected for specific purposes. Data collected for toxicity analyses, effluent 

limit determinations, or other pollution problems may not be useful for developing nutrient 

criteria. Further, data collected for specific purposes may not be representative of the region or 

wetland classes of interest. The investigator should determine if all wetlands or a subset of the 

wetlands in the database are representative of the population of wetlands to be characterized. If a 

sufficient sample of representative wetlands cannot be found, then a new survey is strongly 

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
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In order to compare data collected under different sampling programs or by different agencies, 

sampling protocols and analytical methods should demonstrate comparable data. The most 

efficient way to produce comparable data is to use sampling designs and analytical methods that 

are widely used and accepted and examined for compatibility with other monitoring programs 

prior to initiation of a survey. Comparability should be assessed for field sample collection, 

sample preservation, sample preparation and analysis, and among laboratories used for sample 

analyses. 

ACCURACY

To assess the accuracy of field instruments and analytical equipment, a standard (a sample with a 

known value) should be analyzed and the measurement error or bias determined. Internal 

standards should periodically be checked with external standards provided by acknowledged 

sources. At Federal, State, and local government levels, the National Institute of Standards and 

Technology (NIST) provides advisory and research services to all agencies by developing, 

producing, and distributing standard reference materials for vegetation, soils, and sediments. 

Standards and methods of calibration are typically included with turbidity meters, pH meters DO 

meters, and DO testing kits. The U.S. EPA, USGS, and some private companies provide 

reference standards or QC samples for nutrients. 

VARIABILITY

The variability in field measurements and analytical methods should be demonstrated and 

documented to identify the source and magnitude of variability when possible. EPA QA/QC 

guidance provides an explanation and protocols for measuring sampling variability (USEPA 

1998c). 

DATA REDUCTION

For data reduction, it is important to have a clear idea of the analysis that will be performed and 

a clear definition of the sample unit for analysis. For example, a sample unit might be defined as 

“a wetland during July- August.” For each variable measured, a mean value would then be 

estimated for each wetland during the July-August index period on record. Analyses are then 

conducted on the observations (estimated means) for each sample unit, not with the raw data. 

Steps recommended for reducing the data include: 

1. Selecting the long-term time period for analysis; 

2. Selecting an index period; 

3. Selecting relevant variables of interest; 
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4. Identifying the quality of analytical methods; 

5. Identifying the quality of the data recorded; and, 

6. Estimating values for analysis (mean, median, minimum, maximum) based on the 

reduction selected. 

6.5 QUALITY ASSURANCE / QUALITY CONTROL (QA/QC) 

The validity and usefulness of data depend on the care with which they were collected, analyzed, 

and documented. EPA provides guidance on data quality assurance (QA) and quality control 

(QC) (USEPA 1998c) to assure the quality of data. Factors that should be addressed in a QA/QC 

plan are elaborated below. The QA/QC plan should state specific goals for each factor and 

should describe the methods and protocols used to achieve the goals. 

1. Who will use the data? 

2. What the 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 exposureresponse relationships. 

Statistical analyses are used to interpret monitoring data for criteria development. Statistical 

methods are data-driven and range from very simple descriptive statistics to more complex 

statistical analyses. Generally, the type of statistical analysis used for criteria development is 

determined by the source, quality, and quantity of data available. 

7.2 FACTORS AFFECTING ANALYSIS APPROACH 

Wetland systems should be appropriately classified a priori for nutrient criteria development to 

minimize natural background variation (see Chapter 3). This section discusses some of the 

factors that should be considered when classifying wetland systems and in determining the 

choice of predictor (causal) and response variables to include in the analysis. 

Wetland hydrogeomorphic type http://el.erdc.usace.army.mil/wrap/wrap.html may determine the 

sensitivity of wetlands to nutrient inputs, as well as the interaction of nutrients with other driving 

factors in producing an ecological response. Hydrogeomorphic types differ in landscape 

position, predominant water source, and hydrologic exchanges with adjacent water bodies 

(Brinson 1993). These factors, in turn, influence water residence time, hydrologic regime, and 

disturbance regime. In general, isolated depressional wetlands will have greater residence times 

than fringe wetlands, which, in turn, will have greater residence times than riverine wetlands. 

Systems with long residence times are likely to behave more like lakes than flow-through 

systems and may show a greater response to cumulative loadings. Thus, nutrient loading rates or 

indicators thereof are likely to be a more sensitive predictor of ecological effects for depressional 

wetlands, while nutrient water column or sediment concentrations are likely to be a more 

sensitive predictor of responses for riverine wetlands. Water column concentrations will 

influence the response of algal communities, while macrophytes derive nutrients from both the 
SEPTEMBER 2007 Chapter 7. Data Analysis: Experiments, Observational Data, and Modeling 

93 

water column and sediments. Fringe wetlands are likely to be influenced both by concentration 

of nutrients in the adjacent lake or estuary as well as the accumulation of nutrients within these 

systems from groundwater inflow and, in some cases, riverine inputs. The relative influence of 

these two sources will depend on the exchange rate with the adjacent lake, e.g., through seiche 

activity (Keough et al., 1999; Trebitz et al., 2002). In practice, it is difficult to measure loadings 

from multiple sources including groundwater and exchange with adjacent water bodies. If 

sediment concentrations are shown to be a good indicator of recent loading rates, then sediment 

concentrations might be the best predictor to use across systems. 

It may be important to control for ancillary factors when teasing out the relationship between 

nutrients and vegetation community response, particularly if those factors interact with nutrients 

in eliciting responses. For example, riverine and fringe wetlands differ from basin wetlands in 

the frequency and intensity of disturbance from flooding events or ice. Day et. al. (1988) 

describe a fertility-disturbance gradient model for riverine wetlands describing how the relative 

dominance of plant guilds with different growth forms and life history strategies depends on the 

interactive effects of productivity, fertility, disturbance, and water level. In depressional 

wetlands, the model could be simplified to include only the interaction of fertility with the 

hydrologic regime. Disturbance regimes and water level could be incorporated into analysis of 

cause-effect relationships either as categorical factors or as covariates. 

The selection of assessment and measurement of response attributes for determining ecological 

response to nutrient loadings should depend, in part, on designated uses assigned to wetlands as 

part of standards development. Designated uses such as recreation (aesthetics and contact) or 

drinking water are not typically assigned to wetlands; thus, defining nuisance algal blooms in 

terms of taste or odor problems or aesthetic considerations may not be appropriate for wetlands. 

Guidance for the definition of aquatic life use is currently being refined to describe six stages of 

impact along a human disturbance gradient, from pristine reference condition to heavily 

degraded sites (Figure 7.1, Stevenson and Hauer 2002, Davies and Jackson 2006). The relative 

abundance of sensitive native taxa is expected to shift with relatively minor impacts, while 

organism condition or functional attributes are relatively robust to altered loadings. However, if 

maintenance of ecological integrity of sensitive downstream systems is of concern, then it may 

be important to measure some functional attributes related to nutrient retention. Stevenson and 

Hauer (2002) have suggested a series of “resource condition tiers” analogous to those defined for 

biological condition but related to ecosystem functions. Tier 1 requirements are proposed as: 

“Native structure and function of the hydrologic and geomorphic regimes and processes are in 

the natural range of variation in time and space.” Thus maintenance of structure and function of 

upstream processes should be protective of downstream biological conditions. 
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Bio

ol gic

al C

o

n

dit oi n

BCG Model: Snap Shot

Increasing Levels of Stressors

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

1

2

3

4

5

6

Figure 7.1. Biological condition gradient model describing biotic community condition as levels 

of stressors increase. 

7.3 DISTRIBUTION-BASED APPROACHES 

Frequency distributions can aid in the setting of criteria by describing central tendency and 

variability among wetlands. Approaches to numeric nutrient criteria development based on 

frequency distributions do not require specific knowledge of individual wetland condition prior 

to setting criteria. Criteria are based on and, in a sense, developed relative to the conditions of 

the population of wetlands of a given class. 

The simplest statistic describing the shape of distributions refers to quartiles, or the 25th and the 

75th percentile. These can be defined as the observation which has 25% of the observations on 

one side and 75% on the other side in the case of the first quartile (25th percentile), or vice versa 

in the case of the third quartile (75th percentile). In the same manner, the median is the second 

quartile or the 50th percentile. Graphically, this is depicted in boxplots as the box length, the 

lower extreme represents the first quartile, and the upper extreme represents the third quartile, 

the area inside the box encompassing 50% of the data. 

Distributions of nutrient exposure metrics or response variables can be developed to represent 

either an entire population of wetlands or only a subset of those considered to be minimally 
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95 

impacted. In either case, a population of wetlands should be defined narrowly enough through 

classification so that the range in attributes due to natural variability does not equal or exceed the 

range in attributes related to anthropogenic effects. The effects of natural variability can be 

minimized by classifying wetlands by type and/or region. Nutrient ecoregions define one 

potential regional classification system (USEPA 2000). Alternatively, thresholds in landscape or 

watershed attributes defining natural breakpoints in nutrient concentrations can be determined 

objectively through procedures such as classification and regression tree (CART) analysis 

(Robertson et. al., 2001). If a distribution-based approach is used, periodic reviews using 

empirical data that relate a measured value to an ecological attribute or ecosystem function can 

validate the assumptions of the chosen percentiles. 

7.4 RESPONSE-BASED APPROACHES 

Indicators characterized as “response” or “condition” metrics should be distinguished from 

“stressor” or “causal” indicators, such as nutrient concentrations (Paulsen et al., 1991; USEPA 

1998a; Stevenson 2004a). While both “response“ and “causal” indicators could be used in a 

single multimetric index, it is recommended that separate multimetric indices be used for 

“response” and “causal” assessment. Distinguishing between “response” and “causal” indices 

can be accomplished utilizing a risk assessment approach with separate hazard and exposure 

assessments that are linked to response-stressor relationships (USEPA 1996, 1998a; Stevenson 

1998; Stevenson et al., 2004a, b). A multimetric index that specifically characterizes “responses” 

can be used to clarify goals of management (maintenance or restoration of ecological attributes) 

and to measure whether goals have been attained with nutrient management strategies. 

Response-based multimetric indices can also be used more directly for natural resource damage 

assessments than multimetric indices with response and causal variables. 

Factors that should be considered in selecting indicators include conceptual relevance (relevance 

to the assessment and ecological function), feasibility of implementation (data collection 

logistics, information management, quality assurance, cost), response variability (measurement 

error, seasonal variability, interannual variability, spatial variability, discriminatory ability), and 

interpretation and utility (data quality objectives, assessment thresholds, link to management 

actions) (Jackson et al., 2000). Of these factors, cost, response variability, and ability to meet 

data quality objectives can be assessed through quantitative methods. An analytical 

understanding of the factors that affect wetlands the most will also help States develop the most 

effective monitoring and assessment strategies. 

Designated uses such as contact recreation and drinking water may not be applicable to 

wetlands, hence, it may not be readily apparent what the relative significance of changes in 

different primary producers is for organisms at higher trophic levels. Wetland food webs have 

traditionally been considered to be detritus-based (Odum and de la Cruz 1967; Mann 1972, 

1988). However, more recent research on wetland food webs utilizing stable isotope analysis 
SEPTEMBER 2007 Chapter 7. Data Analysis: Experiments, Observational Data, and Modeling 

96 

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 
SEPTEMBER 2007 Chapter 7. Data Analysis: Experiments, Observational Data, and Modeling 

97 

from macrophyte pollen or diatom frustrules, which will be particularly valuable in the absence 

of sites representing reference condition (Cooper et al., 1999, Jensen et. al., 1999). 

Some ecohydrological models have been derived that incorporate the effect of multiple stressors 

(hydrology, eutrophication, acidity) on wetland vegetation, thus providing a link between 

process-based models and community level response (see Olde Venterink and Wassen 1997 for 

review). These models are based on: 1) a combination of expert opinion to estimate species 

sensitivities, supplemented by multivariate classification of vegetation and environmental data to 

determine boundaries of species guilds; or, 2) field measurements used to derive logistic models 

to quantify dose-response. These approaches could be used to derive wetland nutrient criteria for 

the U.S. provided that models could be calibrated using species and response curves developed 

using data for the U.S. Most multiple-stressor models for wetland vegetation have been 

calibrated using data from Western Europe (Olde Venterink and Wassen 1997). Latour and 

colleagues (Latour and Reiling 1993, Latour et al., 1994) have suggested a mechanism for 

setting nutrient standards using the occurrence probability of species along a trophic gradient to 

extrapolate maximum tolerable concentrations that protect 95% of species. 

A series of linked empirical relationships for wetlands may be most effective for developing 

nutrient criteria. Linked empirical relationships may be most useful in cases where integrative 

exposure measurements such as sediment nutrient concentrations are more sensitive predictors of 

shifts in community composition, or algal P limitation, or other ecological responses 

(phosphatase enzyme assays; Qian et al., 2003) than are spatially and temporally heterogeneous 

water column nutrient concentrations. In these cases, it may be important to develop one set of 

relationships between nutrient loading and exposure indicators for a subset of sites at which 

intensive monitoring is done, and another set of relationships between nutrient exposure and 

ecological response indicators for a larger sample population (Qian et al., 2003). 

7.5 PARTITIONING EFFECTS AMONG MULTIPLE STRESSORS 

Changes in nutrient concentrations within or loadings to wetlands often co-occur with other 

potential stressors such as changes in hydrologic regime and sediment loading. In a few cases, 

researchers have been able to separate the simple effects of nutrient addition through 

manipulations of mesocosms (Busnardo et al., 1992, Gabor et.al., 1994, Murkin et al., 1994, 

McDougal et al., 1997, Hann and Goldsborough 1997), segments of natural systems (Richardson 

and Qian 1999, Thormann and Bayley 1997), or whole wetlands (Spieles and Mitsch 2000). In 

other cases, both simple and interactive effects have been examined experimentally, e.g., to 

separate effects of hydrologic regime from nutrient loading (Neill 1990a, b; Neill 1992, Bayley 

et al., 1985). If nutrient effects are examined by comparing condition of natural wetlands along a 

loading or concentration gradient, effects of other driving factors can be minimized by making 

comparisons among wetlands of similar hydrogeomorphic type and climatic regime within a 

well-defined sampling window. In addition, multivariate techniques for partitioning effects 
SEPTEMBER 2007 Chapter 7. Data Analysis: Experiments, Observational Data, and Modeling 

98 

among multiple factors can be used, such as partial CCA or partial redundancy analysis (Cooper 

et al., 1999, Jensen et al., 1999). 

7.6 STATISTICAL TECHNIQUES 

Quantitative methods can be used to assess metric cost, evaluation, response variability, and 

ability to meet data quality objectives. The most appropriate method varies with respect to the 

indicator or variable being considered. In general, statistical techniques are aimed at making 

conjectures or inferences about a population’s values or relationships between variables in a 

sample randomly taken from the population of interest. In these terms, population is defined as 

all possible values that a certain parameter may take. For example, in the case of total 

phosphorus levels present in marsh sediments in nutrient ecoregion VII, the total population 

would be determined if all the marshes in that ecoregion were sampled, which would negate the 

need for data analysis. Practically, a sample is taken from the population and the characteristics 

associated with that sample (mean, standard deviation) are “transferred” to the entire population. 

Many of the basic statistical techniques are designed to quantify the reliability of this transferred 

estimate by placing a confidence interval over the sample-derived parameter. More complex 

forms of data analysis involve comparisons of these parameters from different populations (for 

example, comparison between sites) or the establishment of complex data models that are 

thought to better describe the original population structure (for example, regression). They are 

still basic inference techniques that utilize sample characteristics to make conjectures about the 

original population. 

A basic and typical issue facing any type of sampling design is the number of samples that 

should be taken to be confident in the translation from samples to population. The degree of 

confidence required should be defined as data quality objectives by the end-user and identify the 

expected statistical rigor for those objectives to be met. There are extensive texts on types and 

manners of sampling schemes; these will not be discussed here. This section is geared to 

determining the minimum data set recommended to work with subsequent sections of the data 

analysis chapter. In interpreting the results of various forms of data analysis, an acceptable level 

of statistical error is formulated; this is called Type I error, or alpha (α). Type I error can be 

defined as the probability of rejecting the null hypothesis (H0) 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 (β), 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. 

 
SEPTEMBER 2007 Chapter 7. Data Analysis: Experiments, Observational Data, and Modeling 

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In experimental or sampling design, of greater interest is a statistic associated with beta (β), 

specifically 1 – β, 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 α 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 (α), and sample size, the relationship between the three factors being relatively 

complex. 

 

1. Effect size is defined as the actual magnitude of the effect of interest. This could be the 

difference between two means or the actual correlation between the variables. The 

relationship between the effect size and power is intuitive; if the effect size is large (for 

example, a large difference between means) this results in a concomitantly large power. 

2. Alpha is related to power; to achieve a higher level of significance, power decreases if 

other factors are kept constant. 

3. Sample size. Generally, this is the easiest factor to control. If the two preceding factors 

are set, increased sample sizes will always result in a greater power. 

As indicated before, the relationship between these three factors is complex and depends on the 

nature of the intended statistical analysis. An online guide for selecting appropriate statistical 

procedures is available at: http://www.socialresearchmethods.net/. Software packages for 

performing power analysis have been reviewed by Thomas and Krebs (1997). Online power 

calculations have been made available by several statistical faculty and are available at these 

Web sites: http://www.math.yorku.ca/SCS/, http://calculators.stat.ucla.edu/powercalc/, 

http://www.surveysystem.com/sscalc.htm, 

http://www.health.ucalgary.ca/~rollin/stats/ssize/index.html, http://www.stat.ohiostate.edu/~jch/ssinput.html, and http://www.stat.uiowa.edu. Additional Web sites are listed in 

Chapter 4 that emphasize designs for monitoring with statistical rigor. 

Metric response variability can be evaluated by examining the signal to noise ratio along a 

gradient of nutrient concentrations or loading rates (Reddy et.al., 1999). The power of regression 

analyses can be determined using the power function for a t-test. Optimization of the design, 

such as the spacing, number of levels of observations, and replication at each level, depend on 

the purpose of the regression analysis (Neter et.al., 1983). 

Multiple correlation analysis can compound uncertainty and in some instances misidentify 

correlations due to chance as relevant. Appropriate corrections (e.g., Bonferroni) should be 

applied to avoid these errors (Rice 1989). 

MULTIMETRIC INDICIES
SEPTEMBER 2007 Chapter 7. Data Analysis: Experiments, Observational Data, and Modeling 

100 

Multimetric indices are valuable for summarizing and communicating results of environmental 

assessments. Use of multimetric indices is one approach in developing criteria. Furthermore, 

preservation of the biotic integrity of algal assemblages, as well as fish and macroinvertebrate 

assemblages, may be an objective for establishing nutrient criteria. Multimetric indices for 

stream macroinvertebrates and fish are common (e.g., Kerans and Karr 1994, Barbour et.al., 

1999), and multimetric indices with benthic algae have recently been developed and tested on a 

relatively limited basis (Kentucky Division of Water 1993; Hill et.al., 2000). Efforts are 

underway to develop multi-metric indices of biotic integrity for wetlands, and methods modules 

are available for characterizing wetland algal, plant, macroinvertebrate, amphibian, and bird 

communities (http://www.epa.gov/waterscience/criteria/wetlands/). Methods for multi-metric 

indices are well developed for streams and are readily transferable to wetlands. However, higher 

trophic levels do not often directly respond to nutrients and therefore may not be as sensitive to 

relatively small changes in nutrient concentrations as algal assemblages. It is recommended that 

relations between biotic integrity of algal or vegetation assemblages and nutrients be defined and 

then related to biotic integrity of macroinvertebrate and fish assemblages in a stepwise, 

mechanistic fashion. The practitioner should realize, however, that wetlands with a history of 

high nutrient loadings have often lost the most sensitive species and in these cases higher trophic 

level species may prove to be the best indicators of current nutrient loadings and wetland 

nutrient condition. 

This section provides an overview for developing a multimetric index that will indicate shifts in 

primary producers that are associated with trophic status in wetlands. The first step in developing 

a multimetric index of trophic status is to select a set of ecological attributes that respond to 

human changes in nutrient concentrations or loading. Attributes that respond to an increase in 

human disturbance are referred to as metrics. Six to 10 metrics should be selected for the index 

based on their sensitivity to human activities that increase nutrient availability (loading and 

concentrations), their precision, and their transferability among regions and habitat types. 

Selected metrics also should respond to the breadth of biological responses to nutrient conditions 

(see discussion of metric properties in McCormick and Cairns 1994). 

Effects of nutrients on primary producers and effects of primary producers on the biotic integrity 

of macroinvertebrates and fish should be characterized to aid in developing nutrient criteria that 

will protect designated uses related to aquatic life (e.g., Miltner and Rankin 1998, King and 

Richardson 2002). 

Another approach for characterizing biotic integrity of assemblages as a function of trophic 

status is to calculate the deviation in species composition or growth forms at assessed sites from 

composition in the reference condition. Similarity or dissimilarity indices can be used for the 

determining the differences in biotic integrity of a wetland in comparison to the reference 

condition. Multivariate similarity or dissimilarity indices need to be calculated for multivariate 

attributes such as taxonomic composition (Stevenson 1984; Raschke 1993) as defined by relative 
SEPTEMBER 2007 Chapter 7. Data Analysis: Experiments, Observational Data, and Modeling 

101 

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 =Σi=1,s min(ai,bi) 

Here ai is the percentage of the ith species in sample a, and bi 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: 

ED = √( Σi=1(ai-bi)

2

) 

Log-transformation of species relative abundances in these calculations can increase precision of 

metrics by reducing variability in the most abundant taxa. However, the practitioner should also 

be aware that transformation, while reducing variability, often decreases sensitivity and the 

ability to distinguish true fine scale changes in community and species composition. 

Theoretically and empirically, we expect to find that multivariate attributes based on taxonomic 

composition more precisely and sensitively respond to nutrient conditions than do univariate 

attributes, for instance multimetric algal assemblages (see discussions in Stevenson and Pan 

1999). 

To develop the multimetric index, metrics should be selected and their values normalized to a 

standard range such that they all increase with trophic status. Criteria for selecting metrics can be 

found in McCormick and Cairns (1994) or many other references. Basically, sensitive and 

precise metrics should be selected for the multimetric index and selected metrics should 

represent a broad range of impacts and, perhaps, designated uses. Values can be normalized to a 

standard range using many techniques. For example, if 10 metrics are used and the maximum 

value of the multimetric index is defined as 100, all 10 metrics should be normalized to the range 

of 10 so that the sum of all metrics would range between 0 and 100. The multimetric index is 

calculated as the sum of all metrics measured in a system. A high value of this multimetric index 

of trophic status would indicate high impacts of nutrients and should be a robust (certain and 

transferable) and moderately sensitive indicator of nutrient impacts in a stream. A 1-3-5 scaling 

technique is commonly used with aquatic invertebrates (Barbour et.al., 1999; Karr and Chu 

1999) and could be used with a multimetric index of trophic status as well. Using the 95th

percentile when developing metrics is an approach that may decrease the influence of outliers 

(Mack 2004). 
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102 

7.7 LINKING NUTRIENT AVAILABILITY TO PRIMARY PRODUCER RESPONSE 

When evaluating the relationships between nutrients and primary producer response within 

wetland systems, it is important to first understand which nutrient is limiting. Once the limiting 

nutrient is defined, critical nutrient concentrations can be specified and nutrient-response 

relationships developed. 

DEFINING THE LIMITING NUTRIENT 

The first step in identifying nutrient-producer relationships should be to define the limiting 

nutrient. Limiting nutrients will control biomass and productivity within a system. However, 

non-limiting nutrients may have other impacts, e.g., toxicological effects related to ammonia 

concentrations in sediments or effects on competitive interactions that determine vegetation 

community composition (Guesewell et.al., 2003). A review of fertilization studies indicated that 

vegetation N:P mass ratios are a good predictor of the nature of nutrient limitation in wetlands, 

with N:P ratios > 16 indicating P limitation at a community level, and N:P ratios < 14 indicative 

of N limitation (Koerselman and Meuleman 1996). Guesewell et.al., (2003) found that 

vegetation N:P ratios were a good predictor of community-level biomass response to fertilization 

by N or P, but for individual species were only predictive of P-limitation and could not 

distinguish between N-limitation, co-limitation, or no limitation. Likewise, N, P, and K levels in 

wet meadow and fen vegetation were found to be correlated with estimated supply rates or 

extractable fractions in soils (Odle Venterink et.al., 2002). A survey of literature values of 

vegetation and soil total N:P ratios by Bedford et.al., (1999) indicated that many temperate North 

American wetlands are either P-limited or co-limited by N and P, especially those with organic 

soils. Only marshes have N:P ratios in both soils and plants indicative of N limitation, while soils 

data suggest that most swamps are also N-limited. 

Many experimental procedures are used to determine which nutrient (N, P, or carbon) limits 

algal growth. Algal growth potential (AGP) bioassays are very useful for determining the 

limiting nutrient (USEPA 1971). Yet, results from such assays usually agree with what would 

have been predicted from N:P biomass ratios, and in some cases N:P ratios in the water. Limiting 

nutrient-potential biomass relationships from AGP bottle tests are useful in projecting maximum 

potential biomass in standing or slow-moving water bodies. However, they are not as useful in 

fast-flowing, and/or gravel or cobble bed environments. Also, the AGP bioassay utilizes a single 

species, which may not be representative of the response of the natural species assemblage. 

Limitation may be detected by other means, such as alkaline-phosphatase activity, to determine 

if phosphorus is limiting. Alkaline phosphatase is an extracellular enzyme excreted by some 

algal species and from roots in some macrophytes in response to P limitation. This enzyme 

hydrolyzes phosphate ester bonds, releasing orthophosphate (PO4) from organic phosphorus 

compounds (Mullholland et.al., 1991). Therefore, the concentration of alkaline phosphatase in 
SEPTEMBER 2007 Chapter 7. Data Analysis: Experiments, Observational Data, and Modeling 

103 

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). 
SEPTEMBER 2007 Chapter 8. Criteria Development 

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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 
SEPTEMBER 2007 Chapter 8. Criteria Development 

105 

interpret and apply criteria, considerations for sampling for comparison to criteria, potential 

modifications to established criteria, and adoption of criteria into water quality standards. 

The RTAG is composed of State and Regional specialists who will help the Agency and States 

establish nutrient criteria for adoption into their water quality standards. Expert evaluations are 

important throughout the criteria development process. The data upon which criteria are based 

and the analyses performed to arrive at criteria should be assessed for veracity and applicability. 

8.2 METHODS FOR DEVELOPING NUTRIENT CRITERIA 

The following discussions focus on three general methods that can be used in developing 

nutrient criteria. First, identification of reference or control systems for each established wetland 

type and class should be based on either best professional judgment (BPJ) or percentile 

selections of data plotted as frequency distributions. The second method uses refinement of 

classification systems, models, and/or examination of system biological attributes to assess the 

relationships among nutrients, vegetation or algae, soil, and other variables. Finally, the third 

method identifies published nutrient and vegetation, algal, and soil relationships and values that 

may be used (or modified for use) as criteria. A weight of evidence approach with multiple 

attributes that combines one or more of these three approaches should produce criteria of 

greater scientific validity. 

USING REFERENCE CONDITION TO ESTABLISH CRITERIA 

One approach to consider in setting criteria is the concept of reference condition. This approach 

involves using relatively undisturbed wetlands as reference systems to serve as examples for the 

natural or least disturbed ecological conditions of a region. These approaches are most useful for 

estimating reference conditions appropriate to the specific designated use for a class of wetlands. 

Three recommended ways of using reference condition to establish criteria are: 

1. Characterize reference systems for each class within a region using best professional 

judgment and use these reference conditions to define criteria. 

2. Identify the 75th to 95th percentile of the frequency distribution for a class of reference 

wetlands as defined in Chapter 3 and use this percentile to define the criteria. 

3. Calculate a 5th to 25th percentile of the frequency distribution of the general population of 

a class of wetlands and use the selected percentile to define the criteria. 

Defining the nutrient condition of wetlands within classes will allow the manager to identify 

protective criteria and determine which systems may benefit from management action. Criteria 

that are identified using reference condition approaches may require comparisons to similar 

systems in other States that share the ecoregion so that reference condition and developed 
SEPTEMBER 2007 Chapter 8. Criteria Development 

106 

criteria can be validated. Furthermore, the 95th percentile of the reference population and the 5th

percentile of the general population are best used to define the criteria when there is great 

confidence that the group of reference waters truly reflects reference conditions as opposed, for 

example, to best available condition. 

Reference wetlands should be identified for each class of wetland within a State or ecoregion 

and then characterized with respect to external nutrient loading, water column N and P, biotic 

response variables (macrophytes, algae, soils) and supporting environmental conditions. 

Wetlands classified as reference quality should be verified by comparing the data from the 

reference systems to general population data for each wetland class. Reference systems should 

be minimally disturbed and should have biotic response values that reflect this condition. 

 

Conditions at reference sites may be characterized using either of two frequency distribution 

approaches (see 2 and 3 above). In both approaches, an optimal reference condition value is 

selected from the distribution of an available set of wetland data for a given wetland class. This 

approach may be of limited value at this time because few States currently collect wetland 

monitoring data. However, as more wetlands are monitored and more data become available, this 

approach may become more viable. 

In the first frequency distribution approach, a percentile (75th – 95th is recommended) is selected 

from the distribution of causal and biotic response variables of reference systems selected a 

priori based on very specific criteria (i.e., highest quality or least impacted wetlands for that 

wetland class within a region). The values for variables at the selected quartile may be used as 

the basis for nutrient criteria. The selection of a specific percentile as the basis for the criterion 

should be determined by the uses designated for that water. 

If reference wetlands of a given class are rare within a given region or if inadequate information 

is available to assign wetlands with historic nutrient data as “reference” versus “impacted” 

wetlands, another approach may be appropriate. The second frequency distribution approach 

involves selecting a percentile of: (1) all wetland data in the class (reference and non-reference); 

or, (2) a random sample distribution of all wetland data within a particular class. Due to the 

random selection process, a lower percentile should be selected because the sample distribution 

is expected to contain some degraded systems. This option is most useful in regions where the 

number of legitimate “natural” reference wetlands is usually very small, such as in highly 

developed land use areas (e.g., the agricultural lands of the Midwest and the urbanized east or 

west coasts). EPA’s recommendation in this case is the 5th to 25th percentile depending upon the 

number of “natural” reference systems available. If almost all systems are impaired to some 

extent, then a lower percentile, generally the 5th percentile, is recommended for selection of 

reference wetlands. 

Both the 75th percentile for the subset of reference systems and the 5th to 25th percentile from a 

representative random sample distribution are only recommendations. The actual distribution of 
SEPTEMBER 2007 Chapter 8. Criteria Development 

107 

the observations should be the major determinant of the threshold point chosen. For example, a 

bi-modal distribution of sediment or water-column nutrients might indicate a natural breakpoint 

between reference and enriched systems. To illustrate, Figure 8.1 shows both options and 

illustrates the presumption that these two alternative methods should approach a common 

reference condition along a continuum of data points. In this illustration, the 75th percentile of 

the reference data distribution produces an extractable soil P reference condition that 

corresponds to the 25th percentile of the random sample distribution. 

75th

25th

Frequency

Concentration

75th percentile of 

reference population is 

the starting point for 

criteria.

Nutrient data from reference waters (blue) or 

from all waters (gold) similar physical 

characteristics.

Measurable Effect

Concentration

Effects thresholds 

can help justify 

criterion value.

Paired nutrient and effects data from waters 

with similar physical characteristics.

75th

25th

Figure 8.1 Use of frequency distributions of nutrient concentration for establishing criteria (left 

graphic), and use of effects thresholds with nutrient concentration for establishing criteria (right 

graphic). 

The choice of a distribution cut-off to define the upper range of reference wetland nutrient levels 

is analogous to defining an acceptable level of Type I error, the frequency for rejecting wetlands 

as members of the “unimpacted” class when in fact they are part of the reference wetland 
SEPTEMBER 2007 Chapter 8. Criteria Development 

108 

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 tradeoff between Type I and Type II errors. When additional information is available, it may be 

possible to justify a range of values that are representative of least-impaired wetlands that would 

reduce Type I errors on a system by system basis. 

State water quality managers also may consider analyzing wetlands data based on designated use 

classifications. Using this approach, frequency distributions for specific designated uses, as 

opposed to frequency distributions of reference or general populations, could be examined and 

criteria proposed based on maintenance of high quality systems that are representative of each 

designated use. For example, one criterion could be derived that protects superior quality 

wetland habitat (SWLH), and a second criterion could be identified that maintains good quality 

wetland habitat (function maintained but some loss of sensitive species (Figure 8.2); see Office 

of Water tiered aquatic life use training module: 

(http://www.epa.gov/waterscience/biocriteria/modules/wet101-05-alus-monitoring.pdf). This 

recommended approach is designated as the Tiered Aquatic Life Use (TALU) and is being 

developed by the EPA Office of Water in a more detailed publication. Using this approach, a 

criterion range is created and a greater number of wetland systems will likely be considered 

protective of the designated use. In this case, emphasis may be shifted from managing wetland 

systems based on a central tendency,toward more pristine systems associated with Tiers I and II. 

This approach also will aid in prioritizing systems for protection and restoration. Subsequent 

management efforts using this approach should focus on improving wetland conditions so that, 

over time, plots of wetland data shift to the left (i.e., improved nutrient condition) of their initial 

position. 

p.p 
SEPTEMBER 2007 Chapter 8. Criteria Development 

109 

Biological Condition 

Low Increasing Effects of Stressors High

1

Native or natural condition

2 Minimal loss of species; some 

density changes may occur

3

Some replacement of 

sensitive-rare species; 

functions fully 

maintained 4

Some sensitive species 

maintained; altered 

distributions; functions 

largely maintained

5

6

Tolerant species show 

increasing dominance; 

sensitive species are rare; 

functions altered Severe alteration of 

structure and function

Natural

Degraded

NA

B

C

AA

A

MAINE TALU

Figure 8.2. Tiered Aquatic Life Use model used in Maine. 

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 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: Louisiana State University’s School of the Coast and Environment 
SEPTEMBER 2007 Chapter 8. Criteria Development 

110 

[http://www.wetlandbiogeochemistry.lsu.edu/] 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). 

 
SEPTEMBER 2007 Chapter 8. Criteria Development 

111 

Figure 8.3. Percent calcareous algal mat cover in relation to distance from the P source showing 

the loss of the calcareous algal mat in those sites closer to the source (Stevenson et.al., 2002). 

USING DATA PUBLISHED IN THE LITERATURE 

Values from the published literature may be used to develop nutrient criteria if a strong rationale 

is presented that demonstrates the suitability of these data to the wetland of interest (i.e., the 

system of interest should share the same characteristics with the systems used to derive the 

published values). Published data, if there is enough of it, could be used to develop criteria for: 

(1) reference condition; (2) predictive (cause and effect) relationships between nutrients and 

biotic response variables; (3) tiered criteria; or, (4) criteria that exhibit a threshold response to 

nutrients. However, published data from similar wetlands should not substitute for collection and 

analysis of data from the wetland or wetlands of interest. 

CONSIDERATIONS FOR DOWNSTREAM RECEIVING WATERS

More stringent nutrient criteria may be appropriate for wetlands that drain into lentic or standing 

waters. For example, it is proposed that 35 μg/L TP concentration and a mean concentration of 8 

μg/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, 
SEPTEMBER 2007 Chapter 8. Criteria Development 

112 

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. 
SEPTEMBER 2007 REFERENCES 

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 Williams, J. R. and H. D. Berndt, 1977. Sediment yield prediction based on watershed 

hydrology. Transactions of the ASAE. 20:1100-04. 

Williams, J. R., Jones, C. A., Kiniry, J. R. and Spanel, D. A. 1989. The EPIC crop growth model. 

Transactions of the ASAE. 32:497-511. 

Young, R., C. A. Onstad, D. D. Bosch, and W. P. Anderson. 1987. AGNPS: Agricultural NonPoint Source Pollution Model: A watershed analysis tool. USDA-Agricultural Research 

Service. Conservation Research Report 35, 77 pp. 
SEPTEMBER 2007 APPENDIX A: ACRONYM LIST AND GLOSSARY 

155 

APPENDIX A. ACRONYM LIST AND GLOSSARY 

ACRONYMS

ACOE/ACE/COE - Army Corps of Engineers 

AGNPS - Agricultural Nonpoint Source Pollution model 

ARS - Agricultural Research Service 

BACI - Before/After, Control/Impact 

BMP - Best Management Practice 

BuRec - Bureau of Reclamation 

CCC - Commodity Credit Corporation 

CENR - Committee for the Environment and Natural Resources 

CGP - Construction General Permit 

CHN - Carbon-Hydrogen-Nitrogen 

CPGL - Conservation of Private Grazing Land 

CPP - Continuing Planning Process 

CREP - Conservation Reserve Enhancement Program 

CRP - Conservation Reserve Program 

CSO - Combined Sewer Overflow 

CWA - Clean Water Act 

CZARA - Coastal Zone Act Reauthorization Amendment 

DIP - Dissolved inorganic phosphorus 

DO - Dissolved oxygen 

DOP - Dissolved organic phosphorus 

DRP - Dissolved reactive phosphorus 

ECARP - Environmental Conservation Acreage Reserve Program 

EDAS - Ecological Data Application System 

Eh - Redox potential 

EMAP - Environmental Monitoring and Assessment Program 

EQIP - Environmental Quality Incentive Program 

FDEP - Florida Department of Environmental Protection 

FIP - Forestry Incentive Program 

GIS - Geographic Information System 

GPS - Geospatial Positioning System 

GWLF - Generalized Watershed Loading Function 

HEL - Highly erodible land 

HGM - Hydrogeomorphic approach 
SEPTEMBER 2007 APPENDIX A: ACRONYM LIST AND GLOSSARY 

156 

HSPF - Hydrologic Simulation Program - Fortran 

MPCA - Minnesota Pollution Control Agency 

NAAQS - National Ambient Air Quality Standard 

NASQAN - National Stream Quality Assessment Network 

NAWQA - National Water Quality Assessment 

NIS - Network Information System 

NIST - National Institute of Standards and Technology 

NOAA - National Oceanic and Atmospheric Administration 

NPDES - National Pollution Discharge Elimination System 

NPP - Net primary production 

NRCS - Natural Resources Conservation Service 

NSF - National Science Foundation 

NWI - National Wetlands Inventory 

OH EPA - Ohio EPA 

ONRW - Outstanding Natural Resource Waters 

PCB - Polychlorinated biphenyls 

PCS - Permit Compliance System 

PIP - Particulate inorganic phosphorus 

POP - Particulate organic phosphorus 

PSA - Particle size analysis 

QA/QC - Quality Assurance/Quality Control 

QC - Quality Control 

REMAP - Regional Environmental Monitoring and Assessment Program 

RF3 - Reach File 3 

SCS - Soil Conservation Service 

SPARROW - Spatially Referenced Regressions on Watersheds 

SRP - Soluble reactive phosphorus 

STORET - Storage and Retrieval System 

SWAT - Soil and Water Assessment Tool 

TKN - Total Kjeldahl Nitrogen 

TMDL - Total Maximum Daily Load 

TP - Total Phosphorus 

TWINSPAN - 

USDA - United States Department of Agriculture 

USEPA - United States Environmental Protection Agency 

USFWS - United States Fish and Wildlife Service 

USGS - United States Geological Survey 

WEBB - Water, Energy, and Biogeochemical Budgets 

WHIP - Wildlife Habitat Incentive Program 

WLA - Wasteload Allocation 

WQBEL - Water Quality Based Effluent Limit 

WQS - Water Quality Standard 

WRP - Wetlands Reserve Program 
SEPTEMBER 2007 APPENDIX A: ACRONYM LIST AND GLOSSARY 

157 

GLOSSARY

biocriteria 

(biological criteria) Narrative or numeric expressions that describe the desired biological condition of aquatic 

communities inhabiting particular types of waterbodies and serve as an index of aquatic community health. (USEPA 

1994). 

cluster analysis 

An exploratory multivariate statistical technique that groups similar entities in an hierarchical structure. 

criteria 

Elements of State water quality standards, expressed as constituent concentrations, levels, or narrative statements, 

representing a quality of water that supports a particular use. When criteria are met, water quality will generally 

protect the designated use (40 CFR 131.3(b)). 

designated use(s) 

Uses defined in water quality standards for each waterbody or segment whether or not the use is being attained 

(USEPA 1994). 

detritus 

Unconsolidated sediments comprised of both inorganic and dead and decaying 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 

et.al., 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 Horne 1983). 

GIS (Geographical Information Systems)

A computerized information system that can input, store, manipulate, analyze, and display geographically 

referenced data to support decision-making processes. (NDWP Water Words Dictionary) 

HGM, hydrogeomorphic 
SEPTEMBER 2007 APPENDIX A: ACRONYM LIST AND GLOSSARY 

158 

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 Horne 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 Horne 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 Horne 1983). 

μg/L 

micrograms per liter, 10-6 grams per liter 

mg/L 

milligrams per liter, 10-3 grams per liter 

mineral soil flats 

Level wetland landform with predominantly mineral soils 

minerotrophic 

Receiving water inputs from groundwater, and thus higher in salt content (major ions) and pH than ombrotrophic 

systems. 

mixohaline 

Water with salinity of 0.5 to 30%, due to ocean salts. 
SEPTEMBER 2007 APPENDIX A: ACRONYM LIST AND GLOSSARY 

159 

M 

Molarity, moles of an element as concentration 

multivariate 

Type of statistics that relates one or more independent (explanatory) variables with multiple dependent (response) 

variables. 

nutrient ecoregion 

Level II ecoregions defined by Omernik according to expected similarity in attributes affecting nutrient supply ( 

http://www.epa.gov/OST/standards/ecomap.html). 

oligotrophic 

Trophic status of a waterbody characterized by a small supply of nutrients (low nutrient release from sediments), 

low production of organic matter, low rates of decomposition, oxidizing hypolimnetic condition (high DO) (Wetzel 

1983). 

palustrine 

“Nontidal wetlands dominated by trees, shrubs, persistent emergents, emergent mosses orlichens, and all such 

wetlands that occur in tidal areas where salinity due to ocean-derived salts is below 0.5%. It also includes wetlands 

lacking such vegetation, but with all of the following four characteristics: (1) area less than 8 ha (20 acres); (2) 

active wave-formed or bedrock shoreline features lacking; (3) water depth in the deepest part of basin less than 2 m 

at low water; and, (4) salinity due to ocean-derived salts less than 0.5%” (Cowardin 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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160 

waters of the U.S. 

Waters of the United States is defined at 40 CFR § 230.3(s)) as including: 

a. All waters that are currently used, were used in the past, or may be susceptible to use in interstate or foreign 

commerce, including all waters that are subject to the ebb and flow of the tide; 

b. All interstate waters, including interstate wetlands; and, 

c. All other waters such as interstate lakes, rivers, streams (including intermittent streams), mudflats, sandflats, 

wetlands, sloughs, prairie potholes, wet meadows, playa lakes, or natural ponds the use, degradation, or destruction 

of which would affect or could affect interstate or foreign commerce including any such waters: 

 1 That are or could be used by interstate or foreign travelers for recreational or other purposes; 

 2 From which fish or shellfish are or could be taken and sold in interstate or foreign 

 commerce; or, 

 3 That are used or could be used for industrial purposes by industries in interstate 

 commerce; 

d. All impoundments of waters otherwise defined as waters of the United States under this definition; 

e. Tributaries of waters identified in paragraphs (a) through (d) of this definition; 

f. The territorial sea; and, 

g. Wetlands adjacent to waters (other than waters that are themselves wetlands) identified in paragraphs (a) through 

(f) of this definition. 

For further information regarding the scope of ‘waters of the U.S.’ in light of the U.S. Supreme Court’s 2006 

decision in Rapanos v. United States, see “Clean Water Act Jurisdiction Following the U.S. Supreme Court’s 

Decision in Rapanos v. United States & Carabell v. United States,” which was jointly issued by the U.S. 

Environmental Protection Agency and the Army Corps of Engineers and is available at: 

http://www.epa.gov/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)]. 
SEPTEMBER 2007 APPENDIX B: CASE STUDIES 

161 

APPENDIX B. CASE STUDY: DERIVING A PHOSPHORUS CRITERION FOR THE 

FLORIDA EVERGLADES

INTRODUCTION

The Everglades (Figure B1.1) is the largest subtropical wetland in North America and is widely 

recognized for its unique ecological character. It has been affected for more than a century by 

rapid population growth in south Florida. Roughly half of the ecosystem has been drained and 

converted to agricultural and urban uses. Among other changes, the conversion of 500,000 acres 

of the northern Everglades to agriculture (the Everglades Agricultural Area or EAA) and the 

subsequent diking of the southern rim of Lake Okeechobee eliminated the normal seasonal flow 

of water southward from Lake Okeechobee. Furthermore, the construction of a complex network 

of internal canals and levees disrupted the natural sheetflow of water through the system and 

created a series of impounded wetlands known as “Water Conservation Areas” or WCAs. This 

conversion from a hydrologically open to a highly managed wetland occurred gradually, 

beginning with the excavation of four major canals during the 1900-1910 period and culminating 

with the construction of the Central and South Florida Flood Control Project (CSFFCP) during 

the 1950s and 60s (Light and Dineen 1994). 

The remnant Everglades is managed for multiple and often conflicting uses including water 

supply, flood control, and the hydrologic needs of the natural ecosystem. Water management 

operations have altered the quantity, quality, timing, and delivery of flows to the Everglades 

relative to the pre-disturbance system; some parts of the system have been damaged by 

overdrainage, excessive flooding in other areas has stressed native vegetation communities. 

Changes to the seasonal pattern of flooding and drying have influenced many ecological 

processes, including changes in the dominant micro- and macro-phytic vegetation, declines in 

critical species, and the nesting success of wading bird populations that rely on drawdowns 

during a narrow window of time to concentrate fish prey. Canal inputs containing runoff from 

agricultural and urban lands contribute roughly 50% of flows to the managed system and have 

increased loads of nutrients and contaminants. In particular, phosphorus (P) has been identified 

as a key limiting nutrient in the Everglades and increased inputs of this nutrient have been 

identified as a significant factor affecting ecological processes and communities. 

The primary source of P to the pre-disturbance Everglades was rainfall, although seasonal flows 

from Lake Okeechobee likely contributed significant P to the northern fringe of the wetland. 

Prior to the implementation of P control efforts in the late 1990s, canal flows were estimated to 

contribute more than half of the P load to the managed Everglades (SFWMD 1992). Discharge 

from the EAA is the main source of water to the Everglades, with approximately 500,000 acres 

of farmland draining southward via SFWMD canals, and is the major source of anthropogenic P. 

Significant inputs also come from Lake Okeechobee, a naturally mesotrophic lake that has also 

been enriched by agricultural runoff. Several other agricultural and urban catchments contribute 
SEPTEMBER 2007 APPENDIX B: CASE STUDIES 

162 

Appendix B1. Figure B1.1. 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. 

Everglades 

Agricultura

l 

LNW

WC

A 

WCA 

Everglade

s 

National 

Lake 

Area of Okeechobe

EnlargemenFLORIDA
SEPTEMBER 2007 APPENDIX B: CASE STUDIES 

163 

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 Penriched discharges and associated impacts to occur in the Everglades. Settlement of this lawsuit 

eventually resulted in the enactment of the Everglades Forever Act by the Florida Legislature in 

1994, which required the Florida Department of Environmental Protection (FDEP) to derive a 

numeric water quality criterion for P that would “prevent ecological imbalances in natural 

populations of flora or fauna” in the Everglades. These legal and legislative events provided the 

basis for numerous research and monitoring efforts designed to better understand the effects of P 

enrichment and to determine levels of enrichment that produced undesirable ecosystem changes. 

Research and monitoring were initiated by the State of Florida (the Florida Department of 

Environmental Protection and the South Florida Water Management District) and other 

university research groups (e.g., Duke University, Florida International University, University of 

Florida) to better understand ecological responses to anthropogenic P inputs and to identify a P 

concentration or range of concentrations that result in unacceptable degradation of the 

Everglades ecosystem. This case study reviews research and monitoring conducted by the State 

to derive a P criterion for the Everglades. This criterion was proposed by the FDEP in 2001 and 

approved in 2003. This process is divided into three parts: 

1. Define the reference (i.e., historical) conditions for P and the oligotrophic ecology of the 

Everglades; 

2. Determine the types of ecological impacts caused by P enrichment; and, 

3. Identify wetland P concentrations that produce these impacts,and determine a 

criterion that will protect the resource from those impacts. 

DEFINING THE REFERENCE CONDITION

Several sources of information were used to characterize reference conditions across the 

Everglades. Sampling in minimally impacted locations (i.e., reference sites) believed to best 

reflect historical conditions provided the quantitative basis for establishing reference conditions 

with respect to P concentrations and associated ecological conditions. Where possible, this 
SEPTEMBER 2007 APPENDIX B: CASE STUDIES 

164 

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 B1.1). 

Water Column Phosphorus 

Nutrient inputs to the Everglades were historically derived primarily from atmospheric 

deposition (rainfall and dry fallout), which is typically low in P. Historical loading rates have 

been estimated from annual atmospheric P inputs in south Florida and reconstructions of P 

accumulation in Everglades soils and probably averaged less than 0.1 g P m-2 

y

-1 (SFWMD 

1992). Atmospheric inputs of P were augmented by inflows from Lake Okeechobee, which was 

connected by surface-water flows to the northern Everglades during periods of high water 

(Parker et.al., 1955). While inflows from this historically eutrophic lake were undoubtedly 

enriched in P compared with the Everglades, the influence of these inputs were likely limited to 

wetlands along the lake’s southern fringe (Snyder and Davidson 1994) as is demonstrated by the 

limited extent of pond apple and other vegetation that require more nutrients for growth than the 

sawgrass (Cladium jamaicense) that dominates most of the Everglades. 

Interior areas of the Everglades generally retain the oligotrophic characteristics of the 

predrainage ecosystem and, thus, provide the best contemporary information on historical P 

concentrations. Water chemistry data were available for several interior locations that had been 

sampled by the State for many years. Median water-column TP concentrations at these stations 

ranged between 4 and 10 μg L-1, with lowest concentrations occurring in southern areas that 

have been least affected by anthropogenic P loads (Figure B1.2). Phosphorus concentrations >10 

μg L-1 were measured periodically at many of these sites. Isolated high P concentrations at 

reference stations were attributed to P released as a result of oxidation of exposed soils, 

increased fire frequency during droughts, and difficulties in collecting water samples that are not 

contaminated by flocculent wetland sediments when water depths are low. Data from reference 

sites may represent an upper estimate of historical TP concentrations in the Everglades since 
SEPTEMBER 2007 APPENDIX B: CASE STUDIES 

165 

several stations are located in areas that either have been overdrained, a condition which 

promotes soil oxidation and P release, or so heavily exposed to canal inflows (e.g., WCA 2A) 

that some P inputs have likely intruded even into interior areas. However, in the absence of 

reliable historical data these values were deemed as best available for defining reference 

condition. 

Soil Phosphorus 

Extensive soil mapping projects across interior portions of the central and northern Everglades 

indicate a reference range for soil TP in the surface 0-10 cm of soil of between 200 and 500 mg 

kg-1 on a mass basis (DeBusk et.al., 1994, Reddy et.al., 1994a, Newman et.al., 1997, Richardson 

et.al., 1997a, Newman et.al., 1998). Fewer data are available from ENP, but available evidence 

indicates background concentrations of < 400 mg kg-1 (Doren et.al., 1997). Soil P content also 

varies volumetrically as a function of changing soil bulk density. The typical bulk density of 

flooded Everglades peat soils is approximately 0.08 g cm-3, whereas soils that have been 

subjected to extended dry out and oxidation can have bulk densities greater than 0.2 g cm-3

(Newman et.al., 1998). Increases in volumetric nutrient concentrations resulting from increased 

bulk density can have a stimulatory effect on plant growth even in the absence of external P 

inputs (see Chapter 2). Following correction for the varying bulk densities in the peat soils of 

the Everglades, a historical TP concentration of <40 μg cm-3 may be applicable for most regions 

(DeBusk et.al., 1994, Reddy et.al., 1994a, Newman et.al., 1997, Newman et.al., 1998, Reddy 

et.al., 1998). In the LNWR, most of the interior area has soil TP < 20 μg TP cm-3 (Newman 

et.al., 1997). 
SEPTEMBER 2007 APPENDIX B: CASE STUDIES 

166 

Hydrologic Unit

Water-column TP (μg/L)

1

10

100

1000

 LNWR WCA2A WCA3A ENP

Appendix B1. 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 μg L-1). 

REFERENCE ECOLOGICAL CONDITIONS

The Everglades is perhaps the most intensively studied wetland in the world and, therefore, the 

ecological attributes that defined the predisturbance structure and function of this ecosystem are 

well understood compared with most wetlands. Clearly, not all of the valued ecological attributes 

of this or any other wetland are affected directly by P enrichment. Thus, in order to define the 

reference condition of the ecosystem with respect to the role of P, this assessment focused on 

those processes and communities that are most sensitive to P enrichment. Based on available 

information and preliminary scoping studies, five ecological features were selected as biotic 

response variables. These features included three indicators of ecosystem structure, one indicator 

of ecosystem function, and one indicator of landscape change. Structural indicators included the 

periphyton community, dominant macrophyte populations, and the benthic macroinvertebrate 

community. Diel fluctuations in water column DO provided an important indicator of shifts in 
SEPTEMBER 2007 APPENDIX B: CASE STUDIES 

167 

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 

(Scheidt 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. 
SEPTEMBER 2007 APPENDIX B: CASE STUDIES 

168 

Dissolved Oxygen 

Interior Everglades habitats exhibit characteristic diel fluctuations in water-column dissolved 

oxygen (DO), although aerobic conditions are generally maintained throughout much or all of 

the diel cycle (Belanger et.al., 1989, McCormick et.al., 1997, McCormick and Laing 2003). High 

daytime concentrations in open-water habitats (i.e., sloughs, wet prairies) are a product of 

photosynthesis by periphyton and other submerged vegetation. These habitats may serve as 

oxygen sources for adjacent sawgrass stands, where submerged productivity is low (Belanger 

et.al., 1989). Oxygen concentrations decline rapidly during the night due to periphyton and 

sediment microbial respiration and generally fall below the 5 mg L-1 standard for Class III 

Florida waters (Criterion 17-302.560(21), F.A.C.). However, these diurnal excursions are 

characteristic of reference areas throughout the Everglades (McCormick et.al., 1997) and are not 

considered a violation of the Class III standard (Nearhoof 1992). In fact, a site specific criterion 

for DO has been adopted by the State; a copy of the technical support document (Weaver 2004) 

can be found at: 

http://www.dep.state.fl.us/water/wqssp/everglades/docs/DOTechSupportDOC2004.pdf. 

Vegetation

The vegetation communities characteristic of the pristine Everglades are dominated by species 

adapted to low P, seasonal patterns of wetting and drying, and periodic natural disturbances such 

as fire, drought, and occasional freezes (Duever et.al., 1994, Davis 1943, Steward and Ornes 

1983, Parker 1974). Major aquatic vegetation habitats in oligotrophic areas include sawgrass 

wetlands, wet prairies, and sloughs (Loveless 1959, Gunderson 1994). The spatial arrangement 

of these habitats is dynamic and controlled by environmental factors such as fire, water depth, 

nutrient availability, and local topography (Loveless 1959). 

Sawgrass (Cladium jamaicense) is the dominant macrophyte in the Everglades, and stands of this 

species compromise approximately 65 to 70% of the total vegetation cover of the Everglades 

(Loveless 1959). Wet prairies include a collection of low-stature, graminoid communities 

occurring on both peat and marl soils (Gunderson 1994). Dominant macrophyte taxa in these 

habitats include Rhynchospora, Panicum, and Eleocharis (Loveless 1959, Craighead 1971). 

Sloughs are deeper water habitats that remain wet most or all of the year and are characterized 

by floating macrophytes such as fragrant white water lily (Nymphaea odorata), floating hearts 

(Nymphoides Aquaticum), and spatterdock (Nuphar 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. 
SEPTEMBER 2007 APPENDIX B: CASE STUDIES 

169 

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 lowP conditions (Steward and Ornes 1983, Craft et.al., 1995). Recent experimental evidence in the 

Everglades National Park (Daoust and Childers 1999) has shown that other native vegetation 

associations such as wet prairie communities are also limited by P. 

Historically, cattail (Typha spp.) was one of several minor macrophyte species native to the 

Everglades (Davis 1943, Loveless 1959). In particular, cattail is believed to have been associated 

largely with areas of disturbance such as alligator holes and recent burns (Davis 1994). Analyses 

of Everglades peat deposits reveal no evidence of cattail peat, although the presence of cattail 

pollen indicates its presence historically in some areas (Gleason and Stone 1994, Davis et.al., 

1994, Bartow et.al., 1996). Findings such as these confirm the historical presence of cattail in the 

Everglades but provide no evidence for the existence of dense cattail stands covering large areas 

(Wood and Tanner 1990) as now occurs in the northern Everglades. In contrast, sawgrass and 

water lily peats have been major freshwater Everglades soils for approximately 4,000 years 

(McDowell et.al., 1969).

Macroinvertebrates 

Aquatic invertebrates (e.g., insects, snails, and crayfish) represent a key intermediate position in 

energy flow through the Everglades food web as these taxa are the direct consumers of primary 

production and, in turn, are consumed by vertebrate predators. Invertebrates occupy several 

functional niches within the Everglades food web; however, most taxa are direct consumers of 

periphyton and/or plant detritus (e.g., Rader and Richardson 1994, McCormick et.al., 2004). 

Rader (1994) sampled both periphyton and macrophyte habitats in this same area and, based on 

the proportional abundance of different functional groups, suggested that grazer (periphyton) and 

detrital (plant) pathways contributed equally to energy flow in low-nutrient areas of the 

Everglades. 

The macroinvertebrate fauna of the Everglades is fairly diverse (approximately 200 taxa 

identified) and is dominated by Diptera (49 taxa), Coleoptera (48 taxa), Gastropoda (17 taxa), 

Odonata (14 taxa), and Oligochaeta (11 taxa) (Rader 1999). Most studies have focused on a few 

conspicuous species (e.g., crayfish and apple snails) considered to be of special importance to 

vertebrate predators, and relatively little is known about the distribution and environmental 

tolerances of most taxa. An assemblage of benthic microinvertebrates (meiofauna) dominated by 

Copepoda and Cladocera is also present in the Everglades (Loftus et.al., 1986), but even less is 

known about the distribution and ecology of these organisms. 
SEPTEMBER 2007 APPENDIX B: CASE STUDIES 

170 

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 detritivoredominated assemblage in sawgrass stands. Higher invertebrate densities in sloughs were 

attributed primarily to abundant growths of periphyton and submerged vegetation, which provide 

oxygen and a source of high-quality food. 

QUANTIFYING P IMPACTS

A targeted design (see Chapter 4) was used to quantify changes in key ecological attributes in 

response to P enrichment. Discharges of canal waters through fixed water-control structures are 

the primary source of anthropogenic P for the Everglades and produce P gradients that extend 

several kilometers into the wetland in several locations. These gradients have existed for several 

decades and provided the clearest example of the long-term ecological impacts associated with P 

enrichment. Monitoring was conducted along gradients in different parts of the Everglades to 

assess ecological responses to P enrichment. Fixed sampling stations were located along the full 

extent of each gradient to document ecological conditions associated with increasing levels of P 

enrichment. Intensive monitoring was performed along gradients in two northern Everglades 

wetlands, WCA 2A and the LNWR. WCA 2A is a mineral-rich, slightly basic peatland and 

contains the most pronounced and well studied P gradient in the Everglades, whereas LNWR is a 

soft-water, slightly acidic peatland. These two wetlands represent the most extreme natural water 

chemistry conditions in the Everglades and support distinct periphyton assemblages and 

macrophyte populations while sharing dominant species such as sawgrass and water lily. Less 

intensive sampling along gradients in other parts of the Everglades (WCA 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. 
SEPTEMBER 2007 APPENDIX B: CASE STUDIES 

171 

Numerous field experiments have been conducted to quantify ecological responses to P 

enrichment and to better understand how interactions between P enrichment and other factors 

such as hydrology may affect these responses. The design of these experiments varied in 

complexity with respect to size and dosing regime depending on the specific objective of each 

study and has included enclosed fertilizer plots (e.g., Craft et.al., 1995), semi-permeable 

mesocosms receiving periodic P additions to achieve fixed loading rates in the form of periodic 

additions (e.g., McCormick and O’Dell 1996), flumes receiving semi-continuous enrichment at a 

fixed rate (Pan et.al., 2000), and flumes receiving flow-adjusted dosing to achieve constant 

inflow concentrations (Childers et.al., 2002). These experiments were useful in establishing the 

causal nature of responses to P enrichment documented along the P gradients described above. 

GRADIENT P CONCENTRATIONS

Strong gradients in P concentrations were documented downstream of canal discharges into most 

Everglades wetlands (Figure B1.3). Inflow TP concentrations in from 1996-1999 have averaged 

as high as 100 μg L-1 as compared with reference and pre-disturbance concentrations < 10 μg L-1 

. The degree and spatial extent of P enrichment varies among areas depending on the source and 

magnitude of inflows. The most extensive enrichment has occurred in the northern Everglades 

near EAA inflows, while southern areas (e.g., ENP) have been relatively less affected. The most 

extensive enrichment has occurred in 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-1 at the most enriched locations as compared with concentrations < 

500 mg kg-1 in reference areas. In general, this enrichment effect is limited to the surface 30 cm 

of soil depth (Reddy et.al., 1998). 
SEPTEMBER 2007 APPENDIX B: CASE STUDIES 

172 

Distance from canal (km)

0 2 4 6 8 10 12 14 16

Water-column TP (μg/L)

0

30

60

90

120

150

Appendix B1. Figure B1.3. Mean water-column TP concentrations (1996-1999) 

at long-term monitoring stations downstream of canal discharges in two northern 

Everglades wetlands, WCA 2A (circles connected by solid line) and LNWR 

(squares connected by dashed line). Error bars are + 1 SE.

ECOLOGICAL RESPONSES TO P ENRICHMENT

Periphyton 

Periphyton responses to P enrichment include changes in productivity, biomass, and species 

composition. Periphyton rapidly accumulates P from the water (McCormick et.al., 2001, Noe 

et.al., 2003), and, thus, a strong relationship between P concentrations in the water and 

periphyton is maintained along the P gradients (Grimshaw et.al., 1993, McCormick et.al., 1996). 

In fact, increases in periphyton P may provide one of the earliest signals of P enrichment (e.g., 

Gaiser et.al., 2004). Rapid increases in periphyton photosynthetic activity and growth rates occur 

in response to P enrichment (e.g., Swift and Nicholas 1987, McCormick et.al., 1996, McCormick 

et.al., 2001). All of these responses are consistent with the P-limited nature of Everglades 

periphyton. 

Paradoxically, these physiological responses are associated with sharply lower periphyton 

biomass in P-enriched areas due to the loss of the abundant community of calcareous 
SEPTEMBER 2007 APPENDIX B: CASE STUDIES 

173 

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 μg L-1) was replaced by a filamentous green algal assemblage at 

moderately elevated concentrations (TP = 10 to 28 μg L-1) and by eutrophic cyanobacteria and 

diatoms species at even higher concentrations (TP = 42 to 134 μg L-1). These results are 

representative of those documented by other investigators (e.g., Swift and Nicholas 1987, Pan 

et.al., 2000). Taxonomic changes in response to controlled P enrichment in field experiments 

have been shown to be similar to those documented along field enrichment gradients (Figure 

B1.4), thereby providing causal evidence that changes in the periphyton assemblage were largely 

a product of P enrichment (McCormick and O’Dell 1996, Pan et.al., 2000). 

Loading rate

(g P m-2 yr-1)

0.1 1 10

Percent Chlorophyta

0

20

40

60

80

100

Water Column P

(μg TP L-1)

10 100

Mesocosms Transects

0.1 1 10

Percent Cyanobacteria

0

20

40

60

80

100

10 100

0.1 1 10

Percent Bacillariophyta

0

10

20

30

40

50

10 100

Appendix B1. Figure B1.4. Changes in percent biomass (as biovolume) of major 

algal groups in field enclosures dosed weekly with different P loads (left panel) 

and along a P enrichment gradient downstream of canal discharges (right panel) 

in WCA 2A. From McCormick and O’Dell (1996). 

Community metabolism and dissolved oxygen concentrations 
SEPTEMBER 2007 APPENDIX B: CASE STUDIES 

174 

Phosphorus enrichment causes a shift in the balance between autotrophy and heterotrophy in the 

water column as a result of contrasting effects on periphyton productivity and microbial 

respiration. Rates of aquatic primary productivity (P) and respiration (R) are approximately 

balanced (P:R ratio = 1) across the diel cycle in minimally impacted sloughs throughout the 

Everglades (Belanger et al., 1989; McCormick et al., 1997). In contrast, respiration rates exceed 

productivity by a considerable margin (P:R ratio << 1) at enriched locations. This change is 

related primarily to a large reduction in areal periphyton productivity as a result of shading by 

dense stands of cattail (Typha domingensis) that form a nearly continuous cover in the most 

enriched areas (McCormick and Laing, 2003). Increased cattail production also stimulates 

microbial respiration (e.g., sediment oxygen demand) (e.g., Belanger et.al., 1989) due to an 

increase in the quantity and decomposability of macrophyte litter. 

The shift towards dominance of heterotrophic processes with P enrichment, in turn, affects 

dissolved oxygen (DO) concentrations in enriched areas. For example, DO concentrations at an 

enriched site in WCA 2A rarely exceeded 2 mg L-1 compared with concentrations as high as 12 

mg L-1 at reference locations (McCormick et al., 1997). Depressed water-column DO 

concentrations have subsequently been documented in enriched areas of WCA 2A and the 

LNWR (Figure B1.5) and confirmed in experimental P-enrichment studies (McCormick and 

Laing 2003). Declines in DO along field P gradients were steepest within a range of watercolumn TP concentrations roughly between 10 and 30 μg L-1. Lower DO in enriched areas are 

associated with other changes including an increase in anaerobic microbial processes and a shift 

in invertebrate species composition toward species tolerant of low DO, described later in this 

study. 

Macrophytes 

Nutrient enrichment initially stimulates the growth of existing vegetation as evidenced by 

increased plant P content, photosynthesis, and biomass production, as it does for periphyton. 

Persistent enrichment eventually produces a shift in vegetation composition toward species 

better adapted to rapid growth and expansion under conditions of high P availability. Two major 

shifts in Everglades plant communities have been documented along P gradients, including: 1) 

the replacement of sawgrass stands by cattail; and, 2) the replacement of slough-wet prairie 

habitat by cattail. 

Sawgrass populations in the Everglades have life-history characteristics indicative of plants 

adapted to low-nutrient environments (Davis 1989, Davis 1994, Miao and Sklar 1998). Sawgrass 

responses to P enrichment include an increase in tissue P, plant biomass, P storage, annual leaf 

production and turnover rates, and seed production (e.g., Davis 1989, Craft and Richardson 

1997, Miao and Sklar 1998). Cattail is characterized by a high growth rate, a short life cycle, 

high reproductive output, and other traits that confer a competitive advantage under enriched 

conditions (Davis 1989, Davis 1994, Goslee and Richardson 1997, Miao and Sklar 1998). 
SEPTEMBER 2007 APPENDIX B: CASE STUDIES 

175 

WCA-2A

Mean DO (mg/L)

0

2

4

6

8

0 10 20 30 40

r

2

 = 0.489

p < 0.001

Water-column TP (μg/L)

0 30 60 90 120

Frequency <1 mg/L (%)

0

25

50

75

100 r

2

 = 0.692

p < 0.001 

r

2

 = 0.436

p < 0.001 

LNWR

r

2

 = 0.314

p = 0.004 

r

2

 = 0.712

p < 0.001 

Minimum DO (mg/L)

0

2

4

6

8 r

2

 = 0.615

p < 0.001 

Appendix B1. Figure B1.5. Relationship between water-column DO metrics and 

TP concentration at several stations and time intervals along P gradients 

downstream of canal discharges into two northern Everglades wetlands (see 

Figure 1 for map). Total P concentrations are mean values for all samples (n = 3 

to 6) collected during the three-month period preceding DO measurements, which 

were typically collected over 3-4 diel cycles using dataloggers. Correlation 

coefficients are Spearman rank coefficients based on all data in the plot. Adapted 

from McCormick and Laing (2003). 
SEPTEMBER 2007 APPENDIX B: CASE STUDIES 

176 

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 Penriched 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 μg L-1. Eleocharis declined in response to increased soil P, and Nymphaea was 

stimulated by enrichment and was dominant in slightly enriched sloughs. Increased occurrence 

of cattail in sloughs was associated with a decline in Nymphaea, probably as a result of increased 

shading of the water surface. These findings are consistent with those of Vaithiyanathan et.al., 

(1995) who documented a decline in slough habitats along this same nutrient gradient and the 

loss of sensitive taxa such as Eleocharis at locations where soil TP exceeded 700 mg kg-1. As 

discussed by McCormick et.al., (2002), loss of these open-water areas is a sensitive landscape 

indicator of P enrichment (Figure B1.6). 

Distance from canal (km)

0 2 4 6 8 10 12 14 16

Percent open water

0

10

20

30

40

50

60

70

80

Water-Column TP (μg/L)

0

20

40

60

80

100

120

140

160

180

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 
SEPTEMBER 2007 APPENDIX B: CASE STUDIES 

177 

photography. Gray line shows the mean (+ 1 SE) water-column TP concentration 

(1996-1999) at 15 long-term monitoring stations along the gradient. 

Benthic Macroinvertebrates 

Macroinvertebrates are the most widely used biological indicator of water quality impacts, and 

several changes that occur in this community along P enrichment gradients in the Everglades are 

similar to those documented in response to eutrophication in other aquatic ecosystems. Several 

studies have documented an overall increase in macroinvertebrate abundance with increasing P 

enrichment (Rader and Richardson 1994, Trexler and Turner et.al., 1999, McCormick et.al., 

2004). However, differences in sampling methodology have apparently produced conflicting 

results with respect to changes in species richness and diversity. For example, Rader and 

Richardson (1994) documented an increase in both macroinvertebrate species richness and 

diversity with P enrichment in open-water (i.e., low emergent macrophyte cover) habitats and 

concluded that enrichment had not impacted this community. McCormick et.al., (2004), 

however, using a landscape approach that involved habitat-weighted sampling, found little 

change in either species richness or diversity in response to enrichment. This latter study 

accounted for the decline in the cover of habitats such as sloughs and wet prairies, which contain 

the most diverse and abundant macroinvertebrate communities (Rader 1994). McCormick et.al., 

(2004) also documented a pronounced shift in community composition with increasing P 

enrichment as taxa characteristic of the oligotrophic interior of the wetland are replaced by 

common pollution-tolerant taxa of oligochaetes and chironomids. These changes were indicative 

of habitat degradation as determined using biotic indices derived by the Florida DEP to assess 

stream condition based on macroinvertebrate composition (results available at 

http://www.epa.gov/owow/wetlands/bawwg/case/fl2.html). 

As for many other P-induced biological changes, the greatest change in the macroinvertebrate 

community occurred in response to relatively small increases in P concentration. Along field 

enrichment gradients, community shifts were associated with increases in water-column TP 

above approximately 10 ug L-1 (McCormick et.al., 2004). Similarly, Qian et.al., (2004) 

documented several shifts in community structure and function in response to long-term 

experimental dosing at average concentrations of approximately 10-15 ug L-1. 

ESTABLISHING A P CRITERION 

The FDEP was charged with reviewing and analyzing available P and ecological data collected 

throughout the Everglades to establish a numeric P criterion. A brief summary of this process is 

provided here, and more detailed information can be found in Payne et al., (2000, 2001a,b; 

available at http://www.dep.state.fl.us/water/wqssp/everglades/pctsd.htm; and, 2002, 2003, 

available at http://www.sfwmd.gov/sfer/previous_ecr.html). 

The narrative nutrient standard for Class III Florida waters such as the Everglades states that “in 

no case shall nutrient concentrations of a body of water be altered so as to cause an imbalance in 
SEPTEMBER 2007 APPENDIX B: CASE STUDIES 

178 

natural populations of aquatic flora or fauna.” The FDEP approach to detecting violations of this 

standard with respect to surface-water P concentrations in the Everglades was to test for 

statistically significant departures in ecological conditions from those at reference sites (i.e., 

interior sampling locations with background P concentrations). Biological and chemical data 

collected along anthropogenic P gradients throughout the Everglades were analyzed to determine 

P concentrations associated with such departures. Results showed that sampling sites with 

average (geometric mean) surface-water TP concentrations significantly greater than 10 ppb 

consistently exhibited significant departures in ecological condition from that of reference sites. 

A key finding supporting this concentration as the standard was the fact that multiple changes in 

each of the major indicator groups—periphyton, dissolved oxygen, macrophytes, and 

macroinvertebrates—all occurred at or near this same concentration (e.g., Payne et.al., 2001). 

Data from field and laboratory experiments conducted by various research groups provided 

valuable supporting information for understanding responses to P enrichment. While such 

experiments were not used directly to derive the P criterion, they established cause-effect 

relationships between P enrichment and ecological change that supported correlative 

relationships documented along field P gradients. For example, McCormick and O’Dell (1996) 

and Pan et.al., (2000) showed that major shifts in periphyton species composition documented 

along field P gradients matched those elicited by controlled P dosing in field enrichment 

experiments. McCormick and Laing (2003) confirmed that controlled P enrichment produced 

declines in water-column DO similar to those measured along the gradients. Macroinvertebrate 

community changes were documented experimentally, Qian et.al., (2004). 

While the criterion established a surface-water concentration of 10 ug L-1 TP as protective of 

native flora and fauna, the methodology used to measure compliance with the criterion needed to 

normalize background fluctuations in concentration. Additional analyses of P data collected over 

several years at reference sites was used to set both a longer-term average concentration and a 

shorter-term maximum concentration for each site. Based on these analyses, the FDEP 

concluded that annual maximum concentrations at a given sampling location should not exceed 

15 ug L-1 TP over the long-term, while five-year average concentrations should not exceed 10 ug 

L-1 TP. These limits would be applied to reference areas to ensure no further degradation and to 

areas already impacted by P enrichment to gauge the rate and extent of recovery in response to a 

suite of P control measures, including agricultural BMPs and the construction of treatment 

wetlands to remove P from surface runoff prior to being discharged into the Everglades. 

Additional information on Florida’s progress in assessing and implementing the adopted 

standard can be found on the South Florida Water Management District Web site: 

www.sfwmd.gov. 
SEPTEMBER 2007 APPENDIX B: CASE STUDIES 

179 

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