United States EnvironmentalProtection Agency

Office of WaterWashington, DC 20460

EPA-822-R-02-019March 2002

Methods for evaluating wetland condition

#9 Developing an Invertebrate Indexof Biological Integrity for Wetlands

United States EnvironmentalProtection Agency

Office of WaterWashington, DC 20460

EPA-822-R-02-019March 2002

Methods for evaluating wetland condition

#9 Developing an Invertebrate Indexof Biological Integrity for Wetlands

Principal Contributor

Minnesota Pollution Control AgencyJudy Helgen, PhD

Prepared jointly by:

The U.S. Environmental Protection AgencyHealth and Ecological Criteria Division (Office of Science and Technology)

and

Wetlands Division (Office of Wetlands, Oceans, and Watersheds)

United States Environmental

Protection Agency

Office of Water

Washington, DC 20460

EPA-822-R-02-019

March 2002

Notice

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

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

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

bioassessment and nutrient e nrichment 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: Developing an Invertebrate Index

of Biological Integrity for Wetlands. Office of Water, U.S. Environmental Protection Agency,

Washington, DC. EPA-822-R-02-019.

Acknowledgments

EPA acknowledges the contributions of the following people in the writing of this module:

Judy Helgen (Minnesota Pollution Control Agency), Jeanne DiFranco (Maine Department of Environ-

mental Protection), Mike Gray (Ohio Environmental Protection Agency), Peter Lowe (United States

Geological Survey), Randy Apfelbeck (Montana Department of Environmental Quality), and Russ

Frydenborg (Florida Department of Environmental Protection).

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

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

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

ii

i i i

Contents

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

List of “Methods for Evaluating WetlandCondition” Modules ...........................................................................................vi

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

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

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

Process for Developing an Invertebrate IBIfor Wetlands .......................................................................................................3

Step 1. Select study sites ......................................................................5Step 2. Plan the invertebrate sampling .............................................5Step 3. Field sampling methods and decisions .................................8Step 4. Sample processing procedures .......................................... 15Step 5. Metric analysis ......................................................................... 18

A. Selection of attributes .................................................... 18B. Forming the IBI...................................................................... 22

Conclusions and Recommendations .......................................................... 23

References ........................................................................................................ 25

Appendixes.......................................................................................................... 34

Glossary ............................................................................................................. 46

List of Figures

Figure 1: Invertebrate IBI Score Plotted Against anEstimation of Human Disturbance on LargeDepressional Wetlands in Minnesota ....................................2

Figure 2: Flowchart for Developing an Invertebrate Index ofBiological Integrity .....................................................................4

Figure 3: Illustration of Sampling Sites in a Wetland WithEmergent Vegetation Shown as Symbols ..............................7

i v

Figure 4: Framed Screen for Separating Vegetation FromInvertebrates During Dipnetting........................................... 12

Figure 5: Activity Traps Used by Minnesota .......................................... 13

Figure 6: Total Number of Invertebrate Taxa Plotted Againstthe Log of the Chloride in the Water (mg/L) FromLarge Depressional Wetlands in Minnesota ..................... 19

Figure 7: Intolerant Taxa Plotted Against the Log ofPhosphorus (mg/L) in the Water of LargeDepressional Wetlands in Minnesota ................................. 20

v

Foreword

In 1999, the U.S. Environmental Protection Agency (EPA) began work on this series of reports entitledMethods for Evaluating Wetland Condition. The purpose of these reports is to help States andTribes develop methods to evaluate (1) the overall ecological condition of wetlands using biologicalassessments and (2) nutrient enrichment of wetlands, which is one of the primary stressors damagingwetlands in many parts of the country. This information is intended to serve as a starting point for Statesand Tribes to eventually establish biological and nutrient water quality criteria specifically refined forwetland waterbodies.

This purpose was to be accomplished by providing a series of “state of the science” modules concerningwetland bioassessment as well as the nutrient enrichment of wetlands. The individual module formatwas used instead of one large publication to facilitate the addition of other reports as wetland scienceprogresses and wetlands are further incorporated into water quality programs. Also, this modularapproach allows EPA to revise reports without having to reprint them all. A list of the inaugural set of20 modules can be found at the end of this section.

This series of reports is the product of a collaborative effort between EPA’s Health and EcologicalCriteria Division of the Office of Science and Technology (OST) and the Wetlands Division of theOffice of Wetlands, Oceans and Watersheds (OWOW). The reports were initiated with the supportand oversight of Thomas J. Danielson (OWOW), Amanda K. Parker and Susan K. Jackson (OST),and seen to completion by Douglas G. Hoskins (OWOW) and Ifeyinwa F. Davis (OST). EPA reliedheavily on the input, recommendations, and energy of three panels of experts, which unfortunately havetoo many members to list individually:

n Biological Assessment of Wetlands Workgroup

n New England Biological Assessment of Wetlands Workgroup

n Wetlands Nutrient Criteria Workgroup

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

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

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

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

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List of “Methods for Evaluating WetlandCondition” Modules

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

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

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

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

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

Wetland Bioassessment Program

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

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

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

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

Integrity for Wetlands

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

in Wetlands

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

Wetlands

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

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

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

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

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

Enrichment

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

Risk Assessment

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

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

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

Module # Module Title

1

Summary

T he invertebrate module gives guidance fordeveloping an aquatic invertebrate Index of

Biological Integrity (IBI) for assessing the condi-tion of wetlands. In the module, details on eachphase of developing the IBI are given. First, in theplanning stage, invertebrate attributes are selected,the wetland study sites are chosen, and decisionsare made about which stratum of the wetland tosample and what is the optimal sampling period orperiods. Then, field sampling methods are chosen.The module describes field methods used in sev-eral States, and gives recommendations. Labora-tory sampling procedures are reviewed and dis-cussed, such as whether and how to subsample,and what taxonomic level to choose for identifica-tions of the invertebrates. Specific categories ofattributes, such as taxa richness, tolerance, feedingfunction, and individual health are discussed, withexamples. Appendices to the invertebrate modulegive details about the advantages and disadvantagesof using invertebrates, of the different attributes, ofvarious field sampling methods, and of lab process-ing procedures as used by several State and Fed-eral agencies. The module and appendices give adetailed example of one State’s process for devel-oping an invertebrate IBI, with a table of metricswith scoring ranges, and a table of scores of indi-vidual metrics for 27 wetlands. A glossary of termsis provided.

Purpose

T he purpose of the invertebrate module is todescribe the advantages of using aquatic

invertebrates for assessing the condition ofwetlands, and to present approaches for develop-ing IBIs for wetlands.

Introduction

T his module describes the advantages of usingaquatic invertebrates for assessing the condi-

tion of wetlands and presents approaches for de-veloping an invertebrate IBI for wetlands. Pro-cesses, methods, and examples of invertebrate IBIsfor wetlands are presented, along with summariesof approaches currently used in several States. Themodule is based primarily on work done on pondedfreshwater wetlands, but the approaches describedcan be modified for other types of wetlands. Themodule describes development of the IBI, but otherindexes and approaches for assessing the conditionof wetlands, particularly multivariate techniques(Davies et al. 1999, Reynoldson et al. 1997), canbe used. A glossary of terms is also provided.

Why use aquatic invertebrates toassess wetlands condition?

n Because they respond to many kinds ofstressors to wetlands, as shown in Figure 1.

What are the advantages anddisadvantages of using aquatic

invertebrates?

Several advantages and disadvantages of usingaquatic invertebrates are reviewed in Appendix A.Briefly, some of the advantages of using inverte-brates for biological assessments of wetlands are:

n They are commonly and widely distributed inmany types of wetlands (Batzer et al. 1999).

n They respond with a range of sensitivities tomany kinds of stressors; they are commonlyused for toxicity testing and ecologicalassessments in waterbodies (e.g., see Barbouret al. 1999, Beck 1977, Cairns andNiederlehner 1995, deFur et al. 1999, Eulissand Mushet 1998, Hart and Fuller 1974,

2

Heliovaara and Vaisanen 1993, Helgen andGernes in press, Hellawell 1986, Kerans andKarr 1994, Lewis et al. 1999, Morris et al.1989, Rainbow 1996, Saether 1979, Servos1999, Stuijfzand et al. 2000, Warwick 1980).

n Many aquatic invertebrates complete their lifecycles in wetlands; they are exposed directly tophysical, chemical, and biological stressorswithin the wetland (Clarke 1981, Driver 1977,Hanson and Swanson 1989, Fairchild 2000,Klemm 1982, Larson 1987, Mackie, in press;Merritt and Cummins 1996a; Walker 1953,1958, Walker and Corbet 1975, Westfall andMay 1996, Wiggins 1996, Wiggins et al. 1980,Wrubleski 1987).

n Aquatic invertebrates are important in wetlandfood webs of wildlife (Batt et al. 1992, Colburn1997, Deutschman 1984, Eldridge, J. 1990,Fredrickson and Reid 1988, King andWrubleski 1998, Krapu and Reinecke 1992,

Swanson et al. 1977, Swanson et al. 1985,Wissinger 1999).

n They have public appeal in citizen monitoringprograms (see Module 8, Volunteers andWetland Biomonitoring; Helgen and Gernes1999).

Many wetland invertebrates complete the life cyclefrom egg to adult in a wetland, and therefore aredirectly exposed to wetland conditions and stres-sors. In infrequently flooded, seasonal, and tem-porary wetlands, invertebrates will have shorter lifecycles of days to weeks (Schneider and Frost 1996,Wiggins et al. 1980). In more regularly flooded,more permanent wetlands, invertebrates with longerlife cycles of weeks to months, such as dragonfliesor crayfish, will be present. Populations of inverte-brates with shorter life cycles, such as fairy shrimpand mosquitoes, will respond more quickly to hu-man disturbances, but they may recover morequickly, either from resting eggs or fromrecolonization by adult insects. Invertebrates with

Figure 1: Invertebrate IBI score plotted against an estimationof human disturbance on large depressional wetlands

in Minnesota. The IBI has 10 scored metrics; the gradient combines factors of chemical pollution and alterations in thebuffer zone and near wetland landscape.

3

longer life cycles, such as dragonflies, some finger-nail clams, and snails, will experience longer expo-sure to wetlands conditions. In some cases, recov-ery from losses of juveniles may take longer, be-cause of more limited seasons of egg laying by adultsand longer development times from egg to adult(Corbet 1999).

The disadvantages of using aquatic invertebratesfor biological assessments are detailed in AppendixA. The biggest challenge is the amount of staff timeand expertise that is needed for picking the organ-isms from the samples and for identifications. Tech-niques for reducing the amount of picking time, suchas using a screen under vegetation while dipnetting,using activity traps, or by subsampling, will be de-scribed below. Some State agencies or organiza-tions may lack the laboratory facilities to do the workin-house and will need to contract out the work.

When work is contracted out, it is important forthe project managers to provide the contractor withexplicit protocols and procedures for identificationsand analysis in relation to the needs of the program.An advantage of doing the work in-house is thatthe staff involved can provide active input into thedevelopment of the biological indexes and can par-ticipate in implementing the findings into the State’sprograms. Whether or not the identifications arecontracted out, it is vital to have scientists on staffto provide active input into biocriteria developmentand implementation.

In sum, disadvantages of using macroinvertebratesare:

n Sample processing takes a lot of staff time orresources.

n Organizations may lack facilities for processingand identifying invertebrates.

Process forDeveloping an

Invertebrate IBI forWetlands

A flow chart for developing an invertebrateIBI for wetlands is shown in Figure 2. A simi-

lar flowchart showing an example of the processfor developing an invertebrate IBI in Minnesota isshown in Appendix K. Overall, the process in-volves sampling invertebrate attributes of severalwetlands of similar class and region representing arange of human disturbance or impairment, fromleast to most disturbed. After sampling, the infor-mation on the degree of impairment is related to themeasures of various invertebrate attributes to seewhich of the attributes show predictable responsesto impairment. These attributes will constitute themetrics for the IBI. Scores are assigned to eachmetric to indicate the level of response to humandisturbance (see Module 6: Developing Metrics andIndexes of Biological Integrity). The metric scoresare summed for the total IBI score. Decisions aremade as to which range of IBI scores indicates apoor condition, i.e., not attaining designated use (ifone exists), or a moderate or excellent condition.This module will focus primarily on the steps in theprocess that relate to developing invertebrate IBIs.

Additional detail for this process can be found inModule 4: Study Design, Module 7: Wetlands Clas-sification, Module 6: Developing Metrics and In-dexes of Biological Integrity, and Module 17: Land-scape Characterization for Wetlands Assessments.Additional information on biological monitoring ofwetlands is also available in Rader et al. (in press).

It needs to be stated that other approaches aresuccessful in evaluating the condition of waterbodieswith invertebrates. Multivariate methods for ana-

4

l Select ecogeographic regionl Decide on wetland classl Select sites within wetland classes that exhibit a

range of disturbances

l Select invertebrate attributes of sensitivity, rich-ness, tolerance, trophic structure, or other attributeslikely to respond to human disturbance

l Gather literature about regional invertebrates for thewetland class

l Determine which strata of wetland to samplel Select optimal seasonal sampling period for maturity

of invertebrates

l Select appropriate sampling methods for objectivesof the program

l Pretest sampling methods to determine number ofsamples to be taken per site, and to assure thedesired types of invertebrates are collected

l Decide if samples will be preserved andprocessed in the lab, or sorted and identifiedin the field; write Standard Operating Procedures

l Sample sites within the index period, at the sametime collect samples for chemical analysis andassess the surrounding landscape

l Decide to pick entire sample or subsamplel Decide on taxonomic levels for identifications

establish database of taxa lists and ITIS codesl Develop Standard Operating Procedures and set up

a Quality Assurance plan for repicking and forindependent verifications of identifications

l Establish a reference collection with severalspecimens of each taxon

l Plot attribute data against human disturbancegradient

l Select most responsive 8-12 metricsl Score metrics by trisecting data or other methodl Sum the metric scores for IBI, plot IBI against

disturbance gradient

step 1:select studysites

step 2:Plan invertebratesampling

step 3:Field Sampling

step 4:Sample Processing

step 5:Metric Analysis

Figure 2: Flowchart for Developing an Invertebrate Index ofBiological Integrity.

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lyzing invertebrate data are used for stream assess-ments in the Biological Monitoring Program in Maine(Davies and Tsomides 1997, Davies et al. 1995,1999). Discriminant analysis of invertebrate datapredicts the degree of impairment by comparisonwith known biological characteristics of the state ofMaine’s four water quality management classes.(See also Marchant et al. 1997, Norris 1995, Wright1995, Hawkins and Carlisle in press, U.S. EPA1998, Lake and Reservoir Bioassessment andBiocriteria Appendix E). Reynoldson and others(1997) found estimates of accuracy and precisionto be higher when multivariate techniques were usedfor data analysis compared with multimetric meth-ods. If multivariate analysis is used, it is importantto use a method that allows interpretation of pro-portional attributes rather than one that is limited todata on the presence or absence of taxa (seeReynoldson et al. 1997). A disadvantage of multi-variate methods is the complexity of setting up thedata analysis.

Step 1. Select study sites

To reduce natural variability, an ecoregion or eco-logical region and a class of wetlands are chosenfor developing the IBI (see Module 7 on Classifi-cation). It is necessary to select specific wetlandclasses, because invertebrate assemblages may dif-fer among classes of wetlands (in Batzer et al. 1999;see Huryn and Gibbs, Leslie et al., Marshall et al.,Smock et al., and others; Carlisle et al. 1999,Weisberg et al. 1997). It is important to includeseveral least impaired or reference wetlands alongwith a range of wetlands that are affected by humandisturbances. Sufficient numbers of least-impairedreference wetlands and wetlands experiencing arange of impairments are needed to detect signifi-cant dose-response relationships between the in-vertebrate attributes (Y axis) and the measures ofhuman disturbances (X axis). See the Glossary fordefinitions of disturbance and human disturbance.

The impaired wetlands can be selected to targetthe major types of human-caused stressors to wet-

lands, those that are most likely to be causing im-pairment to the invertebrates within the region andwetland class. Invertebrates exhibit a wide rangeof sensitivities to human-induced stressors such aspesticides, metals, siltation, acidification, loss ofvegetation or vegetation diversity, nutrient enrich-ment, and changes in the oxygen regime (Adamus1996, Beck 1977, Eyre et al. 1993, Helawell 1986,Resh and Rosenberg 1984, Saether 1979).Macroinvertebrates respond to disturbances inwetland vegetation because invertebrates are de-pendent on the vegetation as part of their foodsource (Wissinger 1999), for attachment sites, refu-gia (Corbet 1999, p. 164, Orr and Resh 1989),and egg laying. Some dragonflies and damselflieslay eggs on specific types of aquatic vegetation(Sawchyn and Gillott 1974, Corbet 1999, p. 591).

Step 2. Plan the invertebratesampling

Selection of invertebrate attributesAttributes are measures of the invertebrate com-

position to be tested to see if they show a gradedresponse, or dose-response, to human disturbancessuch as chemical pollution, siltation, or habitat al-teration. If a response is seen, the attribute will beselected as a metric and scored as part of the over-all IBI score. See Module 6: Developing Metricsand Indexes of Biological Integrity. More detailedinformation on the selection of invertebrate attributesis given near the end of this module in Step 5 onMetric Analysis. Appendix F lists advantages anddisadvantages of different kinds of attributes, andAppendix I shows metrics used by Minnesota forlarge depressional wetlands. Appendix G showsthe attributes used or tested by several States.

Attributes are selected from major categories ofinvertebrate composition (Barbour et al. 1996, Reshet al. 1995), such as measures of taxonomic rich-ness, measures of tolerance proportions and intol-erant taxa, measures related to trophic structure andfunctional feeding groups (see Merritt et al. 1996,

6

1999) and other measures related to longevity, in-troduced or exotic species, and invertebrate healthor condition (see Diggins and Stewart 1998,Hudson and Ciborowski 1996, Warwick 1980).

Several invertebrate attributes are tested, and thedata for the attributes are related to measures ofhuman influence. From the attributes that show sig-nificant relationships with human disturbances, a setof 8 to 12 are selected as metrics. An attribute thatdoes not show a significant response to human dis-turbances will likely be discarded. However, if thereis some reason to think the attribute might show aresponse to different kinds of stressors that werenot included in the study design, it might be retainedfor further testing.

It is important to plan to measure the types of in-vertebrates that would be expected to inhabit theclass of wetland in the ecological region of interest.The taxonomic composition of the invertebrates willlikely differ in bogs, playa lakes, temporary ponds,prairie potholes or riparian wetlands, for example(see Batzer et al. 1999). Information can be soughtfrom regional scientific literature and from inverte-brate biologists in the area. Whatever the class ofwetland might be, the major categories of attributeswill be represented, such as taxa richness and tol-erant and intolerant taxa, even if the taxonomic com-position differs. If there is little preexisting informa-tion on species composition for the particular wet-land class, it may be helpful to do preliminary sam-pling in reference wetlands to develop a list of spe-cies and then select the attributes to be tested. Thiscould be done when the sampling methods are be-ing tested.

Determine which stratum or zone(s) of thewetland to sample

One decision is whether to attempt to sample theentire wetland and all of its habitats, or to sampledefined zones or strata within the wetland. Wet-lands have several zones that are related to the in-

fluence of hydrology and/or plant communities. Forexample, freshwater marshes have shallow water,emergent macrophyte, and floating-leafed and sub-mersed aquatic plant zones. Bottomland forestwetlands may have zones ranging from aquatic toswamp to semipermanently flooded to seasonallythen temporarily flooded (Mitsch and Gosselink1993). It may not be necessary to sample all thezones in a wetland to assess its condition. Eitherenough of the wetland habitat should be sampled toassess its condition, or the area most sensitive toimpairment should be assessed. In a small wet-land, sampling all the habitats may be possible, butin larger wetlands the work effort may necessitatechoosing strata for the sampling and maintaining aconsistency among wetlands of the habitats that aresampled. The choice can include the following con-siderations:

n Sample in the zone or stratum that is likely tohave the greatest variety and production ofmacroinvertebrates,

n Sample in the zone or stratum that is consideredto be most vulnerable or most affected by humandisturbances, or

n Select a habitat type that is representative ofthe wetland, as opposed to unique or minor inextent; sample enough of the habitats to integratethe conditions in the wetland.

See also Module 4: Study Design for MonitoringWetlands. Examples of the zones that were se-lected by different States involved in wetland moni-toring are given in Appendix B.

Aquatic macroinvertebrates occur in associationwith benthic sediments, emergent vegetation,submergent vegetation, and open-water habitats.They colonize hard substrates such as tree roots orrocks. Some feed on the microflora that colonizethe surfaces of plants and hard substrates; someare predators on the smaller herbivorous ordetritivorous invertebrates. Different invertebrateassemblages are associated with these different

7

habitats, even with different kinds of wetland veg-etation (Burton et al. 1999, Gathman et al. 1999,King and Brazner 1999). In preliminary studies ofcoastal wetlands, some invertebrate attributes dif-fered among types of emergent vegetation zones.Attributes were selected that gave consistent, ratherthan contradictory, responses to human disturbanceamong sites across four defined plant zones (Bur-ton et al. 1999).

The vegetated areas of wetlands have been ob-served to have more taxa of chironomids (Driver1977) and aquatic beetles (Aitkin 1991, Timms andHammer 1988) and other taxa (Dvork 1987).Emergent vegetation areas had greater richnesswhen compared with open water areas that lackedsubmersed vegetation (Olson et al. 1995, Voigts1976). If fish are present, open-water areas mayhave more predation by fish on invertebrates

(Hanson and Riggs 1995). Having more taxa invegetated areas may not reflect direct herbivory onthe plants, but the conversion of macrophytes intodetritus is an important source of nutrition for inver-tebrates (Euliss et al. 1999). Also, as stated previ-ously, macrophytes provide refugia, substrates forgrowth of algae and small organisms, and egg lay-ing sites.

An example of sampling locations in a depres-sional wetland in Minnesota is given in Figure 3.

Select the optimal seasonal sampling periodThe seasonal index period is the window of time

when the sampling of the wetland is optimal to ob-tain the most representative, mature invertebratecommunity and the maximum number of identifi-able taxa. The different and seasonal life cycle strat-

Two standardized dipnetting samples are taken from the wetland about 20-30 meters apart (DN1 and DN2).Each sample consists of three to five sweeps repeated in two efforts (represented by two DN1s and twoDN2s). Ten activity traps (BT) are placed at the edge and in representative areas of the near shore emergentvegetation zone in water < 1 m deep. Wetland is not drawn to any scale. Method is used by Minnesota(MPCA). See Appendixes B and C.

Figure 3: Illustration of sampling sites in a wetland withemergent vegetation shown as symbols.

DN1

DN1

DN

DN

BT

BT BT

BT

BT

BT

BT

BT

BT

BT

2

2

8

egies of invertebrates present a challenge as to whento sample, especially if the sampling is to be donejust once in a season. If the wetland is sampled tooearly in the year, the invertebrates may be less ma-ture, making the identifications more difficult. If thewetland is sampled later in the season, there maybe emergences of aquatic insects from the wetlandand immigration of adult insects that fly into thewetland from other waterbodies. If the wetland issampled too late in a season, the smaller wetlandsmay have dried down or become choked with veg-etation.

The seasonal index period will differ across dif-ferent regions of the United States and it will differfor different types of wetlands. Invertebrates areknown to undergo seasonal changes in populationsand species that inhabit a waterbody. Ideally, thewetland should be sampled in more than one sea-son; however, this may not be practical for Stateprograms. In selecting an index period, the follow-ing should be considered:

n The invertebrates should have developedsufficiently to be identified by biologists.

n The index period should bracket a time whenas many resident taxa as possible are present.

n The index period is not during a time that thewetland is likely to dry down or becomechoked with vegetation (so it is still sampleable).

n The index period could attempt to precedemaximum fish predation, if any, while stillencompassing the season of maximum richnessand development of invertebrates.

n The index period should be shifted somewhatto account for unusually late or early seasons(the main goal is to optimize the number ofinvertebrate taxa present and mature).

See Appendix B for the approaches taken by dif-ferent States and Appendix H for addresses of Statecontacts. Maine samples in June, to obtain the most

mature of some of the invertebrates (Davies et al.1999), Minnesota (Gernes and Helgen 1999,Helgen and Gernes in press) samples during Junewhen there is greater maturity in the Odonata andmore water in the wetlands. Wetlands in the moresouthern location of a study set are sampled earlierin the index period. Montana (Apfelbeck 1999)samples the Plains Ecoregion in April to mid-June,the Intermountain Valley and Prairie Ecoregion fromJune to August, and the Rocky Mountain Ecoregionfrom mid-June to September. Rapid BioassessmentProtocols for Use in Streams and Wadeable Riv-ers (Barbour et al. 1999) contains a discussion ofthe sampling seasons for stream invertebrates.

Step 3. Field sampling methodsand decisions

Before the actual sampling for monitoring wetlandstakes place, several decisions need to be made.These decisions will be based in a large part on theprogram objectives or information needs that theinvertebrate IBI is addressing:

n What strata or zones of the wetland to sample(see discussion of selecting sampling stratumabove and see Module 4 on Study Design)

n Whether to sample once or more than onceduring the season (see discussion on selectingseasonal index period above)

n Whether to sample all habitats in the stratum orzone (multihabitat approach), or selectedhabitats

n Whether the approach collects the range ofinvertebrates needed for the attributes

n What sampling methods will be used to collectthe desired invertebrates efficiently

n How many samples can be processed in thelab

Recommendations for field methodsSeveral methods for collecting invertebrates in

wetlands are described below and listed with ad-

9

vantages and disadvantages in Appendix C. Thefollowing are recommended, but may not be appli-cable or suitable for researchers or State agenciesunder certain circumstances.

n Sample a stratum of the wetland that containsmost of the macroinvertebrates: often theshallow areas have emergent or submergedvegetation; very small wetlands can be sampledall around the edges.

n Sample once during the season, afterdetermining when the maximum developmentof the invertebrates occurs, and take more thanone sample at that time; if resources permit,sample in two seasons taking more than onesample on each visit date.

n Sample all habitats within the stratum or zone,or sample selected habitats if they are knownto have a wide representation of invertebrates.

n Use a dipnetting method with a standardizedand repeatable protocol; combine this withactivity traps to collect the motile predators (seediscussion of these and other methods below).

Determining the number of samples to take:species richness and sampling effort

Once these decisions have been made, the sam-pling methods should be pretested in the field toensure they collect the invertebrates that are neededfor the attributes and to determine the numbers ofsamples that will be needed. In practice, States,Tribes, and researchers often have to balance thelimitations of resources against the requirements forvalidation of data. It is useful to test methods inreference wetlands to determine how many samplesare needed to obtain the desired representation ofthe invertebrate fauna.

It is well known in ecological research that thenumber of species or taxa collected frequently in-creases with the sampling effort (Magurran 1988).A quantitative sampling method (e.g., cores orGerking samplers) will yield data on the density of

taxa or species per unit area sampled. Asemiquantitative sampling method (dipnetting, ac-tivity traps), as described below, will record thenumber of taxa per total sample count. This is callednumerical taxa richness. In either case, the numberof species or taxa usually increases with sample size,i.e., with the number of samples taken or the areasampled. For the purposes of comparing sites, it isessential that the number of samples and areasampled be the same at all sites.

Several samples should be taken with consistentmethods at all sites to determine how many samplesare necessary to collect a desired percentage of thetotal number of species collected. Ideally, enoughsamples will be collected to achieve the plateau levelat which taking more samples does not increase thenumber of species. However, this may not be prac-tical, because a plateau may not be reached evenwith many samples (see Mackey et al. 1984).Sparling et al. (1996) collected multiple samples atthe same sites and recorded the increases in thepercent of total invertebrate taxa with the increasein the number of samples analyzed. In 1, 2, 3, 4, 5,and 6 samples there were, cumulatively collected,40%, 56%, 60%, 64%, 68%, and 72% of the in-vertebrate taxa, respectively. In addition to com-paring the taxa gained by added sampling effort,the effects on the final evaluation of the wetland,which lead to the IBI or other index score, shouldbe gauged for each level of effort. To reduce vari-ability, a minimum of three samples is recommended,although each method should be tested for its vari-ability if possible.

It may not be possible to do a power analysis atthe beginning of IBI development. Power analysisdetermines how many samples need to be taken toobtain enough statistical power to detect differencesamong sites using the IBI scores. To do this, sev-eral samples would be taken in each of severalwetlands that have a range of human disturbances.For discussions of power analysis and the numberof samples to take, see Eckblad (1991), Allan

10

(1984), and Green (1989). Several papers maybe helpful (Davies et al. 1995, 1999, Davies andTsomides 1997, Fore et al. 1994, Rankin and Yoder1990, Rathbun and Gerritsen in press). Variabilityin the biological data may increase with greater im-pairment, as seen in biological monitoring in Ohiostreams (Rankin and Yoder 1990, Yoder 1991).

Select the appropriate sampling methodsThe methods appropriate for sampling will depend

on the type of wetland and the goals of the sam-pling. Appendix B describes sampling protocolsused by several states with advantages and disad-vantages. The emergent or submerged vegetationin wetlands presents a challenge for sampling. Se-lected methods used in wetlands studies are sum-marized in Appendix C with advantages and disad-vantages. More detail on the methods can be ob-tained from references cited in the text to follow.See Batzer et al. (in Rader et al. in press) on sam-pling invertebrates in wetlands.

There is a need for comparisons among the mostcommonly used sampling methods for sampling in-vertebrates, particularly for differences in inverte-brate composition and attributes. Brinkman andDuffy compared Gerking samplers, cores, activitytraps, and artificial substrates (1996) and foundGerking samples collected significantly more taxathan cores. Hyvonen and Nummi (2000) comparedactivity traps with corers, finding fewer active in-vertebrates in core samples. Some of the articlescited below have comparative studies of methods.

Is a quantitative sample necessary?A quantitative sampling method collects inverte-

brates by trapping the column of water and/or thebottom sediments from a known dimension of bot-tom area. This permits calculating the number ofinvertebrates per unit area of wetland bottom.Quantitative methods may be particularly useful inassessing the productivity of wetlands in relation towaterfowl production. They are not as necessary

for developing IBIs (Karr and Chu 1999). Ex-amples of quantitative sampling methods formacroinvertebrates are the Gerking box sampler(Gerking 1957, Anderson and Smith 1996); thestovepipe sampler (see Wilding sampler in Welch1948, Turner and Trexler 1997); and various meth-ods for collecting (Gates et al. 1987) or coring thebenthic sediments (Hyvonen and Nummi 2000,Swanson 1978, 1983). Some have used an Ek-man grab sampler mounted on a pole.

The Gerking box sampler—a quantitativesampler

The Gerking box sampler is lowered into the wa-ter until the open bottom of the sampler (0.3 m2) ispushed into the sediments leaving the open top pro-jecting above the water’s surface. Everything withinthe sampler is collected from the sediments, veg-etation, and water column. A flat 1 mm mesh plateis slid across the bottom before the sampler is pulledup and drained, and the sample is rinsed into a sieve.The advantages of this device are the quantitativeestimates of the invertebrates and the fact that itcaptures many of the organisms from the benthos,vegetation, and water column. Gerking samplerscollect greater abundance and greater numbers ofinvertebrate taxa than activity traps or artificial sub-strates (Brinkman and Duffy 1996). The chief dis-advantage of the Gerking box is the labor involvedin processing the large samples that it collects. Inaddition, the device is bulky, requiring two peopleto carry it to the site and a crew of three to four tooperate. It is not useful if woody vegetation is present.This method has been used in projects at the PatuxentNational Wildlife Refuge (see Appendix B).

Core sampler—a quantitative samplerThe advantage of using core samplers is the

quantitation per unit bottom area of wetland andthe shorter collection time. A disadvantage is thefact that core samples contain fewer invertebratetaxa than Gerking samplers or sweep nets (Hyvonenand Nummi 2000, Cheal et al. 1993) and the or-ganisms have to be processed from the mud. Cores

11

sample a smaller bottom area than the Gerking boxand they do not capture the motile taxa. The fre-quently anaerobic benthic sediments of some wet-lands would not be expected to have the range oftaxa found in other habitats. Cores are appropriateif the goal is to analyze the benthic invertebrates,such as oligochaete worms, benthic molluscs, andchironomids, or if the type of wetland has low wa-ter or saturated conditions (see Hershey et al. 1998).Only 2 taxa of chironomids were collected fromcores pooled from benthic sediments in depressionalwetlands, whereas a mean of 12 taxa were col-lected by a dipnet method (Helgen et al. 1993).

In samples that include benthic sediments, suchas cores or stationary samplers, the organisms canbe floated from the sediments in dense (30%) su-crose or salt solutions (Anderson 1959, Ritchie andAddison 1991). As much sediment as possible iswashed out of the sample with running water on aNo. 30 (600 mm) mesh sieve. After water isdrained from the residual debris and sediment, the30% sucrose solution is added to float out the or-ganisms from the residual. This technique is mostlylimited to muddy benthic sediment samples that arevery difficult to pick.

Semiquantitative sampling methodsDipnet or sweep net samples. Dipnetting, also

referred to as sweep netting, is probably the mostcommon method for sampling invertebrates in shal-low vegetated wetlands (see Appendix C). Withconsistent, standardized protocols, dipnetting yieldssemiquantitative data on invertebrate abundancesand taxa richness. Without a consistent effort,dipnetting yields only qualitative results. See Ap-pendix B for methods used by different States toproduce semiquantitative data with dipnetting. Re-peatability is dependent on the standardization ofprotocols and the training and skill of the field crews.

Ways to assure repeatability in dipnetting proto-cols include:

n Defining the number of sweeps (Minnesota,Florida)

n Defining the amount of time for sweeps(Montana, Ohio, Merritt et al. 1996, 1999)

n Defining the distance of sweeps and the number(Florida, Maine)

n Doing consistently repeated efforts at each site(Minnesota)

Dipnetting samples a large area and the range ofwetland habitats. Dipnets have been considered auseful method because they capture a high richnessof species, comparable to that obtained with theGerking box sampler (Cheal et al. 1993, Kaminski1981). Dipnets collect more taxa than are collectedby cores or artificial substrates (Mackey et al. 1984),and collected more taxa of chironomids than cor-ers, artificial substrates, or activity traps in Minne-sota (Helgen et al. 1993). An advantage ofdipnetting is that experienced crews can collectsamples quickly over a wide range of habitats.

See Appendix C for more details of dipnet pro-cedures. In Florida, 20 0.5-m sweep net effortsare distributed in proportion to the representationof the habitat type, with emphasis on the “produc-tive habitats” (Florida DEP 1994, 1996, and FLSOP). In Minnesota, 3 to 5 sweeps are done twicefor each sample, i.e., a total of 6 to 10 sweeps persample, and 2 samples are collected per wetland(Gernes and Helgen 1999, Helgen and Gernes inpress). In Ohio, a 30-minute multihabitat dipnettingis done and invertebrates are handpicked from sub-strates that could not be sampled by dipnet(Fennessey et al. 1998). Montana samples all habi-tats in the wetland for 1 minute, 3 to 4 times, de-pending on the wetland size and complexity, or untilat least 300 organisms are collected into onecomposited sample (Apfelbeck 1999). Merritt,Cummins, and others have used 30-second sweepswith D-frame nets to assess the status of vegetatedriparian systems (Merritt et al. 1996b, 1999,

12

Cummins and Merritt in press; Cummins et al.1999). A time-constrained dipnetting protocol maybe difficult when wetlands are particularly muckyor habitats are farther apart.

A disadvantage of dipnetting is the amount of veg-etation and other debris that gets trapped in the net.This adds greatly to the picking time needed in thelab. Unless debris is removed in the field, it in-creases the amount of sample that must be pre-served. Minnesota reduces the vegetation insamples by laying the net contents on a framed ½”12” x 16” hardware cloth screen that sits on a panof water contained in a floatable tray (see Figure 4and Appendix C). The vegetation is gently teasedapart periodically over a 10-minute period and theinvertebrates are encouraged to drop into the wa-ter in the pan beneath the screen. This process isdone twice for one dipnet sample, then the pan ofwater is poured through 4” cylindrical 200 micronmesh sieves. Florida reduces the amount of veg-etation in its multihabitat dipnet samples by washing

it in the net and removing the larger pieces of veg-etation, as does Ohio.

Some habitats are not amenable to dipnetting, e.g.,areas with a lot of woody debris or roots or verydense vegetation, or water that is too shallow.Coring methods may be necessary in very shallow,saturated wetlands or during drought cycles(Hershey et al. 1998). Also, dipnetting tends to misssome of the very motile invertebrates, e.g., the largepredatory beetles and bugs. This problem is over-come by combining the use of dipnets and activitytraps.

Multihabitat dipnetting methods. The multi-habitat dipnetting method takes samples from mostof the habitats within the wetland. The samplingcan be distributed among the habitats in proportionto the habitat type or by other consistent protocolssuch as time constraints. Training field crews toassess the habitats and to sample consistently using

Figure 4: Framed screen for separating vegetation frominvertebrates during dipnetting.

½” hardware cloth 12” x 16” screen sits on a pan of water contained in a larger tray. Vegetation isplaced on top of the screen and invertebrates are encouraged to drop into water in pan over a period of 10minutes. Process is done two times for one sample.

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standardized protocols is important. See Appen-dix C for the variations on the multihabitat methodused by Florida, Montana, and Ohio.

Advantages of the multihabitat method are thatthe sample represents the complexity of the wet-land and collects most of the invertebrate taxa, ex-cept the very motile taxa. Disadvantages of themethod are the time needed for processing the largecomposite sample, or, alternatively, the need tosubsample or use a minimum count (e.g., 200 or300) or organisms (see Appendix C). Multihabitatsamples tend to have a lot of vegetation and debris,unless it is removed in the field. Also, wetlandsmay differ in habitat types (Burton et al. 1999).

While it would be preferable to preserve sepa-rately the samples from each habitat, for efficiency,the sample is usually a composite of collections fromall the habitat types. Separate preservation wouldrequire added effort in the field. An advantage ofkeeping the collections from the habitat types sepa-rate would be in the analysis of the data to deter-mine which habitats show the most response to hu-man disturbance.

Activity traps—a semiquantitative method. Anactivity trap is a passive sampler usually containinga funnel-shaped opening and an enclosed container(jar or cylinder) that receives and traps organismsthat swim into the trap. With a funnel opening around2.5cm diameter, macro-invertebrates can pass intothe trap. When placed horizontally in the wetland,activity traps (AT) give semiquantitative data on themotile wetland invertebrates, effectively trapping themotile predators (e.g., the leeches, aquatic beetles,and bugs) better than dipnets (Hilsenhoff 1987b,1991, Turner and Trexler 1997). They are less suit-able for collecting the nonmotile types of inverte-brates (Hyvonen and Nummi 2000).

Activity traps are variously styled as funnel traps(Swanson 1978, Fennessey et al. 1998, Hanson etal. 2000, Gernes and Helgen 1999, Helgen andGernes in press, Murkin et al. 1983, Swanson1978). They are left out at least one night, so thenight-active invertebrates swim or crawl into thefunnel openings. The style of trap that is used byMinnesota is pictured in Figure 5. Traps used byMinnesota and Ohio EPA are described in Appen-dix C.

Figure 5: Activitytraps used by

Minnesota. Ten activity traps are placedhorizontally in near shore area ofwetlands. a. Trap is held to ½” 4 ftdowel by a sliding bracket of 3" thinwall PVC. A wingnut unites this andthe larger bracket that holds thebottle; b. funnel is cut from the topend of a 2 liter beverage bottle. Fourgrooves 1/8 x 2" are cut into rim offunnel to snap into bottle, c. bottle isheld by a 4" PVC open bracket. (seeWik D. in References)

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Activity traps should be placed in shallow water(<1 m to a few cm deep), because the active inver-tebrates, such as predaceous beetles and bugs, feedthere. If they are placed too deep, fewer inverte-brates are collected. Typically, the traps are placedhorizontally, although vertical placement has beenused, primarily for zooplankton with smaller open-ing size in the funnel (Whiteside and Lindegarrd1980). The traps are usually retrieved after 24 to48 hours, depending on the water temperature, witha longer period in colder water.

An advantage of activity traps is that they providesemiquantitative data. Also, less training and timeare required to set out and collect several traps in arepeatable way. Activity traps collect a sample thatis clean of most vegetation and requires less pro-cessing time. Minnesota averaged 2.3 hours of pro-cessing time for 10 activity traps per wetland.

A disadvantage of activity traps is the need to re-visit the site to collect the traps after one or twoovernights. Activity traps do not collect the rangeof macroinvertebrates needed for the IBI. Theymust be used in conjunction with another samplingmethod, such as dipnetting, if the goal is to have abroad representation of the invertebrates for the IBIattributes. There is also a concern that predationwithin the trap might alter the invertebrate compo-sition. One study (Elmberg et al. 1992) suggeststhat fish, but not invertebrate predators, may affectrichness, but not abundance, of the invertebrates.

Another disadvantage of activity traps is the pos-sible collection of large numbers of tadpoles so densethey seem to exclude macroinvertebrates. Decom-position was advanced even after 24 hours in thewater (Peter Lowe, Patuxent Wildlife Research,personal communication; Sparling et al. 1995).Dead organisms in the traps might attract somepredators to the traps, although this has not beenevaluated.

More study is needed on the effectiveness of thedifferent designs for activity traps, particularly thesize of the funnel opening and how it might affectthe size of organisms, including vertebrate preda-tors, that can enter the traps. The effect of trapvolume and whether the trap is enclosed (plastic orglass) versus open (screen) should be reviewed forpredation impact that might be reduced by declin-ing oxygen levels in the enclosed traps. Minnesotaexcludes air bubbles in activity traps to reduce ac-tivity of predators inside the traps (Ralph Gunderson,St. Cloud State U., MN, personal communication).Finally, more study is needed on the relation be-tween water temperature and efficiency of funneltraps for active macroinvertebrates. Murkin et al.(1983) suggest that water temperature was not sig-nificantly correlated with the abundance of inverte-brates in activity traps, but temperature does affectinvertebrate activity (Henrikson and Oscarson1978).

Artificial substrates. Artificial substrates arepassive samplers that are made of hard substrates(plates, tiles, or objects that mimic the natural sub-strates) that are placed in the water for a few weeksto allow colonization on the substrates by certainaquatic invertebrates. The substrates are colonizedby epiphytic fauna and have been used to collectinformation on a number of attributes (King andRichardson, in press; King and Richardson, sub-mitted). They were useful in studies on the impactof mosquito control agents on chironomids (Liberet al. 1998, Ferrington 1994). More taxa of chi-ronomids were found on artificial substrates on platesthat were placed up in the aquatic macrophytes thanon plates placed on the bottom (Liber et al. 1998,Ferrington 1994). A disadvantage of artificial sub-strates is the lack of collection of actively swimminginvertebrates and consequent lower taxa than ob-tained with dipnets (Turner and Trexler 1997).

15

Advantages of using artificial substrates are:

n They yield a clean sample relatively free ofdebris.

n The data are semiquantitative (based on area,size and number of plates).

n They are easy to deploy in the field.

Disadvantages of artificial substrates are:

n They collect chironomids, oligochaetes, snails,and other epiphytic taxa, but not Odonata orother active invertebrates collected by othermethods.

n The need to put the samplers out and collectthem several weeks later, with the possibility ofloss or disturbance of samplers over time.

Step 4. Sample processingprocedures

Several decisions need to be made concerningsample processing:

n Whether to preserve samples in alcohol in thefield or chill and bring back live

n Whether to pick samples in the lab or do muchof the picking in the field

n How to conduct the sample picking in the lab

n Whether to pick the entire sample or asubsample

Appendix D lists some options for the abovechoices, along with advantages and disadvantages.If samples are preserved in alcohol or another pre-servative, there should be adequate ventilation forsample processing staff even after the samples havebeen rinsed and placed in water. The following arerecommended, but other options may be neededdepending on the circumstances of the researchersor State agencies. Whatever the protocols are, theymust be used consistently.

n Preservation of the sample in the field ispreferable, so the processing of the sample takesplace in controlled conditions in a laboratory.

n Picking the samples should be done in thelaboratory, not under varying field conditionsof climate and lighting.

n Staff who pick the samples should have sometraining in aquatic invertebrates, but they neednot be the taxonomists who do theidentifications.

n Picking the sample in the lab should be doneeither under a microscope or in a glass tray overa light box with a magnifying lamp.

n The sample should be picked into partly sortedcategories to expedite identifications.

n If the entire sample is picked, it is more efficientto collect a sample that has reduced vegetationand debris.

n Preservative should be rinsed off samplespicked in water; adequate ventilation should beprovided for staff doing the picking and theidentifications.

Subsampling or picking the entire sample?It is recommended the entire sample be picked if

the sampling method and resources permit this. Tomake this more efficient, it is helpful to collectsamples that are not overloaded with vegetation anddebris. When wetlands are sampled with a repeat-able, consistent sampling effort, picking the entiresample improves proportion metrics of total samplecount, taxa richness, and variability in metrics(Doberstein et al. 2000, Ohio EPA 1988,Courtemanch 1996) and allows better compara-bility among sites. However, with stationary samplessuch as the Gerking box, stovepipe, or Wilding sam-plers, or with certain multihabitat dipnetting meth-ods, there may be a lot of vegetation and debris. Insuch cases, a subsampling process may be neces-sary. See Appendix C for some methods to re-duce debris in these samples.

16

A sample can be subsampled by using a griddedscreen or a grid underlying a glass tray. Randomsquares or rows are selected to ensure that a de-fined proportion (at least 20%) of the sample gridis picked. There are sample splitters and othermethods, but these need to be tested and their usemay be difficult with debris-laden samples fromwetlands.

Alternatively, picking the sample until a minimumnumber of macroinvertebrates, typically 100, 200or 300, is found will reduce the picking effort. Thereare disagreements on the validity of taking this kindof subsample. For issues of subsampling see Sovelland Vondracek (1999), Barbour and Gerritsen(1996), Courtemanch (1996), Vinson and Hawkins(1996), Somers et al. (1998), and Doberstein et al.(2000).

Some investigators facilitate the sample pickingby staining the invertebrates with Rose Bengal stain(100 mg Rose Bengal in 1,000 mL preservative,see Lackey and May 1971).

Taxonomic resolution and identifications ofinvertebrates

The level of taxonomic identifications, to order,family, genus, or species, will depend on the at-tributes or metrics that are used, the degree of cer-tainty needed in the wetland assessments, and theease or difficulty of identifying the particular groupsof invertebrates. More information about the con-dition of a waterbody is obtained when organismsare identified to the genus or species level. Amonggenera within a family there are often differences insensitivities to factors causing impairment, likewiseamong the species within a particular genus. A veryrapid assessment approach or a citizen monitoringprogram might identify to the family level.

n It is recommended to identify the invertebratesto the lowest possible taxonomic level, at leastto genus and to species where possible, because

of the different sensitivities within sometaxonomic groups.

n It is recommended, where possible, to have theidentifications done by biologists who are onstaff and trained in taxonomy; these staff canalso participate in the development of biologicalmonitoring tools and help guide the biologicalmonitoring program.

n It is recommended that reference collections bemaintained with several specimens of eachorganism that was identified, and to have theseidentifications verified by outside taxonomists ifthe taxonomist on staff lacks expertise inparticular groups (e.g., chironomids).

n It is recommended that a database managementstaff person be dedicated to the biologicaldatabase and participate with the biological staffin its development of the program.

n It is recommended that the taxonomic namesbe coded in the database with the nationalIntegrated Taxonomic Information System(ITIS) codes (www.itis.usda.gov); unique codeswill be needed for the taxa that are not yetcoded by ITIS.

n It is recommended that the known functionalfeeding groups for each taxon be built into thedatabase so that functional feeding groupattributes can be tested.

Identifications at least to the genus level are rec-ommended for biological assessments to be usedfor resource agency decisions. A number of excel-lent keys and sources are available (for example,Merritt and Cummins 1996a; Hilsenhoff 1995,Thorpe and Covich 1991, Walker 1953, 1958,1975, Needham and Westfall 1954, Klemm 1982,Westfall et al. 1996, Clarke 1973, 1981, Mackiein press, to name a few). Some taxa will be identi-fied to the lowest practical level, depending on avail-able taxonomic sources, staff expertise, and workeffort for identifications. For some groups or lifestages, reliable taxonomic keys may not be avail-

17

able. For other groups, such as the fingernail clamsand leeches, identifications are difficult because ofthe time needed to process the shells to view thehinge teeth, or to relax certain leeches and dissectthe reproductive structures. Some snails can be iden-tified to species, others only to genus level.

Once the choices are made, they should be con-sistently applied in the assessment protocol by allstaff working on the identification of the samples.For the total taxa metric, a clear definition of whichtaxa to be included must be determined for the stan-dard identification procedures in the lab. The staffbiologists need to keep track of changes in tax-onomy and maintain literature sources used for theidentifications. The ITIS codes should be regularlyupdated (see Appendix E).

Some agencies contract out the identifications ofcertain special groups, such as chironomid larvaeto genus level. If chironomids are identified only tothe four subfamily/tribe levels, information aboutcondition is lost compared to identifications to thegenus level, where more than 12 to 16 genera maybe found in one wetland (Diggins and Stewart 1998,Helgen and Gernes 1999, Gernes and Helgen inpress, Beck 1977).

For some of the functional feeding group metrics,taxonomy is carried to the level needed to describethe function (Merritt and Cummins 1996a). In thiscase, all Odonata would immediately be classed aspredators, or all members of a family might beclassed in one functional feeding group. In othercases, identifications to lower taxonomic levels areneeded to define the functional feeding groups (seeMihuc 1997). Therefore it is prudent to identify themacroinvertebrates to the lowest possible taxonomiclevel, genus or species, where possible.

Immature specimens and morphospeciesSome specimens will be too immature to identify

to genus and will have to be left at the higher level

of identification, e.g., family. Others may be dam-aged and not identifiable. In some cases the expe-rienced taxonomist may be able to extrapolate, withcaution, from other specimens in the collection.Some specimens will be identified to genus but willbe distinctly different from others in the same genusin the sample. These specimens must be recordedso that they are recognized as an additional speciesin the sample, i.e., as a “morphospecies” (Oliverand Beattie 1996). If species are carefully identi-fied as distinct morphologies, this level of identifi-cation can produce accurate measures of speciesrichness, but only when the experienced biologist iscertain the differences are not simply due to differ-ing stages of development.

It is important to define standard protocols forcounting the number of different taxa when the iden-tifications of different taxa are at different levels oftaxonomic resolution. For the counting rules usedby Maine, see Davies and Tsomides (1997).

Contracting out the identificationsof the invertebrates

Contracting the services of taxonomic experts isan option when staffing levels or limitations in ex-pertise and facilities prevent analyzing the inverte-brates “in house,” especially for particular inverte-brates that require specialists to identify. Contract-ing some invertebrate taxonomy can free the staffto develop the indexes and analyze and report data.This can be a cost-efficient way to obtain reliabledata, however it entails staff time in forming andtracking contracts.

It is important to give the contractors clear guid-ance on the groups of invertebrates to identify, thetaxonomic levels, the protocols, and the attributesdesired, and not to let the contractor make thesedecisions. It is important to have in-house staff withexpertise in macroinvertebrates give guidance forthe work of any outside consultants. It is recom-mended to have all of the macroinvertebrate groups

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identified to allow calculation of new or improvedmetrics that may not have been previously used.

Step 5. Metric analysis

a. Selection of attributes

Selecting invertebrate attributesAs stated in Step 2, attributes are candidate

metrics that are measures of the invertebrate com-munity. They are tested to see if they show a dose-response to increasing levels of impairment, suchas chemical pollution, unnatural hydrologic or habi-tat alterations, or siltation. If a response to impair-ment is seen, the metric will be scored and its scorewill contribute to the overall IBI score for a wet-land.

An IBI is more robust if it is composed of 8 to 12metrics selected from different categories of at-tributes that represent patterns of responses tochanges in the physical, chemical, and biologicalintegrity of the wetland and its surrounding land-scape. The major categories of attributes and theirexpected responses to increases in impairment (inparentheses) are:

n Measures of taxa richness (decrease)

n Measures of tolerance (increase) andintolerance (decrease)

n Measures of trophic structure and functionalfeeding groups (varies)

n Measures of life cycles, such as longevity andreproduction (decrease)

n Measures of poor condition or poor health ofindividuals (increase)

Advantages and disadvantages and expected re-sponses to human disturbance of these and othercategories of attributes are reviewed in AppendixF. Attributes in use by several States are given inAppendix G. Some of the categories of attributes

are discussed below, with a rationale for the ex-pected responses.

Taxa richnessTaxa richness is the count of the number of types

of invertebrates that inhabit an ecosystem. The taxarichness, primarily genera or species, of a wetlandis enumerated by counting up all the types of inver-tebrates collected from the sampling effort. It isimportant to use a standard protocol for countinginvertebrate taxa when the taxonomic level for theidentifications differs among taxa. The number oftaxa commonly declines as human disturbance in-creases (Barbour et al. 1995, Kerans and Karr1994, Fore et al. 1996). This attribute shows ahigh statistical power for detecting differences amongsites (Sandin and Johnson 2000). However, thereare exceptions, e.g., when low-nutrient wetlandsreceive more nutrients (Rader and Richardson1994), or forested canopy areas are opened upover wetlands that were shaded and less produc-tive before the forest clearing (King et al. 2000).Plotting the taxa richness against the measure of dis-turbance will show the response curve. If there is aunimodal response, with a peak of taxa richness atthe intermediate level of human disturbance, the met-ric may not be useful.

In Figure 6, the number of invertebrate taxa de-creases as the concentration of chloride increasesin the water in the wetland. The increased chloridemay alter the active pumping systems of inverte-brates for maintaining osmotic balance in body flu-ids. Urban wetlands (Urb) receiving stormwaterrunoff are especially high in chloride.

ToleranceTolerant taxa inhabit a wide range of habitats and

tolerate a wide range of conditions. The number oftolerant taxa may not change with impairment, butthe relative abundance of tolerant organisms tendsto increase as the amount of impairment to the siteincreases. This might be measured by the propor-tion of known taxa, or by the proportion repre-

19

sented by the dominant two or three taxa to thesample count.

Tolerance values assigned to stream invertebratesare based largely on organic enrichment from datasets of stream invertebrates (Hilsenhoff 1987a). TheHilsenhoff Biotic Index for streams (HBI, seeHilsenhoff 1987a, 1995) is calculated from toler-ance values assigned to species of various streaminvertebrates in relation to their sensitivities to or-ganic pollution. New England has a list of family-level tolerance values derived primarily from EPA’slisting (EA Mid-Atlantic Regional Operations 1990)with some regional modifications. Hilsenhoff alsohas developed a family-level HBI, the FBI, for arapid field assessment or organic pollution(Hilsenhoff 1988).

Tolerance values assigned to stream invertebratesmay not be applicable to wetlands invertebratesbecause many wetlands invertebrates are tolerantof, or adapted to, the fluctuating oxygen conditionsin wetlands. In addition, there are many inverte-brates in wetlands that are “wetland specialists”:water boatmen; backswimmers; diving beetles andmarsh beetles; fairy shrimp, clam shrimp, and tad-pole shrimp; mosquitoes; marsh flies; biting midges;horse and deer flies; the snails in the familiesPhysidae, Lymnaeidae, and Planorbidae; and fin-gernail clams (see Wissinger 1999). For these andother species that are predominantly wetland spe-cialists, there is little or no existing information ontheir tolerances to human caused impairments.

Attributes that relate to tolerances ofmacroinvertebrates in wetlands need to be derived

20

30

40

50

60

70

80

90

0 0.5 1 1.5 2 2.5

Log Chloride in Water

Tot

al #

Inve

rteb

rate

Tax

a

Ref

Ag

Urb

Figure 6: Total number of invertebrate taxa plotted againstthe log of the chloride in the water (mg/L) from large

depressional wetlands in Minnesota.Total taxa included the number of genera of mayflies, caddisflies, dragonflies, damselflies, chironomids,beetles, bugs, macrocrustaceans, plus the number of genera or species of snails and leeches and thepresence/absence of fingernail clams and Chaoborus. Chloride range 1–110 mg/L.

20

for the invertebrates of the wetland class and re-gion. Decisions about which taxa are “tolerant” needto be based on examination of data sets from a rangeof high-quality and impaired wetlands. Tolerant taxamight be present in the range of wetlands, but theywould show a proportionate increase in wetlandswith greater human disturbance. The designationsof tolerance then need to be tested on another dataset for validation. Karr and Chu (1999) suggestthat about 10% of the taxa, or 5% to 15%, be de-fined as either tolerant or intolerant. One cautionon designations of tolerance values, if done at thegenus level, is the possibility that the species withina genus may differ in their tolerances (Hilsenhoff1998). It is preferable, but not always possible, todesignate species rather than genera as tolerant orintolerant.

Intolerant taxa, by definition, are more likely todisappear under impaired conditions. Their pres-ence indicates good conditions. Preliminary deter-minations of intolerant species would require the

examination of the data set to see which taxa tendto disappear from the more impaired wetlands butare found in reference sites. Again, designations ofintolerant taxa need to be tested with other datasets. An example of intolerant taxa, originally de-rived from data on depressional wetlands and ap-plied to a new data set on large depressions is shownin Figure 7.

Trophic function and functional feedinggroup attributes

Trophic function attributes relate to the type offood eaten by the invertebrates: herbivores con-sume algae and plant material, predators consumeanimals, omnivores eat both plant and animal mate-rial, and detrivores consume decomposed particu-late material. The proportion of predators is ex-pected to decline as impairment increases (Keransand Karr 1994). Many wetlands are lacking in fishpredators and are dominated by invertebrate preda-tors such as leeches, dragonfly and damselfly lar-vae, and juvenile and adult aquatic beetles and bugs

0

1

2

3

4

5

6

7

8

-2 -1.5 -1 -0.5 0 0.5

Log Phosphorus in Water

Num

ber o

f Int

oler

ant T

axa

Ref

Ag

Urb

Figure 7: Intolerant taxa plotted against the log of phosphorus(mg/L) in the water of large depressional wetlands in Minnesota.

The types of intolerant taxa were derived from a previous project on depressional wetlands. The intolerant taxawere two genera of dragonflies (Leucorrhinia, Libellula), two of caddisflies (Triaenodes, Oecetis), two chironomidgenera (Tanytarsus, Procladius) and fingernail clams (Sphaeriidae). P range 0.015–1.38 mg/L.

21

(Fairchild et al. 1999, Wissinger 1999). In the fishIBI, the proportion of individuals that are top carni-vores (Simon and Lyons 1995) is expected to showa decrease in response to human disturbance. Morework is needed in testing of attributes of trophicfunction against gradients of human disturbance inwetlands.

Attributes of functional feeding groups (FFGs)merit further exploration. Such groups are basedon the mode of food acquisition rather than the typeof food eaten (Merritt and Cummins 1996b, Merrittet al. 1996, 1999). Merritt’s work in defining func-tional feeding groups of many macroinvertebrateshas laid a foundation for the analysis of FFG at-tributes. The FFGs of each taxon, if defined, shouldbe included in databases to facilitate the testing ofFFG metrics.

In streams, the analysis of functional feeding groupshas been useful for understanding the changes instream ecology from losses of riparian vegetationor conversion from a shaded, leafy stream to anopen system in which algae, rather than leaf litter,become the primary food source for the inverte-brates (Merritt et al. 1999, see also Rawer-Jost etal. 2000, Hannaford and Resh 1995, Resh 1995).Cummins and Merritt (2001) and Cummins et al.(1999) have analyzed FFGs in wetland riparianareas.

Functional feeding group attributes that decreasedwith increasing human disturbance in streams werethe proportion of grazers and the proportion ofpredators (Kerans and Karr 1994). An attributethat tended to increase as human disturbance in-creased was the relative proportion of filterers(Kerans and Karr 1994). Much more testing isneeded of functional feeding group attributes in re-lation to human disturbance in wetlands. See Merrittet al (1996) for criteria levels for FFG ratios forevaluating ecosystem parameters in streams.

Some functional feeding group attributes haveshown greater variability than taxa richness mea-sures, partly because some of the FFG attributeshave been expressed as ratios (e.g., scrapers/gath-erers) rather than proportions (Resh 1988, Resh1994, Stan Szczytko, University of Wisconsin,Stevens Point, WI, personal communication). Ra-tios are susceptible to variability if both of the vari-ables are changing. Other FFG attributes are ex-pressed as proportions and these may be more ro-bust when tested in wetland systems. Taxonomiclevels needed for FFGs vary widely. Some groups,e.g., Odonata, can be entirely classed as preda-tors, whereas others (see Merritt and Cummins1996a) will require identifications to genus or spe-cies level. It is recommended that identificationsbe done routinely to the lowest taxonomic level.

Other invertebrate attributes to considerOther attributes can be considered; some are in

Appendix F. Some can be found in the literature(Barbour et al. 1996, Resh et al. 1995, Kerans andKarr 1994). A few that might apply to wetlands inthe future are discussed below.

Condition or health of individualinvertebrates

In the fish IBI, there is a metric that records thenumber of deformities, erosion, lesions, and tumorsin individual fish in the sample (Sanders et al. 1999).This metric is most responsive in highly contami-nated areas, as was found in Ohio. To date, mal-formations have been recorded in some aquatic in-vertebrates, i.e., chironomids and dragonflies. Inchironomids, malformations have been shown to bemore numerous in response to contaminants (Palmer1997, Hudson and Ciborowski 1996a,b; Warwick1980 1990). Minnesota has data on malforma-tions in chironomids from 43 wetlands (done byLeonard C. Ferrington), but has not yet developeda metric. Malformations were found in the castexoskeletons (exuviae) of dragonflies in Minnesota,first in a report from rivers and bog/fen areas(Steffens and Smith 1999) and then from some large

22

depressional wetlands (Smith 2000). There is littlemonitoring data on malformations in most inverte-brates. Therefore, it is unknown whether malfor-mations are increasing in invertebrates the way theyappear to have increased in frogs in the 1990s innorthern North America (Helgen et al. 2000, Hoppe2000, Ouellet et al. 1997, Northeast Natural Re-source Center 2000).

A possible attribute to indicate the health of in-vertebrates is the proportion of coverage of aquaticinsects by bacteria as an indicator of nutrient en-richment in wetlands, based on recent work byLemly and King (2000).

Introduced or exotic speciesThere are numerous exotic or introduced species

in freshwaters of the United States (see Cox 1999,Mack et al. 2000). Some of these invade wet-lands. As an attribute, the number of exotic taxa orthe proportion would be expected to increase ashuman disturbances increase. Introduced fish willalter the invertebrate composition (Hanson andRiggs 1995). In Minnesota, the huge oriental mys-tery snail, Cipangopaludina chinensis, has beenfound in urban wetlands, probably after being dis-carded from aquaria. It consumes submersedaquatic plants and creates open areas in the veg-etation. The rusty crayfish, Orconectes rusticus,has been expanding its range and introduced intolakes and wetlands (Helgen 1990), where it con-sumes the macrophytes.

Generalists and specialistsAttributes that address the proportion or richness

of generalists and specialists could be explored (seeWissinger 1999, Mihuc 1997). A community witha high proportion of wetland specialists is thoughtto reflect more competition and evolution of spe-cialists, whereas one with a high proportion of gen-eralists may indicate less competition and more useof the same resources. The number of specialisttaxa, or the proportion of specialist individuals, mightbe expected to decrease as the human disturbance

increases in wetlands. In the Floristic Quality As-sessment method (Fennessy 1998) for using plantcommunities to assess wetlands, plant taxa that havea higher fidelity for particular types of habitats, i.e.,a higher coefficient of conservatism, will give theFloristic Quality Assessment Index a higher score(see Module 10, Using Vegetation to Assess Envi-ronmental Conditions in Wetlands).

b. Forming the IBI

To form the invertebrate IBI, the attributes areplotted as a scatter plot against stressors or humandisturbance gradients (e.g., Figure 1, see Fore etal. 1996, Karr and Chu 1999). Eight to 12 at-tributes that show a response are selected andscored. Another method of visualizing metrics is toplot the attribute data using box-and-whisker plotsto show the spread of values of an attribute in ref-erence sites compared with the range in the impairedsites (Barbour et al. 1995, Barbour et al. 1992).Attributes that show very little overlap between ref-erence sites and impaired sites are chosen as metricsand scored.

There are various ways to score the metrics. Theexamples given below are for assigning scores witha 1, 3, 5 system for metric data that are showing alinear or regular response to disturbance. Otherscoring ranges can be used. For metrics whosedata indicate a nonlinear response to the gradientof human disturbance, other methods, such as as-signing scores on either side of inflection points,need to be used (Karr and Chu 1999). It is impor-tant that the study sites used to assign scores tometrics include the full range of impairment and thefullest range of biological response values for themetrics.

n The range of the data values for the metric candivided evenly into three parts from the lowestdata value to the highest data value. The lowsector is assigned a score of one, the middle isgiven a three, the top third is given a five. This

23

method assumes the data ranges include a rangeof values from the most impaired to the least im-paired wetlands, and the data values respondevenly to the human disturbances (Karr and Chu1999, Helgen and Gernes in press, Gernes andHelgen 1999).

n The data for a metric are plotted in rank orderfor the sites. Then the sites are divided into thirdsand the associated data values are assigned scoresof 1, 3, or 5 for the low, middle, and top third ofranked sites.

n The metric values for the reference sites are ar-ranged in quartiles. The values for the top threequartiles (top 75th percentile) are assigned ascore of 5. The range of values from the upperrange of the lowest quartile to the lowest data

value is divided in two and assigned a 3 or 1(Barbour et al. 1996). This method assumes thereis an adequate number of reference sites includ-ing some with the least amount of human distur-bance or no disturbance. See Module 6: Devel-oping Metrics and Indexes of Biological Integ-rity. Once the metrics are scored, a matrix ofscores is made in a table for all the sites such asthe table in Appendix J. The scores are addedto the total IBI score and the IBI scores are di-vided to indicate three or more categories ofcondition. Appendix I shows the scoring criteriafor the 10 metrics used by Minnesota for largedepressions. It indicates how many wetlands thatwere designated as reference, agricultural orstormwater-influenced received the scores of 5,3, or 1.

Conclusions andRecommendations

1 Biological assessment of wetlands byinvertebrate metrics should be increasedbecause the invertebrate metrics are sensi-

tive to a broad range of impairments to the physi-cal, chemical, and biological integrity of wetlands.This will require:

n More work on the development ofinvertebrate IBIs for different classes ofwetlands

n More information on the tolerances andsensitivities of invertebrates in wetlands

n Consistent funding dedicated to staff to workon invertebrate biological assessments

2 Biological assessment of wetlands usingmacroinvertebrates will provide scientificallysound data for States, Tribes, and organiza-

tions to gauge the degree of impairment to wet-lands from a mix of stressors. This will enablethem to:

n Develop invertebrate biocriteria for determiningaquatic life use support

n Report on condition of wetlands in 305(b)reports and in 303(d) (TMDL) lists and facilitateprioritization

n Understand the condition of watersheds usingcarefully designed studies

n Compare the results from biological conditionassessments with assessments from other“rapid” physical assessment methods to validatethe latter

n Provide a solid foundation for citizenbiomonitoring programs using protocols derivedfrom those used by States, Tribes, andorganizations

n Provide a sound method to determine theeffectiveness and suitability of permittingdecisions

n Provide a sound method to assess the resultsof restorations and mitigations in wetlandreplacements

24

Appendix J shows an example of the metric scoresfor a set of depressional wetlands in Minnesota.The sites are sorted by the IBI scores, and tenta-tive lines were drawn to indicate which of the sitesmight be considered to be in excellent, moderate,or poor condition. This was done by trisecting therange of IBI scores (10 to 50 total points for 10metrics). Although most of the sites that were con-

sidered to be reference, or least impaired, wetlandshad IBI scores in the excellent range, a few candi-date reference sites scored as moderate. It is ex-pected that some sites chosen to be reference sitesmay not be in the highest condition, but will them-selves have a range of conditions. Other approachesmay be used for determining the criteria lines.

25

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34

Appendix A. Advantages and disadvantages of using invertebrates for biological analysis of wetlands

AdvantagesDisadvantages/Comments

Invertebrates can be expected to respond to a wide array of stresses towetlands, such as pollutants in water and bottom sediments, nutrientenrichment, increased turbidity, loss or simplification of vegetation,siltation, rearing of bait or game fish, input of stormwater or wastewaterrunoff, introductions of exotic species, or alterations of the landscapearound the wetland.

Because it is likely that multiple stressors are present, it may not bepossible to pinpoint the precise cause of a negative change in thecomposition of invertebrates. However, data from major sources ofhuman disturbance, e.g., water and sediment chemistry, the nearbywetland landscape features, sources of hydrologic alteration, and otherdisturbance factors cam be assessed in relation to the invertebrate datato see which factors have the greatest effects.

Life cycles of weeks to months allow integrated responses to bothchronic and episodic pollution, whereas algae recover rapidly from acutesources, and vertebrates and macrophytes may take longer to respond tochronic pollution

Information on short-term, pulse impairments (using algae,zooplankton) or more long-term impairments (using macrophytes,vertebrates) or more landscape-level (using birds, amphibians)impairment may be desired.

Toxicological/laboratory based information is extensive. Invertebrates areused for a large variety of experimental approaches.

Toxicological response data may not be available for all invertebrates;data for some wetlands species are less extensive than for stream species.

There is an extensive history of analysis of aquatic invertebrates inbiological monitoring approaches for streams.

Using invertebrates to assess the condition of wetlands is now underdevelopment in several States and organizations.

Invertebrates are used for testing bioaccumulation of contaminants toanalyze effects of pollutants in food webs.

Tissue contaminant analyses are always costly. This is true for tissueanalysis of any group of organisms: vertebrate, invertebrate, or plant.

Invertebrates are important in food webs of fish, salamanders, birds,waterfowl, and predatory invertebrates.

Aquatic invertebrates tend not to be valued by the public as much asfish, amphibians, turtles, or birds. However, citizens do respond toinvertebrates.

Many invertebrates are ubiquitous in standing water habitats.

Invertebrate composition will differ in different wetland classes, as willother groups of organisms (plants, birds) that might be used to assesswetlands.

Many invertebrates are tightly linked to wetland conditions, completingtheir life cycles within the wetlands. They are exposed to site-specificconditions.

Some invertebrates migrate in from other waterbodies, these taxa are notas tightly linked to the conditions in the specific wetland.

Many invertebrates depend on diverse wetland vegetation, some dependon particular types of vegetation for reproduction.

Loss of invertebrates may be a secondary effect from the loss of wetlandvegetation, e.g., from herbicide treatments. Vegetation loss is animpairment.

Invertebrates have short and long life cycles and they integrate stresses towetlands often within a 1-year time frame.

Many complete their life cycle within a year, they are not as "long-lived"as birds, amphibians or perennial vegetation.

Invertebrates can be easily sampled with standardized methods. Picking invertebrate samples is labor-intensive.

Invertebrates can be sampled once during the year, if the best indexperiod is selected for optimal development of invertebrates.

Invertebrate composition of wetlands often varies within the seasons ofthe yearly cycle. Invertebrates mature at different times. This necessitatesselecting an "index period" for sampling once, or alternatively, samplingmore than once in the season.

Invertebrates can be identified using available taxonomic keys within labsof the entities doing the monitoring. Staff help develop biomonitoringprograms.

Expertise is required to perform identifications of invertebrates. Somemay choose to contract out some or all the identifications. There is acost involved.

High numbers of taxa and individual counts permits the use of statisticalordination techniques that might be more diffucult with just a fewspecies, e.g. with amphibians.

Large numbers of taxa and individual counts make the sampleprocessing more labor intensive than other groups. Adequate trainingand staff time are required. More lab time is needed than for someother groups of organisms.

Citizens can be trained to identify wetlands invertebrates and becomeinterested and involved in wetlands assessment. Citizens are excited tosee the richness of wetland invertebrates.

Citizen monitoring requires training to learn many invertebrates in ashort time, a structured program, and a commitment by volunteers andlocal governments; citizens may tend to underrate high quality wetlands.

35

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38

Appendix E. Issues related to Quality Assurance for invertebratebioassessment work

Any biological monitoring program should have its own written Standard Operating Procedures(SOP’s) for each assemblage that is used, and for all field and laboratory protocols and data analysismethods. Detailed guidance for developing a Quality Assurance Project Plan is available from theU.S. Environmental Protection Agency, Guidance for the Data Quality Objectives Process (EPAQA/G-4, EPA/600/R-96/055, ORD) and EPA’s Content Requirements for Quality Assurance ProjectPlans for Water Division Programs (EPA Region V, Environmental Sciences Division, August 1994).For examples of SOPs see Florida DEP SOP Draft 2000, North Carolina DWQ 1997 SOP.

The following text describes some considerations specific to biological assessment usingmacroinvertebrates.

1. At least 10% of the samples should be checked and verified for the accuracy of taxonomicidentifications by a second taxonomist and/or by comparison to the reference collection. Changes intaxonomy must be tracked and continuously updated, using current taxonomic references and re-gional experts. At least 10% of the picked residuals of samples should be checked by the experi-enced taxonomist to assure all the macroinvertebrates were picked out.

2. Samples should be stored carefully for a defined period of time, if not indefinitely, for later verifi-cations or quality assurance, especially if the assessments are part of a regulatory decision. Theyshould not be disposed of right after the identifications are completed. Taxonomists are revisingcertain groups of invertebrates as new information is gathered. Archived samples can be reanalyzedfor the group in question if necessary.

3. The lab should have defined rules for counting of taxa of each invertebrate group to be identifiedat different levels of taxonomic resolution, for identifying immature specimens, and for when it isacceptable to identify “morphospecies.”

4. Taxonomic coding. In addition to having a lab list of taxa identified with unique codes, thewetland invertebrates are coded in the database using the national Integrated Taxonomic InformationSystem (ITIS) codes (www.itis.usda.gov/). This is a partnership of Federal agencies in the UnitedStates and Canada to improve and standardize biological nomenclature nationwide. The ITIS data-base includes taxonomic information with authority, synonyms, common names, a unique taxonomicserial number (the code), publications, experts, and data quality indicators. There should be a routineprocedure for checking the ITIS database to update and change any codes in the invertebrate data-base.

One problem is that not all wetland invertebrates have received the codes or serial numbers in theITIS system. So the agency must, temporarily, create its own codes for uncoded taxa. Minnesota iscoding taxa not found in the ITIS database with unique negative numbers. These can be easilyflagged and have no possibility of interfering with ITIS codes. ITIS is requesting input from biolo-gists, so states can notify them of uncoded taxa. The ITIS database should be searched periodically

39

to see if uncoded taxa have received codes so the in-house, temporary codes can be replaced withITIS codes.

5. Database and records management. It is important to have a database management staffperson assigned to ongoing work with the biological data and the associated physical and chemicalwetlands data. This is especially true during the time of development of the biological database andthe selection of metrics and indexes. But the work is never static; changes occur and new directionsarise as the biological assessments are made and applied to reports and decisions. Taxonomy isupdated, and new needs arise in linking the biological data to other data sets and in making assess-ments accessible to the public through agency web pages. Data should be backed up routinely.

6. Field data forms. Standardized field forms should be developed to ensure that methods and siteconditions are thoroughly recorded and all procedures are consistently documented. Backup photo-copies should be stored separately from original data forms and field notebooks in case data are lostor destroyed. It is important to reconcile issues of data comparability between old and new methods.In addition to the standard locational, wetland habitat, and physical sampling information, the inverte-brate sampling method, numbers of samples collected, and the depth and locations of sampling shouldbe included on a field sketch. GPS (Global Positioning System) locations of latitude and longitude ofsampling locations should be recorded.

7. Sample labeling and tracking. All sample containers should be clearly labeled with pencil orIndia ink on labels of 100% cotton or alcohol-proof paper placed inside the jar and include thefollowing information: sampling method, sample number, station ID, date, collector, site name andlocation (township, county), and sample jar number (e.g., jar 1 of 2, etc.) if more than one jar is usedfor a single sample. Standard procedures for sample tracking and chain of custody should be estab-lished as part the monitoring program’s quality assurance plan.

8. Laboratory Procedures.a. Coding and recordkeeping. In the laboratory, a unique identification code should be assigned toeach sample. This code should be included in all subsequent records associated with the sample (vialor jar labels, tally sheets, databases, etc.). All laboratory data forms should be standardized andshould include the information described above (see Sample Labeling and Tracking) in addition to thesample identification code and laboratory staff name(s). As with field data forms, backup photo-copies should be made of all laboratory records.

b. Sample sorting. Macroinvertebrates should be sorted from detritus (picked) by trained personnelworking under the supervision of a professional biologist. Picking procedures should be included inStandard Operating Procedures. It is recommended that a 10% random subset of all samples berepicked by different experienced laboratory personnel working under the supervision of a profes-sional biologist to determine sorting completeness. In all cases, initial sample sorting and qualitycontrol repicking should be completed by different individuals.

c. The Standard Operating Procedures should clearly define which groups of macroinvertebratesare to be picked, what if any methods can be used to subsample, and what level of taxonomicresolution should be used for the identifications for each group of invertebrates.

Appendix E. (continued)

40

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gnideeflanoitcnuffo

setubirttaetaler

otdedeen

signitset

eroM

sdnaltew

nisecnabrutsid

namuh

fotneidarg

ot

axatfo

ytivegnoLdnalte

wot

erusopxeregnol

ecneirepxe)atanod

O.g.e(axat

dnaltewdevil-regnoL

tcepxe;)pmirhs

yriafdna

seotiuqsom.g.e(

axatdevil-trohs

yrevnaht

snoitidnocsetis

ottne

mriapmi

cinorhcyb

decudereb

otaxat

devil-gnol

evahlliwsdnalte

wtnena

mrepero

m;setarbetrevemos

nahtdevil

retrohsera

axatdnalte

Wsdnalte

wyfissalc

otdeen;re

wefevahlli

wsdnalte

wlanosaesero

m,setarbetrevnidevil

regnolIBI

rof

seicepscitoxe

evisavnI;erutcurts

ytinummoc

etarbetrevnieht

retlaylevitagen

yamseiceps

citoxeevisavnI

ecneulfnina

muhretaerg

htiwseiceps

evisavnini

esaercnina

tcepxesdnalte

wyna

mni

dnuofeb

tonya

msetarbetrevni

citoxE

knabgge

gnitserlioSyrd

evivrusotlios

nisgge

tisopedtaht

seicepstnediser

nonoita

mrofnisedivorP

sdnaltewdednop

yliraropmet

erom

nilufesu;selcyc

erasgge

gnitserot

syek,sliosgnissecorp

seriuqer,sdnaltewtnena

mrepero

mnilufesu

toN

snoitacifitnedirof

sggeraer

otdeen,etauqedani

ssamoib

roecnadnub

Aserusae

mna

muh,dnalteweht

fonoitcudorp

yradnocesllarevognidnatsrednu

roftseretni

fO

axatllaton

tubyna

mfo

secnadnubaecuder

nacecnabrutsid

gnilpmas

dnasegnahclanosaes

ottcejbus

erom,seirogetac

etubirttaeht

foelbairav

tsoM

ecnabrutsidhti

wesaercni

yamslaudividni

tnarelot;rorre

snoitroporp.svsoita

Rytinu

mmoc

eritneeht

otnoitaler

nignignahc

sipuorg

enoneh

wetacidni

naC

erasnoitroporp;)oitar(

puorgetarbetrevni

rehtonaot

noitalerni

ro)noitroporp(dedne

mmocer

rofdetset

ebot

deen)s

msinagro002,.g.e(

tnuocelp

maslaitrapno

desabsnoitroporP

nehwrorre

otelbarenluv

erasoitar;elp

maseritne

ehtgnitnuoc

htiwderap

mocytilibairav

gniyravera

spuorghtob

htlaehetarbetrevnI

nisdi

monorihcni

nwohs

neebevah,stnani

matnocetacidni

snoitamrofla

Meaivuxe

ylfnogardni

derruccoevah,stne

midesdetani

matnoc

,gnitimil

revewoh,esitrepxe

seriuqer;snoitamrofla

mfolevel

enilesabfo

egdelwonk

seriuqeR

esitrepxessel

seriuqer)sdi

monorihcni

hteetartxe

rognissi

m(snoita

mroflamraelc

ot

41

Appendix G. Examples of invertebrate attributes used as metrics indifferent States for biological analysis of wetlands. Attributes beingtested are starred.

Metrics Maine Minnesota Montana OhioPatuxent

RichnessTotal generarichness*

Total taxa Total taxa Total taxa*Total taxa*

EOT genera* Chironomid genera Chironomidae taxa Chironomid taxa*# Snail genera*

Odonata genera* Leech taxa Leech, sponge and clam taxa Mollusca taxa*# Odonata genera*

Ephemeropteragenera*

Odonata genera POET taxa # Intolerant taxa*

# Ephemeroptera and Trichopteragen.+ presence of Sphaeriidae anddragonflies*

Trichopteragenera*

Snail taxa Mollusca+Crustacea taxa — —

Chironomidgenera*

— Odonata + Trichoptera taxa* — —

Composition — — %Chironomidae* — —

— — %Mollusca+Crustacean taxa* — —

— —%Orthocladiinae to totalChironomidae*

— —

— — %Diptera* — —

— — %Tanytarsini* — —

— — %Trichoptera* — —

— — %Odonata* — —

— —Ratio POET to POET andChironomidae*

— —

— — %Pelycypoda* — —

Tolerance/intolerance

% of total countfor :

ETSD metric %1, 2, 5 dominant taxa % dominant 3 taxa of total count—

EOT* # of intolerant taxa — Physella snail abundance —

Odonata*Tolerants % of totalcount

—% Tanypodinae and Tanytarsini ofChironomidae

—

Ephemeroptera*Erpobdella % of totalcount

— — —

Trichoptera*Dominant 3 % of totalcount

— — —

Gastropoda* — — — —

Isopoda* — — — —

Oligochaeta* — — — —

Amphipoda* — — — —

Trophic structureCorixidae % beetles +bugs

% shredders Corixidae % beetles + bugs*

— — — — % Total indiv as scrapers*

— — — — % total indiv as shredders*

— — — — —

Individual health —Chironomidmalformations*

— — —

Other metrics — — — —% total abundance of 3 mostabundant taxa*

— — — —Ratio Ephemeroptera +Odonata+Trichoptera abundance tochironomids*

— — — — Shannon-Weaver Index*

42

txet

nid

na

Bxi

dn

ep

pA

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ga

/s

etat

Sr

ofn

oita

mr

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atn

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eniaM

atosenniM

anatnoM

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OtnexutaP

ema

NocnarFi

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trahrihCleoJ,negle

HyduJ

kceblefpAydna

RgrobnedyrF

ssuR

yarGeki

MreteP

rognilrapS

dlanoD

ewoL

ycnegA

fotne

mtrapeDenia

MnoitcetorPlatne

mnorivnElortno

CnoitulloP

atosenniM

ycnegA

fo.tpeDanatno

Mytilau

QlatnemnorivnE

PEDadirolF

APEoih

Oefildli

WtnexutaP

SGS

Uretne

Chcraese

R

margorPtin

Ugnirotino

MlacigoloiB

tinUgnirotino

MlacigoloiB

gnirotinoMytilau

Qreta

WnoitceS

tnemssess

AlatnemnorivnEnoitceS

WSD

sserddA

EM,dnaltroP,.d

Rocna

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m.etats@kceblefpar

su.lf.etats.ped@grobnedyrf.lessur

su.ho.etats.ape@yarg.eki

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m.etats.sunaj//:ptthsu.n

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-eirotarobal/ecneics/nrael/tnemno

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-/su.ho.etats.ape.www//:ptth

-aoib_dnaltew/sdnalte

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lmth.ssess

vog.sgsu.crwp.w

ww

43

Appendix I. Invertebrate index of biological integrity for depressionalwetlands in Minnesota.

Ten metrics with scoring criteria and data ranges for large depressions. The numbers of reference sites (ref) andagriculture- (ag) and urban stormwater-influenced (urb) sites scoring in each range are given. n is # of sitesscoring in the ranges. Codes are given for each metric. These codes are used in Appendix J.

Metric Metric data range Ranges Score Ref Ag Urb n >59-79 5 9 5 0 14

>41-59 3 5 8 8 21

1. Total invertebrate taxa Code: TaxaTotal

23-29 taxa

<23-41 1 0 3 6 9

5-6 5 8 6 3 17

3-4 3 6 7 4 17

2. Odonata Code: Odonata

1-7 general

0-2 1 0 3 7 10

14->20 5 11 4 3 18

7-13 3 3 9 5 17

3. Chironomid taxa Code: ChirTaxa

0-21 general

0-6 1 0 3 6 9

6-9 5 6 2 0 8

3-5 3 3 8 6 17

4. Leech taxa Code: LeechTaxa

0-9 taxa

0-2 1 5 6 8 19

7-9 5 6 3 2 11

4-6 3 8 8 5 21

5. Snail taxa Code: SnailTaxa

1-9 taxa

0-3 1 0 5 7 12

7-10 5 8 2 1 11

4-6 3 3 9 9 21

6. ETSD* Code: ETSD

1-10

0-3 1 3 5 4 12

5-7 5 7 1 0 8

3-4 3 4 5 7 16

7. Number of intolerant taxa Code: IntolTaxa

0-7 taxa

0-2 1 3 1 7 20

13-39% 5 6 2 2 10

>39-65% 3 5 5 6 16

8. Tolerant taxa proportion of sample count

Code: Toler%

13-92%

>65% 1 7 5 6 18

0-<1% 5 13 7 9 29

1-5% 3 1 5 3 3

9. Leech erpobdella Code: Erpo%

0-14%

>5% 1 0 4 2 6

<33% 5 9 8 8 25

33-67% 3 4 4 3 11

10. Corixidae proportion of beetles and bugs in activity traps

Code: Corix%

14-87%

>67% 1 1 4 3 8

*ETSD metric is total of number of genera of mayflies (Ephemeroptera), caddisflies (Trichoptera) plus the presence of fingernail clams (Sphaeriidae) and dragonflies.

44

Site

Nam

eSi

teTy

peTa

xaTo

talO

dona

taC

hirT

axa

Leec

hTax

aSn

ailT

axa

ETSD

Met

rIn

tolT

axa

Tole

r%Er

po%

Cor

ix%

IBI S

core

Cond

ition

Fiel

dRe

f5

55

55

55

55

550

Exc

Gla

cial

Ref

55

55

55

53

55

48Ex

cLa

sher

Ref

55

53

55

55

53

46Ex

cM

inno

w N

Ref

53

55

55

35

53

44Ex

cBl

oom

Ref

35

53

55

55

51

42Ex

cO

verb

y N

.Re

f5

55

13

55

55

342

Exc

Shee

ts B

igA

g5

55

33

55

55

142

Exc

Kasm

aRe

f5

53

53

35

13

538

Exc

Lem

an's

Ref

53

55

35

11

55

38Ex

cM

alar

diA

g5

33

55

13

53

538

Exc

Mud

Urb

33

53

33

35

55

38Ex

cPr

airie

Ref

33

51

35

53

55

38Ex

cSh

eets

Sm

all 1

Ag

55

53

33

31

35

36M

odTu

rtle

Urb

31

53

33

35

55

36M

odZa

ger

Ref

35

51

31

35

55

36M

odBa

ttle

Urb

35

11

55

35

51

34M

odDo

nley

Lg.

NRe

f5

33

35

31

35

334

Mod

Lake

21

Ref

35

51

31

33

55

34M

odLe

gion

Urb

35

31

33

15

55

34M

odNe

w L

ondo

nRe

f3

35

13

33

55

334

Mod

Cata

ract

Ref

53

35

31

11

55

32M

odLa

ke P

ark

Ag

53

51

51

13

35

32M

odSa

vage

Urb

33

51

33

33

53

32M

odSe

ter

Ag

55

31

33

13

53

32M

odSe

thre

Ag

35

33

53

13

33

32M

odSk

arpn

ess

EA

g3

33

33

33

15

532

Mod

Tyro

ne B

ean

Ag

33

35

13

33

35

32M

odBu

nker

Ag

15

51

13

33

53

30M

odRo

und

Urb

33

31

33

13

55

30M

odSu

nset

Urb

15

11

51

13

55

28M

odJo

nes

Urb

11

13

13

35

35

26M

odNe

w P

rairi

eA

g3

31

33

51

11

526

Mod

Woo

d La

keUr

b3

11

31

33

51

526

Mod

Bree

nA

g3

31

13

11

51

524

Poor

Davi

sA

g1

11

33

11

55

324

Poor

Gra

ssUr

b3

31

31

33

31

324

Poor

Sigl

erA

g3

53

31

31

11

324

Poor

Trap

pers

Ag

31

33

33

11

51

24Po

orNe

yA

g3

33

11

31

51

122

Poor

Case

yUr

b1

13

11

11

33

318

Poor

Lost

1Ur

b1

13

31

11

33

118

Poor

Wak

efie

ldUr

b1

13

11

11

15

318

Poor

Rose

Gol

fUr

b1

11

11

31

15

116

Poor

Suck

er N

Ag

11

31

11

11

51

16Po

or

Ap

pe

nd

ix J

. S

co

re

s f

or

inv

er

teb

ra

te m

etr

ics

fo

r 4

3 l

ar

ge

de

pr

es

sio

na

lw

etl

an

ds

in M

inn

es

ota

, co

nd

itio

n is

hyp

oth

eti

ca

l.C

odes

in A

ppen

dix

I.

45

Appendix KCase study flow chart for developing invertebrate IBI in Minnesota for large depressional

wetlands (see text, Helgen and Gernes in press, Gernes and Helgen 1999).

l Ecoregion: North Central Hardwood Forest (has abundant wetlands, iscentral to the state, includes Twin Cities metro area)

l Wetland class: large depressionsl Range of disturbances: 15 least impaired , 15 agriculture-affected, 16

urban-affected wetlands

l Attribute selection: 10 attributes tested based on previous work,additional attributes were tested (see Appendix J)

l Sampling strata: sampling to take place in near shore emergent vegeta-tion zone from edge to less than 1 m deep (vegetated zone containsgreatest richness of invertebrates; nearshore area may be more exposedto disturbances from the near wetland landscape)

l Sampling methods: two standardized dip netting procedures plus 10activity traps; all samples taken within approx. 40-50 m distance alongshoreline

l Seasonal index period in June for optimal invertebrate development

l Sampling methods had been pretested in previous projectsl Samples were preserved in field and processed in lab; vegetation from

dip netting procedure was left at the sitel Water and sediment chemistry samples were collected (for total N, total

P, conductivity, chloride, chlorophyll a, metals)

l Entire sample was picked for macroinvertebrates (not for Ostracoda orzooplankton); Neopleia was counted on a grid over lightbox and notpicked; chironomid identifications were contracted out, all othersidentified at MPCA lab

l Most taxa were identified to genus with exceptions: snails to specieswhere possible; fingernail clams at family level

l SOP is written and reference collections made for verifcationl Data were entered into ACCESS database using ITIS coding and MPCA

coding where necessary.

l Sites were analyzed for a human disturbance gradient composed ofestimates of disturbance in 50 m buffer and in near wetland landscape,estimates of hydrologic alteration and rankings of water and sedimentchemistry data as compared to reference condition; each disturbancewas scored and summed to one score for human disturbances

l Attribute data was plotted against scores for human disturbancegradient for all the sites, and against water and sediment chemistry data(see Figure 6 and 7) for all sites

l Attribute data that showed a response to the human disturbancegradient or to the chemistry data was trisected for a 1, 3 5 scoring asmetrics (see Appendix I)

l 10 metric scores were summed to IBI score and IBI scores were plottedagainst the human disturbance gradient and chemistry data (see Figure 1)

l IBI scoring range (10 – 50) was trisected for a hypothetical ranking ofbest, moderate and poor condition (see Appendix J)

step 1:select studysites

step 2:Plan invertebratesampling

step 3:Field Sampling

step 4:LaboratoryProcessing

step 5:Metric Analysis

46

Glossary

condition or health of a place (e.g., a stream, wet-land, or woodlot).

Biological integrity “The ability of an aquaticecosystem to support and maintain a balanced,adaptive community of organisms having a speciescomposition, diversity, and functional organizationcomparable to that of natural habitats within a re-gion” (Karr and Dudley 1981).

Biological monitoring Sampling the biota of aplace (e.g., a stream, a woodlot, or a wetland).

Biota All the plants and animals inhabiting anarea.

Bottletraps A kind of activity trap that is con-structed from a bottle with a funnel opening.

Box-and-whisker plots Plots of data valuesmade for individual attributes with percentile “boxes”around the median value, e.g., 25% and 75% boxes.The “whiskers” are lines extending beyond the per-centile boxes for data value ranges that extend out-side the percentile. These are used to compare theamount of overlap in the data range for an attributebetween reference and impaired sites.

Community All the groups of organisms livingtogether in the same area, usually interacting or de-pending on each other for existence.

Detritivores Organisms that consume decom-posed organic particulate matter.

Dipnet A sturdy, long-handled aquatic net forsampling aquatic habitats, also called sweep net.Mesh sizes range from 500 to 1000 microns.

Disturbance “Any discrete event in time thatdisrupts ecosystems, communities, or populationstructure and changes resources, substrate avail-

Abundance The number or count of all individu-als of one taxon or all taxa in a sample. When ex-pressed per unit area or unit volume, it is calleddensity.

Activity trap (AT) A passive sampler, usuallycontaining a funnel-shaped opening and a containerthat is enclosed, either as a bottle or jar, or with amesh screen. The organisms swim into the funneland are trapped in the container. The size of thefunnel opening determines the size of organisms thatcan swim into the trap.

Aquatic life use support The ability of awaterbody to support the native aquatic life that itis capable of supporting when there is little or nohuman disturbance, or the ability of the waterbodyto support aquatic life as designated for that type ofwater in Water Quality Rules.

Assemblage An association of interacting popu-lations of organisms in a wetland or other habitat.Examples of assemblages used for biological as-sessments include algae, amphibians, birds, fish,macroinvertebrates (insects, crayfish, clams, snails,etc.), and vascular plants

Attribute A measurable component of a biologi-cal system. In the context of biological assessments,attributes include the ecological processes or char-acteristics of an individual or assemblage of speciesthat are expected, but not empirically shown, torespond to a gradient of human influence.

Benthic invertebrates Invertebrates that inhabitthe bottom or benthic area of a waterbody.

Benthos All the organisms that inhabit the bot-tom (benthic) area of a waterbody.

Biological assessment Using biomonitoring dataof samples of living organisms to evaluate the

47

ability or the physical environment” (Picket andWhite 1985). Examples of natural disturbances arefire, drought, and floods. Human-caused distur-bances can be referred to as “human influence” andtend to be more persistent over time, e.g., plowing,clearcutting of forests, conducting urban stormwaterinto wetlands.

Dominance The relative increase in the abundanceof one or more species in relation to the abundanceof other species in samples from a habitat.

Dose-response In toxicology, a graded responseby test organisms to increasing concentrations of atoxicant. In biological assessment, dose responseindicates a graded response (up or down) of anattribute to a gradient of human disturbance.

Ecosystem The community plus its habitat; theconnotation is of an interacting system.

Ecoregion A region defined by similarity of cli-mate, landform, soil, potential natural vegetation,hydrology, and other ecologically relevant variables.

Epiphytic A layer of periphyton located on orattached to the surfaces of stems of macrophytes.See periphyton.

Family A taxonomic category comprising one ormore genera or tribes of common evolutionary ori-gin, and often clearly separated from other families.Family is between the categories of order and tribe(or genus).

Functional feeding groups (FFGs) Groupingsof different invertebrates based upon the mode offood acquisition rather than the category of foodeaten. The groupings relate to the morphologicalstructures, behaviors and life history attributes thatdetermine the mode of feeding by invertebrates.Examples of invertebrate FFGs are shredders, whichchew live plant tissue or plant litter, and scrapers,which scrape periphyton and associated matter fromsubstrates (see Merritt and Cummins 1996a,b).

Funnel trap See Activity trap.

Genus (plural genera) A taxonomic categoryof organisms composed of one or more species thatare related morphologically and evolutionarily, theprincipal category between family and species.

Gradient A regularly increasing or decreasingchange in a factor (e.g., a single chemical) or com-bination of factors (as in the Human disturbancegradient).

Gradient of human influence The relative rank-ing of sample sites within a regional wetland classbased on the estimation of degree of human influ-ence (e.g., pollution and physical alteration of habi-tats).

Habitat The sum of the physical, chemical, andbiological environment occupied by individuals of aparticular species, population, or community.

Herbivore An organism that consumes plant oralgal material.

Human disturbance gradient A gradient orrange of perturbations or impairments (or human-caused disturbances) that alter the physical, chemi-cal, or biological integrity of ecosystems or habi-tats. The effects may persist over periods of time.Examples pertaining to wetlands are alterations inthe natural hydrology, in the near wetland landscape,or in the wetland buffer; or chemical pollution, silt-ation, removal of aquatic vegetation, exotic speciesintroductions, cattle, fish-rearing, conducting of ur-ban stormwater, or agricultural runoff. Comparehuman disturbances with discrete events of naturaldisturbances.

Impairment Adverse changes occurring to anecosystem or habitat. An impaired wetland hassome degree of human influence affecting it.

48

Index of biologic integrity (IBI) An integrativeexpression of the biological condition that is com-posed of multiple metrics. Similar to economic in-dexes used for expressing the condition of theeconomy.

Index period A defined interval of the seasonthat serves as the sampling period for biologicalassessments. For invertebrates the index periodwould be the interval of time when there would beoptimal development of invertebrates and optimalpresence of resident taxa that developed in thewaterbody.

Intolerant taxa Taxa that tend to decrease in wet-lands or other habitats that have higher levels ofhuman disturbances, such as chemical pollutionor siltation.

ITIS The national Integrated Taxonomic Infor-mation System (ITIS) coding system for organismsin the United States and Canada. The databaseincludes information on each organism with author-ity, synonyms, common names, and a unique taxo-nomic serial number (the ITIS code) for all taxo-nomic levels. It lists publications, experts, and dataquality indicators. ITIS accepts input from investi-gators regarding uncoded taxa. The database isupdate periodically. Web site: www.itis.usda.gov/

Macroinvertebrates Animals without backbonesthat are caught with a 500-800 micron mesh net.Macroinvertebrates do not include zooplankton orostracods, which are generally smaller than 200microns in size.

Macrophytes The visible aquatic plants that areemergent, floating, or submersed under water. Theymay be attached to the bottom or not. Distinguishedfrom algae, most of which are microscopic.

Metric An attribute with empirical change in thevalue along a gradient of human influence. See At-tribute. Metrics are scored individually, and eachscore composes the total score for the IBI.

Morphology The structure and form of an or-ganism, both external and internal. Taxonomic iden-tifications are mostly derived from the examinationof external morphologies, with exceptions.

Morphospecies A taxon that has distinct mor-phologies from other similar taxa and is identifiedas a distinct taxon based solely on the morphologi-cal differences (see Oliver and Beattie 1996). Thebiologist must determine that the differences are notfrom developmental stages or change in featureswithin the same taxon before the taxon can becounted in the overall taxa richness.

Multihabitat method A sampling method inwhich the sampling effort attempts to sample mostof the habitats with the zone of study. The effort isvariously distributed among the habitats; in somemethods it is distributed in proportion to the repre-sentation of the habitat in the zone of study, in othermethods it is distributed by giving greater effort tohabitats more likely to have the desired organisms.

Multivariate analysis Mathematical analysisthat examines numerous variables simultaneously.Data from communities of organisms are multivari-ate because there are several species with differingabundances responding to numerous environmen-tal factors. Various statistical methods are used,e.g., ordination or discriminant analysis, to analyzeseveral variables at once.

Omnivores Are organisms that consume bothplant and animal material.

Periphyton The layer of algae that coats sub-strates in aquatic systems such as plant stems, rocks,logs, and benthic muds. This layer of algae coatingis often also colonized by bacteria, protozoans, androtifers and other microorganisms.

Population A group of individual organisms ofthe same species living in the same area.

49

Predators Organisms that consume animals.

Proportion The mathematical relation of onepart to the whole, expressed as magnitude or de-gree, e.g., percent. An example of proportion at-tributes are the percent of tolerant individuals of thewhole sample count or the proportion of the abun-dance of the top two dominant taxa to the sampleabundance.

QA or QAPP The written plan for quality assur-ance, or the quality assurance program plan, thatprovides written detail for quality assurance plansfor quality assurance checks for all aspects of fieldand laboratory procedures.

Ratio The numerical quotient of two variables orquantities. An example of an attribute that is a ratiois the ratio of scrapers/collector-filterers (see pro-portion).

Reference site A minimally impaired site that isrepresentative of the expected ecological conditionsand integrity of other sites of the same type andregion.

Relative abundance Is the abundance of onegroup or taxon of organisms in relation to the totalabundance of the sample.

Replicate A term usually reserved for the rep-etition of an experiment to obtain information forestimating experimental error. It is sometimes usedinformally to describe repeated consistent samplestaken at a site with the same method, in the samestrata and habitat, and on the same date.

Sample A representative part of a larger unitused to study the properties of the whole.

SOP Acronym for Standard Operating Proce-dure. This is the detailed, written description of allthe methods to be used for field and laboratory pro-cedures.

Species A taxonomic category below genus, thefundamental biological unit, a population of organ-isms that share a gene pool and are able to repro-duce successfully and produce young that are ableto reproduce.

Stress (or stressor) Any environmental factorthat impedes normal growth, reproduction, or sur-vivorship of organisms, or causes adverse changesin populations of organisms or in ecosystems.

Sweep net Another term for Dipnet.

Taxon (singular, taxa plural) A distinct taxo-nomic group of any level (e.g., family, genus or spe-cies); includes all subordinate groups. Taxon is anygroup of organisms that is distinct enough from othergroups to be treated as a separate unit.

Taxonomic system The hierarchy of classifica-tion of organisms.

Taxonomist A biologist who specializes in theidentification of organisms.

Taxonomy The practice of describing, naming,and classifying organisms.

Tolerance The biological ability of different spe-cies or populations to survive successfully within acertain range of environmental conditions.

Tolerant taxa Taxa that tend to increase in wet-lands or other habitats that have higher levels ofhuman disturbances, such as chemical pollution or siltation.

Trisecting The division into three parts of arange of data for scoring a metric.

Trophic Feeding, thus pertaining to energy trans-fers.

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Wetland(s) (1) Those areas that are inundated orsaturated by surface or groundwater at a frequencyand duration sufficient to support, and that undernormal circumstances do support, a prevalence ofvegetation typically adapted for life in saturated soilconditions [EPA, 40 C.F.R.§ 230.3 (t) / USACE,33 C.F.R. § 328.3 (b)]. (2) Wetlands are landstransitional between terrestrial and aquatic systemswhere the water table is usually at or near the sur-face or the land is covered by shallow water. Forthe purposes of this classification, wetlands musthave one or more of the following three attributes:(a) at least periodically, the land supports predomi-nantly hydrophytes, (b) the substrate is predomi-nantly undrained hydric soil, and (c) the substrate isnonsoil and is saturated with water or covered by

shallow water at some time during the growing sea-son of each year (Cowardin et al. 1979). (3) Theterm “wetland,” except when such term is part ofthe term “converted wetland,” means land that (a)has a predominance of hydric soils, (b) is inundatedor saturated by surface or ground water at a fre-quency and duration sufficient to support a preva-lence of hydrophytic vegetation typically adaptedfor life in saturated soil conditions, and (c) undernormal circumstances does support a prevalenceof such vegetation. For purposes of this Act andany other Act, this term shall not include lands inAlaska identified as having a high potential for agri-cultural development which have a predominanceof permafrost soils [Food Security Act, 16 U.S.C.801(a)(16)].