United States Environmental

Protection Agency

Office of Water

Washington, DC 20460

EPA-822-R-02-021

March 2002

Methods for evaluating wetland condition

#11 Using Algae To Assess

Environmental Conditions in Wetlands
United States Environmental

Protection Agency

Office of Water

Washington, DC 20460

EPA-822-R-02-021

March 2002

Methods for evaluating wetland condition

#11 Using Algae To Assess

Environmental Conditions in Wetlands

Major Contributors

Michigan State University

R. Jan Stevenson

The Nature Conservancy

Paul V. McCormick

Florida Department of Environmental Protection

Russ Frydenborg

Prepared jointly by:

The U.S. Environmental Protection Agency

Health and Ecological Criteria Division (Office of Science and Technology)

and

Wetlands Division (Office of Wetlands, Oceans, and Watersheds)
United States Environmental

Protection Agency

Office of Water

Washington, DC 20460

EPA-822-R-02-021

March 2002

Notice

The material in this document has been subjected to U.S. Environmental Protection Agency (EPA)

technical review and has been approved for publication as an EPA document. The information

contained herein is offered to the reader as a review of the “state of the science” concerning wetland

bioassessment and is not intended to be prescriptive guidance or firm advice. Mention of trade names,

products or services does not convey, and should not be interpreted as conveying official EPA approval,

endorsement, or recommendation.

Appropriate Citation

U.S. EPA. 2002. Methods for Evaluating Wetland Condition: Using Algae To Assess Environmental Conditions in Wetlands. Office of Water, U.S. Environmental Protection Agency, Washington, DC. EPA-822-R-02-021.

This entire document can be downloaded from the following U.S. EPA websites:

http://www.epa.gov/ost/standards

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

ii
iii

Contents

Foreword .............................................................................................................. v

List of “Methods for Evaluating Wetland

Condition” Modules.......................................................................................... vi

Summary .................................................................................................................1

Purpose..................................................................................................................1

Introduction.........................................................................................................1

Field Methods ................................................................................................... 13

Laboratory Methods ...................................................................................... 15

QA/QC ................................................................................................................ 17

Data Analysis..................................................................................................... 18

Limitations of Current Knowledge–

Research Needs ............................................................................................... 21

References ........................................................................................................ 23

Case Study 1: Developing Algal Indicators of the Ecological

Integrity of Maine Wetlands .......................................... 30

Case Study 2: Florida Everglades ........................................................... 36

List of Tables

Table 1: Major Habitats and Algal Assemblages in Wetlands....1

Table 2: Calculation of Total Phosphorus Optima

for 4 Diatom Species With the Total

Phosphorus Concentrations and Relative

Abundances (Nij) of 4 Taxa at 10 Sites.............................. 19
iv

Table 3: Calculation of Inferred Total Phosphorus

Concentration Based on the Relative

Abundances (Nij) of Five Taxa at Two Sites and

Known Total Phosphorus Optima for Four of

the Five Taxa............................................................................. 20

Table CS-1: Number of times algal attributes were correlated

(r.0.30) to 20 possible disturbance indicators for

assemblages from each habitat ......................................... 32

Table CS-2: Number of times attributes of human disturbance

correlated (r>0.30) to 20 possible algal attributes

for algal assemblages from each habitat...................... 35

List of Figures

Figure 1: Relations Between Biological Integrity and

Stressor Indicators Along a Stressor

Gradient ...................................................................................... 7

Figure CS-1: Change in number of species in the diatom genus

eunotia and the trophic status autecological

index with increasing levels of the Maine dep

disturbance index ................................................................... 33

Figure CS-2: Change in number of species in the diatom genus

eunotia and the trophic status autecological

index with increasing levels of chloride

concentration ........................................................................ 34
v

Foreword

In 1999, the U.S. Environmental Protection Agency (EPA) began work on this series of reports entitled

Methods for Evaluating Wetland Condition. The purpose of these reports is to help States and

Tribes develop methods to evaluate (1) the overall ecological condition of wetlands using biological

assessments and (2) nutrient enrichment of wetlands, which is one of the primary stressors damaging

wetlands in many parts of the country. This information is intended to serve as a starting point for States

and Tribes to eventually establish biological and nutrient water quality criteria specifically refined for

wetland waterbodies.

This purpose was to be accomplished by providing a series of “state of the science” modules concerning

wetland bioassessment as well as the nutrient enrichment of wetlands. The individual module format

was used instead of one large publication to facilitate the addition of other reports as wetland science

progresses and wetlands are further incorporated into water quality programs. Also, this modular

approach allows EPA to revise reports without having to reprint them all. A list of the inaugural set of

20 modules can be found at the end of this section.

This series of reports is the product of a collaborative effort between EPA’s Health and Ecological

Criteria Division of the Office of Science and Technology (OST) and the Wetlands Division of the

Office of Wetlands, Oceans and Watersheds (OWOW). The reports were initiated with the support

and oversight of Thomas J. Danielson (OWOW), Amanda K. Parker and Susan K. Jackson (OST),

and seen to completion by Douglas G. Hoskins (OWOW) and Ifeyinwa F. Davis (OST). EPA relied

heavily on the input, recommendations, and energy of three panels of experts, which unfortunately have

too many members to list individually:

n Biological Assessment of Wetlands Workgroup

n New England Biological Assessment of Wetlands Workgroup

n Wetlands Nutrient Criteria Workgroup

More information about biological and nutrient criteria is available at the following EPA website:

http://www.epa.gov/ost/standards

More information about wetland biological assessments is available at the following EPA website:

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

List of “Methods for Evaluating Wetland

Condition” Modules

1 ................. Introduction to Wetland Biological Assessment

2 ................. Introduction to Wetland Nutrient Assessment

3 ................. The State of Wetland Science

4 ................. Study Design for Monitoring Wetlands

5 ................. Administrative Framework for the Implementation of a

Wetland Bioassessment Program

6 ................. Developing Metrics and Indexes of Biological Integrity

7 ................. Wetlands Classification

8 ................. Volunteers and Wetland Biomonitoring

9 ................. Developing an Invertebrate Index of Biological

Integrity for Wetlands

10............... Using Vegetation to Assess Environmental Conditions

in Wetlands

11 ............... Using Algae to Assess Environmental Conditions in

Wetlands

12 ............... Using amphibians in Bioassessments of Wetlands

13 ............... Biological Assessment Methods for Birds

14 ............... Wetland Bioassessment Case Studies

15 ............... Bioassessment Methods for Fish

16 ............... Vegetation-Based Indicators of Wetland Nutrient

Enrichment

17 ............... Land-Use Characterization for Nutrient and Sediment

Risk Assessment

18 ............... Biogeochemical Indicators

19 ............... Nutrient Load Estimation

20 .............. Sustainable Nutrient Loading

Module # Module Title
1

Summary

A

lgae play important roles in wetland function

and can be valuable indicators of biological

integrity and ecological condition of wetlands. Sampling designs for algal assessment vary with objectives of programs and the algal characteristics that

are measured. Both structural and functional

attributes of algae can be measured, including diversity, biomass, chemical composition, plus productivity and other metabolic functions. Species

composition of algae, particularly diatoms, is commonly used as an indicator of biological integrity of

wetlands and the physical and chemical conditions

in wetlands. These latter conditions can be inferred

based on species environmental preferences and

species composition of algae in wetlands. Sampling methods for algae on plants and sediments

and floating in the water are well established, are

reviewed in detail in another chapter of this book,

and are used in streams and lakes as well. Laboratory methods are also well established for most

algal characteristics with relatively standard protocols used in several national stream programs.

Guidelines for data analysis are also reviewed in

this chapter, which includes basic metric development and also the development and application of

indices that infer physical and chemical conditions

in wetlands. Case studies are presented on the

development of algal indicators for Maine wetlands

and use of algae to assess ecological conditions in

the Everglades.

Purpose

T

he purpose of this chapter is to provide guide

lines for the use of algae to assess biological

integrity and ecological condition of wetlands.

Introduction

Background

A

lgae are an ecologically important and often

conspicuous feature of both freshwater and estuarine wetlands (see reviews by Vymazal 1994,

Goldsborough and Robinson 1996, Sullivan 1999).

Periphyton, assemblages of algae and other microorganisms attached to submerged surfaces, occur

in nearly all shallow-water habitats wherever sufficient light penetrates (Table 1). Periphyton grow

attached to submerged surfaces, such as sediments,

woody and herbaceous plants, and rock substrata.

In many wetlands aggregations of algae, called

metaphyton, grow entangled among macrophytes

either at the water surface or below. Phytoplankton also can be abundant in deeper and larger wetlands where water-column nutrient levels are high,

flushing rates are low, and grazing pressure by

planktivores is low. Algae provide a food source

for invertebrates and small fish in wetlands (Sullivan

and Moncreif 1990, Murkin et al. 1992, Campeau

et al. 1994, Browder et al. 1994, Mihuc and Toetz

Community type Growth form and habitat

Phytoplankton Unicellular and colonial forms suspended in the water column

Periphyton: Epidendron Mats or films growing on dead wood

 Epilithon Mats or films attached to hard surfaces

 Epipelon Mats, flocs, or films growing on soft sediments

 Epiphyton Mats or films attached to submerged macrophyte stems and leaves

 Metaphyton Mats or filaments floating on the water surface or suspended in the

water column, often entangled with macrophytes

Table 1: Major Habitats and Algal Assemblages in Wetlands
2

1994). Algal photosynthesis and respiration can

account for a significant fraction of wetland metabolism in some habitats and, therefore, can strongly

influence water-column oxygen dynamics

(McCormick et al. 1997). Algae are important in

energy and nutrient cycling, stabilizing substrata, and

serving as habitat for other organisms in wetlands

(Sullivan and Moncreif 1988, Sundbäck and Granéli

1988, Browder et al. 1994, MacIntyre et al. 1996,

Miller et al. 1996, Wetzel 1996). In some cases,

algal mats may serve as refugia for invertebrates

during periods of wetland desiccation (Harrington

1959).

Algae are among the most widely used indicators

of biological integrity and physico-chemical conditions in aquatic ecosystems (see reviews in

McCormick and Cairns 1994, Adamus 1996,

Danielson 1998, Stoermer and Smol 1999,

Stevenson and Smol in press, Stevenson in press).

Algal growth and taxonomic composition respond

predictably and sensitively to changes in pH, conductivity, nutrient enrichment, organic contamination, sediments, pesticides and many other contaminants (Round 1981, Stevenson et al. 1996). Algae

provide some of the first indications of changes in

wetlands because they respond directly to many

environmental changes, they have high dispersal

rates, and they have rapid growth rates. Algae provide highly precise assessments of changes in wetlands because they have high species numbers and

each species is differentially sensitive to a broad

range of environmental conditions. In fact, algae

may provide a more precise indication of wetland

nutrient status than sporadic measurements of water chemistry, particularly in wetlands that receive

pulsed nutrient inputs (e.g., storm-water runoff).

Effects of varying nutrients are measurable in a historical record manifested in algal assemblage characteristics (see Stevenson in press). Because of

their role in ecosystem energetics and biogeochemical cycling, algae provide an integrated picture of

wetland condition. The glass cell walls of diatoms

that accumulate in sediments provide a historic

record of ecological conditions in wetlands and are

an important indicator in paleolimnological studies.

The persistence of diatoms in sediments, even when

wetlands are dry, may provide a year-round approach for assessing the ecological integrity of wetlands when other organisms are not present. Thus,

diatoms could be used to provide a basis for developing regulatory decisions when many other organisms may not be present. In addition, the rapid

growth rates of algae enable experimental manipulation of environmental conditions to determine

cause-effect relationships between algal response

and specific environmental stressors (McCormick

and O’Dell 1996, Pan et al. 2000).

A common assumption is that algal assessments

require unusually great expertise and effort to complete. Even though detailed, species-level assessments do require substantial skill in algal taxonomy,

these skills can be readily developed with an introductory course in algal taxonomy, experience, a

good library of taxonomic literature, and periodic

consultations with other taxonomists. The taxonomy

of most common algal genera and diatom species is

well established and taxonomic keys are widely

available. Coarser taxonomic analyses (e.g., dominant genera) require considerably less training and

nontaxonomic metrics (e.g., chlorophyll a, nutrient

content) require only a general background in analytical laboratory practices. Field sampling and laboratory processing times for algal taxonomic analyses are comparable or less than for other commonly

used indicators. Thus the utility of using algae as an

assessment tool should not be overly constrained

by a lack of staff expertise and resource limitations.

Considerations When

Formulating a Sampling Design

Objectives of the project

Sampling design is highly dependent on the objectives of specific projects. Initial projects may be

designed to develop and test metrics for applica-
3

tion in a specific class of wetlands and in specific

geographic regions. After metrics have been developed, sampling design should change (e.g., random selection of sites) to apply these metrics to

assess site-specific conditions or status and trends

in wetlands within a region. During development of

metrics, the most efficient sampling design is to select wetlands with a wide range of adverse human

influences. Metrics developed with this strategy will

apply to the range of wetland conditions in a region. Developing metrics using sites that were randomly selected from the set of all sites may cause

oversampling of impaired or unimpaired wetlands

and may diminish development effort. If management concerns are based on specific types of adverse human influences, for example, nutrient enrichment or hydrologic alterations, then metric development should be focused on wetlands with a

range of nutrient or hydrological conditions. After

metrics are developed, sampling designs should be

planned to test hypotheses, for example:

n Are conditions at a specific site significantly different from those found at a population of reference sites; or

n Do wetland conditions in a region have a specific

mean or modal condition and variance?

The effects of project objectives on sampling design are discussed more completely in Module 4:

Study Design for Monitoring Wetlands.

Wetland class

Algal attributes can differ considerably among different wetland types within the same state or

ecoregion (e.g., Stewart et al. 1985). Therefore, it

often will be necessary to define reference conditions separately for each wetland type. Light, pH,

available nutrients, and the mineral content of the

water determine the type of algal community that

develops in a wetland. As a result of shading effects, algal biomass and productivity typically are

lower in forested and emergent-plant wetlands than

they are in sparsely vegetated systems dominated

by submerged aquatic vascular plants (SAV). Rainfall-driven wetlands, which tend to have low ionic

content and a neutral-acidic pH, contain a periphyton community dominated by chlorophytes and

acidophilous diatoms. Wetlands fed by groundwater, which typically has a higher pH and mineral

content, contain a greater abundance of

cyanobacteria and alkaliphilous diatoms.

Hydrology is less important than water chemistry

in determining periphyton structure and function.

Most algae require saturated or flooded conditions

to grow, and hydrologic parameters, such as water

depth, influence light penetration to phytoplankton

in the water column and to submerged surfaces

where periphyton grow. However, many algae

possess adaptations that allow them to either survive dry conditions or to recolonize quickly, which

enables rapid recovery of antecedent algal communities following marsh reflooding. Thus, many

attributes of the wetland algal community are less

sensitive to hydrologic modifications as compared

with macrophytes. However, species composition

of algae may respond indirectly to hydrologic conditions because hydrology often regulates water

chemistry.

Classification systems (discussed in Module 7:

Wetlands Classification) provide a starting point for

classifying wetland types for periphyton sampling

purposes. However, periphyton characteristics may

not follow hydrogeomorphic classification schemes

exactly, as this community is influenced most strongly

by water chemistry. Initial sampling in reference

wetlands provides the best means of classifying

wetland types according to their periphyton characteristics.

Habitats sampled

Algal characteristics also can vary considerably

among habitats within a wetland. Periphyton grows

on most submerged surfaces (e.g., hard and soft

sediments, living and dead vegetation), with the ex-
4

ception of those that exude allelopathic or otherwise inhibitory compounds. A distinct phytoplankton community also may develop. Both the amount

of light and the nature of the substratum affect periphyton abundance, growth, nutrient content, and

taxonomic composition. For example, senescent

or decomposing vegetation may release more nutrients than actively growing plant stems, thereby

increasing periphyton growth and nutrient content.

The sensitivity to environmental change of different

algal communities within a wetland also may vary;

for example, phytoplankton and floating periphyton mats (metaphyton) respond quickly to changes

in water-column nutrients whereas periphyton growing on sediments (epipelon) are influenced most by

nutrient fluxes from the underlying substrate. Given

the potential for such variability in algal metrics

among habitats, it is important that algal habitats be

sampled in a consistent manner across wetlands so

that changes in wetlands can be assessed precisely.

Recent evidence indicates that samples from targeted habitat samples more precisely indicate wetland change than composite samples from multiple

habitats. In a study of correlations between algal

attributes and several indicators of human disturbance in wetlands in Maine (see case study at end

of module), similar numbers of statistically significant correlations were observed with assemblages

from sediments, plants, and plankton. More correlations and higher correlations were observed in

targeted habitat samples than when epipelon,

epiphyton, and plankton were combined in a single,

multihabitat sample.

Introduced substrates (e.g., unglazed clay tiles,

glass slides, acrylic rods) are commonly used to

provide a standardized surface for periphyton

growth. The use of introduced substrates minimizes

problems associated with substrate comparability

among sampling locations. While the periphyton

community developing on such surfaces may differ

in certain respects from that growing on natural substrates (Tuchman and Stevenson 1980), this type

of sampling provides a reliable indicator of wetland

nutrient status and other changes in water chemistry (McCormick et al. 1996). In fact, the use of

inert surfaces for algal colonization may enhance

the sensitivity of the community to changes in water-column nutrient availability because nutrients leak

from plants and sediments (Moeller et al. 1988,

Burkholder 1996, Wetzel 1996). However, if the

assessment goal is to assess periphyton condition

within the wetland and not simply to use periphyton

as an indicator, then natural substrates should be

sampled. Disadvantages to the use of introduced

substrates include the requirement for two visits to

each sampling location, once for deployment and

again for retrieval. In addition, these substrata are

susceptible to loss as a result of vandalism, animal

damage, or fluctuating water levels. The strengths

and weaknesses of using artificial substrates have

been debated extensively in the literature (e.g.,

Stevenson and Lowe 1986, Aloi 1990).

Sampling frequency

Algal communities typically exhibit distinct seasonal patterns of standing crop and species composition, and these patterns can differ among wetland types. For example, deciduous forested wetlands may exhibit maximum algal growth during

spring or following leaf fall, when light penetration

is highest, whereas periphyton abundance in other

wetland types may peak during the warmer months.

Temperature tolerances and optima vary among

species and major algal groups, with diatoms being

relatively more abundant during cooler months and

cyanobacteria (blue-green algae) being more common during the summer. Furthermore, although less

sensitive to hydrology than macrophytes, most algal communities require some surface water to remain active. Disturbance events may be less common and less severe in most wetlands than in most

streams and rivers, but still they can affect periphyton growth and abundance temporarily. For example, heavy rainfall and wind can disrupt or even
5

disintegrate floating algal mats and introduce sediment, nutrients, and other pollutants that can affect

algal metabolism and growth.

Some familiarity with the temporal dynamics of

algal communities in wetland classes of interest

should be gained before initiating routine sampling.

If possible, sampling should be conducted during

more than one season to provide an integrated assessment of periphyton and nutrient conditions. If

this frequency is not practical, then sampling should

be conducted during the peak growing season or at

a time when stressor impacts are most likely to occur. Wetlands to be compared should be sampled

at approximately the same time of year to minimize

the confounding influence of seasonal variability on

algal metrics.

Spatial sampling intensity

The sampling intensity required to adequately assess algal conditions is related to the complexity

and spatial variability of the algal community, which

in turn is a function of habitat heterogeneity. The

sampling effort will be relatively low in instances

where a single algal community predominates and

is distributed in a relatively homogeneous manner

across the wetland. In most instances, however,

multiple communities will coexist and be distributed

patchily within and among vegetative habitats.

Sampling intensity also is affected by the presence of nutrient or other disturbance gradients within

the wetland. For example, point-source nutrient

inputs can produce localized zones of enrichment

that will support an algal community quite different

from that in unenriched portions of the same wetland, whereas nonpoint source inputs or those that

are exceedingly high relative to the size of the wetland may enrich the entire system.

The spatial heterogeneity of the wetlands to be

assessed should be evaluated in both qualitative and

quantitative terms to develop a sampling protocol

that optimizes the tradeoff between precision and

cost. First, major algal habitats and communities

should be identified. Secondly, preliminary sampling should be conducted to assess redundancy of

information among different communities and, in

conjunction with power analysis, to determine the

optimal sampling effort from a statistical standpoint.

Insufficient sampling relative to background variability will reduce the ability to discern trends and

impacts. Oversampling is not cost-effective and may

preclude measurement of other valuable indicators.

In heterogeneous environments, there are several

ways to reduce the sampling effort without introducing excessive variability into the results by (1)

conducting a composite sampling, i.e., combining

several field samples into a single sample for processing to account for local variation without increasing costs, (2) selecting a single “indicator” community for sampling rather than attempting to sample

all algal habitats, and (3) deploying introduced substrates (as discussed above). The efficacy of these

various alternatives will depend on assessment objectives and the types of wetlands being sampled.

Quantitative versus qualitative sampling

In addition to the frequency and intensity of sampling, one of the most important determinants of

effort—and therefore cost—is the type of metrics

to be measured. Quantitative measures of algal

standing crop, nutrient content, and productivity

provide valuable insight into wetland function and

the relative importance of periphyton processes.

Unfortunately, they also are extremely costly to

obtain because they are so spatially and temporally

variable. Costs of some area-specific measures can

be reduced if measures are restricted to specific

habitats. By contrast, qualitative sampling (e.g., collecting grab samples of the dominant periphyton

community from natural substrates) offers a more

cost-effective tool for assessing the nutrient status

of the wetland, albeit providing somewhat less information on overall periphyton condition.
6

Considerations When

Selecting Metrics

The types of algal metrics selected for assessment

and monitoring depend on several factors as follows.

Overall objectives of the sampling program

Sampling is based on the objectives of the program. For example, is the objective to assess the

periphyton condition of the wetland or simply to

get an indicator of wetland condition? Assessing

periphyton condition requires sampling a broad array of quantitative metrics on natural substrates

whereas an assessment of wetland condition, such

as trophic status, can be accomplished using a limited number of measures obtained from either natural or standardized substrata and need not be quantitative in most cases.

Wetland type

Available habitats and the relevance and utility of

different metrics vary among wetland types. Some

wetlands do not have herbaceous macrophytes and

others seldom have standing water. Algae on sediments occur in almost all habitats. Although we

have not thoroughly tested which habitat is most

sensitive to changes in wetland condition, algal

metrics from all three of the habitats we studied can

reflect changes in wetland condition (see Maine case

study). In the Everglades, the occurrence of a floating calcareous algal mat is characteristic of oligotrophic conditions, but this algal attribute is not

found in oligotrophic wetlands from many other

ecoregions.

Frequency of sampling

Sensitive metrics that respond quickly to changes

in nutrient availability and other physicochemical

conditions are useful when wetlands are to be monitored frequently. If sampling is conduct infrequently

(e.g., annually) or is limited to a single assessment,

emphasis should be placed on metrics that integrate

conditions over longer periods of time and, therefore, are not overly susceptible to short-term fluctuations. Surface sediment diatom assemblages, for

example, probably provide the greatest temporal

integration of wetland conditions, because diatoms

have accumulated in those sediments over the last

several years. However, surface sediment diatom

assemblages may not be as sensitive to nutrient conditions because of their location on sediments. Epiphytic algae may integrate environmental conditions

over the last couple of months as diatom assemblages developed on the plants. Phytoplankton

probably reflects the shortest historical context of

all the assemblages. Taxonomic attributes (especially presence/absence of taxa versus their relative

abundances and density) typically have longer histories than metabolic attributes (photosynthesis,

phosphatase activity).

Existing capabilities

Metrics selected for use undoubtedly will be influenced by existing facilities and staff expertise.

Thus metrics may be similar to those currently being used to monitor other types of aquatic systems.

In many instances, algal metrics and protocols used

to sample other benthic habitats can be adapted for

use in wetlands.

Typical Algal Attributes used

for Metrics

Algal attributes generally are classified as either

structural or functional. Structural attributes are

based on measurements of biomass, nutrient content, and taxonomic composition of samples. Functional attributes are based on measurements of

growth rates and rates of metabolism, such as photosynthesis, respiration, nutrient uptake, and enzyme

activity.

Algae, more than other assemblages, have been

used to indicate physicochemical conditions as well

as assess biological integrity in a habitat (Figure 1).
7

In other words, many attributes of algal assemblages

can be used as indicators of a natural, resilient flora,

but species composition of algal assemblages and

environmental preferences of algae have been particularly powerful indicators for diagnosing causes

of environmental impairment. Diagnostic indicators,

usually referred to as stressor indicators (Paulsen

et al. 1991, U.S. EPA 1998), usually are considered to be actual measures of altered physical,

chemical, or biological attributes caused by human

disturbance. Direct measurements of nutrient concentrations, pH, conductivity, acid-neutralizing capacity, depth and period of inundation, or densities

of non-native taxa commonly are used as stressor

indicators related to nutrient enrichment, hydrological alterations, and introduction of non-native taxa.

Thus stressor indicators based on algal assemblages

can be used to complement direct measurement of

environmental conditions. In general, all attributes

of algal assemblages could be used to assess biological integrity, but species composition and, to

some extent, chemical composition most often are

used to diagnose causes of problems.

Taxonomic composition

Taxonomic characteristics of algal assemblages

provide some of the most sensitive and robust indications of wetland nutrient status (e.g., McCormick

and O’Dell 1996). Species-level assessments, although requiring the greatest taxonomic expertise

to perform, yield the most precise indicators of environmental conditions and biological integrity.

However, considerable information can be obtained

from assessments performed at the genus level or

higher (e.g., Prygiel and Coste 1993, VanderBorgh

1999). Taxonomic analyses often focus on diatoms within the algal assemblage because the taxonomy and species’ autecologies of this group are

relatively well established and readily determined

from field collections without additional effort

(e.g., culturing).

0 5 10 15 20 25

0

2

4

6

8

10

-1

Biotic Integrity BI

SI

Ref

SC

BC

Figure 1: Relations between biological integrity and stressor

indicators along a stressor gradient (solid line)

These relations can be developed during indicator development and testing or determined from the literature.

These relations often are most precise between specific assemblage attributes and specific stressors rather than

between multimetric indices and specific stressors and are important for applying a risk assessment approach

to environmental monitoring (adapted from Stevenson in press). Correspondence between observed measures

of biological integrity (BI) and specific stressors (SI) can help diagnose causes of or threats to ecological

impairment. BI - measured biological integrity; SI - measured stressor indicator; RC - Response Criteria; and

SC - Stressor Criteria (dashed lines). Reference (Ref) indicated by arrow.

Stressor Gradient (e.g., TP [μg L-1])

Biological Integrity
8

Taxonomic characteristics of assemblages can be

used to assess biological integrity of wetlands and

diagnose causes of or threats to impairment. Biological integrity of algal assemblages can be evaluated at many taxonomic levels, for example, looking just for changes in species composition or

changes in algal growth form. Whereas the latter

may reflect changes in food availability and habitat

structure, changes in species composition alone are

important indicators that biodiversity has been altered and that the environmental factors regulating

microbial processes in the wetland have changed.

Similarity in taxonomic composition between reference and test sites is the most direct approach for

assessing biological integrity of algal assemblages

in wetlands. The ability to distinguish impaired from

reference assemblages requires precise characterization of taxonomic composition of assemblages in

reference wetlands. Precision in estimates of reference assemblages can be increased by classifying

wetlands and sampling multiple reference wetlands

for each wetland class (see Module 7: Wetlands

Classification). Similarity can be measured with

many indices (e.g., % similarity, Euclidean distance;

Pielou 1984, Jongman et al. 1995) and with many

types of taxonomic data. Similarity based on taxonomic data can be calculated based on densities,

relative biovolumes, relative abundances, or presence/absence of species, genera, or functional

groups. Similarity calculated with both species and

genus composition of assemblages provides sufficient data to compare assemblage similarity. Functional groups often are defined by growth form and

major taxonomic divisions, such as unicellular, colonial, and filamentous forms of cyanobacteria; diatoms; green algae; euglenoids; and cryptomonads.

These groups are thought to represent different food

categories for herbivores (Porter 1977, Lamberti

1996). We recommend two measures of similarity

in algal assemblages: similarity in relative biovolumes

of functional groups and similarity in relative abundances of diatom species as two relatively standard indicators of biological integrity.

Another approach to assessing biological integrity of algal assemblages in wetlands is to compare

the relative abundance of organisms and the number of taxa in genera that are common in reference

conditions and rare in disturbed wetlands. For example, we often find high numbers of taxa in the

diatom genera Eunotia and Pinnularia in relatively

undisturbed wetlands. The % of cells and % of

taxa of Eunotia and Pinnularia can be used as

indicators of biological integrity of wetlands, if reference wetlands have high numbers of these diatom genera. These metrics probably are less precise than direct species-level comparisons with assemblages from reference conditions, but they may

be valuable metrics if reference conditions are not

defined precisely.

A successful approach used in streams is first to

define the sensitivity of all taxa that are common in

reference conditions and rare or absent from disturbed conditions and then to determine the % of

sensitive cells or taxa in assemblages at test sites.

Percents of sensitive cells or taxa are measurements

of similarity between reference and impaired sites.

By placing an emphasis on taxa autecologies (e.g.,

sensitivity to pollution), the emphasis on wetland

classification can be reduced; pairing of wetland

classes and identifying taxa in reference sites is not

as great an issue. Sensitive taxa in any wetland

class, across all classes of wetlands, should be sensitive to the same disturbances by humans.

Taxonomic composition, when combined with

specific environmental tolerances of taxa, can be

used to calculate stressor indicators to infer environmental conditions in wetlands (Pan and

Stevenson 1996, Stevenson et al. 1999, see case

studies). Such indices usually are referred to as

autecological because they are based on the autecological characteristics of taxa. Different levels of

accuracy in environmental tolerances can be used

to distinguish two groups of autecological indices.

For example, in some cases, environmental tolerance categories are known for taxa (Lowe 1974,
9

VanLandingham 1982, Van Dam et al. 1994). In

other cases, specific pH, salinity, or total phosphorus (TP) optima for taxa are known (Pan and

Stevenson 1996, Stevenson et al. 1999). Assessments of environmental conditions based on species optima may provide more accurate inferences

of conditions. However, use of indices based on

species optima characterized in another geographic

region may be biased. Indices based on categorical characterizations of species autecologies may

be more transferable among regions. Probably

they are more reliable in the early stages

ofimplementingalgae assessment programs until species environmental optima in the study region have

been evaluated.

Conceptually, autecological indices also might be

used to infer biological integrity in cases where reference conditions in wetlands are not well defined.

Many environmental contaminants, such as nutrients, are not commonly found in abundance in natural

aquatic ecosystems. Thus, high proportions of taxa

that require high nutrients would indicate that the

biological integrity of the habitat had been compromised and that nutrients were a highly probable

cause of impairment. Wetland conductivity (ionic

concentration) often changes with hydrologic alterations, and algae are highly sensitive to changes in

conductivity. Thus, changes in algal species composition could be used to indicate hydrologic alteration of wetlands.

Diversity

Richness of taxa numbers and evenness of taxa

abundances are two characteristics of many diversity indices (sensu Shannon 1948, Simpson 1949,

Hurlbert 1971) that are used to describe biological

assemblages. Although diversity often is used in

environmental assessments, basic problems with its

use exist. First, species diversity and evenness are

highly correlated with standard 300-600 cell counts;

in these counts many species usually have not been

identified, so richness is more a function of evenness than evenness a function of richness (Patrick

et al.1954, Archibald 1972, Stevenson and Lowe

1986). Using standard counting procedures,

nonmonotonic (showing both positive and negative

changes as the independent variable increases) responses of algal diversity can occur along environmental gradients, which introduces ambiguity into

the interpretation of diversity indices. This ambiguity seems to be related to the maximum evenness of

tolerant and sensitive taxa at midpoints along environmental gradients, fewer species being adapted

to environmental extremes at both ends of environmental gradients, and subsidy-stress perturbation

gradients (Odum et al. 1979). Despite these difficulties, species richness and evenness may respond

monotonically (exhibiting only positive or negative

changes, but not necessarily linear ones, as the independent variable increases). Likewise, they may

respond sensitively and precisely to gradients of

human disturbance in some settings and should be

tested for use as metrics.

Biomass

Biomass of algae often increases with resource

availability and decreases with many toxic and sediment stressors caused by humans. The relationship

between algal biomass and nutrient inputs is one of

the most widely used indicators of eutrophication in

aquatic ecosystems (e.g., Vollenweider 1976,

Schindler et al. 1978, Dodds et al. 1998). Most

relationships have been established for lake phytoplankton; however, periphyton in streams also is

closely related to nutrient status, as increased nutrient availability will yield more biomass (Borchardt

1996). Sediments, toxic substances, and removal

of benthic habitat can limit algal growth and accrual

(Genter 1996, Hoagland et al. 1996). Because biomass and the potential for nuisance algal growths

vary with season and weather (Whitton 1970, Wong

et al. 1978, Lembi et al. 1988), the timing of sampling is important. Biomass is an important attribute

in environmental assessments because it is related

to productivity and nuisance problems.
10

Biomass can be estimated using several measurements, including cell density, cell biovolume, ashfree-dry-mass (AFDM), and chlorophyll (chl) a.

Each of these measurements has strengths and

weaknesses as described by Stevenson (1996, in

press), and the use of multiple estimates can increase

the amount of information obtained. For example,

estimates of periphyton chlorophyll a and AFDM

can be used to calculate the autotrophic index (Weber 1973), which indicates the dominance of heterotrophs (e.g., bacteria, fungi) relative to algae in

the periphyton community. Ratios between nutrients and AFDM in samples provide indicators of

nutrient availability and trophic status (McCormick

and O’Dell 1996, Pan et al. 2000).

In practice, quantitative measures of areal periphyton biomass (e.g., McCormick et al. 1998) can

be time-consuming, destructive and therefore costly

to obtain. Measuring biomass can require harvesting of all periphyton and associated substrates from

known areas of marsh. Sampling with this approach

focuses on particular vegetative habitats or can be

conducted on a habitat-weighted basis to characterize the entire wetland. Multiple plots must be

sampled from each habitat to account for spatial

variation in biomass. Considerable processing time

is required to separate periphyton from associated

macrophyte material and other substrates when sampling at this scale. A second quantitative approach

is to sample at smaller scales, by algal habitats:

plants, sediments, floating mats, and water column.

Then, based on quantitative assessment of area of

these habitats within the wetland, algal biomass can

be estimated with a habitat-weighted calculation.

Qualitative (i.e., presence-absence) or semiquantitative (e.g., percent cover) measures of

periphyton abundance may provide a cost-effective

alternative indicator of nutrient status and wetland

condition in some instances and can be

accompanied by visual assessments of algal

taxonomic composition. These techniques have

been employed successfully in streams (Sheath and

Burkholder 1985, Stevenson and Bahls 1999).

Biomass accumulation on introduced substrates (see

growth rate below) also can be used to assess

biomass-nutrient relationships among wetlands,

although these measurements are not always a

reliable predictor of periphyton abundance on

natural substrata within the same wetland.

Although the relationship between algal biomass

and nutrient availability is logical, it has limitations in

practice. Biomass can be highly variable in space

and time (e.g., episodic algal blooms, sloughing of

periphyton from surfaces) and may respond differently to enrichment in different wetlands. For example, algal biomass in open-water habitats in the

Florida Everglades declines with increased phosphorus availability, which differs from many other

aquatic systems (McCormick and O’Dell 1996,

Pan et al. 2000). Biomass also is affected by differences in the light regime and grazing pressure

among wetlands as well as nutrient levels. Biomass-nutrient relationships also may be confounded

by the presence of other stressors such as toxic

chemicals. Thus, the accurate interpretation of biomass changes requires an understanding of ecological processes and study of cumulative impacts within

a wetland.

Chemical composition

Chemical composition of algal assemblages can

be used to assess trophic status or contamination

of food webs by toxic compounds. Water-column

nutrient concentrations, particularly those of

bioavailable (i.e., dissolved inorganic) forms, can

be highly variable over short periods as a result of

weather events (e.g., heavy rainfall) and pulsed nutrient inputs from anthropogenic sources. In oligotrophic wetlands, water-column nutrient concentrations may be below, at, or near the minimum detection limits, thus increasing the relative uncertainty

associated with analytical results. Periphyton nutrient concentrations integrate variation in nutrient

bioavailability over time scales of weeks, thus providing an indication of the recent nutrient status of
11

the wetland that is not unduly influenced by episodic events or other short-term fluctuations.

Measurements of periphyton nutrients complement

soil nutrient analyses, which indicate the nutrient history of the wetland over years or decades. Many

toxic contaminants, such as heavy metals and organic contaminants, are rapidly adsorbed or taken

up by periphyton (e.g., Vymazal 1994). Their presence in the water column far underestimates their

presence in the habitat and their potential availability to the food web.

Total phosphorus (TP) and nitrogen (TN) concentrations of water and periphyton have been used

to characterize trophic status (Carlson 1975, Dodds

et al. 1998, Biggs 1995). TN:TP ratios are widely

used to infer which nutrient regulates algal growth

(Hecky and Henzel 1980, Hecky and Kilham 1988,

Biggs 1995). In many of these assessments, most

of the total P and N is particulate and much of the

particulate matter is algae. Thus, measurements of

TP or TN per unit volume or area of habitat largely

reflect the amount of algae in the habitat. Of course,

the most widespread use of trophic assessments

with TP and TN is phytoplankton in lakes (Carlson

1975), but use has also been proposed for streams,

rivers, and wetlands (Vymazal and Richardson

1995, Dodds et al. 1998, McCormick and

Stevenson 1998). TP and TN per unit biomass in

benthic algae also have correlated positively with

benthic algal biomass in streams. However, negative-density-dependent effects may reduce biomass-specific concentrations of benthic algal TP and

TN and confound estimates of P and N availability

to cells (Humphrey and Stevenson 1992). Volumespecific, area-specific, and biomass-specific estimates of TP and TN do increase monotonically with

most gradients of human disturbance and may be

good metrics for trophic status in streams, rivers,

and wetlands as well as lakes.

The chemical composition of algae is a valuable

piece of information for monitoring heavy metal contamination in rivers, lakes, and estuaries (Briand et al.

1978, Whitton et al. 1989, Say et al. 1990). Many

algae accumulate heavy metals when exposed to them

in natural environments (Whitton 1984). The toxicity of heavy metals to algae is one reason for monitoring them. Other reasons include their

bioaccumulation in waste streams, and the movement

of heavy metals into the food web (Whitton and

Shehata 1982, Vymazal 1984, Radwin et al. 1990).

Growth

In the absence of other environmental limitations

(e.g., light availability, grazing), algal net production

is positively related to nutrient bioavailability. Periphyton production is quantified most easily in the

field by measuring biomass accumulation on introduced substrates over a standardized period of time.

Though growth rates on these substrates may differ

from those on natural wetland substrates, they do

provide a reliable indicator of nutrient availability.

A similar level of light should be maintained for substrates placed in all wetlands that will be compared;

otherwise, the relationship between biomass accumulation and nutrient availability will be hard to interpret. Maintaining this uniformity may require

clipping macrophyte material in heavily vegetated

wetlands. Incubation times should be sufficiently

long (e.g., 10-20 d) to allow for accumulation of

measurable biomass, but not so long as to result in

sloughing. Determining a standardized incubation

period can be difficult when working in wetlands of

widely varying trophic status. Typically, periphyton

accumulate much faster at enriched sites and therefore may slough before sufficient biomass has been

achieved at low-nutrient sites. We recommend placing plenty of artificial substrata at the sites and sampling frequently throughout the colonization period

to ensure the best characterizations of algal growth

rates and peak biomass (see Stevenson 1996).

Differences in grazing pressure or levels of

nonnutrient stressors among wetlands may confound

the relationship between biomass accumulation and

nutrient availability.
12

Metabolism

Metabolic activities of algal assemblages are important wetland functions and therefore may be included in assessments. Photosynthesis (gross primary productivity), respiration, net primary productivity (photosynthesis-respiration), nutrient uptake,

and phosphatase activity (PA) are commonly measured in ecological studies and are sensitive to environmental change (Bott et al. 1978, Healey and

Hendzel 1979, Wetzel and Likens 1991, Marzolf

et al. 1994, Hill et al. 1997, Young and Huryn 1998,

Whitton et al. 1998). Phosphatase activity is highly

sensitive to even slight changes in trophic status of

P-limited oligotrophic habitats. Phosphatases are

extracellular enzymes that cleave phosphate molecules from organic compounds, thereby making

the P available to algal and other cells. Algal and

bacterial cells excrete these enzymes in response to

P deprivation; thus, PA levels in the water and periphyton of wetlands are inversely proportional to

P availability (Newman et al. in press). Nitrogen

deficiency also can be assessed by measuring the

level of N fixation activity in plankton and periphyton samples. Heterocystous algae and some bacteria are capable of converting dinitrogen gas into

ammonia through a series of enzymatic reactions.

Through this same pathway, acetylene is converted

into ethylene. Thus, the level of N-fixation activity

can be assessed by measuring the rate at which

acetylene, injected into a sealed vessel containing

the water or periphyton sample, is converted to ethylene. Because cellular N-fixation is an energyintensive process, generally it is only induced in response to intracellular N limitation. A gas chromatograph is required to measure the quantity of ethylene produced during this assay.

These techniques to measure metabolism rarely

are incorporated into routine monitoring and survey work because they require more field time than

typical water, phytoplankton, and periphyton sampling. In addition, they are related closely to biomass, which can vary substantially on a seasonal basis and in relation to weather-related disturbances.

Thus, although metabolic attributes of algal assemblages are important attributes of wetlands, algal

metabolism usually is not incorporated into environmental assessments until the later stages of more

in-depth investigations.

Bioassay

For purposes of discussion such as this one, bioassays usually are defined as in-lab cultures of organisms in waters from the study site. A valuable,

field-based use of this technique is the Selenastrum

bottle assay in which known quantities of this highly

culturable green alga are added to water from the

study site and growth is monitored over a predefined

period (Cain and Trainor 1973, United States Environmental Protection Agency 1978, Trainor and

Shubert 1973, Greene et al. 1976, Ghosh and Gaur

1990, McCormick et al. 1996). Samples are inoculated with known amounts of the test alga and

incubated under controlled conditions to determine

the biomass yield after 14 days. This yield, known

as the algal growth potential (AGP), indicates the

bioavailability of nutrients in the water sample. In a

second assay, the Limiting Nutrient Algal Assay

(LNAA), replicate water samples are spiked with

different nutrients, either alone or in combination.

The nutrient yielding the greatest amount of biomass is identified as being most limiting to the growth

of this test population. The test alga used in these

assays is by no means ubiquitous among wetlands,

and certainly the response of this species to nutrient

enrichment differs from that of many other algae.

Furthermore, populations of algae within a wetland

community may be limited by different nutrients.

However, results from these simple tests often provide reliable predictions of wetland nutrient status

and limitation (McCormick et al. 1996). Another

advantage of these tests is that they can be standardized easily for use among wetlands that may

contain different algal communities. Disadvantages

include the effort required to establish and maintain

testing and culture facilities.

Alternatively, bioassays can assess planktonic or

benthic assemblages from reference or test sites
13

(rather than a standard test organism) and can be

conducted under highly controlled laboratory conditions using waters from the studied habitats or else

conducted in the field. Different dilution levels of

effluents entering the regions under study or specific stressors (like phosphate) can be added to lab

cultures or field mesocosms. Twist et al. (1997)

introduced the novel approach of embedding test

organisms in alginate (agarous substance) and culturing them in situ. Nutrient-diffusing substrata, microcosms, and mesocosms can be deployed at

many scales in the field (e.g., Cotê 1983, Fairchild

et al. 1985, Gensemer 1991, Hoagland et al. 1993,

Lamberti and Steinman 1993, McCormick and

O’Dell 1996, Pan et al. 2000). Most investigators

tend to think that larger scale (bigger space and

longer time) manipulations are more likely to reflect

changes that occur in natural systems.

The response of organisms to bioassays can provide another valuable line of evidence for identifying causes of environmental stress. The results of

bioassays where specific chemicals or effluents were

added can be used to confirm cause-effect relations between parameters for which only observational correlations can be obtained in field surveys

(e.g., McCormick and O’Dell 1996, Pan et al.

2000). If changes in multiple algal assemblage attributes, particularly shifts in species composition,

are similar among in situ, laboratory bioassays and

along environmental gradients in the field, then strong

evidence has been found to link causes of change in

biological integrity in the field to the factors that were

manipulated in the bioassays.

Field Methods

Sampling Present-Day

Assemblages

Many algal habitats can be sampled within wetlands using standard methods for other habitats

(Goldsborough and Robinson 1996, Goldsborough

in press). Composite sampling is recommended to

reduce variability in assessments resulting from spatial

variability within wetlands. Composite sampling

means gathering multiple collections (usually about

five) from areas around the wetland and putting them

into the same container. Composite samples all may

be from the same habitat (plankton, plants, sediments) and thus are referred to as targeted habitat

samples; or they may include subsamples from many

habitats and thus are referred to as multihabitat

samples.

In deep, open water wetlands, phytoplankton can

be sampled with Van Dorn, Kemmerer, or similar

discrete-depth samplers (APHA 1998). However,

in most cases, whole-water phytoplankton samples

can be collected by immersing a container. To avoid

sampling particulate material suspended while an

investigator enters the wetland, a small plastic container can be attached to the end of a pole (ca. 2 m

long). Qualitative samples can be collected with

plankton nets. However, we recommend collecting whole water samples with known volumes whenever possible, so that small algae are not missed

and samples can be assayed quantitatively. Algae

in whole water samples can be concentrated by filtering or settling (e.g., Wetzel and Likens 1991,

APHA 1998).

Metaphyton are macroalgal and microalgal masses

suspended in the water column and entangled among

macrophytes or along shorelines (Hillebrand 1983,

Goldsborough and Robinson 1996). Quantitative

sampling of metaphyton requires collecting algae

from a vertical column through the assemblage.

Coring tubes can be used to isolate and collect a

column of metaphyton. Scissors are useful to cut

horizontal filaments that block the insertion of the

tube through the metaphyton assemblage. Depth

of the core should not extend to the substratum.

Diameter of the core depends upon spatial variability of the metaphyton, on necessary sample size,

and on ability to isolate the core of algae from surrounding metaphyton (Stevenson personal observation). Metaphyton in the form of unconsolidated
14

green clouds requires use of wider (ca. 10 cm)

cores, because filaments are difficult to isolate in

narrow cores and related edge-effect error is reduced with wider cores. Narrower cores (ca. 3

cm) can be used to sample consolidated microalgal

mats. Metaphyton biomass should be expressed

on an areal basis. Qualitative samples of metaphyton

can be gathered with grabs, forceps, strainers,

spoons, pipettes, or cooking basters.

Benthic algae are sampled by scraping hard or

firm substrata, such as rocks, plants, and tree

branches, usually after they have been removed from

the water (Stevenson and Hashim 1989, Aloi 1990,

Porter et al. 1993). Cores of algae should be collected on soft or unconsolidated substrata, such as

sediments and sand (Stevenson and Stoermer 1981,

Stevenson and Hashim 1989). Epiphytes can be

collected by cutting plants close to the sediment with

scissors and placing them in a plastic bag with water. Some substrata, such as bedrock and logs, cannot be removed from the water. In those cases,

vertical tubes can be used to isolate an area of substratum. After algae are scraped from the substratum in the tube with a brush, algae and water in the

tube can be removed with suction pumps.

Artificial substrata, such as microscope slides or

dowels made from glass, acrylic plastic, or wood,

can be used to assess benthic algal assemblages in

wetlands (McCormick et al. 1996). Dowels are

particularly easy to use in wetlands because they

only require sticking into sediments. If placed in

the same light and depths, assemblages should be

highly sensitive to water chemistry. Multiple samplings of substrata during colonization can be used

to determine dispersal, growth rates, and peak biomasses of assemblages (Stevenson et al. 1991,

Stevenson 1996).

Samples should be preserved for later processing

as soon as possible. If chlorophyll a will be analyzed, however, samples cannot be preserved until

subsamples have been extracted in the lab. During

large survey projects when immediate sample processing is not practical, samples can be frozen to

preserve them. Freezing disrupts only large cells

with large-cell vacuoles, like Spirogyra or

Vaucheria. Small cells like diatoms and

cyanobacteria are not affected. Samples for AFDM

and cell count assays can be preserved with many

different preservatives. In most situations, M3 (a

combination of formaldehyde, glacial acetic acid,

and iodine; APHA 1998) is effective and reduces

formaldehyde concentrations in samples and in the

lab. If flagella of phytoplankton are important for

identification, Lugol’s preservative (APHA 1998)

is recommended. Some caution should be exercised when fixing microorganisms. Double concentrations of preservative are recommended for

phytoplankton when treating dense periphyton assemblages. Many artifacts can surface in the course

of sampling in wetlands, which are home to a great

diversity of organisms, not all of which will be equally

well preserved (Klein Breteler 1985, Sherr and

Sherr 1993). Artifacts can be detected by examining some samples immediately after sampling and

before preservation. Artifacts can be standardized

by using the same preservative.

Sampling Historic Assemblages

In wetlands with relatively undisturbed sediments,

a chronological record of environmental conditions

may have been stored by algae that settled to the

bottom (Slate 1998, Slate and Stevenson 2000).

Newer assemblages lie close to the surface, and

older assemblages lie deep within the sediments.

Algal assemblages in sediments may have accumulated for months, years, or centuries, depending on

the depth and disturbance of sediments. A large

variety of coring apparatuses have been used to

retrieve sediment cores (Smol and Glew 1992).

Telling the time of historic changes depends on the

type of sectioning techniques and equipment used.

Close-interval sectioning equipment and techniques

(e.g., Glew 1988, 1991) can provide a high degree

of temporal resolution.
15

A sediment core usually is removed from near the

center of the wetland. In general, the central, flat

portion of a basin collects cells from the broadest

region and retains deposits best, and so a more

holistic and complete record of past environmental

change is archived there.

Sediments and diatom assemblages in them can

be dated. 210Pb often is used to date sediments

(Oldfield and Appleby 1984), because it has a halflife of 22.26 years and occurs naturally. Dating with

210Pb is reasonably accurate for about a century.

Alternatively, paleolimnologists have sometimes

used a “top/bottom” approach by removing surface sediment cores as they would in a detailed

paleoenvironmental assessment. Instead of sectioning and analyzing the entire core, however, they simply analyze the top 1 cm of sediment (= presentday conditions) and a sediment level known to have

been deposited before anthropogenic impact (i.e.,

the bottom sediment section). This approach has

been used effectively to infer the amount of acidification occurring in lakes (Cumming et al. 1992, Dixit

et al. 1999) and eutrophication (e.g., Dixit and Smol

1994, Hall and Smol 1992). The employment of

diatom community composition, diatom autecological information, and paleoenvironmental approaches

can imply if not indicate the background conditions

of a system and provide mitigation targets for environmental remediation (Smol 1992).

Laboratory

Methods

L

aboratory procedures for most routine

algal measures (e.g., chlorophyll, AFDM, cell

identification and counts) have been standardized

(e.g., APHA 1998, Stevenson and Bahls 1999).

These methods should be followed whenever feasible so that comparability among studies is as great

as possible. In this section, we set out the steps to

determine algal attributes, and we provide references to standard methods.

Upon return of samples to the lab, fill out all sample

chain of custody (COC) forms and check sample

labels to ensure their adhesion. If samples need to

be subsampled for multiple assays, homogenize

them with a biohomogenizer (tissue homogenizer)

in a beaker before subsampling. Subsampling can

introduce error. Therefore, put homogenized

samples on a magnetic stirrer and remove two or

more aliquots of sample for each subsample to reduce measurement error.

Structural Attributes

Taxonomic composition

Taxonomic composition of algal assemblages

requires microscopic examination of samples. The

methods used for microscopic identification and

counting of algae depend on the objectives of data

analysis and type of sample. A two-step algal counting process is being used in many environmental

programs. The first step is designed to characterize species composition of nondiatom algae in

samples. This step is eliminated from projects in

which only diatoms are analyzed. In this first step,

count all algae and identify only nondiatom algae in

a wet mount at 400X (e.g., Palmer cell). If many

small algae occur in samples, count algae at 1000X

with an inverted microscope (Lund et al. 1958) or

with a regular microscope by drying samples onto

a cover glass, inverting the sample onto a microscope slide in 0.020 mL of water, and sealing the

sample by ringing the cover glass with fingernail

polish or varnish (Stevenson and Bahls 1999). The

second step is to count diatoms after oxidation of

organic material out of diatoms and mounting them

in a highly refractive mounting medium (e.g.,

Stevenson and Bahls 1999). This two-step technique provides the most complete taxonomic assessment of an algal assemblage. Counts of 300

algal cells, colonies, or filaments and about 500 diatom valves are the standard approach used in some

national programs (Porter et al. 1993, Pan et al.

1996). Counting these numbers of cells usually provides relatively precise estimates of the relative
16

abundances of the dominant taxa in sample (with

observation of 10 or more cells, colonies, or filaments of each taxon). Alternatively, counting rules

can be defined so that cells of all algae are identified and counted until at least 10 cells (or natural

counting units = cells, colonies, or filaments) of the

10 dominant taxa are counted (Stevenson unpublished data). This type of rule, rather than a fixed

total number of cells, ensures precision in estimates

of a specified number of taxa. Some assessment

programs primarily use diatoms (Bahls 1993, Kentucky Division of Water 1993, Kelly et al. 1998,

Kwandrans et al. 1998). The numbers of species

in diatom assemblages usually are sufficient to show

a response, provide an indicator of algal biological

integrity, and provide indicators of environmental

stressors.

Taxonomic composition can be recorded as presence/absence, percent or proportional relative abundances, percent or proportional relative biovolumes,

or absolute densities and biovolumes of taxa (cells

or μm3 cm-2 or mL-1). Although there is no published comparison of these forms of data, they represent levels of taxonomic scale and probably reflect a gradient “from least variable to most variable” on a temporal scale. Presence/absence

records of species should be based on observations of thousands of cells and should reflect longterm changes in habitat conditions, especially if immigration and colonization of habitats regulates species membership in a sample. Relative abundance

and biovolumes of taxa probably reflect recent habitat conditions more than long-term conditions because of recent species responses to their environment. Densities and biovolumes of taxa change daily,

so absolute densities and biovolumes may be too

sensitive to detect more long-term environmental

changes. The relative abundance of cells more commonly is used as a metric than are relative

biovolumes, but the latter are particularly valuable

when cell sizes vary greatly among taxa within

samples.

Biomass

Biomass of algal assemblages can be estimated

with measurements of chl a, dry mass, ash-free dry

mass, algal cell density, biovolume, or chemical mass

of samples. All these measurements have pros and

cons (see Stevenson 1996 for review), because

none directly measures all constituents of algal biomass or only algal biomass. Chl a is first extracted

from cells in acetone or methanol before measurement by spectrophotometry, fluorometry, or high

performance liquid chromatography (HPLC)

(Lorenzen 1967, Mantoura and Llewellyn 1983,

Wetzel and Likens 1991, APHA 1998, Van

Heukelem et al. 1992, Millie et al. 1993). Spectrophotometric and fluorometric chl a assays should

be corrected for phaeophytin. Dry mass and ashfree dry mass are measured by drying and combusting samples (APHA 1998). Cell density is

measured after counting cells microscopically (Lund

et al. 1958, APHA 1998, Stevenson and Bahls

1999). Algal biovolume can be measured by distinguishing sizes of cells during microscopic counts,

multiplying biovolume by cell size for all size categories, and finally summing biovolumes for all size

categories in the sample (Stevenson et al. 1985,

Wetzel and Likens 1991, APHA 1998, Hillebrand

et al. 1999).

Biomass also can be estimated rapidly with field

assays, such as Secchi depth in the water column

and percent cover and thickness of algal assemblages on substrata (Wetzel and Likens 1991).

Assessments of algal biomass with Secchi depth

can be confounded by suspended inorganic material and other factors (Preisendorfer 1986). The

advantage of assessing benthic algal biomass with

percent cover and thickness of algal assemblages is

that biomass over a large area can be characterized

readily (Holmes and Whitton 1981, Sheath and

Burkholder 1985, Stevenson and Bahls 1999).

Chemical Composition

Periphyton chemical concentrations can be determined by collecting several (e.g., five) represen-
17

tative grab samples of the dominant community from

different locations to account for spatial variation

within a wetland. If an environmental gradient is

known or suspected to exist within the wetland as a

result of, for example, point-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., metaphyton, epiphyton, epipelon),

as habitat can affect periphyton chemical concentration. For example, in reference areas of the Everglades, epipelon phosphorus concentrations typically are twice those in the metaphyton (McCormick

et al. 1998). Grab samples can be combined into a

single composite sample to reduce analytical costs

and then are frozen until processing. Samples are

processed in the same manner as for macrophyte

material to determine N and P content. N is determined by CHN and P is determined after digestion

and oxidation to PO4. Heavy metals are determined by atomic absorption after digestion or by

other instruments (e.g., inductively couple mass

spectrometry). Many other chemical contaminants

also can be assayed in algal samples, such as toxic

organics. Chemical contaminants usually are expressed on a dry-mass basis, which reflects the

presence of contaminants in the organic (e.g., algal

cells, detritus) and inorganic (e.g., precipitated Ca

or sediment) fractions of samples. See Module 10:

Using Vegetation to Assess Environmental Conditions in Wetlands, to compare with vegetation-based

indicators.

Functional Attributes

Measuring gross and net productivity and respiration can be done in the field with light and dark

chambers and changes in oxygen concentration if

the water column is mixed, as is common in shallow

wetlands (Bott et al. 1978, Wetzel and Likens

1991). Alternatively, productivity can be estimated

with changes in oxygen concentration in the water

during a diel sampling period or at two locations in

a stream, if diffusion of oxygen from the water column is accounted for properly (Kelly et al. 1974,

Marzolf et al. 1994, Young and Huryn 1998).

Nutrient uptake can be measured as depletion of

nutrients in closed chambers. Phosphatase is measured with water samples in the laboratory (Healey

and Hendzel 1979).

QA/QC

P

roper quality assurance/quality control

(QA/QC) is essential, both to ensure that results are accurate and defensible and to quantify

the degree of uncertainty associated with each measurement. In this regard, requirements for algal sampling protocols are no different than for any other

assessment. Standard operating procedures

(SOPs) that detail each sampling and processing

procedure must be distributed to all personnel participating in the assessment process. One or more

individuals within the assessment group must be designated as the QA/QC officer and be responsible

for conducting routine audits of field and laboratory

personnel to ensure compliance with SOPs. Deviations from SOPs resulting from unusual field events

or conditions should be documented in writing, using a standard form. Chain of custody sheets should

follow samples through the processing train; such

documentation is important particularly if samples

are to be transferred among laboratories. Written

documentation, as just described, often is needed

to recreate the sampling and analysis process, to

account for missing data, and perhaps to explain

anomalous results. This reconstruction process can

be critical at the regulatory and litigation stage, which

may occur several years after the samples were

collected and key personnel have left the organization.

Collection of duplicate samples at a subset of all

wetlands studied (e.g., 5-10% of samples) provides

information on the amount of variation associated

with field sampling procedures. Similarly, processing duplicate subsamples allows for laboratory varia-
18

tion to be quantified, as is done routinely for water

chemistry samples. The amount of acceptable variability depends on the degree of resolution required.

If variability is excessive, a search should be made

for the causes (e.g., habitat heterogeneity, sample

preparation, or taxonomic inconsistencies).

Taxonomic QA/QC requires the greatest effort

and should include both photographic documentation and archived specimens of all identified taxa.

The first step in taxonomic QA/QC is having a good

taxonomic library. A table of taxonomic references

can be found in Stevenson and Bahls (1999). Photographs provide a convenient means for comparing identifications among laboratory staff. However, microscopic examination of archived material

often is necessary to confirm identifications. Diatom samples can be archived on microscope slides

when mounted in most resin media, like NaprhaxÒ.

Long-term archiving of preserved algal samples and

cleaned diatom samples is possible by sealing containers with tape and wax to prevent evaporation.

Channels of communication within and among laboratories (e.g., regularly scheduled lab meetings, Web

sites that are updated regularly) must be formalized

to ensure consistency in taxonomic identifications

and nomenclature. These channels of communication should be developed early in the project and

be maintained. Often, taxonomic workshops are

held at regional and national meetings. Periodically,

quantitative QA/QC determinations (e.g., laboratory staff counting the same fields of the same mount)

should be performed to determine the degree of

variability among counters.

Data Analysis

Objectives

The objectives of programs and specific steps in

data analysis should be defined clearly. First, attributes of algal assemblages should be calculated,

which may include the following: areal density of

cells, pigments, or mass; relative abundances of taxa;

diversity attributes; % of organisms or taxa within

taxonomic, autecological, or functional group categories; species environmental optima and tolerances; and inferred environmental conditions based

on species relative abundances. Early exploration

of the data will involve multivariate analyses to assess correlation among environmental variables and

major changes in algal attributes (see Lowe and Pan

1996 for discussion). Early metric development

may include testing algal attributes for merit as

metrics (see Module 6: Developing Metrics and

Indexes of Biological Integrity) and delineating wetland classes to increase precision of metrics and

ability to distinguish impairment (see Module 7:

Wetlands Classification).

Data analysis during early stages of metric development can be simple. The main goal is to find

wetland attributes that reliably change along with

human disturbance (e.g., box plot analysis). During later stages of metric development, studies should

be designed to describe stressor-response relationships more accurately so that criteria can be established for protecting valued ecological attributes (linear and nonlinear regression, change point analysis). Indicators and stressor-response relationships

may vary among classes of wetlands; such variability should be evaluated.

Finally, projects should be established to monitor

status and trends in wetlands, and data analysis

should be used to determine whether sites or populations of sites meet specific criteria and how wetland condition changes over time. Each of these

stages can be approached with a variety of data

analyses to provide multiple lines of evidence on

which management decisions can be based and

benefits of corrective actions monitored. Although

a complete review of these analyses is beyond the

scope of this module, the following paragraphs detail the calculation of environmental optima and of

autecological indicators of environmental conditions.
19

An overview of data analysis used in environmental

programs is described briefly. Case studies following this section provide examples of how these

steps of data analysis are integrated into environmental programs.

Environmental Optima and

Autecological Indices

Environmental optima for taxa can be calculated

with a very straightforward approach, if algal assemblages are collected from a range of environmental conditions and if taxa respond to those conditions (Zelinka and Marvin 1961, ter Braak and

van Dam 1989). Computer programs have been

developed especially to develop and test autecological indices of environmental conditions (Line et

al. 1994, Juggins and ter Braak 1992). Often these

calculations are preceded by a multivariate assessment of variability in species composition among

assemblages and correlations between patterns in

species composition and environmental factors (see

review in Lowe and Pan 1996). Identifying environmental factors that are highly correlated with

changes in species composition helps to narrow the

selection of environmental factors that should be

used to characterize species preferences. Environmental optima (Θik) for each species are calculated

as a weighted average of the relative abundance of

species i in different habitats j (nij) and the k

th environmental factor (ejk) in habitat j:

Θik = Σi=1,Snijejk/Σi=1,Snij

Environmental conditions in a habitat (ECk)can

then be inferred based on species autecologies (Θik)

and on relative abundances of species for which

autecologies are known (nij):

ECk = Σi=1,SnijΘik/Σi=1,Snij

Site (j) TP(μg/L) Frsynegr Masmithi Nacryten Niamphib

1 24.8 0.052 1.30 0.348 8.64 0.003 0.07 0.004 0.11

2 79.3 0.028 2.21 0.032 2.56 0.029 2.32 0.526 41.72

3 12.4 0.089 1.11 0.340 4.22 0.000 0.00 0.000 0.00

4 14.5 0.085 1.24 0.277 4.02 0.000 0.00 0.000 0.00

5 110.3 0.012 1.37 0.123 13.57 0.023 2.58 0.329 36.23

6 31.7 0.111 3.52 0.075 2.39 0.033 1.04 0.027 0.86

7 57.5 0.066 3.82 0.043 2.49 0.037 2.13 0.326 18.74

8 46.9 0.024 1.12 0.093 4.34 0.115 5.39 0.287 13.44

9 9.9 0.308 3.05 0.223 2.21 0.000 0.00 0.000 0.00

10 10.0 0.090 0.90 0.531 5.31 0.000 0.00 0.000 0.00

col. Sums

(E)

0.867 19.63 2.087 49.74 0.240 13.53 1.499 111.09

Optima 22.65 23.84 56.32 74.14

Frsynegr = Fragilaria synegrotesca; Masmithi = Mastogloia smithii; Nacryten = Navicula cryptotenella; and

Niamphib = Nitzschia amphibia.

Table 2: Calculation of total phosphorus optima for 4 diatom

species with the total phosphorus concentrations and relative

abundances (nij) of 4 taxa at 10 sites

nij TP* nij nij TP* nij nij TP* nij nij TP* nij
20

The following example shows how these indices

are calculated. In Table 2, the total phosphorus

concentrations in which 4 taxa (indicated by 8 letter species codes) were found were recorded for

10 sites. The relative abundances (nij) were the

proportions of diatom assemblages that these taxa

represented at the 10 sites. The products of the

phosphorus concentrations and relative abundances

(TP*nij) were calculated; for example, that product

is 1.30 for Fragilaria synegrotesca at site 1 and

1.04 for Navicula cryptotenella at site 6. The

sum of the relative abundances of each taxon at all

sites (Enij) and the sum of the P concentration/relative abundance products (ETP*

 nij) were calculated

and represent column sums (col. sums), for example,

0.867 and 19.63, respectively, for F. synegrotesca.

The environmental optima then were calculated by

dividing the sum of the P concentration/relative abundance products by the sum of relative abundances

of each taxon, for example, 19.63/0.867=22.65.

Based on these calculations, F. synegrotesca and

Mastogloia smithii have lower total phosphorus

optima than Navicula cryptotenella and Nitzschia

amphibia.

In Table 3, inferred environmental conditions (i.e.,

total phosphorus concentration) were calculated

with relative abundances (nij) and environmental

optima (Θik) for diatom taxa in samples from two

sites. Products of species-relative abundances and

environmental optima (Θ*nij) were calculated (e.g.,

6.80 for F. synegrotesca at site 1) and summed for

each sample, as were the relative abundances of

species for which environmental optima are not

known (nij*). If environmental optima are known

for all taxa, nij = nij*. Inferred environmental conditions, (i.e., the TP concentrations in this example)

at sites 1 and 2 were calculated as the sum of products of species-relative abundances and environmental optima (EQ*

nij) divided by the sum of species-relative abundances (Enij*) for which environmental optima were known (e.g., 29.24=26.90/0.92

at site 1).

Developing and Testing Metrics

Developing and testing metrics for algae involve

the same procedure as for other kinds of organisms

(see Module 6: Developing Metrics and Indexes of

Taxa TP optima

(μg/L) Site 1 Site 2

Frsynegr 22.65 0.30 6.80 0.30 0.05 1.13 0.05

Masmithi 23.84 0.50 11.92 0.50 0.10 2.38 0.10

Nacryten 56.32 0.04 2.25 0.04 0.40 22.53 0.40

Niamphib 74.14 0.08 5.93 0.08 0.20 14.83 0.20

Syulna na 0.08 na 0.25 na

col. sums (E) 26.90 0.92 40.87 0.75

Inferred TP conc. 29.24 54.50

Frsynegr = Fragilaria synegrotesca; Masmithi = Mastogloia smithii; Nacryten = Navicula cryptotenella; and Niamphib =

Nitzschia amphibia; and Sulna = Synedra ulna. na = not available. nij* indicates the relative abundances of taxa for which

autecological optima are known.

Table 3: Calculation of inferred total phosphorus concentration

based on the relative abundances (nij) of five taxa at two sites and

known total phosphorus optima for four of the five taxa

nij Q* nij nij*nij Q* nij nij*
21

Biological Integrity). Box plots and regression

analysis can be used to relate algal attributes to human disturbance. Like other metrics, algal metrics,

should be evaluated for their capability to distinguish impaired condition from reference condition

(power) within a region and their applicability to

different regions.

Indexes of biological integrity (IBIs) provide a

means of summarizing complex multimetric results.

These indices combine the responses of several

metrics (e.g., taxonomic information, biomass, and

growth measures) to derive a single number describing wetland condition. These indices provide

a useful and objective means of summarizing complex ecological data and have been adopted for use

by a number of states (USEPA 1996). As for any

summary, these indices are most informative when

presented in conjunction with the response of individual metrics. The development and application

of IBIs to assessing aquatic ecosystem condition

are discussed by Karr (1981) and Barbour et al.

(1999) and described in Module 6. Algal IBIs currently are used and more are under development

for assessing streams and rivers (Kentucky Division of Water 1993, Hill et al. 2000). No IBIs

currently exist, however, for assessing algal condition in wetlands. Development of such is discussed

by Stevenson (in press).

Developing Criteria

Assessing biological impacts requires some sort

of threshold or criterion as to what is considered to

be an unacceptable condition. Defining a wetland’s

condition in terms of biological integrity provides a

response variable for assessment. Changes in habitat structure, productivity, and the functional groups

within wetlands are gross changes in biological integrity that affect other organisms in wetlands. More

subtle changes in algal species composition are a

concern because they indicate a change in biological integrity of wetlands. Moreover, subtle

changes in species composition also may indicate

alteration of the fundamental environmental constraints that regulate microbial processes in wetlands.

Algal characteristics indicative of undisturbed and

altered conditions have been identified for lakes and

rivers, and, in many cases, they apply as indicators

of conditions in wetlands as well. However, the

point where integrity is impaired can be difficult to

determine when metrics change gradually in response to enrichment. Abrupt changes in algal

metrics along a gradient of human disturbance within

or among wetlands provide relatively clear evidence

of impairment. These abrupt changes often are most

precisely indicated by changes in algal species composition. Significant changes along these gradients

can be detected using statistical procedures such

as change-point analysis (see case studies). Nonlinear responses along disturbance gradients, therefore, can provide a basis for establishing criteria if

they are supported by an ecological basis for labeling a change as an impact. Indicators that change

more linearly along disturbance gradients actually

may be most valuable for assessing status and trends

and detecting changes in ecosystems at low levels

of human disturbance as well as at high levels.

Limitations of

Current

Knowledge—

Research Needs

T

he basic tools exist to use algae in wetland

assessments. However, greater precision and

statistical power for detecting impairment can be

achieved. Several factors could improve that effort. First, a more precise characterization of expected condition in wetlands would allow a more

sensitive detection of impairment. That precise characterization depends on better classification of wet-
22

lands and selection of metrics. Still poorly understood is the scale of biological resolution involved,

such as genus versus species level metrics or relative abundances versus presence/absence data.

Other limitations of current knowledge are related

to predicting stressors, effects of changes in algal

biological integrity on other organisms, and results

of different wetland protection and remediation

approaches. Although first principles of ecology

will enable development of good predictions, little

research has been done in wetlands relating algal

assemblages and production to elements of wetland ecology. More basic research in the understanding of the role of algae in wetlands will enable

more effective use of algal assessments and more

successful management of wetlands.
23

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30

Case Study 1:

Developing Algal Indicators of the

Ecological Integrity of Maine Wetlands

Jeanne DiFranco (Project Lead)

Maine Department of Environmental Protection

312 Canco Road

Portland, ME 04103

Jan Stevenson

Michigan State University

Department of Zoology

203 Natural Science Building

East Lansing, MI 48824-1115

Project Objectives

This project was designed to:

• Develop sampling methods for algae and macroinvertebrates

• Develop biological criteria for Maine wetlands

• Diagnose stressors degrading wetlands

Project History

Maine DEP initiated the Casco Bay Watershed biological assessment project in 1998 and has completed

2 years of sampling. The Casco Bay study is a cooperative effort between Jeanne Difranco of Maine DEP

and Jan Stevenson of Michigan State University. As of the January 2000 BAWWG conference, Jeanne

Difranco and the Maine DEP staff have analyzed 1998 macroinvertebrate data and are processing the data

from the summer 1999 season. Jan Stevenson also has completed 2 years of sampling for algae and is

now developing algal protocols and metrics for Maine wetlands. In this presentation of the Maine case

study, some of the results from the algal part of the project will be presented from the first sampling season.

Study Design

In 1998, the first sampling season, 20 wetlands were selected in the Casco Bay Watershed. All the

wetlands are semi-permanent or permanent depressional wetlands and were selected based on six criteria:

hydrologic regime, distribution of sites, landscape position, disturbance gradient, management significance,

and accessibility. Six of the 30 wetlands were selected as minimally disturbed reference sites and the

others range in condition from good to poor quality.
31

Sampling Methods: Algae

Quantitative and qualitative algae samples were gathered from the same 20 wetland sites as used for

macroinvertebrate sampling. Algae from plants, sediments, and the water column were sampled from

multiple sites within each wetland and composited into one sample for each habitat. In addition, a multihabitat

sample was collected from each site in which algae on plants, on sediments, and suspended in the water

were placed in the same container.

Four algal sample types were collected to determine which produced the best indicators. Samples were

collected from the water column, plants, and sediments, and across the wetland as a multihabitat sample.

Samples were examined microscopically to determine species numbers and relative abundances of different species in samples. Chlorophyll a in the water column was assessed as an indicator of algal biomass.

Among the tools used for sampling were scissors to clip plants off of the bottom substrate, a turkey

baster to collect sediment samples, and a bottle on a short pole or a hand-held cup to collect water

samples. For the multihabitat sample, doses from each sample were combined into one container.

Analytical Methods: Algae

Three disturbance indicators were used to evaluate responses of algal attributes to human alteration of

wetlands: a land use indicator developed by Maine DEP, trophic status indicators (total Nitrogen, total

Phosphorus, and chlorophyll a), and hydrologic and sewage chemicals (Ca, Na, Cl). A suite of algal

attributes was compared to the disturbance indicators to determine which types of indicators responded.

The algae indicators included biological integrity measures such as genus and species richness, Shannon

diversity, and a number of taxa in different genera. European autoecological information (Van Dam et al.

1994) was used to determine environmental preferences for the taxa. Weighted-average autecological

indices were calculated with species-relative abundances and their autecological characterizations to infer

environmental stress as a consequence of low moisture, organic N, low oxygen, pH, salt, and nutrients. A

preliminary analysis of the data is presented in which only a few of the many algal attributes are compared

with human disturbance indicators of the 20 wetlands.

Lessons Learned

Diatoms from plants, sediments, and the water column provided similar numbers of metrics of biological

integrity and indices of stressors. Attributes of diatom assemblages in multihabitat samples were not as

well correlated with indicators of environmental gradients of human disturbance as were attributes in assemblages in samples from single habitats (Table CS-1). Only 55 of the possible 400 algal attributes of

multihabitat samples were correlated with r>0.30, where as between 86 and 90 of the possible attributes

of algae on plants, on sediments, and in the water column were correlated to the indicators of human

disturbance.
32

Habitat Genera S N S/N H Even Rich Poss

Water 1 1 2 2 2 5 1 n=20

Sediments 1 4 0 4 2 2 2

Plants 5 4 4 4 3 2 4

Multihabitat 1 1 5 2 2 4 1

Sum 8 10 11 12 9 13 8 n=80

Habitat Achn Cymb Euno Navi Nitz Pinn

Water 4 6 4 5 8 7

Sediment 3 3 8 7 6 5

Plants 1 6 5 2 6 5

Multihabitat 4 3 2 2 5 2

Sum 12 18 19 16 25 19

Habitat Moist Org. N pH Salt Org Tol Trophic Sum

Water 1 8 6 6 7 5 8 89

Sediment 1 7 3 6 7 7 8 86

Plants 0 8 7 4 6 7 7 90

Multihabitat 10 6 0 1 2 1 1 55

Sum 12 29 16 17 22 20 24 n=400

Table CS-1. Number of times algal attributes were correlated

(r>0.30) to 20 possible disturbance indicators for assemblages

from each habitat

The table is broken into three parts, each with a heading and the sum of times over all habitats

that each attribute was correlated to the 20 possible disturbance indicators (maximum = 80).

The three panels are organized into: diversity metrics (Genera = number of genera, S = number

of species, N = number of organisms in count, S/N = number of organisms, H = Shannon

diversity, Even = Hurlburt’s Evenness, Rich = theoretical species richness based on S and

Even); species-based metrics (number of taxa of the diatom genera Achnanthes (Achn), Cymbella

(Cymb), Eunotia (Euno), Navicula (Nav), Nitzschia (Nitz), and Pinnularia (Pinn); and autecological indices (moisture index, organic N index, low O2

 tolerance index, pH, salinity, organic pollution index, and trophic status index).

O2 Tol
33

0 10 20 30

Maine Disturbance Index

0

10

20

30

Number of Eunotia Taxa

0 10 20 30

Maine Disturbance Index

2

3

4

5

6

Trophic Status Index

Figure CS-1. Change in number of species in the diatom genus

Eunotia and the trophic status autecological index with

increasing levels of the Maine DEP Disturbance Index.

Metrics based on the number of taxa in common genera and on autecological characteristics of species

were more highly correlated with indicators of human disturbance than diversity characteristics of diatom

assemblages. Indices based on autecological characteristics of diatom species were slightly more reliable

than genus- based metrics (Figure CS-1), even though those characteristics were based on autecological

characterizations for European populations of the same species. We expect that these autecological indices will improve when environmental preferences are based on distributions of regional populations.

To better understand how to characterize gradients of human disturbance, the number of algal attributes

that correlated with r>0.30 to each indicator of human disturbance was determined. In general, conservative

ions such as Cl, Na, and Ca correlated more highly to changes in diatom assemblages (Figure CS-2) than

did nutrient concentrations and field-based indicators of disturbance (e.g., Maine DEP Disturbance Index).

Of the field-based indicators of human disturbance, algae related most to the percent of impervious surface

and nonpoint source pollution, with 39 out of 80 algal attributes in the 4 habitats being related for the latter

disturbance indicators (Table CS-2). These numbers actually were similar to the 31−45 range of correlations

between disturbance and algal attributes for the chemical, general-disturbance indicators. Note that algae

responded more to direct indicators of individual stressors rather than to a cumulative summary index of

human disturbance based on field assessments. Total phosphorus correlated more to algal attributes than

did total nitrogen or chlorophyll a in the water column.
34

1 10 100

Cl (mg/L)

0

10

20

30

Number of Eunotia Taxa

1 10 100

Cl (mg/L)

2

3

4

5

6

Trophic Status Index

Figure CS-2: Change in Number of Species in the Diatom Genus

Eunotia and the Trophic Status Autecological Index With

Increasing Levels of Chloride Concentration.
35

Habitat Hydro Veg Imperv NPS Cum

Water 5 2 14 10 10

Sediment 5 1 12 9 8

Plants 1 2 3 14 9

Multihabitat 4 6 10 6 4

Sum 15 11 39 39 31

Habitat TN TP Chl a

Water 4 9 2

Sediment 2 11 2

Plants 5 5 3

Multihabitat 5 1 3

Sum 16 26 10

Habitat Ca Na Cl

Water 10 12 10

Sediment 13 13 10

Plants 5 15 13

Multihabitat 3 5 5

Sum 31 45 38

Table CS-2. Number of times attributes of human disturbance

correlated (r>0.30) to 20 possible algal attributes for algal

assemblages from each habitat

The table is broken into three parts, each with a heading and the sum of times over all habitats that

each attribute of human disturbance correlated to the 20 possible algal indicators (maximum = 80).

The three panels are organized into land use indicators based on field assessments by Maine DEP

(hydrologic disturbance, vegetative disturbance, percent impervious surface, nonpoint source pollution, and cumulative index of all four disturbance types); trophic status indicators, total phosphorus, total nitrogen, and chlorophyll a; and general human disturbance indicators as concentrations

of calcium, sodium, and chloride.
36

Case Study 2:

Florida Everglades

Contact Information

Russel Frydenborg

Florida Department Environmental Protection

2600 Blair Stone Road, MS 6511

Tallahassee, FL 32399-2400

(850) 921-9821

Purpose of Project

This project was initiated to monitor biological assemblages across a nutrient gradient in the Florida

Everglades in support of regulatory efforts to define a numeric water quality criterion for phosphorus. The

goal is protection of natural populations of aquatic flora and fauna in the Everglades Protection Area.

 Project History

The historic Florida Everglades consisted of approximately 4 million acres of shallow sawgrass marsh,

with wet prairies and aquatic sloughs interspersed with tree islands. Today, only 50 percent of the original

Everglades ecosystem remains, primarily as a result of drainage and conversion of large portions of the

northern and eastern Everglades to agricultural or urban land use. The remaining portions of the historic

Everglades are located in the Water Conservation Areas (WCAs) and Everglades National Park (ENP).

The Everglades ecosystem evolved under extremely low phosphorus concentrations and is considered

an oligotrophic ecosystem. A large body of evidence indicates that phosphorus is the primary limiting

nutrient throughout the remaining Everglades. The introduction of excess phosphorus into the Everglades

has resulted in ecological changes over large areas of the marsh. The Everglades Forever Act (EFA;

Section 373.4592, Florida Statutes), passed by the Florida Legislature in 1994, stated that waters flowing

into the part of the remnant Everglades known as the Everglades Protection Area (defined as Water

Conservation Areas 1, 2A, 2B, 3A, 3B and ENP) contain excessive levels of phosphorus and that a

reduction in levels of phosphorus will benefit the ecology of the Everglades Protection Area. The EFA

requires the Florida Department of Environmental Protection (FDEP) and the South Florida Water Management District (SFWMD) to complete research necessary to establish a numeric phosphorus criterion

for the Everglades Protection Area.

The SFWMD Everglades System Research Division (ESRD) initiated a succession of studies, beginning

in 1993 and continuing to the present, as part of the research and monitoring being conducted in the
37

Everglades for the purposes of phosphorus criterion development. Biological monitoring for the ESRD

studies was initiated in early 1994 in WCA 2A. Data from this and other studies are being used by FDEP

in the development of a numeric phosphorus criterion for the Everglades Protection Area.

 Study Design

SFWMD ESRD initially selected 13 sites along two transects located downstream of canals discharging

into WCA 2A and extending down the phosphorus gradient into least affected areas of the marsh. Sampling sites ranged from the canal inflows (discharge structures on the north-eastern margin of WCA 2A) to

a site nearly 15 km downstream from the canal inflows. Three of the 13 main sites specifically were chosen

to represent the least affected area of WCA 2A with respect to anthropogenic disturbance (sites U1-U3).

A series of 15 additional ”intermediate” sites were added to the study later to obtain better spatial coverage of the lower portion of the transects. The sites have been monitored for water, sediment, and biological quality.
38

 Assemblages Monitored

n Algae (phytoplankton and periphyton)

n Macroinvertebrates

n Macrophytes

 Sampling Methods: Algae

n Water Bottles—phytoplankton samples initially were collected monthly and later were collected quarterly using water bottles. Samples were preserved in the field and sent to the FDEP Central Biology

Laboratory for taxonomic identification.

n Diatometers—racks each containing six glass diatometer slides were deployed quarterly at each site. It

was determined that an 8-week period of deployment was necessary to allow for sufficient periphyton

growth. Diatometers were collected and preserved and sent to the FDEP Central Biology Laboratory

for processing and taxonomic identification.

n Natural Substrate (benthic)—samples of benthic periphyton were collected from surficial sediment

cores at the main transect sites on several occasions. Samples were retained by SFWMD ESRD for

processing and taxonomic identification.
39

Sampling Methods: Macroinvertebrates

n Dipnet—SFWMD staff conducted quarterly macroinvertebrate sampling using a standard D-frame

dipnet with a 30-mesh bag from September 1994, through November 1995. The sampling method

consisted of the collection of twenty 0.5-meter (in length) discrete dipnet sweeps from representative

habitats in the area of each site on a given sampling date. The 20 dipnet sweeps for a given site were

combined and sent to the FDEP Central Biology Laboratory for processing and taxonomic identification.

n Quan Net—Beginning in May 1996, SFWMD staff conducted quarterly macroinvertebrate sampling

using the Quan Net method. The sampling method consisted of the deployment of a 1 m2 frame at the

site, and the collection of net samples and all vegetation within the area of the frame. Frames were

deployed in each of several representative habitats, where present, in the vicinity of each site. Samples

from each site/habitat were kept separate. Representative habitats were labeled as cattail, sawgrass, or

slough, depending on the predominant vegetation type. The collected material from each site/habitat

was subsampled, preserved, and sent to the FDEP Central Biology Laboratory for processing and

taxonomic identification.

n Hester-Dendy—SFWMD staff deployed Hester-Dendy artificial substrate samplers at each of the

main transect sites on a quarterly basis. The samplers were deployed for a 1-month period, after which

they were collected, preserved, and sent to the FDEP Central Biology Laboratory for processing and

taxonomic identification.

 Sampling Methods: Macrophytes

n Macrophyte Stem Density and Frequency—In April 1997, SFWMD staff conducted a study of macrophytes at the WCA 2A transect sites. A 50-meter tape was laid out at each transect site. A 1-meter

square frame was used every 2 meters along the tape to delineate the sample area for calculation of

macrophyte stem densities (stems/m2) and frequencies (# plots where a species was found/total # of

plots) by species.

n Macrophyte Harvesting—On the other side of the 50-meter tape used for establishing stem densities

and frequencies, SFWMD staff harvested macrophytes for biomass measurements, using the 1-meter

square frame at five predetermined locations to mark the sample area for harvesting.

 Analytical Methods: Algae

n Water Bottles—Samples were processed and enumerated by FDEP Central Biology Laboratory staff

according to FDEP SOPs (e.g., AB-04 and AB-05; available at http://www.dep.state.fl.us/labs/

sops.htm ). Analyses from this and other studies have indicated that Everglades phytoplankton are

largely periphyton that has sloughed off into the water column. Thus, algal data analysis was focused on

the periphyton data.
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n Diatometers—Samples were processed and enumerated by FDEP Central Biology Laboratory staff

according to FDEP SOPs (e.g., AB-02, AB-02.1, AB-02.2, and AB-03; available at http://

www.dep.state.fl.us/labs/sops.htm ).

n Natural Substrate (benthic)— SFWMD processed and enumerated natural substrate samples.

 Analytical Methods: Macroinvertebrates

n Dipnet and Quan Net—FDEP Central Biology Laboratory staff subsampled the dipnet and quan net

samples from each site and analyzed them according to FDEP SOPs (e.g., IZ-02 and IZ-06; available at http://www.dep.state.fl.us/labs/sops.htm ).

n Hester Dendy—FDEP Central Biology Laboratory staff processed and analyzed the Hester-Dendy

samples from each site according to FDEP SOPs (e.g., IZ-03 and IZ-06; available at http://

www.dep.state.fl.us/labs/sops.htm ).

 Analytical Methods: Macrophytes

n Macrophyte Stem Density and Frequency—Stem densities (stems/m2) and frequencies (# plots

where a species was found/total # of plots) by species were counted at each site.

n Macrophyte Harvesting—SFWMD staff conducted biomass analysis of the harvested macrophytes

for comparison of the relative biomass of several species present at each of the WCA 2A transect

sites (e.g., Eleocharis, Nymphaea, Typha).

 Lessons Learned

Periphyton, macroinvertebrate, and macrophyte communities in WCA 2A change substantially from

reference conditions at approximately 7 to 8 km downstream of canal discharges into WCA 2A (see

graphs below). Data analysis has shown that biological populations at the two stations (E5 and F5)

nearest to the three initial reference sites (U1-U3) are very similar in terms of biological community structure. This analysis suggests that these areas, despite slight phosphorus enrichment, still support reference

condition biota. The somewhat higher phosphorus regime at the next stations (E4 and F4 and beyond) are

associated with greater biological changes. Experimental field dosing studies (mesocosms) have been

conducted by SFWMD ESRD, which show that the addition of phosphorus causes changes in periphyton

assemblages consistent with those observed in the transect study.

The WCA 2A transect periphyton data for each site/date have been analyzed using the entire taxonomic

assemblage encountered and using lists of pollution- sensitive and tolerant species based on available

literature and based on experimental phosphorus addition studies (the mesocosms) in WCA 2A.

Macroinvertebrate data have been analyzed using the Florida Index and the macroinvertebrate component

of the Lake Condition Index (LCI), measures of the numbers of pollution-sensitive taxa in a sample that
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Percent Sensitive

Taxa

E367 

(6.08

F425 (7.76

Change Point Analyses of Eleocharis Frequency of Occurrence and

Biomass Data Along the SFWMD Transects. Collected April 1997.

Results of Change Point Analyses Performed on Median Total

Percentage of Pollution-Sensitive (Literature Determined)

Periphyton Taxa.

are routinely used by FDEP in bioassessments of streams and lakes. The use of these methods with the

WCA 2A transect data has demonstrated a clear signal of biological disturbance along the nutrient gradient

in WCA 2A. FDEP is using this information as well as information from other studies conducted in the

Florida Everglades to develop a numeric phosphorus criterion for the Everglades Protection Area.
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Dipnet Quan

Net

Distance 

Median Florida Index

F5 (8.17 

E4 (6.91 

Results of Change Point Analyses on Median Florida Index

(Macroinvertebrate) Values

Additional Comments

The information provided here is based solely on the transect study by SFWMD ESRD in WCA 2A.

Research and monitoring of Florida Everglades water, sediment, and biological quality are being conducted by several research groups in WCA 2A, WCA 1 (Arthur R. Marshall Loxahatchee National

Wildlife Refuge), Everglades National Park (ENP), and WCA 3A, including studies by SFWMD ESRD

similar to the WCA 2A transect study.