Water-Resources Investigations Report 00-4255

National Water-Quality Assessment Program

In cooperation with the Ohio Environmental Protection Agency

Comparison of U.S. Geological Survey and

Ohio Environmental Protection Agency

Fish-Collection Methods Using the Index of Biotic

Integrity and Modified Index of Well-Being, 1996 97

U.S. Department of the Interior

U.S. Geological Survey
Cover photo: View of River Raisin at fish-sampling site near Manchester, Michigan.

Photo by Alex Covert, U.S. Geological Survey, 1996.
U.S. Department of the Interior

U.S. Geological Survey

Comparison of U.S. Geological Survey and

Ohio Environmental Protection Agency

Fish-Collection Methods Using the Index of Biotic

Integrity and Modified Index of Well-Being, 1996–97

By S. Alex Covert

Water-Resources Investigations Report 00–4255

National Water-Quality Assessment Program

In cooperation with the Ohio Environmental Protection Agency
U.S. Department of the Interior

BRUCE BABBITT, Secretary

U.S. Geological Survey

CHARLES G. GROAT, Director

Any use of trade, product, or firm names is for

descriptive purposes only and does not imply

endorsement by the U.S. Government.

For additional information write to

District Chief

U.S. Geological Survey

6480 Doubletree Avenue

Columbus, OH 43229-1111

Copies of this report can be purchased from

U.S.Geological Survey

Branch of Information Services

Box 25286

Denver, CO 80225-0286

Columbus, Ohio

2000
iii Foreword

The mission of the U.S. Geological Survey (USGS) is to assess the quantity and quality of the earth resources of

the Nation and to provide information that will assist resource managers and policymakers at Federal, State, and local

levels in making sound decisions. Assessment of water-quality conditions and trends is an important part of this overall mission.

One of the greatest challenges faced by water-resources scientists is acquiring reliable information that will guide

the use and protection of the Nation’s water resources. That challenge is being addressed by Federal, State, interstate,

and local water-resource agencies and by many academic institutions. These organizations are collecting water-quality data for a host of purposes that include compliance with permits and water-supply standards; development of

remediation plans for specific contamination problems; operational decisions on industrial, wastewater, or water-supply facilities; and research on factors that affect water quality. An additional need for water-quality information is to

provide a basis on which regional- and national-level policy decisions can be based. Wise decisions must be based on

sound information. As a society we need to know whether certain types of water-quality problems are isolated or

ubiquitous, whether there are significant differences in conditions among regions, whether the conditions are changing over time, and why these conditions change from place to place and over time. The information can be used to

help determine the efficacy of existing water-quality policies and to help analysts determine the need for and likely

consequences of new policies.

To address these needs, the U.S. Congress appropriated funds in 1986 for the USGS to begin a pilot program in

seven project areas to develop and refine the National Water-Quality Assessment (NAWQA) Program. In 1991, the

USGS began full implementation of the program. The NAWQA Program builds upon an existing base of water-quality

studies of the USGS, as well as those of other Federal, State, and local agencies. The objectives of the NAWQA Program

are to

• describe current water-quality conditions for a large part of the Nation’s freshwater streams, rivers, and

aquifers,

• describe how water quality is changing over time, and

• improve understanding of the primary natural and human factors that affect water-quality

conditions.

This information will help support the development and evaluation of management, regulatory, and monitoring decisions by other Federal, State, and local agencies to protect, use, and enhance water resources.

The goals of the NAWQA Program are being achieved through ongoing and proposed investigations of a select

set of the Nation’s most important river basins and aquifer systems, which are referred to as study units. These study

units are distributed throughout the Nation and cover a diversity of hydrogeologic settings. More than two-thirds of

the Nation’s freshwater use occurs within the study units, and more than two-thirds of the people served by public

water-supply systems live within their boundaries.

National synthesis of data analysis, based on aggregation of comparable information obtained from the study

units, is a major component of the program. This effort focuses on selected water-quality topics using nationally consistent information. Comparative studies will explain differences and similarities in observed water-quality conditions among study areas and will identify changes and trends and their causes. The first topics addressed by the

national synthesis are pesticides, nutrients, volatile organic compounds, and aquatic biology. Discussions on these

and other water-quality topics will be published in periodic summaries of the quality of the Nation’s ground and surface water as the information becomes available.

This report is an element of the comprehensive body of information developed as part of the NAWQA Program.

The program depends heavily on the advice, cooperation, and information from many Federal, State, interstate,

Tribal, and local agencies and the public. The assistance and suggestions of all are greatly appreciated.

Robert M. Hirsch

Chief Hydrologist

FOREWORD
Contents V

CONTENTS

Abstract ................................................................................................................................................................................. 1

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

Purpose and scope ....................................................................................................................................................... 2

Acknowledgments ....................................................................................................................................................... 2

Study area and sampling sites ............................................................................................................................................... 2

Equipment and sampling methods ........................................................................................................................................ 2

Wading sites ................................................................................................................................................................ 4

Boat sites ..................................................................................................................................................................... 4

Processing fish samples in the field ............................................................................................................................ 5

Analysis tools ....................................................................................................................................................................... 5

Similarities and differences between U.S. Geological Survey and Ohio Environmental Protection Agency

index scores ....................................................................................................................................................................... 5

Data comparability and sources of data variability .............................................................................................................. 10

Index of Biotic Integrity scores ................................................................................................................................... 10

Modified Index of Well-Being scores ......................................................................................................................... 15

Comparison of index scores in relation to aquatic-life criteria ................................................................................... 15

Summary and conclusions .................................................................................................................................................... 16

References cited .................................................................................................................................................................... 16

FIGURES

1. Map showing study area and location of sampling sites, Lake Erie-Lake St. Clair Basin, Michigan, Indiana,

Ohio, and New York ............................................................................................................................................. 3

2-5. Graphs showing:

2. Differences (U.S. Geological Survey/Ohio Environmental Protection Agency) for

Index of Biotic Integrity and Modified Index of Well-Being scores ...................................................... 7

3. Index of Biotic Integrity and Modified Index of Well-Being scores plotted against

the relative number of fish collected ....................................................................................................... 10

4. Differences between U.S. Geological Survey and Ohio Environmental Protection Agency

for each metric of the Index of Biotic Integrity ....................................................................................... 11

5. Percentage of attainment of Warmwater Habitat criteria for Index of Biotic Integrity and

Modified Index of Well-Being scores ..................................................................................................... 13

TABLES

1. U.S. Geological Survey and Ohio Environmental Protection Agency electroshocking equipment ....................... 4

2. U.S. Geological Survey and Ohio Environmental Protection Agency Index of Biotic Integrity

and Modified Index of Well-Being scores for 18 sampling reaches .................................................................... 6

3. U.S. Geological Survey and Ohio Environmental Protection Agency Index of Biotic Integrity,

individual metric, and Modified Index of Well-Being scores in 1996 and 1997 ................................................. 8
VI Contents

CONVERSION FACTORS

Multiply By To obtain

foot (ft) 0.3048 meter

inch (in.) 25.4 millimeter

centimeter (cm) 0.3937 inch

kilometer (km) 0.6214 mile
Abstract 1

Comparison of U.S. Geological Survey and Ohio

Environmental Protection Agency Fish-Collection

Methods Using the Index of Biotic Integrity and

Modified Index of Well-Being, 1996–97

By S. Alex Covert

Abstract

The U.S. Geological Survey (USGS) and Ohio

Environmental Protection Agency (OEPA) collected data on fish from 10 stream sites in 1996

and 3 stream sites in 1997 as part of a comparative study of fish community assessment methods.

The sites sampled represent a wide range of basin

sizes (ranging from 132–6,330 square kilometers)

and surrounding land-use types (urban, agricultural, and mixed). Each agency used its own fishsampling protocol. Using the Index of Biotic

Integrity and Modified Index of Well-Being, differences between data sets were tested for significance by means of the Wilcoxon signed-ranks test

(α = 0.05). Results showed that the median of

Index of Biotic Integrity differences between data

sets was not significantly different from zero (p =

0.2521); however, the same statistical test showed

the median differences in the Modified Index of

Well-Being scores to be significantly different

from zero (p = 0.0158). The differences observed

in the Index of Biotic Integrity scores are likely

due to natural variability, increased variability at

sites with degraded water quality, differences in

sampling methods, and low-end adjustments in

the Index of Biotic Integrity calculation when

fewer than 50 fish were collected. The Modified

Index of Well-Being scores calculated by OEPA

were significantly higher than those calculated by

the USGS. This finding was attributed to the comparatively large numbers and biomass of fish collected by the OEPA. By combining the two

indices and viewing them in terms of the percentage attainment of Ohio Warmwater Habitat criteria, the two agencies’ data seemed comparable,

although the Index of Biotic Integrity scores were

more similar than the Modified Index of WellBeing scores.

Introduction

Since the 1970s, Federal and state government agencies have increased their interest and research in

aquatic biology as part of water-resources assessments. This is particularly true in Ohio, where the

Ohio Environmental Protection Agency (OEPA) and

the U.S. Geological Survey (USGS) have established

substantial data-collection programs in the area of

aquatic biology. OEPA has been one of the leading

agencies to develop and incorporate numeric biological water-quality criteria into water-quality assessments. “In the case of Ohio, these regulatory

biological criteria are supported by the most extensive

sampling, assessment, and implementation program in

the nation” (Southerland and Stribling, 1995). The

USGS collects physical, chemical, and biological data

as part of the National Water-Quality Assessment

(NAWQA) program. This program, which began in

1991, assesses water quality in study units representing major river basins and aquifer systems across the

Nation. Biological approaches include the characterization of fish, invertebrate, and algal communities.
2 Comparison of U.S. Geological Survey and Ohio Environmental Protection Agency Fish-Collection Methods

“Interagency collaboration and the use of comparable biological methods can reduce costs, expand

the base of biological information useful for decision

making, and enhance scientific understanding of biological processes in relation to physical and chemical

processes in ecosystems” (Elizabeth Fellows, U.S.

Environmental Protection Agency, quoted in Gurtz

and Muir, 1994). For these reasons, the Intergovernmental Task Force on Monitoring Water Quality

(ITFM) set as a priority the development of comparable biological methods for interagency use. Certain

similarities in OEPA and USGS objectives and methods suggest that collaboration and data sharing of this

type might be feasible between the two agencies.

(Hereafter, “USGS” is used in reference to NAWQA

activities in Lake Erie-Lake St. Clair Basin part of

Ohio.) Both agencies describe the status and trends of

surface waters on the basis of biological data. The similarity of objectives is apparent in the types of fishcommunity data collected by the two agencies: specifically, species distribution, composition, and relativeabundance data. Fish-collection methods of the two

agencies also are similar; according to 45 biologists

participating in an Interagency Biological Methods

Workshop, differences in fish-sample-collection programs were relatively minor and would not affect data

comparability (Gurtz and Muir, 1994).

In order to determine the feasibility and limitations of fish-community data exchange between OEPA

and USGS programs, the two agencies did an investigation in which both agencies sampled the same sets

of sites independently, after which biotic-index data

derived from the two sets of samplings were compared.

Purpose and scope

This report describes the OEPA-USGS study methodology and discusses the qualitative and statistical comparison of the data. The data sets resulted from

samplings at 10 sites in 1996 and 3 sites in 1997, representing a wide range of drainage areas and land-use/

land-cover settings. The Index of Biotic Integrity (IBI)

and the Modified Index of Well-Being (MIwb) were

the specific measures compared; attainment of applicable aquatic-life standards also was examined.

Acknowledgments

The author thanks Terry Keiser, Head of Biological

Sciences Department at Ohio Northern University, for

his assistance in fish data collection. The author also

acknowledges Marc Smith and the staff at the Ohio

Environmental Protection Agency for collecting and

compiling fish data.

Study area and sampling sites

The USGS and OEPA used electroshocking methods

and equipment to collect fish at the same 10 stream

sites from late July to mid-October in 1996 and 1997

during low-flow conditions. The 10 sampling sites and

reaches were selected for the USGS Lake Erie-Lake

St. Clair Basin (LERI) study unit as part of the

NAWQA program (fig. 1). A “reach” in this report is

any continuous distance electrofished in one sampling

pass. In 1996, all 10 sites were sampled by both agencies. The USGS sampled one reach at each site one

time. The OEPA sampled a single reach at 7 of the 10

sites twice and the remaining 3 sites once. In 1997,

three reaches were sampled, once by each agency, in

each of three rivers.

Equipment and sampling methods

The USGS and OEPA collected fish by use of pulsed

direct-current (DC) electrofishing equipment and techniques during daylight hours (table 1). The USGS also

used seining techniques where applicable. Each

agency used its own fish-sampling protocol (Meador

and others, 1993; Ohio Environmental Protection

Agency, 1989). For both agencies, the choice of electrofishing equipment and sampling techniques used

depends on water depth and flow. In this study, two

methods were used: wading and boat. Wading methods in this study utilized a small tote-barge for hauling

equipment. The tote-barge is pulled by a samplingcrew member, and everyone in the crew walks in the

water. Another wading method not used in this study

utilizes backpack electroshocking equipment. Boat

methods require that the equipment and crew be in a

motor-powered boat.

The two protocols describe the selection of the

appropriate electroshocking method differently. The

USGS protocol bases the method selection on the

description of a wadeable stream. “Towed electrofishing gear is usually more effective,” than backpack

electrofishing, “in relatively wide (greater than about

5 m) wadeable streams with deep pools (greater than

1 m deep)” (Meador and others, 1993). Boat methods
Equipment and sampling methods 3

EXPLANATION

 1 Black River near Jeddo, Michigan 2 Clinton River at Sterling Heights, Michigan 3 River Raisin near Manchester, Michigan 4 St. Joseph River near Newville, Indiana 5 Maumee River at New Haven, Indiana 6 Auglaize River near Ft. Jennings, Ohio 7 Maumee River at Waterville, Ohio 8 Cuyahoga River at Cleveland, Ohio 9 Grand River near Harpersfield, Ohio 10 Cattaraugus Creek at Gowanda, New York

9 SAMPLING SITE

OHIO

PENNSYLVANIA

NEW YORK

INDIANA

MICHIGAN

CANADA

Study Area

Black

River

Tonawanda

Creek

Belle

River

Clinton River

River

H uron Rouge

Raisin

River

Grand

River

River

River Tiffin

Cuyahoga

Black

River

River

St. Joseph

River

Maumee

Blanchard River

St. Marys

River

Sandusky

Cattaraugus

Creek

Buffalo

River

Auglaize

River

Rive r

OHIO

INDIANA

OHIO

PENNSYLVANIA

PENNSYLVANIA

NEW YORK

OHIO

MICHIGAN

UNITED STATES

CANADA

LAKE ERIE LAKE ST. CLAIR

82 ̊

81 ̊

80 ̊

79 ̊

83 ̊

84 ̊

85 ̊

41 ̊

42 ̊

43 ̊

2

4

5

7 8

10

1

9

6

3

Niagara

River

River

0

0

20

20 40

40 60 MILES

60 KILOMETERS

Base from U.S. Geological Survey digital data, 1:2,000,000, 1972Albers Equal-Area Conic ProjectionStandard parallels 29o30' and 45o30', central merdian 83o

Figure 1. Study area and location of sampling sites, Lake Erie-Lake St. Clair Basin, Michigan, Indiana, Ohio, and New York.
4 Comparison of U.S. Geological Survey and Ohio Environmental Protection Agency Fish-Collection Methods

Table 1. U.S. Geological Survey and Ohio Environmental Protection Agency electroshocking equipment

[cm, centimeter; in., inch; ft, foot; DC, direct current]

Type

U.S. Geological Survey

Ohio Environmental Protection Agency

1996 1997

Equipment Used At Wading Sites

Electrofishing unit Boyd

Electrofisher

Smith-Root 2.5 GPP

Electrofisher

Model 1736 VDC T&J

Electrofisher, or

Smithroot 3.5 GPP

Electrofisher,

Rated output current 5 amperes 8 amperes 7 amperes, 11 amperes,

DC output volts 500 volts 500/1,000 volts (low/high) 300 volts; 1,000 volts

Anode 11-in. anode ring 11-in. anode ring Net ring

Cathode 10-ft aluminum boat 12-ft aluminum boat Approximately 15.2 X 45.7 cm stainless steel strip

Tote-barge 10-ft aluminum boat 12-ft aluminum boat Light, plastic boat

Equipment Used At Boat Sites

Electrofishing unit Smith-Root Custom

Electrofisher

Smith-Root VI-A

Electrofisher, or

Smith-Root 3.5 GPP

Electrofisher,

Rated output current 20 amperes 8 amperes, 11 amperes,

DC output volts 1,000 volts 996 volts; 1,000 volts

Anode Two umbrella-shaped

stainless-steel cable configurations

Four stainless steel cables arranged

in a line on boom on front of boat

Cathode Boat Four flexible galvanized steel conduit

arranged in a line on front of boat

Boat (motor-powered) 16-ft metal boat 12-, 14-, or 16-ft metal boat

are used in nonwadeable streams. The OEPA protocol

bases the method selection on the accommodation of

boats and equipment in the stream. Boat methods are

used if a stream can accommodate a boat and equipment. Wading methods are used in “smaller, wadeable

streams that can not accommodate the boat methods”

(Ohio Environmental Protection Agency, 1989).

Equipment used by each agency is listed in table 1.

Wading sites

Where wading methods are used, the USGS requires

two successive sampling passes, in an upstream direction. A sampling pass in this report is any continuous

electroshocking effort from end to end of a reach. Four

to six crew members are involved. The USGS samples

all of the habitat features within a sampling reach. One

person carries the anode pole and controls the electroshocking. One person is needed to pull the totebarge. Two to four people net the fish. An extra person

transports the fish from the netters to the livewell on

the tote-barge in larger rivers.

The OEPA requires one sampling pass in an

upstream direction. Two to three people collect the

fish. The OEPA samples all of the habitat features

within a sampling reach. One person, the primary netter, operates the anode net ring. One person pulls the

tote-barge. Other member or members may be used to

net fish.

Boat sites

Where fish are collected from a boat, the USGS

requires two successive passes, one along each bank,

in a downstream direction. Three people are needed:

one person controls the boat, and the other two people

net the fish. The USGS samples all of the habitat features within a sampling reach.

The OEPA requires one pass in a downstream

direction. Two people are specified: one person to control the boat and the other person to net the fish. The

OEPA samples all of the habitat features within a sampling reach. The actual shocking time is considered an

important factor. Minimum shocking times are specified in order to catch the required numbers and kinds

of fish to adequately represent the sampling reach. The

minimum shocking time is given as 1,300 to 1,600

seconds for a 0.5-km reach. The minimum time is

increased (2,000 seconds) for slow-moving waters

with many obstacles.
Analysis tools 5

Processing fish samples in the field

The IBI and MIwb were compared in this report to

study differing fish-collection methodologies. These

indices require species identification, numbers of fish

of each species, total weight of each species, and numbers of anomalies. Both agencies make an effort to

train crew members in fish identification skills. These

skills are used in the field to identify fish species. Both

agencies, however, keep fish for later lab identification

if any uncertainty exists. Taxonomic nomenclature for

both agencies follows that established by the American Fisheries Society (Walsh and Meador, 1998). The

total weight for each species and number of external

anomalies is collected by the USGS and OEPA. Therefore, differences in equipment and in techniques used

by experienced, trained personnel after the fish are

captured probably are minimal and unlikely to affect

reported results.

Analysis tools

Two major tools available for analysis of fish-community data are the IBI, developed by Karr (1981), and

the Index of Well-Being (Iwb), developed by Gammon

(1976). The IBI is based on fish-community structural

and functional characteristics and is a measure of the

health of an aquatic ecosystem. Fish communities at

study-area stream sites are compared to those at reference stream sites (streams relatively unaffected by

human activity) that drain similar-sized basins within

the same ecoregion. The comparison allows a score to

be assigned to each of 12 metrics. A summation of the

metric scores gives an overall value from 12 to 60.

Higher values usually indicate healthier aquatic ecosystems. The IBI used by the OEPA is specifically tailored to the surface waters of Ohio (Ohio Environmental Protection Agency, 1987). The Iwb is calculated from numbers of individuals, biomass, and the

Shannon diversity index based on the numbers and

weight of fish (Ohio Environmental Protection Agency, 1987). The Shannon diversity index takes into

account species richness and proportion of each species within the local aquatic community (Shannon and

Weaver, 1949). The OEPA modified the Iwb by

excluding fish that were defined as highly tolerant

from the numbers of individuals and biomass calculations. A higher score indicates a healthier aquatic ecosystem. The OEPA-modified versions of these indices

(IBI and MIwb) were also applied to USGS data in

this comparison. The calculation methods and specifics of each index are described by OEPA (1987).

The IBI and MIwb scores were calculated by the

respective agency for each site sampled. The mean IBI

and MIwb scores were calculated for each OEPA site

that had been visited more than once. Both sets of

scores were compared to Ohio Warmwater Habitat criteria.

Statistical analyses were done by means of Statit

3.0c (Statware, Inc., 1990). The Wilcoxon signed-rank

test was used to determine whether the median difference of IBI and MIwb scores between paired observations equaled zero. The test was two-tailed to detect a

difference in either direction. An α level of 0.05 was

chosen.

Similarities and differences between U.S.

Geological Survey and Ohio Environmental Protection Agency index scores

The OEPA consistently had higher scores at most sites

for the IBI (table 2; fig. 2), although the median of differences between USGS and OEPA scores was not significantly different from zero (Wilcoxon signed-ranks

test, p = 0.2521).

Reach A in the Clinton River produced highly

variable results (table 2). The differences between the

USGS and OEPA IBI scores were 15 and 24 in 1996

and 1997, respectively. In 1996, the OEPA score was

higher, whereas the USGS score was higher for the

next year. Because of the high within-year-sampling

variability, the 1996 OEPA data for reach A in the

Clinton River were not statistically compared with

USGS data. No apparent reason could be assigned to

this variability.

The electrofishing method chosen by each

agency, boat or wading, was a possible source of data

variability (table 3). When the USGS and the OEPA

both used boat methods on the Maumee River at New

Haven and on the Cuyahoga River, no differences in

IBI scores were greater than 4; however, when the

OEPA used the boat method and the USGS used the

wading method on the Maumee River at Waterville in

1997 and on the St. Joseph River, differences in IBI

scores were greater than or equal to 4.

The number of fish collected can influence all of

the metrics of the IBI in which a percentage is calculated. As is evident from figure 3, the OEPA consistently captured more fish at most sites in terms of
6 Comparison of U.S. Geological Survey and Ohio Environmental Protection Agency Fish-Collection Methods

Table 2. U.S. Geological Survey (USGS) and Ohio Environmental Protection Agency

(OEPA) Index of Biotic Integrity (IBI) and Modified Index of Well-Being (MIwb) scores for the

18 sampling reaches

[A, B, and C correspond to the 3 reaches that were sampled by each agency in the specified river; N/A, not applicable;

F F, both agencies used wading methods; J J, both agencies used boat methods; F J, OEPA used boat

methods and USGS used wading methods]

Method Year Site location and reach

IBI scores MIwb scores

USGS OEPA USGS OEPA

F F 1996 Grand River—A 48 44 (38, 50)* 8.9 9.5 (9.3, 9.7)*

F F 1997 Grand River—A 52 40 8.7 8.0

F F 1997 Grand River—B 54 48 N/A 8.6

F F 1997 Grand River—C 52 52 9.9 10.1

J J 1996 Maumee River at New Haven 34 30 (30, 30)* 6.9 8.0 (7.8, 8.1)*

F F 1996 Maumee River at Waterville 26 30 (28, 32)* 6.1 7.7 (7.3, 8.1)*

F J 1997 Maumee River at Waterville—A 32 42 7.8 8.6

F J 1997 Maumee River at Waterville—B 30 38 6.5 8.6

F J 1997 Maumee River at Waterville—C 28 32 7.2 8.5

F J 1996 St. Joseph River 22 28 (26, 30)* 4.0 7.4 (7.3, 7.4)*

F F 1996 Auglaize River 32 35 (34, 36)* 7.0 9.3 (9.0, 9.6)*

F F 1996 River Raisin 44 52 (52, 52)* 8.0 8.6 (8.3, 8.9)*

F F 1996 Black River 38 42 6.9 9.1

J J 1996 Cuyahoga River 16 14 5.5 4.0

F F 1996 Clinton River—A 12 27 (14, 40)* 2.3 4.7 (4.1, 5.2)*

F F 1997 Clinton River—A 38 14 5.4 5.1

F F 1997 Clinton River—B 38 42 7.1 6.8

F F 1996 Cattaraugus Creek 36 38 6.2 7.4

* Mean score (individual score).

relative numbers of fish captured (per 0.3 or 1.0 km,

depending on the method used) . Exceptions were

when both agencies used the boat method.

The USGS and OEPA report similar IBI scores

and, thus, similar descriptions of the status of aquatic

ecosystems. The IBI score can be misleading, however, in that two fairly different sets of individual metrics may yield similar IBI scores. For example, the

USGS may score higher on the number of total species

metric but lower on the percent of tolerant fish metric

than the OEPA; the IBI score nonetheless is the same.

A comparison of the individual metric scores (1, 3,

or 5) of the IBI (fig. 4) revealed that the differences

between the USGS and OEPA for three of the metrics

were considerable. The USGS had higher scores for

two metrics, percent top carnivores and percent

DELTs. The OEPA captured greater numbers of fish

per effort as a function of distance.

The MIwb scores between the USGS and OEPA

were considerably different (fig. 2). The Wilcoxon

signed-ranks test showed that the median of differences among USGS and OEPA MIwb scores was significantly different from zero (p = 0.0158). The OEPA

level of “significant departure” for MIwb scores starts

at 0.5.

With reference to attainment of Warmwater

Habitat (WWH) criteria based on IBI and MIwb

scores, fish-community designations are similar for

the two agencies (fig. 5). At one site (Maumee River at

Waterville, reach B), data from the OEPA sample indicated that the WWH criteria for the IBI was satisfied,

but data from the USGS sample indicated otherwise.

At Clinton River, reach A, the USGS data suggested

that WWH criteria for the IBI were met, but the OEPA

data suggested the criteria were not met. At four sites

(Maumee River at Waterville, reach A in 1996 and

reach B in 1997; Auglaize River; and Black River), the

OEPA data suggested that WWH criteria for the MIwb

were met but USGS data suggested the criteria were

not met.
Similarities and differences between U.S. Geological Survey and Ohio Environmental Protection Agency index scores 7

Figure 2. Differences (U.S. Geological Survey/Ohio Environmental Protection Agency) for Index of Biotic

Integrity and Modified Index of Well-Being scores for streams in the Lake Erie-Lake St. Clair Basin. (Sampling sites with A, B, and C correspond to the three reaches (left to right at each site represents upstream to

downstream) that were sampled by each agency in the specified river.)

-25

25

-20

-15

-10

-5

0

5

10

15

20

U.S. GEOLOGICAL SURVEY/OHIO ENVIRONMENTAL PROTECTION AGENCY

GRAND RIVER 1996 AGRAND RIVER 1997 AGRAND RIVER 1997 B

GRAND RIVER 1997 C

MAUMEE RIVER AT NEW HAVEN 1996 A

MAUMEE RIVER AT WATERVILLE 1996 A

MAUMEE RIVER AT WATERVILLE 1997 C

MAUMEE RIVER AT WATERVILLE 1997 AMAUMEE RIVER AT WATERVILLE 1997 B

ST. JOSEPH RIVER 1996 A

AUGLAIZE RIVER 1996 A

RIVER RAISIN 1996 A

BLACK RIVER 1996 A

CUYAHOGA RIVER 1996 A

CLINTON RIVER 1996 ACLINTON RIVER 1997 ACLINTON RIVER 1997 B

CATTARAUGUS CREEK 1996 A

-4

4

-3

-2

-1

0

1

2

3

Insufficient data

INDEX OF BIOTIC INTEGRITY

MODIFIED INDEX OF WELL-BEING Insufficient data
8 Comparison of U.S. Geological Survey and Ohio Environmental Protection Agency Fish-Collection Methods Table 3. U.S. Geological Survey and Ohio Environmental Protection Agency Index of Biotic Integrity (IBI), individual metric, and Modified Index of Well- Being (MIwb) scores in 1996 and 1997 [mi2, square miles; N, number of given metric; V, value of each IBI metric (1, 3, or 5); %, percentage of total number of fish; km, kilometer; DELT, deformities, eroded fins, lesions, and tumors; @, wading metric replaced by boat metric] Year Agency Reach Date Drainage area (mi2) Total species N(V) Darter species N(V) Sunfish species N(V) Sucker species N(V) Intolerant species N(V) Tolerant species %(V) Omnivores %(V) Insectivores %(V) Top carnivores %(V) Number per 0.3 or 1.0 km N(V) Simple lithophils %(V) DELT anomalies %(V) IBI MIwb Grand River (Ohio) 1996 USGS

A 08/06/96 552 31(5) 7(5) 3(3) 2(1) 3(3) 15(5) 14(5) 62(5) 17(5) 374(3) 46(5) 1.2(3) 48 8.9

EPA

A 09/17/96 552 37(5) 5(3) 6(5) 3(3) 7(5) 35(1) 36(1) 38(3) 21.8(5) 450(3) 13(1) 0.2(3) 38 9.3

EPA

A 10/03/96 552 32(5) 5(3) 6(5) 3(3) 4(3) 13(5) 13(5) 67(5) 17.3(5) 642(3) 22(3) 0.2(5) 50 9.7

1997 USGS

A 07/22/97 552 38(5) 6(3) 6(5) 6(5) 6(5) 10(5) 12(5) 69(5) 15(5) 420(3) 48(5) 4.0(1) 52 8.7

EPA

A 08/14/97 552 21(3) 7(5) 1(1) 0(1) 5(3) 25(3) 23(3) 70(5) 3.0(3) 594(3) 38(5) 0.0(5) 40 8.0

USGS

B 07/22/97 552 33(5) 7(5) 4(5) 7(5) 7(5) 13(5) 13(5) 72(5) 11(5) 744(3) 45(5) 3.2(1) 54 N/A

EPA

B 08/14/97 552 22(3) 6(3) 4(5) 3(3) 5(3) 13(5) 14(5) 75(5) 9.1(5) 374(3) 49(5) 0.7(3) 48 8.6

USGS

C 07/23/97 553 30(5) 5(3) 4(5) 5(3) 5(3) 10(5) 10(5) 76(5) 10(5) 1061(5) 47(5) 0.7(3) 52 9.9

EPA

C 08/14/97 553 24(5) 6(3) 2(3) 4(3) 5(3) 7(5) 8(5) 81(5) 6.9(5) 813(5) 46(5) 0.0(5) 52 10.1

Maumee River At New Haven (Indiana)

(OEPA and USGS calculated the IBI using boat criteria. Number of darter species replaced with percent round-bodied suckers.)

1996 EPA 09/05/96 1,966 18(3) 2(1)@ 4(5) 4(3) 0(1) 34(1) 17(3) 73(5) 2(1) 270(3) ?(1) 2.0(3) 30 8.1

USGS 10/10/96 1,966 13(3) 37(3)@ 2(3) 1(1) 1(1) 14(5) 22(3) 65(5) 4(1) 105(1) 45(5) 4.1(3) 34 6.9

EPA 10/17/96 1,966 13(3) 22(3)@ 2(3) 5(3) 1(1) 29(1) 26(3) 66(5) 3(1) 104(1) 23(3) 1.4(3) 30 7.8

Maumee River At Waterville (Ohio)

1996 USGS 08/08/96 6,328 23(5) 1(1) 2(3) 3(1) 0(1) 34(1) 40(1) 23(1) 16(5) 58(1) 12(1) 0.0(5) 26 6.1

EPA 09/10/96 6,328 15(3) 1(1) 1(1) 2(1) 1(1) 7(3) 28(3) 47(3) 19.7(5) 148(1) 21(3) 0.8(3) 28 7.3EPA 10/03/96 6,328 17(3) 2(1) 3(3) 3(1) 1(1) 23(1) 40(1) 58(5) 2.4(3) 801(5) 32(3) 0.0(5) 32 8.1

(OEPA calculated the IBI using boat criteria. Number of darter species replaced with percent round-bodied suckers.)

1997 USGS

C 07/31/97 6,320 21(3) 2(1) 4(5) 4(3) 3(3) 44(1) 48(1) 25(1) 11(5) 66(1) 18(3) 5.7(1) 28 7.2

EPA

C 10/02/97 6,320 12(3) 36(3)@ 0(1) 5(3) 0(1) 13(5) 27(3) 43(3) 10(3) 158(1) 37(5) 4.4(1) 32 8.5

USGS

A 07/30/97 6,328 23(5) 0(1) 5(5) 5(3) 1(1) 32(1) 32(3) 34(3) 13(5) 81(1) 21(3) 5.0(1) 32 7.8

EPA

A 10/02/97 6,328 12(3) 58(5)@ 0(1) 4(3) 0(1) 8(5) 14(5) 67(5) 8(3) 286(3) 61(5) 1.3(3) 42 8.6

USGS

B 07/31/97 6,330 26(5) 0(1) 6(5) 4(3) 3(3) 54(1) 53(1) 20(1) 8(5) 92(1) 8(1) 1.8(3) 30 6.5

EPA

B 10/02/97 6,330 12(3) 53(5)@ 1(1) 4(3) 0(1) 15(5) 24(3) 63(5) 4(1) 244(3) 57(5) 2.1(3) 38 8.6

St. Joseph River (Indiana)

(OEPA calculated the IBI using boat criteria. Number of darter species replaced with percent round-bodied suckers.)

1996 USGS 07/22/96 609 14(3) 1(1) 2(3) 2(1) 1(1) 60(1) 37(1) 47(3) 13(5) 28(1) 6(1) 7.0(1) 22 4.0

EPA 09/10/96 609 17(3) 15(1)@ 5(5) 5(3) 0(1) 50(1) 31(1) 49(3) 13(5) 136(1) 18(1) 4.9(1) 26 7.3EPA 10/17/96 609 15(3) 24(3)@ 3(3) 5(3) 1(1) 16(3) 66(1) 29(3) 3(1) 310(3) 26(3) 1.6(3) 30 7.4
Similarities and differences between U.S. Geological Survey and Ohio Environmental Protection Agency index scores 9 Auglaize River (Ohio) 1996 USGS 07/26/96 327 19(3) 2(1) 4(5) 4(3) 1(1) 31(1) 25(3) 58(5) 2.9(3) 93(1) 28(3) 0.9(3) 32 7.0 EPA 09/09/96 327 30(5) 3(1) 6(5) 4(3) 2(1) 42(1) 31(3) 64(5) 2.1(3) 672(3) 5(1) 0.6(3) 34 9.0 EPA 10/03/96 327 28(5) 3(1) 5(5) 4(3) 1(1) 34(1) 28(3) 67(5) 2.1(3) 791(5) 10(1) 0.1(3) 36 9.6 River Raisin (Michigan) 1996 USGS 07/23/96 132 21(3) 5(3) 0(1) 3(3) 6(5) 10(5) 8(5) 76(5) 13(5) 338(3) 61(5) 1.9(1) 44 8.0 EPA 09/04/96 132 26(5) 4(3) 2(3) 4(3) 7(5) 8(5) 7(5) 85(5) 4.7(3) 924(5) 43(5) 0.0(5) 52 8.9 EPA 10/18/96 132 23(5) 4(3) 3(3) 4(3) 7(5) 12(5) 4(5) 77(5) 10.8(5) 380(3) 56(5) 0.0(5) 52 8.3 Black River (Michigan) 1996 USGS 07/24/96 464 17(3) 3(1) 2(3) 2(1) 2(1) 14(5) 10(5) 79(5) 4.3(3) 106(1) 63(5) 0(5)38 38 6.9 EPA 09/04/96 464 25(5) 4(3) 3(3) 3(3) 3(3) 17(3) 15(5) 76(5) 4.6(3) 623(3) 35(3) 0.4(3) 42 9.1 Cuyahoga River (Ohio) (OEPA and USGS calculated the IBI using boat criteria. Number of darter species replaced with percent round-bodied suckers.) 1996 EPA 08/12/96 786 7(1) 3(1)@ 0(1) 2(1) 0(1) 24(3) 91(1) 8(1) 1(1) 146(1) 11(1) 10.4(1) 14 4 .0 USGS 10/08/96 786 6(1) 2(1)@ 0(1) 2(1) 0(1) 17(3) 97(1) 2(1) 1(1) 447(3) 9(1) 8 (1) 16 5.5 Clinton River (Michigan) 1996 USGS A 07/25/96 309 6(1) 0(1) 1(1) 1(1) 0(1) 7(1) 7(1) 33(1) 40(1) 17(1) 20(1) 0.0(1) 12 2.3 EPA A 09/04/96 309 10(1) 2(1) 4(5) 2(1) 0(1) 10(5) 5(5) 60(5) 34.5(5) 71(1) 43(5) 0.0(5) 40 5.2 EPA A 10/08/96 309 7(1) 2(1) 2(3) 1(1) 0(1) 7(1) 0(1) 50(1) 46.7(1) 38(1) 23(1) 0.0(1) 14 4.1 1997 USGS A 07/29/97 309 8(1) 1(1) 2(3) 2(1) 1(1) 2(5) 2(5) 67(5) 12(5) 69(1) 41(5) 0.0(5) 38 5.4 EPA A 09/09/97 309 8(1) 2(1) 2(3) 1(1) 0(1) 3(1) 3(1) 80(1) 16.7(1) 40(1) 57(1) 0.0(1) 14 5.1 USGS B 07/29/97 309 16(3) 2(1) 4(5) 3(3) 1(1) 16(5) 15(5) 45(3) 10(5) 56(1) 41(5) 7.0(1) 38 7.1 EPA B 09/09/97 309 15(3) 3(3) 4(5) 2(1) 1(1) 8(5) 5(5) 75(5) 14.3(5) 107(1) 34(3) 0.0(5) 42 6.8 Cattaraugus Creek (New York) 1996 USGS 08/07/96 436 11(1) 0(1) 0(1) 3(3) 3(3) 18(3) 18(5) 71(5) 6.6(5) 90(1) 63(5) 1.1(3) 36 6.2 EPA 10/02/96 436 16(3) 2(1) 0(1) 4(3) 4(3) 7(5) 5(5) 70(5) 3.7(3) 641(3) 17(1) 0.0(5) 38 7.4

Table 3. U.S. Geological Survey and Ohio Environmental Protection Agency Index of Biotic Integrity (IBI), individual metric, and Modified Index of WellBeing (MIwb) scores in 1996 and 1997

—Continued

[mi2, square miles; N, number of given metric; V, value of each IBI metric (1, 3, or 5); %, percentage of total number of fish; km, kilometer; DELT, deformities, eroded fins, lesions, and tumors;

@, wading metric replaced by boat metric]

Year Agency Reach Date

Drainage

area

(mi2)

Total

species

N(V)

Darter

species

N(V)

Sunfishspecies

N(V)

Sucker

species

N(V)

Intolerant

species

N(V)

Tolerant

species

%(V)

Omnivores

%(V)

Insectivores

%(V)

Top

carnivores

%(V)

Number per

0.3 or 1.0

km N(V)

Simple

lithophils

%(V)

DELT

anomalies

%(V)

IBI MIwb
10 Comparison of U.S. Geological Survey and Ohio Environmental Protection Agency Fish-Collection Methods

Figure 3. Index of Biotic Integrity and Modified

Index of Well-Being scores plotted against the

relative number of fish collected in the Lake

Erie-Lake St. Clair Basin. (Axes are ratios, U.S.

Geological Survey (USGS)/Ohio Environmental

Protection Agency (OEPA). A data point greater

than 1.0 indicates the USGS scored higher,

whereas a data point below 1.0 indicates the

OEPA scored higher.)

Data comparability and sources of data

variability

In order to determine the limits of exchanging fishcommunity data, this study design included possible

sources of variability by allowing each agency to use

its own fish-sampling protocol. Variability in IBI and

MIwb scores can be affected by temporal, spatial, and

sampling differences, and (or) by anthropogenic

sources. Variability from spatial and temporal differences in sampling was minimized in this study

because the sampling was done in the same reaches

during the same seasons. Anthropogenic sources of

variability, as reflected in land use/cover among the 10

study sites, differed considerably; however, only the

potential anthropogenic effects at the most disturbed

sites were examined in this study.

Index of Biotic Integrity scores

Most of the differences in IBI scores fell within the

OEPA range of “insignificant departure” (4 or fewer

IBI points) (Ohio Environmental Protection Agency,

1987). In other words, a difference of 4 or fewer IBI

points could be accounted for by natural or background variability. Differences of greater than 4 IBI

points directed further analysis. Rankin and Yoder

(1990) conclude that those rivers most affected by

human degradation exhibit the most variability in IBI

scores. Perhaps this was the case where the difference

in IBI scores was much greater than 4 (for example,

the Clinton River, reach A).

The differences greater than 4 IBI points may

represent sampling variability in some form. Sampling

variability can include, but is not limited to, electroshocking methods, sampling equipment, water conditions during sampling, amount of fishing effort (as a

function of time), and technical skill level of the crew.

Although the quantitative requirements for sampling

fish between the USGS and OEPA were not the same,

the differences in requirements would be easy to reconcile. The requirements specify the number of

passes, the number of crew members, the equipment to

use, and the length of the reaches to be fished. Numerous suggestions in the sampling protocols, however,

leave room for individual operator preference and

allow subjective decisions that come with experience;

hence, the exact sampling approach at a site is difficult

to replicate. The length of time and pattern that electrical current is applied to the water can be variable.

Electricity can be applied continuously or sporadically. Another variable, in-stream movement of the

sampling effort, is under the control of the operator.

One technique is to collect fish in a zig-zag pattern

from bank to bank. Natural barriers, such as riffles,

can be used to herd the fish. The habitat features to

sample is another decision that depends on the individual operator.

0 2.2 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0

RELATIVE NUMBER OF FISH,

USGS/OEPA

0

3.0

0.5

1.0

1.5

2.0

2.5

INDEX OF BIOTIC INTEGRITY,

USGS/OEPA

0 1.4 0.2 0.4 0.6 0.8 1.0 1.2

0.4

1.4

0.6

0.8

1.0

1.2

MODIFIED INDEX OF WELL-BEING,

USGS/OEPA
Data comparability and sources of data variability 11

Figure 4. Differences between U.S. Geological Survey and Ohio Environmental Protection Agency for

each metric of the Index of Biotic Integrity at stream sites in the Lake Erie-Lake St. Clair Basin. (Sampling

sites with A, B, and C correspond to the three reaches that were sampled by each agency in the specified

river.)

-4

4

0

-4

4

0

-4

4

0

-4

4

0

-4

4

0

-4

4

0

DIFFERENCE BETWEEN INDEX OF BIOTIC INTEGRITY METRIC SCORE

GRAND RIVER, 1996

GRAND RIVER, 1997 A

GRAND RIVER, 1997 B

GRAND RIVER, 1997 C

MAUMEE RIVER, NEW HAVEN, 1996

MAUMEE RIVER, WATERVILLE, 1996

-4

4

0

-4

4

0

TOTAL SPECIES

DARTER SPECIES

SUNFISH SPECIES

SUCKER SPECIES

INTOLERANT SPECIES

TOLERANT SPECIES

OMNIVORES

INSECTIVORES

TOP CARNIVORES

NUMBER PER 0.3 OR 1.0 KM

SIMPLE LITHOPHILS

DELT ANOMALIES

-4

4

0

MAUMEE RIVER, WATERVILLE, 1997 C

MAUMEE RIVER, WATERVILLE, 1997 A

MAUMEE RIVER, WATERVILLE, 1997 B
12 Comparison of U.S. Geological Survey and Ohio Environmental Protection Agency Fish-Collection Methods

Figure 4. Differences between U.S. Geological Survey and Ohio Environmental Protection Agency for each

metric of the Index of Biotic Integrity at stream sites in the Lake Erie-Lake St. Clair Basin—Continued.

-4

4

0

-4

4

0

-4

4

0

DIFFERENCE BETWEEN INDEX OF BIOTIC INTEGRITY METRIC SCORES

ST. JOSEPH RIVER, 1996

AUGLAIZE RIVER, 1996

RIVER RAISIN, 1996

-4

4

0

-4

4

0

-4

4

0

-4

4

0

-4

4

0

TOTAL SPECIES

DARTER SPECIES

SUNFISH SPECIES

SUCKER SPECIES

INTOLERANT SPECIES

TOLERANT SPECIES

OMNIVORES

INSECTIVORES

TOP CARNIVORES

NUMBER PER 0.3 OR 1.0 KM

SIMPLE LITHOPHILS

DELT ANOMALIES

-4

4

0

BLACK RIVER, 1996

CUYAHOGA RIVER, 1996

CLINTON RIVER, 1996

CLINTON RIVER, 1997 A

CLINTON RIVER, 1997 B

CATTARAUGUS CREEK, 1996
Data comparability and sources of data variability 13

Figure 5. Percentage of attainment of Warmwater Habitat criteria for Index of Biotic Integrity and Modified

Index of Well-Being scores for streams in the Lake Erie-Lake St. Clair Basin. (Sampling sites with A, B, and C

correspond to the three reaches that were sampled by each agency in the specified river. For sites that fall

into an ecoregion with no criteria for warmwater habitat, percent attainment was calculated using the Ohio

Environmental Protection Agency (1987) narrative criteria for “Good”.) PERCENT ATTAINMENT OF WARMWATER HABITAT CRITERIA

20

160

40

60

80

100

120

140

U.S. GEOLOGICAL SURVEY

OHIO ENVIRONMENTAL

PROTECTION AGENCY

GRAND RIVER 1996

GRAND RIVER 1997 AGRAND RIVER 1997 B

GRAND RIVER 1997 C

MAUMEE RIVER AT NEW HAVEN 1996

MAUMEE RIVER AT WATERVILLE 1996

MAUMEE RIVER AT WATERVILLE 1997 C

MAUMEE RIVER AT WATERVILLE 1997 AMAUMEE RIVER AT WATERVILLE 1997 B

ST. JOSEPH RIVER 1996

AUGLAIZE RIVER 1996

RIVER RAISIN 1996

BLACK RIVER 1996

CUYAHOGA RIVER 1996

CLINTON RIVER 1996

CLINTON RIVER 1997 ACLINTON RIVER 1997 B

CATTARAUGUS CREEK 1996

0

140

20

40

60

80

100

120

MODIFIED INDEX OF WELL-BEING

INDEX OF BIOTIC INTEGRITY
14 Comparison of U.S. Geological Survey and Ohio Environmental Protection Agency Fish-Collection Methods

One evident source of sampling variability was

the method—boat or wading—of fish collection used

(table 3), and results may indicate that fish data

obtained using the two methods cannot be compared.

Two IBI metrics do not compare when different methods are used: relative numbers of fish and percentage

of darter species or round-bodied suckers.

The major differences in the relative numbers of

fish are a direct result of the calculation of the IBI and

greater capture rates. This has implications on many of

the results and may have been avoided had the same

methods been selected. The number of fish collected is

calculated per 0.3 and 1.0 km for wading and boat

methods, respectively, in order to normalize the number of fish captured and allow comparison of data collected by the same method. In those instances when

the USGS used the wading method and the OEPA used

the boat method, the calculated number of fish caught

per reach was much lower for USGS. For example, the

OEPA caught approximately 143 fish at one 0.5 km

reach (boat), whereas the USGS captured 135 fish in

0.5 km (wading). Converting the number of fish using

the boat method calculations, the OEPA caught 286

fish per 1.00 km; using the wading method calculations, the USGS captured 81 fish in 0.3 km. The OEPA

had a metric score of 3, whereas the USGS scored 1.

The boat-site criterion is actually lower in terms of the

numbers of fish required to meet that criterion. Thus,

because the number of fish captured by the wading

method is normalized with a shorter distance than for

the boat method, the relative-number metric does not

accurately compare scores if both methods are used at

the same site.

The use of number of darter species or percentage of round-bodied suckers as an IBI metric depends

on the electroshocking methods: for wading sites,

number of darter species is used, whereas for boat

sites, the percentage of round-bodied suckers is used.

When the USGS used wading methods and the OEPA

used boat methods, the USGS scored lower on this

metric, although the differences were not significant.

Again, this metric does not accurately compare scores

if both methods are used at the same site.

Sampling results can be affected by the type of

electrofishing equipment used. One potential source of

sampling variability might have been the differing

numbers of fish captured due to the use of different

equipment, especially in 1996. The USGS used a less

powerful electroshocker during 1996 (table 1) and the

OEPA consistently collected a higher number of fish

for most sites that year (fig. 3).

Besides being a source of variability in and of

itself, the number of fish collected can influence all of

the metrics of the IBI in which a percentage is calculated. If the relative number (number per specified distance) of fish collected is less than 50 individuals, then

the metrics are adjusted for percentages of tolerant

fishes, omnivores, insectivores, top carnivores, simple

lithophils, and DELTs. These adjustments (called lowend adjustments) reflect the low ecosystem health and

skewness exerted on the those metrics that often

results from such low numbers (Ohio Environmental

Protection Agency, 1987). For samples of 50 to 200

fish (relative number, including tolerants), these same

metrics can also be low-end adjusted if the metric data

meet certain requirements. These adjustments were

based on many reference sites (Ohio Environmental

Protection Agency, 1987). This study involved 18

samples from 10 study sites. Because of the small

sample size, the cutoff point of 50 individuals caused

large differences between the USGS and OEPA IBI

scores in certain situations. For example, the 1997

USGS and OEPA IBI scores at reach A in the Clinton

River were 38 and 14, respectively. The USGS collected 69 fish and the OEPA collected 40, a difference

of 29 fish. If the USGS had caught fewer fish, the

adjustments for low numbers would have resulted in a

smaller difference in the IBI scores.

A large change in streamflow can affect the collection of fish. Increased flow and decreased clarity

can reduce sampling effectiveness (Ohio Environmental Protection Agency, 1987). The fish-collection protocols of both agencies indicate that sampling should

be done during stable-flow conditions for this reason;

however, the large difference in the numbers of fish

between the two agencies prompted an evaluation of

the streamflow data. Streamflow records were examined for one week prior to sampling. The three samples of highest concern were those collected by the

OEPA at the Grand River on October 3, 1996, by the

USGS at the Auglaize River on July 26, 1996, and by

the OEPA at Cattaraugus Creek on October 2, 1996.

Greater magnitudes of change in streamflow were

expected to correlate closely with numbers of fish captured, but, in fact, no relation was found between daily

streamflow and numbers of fish captured.

The amount of time that electricity was applied

to the water was recorded in 1997. This measure is one

way to indirectly explain numbers of fish captured.
Data comparability and sources of data variability 15

Greater shocking times were expected to correlate

closely with greater numbers of fish. The different

number of passes performed by each agency adds

some difficulty to the analysis. The total shock time

for the USGS was divided by 2 to represent one sampling pass. Correspondingly, the number of fish collected by the USGS should also be divided by 2;

however, the number of fish captured for the first pass

is usually higher than any subsequent passes, so comparing an average number of fish would be a misrepresentation of reality. A comparison of the USGS and

OEPA electroshocking times did not reveal a relation

to the number of fish captured. At the Maumee River

at Waterville, the USGS applied a longer shocking

time (than did OEPA), but collected fewer fish. This

result may be attributable to the OEPA’s use of the

boat method (table 3). For the Grand River, the shock

times for the OEPA were greater and produced only

slightly greater numbers of fish.

In summary, the number of fish collected is a

major component of many of the factors affecting the

comparability of IBI scores between the USGS and

OEPA. Two major considerations arise from this

investigation that relate directly to the number of fish

captured. First, because of the small numbers of fish

collected by the USGS at some of the sites, not all of

the metrics measured by the IBI may be adequately

represented, especially where the USGS chose totebarge wading methods and OEPA chose boat methods

(table 3). This has implications on many of the results

and may have been avoided had the same methods

been selected. Because the scoring of metrics in the

IBI differs depending on the method used, problems

can occur with results not falling into the calibration

range intended for a given site (Yoder and Smith,

1999) and with differences in how low-end adjustments are applied. Second, the OEPA performs one

pass on each of two separate visits and then combines

the data; between passes, there is sufficient time for

fish to repopulate the area; resulting in greater apparent OEPA sampling effectiveness compared to that of

the USGS.

Modified Index of Well-Being scores

Similar IBI scores do not necessarily signify low sampling variability. Because it is a multimetric biological

index that incorporates several factors, the IBI is not

extremely sensitive to the total numbers of fish collected. For this reason, the MIwb was also included in

the analysis.

Three components make up and affect the MIwb

scores: the numbers of fish, the weights of the fish,

and the percentage of tolerant fish collected. As discussed previously, the numbers of fish collected by the

OEPA were considerably higher than those of the

USGS. In only four instances did the USGS collect

more fish than the OEPA; thus, it follows that this

would help explain why the MIwb scores computed by

the OEPA were usually higher than those of the USGS

(fig. 2). Of the four times when the USGS had higher

MIwb scores than the OEPA, only two of the differences were greater than the 0.5 accounted for by natural variation: reach A in the Grand River, 1997, and

the Cuyahoga River, 1996 (fig. 2). The OEPA caught

more fish in reach A of the Grand River, but 25 percent of those fish were tolerant species. This lowered

the OEPA-MIwb compared to the USGS score. In the

Cuyahoga River, the number of fish and percentage of

tolerant fish species caught by each agency were similar, an indication that the USGS captured larger fish.

Of the remaining MIwb scores, the main metric causing the large differences was the higher number of fish

collected by the OEPA. As with the IBI, the differences between use of the wading and boat methods,

which affected relative numbers of fish collected, were

a major influence on differences in MIwb scores.

Comparison of index scores in relation to

aquatic-life criteria

The OEPA has established numeric aquatic-life criteria on the basis of the regional reference-site concept

(Yoder and Rankin 1995; Simon and Lyons, 1995).

The various ecoregions in Ohio have differing levels

of “tolerance, resilience, and attainable quality of ecosystems” (Omernik, 1995), which are accounted for in

these criteria. IBI and MIwb results are shown in figure 5 as a percentage of the attainment of the Warmwater Habitat (WWH) criteria for the ecoregions in

which the sampling sites were located. The WWH-use

designation is the most commonly applied aquatic-life

use designation in Ohio (Yoder and Rankin, 1995).

This and other aquatic-life use designations are based

on the potential to support a healthy fish community.

The goal, then, as presented in the Clean Water Act

and supported by the aquatic-life criteria, is to maintain or improve the integrity of the aquatic ecosystem.

The IBI and MIwb scores have been directly compared throughout most of this report. Perhaps comparing the attainment of an aquatic-life use mandated by

law would be a more relevant analysis with respect to
16 Comparison of U.S. Geological Survey and Ohio Environmental Protection Agency Fish-Collection Methods

how well fish-community data can be shared for purposes of assessing and maintaining the integrity of

aquatic ecosystems. The results of the comparison

done in this study show that the fish communities, as

measured by the attainment of aquatic-life use designations are similar for the two agencies. With respect

to the IBI, there were only 2 sampled reaches out of 18

where one agency’s data met the WWH criteria (100

percent attainment) and the other’s did not. With

respect to the MIwb, there were only 4 such reaches

out of 17.

Summary and conclusions

The Index of Biotic Integrity and Modified Index of

Well-Being can be used to help evaluate aquatic ecosystem health. A comparison of these two indices was

used to determine the feasibility and limitations of

fish-community data exchange between U.S. Geological Survey and Ohio Environmental Protection

Agency programs.

The analysis indicated that the USGS and OEPA

IBI scores were similar, although OEPA tended to

report higher IBI scores. However, the median of differences of IBI scores was not statistically different

from zero.

Small differences in the individual IBI metric

scores were found between the two agencies. Several

factors may have contributed to these differences in

the form of temporal, spatial, sampling, and (or)

anthropogenic variability. IBI scores for rivers that

have been affected by major anthropogenic activity are

more variable than those in less affected streams

(Rankin and Yoder, 1990). Another possible factor is

that low-end adjustments may have inflated the differences between certain metrics when small numbers of

fish were collected. Calculation of relative numbers of

fish at the same site based on two different methods

(wading and boat) can also cause differences in IBI

scores.

The MIwb scores were considerably different

between the two agencies, OEPA having higher

scores. This finding was attributed to the higher

reported numbers of fish captured by the OEPA.

Despite the differing MIwb scores, there were only

four instances where the OEPA MIwb values indicated

the stream met the Warmwater Habitat criteria and the

corresponding USGS values did not.

On the basis of IBI scores alone, the fish-sampling results of the two agencies are comparable.

Examination of the MIwb scores highlights differences in the fish data, specifically in the numbers of

fish captured by each agency. Yet, if both agencies’

results for the two indices are viewed relative to the

percentage attainment of Ohio Warmwater Habitat criteria, considerable data comparability is once again

evident.

One common factor, the number of fish captured, drives most of the differences in IBI and MIwb

scores between the two agencies. The OEPA consistently collected more fish, for several possible reasons:

differences in electroshocking equipment (particularly

in 1996), the type of electrofishing method used (boat

or wading) and the associated difference in how the

fish-number metric in the IBI was calculated, differences in streamflow, unknown influences of samplingcrew experience, and the OEPA approach of one sampling pass each on two separate visits, thus allowing a

period of time for fish to possibly repopulate the area.

There are several areas in which the use of similar sampling approaches by the two agencies would

minimize the differences in numbers of fish collected

and, thus, the variability in the comparison and

exchange of fish-community data. These include the

following:

• Use of electroshocking equipment comparable in

output power.

• Choice of the identical method of electroshocking

based on the depth, width, and flow of the river (if

there is a question as to which method to use and

a check of past electrofishing methods used at that

site for a reference).

• No collection of fish if streamflow is changing

quickly.

• Continued training of field crews on electroshocking methods.

• Interagency communication on specific issues to

help facilitate data exchange.

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Karr, J.R., 1981, Assessment of biotic integrity using fish

communities: Fisheries, v. 6, p. 21-27.
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