HABITAT SUITABILITY INFORMATION:

YELLOW PERCH

SK

361

. U54

no. 82-

10 .55

and Wildlife Service

Department of the Interior
FWS/OBS-82/10.55

December 1983

HABITAT SUITABILITY INFORMATION: YELLOW PERCH

by

Douglas A. Krieger

Colorado Division of Wildlife

317 West Prospect

Fort Collins, CO 80526

James W. Terrell

Habitat Evaluation Procedures Group

Western Energy and Land Use Team

U.S. Fish and Wildlife Service

Drake Creekside Building One

2627 Redwing Road

Fort Collins, CO 80526-2899

Patrick C. Nelson

Instream Flow and Aquatic Systems Group

Western Energy and Land Use Team

U.S. Fish and Wildlife Service

Drake Creekside Building One

2627 Redwing Road

Fort Collins, CO 80526-2899

Performed for

Western Energy and Land Use Team

Division of Biological Services

Research and Development

Fish and Wildlife Service

U.S. Department of the Interior

Washington, DC 20240
This report should be cited as:

Krieger, D. A., J. W. Terrell, and P. C. Nelson. 1983. Habitat suitability

information: Yellow perch. U.S. Fish Wildl. Servo FWS/OBS-83/10.55.

37 pp.
PREFACE

The habitat use information and Habitat Suitabil ity Index (HSI) model s

presented in this document are an aid for impact assessment and habitat management activities. Literature concerning a species' habitat requirements and

preferences is reviewed and then synthesized into subjective 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. Also included is a brief discussion of Suitability Index (SI)

curves as used in the Instream Flow Incremental Methodology (IFIM), and a discussion of SI curves available for the IFIM analysis of yellow perch habitat.

Use of the mode 1s presented in thi s pub1i cati on for impact assessment

requires the setting of clear study objectives, and the selection of the

correct model variables to meet those objectives. Methods for reducing model

complexity and recommended measurement techniques for model variables are

presented in Terrell et a1. (1982).1 A di scussi on of HSI model buil di ng

technologies is presented in U.S. Fish and Wildlife Service (1981).2

The HSI models presented herein are hypotheses of species-habitat relationships, not statements of proven cause and effect relationships. Results

of model performance tests, when available, are referenced; however, models

that have demonstrated reliability in specific situations may prove unreliable

in others. For this reason, the U.S. Fish and Wildlife Service 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

Western Energy and Land Use Team

U.S. Fish and Wildlife Service

2627 Redwing Road

Fort Collins, CO 80526-2899

lTerre11, J. W., T. E. McMahon, P. D. Inskip, R. F. Raleigh, and K. L.

Williamson. 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 Wildl. Servo FWS/OBS-82/10.A. 54 pp.

2U.S. Fish and Wildife Service.

habitat suitability index models.

Ecol. Servo n.p.

1981. Standards for the development of

103 ESM. U.S. Fish Wildl. Serv., Div.

iii
iv
CONTENTS

Page

PREFACE iii

FIGURES vi

TABLES vi i

ACKNOWLEDGMENTS vi i i

HABITAT USE INFORMATION 1

Genera 1 1

Age I Growth I and Food 1

Reproduct ion 1

Specific Habitat Requirements..................................... 2

HABITAT SUITABILITY INDEX (HSI) MODELS 4

Model Applicability 4

Model Description - Riverine...................................... 4

Mode 1 Descri pt ion - Lacustri ne 6

Suitability Index (SI) Graphs for Model Variables 8

Application of Lacustrine Model to Reservoir Sites 17

Interpreti ng Model Outputs 17

ADDITIONAL HABITAT MODELS ".................................. 22

Mode 1 1 22

Model 2 22

Model 3 22

Model 4 22

INSTREAM FLOW INCREMENTAL METHODOLOGY (IFIM) 23

Suitability Index Graphs as Used in IFIM 23

Availability of Graphs for Use in IFIM 25

REFERENCES 32

v
FIGURES

Number

1 Tree diagram illustrating relationships between model variables, components (life requisites) and HS1 for the riverine

yellow perch model............................................ 5

2 Tree diagram illustrating relationships between model variables, components (life requisites) and HS1 for the lacustrine

yellow perch model 7

3 Category one SI curves for yellow perch spawning habitat 27

4 Category two SI curves for yellow perch fry 29

5 Category two SI curves for yellow perch juveniles 30

6 Category two SI curves for yellow perch adults 31

vi
Number

Page

1

2

3

4

5

6

7

TABLES

Trophi c status cri teri a .

Sources of information and assumptions for construction of

suitabi 1i ty index graphs .

Environmental data for Chatfield Reservoir, Colorado .

Environmental data for Stalker Lake, Colorado .

Environmental data for Jacassee Reservoir, South Carolina ....

Environmental data for Keowee Reservoir, South Carolina .

Availability of curves for IFIM analysis of yellow perch

habitat .

vii

12

13

18

19

20

21

26
ACKNOWLEDGMENTS

We would like to thank J. P. Clugston, J. L. Forney, and J. L. Oliver for

reviewing the manuscript. They provided many helpful comments, but the reader

should not assume that they endorse the models presented in this manuscript.

J. P. Clugston and J. L. Oliver also provided unpublished data on habitat

conditions in Lakes Keowee and Jocassee. C. J. Short provided editorial

assistance. Word processing was provided by C. J. Gulzow and D. E. Ibarra.

K. Twomey assisted in finalizing the manuscript. Cover art is from Freshwater

Fishes of Canada 1973, Bulletin 184, Fisheries Research Board of Canada by W.

B. Scott and E. J. Crossman.

viii
YELLOW PERCH (Perca flavescens)

HABITAT USE INFORMATION

General

The native distribution of yellow perch (Perca flavescens) extends from

Nova Scotia south to Georgia and west to the~sissippi, and in Canada,

across Onta ri 0, centra 1 Mani toba, and Saskatchewan to Great Slave Lake (Scott

and Crossman 1973; Collette and Banarescu 1977). The range has been extended

by introductions to include areas in the United States south to Florida and

Alabama (Clugston et al. 1978), most States west of the Mississippi to the

Pacific coast, and as far north as British Columbia (S~ott and Crossman 1973;

Collette and Banarescu 1977).

Age, Growth, and Food

In Canadian and northern United States waters, female yellow perch mature

at 3-4 years of age, one year later than males (Herman et al. 1964; Scott and

Crossman 1973). Maximum age is usually 9-10 years. Few fish live longer than

5 years in southern reservoirs (Clugston et al. 1978).

Yellow perch larvae (6 mm) feed on copepod nauplii, cyclopoid copepods

and cladocerans (Siefert 1972; Kelso and Ward 1977) including Diaptomus and

Diaphanosoma (Oliver, in press). Fry survival, and ultimately year-class

strength, are dependent on a plentiful supply of zooplankton at the onset of

feeding (Kelso and Ward 1977). Turbidity may lower visibility of prey and

restrict zooplankton to upper water strata, where they are unavailable to

feeding young (El-Zarka 1959). After becoming bottom dwelling in the littoral

areas, juveniles feed on amphipods, ostracods, and chironomid larvae. Larger

yellow perch (> 120 mm) prey on aquatic insects, fish, and crayfish (Ward and

Robinson 1974; Kelso and Ward 1977). Collette et al. (1977) concluded that

the composition of the diet is determined more by the relative availability of

different prey types than by preference for certain prey types.

Reproduction

Yellow perch begin spawning migrations from deep water into tributaries,

lake shallows, or low velocity areas of rivers from April to June when water

temperatures reach 7-13 0 C (Harrington 1947; Wells 1968; Scott and Crossman

1973). Photoperi od (Hergenrader 1969), ri si ng water temperatures (Amundrud

et al. 1974), and/or completion of maturation (Hokanson 1977) may trigger

1
spawning. Adults must be exposed to an extended period of cold water temperatures to ensure ri peni ng of eggs. A wi nter mi nimum temperature of 10° Cis

near the upper limit for maturation of gonads (Hokanson 1977).

The female releases a gelatinous, semi-bouyant string of eggs near aquatic

or inundated terrestrial vegetation. Rocks, sand, or gravel may be used if

submerged vegetation is not available (Herman et al. 1964; Mansueti 1964;

Scott and Crossman 1973; Clady and Hutchinson 1975). There is no parental

care (Hergenrader 1969; Scott and Crossman 1973).

Year-class strength is positively correlated with the rate of warming

during incubation and hatching (Hartman 1972; Eschenroder 1977). Rising water

level s during spawning season in Missouri River reservoirs led to large year

classes due to increased inundation of terrestrial vegetation (Nel son and

Wa 1burg 1977).

Specific Habitat Requirements

Yellow perch are frequently associated with shoreline (littoral) areas in

lakes and reservoirs where there are moderate amounts of vegetation present

(Herman et al. 1964; Ward and Robinson 1974; Kitchell et al. 1977; Helfman

1979). These areas provide both cover and spawning habitat. Suitable riverine

habitat resembles the lacustrine habitat; i.e., pools and slack water areas

with moderate amounts of vegetation (> 20% of area) (Coots 1956; Kitchell

et al. 1977).

Several laboratory and field studies have examined winter dissolved

oxygen (D.O.) requirements of yellow perch and determined that levels from 0.2

to 1.5 mg/l are lethal (Moore 1942; Cooper and Washburn 1949; Magnuson and

Karlen 1970). At a summer temperature of 26° C, D.O. concentrations below

3.1 mg/l were lethal (Moore 1942). Because these studies were of a short

duration « 5 days), we concluded that a D.O. level of 5 mg/l would be the

lower optimum limit.

Yellow perch are found in brackish water at river mouths [up to 13 ppt in

Chesapeake Bay (Hildebrand and Schroeder 1928)J and in Manitoba lakes with

salinities as high as 10.3 ppt (Driver and Garside 1966). However, they

require freshwater for spawning (Scott and Crossman 1973).

In general, yellow perch are most common in clear water and numbers

decrease with increasing turbidity (Scott and Crossman 1973; Nelson and Walburg

1977). Yellow perch are found in Ontario lakes with a pH range from approximately 3.9 to 9.5 (Johnson et al. 1977). Yellow perch are relatively tolerant

of low pH (Rahel 1983) but reproductive success is reduced in lakes with pH

< 5.5 (Ryan and Harvey 1979). Using Stroud's (1967) criteria for freshwater

fish, it is assumed that the optimum pH ranges from 6.5-8.5.

Adult. Preferred temperatures of adult perch during the growing season

are between 17.6° C and 25.0° C (Ferguson 1958; McCauley and Read 1973) with

19 to 24° C being optimum (Scott and Crossman 1973). Growth is initiated at 6

to 10° C (Nakashima and Leggett 1978; Hokanson 1977). The upper lethal summer

temperature is 32.3° C (Ferguson 1958).

2
Yellow perch adults can be found in moderate currents (Muncy 1962; Manion

1977) but prefer sluggish currents or slack water habitat (Coots 1956; Kitchell

et al. 1977), particularly during spawning (Harrington 1947).

Embryo. Yellow perch egg strands are broadcast in water depths of 1.0 to

3.7 m (Harrington 1947; Herman et al. 1964; Benson 1973; Clady and Hutchinson

1975). Minimum winter water temperatures (4-10° C) should be maintained for

145-175 days to allow for normal gonadal development of adults so that viable

gametes will be produced (Hokanson 1977; Jones et al. 1977). Hokanson and

Kl ei ner (1973) reported that 7-20° C was the temperature range for embryo

incubation and hatching. Temperatures of 10° C, increasing l°/day to 20° C,

are optimum for embryo development.

Spawning occurs in low « 5 cm/s) current velocities (Harrington 1947).

Velocities above 25 cm/s have been found to fragment egg strands in the Klamath

River, California (Coots 1956).

A moderate amount of vegetation in littoral areas (either aquatic or

flooded terrestrial) is important for spawning (Clady and Hutchinson 1975) and

cover (Helfman 1979). Reduction in water levels during spawning may lead to

dessication of eggs (Benson 1973). Drawdown of mainstem Missouri River

reservoirs resulted in the el imination of inundated terrestrial vegetation

used for spawning and a corresponding decrease in perch abundance (Beckman and

Elrod 1971; Nelson and Walburg 1977). Hatching success may be higher in areas

of sparse aquatic vegetation than in areas of very dense vegetation (Forney,

pers. comm.).

Fry. Perch fry are susceptible to a number of environmental factors which~ffect year-class strength. Fry tolerate temperatures from 3.0 to

28.0° C, but they are inactive below 5.3° C, and survival is better at 20° C

than at 10° C (Hokanson 1977). Young fry (before swim bladder formation) have

a tendency to move to warm water areas (Ross et al. 1977).

Fry move to open water duri ng the fi rst two months of 1i fe. Larvae

« 9.5 mm) are unable to maintain position in current velocities greater than

2.5 cm/s (Houde 1969). Clady (1976) determined that larval survival and wind

velocity are inversely related.

Juvenile. Habitat requirements of juvenile perch are similar to those of

adults. Temperatures selected in summer months are in the range of 20-23° C

(McCauley and Read 1973). This range is slightly higher than that for adults,

and juveniles can be expected to inhabit slightly shallower water. The

ultimate upper incipient lethal temperature for yellow perch is between 29.2

and 35° C (Hokanson 1977).

3
HABITAT SUITABILITY INDEX (HSI) MODELS

Model Applicability

Geographic area. The models provided are designed to be applicable

throughout the 48 contiguous United States. The standard of compari son for

each variable is the optimum value of the variable that occurs anywhere within

thi s regi on. Therefore, the models wi 11 never provi de an HSI of 1. 0 when

applied to bodies of water in the far southern portions of this region where

temperature-related variables do not reach the optimum values found in the

northern portion of the region.

Season. The model s provide a rating for a body of water based on its

ability to support a reproducing population of yellow perch throughout the

year.

Cover types. The models are applicable to riverine, lacustrine, and

palustrine habitats, as described by Cowardin et al. (1979).

Verification level. The models provided in this section represent our

interpretation of how some specific environmental factors determine potential

carrying capacity for yellow perch. The reservoir version of the model ranked

the habitat suitability of one pair of reservoirs in similar order as harvest

data while producing low but equal rankings to a pair of reservoirs with low

standing crops. We interpret this to mean that some of the model variables

were important in determining carrying capacity for yellow perch in the

selected reservoirs. The sample size is too small to determine what degree of

accuracy we have obtained in our model. The riverine version of the model has

not been field tested nor applied to field data. We assume that some of the

riverine model variables will also be important in determining carrying

capacity of riverine habitat for yellow perch.

Model Description - Riverine

The structure of the riverine HSI model for yellow perch is represented

in Figure 1.

Food/cover component. Percent pool and backwater area (V2 ) was included

because yellow perch abundance varies with the amount of pools and backwaters

present. We also assumed V2 would be an important measure of food availability

to yellow perch in rivers since these areas are habitat for forage species

utilized by yellow perch. Percent cover in pool and backwater areas (V 3 ) was

included in this component because abundance of perch varies directly with

amount of cover present. Cover consisting of brush, debris, standing timber,

or vegetation should also tend to increase abundance of forage items.

Water quality component. The water quality component is limited to

temperature (V 4 ) , dissolved oxygen (V6 ) , and pH (Va) because these parameters

are commonly measured and have been shown to affect abundance, growth, or

survival. Toxic substances were not considered in this model.

4
Habitat variables Life requisites

% pool and backwater area (V2)~

Food/cover------~

% cover in pool and backwater areas (V 3 )

pH (V8) --------------'

Temperature (V4)----------------~

0; 5501 ved oxygen (V.) 3> Water Qua1; ty ----------4 HS I

Temperature (V5)----------------~

Degree days (4 to 10° C) (V 7) -------------7 Reproduct ion __-F

% cover in pools and

backwaters (V3)----------------~

Figure 1. Tree diagram illustrating relationships between model

variables, components (life requisites) and HSI for the riverine

yellow perch model.

5
Reproduction component. The temperature during embryonic development

(V s ) is critical to reproductive success. Gonadal development also depends on

the duration of low winter temperatures. This is accounted for by V7 , water

temperature degree days when the water is between 4 and 10° C. Area of aquatic

vegetation (V3 ) is included because perch spawn on aquatic vegetation if it is

ava il ab1e.

HSI determination. We assumed that the most limiting factor (i .e.,

lowest SI score) defines the carrying capacity for yellow perch; thus, the HSI

equals the minimum value of suitability indices V2 , V3 , V4 , Vs, V6 , V7 , or Va.

Model Description - Lacustrine

The structure of the lacustrine HSI model for yellow perch is represented

in Figure 2.

Food/cover component. Percent of littoral area (V1 ) and percent cover in

1ittora 1 area (V 3) were inc 1uded becau se abundance of ye 11 ow perch has been

shown to vary with the percent of littoral area and with the percent of cover

within the littoral zone. These variables also provide a measure of the

habitat available for the insects and small fish used as forage by yellow

perch.

Water quality component. This includes the same variables (V4 , V6 , and

Va) as presented in the riverine model description.

Reproduction component. Percent cover in littoral area (V3 ) was included

because yellow perch deposit eggs in shallow areas with cover. Temperature

(V s ) was included because it affects spawning and embryo development. Degree

days between 4 and 10° C (V7 ) was included because it affects the ability of

perch to produce viable gametes.

Other component.

yellow perch has often

body.

Trophic status (Vg ) was included because abundance of

been related to trophic conditions present in a water

HSI determination.

lowest SI score) defines

equals the minimum value

Vg •

We assumed that the most limiting factor (i .e.,

the carrying capacity for yellow perch; thus, the HSI

of suitability indices V1 , V3 , V4 , v.. V6 , V7 , ».. or

6
Habitat variables Life requisites

% 1ittoral area (V 1 ) ------~

% cover in littoral area (V3 ) ------~

Food/Cover ---"""'

pH (Va) ----------"

Temperature (V4)-------------~

Dissolved oxygen (V,) :=> Water Qual ity ---------7HSI

Trophic status (V g ) -----------Other------'

% cover in littoral area (V3)~

Temperature (Vs ) Reproduction--~

Degree days (4 to 10° C) (V 7 )

Figure 2. Tree diagram illustrating relationships between model

variables, components (life requisites) and HSI for the lacustrine

yellow perch model.

7
Suitability Index (SI) Graphs for Model Variables

Variables may pertain to either a riverine (R) habitat, a lacustrine (l)

habitat, or both. Tables 1 and 2 list the information sources and assumptions

used in constructing each SI graph.

Habitat Variable

Percent littoral area

during summer.

Percent pool and backwater areas during

average summer flow.

8

Suitability Graph

1.0

x

(lJ

-0

c 0.8 ......

-+J

...... 0.6 ......

.D

ro

-+J 0.4 ......

=' (/)

0.2

0.0

10 20 30 40 >50

%

1.0

x 0.8 (lJ

-0

C

...... 0.6

......

r-

...... 0.4

.D

ro

-+J 0.2 ......

=' (/)

0.0

0 20 40 60 80 100

%
R,L

V3 Percent cover (e.g., 1.0

vegetation, brush,

debris, or standing 0.8 timber) during summer ><

Q) within pools, backwater "'0

I::

areas (R), and 1i ttora

1 ....... 0.6

areas (L). >,

+-l

...... 0.4 ......

.0

ttl

+-l

...... 0.2 ::l

t/)

0.0

%

R,L

V4 Most suitable water temp- 1.0

erature within the water

column during midsummer.

>< 0.8 Use the measured temper- Q)

ature which gives the I::

highest SI (adult, ....... 0.6

juvenile, fry). To

estimate, determine ......

:;: 0.4

a temperature profile, .0

and select the temper- ttl

+-l 0.2 ature that gives the ......

::l

highest SI. t/)

0.0

5 10 15 20 25 30

°C

R,L

Vs Most suitable water temp- 1.0

eratures within pools,

backwaters, and littoral >< 0.8

areas during spawning Q)

"'0

and embryo development. I::

.......

Use 0.6 the temperature >,

which gives the highest +-l

...... SI (embryo) within the ...... 0.4

above locations. .0

ttl

+-l

......

::l 0.2 t/)

0.0

a

4

8 12 16 20

°C

9
R,L V6 Minimum dissolved 1.0

oxygen level at

the two locations

>< 0.8 selected for the Q)

most suitable "0s::::::

temperature for .......

c-, 0.6

variables V4 and +>

VS "

......

:;=: 0.4 ..c

to

+>

.; 0.2 (/)

0.0

0 2 4 6 8

mg/l

R,L V7 Degree-days (between 1.0

4 and 10° C) from

October 30 to April l.

Calculate 0.8 by multiply- ><

Q)

ing water temperatures "0s::::::

in the range of 4-10° C ....... 0.6

by number of days that >,

+>

are in this temper- ......

r- 0.4 ature range (e.g., ......

..c

160 days of water to

+>

temperature of 8° C = ......

::::l 0.2

1,080 degree-days = (/)

51 of 1.0). 0.0

0 500 1500 2500

Degree-days

10
n. I

8 I6 f4 I2'" fR,L Va pH range during the l.

year, assumed never x

to reach 1etha 1 levels OJ

"'0 O. (i .e., < 3.5 and c

......

> 10.4). >,

...... O.

A) pH stable in 6.5 ......

to 8.5 range ..0

co O. B) pH stable in 5.5 ......

to 6.5 or 8.5 to :::J(/)

9.5 range O.

C) pH usually in the

4.5 to 6.5 or 8.5

to 9.5 range, but

pH occasionally

drops to < 4.5 or

increases to > 9.5

D) pH frequently < 4.5

or > 9.5

A B C D

L Trophic status of

1ake or 1ake

section.

1. 0 -t----;----t---_t_

x 0.8 OJ

"'0

C

...... 0.6

>,

:;: 0.4 ..0

co

0.2 :::J

(/)

o. 0 +---~---r---+

o 2

Trophic status

3

Table 1 provides a list of parameters which can be used to classify a water

body by trophic status. Leach et al. (1977) provided values for each parameter

corresponding to a trophic status. These values were based on data collected

from lakes in Northwestern Ontario and may not adequately describe trophic

status in other geographical areas. We believe that the class boundaries for

each parameter corresponding to trophic status should be developed by the

model user to reflect the conditions in his or her particular study location.

Parameter tropic status data must be subjectively evaluated to determine the

tropic status rating for the lake.

11
Table 1. Trophic status criteria. (Adapted from Leach et al. 1977).

Parameter

Primary production rate

Organic matter in sediments

Hypolimnetic O2 loss

Nutrient loading rates

(phosphorus, nitrogen)

Morphoedaphic index

(MEl - metric)

Transparency (Secchi

depth)

0-1

(oligotrophic)

low

low

low

low

< 6.0

high (> 6 m)

12

Trophic Status

1-2

(mesotrophic)

moderate

moderate

moderate

moderate

6 to 7.2

moderate (1 to 6 m)

2-3

(eutrophic)

high

high

high

high

> 7.2

low « 1 m)
Table 2. Sources of information and assumptions for construction of

the suitability index graphs. In construction of the graphs,

"excellent" habitat for yellow perch was assumed to correspond to an

SI of 0.8 to 1.0, "good" to an SI of 0.5 to 0.7, "fair" to an SI of

0.2 to 0.4, and "poor" to an SI of 0.0 to 0.1.

Variable Assumptions and sources

Yellow perch of all sizes are abundant in the littoral zone of

lakes (Wells 1968; Helfman 1979) and reservoirs (Beckman and

Elrod 1971; Nelson and Walburg 1977). Kitchell et al. (1977)

stated that extensive littoral and shoreline areas are optimum

for percids. We interpret "extensive" to mean approximately

1/4 of total lake area. We selected 35% as the upper limit for

excellent conditions to reflect the need for deeper water for

summer (or winter) refugia (e.g., Ferguson 1958). We deemed

> 40% littoral area good-fair since only moderate biomass levels

of yellow perch are found in lakes with very extensive littoral

area (Carlander 1977; Forney pers. comm.). The percent littoral

area selected as the minimum for excellent habitat suitability was

near 15% based on the observations of Forney (pers. comm.) who

found that high perch biomass occurs in New York lakes with < 20%

littoral zone. Because even a deep reservoir, such as Jocassee

(Table 3) with only 5% littoral area contained perch, the ascending

portion of the SI graph begins at a value greater than O.

Yellow perch are most abundant in pools and backwaters of rivers

(Coots 1956; Kitchell et al. 1977) and utilize these habitats for

spawning (Harrington 1947), but little specific information was

available to relate percentages of these areas present to habitat

quality for yellow perch. We have developed the SI curve based on

the assumption that the riverine habitat categories described by

Kitchell et al. (1977) as optimum percid habitat (moderate

current, mixed substrate) would contain at least 25% pools and

backwaters. We also assumed that very high percent pools was

a condition commonly associated with very low gradient streams

more characteristic of centrarchid habitat. Kitchell et al.

(1977) noted that the littoral areas occupied by perch in lakes

were similar to pool habitat in rivers. Given the generality of

the data, we constructed a very broad SI graph. The ascending

limb starts at 0 since perch are not collected in areas of faster

current (Coots 1956). Conversely, a very high percentage of pool

area was assumed to provide only fair habitat because conditions

present in very low gradient streams would likely be suboptimum

for perch (e.g., unsuitable temperatures and D.O.; Kitchell et al.

1977).

13
Variable

Table 2. (continued)

Assumptions and sources

Yellow perch utilize aquatic vegetation, brush, and other underwater structure as spawning substrate (Harrington 1947; Muncy

1962; Beckman and Elrod 1971; Scott and Crossman 1973; Kitchell

et al. 1977; Nelson and Walburg 1977) and as cover (Helfman 1977).

In Missouri River reservoirs, perch year-class strength was

positively correlated to the amount of newly-inundated terrestrial

vegetation present during spawning (June 1976; Nelson and Walburg

1977). We assumed that at least 25% vegetative cover would be

necessary for optimum habitat suitability. Areas with large

percentages of vegetation were considered suboptimum because they

would likely lack the deeper water used as summer (or winter)

refugia. We assumed percent cover of < 20% good-fair habitat

suitability. June (1976) found that spawning success of yellow

perch in Lake Oahe declined greatly when submerged brush and

vegetation was unavailable. Forney (pers. comm.) reported that

significant yellow perch populations develop in shallow New York

lakes with only sparse (~ 15%) vegetative cover.

We assumed summer temperatures that correspond to optimum growth

[23° C (Schneider 1973), 22° C (Huh et al. 1976)], preference

[18 to 24° C depending on age (Ferguson 1958; McCauley and Read

1973)], and classified by Hokanson (1977) as the physiological

optimum for yellow perch (24.7° C) as excellent. Lethal temperatures [29.2 to 33° C (Hokanson 1977)] were deemed poor. The

descending limb of the graph is based on the seasonal temperature

envelope for yellow perch presented by Hokanson (1977) wherein

5% of stream stations with midsummer water temperatures of

15° C contained perch.

The most suitable temperature within the water column is used

to develop a rating because fish can select temperatures closest

to their preferred temperature.

Vs Successful reproduction of yellow perch depends on rising temperatures during spawning and early life stages (Hokanson 1977).

Temperatures corresponding to peak spawning [e.g., 9° C (Harrington

1947); 7.2 to 11.1° C (Herman et al. 1964); 7.2 to 12.8° C (Coots

1966); 10° C (Clugston et al. 1978)] and highest gamete viability

[8 to 11° C (Jones et al. 1977 cited in Hokanson (1977)] of yellow

perch were considered excellent. We assumed that temperatures

less than the lower TL50 (6.8° C) or greater than the upper TL50

(19.9° C) (Hokanson and Kleiner 1974) for perch embryos were poor.

14
Variable

Table 2. (continued)

Assumptions and sources

D.O. levels 5.0 were considered optimum based on the optimum

D.O. criteria for Canadian freshwater fish (excluding salmonids)

developed by Davis (1975). We considered D.O. levels < 3.0 as

poor since Kitchell et al. (1977) defined> 2-4 mg/l as the

minimum D.O. concentration suitable for spawning by percids and

since Carlson et al. (1980) reported a significant decrease in

growth in yellow perch at a D.O. concentration of 2 mg/l.

This SI graph is based on information found in Jones et al. (1977)

and Hokanson (1977) demonstrating that yellow perch require winter

minimum temperatures < 10° C for proper gonad maturation. They

found that optimum conditions for maturation occurred when fish

were exposed to water temperatures 6° C for 185 days from

October 30. We then assumed that a chill duration of 740 (4° C

times 185 days) to 1,110 (6° C times 185 days) degree-days would

provide optimum habitat quality for gonad maturation and subsequent spawning for yellow perch. We considered a chill duration

of 360 degree-days to be near the lower limit for gonad maturation

because limited viable spawnings occurred in yellow perch held at

a minimum of 12° C except for 45 days at 8° C. We considered

> 2,000 degree-days to be fair to poor habitat quality since only

a small percentage of perch reared at 10° C for 200 or 240 days

spawned successfully.

pH levels in the range of 6.5 to 8.5 were considered optimum

according to the pH criteria considered optimum for growth and

survival of freshwater fish populations (Stroud 1967). Yellow

perch are relatively tolerant to low pH. Rahel (1983) found that

perch from naturally acidic (pH 4.5) bog lakes in Wisconsin could

survive at pH 3.2. However, Ryan and Harvey (1979) found that

abundance of age 0 perch was greatly reduced in Ontario lakes with

pH levels < 5.5. Runn et al. (1977, cited by Ryan and Harvey

1979) found a much reduced egg hatchability in another, similar

perch species, the Eurasian perch (Perca fluviatilis), at pH <

5.5. Thus, we deemed pH levels < 5~ fair-poor. We considered pH > 9.5 as poor because a pH value 10.4 is lethal to

yellow perch (Rahel 1983) and growth and survival of freshwater

fish populations decreases at pH > 9.5 (Stroud 1967).

15
Variable

Table 2. (concluded)

Assumptions and sources

Yellow perch are most abundant in waters classifed as mesotrophic,

i.e., waters with moderate fertility and moderate turbidity

(Herman et al. 1964; Kitchell et al. 1977; Leach et al. 1977;

Thorpe 1977) and hence we considered mesotrophic conditions to

be excellent. Perch populations decline with increasing turbidity

(decreasing transparency) and decreasing amounts of aquatic

vegetation accompanying eutrophication (Scott and Crossman 1973;

Kitchell et al. 1977; Leach et al. 1977; Nelson and Walburg 1977).

Perch also are less abundant in clear, deep, unproductive lakes or

lake sections (Nakashima and Leggett 1975; Kitchell et al. 1977).

We provide broad gUidelines of trophic status by adapting the

classification system of Leach et al. (1977). We assumed that

very eutrophic or very oligotrophic water bodies would be less

suitable as habitat for yellow perch.

16
Application of Lacustrine Model to Reservoir Sites

The lacustrine model correctly ranked two eastern Colorado reservoirs

(Stalker and Chatfield) with very different perch densities, as reflected by

sport harvest estimates (Tables 3 and 4). When applied to two South Carolina

reservoi rs (Jocassee and Keowee) wi th low perch standi ng crops (Cl ugston

et al. 1978), the model rated both as having equally low habitat suitability

for yellow perch (Tables 5 and 6).

Interpreting Model Outputs

The models described above are generalized descriptions of habitat

requirements for yellow perch and, as such, the outputs of either model are

not expected to discriminate among different habitats with a high resolution

at this stage of development. Each model variable is considered to be able to

limit carrying capacity for yellow perch. The suitability index graphs are

based on easily measurable responses, such as growth or survival, and may not

accurately depict the relationship to carrying capacity. The model assumes

that each model variable can limit perch production, but this has not been

tested. A major potential weakness in the models is that while model variables

may be necessary in determining suitability of habitat for yellow perch, they

may not be sufficient. Species interactions and other factors may determine

carrying capacity to a greater degree than the variables included in the

models (e.g., Forney 1971, 1974). The model must be viewed as conceptual and

very subjective. Any attempt to use the model as a predictive model should be

preceded by testing the model in areas of known-carrying capacity where habitat

conditions are similar to the area of proposed model application. This testing

should help determine which, if any, model variables are predictors of carrying

capacity in the proposed area of model application. For example, MEl values

ranked the pair of South Carolina reservoirs (Tables 4 and 5) in the same

order as the standing crop data while the complete model rated both reservoirs

as having the same HSI.

We recommend interpreting model outputs as indicators (or predictors) of

excellent (0.8 to 1.0), good (0.5 to 0.7), fair (0.2 to 0.4), or poor (0.0 to

0.1) habitat for yellow perch. If two areas have different HSI1s, the one

with the higher HSl is assumed to have the potential to support more yellow

perch. Given the limited (four reservoirs) usage the model has had, the

assumption must be considered virtually untested. Model variables may be

useful for developing revised models that incorporate site-specific factors

affecting habitat suitability for yellow perch. Helfman (1979) noted the

ecological plasticity and varying habitat preferences of perch in different.,

studies. Users of the model should be cautious of such differences when using

habitat use data from one part of the country to evaluate habitats in another

area.

17
Table 3. Environmental data for Chatfield Reservoir, Colorado.

Variable Data 51

V1 Percent 1ittoral area 13% 0.8

V3 Percent cover 60% 0.7

V4 H2O temperature (summer) 20° C 1.0

Vs H2O temperature (embryo) 11° C 1.0

V6 D.O. 7.2 mg/l 1.0

V7 Degree Days 1460 0.8

Va pH 7.8-8.3 1.0

Vg Trophic status Mesotrophica 1.0

aMesotrophic classification and 51 determined on basis of secchi depth

transparency (~ 3.0 to 4.0m).

H51 = lowest 51 score = 0.7.

Measured population level of yellow perch = sport harvest of 20.6 kg/ha.

18
Table 4. Environmental data for Stalker Lake, Colorado.

Variable Data SI

V1 Percent 1ittoral area 30% 1.0

V3 Percent cover 80% 0.4

V4 H2O temperature (summer) 22° C 1.0

Vs H2O temperature (embryo) 13° C 0.9

V6 D.O. 8.5 mg/l 1.0

V7 Degree days 1587 0.3

Va pH 8.7-9.0 0.5

Vg Trophic status Mesotrophic/Eutrophic a 0.7

aClassification and SI determined on basis of organic matter in

sediments (moderately high), and secchi transparency (- 2 m). We selected an

SI from the rating curve that was between the mesotrophic optimum and the lower

eutrophic rating to reflect the intermediate nature of the variable values.

HS1 = lowest SI score = 0.3.

Measured population level of yellow perch = sport harvest of < 0.1 kg/ha.

19
Table 5. Environmental data for Jocassee Reservoir, South Carolina.

Variable Data Sl

V1 Percent littoral area 5% 0.4

V3 Percent cover 80% 0.4

V4 H2O temperature (summer) 200 C 1.0

Vs H2O temperature (embryo) 9.60 C 1.0

V6 D.O. 8.2 mg/l 1.0

V7 Degree days 2346 0.2

Vs pH 5.6-6.9 0.5

Vg Trophic status Oligotrophica 0.2

aOligotrophic classification and Sl determined on basis of MEl. TDS was

18 mg/l and mean depth, 46.0 m (Clugston et al. 1978; Clugston pers. comm.).

18 Thus, MEl = 46 = .39

HSl = lowest Sl score = 0.2.

Measured population level of yellow perch = Mean standing crop of 0.5 kg/ha.

20
Table 6. Environmental data for Keowee Reservoir, South Carolina.

Variable Data Sl

V1 Percent littoral area 10% 0.6

V3 Percent cover 10% 0.5

V4 H2O temperature (summer) 200 C 1.0

Vs H2O temperature (embryo) 12.80 C 1.0

V6 D.O. 6.4 mg/l 1.0

V7 Degree days 2672 0.2

Va pH 5.7-7.0 0.5

V9 Trophic status 01 i gotrophi ca 0.3

aOligotrophic classification and Sl determined on basis of MEl. TDS was

20 mg/l and mean depth 15.8 m (Clugston et al. 1978; Clugston pers. comm.).

20 Thus, MEl = 15.8 = 1.27

HSl = lowest Sl score = 0.2.

Measured population level of yellow perch = Mean standing crop of 1.6 kg/ha.

21
ADDITIONAL HABITAT MODELS

Modell

Optimum riverine habitat for yellow perch is characterized by the following conditions, assuming water quality is adequate: deep pools (deeper than

average river depth) and slack water areas· (25 to 75% of river area) with

moderate amounts of vegetation (25 to 50% of pool and backwater area), with

low to moderate turbidities « 100 JTU); low velocities (s 10 em/sec); and

warm (20 to 28° C) summer temperatures.

HSI = number of above criteria met

6

Model 2

Optimum lacustrine habitat for yellow perch is characterized by the

following conditions, assuming water quality is adequate: a littoral area 20

to 30% of the total lake or reservoir area; 25 to 50% of the littoral area

vegetated; warm (20 to 28° C) surface water temperature in summer; and low to

moderate turbidities « 100 JTU).

HSI = number of above criteria present

4

Model 3

Use the yellow perch HSI model for planned cool and coldwater reservoirs

developed by McConnell et al. (1982).

Model 4

Aggus and Bivin (1982) used angler harvest as a measure of habitat suitability and developed a regression equation relating harvest to reservoir

habitat variables for 37 reservoirs in the conterminous United States:

Log 1D (harvest of yellow perch) = 3.7117 - 0.0142 (growing season)

- 0.7530 10g1D (outlet depth).

R2 = 0.38.

22
Units for the above equation are kg/ha (harvest),

feet below a specified elevation (outlet depth).

summary of reservoir harvest data and discuss

measured or predicted harvest values to HSI's.

INSTREAM FLOW INCREMENTAL METHODOLOGY (IFIM)

days (growing season), and

These authors present a

procedures for convert i ng

The U.S. Fish and Wildlife Service1s Instream Flow Incremental Methodology

(IFIM), as outlined by Bovee 1982, is a set of ideas used to assess instream

flow problems. The Physical Habitat Simulation System (PHABSIM), described by

Milhous et al. 1981, is one component of IFIM that can be used by investigators

interested in estimating the amount of available instream habitat for a fish

species as a function of streamflow. The output generated by PHABSIM can be

used for several IFIM habitat display and interpretation techniques, including:

1. Optimization. Estimation of monthly flows that minimize habitat

reductions for species and life stages of interest;

2. Habitat Time Series. Estimation of the impact of a project on

habitat by imposing project operation curves over historical flow

records and integrating the difference between the curves; and

3. Effective Habitat Time Series. Estimation of the habitat requirements of each life stage of a fish species at a given time by using

habitat ratios (relative spatial requirements of various life

stages).

Suitability Index Graphs as Used in IFIM

PHABSIM utilizes Suitability Index graphs (SI curves) that describe the

instream suitability of the habitat variables most closely related to stream

hydraulics and channel structure (velocity, depth, substrate, temperature, and

cover) for each major life stage of a given fish species (spawning, egg incubation, fry, juvenile, and adult). The specific curves required for a PHABSIM

analysis represent a species preference for hydraulic-related parameters

(i.e., a pelagic species that only shows preferences for velocity and

temperature will have very broad curves for depth, substrate, and cover).

Instream Flow Information Papers 11 (Milhous et al. 1981) and 12 (Bovee 1982)

should be reviewed carefully before using any curves for a PHABSIM analysis.

SI curves used with the IFIM that are generated from empirical microhabitat

data are quite similar in appearance to the more generalized literature-based

SI curves developed in many HSI models (Armour et al. 1983). These two types

of SI curves are interchangeable, in some cases, after conversion to the same

units of measurement (English, metric, or codes). SI curve validity is

dependent on the qual i ty and quantity of i nformat i on used to generate the

curve. The curves used need to accurately reflect the conditions and assumptions inherent to the model(s) used to aggregate the curve-generated SI values

into a measure of habitat suitability. If the necessary curves are unavailable

or if available curves are inadequate (i.e., built on different assumptions),

23
a new set of curves should be generated. (Data collection and analyses

techniques for curve generation will be included in a forthcoming Instream

Flow Information Paper.)

There are several ways to develop 51 curves for use with IFIM. The

method selected depends on the habitat model that will be used and the available database for the species. The validity of the curve is not obvious and,

therefore, the method by which the curve is generated and the quality of the

database are very important. Care al so must be taken to choose the habitat

model most appropriate for the specific study or evaluation; the choice of

models will determine the type of 51 curves that will be used. For example,

in an H5I model, a 51 curve for velocity usually reflects suitability of

average channel (stream) velocity (i.e., a macrohabitat descriptor); in an

IFIM analysis, 51 curves for velocity are assumed to represent suitability of

the velocity at the point in the stream occupied by a fish (i.e., a microhabitat descriptor) (Armour et al. 1983).

A system with standard terminology has been developed for classifying 51

curve sets and describing the database used to construct the curves in IFIM

applications. The classification is not intended to define the quality of the

data or the accuracy of the curves. There are four categories in the classification. A literature-based (category one) curve has a generalized description or summary of habitat preferences from the 1iterature as its database.

This type of curve usually is based on information in published references on

the upper and lower limits of a variable for a species (e.g., juveniles are

usua lly found at water depths of 0.3 to 1. 0 m). Unpub1i shed data and expert

opinion can also be used to develop these curves. Occasionally, the reference

also contains information on the optimum or preferred condition within the

limits of tolerance (e.g., juveniles are found at water depths of 0.3 to

1.0 m, but are most common at depths from 0.4 to 0.6 m). Virtually all of the

51 curves published in the H5I series for depth, velocity, and substrate, are

category one curves.

Utilization curves (category two) are based on a frequency analysis of

fish observations in the stream environment with the habitat variables measured

at each sighting [see Instream Flow Information Paper 3 (Bovee and Cochnauer

1977) and Instream Flow Information Paper 12 (Bovee 1982:173-196)]. These

curves are designated as utilization curves because they depict the habitat

conditions a fish will use within a specific range of available conditions.

Because of the way the data are collected for utilization curves, the resulting

function represents the probability of occurrence of a particular environmental

condition, given the presence of a fish of a particular species, P(EIF).

Utilization curves are generally more precise for IFIM applications than

1iterature-based curves because they are based on specific measurements of

habitat characteristics where the fish actually occur. However, utilization

curves may not be transferable to streams that differ substantially in size

and complexity from the streams where the data were obtained.

24
A preference curve (category three) is a utilization curve that has been

corrected for environmental bias. For example, if 50% of the fish are found

in pools over 1.0 m deep, but only 10% of the stream has such pools, the fish

are actively selecting that type of habitat. Preference curves approximate

the function of the probability of occurrence of a fish, given a set of environmental conditions:

P(FIE)::: P(EjF) P( E)

Only a limited number of experimental data sets have been compiled into

IFIM preference curves. The development of these curves should be the goal of

all new IFIM curve development efforts.

The fourth category of curves is still largely conceptual. One type of

curve under consideration is a cover-conditioned, or season-conditioned,

preference curve set. Such a curve set would consi st of di fferent depthve1ocity preference curves as a funct i on or condi t i on of the type of cover

present or the time of year. No fourth category curves have been developed at

this time.

The advantage of category three and four curves is the significant

improvement in precision and confidence in the curves when applied to streams

similar to the streams where the original data were obtained. The degree of

increased accuracy and transferabil i ty obta i nab1e when applyi ng these curves

to dissimilar streams is unknown. In theory, the curves should be widely

transferable to any stream in which the range of environmental conditions is

within the range of conditions found in the streams from which the curves were

developed.

Availability of Graphs for Use in IFIM

Investigators who wish to do an IFIM analysis of yellow perch habitat

should study the available SI curves (Table 7) carefully and determine if they

reflect yellow perch habitat utilization in the study area of interest. SI

curves for spawning velocity, depth, and substrate utilization (Fig. 3) are

category one. Yellow perch seem to prefer aquatic or submerged terrestrial

vegetation for spawning substrate, but will utilize rocks, gravel, or sand

when vegetation is absent. Therefore, an investigator may want to modify the

SI curve for spawning substrate (Fig. 3) into a much broader curve.

Assuming that habitat requirements for egg incubation are similar to

those for spawning, SI curves for spawning (Fig. 3) may be used for IFIM

analysis of egg incubation habitat. The SI curve for egg incubation substrate

should be modified as it was for analysis of spawning habitat.

25
Table 7. Availability of curves for IFIM analysis of yellow perch habitat.

Fry Use SI curve, Use SI curve,

Figure 4. Figure 4.

N Juvenile Use SI curve, Use SI curve,

O'l Figure 5. Figure 5.

Adult Use SI curve, Use SI curve,

Figure 6. Figure 6.

Spawning

Egg incubation

Velocitl

Use SI curve,

Figure 3.

Use SI curve,

Figure 3.

Deptha

Use SI curve,

Figure 3.

Use SI curve,

Figure 3.

Substratea,c Temperaturea Covera

Use SI = 1.0b for Use SI curve No curve

submerged vegeta- for V5. avail able.

tion and SI curve,

Figure 3.

Use SI = 1.0b for Use SI curve No curve

submerged vegeta- for V5' available.

tion and SI curve,

Figure 3.

Use SI curve, Use SI curve No curve

Figure 4. for V4 • available.

Use SI curve, Use SI curve Use SI curve

Figure 5. for V4 • for V3'

Use SI curve, Use SI curve Use SI curve

Figure 6. for V4 • for V3 •

aWhen use of SI curves is prescribed, refer to the appropriate curve in the HSI model section or IFIM section.

bUse SI = 1.0 if the habitat variable is optimal; but if the habitat variable is less than optimal, the user

must determine, by judgement, what is the most appropriate SI value.

cThe following categories may be used for IFIM analyses (see Bovee 1982):

1 = plant detritus/organic material

2 = mud/soft clay

3 = silt (particle size < 0.062 mm)

4 = sand (particle size 0.062-2.000 mm)

5 = gravel (par~jcle size 2.0-64.0 mm)

6 = cobble/rubble (particle size 64.0-250.0 mm)

7 = boulder (particle size 250.0-4000.0 mm)

8 = bedrock (solid rock)
o

50203 SPAWNING

o

79/06/22.

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1\

I

,

I

i\ I

\

\

J \

'"ci

)o~

t:: 0

..J

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:no

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ci

o

ci

o

.,; '"

'"' )0 •

t:: 0

::

CD

CI

5"': "'0

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ci

o

.,;

\

I I

I

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VELOCITY [rT/SECl

I 1\ I

I

\

\

\

\

2

'"ci

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.,;

o

.,;

o 3

DEPTH .rn

5 6

2 3

SUBSTRATE 5 6

Figure 3. Category one SI curves for yellow perch spawning habitat

(Coots 1966; Scott and Crossman 1973).

27
The SI curves for adults, juveniles, and fry (Figs. 4-6) are category

two, and were generated from frequency analyses of raw data collected from the

Missouri River (Kallemeyn and Novotny unpubl. data). Each of four stations

was sampled for 4 days every 4 weeks from 29 March to 4 November 1976. Three

stations were unchannelized sections of river located on the South Dakota/

Nebraska border, one below Fort Randall Dam and two below Gavins Point Dam.

The fourth station was on a channelized section of river on the Iowa/Nebraska

border below Sioux City. Sampling gear included gill nets, trammel nets, hoop

nets, seines, a drop trap, an electroshocker, and plankton nets. A total of

787 fry, 400 juveniles, and 70 adult yellow perch were collected and used in

the frequency analyses.

Habitat types identified in the unchannelized sections of the Missouri

River included main channel, main channel border, sandbar, chute, backwater,

pool, and marsh; those in channelized sections of the river included main

channel, spur dike, notched spur dike, notched wing dike, revetment, and

notched revetment. Duri ng the study channel, widths ranged 300 to 1,500 m

(X = 640 to 760 m), depths ranged 0.0 to 8.0 m (x < 2.0 m), daily mean discharges ranged from 872 to 1,104 m3/second (x 1,015 m3/second), surface

velocities ranged from 0.0 to 2.1 m/second, the gradient was approximately

0.2 m/km, surface water temperatures ranged from 3.5 to 27.5° C, turbidity

ranged from 2.3 to 33.0 JTU·s, and conductivity ranged from 550 to 780 pmhos/

cm. The substrate consisted primarily of sand; silt was dominant in backwater

and marsh areas.

28
50200 FRY 79106/22.

\

i I I

f \

\

I \

I \

J

J \

o

CD

o

>-"!

t: 0

..J

iii

<I:

l-5 ... 11>0

N

o

o

o

o

CD

ci

>-"!

1-0

..J

iii

5 ... 11>0

N

o

o

o

o

0.5 I 1.5

VELOCITY IrT/SECJ

3

SUBSTRATE

2

6

0

CD

0

>- '" t: 0

..J

iii

5 ... II> 0

N

0

0

0

0 2 1

DEPTH rrr:

Figure 4. Category two 51 curves for yellow perch fry

(Kallemeyn and Novotny unpubl. data).

29
I

\

\

\

J 1\ / -,

-,

50201 79/06/22.

\ II

CD

0 ,

>"!

t: 0

...

iii

5~

(1)0

'"0

0

0

0 O.S I I.S

VELOCITY lfT/SECl

o

JUVENILES

o i

DEPTH irn 6 e

CD

o

'"o

o

o

I '\

I

J

I

1/

I 3

SUBSTRATE 6

Figure 5. Category two 5I curves for yellow perch juveniles

(Kallemeyn and Novotny unpubl. data).

30
/

I \

/ ,

/

/

50202 79/06/22.

0

'"ci \, ~"!

1-0

..J

Qi

·4

I5",:

fIIo

N

ci

0

ci

0 0.5 1 1.5

VELOCITY 1fT/SEC)

o

ADULTS

o

o 2 1

DEPTH IfTJ 6 B

OJ

ci

N

ci

o

ci

/

I ,

I

2 3

SUBSTRATE 5 6

Figure 6. Category two SI curves for yellow perch adults

(Kallemeyn and Novotny unpubl. data).

31
REFERENCES

Aggus, L. R., and W. M. Bivin. 1982. Habitat suitability index models:

Regression models based on harvest of coolwater and coldwater fishes in

reservoirs. U.S. Fish Wildl. Servo FWS/OBS-82/10.25. 38 pp.

Amundrud, J. R., D. J. Faber, and A. Keast. 1974. Seasonal

free-swimming perciform larvae in Lake Opinicon, Ontario.

Board Can. 31:1661-1665.

successi on of

J. Fish. Res.

Armour, C. L., R. J. Fisher, and J. W. Terrell. Unpub. Comparison and recommendations for use of Habitat Evaluation Procedures (HEP) and the Instream

Flow Incremental Methodology (IFIM) for aquatic analyses. U.S. Fish

Wildl. Serv., Western Energy and Land Use Team, Fort Collins, CO. 42 pp.

Beckman, L. G., and J. H. Elrod. 1971. Apparent abundance and distribution

of young-of-year fishes in Lake Oahe, 1965-1969. Pages 333-347 in G. E.

Hall, ed. Reservoir fisheries and limnology. Am. Fish. SoC-:- Spec.

Publ. 8.

Benson, N. G. 1973. Evaluating the effects of discharge rates, water levels,

and peaking on fish populations in Missouri River mainstream impoundments.

Pages 683-689 in W. C. Ackermann, G. F. White, and E. B. Worthington,

eds. Man-made -lakes: Their problems and environmental effects. Am.

Geophysical Union, Geophysical Monogr. Ser., Vol. 17.

Bovee, K. D. 1982. A guide to stream habitat analysis using the Instream

Flow Incremental Methodology. Instream Flow Information Paper 12. U.S.

Fish Wildl. Servo FWS/OBS-82/26. 248 pp.

Bovee, K. D., and T. Cochnauer. 1977. Development and evaluation of weighted

criteria, probability-of-use curves for instream flow assessments:

fisheries. Instream Flow Information Paper 3. U.S. Fish Wildl. Servo

FWS/OBS-77/63. 39 pp.

Carlander, K. D. 1977. Biomass, production, and yields of walleye

(Stizostedion vitreum vitreum) and yellow perch (Perca flavescens) in

North American lakes. J. Fish. Res. Board. Can. 34(10):1602-1612.

Carlson, A. R., J. Blocher, and L. J. Herman. 1980. Growth and survival of

channel catfish and yellow perch exposed to lowered constant and diurnally

fluctuating dissolved oxygen concentrations. Prog. Fish-Cult.

42(2):73-78.

Clady, M. D. 1976. Influence of temperature and wind on the survival of

early stages of yellow perch, Perca flavescens. J. Fish Res. Board Can.

33:1887-1893.

32
Clady, M., and B. Hutchinson. 1975. Effects of high winds on eggs of yellow

perch in Oneida Lake, New York. Trans. Am. Fish. Soc. 104(3):524-525.

Clugston, J. P. 1982. Personal communication. Chief, Southeast Reservoir

Investigations, Clemson, SC.

Clugston, J. P., J. L. Oliver, and R. Ruelle. 1978. Reproduction, growth,

and standi ng crops of yellow perch in Southern reservoi rs. Pages 89-99

in R. L. Kendall, ed. Selected Coolwater Fishes of North America. Am.

Fish. Soc. Spec. Publ. 11.

Collette, B. B., and P. Banarescu. 1977. Systematics and zoogeography of the

fishes of the family Percidae. J. Fish. Res. Board Can. 34(10):1450-1463.

Collette, B. B., M. A. Ali, K. E. F. Hokanson, M. Nagiec, S. A. Smirnov, J. E.

Thorpe, A. H. Weatherley, and J. Willemsen. 1977. Biology of the

percids. J. Fish. Res. Board Can. 34(10):1890-1899.

Cooper, G. P., and G. W. Washburn. 1949. Relation of D.O. to winter mortality

of fish in Michigan lakes. Trans. Am. Fish. Soc. 76:23-33.

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River. Calif. Fish Game 42(3):219-228.

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546 pp.

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Wildl. Servo FWS/OBS-79/31.

Davis, J. C. 1975. Minimal dissolved oxygen requirements of aquatic life

with emphasis on Canadian species: a review. J. Fish. Res. Board Can.

32(12):2295-2332.

Driver, E. A., and E. T. Garside. 1966. Meristic numbers of yellow perch in

saline lakes in Manitoba. J. Fish. Res. Board Can. 23:1815-1817.

El-Zarka, S. E. D. 1959. Fluctuations in the population of yellow perch,

Perca flavescens (Mitchill), in Saginaw Bay, Lake Huron. U.S. Fish

Wildl. Servo Fish. Bull. 59:365-415.

Eschenroder, R. L. 1977. Effects of intensified fishing, species change, and

spring water temperatures on yellow perch, Perca flavescens, in Saginaw

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Ferguson, R. G. 1958. The preferred temperature of fish and their midsummer

di stri bution intemperate 1akes and streams. J. Fish. Res. Board Can.

15(4):607-624.

33
Forney, J. L. 1971. Development of dominant year classes in a yellow perch

population. Trans. Am. Fish. Soc. 100:739-749.

1974. Interactions between yellow perch abundance, walleye

predation, and survival of alternate prey in Oneida Lake, New York.

Trans. Am. Fish. Soc. 103:15-24.

1982. Personal communication. Dept. of Natural Resources,

Cornell University, Fernow Hall, Ithaca, NY.

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yellow perch, Perca flavescens (Mitchill). Copeia 1947(3):199-200.

Hartman, W. L. 1972. Lake Erie: Effects of exploitation, environmental

changes and new species on the fishery resources. J. Fish. Res. Board

Can. 29(6):899-912.

Helfman, G. S. 1979. Twilight activities of yellow perch, Perca flavescens.

J. Fish. Res. Board Can. 36(2):173-179.

Hergenrader, G. L. 1969. Spawning behavior of Perca flavescens in aquaria.

Copeia 1969(4):839-841.

Herman, E., W. J. Wisky, L. Wiegert, and M. Burdick.

its life history, ecology, and management.

Publ. 228:1-14.

1964. The yellow perch,

Wisconsin Conserv. Dept.

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Bull. U.S. Bur. Fish. 43(1):1-366.

Hokanson, K. E. F. 1977. Temperature requirements of some percids and adaptations to the seasonal temperature cycle. J. Fish. Res. Board Can.

34:1524-1550.

Hokanson, K. E. F., and C. F. Kleiner. 1973. The effects of constant and

rising temperatures on survival and developmental rates of embryonic and

larval yellow perch, Perca flavescens (Mitchill). Pages 437-448 in Early

life history of fish~oc. Int. Symp. Dunstaffnage Mar. Re~ Lab.,

Oban, Scotland.

1974. Effects of constant and ri si ng temperatures on

survival and development rates of embryonic and larval yellow perch,

Perca flavescens (Mitchill). Pages 437-448 in J. H. S. Blaxter (ed.).

The early life history of fish. Springer-Verlag-:-New York, NY.

Houde, E. D. 1969. Sustained swimming ability of larvae of walleye

(Stizostedion vitreum vitreum) and yellow perch (Perca flavescens). J.

Fish. Res. Board Can. 26(6):1647-1659.

Huh, H. T., H. E. Calbert, and D. A. Stuber. 1976. Effects of temperature

and light on growth of yellow perch and walleye using formulated feed.

Trans. Am. Fish. Soc. 105(2):254-258.

34
Johnson, M. G., J. H. Leach, C. K. Minns, and C. H. Oliver. 1977. Limnological characteristics of Ontario lakes in relation to associations of

walleyes (Stizostedion vitreum vitreum), northern pike (Esox lucius),

lake trout (Salvelinus namaycush), and smallmouth bass(Micropterus

dolomieui). J. Fish. Res. Board Can. 34(10):1592-1601.

Jones, B. R., K. E. F. Hokanson, and J. H. McCormick. 1977. Winter temperature requirements for maturation and spawning of yellow perch, Perca

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the world conference towards a plan-of action for mankind. Vol. 3.

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June, F. C. 1976. Changes in young-of-the-year fish stocks during and after

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four stations on the Missouri River in South Dakota, Nebraska, and Iowa,

from 29 March to 4 November 1976. North Central Res.ervoi r Investi gations,

Yankton, SO.

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West Blue Lake, Manitoba, and their interactions. J. Fish. Res. Board

Can. 34(10):1655-1669.

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C. M. Olver. 1977. Percid habitat: The river analogy. J. Fish. Res.

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B. Entz. 1977. Responses of percid fishes and their habitats to

eutrophication. J. Fish. Res. Board Can. 34(10):1964-1971.

Magnuson, J. J., and D. J. Karlen. 1970. Visual observations of fish beneath

the ice in a winterkill lake. J. Fish. Res. Board Can. 27:1059-1068.

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flavescens. Chesapeake Sci. 5(1-2):46-66.

McCauley, R. W., and L. A. A. Read. 1973. Temperature selection by juvenile

and adult yellow perch acclimated to 24° C. J. Fish. Res. Board Can.

30:1253-1255.

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Suitability Index Models: a low effort system for planned cool water and

coldwater reservoirs. U.S. Fish Wildl. Servo FWS/OBS-82/10.3. 47 pp.

35
Milhous, R. T., D. L. Wegner, and T. Waddle. 1981. User's guide to the

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freshwater fishes. Ecology 23(3):319-329.

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biomass responses to different levels of phytoplankton and benthic biomass

in Lake Memphremagog, Quebec-Vermont. J. Fish. Res. Board Can.

32:1785-1797.

1978. Daily ration of yellow perch (Perca flavescens) from

Lake Memphrenagog, Quebec-Vermont, with a comparison of methods for

in-situ determinations. J. Fish. Res. Board Can. 35(12):1597-1603.

Nelson, W. R., and C. H. Walburg. 1977. Population dynamics of yellow perch

(Perca flavescens), sauger (Stizostedion canadense), and walleye (S.

vitreUm vi treum) in four main stem Mi ssouri Ri ver reservoi rs. J. Fish.

Res. Board Can. 34(10):1748-1763.

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receiving heated effluent. Proc. Southeastern Assoc. Game and Fish Comm.

35(1981) .

Rahel, F. J. 1983. Population differences in acid tolerance between yellow

perch, Perca flavescens, from naturally acidic and alkaline lakes. Can.

J. Zool~147-152.

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behavior in larval yellow perch (Perca flavescens). Can. Field-Nat.

91(4):406-410. -----

Runn, P., N. Johansson, and G. Milbrink. 1977. Some effects of low pH on the

hatchability of eggs of perch. Zoon 5:115-127.

Ryan, P. M., and H. H. Harvey. 1979. Growth responses of yellow perch, Perca

flavescens (Mitchill), to lake acidification in the La Cloche Mountain

Lakes of Ontario. Env. Biol. Fish. 5(2):97-108.

Schneider, J. C. 1973. Influence of diet and temperature on food consumption

and growth by yellow perch, with supplemental observations on the bluegill. Michigan Dept. Nat. Resour. Fish. Res. Rep. 1802. 25 pp.

Scott, W. B., and E. J. Crossman. 1973. Freshwater fishes of Canada. Fish.

Res. Board Can. Bull. 184. 966 pp.

36
Siefert, R. E. 1972. Fish food of larval yellow perch, white suckers, emerald

shiner, and rainbow smelt. Trans. Am. Fish. Soc. 101:219-225.

Stroud, R. H. 1967. Water quality criteri a to protect aquatic 1ife: a

summary. Am. Fish. Soc. Spec. Publ. 4:33-37.

Thorpe, J. E. 1977. Morphology, physiology, behavior, and ecology of Perca

fluviatilis L. and Perca flavescens Mitchill. J. Fish. Res. Board~

34(10):1504-1514.

U.S. Fish and Wildlife Service. 1982. Standards for the development of

habitat suitability index models. 103 ESM. U.S. Fish Wildl. Servo n.p.

Ward, J. F., and G. G. C. Robinson. 1974. A review of research on the limnology of West Blue Lake, Manitoba. J. Fish. Res. Board Can. 31:977-1005.

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Michigan. U.S. Fish. Wildl. Servo Fish. Bull. 67:1-15.

37
50212 ., 01

\Z.

4. Titl. Ind Sucrtltt.

Habitat Suitability Information: Yellow Perch

5. R.DQft OR.

December 1983

"

Colorado Division of Wildlife

317 W. Prospect Street

Fort Collins, CO 80526

1. AutflOf'(ll

Krieger, Douglas A, James W. Terrell, and Patrick C. Nelson

9. ~""inc O....ni~.tion N.m. Ino AdO'''. Western Energy and Land Use Team

U.S. Fish and Wildlife Service

Creekside One Building

2627 Redwing Road

Fort Collins, CO 80526-2899

10. Pfoaj-=t/Tasll/Wonc Unit No.

11. contr'8c:t(C) or arllnt(G) No.

(<:)

12. SOOMOtinC O....nizatlon N.me Ind Add,...

15. SUOOI.fftentary Nat..

. 1L AbatrKt (Wmit: 200 _nIIl

Western Energy and Land Use Team

Division of Biological Services

Research and Development

Fish and Wildlife Service

U.S. Deoartment of the Interior

Washington, DC 20240

14.

A review and synthesis of existing information were used to develop riverine and

lacustrine habitat models for the yellow perch (Perca flavescens). The models are

scaled to produce indices of habitat suitability between 0 (unsuitable habitat) and

1 (optimally suitable habitat) for riverine, lacustrine, and palustrine habitat in

the 48 contiguous United States. Habitat Suitability Indices (HSI) are designed for

use with the Habitat Evaluation Procedures previously developed by the U.S. Fish and

Wildlife Service.

Also included are discussions of Suitability Index (SI) curves as used in the Instream

Flow Incremental Methodology (IFIM) and SI curves available for an IFIM analysis of

yellow perch habitat.

17. Oocument Analysis I. Oncnllto"

Mathematical models

Fishes

Aq ua tic bi 01 ogy

Habitability

O. Id.ntlfle~/~.n·£nd" ;.I'1"I'IS

Yellow perch

Perca flavescens

Habitat Suitability Index

Instream Flow Incremental Methodology

e, COSArl ;:;efd/Grouo

18. AvaIlability 5tate....eM

Release unlimited

19. SltCun~ CIlss (TIns ".ooft)

Unclassified

20. SlICUrtty ellS. (nils PSllle'

Unclassified

21. No. of !"sces

, 37

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OPTIONAL FORM Z7'Z (01.-771

(Formerty ~rlS-3S1

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REGION I

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~abitat SU1t~bilit, IBTOrmion :

lrJeger, Oouglas A.

2 4\j 46

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DEPARTMENT OF THE INTERIOR

u.s. FISH AND WILDLIFESERVICE

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