United States
Environmental Protection
Agency
Office of Water
Regulations and Standards
Washington, DC 20460
November 1983
Water
Technical Support Manual:
Waterbody Surveys and
Assessments for Conducting
Use Attainability Analyses
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Foreword
The Technical Support Manual: Water BodySurveys and Assessments for
Conducting Use Attainability Analyses.contains technical guidance prepared
by EPA to assist States in implementing the revised Water Quality Standards
Regulation (48 FR 51400, November 8, 1983). EPA prepared this document
in response to requests by several States for additional guidance and
detail on conducting use attainability analyses beyond that which is
contained in Chapter 3 of the Water Quality Standards Handbook (December,
1983).
Consideration of the suitability of a water body for attaining a given
use is an integral part of the water quality standards review and revision
process. This guidance is intended to assist States in answering three
central questions:
(1) What are the aquatic protection uses currently being achieved in the
water body?
(2) What are the potential uses that can be attained based on the physical,
chemical and biological characteristics of the water body?; and,
(3) What are the causes of any impairment of the uses?
EPA will continue providing guidance and technical assistance.to the
States in order to improve the scientific and technical basis of water
quality standards decisions. States are encouraged to consult with EPA at
the beginning of any standards revision project to agree on appropriate
methods before the analyses are initiated, and frequently as they are
conducted.
Any questions on this guidance may be directed to the water quality
standards coordinators located in each of the EPA Regional Offices or to:
Elliot Lomnitz
Criteria and Standards Division (WH-585)
401 M Street, S.W.
Washington, D.C. 20460
Steven Schatzow, Director
Office of Water Regulations and Standards
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TECHNICAL SUPPORT MANUAL:
WATER BODY SURVEYS AND ASSESSMENTS
TABLE OF CONTENTS
'Foreword
°Section I: Introduction
°Section II: Physical Evaluations
Chapter II-l
Chapter II-2
Chapter II-3
Chapter II-4
Chapter
Chapter
II-5
II-6
Flow
Suspended Solids and Sedimentation
Pools, Riffles and Substrate Composition
Channel Characteristics and Effects of
Channeli zation
Temperature
Riparian Evaluations
°Section III: Chemical Evaluations
Chapter III-l Water Quality Indices
Chapter III-? Hardness, Alkalinity, pH and Salinity
°Section IV:
Chapter IV-
Chapter IV-2
Chapter IV-
Chapter IV-
Chapter IV-
Chapter IV-
Biological Evaluations
1 Habitat Suitability Indices
Diversity Indices and Measures of
Community Structure
3 Recovery Index
4 Intolerant Species Analysis
5 Omnivore-Carnivore Analysis
fi Reference Reach Comparison
°Section V: Interpretation
°Section VI: References
°Appendix A-l:
°Appendix B-l:
"Appendix B-2:
"Appendix C:
Sample Habitat Suitability Index
List of Resident Omnivores Nationally
List of Resident Carnivores Nationally
List of Intolerant Species Nationally
Page
i
1-1
II-l-l
II-2-1
II-3-1
II-4-1
II-5-1
II-6-1
III-l-l
III-2-1
IV-1-1
IV-2-1
IV-3-1
IV-4-1
IV-5-1
IV-6-1
V-l
VI-1
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0 SECTION I: INTRODUCTION
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One of the major pieces of guidance discussed within the Water Quality
Standards Handbook (November, 1983) is the "Water Body Survey and
Assessment Guidance for Conducting Use Attainability Analyses" which
discusses the framework for determining the attainable aquatic protection
use_/J This guidance describes the framework and suggests parameters to be
examined in order to determine:
(1) What are the aquatic use(s) currently being achieved in the water body?
(2) What are the potential uses that can be attained based on the physical,
chemical and biological characteristics of the water body?; and,
(3) What are the causes of any impairment of the uses?
The purpose of the technical support manual is to highlight methods and
approaches which can be used to address these questions as related to the
aquatic life protection use. This document specifically addresses stream
and river systems. EPA is presently developing guidance for estuarine and
marine systems and plans to issue such guidance in 1984.
Several case studies were performed to test the applicability of the "Water
Body Survey and Assessment" guidance. These case studies demonstrated that
the guidance could successfully be applied to determine attainable uses.
Several of the States involved in these studies suggested that it would be
helpful if EPA could provide a more detailed and technical explanation of
the procedures mentioned in the guidance. In response, EPA has prepared
this technical support manual. TThe methods and procedures offeredjin this
manual Tare optional and States may apply them selectively. States may also
use theTr own techniques or methods for conducting use attainability
analyses^
A State that intends to conduct a use attainability analysis is encouraged
to consult with EPA before the analyses are initiated and frequently as
they are carried out. EPA is striving to develop a partnership with the
States to improve the scientific and technical bases of the water quality
standards decision-making process. This consultation will allow for
greater scientific discussion and better planning to ensure that the
analyses are technically valid.
Consideration of the suitability of a water body for attaining a given use
is an integral part of the water quality standards review and revision
process. The data and information collected from the water body survey
provide a basis for evaluating whether the water body is suitable for a
particular use. It is not envisioned that each water body would
necessarily have a unique set of uses. Rather the characteristics
necessary to support a use could be identified so that water bodies having
those characteristics might be grouped together as likely to support
particular uses.
Since the complexity of an aquatic ecosystem does not lend itself to simple
evaluations, there is no single formula or model that will provide all the
answers. Thus, the professional judgment of the evaluator is key to the
interpretation of data which is gathered.
1-1
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SECTION II: PHYSICAL EVALUATIONS
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OVERVIEW
The physical characteristics of a water body greatly influence its reaction
to pollution and its natural purification processess. The physical
characteristics also play a great role in the availability of suitable
habitat for aquatic species. An understanding of the nature of these
characteristics and influences is important to the intelligent planning and
execution of a water body survey. Important physical factors include flow,
temperature, substrate composition, suspended solids, depth, velocity and
modifications made to the water body. Effects of some of these factors are
so interrelated that it is difficult or even impossible to assign more or
less importance to one or the other of them. For example, slope and
roughness of channel influence both depth and velocity of flow, which
together control turbulence. Turbulence, in turn, affects rates of mixing
of wastes and tributary streams, reaeration, sedimentation or scour of
solids, growths of attached biological forms and rates of purification
(FWPCA, 1969). Thus evaluating the factors which constitute the physical
environment cannot be done by just assessing one parameter but rather a
broader assessment and view is needed.
The purpose of this section is to amplify the methods and types of
assessments discussed in Chapter 3 of the Water Quality Standards Handbook
for evaluating the physical characteristics of a water body. The analyses
proposed in this section, as well as the other sections of this document,
do not constitute required analyses nor are these all the analyses
available or acceptable for conducting a use attainability analysis.
States should design and choose assessment methodologies based on the
site-specific considerations of the study area. The degree of complexity
of the water body in question will usually dictate the amount of data and
analysis needed. States should consult with EPA prior to conducting the
survey to facilitate greater scientific discussion and better planning of
the study.
CHAPTER II-l
FLOW ASSESSMENTS
The instream flow requirement for fish and wildlife is the flow regime
necessary to maintain levels of fish, wildlife and other dependent
organisms. Numerous methodological approaches for quantifying the instream
flow requirements of fish, wildlife, recreation, and other instream uses
exist. Each method has inherent limitations which must be examined to
determine appropriate methods for recommending stream flow quantities on a
site-specific basis. The following describes in detail several of the more
commonly used and accepted methods.
TENNANT METHOD
One of the widely known examples of an instream flow method is the Tennant
method (1976). Based on analyses conducted on 11 streams in Montana,
Wyoming and Nebraska, Tennant determined the following:
(1) Changes in aquatic habitat are remarkably similar among streams having
similar average flow regimes.
(2) An average stream depth of 0.3 meters and an average water velocity of
0.75 ft/sec were the critical minimum physical requirements for most
aquatic organisms.
II-l-l
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(3) Ten percent of the average annual flow would sustain short-term
survival for most fish species.
(4) To sustain good survival habitat, thirty percent of the average annual
flow was adequate since the depth and velocities generally would allow fish
mi gration.
(5) Sixty percent of flow provides outstanding habitat.
Using the above information, Tennant proposed a range of percentages of the
average annual flow regime needed to maintain desired flow conditions on a
semi-annual basis. These ranges are summarized by the following:
Recommended flow regime
Flow Description October-March April-September
Flushing 200% of the average annual flow
Optimum*range 60%-100% of the average annual flow
Outstanding 40% 60%
Excellent 30% 50%
Good 20% 40%
Fair, Degrading 10% 30%
Poor, Minimum 10% 10%
Severe Degradation <10% <10%
The determination of average annual flow was conducted by Tennant by the
summation of the average monthly flow for a ten year period. After average
annual flows are determined, recommendations can be calculated by
multiplying the average annual flow by the percentages in the above table.
INSTREAM FLOW INCREMENTAL METHODOLOGY (IFIM)
The IFIM is a computerized water management tool developed by the U.S.
Fish and Wildlife Service for evaluating changes on aquatic life and
recreational activities resulting from alterations in channel monphology,
water quality and hydraulic components. Bovee (1982) outlined the
underlying principles of IFIM as: (1) each species exhibits preferences
within a range of habitat conditions that it can tolerate; (2) these ranges
can be defined for each species; and (3) the area of stream providing these
conditions can be quantified as a function of discharge and channel
structure. IFIM is designed to simulate hydraulic conditions and habitat
availability for a particular species and size class or usable waters for a
particular recreational activity. The hydraulic and channel
characteristics are simulated for IFIM by use of the Physical Habitat
Simulation Model (PHABSIM).
PHABSIM is a series of computer programs which relate changes in flow and
channel structure to changes in physical habitat availability. Hilgart
(1982) summarized the PHABSIM model as comprised of two parts: (1) a
hydraulic simulation program which will predict the values of hydraulic
II-1-2
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parameters for a range of flows from either a single measured flovv (WSP) or
two or more measured flows
called HABTAT, which rates
relative fisheries values.
series of depth, velocity
(IFG4), and (2) a habitat assessment program
the predicted hydraulic conditions for their
Rather than describing the stream reach as a
and substrate contours, PHABSIM is used r.o
describe the reach as a series of small cells (Figure II-l-l).
Figure II-l 1: Conceptualization of Simulated Stream Reach. Shade-
Subsections Have Similar Depth and Velocity Ranges.
Instead of summarizing average depth and velocity for a cross sectin,,
PHABSIM is used to predict the average depth and velocity for each cei;.
Using curves showing the relative suitability of various stream attributes
by species and life stage.
substrate in each cell
multiplied together to
combination of variables,
surface area of the cell.
a weighting factor for the depth, velocity, and
is determined. These weighting factors are
estimate the composite suitability for that
and this composite index is multiplied by t-ie
This process is repeated for each cell and the
results are summed to calculate the total weighted usable area. Computer
simulations are then produced for the distribution of microhabitat
variables for existing and alternate flows, e.g., flows for a proposed and
alternative actions which could affect flow regime.
The basic steps to IFIM can be summarized by the following:
STEP 1: Project Scoping - Scoping involves defining objectives for
the delineation of study area boundaries, determining the
stability of the microhabitat variables, selecting evaluation
species, and defining their life history, food types, water
quality tolerances and microhabitat.
STEP 2: Study Reach and
Site Selection -
reaches
delineating critica
major changes and transition
the evaluation species.
Involves identifying and
to be sampled, delineation of
zones and the distribution of
II-1-3
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STEP 3: Data Collection - Transects are selected to adequately
characterize the hydraulic and instream habitat conditions.
Data gathering must be compatible to IFIH computer models.
STEP 4: Computer Simulation - Involves reducing field data and
entering into programs described above.
STEP 5: Interpretation of Results - The output from the computer
program is expressed as the Weighted Usable Area (WUA), a
discrete value for each representative and critical study
reach, for each life stage and species, and for each flow
regime.
For further information on IFIM and PHABSIM the following publication
should be consulted: "A Guidance to Stream Habitat Analysis Using the
Instream Flow Incremental Methodology" U.S. FWS/OBS-82/26, June, 1982.
II-1-4
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CHAPTER II-2
SUSPENDED SOLIDS AND SEDIMENTATION
The consideration of the potential effects of suspended solids and
sedimentation on aquatic organisms may reveal important data and
information pertinent to a use attainability analysis. Suspended solids
generally may affect fish populations and fish in several major ways:
(1) "By acting directly on the fish swimming in water in which solids are
suspended, and either killing them or reducing their growth rates,
resistence to disease, etc.;
(2) By preventing the successful development of fish eggs and larvae;
(3) By modifying natural movements and migrations of fish; and
(4) By reducing the abundance of food available to the fish" (EIFAC,
1964).
(5) By hindering the foraging and mating abilities of visual feeders and
those with visual mating displays.
The effects of sedimentation on aquatic organisms were summarized by
Iwamoto et al. (1978). These effects include:
(1) clogging and abrasion of respiratory surfaces, especially gills;
(2) adhering to the chorion of eggs;
(3) providing conditions conducive to the entry and persistence of
disease-related organisms;
(4) inducing behavioral modifications;
(5) entomb different life stages;
(6) altering water chemistry by the absorption and/or adsorption of
chemicals;
(7) affecting utilizable habitat by the scouring and filling of pools and
riffles and changing bedload composition;
(8) reducing photosynthetic growth and primary production, and;
(9) affecting intragravel permeability and dissolved oxygen levels.
This chapter of the manual will explore these effects in detail. An
excellent review of the effects of suspended solids and sedimentation on
warmwater fishes was conducted by EPA in 1979 entitled "Effects of
Suspended Solids and Sediment on Reproduction and Early Life of Warmwater
Fishes" (EPA-600-3-79-042) and should be consulted.
GENERAL ECOSYSTEM EFFECTS
Suspended solids and sedimentation may affect several trophic levels and
components of the ecosystem. The interactions between components of the
II-2-1
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ecosystem are closely linked thus changes in one component can reverberate
throughout the system. The following examines changes in each component
resulting from suspended solids and sedimentation:
Influences on Primary Productivity
Increases in suspended solids can greatly alter primary productivity
because of decreasing light penetration and subsequently decreasing
photosynthetic activity. Cairns (1968) reviewed the literature on the
effects on primary producers. The decrease in light penetration can affect
the depth distribution of vascular aquatic plants and algae. Greatly
reduced light penetration may shift algal composition from green to
bluegreen since the latter are tolerant to higher levels of ultraviolet
light. Butler (1964) observed an inverse relationship between turbidity
and primary productivity; gross primary productivity in a clear pond was
three-fold greater than an adjacent turbid pond (with Permian red clay).
Benson and Cowell (1967) found that turbidity in Missouri River
impoundments was the strongest limiting factor to plankton abundance and
that plankton was of great importance to fish growth and survival.
Suspended solids can also alter the distribution of heat in a water body.
Butler (1963) reported that colloidal clay in central Oklahoma was altering
the heat distribution and consequently summer stratification was more
pronounced in turbid situations. This stratification causes greater
differences between the surface and bottom temperature in turbid water
bodies.
To protect against the deleterious effects of suspended solids on aquatic
life by decreasing photosynthetic activity, EPA (1976) developed the
following criteria: "Settleable and suspended solids should not reduce the
depth of the compensation point for photosynthetic activity by more than 10
percent from the seasonally established norm for aquatic life." The
compensation point is the point at which incident light penetration is
sufficient for plankton to photosynthetically produce enough oxygen to
balance their respiration requirements. To determine this compensation
point, a set of "light" bottle D.O. and "dark" bottle D.O. tests would be
needed (see "Standard Methods", APHA, 1979 for details).
Effect on Zooplankton and Benthos
Benthic macroinvertebrates and zooplankton are major sources of food for
fish which can be adversely affected by suspended matter and sediment.
Depopulation and mortality of benthic organisms occurs with smothering or
alteration of preferred habitats. Zooplankton populations may be reduced
via decreasing primary productivity resulting from decreased light
penetration. Ellis (1936) demonstrated that freshwater mussels were killed
in silt deposits of 6.3 to 25.4 mm of primarily adobe clay. Major
increases in stream suspended solids (25 ppm turbidity upstream vs. 390 ppm
downstream) caused smothering of bottom invertebrates, reducing organism
diversity to only 7.3 per square foot from 25.5 per square foot upstream
(Tebo, 1955). Deposition of organic materials to bottom sediments can also
cause imbalances in stream biota by increasing bottom animal density,
principally oligochaete populations, and diversity is reduced as pollution
11-2-2
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sensitive forms disappear. Deposition of organic materials can also cause
oxygen depletion and a change in the composition of bottom organisms.
Increases in oligochaetes and midges may occur since certain species in
these groups are tolerant of severe oxygen depletion.
Sensitivity of Fish Populations to Suspended Solids and Sediment
Field and laboratory studies have shown that fish species vary considerably
in their population-level responses to suspended solids and sediment.
Atchison and Menzel (1979) reviewed the population level effects on
warmwater species and categorized species as either tolerant or intolerant
based on their habitat preferences. This review also revealed species with
a preference for turbid systems. Tables 1 and 2 have been adapted from
this review and provide valuable information on population effects. As can
be seen from these tables, the intolerant assemblage is composed of a large
number of species with complex spawning behavior whereas the tolerant
fishes include a larger percentage of simple spawners and forms with
special early life adaptations for turbid waters.
Effects on Fish Reproduction
The impacts of suspended solids and sediments on fish reproduction vary
with the phases of the reproductive cycle. The following describes several
of the mechanisms of impairment:
(1) Diminished Light Penetration
Swingle ("1956) provided data which shows that suspended materials might
affect fish reproductive processes by reducing light penetration. He found
that largemouth bass spawning was delayed by as much as 30 days in muddy
ponds as compared to clear ponds.
(2) Visual Interference
Some species such as black bass and centrarchid sunfish have strong visual
components in their reproductive behavior. For example, Trautman (1957)
found that smallmouth bass populations in Lake Erie shunned potential
spawning areas that were highly turbid. Chew (1969) observed that in
turbid Lake Hoi lingsworth (Fla.) largemouth bass spawning was very limited
and that most females failed to shed their eggs and gradually resorbed
them.
(3) Loss of Spawning Habitat
Reproductive failure among many species is attributable to direct loss of
spawning habitat through two pathways: (a) siltation of formerly clean
bottom and (b) loss of vegetation due to the reduction of the photic zone
by turbidity.
(4) Physiological Alterations
the major physiologicalalterations are:
(a) the failure of gonadal maturation at the appropriate time and (b)
stress incurred by the organism thus creating increased susceptability to
disease.
In general, laboratory bioassays indicate that larval stages of selected
species are less tolerant of suspended solids than eggs or adults.
Available evidence suggests that lethal levels for suspended solids are
determined by interaction between biotic factors, including age-specific
and species specific differences, and abiotic factors such as particle
size, shape, concentration and amount of turbulence in the system.
II-2-3
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TABLE 1: SELECTED MIDWESTERN WARMWATER FISHES WHICH ARE INTOLERANT OF
SUSPENDED SOLIDS (TURBIDITY) AND SEDIMENT
Species
Spawni
Ichthyomyzon - Chestnut lamprey
castaneus X
Acipenser - Lake Sturgeon
fulvescens X
Polyodon spathula - Paddlefish X
Lepisosteus - Shortnose gar
platostomus
Ami a calva - Bowfin X
Hiodon tergisus - Mooneye
Esox lucius - Northern pike X
Esox masquinongy - Muskel lunge
Clinostomus - Redside dace
elongatus
Dionda nubila - Minnow
Exoglossum laurae - Tonguetied minnow
Exoglossum - Cutlips minnow
maxil 1 ingua
Hybopsis amblops - Bigeye chub
Hybopsis dissimilis - Streamline chub
Hybopsis x-punctata - Gravel chub
Nocomis biguttatus - Horneyhead chub X
Nocomis micropogoh - River chub
Notropis amnis - Pallid shiner
Notropis boops - Bigeye shiner
Notropis cornutus - Common shiner
Notropis emiliae - Pugnose minnow
Notropis heterodon - Blacknose shiner
Notropis heterolepis - Blacknose shiner
Notropis hudsonius - Spottail shiner
Notropis rubellus - Rosyface shiner
Notropis stramineus - Sand shiner
Notropis texanus - Weed shiner
Notropis topeka - Topeka shiner
Notropis volucellus - Mimic shiner
Carpiodes velifer - Highfin carpsucker
Cycleptus elongatus - Blue sucker
Erimyzon oblongus - Creek chubsucker
Erimyzon sucetta - Lake chubsucker
Hypentelium nigricans - Northernhoq
sucker
Lagochila lacera - Harelip sucker
Minytrema melanops - Spotted sucker
Moxoxtoma carinatum - River redhorse
Moxostoma duquesnei - Black redhorse
Moxostoma valenciennesi - Greater redhorse
Ictalurus furcatus - Blue Catfish
Effect
ng General
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Impact
Suspended so
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
through
lids Sediment
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
II-2-4
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TABLE 1: SELECTED MIDWESTERN WARMWATER FISHES WHICH ARE INTOLERANT OF
SUSPENDED SOLIDS (TURBIDITY) AND SEDIMENT (Cont'd)
Species
Etheostoma - Greenside darter
blennioides
Etheostoma exile - Iowa darter
Etheostoma tippecanoe - Tippe canoe
darter
Etheostoma zonal e - Banded darter
Perca flavescens - Yellow perch
Percina caprodes - Log perch
Percina copelandi - Channel darter
Percina evides - Gilt darter
Percina maculata - Blackside darter
Percina phoxocephala - Slenderhead
darter
Noturus flavus - Stonecat
Noturus furiosus - Caroline madtom
Noturus gyrinus - Tadpole madtom
Nocturus miurus - Brindled madtom
Nocturus trautmani - Scioto madtom
Pylodictis ol i van's - Flathead catfish
Percopsis - Trout perch
omi scomaycus
Fundulus notatus - Blackstripe
topminnow
Labidesthes sicculus - Brook silverside
Culaea inconstans - Brook stickleback
Ambloplites rupestris - Rock bass
Lepomis gibbosus - Pumpkin seed
Lepomis megalotus - Longear sunfish
Micropterus dolomieui - Smallmouth bass
Micropterus salmoides - Largemouth bass
Ammocrypta asprella - Crystal darter
Ammocrypta clara - Western sand darter
Ammocrypta pellucida ~ Eastern sand
darter
Effect
Spawning General
X
X
X
X
X X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X X
X
X
X
X
Impact
Suspended so
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
' X
X
X
X
X
through
lids Sediment
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
II-2-5
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TABLE 2: WARMWATER FISHES WHICH ARE TOLERANT OF SUSPENDED SOLIDS AND SEDIMENT
Species
Scaphi rhynchus a"! bus - Pallid sturgeon
Dorosoma cepedianum - Gizzard shad
Hiodon alosoides - Goldeye
Carassius auratus - Goldfish
Couesius plumbeus - Lake chub
Cyprinus carpi o Common Carp
Ericymba buccata - Silverjaw minnow
Hybopsis gelida - Sturgeon chub
Hybopsis gracilis - Flathead chub
Notropis dorsal is - Bigmouth shiner
Notropis lutrensis - Red shiner
Orthodon microlepidotus - Sacramento blackfish
Phenacobius mirabilis - Suckermouth minnow
Phoxinus oreas - Mountain redbelly dace
Pimephales promelas - Fathead minnow
Pimephales vigil ax - Bullhead minnow
Plagopterus argentissimus - Woundfin
Semotilus atromaculatus - Creek chub
Catostomus commersoni - White sucker
Ictiobus cyprinellus - Bigmouth buffalo
Moxostoma erythrurum - Golden redhorse
Ictalurus catus - White catfish
Ictalurus melas - Black bullhead
Aphredoderus sayanus - Pirate perch
Lepomis cyanellus - Green sunfish
Lepomis humilis - Orangespotted sunfish
Lepomis microlophus - Redear sunfish
Micropterus treculf - Guadalupe bass
Pomoxis annul aris - White crappie
Pomoxis nigromaculatus - Black crappie
Etheostoma gracile - Slough darter
Etheostoma micriperca - Least darter
Etheostoma nigrum - Johnny darter
Etheostoma spectabile - Orangethroat darter
Stizostedion canadense - Sauger
Aplodinotus grunniens - Freshwater drum
General Preference
tolerance for turbid systems
X
X
X
X
X
X
X X
X
X
X
X
X
X
X
X X
X
X
X
X
X
X
X
X X
X
X
X
X
X
X
X
X
X
X
X
X
X
II-2-6
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CHAPTER II-3.
POOLS, RIFFLES AND SUBSTRATE COMPOSITION
AQUATIC INVERTEBRATES
Many factors regulate the occurrence and distribution of stream-dwelling in-
vertebrates. The most important of these are current speed, shelter, tempera-
ture, the substratum (including vegetation), and dissolved substances. Other
important factors are liability to drought and to floods, food and competition
between species. Many of these factors are interrelated - current, for
example, largely controls the type of substratum and consequently the amount
and type of food available. Of these, current speed, the substratum, and the
significance of riffle and pool areas will be discussed in greater detail in
the following paragraphs.
Current Speed
Many invertebrates have an inherent need for current, either because they rely
on it for feeding purposes or because their respiratory requirements demand
it. However, persistently very rapid current may make life intolerable for
almost all species. At the other extreme, stagnant or very slow areas in
rivers which at time flow swiftly are often without much fauna. This is
because silt collects during periods of low discharge, and the conditions
become unsuitable for riverine animals. On the other hand, many common stream
creatures (e.g. flatworms, annelids, crustaceans, and a great number of the
insects) persist in running water simply because they avoid the current by
living under stones or in the dead water behind obstructions. Still other
animals which are poor swimmers and lack attachment mechanisms and therefore
can only scuttle from one shelter to another select areas where the current is
tolerable, and move further out or back into shelter as the flow varies. This
applies to many genera of mayflies and to snails. Other animals actually bur-
row down into the substratum to avoid the current and require only to remain
buried. Many animals, such as the annelids and some Diptera larvae, have this
habit as a birthright; several other groups have acquired this habit, such as
several genera and species of stoneflies and mayflies. Similarly, as the
current changes from place to place in a stream at a given discharge so the
fauna changes.
In conclusion, current speed is a factor of major importance in running water.
It controls the occurrence and abundance of species and hence the whole struc-
ture of the animal community.
The Substratum and Its Effect On Aquatic Invertebrates
The substratum is the material (including vegetation) which makes up the
streambed. It is true of many river systems that the further down a river the
smaller the general size of the particles forming the bed. This is partly due
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to the fact that the shear stress on the bottom and hence the power to move
(and break up) particles decreases with increasing discharge. In streams where
current speeds do not normally exceed about 40 cm/sec a streambed is likely to
be sand, or even silt at still lower maximum currents of about 20 cm/sec. How-
ever, large amounts of silt occur only in backwaters and shallows or as a
temporary thin sheet over sand during periods of low flow; silt is certainly
not a major component of the substratum in the main channels of the great
majority of even base-level rivers. Where currents frequently exceed about bu
cm/sec on steep slopes the bed is likely to be stony and the animals which
live there must be able to maintain their position.
The substratum is the major factor controlling the occurrence of animals and
there is a fairly sharp distinction between the types of fauna found on hard
and on soft streambeds. In general, clean and shifting sand is the poorest
habitat with few specimens of few species. Bedrock, gravel and rubble on the
one hand and clay and mud on the other, especially when mixed with sand, sup-
port increasing biomasses. The fauna of hard substrata has its own typical
character, and it is here that most of the obviously specialized forms occur;
that of the soft substrata is more generally shared with still water, and it
shows much more geographical variety.
The fact that rubble supports more animals than does sand is almost certainly
correlated with the amount of living space (shelter) and with the greater pro-
bability that organic matter will lodge among stones and provide food.
Another factor affecting the occurrence of fauna in the substratum is the
temporary nature of some types of substratum themselves. For example, stony
areas can be alternately covered with silt or sand and then cleared away by
spring floods (spates). Streams that are more liable to spates or other
similar phenomena (which greatly and rapidly alter the fauna! density) have
less abundant and less varied faunas than others. An interesting consequence
of this is that small tributaries, being less exposed to the effects of storms
covering limited areas, are richer than the larger streams into which they
flow. Another consequence is that as development increases the intensity of
runoff, the variety and abundance of stream fauna also decreases.
The presence of solid objects also affects the fauna, and the nature of the
solid object affects the animals which colonize it. As shelter is more impor-
tant, some animals prefer irregular stones as opposed to smooth ones. Still
other animals occur only on wood.
Other factors which may account for differences of invertebrate biomass in
streams or reaches of streams are the differences in plant detritus and in
vegetation on the banks, which, of course, supplies food to the biota. Both
the amounts and the nature of the deposits and the vegetation are important.
In any case there are more animals in moss, rooted plants, and filamentous
algae than there are on stones, and all plants are more heavily colonized than
the nonvegetated areas of substratum.
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Finally, the availability of food (whether it be organic detritus lodged
amongst stones, vegetation, wood. . . ) is an obvious factor controlling the
abundance of species. Generally speaking species occur, or are common, only
where their food is readily available, but it should not be forgotten that few
running water invertebrates are very specialized in their diets.
It seems appropriate at this time to restate the three ecological principles
of Theisemann (Hynes, 1970) which summarize the implications of the foregoing
discussion. They are:
o The greater the diversity of the conditions in a locality the larger is
the number of species which make up the biotic community.
o The more the conditions in a locality deviate from normal and hence
from the normal optima of most species, the smaller is the number of
individuals of each of the species which do occur.
o The longer a locality has been established in the same condition the
richer is its biotic community and the more stable it is.
In conclusion, it can be stated that the fauna of clean, stable, diverse stony
runs is richer than that of silty reaches and pools both in number of species
and total biomass.
As previously discussed, certain species are confined to fairly well-defined
types of substraum, and others are at least more abundant on one type than
they are on others. The result of these preferences is that as the type of sub-
stratum varies from place to place so does the fauna. In general, the larger
the stones, and hence the more complex the substratum, the more diverse is the
invertebrate fauna.
The following groups of invertebrates almost invariably provide the major con-
stituents of the fauna of stony streams:
o Parazoa
o Cnidaria
o Tricladida
o Oligochaeta
o Gastropoda
o Pelecypoda
o Peracarida
o Eurcarida
o Plecoptera
o Odonata
o Ephemeroptera
o Hemiptera
o Megaloptera
o Trichoptera
o Lepidoptera
o Coleoptera
o Diptera
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The fauna of the softer substrata in rivers is much less evident than that of
the hard substrata. However, there are still many genera of invertebrates such
as Limnaea, Chironomus. Tubifex, and Limnodrilus which can be found in rivers
in most continents, but the less-rigorous habitat of areas of slower current
which allows less-specialized species to -occur also permits the local charac-
ter of the fauna to be dominant.
It is therefore difficult to generalize, but characteristic organisms of'soft
riverine substrata are: Tubificldae, Chironomidae, burrowing mayflies lhPhe-
meridae, Potomanthidae, Polymitarcidae), Prosobranchia, Unionidae, and Sphae-
riidae, and when plants are present a great variety of organisms may be added.
Riffle/Pool Areas
Natural streams tend to have alternating deep and shallow areas - pools and
riffles - especially where there are coarse constituents in the substratum.
Riffles tend to be spaced at more or less regular distances of five to seven
stream widths apart and to be most characteristic of gravel-bed streams. They
do not naturally form in sandy streams, since their presence seems to be con-
nected with some degree of heterogeneity of particle size. Riffles are formed
when the larger particles (boulders, stone and gravel) congregate on bars.
The reasons for the regular spacing of riffles is unknown; however, it is
known that riffles do not move, although the stones that compose them may mi-
grate downstream, being replaced by others. Furthermore, it has been estab-
lished that riffles are superficial features with the largest stones in the
upper layer.
Pools tend to be wider and deeper than the average stream course. In contrast
to the broken surface of riffles, the surface of a pool or backwater is
smooth. In pools, the current is reduced, a little siltation may occur, and
aquatic seed plants may form beds. The significance of riffle/pool areas to
the production potential of aquatic invertebrates has been alluded to in the
previous discussions of the current speed and the substratum. One result of
the complex interaction of local factors on faunal density is that in streams
with pool and riffle structure, the fauna is considerably denser on the lat-
ter. Similarly, aquatic invertebrates are most diverse in riffle areas with a
rubble substrate. As a consequence the amount, of drift produced by riffles is
greater than that produced by pools.
FISHES
Like the invertebrates, there are many factors which regulate the occurrence
and distribution of running water fishes. The most important of these are the
substratum, food availability, cover, current speed, and the presence of a
suitable spawning habitat. All of these are directly related to the distribu-
tion of pool/riffle areas in a stream, and for most fishes a 1:1 ratio of pool
to riffle run areas is sufficient for successful propagation and maintenance.
The significance of the substratum (type and amount), and the presence of both
pools and riffle areas will be discussed in greater detail in the following
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paragraphs. Finally, the specific habitat requirements of several fish species
(including black & white crappie, channel catfish, cutthroat trout, creek chub
and bluegill) will be discussed in order to illustrate the importance of the
substratum and the pool/riffle structure and to indicate the similarities and
differences in requirements between species.
The Substratum and Its Effect on Fishes
A few fishes, particularly small benthic species, are more or less confined to
rocky or stony substrata. These include all those with ventral suckers and
friction plates (e.g. some species of darters). Many others are also fairly
definitely associated with a specific type of substratum. For example, the gud-
geon is associated with gravel, the sand darter with sand, and the mudfish
with thick marginal vegetation.
For the great majority of fish species, however, the nature of the substratum
is apparently of little consequence except at times of breeding. Nearly all
species of fish have fairly well-defined breeding habits and requirements. The
great majority of freshwater fishes spawn on a solid surface (such as a flat
area under a large stone) in stoney or gravel substrata. Other species dig
pits in gravel (e.g. the stoneroller) in which the eggs are laid. This re-
quires that the gravel be a suitable size and be relatively free of silt and
sand. Still other species make piles of pebbles (e.g. some chubs and minnows)
through which water passes freely bringing oxygen to the buried eggs. Some
species of trout and Atlantic salmon select places for spawning where there is
a down-flow of water, say at the downstream end of pools, where the water
flows into riffles. In summary, species which construct nests (see Table
II-3-1) or redds are restricted not only in respect of the size of the mate-
rial of the substratum, which they must be able to move, but by the need to be
free of silt; and salmonids, and probably some other fishes, are also restric-
ted to places where there is a natural intra-gravel flow of water.
On the other hand, there are a great many species (e.g. the whitefish, ster-
let, grayling, etc.) which breed on gravel or stones but build no nests. In
fact, this is probably the most common pattern of breeding among running-water
species. Table II-3-2 is a partial list of fish species (which build no nests)
along with their desired spawning habitat. The fishes which breed in this
manner move onto the clean gravel in swifter and shallower water than is their
normal adult habitat to spawn.
There are also those species which spawn on other substrata besides stones and
gravel, including sand (e.g. the log-perch), mud (e.g. the Murray cod), and
vegetation (e.g. some species of darters and most still-water species).
Finally, there are many riverine species (e.g. grass carp, some perch species)
which lay buoyant or semi-buoyant eggs which float in the water and are
carried downstream while they develop.
In conclusion, it can be seen from the previous discussion that breeding
habitat requirements for fishes can be very restrictive, and consequently, the
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TABLE II-3-1. EXAMPLES OF NEST-BUILDING FISH
Species Type of Nest
Sticklebacks (Gasterosteidae) Nest a circular
Largemouth Bass (Micropterus salmoides) depression in mud,
Crappies (Pomoxis) silt, or sand and
Rock Basses (Ambloplites) often in and among
Warmouth (Chaenobryttus) roots of aquatic
Bluegill (Lepomis macrochirus) flowering plants
Most Bullheads (Ictalurus)
Small mouth Bass (Micropterus dolomieu) Nest a circular
Trouts (Salmo) depression in
Stoneroller (Campostoma anomalum) gravel
Brook Trout (Salvelinus fontinalis)
Creek Chubs (Semotilus) Nest a pile of
Bluntnose & Fathead Minnows (Pimephales) pebbles
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TABLE II-3-1. EXAMPLES OF FISH THAT DO NOT BUILD NESTS
species
Northern Pike (Esox lucius)
Carp (Cyprinus carpio)
Goldfish (Carassium auratus)
Golden Shiner (Notemigonus crysoleucas)
Whitefishes (Coregonus)
Ciscos (Leucicthys)
Lake Trout (Salvelihus namaycush)
Log Perch (Percina caprodes)
Suckers (Catostomus)
Walleyes (Stizosstedion)
Yellow Perch (Perca flavescens)
White Perch (Morone americana)
Grass Carp (Ctenopharyngodon idellus)
Brook Silverside (Labidesthes sicculus)
Alewife (Alosa pseudoharengus)
Siamese Fighting Fish (Betta)
Bitterling (Rhodeus)
Lumpsucker (Careproctus)
Spawning Habitat^
Scattering eggs over
aquatic plants, or
their roots or
remains
Scattering eggs over
shoals of sand, gra-
vel , or boulders
Semi-buoyant or
buoyant eggs
Eggs deposited in the
mantle cavity of a
freshwater mussel
Eggs deposited
beneath the carapace
of the Kamchatka crab
II-3-7
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suitable breeding sites can be extremely limited. Furthermore, the require-
ments can be extremely varied among species. However, the general breeding
habitat requirements fall into the following categories:
o Build a nest and breed on stone or gravel substrata.
o Breed on stone or gravel substrata without building a nest.
o Breed on other substrata, including sand, mud, or vegetation.
o Lay buoyant or semi-buoyant drifting eggs and larvae.
Pool Areas
Pool areas in a stream are essential for providing shelter for both resting
and protection from predation. To a lesser extent pools are important as a
spawning habitat and for food production (although food production is lower in
pools than in riffles).
Even the streamlined species that are well adapted to fast-flowing water (e.g.
salmon and trout) need time to rest or seek shelter to avoid predators. As a
matter of fact all fishes spend most of their time resting in shelters in
lower velocity pool areas. Still other species (e.g. channel catfish, particu-
larly adults) reside primarily in pool areas and generally move only to riffle
areas at night to feed.
Therefore, based on the foregoing discussion, one must conclude that the exis-
tence of pools is critical to the well-being of all fish species, since they
provide resting cover and protection from predators.
Riffle/Run Areas
As discussed previously in the section on benthic invertebrates and again in
the section on the substratum and its affect on fishes, it is apparent that
riffle areas are most important due to their food producing capability (i.e.
benthic invertebrates) and their suitability as a fish spawning habitat (i.e.
it is in riffle areas where the silt-free stone or gravel exists and where oxy-
gen to the eggs is constantly being renewed). Without an abundant food supply
and the proper spawning habitat, propagation and maintenance of a fish species
would be impossible.
Species Examples
Bluegill (Lepomis macrochirus)
The bluegill is native from the Lake Champlain and southern Ontario region
through the Great Lakes to Minnesota, and south to northeastern Mexico, the
Gulf States, and the Carolinas.
Bluegills are most abundant in large low velocity (<10 cm/sec preferably)
streams. Abundance has been positively correlated to a high percentage (>60%)
of pool area and negatively correlated to a high percentage of riffle/run
areas.
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Cover in the form of submerged vegetation, logs, brush and other debris is uti-
lized by bluegills. Excessive vegetation can influence both feeding ability
and abundance of food by inhibiting the utilization of prey by bluegills.
Bluegills are guarding, nest building lithophils. Nests are usually found in
quiet shallow water over almost any substrate; however, fine gravel or sand is
preferred.
In summary, riffles and substrate play a small role in the life cycle of the
bluegill. In fact, excessive riffle/run areas have been negatively correlated
with an abundance of bluegills. On the other hand, pools are significant as
the typical bluegill habitat for resting, feeding, and spawning.
Creek Chub (Semotilus atromaculatus)
The Creek Chub is a widely distributed cyprinid ranging from the Rocky Moun-
tains to the Atlantic Coast and from the Gulf of Mexico to southern Manitoba
and Quebec. Within its range, it is one of the most characteristic and common
fishes of small, clear streams.
The optimum habitat for creek chubs is small, clear, cool streams with mode-
rate to high gradients, gravel substrate, well-defined riffles and pools with
abundant food, and cover of cut-banks, roots, aquatic vegetation, brush, and
large rocks. Creek chubs are found over all types of substrate with abundance
correlated more with the amount of instream cover than with the substrate
type. It is assumed that stream reaches with 40-60% pools are optimum for pro-
viding riffle areas for spawning habitat and pools for cover.
Rubble 'substrate in riffles, abundant aquatic vegetation, and abundant stream-
bank vegetation are conditions associated with high production of food types
consumed by creek chubs.
Spawning occurs in gravel nests constructed by the male in shallow areas just
above and below riffles to insure a good water exchange rate through the creek
chub redds. Reproductive success of creek chubs varies with the type of spawn-
ing substrate available. Production is highest in clean gravel substrate in
riffle-run areas with velocities of 20-64 cm/sec. Production is negligible in
sand or silt.
In summary, pools, riffles and substrate are important to the creek chub in
the following manner.
1) Riffles - provide a suitable spawning habitat,
2) Substrate - a clean gravel substrate is required for spawning, and
3) Pools - provide resting cover and abundant food.
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White Crappie (Pomoxis annularis)
The white crappie is native to freshwater lakes and streams from the southern
Great Lakes, west to Nebraska, south to Texas and Alabama, east to North Caro-
lina, then west of the Appalachian Mountains to New York. It has been widely
introduced outside this range throughout North America.
White crappie are most numerous in base-level low gradient rivers preferring
low velocity areas commonly found in pools, overflow areas, and backwaters of
rivers. In these areas, cover is important for providing resting areas and pro-
tection from predation. Cover also provides habitat for insects and small for-
age fish, which are important food for the crappie. In addition, cover is
important during reproduction as the male white crappie constructs and guards
nests over a variety of substrates almost always near vegetation or around sub-
merged objects.
In summary, riffles and substrate composition are for the most part insignifi-
cant to the white crappie. However, pools are important for resting, feeding,
spawning and providing protection from predation.
Channel Catfish (Ictalurus punctatus)
The native range of channel catfish extends from the southern portions of the
Canadian prairie provinces south to the Gulf States, west to the Rocky Moun-
tains, and east to the Appalachian Mountains. They have been widely introduced
outside this range and occur in essentially all of the Pacific and Atlantic
drainages in the 48 contiguous states.
Optimum riverine habitat for the channel catfish is characterized by a diver-
sity of velocities, depths and structural features that provide cover and
food. Low velocity (<15 cm/sec) areas of deep pools and littoral areas and
backwaters of rivers with greater than 40 percent suitable cover are desir-
able. Riffle and run areas with rubble substrate, pools, and areas with debris
and aquatic vegetation are conditions associated with high production of aqua-
tic insects consumed by channel catfish. A riverine habitat with 40-60% pools
would be optimum for providing riffle habitat for food production and feeding
and pool habitat for spawning and resting cover.
Adult channel catfish in rivers are found in large, deep pools with cover.
They move to riffles and runs at night to feed. Catfish fry have strong
shelter-seeking tendencies and cover availability is important in determining
habitat suitability. However, dense aquatic vegetation generally does not pro-
vide optimum cover because predation on- fry by centrarchids is high under
these conditions.
Dark and secluded areas are required for nesting. Males build and guard nests
in cavities, burrows, under rocks and in other protected sites.
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In summary, the presence of riffles and pools are equally important to the suc-
cessful propagation of channel catfish, with riffles providing a suitable
habitat for food production and feeding and with pools providing a suitable
habitat for spawning and resting. Additionally, channel catfish appear to be
relatively insensitive to variations in the substrate type.
Cutthroat Trout (Salmo clarki)
Cutthroat trout are a polytypic species consisting of several geographically
distinct forms with a broad distribution and a great amount of genetic diver-
sity.
Optimal cutthroat trout riverine habitat is characterized by clear, cold
water; a silt free rocky substrate in riffle-run areas; an approximately 1:1
pool/riffle ratio with areas of slow, deep water; well vegetated stream banks;
abundant instream cover; and relatively stable water flow, temperature regimes
and stream banks. A 1:1 ratio (40-60% pools) of pool to riffle area appears to
provide an optimal mix of trout food producing and rearing areas.
Cover is recognized as one of the essential components of trout streams. Cover
is provided by overhanging vegetation; submerged vegetation, undercut banks
and instream objects. The main use of this cover is predator avoidance and
resting.
Conditions for spawning require a gravel substrate with _< 5% fines. Greater
than 30% fines will result in a low survival rate of embryos. Optimal sub-
strate size averages 1.5 - 6.0 cm in diameter; however, gravel size as small
as 0.3 cm in diameter is suitable for incubation.
Black Crappie (Pomoxis nigromaculatus)
The black crappie is native to freshwater lakes and streams from the Great
Lakes south to the Gulf of Mexico and the southern Atlantic States, north to
North Dakota and eastern Montana and east to the Appalachians.
Black crappie are common in base or low gradient streams of low velocities,
preferring quiet, sluggish rivers with a high percentage of pools, backwaters,
and cut-off areas. Black crappie prefer clear water and grow faster in areas
of low turbidity.
Abundant cover, particularly in the form of aquatic vegetation, is necessary
for growth and reproduction. Common daytime habitat is shallow water in dense
vegetation and around submerged trees, brush or other objects.
Conclusions
In conclusion, a review of the substratum and its effects on benthic inverte-
brates and fishes reveals that the invertebrates are dependent on a suitable
substrata for growth, successful reproduction, and maintenance, and the fishes
are dependent on a suitable substrata primarily only during breeding. With the
II-3-11
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proper substrata, an adequate supply of benthic invertebrates is available as
food for the fishes.
Similarly, it is the proper balance between pools and riffles (approximately
1:1 ratio) that will insure an abundant food supply for both invertebrates and
fishes, the existence of the proper habitat for reproduction of both inverte-
brates and fishes, and adequate cover for resting and protection from pre-
dation.
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CHAPTER 11-4
CHANNEL CHARACTERISTICS AND
EFFECTS OF CHANNELIZATION
INTRODUCTION
Channelization can be defined as modification of a stream system - including
the stream channel, stream bank, and nearstream riparian areas - in order to
increase the rate of drainage from the land and conveyance of water down-
stream. Simpson et al. (1982) listed the common methods of channelization as:
1. Clearing and Snagging. Removal of obstructions from the streambed and
banks to increase the capacity of a system to convey water. Such oper-
ations include removal of bedload material, debris, pilings, head walls,
or other manmade materials.
2. Rip-rapping. Placement of rock or other material in critical areas to
minimize erosion.
3. Widening. Increase of channel width to improve the conveyance of water
and increase the capacity of the system.
4. Deepening. Excavation of the channel bottom to a lower elevation so as
to increase the capacity to convey water or to promote drainage or lower-
ing of the water table, or to enhance navigation.
5. Realignment. Construction of a new channel or straightening of a channel
to increase the capacity to convey water.
6. Lining. Placement of a nonvegetative lining on a portion of a channel to
minimize erosion or increase the capacity of a stream to convey or con-
serve water.
Channelization projects are classified according to their magnitude as either
short-reach or long-reach. Short-reach channelization is associated with road
and bridge construction and may entail 0.5 km of stream length within the vi-
cinity of the crossing. Although short-reach projects may adversely affect
stream biota, they should not produce significant long-term impacts with pro-
per mitigation (Bulkley et al. 1976). The comments in this chapter generally
refer to the effects of long-reach channelization; those impacts are greater
in duration, dimension, and severity. Simpson et al. (1982) listed the pur-
poses of (long-reach) channelization as:
1. Local flood control to prevent damage to homes, industrial areas, and
farms on the flood plain by increased stream conveyance of water past
the protected areas;
II-4-1
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2. Increase of arable land for agriculture by channel straightening, deep-
ening, and widening to remove meanders, increase channel capacity, ana
lower the channel bed. Straightening reduces the stream area and length
of bordering lands, increases land area at cutoffs, and increases flow
velocity. Deepening and widening increases channel capacity and improves
drainage from adjacent lands;
3. Increased navigability of waterborne commerce and recreational boating,
usually performed in large streams; and
4. Restoration of hydraulic efficiency of streams following unusually se-
vere storms.
In the interest of such goals, several thousand miles of streams in the United
States have been altered over the past 150 years (Simpson et al. 1982). How-
ever, in achieving these goals, detrimental effects are often incurred on
water quality and stream biota. This chapter addresses the effects of channel-
ization on stream characteristics and the associated biological impacts.
CHARACTERISTICS OF THE STREAM SYSTEM
Stream Depth and Width
The depth and width of a stream are usually made uniform (generally by widen-
ing and deepening) by stream channelization in order to increase the hydraulic
efficiency of the system. This practice results in a monotony of habitats
throughout the modified reach. Gorman and Karr (1978) demonstrated the direct
relationship that exists between habitat diversity (considering depth, sub-
strate, and velocity) and fish species diversity. Alteration of stream depth
involves the disturbance and removal of natural bottom materials. Increasing
stream depth can lower the water table of the area. Probably the most signi-
ficant impact of depth modification is the disruption of the run-riffle-pool
sequence (See Chapter II-3: Pools, Riffles, and Substrate Composition). Wid-
ening a stream increases the surface area and often involves removal of stream-
side vegetation. These practices increase the amount of light received by the
water column and can lead to changes in the productivity and trophic regime of
the system. Increasing and regularizing stream width also may reduce the pro-
portion of bank/water interface, which constitutes important wildlife habitat.
Stream Length
Stream channelization usually involves realignment of the stream channel in
order to convey water more quickly out of the modified reach. By straightening
a stream its overall length is decreased. Channelized streams have been short-
ened an average of 45 percent (ranging from 8 to 95 percent) in Iowa (Bulkley
1975) and approximately 31 percent in Southcentral Oklahoma (Barclay 1980).
Shortening the linear distance between two points with a constant change in
elevation increases the slope or gradient of the stream, causing a corre-
sponding increase in current velocity. Reducing the time required for a given
parcel of water to flow through a stream segment may lower the capacity of the
11-4-2
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stream to assimilate wastes and increase the organic loading on downstream
reaches.
The obvious effect of reducing stream length is the loss of living space.
Stream segments that are isolated by channelization eventually become
eutrophic and fill with sediment (Winger et al. 1976), and their function is
severely impaired. In these eutrophic habitats, normal stream benthos,
especially mayflies, stoneflies, caddisflies, and he! Igramites, are replaced
by tolerant chironomids and oligochaetes (Hynes 1970).
In addition to the loss of total living space, the amount of valuable edge
habitat is decreased by stream straightening. Fish are habitat specialists
(Karr and Schlosser 1977) and are not found uniformly distributed throughout
the water column. Most fish and macroinvertebrate species utilize cover in
lotic systems, much of which is associated with the sloping stream bank.
Channel Configuration
A stream is straightened by cutting a linear channel that eliminates natural
bends (meanders) from the main course of flow. Sinuosity is a measure of the
degree of meandering by a stream and is measured as the ratio of channel
length to linear length or down-valley distance (Leopold et al. 1964). Sinu-
osity index values may range from 1.0 for a straight conduit to as high as 3.5
for mature, winding rivers (Simpson et al. 1982). A high gradient mountain
stream may have a sinuosity index of 1.1, while a value of 1.5 or greater jus-
tifies designation as a meandering stream (Leopold et al. 1964).
Channelization (straightening) decreases sinuosity. Reducing sinuosity de-
creases the total amount of habitat available to biota as well as the amount
of effective and unique habitat. Zimmer and Bachman (1976, 1978) found that
habitat diversity was directly related to the degree of meandering in natural
and channelized streams in Iowa, and that as sinuosity increased the biomass
and number of organisms in the macroinvertebrate drift increased. Drift of ben-
thic invertebrates is a major food source of fish.
The S-shaped meanders commonly observed in streams serve as a natural system
of dissipating the kinetic energy produced by water moving downstream (Leopold
and Langbein 1966). When a stream is straightened the energy is expended more
rapidly, resulting in increased scour during high-flow periods.
Bedform
Bedform, or vertical sinuosity, is a measure of riffle-pool periodicity and is
expressed in terms of the average distance between pools measured in average
stream widths for the section (Leopold et al. 1964). Leopold et al. (1964) re-
ported that natural streams have a riffle-pool periodicity of five to seven
stream widths. This is variable, however, and is dependent on gradient and
geology (as is horizontal sinuosity). Channelization eliminates or reduces
II-4-3
-------
riffle-pool periodicity (Huggins and Moss 1975, Lund 1976, Winger et al. 1976,
Bulkley et al. 1976. Griswold et al. 1978).
Disruption of the run-riffle-pool sequence has detrimental consequences on mac-
roinvertebrate and fish populations. Creating a homogeneous bedform drasti-
cally reduces habitat diversity and leads to shifts in species composition.
Griswold et al. (1978) concluded that riffle species (heptageniids, hydro-
sychid, elmids) in macroinvertebrate communities are replaced by slow water
forms (chironomids and tubifictds) after channelization of warmwater streams.
Riffles are commonly considered to be the most productive areas in the stream
in terms of macroinvertebrate density and diversity. Also, the benthic fauna
adapted to riffles are highly desirable fish food species. Pools can support
an abundant benthic fauna, but pool-adapted forms are not as heavily utilized
by fish. Habitat diversity provided by the run-riffle-pool sequence also con-
tributes greatly to species richness in the fish community.
Velocity and Discharge
Stream velocity is a function of stream gradient and channel roughness. Rough-
ness is a measure of the irregularity in a drainage channel, which will reduce
water velocity, and is affected by sinuosity, substrate size, instream vege-
tation, and other obstructions (Karr and Schlosser 1977).
Discharge or flow (Q) is the volume of water moving past a location per unit
time, and is related to velocity as follows:
Q = VA
3
where Q = discharge (ft /s)
V = velocity (ft/s) 2
A = cross-sectional area (ft ).
By increasing the slope and reducing roughness, channelization often increases
water velocity (King and Carlander 1976, Simpson et al. 1982); however, if the
cross-sectional area of the channel is sufficiently enlarged by widening and
deepening, the average velocity may be unchanged or decrease (Bulkley et al.
1976, Griswold et al. 1978). In either case, the velocity is usually made uni-
form by channelization.
The concept of unit stream power has been developed to predict the rate of sed-
iment transfer in streams. Unit stream power (USP) is defined as the rate of
potential energy expenditure per unit weight of water in a channel (Karr and
Schlosser 1977) and can be calculated by the following equation (Yang 1972):
aY ax aY
= - " = MS.
at at dx Vb
11-4-4
-------
where t = time (s)
V = average stream velocity (ft/s)
S = slope or gradient of the channel 'ft/100 ft)
Y = elevation above a given point and is equivalent to the potential
energy per unit weight of water (i.e., foot-pounds of energy per
pound of water)
X = longitudinal distance
USP = unit stream power, (foot-pounds of energy per pound of water per
second)
The USP is a measure of the amount of energy available for sediment transport;
however, a stream may carry less than the maximum load depending on the avail-
ability of sediment due to such factors as bank stability, substrate sta-
bility, vegetative cover, and surface erosion.
The effect of channelization on discharge is seasonally variable. During rainy
periods a natural stream tends to overflow its banks, inundating adjacent low-
lying areas. This flood water is temporarily stored and slowly percolates to
the water table. Natural storage dampens runoff surges. Also, the roughness of
natural streams slows conveyance, lengthening the time of energy dissipation.
A variety of channelization practices designed to increase drainage and hydrau-
Mc efficiency (e.g., straightening, removal of channel obstructions, removal
f instream and streamside vegetation, berming and leveeing) result in a sharp-
r flow hydrograph and a shorter flow period following rainfall events (Huish
and Pardue 1978). The hypothetical hydrographs shown in Figure II-4-1 illus-
trate the hydrologic/hydraulic effects of channelization. Channelization is
designed to rapidly convey water off the land and downstream through the con-
duit. Properly-functioning channelized streams amplify the impact of high
flows. Increased flow velocity, discharge, and unit stream power result in ac-
centuated scour, erosion, bank cutting, sediment transport, and hydraulic
loading (flooding); especially below channelized segments. Because of in-
creased hydraulic efficiency, channelized streams return to base flow levels
following rainfall more rapidly than natural streams (see Figure II-4-1), and
can reduce water availability by lowering the water table. Griswold et al.
(1978) concluded that in small, well-drained, agricultural watersheds channel
alterations can lead to complete dewatering of long sections of the stream bed
during drought conditions. Simpson et al. (1982) summarized the seasonal im-
pacts of channelization as causing lower than natural base flows and higher
than normal high flows.
Instream vegetation can be reduced, eliminated, or prevented from reestablish-
ment by high stream velocity.
Current velocity has been cited as one of the most significant factors in de-
termining the composition of stream benthic communities (Cummins 1975). Hynes
(1970) suggested that many macroinvertebrates are associated with specific vel-
ocities because of their method of feeding and respiration. Macroinvertebrate
li
of
er
and
II-4-5
-------
Time
NATURAL STREAM
natural stream
ime
CHANNELIZED STREAM
Figure II-4-1.
Generalized hydrographs of natural and channelized streams
following a rainfall event or season (modified from Simpson
et al. 1982).
II-4-6
-------
drift has been found to increase as discharge decreases (Minshall and Winger
1968) and as velocity increases (Walton 1977, Zimmer 1977).
By altering stream velocity, discharge, and unit stream power, channelization
modifies the natural substrate. Disruption of the streambed may produce shift-
ing substrates that are unstable habitats for rnacroinvertebrates. Scour and
erosion due to high velocity increases stream turbidity and leads to siltation
of downstream reaches. High turbidity can damage macroinvertebrate populations
via abrasive action on fragile species (Hynes 1970) and clogging the gills of
species without protective coverings (Cairns et al. 1971).
High turbidity and velocity in conjunction with a lack of cover is detrimental
to fish. Usually, a very high concentration of sediment is required to direct-
ly kill adult fish by clogging the opercular cavity and gill filaments (Wallen
1951), but detrimental behavioral effects occur at much lower levels (Swenson
et al. 1976). Turbid waters can also hinder the capture of prey by sight-
feeders. An obvious impact of channelization is the loss of habitat due to re-
duced flow and dessication during drought conditions. Productive riffle areas
can be exposed by low flows, thereby directly affecting the benthos and reduc-
ing the food supply of fish. Low dissolved oxygen levels during summer low
flows can eliminate macroinvertebrates with high oxygen requirements (Hynes
1970), and can affect emergence (Nebeker 1971), drift (Lavandier and Caplancef
1975), and feeding and growth (Cummins 1974).The effects of reduced flow on
fish include a degraded food source, and interference with spawning. Concen-
trating fish into a greatly reduced volume can lead to increased competition,
predation, and disease.
Bulkley et al. (1976) found that gradient was a major factor affecting the dis-
tribution of fishes. Thus, modifications in gradient by channelization can
drastically alter the species composition of a fish community.
Substrate
The stream substrate is ultimately a product of climatic conditions and the
underlying geology of the watershed. It is specifically affected by factors
such as gradient, weathering, erosion, sedimentation, biological activity, and
land use. Channelization generally alters the substrate characteristics of a
stream; more often than not, average substrate particle size is reduced
(Etnier 1972, King 1973, Griswold et al. 1978).
The substrate of a stream is one of the most important factors controlling the
distribution and abundance of aquatic macroinvertebrates (Cummins and Lauff
1969, Minshall and Minshall 1977, Williams and Mundie 1978), and therefore,
the impact of channelization on benthic communities is directly related to the
degree to which the substrate is affected. Siltation is especially detrimental
to the benthos and can cause the following impacts:
II-4-7
-------
1. Decreased habitat diversity due to filling of interstitial spaces
(Simpson et al. 1982)
2. Decreased standing crop (Tebo 1955)
3. Decreased density (Gammon 1970)
4. Decreased number of taxa (Simpson et al. 1982),
5. Decreased reproductive success by affecting eggs (Chutter 1969)
6. Decreased productivity (King and Ball 1967)
7. Species shifts from valuable species to burrowing insects and oligo-
chaetes (Morris et al. 1968)
Generally, the impact of channelization via substrate disruption is more sign-
ificant in high gradient headwater streams (where coarse substrates are essen-
tial for protection from a strong current) than in low gradient warmwater
streams. Little or no change in benthic communities has been observed in the
latter stream type following channelization (Wolf et al . 1972, King and
Carlander 1975, Possardt 1976), at least partially because the natural sub-
strate of these ecosystems was not drastically altered by channelization.
Shifting substrates are often a consequence of channelizing streams. The ab-
sence of a stable habitat leads to reductions in macroinvertebrate populations
(Arner et al. 1976). In some streams where channelization has not permanently
disturbed the substrate, rapid recoveries (within one year) in the benthic com-
munity have been observed (Meehan 1971, Possardt et al. 1976, King and
Carlander 1976, Whitaker et al. 1979); however, recovery of macrobenthos can
be very slow (Arner et al. 1976).
Changes in macroinvertebrate populations affect the fish community through the
food chain. Substrate composition is also important to fish reproduction. For
example: trout and salmon require a specific size of gravel in.which to build
redds and spawn; pikes broadcast eggs over aquatic vegetation which requires
silt and mud to grow; sculpins require a slate-type substrate under which they
deposit adhesive eggs; and catfish prefer natural cavities for reproduction
(Pflieger 1975). Siltation can decrease reproductive success by smothering or
suffocating eggs. Channelization can also affect fish adversely by reducing
substrate heterogeneity, thereby decreasing habitat diversity.
Cover
Cover is anything that provides real or behavioral protection for an organism.
It can allow escape from predators, alleviate the need to expend energy to
maintain a position in the current, or provide a place to hide from potential
prey or to just be out of sight. Cover includes rocks, logs, brush, instream
and overhanging vegetation, snags, roots, undercut banks, crevices, inter-
stices, riffles, backwaters, pools, and shadows. Channelization generally de-
creases the amount of cover in a stream. Practices such as modification of the
11-4-8
-------
streambed (usually into a uniform trapezoidal shape), snagging and clearing,
and vegetation removal decrease the total amount and variety of cover, and re-
duce habitat diversity.
Cover such as logs, stumps, and snags provide valuable stable substrate for
macroinvertebrates - especially in streams with a shifting substratum. In-
stream vegetation serves macroinvertebrates as a substrate for attachment,
emergence, and egg deposition. Instream obstructions accumulate leaves, twigs,
and other detritus. This coarse particulate organic matter (CPOM) is used as a
food source by detritivorous invertebrates (shredders). Retention of CPOM re-
duces the organic loading on downstream reaches (Marzolf 1978).
Both fish and aquatic macroinvertebrates use cover for predator avoidance,
resting, and concealment. Simpson et al. (1982) stated that cover can be re-
garded as a behavioral habitat requirement for many fish species, and that re-
moval of cover adversely affects fish populations.
Inundation and Desiccation
The modified hydroperiod typical of channelized streams (illustrated in Figure
II-4-1) often causes downstream reaches to flood more frequently and more in-
tensely, altering floodplain soils and vegetation, and damaging land values
and personal property.
By augmenting land drainage and hydraulic efficiency, channelization has also
led to summer drying of streams and desiccation of adjacent and upstream land
areas. Nearstream riparian areas provide a number of valuable functions which
are often disrupted by channelization. Wetlands assimilate nutrients and trap
sediment from runoff and stream overflow, thereby acting as natural puri-
fication systems (Karr and Schlosser 1977, Brown et al. 1979). Rapid convey-
ance and accumulation of nutrients has led to eutrophication problems down-
stream (Montalbano et al. 1979). Natural fertilization of the floodplain is
prevented by restricting flow to the channel. In natural systems, detritus
entering the stream from backwaters constitutes an important food source for
benthic invertebrates (Wharton and Brinson 1977). Likewise, riparian areas are
often rich sources of macroinvertebrates (Wharton and Brinson 1977) that can
become available to stream fish during floods or serve as an epicenter for re-
populating stream benthos. Some fish (e.g., Esocidae, the pike family) use
swampy areas that are seasonally connected to a stream as spawning and nursery
habitat. Loss of wetlands due to dewatering precludes these functions.
When wetland areas are drained they become available for other types of land
use such as agriculture or development. Conversion of wetlands to pastures and
cropland has frequently occurred following channelization. Relative to wet-
lands, agricultural land uses accentuate runoff, sedimentation, nutrient en-
richment (from fertilizers and animal waste), and toxicant leaching (from
pesticides).
The response of the benthic community to nutrient enrichment (i.e., from agri-
cultural runoff) generally involves the demise of intolerant, "clean-water"
II-4-9
-------
taxa and an increase in numbers and biomass of forms that are tolerant of or-
ganic pollution and low dissolved oxygen; a decrease in species diversity OT-
ten occurs as well.
Land use changes can increase the load of toxic chemicals reaching the stream.
Agricultural and urban runoff contribute a variety of toxicants. Saltwater in-
trusion may become a problem following drainage of coastal wetlands. Chough
sodium chloride is generally not considered a toxic chemical it can oe leinai
to freshwater organisms.) Potential impacts include lethal and chronic ef-
fects, biomagnification (via bioaccumulation'and bioconcentration), and contam-
ination of human food and recreational resources.
The impact of draining and dewatering riparian areas on terrestrial organisms
is extensive. Vegetation (including bottomland hardwoods) tends to undergo a
shift from water-tolerant to water-intolerant forms (i.e., hydric > mesic >
xeric) (Fredrickson 1979, Maki et al. 1980, Barclay 1980). These vegetative
changes along with land use changes and land drainage commonly cause the fol-
lowing impacts on terrestrial fauna:
loss of habitat
loss of cover
loss of food sources
species composition changes
reduced diversity, density, and productivity
increased susceptibility to predation
increased exposure to toxic chemicals.
Streamside Vegetation
Channelization may impact streamside vegetation indirectly through changes in
drainage as described above or directly by the clearing of stream banks and
the deposition of dredge spoils. Clearing, dredging, and spoil deposition typi-
cally result in reduced species diversity and vertical and horizontal struc-
tural diversity of streamside vegetation. Tree removal is performed in many
channelization projects (Fredrickson 1979, Barclay 1980). Removal of woody spe-
cies eliminates wildlife habitat, mast production, canopy cover, and shade.
Other detrimental impacts of channelization on vegetation include dieback, sun-
scald, undercutting, and windthrow (Simpson et al. 1982). Spoils deposited on
the streambank from channel cutting, dredging, and berming generally make in-
fertile, sandy soils that are easily eroded. Subsequent channel maintenance
procedures hinder ecological succession and delay recovery of the stream sys-
tem.
Interception of rainfall by the vegetative canopy lessens the impact of rain-
drops on the soil, and bank stability is enhanced by the binding of soil by
plant roots. Loss of these functions permits the rate of erosion and the
stream sediment load to increase.
II-4-10
-------
Removal of vegetation that shades the stream increases the intensity of sun-
light reaching the water column. A resultant increase in the rate of photo-
synthesis causes changes in the natural pathways of energy flow and nutrient
cycling (i.e., trophic structure). Increased primary production can lead to
amplification of the diurnal variation in pH and dissolved oxygen concen-
tration following channelization (O'Rear 1975, Huish and Pardue 1978, Parrish
et al. 1978). Increasing the incident sunlight raises water temperature. High-
er temperatures increase the rates of chemical reactions and biological pro-
cesses, decrease oxygen solubility, and can exceed the physiological tolerance
limits of some macroinvertebrates and fish - most notably trout (Schmal and
Sanders 1978, Parrish et al. 1978).
In natural stream systems, allochthonous input of organic matter from stream-
side vegetation constitutes the major energy source in low-order streams
(Cummins 1974). A functional group of benthic organisms called shredders uses
allochthonously-derived detritus (CPOM) as a food source, and process it into
fine particulate organic matter (FPOM) which is utilized by another functional
group, the collectors. Removing streamside vegetation greatly reduces the in-
put of allochthonous detritus and allows primary productivity to increase be-
cause of greater light availability. These factors bring about a decline in
shredder populations and an increase in herbivorous grazers which take advan-
tage of increasing algae abundance. In headwater areas, species diversity is
likely to decrease due to the loss of detritivorous taxa, and macroinver-
tebrate density may decline because the swift current of those reaches is not
conducive to planktonic and some periphytic algae forms. Loss of allochthonous
material has less impact on intermediate-order streams because they are natu-
rally autotrophic (P/R>1), except that channelization of upstream reaches re-
duces the amount of FPOM that is received via nutrient spiraling. The liter-
ature contains excellent discussions of energy and materials transport in
streams (Cummins et al. 1973, Cummins 1974, Cummins 1975, Marzolf 1978, Van-
note et al. 1980).
Reductions and changes in the macroinvertebrate community affect the food
source of fishes. Changing availabilities of detritus and algae may skew the
fish community with respect to trophic levels that utilize those energy
sources. Clearing away nearstream vegetation also reduces the input of terres-
trial insects that are eaten by fish.
In addition, streamside vegetation provides cover in the form of shadows, root
masses, limbs, and trees which fall into the stream. Most game fish species
prefer shaded habitats near the streambank.
SUMMARY
The benefits realized by channelizing a stream are often obtained at the ex-
pense of such impacts as:
II-4-11
-------
1. Increased downstream flooding
2. Reduction of groundwater levels and stream dewatering
3. Increased bank erosion, turbidity, and sedimentation
4. Degradation of water quality
5. Promotion of wetland drainage and woodland destruction
6. Promotion of land development (agricultural, urban, residential,
industrial)
7. Loss of habitat and reduced habitat diversity
8. Adverse effects on aquatic and terrestrial communities (productivity,
diversity, species composition)
9 Lowered recreational values
The time required for a natural stream to return to a productive, visually-
appealing body of water is highly variable. Natural recovery of some channel-
ized streams requires better than 30 years. Restoration of the stream channel
and biota can be accelerated by mitigation practices.
The potential negative impacts and time frame of recovery should weigh heavily
in the evaluation of any newly-proposed channelization project.
II-4-12
-------
CHAPTER Il-o
TEMPERATURE
Temperature exerts an Important influence on the chemical and biological
processes in a water body. It determines the distribution of aquatic species;
controls spawning and hatching; regulates activity; and stimulates or
suppresses growth and development. The two most important causes of temper-
ature change in a water body are process and cooling water discharges, and
solar radiation. The consequences of temperature variation caused by thermal
discharges (thermal pollution) continue to receive considerable attention. An
excellent review on this subject may be found in the Thermal Effects section
of the annual literature review issue of the Journal of the Water Pollution
Control Federation. Discussion in this chapter is limited to the influence of
seasonal temperature variation on a water body.
PHYSICAL EFFECTS
Annual climatological cycles and precipitation patterns are controlled by the
annual cycle of solar radiation. Specific patterns of temperature and precipi-
tation, which vary geographically, determine annual patterns of flow to lakes
and streams. In general, winter precipitation in northern latitudes does not
reach a body of water until the spring snow melt. For this reason, streamflow
may be quite low in the winter but increase rapidly in the spring. Low flow
typically occurs in the summer throughout North America.
Changes in season cause changes in water temperature in lakes and streams. The
patterns of temperature change in lakes are well understood. Briefly, many
lakes tend to stratify in the summer, with a warm upper layer (the
epilimnion), a cold bottom layer (the hypolimnion) and a sharp temperature
difference between the two, known as the thermocline. The depth of the
thermocline is determined to large extent by the depth to which solar radia-
tion penetrates the water body. The epilimnion tends to be well oxygenated,
through both algal photosynthesis, and through oxygen transfer from the atmo-
sphere. Surface wind shear forces help mix the epilimnion and keep it oxygen-
ated. The thermocline presents a physical barrier, in a sense, to mixing be-
tween the epilimnion and the hypolimnion. If no photosynthesis takes place in
the hypolimnion, due to diminished solar radiation, and if there is no ex-
change with the epilimnion, dissolved oxygen levels (DO) in the bottom layer
may drop to critical levels, or below. Often water released through the bottom
of a dam has no dissolved oxygen, and may severely jeopardize aquatic life
downstream of the impoundment.
Typical summer and annual lake temperature profiles are presented in Figures
II-5-1 and II-5-2, respectively. In the fall the thermocline disappears and
the lake undergoes turnover and becomes well mixed. The temperature becomes
fairly homogeneous in the winter (Figure II-5-2), there is another wind in-
duced turnover in the spring and the cycle ends with the development of epi-
limnion, hypolimnion and thermocline in the summer.
II-5-1
-------
TEMPERATURE °C
02468 10 12 14 16 18 20 22
10
t£
01
I 20
z
X30
a.
Q40
50
Figure II-5-1.
Summer Temperature Conditions in a Typical
(Hypothetical) Temperate-Region Lake.
• i '—' ' I ,1 I i u_^—-i . - . i... . . 1.1. .1. . . .. • 7 | ,; •"> i.-
MARCH APRIU MAY I J'JNS ' HILY i AUG. I SEPT. I OCT. ' NOV.
Figure II-5-2.
The Seasonal Cycle of Temperature and Oxygen
Conditions in Lake Mendota, Wisconsin, 1906,
(Reid and Wood).
II-5-2
-------
Rivers and streams generally show a much more homogeneous temperature profile,
largely because turbulent stream flow assures good vertical mixing. Neverthe-
less, small streams may undergo temperature variation as flow passes through
shaded or sunny areas, as it is augmented by cool groundwater or warm agri-
cultural or other surface return flow, or as it becomes more turbid and cap-
tures solar radiation in the form of heat.
TEMPERATURE RELATED BIOLOGICAL EFFECTS
Warm blooded homeothermic animals, such as the mammals, have evolved a number
of methods by which to control body temperature. Cold blooded poikilothermic
animals, such as fish, have not evolved these mechanisms and are much more sus-
ceptible to variation in temperature than are warm blooded animals. Perhaps
the most important adaptation of fish to temperature variation is seen in the
timing of reproductive behavior.
Gradual seasonal changes in water temperature often trigger spawning, metamor-
phosis and migration. The eggs of some freshwater organisms must be chilled
before they will hatch properly. The tolerable temperature range for fish is
often more restrictive during the reproductive period than at other times dur-
ing maturity. The temperature range tolerated by many species may be narrow
during very early development but increases somewhat during maturity. Reproduc-
tion may be hindered significantly by increased temperature because this func-
tion takes place under restricted temperature ranges. Spawning may not occur
at all when temperatures are too high. Thus, a fish population may exist in a
heated area only because of continued immigration.
Because fish are cold-blooded, temperature is important in determining their
standard metabolic rate. As temperature increases, all standard metabolic func-
tions increase, including feeding rates. Water temperature need not reach
lethal levels to eliminate a species. Temperatures that favor competitors, pre-
dators, parasites and disease can destroy a species at levels far below those
that are lethal.
Since body temperature regulation is not possible in fish, any changes in am-
bient temperature are immediately communicated to blood circulating in the
gills and thereby to the rest of the fish. The increase in temperature causes
an increase in metabolic rates and the feeding activity of the fish must in-
crease to satisfy the requirements of these elevated levels. Elevated bio-
chemical rates facilitate the transport of toxic pollutants to the circulatory
system via the gill structure, and hasten the effect these toxicants might ex-
ert on the fish. Increased temperature will also raise the rate at which detox-
ification takes place through metabolic assimilation, or excretion. Despite
these mechanisms of detoxification, a rise in temperature increases the lethal
effect of compounds toxic to fish. A literature review on this subject will
also be found in the JWPCF annual literature review number.
The importance of temperature to fish may also be seen in Tables II-5-1 and
II-5-2. The data in these tables were found in references by Carlander (1969,
1972) and Brungs and Jones (1977). Table II-5-1 shows the preferred tempera-
ture for a number of fish and Table II-5-2 shows the range of temperatures
within which spawning may occur in several species of fish.
II-5-3
-------
Preferred temperatures usually are determined through controlled laboratory
experiments although some values published in the literature are based on
field observations. Determination of final temperature preferenda of fish in
the field is difficult because field environments cannot be controlled to
match laboratory studies (Cherry and Cairns, 1982). Temperature preference
studies are based on an acclimation temperature which is used as a reference
point against which to examine the • response of fish to different temperature
levels. The acclimation temperature itself is critical for it affects tne
range of temperatures within which fish prefer to live. This may be seen in
Figure II-5-3 which shows an .increase in preferred temperature and in the
upper threshold of avoidance with an increase in acclimation temperature. The
range between the acclimation and the upper avoidance temperatures is species
specific and is dependent on the acclimation temperature in which the fish
were tested. A greater variability in fish avoidance response is observed in
winter than in summer testing conditions (Cherry and Cairns, 1982).
Temperature preference/avoidance studies are important to an understanding of
the effect of thermal pollution on the biota of a water body. The literature
on temperature preference will be important to the water body survey in two
ways: when the stream reach of interest is affected by thermal pollution or
when ambient temperature patterns may be a contributing factor which deter-
mines the types of fish that might be expected to inhabit a water body under
different management schemes identified during the assessment.
Temperature is also important because it strongly influences self-purification
in streams. When a rise in temperature occurs in a stream polluted by organic
matter, an increased rate of utilization of dissolved oxygen by biochemical
processes is accompanied by a reduced availability of DO due to the reduced
solubility of gases at higher temperatures. Because of this, many rivers which
have adequate DO in the winter may be devoid of DO in the summer.
Bacteria and other microorganisms which mediate the breakdown of organic mat-
ter in streams are strongly influenced by temperature changes and are more ac-
tive at higher than at lower temperatures. The rate of oxidation of organic
matter is therefore much greater during the summer than during the winter.
This means self purification will be more rapid, and the stream will recover
from the effects of organic pollution in a shorter distance during the warmer
months of the year than in the colder months of the year, provided there is an
adequate supply of dissolved oxygen.
Temperature is an important regulator of natural conditions. It has a profound
effect on habitat properties in lakes and streams; on the solubility of gases
such as oxygen, upon which most aquatic life is dependent; on the toxicity of
pollutants; on the rate and extent of chemical and biochemical reactions; and
on the life cycle of poikilothermic aquatic life in general. Since in the con-
text of the water body survey uses are framed in reference to the presence and
II-5-4
-------
36 --
u
UJ
z
o
0.
C/J
LU
OC.
cr
fe
cr
LJ
CL
24--
12--
— Upper Avoidance
—L- Lethal Temp.
— P - Preferred Temp.
•A-Acclimation Temp.
Lower Avoidance
--P
--P
--P
--P
--P
LMB MOS
s/
RBT LMB MOS
COH RBT LMB MOS
12
24
36
ACCLIMATION TEMPERATURE CO
Figure II-5-3. Relationships of preffered (P), avoidance 0, and lethal temp-
eratures to the acclimation (A) temperature for coho salmon (COH), rainbow trout
(RBT), largemouth bass (LMB), and mosquitofish (MOS) from laboratory trials
(from Cherry and Cairns, 1982).
II-5-5
-------
the protection of aquatic life, those factors which support or jeopardize
aquatic life must be considered.
Perhaps the most critical element in the aquatic environment is dissolved oxy-
gen, whose solubility is a function of temperature. Oxygen is added to an aqua-
tic system by photosynthesis and by transfer from the atmosphere. Unfortu-
nately, the availability of dissolved oxygen is apt to be greatest when the
requirement for DO is least, i.e., in the winter when metabolic activity has
been substantially reduced. Conversely, the availability may be lowest when
the demand is greatest.
Consideration of the relationship of temperature and availability of dissolved
oxygen is important to the water body survey, and will require a close examina-
tion of natural seasonal variation in DO and its interaction with treatment
process efficiency, with the oxygen demand of the CBOD and NBOD in waste-
waters, and with the seasonal requirements of aquatic life.
II-5-6
-------
TABLE II-5-1. PREFERRED TEMPERATURE OF SOME FISH SPECIES.
Common name
Species
Latin name
Life Acclimation
Stage Temperature,°C
Preferred
Temperature,0^
Alewife
Threadfin shad
Sockeye salmon
Pink salmon
Chum salmon
Chinook salmon
Coho salmon
Cisco
Lake whitefish
Cutthroat trout
Rainbow trout
Atlantic salmon
Brown trout
Brook trout
Lake trout
Rainbow smelt
Alosa pseudoharengus
Dorosoma petenense
Oncorhynchus nerka
0. gorbuscha
0. keta
0. tshawytscha
0. Kisutch
Coregonus artedii
C. clupeaformis
Sal mo clarki
S. gairdneri
S. salar
S. trutta
Salvelinus fontinalis
Salvelinus namaycush
Osmerus mordax
J 18
J 21
A 24
A 31
A
J
A
J
J
J
J
A
A
A
A
J not given
J 18
J 24
A
A
A
J 6
J 24
A
J
A
20
22
23
23
>19
12-14
10-15
12-14
12-14
12-14
12-14
13
13
13
9-12
14
18
22
13
14-16
12-18
12
19
14-18
8-15
6-14
Grass pickerel
Esox americanus
vermiculatus
J,A
24-26
II-5-7
-------
TABLE II-5-1. PREFERRED TEMPERATURE OF SOME FISH SPECIES. (Continued)
Species Life Acclimation
Common name Latin namp Staae Temperature, °C
Muskellunge
Common carp
Emerald shiner
White sucker
Buffalo
Brown bullhead
Channel catfish
White perch
White bass
Striped bass
Rock bass
Green sunfish
Esox masquinongy
Cyprinus carpio
Notropis atherinoides
Catostomus commersoni
Ictiobus sp.
Ictalurus nebulosus
Ictalurus punctatus
Morone americana
M. chrysops
M. saxat ilis
Ambloplites rupestris
Lepomis cyanellus
J
J
J
J
J
J
A
J
A
A
J
J
J
A
J
A
J
J
J
J
A
J
J
J
J
A
J
J
J
J
J
10
15
20
25
35
Summer
Summer
18
23
26
22-29
6
15
20
26-30
Summer
5
14
21
28
6
12
18
24
30
Preferred
Temperature, °C
26
17
o c
25
27
31
32
33-35
25
19-21
31-34
21
27
31
29-31
35
30-32
10
20
25
31-32
28-30
12
22
26
28
26-30
16
21
25
30
31
II-5-8
-------
TABLE II-5-1. PREFERRED TEMPERATURE OF SOME FISH SPECIES. (Continued)
Species Life Acclimation Preferred
Common name Latin name Stage Temperature,°C Temperature,°C
Pumpkinseed L. gibbosus
Bluegill L. machrochirus
Smallmouth bass Micropterus dolomieui
Spotted bass M. punctulatus
Largemouth bass M. salmoides
White crappie Pomoxis annul aris
Black crappie P. nigromaculatus
Yellow perch Perca flavescens
Sauger Stizostedion canadense
Walleye S. vitreum
Freshwater drum Aplodinotus grunniens
J
J
J
J
A
J
J
J
J
J
J
J
J
J
J
J
J
J
J
J
J
J
J
A
J
A
J,A
A
J,A
A
8
19
24
26
6
12
18
24
30
15
18
24
30
6
12
18
24
30
5
24
27
10
21
31
33
31-31
19
24
29
31
32
20
23
30
31
17
20
27
30
32
26-32
10
26
28
28-29
27-29
24-31
19-24
18-28
20-25
29-31
II-5-9
-------
TABLE II-5-2. SPAWNING TEMPERATURE OF SOME FISH SPECIES.
Species
Common name Latin name
Spawning temperature,°C
approximate
value or optimum
range or peak
Lamprey
Northern brook
Southern brook
Allegheny brook
Mountain brook
Silver
Least brook
Arctic
American brook
Western brook
Pacific
Sea
Sturgeon
Ichthyomyzon fosser
Ichthyomyzon gagei
Ichthyomyzon greeleyi
Ichthyomyzon hubbsi
Ichthyomyzon unicuspis
Ichthyomyzon aepyptera
Lampetra japonica
Lampetra lamottei
Lampetra richardsoni
Lampetra tridentata
Petromyzon marinus
Shortnose
Lake
Atlantic
White
Paddlefish
Gar
Longnose
Shortnose
Acipenser brevi rostrum
Acipenser fulvenscens
Acipenser oxyrhynchus
Acipenser transmontanus
Polydon spathula
Lepisosteus osseus
Lepisosteus platostomus
Bowfin
Ami a calva
Blueback herring Alosa aestivalis
Shad
Alabama
Hickory
Alewife
American
Gizzard
Threadfin
Alosa alabamae
Alosa mediocris
Alosa pseudoharengus
Alosa sapidissima
Dorosoma cepedium
Dorosoma petenense
13-77
15
19
10-12
10-16
12-15
8-20
>8
11-24
8-12
12-19
13-18
9-17
16
19-24
16-19
14-27
19-22
18-21
13-28
11-19
17-29
14-23
17
9-11
21
Spawning
season
month
May-Jun
Mar-May
May
Mar-Apr
Apr-Jun
Mar-May
May-Jul
Apr-Jun
Mar-Jun
Apr
Apr-Jul
Apr-Jun
Apr-Jun
Feb-Jul
May-Jul
May-Jun
Mar-Aug
May-Jul
Apr-Jul
Apr-Jul
Jan-Jul
May-Jun
Apr-Aug
Jan-Jul
Mar-Aug
Apr-Aug
II-5-10
-------
TABLE II-5-2. SPAWNING TEMPERATURE OF SOME FISH SPECIES. (Continued)
Spawning temperature,°C
approximate Spawning
Species value or
Common name
Salmon
Pink
Sockeye
(Kokanee)
Coho
Whitefish
Cisco
Lake
Bloater
Alaska
Least cisco
Kiyi
Shortnose cisco
Pygmy
Round
Mountain
Trout
Golden
Arizona
Cutthroat
Rainbow
Gil a
Atlantic salmon
Brown
Arctic char
Brook trout
Latin name
Oncorhynchus gorbuscha
Oncorhynchus nerka
(anadromous)
Oncorhynchus nerka
(landlocked)
Oncorhynchus kisutch
Coregonus artedii
Coregonus clupeaformis
Coregonus hoyi
Coregonus nelsoni
Coregonus sardinella
Coregonus kiyi
Coregonus reighardi
Prospium coulteri
Prospium cylindraceum
Prospium spilonotus
Salmo aguabonita
Salmo apache
Salmo clarki
Salmo gairdneri
Salmo gilae
Salmo salar
Salmo trutta
Salvelinus alpinus
Salvelinus fontinalis
range
3-7
5-10
7-13
1-5
1-10
5
0-3
0-3
2-5
3-5
0-4
0-4
5-12
7-10
8
10
5-17
8
2-10
1-13
1-13
3-12
optimum season
or peak month
10 Jul-Oct
Jul-Dec
Aug-Feb
Oct-Jan
3 Nov-Dec
Sep-Dec
Nov-Mar
Sep-Oct
Sep-Oct
Oct-Jan
Apr-Jun
Oct-Jan
Oct-Dec
Sep-Dec
Jun-Jul
May
Jan-May
9-13 Apr-Jul/Nov-Feb
Apr-May
4-6 Oct-Dec
7-9 Oct-Feb
3-4 Sep-Dec
9 Aug-Dec
II-5-11
-------
TABLE II-5-2. SPAWNING TEMPERATURE OF SOME FISH SPECIES. (Continued)
Spawning temperature,°C
approximate Spawning
Species value or optimum season
Common name Latin name range or peak month
Dolly Varden
Lake
Inconnu
Arctic grayling
Rainbow smelt
Eulachon
Goldeye
Alaska blackfish
Salvelinus malma
Salvelinus namaycush
Stenodus leucichthys
Thymallus arcticus
Osmerus mordax
Thaleichthys pacificus
Hiodon alosoides
Dallia pectoral is
5-8
3-14
1-5
4-11
1-15
4-8
10-13
10-15
Sep-Nov
Aug-Dec
Sep-Oct
Mar-Jun
Feb-May
Mar -May
May-Jul
May-Aug
Central
mudminnow
Pickerel
Redfin
Grass
Chain
Northern pike
Muskellunge
Chiselmouth
Central
stoneroller
Goldfish
Redside dace
Lake chub
Common carp
Umbra limi
Esox americanus
americanus
Esox americanus
vermiculatus
Esox niger
Esox lucius
Esox masquinongy
Acrocheilus alutaceus
Campostoma anomalum
Carassius auratus
Clinostomus elongatus
Couesius plumbeus
Cyprinus carpio
13
10
Apr
Feb-Apr
7-12 10 Mar-May/Aug-Oct
6-16 8 Mar-May
3-19
9-15 13
17
13-27
16-30
>18
14-19
14-26 19-23
Feb-Jul
Apr-May
Jun-Jul
Apr-Jun
Feb-Nov
May
May-Jun
Mar-Aug
II-5-12
-------
TABLE II-5-2. SPAWNING TEMPERATURE OF SOME FISH SPECIES. (Continued)
Spawning temperature,°C
approximate
Species value or optimum
Common name Latin name range or peak
Utah chub
Tui chub
Brassy minnow
Silvery minnow
Chub
River
Silver
Clear
Rosyface
Peamouth
Hornyhead chub
Shiner
Golden
Satinfin
Emerald
Bridle
Warpaint
Common
Fluvial
Whitetail
S pott ail
Rosyface
Saffron
Sacremento
blackfish
Bluntnose minnow
Fathead minnow
Sacremento
squawfish
Northern
squawfish
Gila atraria
Gil a bicolor
Hybognathus hankinsoni
Hybognathus nuchalis
Hybobsis micropogon
Hybobsis storeriana
Hybobsis winchelli
Hybobsis rubri formes
Mylocheilus caurinus
Nocomis biguttatus
Notemigonus crysoleucas
Notropis analostanus
Notropis atherinoides
Notropis bifrenatus
Notropis coccogenis
Notropis cornutus
Notropis edwardraneyi
Notropis galacturus
Notropis hudsonius
Notropis rubellus
Notropis rubri croceus
Orthodon microlepidotus
Pimephales notatus
Pimephales promelas
Ptychocheilus grandis
Ptychochei lus oregonensis
12-16
16
10-13
13-21
19-28
18-21
10-17
19-23
11-22
24
16-21
18-27
20-28 24
14-27
20-24
15-28 19-21
28
24-28
20
20-29
19-30
15
21-26
14-30 23-24
4
12-22 18
Spawning
season
month
Apr-Aug
Apr-Jun
May-Jun
Apr-May
May-Aug
May-Jun
Feb-Mar
Apr-Jun
May-Jun
Spring
May-Aug
May-Aug
May-Aug
May-Jul
Jun-Jul
Apr-Jul
Jun
May-Jun
May-Jul
May-Jul
May-Jul
Apr-Jun
Apr-Sep
May-Aug
Apr-Jun
May-Jun
II-5-13
-------
TABLE II-5-2. SPAWNING TEMPERATURE OF SOME FISH SPECIES. (Continued)
Common name
Blacknose dace
Longnose dace
Redside shiner
Creek chub
Fallfish
Pearl dace
Sucker
Longnose
White
Flannelmouth
Largescale
Mountain
Tahoe
Blue
Northern hog
Smal1 mouth
buffalo
Bigmouth
buffalo
Spotted sucker
Blackfin sucker
Redhorse
Species
Latin name
Rhinichthys atratulus
Rhinichthys cataractae
Richardsonius balteatus
Semotilus atromaculatus
Semotilus corporal is
Semotilus margarita
Catostomus catostomus
Catostomus commersoni
Catostomus latipinnis
Catostomus macrocheilus
Catostomus platyrhynchus
Catostomus tahoensis
Catostomus elongatus
Hypentelium nigricans
Ictiobus bubalus
Ictiobus cyprinellus
Minytrema melanops
Moxostoma atripinne
Silver redhorse Moxostoma anisurum
River Moxostoma breviceps
Black Moxostoma duquesnei
Golden Moxostoma erythrurum
Shorthead Moxostoma macrolepidotum
Greater Moxostoma valenciennesi
Humpback sucker Xyrauchen texanus
Spawning temperature, °C
approximate
value or optimum
range or peak
16-22 21
! 12-16
s 10-18
s >12
>16
17-18
>5
8-21
13
s >7
us 10-19
11-14
10-15
>15
14-28 17-24
14-27 16-18
13-18
12-18
>13
22-25
13-23
15-22
urn 11-22
i 16-19
Spawning
season
month
May-Jun
May-Aug
Apr-Jul
Apr-Jul
May-Jun
May-Jun
May-Jun
Mar-Jun
Apr-Jun
Apr-Jun
Jun-Jul
Apr-Jun
Apr-Jun
May
Mar-Sep
Apr-Jun
Apr-May
Apr
Apr -May
Apr
Apr-May
Apr-May
Apr-May
May-Jul
12-22
Mar-Apr
II-5-14
-------
TABLE II-5-2. SPAWNING TEMPERATURE OF SOME FISH SPECIES. (Continued)
Spawning temperature,°C
approximate
Species value or optimum
Common name Latin name range or peak
Catfish
White
Blue
Black bullhead
Brown bullhead
Channel
Flathead
Stonecat
Bridled madtom
White River
springf ish
Desert pupfish
Banded ki 1 if ish
Plains kilifish
Mosquitofish
Burbot
Brook stickleback
Threespine
stickleback
Trout-perch
White perch
White bass
Striped bass
Rock bass
Sacremento perch
Flier
Ictalurus catus
Ictalurus furcatus
Ictalurus melas
Ictalurus nebulosus
Ictalurus punctatus
Pylodictis olivaris
Noturus flavus
Noturus miurus
Crenichthys baileyi
Cyprinodon macularius
Fundulus diaphanus
Fundulus kansae
Gambusia af finis
Lota lota
Eucalia inconstans
Gasterosteus aculeatus
Percopsis omiscomaycus
Morone americana
Morone chrysops
Morone saxatilis
Ambloplites rupestris
Archoplites interruptus
Centrarchus macropterus
20-29
>22
>21
>21
21-29 27
22-28
27
25-26
32
>20 28-32
>21 23
28
23
0-2
4-21
5-20
6-21
11-20
12-21
12-22 16-19
16-26
22-28
17
Spawning
season
month
Jun-Jul
Apr-Jun
May-Jul
Mar-Sep
Mar-Jul
May-Jul
Jun-Aug
Jul-Aug
Apr-Oct
Apr-Sep
Jun-Aug
Mar-Oct
Jan-Feb
Apr-Jul
Apr-Sep
May-Aug
May-Jul
Apr-Jun
Apr-Jun
Apr-Jun
May-Aug
Mar -May
II-5-15
-------
TABLE II-5-2. SPAWNING TEMPERATURE OF SOME FISH SPECIES. (Continued)
Common name
Banded pygmy
sunfish
Sunfish
Redbreast
Green
Pumpkinseed
Warmouth
Orangespotted
Bluegill
Longear
Redear
Spotted
Bass
Redeye
Small mouth
Suwannee
Spotted
Largemouth
Species
Latin name
Elassoma zonatum
Lepomis auritus
Lepomis cyanellus
Lepomis gibbosus
Lepomis gulosus
Lepomis humilis
Lepomis machrochirus
Lepomis megalot is
Lepomis microlophus
Lepomis punctatus
Micropterus coosae
Micropterus dolomieui
Micropterus notius
Micropterus punctulatus
Micropterus salmoides
White crappie
Black crappie
Yellow perch
Sauger
Waileye
Pomoxis annularis
Pomoxis nigromaculatus
Perca flavescens
Stizostedion canadense
Stizostedion vitreum
Greenside darter Etheostoma blennioides
Johnny darter Etheostoma nigrum
Channel darter Percina copelandi
Blackside darter Percina maculata
Mottled sculpin Cottus bairdi
Freshwater drum Aplodinotus grunniens
Spawning temperature,
approximate
value or optimum
range or peak
14-23
17-29
20-28
19-29
21-26
19-32 25
22-30
20-32
18-33
17-23
13-23 17-18
s 15-21
12-27 21
14-23 16-20
14-20
4-15 12
4-15 9-15
4-17 6-9
>10
20-21
16-17
10
18-24 23
°C
Spawning
season
month
Mar -May
Apr-Aug
May-Aug
May-Aug
May-Aug
May-Aug
Feb-Aug
May-Aug
Mar-Sep
Mar-Nov
Apr-Jul
Apr-Jul
Feb-Jun
May-Jun
Apr-Jun/Nov-May
Mar-Jul
Mar-Jul
Mar-Jul
Mar-Jul
Mar-Jun
Apr-Jun
Jul
May-Jun
Apr -May
May-Aug
II-5-16
-------
CHAPTER H-6
RIPARIAN EVALUATIONS
Riparian ecosystems can be variously identified but their common element is
that they are adjacent to aquatic systems. Bn'nson et al., (1981) defines
them as "riverine floodplain and streambank ecosystems. Cowardin et al.,
(1979) in their"Classification of Wetlands Habitats of the U.S.", do not
clearly delineate riparian and wetland zones. For this chapter emphasis
will be given to floodplain, riverine and lacustrine riparian habitats and
no distinction has been made between riparian and wetland land
envi ronments.
The primary legislative justification for riparian protection is the Clean
Water Act, specifically that section dealing with water quality. Many
factors enter into the relationship between riparian ecosystems and water
quality; a simple correlation between any single measure of riparian
habitat and water quality does not exist. A well developed riparian zone
is frequently the juncture between terrestrial and aqautic environments and
its characteristics are governed to some extent by both. The riparian zone
is usually related to the adjacent terrestrial environment with respect to
climatic conditions, soil types, land topography etc. The aquatic system
is an integration of upstream drainage (Lotspeich 1980) and has the
riparian zone as an important component. The aquatic effects to the
riparian ecosystem will vary with factors such as stream size, climatic
vegetation and soil type. Although no ideal riparian habitat water quality
scenario is possible, general relationships can be derived.
A critical relationship exists between stream size and the extent of
riparian habitat. Small streams canopied by riparian vegetation will be
more influenced than large streams where riparian canopy represents only a
small fraction of the immediate channel. The small riparian zone in
relation to stream size of many large streams has frequently been cited in
order to diminish the importance of this habitat. The presumption is made
that riparian importance is minimal because the riparian/river size ratio
is small. It is also argued that alteration of smaller streams is
insignificant with respect to the total drainage basin and that such
activities have minimal implications for larger streams. An obvious impact
of large stream riparian modification is shore line destruction and
subsequent loss of near shore stream habitat. Although modification of a
single small tributary may have a minimal effect on the larger water body,
major drainage basin alterations could seriously damage water resources,
the larger stream being a product of its tributaries.
Riparian system have unique ecosystem qualities which should be considered
in addition to their water qualiy values. Riparian zones are cited as
classical ecotones which will usually support greater species and numerical
diversity than adjacent aquatic or terrestrial environments. Large numbers
of rare and endangered animal and plant species reside here. It is often
critical habitat for an entire life span or it may be used in a transitory
manner for reproduction, migration or as hunting territory for raptors and
carnivorous mammals. Even though organisms may not use the riparian zone
II-6
-------
as their primary living habitat, its loss may seriously disrupt foodchain
mechanisms and life history processes. Significant changes in species
numbers, diversity and types may occur in both the terrestrial and aquatic
environments following riparian destruction. It is estimated that less
than two percent of the land area in the U.S. is riparian habitat (Bnnson
et al., 1981). Large portions have been converted to agricultural use,
e.g. the Mississippi bottomland hardwoods, and stream channelization
has destroyed adjacent riparian ecosystems. Timber removal has greatly
reduced riparian habitat in forested regions. Livestock grazing has had
extremely detrimental riparian effects on semi-arid rangelands. Land
values have favored agricultural and urban development immediately adjacent
to the aquatic environment with the exclusion of most natural vegetation.
PHYSICAL RELATIONSHIPS
Key physical stream characteristics are affected by the riparian ecosystem.
Water temperature responds to almost any riparian alteration in smaller
streams. Several studies (Karr and Schlosser 1978, Moring 1975, Campbell
1970) have demonstrated that shade afforded by adjacent vegetation
significantly moderates water temperature, reducing summer highs and
decreasing winter lows. This can have significant effects on many chemical
and biological processes. Chemical reaction rates are temperature
dependent and increased temperature generally increases reaction rates.
Adsorption, absorption, precipitation reactions, decomposition rates, and
nutrient recycling dynamics could all be altered. Many aquatic organisms
have relatively specific temperature requirements. Elevated temperatures
increase poikilotherm metabolic rates causing excessively low production
during food deprivation and the increased temperature may disrupt critical
life stages such as reproduction. Temperatures exceeding or substantially
below optimal requirements, even for relatively brief periods, can
completely alter the biota. Larger streams may not be physically affected
as readily as the smaller tributaries but large scale tributary
modifications could have dramatic downstream consequences.
Another direct physical consequence is alteration in the quality and
quantity of incident solar radiation. Optimal photosynthetic wave lengths,
especially for diatoms, may be altered by the canopy, but as will be
elaborated later, this may not have serious consequences to a diversified
biota. Turbidity will be reduced by riparian vegetation. This too will be
discussed in greater detail. A further loss with reduction in riparian
habitat is the fine particulate matter, especially the nutrient rich
organic material. This may be transferred to the adjacent terrestrial
environment during floods or carried directly to the large streams with
such a reduced residence time in the smaller stream that they become
nutrient limited.
FLUVIAL RELATIONSHIPS
Fluvial characteristics are governed by such processes as stream bank
stability, flow rates, rainfall seasonality and water volumes. Stream bank
stability is important in maintaining stream integrity. This stability is
a function of the local geology and riparian vegetation.
II-6-1
-------
Streams are not static but new channel formation rates are slowed with
increased bank stability. During high water, bank erosion is minimized and
excess flow energy dissipated over floodplains with minimal environmental
damage. Without riparian vegetation, flooding is more erosive and
extensive. Energies are not dissipated readily but remain excessive for
the duration of the high water. The geomorphological consequences can be
considerable; extreme erosion, formation of additional channels, upland
sediment deposition etc. The biological impact can be devastating, with
the aquatic habitat physically destroyed or silted to the extent it is no
longer a biologically viable unit. Under extreme conditions, silt levels
may be sufficient to cause embryo death and physiological damage to gill
breathing organisms. This scenario is best illustrated using the example
of stream channelization. High energy water movement leads to rapid land
drainage but also to extremely damaging floods when stream banks overflow.
Biological communities may become species depauperate, biomass greatly
reduced and those populations remaining may be undesirable compared to
previous inhabitants.
Riparian zone groundwater levels are controlled by adjacent surface water
levels. The vegetated riparian system retains more water and releases it
at slower rates than non-vegetated shore zones. This has important
implications for stream water quality. Flood surge may be diminished
downstream of precipitation events by water movement into non-saturated
riparian soils. This would reduce sediment transport capacity, flooding
and channel erosion. Water movement into the terrestrial water table is
especially important to stream stability in arid regions where rainfall may
occur rarely hut may lead to devastating floods. Stream-side vegetation
moderates the potential impact of local rainfall events by retaining
surface runoff. Groundwater can moderate stream temperatures where
significant flow is derived from underground sources.
BIOLOGICAL RELATIONSHIPS
Primary production is controlled by the quality and quantity of incident
solar radiation, nutrients and plant community structure. In smaller
streams with extensive canopies the radiation quantity may be significantly
reduced and the wavelength distribution altered. This may reduce
production in that section but may at the same time make nutrients more
available to downstream organisms. Water temperature will also be
affected, and photosynthesis may be reduced by cooler water but also
temporarily extended by a reduction in seasonal temperature extremes. Many
stream primary producers, especially diatoms and mosses, have adapted to
reduced light intensity, and relatively high photosynthetic rates are
maintained under low light conditions.
Stream flow characteristics are also affected by debris. Flow rates are
moderated by the pool-riffle morphology common to streams with well
developed riparian systems. It has been demonstrated that the rate of
water movement can be significantly different for a given elevation loss
between well developed pool/riffle complexes and streams which allow free
water flow. The streams with the most complex morphology retain the water
II-6-2
-------
for the greatest period. This has important secondary implications for
groundwater, hydrologic regime, water temperature and biota.
Perhaps the most severe effect on water quality following riparian
destruction is increased channel sedimentation. Agricultural and forestry
practices frequently remove vegetation to the immediate streambank thus
allowing unhindered surface water movement directly into the stream.
Riparian vegetation will retard surface sheet flow, substantially reducing
stream sediment loads. Stream sedimentation results in extreme habitat
diversity loss, and the bottom morphology becomes a monotony of fine
grained sediments. The immediate biotic symptom may be acute suffocation
of the invertebrate fauna with the possibility of chronic physiological
stress. The long term effects are extensive. Table II-6-1 prepared by
Karr and Schlosser (1978) illustrates the relationships between land use
practices and stream sediment loads.
Table II-6-1: POTENTIAL EFFECTS OF VARYING MANAGEMENT PRACTICES ON
EQUILIBRIUMS OF EQUIVALENT WATERSHEDS. THESE ARE BEST ESTIMATES OF
RELATIVE EFFECTS FOR A VARIETY OF WATERSHED CONDITIONS, INCLUDING SOURCES
AND AMOUNTS OF SEDIMENTS.
Management
Practice
Relative Amount of
Sediment From
Land Stream
Surface Channel
Natural watershed
Clear land for
rowcrop agriculture;
maintain natural
stream channel
Channelize stream
in forested
watershed
Clear land and
channelize stream
Best land surface
management with
channelization
Best land surface
and natural channel
Very low Very low
High Low
Very low High
Suspended Source
Solids Load of
in Stream Sediment
Very low
Medium Land surface
High
Channel
banks
High
Low
Low
High
High
Low
Very high Land surface
and channel
banks
Medium to
high
Low to
medium
Channel
banks
Equilibrium
between land
and channel
II-6-3
-------
TABLE II-6-2: COMPARISON OF THE EFFECT OF WELL DEVELOPED AND REDUCED RIPARIAN ZONES ON WATER QUALITY OF SMALL STREAMS
Riparian system
well developed.
Reduced riparian
system
Flow
1. Extremes
moderated
2. Little reaction
to local events
1. Erratic flow
2. Reacts to local
rain events
Temperature
1. High and low
extremes
moderated
2. Reduced daily
fluctuations
1. Extreme
seasonal
variation
2. Extreme daily
fl uctuation
Sedimentation
Moderated by
vegetation
Usually higher
loads, partic-
ularly
following
watershed
disruption
Primary Production
Reduced speciation related
to organisms able to
photosynthesis with
reduced light intensity
Increased production but
often of undesirable
species.
High nutrient loading
and temperatures favor
undesirable speciation
(filamentous blue-green
algae or macrophytes)
Nutrient Load
1. Moderated by
riparian uptake
2. Regulated release
through highly
organic soils.
3. Available supplies
because of riparian
primary production
1. Large seasonal
fluctuations
2. Availability to
stream biota related
to wash out rate,
flooding may remove
nutrients before
they are utilized by
aquatic biota
-------
TABLE II-6-2 (Cont'd)
Diversity
No. Individuals
Biomass
Groundwater
Riparian Vegetation
Surface Water
Diverse speciation with
diverse habitat
selection
May have large speciation
in fish and invertebrates
or as common to western
streams, large in-
vertebrate population
diversity with little
fish diversity
May have large
number of species
with few organisms
for each taxa
Diversity of
organism types
and able to
sustain large
biomass
Slow change
elevation
gaged to
changes in
stream level
in
Self sustaining
with respect to
water, nutrients,
habitat etc.
1. Little flooding
water generally
retained in channel
2. If flood occur,
energy dissipated
by vegetation
Low species numbers
Large number of
organisms for a
few taxa
Large biomass
with little
diversity
Rapid change
following
changes in
stream flow
Rapid soil
drying
Once system degrades
may no longer be
possible to sustain
riparian habitat
without extensive
reworking of the
stream bed and
adjacent upland
1. Large scale flooding
may occur
2. High energy water
flow causing large
erosional losses
-------
Several studies have investigated the use of riparian wetlands for waste
water treatment. Generally, significant phosphorus and nitrogen reductions
occur following varying wetland exposure. EPA Regions IV and V have
prepared documentation for generic EIS statements which address the wetland
alternative to secondary and tertiary waste treatment technology. Riparian
vegetation has also been used to treat urban runoff where it has been found
to significantly reduce treatment costs and sediment loads, and to improve
water quality and greatly moderate flows.
Recent research has indicated that humic acids released from some riparian
ecosystems, particularly wetlands, can significantly affect water quality.
Humates are generally large organic molecules which may sequester
substances making them biologically unavailable or may, conversely, act as
chelating agents making them more available. These phenomena can also
occur with toxic materials. Humates may cause considerable oxygen demand
and significantly affect such chemical properties as COD. These substances
remain largely unclassified and their exact effects unknown.
RIPARIAN CASE HISTORY STUDIES
A long standing controversy has developed in western States where cattle
are permitted to graze adjacent to or in both permanent and intermittent
streams beds (Behnke 1979). The unprotected riparian vegetation is altered
in virtually all respects; species change, biomass is reduced, herbs and
shrubs become almost non-existent. A critical question is how this affects
water quality and ultimately the fishery. Platts (1982), following an
extensive literature review, concluded that studies conducted by fisheries
personnel generally found significant biomass and speciation changes
following "heavy grazing". Similar studies by range personnel frequently
repudiated these results but Platts suggests many were improperly designed
or alternative data interpretations are possible. Platts' overall
conclusion is "Regardless of the biases in the studies, when the findings
of all studies are considered together there is evidence indicating that
past livestock grazing has degraded riparian- stream habitats and in turn
decreased fish populations".
Studies are underway in the western U.S. testing stream exclosures as means
to improve riparian and stream habitat. These are usually qualitative
efforts and frequently do not emphasize water quality or stream biota
surveys. Hughes (personal communication) observed distinct physical and
biological differences between grazed and upgrazed small streams in a study
of a Montana watershed. Grouse and Kindschy (1982) have observed
consideration variation in riparian vegetation recovery following both long
and short term cattle exclosure.
Studies conducted in the Kissimmee-Okeechobee basin, Florida (Council of
Environmental Quality 1978), indicate distinct physical and biological
differences that follow everglade stream channelization. Nutrients once
removed by riparian vegetation make their way to lakes and aid in
accelerating eutrophication. The Corps of Engineers (Council of
Environmental Quality 1978) is using the Charles River watershed in
Massachusetts to control downstream flooding. This project has preserved
large riparian watershed tracts to serve as "sponges" to control abnormally
high runoff. The preservation of southwestern playas and their vegetation
II-6-6
-------
has assumed added importance* following realization of their function _in
groundwater recharge and wildfowl preservation (Bolen 1982). Prarier
potholes have long been recognized as critical bird and mammal habitat and
recent studies have demonstrated that they too act as nutrient sinks,
groundwater recharge areas and as important mechanisms to retain excessive
precipitation and surface runoff (van de Valk et al., 1980). Southern
bottomland hardwood forests are essential for both indigenous fauna and
migratory birds but also are critical water management areas to retain
excessive runoff to prevent flooding.
The value of the freshwater tidal riparian zone to aquatic fauna is
considerable. Many commercially important anandromous fish require nearly
pristine environmental conditions to breed. Perhaps the best documented
example is the Pacific Coast Salrnonid fishery which is. extremely sensitive
to physical and chemical alterations. Increased sedimentation and
temperatures associated with riparian vegetation removal can destroy a
historical fishery. Large number of commercial and non-commercial
(sniffen, personal communication) east coast fish depend on extensive
freshwater floodplains during their life cycle. South eastern .U.S. salt
marshes, perhaps an extended riparian definition, are critical for numerous
commercially important organisms. The panaeid shrimp totally depend on
this environment during the early stages of their life cycle (Vetter,
personal communication). It has been hypothesized that these marshes are
critical to many near shore organisms through organic carbon export (Odum
1973). Several midwestern fish species also are dependent on riparian
habitat, the muskelunge requiring it for completion of their life cycle.
Table 11-6-2 is an abbreviated summary of differences between small stream
with well developed riparian zones and streams with- a reduced riparian
zone.
ASSESSMENT OF RELATIONSHIPS BETWEEN RIPARIAN AND AQUATIC SYSTEMS
A variety of methods exist to measure water quality in physical, chemical
and biological terms. These are treated in Chapter III-2 and will not be
discussed here. Riparian environmental measures are similar to those used
in terrestrial ecology (Muel ler-Dumbois and Ellenberg 1974).
Ties between the aquatic and riparian or the aquatic, riparian and upland
environments can only be estimated. There is a paucity of such
information because of the extremely high research costs and the inability
to devise procedures to test experimental hypotheses.
The results are that most such evaluations are qualitative. Their quality
is based on the integrity and knowledge of the person making the
evaluation. The remainder of this section lists physical, chemical and
biological factors which might be 'considered when evaluating the riparian
aquatic interaction. It is not meant to be exhaustive but only an example
of factors affecting the interactions.
I. Riparian Measures and Their Effect on Water Quality
A. Geomorphology (erosion, runoff rate, sediment loads)
1. Slope
2. Topography
3. Parent material
II-6-7
-------
B. Soils (sediment loads, nutrient inputs, runoff rates)
1. Particle size distribution
2. Porosity
3. Field saturation
4. Organic component
5. Profile (presence or absence of mottling)
6. Cation exchange capacity
7. Redox (Eh)
8. pH
C. Hydrology (water budget, flooding potential, nutrient loads)
1. Groundwater
a. Elevation
b. Chemical quality
c. Rate of movement
2. Climatic factors
a. Total annual rainfall and temporal distribution
1) Chemical quality
b. Temperature
c. Humidity
d. Light
II. Vegetative and Faunal Characteristics
A. Floristics ("community health", disturbance levels)
1. Presence/absence
2. Nativity
B. Vegetation (nutrient loads, "community health", disturbance levels)
1. Production
2. Biomass
3. Decomposition
4. Litter dynamics
a. Detritus
1) Size
2) Transportability
3) Quantity
5. Plant size classes
a. Grasses, herbs (forbs), shrubs, trees
6. Canopy density and cover
a. Light intensity
7. Cover values
C. Fauna (community disturbance, community health)
1. Production
2. Biomass
3. Mortality
D. Community structure
1. Diversity
2. Evenness
II-6-8
-------
III. Physiological Processes
A. Transpirational water loss (community health)
B. Photosynthetic rates (community health)
IV. Streambank characteristics
A. Stream sinvosity
B. Stream bank stability (sediment loads, habitat availability)
II-6-9
-------
"SECTION III : CHEMICAL EVALUATIONS
-------
CHAPTER III-l
WATER QUALITY INDICES
One of the most effective ways of communicating information on environ-
mental trends to policy makers and the general public is by use of
indices. Many water quality indices have been developed which seek to
summarize a number of water quality parameters into a single numerical
index. As with all indices the various components need to be evaluated
in addition to the single number. U.S. EPA (1978) published an
excellent review of water quality indices entitled "Water Quality
Indices: A Survey of Indices Used in the U.S." which provides the
reader with the types of indices used by various water pollution
control agencies. The purpose of this chapter is to identify and
explain the various indices that would be applicable to a use attain-
ability analysis. The choice of indices is at the discretion of the
States and will primarily be dictated by the water quality parameters
traditionally analyzed by the State.
NATIONAL SANITATION FOUNDATION INDEX (NSFI)/WATER QUALITY INDEX (WQI)
Brown et al (1970) presented a water quality index based upon a
national survey of water quality experts. In this survey respondents
were asked (1) which variables should be included in a water quality
index, (?.} the importance (weighting) of each variable and (3) the
rating scales (sub-index relationships) to be used for each variable.
Based on this survey, nine variables were identified: dissolved oxygen
pH, nitrates, phosphates, temperature, turbidity, total solids, fecal
coliform, and 5-day biochemical oxygen demand. Appropriate weights
were assigned to each parameter. The index is arithmetic and is based
on the equation:
WQI A = £ w.tq:
where: WQIA"= the water quality index, a number between 0 and 100.
%;= a quality rating using the rating transformation curve.
u);= relative weight of the th parameter such that =1.
Figures A-l-9 show the rating curves and relative weights for each of
the parameters. To determine the water quality index follow these
steps:
(1) determine the measured values for each parameter
(2) determine q for an individual parameter by finding the
appropriate value from curves (Figures A 1-9)
(3) multiply by the weight (w) listed on each figure
(4) add the wq for all parameters to determine the water
quality index (a number from 0-100)
The water quality index can then be compared to a "worst" or "best"
case stream. Examples of a best and worst quality stream cases follow:
in-i
-------
Best Quality Stream
Measured
values
Inch" vidual
quality
rating
Weights
(WL)
Overal1
quality
rating
(qo< w.
DO, percent sat.
Fecal coliform
density, # /100 ml
pH
BOD mg/1
Nitrate, mg/1
Phosphate, mg/1
Temperature °C
departure from equil
Turbidity, units
Total solids, mg/1
100
0
7.0
0.0
0.0
0.0
0.0
0
25
98
100
92
100
98
98
94
98
84
0.17
0.10
0.08
0.08
WQI=lwLqL= 96.3
Worst Quality Stream
16.7
0.15
0.11
0.11
0.10
0.10
15.0
10.1
11.0
9.8
9.8
7.8
6.7
Parameters
DO. percent sat.
Fecal col i form
density, # /100 ml
pH
BOD , mg/1
Nitrate, mg/1
Phosphate, mg/1
Temperature °C
departure from equil
Turbidity, units
Total solids, mg/1
Measured
values
0
5
2
30
100
10
+15
100
500
Individual
qual ity
rating
(qj
0
4
4
8
2
6
10
18
20
Weights
(w-)
0.17
0.15
0.11
0.11
0.10
0.10
0.10
0.08
0.08
Overal 1
qual ity
rating
(q;x wL)
0
0.6
0.4
0.9
0.2
0.6
1.0
1.4
2.4
= 7.5
III-l-l
-------
MTU OMLITY 1KO
MITHMTIC «A* —
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NOTE:
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cot.!Foitn. AVCRA&C itumw or oMAMism m 100 «t
figure A-2
III-1-2
-------
M
A
T
i
WATER QUALITY INDEX
A«IT*«TIC .rtAN ---- 30J CONFIDENCE LIMITS
90
80
70
60
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2345678 9.101112
PH. UNITS
fiqur* A-J
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III-1-3
-------
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III-1-4
-------
QUALITY IWQ
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11BOSBITY >iOO JTU
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III-1-5
-------
H
A
r
c
*
QUALITY
TOTAL SOLIDS
ntA« --- • MX
tiwn
us
90
80
"3
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TOTAL SOLIDS. N6/L
Hl-1-6
-------
DINIIJS WATER QUALITY INDEX
In 197?, Dinius proposed a water quality index as part of a larger social
accounting system designed to evaluate water pollution control
expenditures. This index includes 11 variables and like the NSFI, it has a
scale which decreases with increased pollution, ranging from 0 to 100. The
index is computed as the weighted sum of its sub indices. The 11 variables
included in the index are: dissolved oxygen, biological oxygen demand,
Eschericia coli, alkalinity, hardness, specific conductivity, chlorides,
pH, temperature, coliform, and color. This index is unique in that the
calculated water quality index could be matched to specific water uses.
Dinius proposed different descriptor language for different index ranges
depending on the specific water use under consideration as illustrated in
Figure A-100. The index values can be derived from the following formula:
0
++
= 5(00)
5
535 (SC)
1
-0
54(ALK)
+ .5
Note: If
+ 214(ROD)
+
U * 7D IP
•m
the
9
r
+
+
+
PH
+
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/o
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>6;
)
2
7.3, 100
3
'tt(HA)
I
+ 224 +
+
should
128(C)
1
be subs
;uted for
for the pH expression. If pH is greater than 7.3, the pH
expression should be 10
DO = dissolved oxygen in percent saturation
BOD = biological oxygen demand in mg/1
E.coli = Fschericia coli as E.coli per ml
Coli = coliform per ml
SC = specific conductivity expressed in microhms per an at 25°C
Cl = chlorides in mg/1
HA = hardness as ppm CaCO
ALK = alkalinity as ppm CaCO
pH = pH units
Ta = actual temperature
Ts = standard temperature (average monthly temperature)
C = Color units
Once the quality unit is determined based on the above calculation, a
comparison to Figure A-10 should reveal the quality of the water for a
specific use.
HARKINS/KENDALL WATER QUALITY INDEX
A statistical index was developed by Harkins (1974) using a nonparametric
classification procedure developed by Kendall (1963). The procedure was
summarized by Harkins by the following four steps:
(1) For each water quality parameter used, choose a minimum or maximum
value as a starting point. This sector of values is the control
observation from which standardized distances will be computed.
III-1-7
-------
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Supply and A«ri- Trana-
fr, Wlldlire cultural portation
Fig. 10 Geaerftl ratine 3C*i* for tht quality unit.
III-l-E
-------
(2) Rank each column of water quality parameters including the control
value. Tied ranks are split in the usual manner.
(3) Compute the rank variance for each parameter using the equation:
Variance (R;. ) =(^rtx [(n3- n) - £(tt - tj]
where: i = l,2...p, ^''
p = the number of parameter being used
n = the number of observations plus the number of control
points, and
k = the number of ties encountered.
These variances are used to standardize the indices computed.
(A) For each member of observation vector, compute the standardized
distances:
where R is the rank of the control value.
This index is meant as a method for summarizing a large amount of data to
present a concise picture of overall trends. This method provides a
simple, expedient method whereby one station can be compared with another
or previous time periods from a particular station may be compared with
another time period at the same station. A detailed example of this index
may be found in Harkins (1974).
OTHER INDICES
Many other water quality indices have been developed; some being variations
of the indices described previously. Several States (Georgia, Oregon,
Nevada, Illinois) have developed their own systems based on the
characteristics of the water bodies of the State. McOuffie and Haney
(1973) proposed an eight-variable water quality index which was applied to
streams in New York State.
III-1-9
-------
CHAPTER III-2
pH, HARDNESS, ALKALINITY AND SALINITY
INTRODUCTION
The chemical composition and the chemical interactions of the aquatic environ-
ment exert an important influence on the aquatic life of a water body. Many
chemical constituents in a body of water have the ability to alter the toxic-
ity of specific pollutants, or to protect organisms from toxic materials by
removing them or by blocking their action. The importance to aquatic life of
four water quality parameters - pH, alkalinity, hardness and salinity - is
discussed in this section.
pH
The pH of water is a measure of its acid or alkaline nature. Specifically, it
is an expression of the hydrogen ion activity of the solution. Hydrogen ion
activity is mathematically related to the hydrogen ion concentration [H ], and
for most natural waters these may be considered equivalent. pH is expressed as
the negative logarithm of the hydrogen ion concentration:
pH = - log [H+]
The water molecule, H^O, ionizes to yield one hydrogen and one hydroxyl ion:
H20 =^ H+ + OH"
The equilibrium expression for this reaction is:
K - CH
[H20]
The concentration of water, [H^O], is considered to be a constant, and the
equation simplifies to:
Kw = [H+][OH-] = 10'14
-14
Because the product of the concentration of both ions is always 10 , when
they are equal to each other,
[H+] = [OH~] = 10"7, and
pH = - log (10~7) = 7.
At pH 7 the solution is neutral. When there are more hydrogen ions than hydrox-
yl ions, the pH is less than 7 and the solution is acidic. When there are more
hydroxyl ions, the pH is greater than 7 and the solution is alkaline.
III-2-1
-------
The pH of most natural freshwaters in the U.S. is between 6 and 9. It is inter-
esting to note that the pH of most ocean waters falls in a much narrower
range, 8.1 to 8.3 (Warren 1971). This is due to the presence of several buffer-
ing systems in salt water which control pH changes. In freshwater, pH is regu-
lated primarily by the carbonate buffer system. Biological activities such as
photosynthesis or respiration can cause significant diel variations i,i pH.
Extreme pH values or variations in pH can be caused by pollution such as acid
mine drainage.
Importance to Aquatic Life
The importance of pH to aquatic organisms resides primarily in its effect on
other environmental factors. In general, the change in pH itself is not direct-
ly harmful. Rather, the impact on aquatic life accompanies a change in an asso-
ciated variable such as the solubility or toxicity of a toxic pollutant. The
pH range 6.5-9.0 is considered to be generally protective for fish and the
range 5.0-9.0 is not considered directly lethal (EIFAC 1965).
Aquatic organisms have protective membranes and internal regulatory systems
which afford a degree of protection from the direct effects of hydrogen and
hydroxyl ions. The indirect effects of pH seem to intensify as the pH deviates
from the optimum (EIFAC 1969).
The degree of dissocation of weak acids is pH-dependent and thus the toxicity
of several common pollutants is affected. Ammonia (NHg), hydrogen sulfide
(HUS), and hydrocyanic acid (HCN) are examples. Under low pH conditions the
NhL molecule ionizes and becomes the NH^ ion (Thurston, et al. 1974). The tox-
icfty of ammonia is attributed to the un-ionized form (NH^), so that increased
pH conditions result in increased levels of the toxic un-ionized fraction.
The lower the pH, the smaller the degree of dissociation of hydrocyanic acid
to hydrogen and cyanide ions. The molecular form (HCN) is the toxic form, and
so the toxicity of cyanide is favored by low pH. The undissociated form of hy-
drogen sulfide (H^S) is the primary source of sulfide toxicity. Therefore,
under low pH conditions, very little HoS is dissociated, and toxicity is in-
creased.
The solubility of toxic metals is a function of pH. Metals in water tend to
form complexes with such anions as sulfate, carbonate or hydroxide. The solu-
bility of these complexes increases with decreasing pH, as illustrated for hy-
droxides in Figure III-2-1, so that low pH conditions may cause the release of
metals from sediment deposits into the water column. Metal toxicity is be-
lieved to be related to the total metal concentration (i.e., free ions plus
complexed ions) in solution (Calavari et al. 1980). Table III-2-1 illustrates
the effect of pH on metal concentrations in natural waters.
Due to the complexity of its interactions with elements of the environment,
there may be several mechanisms by which pH affects toxicity. The exact mecha-
111-2-2
-------
O)
o
10
12 14
pH
Figure III-2-1. Relationship Between pH and Solubility of Metallic Hydroxides
III-2-3
-------
TABLE III-2-1.
CONCENTRATION (ug/1) OF METALS
ACIDITIES (From Haines, 1981).
IN LAKE WATERS OF VARIOUS
Local it v
102 lakes, Ontario (average)
Blue Chiii li I -ike. Ontario
L'lkc I'anadie, .Sndhiiry, Oniario
North Sweden (range)
Central Norwav (range)
North Norway (range)
South-central Ontario, 14 lakes
(average)
Nelson Lake, Ontario
Metal
Al
13
Cu
2
8
6
Cd
Nonacidified
<0.1
Mn Ni
(pH 6.9-7.8)
3 <3
40 3
28
<5() 0.05-0.23 <100
<20-65
13
1-10
5.7
13
0-0.5
Intermediate
(pH 5.5-6.0)
49 3.6
18 10
Pb Zn
<1 <1
9
6
10-30
0-5 1-17
12.6
16
Acidified (pH 4.1 -5. 3)
Four lakes, Ontario (average)
Clearwater Lake. Sudhurv, Oniario
Four lakes. Suclburv, Oniario (average)
West coast Sweden (range)
Southeast Norway (range)
Lake Langtjern. Norway (average)
South Norway (range)
Adirondack lakes. New York (average)
South Norway (range)
Laxinrsen, west Sweden
453
200-600
218
50-600
286
40-f>00
288
3
97
450
0.4
239 10
300 215
338 820
0.08-0.63 300-400
1-10
6
1
0-0.6
0.21
0.2
45
190
2 30
46
83
1-5 30-122
1-10 3-35
2 15
23
3 28
III-2-4
-------
nism of direct toxicity of pH in water is not certain. It has been suggested
that at very low pH values, oxygen uptake may be affected and this may be the
toxic event. Acid-base regulation and ionoregulation appear to be affected at
higher, but still acidic, pH values (Graham and Wood 1981). There is evidence
that the chronic effects of pH on fish include effects on reproduction, such
as reduced egg production and hatchability (Peterson, et al. 1980), and on be-
havior (Mount 1973). Some mobile organisms may have the ability to avoid low
pH conditions if the detrimental conditions are localized. Evidence suggests
(U.S. EPA 1960, p. 180) that outside a range of 6.5 to 9.0, fish suffer ad-
verse physiological effects which increase in severity as the degree of devi-
ation increases. Tables III-2-2 and III-2-3 present pH values that have been
found to cause adverse effects on a number of fish species in the field and in
laboratory investigations, respectively. These values represent only the low
end of the tolerated range of pH. (The lower limit is most often exceeded due
to anthropogenic causes such as acid rainfall, acid mine drainage and
industrial discharges.)
Marine organisms, as a group, tend to be much less tolerant of extreme pH con-
ditions. As mentioned previously, the marine environment is buffered more ef-
fectively than freshwater. As a result, these organisms have not evolved an
ability to cope with pH variations outside their narrow optimum range.
ALKALINITY
Alkalinity is the property of water which resists or buffers against changes
in pH upon addition of acid or base. The primary buffer in freshwater is the
carbonate-bicarbonate system. Phosphates, borates, and organic acids also im-
part buffer capacity to water. These additional buffer systems are more signi-
ficant in saltwater than in freshwater.
Bicarbonate (HC03~) is the major form of alkalinity. Carbon dioxide (C02) dis-
solved in water is carbonic acid (H?C03) ..Carbonic acid dissociates in two
steps to form bicarbonate and carbonate (CU3~) ions as follows:
CO- + H90 =£= H9C07 ^ H+ + HCOo"
c. £ £ O O
HCO-," ^ H+ + CO"
•j 0
The ability of these chemical reactions to shift back and forth with changes
in hydrogen ion concentration (pH) to "absorb" these changes is what imparts
buffer capacity. This system tends to control pH best in the neutral range.
The form of alkalinity in solution is governed by pH. Figure III-2-2 illus-
trates this effect. Biological activities such as photosynthesis and respir-
ation cause shifts in pH and in the relative concentrations of the forms of
alkalinity, without significant effect on the total alkalinity. The production
of COo during respiration shifts the equilibrium to the right, toward carbon-
ate formation. The removal of C0? from solution during algal photosynthesis
shifts the alkalinity equilibrium to the left, toward the bicarbonate form.
III-2-5
-------
TABLE III-2-2.
SPECIES OF FISH THAT CEASED REPRODUCING, DECLINED, OR DISAP-
PEARED FROM NATURAL POPULATIONS AS A RESULT OF ACIDIFICATION
FROM ACID PRECIPITATION, AND THE APPARENT pH AT WHICH THIS
OCCURRED (From Haines, 1981).
Familv and species
Apparent pH at which population ceased
reproduction, declined, or disappeared
Salmnnidac
1 jke (rout Salvrlinus namaycush
Brook trout Salrrlinus fontinalis
Aurora trout Salvelinusfontinalu timngnmienxu
Arctic char Sahelinia alpiinu
Rainbow trout Salmo gairrineri
Brown trout Salmo trutta
Atlantic salmon Salmo salar
Lake herring Core/rnnus arteriii
Lake whitefish Coregonus clufieaformis
Esocidae
Northern pike Esox Lucius
Cyprinidae
Golden shiner Notcmigon-us cnsoleucas
Common shiner Nttropa cornutus
Lake chub Couesius plumbrus
Bluntnose minnow Pimephales notaius
Roach Rutilus rutilus
Qitostomidae
White sucker Catoatomus commmoni
Ictaluridae
Brown bullhead Ictalurus neintlosus
Percopsidae
Trout-perch Percopsis omiscoma\cus
Gadidae
Burbot Lota lota
Centrarchidae
Smallmouth bass MicroptrriLS dolomirui
1-arKcmouih bass Microptrnu
Rock b;i«is .imbloptitn ruprtfru
Pumpkimeed Lcpoinu gihbosus
Blue^ill Lepomis macrochina
Percidae
Johnnv daner Ethrostoma nigrum
Iowa darter Ethrostoma exile
Walleve Stizoslrtlion v. vitreum
S'cllow perch Prrea ft5.5 ; -5.8 ; 4.4-5.0
4.4-5.2
4.7-5.2 ; 4.2-5.0
4.7-5.2 ; <4.2
<4.2
5.0-5.9
4.8-5.9
5.5-6.0 ; 5.2-5.H
4.5-4.8 ; <4.7 ; 4.2-4.4
5.0-5.5
III-2-6
-------
TABLE III-2-3. VALUES OF pH FOUND IN LABORATORY EXPERIMENTS TO CAUSE VARIOUS
ADVERSE EFFECTS ON FISH SPECIES (From Haines, 1981).
Increased mortality
Family and
species
Salmonidae
Brook trout
Arctic char
Rainbow trout
Brown trout
Atlantic salmon
Esocidae
Northern pike
Cvprinidae
Roach
Fathead minnow
Catostomidae
While sucker
Percidae
turopean percli
Emhrvo
6.5
5.6
4.5
5.5
4.0
4.1
3.4-4.4
3.6
3.9
4.0
4.0-5.5
4.1
5.0
5.6
5.9
4.5
5.6
5.5
Juveniles Reduced
Frv or adults gnmih Oilier effects
4.4 4.5 6.5 Reduced i-tfj,' viability: 5.0
4.5 4.1 4.6 Tissue damage: .r>.2
6. 1 3.5
4.8
4.3 3.6-4.1 1.8
5.0
4.0 [issue damage: 5.0
4.3
4.3
5.0
5.9 2.1 4.5 Reduced egg viability: 0.6
5.3 4.5 Ceased lecding: 4.5
4.0 Bone deformity: 4.2 : 5.0
III-2-7
-------
100
C\J
O
O
"co
•)-•
o
c
03
O
u.
0)
Q_
50
Free
CO
HCO
8
pH
10
11
FIGURE III-2-2. The relationship between pH and the forms of CO^ in water.
Importance to Aquatic Life
The forms of alkalinity are biologically
source of the essential elements carbon,
is not available, algae are capable of
source. Free CCU in solution regulates a
as seed germination, plant growth
transport in the blood.
significant because they serve as a
oxygen, and hydrogen. When free CCL
using bicarbonate as their carbon
variety of biological processes such
(photosynthesis), respiration, and oxygen
Alkalinity is critical to the maintenance df healthy conditions in aquatic sys-
tems, particularly where they are stressed by pollution. Alkalinity helps to
maintain pH in the optimum range for biological activities. The impact of acid-
ic wastes such as coal ash or basic wastes such as metal plating discharges
can be moderated to a degree by the natural buffering capacity of the receiv-
ing water. The indirect effects of alkalinity on toxicity are also important.
In particular, alkalinity reacts with the toxic soluble metal fraction in
III-2-8
-------
water to form insoluble carbonate and hydroxide precipitates. Figure III-2-3
illustrates that the concentration of heavy metals drops rapidly as the concen-
tration of carbonate increases. Metals which are precipitated from the water
column are effectively removed from the aquatic environment and no longer rep-
resent an immediate source of toxicity to aquatic life.
2 -
4 -
O)
O
6 -
Figure III-2-3.
HARDNESS
Relationships of metallic carbonate solubility and carbonate
concentrations
Water hardness generally refers to the capacity of the water to precipitate
soap from solution. The constituents which impart hardness to water are poly-
valent cations, chiefly calcium (Ca) and magnesium (Mg). These form insoluble
complexes with a variety of anions, notably the salts of organic acids
(soaps). By convention, hardness is reported on the basis of equivalence as
mg/1 calcium carbonate (CaCOo).
Hardness cations are primarily associated with carbonate or sulfate anions.
Calcium and magnesium carbonate are referred to as carbonate hardness. When
the anion is other than carbonate, such as sulfate or nitrate, this is refer-
red to as noncarbonate hardness. Because alkalinity and hardness are both ex-
III-2-9
-------
pressed as mg/1 CaC03, it can be concluded that carbonate alkalinity will be
responsible for forming carbonate hardness and that hardness in excess of the
alkalinity is noncarbonate.
Importance to Aquatic Life
Hardness, the capacity of water to precipitate soap, is an aesthetic consider-
ation important to potable water supply. The importance of hardness to aquatic
life is related to the ions which impart hardness to water. There is some evi-
dence to suggest that hard water environments are more favorable for aquatic
life because they support more diverse and abundant biological communities
(Reid 1961).
There is a large body of evidence that hardness mediates the toxicity of heavy
metals to aquatic organisms. Mathematical correlations between the toxicity of
several heavy metals (Cr , Pb, Ag, Ni, In, Cd, and Cu) have been developed.
Table III-2-4 presents the equations (taken from the Water Quality Criteria
Documents) which enable the calculation of allowable metal concentrations as a
function of hardness. Although increased hardness can be correlated directly
with decreased toxicity, the mechanism of this effect is not certain. Two dif-
ferent mechanisms have been proposed, one chemical and one biological. Cala-
mari, et al. (1980) have reviewed the literature concerning these mechanisms,
and discussed both with regard to their own experimental data.
Hardness may operate through two chemical mechanisms to reduce heavy metal tox-
icity. Complexation of the toxic metal with carbonate might be the mechanism
if the free metal ion is the toxic species. Data may be found in the litera-
ture to support (Stiff 1971, Pagenkopf et al. 1974, Calamari and Marchetti
1975, Andrew et al. 1977), or contradict (Shaw and Brown 1974, Calamari et al.
1980) this suggestion. It is also possible that it is the calcium or magnesium
ion alone, rather than the associated carbonate, that is protective. Carroll
et al. (1979) present data which show that the calcium ion, much more than mag-
nesium, seems to reduce cadmium toxicity to brook trout.
Further, the question remains whether the hardness ions are antagonistic to
the action of the toxic metals and they may function biologically through
competitive inhibition of metal uptake or binding of sites of action. Kinkade
and Erdman (1975) published data to support the uptake inhibition mechanism.
Lloyd (1965) suggests that calcium has a protective effect on fish gill
tissue, an organ which is significantly involved in heavy metal uptake.
Calcium has been shown to decrease gill permeability to water, which would
influence metal uptake (Maetz and Bornancin 1975).
III-2-10
-------
TABLE III-2-4. DEPENDENCE OF HEAVY METAL TOXICITY ON WATER HARDNESS*
M eta 1 Calculation of Maximum Allowable Concentration
Cadmium (Cd) e(1.05[ln (hardness)]-3.73)
Chromium (Cr+3) ed.08[ln (hardness)>3.48)
Copper (Cu) e(0.94[ln (hardness)]-!.23)
Lead (Pb) e(L22[ln (hardness)]-0.47)
N1ckel (N1) e(0.76[ln (hardness)]+4.02)
Silver (Ag) e(1.72[ln (hardness)]-6.52)
Z1nc (Zn) e(0.83[ln (hardness)]-H.95)
EPA Ambient Water Quality Criteria Documents (1980).
There is evidence that calcium may be protective against the toxic action of
pollutants other than metals. Hillaby and Randal (1979) found that increased
calcium concentration decreased the acute toxicity of ammonia to rainbow
trout. Calcium concentration has also been associated with increased survival
of fish in acidic conditions (Haranath et al. 1978).
SALINITY
Salinity is a measure of the weight of dissolved salts per unit volume of
water. The chloride content of water, the chlorinity, is strongly correlated
with salinity. In freshwater, the total concentration of ionic components
constitutes salinity. The major anions are commonly carbonate, chloride, sul-
fate, and nitrate. The predominant associated cations are sodium, calcium,
potassium, and magnesium.
The source of these materials is the substrate upon which the water lies and
the earth through and over which water flows. The salinity of a given body of
water is a function of the quantity and quality of inflow, rainfall, and evap-
oration.
Importance to Aquatic Life
Salinity has an impact on a variety of parameters related to biological func-
III-2-11
-------
tions. It controls the ability of organisms to live in or pass through various
waters. It also has an effect on the presence of various food or habitat-
forming plants.
Salinity is important not only in an absolute sense, but the degree of vari-
ation in the salinity of a given water is biologically important. The invasion
of species to or from fresh or saltwater depends on their ability to tolerate
changes in salinity. Rapid changes in salinity cause disruption of osmoregula-
tion in aquatic organisms and can cause plasmolysis in plants. Organisms that
can tolerate a range of salinity can frequently use salinity gradients to
evade less tolerant predators.
Salinity is important to the heat capacity of aquatic systems. As salinity in-
creases, the specific heat of water decreases. This means that there is less
heat required to warm the water. Temperature is a significant factor in biolog-
ical activity and governs many physical processes in water as well.
Salinity also governs the dissolved oxygen concentration in water. For a given
temperature, the solubility of oxygen decreases with increasing salinity.
Table III-2-6 illustrates this effect. The dissolved oxygen concentration is
among the most critical of all water quality parameters to aquatic life.
The ions which make up the total salinity of water have individual effects as
well. The effects of calcium, magnesium, and carbonate have been discussed pre-
viously with respect to their effect on the toxicity of pollutants. Several of
the ions (e.g., nitrate, and potassium) are plant nutrients.
Aquatic organisms have evolved a variety of physiological adaptations to the
salinity of their environments. These adaptations are largely related to their
osmoregulatory systems whose primary function is to solve the problem of the
difference between the salt concentration of the internal fluids of the organ-
ism and the salt concentration of the surrounding water. Freshwater organisms
must maintain an internal salt concentration against the tendency to gain
water from and lose salts to the environment. Osmoregulation in freshwater
fish results in the production of high volumes of liquid waste with a low salt
concentration. In contrast, marine organisms must maintain an internal salt
concentration that is lower than that of the environment, against a tendency
to lose water and gain salts. Osmoregulation in salt water fish results in the
production of small volumes of liquid waste carrying a relatively high salt
concentration.
The gills and kidneys of both types of fish are specially developed to accom-
plish these actions against the natural environmental gradient. Therefore, the
nature of these systems governs the ability of organisms to survive in regions
of varying salinity or to successfully migrate through them.
III-2-12
-------
TABLE III-2-5.
SOLUBILITY OF DISSOLVED OXYGEN IN WATER IN EQUILIBRIUM WITH
DRY AIR AT 760 mm Hg AND CONTAINING 20.9 PERCENT OXYGEN.
Tempera-
ture. °C
0
1
•>
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
0
14.6
14.2
13.8
13.5
13.1
12.8
12.5
12.2
11.9
11.6
11.3
11.1
10.8
10.6
10.4
10.2
10.0
9.7
9.5
9.4
9.2
9.0
8.8
8.7
8.5
8.4
8.2
8.1
7.9
7.8
7.6
Chloride
5000
13.8
13.4
13.1
12.7
12.4
12.1
11.8
11.5
11.2
11.0
10.7
10.5
10.3
10.1
9.9
9.7
9.5
9.3
9.1
8.9
8.7
8.6
8.4
8.3
8.1
8.0
7.8
7.7
7.5
7.4
7.3
concentration.
10.000
13.0
12.6
12.3
12.0
11.7
11.4
11.1
10.9
10.6
10.4
10.1
9.9
9.7
9.5
9.3
9.1
9.0
8.8
8.6
8.5
8.3
8.1
8.0
7.9
7.7
7.6
7.4
7.3
7.1
7.0
6.9
mg/1
15.000
12.1
11.8
11.5
11.2
11.0
10.7
10.5
10.2
10.0
9.8
9.6
9.4
9.2
9.0
8.8
8.6
8.5
8.3
8.2
8.0
7.9
7.7
7.6
7.4
7.3
7.2
7.0
6.9
6.8
6.6
6.5
20.000
11.3
11.0
10.8
10.5
10.3
10.0
9.8
9.6
9.4
9.2
9.0
8.8
8.6
8.5
8.3
8.1
8.0
7.8
7.7
7.6
7.4
7.3
7.1
7.0
6.9
6.7
6.6
6.5
6.4
6.3
6.1
III-2-13
-------
SECTION IV: BIOLOGICAL EVALUATIONS
-------
CHAPTER IV-1
HABITAT SUITABILITY INDICES
Habitat Suitability Index (HSI) models developed by the U.S. Fish and
Wildlife Service are used to evaluate habitat quality for a fish species.
HSI models can be used independently or in conjunction with the Habitat
Evaluation Procedures (HEP) applications described in Chapter II-l.
The HSI models provide a basic understanding of species habitat
requirements, and have utility and applicability to use attainability
analyses. There are several types of HSI models including pattern
recognition, word models, statistical, linear regression, and mechanistic
forms in the FWS model publication series. Use of models is predicated on
two assumptions: (1) an HSI value has a positive relationship to potential
animal numbers: and (?) there is a positive relationship between habitat
quality and some measure of carrying capacity. The mechanistic model
(Figure 1) sometimes referred to as a structural model is one type that
would be useful for use attainability assessments. Information from
literature reviews, expert opinion, and study results is integrated in
these models to define relationships between variables and habitat
suitability. Suitability Index (SI) graphs are developed for each model
variable (Figure 2}. The variables included in a model represent key
habitat features known to affect the growth, survival, abundance, standing
crop, and distribution for specific species. The model provides a verbal
or mathematical comparison of the habitat being evaluated to the optimum
habitat for a particular evaluation species. For some mechanistic models
(Figure 3) a mathematical aggregation procedure is used to integrate
relationships of model components. In others (Figure 4) an HSI value is
defined as the lowest SI value for any variable in the model.
Nonmechanistic models (e.g., statistical models for standing crop and
harvest) do not require use of SI graphs. Output from an HSI model,
regardless of the type, is used to determine the quantity of habitat for a
specific species at a site, and an HSI value ranges from 0 to 1, with 1
representing optimum conditions. The relationship:
Habitat area x Habitat quality (HSI) = Habitat Units (HU's)
provides the basis for obtaining habitat data to compare before and after
conditions for a site if pollution problems or other environmental
problems are solved.
As with all models, some potential sources of subjectivity exist in HSI
models. Potential subjectivity in mechanistic models may occur when: (1)
determining which variables should be included in the model; (?.}
developing suitability index graphs from contradictory or incomplete data;
(3) incorporating information for similar species of different life stages
in the suitability index graphs; (4) determining whether or not highly
correlated variable really affect habitat suitability independently and
which variables, if any, should be eliminated from the model; (5)
determining when, where and how model variables should be measured; and
(6) converting assumed relationships between variables into mathematical
equations that aggregate suitability indices for individual variables into
a species HSI (Terrell et al. , 1982). All models developed and published
IV-1-1
-------
by the U.S. Fish and Wildlife Service are subjected to reviews by species
experts to eliminate as much subjectivity as possible.
Appendix A-l of this manual is a reprint of the HSI developed for the
channel catfish. Readers are encouraged to read the appendix to gain
greater understanding of features of the model. HSI models for 19 aquatic
and estuarine fish species were published in FY 82, and an additional 20
are under development and planned for publication in FY 83. Models have
been published for striped bass, channel catfish, creek chub, cutthroat
trout, black crappie, white crappie, blue gill, slough darter, common
carp, smallmouth buffalo, black bullhead, green sunfish, largemouth bass,
northern pike, juvenile spot, juvenile Atlantic croaker, gulf menhaden,
brook trout, and the southern kingfish. Models for coastal species were
developed at the National Coastal Ecosystems Team (MCET) and those for
inland species were developed at the Western Energy and Land Use Team
(WELIIT).
For more information concerning models for inland species, contact: Team
Leader, Western Energy and Land Use Team, 2627 Redwing Road, Fort Collins,
Colorado 80526 (FTS 323-5100, or comm. 303-226-9100). Individuals
interested in models for coastal species should contact Team Leader,
National Coastal Ecosystems Team, 1010 Gause Boulevard, SIidell, Louisiana
70458 ( FTS 685-6511, or comm. 504-255-6511).
IV-1-2
-------
Habitat Variables
Life Requisites
% cover (V2)
Substrate type (VJ
Food (CF),
% pools (V-,)
% cover (V2)
Average current velocity
Cover (Cc),
Temperature (adult) (V5)
Temperature (fry) (V12
Temperature (juvenile)
Dissolved oxygen (Vg)
Turbidity (V?)
Salinity (adult) (Vg)
Salinity (fry, juvenile) (V13)
Length of agricultural
growing season (Vg)
Water Quality (CWQ)
% pools (V.,)
% cover (V2)
Dissolved oxygen
Temperature (embryo) (V-.Q)
Salinity (embryo) (V
Reproduction (CD)'
Figure 1. Tree diagram illustrating the relationship of habitat variables
and life requisites in the riverine model- for the channel catfish HSI
model. The dashed line for the length of agricultural growing season
(V) is for optional use in the model (McMahon and Terrell 1982).
IV-l-3
-------
u^c^-'^v Grash
Variable
(Vi)
Percent pools during
average summer flow.
3
to
1.0
-5 o.s.
;' 0.6.
0.2-1
0.0
25
50
75 100
(V9)
Percent cover (logs,
boulders, cavities,
brush, debris, or
standing timber) during
summer within pools,
backwater areas, and
littoral areas.
0.0
10 20 .30 40 50
Figure 2. Suitability Index graphs for variables V, and V? in the
channel catfish riverine model. A SI value can range from 0 to 1 with 1
representing an optimum condition (McMahon and Terrell 1982).
IV-1-4
-------
Food (CF)
CF ' V2 * V4
Cover (Cr)
______ V *
Cc = (V, x V2 x V18)1/3
Water Quality (CWQ)>
2(V5*V12*V14)+V7x2(V8)*V9+V13
LWQ " _ 3
^ ^5' V12' V14' V8' V9' or V13 1>s - °'4> then CWO eclua^s tne
of the following: V5, V^2» V14, VQ, Vg, V13, or the above equation.
Note: If temperature data are unavailable, 2(Vg) (length of
agricultural growing season) may be substituted for the term
+ V12 + V14>
3 in the above equation
Reproduction (CR)
CR= (V] xV22xV82x V^^V^)178
If Vg, V-JQ, or V-j-j is'£ 0.4, then CR equals the lowest of the
following: Vg, V-JQ, V-j-|, or the above equation.
HSI determination.
2x1/6
HSI = (CF x Cc x C^ x CR )l/0, or
If CWQ or CR is £ 0.4, then the HSI
following: CWQ, CR> or the above equation.
If Cwo or CR is £ 0.4, then the HSI equals the lowest of the
Figure 3. Formulas for the channel catfish riverine HSI model (McMahon
and Terrell 1982).
rv-i-5
-------
Habitat Variables
Suitability Indices
Ratio of spawning habitat
to summer habitat [area that
is less than 1 m deep and
vegetated (spring) divided
by total midsummer area] (V-|)
Drop in water level during embryo
and fry stages (V2)
Percent of midsummer area with
emergent and/or submerged
aquatic vegetation or remains
of terrestrial plants (bottom
debris excluded) (V)
Log-,Q IDS during midsummer (V,)
Least suitable pH in spawning
habitat during embryo and
fry stages (V^) —
Average length of frost-free
season (V,,)——-
Maximal weekly average
temperature (1 to 2 m
deep) (V7)
Area of backwaters, pools, or
other standing/sluggish
(less than 5 cm/sec) water
during summer, as a percent
of total area (Vft)
Stream gradient.(Vg)
Figure 4. A tree diagram for the northern pike riverine HSI model. Note
that habitat variables are not aggregated for separate life requisite
components (Inskip 1982).
iv-i-6
-------
CHAPTER IV-2
DIVERSITY INDICES AND MEASURES OF COMMUNITY STRUCTURE
Diversity is an attribute of biological community structure. The
concepts of richness and composition are commonly associated with
diversity. Species richness is simply the number of species, while
composition refers to the relative distribution of individuals among
the species, or evenness. Odum (1959) defined diversity indices as
mathematical expressions which describe the ratio between species and
individuals in a hiotic community. A major advantage of diversity
indices is that they permit the summarization of large amounts of data
about the numbers and kinds of organisms into a single numerical
description of community structure which is comprehensible and useful
to people not immediately familiar with the specific biota. Some
diversity indices are expressions of the number of taxa, usually
species, in the community. Whittaker (1964) referred to these formulas
as indices of "species diversity", i.e. the more species - the greater
the diversity. "Dominance diversity indices" (Whittaker, 1964)
incorporate the concepts of both richness and evenness; thus, diversity
increases as the number of species increases or as the individuals
become more evenly distributed between the species.
The response of bottom fauna to four types of pollution is represented
in Figure IV-2-1 (Keup 1966). Figure IV-2-1A shows that organic
pollutants generally decrease the number of species present while
increasing the numbers of surviving taxa, whereas toxic pollutants tend
to reduce both numbers and kinds of organisms (Figure IV-2-1B). In
general, the effect of all types of pollutant stress on community
structure is the loss of diversity. The value of diversity in natural
communities lies in the fact that the presence of many species insures
the likelihood of "redundancy of function" (Cairns et al. 1973). As
explained by Cairns and Dickson (1971), in a highly diverse community,
the constantly changing environment will probably affect only a small
portion of the complex bottom fauna community at any time. Because
there are many different kinds of organisms present, the role of those
eliminated as a result of natural environmental change will be filled
by other organisms. Thus the food cycle and the system as a whole
remain stable. On the other hand, natural environmental variation
might eliminate a significant portion of a community that has been
simplified by pollutant stress. With no organism available to fill the
vacated niche, the functional capacity of the unstable community may be
jeopardized. Generally, maintenance of diversity is important because
it enhances the stability of a system.
Diversity indices are commonly computed as one tool among many in the
analysis of aquatic (as well as terrestrial) communities. Some
prevalent reasons for measuring community diversity are listed below
(these purposes are by no means independent of each other):
To investigate community structure or functions
To establish its relationship to other community properties
such as productivity and stability
To establish its relationship to environmental conditions
IV-2-1
-------
DIRECTION OF FLOW
LU
CD
X "V
/ -V,
/ \
/
t /
Ol
l/l
-------
0 To compare communities
0 To evaluate the biotic health of the community
0 To assess the effects of pollutant discharges
0 To monitor water quality by biological rather than
physicochemical means
In analyses of freshwater aquatic communities, diversity studies generally
involve benthic macroinvertebrates or fish. Several advantages and
disadvantages have been given for the study of these groups (Cairns and
Dickson 1971, Karr 1981), and are listed in Table IV-2-1. These two groups
are generally considered to be the most suitable organisms for evaluation
of community integrity. Whereas it might be desirable to investigate the
diversity of both fish and macroinvertebrates, the two groups generally are
not used in combination to calculate a single diversity index because of
differences in sampling selectivity and error.
DIVERSITY INDICES
Many indices of diversity have been developed. Some indices selected from
the literature are presented in Table IV-2-2, and the more common ones are
discussed below.
Species Diversity Indices
Of the expressions described as species diversity indices (equations 1
through 4 in Table IV-2-2, plus others), the Margalef formula is probably
the most popular. Once the sampling and identification is completed, it is
an easy matter to calculate the diversity index using the Margalef formula
by substituting the number of species(s) and the total number of
individuals (n) into the equation below.
d = s-1
TfT"n
The use of this formula, and others of the type, has some important
limitations. First, it is not independent of sample size. Menhinick
(1964) found that for sample sizes from 64 to 300 individuals the Margalef
diversity index varied from 3.05 to 14.74, respectively. In that study,
four species diversity indices were evaluated for variation with sample
size and all were found unsatisfactory except for the equation referred to
as the Menhinick formula in Table IV-2-2. The second limitation of species
diversity indices is that, by definition, they do not consider the relative
abundance among species, and, therefore, rare species exert a high
contribution to the index value. To illustrate this limitation, Wilhm
(1972) calculated diversity by the Margalef and Menhinick formulas for
three hypothetical communities each containing five species and 100
individuals (see Table IV-2-3). Communities A, B, and C exhibit a wide
range of relative distribution of individuals between the five species.
Intuitively, community A is more diverse than community C, but the two
species diversity indices fail to express any difference.
IV-2-3
-------
TABLE IV-2-1. ADVANTAGES AND DISADVANTAGES OF USING MACROINVERTEBRATES AND
FISH IN EVALUATION OF THE BIOTIC INTEGRITY OF
AQUATIC COMMUNITIES (CAIRNS AND DICKSON, 1971
FRESHWATER
KARR , 1981')
MACROINVERTEBRATES
Advantages
Fish that are highly valued by humans
are dependent on bottom fauna as a
food source.
Many species are extremely sensitive
to pollution and respond quickly to
it.
Bottom fauna usually have a complex
life cycle of a year or more, and if
at any time during their life cycle
environmental conditions are out_ide
their tolerance limits, they die.
Many have an attached or sessile mode
of life and are not subject to rapid
migrations, therefore they serve as
natural monitors of water quality.
Disadvantages
al so
They require specialized
t/ixonornic expertise for
identification, which is
time-consumi ng.
Background life-history
information is lacking for
species and groups.
Results are difficult to
translate into values meaningfu'
to the general public.
many
FISH
Life history information is extensive
for most species.
Fish communities generally include a
range of species that represent a
variety of trophic levels (omnivores,
herbivores, insectivores,
pianktivores, piscivores) and utilize
foods of both aquatic and terrestial
origin. Their position at the top of
the aquatic food web also helps
provide an integrated view of the
watershed environment.
Fish are relatively easy to identify.
Most samples can be sorted and
identified in the field, and then
released.
The general public can relate to
statements about conditions of the
fish community.
Both acute toxicity (missing taxa)
and stress effects (depressed growth
and reproductive success) can be
evaluated. Careful examination of
recruitment and growth dynamics among
years can help pinpoint'periods of
unusual stress.
Sampling fish communities is
selective in nature.
Fish are highly mobile. This
can cause sampling difficulties
and also creates situations of
preference and avoidance. Fish
also undergo movements on diel
and seasonal time scales.
There is a high requirement for
manpower and equipment for field
sampli ng.
IV-2-4
-------
TABLE IV-2-2. SUMMARY OF DIVERSITY INDICES
Descriptive Name
1. Simplest possible ratio of
species per individual
Formula
d = w
Reference
Wilhm, 1967
2. Gleason
d =
log n
Menhinick, 1964,
Gleason, 1922
3. Margalef
d =
s-1
I n n
Margalef, 1951
1956
4. Menhinick
d =
Menhinick, 1964
5. Mclntosh
d =
n-(In.)
n- (n
21/2
Mclntosh, 1967
6. Simpson
d =
In.{nrl)
n (n-1)
Simpson, 1949
7. Brillouin
H = (I) (log n! - l log n.l) Brillouin, 1960
n i = l 1
8. Shannon-Wiener
H = -I (p.log2pi
Shannon and
Weaver, 1963;
Wiener, 1948
Approximate form of the
Shannon Index
Shannon Index using
biomass (weight) units
a -
Wilhm, 1968
IV-2-5
-------
TABLE IV-2-2. (Cont'd)
9. Hierarchical
Diversity Index
(HDD
HDI = H'(F)+H'F+H'GF(S)
Pielou, 1969,
1975
10. Hierarchical Trophic- HTDI = H ' (T. )+H' (T9 )+H' T7(T?). Osborne et al .,.
Based D.I. (HTDI) l T1 2 T1'"^ 6 1Q«n
1980
11. Redundancy (r)
r =
- d
max" min
Patten, 1962;
Wilhm, 1967
12. Equitability (e)
e =
Lloyd and
Ghelardi, 1964
13. Evenness (J,J' , v)
J =
max
Pielou 1969,
1975; Hurlbert,
1971
"dmax 1og s
v =
d - dnnn
a - a .
max min
14. Number of moves (MM)
Rini
Fager, 1972
15. Sequential Comparison Index Oh .
= (UT,j(number of taxa,
Cairns et al .
1968; Cairns &
Dickson, 1971;
Buikema et al.
1980
IV-2-6
-------
TABLE IV-2-2. (Cont'd)
KEY
H = d = H' =3= diversity index.
n = total number of individuals.
n. = number of individuals in species i.
s = total number of species.
ni
p. = probability of selecting an element of state i = —.
R. = rank of species i.
s1 = the species required to produce the calculated d.i. value if
the individuals were distributed among the species accord-
ing to MacArthur's (1957, 1960) "broken-stick" model.
IV-2-7
-------
TABLE IV-2-3. DIVER!
5ITY OF THREE HYPOTHETICAL COMMUNITIES EVALUATED BY THE
MARGALEF, MEMHINICK,
AND SHANNON-WIENER INDICES
Community
A
B
C
nl
20
40
1
n2
20
30
1
n3
20
15
1
n4
20
10
1
n5
20
5
96
n
100
100
100
s
5
5
5
s-1
In n
0.87
0.87
0.87
s
n1/2
0.50
0.50
0.50
d"
2.32
1.67
0.12
Another shortcoming of species per individual formulas is that they are not
dimensionless , thus substitution of alternate variables for numbers - such
as biomass or energy flow - would produce values dependent on the arbitrary
choice of units.
The major advantage of using species diversity indices is the simplicity of
calculation; however, certain conditions for their proper use must be
considered. Since these formulas are dependent on sample size (except
possibly, the Menhinick equation), for intercommunity comparison the sample
sizes should be as nearly identical as possible. It mus.t be kept in mind
that these expressions represent only the number of species and not any
expression of relative abundance. Finally, for use of variables other than
numbers, the units must be specified and kept consistent.
Dominance Diversity Indices
The most prominent dominance diversity index (equations 5 through 8 in
Table IV-2-2, plus others) is the Shannon-Wiener formula. This index is
used extensively in research projects, as is the Simpson equation. The
Shannon-Weiner diversity index evolved from information theory to the
functional equation shown below:
a - -I Cio
in which the ratio of' the number of individuals collected of species i
to the total number of individuals in the sample (n-j/n) estimates the
total population value (N-j/N), which is an approximation of the
probability of collecting an individual of species i (p^ ). It should be
noted^that the units of d using Iog2 is the binary unit, or bit. Natural
logarithms or log-]0 are sometimes substituted into the equation for
convenience, in which case different index values would be obtained, with
the units of nats or decits, respectively. The Shannon-Wiener . di versity
index is calculated using base 10 logarithms, for two simple, hypothetical
samples in Example IV-2-1 (see statistical analysis section). A formula
for conversion between differently-based logarithms is given below:
1og2Y' = 1 .443 In Y = 3.323 loglQY
The logarithm base and units should always be given when reporting data.
IV-2-8
-------
The dominance and species diversity indices discussed can be used to
measure the diversity of virtually any biological community (including
macroinvertebrates and fish), and their application is limited only by
sampling effectiveness. Wilhm and Dorris (1968) evaluated species
diversity of benthic macroinvertebrates using the Shannon-Wiener formula
and obtained values less than 1.0 in areas of heavy pollution, values from
1.0 to 3.0 in areas of moderate pollution, and values exceeding 3.0 in
clean water areas (values given are in decits).
Disadvantages of using the Shannon index (or others of the type) include
the considerable time, expense, and expertise involved in sampling,
sorting, and identification of samples. Calculation of the index value can
be mathematically tedious if done manually, but is greatly simplified if a
computer is available. Computer programs for computing d and r are
provided in the literature (Wilhm, 1970; Cairns and Dickson, 1971).
The Shannon-Wiener formula has a number of features which enhance its
usefulness. This index of diversity is much more independent of sample
size than the species diversity indices (Wilhm 1972). Since it
incorporates the concept of dominance diversity, the relative importance of
each species collected is expressed and the contribution of rare species to
diversity is low. This is illustrated by the d values calculated using the
Shannon equation for the three communities in Table IV-2-3. Also, the
Shannon formula is dimensionless, facilitating the measurement of biomass
diversity. Odum (1959) recognized that the structure of the biomass
pyramid held more ecological (trophic) significance than the numbers
pyramid because it takes many small individuals to equal the mass of one
large individual. The Shannon-Wiener equation can easily be modified to
accomodate any units of weight as shown below:
a - -I £)i.g2£)
Wilhm (1968) pointed out that use of this diversity index with units of
energy flow might be even more valuable to the study of community structure
and function.
Hierarchical Diversity
Diversity indices, such as the Shannon-Wiener index, can be partitioned to
reflect the contribution made by different taxonomic and trophic levels.
Pielou (1975) suggested that a community showing more diversity at higher
taxonomic levels (e.g. genus and family) should be considered to be more
diverse than a community with the same number of species but congeneric or
cofamilial. Osborne et al (1980)questioned the ecological significance of
Pielou's suggestion, but investigated the use of the hierarchical diversity
index (HDI) shown below:
HDI = H'(F) + H'F(G) + H'FG(S)
in which H'C1) is the familial component of the total diversity, H'F(G)
is the generic component of the total diversity, and H FQ(S) is the
IV-2-9
-------
specific component of the total diversity. The equation used by Kaesler et
al . (1978) illustrates the calculation of the hierarchical components.
They used
N,
fi N..
f1
ij N.-k
where a, 6, y, and
-------
TABLE IV-2-4. FUNCTIONALLY-BASED HIERARCHICAL CLASSIFICATION SYSTEMS
A. Hierarchical trophic classification used for HTDI calculations
HT1 HT2 HT3
(Trophic level) (Functional group) (Number of individuals)
Omnivore Filter Feeders Number of individuals of each
Collector-Gatherer- taxon within each functional
Shredder-Engulfer group.
Engulfer-Shredder
Col 1ector-Fi1terer-
Engulfer
Engul fer-Grazer
Engul fer-Col 1ector-
Grazer
Carnivore Engulfer
Piercer
Herbi vore Sera per-Col lector-Gatherer
Col lector-Gatherer-Shredder
Collector-Fi1terer-Gatherer
Col lector-Gatherer
Col 1ector-Fi1terer
Shredder
Detritivore Shredder
Col 1ector-Gatherer
B. Trophic classification of macrobenthic invertebrates. For any specific
application, not all possible combinations are likely to be realized.
Level of
Hierarchy Name Subdivisions
I Functional group shredders (vascular plant tissues)
collectors (detrital materials)
grazers (Aufwuchs)
predators
parasites
II Feeding mechanism chewers and miners
filters (suspension feeders)
gatherers (sediment or deposit feeders)
scrapers
chewers and suckers
swallowers and chewers
pi ercers
attachers
III Dependence obligate
facultati ve
IV Food habit herbivory
detriti vory
carni vory
omni vory
V Species number of individuals
IV-2-11
-------
TABLE IV-2-4 . FUNCTIONALLY-BASED HIERARCHICAL CLASSIFICATION SYSTEMS (Cont'd)
C. HBR (head, body, respiratory organ) classification of macrobenthic
invertebrates according to functional morphology: head position,
body shape, and respiratory organs.
Level of
Hierarchy
Name
Subdivisions
I
II
Head position
category)
(feedi ng
Body shape (current
of stream)
III
Respiratory organs
(substratum)
IV
Species
hypognathous
prognathous
opisthorhynchous
vestigial or other
flattened irregular
flattened oval
flattened elongate
compressed laterally
cyl indrical
elongate
short, compact
fusiform
irregular
hemicylindrical or
simple filamentous
compound filamentous gills
pi ate!ike gills
operculate gills
leaflike gills or organs
respiratory dish
respiratory tube
spiracular gills
caudal chamber
plastron
body integument
tracheal respiration
number of individuals
subtriangular
gills
IV-2-12
-------
in= (1) (log2n! -log2[n-
Then the location of d betwe-en the theoretical extremes can be computed by
the redundancy formula: g g
max"
r =
a - a .
max nnn
Table IV-2-5 illustrates the expression of redundancy.
TABLE IV-2-5.
THE SHANNON-WIENER INDEX AND CORRESPONDING
REDUNDANCY VALUES FOR 11 HYPOTHETICAL
COMMUNITIES, (after Patten, 1962).
Communities
(N = 6)
Species A
Si 1
B
2
1
1
1
C
2
2
1
1
D
3
1
1
1
E
2
2
2
_
F
3
2
1
_
G
4
1
1
_
H
3
3
_
_
I
4
2
_
_
J
5
1
_
_
K
6
_
_
_
s2
si
$5
d(bits)2.58 2.25 1.93 1.79 1.61 1.47 1.25 1.00 0.92 0.65 0.00
R 0.00 0.13 0.25 0.30 0.38 0.43 0.52 0.61 0.64 0.75 1.00
Expressions have also been developed to describe the evenness of
apportionment of individuals among species in a community. Evenness
measures have historically taken two forms. One is the ratio of diversity
to the maximum possible diversity, where dmax is defined as the
community in which all species are -equally distributed:
J1 -
max
= I/log s
as used in the corresponding
s is only an approximation of
Where the logarithm is to the same base
diversity index calculation. However, log
dmax because all species in the community generally will not be
sampled. A measure of evenness that does not depend on s is shown below:
d-d
v = —
mi n
d
- d
It was from this measure
(shown above) was derived
also be thought of as a
individuals among species.
"max mi n
of evenness that the expression for redundancy
by the relationship r = 1-V; thus, redundancy may
measure of the unevenness of apportionment of
Sequential Comparison Index
The sequential comparison index (SCI) is probably the most widely used
index of diversity because of its extensive worldwide use in industrial
(non-academic) studies. The SCI is a simplified, rapid method for
estimating relative differences in biological diversity and has been used
IV-2-13
-------
mainly for assessing the biological consequences of pollution. Use of the
SCI requires no taxonomic expertise on the part of the investigator.
Although it has been used with microorganisms, the SCI is predominately
used to evaluate diversity in benthic macroinvertebrate communities. The
collected specimens are randomly poured into a white enamel pan with
parallel lines drawn on the bottom. Only two specimens are compared at a
time. Comparisons are based on differences in shape, color, and size of
the organisms. If the imminent specimen is apparently the same as the
previous one, it is part of the same "run"; if it is not, it is part of a
new run. An easy way of recording runs is to use a series of X's and O's.
For example, the specimens shown in line one of Figure IV-2-2 would be
recorded, from left to right as X 0_ _X 0_ _X 0_ _X> or seven runs. The
specimens in line two would be tabulated by X X X _0 X X X. Sample two only
contains three runs and is obviously less dfverse. Ultimately, it will be
necessary to know the total number of taxa in the collection. This can
either be counted after determining the number of runs or determined
simultaneously by under! i ning^ the symbol of each new taxon as shown above.
Cairns, et al . (1971) described the following stepwise procedure for
calculating the Sequential Comparison Diversity Index:
1. Gently randomize specimens in a jar by swirling.
2. Pour specimens out on a lined white enamel pan.
3. Disperse clumps of specimens by pouring preservative or water on
cl umps.
4. If the sample has fewer than 250 specimens, determine the number of
runs for entire sample and go to Step 12.
5. If sample has more than 250 specimens, determine the number of runs for
the first 50 specimens.
6. Calculate 01} where DI]_ = numbers of runs/50.
7. Plot 01} against the number of specimens examined as in Figure
IV-2-3.
8. Calculate the SCI for the next 50 specimens.
9. Determine the total number of runs for the 100 specimens examined.
10. Calculate a new 01} for 100 specimens as in Step 6 and plot the value
obtained on the graph made in Step 7, where DIi = number of runs/100.
11. Repeat 'this procedure in increments of 50 until the curve obtained
becomes asymptotic. At this point enough specimens have been examined
so that continued work will produce an insignificant change in the
final 01} value.
12. Calculate final 01} where
01 = number of runs
number of specimens
13. Record the number of different taxa observed in the entire sample. This
can be done after deriving the final 01} or simultaneously by simply
noting each new taxon as it is examined in the determination of runs.
IV-2-14
-------
2.
STOP
SO 100 150 200 250 JOO 350 «0 490 SOO
NUMBER OF SPECIMENS
Figure IV-2-2. Determination of runs in SCI
technique (from Cairns and Dickson, 1971).
Figure IV-2-3. DL and sample
size (from Cairns and Dickson,
1971).
DI.
1.0
0.9
0.8
0.7
0.6
0.5
0.4 |-
0.3
0.2
0.1
0
A = use line A to be 95%
confident the mean DI
,
is within 20/o of true value
B = use 1 ine B to be 95"0
confident the mean DI
,
is within 10» of true value
0 1
5
7
1(J 11 \.L
L6
io
Number of times to repeat SCI
examination on same sample
Figure IV-2-4. Confidence limits for D^ values (from Cairns and Dickson, 1971)
IV-2-15
-------
14. Determine from Figure IV-2-4 the number of times the SCI examination
must be repeated on the same sample to be 95 percent confident that the
mean DI^ is within a chosen percentage of the true value for DIi.
In most pollution work involving gross differences between sampling
areas, Line A of Figure IV-2-4 should be used. For example, suppose
D-II were 0.60. Using Line A of Figure IV-2-4 the SCI should be
performed twice to be 95 percent confident that the mean DIj is
within 20 percent of the true value.
15. After determining N, rerandomize the sample and repeat the SCI
examination on the same number of specimens as determined in Step
11. Repeat this procedure M - 1 times.
16. Calculate DI} by the following equation:
DIj = DI] x (number of taxa)
17. Calculate DIj by the following equation:
Dly = (DI] ) x (number of taxa)
18. Repeat the above procedure for each bottom fauna collection.
19. After determining the DIj for each bottom fauna collection at each
sampling station, there is a simple technique for determining if the
community structures of the bottom fauna as evaluated by the SCI
(Dly) value are significantly different within a station or between
stations. Calculate the 95 percent confidence intervals around each
Dly value. If the 95 percent confidence intervals do not overlap,
then the community structures of the bottom fauna as reflected by the
Dly values are significantly different. For example, suppose the
Dly value for Station 1 were 45 and for Station 2 were 28. In the
determination of Dly a decision was made to use Line A in Figure
IV-2-4, which means that the Dly is within 20 percent of the true
value 95 times out of 100. Therefore the 95 percent confidence
interval for the Dly value at Station 1 would be from 49.5 to 40.5,
or 10 percent of the Dly value on either side of the determined
Dly. Station 2 would have a 95 percent confidence interval for the
Dly value of from 30.8 to 25.2. The bottom fauna communities at the
two stations as evaluatd by the Dly index are significantly
different.
The SCI permits rapid evaluation of the diversity of benthic
macroinvertebrates. Some insight into the integrity of the bottom
community can be gained from Dly values. Cairns and Dickson (1971)
reported that healthy streams with high diversity and a balanced density
seem to have Dly values above 12.0, while polluted communities with
skewed population structures have given values for Dly of 8.0 or less,
and intermediate values have been found in semipol1uted situations.
IV-2-16
-------
SPECIAL INDICES
Several expressions that are not diversity indices per se but which
incorporate the concept of diversity have been formulated? These include
numerous biotic indices (Pantle and Buck, 1955; Beck, 1955; Beak, 1964;
Chutter 1971, Howmiller and Scott 1977, Hilsenhoff 1977, Winget and Mangum
1979), a composite index of "well-being" (Gammon 1976), and Karr's index
(Karr 1981). These indices are designed to evaluate the biotic integrity,
or health, of biological communities and ecosystems.
Biotic Indices
Beck (1955) developed a biotic index
streams using aquatic macroinvertebrates.
for evaluating
In the equation
the health of
Biotic index = 2(n Class I) + (n Class II)
where n represents the number of macroinvertebrate species, more weight is
assigned to Class I organisms (those tolerant of little organic pollution)
than to Class II organisms (those tolerant of moderate organic pollution
but not of anaerobic conditions). A stream nean'ng septic conditions will
have a biotic index value of zero; whereas streams receiving moderate
amounts of organic wastes will have values from 1 to 6, and streams
receiving little or no waste will have values usually over 10 (Gaufin
1973).
The biotic index proposed by Hilsenhoff uses the arthropod community
(specifically insects, amphipods, and isopods) to evaluate the integrity of
aquatic ecosystems via the formula:
BI =
n.a./n
where n-j is the total number of individuals of the ith species (or
genus), a-,- is the tolerance value assigned to that species (or genus),
and n is the total number of individuals in the sample (Hilsenhoff, 1977;
Hilsenhoff, 1982). Pollution tolerance values of zero to five are assigned
to species (or genera when species cannot be identified) on the basis of
previous field studies. A zero value is assigned to species found only in
unaltered streams of very high water quality, a value of 5 is assigned to
species known to occur in severely polluted or disturbed streams, and
intermediate values are assigned to species occurring in intermediate
situations. Calculation of this and other biotic indices are methods of
biologically assessing water quality.
Index of Well-Being
Utilizing fish communities, Gammon developed a composite index of well-
being (IUR) as a tool for measuring the effect of various human
activities on aquatic communities (Gammon, 1976; Gammon and Reidy, 1981;
Gammon et al., 1981). This index was calculated by:
= 0.51nn+0.51nw
no
in which n is the number of individuals captured
weight in kilograms captured per km,
-------
Karr's Index of Biotic Integrity (IBI)
Karr (1981) presented a procedure for classifying water resources by
evaluating their biotic integrity using fish communities. Use of the
system involves three assumptions: (1) the fish sample is a balanced
representation of the fish community at the sample site; (2) the sample
site is representative of the larger geographic area of interest; and (3)
the scientist charged with data analysis, and the final classification is a
trained; competent biologist with considerable familiarity with the local
fish fauna. For each of the twelve criteria listed in Table IV-2-6, the
evaluator subjectively assigns a minus (-), zero (0), or plus (+) value to
the sample. The grades are assigned numerical values - (-)=!, (0)=3, (+)=5
- which are summed over all twelve criteria to produce an index of
community quality. The sampled community is then placed in one of the
biotic integrity classes described in Table IV-2-7 based on numerical
boundaries such as those tentatively suggested by Karr (1981) and shown in
Table IV-2-8.
TABLE IV-2-6. PARAMETERS USED IN ASSESSMENT OF FISH
COMMUNITIES. (SEE ARTICLE TEXT FOR DISCUSSION.)
Species Composition and Richness
Number of Species
Presence of Intolerant Species
Species Richness and Composition of Darters
Species Richness and Composition of Suckers
Species Richness and Composition of Sunfish (except
Green Sunfish)
Proportion of Green Sunfish
Proportion on Hybrid Individuals
Ecological Factors
Number of Individuals in Sample
Proportion of Omnivores (Individuals)
Proportion of Insectivorous Cyprinids
Proportion of Top Carnivores
Proportion with Disease, Tumors, Fin Damage, and
Other Anomalies
BIOLOGICAL POLLUTION SURVEY DESIGN
The first step in planning any survey of water quality is to identify
specific objectives and clearly define what information is sought. For
instance, the objective of a use attainability analysis might be to
evaluate the water quality or degree of degradation of a body of water, in
general, in order to ascertain the accuracy of the current use designation.
Alternately, the analysis objective might be to determine the extent of
damage caused by a discharge or series of discharges. From such
information, the potential attainable use can be identified; judgments must
then be made regarding the benefits/costs of improving the degree of waste
treatment.
IV-2-18
-------
TABLE IV-2-7: BIOTIC INTEGRITY CLASSES USED IN-ASSESSMENT OF FISH COMMUNITIES
ALONG WITH GENERAL DESCRIPTIONS OF THEIR ATTRIBUTES
Class Attributes
Excellent Comparable to the best situations without influence of
man; all regionally expected species for the habitat and
stream size, including the most intolerant forms, are
present with full array of age and sex classes; balanced
trophic structure.
Good Species richness somewhat below expectation especially
due to loss of most intolerant forms; some species with
less than optimal abundances or size distribution;
trophic structure shows some signs of stress.
Fair Signs of additional deterioration include fewer
intolerant forms, more skewed trophic structure (e.g.,
increasing frequency of omnivores); older age classes of
top predators may be rare.
Poor Dominated by omnivores, pollution-tolerant forms, and
habitat generalists; few top carnivores; growth rates
and condition factors commonly depressed; hybrids and
diseased fish often present.
Very Poor Few fish present, mostly introduced or very tolerant
forms; hybrids common; disease, parasites, fin damage,
and other anomalies regular.
No Fish Repetitive sampling fails to turn up any fish.
TABLE IV-2-8: TENTATIVE RANGES FOR THE BIOTIC
INTEGRITY CLASSES.
Class Index Number
Excellent (E) 57-60
E-G 53-56
Good (G) 48-52
G-F 45-47
Fair (F) 39-44
F-P 36-38
Poor (P) 28-35
p-VP 24-27
Very Poor (VP) _< 23
IV-2-19
-------
The next steps in planning the survey are to review all available reports
and records concerning the waste effluents and receiving waters, and to
make a field reconnaissance of the waterway, noting all sources of
pollution, tributaries, and uses made of the water?.
Sampling Stations
There is no set number of sampling stations that will be sufficient to
monitor all types of waste discharges; however, some basic rules for a
sound survey design are listed below (Cairns and Dickson 1971). The
following describes an "upstream-downstream" study. The reader should also
consult Section IV-6 on the reference reach approach to see an alternative
method.
1. Always have a reference station or stations above all possible
discharge points. Because the usual purpose of a survey is to
determine the damage that pollution causes to aquatic life, there must
be some basis for comparison between areas above and below the point or
points of discharge. In practice, it is usually advisable to have at
least two reference stations. One should be well upstream from the
discharge and one directly above the effluent discharge, but out of any
possible influence from the discharge.
2. Have a station directly below each discharge.
3. If the discharge does not completely mix on entering the waterway but
channels on one side, stations must be subdivided into left-bank,
midchannel, and right-bank substations. All data collected
biological, chemical, and physical - should be kept separate by
substations.
4. Have stations at various distances downstream from the last discharge
to determine the linear extent of damage to the river.
5. All sampling stations must be ecologically similar before the bottom
fauna communities found at each station can be compared. For example,
the stations should be similar with respect to bottom substrate (sand,
gravel, rock, or mud), depth, presence of riffles and pools, stream
width, flow velocity, and bank cover.
6. Biological sampling stations should be located close to those sampling
stations selected for chemical and physical analyses to assure the
correlation of findings.
7. Sampling stations for bottom fauna organisms should be located in an
area of the stream that is not influenced by atypical habitats, such as
those created by road bridges.
8. In order to make comparisons among sampling stations, it is essential
that all stations be sampled approximately at the same time. Not more
than 2 weeks should elapse between sampling at the first and last
stations.
IV-2-20
-------
For a long-term biological monitoring program, bottom organisms should be
collected at each station at least once during each of the annual seasons.
More frequent sampling may be necessary if water quality of any discharge
changes or if spills occur. The most critical period for bottom fauna
organisms is usually during periods of high temperature and low flow of the
waterway. Therefore, if time and funds available limit the sampling
frequency, then at least one survey during this time will produce useful
i nformation.
Sampling Equipment
Commonly used devices for sampling benthic macroinvertebrate communities
include the Peterson dredge, the surber square foot sampler, aquatic bottom
nets, and artificial substrate samplers. Proper use of the first three
pieces of equipment requires that the operator exert the same amount of
effort at each station before comparisons can be made. This subjectivity
can cause error, but can be minimized by an experienced operator.
Artificial substrates standardize sampling to some extent by providing the
same type of habitat for colonization when placed in ecologically similar
conditions. A simple type of artificial substrate sampler is a wire basket
containing rocks and debris. Others consist of masonite plates or plastic
webs which can be floated or submerged. Additional advantages of
artificial substrate samplers are quickness and ease of use.
Fish sampling equipment includes electrofishing gear, encircling gear (haul
seine, purse seine), towed nets (otter trawl),
chemical toxicants (rotenone, antimycin). As
sampling effort must be put forth at each
equipment. Also, measures should be taken to
fish sampling.
gill nets, maze gear, and
discussed above, the same
station when using this
reduce the selectivity of
Number of Samples
If comparisons are to be made between stations in a pollution survey-, each
station must be sampled equally. Either an equal number of samples must be
taken at each station or an equal amount of time and effort must be
expended.
Qrgani sms
clusters.
order to obtain
are not randomly distributed in nature, but tend to occur in
Because of this, it is necessary to take replicate samples in
a composite sample that is representative of that station.
There is no "cookbook recipe" which defines the number of samples to take
in a given situation. Cairns and Dickson (1971) have found practical
experience to show that not less than three artificial substrate samplers,
3 to 10 dredge hauls, and at least three Surber square foot samples
represent the minimum number of samples required to describe the bottom
fauna of a particular station. Naturally, increasing the number of
replicate samples increases the reliability of the data. The data of
replicate samples taken at a given station are combined to form a pooled
sample. It has been found that a plot of the pooled diversity index versus
IV-2-21
-------
cumulative sample units becomes asymptotic, and that once this asymptotic
diversity index value is found, little is gained by additional sampling.
Ideally, a base line study would be conducted to determine the optimum
number of samples for a pollution survey.
STATISTICAL ANALYSES
This section describes some of the statistical methods of comparing the
diversity indices calculated for different sampling stations.
Hutcheson's t-test
Hutcheson (1970) proposed a t-test for testing for difference between two
diversity indices:
U LJ
n, - ftp
t =
Hl " H2
Where H]_-H£ is simply the difference between the two diversity indices,
and
- S
2,
1
The variance of H may be approximated by:
log2 f1 - (If. log f.)2/n
wij r-\
H n2'
Where f-; is the frequency of occurrence of species i and n
number of individuals in the sample. The degrees of
associated with the preceding t are approximated by:
is the total
freedom (df)
df = ($„ + S
1
H,
Convenient tables
and t-distribution
of f1
tables
.2 2
'1
.2 2
>u 1
H?J
og2f-j are provided by Lloyd, et al. (1968),
can be found in any statistics textbook (such as
Dixon and Massey, 1969; Zar, 1974; etc.). Example IV-2-1 demonstrates the
calculation of the Shannon-Wiener index (H) for two sets of hypothetical
sampling station data, and then tests for significant difference between
them using Hutcheson1s t-test.
IV-2-22
-------
Example IV-2-1. Comparing Two Indices of Diversity (adapted from Zar
1974). '
HQ: The diversity index of station 1 is the same as the diversity
index of station 2.
H^: The diversity indices of stations 1 and 2 are not the same. The
level of siqnificance (CL) = 0.05
Station 1
Species
1
2
3
4
5
6
number of
individua1s( f)
47 ,
35
7
5
3
3
percentage(
47
35
7
5
3
3
. f., f. log f.
,1)1 i
78.5886
54.0424
5.9157
3.4949
1.4314
1.4314
fj log2 f,.
131.4078
83.4452
4.9994
2.4429
0.6830
0.6830
n . n .
-llog-I
n y n
-0.1541
-0.1596
-0.0808
-0.0651
-0.0457
-0.0457
100
100
144.9044
223.6613 -0.5510
Species
1
2
3
4
5
6
number of
individualsf f)
48
23
11
13
3
2
Station 2
percentagef i)
48
23
11
13
3
2
fj log f.
80.6996
31.3197
11.4553
14.4813
1.4314
0.6021
f , 2
fj log' f.
135.6755
42.6489
11.9294
16.1313
0.6830
0.1813
n. n
TT^TT
-0.1530
-0.1468
-0.1054
-0.1152
-0.0457
-0.0340
100
100
139.9894
207.2494 -0.6001
IV-2-23
-------
H, = 0.5510 H2 = 0.6001
S* = 0.00136884 SM = 0.00112791
Hl H2
SH _H = 0.0499
t = -0.98
df = 198.2 = 200
From a t-distribution table: tQ net2) 200 = ^
Therefore, since the t value is not as great as the critical value for the
95 percent level of significance (d = 0.05), the null hypothesis (H0) is
not rejected.
Analysis of Variance
Analysis of variance (ANOVA) can be used to test the null hypothesis that
all means are equal, e.g. HO:U]_=UO = =11^, where k is the number of
experimental groups. "Single factor or "one-way" ANOVA is used to test
the effect of one factor (sampling site) on the variable in question
(diversity) in Example IV-2-2. Two-way ANOVA can be used for comparison of
spacial and temporal data.
In Example IV-2-2, each datum (X-jj) represents a diversity index that
has been calculated for j replicate samples at each of i stations.
Also, x. represents the mean of station i, n-j represents the number of
replicates in sample i, and N(=Jn.) represents the total number of indices
calculated in the survey.
After computing the mathematical summations, the ANOVA results are
typically summarized in a table as shown. The equality of means is
determined by the F test.
IV-2-24
-------
Cl, groups df, error df = group MS
error MS
The critical value for this test is obtained from an F-di stri buti on table
based on the degrees of freedom of both the numerator and denominator.
Since the computed F is at least as large as the critical value, H0 is
rejected, e.g. the diversity index means at all stations are not equal.
Example IV-2-2. A Single Factor Analysis of Variance (adapted from Zar
1974J.
H0:
A: The mean diversity indices of the five stations are not the same
Q = 0.05
Station !
2 .£2
3.32
3.64
3.46
2.91
3.10
Station
x .
i
n-
L Station
3.96
4.08
3.79
3.71
4.36
4.24
1
3.21
6
2 Station 3
4.10
4.41
4.64
4.02
3.86
3.63
2 3
4.02 4.11
6 6
Station 4
4.63
4.21
4.35
4.88
4.37
4.01
4
4.41
6
Station 5
5.63
5.41
5.94
6.27
6.00
5.73
5
5.83
6
n.
[ x.
19.25
24.14
24.67
26.45
34.98
n.
/n. 61.76
I x. .
= 1J
97.12
/n. = 580.84
I !x
i J
ij = 129.49
r r
total sum of squares = I I x , -C = 24.29
1 J
101.43
116.60 203.93
xij = 583.21
-------
groups sum of squares =
n.
I
/nr
C = 21.92
error sum of squares = total ss - groups ss = 2.37
total degrees of freedom = N - 1 = 29
groups degrees of freedom = k - 1 = 4
error degrees of freedom = total df - groups df = 25
mean squared deviations from the mean (MS) = ss/df
groups MS = 21.92/4 = 5.48
error MS = 2.37/25 = 0.09
Summary of the Analysis of Variance
Source of Variation
SS
df
MS
total
groups
error
F = groups MS
error MS
24.29
21.92
2.37
5.480 = 57. 6(
0.095
29
4
25
3
5.480
0.095
F 0.05(1),4,25 = 2'76
Therefore, Reject HQ : u.,=Uo=u.,=u/, = u
Multiple Range Testing
The single factor analysis of variance tests whether or not all of the mean
diversity indices are the same, but gives no insight into the location of
the differences among stations. To determine between which stations the
equalities or inequalities lie, one must resort to multiple comparison
tests (also known as multiple range tests). The most commonly used methods
are the Student-Newman-Keuls test (Newman 1939, Keuls 1952) and the
Duncan's test (Duncan 1955).
Student-Newman-Keuls Test
Example IV-2-3 demonstrates the Student-Newman-Keuls (SNK) procedure for
the data presented in Example 2. Since the ANOVA in Example IV-2-2
rejected the null hypothesis that all means are equal, the SNK test may be
applied. First, the diversity index means are ranked in increasing order.
Then, pairwise differences ( XB-*A ) are tabulated as shown in Example
IV-2-2 . The value of p is determined by the number of means in the range
of means being tested. Using the p value and the error degrees of freedom
from the ANOVA, "studentized ranges," abbreviated qa>df>/0 are obtained
from a table of q-distribution critical values. The standard error is
calculated by:
SE = (S2/n)1/2 = (error MS/n)1/2
If the k group sizes are not equal,
For each comparison involving unequal
by:
SE =
n
MS/n)'
slight modification is necessary.
the standard error is approximated
1/2
IV-2-26
-------
Examole IV-2-3.
Student-Newman-Keuls Multiple Range Test with Eoua
Si zes. This example utilizes the raw aata and
van ance presented in Example IV-2-2.
Sample
analysis of
Ranks of sample means (i
Ranked sample means (x.)
1
3.21
2
4.02
3
4.11
4.41
5
5.83
SE = (error MS/n)V2 = (0.095-/6)]/2 = 0.126
Compari son
(B vs. /
5 vs.
5 vs.
5 vs.
5 vs.
4 VS.
4 vs.
4 vs.
3 vs.
3 vs.
2 vs.
*
Since
1
2
3
4
1
2
3
1
2
1
Di fference
( ^n -
5.83-3.
5.83-4.
5.83-4.
5.83-4.
4.41-3.
4.41-4.
Do Not
4.11-3.
Do Not
4.02-3.
A '
21 = 2
02 = 1
11 = 1
41 = 1
21 = 1
02 = 0
Test
21=0
Test
21=0
.62
.81
.72
.42
.20
.39
.90
.81
Qn nc oc „ does not ap
SE
0.126
0.125
0.126
0.126
0.126
0.126
0.126
0.126
pear in
q
20.79
14.37
13.65
11.27
9.52
3.10
7.14
6.43
P 3
5
4
3
2
4
3
3
2
the q-distributi
0.
4.
3.
3.
2.
3.
3.
3.
2.
on
05,24,p*
166
901
532
919
901
532
532
919
table, q.
Concl usi
Reject
Reject
Reject
Reject
Reject
Accept
Reject
Reject
i nj; 9/1 n
on
H0;U5=U1
HO: U5=u3
Ho:u5=u4
H0:U4=U1
Ho:u4=u2
HO: u3=U]
H0:u?=u,
is used.
Overall conclusion: u
,
U = u*
The q value is computed by:
q = (XR - xfl)/SE
If the computed q value is greater than or equal to the critical value,
then H
= u/\ is rejected.
In Example 3, after accepting H0:U4=U2 there is no need to test 4 vs.
3 or 3 vs. 2. The conclusions drawn in the example are that the community
at Station 1 has a significantly different mean diversity index from all
other sampled communities; likewise, the Station 5 mean is different from
the others. However, the communities at Stations 2, 3, and 4 have
statistically equal diversity index means. These conclusions can be
visually represented by underlining the means that are not significantly
different with a common line as shown below:
station 12345
mean diversity index 3.21 4.02 4.11 4.41 5.83
Conversely, any two means not underscored by the same line are
significantly different.
Duncan's Multiple Range Test
The theoretical basis of the Duncan's test is somewhat different from the
Student-Newman-Keul test, although the procedures and conclusions are quite
similar. Duncan's test makes use of the concept of Least Significant
IV-2-27
-------
Difference (LSD) which is related to the t-test,
discussed previously. The LSD is calculated by:
(2S2/n)1/2
a form of which was
where
LSDa =
is the mean square for error, n
is the tabulated t value for
is
the
in
replications, and
freedom (MS and df for error are calculated
variance). After determining p as in the SNK procedure,
obtained from a table dependent on the level of significance,
the number of
error degrees of
the analysis of
R values are
error df, and
p. The shortest significant difference (SSD) is computed by the equation:
SSD = R(LSD)
Example IV-2-4 demonstrates Duncan's procedure for hypothetical data. As
before, the difference between means is calculated for every possible
pairwise comparison of means. This difference is then compared to the
corresponding SSD value and conclusions are drawn. If the difference is at
least as large as the SSD, then the null hypothesis - that the two means
are equal - is rejected; if the difference is less than SSD, H0 is
accepted. The results are visually represented as described for the SNK
test.
Example IV-2-4. Duncan's Multiple Range Test.
H0: Ul=u2=u3=u4
HA: The mean diversity indices of the four sampling stations are not
the same
d = 0.05
n = 4
Ranks of sample means (-1)
Ranked sample means (x-j )
error MS = 0.078
1
5.3
2
5.7
LSD
0.05
= t0>Q5 (2s2/n)1/2 = 0.447
3
5.9
error df=9
4
6.3
Compari son
(B vs.
4 vs.
4 vs.
3 vs.
3 vs.
2 vs.
mean di
vi sual
A )
1
3
1
2
1
versi
Difference
(xB -
6.3-5.
6.3-5.
6.3-5.
5.9-5.
5.9-5.
5.7-5.
station
ty index
Xfl )
3=1.0
7=0.6
9=0.4
3=0.6
7=0.2
3=0.4
1
5.3
P
4
3
2
3
2
2
2
5.7
R
a
i
i
i
i
i
i
3
5.9
SSD
,df ,p
.07
.04
.00
.04
.00
.00
4
6.3
=R(LSD)
0.
0.
n.
0.
0.
0.
48
46
45
46
45
45
Conclusion
reject
reject
accept
reject
accept
accept
HO
Hn
HO
HO
HO
Ho
:ua=U]
:u4=u2
:u4=u3
:u3=u1
:u3=u2
:u?=u1
L. \
representation
IV-2-28
-------
COMMUNITY COMPARISON INDICES
Introduction
Whereas the statistical analyses discussed above can discern significant
differences between diversity indices calculated at two or more sampling
stations, community comparison indices have been developed to measure the
degree of similarity or dissimilarity between communities. These indices can
detect spatial or temporal changes in community structure. Polluted
communities presumably will have different species occurrences and abundances
than relatively non-polluted communities, given that all other factors are
equal. Hence, community comparison indices can be used to assess the impact of
pollution on aquatic biological communities.
There are two basic types of community comparison indices: qualitative and
quantitative. Qualitative indices use binary data: in ecological studies, the
two possible attribute states are that a species is present or is not present
in the collection. This type of community similarity index is used when the
sampling data consists of species lists. Kaesler and Cairns (1972) considered
the use of presence-absence data to be the only justifiable (and defensible)
approach when comparing a variety of organism groups (e.g. algae and aquatic
insects). Also, qualitative similarity coefficients are simple to calculate.
When data on species abundance are available, quantitative similarity indices
can be used. Quantitative coefficients incorporate species abundance as well
as occurrence in their formulas, and thus, retain more information than
indices using binary data. An annotated list of community comparison indices
of both types appears in Table IV-2-9.
Qualitative Similarity Indices
Although the terminology used in the literature varies considerably, the
qualitative similarity indices in Table IV-2-9 (1 - 6) are represented using
the symbolism of the 2X2 contingency table shown in Figure IV-2-5. In the form
of the contingency table shown, collections A and B are entities and all of
the species represented in a collection are the attributes of that entity.
Indices 1 through 4 in Table IV-2-9 are constrained between values of 0 and 1,
while equation 6 has a potential range of -1 to 1. The minimum value
represents two collections with no species in common and the maximum value
indicates structurally identical communities.
According to Boesch (1977), the Jaccard, Dice, and Ochiai coefficients are the
most attractive qualitative similarity measures for biological assessment
studies. The Jaccard coefficient (1) is superior for discriminating between
highly similar collections. The Dice (2) and Ochiai (4) indices place more
emphasis on common attributes and are better at discriminating between highly
dissimilar collections (Clifford and Stehpenson, 1975; Boesch, 1977; Herricks
and Cairns, 1982). Thus, the nature of the data determines which index is most
suitable. The Jaccard coefficient has been widely used by some workers in
stream pollution investigations (Cairns and Kaesler, 1969; Cairns et al.,
1970; Cairns and Kaesler, 1971; Kaesler at al., 1971; Kaesler and Cairns,
1972; Johnson and Brinktiurst, 1971; Foerster et al., 1974). Peters (1968) has
written BASIC computer programs for calculating Jaccard, Dice, and Ochiai
indices.
IV-2-29
-------
TABLE IV-2-9. SUMMARY OF COMMUNITY COMPARISON INDICES
Descriptive Name
Formula
Reference
1. Jaccard Coefficient of Community S =
Jaccard, 1912
2. Dice Index (Czekanowski, Sorenson) S =
2a
Czekanowski, 1913
3. Sokal and Michener Simple Matching S = ,k A
Index a+b+c+d
Sokal and Michener, 1958
4. Ochiai Index (Otsuka)
Ochiai, 1957
o 5- Fager Index
6. Point Correlation Coefficient
S =
S -
1
2(a+b)
1/Z
ab-bc
(Kendall Coefficient of Association) ~ [(a+b)(c+d)(a+c)(b+d)]l/2
Boesch, 1977
Boesch, 1977
7. Bray-Curtis Similarity Coefficient
, 2 I mi'n(xTa' Xib)
'ab " t <*ia+ *ib>
Boesch, 1977
Bray-Curtis Dissimilarity
Coefficient
. xia - xib
ab I (x-a + x.b]
Bray and Curtis, 1957
Percentage Similarity of Community S = 1 - 0.5 lip., - p., I = I min (p. , p.. )
3D la ID la ID
Whittaker, 1952
-------
TABLE IV-2-9 (continued)
Pinkham and Pearson Index of
Similarity
, 1 y min (xia' Xib)
ab n max (x. , x.K)
i a ID
Pinkham and Pearson, 1976
9. Morisita Index of Affinity
>ab
Morisita, 1959
• 10.
rv>
I
GO
Horn Index of Overlap
H - H ,
_ max ab
>ab Hmax " Hmin
Horn, 1966
11. Distance
ab
2-,1/2
Boesch, 1977
ab
>
ia- xib)
2-,l/2
Sokal , 1961
12. Product-Moment Correlation
Coefficient (Pearson)
(xia " xa)(xib - xb}
(x
U
(x - x
u x
Sneath and Sokal, 1973
-------
TABLE IV-2-9 (continued)
Key: S = similarity between samples.
D = dissimilarity between samples.
a,b,c,d = (see Figure IY-2-5).
x. , x., = number of individuals of species i at Station A or B.
"13 ID
p. , p.. = relative abundance of species i at Station A or B.
13 1 D
X , X, = total number of individuals at Station A or B.
a' b
n = total number of different taxa.
X t X, = Simpson diversity index for Station A or B.
H = Shannon-Wiener diversity index of Station A and B combined.
ab
H = maximum possible value of H , .
max ao
H . = minimum possible value of H . .
ib log Xia + X1b
_ (Xa * Xb) log (Xa + Xb) - I x1a log x.a - I x-b log x.b
max X + X.
a b
(Xa I
Hmin = aa
X + XT
a b
IV-2-32
-------
COLLECTION A
CQ
Z
O
*—H
I—
C_J
to
o»
.0
-------
The Fager coefficient (5) is simply a modification of the Ochiai index.
Because a correction factor is subtracted from the Ochiai index, the Fager
coefficient may range from slightly less than zero to slightly less than one;
this makes it less desirable. The Fager index has been used a great deal in
marine ecology.
Both the Sokal and Michener index (3) and the Point Correlation Coefficient
(6) include the double-absent term d. A number of authors (Kaesler and Cairns,
1972; Clifford and Stephenson, 1975; Boesch, 1977) have criticized the
approach of considering two collections similar on the basis of species being
absent from both.
Pinkham and Pearson (1976) illustrated the weaknesses of qualitative
comparison indices. The basic shortcoming is that two communities having
completely different species abundances but the same species occurrence will
produce the maximum index value, indicating that the two collections are
identical.
Quantitative Comparison Indices
Quantitative indices (7 - 12) consider species abundance in addition to mere
presence-absence. Incorporating species abundance precludes the over-emphasis
of rare species, which has been a criticism of the Jaccard coefficient
(Whittaker and Fairbanks, 1958). Quantitative measures are not as sensitive to
rare species as qualitative indices and emphasize dominant species to a
greater extent. Distance (11), information (9, 10), and correlation (12)
coefficients weight dominance even more than other quantitative indices.
Quantitative indices also avoid the loss of information involved in
considering only presence-absence data when species abundance data are
available. However, data transformations (e.g., to logarithms, roots, or
percentages) may be desirable or necessary for the use of some quantitive
comparison indices. Calculation of quantitative indices is more complicated
than qualitative coefficients, but can be facilitated by computer application.
The Bray-Curtis index (7) is one of the most widely used quantitive comparison
measures. Forms of this index have been referred to as "index of associaton"
(Whittaker, 1952), as "dominance affinity" (Sanders, 1960), and as "percentage
similarity of community" (Johnson and Brinkhurst, 1971; Pinkham and Pearson,
1976; Brock, 1977). The simplest and probably most commonly used form of the
Bray-Curtis index is the Percent Similarity equation:
S :
ab •• i a~ • i D '
where the attributes have been standardized into a proportion or percent of
the total for that entity (collection). The shortcoming of the Percent
Similarity coefficient was illustrated by Pinkham and Pearson (1976) as shown
below.
IV-2-34
-------
TAX A
A B C D
Station A
Station B
40 20 10 10 10
20 10 5 5 5
In this hypothetical comparison, all species are
A as at Station B but their relative abundance
maximum similarity value of 1.0 is registered.
situation is germane to pollution assessment
difference between two sampling stations is the
eutrophication.
twice as abundant at Station
is identical; therefore, the
The authors felt that this
surveys in which the only
relative degree of cultural
as both a measure of
index can be converted
In Table IV-2-9, the Bray-Curtis index is displayed
similarity and dissimilarity. Any community similarity
to a dissimilarity measure by the simple equality:
D = 1 - S
Of course, values obtained by a dissimilarity expression are inversely related
to similarity values; they increase with decreasing similarity.
Pinkham and Pearson (1976) presented a community similarity index (8) that
would overcome the shortcomings of other indices (e.g. 1,3,7,12) that were
discussed in the article. Their similarity coefficient can be calculated
using either actual or relative (percent) species abundance, although they
suggested using actual abundance whenever possible. The authors also offered
a modified formula that includes a weighting factor for assigning more
significance to dominant species:
min(x.a,x.b)
.
Xa Xb
/
Two community comparison indices that employ diversity indices in their
formulas are the Morisita Index of Affinity (9) and the Horn Index of Overlap
(10). The Morisita comparison measure incorporates the Simpson (1949)
diversity index, and the Horn coefficient uses the Shannon-Wiener (1948)
diversity index. Horn (1966) described the Morisita index as the probability
that two individuals drawn randomly from communities A and B will both belong
to the same species, relative to the probability of randomly drawing two
individuals of the same species from A or B alone. Because the numerator of
the Morisita index is a product rather than a difference ( or minimum value)
it tends to be affected by abundant species to a greater extent than the
Bray-Curtis or Pinkham and Pearson indices. Like those similarity measures,
IV-2-35
-------
the Morisita index ranges from zero for no resemblance to one for identical
collections. The Horn Index of Overlap is a manipulation of Shannon's
information theory equation that closely resembles the expression of community
redundancy developed by Margalef:
R = (H - H)/ (H - H . )
v max " v max mm'
The observed value in Horn's index (Hab) is the Shannon index calculated for
the sum of the two collections being considered. The maximum diversity value
(Hmax) would occur if the two collections contained no species in common, and
the minimum diversity value (Hmin) would be attained if the two collections
contained the same species in the same proportions. It should be noted that
the equations given for Hab, Hmax, and Hmin in the key to Table IV-2-9 are
adapted from those given by Perkins (1983) since those appearing in the
original article (Horn, 1966) are apparently inconsistent with the Shannon
index. The Morisita and the Horn indices have been used in aquatic ecology
studies (Kohn, 1968; Bloom et a!., 1972; Livingston, 1975; Heck, 1976).
If two entities (i.e. communities) are thought of as points in an
n-dimensional space whose dimensions are determined by their attributes (i.e.
species occurrence and abundance ), then the linear distance between the two
points in the hyperspace can be construed as a measure of dissimilarity
between the two entities. The two distance formulas shown in Table IV-2-9
(11) are simply forms of the familiar geometrical distance formula,
j _ i /„ ,, \<- i /,, ,, ^ I l/<-
which has been expanded to accomodate n dimensions. Sokal (1961) divided the
distance by n to produce a mean squared difference, which he felt was an
appropriate measure of taxonomic distance. Values computed by the distance
formulas may range from zero for identical collections to infinity; the
greater the distance the less similar the two comunities are. Because the
difference in species abundance is squared in the numerator, the distance
formulas are heavily influenced by abundant species and may over-emphasize
dominance. The similarity of disparate communities with low species
abundances may be overstated, while the resemblance of generally similar
communities with a few disproportionately high species abundances may be
understated. To avoid indicating misleading resemblance, it may be necessary
to transform data (e.g. to squared or cubed roots) before computing taxonomic
distance.
The Product-Moment Correlation Coeffficient (12) is a popular resemblance
measure that ranges from -1 (completely dissimilar) to +1 (entirely similar).
Several undersirable characteristics of this measure have been cited (Sneath
and Sokal, 1973; Clifford and Stephenson, 1975; Boesch, 1977). Deceptive
resemblance values can result from outstandingly high species abundances or
the presence of many species absences, and non-identical communities can
register perfect correlation scores. Pinkham and Pearson (1976) demonstrated
how the Product-Moment Correlation Coefficient, like the Percent Community
Similarity Index, indicates maximum similarity for two communities having the
same relative species composition but different actual species abundances.
IV-2-36
-------
Experimental Evaluation of Comparison Indices
Brock (1977) compared the Percent Community Similarity Index (7) and the
Pinkham and Pearson Similarity Index (8) for their ability to detect changes
in the zooplankton community of Lake Lyndon B. Johnson, Texas, due to a
thermal effluent. For this study, the Pinkham and Pearson index was
considered too sensitive to rare species and not sensitive enough to dominant
forms, whereas the Percent Similarity coefficient was more responsive to
variation in dominant species and relationships between dominant and
semi-dominant forms. Linking dominance to function, the author concluded that
the later index may better indicate structural-funcitonal similarity between
communities.
Perkins (1983) evalutaed the responsiveness of eight diversity indices and
five community comparison indices to increasing copper concentrations. The
indices were calculated for bioassays conducted using benthic
macroinvertebrates and artificial streams. The indices evaluated by Perkins
correspond to equations presented in Tables IV-2-2 and IV-2-9 except: Perkins
tested the Bray-Curtis dissimilarity index; Perkins' Biosim index is Pinkham
and Pearson's index, and the distance formula tested by Perkins (not included
in this report) is shown below.
D -
The results of the study ap
are presented for comparison
!Z
n
ar in
i
x . -x .,
la ib
x. +x.,
ia ib
i
Fi gure
IV-2
I/
-6;
the diversity index results
increased
increasi ng
The diversity indices did not clearly demonstrate the perturbation caused by
increasing copper concentrations. The Shannon and Brillouin formulas
initially, in spite of a decreasing number of species, because of
/enness of species distribution. Other than the increasing
diversity indicated at the lower copper concentrations, these two indices
reflected perturbation effectively by decreasing rapidly with increasing
pollutant concentration. The Mclntosh, Simpson, and Pielou (evenness) indices
(not shown for 28 days in Figure IV-2-6) resembled the trends demonstrated by
the Shannon and Brillouin formulas albeit less dramatically. Because the
results obtained for those three indices were less pronounced, they were more
difficult to interpret than the Shannon and Brillouin findings.
The community comparison indices were found to be good indicators of the
perturbation of macroinvertebrate communities caused by copper pollution.
Although the Bray-Curtis index was considered the most accurate after 14 days,
all of the comparison indices tested effectively reflected community response
after 28 days (see Figure IV-2-6). Note that by definition the Biosim,
Morisita, and Percent Community Similarity indices decrease as similarity
decreases, while the Distance and Bray-Curtis dissimilarity indices increase.
It has frequently been suggested that it may be desirable to apply several
indices in a pollution assessment study (Peters, 1968; Brock, 1977; Perkins,
1983).
IV-2-37
-------
l=Shannon
2=Brillouin
3=Pielou
4=Simpson
5-McIntosh
6-Menhinlck
7=Species(xlO)
8=Equitability
3.5-
3.0
2.0
I 0
0.5
0.5 10 1.5
Log Cu~(/j.g/l)
(b)
8-
7-
_
E .6
"0
05 1.0
LogCu'
(c)
15
2.0
l=D1stance
2=Bray-Curtis
3=% Similarity
4=Morisita
5=Biosim
'35
0.5
1.0
LogCu~(/ug/l)
(d)
Figure IV-2-6.
Evaluation of diversity indices and community comparison indices
using bioassay data: a,c=after 14 davs; b,drafter 28 davs (from
Perkins, 1983).
IV-2-38
-------
Numerical Classification or Cluster Analysis
A common use of similarity indices is in numerical clasification of biological
communities. Numerical classification, or cluster analysis, is a technique
for grouping similar entities on the basis of the rsemblance of their
attributes. In instances where subjective classification of communities is
not clear-cut, cluster analysis allows incorporation of large amounts of
attribute data into an objective classification procedure. Kaesler and Cairns
(1972) outlined five steps involved in normal cluster analysis. First, a
community similarity index is chosen based on pre-determined criteria and
objectives. Second, a matri-x of similarity coefficients is generated by
pairwise comparison of all possible combinations of stations. The third step
is the actual clustering based on the resemblance coefficients. A number of
clustering procedures are discussed in the literature (Williams, 1971; Sneath
and Sokal, 1973; Hartigan, 1975; Boesch, 1977). In the fourth step, the
clustered stations are graphically displayed in a dendogram. Because
multi-dimensional resemblance patterns are displayed in two dimensions and
because the similarity coefficients are averaged, a significant amount of
distortion can occur. For this reason, a distortion measure should be
evaluated and presented as the fifth step in the cluster analysis. The
Cophenetic Correlation Coefficient (Sokal and Rohlf, 1962) is a popular metric
of display accuracy. An additional step in any cluster analysis application
should be interpretation of the numerical classification results since the
technique is designed to simplify complex data and not to produce ecological
interpretation.
SUMMARY
The ability of a water resource to sustain a balanced biotic community is one
of the best indicators of its potential for beneficial use. This ability is
essential to the community's health. Although several papers have criticized
the use of diversity indices (Hurlbert,1971; Peet,1975; Godfrey,1978), Cairns
(1977) stated that "the diversity index is probably the best single means of
assessing biological integrity in freshwater streams and rivers". Cairns
concluded that no single method will adequately assess biological integrity,
but rather its quantification requires a mix of assessment methods suited for
a specific site and problem. The index of diversity is an integral part of
that mix. Community comparison indices are also useful in assessing the
biological health of aquatic systems. By measuring the simiarity (or
dissimilarity) between sampling stations, community comparison indices
indicate relative impairment of the aquatic resource.
IV-2-39
-------
CHAPTER IV-3
RECOVERY INDEX
It is important to examine the ability of an ecosystem to recover from
displacement due to pollutional stress in order to evaluate the potential
uses of a water body. Cairns (1975) developed an index which gives an
indication of the ability of the system to recover after displacement. The
factors and rating system for each factor are:
(a) Existence of nearby epicenters (e.g., for rivers these might be
tributaries) for providing organisms to reinvade a damaged system.
Rating System : l=poor, 2=moderate, 3=good
(b) Transportability or mobility of disseminules (the disseminules might be
spores, eggs, larvae, flying adults which might lay eggs, or other stages
in the life history of an organism which permit it to move to a new area).
Rating System : l=poor, 2-moderate, 3=good
(c) Condition of the habitat following pollutional stress (including
physical habitat and chemical quality).
Rating system : l=poor, 2=moderate, 3=good
(d) Presence of residual toxicants following pollutional stress.
Rating System : l=large amounts, 2=moderate amounts, 3=none
(e) Chemical-physical environmental quality after pollutional stress.
Rating System : l=in severe disequilibrium, 2=partially restored,
3=normal
(f) Management or organizational capabilities for control of damaged area.
Rating system : l=none, 2-some, 3=strong enforcement possible.
Using the characteristics listed above, and their respective rating
systems, a recovery index can be developed. The equation for the recovery
index follows:
Recovery Index = a xbxcxdxexf
400+ = chances of rapid recovery excellent
55-399 = chances of rapid recovery fair to good
less than 55 = chances of rapid recovery poor
This index and the rating system was developed by Cairns based on his
experience with the Clinch River. For a full description of the rationale
for the rating factor, the reader should refer to Cairns (1975).
IV-3
-------
CHAPTER IV-4
INTOLERANT SPECIES ANALYSIS
NICHE CONCEPT
The ecological niche of a species is its position and role in the biological
community. Hutchinson (1957) described niche as a multidimensional space, or
hypervolume, that is delineated by the species' environmental requirements and
tolerances. Physical, chemical, and biological conditions and relationships
constitute the dimensions of the hypervolume, and the magnitude of each dimen-
sion is defined by the upper and lower limits of each environmental variable
within which a species can persist. If any one of the variables is outside of
this range the organism will die, regardless of other environmental conditions.
TOLERANCE
The "Law of Toleration" proposed by Shelford (1911) is illustrated in Figure
IV-4-1. For each species and environmental variable there is a range in the
variable intensity over which the organism functions at or near its optimum
level. Outside the maximum and minimum extremes of the optimum range there are
zones of physiological stress, and, beyond, there are zones of intolerance in
which the functions of the organism are inhibited. The upper and lower toler-
ance limits (also called incipient lethal levels) are intensity levels of the
environmental variable that will eventually cause the death of a stated frac-
tion of test organisms, usually 50 percent.
VARIABILITY OF TOLERANCE
The tolerance of an organism for a lethal condition is dependent on its gene-
tic constitution - both its species and its individual genetic makeup - and
its early and recent environmental history (Warren 1971). Acclimation has a
marked effect on the tolerance of environmental factors such as temperature,
dissolved oxygen, and some toxic substances (see Figure IV-4-2). Tolerance is
also a function of the developmental stage of the organism and it may change
with age throughout the life of the animal. Because of this variability, no
two organisms have exactly the same tolerance for a lethal condition and toler-
ance limits must be expressed in terms of an "average" organism.
INTERACTIONS INFLUENCING TOXICITY
An organism's tolerance for a particular lethal agent is dependent not only on
its own characteristics but also on the environmental conditions. The inter-
actions between lethal and nonlethal factors are well documented and are ad-
dressed elsewhere in this handbook (Chapters II-5 and III-2). Briefly, these
nonlethal effects include:
IV-4-1
-------
Lower limit of tolerance
Upper limit of tolerance •
Zone of
intolerance
Zone of
physiological
stress
RANGE OF OPTIMUM-
Zone of
physiological
stress
Zone of
intolerance
Low
Figure IV-4-1.
Law of toleration in
level--often a norma'
Shelford (1911)).
relation to distribution and population
curve (modified by Kendeigh (1974) from
u
2 3°
"5
z
Q.
0 20
U
IO - 20 30
Acclimaiion temperature (C)
4O
Figure IV-4-2.
The zones of tolerance of brown bullheads (Ictalurus nebulosus)
and chum salmon (Oncorhynchus keta) as delimited by incipient
lethal temperature and influenced by acclimation temperature
(after Brett 1956).
IV-4-2
-------
Hardness. Increasing hardness decreases the effect of toxic metals on aqua-
tic organisms by forming less-toxic complexes.
pH. The dissociation of weak acids and bases is controlled by pH and either
the molecular or ionic form may be more toxic.
Alkalinity and Acidity. These modify pH by constituting the buffering capa-
city of the system.
Temperature. Increasing temperature enhances the effect of toxicants by in-
creasing the rates of metabolic processes.
Dissolved Oxygen. Decreasing dissolved oxygen concentration augments the
exposure and absorption of toxicants by increasing the necessary irriga-
tion rate of respiratory organs.
When two or more lethal agents are present, several types of interactions are
possible: synergistic, additive, antagonistic, or no interaction.
INTOLERANT SPECIES ANALYSIS
The tolerance ranges for environmental variables differ widely between spe-
cies. Thus, the range of conditions under which an organism can survive (its
niche) is broader for some species than it. is for others. Fish species with
narrow tolerance ranges are relatively sensitive to degradation of water qual-
ity and other habitat modifications, and their populations decline or disap-
pear under those circumstances before more tolerant organisms are affected. In
general, intolerant species can be identified and used in evaluating environ-
mental quality. The presence of typically intolerant species in a fish sam-
pling survey indicates that the site has relatively high quality; while the
absence of intolerant species that, it is judged, would be there if the envi-
ronment was unaltered indicates that the habitat is degraded.
LISTS OF INTOLERANT FISH SPECIES
While the tolerance limits of a fish species for a particular environmental
factor can be defined relatively precisely by toxicity bioassays, its degree
of tolerance may vary considerably over the range of physical, chemical, and
biological variables that may be encountered in the environment. The variables
that are the object of intolerant species analysis are intentionally left
vague in order to accommodate the variety of situations precipitated by man's
activities. A species may be intolerant of alterations in water quality or in
habitat structure, such as those listed below.
Water Quality Changes Habitat Alterations
increased turbidity substrate disruption
increased siltation cover removal
increased water temperature changes in velocity and discharge
increased dissolved solids removal of instream and streamside
organic enrichment vegetation
lowered dissolved oxygen water level fluctuation
impoundment and channelization
blockage or hinderance of migration
IV-4-3
-------
Many species can be identified that are relatively intolerant of anthropogenic
alterations of the aquatic environment compared to other fish. Appendix C con-
tains a list of fish species, nationally, which are relatively intolerant to
one or more of the environmental changes shown above. The information in Appen-
dix C is based on literature sources (Wallen 1951; Trautman 1957; Carlander
1969, 1977; Scott and Grossman 1973; Pflieger 1975; Moyle 1976; Timbol and
Maciolek 1978; Smith 1979; Muncy et al. 1979; Lee et al. 1980; Morrow 1980;
Johnson and Finley 1980; U.S. EPA 1980; Karr 1981; Haines 1981; and Ball 1982)
and on the professional judgment of State and University biologists.
The darters and sculpins are listed only by genus in Appendix C. Identifica-
tion of those taxa to species would have been inconvenient (together, Ammo-
crypta, Etheostoma, Percina, and Cottus contain 150 species in the United
States) and largely unnecessary because, with a few possible exceptions, all
of the species of darters and sculpins can be considered intolerant. Karr
(1981) recognized the johnny darter (Etneostoma m'grum) as the most tolerant
darter species in Illinois and Ball(1982)did not categorize the johnny
darter as an intolerant forage fish. Other darter species that appear to be
relatively more tolerant of turbidity, silt, and detritus than others in their
genus are listed below:
mud darter Etheostoma asprigene
bluntnose darter E. chlo role-mum
slough darter F^ graci1e
cypress darter ET proeliTre
orangethroat darter F. spectabi'Te
swamp darter F. fusiforme~
river darter Percina shumardi
The list in Appendix C is intended to be used by knowledgeable biologists as a
rough guide to the relatively intolerant fish species in their state. Site-
specific editing is left to persons familiar with the local fish fauna and en-
vironmental conditions. Local editing of the provided data should produce a
workable list for intolerant species analyses of the streams in that area.
IV-4-4
-------
OMNIVORE-CARNIVORE (TROPHIC STRUCTURE) ANALYSIS
INTRODUCTION
Water pollution problems nearly always involve changes in the pathways by
which aquatic populations obtain energy and materials (Warren 1971). These
changes lead to differential success of constituent populations which affects
the composition of the aquatic community- Anthropogenic introduction of or-
ganic substances or mineral nutrients directly increases the energy and ma-
terial resources of the system, but other pollution problems - such as pH or
temperature changes, toxic materials, low dissolved oxygen, turbidity, silta-
tion, et cetera - also lead to changes in trophic pathways. Thus, the health
of a system can be evaluated through a study of its trophic structure. The
following material concentrates on stream and river systems. Lakes will have
different structural aspects.
TROPHIC STRUCTURE
The ecosystem has been described as the entire complex of interacting physi-
cochemical and biological activities operating in a relatively self-supporting
community (Reid and Wood 1976). The biological operations of an ecosystem can
be viewed as a series of compartments which are described by three general cat-
egories: producers, consumers, and decomposers. The producers include all auto-
trophic plants and bacteria (both photosynthetic and chemosynthetic) which, by
definition, are capable of synthesizing organic matter from inorganic sub-
strates. The consumers are heterotrophic organisms that feed on other organ-
isms, and are typically divided into herbivores and carnivores. Herbivores
(primary consumers) feed principally on living plants while carnivores (sec-
ondary, tertiary, and quarternary consumers) feed principally on animals that
they kill. Another type of consumer, the omnivore, feeds nearly equally on
plants and animals, and occupies two or more trophic levels. The decomposers
include all organisms that release enzymes which break down dead organisms.
Food chains are sometimes used to simply represent feeding relationships be-
tween trophic levels (e.g., plant > herbivore > carnivore). Ecosystems common-
ly contain three to five links in their food chains. Diagramming all of the
pathways of energy and material transfer in a community entails many inter-
connecting food chains, forming a complex food web.
The concept of trophic structure, first formally discussed by Lindeman (1942),
is a method of dealing with the pathways of energy and material transfer which
focuses on functional compartments without considering the specific feeding
relationships. The pathways between functional compartments are illustrated in
Figure IV-5-1. Trophic structure is commonly represented by trophic or ecolog-
ical pyramids. An ecological pyramid is a diagramatic representation of the r-
elationships between trophic levels arranged with the producers making up the
base and the terminal or top carnivore at the apex. An ecological pyramid may
IV-5-1
-------
HERBIVORES .
CARNIVORES
1C,)- (C.)-(C,)
PRODUCERS
:DECOMPOSERS
Figure IV-5-1. Trophic pathways of an ecosystem (after Reid and Wood 1976)
S-5
I C.-1.5
i-
-
C,-37
P-809
kcal/m:
(al
S-5060
C,-383
C.-3368
P-20,810
kca(/ma/YEAR
Figure IV-5-2.
Ecological pyramids for Silver Springs, Florida, indicating (a)
biomass and (b) productivity. P=producers; C=consumers; S=sapro-
phytes or heterotrophs (after Odum 1957).
IV-5-2
-------
represent the number of individuals that compose each trophic level, or, of
more ecological significance, the biomass or productivity of each level (Fig-
ure IV-5-2). Because energy transfer between trophic levels is less than 100 p-
ercent efficient the pyramid of productivity must always be regular in shape,
while pyramids of numbers and biomass may be partially inverted in some in-
stances (Richardson 1977).
TROPHIC STRUCTURE OF FISH COMMUNITIES
Fish communities generally include a range of species that represent a variety
of trophic levels. The trophic classification system shown below was used in
the assessment of fish fauna of the Illinois and Maumee River basins (Karr and
Dudley 1978, Karr et al. 1983).
(1) Invertivore - food predominantly (>75%) invertebrates.
(2) Invertivore/Piscivore - food a mixture of invertebrates and fish; rela-
tive proportions often a function of age.
(3) Planktivore - food dominated by microorganisms extracted from the water
column.
(4) Omnivore - two or more major (>2b% each) food types consumed.
(5) Herbivore - feed mostly by scraping algae and diatoms from rocks, and
other stream substrates.
(6) Piscivore - feed on other fish.
Schlosser (1981, 1982a, 1982b) used the trophic structure of fish communities
to investigate differences in Illinois stream ecosystems. His categorization
scheme appears in Table 1.
In addition to representing a range of trophic levels, fish utilize foods of
both aquatic and terrestrial origin, and occupy a position at the top of the
aquatic food web in relation to plants and invertebrates. These facts enhance
the ability of fish communities to provide an integrative view of the water-
shed environment (Karr 1981).
BIOLOGICAL HEALTH
Degradation of water quality and habitat affects the availability of many food
resources, resulting in changes in the structure and functions, and, thus, the
health of the aquatic community. Structural characteristics include the num-
bers and kinds of species and the number of individuals per species. These
parameters can be evaluated relatively quickly via compilation of species
lists, calculation of diversity indices, and identification of indicator spe-
cies. The importance of evaluating the impact of pollution on community func-
tions - such as production, respiration, energy flow, degradation, nutrient
cycling, and other rate processes - is becoming increasingly evident, and,
ideally, any study of community health should include both structural and
functional assessment. However, use of functional methods has been hindered
because they are often expensive, time-consuming, and not well understood.
IV-5-3
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TABLE IV-5-1.
TROPHIC GUILDS USED BY SCHLOSSER (1981, 1982A, 1982B)
TO CATEGORIZE FISH SPECIES
Herbivore - detritivores (HD)
Omnivores (OMN)
Generalized Insectivores (GI)
Surface and Water Column
Insectivores (SWI)
Benthic insectivores (BI)
Insectivore - Piscivores (IP)
HD species fed almost entirely on dia-
toms or detritus.
OMN species consumed plant and animal
material. They differed from GI species
in that, subjectively, greater than 25
percent of their diet was composed of
plant or detritus material.
GI species fed on a range of animal and
plant material including terrestrial
and aquatic insects, algae, and small
fish. Subjectively, less than 25 per-
cent of their diet was plant material.
SWI species fed
or terrestrial
surface.
on water column drift
insects at the water
BI species fed predominantly
ture forms of benthic insects.
on imrna-
IP species fed on aquatic invertebrates
and small fish. Their diets ranged from
predominantly fish to predominantly in-
vertebrates.
IV-5-4
-------
Examining the trophic structure of a community can provide insight into its
production and consumption dynamics. A trophic-structure approach to the study
of the functional processes of stream ecosystems has been proposed by Cummins
and his colleagues (Cummins 1974, 1975; Vannote et al. 1980). Their concept
assumes that a continuous gradient of physical conditions in a stream, from
its headwaters to its mouth, will illicit a series of consistent and predict-
able responses within the constituent populations. The River Continuum Concept
identifies structural and functional attributes t-hat will occur at different
reaches of natural (unperturbed) stream ecosystems. These attributes (sum-
marized in Table IV-5-2) can serve as a reference for comparison to measured
stream data. Measured data which are commensurate with those predicted by the
river continuum model indicate that the studied system is unperturbed, while
disagreement between actual and expected data indicates that modification of
the ecosystem has occurred (Karr and Dudley 1978).
EVALUATION OF BIOLOGICAL HEALTH USING FISH TROPHIC STRUCTURE
Karr (1981) developed a systejn for assessing biotic integrity using fish com-
munities, which is discussed in Chapter IV-2: Diversity Indices. Three em-
pirical trophic metrics are incorporated into Karr's index of biotic integrity
(IBI). They are:
(1) the proportion of individuals that are omnivores,
(2) the proportion of insectivorous individuals of the Cyprinidae family,
and
(3) the presence of top carnivore populations.
Karr (1981) observed that the proportion of omnivores in a community increases
as the quality of the aquatic environment declines. Nearly all major consumer
species are omnivorous to a degree (Darnell 1961), so populations are con-
sidered to be truly omnivorous only if they feed on plants and animals in
nearly equal amounts or indiscriminately (Kendeigh 1974). Recall that Karr and
Schlosser used 25 percent of plant material ingested as the level for distin-
guishing between omnivores and other trophic guilds. Presumably, changes in
the food base due to pollutional stress allow the euryphagic omnivores to be-
come dominant because their opportunistic foraging ecology makes them more suc-
cessful than more specific feeders. Omnivores are often virtually absent from
unmodified streams. Even in moderately - altered streams omnivorous species
usually constitute a minor portion of the community. For this reason, the bi-
ologist responsible for assessment must be familiar with the local fish fauna
and aquatic habitats in order to be able to interpret subtle disproportions in
trophic structure. In general, Karr (1981) has found samples with fewer than
20 percent of individuals as omnivores to be representative of good environ-
mental quality, while those with greater than 45 percent omnivores represent
badly degraded sites.
Karr (1981) reported that a strong inverse correlation exists between the abun-
dance of insectivorous cyprinids and omnivores. Thus, communities containing a
large proportion of insectivorous members of the minnow family (>45%) tends to
indicate relatively high environmental quality.
IV-5-5
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TABLE IV-5-2. GENERAL CHARACTERISTICS OF RUNNING WATER ECOSYSTEMS ACCORDING TO SIZE OF STREAM.
(From Karr and Dudley 1978, modified from Cummins 1975)
Stream
size
*Smal 1
headwater
streams
( stream
order
1-3)
*Medium
sized
streams
(4-6)
*Large
rivers
(7-12)
Primary
energy
source
Coarse particulate
organic matter
(CPOM) from the
terrestrial
environment
Little primary
production
Fine particulate
organic matter
(FROM), mostly
Considerable
primary
production
FROM from
upstream
•-•- - •*— — |— r-B r r-~—r — r '— i— n
Production
(trophic)
state
Heterotrophic
P/R <1
Autotrophic
P/R >1
Heterotrophic
P/R <1
1 in •" *•• j — — — f- — — — ——- •- —
Light and
temperature
regimes
Heavily
shaded
Stable
temperatures
Little
shading
High daily
temperature
variation
Little shading
Stable
temperatures
• — — - .— —••II. - • • • .I i
Trophic status of dominant
insects
Shredders
Collectors
Collectors
Scrapers
(grazers)
Planktonic
collectors
Msn
Invertivores
Invertivores
Piscivores
Planktivores
Streams are typically subdivTdird into these three size classes based on the stream order classification system
of Kuehne (1962).
IV-5-6
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Faucsh et al. (unpublished manuscript) investigated the regional applicability
of the IBI. Results from the two least disturbed watersheds in the study --
the Embaras River, Illinois and the Red River, Kentucky — confirmed the fixed
scoring criteria proposed by Karr (1981) for omnivores and insectivorous cypri-
nids. At most of the undisturbed sites in each stream, omnivores constituted
20 percent or less of all individuals and at least 45 percent of individuals
were insectivorous cyprinids.
The presence of viable, vigorous populations of top carnivores is another in-
dicator of a relatively healthy, trophically diverse community used in Karr's
index. As described earlier, top carnivores constitute the peak of the eco-
logical pyramid, and, therefore, occupy the highest trophic level in that par-
ticular community. Degradation of environmental quality causes top carnivore
populations to decline and disappear. Theoretically, since top carnivore pop-
ulations are supported (directly or indirectly) by all of the other (lower)
trophic levels, they serve as a natural monitor of the overall health of the
community. Because of their position atop the food chain, terminal carnivores
are most vulnerable to detrimental effects of biomagnified toxicants. Also,
predation by top carnivores keeps the populations of forage and rough fish in
check, thereby functioning to maintain biotic integrity. As always, it is as-
sumed that the project biologist will use considerable personal knowledge of
local ichthyology and ecology in adjusting expectations of top carnivore spe-
cies to stream size. The top carnivore populations, must be evaluated in rela-
tion to what would be there if the habitat were not modified. Defining the
baseline is a major problem in any study of pollutional stress. In determining
the baseline community, the biologist may rely on the faunas of similar, unal-
tered habitats in the area, literature information, and personal experience —
remembering the concepts of the river continuum model.
The results of research conducted throughout the midwest tend to support the
theoretical basis of the omnivore and top carnivore metric approaches to as-
sessing biotic integrity (Larimore and Smith 1963, Cross and Collins 1975,
Menzel and Fierstine 1976, Karr and Dudley 1978, Schlosser 1982a, Karr et al.
1983), Fausch et al. (unpublished manuscript) evaluated five watersheds in
Illinois, Michigan, Kentucky, Nebraska, and North and South Dakota using the
IBI, and found that scores accurately reflected watershed and stream condi-
tions.
However, experts in the field recognize that the omnivore - top carnivore anal-
ysis may not be applicable in every situation on a nationwide basis. Reser-
vations over use of this approach seem to be based on three variables.
(1) Type of pollutional stress - e.g., the trophic metrics proposed by Karr
(1981) were largely derived from agricultural watersheds in which sedi-
mentation and nutrient enrichment are the predominant forms of anthro-
pogenic stress; other pollution problems such as toxic waste discharge
could conceivably have a different impact on fish trophic structure.
IV-5-7
-------
(2) lype of aquatic habitat - e.g., headwater streams, large rivers, and
flowing swamps represent very different environments which are charac-
terized by a variety of trophic pathways and food sources.
(3) Type of ambient fish fauna - e.g., no or very tolerant top carnivores
might be present naturally, or no or very intolerant omnivores.
LIST OF OMNIVORES AND TOP CARNIVORES
Examples of resident omnivore and top carnivore fish species are listed nation-
ally in Appendices B-l and B-2, respectively. These tables were compiled based
on information found in the literature (Morita, 1963; Carlander, 1969, 1977;
Pflieger, 1975; Moyle, 1976; Timbol and Maciolek, 1978; Smith, 1979; Morrow,
1980; Lee et al.,1980; Karr et al., 1983). The purpose of the lists is to
provide a framework for assessing omnivore and top carnivore populations.
However, because of the geographic variability in feeding habits, the gaps in
available foraging data, and the dynamic nature of range boundaries, some
members of the list may not occupy the specified trophic compartment in a
particular area, while other species that belong on the list may have been
overlooked. The list is intended to be used by knowledgeable biologists who
are capable of adding and deleting species where necessary to produce a list
which is appropriate for the particular area of study.
IV-5-8
-------
CHAPTER IV-6
REFERENCE SITES
Introduction
The goal of this section is to suggest an objective, ecological
approach that should aid States in determining the ecological potential of
priority aquatic ecosystems, evaluating and refining standards,
prioritizing ecosystems for improvements, and comprehensively evaluating
the ecological quality of aquatic ecosystems. The objectives of this
section are to demonstrate the need for regional reference sites and to
demonstrate how they can be determined. To do this the need for some type
of control or reference sites will be discussed and alternate types will be
outlined, the concept of ecological regions and methods for determining
them will be described, aspects that should be considered when selecting
reference sites will be listed, and the limitations of the regionalization
method will be discussed.
Although correlation between a disturbance and the resulting
functional or structural disorder can stimulate considerable insight, the
disorder that results from disturbing a water body can be demonstrated
scientifically only by comparing it with control or reference sites. To
scientifically test for functional or structural disorder, data must be
collected when the disturbances are present and when the disturbances are
absent but everything else is the same. Disorders that are unique to the
disturbed areas must be related to the disturbances but separated from
natural variability. This requires carefully selected reference sites, but
it is difficult or impossible to find pristine control or reference sites
in most of the conterminous United States. Also, it is unlikely that
pristine reference sites would be appropriate for most disturbed sites
because they would differ in ways besides the distrubance, as will be
discussed later.
The most commonly used reference sites are upstream and downstream of
the recovery zone of a point source. However, these sites provide little
value where diffuse pollution is a problem, where channel modifications are
extensive, where point sources occur all along the stream, where the
stream's morphology or flow changes considerably among sites, or where
various combinations of these disturbances occur. Hughes et al. (1983)
suggest a different approach, which reduces the problems of upstream-
downstream reference sites. Their approach is based on first determining
large, relatively-homogeneous, ecological regions (areas with similar
land-surface form, climate, vegetation, etc.) followed by selection of a
series of reference sites within each region. These sites could possibly
serve as references for a number of polluted sites on a number of streams
thereby economizing on and simplifying concurrent or future studies. A
modification of Hughes et al.'s approach has been tested on two polluted
streams in Montana (Hughes MS) and the approach is being rigorously tested
on 110 sites in Ohio (Omernik and Hughes 1983).
IV-6-1
-------
The logical basis for Omernik and Hughes' approach was developed from
ailey (1976), Green (1979), Hall et al. (1978), and arren (1979). Their
logic fits well with the proposed water quality standards regulation
(Federal Register 1982) that suggests grouping of streams wherever
possible. Bailey stressed that heterogeneous lands, such as those managed
by the U.S. Forest Service, must be hierarchically classified by their
capabilities. He added that classification should be objective,
synthesized from present mapped knowledge, and based on the spatial
relationships of several environmental characteristics rather than on one
characteristic or on the similarity of the characteristics alone.
One of Green's ten principles for optimizing environmental assessments
is that wherever there are broad environmental patterns, the area should be
broken into relatively homogeneous subareas. Clearly, this principle
applies to most States. Hall et al. found that studies that incorporate
several variously-impacted sites were more useful than separate intensive
studies of one or two sites and more practical than long-term pre- and
post- impact studies.
Warren proposed that a watershed/stream classification should
integrate climate, topography, substrate, biota, and culture at all levels,
as opposed to considering them separately. He also stated that the
integration and classification should be hierarchical and be determined
from the potentials of the lands and waters of interest, rather than from
their present conditions. Streams within Warren's proposed classification
would have increasingly similar ecological potentials as one moved down
through the hierarchy to ever smaller watersheds or ecological regions.
The Concept of Ecological Regions
The ecological potential of a reference or disturbed site is
considered to be the range of ecological conditions present in a number of
typical, but relatively-undisturbed sites within an ecological region.
Suchrelatively-undisturbed sites, can be found even in the channelized
streams of the Midwest Corn Belt (Marsh and Luey 1982). One should not
suppose that such sites represent pristine or undisturbed controls, only
that they are the best that exist given the prevalent land use patterns in
an ecological region. Because of the major economic and political strains
required, we do not believe that resource managers or even knowledgeable
and concerned citizens will change those general land use patterns much.
But such persons will need to know the best conditions they can expect in a
water body in order to decide whether the economic and noneconomic benefits
of a particular water body standard are worth their economic and
noneconomic costs. To make such determinations rationally, the reference
sites must also be typical of a region. That is, their watersheds must
wholly reflect the predominant climate, land-surface form, soil, potential
natural vegetation, land use, and other environmental characteristics
defining that region, and the site itself must contain no anomalous
feature. For example, a cobble-bottomed stream in an entirely forested,
highly dissected watershed would not be typical of the sand and
gravel-bottomed streams in the agricultural prairies of the Midwest, nor
could it be a useful predictor of such an agricultural stream's ecological
potential, even though such a watershed and stream might be found in such a
region.
IV-6-2
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Although all aquatic ecosystems differ to some degree, the basis of
ecological regions is that there also is considerable similarity among
aquatic ecosystem characteristics and that these similarities occur in
definable geographic patterns. Also, the variabilities in the present and
potential conditions of the chemical and physical environment and the biota
are believed to be less within an area than among different areas. For
example, streams in the Appalachian Mountains, are more similar to each
other than to those in the Corn Belt or those on the Atlantic Coastal
Plain. It is assumed that streams acquire their similarities from
similarities in their watersheds and that streams draining watersheds with
similar characteristics will be more similar to each other than to those
draining watersheds with dissimilar characteristics. Thus, an ecological
region is defined as a large area where the .homogeneity in climate,
land-surface form, soil, vegetation, land use, and other environmental
characteristics is sufficient to produce relative homogeneity in stream
ecosystems.
The concept of an ecological region is an out-growth of the work of
vegetation ecologists, climatologists, physiographers, and soil
taxonomists, all of whom have sought to display national patterns by
mapping classes of individual environmental characteristics (USDI
Geological Survey 1970). James (1952) discusses the value of integrating
or regionalizing such environmental characteristics and Warren (1979)
provides an excellent rationale for classifying ecological regions, but
Bailey's ecoregion map (1976) comes the closest to actually doing so.
However, Bailey's map incorporates a hierarchical approach, concentrating
on an individual environmental characteristic at each level, and does not
yet incorporate land-surface form or land use. Hughes and Omernik (1981b)
agree with Warren that it is most useful to integrate these features at
every level in the hierarchy of ecological regions. Such an approach
facilitates the mapping of ecological regions at a national, state, or
county level with increasing resolution (but decreasing generality) at each
lower level.
Ecological regions should improve States' abilities to manage aquatic
ecosystems in at least four ways (Hughes and Omernik 1981b): (1) They
should provide ecologically-meaningful management units. Such units allow
objective and logical synthesis of existing data from ecologically-similar
aquatic ecosystems and, using that synthesis, extrapolation to other
unstudied ecosystems in the same ecological region. (2) They should
provide an objective, ecological basis to refine use classifications and to
evaluate the attainment of uses for aquatic ecosystems. This is because
they provide an ecological basis for determining typical and potential
states of aquatic ecosystems located in similar watersheds. (3) They
should provide an objective ecological basis to prioritize aquatic
ecosystems for improvements or for attainability analyses. Given knowledge
of the typical and potential conditions of aquatic ecosystems in the
separate ecological regions of a State, that State can rationally determine
what to expect from improvements and thereby know where it will get the
greatest ecological returns for its investments. (4) They should simplify
setting site-specific criteria on site-specific biota, as allowed by the
proposed water quality regulation. Rather than set separate criteria for a
large number of sites at enormous expense, a State could use criteria
obtained from a series of sites that typify potential conditions in each
ecological region of that state or neighboring states.
IV-6-3
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The process of selecting reference sites can be broken into two major
phases with most of the work done in an office. First, the ecological
regions, and most-typical area(s) of interest are determined. Second,
various sizes of candidate watersheds and reaches are evaluated for
typicalness and level of disturbance in order to select reference sites.
Determining Ecological Regions
There are several methods for determining ecological regions.
Trautman (1981) suggested that one factor, physiography, could be used to
determine patterns of stream types and fish assemblages in Ohio. Lotspeich
and Platts (1982) believed regions should be determined from two factors,
climate and geology. Bailey (1976) used three factors, climate, soil, and
potential natural vegetation, in his ecoregion map of the United States but
suggested adding land-surface form and lithology if smaller ecoregions are
mapped. Warren (1979) proposed that five factors, climate, topography,
substrate, biota and culture, should all be incorporated in watershed
classification. Hughes and Omernik (1981b), Omernik et al. (1982), and
Omernik and Hughes (1983) overlaid maps of land-surface form, soil
suborders, land use, and potential natural vegetation in studies of the
Corn Belt and Ohio, but suggest using precipitation, temperature, and
lithology if major differences in these factors are suspected. Lotspeich
and Platts, Bailey, and Warren all emphasized the use of hierarchical
ecoregions, moving from broad national regions thousands of square
kilometers in size to small watersheds a few square kilometers in area. A
much different approach to determining ecological regions, is the stream
habitat classification of Pflieger et al. (1981). They used cluster
analysis of fish collections from throughout Missouri to group localities
having similar fish faunas. Where States have computerized fish collection
data from a thousand or more sites, cluster analysis is a useful approach,
however only a handful of States have such data.
Because of the diversity of methods for determining ecological
regions, the limited testing of their applicability to aquatic ecosystems,
and the limited number of large computerized data files, States are
encouraged to select a method that allows the greatest potential for later
modification. The method of Hughes and Omernik requires no prior
collection data and appears to allow more modification than the others.
The greater number of characteristics used to determine regions increases
the opportunity that those regions will have a variety of uses by several
agencies and greater value in predicting impacts of managment actions.
Therefore, their method is outlined by the following steps:
1. Select the area and aquatic characteristics of interest. In many cases
the area of interest will be a State, but wherever major environmental
characteristics or watersheds do not coincide with state borders, States
may find it useful and economical to work cooperatively and incorporate
portions of neighboring States. Aquatic characteristics of interest may
include fish and macro-invertebrate assemblages and various aspects of
the chemical and physical environment affecting those assemblages.
IV-fi-4
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2. Select broad environmental characteristics most likely to control the
aquatic characteristics of interest. Environmental characteristics to
consider are climate (especially mean annual precipitation and summer
aad winter temperature extremes), land-surface form (types of plains,
hills, or mountains), surficial geology (types of soil parent material),
soils (whether wet or dry, hot or cold, shallow or deep, or low or high
in nutrients), potential natural vegetation (grassland, shrubland, or
forestland, and dominant species), major river basins (especially
important in unglaciated areas for limiting fish and mollusk
distribution), and land use (especially cropland, grazing land, forest,
or various mixes of these). National maps of most of these
characteristics are available in USDI-Geological Survey (1970), but,
often, larger-scale State maps can be obtained from State agencies or
university departments.
3. Examine maps of the selected environmental characteristics for classes
of characteristics that occur in regional patterns. When original maps
differ in scale or when finer resolution is required, a mechanical
enlarger/reducer, photocopy machine, photo-enlarger, or slide projector
can be used to produce maps of the desired scale. Select those classes
of characteristics that best represent tentative ecological regions.
For example, is the predominant class of land-surface form flat plains
or high hills; is the predominant potential natural vegetation oak
forest or ash forest? List the predominant class of all the
characteristics considered for each tentative ecological region.
4. Overlay the selected environmental characteristics mapped at the same
scale and outline the most-typical areas in each tentative ecological
region. The maps are examined in combination on a light table and lines
are drawn on a sheet of clear plastic or transparent paper (e.g.
albanene). Most-typical areas are those areas in each tentative
ecological region where all the predominant classes of environmental
characteristics in that region are present. These can be considered as
most-typical areas because they contain all the classes of
characteristics that will be used to determine that ecological region.
For example, if the predominant classes of land use, potential natural
vegetation, and land-surface form in an ecological region are cropland,
grassland, and plains, respectively, only the portion of that region
where cropland, grassland, and plains all occur together would be
most-typical. This overlay approach and some of the environmental
characteristics are similar to those used by McHarg (1969) in his
examination of the values of various land uses in the Potomac River
Basin.
5. Determine which environmental characteristics best distinguish between
regions. Where the major characteristics abruptly differ at the same
place (e.g. hilly forestlands vs. prairie croplands) this is easily
done, but where there are gradual transitions (e.g. from flat to smooth
and irregular plains with decreasing amounts of croplands and increasing
forestlands) it is more difficult and the boundries are less precise.
At one boundary the distinguising characteristic may be land-surface
form and surficial geology, at another it may be land use or a river
IV-6-5
-------
basin divide. Thus, this boundary determination is a subjective - not a
mechanical or McHargian - process and it requires considerable judgment
and knowledge of the key environmental characteristics along the
tentative boundary. See Figure IV-7-1 for an example of a final
product. Fianlly, the regional lines are transferred to a base map of
the area of interest. On a State level, most of this work should be
done using map scales of 1:500,000 to 1:7,BOO,000. The base map should
then be circulated among knowledgeable professionals to evaluate the
significance of the ecological regions as drawn.
For cases where top-priority aquatic ecosystems are anomalies, or where
the State is interested in only a few sites, it may be more appropriate to
use a slightly different approach based only on the watershed
characteristics of the sites in question. For such cases, rather than
analyze the entire State, researchers can determine the climate,
land-surface form, soils, potential natural vegetation, land use, river
basin, etc. of the watershed upstream of the site of interest. The same
classes of characteristics elsewhere in the State or neighboring States can
then be determined from maps. The rest of the regional ization process is
the same as described above. The major difference in this approach is
that, because of the spatially-narrower objective, fewer ecological regions
will be determined, consequently, the product would have only local
application.
Determining Candidate References Reaches
The most-typical areas are considered the most-logical places to
locate reference reaches for several reasons: (1) Such areas should
contain a narrower range of land use or disturbance potentials compared to
the entire region or other regions. Hence, there should be a narrower
range of aquatic ecosystem conditions in these most-typical areas compared
to the entire region or other regions. (2) Such areas are more likely to
be free of major anomalies that might produce undisturbed sites that are
also atypical, such as an entirely forested, mountainous watershed in a
region typified by shruhlands and plains. (3) Such areas can potentially
represent the greatest number of streams in the ecological region because
they drain watersheds having all the predominant classes of environmental
characteristics that were used to identify the region. (4) Such areas best
represent the prevailing land use of the ecological region and the best
background conditions likely. For example, there is little likelihood of
transforming an area dominated by rangeland into forestland, therefore, the
predominant land use in the watershed of a reference reach in such an area
should be grazing.
For the above reasons, if watersheds of reference or benchmark reaches
are to have the broadest possible applicability, they should fall entirely
within the most-typical areas of ecological regions. Thus, the size of the
most-typical area will determine the maximum size of such watersheds. The
smallest watersheds should include the smallest intermittent or permanent
streams and ponds that support spawning or rearing or valued populations.
Valued populations may include sport,, commercial, rare, threatened,
endangered, forage, or intolerant species of any phylum.
IV-6-6
-------
Refining the Number of Candidate Reference Reaches
Regardless of how candidates for reference watersheds are determined
there are several important aspects to consider when selecting reference
reaches:
1. Human Disturbances. Obviously, watersheds that contain dense human
populations, concentrations of mines or industry, several or important
point sources, or major and atypical problems with diffuse pollution
(e.g. acidification, soil erosion, overgrazing, mine wastes, landslides)
should be eliminated from consideration as reference watersheds.
Intentional stocking of sport fishes and incidental releases of aquarium
and bait organisms have extended the ranges of many aquatic species. If
these introductions are only local, knowledge of such populations should
he considered when selecting least-disturbed watersheds because
introduced stocks of species are one of the most detrimental changes
that humans initiate in aquatic ecosystems. Where human disturbances
are mapped this step should be done for the entire State.
2. Size: Because of the gradual change in many stream characteristics from
headwaters to rivers (Vannote et al. 1980), plus application of
MacArthur and Wilson's (1967) theory of island biogeography to lakes
(Barbour and Brown 1974), it is important to consider the size of the
reference reaches when they are to be compared with a priority water
body. Although stream order (Strahler 1957) has often been used by
biologists to approximate stream size, Hughes and Omernik (1981a, 1983)
give several reasons why watershed area and mean annual discharge are
preferable measures. Limnologists typically use surface area and volume
to estimate lake size. Although regional differences make any
generalizations difficult, the stream order of priority and reference
reaches should not differ by more than one order in most cases and the
watershed areas usually should differ by less than one order of
magnitude.
3. Surface water hydrology. While determining size, the researcher should
also briefly examine the types of the watersheds, streams, or lakes for
anomalies. Large scale topographic maps will usually reveal whether the
streams are effluent or influent, i.e., whether the net movement of
water if from the streams to the ground water or the reverse. The same
maps reveal drainage lakes, lake type (kettle, solution, oxbow, etc.),
amount of ditching or canalization, and drainage pattern (dendritic,
trellis, aimless, etc.).
4. Refugia. Parks, monuments, wildlife refuges, natural areas, preserves,
state and federal forests, and woodlots are often indicated on large
scale topographic maps and locations of others can be obtained from
state agencies charged with their administration. Such refugia are
often excellent places to locate reference sites and reference
watersheds.
IV-6-7
-------
5. Groundwater hydrology. Reports from the State water resource agency and
the State office of the U.S. Geological Survey reveal whether lakes are
influent or effluent. The direction of water movement in lakes is
extremely important in determining their nutrient balance, causes of
eutrophication, and possible results of lake restoration efforts. For
example, in shallow effluent lakes with small watersheds the major
source of nutrients is the atmosphere and hence uncontrollable.
6. Runoff per unit area. This is extremely important in estimating stream
size. The summarized runoff data are published in U.S. Geological
Survey reports for each State. These data can be used to estimate
isolines of runoff per unit area or existing runoff maps produced by
State water resource agencies can be used. For a national example, see
USDI - Geological Survey (1970).
7. Water chemistry. These data can be used to estimate background or
typical conditions. Most are not summarized, but they can be located
using NAWDEX and are available from computerized data bases such as
WATSTORE and STORET and from State water reports of the U.S. Geological
Survey and State water resource agencies.
8. Geoclimatic history. The historical geomorphology and climate determine
the basin divides and historical connections among water bodies and
basins. The absence of such connections and the locations of basin
divides and major gradient changes determine centers of origin or
endemism. Regionally, continental glaciation, ocean subsidence, and
pluvial flooding, and locally, stream capture, canals, and headwater
flooding all provided passages across apparent barriers that allowed
range extension, and, in large part, determine the present ranges of
primary freshwater fish and mollusks. This information is usually
available from university geology departments and often from the state
geologist.
9. Known zoogeographic patterns. These are best revealed by maps in books
and articles on the biota of the state, e.g. Smith (1983), Trautman
(1981), or Pflieger (1975). Such patterns may also be predicted by
present river basins where the basin divides are substantial and the
river mouths distant.
After considering the broad watershed and regional aspects of the
candidate watersheds, the highly-degraded or unusual watersheds should be
easily rejected. Candidate reaches can then be selected and ranked or
clustered by expected level of disturbance. At this level of resolution,
the researcher should study air photo mosaics and large-scale (1:24,000-
1:250,000) maps of the candidate reaches. Stream gradient, distance from
other refugia, barriers (falls, dams) between reference reaches and other
refugia, distance from the major receiving water, number of mines, and
buildings, amount of channelization, and presence of established monitoring
or gaging sites should all be considered. The list of candidate reaches
should be distributed to other professionals to query them about their
knowledge of disturbance levels, previous or concurrent studies, fish
stocking schedules, fish catch per unit effort, spawning or hatching
pulses, valued species, etc.
IV-6-8
-------
Selecting Actual Reference Sites
All the preceding research can, and should, be done in an office. It
is then useful to view and photograph the reduced number of candidate
reaches from the air. A small wing-over airplane flying 300-1500 meters
above the ground is ideal for this or recent stereo pairs of air photos can
suffice. The candidate reach should be examined at several access points
to assess typical and least-disturbed conditions, i.e., the absence of farm
yards, feed lots, livestock grazing, irrigation diversions, row crops,
channelization, mines, housing developments, clearcuts, or other small
scale disturbances should be rejected, though the candidate reaches may be
moved upstream of them. The main reasons for this aerial view are to
determine what the candidate watersheds and reaches typically look like, to
characterize relatively undisturbed conditions, and to help select actual
reference sites. The photographs are also useful as visual aids in
briefings and public meetings. This phase is not essential if the chief
state ecologist has developed this knowledge of present conditions through
years of experience statewide.
Finally, the remaining candidate reaches can be assessed and ranked
for disturbance from the ground. Three to four candidate reference sites
in each reach should be examined for typical natural features, least-
disturbed channel and riparian characteristics, and ease of access. The
concept of typicalness of natural features is similar to that of
typicalness of watershed features; for example, riffle-pool morphology and
swift current would not be typical of coastal plain or swamp streams and
such anomolous sites should not be included as reference sites.
One of the best indicators of least-disturbed sites is extensive,
old, riparian forest (see Section II-6). Another is relatively-high
heterogeneity in channel width and depth (shallow riffles, deep pools,
runs, secondary channels, flooded backwaters, sand bars, etc.). Abundant
large woody debris (snags, root wads, log jams, brush piles), coarse bottom
substrate (gravel, cobble, boulders), overhanging vegetation, undercut
banks, and aquatic vascular macrophytes and additional substrate
heterogeneity and concealment for biota. Relatively high discharges;
clear, colorless, and odorless waters; visually-abundant diatom, insect,
and fish assemblages; and the presence of beavers and piscivorous birds
also indicate relatively-undisturbed sites.
In order to confidently ascertain whether a designated biotic use of
a priority aquatic ecosystem is attainable it is necessary to (1) clearly
define that use in objective, measurable, biotic conditions and (2) examine
those conditions in at least three least-disturbed reference sites. We
have described a process to locate and rank a number of least-disturbed
reference sites. However, there are several limitations to that approach.
To date this process has only been tested on streams with watersheds less
than 1600 km^. Major lakes and rivers can be examined in the same
manner, but a multistate or national analysis will be needed and greater
allowances for variability in the level of disturbance and the degree of
typicalness may be necessary because large ecosystems encompass more
variability, they are more likely to receive major point sources, and they
are rarer to begin with.
IV-6-9
-------
Where priority aquatic ecosystems are unique it will be more
difficult to find reference sites. For example, if the priority system is
a forested watershed with a high-gradient stream in Iowa, where such a
system is rare, it would be necessary to seek reference sites in
neighboring States. Where a stream passes through extremely dissimilar
ecological regions, reference streams should do likewise. For example, the
Yampa River of Northwestern Colorado passes from spruce-forested mountains
through sagebrush tablelands and should not be compared with a river that
flows through only one of those regions.
Stream reaches above barriers, such as the falls on the Cumberland
River or the relatively steep gradients of the Watauga River at the North
Carolina-Tennessee border, should not be compared with those below because
few purely aquatic species have passed those historical barriers. Streams
that had glacial or pluvial connections (such as the Susquehanna and James
Rivers) may have more species in common than neighboring rivers of either,
the neighboring rivers have similar environmental conditions. Gilbert
(1980) provides a clear discussion of these possible zoogeographic
anomalies using examples from the eastern United States. Decisions about
reference sites must also take such knowledge into consideration.
Finally, ecological regions and reference sites as described herein
are believed most useful for making comparisons between broad assemblage-
level patterns or patterns between widely-ranging and common species of
importance, not between the presence or absence of specific uncommon or
localized species viewed separately. That is, multivariate approaches such
as ordination and classification or biotic indices such as Karr's (1981)
are most applicable and researchers should not expect to discriminate among
sites that vary only slightly.
Summary
The final product of this approach is a map like that of Figure
IV-7-1. Data from the reference sites in each ecological region can be
compared with those from disturbed sites in that region. For aquatic
ecosystems that cross boundaries between ecological regions, state
ecologists ought to examine data from the reference sites in those
respective regions. Comparisons should he limited to ecosystems of similar
size.
Rather than an ad hoc, best - biological judgment approach, a
regionalization approach as described provides a rational, objective means
to compare similarities and differences over large areas. The regions
provide ecologically-meaningful management units and they would help in the
organization and interpretation of State water quality and NFS reports.
Data from the reference sites provide an objective, ecological basis to
refine use classifications and, when compared with more disturbed sites, to
evaluate the attainment of uses. Knowledge of potential conditions in a
region provides an objective, ecological basis to predict effects of land
use changes and pollution controls, to prioritize aquatic ecosystems for
improvements, and to set site-specific criteria. Regular monitoring of the
reference sites and comparisons with historical information will provide a
useful assessment of temporal changes, not only in those aquatic
ecosystems., but in the ecological regions that they model.
IV-6-10
-------
NORTHWEST FLAT PLAINS
WESTERN ROLLING PLAINS
NE and SW IRREGULAR
DISSECTED SOUTHEAST
Most Typical Areas
Generally Typical Areas
• Study Watersheds
IV-6-11
-------
0 SECTION V: INTERPRETATION
-------
CHAPTER V
INTERPRETATION
INTRODUCTION
There are many use classifications which might be assigned to a water body,
such as navigation, recreation, water supply or the protection of aquatic
life. These need not be mutually exclusive. The water body survey as discussed
in this manual is concerned only with aquatic life uses and the protection of
aquatic life in a water body.
The water body survey may also be referred to as a use attainability analysis.
The objectives in conducting a water body survey are to identify:
1. What aquatic protection uses are currently being achieved in the water
body,
2. What the causes are of any impairment to attaining the designated aqua-
tic protection uses, and
3. What the aquatic protection uses are that could be attained, based on
the physical, chemical and biological characteristics of the water body.
The types of analyses that might be employed to address these three points are
summarized in Table V-l. Most of these are discussed in detail elsewhere in
this manual.
CURRENT AQUATIC PROTECTION USES
The actual aquatic protection use of a water body is defined by the resident
biota. The prevailing chemical and physical attributes will determine what
biota may be present, but little need be known of these attributes to describe
current uses. The raw findings of a biological survey may be subjected to
various measurements and assessments, as discussed in Chapters IV-2, IV-4, and
IV-5. After performing a biological inventory, omnivore-carnivore analysis,
and intolerant species analysis, and calculating a diversity index and other
indices of biological health, one should be able adequately to describe the
condition of the aquatic life in the water body.
It will be helpful to digress at this juncture briefly to discuss water body
use classification systems and their relationship to the water body survey.
Classification systems vary widely from state to state. Some consist of as few
as three broad categories, while others include a number of more sharply-
defined categories. Also, the use classes may be based on geography, salinity,
recreation, navigation, water supply (municipal, agricultural, or industrial),
or aquatic life. Often an aquatic protection use must be categorized as either
V-l
-------
TABLE V-l. SUMMARY OF TYPICAL WATER BODY EVALUATIONS (from EPA,1983, Water Quality Standards Handbook).
PHYSICAL EVALUATIONS CHEMICAL EVALUATIONS BIOLOGICAL EVALUATIONS
• Instream Characteristics
- size (mean width/depth)
- flow/velocity
- total volume
- reaeration rates
- gradient/pools/rlffles
- temperature
- suspended sol Ids
- sedimentation
- channel modifications
- channel stability
0 Substrate composition and
characteristics
0 Channel debris
0 Sludge deposits
0 Riparian characteristics
0 Downstream characteristics
0 dissolved oxygen
0 toxicants
0 nutrients
- nitrogen
- phosphorus
0 sediment oxygen demand
0 salinity
0 hardness
0 alkalinity
0 PH
0 dissolved solids
0 Biological Inventory (Existing Use
Analysis)
- fish
- niacroinvertebrates
- microinvertebrates
- phytoplankton
- tnacrophytes
0 Biological Condition/Health Analysis
- Diversity Indices
- HSI Models
- Tissue Analyses
Recovery Index
- Intolerant Species Analysis
- Omnivore-Carnivore Analysis
0 Biological Potential Analysis
- Reference Reach Comparison
V-2
-------
a warmwater or coldwater fishery. Clearly, little information is required
to place a water body into one of these two categories. Far more
information may be gathered in a water body survey than is needed to
assign a classification, based on existing classes, but the additional
data may be necessary to evaluate management alternatives and refine use
classification systems for the protection of aquatic life in the water
body.
Since there may not be a spectrum of aquatic protection use categories
available against which to compare the findings of the biological survey;
and since the objective of the survey is to compare existing uses with
designated uses, and existing uses with potential uses, as seen in the
three points listed above, the investigators may need to develop their own
system of ranking the biological health of a water body (whether
qualitative or quantitative) in order to satisfy the intent of the water
body survey. Implicit to the water body survey is the development of
management strategies or alternatives which might result in enhancement of
the biological health of the water body. To do this it would be necessary
to distinguish the predicted results of one strategy from another, where
the strategies are defined in terms of aquatic life. The existing State
use classifications will probably not be helpful at this stage, for one
may very well be seeking to define use levels within an existing use
category, rather than describing a shift from one use classification to
another. To conclude, it may be helpful to develop an internal use
classification system to serve as a yardstick during the course of the
water body survey, which may later be referenced to the legally
constituted use categories of the state. Sample scales of aquatic life
classes are presented in Table V-? and V-3.
CAUSES OF IMPAIRMENT OF AQUATIC PROTECTION USES
If the biological evaluations indicate that the biological health of the
system is impaired relative to a "healthy" or least disturbed control
station or reference aquatic ecosystem (e.g., as determined by reference
reach comparisons), then the physical and chemical evaluations can be used
to pinpoint the causes of that impairment. Figure V-l shows some of the
physical and chemical parameters that may be affected by various causes of
change in a water body. The analysis of such parameters will help clarify
the magnitude of impairments to attaining other uses, and will also be
important to the third step in which potential uses are examined.
ATTAINABLE AQUATIC PROTECTION USES
The third element to be considered is the assessment of potential uses of
the water body. This assessment would be based on the findings of the
physical, chemical and biological information which has been gathered, but
additional study may also be necessary. Procedures which might be
particularly helpful in this stage include the Habitat Suitability Index
Models of the Fish and Wildlife Service, that may indicate which fish
species could potentially occupy a given habitat: and the Recovery Index
of Cairns et al. (1977) which estimates the ability of a system to
recover following stress. A reference reach comparison will be
particularly important. In addition to establishing a comparative
V-3
-------
TABLE V-2. BIOLOGICAL HEALTH CLASSES WHICH COULD BE USED
IN WATER BODY ASSESSMENT (Modified from Karr, 1981)
Class Attributes
Excellent Comparable to the best situations unaltered by man; all re-
gionally expected species for the habitat and stream size,
including the most intolerant forms, are present with full
array of age and sex clases; balanced trophic structure.
Good Fish and macroinvertebrate species richness somewhat less
than the best expected situation, especially due to loss of
most intolerant forms; some species with less than optimal
abundances or size distribution (fish); trophic structure
shows some signs of stress.
Fair Fewer intolerant forms of fish and macroinvertebrates are
present. Trophic structure of the fish community is more
skewed toward an increasing frequency of omnivores; older
age classes of top carnivores may be rare.
Poor Fish community is dominated by omnivores; pollution-toler-
ant forms and habitat generalists; few top carnivores;
growth rates and condition factors commonly depressed; hy-
brids and diseased fish may be present. Tolerant macroinver-
tebrates are often abundant.
Very Poor Few fish present, mostly introduced or very tolerant forms;
hybrids, common; disease, parasites, fin damage, and other
anomalies regular. Only tolerant forms of macroinverte-
brates are present.
Extremely Poor
No fish,
life.
very tolerant macroinvertebrates, or no aquatic
V-4
-------
Table V-3; Aquatic Life Survey Rating System (EPA, 1983 Draft)
A reach that is rated a five has:
-A fish community that is well balanced among the different levels
of the food chain.
-An age structure for the most species that is stable, neither
progressive (leading to an increase in population) or regressive
(leading to a decrease in population),
-A sensitive sport fish species or species of special concern always
present.
-Habitat which will support all fish species at every stage of their
life cycle.
-Individuals that are reaching their potential for growth.
-Fewer individuals of each species.
-All available niches filled.
A reach that is rated a four has:
-Many of the above characteristics but some of them are not
exhibited to the full potential. For example, the reach has a well
balanced fish community; the age structure is good, sensitive
species are present; but the fish are not up to their full growth
potential and may be present in higher numbers; an aspect of the
habitat is less than perfect (i.e. occasional high temperatures
that do not have an acute effect on the fish); and not all food
organisms are available or they are available in fewer numbers.
A reach that is a three has:
-A community is not well balanced, one or two tropic levels
dominate.
-The age structure for many species is not stable, exhibiting
regressive or progressive charisteristics.
-Total number of fish is high, but individuals are small.
-A sensitive species may be present, but is not flourishing.
-Other less sensitive species make up the majority of the biomass.
-Anadromous sport fish infrequently use these water as a migration
route.
A reach that is rated a two has;
-Few sensitive sport fish are present, nonsport fish species are
more common than sport fish species,
-Species are more common than abundant.
-Age structures may be very unstable for any species.
-The composition of the fish population and dominate species is very
changeble.
-Anadromous fish rarely use these waters as a migration route.
-A small percent of the reach provides sport fish habitat.
A reach that is a one has:
-The ability to support only nonsport fish. A occasional sport fish
may be found as a transient.
A reach that is rated a zero has:
-No ability to support a fish of any sort, an occasional fish may be
found as a transient.
V-5
-------
SOURCE OF MODIFICATION
pH
Alkal inity
Hardness
Chlorides
Sul fates
TDS
TKN
NH,-N
Total -P
Ortho-P
BOD.
COO
TOC
a- COD/BODg
}±| D.O.
•E Aromatic Compounds
§ Fluoride
S Cr
s Cu
2 Pb
£ In
1/1 Cd
Fe
Cyanide
Oil and Grease
Col i forms
Chlorophyll
Diversity
Biomass
Riparian Characteristics
Temperature
TSS
YSS
Color
Conductivity
Channel Characteristics
Acid Mine Drainage
or Acid Precipitation
Sewage Treatment Plant
Discharge (primary or
secondary)
D
D
I
I
I
I
I
I
I
I
I
I I
I
I
D
I
I
I
I
D I
D I
0 D
D I
I
Agricultural Runoff
(pasture or cropland)
Urban Runoff
Channelization
I
I I
I I
I
I
I I
I
I I
I
I
I
I
I
I
I I
I I
0 0
I I
C
I
I I I
I
c
(Industries) Pulp and
Paper
C
I
I
I
I
0
I
I
I
I
I
D
0
I
I
I
Textile
I
I
I
I
I
I
I
I
I
D
I
I
I
Metal Finishing and
Electroplating
C
I
I
I
I
I
I
I
I
I
I
D
D
0
D
I
u
3
73
0
L.
Q.
0) ^ fa
z
E -e 73
3 73 C C
(U c fa ra
i — fa
C *-> 5S
1- C C I_
4-> O •— "-
cj ^« TO fa
o_ >— o. a
0 C
I
I I
I I
I I I
I I
I
I I I I
I I I
I I I I
D I
D
I
I I
I
I I I
I I I
I
I I
I
I I I I
0 0 I
0 D D I
ODD
0001
I
I I
'Fertilizer Production
and Lime Crushing
Plastics and Synthetic
0,1 C
0,1
I
I I
I
I I
I I
I
I
I
I
I
I
I I
I
I
I
I
I I
I
I
I , ; D
0
I 0
I I
I
-I
Figure Y-l. Potential Effects of Some Sources of Alteration on Stream Parameters;
D - decrease, I = increase, C = change.
V-6
-------
baseline community, defining a reference reach can also provide insight to the
aquatic life that could potentially occur if the sources of impairment were
mitigated.
The analysis of all information that has been assembled may lead to the defini-
tion of alternative strategies for the management of the water body at hand.
Each such strategy corresponds to a unique level of protection of aquatic
life, or aquatic life protection use. If it is determined that an array of
uses are attainable, further analysis which is beyond the scope of the water
body survey would be required to select a management program for the water
body.
A number of factors which contribute to the health of the aquatic life will
have been evaluated during the course of the water body survey. These may be
divided into two groups: those which can be controlled or manipulated, and
those which cannot. The factors which cannot be regulated may be attributable
to natural phenemona or may be attributable to irrevocable anthropogenic
(cultural) activities. The potential for enhancing the aquatic life of a
water body essentially lies in those factors over which some control may be
exerted.
Whether or not a factor can be controlled may itself be a subject of contro-
versy for there may be a number of economic judgments or institutional consid-
erations which are implicit to a definition of control. For example, there are
many cases in the West where a wastewater discharge may be the only flow to
what would otherwise be an intermittent stream. If water rights have been es-
tablished for that discharge then the discharge cannot be diverted elsewhere,
applied to the land for example, in order to reduce the pollutant load to the
stream. If a stream does not support an anadromous fishery because of dams and
diversions which have been built for water supply and recreational purposes,
it is unlikely that a concensus could be reached to restore the fishery by re-
moving the physical barriers - the dams - which impede the migration of fish.
However, it may be practical to build fish ladders and by-passes to allow
upstream and downstream migration. In a practical sense these dams represent
anthropogenic activity which cannot be reversed. A third example might be a
situation in which dredging to remove toxic sediments in a river may pose a
much greater threat to aquatic life than to do nothing. In doing nothing the
toxics may remain in the sediment in a biologically-unavailable form, whereas
dredging might resuspend the toxic fraction, making it biologically available
and also facilitating wider distribution in the water body.
The points touched upon above are presented to suggest some of the phenomena
which may be of importance in a water body survey, and to suggest the need to
recognize whether or not they may realistically be manipulated. Those which
cannot be manipulated essentially define the limits of the highest potential
use that might be realized in the water body. Those that can be manipulated
define the levels of improvement that are attainable, ranging from the current
aquatic life uses to those that are possible within the limitations imposed by
factors that cannot be manipulated.
V-7
-------
SECTION VI: REFERENCES
-------
CHAPTER VI
REFERENCES
CHAPTER II-l: FLOW ASSESSMENTS
Bovee, K., 1982. A Guide to Stream Habitat Analysis Using the Instream Flow
Incremental Methodology, FWS/OBS-82/26. U.S. Fish and Wildlife Service, Fort
Collins, CO.
Hilgert, P., 1982. Evaluation of Instream Flow Methodologies for Fisheries in
Nebraska. Nebraska Game & Park Commission Technical Bulletin No. 10, Lincoln,
NB.
Tennant, D.L., 1976. Instream Flow Regimens for Fish, Wildlife, Recreation and
Related Environmental Resources, pp. 359-373. In J.F. Osborn, and C.H. Allman,
eds. Proceedings of the Symposium and Specialty Conference in Instream Flow
Needs. Vol. II, American Fisheries Society, Bethesda, MD.
CHAPTER II-2: SUSPENDED SOLIDS AND SEDIMENTATION
Atchinson, G.J., and B.W. Menzel, 1979. Sensitivity of Warmwater Fish
Populations to Suspended Solids and Sediments. In Muncey, R.J. et al. "Effects
of Suspended Solids and Sediment on Reproduction and Early Life of Warmwater
Fishes." U.S. EPA, Corvallis, OR, EPA/600/3-79-049.
Benson, N.G., and B.C. Cowell, 1967. The Environmental and Plankton Diversity
in Missouri River Reservoirs, pp. 358-373. In Reservoir Fishery Resources
Symposium. Reservoir Comm., Southern Div., Am. Fish. Soc., Bethesda, MD.
Butler, J.L., 1963. Temperature Relations in Shallow Turbid Ponds. Proc. Okla.
Acad. Sci. 43:90.
Cairns, J. Jr., 1968. Suspended Solids Standards for the Protection of Aquatic
Organisms. Eng. Bull. Purdue University 129:16.
Chew, R.L., 1969. Investigation of Early Life History of Largemouth Bass in
Florida. Florida Game and Fish Comm. Proj. Rept. F-024-R-02. Tallahassee, FL.
Ellis, M.M., 1969. Erosion Salt as a Factor in Aquatic Environments. Ecology
17:29.
European Inland Fisheries Advisory Committee, 1964. Water Quality Critria for
European Freshwater Fish: Report on Finely Divided Solids and Inland
Fisheries. EIFAC Tech. Paper(l) 21 pp.
Iwamoto, R.N., E.O. Salo, M.A. Madeq, R.L. Comas and R. Rulifson, 1978.
Sediment and Water Quality: A Review of the Literature Including a Suggested
Approach for Water Quality Criteria With Summary of Workshop and Conclusions.
EPA 910/9-78-048.
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Swingle, H.S., 1956. Appraisal of Methods of Fish Population Study Part IV:
Determination of Balance in Farm Fish Ponds. Trans. N. Am. Wild. Conf. 21:298.
Trautman, M.G., 1957. The Fishes of Ohio. Ohio State Univ. Press, Columbus.
683 pp.
U.S. EPA. 1976. Quality Criteria for Water. U.S. EPA, Washington, D.C. U.S.
Government Printing Office, 055-001-01099.
CHAPTER II-3: POOLS, RIFFLES AND SUBSTRATE COMPOSITION
Edwards, E.A., et al., 1982. Habitat Suitability Index Models: Black Crappie.
U.S. Fish and Wildlife Service, Ft. Collins, CO. FWS/OBS-82/10.6.
Edwards, E.A., et al., 1982. Habitat Suitability Index Models: White Crappie.
U.S. Fish and Wildlife Service, Ft. Collins, CO. FWS/OBS-82/10.7.
Hickman, T. and R.F. Raleigh, 1982. Habitat Suitability Index Models:
Cutthroat Trout. U.S. Fish and Wildlife Service, Ft. Collins, CO.
FWS/OBS-82/10.5.
Hynes, H.B.N., 1970. The Ecology of Running Waters. University of Toronto
Press, Toronto.
Lagler, Karl F., et al., 1977. Ichthyology. John Wiley & Sons, NY. 506 pp.
La Gorce, J. (editor), 1939. The Book of Fishes. National Geographic Society,
Washington, D.C. 367 pp.
McMahon, T.E., 1982. Habitat Suitability Index Models: Creek Chub. U.S. Fish
and Wildlife Service, Ft. Collins, CO. FWS/OBS-82/10.4.
McMahon, T.E. and J.W. Terrell, 1982. Habitat Suitability Index Models:
Channel Catfish. U.S. Fish and Wildlife Service, Ft. Collins, CO.
FWS/OBS-82/10.2.
Migdalski, Edward C. and G.S. Fichter, 1976. The Fresh and Salt Water Fishes
of the World. Alfred A. Knopf, NY. 316 pp.
Odum, E.P., 1971. Fundamentals of Ecology. W.B. Saunders Co. 574 pp.
Stalnaker, C.B. and J.L. Annette (editor), 1976. Methodologies for the
Determination of Stream Resource Flow Requirements: An Assessment. U.S.
Fish and Wildlife Service, FWS/OBS-76/03.
Stuber, Robert J., et al., 1982. Habitat Suitability Index Models: Bluegill.
U.S. Fish and Wildlife Service, Ft. Collins, CO. FWS/ OBS-82/10.8.
Whitton, B.A., (editor), 1975. River Ecology. University of California Press.
724 pp.
VI-2
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CHAPTER II-4: CHANNEL CHARACTERISTICS AND EFFECTS OF CHANNELIZATION
Arner, D.H., et al. 1976. Effects of Channelization on the Luxapalila River on
Fish, Aquatic Invertebrates, Water Quality, and Furbearers. U.S. Fish and
Wildlife Service, Washington, D.C. FWS/OBS-76/08.
Barclay, J.S., 1980. Impact of Stream Alterations on Riparian Communities in
Southcentral Oklahoma. U.S. Fish and Wildlife Service, Albuquerque, NM.
FWS/OBS-80/17.
Brown, S., et al., 1979. Structure and Function of Riparian Wetlands. In
Strategies for Protection and Management of Floodplain Wetlands and Other
Riparian Ecosystems, Johnson, R.R., and McCormick, J.F. (editors), U.S. Dept.
of Agriculture, Washington, D.C., Tech. Rept. WO-12, pp. 17-32.
Bulkley, R.V., 1975. A Study of the Effects of Stream Channelization and Bank
Stabilization on Warm Water Sport Fish in Iowa: Subproject No. 1. Inventory of
Major Stream Alterations in Iowa. U.S. Fish and Wildlife Service, Washington,
D.C. FWS/OBS-76/11.
Bulkley, R.V., et al. 1976. Warmwater Stream Alteration in Iowa: Extent,
Effects on Habitat, Fish, and Fish Food, and Evaluation of Stream Improvement
Structures (Summary Report). U.S. Fish and Wildlife Service, Washington, D.C.,
FWS/OBS-76/16.
Cairns, J., Jr., et al., 1976. The Recovery of Damaged Streams. Assoc. SE
Biol. Bull., 13:79.
Chow, V.T., 1959. Open Channel Hydraulics. McGraw-Hill Book Co., NY. 680 pp.
Chutter, F.M., 1969. The Effects of Silt and Sand on the Invertebrate Fauna of
Streams and Rivers. Hydrobiologia, 34:57.
Cummins, K.W., 1973. Trophic Relations of Aquatic Insects. Ann. Rev. Entomol.,
18:183.
Cummins, K.W., 1974. Structure and Function of Stream Ecosystems. Bioscience,
24:631.
Cummins, K.W., 1975. Ecology of Running Waters: Theory and Practice. In Proc.
Sandusky River Basin Symposium, in Baker, D.B., et al., (editors) Heidelburg
College, Tiffin, OH.
Cummins, K.W., and G.H. Lauff, 1969. The Influence of Substrate Particle Size
on the Microdistribution of Stream Macrobenthos. Hydrobiologia, 34:145.
Etnier, D.A., 1972. Effect of Annual Rechanneling on Stream Population. Trans.
Amer. Fish. Soc., 101:372.
Frederickson, L.H., 1979. Floral and Faunal Changes in Lowland Hardwood
Forests in Missouri Resulting from Channelization, Drainage, and Impoundment.
U.S. Fish and Wildlife Service, Washington, D.C. FWS/OBS-78/91.
VI-3
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Gammon, J.R., 1979. The Effects of Inorganic Sediment on Stream Biota. Water
Poll. Con. Res. Series, 108050 DWC 12/70, U.S. EPA, Washington, D.C.
Gorman, O.T., and Karr, J.R., 1978. Habitat Structure and Stream Fish
Communities. Ecology, 59:507.
Griswold, B.L., et al., 1978. Some Effects of Stream Channelization on Fish
Populations, Macroinvertebrates, and Fishing in Ohio and Indiana. U.S. Fish
and Wildlife Service, Columbia, MO, FWS/OBS-77/46.
Huggins, D.G., and R.E. Moss, 1975. Fish Population Structure in Altered and
Unaltered Areas of a Small Kansas USA Stream. Trans. Kansas Acad. Sci., 77:18.
Huish, M.T., and G.B. Pardue, 1978. Ecological Studies of One Channelized and
Two Unchannelized Swamp Streams in North Carolina. U.S. Fish and Wildlife
Service, Washington, D.C. FWS/OBS-78/85.
Hynes, H.B.N., 1970. The Ecology of Running Waters. Univ. of Toronto Press,
Toronto, 555 pp.
Karr, J.R., and I.J. Schlosser, 1977. Impact of Nearstream Vegetation and
Stream Morphology in Water Quality and Stream Biota. U.S. EPA, Athens, GA,
Ecol. Res. Series, EPA-600/3-77-097.
King, D.L., and R.C. Ball, 1967. Comparative Energetics of a Polluted Stream.
Limnol. Oceanog., 12:27.
King, L.R., 1973. Comparison of the Distribution of Minnows and Darters
Collected in 1947 and 1972 in Boone County, Iowa. Proc. Iowa Acad. Sci., 80:
133.
King, L.R., and K.D. Carlander, 1976. A Study of the Effects of Stream
Channelization and Bank Stabilization on Warmwater Sport Fish in Iowa:
Subproject No. 3. Some Effects of Short-Reach Channelization on Fishes and
Fish Food Organisms in Central Iowa Warmwater Streams. U.S. Fish and Wildlife
Service, Washington, D.C. FWS/OBS-76/13.
Lavandier, R., and Caplancef, J., 1975. Effects of Variations in Dissolved
Oxygen on the Benthic Invertebrates of a Stream in the Pyreenees. Ann. Limnol.
11.
Leopold, L.B., et al., 1964. Fluvial Processes in Geomorphology. W.H. Freeman
and Co., San Francisco, CA.
Leopold, L.B., and W.B.' Langbein, 1966. River Meanders. Scientific American
214:60.
Lund, J., 1976. Evaluation of Stream Channelization and Mitigation of the
Fishery Resources of the St. Regis River, Montana. U.S. Fish and Wildlife
Service, Washington, D.C. FWS/OBS-76-07.
Maki, T.E., et al., 1980. Effects of Stream Channelization on Bottomland and
Swamp Forest Ecosystems. Univ. of North Carolina, Chapel Hill, NC,
UNC-WRRI-80-147.
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Marzolf, G.R., 1978. The Potential Effects of Clearing and Snagging on Stream
Ecosystems. U.S. Fish and Wildlife Service, Washington, D.C. FWS/OBS-78-14.
Meehan, W.R., 1971. Effects of Gravel Cleaning on Bottom Organisms in the
Southern Alaska Streams. Prog. Fish-Cult., 33:107.
Minshall, G.W., and P.V. Winger, 1968. The Effect of Reduction in Stream Flow
on Invertebrate Drift. Ecology, 49:580.
Minshall, J.W. and J.N. Minshall, 1977. Microdistribution of Benthic
Invertebrates in a Rocky Mountain Stream. Hydrobiologia, 53:231.
Montalbano, F., et al., 1979. The Kissimmee River Channelization: A
Preliminary Evaluation of Fish and Wildlife Mitigation Measures. In Proc. of
the Mitigation Symp., Colorado State Univ., Ft. Collins, CO, pp. 508-515.
Morris, L.A., et al., 1968. Effects of Main Stream Impoundments and
Channelization Upon the Limnology of the Missouri River, Nebraska. Trans.
Amer. Fish. Soc., 97:380.
Nebeker, A.V., 1971. Effect of Temperature at Different Altitudes on the
Emergence of Aquatic Insects from a Single Stream. Jour. Kansas. Entomol.
Soc., 44:26.
O'Rear, C.W., Jr., 1975. The Effects of Stream Channelization on the
Distribution of Nutrients and Metals. East Carolina Univ., Greenville, NC,
UNC-WRRI-75-108.
Parrish, J.D., et al., 1978. Stream Channel Modification in Hawaii. Part D:
Summary Report. U.S. Fish and Wildlife Service, Columbia, MO FWS/OBS-78/19.
Pfleiger, W.L., 1975. The Fishes of Missouri. Missouri Dept. Conserv.,
Jefferson City, MO.
Possardt, E.E., et al., 1976. Channelization Assessment, White River, Vermont:
Remote Sensing, Benthos, and Wildlife. U.S. Fish and Wildlife Service,
Washington, D.C. FWS/OBS-76/07.
Schmal, R.N., and D.F. Sanders, 1978. Effects of Stream Channelization on
Aquatic Macroinvertebrates, Buena Vista Marsh, Portage County, WI. U.S. Fish
and Wildlife Service, Washington, D.C. FWS/OBS-78/92.
Simpson, P.W., et al., 1982. Manual of Stream Channelization Impacts on Fish
and Wildlife. U.S. Fish and Wildlife Service, Kearneysville, WV FWS/OBS-82/24.
Swenson, W.A., et al., 1976. Effects of Red Clay Turbidity on the Aquatic
Environment. In Best Management Practices for Non-Point Source Pollution
Control Seminar, U.S. EPA, Chicago, IL, EPA 905/9-76-005.
Tebo, L.B., 1955. Effects of Siltation, Resulting from Improper Logging, on
the Bottom Fauna of a Small Trout Stream in the Southern Appalachians. Prog.
Fish-Cult. 17:64.
VI-5
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Vannote, et al., 1980. The River Continuum Concept. Can. Jour. Fish. Aquat.
Sci., 37:130.
Wallen, E.I., 1951. The Direct Effect of Turbidity on Fishes. Oklahoma A&M,
Stillwater, OK, Biol. Series No. 2, 48:1.
Walton, O.E., Jr., 1977. The Effects of Density, Sediment Size, and Velocity
on Drift of Acroneuria abnormis (Plecoptera). OIKOS, 28:291.
Wharton, C.H., and M.M. Brinson, 1977. Characteristics of Southeastern River
Systems. In Stategies for Protection and Management of Floodplain Wetlands and
Other Riparian Ecosystems, Johnson, R.R. and J.F. McCormick (editors),
U.S.D.A., Washington, D.C., Tech. Report WO-12, pp. 32-40.
Whitaker, G.A., et al., 1979. Channel Modification and Macroinvertebrate
Diversity in Small Streams. Wat Res. Bull., 15:874.
Williams, D.C., and J.H. Muncie, 1978. Substrate Size Selection by Stream
Invertebrates and the Influence of Sand, Limnol. Oceanog. 73:1030.
Winger, P.V., et al., 1976. Evaluation Study of Channelization and Mitigation
Structures in Crow Creek, Franklin County, Tennessee and Jackson County,
Alabama. U.S. Soil Conservation Service, Nashville, TN.
Wolf, J., et al., 1972. Comparison of Benthic Organisms in Semi-Natural and
Channelized Portions of the Missouri River. Proc. S.D. Acad. Sci., 51:160.
Yang, C.T., 1972. Unit Stream Power and Sediment Transport. A.S.C.E., Jour.
Hydraulics Div., 98:1805.
Zimmer, D.W., 1977. Observations of Invertebrate Drift in the Skunk River,
Iowa. Proc. Iowa Acad. Sci., 82:175.
Zimmer, D.W., and R.W. Bachman, 1976. A Study of the Effects of Stream
Channelization and Bank Stabilization on Warmwater Sport Fish in Iowa:
Subproject No. 4. The Effects of Long Reach Channelization on Habitat and
Invertebrate Drift in Some Iowa Streams. U.S. Fish and Wildlife Service,
Washington, D.C. FWS/OBS-76/14.
Zimmer, D.W., and R.W. Bachman, 1978. Channelization and Invertebrate Drift in
Some Iowa Streams. Water Res. Bull. 14:868.
CHAPTER II-5: TEMPERATURE
Brungs, W.A. and Jones, B.R., 1977. Temperature Criteria for Freshwater Fish:
Protocol and Procedures, U.S. EPA, Duluth, EPA-600/ 3-77-061.
Butler, J.N., 1964. Ionic Equilibrium, A Mathematical Approach, Addison-
Wesley, Reading, MA.
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Cherry, D. and Cairns, C., 1982. Biological Monitoring, Part V - Preference
and Avoidance Studies, Water Research, 16:263.
Hokanson, K., 1977. Temperature Requirements of Some Percids and Adaptations
to the Seasonal Temperature Cycle, J. Fish. Res. Board Can., 34:1524-1550.
Karr, J.R. and Schlosser, 1978. I.J., Water Resources and the Land Water Inter-
face, Science 201: 229-234.
Klein, L., 1962. River Pollution, II. Causes and Effects, Butterworths, London.
Machenthun, K.M., 1969. The Practice of Water Pollution Biology, U.S. DOI,
Federal Water Pollution Control Agency, U.S.G.P.O., Washington, DC.
Metcalf and Eddy, Inc., 1972. Wastewater Engineering, McGraw-Hill.
Morrow, J.E., 1980. The Freshwater Fishes of Alaska, Alaska Northwest
Publishing Company, Anchorage.
Scott, W., and Grossman, E., 1973. Freshwater Fishes of Canada, Fish. Res.
Board Can., Bulletin 184.
Stumm, W. and Morgan, 1970. J. Aquatic Chemistry, Wiley-Interscience, New York.
Warren, C.E., 1971. Biology and Water Pollution Control, W.B. Saunders
Company, Philadelphia.
CHAPTER 11-6: RIPARIAN EVALUATIONS
Behnke, A.C., et al., 1979. Biological Basis for Assessing Impacts of Channel
Modification: Invertebrate Production, Drift and Fish Feeding in Southeastern
Blackwater River. Environmental Resources Center, Rep. 06-79. Georgia Inst.
Techn., Atlanta.
Behnke, R.J., 1979. Values and Protection of Riparian Ecosystems. In The
Mitigation Symposium: A National Workshop on Mitigating Losses of Fish and
Wildlife Habitats. Gustav A. Sandon, Tech. Coordinator, U.S.D.A., Rocky Mt.
For. and Rng. Exp. Stn., Ogden, UT, Gen. Tech. Rept., RM-65 p. 164-167.
Bolen, E.G., 1982. Playas, Irrigation and Wildlife in West Texas.
Transactions, North American Wildlife Conference.
Brinson, M.M., B.L. Swift, R.C. Plantico and J.S. Barclay, 1981. Riparian
Ecosystems: Their Ecology and Status. U.S. Fish and Wildlife Service
FWS/OBS-81/17.
Campbell, C.J., 1970. Ecological Implication of Riparian Vegetation
Management. J. Soil Water Conserv. 25:49.
Crouse, M.R. and R.R. Kindschy, 1981. A Method for Predicting Riparian
Vegetation Potential. Presented at Symposium on Acquisition and Utilization of
Aquatic Habitat Inventory Information. Portland, OR.
VI-7
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Cowardin, L.M., et al., 1979. Classification of Wetlands and Deepwater
Habitats of the United States. U.S. Fish and Wildlife Service, Washington,
D.C. FWS/OBS-79/31.
Council of Environmental Quality. 1978. Our Nation's Wetlands. An Interagency
Task Force Report. U.S. Government Printing Office, Washington, D.C.
(041-011-000045-9).
Greeson, P.E., et al., editors, 1979. Wetland Function and Values: The State
of Our Understanding. American Water Resources Association, Minneapolis, MM.
Hawkins, C.P., M.L. Murphy and N.H. Anderson, 1982. Effects of Canopy,
Substrate Composition and Gradient on the Structure of Macroinvertebrate
Communities in Cascade Range Streams of Oregon. Ecology 63:1840.
Johnson, R.R. and D.A. Jones, 1977. Importance, Preservation and Management of
Riparian Habitat: A Symposium. U.S.D.A. For. Sen/., Gen. Tech. Rep. RM-43. Ft.
Collins, Co.
Johnson, R.R. and J.F. McCormik, 1978. Strategies for Protection and
Management of Floodplain Wetlands and Other Riparian Ecosystems. U.S.D.A. For.
Serv., Gen. Tech. Rep. WO-12, Washington, D.C.
Karr, J.R. and I.J. Schlosser, 1977. Impact of Vegetation and Stream
Morphology on Water Quality and Stream Biota. U.S. EPA Cincinnati, Ohio EPA/
3-77-097.
Karr, J.R. and I.J. Schlosser, 1978. Water Resources and the Land-Water
Interface. Science 201:229.
Lotspeich, F.B., 1980. Watershed as the Basic Ecosystem: This Conceptual
Framework Provides a Basis for a Natural Classification System. Water
Resources Bulletin, American Water Resources Association, 16(4):581.
Moring, J.R., 1975. Fisheries Research Report No. 9, Oregon Dept. of Fish and
Wildlife, Corvallis.
Mueller-Dombois, D. and H. Ellenberg, 1974. Aims and Methods of Vegetation
Ecology. John Wiley and Sons, NY.
Peterson, R.C. and K.W. Cummins, 1974. Leaf Processing in a Woodland Stream.
Freshwater Biology 4:343.
Platts, W.S., 1982. Livestock and Riparian-Fishery Interactions: What are the
Facts? Trans. No. Amer. Wildlife Conf. (47), Portland, OR.
Ross, S.T. and J.A. Baker, 1983. The Response of Fishes to Periodic Spring
Floods in a Southeastern Stream. The American Midland Naturalist 109:1.
Schlosser, I.J., 1982. Fish Community Structure and Function Along Two Habitat
Gradients in a Headwater Stream. Ecological Monographs 52:395.
VI-8
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Sedell, J., et al., 1975. The Processing of Conifer and Hardwood Leaves in Two
Coniferous Forest Streams. I. Weight Loss and Associated Invertebrates. Verh.
des. Inter. Vereins. Limn. 19:1617.
Sharpe, W.E., 1975. Timber Management Influences on Aquatic Ecosystems and
Recommendations for Future Research. Water Res. Bui. 11:546.
U.S. EPA, 1976. Forest Harvest, Residue Treatment, Reforestation and
Protection of Water Quality. U.S. EPA, Washington, D.C. EPA 910/9-76-020.
Van der Valk, A.G., C.B. Davis, J.L. Baker and C.F. Beer, 1980. Natural
Freshwater Wetlands as Nitrogen and Phosphorus Traps for Land Runoff p.
457-467. In Wetland Functions and Values: The State of Our Understanding, P.E.
Greeson, et al. (editors) Amer. Water Res. Asso. Minneapolis, MN.
CHAPTER III-l: WATER QUALITY INDICES
Brown, R.M., et al., 1970. "A Water Quality Index - Do We Dare?" Water and
Sewage Works, p. 339.
Dinius, S.H., 1972. "Social Accounting System for Evaluating Water Resources"
Water Resources Res. 8(5):1159.
Harkins, R.D., 1974. "An Objective Water Quality Index" Jour. Water Poll.
Cont. Fed. 46(3):588.
Kendall, M., 1975. Rank Correlation Methods, Charles Griffen and Co., London.
U.S. EPA, 1978. "Water Quality Indices: A Survey of Indices Used in the United
States," U.S. EPA, Washington, D.C., 600/4-78-005.
CHAPTER III-2: HARDNESS, ALKALINITY, pH AND SALINITY
Andrew, R.W., et al., 1977. Effects of Inorganic Complexing on the Toxicity of
Copper to Daphnia magna. Water Research, 11: 309.
Calamari, D. and Marchetti, R., 1975. Predicted and Observed Acute Toxicity of
Copper and Ammonia to Rainbow Trout (Salmo gairdneri Rich.). Progress in Water
Technology, 7: 569.
Calamari, D., et al., 1980. Influence of Water Hardness on Cadmium Toxicity to
Salmo gairdneri Rich. Water Research. 14: 1421.
Carroll, J.J., et al., 1979. Influences of Hardness Constituents on the Acute
Toxicity of Cadmium to Brook Trout (Salvelnus fontinalis). Bulletin of Environ-
mental Contamination and Toxicology-, 22: 575.
European Inland Fisheries Advisory Commission. 1969. Water Quality Criteria
for European Freshwater Fish - Extreme pH Values and Inland Fisheries. Water
Research, 3: 593.
VI-9
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Graham, M.S. and Wood, C.M., 1981. Toxicity of Environmental Acids to the
Rainbow Trout: Interactions of Water Hardness, Acid Type, and Exercise.
Canadian Journal of Zoology, 59: 1518.
Haines, T.A., 1981. Acid Precipitation and its Consequences for Aquatic
Ecosystems: A Review. Transactions of the-American Fisheries Society, 110:669.
Haranath, V.B., et al., 1978. Effect of Exposure to Altered pH Media on Tissue
Proteolysis and Nitrogenous End Products in a Freshwater Fish Tilapia
mossambica (Peters). Indian Journal of Experimental Biology, 16: 1088.
Hillaby, B.A., and Randall, D.J., 1979. Acute Ammonia Toxicity and Ammonia
Excretion in Rainbow Trout (Sal mo gairdneri). Journal of the Fisheries
Research Board of Canada 36:621.
Kinkade M.L., and Erdman, H.E., 1975. The Influence of Hardness Components
(Ca and Mg ) in Water on the Uptake and Concentration of Cadmium in a
Simulated Freshwater Ecosystem. Environmental Research, 10: 308.
Lloyd, R., 1965. Factors that Affect the Tolerance of Fish to Heavy Metal
Poisoning, In: Biological Problems in Water Pollution,, 3rd Seminar, U.S.
Department of Health Education and Welfare, pp. 181-187.
Maetz, J. and Bornancin M., 1975, referenced in Calamari, et al., 1980.
Mount, D.I.,1973. Chronic Effect of Low pH on Fathead Minnow Survival, Growth,
and Reproduction. Water Research, 7: 987.
Pagenkopf, G.K., et al., 1974. Effect of Complexation on Toxicity of Copper to
Fish. Journal of the Fisheries Research Board of Canada, 31: 462-465.
Peterson, R.H., et al.,1980. Inhibition of Atlantic Salmon Hatching at Low pH.
Canadian Journal of Fisheries and Aquatic Sciences, 37:370.
Reid, G.K., 1961. Ecology of Inland Waters and Estuaries, D. Van Nostrand
Company, New York.
Sawyer, C.N. and McCarty, P.L., 1978. Chemistry for Environmental Engineering,
McGraw-Hill Book Company, New York.
Shaw, T.L. and Brown, V.M., 1974. The Toxicity of Some Forms of Copper to
Rainbow Trout. Water Research, 8: 377-392.
Stiff, M.J., 1971. Copper/Bicarbonate Equilibria in Solutions of Bicarbonate
Ions at Concentrations Similar to those Found in Natural Waters. Water
Research, 5: 171-176.
Thurston, R.V., et al., 1974, referenced in U.S. EPA, 1976.
U.S. EPA, 1976. Quality Criteria for Water, U.S. EPA, Washington, D.C.
Warren, C.E. 1971. Biology and Water Pollution Control, W.B. Saunders Company,
Philadelphia, Pennsylvania.
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CHAPTER IV-1: HABITAT SUITABILITY INDICES
Inskip, P.O., 1982. Habitat Suitability Index Models: Northern pike, U.S. Fish
and Wildlife Service, Ft. Collins, CO, FWS/OBS-82/10.17.
McMahon, T.E. and J.W. Terrell, 1982. Habitat Suitability Index Models:
Channel Catfish. U.S. Fish and Wildlife Service, Ft. Collins, CO,
FWS/OBS-82/10.2.
Terrell, J.W., et al., 1982. Habitat Suitability Index Models: Appendix A.
Guidelines for Riverine and Lacustrine Applications of Fish HSI Models With
the Habitat Evaluation Procedures, U.S. Fish and Wildlife Service, Ft.
Collins, CO, FWS/OBS-82/10.A.
CHAPTER IV-2: DIVERSITY INDICES AND MEASURES OF COMMUNITY STRUCTURE
Beak, T.W., 1964. Biotic Index of Polluted Streams and Its Relationship to
Fisheries. Second International Conference on Water Pollution Research, Tokyo,
Japan.
Beck, W.M. Jr., 1955. Suggested Method for Reporting Biotic Data. Sewage Ind.
Wastes, 27:1193.
Bloom, S.A., et al., 1972. Animal-Sediment Relations and Community Analysis of
a Florida Estuary. Marine Biology, 13:43.
Boesch, D.F., 1957. Application of Numerical Classification in Ecological
Investigations of Water Pollution. EPA-600/3-77-033, U.S. EPA, Corvallis.
Bray, J.R. and Curtis, J.T., 1957. An Ordination of the Upland Forest
Communities of Southern Wisconsin. Ecological Monographs, 27:325.
Brillouin, L., 1960. Science and Information Theory. 2nd ed. Academic Press
Inc. NY.
Brock, D.A., 1977. Comparison of Community Similarity Indexes. Journal Water
Pollution Control Federation, 49:2488.
Buikema, A.L. Jr., 1980. Pollution Assessment: A Training Manual. UNESCO, U.S.
MAB Handbook No. 1. Washington, D.C.
Cairns, J. Jr., et al., 1968. The Sequential Comparison Index - A Simplified
Method for Non-Biologists to Estimate Relative Differences in Biological
Diversity in Stream Pollution Studies. Jour. Water Poll. Control Fed., 40:1607.
Cairns, J.R., Jr. and K.L. Dickson, 1969. Cluster Analysis of Potomac River
Survey Stations Based on Protozoan Presence-Absence Data. Hydrobiologia,
34:3-4, 414-432.
Cairns, J. Jr., et al., 1970. Occurrence and Distribution of Diatoms and Other
Algae in the Upper Potomac River. Notulae Naturae Acad. Nat. Sci.
Philadelphia, 436:1.
VI-11
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Cairns, J. Jr. and K.L. Dickson, 1971. A Simple Method for the Biological
Assessment of the Effects of Waste Discharges on Aquatic Bottom-Dwelling
Organisms. Jour. Water Poll. Control Fed., 43:755.
Cairns, J., Jr. and R.L. Kaesler, 1971. Cluster Analysis of Fish in a Portion
of the Upper Potomac River. Trans. American Fishery Society, 100:750.
Cairns, J. Jr., et al., 1973. Rapid Biological Monitoring Systems for
Determining Aquatic Community Structure in Receiving Systems. In Biological
Methods for the Assessment of Water Quality, (J. Cairns, Jr. and K.L. Dickson,
editors) American Society for Testing and Materials, STP 528, p. 148.
Cairns, J.R., Jr., 1977. Quantification of Biological Integrity. In The
Integrity of Water (R.K. Ballentine and L.J. Guarraia, editors) U.S.
Government Printing Office, Washington, D.C.
Chutter, P.M., 1972. An Empirical Biotic Index of the Quality of Water in
South African Streams and Rivers. Water Resources, 6:19.
Clifford, H.T. and W. Stephenson, 1975. An Introduction to Numerical
Classification. Academic Press, New York.
Czekanowski, J., 1913. Zarys Metod Statystycznych. Die Grundzuge der
Statischen Metoden, Warsaw.
Dixon, W.J. and F.J. Massey, Jr., 1969. Introduction to Statistical Analysis,
3rd ed. McGraw-Hill, NY.
Duncan, D.B., 1955. Multiple Range and Multiple F Tests, Biometrics, 11:1.
Fager, E.W., 1972. Diversity: A Sampling Study. Amer. Natur., 106:293.
Foerster, J.W., et al., 1974. Thermal Effects on the Connecticut River:
Phycology and Chemistry. Journal Water Pollution Control Federation, 46:2138.
Gammon, J.R., 1976. The Fish Populations of the Middle 340 km of the Wabash
River. Technical Report No. 86, Purdue University Water Resources Research
Center, West Lafayette, IN, pp. 1-48.
Gammon, J.R. and J.M. Reidy, 1981. The Role of Tributaries During an Episode
of Low Dissolved Oxygen in the Wabash River, IN. In AFS Warmwater Streams
Symposium. American Fish Society, Bethesda, MD.
Gammon, J.R., et al., 1981. Role of Electrofishing in Assessing Environmental
Quality of the Wabash River. In Ecological Assessments of Effluent Impacts on
Communities of Indigenous Aquatic Organisms (J.M. Bates and C.I Weber,
editors) Am. Soc. Testing and Materials, STP 730, Philadelphia, PA.
Gaufin, A.R., 1973. Use of Aquatic Invertebrates in the Assessment of Water
Quality. In Biological Methods for the Assessment -of Water Quality, (J.
Cairns, Jr, and K.L. Dickson, editors) Am. Soc. for Testing and Materials, STP
528, Philadelphia, PA.
VI-12
-------
Gleason, H.A., 1922. On the Relation Between Species and Area. Ecology, 3:158.
Godfrey, P.J., 1928. Diversity as a Measure of Benthic Macroinvertebrate
Community Response to Water Pollution. Hydrobiologia, 57:111.
Hartigan, J.A., 1975. Clustering Algorithms. Wiley-Interscience, NY.
Heck, K.L. Jr., 1976. Community Structure and the Effects of Pollution in
Sea-Grass Meadows and Adjacent Habitats. Marine Biology, 35:345.
Herricks, E.E. and J. Cairns Jr., 1982. Biological Monitoring. Part III:
Receiving System Methodology Based on Community Structure. Water Research,
16:141.
Hilsenhoff, W.L., 1977. Use of Arthropods to Evaluate Water Quality of
Streams. WI Dept. Nat. Resour. Tech. Bull. No. 100.
, 1982. Using a Biotic Index to Evaluate Water Quality in
Streams. WI Dept. Nat. Resour. Tech. Bull No. 132.
Horn, H.S., 1966. Measurement of "Overlap" in Compaative Ecological Studies.
American Naturalist, 100:419.
Howmiller, R.P. and M.A. Scott, 1977. An Environmental Index Based on Relative
Abundance of Oligochaete Species. Jour. Water Poll. Control Fed. 49:809.
Hughes, B.D., 1978, The Influence of Factors Other than Pollution on the Value
of Shannon's Diversity Index, for Benthic Macroinvertebrates in Streams, Water
Res., 92:359.
Hurlbert, S.H., 1971. The Nonconcept of Species Diversity: A Critique and
Alternative Parameters. Ecology, 52:577.
Hutcheson, K., 1970. A Test for Comparing Diversities Based on the Shannon
Formula. Jour. Theoret. Biol. 29:151.
Jaccard, P., 1912. The Distribution of Flora in an Alpine Zone. New Phytol.,
11:37.
Johnson, M.G. and R.O. Brinkhurst, 1971. Associations and Species Diversity in
Benthic Macroinvrtebrates of Bay of Quninte and Lake Ontario. Jour. Fish. Res.
Bd. Canada, 28:1683.
Kaesler, R.L., et al., 1971. Cluster Analysis of Non-Insect
Macro-Invertebrates of the Upper Potomac River. Hydrobiologia, 37:173.
, 1978. Use of Indices of Diversity and Hierarchical
Diversity in Stream Surveys. In Biological Data in Water Pollution Assessment;
Quantitative and Statistical Analyses (K.L. Dickson, et al., editors). Am.
Soc. Testing and Materials, STP 652, Philadelphia, PA.
Kaesler, R.L. and J. Cairns, Jr., 1972. Cluster Analysis of Data from
Limnological Surveys of the Upper Potomac River. Am. Midland Naturalist, 88:56.
VI-13
-------
Keuls, M., 1952. The Use of the "Studentized Range" in Connection with an
Analysis of Variance. Euphytica, 1:112.
Keup, L.E., 1966. Stream Biology for Assessing Sewage Treatment Plant
Efficiency. Water and Sewage Works, 113:411.
Kohn, A.J., 1968. Microhabitats, Abundance and Food of Conus on Atoll Reefs in
the Maldive and Chagos Islands. Ecology, 49:1046.
Livingston, R.J., 1975. Impact of Kraft Pulp-Mill Effluents on Estuarine
Coastal Fishes in Apalachee Bay, FL. Marine Biology, 32:19.
Lloyd, M.J., et al., 1968. On the Calculation of Information-Theoretical
Measures of Diversity. Amer. Midland Natur., 79:257.
Lloyd, M., and R.J. Ghelardi, 1964. A Table for Calculating the "Equitability"
Component of Species Diversity. Jour. Anim. Ecol., 33:217.
MacAuthur, R.H., 1957. On the Relative Abundance of Bird Species. Proc. Nat.
Acad. Sci. Washington, D.C. 43:293.
, 1960. On the Relative Abundance of Species. Am. Natur., 94:25.
Margalef, R., 1951. Diversidad de Especies en las Communidades Naturales. Pub.
Inst. Biol. Apl. (Barcelona) 9:5.
, 1956. Information of Diversidad Especifica en las Communidades
de Organismos. Invest. Pesq., 3:99.
_, 1958. Information on Theory in Ecology. English translation by
W. Hall in Yearbook of the Society for General Systems Research, 3:36.
Mclntosh, R.P., 1967. An Index of Diversity and the Relation of Certain
Concepts to Diversity. Ecology, 48:392.
Menhinick, E.F., 1964. A Comparison of Some Species-Individuals Diversity
Indices Applied to Samples of Field Insects. Ecology, 45:859.
Morisita, M., 1959. Measuring of Interspecific Association and Similarity
Between Communities. Memoirs Faculty Sci., Kyushu Univ. Ser. E. Biol., 3:65.
Newman, D., 1939. The Distribution of Range in Samples from a Normal
Population, Expressed in Terms of an Independent Estimate of Standard
Deviation. Biometrika, 31, 20.
Ochiai, A., 1957. Zoogeographical Studies on the Soleoid Fishes Found in Japan
and its Neighboring Regions - II. Bull. Japan. Soc. Sci. Fisheries, 22:526.
Odum, E.P., 1959. Fundamentals of Ecology, 2nd ed. W.B. Sanders Co.,
Philadelphia, PA.
Osborne, L.L., et al., 1980. Use of Hierarchical Diversity Indices in Lotic
Community Analysis. Jour. Appl. Ecol., 17:567.
VI-14
-------
Pantle, R., and H. Buck, 1955. Die Biologische Uberwachund der Gewasser und
die Darstellung der Ergebnisse. Gas und Wasserfach, 96:604.
Patten, B.C., 1962. Species Diversity in Net Phytoplankton of Raritan Bay.
Jour. Mar. Res., 20:57.
Peet, R.K., 1975. Relative Diversity Indices. Ecology, 56:496.
Perkins, J.D., 1983. Bioassay Evaluation of Diversity and Community Comparison
Indexes. Jour. Water Poll. Con. Fed., 55:522.
Peters, J.A., 1968. A Computer Program for Calculating Degree of
Biogeographical Resemblence Between Areas. Systematic Zoology, 17:64.
Pielou, E.C., 1969. An Introduction to Mathematical Ecology.
Wiley-Interscience, NY, 286.
, 1975. Ecological Diversity. Wiley-Interscience, NY, 165.
Pinkham, C.F.A. and J.G. Pearson, 1976. Applications of a New Coefficient of
Similarity to Pollution Surveys. Jour. Water Poll. Con. Fed., 48:717.
Sanders, H.L. 1960. Benthic Studies in Buzzards Bay III. The Structure of the
Soft-Bottom Community, Limnology and Oceanography 5:138.
Shannon, C.E., and W. Weaver, 1963. The Mathematical Theory of Communication.
University of Illinois Press, Urbana, IL.
Sneath, P.H.A. and R.R. Sokal, 1973. Numerical Taxonomy. The Principles and
Practice of Numerical Classification. Freeman, San Francisco.
Simpson, E.H., 1949. Measurement of Diversity. Nature, 163:68.
Sokal, R.R., 1961. Distance as a Measure of Taxonomic Similarity. Systematic
Zoology, 10:70.
Sokal, R.R., and C.D. Michener, 1958. A Statistical Method for Evaluating
Systematic Relationships. Univ. Kansas Sci. Bull., 38:1409.
Sokal, R.R. and F.J. Rohlf, 1962. The Comparison of Dendograms by Objective
Methods. Taxon, 11:33.
Whittaker, R.H., 1952. A Study of Summer Foliage Insect Communities in the
Great Smoky Mountains. Ecological Monographs, 22: 6.
, 1964. Dominance and Diversity in Land Plant Communities.
Science, 147:2bU.
Whittaker, R.H. and C.W. Fairbanks, 1958. A Study of Plankton and Copepod
Communities in the Columbia Basin, Southeastern Washington. Ecology, 39:46.
Wiener, N., 1948. Cybernetics. John Wiley & Sons, Inc., NY, 194 p.
VI-15
-------
Wilhm, J.L., 1967. Comparison of Some Diversity Indices Applied to Populations
of Benthic Macroinvertebrates in a Stream Receiving Organic Wastes. Jour.
Water Poll. Control. Fed., 39:1673.
, 1968. Use of Biomass Units in Shannon's Formula. Ecology, 49:153.
, 1970. Range of Diversity Index in Benthic Macroinvertebrate
Populations. Jour. Water Poll. Con. Fed., 42:R221.
, 1972. Graphic and Mathematical Analyses of Biotic Communities in
Polluted Streams. Ann. Rev. Entomology, 17:223.
Wilhm, J.L. and T.C. Dorris, 1968. Biological Parameters for Water Quality
Criteria. Bioscience, 18:477.
Williams, W.T., 1971. Principles of Clustering. Ann. Rev. Ecol. Syst., 2:303.
Winget, R.N. and F.A. Mangum, 1979. Biotic Condition Index: Integrated
Biological, Physical, and Chemical Stream Parameters for Management. U.S.
Forest Service Intermountain Reg., p. 1-51.
Zar, J.H., 1974. Biostatistical Analysis, Prentice-Hall, Inc., Englewood
Cliffs, NJ, 620 p.
CHAPTER IV-3: RECOVERY INDEX
Cairns, J. Jr., 1975. Biological Integrity-A Quantitative Determination. In
U.S. EPA, The Integrity of Water (R.K. Ballentine and L.J. Guarraia, editors).
U.S. Government Printing Office, Washington, D.C., 055-001-01068-1.
CHAPTER IV-4: INTOLERANT SPECIES ANALYSIS
Ball, J., 1982. Stream Classification Guidelines for Wisconsin. Technical
Bulletin (Draft), Wisconsin Department of Natural Resources, Madison.
Brett, J.R., 1956. Some Principles in the Thermal Requirements of Fishes.
Quarterly Review of Biology 31:75.
Carlander, K.D., 1969 and 1977. Handbook of Freshwater Fishery Biology, Vols.
I and II, Iowa State University Press, Ames, Iowa.
Haines, T.A., 1981. Acidic Precipitation and Its Consequences for Aquatic Eco-
systems: A Review. Trans. Amer. Fish. Soc., 110: 669.
Hutchinson, G.E., 1957. Concluding Remarks in Population Studies: Animal
Ecology and Demography, Cold Spring Harbor Symposia on Quantitative Biology,
£• w • i X 3 »
Johnson, W.W., and Finley, M.T., 1980. Handbook of Acute Toxicity of Chemicals
to Fish and Aquatic Invertebrates. U.S. FWS, Washington, D.C., Resource
Publication 137.
VI-16
-------
Karr, J.R., 1981. Assessment of Biotic Integrity Using Fish Communities.
Fisheries 6:21.
Kendigh, S.C., 1974. Ecology with Special Reference to Animals and Man.
Prentice-Hall, Inc., Englewood Cliffs, NJ.
Lee, D.S., et al., 1980. Atlas of North American Freshwater Fishes. N.C.,
State Mus. Nat. Hist., Raleigh, NC.
Morrow, J.E., 1980. The Freshwater Fishes of Alaska. Alaska Northwest
Publishing Co., Anchorage, AK.
Moyle, P.B., 1976. Inland Fishes of California. University of California
Press, Berkeley, CA.
Muncy, R.J., et al., 1979. Effects of Suspended Solids and Sediment on
Reproduction and Early Life of Warmwater Fishes: A Review. U.S. EPA,
Corvallis, OR, EPA-600/3-79-042.
Pflieger, W.L., 1975. The Fishes of Missouri. Missouri Dept. Conserv.,
Jefferson City, MO.
Robins, C.R., et al., 1980. A List of Common and Scientific Names of Fishes
from the United States and Canada, 4th ed., AFS Special Publ. No. 12,
Bethesda, MD.
Scott, W.B., and Grossman, E.J., 1973. Freshwater Fishes of Canada. Fisheries
Research Board of Canada, Bull. 184.
Shelford, V.E., 1911. Ecological Succession. Biol. Bull. 21: 127-151, 22:1.
Smith, P.W., 1979. The Fishes of Illinois. University of Illinois Press,
Urbana, IL.
Timbol, A.S., and Maciolek, J.A., 1978. Stream Channel Modification in Hawaii.
Part A: Statewide Inventory of Streams, Habitat Factors, and Associated Biota.
U.S. FWS, Columbia, MO, FWS/OBS-78/16.
Trautman, M.B., 1957. The Fishes of Ohio. Ohio State University Press,
Columbus, OH.
U.S. EPA, 1980. Ambient Water Quality Criteria for Aldrin/Dieldrin, Chlordane,
DDT, Endosulfan, Endn'n, Heptachlor, Lindane, PCBs, Toxaphene, Cyanide,
Arsenic, Cadmium, Chromium, Copper, Lead, Mercury, Nickel, Selenium, Silver,
and Zinc. U.S. EPA, Washington, D.C., EPA 440/5-80-
Vannote, R.L., et al., 1980. The River Continuum Concept. Can. Jour. Fish.
Aquat. Sci., 37:130.
Wallen, E.I., 1951. The Direct Effect of Turbidity on Fishes. Oklahoma A&M
College, Stillwater, OK, Biol. Series No. 2, 48:1.
Warren, C.E., 1971. Biology and Water Pollution Control. W.B. Saunders Co.,
Philadelphia, PA.
VI-17
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CHAPTER IV-5: OMNIVORE-CARNIVORE ANALYSIS
Cairns, J., Jr., 1977. Quantification of Biological Integrity. In the
Integrity of Water (R.K. Ballentine and L.J. Guarraia, editors). U.S.
Government Printing Office, Washington, D.C., 055-001-01068-1.
Carlander, K.D., 1969. Handbook of Freshwater Fishery Biology, Vol. I. Iowa
State University Press, Ames, IA.
1977. Handbook of Freshwater Fishery Biology, Vol. II. Iowa
State University Press, Ames, IA.
Cross, F.B. and J.T. Collins, 1975. Fishes in Kansas (R.F. Johnson, editor).
University of Kansas Publ., Museum of Nat. Hist., Lawrence, KS.
Cummins, K.W., 1974. Structure and Function of Stream Ecosystems. BioScience
24:631.
, 1975. The Ecology of Running Waters: Theory and Practice. In
Proc. Sandusky River Basin Symp. (D.B. Baker, et al. editors). International
Joint com. on the Great Lakes, Heidelburg College, Tiffin, OH.
Darnell, R.M. 1961. Trophic Spectrum of an Estuarine Community, Based on
Studies of Lake Ponchartrain, Louisiana. Ecology 42: 553.
Fausch, K.D., et al., 1982. Regional Application of an Index of Biotic
Integrity Based on Stream Fish Communities, Submission to Trans. Amer. Fish.
Soc.
Karr, J.R., 1981. Assesment of Biotic Integrity Using Fish Communities.
Fisheries 6:21.
Karr, J.R., et al., 1983. Habitat Preservation for Midwest Stream Fishes:
Principles and Guidelines, U.S. EPA, Corvallis, OR, EPA-600/3-83-006.
Karr, J.R. and D.R. Dudley, 1978. Biological Integrity of a Headwater Streams:
Evidence of Degradation, Prospects for Recovery. In Environmental Impact of
Land Use on Water Quality: Final Report on the Black Creek Project
(Supplemental Comments) (J. Morrison, editor), U.S. EPA, Chicago, IL,
EPA-905/9-77-007-D, pp. 3-25.
Kendeigh, S.C., 1974. Ecology with Special Reference to Animals and Man.
Prentice-Hall, Inc., Englewood Cliffs, NJ.
Kuehne, R.A., 1962. A Classification of Streams, Illustrated by Fish
Distribution in an Eastern Kentucky Creek. Ecology 43: 608.
Larimore, W.R., and P.M. Smith, 1963. The Fishes of Champaign County, Illinois
as Affected by 60 Years of Stream Changes. 111. Nat. Hist. Sur. Bull. 28:299.
Lee, D.S., et al., 1980. Atlas of North American Freshwater Fishes. N.C. State
Mus. Nat. Hist., Raleigh, NC.
Lindeman, R.L., 1942. The Trophic-Dynamic Aspect of Ecology. Ecology 23.
VI-18
-------
Menzel, B.W., and H.L. Fierstine, 1976. A Study of the Effects of Stream
Channelization and Bank Stabilization on Warmwater Sport Fish in Iowa. No. 5:
Effects of Long-Reach Stream Channelization on Distribution and Abundance of
Fishes. U.S. Fish and Wildlife Service, Columbia, MO, FWS/OBS-76-15.
Morita, C.M., 1953. Freshwater Fishing in Hawaii. Div. of Fish and Game, Dept.
Land Nat. Res., Honolulu, HI.
Morrow, J.E., 1980. The Freshwater Fishes of Alaska. Alaska Northwest
Publishing Co., Anchorage, AK.
Moyle, P.B., 1976. Inland Fishes of California. University of California
Press, Berkeley.
Odum, H.T., 1957. Trophic Structure and Productivity of Silver Springs, FL,
Ecol. Monogr. 27:55.
Pflieger, W.L., 1975. The Fishes of Missouri. Missouri Dept. Conserv.,
Jefferson City, MO.
Reid, G.K., and R.D. Wood, 1976. Ecology of Inland Waters and Estuaries, 2nd
Ed., D. Van Nostrand Co., NY.
Richardson, J.L., 1977. Dimensions in Ecology. Williams & Wilkins, Baltimore,
MD.
Robins, C.R., et al., 1980. A List of Common and Scientific Names of Fishes
from the United States and Canada, 4th ed., Special Publ. No. 12, American
Fisheries Soc., Bethesda, MD.
Schlosser, I.J, 1981. Effects of Perturbations by Agricultural Land Use on
Structure and Function of Stream Ecosystems. Ph.D. dissertation, University of
Illinois, Champaign - Urbana, IL.
, 1982a. Trophic Structure, Reproductive Success, and Growth
Rate of FishesTn a Natural and Modified Headwater Stream. Can. Jour. Fish
Aquat. Sci. 39:968.
, 1982b. Fish Community Structure and Function Along Two Habitat
Gradients in a Headwater Stream. Ecol. Monog. 52: 395.
Scott, W.B., and E.J. Grossman, 1973. Freshwater Fishes of Canada. Fisheries
Research Board of Canada, Bull. 184.
Shelford, V.E., 1911. Ecological Succession. Biol. Bull. 21:127, 22:1.
Smith, P.W., 1979. The Fishes of Illinois. University of Illinois Press,
Urbana, IL.
Timbol, A.S. and J.A. Maciolek, 1978. Stream Channel Modification in Hawaii.
Part A: Statewide Inventory of Streams, Habitat Factors, and Asociated Biota.
U.S. Fish and Wildlife Service, Columbia, MO, FWS/OBS-78/16.
VI-19
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Trautman, M.B., 1957. The Fishes of Ohio. Ohio State University Press,
Columbus, OH.
U.S. EPA, 1980. Ambient Water Quality Criteria (several volumes) for
Aldrin/Dieldrin, Chlordane, DDT, Encosulfan, Endrin, Heptachlor, Lindane,
PCBs, Toxaphene, Cyanide, Arsenic, Cadmium, Chromium, Copper, Lead, Mercury,
Nickel, Selenium, Silver, and Zinc. U.S. EPA, Washington, D.C., EPA 440/5-80.
Wallen, E.I., 1951. The Direct Effect of Turbidity on Fishes. Oklahoma A&M
College, Stillwater, OK, Biol. Series No. 2, 48:1.
Warren, C.E., 1971. Biology and Water Pollution Control. W.B. Saunders,
Philadelphia, PA.
CHAPTER IV-6: REFERENCE REACH COMPARISON
Bailey, R.G., 1976. Ecoregions of the United States. U.S.D.A.-Forest Service.
Intermtn. Reg. Ogden, UT.
Barbour, C.D. and J.H. Brown, 1974. Fish Species Diversity in Lakes. Am. Nat.
108:473.
Federal Register, 1982. Proposed Water Quality Standards and Public Meetings.
47(210):49234.
Gilbert, C.R., 1980. Zoogeographic Factors in Relation to Biological
Monitoring of Fish. In Biological Monitoring of Fish (C.H. Hocutt and J.R.
Stauffer, Jr., editors). D.C. Hath Co., Lexington, MA, p. 309-355.
Green, R.H., 1979. Sampling Design and Sampling Methods for Environmental
Biologists. John Wiley and Sons, NY.
Hall, J.D., et al.,1 1978. An Improved Design for Assessing Impacts of
Watershed Practices on Small Streams. Verh. Interna. Verein. Limnol. 20:1359.
Hughes, R.M., Effects of Mining Wastes on Two Stream Ecosystems: Demonstration
of an Approach for Estimating Ecological Integrity and Attainable Uses.
Hughes, R.M., et al., 1982. An Approach for Determining Biological Integrity
in Flowing Waters. In Place Resource Inventories: Principles and Practices
(T .B. Brann, L.O. House IV, and H.G. Lund, editors). Soc. Am. Foresters,
Bethesda, MD.
Hughes, R.M. and J.M. Omernik, 1981a. Use and Misuse of the Terms Watershed
and Stream Order. In The Warmwater Streams (L.A. Krumholz, editor). Symposium
Am. Fish. Soc., Bethesda, MD.
, 1981b. A Proposed Approach to Determine
RegionalPatternsin Aquatic Ecosystems. In Acquisition and Utilization of
Aquatic Habitat Inventory Information (N.B. Armantrout, editor). Am. Fish.
Soc., Bethesda, MD.
VI-20
-------
, 1983. An Alternative for Characterizing Stream
Size. InDynamics of Lotic Ecosystems (T.D. Fontain III and S.M. Bartell,
editors). Ann Arbor Science, Ann Arbor, MI.
Karr, J.R., 1981. Assesment of Biotic Integrity Using Fish Communties.
Fisheries 6:21.
Lotspeich, F.B. and W.S. Piatts, 1982. An Integrated Land-Aquatic
Classification System. N. Amer. J. Fish. Mgmt. 2:138.
MacArthur, R.H. and E.O. Wilson, 1967. The Theory of Island Biogeography,
Princeton Univ. Press., Princeton, NJ.
Marsh, P.C. and J.E. Luey, 1982. Oases for Aquatic Life in Agricultural
Watersheds. Fisheries 7:16.
Omernik, J.M. and R.M. Hughes, 1983. An Approach for Defining Regional
Patterns of Aquatic Ecosystems and Attainable Stream Quality in Ohio. Progress
Report. U.S. EPA, Corvallis, OR.
Pfleiger, W.L., M.A. Schene, Jr., and P.S. Haverland. 1981. Techniques for the
Classification of Stream Habitats With Examples of Their Application in
Defining the Stream Habitats of Missouri. In Acquisition and Utilization of
Aquatic Habitat Inventory Information (N.B. Armantrout, editor). Am. Fish.
Soc., Bethesda, MD.
Strahler, A.N., 1957. Quantitative Analysis of Watershed Geomorphology. Trans.
Am. Geophys. Union 38:913.
Trautman, M.G., 1981. The Fishes of Ohio. Ohio State Univ. Press.
U.S.D.I.-Geological Survey, 1970. The National Atlas of the United States of
America. U.S. Government Printing Office, Washington, D.C.
Vannote, R.L., et al., 1980. The River Continuum Concept. Can. J. Fish. Aquat.
Sci. 37:130.
Warren, C.E., 1979. Toward Classification and Rationale for Watershed
Management and Stream Protection. EPA-600/3-79-059. NTIS Springfield, VA.
VI-21
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0 APPENDIX A-l:
SAMPLE HABITAT SUITABILITY INDEX
(Channel Catfish)
-------
Biological Services Program
FWS/OBS-82/10.2
FEBRUARY 1982
HABITAT SUITABILITY INDEX MODELS:
CHANNEL CATFISH
Fish and Wildlife Service
U.S. Department of the Interior
-------
FWS/OBS-82/10.2
February 1982
HABITAT SUITABILITY INDEX MODELS: CHANNEL CATFISH
by
Thomas E. McMahon
and
James W. Terrell
Habitat Evaluation Procedures Group
Western Energy and Land Use Team
U.S. Fish and Wildlife Service
Drake Creekside Building One
2625 Redwing Road
Fort Collins, Colorado 80526
Western Energy and Land Use Team
Office of Biological Services
Fish and Wildlife Service
U.S. Department of the Interior
Washington, D.C. 20240
-------
PREFACE
The habitat use information and Habitat Suitability Index (HSI) models
presented in this document are an aid for impact assessment and habitat man-
agement activities. Literature concerning a species' habitat requirements and
preferences is reviewed and then synthesized into HSI models, which are scaled
to produce an index between 0 (unsuitable habitat) and 1 (optimal habitat).
Assumptions used to transform habitat use information into these mathematical
models are noted, and guidelines for model application are described. Any
models found in the literature which may also be used to calculate an HSI are
cited, and simplified HSI models, based on what the authors believe to be the
most important habitat characteristics for this species, are presented.
Use of the models presented in this publication for impact assessment
requires the setting of clear study objectives and may require modification of
the models to meet those objectives. Methods for reducing model complexity
and recommended measurement techniques for model variables are presented in
Appendix A.
The HSI models presented herein are complex hypotheses of species-habitat
relationships, not statements of proven cause and effect relationships.
Results of model performance tests, when available, are referenced; however,
models tnat have demonstrated reliability in specific situations may prove
unreliable in others. For this reason, the FWS encourages model users to
convey comments and suggestions that may help us increase the utility and
effectiveness of this habitat-based approach to fish and wildlife planning.
Please send comments to:
Habitat Evaluation Procedures Group
Western Energy and Land Use Team
U.S. Fish and Wildlife Service
2625 Redwing Road
Ft. Collins, CO 80526
-------
CONTENTS
Page
PREFACE . iii
ACKNOWLEDGEMENTS vi
HABITAT USE INFORMATION 1
General 1
Age, Growth, and Food 1
Reproduction 1
Specific Habitat Requirements 1
HABITAT SUITABILITY INDEX (HSI) MODELS 4
Model Applicability • 4
Model Description - Riverine 5
Model Description - Lacustrine 8
Suitability Index (SI) Graphs for
Model Variables 9
Riverine Model 15
Lacustrine Model 17
Interpreting Model Outputs 22
ADDITIONAL HABITAT MODELS 24
Model 1 24
Model 2 25
Model 3 25
REFERENCES CITED 25
-------
CHANNEL CATFISH (Ictalurus punctatus)
HABITAT USE INFORMATION
General
The native range of channel catfish (IC-lilyiyi punctatus) extends from
the southern portions of the Canadian prairie province's south to the Gulf
states, west to the Rocky Mountains, and east to -the Appalachian Mountains
(Trautman 1957; Miller 1966; Scott and Crossman 1973). They have been widely
introduced outside this range and occur in essentially all of the Pacific and
Atlantic drainages in the 48 contiguous states (Moore 1968; Scott and Crossman
1973). The greatest abundance of channel catfish generally occurs in the open
(unleveed) floodplains of the Mississippi and Missouri River drainages (Walden
1964).
Age, Growth, and Food
Age at maturity in channel catfish is variable. Catfish from southern
areas with longer growing seasons mature earlier and at smaller sizes than
those from northern areas (Davis and Posey 1958; Scott and Crossman 1973).
Southern catfish mature at age V or less (Scott and Crossman 1973; Pflieger
1975) while northern catfish mature at age VI or greater for males and at age
VIII or greater for females (Starostka and Nelson 1974).
Young-of-the-year (age 0) catfish feed predominantly on plankton and
aquatic insects (Bailey and Harrison 1948; Walburg 1975). Adults are oppor-
tunistic feeders with an extremely varied diet, including terrestrial and
aquatic insects, detrital and plant material, crayfish, and molluscs (Bailey
and Harrison 1948; Miller 1966; Starostka and Nelson 1974). Fish may form a
major part of the diet of catfish > 50 cm in length (Starostka and Nelson
1974). Channel catfish diets in rivers and reservoirs do not appear to be
significantly different (see Bailey and Harrison 1948; Starostka and Nelson
1974). Feeding is done by both vision and chemosenses (Davis 1959) and occurs
primarily at night (Pflieger 1975). Bottom feeding is more characteristic but
food is also taken throughout the water column (Scott and Crossman 1973).
Additional information on the composition of adult and juvenile diets is
provided in Leidy and Jenkins (1977).
Reproduction
Channel catfish spawn in late spring and early summer (generally late May
through mid-July) when temperatures reach about 21° C (Clemens and Sneed 1957;
Marzolf 1957; Pflieger 1975). Spawning requirements appear to be a major
factor in determining habitat suitability for channel catfish (Clemens and
Sneed 1957). Spawning is greatly inhibited if suitable nesting cover is
unavailable (Marzolf 1957).
Specific Habitat Requirements
Channel catfish populations occur over a broad range of environmental
conditions (Sigler and Miller 1963; Scott and Crossman 1973). Optimum riverine
-------
habitat is characterized by warm temperatures (Clemens and Sneed 1957; Andrews
et al. 1972; Biesinger et al. 1979). and a diversity of velocities, depths, and
structural features that provide cover and food (Bailey and Harrison 1948).
Optimum lacustrine habitat is characterized by large surface area, warm temper-
atures, high productivity, low to moderate turbidity, and abundant cover
(Davis'l959; Pflieger 1975).
Fry, juvenile, and adult channel catfish concentrate in the wannest
sections'of rivers and reservoirs (Ziebell 1973; Stauffer et al . 1975; McCall
1977). They strongly seek cover, but quantitative data on cover requirements
of channel catfish in rivers and reservoirs are not available. Debris, logs,
cavities, boulders, and cutbanks in lakes and in low velocity (< 15 cm/sec)
areas of deep pools and backwaters of rivers will provide cover for channel
catfish (Bailey and Harrison 1948). Cover consisting of boulders and debris
in deep water is important as overwintering habitat (Miller 1966; Jester 1971;
Cross and Collins 1975). Deep pools and littoral areas (< 5-m deep) with
> 40% suitable cover are assumed to be optimum. Turbidities > 25 ppm but
< 100 ppm may somewhat moderate the need for fixed cover (Bryan et al. 1975).
Riffle and run areas with rubble substrate and pools (< 15 cm/sec) and
areas with debris and aquatic vegetation are conditions associated with high
production of aquatic insects (Hynes 1970) consumed by channel catfish in
rivers (Bailey and Harrison 1948). Channel catfish are most abundant in river
sections with a diversity of velocities and structural features. Therefore, it
is assumed that a riverine habitat with 40-60% pools would be optimum for
providing riffle habitat for food production and feeding and pool habitat for
spawning and resting cover (Bailey and Harrison 1948). It also is assumed
that at least 20% of lake or reservoir surface area should consist of littoral
areas (< 5 m deep) to provide adequate area for spawning, fry and juvenile
rearing, and feeding habitat for channel catfish.-
High standing crops of warmwater fishes are associated with total
dissolved solids (TDS) levels of 100 to 350 ppm for reservoirs in which the
concentrations of carbonate-bicarbonate exceed those of sulfate-chloride
(Jenkins 1976). It is assumed that high standing crops of channel catfish in
lakes or reservoirs will, on the average, correspond to this TDS level.
Turbidity in rivers and -reservoirs and reservoir size are other factors
that may influence habitat suitability for channel catfish populations.
Channel catfish are abundant in rivers and reservoirs with varying levels of
turbidity and siltation (Cross and Collins 1975). However, low to moderate
turbidities (< 100 ppm) are probably optimal for both survival and growth
(Finnell and Jenkins 1954; Buck 1956; Marzolf 1957). Larger reservoirs
(> 200 ha) are probably more suitable reservoir habitat for channel catfish
populations because survival and growth are better than in smaller reservoirs
(Finnell and Jenkins 1954; Marzolf 1957). Other factors that may affect
reservoir habitat suitability for channel catfish are mean depth, storage
ratio (SR), and length of agricultural growing season. Jenkins (1974) found
that high mean depths were negatively correlated with standing crop of channel
catfish. Mean depths are an inverse correlate of shoreline development (Ryder
et al. 1974), thus higher mean depths may mean less littoral area would be
available. Jenkins (1976) also reported that standing crops of catfishes
(Ictaluridae) peaked at an SR of 0.75. Standing crops of channel catfish were
-------
postively correlated to growing season length (Jenkins 1970). However, harvest
of channel catfish reported in reservoirs was not correlated with growing
season length (Jenkins and Morais 1971.).
Dissolved oxygen (DO) levels of 5 mg/1 are adequate for growth and
survival of channel catfish, but D.O. levels of > 7 mg/1 are optimum (Andrews
et al. 1973; Carlson et al. 1974). Dissolved oxygen levels < 3 mg/1 retard
growth (Simco and Cross 1966), and feeding is reduced at D.O. levels < 5 mg/1
(Randolph and Clemens 1976).
AdjJ_H. Adults in rivers are found in large, deep pools with cover They
move to riffles and runs at night to feed (McCammon 1956'; Davis 1959; Pflieger
1971; 1975). Adults in reservoirs and lakes favor reefs and deep, protected
areas with rocky substrates or other cover They often move to the shoreline
or tributaries at night to feed (Davis 1959; Jester 1971; Scott and Grossman
1973).
The optimal temperature range for growth of adult channel catfish is
26-29° C (Shrable et al . 1969; Chen 1976). Growth is poor at temperatures
< 21° C (McCammon and LaFaunce 1961; Macklin and Soule 1964; Andrews and
Stickney 1972) and ceases at < 18° C (Starostka and Nelson 1974). An upper
lethal temperature of 33.5° C has been reported for catfish acclimated at
25° C (Carlander 1969).
Adult channel catfish were most abundant in habitats with salinities
< 1.7 ppt in Louisiana, although they occurred in areas with salinities up to
11.4 ppt (Perry 1973). Salinities < 8 ppt are tolerated with little or no
effect, but growth slows above this level and does not occur at salinities
> 11 ppt (Perry and Avault 1968).
Embryo. Dark and secluded areas are required for nesting (Marzolf 1957).
Males build and guard nests in cavities, burrows, under rocks, and in other
protected sites (Davis 1959; Pflieger 1975). Nests in large impoundments
generally occur among rubble and boulders along protected shorelines at depths
of about 2-4 m (Jester 1971). Catfish in large rivers are likely to move into
shallow, flooded areas to spawn (Bryan et al. 1975). Lawler (1960) reported
that spawning in Utah Lake, Utah, was concentrated in sections of the lake
with abundant spawning sites of rocky outcrops, trees, and crevices. The male
catfish fans embryos for water •exchange and guards the nest from predators
(Miller 1966; Minckley 1973). Embryos can develop in the temperature range of
15.5 to 29.5° C, with the optimum about 27° C (Brown 1942; Clemens and Sneed
1957). They do not develop at temperatures < 15.5° C (Brown 1942). Embryos
hatch in 6-7 days at 27° C (Clemens and Sneed 1957).
Laboratory studies indicate that embryos three days old and older can
tolerate salinities up to 16 ppt until hatching, when tolerance drops to 8 ppt
(Allen and Avault 1970). However, 2 ppt salinity is the highest level in
which successful spawning in ponds has been observed (Perry 1973). Embryo
survival and production in reservoirs will probably be high in areas that are
not subject to disturbance by heavy wave action or rapid water drawdown.
Fry. The optimal temperature range for growth of channel catfish fry is
29-30° C (West 1966). Some growth does occur down to temperatures of 18° C
(Starostka and Nelson 1974), but growth generally is poor in cool waters with
average summer temperatures < 21° C '(McCammon and LaFaunce 1961; Macklin and
-------
Soule 1964; Andrews et al. 1972) and in areas with short agricultural growing
seasons (Starostka and Nelson 1974). Upper incipient lethal levels for fry
are about 35-38° C, depending on acclimation temperature (Moss and Scott 1961;
Allen and Strawn 1968). Optimum salinities for fry range from 0-5 ppt;
salinities £ 10 ppt are marginal as growth is greatly reduced (Allen and
Avault 1970).
Fry habitat suitability in reservoirs is related to flushing rate of
reservoirs in midsummer. Walburg (1971) found abundance and survival of fry
greatly decreased at flushing rates < 6 days in July and August.
Channel catfish fry have strong shelter-seeking tendencies (Brown et al.
1970), and cover availability will be important in determining habitat suit-
ability. Newly hatched fry remain in the nest for 7-8 days (Marzolf 1957) and
then disperse to shallow water areas with cover (Cross and Collins 1975). Fry
are commonly found aggregated near cover in protected, slow-flowing (velocity
< 15 cm/sec) areas of rocky riffles, debris-covered gravel, or sand bars in
clear streams (Davis 1959; Cross and Collins 1975), and in very shallow
(< 0.5 m) mud or sand substrate edges of flowing channels along turbid rivers
and bayous (Bryan et al. 1975). Dense aquatic vegetation generally does not
provide optimum -cover because predation on fry by centrarchids is high under
these conditions, especially in clear water (Marzolf 1957; Cross and Collins
1975). Fry overwinter under boulders in riffles (Miller 1966) or move to
cover in deeper water (Cross and Collins 1975).
Juvenile. Optimal habitat for juveniles is assumed to be similar to that
for fry. The temperature range most suitable for juvenile growth is reported
to be 28-30° C (Andrews et al. 1972; Andrews and Stickney 1972). Upper lethal
temperatures are assumed to be similar to those for fry.
HABITAT SUITABILITY INDEX (HSI) MODELS
Model Applicability
Geographic area. The model is applicable throughout the 48 conterminous
States. The sta'ndard of comparison for each individual variable suitability
index is the optimum value of the variable that occurs anywhere within the 48
conterminous States. Therefore, the model will never provide an HSI of 1.0
when applied to water bodies in the Northern States where temperature-related
variables do not reach the optimum values for channel catfish found in the
Southern States.
Season. The model provides a rating for a water body based on its ability
to support a self-sustaining population of channel catfish through all seasons
of the year.
Cover types. The model is applicable in riverine, lacustrine, palustrine,
and estuarine habitats, as described by Cowardin et al. (1979).
Minimum habitat area. Minimum habitat area is defined as the minimum
area of contiguous suitable habitat that is required for a species to succes-
fully live and reproduce. No attempt has been made to establish a minimum
-------
habitat size for channel catfish, although this species is most abundant in
larger water bodies.
. The acceptable output of these models is an index
between 0 and 1 which the authors believe has a positive relationship to
carrying capacity. In order to verify that the model output was acceptable,
sample data sets were developed for calculating HSI's from the models..
The sample data sets and their relationship to model verification are
discussed in greater detail following the presentation of the models.
Model Description
It is assumed that channel catfish habitat quality is based primarily on
their food, cover, water quality, and reproduction requirements. Variables
that have been shown to have an impact on the growth, survival, distribution,
abundance, or other measure of well-being of channel catfish are placed in the
appropriate component and a component rating derived from the individual
variable suitability .he important for rating
the food component because if cover is available, fish would be more likely to
occupy an area and utilize the food resources. Substrate (V*) is included
because stream production potential of aquatic insects (consumed directly by
both channel catfish and their prey species) is "related to amount and type of
substrate .
Cover component. Percent pools (Vt) is included because channel catfish
utilize pools as cover. Percent cover (V2) is an index of all types of
objects, Including logs and debris, used for cover in rivers. Average current
velocity in cover areas (Vlt) is important because the usable habitat near a
cover object decreases if cover objects are surrounded by high velocities.
Water quality component. The water quality component is limited to
temperature, oxygen, turbidity, and salinity measurements. These parameters
have been shown to effect growth or survival, or have been correlated with
changes in standing crop. Variables related to temperature, oxygen, and
salinity are assumed to be limiting when they approach lethal levels. Toxic
substances are not considered.
-------
Habitat Variables
% cover (Va)
Substrate type (Vfc)
Life Requisites
Food (CF),
% pools (VJ
% cover (V2)
Average current velocity
Cover (Cr),
Temperature (adult) (V5)
Temperature (fry) (V12)
Temperature (juvenile) (VJ(,)
Dissolved oxygen (V,)-
Turbidity (V7)
Salinity (adult) (V.)
Salinity (fry, juvenile) (V13)
Length of agricultural growing season (V«)
Water quality
% pools
% cover (V2)
Dissolved oxygen (V,)-
Temperature (embryo.) (V10)
Salinity (embryo) (VM)
Reproduction (CR)'
Figure 1. Tree diagram illustrating relationship of habitat variables
and life requisites in the riverine model for the channel catfish.
Dashed lines indicate optional variables in the model.
-------
Habitat Variables
% cover (V2)
% littoral area (V,)
Total dissolved solids (Vi6)
% cover (V2)
% littoral area (Vj)
Cover (Cc),
Temperature (adult) (V5)
Temperature (fry) (Vj2)
Temperature (juvenile)
Dissolved oxygen (Vt)
Turbidity (V7)
Salinity (adult) (V,)
Salinity (fry, juvenile) (V13)
Length of agricultural growing season (V,)
Water quality (CWQ)
% cover (V,)
% littoral tit-* (V,)
Dissolved oxygen (V,)
Temperature (embryo) (V10)
Salinity (embryo)
Reproduction (CR)'
Storage ratio (VjS)
Flushing rate (V17)
Other (CQT)
Figure 2. Tree diagram illustrating relationship of habitat variables
and life requisites in the lacustrine model for the channel catfish.
Dashed lines indicate optional variables in the model.
-------
Reproduction component. Percent pools (VJ is in the reproductive compcr
nent because channel catfish spawn in low velocity areas in rivers. Percent
cover (V2) is in this component since channel catfish require cover for ,
spawning. If minimum dissolved oxygen (DO) levels within pools and backwaters
during midsummer (V,) are adequate, they should be adequate during spawning,
which occurs earlier in the year. Dt levels measured during spawning and
embryo development could be substituted for V8. Two additional variables,
average water temperatures within pools and backwaters during spawning and
embryo development (V1D) and maximum salinity during spawning and embryo
development (V1X) are included' because these water quality conditions affect
embryo survival and development.
Model Description - Lacustrine
Food component. Percent cover (Vj) is included since it is assumed that
if cover is available, channel catfish would be more likely to utilize an area
for feeding. Percent littoral area (V3) is included because littoral areas
generally produce the greatest amount of food and feeding habitat for catfish.
Total dissolved solids (TDS) (Vis) is included because adult channel catfish
eat fish, and fish production in lakes and reservoirs is correlated with TDS.
Cover component. Percent cover (V2) is included since channel catfish
strongly seek structural features of logs, debris, brush, and other objects
for shelter. Percent littoral area (V3) is included because all life stage
predominantly utilize cover found in littoral areas of a lake.
Water quality component. Refer to riverine model description.
Reproduction component. Percent cover (V2) is included since catfish
build nests in dark and secluded areas; spawning is not observed if suitable
cover is unavailable. Percent littoral area (Vj) is included since catfish
spawning is concentrated along the shoreline. DO (V,), temperature (Vlo) and
salinity (Vn) are included because these water quality parameters affect
embryo survival and development.
Other component. For reservoirs, storage ratio (Vls) and maximum flushing
rate when fry are present (V17) are included in this component because storage
ratio may affect standing crop and the flushing of fry from a reservoir outlet
can reduce the abundance of fry.
-------
Suitability index (SI) Graphs for Model Variables
This section contains suitability index graphs for the 18 variables
described above, and equations for combining selected variables into a species
HSI using the component approach. Variables pertain to a riverine (R) habitat,
lacustrine (L) habitat, or both (R, L).
Habitat Variable
Percent pools during
average summer flow.
1.0
I 0.8 I
0.6 .
« 0.4J
0.2 -I
0.0
0
Sultability Graph
25
50
75 100
R,L
(V2) Percent cover (logs,
boulders, cavities,
brush, debris, or
standing timber) during
summer withi n pools ,
backwater areas, and
littoral areas.
X
CD
-o
-Q
1.0
0.8-
0.6-
0.4H
0.2H
0.0
I i
10 20 30 40 50
-------
(V3) Percent littoral area
during summer.
0.0
25
50 75 100
(V,,) Food production potential
in river by substrate type
present during average
summer flow.
A) Rubble dominant in
riffle-runs with some
gravel and/or boulders
present; fines (silt
and sand) not common;
aquatic vegetation
abundant (> 30%) in
pool areas.
B) Rubble, gravel,
boulders, and fines
occur in nearly equal
amounts in riffle-run
areas
tion
pool areas.
C) Some rubble and gravel
present, but fines or
boulders are dominant;
aquatic vegetation is
scarce (< 10%) in pool
areas.
D) Fines or bedrock are
the dominant bottom
material. Little or
no aquatic vegetation
or rubble present.
1.0
x
O)
-o
JD
(O
; aquatic vegeta-'5
is 10-30% in °°
0.8 -
0.6 .
0.4 -
0.2 -
0.0
A
C
Class
10
-------
R,L (V|) Average midsummer water
temperature within
pools, backwater's, or
littoral areas (Adult).
IQ
1.0
0.8
0.6
0.4 1
0.2
0.0
10 20 30 40
°C
R,L
(V§) Length of agricultural
growing season (frost-
free days).
Note: This variable
is optional.
1.0
•S 0.8 -
C
*""*
£> 0.6 -
•r»
•i 0.4
•*-> /
<§ 0.2
0.0
125
Days
250
R,L (V7) Maximum monthly average
turbidity during summer.
0.0
100
11
-------
R,l_
R,L
(V,)
(Vs)
Average minimum dissolved 1.0
oxygen levels within
pools, backwaters, or £ Q g
littoral areas during 1
midsummer. ""'
$ 0.6
•r—
"L 0.4 .
'0.2 .
Maximum salinity
during summer
(Adult).
0.0
1.0
-o 0.8 -
£ 0.6 -
•^
1 0.4 -
j? 0.2 .
0.0
0
4
mg/1
10
ppt
R,L (Vlo) Average water
temperatures within
pools, backwaters,
and littoral areas
during spawning and
embryo development
(Embryo).
1.0
£ 0.8 J
•o
£> 0.6 -
5 0.4 -
•r*
uo 0.2 -
0.0
10
20
°C
12
-------
Maximum salinity
curing spawning
and embryo development
(Embryo).
1.0
10
ppt
20
R,L
(Vi2)
Average midsummer water '-0
temperature within pools, x
backwaters, or littoral % 9.8
areas (Fry). £
0.6 -
-o 0.4
(O
0.2 J
0.0
10
40
R..L
Maximum salinity
during summer
(Fry, Juvenile).
6 78 9 10
ppt
13
-------
«.jLc-r
temperature within
pools, backwaters, or
littoral areas
(Juvenile).
1.0
x
~° 0.8
»—«
$ 0.6
5 0.4
0.2 .
0.0
10 20 30 40
°C
Storage ratio.
(V1S) Monthly average IDS
(total dissolved
solids) during
summer.
1000
14
-------
(V17)
Maximum reservoir
f1ushing rate while
fry present (Fry).
1.0
0.0
Average current velocity
in cover areas during
average summer flow.
1.0
X
at
X)
0.8 -
0.6 -
0.4 :
0.2 -
0.0
5
Days
10 20 30 40
cm/sec
50
Riverine Model
These equations utilize the life requisite approach and consist of four
components: food, cover, water quality, and reproduction.
Food (CF)
V2 + V.
15
-------
Cover (Cc).
Cc = (V, x V2 x V1S)1/3
Water Qual ity (C,/n).
2(V5 + V12 + VSb)
3 + v, + 2(V.) + V9 + V,,
CWQ = j—
If Vs, V12, Vlh V., V9, or V13 is < 0.4, then CWQ equals the lowest
of the following: Vs, VJ2, Vlfc, V,, V,, VJ3, or the above equation.
Note: If temperature data are unavailable, 2(V6) (length of agricul-
tural growing season) may be substituted for the term
V12 + VIt)
5 in the above equation
Reproduction (CR).
C = (V! x V22 x V82 x V182 x V^
If V., V10, or,Vu is < 0.4, then CR equals/the lowest of the
following: Vs, Vlo, Vn, or the above equation.
HSI determination.
,1/6
HSI = (CF x Cc x CWQ2 x CR2)1/W , or
WQ
If CWQ or CR is < 0.4, then the HSI equals the lowest of the
., following: Cwn, CR, or the above equation.
16
-------
Sources of data and assumptions made in developing the suitability indices
are presented in Table 1.
Sample data sets using riverine HSI model are listed in Table 2.
Lacustrine Model
This model utilizes the life requisite approach and consists of five
components: food, cover, water quality, reproduction, and other.
Food (CF).
V* + V, + V,,
Cover (Cc).
Cc = (V, x V,)1/2
Water Quality (CWQ).
C = same as in Riverine HSI Model
Reproduction (CR).
CR = (Vz2 x V, x V,2 x V102 x V^)
If V,, Vic, or Vn is < 0.4, then CR equals the lowest of the
following: V,, VK, Vn, or the above equation.
Other (CQT).
COT =
17
-------
Table 1. Data sources and assumptions for channel catfish suitability indices.
Variable and source
Assumption
Bailey and Harrison 1948
V,
V6
V7
V,
V,
Bailey and Harrison 1948
Marzolf 1957
Cross and Collins 1975
Bailey and Harrison 1948
Marzolf 1957
Cross and Collins 1975
Bailey and Harrison 1948
Clemens and Sneed 1957
West 1966
Shrable et al. 1969
Starostka and Nelson 1974
Biesinger et al. 1979
Jenkins 1970
Finnell and Jenkins 1954
Buck 1956
Marzolf 1957
Moss and Scott 1961
Andrews et al. 1973
Carlson et al. 1974
Randolph and Clemens 1976
Perry and Avault 1968
Perry 1973
Optimum conditions for a diversify of
velocities, depths, and structural
features for channel catfish will be
found when there are approximately equal
amounts of pools and riffles.
The strong preference of all life stages
of channel catfish for cover indicates
that some cover must be present for
optimum conditions to occur.
Lakes with small littoral area will pro-
vide less area for cover and food pro-
duction for channel catfish and are there-
fore less suitable.
The amount and type of substrate or the
amount of aquatic vegetation associated
with high production of aquatic insects
(used as food by channel catfish and
channel catfish prey species) is optimum.
Temperatures at the warmest time of year
must reach levels that permit growth in
order for habitat to be suitable. Optimum
temperatures are those when maximum growth
occurs.
Growing seasons that are correlated with
high standing crops are optimum.
High turbidity levels are associated with
reduced standing crops and therefore are
less suitable.
Lethal levels of dissolved oxygen are
unsuitable. DO levels that reduce feeding
are suboptimal.
Salinity levels where adults are most
abundant are optimum. Any salinity
level at which adults have been
reported has some suitabilty.
18
-------
Table 1. (concluded)
Variable and source
Assumption
Vxo Brown 1942
Clemens and Sneed 1957
Vi:
'12
1 5
Vlt
Perry and Avault 1968
Perry 1973
McCammon and LaFaunce 1961
Moss and Scott 1961
Macklin and Soule 1964
West 1966
Allen and Strawn 1968
Andrews 1972
Starostka and Nelson 1974
Allen and Avault 1970
Andrews et al. 1972
Andrews and Stickney 1972
Jenkins 1976
Vls Jenkins 1976
Walburg 1971
Miller 1966
Scott and Grossman 1973
Cross and Collins 1975
Optimum temperatures are those which
result in optimum growth. Temperatures
that result in death or no growth are
unsuitable.
Salinity levels at which spawning has
been observed are suitable.
Optimum temperatures for fry are those
when growth is best. Temperatures that
result in no growth or death are unsuit-
able.
Salinities that do not reduce growth
of fry and juveniles are optimum.
Salinities that greatly reduce growth
are unsuitable.
Temperatures at which growth of juveniles
is best are optimum. Temperatures that
result in no growth or death are unsuit-
able.
Storage ratios correlated with maximum
standing crops are optimum; those cor-
related with lower standing crops are
suboptimum.
Total dissolved solids (TDS) levels cor-
related with high standing crops of warm-
water fish are optimum; those correlated
.with lower standing crops are suboptimum.
The data used to develop this graph are
primarily from southeastern reservoirs.
Flushing rates correlated with reduced
levels of fry abundance are suboptimal.
High velocities near cover objects will
decrease the amount of usable habitat
around the objects and are thus
considered suboptimum.
19
-------
Table 2. Sample data sets using riverine HSI model.
Variable
% pools Vi
% cover V2
Substrate for V,.
food production
Temperature-Adul t
(° C) V5
Grow-ing season V6
Turbidity (ppm) V7
Dissolved oxygen
(mg/1) V,
Salinity-adult
(ppt) V,
Temperature-Embryos
(°C) Vlo
Sal inity-Embryo
(ppt) VM
Temperature-Fry
(° C) V12
Sal inity-Fry/
Juvenile (ppt) VtJ
Temperature-
Juvenile (° C) Vlt
Velocity V1§
Data set 1
Data SI
60 1.0
50 1.0
silt- 0.7
gravel
28 .1.0
180 0.8
50 1.0
4.5 0.6
< 1 1.0
25 0.8
< 1 1.0
26.5 0.8
< 1 1.0
29 1.0
15 1.0
Data set 2 Data
Data SI Data
90 0.6 15
10 0.4 5
silt- 0.5 sand
sand
32 0.4 22
_
210 0.5 160
4.0 0.5 4.0
< 1 1.0 < 1
21.5 0.5 28.5
< 1 1.0 < 1
32 0.7 23
< 1 1.0 < 1
32 0.7 22
5 1.0 30
set 3
SI
0.5
0.2
0.2
0.5
-
0.8
0.5
1.0
0.5
1.0
0.5
1.0
0.5
0.3
20
-------
Table 2. (concluded)
Variable
Component SI
CF =
CC =
CWQ =
CR =
HSI =
Data set 1
Data SI
0.85
1.00
0.87
0.86
0.88
Data set 2
Data SI
0.45
0.62
0.40*
0.58
0.40*
Data set 3
Data SI
0.20
0.31
0.69
0.47
0.43
*Note: CWQ < 0.4; therefore, HSI = CWQ in Data Set 2.
21
-------
HSI determination.
HSI = (CF x Cc x CWQ* x CR2 x CQT)1/7 , or
If Cwn or CR is £ 0.4, then the HSI equals the lowest of the
following: CWQ, CR, or the above equation.
Sample data sets using lacustrine HSI model are listed in Table 3.
Interpreting Model Outputs
The proper interpretation of the HSI produced by the models is one of
comparison. If two water bodies have large differences in HSI's, then the one
with the higher HSI should be able to support more catfish than the water body
with the lower HSI, given that the model assumptions have not been violated.
The actual differences in HSI that indicate a true difference in carrying
capacity are unknown .and likely to be high. We have aggregated a large number
of variables into a single index with little or no quantitative information on
how the variables interact to effect carrying capacity. The probability that
we have made an error in our assumptions on variable interactions is high.
However, we believe the model is a reasonable hypothesis of how the selected
variables interact to determine carrying capacity.
Before using the model, any available statistical models, such as those
described under model 3 in the next section, should be examined to determine
if they better meet the goals of model application. Statistical models are
likely to be more accurate in predicting the value of a dependent variable,
such as standing crop, from habitat related variables than the HSI models
described above. A statistical model is especially useful when the habitat
variables in the data set used to derive the model have values similar to the
proposed model application site. The HSI models described above may be most
useful when habitat conditions are dissimilar to the statistical model data
set or it is important to evaluate changes in variables not included 1n the
statistical model.
The sample data sets consist of different variable values (and their
corresponding SI score), which although not actual field measurements, are
thought to represent realistic conditions that could occur ,in various channel
catfish riverine or lacustrine habitats. We believe the HSI's calculated from
the data reflect what carrying capacity trends would be in riverine or lacus-
trine habitats with the characteristics listed in the respective data sets.
22
-------
Table 3. Sample data.sets using lacustrine HSI model.
Variable
% cover V2
% littoral area V3
Temperature-Adult
(° C) V5
Growing season V(
Turbidity V7
Dissolved oxygen V,
Salinity-Adult
(ppt) V,
Temperature-Embryo
(° C) V1B
Salinity- Embryo
(ppt) Vn
Temperature-Fry
(° C) Vlt
Salinity- Fry/
Juvenile (ppt) V|,
Temperature-
Juvefiile (° C) V»»
Storage ratio VJS
TDS (ppm) V,,
Data set 1
Data SI
50 1.0
40 1.0
26 1.0
180 0.8
175 0.7
4.5 0.6
< 1 1.0
25 0.8
< 1 1.0
26.5 0.8
< 1 1.0
29 1.0
1.5 0.9
200 1.0
Data set 2 Data
Data SI Data
10 0.4 5
20 0.7 70
20 0.3 33
_
210 0.5 250
4.5 0.6 2.5
< 1 1.0 < 1
21.5 0.5 28
< 1 1.0 < 1
32 0.7 23
< 1 1.0 < 1
32 0.7 22
.3 0.7 0.8
300 1.0 600
set 3
SI
0.2
0.6
0.2
-
0.3
0.2
1.0
0.5
1.0
0.5
1.0
0.5
1.0
0.6
Flushing rate
while fry
present (days) V17 15 1.0 4 0.4 11 1.0
23
-------
Table 3. (concluded)
Variable
Component SI
c -
LF
CC =
CWQ =
CR =
COT =
HSI =
Data set 1
Data SI
1.00
1.00
0.82
0.83
0.95
0.89
Data set 2
Data SI
0.70
0.52
0.30*
0.56
0.55
0.30*
Data set 3
Data SI
0.47
0.33
0.20*
0.20
1.00
0.20*
*Note: Cwo $ 0.4; therefore, HSI = CWQ in Data Sets 2 and 3.
ADDITIONAL HABITAT MODELS
Model 1
Optimal riverine habitat for channel catfish is characterized by the
following conditions, assuming water quality is adequate: warm, stable water
temperatures (summer temperatures of 25-31° C); an approximate 40-60% area of
deep pools; and .abundant cover in the form of logs, boulders, cavities, and
debris (> 40% of pool area).
UQT = number °f above criteria present
24
-------
Model 2
Optimal lacustrine habitat for channel catfish is characterized by the
following conditions, assuming water quality is adequate: warm, stable water
temperatures (summer temperatures of 25-30° C); large surface area (> 500 ha);
moderate to high fertility (IDS 100-350 ppm); clear to moderate turbidities
(< 100 JTU); and abundant cover (> 40?o in areas < 5 m deep).
MPT _ number of above criteria present
0
Mqdel__3
Use the reservoir standing crop regression equations for catfishes pre-
sented by Aggus and Morais (1979) to predict standing crop, then divide the
predicted standing crop by the highest standing crop value used to develop the
regression equation, in order to obtain an HSI.
REFERENCES CITED
Aggus, L. R., and D. I. Morais. 1979. Habitat suitability index equations
for reservoirs based on standing crop of fish. Nat!. Reservoir Res.
Program. Rept. to U.S. Fish Wild!. Serv., Hab. Eval. Proj., Ft. Collins,
CO. 120 pp.
Allen, K. 0., and J. W. Avault. 1970. The effect of salinity on growth of
channel catfish. Proc. Southeastern Assoc. Game and Fish Commissioners
23:319-331.
Allen, K. 0., and K. Strawn. 1968. Heat tolerance of channel catfish,
Ictalurus punctatus. Proc. Southeastern Assoc. Game and Fish
Commissioners 21:399-411.
Andrews, J. W., and R. R. Stickney. 1972. Interactions of feeding rates and
environmental temperature on g.rowth, food conversion and body composition
of channel catfish. Trans. Am. Fish. Soc. 101(1):94-99.
Andrews, J. W., L. H. Knight, and T. Murai. 1972. Temperature requirements
for high density rearing of channel catfish from fingerlings to market
size. Prog. Fish-Cult. 34:240-242.
Andrews, J. W., T. Murai, and G. Gibbons. 1973. The influence of dissolved
oxygen on the growth of channel catfish. Trans. Am. Fish. Soc.
102(4):835-838.
25
-------
Bailey, R. M., and H. M. Harrison, Jr. 1948. Food habits of the southern
channel catfish (]ctal_yrus lacustris pjJ_ncta_tus) in the Des Moines River,
Iowa. Trans. Am. Fish. Soc.~75:110-l"38. ~
Biesinger, K. E., R. B. Brown, C. R. Bernick, G. A. Flittner, and K. E. F.
Hokanson. 1979. A national compendium of freshwater fish and water
temperature data. Vol. I. U.S. Environ. Protection Agency Rep., Environ.
Res. Lab., Duluth, Minn. 207 pp.
Brown, B. E., I. Inman, and A. Jearld, Jr. 1970. Schooling and shelter
seeking tendencies in fingerling catfish behavior. Trans. Am. Fish. Soc.
99(3):540-545.
Brown, L. 1942. Propagation of the spotted channel catfish (Ictalurus
lacustris punctatus). Trans. Kansas Acad. Sci. 45:311-314.
Bryan, C. F., F. M. Truesdale, and D. S. Sabins. 1975. A limnological survey
of the Atchafalaya Basin, annual report. Louisiana Coop. Fish. Res.
Unit, Baton Rouge. 203 pp.
Buck, H. D. 1956. Effects of turbidity on fish and fishing. Trans. N. Am.
Wild!. Conf. 21:249-261.
Carlander, K. C. 1969. Channel catfish. Pages 538-554 j_n Handbook of fresh-
water fishes of the United States and Canada, exclusive of the
Perciformes. Iowa State Univ. Press, Ames. 752 pp.
Carlson, A. R., R. E. Siefert, and L. J. Herman. 1974. Effects of lowered
dissolved oxygen concentrations on channel catfish (Ictalurus punctatus)
embryos and larvae. Trans. Am. Fish. Soc. 103(3):623-626.
Chen, T. H. 1976. Cage culture of channel catfish in a heated effluent from
a power plant, Thomas Hill reservoir. Ph.D. Dissertation, Univ. Missouri,
Columbia. 98 pp.
Clemens, H. P., and K. E. Sneed. 1957. Spawning behavior of channel catfish,
Ictalurus punctatus. U.S. Fish Wildl. Serv. Spec. Sci. Rep.-Fish. 219.
11 PP.
Cowardin,, L. M., V. Carter, F. C. Golet, and E. T. LaRoe. 1979. Classifica-
tion of wetlands and deepwater habitats of the United States. U.S.D.I.
Fish and Wildlife Service. FWS/OBS-79/31. 103 pp.
Cross, F. B., and J. T. Collins. 1975. Fishes in Kansas. Univ. Kansas Mus.
Nat. Hist. Publ. Educ. Ser. 3. 180 pp.
Davis, J. 1959. Management of channel catfish in Kansas. Univ. Kansas Mus.
Nat. Hist. Misc. Publ. 21. 56 pp.
Davis, J. T., and L. E. Posey, Jr. 1958. Length at maturity of channel
catfish (Ictalurus .lacustris)' in Louisiana. Proc. Southeastern Assoc.
Game and Fish. Commissioners" 21:72-74.
26
-------
Finnell, J. C., and R. M. Jenkins. 1954. Growth of channel catfish in
Oklahoma waters: 1954 revision. Oklahoma Fish. Res. Lab., Rept. 41.
37 pp. (Cited in Miller 1966.)
Hynes, H. B. N. 1970. The ecology of running waters. Univ. Toronto Press,
Canada. 555 pp.
Jenkins, R. M. 1970. The influence of engineering design and operation and
other environmental factors on reservoir fishery resources. Water
Resources Bull. 6(1):110-119.
Jenkins, R. M. 1974. Reservoir management prognosis: migraines or miracles.
Proc. Southeastern Assoc. Game and Fish Commissioners 27:374-385.
Jenkins, R. M. 1976. Prediction of fish production in Oklahoma reservoirs on
the basis of environmental variables. Ann. Oklahoma Acad. Sci. 5:11-20.
Jenkins, R. M., and D. I. Morais. 1971. Reservoir sport fishing effort and
harvest in relation to environmental variables. Pages 371-384 j_n G. E.
Hall, ed. Reservoir fisheries and limnology. Am. Fish. Soc.Spec
Publ. 8.
Jester, D. B. 1971. Effects of commercial fishing, species introductions,
and drawdown control on fish populations in Elephant Butte Reservoir, New
Mexico. Pages 265-285 jjn G. E. Hall, ed. Reservoir fisheries and
limnology. Am. Fish. Soc. Spec. Publ. 8.
Lawler, R. E. 1960. Investiqations of the channel catfish of Utah Lake. Utah
State Dept. Fish Game. Inform. Bull. 60-8. 69 pp.
Leidy, G. R., and R. M. Jenkins. 1977. The development of fishery compart-
ments and population rate coefficients for use in reservoir ecosystem
modeling. Contract Report Y-77-1, prepared for Office, Chief of
Engineers, U.S. Army, Washington, D.C. 72 pp.
Macklin, R., and S. Soule. 1964. Feasibility of establishing a warmwater
fish hatchery. Calif. Fish .Game, Inland Fish. Admin. Rept. 64-14.
13 pp. (Cited in Miller 196.6.)
Marzolf, R. C. 1957. The reproduction of channel catfish in Missouri ponds.
J.'wil'dl.'Manage. 21(l):22-28.
McCall, T. C. 1977. Movement of channel catfish, Ictalurus punctatus. in
Cholla Lake, Arizona, as determined by ultrasonic tracking. Western
Assoc. Game Fish. Comm. 57:359-366.
McCammon, G. W. 1956. A tagging experiment with channel catfish (Ictalurus
punctatus) in the lower Colorado River. Calif. Fish Game 42(4):323-335.
McCammon, G. W., and D. A. LaFaunce. 1961. Mortality rates and movement In
the channel catfish population of the Sacramento Valley. Calif. Fish
Game 47(l):5-26.
27
-------
Hiller, E. E. 1966. Channel catfish. Pages 440-463 in A. Calhoun, ed.
Inland fisheries management. Calif. Fish Game Res. Agency, Sacramento.
546 pp.
Minckley, W. L. 1973. Fishes of Arizona. Arizona Fish Game Publ., Phoenix.
293 pp.
Moore, G. A. 1968. Vertebrates of the United States. McGraw-Hill, New York.
Moss, D. D., and D. C. Scott. 1961. Dissolved oxygen requirements of three
species of fish. Trans. Am. Fish. Soc. 90(4):377-393.
Perry, W. G. 1973. Notes on the spawning of blue and channel catfish in
brackish water ponds. Prog. Fish-Cult. 35(3):164-166.
Perry, W. G., and J. W. Avault. 1968. Preliminary experiments on the culture
of blue, channel, and white catfish in brackish water ponds. Proc.
Southeastern Assoc. Game and Fish Commissioners 22:396-406.
Pflieger,. W. L. 1971. A distributional study of Missouri fishes. Univ.
Kansas Mus. Nat. Hist. Publ. 20(3) -.225-570.
Pflieger, W. L. 1975. Fishes of Missouri. Missouri Dept. Conserv. Publ.,
Columbia. 343 pp.
Randolph, K. N., and H. P. Clemens. 1976. Some factors influencing the
feeding behavior of channel catfish in culture ponds. Trans. Am. Fish.
Soc. 105(6):718-724.
Ryder, R. A. 1965. A method for estimating the potential fish production of
north-temperate lakes. Trans. Am. Fish. Soc. 94(3):214-218.
Ryder, R. A., S. R. Kerr, K. H. Loftus, and H. A. Regier. 1974. The morpho-
edaphic index, a fish yield estimator - review and evaluation. J. Fish.
Res. Board Can. 31(5):663-688.
Scott, W. B., and E. J. Grossman. 1973. Freshwater fishes of Canada. Fish.
Res. Board Can. Bull. 184. 966 pp.
Shrable, J. B., 0. W. Tiemeier, and C. W. Deyoe. 1969. Effects of temperature
on rate of digestion by channel catfish. Prog. Fish-Cult. 31(3):131-138.
Sigler, W. F., and R. R. Miller.- 1963. Fishes of Utah. Utah Fish Game, Salt
Lake City. 203 pp.
Simco, D. A., and F. B. Cross. 1966. Factors affecting growth and production
of channel catfish, Ictalurus punctatus. Univ. Kansas Mus. Nat. Hist.
Publ. 17(4):191-256.
Starostka, V. J., and W. R. Nelson. 1974. Channel catfish in Lake Oahe. U.S.
Fish Wild!. Senv. Tech. Pap. 81. 13 pp.
28
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Stauffer, J. R., Jr., K. L. Dickson, J. Cairns, Jr., W. F. Calhoun, M. T.
Masnik, and R. H. Myers. 1975. Summer distribution of fish species in
the vicinity of a thermal discharge, New River, Virginia. Arch.
Hydrobiol. 76(3):287-301.
Trautman, M. B. 1957. Fishes of Ohio. Ohio State Univ. Press. 683 pp.
Walburg, C. H. 1971. Loss of young fish in reservoir discharge and year-class
survival, Lewis and Clark Lake, Missouri River. Pages 441-448 i_n G. E.
Hall, ed. Reservoir fisheries and limnology. Am. Fish. Soc. Spec.
Publ. 8.
Walburg, C. H. 1975. Food of young-of-year channel catfish in Lewis and
Clark Lake, a Missouri River reservoir. Am. Midi. Nat. 93(1):218-221.
Walden, H. T. 1964. Familiar freshwater fishes of America. Harper and Row,
New York. 324 pp.
West, B. W. 1966. Growth, food conversion, food consumption and survival at
various temperatures of the channel catfish, Ictalurus punctatus
(Rafinesque). M.S. Thesis. Univ. Arkansas, Fayettevi1le. (Cited in
Shrable et al. 1969.)
Ziebell, C. 1973. Ultrasonic transmitters for tracking channel catfish.
Prog. Fish-Cult. 35(l):28-32.
29
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APPENDIX B-l. NATIONAL LIST OF OMNIVORE FISH SPECIES.
Common name
Gizzard.shad
Threadfin shad
Central mudminnow
Eastern mudminnow
Mexican tetra
Longfin dace
Goldfish
Grass carp
Common carp
Silverjaw minnow
Alvord chub
Utah chub
Tui chub
Blue chub
Sonora chub
Yaqui chub
Speckled chub
Blotched chub
California roach
Virgin spinedace
Hardhead
Bluehead chub
Golden shiner
White shiner
Common shiner
Bigmouth shiner
Blacknose shiner
Spottail shiner
Swallowtail shiner
Sand shiner
Skygazer shiner
Mimic shiner
Black side dace
Northern redbelly dace
Southern redbelly dace
Bluntnose minnow
Fathead minnow
Blacknose dace
Speckled dace
Redside shiner
Creek chub
River carpsucker
Quill back
Highfin carpsucker
Utah sucker
Longnose sucker
Bluehead sucker
Owens sucker
Flannelmouth sucker
Largescale sucker
Sacramento sucker
Latin name
Dorosoma cepedianum
Dorosoma petenense
Umbra limi
Umbra pygmaea
Astyanax tetra
Agosia chrysogaster
Carassius auratus
Ctenopharyngodon idel la
Cyprinus carpio
Ericymba buccata
Gil a alvordensis
Gil a atravia
Gil a bicolor
Gila coerulea
Gil a ditaenia
Gila purpurea
Hybopsis aestivalis
Hybopsis insignis
Lavinia symmetricus
Lepidomeda mollispinis
Mylopharodon conocephalus
Nocomis leptocephalus
Notemigonus crysoleucas
Notropis albeolus
Notropis cornutus
Notropis dorsal is
Notropis heterolepis
Notropis hudsonius
Notropis procne
Notropis stramineus
Notropis uranoscopus
Notropis volucellus
Phoxinus cumberlandensis
Phoxinus eos
Phoxinus erythrogaster
Pimephales notatus
Pimephales promelas
Rhtnichthys atratulus
Rhinichthys osculus
Richardsonius balteatus
Semotilus atromaculatus
Carpiodes carpio
Carpiodes cyprinus
Carpiodes velifer
Catostomus ardens
Catostomus catostomus
Catostomus discobolus
Catostomus fumeiventris
Catostomus latipinnis
Catostomus macrocheilus
Catostomus occidental is
-------
Mountain sucker Catostomus platyrhyncus
Rio grande sucker Catostomus plebeius
Tahoe sucker Catostomus tahoensis
Blue sucker Cycleptus elongatus
Smallmouth buffalo Ictiobus bubalus
Black buffalo Ictiobus niger
Oriental weatherfish Misgurnus anguillicaudatus
Snail bullhead Ictalurus brunneus
Black bullhead Ictalurus melas
Yellow bullhead Ictalurus natalis
Flat bullhead Icalurus platycephalus
Channel catfish Ictalurus punctatus
Walking catfish Clarias batrachus
Chinese catfish Clarias fuscus
Desert pupfish Cyprinodon macularius
Sheepshead minnow Cyprinodon variegatus
Plains killifish Fundulus zebrinus
Porthole livebearer Poeciliopsis gracilis
Gila topminnow Poeciliopsis occidentalis
Pinfish Lagodon rhomboides
Black acara Cichlasoma bimaculatum
Rio grande perch Cichlasoma cyanoguttatum
Firemouth Cichlasoma meeki
Jewel fish Hemichromis bimaculatus
Mozambique tilapia Tilapia mossambica
Redbelly tilapia Tilapia zilli
Shiner perch Cymatogaster aggregata
-------
APPENDIX B-2. NATIONAL LIST OF TOP CARNIVORE FISH SPECIES.
Common name Latin name
Bull shark
Alligator gar
Spotted gar
Longnose gar
Florida gar
Shortnose gar
Bowfin
Machete
Ladyfish
Tarpon
Skipjack herring
Hickory shad
Pink salmon
Chum salmon
Coho salmon
Sockeye salmon
Chinook salmon
Golden trout
Arizona trout
Cutthroat trout
Rainbow trout
Atlantic salmon
Brown trout
Arctic char
Bull trout
Brook trout
Dolly varden
Lake trout
Inconnu
Redfin pickerel
Grass pickerel
Northern pike
Muskellunge
Chain pickerel
Sacramento squawfish
Colorado squawfish
Northern squawfish
Umpqua squawfish
Flathead catfish
Burbot
Fat snook
Tarpon snook
Snook
White bass
Striped bass
Yellow bass
Rock bass
Roanoke bass
Redeye bass
Small mouth bass
Suwanee bass
Carcharhinus leucas
Atractosteus spatula
Lepisosteus oculatus
Lepisosteus osseus
Lepisosteus platyrhincus
Lepisosteus platostomus
Ami a calva
Elops affinis
Elops saurus
Megalops atlanticus
Alosa chrysochloris
Alosa mediocris
Oncorhynchus gorbuscha
Oncorhynchus keta
Oncorhynchus kisutch
Oncorhynchus nerka
Oncorhynchus tshawytscha
Salmo aguabonita
Salmo apache
Salmo clarki
Salmo gairdneri
Salmo salar
Salmo trutta
Salvelinus alpinus
Salvelinus confluentus
Salvelinus fontinalis
Salvelinus malma
Salvelinus namaycush
Stenodus leucichthys
Esox americanus americanus
Esox americanus vermiculatus
Esox lucius
Esox masquinongy
Esox niger
Ptychocheilus grandis
Ptychocheilus lucius
Ptychocheilus oregonensis
Ptychocheilus umpquae
Pylodictis olivaris
Lota lota
Centropomus parallelus
Centropomus pectinatus
Centropomus undecimalis
Morone chrysops
Morone saxatilis
Morone mississippiensis
Ambloplites rupestris
Ambloplites cavifrons
Micropterus coosae
Micropterus dolomieui
Micropterus notius
-------
Spotted bass Micropterus punctulatus
Largemouth bass Micropterus salmoides
Guadalupe bass Micropterus treculi
White crappie Pomoxis annularis
Black crappie Pomoxis nigromaculatus
Yellow perch Perca flavescens
Sauger Stizostedion canadense
Walleye Stizostedion vitreum
Gray snapper Lutjanus griseus
Freshwater drum Aplodinotus grunniens
Spotted seatrout Cynoscion nebulosus
Red drum Sciaenops ocellatus
Goldeye Hiodon alosoides
White catfish Ictalurus catus
Blue catfish Ictalurus furcatus
Tucunare Cichla ocellaris
Snakehead Channa striata
-------
APPENDIX C. NATIONAL LIST OF INTOLERANT FISH SPECIES.
Common name
Cisco
Arctic cisco
Lake whitefish
Bloater
Kiyi
Bering cisco
Broad whitefish
Humpback whitefish
Shortnose cisco
Least cisco
Shortjaw cisco
Pink salmon
Chum salmon
Coho salmon
Sockeye salmon
Chinook salmon
Pygmy whitefish
Round whitefish
Mountain whitefish
Golden trout
Arizona trout
Cutthroat trout
Rainbow trout
Atlantic salmon
Brown trout
Arctic char
Bull trout
Brook trout
Dolly varden
Lake trout
Inconnu
Arctic grayling
Largescale stoneroller
Redside dace
Cutlips minnow
Bigeye chub
River chub
Pallid shiner
Pugnose shiner
Rosefin shiner
Bigeye shiner
Pugnose minnow
Whitetail shiner
Blackchin shiner
Blacknose shiner
Spottail shiner
Sailfin shiner
Tennessee shiner
Yellowfin shiner
Ozark minnow
Ozark shiner
Latin name
Coregonus artedii
Coregonus autumnal is
Coregonus clupeaformis
Coregonus hoyi
Coregonus kiyi
Coregonus laurettae
Coregonus nasus
Coregonus pidschian
Coregonus reighardi
Coregonus sardinella
Coregonus zenithicus
Oncorhynchus gorbuscha
Oncorhynchus keta
Oncorhynchus kisutch
Oncorhynchus nerka
Oncorhnchus tshawytscha
Prosopium coulteri
Prosopium cylindraceum
Prosopium williamsoni
Salmo aguabonita
Salmo apache
Salmo clarki
Salmo gairdneri
Salmo salar
Salmo trutta
Salvelinus alpinus
Salvelinus confluentus
Salvelinus fontinalis
Salvelinus malma
Salvelinus namaycush
Stenodus leucichthys
Thymallus arcticus
Campostoma oligolepis
Clinostomus elongatus
Exoglossum maxillingua
Hybobsis amblops
Nocomis micropogon
Notropis amnis
Notropis anogenus
Notropis ardens
Notropis boops
Noropis emiliae
Notropis galacturus
Notropis heterodon
Notropis heterolepis
Noropis hudsonius
Notropis hypselopterus
Notropis leuciodus
Notropis lutipinnis
Notropis nubilus
Notropis ozarcanus
-------
Silver shiner
Duskystripe shiner
Rosyface shiner
Safron shiner
Flagfin shiner
Telescope shiner
Topeka shiner
Mimic shiner
Steel col or shiner
Coosa shiner
Bleeding shiner
Bandfin shiner
Blackside dace
Northern redbelly dace
Southern redbelly dace
Blacknose dace
Pearl dace
Alabama hog sucker
Northern hog sucker
Roanoke hog sucker
Spotted sucker
Silver redhorse
River redhorse
Black jumprock
Gray redhorse
Black redhorse
Rustyside sucker
Greater jumprock
Blacktail redhorse
Torrent sucker
Striped jumprock
Greater redhorse
Ozark madtom
Elegant madtom
Mountain madtom
Slender madtom
Stonecat
Black madtom
Least madtom
Margined madtom
Speckled madtom
Brindled madtom
Frecklebelly madtom
Brown madtom
Roanoke bass
Ozark rock bass
Rock bass
Longear sunfish
Darters
Darters
Darters
Sculp^ns
O'opu alamoo (goby)
O'opu nopili (goby)
O'opu nakea (goby)
Notropis photogenis
Notropis pilsbryi
Notropis rubellus
Notropis rubricroceus
Notropis signipinnis
Notropis telescopus
Notropis topeka
Notropis volucellus
Notropis whipplei
Notropis xaenocephalus
Notropis zonatus
Notropis zonistius
Phoxinus cumberlandensis
Phoxinus eos
Phoxinus erythrogaster
Rhinichthys atratulus
Semotilus margarita
Hypentelium etowanum
Hypentelium nigricans
Hypentelium roanokense
Minytrema melanops
Moxostoma anisurum
Moxostoma carinatum
Moxostoma cervinum
Moxostoma congestum
Moxoatoma duquesnei
Moxostoma hamiltoni
Moxostoma lachneri
Moxostoma poecilurum
Moxostoma rhothoecum
Moxostoma rupiscartes
Moxostoma valenciennesi
Noturus albater
Noturus elegans
Noturus eleutherus
Noturus exilis
Noturus flavus
Noturus funebn's
Noturus hildebrandi
Noturus insignis
Noturus leptacanthus
Noturus miurus
Noturus munitus
Noturus phaeus
Ambloplites cavifrons
Ambloplites constellatus
Ambloplites rupestris
Lepomis megalotis
Ammocrypta sp.
Etheostoma sp.
Percina sp.
Cottus sp.
Lentipes concolor
Sicydium stimpsoni
Awaous stamineus
*U.s. GOVERNMENT PRINTING OFFICE:
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