&EPA
United States Environmental Office of Water EPA-822-R-02-021
Protection Agency Washington, DC 20460 March 2002
METHODS FOR EVALUATING WETLAND CONDITION
#\ I Using Algae To Assess
Environmental Conditions in Wetlands
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United States Environmental Office of Water EPA-822-R-02-021
Protection Agency Washington, DC 20460 March 2002
METHODS FOR EVALUATING WETLAND CONDITION
#\ I Using Algae To Assess
Environmental Conditions in Wetlands
Major Contributors
Michigan State University
R.Jan Stevenson
The Nature Conservancy
PaulV. 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)
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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 Environ-
mental Conditions in Wetlands. Office of Water, U. S. Environmental Protection Agency, Washing-
ton, 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
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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 l: DEVELOPING ALGAL INDICATORS OF THE ECOLOGICAL
INTEGRITY OF MAINE WETLANDS 3O
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 (Nu) OF4TAXAAT 1O SITES 19
in
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TABLE 3: CALCULATION OF INFERRED TOTAL PHOSPHORUS
CONCENTRATION BASED ON THE RELATIVE
ABUNDANCES (Nu) OF FIVE TAXA AT Two SITES AND
KNOWN TOTAL PHOSPHORUS OPTIMA FOR FOUR OF
THE FIVE TAXA
2O
TABLE CS-l:
NUMBER OF TIMES ALGAL ATTRIBUTES WERE CORRELATED
(R.O.3O) TO 2O POSSIBLE DISTURBANCE INDICATORS FOR
ASSEMBLAGES FROM EACH HABITAT 32
TABLE CS-2:
NUMBER OF TIMES ATTRIBUTES OF HUMAN DISTURBANCE
CORRELATED (R>O.3O) TO 2O POSSIBLE ALGAL ATTRIBUTES
FOR ALGAL ASSEMBLAGES FROM EACH HABITAT 35
LIST OF FIGURES
FIGURE l: RELATIONS BETWEEN BIOLOGICAL INTEGRITY AND
STRESSOR INDICATORS ALONG A STRESSOR
GRADIENT
7
FIGURE CS-l: 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
IV
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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 EPAs 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). EPArelied
heavily on the input, recommendations, and energy of three panels of experts, which unfortunately have
too many members to list individually:
• Biological Assessment of Wetlands Workgroup
• New England Biological Assessment of Wetlands Workgroup
• 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:
htto ://www.epa. gov/owow/wetlands/bawwg
V
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LIST OF "METHODS FOR EVALUATING WETLAND
CONDITION" MODULES
MODULE # MODULE TITLE
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 BlOASSESSMENTS 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 BlOGEOCHEMICAL INDICATORS
19 NUTRIENT LOAD ESTIMATION
2O SUSTAINABLE NUTRIENT LOADING
VI
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SUMMARY
PURPOSE
ae play important roles in wetland function
nd can be valuable indicators of biological
integrity and ecological condition of wetlands. Sam-
pling designs for algal assessment vary with objec-
tives of programs and the algal characteristics that
are measured. Both structural and functional
attributes of algae can be measured, including di-
versity, biomass, chemical composition, plus pro-
ductivity and other metabolic functions. Species
composition of algae, particularly diatoms, is com-
monly 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. Sam-
pling 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. Labora-
tory methods are also well established for most
algal characteristics with relatively standard proto-
cols used in several national stream programs.
Guidelines for data analysis are also reviewed in
this chapter, which includes basic metric develop-
ment 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.
r I Tne purpose of this chapter is to provide guide
J. lines for the use of algae to assess biological
integrity and ecological condition of wetlands.
INTRODUCTION
BACKGROUND
y^lgae are an ecologically important and often
-Zlconspicuous feature of both freshwater and es-
tuarine wetlands (see reviews by Vymazal 1994,
Goldsborough and Robinson 1996, Sullivan 1999).
Periphyton, assemblages of algae and other micro-
organisms attached to submerged surfaces, occur
in nearly all shallow-water habitats wherever suffi-
cient 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. Phytoplank-
ton also can be abundant in deeper and larger wet-
lands 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
TABLE 1: MAJOR HABITATS AND ALGAL ASSEMBLAGES IN WETLANDS
COMMUNITY TYPE
Phytoplankton
Periphyton: Epidendron
Epilithon
Epipelon
Epiphyton
Metaphyton
GROWTH FORM AND HABITAT
Unicellular and colonial forms suspended in the water column
Mats or films growing on dead wood
Mats or films attached to hard surfaces
Mats, floes, or films growing on soft sediments
Mats or films attached to submerged macrophyte stems and leaves
Mats or filaments floating on the water surface or suspended in
water column, often entangled with macrophytes
the
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1994). Algal photosynthesis and respiration can
account for a significant fraction of wetland metabo-
lism 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, Sundback and Graneli
1988,Browderetal. 1994,MacIntyreetal. 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 condi-
tions 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, con-
ductivity, nutrient enrichment, organic contamina-
tion, sediments, pesticides and many other contami-
nants (Round 1981, Stevenson etal. 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 pro-
vide highly precise assessments of changes in wet-
lands 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 wa-
ter chemistry, particularly in wetlands that receive
pulsed nutrient inputs (e.g., storm-water runoff).
Effects of varying nutrients are measurable in a his-
torical record manifested in algal assemblage char-
acteristics (see Stevenson in press). Because of
their role in ecosystem energetics and biogeochemi-
cal 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 ap-
proach for assessing the ecological integrity of wet-
lands when other organisms are not present. Thus,
diatoms could be used to provide a basis for devel-
oping regulatory decisions when many other organ-
isms may not be present. In addition, the rapid
growth rates of algae enable experimental manipu-
lation 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 com-
plete. Even though detailed, species-level assess-
ments do require substantial skill in algal taxonomy,
these skills can be readily developed with an intro-
ductory 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., domi-
nant genera) require considerably less training and
nontaxonomic metrics (e.g., chlorophyll a, nutrient
content) require only a general background in ana-
lytical laboratory practices. Field sampling and labo-
ratory processing times for algal taxonomic analy-
ses 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 ob-
j ectives of specific proj ects. Initial proj ects may be
designed to develop and test metrics for applica-
2
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tion in a specific class of wetlands and in specific
geographic regions. After metrics have been de-
veloped, sampling design should change (e.g., ran-
dom 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 se-
lect wetlands with a wide range of adverse human
influences. Metrics developed with this strategy will
apply to the range of wetland conditions in a re-
gion. Developing metrics using sites that were ran-
domly selected from the set of all sites may cause
oversampling of impaired or unimpaired wetlands
and may diminish development effort. If manage-
ment concerns are based on specific types of ad-
verse human influences, for example, nutrient en-
richment or hydrologic alterations, then metric de-
velopment 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:
• Are conditions at a specific site significantly dif-
ferent from those found at a population of refer-
ence sites; or
• Do wetland conditions in a region have a specific
mean or modal condition and variance?
The effects of project objectives on sampling de-
sign are discussed more completely in Module 4:
Study Design for Monitoring Wetlands.
Wetland class
Algal attributes can differ considerably among dif-
ferent wetland types within the same state or
ecoregion (e.g., Stewart et al. 1985). Therefore, it
often will be necessary to define reference condi-
tions 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 ef-
fects, 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 (S AV). Rain-
fall-driven wetlands, which tend to have low ionic
content and a neutral-acidic pH, contain a periphy-
ton community dominated by chlorophytes and
acidophilous diatoms. Wetlands fed by ground-
water, 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 sur-
vive dry conditions or to recolonize quickly, which
enables rapid recovery of antecedent algal com-
munities 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 con-
ditions 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 char-
acteristics.
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-
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ception of those that exude allelopathic or other-
wise inhibitory compounds. A distinct phytoplank-
ton community also may develop. Both the amount
of light and the nature of the substratum affect per-
iphyton abundance, growth, nutrient content, and
taxonomic composition. For example, senescent
or decomposing vegetation may release more nu-
trients 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 periphy-
ton mats (metaphyton) respond quickly to changes
in water-column nutrients whereas periphyton grow-
ing 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 tar-
geted habitat samples more precisely indicate wet-
land change than composite samples from multiple
habitats. In a study of correlations between algal
attributes and several indicators of human distur-
bance in wetlands in Maine (see case study at end
of module), similar numbers of statistically signifi-
cant correlations were observed with assemblages
from sediments, plants, and plankton. More cor-
relations 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 sub-
strates (Tuchman and Stevenson 1980), this type
of sampling provides a reliable indicator of wetland
nutrient status and other changes in water chemis-
try (McCormick et al. 1996). In fact, the use of
inert surfaces for algal colonization may enhance
the sensitivity of the community to changes in wa-
ter-column nutrient availability because nutrients leak
from plants and sediments (Moeller et al. 1988,
Burkholderl996,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 sea-
sonal patterns of standing crop and species com-
position, and these patterns can differ among wet-
land types. For example, deciduous forested wet-
lands 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 com-
mon during the summer. Furthermore, although less
sensitive to hydrology than macrophytes, most al-
gal communities require some surface water to re-
main active. Disturbance events may be less com-
mon and less severe in most wetlands than in most
streams and rivers, but still they can affect periphy-
ton growth and abundance temporarily. For ex-
ample, heavy rainfall and wind can disrupt or even
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disintegrate floating algal mats and introduce sedi-
ment, 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 as-
sessment 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 oc-
cur. 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 as-
sess 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 pres-
ence 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 wet-
land, whereas nonpoint source inputs or those that
are exceedingly high relative to the size of the wet-
land 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 sam-
pling 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 vari-
ability 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 intro-
ducing excessive variability into the results by (1)
conducting a composite sampling, i.e., combining
several field samples into a single sample for pro-
cessing to account for local variation without in-
creasing costs, (2) selecting a single "indicator" com-
munity for sampling rather than attempting to sample
all algal habitats, and (3) deploying introduced sub-
strates (as discussed above). The efficacy of these
various alternatives will depend on assessment ob-
jectives and the types of wetlands being sampled.
Quantitative versus qualitative sampling
In addition to the frequency and intensity of sam-
pling, 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., col-
lecting 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 in-
formation on overall periphyton condition.
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CONSIDERATIONS WHEN
SELECTING METRICS
The types of algal metrics selected for assessment
and monitoring depend on several factors as fol-
lows.
Overall objectives of the sampling program
Sampling is based on the objectives of the pro-
gram. 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 abroad ar-
ray of quantitative metrics on natural substrates
whereas an assessment of wetland condition, such
as trophic status, can be accomplished using a lim-
ited number of measures obtained from either natu-
ral or standardized substrata and need not be quan-
titative 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 sedi-
ments 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 float-
ing calcareous algal mat is characteristic of olig-
otrophic 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 moni-
tored 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, there-
fore, are not overly susceptible to short-term fluc-
tuations. 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 con-
ditions because of their location on sediments. Epi-
phytic algae may integrate environmental conditions
over the last couple of months as diatom assem-
blages developed on the plants. Phytoplankton
probably reflects the shortest historical context of
all the assemblages. Taxonomic attributes (espe-
cially presence/absence of taxa versus their relative
abundances and density) typically have longer his-
tories than metabolic attributes (photosynthesis,
phosphatase activity).
Existing capabilities
Metrics selected for use undoubtedly will be in-
fluenced by existing facilities and staff expertise.
Thus metrics may be similar to those currently be-
ing 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 con-
tent, and taxonomic composition of samples. Func-
tional attributes are based on measurements of
growth rates and rates of metabolism, such as pho-
tosynthesis, 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).
6
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10
8
SC
13 BI-
• i-H
JD
'o
PQ
Ref
BC
0
10
15 | 20 25
SI
Stressor Gradient (e.g., TP [«g L'1])
FIGURE l: 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 (adaptedfrom 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.
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 par-
ticularly 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 consid-
ered to be actual measures of altered physical,
chemical, or biological attributes caused by human
disturbance. Direct measurements of nutrient con-
centrations, pH, conductivity, acid-neutralizing ca-
pacity, depth and period of inundation, or densities
of non-native taxa commonly are used as stressor
indicators related to nutrient enrichment, hydrologi-
cal 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 bio-
logical 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 indi-
cations of wetland nutrient status (e.g., McCormick
andO'Dell 1996). Species-level assessments, al-
though requiring the greatest taxonomic expertise
to perform, yield the most precise indicators of en-
vironmental 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 dia-
toms within the algal assemblage because the tax-
onomy and species' autecologies of this group are
relatively well established and readily determined
from field collections without additional effort
(e.g., culturing).
7
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Taxonomic characteristics of assemblages can be
used to assess biological integrity of wetlands and
diagnose causes of or threats to impairment. Bio-
logical integrity of algal assemblages can be evalu-
ated at many taxonomic levels, for example, look-
ing 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 al-
tered and that the environmental factors regulating
microbial processes in the wetland have changed.
Similarity in taxonomic composition between ref-
erence 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 character-
ization of taxonomic composition of assemblages in
reference wetlands. Precision in estimates of refer-
ence 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 taxo-
nomic data can be calculated based on densities,
relative biovolumes, relative abundances, or pres-
ence/absence of species, genera, or functional
groups. Similarity calculated with both species and
genus composition of assemblages provides suffi-
cient data to compare assemblage similarity. Func-
tional groups often are defined by growth form and
major taxonomic divisions, such as unicellular, co-
lonial, and filamentous forms of cyanobacteria; dia-
toms; 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 abun-
dances of diatom species as two relatively stan-
dard indicators of biological integrity.
Another approach to assessing biological integ-
rity of algal assemblages in wetlands is to compare
the relative abundance of organisms and the num-
ber of taxa in genera that are common in reference
conditions and rare in disturbed wetlands. For ex-
ample, we often find high numbers of taxa in the
diatom generaEunotia andPinnularia 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 ref-
erence wetlands have high numbers of these dia-
tom genera. These metrics probably are less pre-
cise than direct species-level comparisons with as-
semblages 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 dis-
turbed 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 sen-
sitive 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 envi-
ronmental 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 aute-
cological 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 toler-
ance categories are known for taxa (Lowe 1974,
8
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VanLandingham 1982, Van Dam et al. 1994). In
other cases, specific pH, salinity, or total phospho-
rus (TP) optima for taxa are known (Pan and
Stevenson 1996, Stevenson etal. 1999). Assess-
ments of environmental conditions based on spe-
cies 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 categori-
cal characterizations of species autecologies may
be more transferable among regions. Probably
they are more reliable in the early stages
ofimplementingalgae assessment programs until spe-
cies environmental optima in the study region have
been evaluated.
Conceptually, autecological indices also might be
used to infer biological integrity in cases where ref-
erence conditions in wetlands are not well defined.
Many environmental contaminants, such as nutri-
ents, 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 compro-
mised and that nutrients were a highly probable
cause of impairment. Wetland conductivity (ionic
concentration) often changes with hydrologic alter-
ations, and algae are highly sensitive to changes in
conductivity. Thus, changes in algal species com-
position could be used to indicate hydrologic alter-
ation of wetlands.
Diversity
Richness of taxa numbers and evenness of taxa
abundances are two characteristics of many diver-
sity 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 even-
ness 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) re-
sponses of algal diversity can occur along environ-
mental gradients, which introduces ambiguity into
the interpretation of diversity indices. This ambigu-
ity seems to be related to the maximum evenness of
tolerant and sensitive taxa at midpoints along envi-
ronmental gradients, fewer species being adapted
to environmental extremes at both ends of environ-
mental gradients, and subsidy-stress perturbation
gradients(Odumetal. 1979). Despite these diffi-
culties, species richness and evenness may respond
monotonically (exhibiting only positive or negative
changes, but not necessarily linear ones, as the in-
dependent 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 sedi-
ment 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 etal. 1998). Most
relationships have been established for lake phy-
toplankton; however, periphyton in streams also is
closely related to nutrient status, as increased nutri-
ent availability will yield more biomass (Borchardt
1996). Sediments, toxic substances, and removal
of benthic habitat can limit algal growth and accrual
(Genter 1996, Hoagland etal. 1996). Because bio-
mass and the potential for nuisance algal growths
vary with season and weather (Whitton 1970, Wong
etal. 1978, Lembi etal. 1988), the timing of sam-
pling is important. Biomass is an important attribute
in environmental assessments because it is related
to productivity and nuisance problems.
9
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Biomass can be estimated using several measure-
ments, including cell density, cell biovolume, ash-
free-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 (We-
ber 1973), which indicates the dominance of het-
erotrophs (e.g., bacteria, fungi) relative to algae in
the periphyton community. Ratios between nutri-
ents 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 peri-
phyton biomass (e.g., McCormick et al. 1998) can
be time-consuming, destructive and therefore costly
to obtain. Measuring biomass can require harvest-
ing 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 charac-
terize 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 sam-
pling 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 semi-
quantitative (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 sub strata 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 differ-
ently to enrichment in different wetlands. For ex-
ample, algal biomass in open-water habitats in the
Florida Everglades declines with increased phos-
phorus availability, which differs from many other
aquatic systems (McCormick and O'Dell 1996,
Pan et al. 2000). Biomass also is affected by dif-
ferences in the light regime and grazing pressure
among wetlands as well as nutrient levels. Biom-
ass-nutrient relationships also may be confounded
by the presence of other stressors such as toxic
chemicals. Thus, the accurate interpretation of bio-
mass changes requires an understanding of ecologi-
cal 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 nu-
trient inputs from anthropogenic sources. In olig-
otrophic wetlands, water-column nutrient concen-
trations may be below, at, or near the minimum de-
tection limits, thus increasing the relative uncertainty
associated with analytical results. Periphyton nutri-
ent concentrations integrate variation in nutrient
bioavailability overtime scales of weeks, thus pro-
viding an indication of the recent nutrient status of
10
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the wetland that is not unduly influenced by epi-
sodic events or other short-term fluctuations.
Measurements of periphyton nutrients complement
soil nutrient analyses, which indicate the nutrient his-
tory of the wetland over years or decades. Many
toxic contaminants, such as heavy metals and or-
ganic contaminants, are rapidly adsorbed or taken
up by periphyton (e.g., Vymazal 1994). Their pres-
ence in the water column far underestimates their
presence in the habitat and their potential availabil-
ity to the food web.
Total phosphorus (TP) and nitrogen (TN) con-
centrations 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 andHenzel 1980, Hecky andKilham 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, nega-
tive-density-dependent effects may reduce biom-
ass-specific concentrations of benthic algal TP and
TN and confound estimates of P and N availability
to cells (Humphrey and Stevenson 1992). Volume-
specific, area-specific, and biomass-specific esti-
mates 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 con-
tamination in rivers, lakes, and estuaries (Briand et al.
1978,Whittonetal. 1989, Say etal. 1990). Many
algae accumulate heavy metals when exposed to them
in natural environments (Whitton 1984). The toxic-
ity of heavy metals to algae is one reason for moni-
toring 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. Per-
iphyton production is quantified most easily in the
field by measuring biomass accumulation on intro-
duced 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 sub-
strates placed in all wetlands that will be compared;
otherwise, the relationship between biomass accu-
mulation and nutrient availability will be hard to in-
terpret. Maintaining thi s 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 there-
fore may slough before sufficient biomass has been
achieved at low-nutrient sites. We recommend plac-
ing plenty of artificial substrata at the sites and sam-
pling 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.
1 1
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Metabolism
Metabolic activities of algal assemblages are im-
portant wetland functions and therefore may be in-
cluded in assessments. Photosynthesis (gross pri-
mary productivity), respiration, net primary produc-
tivity (photosynthesis-respiration), nutrient uptake,
and phosphatase activity (PA) are commonly mea-
sured in ecological studies and are sensitive to en-
vironmental change (Bott et al. 1978, Healey and
Hendzel 1979, Wetzel and Likens 1991, Marzolf
etal. 1994, Hill etal. 1997, Young and Huryn 1998,
Whittonetal. 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 mol-
ecules 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, PAlevels in the water and pe-
riphyton 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 periphy-
ton samples. Heterocystous algae and some bac-
teria 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 eth-
ylene. Because cellular N-fixation is an energy-
intensive process, generally it is only induced in re-
sponse to intracellular N limitation. A gas chromato-
graph is required to measure the quantity of ethyl-
ene produced during this assay.
These techniques to measure metabolism rarely
are incorporated into routine monitoring and sur-
vey work because they require more field time than
typical water, phytoplankton, and periphyton sam-
pling. In addition, they are related closely to biom-
ass, which can vary substantially on a seasonal ba-
sis and in relation to weather-related disturbances.
Thus, although metabolic attributes of algal assem-
blages are important attributes of wetlands, algal
metabolism usually is not incorporated into envi-
ronmental assessments until the later stages of more
in-depth investigations.
Bioassay
For purposes of discussion such as this one, bio-
assays usually are defined as in-lab cultures of or-
ganisms in waters from the study site. A valuable,
field-based use of this technique is theSelenastrum
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 En-
vironmental Protection Agency 1978, Trainor and
Shubert 1973, Greene et al. 1976, Ghosh and Gaur
1990, McCormick et al. 1996). Samples are in-
oculated 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 biom-
ass 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 pro-
vide reliable predictions of wetland nutrient status
and limitation (McCormick etal. 1996). Another
advantage of these tests is that they can be stan-
dardized 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
12
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(rather than a standard test organism) and can be
conducted under highly controlled laboratory con-
ditions using waters from the studied habitats or else
conducted in the field. Different dilution levels of
effluents entering the regions under study or spe-
cific 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 cul-
turing them in situ. Nutrient-diffusing substrata, mi-
crocosms, and mesocosms can be deployed at
many scales in the field (e.g., Cote 1983, Fairchild
etal. 1985, Gensemer 1991, Hoaglandetal. 1993,
Lamberti and Steinman 1993, McCormick and
O'Dell 1996, Pan etal. 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 pro-
vide another valuable line of evidence for identify-
ing causes of environmental stress. The results of
bioassays where specific chemicals or effluents were
added can be used to confirm cause-effect rela-
tions between parameters for which only observa-
tional correlations can be obtained in field surveys
(e.g., McCormick and O'Dell 1996, Pan et al.
2000). If changes in multiple algal assemblage at-
tributes, 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 wet-
lands 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, sedi-
ments) and thus are referred to as targeted habitat
samples; orthey 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 (APHA1998). 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 con-
tainer can be attached to the end of a pole (ca. 2 m
long). Qualitative samples can be collected with
plankton nets. However, we recommend collect-
ing whole water samples with known volumes when-
ever possible, so that small algae are not missed
and samples can be assayed quantitatively. Algae
in whole water samples can be concentrated by fil-
tering 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 vari-
ability of the metaphyton, on necessary sample size,
and on ability to isolate the core of algae from sur-
rounding metaphyton (Stevenson personal obser-
vation). Metaphyton in the form of unconsolidated
13
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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 re-
duced with wider cores. Narrower cores (ca. 3
cm) can be used to sample consolidated microalgal
mats. Metaphyton biomass should be expressed
on an area! 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 etal. 1993). Cores of algae should be col-
lected 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 wa-
ter. Some substrata, such as bedrock and logs, can-
not be removed from the water. In those cases,
vertical tubes can be used to isolate an area of sub-
stratum. After algae are scraped from the substra-
tum 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 (McCormicket 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 sam-
plings of substrata during colonization can be used
to determine dispersal, growth rates, and peak bio-
masses of assemblages (Stevenson et al. 1991,
Stevenson 1996).
Samples should be preserved for later processing
as soon as possible. If chlorophyll a will be ana-
lyzed, however, samples cannot be preserved until
subsamples have been extracted in the lab. During
large survey projects when immediate sample pro-
cessing 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 exer-
cised when fixing microorganisms. Double con-
centrations of preservative are recommended for
phytoplankton when treating dense periphyton as-
semblages. 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 examin-
ing 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 accumu-
lated 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.
14
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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 half-
life 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 sur-
face sediment cores as they would in a detailed
paleoenvironmental assessment. Instead of section-
ing and analyzing the entire core, however, they sim-
ply analyze the top 1 cm of sediment (= present-
day 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 acidifi-
cation occurring in lakes (Gumming 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 autecologi-
cal information, and paleoenvironmental approaches
can imply if not indicate the background conditions
of a system and provide mitigation targets for envi-
ronmental remediation (Smol 1992).
LABORATORY
METHODS
T aboratory procedures for most routine
/ J 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 fea-
sible so that comparability among studies is as great
as possible. In thi s section, we set out the steps to
determine algal attributes, and we provide refer-
ences 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 sub sample to re-
duce 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 count-
ing process is being used in many environmental
programs. The first step is designed to character-
ize 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 micro-
scope 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 tech-
nique provides the most complete taxonomic as-
sessment of an algal assemblage. Counts of 300
algal cells, colonies, or filaments and about 500 dia-
tom valves are the standard approach used in some
national programs (Porter et al. 1993, Pan et al.
1996). Counting these numbers of cells usually pro-
vides relatively precise estimates of the relative
15
-------
abundances of the dominant taxa in sample (with
observation of 10 or more cells, colonies, or fila-
ments of each taxon). Alternatively, counting rules
can be defined so that cells of all algae are identi-
fied and counted until at least 10 cells (or natural
counting units = cells, colonies, or filaments) of the
10 dominant taxa are counted (Stevenson unpub-
lished 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, Ken-
tucky Division of Water 1993, Kelly et al. 1998,
Kwandransetal. 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 pres-
ence/absence, percent or proportional relative abun-
dances, percent or proportional relative biovolumes,
or absolute densities and biovolumes of taxa (cells
or |im3 cm"2 or ml/1). Although there is no pub-
lished comparison of these forms of data, they rep-
resent levels of taxonomic scale and probably re-
flect a gradient "from least variable to most vari-
able" on a temporal scale. Presence/absence
records of species should be based on observa-
tions of thousands of cells and should reflect long-
term changes in habitat conditions, especially if im-
migration and colonization of habitats regulates spe-
cies membership in a sample. Relative abundance
and biovolumes of taxa probably reflect recent habi-
tat conditions more than long-term conditions be-
cause of recent species responses to their environ-
ment. 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 com-
monly 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 bio-
mass or only algal biomass. Chl a is first extracted
from cells in acetone or methanol before measure-
ment 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 etal. 1993). Spec-
trophotometric and fluorometric chl a assays should
be corrected for phaeophytin. Dry mass and ash-
free dry mass are measured by drying and com-
busting 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 dis-
tinguishing sizes of cells during microscopic counts,
multiplying biovolume by cell size for all size cat-
egories, and finally summing biovolumes for all size
categories in the sample (Stevenson et al. 1985,
Wetzel and Likens 1991, APHA 1998, Hillebrand
etal. 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 assem-
blages on substrata (Wetzel and Likens 1991).
Assessments of algal biomass with Secchi depth
can be confounded by suspended inorganic mate-
rial 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 de-
termined by collecting several (e.g., five) represen-
16
-------
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 sepa-
rately. Comparisons among wetlands or locations
within a wetland should be done on a habitat-spe-
cific basis (e.g., metaphyton, epiphyton, epipelon),
as habitat can affect periphyton chemical concen-
tration. For example, in reference areas of the Ev-
erglades, epipelon phosphorus concentrations typi-
cally 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 deter-
mined by CHN and P is determined after digestion
and oxidation to PO4. Heavy metals are deter-
mined 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 ex-
pressed 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 Condi-
tions in Wetlands, to compare with vegetation-based
indicators.
FUNCTIONAL ATTRIBUTES
Measuring gross and net productivity and respi-
ration 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 col-
umn 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 mea-
sured with water samples in the laboratory (Healey
and Hendzel 1979).
QA/QC
7)roper quality assurance/quality control
-L (QA/QC) is essential, both to ensure that re-
sults are accurate and defensible and to quantify
the degree of uncertainty associated with each mea-
surement. In this regard, requirements for algal sam-
pling 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 par-
ticipating in the assessment process. One or more
individuals within the assessment group must be des-
ignated as the QA/QC officer and be responsible
for conducting routine audits of field and laboratory
personnel to ensure compliance with SOPs. De-
viations from SOPs resulting from unusual field events
or conditions should be documented in writing, us-
ing 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 organiza-
tion.
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, process-
ing duplicate subsamples allows for laboratory varia-
17
-------
tion to be quantified, as is done routinely for water
chemistry samples. The amount of acceptable vari-
ability 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 documenta-
tion 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). Pho-
tographs provide a convenient means for compar-
ing identifications among laboratory staff. How-
ever, microscopic examination of archived material
often is necessary to confirm identifications. Dia-
tom samples can be archived on microscope slides
when mounted in most resin media, like NaprhaxO.
Long-term archiving of preserved algal samples and
cleaned diatom samples is possible by sealing con-
tainers with tape and wax to prevent evaporation.
Channels of communication within and among labo-
ratories (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 communica-
tion 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., labora-
tory 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, at-
tributes 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 cat-
egories; species environmental optima and toler-
ances; and inferred environmental conditions based
on species relative abundances. Early exploration
of the data will involve multivariate analyses to as-
sess 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 wet-
land classes to increase precision of metrics and
ability to distinguish impairment (see Module 7:
Wetlands Classification).
Data analysis during early stages of metric devel-
opment can be simple. The main goal is to find
wetland attributes that reliably change along with
human disturbance (e.g., box plot analysis). Dur-
ing later stages of metric development, studies should
be designed to describe stressor-response relation-
ships more accurately so that criteria can be estab-
lished for protecting valued ecological attributes (lin-
ear and nonlinear regression, change point analy-
sis). Indicators and stressor-response relationships
may vary among classes of wetlands; such variabil-
ity 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 popu-
lations of sites meet specific criteria and how wet-
land condition changes overtime. 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 de-
tail the calculation of environmental optima and of
autecological indicators of environmental conditions.
18
-------
An overview of data analysis used in environmental
programs is described briefly. Case studies fol-
lowing this section provide examples of how these
steps of data analysis are integrated into environ-
mental programs.
ENVIRONMENTAL OPTIMA AND
AUTECOLOGICAL INDICES
Environmental optima for taxa can be calculated
with a very straightforward approach, if algal as-
semblages are collected from a range of environ-
mental conditions and if taxa respond to those con-
ditions (Zelinka and Marvin 1961, ter Braak and
van Dam 1989). Computer programs have been
developed especially to develop and test auteco-
logical indices of environmental conditions (Line et
al. 1994, Juggins and ter Braak 1992). Often these
calculations are preceded by a multivariate assess-
ment 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 envi-
ronmental 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. Environ-
mental optima (0ft) for each species are calculated
as a weighted average of the relative abundance of
species /' in different habitatsy (n..) and the Kh envi-
ronmental factor (e^) in habitaty:
Environmental conditions in a habitat (ECk)can
then be inferred based on species autecologies (0ft)
and on relative abundances of species for which
autecologies are known (n.):
TABLE 2: CALCULATION OF TOTAL PHOSPHORUS OPTIMA FOR 4 DIATOM
SPECIES WITH THE TOTAL PHOSPHORUS CONCENTRATIONS AND RELATIVE
ABUNDANCES (N ) OF 4 TAXA AT 1 O SITES
SITE U)
i
2
3
4
5
6
7
8
9
10
TP(|JG/L)
24.8
79.3
12.4
14.5
110.3
31.7
57.5
46.9
9.9
10.0
FRSYNEGR
n*
0.052
0.028
0.089
0.085
0.012
0.111
0.066
0.024
0.308
0.090
TP* n,
1.30
2.21
1.11
1.24
1.37
3.52
3.82
1.12
3.05
0.90
MASMITHI
n*
0.348
0.032
0.340
0.277
0.123
0.075
0.043
0.093
0.223
0.531
TP* n..
8.64
2.56
4.22
4.02
13.57
2.39
2.49
4.34
2.21
5.31
NACRYTEN
n>,
0.003
0.029
0.000
0.000
0.023
0.033
0.037
0.115
0.000
0.000
TP* n,
0.07
2.32
0.00
0.00
2.58
1.04
2.13
5.39
0.00
0.00
NIAMPHIB
n*
0.004
0.526
0.000
0.000
0.329
0.027
0.326
0.287
0.000
0.000
TP* n..
0.11
41.72
0.00
0.00
36.23
0.86
18.74
13.44
0.00
0.00
col. Sums
(£)
Optima
0.867
19.63
22.65
2.087
49.74
23.84
0.240
13.53
56.32
1.499
111.09
74.14
Frsynegr = Fragilaria synegrotesca; Masmithi = Mastogloia smithii; Nacryten = Navicula cryptotenella; and
Niamphib = Nitzschia amphibia.
19
-------
The following example shows how these indices
are calculated. In Table 2, the total phosphorus
concentrations in which 4 taxa (indicated by 8 let-
ter species codes) were found were recorded for
10 sites. The relative abundances (n..) were the
v y'
proportions of diatom assemblages that these taxa
represented at the 10 sites. The products of the
phosphorus concentrations and relative abundances
(TP^n.) 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 (Sn.) and the sum of the P concentration/rela-
tive abundance products (STP,, n.) were calculated
and represent column sums (col. sums), for example,
0.867 and 19.63, respectively, forF. synegrotesca.
The environmental optima then were calculated by
dividing the sum of the P concentration/relative abun-
dance 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 andNitzschia
amphibia.
In Table 3, inferred environmental conditions (i.e.,
total phosphorus concentration) were calculated
with relative abundances (n.) and environmental
v y'
optima (&ik) for diatom taxa in samples from two
sites. Products of species-relative abundances and
environmental optima (0»n..) 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 (n.*). If environmental optima are known
for all taxa, n.. = n. *. Inferred environmental con-
' y y
ditions, (i.e., the TP concentrations in this example)
at sites 1 and 2 were calculated as the sum of prod-
ucts of species-relative abundances and environ-
mental optima (SQ/i.) divided by the sum of spe-
cies-relative abundances (Sn.*) for which environ-
mental 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
TABLE 3: CALCULATION OF INFERRED TOTAL PHOSPHORUS CONCENTRATION
BASED ON THE RELATIVE ABUNDANCES (NU) OF FIVE TAXA AT TWO SITES AND
KNOWN TOTAL PHOSPHORUS OPTIMA FOR FOUR OF THE FIVE TAXA
TAXA
Frsynegr
Masmithi
Nacryten
Niamphib
Syulna
TP OPTIMA
(UG/L)
22.65
23.84
56.32
74.14
na
SITE 1
"*•
0.30
0.50
0.04
0.08
0.08
Q*n,
6.80
11.92
2.25
5.93
na
V
0.30
0.50
0.04
0.08
n*
0.05
0.10
0.40
0.20
0.25
SITE 2
Q*n,y
1.13
2.38
22.53
14.83
na
V
0.05
0.10
0.40
0.20
col. sums (S)
Inferred TP cone.
26.90
0.92
29.24
40.87
0.75
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.
20
-------
Biological Integrity). Box plots and regression
analysis can be used to relate algal attributes to hu-
man disturbance. Like other metrics, algal metrics,
should be evaluated for their capability to distin-
guish 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 de-
scribing wetland condition. These indices provide
a useful and objective means of summarizing com-
plex ecological data and have been adopted for use
by a number of states (USEPA1996). As for any
summary, these indices are most informative when
presented in conjunction with the response of indi-
vidual 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 cur-
rently are used and more are under development
for assessing streams and rivers (Kentucky Divi-
sion of Water 1993, Hill et al. 2000). No IBIs
currently exist, however, for assessing algal condi-
tion 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 habi-
tat structure, productivity, and the functional groups
within wetlands are gross changes in biological in-
tegrity that affect other organisms in wetlands. More
subtle changes in algal species composition are a
concern because they indicate a change in bio-
logical integrity of wetlands. Moreover, subtle
changes in species composition also may indicate
alteration of the fundamental environmental con-
straints that regulate microbial processes in wet-
lands.
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 re-
sponse 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 com-
position. Significant changes along these gradients
can be detected using statistical procedures such
as change-point analysis (see case studies). Non-
linear responses along disturbance gradients, there-
fore, can provide a basis for establishing criteria if
they are supported by an ecological basis for label-
ing 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
r I ne basic tools exist to use algae in wetland
J. assessments. However, greater precision and
statistical power for detecting impairment can be
achieved. Several factors could improve that ef-
fort. First, a more precise characterization of ex-
pected condition in wetlands would allow a more
sensitive detection of impairment. That precise char-
acterization depends on better classification of wet-
21
-------
lands and selection of metrics. Still poorly under-
stood is the scale of biological resolution involved,
such as genus versus species level metrics or rela-
tive 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 wet-
land ecology. More basic research in the under-
standing of the role of algae in wetlands will enable
more effective use of algal assessments and more
successful management of wetlands.
22
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CASE STUDY 1:
DEVELOPING ALGAL INDICATORS OF THE
ECOLOGICAL INTEGRITY OF MAINE WETLANDS
Jeanne DiFranco (Project Lead)
Maine Department of Environmental Protection
312CancoRoad
Portland, ME 04103
Jan Stevenson
Michigan State University
Department of Zoology
203 Natural Science Building
East Lansing, MI 48824-1115
PROJECT OBJECTIVES
This proj ect 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 proj ect 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 B AWWG 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.
30
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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 differ-
ent 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 as-
semblages 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.
31
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TABLE CS-l. NUMBER OF TIMES ALGAL ATTRIBUTES WERE CORRELATED
(R>O.3O) TO 2O POSSIBLE DISTURBANCE INDICATORS FOR ASSEMBLAGES
FROM EACH HABITAT
HABITAT
Water
Sediments
Plants
Multihabitat
Sum
GENERA
l
l
5
1
8
s
1
4
4
1
10
N
2
0
4
5
11
S/N
2
4
4
2
12
H
2
2
3
2
9
EVEN
5
2
2
4
13
RICH
1
2
4
1
8
Poss
n=20
n=80
HABITAT
Water
Sediment
Plants
Multihabitat
Sum
ACHN
4
3
1
4
12
CYMB
6
3
6
3
18
EUNO
4
8
5
2
19
NAVI
5
7
2
2
16
NITZ
8
6
6
5
25
FINN
7
5
5
2
19
HABITAT
Water
Sediment
Plants
Multihabitat
Sum
MOIST
l
l
0
10
12
ORG. N
8
7
8
6
29
O2Toi_
6
3
7
0
16
PH
6
6
4
1
17
SALT
7
7
6
2
22
ORG Toi_
5
7
7
1
20
TROPHIC
8
8
7
1
24
SUM
89
86
90
55
n=400
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 (Finn); and autecologi-
cal indices (moisture index, organic N index, low O2 tolerance index, pH, salinity, organic pollu-
tion index, and trophic status index).
32
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H
30
20
o 10
0
0 10 20 30
Maine Disturbance Index
x
CO
2 4
00
o
2
H
3
2
0 10 20 30
Maine Disturbance 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 indi-
ces 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.
33
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H
30
20
x 6
0^
^"O
rH
5
en
o 10
O
0
10 100
Cl (mg/L)
10 100
Cl (mg/L)
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
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TABLE CS-2. NUMBER OF TIMES ATTRIBUTES OF HUMAN DISTURBANCE
CORRELATED (R>O.3O) TO 2O POSSIBLE ALGAL ATTRIBUTES FOR ALGAL
ASSEMBLAGES FROM EACH HABITAT
HABITAT
Water
Sediment
Plants
Multihabitat
Sum
HYDRO
5
5
1
4
15
VEG
2
1
2
6
11
IMPERV
14
12
3
10
39
NFS CUM
10 10
9 8
14 9
6 4
39 31
HABITAT
Water
Sediment
Plants
Multihabitat
Sum
TN
4
2
5
5
16
TP
9
11
5
1
26
CHL A
2
2
3
3
10
HABITAT
Water
Sediment
Plants
Multihabitat
Sum
CA
10
13
5
3
31
NA
12
13
15
5
45
CL
10
10
13
5
38
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 pol-
lution, and cumulative index of all four disturbance types); trophic status indicators, total phospho-
rus, total nitrogen, and chlorophyll a; and general human disturbance indicators as concentrations
of calcium, sodium, and chloride.
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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 (WC As) 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, 3 A, 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 Man-
agement 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
36
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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.
Area of Interest within
Everglades Protection Area
10 0 10 20 30 Kilometers
10 0 10 20 30 Miles
^^^^ Everglades Agricultural Area
Everglades Protection Area
WCA-2A (Area of Interest)
Major Conveyance Canal
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. Sam-
pling 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 Ul -U3).
A series of 15 additional "intermediate" sites were added to the study later to obtain better spatial cover-
age of the lower portion of the transects. The sites have been monitored for water, sediment, and biologi-
cal quality.
37
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SFWMD Traiiseul Si I
SFWMD Mesouosms
Location of Nutrient Threshold Research Stations in WCA 2 A
4048 Kilometers
ASSEMBLAGES MONITORED
Algae (phytoplankton and periphyton)
Macroinvertebrates
Macrophytes
SAMPLING METHODS: ALGAE
Water Bottles—phytoplankton samples initially were collected monthly and later were collected quar-
terly using water bottles. Samples were preserved in the field and sent to the FDEP Central Biology
Laboratory for taxonomic identification.
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.
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.
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SAMPLING METHODS: MACROINVERTEBRATES
Dipnet—SFWMD staff conducted quarterly macroinvertebrate sampling using a standard D-frame
dipnet with a 3 0-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 identifica-
tion.
QuanNet—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.
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
Macrophyte Stem Density and Frequency—In April 1997, SFWMD staff conducted a study of mac-
rophytesattheWCA2A 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.
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
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.
39
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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 ).
Natural Substrate (benthic)— SFWMD processed and enumerated natural substrate samples.
ANALYTICAL METHODS: MACRO-INVERTEBRATES
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; avail-
able at http://www.dep.state.JI.us/labs/sops.htm ).
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 athttp://
www. dep. state.fl. us/labs/sops, htm ).
ANALYTICAL METHODS: MACROPHYTES
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.
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 WC A 2A transect
sites (e.g..,Eleocharis.,Nymphaea, Typhd).
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 struc-
ture. 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
40
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are routinely used by FDEP in bioassessments of streams and lakes. The use of these methods with the
WC A 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.
c
0 0 D i
DO cc CDO c
O O 05
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;o o D
0
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£ -
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Cl
«
0
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r"
__j4J .
10 12
14
e s 10 is 14
CHANGE POINT ANALYSES OF ELEOCHARIS FREQUENCY OF OCCURRENCE AND
BIOMASS DATA ALONG THE SFWMD TRANSECTS. COLLECTED APRIL 1997.
}«H
a
F425 (1.16
DO „ 00
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RESULTS OF CHANGE POINT ANALYSES PERFORMED ON MEDIAN TOTAL
PERCENTAGE OF POLLUTION-SENSITIVE (LITERATURE DETERMINED)
PERIPHYTON TAXA.
41
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Dipnet
Quan
&
a
^
§:
- - do m
1L
o - a a
4 £ S 10 12 Ti
Distance
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 con-
ducted 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 WCA2A transect study.
42
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