&EPA
            United States       Office of
            Environmental Protection   Water
            Agency         (WH-553)
                        EPA/444/4-89-001
                        May 1989
Rapid Bioassessment
Protocols
For Use In Streams And
Rivers

Benthic Macroinvertebrates
And Fish

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    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

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                              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.

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                                           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.
                                                      m

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                                  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.

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                                TABLE  OF  CONTENTS
                                                                                              Page

FOREWORD	     iii

ACKNOWLEDGMENTS	      v

LIST OF FIGURES	     xi

LIST OF TABLES	    xv

1. INTRODUCTION	    11
   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 Particulate 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
                                                vu

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   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. BENTfflC  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 ffil 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

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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.I Guidance for Header Information	   A-l
              A.2 Guidance for Biosurvey Field Data Sheet for Benthic RBPs I, II, and HI	   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 in	   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 HI (100-Organism Count Technique)
              B. 1 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

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                                      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 n	     6-6

6.2-2  Data  Summary Sheet  suggested for use  in  recording benthic data utilized in Rapid  Bioassessment
       Protocol H	     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 HI	    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

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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
                                                       xn

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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
                                                        xni

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                                       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 in	    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 Nummary of metric values, percent comparison, and bioassessment scores for Ararat and Mitchell Rivers
       benthic case-study data	    8-18

C-1    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

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                                     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
other 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 III.
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.
                                                    1-1

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    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 Howland,  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

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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

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                                     Assessment of
                           Impairment of Biological Integrity
                   (Not Human Health, Recreation or Aesthetics)^)
               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)
 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

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                   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 parameter. 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

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 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; Kan-
 el 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

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   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,
   coolwater, 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

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         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); USDATSoil 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

-------
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nxvn*mt R«»«ircfi LKxxMory US EfMtfonnwrTtml PmMacn Af^ncv [ *« | BUJt WOOf UOUMT1JKS [ II 1 CEKTRM. w**tjM>«jw noau L" J *M>«ii£V» nn»^- CE3- [] i* j FIOIWO* CO*SI*i 1»V 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 BENTfflC  COMMUNITY
            CONSIDERATIONS


            2.7.1 Seasonally for
             Benthic Collections

    Rapid bioassessment is based on evaluation of rela-*
 lively few samples at a site. Seasonality is particularly
 important when only a few collection sites are
 involved. The intent of the  benthic rapid bioassess-
                                                   2-6

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                                  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

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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.

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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 nonpoint-
 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,
 whererimpairment 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

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                                                                                                                                                           Boston, Mass.
                                                                                                                                                    New York, N.Y.
                                                                                                                                                 Philadelphia, Pa.
to
            fill = Mediterranean



            \—I = Humid Continental



            ['•:•] = Humid Subtropical



            0 = Highlands
                                             Figure 2.7-1. Classification of U.S. climatological regions. (Taken from Gabler et al. 1976.)

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   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 thpt, 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 ingestjon 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

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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-
ments. 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 ni 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.

      2.1 A   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 Hilsenhoff s 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 Hilsenhoff s when
evaluating nonpoint-source problems.
        2.8  FISH COMMUNITY
            CONSIDERATIONS


 2.8.1  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 al. (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

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   2X2  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.

2X2.2 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

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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 IBI 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 lexicological
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
IBFs basic theoretical foundations.
                                                   2-14

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                     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
HI, 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,  HI,
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, HI
and V is  the level of taxonomic resolution  (i.e.,
family level vs. genus/species level identification)
necessary to perform an assessment. RBPs HI and V
require more time and expertise than RBP n, 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 n and intended to promote a consis-
tent level of effort, allows for better comparison
among sites.
   The primary objective of benthic RBP in 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 in 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 in 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

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                                                TABLE  3.1-1   COMPARISON  OF RAPID BIOASSESSMENT  PROTOCOLS
                                  Protocol  I
        Objectives
        Level of Effort
        {per stat ion)
        Experience
        Required
t
        Minimal  skill Mix
        Habitat  Assessment
        Water Quality and
        Phys/Chem
                              Determine whether
                              biological  impair-
                              ment 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  l.S
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
                                                           Protocol  II
                                                                                   Protocol III
                                                                                                             Protocol IV
                                                                                                                                      Protocol V
                       .  Assess  biological
                         impairment
                       .  Provide information
                         for ranking sites
                       .  Prioritize  sites  for
                         further assessment
                         and/or  testing
                         (toxicity,  chemical)
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
subst rate/inst ream
cover, channel
morphology, and
riparian/bank
atructure

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,
                         chemica1)
Field—1 to 2 hours/
person (2 persons)
Lab—2 to 3 hours
(1 pe rson)

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
riparian/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
Characterize and rate
substrate/instream
cover, channel
morphology, and
riparian/bank
st ructure

Measure conventional
water quality
parameters
Examine physical
characteristics
Assess biological
impai rment
Establish basis for
trend monitoring
Provide information
for ranking sites
Prioritize for
further assessment
and/or testing
(toxicity, chemical)

Field—1-5 hours/
person
(2 persons minimum)
Lab—None

Data—1-2 hours
(1 pe rson)
Budget—Total of 3 to
17 work hours

Professional impact
assessment experience
Knowledge in the use
of the IBI and IWB
Biologist and
technicianls)

Characterize and rate
substrate/instream
cover, channel mor-
phology, and
riparian/bank
structure

Measure conventional
water quality
parameters
Examine physical
characteristics

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                                                            TABLE  3.1-1   (Cont.)
                          Protocol I
                                                  Protocol II
                                                                           Protocol III
                                                                                                     Protocol  IV
                                                                                                                               Protocol  V
Biosurvey
Cursory examination
Determine relative
abundance of •aero-
benthos; field IDs
                                              Examination focusing
                                              on the  riffle/run
                                              comauni ty,
                                              suppleaented with a
                                              CPOH sample
                                              100-organisa sub-
                                              saaple  IDed in field
                                              to family or order
                                              level
                                              Functional Feeding
                                              Group analysis of
                                              riffle/run and CPOH
                                              saaple  in the field
                         Examination focusing
                         on the riffle/run
                         community,
                         supplemented with a
                         CPOM sample
                         Collect riffle/run
                         benthos;  collect CPOH
                         sample, determine
                         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
Conclus ion
Minimal; determine
presence or absence
of impairment
                      Determine  if  impair-
                      ment exists
                      Indicate generic
                      cause of impairment
                      (habitat,  organic
                      enrichment,
                      toxicity)
Integrated assessment
of aetrics measuring
various components of
family level com-
munity structure
                        Characterize
                        conditions as no
                        impairment, aoderate
                        impairaent, severe
                        impairment
                        Indicate generic
                        cause of impairment
                        (habitat, organic
                        enrichment, toxicity)
Integrated assessment
of metrics measuring
various components of
genus/species level
community structure
                         Evaluate site as no
                         impairaent,  slight
                         impairment,  moderate
                         impairaent,  severe
                         iapai rment
                         Indicate generic cause
                         of impairment
                         (habitat,  organic
                         enrichment,  toxicity)
Suamarize survey
responses to deter-
aine degree and
probable cause of
iapa i raent
                          Deteraine if iapair-
                          aent exists
                          Indicate generic
                          cause of impairment
                          (habitat, water
                          quality)
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
            SITE RANKING
                                                    Level One
-Focus on
 Communities
-Three Levels
 of Impairment
 Detected
                            Level Two
                                 I
-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

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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

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            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

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    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

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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 investigators 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

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                          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

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                                               PHYSICAL  CHABACTEBIIATIOH/VATEB QUALITY
                                                          FIELD DATA SHEET
PHYSICAL CBABACTEBIXATXOa

BIPABIAH lOHE/IBSTBEAM fEATUBES

Pradoainant Surrounding Land Uaa:

forast      Flald/Paatura      Agricultural       Baaidantial      Coaaarcial

Local Matarshad Eroalon:  Hona    Hodarata     Haavy

Local tfatarahad BPS Pollution:   Bo avidanca     Soaa  Potantlal Sourcas     Obvio

Eatiaatad Straaa Width 	 n  Estiaatad Straaa Dapth:   Biftla _____ *   Bun 	

High Watar Hark 	 n   Valocity 	    Daa Praaant:   Yaa 	   Bo

                          Partly Opan       Partly shadad       shadad
                                                                                  Industrial
                                                                              channallaad:  Taa
 Canopy Covar:   Opan

 SEDIMEBT/SUaSTBATE;

 Sadiaant odora:  Horaial

 Sadiaant oils:   Abaant
                             Sawaga      Patrolaua       Cbanical

                            Slight     Hodarata       Profuaa
                                                                     Anaarobic
Sadiaant Daposits: Sludaa Sawdust Papar ribar Sand Ballet Shalla othar
Ara tha undaraidaa of atouaa which ara not daaply a»t»ddad black7 Yaa Ho
Substrata Typa
•adrock
Bouldar
Cobbla
Oraval
Sand
Silt
Clay
Parcant
COBpoait ion
>»«-•• (10 in.)
«4-2S6-n (J.5-10 in.)
2-C4-U (0.1-2.5 in.)
0.06-2.00-M (gritty)
.00«-.OC-u
<.004-M (alick)

Datrltua Sticks, Wood,
Coaraa Plant
Matarials (CPOH)
Muck-Mud Black, Vary rina
Organic (rpOH)
Marl Oray, Shall
rragaanta
Parcant
Composition
in Sanplin^ Araa


WATEB QUALITY
C Disaolvad oxygan pH Conductivity Otbar

Inatruaantla) Uaad
Straaa Typa:  Coldwatar       Warawatar

Watar Odors:  Boraal      Sawaga      Patrolaua     cbaaical      Hona      othar

Watar Surlaca of la:   slick      Shaan      Globa      riacka      Boaa

Turbidity:  claar      slightly Turbid      Turbid      Opa.ua      Watar Color  	
WEATHEB COHDITIORS
FHOTOOBAPH BUHSEB
OB1EBVATIOHS ABD/OB SKETCH
     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

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                                                                             Condition
                  Condition/Parameter
        Excellent    Good
          Fair
  PRIMARY—SUBSTRATE AND EVSTREAM 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
          16-20       11-15      6-10
          16-20       11-15      6-10
          16-20       11-15      6-10
          12-15
          12-15
          12-15


          9-10
          9-10
          9-10
8-11
8-11
8-11


6-8
6-8
6-8
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.

1.  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

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                                                 HABITAT ASSESSMENT  FIELD  DATA  SHEET
Habitat Parameter
                                                                           Ca teg o ry
                                     Excel lent
                                                                 Good
                                                                                              Fair
                                                                                                                       Poo r
1.  * Bottom substrate/
    available cover
Greater than 50% rubble,
gravel, submerged logs,
undercut banks, or
other stable habitat.
                 16-20
30-50% rubble, gravel
or other stable habitat.
Adequate habitat.

                  11-15
                                                     10-30%  rubble,  gravel
                                                     or  other  stable habitat.
                                                     Habitat  availability
                                                     less  than  desirable.
                                                                       6-10
                                                     Less  than 10% rubble
                                                     gravel  or other stable
                                                     habitat.   Lack  of
                                                     habitat  is  obvious.
                                                                        0-5
2. Erabeddednes s Gravel, cobble
between 0 a
surrounded
sediment

3. <0.15 cms (Sets) • Cold >0.05
•Flow at rep. low Warn >0.15
flow'41
nd
by


ens
ens

, and
25 *
fine


(2
(5


16-20
cfs)
cfs )
10-20
Gravel, cobble
between 25 and
surrounded by
sediment

0.03-0.05 cms
0.05-0.15 cms

, and
50
fine


(1-2
(2-5

t

11-15
cfs)
cfs)
11-15
Gravel, cobble
between 50 and
surrounded by
sediment

0.01-0.03 cms
0.03-0.05 cms

, and
fine

6-10
( .5-1 cfs)
11-2 cfs)
6-10
Gravel ,
by fine


cobbl e , and
sediaen t




0-5
<0 .01 cms ( .5 cfs )
<0.03 cms (1 cfs)


0-5
     >0 . 15  cms  (5cfs}
     Velocity/depth
Slow (< 0 . 3 ra/s),  deep
(>0.5 m);  slow,  shallow
(<0.5 m);  fast
( >0 . 3 m/s), deep; fast,
shallow habitats  all
pres ent.
                 16-20
Only 3 of the^4 habitat
categories present
(missing riffles or runs
receive lower score than
missing poo Is).

                  11-15
                                                     Only 2 of the 4 habitat
                                                     categories present
                                                     (missing riffles/runs
                                                     receive lower score).
                                                                                                      6-10
                                                     Dominated by one
                                                     velocity/depth
                                                     category  (usually
                                                     poo 1 ) .
                                                                                                                                0-5
       Channel  alteration
                               Little  or  no  enlarge-
                               ment  of  islands  or
                               point bars,  and/o r
                               no  channelization.
                          Sono new increase in bar
                          formation, mostly fron
                          coarse gravel; a nd/o r
                          some channelization
                          pres ent .

                                             8-11
                            Moderate deposition of
                            new gravel,  coarse sand
                            on  old and new bars;
                            pools  partially filled
                            w/s ilt;  and/or embank —
                            ments  on both banks.
                                               4-7
                                                                              Heavy deposits  of  fine
                                                                              material, increased  bar
                                                                              development; most  pools
                                                                              filled w/silt;  and/or
                                                                              extensive channelization.

                                                                                                 0-3
 5.   Bottom scouring and
     depos i tion
Less  than  5%  of  the
bottoB  affected  by
scour ing and
deposition.
                         5-30%  affected.   Scour
                         at constrictions  and
                         where  grades  steepen.
                         Some deposition  in  pools.
                            30-50%  affected.
                            Deposits  and  scour  at
                            obstructions,  con-
                            strictions  and bends.
                            Some  filling  of pools.
                                                                                                       4-7
                                                     More  than  50%  of  the
                                                     bottom  changing
                                                     nearly  year  long.
                                                     Pools almost absent
                                                     due  to  deposition.
                                                     Only  la rge  rock s
                                                     in  riffle  exposed.
 (a f   From Ball 1982.
 (b)   From Platts et al. 1983.
 Note:   *  = Habitat parameters not  currently  incorporated  into BIOS
                     Figure 5.2-1.  Habitat Assessment Field Data Sheet for use with all Rapid Bioassessment Protocols.

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                                             HABITAT  ASSESSMENT  FIELD DATA  SHEET  Icont . ]
                                                                          Ca t ego ry


                                                                 Good
                                                                                             Fair
                                                                                                                      Poor
6.  Pool/riffle,  run/bend
    ratio13   (distance
    between riffles divided
    by stream width)
5-7.   Variety of
habitat.  Deep riffles
and -pools .
                                                12-15
7-15.  Adequate depth
in pools and riffles.
Bends provide habitat.
                                                                           8-11
15-25.  Occassional
riffle or bend.  Bottom
contours provide some
habitat .
                                                                                                      4-7
                                                                             >25.  Essentially a
                                                                             straight stream.
                                                                             Generally all flat
                                                                             water or shallow
                                                                             riffle.   Poor
                                                                             habitat.
                                                                                                                               0-3
7.  Bank stability
                   *3'
9.  St reams ide cover

Stable.   No evidence
of erosion or
bank failure.
Side slopes gener-
ally <30%.  Little
potential for future
p roblem.
                                                 9-10
Mode rat ely stable .
Infrequent, small areas
of erosion mostly healed
over.  Side slopes  up to
40% on one bank.  Slight
potential in extreme
floods .

                    6-8
                                                    Moderately unstable.
                                                    Moderate frequency and
                                                    size of erosional areas.
                                                    Side slopes up to 60%
                                                    on some banks.  High
                                                    erosion potential
                                                    during extreme high
                                                    flow.
                                                                       3-5
                         Unstable.  Many
                         eroded areas.  Side
                         slopes >60t common.
                         "Raw" areas frequent
                         along straight sections
                         and bends .
                                                                                                                               0-2
8. Bank vegetative
stability
Over 80% of
covered by
vegetat ion
and cobble'.
the
or boulders
9-10
50-79* of the

streambank

larger material.
6-8
25-49% of
the
by vegetat ion


stream-
, gravel ,
3-5
Less than
covered by
gravel , or
material .
25% of the
vegetat ion
la rge r
0-
2
                              Dominant  vegetation
                              is shrub.
Dominant vegetation
is of tree form.
Dominant vegetation
is grass or forbes.
                                                 9-10
                                                                                                      3-5
                                                                             Over 50% of the stream-
                                                                             bank, has no vegetation
                                                                             and dominant material
                                                                             is soil, rock, bridge
                                                                             materials, culverts,
                                                                             or mine tailings.
                                                                                                0-2
Column Totals
                                                        Figure 5.2-1.  (Cont.).

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   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
   (0.5 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

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Stream channel alteration downstream of WWTP.
                    5-8

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      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

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Poor bank stability with high erosional potential.
   Stream banks stabilized by dense vegetation.
                      5-10

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                     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

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                             Rapid  Bioassessment Protocol  I

                                   Biosurvey Field Data Sheet
RELATIVE ABUNDANCE OF AQUATIC BIOTA
Periphyton
Filamentous Algae
Macrophytes
0 = Absent/Not Observed
1     2
1     2
1     2
                              1=Rare
Slimes
Macroinvertebrates
Fish
0     1
0     1
0     1
                                             2 = Common
                                                                 3 = Abundant
234
234
234


  4 = Dominant
MACROBENTHOS QUALITATIVE SAMPLE LISTflndicate Relative Abundance R = Rare, C = Common, A = Abundant, 0 = Dominant)
Porifera
Hydrozoa
Platyhelminthes
Turbellarla
Hirudinea
Oligochaeta
Isopoda
Amphipoda
Pecapoda
Gastropoda
Bivalvia

Anisoptera
Zygoptera
Hemiptera
Coleoptera
Lepidoptera
Sialidae
Corydalidae
Tipulidae
Empididae
Simuliidae
Tabanidae
Cullcidae
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

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                                     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

                  	 low taxa richness              	 Macrophytes

                  	 other                          	 Slimes

                                                           Fish
              3.  Brief description of problem:
                  Year and date of previous surveys:
                  Survey data, available in: 	
                  Cause: (indicate major cause)   organic enrichment   toxicants   flow

                      habitat limitations   other 	

                  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

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 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. Purse
 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
Particulate 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

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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 = Common 3 = Abundant
2 3
2 3
2 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. 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.
                                               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
9s
oo
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 II.

-------
Field sorting of benthic macroinvertebrate
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
entire 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 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 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*** FOR CHARACTERIZATION OF BIOLOGICAL CONDITION  FOR RAPID BIOASSESSMENT PROTOCOL  II
                                                                      Biological Condition
    	Metric	      Non-Impaired      Moderately Impaired      Severely Impaired





1.  Taxa Richness                                       5 S3-Si                  ~ <                     S<3 2
                                                         3 -o it •o                    a                     t> 01
                                                        M O 3" O B>                  g» 1                     • 3 .-»


2.  Family Biotic  Index (modified)                     SS"ig-                  gg                     088
         J                                              o> it i/>  i-1                  w *                     3«
                                                        g  n C_ID                  •  »                     H"  -O



3.  Ratio of  Scrapers/Filtering Collectors^*          ^il^°                  »S                     o?S


                                                         O r(  3-                  C J                     It  r»

4.  Ratio of  EPT and  Chironomid Abundances             ?. w « » «                  ^^                    no.-

                                                         M-ltlB                  00                     rtH-M
                                                        3-OOOW                  3W                      3M.


5.  /K Contribution of Dominant Family                  £p£3w                  5"o                     SmZ
                                                        rvSBOQi-'*                    r~n                    W G.W1




6.  EPT Index                                          ^g"o?l                  3S                     i""3"™
                                                        C301--                  •;• «                     W03
                                                        01 M. 30                  3                       3W
7.  Community  Similarity Indexv'"/                      X'S I f^rT                  SS                    3 o £
            ^           '                                •< n ^* tU O                  •  O                    in it m
                                                           ^ 3                      1                    (0  W
8.  Ratio of  Shredders/Total(b)                            2.™                    7                    r  °
(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.

-------
                                               Site-Specific Study
                                              Sampling & Analysis
          CRITERIA FOR CHARACTERIZATION OF BIOLOGICAL CONDITION FOR PROTOCOL II
                    Metric
1.  Taxa Richness*2'
1.  Family Biotic Index (modified)*'
3.  Ratio of Scrapers/Filt. Collectors1"'0'
4.  Ratio of EPT and Chironomid Abundances*"'
5.  %  Contribution of Dominant Family1"'
6.  EPT Index*"'
7.  Community Loss Index*6'
8.  Ratio of Shredders/Total*"'0'

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.
                                                      _L
                                               BIOASSESSMENT
                    % Comp.
                     to Ref.
                     Score(a)
 Biological Condition
	Category	
Attributes
                      >79%     Non-impaired
                     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  II.
                                                     6-12

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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 EFT 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 weighting1 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:
                          FBI =
          where
          Xj = number of individuals within a taxon
          tj = tolerance value of a taxon
          n = total number of organisms in the sample

             Hilsenhoff s 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 Hilsenhoff s 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 )L
-------
• 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 Davies (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
         SI
          '  "
(xia' xib>
             ab
            where
                                      ia     lb   ,
                                   veighting  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  seasonality, 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 to 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 rivets
and wadable streams and rivers with unstable
substrates.
                                                    6-16

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                              Rapid Bioassessment Protocol III
                                    Biosurvey Field Data Sheet
RELATIVE ABUNDANCE OF AQUATIC BIOTA
Periphyton          0
Filamentous Algae   0
Macrophytes         0
1     2     3
1     2     3
1     2     3
Slimes
Macroinvertebrates
Fish
0     1
0     1
0     1
234
234
234
0 = Absent/Not Observed
                               1 =Rare
                                               2 = Common
                                                                   3 = Abundant
                                                                                       4 = Dominant
MACROBENTHOS QUALITATIVE SAMPLE LISTdndlcate Relative Abundance R = Rare, C = Common, A = Abundant, D = Dominant)
Porifera
Hydrozoa
Platyhelminthes
Turbellaria
Hirudlnea
Oligochaeta
Isopoda
Amphipoda
Decapoda
Gastropoda
Bivalvia

Anlsoptera
Zygoptera
Hemiptera
Coleoptera
Lepidoptera
Sialidae
Corydalidae
Tipulidae
Empidldae
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.
                                               6-17

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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 IE  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
particulate 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 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 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

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                       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

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  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)


(b)
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 v '

Non-
Impaired
rh to rr (B O
0 rr rl X 0
n n O *o 3
C "O IB T3
M n 3" o 01
n c n IB 01
IB n a. cr
01 IB to 1— '
3 rr < IB

W O C rr rr
M. O O 3" O
N 3 rr H-
IB *U C 3 rr
O rl 3-
01 W IB 01 IB
3 H- • 3
O. rr CT
M. (B IB
3" O O 0 to
01 3 T> 0 rr
er rr n
M. 01 r-»- IB W
rr 3 3 N M-
01 O- C ^- rr
rr 3 0 C
O. 3 01
.O O O • rr
c a a M-
01 M* 3 o
r- 3 3 OB 3
M. oi e 01
rr 3 3 I-1 rr
•< 0 M- 01 O
• IB r» 3
**** *^ 1*1 CT"
IB tO
a.
Biological
Slightly
Impaired
0 M- rr O O
It! 3 3- O O
rr 01 3 3
rr O 3 •O 3
O 1— 0 C
h-* IB IB M 3
IB H X r-i. H-
n 01 "O rr rr
01 3 IB M-v<
3 rr 0 O
rr • rr 3 to
r-h O O* '-•' •"(
On we
n 3 Q.-O o
3 U C ID rr
u • IB n c
i— rr IB IB
3 T3 O to
O IB r->
IB O O r-- to
01 IB to O to
W 3 M 3-
IB rr 3 rr
Ul O IB 3"
• n rn M 0)
O U 3
3 to •— '
rr 0 IB
M- 3 l-i X
CT IB O 13
c «; IB
rr IB 0
M- n rr
O IB
3 O.
Condition
Moderately
Impaired
3 3 IB
0. rr <
IB O IB
X H-* r(
n to
(U TJ
3 IB
rr O
H-
O U
3 0.
U C
• ro

70 O
IB
O- r-'
C O
O to
rr M
M*
0 0
3 m
H- 3
3 O
U
PI rr
•T3
H




Severely
Impaired
•U rr O "1
r| <• l-n ID-
ID O «:
M O
IB rr M U
3 01 (W t3
rr X 01 IB
• 01 3 0

U IB
3 M
O W
3 - Tl
•< rr IB
3" to
rr IB IB
033
(—• rr
IB 0. •
rl O
01 3
3 M- M
rr 3 hn
01
O rr 3"
rl fB M-
oq CLOP
01 3-
3 cr
H-*< a.
Co IB
303
to 3 W
ID K-

O M-
rl (B
to
(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 Hilsenhoff s 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 =
                                  Xj tj
          where
          x;=number of individuals within a species
          ti = 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 Hilsenhoff s 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

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                                                                        DATA SUMMARY SHEET
K)
U)
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.

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            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 DIC  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

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Metric 6.  EFT Index

             The EFT Index generally increases with
          increasing water quality. The EFT 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 EFT 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
          EFT 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..]
S.I.
    ab
   where
max (x
                 ia'
                          weighting factor
   xia, xib = number of individuals in the 1th
            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

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                                               Site-Specific Study
                                              Sampling & Analysis
                    Metric
1.  Taxa Richness*3'
2.  Hilsenhoff Biotic Index (modified)0'*
3.  Ratio of Scrapers/Filt. Collectors'3-0'
4.  Ratio of EPT and Chironomid Abundances'"'
5.  %  Contribution of Dominant Taxon(d)
6.  EPT Index(a)
7.  Community Loss Index'6'
8.  Ratio of Shredders/Total(a'c>
                        >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""
 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

                                                     6-27

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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 in. 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-eontrol 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

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               NC 104
ARARAT RIVER
  SR 2019
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

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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.

6.4.2.2  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 Indexto 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
  (a)lolerance characterization developed by North Carolina
    DEM.
                                                   6-30

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       TABLE 6.A-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
Total Taxa  Richness
   ,(a)
EPTV<*-'  Taxa  Richness

EPT Abundance(b)

Biotic  Index

   Numeric Value

   Hilsenhoff Rating

ft  Intolerant Taxa(c)

   All
#  Unique
                ^  '
                                         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.
                     (e\
Bioclassificationv  '
(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. infiiscatus 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,  Alherix lantha) 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

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           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(a)
0
0
0
1
32

4
6
2
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   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 EFT 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
Distance between Cluster Centroids
o o o o -L _» —
o roJ>b)ca-t.roiub>
• titiiiii


1


1

— i — . 	 -auti — i i 1 i




1

                   tc.
                   I
                        #B
                             t
                             UJ
                                                                                                  UJ
             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

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              TABLE 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
(a)
4

R
                                                       100-ORGANISM SUBSAMPLE
Taxa. Richness
HBI10'
Scrapers/Filt . Collect.
EPT/Chiron. Abundance. .
» Contrib. DOB. Taxon'0'
EPT Index
Community Loss Index
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
88
56
26
11
86
—
76
85
40
16
20
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
Total Score
Biological Condition
Taxa. Richness
Scrapers/Filt.
EPT/Chiron. Abundance
% Contrib. Dom.
EPT Index
Community Loss Index

Total Score
Biological Condition


Taxa. Richness
RBI
Scrapers/Filt. Collect.
EPT/Chiron. Abundance. .
* Contrib. DomJ Taxon
EPT Index           ...
Community Loss Index

Total Score
Biological Condition
                                                       200-ORGANISM SUBSAMPLE


lollect.

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              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

Tax*, richness
HBI1 '
Scrapecs/Filt . Collect.
EPT/Chiron. Abundance
% Contrib. Don. Taxon
EPT Index
Community Loss Index

Total Score
1

18
4.26
1.47
12.6
20.0
11
1.00


2

30
3.98
1 .60
5.08
12.0
IS
0 .53


3

7
8.33
0.00
0 .00
53.8
0
3 .50


4

17
5.41
0.32
1.96
23.2
10
1 .06


R
EA
29
4.19
2.15
32.00
10.9
17
0


1
FIELD
62
98
68
39
20
65



% Comparison
Bioassessaent Score
Station
2
SORTED
103
105
74
16
12
88



3

24
50
0
0
54
0



4

59
77
15
6
23
59



R

100
100
100
100
11
100



1

4
6
6
2
4
0
4
	
26
Station
2

6
6
6
0
6
4
4
	
32
3

0
2
0
0
0
0
2
—
4
4

2
4
0
0
4
0
4
—
14
R

6
6
6
6
6
6
6
i
42
Biological Condition
Slightly  Slightly   Sev.  Mod.
                                                                                                                               Non
                                                     FAMILY-LEVEL IDENTIFICATION
Taxa. richness
FBI™
Scrapers/Filt. Collect.
EPT/Chiron. Abundance    ,
% Contrib. don. fanily
-------
   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 EFT 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-
          20
      o

      j§  15-

      I  10-
           5-
NC Multihabitat
          —   -
NC Field Sorted Rime
                   NC Multihabitat
                                                 •»
                   NC Reid Sorted Riffle
                   EA Field Sorted Riffle
                                                      %
                                                          %
                                                                                                 w
                                                                         /
                                                                   /
                                                             ./
                                              V
                                                        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

                    1.4
    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
                O    1 "
                 *
                2  0.8-
                o
                 I  0.6 -

                *0.4-
                3  0.2  -\
                0
                      0  4
   4
Stations
                                                                        R
           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-
                       1  -
                     0.4-
                                                           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

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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-sav-ings 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
                  1.4
                  0.8 -<

                  0.6-

                  0.4-

                  0.2-

                    0-
                                          2            4
                                                    Stations
             R
            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

-------
s
I
0)
O
<5
|
O
               2-
             1.5-
               1-
             0.5-
d)
J3
8
8
z    ^
                                i

                                                      Metrics
               Figure 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 (Stations 1—4) and Mitchell Rivers (Station R).
                     1.4
                     1.2 -
                               1
                                                                        R
                                    2            4
                                              Stations
Figure 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
             (Stations 1-4) and Mitchell (Station R) Rivers.
the species level and subtle differences in biological
impairment will  not be readily discerned. In this par-
ticular pilot study, the family-level bioclassification
provided station  relationships similar to those of the
species level.  The bioclassification is:
                        = 2>4»3
   The family-level data differed slightly in level of
station similarity compared to that for the species-
level (100-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 effort
                                                 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                               R»l  =  2>4»3

     EA  field-sorted riffle;  RBP III analysis                R»l=2>4»3

     100-organism riffle; RBP III  analysis                    R»l=2>4»3

     300-organism riffle; RBP III  analysis                    R»l=2>4»3

     100-organism riffle; RBP II (family) analysis         R»l=2>4»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
                             = 2>4»3

                           = 2>4>3

                           = 2>4»3

                             = 2>4>3

                           = 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 n 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-reference, 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

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                 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
assessment of 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 waters 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  waterbody  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)


(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 onnivory.
 Figure 7.1-1. Fish assemblage questionaire for use with Rapid Bioassessment Protocol IV.
                                    7-2

-------
2  Dominated by highly tolerant species, omnivpres, 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

        543210

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 I—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
29
30
31
32
33
34
35
36  Natural
37  Unknown
3B  Other (specify below)
Landfill leachate
Construction
Agriculture
Feedlot
Grazing
Silviculture
Mining
                          Figure 7.1-1.  (Cent.).
                                  7-3

-------
Subsection 2—Water 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.  (Cent.
                              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, n,
and in (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

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Field crew electrofishing with a pram-towed unit.
                       7-6

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                              IMPAIRMENT ASSESSMENT SHEET
       1.   Detection of impairment:  Impairment detected
                                     (Complete Items 2-6)
             No impairment
                detected
              (Stop here)
       2.   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

       3.   Brief description of problem:  	
  Other aquatic communities

  	 Macroinvertebrates
  	 Periphyton
  	 Macrophytes
           Year and date of previous surveys:

           Survey data available in: 	
       A.   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

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                                            Select a Site
                                                 I
                                    Identify Regional Fish Fauna
                        Assign Species to Trophic, Tolerance, and Origin Guilds
                                                _L
                        Assess Available Data for Metric Suitability and Stream
                                            Size Patterns
                                                J_
                             Develop Scoring Criteria from Reference Sites
                                     Quantitatively Sample Fish
                         List Abundances of Species, Hybrids, and Anomalies
                                  Calculate and Score Metric Values
                                                _L
                                      METRIC SCORES (ffil)
                                                            Scoring Criteria*"'
                                Metric
                                                          >67%   33-67%
                                                          >67%   33-67%
 1.  Number of native fish species
 2.  Number of darter or benthic species
 3.  Number of sunfish or pool species
 4.  Number of sucker or long-lived species
 5.  Number of intolerant species
 6.  Proportion of green sunfish or tolerant
      individuals
 7.  Proportion omnivorous individuals
 8.  Proportion insectivores
 9.  Proportion top carnivores
10.  Total number of individuals
11.  Proportion hybrids or exotics
12.  Proportion with disease/anomalies
                 (a)Metrics 1-5 are scored relative to the maximum species richness line.
                   Metric 10 is drawn from reference site data.
                             <33%
                             <33%
          >67%   33-67%   <33%
          >67%   33-67%   <33%
          >67%   33-67%   <33%
                                                                  10-25%   >25%
                                                          <20%   20-45%   >45%
                                                          >45%   20-45%   <20%
                                                           >5%     1-5%     <1%
                                                          >67%   33-67%   <33%
                               INDEX SCORE INTERPRETATION'"'
                 IB1
                58-60

                48-52

                40-44

                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 I

Figure 7.2-2. Flowchart of bioassessment approach advocated for Rapid Bioassessment Protocol V.

                                                7-8

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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

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                           FISH  FIELD COLLECTION DATA SHEET
                                                                   page_
                                                                           of
                                          Date .
Drainage 	
Sampling Duration (rain) 	
Sampling Distance (m)   	  Sampling Area  (m')  	
Habitat Complexity/Quality (excellent   good    fair
Veather  	  Flow  (flood  bankfull moderate low)
Gear Used                    Gear/Crew Performance 	
Comments                           	
                                                               Crew	
                                                             poor   very
        poor)
      Fish (preserved)  Number of Individuals
                                                  Number of Anomalies
      Genus/Species
                                 Adults
                                           Juveniles
                               No.
                                      tft.
                                                 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

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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 In 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
          6X2 _ 3XY - Y2 + Y(Y2 + 6XY -     '/2
                        18(X-Y)
N=-
where X=2C,+C2, and Y=C1 + 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 IBI 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(!A5)- 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(5), sculpin and darter species(S)
              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 m2
           (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(5), and sunfish and trout species(S)
              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 salmonids are important
           sport species. The sunfish metric works
                                                     7-12

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                                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 f, ^                                  X                                 X
    # salmonid age classes^ '                                                                    X          X

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
    # 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
    # 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.

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                                                TABLE 7.2-1   (Cont.)

5.
6.
7.
8.
Variations in IBI Metrics
Number of Intolerant Species
# sensitive species
# amphibian species
presence of brook trout
X Green Sun fish
% common carp
% white sucker
% tolerant species
X creek chub
% dace species
X Omnivores
X yearling salmonids( '
X Insectivorous Cyprinids
New Central Colorado Western Sacramento-
Midwest England Ontario Appalachia Front Range Oregon San Joaquin
XX XX
X
X
X
X
X
X X
X
X
X
X X X X X X
X X
X
    % 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
                                          X
                                          X
                                                               X
                                                     X

                                                     X

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     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

X
                                                                  X
                                                                  X

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                              10                                 50
                                      Log Watershed Area (mile2)
100
200    300
Figure 7.2-4. Total number of fish species versus watershed area for Ohio regional reference sites.

-------
           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.  Kan-
           el 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(5), 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(l).  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(5); 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 piscivores 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)

Metrics(a)
1. Niwber of Native Fish Species
2. Niwber of Darter or Benthic Species
3. Niwber of Sunfish or Pool Species
4. Niwber of Sucker or Long-Lived Species
5. Ninber of Intolerant Species
6. X Green Sunfish or Tolerant Individuals
7. X Omnivores
8. X Insectivores or Invertivores
9. X Top Carnivores
10. Total Niwber of Individuals
11. X Bybrids or Exotics
12. X Anomalies
Scorer
Coaaents:
5

>67
>67
>67
>67
>67
<10
<20
>45
>5
>67
0
<1


T

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
7JE7 Metric Value Metric Score
<33
<33
<33
<33
<33
>25
>45
<20
<1
<33
>1
>5
IBI Score




(a) Rarr's original Metrics or coaaonly used
ties.
(b) Karr's original scoring criteria or cou<
ecoregions.
substitutes.

See text

>nly 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.

                                                     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
                    888:$ 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
                                              Table 7.3-1
                                          COLLECTION  DATA FOR TWO
                                          OHIO ECOREGION REFERENCE
                                          SITES
  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
                                                     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 madtom
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
                                                                               Site
                                                       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)
X 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

     9
  i
  Poor
         LU
         CC
         O
         O
         CO
         s
                                               Jl—
r
•o
§ 50-
O!
l_ _
46-

r ~
•5 42-
L
38-
,-34-







1






1
o 	










f





i=.

i









-











1

o





0
... ...
LJ
I
1
3


             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
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
80
occurance
g

-------
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 IVB SCORES  FOR
                           TWO  SITES  ON THE WILLAMETTE RIVER,  OREGON
                                                                         Value(Score)
                     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  (>92=1,  1-92=3,  <12=5)
  % Omnivores  (>502=1, 25-502=3, <252=5)
  % Insectivores (<202=1,  20-402=3,  >402=5)
  % Catchable  Salmonids  (0%=1,  1-92=3, >92=5)
  Number of Individuals/km (<50=1,  50-99=3, >99=5)
  2 Introduced  (>92=1, 1-92=3,  <12=5)
  2 Anomalies  (>52=1,  2-52=3,  <22=5)

  Total IBI Score

  IWB  Score
  Integrity
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
River
270
10(5)
3(5)
3(3)
2(5)
2(3)
0(5)
46(3)
22(3)
23(5)
95(3)
0(5)
0(5)
50
6.1
Good
Kilometer
31
4(1)
KD
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).
                180-1


                160-


                140-


                120-


              t'J 100-
              */i

              <  80-


                 60-


                 40-


                 20-
Upper
River
                              Portland
                              Metro
  Middle
  River
                                . -1—I—I—I—I—I—'—I—'—I—'—I—'—I—'—I—'
                       20  40  60  80  100 120  140 160 180 200 220  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).
                                            7-25

-------
60
50
40
30
20
10
         IBI
                                          	J
         NO3 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 and 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
 0)
 u
 0)   80
 0)
oe   70

3?   60

     50
         S
         re
        '5>
        "5   20
 O   40
U
     30 -
             10 —
                       t
                    Nonimpaired
                       I
                       t
                      Slightly
                      Impaired
                       i
                       T
                     Moderately
                      Impaired
                  Severely Impain
                                    Nonsupporting
                                                        Partially
                                                       Supporting
                                                                          Supporting
                                                                                    Comparable
         0      10      20     30      40     50     60      70
                             Habitat Quality (% of Reference)
                                                                            80
                                                                          90     100
                    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>
               "3
               «
               u
               o
 o
o
"5
 u
 o>
 o
 o
25
                                                      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 n 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
                    o
                        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
                       Toxicants
                               Metrics
                       ' Taxa Richness
                        HBI
                        FFG 4 Scrapers/Filterers
                        EPT Abund./Chiron.Abund.
                        % Contribution (dom.taxon)
                        EPT
                        Community Similarity Index
                      [ FFG 4 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 Barbour 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











                     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

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         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)
                IHC + 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., lexicological 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

-------
                   BC = BR
               HC = HR; BC = BR
                Include "C" in
                "R" database.
                      d)
                                       HC = HR
                                          (I)
       BC

-------
           HC + RHA = I-R
              BC =  BR
          Use designation
          is appropriate.
                 (3)
             Use "C" as
           bioassessment
             reference.
Continue RBP —
habitat and
biosurvey
approach .
(6)
i
f


« — 1


                                       HC + RHA = HR
                                           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 <  HR
(III)
                                   Select  Cx
   HCX  = HR
       (B)
HCX
+ RHA
(9)
< HR
                                                           HCX +  RHA  = HR
                                                                 (10)
     Go to
       (I)
  BCX  = BR
  (unlikely
 scenario)
    (11)
HC + RHA < HR;
BC = BR
Habitat not
limiting;
No bioimpact
at "Cx"
*


Use^ "Cx" or
"R'as
reference for
bioassessment








i





(a



HCX + RHA < HR BCX < BR
Bioimpact at "Cx".
Effects due to degraded
habitat +/or WQ
(UAA is eventually
needed)






* i


Perform UAA.
Redefine'Rx"
or subset of'R"







(b)
Consider "Cx"
best attainable
condition. Use
"Cx" as
reference for
bioassessment.




F
(c)
Predict
biological
condition using
known habitat
gua'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  "Cn
                             [or  "C*"]
                                as a
                             reference
                             station)
Figure 8.3-5.  Bioassessfhent using a site-specific control station.
             (Numbers in parentheses refer to points of discussion in text.)
                                8-11

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                               TABLE 8.3-1  BIOASSESSMENT CONCLUSIONS RELATIVE TO USE OF A SITE-SPECIFIC  CONTROL  OR REGIONAL REFERENCE
oo
 I

F3
M
9B
U
X
u
X
X
tt
•f
M
X
H
CO
II
u
n
M
a
u
a
M
a
u
n
H
n
u
m
HC s HR
BC = BR BC < BR
No bioiapairaent at C
or I; I is a candi-
date for inclusion in
the R database.
Bioiapairment at I
due to WQ effects.
No bioimpairaent at
I; reversible habitat
alterations are
limiting.
Bipiapairaent at I
(Sue to degraded
habitat (reversible
parameters) and/or
WQ . ' '
HC + RHA • HR
BC = BR BC < BR( a)

or I; use designation
appropriate. I is a
candidate for inclu-
sion in R database.
Reversible habitat
sent but not limiting
Bioimpairaent at I.
due to WQ effects1
sible habitat
alterations .
Unlikely scenario
Bioiapairaent at I
due to degraded
habitat (reversible
parameters) and/or WQ
effects.
HC + RHA
BC = BR
Unlikely scenario
Unlikely scenario
Unlikely scenario
Bioiapairaent at I
due to degraded
habitat (rever-
sible w/respect
to C, and both
reversible and
irreversible para-
meters w/respect
to R) and/or WQ
effects. TfaT
< HR
BC < BR(a)
Bioinpairment at C
and I due to
(reversible and/or
irreversible para-
meters) and/or WQ
effects.1 '
Both C and I
to R due to
degraded habitat
(reversible and/or
aeters) and/or WQ
effects. ' Addi-
tional bioiapair—
aent at I due to
WQ.
Bioiapairment at C
and I due to
degraded habitat
(reversible and/or
irreversible para-
meters) and/or WQ
effects. TbT
Both C and I
iaoaired relative
to R due to
degraded habitat
(reversible and/or
irreversible
WQ effects. '
Additional
due to degraded
habitat (reversible
parameters ) .

-------
TABLE  8.3-1   (Cont.)
M
ff
41
U
to
1
H
CO
•V
U
to
•
Pi
to
M
(0
Pi
CO
hC a HR HC + RHA =* HR
BC » BR BC < BR BC = BR " BC < BR ( a 1



habitat alteration?
present .
Bioidpairaent at I , Bioiipai rue n't at I,
due to degraded due to degraded
and/or irreversible parameters) and/or WQ
parameters} and/or WQ effects-
effects. (D)

Include I in R at C, but not I.
database .

parameters) and/or WQ
effects. Bioimpair-
aent at I due to WQ
effects .
HC + RHA < HR
BC = BR BC < BR(a 1

and C due to
degraded habitat
(reversible and/oc
i rreve rs ible
parameters ) and/or
WQ effects , { '
'Bioinpairaent at BothCandl
.habitat toRdueto
(reversible and/or degraded habitat
• *C hi "

WQ effects. ( '
Additional bio-
inpairnent at I due
to degraded habitat
( reversible and/o r
itat parameters)
and/oc WQ. ( '
Unlikely scenario Unlikely scenario
due to WQ. Habitat to R due to
not limiting at C. degraded habitat
( reversible and/o r
•eters) and/ or WQ
effects . ' Bio-
impairment at I due
                                                          to degraded habitat
                                                          (reversible para-
                                                          meters ) and/or WQ.

-------
                             TABLE  8.3-1   (Cont.)
HR
                                    HC + RHA s  HR
                                                                           HC  + RHA <  HR
M
0)
H
Pi
n
M
n
PS
CO
M
n
•
OS
CO
M
n
V
Pi
en
BC = BR
Ho bioinpai raent at
alterations present,
but not limiting.
Bioinpai raent at I
due to reversible
habitat alterations
and/oc WQ effects. lc)
No bioinpai raent at
I, but reversible
and/or irreversible

Bioiapai raent at I
due to degraded
para«*«t*r9 t and/or *
-------
                     (Using "FT
                        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
(HI the reference. This probably indicates a nonpoint- source water quality problem. Because of this bioii|i- pairment noted at C, it is Best to use trie regional reference for bioassessment. Judgment erf bi«W0ai«Bept in this Qase study was done in the strictest sense, where specific comparabil- ity to the reference conditions needed to be attained at the site of comparison. Conditions at Station 4 indi- cated that habitat quality was supporting relative to the reference, and biological conditions were moder- ately impaired. Therefore, bioimpairment at Station 4 is not as severe as that noted at Station 3. -16

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 TABLE 8.4-1  SUMMARY OF HABITAT ASSESSMENT  SCORING  FOR ARARAT AND MITCHELL RIVERS BENTHIC  CASE  STUDY DATA



Habitat Category/Parameter

C(l)
Stations
3

4

R(6)
Primary — Substrate and Instream Cover
1.
2.
3.
Bottom substrate and available cover
Embeddedness^
Flow/ velocity
14
18
16
8
6 (18)
9
18
10
18
18
18
19
Secondary — Channel Morphology
4.
5.
6.
Channel alteration
Bottom scouring and deposition
Pool/riffle, run/bend ratio
7
10
11
2
4
10
11
13
11
13
13
14
Tertiary — Riparian and Bank Structure
7.
8.
9.




Bank stability^*
Bank vegetation^'*
Streamside cover '
Subtotal for tertiary parameters
Score =
Proportion (%) of ecoregional reference
Classification =
6
9
10
25
101
81
S
7 (10)
9 (10)
8 (10)
24 (30)(b)
63 (81)
50 (65)
P
9
10
8
27
108
86
S
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.

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53
                            TABLE 8.4-2  SUMMARY OF METRIC VALUES, PERCENT COMPARISON, AND BIOASSESSMENT SCORES FOR
                                         ARARAT AND MITCHELL RIVERS BENTHIC CASE STUDY DATA
100-Organism Subsample
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
% Comparison to Reference
Station
C( 1 ) 3
76 32
88
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   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.
              0)
              O
              4-rf
              0)
              ffl
              Q.
              00
              tr
                     10-
                                                                                           125
                                                                                         - 100
                                                                                          CO
                                                                                          O
                                                                                          .0
                                                                                          to
                                                                                          X
     Figure 8.4-1. The relationship between habitat quality and benthic community condition at the North Carolina
                  pilot study site.
     100 —

_   90-
 0)
 u
 cu   80 —
 Ol
s-
ce   70 —
M-
 o
S?   60 —I
          I    50
          O    40 —
          U

          8    30 -I
^
 O   20
im
                           f
                       Nonimpaired
                           I
                           t
                          tightl
                          ipain
                          i
                Slightly
               Impaired
                           t
              Moderately
               Impaired
                           I
                             \
                            10
                                          Nonsuppocting
                                                                 Partially
                                                                Supporting
                                                                                     Supporting
                                                                                                Comparable
                           I         I        I         I
                           20      30      40       50
 I        I
60      70
 I        I
80      90
           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

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Seber,  G.A.F.  and E.D. LeCren. 1967. Estimating
population parameters from catches large relative to
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Seber,  G.A.F.  and J.F. Whale. 1970. The removal
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26:393-400.

Shackleford, B. 1988. Rapid Bioassessments of Lotic
Macroinvertebrate Communities: Biocriteria Develop-
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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
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SteedmairrR.J.  1988.  Modification and assessment of
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45:492-501.
Swift,  M.C., K.W. Cummins, and  R.A.  Smucker.
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Swift,  M.C., R.A. Smucker, and K.W. Cummins.
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U.S. Environmental Protection Agency (EPA). 1980a.
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U.S. EPA, Washington, D.C.
U.S. Environmental Protection Agency (EPA). 1980b.
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U.S. Environmental Protection Agency (EPA). 1984a.
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                                                    R-5

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Correspondence between ecoregions and spatial pat-
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Insect community structure as  an index of heavy-metal
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                                                  R-6

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     APPENDIX A

 GUIDANCE FOR USE OF FIELD
AND LABORATORY DATA SHEETS

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                                     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, H, AND III
    (Figures 6.1-1, 6.2-1,  and 6.3-1)
   A.I GUIDANCE FOR  HEADER
    INFORMATION (Figure 2.6-1)
Waterbody 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/MHepoint:
  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

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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

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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 Bioassessment 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

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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

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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 agS 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

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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.

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                             Rapid Bioassessment Protocol  I
                                   Blosurvey Field Data Sheet
RELATIVE ABUNDANCE OF AQUATIC BIOTA
Perlphyton
Filamentous Algae
Macrophytes
1     2     3
1     2     3
1     2     3
Slimes
Macrolnvettebrates
Fish
0     1
0     1
0     1
234
234
234
0 = Absent/Not Observed
                              1 =Rare
                                             2 = Common
                                                                 3 = Abundant
                                                                                    4 = Dominant
MACROBENTHOS QUALITATIVE SAMPLE LIST(lndlcate Relative Abundance R = Rare, C = Common, A = Abundant, D = Dominant)
Porlfera
Hydrozoa
Platyhelminthes
Turbellarla
Hlrudlnea
Oligochaeta
Isopoda
Amphipoda
Decapoda
Gastropoda
Bivalvia

Anisoptera
Zygoptera
Hemiptera
Coleoptera
Lepldoptera
Slalldae
Corydalldae
Tlpulldae
Empldldae
Slmullldae
Tabanldae
Cullcldae
Chironomidae
Plecoptera
Ephemeroptera
Trlchoptera
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

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                             Rapid Bioassessment Protocol II

                                   Biosurvey Field Data Sheet
RELATIVE ABUNDANCE OF AQUATIC BIOTA
Periphyton
Filamentous Algae
Macrophytes
0 1
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 3
2 3
2 3
4
4
4
4 = Dominant
MACROBENTHOS QUALITATIVE SAMPLE LIST
                                                                   List Families Present/Indicate Abundance
Oligochaeta


Gastropoda


Blvalvla


Ephemeroptera




Anisoptera


Zygoptera

Plecoptera


Trlchoptera




Coleoptera


Dlptera





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

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                             Rapid Bioassessment Protocol III
                                    Biosurvey Field Data Sheet
RELATIVE ABUNDANCE OF AQUATIC BIOTA
Perlphyton
Filamentous Algae
Macrophytes
2     3
2     3
2     3
Slimes
Macroinvertebrates
Fish
0     1
0     1
0     1
0 = Absent/Not Observed
                               1 = Rare
                                               2 = Common
                                                                   3 = Abundant
                                                                                       4 = Dominant
MACROBENTHOS QUALITATIVE SAMPLE LIST (Indicate 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
Chironomldae
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

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                                     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: 	
              A.   Cause:  (indicate major cause)   organic enrichment   toxicants   flow

                      habitat limitations   other 	

              5.   Estimated areal extent of problem (m ) and length of stream reach

                  affected (m),  where applicable: 	
              6.  Suspected soiirce(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-10

-------
                              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

  	 Macroinvertebratea
  	 Periphyton
  	 Macrophytes
           Year and date of previous surveys:

           Survey data available in: 	
       4.   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.
                                       A-ll

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                                                                      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 6.2-2. Data Summary Sheet suggested for use in recording benthic data utilized in Rapid Bioassessment Protocol II.

-------
                                          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.

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                      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

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                           FISH FIELD COLLECTION DATA SHEET
                                                                   page_
                                                                           of
                                           Date .
Drainage 	
Sampling Duration  (rain) 	
Sampling Distance  (m)
Habitat Complexity/Quality
Weather
Gear Used
Comments
Fish (preserved) Number of  Individuals
                                     Sampling  Area (m )  	
                                  fexcellent    good   falF
Crev
                                                             poor   very
                                    Flow  (flood  bankfull moderate low)
                                    Gear/Crew  Performance
                                                   Number  of  Anomalies
            poor)
      Genus/Species
                            Adults
                                            Juveniles
                               No.
                                      Wt.
                                                  No.
                                                          Vt.
    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.
                                         A-15

-------
Station No.
Site






Scoring Criteria(b)
Hetrics(a)
1. NuBber of Native Fish Species
2. Nuaber of Darter or Benthic Species
3. NuBber of Sunfish or Pool Species
4. NuBber of Sucker or Long-Li ved Species
5. Nu«ber of Intolerant Species
6. Z Green Sunfish or Tolerant Individuals
7. X Oanivores
8. X Insectivores or Invertivores
9. X Top Carnivores
10. Total Nuaber of Individuals
11. X Hybrids or Exotics
12. X Anoaalies
Scorer
CoBBents:
5
>67
>67
>67
>67
>67
<10
<20
>45
>5
>67
0
<1


3
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
(XT Metric Value Metric Score
<33
<33
<33
<33
<33
>25
>45
<20
<1
<33
>1
>5
IBI Score





(a) Karir's original Betrics or couonly used substitutes.
ties.
(b) Karr's original scoring criteria or coaaonly
ecoregions.

See text

used substitutes.


and Table 7.2-1 for other possibili-

These Bay require refinement in other

Figure 7.2-5. Data Summary Sheet for Rapid Bioassessment Protocol V.
                             A-16

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              APPENDIX B

RAPID BIOASSESSMENT SUBSAMPLING METHODS FOR
         BENTHIC PROTOCOLS II AND III
          (100-Organism Count Technique)

-------
                                      APPENDIX B
    RAPID BIOASSESSMENT SUBSAMPLING  METHODS FOR
                      BENTfflC  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, cryptic 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

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             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 1987b) 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-
mat id ae 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

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 TABLE C-2  TOLERANCE VALUES FOR SOME MACROINVERTEBRATES NOT INCLUDED IN
	HILSENHOFF (1982, 1987b)U;; FROM BODE (1988)	


                  Acariformes                    4
                  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                    4
(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

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       APPENDIX D

TOLERANCE, TROPHIC GUILDS, AND
ORIGINS OF SELECTED FISH SPECIES

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                                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,
                    FISH  SPECIES
                                         AND ORIGINS OF SELECTED
  WILLAMETTE SPECIES

  Salmonidae
    Chinook salmon
    Cutthroat trout
    Mountain whitefish
    Rainbow trout
  Cyprinidae
    Chiselmouth
    Common carp
    Goldfish
    Leopard dace
    Longnose 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
               essarily the  final designations; designations may vary for
               nt regions.
Not nee	  .
different  regions
                                       D-l

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                            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

exotic
exotic

native

native

exotic
exotic
exotic
exotic

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

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TABLE D-l   (Cont.)

Rainbov trout
Brook trout
Lake trout
Coho salmon
Chinook salmon
Lake herring
Lake whitefish
Osmeridae
Rainbov smelt
Umbridae
Central mudminnow
Esocidae
Grass pickerel
Chain pickerel
Northern pike
Muskel lunge
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 madtom
Slender madtom
Freckled madtom
Northern madtom
Scioto madtom
Trophic Level
insectivore
insectivore
insectivore
insectivore
insectivore

herbivore
omnivore
omnivore
omnivore
herbivore
insectivore
herbivore
omnivore
omnivore
herbivore

insectivore
insectivore
insectivore
insectivore
omnivore
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 madtora
  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, I.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 DC. 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, KB.  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
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,  FA. 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, D.A. 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.,  EC. 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, WB. 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 FAmenagement de la Faune, Ministere du
   Tourisme, de la Chasse et de la Peche,  Quebec.
   59pp.

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 commer-
   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, J.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.

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    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 Kite)

Iowa Conservation Commission  (Vaughn Paragamian)

Kansas Department of Wildlife and Parks
   (L. Zuckerman)
                                                  D-ll

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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:  624-804

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