&ER&
United States
Environmental Protection
Agency
Office of
Water
(WH-553)
EPA/440/4-89/001
May 1989
Rapid Bioassessment
Protocols for Use in
Streams and Rivers
, V
Benthic
Macroiinvertebrates and
Fish
Previously Published as EPA/444/4j89-u01
-------
RAPID BIOASSESSMENT PROTOCOLS
FOR USE IN STREAMS AND RIVERS:
BENTHIC MACROINVERTEBRATES AND FISH
by
James L.
Michael T. Barbour
Kimberly D. Porter
Sharon K. Gross
Robert M. Hughes
(a)U.S. Environmental Protection Agency
Assessment and Watershed Protection Division
401 M Street, S.W.
Washington, D.C. 20460
-------
Notice
This document has been reviewed in accordance with U.S. Environmental
Protection Agency policy and approved for publication. Mention of trade names
or commercial products does not constitute endorsement or recommendation
for use.
-------
FOREWORD
In December 1986, U.S. EPA's Assistant Administrator for Water initiated a major study of the Agency's sur-
face water monitoring activities. The resulting report, entitled "Surface Water Monitoring: A Framework for
Change" (U.S. EPA 1987), emphasizes the restructuring of existing monitoring programs to better address the
Agency's current priorities, e.g., toxics, nonpoint source impacts, and documentation of "environmental results."
The study also provides specific recommendations on effecting the necessary changes. Principal among these are:
1. To issue guidance on cost-effective approaches to problem identification and trend assessment.
2. To accelerate the development and application of promising biological monitoring techniques.
In response to these recommendations, the Assessment and Watershed Protection Division has developed rapid
bioassessment protocols designed to provide basic aquatic life data for planning and management purposes such as
screening, site ranking, and trend monitoring. All of the protocols utilize fundamental assessment techniques to
generate basic information on ambient physical, chemical, and biological conditions. Level of assessment and level
of effort vary with successive protocols, and choice of a given protocol should depend on the specific objective of
the monitoring activity and available resources. Although none of the protocols are meant to provide the rigor of
fully comprehensive studies, each is designed to supply pertinent, cost-effective information when applied in the
appropriate context.
Martha G. Prothro
Director, Office of Water Regulations and Standards
U.S. EPA, Washington, D.C.
in
-------
DEDICATION TO DR. JAMES L. PLAFKIN
All of us in the Environmental Protection Agency (EPA) owe an immeasurable debt of
gratitude to Dr. James L. Plafkin. In addition to developing this document, Jim was a driving
force within EPA to increase the use of biology in the water pollution control program until his
untimely death on February 6, 1990. Throughout his decade-long career with EPA, his expertise
in ecological assessment, his dedication, and his vision were instrumental in changing commonly-
held views of what constitutes pollution and the basis for pollution control programs. Jim will
be remembered for his love of life, his enthusiasm, and his wit. As a small token of our esteem,
we dedicate this document to his memory.
IV
-------
ACKNOWLEDGMENTS
Dr. James L. Plafkin of the Assessment and Watershed Protection Division (AWPD) served as principal editor
and coauthor of this document. Other coauthors were consultants Michael T. Barbour, Kimberly D. Porter, and
Sharon Gross working for AWPD and Dr. Robert M. Hughes working for EPA's Corvallis Research Laboratory.
Many others also contributed to the development of this document and deserve special thanks. First and fore-
most, the Rapid Bioassessment Workgroup. The Workgroup, composed of both State and EPA Regional biologists
(listed in Chapter 1), was instrumental in providing a framework for the basic approach and served as primary
reviewers of various drafts. Dr. Kenneth Cummins and Dr. William Hilsenhoff provided invaluable advice on for-
mulating certain assessment metrics, and Dr. Anthony Maciorowski and Paul Leonard supplied helpful editorial
comments on the final drafts. Special thanks go to the biologists in the field (well over a hundred) who con-
tributed their valuable time to review the document and provide constructive input. Their help in this endeavor is
sincerely appreciated.
-------
TABLE OF CONTENTS
Page
FOREWORD iii
ACKNOWLEDGMENTS v
LIST OF FIGURES xi
LIST OF TABLES xv
1. INTRODUCTION 1-1
1.1 Purpose of the Document 1-1
1.2 Development of This Document 1-1
1.3 A Framework for Implementing the Rapid Bioassessment Protocols 1-2
2. THE CONCEPT OF BIOMONITORING 2-1
2.1 Biosurveys, Bioassays, and Chemical Monitoring 2-1
2.2 Use of Different Taxonomic Groups in Biosurveys 2-2
2.3 Station Siting 2-3
2.4 Importance of Habitat Assessment 2-4
2.5 The Ecoregion Concept 2-4
2.6 Data Management and Analysis 2-6
2.6.1 Integration into BIOS 2-6
2.6.2 Computerizing Field Data for Calculation of the Metrics 2-6
2.7 Benthic Community Considerations 2-6
2.7.1 Seasonality for Benthic Collections 2-6
2.7.2 Benthic Sampling Methodology 2-9
2.7.2.1 Natural and Artificial Substrates 2-9
2.7.2.2 Single and Multiple Habitat Sampling 2-11
2.7.2.3 Sampling Coarse Paniculate Organic Material (CPOM) 2-11
2.7.3 Benthic Sample Processing and Enumeration 2-12
2.7.4 Benthic Environmental Tolerance Characterizations 2-12
2.8 Fish Community Considerations 2-12
2.8.1 Seasonality for Fish Collections 2-12
2.8.2 Fish Sampling Methodology 2-13
2.8.2.1 Use of Electrofishing, Seining, and Rotenoning 2-13
2.8.2.2 Sampling Representative Habitat 2-13
2.8.3 Fish Sample Processing and Enumeration 2-14
2.8.4 Fish Environmental Tolerance Characterizations 2-14
3. OVERVIEW OF PROTOCOLS AND SUMMARY OF COMPONENTS 3-1
3.1 Summary of the Protocols 3-1
3.2 Objectives of the Protocols 3-1
3.3 Level of Effort and Investigator Expertise 3-1
4. QUALITY ASSURANCE/QUALITY CONTROL 4-1
4.1 Program Description 4-1
4.2 Data Quality Objectives 4-1
4.3 Quality Assurance Program Plans and Project Plans 4-1
vn
-------
4.4 EPA Responsibilities 4-2
4.5 Importance of QA/QC for Rapid Bioassessments 4-2
5. HABITAT ASSESSMENT AND PHYSICOCHEMICAL PARAMETERS 5-1
5.1 Physical Characteristics and Water Quality 5-1
5.1.1 Physical Characterization 5-1
5.1.2 Water Quality 5-3
5.2 Habitat Assessment 5-3
5.2.1 Primary Parameters—Substrate and Instream Cover 5-4
5.2.2 Secondary Parameters—Channel Morphology 5-7
5.2.3 Tertiary Parameters—Riparian and Bank Structure 5-7
6. BENTHIC MACROINVERTEBRATE BIOSURVEY AND DATA ANALYSIS 6-1
6.1 Rapid Bioassessment Protocol I—Benthic Macroinvertebrates 6-1
6.1.1 Field Methods 6-1
6.1.2 Data Analysis Techniques 6-1
6.2 Rapid Bioassessment Protocol II—Benthic Macroinvertebrates 6-4
6.2.1 Field Methods 6-4
6.2.1,1 Sample Collection 6-4
6.2.1.2 Sample Sorting and Identification 6-7
6.2.2 Data Analysis Techniques 6-10
6.3 Rapid Bioassessment Protocol HI—Benthic Macroinvertebrates 6-16
6.3.1 Field Methods 6-16
6.3.1.1 Sample Collection 6-16
6.3.1.2 Field Processing of the CPOM Sample 6-18
6.3.2 Lab Methods 6-18
6.3.2.1 Sample Sorting and Identification 6-18
6.3.3 Data Analysis Techniques 6-19
6.4 Results of a Pilot Study Conducted on the Ararat and Mitchell Rivers, North Carolina 6-26
6.4.1 Introduction 6-26
6.4.2 Methods 6-28
6.4.2.1 Field Collections 6-28
6.4.2.2 Laboratory Processing 6-30
6.4.2.3 Quality Assurance 6-30
6.4.3 Bioclassification of Stations Based on the North Carolina DEM Protocol 6-30
6.4.4 Selection of Metrics 6-32
6.4.5 Comparison of Multihabitat vs. Single Habitat Collections 6-33
6.4.6 Evaluation of the 100-Organism Subsample 6-38
6.4.7 Family-Level vs. Species-Level Identification 6-38
6.4.8 Integrated Bioassessment 6-39
7. FISH BIOSURVEY AND DATA ANALYSIS 7-1
7.1 Rapid Bioassessment Protocol IV—Fish '. 7-1
7.1.1 Design of Fish Assemblage Questionnaire Survey 7-1
7.1.2 Response Analysis 7-1
7.2 Rapid Bioassessment Protocol V—Fish 7-5
7.2.1 Field Survey Methods 7-5
7.2.1.1 Sample Collection 7-5
7.2.1.2 Sample Processing 7-9
7.2.2 Data Analysis Techniques 7-9
7.2.2.1 Description of IBI Metrics 7-12
7.3 Results of Pilot Studies in Ohio and Oregon 7-20
7.3.1 Methods 7-20
7.3.2 Results and Interpretation '. 7-20
Vlll
-------
8. INTEGRATION OF HABITAT, WATER QUALITY, AND BIOSURVEY DATA 8-1
8.1 The Relationship Between Habitat Quality and Biological Condition 8-1
8.2 Bioassessment Technique 8-3
8.3 An Integrated Assessment Approach 8-5
8.4 Case Study 8-16
REFERENCES R-l
APPENDIX A: GUIDANCE FOR USE OF FIELD AND LABORATORY DATA SHEETS
A. 1 Guidance for Header Information A-l
A.2 Guidance for Biosurvey Field Data Sheet for Behthic RBPs I, II, and III A-l
A.3 Guidance for Impairment Assessment Sheet for RBPs I, II, III, and V A-2
A.4 Guidance for Data Summary Sheet for Benthic RBPs II and III A-2
A.5 Guidance for Laboratory Bench Sheet for Benthic RBP III A-4
A.6 Guidance for Field Collection Data Sheet for Fish RBP V A-4
A.7 Guidance for Data Summary Sheet for Fish RBP V A-5
APPENDIX B: RAPID BIOASSESSMENT SUBSAMPLING METHODS FOR BENTHIC PROTOCOLS
II AND III (100-Organism Count Technique)
B.I Rapid Bioassessment Subsampling Methods for Protocol II B-l
B.2 Rapid Bioassessment Subsampling Methods for Protocol III B-l
APPENDIX C: FAMILY AND SPECIES-LEVEL MACROINVERTEBRATE TOLERANCE
CLASSIFICATIONS
C. 1 Family-Level Tolerance Classification C-l
C.2 Genus/Species-Level Tolerance Classification .• C-l
C.3 References for Determining Family and Species-Level Tolerance Classifications C-l
C.4 A Partial Listing of Agencies That Have Developed Tolerance Classifications and/or Biotic
Indices C-4
APPENDIX D: TOLERANCE, TROPHIC GUILDS, AND ORIGINS OF SELECTED FISH SPECIES
D.I Species-Level Fish Tolerance, Trophic, and Origin Classifications D-l
D.2 Selected References for Determining Fish Tolerance, Trophic, Reproductive, and Origin
Classifications D-7
D.3 Agencies Currently Using or Evaluating Use of the IBI for Water Quality Investiga-
tions D-l 1
IX
-------
LIST OF FIGURES
Page
1.3-1 Bioassessment decision matrix 1-4
2.5-1 Ecoregions of the conterminous United States 2-5
2.5-2 Flowchart illustrating potential delineation of reference sites within an ecoregion 2-7
2.6-1 Header information used for documentation and identification of sampling stations 2-8
2.7-1 Classification of U.S. climatological regions 2-10
3.2-1 Overview of the five bioassessment approaches and their primary objectives 3-4
5.1-1 Physical Characterization/Water Quality Field Data Sheet for use with all Rapid Bioassessment
Protocols 5-2
5.2-1 Habitat Assessment Field Data Sheet for use with all Rapid Bioassessment Protocols 5-5
6.1-1 Biosurvey Field Data Sheet for use with Rapid Bioassessment Protocol I 6-2
6.1-2 Impairment Assessment Sheet for use with macroinvertebrate Rapid Bioassessment Protocols 6-3
6.2-1 Biosurvey Field Data Sheet for use with Rapid Bioassessment Protocol II 6-6
6.2-2 Data Summary Sheet suggested for use in recording benthic data utilized in Rapid Bioassessment
Protocol II 6-8
6.2-3 Flowchart of bioassessment approach advocated for Rapid Bioassessment Protocol II 6-12
6.3-1 Biosurvey Field Data Sheet for use with Rapid Bioassessment Protocol III 6-17
6.3-2 Laboratory Bench Sheet suggested for use in recording benthic data utilized in Rapid Bioassessment
Protocol III 6-20
6.3-3 Data Summary Sheet suggested for use in recording benthic data utilized in Rapid Bioassessment
Protocol III 6-23
6.3-4 Flowchart of bioassessment approach advocated for Rapid Bioassessment Protocol III 6-27
6.4-1 Pilot study station locations, Ararat River, North Carolina, September 1986 6-29
6.4-2 Cluster analysis results for benthic community metrics, based on 100-organism subsamples from riffle
samples collected on the Ararat and Mitchell Rivers 6-33
6.4-3 Comparison of taxa richness for all field-sorted samples collected on the Ararat and Mitchell
Rivers 6-36
6.4-4 Station cluster analysis results for field-sorted riffle samples collected on the Ararat and Mitchell
Rivers 6-37
xi
-------
6.4-5 Station cluster analysis results for 100-organism subsamples from riffle samples collected on the Ararat
and Mitchell Rivers 6-37
6.4-6 Station cluster analysis results for 300-organism subsamples from riffle samples collected on the Ararat
and Mitchell Rivers 6-38
6.4-7 Cluster analysis results for benthic community metrics, based on family-level identifications of
100-organism subsamples from riffle samples collected on the Ararat and Mitchell Rivers 6-39
6.4-8 Station cluster analysis results for benthic community metrics, based on family-level identifications of
100-organism subsamples from riffle samples collected on the Ararat and Mitchell Rivers 6-39
7.1-1 Fish assemblage questionnaire for use with Rapid Bioassessment Protocol IV 7-2
7.2-1 Impairment Assessment Sheet for use with fish Rapid Bioassessment Protocol V 7-7
7.2-2 Flowchart of bioassessment approach advocated for Rapid Bioassessment Protocol V 7-8
7.2-3 Fish Field Collection Data Sheet for use with Rapid Bioassessment Protocol V 7-10
7.2-4 Total number of fish species versus watershed area for Ohio regional reference sites 7-16
7.2-5 Data Summary Sheet for Rapid Bioassessment Protocol V 7-19
7.3-1 Locations of regional reference sites in Ohio 7-20
7.3-2 Locations of sampling sites on the mainstem Willamette River, Oregon 7-21
7.3-3 Index of Biotic Integrity scores by Ohio ecoregion 7-22
7.3-4 Dominant Ohio fish species by ecoregion 7-23
7.3-5 Patterns in mainstem Willamette River fish assemblages as revealed by detrended correspondence
analysis /:. 7-25
7.3-6 Longitudinal trends in Index of Biotic Integrity and nitrate in the Willamette River 7-26
8.1-1 The relationship between habitat and biological condition 8-1
8.1-2 Relationship of habitat quality and biological condition in the context of water quality 8-2
8.2-1 Range of sensitivities of Rapid Bioassessment Protocol II and III benthic metrics in assessing biological
condition in response to organics and toxicants 8-3
8.2-2 Range of sensitivities of Rapid Bioassessment Protocol V fish metrics in assessing biological
condition 8-4
8.3-1 Evaluation of habitat at a site-specific control relative to that at a regional reference 8-5
8.3-2 Evaluation of water quality effects 8-7
8.3-3 Evaluation of biological impairment due to reversible habitat alterations 8-8
8.3-4 Evaluation of an alternative site-specific control station 8-10
XII
-------
8.3-5 Bioassessment using a site-specific control station 8-11
8.3-6 Bioassessment using a regional reference 8-15
8.4-1 The relationship between habitat quality and benthic community condition at the North Carolina pilot
study site 8-19
8.4-2 Pilot study results applied to the theoretical habitat versus biological condition curve 8-19
Xlll
-------
LIST OF TABLES
Page
3.1-1 Comparison of Rapid Bioassessment Protocols 3-2
6.2-1 Criteria for characterization of biological condition for Rapid Bioassessment Protocol II 6-11
6.3-1 Criteria for characterization of biological condition for Rapid Bioassessment Protocol III 6-21
6.4-1 Bioclassification results for North Carolina DEM multihabitat benthic samples collected from the Ararat
and Mitchell Rivers, 23-24 September 1986 6-31
6.4-2 Taxa richness, by group, for samples collected by North Carolina DEM from the Ararat and Mitchell
Rivers 6-32
6.4-3 Metric values, percent comparison, and bioassessment scores for benthic pilot study results: 100-, 200-,
and 300-organism subsample data 6-34
6.4-4 Metric values, percent comparison, and bioassessment scores for benthic pilot study results: EA field-
sorted and family level identification data .. . 6-35
6.4-5 Summary of the bioclassification derived from an analysis of samples collected from the Ararat and
Mitchell Rivers 6-40
7.2-1 Regional variations of IBI metrics 7-13
7.3-1 Collection data for two Ohio ecoregion reference sites 7-21
7.3-2 Scoring criteria and IBI and IWB scores for two Ohio ecoregion reference sites 7-22
7.3-3 Collection data (number of individuals) for two sites on the Willamette River, Oregon 7-24
7.3-4 Scoring criteria and IBI and IWB scores for two sites on the Willamette River, Oregon 7-25
8.3-1 Bioassessment conclusions relative to use of a site-specific control or regional reference 8-12
8.4-1 Summary of habitat assessment scoring for Ararat and Mitchell Rivers benthic case-study
data 8-17
8.4-2 -Summary of metric values, percent comparison, and bioassessment scores for Ararat and Mitchell Rivers
benthic case-study data 8-18
C-l Tolerance values for families of stream arthropods in the western Great Lakes region C-2
C-2 Tolerance values for some macroinvertebrates not included in Hilsenhoff (1982, 1987b) C-3
D-l Tolerance, trophic guilds, and origins of selected fish species D-l
xv
-------
1. INTRODUCTION
1.1 PURPOSE OF THE
DOCUMENT
The primary purpose of this document is to pro-
vide States with a practical technical reference for
conducting cost-effective biological assessments of
lotic systems. The protocols presented are not neces-
sarily intended to replace those already in use by State
agencies. Instead, they provide options for agencies
that wish to implement rapid biological assessment
techniques. Three macroinvertebrate and two fish pro-
tocols are presented: Benthic Rapid Bioassessment
Protocol I (RBP I) and fish Rapid Bioassessment Pro-
tocol IV (RBP IV) are cost-effective screening proce-
dures that provide some supporting data; benthic
Rapid Bioassessment Protocol II (RBP II) can help set
priorities for more intensive evaluations; and benthic
Rapid Bioassessment Protocol III (RBP III) and fish
Rapid Bioassessment Protocol V (RBP V) are progres-
sively more rigorous and provide more confirmational
data, but also require more resources. The choice of a
particular protocol should depend on the purpose of
the bioassessment, the need to document conclusions
with confirmational data, the degree of discrimination
desired, and available resources. Although the benthic
protocols were designed and tested in wadable fresh-
water streams rather than large rivers (or lakes, estu-
aries, or marine systems), the fundamental approach
should be applicable to large freshwater rivers as well.
The fish protocols were validated in freshwater
streams and large rivers and are applicable to both.
The original rapid bioassessment protocols were
designed as inexpensive screening tools for determin-
ing if a stream is supporting or not supporting a
designated aquatic life use. The basic information
generated would enhance the coverage of broad
geographical assessments, such as State and National
305(b) Water Quality Inventories. However, members
of a 1986 benthic Rapid Bioassessment Workgroup
and reviewers of this document indicated that the
rapid bioassessment protocols can also be applied to
otrler program areas, for example:
• Characterizing the existence and severity of use
impairment
• Helping to identify sources and causes of use
impairment
• Evaluating the effectiveness of control actions
• Supporting use attainability studies
• Characterizing regional biotic components
Therefore, the scope of this guidance might now be
considered applicable to a wider range of planning
and management purposes than originally envisioned,
i.e., they may be appropriate for priority setting, point
and nonpoint-source evaluations, use attainability anal-
yses, and trend monitoring, as well as initial
screening.
1.2 DEVELOPMENT OF
THIS DOCUMENT
This document was developed in two phases. The
first phase centered on the development and refine-
ment of the benthic rapid bioassessment protocols.
The second phase involved the addition of analogous
protocols pertinent to the assessment of fish
communities.
The benthic protocols were developed by con-
solidating procedures in use by various State water
quality agencies. In 1985, a survey was conducted to
identify States that routinely perform screening-level
bioassessments and believe that such efforts are
important to their monitoring programs. Guidance
documents and field methods in common use were
evaluated in an effort to identify successful bioassess-
ment methods that use different levels of effort. Origi-
nal survey materials and information obtained from
direct personal contacts were used to develop the draft
protocols.
Missouri Department of Natural Resources and
Michigan Department of Natural Resources both use
the "stream walk" approach upon which the screening
protocol (RBP I) in this document is based. The sec-
ond protocol (RBP II) is more time and labor inten-
sive, incorporating field sampling and family-level
taxonomy, and is a less intense version of RBP HI.
The concept of family-level taxonomy is based on the
approach used by the Virginia State Water Control
Board. The third protocol (RBP III) incorporates
certain aspects of the methods used by the North
Carolina Division of Environmental Management and
the New York Department of Environmental Conser-
vation and is the most rigorous of the three
approaches.
-------
A workgroup of State and U.S. EPA Regional biol-
ogists (listed below) was formed to review and refine
the draft benthic protocols. The Rapid Bioassessment
Workgroup included biologists using the State methods
described above and biologists from other regions
where pollution sources and aquatic systems differed
from those areas for which the draft protocols were
initially developed.
EPA
James Plafkin, AWPD
Michael Bilger, Region I
Michael Bastian, Region VI
William Wuerthele, Region VIII
Evan Hornig, Region X
STATES
Brenda Sayles, Michigan DNR
John Rowland, Missouri DNR
Robert Bode, New York DEC
David Lenat, North Carolina DEM
Michael Shelor, Virginia SWCB
Joseph Ball, Wisconsin DNR
The rapid bioassessment protocols for benthos
presented here include modifications discussed in the
workgroup's first meeting held in 1986, as well as
comments on a subsequent draft. This document also
includes results of a field validation study (Section 6.4)
conducted with the North Carolina Department of
Environmental Management to examine certain
methodological issues highlighted in the workgroup's
review (Chapter 2). In addition, these protocols and
the concept of "rapid" bioassessment have been dis-
cussed at the 1986, 1987, and 1988 annual meetings of
the North American Benthological Society and in per-
sonal communications with Dr. Kenneth Cummins,
Dr. William Hilsenhoff, Dr. James Karr, and Dr.
Vincent Resh.
In response to a number of comments received
from State and EPA personnel on an earlier version of
the rapid bioassessment protocols, a set of fish pro-
tocols was also developed. Fish protocol V is based
on Karr's work (1981) with the Index of Biological
Integrity (IBI), Gammon's Index of Well Being (1980),
and standard fish population assessment models, cou-
pled with certain modifications for implementation in
different geographical regions. Ohio EPA has devel-
oped biological criteria using the IBI and Index of
Well Being (IWB), and a substantial database on their
use for site-specific fish assessments exists.
1.3 A FRAMEWORK FOR
IMPLEMENTING THE RAPID
BIOASSESSMENT PROTOCOLS
The rapid bioassessment protocols advocate an
integrated assessment, comparing habitat (e.g., physi-
cal structure, flow regime) and biological measures
with empirically defined reference conditions (Figure
1.3-1). Reference conditions are established through
systematic monitoring of actual sites that represent the
natural range of variation in "least disturbed" water
chemistry, habitat, and biological condition. Of these
three components of ecological integrity, ambient
water quality may be the most difficult to characterize
because of the complex array of chemical constituents
(natural and otherwise) that affect it. Therefore, the
implementation framework presented below first
describes the development of an empirical relationship
between habitat quality and biological condition, then
refines this relationship for a given region. As addi-
tional information is obtained from systematic
monitoring of potentially impacted and site-specific
control sites, the predictive power of the empirical
relationship is enhanced. Once the relationship
between habitat and biological potential is understood,
water quality impacts can be objectively discriminated
from habitat effects and control efforts can be focused
on the most important source of impairment.
1-2
-------
Explanatory Notes—
Bioassessment Implementation Framework
The following notes describe the implementation
framework of the RBPs presented in Figure 1.3-1;
each note corresponds to a similarly numbered ele-
ment in the flow diagram. The reader should examine
the figure first, then refer back to the numbered notes
for explanations.
1. The "reference site" (RS) should represent a data-
base consisting of the best attainable physical
habitat, water chemistry, and biological parameters
for specific environmental conditions. Acceptable
ranges for the habitat and biological parameters of
concern are based on this reference database.
In the RBP assessment scheme, selected
parameters are integrated to define generic habitat
categories and bioclassifications. The integrated
characterizations describe important attributes of
the designated use and represent criteria for
attainment/non-attainment of the designated use.
Figure 1.3-1 also illustrates how designated uses
and criteria may be established or refined as
ambient monitoring activities proceed, and how
new data are incorporated into the reference
database.
Considerable effort may be required initially to
identify reference sites and the habitat and biologi-
cal characteristics of a specified aquatic life use.
Alternatively, data required to define new or
refined use characterizations and assessment
criteria could be collected through implementation
of an effective ambient monitoring program. How-
ever, when the initial reference database includes a
spectrum of "least disturbed" habitats and con-
comitant biotic conditions, the need for site-specific
controls may be greatly reduced. The value of a
comprehensive reference database becomes more
evident with progression through the implementa-
tion framework.
2. The purpose of the habitat assessment is to deter-
mine whether "IS" (impaired site) has the potential
to support a biological community comparable to
that of the reference (see note 6).
3. Generally applicable ranges for several important
habitat characteristics are incorporated into the
habitat assessment field sheets (Figure 5.2-1) and
the habitat evaluation can be made quickly onsite.
However, preliminary reconnaissance is especially
helpful when impaired site habitat (HIS) proves to
be much lower in quality than reference habitat
(HRS) and an evaluation of reversible habitat alter-
ations ("attainability") may also be necessary.
Reconnaissance information allows planning for the
additional work needed to characterize more
appropriate reference sites.
4. In the early stages of developing assessment
criteria for a given aquatic life use, HIS may often
appear degraded relative to the HRS database. The
likelihood of such an outcome is proportional to
the richness of the initial HRS database. As more
potentially impacted stations are assessed, however,
certain stations will be shown to support:
—Biological communities equivalent to the refer-
ence sites despite apparent habitat deficiencies.
Information from such sites will enrich the refer-
ence database and broaden the applicability of
the use designation.
—A relatively degraded community that is limited
by intrinsic or irreversible habitat constraints. In
this case, the original use is not attainable, and
data collected from such a site should be used to
revise the use designation.
5. The robustness of the comparison between the bio-
logical condition at the impaired site (BIS) and that
at the reference (BRS) is limited by the rigor
of the assessment procedure used (e.g., many
versus few replicates) and the scope of the overall
assessment (i.e., the number of biological commu-
nity segments actually evaluated). The comparison
of BIS and BRS is useful for detecting or confirm-
ing appreciable impact to the biotic community
and may be insensitive to certain subtle and/or
threshold effects.
6. If BIS = BRS, there is no detectable impairment.
This conclusion assumes no overriding limitations
on the biological potential of "IS" relative to "RS
that are not accounted for by the previous habitat
comparison (see Note 2). Factors that could
uniquely affect "IS" are discussed in Section 2.3.
For example, stations "RS" and "IS" may be
located on a first order stream with primary
organic inputs from a coniferous forest. In this sit-
uation, certain characteristics of the benthic com-
munity, such as taxa richness, may actually
increase with organic enrichment from point source
discharges rather than decrease as otherwise
expected. This atypical situation should be assessed
as if HIS-(-(Reversible Habitat Alterations)< HRS
(Step 7).
7. The HIS + (Reversible Habitat Alterations) versus
HRS comparison amounts to a simplistic use
attainability analysis (UAA) that only considers
habitat. The comparison involves scaling up the
observed habitat parameter values to the extent that
they might be feasibly improved. For example,
bank stability, bank vegetation, and streamside
cover could be greatly enhanced by fencing a pas-
ture and planting trees, whereas other parameters
may be unalterable. This "mini-UAA" can help to
assess site-specific potential in the determination of
actual impairment. If HIS and HRS are potentially
equivalent, then use impairment can be appropri-
ately assessed in terms of the resident biota. If HIS
and HRS are not equivalent even when reversible
habitat alterations are considered, biological effects
may not be independent of habitat constraints.
These potential scenarios are discussed in more
detail in Chapter 8, Integration of Habitat, Water
Quality, and Biosurvey Data. The approach to con-
ducting a habitat assessment and bioassessment is
discussed in Chapters 5, 6, and 7.
1-3
-------
Assessment of
Impairment of Biological Integrity
(Not Human Health, Recreation or Aesthetics)*1)
Potentially Impacted/
Impaired Site (IS)
HIS = Habitat; BIS = Biological
Classification
vs
Reference Site (RS)
for a given Designated Use;
HRS = Habitat; BRS = Biological
Classification (Criterion)
HIS = HRS
HIS < HRS
(4)
BIS < BRS
BIS = BRS
(5)
Bioimpact
Impairment
at IS
(6)
HIS+
(Revs Hab Alts)
vsHRS
(7)
No Bioimpact
No Impairment
at IS
See
Chapter
8
Figure 1.3-1. Bioassessment decision matrix. (Numbers in
parentheses refer to points of discussion in text).
1-4
-------
2. THE CONCEPT OF BIOMONITORING
2.1 BIOSURVEYS, BIOASSAYS,
AND CHEMICAL MONITORING
The water quality-based approach to pollution
assessment requires various types of data. Biosurvey
techniques, such as the rapid bioassessment.protocols,
are best used for detecting aquatic life impairments
and assessing their relative severity. Once an impair-
ment is detected, however, additional chemical and
biological (toxicity) testing is usually necessary to
identify the causative agent and its source and to
implement appropriate mitigation (U.S. EPA 1985).
Following mitigation, biosurveys are important for
evaluating the effectiveness of such control measures.
Biosurveys may be used within a planning and
management framework to prioritize water quality
problems for more stringent assessments and to docu-
ment "environmental recovery" following control
action. Some of the advantages of using biosurveys for
this type of monitoring are:
1. Biological communities reflect overall ecological
integrity (i.e., chemical, physical, and biological
integrity)., Therefore, biosurvey results directly
assess the status of a waterbody relative to the
primary goal of the Clean Water Act.
2. Biological communities integrate the effects of
different pollutant stressors and thus provide a
holistic measure of their aggregate impact. Com-
munities also integrate the stresses over time and
provide an ecological measure of fluctuating
environmental conditions. Assessing the integrated
response of biological communities to highly
variable pollutant inputs offers a particularly useful
approach for monitoring nonpoint-source impacts
and the effectiveness of certain Best Management
Practices.
3. Routine monitoring of biological communities can
be relatively inexpensive, particularly when com-
pared to the cost of assessing toxic pollutants,
either chemically or with toxicity tests (Ohio EPA
1987a).
4. The status of biological communities is of direct
interest to the public as a measure of a pollution
free environment, while reductions in chemical
pollutant loadings are not as readily understood by
the layman as positive environmental results.
5. Where criteria for specific ambient impacts do not
exist (e.g., nonpoint-source impacts that degrade
habitat), biological communities may be the only
practical means of evaluation.
Biosurvey methods have a long-standing history of
use for "before and after" monitoring. However, the
intermediate steps in pollution control, identifying
causes and limiting sources, require information of a
different type—chemical, physical, and/or additional
biological data. These data are needed to:
1. Identify the specific stress agents causing impact.
This may be a relatively simple task; but, given
the array of potentially important pollutants (and
their possible combinations), it is likely to be both
difficult and costly. In situations where specific
chemical stress agents are either poorly understood
or too varied to assess individually, toxicity tests
can be used to focus specific chemical investiga-
tions or to characterize generic stress agents (e.g.,
whole effluent toxicity).
2. Identify and limit the specific sources of these
agents. Although biosurveys can be used to help
locate the likely origins of impact, chemical anal-
yses and/or toxicity tests are usually necessary to
confirm the responsible sources and develop
appropriate discharge limits.
3. Design appropriate treatment to meet the
prescribed limits and monitor compliance. Treat-
ment facilities are designed to remove identified
chemical constituents with a specific efficiency.
Chemical data are therefore required to construct
such facilities and evaluate treatment effectiveness.
To some degree, a biological endpoint resulting
from toxicity testing can also be.used to evaluate
the effectiveness of prototype treatment schemes
and can serve as a design pa-ameter. In most
cases, these same parameters are limited in dis-
charge permits and, after controls are in place, are
used to monitor for compliance. Where discharges
are not controlled through a permit system (e.g.,
nonpoint-source runoff, combined sewer outfalls,
and dams) compliance must be assessed in terms
of ambient standards.
Effective implementation of the water quality-based
approach requires that various monitoring techniques
be considered within a larger context of water
resource management. Both biological and chemical
2-1
-------
methods play critical roles in a successful pollution
control program. They should be considered com-
plementary rather than mutually exclusive approaches
that will enhance overall program effectiveness when
used appropriately.
2.2 USE OF DIFFERENT
TAXONOMIC GROUPS
IN BIOSURVEYS
The bioassessment techniques presented in this
document focus on the evaluation of water quality,
habitat, and benthic macroinvertebrate and fish com-
munity parameters. Many State water quality agencies
employ trained and experienced benthic biologists,
have accumulated considerable background data on
macroinvertebrates, and consider benthic surveys a
useful assessment tool. However, water quality stan-
dards, legislative mandate, and public opinion are
more directly related to the status of a waterbody as a
fishery resource. For this reason, separate protocols
were developed for fish and were incorporated as
Chapter 7 in this document. The fish survey protocol
is based largely on James Karr's IBI (Karr 1981; Karr
et al. 1986; Miller et al. 1988a), which uses fish
community structure to evaluate water quality. The
integration of functional and structural/compositional
metrics, which forms the basis for the IBI is a com-
mon element to the fish and benthic rapid bioassess-
ment approaches.
Although no methods are presented here for con-
ducting algal assessments, algal communities are also
useful for water quality monitoring. They represent
another trophic level, exhibit a different range of sen-
sitivities, and will often indicate effects only indirectly
observed in the benthic and fish communities. As in
the benthic macroinvertebrate and fish communities,
integration of structural/compositional and functional
characteristics provides the best means of assessing
impairment (Rodgers et al. 1979).
Algal community structural/compositional analyses
may be taxonomic or non-taxonomic. Taxonomic anal-
yses (e.g., diversity indices, taxa richness, indicator
species) are commonly used, and are described in
studies by Rodgers et al. (1979), Weitzel (1979),
Palmer (1977), and Patrick (1973). Non-taxonomic
measures, such as biomass and chlorophyll, can also
be useful for detecting effects not indicated by taxo-
nomic analysis. For example, toxic pollutants may
cause sublethal (i.e., reproductive) effects which
would not immediately be detected by taxonomic ana-
lyses such as taxa richness, but would be indicated by
low biomass (Patrick 1973). A summary of non-
taxonomic measurements is presented in Weitzel
(1979).
Functional aspects of algal communities, such as
primary productivity rates, can also be assessed.
These analyses, which are described in Rodgers et al.
1979, can be performed at the taxonomic level (e.g.,
determination of species colonization rate) or at the
non-taxonomic level (e.g., community respiration) to
evaluate effects of toxicants or nutrient enrichment.
In determining the taxonomic group or groups
appropriate for a particular biomonitoring situation,
the advantages of using each taxonomic group must be
considered along with the objectives of the program.
Some of the advantages of using macroinvertebrates,
fish, and algae in a biomonitoring program are
presented in this section. References for this list are
Cairns and Dickson 1971; Karr 1981; U.S. EPA 1983;
Hughes et al. 1982; American Public Health Associa-
tion et al. 1971; Patrick 1973; Rodgers et al. 1979; and
Weitzel 1979.
Advantages of Using Benthic Macroinvertebrates
1. Macroinvertebrate communities are good indicators
of localized conditions.
• Because many benthic macroinvertebrates have
limited migration patterns or a sessile mode of
life, they are particularly well suited for assess-
ing site-specific impacts (upstream-downstream
studies).
2. Macroinvertebrate communities integrate the effects
of short-term environmental variations.
• Most species have a complex life cycle of
approximately 1 year or more. Sensitive life
stages will respond quickly to stress; the overall
community will respond more slowly.
3. Degraded conditions can often be detected by an
experienced biologist with only a cursory examina-
tion of the macroinvertebrate community.
• Macroinvertebrates are relatively easy to identify
to family; many "intolerant" taxa can be identi-
fied to lower taxonomic levels with ease.
4. Sampling is relatively easy, requires few people
and inexpensive gear, and has no detrimental effect
on the resident biota.
5. Benthic macroinvertebrates serve as a primary food
source for many recreationally and commercially
important fish.
6. Benthic macroinvertebrates are abundant in most
streams.
• Many small streams (1st and 2nd order), which
naturally support a diverse macroinvertebrate
fauna, only support a limited fish fauna.
7. Most State water quality agencies that routinely
2-2
-------
collect biosurvey data focus on macroinvertebrates.
(This may be due to the emphasis placed on mac-
roinvertebrates for community-level evaluations in
the 1976 Basic Monitoring Programs Guidance.)
• Many States already have background macroin-
vertebrate data.
• Most State water quality agencies have more
expertise in aquatic entomology than in
ichthyology.
Advantages of Using Fish
1. Fish are good indicators of long-term (several
years) effects and broad habitat conditions because
they are relatively long-lived and mobile (Karr et
al. 1986).
2. Fish communities generally include a range of spe-
cies that represent a variety of trophic levels
(omnivores, herbivores, insectivores, planktivores,
piscivores). They tend to integrate effects of lower
trophic levels; thus, fish community structure is
reflective of integrated environmental health.
3. Fish are at the top of the aquatic food chain and
are consumed by humans, making them important
subjects in assessing contamination.
4. Fish are relatively easy to collect and identify to
the species level. Most specimens can be sorted
and identified in the field and released unharmed.
• Environmental requirements of common fish are
comparatively well known.
• Life history information is extensive for most
species.
• Information on fish distributions is commonly
available.
5. Aquatic life uses (water quality, standards) are typi-
cally characterized in terms of fisheries (coldwater,
cool water, warmwater, sport, forage).
• Monitoring fish communities provides direct
evaluation of "fishability", which emphasizes the
importance of fish to anglers and commercial
fishermen.
6. Fish account for nearly half of the endangered ver-
tebrate species and subspecies in the United States.
Advantages of Using Algae
1. Algae generally have rapid reproduction rates and
very short life cycles, making them valuable indi-
cators of short-term impacts.
2. As primary producers, algae are most directly
affected by physical and chemical factors.
3. Sampling is easy, inexpensive, requires few people,
and creates minimal impact to resident biota.
4. Relatively standard methods exist for evaluation of
functional and non-taxonomic structural (biomass,
chlorophyll measurements) characteristics of algal
communities.
5. Algal communities are sensitive to some pollutants
which may not visibly affect other aquatic commu-
nities, or may only affect other communities at
higher concentrations (i.e., herbicides).
2.3 STATION SITING
RBP I, RBP II, RBP III, and RBP V include the
collection of biological samples to assess the biotic
integrity of a given site. To meaningfully evaluate bio-
logical condition, sampling locations must be carefully
selected to ensure generally comparable habitat at
each station. Unless basically comparable physical
habitat is sampled at all stations, community differ-
ences attributable to a degraded habitat will be diffi-
cult to separate from those resulting from water
quality degradation. Availability of habitats at each
sampling location can be established during prelim-
inary reconnaissance (such as RBP I). In evaluations
where several stations on a waterbody will be com-
pared, the station with the greatest habitat constraints
(in terms of productive habitat availability) should be
noted. The station with the least number of productive
habitats available will often determine the type of
habitat to be sampled at all stations of comparison.
Locally modified sites, such as small impound-
ments and bridge areas, should be avoided unless data
are needed to assess their effects. Sampling near the
mouths of tributaries entering large waterbodies
should also be avoided since these areas will have
habitat more typical of the larger waterbody (Karr
et al. 1986).
Although the specific bioassessment objective is an
important consideration in locating sampling stations,
all assessments require a site-specific control station
or reference data from comparable sites within the
same region. A site-specific control is generally
thought to be most representative of "best attainable"
conditions for a particular waterbody. However,
regional reference stations may also be desirable to
allow evaluation of conditions on a larger scale.
Where feasible, effects should be bracketed by estab-
lishing a series or network of sampling stations at
points of increasing distance from the impact
source(s). These stations will provide a basis for
delineating impact and recovery zones.
2-3
-------
2.4 IMPORTANCE OF
HABITAT ASSESSMENT
The procedure for assessing habitat quality
presented in this document (Section 5.2) is an integral
component of the final evaluation of impairment. The
matrix used to assess habitat quality is based on key
physical characteristics of the waterbody and sur-
rounding land. All of the habitat parameters evaluated
are related to overall aquatic life use and are a poten-
tial source of limitation to the aquatic biota.
Habitat, as affected by instream and surrounding
topographical features, is a major determinant of
aquatic community potential. Both the quality and
quantity of available habitat affect the structure and
composition of resident biological communities.
Effects of such features can be minimized by sampling
similar habitats at all stations being compared. How-
ever, when all stations are not physically comparable,
habitat characterization is particularly important for
proper interpretation of biosurvey results.
Where habitat quality is similar, detected impacts
can be attributed to water quality factors. However,
where habitat quality differs substantially from refer-
ence conditions, the question of use attainability and
physical habitat alteration/restoration must be
addressed. Final conclusions regarding the presence
and degree of biological impairment should thus
include an evaluation of habitat quality to determine
the extent that habitat may be a limiting factor. The
habitat characterization matrix included in the rapid
bioassessment protocols provides an effective means of
evaluating and documenting habitat quality at each
biosurvey station.
2.5 THE ECOREGION CONCEPT
Innate regional differences exist in forests, agricul-
tural potential, wetlands, and waterbodies. These
regional differences have been mapped by Bailey
(1976); ~USDA Soil Conservation Service (1981),
Energy, Mines and Resources Canada (1986), and
Omernik (1987). All four maps were developed from
examination of several mapped land variables. It is
assumed that waterbodies reflect the lands they drain
and that similar lands should produce similar water-
bodies. This ecoregional approach provides much
more robust and ecologically-meaningful regional
maps than could be attained by mapping a single vari-
able. For example, hydrologic unit maps are useful for
mapping drainage patterns, but have limited value for
explaining the substantial changes that occur in water
quality and biota independent of stream size and river
basin. Recognition of these changes stimulated
Warren's (1979) work, and Ohio's and Arkansas'
development of ecoregional standards.
Omernik (1987) provides an ecoregional framework
for interpreting spatial patterns in state and national
data. The geographical framework is based on
regional patterns in land-surface form, soil, potential
natural vegetation, and land use, which vary across
the country. Two major applications grew out of the
regional approach. The first was the use of a rela-
tively small number of minimally-impacted regional
reference sites to assess feasible but protective biologi-
cal goals for an entire region (Hughes et al. 1986).
The second was the use of regions as a statistical
framework for stratified random sampling of lakes in
a national survey of the effects of acid deposition
(Linthurst et al. 1986, Landers et al. 1987). These two
site selection methods offer ecologically and statisti-
cally valid means to establish baseline conditions and
assess water quality in entire regions by monitoring a
relatively small number of sites.
Geographic patterns of similarity among
ecosystems can be grouped into ecoregions. Naturally
occurring biotic assemblages, as components of the
ecosystem, would be expected to differ among
ecoregions but be relatively similar within a given
ecoregion. The ecoregion concept thus provides a
geographic framework for more efficient management
of aquatic ecosystems and their components (Hughes
et al. 1986, Hughes 1985, and Hughes and Larsen
1988). For example, studies in Ohio (Larsen et al.
1986), Arkansas (Rohm et al. 1987), and Oregon
(Hughes et al. 1987, Whittier et al. 1988) have shown
that distributional patterns of fish communities coin-
cide with the States' ecoregions as defined a priori by
Omernik (1987). This, in turn, implies that similar
water quality standards, criteria, and monitoring
strategies are likely to be valid throughout a given
ecoregion, but should be tailored to accommodate the
innate differences among ecoregions (Ohio EPA
1987b). Figure 2.5-1 shows the 76 ecoregions devel-
oped by Omernik (1987) for the conterminous United
States.
Macroinvertebrate communities reflect habitat
differences on a smaller scale than fish, and may be
better suited for site-specific assessments. Within an
ecoregion (Omernik 1987), additional qualifiers such
as stream size, hydrologic regime, and riparian vegeta-
tion need to be considered. In addition, streams or
stream segments may represent characteristics atypical
for that particular ecoregion. For instance, a given
2-4
-------
[ "il" "J NO"TH CEKTAAL HABOWOOO FORESTS
|~M ~] WHFTLESS AREA
[ M "j SOUTHEASTER* wiSCOfcSw TX1 PLAINS |
j *» ^ CENTRAL CORN BELT PLAINS
| » j EASTER* CORN BELT ltAM*5
i M ' S MKWGAN ' 1 INDIANA T)LL PLAMS
;>X
: -
\cM „ P \%v/ **<£-*
X^ « !,KJ \ ^t3 is\ X^
*"i
f^T«]B«,««,
P^fl| WllLAMtm *LLET l^1» "1 MIODLE ROCKIES
\ t 1 CASCADES F li 1 WVOUIMQ BASIN
1 • ) SOUTHERN CAL*ORNIA MOUNTAINS [ S 1 ARIZONA HEW MEXICO PLATEAU H^H TEXAS hJKMLANO PHAH"€S
I 1 ] EASTERN CASCADES SLOPES AMD roOTmiS I n 1 ARlZOMA.'MFW MEXICO MOUNTAINS 1 M 1 EAST CfNtBAI. TEXAS PUMM8
[ '0 ] CXXUH8W MS" ] ;« [ SOUTHERN DESERTS | M | wtSTERw OU1.F COASTAL PXAW
r Tl ^j Blue MOUNOUHS f M 1 WESTERN HK-.H Pi-AINS ! M ""] SOUTH CENIEUM. PLAINS
[ ii 1 SMAirf RIVER *ASM"*3H DESERT I 2*~~\ BOU'HwrSTERW lABCtLAMJS 1 X 1 OUATXI-A MOUMTJIIH;
| MOO'-^RN BASW, AND OAMGE F >T 1 CtHlBJU. G«E«I PVAMS j J) I ABXAKSAfl WW.LFV
[ l« ] 3OMTHERN BASIN AND RANGE [ a j FLINT HIL1S J • [ BOSTON MOUNTAINS
I IS 1 HOHTXCRN BOCWeS f M^ ] CEHIBAI OKLAHOMA'TEJ-AS PVAPIS 1 » | OIAJtH HIQHLAMDS
I i| j MOHIAHA MtLLEV AM} FOOTHW.L P«A«WES F 3O I CEN'RAt TEXAS PLATEAU C .- I CENTRAL ItWEQULAH PtAJHS
2fe'.Ajpi^ , A ^
ikF^'
r*^M; S^^^r^
\Y? "v
*s*™^
ECOREGIONS OF THE CONTERMINOUS UNITED STATES
CarnUa Environmanttl Fteswrch Utxwwory
1986
[ M^ NORTHCASTtHN HIGHLANDS
I SS 1 NORThEASTERN COASTAL ZONE
: 1 NC«T«EBN APPALACHIAN PLATEAU
1 " J UNO UPLANDS
| * \ E«'0«»0 LAKE PLAIN
' JB 1 nOfTTH CENTRAL APPALACHIANS
1 M 1 UCOLE ATLANTK; COASTAL PLAIN
1 M | NORTHEJW PIEDMONT
[^•g j SOUTHEASTERN PLAINS
I II 1 CENTRAL WPALACHIAN WOGE&
t A AND «U1£VS
P • \ SOUTHWESnpK APPALACHIANS
1 m | CENTRAL APPALACHIANS
[TSJ ^TE^^VER LOWLAND
L" j -«««, AiiOVlAL PUM
[ » | WSSSS1PM VHLLEV LOESS PLAINS
1 S 1 SOVTHtRN CClASTAL PVAtN
r~TJj) SOUTH£flN tLOWIM COASTAL PLAIN
Figure 2.5-1. Ecoregions of the conterminous United States (after Omernik 1986).
-------
stream segment may be wooded (deciduous or conifer-
ous) or open, within a perennial or intermittent flow
regime, and represent a particular stream size (Figure
2.5-2). Individual descriptors may not apply to all
ecoregions, nor will all conditions (i.e., deciduous,
coniferous, open) be present in all stream sizes.
The final rapid bioassessment guidance should be
generally applicable to all ecoregions of the United
States, although specific elements and evaluation
criteria may require modification for particular
ecoregions. When rapid bioassessment protocols are
used to assess impact sources (upstream-downstream
studies), reference criteria may not be as important if
an unimpacted site-specific control station can be sam-
pled. However, when a synoptic ("snapshot") survey
is being conducted or an appropriate control does not
exist in the immediate study area, use of idealized
criteria may be the only means of discerning use
impairment or assessing impact.
Each agency will need to evaluate the generic
criteria suggested in this document for inclusion into
specific programs. To this end, the application of the
ecoregion concept versus the site-specific control
approach will need to be evaluated by each agency. It
is likely that additional investigation will be needed
to: delineate areas that differ significantly in their
innate biological potential; locate reference sites
within each ecoregion that fully support aquatic life
uses; and develop biological criteria (e.g., define
optimal values for the metrics recommended) using
data generated from one of the higher level protocols.
2.6 DATA MANAGEMENT
AND ANALYSIS
2.6.1 Integration into BIOS
The U.S. Environmental Protection Agency (EPA)
has developed a biological data management system
known as BIOS. BIOS provides a centralized system
for storage of biological data in addition to analytical
tools for data analysis. The field survey file compo-
nent of BIOS provides a means of storing, retrieving,
and analyzing biosurvey data, and will process data
on the distribution, abundance, and physical condition
of aquatic organisms, as well as descriptions of their
habitats. Data stored in BIOS become part of a com-
prehensive database that can be used as a reference, to
refine analysis techniques, or to define ecological
requirements for aquatic populations. Data from the
rapid bioassessment protocols can be readily managed
with the BIOS field survey file using header informa-
tion presented in Figure 2.6-1 to identify sampling
stations.
Habitat information and physical characterization
information may also be stored in the field survey file
with abundance data. Parameters available in the field
survey file can be used to store some of the environ-
mental characteristics associated with the sampling
event, including physical characteristics, water quality,
and habitat assessment. Physical/chemical parameters
with discrete values may be stored in the field survey
file or the water quality file of STORET, under the
same station description. Such parameters include
stream depth, velocity, and substrate characteristics, as
well as many other parameters. The system will also
allow storage of other pertinent station or sample
information in the comments section.
2.6.2 Computerizing Field Data for
Calculation of the Metrics
Entering data into a computer system can provide
a substantial time savings. An additional advantage to
computerization is analysis documentation, which is
an important component for a QA/QC plan. An
agency conducting rapid bioassessment programs can
choose an existing system within their agency or
utilize the BIOS system developed as a national
database system.
The field survey file of BIOS can calculate several
metrics used in the RBPs. Metric values that may cur-
rently be calculated in a BIOS PGM = TAXATABLE
retrieval report include taxa richness, EFT Index, and
percent contribution of the dominant taxon. Other
metrics are planned as future additions to the field
survey file. Additional metrics can be calculated using
SAS, which is easily accessible to the file. BIOS may
also be used to create a machine-readable file for use
as input to either a user-written program or to an
external analytical software package (SPSS, BMDP,
dBase III).
2.7 BENTHIC COMMUNITY
CONSIDERATIONS
2.7.1 Seasonality for
Benthic Collections
Rapid bioassessment is based on evaluation of rela-
tively few samples al a site. Seasonality is particularly
important when only a few collection sites are
involved. The intent of the benthic rapid bioassess-
2-6
-------
Ecoregion
A, B, C, etc.
Surrounding
Land Use
Evaluation
Figure 2.5-2. Flowchart illustrating potential delineation of reference sites within an ecoregion.
2-7
-------
00
Waterbody Name.
Reach/Milepoint _
County
Station Number.
Date
Hydrologic Unit Code
Reason for Survey
State.
Time.
Location.
Latitude/Longitude.
Aquatic Ecoregion _
Investigators._
Agency
Form Completed by
Figure 2.6-1. Header information used for documentation and identification for sampling stations.
-------
ment is to evaluate overall biological condition,
optimizing the use of the benthic community's capac-
ity to reflect integrated environmental effects over
time. Ideally, the optimal biological sampling season
will correspond to recruitment cycles of the inver-
tebrates. Maximum information for a benthic commu-
nity is obtained when most benthic macroinvertebrates
are within a size range (later instars) retained during
standard sieving and sorting, and can be identified
with the most confidence.
Reproductive periods and different life stages of
aquatic insects are related to the abundance of particu-
lar food supplies (Cummins and Klug 1979). Peak
emergence and reproduction typically occur in the
spring and fell, although onset and duration vary
somewhat across the United States. During peak
reproduction, approximately 80 percent of the macro-
invertebrates will be too small to be captured in suffi-
cient numbers to accurately characterize the
community. Additionally, food source requirements for
early instars are different from those for later instars.
Therefore, the biologically optimal sampling season
would occur when the habitat is utilized most heavily
by later instars and the food resource has stabilized to
support a balanced indigenous community.
Field collections scheduled to correspond to sea-
sonal recruitment cycles of invertebrates will provide
the optimal biological sampling period. However,
sampling during these optimal biological periods may
not be logistically feasible due to adverse weather
conditions, manpower availability, scheduling con-
straints, or other factors. Additionally, an agency may
be required to perform biological sampling during
periods of greatest environmental stress such as low
flow/high temperature periods for point-source dis-
charges or high flow/runoff periods for nonpoirit-
source discharges. Although an estimate of benthic
community structure during optimal biological condi-
tions is expected to reflect effects of, or recovery
from, environmental stress periods (Ohio EPA 1987a),
assessment of worst-case conditions may be needed
under certain permitting regulations, or as a follow-up
to sampling during biologically optimal periods,
where impairment is detected.
Optimal biological conditions for sampling vary
with climate. Seven major climatological regions are
represented within the United States (Figure 2.7-1).
Temperature and/or rainfall are the principal factors
influencing optimal biological conditions in each
climatological region. Several ecoregions are
represented within each of these climatological
regions. Some scaling of the optimal collection period
will be necessary, depending on the elevation of the
site and the habitat type.
2.7.2 Benthic Sampling Methodology
2.7.2.1 Natural and Artificial Substrates
The benthic RBPs employ direct sampling of natu-
ral substrates. Because routine evaluation of a large
number of sites is a primary objective of the RBPs,
artificial substrates were eliminated from consideration
due to time required for both placement and retrieval,
and the amount of exposure time required for coloni-
zation. However, where conditions are inappropriate
for the collection of natural substrate samples, artifi-
cial substrates may be an option. Artificial substrates
may be useful in situations such as large rivers, where
an impact is attributable to physical alteration and
channelization or chemical effects. Artificial substrates
may be used to separate the two impact sources.
Advantages and disadvantages of artificial sub-
strates (Cairns 1982) relative to the use of natural sub-
strates are presented below.
Advantages of Sampling With Artificial Substrates
1. Artificial substrates allow sample collection in
locations that are typically difficult to sample
effectively (e.g., bedrock, boulder, or shifting sub-
strates; deep or high velocity water).
2. As a "passive" sample collection device, artificial
substrates permit standardized sampling by
eliminating subjectivity in sample collection tech-
nique. Direct sampling of natural substrate requires
similar effort and degree of efficiency for the col-
lection of each sample. Use of artificial substrates
requires standardization of setting and retrieval;
however, colonization provides the actual sampling
mechanism.
3. Confounding effects of habitat differences are
minimized by providing a standardized micro-
habitat. Microhabitat standardization may promote
selectivity for specific organisms if the artificial
substrate provides a different microhabitat than that
naturally available at a site (see Disadvantage 2).
Most artificial substrates, by design, select for the
Scraper and Filtering Collector communities,
which are the macroinvertebrate communities
emphasized in this document. However, in some
situations, accumulation of debris may cause a pre-
dominance of Collector-Gatherers (Hilsenhoff, per-
sonal communication).
4. Sampling variability is decreased due to a reduc-
tion in microhabitat patchiness, improving the
potential for spatial and temporal similarity among
samples.
5. Sample collection using artificial substrates may
2-9
-------
Boston, Mass.
New York, N.Y.
= Mediterranean
= Humid Continental
= Humid Subtropical
= Highlands
= Steppe
= Desert
= Marine West Coast
Figure 2.7-1. Classification of U.S. climatological regions. (Taken from Gabler et al. 1976.)
-------
require less skill and training than direct sampling
of natural substrates. Depending on the type of
artificial substrate used, properly trained techni-
cians could place and retrieve the substrates.
However, an experienced specialist should be
responsible for the selection of habitats and sample
sites.
Disadvantages of Sampling
With Artificial Substrates
1. Two trips (one to set and one to retrieve) are
required for each artificial substrate sample; only
one trip is necessary for direct sampling of the
natural substrate. Artificial substrates require a
long (8-week average) exposure period for coloni-
zation. This decreases their utility for certain rapid
biological assessments.
2. Samples may not be fully representative of the
benthic community at a station if the artificial sub-
strate offers different microhabitats than those
available in the natural substrate. Artificial sub-
strates often selectively sample certain taxa, mis-
representing relative abundances of these taxa in
the natural substrate. Artificial substrate samples
would thus indicate colonization potential rather
than the resident community structure. This could
be advantageous if a study is designed to isolate
water quality effects from substrate and other
microhabitat effects. Where habitat quality is a
limiting factor, artificial substrates could be used to
discriminate between physical and chemical effects
and assess a site's potential to support aquatic life
on the basis of water quality alone.
3. Sampler loss or perturbation commonly occurs due
to sedimentation, extremely high or low flows, or
vandalism during the relatively long (at least
several weeks) exposure period required for
colonization.
4. Depending on the configuration of the artificial
substrate used, transport and storage can be diffi-
cult. The number of artificial substrate samplers
required for sample collection increases such
inconvenience.
2.7.2.2 Single and Multiple Habitat Sampling
A central issue in the development of the rapid
bioassessment protocols has been whether sampling
all available habitats is necessary to evaluate biological
integrity at a site, or if sampling only selected habitats
will provide a sufficient characterization. The pilot
study in North Carolina (see Section 6.4) addressed
this issue and indicated that the riffle community and
the multihabitat assemblage responded similarly to
differences among stations. For example, under stress,
taxa richness was reduced by the same proportion in
both the riffle community and the multihabitat assem-
blage at a given station. These responses suggest that
either the riffle community or the multihabitat assem-
blage will give a good assessment of biotic integrity
but assessing both may be redundant.
The sampling of a single habitat type (e.g., riffle/
run) is intended to limit the variability inherent in
sampling natural substrates. Kicknet samples are used
in the RBPs because they have been shown to provide
good statistical replication (Pollard 1981). However,
some streams lack the cobble substrate (riffle/run) to
support the periphyton-based benthic community
emphasized in the RBPs. In this case, an alternate
habitat(s) will need to be sampled. Some State agen-
cies, such as North Carolina DEM, have been suc-
cessful in using a multihabitat sampling approach, and
advocate this technique as being more appropriate in
North Carolina than simply sampling the riffle/run
habitat.
Discussions at the 1987 Biocriteria Workshop (U.S.
EPA 1988) indicated strong support for multihabitat
sampling where time and resources permit and the
particular region or specific study emphasizes non-
Scraper communities. It was generally agreed, how-
ever, that samples from various habitats should be
processed and analyzed separately. Data can always be
aggregated after individual samples are analyzed and
tabulated, but potentially important comparisons
among habitats are lost if samples are composited.
2.7.2.3 Sampling Coarse Participate
Organic Material (CPOM)
In addition to sampling the riffle habitat, the ben-
thic RBPs recommend that a Coarse Particulate
Organic Material (CPOM) sample also be collected
(Sections 6.2.1.1 and 6.3.1.1). In lotic systems, CPOM
generally exists in -the form of plant debris (leaves,
needles, twigs, bark) which accumulates in deposi-
tional areas. The rationale for collecting the CPOM
samples is that, as a group, Shredders should be par-
ticularly affected by toxic pollutants that often adsorb
to CPOM (Cummins 1987, personal communication).
Toxicants adsorbed to CPOM affect Shredders directly
through ingestion and indirectly by killing attached
microbes that "prepare" CPOM for Shredder con-
sumption. In a study by Newman et al. (1987), amphi-
pod Shredders colonizing litter bags were significantly
reduced in numbers by 230 5g/L total residual
chlorine.
The CPOM sample is processed separately and
2-11
-------
the organisms are identified as Shredders or Non-
Shredders (Sections 6.2.1.1 and 6.3.1.1). Taxonomic
identifications are not necessary in that most aquatic
insects can be classified to Functional Feeding Group
on the basis of morphological and behavioral features
using the procedures in Cummins and Wilzbach
(1985). These counts are used to calculate the ratio of
Shredders to the total number of individuals collected,
one of the eight metrics used in the final biosurvey
analysis.
2.7.3 Benthic Sample Processing
and Enumeration
One of the underlying goals of this guidance is to
promote consistency in the conduct of rapid bioassess-
rnents. In RBP II, consistent sample handling is very
important because relatively detailed comparisons are •
made among stations and sites. The RBP n 100-count
subsampling procedure is adapted from Hilsenhoff
(1987b) and is performed in the field. The level of
effort and subsampling process used for RBP III is
similar to RBP II, except subsampling is conducted in
the laboratory. This laboratory subsampling procedure
provides a more standard unit of effort.
Much of the useful information regarding assess-
ment of biological condition can be obtained from a
relatively small subsample, such as the 100-count sub-
sample recommended in this document (see Section
6.4). However, an agency may be willing to expend
additional time to attain a higher degree of resolution.
In this case, a 200- or 300-count subsample may be
selected. Some agencies may wish to process the /
entire sample for analysis.
2.7.4 Benthic Environmental
Tolerance Characterizations
Assessment of biological condition using the ben-
thic protocols presented in this document is based on
the calculation of several metrics. Certain metrics rely
on classification of benthic taxa according to their
relative sensitivity to pollution. This approach reflects
the longstanding indicator species concept, with sensi-
tivity primarily related to responses of species to
organic pollution. Responses to toxicants are also
incorporated into the tolerance characterizations, but
to a lesser extent. Evaluation of toxic effects is
addressed primarily at the Functional Feeding Group
level.
The specific tolerance characterizations used in the
RBPs were obtained from Hilsenhoff (1987b, 1988).
Hilsenhoff s species level tolerance characterization
system was selected due to its extensive use across the
country. A more recently developed family level sys-
tem (Hilsenhoff 1988) has not been used extensively,
but was based on Hilsenhoffs original widely
accepted index. Several other general tolerance clas-
sification systems are fairly well established, generally
applicable, and may also be used as guidelines. Some
of these are listed in Appendix C. Additional biotic
indices are also listed in U.S. EPA 1983. However,
types of pollution and causes of impairment will differ
regionally, and the meaning of "pollution tolerance"
may vary among regions. Therefore, optimal
implementation of the tolerance characterization
approach requires that each State agency refine estab-
lished tolerance classification systems for their own
use. Winget and Mangum (1979) have developed a
tolerance classification based on nonpoint-source
effects (Biotic Condition Index). This classification
may prove useful as a substitute for Hilsenhoffs when
evaluating nonpoint-source problems.
2.8 FISH COMMUNITY
CONSIDERATIONS
2X1 Seasonality for Fish Collections
Seasonal changes in the relative abundances of the
fish community primarily occur during reproductive
periods and (for some species) the spring and fall
migratory periods. However, because larval fish sam-
pling is not recommended in this protocol, reproduc-
tive period changes in relative abundance are not of
primary importance.
Generally, the preferred sampling season is mid to
late summer, when stream and river flows are moder-
ate to low, and less variable than during other sea-
sons. Although some fish species are capable of
extensive migration, fish populations and individual
fish tend to remain in the same area during summer
(Funk 1957; Gerking 1959; Cairns and Kaesler 1971).
The Ohio Environmental Protection Agency (Rankin
1987, personal communication) confirmed that few
fishes in perennial streams migrate long distances.
Hill and Grossman (1987) found that the three domi-
nant fish species in a North Carolina stream had
home ranges of 13 to 19 m over a period of 18
months. Ross et a!. (1985) and Matthews (1986) found
that stream fish assemblages were stable and persistent
for 10 years, recovering rapidly from droughts and
floods indicating that large population fluctuations are
unlikely to occur in response to purely natural
environmental phenomena. However, comparison of
data collected during different seasons is discouraged,
as is data collected during or immediately after major
flow changes.
2-12
-------
2.8.2 Fish Sampling Methodology
2.8.2.1 Use of Electrofishing, Seining,
and Rotenoning
Although various gear types are routinely used to
sample fish, electrofishers, seines, and rotenone are
the most commonly used collection methods in fresh-
water habitats. Each method has advantages and disad-
vantages (Nielsen and Johnson 1983; Hendricks et al.
1980). However, electrofishing is recommended for
most fish field surveys because of its greater applica-
bility and efficiency. Local conditions may require
consideration of seining and rotenoning as optional
collection methods. Advantages and disadvantages of
each gear type are presented below.
Advantages of Electrofishing
1. Electrofishing allows greater standardization of
catch per unit of effort.
2. Electrofishing requires less time and manpower
than some sampling methods (e.g., use of ichthyo-
cides) (Hendricks et al. 1980).
3. Electrofishing is less selective than seining
(although it is selective towards size and species)
(Hendricks et al., 1980). (See disadvantage
number 2).
4. If properly used, adverse effects on fish are
minimized.
5. Electrofishing is appropriate in a variety of
habitats.
Disadvantages of Electrofishing
1. Sampling efficiency is affected by turbidity and
conductivity.
2. Although less selective than seining, electrofishing
is size and species selective. Effects of electrofish-
ing increase with body size. Species specific
behavioral and anatomical differences also deter-
mine vulnerability to electroshocking (Reynolds
1983).
3. Electrofishing is a hazardous operation that can
injure field-personnel if proper safety procedures
are ignored.
Advantages of Seining
1. Seines are relatively inexpensive.
2. Seines are lightweight and are easily transported
and stored.
3. Seine repair and maintenance are minimal and can
be accomplished onsite.
4. Seine use is not restricted by water quality
parameters.
5. Effects on the fish population are minimal because
fish are collected alive and are generally
unharmed.
Disadvantages of Seining
1. Previous experience and skill, knowledge of fish
habitats and behavior, and sampling effort are
probably more important in seining than in the use
of any other gear (Hendricks et al. 1980).
2. Seining sample effort and results are more variable
than sampling with electrofishing or rotenoning.
3. Seine use is generally restricted to slower water
with smooth bottoms, and is most effective in
small streams or pools with little cover.
4. Standardization of unit of effort to ensure data
comparability is difficult.
Advantages of Rotenoning
1. The effective use of rotenone is independent of
habitat complexity.
2. Rotenoning provides greater standardization of unit
of effort than seining.
3. Rotenoning has the potential, if used effectively, to
provide more complete censusing of the fish popu-
lation than seining or electrofishing.
Disadvantages of Rotenoning
1. Use of rotenone is prohibited in many States.
2. Application and detoxification can be time and
manpower intensive.
3. Effective use of rotenone is affected by tempera-
ture, light, dissolved oxygen, alkalinity, and tur-
bidity (Hendricks et al. 1980).
4. Rotenoning typically has a high environmental
impact; concentration miscalculations can produce
substantial fish kills downstream of the study site.
2£.2.2 Sampling Representative Habitat
The sampling approach advocated in fish RBP V
optimizes the conservation of manpower and resources
by sampling areas of representative habitat. The fish
survey provides a representative estimate of the fish
community at all habitats within a site, and a realistic
sample of fish likely to be encountered in the water-
body. When sampling large streams, rivers, or water-
bodies with complex habitats, a complete inventory of
the entire reach is not necessary for the level of
assessment used in RBP V. The sampling area should
be representative of the reach, incorporating riffles,
runs, and pools if these habitats are typical of the
stream in question. Although a sampling site with two
riffles, two runs, and two pools is preferable, at least
2-13
-------
one of each habitat type should be evaluated. Mid-
channel and wetland areas of large rivers, which are
difficult to sample effectively, may be avoided. Sam-
pling effort may be concentrated in near-shore habitats
where most species will be collected. In doing so,
some deep water or wetland species may be under-
sampled, however, the data should be adequate for the
objective of RBP V.
2.8.3 Fish Sample Processing and
Enumeration
To ensure data comparability for assessing biologi-
cal condition with fish RBP V, sample processing and
species enumeration must be standardized.
Processing of the fish biosurvey sample includes
identification of all individuals to species, weighing (if
biomass data are desired), and recording incidence of
external anomalies. It is recommended that each fish
be identified and counted. Subsamples of abundant
species may be weighed if live wells are unavailable.
(This is especially important for warmwater sites,
where handling mortality is highly probable.) The
data from the counted and weighed subsample is
extrapolated for the total. Ohio EPA (1987a) found that
subsampling reduced potential error and made the
extra time required for weighing insignificant. Proce-
dural details for subsampling are presented in Ohio
EPA 1987c. Determination of trophic guild designation
is also necessary for some FBI metrics.
2X4 Fish Environmental Tolerance
Characterizations
Use of the IBI in fish RBP V requires classifica-
tion of fish species in terms of environmental toler-
ance. Responses of individual species to pollution will
vary regionally and according to the type of pollutant.
Tolerance characterizations of selected midwestern and
northwestern fish species are presented in Appendix
D. Effective use of the tolerance characterization
approach requires an appropriate regional tolerance
characterization system. Regional modifications or
substitutions may be based upon regional fish refer-
ences, historical distribution records, objective assess-
ment of a large statewide database, and toxicological
test data. IBI tests in the southeastern and south-
western United States, and its widespread use by
water resource agencies may result in additional
modifications. Past modifications have occurred (Sec-
tion 7.2.2.1, Miller et al. 1988a) without changing the
IBI's basic theoretical foundations.
2-14
-------
3. OVERVIEW OF PROTOCOLS AND
SUMMARY OF COMPONENTS
The bioassessment protocols presented in this
document provide guidance to those agencies not
presently using biosurveys as investigative tools or
who are seeking alternatives to their present methods.
Agencies with successful biological monitoring pro-
grams are encouraged to continue their programs and
provide further leadership and guidance in the use of
bioassessment. The five separate protocols presented
below reflect different levels of effort and expertise
and focus on different objectives.
3.1 SUMMARY OF THE
PROTOCOLS
A summary of the key features of the five pro-
tocols is presented in Table 3.1-1. The first and fourth
protocols are subjective because an investigator or
agency may conduct any level of investigation deemed
necessary. The presence or absence of impairment
using Rapid Bioassessment Protocols (RBPs) I and IV
is supported by a limited analysis of the biological
communities. Benthic RBP I and fish RBP IV are
used as screening or reconnaissance techniques for
discerning biological impairment. Benthic RBPs II and
III, and fish RBP V are progressively more rigorous
and are intended to provide more objective and repro-
ducible evaluations than RBPs I and IV. RBPs II, III,
and V are designed to be semi-quantitative and utilize
an integrated analysis technique to provide continuity
in the evaluation of impairment among sites and sea-
sons. The primary difference between RBPs II, III
and V is the level of taxonomic resolution (i.e.,
family level vs. genus/species level identification)
necessary to perform an assessment. RBPs III and V
require more time and expertise than RBP II, but are
better able to discriminate degrees of impairment.
3.2 OBJECTIVES OF
THE PROTOCOLS
As presented in Figure 3.2-1, selection of the
appropriate bioassessment approach depends on the
objectives of the study. RBPs I and IV provide a
screening mechanism for identification of biological
impairment; they are not intended to quantify the
degree of impairment nor provide definitive data that
would be used to establish a cause-and-effect. RBPs I
and IV allow a cursory assessment incorporating the
cost and time efficiencies necessary to evaluate a large
number of sites. RBPs I and IV are used primarily to
identify major water quality problems as an aid in
planning and developing management strategies.
The information derived from benthic RBP II pro-
vides a basis for ranking sites as severely or moder-
ately impaired. This classification can then be used to
focus additional study or regulatory action. RBP II
can also be used as a screening technique in lieu of
benthic RBP I. Like RBP I, RBP II is designed to
enable agencies to evaluate a large number of sites
with relatively limited time and effort. However, the
concept of a documented procedure for collections,
inherent in RBP II and intended to promote a consis-
tent level of effort, allows for better comparison
among sites.
The primary objective of benthic RBP III and fish
RBP V is to provide a consistent, well-documented
biological assessment. Repeatable results provide a
basis for comparison among sites over time (trend
monitoring). The ability to discriminate the level of
impairment among sites is enhanced by performing
taxonomic identifications to the lowest practical level,
thereby providing information on population as well as
community level effects. RBPs III and V can be used
to rank sites according to impairment in lieu of
RBP II, but will also establish a basis for trend
monitoring over a period of time. RBPs III and V
place still greater emphasis on consistency in unit
effort and documentation.
3.3 LEVEL OF EFFORT AND
INVESTIGATOR EXPERTISE
The level of effort required for RBP I is estimated
to be 1 to 2 hours per station, excluding travel time.
The effort consists of habitat assessment, physico-
chemical measurements, and biological collections and
observations. All of this effort is expended in the
field. An additional 0.5 to 1 hour of data analysis and
3-1
-------
TABLE 3.1-1 COMPARISON OF RAPID BIOASSESSMENT PROTOCOLS
Protocol I
Protocol II
Protocol III
Protocol IV
Protocol V
Objectives
Level of Effort
(per station}
Experience
Required
Minimal Skill Mix
Habitat Assessment
Water Quality and
Phys/Chen
Determine whether
biological inpair-
aent exists
Determine if further
investigation is
needed
Field—1 to 2 hours/
person (1 person)
Lab—None
Data—0.5 to 1 hour
(1 person)
Budget—Total of 1.5
to 3 work hours
High level of pro-
fessional impact
assessment
experience
Knowledge of benthic
invertebrate ecology
Biologist
Characterize and
rate substrate/
instream cover,
channel morphology,
and riparian/bank
structure
Measure conventional
water quality
parameters
Examine physical
characteristics
. Assess biological
impairment
. Provide infornation
for ranking sites
. Prioritize sites for
further assessment
and/or testing
(toxicity, chenical)
Field—1.5 to 2.5
hours/person (2 per-
sons )
Lab—None
Data — 2 to 4 hours
(1 person)
Budget—Total of 5
to 9 work hours
Professional impact
assessment experience
Knowledge of benthic
ecology and taxonomy
Biologist and
technician
Characterize and rate
substrate/instream
cover, channel
morphology, and
riparian/bank
structure
Measure conventional
water quality
parameters
Examine physical
characteristics
Assess biological
impai rment
Establish basis for
trend monitoring
Prioritize for further
assessment and/or
testing (toxicity,
chenical)
Field—1 to 2 hours/
person (2 persons)
Lab—2 to 3 hours
(1 person)
Data—1 to 3 hours
(1 person)
Budget—Total of 5
to 10-work hours
Professional impact
assessment experience
Knowledge of benthic
ecology and taxonomy
Biologist and
technician
Characterize and rate
substrate/instream
cover, channel
morphology, and
r ipa r ian/bank
structure
Measure conventional
water quality
parameters
Examine physical
characteristics
Determine whether
biological impairment
exists
Determine if further
investigation is
needed
Field—None
Lab—None
Data — 3 hours
(1 person)
Budget—Total- of
3 work hours
Survey design
experience
Knowledge in broad
patterns of fish
species distribution
and abundance
Biologist
Characterise and ratt
substrate/instream
cover, channel
morphology, and
riparian/bank
structure
Measure conventional
water quality
parameters
Examine physical
characteristics
Assess biological
impa i rment
Establish basis for
trend aonitoring
Provide information
for ranking sites
Prioritize for
further assessment
and/or testing
(toxicity, chemical)
Field—1-5 hours/
pe rson
(2 persons minimum)
Lab—None
Data —1-2 hours
(1 person)
Budget—Total of 3 to
17 work hours
Professional impact
assessment experience
Knowledge in the use
of the IBI and 1KB
Biologist and
technician(s)
Characterise and rati
substrate/instream
cover, channel mor-
phology, and
riparian/bank
structure
Measure conventional
water quality
parameters
Examine physical
characteristics
-------
TABLE 3.1-1 (Cont.)
Protocol I
Protocol II
Protocol III
Protocol IV
Protocol V
Biosurvey
Cursory examination
Determine relative
abundance of aacro-
benthos; field IDs
Exaaination focusing
on the riffle/run
coaaunity,
supplenented with a
CPOH saaple
100-organisa sub-
sample IDed in field
to faaily or order
level
Functional Feeding
Group analysis of
riffle/run and CPON
sample in the field
Examination focusing
on the riffle/run
coaaunity,
supplemented with a
CPOH sample
Collect riffle/run
benthos; collect CPON
saaple, deteraine
Shredder abundance
Preserve riffle/run
sample, return to lab,
do 100-organism sub-
sample, IDs to species
level and Functional
Feeding Group analysis
Questionnaire survey
Survey ecoregional
reference reaches and
randomly selected
reaches
Examination with
sampling of all major
habitats and cover
types
Collect fish, note
condition, ID to
species level in
the field
Preserve voucher col-
lection for deposit
in museum
Analysis
Conclusion
Minimal; deteraine
presence or absence
of iapairment
Determine if iapair-
ment exists
Indicate generic
(habitat, organic
enr ichaent,
toxicity|
Integrated assessaent
of metrics measuring
various components of
family level com-
munity structure
Characterise
conditions as no
impairment, moderate
impairment, severe
impa i rment
Indicate generic
cause of iapairaent
(habitat, organic
enrichaent, toxicity)
Integrated assessment
of aetrics measuring
various components of
genus/species level
community structure
Evaluate site as no
impairment, slight
iapairaent, aoderate
impairment, severe
impairment
Indicate generic cause
of iapairaent
(habitat, organic
enrichaent, toxicity)
Summarize survey
responses to deter-
aine degree and
probable cause of
impairment
Deteraine if impair-
ment exists
Indicate generic
cause of iapairment
(habitat, water
quali ty)
Integrated assessment
of metrics measuring
various components of
species, family, and
trophic level com-
munity structure
Evaluate biological
integrity as
excellent, good,
fair, poor, very poor
Indicate generic
cause of impairment
(habitat, organic
enrichment, toxicity)
-------
APPROACH
Decide on
Monitoring
Objectives
SCREENING
-Limited Effort
-Impairment
Noted
r~
i
SITE RANKING
Level One I
1
-Focus on
Communities
-Three Levels
of Impairment
Detected
i
Level Two
1
-Focus on
Communities
and Populations
-Four Levels
of Impairment
Detected
Figure 3.2-1. Overview of the five bioassessment approaches and their primary objectives.
evaluation might be needed. No laboratory analysis is
anticipated for RBP I. Only a single experienced biol-
ogist is needed to conduct RBP I. However, a second
person, for reasons of safety, quality control, or train-
ing, may be assigned by the agency.
The biologist conducting RBP I should have
professional impact assessment experience with knowl-
edge of benthic invertebrate ecology. A HIGHLY
EXPERIENCED INDIVIDUAL IS REQUIRED. The
accuracy of the assessment depends upon the biolo-
gist's professional integrity.
The field survey for RBP II can be completed by
two persons in 1.5 to 2.5 workhours per person for
each station, excluding travel time. The necessity for a
reconnaissance survey (similar to RBP I) is somewhat
dependent on agency familiarity with the site and pur-
pose of the investigation. Habitat assessment, physico-
chemical measurements, and biological collections/
observations are also required in this protocol. All of
the sorting and identifications (family level) are done
in the field to minimize laboratory time. RBP II
requires one field investigator experienced in impact
assessment, benthic ecology, and taxonomy. The sec-
ond field person can be a trained technician with a
biological background. Data analysis may take from 1
to 2 hours per station and should be performed by an
experienced biologist. Use of computers for data entry
and calculation of results provides optimal time effi-
ciency for data analysis. Hand calculation of results
may require an additional 1 to 2 hours per station for
data analysis.
The field effort for RBP III can be done by two
biologists in 1 to 2 workhours per biologist for each
station. RBP III is the most detailed of the benthic
protocols and provides a means of obtaining repeat-
able results; the sorting and identification tasks are
conducted in the laboratory. Laboratory processing is
estimated to take 2 to 3 hours per station for one biol-
ogist. Data analysis is expected to take an additional 1
to 3 hours per station for one biologist. One of the
field investigators must be experienced in impact
assessment of benthic communities. This investigator
should also perform the data analysis to provide con-
tinuity throughout the assessment process. The person
performing the laboratory analysis needs to be
experienced in taxonomy, but does not necessarily
need to perform the final assessment. Data analysis
can be expedited by computerized data entry for cal-
culation of results. An additional 1 to 2 hours per sta-
tion may be required if results are hand calculated. As
field and analysis procedures are mastered, time effi-
ciencies can be expected.
The level of field effort for RBP IV requires 1 to
3 work hours per reach. This includes reach selec-
3-4
-------
tion, respondent identification, mailing, questionnaire
completion, and response tabulation. No additional
field or laboratory work is required and no travel or
equipment are necessary. All effort is expended in the
office and is independent of season or weather condi-
tions. The designer of the survey must be familiar
with survey design. Respondents should also be famil-
iar with broad patterns in species distribution and
abundance. The accuracy of statements depends on the
respondent's professional knowledge and integrity.
Only one respondent is needed per reach but some
confirmation from additional sources and methods is
advisable for quality assurance.
The level of effort for RBP V includes 1 to 5
hours for fish collection and identification (depending
upon habitat complexity and gear used), and 1 to 2
hours for data analysis. Data analysis can be per-
formed by one biologist. The field effort requires a
minimum of 2 persons; up to 5 people may be needed
in wide shallow rivers and rivers with complex
habitats. Typically, using this protocol, stream sites
can be sampled and data analyzed within a total of 5
. hours. At least one biologist should have professional
impact assessment experience, with specific knowl-
edge in the use of the Index of Biotic Integrity (IBI)
and the Index of Well Being (IWB). This biologist
should be involved in all phases of the protocol to
improve continuity and to provide greater insight. The
remaining crew members can be experienced techni-
cians. Sample quality can be assessed by replicate
sampling and inter-crew sampling.
3-5
-------
4. QUALITY ASSURANCE/QUALITY CONTROL
Effective quality assurance and quality control
(QA/QC) procedures and a clear delineation of
QA/QC responsibilities are essential to ensure the
utility of environmental monitoring data. The term
"quality control" refers to the routine application of
procedures for obtaining prescribed standards of per-
formance in the monitoring and measurement process.
The term "quality assurance" includes the quality
control functions and involves a totally integrated pro-
gram for ensuring the reliability of monitoring and
measurement data.
4.1 PROGRAM DESCRIPTION
The U.S. EPA QA/QC program requires that all
EPA national program offices, EPA regional offices,
and EPA laboratories participate in a centrally
planned, directed, and coordinated Agency-wide
QA/QC program. This requirement also applies to
efforts carried out by the States and interstate agencies
that are supported by EPA through grants, contracts,
or other formalized agreements. The EPA QA pro-
gram is based upon EPA order 5360.1, "Policy and
Program Requirements to Implement the Quality
Assurance Program" (U.S. EPA 1984a), which
describes the policy, objectives, and responsibilities of
all EPA Program and Regional offices.
Each office or laboratory that generates data under
EPA's QA/QC program must implement, at a mini-
mum, the prescribed procedures to ensure that preci-
sion, accuracy, completeness, comparability, and
representativeness of data are known and documented.
4.2 DATA QUALITY OBJECTIVES
A full assessment of the data quality needed to
meet the intended use should be made prior to
specification of QA/QC controls. The determination of
data quality is accomplished through the development
of data quality objectives (DQOs). DQOs are qualita-
tive and quantitative statements developed by data
users to specify the quality of data needed to support
specific decisions or regulatory actions. Establishment
of DQOs involves interaction of decision-makers and
the technical staff.
The process for developing DQOs includes a first
stage involving input by the decision-maker regarding
the information needed, reasons for the need, how the
information will be used, and specification of any
time and resource constraints. The second stage in
developing DQOs involves clarification of the specific
problem. Here, the technical staff and decision-maker
interact to establish a detailed specification of the
problem and any constraints imposed on data collec-
tion. The third stage involves developing alternative
approaches to data collection, selecting the approach
to be used, and establishing the final data quality
objectives. Once the data collection approach and data
quality objectives have been established, a clear
understanding of data quality will help ensure success-
ful study completion. U.S. EPA (1984b) describes the
process for developing DQOs in more detail.
4.3 QUALITY ASSURANCE
PROGRAM PLANS AND
PROJECT PLANS
To provide adequate control and guidance, the
Agency's QA program relies on the development and
implementation of two QA documents: the QA Pro-
gram Plan and the QA Project Plan. These plans are
required of all recipients of EPA grants and assistance
programs. Grant regulations, 40 CFR Part 30, require
submission of QA Program Plans to EPA as a prior
condition of receiving an EPA grant. QA Project
Plans also must be developed according to an accept-
able schedule within the QA Program Plan. The QA
Program Plan (U.S. EPA 1980a) describes manage-
ment policies, organization, objectives, principles, and
general procedures that establish how data of known
and acceptable quality will be produced. The QA
Project Plan describes and defines specific objectives,
network design, procedures, methods, and controls
that will be applied to a specific project to ensure the
production of data of known and acceptable quality.
Two guidance documents are available to assist in
preparation of the QA Project Plan: a general gui-
dance document (U.S. EPA 1980b) and a more
detailed guidance document that combines a work
plan with the QA Project Plan (U.S. EPA 1984c).
These documents also provide guidance on the use of
a short form for limited surveys.
4-1
-------
4.4 EPA RESPONSIBILITIES
EPA Headquarters is responsible for providing gui-
dance for developing Quality Assurance Program
Plans and Quality Assurance Project Plans. This
includes updates necessitated by new Agency require-
ments and additional technical guidance for the
Regional offices and States to develop sound plans. In
addition, Headquarters is responsible for developing
guidance for inclusion of Data Quality Objectives in
Quality Assurance Project Plans and providing gui-
dance to the Regions on application of the DQO
development process. In order to provide on-going-
guidance, the Office of Water has formed a Water
Monitoring Data Quality Objective Advisory Group.
EPA Regional offices are responsible for develop-
ing Quality Assurance Program Plans and Quality
Assurance Project Plans for the activities that they
conduct. In addition, they are responsible for ensuring
that States prepare QA Program Plans and Project
Plans in conformance with grant requirements speci-
fied in 40 CFR Part 30. The Regions are responsible
for developing DQO requirements compatible with
Headquarter's requirements and meeting the Regions'
specific needs. The Regions are also .responsible for
assisting the States in developing DQO requirements
that meet State needs.
4.5 IMPORTANCE OF QA/QC
FOR RAPID BIOASSESSMENTS
Quality assurance and control (QA/QC) should be
a continuous process implemented throughout the
entire bioassessment program. All aspects of the
study, including field collection, habitat assessment,
lab processing, and data analysis are subject to
QA/QC procedures. As with any scientific study,
quality must be assured before the results can be
accepted. As described below, quality assurance is
accomplished-through establishment of thorough inves-
tigator training, protocol guidelines, comprehensive
field and lab data documentation and management,
verification of data reproducibility, and instrument
calibration.
The protocols for rapid bioassessment presented in
this document can be modified to achieve specific
objectives. A different habitat assessment approach,
replicate sampling, more intensive sample enumera-
tion, or modified analytical metrics may be preferred
by a particular State over the methods suggested in the
RBPs. Such refinements can be accommodated,
provided they are clearly documented in an EPA
approved Quality Assurance Program and/or Project
Plan.
Training
All personnel conducting assessments must be
trained in a consistent manner (preferably by the same
person) to ensure that the assessments are conducted
properly and to ensure standardization. At least one
investigator for each site should be a professional biol-
ogist trained and skilled in field aquatic sampling
methods and organism identification. Additionally, the
investigator should be familiar with the objectives of
each site investigation. Each agency should have a
designated QA/QC officer (or a person in charge of
the program) responsible for maintaining consistency
among investigators. At regularly scheduled intervals,
the QA/QC officer should visit selected overlap sites
and perform assessment techniques to use as a repli-
cate of a previous assessment. Results from two sepa-
rate assessments conducted by two different teams can
determine if reproducible results are being attained.
Quality control of taxonomic identifications can also
be evaluated in this way.
Standard Procedures
It is the responsibility of each agency to define
precise methods and review inconsistencies before the
assessment begins. Because RBPs I and IV are
primarily subjective investigations, a specific level of
effort should be established prior to the actual field
investigation. Taxonomic identification is required at
various levels for RBP I (order level), RBP II (family
level), RBP III (genus and species level), and RBP V
(species level). Field experience and taxonomic exper-
tise requirements for the particular level of assessment
performed must be met. Any deviations from the pro-
tocol should be documented as to the reason for devi-
ation, and corrective actions taken.
Field validation, conducted at a frequency to be
determined by each agency, should involve two proce-
dures: (1) collection of replicate samples at various
stations to check on the accuracy of the collection
effort, and (2) repeat field collections and analyses
performed by separate field crews to provide support
for the bioassessment. In addition, field crews should
occasionally alternate personnel to maintain objectivity
in the bioassessment.
Documentation
The field data sheets should be filled out as com-
pletely and as accurately as possible to provide a rec-
ord in support of the survey and analysis conclusions.
Abbreviations commonly used in documentation (e.g.,
4-2
-------
scientific names) should be standardized to decrease
data manipulation errors. Field and laboratory data
sheets and final reports should be filed.
Habitat Assessment
Because the habitat characterization step of the
protocols is primarily a subjective evaluation, final
conclusions are potentially subject to variability
among investigators. This limitation can be mini-
mized, however, by ensuring that each investigator is
appropriately trained in the evaluation technique and •
periodic cross-checks are conducted among investiga-
tors to promote consistency.
Benthic Collections
The data developed during the benthic collection
effort is directly comparable to data developed at
other sites because: (1) only similar habitats are sam-
pled at each site, and (2) a uniform method (consis-
tent unit of effort, 100-organism count) is used for
benthic data acquisition. To ensure that sampling
methods are applicable to a specific region, results
may be evaluated by comparing results obtained using
other sampling methods. To ensure reproducible data,
well characterized sites should be periodically resam-
pled by a variety of investigators. To document con-
sistency among field teams, selected sites should be
sampled simultaneously by several field teams.
Fish Collections
To ensure fish field survey data is representative of
the fish assemblage at a particular site requires careful
regional analysis and station siting. Data comparability
is maintained by using similar collection methods and
sampling effort in waterbodies of similar size. Also,
where possible, major habitats (riffle, run, pool) are
sampled at each site, and the proportion of each habi-
tat type sampled, should be comparable.
Precision, accuracy, and completeness should be
evaluated in pilot studies along with sampling methods
and site size. Variability among replicates from the
same site or similar sites, should not produce differ-
ences exceeding 10 percent at minimally-impacted sites
and 15 percent at highly-impacted sites. IBI differ-
ences at the same site should not exceed 4 (Karr et al.
1986).
Data reproducibility may be ensured by having a
variety of investigatprs periodically resample well
characterized sites. Investigator accuracy for use of the
IBI and the IWB may be determined by having inves-
tigators evaluate a standard series of data sets or
preserved field collections.
Calibration of Instruments
Instruments used for measuring water quality, cur-
rent velocity, or any other measurable parameters
should be calibrated with known standards. All field
measurements should be accompanied by documenta-
tion of the type of instrument and the identification
number of the instrument used.
4-3
-------
5. HABITAT ASSESSMENT AND
PHYSICOCHEMICAL PARAMETERS
An evaluation of habitat quality is critical to any
assessment of ecological integrity. The habitat quality
evaluation can be accomplished by characterizing
selected physicochemical parameters and systematic
habitat assessment. Through this approach, key
parameters can be identified to provide a consistent
assessment of habitat quality. This evaluation of
habitat quality is relevant to all levels of rapid
bioassessment.
5.1 PHYSICAL
CHARACTERISTICS
AND WATER QUALITY
Both physical characteristics and water quality
parameters are pertinent to characterization of the
stream habitat. An example of the data sheet used to
characterize the physical characteristics and water
quality of a site is shown in Figure 5.1-1. The infor-
mation requested includes measurements made rou-
tinely during biological surveys. This phase of the
survey is broken into two sections: Physical Charac-
terization and Water Quality (Figure 5.1-1). These sec-
tions are discussed separately below.
5.1.1 Physical Characterization
Physical characterization parameters include esti-
mations of general land use and physical stream
characteristics such as width, depth, flow, and sub-
. strate. The evaluation begins with the riparian zone
(stream bank and drainage area) and proceeds
instream to sediment/substrate descriptions. Such
information will provide insight as to what organisms
may be present or are expected to be present, and to
presence of stream impacts. The information requested
in the Physical Characterization section of the Field
Data Sheet (Figure 5.1-1) is briefly discussed below.
Predominant Surrounding Land Use: Observe the
prevalent land-use type in the vicinity (noting any
other land uses in the area which, although not pre-
dominant, may potentially affect water quality).
Local Watershed Erosion—The existing or potential
detachment of soil within the local watershed (the por-
tion of the watershed that drains directly into the
stream) and its movement into a stream is noted. Ero-
sion can be rated through visual observation of water-
shed and stream characteristics. (Note any turbidity
observed during water quality assessment below.)
Local Watershed Nonpoint-Source Pollution—This
item refers to problems and potential problems other
than siltation. Nonpoint-source pollution is defined as
diffuse agricultural and urban runoff. Other com-
promising factors in a watershed that may affect water
quality are feedlots, wetlands, septic systems, dams
and impoundments, and/or mine seepage.
Estimated Stream Width (m): Estimate the distance
from shore to shore at a transect representative of the
stream width in the area.
Estimated Stream Depth (m): Riffle, run, and pool.
Estimate the vertical distance from water surface to
stream bottom at a representative depth at each of the
three habitat types.
High Water Mark (m): Estimate the vertical distance
from the stream bank to the peak overflow level, as
indicated by debris hanging in bank or floodplain
vegetation, and deposition of silt or soil. In instances
where bank overflow is rare, a high water mark may
not be evident.
Velocity: Record an estimate of stream velocity in a
representative run area.
Dam Present: Indicate the presence or absence of a
dam upstream or downstream of the sampling station.
If a dam is present, include specific information relat-
ing to alteration of flow.
Channelized: Indicate whether or not the area around
the sampling station is channelized.
Canopy Cover: Note the general proportion of open
to shaded area which best describes the amount of
cover at the sampling station.
Sediment Odors: Disturb sediment and note any
odors described (or include any other odors not listed)
5-1
-------
PHYSICAL CBABACTERISATIOB/VATE8 QUALITY
FIELD DATA SHEET
PBT3ICAI. CBABJLCTERI1ATIOB
BIPABIAB EOBE/IBSTBEAH FIXTURES
Predominant Surrounding Land Uaa:
Poraet riald/paiture Agricultural Raaidential Co»ercial
Local tratarahed Eroaion: Ion* Moderate Heavy
tool Waterehed BP3 Pollution: Bo evidence Sone Potential Sourcea
Eatiuatad Stream Width B Estimated Stream D«pth: Biffl*
High H>t«r Mark n V.loclty Dai Pr«««nt: Taa
Partly Opan Partly Shadad
Canopy Covar: Opan
SEDImaT/SUBSTBATB:
sadiaant Odora: Uoraial
Sodiaiant Oila: Abaont
Industrial
Obvioua Sourcaa
Run n Pool
Channalilad: Taa
Oth.c
Sawaga Patrolaua Chaaical
Slight Hodarata profuaa
Anaerobic
•: Sludge Savduat Ptpar ribar Sand Belict Shells Other
Are the underaidea of atoi.ea which ara not deeply ambidded black? Yes Bo
Substrata Typa
B drock
B ulder
C bble
0 aval
S nd
Silt
Clay
Percent
Compoait ion
Diameter in Sampling Area
>256-mm (10 in.)
<4-}S6-mm (2.5-10 in.)
2-C4-mm (0.1-2.5 in. )
0.06-2.00-mm (gritty)
.004-.06-mm
<.004-mm (slick)
Percent
Composition
Substrate Type characteristic in Sampling Araa
Datritua Sticks, Wood,
Coarse Plant
Materials (CPOM)
Muck-Hud alack. Very fine
Organic (rPOH)
Marl dray. Shell
pragmenta
HATEB QUALITY
C Dlaaolvad Oiygen pH Conductivity Other
Straaa Typa: Colduatar Waraiwatar
Watar Odora: Boraal Sawaga Patrolaun Chaaical Bona Othar
Hatar Surtaca Ofli: slick Shaan Globa rlacka Bona
Turbidity: Claar Slightly Turbid Turbid Opag.ua Uatar Color
HEATBEB COBDITIOHS
PHOTOOBAPH HUMBEB
OBSERVATIONS AHD/OR SKETCB
Figure 5.1-1. Physical Characterization/Water Quality Field Data Sheet for use with all Rapid Bioassessment Protocols.
-------
which are associated with sediment in the area of the
sampling station.
Sediment Oils: Note the term which best describes
the relative amount of any sediment oils observed in
the sampling area.
Sediment Deposits: Note those deposits described (or
include any other deposits not listed) which are pres-
ent in the sampling area. Also indicate whether the
undersides of rocks not deeply embedded are black
(which generally indicates low dissolved oxygen or
anaerobic conditions).
Inorganic Substrate Components: Visually estimate
the relative proportion of each of the seven sub-
strate/particle types listed that are present in the sam-
pling area.
Organic Substrate Components: Indicate relative
abundance of each of the three substrate types listed.
5.1.2 Water Quality
Information requested in this section (Figure 5.1-1)
is standard to many aquatic studies and allows for
some comparison between sites. Additionally, condi-
tions that may significantly affect aquatic biota are
documented. Documentation of recent and current
weather conditions is important because of the poten-
tial impact that weather may have on water quality. To
complete this phase of the bioassessment, a photo-
graph may be helpful in identifying station location
and documenting habitat conditions. Any observations
or data not requested but deemed important by the
field observer should be recorded. This section is
identical for all protocols and the specific data
requested are described below.
Temperature (C), Dissolved Oxygen, pH, Conduc-
tivity: Measure and record values for each of the
water quality parameters indicated, using the appropri-
ate calibrated water quality instrument(s). Note the
type of instrument and unit number used.
Stream Type: Note the appropriate stream designa-
tion according to State water quality standards.
Water Odors: Note those odors described (or include
any other odors not listed) that are associated with the
water in the sampling area.
Water Surface Oils: Note the term that best describes
the relative amount of any oils present on the water
surface.
Turbidity: Note the term which, based upon visual
observation, best describes the amount of material
suspended in the water column.
5.2 HABITAT ASSESSMENT
The habitat assessment matrix (Figure 5.2-1) is
based on the Stream Classification Guidelines for
Wisconsin developed by Ball (1982) and Methods of
Evaluating Stream, Riparian, and Biotic Conditions
developed by Platts et al. (1983). Because this habitat
assessment approach is intended to support biosurvey
analysis, the various habitat parameters are weighted
to emphasize the most biologically significant
parameters. All parameters are evaluated for each sta-
tion studied. The ratings are then totaled and com-
pared to a reference to provide a final habitat ranking.
Scores increase as habitat quality increases. To ensure
consistency in the evaluation procedure, descriptions
of the physical parameters and relative criteria are
included in the rating form.
Reference conditions are used to normalize the
assessment to the "best attainable" situation. This
approach is critical to the assessment because stream
characteristics will vary dramatically across different
regions. Other habitat assessment approaches may be
used; or a more rigorously quantitative approach to
measuring the habitat parameters may be used. How-
ever, the importance of a holistic habitat assessment to
enhance the interpretation of biological data cannot be
overemphasized. A more detailed discussion of the
relationship between habitat quality and biological
condition is presented in Chapter 8.
Habitat parameters pertinent to the assessment of
habitat quality are separated into three principal cate-
gories: primary, secondary, and tertiary parameters.
Primary parameters are those that characterize the
stream "microscale" habitat and have the greatest
direct influence on the structure of the indigenous
communities. The primary parameters, which include
characterization of the bottom substrate and available
cover, estimation of embeddedness, and estimation of
the flow or velocity and depth regime, have the widest
score range (0-20) to reflect their contribution to hab-
itat quality. The secondary parameters measure the
"macroscale" habitat such as channel morphology
characteristics. These parameters evaluate: channel
alteration, bottom scouring and deposition, and stream
sinuosity. The secondary parameters have a score
range of 0-15. Tertiary parameters evaluate riparian
and bank structure and comprise three parameters:
bank stability, bank vegetation, and streamside cover.
These tertiary parameters include those that are most
often ignored in biosurveys. The tertiary parameters
have a score range of 0-10.
5-3
-------
Condition
Condition/Parameter
PRIMARY—SUBSTRATE AND INSTREAM COVER
1. Bottom substrate and available cover
2. Embeddedness
3. Flow/velocity
SECONDARY-CHANNEL MORPHOLOGY
4. Channel alteration
5. Bottom scouring and deposition
6. Pool/riffle, run/bend ratio
TERTIARY—RIPARIAN AND BANK STRUCTURE
7. Bank stability
8. Bank vegetation
9. Streamside cover
Excellent Good
16-20 11-15
16-20 11-15
16-20 11-15
12-15
12-15
12-15
9-10
9-10
9-10
8-11
8-11
8-11
6-8
6-8
6-8
Fair
6-10
6-10
6-10
4-7
4-7
4-7
3-5
3-5
3-5
Poor
0-5
0-5
0-5
0-3
0-3
0-3
0-2
0-2
0-2
Habitat evaluations are first made on instream hab-
itat, followed by channel morphology, and finally on
structural features of the bank and riparian vegetation.
Stream segment length or area assessed will vary with
each site. Generally, primary parameters are evaluated
within the first riffle/pool sequence, or the immediate
sampling area, such as in the case of fish sampling.
Secondary and tertiary parameters are evaluated over a
larger stream area, primarily in an upstream direction
where conditions will have the greatest impact on the
community being studied. The actual habitat assess-
ment process involves rating the nine parameters as
excellent, good, fair, or poor based on the criteria
included on the Habitat Assessment Field Data Sheet
(Figure 5.2-1).
A total score is obtained for each biological station
and compared to a site-specific control or regional
reference station. The ratio between the score for the
station of interest and the score for the control or
regional reference provides a percent comparability
measure for each station. The station is then classified
on the basis of its similarity to expected conditions (as
represented by the control or reference station), and
its apparent potential to support an acceptable level of
biological health.
Use of a percent comparability evaluation allows
for regional and stream-size differences which affect
flow or velocity, substrate, and channel morphology.
Some regions are characterized by streams having a
low channel gradient. Such streams are typically shal-
lower, have a greater pool/riffle or run/bend ratio, and
less stable substrate than streams with a steep channel
Assessment Category
Comparable to Reference
Supporting
Partially Supporting
Non-Supporting
Percent of
Comparability
>90%
75-88%
60-73%
<58%
gradient. Although some low gradient streams do not
provide the diversity of habitat or fauna afforded by
steeper gradient streams, they are characteristic of
certain regions. Using the approach presented here,
these streams may be evaluated relative to other low
gradient streams.
Listed below is a general explanation for each of
the nine habitat parameters to be evaluated.
5.2.1 Primary Parameters—
Substrate and Instream Cover
The primary instream habitat characteristics
directly pertinent to the support of aquatic communi-
ties consists of substrate type and stability, availability
of refugia, and migration/passage potential. These pri-
mary habitat parameters are weighted the highest to
reflect their degree of importance to biological
communities.
I. Bottom Substrate—This refers to the availability
of habitat for support of aquatic organisms. A vari-
ety of substrate materials and habitat types is
5-4
-------
HABITAT
ASSESSMENT FIELD DATA SHEET
Ca t ego ry
1. 'Bottom substrate/
aval 1 abl« cover
2. Embeddedness(b)
3 . 50.15 ens (Scf s ) •
•Floy, at rep. low
flow14'
or
>0 .15 cms ( Scf s I «
Velocity/depth
4. • Channel alteration
S. Bottom scouring and
depos it ion
(a) From Ball 1982.
(b) From Platts et al. 1983.
Excel lent
Greater than 50% rubble,
gravel, submerged logs,
undercut banks, or
other stable habitat.
16-20
Gravel, cobble, and
between 0 and 25 %
surrounded by fine
sediment
16-20
Cold >O.OS cms (2 cfs)
Warm >0.15 cms (5 cfs)
10-20
Slow (<0.3 m/s 1 , deep
(>O.S m); slow, shallow
( <0 .5 m) ; Cast
shallow habitats all
present .
16-20
point bars, and/or
no channelization.
12-15
Less than 51 of the
bottom affected by
scouring and
depos it ion .
12-15
Good
30-50% rubble, gravel
or other stable habitat.
Adequate habitat.
11-15
Gravel , cobble , and
between 25 and 50 t
surrounded by fine
sedi nent
11-15
0.03-0.05 cms (1-2 cfs)
0.05-0.15 cms (2-5 cfs)
11-15
Only 3 of the 4 habitat
categories present
(missing riffles or runs
missing pool s ) .
.11-15
coarse gravel; and/ or
some channelization
pr esent .
8-11
5-30% affected. Scour
at constrictions and
where grades steepen.
8-11
Fair
10-30% rubble, gravel
or other stable habitat.
Habitat availability
less than desirable.
6-10
Gravel, cobble, and
between 50 and 75 t
surrounded by fine
sediment
6-10
0.01-0.03 cms ( .5-1 cfsl
0.03-0.05 cms (1-2 cfs)
6-10
Only 2 of the 4 habitat
categories present
(missing riffles/runs
6-10
on old and new bars;
pools partially filled
ments .on both banks.
. 4-7
30-50% affected.
Deposits and scour at
4-7
Poo r
Less than 10% rubble
gravel or other stable
habitat. Lack of
habitat is obvious.
0-5
Gravel , cobble, and
over 75 % surrounded
by fine sediaent
0-5
(0.01 cms I . S cfs )
<0.03 cms (1 cfs)
0-5
Dominated by on'e
velocity/depth
category (usually
0-5
development; most pools
filled w/silt; and/or
0-3
More than 50% of the
bottom changing
nearly year long.
On ly la rge rocks
in riffle exposed.
0-3
Figure 5.2-1. Habitat Assessment Field Data Sheet for use with all Rapid Bioassessment Protocols.
-------
HABITAT ASSESSMENT FIELD DATA SHEET (cont.f
Ca t eao r v
6. Pool/riffle, run/bend 5-7. Variety of 7-15. Adequate depth
ratio (distance habitat. Deep riffles in pools and riffles.
between riffles divided and pools. Bends provide habitat.
by s t ream width )
12-15 8-11
7. Bank stability Stable. No evidence Moderately stable.
bank failure. of erosion mostly healed
Side slopes gener- over. Side slopes up to
ally <30% . Little 40% on one bank. Slight
probl em . f loods .
9-10 6-8
8. Bank vegetative Over 80% of the 50-79% of the streambank
covered by vegetation, gravel or
vegetation or boulders larger material.
and cobbl e'.
9-10 6-8
< b ) . . .
t s shrub . is of tree form.
9-10 6-8
Column Totals
Sco re
Fair
15-25. Occassional
riffle or bend. Bottom
contours provide some
habitat .
4-7
Mode rately unstable.
Mo derate frequency and
size of erosional areas.
Side slopes up to 60%
on some banks. High
erosion potential
during extreme high
flow.
3-5
25-49% of the stream-
by vegetation, gravel,
3-5
Dominant vegetation
is grass or f orbes .
3-5
Poo r
>25. Essentially a
straight stream.
Generally all flat
wa te r or sha 1 low
riffle. Poor
habitat .
0-3
Unstable - Many
eroded areas. Side
slopes > 60% common.
along straight sections
and bends.
0-2
Less than 25% of the
covered by vegetation,
gravel , or larger
ma t e r ia 1 .
0-2
Over 50% of the stream-
bank has no vegetation
and dominant material
is soil, rock, bridge
materials, culverts,
o r nine tail ings .
0-2
Figure 5.2-1. (Cont.).
-------
desirable. The presence of rock and gravel in flow-
ing streams is generally considered the most
desirable habitat. However, other forms of habitat
may provide the niches required for community
support. For example, logs, tree roots, submerged
or emergent vegetation, undercut banks, etc., will
provide excellent habitat for a variety of organisms,
particularly fish. Bottom substrate is evaluated and
rated by observation.
2. Embeddedness—The degree to which boulders,
rubble, or gravel are surrounded by fine sediment
indicates suitability of the stream substrate as habi-
tat for benthic macroinvertebrates and for fish
spawning and egg incubation. Embeddedness is
evaluated by visual observation of the degree to
which larger particles are surrounded by sediment.
In some western areas of the United States, embed-
dedness is regarded as the stability of cobble sub-
strate by measuring the depth of burial of large
particles (cobble, boulders).
3. Stream Flow and/or Stream Velocity—Stream
flow relates to the ability of a stream to provide
and maintain a stable aquatic environment. Stream
flow (water quantity) is most critical to the support
of aquatic communities when the representative low
flow is <0.15 cms (5 cfs). In these small streams,
flow should be estimated in a straight stretch of
run area where banks are parallel and bottom con-
tour is relatively flat. Even where a few stations
may have flows in excess of 0.15 cms, flow may
still be the predominating constraint. Therefore, the
evaluation is based on flow rather than velocity.
In larger streams and rivers (>0.15 cms), velocity,
in conjunction with depth, has a more direct
influence than flow on the structure of benthic
communities (Osborne and Hendricks 1983) and
fish communities (Oswood and Barber 1982). The
quality of the aquatic habitat can therefore be
evaluated in terms of a velocity and depth relation-
ship. As patterned after Oswood and Barber (1982),
four general categories of velocity and depth are
optimal for benthic and fish communities: (1) slow
(<0.3 m/s), shallow (<0.5 m); (2) slow
(<0.3 m/s), deep (>0.5 m); (3) fast (>0.3 m/s),
deep (>0.5 m); and (4) fast (>0.3 m/s), shallow
(<0.5 m). Habitat quality is reduced in the
absence of one or more of these four categories.
5.2.2 Secondary Parameters—
Channel Morphology
Channel morphology is determined by the flow
regime of the stream, local geology, land surface
form, soil, and human activities (Platts et al.
1983). The sediment movement along the channel,
as influenced by the tractive forces of flowing
water and the sinuosity of the channel, also affects
habitat conditions.
4. Channel Alteration—The character of sediment
deposits from upstream is an indication of the
severity of watershed and bank erosion and stability
of the stream system. The growth or appearance of
sediment bars tends to increase in depth and length
with continued watershed disturbance. Channel
alteration also results in deposition, which may
occur on the inside of bends, below channel con-
strictions, and where stream gradient flattens out.
Channelization (e.g., straightening, construction of
concrete embankments) decreases stream sinuosity,
thereby increasing stream velocity and the potential
for scouring.
5. Bottom Scouring and Deposition—These
parameters relate to the destruction of instream
habitat resulting from the problems described
above. Characteristics to observe are scoured sub-
strate and degree of siltation in pools and riffles.
Scouring results from high velocity flows. The
potential for scouring is increased by channeliza-
tion. Deposition and scouring result from the trans-
port of sediment or other particulates and may be
an indication of large scale watershed erosion.
Deposition and scouring is rated by estimating the
percentage of an evaluated reach that is scoured or
silted (i.e., 50-ft silted in a 100-ft stream length
equals 50 percent).
6. Pool/Riffle or Run/Bend Ratio—These parameters
assume that a stream with riffles or bends provides
more diverse habitat than a straight (run) or uni-
form depth stream. Bends are included because low
gradient streams may not have riffle areas, but
excellent habitat can be provided by the cutting
action of water at bends. The ratio is calculated by
dividing the average distance between riffles or
bends by the average stream width. If a stream
contains riffles and bends, the dominant feature
with the best habitat should be used.
5.2.3 Tertiary Parameters-
Riparian and Bank Structure
Well-vegetated banks are usually stable regard-
less of bank undercutting; undercutting actually
provides excellent cover for fish (Platts et al.
1983). The ability of vegetation and other materials
on the streambanks to prevent or inhibit erosion is
an important determinant of the stability of the
stream channel and instream habitat for indigenous
organisms. Because riparian and bank structure
indirectly affect the instream habitat features, they
are weighted less than the primary or secondary
parameters.
5-7
-------
Stream channel alteration downstream of WWTP.
5-8
-------
Tertiary parameters are evaluated by observation
of both upper and lower bank characteristics. The
upper bank is the land area from the break in the
general slope of the surrounding land to the normal
high water line. The upper bank is normally
vegetated and covered by water only during
extreme high water conditions. Land forms vary
from wide, flat floodplains to narrow, steep slopes.
The lower bank is the intermittently submerged
portion of the stream cross section from the nor-
mal high water line to the lower water line. The
lower channel defines the stream width.
7. Bank Stability—Bank stability is rated by observ-
ing existing or potential detachment of soil from
the upper and lower stream bank and its potential
movement into the stream. Steeper banks are
generally more subject to erosion and failure, and
may not support stable vegetation. Streams with
poor banks will often have poor instream habitat.
Adjustments should be made in areas with clay
banks where steep, raw areas may not be as sus-
ceptible to erosion as other soil types.
8. Bank Vegetative Stability—Bank soil is generally
held in place by plant root systems. Erosional pro-
tection may also be provided by boulder, cobble, or
gravel material. An estimate of the density of bank
vegetation (or proportion of boulder, cobble, or
gravel material) covering the bank provides an indi-
cation of bank stability and potential instream
sedimentation.
9. Streamside Cover—Streamside cover vegetation is
evaluated in terms of provision of stream-shading
and escape cover or refuge for fish. A rating is
obtained by visually determining the dominant
vegetation type covering the exposed stream bot-
tom, bank, and top of bank. Platts (1974) found
that Streamside cover consisting primarily of shrub
. had a higher fish standing crop than similar-size
streams having tree or grass Streamside cover.
Riparian vegetation dominated by shrubs and trees
provides the CPOM source in allochthonous
systems.
5-9
-------
Poor bank stability with high erosional potential.
Stream banks stabilized by dense vegetation.
5-10
-------
6. BENTHIC MACROINVERTEBRATE
BIOSURVEY AND DATA ANALYSIS
The biosurvey and data analysis components of the
three benthic bioassessment protocols are presented
below. All three protocols have common biosurvey
and data analysis elements. Common elements and
discussions are repeated in each protocol to maintain
discrete protocol integrity.
Examples of field and laboratory data sheets
referred to in this chapter are presented for guidance.
The example data sheets do not include headers for
documenting identifier information, and may be modi-
fied for the needs of different agencies. Descriptive
guidance for use with each data sheet is found in
Appendix A.
The three protocols consist of three basic compo-
nents: water quality/physical characteristics (Fig-
ure 5.1-1), habitat assessment (Figure 5.2-1), and a
biosurvey (Figures 6.1-1, 6.2-1, and 6.3-1). The overall
habitat assessment evaluates habitat quality using the
key environmental parameters described in Chapter 5.
If a degraded community is found from the results of
the biosurvey, habitat information will aid interpreta-
tion of effects relative to the biotic potential of a site.
The water quality and physical characterizations pro-
vide data on stream habitat quality as- well as potential
sources and/or causes of impairment.
6.1 RAPID BIOASSESSMENT
PROTOCOL I—Benthic
Macroinvertebrates
Rapid Bioassessment Protocol I (RBP I) is a
screening or reconnaissance assessment that involves
systematic -documentation of specific visual observa-
tions made in the field by a trained professional.
RBP I is used to discriminate obviously impacted and
non-impacted areas from potentially affected areas
requiring further investigation. Use of RBP I allows
rapid screening of a large number of sites. Areas
identified for further study can then be rigorously
evaluated using RBPs II, III, and V; quantitative fish
or benthic surveys; or ambient toxicity studies.
Because RBP I involves limited data generation, its
effectiveness depends largely on the experience ("best
professional judgment") of the professional biologist
performing the assessment. The biologist conducting
RBP I should have professional impact assessment
experience with a knowledge of aquatic ecology and
basic expertise in benthic macroinvertebrate taxonomy.
6.1.1 Field Methods
The biosurvey component of RBP I focuses on
qualitative sampling of benthic macroinvertebrates,
supplemented by a preliminary field examination of
other aquatic biota (periphyton, macrophytes, slimes,
and fish). Qualitative benthic samples are collected
from all available habitats using a dip net or kick net,
or by hand. Benthic macroinvertebrate orders/families
(e.g., families for Megaloptera and Diptera) collected
are listed on the Biosurvey Field Data Sheet (Fig-
ure 6.1-1), with an estimate of their relative abundance
in the sampling area. Each State agency should
develop its own definitions for abundance categories.
Lower levels of identification, if they are easily deter-
mined, can enhance the assessment. Any observations
on the relative abundance of other aquatic biota are
also noted; these observations provide additional infor-
mation on the presence or absence of impact.
6.1.2 Data Analysis Techniques
Impairment may be indicated by the absence of
generally pollution-sensitive benthic macroinvertebrate
taxa such as Ephemeroptera, Plecoptera, and Trichop-
tera (EPT); dominance of generally pollution-tolerant
groups such as Oligochaeta or Chironomidae; or over-
all low benthic abundance or taxa richness. Benthic
abundance or taxa richness indicative of impairment is
variable and must be evaluated with respect to the
waterbody being evaluated. Some headwater streams
are naturally unproductive and will be characterized
by low benthic abundance.and taxa richness in their
pristine state. Impairment may also be indicated by an
overabundance of slimes or filamentous algae in the
area or an absence of expected fish populations.
On the basis of the observations made on habitat,
water quality, physical characteristics, and the qualita-
tive biosurvey, the investigator determines whether
impairment is detected. The determination of impair-
ment requires the judgment of an experienced profes-
sional. If impairment is detected, the investigator
provides an estimation of the probable cause and
source on the Impairment Assessment Sheet (Fig-
ure 6.1-2). The aquatic biota that indicated an impair-
6-1
-------
Rapid Bioassessment Protocol I
Biosurvey Field Data Sheet
RELATIVE ABUNDANCE OF AQUATIC BIOTA
Periphyton 01234
Filamentous Algae 01234
Macrophytes 01234
0 = Absent/Not Observed 1 = Rare
Slimes
Macroinvertebrates
Fish
0 1
0 1
0 1
2 = Common
3 = Abundant
234
234
234
4 = Dominant
MACROBENTHOS QUALITATIVE SAMPLE LISTflndrcate Relative Abundance R = Rare, C = Common, A = Abundant, O = Dominant)
Porifera
Hydrozoa
Platyhelminthes
Turbellaria
Hirudinea
Oligochaeta
Isopoda
Amphipoda
pecapoda
Gastropoda
Bivalvia
Anisoptera
Zygoptera
Hemiptera
Coleoptera
Lepidoptera
Sialidae
Corydalidae
Tipulidae
Empididae
Simuliidae
Tabanidae
Culicidae
Chironomidae
Plecoptera
Ephemeroptera
Trichoptera
Other
Rare < 3
Observations
Common 3-9
Abundant > 10
Dominant > 50 (Estimate)
Figure 6.1-1. Biosurvey Field Data Sheet for use with Rapid Bioassessment Protocol I.
6-2
-------
IMPAIRMENT ASSESSMENT SHEET
1. Detection of impairment: Impairment detected No impairment
(Complete items 2-6) detected
(Stop here)
2. Biological impairment indicator:
Benthic macroinvertebrates Other aquatic communities
absence of EFT taxa Periphyton
dominance of tolerant groups filamentous
low benthic abundance other
lov taxa richness Macrophytes
other Slimes
Fish
3. Brief description of problem:
Year and date of previous surveys:
Survey date, available in:
Cause: (indicate major cause) organic enrichment toxicants flow
habitat limitations other
2
Estimated areal extent of problem (m ) and length of stream reach
affected (m), where applicable:
6. Suspected source(s) of problem:
point source discharge (name, type of facility, location)
construction site runoff
combined sewer outfall
silviculture runoff
animal feedlot
agricultural runoff
urban runoff
ground water
other
unknown
Briefly explain:
Figure 6.1-2. Impairment Assessment Sheet for use with macroinvertebrate Rapid Bioassessment Protocols.
6-3
-------
ment are noted, as are potential sources of pollutants.
The downstream extent of impact is estimated, and
multiplied by either the approximate stream width at
the estimated fully mixed zone or the width of the
discharge plume. This calculation provides an estimate
of the area impacted at the site.
6.2 RAPID BIOASSESSMENT
PROTOCOL II—Benthic
Macroinvertebrates
Rapid Bioassessment Protocol II (RBP II) utilizes
the systematic field collection and analysis of major
benthic taxa. RBP II provides a more intense assess-
ment than RBP I and can detect sites of intermediate
impairment with relatively little additional time and
effort. The protocol can be used to prioritize sites for
more intensive evaluation (i.e., RBP III, replicate
sampling, ambient toxicity testing, chemical charac-
terization) or can be used in lieu of RBP I as a
screening technique. RBP II is based on RBP III at a
reduced level of effort. RBP II incorporates the con-
cept of benthic analysis at the family taxonomic level,
as advocated by some States (e.g., Virginia, Illinois),
and utilizes field sorting and identification. This level
of effort involves minimal taxonomic identification and
is sufficient to address the objectives of RBP II. Furse
et al. (1984) stated that family-level classifications are
valuable in developing local site inventories of organ-
isms and in the evaluation of pollution monitoring
programs. The strength of RBP II is a result of sys-
tematic data collection procedures and the use of
recently developed data analysis techniques.
6.2.1 Field Methods
The biosurvey component of RBP II focuses on
standardized sampling of benthic macroinvertebrates,
supplemented by a cursory field observation of other
aquatic biota (periphyton, macrophytes, slimes, and
fish) (Figure 6.2-1). Although RBP II emphasizes the
benthic community, the observation of effects on other
aquatic biota will support the final evaluation. (This
approach is adapted from Michigan DNR's protocol.)
6.2.1.1 Sample Collection
The collection procedure provides representative
samples of the macroinvertebrate fauna from compara-
ble habitat types at all stations constituting a site
evaluation, and is supplemented with separate Coarse
Paniculate Organic Matter (CPOM) samples. RBP II
focuses on the riffle/run habitat because it is the most
productive habitat available in stream systems and
includes many pollution-sensitive taxa of the Scraper
and Filtering Collector Functional Feeding Groups.
The CPOM sample provides a measure of effects
(particularly toxicity effects), on a third trophic com-
ponent of the benthic community, the Shredders.
In sampling situations where a riffle/run habitat
with a rock substrate is not available, any submerged
fixed structure will provide a substrate for the Scraper
and Filtering Collector Functional Groups emphasized
here. This allows for the same approach to be used in
non-wadable streams and large rivers and wadable
streams and rivers with unstable substrates.
Riffle/Run Sample
Riffle areas with relatively fast currents and cobble
and gravel substrates generally provide the most
diverse community. Riffles should be sampled using a
kick net to collect from an approximately 1 m2 area.
Two 1 m2 riffle samples should be collected at each
station: one from an area of fast current velocity and
one from an area of slower current velocity. The two
samples are composited for processing. In streams
lacking riffles, run areas with cobble or gravel sub-
strate are also appropriate for kick net sampling.
Where riffle/run communities with a rock substrate
are not available, other submerged fixed structures
(e.g. submerged boulders, logs, bridge abutments, pier
pilings) should be sampled by hand picking. These
structures provide suitable habitat for the Scrapers and
Filtering Collectors and will allow use of RBP II for a
wider range of regions and stream orders. Benke et
al. (1984) determined that although submerged wood
substrates, or snags, accounted for only a small por-
tion of the available substrate in a blackwater river in
Georgia, this habitat provided the greatest taxa rich-
ness and more than half of all benthic biomass.
CPOM Sample
In addition to the riffle/run sample collected for
evaluation of the Scraper and Filtering Collector
Functional Feeding Groups, a CPOM sample should
also be collected to provide data on the abundance of
Shredders at the site. Large paniculate Shredders are
important in forested areas of stream ecosystems rang-
ing from stream orders 1 through 4 (Minshall et al.
1985). The absence of Shredders of large paniculate
material is characteristic of unstable, poorly retentive
headwater streams in disturbed watersheds or in dry
areas where leaf material processing is accomplished
by terrestrial detritivores (Minshall et al. 1985).
McArthur et al. (1988) reported that very few Shred-
ders were found in summer leaf packs in South Caro-
lina because processing was so rapid.
6-4
-------
Kick net sampling in riffle area.
6-5
-------
Rapid Bioassessment Protocol II
Biosurvey Field Data Sheet
RELATIVE ABUNDANCE OF AQUATIC BIOTA
Periphyton
Filamentous
Macrophytes
0 1
Algae 0 1
0 1
0 = Absent/Not Observed
2
2
2
1
3
3
3
= Rare
4 Slimes
4 Macroinvertebrates
4 Fish
0 1
0 1
0 1
2
2
2
2 = Common 3 = Abundant
3
3
3
4
4
4
4 = Dominant
MACROBENTHOS QUALITATIVE SAMPLE LIST
List Families Present/Indicate Abundance
Oligochaeta
Gastropoda
Bivalvia
Ephemeroptera
Anisoptera
Zygoptera
Plecoptera
Trichoptera
Coleoptera
Diptera
Other
RIFFLE SAMPLE
FUNCTIONAL FEEDING GROUPS
(Indicate No. ol Individuals Representing Group)
Scrapers
Filtering Collectors
CPOM SAMPLE FUNCTIONAL FEEDING GROUPS (Indicate No. ol Individuals Representing Group)
Shredders
Total Org. in Sample
Observations
Figure 6.2-1. Biosurvey Field Data Sheet for use with Rapid Bioassessment Protocol II.
6-6
-------
. The CPOM sample is processed separately from
the riffle/run sample and used only for characterizing
the Functional Feeding Group representation. Sam-
pling the CPOM component requires a composite col-
lection of various plant parts such as leaves, needles,
twigs, bark, or their fragments. Potential sample
sources include leaf packs, shorezones, and other
depositional areas where CPOM may accumulate.
Only the upper surface of litter accumulation in
depositional areas should be sampled to ensure that
they are from the aerobic zone. For the Shredder
community analysis, several handfuls of material
should be adequate. A variety of CPOM forms should
be collected if available. CPOM collected may be
washed in a dip net or a sieve bucket.
Shredder abundance is maximum when the CPOM
is about 50 percent decomposed (Cummins et al.
1989). Care must be taken to avoid collecting recent
or fully decomposed leaf litter to optimize collection
of the Shredder community. For this CPOM collection
technique, seasonality may have an important •
influence on Shredder abundance data. For instance,
fast-processing litter (e.g., basswood, alder, maples,
birch) would have the highest Shredder representation
in the winter (Cummins et al. 1989). The slow-
processing litter (e.g., oaks, rhododendrons, beech,
conifers) would have the highest Shredder representa-
tion in the summer.
6.2.1.2 Sample Sorting and Identification .
Riffle/Run Sample
Sorting and enumeration in the field to obtain a
100-count organism subsample is recommended for
the riffle/run sample. After processing in the field,
the organisms and sample residue should be preserved
for archiving. Thus, a re-analysis (quality control) or
more thorough processing (e.g., larger counts, more
detailed taxonomy) would be possible. The subsam-
pling method described in this protocol is based on
Hilsenhoff s Improved Biotic Index (Hilsenhoff 1987b)
and is similar to that used by New York DEC (Bode
1988). This subsampling technique provides for a con-
sistent unit of effort and a representative estimate of
the benthic fauna.
The subsampling procedure consists of evenly dis-
tributing the composite sample into a gridded pan
with a light colored bottom. Grids are randomly
selected and all organisms within those grids are
removed until approximately 100 organisms are picked
out. Because this subsampling technique is being
applied to samples with live organisms, narcotization
using club soda or tobacco is recommended. A more
detailed description of this technique may be found in
Appendix B.
An alternative method of subsampling live samples
in the field is to simply sort 100 organisms in a ran-
dom manner. Narcotization to slow the organisms is
less important with this subsampling technique. To
lessen sampling bias, the investigator should pick
smaller, cryptic organisms, as well as the larger, more
obvious organisms.
All organisms in the subsample should be classi-
fied according to Functional Feeding Group. Field
classification is important because many families com-
prise genera and species representing a variety of
functional groups. Knowing the family-level identifica-
tion of the organisms will generally be insufficient for
categorization by Functional Feeding Group. Func-
tional Feeding Group classification can be done in the
field, on the basis of morphological and behavioral
features, using Cummins and Wilzbach (1985). Care
should be taken in noting early instars, which may
constitute different Functional Feeding Groups from
the later instars.
The Scraper and Filtering Collector Functional
Groups are the most important indicators in the riffle/
run community. Numbers of individuals representing
each of these two groups are recorded on the Biosur-
vey Field Data Sheet (Figure 6.2-1). All organisms in
the subsample should be identified to family or order,
enumerated, and recorded, along with any observa-
tions on abundance of other aquatic biota, on the
Biosurvey Field Data Sheet. A summary of all benthic
data to be used in the final analysis will be recorded
on the Data Summary Sheet (Figure 6.2-2) upon
return to the laboratory.
The use of family-level identification in this pro-
tocol is based on Hilsenhoff s Family .Biotic Index
which uses higher taxonomic levels of identification
(Hilsenhoff 1988). Tolerance characterizations for the
Family Biotic Index (FBI) and excerpts from Hilsen-
hoff s paper describing the index are included in
Appendix C. Assessment based on family-level iden-
tifications has been used successfully by the States of
Virginia and Illinois.
CPOM Sample
Organisms collected in the supplemental CPOM sam-
ple are classified as Shredders or Non-Shredders. Tax-
onomic identification is not necessary for this
component. The composited CPOM sample may be
field sorted in a small pan with a light colored bottom
or in the net or sieve through which it was rinsed. (If
a large number of benthic macroinvertebrates have
been collected, a representative subsampling of 20-60
organisms may be removed for Functional Feeding
Group classification.) Numbers of individuals
representing the Shredder Functional Group, as well
6-7
-------
DATA SUMMARY SHEET
Station No.
Station Location
Taxa Richness
FBI (modified)
Functional Feeding Groups
Riffle Community
Scrapers/Filt. Collect.
CPOM Community
Shredders/Total
EPT/Chironomidae
% Contribution (dom. family)
EPT Index
Community Similarity Index
Comments:
Figure 6.2-2. Data Summary Sheet suggested for use in recording benthic data utilized in Rapid Bioassessment Protocol
-------
Field sorting of benthic macroirwertebrate
samples for Rapid Bioassessment Protocol II.
6-9
-------
as total number of macroinvertebrates collected in this
sample, should be recorded on the Biosurvey Field
Data Sheet (Figure 6.2-1) for later analysis. The
Shredder/Non-Shredder metric may be deemed
optional in rivers or in some regions where Shredder
abundance is naturally low. However, the potential
utility of such a metric for assessing toxicant effects
warrants serious consideration in this bioassessment
approach.
6.2.2 Data Analysis Techniques
Biological impairment of the benthic community
may be indicated by the absence of generally
pollution-sensitive macroinvertebrate taxa such as
Ephemeroptera, Plecoptera, and Trichoptera (EFT);
excess dominance by any particular taxon, especially
pollution-tolerant forms such as some Chironomidae
and Oligochaeta taxa; low overall taxa richness; or
appreciable shifts in community composition relative
to the reference condition. Impairment may also be
indicated by an overabundance of fungal slimes or
filamentous algae, or an absence of expected popula-
tions of fish. All of these indicators can be evaluated
using the sampling data generated in RBP II.
On the basis of observations made in the assess-
ment of habitat, water quality, physical characteristics,
and the qualitative biosurvey, the investigator con-
cludes whether impairment is detected. If impairment
is detected, an estimation of the probable cause and
source is provided on the Impairment Assessment
Sheet (Figure 6.1-2). The aquatic biota that indicated
an impairment are noted along with observed indica-
tions of potential problem sources. The downstream
extent of impact is estimated and multiplied by
appropriate stream width to provide an estimate of the
areal extent of the problem.
The data analysis scheme used in RBP II integrates
several community, population, and functional
parameters into a single evaluation of biotic integrity
(Table 6.2-1). Each parameter, or metric, measures a
different component of community structure and has a
different range of sensitivity to pollution stress (Fig-
ure 8.2-1). This integrated approach provides more
assurance of a valid assessment because a variety of
parameters are evaluated. Deficiency of any one met-
ric in a particular situation should not invalidate the
entjre approach.
The eight metrics used in RBP II are the same as
those in RBP III, but the scoring criteria used to
evaluate the metrics have been modified to accommo-
date the less rigorous taxonomy (family-level identifi-
cations) of RBP II. The integrated data analysis
(Figure 6.2-3) is performed as follows. Using the raw
benthic data, a numerical value is calculated for each
metric. Calculated values are then compared to values
derived from either a reference site within the same
region, a reference database applicable to the region,
or a suitable control station on the same stream. Each
metric is then assigned a score according to the com-
parability (percent similarity) of calculated and refer-
ence values. Scores for the eight metrics are then
totaled and compared to the total metric score for the
reference station. The percent comparison between the
total scores provides a final evaluation of biological
condition.
The criteria to be used for scoring the eight met-
rics were derived from an evaluation of pilot study
results (Section 6.4); certain compliance monitoring
requirements now in use (Vermont Department of
Environmental Conservation 1987); and discussions
with various aquatic biologists regarding the level of
detection considered dependable for certain metrics.
However, these criteria may need to be adjusted for
use in particular regions.
Inherent variability in each metric was considered
in establishing percent comparability criteria. The
metrics based on taxa richness, FBI, and EFT Indices
have low variability (Resh 1988). This variability is
accounted for in the criteria for characterization of
biological condition (Figure 6.2-3), based on existing
data. For metrics based on standard taxa richness and
FBI and EPT Indices, differences of 10-20 percent
relative to the reference condition would be considered
nominal, and the station being assessed would receive
the maximum metric score. Because increasing FBI
values denote worsening biological condition, percent
difference for this metric is calculated by dividing the
reference value by the value for the station of
comparison.
Metrics that utilize ratios fluctuate more widely,
however, and comparing percent differences between
ratios (ratios of ratios) will compound the variability.
Scoring increments are therefore set at broad intervals
of 25 percent or greater. For metrics based on Func-
tional Feeding Group ratios, Cummins (1987, personal
communication) contends that differences as great as
50 percent from the reference may be acceptable, but
differences in the range of 50-100 percent are not
only important but discriminate degrees of impact
more clearly.
The contribution of the dominant taxon to total
abundance is a simple estimator of evenness. Scoring
criteria are based on theoretical considerations rather
than direct comparison with a reference.
The Community Loss Index (a representative
similarity index) already incorporates a comparison
with a reference. Therefore, actual index values are
used in scoring.
The metrics used to evaluate the benthic data and
their significance are explained below.
6-10
-------
TABLE 6.2-1 CRITERIA*3* FOR CHARACTERIZATION
1.
2.
3.
4.
5.
6.
7.
8.
Metric
Taxa Richness
Family Biotic Index (modified)
Ratio of Scrapers/Filtering Collectors*
Ratio of EPT and Chironomid Abundances
% Contribution of Dominant Family
EPT Index
/c\
Community Similarity Indexv
Ratio of Shredders/Total* '
OF BIOLOGICAL CONDITION FOR RAPID BIOASSESSMENT PROTOCOL II
Non-Impaired
hn tn «-t IB O
o n n x o
i-l n O T3 3
C T> IB T3
VI O 3" O 0»
i-i c n IB 01
IB n a. cr
a IB in i->
3 n C IB
x-x n >-*•
W O C r^ r»
M. 0 0 3" O
N 3 <-> r—
IB "O C 3 «-»
on 3-
3 M. • 3
O-'rr CT
3" O O O W
0) 3 -a o <-•
cr rr n
H- 01 H- IB M
~ 3 3 W M.
01 0. C t-. ,-r
n 3 O C
a. 3 01
XI O O • rr
C 3 O M.
01 M. 3 0
p-> 3 3 CD 3
M. 01 C 01
r-r 3 3 1— r>
•< n M. o> o
• IB ~ 3
s^>< o cr
IB IB
0-
Biological Condition
Moderately Impaired
01 -«1
3 IB
ID
O
n ~
3 Oi
in x
• 01
a.
IB IB
a.
C rf
o o
o' o
3 in
in
3 0
tTt
PI
H O
in
3
CL t->*
(B 3
X r»
• O
t— *
IB
I-I
1
Severely Impaired
•-» O 1J
01 H IB
x oq «
U 01
w" x
O 3 01
3 M
>-"• 13
>< r,
•-• IB
rr T W
O .il IB
t— 3 3
IB ^
n Q. •
0) O
3 3
3 1-h
O 01
n -r 3-
W IB M-
3 3"
M -< Q.
3 IB
MOD
3 M
•O (B M.
IB 0 £
M 1 IB
IB M
3 »-t
rr < 0
• O rt%
(a) Scoring criteria are generally based on percent comparability to the reference sta±ion...
(b) Determination of Functional Feeding Group is independent of taxonomic grouping.
(c) Community Similarity Indices are used in comparison to a reference station.
-------
Site-Specific Study
Sampling & Analysis
CRITERIA FOR CHARACTERIZATION OF BIOLOGICAL CONDITION FOR PROTOCOL II
1.
2.
3.
4.
5.
6.
7.
8.
Metric
Taxa Richness'3'
Family Biotic Index (modified)(b)
Ratio of Scrapers/Filt. Collectors'2-0'
Ratio of EPT and Chironomid Abundances'3'
% Contribution of Dominant Family'2'
EPT Index'8'
Community Loss Index'e'
Ratio of Shredders/Total'a-c)
6
>80%
>85%
>50%
>75%
<30%
>90%
<0.5
>50%
Biological Condition Scoring Criteria
3
40-80%
50-85%
25-50%
25-75%
30-50%
70-90%
0.5-4.0
25-50%
0
<40%
<50%
<25%
<25%
>50%
<70%
>4.0
<25%
(a) Score is a ratio of study site to reference site x 100.
(b) Score is a ratio of reference site to study site x 100.
(c) Determination of Functional Feeding Group is independent of taxonomic grouping.
(d) Scoring criteria evaluate actual percent contribution, not percent comparability to the reference station.
(e) Range of values obtained. A comparison to the reference station is incorporated in these indices.
BIOASSESSMENT
% Comp.
to Ref.
Score'"'
>79% Non-impaired
Biological Condition
Category
Attributes
29-72% Moderately impaired
<21% Severely impaired.
Comparable to the best situation
to be expected within an ecoregion.
Balanced trophic structure. Optimum
community structure (composition and
dominance) for stream size and habi-
tat quality.
Fewer species due to loss of most
intolerant forms. Reduction in EPT
index.
Few species present. If high den-
sities of organisms, then dominated
by one or two taxa. Only tolerant
organisms present.
(a) Percentage values obtained that are intermediate to the above ranges
will require subjective judgement as to the correct placement. Use
of the habitat assessment and physicochemical data may be necessary to aid in
the decision process.
Recommendations
Figure 6.2-3. Flowchart of bioassessment approach advocated for Rapid Bioassessment Protocol
6-12
-------
Riffle/Run Sample
Metric 1. Taxa Richness
Reflects health of the community
through a measurement of the variety of
taxa (total number of families) present.
Generally increases with increasing water
quality, habitat diversity, and habitat suit-
ability. Sampling of highly similar habitats
will reduce the variability in this metric
attributable to factors such as current speed
and substrate type. Some pristine headwater
streams may be naturally unproductive, sup-
porting only a very limited number of taxa.
In these situations, organic enrichment may
result in an increased number of taxa
(including EPT taxa).
Metric 2. Modified Family Biotic Index
Tolerance values range from 0 to 10 for
families and increase as water quality
decreases. The index was developed by Hil-
senhoff (Hilsenhoff 1988) to summarize the
various tolerances of the benthic arthropod
community with a single value. The Modi-
fied Family Biotic Index was developed to
detect organic pollution and is based on the
original species-level index (Hilsenhoff
1982). Tolerance values for each family
were developed by weighting' species
according to their relative abundance in the
State of Wisconsin.
The family-level index has been modi-
fied for this document to include organisms
other than just arthropods using the genus
and species-level biotic index developed by
the State of New York (Bode 1988). The
formula for calculating the Family Biotic
Index is:
X: tj
-
where
Xj = number of individuals within a taxon
tj = tolerance value of a taxon
n = total number of organisms in the sample
Hilsenhoffs family-level tolerance values
may require modification for some regions.
Alternative tolerance classifications and
biotic indices have been developed by some
State agencies (Appendix C). Additional
biotic indices are listed in U.S. EPA (1983).
Although the FBI may be applicable for
toxic pollutants, it has only been evaluated
for organic pollutants. The State of Wiscon-
sin is conducting a study to evaluate the
ability of Hilsenhoffs index to detect non-
organic effects. '.
Metric 3. Ratio of Scraper and Filtering Collector
Functional Feeding Groups
The Scraper and Filtering Collector met-
ric reflects the riffle/run community food-
base. When compared to a reference site,
shifts in the dominance of a particular feed-
ing type indicate a community responding
to an overabundance of a particular food
source. The predominant feeding strategy
reflects the type of impact detected. Assign-
ment of individuals to Functional Feeding
Groups is independent of taxonomy, with
some families representing several func-
tional groups.
A description of the Functional Feeding
Group concept can be found in Cummins
(1973) and Merritt and Cummins (1984).
Functional Feeding Group designations for
most aquatic insect families may be found
in Merritt and Cummins (1984). Most
aquatic insects can also be classified to
Functional Feeding Group in the field, on
the basis of morphological and behavioral
features, using Cummins and Wilzbach
(1985).
The relative abundance of Scrapers and
Filtering Collectors in the riffle/run habitat
is an indication of the periphyton commu-
nity composition, availability of suspended
Fine Paniculate Organic Material (FPOM),
and availability of attachment sites for filter-
ing. Scrapers increase with increased dia-
tom abundance and decrease as filamentous
algae and aquatic mosses (which scrapers
cannot efficiently harvest) increase. How-
ever, filamentous algae and aquatic mosses
provide good attachment sites for Filtering
Collectors, and the organic enrichment
often responsible for overabundance of
filamentous algae can also provide FPOM
that is utilized by the Filterers.
Filtering Collectors are also sensitive to
toxicants bound to fine particles and should
be the first group to decrease when exposed
6-13
-------
to steady sources of such bound toxicants.
This situation is often associated with point-
source discharges where certain toxicants
adsorb readily to dissolved organic matter
(DOM) forming FPOM during flocculation.
Toxicants thus become available to Filterers
via FPOM. The Scraper to Filtering Collec-
tor ratio may not be a good indicator of
organic enrichment if adsorbing toxicants
are present. In these instances the FBI and
EPT Index may provide additional insight.
Qualitative field observations on periphyton
abundance may also be helpful in interpret-
ing results.
Metric 4. Ratio of EPT and Chironomidae
Abundances
The EPT and Chironomidae abundance
ratio uses relative abundance of these indi-
cator groups (Ephemeroptera, Plecoptera,
Trichoptera, and Chironomidae) as a mea-
sure of community balance. Good biotic
condition is reflected in communities with
an even distribution,among, all four major
groups and with substantial representation
in the sensitive groups Ephemeroptera,
Plecoptera, and Trichoptera. Skewed popu-
lations having a disproportionate number of
the Chironomidae relative to the more sen-
sitive insect groups may indicate environ-
mental stress (Ferrington 1987, Shackleford
1988). Certain species of some genera such
as Cricotopus are highly tolerant (Lenat
1983, Mount et al. 1984) and as oppor-
tunists may become numerically dominant
in habitats exposed to metal discharges
where EPT taxa are not abundant, thereby
providing a good indicator of toxicant stress
(Winner et al. 1980). Clements et al. (1988)
found that mayflies were more sensitive
than chironomids to exposure levels of 15 to
32 ^g/L of copper. Chironomids tend to
become increasingly dominant in terms of
percent taxonomic composition and relative
abundance along a gradient of increasing
enrichment or heavy metals concentration
(Ferrington 1987).
An alternative to the ratio of EPT and
Chironomidae abundance metric is the Indi-
cator Assemblage Index (IAI) developed by
Shackleford (1988). The IAI integrates the
relative abundances of the EPT taxonomic
groups and the relative abundances of
chironomids and annelids upstream and
downstream of a pollutant source to evalu-
ate impairment. The IAI may be a valuable
metric in areas where the annelid commu-
nity may fluctuate substantially in response
to pollutant stress.
Metric 5. Percent Contribution of Dominant Family
The percent contribution of the domi-
nant family to the total number of organ-
isms uses abundance of the numerically
dominant taxon relative to the rest of the
population as an indication of community
balance at the family-level. A community
dominated by relatively few families would
indicate environmental stress. (This metric
may be redundant if the Pinkham and Pear-
son Similarity Index is used as a commu-
nity similarity index for metric number 7.)
Metric 6. EPT Index
The EPT Index generally increases with
increasing water quality. The EPT Index
value is the total number of distinct taxa
within the groups Ephemeroptera, Plecop-
tera, and Trichoptera. The EPT Index value
summarizes the taxa richness within the
insect groups that are generally considered
pollution sensitive. This was developed for
species-level identifications; however, the
concept is valid for use at family-level
identifications.
Headwater streams which are naturally
unproductive may experience an increase in
taxa (including EPT taxa) in response to
organic enrichment.
Metric 7. Community Similarity Indices
Community Similarity Indices are used
in situations where a reference community
exists, either through sampling or through
prediction for a region. Data sources or
ecological data files may be available to
predict a reference community to be used
for comparison. The combined information
provided through a regional analysis and
EPA's ERAFT ecological database (Dawson
and Hellenthal 1986) may be useful for this
analysis. These indices are designed to be
used with either species level identifications
or higher taxonomic levels. Three of the
many community similarity indices available
are discussed below:
6-14
-------
Community Loss Index—Measures the
loss of benthic taxa between a reference
station and the station of comparison.
The Community Loss Index was devel-
oped by Courtemanch and Dav'ies (1987)
and is an index of compositional dis-
similarity, with values increasing as the
degree of dissimilarity with the reference
station increases. Values range from 0 to
"infinity." Based on preliminary data
analysis, this index provides greater dis-
crimination than either of the following
two community similarity indices.
Jaccard Coefficient of Community
Similarity—Measures the degree of
similarity in taxonomic composition
between two stations in terms of taxon
presence or absence. The Jaccard Coeffi-
cient discriminates between highly similar
collections. Coefficient values, ranging
from 0 to 1.0, increase as the degree of
similarity with the reference station
increases. See Jaccard (1912), Boesch
(1977), and U.S. EPA (1983) for more
detail. The formulae for the Community
Loss Index and the Jaccard Coefficient
are
Community Loss =
d-a
Jaccard Coefficient =
a + b + c
where
a = number of taxa common to both
samples
b = number of taxa present in Sample
B but not A
c = number of taxa present in Sample
A but not B
d = total number of taxa present in
Sample A
e = total number of taxa present in
Sample B
Sample A = reference station (or mean
of reference database)
Sample B = station of comparison
• Pinkham and Pearson Community
Similarity Index—Incorporates abundance
and compositional information and can
be calculated with either percentages or
numbers. A weighting factor can be
added that assigns more significance to
dominant taxa. See Pinkham and Pearson
(1976) and U.S. EPA (1983) for more
detail. The formula is
S.I.
min (xia,
ab " max (xja,
where
!is .^fi /2
X V. '
weighting factor
xia, xib = number of individuals in the ith
taxon in Sample A or B
Other community similarity indices sug-
gested by reviewers of this document
include Spearman's Rank Correlation
(Snedecor and Cochran 1967), Morisita's
Index (Morisita 1959), Biotic Condition
Index (Winget and Mangum 1979), and
Bray-Curtis Index (Bray and Curtis 1957,
Whittaker 1952). Calculation of a chi-
square "goodness of fit" (Cochran 1952)
may also be appropriate.
CPOM Sample
Metric 8. Ratio of Shredder Functional Feeding
Group and Total Number of Individuals
Collected
Also based on the Functional Feeding
Group concept, the abundance of the Shred-
der Functional Group relative to the abun-
dance of all other Functional Groups allows
evaluation of potential impairment as indi-
cated by the CPOM-based Shredder com-
munity. Shredders are sensitive to riparian
zone impacts and are particularly good indi-
cators of toxic effects when the toxicants
involved are readily adsorbed to the CPOM
and either affect microbial communities
colonizing the CPOM or the Shredders
directly (Cummins 1987, personal
communication).
The degree of toxicant effects on Shred-
ders versus Filterers depends on the nature
of the toxicants and the organic particle
adsorption efficiency. Generally, as the size
of the particle decreases, the adsorption
efficiency increases as a function of the
increased surface to volume ratio (Hargrove
1972). Because water-borne toxicants are
readily adsorbed to FPOM, toxicants of a
6-15
-------
terrestrial source (e.g., pesticides, herbi-
cides) accumulate on CPOM prior to leaf
fall thus having a substantial effect on
Shredders (Swift et al. 1988a and 1988b).
The focus of this approach is on a compari-
son to the reference community which
should have a reasonable representation of
Shredders as dictated by seasonally, region,
and climate. This allows for an examination
of Shredder or Collector "relative" abun-
dance as indicators of toxicity.
The data collected in the 100-organism riffle/run
subsample and the CPOM sample are summarized
according to the information required for each metric
and entered on the Data Summary Sheet (Fig-
ure 6.2-2).
Each metric result is given a score based on per-
cent comparability to a reference station. Scores are
totaled and compared to the total metric score for the
reference station. The percent comparison between the
total scores provides a final evaluation of biological
condition. Values obtained may sometimes be inter-
mediate to established ranges and require some judg-
ment as to assessment of biological condition. In these
instances, habitat assessment, physical characteriza-
tion, and water quality data may aid in the evaluation
process.
6.3 RAPID BIOASSESSMENT
PROTOCOL III—Benthic
Macroinvertebrates
Rapid Bioassessment Protocol in (RBP III) is a
more rigorous bioassessment technique than RBP II,
involving systematic field collection and subsequent
lab analysis in order to allow detection of more subtle
degrees of impairment. Discrimination of four levels
of impairment should be possible with this assess-
ment. Although Protocol III requires more detailed
taxonomy than can ordinarily be accomplished in the
field, lab analysis procedures emphasize a minimal
level of effort to ensure the protocol's time- and cost-
effectiveness. Where differences among stations are
subtle, however, more detailed sample analyses (e.g.,
enumeration of larger subsamples) or processing of a
greater number of samples (to define replicability or
assess more habitats) may be necessary to resolve
such differences.
Data provided by RBP III can be used lo prioritize
sites for more intensive evaluation (e.g., quantitative
biological surveys, ambient toxicity testing, chemical
characterization). Besides providing a means of evalu-
ating effects among stations, this protocol provides a
basis for monitoring trends in benthic community
structure that might be attributable to improvement or
worsening of conditions over time.
6.3.1 Field Methods
The biosurvey component of RBP III focuses on
the sampling of benthic macroinvertebrates supple-
mented by cursory field observation of the periphyton,
macrophyton, slime, and fish communities. The infor-
mation on observed effects upon other aquatic biota
is recorded on the Biosurvey Field Data Sheet (Fig-
ure 6.3-1) and may be used to support or further
evaluate benthic data.
The habitat assessment evaluates habitat quality on
the basis of key parameters of the waterbody and sur-
rounding land as described in Chapter 5. Habitat
assessment is especially important in situations where
benthos and other biological communities indicate an
impairment. In these instances, an evaluation of habi-
tat quality will aid in the interpretation of effects rela-
tive to a site's biotic potential. The water quality/
physical characterization provides pertinent data on
habitat quality as well as potential sources or causes
, of impairment.
6.3.1.1 Sample Collection
The purpose of the standardized collection proce-
dure is to obtain representative samples of the macro-
invertebrate fauna from comparably productive habitat
types available at all stations constituting a site evalua-
tion, supplemented with separate CPOM samples.
This protocol focuses on the riffle/run habitat as the
most productive habitat available in stream systems.
The riffle/run benthic community includes many
representatives of the Scraper and Filtering Collector
Functional Feeding Groups. Riffle/run sampling is
supplemented with collection of a CPOM sample. The
CPOM sample provides a measure of effects on a
third trophic component of the benthic community, the
Shredders.
Where riffle/run habitat with a rock substrate is
not available, other submerged fixed structures e.g.,
submerged boulders, logs, bridge abutments, pier pil-
ings, will provide a substrate for the Scraper and
Filtering Collector Functional Groups emphasized
here. Sampling submerged fixed structures would also
be appropriate in non-wadable streams and large rivers
and wadabie streams and rivers with unstable
substrates.
6-16
-------
Rapid Bioassessment Protocol III
Biosurvey Field Data Sheet
RELATIVE ABUNDANCE OF AQUATIC BIOTA
Periphyton 0
Filamentous Algae 0
Macrophytes 0
0 = Absent/Not Observed
3
3
3
1 = Rare
Slimes 0 1
Macroinvertebrates 0 1
Fish 0 1
2 = Common
3 = Abundant
2 3
2 3
2 3
4 = Dominant
MACROBENTHOS QUALITATIVE SAMPLE LIST'lndicate Relative Abundance R = Rare, C = Common, A = Abundant, D = Dominant)
Porilera
Hydrozoa
Platyhelminthes
Turbellaria
Hirudinea
Oligochaeta
Isopoda
Amphipoda
Decapoda
Gastropoda
Bivalvia
Anisoptera
Zygoptera
Hemiptera
Coleoptera
Lepidoptera
Sialidae
Corydalidae
Tipulidae
Empididae
Simuliidae
Tabanidae
Culicidae
Chironomidae
Plecoptera
Ephemeroptera
Trichoptera
Other
Rare < 3
Common 3-9
Abundant > 10
Dominant > 50 (Estimate)
CPOM SAMPLE FUNCTIONAL FEEDING GROUPS (Indicate No. ol Individuals Representing Group)
Shredders
Total Org. in Sample
Observations
Figure 6.3-1. Biosurvey Field Data Sheet for use with Rapid Bioassessment Protocol III.
6-17
-------
Riffle/Run Sample
In most situations, a riffle area with relatively fast
current and a cobble and gravel substrate provide the
most diverse community. Riffles should be sampled
using a kick net to collect from an approximately
1 m2 area. Two 1 m2 riffle samples should be col-
lected at each station: one from an area of fast current
velocity and one from an area of slower current veloc-
ity. The two samples are composited for processing.
In streams lacking riffles, run areas with cobble or
gravel substrate are also appropriate for kick net
sampling.
Where a riffle/run community with a rock sub-
strate is not available, other submerged fixed struc-
tures, e.g., submerged boulders, logs, bridge
abutments, pier pilings, should be sampled by hand
picking. These structures provide suitable habitat for
the Scrapers and Filtering Collectors and will allow
use of RBP III for a wider range of regions and
stream orders. Evaluation of benthic production in a
blackwater stream in Georgia by Benke et al. (1984)
indicated that although submerged wood substrates
(snags) comprised a minor portion of available sub-
strate, the greatest taxa richness and more than half of
all benthic biomass were associated with this habitat.
Field inspection of the sample is recommended to
obtain a preliminary assessment of presence and rela-
tive abundance of major groups (to be indicated on
the Biosurvey Field'Data Sheet, Figure 6.3-1), and to
determine if the sampling effort was adequate to
obtain at least 100 organisms. In some samples from
severely impaired areas, organism abundance may not
total 100 organisms. The samples collected at the two
current velocities from the same habitat are com-
posited, preserved, labeled, and returned to the
laboratory for processing.
CPOM Sample
In addition to the riffle/run sample collected for
evaluation of the Scraper and Filtering Collector
Functional Feeding Groups, a CPOM sample should
also be collected to provide data on the relative abun-
dance of the Shredders at the site. Shredders of large
paniculate material are important in forested areas of
stream ecosystems ranging from stream orders 1
through 4 (Minshall et al. 1985). The absence of large
particulate Shredders is characteristic of unstable,
poorly retentive headwater streams in disturbed
watersheds or in dry areas where leaf material
processing is accomplished by terrestrial detritivores
(Minshall et al. 1985). McArthur et al. (1988)
reported that very few Shredders were found in sum-
mer leaf packs in South Carolina because processing
was so rapid.
The CPOM sample is processed separately from
the riffle/run sample and used for Functional Feeding
Group characterization. Sampling of the CPOM com-
ponent requires a composite collection of any of a
variety of forms of CPOM (plant parts such as leaves,
needles, twigs, bark, or fragments of these). Potential
sample sources include leaf packs and shorezone areas
where CPOM may accumulate. For the Shredder com-
munity analysis, collection of several handfuls of
material should be adequate. A variety of CPOM
forms should be collected if they are available. Mate-
rial collected may be washed in a dip net or a sieve
bucket.
Maximum Shredder abundance is obtained when
the CPOM is about 50 percent decomposed (Cum-
mins et al. 1989). Care must be taken to avoid col-
lecting recent or fully decomposed leaf litter to
optimize collection of the Shredder community. Sea-
sonality may have an important influence on Shredder
abundance data. For instance, fast-processing litter
(e.g., basswood, alder, maples, birch) would have
the highest Shredder representation in the winter
(Cummins et al. 1989). The slow-processing litter
(e.g., oaks, rhododendrons, beech, conifers) would
have the highest Shredder representation in the summer.
6.3.1.2 Field Processing
of the CPOM Sample
Organisms collected in the supplemental CPOM
sample are classified as either Shredders or Non-
Shredders. Taxonomic identification is not necessary
for this component. The composited CPOM sample
may be sorted in the field in a small pan with a light
colored bottom. (If a large number of benthic macro-
invertebrates has been collected, a representative sub-
sampling of 20-60 organisms may be removed for
Functional Feeding Group classification.) Numbers of
individuals representing the Shredder Functional
Group, as well as total number of macroinvertebrates
collected in this sample, should be recorded on the
Biosurvey Field Data Sheet (Figure 6.3-1) for later
analysis.
6.3.2 Lab Methods
6.3.2.1 Sample Sorting and Identification
A 100-organism subsample is recommended as a
time-saving sorting procedure for use with the riffle/
run sample. The subsampling method described for
use in this protocol is based on that used for Hilsen-
hoff s Biotic Index (Hilsenhoff 1987b) and is similar to
that used by New York DEC (Bode 1988) and in
Arkansas (Shackleford 1988). The subsampling proce-
6-18
-------
dure consists of evenly distributing the composite
sample in a gridded pan with a light-colored bottom.
As grids are randomly selected, all organisms within
those grids are removed, until at least 100 organisms
have been selected from the sample. This method of
subsampling provides a representative estimate of the
benthic fauna as well as a consistent unit of effort. A
more detailed description of this technique may be
found in Appendix B. Although pilot study results
(Section 6.4.6) indicated that a 100-organism subsam-
ple is sufficient, a 200- or 300-organism subsample
may be preferred, depending on investigator prefer-
ence, budget constraints, and individual sample
characteristics. Some agencies may prefer to expend
additional resources to process whole samples instead
of subsampling.
All benthic macroinvertebrates in the subsample
(or sample) should be identified to the lowest posi-
tively identified taxonomic level (generally genus or
species), enumerated, and recorded on the Laboratory
Bench Sheet (Figure 6.3-2). Based on the taxonomic
identifications, Functional Feeding Group classifica-
tions can be assigned for most aquatic insects using a
reference such as Merritt and Cummins (1984). Once
a Functional Feeding Group classification list has
been established, it can be incorporated into the com-
puter analysis for computation of the metrics. Care
should be taken to note the presence of early instars
which may represent different Functional Feeding
Groups from later instars. The Scraper and Filtering
Collector Functional Groups are considered the
important indicators in the riffle/run community; if
this metric is not calculated using a computer pro-
gram, numbers of individuals representing each of
these two groups are recorded on the Laboratory
Bench Sheet (Figure 6.3-2).
6.3.3 Data Analysis Techniques
Based on observations made in assessing habitat,
water quality, physical characteristics, and the qualita-
tive biosurvey, the investigator makes a preliminary
judgment on the presence or absence of biological
impairment and an estimation of probable cause
and source on the Impairment Assessment Sheet
(Figure 6.1-2).
The integrated benthic data analysis is performed
as follows. Using the raw benthic data, a numerical
value is calculated for each metric. Calculated values
are then compared to values derived from either an
unimpaired reference site within the same region or a
suitable control station on the same stream. Each met-
ric is then assigned a score according to the compara-
bility (percent similarity) of calculated and reference
values. Scores for the eight metrics are then totaled
and compared to the total metric score for the refer-
ence station. The percent comparison between the
total scores provides a final evaluation of biological
condition.
Criteria to be used for scoring the eight metrics
were derived from an evaluation of pilot study results
(Section 6.4), certain project compliance monitoring
requirements now in use (Vermont Department of
Environmental Conservation 1987), and discussions
with various aquatic biologists regarding the level of
detection considered dependable for certain metrics.
However, it is envisioned that these criteria may need
to be adjusted for use in particular regions.
Inherent variability in each metric was considered
in establishing percent comparability criteria. The
metrics based on taxa richness, HBI, and EFT indices
have low variability (Resh 1988). This variability is
accounted for in the criteria for characterization of
biological condition (Figure 6.2-3) based on existing
data. For metrics based on standard taxa richness and
HBI and EFT Indices, differences of 10-20 percent
relative to the reference condition would be considered
nominal, and the station being assessed would receive
the maximum metric score. Because increasing HBI
values denote worsening biological condition, percent
difference for this metric is calculated by dividing the
reference value by the value for the station of
comparison.
Metrics that utilize ratios will fluctuate more
widely, however, and comparing percent differences
between ratios (ratios of ratios) will compound the
variability. Scoring increments are therefore set at
broad intervals of 25 percent or greater. For metrics
based on Functional Feeding Group ratios, Cummins
(1987, personal communication) contends that differ-
ences as great as 50 percent from the reference may
be acceptable, but differences in the range of 50-100
percent are not only important but discriminate
degrees of impact more clearly.
The percent contribution of the dominant taxon to
total abundance is a simple estimator of evenness.
Scoring criteria are based on theoretical considera-
tions rather than direct comparison with a reference.
The Community Loss Index already incorporates
comparison with a reference. Therefore, actual index
values are used in scoring.
Analysis of the benthic data combines several com-
munity population and functional parameters. An
integrated assessment is used, based on eight metrics
(Table 6.3-1). Each metric has a different range of
sensitivity measuring a slightly different component of
community structure (Figure 8.2-1). The data collected
in the 100-organism riffle/run subsample and the
CPOM sample are summarized according to the infor-
mation required for each metric and entered on the
6-19
-------
LABORATORY BENCH SHEET
Number of Organisms
Station Number
Station Location
Species Name
Total Organisms
Number of Taxa
Figure 6.3-2. Laboratory Bench Sheet suggested for use in recording benthic
data utilized in Rapid Bioassessment Protocol III.
6-20
-------
to
TABLE 6.3-1 CRITERIA
(a)
FOR CHARACTERIZATION OF BIOLOGICAL CONDITION FOR RAPID BIOASSESSMENT PROTOCOL III
1.
2.
3.
A.
5.
6.
7.
8.
Metric
Taxa Richness
Hilsenhoff Biotic Index (modified)
Ratio of Scrapers/Filtering Collectors
Ratio of EPT and Chironomid Abundances
% Contribution of Dominant Taxon
EPT Index
/c\
Community Similarity Index
Ratio of Shredders/Total^ '
Non-
Impaired
rt, (rt rt IB O
O rt *l X O
n n o *o 3
in n 3* n oi
n c n IB 01
n n a. cr
01 IB in t— *
3 ^ rt £1 3-
01 (rt (B 01 IB
3 M. . 3
O> rt O"
t-** IB (B
3" O o n in
01 3 "O- O rt
O" rt l-l
M> 01 M- IB in
rt 3 3 03 t-"
01 O. C M- rt
rt 3 O C
Q. 3 01
A O O • rt
C 3 O >".
01 H. 3 O
M 3 3 CB 3
M. 01 C 01
rt 3 3 I-" rt
>< 0 M. 01 0
• ID rt 3
(B IB
O-
Biological
Slightly
Impaired
0 H- rt o O
rt, 3 3" 0 0
rt 01 3 3
rt O 3 TJ 3
O M 0 C
k-» IB IB In 3
IB n X H- M-
n 01 T3 rt rt
B 3 IB M-><
3 rt O O
rt • rt 3 in
rt, IB rt
rt, o Q.-~ • n
on me
n 3 a. xi n
3 la C IB rt
M • IB n c
M» n
3 "0 o in
n IB i-«
n n *-* n IB
IB n o M- in
01 IB in n in
in 3 in 3-
IB rt 3 rt
(A O IB 3"
• o n in 01
o in 3
3 w ^
rt O (B
M. 3 1-1 X
er IB o -a
c c IB
« IB n
H- H rt
O IB
3 a.
Condition
Moderately
Impaired
3 3 IB
O. rt <
n o IB
• (B
n (n
01 -a
3 IB
rt, IB
O in
n
a OL.
in c
• IB
7> 0
(B
a, 1-1
C 0
n in
rt in
M*
O 0
3 r«
M. 3
3 O
in
PI rt
3
Severely
Impaired
"O rt O *13
1 < rt, (B
IB O C
in 0
IB rt n in
3 01 OP *O
rt X 01 IB
• oi 3 n
in IB
3 in
0 I/l
3— -0
t-1 n
•< rt IB
3- in
rt (B IB
O 3 3
IB 0. •
n o
01 3
3 M. 1-1
rt 3 rt,
01
O rt 3"
« IB M.
09 Q.OQ
W 3*
3 or
H-V; a.
In IB
303
w 3 in
IB M-
O M*
n IB
(A
(a) Scoring criteria are generally based on percent comparability to the reference station.
(b) Determination of Functional Feeding Group is independent of taxonomic grouping.
(c) Community Similarity Indices are used in comparison to a reference station.
-------
Data Summary Sheet (Figure 6.3-3). Each metric
result is given a score based on percent comparability
to a reference station. Evaluation of biological condi-
tion is based on comparison to the reference condition
(site-specific or reference database) that is representa-
tive of the "best attainable" condition. Using this
approach, metrics can be eliminated if found inap-
plicable, without altering the biological classification.
However, this integrated assessment approach is
intended to remain intact to avoid jeopardizing the
integrity of the bioassessment concept.
Scores are totaled and a Biological Condition Cate-
gory is assigned based on percent comparability with
the reference station score. Values obtained may some-
times be intermediate to established ranges and
require some subjective judgment as to assessment of
biological condition. In these instances, habitat assess-
ment, physical characterization, and water quality data
may aid in the evaluation process. An explanation of
the importance of interpreting biological data in the
context of habitat quality is presented in Chapter 8.
The metrics used to evaluate the benthic data and
their significance are described below.
Riffle/Run Sample
Metric 1. Species Richness
Reflects health of the community
through a measurement of the variety of
taxa (total number of genera and/or species)
present. Generally increases with increasing
water quality, habitat diversity, and/or habi-
tat suitability. Sampling of highly similar
habitats will reduce the variability in this
metric attibutable to factors such as current
speed and substrate type. Some pristine
headwater streams may be naturally
unproductive, supporting only a very
limited number of taxa. In these situations,
organic enrichment may result in an
increase in number of taxa (including EFT
taxa).
Metric 2. Modified Hilsenhoff Biotic Index
Tolerance values range from 0 to 10,
increasing as water quality decreases. The
index was developed by Hilsenhoff (1987b)
to summarize overall pollution tolerance of
the benthic arthropod community with a
single value. This index was developed as a
means of detecting organic pollution in
communities inhabiting rock or gravel rif-
fles, and has been modified for this docu-
ment to include non-arthropod species as
well, on the basis of the biotic index used
by the State of New York (Bode 1988).
Although Hilsenhoffs biotic index was
originally developed for use in Wisconsin,
it is successfully used by several States and
should prove reliable for extensive use,
requiring regional modification in some
instances. Alternative tolerance classifica-
tions and biotic indices have also been
developed by some State agencies (Appen-
dix C). The formula for calculating the
Biotic Index is:
HBI=I
where
Xj = number of individuals within a species
tj = tolerance value of a species
n = total number of organisms in the sample
Although it may be applicable for other
types of pollutants, use of the HBI in
detecting non-organic pollution effects has
not been thoroughly evaluated. The State of
Wisconsin is conducting a study to evaluate
the ability of Hilsenhoffs index to detect
non-organic effects. Winget and Mangum
(1979) have developed a tolerance classifica-
tion system applicable to the assessment of
nonpoint source impact. Additional biotic
indices are also listed in U.S. EPA (1983).
Metric 3. Ratio of Scraper and Filtering Collector
Functional Feeding Groups
The Scraper and Filtering Collector
Functional Group ratio reflects the riffle/run
community foodbase and provides insight
into the nature of potential disturbance fac-
tors. The proportion of the two feeding
groups is important because predominance
of a particular feeding type may indicate an
unbalanced community responding to an
overabundance of a particular food source.
The predominant feeding strategy reflects
the type of impact detected.
A description of the Functional Feeding
Group concept can be found in Cummins
(1973). Genus-level Functional Feeding
Group designations for most aquatic insects
can be found in Merritt and Cummins
(1984).
6-22
-------
DATA SUMMARY SHEET
o\
Station No.
Station Location
Taxa Richness
FBI (modified)
Functional Feeding Groups
Riffle Community
Scrapers/Filt. Collect.
CPOM Community
Shredders/Total
EPT/Chironomidae
% Contribution (dom. family)
EPT Index
Community Similarity Index
Comments:
Figure 6.3-3. Data Summary Sheet suggested for use in recording benthic data utilized in Rapid Bioassessment Protocol III.
-------
The relative abundance of Scrapers and
Filtering Collectors in the riffle/run habitat
provides an indication of the periphyton
community composition and availability of
suspended Fine Paniculate Organic Material
(FPOM) associated with organic enrich-
ment. Scrapers increase with increased
abundance of diatoms and decrease as
filamentous algae and aquatic mosses
(which cannot be efficiently harvested by
Scrapers) increase. However, filamentous
algae and aquatic mosses provide good
attachment sites for Filtering Collectors,
and the organic enrichment often responsi-
ble for overabundance of filamentous algae
provides FPOM utilized by the Filterers.
Filtering Collectors are also sensitive to
toxicants bound to fine particles and may
decrease in abundance when exposed to
sources of such bound toxicants (Cummins
1987). The Scraper to Filtering Collector
ratio may not be a good indication of
organic enrichment if adsorbing toxicants
are present. This situation is often
associated with point source discharges
where certain toxicants adsorb readily to
dissolved organic matter (DOM) forming
FPOM during flocculation. Toxicants thus
become available to Filterers via FPOM. In
these instances the HBI and EPT Index may
provide additional insight. Qualitative field
observations on periphyton abundance may
also be helpful in interpreting results.
Metric 4. Ratio of EPT and Chironomidae
Abundances
The EPT and Chironomidae abundance
ratio uses relative abundance of these indi-
cator groups as a measure of community
balance. Good biotic condition is reflected
in communities having a fairly even distri-
bution among all four major groups and
with substantial representation in the sensi-
tive-groups Ephemeroptera, Plecoptera, and
Trichoptera. Skewed populations having a
disproportionate number of the generally
tolerant Chironomidae relative to the more
sensitive insect groups may indicate
environmental stress (Ferrington 1987).
Certain species of some genera such as
Cricotopus are highly tolerant (Lenat 1983,
Mount et al. 1984), opportunistic, and may
become numerically dominant in habitats
exposed to metal discharges where EPT
taxa are not abundant, thereby providing a
good indicator of toxicant stress (Winner
et al. 1980). Clements et al. (1988) found
that mayflies were more sensitive than
chironomids when exposed to 15 to 32
of copper.
Chironomids tend to become increas-
ingly dominant in terms of percent taxo-
nomic composition and relative abundance
along a gradient of increasing enrichment
or heavy metals concentration (Ferrington
1987).
An alternative to the ratio of EPT and
Chironomidae abundance metric is the Indi-
cator Assemblage Index (IAI) developed by
Shackleford (1988). The IAI integrates the
relative abundances of the EPT taxonomic
groups and the relative abundances of
chironomids and annelids upstream and
downstream of a pollutant source to evalu-
ate impairment. The IAI may be a valuable
metric in areas where the annelid commu-
nity may fluctuate substantially in repsonse
to pollutant stress.
Metric 5. Percent Contribution of Dominant Taxon
The percent contribution of the numeri-
cally dominant taxon to the total number of
organisms is an indication of community
balance at the lowest positive taxonomic
level. (The lowest positive taxonomic level
is assumed to be genus or species in most
instances.) A community dominated by rela-
tively few species would indicate environ-
mental stress. (If the Pinkham and Pearson
Similarity Index is used as a community
similarity index for metric number 7, this
metric may be redundant.) Shackleford
(1988) has modified this metric to reflect
"dominants in common" (DIG) utilizing the
dominant five taxa at the stations of
comparison.
This DIG approach is based on the
original metric used in earlier drafts of this
RBP document. The DIG will provide a
measure of replacement or substitution
between the reference community and the
downstream station. The purpose of the
modification to "percent contribution of
dominant taxon" used in RBP III (and RBP
II) is to focus on evenness/redundancy of
the benthic community regardless of taxa
composition. Compositional shifts are mea-
sured by other metrics such as the commu-
nity similarity indices.
6-24
-------
Metric 6. EPT Index
The EPT Index generally increases with
increasing water quality. The EPT Index is
the total number of distinct taxa within the
orders Ephemeroptera, Plecoptera, and
Trichoptera. This value summarizes taxa
richness within the insect orders that are
generally considered to be pollution
sensitive.
Headwater streams which are naturally
unproductive may experience an increase in
taxa (including EPT taxa) in response to
organic enrichment. In this situation, a
"missing genera" approach may be more
valuable. Shackleford (1988) uses a "miss-
ing genera" metric to evaluate the loss of
EPT taxa from upstream to downstream to
avoid the complication in data interpretation
resulting from the addition or replacement
of genera.
Metric 7. Community Similarity Indices
Community Similarity Indices are used
in situations where reference communities
exist. The reference community can be
derived through sampling or prediction for
a region using a reference database. Data
sources or ecological data files may be
available to establish a reference community
for comparison. The combined information
provided through a regional analysis and
EPA's ERAPT ecological database (Dawson
and Hellenthal 1986) may be useful for this
analysis. Three of the many similarity indi-
ces available are discussed below:
• Community Loss Index—Measures the
loss of benthic species between a refer-
ence station and the station of compari-
son. The Community Loss Index was
developed by Courtemanch and Davies
(1987) and is an index of dissimilarity
with values increasing as the degree of
dissimilarity from the reference station
increases. Values range from 0 to
"infinity." Based on preliminary data
analysis, this index provides greater dis-
crimination than the following two com-
munity similarity indices.
• Jaccard Coefficient of Community—
Measures the degree of similarity in taxo-
nomic composition between two stations
in terms of taxon presence or absence.
The Jaccard Coefficient discriminates
between highly similar collections.
Coefficient values, ranging from 0 to 1.0,
increase as the degree of similarity with
the reference station increases. See
Jaccard (1912), Boesch (1977), and U.S.
EPA (1983) for more detail. The formulae
for the Community Loss Index and the
Jaccard Coefficient are
Community Loss =
d-a
Jaccard Coefficient =
a + b+c
where
a = number of species common to both
samples
b = number of species present in Sample B
but not A
c = number of species present in Sample A
but not B
d = total number of species present in
Sample A
e = total number of species present in
Sample B
Sample A = reference station
Sample B = station of comparison
• Pinkham and Pearson Community
Similarity Index—Measures the degree of
similarity in taxonomic composition in
terms of taxon abundances and can be
calculated with either percentages or
numbers. A weighting factor can be
added that assigns more significance to
dominant species. See Pinkham and Pear-
son (1976) and U.S. EPA (1983) for more
detail. The formula is
min (x. , x.. ) fx. x..
Si _ r *a I" ia . ib / ,
•ab max (xia, xib) [xg xb /
where
weighting factor
Xja, X|b = number of individuals in the ilh
species in Sample A or B
Other community similarity indices sug-
gested by reviewers of this document
include Spearman's Rank Correlation
6-25
-------
(Snedecor and Cochran 1967), Morisita's
Index (Morisita 1959), Biotic Condition
Index (Winget and Mangum 1979), and
Bray-Curtis Index (Bray and Curtis 1959,
Whittaker 1952). Calculation of a chi-
square "goodness of fit" (Cochran 1952)
may also be appropriate.
CPOM Sample
Metric 8. Ratio of Shredder Functional Feeding
Group and Total Number of Individuals
Collected
Also based on the Functional Feeding
Group concept, the abundance of the Shred-
der Functional Group relative to the abun-
dance of all other Functional Groups allows
evaluation of potential impairment as indi-
cated by the CPOM-based Shredder com-
munity. Shredders are sensitive to riparian
zone impacts and are particularly good indi-
cators of toxic effects when the toxicants
involved are readily adsorbed to the CPOM
and either affect the microbial communities
colonizing the CPOM or the Shredders
directly (Cummins 1987).
The degree of toxicant effects on Shred-
ders versus Filterers depends on the nature
of the toxicants and the organic particle
adsorption efficiency. Generally, as the size
of the particle decreases, the adsorption
efficiency increases as a function of the
increased surface to volume ratio (Hargrove
1972). As stated in metric 3, water-borne
toxicants are readily adsorbed to FPOM.
Toxicants of a terrestrial source (e.g., pesti-
cides, herbicides) accumulate on CPOM
prior to leaf fall thus having a substantial
effect on Shredders (Swift et al. 1988a and
1988b). The focus of this approach is on a
comparison to the reference community,
which should have an abundance and diver-
sity of Shredders representative of the par-
ticular area under study. This allows for an
examination of Shredder or Collector "rela-
tive" abundance as indicators of toxicity.
The data collected in the 100-organism riffle/run
subsample and the CPOM sample are summarized
according to the information required for each
metric and entered on the Data Summary Sheet
(Figure 6.3-3).
Each metric result is given a score based on per-
cent comparability to a reference station. Scores are
totaled and a Biological Condition Category is
assigned based on percent comparability with the
reference station score (Figure 6.3-3). Values obtained
may sometimes be intermediate to established ranges
and require some subjective judgment as to assess-
ment of biological condition. In these instances, habi-
tat assessment, physical characterization, and water
quality data may aid in the evaluation process.
For RBP III, four categories of scores are estab-
lished for the assessment of biological condition. The
power to differentiate four categories for RBP III over
three for RBP II is derived from additional effort
necessary for the lowest possible taxonomic identifica-
tions. However, the rationale for metric percentage
ranges is essentially the same as for RBP II. Fig-
ure 6.3-4 outlines the steps that would be taken in a
biological assessment patterned after Protocol III.
6.4 RESULTS OF A PILOT STUDY
CONDUCTED ON THE ARARAT
AND MITCHELL RIVERS,
NORTH CAROLINA
6.4.1 Introduction
A joint survey was conducted by EA Engineering,
Science, and Technology and North Carolina Division
of Environmental Management (DEM) on 23-24 Sep-
tember 1986. The objective of this study was to inves-
tigate several methodological questions raised at the
Benthic Rapid Bioassessment Workshop held in July
1986.
The principal questions were
• Is it necessary to integrate sampling across all
appropriate habitats at a given site or will sampling
a single productive habitat (such as a riffle) suffice
for a general characterization of biological
integrity?
• Should abundances be characterized as categorical
estimates for a total sample or as relative abun-
dances based on a given size subsample? If counts
on subsamples are preferred, what is the minimum
count needed to detect basic differences among
stations?
• Can family-level identifications be useful for a site
prioritization or is it necessary to identify all organ-
isms to the lowest taxonomic level?
The purpose of this research project was to assess
the use of protocols II and III relative to the above
6-26
-------
Site-Specific Study
Sampling & Analysis
Metric
1. Taxa Richness'"'
2. Hilsenhoff Biotic Index (modified)0"
3. Ratio of Scrapers/Filt. Collectors*3-"0
4. Ratio of EPT and Chironomid Abundances'3'
5, % Contribution of Dominant Taxon'd)
6. EPT Index'a)
7. Community Loss Index'e'
8. Ratio of Shredders/Total'"-10
>80%
>85%
>50%
>75%
<20%
>90%
<0.5
>50%
Biological Condition Scoring Criteria
60-80%
70-85%
35-50%
50-75%
20-30%
80-90%
0.5-1.5
35-50%
40-60%
50-70%
20-35%
25-50%
30-40%
70-80%
1.5-4.0
20-35%
0
<40%
<50%
<20%
<25%
>40%
<70%
>4.0
<20%
(a) Score is a ratio of study site to reference site X 100.
(b) Score is a ratio of reference site to study site x 100.
(c) Determination of Functional Feeding Group is independent of taxonomic grouping.
(d) Scoring criteria evaluate actual percent contribution, not percent comparability to the reference station.
(e) Range of values obtained. A comparison to the reference station is incorporated in these indices.
BIOASSESSMENT
% Comp.
to Ref.
Score(a)
Biological Condition
Category
Attributes
>83% Nonimpaired
54-79% Slightly impaired
21-50% Moderately impaired
<17% Severely impaired.
Comparable to the best situation to be
expected within an ecoregion. Balanced
trophic structure. Optimum community
structure (composition and dominance)
for stream size and habitat quality.
Community structure less than
expected. Composition (species rich-
ness) lower than expected due to loss
of some intolerant forms. Percent con-
tribution of tolerant forms increases.
Fewer species due to loss of most
intolerant forms. Reduction in EPT
index.
Few species present. If high densities
of organisms, then dominated by one
or two taxa.
(a) Percentage values obtained that are intermediate to the above ranges
will require subjective judgement as to the correct placement. Use
of the habitat assessment and physiochemical data may be necessary to aid
in the decision process.
Recommendations
Figure 6.3-4. Flowchart of bioassessment approach advocated for Rapid Bioassessment Protocol III.
6-27
-------
questions. The purpose was not to disprove or dis-
credit any sampling techniques or assessment methods
presently in use. As stated earlier, the benthic rapid
bioassessment protocols are essentially a synthesis of
existing methods that have been employed for some
time by various States, (e.g., North Carolina, New
York, and Virginia). This guidance, therefore, is
meant to provide basic, cost-effective data gathering
methods for States that (1) have no established bioas-
sessment procedures, (2) are looking for alternative
methodologies, or (3) may need to supplement their
existing programs, (not supersede other bioassessment
approaches that have already been successfully
implemented). Furthermore, the results of the Ararat
and Mitchell River Pilot Study should not be viewed
as full validation of Rapid Bioassessment Protocols II
and III. Subsequent studies and additional refinement
in the course of implementation are needed to fully
validate the procedures presented in this document.
The Pilot Study was performed in conjunction with
North Carolina DEM because their methods were well
developed and supported by a large database. There-
fore, results from the North Carolina DEM biosurvey
provide the basis of evaluation for resolution of the
issues listed above.
6.4.2 Methods
The study site was the Ararat River near Mt. Airy,
North Carolina, located in the Central Appalachian
Ridge and Valley ecoregion. Sampling was conducted
at four stations on the Ararat River an'd one station on
the Mitchell River. The Mitchell River served as a
reference site representative of excellent biological
condition within the region. Two sites above the town
of Mt. Airy were selected to be used as site-speqific
controls. The station selected as a regional reference
(Station R) was on the Mitchell River, located near
the Ararat River in the same county. A description of
the biological sampling stations as illustrated in Fig-
ure 6.4-1 are as follows:
Station 1, Ararat River at NC 104. Station 1
served as a control station and was located near the
North Carolina-Virginia border. Station 1 was
established by North Carolina DEM to monitor the
water quality of the Ararat River above the town of
Mt. Airy. Land use in this area was a mixture of
forestry and agriculture.
Station 2, Ararat River at NC 52 (Bus.).
Station 2 provided an alternate control station and
was located approximately 1 mi above the WWTP
discharge. Station 2 was established by North Caro-
lina DEM to assess the impacts of urban runoff
and any unpermitted discharges. Land use was
predominantly urban.
Station 3, Ararat River near SR 2116. Station 3
was located just above the confluence of Lovills
Creek and the Ararat River and was several hun-
dred meters below the WWTP discharge. Land use
was predominantly urban.
Station 4, Ararat River at SR 2019. Station 4 was
a site sampled as part of the North Carolina DEM
ambient network on 4 August 1986. Station 4,
located about 11 miles below the Mt. Airy WWTP
discharge, was intended as a primary station for the
evaluation of recovery. Land use was primarily for-
estry with some agriculture.
Station R, Mitchell River at SR 1419. This "refer-
ence" station was established in an area known to
have good to excellent water quality. Land use was
predominantly forestry. Regional reference stations
are especially valuable in differentiating between
the effects of pollution and natural seasonal and
temporal variation, and in estimating the biological
potential of waterbodies within a region.
6.4.2.1 Field Collections
Samples were collected concurrently by personnel
from North Carolina DEM and EA Engineering,
Science, and Technology. At each station, one collect-
ing team from both North Carolina DEM and EA col-
lected two kick-net samples from riffle areas (from
both a fast and a slow current velocity area). In addi-
tion, North Carolina DEM personnel sampled other
habitats according to their standardized collection
technique utilizing a variety of sampling methods to
collect from all microhabitats present at a station
(Lenat 1988). Methods included kick net and sweep
net sampling of riffle areas, root masses, "snags,"
bank areas, and macrophyte beds; use of fine mesh
samplers into which invertebrates inhabiting rocks and
logs were washed; sieving of leaf pack and sand sam-
ples; and visual inspection of large rocks and logs to
collect attached organisms (N.C. DNR and Commu-
nity Development 1983).
EA samples were sorted in the field, with all
organisms and sample remains being preserved for
additional analysis. North Carolina samples were also
sorted in the field (according to their standard proce-
dure), but the organisms collected from the riffle
sample were kept separate from those found in all
other habitats. These samples were preserved in the
event that additional analysis was needed. Additional
information collected included a habitat assessment
and general physical characterization of the site (e.g.,
6-28
-------
NC 104
ARARAT RIVER
SR2019
ARARAT RIVER
Figure 6.4-1. Pilot study station locations, Ararat River, North Carolina, September 1986.
(Taken from 1 October 1986 NC DEM memorandum.)
6-29
-------
stream depth, width). The EA sampling effort did not
include collection of a CPOM sample. This pilot
study pre-dated inclusion of the Shredder metric in
RBPs H and III.
6A2.2 Laboratory Processing
Samples (vials of organisms) collected by North
Carolina DEM were taken to their laboratory and
processed according to standard agency procedures
(N.C. DNR and Community Development 1983).
Organisms were identified to genus or species and
tabulated as a total multihabitat sample with the taxa
composition for the riffle sample presented separately.
Abundances were characterized as categorical esti-
mates of total abundance.
Samples collected by EA were taken to the EA
laboratory and processed by a variety of methods to
allow comparisons among data sets. First, organisms
picked in the field were identified to the lowest posi-
tive taxon (species in most cases). Afterwards, these
organisms were added to the remainder of the sample
brought in from the field. Subsampling to obtain 100
organisms was then performed on the sample using
the methods in Appendix B. After picking and
separating 100 organisms, an additional 100 were
picked and kept separate a second and third time. All
three 100-organism subsamples (a total of approxi-
mately 300 organisms) were enumerated and identified
as separate entities.
6.4.2.3 Quality Assurance
Quality assurance measures were adhered to
throughout the pilot study to ensure the reliability of
results. Field collection of samples was conducted in
conjunction with North Carolina DEM personnel; all
samples being collected simultaneously at a given sta-
tion. Habitat was assessed consistently by the same
individual at all stations. All field efforts were
thoroughly documented.
All sample processing in the lab was performed by
the same individual to ensure consistency in sorting
and identification. Subsampling was randomized by
using a random numbers table. Number of organisms
picked from each block was recorded to verify ran-
dom distribution and to validate the Subsampling
procedure. Taxonomic identification was separately
documented for each subsample.
6.4.3 Bioclassification of
Stations Based on the
North Carolina DEM Protocol
Results of the North Carolina DEM study are
presented here as described in a memorandum from
Dave Lenat to Steve Tedder dated 1 October 1986
(Lenat 1986). These results form the basis for this
evaluation of the rapid bioassessment protocols. The
biological condition of the Ararat River is discussed
in reference to the condition of the Mitchell River
(reference station "R").
Although the Ararat River more than doubles in
size within the study area, we would expect only
minor changes in the composition of the benthic
community. Depth and substrate characteristics are
similar at all sites, although less sand was observed
at the Mitchell River station. This may reflect
fewer nonpoint-source problems in the Mitchell
River drainage area. Some substrate differences
may also be due to differences in soil type.
Taxa richness values (Table 6.4-1) indicated
good-fair water quality at Stations 1 and 2. Poor
water quality was indicated at Station 3, and fair
water quality at Station 4. Only the Mitchell River
(Station R) was found to have excellent water qual-
ity. There was little indication that urban runoff or
unpermitted discharges had any effect on the biota
of the Ararat River upstream of Station 2. The Mt.
Airy WWTP discharge eliminated all but the most
tolerant species, and full recovery appears to take
over 25 river miles under low flow conditions.
A Biotic IndexW has been computed for all
sites, using a numeric abundance of 1 for rare spe-
cies, 3 for common species, and 10 for abundant
species. This method will probably give a slightly
different value than more quantitative methods, but
this type of computation still appears to allow valid
between-station comparisons.
Ranking of stations by the Biotic Index values
gives results very similar to the taxa richness
criteria, i.e.:
= 2>4>3.
Plecoptera (stoneflies) were completely elimi-
nated at Stations 3 and 4 (Table 6.4-2).
Ephemeroptera (mayflies) were largely absent at
Station 3 and sharply reduced at Station 4.
Trichoptera (caddisflies) were also eliminated at
Station 3, but recovered more quickly than the
mayflies.
Patterns of numeric abundance for the major
groups also have been very roughly indicated
(Table 6.4-2) from both field notes and lab counts.
These data again indicate a strong similarity
between Stations 1 and 2, but note the increased
abundance of some Coleoptera (riffle beetles) at
WTolerance characterization developed by North Carolina
DEM.
6-30
-------
TABLE 6.4-1
BIOCLASSIFICATION RESULTS FOR NORTH CAROLINA DEM
MULTIHABITAT BENTHIC SAMPLES COLLECTED FROM THE
ARARAT (STATIONS 1-4) AND MITCHELL (STATION R)
RIVERS, 23-24 SEPTEMBER 1986
Stations
3
Total Taxa Richness
EpT(a) Taxa Richness
EPT Abundance(b)
Biotic Index
Numeric Value
Hilsenhoff Rating
tt Intolerant Taxa
All
(c)
# Unique Taxa
(d)
Bioclassification
(e)
64
18
92
63
20
75
32
1
1
50
11
76
94
31
133
2.6
Good
11
14
2
Good-
Fair
2.7
Good
7
11
6
Good-
Fair
3.4
Poor
0
1
2
V.Poor
3.2
Fair
1
3
3
Fair
2.3
V.Good
15
24
24
Excel.
(a) Intolerant groups—Ephemeroptera, Plecoptera, and Trichoptera.
(b) Rare=l, common=3, abundant=10, summed for all EPT groups.
(c) Only those intolerant taxa which are common or abundant are counted.
(d) Number of taxa occuring at only one of the five stations, very
tolerant species excluded.
(e) Based on DEM Taxa Richness Criteria for Piedmont Rivers.
Station 2. This site also had a greater number of
"unique" species (defined here as occurring at only
one of the study sites). These between-station
differences are probably due to the presence of
Podostemum (riverweed) at Station 2. Unexplained
factors appear to have reduced or eliminated
Podostemum growths at Station 1.
Organic indicator species were generally not
abundant at Ararat River sites. Only Limnodrilus
hoffmeisteri was found to be abundant, and only at
Station 3 (immediately below the WWTP dis-
charge). Note that another oligochaete taxon, Lum-
. briculidae, was abundant at both Stations 3 and 4.
This group is more strongly associated with toxics
than with organic pollution.
Toxic indicator species were abundant through-
out the Ararat River. The presence of Cricotopus
bicinctus and C. infuscatus gr. at both Stations 1
and 2 suggested some upstream toxicity problems.
Although these species were abundant at the
upstream stations, they were not dominant taxa. At
Stations 3 and 4, however, toxic indicator species
clearly dominated the benthic macroinvertebrate
community. These data indicate that toxic problems
are of greater importance in the Ararat River than
organic loading.
Other species-level data are also helpful in mak-
ing between-station comparisons. These data again
indicate comparable water quality at Stations 1 and
2. The loss of some intolerant species at Station 2
(Heptagenia aphrodite, Helichus, Hydropsyche
bronta, Atherix lanthd) seems to be offset by the
appearance of other intolerant species (Baetisca
Carolina, Promoresia elegans). It is also evident
that Station 3, just below the Mt. Airy discharge,
is occasionally influenced by drift from the
6-31
-------
TABLE 6.4-2 TAXA RICHNESS, BY GROUP, FOR SAMPLES COLLECTED BY
NORTH CAROLINA DEM FROM THE ARARAT (STATIONS 1-4)
AND MITCHELL (STATION R) RIVERS
Group
Ephemeroptera
Plecoptera
Trichoptera
Coleoptera
Odonata
Megaloptera
Diptera: Misc.
Diptera: Chiron.
Oligochaeta
Crustacea
Mollusca
Other
Subtotal (EPT)
Total
1
12(a)
2
4
6
3
2
4
23
3
2(a)
13(a)
6 ,
6
2
4
32
4
1
5(a)
3
31
94
(a) Dominant groups (from lab counts and field notes).
upstream sites. This explains the presence of spe-
cies such as Baetis ptuto and Promoresia elegans.
These species did not persist 11 miles downstream.
Several tolerant species were most abundant at
Station 4, about 11 miles below the discharge.
These taxa included Rheotanytarsus, Hydropsyche
betteni, Argia, and Stenacron interpunctatum. Note
that S.~interpunctatum has replaced the more
intolerant S. pallidum at this station.
6.4.4 Selection of Metrics
The analysis techniques in this document focus on
the use of metrics for assessment of various compo-
nents of benthic macroinvertebrate community struc-
ture and function. Various metrics were evaluated for
use in making a biological assessment of the benthic
community in the Ararat and Mitchell Rivers. The
metrics evaluated were:
Taxa or species richness—The number of taxa at the
lowest identifiable level.
Percent contribution of the dominant taxon—
Intended as a simple measure of evenness.
Modified Hilsenhoff Biotic Index (HBI)—Integrates
tolerance classification with abundance.
EPT Index—The number of distinct taxa within the
insect orders Ephemeroptera (mayflies), Plecoptera
(stoneflies), and Trichoptera (caddisflies).
Ratio of abundance of EFT organisms and
chironomid larvae—Intended to measure a shift in
organism dominance as a response to toxicants or
other pollutants.
Community Similarity Indices—The Jaccard Coeffi-
cient, Pinkham and Pearson Index, weighted Pink-
ham and Pearson Index, and Community Loss
Index.
Functional Group ratios—Shredders/Collectors,
Scrapers/Filterers, and Filterers/Gatherers.
6-32
-------
Cluster analyses were used as a means of data
evaluation, providing a level of differentiation among
varied data sets independent of the rapid bioassess-
ment technique. The few data acquired by this one
pilot study do not constitute a rigorous analysis, nor
are the results obtained by the cluster analysis
intended to be a definitive validation of the rapid
bioassessment technique. Hopefully, a larger database
will be available in the future to more adequately
refine the rapid bioassessment metrics and associated
criteria.
Thirteen metrics were calculated using the
100-organism subsample data collected from the riffle
habitat of the Ararat and Mitchell River stations. The
resulting information was compared using a cluster
analysis (Figure 6.4-2). The relative proximity of met-
rics on the dendrogram, based on distance between
cluster centroids, was used to determine the unique
information contributed by each metric to an
integrated bioassessment.
Seven metrics were considered to add some level
of information to the biological assessment, as
denoted by the distance between cluster centroids.
These are Taxa Richness, Percent Contribution of the
Dominant Taxon, Ratio of Scraper to Filtering Collec-
tor Functional Feeding Groups, Community Loss
Index, Ratio of EFT and Chironomid Abundances,
Modified HBI, and EPT Index. The other six metrics
appeared to be somewhat redundant to one or more of
these seven selected metrics in terms of contributed
information. These seven metrics, along with an
eighth metric added subsequently to the pilot study,
the Ratio of Shredder Functional Group to Total Num-
ber of Organisms (derived from a CPOM sample),
form the basis of the integrated analysis advocated in
this rapid bioassessment approach. These metrics are
described in Sections 6.2 and 6.3. The computed data
for the original seven metrics are presented in Tables
6.4-3 and 6.4-4.
In addition to cluster analysis, the bioassessment
technique described in Sections 6.2 and 6.3 was used
to evaluate relationships of biological condition among
stations. These results are presented in Section 6.4.8.
6.4.5 Comparison of Multihabitat vs.
Single Habitat Collections
From the analysis conducted by North Carolina
DEM, the stations were ranked from excellent to poor
biological condition as follows:
= 2>4»3
The double brackets, which indicate a greater
degree of difference between stations than a single
bracket, were added to the North Carolina DEM
p p
p
o
i
fi
cr
B M
in
M
§
o
Ul
m
Figure 6.4-2. Cluster analysis results for benthic community metrics, based on 100 organism
subsamples from riffle samples collected on the Ararat and Mitchell Rivers.
6-33
-------
T/BLE 6.4-3
METRIC VALUES, PERCENT COMPARISON, AND BIOASSESSMENT SCORES FOR BENTHIC PILOT STUDY RESULTS:
100-, 200-, AND 300-ORGANISM SUBSAMPLE DATA
Metric Value
Station
Metrics
1
2
3
4
R
% Comparison
Station
1 2
3
4
R
Bioassessment Score
Station
1
2
3
4 R
100-ORGANISM SUBSAMPLE
Taxa, Richness
HB I
Scrapers/Filt. Collect.
EPT/Chiron. Abundance
% Contrib. Dom. Taxon
EPT Indox ...
Community Loss Index
Total Score
Biological Condition
26
4.46
0.833
2.45
11.2
12
0.64
26
4.63
0.604
1.47
19.8
13
0.64
11
9.34
0.000
0.00
53.5
0
2.31
34
6.24
0.108
0.55
16.5
12
0.62
34
3.93
1.500
9.28
14.2
14
0
76 76
88 85
56 40
26 16
11 20
86 93
32
42
0
0
54
0
100
63
7
6
16
86
100
100
100
100
14
100
4
6
6
2
6
4
4
32
Slightly
4
4
4
0
4
6
4
26
Slightly
0
0
0
0
0
0
2
2
Sev.
6 6
2 6
0 6
0 6
6 6
4 6
4 6
22 42
Mod. Non
200-ORGANISM SUBSAMPLE
Taxa Richness
HB I
Scrapers/Filt . Collect.
EPT/Chiron. Abundance
% Contrib. Dom. Taxon
EPT Index d
Community Loss Index
Total Score
Biological Condition
32
4.55
0.92
3.07
11.1
15
0.68
32
4 .57
0 .54
1 .28
21 .1
15
0.73
15
9 . 33
0.00
0.00
56 .5
0
2.12
38
6 .06
0 .26
0.59
16.2
13
0.68
41
3 .63
3 .02
13.40
20.1
17
0
78 78
80 79
30 18
23 10
11 21
88 88
36
39
0
0
56
0
93
60
8
4
16
76
100
100
100
100
20
100
4
4
2
0
6
4
4
24
Slightly
4
4
0
0
4
4
4
20
Mod.
0
0
0
0
0
0
2
2
Sev.
6 6
2 6
0 6
0 6
6 4
2 6
4 6
20 40
Mod. Non
300-ORGANISM SUBSAMPLE
Taxa. Richness
HBITb'
Scrapers/Filt. Collect.
EPT/Chiron. Abundance
% Contrib. Dom. Taxon'
EPT index
Community Loss Index
Total Score
Biological Condition
36
4.56
0.84
2.91
10.6
16
0.68
42
4 .60
0.58
1 .39
19.5
18
0.75
19
9.31
0.00
0.00
56.3
0
2 .00
43
6.07
0.20
0.49
16.7
13
0.64
51
3.55
2.96
15.14
24.2
21
0
70 82
78 77
28 19
19 9
11 20
76 86
37
38
0
0
56
0
84
58
7
. 3
17
62
100
100
100
100
24
100
4
4
2
0
6
2
4
22
Slightly
6
4
0
0
4
4
4
22
Slightly
0
0
0
0
0
0
2
2
Sev.
6 6
2 6
0 6
0 6
6 4
0 6
4 6
18 40
Mod. Non
(a) Adjusted for use with seven metrics.
(b) Ratio of reference to station of comparison.
(c) Actual percent contribution evaluated, not percent comparability.
(d) Range of values evaluated, not percent comparability.
-------
TABLE 6.4-4
METRIC VALUES, PERCENT COMPARISON, AND BIOASSESSMENT SCORES FOR BENTHIC PILOT STUDY RESULTS:
EA FIELD-SORTED AND FAMILY-LEVEL IDENTIFICATION DATA
Metric Value
Station
Metrics 1 2 3 4 • R
% Comparison
Station
1 2 3 4 R
Bioas sessment Score
Station
1 234
R
EA FIELD SORTED
Taxa. richness
H BI
Scrapers/Filt. Collect.
EPT/Chiron. Abundance
% Contrib. Dora. Taxon
EFT Index
Community Loss Index
Total Score
Biological Condition
18
4.26
1.47
12.6
20.0
11
1 .00
30
3.98
1.60
s.oa
12 .0
15
0.53
7
8.33
0.00
0 .00
53.8
0
3 .50
17
5 .41
0 .32
1.96
23.2
10
1 .06
29
4.19
2.15
32.00
10.9
17
0
62
98
68
39
20
65
—
103
105
74
16
12
88
—
24
50
0
0
54
0
—
59
77
15
6
23
59
—
100
100
100
100
11
100
—
4
6
6
2
4
0
4
6
6
6
0
6
4
4
0
2
0
0
0
0
2
2
4
0
0
4
0
4
6
6
6
6
6
6
6
26 32 4 14 42
Slightly Slightly Sev. Mod. Non
FAMILY-LEVEL IDENTIFICATION
Taxa.richness
FBI
Scrapers/Filt. Collect.
EPT/Chiron. Abundance
% Contrib. dom. family
EFT Index
Community Loss Index
Total Score
Biological Condition
ct .
e , ,
iy(c|
(d)
12
5.15
0 .83
2.45
19.0
5
0.83
13
5.37
0.60
1.474
34.2
6
0.85
5
9.30
0.00
0.000
70.9
0
3.60
12
6 .14
0.11
0.550
54 .5
4
1 .08
21
4.59
1.50
9.286
34.0
8
0
57
89
56
26
19
62
62
85
40
16
34
75
24
49
0
0
71
0
57
75
7
6
54
50
100
100
100
100
34
100
3
6
6
3
6
0
3
27
Mod.
3
3
3
0
3
3
3
0
0
0
0
0
0
3
3
3
0
0
0
0
3
6
6
6
6
3
6
6
18
Mod.
Sev.
Sev.
39
Non
(a) Adjusted Cor use with seven metrics.
(b) Ratio of reference to station of comparison.
(c) Actual percent contribution evaluated, not percent comparability.
(d) Range of values evaluated, not percent comparability.
-------
results to provide another level of differentiation of
biological condition.
The North Carolina DEM analysis was conducted
by sampling several habitats and making an integrated
assessment focusing primarily on taxa richness and
EFT Index. These results were used as a basis for
comparison to results obtained only from the riffle
habitat. Comparison of taxa richness for the multi-
habitat and riffle samples that were analyzed using the
same method indicates that more taxa were collected
using the multihabitat approach (Figure 6.4-3). The
general trend of taxa richness among stations was
similar. Although the multihabitat approach provides a
distinct separation of benthic diversity among stations,
data obtained from the riffle habitat alone is sufficient
for a discrimination among the stations with regard
to taxa richness. A comparison of the EPT Index
between the multihabitat and riffle samples was highly
similar at all stations except at Station R (Fig-
ure 6.4-3).
The use of combined information from the seven
metrics was evaluated by performing independent clus-
ter analyses and comparing station relationship results
with those obtained from the North Carolina DEM
40
35
30-
25-
20
is-
le-
s'
NC Multihabitat
— -
NC Field Sorted Riffle
EA Field Sorted Riffle
NC Multihabitat
NC Field Sorted Riffle
EA Field Sorted Riffle
Stations
Figure 6.4-3. Comparison of taxa richness for all field sorted samples collected on the Ararat (Stations 1—4)
and Mitchell (Station R) Rivers.
6-36
-------
approach. Results of the cluster analysis performed on
the EA field-sorted .riffle sample (Figure 6.4-4) indi-
cate a station relationship based on similarity of
attributes from the seven metrics. However, the rela-
tionships of the stations in terms of biological condi-
tion cannot be determined using only the. clusters.
Therefore, a knowledge of the biological results
obtained using the North Carolina DEM analysis tech-
nique is used to put the station relationships in .
perspective.
= 2>4»3
A further analysis was conducted on the riffle
sample by subsampling to 100 organisms in the
laboratory, identifying and enumerating, and perform-
ing a cluster analysis on the computed metrics. The
results of the clusters indicate that Stations 1 and 2
are most similar, with Station 4 being next most simi-
lar to the centroid of 1 and 2. The reference station
was unlike any of the others, as was Station 3. Rear-
ranging these results in the context of the biological
data to provide an interpretation of impairment, these
results (Figure 6.4-5) also indicate a strong similarity
with the classification presented by the North Carolina
DEM. The ranking of stations according to biological
condition from the laboratory-processed samples using
1.4 -
3 1.2-
1 1-
*
5 0.8-
O
§ 0.6 -
** 0 4 -
S?
S 0.2 -
5
0 -
I
1 2
4 R 3
Stations
Figure 6.4-4. Station cluster analysis results for field sorted riffle samples collected on the Ararat
(Station 1-4) and Mitchell (Station R) Rivers.
1.4
1.2-
o,-
0-
4
Stations
n
Figure 6.4-5. Station cluster analysis results for 100 organism subsamples from riffle samples
collected on the Ararat (Stations 1-4) and Mitchell (Station R) Rivers.
6-37
-------
the clusters is:
= 2>4»3
This preliminary analysis of multihabitat versus
single habitat conducted at one site suggests that the
single habitat approach can provide a representative
sample for an evaluation of biological condition.
6.4.6 Evaluation of the
100-Organism Subsample
To determine if a 100-organism subsample pro-
vides an adequate estimate of community structure,
comparisons were made between 100-, 200-, and 300-
organism subsamples. Although comparison of the
cumulative taxa richness and EFT values for the 100-,
200-, and 300-organism subsamples (Table 6.4-3) indi-
cates that additional information is gained with each
incremental increase in organism count, results of a
cluster analysis of the seven metrics performed on the
300-organism count data (Figure 6.4-6) showed the
same station relationship as that obtained with the
100-organism data (Figure 6.4-5). The greater sensitiv-
ity demonstrated with the 300-organism data was
subtle and may not warrant the additional time expen-
diture required.
Laboratory sorting of each 100-organism subsam-
ple was estimated to require between 1 and 1.5 hours.
If a 300-organism subsample was used, approximately
3 to 4.5 hours would be necessary to pick the organ-
isms from the sample. The time-savings estimated
for the 100-organism subsample, combined with the
minimal additional information provided with addi-
tional subsamples, supports the contention that a
100-organism subsample is adequate for assessment of
the benthic community. Other researchers have also
found that a 100-organism subsample will provide
sufficient data to detect impact (Nuzzo 1986, Bode
1988, Shackleford 1988).
6.4.7 Family-Level vs.
Species-Level Identification
Additional tabulation was done to determine if
family-level identifications resulted in similar site clas-
sifications. A cluster analysis was performed on all of
the 13 metrics described in Section 6.4.4 for the
family-level data of the 100-organism riffle sample.
Results obtained with the cluster analysis (Figure 6.4-7)
showed the same relationship in terms of contribution
of the metrics to the assessment as did the species-
level (lowest taxon) analysis. Therefore, the seven
metrics used for the lowest taxonomic level assess-
ment were used for the family-level assessment.
Data for the seven computed metrics using family-
level identification are presented in Table 6.4-4.
Results of station clusters illustrate a spatial trend
(Figure 6.4-8) that is the same as that obtained using
the RBP III approach on the 100-organism (lowest
taxon) data (Figure 6.4-5). Stations 1 and 2 were most
similar; Station 4 clustered next, then R, and finally
3. However, the bioassessment scheme of the family-
level protocol is more general than that provided by
Distance between Cluster Centroids
0 O 0 0 — -
oK>*d»OB-*r\>*
I 1 I I 1 I 1 I
1
1 1
1 2 4 R 3
Stations
Figure 6.4-6. Station cluster analysis results for 300 organism subsamples from riffle samples
collected on the Ararat (Station 1—4) and Mitchell (Station R) Rivers.
6-38
-------
p
2
o>
O
S
in
O
5
S
4»3
The family-level data differed slightly in level of
station similarity compared to that for the species-
level (I00-organism riffle), which is to be expected
with different taxonomic levels of identification. How-
ever, results indicate that a reasonably good evaluation
can be obtained with family-level identifications. The
relative sensitivity of a family-level identification effor.
is sufficient for a prioritization or site ranking pro-
tocol that would differentiate between non-impaired,
moderately impaired, and severely impaired
conditions.
6.4.8 Integrated Bioassessment
A summary of the bioclassification scheme for the
stations that was derived from the cluster analysis per-
formed on all of the data sets and the North Carolina
DEM analysis technique is presented in Table 6.4-5.
6-39
-------
TABLE 6.4-5
SUMMARY OF THE BIOCLASSIFICATION DERIVED FROM
AN ANALYSIS OF SAMPLES COLLECTED FROM THE
ARARAT AND MITCHELL RIVERS
Data Set
Bioclassification
Cluster Analysis (Based on NC DEM Classifications)
NC multihabitat; NC analysis
EA field-sorted riffle; RBP III analysis
100-organism riffle; RBP III analysis
300-organism riffle; RBP III analysis
100-organism riffle; RBP II (family) analysis
R
R
R
R
R
»
»
»
»
»
1
1
1
1
1
= 2
= '2
= 2
= 2
= 2
>
>
>
>
>
4
4
4
4
4
»
»
»
»
»
3
3
3
3
3
Bioassessment Technique
NC multihabitat; NC analysis
EA field sorted riffle; RBP III analysis
100-organism riffle; RBP III analysis
300-organism riffle; RBP III analysis
100-organism riffle; RBP II (family) analysis
R » 1 = 2 > 4 » 3
R>1 = 2>4>3
R>1 = 2>4»3
R»l = 2>4>3
R>1 = 2>4 = 3
Very little variation existed in the relationship of Sta-
tions R, 1, and 2, whereby R was always of greater
quality than Station 1, and essentially the same quality
existed between Stations 1 and 2. In addition, the
orientation of the stations in terms of biological condi-
tion was the same for all data sets. The subjectivity in
these analyses exists in the fact that some judgment
has to be used in interpreting the biological relation-
ships from the station similarity information illustrated
by the dendrograms of the cluster analysis. It is possi-
ble that the close proximity of Station 4 to the cen-
troid of Stations 1 and 2 could indicate equality rather
than a slightly lower quality. This situation occurred
particularly in the data sets of the 300-organism riffle
subsample and the multihabitat RBP III analysis.
Using the scoring criteria described for RBP II
(Section 6.2) and RBP III (Section 6.3), the bioassess-
ment metrics were calculated. The bioclassification
for the 100-organism subsample species-level identifi-
cation resulted in Station R being classified as non-
impaired, Stations 1 and 2 as slightly impaired, Sta-
tion 4 as moderately impaired, and Station 3 as
severely impaired (Table 6.4-3). Therefore,
R>1 =2>4»3. Bioclassification for the
300-organism subsample resulted in a classification
similar to that of the 100-organism count samples.
The station relationship results based on biological
condition using the bioassessment approach are not
unlike those obtained using the cluster analysis
(assuming the biological condition as identified by
NC DEM) on the same data sets. However, the
amount of data was limited for an adequate cluster
analysis. Station ranking based on results of the field-
sorted riffle sample is similar to that resulting from
the North Carolina DEM multihabitat bioclassifica-
tion. Although differences among stations were more
conservative using the RBP approach, these are the
same station trends observed in the cluster analysis for
this data set (Table 6.4-5).
The family-level bioclassification results suggest an
orientation slightly different from that obtained with
the 100-organism (species-level) sample (Table 6.4-4).
6-40
-------
Both the species-level bioassessment and the station
cluster for the family-level data indicated that Station
3 .is different from Station 4, which reflects the lesser
sensitivity associated with the family-level identifica-
tion used in RBP II (Table 6.4-5). The difference
between family-level bioclassification (moderate
impairment) and species-level bioclassification (slight
impairment) at Stations 1 and 2 is attributable to the
fact that the RBP II classification scheme is based on
only three levels of impairment as opposed to the four
levels used in RBP III.
The bioassessment technique appears to be more
conservative than the clustering technique, which may
be beneficial from a water quality management point
of view. Subtle differences in structure and function
will be regarded as rationale for further confirmative
study, to ascertain the significance of complex impair-
ment problems. If an evaluation of biological condi-
tion was based on a straight percent-of-refere.nce, a
slightly different scenario might be obtained. A
greater differentiation between Stations R and 1 and
between Stations 3 and 4 would be one outcome.
However, based on this single pilot study, the ranges
of biological condition are necessarily conservative.
With a good reference database, these ranges can be
modified, making them either more or less protective.
6-41
-------
7. FISH BIOSURVEY AND DATA ANALYSIS
Two levels of fish biosurvey analyses are
presented: Rapid Bioassessment Protocol IV consti-
tutes a questionnaire approach where local and State
fisheries experts are canvassed for existing data and
information; Rapid Bioassessment Protocol V consists
of collecting fish at selected sites for biosurvey anal-
yses. The data analysis used in RBP V is based on
the IBI (Karr et al. 1986) and the IWB (Gammon
1980). This document only provides an overview of
the IBI and IWB and their conceptual foundations.
Effective use of RBP V requires information presented
in Karr et al. (1986) and Gammon (1980). Sample
field and data sheets are presented as guidance.
Pilot studies based on use of the fish biosurvey
(RBP V) have been published. An overview of two of
these studies is presented in Section 7.3.
7.1 RAPID BIOASSESSMENT
PROTOCOL IV-FISH
The intent of RBP IV is to serve as a screening
tool and to maximize the use of existing knowledge of
fish communities. The questionnaire polls State fish
biologists and university ichthyologists- believed
knowledgeable about the fish assemblages in stream
reaches of concern. The proposed questionnaire (Fig-
ure 7.1-1) is modeled after one used in a successful
national survey of 1,300 river reaches or segments
(Judy et al. 1984). Unlike field surveys, questionnaires
can provide information about tainting or fish tissue
contamination and historical trends and conditions.
Disadvantages of questionnaires include inaccuracy
caused by hasty responses, a desire to report condi-
tions as better or worse than they are, and insufficient
knowledge. The questionnaire provides a qualitative
assessmenrof"a~ large number of waterbodies quickly
and inexpensively. Its quality depends on the survey
design (the number and location of waterbodies), the
questions presented, and the knowledge and coopera-
tion of the respondents.
This document provides guidance on the design
and content of the questionnaire survey. Judy et al.
(1984) found that State fish and game agencies have a
vested interest in assuring the quality of the data, and
they generally provide reliable information.
7.1.1 Design of Fish Assemblage
Questionnaire Survey
Selection of stream reaches requires considerable
forethought. If the survey program is statewide or
regional in scope, a regional framework is advisable.
Regional reference reaches can be selected to serve as
benchmarks for comparisons (Hughes et al. 1986).
These sites should be characteristic of the waterbody
types and sizes in the region and should be minimally
impacted. The definition of minimal impact varies
from region to region, but includes those waters that
are generally free of point sources, channel modifica-
tions, and diversions, and have diverse habitats, com-
plex bottom substrate, considerable instream cover,
and a wide buffer of natural riparian vegetation.
Remaining sites should also be selected carefully.
If the questionnaire focuses on larger streams, a
1:1,000,000 scale topographic map should be used for
reach selection. Reaches of small streams should be
selected from the largest scale map possible; reaches
selected from 1:250,000 versus 1:24,000 scale topo-
graphic maps may omit as much as 10 percent of the
permanent streams in humid, densely forested areas.
Small, medium, and large streams should be selected
based on their importance in the region.
The potential respondent (or the agency chief if a
number of agency staff are to be questioned) should
be contacted initially by telephone to identify
appropriate respondents. To ensure maximum
response, the questionnaire should be sent at times
other than the field season and the beginning and end
of the fiscal year. The questionnaire should be accom-
panied by a personalized cover letter written on offi-
cial stationary, and closed by an official title below
the signature. A stamped, self-addressed return enve-
lope increases the response rate. Materials mailed first
or priority class are effective; special delivery and
certified letters are justified in follow-up mailings. Tel-
ephone contact is advisable after three follow-up
notes.
7.1.2 Response Analysis
Questionnaire response should provide the follow-
ing information:
1. The integrity of the fish community
7-1
-------
FISH ASSEMBLAGE QUESTIONNAIRE
INTRODUCTION
This questionnaire is part of an effort to assess the biological health
or integrity of the flowing vaters of this state. Our principle focus is
on the biotic health of the designated vaterbody as indicated by its fish
community. You were selected to participate in the study because of your
expertise in fish biology and your knowledge of the vaterbody identified
in this questionnaire.
Using the scale below, please circle the rank (at left) corresponding to
the explanation (at right) that best describes your impression of the
condition of the waterbody. Please complete all statements. If you feel
that you cannot complete the questionnaire, check here [ ] and return
it. If you are unable to complete the questionnaire but are aware of
someone who is familiar with the waterbody, please give this person's
name, address, and telephone number in the space provided below.
Vaterbody code
Vaterbody name
Vaterbody location (also see map)
State County Long/Lat
Ecoregion
Vaterbody size
Stream (<1 cfs, 1-10 cfs, >10 cfs)
r
(Answer questions 1-4 using the scale below.)
5 Species composition, age classes, and trophic structure comparable to
non (or minimally) impacted sites of similar waterbody size in that
ecoregion.
4 Species richness somewhat reduced by loss of some intolerant species;
young of the year of top carnivores rare; less than optimal
abundances, age distributions, and trophic structure for waterbody
size and ecoregion.
3 Intolerant species absent, considerably fewer species and individuals
than expected for that waterbody size and ecoregion, older age classes
of top carnivores rare, trophic structure skewed toward omnivory.
Figure 7.1-1. Fish assemblage questionaire for use with Rapid Bioassessment Protocol IV.
7-2
-------
2 Dominated by highly tolerant species, omnlvpres, and habitat
generalists; top carnivores rare or absent; older age classes of all
but tolerant species rare; diseased fish and anomalies relatively
common for that vaterbody size and ecoregion.
1 Few individuals and species present, mostly tolerant.species and small
individuals, diseased fish and anomalies abundant compared to other
similar-sized vaterbodies in the ecoregion.
0 No fish
(Circle one number using the scale above.)
1. Rank the current conditions of the reach
5 -4 3 2 1 0 ' '
2. Rank the conditions of the reach 10 years ago
543210
3. Given present trends, hov will the reach rank 10 years from now?
543210 ....
4. If the major human-caused limiting factors were eliminated, how
would the reach rank 10 years from now?
(Complete each subsection by circling the single most appropriate
limiting factor and probable cause.)
Subsection 1—Water Quality
Limiting factor
5 Temperature too high
6 Temperature too low
7 Turbidity
8 Salinity
9 Dissolved oxygen
10 Gas supersaturation
11 pH too acidic
12 pH too basic •
13 Nutrient deficiency
14 Nutrient surplus
15 Toxic substances
16 Other (specify below)
17 Not limiting
Probable cause
18 Primarily upstream
19 Within reach
20 Point source discharge
21 Industrial
22 Municipal
23 Combined sewer
24 Mining '
25 Dam release
26 Nonpoint source discharge
27 Individual sewage
28 Urban runoff '•
Landfill leachate
Construction
Agriculture
Feed lot
Grazing
Silviculture
Mining
29
30
31
32
33
34
35
36 Natural"
37 Unknown
38 Other (specify below)
Figure 7.1-1. (Cont.).
7-3
-------
Subsection 2--Vater Quantity
Limiting factor
39 Below optimum flows
40 Above optimum flows
41 Loss of flushing flows
42 Excessive flow fluctuation
43 Other (specify below)
44 Not limiting
Probable source
45 Dam
46 Diversion
47 Watershed conversion
48 Agriculture
49 Silviculture
50 Grazing
51 Urbanization
52 Mining
53 Natural
54 Unknown
55 Other (specify below)
Subsection 3--Habitat Structure
Limiting factor
56 Excessive siltation
57 Insufficient pools
58 Insufficient riffles
59 Insufficient shallows
60 Insufficient concealment
61 Insufficient reproductive
habitat
62 Other (specify below)
63 Not limiting
Subsection 4—Fish Community
Limiting factor
76 Overharvest
77 Underharvest
78 Fish stocking
79 Non-native species
80 Migration barrier
81 Tainting
82 Other (specify below)
83 Not limiting
Probable cause
64 Agriculture
65 Silviculture
66 Mining
67 Grazing
68 Dam
69 Diversion
70 Channelization
71 Snagging
72 Other channel modifications
73 Natural
74 Unknown
75 Other (specify below)
Probable source
84 Fishermen
85 Aquarists
86 State agency
87 Federal agency
88 Point source
89 Nonpoint source
90 Natural
91 Unknown
92 Other (specify below)
Subsection 5—Major Limiting Factor
93 Water quality
94 Water quantity
95 Habitat structure
96 Fish community
97 Other (specify)
Your name (please print)
Figure 7.1-1. (Cont.).
7-4
-------
2. The frequency of occurrence of particular limiting
factors and causes
3. The frequency of occurrence of particular fish
community condition characterizations for the past,
present, and future.
4. The geographic patterns in these variables
5. The temporal trends in the variables
6. Effect of waterbody type and size on the spatial
and temporal trends and the associated limiting
factors
7. The likelihood of improvement and degradation
8. The major limiting factor
The questionnaire data are most effectively entered
and analyzed by using a microcomputer and interac-
tive database management software (e.g., dBase III or
Revelation). This software reduces data entry errors
and facilitates the qualitative analysis of numerous
variables. Results can be reported as histograms, pie
graphs, or box plots. If such a system is unavailable
data can be analyzed and the results plotted by hand.
RBP IV allows considerable flexibility.
7.2 RAPID BIOASSESSMENT
PROTOCOL V—FISH
Rapid Bioasssessment Protocol V (RBP V) is a
rigorous approach similar to macroinvertebrate
RBP III in accuracy and effort, but focuses on the
fish community. RBP V involves careful, standardized
field collection, species identification and enumera-
tion, and community analyses using biological indices
or quantification of the biomass and numbers of key
species. The RBP V survey yields an objective, dis-
crete measure of the health of the fish community that
usually can be completed onsite by qualified fish biol-
ogists (difficult species identifications may require
laboratory confirmation). Data provided by RBP V
can serve to assess use attainment, develop biological
criteria, prioritize sites for further evaluation, provide
a reproducible impact assessment, and assess fish
community status and trends. RBP V is based primar-
ily on the Index of Biotic Integrity (IBI), a fish com-
munity assessment approach developed by Karr (1981).
A more detailed description of this approach is
presented in Karr et al. (1986) and Ohio EPA (1987b).
Regional modifications and applications are described
in Hughes and Gammon (1987), Leonard and Orth
(1986), Steedman (1988), Wade and Stalcup (1987),
and Miller et al. (1988a).
7.2.1 Field Survey Methods
RBP V involves field evaluation of the same phys-
icochemical and habitat characteristics as RBPs I, II,
and III (Figures 5.1-1 and 5.2-1), a similar impairment
assessment (Figure 7.2-1), and a fish community
biosurvey. Because it provides critical information for
evaluating the cause and source of impairment, the
habitat and physical characterization (described in
Chapter 5 of this document) are essential to RBP V.
The approach for conducting a RBP V site-specific
fish community analysis is based on the use of the IBI
(Figure 7.2-2).
7.2.1.1 Sample Collection
Electrofishing, the most common technique used
by agencies that monitor fish communities, and the
most widely applicable approach for stream habitats,
is the sampling technique recommended for use with
RBP V. However, pilot studies may indicate the need
for different or multiple gear.
The fish community biosurvey data are designed to
be representative of the fish community at all station
habitats, similar to the "representative qualitative sam-
ple" proposed by Hocutt (1981). The sampling station
should be representative of the reach, incorporating at
least one (preferably two) riffle(s), run(s), and pool(s)
if these habitats are typical of the stream in question.
Sampling of most species is most effective near shore
and cover (macrophytes, boulders, snags, brush). The
biosurvey is not an exhaustive inventory, but it pro-
vides a realistic sample of fishes likely to be encoun-
tered in the waterbody. Sampling procedures effective
for large rivers are described in Gammon (1980),
Hughes and Gammon (1987), and Ohio EPA (1987b).
Typical sampling station lengths range from
100-200 meters for small streams to 500-1000 meters
in rivers, but are best determined by pilot studies. The
size of the reference station should be sufficient to
produce 100-1000 individuals and 80-90 percent of
the species expected from a 50 percent increase in
sampling distance. Sample collection is usually done
during the day, but night sampling can be more effec-
tive if the water is especially clear and there is little
cover (Reynolds 1983). Use of block nets set (with as
little wading as possible) at both ends of the reach
increases sampling efficiency for large, mobile species
sampled in small streams.
The RBP V fish community assessment requires
that all fish species (not just gamefish) be collected.
This reduces the effects of stocking and fishing and
acknowledges the growing public interest in nongame
7-5
-------
Field crew electrofishing with a pram-towed unit.
7-6
-------
IMPAIRMENT ASSESSMENT SHEET
1. Detection of impairment: Impairment detected
(Complete Items 2-6)
No impairment
detected
(Stop here)
2. Biological impairment indicator:
Pish
sensitive species reduced/absent
dominance of tolerant species
skewed trophic structure
abundance reduced/unusually high
biomass reduced/unusually.high
hybrid or exotic abundance '
unusually high
poor size class representation
high incidence of anomalies
3. Brief description of problem:
Other aquatic communities
Macroinvertebrates
Periphyton
Macrophytes
Year and date of previous surveys:
Survey data available in:
i>. Cause (indicate major cause): organic enrichment toxicants flow
• sediment temperature poor habitat
other
5. Estimated areal extent' of problem (m ) and length of stream reach
affected (m) where applicable: -
6. Suspected source(s) of problem
point source
urban runoff
agricultural runoff
silvicultural runoff
livestock
landfill
mine
dam or diversion
channelization or snagging
natural
other
unknown
Comments:
Figure 7.2-1. Impairment Assessment Sheet for use with fish Rapid Bioassessment Protocol V.
7-7
-------
I Select a Site
I
Identify Regional Fish Fauna
I
Assign Species to Trophic, Tolerance, and Origin Guilds
Assess Available Data for Metric Suitability and Stream
Size Patterns
_L
Develop Scoring Criteria from Reference Sites
Quantitatively Sample Fish
I
List Abundances of Species, Hybrids, and Anomalies
_L
Calculate and Score Metric Values
METRIC SCORES (IBI)
Scoring Criteria'"'
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
Metric
Number of native fish species
Number of darter or benthic species
Number of sunfish or pool species
Number of sucker or long-lived species
Number of intolerant species
Proportion of green sunfish or tolerant
individuals
Proportion omnivorous individuals
Proportion insectivores
Proportion top carnivores
Total number of individuals
Proportion hybrids or exotics
Proportion with disease/anomalies
5
>,67%
>67%
>67%
>67%
>67%
<10%
<20%
>45%
>5%
>67%
0%
3
33-67%
33-67%
33-67%
33-67%
33-67%
10-25%
20-45%
20-45%
1-5%
33-67%
0-1%
<1% 1-5%
'"'Metrics 1-5 are scored relative to the maximum species richness
Metric 10 is drawn from reference site data.
1
<33%
<33%
<33%
<33%
<33%
>25%
>45%
<20%
<1%
<33%
>1%
>5%
line.
INDEX SCORE INTERPRETATION'"'
IBI
58-60
48-52
28-34
12-22
Integrity Class
Excellent
Good
Fair
Poor
Very Poor
Characteristics
Comparable to pristine conditions,
exceptional assemblage of species
Decreased species richness,
intolerant species in particular;
sensitive species present
Intolerant and sensitive species
absent; skewed trophic structure
Top carnivores and many expected
species absent or rare; omnivores and
tolerant species dominant
Few species and individuals present;
tolerant species dominant; diseased
fish frequent
(a'From Karr et al. 1986; Ohio EPA 1987.
Recommendations
Figure 7.2-2. Flowchart of bioassessment approach advocated for Rapid Bioassessment Protocol V.
7-8
-------
species. Small fish that require special gear for their
effective collection may be excluded. Exclusion of
young-of-the-year fish during collection can have a
minor effect on IBI scores (Angermeier and Karr
1986), but lowers sampling costs and reduces the need
for laboratory identification. Karr et al. (1986) recom-
mended exclusion of fish less than 20 mm in length.
This recommendation should be considered on a
regional basis and is also applicable to large fish
requiring special gear for collection (e.g., sturgeon).
The intent of the sample (as with the entire protocol)
is to obtain a representative estimate of the species
present, and their abundances, for a reasonable
amount of effort.
Sampling effort among stations is standardized as
much as possible. Regardless of the gear used, the
collection method, site length (or area), and work
hours expended must be comparable to allow compari-
son of fish community status among sites. Major habi-
tat types (riffle, run, and pool) sampled at each site
and the proportion of each habitat type sampled
should also be comparable. Generally 1 to 2 hours of
actual sampling time are required, but this varies con-
siderably with the gear used and the size and com-
plexity of the site.
Atypical conditions, such as high flow, excessive
turbidity or turbulence, heavy rain, drifting leaves, or
other unusual conditions, that affect sampling effi-
ciency, are best avoided. Glare, a frequent problem, is
reduced by wearing polarized glasses during sample
collection.
7.2.1.2 Sample Processing
A field collection data sheet (Figure 7.2-3) is com-
pleted for each sample. Sampling duration and area or
distance sampled are recorded in order to determine
level of effort. Species may be separated into adults
and juveniles by size and coloration; then total num-
bers and weights and the incidence of external anoma-
lies are recorded for each group. Reference specimens
of each species from each site are preserved in
10 percent formaldehyde, the jar labeled, and the col-
lection placed with the State ichthyological museum to
confirm identifications and to constitute a biological
record. This is especially important for uncommon
species, for species requiring laboratory identification,
and for documenting new distribution records. If
retained in a live well, most fish can be identified,
counted, and weighed in the field by trained personnel
and returned to the stream alive. In warmwater sites,
where handling mortality is highly probable, each fish
is identified and counted, but for abundant species,
subsampling may be considered. When subsampling is
employed, the subsample is extrapolated to obtain a
final value. Subsampling for weight is a simple,
straightforward procedure, but failure to examine all
fish to determine frequency of anomalies (which may
occur in about 1 percent of all specimens) can bias
results. The trade off between handling mortality and
data bias must be considered on a case-by-case basis.
If a site is to be sampled repeatedly over several
months (i.e., monitoring), the effect of sampling mor-
tality may outweigh data bias. Holding fish in live-
boxes in shaded, circulating water will substantially
reduce handling mortality. More information on field
methods is presented in Karr et al. (1986) and Ohio
EPA (1987b).
7.2.2 Data Analysis Techniques
Based on observations made in the assessment of
habitat, water quality, physical characteristics, and the
fish biosurvey, the investigator concludes whether
impairment is detected. If impairment is detected, the
probable cause and source is estimated and recorded
on an Impairment Assessment Sheet (Figure 7.2-1). A
preliminary judgment on the presence of biological
impairment is particularly important if RBP IV is not
used prior to RBP V.
Data can be analyzed using the IBI (or individual
IBI metrics), the IWB (Gammon 1980), and multivari-
ate statistical techniques to determine community
similarities. Detrended correspondence analysis (DCA)
is a useful multivariate analysis technique for revealing
regional community patterns and patterns among mul-
tiple sites. It also demonstrates assemblages with com-
positions differing from others in the region or reach.
See Gauch (1982) and Hill (1979) for descriptions of,
and software for, DCA. Data analyses and reporting,
including parts of the IBI, can be computer generated.
Computerization reduces the time needed to produce a
report and increases staff capability to examine data
patterns and implications. Illinois EPA has developed
software to assist professional aquatic biologists in cal-
culating IBI values in Illinois streams (Bickers et al.
1988). (Use of this software outside Illinois without
modification is not recommended.) However, hand
calculation in the initial use of the IBI promotes
understanding of the approach and provides insight
into local inconsistencies.
The IBI is a broadly-based index firmly grounded
in fisheries community ecology (Karr 1981; Karr et al.
1986). The IBI incorporates zoogeographic, ecosys-
tem, community, population, and individual perspec-
tives. It can accommodate natural differences in the
distribution and abundance of species that result from
differences in waterbody size, type, and region of
occurrence (Miller et al. 1988a). Use of the IBI
allows national comparisons of biological integrity
7-9
-------
FISH FIELD COLLECTION DATA SHEET
page
of
Date .
Drainage
Sampling Duration (rain)
Sampling Distance (m)
Habitat Complexity/Quail
Weather
Gear Used
Comments
Fish (preserved) Number of Individuals
Sampling Area
ty (excellent good
Crew
poor very
_
fair
Flow (flood bankfull moderate lov)
Gear/Crev Performance
poor)
Number of Anomalies
Genus/Species
Adults
Juveniles
No.
Ut.
No.
tft.
Anomalies
No.
(*)
(*) Discoloration, deformities, eroded fins, excessive mucus, excessive
external parasites, fungus, poor condition, reddening, tumors,
and ulcers
Figure 7.2-3. Fish Field Collection Data Sheet for use with Rapid Bioassessment Protocol V.
7-10
-------
without the traditional bias for small coldwater
streams (e.g., a salmon river in Alaska and a minnow
stream in Georgia both could be rated excellent if
they were comparable to the best streams expected in
their respective regions).
Karr et al. (1986) provided a consistent theoretical
framework for analyzing fish community data. The
IBI uses 12 biological metrics to assess integrity based
on the fish community's taxonomic and trophic com-
position and the abundance and condition of fish.
Such multiple-parameter indices are necessary for
making objective evaluations of complex systems. The
IBI was designed to evaluate the quality of small mid-
western streams but has been modified for use in
many regions of the country and in large rivers (Sec-
tion 7.2.2.1).
The metrics attempt to quantify an ichthyologist's
best professional judgment of the quality of the fish
community. The IBI utilizes professional judgment,
but in a prescribed manner, and it includes quantita-
tive standards for discriminating fish community con-
dition. Judgment is involved in choosing the most
appropriate population or community element that is
representative of each metric and .in setting the scor-
ing criteria. This process can be easily and clearly
modified, as opposed to judgments that occur after
results are calculated. Each metric is scored against
criteria based on expectations developed from
appropriate regional reference sites. Metric values
approximating, deviating slightly from, or deviating
greatly from values occurring at the reference sites are
scored as 5, 3, or 1, respectively. The scores of the
12 metrics are added for each station to give an IBI of
60 (excellent) to 12 (very poor). Trophic and tolerance
classifications of midwestern and northwestern fish
species are listed in Appendix D. Additional classifi-
cations can be derived from information in State and
regional fish texts or by objectively assessing a large
statewide database. Use of the IBI in the southeastern
and southwestern United States and its widespread use
by water resource agencies may result in further
modifications. Past modifications have occurred (Sec-
tion 7.2.2.1; Miller et al. 1988a) without changing the
IBI's basic theoretical foundations. Sample calcula-
tions of the IBI are given in Section 7.3.
The steps in calculating the IBI (Figure 7.2-2) are
explained below:
1. Assign species to trophic guilds; identify and
assign species tolerances. Where published data are
lacking, assignments are made based on knowledge
of closely related species and morphology.
2. Develop scoring criteria for each IBI metric. Maxi-
mum species richness (or density) lines are devel-
oped from a reference database.
3. Conduct field study and identify fish; note anoma-
lies, eroded fins, poor condition, excessive mucous,
fungus, external parasites, reddening, lesions, and
tumors. Complete field data sheets.
4. Enumerate and tabulate number of fish species and
relative abundances.
5. Summarize site information for each IBI metric.
6. Rate each IBI metric and calculate total IBI score.
7. Translate total IBI score to one of the five integrity
classes.
8. Interpret data in the context of the habitat assess-
ment (see Chapter 8). Individual metric analysis
may be necessary to ascertain specific trends.
The IBI is based on an integrated analysis of the
metrics. However, individual IBI metrics may serve as
separate variables to aid in data interpretation. Com-
parison of commonly-occurring and dominant species
are revealing, especially when related to their ecologi-
cal requirements and tolerances. Larsen et al. (1986)
and Rohm et al. (1987) provide examples of such
regional characterizations of common and abundant
species. The IWB (Gammon 1980; Hughes and Gam-
mon 1987) incorporates two abundance and two diver-
sity estimates in approximately equal fashion, thereby
representing fish assemblage quality more realistically
than a single diversity or abundance measure. The
IWB is calculated as
IWB=0.5.1n N + 0.5 In B+H'N+H'B
where N equals the number of individuals caught per
kilometer, B equals the biomass of individuals caught
per kilometer, and H' is the Shannon diversity index.
Ohio EPA and J.R. Gammon (Gammon 1989) found
that subtracting highly tolerant species from the num-
ber and biomass variables increases sensitivity of the
index in degraded environments (Ohio EPA 1987b).
If the size of a particular fish population (e.g.,
trout or bass species) is of concern, it can be esti-
mated with known confidence limits by several
methods. One of the most popular approaches is the
removal method (Seber and LeCren 1967; Seber and
Whale 1970, Seber 1982). This approach assumes a
closed population, equal probability of capture for all
fish, and a constant probability of capture from sam-
ple to sample (equal sampling effort and conditions).
The removal method is applicable to situations in
which the total catch is large relative to the total
population. If subsequent samples produce equal or
greater numbers than previous samples, the population
must be resampled. Population size in the two sample
cases is estimated by
N = C,2/(C,-C2)
where C, and C2 are the number of fish captured in
7-11
-------
the first and second samples, respectively.
In the three sample cases, population size is estimated
by
J/2
N =
6X2 - 3XY - Y? 4- Y(Y2 + 6XY - 3X?)
18(X-Y)
where X=2C,+C2, and Y = C,+C2 + C3.
Many methods are available to calculate population
statistics from removal data including regression, max-
imum likelihood, and maximum weighted-likelihood.
Public-domain software is available to assist in cal-
culating these and other fisheries population statistics
(Van Deventer and Platts 1989).
7.2.2.1 Description of BBI Metrics
The IBI serves as an integrated analysis because
individual metrics may differ in their relative sensitiv-
ity to various levels of biological condition. A
description and brief rationale for each of the 12 IBI
metrics is outlined below. The original metrics
described by Karr (1981) for Illinois streams (under-
lined) are followed by substitutes used in or proposed
for different geographic regions and stream sizes.
Because of zoogeographic differences, different fami-
lies or species are evaluated in different regions, with
regional substitutes occupying the same general habitat
or niche. The source for each substitute is footnoted
below. Table 7.2-1' presents an overview of the IBI
metric variations for six areas of the United States
and Canada and their sources. Scoring criteria for the
12 original IBI metrics (Karr 1986) are included in
Figure 7.2-1 as an example of the assessment approach
for evaluating fish community condition.
Species Richness and Composition Metrics
These metrics assess the species richness compo-
nent of diversity and the health of the major taxo-
nomic groups and habitat guilds of fishes. Two of the
metrics assess community composition in terms of
tolerant or intolerant species. Scoring for the first five
of these metrics and their substitutes, requires
development of species-waterbody size relationships
for different zoogeographic regions. Development of
this relationship requires data sufficient to plot the
number of species collected from regional reference
sites of various stream sizes against a measure of
stream size (watershed area, stream order) of those
sites. A line is then drawn with slope fit by eye to
include 95 percent of the points. Finally the area
under the line is trisected into areas that are scored as
5, 3, or 1 (Figure 7.2-4). A detailed description of
these methods can be found in Fausch et al. (1984),
Ohio EPA (1987b), and Karr et al (1986).
Metric 1. Total number of fish species(l,4,5). Sub-
stitutes: Total number of native fish spe-
cies(2,8), and salmonid age classes(6)
This number decreases with increased
degradation; hybrids and introduced spe-
cies are not included. In coldwater streams
supporting few fish species, the age classes
of the species found represent the suitabil-
ity of the system for spawning and rearing.
The number of species is strongly affected
by stream size at small stream sites, but
not at large river sites (Karr et al. 1986;
Ohio EPA 1987b). Thus, scoring depends
on developing species/waterbody size
relationships.
Metric 2. Number and identity of darter spe-
cies(l). Substitutes: Number and identity
of sculpin species(2,4), benthic insectivore
species(3,4), salmonid yearlings
(individuals)(6); number of sculpins
(individuals)(4); percent round-bodied
suckers(S), sculpin and darter species(8)
These species are sensitive to degrada-
tion resulting from siltation and benthic
oxygen depletion because they feed and
reproduce in benthic habitats (Kuehne and
Barbour 1983; Ohio EPA 1987b). Many
smaller species live within the rubble
interstices, are weak swimmers, and spend
their entire lives in an area of 100-400 m^
(Hill and Grossman 1987; Matthews 1986).
Darters are appropriate in most Mississippi
Basin streams; sculpins and yearling trout
occupy the same niche in western streams.
Benthic insectivores and sculpins or darters
are used in small Atlantic slope streams
that have few sculpins or darters, and
round-bodied suckers are suitable in large
midwestern rivers. Scoring requires
development of species/waterbody size
relationships.
Metric 3. Number and identity of sunfish spe-
cies(l). Substitutes: Number and identity
of cyprinid species(2,4), water column spe-
cies(3,4), salmonid species(4), headwater
species(S), and sunfish and trout species(8)
These pool species decrease with
increased degradation of pools and
instream cover (Gammon et al. 1981;
Angermeier 1983; Platts et al. 1983). Most
of these fishes feed on drifting and surface
invertebrates and are active swimmers. The
sunfishes and salmor.ids are important
sport species. The sunfish metric works
7-12
-------
TABLE 7.2-1 REGIONAL VARIATIONS OF IBI METRICS(a)
New Central Colorado Western Sacramento-
Variations in IBI Metrics Midwest England Ontario Appalachia Front Range Oregon San Joaquin
1. Total Number of Species XX XX X
# native fish species ,, ,. X X
# salmonid age classes XX
2. Number of Darter Species X XX
# sculpin species X
# benthic insectivore species X
# darter and sculpin species (.^ X
# salmonid yearlings (individuals) XX
% round-bodied suckers X
# sculpins (individuals) X
3. Number of Sunfish Species X X
# cyprinid species X
# water column species X
ft sunfish and trout species X
# salmonid species X
# headwater species X
4. Number of Sucker Species XX X
# adult trout species^ ' X X
# minnow species X X
ft sucker and catfish species X
(a) Taken from Karr et al. (1986), Hughes and Gammon (1987), Miller et al. (1988a), Miller et al. (1988b In
Review), Ohio EPA (1987b), Steedman (1988).
(b) Metric suggested by Moyle or Hughes as a provisional replacement metric in small western salmonid streams.
(c) An optional metric found to be valuable by Hughes and Gammon (1987).
Note: X = metric used in region. Many of these variations are applicable elsewhere.
-------
TABLE 7.2-1 (Cont.)
Variations in IBI Metrics
New Central Colorado Western Sacramento-
Midvest England Ontario Appalachia Front Range Oregon San Joaquin
5. Number of Intolerant Species
tt sensitive species
tt amphibian species
presence of J)rook trout
6. % Green Sunfish
% common carp
% white sucker
% tolerant species
% creek chub
% dace species
7. % Omnivores
% yearling salmonids1
8. % Insectivorous Cyprinids
,(b)
% insectivores
% specialized insectivores
# juvenile trout
% insectivorous species
9. % Top Carnivores
% catchable salmonids
% catchable wild trout
% pioneering species
Density catchable wild trout
X
X
X X
X X
X
X
-------
TABLE 7.2-1 (Cont.)
Variations in IBI Metrics
10. Number of Individuals
Density of individuals
11. % Hybrids
% introduced species
% simple lithophils
# simple lithophilic species
% native species
% native wild individuals
12. % Diseased Individuals
13. Total Fish Biomass
New Central Colorado Western Sacramento-
Midwest England Ontario Appalachia Front Range Oregon San Joaquin
X
X
X
X
X
X
X
X
-------
40
%
-------
for most Mississippi Basin streams, but
where sunfish are absent or rare, other
groups are used. Cyprinid species are used
in cool water western streams; water
column species occupy the same niche in
northeastern streams; salmonids are suit-
able in coldwater streams; headwater spe-
cies serve for midwestern headwater
streams and trout and sunfish species are
used in southern Ontario streams. Karr
et al. (1986) and Ohio EPA (1987b) found
the number of sunfish species to be depen-
dent on stream size in small streams, but
Ohio EPA (1987b) found no relationship
between stream size and sunfish species in
medium to large streams, nor between
stream size and headwater species in small
streams. Scoring of this metric requires
development of species/waterbody size
relationships.
Metric 4. Number and identity of sucker spe-
cies(l). Substitutes: Number of adult trout
species(6), number of minnow species(5);
and number of suckers and catfish(S)
These species are sensitive to physical
and chemical habitat degradation and com-
monly comprise most of the fish biomass
in streams. All but the minnows are long-
lived species and provide a multiyear
integration of physicochemical conditions.
Suckers are common in medium and large
streams; minnows dominate small streams
in the Mississippi Basin; and trout occupy
the same niche in coldwater streams. The
richness of these species is a function of
stream size in small and medium sized
streams, but not in large rivers. Scoring of
this metric requires development of spe-
cies/waterbody size relationships.
Metric 5. Number and identity of intolerant spe-
cies(l). Substitutes: Number and identity
of sensitive species(S), amphibian spe-
cies(4); and presence of brook trout(8)
This metric distinguishes high and
moderate quality sites using species that
are intolerant of various chemical and
physical perturbations. Intolerant species
are typically the first species to disappear
following a disturbance. Species classified
as intolerant or sensitive should only rep-
resent the 5-10 percent most susceptible
species, otherwise this becomes a less dis-
criminating metric. Candidate species are
determined by examining regional ichthyo-
logical books for species that were once
widespread but have become restricted to
only the highest quality streams. Ohio EPA
(1987b) uses number of sensitive species
(which includes highly intolerant and
moderately intolerant species) for head-
water sites because highly intolerant spe-
cies are generally not expected in such
habitats. Moyle (1976) suggested using
amphibians in northern California streams
because of their sensitivity to silvicultural
impacts. This also may be a promising
metric in Appalachian streams which may
naturally support few fish species. Steed-
man (1988) found that the presence of
brook trout had the greatest correlation
with IBI score in Ontario streams. The
number of sensitive and intolerant species
increases with stream size in small and
medium sized streams but is unaffected by
size of large rivers. Scoring of this metric
requires development of species/waterbody
size relationships.
Metric 6. Proportion of individuals as green sun-
fish (1). Substitutes: Proportion of
individuals as common carp(2,4), white
sucker(3,4), tolerant species(5), creek
chub(7), and dace(8)
This metric is the reverse of Metric 5. It distin-
guishes low from moderate quality waters. These spe-
cies show increased distribution or abundance despite
the historical degradation of surface waters, and they
shift from incidental to dominant in disturbed sites.
Green sunfish are appropriate in small Midwestern
streams; creek chubs were suggested for central
Appalachian streams; common carp were suitable for
a coolwater Oregon river; white suckers were selected
in the northeast and Colorado where green sunfish are
rare to absent; and dace (Rhinichthys species) were
used in southern Ontario. To avoid weighting the met-
ric on a single species, Karr et al. (1986) and Ohio
EPA (1987b) suggest using a small number of highly
tolerant species. Scoring of this metric may require
development of expectations based on waterbody size.
Trophic Composition Metrics
These three metrics assess the quality of the
energy base and trophic dynamics of the community.
Traditional process studies, such as community
production and respiration, are time consuming to
conduct and the results are equivocal; distinctly differ-
ent situations can yield similar results. The trophic
7-17
-------
composition metrics offer a means to evaluate the shift
toward more generalized foraging that typically occurs
with increased degradation of the physicochemical
habitat.
Metric 7. Proportion of individuals as omni-
vores(l,2,3,4,5,8). Substitutes: Proportion
of individuals as yearlings(4)
The percent of omnivores in the com-
munity increases as the physical and chem-
ical habitat deteriorates. Omnivores are
defined as species that consistently feed on
substantial proportions of plant and animal
material. Ohio EPA (1987b) excludes sensi-
tive filter feeding species such as paddle-
fish and lamprey ammocoetes and
opportunistic feeders like channel catfish.
Where omnivorous species are nonexistent,
such as in trout streams, the proportion of
the community composed of yearlings,
which initially feed omnivorously, may be
substituted.
Metric 8. Proportion of individuals as insec-
tivorous cyprinids(l). Substitutes: Propor-
tion of individuals as insectivores (2,3,5),
specialized insectivores(4), and insec-
tivorous species(S); and number of juvenile
trout(4)
Insectivores or invertivores are the
dominant trophic guild of most North
American surface waters. As the inver-
tebrate food source decreases in abundance
and diversity due to physicochemical habi-
tat deterioration, there is a shift from
insectivorous to omnivorous fish species.
Generalized insectivores and opportunistic
species, such as blacknose dace and creek
chub were excluded from this metric by
Ohio EPA (1987b). This metric evaluates
the midrange of biotic integrity.
Metric 9. Proportion of individuals as top carni-
vores(l,3,8). Substitutes: Proportion of
individuals as catchable salmonids(2),
catchable wild trout(4), and pioneering
species(5)
The top carnivore metric discriminates
between systems with high and moderate
integrity. Top carnivores are species that
feed as adults predominantly on fish, other
vertebrates, or crayfish. Occasional pisci-
vores, such as creek chub and channel cat-
fish, are not included. In trout streams,
where true pisctvores are uncommon, the
percent of large salmonids is substituted
for percent piscivores. These species often
represent popular sport fish such as bass,
pike, walleye, and trout. Pioneering spe-
cies are used by Ohio EPA (1987b) in
headwater streams typically lacking
piscivores.
Fish Abundance and Condition Metrics
The last three metrics indirectly evaluate popula-
tion recruitment, mortality, condition, and abundance.
Typically, these parameters vary continuously and are
time consuming to estimate accurately. Instead of such
direct estimates, the final results of the population
parameters are evaluated. Indirect estimation is less
variable and much more rapidly determined.
Metric 10. Number of individuals in sam-
ple(l,2,4,5,8). Substitutes: Density of
individuals(3,4)
This metric evaluates population abun-
dance and varies with region and stream
size for small streams. It is expressed as
catch per unit effort, either by area, dis-
tance, or time sampled. Generally sites
with lower integrity support fewer
individuals, but in some nutrient poor
regions, enrichment increases the number
of individuals. Steedman (1988) addressed
this situation by scoring catch per minute
of sampling greater than 25 as a three, and
less than 4 as a one. Unusually low num-
bers generally indicate toxicity, making this
metric most useful at the low end of the
biological integrity scale. Hughes and
Gammon (1987) suggest that in larger
streams, where sizes of fish may vary in
orders of magnitude, total fish biomass
may be an appropriate substitute or addi-
tional metric.
Metric 11. Proportion of individuals as hybrids(l).
Substitutes: Proportion of individuals as
introduced species(2,4), simple litho-
phils(5); and number of simple lithophilic
species(5)
This metric is an estimate of reproduc-
tive isolation or the suitability of the habi-
tat for reproduction. Generally as
environmental degradation increases, the
percent of hybrids and introduced species
also increases, but the proportion of simple
lithophils decreases. However, minnow
hybrids are found in some high quality
streams, hybrids are often absent from
7-18
-------
highly impacted sites, and hybridization is
rare and difficult for many to detect. Thus,
Ohio EPA (1987b) substitutes simple
lithophils for hybrids. Simple lithophils
spawn where their eggs can develop in the
interstices of sand, gravel, and cobble sub-
strates without parental care. Hughes and
Gammon (1987) and Miller et al. (1988a)
propose using percent introduced indi-
viduals. This metric is a direct measure of
the loss of species segregation between
midwestern and western fishes that existed
before the introduction of midwestern spe-
cies to western rivers.
Metric 12. Proportion of individuals with disease,
tumors, fin damage, and skeletal
anomalies(l).
This metric depicts the health and con-
dition of individual fish. These conditions
occur infrequently or are absent from
minimally impacted reference sites but
occur frequently below point sources and
in areas where toxic chemicals are concen-
trated. They are excellent measures of the
subacute effects of chemical pollution and
the aesthetic value of game and nongame
fish.
Metric 13. Total fish biomass (optional).
Hughes and Gammon (1987) suggest
that in larger areas where sizes of fish may
vary in orders of magnitude this additional
metric may be appropriate.
Because the IBI is an adaptable index, the choice
of metrics and scoring criteria is best developed on a
regional basis through use of available publications
(Karr et al. 1986; Ohio EPA 1987b; Miller et al.
1988a). Several steps are common to all regions. The
fish species must be listed and assigned to trophic and
tolerance guilds. Scoring criteria are developed
through use of high quality historical data and data
from minimally-impacted regional reference sites. This
has been done for much of the country, but continued
refinements are expected as more fish community
ecology data become available. Once scoring criteria
have been established, a fish sample is evaluated
by listing the species and their abundances
(Figure 7.2-3), calculating values for each metric, and
comparing these values with the scoring criteria.
Individual metric scores are added to calculate the
total IBI score (Figure 7.2-5). Hughes and Gammon
(1987) and Miller et al. (1988a) suggest that scores
lying at the extremes of scoring criteria can be modi-
fied by a plus or minus; a combination of three pluses
or three minuses results in a two point increase or
Station No.
Site
Scoring Criteria(b)
1.
2.
3.
4.
5.
(,.
1.
8.
9.
10.
11.
12.
Hetrics(a)
Nuaber of Native Pish Species
Nuaber of Darter or Benthic Species
NuBber of Sunfish or Pool Species
NuBber of Sucker or Long-Lived Species
Nunber of Intolerant Species
X Green Sunfish or Tolerant Individuals
X Omnivores
X Insectivores or Invertivores
X Top Carnivores
Total Nunber of Individuals
X Hybrids or Exotics
X Anomalies
5
m
>67
>67
>67
>67
>67
<10
<20
>45
>5
>67
0
<1
3
~rcr
33-67
33-67
33-67
33-67
33-67
10-25
20-45
20-45
1-5
33-67
0-1
1-5
1
<33
<33
<33
<33
<33
>25
>45
<20
<1
<33
>1
>5
Scorer
GOBI
ents:
Hetric Value Metric Score
IBI Score
(a)
(b)
Karr's original netrics or commonly used substitutes. See text
ties.
Karr's original scoring criteria or commonly
ecoregions.
used
substitutes.
and Table
These may
7.2-1 for other possibili-
require refinement in other
Figure 7.2-5. Data Summary Sheet for Rapid Bioassessment Protocol V.
7-19
-------
decrease in IBI. Ohio EPA (1987b) scores proportional
metrics as 1 when the number of species and
individuals in samples are fewer than 6 and 75,
respectively, when their expectations are of higher
numbers.
7.3 RESULTS OF PILOT STUDIES
IN OHIO AND OREGON
Surveys of 109 regional reference sites in five Ohio
ecoregions and of 26 sites on the mainstem Willamette
River, Oregon, were conducted during the summers of
1983 and 1984. The Ohio survey was a cooperative
project between Ohio EPA, EPA Region V, and EPA's
Environmental Research Laboratory at Corvallis
(ERL-C); the Willamette survey was a cooperative
project between DePauw University, EPA-Region X,
Oregon Department of Environmental Quality, U.S.
Fish and Wildlife Service, and ERL-C. The objectives
of the Ohio survey were to evaluate the correspon-
dence between ecoregions and stream ecosystem
attributes and to assess regional patterns in attainable
water resource quality. The Willamette study was
intended to measure the effects of water resource qual-
ity on the fish community and to examine the useful-
ness of the IBI and IWB in a large western river. The
results of these two surveys have been published else-
where (Larsen et al. 1986; Hughes and Gammon
1987; Ohio EPA 1987b; Whittier et al. 1987; Larsen et
al. 1988) and only the fisheries aspects will be sum-
marized here.
7.3.1 Methods
Ohio
Minimally-impacted regional reference sites were
selected based on: census and point-source data; maps
of population density, land use, and mining; and aerial
and ground inspection of the watershed and site (Fig-
ure 7.3-1).
Ohio EPA collected fish at half the sites two to
three times at 1 month intervals each summer (1983
and 1984). Rivers were sampled via boat-mounted
electrofishers for 500 meters, headwaters were sam-
pled with backpack electrofishers for 200 meters,
most streams were sampled with a towed electrofisher
for 300 meters. All captured fish were identified to
species, counted, and examined for disease; a subsam-
ple was weighed at the site. The data were analyzed
through use of the IBI, IWB, and identification of
regionally characteristic species.
...*.. Regional Reference Sampling Site
SSSB Most Typical Areas
I Huron/Erie Lake Plain (HELP)
II Eastern Corn Belt Plains (ECBP)
"I Erie/Ontario Lake Plain (EOLP)
IV Interior Plateau (IP)
V Western Allegheny Plateau (WAP)
Figure 7.3-1. Locations of regional reference sites in Ohio
(from Whittier et al. 1987).
Willamette River
Sites were selected along one side of the river
about 2 yd offshore to bracket large point sources and
to space sites approximately 16 km apart (Figure
7.3-2). Each site was 500 meters long and included
slow, deep water; shallow, fast, water; and cover.
Each site was sampled twice in the summer of
1983 with a boat-mounted electrofisher. All fish were
identified to species, counted, and examined for
anomalies, and a subsample was weighed. Data were
analyzed through use of IBI, IWB, and DCA.
7.3.2 Results and Interpretation
The tolerance and trophic guilds, and origin of
selected species are given in Appendix D. For the
sake of brevity, IBI and IWB calculations are
presented for four selected sites only.
7-20
-------
t
N
Table 7.3-1
OREGON
AQUATIC ECOREGION'S
WILLAMETTE VALLEY
CASCADES
COAST RANGE
Figure 7.3-2. Locations of sampling sites on the mainstem
Willamette River, Oregon (taken from Hughes
and Gammon 1987).
Ohio
The unmodified IBI metrics and criteria (Karr
et al. 1986) were used to analyze the Ohio data. Spe-
cies richness metrics were determined as suggested by
Karr et al. 1986 (Figure 7.2-4). Sample data, scoring
criteria, and scores are given in Tables 7.3-1 and 7.3-2
for a site in the Huron Erie Lake Plain (HELP) and
Western Allegheny Plateau (WAP) ecoregions. The
COLLECTION DATA FOR TWO
OHIO ECOREGION REFERENCE
SITES
Site
Species
Grass pickerel
White sucker
Black redhorse
Golden redhorse
Northern hogsucker
Common carp
Blacknose dace
Creek chub
Golden shiner
Redfin shiner
Silver shiner
Rosyface shiner
Striped shiner
Sand shiner
Mimic shiner
Silverjaw shiner
Bluntnose minnow
Fathead minnow
Central stoneroller
Yellow bullhead
Black bullhead
Tadpole madtorn
Brindled madtom
Blackstripe topminnow
White crappie
Green sunfish
Bluegill
Rock bass
Longear sunfish
Smallmouth bass
Largemouth bass
Orangespotted sunfish
Blackside darter
Logperch
Johnny darter
Greenside darter
Banded darter
Rainbow darter
Fantail darter
WAP
21
2
24
26
3
94
6
41
443
264
1
93
101
559
16
3
11
3
3
40
56
25
60
113
HELP
19
24
26
2
42
22
8
3
23
13
2
66
6
156
1
2
2
fish communities of the Ohio regional reference sites
showed distinct ecoregional differences between the
Western Allegheny Plateau and the Huron Erie Lake
Plain ecoregions. Differences among the three transi-
tional ecoregions were less obvious. This was true
whether examining patterns in IBI scores (Fig-
ure 7.3-3) or dominant species (Figure 7.3-4).
7-21
-------
TABLE 7.3-2
SCORING CRITERIA AND IBI AND IWB SCORES
FOR TWO OHIO ECOREGION REFERENCE SITES
Metric (Criteria)
Value(Score)
WAP
Total Number of Species (<9=1, 9-18=3, >18=5)
Number of Darter Species (<2=1, 2-5=3, >5=5)
Number of Sunfish Species (<2=1, 2-4=3, >4=5)
Number of Sucker Species (<2=1, 2-4=3, >4=5)
Number of Intolerant Species (<4=1, 4-8=3, >8-5)
% Green Sunfish (>20=1, 5-20=3, <5=5)
% Omnivores (>45=1, 20-45=3, <20=5)
% Insectivorous Minnows (<20=1, 20-45=3, >45=5)
% Top Carnivores (<1=1, 1-5=3, >5=5)
Number of Individuals (<200=1, 200-800=3, >800=5)
% Hybrids (>1=1, 0-1=3, 0=5)
% Diseased (>5=1, 2-5=3, <2=5)
Total IBI Score
IWB Score
Integrity
25(5)
7(5)
2(3)
4(3)
8(3)
0(5)
5(5)
42(3)
1(3)
2,012(5)
0(5)
1(5)
50
10
Good
HELP
17(3)
0(1)
4(3)
1(1)
0(1)
37(1)
9(5)
15(1)
5(3)
417(3)
0(5)
4(3)
30
Poor
UJ
cc
O
o
CO
5
r
•o
§
50-
46-
F •
•£42-
38-
34-
o
o
a
L30
HELP ECBP EOLP IP
'ECOREGION
WAP
Figure 7.3-3. Index of biotic integrity scores by Ohio ecoregion (from Whittier et al. 1987).
Vertical lines represent ranges; horizontal lines represent 10th, 25th, 75th, and
90th percentiles; open circles are medians.
7-22
-------
1 bluntnose minnow
2 creek chub
3 green sunf ish
4 blackstripetopminnow
5 fathead minnow
6 yellow bullhead
7 johnny darter
8 white sucker
9 rockbass
10 rosefin shiner
11 greenside darter
12 bluegill
13 mottled sculpin
14 common shiner
15 rainbow darter
16 fantail darter
17 spotfin shiner
18 longear sunf ish
19 sand shiner
20 golden redhorse
21 emerald shiner
22 central stoneroller
23 striped shiner
100
c
ro
i 60
20
llllll
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 1819 20 21 22 23
fish species
Huron/Erie Lake Plain
80
0)
w
C
2 60
V
0
g 40
V
fll
a
20
Im
1
ill ll
80
a>
c
3 60
O
v 1°
W
a>
Q.
20
1
I 1
III i i ill i Illlll II
1 23 456 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
fish species
Eastern Corn Belt Plains
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 1819 20 21 22 23
fish species
Erie/Ontario Lake Plain
80
-------
Willamette River
Five of the original 12 metrics that Karr et al.
(1986) found appropriate for midwestern streams were
inappropriate for a large western river. These five
metrics were modified by making the following substi-
tutions: (1) The number of sculpin species replaced
the number of darter species as suggested by Karr et
al. (1986); (2) The number of native minnow species
replaced the number of sunfish species. In cool and
warmwater western streams, the introduced sunfish
increase and native minnows decline when habitat
structure deteriorates (Minckley 1973; Moyle 1976);
(3) Percent common carp replaced percent green sun-
fish. No green sunfish were collected in the Wil-
lamette, the other relatively tolerant species were
either rarely captured or dominant, and common carp
increased as the physicochemical habitat deteriorated;
(4) Percent catchable salmonids (longer than 20 cm)
replaced percent piscivores. The dominant piscivore in
the Willamette is a relatively tolerant species and is
not indicative of integrity; most Willamette salmonids
(juvenile whitefish and anadromous salmon) are not
piscivorous in freshwater rivers; and (5) Percent
introduced individuals replaced percent hybrids.
Hybrids are too rare in the Willamette to make this a
useful metric for discriminating degradation. Percent
introduced individuals do increase with degradation
(Moyle and Nichols 1973; Holden and. Stalnaker 1975;
Leidy and Fiedler. 1985) and represent a loss of the
segregation existing before midwestern species were
brought to western waters.
Scoring criteria were based on the Willamette data
due to the lack of sufficient quantitative historical
data; no adjustments were required for stream size
because it changed little. Criteria were based on
characteristics of the fish assemblages at the
minimally impacted sites of the upper mainstem
(Table 7.3-3). Like the metrics, criteria were adjusted
in the following ways to reflect western conditions
(Table 7.3-4): (1) Criteria for common carp were
reduced because carp are much less common in
Oregon than the green sunfish is in the Midwest;
(2) Omnivore criteria were increased because a domi-
nant species (largescale sucker) is an omnivore;
(3) The catchable salmonids criteria were increased
because salmonids are more common than midwestern
piscivores; (4) Percent introduced individuals had
TABLE 7.3-3 COLLECTION DATA (NUMBER OF INDIVIDUALS) FOR TWO SITES ON THE
WILLAMETTE RIVER, OREGON
River
Kilometer
Species
Mountain whitefish
Chinook salmon
Longnose dace
Speckled dace
Northern squawfish
Common carp
Largescale sucker
Mountain sucker
Largemouth bass
Yellow perch
Prickly sculpin
Reticulate sculpin
Torrent sculpin
Paiute sculpin
270
25
4
1
3
2
44
6
2
3
5
31
2
7
10
2
1
1
7-24
-------
TABLE 7.3-4 SCORING CRITERIA AND IBI AND IWB SCORES FOR
TWO SITES ON THE WILLAMETTE RIVER, OREGON
Metric (Criteria)
Number of Native Species (<5=1, 5-9=3, >9=5)
Number of Sculpin Species (<2=1, 2=3, >2=5)
Number of Native Minnow Species (<3=1, 3-5=3, >5=5)
Number of Sucker Species (0=1, 1=3, >1=5)
Number of Intolerant Species (0=1, 1-2=3, >2=5)
% Common Carp (>9%=1, l-9%=3, 50%=1, 25-502=3, <25%=5)
% Insectivores (<20%=1, 20-40%=3, >40%=5)
% Catchable Salmonids (0%=1, l-9%=3, >9%=5)
Number of Individuals/km (<50=1, 50-99=3, >99=5)
% Introduced (>9X=1, l-9%=3, <1%=5)
% Anomalies (>5%=1, 2-5%=3, <2%=5)
Total IBI Score
IWB Score
Integrity
Value(Score)
River Kilometer
270
31
higher criteria than expected for percent hybrids; and
(5) Percent anomalies criteria were higher because,
where they occurred, they were above the 1 percent
maximum as referenced in Karr et al. (1986).
A detrended correspondence analysis (DCA)
showed four distinct clusters among the 26 sites cor-
responding to upper river, middle river, Newberg
pool, and Portland metropolitan fish assemblages
(Figure 7.3-5). These differences and the longitudinal
4(1)
1(1)
KD
1(3)
1(3)
28(1)
68(1)
16(1)
0(1)
25(1)
40(1)
8(1)
16
4.7
Very Poor
trends shown by the IBI (Figure 7.3-6) corresponded
to declining physical and chemical habitat quality and
increased nonpoint-source pollution.
(l)Karr et al. (1986); (2)Hughes and Gammon (1987); (3)Miller et
al., (1988b In Review); (4)Miller et al. (1988a); (5)Ohio EPA
(1987b); (6)Metric suggested by Moyle or Hughes as a provisional
replacement metric in small western salmonid streams; (7)Leonard
and Orth (1986); (8) Steedman (1988).
Upper
River
Portlond
Metro
180-
160-
140
120-
c^ 100
c/»
•5 80-
60-
40-
20
20 40 60 80 100 120 140 16O 18O 200 220 240 280
Axis 1
Figure 7.3-5. Patterns in mainstem Willamette River fish assemblages as revealed by
detrended correspondence analysis (taken from Hughes and Gammon 1987).
Middle
River
7-25
-------
60
50
40
= 30
20
10
IBI
NO.3 x 100
300
200
100
River Kilometer
Figure 7.3-6. Longitudinal trends in Index of Biotic Integrity and nitrate in the
Willamette River (modified from Hughes and Gammon) 1987.
7-26
-------
8. INTEGRATION OF HABITAT,
WATER QUALITY, AND BIOSURVEY DATA
The overall assessment of ecological condition first
focuses on the evaluation of habitat quality, then ana-
lyzes the biological components of the system in light
of these data. Habitat, as the principal determinant of
biological potential, sets the context for interpreting
biosurvey results arid can be used as a general predic-
tor of biological condition. Routine water chemistry
can also help to characterize certain impacts.
In Rapid Bioassessment Protocols (RBPs) I and IV,
the habitat evaluation carries considerable weight in
the final'assessment because minimal effort is
expended on the collection and analysis of biological
data. In RBPs II, III, and V, however, the biological
evaluations are more rigorous and appropriately take
precedence. The habitat assessment plays a supporting
role within these protocols. It is used to identify obvi-
ous constraints on the attainable potential of the site,
help in the selection of appropriate sampling stations,
and provide basic information for interpreting biosur-
vey results.
8.1 THE RELATIONSHIP
BETWEEN HABITAT QUALITY
AND BIOLOGICAL CONDITION
The attainable biological potential of a site is
primarily determined by the quality of the habitat at
that site. The relationship between habitat quality and
biological condition can be envisioned as a sigmoid
curve (Figure 8.1-1) with community response varying
with habitat quality. In the upper segment of the
curve, good quality habitat (supporting or excellent)
will support high quality communities, and responses
to minor alterations in habitat will be only subtle and
of little consequence. As habitat quality continues to
decline, however, discernible biological impairment
results, and, in the absence of confounding water
quality effects, the relationship is roughly linear.
100
90 100
Habitat Quality (% of Reference)
Figure 8.1-1. The relationship between habitat and biological condition.
8-1
-------
In areas of severe habitat degradation, predicting
the degree of biological impairment becomes more
difficult. Community structure is less dependent on
habitat diversity, which is effectively simplified by
degradation, and more dependent on the opportunistic
colonization strategies of a relatively few tolerant spe-
cies. These opportunists are adapted to environmental
conditions that are unfavorable to most other species
and, in the absence of competition, thrive (or at least
survive) in these marginal conditions. Therefore, bio-
logical measures, particularly those used in the RBPs,
are relatively insensitive to habitat variations in this
range, and a nonsupporting characterization may cor-
respond to either a moderately or severely impaired
biological condition, depending on the specific site.
When habitat and biological data are systematically
collected together, empirical relationships can be
quantified and subsequently used for screening impact
sites, scoping field activities, and discriminating water
quality impacts from habitat degradation. With the
acquisition of a multiple-site database, confidence
bounds can be established for the habitat/indigenous
community relationship.
A theoretical relationship of habitat quality and
biological condition as affected by water quality prob-
lems (organic or toxicant loadings) also can be
hypothesized (Figure 8.1-2). Curve II in Figure 8.1-2
indicates the general relationship of biological condi-
tion to habitat quality in the absence of water quality
effects. Curve II may, in fact, resemble a sigmoid
curve as illustrated by Figure 8.1-1. Curve III repre-
sents a situation where organic pollution or toxicants
will adversely affect biological condition regardless of
the quality of the habitat.
In areas of good or excellent habitat, biological
communities will reflect degraded conditions when
water quality effects are present. However, as habitat
degrades to a poor condition in the presence of water
quality problems, response of the communities may be
less dramatic because the community is composed of
tolerant and generally opportunistic species. Curve I is
representative of a situation indicative of nutrient
enrichment, which will artificially sustain a more
diverse fauna than dictated by the habitat quality.
However, at some point along the curve as habitat
degradation proceeds, nutrient enrichment will no
longer support a diverse community, and a drastic
decrease in biological condition will result.
o>
o
o
o
O
75
o
w
o
o
3
Habitat Quality
Decreasing
Figure 8.1-2. Relationship of habitat quality and biological condition in the context of water quality.
8-2
-------
8.2 BIOASSESSMENT
TECHNIQUE
As described in Chapters 6 and 7, the biological
assessment involves an integrated analysis of both
functional and structural components of the aquatic
communities. These functional and structural compo-
nents are evaluated through the use of eight metrics
for benthic RBPs H and III and 12 metrics for fish
RBP V. The range of pollution sensitivity exhibited by
each metric differs among metrics (Figures 8.2-1 and
8.2-2); some are sensitive across a broad range of bio-
logical conditions, others only to part of the range.
Sensitivity of metrics may also vary depending on
whether organic or toxicant impacts are being evalu-
ated (Figure 8.2-1). The considerable overlap in the
ranges of sensitivity helps reinforce final conclusions
regarding biological condition, while metrics that are
better able to differentiate responses at the extremes
of the range of impairment enable a more complete
bioassessment. The integrated analysis approach thus
allows a broader assessment of condition than an anal-
ysis using any single metric. However, information
from individual metrics will be useful in enhancing
overall data interpretation.
Certain metrics are designed to be better estima-
tors of either organic or toxicant effects. For instance
in the benthic protocols, the Hilsenhoff Biotic Index
(HBI) utilizes a tolerance classification scheme that is
based on organic pollution effects, while Functional
Group representation can be altered by either organics
or toxicants (Figure 8.2-1). Although Scrapers and •
Filterers are affected by toxicants to a certain extent,
their ratio can best be used to assess'organic enrich-
ment (Cummins 1987, personal communication). As
discussed in Chapter 6, a reduction in the value
Organics
Metrics
Taxa Richness
HBI
FFG* Scrapers/Filterers
EPT Abund./Chiron.Abund.
% Contribution (dom.taxon)
EPT
Communily Similarity Index
£ [ FFG •» Shredders/Total
o
Biological Condition
Non-
Impaired
Severely
Impaired
I 1
—I
Toxicants
Metrics
Taxa Richness
HBI
FFG* Scrapers/Filterers
EPT Abund./Chiron.Abund.
% Contribution (dom.taxon)
EPT
Community Similarity Index
[ FFG •» Shredders/Total
Biological Condition
Non-
Impaired
Severely
Impaired
Figure 8.2-1. Range of sensitivities of Rapid Bioassessment Protocol II and III benthic metrics
in assessing biological condition in response to organics and toxicants.
8-3
-------
obtained for Scrapers/Filterers can be indicative of
either a reduction in the quality of the periphyton as a
food source and/or an increase in the suspended
FPOM. Filterers are also affected by FPOM contami-
nated by toxicants.
The relative abundance of Shredders in the benthic
community is a good indicator of toxicant problems
because of the sensitivity of the Shredder community
to toxic conditions (Cummins 1987, personal commu-
nication). Vegetation sprayed with pesticides eventually
becomes a CPOM food source for Shredders. In suffi-
cient concentrations, toxicants bound to CPOM may
affect Shredders directly through ingestion, as well as
indirectly by killing attached microbes that serve as a
nutrition base for Shredders. The ratio of the abun-
dances of EPT taxa and chironomids may also func-
tion as a toxicant indicator, since some midge species
such as Cricotopus sp. become abundant in areas
affected by metals (Winner et al. 1980; Mount et al.
1986).
The 12 IBI metrics used in fish Protocol V also
represent differing sensitivities (Figure 8.2-2). For
example, municipal effluents typically affect total
abundance and trophic structure (Karr et al. 1986),
while unusually low total abundance generally indi-
cates a toxicant effect. However, some nutrient-
deficient environments support a limited number of
individuals, and an increase in abundance may indi-
cate organic enrichment. Bottom dwelling species
(e.g., darters, sculpins) that depend upon benthic
habitats for feeding and reproduction are particularly
sensitive to the effects of siltation and benthic oxygen
depletion (Kuehne and Harbour 1983; Ohio EPA
1987b) and are good indicators of habitat degradation.
For the benthic and fish biosurveys and habitat
assessment, scores are assigned to each metric or
parameter based on a decision matrix. In the case of
habitat assessment, evaluation of the quality of the
parameter is based on visual observation. The score
assigned to each habitat parameter is a function of a
range of scores and is weighted in terms of its contri-
bution to the total habitat quality. The scores assigned
to the benthic and fish metrics are based on computed
values of the metrics and a station comparison, where
the regional or stream reference station serves as the
highest attainment criterion. Comparison of the total
score computed for the metrics or parameters with
that of the reference station provides a judgment as to
impairment of biological condition.
Effects indicated by the aquatic community need to
be evaluated in the context of habitat quality. A poor
habitat in terms of riparian vegetation, bank stability,
stream substrate, etc., would not be conducive to sup-
porting a well-balanced community structure. The
attainment of a higher quality biological condition
may be prohibited by the constraints of habitat quality.
Biological Condition
Metrics
Species
Darters
Sunfishes
Suckers
Intolerants
% Green Sunfish
% Omnivores
% Insectivorous Cyprinids
% Piscivores
Number
% Hybrids
% Diseased
Non- Severely
Impaired Impaired
u> < » . .I i
Figure 8.'2-2. Range of sensitivities of Rapid Bioassessment Protocol V fish
metrics in assessing biological condition (from Karr et al. 1986).
8-4
-------
8.3 AN INTEGRATED
ASSESSMENT APPROACH
The initial focus of a bioassessment should be on
habitat quality. Based on a regional reference, the hab-
itat at an impacted site may be equal to or less than
the desired quality for that particular system. As dis-
cussed in Section 1.4, if the habitat at the impact site
and reference are equal, then a direct comparison of
biological condition can be made. If the habitat at the
impact site is lower in quality than the reference, the
habitat potential should be evaluated as a first step. A
site-specific control may be more appropriate than a
regional reference for an assessment of an impact site.
Once a determination of the appropriate reference site
type is made, possible outcomes of the bioassessment
are: (1) no biological effects; (2) effects due to habi-
tat degradation; (3) effects due to water quality; or
(4) effects due to a combination of water quality and
habitat degradation. Once habitat problems are identi-
fied, in most cases, separating the cause of impair-
ment from water quality problems is difficult. The
following decision matrix illustrates the approach to
assessing biological effects.
Evaluation of Habitat at a Site-Specific
Control Relative to that at a Regional
Reference (Figure 8.3-1)
Selection of an appropriate station of comparison
for evaluation of biological impact begins with an
evaluation of habitat at the potential control station.
HC+RHA=HR
(II)
HC + RHA
-------
This comparison assumes that a regional reference
database is available for the particular site being stud-
ied. Reference data used for comparison may be
obtained from a single reference site. However, a
reference database derived from numerous sites is
much preferred and strongly recommended.
Scenario I depicts the situation where the habitat
quality at the control station (HC) is equivalent to that
at the regional reference (HR). If the control station
habitat is degraded relative to that at the regional
reference, it becomes necessary to consider the effect
that reversible habitat alterations (RHA) may have on
habitat quality (Scenarios II and III). Reversible habi-
tat alterations are those habitat parameters that can
potentially be altered by remedial action (i.e., bank
stability, bank vegetation, streamside cover, and some-
times embeddedness).
Evaluation of Water Quality Effects
(Figure 8.3-2)
A determination may be made that the habitat
quality at the site-specific control station (C) is
equivalent to that at the reference (R) (Scenario I). In
this case, a biological assessment can be used to
evaluate potential water quality effects at C (Fig-
ure 8.3-2).
(1) If impairment is not detected in a comparison of
biological condition at the site-specific control
station (BC) to biological condition at the refer-
ence (BR), then C should be included in the R
database and either C or R may be used as a
reference for biological assessment at the impact
site (I). The site-specific control would be the
best indicator of a site-specific situation. In addi-
tion, C would be more appropriate for use in
determining water quality effects of point-source
pollutants since it would be located on the same
waterbody (or a nearby waterbody) and would
integrate all other background sources of impair-
ment other than the point source being evaluated.
This allows segregation of effects of a particular
point source. The reference would be more
appropriate in an assessment of nonpoint-source
effects since it is virtually impossible to find a
nearby site-specific control which would not be
impacted by the impact sources being studied. If
R is based on an extensive database, then use of
R as a reference would provide a better estimate
of acceptable variation in a data set. Confidence
intervals could be derived and used to put bounds
on the data from C and/or the impact site (I).
(2) If biological impairment is detected at C relative
to R, the impairment may be attributed to water
quality effects. The use designation at C is proba-
bly appropriate, but R should be used as the bio-
assessment reference because of impairment at C.
Evaluation of Biological Impairment Due
to Reversible Habitat Alterations
(Figure 8.3-3)
If the habitat quality at C is degraded relative to
that at R, but habitat quality could potentially be
improved by reversing those degraded habitat parame-
ters which are reversible (Scenario II), biological
assessment at C will indicate whether C, R, or an
alternative control site (C*) should be used as a
bioassessment reference for the impact site (I)
(Figure 8.3-3).
(3) When BC is equal to BR, the use designation at
C may be considered appropriate, and C should
be used as the bioassessment reference. This is a
potential situation since reversible habitat param-
eters are mainly tertiary characteristics and
should have the least effect on the biological
community. However, in this situation benthic
RBP III or fish RBP V should be utilized as a
minimum. A more rigorous biological analysis
(e.g., quantitative sampling) may be warranted to
ensure that the approach is sufficiently sensitive
to detect impairment.
(4) In situations where BC is less than BR, impair-
ment may be due to either reversible habitat alter-
ations, water quality effects, or a combination of
the two. Selection of a bioassessment reference is
dependent on the purpose of the assessment and
the suspected source of impairment.
(5) If point source effects are being assessed, a habi-
tat independent approach (e.g., toxicological test-
ing, sampling with artificial substrates) may be
warranted, using R as a reference. C could be
considered an impact site.
(6) It may be appropriate to continue the rapid bioas-
sessment (and habitat evaluation) approach using
R as the reference because of impairment at C.
Assuming that impairment at C indicates impair-
ment also at I, the degree of impairment at I can
be assessed relative to C. An a priori knowledge
of potential water quality problems from an exist-
ing database would enhance interpretation of find-
ings in this case.
(7) Another alternative would be to eliminate the
confounding effects of the reversible habitat alter-
ations by selecting another site-specific control
station (C*), which, if possible, would then be
evaluated relative to R (Figure 8.3-1).
8-6
-------
HC = HR
(I)
BC = BR
HC = HR; BC = BR
Include "C" in
"R" database.
(1)
BC
-------
HC + RHA = HR
BC = BR
Use designation
is appropriate.
(3)
Use "C" as
bioassessment
reference.
Continue RBP—
habitat and
biosurvey
approach .
(6)
i
r
« — 1
HC + RHA = Hft
BC < BR
Impairment at "C"
due to revs hab alts
•(-/or WQ effects.
Use habitat
independent
approach
(toxicological.
art. substrates)
(5)
Use "R" as
bioassessment
reference.
Consider "C" as
an impact site.
Use "C" as
control if
habitat quality
is best
attainable
Use ecoregional
database as
bioassessment
reference.
Consider "C" an
impact site.
Evaluate
habitat
at new
control
Figure 8.3-3. Evaluation of biological impairment due to reversible habitat alterations
(RHAs). (Numbers in parentheses refer to points of discussion in text.)
8-8
-------
Evaluation of an Alternative Site-Specific
Control Station (Figure 8.3-4)
If the habitat quality at C is degraded relative to
that at R, and reversible habitat alterations do not
account for all of the habitat differences, then it is
necessary to select an alternative site-specific control
station (C*), if one is available (Figure 8.3-4).
(8) If a more appropriate control is located (where
HC* = HR) then use C* as the reference and pro-
ceed with the bioassessment.
(9) If HC* is also degraded relative to HR, and it
appears that a better quality site-specific control
is not available, then biological condition should
be evaluated at C* relative to R.
(10) Where reversible habitat alterations account for
all differences in habitat quality between C* and
R, then use C* as the reference and proceed with
the bioassessment.
(11) In the unlikely situation where the degraded habi-
tat (reversible and/or irreversible parameters) at
C* is not limiting to biological condition, and
BC* = BR, then either C* or R would be an
appropriate reference.
(12) If biological impairment is detected at C* the
effects may be attributable to either degraded hab-
itat (reversible and/or irreversible parameters)
and/or water quality effects. Three possible alter-
natives should be considered: (a) A Use Attain-
ability Analysis (UAA) is needed to determine the
appropriate use classification of the system. In
this case, the system as represented by C or C* is
aberrant to R. A UAA will be needed to redefine
R* or a subset of R, for interpretation of an
appropriate bioassessment. (b) C* would be used
as a reference for bioassessment because it
represents the best attainable condition for that
system. However, interpretation of effects, would
be in the context of a control that does not meet
the criteria of the region, (c) A prediction of the
expected biological condition can be made from
an extrapolation of the regression line formed
from the reference database and the best potential
habitat quality at C*.
Bioassessment Using a Site-Specific
Control Station (Figure 8.3-5)
Once the decision is made to use a site-specific
control (C or C*) then evaluation of the impact site
relative to C (or C*) proceeds as in Figure 8.3-5. As
indicated in the previous flowcharts, C is used when it
is biologically representative of the region or is con-
sidered to represent the best attainable condition. A
matrix of conclusions from the potential scenarios is
presented in Table 8.3-1. The general bioassessment
approaches are as follows:
(13) If HC = HI, then bioassessment for the purpose of
detecting water quality effects at I (impact site)
would proceed similarly to the evaluation of BC
relative to BR (Figure 8.3-2).
(14) Where reversible habitat alterations account for
all habitat differences between C and I, then
bioassessment would proceed as in Figure 8.3-3.
(15) If habitat degradation is due to reversible and/or
irreversible alterations, then bioassessment would
proceed as in Figure 8.3-4.
Bioassessment Using a Regional Reference
(Figure 8.3-6)
In situations where R is to be used as a reference,
reference data could be obtained either from a single
reference site or a regional database made up of
numerous sites, and evaluation of the impact site
would proceed as in Figure 8.3-6. As data are
accumulated and processed, regional databases will
provide refinement to the criteria and enhance bio-
assessments. A matrix of conclusions that would
result from the possible scenarios is presented in
Table 8.3-1.
(16) If HR = HI, then the approach in assessing poten-
tial water quality effects at I would be similar to
that followed in evaluating BC relative to BR
(Figure 8.3-2).
(17) Where reversible habitat alterations account for
all habitat differences between I and R, then
bioassessment would proceed as in Figure 8.3-3.
(18) Where habitat degradation may be caused by
reversible and/or irreversible alterations, then
bioassessment would proceed according to Fig-
ure 8.3-4.
8-9
-------
HC
RHA <
(III)
HR
Select C*
HC* = HR
IB)
HC*
+ RHA
.19)
< HR
HC* + RHA
(10)
HR
Go to
(I)
BCX = BR
(unlikely
scenario)
(11)
HC + RHA < HR;
BC = BR
Habitat not
limiting;
No bioimpact
at "CH"
*
Use "C*" or
'R'as
reference for
bioassessment
^
(a
HC* + HHA < HR BC* < BR
Bioimpact at "C*n.
Effects due to degraded
habitat +/or WQ
(UAA is eventually
needed)
^ ,
Perform UAA.
Redef ine'Rx"
or subset of'R"
(b)
Consider "CK"
best attainable
condition. Use
°C*° as
reference for
bioassessment.
r
Icl
Predict
biological
condition using
known habitat
qua'lity and
reference
database.
Figure 8.3-4. Evaluation of an alternative site-specific control station (C*).
(Numbers in parentheses refer to points of discussion in text.)
8-10
-------
(Using "C"
[or "C*"]
as a
reference
station)
Figure 8.3-5. Bioassessment using a site-specific control station.
(Numbers in parentheses refer to points of discussion in text.)
-------
TABLE 8.3-1 BIOASSESSMENT CONCLUSIONS RELATIVE TO USE OF A SITE-SPECIFIC CONTROL OR REGIONAL REFERENCE
HC * RHA
HC t RHA < HR
oo
fo
BC = BR BC
No bioimpairment at C
or I ; I is a candi-
n date for inclusion in
th* R database .
u
CO
M
R Bioiopaiment at I
0 due to WQ effects .
X
M
0
U
Q
o I; reversible habitat
I alterations are
w present but not
n liaiting.
u
X
* Bioiapairnent at I
< due to degraded
« habitat (reversible
t parameters) and/or
M WQ.|B)
M CO
X
u
n
(a) Use attainability analysis
(b) To differentiate water qual
< BR BC = BR
or I; use designation
appropriate. X is a
candidate for inclu-
sion in R database.
Reversible habitat
alterations arc pre-
sent but not limiting
Bioimpairment at I .
due to WQ effects
sible habitat
alterations.
'Unlikely scena'rio
Bioinpairaent at I
due to degraded
paraneters) and/or WQ
effects.
eventually needed.
ity effects from habitat effects, a
BC < BR(a) BC = BR
Unlikely scenario
Unlikely scenario
Unlikely scenario
Bioimpiiraent at I
due Co degraded
habitat (rever-
sible w/respect
to C, and both
reversible and
irreversible para-
aeters w/respect
to R) and/or WQ
effects.
fairly extensive database on water quality
BC < BRIa)
Bioimpairment at C
and I due to
(reversible and/or
meters) and/or WQ
effects. TbT
Both C and I
impaired relative
to R due to
(reversible and/or
irreversible para-
meters) and/or WQ
effects. ' Addi-
ment at I due to
WQ.
Bioimpairment at C
and I due to
degraded habitat
(reversible and/or
irreversible para-
meters) and/or WQ
effects.'01
Both C and I
inoaired relative
to R due to
degraded habitat
(reversible and/or
irreversible
parameters ) and/or
WQ effects. 1DI
Additional
due to degraded
parameters I .
parameters is
(0
necessary. This information, if it exists, should be available Cor prior review. Thus, an agency would b« aware of a
potential water quality problea prior to biological assessment, which would aid in the determination of course and effects
relative to habitat constraints or water quality probleas.
Unlikely, but nay occur in response to organic enrichment.
-------
TABLE 8.3-1 (Cont. )
HR
HC + RHA < HR
BC < 8RIa I
BC < BRIa)
M
m
n
u
03
H
a
u
m
M
n
M
K
ra
M
O)
tt
m
NO DLO impairment at
I, but reversible
and/or irreversible
habitat alterations
present .
Bioimpaiment at I,
duo to degraded
habitat ( reversible
and/or irreversible
parameters) and/or WQ
effects. '
Include I in R
database .
due to WQ effects.
para no tors) and/or WQ (reversible and/or
WQ effects. ( '
Biological impaitxent Unlikely scenario Unlikely scenario
at C, but not I .
Both C and I impaired C impaired relative to Bioimpairnent at I
relative to R due to Rduetodegraded dueto WQ . Habitat
parameters) and/or WQ
effects. Bioimpair-
nent at I due to WQ
effects .
nioiapairment ac I,
and C due to
degraded habitat
( reversible and/or
irreversible
parameters ) and/or
WQ effects. ' '
Both C and I
to R due to
degraded habitat
(reversible and/or
parameters ) and/or
WQ effects .
Addi tional bio-
to degraded habitat
( reversible and/or
itat parameters)
and/or WQ . '
Unlikely scenario
C iap aired relative
to R due to
degraded habitat
( reversible and/or
•eters ) and/or WQ
effects.' ' Bio-
to degraded habitat
(reversible para-
Be ters) and/or WQ.
-------
TABLE 8.3-1 ICont.)
HR
HC + RHA = HR
HC * RHA < HR
00
BC = BR
alterations present,
but not Uniting.
Bioimpairoent at I
habitat alterations
and/or WQ •f«»cts.lcl
BC < BR
habitat parameters
and/or WQ effects .
due to WQ.
C impaired relative
effects . Bioimpair-
ment at I due to
(reversible para-
meters) and/or WQ . '
BC = BR BC < BR(a) BC = BR
Unlikely scenario Un likely scenario
Dioimpairment at C and Bioimpairaent at X
reversible habitat habitat altera-
alterations and/or WQ . tions and/or WQ .
1 imi ting at C .
Unlikely scenario Unlike ly scenario
BC < BRtal
Unlikely scenario
Bioiapairaent at C
due to degraded
habitat (reversible
for C , reve rs ible
for I) and/or WQ .
Unlikely scenario
I. but reversible
and/or irreversible
habitat alterations
a re present.
Bioiapaicment at I
due to degraded
habitat (reversible
ar.H/or irreversible
paranecersi and/or MQ
effects.101
due to degraded
habitat '{reversible
and/or irreversible
parameters) and/or
WQ. Bioimpairment
at C due to WQ.
C impaired relative
to R due to WQ
effects. Bioimpair-
aent «*t I due to
degraded haoitat
(r»>v*rsible and/or
irreversible para-
meters) and/or WQ.
Bioinpai raent at C
relative to R due to
reversible habitat
alterations and/or WQ.
Bioiapairment at I due
to degraded habitat
(reversible and/or
irreversible para-
meters) and/or WQ
effects.top
Bioinpairaent at
I due to degraded
habitat and/or WQ.
Habitat at C ttot
limiting.
Bioimpairment at C
and I relative to R
due to degraded
habitat (irrever-
sible and rever-
sible parameters)
and/or WQ.
-------
R"
(Using
as a
reference
station)
Figure 8.3-6. Bioassessment using a regional reference.
(Numbers in parentheses refer to points of
discussion in text.)
8-15
-------
8.4 CASE STUDY
HI+RHA = HR — HI + RHA VS
Using the data from the North Carolina DEM pilot
study (discussed in Section 6.4), an integrated assess-
ment can be performed using the decision matrix
approach described in Section 8.3. This case study is
presented in a step-by-step fashion to illustrate the
concepts of the decision matrix. Only data from Sta-
tions 3 and 4 are compared to Stations 1 (site-specific
control) and R (regional reference).
1. The habitat quality of the site-specific control is
first compared to that of the regional reference.
HC = HR «- HC VS HR -* HC
-------
TABLE 8.4-1 SUMMARY OF HABITAT ASSESSMENT SCORING FOR ARARAT AND MITCHELL RIVERS BENTHIC CASE STUDY DATA
00
Habitat Category/Parameter
Primary — Substrate and Ins t ream Cover
1. Bottom substrate and available cover
2. Embeddedness^ '
3. Flow/velocity
Secondary — Channel Morphology
4. Channel alteration
5. Bottom scouring and deposition
6. Pool/riffle, run/bend ratio
Tertiary — Riparian and Bank Structure
7. Bank stability*^
8. Bank vegetation^'.
9. Streamside cover
Subtotal for tertiary parameters
Score =
Proportion (%) of ecoregional reference
Classification =
C(D
14
18
16
7
10
11
6
9
10
25
101
81
S
Stations
3
8
6 (18)
9
2
4
10
7 (10)
9 (10)
8 (10)
24 (30)(b)
63 (81)
50 (65)
P
4
18
10
18
11
13
11
9
10
8
27
108
86
S
R(6)
18
18
19
13
13
14
10
10
10
30
125
100
E
Criteria:
> 90% excellent (comparable to reference)
75-89 supporting
60-74 partially supporting
< 59 nonsupporting
(a) Reversible habitat alteration (RHA) parameters.
(b) Parentheses indicate adjustment for RHAs pertinent to ecoregional reference.
-------
TABLE 8.4-2 SUMMARY OF METRIC VALUES, PERCENT COMPARISON, AND BIOASSESSMENT SCORES FOR
ARARAT AND MITCHELL RIVERS BENTHIC CASE STUDY DATA
Metric Value
Station
Metrics
Taxa richness
HBI
Scrapers/Filt. Collect.
EPT/Chiron. Abundance
% Contrib. Dom. Taxon
EPT Index
Community Loss Index
C( 1 )
26
4.46
0.833
2.45
11.2
12
0.64
3
11
9.34
0.000
0.00
53.5
0
2.31
4
34
6.24
0.108
0.55
16.5
12
0.62
R(6)
34
3.93
1.500
9.28
14.2
14
0 .00
100-Organism Subsample
% Comparison to Reference
Station
C( 1 ) 3 4 R(6)
76 32 100 100
t a \ ( a ) 1 A \ fat
88|a) 42(a) 63
56 0 7 100
26 0 6 100
__<"> __<»> __ __<»>
86 0 86 100
(c) (c) (c ) (c)
Bioassessment Score
Station
C( 1 )
4
6
6
2
6
4
4
3
0
0
0
0
0
0
2
4
6
2
0
0
6
4
4
R(6)
6
6
6
6
6
6
6
Total score
Biological condition
32 2 22 T2
Slight Sev. Mod. Non
(a) HBI comparison is ratio of reference to station evaluated.
(b) Actual percent contribution is evaluated, not percent comparability.
(c) Range of values is evaluated, not percent comparability.
-------
It is apparent from a general comparison of habitat
quality and biological condition at this North Carolina
site that there is a close relationship between habitat
and biological condition (Figure 8.4-1). As habitat
quality declines, so does the value of the benthic
index (based on the RBP approach). If these data
from the pilot study are plotted against the theoretical
curve depicting the relationship between habitat and
biological condition, the deviation from the predicted
relationship for each station can be discerned (Fig-
ure 8.4-2). The development of a substantial reference
database would allow for the development of an
empirical line with statistical confidence intervals
around the line. From this information, predictions of
water quality effects beyond the habitat constraints are
possible. In this manner, cause of the degradation of
biological condition at Stations 3 and 4 could be
refined.
125
- 100
0)
m
OL
m
tr
a
s
'E
a
Figure 8.4-1. The relationship between habitat quality and benthic community condition at the North Carolina
pilot study site.
100 —
0 10 20 30 40 50 60 70 80 90 100
Habitat Quality (% of Reference)
Figure 8.4-2. Pilot study results applied to the theoretical habitat vs. biological condition curve.
8-19
-------
REFERENCES
American Public Health Association, American Water-
works Association, and Water Pollution Control Feder-
ation. 1971. Standard Methods for the Examination of
Water and Wastewater. American Public Health
Association, Washington, D.C.
Angermeier, PL. 1983. The Importance of Cover and
other Habitat Features to the Distribution and Abun-
dance of Illinois Stream Fishes. Ph.D. Dissertation,
University of Illinois, Urbana.
Angermeier, PL. and J.R. Karr. 1986. Applying an
index of biotic integrity based on stream fish commu-
nities: Considerations in sampling and interpretation.
N. Am. J. Fish. Manage. 6:418-429.
Bailey, R.G. 1976. Ecoregions of the United States
(Map scale 1:7,500,000). USDA, Forest Service,
Ogden, Utah.
Ball, J. 1982. Stream Classification Guidelines for
Wisconsin. Wisconsin Department of Natural
Resources Technical Bulletin. Wisconsin Department
of Natural Resources, Madison, Wisconsin.
Benke, A.C., T.C. Van Arsdall, Jr., and D.M.
Gillespie. 1984. Invertebrate productivity in a subtrop-
ical blackwater river: The importance of habitat and
life history. Ecol. Monogr. 54(l):25-63.
Bickers, C.A., M.H. Kelly, J.M. Levesque, and R.L.
Hite. 1988. User's Guide to IBI-AIBI-Version 2.01 (A
BASIC Program for Computing the Index of Biotic
Integrity with the IBM-PC). State of Illinois, Environ-
mental Protection Agency, Marion, Illinois.
Bode, R.W. 1988. Quality Assurance Work Plan
for Biological Stream Monitoring in New York State.
New York State Department of Environmental
Conservation.
Bond, C.E. 1986. Department of Fisheries and Wild-
life, Oregon-State University, Corvallis. Personal
communication.
Boesch, D.F. 1977. Application of Numerical Classifi-
cation in Ecological Investigation of Water Pollution.
Report No. EPA-600/3-77-033. U.S. EPA, Corvallis,
Oregon.
Bray, J.R. and J.T. Curtis. 1957. An ordination of the
upland forest communities of southern Wisconsin.
Ecol. Monogr. 27:325.
Cairns, J., Jr. 1982. Artificial Substrates. Ann Arbor
Science Publishers, Inc., Ann Arbor, Michigan.
Cairns, J., Jr. and K.L. Dickson. 1971. A simple
method for the biological assessment of the effects of
waste discharges on aquatic bottom-dwelling organ-
isms. J. Water Pollut. Control Fed. 43:755-772.
Cairns, J., Jr. and R.L. Kaesler. 1971. Cluster analysis
of fish in a portion of the Upper Potomac River.
Trans. Am. Fish. Soc. 100:750-756.
Clements, W.H., D.S. Cherry, and J. Cairns, Jr. 1988.
Structural alterations in aquatic insect communities
exposed to copper in laboratory streams. Environ.
Tox. and Chem. 7(9):715-722.
Cochran, W.G. 1952. The x2 test of goodness of fit.
Ann. Math. Statistics 23:315-345.
Courtemanch, D.L. and S.P Davies. 1987. A coeffi-
cient of community loss to assess detrimental change
in aquatic communities. Water Res. 21(2):217-222.
Cummins, K.W. 1973. Trophic relations of aquatic
insects. Ann. Rev. of Entomol. 18:183-206.
Cummins, K.W. 1987. Appalachian Environmental
Laboratory, University of Maryland, Frostburg. Per-
sonal communication.
Cummins, K.W. and M.J. Klug. 1979. Feeding ecology
of stream invertebrates. Ann. Rev. Ecol. Syst.
10:147-172.
Cummins, K.W. and M.A. Wilzbach. 1985. Field
Procedures for Analysis of Functional Feeding Groups
of Stream Macroinvertebrates. Contribution 1611.
Appalachian Environmental Laboratory, University of
Maryland, Frostburg.
Cummins, K.W., M.A. Wilzbach, D.M. Gates, J.B.
Perry, and W.B. Taliaferro. 1989. Shredders and ripar-
ian vegetation. Bioscience. 39(1):24-30.
Dawson, C.L. and R.A. Hellenthal. 1986. A Com-
puterized System for the Evaluation of Aquatic
Habitats Based on Environmental Requirements and
Pollution Tolerance Association of Resident Organ-
isms. Report No. EPA-600/53-86/019. U.S. EPA, Cin-
cinnati, Ohio.
Dimick, R.E., and F. Merryfield. 1945. The Fishes of
the Willamette River System in Relation to Pollution.
R-l
-------
Engineering Experiment Station Bulletin Series
20:7-55. (Oregon State College, Corvallis, Oregon).
Energy, Mines, and Resources Canada. 1986. Canada
Wetland Regions (Map scale 1:7,500,000). MCR 4108.
Canada Map Office, Energy, Mines, and Resources
Canada, Ottawa, Ontario.
Fausch, D.D., J.R. Karr, and P.R. Yant. 1984.
Regional application of an index of biotic integrity
based on stream fish communities. Trans. Am. Fish.
Soc. 113:39-55.
Ferrington, L.C. 1987. Collection and Identification of
Floating Exuviae of Chironomidae for Use in Studies
of Surface Water Quality. SOP No. FW 130A. U.S.
EPA, Region VII, Kansas City, Kansas.
Funk, J.L. 1957. Movement of stream fishes in Mis-
souri. Trans. Am. Fish. Soc. 85:39-57.
Furse, M.T., D. Moss, J.F. Wright, and P.D.
Armitage. 1984. The influence of seasonal and taxo-
nomic factors on the ordination and classification of
running-water sites in Great Britain and on the predic-
tion of their macro-invertebrate communities. Fresh-
water Biol. 14:257-280.
Gabler, R.E., R.J. Sager, S. Brazier, and D.L. Wise.
1976. Essentials of Physical Geography. CBS College
Publishing, The Dryden Press, New York, N.Y.
Gammon, J.R. 1980. The use of community param-
eters derived from electrofishing catches of river fish
as indicators of environmental quality, in Seminar on
Water Quality Management Tradeoffs. Report No.
EPA-905/9-80-009. U.S. EPA, Washington, D.C.
Gammon, J.R. 1989. Department of Biological
Science, DePauw University, Greencastle, Indiana.
Personal communication.
Gammon, J.R., A. Spacie, J.L. Hamelink, and R.L.
Kaesler. 1981. Role of electrofishing in assessing
environmental quality of the Wabash River, in Ecolog-
ical Assessments of Effluent Impacts on Communities
of Indigenous Aquatic Organisms (J.M. Bates and
C.I. Weber, eds.). STP 730, pp. 307-324. American
Society for Testing and Materials, Philadelphia,
Pennsylvania.
Gauch, H., Jr. 1982. Multivariate Analysis in Com-
munity Ecology. Cambridge University Press, New
York.
Gerking, S.D. 1959. The restricted movement of fish
populations. Biol. Review. 34:221-242.
Hargrove, B.T. 1972. Aerobic decomposition of sedi-
ment and detritus as a function of particle surface
area and organic content. Limnol. Oceanogr.
17:583-596.
Hendricks, M.L., C.H. Hocutt, and J.R. Stauffer, Jr.
1980. Monitoring of fish in lotic habitats, in Biologi-
cal Monitoring of Fish (C.H. Hocutt and J.R.
Stauffer, Jr., eds.). D. C. Heath Co., Lexington,
Massachusetts.
Hill, M.O. 1979. DECORANA: A FORTRAN Pro-
gram for Detrended Correspondence Analysis and
Reciprocal Averaging. Cornell University, Ithaca, New
York.
Hill, J. and G.D. Grossman. 1987. Home range esti-
mates for three North American stream fishes. Copeia
1987:376-380.
Hilsenhoff, W.L. 1982. Using a Biotic Index to Evalu-
ate Water Quality in Streams. Technical Bulletin
No. 132. Department of Natural Resources, Madison,
Wisconsin.
Hilsenhoff, W.L. 1987a. Department of Entomology,
University of Wisconsin-Madison. Personal
communication.
Hilsenhoff, W.L. 1987b. An improved biotic index
of organic stream pollution. Great Lakes Entomol.
20:31-39.
Hilsenhoff, W.L. 1988. Rapid field assessment of
organic pollution with a family level biotic index.
J. N. Am. Benthol. Soc. 7(l):65-68.
Hocutt, C.H. 1981. Fish as indicators of biological
integrity. Fisheries 6(6):28-31.
Holden, P.B. and C.B. Stalnaker. 1975. Distribution
and abundance of mainstream fishes of the middle and
upper Colorado river basins, 1967-1973. Trans. Am.
Fish Soc. 104:217-231.
Hughes, R.M. 1985. Use of watershed characteristics
to select control streams for estimating effects of
metal mining wastes on extensively disturbed streams.
Environ. Manage. 9:253-262.
Hughes, R.M., J.H. Gakstatter, M.A. Shirazi. and
J.M. Omernik. 1982. An approach for determining
biological integrity in flowing waters, in Inplace
Resource Inventories: Principles and Practices,
Proceedings of a National Workshop (T.B. Brann,
ed.). Society of American Foresters. Bethesda,
Maryland.
R-2
-------
Hughes, R.M., D.P. Larsen, and J.M. Omernik. 1986.
Regional reference sites: A method for assessing
stream potentials. Environ. Manage. 10:629-635.
Hughes, R.M. and J.R. Gammon. 1987. Longitudinal
changes in fish assemblages and water quality in the
Willamette River, Oregon. Trans. Am. Fish. Soc.
116(2): 196-209.
Hughes, R.M., E. Rexstad, and C.E. Bond. 1987. The
relationship of aquatic ecoregions, river basins, and
physiographic provinces to the ichthyogeographic
regions of Oregon. Copeia 1987:423-432.
Hughes, R.M. and D.P. Larsen. 1988. Ecoregions: An
approach to surface water protection. J. Water Pollut.
Control Fed. 60:486-493.
Jaccard, P. 1912. The distribution of flora in an alpine
zone. New Phytol. 11:37.
Judy, R.D., Jr., P.N. Seeley, T.M. Murray, S.C.
Svirsky, M.R. Whitworth, and L.S. Ischinger. 1984.
Technical Report, Initial Findings: Vol. 1 of 1982
National Fisheries Survey. Report No. FWS/OBS-84/06.
U.S. Fish and Wildlife Service, Fort Collins,
Colorado.
Karr, J.R. 1981. Assessment of biotic integrity using
fish communities. Fisheries 6:21-27.
Karr, J.R., K.D. Fausch, P.L. Angermeier, P.R. Yant,
and I.J. Schlosser.. 1986. Assessing Biological Integrity
in Running Waters: A Method and Its Rationale. Spe-
cial Publication 5. Illinois Natural History Survey.
Kuehne, R.A. and R.W. Barbour. 1983. The American
Darters. University Press of Kentucky, Lexington,
Kentucky.
Landers, D.H., J.M. Eilers, D.F. Brakke, W.S. Overton,
P.E. Kellar, M.E. Silverstein, R.D. Schonbrod,
R.E. Crowe, R.A. Linthurst, J.M. Omernik, S.A.
Teague, and E.P. Meier. 1987. Characteristics of Lakes
in the Western United States. Volume I. Population
Descriptions and Physico-Chemical Relationships.
Report No. EPA-600/3-86/054a. U.S. EPA, Washing-
ton, D.C.
Larsen, D.P., J.M. Omernik, R.M. Hughes, C.M.
Rohm, T.R. Whittier, A.J. Kinney, A.L. Gallant, and
D.R. Dudley. 1986. The correspondence between spa-
tial patterns in fish assemblages in Ohio streams and
aquatic ecoregions. Environ. Manage. 10:815-828.
Larsen, D.P, D.R. Dudley, and R.M. Hughes. 1988.
A regional approach for assessing attainable water
quality: An Ohio case study. J. Soil Water Conserv.
43:171-176.
Lee, D.S., C.R. Gilbert, C.H. Hocutt, R.E. Jenkins,
D.E. McAllister, and J.R. Stauffer, Jr. 1980. Atlas of
North American Freshwater Fishes. North Carolina
State Museum of Natural History. Raleigh, North
Carolina.
Leidy, R.A. and P.L. Fiedler. 1985. Human distur-
bance and patterns of fish species diversity in the San
Francisco Bay drainage, California. Biol. Conserv.
33:247-267.
Lenat, D.R. 1983. Chironomid taxa richness: Natural
variation and use in pollution assessment. Freshwater
Invertebr. Biol. 2(4): 192-198.
Lenat, D.R. 1986. Memorandum to Steve Tedder re:
Biomonitoring of Ararat River, September 1986. North
Carolina Department of Natural Resources and Com-
munity Development, Division of Environmental
Management. 1 October. Unpublished.
Leonard, P.M. and D.J. Orth. 1986. Application and
testing of an index of biotic integrity in small, cool-
water streams. Trans. Am. Fish. Soc. 115:401-414.
Linthurst, R.A., D.H. Landers, J.M. Eilers, D.F.
Brakke, W.S. Overton, E.P. Meier, and R.E. Crowe.
1986. Characteristics of Lakes in the Eastern United
States. Volume I. Population Descriptions and
Physico-Chemical Relationships. Report No.
EPA-600/4-86/007a. U.S. EPA, Washington, D.C.
Matthews, W.J. 1986. Fish faunal structure in an
Ozark stream: Stability, persistence, and a catastrophic
flood. Copeia. 1986:388-397.
McArthur, J.V., J.R. Barnes, B.J. Hansen, and L.G.
Leff. 1988. Seasonal dynamics of leaf litter breakdown
in a Utah alpine stream. J. N. Am. Benthol. Soc.
7(1):44-50.
Merritt, R.W. and K.W. Cummins, eds. 1984. An
Introduction to the Aquatic Insects of North America.
Second edition. Kendall/Hunt Publishing Co.,
Dubuque, Iowa.
Miller, D.L., P.M. Leonard, R.M. Hughes, J.R. Karr,
P.B. Moyle, L.H. Schrader, B.A. Thompson, R.A.
Daniels, K.D. Fausch, G.A. Fitzhugh, J.R. Gammon,
D.B. Halliwell, P.L. Angermeier, D.J. Orth. 1988a.
Regional applications of an Index of Biotic Integrity
for use in water resource management. Fisheries
5:12-20.
Miller, D.L., R.A. Daniels, and D.B. Halliwell.
1988b. Modification of an Index of Biotic Integrity
based on fish communities for streams of the north-
eastern United States. N. American J. Fish. Man. (In
Review).
R-3
-------
Minckley, W.L. 1973. Fishes of Arizona. Sims Print-
ing, Phoenix, Arizona.
Minshall, G.W., K.W. Cummins, R.C. Petersen, C.E.
Gushing, D.A. Bruns, J.R. Sedell, and R.L. Vannote.
1985. Developments in stream ecosystem theory. Can.
J. Fish. Aquat. Sci. 42:1045-1055.
Moriseta, M. 1959. Measuring of interspecific associ-
ation and similarity between communities. Memoirs
Faculty Sci., Kyoshu Univ. Ser. E. Biol. 3-65.
Mount, D.I., N.A. Thomas, T.J. Norberg, M.T. Bar-
bour, T.H. Roush, and W.F. Brandes. 1984. Effluent
and Ambient Toxicity Testing and Instream Commu-
nity Response on the Ottawa River, Lima, Ohio.
Report No. EPA-600/3-84-080. U.S. EPA, Duluth,
Minnesota.
Mount, D.I., T.J. Norberg-King, and A.E. Steen.
1986. Validity of Effluent and Ambient Toxicity Tests
for Predicting Biological Impact, Naugatuck River,
Waterbury, Connecticut. Report No. EPA-600/8-86/005.
U.S. EPA, Duluth, Minn.
Moyle, P.B. 1976. Inland Fishes of California. Univer-
sity of California Press, Berkeley, California.
Moyle, P.B., and R.D. Nichols. 1973. Ecology of
some native and introduced fishes of the Sierra
Nevada foothills in central California, Copeia.
1973:478-490.
Newman, R.M., J.A. Perry, E. Tam, and R.L. Craw-
ford. 1987. Effects of chronic chlorine exposure on lit-
ter processing in outdoor experimental streams.
Freshwater Biol. 18:415-428.
Nielsen, L.A. and D.L. Johnson, eds. 1983. Fisheries
Techniques. American Fisheries Society, Bethesda,
Maryland.
North Carolina Department of Natural Resources and
Community Development. 1983. Qualitative Sampling
of Benthic Macroinvertebrates: A Reliable, Cost-
Effective Biomonitoring Technique. Biological Series
No. 108. North Carolina Department of Natural
Resources and Community Development, Division of
Environmental Management, Raleigh, North Carolina.
Nuzzo, R. 1986. Macroinvertebrate Rapid Assessment
Methodology. Mass. Viv. WPC.
Ohio Environmental Protection Agency. 1987a. Biolog-
ical Criteria for the Protection of Aquatic Life: Vol-
ume I. The Role of Biological Data in Water Quality
Assessment (Final Draft). Ohio Environmental Protec-
tion Agency, Columbus, Ohio.
Ohio Environmental Protection Agency. 1987b. Biolog-
ical Criteria for the Protection of Aquatic Life: Vol-
ume II. User's Manual for Biological Assessment of
Ohio Surface Waters. Ohio Environmental Protection
Agency, Columbus, Ohio.
Ohio Environmental Protection Agency. 1987c. Biolog-
ical Criteria for the Protection of Aquatic Life: Vol-
ume III. Standardized Biological Field Sampling and
Laboratory Methods for Assessing Fish and Macroin-
vertebrate Communities. Ohio Environmental Protec-
tion Agency, Columbus, Ohio.
Omernik, J.M. 1987. Ecoregions of the Conterminous
United States. Ann. Assoc. Am. Geograph. 77(1): 118-125.
Osborne, L.L. and E.E. Hendricks. 1983. Streamflow
and Velocity as Determinants of Aquatic Insect Distri-
bution and Benthic Community Structure in Illinois.
Water Resources Center, University of Illinois, Report
No. UILU-WRC-83-183. U.S. Department of the
Interior, Bureau of Reclamation.
Oswood, M.E. and WE. Barber. 1982. Assessment of
fish habitat in streams: Goals, constraints, and a new
technique. Fisheries 7(3): 8-11.
Palmer, C.M. 1977. Algae and Water Pollution. Report
No. EPA-600/9-77-036. U.S. EPA, Cincinnati, Ohio.
Patrick, R. 1973. Use of algae, especially diatoms in
the assessment of water quality, in Biological Methods
for the Assessment of Water Quality (J. Cairns, Jr.
and K.L. Dickson, eds.), Special Technical Publica-
tion 528. American Society for Testing and Materials,
Philadelphia, Pennsylvania.
Pinkham, C.F.A. and J.B. Pearson. 1976. Applications
of a new coefficient of similarity to pollution surveys.
J. Water Pollut. Control Fed. 48:717-723.
Platts, W.S. 1974. Geomorphic and aquatic conditions
influencing salmonids and stream classification—with
application to ecosystem management. U.S. Depart-
ment of Agriculture SEAM Program, Billings,
Montana.
Platts, W.S., W.F. Megahan, and G.W. Minshall. 1983.
Methods for Evaluating Stream, Riparian, and Biotic
Conditions. General Technical Report INT-138. U.S.
Department of Agriculture, U.S. Forest Service,
Ogden, Utah.
Pollard, J.E. 1981. Investigator differences associated
with a kicking method for sampling macroinver-
tebrates. J. Freshwater Ecol. 1:215-224.
Rankin, E. 1987. Ohio Environmental Protection
Agency. Personal communication.
Resh, V.H. 1988. Variability, accuracy, and taxonomic
costs of rapid assessment approaches in benthic
biomonitoring. Presented at the 36th annual North
R-4
-------
American Benthological Society meeting at Tus-
caloosa, Alabama, 17-20 May 1988.
Reynolds, J.B. 1983. Electrofishing, in Fisheries Tech-
niques (L.A. Nielsen and D.L. Johnson, eds.),
American Fisheries Society, Bethesda, Maryland.
Rodgers, J.H., Jr., K.L. Dickson, and J. Cairns, Jr.
1979. A review and analysis of some methods used to
measure functional aspects of periphyton, in Methods
and Measurements of Periphyton Communities: A
Review (R.L. Weitzel, ed.), Special Technical Publi-
cation 690. American Society for Testing and
Materials.
Rohm, C.M., J.W. Giese, and C.C. Bennett. 1987.
Evaluation of an aquatic ecoregion classification of
streams in Arkansas. Freshwater Ecol. 4:127-140.
Ross, ST., W.J. Matthews, and A.E. Echelle. 1985.
Persistence of stream fish assemblages: Effects of
environmental change. Am. Nat. 126:24-40.
Scott, W.B. and E.J. Grossman. 1973. Freshwater
Fishes of Canada. Fisheries Resource Board of
Canada, Bulletin 184.
Seber, G.A. 1982. The Estimation of Animal Abun-
dance. McMillan Publishing, New York, N.Y.
Seber, G.A.F. and E.D. LeCren. 1967. Estimating
population parameters from catches large relative to
the population. J. Anim. Ecol. 36:631-643.
Seber, G.A.F. and J.F. Whale. 1970. The removal
method for two and three samples. Biometrics.
26:393-400.
Shackleford, B. 1988. Rapid Bioassessments of Lotic
Macroinvertebrate Communities: Biocriteria Develop-
ment. Arkansas Department of Pollution Control and
Ecology, Little Rock, Arkansas.
Simpson, J.C. and R.L. Wallace. 1982. Fishes of
Idaho. University Press of Idaho. Moscow, Idaho.
Snedecor, G.W. and W.G. Cochran. 1967. Statistical
Methods. Iowa State University Press, Ames, Iowa.
Steedman—R:J. 1988. Modification and assessment of
an index of biotic integrity to quantify stream quality
in southern Ontario. Can. J. Fish. Aquat, Sci.
45:492-501.
Swift, M.C., K.W. Cummins, and R.A. Smucker.
1988a. Effects of Dimilin on stream leaf-litter process-
ing rates..Verh. Internal. Verein. Limnol. 23:1255-1260.
Swift, M.C., R.A. Smucker, and K.W. Cummins.
1988b. Effects of Dimilin on freshwater litter decom-
position. Environ. Toxic, and Chem. 7:161-166.
U.S. Department of Agriculture, Soil Conservation
Service. 1981. Land Resource Regions and Major
Land Resource Areas of the United States. Agricul-
tural Handbook 296. U.S. Government Printing
Office, Washington, D.C.
U.S. Environmental Protection Agency (EPA). 1980a.
Guidelines and Specifications for Preparing Quality
Assurance Program Plans. Report No. QAMS-004180.
U.S. EPA, Washington, D.C.
U.S. Environmental Protection Agency (EPA). 1980b.
Interim Guidelines and Specifications for Preparing
Quality Assurance Project Plans. Report No. QAMS-
005180. U.S. EPA, Washington, D.C.
U.S. Environmental Protection Agency (EPA). 1983.
Technical Support Manual: Waterbody Surveys and
Assessments for Conducting Use Attainability
Analyses.
U.S. Environmental Protection Agency (EPA). 1984a.
Policy and Program Requirement to Implement the
Quality Assurance Program. EPA Order 5360.1. U.S.
EPA, Washington, D.C.
U.S. Environmental Protection Agency (EPA). 1984b.
The Development of Data Quality Objectives. Pre-
pared by the EPA Quality Assurance Management
Staff and the DQO Workgroup. U.S. EPA, Washing-
ton, D.C.
U.S. Environmental Protection Agency (EPA). 1984c.
Guidance for Preparation of Combined Work/Quality
Assurance Project Plans for Environmental Monitor-
ing. Report No. OWRS QA-1. U.S. EPA, Washington,
D.C.
U.S. Environmental Protection Agency (EPA). 1985.
Technical Support Document for Water Quality-based
Toxics Control. Report No. 440/4-85-03. Office of
Water, U.S. EPA, Washington, D.C.
U.S. Environmental Protection Agency (EPA). 1987.
Surface Water Monitoring: A Framework for Change.
Office of Water, Office of Policy Planning and Evalua-
tion, U.S. EPA, Washington, D.C.
U.S. Environmental Protection Agency (EPA). 1988.
Proceedings of the First National Workshop on Bio-
logical Criteria, Lincolnwood, Illinois, December 2-4,
1987. Report No. 905/9-89/003. U.S. EPA, Chicago,
Illinois.
Van Deventer, J.A. and W.S. Platts. 1989. Microcom-
puter Software System for Generating Population
Statistics from Electrofishing Data-User's Guide for
MicroFish 3.0. Technical Report No. INT-254. U.S.
Department of Agriculture, U.S. Forest Service,
Ogden, Utah.
R-5
-------
Vermont Department of Environmental Conservation.
1987. Compliance Monitoring of the Aquatic Biota.
Report No. 388-1330-RJ10.
Wade, D.C. and S.B. Stalcup. 1987. Assessment of the
Sport Fishery Potential for the Bear Creek Floatway:
Biological Integrity of Representative Sites, 1986.
Report No. TVA/ONRED/AWR-87/30. Tennessee Val-
ley Authority, Muscle Shoals, Alabama.
Warren, C.E. 1979. Toward Classification and Ration-
ale for Watershed Management and Stream Protection.
Report No. EPA-600/3-79-059. U.S. Environmental
Protection Agency, Corvallis, Oregon.
Weitzel, R.L. 1979. Periphyton measurements and
applications, in Methods and Measurements of
Periphyton Communities: A Review (R.L. Weitzel,
ed.), Special Technical Publication 690. American
Society for Testing and Materials.
Whittaker, R.H. 1952. A study of summer foliage
insect communities in the Great Smokey Mountains.
Ecol. Monogr. 22:6.
Whittier, T.R., D.P. Larsen, R.M. Hughes, CM.
Rohm, A.L. Gallant, and J.M. Omernik. 1987. The
Ohio Stream Regionalization Project: A Compendium
of Results. Report No. EPA-600/3-87/025. U.S. EPA,
Corvallis, Oregon.
Whittier, T.R., R.M. Hughes, and D.P. Larsen. 1988.
Correspondence between ecoregions and spatial pat-
terns in stream ecosystems in Oregon. Can. J. Fish.
Aquat. Sci. 45:1264-1278.
Winget, R.N. and F.A. Mangum. 1979. Biotic Condi-
tion Index: Integrated Biological, Physical, and Chem-
ical Stream Parameters for Management. Intermountain
Region, U.S. Department of Agriculture, Forest Ser-
vice, Ogden, Utah.
Winner, R.W., M.W. Boesel, and M.P. Farrell. 1980.
Insect community structure as an index of heavy-metal
pollution in lotic ecosystems. Can. J. Fish. Aquat.
Sci. 37:647-655.
Wydoski, R.S. and R.R. Whitney. 1979. Inland Fishes
of Washington. University of Washington Press.
Seattle, Washington.
R-6
-------
APPENDIX A
GUIDANCE FOR USE OF FIELD
AND LABORATORY DATA SHEETS
-------
APPENDIX A
GUIDANCE FOR USE OF FIELD
AND LABORATORY DATA SHEETS
This appendix provides guidance for use of the
rapid bioassessment field and laboratory data sheets.
The guidance sheets give brief descriptions of the
information required for each data sheet.
A.2 GUIDANCE FOR BIOSURVEY
FIELD DATA SHEET FOR
BENTHIC RBPs I, II, AND III
(Figures 6.1-1, 6.2-1, and 6.3-1)
A.I GUIDANCE FOR HEADER
INFORMATION (Figure 2.6-1)
Water body Name:
Name of river, stream, or drain.
Location:
Township, range, section, county where problem
area is located. For rivers, streams, or drains, road
crossings or outfall locations should be referenced
where applicable.
Reach/Milepoint:
Indicate station reach/milepoint.
Latitude/Longitude:
Indicate station latitude/longitude.
County/State:
Name of county and state where station is located.
Aquatic Ecoregion:
Name of ecoregion.
Station:
Agency name or number for station.
Investigators:
List field personnel involved.
Date:
Date of survey.
Agency:
Agency name or affiliation (academic, private
consulting)
Hydrologic Unit Code:
Indicate the USGS cataloging unit number in which
the station is located.
Form Completed By:
List personnel completing form.
Reason for Survey:
Reason survey was conducted.
Rapid Bioassessment Protocol I
(Figure 6.1-1)
Estimated Abundance Level of Aquatic Biota:
Record estimated abundance level of biota found in
the sampling area. Circle the number (corresponding
to the descriptions just below on the data sheet) that
best indicates the estimated size of each population
found in the sampling area. Each agency should
develop its own abundance level criteria.
Macrobenthos Qualitative Sample: Using the guide-
lines of rare, common, abundant, or dominant, record
the estimated abundance level of each major taxa
found in the sampling area. Each agency should
develop its own abundance level criteria.
Observations: Information included here would
include abundance of fish nesting sites; notes concern-
ing biota present; type of game fish observed; location
or presence of noteworthy physical structures such as
bridges, rip-rap, culverts; habitat alteration due to
construction activities; or any other observations perti-
nent to an impact assessment.
Rapid Bioassessment Protocol II
(Figure 6.2-1)
Estimated Abundance Level of Aquatic Biota:
Record estimated abundance level of biota found in
the sampling area. Circle the number (corresponding
to the descriptions just below on the data sheet) that
best indicates the estimated size of each population
found in the sampling area. Each agency should
develop its own abundance level criteria.
A-l
-------
Macrobenthos Qualitative Sample List: List families
found in 100-organism subsample and the number of
individuals within each family.
Riffle Sample Functional Feeding Groups:
Record the number of individuals collected in the
100-organism riffle subsample which represent the
Scraper and Filtering Collector Functional Feeding
Groups.
CPOM Sample: Record the number of individuals
collected in the supplemental CPOM sample which
represent the Shredder Functional Feeding Group, and
total number of individuals sorted.
Observations: Information included here would
include abundance of fish nesting sites; notes concern-
ing biota present; type of game fish observed; location
or presence of noteworthy physical structures such as
bridges, rip-rap, culverts; habitat alteration due to
construction activities; or any other observations perti-
nent to an impact assessment.
Rapid Bioassessment Protocol III
(Figure 6.3-1)
Estimated Abundance Level of Aquatic Biota:
Record estimated abundance level of biota found in
the sampling area. Circle the number (corresponding
to the descriptions just below on the data sheet) that
best indicates the estimated size of each population
found in the sampling area. Each agency should
develop its own abundance level criteria.
Macrobenthos Qualitative Sample: Using the guide-
lines of rare, common, abundant, or dominant, record
the estimated abundance level of each major taxa
found in the sampling area. Each agency should
develop their own abundance level criteria.
CPOM Sample: Record the number of individuals
collected in the supplemental CPOM sample which
represents the Shredder Functional Feeding Group,
and total number of individuals sorted.
Observations: Information recorded here would
include abundance of fish nesting sites; notes concern-
ing biota present; type of game fish observed; location
or presence of noteworthy physical structures such as
bridges, rip-rap, culverts; habitat alteration due to
construction activities; or any other observations perti-
nent to an impact assessment.
A.3 GUIDANCE FOR IMPAIRMENT
ASSESSMENT SHEET FOR
RBPs I, II, III, AND V
(Figures 6.1-2 and 7.2-1)
Rapid Bioassessment Protocols I, II,
III, and V
1. Detection of Impairment: Circle the one that
applies.
2. Biological Impairment Indicator: Circle those
that apply, as indicated by the benthos, fish, and
other aquatic biota.
3. Brief Description of Problem: Briefly explain the
biological nature of the problem, based on field
investigation and sampling. List the year and date
of previous biological data and reports, and where
the information can be found (state file, BIOS).
4. Cause: Circle those that apply. Indicate which is
the major cause of the stream problem.
5. Estimated Areal Extent of Problem: Record esti-
mated downstream extent of impact (in m) and
multiply by approximate stream width (in m) to
estimate areal width.
6. Suspected Source(s) of Problem: Check those that
are suspected. Briefly explain why you suspect a
specific source, and reference other surveys or
studies done to document the problem and its
source. Give title of applicable report, author(s),
and year published or completed. Use back of
sheet if necessary.
A.4 GUIDANCE FOR DATA
SUMMARY SHEET FOR
BENTHIC RBPs II AND III
(Figure 6.2-2 and 6.3-3)
Rapid Bioassessment Protocol II
(Figure 6.2-2)
Station Number: Indicate station number for each
data set recorded.
Station Location: Record brief description of sam-
pling site relative to established landmarks (i.e.,
roads, bridges).
A-2
-------
Taxa Richness: Record total number of families (or
higher taxa) collected in the 100-organism riffle
subsample.
FBI (modified): Record the Family Biotic Index value
(Hilsenhoff 1988) calculated for the 100-organism rif-
fle subsample using the formula presented in RBP II.
Tolerance classification values can be entered into the
computer database to simplify calculation.
Functional Feeding Group: Functional Feeding
Group classifications may be entered into the com-
puter database to simplify calculations.
Riffle Community; Scrapers/Filtering Collectors:
Enter the value obtained by dividing the number of
individuals in the riffle subsample representing the
Scraper Functional Group, by the number repre-
senting the Filtering Collector Functional Group.
CPOM Community; Shredders/Total: Enter the
value obtained by dividing the number of
individuals in the CPOM sample (or subsample)
representing the Shredder Functional Group, by the
total number of organisms in the sample (or
subsample).
EPT/Chironomidae: Enter the value obtained by
dividing the number of individuals in the
100-organism riffle subsample in the family
Chironomidae, by the total number of individuals in
the orders Ephemeroptera, Plecoptera, and
Trichoptera.
Percent Contribution (Dominant Family): Record
the value obtained by dividing the number of individ-
uals in the family that is most abundant in the
100-organism riffle subsample, by the total number of
individuals in the sample.
EPT Index: Record the total number of taxa in the
100-organism riffle subsample representing the orders
Ephemeroptera, Plecoptera, and Trichoptera.
Community Similarity Index: Enter the value calcu-
lated for the appropriate community similarity index,
using data from the 100-organism riffle subsample.
Values obtained for each metric should be assigned
a score based on percent comparability to the control
or reference station data. Scores are summed for both
the impaired and reference station. The percent com-
parison between the total scores provides the final
evaluation of biological condition.
Rapid Reassessment Protocol III
(Figure 6.3-3)
Station Number: Indicate station number for each
data set recorded.
Station Location: Record brief description of sam-
pling site relative to established landmarks (i.e.,
roads, bridges).
Species Richness: Record total number of species (or
higher taxa) collected in the 100-organism riffle
subsample.
HBI (modified): Record the species level Hilsenhoff
Biotic Index value (Hilsenhoff 1987b) calculated for
the 100-organism riffle subsample using the formula
presented in Rapid Bioassessment Protocol III. Toler-
ance classification values can be entered into the com-
puter database to simplify calculation.
Functional Feeding Group: Functional Feeding
Group classifications may be entered into the com-
puter database to simplify calculations.
Riffle Community; Scrapers/Filtering Collectors:
Enter the value obtained by dividing the number of
individuals in the riffle subsample representing the
Scraper Functional Group, by the number repre-
senting the Filtering Collector Functional Group.
CPOM Community; Shredders/Total: Enter the
value obtained by dividing the number of indi-
viduals in the CPOM sample (or subsample)
representing the Shredder Functional Group, by the
total number of organisms in the sample (or
subsample).
EPT/Chironomidae: Enter the value obtained by
dividing the total number of individuals in the
100-organism riffle subsample in the orders
Ephemeroptera, Plecoptera, and Trichoptera, by the
number of individuals in the family Chironomidae.
Percent Contribution (Dominant Taxon): Record the
value obtained by dividing the number of individuals
in the taxon that is most abundant in the 100-organism
riffle subsample, by the total number of individuals in
the sample.
EPT Index: Record the total number of taxa in the
100-organism riffle subsample representing the orders
Ephemeroptera, Plecoptera, and Trichoptera.
A-3
-------
Community Similarity Index: Enter the value calcu-
lated for the appropriate community similarity index,
using data from the 100-organism riffle subsample.
Values obtained for each metric should be assigned
a score based on percent comparability to the control
or reference station data. Scores are summed for both
the impacted and reference station. The percent com-
parison between the total scores provides the final
evaluation of biological condition.
Note: To maximize time efficiency, the metric
values entered on the Data Summary Sheets
are intended to be generated by use of a
computerized database.
A.5 GUIDANCE FOR LABORA-
TORY BENCH SHEET FOR
BENTHIC RBP III
(Figure 6.3-2)
Station Number: Indicate agency assigned number for
each sample dataset recorded.
Station Location: Record brief description of sam-
pling site relative to established landmarks (i.e.,
roads, bridges).
Species: List species identified from the 100-organism
riffle subsample.
Number of Organisms: Indicate number of indi-
viduals of each species collected in the 100-organism
riffle subsample at each station.
Total Organisms: Record total number of individuals
collected in the 100-organism riffle subsample at each
station.
Number of Taxa: Record the total number of taxa
collected in the 100-organism riffle subsample at each
station.
A.6 GUIDANCE FOR FIELD
COLLECTION DATA SHEET FOR
FISH RBP V
(Figure 7.2-3)
Drainage: Give name of stream or river and its basin,
site descriptor, and unique site code.
Date: Enter day, month, and year of collection.
Sampling Duration: Record length of time in minutes
actually collecting fish. If replicates are taken, record
them separately.
Sampling Distance: Measure, with a tape or cali-
brated range finder, the length in meters of reach
sampled.
Sampling Area: Multiply the length or reach sampled
by the average width sampled. Express in meters
squared.
Crew: Indicate crew chief and crew members.
Habitat Complexity/Quality: Circle the descriptor
that best describes subjective evaluation of the phys-
icochemical habitat.
Weather: Record air temperature, estimated wind
velocity, percent cloud cover, and precipitation.
Flow: Circle most appropriate descriptor.
Gear Used: Specify type, model, and number of elec-
trofisher, mesh size and length of seine, or concentra-
tion of fish toxicant.
Gear/Crew Performance: Indicate effectiveness of
crew in sampling the site. Note problems with equip-
ment, staff, or site obstacles, such as extensive cover,
high velocity current, excessive turbidity, floating
debris, deep muck or pools, or weather conditions.
Comments: Record any additional qualitative site
data: sketch map or photographs, presence of springs,
evidence of fishing activity, any potential or current
impacts, weather conditions (such as evidence of
recent high flows or unusually hot or cold weather
immediately preceding the survey), biota observed
(insect hatches, potential vertebrate predators, fish
nesting and grazing sites, fish reproductive condition,
fish seen but not captured).
Fish (preserved): Indicate if specimens were
preserved for permanent collection or further
examination.
Number of Individuals; Number of Anomalies:
Give total numbers of fish and anomalies for the
sample.
Genus/Species: Enter scientific name or unique stan-
dard abbreviation for each species captured.
A-4
-------
Adults (Number, Weight): Enter the number of adults
of each species and their total weight in grams. Weigh
individually or by batch, depending on the species'
size and abundance. Species weight can also be deter-
mined by weighing a subsample of individuals (20-30
fish spanning the size range collected) and extrapolat-
ing for the total number of that species.
Juveniles (Number, Weight): Record the number of
juveniles of each species and their total weight as
above. Juveniles and adults are distinguished subjec-
tively by coloration and size; the objective is to deter-
mine whether both age classes are present.
Anomalies (Number): Indicate the number of fish by
individual or species, that are diseased, deformed,
damaged, or heavily parasitized. These are determined
through careful external examination by a field-trained
fish biologist.
A.7 GUIDANCE FOR DATA
SUMMARY SHEET FOR FISH
RBP V
(Figure 7.2-5)
Station Number: Indicate station number.
Station Location: Record brief description of sam-
pling site relative to established landmarks (i.e.,
roads, bridges).
Metrics: List metrics used to conduct IBI calcula- -
tions. Use Karr's original metrics or published (or
well supported) substitutes. Precede metric selection
with analysis of reference site data or a high quality
historical database from a representative, large river
basin.
Scoring Criteria: List published scoring criteria or
use substitutes where necessary. Analyze reference site
data or historical data from a representative large
river basin before selecting criteria.
Metric Value: Record metric values (number or per-
cent) for the station. Metric values are obtained by
comparing the collection data (Figure 7.2-3) with the
tolerance and trophic guilds previously listed (e.g.,
Appendix D). For taxonomic metrics numbers of spe-
cies are added. Total number of individuals is
recorded from the field collection data sheet. Propor-
tional metrics are determined by adding the number of
individuals in each category and then dividing by the
total number of individuals.
Metric Score: Score each metric by comparing the
metric value for the station with the previously chosen
scoring criteria. Marginal values can be. given a plus
or minus (see IBI score below).
Scorer: Enter scorer's name.
IBI Score: The'metric scores (and pluses and
minuses if used) are added to give the IBI score.
Three pluses or three minuses may increase or
decrease the IBI score by two points.
Comments: Metrics producing contrary results or
suggestions for improvement are entered here.
A-5
-------
Waterbody Name.
Reach/Milepoint _
County
State.
Location.
Latitude/Longitude
Aquatic Ecoregion _
Station Number.
Date
Hydrologic Unit Code.
Reason for Survey
Time
Investigators.
Agency
Form Completed by.
Figure 2.6-1. Header information used for documentation and identification for sampling stations.
-------
Rapid Bioassessment Protocol I
Biosurvey Field Data Sheet
RELATIVE ABUNDANCE OF AQUATIC BIOTA
Perjphyton 0123
Filamentous Algae 0123
Macrophytes 0123
0 = Absent/Not Observed 1 = Rare
Slimes 0 1
Macroinvertebrates 0 1
Fish 0 1
2 = Common
3 = Abundant
234
234
234
4 = Dominant
MACROBENTHOS QUALITATIVE SAMPLE LIST(lndicate Relative Abundance R = Rare, C = Common, A = Abundant, 0 = Dominant)
Porifera
Hydrozoa
Platyhelminthes
Turbellaria
Hirudinea
Oligochaeta
Isopoda
Amphipoda
Decapoda
Gastropoda
Bivalvia
Anisoptera
Zygoptera
Hemiptera
Coleoptera
Lepidoptera
Sialidae
Corydalidae
Tipulidae
Empididae
Simuliidae
Tabanidae
Culicidae
Chironomidae
Plecoptera
Ephemeroptera
Trichoptera
Other
Rare < 3
Observations
Common 3-9
Abundant > 10
Dominant > 50 (Estimate)
Figure 6.1-1. Biosurvey Field Data Sheet for use with Rapid Bioassessment Protocol I.
A-7
-------
Rapid Bioassessment Protocol II
Biosurvey Field Data Sheet
RELATIVE ABUNDANCE OF AQUATIC BIOTA
Periphyton
Filamentous
Macrophytes
0 1
Algae 0 1
0 1
0 = Absent/Not Observed
2
2
2
1
3
3
3
= Rare
4 Slimes
0 1
4 Macroinvertebrates 0 1
4 Fish
2 = Common
0 1
3 = Abundant
2
2
2
3
3
3
4
4
4
4 = Dominant
MACROBENTHOS QUALITATIVE SAMPLE LIST
List Families Present/Indicate Abundance
Oligochaeta
Gastropoda
Bivalvia
Ephemeroptera
Anisoptera
Zygoptera
Plecoptera
Trlchoptera
Coleoptera
Diptera
Other
RIFFLE SAMPLE
FUNCTIONAL FEEDING GROUPS
(Indicate No. of Individuals Representing Group)
Scrapers
Filtering Collectors
CPOM SAMPLE FUNCTIONAL FEEDING GROUPS (Indicate No. of Individuals Representing Group)
Shredders
Total Org. in Sample
Observations
Figure 6.2-1. Biosurvey Field Data Sheet for use with Rapid Bioassessment Protocol II.
A-8
-------
Rapid Bioassessment Protocol III
Biosurvey Field Data Sheet
RELATIVE ABUNDANCE OF AQUATIC BIOTA
Periphyton 0
Filamentous Algae 0
Macrophytes 0
0 = Absent/Not Observed
1 2
1 2
1 2
1 = Rare
Slimes 0 1
Macroinvertebrates 0 1
Fish 0 1
2 = Common
3 = Abundant
2 34
2 34
234
4 = Dominant
MACROBENTHOS QUALITATIVE SAMPLE LIST(lndicate Relative Abundance R = Rare, C = Common, A = Abundant, D = Dominant)
Porifera
Hydrozoa
Platyhelminthes
Turbellaria
Hirudinea
Oligochaeta
Isopoda
Amphipoda
Decapoda
Gastropoda
Bivalvia
Anisoptera
Zygoptera
Hemiptera
Coleoptera
Lepidoptera
Sialidae
Corydalidae
Tipulidae
Empididae
Simuliidae
Tabanidae
Culicidae
Chironomidae
Plecoptera
Ephemeroptera
Trichoptera
Other
Rare < 3
Common 3-9
Abundant > 10
Dominant > 50 (Estimate)
CPOM SAMPLE FUNCTIONAL FEEDING GROUPS (Indicate No. of Individuals Representing Group)
Shredders
Total Org. in Sample
Observations
Figure 6.3-1. Biosurvey Field Data Sheet for use with Rapid Bioassessment Protocol III.
A-9
-------
IMPAIRMENT ASSESSMENT SHEET
1. Detection of impairment: Impairment detected No impairment
(Complete items 2-6) detected
(Stop here)
2. Biological impairment indicator:
Benthic macroinvertebrates Other aquatic communities
absence of EPT taxa Periphyton
dominance of tolerant groups filamentous
low benthic abundance other
low taxa richness Macrophytes
other Slimes
Fish
3. Brief description of problem:
Year and date of previous surveys:
Survey date, available in:
Cause: (indicate major cause) organic enrichment toxicants flow
habitat limitations other
2
Estimated areal extent of problem (m ) and length of stream reach
affected (m), where applicable:
6. Suspected source(s) of problem:
point source discharge (name, type of facility, location)
construction site runoff
combined sewer outfall
silviculture runoff
animal feedlot
agricultural runoff
urban runoff
ground water
other
unknown
Briefly explain:
Figure 6.1-2. Impairment Assessment Sheet for use with macroinvertebrate Rapid Bioassessment Protocols.
A-IO
-------
IMPAIRMENT ASSESSMENT SHEET
Detection of impairment: Impairment detected
(Complete Items 2-6)
No impairment
detected
(Stop here)
Biological impairment indicator:
Fish
sensitive species reduced/absent
dominance of tolerant species
skewed trophic structure
abundance reduced/unusually high
biomass reduced/unusually high
hybrid or exotic abundance
unusually high
poor size class representation
high incidence of anomalies
Brief description of problem:
Other aquatic communities
Macroinvertebrates
__ Periphyton
Macrophytes
Year and date of previous surveys:
Survey data available in:
Cause (indicate major cause): organic enrichment toxicants flow
sediment temperature poor habitat
other
Estimated areal extent of problem (m ) and length of stream reach
affected (m) where applicable:
Suspected source(s) of problem
point source
urban runoff
agricultural runoff
silvicultural runoff
livestock
landfill
mine
dam or diversion
channelization or snagging
natural
other
unknown
Comments:
Figure 7.2-1. Impairment Assessment Sheet for use with fish Rapid Bioassessment Protocol V.
A-ll
-------
DATA SUMMARY SHEET
Station No.
Station Location
Taxa Richness
FBI (modified)
Functional Feeding Groups
Riffle Community
Scrapers/Filt. Collect.
CPOM Community
Shredders/Total
EPT/Chironomidae
% Contribution (dom. family)
EPT Index
Community Similarity Index
Comments:
Figure 6.2-2. Data Summary Sheet suggested for use in recording benthic data utilized in Rapid Bioassessment Protocol
-------
DATA SUMMARY SHEET
Station No.
Station Location
Taxa Richness
FBI (modified)
Functional Feeding Groups
Riffle Community
Scrapers/Filt. Collect.
CPOM Community
Shredders/Total
EPT/Chironomidae
% Contribution (dom. family)
EPT Index
Community Similarity Index
Comments:
Figure 6.3-3. Data Summary Sheet suggested for use in recording benthic data utilized in Rapid Bioassessment Protocol III.
-------
LABORATORY BENCH SHEET
Number of Organisms
Station Number
Station Location
Species Name
•
-
Total Organisms
Number of Taxa
Figure. 6.3-2. Laboratory Bench Sheet suggested for use in recording benthic
data utilized in Rapid Bioassessment Protocol III.
A-14
-------
FISH FIELD COLLECTION DATA SHEET
page
of
Drainage
Date .
Sampling Duration (rain)
Sampling Distance (m) Sampling
Habitat Complexity/Quality (excellent
Veather Flow (floe
Gear Used Gear/Crev
Area (m ) rreu
good fair poor very poor)
d bankfull moderate lov)
Performance
Comments
Fish (preserved) Number of Individuals
Genus/Species Adults
Number of Anomalies
Juveniles Anomalies^ '
No. tft. No. tft. No.
(*) Discoloration, deformities, eroded fins, excessive mucus, excessive
external parasites, fungus, poor condition, reddening, tumors,
and ulcers
Figure 7.2-3. Fish Field Collection Data Sheet for use with Rapid Bioassessment Protocol V.
A-15
-------
Station No.
Site
Scoring Criteria(b)
Hetrics(a)
1. Nuaber of Native Fish Species
2. Nuaber of Darter or Benthic Species
3. Nuaber of Sunfish or Pool Species
4. Nuaber of Sucker or Long-Lived Species
5. Number of Intolerant Species
6. X Green Sunfish or Tolerant Individuals
7. X Oanivores
8. X Insectivores or Invertivores
9. Z Top Carnivores
10. Total Nunber of Individuals
11. t Hybrids or Exotics
12. X Anomalies
Scorer
Coaaents:
m
>67
>67
>67
>67
>67
<10
<20
>45
>5
>67
0
<1
3
~TCT
33-67
33-67
33-67
33-67
33-67
10-25
20-45
20-45
1-5
33-67
0-1
1-5
1
TZ~) Metric Value Metric Score
<33
<33
<33
<33
<33
>25
>45
<20
<1
<33
>1
>5
IBI Score
(a) Karr's original aetrics or commonly used substitutes.
ties.
(b) Karr's original scoring criteria or coanonly
ecoregions.
See text
used substitutes.
and Table 7.2-1 for other possibili-
These nay require refinement in other
Figure 7.2-5. Data Summary Sheet for Rapid Bioassessment Protocol V.
A-16
-------
APPENDIX B
RAPID BIOASSESSMgNT SUBSAMPLING METHODS FOR
BENTHIC PROTOCOLS II AND III
(100-Organism Count Technique)
-------
APPENDIX B
RAPID BIOASSESSMENT SUBSAMPLING METHODS FOR
BENTHIC PROTOCOLS II AND III
(100-Organism Count Technique)
B.1 RAPID BIOASSESSMENT
SUBSAMPLING METHODS FOR
PROTOCOL II
1. Thoroughly rinse sample in a (500-micron) screen
or the sampling net to remove fine sediments. Any
large organic material (whole leaves, twigs, algal or
macrophyte mats) should be rinsed, visually
inspected, and discarded.
2. Place sample contents in a large, flat pan with a
light-colored (preferably white) bottom. The bottom
of the pan should be marked with a numbered grid
pattern, each block in the grid measuring 5 cm x
5 cm. (Sorting using a gridded pan is only feasible
if the organism movement in the sample can be
slowed by the addition of club soda or tobacco to
the sample. If the organisms are not anesthetized,
100 organisms should be removed from the pan as
randomly as possible.) A 30 X 45 cm pan is
generally adequate, although pan size ultimately
depends on sample size. Larger pans allow debris
to be spread more thinly, but they are unwieldy.
Samples too large to be effectively sorted in a sin-
gle pan may be thoroughly mixed in a container
with some water, and half of the homogenized
sample placed in each of two gridded pans. Each
half of the sample must be composed of the same
kinds and quantity of debris and an equal number
of grids-must be sorted from each pan, in order to
ensure a representative subsample.
3. Add just enough water to allow complete dispersion
of the sample within the pan; an excessive amount
of water will allow sample material to shift within
the grid during sorting. Distribute sample material
evenly within the grid.
4. Use a random numbers table to select a number
corresponding to a square within the gridded pan.
Remove all organisms from within that square and
proceed with the process of selecting squares and
removing organisms until the total number sorted
from the sample is within 10 percent of 100. Any
organism which is lying over a line separating two
squares is considered to be in the square containing
its head. In those instances where it is not possible
to determine the location of the head (worms for
instances), the organism is considered to be in the
square containing the largest portion of its body.
Any square sorted must be sorted in its entirety,
even after the 100 count has been reached. In order
to lessen sampling bias, the investigator should
attempt to pick smaller, cryptk^ organisms as well
as the larger, more obvious organisms.
Source: Modified from Hilsenhoff 1987b.
B.2 RAPID BIOASSESSMENT
SUBSAMPLING METHODS FOR
PROTOCOL III
1. Thoroughly rinse sample in a No. 35 mesh
(500-micron) screen to remove preservative. Any
large organic material (whole leaves, twigs, algal or
macrophyte mats) not removed in the field should
be rinsed, visually inspected, and discarded. If the
samples have been preserved in alcohol, it will be
necessary to. soak the sample contents in water for
about 15 minutes to hydrate the benthic organisms,
preventing them from floating on the water surface
during sorting.
2. Place sample contents in a large, flat pan with a
light-colored (preferably white) bottom. The bottom
of the pan should be marked with a numbered grid
pattern, each block in the grid measuring 5 cm x
5 cm. A 30 X 45 cm pan is generally adequate,
although pan size ultimately depends on sample
size. Larger pans allow debris to be spread more
B-l
-------
thinly, but they are unwieldy. Samples too large to
be effectively sorted in a single pan may be
thoroughly mixed in a container with some water,
and half of the homogenized sample placed in each
of two gridded pans. Each half of the sample must
be composed of the same kinds and quantity of
debris and an equal number of grids must be
sorted from each pan, in order to ensure a
representative subsample.
3. Add just enough water to allow complete dispersion
of the sample within the pan; an excessive amount
of water will allow sample material to shift within
the grid during sorting. Distribute sample material
evenly within the grid.
4. Use a random numbers table to select a number
corresponding to a square within the gridded pan.
Remove all organisms from within that square and
proceed with the process of selecting squares and
removing organisms until the total number sorted
from the sample is within 10 percent of 100. Any
organism which is lying over a line separating two
squares is considered to be in the square containing
its head. In those instances where it is not possible
to determine the location of the head (worms for
instances), the organism is considered to be in the
square containing the largest portion of its body.
Any square sorted must be sorted in its entirety,
even after the 100 count has been reached. If many
of the organisms are very small and it appears that
the potential for missing individuals is great, an
illuminated 5X magnifier will facilitate the sorting
procedure.
Source: Modified from Hilsenhoff 1987b.
B-2
-------
APPENDIX C
FAMILY AND SPECIES-LEVEL
MACROINVERTEBRATE TOLERANCE CLASSIFICATIONS
-------
APPENDIX C
FAMILY AND SPECIES-LEVEL
MACROINVERTEBRATE TOLERANCE CLASSIFICATION
C.1 FAMILY-LEVEL
TOLERANCE CLASSIFICATION
average of tolerance values of species and genera
within each family based on their relative abun-
dance in Wisconsin.
RBP II is based on family-level identifications. The
adequate assessment of biological condition for RBP
II requires the use of a tolerance classification for
differentiating among responses of the benthic com-
munity to pollutants. Hilsenhoffs Family Biotic Index
(FBI) is used as a basis for the family-level tolerance
classification presented in this document.
A brief description of the FBI is taken from
Hilsenhoffs paper entitled "Rapid Field Assessment
of Organic Pollution with a Family Biotic Index"
(Hilsenhoff 1988). The family-level tolerance values
assigned for western Great Lakes region stream
arthropods are presented in Table C-l.
A special symposium on rapid biological assess-
ment at the 1986 meeting of the North American
Benthological Society stressed the need for rapid
field-based assessment approaches. It was recog-
nized that in order to save time, a degree of
accuracy would be sacrificed. Consequently, I
adapted the biotic index (BI) of organic pollution
(Hilsenhoff I987b) for rapid evaluation by providing
tolerance values for families (Table C-l) to allow a
family-level biotic index (FBI) to be calculated in
the field. The FBI is an average of tolerance values
of all arthropod families in a sample. It is not
intended as a replacement for the BI and can be
effectively used in the field only by biologists who
are familiar enough with arthropods to be able to
identify families without using keys.
Using the same method and more than 2,000
stream samples from throughout Wisconsin that
were used to revise tolerance values for species and
genera (Hilsenhoff 1987b) family-level tolerance
values were established by comparing occurrence of
each family with the average BI of streams in
which they occurred in the greatest numbers. Thus,
family-level tolerance values tend to be a weighted
C.2 GENUS/SPECIES-LEVEL
TOLERANCE CLASSIFICATION
The tolerance classification used in RBP III is
based on Hilsenhoff (1987b). Because Hilsenhoffs
tolerance classification is restricted to arthropods,
nonarthropod tolerance designations have been taken
from Bode (1988). Some of these tolerance values for
macroinvertebrates not listed in Hilsenhoff (1982,
1987b) are presented in Table C-2.
C.3 REFERENCES FOR
DETERMINING FAMILY AND
SPECIES-LEVEL TOLERANCE
CLASSIFICATIONS
Beck, W.M., Jr. 1977. Environmental Requirements
and Pollution Tolerance of Common Freshwater
Chironomidae. Environmental Monitoring and Sup-
port Laboratory, Report No. EPA-600/4-77-024.
U.S. EPA, Cincinnati.
Bode, R.W. 1988. Quality Assurance Workplan for
Biological Stream Monitoring in New York State.
New York State Department of Environmental Con-
servation, Albany, New York.
Dawson, C.L. and R.A. Hellenthal. 1986. A Com-
puterized System for the Evaluation of Aquatic
Habitats Based on Environmental Requirements and
Pollution Tolerance Association of Resident Organ-
isms. Report No. EPA-600/S3-86/019.
Harris, T.L. and T.M. Lawrence. 1978. Environmental
C-l
-------
TABLE C-l TOLERANCE VALUES FOR FAMILIES OF STREAM ARTHROPODS IN THE
WESTERN GREAT LAKES REGION (FROM HILSENHOFF 1988)
Plecoptera
Ephemeroptera
Odonata
Trichoptera
Megaloptera
Lepidoptera
Coleoptera
Diptera
Amphipoda
Isopoda
Capniidae 1, Chloroperlidae 1, Leuctridae 0,
Nemouridae 2, Perlidae 1, Perlodidae 2,
Pteronarcyidae 0, Taeniopterygidae 2
Baetidae 4, Baetiscidae 3, Caenidae 7, Ephemerellidae
1, Ephemeridae 4, Heptageniidae 4, Leptophlebiidae 2,
Metretopodidae 2, Oligoneuriidae 2, Polymitarcyidae
2, Potomanthidae 4, Siphlonuridae 7, Tricorythidae 4
Aeshnidae 3, Calopterygidae 5, Coenagrionidae 9,
Cordulegastridae 3, Corduliidae 5, Gomphidae 1,
Lestidae 9, Libellulidae 9, Macromiidae 3
Brachycentridae 1, Glossosomatidae 0, Helicopsychidae
3, Hydropsychidae 4, Hydroptilidae 4, Lepidosto-
matidae 1, Leptoceridae 4, Limnephilidae 4,
Molannidae 6, Odontoceridae 0, Philopotamidae 3,
Phryganeidae 4, Polycentropodidae 6, Psychomyiidae 2,
Rhyacophilidae 0, Sericostomatidae 3
Corydalidae 0, Sialidae 4
Pyralidae 5
Dryopidae 5, Elmidae 4, Psephenidae 4
Athericidae 2, Blephariceridae 0, Ceratopogonidae 6,
Blood-red Chironomidae (Chironomini) 8, other
(including pink) Chironomidae 6, Dolochopodidae 4,
Empididae 6, Ephydridae 6, Psychodidae 10, Simuliidae
6, Muscidae 6, Syrphidae 10, Tabanidae 6, Tipulidae 3
Gammaridae 4, Talitridae 8
Asellidae 8
C-2
-------
TABLE C-2 TOLERANCE VALUES FOR SOME MACROINVERTEBRATES NOT INCLUDED IN
HILSENHOFF (1982, 1987b>ra7; FROM BODE (1988)
Acariformes A
Decapoda 6
Gastropoda
Amnicola 8
Bithynia 8
Ferrissia 6
Gyraulus~ 8
Helisoma 6
Lymnaea 6
Physa 8
Sphaeriidae 8
Oligochaeta
Chaetogaster 6
Dero 10
Nais barbata 8
Nais behningi 6
Nais bretscheri 6
Nais communis 8
Nais elinguis 10
Nais pardalis 8
Nais simplex" 6
Nais variabilis 10
Pristina 8
Stylaria 8
Tubificidae
Aulodrilus 8
Limnodrilus 10
Hirudinea
Helobdella 10
Turbellaria A
(a) These values are for use with the biotic index scale of 0-10.
Additional tolerance values are available in Bode (1988).
C-3
-------
Requirements and Pollution Tolerance of Trichop-
tera. Report No. EPA-600/4-78-063. U.S. EPA,
Washington.
Hilsenhoff, W.L. 1982. Using a Biotic Index to Evalu-
ate Water Quality in Streams. Technical Bulletin
No. 132. Department of Natural Resources, Madi-
son, Wisconsin.
Hilsenhoff, W.L. 1987. An improved biotic index of
organic stream pollution. Great Lakes Entomologist
20:31-39.
Hilsenhoff, W.L. 1988. Rapid field assessment of
organic pollution with a family-level biotic index. J.
N. Am. Benthol. Soc. 7(l):65-68.
Hubbard, M.D. and W.L. Peters. 1978. Environmental
Requirements and Pollution Tolerance of
Ephemeroptera. Report No. EPA-600/4-78-061. U.S.
EPA, Washington.
Shackleford, B. 1988. Rapid Bioassessment of Lotic
Macroinvertebrate Communities: Biocriteria
Development. Arkansas Department of Pollution
Control and Ecology, Little Rock, Arkansas.
Surdick, R.F. and A.R. Gaufin. 1978. Environmental
Requirements and Pollution Tolerance of Plecop-
tera. Report No. EPA-600/4-78-062. U.S. EPA,
Cincinnati.
U.S. Department of Agriculture. 1985. Fisheries Sur-
vey Handbook, Aquatic Ecosystem Inventory,
Chapter 5 Aquatic Macroinvertebrate Surveys.
Document No. R-4 FSH 2609.23. U.S. Department
of Agriculture,' Forest Service, Ogden, Utah.
Weber, C.I. 1973. Biological Field and Laboratory
Methods for Measuring the Quality of Surface
Waters and Effluents. Report No. EPA-670/4-73-001.
U.S. EPA, Cincinnati.
Winget, R.N. and F.A. Mangum. 1979. Biotic Condi-
tion Index: Integrated Biological, Physical, and
Chemical Stream Parameters for Management. U.S.
Department of Agriculture, Forest Service, Ogden,
Utah.
C.4 A PARTIAL LISTING OF
AGENCIES THAT HAVE
DEVELOPED TOLERANCE
CLASSIFICATIONS AND/OR
BIOTIC INDICES
Florida Department of Environmental Regulation
Illinois EPA
New York Department of Environmental Conservation
North Carolina Department of Environmental
Management
Ohio EPA
U.S. Department of Agriculture, Forest Service,
Intermountain Region
U.S. EPA Region V
Vermont Department of Environmental Conservation
C-4
-------
APPENDIX D
TOLERANCE, TROPHIC GUILDS, AND
ORIGINS OF SELECTED FISH SPECIES
-------
APPENDIX D
TOLERANCE, TROPHIC GUILDS, AND
ORIGINS OF SELECTED FISH SPECIES
D.1 SPECIES-LEVEL FISH
TOLERANCE, TROPHIC, AND
ORIGIN CLASSIFICATIONS
Calculation of the IBI and assessment of biotic
integrity requires classification of fish species toler-
ances to an array of stressors and/or the species'
characteristic trophic guilds (Table D-l). Classifica-
tions for the Willamette River, Oregon were derived
from Wydoski and Whitney (1979), Moyle (1976), Scott
and Grossman (1973), Simpson and Wallace (1982),
Dimick and Merryfield (1945), and C.E. Bond (1988,
personal communication). Those for midwestern fishes
were taken from Karr et al. (1986) and Ohio EPA
(1987b). Classifications for other species and regions
can be developed using Lee et al. (1980), the regional
fish texts listed in Section D.2, and various journal
manuscripts, theses, and grey literature.
Agencies contemplating the development of
regional IBIs may wish to contact the author of this
protocol, authors of the IBI papers cited in Section 7,
or the State agencies now using the IBI (Section D.3)
for further guidance.
TABLE D-l TOLERANCE, TROPHIC GUILDS, AND ORIGINS OF SELECTED
FISH SPECIES^'
WILLAMETTE SPECIES
Salmonidae
Chinook salmon
Cutthroat trout
Mountain whitefish
Rainbow trout
Cyprinidae
Chiselmouth
Common carp
Goldfish
Leopard dace
Longriose dace
Northern squawfish
Peamouth
Redside shiner
Speckled dace
Catostomidae
Largescale sucker
Mountain sucker
Trophic Level
piscivore
insectivore
insectivore
insectivore
herbivore
omnivore
omnivore
insectivore
insectivore
piscivore
insectivore
insectivore
insectivore
omnivore
herbivore
Tolerance
intolerant
intolerant
intolerant
intolerant
intermediate
tolerant
tolerant
intermediate
intermediate
tolerant
intermediate
intermediate
intermediate
tolerant
intermediate
Origin
native
native
native
native
native
exotic
exotic
native
native
native
native
native
native
native
native
(a)Not necessarily the final designations; designations may vary for
different regions.
D-l
-------
TABLE D-l (Cont.)
Ictaluridae
Brown bullhead
Yellow bullhead
Percopsidae
Sand roller
Gasterosteidae
Threespine stickleback
Centrarchidae
Bluegill
Largemouth bass
Smallmouth bass
White crappie
Percidae
Yellow perch
Cottidae
Paiute sculpin
Prickly sculpin
Reticulate sculpin
Torrent sculpin
Trophic Level
insectivore
insectivore
insectivore
insectivore
insectivore
piscivore
piscivore
insectivore
insectivore
insectivore
insectivore
insectivore
insectivore
Tolerance
tolerant
tolerant
intermediate
intermediate
tolerant
tolerant
intermediate
tolerant
intermediate
intolerant
intermediate
tolerant
intolerant
Origin
exo tic
exotic
native
native
exotic
exotic
exotic
exo t i c
exotic
native
native
native
native
MIDWEST SPECIES
Petromyzontidae
Silver lamprey
Northern brook lamprey
Mountain brook lamprey
Ohio lamprey
Least brook lamprey
Sea lamprey
Polyodontidae
Paddlefish
Acipenseridae
Lake sturgeon
Shovelnose sturgeon
Lepisosteidae
Alligator gar
Shortnose gar
Spotted gar
Longnose gar
Amiidae
Bowfin
Hiodontidae
Goldeye
Mooneye
Clupeidae
Skipjack herring
Alewife
Gizzard shad
Threadfin shad
Salmonidae
Brown trout
piscivore
filterer
filterer
piscivore
filterer
piscivore
filterer
invertivore
insectivore
piscivore
piscivore
piscivore
piscivore
piscivore
insectivore
insectivore
piscivore
invertivore
omnivore
omnivore
insectivore
intermediate
intolerant
intolerant
intolerant
intermediate
intermediate
intolerant
intermediate
intermediate
intermediate
intermediate
intermediate
intermediate
intermediate
intolerant
intolerant
intermediate
intermediate
intermediate
intermediate
intermediate
native
native
native
native
native
exotic
native
native
native
native
native
native
native
native
native
native
native
exotic
native
native
exotic
D-2
-------
TABLE D-l (Cont.)
Rainbow trout
Brook trout
Lake trout
Coho salmon
Chinook salmon
Lake herring
Lake whitefish
Osmeridae
Rainbow smelt
Umbridae
Central mudminnow
Esocidae
Grass pickerel
Chain pickerel
Northern pike
Muskellunge
Cyprinidae
Common carp
Goldfish
Golden shiner
Horneyhead chub
River chub
Silver chub
Bigeye chub
Streamline chub
Gravel chub
Speckled chub
Blacknose dace
Longnose dace
Creek chub
Tonguetied minnow
Suckermouth minnow
Southern redbelly dace
Redside dace
Pugnose minnow
Emerald shiner
Silver shiner
Rosyface shiner
Redfin shiner
Rosefin shiner
Striped shiner
Common shiner
River shiner
Spottail shiner
Blackchin shiner
Bigeye shiner
Steelcolor shiner
Spotfin shiner
Bigmouth shiner
Sand shiner
Trophic Level
insectivore
insectivore
piscivore
piscivore
piscivore
piscivore
piscivore
' invertivore
insectivore
piscivore
piscivore
piscivore
piscivore
omnivore
omnivore
omnivore
insectivore
insectivore
insectivore
insectivore
insectivore
insectivore
insectivore
generalist
insectivore
generalist
insectivore
insectivore
herbivore
insectivore
insectivore
insectivore
insectivore
insectivore
insectivore
insectivore
insectivore
insectivore
insectivore
insectivore
insectivore
insectivore
insectivore
insectivore
insectivore
insectivore
Tolerance
intermediate
intermediate
intermediate
intermediate
intermediate
intermediate
intermediate
intermediate
tolerant
intermediate
intermediate
intermediate
intermediate
tolerant
tolerant
tolerant
intolerant
intolerant
intermediate
intolerant
intolerant
intermediate
intolerant
tolerant
intolerant
tolerant
intolerant
intermediate
intermediate
intolerant
intolerant
intermediate
intolerant
intolerant
intermediate
intermediate
intermediate
intermediate
intermediate
intermediate
intolerant
intolerant
intermediate
intermediate
intermediate
intermediate
Origin
exotic
native
native
exotic
exotic
native
native
exotic
native
native
native
native
native
exotic
exotic
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
D-3
-------
TABLE D-l (Cont.)
Mimic shiner
Ghost shiner
Blacknose shiner
Pugnose shiner
Silver jaw minnow
Mississippi silvery
minnow
Bullhead minnow .
Bluntnose minnow
Fathead minnow
Central stoneroller
Popeye shiner
Grass carp
Red shiner
Brassy minnow
Central silvery minnow
Catostomidae
Blue sucker
Bigmouth buffalo
Black buffalo
Smallmouth buffalo
Quillback
River carpsucker
Highfin carpsucker
Silver redhorse
Black redhorse
Golden redhorse
Shorthead redhorse
Greater redhorse
River redhorse
Harelip sucker
Northern hog sucker
White sucker
Longnose sucker
Spotted sucker
Lake chubsucker
Creek chubsucker
Ictaluridae
Blue catfish
Channel catfish
White catfish
Yellow bullhead
Brown bullhead
Black bullhead
Flathead catfish
Stonecat
Mountain mad torn
Slender mad torn
Freckled mad torn
Northern mad torn
Scioto mad torn
Trophic Level
insectivore
insectivore
insectivore
insectivore
insectivore
herbivore
omnivore
omnivore
omnivore
herbivore
insectivore
herbivore
omnivore
omnivore
herbivore
insectivore
insectivore
insectivore
insectivore
oranivore
omnivore
omnivore
insectivore
insectivore
insectivore
insectivore
insectivore
insectivore
invertivore
insectivore
omnivore
insectivore
insectivore
insectivore
insectivore
piscivore
generalist
insectivore
insectivore
insectivore
insectivore
piscivore
insectivore
insectivore
insectivore
insectivore
insectivore
insectivore
Tolerance
intolerant
intermediate
intolerant
intolerant
intermediate
intermediate
intermediate
tolerant
tolerant
intermediate
intolerant
intermediate
intermediate
intermediate
intolerant
intolerant
intermediate
intermediate
intermediate
intermediate
intermediate
intermediate
intermediate
intolerant
intermediate
intermediate
intolerant
intolerant
intolerant
intolerant
tolerant
intermediate
intermediate
intermediate
intermediate
intermediate
intermediate
intermediate
tolerant
tolerant
intermediate
intermediate
intolerant
intolerant
intolerant
intermediate
intolerant
intolerant
Origin
native
native
native
native
native
native
native
native
native
native
native
exotic
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
D-4
-------
TABLE D-l (Cont.)
Brindled madtorn
Tadpole madtorn
Anguillidae
American eel
Cyprinodontidae
Western banded
killifish
Eastern banded
killifish
Blackstripe topminnow
Poeciliidae
Mosquitofish
Gadidae
Burbot
Percopsidae
Trout-perch
Aphredoderidae
Pirate perch
Atherinidae
Brook silverside
Percichthyidae
White bass
Striped bass
White perch
Yellow bass
Centrarchidae
White crappie
Black crappie
Rock bass
Smallmouth bass
Spotted bass
Largemouth bass
Warmouth
Green Sunfish
Bluegill
Orangespotted sunfish
Longear sunfish
Redear sunfish
Pumpkinseed
Percidae
Sauger
Walleye
Yellow perch
Dusky darter
Blackside darter
Longhead darter
Slenderhead darter
River darter
Channel darter
Gilt darter
Logperch
Trophic Level
insectivore
insectivore
piscivore
insectivore
insectivore
insectivore
insectivore
piscivore
insectivore
insectivore
insectivore
piscivore
piscivore
piscivore
piscivore
invertivore
invertivore
piscivore
piscivore
piscivore
piscivore
invertivore
invertivore
insectivore
insectivore
insectivore
insectivore
insectivore
piscivore
piscivore
piscivore
insectivore
insectivore
insectivore
insectivore
insectivore
insectivore
insectivore
insectivore
Tolerance
intolerant
intermediate
intermediate
intolerant
tolerant
intermediate
intermediate
intermediate
intermediate
intermediate
intermediate
intermediate
intermediate
intermediate
intermediate
intermediate
intermediate
intermediate
intermediate
intermediate
intermediate
intermediate
tolerant
intermediate
intermediate
intolerant
intermediate
intermediate
intermediate
intermediate
intermediate
intermediate
intermediate
intolerant
intolerant
intermediate
intolerant
intolerant
intermediate
Origin
native
native
native
native
native
native
exotic
native
native
native
native
native
exotic
exotic
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
D-5
-------
TABLE D-l (Cont.)
Crystal darter
Eastern sand darter
Western sand darter
Johnny darter
Greenside darter
Banded darter
Variegate darter
Spotted darter
Bluebreast darter
Tippecanoe darter
Iowa darter
Rainbow darter
Orangethroat darter
Fantail darter
Least darter
Slough darter
Sciaenidae
Freshwater drum
Cottidae
Spoonhead sculpin
Mottled sculpin
Slimy sculpin
Deepwater sculpin
Gasterosteidae
Brook stickleback
Trophic Level
insectivore
insectivore
insectivore
insectivore
insectivore
insectivore
insectivore
insectivore
insectivore
insectivore
insectivore
insectivore
insectivore
insectivore
insectivore
insectivore
invertivore
insectivore
insectivore
insectivore
insectivore
insectivore
Tolerance
intolerant
intolerant
intolerant
intermediate
intermediate
intolerant
intolerant
intolerant
intolerant
intolerant
intermediate
intermediate
intermediate
intermediate
intermediate
intermediate
intermediate
intermediate
intermediate
intermediate
intermediate
intermediate
Origin
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
native
D-6
-------
D.2 SELECTED REFERENCES
FOR DETERMINING FISH
TOLERANCE, TROPHIC,
REPRODUCTIVE, AND ORIGIN
CLASSIFICATIONS
ALABAMA
Smith-Vaniz, W.F. 1968. Freshwater Fishes of
Alabama. Auburn University Agricultural Experi-
ment Station, Auburn, Alabama. 211 pp.
ALASKA
McPhail, J.D. and C.C. Lindsey. 1970. Freshwater
Fishes of Northwestern Canada and Alaska. Bulle-
tin No. 173. Fisheries Research Board of Canada.
381 pp.
Morrow, J.E. 1980. The Freshwater Fishes of Alaska.
Alaska Northwest Publishing Company, Anchorage,
Alaska. 300 pp.
ARIZONA
Minckley, W.L. 1973. Fishes of Arizona. Arizona
Game and Fish Department, Phoenix, Arizona.
293 pp.
ARKANSAS
Buchanan, T.M. 1973. Key to the Fishes of Arkansas.
Arkansas Game and Fish Commission Little Rock,
Arkansas. 68 pp., 198 maps.
CALIFORNIA
Moyle, P.B. 1976. Inland Fishes of California. Univer-
sity of California Press, Berkeley, California.
405 pp.
COLORADO
Beckman, W.C. 1953. Guide to the Fishes of
Colorado. Leaflet No. 11. University of Colorado
Museum. 110 pp.
Everhart, W.H. and W.R. Seaman. 1971. Fishes of
Colorado. Colorado Game, Fish and Parks Divi-
sion, Denver, Colorado. 77 pp.
CONNECTICUT
Whitworth, W.R., PL. Berrien, and W.T. Keller.
1968. Freshwater Fishes of Connecticut. Bulletin
No. 101. State Geological and Natural History Sur-
vey of Connecticut. 134 pp.
DELAWARE
Lee, D.S., S.P. Platania, C.R. Gilbert, R. Franz, and
A. Norden. In press. A Revised List of the Fresh-
water Fishes of Maryland and Delaware. Proceed-
ings of the Southeastern Fishes Council.
FLORIDA
Briggs, J.C. 1958. A list of Florida fishes and their
distribution. Bulletin of the Florida State Museum
1(8):223-318.
Gilbert, C.R., G.H. Burgess, and R.W. Yerger. In
preparation. The Freshwater Fishes of Florida.
GEORGIA
Dahlberg, M.D., and D.C. Scott. 1971. The Freshwater
Fishes of Georgia. Bulletin of the Georgia
Academy of Science 29:1-64.
IDAHO
Simpson, J.C. and R.L. Wallace. 1978. Fishes of
Idaho. The University of Idaho Press, Moscow,
Idaho. 237 pp.
ILLINOIS
Forbes, S.A. and R.E. Richardson. 1908. The Fishes
of Illinois. Illinois State Laboratory of Natural His-
tory. 357 pp., plus separate atlas containing 102
maps.
Forbes, S.A. and R.E. Richardson. 1920. The Fishes
of Illinois. Second edition. Illinois Natural History
Survey. 357 pp.
Smith, P.W. 1979. The Fishes of Illinois. Illinois State
Natural History Survey, University of Illinois Press,
Urbana, Illinois. 314 pp.
INDIANA
Gerking, S.D. 1945. The distribution of the fishes of
Indiana. Investigation of Indiana Lakes and Streams
3:1-137.
IOWA
Harlan, J.R. and E.B. Speaker. 1951. Iowa Fish and
Fishing. State Conservation Commission, State of
Idaho. 237 pp.
KANSAS
Cross, F.B. 1967. Handbook of Fishes of Kansas. Pub-
lic Education Series No. 3. University of Kansas
Museum of Natural History. 189 pp.
D-7
-------
KENTUCKY
Burr, B.M. In press. A distribution checklist of the
fishes of Kentucky. Brimleyana No. 3.
Clay, W.M. 1975. The Fishes of Kentucky. Kentucky
Department of Fish and Wildlife Resources, Frank-
ford, Kentucky. 416 pp.
LOUISIANA
Douglas, N.H. 1974. Freshwater Fishes of Louisiana.
Claitors Publishing Division, Baton Rouge, Loui-
siana. 443 pp.
MAINE
Everhart, W.H. 1966. Fishes of Maine. Third edition.
Maine Department of Inland Fisheries and Game,
Augusta, Maine. 96 pp.
MARYLAND
Lee, D.S., S.P. Platania, C.R. Gilbert, R. Franz, and
A. Norden. In press. A Revised List of the Fresh-
water Fishes of Maryland and Delaware. Proceed-
ings of the Southeastern Fishes Council.
MASSACHUSETTS
Mugford, PS. 1969. Illustrated Manual of Mas-
sachusetts Freshwater Fish. Massachusetts Division
of Fish and Game, Boston, Massachusetts. 127 pp.
MICHIGAN
t
Hubbs, C.L. and G.P. Cooper. 1936. Minnows of
Michigan. Bulletin of Cranbrook Institute Science
8:1-99.
Hubbs, C.L. and K.F. Lagler. 1946. Fishes of the
Great Lakes Region. Cranbrook Institute of
Science, Bloomfield Hills, Michigan. 186 pp.
Taylor, W.R. 1954. Records of fishes in the John N.
Lowe collection from the Upper Penninsula of
Michigan. Miscellaneous Publications of the
Museum of Zoology, University of Michigan
87:5-49.
MINNESOTA
Eddy, S. and J.C. Underbill. 1974. Northern Fishes,
with Special Reference to the Upper Missippi Val-
ley. University of Minnesota Press, Minneapolis,
Minnesota. 414 pp.
Phillips, G.L. and J.C. Underbill. 1971. Distribution
and variation of the Catostomidae of Minnesota.
Occasional Papers of the Bell Museum of Natural
History 10:1-45.
Underbill, J.C. 1957. The distribution of Minnesota
minnows and darters in relation to Pleistocene
glaciation. Occasional Papers of the Minnesota
Museum of Natural History 7:1-45.
MISSISSIPPI
Clemmer, G.H., R.D. Suttkus, and J.S. Ramsey. 1975.
A preliminary checklist of endangered and rare
fishes of Mississippi, in Preliminary List of Rare
and Threatened Vertebrates in Mississippi. Missis-
sippi Game and Fish Commission, pp. 6-22.
Cook, F.A. 1959. Freshwater Fishes in Mississippi.
Mississippi Game and Fish Commission, Jackson,
Mississippi. 239 pp.
MISSOURI
Pflieger, W.L. 1971. A distributional study of Missouri
Fishes. University of Kansas Museum of Natural
History, Publication 20(3):225-570.
Pflieger, W.L. 1975. The Fishes of Missouri. Missouri
Department of Conservation, Columbia, Missouri.
343 pp.
MONTANA
Brown, C.J.D. 1971. Fishes of Montana. Montana
State University, Bozeman, Montana. 207 pp.
NEBRASKA
Johnson, R.E. 1941. The Distribution of Nebraska
Fishes. Ph.D. dissertation. University of Michigan
Library.
Morris, J.L. Morris, and L. Witt. 1972. The Fishes of
Nebraska. Nebraska Game and Parks Commission,
Lincoln, Nebraska. 98 pp.
NEVADA
LaRivers, I. 1962. Fish and Fisheries of Nevada.
Nevada State Fish and Game Commission, Carson
City, Nevada. 782 pp.
NEW HAMPSHIRE
Scarola, J.F. 1973. Freshwater Fishes of New Hamp-
shire. New Hampshire Fish and Game Department,
Concord, New Hampshire. 131 pp.
NEW JERSEY
Stiles, E.W. 1978. Vertebrates of New Jersey. Edmund
W. Stiles Publishers, Somerset, New Jersey.
148 pp.
D-8
-------
NEW MEXICO
Koster, W.J. 1957. Guide to the Fishes of New Mex-
ico. University of New Mexico Press, Albuquer-
que, New Mexico. 116 pp.
NEW YORK
Greeley, J.R. 1927-1940. Watershed survey reports on
fishes of New York rivers, published as supple-
ments to the 16th through 29th Annual Reports of
the New York State Conservation Department,
Albany, New York.
Smith, C.L. In preparation. Inland Fishes of New
York.
NORTH CAROLINA
Menhinick, E.F., T.M. Burton, and J.R. Bailey. 1974.
An annotated checklist of the freshwater fishes of
North Carolina. Journal of the Elisha Mitchell
Scientific Society 90(1):24-50.
Menhinick, E.F. In preparation. The Freshwater
Fishes of North Carolina.
NORTH DAKOTA
Hankinson, T.L. 1929. Fishes of North Dakota.
Papers of the Michigan Academy of Science, Arts,
and Letters 10:439-460.
OHIO
Trautman, M.B. 1981. The Fishes of Ohio. Ohio State
University Press, Columbus, Ohio. 683 pp.
OKLAHOMA
Miller, R.J. and H.W. Robinson. 1973. The Fishes of
Oklahoma. Oklahoma State University Press, Still-
water, Oklahoma. 246 pp.
OREGON
Bond, C.E. 1973. Keys to Oregon freshwater fishes.
Technical Bulletin 58:1-42. Oregon State University
Agricultural Experimental Station, Corvallis,
Oregon.
PENNSYLVANIA
Cooper, E.L. In preparation. Fishes of Pennsylvania.
Fowler, H.W. 1940. A list of,the fishes recorded from
Pennsylvania. Bulletin of the Pennsylvania Board of
Fish Commission 7:1-25.
SOUTH CAROLINA
Anderson, W.D. 1964. Fishes of some South Carolina
coastal plain streams. Quarterly Journal of the
Florida Academy of Science, 27:31-54.
Loyacano, H.A. 1975. A List of Freshwater Fishes of
South Carolina. Bulletin No. 580. South Carolina
Agricultural Experiment Station.
SOUTH DAKOTA
Bailey, R.M. and M.O. Allum. 1962. Fishes of South
Dakota. Publication No. 119. Miscellaneous Publi-
cations of the Museum of Zoology, University of
Michigan. 131 pp.
TENNESSEE
Etnier, DA. and W.C. Starnes. In preparation. The
Fishes of Tennessee.
Kuhne, E.R. 1939. A Guide to the Fishes of Tennes-
see and the Mid-South. Tennessee Department of
Conservation, Nashville, Tennessee. 124 pp.
TEXAS
Hubbs, C. 1972. A checklist of Texas freshwater
fishes. Texas Parks and Wildlife Department Tech-
nical Service 11:1-11.
Knapp, FT. 1953. Fishes Found in the Fresh Waters
of Texas. Ragland Studio and Lithograph Printing
Company, Brunswick, Georgia. 166 pp.
UTAH
Sigler, W.F. and R.R. Miller. 1963. Fishes of Utah.
Utah Game and Fish Department, Salt Lake City,
Utah. 203 pp.
VERMONT
MacMartin, J.M. 1962. Vermont stream survey
1952-1960. Vermont Fish and Game Department,
Montpelier, Vermont. 107 pp.
VIRGINIA
Jenkins, R.E., N.M. Burkhead, and D.J. Jenkins. In
preparation. The Freshwater Fishes of Virginia.
WASHINGTON
Wydoski, R.S. and R.R. Whitney. 1979. Inland Fishes
of Washington. University of Washington Press.
220 pp.
WEST VIRGINIA
Denoncourt, R.F., B.C. Raney, C.H. Hocutt, and
J.R. Stauffer, Jr. 1975. A checklist of the fishes of
West Virginia. Virginia Journal Science
26(3):117-120.
Hocutt, C.H., R.F. Denoncourt, and J.R. Stauffer, Jr.
1979. Fishes of the Gauley River, West Virginia.
Brimleyana 1:47-80.
D-9
-------
WISCONSIN
Becker, G.C. 1983. Fishes of Wisconsin. University of
Wisconsin Press, Madison, Wisconsin. 1052 pp.
WYOMING
Baxter, G.T. and J.R. Simon. 1970. Wyoming Fishes.
Bulletin No. 4. Wyoming Game and Fish Depart-
ment. Cheyenne, Wyoming. 168 pp.
CANADA
McPhail, J.D. and C.C. Lindsey. 1970. Freshwater
Fishes of Northwestern Canada and Alaska. Bulle-
tin No. 173. Fisheries Research Board of Canada.
381 pp.
Scott, W.B. and E.J. Grossman. 1973. Bulletin No.
1984. Freshwater Fishes of Canada. Fisheries
Research Board of Canada. 866 pp.
Walters, V. 1955. Fishes of Western Arctic America
and Alaska. Bulletin of the American Museum of
Natural History 106:259-368.
EASTERN CANADA
Hubbs, C.L. and K.F. Lagler. 1964. Fishes of the
Great Lakes Region. University of Michigan Press,
Ann Arbor, Michigan. 213 pp.
McAllister, D.E. and B.W. Coad. 1974. Fishes of
Canada's National Capital Region. Special Publica-
tion 24. Fisheries and Marine Service. 200 pp.
ALBERTA
Paetz, M.J. and J.S. Nelson. 1970. The Fishes of
Alberta. Queen's Printer, Edmonton, Alberta. 282
pp.
BRITISH COLUMBIA
Carl, G.C., W.A. Clemens, and C.C. Lindsey. 1967.
The Freshwater Fishes of British Columbia. Fourth
edition. Handbook No. 5. British Columbia Provin-
cial Museum. 192 pp.
Hart, J.L. 1973. Pacific Fishes. Second edition. Bulle-
tin No. 180. Fisheries Research Board of Canada.
740 pp.
MANITOBA
Fedoruk, A.N. 1969. Checklist and Key of the Fresh-
water Fishes of Manitoba. Manitoba Department of
Mines and Natural Resources, Canada Land Inven-
tory Project. 98 pp.
Hinks, D. 1943. The Fishes of Manitoba. Manitoba
Department of Mines and Natural Resources.
102 pp.
NEW BRUNSWICK
Gorham, S.W. 1970. Distributional Checklist of the
Fishes of New Brunswick. Saint John, New Brun-
swick. 32 pp.
Scott, W.B. and E.J. Grossman. 1959. The Freshwater
Fishes of New Brunswick. A checklist with dis-
tributional notes. Contribution No. 51. Royal
Ontario Museum, Division of Zoology and
Palaeontology. 37 pp.
NORTHWEST TERRITORIES
Stein, J.N. C.S. Jessop, T.R. Porter, and K.T.J.
Chang-Kue. 1973. An Evaluation of the Fish
Resources of the McKenzie River Valley as Related
to Pipeline Development. Volume 1. Report 73-1.
Information Canada Catalogue Number
Fs37-1973/l-l. Environmental-Social Committee
Northern Pipelines, Task Force on Northern
Development. 122 pp;
NOVA SCOTIA
Gilhen, J. 1974. The Fishes of Nova Scotia's Lakes
and Streams. Nova Scotia Museum, Halifax. 49 pp.
Livingstone, D.A. 1951. The Freshwater Fishes of
Nova Scotia. Nova Scotian Institute of Science
Proceedings. 23:1-90.
ONTARIO
MacKay, H.H. 1963. Fishes of Ontario. Ontario
Department of Lands and Forest. 360 pp.
Ryder, R.A., W.B. Scott, and E.J. Grossman. 1964.
Fishes of Northern Ontario, North of the Albany
River. Life Sciences Contribution, Royal Ontario
Museum. 30 pp.
QUEBEC
Legendre, V. 1954. Key to Game and Commercial
Fishes of the Province of Quebec. First English
edition. Quebec Department of Game and Fisher-
ies. 189 pp.
Masse G., et J. Mongeau. 1974. Repartition Geograp-
hique des Poissons, leur abondance relative et
bathymetric de la region du Lac Saint-Pierre. Ser-
vice de lAmenagement de la Faune, Ministere du
Tourisme, de la Chasse et de la Peche, Quebec.
59 pp.
Melancon, C. 1958. Les Poissons de nos Eaux. Third
edition. La Societe Zoologique de Quebec, Quebec.
254 pp.
D-10
-------
Mongeau J., A. Courtemanche, G. Masse, et Bernard
Vincent. 1974. Cartes de repartition geographique
des especes de poissons au sud du Quebec, d'apres
les inventaires ichthyologiques effectues de 1963 a
1972. Rapport Special 4, Faune du Quebec. 92 pp.
Mongeau J., et G. Masse. 1976. Les poissons de la
region de Montreal, la peche sportive et cornmer-
ciale, les ensemencements, les frayeres, la contami-
nation par le mercure et les PCB. Service de
I'Amegagement de la Faune, Ministere du
Tourisme, de la Chasse et de la Peche, Quebec.
286 pp.
SASKATCHEWAN
Symington, D.F. 1959. The Fish of Saskatchewan.
Conservation Bulletin No. 7. Saskatchewan Depart-
ment of Natural Resources. 25 pp.
YUKON TERRITORY
Bryan, I.E. 1973. The influence of pipeline develop-
ment on freshwater fishery resources of northern
Yukon Territory. Aspects of research conducted in
1971 and 1972. Report No. 73-6. Information
Canada Catalogue Number R72-9773.
Environmental-Social Committee Northern Pipe-
lines, Task Force on Northern Development. 63 pp.
GENERAL
Grossman, E.J. and H.D. VanMeter. 1979. Annotated
List of the Fishes of the Lake Ontario Watershed.
Technical Report 36. Great Lakes Fishery Commis-
sion, Ann Arbor, Michigan.
Eddy, S. and T. Surber. 1947. Northern Fishes with
Special Reference to the Upper Mississippi Valley,
2nd edition. University of Minnesota Press. Second
edition. Minneapolis, Minnesota. 267 pp.
Hocutt, C.H. and E.O. Wiley. 1986. The Zoogeogra-
phy of North American Freshwater Fishes. John
Wiley and Sons, New York.
Hubbs, C.L. and K.F. Lagler. 1947. Fishes of the
Great Lakes Region. The Cranbrook Press, Bloom-
field Hills, Michigan. 186 pp.
Jenkins, R.E., E.A. Lachner, and F.J. Schwartz. 1972.
Fishes of the central Appalachian drainages: Their
distribution and dispersal, in The Distributional
History of the Biota of the Southern Appalachians.
Part III: Vertebrates (P.C. Holt, ed.), Research
Division Monograph 4. Virginia Polytechnic Insti-
tute and State University, Blacksburg, Virginia.
Lee, D.S., C.R. Gilbert, C.H. Hocutt, R.E. Jenkins,
D.E. McAllister, and J.R. Stauffer, Jr. 1980. Atlas
of North American Freshwater Fishes. North Caro-
lina Museum of Natural History, Raleigh, North
Carolina.
Metcalf, A.L. 1966. Fishes of the Kansas River sys-
tem in relation to zoogeography of the Great
Plains. Publication of the Museum of Natural His-
tory, University of Kansas 17(3):23-189.
Miller, R.R. 1948. The Cyprinodont fishes of the
Death Valley system of eastern California and south-
western Nevada. Miscellaneous Publication of the
Museum of Zoology, University of Michigan
68:1-55.
Miller, R.R. 1959. Origin and Affinities of the Fresh-
water Fish Fauna of Western North America. Zoo-
geography Publication Number 51. American
Association for the Advancement of Science,
Washington, D.C.
Rostlund, E. 1952. Freshwater fish and fishing in
native North America. University of California
Geography Publications 9:1-313.
Seehorn, M.E. 1975. Fishes of Southeastern National
Forests. Proceedings 29th Annual Conference
Southeastern Association Game Fish Commissions,
pp. 10-27.
Soltz, D.L. and R.J. Naiman. 1978. The natural his-
tory of native fishes in the Death Valley system.
Natural History Museum of Los Angeles County.
Science Series 30:1-76.
D.3 AGENCIES CURRENTLY
USING OR EVALUATING USE OF
THE IBI FOR WATER QUALITY
INVESTIGATIONS
Alabama Geological Survey (Scott Mettee)
Illinois Environmental Protection Agency (Bob Hite)
Iowa Conservation Commission (Vaughn Paragamian)
Kansas Department of Wildlife and Parks
(L. Zuckerman)
D-ll
-------
Kansas Department of Health and Environment
(S. Haslover)
Kentucky Cabinet for Natural Resources and Environ-
mental Protection (Mike Mills)
Nebraska Department of Environmental Control (Terry
Maret)
North Carolina Division of Environmental Manage-
ment (Vince Schneider)
Ohio Environmental Protection Agency (Ed Rankin)
Oklahoma State Department of Health (Jimmy Pigg)
Tennessee Valley Authority (Neil Carriker)
U.S. EPA Region II (Jim Kurtenbach)
U.S. EPA Region I (Jim Luey)
Vermont Department of Environmental Conservation
(Rich Langdon)
Wisconsin Department of Natural Resources (Steve
Lyons)
D-12
• U.S.GOVERNMENT PRINTING OFFICE:! 9 92 -750 -0 02/60070
------- |