FWS/OBS-82/10.56

APRIL 1984

HABITAT SUITABILITY INFORMATION:

WALLEYE

__b:

SK

361

. U54

no . 8 2-

10.56

and Wildlife Service

. Department of the Interior
HABITAT SUITABILITY INFORMATION: WALLEYE

by

Thomas E. McMahon

James W. Terrell

Habitat Evaluation Procedures Group

and

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

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

FWS/OBS-82/10.56

Apri 1 1984
This report should be cited as:

McMahon, T. E., J. W. Terrell, and P. C. Nelson. 1984. Habitat suitability

information: Walleye. U.S. Fish Wildl. Servo FWS/OBS-82/10.56. 43 pp.
1981. Standards for the deve 1opment of

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

PREFACE

The Habitat Suitability Index (HSI) models presented in this publication

aid in identifying important habitat variables. Facts, ideas, and concepts

obtained from the research literature and expert reviews are synthesized and

presented ~n a format that can be used for impact assessment. The models are

hypotheses of species-habitat relationships, and model users should recognize

that the degree of veracity of the HSI model, SI graphs, and assumptions will

vary according to geographical area and the extent of the data base for

individual variables. After clear study objectives have been set, the HSI

model building techniques presented in U.S. Fish and Wildlife Service (1981)1

and the general guidel ines for modifying HSI model s and estimating model

variables presented in Terrell et al. (1982)2 may be useful for simplifying

and applying the models to specific impact assessment problems. Simplified

models should be tested with independent data sets, if possible.

Statistically-derived models that are an alternative to using Suitability

Indices to calculate an HSI are referenced in the text.

A brief discussion of the appropriateness of using selected Suitability

Index (SI) curves from HSI models as a component of the Instream Flow

Incremental Methodology (IFIM) is provided. Additional SI curves, developed

specifically for analysis of walleye habitat with IFIM, also are presented.

Results of a model performance test in a 1imited geographical area are

summarized, but model reliability is likely to vary in different geographical

areas and situations. The U.S. Fish and Wildlife Service encourages model

users to provide comments, suggestions, and test results that may help us

increase the utility and effectiveness of this habitat-based approach to

impact assessment. Please send comments to:

Habitat Evaluation Procedures Group or Instream Flow and

Aquatic Systems Group

Western Energy and Land Use Team

U.S. Fish and Wildlife Service

2627 Redwing Road

Fort Collins, CO 80526-2899

1U.S. Fish and Wildlife Service.

habitat suitability index models.

Ecol. Servo n.p.

2Terrell, 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.

iii
iv
CONTENTS

PREFACE iii

FIGURES vi

ACKNOWLEDGMENTS vi i

HABITAT USE INFORMATION................................................ 1

Genera 1 1

Age, Growth, and Food 1

Reproduct ion 1

Specific Habitat Requi rements 2

HABITAT SUITABILITY INDEX (HSI) MODELS................................. 5

Model Applicability............................................... 5

Model Description................................................. 6

Model Description - Riverine...................................... 6

Model Description - Lacustrine................... 10

HSI Calculation................................................... 12

Suitability Index (SI) Graphs for Model Variables 12

Riverine Model 18

Lacustrine Model 24

Application of Lacustrine Model................................... 25

Interpreting Model Outputs 25

ADDITIONAL HABITAT MODELS 27

Modell....................................................... 27

Model 2 27

Mode 1 3 28

Mode 1 4 28

INSTREAM FLOW INCREMENTAL METHODOLOGY (IFIM) 28

Suitabil ity Index Graphs as Used in I FIM 28

Availability of Graphs for Use in IFIM 30

REFERENCES 37

v
Figure

1

2

3

4

5

6

FIGURES

Tree diagram illustrating relationships between model

variables, model components, and HSI for the walleye

in ri veri ne envi ronments .

Tree diagram illustrating relationships between model

variables, model components, and HSI for walleye in

1acustri ne envi ronments .

SI curves for adult wa 11 eye habitat ..

SI curves for juvenile walleye habitat

Category two SI curves for walleye fry habitat .

SI curves for walleye spawning habitat

vi

7

11

32

33

34

36
ACKNOWLEDGMENTS

We wish to acknowledge the following reviewers who provided many helpful

comments and suggestions: B. Griswold, Great Lakes National Fisheries Reseach

Center; J. F. Ki tche 11, J. Lyons, and B. John son, Center for Li mno logy,

University of Wisconsin, Madison; W. T. Momot, Department of Biology, Lakehead

University, Ontario; J. Ney, Virginia Polytechnic Institute and State

University, Blacksburg, Virginia; P. D. Inskip, Harvard University, Boston,

Massachusetts; and B. Nelson and D. Rondorf, Seattle National Fisheries

Research Center. W. R. Persons, W. G. Workman, and R. V. Bulkley, Utah State

University, Logan, Utah developed a preliminary draft and bibliography that

provided useful raw material. C. Short provided editorial assistance. Word

processing was by C. J. Gulzow and D. E. Ibarra. K. Twomey assisted in

finalizing the manuscript. The cover illustration is from Freshwater Fishes

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

Scott and E. J. Crossman.

vii
WALLEYE (Stizostedion vitreum vitreum)

HABITAT USE INFORMATION

Genera 1

The wall eye is native to freshwater ri vers and 1akes of Canada and the

United States, with rare occurrences in brackish water (Scott and Crossman

1973). In the United States, its native range occurs primarily in drainages

east of the Rocky Mountains and west of the Appalachians; however, it has been

widely introduced into reservoirs outside its native range (Colby et al.

1979). Walleye hybridize with sauger (S. canadense) and blue pike (S. v.

glaucum) (Scott and Crossman 1973). - - -

Age, Growth, and Food

Walleye live at least 17 years in cool northern waters (Momot pers.

comm.); age VIII or younger fish were predominant in Tennessee impoundments

(Hackney and Holbrook 1978). Males mature at age II to IV and females at age

III to VIII (Scott and Crossman 1973; Colby et al. 1979). Growth of walleye

depends primarily on food supply (Swenson and Smith 1976), temperature (Koenst

and Smith 1976; Hokanson 1977), and population density (Carlander and Payne

1977; Kempinger and Carline 1977). In general, length of sexually mature

walleye (age III+) is> 30 cm (Colby et al. 1979).

Walleye fry eat zooplankton and aquatic insects and start feeding on fish

at 1.5 to 2.5 cm in length (Forney 1966; Bul kl ey et al. 1976). The diet of

juvenile and adult walleye consists primarily of fish, but aquatic invertebrates, particularly mayfly larvae and crayfish, may be locally or seasonally

important (Priegel 1963; Wagner 1972; Johnson and Hale 1977). In northern

areas, age 0+ and 1+ yellow perch often account for a large portion of the

diet in classic large, shallow perch-walleye lakes (Forney 1977; Kelso and

Ward 1977). In the southern parts of the walleye range, clupeids and

centrarchids often are most important (Miller 1967; Momot et al. 1977; Fitz

and Holbrook 1978). Cannibalism may become significant when other prey are

scarce (Chevalier 1973; Forney 1974).

Reproduction

The water temperature regime and the qual ity and quantity of suitable

substrate are major factors affecting walleye reproductive success (Scott and

Crossman 1973; Co 1by et a1. 1979). Wa 11 eye spawn in spri ng duri ng peri ods of

1
rapid warming soon after ice break-up (Colby et al. 1979). Spawning is usually

initiated at water temperatures of 7 to 9° C, with most spawning occurring in

the range of 6 to 11° C (Scott and Crossman 1973). Preferred spawning habitats

are shallow shoreline areas, shoals, riffles, and dam faces with rocky

substrate and good water circulation from wave action or currents (Eschmeyer

1950; Johnson 1961; Colby et al. 1979). Lacustrine populations often migrate

up rivers to spawn (Priegel 1970).

Walleye spawning activity occurs at night (Ryder 1977) and is often concentrated within a few days. Eggs are broadcast freely over the substrate and

fall into cracks and crevices (Scott and Crossman 1973). Walleye do not

provide any parental care (Balon et al. 1977).

Specific Habitat Requirements

Habitat requirements of walleye have been summarized in reviews in the

PERCIS Symposium [J. Fish. Res. Board Can. 34(10) Oct. 1977J and by Kendall

(1978), and Colby et al. (1979). Walleye are tolerant of a wide range of

environmental conditions (Scott and Crossman 1973) but are generally most

abundant in moderate-to-large lacustrine (> 100 ha) or riverine systems

characterized by cool temperatures, shallow to moderate depths, extensive

littoral areas, moderate turbidities, extensive areas of clean rocky substrate,

and mesotrophic conditions (Kitchell et al. 1977; Leach et al. 1977). Kitchell

et al. (1977) suggest that the 1ittoral and subl ittoral habitats occupied by

walleyes in lakes are the equivalent of extensions of suitable riverine habitat

into the lacustrine environment.

Walleye survival, growth, and standing crop have been related to the

abundance and availability of the small forage fishes it utilizes as food

(Jester 1971; Forney 1974; Swenson and Smith 1976; Momot et al. 1977; Groen

and Schroeder 1978). Light conditions also are an important factor affecting

walleye distribution, abundance, and feeding (Ryder 1977). Walleye survive

and grow in a wide range of turbidities (Ali et al. 1977; Ryder 1977), but

reach their highest abundance in moderately turbid conditions (Ryder 1968;

Elsey and Thomson 1977; Kitchell et al. 1977; Ryder and Kerr 1978). Peak

feeding occurs at water transparencies of approximately 1 to 2 m Secchi disk

depths, with a great decrease in activity at < 1 or > 5 m Secchi disk depths

(Ryder 1977). Walleye feed most actively under low light intensity. Lower

standing crops of walleye in clear lakes may be at least partially attributable

to the reduced length of time favorable for feeding (Ryder 1977; Swenson

1977). However, this relationship may not always hold in deep, clear lakes

with adequate forage (e.g., cisco or whitefish, Coregonus ~.) available in

deep water (Momot pers. comm.).

Walleye fry are photopositive until becoming demersal at lengths of 25 to

40 mm (Ney 1978). The demersal fry, juveniles, and adults are very photosensitive. They actively seek the shelter of dim light during periods of

strong light intensities in clear waters (Scherer 1971; Ryder 1977). They are

often found in deep or turbid water or in contact with the substrate under

cover of boulders, log piles, brush, and dense beds of submerged vegetation

during the day (Ryder 1977).

2
Walleye are generally most abundant in lakes or lake sections classified

as mesotrophic (Regier et al. 1969; Kitchell et al. 1977; Leach et al. 1977;

Schupp 1978). They are less abundant in oligotrophic conditions (usually

dominated by salmonids) and in eutrophic conditions (usually dominated by

ce nt r arc hid s ) ( Kit c hell eta1. 1977) . Eut r 0 phi cat ion ten d s t 0 sign ifi can t 1y

reduce habitat quality for walleye (Kitchell et al. 1977; Leach et al. 1977;

Momot et al. 1977; Schupp 1978). Ryder et al. (1974) and Ryder and Kerr

(1978), considering only Precambrian Shield lakes of the north temperate

boreal forest zone, found walleye to be most abundant in lakes or lake sections

with morphoedaphic indices (MEl) in the mesotrophic range of about 6.0 to 7.2.

Carlander (1977), in contrast, found no correlation between MEl and walleye

biomass in 23 lakes and reservoirs located over a broad geographic range. He

concluded that the lack of correlation between biomass or yields of walleye

and the usual indicators of productivity (e.g., MEl) was probably due to the

fact that walleye populations do not bear a constant relationship to the total

f ish b i omas s 0 r y i e 1d .

Walleye are commonly found in lakes with a pH ranging from 6.0 to 9.0;

the species exhibits no behavioral changes when exposed to varying pH levels

within this range (Scherer 1971). Lower pH levels « 6.0) are associated with

failures in reproduction (Anthony and Jorgenson 1977) and recruitment (Spangler

et al. 1977). Higher pH levels (> 9.0) generally are unsuitable for most

freshwater fish (McKee and Wolf 1963).

Adult. Adult walleye generally are found under cover in moderately

shall~< 15 m) waters during the day and move inshore at night to feed

(Johnson and Hale 1977; Ryder 1977). Adults often are found in areas with

slight currents (Ryder 1977), except during the winter when they tend to avoid

turbulent areas (Colby et al. 1979). Using the velocity equation developed by

Jones et al. (1974), the critical velocity (maximum velocity that can be

sustained for 10 min) for adult walleye 30 em in fork length is 74 em/sec

[critical velocity = (13.07)LO. 51, where L = fork length in cm].

Preferred (optimum) temperatures for grow.th of adults are 20 to 24° C

(Dendy 1948; Ferguson 1958; Kelso 1972; Huh et al. 1976). Adults seem to

avoid temperatures > 24° C, if possible (Fitz and Ho l br-ock 1978). Kelso

(1972) reported that growth in adults ceases at temperatures < 12° C. Upper

lethal temperatures of 29 to 32° C were reported by Hokanson (1977), while

Wrenn and Forsythe (1978) reported an upper lethal range of 34 to 35° C.

Momot et al. (1977) attributed low survival and poor growth of age lV+ fish in

a eutrophic central Ohio reservoir to absence of areas of summer habitat with

cool « 24° C) water and adequate (> 5 mg/l) dissolved oxygen.

Adult walleye can tolerate dissolved oxygen (DO) levels of

short time (Scherer 1971), but the greatest abundance of walleye

minimum DO levels are greater than 3 to 5 mg/l (Dendy 1948).

< 1 mg/l are 1etha 1 (Scherer 1971).

2 mg/l for a

occurs where

DO 1eve 1s of

Embryo. Highest embryo production and survival has been observed on

clean gravel or rubble substrates (2.5 to 15 cm in diameter) (Johnson 1961).

Survival also is good on dense mats of vegetation with adequate water circulation (Priegel 1970). Percent survival of embryos is greatly reduced on sand,

3
and survival of eggs deposited on soft muck and detritus is negligible (Johnson

1961; Priegel 1970). Years of highest embryo production in lakes are often

associated with rising or stable spring water levels that increase the amount

of littoral area available for spawning and prevent stranding of embryos

(Johnson 1961; Chevalier 1977; Groen and Schroeder 1978).

Embryos require well-oxygenated water (Balon et al. 1977), and DO levels

5 mg/l are considered necessary for high survival and growth (Oseid and

Smith 1971). DO levels s 3.4 mg/l resulted in delayed hatching and a significant reduction in size at hatching (Colby and Smith 1967; Siefert and Spoor

1974). Streamflows and wind-generated currents in spawning areas must be

sufficient for adequate circulation of oxygenated water around embryos (Priegel

1970). Positive correlations between spring river discharge and walleye year

class strength have been reported for several rivers (Nelson and Walburg 1977;

Spangler et al. 1977). The nonadhesive eggs can be dislodged from the

substrate if stream flows or wind-generated currents are too high (Eschmeyer

1950; Priegel 1970). In the Great Lakes, the littoral substrate of exposed

shoreline areas may be unsuitable for spawning due to strong wave action.

Sedimentation (Benson 1968) and anoxia-producing pollutants (Colby and Smith

1967) are other factors that can reduce the availability of oxygen and, therefore, affect the survival of embryos.

Proper maturation of gonads in female walleyes requires minimum winter

water temperatures of < 10° C (Hokanson 1977). Mill er (1967) reported that

walleyes failed to reproduce in a reservoir with minimum winter temperatures

of 10 to 12.5° C. Embryos are adapted to stead i ly i ncrea sing water

temperatures during the spring. Optimum temperatures are 6 to 9° C for

fertilization and 9 to 15° C for incubation (Koenst and Smith 1976). Upper

lethal (TL50) temperatures for embryos are near 19° C (Smith and Koenst 1975).

Eggs hatch in 14 to 21 days at temperatures of 8 to 15° C (Ney 1978). Steady

spring warming rates of 0.28° C/day have been positively correlated with

embryo and fry production (Busch et al. 1975). Poor survival of embryos is

associated with cold water temperatures due to slow spring warming rates

[< 0.18° C/day (Busch et al. 1975)J, cold weather fronts (Busch et al. 1975),

or release of cold reservoir water into tailwaters during spawning and incubation (Pfitzer 1967).

Fry. Stream velocities in spawning tributaries must be sufficient to

transport fry downstream to lakes within the period of yolk-sac absorption (3

to 5 days) or fry will perish from lack of food (Priegel 1970). Fry will not

begin to feed at temperatures < 15° C (Smith and Koenst 1975). Momot et al.

(1977) reported that stocked walleye fry exhibited greater survival when there

was a high availability of newly hatched gizzard shad (Dorosoma cepedianum) at

time of stocking.

Optimum temperatures for growth of walleye fry are near 22° C (Kelso

1972; Huh et al. 1976; Koenst and Smith 1976). No growth occurs at temperatures s 12° C or 29° C (Kelso 1972; Hokanson 1977). Upper lethal temperatures for fry are in the range of 31 to 33° C (Smith and Koenst 1976;

Wrenn and Forsythe 1978). Conditions that reduce or retard growth (e.g., low

4
temperature, low zooplankton abundance, and delayed hatching) can greatly

affect fry overwinter survival because smaller fry experience more overwinter

mortality than larger fry (Forney 1966).

Optimum DO concentrations for fry are 5 mg/l (Siefert and Spoor 1974).

Moyle and Clothier (1959) reported that DO levels below 5 mg/l resulted in

poor survival of stocked fry. Low DO levels also retard fry development

(Oseid and Smith 1971) and reduce swimming ability (Siefert and Spoor 1974).

Fry can withstand only slight current velocities (Houde 1969). Walburg

(1971) and Groen and Schroeder (1978) reported that high velocities near a

reservoir outlet can result in significant fry losses, particularly if spawning

occurs at the dam face.

Juvenile. Habitat requirements for juvenile walleye seem to be similar

to those of adults (Colby et al. 1979). Using the previously described regression equation from Jones et al. (1974), the critical velocity for juveniles

wi th a fork 1ength of 20 cm is 60 cm/ sec.

HABITAT SUITABILITY INDEX (HSI) MODELS

Model Applicability

Geographic area. This model is applicable to North American waters

within the native and introduced range of walleye. The standard of comparison

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

within this area. Optimum conditions will most likely occur in the northern

United States, southern Canada, or within the median temperature envelope

boundaries of percids, as defined by Hokanson (1977).

Season. The model provides an index for a riverine or lacustrine habitat

based on its ability to support all life stages of walleye throughout the

year.

Cover types. The model is app 1i cab1e in ri veri ne, 1acustri ne, and

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

Minimum habitat area. Minimum habitat area is defined as the mt nnnum

area of contiguous, suitable habitat that is required to sustain a population.

The minimum habitat area required by walleye populations is unknown, but

relatively large lakes (> 100 ha) or river systems are more likely to provide

adequate conditions for spawning (Kitchell et al. 1977; Leach et al. 1977).

Self-sustaining walleye populations are generally rare in small lakes that are

not connected to other lakes (Johnson et al. 1977). However, walleye are

often abundant in small lakes « 400 ha), where natural reproduction is

supplemented by stocking (J. Lyons, pers. comm.; B. Johnson, pers. comm).

Kitchell et al. (1977) noted that while walleye were present in many small

« 100 ha) lakes, they were abundant in only a few.

5
Verifi cation 1eve 1. The model represents our i nterpretat i on of how

selected environmental factors limit potential carrying capacity. Portions of

the model have been subjected to limited field application, by comparison with

standing crop and catch per unit effort data. Reviewers of the model have

recommended extensive testing and evaluation before accepting the model, or

port ions of the mode 1, based on suitabi 1ity index graphs as an accurate

predictor of habitat quality. We agree with these recommendations.

Model Description

The Habitat Suitability Index (HSI) model that follows has two versions:

riverine and lacustrine. These two versions condense the preceding observations into a set of measurable habitat variables. The model is structured to

produce an index of walleye habitat quality between 0.0 (unsuitable) and 1.0

(optimum). A positive relationship between HSI and carrying capacity is

assumed but has not been demonstrated. Habitat variables believed to be

important in limiting distribution, abundance, or survival of walleye are

included in the models. An assumed functional relationship between each

habitat variable and habitat suitability is represented in a variable suitability index (SI) graph. It is assumed that SI ratings for different habitat

variables can be compared. This is one of the weakest model assumptions. It

is likely to be violated for some ranges of the selected variables because the

impacts (e.g., changes in growth rates, survival rates, distribution, and

abundance) measured by each variable are not directly comparable. The model

is likely to provide the most accurate description of carrying capacity when

all of the variables have extreme SI values; i.e., either near optimum or

unsuitable.

Walleye habitat quality is represented by food, cover, water quality, and

reproductive components. Variables that are thought to be direct or indirect

measures of the relative ability of a habitat to meet these requirements are

included in the appropriate component. Variables that affect habitat quality

for walleyes, but do not easily fit into one of these four major components,

are combined under the "other component." heading.

It should be noted that not all variables that potentially affect walleye

populations are included in the models. Variables were not included if:

(1) the variable was adequately measured by another variable(s); or (2) it

would be difficult to measure the variable quantitatively [e.g., effects of

inter- and intraspecific interactions on walleye biomass (Forney 1977)J.

Model Description - Riverine

The structure of the riverine HSI model for walleye is presented graphically in Figure 1.

Food component. Average Secchi disk depth (V1 ) is considered part of the

food component because feeding activity is related to transparency (light)

conditions. The optimum transparency range depicted in the graph is reasonably

well defined in the literature from observations of conditions associated with

6
Habitat variables Life requisite

Transparency (Vl)----------------~>Food ----------,

Forage fish abundance (V2)--------~

Transparency (V 1 ) ------------------->Cove r ------------..... Percent cover (V3)----------------~·

HSI

pH (V 4) -------------.

D.O. (fry) (V 6 ) ---------------iWater Quality---'

Temperature (gonad maturation) (V ll ) --~Reproduction ------'

D.O. (embryo) (V 7 ) -------~

Temperature (fry) (V 9 ) ---l

D.O. (adult, juvenile) (V s ) ---------..

Temperature (adult, juvenile) (Va)

Temperature (embryo) (V10)--------~

Spawning habitat index (V 1 2 ) - - - -J

Water level (V13)----------------~

Figure 1. Tree diagram illustrating relationships between model

variables, model components, and HSI for the walleye in riverine

environments.

7
high feeding levels. Walleyes occur in very clear waters, although the time

available for efficient foraging is reduced in those lakes that lack deep

water and deep-water prey, such as cisco (Ryder 1977; Momot, pers. comm.). It

was assumed that walleyes can find some shelter from light even in very clear

waters, either in the form of cover or deep water; therefore, the descending

limb of the graph remains above zero. Too much turbidity favors competitors,

such as centrarchids (Kitchell et al. 1977), and apparently results in reduced

feeding efficiency (Ryder 1977). Although some feeding probably occurs at

high turbidity levels, the graph descends to 0 at very low Secchi disk depths,

because it was assumed that clogging and abrasion of gills or high embryo

mortality would occur at these levels.

The relative abundance of forage fishes (V2 ) was included in this

component because growth, food consumption, and standi ng crop of wa 11 eye are

related to forage abundance. The index of relative abundance was measured in

units of mg/m 3 of prey density, after Swenson and Smith (1976).

Variables V1 and V2 are assumed to be direct measures of food availability. Therefore, an increase in the suitability of either food component

variable is assumed to increase the amount of available food by the same

amount, regardless of the other food component variable rating. This assumption is expressed by combining variables through a simple arithmetic mean.

Cover component. The cover component was broken down into two subcomponent ratings, based on the amount of cover related to light conditions and

cover in the form of physical shelter. Transparency (V1 ) is included in a

light intensity subcomponent because standing crop of walleye is reduced in:

(1) clear water without sufficient water depth to provide cover from bright

light; or (2) in very turbid waters where sauger (S. canadense) or centrarchids

predominate (Leach et al. 1977; Ryder 1977). Percent of area with cover (V3 )

is included in both subcomponents because cover is used both as an escape from

intense light levels and as a resting area to avoid high water velocities.

The importance of percent cover (V 3 ) for shelter from light is assumed to

vary. When transparency is too high to be optimum (Secchi disk transparency > 3.2 m), cover should become more important in determining habitat quality

because the clearer the water, the greater the need to have cover to escape

from high light intensities. These assumptions are quantified by combining

the two variable ratings into a subcomponent of cover related to the ability

of a water body to provide shelter from light. The coefficients in the equation quantify these subjective opinions; they are not the result of rigorous

experimentation.

If the Secchi transparency is < 3.4 m (3.4 m rates an SI of 0.9), the

subcomponent equals:

8
This equation reflects the greater importance of transparency (VI) in determining habitat quality in terms of cover from light in waters that have near

optimum or lower than optimum transparency levels. It could be ctrgued that,

when water transparency is too low to be optimum, percent cover should not be

included in a subcomponent rating depicting cover from light. Percent cover

was left in the equation because transparency levels can be variable and COV2r

can occasionally become important in water that normally has transparency

levels too low to be optimum. If the Secchi transparency is greater than

3.4 m, the SI rating is less than 0.9 and is determined from the descending

limb of the SI curve for VI' In this situation, the subcomponent equals:

where N = [10(1-S1 of VI)]' The second equation provides the same answer as

the first equation when VI has an SI of 0.9. It predicts a slower drop in

suitability when increasing transparency is associated with high cover ratings

than when it is associated with low cover ratings. The equation thus

quantifies the assumption that cover is more important for shelter from light

when the water is too clear to be optimum.

Water quality component. Dissolved oxygen (Vs, V6 ) and temperature (Va,

V9 ) levels for adults-juveniles and fry, respectively, as well as pH (V4 ) , are

i ncl uded because these water qua 1i ty parameters affect growth, survi va1, or

feeding (or all three) in walleye. Suboptimum levels of these variables are

defined primarily from well-documented negative impacts that do not appear to

be mitigated by a higher suitability of other variables. This, and the fact

that the dependency of dissolved oxygen requirements on temperature is included

in the variable definition, justifies combining these variables into a subcomponent rating by selecting the lowest variable rating.

Reproduction component. Dissolved oxygen (V 7 ) , mean weekly temperatures

in spring (V lO ), and minimum winter water temperatures (V ll ) are included in

this component because they can be limiting factors to successful embryo

survival or gamete development. Quantity (percent riffles in riverine situations or littoral area in lacustrine situations) and quality (substrate type)

of spawning habitat have been shown to affect embryo survival and production

and, therefore, are included in a spawning habitat index (V I 2 ) based on the

product of quantity (percent riffle or littoral area> .3 m but < 1.5 m deep)

and qual ity (determined from a substrate index) of spawning habitat. Model

users may want to modify the depth criteria based on available data for local

walleye populations.

9
In order to interpret the spawn i ng habi tat index, it is necessary to

assume some optimum quantity of spawning habitat needed to ensure maximum

reproductive success. This quantity is likely to vary for different types of

water bodies in different geographic areas, and the impact of a change in

spawning area is likely to be difficult to evaluate. For example, Busch

et al. (1975) found that, while suitable spawning habitat (and walleye populations) in western Lake Erie had been substantially reduced from historical

levels, the remaining spawning reef area of 51.3 to 110.4 ha (depending on

water level) was still capable of producing strong year classes of walleye in

the western basin. However, the limited spawning habitat appeared to be a

factor in making spawning success more vulnerable to variations in weather. A

high value (20%) was selected as the optimum proportion of a water body that

should meet the criteria for spawning. Model users should critically evaluate

the suggested percentage and modify it based on local data. Multiplication of

the derived spawning substrate index (e.g., 0.20) by the maximum possible

spawning substrate index (e.g., 200, derived by multiplying 100% rubble times

the proposed weighting factor of 2) obtainable for a specified area resulted

in a product of 40 (see spawning habitat index V1 2 ) . Therefore, 40 was defined

as the optimum value of the spawning habitat index (V 12 ) and a suitability

index of 1.0 was assigned to all spawning habitat indices 40. A spawning

habitat index of 0 was equated to an H5I of 0 because 0 was believed to represent conditions where the likelihood of successful reproduction is nil (e.g,

100% silt = spawning habitat index of 0).

Water level during the spawning period (V13 ) is also included in this

component because the water level can affect the area and type of substrate

available for spawning; it has also been related to year-class strength. A

suboptimum water level fluctuation was assumed to consistently have a negative

impact on reproductive success; this is especially so because walleye spawning

is restricted to a relatively short time period in the spring.

Compensation among reproduction variables was considered unlikely; therefore, the lowest variable rating among the combined variables was selected as

the subcomponent value.

H5I calculation. The H5I was defined as the minimum value for any

component 51 because "s ubop t imurn" conditions for a component were assumed to

represent conditions that have measurable negative impacts on individuals and

thus limit carrying capacity even when other conditions are optimum.

Model Description - Lacustrine

The structure of the lacustrine H5I model for walleye is shown in

Figure 2. The model includes the components from the riverine model, with

an "o the r" component added to the mode1.

\lOther\l component. A measure of the trophic status of a lake (V 1 4 ) is

assumed to be a general determinant of habitat suitability for walleye because

abundance of walleye often has been related to trophic conditions. Trophic

status is a composite variable that includes many of the factors that appear

10
Habitat variables Life requisite

HSI

pH (V 4) ----------------..

Transparency (Vl)----------------~

_______~> Food -----, Forage fish abundance (V 2 ) -

Water level (V 1 3 ) ------------------/

Transparency (V 1 ) -------------------

Cove r ---------.,

Percent cover (V 3 ) --------~-~

o.O. (embryo) (V 7) ----------..

Temperature (adult, juvenile) (Va)

D.O. (adult, juvenile) (Vs)----~

Trophic class (V 1 4 ) ------------- Other----~

Temperature (fry) (V g ) ------~

Temperature (embryo) (VID)-----~

D.O. (fry) (VG)--------------:')Water Quality

Temperature (gonad maturation) (V 1 1)------7Reproduction

Spawning habitat index (V 1 2 ) -----'

Figure 2. Tree diagram illustrating relationships between model

variables, model components, and HSI for walleye in lacustrine

environments.

11
to affect walleye population levels and is, therefore, assumed to have an

impact on carrying capacity. Trophic status is considered a potentially

useful variable for predicting the suitability of future habitat conditions

for walleye populations in some types of lakes. However, the variable may be

biased towards Canadian shield lakes and inadequately represent excellent

walleye lakes that are large and relatively eutrophic but do not stratify for

extended periods of time. The trophic status variable is in the model in

order to call attention to a variety of environmental variables that may be

useful in providing a very general description of walleye habitat quality.

Users should evaluate the accuracy of the trophic status definition they

select under environmental conditions similar to those where the model will be

applied.

HSI Calculation

The HSI was defined as the minimum component value for the same reasons

described for the riverine model.

Suitability Index (SI) Graphs for Model Variables

Suitability index graphs pertain to riverine (R) or lacustrine (L)

habitats or both.

Habitat

R,L

Variable

Average transparency

(Secchi depth) during

summer.

12
R,L Vz Relative abundance of 1.0

small « 12 cm) forage

fishes during spring 0.8

and summer (fry, x

Q)

juvenile, and adult). -0

s::

...... 0.6

Note: SI for this variable for »

+-'

predicted or future con- ...... 0.4

ditions can be based on ......

..0

standing crop predictive <t:l

+-' 0.2 models, such as those

presented by Aggus and V')

Morais (1979). 0.0

0 200 >400

mg-prey/m3

LOW > HIGH

R,L V3 Percent of water body 1.0

with cover (boulders,

log piles, brush, 0.8 submerged vegetation) x

Q)

and adequate dissolved -0

s::

oxygen (> 3 mg/l) during ...... 0.6

the spring and summer »

+-' (fry, juvenile, and adult). ......

,..... 0.4 ......

..0

<t:l

+-'

...... 0.2

V')

0.0

20 40 60 >80

%

R,L V4 Least suitable pH 1.0

during the year.

x 0.8 Q)

-0

s::

...... 0.6

»

+-'

......

:;: 0.4 ..0

<t:l

+-'

.; 0.2 V')

0.0

4 6 8 10 12

pH

13
R,L

Vs Minimum dissolved oxygen 1.0

level in pools and runs (R) or above thermocline 0.8 ( L) in summer (adult and x

(l)

juvenile). "'0c

...... 0.6

c-,

+.>

......

r-

...... 0.4 oD

<0

+.>

::l 0.2 Vl

0.0

2

4 6 8

mg/l

R,L

V6 Minimum dissolved oxygen 1.0 level during summer-fa 11

along shallow shoreline areas (fry).

x 0.8 (l)

"'0C

...... 0.6

c-,

+.>

......

r- 0.4 ......

.a

<0

+.>

...... 0.2 ::l

Vl

0.0

2

4 6 8

mg/l

R,L

V7 Minimum dissolved oxygen 1.0 level measured in

spawning areas during

spri ng (embryo).

x 0.8 (l)

"'0C

...... 0.6

c-,

+.>

......

...... 0.4 oD

<0

+.>

......

::l 0.2 Vl

0.0

2

4 6 8

mg/l

14
R,L Va Mean weekly water 1.0

temperature in pools

(R) or above thermo- x 0.8 cline (L) during <lJ

summer (adult and -0

s::

juvenile). ...... 0.6

>,

+-'

......

...... 0.4 .0

n::l

+-'

......

:::J 0.2 (/)

0.0

12 16 20 24 28 32

°C

R,L Vg Mean weekly water 1.0

temperature in

shallow shoreline 0.8 areas during late x

<lJ

spring-early summer -0

s::

(fry) . ...... 0.6

>,

+-l

......

r--

...... 0.4 ..c

n::l

+-'

...... 0.2 :::J

(/)

0.0

12 16 20 24 28 32

°C

R,L VlD Mean weekly water 1.0 temperature during

spawning in spring

(embryo) . x 0.8 <lJ

-0

s::

...... 0.6

>,

+-'

......

...... 0.4 ..c

n::l

+-l

......

:::J 0.2 (/)

0.0

4 8 12 16 20 24

°C

15
R,L

R,L

1.0

VII Degree days between

4 and 10° C from

x 0.8

October 30 to April 15. (1)

-0

(Calculate by multi- t::

...... 0.6 plying water tempera- >,

tures in the range of ...... 0.4 4 to 10° C by number ......

of days that are in .0

this temperature range. ...... 0.2

For example, 160 days (/)

of 6° C 960 degree- 0.0 days SI of 1.0).

0 500 1000 1500 2000 2500

Degree -days

Spawning habitat index.

I

""

R,L

Calculated by multiplying the

proportion of the water body

composed of riffle or littoral

areas> 0.3m but< 1.5 m deep

by the substrate index where

the substrate index is defined

by the following equation:

Substrate Index 2(% gravel/

rubble 2.5 to 15 cm in

diameter)+ (% boulders/

bedrock)+ 0.5(% sand)+

0.5(% dense vegetation)+

0(% silt/detritus).

Water level during

spawning and embryo

development (embryo).

A) Rising or normal

and stable:

abundance of

shallow shoreline

or shoal areas

for spawning.

B) Low: many

spawning areas

are exposed, and

never inundated.

C) Fluctuating: fluctuations sufficient

to alternately expose and f1 ood

spawning areas.

16

x 0.8 (1)

-0

t::

......

>, 0.6

......

...... 0.4 .0

+>...... 0.2 (/)

0.0

1.0

x 0.8 (1)

-0

t::

...... 0.6

>,

+>...... 0.4 ......

.0

...... 0.2 (/)

0.0

A

50

Spawning index B

c

>100
L

Note:

Vl 4 Trophic status of lake

or lake section.

The following list of parameter

levels can be used to classify

a water body according to trophic

status (adapted from Leach

et al. 1977).

1.0

0.8

-0

s:::

....... 0.6

>,

+-'

:;: 0.4 ..c

ro

+-' 0; 0.2 (/')

0.0

0-1

Parameter (Oligotrophic)l

Primary production

rate low

Organic matter in

sediments low

Hypolimnetic O2 loss low

Trophic status

1-2

(Mesotrophic)

moderate

moderate

moderate

o 2

Trophic status

2-3

(Eutrophic)

high

high

high

3

Nutrient loading

rates (phosphorus,

nitrogen)

Morphoedaphic

index (MEl)

(metric)

Transparency

(Secchi depth)

low

< 5.9

high (> 6 m)

moderate

6.0-7.2

moderate (1-6 m)

high

> 7.3

low « 1m)

lFor actual values of these parameters for each trophic status, refer to Leach

et al. (1977). Values may differ by geographic location.

17
Riverine Model

This model attempts to describe life requisite requirements separately

and consists of four components: Food, Cover, Water Quality, and Reproduction.

Rationale for the form of the equations is the same as that for the riverine

mode 1.

(2) Cover (CC)

Cc = the lowest of the subcomponent ratings for cover from the

appropriate CL' where:

C = -----,,--- L 4

(3) Water Quality (CWQ)

when Secchi transparency is 3.4 m

when Secchi transparency is > 3.4 m

N = [10(1-S1 of V1 ) ]

(4) Reproduction (CR)

(5) HS1 determination

HS1 = the lowest of CF' CC' CWQ' or CR

Sources of data and a synopsis of the assumptions made in developing

suitability indices are presented in Table 1.

18
Table 1. Sources of information and assumptions used in construction of

the suitability index graphs are listed below. "Excellent" habitat for

walleye was assumed to correspond to an SI of 0.8 to 1.0, "good" habitat

to an .SI of 0.5 to 0.7, "fair" habitat to an SI of 0.2 to 0.4, and "poor"

habitat to an SI of 0.0 to 0.1.

Variable Assumptions and sources

Transparency levels of 1 to 3 m Secchi disk depths were considered excellent because feeding activity in the lightsensitive walleye is highest under moderately turbid conditions

(Ryder 1977). Secchi depths < 1 m or > 5 m were deemed fair

because feeding activity is greatly reduced in very turbid or

very clear waters.

High abundance of forage fishes was considered excellent because

strong year-classes of walleyes develop when small forage fishes

are both abundant and available (Jester 1971; Forney 1977).

Groen and Schroeder (1978) reported that walleye abundance in

Kansas reservoirs increased substantially following implementation of water management plans that provided higher water levels

in the spring and also resulted in increased habitat and production of forage fishes. Low forage fish production or availability at the time walleye fry switch to piscivory results in

increased cannibalism (Forney 1977) and reduced recruitment and

growth of walleye populations (Momot et al. 1977) and, therefore, was considered to provide only "fairll habitat conditions.

Forage abundance was defined in units of mg/m 3 , based on the

work of Swenson and Smith (1976) and Swenson (1977) who showed

that walleye prey consumption rate was low at prey densities

< 50 mg/m 3 , but increased with increasing prey densities and

stabilized at prey densities> 400 mg/m 3 •

There are no quantitative data relating amount of cover to walleye standing crop or abundance. However, walleye of all sizes

strongly favor shelter or dim light during the day (Scherer

1971) and are often found under cover of boulders, logs, brush,

or submerged vegetation during periods of high light intensity

(Ryder 1977). Thus, areas with sparse cover are assumed to be

less suitable as walleye habitat. Too much vegetation is

assumed to reduce habitat suitability by reducing foraging

ability (Swenson 1977).

19
Table 1. (continued).

Variable Assumptions and sources

pH levels in the range of 6.0 to 9.0 are considered goodexcellent. Levels within this range correspond to optimal pH

levels for freshwater fish in general (McKee and Wolf 1963).

Also, walleye exhibit no behavioral responses to pH changes

within this range. pH levels < 5.5 are deemed poor because

walleye spawning ceases at a pH 4.0 (Anthony and Jorgensen

1977) and because pH levels 5.5 are thought to be responsible

for recruitment failures in walleye populations (Spangler et al.

1977) .

D.O. concentrations identified by Davis (1975) as optimum for

Canadian nonsalmonid freshwater fish populations (~ 5.5 mg/l)

are considered excellent. Concentrations that resulted in

stress « 3 mg/l) or loss of equilibrium (0.6 mg/l) in walleye

in the laboratory (Scherer 1971) are deemed poor.

D.O. concentrations of 3 to 5 mg/l are considered fair because

Moyle and Clothier (1959) reported poor survival of stocked

walleye fry within this range. D.O. concentrations < 3 mg/l

are considered poor because Siefert and Spoor (1974) reported

that walleye larvae raised at 2.4 and 1.9 mg/l were noticeably

weak swimmers.

D.O. concentrations near saturation (> 6 mg/l) are considered

excellent because embryos require well-oxygenated water for

successful hatching (Colby and Smith 1967; Priegel 1970; Balon

et al. 1977). Concentrations < 3 mg/l are considered poor

because the size of walleye fry at hatching was significantly

reduced at < 3.4 mg/l (Siefert and Spoor 1974).

Temperatures < 12° C are considered poor because growth

does not occur at these temperatures (Kelso 1972). Temperatures

30° C are lethal (Koenst and Smith 1976) and, therefore,

also are deemed poor. "Excellent" habitat suitability is defined

as those temperatures (20 to 24° C) that correspond to the

highest growth rate (Kelso 1972; Smith and Koenst 1975) and

highest abundance (Dendy 1948; Ryder 1977). Temperatures of 25

to 30° C are considered fair to poor because walleyes appear to

exhibit a strong aversion to water temperatures> 24° C

(Fitz and Holbrook 1978).

20
Table 1. (continued).

Variable Assumptions and sources

Upper lethal temperatures for walleye fry [31.6° C (Smith and

Koenst 1975); 32 to 33° C (Wrenn and Forsythe 1978)J are deemed

poor, as are temperatures below those needed to initiate

feeding in fry in the laboratory [15° C (Smith and Koenst

1975)J. Temperatures identified as preferred [20.6 to 23.2° C

(Ferguson 1958)J or as optimum for growth [22° C (Huh et al.

1976; Koenst and Smith 1976)J are considered excellent. Temperatures near 16° C and 28° C are considered fair because

growth is slow at these temperatures (Huh et al. 1976).

Temperatures corresponding to the TL50 maximum (19.2° C) and

minimum « 6.0° C) (Smith and Koenst 1975) are deemed poor.

Temperatures corresponding to the highest percent hatch rate of

walleye embryos in the laboratory [9 to 15° C (Koenst and Smith

1976)J are considered excellent.

The shape of this SI graph was based primarily on temperature

requirements for gonad maturation in yellow perch (Perea

flavescens), a percid often sympatric with walleye that also

requires winter temperatures < 10° C for proper gonad maturation

(Hokanson 1977). Gonad maturation is a function of temperature

and time (Jones et al. 1974; Hokanson 1977); therefore, chill

duration (measured in degree-days) was used as the measure of

suitability. Chill durations are only calculated for temperatures < 10° C because no viable spawnings occurred in yellow

perch held at 12° C and Miller (1967) reported that walleye

failed to reproduce in a California reservoir with minimum

winter water temperatures of 10 to 12.5° C (Hokanson 1977).

A chill duration of > 2,000 degree-days is assumed to be of

poor suitability because only a small percentage of yellow

perch reared at 10° C for 200(= 2000 degree-days) or 240(= 2400

degree-days) days spawned successfully (Jones et al. 1974).

A chill duration of 740 to 1110 degree-days is deemed excellent

because Jones et al. (1974) reported that optimum conditions for

gonad maturation in yellow perch occurred when the fish were

exposed to 4 to 6° C temperatures for 185 days(= 740 to 1110

degree-days) starting October 30. A chill duration of 360

degree-days is considered the lower limit for gonad maturation

because only limited viable spawnings occurred in yellow perch

held at a minimum of 12° C, except for those held 45 days at

8° C(= 360 degree-days) (Jones et al. 1974; Hokanson 1977). It

should be noted that these laboratory results may not be

directly applicable to field situations, particularly when

dealing with populations near or beyond the southern limit of

the natural walleye range (Clugston et al. 1978).

21
Table 1. (continued).

Variable Assumptions and spurces

A rubble-gravel substrate is assumed to be excellent as spawning

habitat for walleye because: (1) gravel and rubble are preferred

for spawning when available (Eschmeyer 1950; Priegel 1970;

Nelson and Walburg 1977); (2) Chevalier (1977) reported that

walleye eggs are most abundant on beaches with gravel, rubble,

or shingle rock; (3) Johnson (1961) reported that percent

survival of walleye eggs was highest on gravel-rubble substrate;

and (4) the addition of gravel and rubble to marginal walleye

spawning areas is followed by increased egg deposition and

survival (Johnson 1961; Newburg 1975). Substrates where O2 is

low and/or water circulation is poor (i .e., sand, silt, and

detritus) are associated with low embryo survival (Johnson

1961; Colby and Smith 1967; Benson 1968; Priegel 1970) and

are deemed poor. Mats of dense vegetation are considered to be

moderately suitable because Priegel (1970) found good survival

of walleye eggs in dense grass-sedge vegetation with good water

circulation. Weighting factors used in the substrate index

equation were based on documented survival of embryos in the

order: gravel-rubble gravel-sand> sand> silt-detritus

(Johnson 1961; Priegel 1970).

A positive correlation between spring water levels and yearclass strength of walleye was reported by Chevalier (1977).

Stable or rising spring water levels result in more successful

reproduction in walleye by increasing the availability of

spawning and rearing habitat (Chevalier 1977; Groen and

Schroeder 1978). Therefore, stable or rising water levels are

considered excellent. Low water levels are considered fair

because Johnson (1961) and Chevalier (1977) reported that low

water levels decrease availability of spawning habitat by

exposing shallow rocky shoreline areas and shoals. Reservoirs

with rapidly fluctuating spring water levels are considered poor

because sudden drawdowns can interrupt spawning activity and

lead to stranding and dessication of eggs (Groen and Schroeder

1978). Also, high discharge rates accompanying rapid drawdown

can result in a significant loss of age 0 and older walleye

(Walburg 1971; Groen and Schroeder 1978). The degree of

lake drawdown necessary to expose spawning areas is likely to

vary, depending on the depth of major spawning areas. If site

specific data are lacking, a drop of 0.3 m from normal elevation should be defined as 11 0 W" because Johnson (1961) and

Chevalier (1977) reported that the majority of walleye spawn at

depths of 0.3 m or less.

22
Table 1. (concluded).

Variable Assumptions and sources

Walleye are most abundant in waters classified as mesotrophic;

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

(Regier et al. 1969; Kitchell et al. 1977; Schupp 1978). Schupp

(1978) reported that walleye abundance and growth in a large

heterogenous Minnesota lake was greatest in lake sections characterized by mesotrophic conditions. Walleye are less abundant

in deep, clear, unproductive lakes and in shallow, highly

productive areas. Kitchell et al. (1977) and Leach et al.

(1977) proposed the assumption that habitat quality for walleye

populations is related to the trophic conditions present in the

lake or lake section, with mesotrophic status most likely to

represent optimum conditions. Therefore, it is assumed that

the more eutrophic or oligotrophic a water body is, the less

suitable it is as walleye habitat. The trophic classification system of Leach et al. (1977) was revised for use as a

guide in classifying a water body as oligo-, meso-, or

eutrophic.

23
Lacustrine Model

This model utilizes the life requisite approach and consists of five

components: Food, Cover, Water Quality, Reproduction, and Other.

(2) Cover (CC)

when Secchi transparency is 3.4 m

when Secchi transparency is > 3.4 m

where N = [10(1-SI of V1 ) ]

(3) Water Quality (CWQ)

(4) Reproduction (C R)

Note: The variables in this component should be measured in

tributaries if that is where reproduction primarily occurs.

(5) Other (COT)

COT = V1 4

(6) HSI determination

HSI = the lowest of CF' CC' CWQ' CR' or COT

24
Sources of data and assumptions made in developing the suitability indices

are presented in Table 1.

Application of Lacustrine Model

Two modified versions of the lacustrine HSI model were appl ied to 10

lakes in Iowa, Wisconsin, and Minnesota using environmental and fish population data provided by Nickum (pers. comm.). Environmental data were used to

estimate five model variables: V1 , VJ , V4 , V1 2 , and V13 (Table 2). The

original model structure was retained, with the HSI defined as the lowest SI

of the cover component (derived from V1 and VJ ) , V4 , V1 2 , or-V 1 J • The second

modified model had the same structure, except that variables directly related

to reproductive success (V1 2 and V1 J ) were excluded.

The first modified model assigned only a "qcod" rating to an Iowa lake

with a standing crop of 38.7 fish/ha. However, this lake is stocked with

walleye fry, which could negate the impact of the availability of spawning

habitat on standing crop. The second modified model (HSI ' in Table 2) excluded

variables related directly to reproductive success and resulted in a high HSI

for the lake with the high standing crop. Both of the tested HSI model s

assigned high HSI's to Wisconsin and Minnesota lakes with high and low standing

crops and fair (0.2) and excellent (0.8) HSI's to two Minnesota lakes that

apparently contained no walleye.

The test results are consistent with the assumption that the type of HSI

model tested can predict an upper limit to population levels but not a lower

limit. High HSI's were associated with both high and low standing crops; low

HSI's were associated only with low standing crops. Lakes with very similar

habitat conditions (e.g., Wisconsin lakes 4 and 5), as rated by the mode ]

variables, had very different walleye population densities. This seems to

indicate that additional factors not included in the model were influencing

population levels.

The test results indicate that the SI of 0.7 assigned to 15% cover may be

either too low or that the combined effect of cover and light transparency are

incorrectly depicted in the model. This conclusion is based on the fact that

lake number three, which had the highest standing crop, had 15% cover. Therefore, the curve (VJ ) should probably be modified so that 15% cover receives an

SI of 1.0.

Interpreting Model Outputs

The models described above are generalized descriptions of habitat

requirements for walleye and are unlikely to discriminate among different

habitats with a high level of accuracy or precision at this stage of development. Each model variable is considered to have some effect on carrying

capacity for walleye, and the suitability index graphs depict this assumed

effect. However, the graphs are derived from a series of untested assumptions

and have unknown accuracy in depicting habitat suitability for walleye. The

model assumes that each model component alone can limit walleye production,

25
Table 2. Suitability indices for walleye in selected lakes.

v v V 1 3

V 4 12 Water

Standing 1 V

3

Lea st Spawning level

crop Secchi sUitable habitat du ring HSI' b

transp. % cove r pH index _----.i.Pawn ill~ without

La ke number fish/ fish/

HS,a V and

and State net ha Dat a SI Dat a SI Dat a SI Data SI Data SI 12 V

13

IA - 38.70 2.9 1. 00 50.0 0.90 7.2 1.0 125.5 1.0 2 0.5 0.50 0.98

2 IA - 2.60 0.5 0.30 5.0 0.35 8.1 1.0 50.0 1.0 1 1 .0 0.31 0.31

3 WI - 63.00 2.7 1. 00 15.0 0.70 7.4 1.0 112.5 1.0 1 1 . 0 0.90 0.90

4 WI - 1.70 1.5 1. 00 6.0 0.40 6.4 1.0 66.0 1.0 1 1.0 0.85 0.85

rv 5 WI - 12.10 2.7 1.00 7.0 0.40 7.0 1.0 58.0 1.0 1 1.0 0.85 0.85

O'l

6 MN 26.69 - 3.8 0.80 50.0 0.90 8.0 1.0 135.0 1.0 1 1.0 0.84 0.81j

7 MN 6.37 - 0.9 0.70 15.0 0.70 - - 17.5 0.4 1 1 . f) 0.40 0.70

8 MN 0.00 - 7.5 0.30 3.0 0.30 - - 105.5 1.0 1 1.0 0.30 0.30

9 t~N 15.00 - 2.7 1.00 61.0 0.50 - - 50.5 1.0 2 0.5 0.50 0.87

10 MN 0.00 - 1.1 0.85 15.0 0.70 - - 110.0 1.0 1 1 .0 0.81 0.81

a . in text using VI and V3)' V4' V I 2' or V13 HSI Lowest of cover component (as defined .

bHS 1' Lowest of cover component (as defined in text using VI and V 3) or V4.

CFry stocked.

dvalue estimated based on pH of similar lakes.
but this has not been tested. A major weakness of the models is that, while

model variables may be necessary to determine the suitability of habitat for wall~ye, they may not be sufficient. Therefore, high HSI's may be associated

with low or zero standing crops, as well as high standing crops. It should be

remembered that lakes unsuitable for walleye reproduction may support a walleye

fishery through supplemental stocking with fry.

Model outputs should be interpreted 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 walleye. The output of the model s provided should be most

useful in comparing different habitats. If two study areas have different

HSI's, the one with the higher HSI is expected to have the potential to support

a larger walleye population. The models also provide the basic framework for

incorporating new model hypotheses or other site-specific factors that affect

habitat suitability for walleye. Users should recognize that carrying capacity

is a concept not a measurable response for which one can build a falsifiable

predictive model. Users conducting impact assessments r equt r l no major model

improvements and testing should concentrate on building a falsifiable model.

The model should use a clearly documented chain of logic to predict a measurable response (e.g., growth) that is acceptable for judging a selected impact.

ADDITIONAL HABITAT MODELS

Mode 1 1

Where water quality is not limiting, optimum riverine habitat for walleye

is characterized by the following conditions: moderate-to-large river size;

cool temperatures (average summer temperature from 20 to 24° C; winter temperatures < 10° C); mesotrophic conditions; high abundance of rocky shoal and

shoreline areas for spawning; and high abundance of small forage fishes:

HSI = number of above criteria present

5

Model 2

Where water quality is not 1imit i ng, optimum 1acustri ne habi tat for

walleye is characterized by the following conditions: moderate-to-large lake

size (> 100 ha); cool temperatures (as in Modell above); mesotrophic conditions; abundance of rocky shoal and shoreline areas for spawning; and high

abundance of small forage fishes:

HSI = number of above criteria present

5

27
Model 3

Aggus and Morais (1979) and Aggus and Bivin (1982) developed regression

equations relating walleye standing crop or harvest in reservoirs to easily

measured environmental variables. These authors discuss procedures for using

the equations, as well as limitations of the models.

Model 4

Prentice and Clark (1978) presented a walleye population dynamics model

(WALLEYE) for predicting walleye stocking success based on reservoir habitat

conditions and predator abundance. The model was developed from data on 17

Texas reservoirs. Model simulations showed good agreement with actual walleye

population abundance data. WALLEYE can provide information on potential

success of walleye introductions and evaluate the need for, and success of,

habitat improvements.

INSTREAM FLOW INCREMENTAL METHODOLOGY (IFIM)

The U.S. Fish and Wildlife Service's 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 the IFIM that can be used by

investigators interested in determining 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. Determination of monthly flows that minimize habitat

reductions for species and life stages of interest;

2. Habitat Time Series. Determination 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. Calculation of the habitat requirements of each life stage of a fish species at a giv8n 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 (spawning, egg incubation, fry, juvenile, and

adult) of a given fish species. The specific curves required for a PHABSIM

analysis represent the hydraulic-related parameters for which a species or

life stage demonstrates a strong preference (i .e., a pelagic species that only

shows preferences for velocity and temperature will have very broad curves for

28
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 PHAB5IM analysis. 51 curves used with the IFIM that are generated

from empirical microhabitat data are quite similar in appearance to the more

genera 1i zed 1i terature-based 51 curves developed in many H5I mode 1s (Armour

et al. 1983). These two types of 51 curves are interchangeable, in some

cases, after conversion to the same units of measurement (English, metric, or

codes).

51 curve validity is dependent on the quality and quantity of information

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 5I 's into a measure of habitat suitability. If the necessary

curves are unavailable or if available curves are inadequate (i.e., built on

different assumptions), 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. 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 qual ity 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 determines

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 is a generalized description

or summary of habitat preferences based data found in the literature. 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 usually

found at water depths of 0.3 to 1.0 m). Unpublished data and expert opinion

also can 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). Vi rtua lly a 11 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)J. These

29
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(EI F).

Utilization curves are generally more precise for IFIM applications than

literature-based curves because they are based on specific measurements of

habi tat cha racteri sti cs where the fi sh actually occur. However, ut i 1i zat ion

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

and complexity from the streams where the data were obtained.

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

corrected for envi ronmenta 1 bi as. For examp 1e, if 50% of the fi sh 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(EIF)

peE)

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 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 woul d con si st of di fferent depthvelocity preference curves as a function or condition 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 sign i fi cant

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 transferability obtainable when applying these curves

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

transferable to any stream in which the environmental conditions are within

the range of conditions found in the streams for which the curves were

developed.

Availability of Graphs for Use in IFIM

Table 3 lists the SI curves available for an IFIM analysis of walleye

habitat. All curves should be reviewed before use to determine applicability.

Category two 51 curves for adult velocity and substrate (Fig. 3), juvenile

velocity, depth, and substrate (Fig. 4), and fry velocity, depth, and substrate

(Fig. 5) were generated as a result of frequency analyses of raw data collected

30
Table 3. Availability of curves for an IFIM analysis of walleye habitat.

Velocity Depth SUbstratea Temperatureb Coverb

Spawning Use S1 curve, Use S1 curve, Use S1 curve, Use S1 curve No curve

Fig. 6. Fig. 6. Fig. 6. for V10. available.

Egg incubation Use S1 curve, Use S1 curve, Use S1 curve, Use S1 curve No curve

Fig. 6. Fig. 6. Fig. 6. for V10. available.

Fry Use S1 curve, Use S1 curve, Use S1 curve, Use S1 = 1. 0 Use S1 curve

Fig. 5. Fig. 5. Fig. 5. for 12-290 C for V3.

(see text,

page 9).c

Juvenile Use S1 curve, Use S1 curve,

Fig. 4. Fig. 4.

w Adult Use SI curve, Use S1 curve, ....... Fig. 3. Fig. 3.

Use S1 curve,

Fig. 4.

Use S1 curve,

Fig. 3.

Use S1 curve,

Fig. 4.

Use S1 curve,

Fig. 3.

Use S1 curve

for V3.

Use S1 curve

for V3.

aThe following categories can be used for 1F1M 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 (particle 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)

bWhen use of S1 curves is prescribed, refer to the appropriate curve in the HS1 model section.

cUse S1 = 1.0 if the habitat variable is optimal; if the habitat variable is less than optimal, the user

must determine, by judgement, the most appropriate S1.
a

50002 ADULTS

a

78/07/26.

\

-,I--

-- o

co

o

>- '" I- 0

-J

III

:3 ... VI 0

...

o

a

o

a

o 2

vELOCITY 1fT/SEC)

co

a

...

o

a

o

a

/

I

2

7

DEPTH IfTJ

! \

\

\

\

\

II \ I

I

1

p

co

a

>-'"

~a

-J

III

3'"

VIa

...

a

a

a

o 2 4

SUBSTRRTE 6 I

co

a

>-'"

1-0

....

III

S ... VIa

...

o

a

a

o 20 40 60

TEMPERRTURE Ir: 10 100

Figure 3. 51 curves for adult walleye habitat (Kallemeyn and Novotny

unpubl. data; Coutant 1977).

32
o

50001 JUVENILES

o

78/07/19.

\

\

-" o

I \

I \ '"ci

>-~

1-0

-'

aI

;:!

3" m";

N

.,;

o

.,;

o

o 2 ]

VELOCITY (fT/SEC)

'".,;

>-~

1- 0

:::!

aI

;:!

3·

m";

N

ci

o

ci

o

4 6

DEPTH trr, 8 10

( \

I \

\

\

\

/

I \

I

I

/

/ --

e'"

>-

1-0

-'

aI

;:!

3~m 0

...

.,;

o

.,;

o 2 ]

SUBSTRATE

5 6

CD

.,;

>-<D

t::: ci

-'

aI

<Of

I3· me

...

e

o

ci

o 20 4g 60

TEMPERATURE IrJ

80 100

Figure 4. 51 curves for juvenile walleye habitat (Kallemeyn and Novotny

unpubl. data; Coutant 1977).

33
\ -----------

7 \

\

l\

\

\

\

/ \

I

._-

I

o

'"ci

N

ci

o

c:i

o

'"c:i

>-'"

t: ci

-'

iii

;=

S·

lJ)0

N

ci

o

c:i

o

o

50000

0.5 I 1.5

VELOCITY (fT/SECI

3

SUBSTRATE

FRY

o

.,

ci

>--'" ... 0

-'

al

<f

l::.

::J"

lJ)0

N

ci

o

ci

6

o 2

78/07/19.

1

DEPTH 1fT) 8

Figure 5. Category two 51 curves for walleye fry habitat

(Kallemeyn and Novotny unpubl. data).

34
by Kallemeyn and Novotny (unpubl. data). Kallemeyn and Novotny sampled the

Missouri River at each of four stations for 4 days every 4 weeks from 29 March

to 4 November 1976. Three stations were on unchannelized sections of river

located on the South Dakota/Nebraska border, one be low the Fort Renda11 Dam

and two below the 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 20 fry, 48 juveniles, and 41 adult

walleye were collected and the data used in 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. During the study, channel widths ranged from 300 to 1,500 m

(x = 640 to 760 m), depths ranged from 0.0 to 8.0 m (x < 2.0 m), da ily mean

discharges ranged from 872 to 1,104 m3/sec' (x 1,105 m3/sec), surface velocities ranged from 0.0 to 2.1 m/sec, 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 urnho sz' cm. The

substrate consisted primarily of sand, but silt was dominant in backwater and

marsh areas.

The category two SI curve for spawning velocity (Fig. 6) was generated

from a frequency analysis of raw data (Graham unpubl. data) collected from

below the intake diversion (river mile 71.1) on the Yellowstone River in

Montana from 18 Apri 1 to 6 May 1977. A tota 1 of 230 eggs were co 11 ected at

night from four transects located on a 3/4 mile gravel bar. Collections were

made using a 20-inch square net for kick sampling. During the study, flows

ranged from 5,900 to 10,600 CFS, velocities sampled ranged from 0.7 to 3.9 fps,

depths sampled ranged from 1 to 3 ft, substrate observed was predominantly

gravel and cobble with some sand, and temperatures ranged from 52 to 53° F.

The category two SI curve for spawning depth (Fig. 6) was derived from

frequency analyses of the raw data collected by Graham (unpubl. data) and the

data collected by Kallemeyn and Novotny (unpubl. data). The SI curve for

spawning substrate (Fig. 6) is a category one curve and was generated as a

result of information obtained from Graham's unpublished data and articles

published by Kallemeyn and Novotny (1977), and Newburg (1975). The category

one curve for adult temperature preferences (Fig. 2) was derived from information in a publication by Coutant (1977); the assumption was made that juvenile

walleye prefer the same temperatures as adults.

The SI curve for adult walleye depth utilization (Fig. 2) was generated

from a frequency analysis of the data collected by Kallemeyn and Novotny

(unpubl. data) and data collected by Russell (unpubl. data). Russell used

scuba diving to observe walleye adults in 36 pools within 39 mi of the Current

River, between Van Buren and Doniphan in Carter and Ripley counties of

Missouri, during 6 days in 1970 and 1971. Approximately 613 walleye were

observed, wei ghi ng from 1 to 10 1bs. Pool 1engths ranged from 75 to 450 ft,

35
50003 SPAWNING 78/07/13.

o o

/

I \

V \

J

/

i.>v

o

/ \

\

,

I 1\

I 1\

/ 6 • DEPTH IfTl 2

'"o

Cl

o

o

o

2

VELOCITY 1fT/SEC) o

o

o

'"o

Cl

o

>-~

1- 0

..J

III

4

t.

~.

1Jl0

o

( \

( \

II

/

/

Cl

o

>-'" 1-0

..J

III

5· lJlo

'"o

o

o

o 2 • sueSTRATE 6 8

Figure 6. SI curves for walleye spawning habitat (Graham unpubl.

data; Kallemeyn and Novotny unpubl. data; Kallemeyn and Novotny

1977; Newburg 1975).

36
and maximum pool depths ranged from 8 to 18 ft. Walleye congregated in pools

during the day and moved into the shallows to feed at night in these sample

areas. Therefore, users of the SI curve for adult depth utilization should be

aware that the curve represents daytime resting habitat.

REFERENCES

Aggus, L. R., and D. 1. Morais. 1979. Habitat suitability index equations

for reservoi rs based on standi ng crop of fi sh. Nat 1. Reservoi r Res.

Prog. Rep. to U.S. Fish Wildl. Servo 120 pp.

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.

Ali, M. A., R. A. Ryder, and M. Anctil. 1977. Photoreceptors and visual pigments as related to behavioral responses and preferred habitats of perches

(Perea spp.) and pikeperches (Stizostedion spp.). J. Fish. Res. Board

C~34(10):1475-1480.

Anthony, D. D., and C. R. Jorgensen. 1977. Factors in the declining contributions of walleye (Stizostedion vitreum vitreum) to the fishery of Lake

Nipissing, Ontario 1960-76. J. Fish. Res. Board Can. 34(10):1703-1709.

Armour, C. L., R. J. Fisher, and J. W. Terrell. 1983. Comparison and

recommendations for use of Habitat Evaluation Procedures (HEP) and the

Instream Flow 1ncremental Methodology (IFIM) for aquatic analyses. Draft

rep. U.S. Fish Wildl. Serv., Western Energy and Land Use Team, Fort

Collins, CO. 42 pp.

Balon, E. K., W. T. Momot, and H. A. Regier. 1977. Reproductive guilds of

percids: results of the paleogeographical history and ecological succession. J. Fish. Res. Board Can. 34(10):1910-1921.

Benson, N. G.

reservoirs.

1968. Revi ew of fi shery studi es on Mi ssouri

U.S. Fish Wildl. Servo Res. Rep. 71. 61 pp.

main stem

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.

Bu"lkley, R. V., V. L. Spykermann, and L. E. Inmon. 1976. Food of the pelagic

young of walleyes and five cohabiting fish species in Clear Lake, Iowa.

Trans. Am. Fish. Soc. 105(1):77-83.

37
Busch, W. D. N., R. L. Scholl, and W. L. Hartman. 1975. Environmental factors

affecting the strength of walleye (Stizostedion vitreum vitreum) yearclasses in western Lake Erie 1960-70. J. Fish. Res. Board Can.

32(10):1733-1743.

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.

Carlander, K. D., and P. M. Payne. 1977. Year-class abundance, population,

and production of walleye (Stizostedion vitreum vitreum) in Clear Lake,

Iowa, 1948-74, with varied fry stocking rates. J. Fish. Res. Board Can.

34(10):1792-1799.

Chevalier, J. R. 1973. Cannibalism as a factor in the first year survival of

walleye in Oneida Lake. Trans. Am. Fish. Soc. 102(4):739-744.

______ . 1977. Changes in walleye (Stizostedion vitreum vitreum)

population in Rainy Lake and factors in abundance 1924-75. J. Fish. Res.

Board Can. 34(10):1696-1702.

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

and standing crops of yellow perch in southern reservoirs. Pages 89-99

in R. L. Kendall (ed.). Selected coolwater fishes of North America. Am.

Fish. Soc. Spec. Publ. 11. 437 pp.

Colby, P. J., and L. L. Smith, Jr. 1967. Survival of walleye eggs and fry on

paper fiber sludge deposits in Rainy River, Minnesota. Trans. Am. Fish.

Soc. 96(3):278-296.

Colby, P. J., R. E. McNicol, and R. A. Ryder. 1979. Synopsis of biological

data on the walleye Stizostedion v. vitreum (Mitchill 1818). Contribution 77-13, Ontario Ministry Nat. Resources, Fish. Res. Sect. Food and

Agriculture Organization of the United Nations. 123 pp.

Coutant, C. C. 1977. Compilation of temperature preference data. J. Fish.

Res. Board Can. 34(5):739-746.

Cowardin, L. M., V. Carter, F. C. Golet, and E. T. LaRoe. 1979. Classification of wetlands and deepwater habitats of the United States. U.S. Fish

Wildl. Servo FWS/OBS-79/31. 103 pp.

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

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

32:2295-2332.

Dendy, J. S. 1948. Predicting depth distribution of fish in three TVA

storage-type reservoirs. Trans. Am. Fish. Soc. 75(1945):65-71.

38
Elsey, C. A., and R. T. Thomson. 1977. Exploitation of walleye (Stizostedion

vitreum vitreum) in Lac Des Mille Lacs, Northern Ontario, by commercial

and sport fisheries 1958-1975. J. Fish. Res. Board Can. 34(10):1769-1773.

Eschmeyer, P. H. 1950. The life history of the walleye, (Stizostedion vitreum

vitreum), Mitchell, in Michigan. Mich. Dept. Conserv., Inst. Fish. Res.

Bull. 3. 99 pp.

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

distribution in temperate lakes and streams. J. Fish. Res. Board Can.

15(4):607-624.

Fitz, R., B., and J. A. Holbrook,II. 1978. Sauger and walleye in Norris

Reservoir, Tennessee. Pages 11-82 in R. L. Kendall (ed.) Selected coolwater fishes of North America. Am. Flsh. Soc. Spec. Publ. 11.

Forney, J. L. 1966. Factors affecting .ft r st-vear growth of walleyes in

Oneida Lake, New York. New York Fish and Game J. 13(2):146-147.

1974. Interactions between yellow perch abundance, walleye

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

Trans. Am. Fish. Soc. 103(1):15-24.

1977. Evidence of inter- and intraspecific competition as

factors regulating walleye (Stizostedion vitreum vitreum) biomass in

Oneida Lake, New York. J. Fish. Res. Board Can. 34(10):1812-1820.

Graham, P. Unpublished field data collected below the intake diversion (river

mile 71.1) on the Yellowstone River in Montana, from 18 April to 6 May

1977. Montana Dept. Fish Game, Miles City, MT.

Groen, C. L., and T. A. Schroeder. 1978. Effects of water level management

on walleye and other coolwater fishes in Kansas reservoirs. Pages 278-283

in R. L. Kendall (ed.). Selected coolwater fishes of North America. Am.

Flsh. Soc. Spec. Publ. 11.

Hackney, P. A., and J. A. Holbrook, II. 1978. Sauger, walleye, and perch in

the southeastern United States. Pages 82-83 in R. L. Kendall (ed.).

Selected coolwater fishes of North America. A~ Fish. Soc. Spec. Publ.

11.

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

34(10):1524-1550.

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. Stuiber. 1976. Effects of temperature

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

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

39
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 in G. E. Hall (ed.). Reservoir fisheries and

limnology. Am. FiSh. So~Spec. Publ. 8.

Johnson, B. 1983. Personal communication. Univ. Wisconsin, Cent. Limnology,

Madison.

Johnson, F. H. 1961. Walleye egg survival during incubation on several types

of bottom in Lake Winnibigoshish, Minnesota, and connecting waters.

Trans. Am. Fish. Soc. 90(3):312-322.

Johnson, F. H., and J. G. Hale. 1977. Interrelations between walleye

(Stizostedion vitreum vitreum) and smallmouth bass (Micropterus dolomieui)

in four northeastern Minnesota Lakes, 1948-69. J. Fish. Res. Board Can.

34(10):1626-1632.

Johnson, M. G., J. H. Leach, C. K. Minns, and C. H. Olver. 1977. Limnological

characteristics of Ontario Lakes in relation to associations of walleye

(Stizostedion vitreum vitreum), northern pike (Esox lucius), lake trout

(Salvelinus namaycush), and smallmouth bass (Micropterus dolomieui). J.

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

Jones, D. R., J. W. Kiceniuk, and O. S. Bamford. 1974. Evaluation of the

swimming performance of several fish species from the MacKenzie River.

J. Fish. Res. Board Can. 31(10):1641-1647.

Kallemeyn, L. W., and J. F. Novotny. 1977. Fish and fish food organisms in

various habitats of the Missouri River in South Dakota, Nebraska, and

Iowa. U.S. Fish Wildl. Servo FWS/OBS-77/25. 100 pp.

Kallemeyn, L. W., and J. F. Novotny. Unpublished field data collected from

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

from 29 March to 4 November 1976. N. Centra 1 Reservoi r Invest. Yankton,

SO.

Kelso, J. R. M. 1972. Conversion, maintenance, and assimilation for walleye

(Stizostedion vitreum vitreum), as affected by size, diet, and temperature. J. Fish. Res. Board Can. 29(8):1181-1192.

Kelso, J. R. M., and F. J. Ward. 1977. Unexploited percid populations of

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

Can. 34(10):1655-1669.

Kempinger, J. J., and R. F. Carline. 1977. Dynamics

(Stizostedion vitreum vitreum) population in Escanaba

1955-72. J. Fish. Res. Board Can. 34(10):1800-1811.

of the walleye

Lake, Wisconsin

Kendall, R. L. (ed.). 1978. Selected coolwater fishes of North America. Am.

Fish. Soc. Spec. Publ. 11. 437 pp.

40
Kitchell, J. F., M. G. Johnson, C. K. Minns, K. H. Loftus, L. Grieg, and C. H.

Olver. 1977. Percid habitat: the river analogy. J. Fish. Res. Board

Can. 34(10):1936-1940.

Koenst, W. M., and L. L. Smith, Jr. 1976. Thermal requirements of the early

life history of walleye (Stizostedion vitreum vitreum) and sauger

(Stizostedion canadense). J. Fish. Res. Board Can. 33(5):1130-1136.

Leach, J. H., M. G. Johnson, J. R. M. Kelso, J. Hartmann, W. Numann, and B.

Entz. 1977. Responses of percid fishes and their habitats to eutrophication. J. Fish. Res. Board Can. 34(10):1964-1971.

Lyons, J. 1983. Personal communication. Univ. Wisconsin. Cent. Limnology,

Madison.

McKee, J. E., and H. W. Wolf. 1963. Water quality criteria. State Water

Quality Control Board. Sacramento, CA. Publ. 3A. 548 pp.

Nickum, J. G. 1983. Personal communication. Leader, Iowa Cooperative Fishery

Research Unit, Ames.

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

Physical Habitat Simulation System. Instream Flow Information Paper II.

U.S. Fish Wildl. Servo FWS/OBS-81/43. 273 pp.

Miller, L. W. 1967. The introduction, growth, diet, and depth distribution

of walleye, Stizostedion vitreum (Mitchill), in El Capitan Reservoir, San

Diego County. Calif. Res. Agency, Dept. Fish Game, Inland Fish. Br.,

Admin. Rep. 67-10. 13 pp.

Momot, W. T. 1983. Personal communication. Dept. Biol., Lakehead Univ.,

Thunder Bay, Ontario.

Momot, W. T., J. Erickson, and F. Stevenson. 1977.

(Stizostedion vitreum vitreum) fishery in a

Fish. Res. Board Can. 34(10):1725-1733.

Maintenance of a walleye,

eutrophic reservoir. J.

Moyle, J. B., and W. D. Clothier. 1959. Effects of management and winter

oxygen levels on the fish population of a prairie lake. Trans. Am. Fish.

Soc. 88(3):178-185.

Nelson, W. R., and C. H. Wa'iburg. 1977. Population dynamics of yellow perch

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

v~m vitreum) in four main stem Missouri River reservoirs. J. Fish.

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

41
Newburg, H. J. 1975. Evaluation of an improved walleye (Stizostedion vitreum)

spawning shoal with criteria for design and placement. Minn. Dept. Nat.

Res. Invest. Rep. 340. 39 pp.

Ney, J. J. 1978. A synoptic review of yellow perch and walleye biology.

Pages 1-12 in R. L. Kendall (ed.). Selected coolwater fishes of North

America. Am~Fish. Soc. Spec. Publ. 11.

Oseid, D. M., and L. L. Smith, Jr. 1971.

eggs at various dissolved oxygen levels.

Survival and hatching of walleye

Prog. Fish-Cult. 33(2):81-85.

Pfitzer, D. W. 1967. Evaluations of tailwater fishery resources resulting

from high dams. Pages 477-488 in Reservoir fishery resources symposium.

Am. Fish. Soc. Publ., Univ. GeorgTa, Athens.

Prentice, J. A., and R.

Texas - a systems

Selected coolwater

11.

D. Clark, Jr. 1978. Walleye fishery management in

approach. Pages 408-416 in R. L. Kenda11 (ed.).

fi shes of North Ameri ca. A-m-.- Fi sh. Soc. Spec. Pub1.

Priegel, G. R. 1963. Food of walleye and sauger in Lake Winnebago, Wisconsin.

Trans. Am. Fish. Soc. 92(3):312-313.

1970. Reproduction and early life history of the walleye in

the Lake Winnebago region. Wisconsin Conserv. Dept. Tech. Bull. 45.

105 pp.

Regier, H. A., J. C. Applegate, and R. A. Ryder.

management of the wa 11 eye in western La ke Eri e.

Tech. Rep. 15. 101 pp.

1969. The ecology and

Great Lakes Fi sh Comm.

Russell, T. R. Unpublished field data collected from the Current River between

Van Buren and Doniphan, Missouri, in 1970 and 1971. State of Missouri

Project F-1-R-21, Study S-10, Job 2.

Ryder, R. A. 1968. Dynamics and exploitation of mature walleye, Stizostedion

vitreum vitreum, in the Nipigon Bay region of Lake Superior. J. Fish.

~Board Can. 25(7):1347-1376.

1977. Effects of ambient 1ight variations on behavior of

yearling, subadult, and adult walleyes (Stizostedion vitreum vitreum).

J. Fish. Res. Board Can. 34(10):1481-1491.

Ryder, R. A., and S. R. Kerr. 1978. The adult walleye (Stizostedion v.

vitreum) in the percid community - a niche definition based on feeding

behavior and food specificity. Pages 39-51 in R. L. Kendall (ed.).

Selected coolwater fishes of North America. Am:- Fish. Soc. Spec. Publ.

11.

Ryder, R. A., S. R. Kerr, K. H. Loftus, and H. A. Regier. 1974. The morphoedaphic index, a fish yield estimator - review and evaluation. J. Fish.

Res. Board Can. 31:663-688.

42
Scherer, E. 1971. Effects of oxygen depletion and of carbon dioxide buildup

on the photic behaviour of the walleye (Stizostedion vitreum vitreum).

J. Fish. Res. Board Can. 28:1303-1307.

Schupp, D. H. 1978. Walleye abundance, growth, movement, and yield in disparate environments within a Minnesota lake. Pages 58-65 in R. L. Kendall

(ed.). Selected coolwater fishes of North America. Am.-Fish Soc. Spec.

Pub1. 11.

Scott, W. B., and E. J. Crossman.

Res. Board of Canada, Ottawa.

1973. Freshwater Fi shes of Canada.

Bull. 184. 966 pp.

Fish.

Siefert, R. E., and W. A. Spoor. 1974. Effects of reduced oxygen on embryos

and larvae of the white sucker, coho salmon, brook trout, and walleye.

Pages 487-495 in J. H. S. Blaxter (ed.). The early life history of fish.

Springer-Verla~ New York.

Smith, L. L., Jr., and W. M. Koenst. 1975. Temperature effects on eggs and

fry of percoid fishes. U.S. Environ. Protection Agency. Ecol. Res. Ser.

EPA-660/3-75-017. 91 pp.

Spangler, G. R., N. R. Payne, G. K. Winterton. 1977. Percids in the Canadian

waters of Lake Huron. J. Fish. Res. Board Can. 34(10):1839-1848.

Swenson, W. A. 1977. Food consumption of walleye (Stizostedion vitreum

vitreum) and sauger (S. canadense) in relation to food availability and

physical conditions in Lake of the Woods, Minnesota, Shagawa Lake, and

western Lake Superior. J. Fish. Res. Board Can. 34(10):1643-1654.

Swenson, W. A., and L. L. Smith, Jr. 1976. Influence of food, competition,

predation, and cannibalism in walleye (Stizostedion vitreum vitreum). J.

Fish. Res. Board Can. 30(9):1327-1336.

Wagner, W. C. 1972. Utilization of alewives by inshore piscivorous fishes in

Lake Michigan. Trans. Am. Fish. Soc. 101(1):55-63.

Walburg, C. H. 1971. Loss of young fish in reservoir discharge and year-class

survival, Lewis and Clark Lake, Missouri River. Pages 441-448 in G. E.

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

Publ. 8.

Wrenn, W. B., and T. D. Forsythe. 1978. Effects of temperature on production

and yield of juvenile walleyes in experimental ecosystems. Pages 66-73

in R. L. Kendall (ed.). Selected coolwater fishes of North America. Am.

Fish. Soc. Spec. Publ. 11.

43
50272 ·101

REPORT DOCUMENTATION I 1. REPORT NO.

1

2

•

3. Recipient's Accession No.

PAGE I

FWSjOBS-82jlO.56

4. Title and Subtitle 5. Report Date

Anrt 1 1984 ... Habitat suitability information: Walleye 6. .. 7. Author(s) 8. Performing Organization Rept. No.

Thomas E. McMahon, James W. Terrell, and Patrick C. Nelson

9. Performing Organization Name and Address 10. Project/Task/Work Unit No.

Western Energy and Land Use Team

U.S. Fish and Wildlife Service 11. Conlracl(C) or Grant(G) No.

Drake Creekside Building One (C)

2627 Redwing Road

Fort Collins, CO 80526-2899 (G)

12. Sponsoring Organization Name and Address ~~e ste rn Energy and Land Use Team .'-

13. Type of Report & Period Covered

Division of Biological Services

Research and Development

Fish and Wildlife Service 14.

U.S. Department of the Interior

15. Supplementary Notes Washington, DC 20240

1&. Abstract (Limit: 200 words)

The habitat suitability index (HSI) mode 1s presented in this publication aid

in identifying important habitat variables for the walleye (Stizostedion

vitreum vitreum). Information obtained from the research 1iterature and

expert reviews are synthesized into models which present hypotheses of species -

- habitat relationships.

A brief discussion of using selected suitability Index (SI) curves from HSI

models as a component of the Instream Flow Incremental Methodology (IFIM) is

provided. Additional SI curves, specifically designed for analysis of walleye habitat with IFIM, are also presented.

17. Document Analysis a. Desc ri ptors

Fishes

Habi tabil i ty

Mathematical models

Aquatic biology

b. Identifiers/Open.Ended Terms

Walleye

Stizostedion vitreum vitreum

Habitat suitability

Instream Flow Incremental ~lethodology

c. COSATI Field/Group

18. Availabilily Stalement 19. Security Class (This Report) 21. No. of Pages t

Release unlimited Unclassified 43

I 20. Securily Class (This Page) 22. Price

i Unclassified N/A

(See ANSI-Z39.18) See Instructions on Reverse

U.S GOVERNMENT PRINTING OFFICE: 1984~77g·1349288 REGION NO.8

OPTIONAL FORM 272 (4-77

(Formerly NTI>35)

Department of Commerce
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Habitat suitabi Iity inrmation :

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)( Estern Energv .nd Land Use Team

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Slidell LA

REGION 1

Regionltl Director

U,S. Fish and Wildlife Service

Lloyd FiveHundred BUilding, Suile 1692

500 N E. Multnomah Street

Portland, Oregon 971 n

REGION :2

RegionalDirector

U.S. Fish and Wildlife Service

P,O. Box 1306

Albuquerque, New Mexico 87103

REGION J

RegionalDirector

U.S. Fi h and Wildlife Service

Federal Building. Fort Snelling

Twin rilles, innesota 55111

REGION 4 REGION 5

Regional Director

U.s. Fish and Wildlife Service

One Gateway Center

Newton Comer, \1assachu5Clls 02158

REGION 6

Regional Director

U.S. Fish lindWildlife Service

P.O. Box 25486

Denver Federa Center

Denver,COlorado 80225

REGION 7

Regional Director

U.S. Fish and Wildlire Service

1011 E. Tudor Road

Anchorage, Alaska 99503
DEPARTMENT OF THE INTERIOR

u.s. FISH AND WILDLIFE SERVICE

As the Nation's principal conservation agency, the Department of the Interior has responsibility for most of our .nationally owned public lands and natural resources. This includes

fostering the wisest use of our land and water resources, protecting our fIsh and wildlife,

preserving th&environmental and cultural values of our national parks and historical places,

and providing for the enjoyment of life throulh outdoor recreation. The Department as·

sesses our energy and mineral resources and works to assure that their development is in

the best interests of all our people. The Department also has a major responsibility for

American Indian reservation communities and for people who live in island territories under

U.S. administration.