United States Environmental

Protection Agency

Office of Water

Washington, DC 20460

EPA-822-R-02-020

March 2002

Methods for evaluating wetland condition

#10 Using Vegetation To Assess

Environmental Conditions in Wetlands
United States Environmental

Protection Agency

Office of Water

Washington, DC 20460

EPA-822-R-02-020

March 2002

Methods for evaluating wetland condition

#10 Using Vegetation To Assess

Environmental Conditions in Wetlands

Major Contributors

Department of Biology, Kenyon College

Siobhan Fennessy

Minnesota Pollution Control Agency

Mark Gernes

Ohio Environmental Protection Agency

John Mack

Penn State Cooperative Wetlands Center

Denice Heller Wardrop

Prepared jointly by:

The U.S. Environmental Protection Agency

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

and

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

Protection Agency

Office of Water

Washington, DC 20460

EPA-822-R-02-020

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 enrichment and is not intended to be prescriptive guidance or firm advice.

Mention of trade names, products or services does not convey, and should not be interpreted as

conveying official EPA approval, endorsement, or recommendation.

Appropriate Citation

U.S. EPA. 2002. Methods for Evaluating Wetland Condition: Using Vegetation To Assess

Environmental Conditions in Wetlands. Office of Water, U.S. Environmental Protection Agency,

Washington, DC. EPA-822-R-02-020.

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

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

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

ii
iii

Contents

Foreword ............................................................................................................. vi

List of “Methods for Evaluating Wetland

Condition” Modules..........................................................................................vii

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

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

Background ..........................................................................................................1

Plants as Indicators..........................................................................................2

Advantages of Using Vegetation in Biological Assessment .................2

Considerations for Sampling Design ...........................................................3

Field Methods ......................................................................................................5

Data Analysis..................................................................................................... 12

Limitations of Current Knowledge—Research Needs .......................... 17

References ........................................................................................................ 19

Appendix A .......................................................................................................... 23

Appendix B .......................................................................................................... 27

Appendix C .......................................................................................................... 32

Appendix D .......................................................................................................... 36

List of Tables

Table 1: Some potential metrics for wetland plants

including how they could be scored, how they

would respond to human disturbance, and

geographic areas of the U.S. where they have

been tested................................................................................... 16
iv

Table C-1: Scoring criteria for vegetation-based metrics

in the Minnesota IVI. ................................................................... 33

List of Figures

Figure 1: Three-tiered flow diagram used to rank wetlands

along a gradient of human disturbance ................................ 5

Figure 2: Example of how transects might be established

in a wetland .................................................................................... 8

Figure 3: Example of point-quarter sampling at two

randomly selected forest locations. ................................. 10

Figure 4: Relationship between FQAI scores and biomass

production in eight central Ohio

emergent wetlands.................................................................... 15

Figure A-1: Proportion of plant species that were missing

dominance or density data at three wetlands

resampled in 1999 using releve method ............................. 24

Figure A-2: Number of species found at three wetlands

sampled using transect-quadrat, transect-belt,

and releve methods ................................................................... 25

Figure A-3: Floristic Quality Assessment Index (FQAI) score

at three wetlands sampled using transect-quadrat,

transect-belt, and releve methods ...................................... 25

Figure A-4: Interim Vegetation Indices of Biological

Integrity (IBI) scores for 45 wetlands in the

Eastern Cornbelt Plains Ecoregion of Ohio ................... 26

Figure B-1: Vegetation Index of Biological Integrity score by

hydrogeomorphic classification for N=65

forested and emergent wetlands in the State of

Ohio. ............................................................................................... 28

Figure B-2: Box and whisker plots of emergent and forested

reference (least-impacted) wetlands ................................. 29
v

Figure B-3: Relative cover of tolerant herb and shrub

stratum species for reference (least impacted)

and nonreference (all other sites) of

forested and emergent wetlands (N=65) for

four ecological regions in the State of Ohio .................. 29

Figure B-4: FQAI Scores for 45 wetlands in the Eastern

Corn Belt Plains Ecoregion of Ohio................................... 30

Figure B-5: Floristic Quality Assessment Index (FQAI) score by

hydrogeomorphic classification for N=65

forested and emergent wetlands in Ohio .......................... 30

Figure D-1: Sediment Tolerance Groups of Wetland Plants

in Slope Wetlands of Central Pennsylvania

Wetlands ...................................................................................... 38
vi

Foreword

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

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

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

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

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

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

wetland waterbodies.

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

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

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

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

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

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

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

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

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

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

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

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

too many members to list individually:

n Biological Assessment of Wetlands Workgroup

n New England Biological Assessment of Wetlands Workgroup

n Wetlands Nutrient Criteria Workgroup

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

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

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

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

List of “Methods for Evaluating Wetland

Condition” Modules

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

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

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

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

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

Wetland Bioassessment Program

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

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

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

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

Integrity for Wetlands

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

in Wetlands

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

Wetlands

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

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

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

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

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

Enrichment

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

Risk Assessment

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

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

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

Module # Module Title
1

SUMMARY

Vegetation has been shown to be a sensitivemeasure of anthropogenic impacts to wetland

ecosystems. As such it can serve as a means to

evaluate best management practices, assess restoration and mitigation projects, prioritize wetlandrelated resource management decisions, and establish aquatic life use standards for wetlands. The

basic steps necessary for developing a vegetationbased wetland biological assessment and monitoring program are relatively straightforward, but their

simplicity belies their effectiveness. By building upon

such monitoring tools, we will be able to more fully

incorporate wetlands into water quality assessment

programs.

Purpose

The purpose of this module is to introduce the scientific basis for using wetland vegetation to

assess the biological integrity of wetlands, review

methods for sampling vegetation communities, discuss the techniques by which biological metrics are

developed, and present examples of metrics and

indices that have been used successfully. We discuss here how the composition of the plant community and the predictable changes that result from

human activities can act as sensitive indicators of

the biological integrity of wetland ecosystems. This

information has many potential applications including conducting an inventory, monitoring the status

and trends of wetland ecosystems, performing an

impact assessment, and setting goals for and/or

monitoring mitigation and restoration projects.

Background

Vegetation is perhaps the most conspicuousfeature of wetland ecosystems and has been

used extensively as an indicator of the presence of

wetlands themselves, their boundaries, and as a basis

for many wetland classification schemes. Wetland

plants are commonly defined as those “growing in

water or on a substrate that is at least periodically

deficient in oxygen as a result of excessive water

content” (Cowardin et al. 1979). This term includes

both herbaceous (vascular and nonvascular) and

woody species. Wetland plants may be floating,

floating-leaved, submerged, or emergent and may

complete their life cycle in still or flowing water, or

on inundated or noninundated hydric soils (Cronk

and Fennessy 2001).

One key to understanding why plants are considered “one of the best indicators of the factors that

shape wetlands within their landscape” (Bedford

1996), is to understand the contributions they make

to wetland ecosystems more generally. These contributions include (Wiegleb 1988, Mitsch and

Gosselink 2000):

 Wetland vegetation is at the base of the food

chain and, as such, is a primary pathway for

energy flow in the system. Through the photosynthetic process, plants link the inorganic environment with the biotic one. Primary production (or plant biomass production) in wetlands varies, but some herbaceous wetlands

have extremely high levels of productivity, rivaling those of tropical rain forests.

 Wetland vegetation provides critical habitat

structure for other taxonomic groups, such as

epiphytic bacteria, phytoplankton, and some

species of algae, periphyton, macroinvertebrates, amphibians, and fish. The composition

and diversity of the plant community influences

diversity in these other taxonomic groups.

 Strong links exist between vegetation and wetland water chemistry. Plants remove nutrients

through uptake and accumulation in tissues, but

they also act as a nutrient pump by moving compounds from the sediment and into the water

column. The ability of vegetation to improve

water quality through the uptake of nutrients,

metals, and other contaminants is well docu-
2

mented (e.g., Gersberg et al. 1986, Reddy et

al. 1989, Peverly et al. 1995, Rai et al. 1995,

Tanner et al. 1995).

 Vegetation influences the hydrology and sediment regime through processes such as sediment and shoreline stabilization, or by modifying currents and helping to desynchronize flood

peaks.

 Plants as Indicators

Plants are excellent indicators of wetland condition for many reasons including their relatively

high levels of species richness, rapid growth rates,

and direct response to environmental change. Many

human-related alterations to the environment that

act to degrade wetland ecosystems cause shifts in

plant community composition that can be quantified easily. Individual species show differential tolerance to a wide array of stressors. Thus as environmental conditions vary, community composition

shifts in response. Plant communities have been

shown to change in response to hydrologic alterations (e.g., Gosselink and Turner 1978, van der

Valk 1981, Spence 1982, Squires and van der Valk

1992, Wilcox 1995), nutrient enrichment (e.g., Pip

1984, Kadlec and Bevis 1990, Templer et al. 1998,

Craft and Richardson 1998), sediment loading and

turbidity (e.g., van der Valk 1981, 1986, Sager et

al. 1998, Wardrop and Brooks 1998), and metals

and other pollutants. These patterns can be interpreted and used to diagnose wetland impacts. Because they represent a diverse assemblage of species with different adaptations, ecological tolerances,

and life history strategies, the composition of the

plant community can reflect (often with great sensitivity) the biological integrity of the wetland.

A wetland's hydrologic regime can be thought of

as a master variable with respect to the structure

(e.g., species richness) and function (e.g., primary

production) of the plant community, and much research has been done on the links between hydrology and plant community dynamics (Mitsch and

Gosselink 2000). Factors related to the hydrologic regime that affect wetland plants include water depth (Spence 1982, Grace and Wetzel 1982,

1998), water chemistry (Ewel 1984, Pip 1984, Rey

Benayas et al. 1990, Rey Benayas and Scheiner

1993) and flow rates (Westlake 1967, Lugo et al.

1988, Nilsson 1987, Carr et al. 1997). As hydrology changes, other environmental conditions change

as well. Thus, hydrology influences community composition and productivity by influencing the availability of nutrients (Neill 1990), soil characteristics

(Barko and Smart 1978, 1983), and the deposition of sediments (Barko and Smart 1979).

Water quality also has a strong bearing on community structure (Grootjans et al. 1998, Rey

Benayas et al. 1990, Rey Benayas and Scheiner

1993). Fens, for example, tend to be high in calcium and magnesium bicarbonates with circumneutral pH (Wilcox et al. 1986). Bogs, on the

other hand, depend solely on precipitation for their

water supply and tend to be nutrient poor and of

low pH. Plants adapted to bog conditions often

exhibit a number of mechanisms that serve to

conserve or help acquire nutrients, including

evergreen leaves, carnivory, or nitrogen fixation.

 Advantages of Using

Vegetation in

Biological

Assessment

Wetland plants, both vascular and nonvascular,are commonplace, and they exist in sufficient

richness to provide clear and robust signals of human disturbance. They have been used effectively

to distinguish environmental stressors including hydrologic alterations, excessive siltation, nutrient enrichment, and other types of human disturbance (van

der Valk 1981, Moore and Keddy 1989,
3

Galatowitsch 1993, Wilcox 1995, Kantrud and

Newton 1996, Stromberg et al. 1996, Philippi et

al. 1998). Vegetation is useful to evaluate wetland

integrity because:

 Plants are found in all wetlands.

 Plants are primarily immobile (save for a few

free-floating species). Because they reflect

the temporal, spatial, chemical, physical, and

biological dynamics of a system, they can

indicate any long-term, chronic stress it undergoes.

 Plant taxonomy is well known, and excellent

field guides are available for all regions.

Experienced field biologists can identify genus or

species relatively easily because:

 A great diversity of species exists with differing

responses to human disturbance.

 Ecological tolerances are known for many species, and thus changes in community composition might be used to diagnose the stressor responsible. For example, plant responses to

changing hydrology are reasonably predictable

(see above).

 Sampling techniques are well developed and

extensively documented.

 Similar sampling techniques can be used in both

freshwater and saltwater systems.

 Functionally or structurally based vegetation

guilds have been proposed for some regions.

Despite the many advantages to developing biological assessment techniques based on vegetation,

limitations should be recognized:

 A lag may occur in the response time to

stressors, particularly in long-lived species.

When this is the case the species present may

not be indicative of the stressors present and/

or the overall biological integrity.

 Plant identification to species level can be

laborious, or restricted to narrow periods

during the field season. Several assemblages,

such as the grasses and sedges, may be

particularly difficult to identify to species. Concern is sometimes expressed about the skill

that good field botany requires. However, with

a modest amount of training, most species

in a given class of wetland can be easily

learned, or the art of keying out species can be

learned.

 Sampling techniques for some assemblages,

such as the submerged species, can be difficult; thus it is possible to miss or erroneously

sample a group of species that could provide

strong signals on the condition of a site.

 Vegetation sampling is generally limited to the

growing season.

 Research or literature on plant species

responses to specific stressors is not well

developed. Adamus and Gonyaw (2000) estimate that only 17% of all wetland plant species

have been the subject of studies that detail their

response to specific stressors, although the

general tolerance of many species to human

change to the environment is more well

known.

 Considerations For

Sampling Design

A sound framework for developing biological indicators based on wetland vegetation should

include several key components.

Objectives of the Project

The vegetation community changes seasonally,

and these patterns can differ among wetland types.

Standardized field methods must be tested and re-
4

fined to ensure that a consistent sampling effort is

made at each site. Consideration must be given to

the type of data that will be collected (species inventory, cover, stem counts, etc.), the sampling window (i.e., the seasonal period) that will be used to

characterize the vegetation, the sampling technique

that will be employed, the number of samples that

will be collected, and retention of voucher specimens. The same considerations apply to any methods that will be performed subsequent to field surveys either in the laboratory or the office. Projects

may be designed to develop or test metrics that are

sensitive to specific stressors such as hydrologic

alteration or nutrient enrichment. In this case wetlands that vary in their degree of impact should be

included. This approach allows for hypothesis testing, i.e., whether the conditions at a site differ significantly from those found in a population of reference wetlands (see Module 11 for further examples).

 Wetland Classification

Because the composition of wetland plant communities varies by wetland type (class), it is necessary to group “like-kind” wetlands into classes that

are structurally and functionally similar. In this way

natural variability is reduced, making detection of

human-induced variability easier. This leads to more

meaningful comparisons between wetlands and creates a more sensitive tool for decisionmakers. There

are several well-established wetland classification

schemes, including the hydrogeomorphic (HGM)

approach (Brinson 1993), which has proven to be

useful in classifying wetlands for biological assessment (e.g., Fennessy et al. 1998b), as has the classification system employed in the National Wetland

Inventory (Cowardin et al. 1979). Ecoregions have

also been used to classify wetlands for vegetation

analysis (Omernik 1987). (See Module 7 for further discussion on wetland classification.)

 Define the Reference Condition

A crucial component of a biological assessment

program is the careful selection of least-impacted

reference sites. Reference sites are wetlands of the

same class that define the best possible condition

for that class. Reference sites serve as the standard

against which other sites are judged (Yoder and

Rankin 1993, Karr and Chu 1999).

 Select Wetlands that Represent

the Full Range of Human

Disturbance

In addition to reference sites, other sites should

be selected to represent the full range of human disturbance for each wetland class. This makes it possible to evaluate the response of the wetland plant

community to increasing “doses” of human activity

(i.e., construct a dose-response curve) (Karr and

Chu 1999). There is currently no standard method

to quantify human disturbance at a site, so many

projects have relied on surrogate measures such as

percent impervious surface (Richter and Azous

1994) or percent agricultural land use in the watershed. If assessing plant community response to nutrient enrichment is the objective, potential metrics

can be tested against individual environmental measures such as soil phosphorus content or turbidity

of the water column. Another approach is development of a qualitative index of human disturbance

based on dominant land use surrounding the wetland, buffer characteristics, and the degree of hydrologic alteration to the site (Figure 1) (Fennessy

et al. 1998a, Lopez and Fennessy in press). The

criteria for judging whether a site is least or most

impacted are, in part, subjective, but there are several standardized, semiquantitative checklists for

evaluating human disturbance at different wetlands.

These include the Ohio Rapid Assessment Method

(Ohio EPA 2000) and a “Stressor Checklist” developed for wetlands in Pennsylvania (Wardrop and

Brooks, personal communication). Both techniques

provide a means to standardize the evaluation of

human impact.
5

 Establish Standard Sampling

Methods

Standardized field methods must be adopted,

tested, and refined to ensure that an equal and consistent sampling effort is made at each site (discussed

in detail below).

 Choice of Metrics

Karr and Chu (1999) have said that “a bewildering variety of biological attributes can be measured,

but only a few provide useful signals about the impact of human activities.” Not all attributes will show

a consistent response to human disturbance; those

that do have been termed “metrics.” Certain attributes of wetland plant communities have been

shown to vary consistently and systematically with

human disturbance. Detailed examples will be discussed below.

Field Methods

Vegetation sampling techniques vary greatly depending on the goals of the project and the

wetlands included in the study. In general, sampling methods should be designed for wetland type,

project scope, season, funding, and other constraining factors. Major concerns include ease of use,

cost, reproducibility of results, and quality assurance/quality control protocols. The sampling technique should adequately represent site heterogeneFigure 1: Three-tiered flow diagram used to rank wetlands along a

gradient of human disturbance.

Tier 1 indicates the land cover that surrounds a site, Tier 2 indicates the type and extent of vegetated buffer that

encompasses a wetland, and Tier 3 indicates either little direct hydrologic modification (denoted “A”) or human

modified hydrology (“B”) in a wetland. Numerical ranks are displayed in squares at the bottom of the flow

diagram (Fennessy et al. 1998b, Lopez and Fennessy, in press).

.
6

ity. Data requirements, level of sampling effort, and

types of ancillary data collected all hinge on the goals

of the study and the anticipated uses of the results

(biocriteria development, setting goals for mitigation wetlands, monitoring wetland condition, etc).

In addition, the development of any biological assessment tools will likely be the effort of a team of

people with various areas of expertise and experience. We recommend that interdisciplinary crews

conduct biological assessment during both the planning and data collection phases if at all possible.

 Organizing Data Collection

There are several essential steps in developing

vegetation-based bioassessment protocols. These

include (1) decisions about the frequency and intensity of sampling, (2) site reconnaissance, and (3)

decisions about the sampling technique(s) that will

be used in the field.

 Timing and Intensity of Sampling

Sampling season

The establishment of a standard sampling window

will help ensure that representative results are obtained at each site and that valid comparisons can

be made between different wetlands. Wetland

plants pose a challenge in terms of their identification and because different species reach maturity

or flower at different times during the growing season. Thus, some species may be present but cannot be identified because of a lack of flowing parts

(a critical feature used in identification). Members

of Asteraceae (e.g., Aster sp. [asters]), which tend

to bloom late in the growing season, are a classic

example. Temporal variability in the plant community is a function of geographic location and the class

of wetland ecosystem being studied. Any decision

will involve trade-offs because no one sampling

period will be able to capture all species. Setting

an index period that corresponds to the peak maturity of the community as a whole is generally considered most appropriate, particularly if the goal is

to assess a wetland in a single visit. Interestingly,

three States that have established index periods have

arrived at nearly the same period. These include

Minnesota (June 15–August 15), Ohio (June 15–

August 30), and Pennsylvania (June 15–August 15).

Forested wetlands appear to be less sensitive in

terms of when the vegetation is surveyed. For example, in the southeastern States, the changes that

occur in the plant community over the growing

season are relatively minor (see Module 16: Vegetation-Based Indicators of Wetland Nutrient

Enrichment). In this case, it may be desirable to

coordinate vegetation sampling periods with the sampling period for other assemblages.

Number of survey plots

In any study, the number of plots to sample is an

important consideration. The appropriate number

can be determined by plotting species numbers (or

the cover of a given species) as a function of the

number of quadrats sampled and then identifying

where species richness “levels off.” Daubenmire

(1959) systematically investigated how sampling effort affects the number of species recorded at a site

and found a point of diminishing returns was reached

when 40 quadrats had been sampled. In the initial

10 quadrats some species were underrepresented

whereas others were overrepresented. At the point

where 30 to 40 quadrats had been sampled, the

data had leveled off, and increasing the sample size

to 50 quadrats did not give any additional information. Another recommendation is that a total of 1%

of the total wetland area be sampled (Krebs 1999).

One method to accomplish this, which several States

have adopted, is use of releve techniques. Releve

plots can adequately represent the vegetation of a

site with a single large plot (e.g., 100 m2

). Regardless of the method selected, tradeoffs regarding sampling effort must be made in light of the time and

resources available.
7

Site Reconnaissance

Before in-depth field sampling begins, general information should be collected on the landscape setting of the site, its hydrologic features, and other

general characteristics. Many valuable observations can be made from the edges of the wetland

that will describe obvious stressors such as hydrologic alterations (berms, culverts), or the extent of

vegetation cover and the characteristics of any buffer

areas. Buffer areas are typically defined as the

100 m of land surrounding the wetland boundary

(Magee et al. 1993). Land use and/or the dominant vegetation communities within the buffer should

be recorded. Depending on the goals of the project

it may be desirable to collect samples to quantify

characteristics of the buffer.

Inspecting the topography and landscape features

that surround the site can provide much information

on the context of a site. There are also many characteristics that can be recorded about the wetland

itself, including its shape and approximate size, the

general distribution of wetland vegetation and open

water, interspersion of plant communities, the type

of buffer, hydrological features including surface

water inflows or outflows, and human-made water

control structures.

Choice of Vegetation Field

Sampling Methods

Below are examples of vegetation sampling protocols that can integrate the above considerations

of plot locations, shape, size, and number, and that

have been used successfully in wetland

bioassessment projects.

Standard releve (Braun-Blanquet) for

emergent vegetation

The releve approach has been adapted from

Mueller-Dombois and Ellenberg (1974). Prior to

sampling, each wetland is evaluated briefly for overall community structure. A 100 m2

 plot is established in a typical or “representative” location within

the emergent plant community. Plants in the plot are

inventoried and the cover class (abundance) of each

plant taxon is estimated using cover classes

(Almendinger 1987). Similar sampling effort can

also be made in the floating or submerged community zones when they are present and wading is

possible.

This sampling technique is easy to apply and practical, taking a field-trained botanist with an assistant

typically 2 hours or less to complete per site. An

advantage (or disadvantage, depending on one's

view) is fact that sampling is restricted to the dominant vegetation community represented at the site.

One negative side is that it is not very data intensive

for spatially heterogeneous or complex communities. In some cases it may be desirable to collect

samples across all communities present. This can

be done using multiple releve plots, although this is

more difficult and time-consuming.

The required equipment includes two 50-m measuring tapes, four corner markers or posts (8-foot

rebar works well), a clipboard with data forms, and

plant collecting materials. Data gathered in the releve

plot can be augmented with a more complete list of

taxa occurring at the entire site, for example, as

collected by a walk-through (care should be taken

in this case as sampling effort can vary depending

on the investigator). A modification of the releve

method has been adopted in Ohio (see

Appendix A).

Transect sampling

There are numerous variations on the use of

transects for sampling vegetation in herbaceous,

shrub-scrub, or wooded wetlands. The location of

transects within a wetland can be determined in several ways. One approach is to locate them either

randomly (using a random numbers table for example) or systematically (e.g., located at fixed in-
8

tervals) perpendicular to a baseline. Baselines are

generally established just outside the wetland parallel to its longest axis (Figure 2). Transect locations can also be determined using a stratified random design in which different portions of the site

are targeted for sampling to ensure that the habitat

complexity of the wetland is represented, but within

those zones transects are located randomly.

Transects may be a single line, or a belted transect

can be used in which data are recorded in a zone

extending on either side of the line (often to a distance of 1 m). Often a transect line is used in combination with quadrats placed at random or regular

intervals along the line.

Data can be collected along the transects using

several techniques:

 All vegetation in each quadrat is sampled (see

section on quadrats below).

 The line-intercept method is frequently used.

In this technique, the transect line is thought of

as a vertical plane that is perpendicular to the

ground. All plant canopies projecting through

the plane (over the line) are counted. The total

decimal fraction of the line covered by each

species and multiplied by 100 is equal to its

percent cover (Barbour et al. 1987). Total

cover can be more than 100% using this

technique.

Quadrat methods

Many possible sampling schemes are available for

sampling using quadrats, and there are variations

appropriate for all vegetation types. Often, communities or stands are selected subjectively, but then

sampled using randomly located quadrats (stratified random technique). Common variations include

(Barbour et al. 1987):

Figure 2: Example of how transects might be established in a wetland.

In this case a baseline is established along the long axis of the site,

and transects can be run both parallel and perpendicular to this axis.
9

 Locating quadrats in a completely random

fashion

 Locating quadrats in a restricted or stratified

random manner (stratified random sampling).

This is often based on the plant community types

that are present. Placing quadrats randomly

within the various community types helps ensure that habitat heterogeneity will be adequately

represented.

Quadrat size, shape, and number: Many methodological studies have been conducted to determine the precision and accuracy of different quadrat types (Krebs 1999). For surveying herbaceous

plant communities, there are two primary issues regarding shape: edge effects and habitat heterogeneity. Many studies have found that long, narrow

rectangles work best because this shape tends to

cross more patches (i.e., cover more habitat heterogeneity) and therefore tends to pick up more

species. Square and round quadrats have been

reported to be less accurate because less heterogeneity is encompassed. However, sampling accuracy tends to decrease as quadrat shape lengthens

because of edge effects. The longer the perimeter

of a quadrat, the greater the necessity for any field

personnel to make subjective decisions about

whether a plant near the edge is “in” or not. This

kind of decisionmaking leads to possible counting

errors, and results can vary greatly between individuals. In light of this concern, round quadrats are

considered by many to be the most accurate because this shape has the smallest perimeter:area ratio (Krebs 1999).

The appropriate quadrat size also varies with the

goals of data collection. If the goal is to collect

cover data, then quadrats may be small. If data on

plant numbers are required, then the decision about

quadrat size is a critical one. Although there are no

fixed rules, several recommendations can be derived from the literature (analysis from Krebs 1999):

 Use a quadrat that is at least twice as large as

the average canopy spread of the largest species (Greig-Smith 1964).

 Use a quadrat size that will include only one or

two species (Daubenmire 1968).

 Use a size that allows the most common

species to occur in more than 80% of all

quadrat.

Sampling Considerations Specific

to Forested Wetlands

For herbaceous plants, quadrats of 1 m2

 or 10 m

× 10 m have most commonly been used. For

woody plants, plots of at least 10 m × 10 m are

used. The forestry literature recommends 400-

1,000 m2

 as a minimum area to adequately characterize eastern forest communities (Peet et al. 1998).

A number of sampling techniques work well for trees

and shrubs in forested systems, many of which are

plotless methods. These are generally called distance methods because they are based on distances

between:

 Random individuals (trees or shrubs) and their

nearest neighbors

 Random points and the nearest organism(s)

(Krebs 1999)

Point-quarter method

The point-quarter method is a distance technique

commonly used in forestry studies. A series of random points is selected, generally along a transect

line, with the limitation that points should be far

enough apart such that the same individual is not

measured twice at two successive points. The area

around each random point is divided into four 90o

quadrants, and the distance to the nearest tree is

measured in each (Figure 3). In this way four pointto-tree distances are measured at each random point

(Krebs 1999). These data can be used to calcu-
10

into four equal quadrants. The primary criticism of

this method is that because only four trees are measured at each point, the number of individuals

sampled is often too low to truly represent large

populations.

Bitterlich variable plot method

This is a forestry technique that can be used to

calculate basal area only. The advantage of this

method is that it is extremely fast and has been used

widely in forestry studies. Sampling is done using a

sighting device (either a stick with a crosspiece at

one end, or a prism). The stick is held horizontally

with the crosspiece at the far end and the viewer

slowly turns in a complete circle. Each tree whose

trunk is seen in the line of sight is tallied and identified by species if its trunk size exceeds the width of

the crosspiece; all other tress are ignored. Total

basal area (m2 Ha–1) for each species is then calculated as the number of trees of that species divided

by 2. Plot size is variable in this method because

the plot radius is not fixed.

late an unbiased estimate of population density as

follows:

N

p

 = 4(4n - 1)/pi 3 (r2

ij)

where N

p

 = the estimate of population density, n =

number of random points, pi = 3.14159, and (r2

ij)

= distance from random point i to the nearest organism in quadrant j (j = 1, 2, 3, 4; i = 1,...,n).

The variance of the population density can be calculated as follows:

Variance (Np

) = Np

2

/(4n – 2)

Standard error is expressed as:

Standard error of N

p

 = [(variance of Np)/4n]1/2

Each tree is identified by species, and diameter at

breast height (DBH) is measured. This method is

easy and efficient when site conditions allow one to

quickly divide the area around the random points

Figure 3: Example of point-quarter sampling at two randomly selected

forest locations. In each case, the shortest point-to-tree distance is

measured in each of the four quadrants.
11

Collection of Ancillary

Data to Characterize

Environmental Conditions

Some physical and chemical data on the site should

be collected in order to interpret and understand

vegetation data. The need for information on the

hydrology and soils of the system, for example, is a

primary reason why many wetland assessment teams

are made up of individuals from several different

disciplines. Some States are developing methods

for assessing wetland functions on the basis of wetland HGM (Smith et al. 1995). Data on composition of wetland plant communities can be used to

assist HGM determinations of wetland function, and

conversely, HGM data can be invaluable in

bioassessment to organize sampling and interpret

the influence of hydrogromorphic factors on wetland plant communities. Some examples of hydrological indicators that might be included are:

 Presence of any surface water inflows and

outflows

 Other indicators of wetland hydrology such as

water marks, stained leaves, sediment deposits, or soil saturation in top 30 cm (see wetland

delineation manual, ACOE 1987)

 Collection of water samples for analysis. If your

system is seasonally flooded and water chemistry data are required, this must be taken into

account when developing the sampling design.

It may be necessary to sample water chemistry

at different times than the vegetation. Parameters to analyze might include pH, dissolved

oxygen, conductivity, total phosphorus, soluble

reactive phosphorus, nitrogen (nitrate, ammonia, and total Kjehldahl N), total suspended

solids, turbidity, metals (in some instances), and

total organic carbon. Percent salinity is an additional variable to measure in saline wetlands.

Soils can be easily characterized using a standard

soil probe. Some examples of soil data that might

be gathered are:

 Thickness of the organic horizon

 Soil texture

 Organic matter content

 Munsell soil color

 Presence of mottles, their size and color, and

presence of oxidized root channels

Depending on the study goals, it may also be necessary to collect soil samples for laboratory analysis. Standard analysis generally include pH, percent organic matter, and nutrients or perhaps metals. Total phosphorus is often a good indicator of

human disturbance and/or the deposition of heavy

sediment loads.

Vouchers and QA/QC

The rigor of QA/QC requirements should be appropriate to the goals of the study and the intended

use of the results. Requirements that are appropriate for a “pilot” study whose purpose is to identify

promising metrics may not be as rigorous as those

of a full-blown regional study whose purpose is to

provide statistical estimates with known confidence

limits regarding the numbers (or proportion) of wetlands that are degraded. Depending on project goals

and budget, consider including the following:

 Collect all species that are unknown and return

them to the lab for identification. We recommend pressing plants in the field to ensure the

quality of the samples and allow their preservation as voucher specimens (e.g., in herbaria) if

that becomes desirable.

 Because of their difficult taxonomy, we recommend collecting all but the most common sedges

(e.g., Carex sp.), grasses, and rushes.

 Confirm unknown species with local university

herbaria or other botanical experts.

 Generally, err on the side of conservatism;

overcollect rather than undercollect.
12

 One approach developed in Minnesota is to

establish a column on the field data sheet to

indicate the level of certainty on the identification of a given species. This information can

help in later data interpretation.

 If project personnel are changing, then more

confirmation and vouchering will be necessary.

 Calibrate the personnel in terms of judging percent cover and species identification.

 Collect a specimen of each species if possible.

These could then be donated to a local herbarium. This is especially important during the

reference phase when metrics are being developed and validated.

 Collect species whose identity is uncertain in

order to confirm the species using standard

floras. In addition, have another person confirm the species. That way there is a more defensible record.

 Use rare-plant protocols when necessary (e.g.,

if there are fewer than 20 individuals of a given

species, photograph them only).

One example of a quality assurance field protocol

comes from Ohio EPA (Fennessy et al. 1998). In

a study designed to test a vegetation-based indicator in forested riparian wetlands, a QA/QC protocol was developed to evaluate the accuracy of plant

identification. In this technique, a random sample

of 10% or 10 specimens (whichever was greater)

of the total number of species identified at the site

was collected for subsequent confirmation by a botanical expert. Prior to the vegetation survey, a random numbers table was used to generate 10, 2-

digit (01, 02, etc.) nonrepeating numbers within the

range of 1 to 30 (30 was the maximum value because 30 plots were sampled at each site). These

numbers identified the quadrats in which quality

control samples were to be collected.

Following identification of all species in the quadrat selected in step 1, a second two-digit random

number within the range of the number of species

found in that quadrat was generated and used to

select a voucher sample. For example, if there were

10 species found in the quadrat, a number between

1 and 10 was generated. If that number was 3,

then a voucher specimen of the third species encountered in that quadrat was collected. This was

done even if the species selected was very common and easy to identify, such as Typha latifolia.

Accuracy (defined as the closeness of a measured

value to the true value) was assessed by comparing

the confirmed species identifications to the identification given by the field personnel such that:

% accuracy = (number of species correctly

identified in field/total number

confirmed)*100

Data Analysis

Vegetation-Based Metrics

 Vegetation metrics can be organized into three

groups based on the general level of biological organization they reflect: community-based metrics,

metrics based on plant functional groups, and species-specific metrics. All should be developed on

the basis of field data collection and interpretation

of those data. In general, there are many more

potential metrics (i.e., plant community attributes)

than those that show strong biological signal. In all

cases, there should be an ecological understanding

as to why the metric works or does not (i.e., does it

make ecological sense). Unfortunately, not all metrics

are likely to work across all wetland types; therefore metrics must be tested when they are used in a

new wetland class (Keddy et al. 1993).
13

A useful prelude to data analysis may include consulting existing information on the autecology of

wetland plant species. One source of information

on species-specific tolerances is the EPA's National

Database of Wetland Plant Sensitivities (Adamus

and Gonyaw 2000). This database documents published, species-specific assessments of plant tolerances, sensitivity, and general response to stressors,

particularly nutrient enrichment and hydrologic alteration. Responses are qualified by season and

plant life stage whenever such information is available. Limited information is also presented on the

tolerance of plant species to increased salinity, sedimentation, and other stressors, but no attempt was

made to comprehensively compile literature on those

topics. The database summarizes information from

more than 200 sources on 1,082 plant species

(about 16% of all U.S. wetland plant species) and

450 nonwetland species that occur in the United

States. Little or no information has been published

for the remaining 84% of wetland plant species.

Community Metrics

Extensive ecological literature describes the

changes in plant community composition in response

to human disturbance. For instance, there are predictable changes in plant species diversity, as well

as in the types of species that remain (Tilman 1999).

Guilds or functional groups, defined as groups of

species sharing certain traits predisposing them to

perform similar functions or respond in similar ways

to human disturbance, can be created to indicate

environmental change in wetlands (Hobbs 1997).

Well-known guilds in wetlands include carnivorous

plants, submerged aquatic species, or species tolerant of high sediment loads (Keddy et al. 1993,

Wardrop and Brooks 1998). An increase in nonnative invasive species is also considered to indicate ecosystem change that may be due, for example, to nutrient enrichment (Ehrenfeld 1983,

Thompson et al. 1987). These types of biological

signals can provide reliable information on the condition of the wetland.

Human activities that alter natural hydrologic regimes (changes to water quantity, water level fluctuations, or water quality) have well-documented

impacts on plant communities (Ehrenfeld 1983, Vitt

and Bayley 1984, Ehrenfeld and Schneider 1991,

Wilcox 1995). Plant zonation patterns may shift,

species tolerant of human disturbance may invade,

or woody species may invade or die back as a result of drainage or flooding. Some of the responses

by the plant community that occur as a result of

hydrologic change include the following (from

Wilcox 1995, Ehrenfeld 2000):

 Decrease in species richness

 Possible decline of mutualistic interactions, such

as with pollinators or mycorrhizal fungi

 Absence of species that are sensitive to human

disturbance

 Increase in the numbers and dominance of invasive and exotic species, such as Typha

angustifolia and Lythrum salicaria

 Vegetation that is dominated by one species

(monospecific) or of one structural type

 Presence of either very dense or sparse stands

of vegetation (e.g., in response to water levels

that were stabilized at either lower or higher

than normal levels).

Floristic quality assessment index

The Floristic Quality Assessment Index (FQAI)

is a vegetative community index based on the

method developed for the Chicago region by

Wilhelm and Ladd (1988). It has been tailored

specifically to Ohio flora (Andreas and Lichvar

1995) and the flora of Michigan (Herman et al.

1996). Other States and regions are currently developing FQAI lists. The FQAI was originally designed to assess the degree of “naturalness” of an

area based on the presence of ecologically conservative species. It is thought to reflect the degree of

human disturbance to an area by accounting for the

presence of cosmopolitan, native species, as well
14

as nonnative taxa. This index is capable of measuring ecosystem condition because it assigns a repeatable and quantitative value to vegetation community composition. Use of the index requires that

local flora be available with coefficients of conservatism assigned to each species. These lists are

finalized for some areas (e.g., Ohio, Michigan) and

under development in many others (e.g., Florida).

To calculate the FQAI, a species list is compiled

for the site. Then each species on the list is assigned a rating (tolerance values) of between 0 and

10 (Andreas and Lichvar 1995). A rating of 0 is

given to opportunistic native invaders and nonnative species. Tolerance values of 1–10 are assigned

as follows:

 Values of 1–3: applied to taxa that are widespread and do not indicate a particular community

 Values of 4–6: applied to species that are typical of a successional phase of some native community

 Values of 7–8: applied to taxa that are typical

of stable or “near climax” conditions

 Values of 9–10: applied to taxa that exhibit high

degrees of fidelity to a narrow set of ecological

parameters.

The total species list from each wetland is used to

calculate the FQAI value for each site as follows:

I = R/N (N1/2)

where I = the FQAI score, R = the sum of the

tolerance values (C of C) for all species at the site,

and N = the total number of native species.

The FQAI has been shown to respond to human

disturbance (see Appendix B) as well as wetland

functions such as biomass production (Figure 4) and

decomposition.

Other community-based metrics that we have

found useful, at least in some wetland classes are

shown in Table 1. This list provides a starting point

for investigating characteristics of the plant community and their response to human impacts.

Plant functional groups or guilds (also see

Appendix D)

Guilds can be defined as a group of species that

share similar traits or responses to human disturbance, although they may not be closely related

species. There are many ways in which wetland

species can be grouped on the basis of their role in

ecosystem function or their response to environmental variables (Hobbs 1997, 1992). The creation of functional groups is a means to investigate

environmental change at the scale of the ecosystem

or landscape, and is based on the fact that set groups

of species will respond in similar ways to similar

types of stressors (e.g., hydrologic change, high

sediment loads). The creation of functional groups

then, is often based on nonphylogenetic groupings

(Gitay and Noble 1997). Some suggestions defining functional groups include:

 Perennials

 Annuals

 Sediment tolerant species

 Species tolerant of hydrological alterations

 Species tolerant of elevated nutrient levels

 Use of the tolerance values (“coefficients of

conservatism”) provided in schemes like the

FQAI to establish “very tolerant” or “very intolerant” groups

 C3 versus C4 species

 Submersed aquatic species

 Species that form persistent standing litter (see

Appendix C).

Responses of the wetland plant community to landscape change (including fragmentation of habitat)
15

have been observed in certain guilds such as submersed and emergent plant species. For example,

Lopez et al. (in press) found that wetland patch size

(defined as the size of the habitat fragment that contained the study wetland) and the distance to neighboring wetlands were positively correlated with the

diversity of some plant guilds (e.g., submersed herbaceous plant species). The FQAI has also been

shown to respond to fragmentation (Figure 4).

Chapin (1991) specifically suggests using plant

guilds, such as plants that live in nutrient-poor soil

conditions, because particular traits might be strong

indicators of a stressful environment (e.g., a slow

growth rate, low photosynthetic rate, low capacity

for nutrient uptake, or specific hormone levels).

Chapin (1991) also reports that guilds made up of

longer-lived species may be a good indicator of

chronic ecosystem stress, whereas an “annual-plant

guild” may be a good indicator of acute ecosystem

stress. That is, relatively longer-lived wetland plants

may have longer response times to environmental

stressors than shorter-lived plants and may be better indicators of historic landscape change.

Species-specific attributes

Some species-specific traits also can be indicative of wetland integrity, for example:

 Dominance of an early successional species

(e.g., Salix exigua)

 Metrics based on the health of individual plants

(e.g., Miller et al. 1993).

Attributes that do not seem to work

Some attributes do not give consistent, ecologically meaningful indications of wetland integrity.

Although they may be worth investigating on a

case-by-case basis, our experience has shown the

following:

Figure 4: Relationship between FQAI scores and biomass production

(g.m2) in eight central Ohio emergent wetlands (Fennessy et al. 1998).
16

Table 1: Some potential metrics for wetland plants including how

they could be scored, how they would respond to human disturbance,

and geographic areas of the U.S. where they have been tested
17

 Forest canopy species are often limited in the

signal they can provide because of their relatively long response time.

 Some doubt prevails as to the utility of metrics

that are based on the health of individual plants.

For example, chlorosis (yellowing or turning

brown) in plant leaves may indicate stress to

that individual; however, this condition may also

result from many naturally occurring phenomena such as aging. Quantifying individual health

has worked well in other taxonomic assemblages

(e.g., fish and the presence of tumors), but no

clear dose-response pattern has been seen with

regard to plants.

 Although there has been some interest in the

potential of the wetland plant indicator status

classification system developed for conducting

delineations (U.S. CoE 1997) to interpret vegetation patterns, there is concern about using

the indicator status to evaluate integrity. The

wetland indicator status describes the probability that a given plant species will occur in wetlands. The ratings are found in the “National

List of Plant Species that Occur in Wetlands”

(Reed 1997, 1988); within it is a list of the indicator status of all wetland plants known to occur in U.S. wetlands. Currently about 7,000

species are on the list, each of which has been

assigned an indicator status for the regions in

which it occurs. Each species is assigned one

of four indicator status categories based on the

probability that the species will be found in a

wetland. These are obligate wetland (OBL),

facultative wetland (FACW), facultative (FAC),

and facultative upland (FACU). Obligate species occur in wetlands more than 99% of the

time, whereas facultative species are just as

likely to be found in uplands (50% of the time)

as in wetlands (50% of the time). Species not

found on the list are considered to be obligate

upland (UPL) species. The indicator status was

not designed to provide information on the condition of a wetland. Many obligate (OBL) wetland species, for instance, are invasive and/or

nonnative species (Typha sp., for example), and

so do not provide an indication of “integrity” in

this way.

 In general, care should be taken because metrics

that are useful in one class of wetland (e.g.,

emergent) are not necessarily transferable to

other classes.

Limitations of

Current Knowledge—

Research Needs

Wetland vegetation promises to be one of the

best indicators for use in assessing the biological integrity of wetlands. The examples given in

Appendixes A–D provide illustrations of how these

techniques are currently being tested and used in

different State programs. However, research on

the relationship between environmental conditions

and the response of different species could provide

greater sensitivity and precision in detecting impairment. For instance, methods are lacking for characterizing the role of the landscape surrounding a

wetland. Questions such as the effect of surrounding uplands on determining the site's condition are

difficult to answer. Land use in a wetland's watershed largely determines the quantity and quality of

water that enters the site, and this has obvious repercussions for the composition of biotic communities. In addition, human disturbance can be manifest at many scales; how can we assess these and

begin to be truly diagnostic about the stressors that

lead to a loss of biological integrity? Sampling techniques are sometimes lacking as well. For instance,

small wetlands are sometimes undervalued, particularly when they occur in a mosaic of wetland patches

interspersed with another habitat type. Useful techniques to evaluate wetlands in this landscape context are needed.
18

There are also limits on the use of methods that

have already been developed (e.g., the FQAI) because we lack the information needed to apply them

to wider geographic areas. There is a need to create plant response guilds and/or FQAI tolerance

lists for more regions of the country. In fact, despite the vast literature on wetland vegetation, the

majority of wetland plant species have not been studied at all, so there is no literature to consult on the

autecology of many species. One remedy is to initiate studies on the dose-response relationship, both

in the field and in the lab or greenhouse, between

different plant species and different types of stressors. This would do much to provide information

on species for which little is known.
19

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CA: Benjamin-Cummings.

Lopez RD, Davis CB, Fennessy MS. In press.

Ecological relationships between fragmented

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Limnol Oceanogr 33:894-909.
21

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23

Appendix A

A Tale of Two Methods: Developing, Evaluating, and

Changing Sampling Methods

John J. Mack and M. Siobhan Fennessy

The Ohio Environmental Protection Agency began evaluating vegetation sampling methods in 1996.

Major concerns in selecting a sampling method were

ease of use, cost, reproducibility of results, and obtaining as complete a list plant species at a wetland

as possible. This last concern related to Ohio’s use

of a Floristic Quality Assessment Index (FQAI)

(Wilhelm 199X ; Andreas and Ladd 1995) which

requires a relatively complete flora of a site.

Ohio EPA sampled disturbed and undisturbed

wetlands in western and central Ohio in 1996 and

1997. Initially, Ohio EPA adopted a fixed transect

method with 1m2

 and 10m2 circular nested quadrats spaced evenly along the transect. A minimum

of 30 quadrats were sampled along 3 transects

(30m2 area sampled herbaceous vegetation and

300m2 woody vegetation), with at least one transect

oriented perpendicular to the other two (hereafter

transect-quadrat method). In addition, plants located outside the quadrats but within a 5m wide

“belt” along the transect were identified but no density or dominance information was recorded for

these plants (hereafter transect-belt method). Within

the quadrats, percent cover, stem counts and DBH

(woody only) were recorded for each species.

As Ohio EPA IBI development advanced, it become apparent that many successful attributes were

associated with measures of dominance, including

percent cover and density (stems/ha). However,

using the existing method, 30%–60% of the plants

observed had only presence/absence data associated with them (Figure A-1). Other issues included

(1) the size of the area sampled to characterize

forested communities was too small. The forestry

literature recommends 400-1,000 m2 as minimum

area to adequately characterize eastern forest communities (Peet et al. 1998); (2) a perceived over

sampling of species at the wetland edges.

In 1999, Ohio EPA reevaluated its sampling

method and adopted a flexible, multipurpose releve

method used by the North Carolina Vegetation Survey (hereafter releve method) as described in Peet

et al. (1997, 1998). This method can be used to

sample such diverse communities as grass and forb

dominated savannahs, dense shrub thickets, forest,

and sparsely vegetated rock outcrops and has been

used at over 3000 sites for over 10 years as part of

the North Carolina Vegetation Survey. It is appropriate for most types of vegetation, flexible in intensity and time commitment, compatible with other

data types from other methods, and provides information on species composition across spatial scales.

It also addresses the problem that processes affecting vegetation composition differ as spatial scales

increase or decrease and that vegetation typically

exhibits strong autocorrelation (Peet et al. 1998).

The method employs a set of 10, 10 x10m sampling units in a 20 x 50 m layout. Within the site to

be surveyed, a 20 x 50 m grid is located such that

the long axis of the plot is oriented to minimize the

environmental heterogeneity within the plot. In effect then, the method proposed by Peet et al. incorporates the use of releves found in the BraunBlanquet methodology in as much as the length,

width, orientation, and location of the modules are

qualitatively selected by the investigator based on

site characteristics; however, within the modules,
24

standard quantitative floristic and forestry information is recorded, e.g. density, basal area, cover, and

so on.

Ohio EPA resampled several wetlands with the

new method that had previously been sampled with

transect-quadrat method. These wetlands included

a highly degraded emergent marsh, a sparsely vegetated vernal pool, and a floristically rich forested

wetland. The releve method solved many of the

problems listed above. For instance, all plants have

cover or density data associated with them. However, at all three sites, the original transect-belt

method had the highest species list (highest species

richness) (Figure A-2); this difference was most

apparent in the degraded to moderately degraded

sites (Mishne and Gahanna). At the floristically rich

wetland (Leafy Oak), the difference between the

releve method and the transect-belt method was

11 species, or 14% of the maximum value (Figure

A-2). At the highly degraded emergent marsh

(Mishne), substantially greater numbers of species

(80% more) were identified using the transect-quadrat and transect-belt methods than the releve

method. These tended to be upland or facultative

species growing in a band around the edge of the

wetland. Inclusion of these plants raised the Floristic Quality Assessment Index scores for the Mishne

site (Figure A-3). Species richness was 48% higher

at the Gahana Woods site using the quadrat + belt

method as it was using the releve method. But, at

the floristically rich Leafy Oak site, the releve

method performed nearly as well as the transectbelt method with regards to FQAI scores (Figure

A-3). Using the quadrat only data from the transectquadrat methods yielded very similar scores to the

releve method.

A comparison of vegetation IBI scores of data

from the transect-quadrat and releve methods

yielded very similar results: the relative position of

the wetlands sampled using both methods did not

significantly change (Figure A-4).

gahanna leafy oak mishne

1.0

0.8

0.6

0.4

0.2

0.0

proportion of specieswithout cov er data

Figure A-1: Proportion of plant species that were missing dominance

or density data at three wetlands resampled in 1999 using releve

method as described in Peet et al. (1998).
25

quadrat only

quadrat+belt

releve 

gahanna

(f orested)

leaf y oak

(f orested)

mishne

(emergent)

0

6

12

18

24

30

FQAI score

Figure A-3: Floristic Quality Assessment Index (FQAI) score at three

wetlands sampled using transect-quadrat, transect-belt, and releve

methods (see text for description of FQAI score and box text for

description of methods).

quadrat only

quadrat+belt

relev e 

gahanna

(f orested)

leaf y oak

(f orested)

mishne

(emergent)

0

10

20

30

40

50

60

70

80

number of species

Figure A-2: Number of species found at three wetlands sampled using

transect-quadrat, transect-belt, and releve methods (see text) .
26

The releve method has several advantages over

transect-quadrat methods: (1) it allows for an easy

qualitative stratified sampling of the dominant plant

communities; (2) it provides a more complete forest inventory; (3) the quantitative data is

intercomparable with other standard vegetation sampling methods; (4) it is relatively quick (1-3 sites

per day with an experienced team); it is easily

adaptable to unique situations and shapes of communities (the module system allows you to build up

or down in plot size); (5) it provides the data for

phytosociological analysis; and (6) it ensures all

plants identified have dominance data associated

with them.

The releve does not allow mapping of the vegetation communities like a fixed transect method would

and the releves are often difficult to lay out in dense

shrub communities. In addition, the flora of the

wetland is somewhat less complete using the releve

method, although this could be compensated for by

doing a qualitative survey outside of the plot (something Ohio EPA does as a qualitative check on the

appropriateness of the plot location). Cover data

would again be lacking however.

In sum, both the transect-quadrat and releve

methods yielded equivalent results when the data

resulting from these methods was used to calculate

a vegetation IBI. Thus, the conclusion may be that

whatever method is selected, that it be capable of

sampling with sufficient completeness such that human disturbances are detectable.

Figure A-4: Interim Vegetation Indices of Biological Integrity (IBI)

scores for 45 wetlands in the Eastern Cornbelt Plains Ecoregion

of Ohio. Comparison of IBI scores for three wetlands

sampled using transect-quadrat and releve method.

Data from Mack and Micacchion (in prep).

gahanna 97 

gahanna 99 

leafy oak 97

leafy oak 99

mishne 97 

mishne 99 

other 

10 20 30 40 50 60 70 80

10

20

30

40

50

Vegetation IBI

high disturbace

low integrity

low disturbance

high integrity

high disturbance

low integrity
27

Appendix B

Development of Vegetation IBIs:

The Ohio Experience and Lessons Learned

John J. Mack, Ohio Environmental Protection Agency

The State of Ohio has well-developed biological

criteria (or biocriteria) for streams, e.g., the Invertebrate Community Index (macroinvertebrates), Index of Biological Integrity (fish), and Modified Index of Well Being (fish) (Yoder and Rankin 1995).

These indices are codified in Ohio Administrative

Code Chapter 3745-1. Until recently however,

surface waters of the State that are jurisdictional

wetlands were only generically protected under

Ohio's water quality standards. On May 1, 1998,

the State of Ohio adopted wetland water quality

standards and a wetland antidegradation rule (OAC

Rules 3745-1-50 to -54). These wetland quality

standards developed narrative criteria for wetlands

and created the “wetland designated use.”

Ohio began development of sampling methodologies and began sampling reference wetlands for

biocriteria development in 1996. To date, Ohio

has sampled nearly 60 wetlands located primarily

in the Eastern Cornbelt Plains Ecoregion located in

central and western Ohio. This work has been

funded since 1996 by several different U.S. EPA

Region 5 Wetland Program Development Grants

including CD995927, CD995761, CD985277,

CD985276, CD985875, and CD975350.

The first two years of data laid the groundwork

for standardizing sampling methodologies, classifying wetlands, identifying potential attributes, and

developing metrics using vascular plants, amphibians, and macroinvertebrates. The wetlands studied have included depressional emergent, forested,

and scrub-shrub wetlands, floodplain wetlands, fens,

kettle lakes, and seep wetlands. The wetlands being studied span the range of condition from highly

disturbed to relatively undisturbed, i.e., “reference”

conditions.

Based on the results to date (see Fennessy et al.

1998a, b; Mack et al. 2000, Mack in prep.), Ohio’s

research supports the use of vascular plants as taxa

group for wetland biocriteria (Figure B-1).

Successful attributes for emergent wetlands include

floristic quality assessment index (FQAI) score (see

below), ratio of shrub species to total species, numbers of Carex spp., numbers of dicot spp., numbers of plants with facultative wet (FACW) or obligate (OBL) wetland indicator status, heterogeneity (Simpson's Index), standing biomass, and relative cover of tolerant and intolerant plant species,

where “tolerance” is determined by the plant's “coefficient of conservatism,” which is derived from a

State or regional FQAI system. In addition, for

wetlands dominated by woody species, relative density of shrubs and small trees and tree size class

equitability have also proved to be useful attributes.

Semiquantitative disturbance/integrity scales

Ohio EPA has had good success in developing a

semiquantitative disturbance/biological integrity

scale called the Ohio Rapid Assessment Method

for Wetlands v. 5.0 (Mack 2001, Figure B-2). Until

such time as more quantitative variables like percent impervious surface are found, this type of tool

is a good candidate for the problematic x-axis in
28

wetland biocriteria development. See also Carlisle

et al. (1999), where a similar system was used to

rank levels of disturbance.

Classification

Classification is definitely an iterative process. Investigators should definitely consider a

hydrogeomorphic (HGM) classification scheme if

one has been developed for their region of interest,

at least as a starting point. For example, shrub dominated wetlands began to emerge as a separate class

only after several years of sampling. However, the

experience in Ohio suggests that grosser classes

based on dominant vegetation (emergent, scrubshrub, forested, etc.) may work also. A goal of a

cost-effective biocriteria program is to have the fewest classes that provide the most cost-effective feedcoastal 

flats 

fringing 

impndmnt 

isol deprs

ripar deprs

ripar hdw tr 

slope isol 

slope ripar 

0 302010 40 1009080706050

100

90

80

70

60

50

40

30

20

10

0

low integrity

high disturbance

VIBI

high integrity

low disturbance

Figure B-1: Vegetation Index of Biological Integrity score by

hydrogeomorphic classification for N=65 forested and emergent

wetlands in the State of Ohio.

“Coastal”=Lake Erie coastal marsh, “flats”=isolated flats wetlands, “fringing”=wetlands fringing natural lake

other than Lake Erie, “impoundment”=wetlands located in or formed by human impoundment, “isol

depr”=isolated depressional wetland, “ripar depr”=depressional wetland located in a riparian context, “ripar

hdwtr”=wetland located next to or near 1 or 2 order stream, “slope isol”=slope wetland in isolated landscape

position, “slope ripar”=slope wetland in riparian landscape position.

back. With vegetation, data from Ohio are suggesting somewhat diverse wetland types may be

“clumpable,” since even though their floras are different at the species level, the quality/responsiveness of their unique floras to human disturbance is

equivalent (Figure B-2). This is also a concern in

States with high degrees of wetland loss where two

few wetlands of a particular HGM class remain to

analyze as a separate class.

Floristic quality assessment indexes

Ohio EPA has found that Floristic Quality Assessment Index (FQAI) scores and subscores are very

successful attributes and metrics for detecting disturbance in wetlands (Figures B-4 and B-5) (see

Andreas and Lichvar 1995, Herman et al. 1996,

Wilhelm and Masters 1995).
29

fringing

isol depr

ripar depr

ripar hdwtr

slope isol

45

55

65

75

85

95

HGM Code VIBI

Boxplots of VIBI by HGM Code

(means are indicated by solid circles)

Figure B-3: Box and whisker plots of emergent and forested

reference (least-impacted) wetlands (N=29).

See Figures B-5 and B-6 for HGM code descriptions.

E 

F

SS

0 302010 5040 7060 80 90 100

100

90

80

70

60

50

40

30

20

10

0

3rd=67.3

2nd=44.9

1st=22.4

ORAM v 5.0 score

VIBI score

category 1

1 to 2 gray zone

2 to 3 gray zone

category 2 category 3

cat 2

modified

cat 2

disturbance

low quality high

disturbance

high quality low

category 1

category 2

category 3

Actual biologically derived Category

Category using biologically calibrated ORAM score

35 45 65

Figure B-2: Relative cover of tolerant herb and shrub stratum species

for reference (least impacted) and nonreference (all other sites) of

forested and emergent wetlands (N=65) for four ecological regions

in the State of Ohio.

E=emergent, F=forested, SS=scrub-shrub.
30

coastal 

flats 

fringing 

impdmnt

isol depr

ripar depr

ripar hdw tr

slope isol

slope ripar

2010 90807060504030

40

30

20

10

0

ORAM v5

FQAI

Figure B-5: FQAI score by hydrogeomorphic classification for N=65

forested and emergent wetlands in Ohio.

“coastal”=Lake Erie coastal marsh, “flats”=isolated flats wetlands, “fringing”=wetlands fringing natural lake

other than Lake Erie, “impoundment”=wetlands located in or formed by human impoundment, “isol

depr”=isolated depressional wetland, “ripar depr”=depressional wetland located in a riparian context, “ripar

hdwtr”=wetland located next to or hear 1 or 2 order stream, “slope isol”=slope wetland in isolated landscape

position, “slope ripar”=slope wetland in riparian landscape position.

non-ECBP

non-EOLP

non-WAP 

ref-ECBP

ref-EOLP

ref-HELP

ref-MIDP

10 20 30 5040 90807060

1.0

0.9

0.8

0.7

0.6

0.5

0.4

0.3

0.2

0.1

0.0

ORAM v5

%tolerant

Figure B-4: Relative cover of tolerant herb and shrub stratum

species for reference (least impacted) and nonreference

(all other sites) of forested and emergent wetlands (N=65) for four

ecological regions in the State of Ohio.

ECBP=Eastern Corn Belt Plains, EOLP=Erie-Ontario Lake Plains, HELP=Huron-Erie Lake Plains,

MIDP=Michigan-Indiana Drift Plains, WAP=Western Allegheny Plateau.
31

Field and lab methods

After experimenting with both transect/quadrat and

releve-style plot methods, Ohio has adopted a plot

based method which allows for a qualitative stratification of wetland by dominant vegetation communities. This method appears flexible and adaptable to unique site conditions, provides dominance

data for all species in all strata, provides data

intercomparable with other common methods, is

relatively easy to learn, and is relatively fast and

cost-effective (up to 2 to 3 plots can be completed

in a day).

Whatever sampling method is adopted, it is essential that dominance and density information

(cover, basal area of trees, stems per unit area, relative cover, relative density, importance values, etc.)

be collected. Many of the most successful attributes

Ohio has found in developing a vegetation IBI are

based on cover data of the herb and shrub layers

and density data of the shrub and tree layers.

Definitely consider using cover classes in general

and a class scheme that works on a doubling principle to aid in consistent inter-investigator usage.

Then use the midpoints of the class for your analysis. This seemed to help with consistent usage and

smoothing out the roughness in cover data.
32

Appendix C

Minnesota Index of Vegetative Integrity (IVI)

Mark Gernes

Minnesota intends to use its biological assessment

results to report on and track wetland conditions

within local watersheds. This assessment tool will

be useful for evaluating best management practices

for wetlands and wetland restorations, and prioritizing wetland-related resource management decisions. Minnesota also intends to develop numeric

wetland biological criteria.

Minnesota has proposed 10 wetland vegetation

metrics that have been combined into a multimetric

“Index of Vegetative Integrity” (IVI). Two metrics

focus on taxa richness, four are based on life-form

guilds, two are sensitive and tolerant taxa metrics,

and two are community-structure metrics. This

multimetric index has been used effectively in Minnesota to assess wetland condition. A 100 m2

 releve

plot method was used to sample the vegetation. All

sampling was conducted in the wetland emergent

vegetation zone. Additional metrics may be developed as this work progresses. Reference sites were

chosen as least-impacted wetlands; stormwater runoff or agricultural activities disturbed the other sites.

Scoring criteria for the metrics described below are

shown in Table C-1.

1. Vascular genera metric

Rationale: The vascular genera metric expresses

the richness of native genera occurring in the wetland (i.e., the number of native vascular plant genera in a 100 m2

 releve plot). Many genera have

some species that are native and others that are

nonnative. In these instances the genus is not excluded from the count. When all taxa within the

genus are not native to Minnesota the genus is not

counted. An example might be the genus

Echinochloa, where two common wetland species occur. Echinochloa muricata is native

whereas E. crusgalli is not. When plants in this

genus occurred in the sampling plot but could not

be identified by species, they were counted. This

metric was developed for depressional wetlands,

so all taxa recognized as being nonwetland taxa

were excluded from the count. Species are identified as being nonwetland taxa in accordance with

the Region III assignment (Reed 1988) and include

those species with indicators of FAC+, FACU, and

UPL. This forces the resulting count to reflect the

wetland condition as opposed to the terrestrial and

aquatic community edge.

Although keeping this metric at the genus level will

make it accessible for less specialized biologists and

simplify the sampling, whenever possible all identifications were done to the species level. Interestingly, when this metric was developed it was based

on species-level identification. However, the genus-level scoring gave a stronger negative response

to human disturbance. Caution should be used in

applying this metric where plant diversity is naturally low. Some examples of wetland plant communities that have naturally low numbers of species

are lake sedge (Carex lacustris), fringe communities, wild rice (Zinnia palustris) beds, and hardstem

bulrush (Scirpus acutus) communities.

2. Nonvascular taxa metric

Rationale: The nonvascular taxa metric expresses

the number of nonvascular taxa including liverworts,

mosses, lichen taxa, and the macroscopic algae

Chara and Nitella. In the Minnesota study, the

maximum number of nonvascular taxa observed at

any site was two (including four of the six reference

sites). Six of the agriculturally impacted sites and
33

five of the stormwater sites supported no

nonvascular taxa. This was not surprising. Blindow

(1992) reported that charaphytes and possibly other

nonvascular taxa are more sensitive to eutrophication than are angiosperms. It is likely this metric

could be strengthened by improving the level of identification for the mosses, bringing them to genus.

Table C-1: Scoring criteria for vegetation-based metrics in the

Minnesota IVI. The number of sites scoring at each level is given, as are

the number of least-impacted reference (ref) sites.

Note: All data were collected in 100 m2

 releve plots.

3. Carex cover metric

Rationale: The Carex cover metric was calculated by summing the cover class for all Carex taxa

sampled in each plot. Carex occur as an important

structural component of shallow wetland emergent

plant communities. Members of the Carex genus

are particularly common in shallow marsh and wet
34

meadow communities (Eggers and Reed 1997).

They are known to be adversely affected by such

environmental stressors as excessive siltation and

hydrologic alteration and nutrient enrichment

(Wilcox 1995). Field observations have demonstrated that these plants are among the most sensitive to human disturbance and among the first to

either disappear from sites or be poorly recruited in

most wetland restoration projects (Galatowitsch

1993).

In order to receive a score of 5 a site must support at least 25% Carex cover. It is interesting that

two agricultural, two stormwater, and two reference sites had a score of 5 for this metric. These

sites were likely influenced by groundwater that may

have positively influenced the amount of Carex they

supported.

4. Grasslike species metric

Rationale: The grasslike species metric expresses

the richness of grasses (Poaceae), sedges

(Cyperaceae), and rushes (Juncaceae). Structurally these plants are very similar and generally occupy similar niches. Only native taxa in these three

families were tabulated for the grasslike species

metric. This metric is important because native taxa

in these plant families are frequently among the first

to begin decreasing following human disturbance

(Wilcox 1995). Galatowitsch (1993) reports that

particularly the sedges are poorly recruited in wetland restoration projects, which suggests sedges

have a relatively low ecological tolerance to stress.

There was only a moderate (R2

 = 0.43) linear relationship between the number of grasslike species

and the gradient of human disturbance. The statistical analysis showed this metric to be one of the

weaker plant metrics. However, this measure was

able to distinguish the severely impaired sites from

the reference sites.

5. Monocarpic species metric

Rationale: Monocarpic species flower only once

in their life cycle and typically including annual and

biennial species. We used a mathematical function

to relate the importance of monocarpic species (using cover) at each study site. van der Valk (1981)

reported that changes in water level through natural

drying or inundation can result in habitat changes

that facilitate the growth of monocarpic species. We

calculated this metric as a sum of the monocarpic

species richness and cover class values divided by

the monocarpic species cover. Only native monocarpic taxa were not included because nonnative

monocarpic taxa are often aggressive and could

skew the response.

The monocarpic species metric responded

strongly to hydrologic fluctuations. As such it would

be useful to include this metric in a multimetric index to respond to signals from worst-case sites,

particularly those affected by severe hydrologic fluctuations.

6. Aquatic guild metric

Rationale: This metric evaluates the number of

aquatic guilds at a site. Submerged plants, either

rooted or unrooted, and floating vascular plants such

as the duckweeds are life-form-dependent aquatic

macrophytes that comprise the aquatic guild used

in this metric. The guild is adapted from

Galatowitsch and McAdams (1994), who recognize six separate aquatic guilds. Four of their guilds,

including “rooted submersed aquatics,” “unrooted

submersed aquatics,” “floating perennials,” and

“floating annuals” were used in constructing this

metric. When counting the number of aquatic guild

species only native species were included. The

aquatic guild taxa were expected to be most responsive to the water quality. Though the relationship between this metric and the human disturbance

index was not a statistically significant linear relationship (R2

 = 0.28), the data show a separation of
35

the a priori reference sites from more than half of

the degraded sites. This metric appears to be particularly important in larger or more open wetlands.

7. Sensitive taxa metric

Rationale: The sensitive taxa metric evaluates the

decrease in richness of taxa that are most susceptible to human disturbance. To determine which

species were sensitive, a matrix of all plant taxa

sampled in the project was created by site. In this

matrix the a priori reference sites were arranged

along one side of the site continuum. Taxa either

unique to the reference sites or those that occurred

in two or more reference sites and only one impaired site were considered to be sensitive. Any

nonnative species meeting these criteria were not

considered to be sensitive taxa. The list of taxa

considered to be sensitive included Asclepias

incarnata, Dulichium arundinaceum,

Eriophorum gracile, Scirpus validus, and Iris versicolor. Recognition of tolerant taxa was based

partly on reported responses of plant species to

human disturbance (Wilcox 1995, Rice and

Pinkerton 1993, Weisner 1993, Squires and van

der Valk 1992) as well as personal field observations in this project. All nonnative plant taxa were

also considered to be tolerant. Percent tolerant species values were developed as a proportion of the

number of tolerant species in a sample divided by

the total number of all taxa in the sample. Possible

values for this metric range from 1 to 100. Our

results for this metric showed that from 11% to

100% of the taxa in the sample were tolerant. The

reference wetlands clearly had proportionately fewer

tolerant species than the impaired sites. This metric

gave the strongest response signal out of the 10

vegetation metrics.

8. Dominance metric

Rationale: The dominance metric incorporates the

distribution or concentration of cover class values

relative to the taxa richness for native species within

the sample. Used in this way it is similar to an expression of evenness. The formula for calculating

dominance was taken from Odum (1971) and expressed as:

D = (ni

/N)2

where ni = the cover class for each taxa within an

emergent sampling plot, and N = the sum of all cover

class values for all taxa within the sampling plot.

The mathematical range of this function is between

0 and 1, with a more biologically diverse wetland

scoring near 0 and more monotypic sites scoring

near 1. In this study, the eight most impaired sites

had higher dominance values than all the reference

sites. The dominance metric is considered to be

one of the moderately reliable metrics.

9. Persistent litter metric

Rationale: Persistent litter is defined as being resistant to decomposition. It does not provide as

many available nutrients or as much detrital energy

to drive the wetland system as does readily decomposable litter. Decomposing litter provides microhabitats and nutritional benefit for many aquatic invertebrates (Campeau et al. 1994). Scoring for

the persistent litter metric was based on a sum of

the abundance cover classes for plant taxa recognized as having persistent litter, including: common

reed (Phragmites), bullrushes (Scirpus), smartweeds (Polygonum), cattails (Typha), and

burreeds (Sparganium). This measure proved to

be a reliable metric.
36

Appendix D

Tolerance Groups of Wetland Plants for Use in a Plant-Based

Index of Biological Integrity

Denice Heller Wardrop and Robert P. Brooks

Penn State Cooperative Wetlands Center

In preparation for a plant-based Index of Biological Integrity (IBI), individual plant community

metrics have been tested for robustness along a gradient of human disturbance in Pennsylvania wetlands. Human activities of high interest in Pennsylvania include land-use conversion to agricultural and

urban uses; dominant stressors associated with these

activities are hydrologic modification, sedimentation, and nutrient input. General measures of community response, such as species richness, diversity, and evenness, when taken over all wetland

types, do little to establish general patterns of response to these stressors. Suitable metrics for expressing plant community responses to disturbance

were not available and therefore needed to be constructed. One traditional metric is the use of functional, or tolerance, groups of organisms. Existing

functional groups do not incorporate stress-resistant characteristics. For example, currently-used

functional groups do not include traits that exemplify a species’ germination capabilities as well as

its ability for clonal growth; both traits are basic to

a plant’s ability to tolerate sedimentation. Tolerance groups of plants relating to sedimentation and

hydrologic stress were, therefore, constructed using field data on 70 reference wetlands in Pennsylvania.

Our wetland sites were chosen to encompass six

common (HGM) subclasses of Pennsylvania’s five

ecoregions (headwater floodplains, mainstem floodplains, slopes, riparian depressions, surface depressions, and fringing), as well as high, moderate, and

low levels of impact from human activities (e.g., elevated sedimentation, nutrient loading, habitat fragmentation). Field data included presence/absence

and percent cover data, resulting in more than 500

plant species represented over approximately 800

plots. Characterization of plant communities in these

wetlands showed clear associations between individual species and ability to tolerate sediment. The

tolerance for sedimentation in most species, however, is also dependent on other possible co-occurring stressors, such as wetting and drying cycles.

HGM subclass was used as an indicator of levels

of these co-occurring stressors. It was expected

that the ability of a plant community or individual

species to occupy space along a gradient of increasing sediment accumulation would be different for

various HGM subclasses. This was borne out in

shifts of some species between sediment tolerance

groups within wetlands of different HGM types, or

drastic reductions in the mean percent cover demonstrated between HGM subclasses. In this context, HGM classification was important in establishing the range of other co-occurring stressors,

and thus provided a constrained condition for examining the effects of sedimentation. Because of

the clear value of HGM classification as an organizing variable of co-occurring stressors, sediment

tolerance groups were established for each HGM

wetland type.

Sediment tolerance groups were established by

tabulating average percent cover of individual species, when present, with sedimentation levels. Species were categorized as very tolerant, moderately

tolerant, slightly tolerant, and intolerant on the basis

of their association with environments of varying

sedimentation. In general, species that were cat-
37

egorized as very tolerant or moderately tolerant increased their percent cover (dominance) over the

disturbance gradient. For species that represented

either end of the disturbance gradient (i.e., highly

tolerant or intolerant), the appropriateness of the

plant species as an ecological indicator was assessed

utilizing calculation of validity and significance. Validity is a measure of how often an indicator (e.g., a

particular plant species) is found with whatever it is

expected to indicate (e.g., sedimentation category).

This is expressed as the ratio of the number of plots

where these two items occur together to the total

number of plots where the indicator occurs, expressed as a percentage. Significance denotes the

frequency with which the indicator and that particular object are associated. Significance is determined by expressing as a percentage the ratio of

the number of plots where both occur to the total

number of plots where the indicator object is found.

Validity and significance were calculated for each

plant species/sedimentation category combination.

Plant species were sorted according to validity and

significance values in each sedimentation category.

Hydrologic groups were determined in a similar

fashion, utilizing well monitoring data collected by

the Penn State Cooperative Wetlands Center at 27

sites. Hydrologic measures, based on water level

data recorded every 6 hours, were the following:

 Median depth to water

 Percent time water level was within the top 30

cm

 Percent time upper 30 cm was saturated, inundated, or dry

 Percent time upper 10 cm was saturated, inundated, or dry

Utilizing these data, sites were assigned to one of

five hydrologic groups, ranging from predominantly

inundated to predominately dry. Plant data from

406 plots, with a total of 187 plant species, was

used to construct the groups. Groups were established by tabulating average percent cover of individual species, when present, within each of the five

hydrologic groups. Wetland plant indicator status

(obligate, facultative, etc.) was an extremely poor

predictor of an individual species’ associated hydrologic regime. For example, species found in

wetlands that were almost constantly inundated had

indicator statuses ranging from obligate to facultative-upland. However, HGM classification is a suitable surrogate for hydrologic regime, suggesting that

hydrologic groups can be constructed without extensive monitoring well data.

A number of reasons indicate that stressor-specific tolerance groups of plant species, constructed

with field data, are an effective basis for metrics in a

plant-based IBI:

 Linkages of plant species to specific stressors

are well documented

 Ecological suitability of a site for an individual

plant species is documented

 Field-based groups complement literaturebased ones

 Field-based construction improves the diagnostic capabilities of metrics

An example of tabulation of field data for establishment of groups is presented in Figure D-1.
38

Figure D-1: Sediment Tolerance Groups of Wetland Plants in Slope

Wetlands of Central Pennsylvania Wetlands.