HABITAT SU TABILITY INDEX MODELS

AND INSTREAM FLOW SUITABILITY

CURVES: WHITE SUCKER

SK

361

.U54

no. 82-

10.64
MODEL EVALUATION FORM

Habitat models are designed for a wide variety of planning applications where habitat information is an important consideration in the

decision process. However, it is impossible to develop a model that

performs equally well in all situations. Assistance from users and

researchers is an important part of the model improvement process. Each

model is published individually to facilitate updating and reprinting as

new information becomes available. User feedback on model performance

will assist in improving habitat models for future applications. Please

complete this form following application or review of the model. Feel

free to include additional information that may be of use to either a

model developer or model user. We also would appreciate information on

model testing, modification, and application, as well as copies of modified

models or test results. Please return this form to:

Habitat Evaluation Procedures Group

or

Instream Flow Group

U.S. Fish and Wildlife Service

2627 Redwing Road, Creekside One

Fort Collins, CO 80526-2899

Thank you for your assistance.

Species _

Habitat or Cover Type(s)

Geographic

Location

Type of Application: Impact Analysis Management Action Analysis ___ Baseline Other -------------------------

Variables Measured or Evaluated -------------------

Was the species information useful and accurate? Yes No

If not, what corrections or improvements are needed?------------
Were the variables and curves clearly defined and useful? Yes No

If not, how were or could they be improved?

Were the techniques suggested for collection of field data:

Appropriate? Yes No

Clearly defined? Yes No

Easily applied? Yes No

If not, what other data collection techniques are needed?

Were the model equations logical? Yes No

Appropriate? Yes No

How were or could they be improved?

Other suggestions for modification or improvement (attach curves,

equations, graphs, or other appropriate information)

Additional references or information that should be included in the model:

Model Evaluater or Reviewer Date ------------ -------

Agency _

Address _

Telephone Number Comm:----------- FTS
FWS/OBS-82/10.64

September 1984

HABITAT SUITABILITY INDEX MODELS AND INSTREAM FLOW

SUITABILITY CURVES: WHITE SUCKER

by

Kathleen A. Twomey

Wyoming Cooperative Fishery Research Unit

University of Wyoming

Laramie, WY 82071

and

Kathryn L. Williamson

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

2627 Redwing Road

Fort Collins, CO 80526-2899

Project Officer

Carl Armour

Western Energy and Land Use Team

U.S. Fish and Wildlife Service

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
This report should be cited as:

Twomey, K. A., K. L. Williamson, and P. C. Nelson. 1984. Habitat suitability

index models and instream flow suitability curves: White sucker. U.S.

Fish Wildl. Servo FWS/OBS-82/10.64. 56 pp.
PREFACE

The habitat use information and Habitat Suitability Index (HSI) models

presented in this publication aid in impact assessment and habitat management

activities. Literature concerning a species' habitat requirements and

preferences is reviewed and then synthesized into subjective HSI models, which

are scaled to produce an index between 0 (unsuitable habitat) and 1 (optimal

habitat). Assumptions used to transform habitat use information into these

mathematical models are noted, and guidelines for model application are

described. Any models found in the literature which may also be used to

calculate an HSI are cited, and simplified HSI models, based on the most

important habitat characteristics for the species, are presented. Also

included is a brief discussion of Suitability Index (SI) curves as used in the

Instream Flow Incremental Methodology (IFIM), and a discussion of SI curves

available for the IFIM analysis of white sucker habitat.

Use of habitat information presented in this publication for impact

assessment requires the setting of clear study objectives and may require

modification of the models to meet those objectives. Methods for modifying

HSI model s and recommended measurement techniques for model variables are

presented in Terrell et al. (1982).1 A discussion of HSI model building

techniques, including the component approach is presented in U.S. Fish and

Wildlife Service (1981).2

The HSI models presented herein are complex hypotheses of species-habitat

relationships, not statements of proven cause and effect relationships.

Resul ts of mode ,..--performance tests, when avail ab1e, are referenced; however,

models that have demonstrated reliability in specific situations may prove

unreliable 'in others. For this reason, the FWS encourages model users to

convey comments and suggestions that may help us increase the utility and

effectiveness of this habitat-based approach to fish and wildlife planning.

Please send comments to:

Habitat Evaluation Procedures Group

Western Energy and Land Use Team

U.S. Fish and Wildlife Service

2627 Redwing Road

Ft. Collins, CO 80526-2899

1Terrell, J. W., T. E. McMahon, P. D. Inskip, R. F. Raleigh, and K. L.

Williamson. 1982. Habitat suitability index models: Appendix A. Guidelines

for riverine and lacustrine applications of fish HSI models with the Habitat

Evaluation Procedures. U.S. Fish Wildl. Servo FWS/OBS-82/10.A. 54 pp.

2U.S. Fish and Wildlife Service.

habitat suitability index models.

Ecol. Servo n.p.

1981. Standards for the deve 1opment of

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

iii
iv
CONTENTS

Page

PREFACE iii

TABLES vi

FIGURES vi i

AC KNOWLEDGMENTS vii i

HABITAT USE INFORMATION 1

Genera 1 1

Age, Growth, and Food 1

Reproduct ion 1

Speci fi c Habitat Requi rements 3

HABITAT SUITABILITY INDEX (HSI) MODELS 6

Model Applicability 6

Model Description - Riverine...................................... 7

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

Suitability Index (SI) Graphs for Model Variables ..... ..... ... .... 10

Riverine Model.................................................... 18

Lacustri ne Model.................................................. 21

ADDITIONAL HABITAT MODELS........... 23

Mode 1 1 23

Model 2 23

Model 3 23

Model 4 24

Model 5 24

SUITABILITY INDEX (SI) GRAPHS FOR MODEL 5 26

Ri veri ne Model.................................................... 35

INSTREAM FLOW INCREMENTAL METHODOLOGY (IFIM) .. 38

Suitability Index Graphs as Used in IFIM . 38

Availability of Graphs for Use in IFIM 40

REFERENCES 52

v
Number

1

2

3

4

5

6

7

TABLES

Sources of information and assumptions used in construction

of the sui tabi 1i ty index graphs .

Data sets from application of the riverine HS1 model for

white suckers at LaGarde Creek, Colorado .

Data sets from application of the riverine HS1 model for

white suckers at St. Vrain Creek and Big Thompson River,

Colorado (Propst 1982a) .

Sample data sets using lacustrine HS1 model

Sources of information and assumptions used in construction

of the sui tabi 1i ty index graphs .

Sample data sets using HS1 ModelS .

Availability of 51 curves for the 1F1M analyses of white

sucker habi ta t .

vi

15

19

20

22

33

36

41
Number

1

2

3

4

5

6

7

8

FIGURES

Tree diagram illustrating relationship of habitat variables

and life requisites in the riverine model for the white

sucker .

Tree diagram illustrating relationship of habitat variables

and life requisites in the lacustrine model for the white

sucker .

Tree diagram illustrating relationship of habitat variables

and life requisites in riverine HS1 Model 5 for the white

sucker .

S1 curves for white sucker spawning velocity, depth,

substrate, cover, and temperature '" .

51 curves for white sucker egg incubation velocity, depth,

substrate, cover, and temperature .

S1 curves for white sucker fry velocity, depth, substrate,

cover, and temperature .

S1 curves for white sucker juvenile velocity, depth,

substrate, cover, and temperature .

51 curves for white sucker adult velocity, depth, substrate,

cover, and temperature .

vii

8

9

25

42

44

46

48

50
ACKNOWLEDGMENTS

We would like to thank Doug Krieger, Colorado Division of Wildlife, and

D. W~ Coble, Wisconsin Cooperative Fishery Research Unit, for their comprehensive review and helpful comments. We would also like to thank Robert Muth,

Colorado State University, Ray Smith, Soil Conservation Service, David Propst,

New Mexico Game and Fish, and Joan Trial, Maine Cooperative Fishery Research

Unit, for their review and comments on earlier versions of this model package.

C. J. Short provided editorial assistance. C. J. Gu1zow and D. E. Ibarra

provided word processing. Cover art is from Freshwater Fishes of Canada 1973,

Bulletin 184, Fisheries Research of Canada by W. B. Scott and E. J. Crossman.

viii
WHITE SUCKER (Catostomus commersoni)

HABITAT USE INFORMATION

General

The white sucker (Catostomus commersoni) is a highly adaptable, freshwater

fish species found in lacustrine and riverine environments from the Mackenzie

River, Hudson Bay drainage, and the Labrador Peninsula; south along the

Atlantic Coast to western Georgia; along the northern extremes of the Gulf

States to northern Oklahoma; north through the eastern sections of Colorado,

Wyomi ng, and Montana; and through A"I berta, north-central Bri t ish Col umbi a and

southeastern Yukon territory (Carlander 1969; Scott and Crossman 1973).

Age, Growth, and Food

Male white suckers typically reach maturity between ages II (Hayes 1956)

and VI (Campbell 1935; Geen et al. 1966), depending on geographic location.

Females usually mature 1 to 2 years later than males (Spoor 1938). Like most

fishes, populations in northern latitudes or at higher altitudes generally

have slower growth, mature later, and live longer than more southern or lower

elevation populations. Size at sexual maturity ranges from 15 to 23 cm in

males (Hayes 1956; Geen et al. 1966) and up to 27 cm in females (Hayes 1956).

Ages of X to XII have been reported (Dence 1948; Olson 1963) and a maximum age

of XVII was recorded by Beamish (1973).

Sac-fry feed on surface associated zooplankton (e.g., copepods,

cladocerans, and rotifers) (Olson 1963; Siefert 1972; Lalancette 1977) or on

suspended phytoplankton (Nurnberger 1928; Siefert 1972). After complete yolk

absorption (20 to 29 days, at 14 to 18 mm), the mouth moves from a terminal to

a vent~al position, and an associated shift to bottom feeding occurs (Stewart

1926; Siefert 1972). The diet after yolk absorption consists of benthic

organisms, such as chironomid larvae, pupae, and fingernail clams (Olson 1963;

Pflieger 1975; Krieger 1980). Juveniles feed primarily on benthic organisms.

As size increases with maturation, the size range of food items ingested

increases to include amphipods, gastropods, and large immature aquatic insects

(Stewart 1926; Dence 1948). White suckers are active and feed throughout the

year. Maximum growth occurs from June to August but growth is inhibited

during gonadal development and spawning (Lalancette 1977).

Reproduction

White suckers start their upstream spawning migration in spring to early

summer, when the daily maximum water temperature reaches 10° C (Olson 1963;

Geen et al. 1966; Fuiman 1978; Curry 1979; Walton 1980). The migration

continues until the water temperature reaches about 18° C (Raney 1943; Hayes

1956; Olson 1963). Initiation of spawning migrations appears to be either

1
temperature-dependent (Raney and Webster 1942; Dence 1948) and/or stream

di scharge-dependent (Walton 1980). Sudden temperature drops may di mi nish or

stop migration (Raney and Webster 1942; Dence 1948). White suckers usually

migrate from lentic systems or stream pools to spawning riffles; therefore, it

is assumed that distance to spawning habitat may be a factor in determining

optimum habitat. Raney and Webster (1942) observed white suckers migrating

from only a few hundred meters to as much as 6.4 km upstream where obstructions

blocked further passage. Dence (1948) reported that a rock 1edge 2.5 feet

(76.2 em), with a moderately fast current, stopped the migration of most dwarf

suckers, Catostomus commersoni utawana (closely related to the white sucker).

Suckers depend to some degree on 1oca 1 1andmarks and primari lyon 01fact ion

during the spawning run (Dence 1948; Werner 1979); therefore, it is assumed

that impacts which could change the spawning stream integrity may affect

spawning run success.

White sucker spawning habitat is generally considered to be areas in

inlets, outlets, small creeks, and rivers with relatively swift shallow waters

running over a gravel bottom (Forbes and Richardson 1920; Dence 1948; Nel son

1968; Carlander 1969; Schneberger 1977). Reighard (1913) suggested that the

essential breeding habitat requirement is suitable substrate, not running

water, but Curry (1979) indicated that spawning site selection is influenced

primarily by water velocity and depth of substrate type. Nelson (1968)

reported that spawni ng over gravel was usually at water depths 1ess than

30 em. Fuiman (1978) stated that egg collections in his study typically took

place in shallow (15 to 20 em deep) gravel riffles. Curry (1979) reported

spawning site depths of 20 to 25 em.

A clean bottom of coarse sand (Minckley 1963) or gravel is an essential

quality of the spawning habitat for white suckers (Dence 1948). Curry (1979)

reported that, after white suckers cleaned out a spawning site, the remaining

gravel was larger and more free of silt and sand than when the site was

selected. Curry (1979) reported that white suckers spawned over medium-sized

grave 1 (2 to 16 mm). Nelson (1968) reported that whi te suckers apparently

seldom spawn in deep waters with a sand bottom, although Raney (1943) observed

spawning in a relatively deep, quiet pool with a gravel substrate. Pflieger

(1975) reported spawning in gravelly areas near the lower end of pools, in

quiet water or where the current begins to quicken. Gravel appears to be the

preferred substrate. If access to streams with suitable spawning habitat is

limited, lacustrine populations may spawn on sand or gravel shoals subject to

wave action (Reighard 1913; Hayes 1956; Olson 1963; Krieger 1980).

Nelson (1968) reported that the velocity in rivers where white suckers

congregated for spawning varied from a low of 14 em/sec to a high of 90 em/sec.

White suckers also were observed in streams with mean spring velocities of 60

to 90 em/sec (Minckley 1963; Curry 1979). Although white suckers have been

observed at velocities> 60 em/sec, Symons (1976) reported that white suckers

in an arti fi ci a 1 stream with fast velocity were most often located at modal

velocities of 30 to 49 em/sec. Curry (1979) reported spawning site velocities

for white suckers of 50 to 59 em/sec. Although Dence (1948) never observed

suckers in the act of spawning in deep pools where the current was very slow,

2
he suggested that these habitats might be used if more desirable habitats were

not available. Therefore, it is assumed that white sucker adults select

moderate stream velocities for spawning.

The fertilized eggs adhere to the gravel in riffles or drift downstream

where they adhere to the substrate in areas with water of slow velocity (Geen

et al. 1966). White sucker fry emerge about 9 to 11 days after hatching and

drift downstream at night.

Specific Habitat Requirements

White suckers tolerate a relatively broad range of environmental conditions. Even though white suckers are generalists, optimum habitat conditions

for the species can be described.

Stream populations of white suckers reach maximum abundance in low to

moderate gradient streams (Stewart 1926). Minckley (1963) and Hocutt and

Stauffer (1975) reported white suckers in streams with an average gradient of

6 m/km; Hocutt and Stauffer (1975) collected 70 white suckers at gradients of

2.8 to 7.8 m/km, 28 suckers at gradients of 10 to 13.4 m/km, and only 5 suckers

at a gradient of 28.4 m/km. Curry (1979) observed white suckers spawning in

streams with gradients of 1.2 to 2.3 m/km.

Adult white suckers (> 150 mm TL) primarily inhabit pools (Propst 1982b)

and are common in areas of slow to moderate velocity (approximately 40 cm/sec),

although smaller individuals « 150 mm TL) occur in a greater variety of

habitats than adults (Stewart 1926; Scherer 1965; Pflieger 1975; Propst 1982b).

Stewart (1926) was unable to find white suckers in pools that were

entirely isolated from any inflow; Propst (1982b) supported the idea that

water movement was important because suckers were uncommon or absent at pothole

sites with no flow. Symons (1976) reported that white suckers appeared to

have trouble maintaining equil ibrium in fast or turbulent water and that

suckers were sighted more often in artificial streams with slow runs at modal

velocities of 10 to 19 cm/sec. Propst (1982b) did not find white suckers in

pools with flows> 10 cm/sec and Minckley (1963) found white suckers in pools

with flows that were usually near 15 cm/sec. Propst (1982b) reported that

substrates in pools inhabited by adult white suckers were a mixture of rubble,

gravel, and sand with a silt overburden.

Propst (1982b) reported a high correlation between pool cover and white

sucker populations. Minckley (1963) observed that when aggregations of white

suckers in pools were disturbed they moved quickly into debris or other cover.

Cover, including both streamside cover and within-stream cover, is a very

important, if not essential, component of spawning areas for dwarf suckers, C.

c. utawana (Dence 1948). Thompson and Hunt (1930), Dence (1948), and Propst

{1982b) descri bed whi te sucker habi tats with exposed tree roots, numerous

drifts of brush and logs against fallen trees, bridge supports, riprapped and

undercut banks, and large boulders available as cover. Dence (1948) reported

that the dwarf sucker seeks out streams in shaded woods during breeding season.

Thompson and Hunt (1930) described white sucker habitat as commonly shaded by

trees on the bank or by overhanging grass, weeds, and shrubs.

3
Poo1 depth a1so can provi de cover. Dwarf suckers frequently congregate

in deeper pools when not spawning (Dence 1948). Suckers are generally easily

disturbed and quickly retreat to pools (Stewart 1926). Propst (1982b)

collected white suckers at water depths of 21 to 110 em, but most common

depths were 61 to 90 cm. Thompson and Hunt (1930) observed white suckers in

slow water habitat at depths of 15 to 240 cm. The value of pools as white

sucker habitat is greatly improved when logs, brush, or other types of cover

are present (Dence 1948).

Symons (1976) demonstrated that cover-seeking behavior increased signifi cantly as stream ve1ocity increased. Mi nck1ey (1963) reported that most

white suckers were in deeper pools, with fewer suckers in swifter, shallower

water. When white suckers were present in shallow water with an appreciable

current, they were usually in the shelter of vegetation. When vegetation was

lacking in the stream current, the suckers were in the deepest pools. When

white suckers were found in smaller, shallow pools there was an accumulation

of debris and overhanging riparian vegetation for cover. '

Pools provide habitat with a slower current in which fish can rest.

Suckers recuperate in pools after negotiating a difficult stream obstruction

during migration or after breeding (Stewart 1926; Dence 1948). Optimum white

sucker habitat is assumed to have a pool to riffle/run ratio of 1:1.

White suckers avoided areas in reservoirs where the dissolved oxygen (DO)

was S 2.4 mg/l (Dence 1948), but specific information on adult and juvenile

dissolved oxygen (DO) requirements generally are lacking. Siefert and Spoor

(1974) reported that embryos could not survive DO levels S 1.2 mg/l and that

the growth of fry was reduced at DO levels < 2.5 mg/l. Minckley (1963)

described an abundant white sucker population in a portion of a stream that

had yearly DO values ranging from 4.3 mg/l to an occasional average supersaturation level of 14.79 mg/l.

Whit'e suckers have been collected from areas with a pH as low as 4.3

(Dunson and Martin 1973), but Beamish (1974) reported sharp declines in white

sucker populations in Canadian lakes when the pH was lowered to 4.5 to 5.0 as

a resul t of aci d preci pitation. Laboratory studi es on the effects of pH on

white sucker growth and survival indicated that feeding stops at a pH of 4.5

and death occurs at a pH of 3.0 to 3.8 (Beamish 1972). Maximum successful

reproduction occurs at a pH above 5.8 (Trojnar 1977). The pH range which is

generally considered not harmful to fish is 5.0 to 9.0; the further the pH

varies from this range, the lower the water quality. Laboratory data indicate

that a pH between 9 and 10 may be harmful to some fish species, and that a pH

above 10 usually is lethal to all species (EIFAC 1969).

White suckers can survive in turbid waters, but they are more common in

clearer streams « 50 JTU) and lakes (Pflieger 1975) and prefer relatively

clear spawning streams (Raney and Webster 1942). Young-of-the-year, juveniles,

and adults have been reported in the Missouri and James Rivers (North Dakota)

at relatively consistent turbidities of 50 to 135 JTU's. Smaller numbers of

white suckers occur in the Colorado and Yampa Rivers (Colorado) at more

variable turbidities of 85 to 100 and up to 350 JTU's (R. Muth, pers. comm.).

Pflieger (1971) stated that white suckers are uncommon in large turbid rivers.

4
Adult. Whi te suckers have broad temperature tolerances, and optimum

temperatures vary geographi ca lly. White suckers occur in III i noi s headwater

streams with summer temperatures up to 32° C (Thompson and Hunt 1930). A

preferred temperature range of 19 to 21° C was reported for a Colorado

reservoir (Horak and Tanner 1964). Experimental evidence suggests an optimum

summer water temperature of 24° C (Reynolds and Casterlin 1978). Reutter and

Herdendorf (1976) reported a critical thermal maximum for white suckers of

31.6° C. Brett (1944) reported an upper lethal temperature of 31.2° C for

suckers acclimated at 26° C. Specific minimum temperatures have not been

reported, but the wide distribution of white suckers indicates that they can

survive temperatures as low as 1 to 2° C. For example, Minckley (1963)

reported average January temperatures between 1.1 and 2.2° C in Doe Run,

Kentucky, where white suckers occurred.

Embryo. Embryo development is temperature dependent (Raney and Webster

1942; Geen et al. 1966). Fuiman (1978) collected eggs in streams with water

temperatures ranging from 11 to 16° C. McCormick et al. (1977) reported

maximum hatching success at 15° C. Hatching success diminished significantly

at temperatures < 9° C or > 17° C, and upper and lower lethal 1imits were

24° C and 6° C, respectively.

Larval. White sucker larvae apparently prefer water temperatures of 23

to 25° C, but occur in water temperatures of 13 to 25° C (Marcy 1976). The

greatest growth was obtained experimentally in water that was 27° C, and the

upper lethal limit was 30 to 32° C (McCormick et al. 1977). Krieger (1980)

reported that the highest larval densities in lacustrine habitats were in

shoreline areas with sand and sand/gravel substrate combinations. Few larval

fish occurred in areas with a rock substrate, and no larval fish occurred in

areas with silty sand or boulders. Thompson and Hunt (1930) usually found

young suckers in streams where the substrate was a mixture of sand and gravel.

White sucker fry prefer moderate currents and do not occur in rapids or still

pools, although they may be present in intermediate situations where the

stream enters deep, qui et stretches (Stewart 1926). Young suckers in the

surface-feeding stage appear to congregate in eddies and backwaters in response

to gentle currents.

Juvenile. Upper lethal temperature limits for juvenile white suckers

were 26 to 31° C at acclimation temperatures of 5 to 25° C (Brett 1944;

Carlander 1969). At accl imation temperatures of 20 to 25° C, the reported

lower lethal temperatures were 2 to 6° C (McCormick et al. 1977). Small white

suckers « 150 mm TL) have been co 11 ected from shallow backwaters, ri ffl es

with moderate water velocity (approximately 50 cm/sec), and sand-rubble bottom

runs (Propst 1982b).

5
HABITAT SUITABILITY INDEX (HSI) MODELS

Model Applicability

Geographic area. This model is applicable throughout North America where

white suckers occur. The standard of comparison for each individual variable

Suitability Index (SI) is the optimum value that occurs anywhere within this

geographic range.

Season. The 1acustri ne mode1 provi des a rating for 1ake or reservoi r

habitat based on its ability to support all life stages of white suckers

throughout the year. The riverine model can be used two ways: (1) to provide

a rating for streams and rivers used by resident white sucker populations

throughout the year; or (2) it may be incorporated into the lacustrine model

to provide a rating for tributary streams or rivers during the spawning and

fry migration period when these streams serve as recruitment areas for the

lake population.

Cover types. Riverine and lacustrine.

Minimum habitat area. Minimum habitat area is defined as the minimum

area of contiguous suitable habitat that is required for a population to

maintain itself indefinitely. The minimum habitat area necessary for a white

sucker population has not been established.

Verification level. The acceptance level of the lacustrine and riverine

model is that it produces an index between 0 and 1 which the authors believe

has a positive relationship to carrying capacity for white suckers. Data from

LaGarde Creek, Colorado, was used to evaluate the riverine HSI model (Table 2).

The low HSI I S generated for LaGarde Creek indicated poor habitat, and white

suckers did not occur in the study reach.

The riverine HSI model also was tested with data from eight sites in the

St. Vrain Creek and Big Thompson River, Colorado, that had viable white sucker

populations. Sites with low HSI's were assumed to have a correspondingly

lower relative abundance of white suckers than sites with higher HSI's. A

poor correlation or lack of correlation between relative abundance and HSI's

might indicate that the model is inadequate or that species interactions may

have a significant influence on relative abundance. The correlation coeffi ci ent between the re 1ati ve abundance of whi te suckers and the HSII S was

moderate (r = 0.477) (Propst 1982a). The data sets determined by sampling are

given in Table 3. This moderate correlation between the HSI's and the relative

abundance of white suckers may be the result of two factors. The first factor

is that there may have been inadequate di fferent i ati on between 1i fe stage

requisites. White sucker fry and juveniles occur in a greater variety of

habitats (shallow riffles, slow runs, along edges, and backwater pools), while

white sucker adults (> 150 TL mm) are usually more common to pool habitats

(Propst 1982b). The second factor is that white suckers of all life stages

have the ability to survive in a variety of conditions. In stressed streams

(or sections) which would have low HSI's, white suckers may account for 50 to

80% of the relatively few species (3 or 4) of the fish population found.

While in less stressed environments more species are present and the relative

6
abundance of white sucker is lower (Propst 1982a). Thi s phenomenon could

occur when the high tolerance of white suckers allows them to survive periods

of stress that are lethal to other species, thus affecting the HSI and relative

abundance correlation.

In order to achieve a better correlation between HSI's and white sucker

relative abundance in riverine habitats, an additional model (Model 5) was

developed. More importance was given to cover with the addition of variables

for stream cover, percent shade, and pool depth. The importance of pool

velocity was considered by adding pool velocity and gradient variables. These

variables were intended to better define adult white sucker habitat. This

model has not been field tested. Decisions on which, if any, model to use

should be made by the potential user and wi l 1 depend on the user ' s needs and

resources available.

The lacustrine model was tested by entering reasonable combinations of

habitat variable values into the model (Table 4) and examining the model

output. The HSI's resulting from the model reflected assumed carrying capacity

trends in habitats with the same characteristics as the sample data sets.

Model Description

Because white suckers are opportunistic feeders, we did not consider food

to be important in determining white sucker habitat suitability. In unproductive lakes and streams food may influence abundance. However, measures of

lake and stream productivity for white suckers have not been quantified. We

assumed that habitat quality is determined primarily by cover, water quality,

and spawning habitat. These were used as model components. Componen~ ratings

were derived from individual variable suitability indices (Figs. 1 and 2).

Reasons for placing individual variables in specific components and assumed

variable interactions are described below.

Model Description - Riverine

Water quality component. The water quality component consists of turbidity (V 1 ) , pH (V 2 ) , dissolved oxygen (V l ) , and temperature (V 4 ) . These variables affect growth, survival, and/or distribution of white suckers. Suboptimum levels of these variables, as defined by the suitability index graphs,

result in negative effects on individuals. Toxic substances are not considered

in this model.

Reproduction. Temperature during spawning (V 6 ) is included in the reproduct i on component becau se it is be1i eved to be a pri ma ry factor i nfl uenci ng

initiation of spawning migration. Discharge may also be important, but would

be variable depending on the size of a river or stream. Also, less suitable

discharge levels can likely be compensated for by selection of more favorable

7
Habitat variables LHe requi sites

pH (V2 ) ----------------':::.Water qual ity (CWQ)-----

Dissolved oxygen (V 3 ) - - ----

Temperature (V 4 ) --- - - --'

Turbidity (V l ) -----~

Temperature (V S , V6)--~

Riffle velocity (V7)---~ .

Reproduction

Riffle depth (Vs ) ------

% cover (V g ) -------~____

_____________ Cover (CC)

% pools (V l O) --- - - - - -

Figure 1. Tree diagram illustrating relationship of habitat variables

and life requisites in the riverine model for the white sucker.

8
Habitat variables Life requisites

Turbidity (Vl)----------~

pH (V 2) ------------------------....:....::;~ Wa te r qua1i ty (CWQ)-----....

Dissolved oxygen (V])------~

Temperature (V4 ) -----------'

Temperature (V6)----------~

Dissolved oxygen (V]) Reproduction (CR)

Substrate (V 1 1 ) ------------

Figure 2. Tree diagram illustrating relationship of habitat variables

and life requisites in the lacustrine model for the white sucker. When

spawning occurs in inlet streams, riverine measurements for reproduction

and water quality may be substituted for the reproduction component.

9

HSI
velocity and depth. Riffle velocity (V 7 ) and depth (Va) are important for

spawning site selection. Temperature during larval development (Vs ) is

important to larval ontogeny and survival and to the timing of migration of

larvae to a lake or riverine rearing area. The time periods specified for

each variable (e.g., April through July) indicate when the variables are

important for the specified life stage throughout the entire range of the

species. If one of these suitability indices is used in an HSI model developed

to rate habitat, the time period when the life stage is actually present, or

expected to be present, should be used.

Cover. Shelter availability and presence of resting areas (V 9 ) is assumed

to enhance the carrying capacity of streams for white suckers. Percent pools

(V lO ) was included because pools serve as resting areas before spawning and

provide cover in the form of deeper water:

Model Description - Lacustrine

Water quality component. Refer to riverine model description.

Reproduction component. Lacustrine populations of white suckers spawn in

tributary streams or in littoral areas over sand and sand/gravel substrates

(VII) at suitable temperatures (V6 ) and dissolved oxygen levels (V 3 ) , any of

which can be limiting. If stream spawning occurs, the reproduction component

rating is derived from measurements taken in the riverine environment.

Suitability Index (51) Graphs for Model Variables

Suitability indices for selected variables are given below. The "R" for

riverine and "L" for lacustrine, under the heading "Habitat", describe where

the variable should be measured. Sources of data and assumptions used to

develop the suitability indices are listed in Table 1.

Habitat Variable Su itabi 1ity graph

R,L VI Maximum monthly average 1.0

turbidity during the

year. x

Q) 0.8 "'0

t:

......

>, 0.6

+-'

.....

.....

.0 0.4 C'tl

+-'

.....

:::J

(/) 0.2

0.0

a 100 200 300 400 I

JTU

10
R,L

V2 Weekly average pH during 1.0

year under stable conditions. If frequent

(diurnal ), large (> 1.0

x 0.8 Q)

pH unit) changes occur, '0

c:::

5I score should be ...... 0.6

reduced by 10%. >,

+-'

0.4 ..c

rc:l

+-' 0.2 ::i

Vl

0.0

0 2 4 6 8 10

pH

R,LV3 Minimum dissolved 1.0

oxygen levels near

sunrise during 0.8 May through August x

Q)

in areas of most '0

c::: suitable water ...... 0.6

temperature. >,

+-' 0.4

..c

rc:l

+-' 0.2 ::i

Vl

0.0

0

2

4

6

8 10

mg/l

R,L

V.. Average of mean weekly 1.0

water temperatures

at mid-afternoon during

x

July and August (Adult Q) 0.8

'0

and Juvenile). c:::

......

>, 0.6

+-'

..c 0.4 rc:l

+-'

Vl

::i 0.2

0.0

0 10 20 30 ~O

DC

11
R,L

Vs Average of mean weekly 1.0

water temperatures

during July and August

x

(1) 0.8 (Fry) . "'0

s::

...... b 0.6

.....

.....

..c 0.4 C'tl

+J

.....

:::l

(/) 0.2

0.0

a 10 20 30 40

DC

R,L

V 1.0 6 Average of mean weekly

water temperatures

x during spawning and (1) 0.8 "'0 incubation (April s::

through July) (Embryo). ......

>, 0.6 +J

.....

.....

..c 0.4 C'tl

+J

.....

:::l

(/) 0.2

0.0

a 10 20 30 40

DC

RV7 Average riffle velocity 1.0

during spawning and

incubation (April

x 0.8 through July) (Embryo). (1)

"'0

s::

......

c-, 0.6 +J

.....

..... 0.4 ..c

C'tl

+J

.....

:::l 0.2 (/)

0.0

a 25 50 75 100

em/sec

12
R Va Mean riffle depth 1.0

during spawning and

incubation (April x

Q) 0.8 through July) (Embryo). -0

c

......

>, 0.6 +..l

......

......

.D 0.4 ro

+..l

......

V) 0.2

0.0

0 15 30 45 60

cm

R Vg Percent instream and 1.0

overhanging shoreline

cover (e. g. , roots, x 0.8 brush, logs, willows, Q)

-0 undercut banks, and c

...... grass). 0.6

......

...... 0.4 .D

ro

+..l

...... 0.2 V)

0.0

a 25 50 75 100

%

1.0

R VlO Percent pools during

average summer flows x

Q) 0.8 (July through August) -0

c

(Adult, Juvenile, ......

>, 0.6 and Fry). +..l

......

......

.D

ro 0.4 +..l

......

V) 0.2

0.0

a 25 50 75 100

%

13
L Vll Littoral spawning 1.0 substrate. x

A. Cl ay, sil t , Q)

very '"0 0.8

fine sand « 0.25 s::

......

mm), S1 = 0.05. >, 0.6

B. Medium to coarse

+J

.... sand (0.25 to 1 mm), .... 0.4 S1 = 0.7. to

C. Very coarse sand .... (l to 2 mm), S1 ::::l

= V) 0.2

1.0.

D. Gravel-granule 0.0 (2 to 4 mm), S1 =

0.9.

E. Gravel-small

pebble (4 to

16 mm), S1 = 0.5.

F. Pebble (large),

cobble, boulders,

(> 16 mm), S1 =

0.05.

Adjust S1 according to

mixture of substrate

sizes, by judgment.

(Substrate categories

adapted from Cummins

1962; Cummins and

Lauff 1969).

14

I

r---

ABC D E F
Table 1. Sources of information and assumptions used in construction

of the suitability index graphs. "Excellent" habitat for the white

sucker was assumed to correspond to an SI of 0.8 to 1. 0, "good" habi tat

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 Assumption and sources

Although white suckers can tolerate a wide range of turbidities,

clear waters « 50 JTU) are considered excellent (Raney and

Webster 1942; Pflieger 1975). Waters of 50 to 150 JTU are good

to fair depending on the range of turbidity variability. Rivers

exhibiting constant turbidities are more conducive to stable,

wide spread white sucker populations than rivers which have

widely variable turbidities even if moderate (Muth pers. comm.

1983). High turbidities are judged to be fair to poor depending

on the variability and length of time a habitat is turbid because

reduced populations have been reported in turbid waters (Muth

pers. comm. 1983; Pflieger 1971).

The pH ranges which cause population declines or result in

slower growth are suboptimal (EIFAC 1969; Beamish 1972, 1974).

Levels of pH which allow maximum growth and reproduction are

optimum (EIFAC 1969; Trojnar 1977). It is assumed that frequent

pH fluctuations are suboptimum.

Dissolved oxygen levels which are low enough to cause white

suckers to avoid the area (2.4 mg/l) (Dence 1948), or are inadequate for reproductive success ($ 1.2 mg/l), or decrease

growth « 2.5 mg/l) (Siefert and Spoor 1974) are poor. Dissolved

oxygen levels 6 mg/l are generally considered optimum and D.O.

levels in which white sucker populations can be successfully

maintained, reproduce, and grow would be judged as at least fair

to good.

Temperatures which correspond to optimum growth and activity are

considered excellent (Horak and Tanner 1964; Reynolds and

Casterlin 1978). Temperatures which are lethal are judged poor

(Brett 1944; Carlander 1969; McCormick et al. 1977). White

suckers, when acclimated, can survive a wide range of temperatures when the temperature extremes are common to the area

and seasonal. These temperatures are rated poor to fair

(Thompson and Hunt 1930; Minckley 1963).

15
Table 1. (continued).

Variable Assumption and sources

Temperatures which allow larval white suckers optimum growth are

excellent (McCormick et al. 1977) and temperatures in which the

larvae can be commonly found are good (Marcy 1976). Temperatures which are lethal, cause high incidence of deformities,

or allow little or no growth are considered poor (McCormick

et al. 1977).

Temperatures which allow maximum hatching rates and at which

collection of viable eggs occurs are good to excellent

(McCormick et al. 1977; Fuiman 1978; Kreiger 1980; Curry 1979).

If hatching rates are diminished, the temperatures are considered fair and if hatching rates are very low or nonexistent

the temperatures are judged poor.

White suckers have not been observed spawning in areas of no

flow or in very fast (> 90 cm/sec) riffle areas, therefore,

these riffle velocities are judged as poor (Dence 1948; Symons

1976). White suckers, when in fast waters, preferred areas of

moderate velocities (30 to 49 cm/sec) (Symons 1976) and were

observed spawning at velocities of 50 to 59 cm/sec (Curry 1979),

these velocities are assumed excellent.

Spawning is reported most often to take place in shallow riffles

(Dence 1948; Geen et al. 1966). Spawning has been reported to

take place at depths of 30 cm (Nelson 1968) and 20 to 25 cm

(Curry 1979) and Fuiman (1978) has collected white sucker eggs

at depths of 15 to 20 cm. Depths at which eggs were deposited

or spawning observed are considered excellent. Increasing

depths and decreasing depths were assumed to exhibit less

optimum to poor conditions, respectively.

Propst (1982b) reported a high correlation between pool cover

and white sucker populations. Total cover is considered good

and cover of 40 to 75% is assumed excellent. An absence of

stream cover is assumed poor.

16
Table 1. (concluded).

Variable Assumption and sources

White suckers utilize pools for resting after negotiating

obstructions during migration and spawning (Stewart 1926;

Dence 1948). Larval white suckers feed in quiet eddies and

gentle currents (Stewart 1926); adult white suckers are primarily pool inhabitants (Propst 1982b) and seek out pools for

cover (Stewart 1926; Raney 1943; Dence 1948; Nelson 1968).

Streams without pools are suboptimum and streams with 40% to 60%

pools are considered optimum.

It has been reported that lacustrine populations spawn on sand

or gravel shoals subject to wave action (Reighard 1913; Hayes

1956; Olson 1963) and that the highest larval densities were

found over sand and sand/gravel substrates in littoral regions

(Krieger 1980). It is assumed that optimum lentic spawning

substrate is coarse sand and/or granule gravel. Large pebbles

and boulders or silt substrates are poor. Medium sand or small

pebble substrates are good to fair.

17
Riverine Model

This model utilizes the life requisite approach and consists of three

components: cover; water quality; and reproduction. The generated HSI applies

to resident fish in streams. However, the water quality and reproduction

components can also be used for deriving a reproduction component score in the

lacustrine model.

Water Quality (CWQ)'

CWQ = the lowest SI rating of V1 , V2 , V3 , or V4 •

Reproduction (CR).

CR =the lowest SI rating of Vs , V6 , V7 , Va.

CC = ------:=2--

HSI determination.

HSI

If CWQ or CR 0.4, the HSI equals the lowest of the following:

CWQ; CR; or the HSI rating from the above equation.

Data from application of the riverine HSI model at LaGarde Creek,

Colorado, are listed in Table 2. Data from application of the riverine HSI

model at St. Vrain Creek and Big Thompson River, are listed in Table 3.

18
Table 2. Data sets from application of the riverine H51 model

for white suckers at LaGarde Creek, Colorado.

Data set 1 Data set 2 Data set 3

Variable Data 51 Data 51 Data 51

Turbidity (JTU) VI Visually 1.00 Vi sua lly 1.00 Visually 1.00

observed observed observed

pH V2 7.5 1.00 7.7 1.00 7.7 1.00

Dissolved oxygen

(mg/l) V3 1.00 1.00 1.00

Temperature - adult/juvenile

(OC) V4 20.0 1.00 12.2 0.70 16.0 0.90

Temperature - fry (OC) Vs 20.0 0.85 11.0 0.28 18.0 0.75

Temperature - embryo (OC) Vs 19.0 0.30 12.0 1. 00 17.8 0.40

Riffle velocity

spawning/embryo

(cm/sec) V7 0.00 0.00 8.10 0.23 3.00 0.10

Riffle depth (cm) Va 16.0 1.00 26.0 0.95 25.0 1.00

Percent cover Vg 18.5 0.50 4.0 0.20 3.0 0.18

Percent pools VlO 82.0 0.70 53.0 1.00 49.0 1.00

Component 51

C

WQ = 1.00 0.70 0.90

CR = 0.00 0.23 0.10

Cc = 0.60 0.60 0.59

H51 = 0.00 0.23 0.10

19
Table 3. Data sets from application of the riverine HSI model for white suckers

at St. Vrain Creek and Big Thompson River, Colorado (Propst 1982a).

St. Vrain Creek Big Thompson River

Variable

Hygiene

Data SI

Longmont

Data SI Data

RR

SI

Gowanda

Data SI

Mtn. View

Data SI

Sewage

Data SI

Johnstown

Data SI Data SI

Turbidity (JTU)

pH

VI

V2

a 1.00

7.81.00

a 1. 00

8.5 0.90

a 1. 00

8.3 0.95

a 1.00

8.8 0.83

4.1 1.00

8.0 1.00

7.11.00

7.81.00

7.71.00

8.5 0.90

16.0 1.00

8.5 0.90

Dissolved oxygen

(mg/l) V3 9.21.00 8.4 1.a 8.4 1. 00 8.8 1.00 10.6 1.00 7.4 1. 00 8.0 1.00 10.0 1.00

Temperature (adult/b

juvenile) (0 C) V4

Temperature (fry)b

(0 C) V5

21.51.00

21.5 0.93

12.0 0.70

12.0 0.35

13.5 0.80

13.5 0.45

20.0 1.00

20.0 0.85

14.0 0.80

14.0 0.48

13.0 0.75

13.0 0.45

16.0 0.90

16.0 0.60

19.0 1.00

19.0 0.80

Temperature (spawning/embryo)c

(0 C) V6 10.0 0.65 10.0 0.65 10.0 0.65 10.0 0.65 10.0 0.65 10.0 0.65 10.0 0.65 10.0 0.65

Riffle velocity (spawning/embryo)

(cm/sec) V7

Riffle depth (cm)e Va

37.6 0.95

10.8 0.26

80.0 0.9

10.0 0.25

15.0 0.43

25.0 0.63

c 0.80

2.0 0.10

5.0 0.10

d 1.00 d 0.85

c/d 0.90

6.0 0.20

26.5 0.70

1.00

c 0.80

d

16.8 0.45

0.0 0.00

d 1.00

c/d 0.90

0.3 0.15

8.9 0.21

d 0.85

alb 0.30

0.0 0.1

6.6 0.15

1.00

c 0.80

1.00 d

0.80

d

c

0.9

0.80

d

Vg c

VI 0

% pools VI 2

%cover

Spawning substrate

N

a

Component SI

C

WQ =

C = R

C = C

HSI =

1.00

0.65

0.61

0.74

0.70

0.35

0.58

0.35

0.80

0.45

0.53

0.58

0.83

0.30

0.13

0.30

0.80

0.48

0.18

0.41

0.75

D.45

0.23

0.43

0.90

0.60

0.45

0.63

0.90

0.65

0.10

0.39

aNo measurements were taken at these four sites on the St. Vrain Creek. but it is assumed that turbidity would be very close or the same as the turbidity in the Big Thompson River, which has SI's of 1.0.

bTested as the same.

cApri1 to June temperature measurements were only recorded at the St. Vrain River, Hygiene site, so it is assumed that the other sites also

had early spring temperatures of 100 C.

dNo direct measurements were taken for riffle velocity. but gradient (m/km) was taken at all sites. The gradients ranged from 1.5 to 9.1 m/km,

with SI ratings of 1.0 to 0.95, respectively. From this information. it was assumed that the riffle velocities ranged from low to moderate, and were given SI ratings of 0.85 to 1.0.

eNo riffle depth measurements were taken, thus the riffle depth variable was not included in this model.
Lacustrine Model

This model utilizes the life requisite approach and consists of two

components: water quality and reproduction.

CWQ = the lowest SI rating of V1 , V2 , V3 , or V4 •

Reproduction (CR). Two options exist:

1) If there is evidence of spawning or it is suspected within a

lake and a windswept shoreline is available for lake or

reservoir spawners,

CR = V3 , V6 , or V1 1 , whichever is lower

provided that the lake or reservoir is not subject to extreme

drawdown or fluctuation from March through July. If drawdown

is 2 m, reduce CR by 0.3; if drawdown is 5 m, reduce CR by

0.5, with a minimum CR value of O.

2) If there is evidence of spawning or it is suspected to take

place in a suitable inlet stream,

CR = [(lowest of V1 , V2 , V3 , or V4 ) 1/2

x (lowest of Vs , V6 , V7 , or Vs ) ]

where all CR variables are measured in the inlet stream.

HSI determination.

1/2

HSI = (CWQ x CR)

If CWQ or CR 0.4, the HSI equals the lowest of CWQ or CR; or the HSI

rating from the above equation.

Sample data sets using the lacustrine HSI model are listed in Table 4.

21
Table 4. Sample data sets using lacustrine HS1 model.

Data set 1 Data set 2 Data set 3

Variable Data S1 Data S1 Data SI

Turbidity (JTU) VI 65 0.9 4()' 1.0 200 0.4

pH V2 8.0 1.0 8.0 1.0 6.2 0.8

Dissolved oxygen

(mg/l) Vl 7.1 1.0 5 0.9 4 0.7

Temperature - adult/

juvenile (OC) V4 25 0.9 20 1.0 16 0.9

Temperature - spawning/embryo

(OC) Vs 10.5 0.8 9.5 0.6 13 1.0

Littoral spawning

substrate Vll S/C 0.8 S/C 0.9 C/D 0.95

Component SI

CWQ = 0.90 0.90 0.40

C a = 0.80 0.60 0.70 R

HS1 = 0.85 0.73 0.40

aAssumes spawning is in 1ake.

22
ADDITIONAL HABITAT SUITABILITY INDEX MODELS

Model 1

Optimum riverine habitat for white suckers is characterized by the following conditions (assuming water quality is adequate): clear « 50 JTU) streams

with cool to moderate summer temperatures (18 to 24° C); 40 to 60% pools; and

greater than 40% of the stream area with cover, such as aquatic vegetation,

brush, logs, and undercut banks.

HSI = number of above criteria present

4

Model 2

Optimum 1acustri ne habi tat for whi te suckers is cha racteri zed by the

following conditions (assuming water quality is adequate): majority of water

body moderately clear « 75 JTU); greater than 30% of littoral area with

aquatic vegetation; and an available spawning stream or windswept lake shore

with sand or gravel substrate. -

HSI = number of above criteria present

3

Model 3

The appropriate catostomid standing crop model from Aggus and Morais

(1979) can be used to calculate an HSI in lakes and reservoirs. The data base

was developed from fish standing crop, angler use and harvest, and environmental data from United States reservoirs with surface areas of 500 acres

or larger. The analytical method used includes the application of correlationregression analysis to experimental data to identify and quantify important

relationships between fish standing crop and environmental features in

reservoirs. To make the method compatible with HEP, it was necessary to:

(1) locate and quantify important standing crop/environmental relations;

(2) reduce these to a single estimate of standing crop of a particular species

using multiple regression analysis; and (3) convert these to an index of

habi tat sui tabi 1i ty compati b1e wi th the Habi tat Eva 1uat i on Procedures for

comparison to other habitat types.

The National Reservoir Research Program utilizes standing crop of fish as

a direct measure of abundance. Therefore, suitability of a particular

reservoir habitat to a particular fish species or species group is considered

to be positively related to the average standing crop biomass. This approach

assumes that total biomass of a particular species reflects successful

reproduction, feeding, and presence of suitable habitat for other life

23
processes. In Aggus and Morais (1979), catostomid standing crops were used to

develop regionalized reservoir fisheries predictive equations.

Model 4

Use the appropriate reservoir description and suitability rating list

from McConnell et al. (1982) to calculate an HSI for white suckers in planned

reservoirs.

Model 5

This model was developed after testing the original riverine model in the

summer in LaGarde Creek, St. Vrain Creek, and Big Thompson River, Colorado.

The model was expanded to include additional variables to better assess adult

habitat, spawning habitat and cover. This model follows a life requisite

approach, as. used in the original riverine model (page 26). Many of the

variables are the same used in the original riverine model (turbidity, pH,

dissolved oxygen, temperature [adult/juvenile, fry, embryo], riffle velocity,

riffle depth, percent cover, percent pools). The new variables include:

riverine spawning substrate; pool depth; percent shade; gradient; pool

velocity; and spawning distance. Propst (1982b) felt cover was most important

in determining the suitability of a stream for white suckers.

This alternate riverine model combines the variables into components of

water quality, reproduction, and cover (Fig. 3), which are used to derive the

habitat suitability index. Reasons for placing individual variables in

specific components are described below.

Water quality component. Refer to riverine model description (page 14).

Reproduction. Spawning temperature (V6 ) is included because it influences

spawning migrations, reproductive success, and hatching rates. Larval temperature (Vs ) is included because of its influence on larval growth and

activity. Riffle velocity (V,) and riffle depth (Va) are important in spawning

site sel ecti on. White suckers prefer to spawn in moderately fast, shallow

riffle areas, although they are tolerant of a relatively wide range of riffle

depths. Spawning substrate (V 1 2 ) is included because spawning has been

observed over sand and gravel substrates and not over mud or boulders. Spawning habitat distance (Vi') is included because we assume the distance fish

must mi grate to spawn i nfl uences reproductive success. Whi te suckers can

migrate to and spawn successfully in small streams that do not contain habitat

for adults, but do contain spawning habitat and habitat that can support

sizable fry and juvenile populations. Quantitative data on the effect of

distance on reproductive success are not available, thus, this variable is

based solely on professional judgment.

24
Habitat variables Life requisites

Rep roduct ion ---------------------4 HSI

Cove r -J

Water Qual i ty --____ pH (V2) -----------_____

Riffle velocity (V 7 ) --------------

Riffl e depth (V8) ---------------

Turbidity (Vl)--------------~

Poo 1 depth (V 13) --------------___

~6 pool s (V1 0 ) -------------------.,.

Spawning substrate (V 1 2 ) --------'

Spawning distance (V 1 7 ) ---------'

Dissolved oxygen (V3)----------~

Temperature (V4 ) ---------------'

Gradi ent (V 1 s) ------------------"

Poo 1 ve1ocity (V16) -------------/

% shade (V 14) -----------------~

Temperature (Vs , V6 ) -----------...

% instream/shoreline cover (Vs )

Figure 3. Tree diagram illustrating relationship of habitat

variables and life requisites in riverine HSI model 5 for the

white sucker.

25
Cover. Pool velocity (V 1 6 ) and gradient (VIS) are included because white

suckers show a marked preference for slow to moderate velocities and do not

occur where there is no fl ow. Juvenil es and adults prefer water of low

velocity, while fry are found in a wider range of velocities. Shade (V 1 4 ) is

an indication of cover, and white suckers are observed in shaded pools.

Instream cover (root systems, uprooted trees, undercut banks, brush) and

shoreline cover (willows, grass) (Vg ) are very important to white suckers,

especially in pools. A high correlation between pool cover and white sucker

populations was observed by Propst (1982b) and white suckers flee to the cover

of pools when disturbed. Pool depth (V 1 l ) is included because depth offers

cover and greater numbers of white suckers are found in deeper pools, especially those lacking in instream cover. Percent pools (V lO ) is important

because adult and juveniles are common pool inhabitants and pools allow resting

areas for white suckers moving upstream to spawn or waiting to spawn.

SUITABILITY INDEX (SI) GRAPHS FOR MODEL 5

Suitability indices for model 5 are given below. The model is for

riverine (R) habitats. The rationale for the alternative variables is listed

in Table 5.

Habitat Variable

Maximum monthly

average turbidity

during the year.

26

Suitability graph

1.0

x

Q) 0.8

"0

s::

......

>, 0.6

+-'

.~

.......

0.4 rc

+-'

Vl

::l 0.2

0.0

0 100 200 300 400

JTU
R

V2 Weekly average pH 1.0

during year under

x 0.8 stable conditions. (I)

-0

If frequent (diurnal), c:::

......

large (> 1.0 pH unit) >, 0.6

changes occur, SI +.>

'rscore should be 'r- 0.4 reduced by 10%. ..a

to

+.>

'r-

::l

Vl 0.2

0.0

0

2

4 6 8 10

pH

RV3 Minimum dissolved 1.0

oxygen levels near

sunrise during May

x 0.8 through August in (I)

-0

area of most suitable c:::

......

water temperature. >, 0.6 +.>

'r-

'r- 0,4 ..a

to

+.>

'rVl

::l 0.2

0,0

0

2

4 6 8 10

mg/l

R

V4 Average of mean 1.0

weekly water temperatures at midx

(I) 0.8 afternoon during -0

c:::

July and August ......

(Adult and Juvenile). >, 0.6 +.>

'r-

'r-

..a 0.4 to

+.>

'r-

::l 0.2 Vl

0.0

0 10 20 30 40

DC

27
R Vs Average of mean 1.0

weekly water temperatures during x 0.8 OJ

July and August "'C

s::

(Fry) 0

....... 0.6

>,

.......,

orr-

'r- 0.4

.0

co.......,

:::::l 0.2 Vl

0.0

0 10 20 30 40

°c

R V6 Average of mean 1.0 weekly water temeratures during x

OJ 0.8 spawning and in- "'C

s::

cubat ion (Apri 1 .......

through July) >,

......., 0.6

(Embryo) °

orr-

'r-

.0 0.4 co.......,

or-

:::::l

Vl 0.2

0.0

0 10 20 30 40

°c

R V7 Average riffle 1.0

velocity during

spawning and in- x

OJ 0.8 cubati on (April "'C

s::

through July) .......

(Embryo) ° .......,

>, 0.6 'rr-

.0 0.4 co .......,

Vl

:::::l 0.2

0.0

0 25 50 75 100

em/sec

28
R Va Mean riffle depth 1.0

during spawning

x and incubation CJ) 0.8

(April through "'0

July) (Embryo). ......

>, 0.6

+-'

.,.....

r-

.,..... 0.4 ..Cl

to

+-'

.,.....

:::s 0.2 (./)

0.0

0 15 30 45 60

cm

R

Vg Percent instream 1.0 and overhanging

shoreline cover

x

(e. g. , roots, brush, CJ) 0.8 "'0

logs, willows, under- ......

cut banks, grass). >, 0.6

+-'

.,.....

r-

.,.....

..Cl 0.4 to

+-'

.,.....

:::s

(./) 0.2

0.0

0 25 50 75 100 %

R

VlO Percent pools during 1.0

average summer flows

(July through August)x 0.8

(Adult, Juvenile, and CJ)

"'0

Fry) . ...... 0.6

>,

+-'

.,.....

.,..... 0.4 ..Cl

to

+-'

.,.....

:::s 0.2 (./)

0.0

0 25 50 75 100 %

29
R V12 Riverine spawning 1.0 substrate.

>< 0.8 A. Clay, silt, Q)

very "'0

fine sand « 0.0039 s:::::

......

to 0.125 mm), SI = >, 0.6

0.1 +-'

B. Fine sand, medium 0.4

sand (0.125 to .0

ro

.5 mm), SI =0.5 +-'

C. Coarse sand, ::l 0.2 very VI

coarse sand (0.5 to

2 mm), SI = O. 8 0.0

D. Gravel-granule (2 to

4 mm), SI = 1. 0

E. Gravel-small pebble

(4 to 16 mm), SI =

0.8

F. Pebble, cobble,

boulders (> 16 mm),

SI =0.2

Adjust SI according to

mixture of substrate

sizes, by judgment.

(Substrate categories

adapted from Cummins

1962; Cummins and

Lauff 1969).

......- I--

......- l-

.

I--

ABC D E F

R Depth of pools

in study reach.

30

1.0

><

Q) 0.8 "'0

s:::::

......

>, 0.6 +-'

.0 0.4 ro

+-'

::l

V) 0.2

0.0

a 50 100 150 200 250 300

em
R V14 Percent shade. 1.0

x

Q) 0.8 "'C

s::

......

>, 0.6 +J

......

...... 0.4 .0

to

.;...>

......

::::l 0.2 Vl

0.0

0 25 50 75 100

%

R V15 Stream gradient in 1.0 study reach.

x 0.8

Q)

"'C

s::

...... 0.6

>,

+J

......

0.4 .0

to

+J

::::l 0.2 Vl

0.0

0 10 20 30 40

m/km

R V16 Mean water velocity 1.0 in pools during year. x

Q)

"'C 0.8 s::

......

>,

+J 0.6 ......

......

.0 0.4 to

+J

......

::::l

Vl 0.2

0.0

0 8 16 24 32 40

em/sec

31
R Distance of potential

spawning habitat from

lentic or pool habitat.

(Adjust 51 on judgments

on the passability of

obstructions).

32

1.0

x 0.8 Q)

i:J

C

...... 0.6

>,

+.>

.,....

r- 0.4 .0

to

+.>

.,....

::::l 0.2 t/)

0.0

0 10

distance ( km)

20
Table 5. Sources of information and assumptions used in construction

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

the white sucker was assumed to correspond to an SI of 0.8 to 1.0,

II goodll habitat to an SI of 0.5 to 0.7, IIfairll 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 source

Refer to the general riverine HSl turbidity variable

(V1) .

Refer to the general riverine HSl pH variable (V2 ) .

Refer to the general riverine HSl dissolved oxygen

variable (V 3 ) .

Refer to the general riverine HSl temperature (adult,

juvenile) variable (V4 ) .

Refer to the general riverine HSl temperature (fry)

variable (Vs ) .

Refer to the general riverine HSl spawning temperature

(embryo) variable (V6 ) .

Refer to the general riverine HSl riffle velocity

variable (V 7 ) .

Refer to the general riverine HSl riffle depth variable

(Va).

Refer to the general riverine HSl instream/shoreline

cover variable (V 9 ) .

Refer to the general riverine HSl percent pool variable

(V lO ) .

White suckers have been observed spawning over gravel

(Curry 1979) and sand/gravel substrates. These substrates are considered to be excellent (Dence 1948;

Minckley 1963). It is assumed that substrates of silt,

mud, and large gravel and boulders are suboptimum.

33
Table 5. (concluded).

Variable Assumptions and source

Pool depth is important as cover (Stewart 1926). Pool

depths at which white suckers are commonly found (60 to

90 em) (Propst 1982b) are considered optimum. Very

shallow depths « 25 em) are considered poor and very

deep pools were assumed to contribute to a good to fair

habitat because white suckers are found at varying pool

depths in streams (Thompson and Hunt 1930; Propst

1982b). Deeper pool depths are usually not considered a

habitat detriment because the white sucker inhabits many

depths in lacustrine habitats (Reighard 1913).

Shade is an indication of cover and streams with 50%

shade are considered excellent. Thompson and Hunt (1930)

and Dence (1948) report that suckers are commonly found

in shaded portions of streams. Unshaded streams are

assumed to be poor to fair depending on other cover

available.

White suckers reach maximum abundance in low to moderate gradients (Stewart 1926). Since Propst (1982b)

failed to find white suckers where there was no flow,

very low gradients « .5 m/km) were considered poor.

Very high gradients (> 25 m/km) were also considered

poor because white suckers appeared to have trouble

maintaining equilibrium in turbulent waters (Symons

1976). Minckley (1963), Curry (1979), and Hocutt and

Stauffer (1975) reported on white suckers occupying

streams with gradients of 1.2 to 13 m/km, which are

considered excellent to fair, respectively, as the

gradient increases.

White suckers are common in pools with slow to moderate

velocities « 40 em/sec), but Minckley (1963), and

Symons (1976) most frequently found adult white suckers

at velocities of 10 to 19 em/sec which were assumed

excellent. As mentioned in VIS' turbulent velocities

(Symons 1976) or zero velocities (Propst 1982b) are

considered poor.

Suckers have been reported to successfully spawn after

migrating up to 6.4 km (Dence 1948). Spawning habitat

up to these distances, without known obstructions, are

considered excellent. It is assumed that longer

distances would be progressively less suitable.

34
Riverine Model

This model utilizes the life requisite approach and consists of three

components: cover; water quality; and reproduction. The generated HSI applies

to resident fish in streams.

Water Quality (CWQ).

Reproduction (CR) .

2

4

(VIS + V16 )

X V10 + V13 + ----=---

HSI determination.

HSI (C C X CC) 1/ 3

= WQ x R

If C

WQ' CR' or Cc 0.4, the HSI equals the lowest of the following:

C

WQ; CR; CC; or the HSI rating from the above equation.

Sample data sets for model 5 are listed in Table 6.

35
Table 6. Sample data sets using HS1 modelS.

Data set 1 Data set 2 Data set 3

Variable Data SI Data SI Data S1

Turbidity (JTU) VI 25 1.00 30 1.00 75 0.9

pH V2 6.0 0.73 7.0 1.00 6.0 0.73

Dissolved oxygen

(mg/l) V] 6.0 1.00 7.0 1. 00 5.0 0.90

Temperature - adult/juvenile

(0C) V4 19.0 1. 00 10.0 0.60 15.0 0.85

Temperature - fry

(0C) Vs 17.5 0.70 14.0 0.50 14.0 0.50

Temperature - embryo (0 C) V6 12.0 1. 00 10.1 0.65 12.0 1. 00

Riffle velocity - spawning/embryo

(cm/sec) V7 75.0 0.50 80.0 0.30 60.0 1.00

Riffle depth (cm) Va 19.0 1. 00 19.0 1.00 38.0 0.60

Percent cover V, 50.0 1. 00 12.0 0.40 50 1.00

Percent pools VlO 23.0 0.60 15.0 0.40 36.0 0.90

Spawning substrate V12 S/C 0.60 C 0.80 C/D 0.90

Pool depth V13 75.0 1. 00 55 0.80 40.0 0.50

Percent shade V14 50 1.00 25 0.6 60 1.00

Gradient (m/km) VIS 2.5 1.00 11.0 0.90 6.0 1.00

Pool velocity

(cm/sec) V16 10.0 1. 00 8.0 0.9 12.0 1.00

Spawning distance

( km) V17 2 1.00 0.5 1.00 0.2 1.00

36
Table 6. (concluded).

Variable

Data set 1

Data 51

Data set 2

Data 51

Data set 3

Data 51

Component 51

CWQ = 0.73 0.60 0.73

CR = 0.50 0.30 0.50

Cc = 0.90 0.65 0.85

H51 = 0.69 0.30 0.68

37
INSTREAM FLOW INCREMENTAL METHODOLOGY (IFIM)

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

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

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

Milhous et al. (1981), is one component of IFIM that can be used by investigators interested in 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 given time by using

habitat ratios (relative spatial requirements of various life

stages).

Suitability Index Graphs as Used in IFIM

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

instream suitability of the habitat variables most closely related to stream

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

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

ana lysis represent the hydraul i c-re 1ated parameters for whi ch a speci es or

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

preferences for velocity and temperature will have very broad curves for

depth, substrate, and cover).

WELUT has standardized the terminology pertaining to SI curves and

designated four categories of curves. All species curves for HEP and IFIM are

referred to collectively as suitability index (SI) curves or graphs. The

designation of a curve as belonging to a particular category does not imply

that there are differences in the quality or accuracy of curves among the four

categories.

Category one curves are the most common type presently available for use

with HEP or IFIM. Usually category one curves have as their basis one or more

1i terature sources. Some SI curves may be deri ved from genera 1 statements

made in the literature about fishes (i.e., rainbow trout spawn in gravel; fry

prefer shallow water). Some category one curves may come from 1iterature

sources which include variable amounts of field data (i.e., from a sample size

of 300, fry were observed in velocities ranging 0.0 to 3.0 ft/sec, and 80%

were found in velocities less than 1.0 ft/sec). Other category one curves may

be based entirely on professional opinion, by using the Delphi technique or

38
educated guesswork (i. e., an expert bel i eves that vel oci ties rangi ng 1. 0 to

8.0 ft/sec are necessary for successful spawning of striped bass). Most

category one curves are the resul t of a combi nat i on of sources; the fi na1

curve may include information from the literature, combined with field data,

and smoothed or modifi ed using professi ona 1 judgement. Category one curves

usua lly are intended to refl ect genera 1 habi tat sui tabil ity throughout the

entire geographi c range of the speci es and throughout the year, un1ess they

are identified as being applicable only to a given area or season. In the

latter case, curves developed for a specific area or stream may not accurately

reflect habitat utilization in other areas. Curves meant to describe the

general habitat suitability ofa variable throughout the entire range of a

species may not be as sensitive to small changes of the variable within a

specific stream (i .e., rainbow trout will generally utilize silt, sand, gravel,

and cobble for spawning substrate, but utilize only cobble in Willow Creek,

Colorado).

Category two curves are derived from frequency analyses of field data,

and are basi ca lly curves fi t to a frequency hi stogram. Each curve descri bes

the observed utilization of a habitat variable by a life stage. Category two

curves unaltered by professional judgment or other sources of information are

referred to as utilization curves. When modified by judgment they then become

category one curves. Utilization curves from one set of data are not

applicable for all streams and situations (i.e., a depth utilization curve

from a shallow stream cannot be used for the Mi ssouri River). Category two

curves, therefore, are usually biased because of limited habitat availability.

An ideal study stream woul d have all substrate and cover types present in

equal amounts; all depth, velocity, and percent cover intervals available in

equal proportions; and all combinations of all variables in equal proportions.

Utilization curves from such a perfectly designed study theoretically should

be transferable to any stream within the geographical range of the species.

Curves from streams with high habitat diversity, then, are generally more

transferable than curves from streams with low habitat diversity. Users of a

category two curve should first review the stream description to see if conditions are similar to those present in the stream segment to be investigated.

Some variables to consider might include stream width, depth, discharge,

gradient, elevation, latitude and longitude, temperature, water quality,

substrate and cover diversity, fish species associations, and data collection

descriptors (time of day, season of year, sample size, sampling methods). If

one or more deviate significantly from those of the proposed study site, then

curve transference is not advised, and the investigator should develop his own

curves.

Category three curves are derived from utilization curves which have been

corrected for envi ronmenta 1 bi a s and therefore represent preference of the

speci es. To generate a preference curve, one must s imul taneously collect

habitat utilization data and habitat availability data from the same area.

Habitat availability should reflect the relative amount of different habitat

types in the same proportions as they exi st throughout in the stream-study

area. A curve is then developed for the habitat frequency distribution in.the

same way as for fish utilization observations, and the equation coefficients

of the availability curve are subtracted from the equation coefficients of the

39
the utilization curve, resulting in preference curve coefficients. Theoretically, category three curves should be unconditionally transferable to any

stream, although this has not been validated. At present, very few category

three curves exist because most habi tat uti 1i zat i on data sets are wi thout

concomitant habitat availability data sets. In the future, the need to collect

habitat availability data will be impressed upon investigators.

Category four curves (conditional preference curves), describe habitat

requirements as a function of interaction among variables. For example, fish

depth utilization may depend on the presence or absence of cover; or velocity

utilization may depend on time of day or season of year. Category four curves

are just beginning to be developed by IFASG.

HSI models generally utilize category one curves for habitat eva1u~ion.

IFIM analyses may utilize any or all categories of curves, but category three

and four curves yield the most precise results in IFIM applications; and

category two curves wi 11 yield accurate results if they are found to be

transferable to the stream segment under investigation. If category two

curves are not felt to be transferable for a particular application, then

category one curves may be a better choice.

For an I FIM ana1ysis of ri veri ne habi tat, an investigator may wi sh to

utilize the curves available in this publication; modify the curves based on

new or additional information; or collect field data to generate new curves.

For example, if an investigator has information that spawning habitat utilization in his study stream is different from that represented by the SI curves,

he may want to modify the existing SI curves or collect data to generate new

curves. Once the curves to be used are decided upon, then the curve coordinates are used to build a computer file (FISHFIL) which becomes a necessary

component of PHABSIM analyses (Mi1hous et a1. 1981).

Availability of Graphs for Use in IFIM

All curves ava i 1ab1e for I FIM analysis of whi te sucker habi tat are

category one (Table 7). Investigators are asked to review the curves (Figs. 4

to 8) and modify them, if necessary, before using them.

Spawning. For IFIM analyses of white sucker spawning habitat, use curves

for the time period during which spawning occurs (sometime between March and

July, depending on locale). Spawning curves are broad and, if more accuracy

is desired, investigators are encouraged to develop their own curves which

will specifically reflect habitat utilization at the selected site.

There are two approaches for determining the amount of spawning/egg

incubation habitat for a given stream reach. The recommended approach for the

white sucker is to treat spawning and egg incubation as separate life stages,

each with its own set of criteria (Figs. 4 and 5). If the spawning/egg incubation weighted useable area varies by more than 10% during the 5 to 14 day egg

incubation period, then investigators may wish to determine the effective

spawning habitat, using methods outlined by Mi1hous (1982).

40
Table 7. Availability of 51 curves for the 1F1M analyses of white sucker habitat.

Velocitl Deptha Substratea,b Temperaturea Covera

Spawning Use SI curve, Use SI curve, Use SI curve, Use SI curve, No curve

Fig. 4. Fig. 4. Fig. 4. Fig. 4. necessary.

Egg incubation Use SI curve, Use SI curve, Use SI curve, Use SI curve No curve

Fig. 5. Fig. 5. Fig. 5. Fig. 5. necessary.

Fry Use SI curve, Use SI curve, Use SI curve, Use SI curve Use SI curve,

Fig. 6. Fig. 6. Fig. 6. Fig. 6. Fig. 6.

Juvenile Use SI curve, Use SI curve, Use SI curve, Use SI curve Use SI curve,

Fig. 7. Fig. 7. Fig. 7. Fig. 7. Fig. 7.

..... Adult Use SI curve, Use SI curve, Use SI curve, Use SI curve Use SI curve,

Fig. 8. Fig. 8. Fig. 8. Fig. 8. Fig. 8.

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

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

1 = plant detritus/organic material

2 = mud/soft clay 3 = silt (particle size < 0.062 mm)

4 = sand (particle size 0.062-2.000 mm)

5 = gravel (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)
Coordinates 1.0

x .x: x 0.8 0.0 0.0 (]J

"'0

0.5 0.4 ..... 0.6 1.0 1.0

2.0 1.0 .~

3.0 0.0 r-

.~ 0.4

100.0 0.0 .0

111

+>

.~

;:] 0.2 U')

0.0

a 1 2 3

Velocity (ft/sec)

x

0.0 0.0

0.5 1.0

0.8 1.0

1.0 0.8

2.0 0.0

100.0 0.0

1.0

(]J

x 0.8

"'0

C

..... 0.6

+>

.~

'r-. 0.4 .0

111

+>

.~ 0.2 U')

0.0

a 1 2

Depth (ft)

o. a I I I I

0.0 0.2 0.4 0.6 0.8 1.0

Substrate particle diameter (inches)

x

0.000

0.001

0.002

0.009

0.010

0.039

0.040

0.078

0.079

0.156

0.157

0.629

0.630

100.000

J.-.-

0.00

0.00

0.05

0.05

0.80

0.80

1.00

1.00

0.90

0.90

0.50

0.50

0.05

0.05

1.0

x 0.8

(]J

"'0

..... 0.6

;:: 0.4 - 'r-

.0

111

+>'; 0.2 - U')

L

Figure 4. 51 curves for white sucker spawning velocity, depth,

substrate, cover, and temperature.

42
Cover is assumed not to be important

for white sucker spawning. No curve

is necessary.

Coordinates

x -L

1.0

0.0 0.0

43.0 0.0 Q)

x 0.8

54.0 1.0 "'C

61.0 1.0 ....... 0.6

64.0 0.4 -lJ 75.0 0.0 'rr-' 0.4 100.0 0.0 or-

..c \ nj

-lJ

or- 0.2 ::s

(/)

0.0

0 20 40 60 80 100

Temperature (OF)

Figure 4. (concluded).

43
Coordinates 1.0

x ...L

0.0 0.0 x 0.8 OJ 0.5 0.4 "'0

c

1.0 1.0 ...... 0.6 2.0 1.0 >,

+->

3.0 0.0 orr- 0.4 100.0 0.0 or-

..0

tt3

+-> 'r-

::I 0.2

V)

0.0

0 2 3

Ve 1ocity (ft/sec)

x ...L 1.0

0.0 0.0

0.5 1.0 x 0.8 0.8 1.0 OJ

1.0 0.8 "'0

c

2.0 0.0 ...... 0.6

>,

100.0 0.0 +-> or-

:;:: 0.4 ..0

tt3

+-> or- 0.2 ::I

V)

0.0

0 1 2

Depth (ft)

I I I

IL

lI1.0

orx 0.8

OJ

"'0

C

...... 0 6 ~.

:;: 0.4 ..0

tt3

+->

.; 0.2

V)

1.-

0.00

0.00

0.05

0.05

0.80

0.80

1.00

1.00

0.90

0.90

0.50

0.50

0.05

0.05

x

0.000

0.001

0.002

0.009

0.010

0.039

0.040

0.078

0.079

0.156

0.157 .

0.629

0.630

100.000

0.0

0.0 0.2 0.4 0.6 0.8 1.0

Substrate particle diameter (inches)

Figure 50 S1 curves for white sucker egg incubation velocity, depth,

substrate, cover, and temperatureo

44
Cover is assumed not to be important

for white sucker egg incubation. No

curve is necessary.

Coordinates

x

0.0

41.0

48.0

53.0

59.0

63.0

69.0

75.0

100.0

.1.-

0.0

0.0

0.8

0.9

1.0

0.8

0.7

0.0

0.0

0.8

"'0

c

......

>, 0.6

+>......

=::: 0.4 .D

t'O'

+>

-S' 0.2

V)

o 20 40 60 80 100

Temperature (OF)

Figure 5. (concluded).

45
Coordinates

x

0.0

0.3

1.0

100.0

....L1.0

1.0

0.0

0.0

1.0

0.8

"0

s=

....... 0.6

-l-l

.r0.0

012

Velocity (ft/sec)

:;: 0.4

0.0

1.0

0.6

..0

ttl"

-l-l

:3 0.2 V)

.r-

>< 0.8

OJ

"0

t::

.......

....L0.0

1.0

1.0

x

0.0

1.0

100.0

o 1

Depth (ft)

2

x ....L0.0 1.0

100.0 1.0

Based on assumption that all substr~te

types are suitable.

1.0

>< 0.8 - OJ

"0

t::

....... 0.6 -

?;>

;:: 0.4 - .r-

..0

ttl

0.2 - ::I

V)

I0.0

Substrate

Figure 6. 51 curves for white sucker fry velocity, depth,

substrate, cover, and temperature.

46
Coordinates 1.0

x -L 0.8 0.0 0.1 -a 40.0 1.0 s::

75.0 1.0 ...... 0.6

e-, 100.0 0.5 +-> ......

:;:::: 0.4 ..c

to

+->

.; 0.2 V)

0.0

0 25 50 75 100

Cover (%)

1.0 x ....1.- 0.0 0.00

50.0 0.00 x 0.8

59.4 0.47 Q)

-a 63.0 0.66 s::

69.4 0.81 ...... 0.6

75.4 0.88

80.4 1.00 ;:: 0.4 ...... 85.5 0.00 ..c

to 100.0 0.00 +->

...... 0 2. V)

0.0

0 25 50 75 100

Temperature (oF)

Figure 6. (concluded).

47
Coordinates

x

0.00

0.16

0.33

0.49

0.66

1. 31

100.00

.s:

0.0

0.7

1.0

1.0

0.7

0.0

0.0

1. 0+-..........__~............JL........o -+

x 0.8

Q)

"'0

...... 0 6

>, •

+.>

.r-

;.: 0.4 ..c

ttl

+.> 0; 0.2

Vl

o.0 +-....-----..--,r---'~--__t_

012

Velocity (ft/sec)

5 10

Depth (ft)

1.0

0.8

"'0

......

>, 0.6 +.>

or0.4 ttl

+.>

0.2

0.0

0

x .x:

0.0 0.0

0.5 0.0

2.3 1.0

3.3 1.0

9.8 0.5

16.4 0.0

100.0 0.0

x .s:

0.0 1.0

100.0 1.0

Based on assumption that all substrate

types are suitable.

1.0+----------+

x 0.8

Q)

"'0

...... 0.6

or-

;.: 0.4 ..c

ttl

+.>

'r- 0.2 :::::l

Vl

0.0-+----------+

Substrate

Figure 7. SI curves for white sucker juvenile velocity, depth,

substrate, cover, and temperature.

48
Coordinates 1.0

x -L

0.0 0.1 x 0.8

40.0 1.0 Q)

-0

75.0 1.0 s::

...... 0.6 100.0 0.5 >,

+>......

r-

...... 0.4 ..c

I'C

+>

.; 0.2

VI

0.0

a 25 50 75 100

Cover (%)

1.0 x -L

0.0 0.0

33.8 0.0 0.8

57.2 0.8 -0

66.2 1.0 s::

...... 0.6 75.2 1.0 >,

93.2 0.0 +>

100.0 0.0 0.4 ..c

I'C

+>

.; 0.2

VI

0.0

a 25 50 75 lOa

Temperature (0 F)

Figure 7. (concluded).

49
Coordinates 1.0

x .s..

0.00 0.0 x 0.8 0.16 0.7 OJ

-0 0.33 1.0 t:

0.49 1.0 ...... 0.6

>, 0.66 0.7 +->

'r- 1. 31 0.0 :;: 0.4

100.00 0.0 ..0

co

+->

.; 0.2 V)

0.0

0 1 2

Velocity (ft/sec)

1.0 x .s..

0.0 0.0

0.5 0.0 x 0.8 OJ 2.3 1.0 -0

t: 3.3 1.0 ......

9.8 0.5 >, 0.6

+-> 16.4 0.0 ......

100.0 0.0 :;: 0.4 ..0

co

+->

.; 0.2 V)

0.0

0 5 10

Depth (ft)

1.0

x .x:

0.0 1.0

x 0.8 100.0 1.0 OJ

-0

t: Based on assumption that all substrate ...... 0.6 Itypes are suitable. >,

+->

'rr-- 0.4 I- or-

..0

co

+->

.; 0.2 V)

0.0

Substrate

Figure 8. S1 curves for white sucker adult velocity, depth,

substrate, cover, and temperature.

50
Coordinates 1.0

x ....L

0.0 O. 1 0.8

40.0 1.0 -0

s::: 75.0 1.0 ...... 0.6 100.0 0.5 c-,

....

:;: 0.4

.0

ttl

.; 0.2

VI

0.0

0 25 50 75 100

Cover (%)

x 1.0 ....L 0.0 0.0

33.8 0.0 x 0.8 57.2 0.8 Q)

66.2 1.0 -0

s:::

75.2 1.0 ...... 0.6

c-, 93.2 0.0 .... 100.0 0.0 .-.... 0.4

.0

ttl

.~ 0.2 ::::l

VI

0.0

0 25 50 75 100

Temperature (oF)

Figure 8. (concluded).

51
SI curves for spawning (Fig. 4) were taken from the HSI model section

(Vs, V7 , Va, V12 ) . Assumptions and sources used in developing the curves are

in Table 1.

Egg incubation. For IFIM analyses of white sucker egg incubation habitat,

use curves for the time period from the beginning of spawning to 14 days

beyond the end of spawning. All SI curves for egg incubation (Fig. 5) were

taken from the HSI model section (V7 , Va, V12 ) except for the temperature

curve, which was taken from McCormick et al. (1977). See Table 1 for assumptions and information sources.

Fry. For IFIM analyses of white sucker fry habitat, curves should be

used for the time period beginning with the end of spawning, and ending approximately 2 months after spawning, at which time fry become juveniles (at lengths

of 0.7 to 0.9 inches, when their mouths become ventral). Very little information was found concerning fry habitat requirements. The SI curve for fry

depth (Fig. 6) was derived from observations of fry inhabiting the upper

6 inches of the water column (Stewart 1926), and the assumption that a maximum

depth does not ex i st. The SI curve for fry vel oci ty was based entirely on

professional guesswork, and the assumption that free-swimming fry can tolerate

only the lowest of velocities because of their small size. The SI curve for

fry substrate resulted from the assumption that substrate type is unimportant

to fry after their emergence from the gravel. The SI curve for fry cover was

taken from the HSI model section (V9 ), and the assumption that the cover

requirements for fry are the same as for juveniles and adults. The SI curve

for fry temperature was taken from McCormick et al. (1977).

Juvenile. For IFIM analyses of white sucker juvenile habitat, curves

should be used for individuals 1.0 to 9.9 inches in length, or from age two

months to age at sexual maturity (usually ages III to VIII; Carlander 1969).

SI curves were taken from the HSI model section (V4 , V9 , V1 3 , V1 6 ) , except for

the substrate curve. Juveniles and adults have been observed over all forms

of substrate ranging from sludge to rock (Thompson and Hunt 1930; Shurrager

1932). See Table 1 for all other assumptions and information sources.

Adult. For IFIM analyses of white sucker adult habitat, all curves are

the same as for juveniles, and assumptions are outlined in Table 1. Adults

are considered to be sexually mature at lengths 10 inches.

REFERENCES

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

for reservoirs based on standing crop of fish. Natl. Reservoir Res.

Prog. Unpubl. Rept. to U.S. Fish Wildl. Serv., Habitat Eval. Proc. Group,

Ft. Collins, CO. 120 pp.

Beamish, R. J. 1972. Lethal pH for the white suckers, Catostomus commersonii

(Lacepede). Trans. Am. Fish. Soc. 101(2):355-358.

52
1973. Determination of age and growth of populations of white

sucker (Catostomus commersoni) exhibiting a wide range in size at

maturity. J. Fish. Res. Board Can. 30(5):607-616.

. 1974. Growth and survival of white sucker (Catostomus

-----c-o-mm-e-r-s-onii) in acidified lake. J. Fish. Res. Board Can. 31(1):49-54.

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-82/16. 248 pp.

Brett, J. R. 1944. Some lethal temperature relations of Algonquin Park

fishes. Publ. Ontario Fish. Res. Lab. 63:1-49.

Campbe 11, R. S.

( Lacepede) ,

48 pp.

1935. A study of the common sucker, Catostomus commersoni

of Waskesiu Lake. M.A. Thesis, Univ. Sask., Saskatoon.

Carlander, K. D. 1969. Handbook of freshwater fishery biology. Vol. 1.

Life history data on freshwater fishes of the United States and Canada,

exclusive of the Perciformes. Iowa State Univ. Press, Ames, IA. 752 pp .

Cummins, K. W. 1962. An evaluation of some techniques for the collection and

analysis of benthic samples with special emphasis on lotic waters. Am.

Midl. Nat. 67(2):477-504.

Cummins, K. W., and G. H. Lauff. 1969.

size on the microdistribtion of

34: 145-181.

The influence of substrate particle

stream macrobenthos. Hydrobiologia

Curry, K. D. 1979.

reproduction.

Use of a Wabash River tributary for sucker (Catostomidae)

Ph.D. Dissertation, Purdue Univ., Lafayette, IN. 96 pp.

Dence, W. A. 1948. Life history, ecology, and habits of the dwarf sucker,

Catostomus commersonnii utawana Mather, at the Huntington Wildlife

Station. Roosevelt Wildl. Bull. 8(4):81-150.

Dunson, W. A., and D. R. Martin. 1973. Survival of brook trout in a bogderived acidity gradient. Ecology 54(6):1370-1376.

European Inland Fisheries Advisory Commission. Working Party on Water Quality

Criteri a for European Freshwater Fish. 1969. Report of extreme pH

values and inland fisheries. Water Res. 3(8):593-611.

Forbes, S. A., and R. E. Richardson. 1920. The fishes of Illinois. Ill.

Nat. Hist. Surv. pp. 85-86.

Fuiman, L. A. 1978. Descriptions and comparisons of northeastern catostomid

fish larvae. M.S. Thesis, Cornell Univ., Ithaca, NY. 110 pp.

53
Geen, G. H., T. G. Northcote, G. F. Hartman, and C. C. Lindsey. 1966. Life

histories of two species of catostomid fishes in Sixteenmile Lake, British

Columbia, with particular reference to inlet stream spawning. J. Fish.

Res. Board Can. 23(11):1761-1788.

Hayes, M. L. 1956. Life history studies of two species of suckers in Shadow

Mountain Reservoir, Grand County, Colorado. M.S. Thesis, Colorado A&M

College, Ft. Collins. 126 pp.

Hocutt, C. H., and J. R. Stauffer. 1975. Influence of gradient on the distribution of fishes in Conowingo Creek, Maryland and Pennsylvania.

Chesapeake Sci. 16(2):143-147.

Horak, D. L., and H. A. Tanner. 1964. The use of vertical gill nets in

studying fish depth distribution, Horsetooth Reservoir, Colorado. Trans.

Am. Fish. Soc. 93(2):137-145.

Krieger, D. A. 1980. Life histories of catostomids in Twin Lakes, Colorado,

in relation to a pumped-storage powerplant. M.S. Thesis, Colorado State

Univ., Ft. Collins. 116 pp.

La 1ancette, L. M. 1977. Feedi ng in white suckers (Catostomus commersoni)

from Gamelin Lake, Quebec, over a twelve month period. Naturaliste

Canadien 104(4):369-376.

Marcy, B. C., Jr. 1976. Planktonic fish eggs and larvae of the Lower

Connecticut River and the effects of the Connecticut Yankee Plant including entrainment. Pages 115-139 in D. Merriman and L. M. Thorpe, eds.

The Connecticut River ecological Study, the impact of a nuclear power

plant. Am. Fish. Soc. Monogr. 1. 252 pp.

McConnell, W. J., E. P. Bergersen, and K. L. Williamson. 1982. Habitat

suitability index models: A low effort system for planned coolwater and

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

McCormick, J. H., B. R. Jones, and K. E. F. Hokanson. 1977. White sucker

(Catostomus commersoni) embryo development, and early growth and survival

at different temperatures. J. Fish Res. Board Can. 34(7):1019-1025.

Milhous, R. T. Unpub. (1982). Working paper on the application of the

Physical Habitat Simulation System to water management - the use of the

PHABSIM system for incubation-spawning analysis. U.S. Fish Wildl. Servo

21 pp.

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

Physical Habitat Simulation System. Instream Flow Information Paper 11.

U.S. Fish Wildl. Servo FWS/OBS-8l/43. 273 pp.

Minckley, W. L. 1963. The ecology of a spring stream, Doe Run, Meade Co.,

Kentucky. Wildl. Monogr. 11:3-124.

54
Muth, R. T. 1983. Personal communication. Fish Wildl. Dept., Colo. State

Univ., Ft. Collins. Phone conversation, October 20.

Nelson, J. S. 1968. Hybridization and isolating mechanisms between Catostomus

commersoni and C. macrocheilus (Pisces:Catostomidae). J. Fish. Res.

Board Can. 25(1):101-150.

Nurnberger, P. K. 1928. A list of the plant and animal food of some fishes

of Jay Cooke Park. Trans. Am. Fish. Soc. 58:175-177.

Olson, D. E. 1963. Role of the white sucker in Minnesota waters. Proc.

Minnesota Acad. Sci. 31(1):63-73.

Pflieger, W. L. 1971. A distributional study of Missouri fishes. Mus. Nat.

Hist., Univ. Kansas, Publ. 20(3):225-570.

1975. The fishes of Missouri. Missouri Dept. Conserv.,

Jefferson City. 343 pp.

Propst, D. L. 1982a. Performance of creek chub and whlte sucker habi tat

models in central Colorado. Unpubl. Rpt. to U.S. Fish Wildl. Serv.,

Habitat Eval. Proc. Group, Ft. Collins, CO. 120 pp.

. 1982b. Warmwater fishes of the Platte River basin, Colorado; -----:-::------,-,---:- distribution, ecology, and community dynamics. Ph.D. Dissertation,

Colorado State Univ., Ft. Collins. 284 pp.

Raney, E. C. 1943. Unusual spawning habitat for the common white sucker

Catostomus ~. commersonii. Copeia (1943) 4:256.

Raney, E. C., and D. A. Webster. 1942. The spring migration of the common

white sucker, Catostomus c. commersonnii (Lacepede), in Skaneateles Lake

Inlet, New York. Copeia 1942(3):139-148.

Reighard, J. E. 1913. An ecological reconnaissance of the fishes of Douglas

Lake, Cheboygan County, Michigan, in midsummer. Bull. U.S. Bur. Fish.

XXXIII:215-249.

Reutter, J. M., and C. E. Herdendorf.

power plant: predicted effects

76(1) : 39-45.

1976. Thermal discharge from a nuclear

on Lake Erie fish. Ohio J. Sci.

Reynolds, W. W., and M. E. Casterlin. 1978. Behavioral thermoregulation and

diel activity in white sucker (Catostomus commersoni). Compo Biochem.

Physiol. A. Compo Physiol. 59(3):261-262.

Scherer, R. C. 1965. Dynamics of stream populations of the white sucker,

Catostomus commersoni Lacepede. Ph. D. Di ssertation. Pennsyl vani a State

Univ., University Park. 53 pp.

55
Schneberger, E.

management.

1977. The white sucker, its life history, ecology, and

Dept. Nat. Res., Madision, WI. 18 pp.

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

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

Shurrager, S. 1932. An ecological study of the fishes of the Hocking River.

Ohio Biol. Survey Bull. 28; 5(5):377-401.

Siefert, R. E. 1972. The first food of larval yellow perch, white sucker,

bluegill, emerald shiner, and rainbow smelt. Trans. Am. Fish. Soc.

101:219-225.

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.

Spri nger-Verl a~ NY.

Spoor, W. A. 1938. Age and growth of the sucker, Catostomus commersoni

(Lacepede), in Muskellunge Lake, Vilas County, Wisconsin. Trans. Wisc.

Acad. Sci. Art and Letters 31:457-505.

Stewart, N. H. 1926. Development, growth, and food habits of the white

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42:147-184.

Symons, P. E. K. 1976. Behavior and growth of juvenile Atlantic salmon

(Salmo salar) and three competitors at two stream velocities. J. Fish.

Res. Board Can. 33(2):2766-2773.

Thompson, D. H., and F. D. Hunt. 1930. The fishes of Champaign County. A

study of the di stri buti on and abundance of fi shes in sma 11 streams.

Illinois Div. Nat. Hist. Survey Bull., Vol. 19.71 pp.

Trojnar, J. R. 1977. Egg and larval survival of white sucker (Catostomus

commersoni) at low pH. J. Fish. Res. Board Can. 34(2):262-266.

Walton, B. D. 1980. The reproductive biology, early life history and growth

of white suckers, Catostomus commersoni, and longnose suckers, C.

catostomus, in the Wi 11 ow Creek-Chai n Lakes System, Alberta. Alberta

Dept. Energy Nat. Resour. Fish Res. Rep. 23.

Werner, R. G. 1979. Homing mechanism of spawning white suckers in Wolf Lake,

New York. New York Fish and Game J. 26(1):48-58.

56
50272 -101

REPORT DOCUMENTATION 110 REPORT NO.

PAGE FWS/ORS-A? /10 f\4

4. Title and Subtitle

Habitat suitability index models and instream flow suitability

urves: White sucker

3. Recipient"s Accession No.

5. Report Dete

September 1984

6.

7. Author(s)

Kathleen A. Twomey, Kathryn L.

9. Performing Organization Name and Address

Wyoming Cooperative Fishery

Research Unit and

University of Wyoming

Laramie, WY 80271

12. Sponsoring Organization Name and Address

15. Supplementary Notes

·11. Abstract (Limit: 200 words)

Williamson, and Patrick C. Nelson

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

8. Performing Organization Rept. No.

10. Project/Task/Work Unit No.

11. Contract(C) or Grant(G) No.

(C)

(G)

13. Type of Report & Period Covered

14.

The habitat suitability index (HSI models presented in this publication aid in

identifying important habitat variables for the white sucker (Catostomus commersoni),

a freshwater species found in lacustrine and riverine environments. Information

obtained from the research literature and expert reviews are synthesized into models

which present hypotheses of species/habitat relationships.

A brief discussion of suitability index (SI) curves as used in the Instream Flow

Incremental Methodology (IFIM), and a discussion of SI curves available for the IFIM

analysis of white sucker habitat are also included.

17. Document Analysis a. Descriptors

Fishes

Habi tabi 1i ty

Mathematical models

Aquatic biology

b. Identifiers/Open-Ended Terms

Whi te sucker

Catostomus commersoni

Habitat suitability

Instream Flow Incremental Methodology

c. COSATI Field/Group

Availability Statement

Release unlimited

19. Security Class (This Report)

Unclassified

20. Sec\lrity Class (1hJ$. Pale) UnCIaSS1Tlea

21. No. of Pages

56

22. Price

(See ANSI--Z39.18) See InstructIons on Reverse

*u. S. GOVERNMENT PRINTING OFFICE' '9.4-0-711·...1/••' • • • • 31

OPTIONAL FORM 272 (4-771

(Formerly NTI~35)

Department of Commerce
.. ....,-. .. ..

""

*Headquarters, 0lvI5 10n Of Biolog ical

services. Wasn,ngton. DC

)( Eastern Energy and Land Use Team

Leerown. WV

* Naloonal Coastal Ecosystems Team

Slide ll LA

• Western Energy aM LaM Use Team

FI ccu.ns. CO

• Locat ions of RegIonal Ollices

UGION 1

Rqiunlll Director

O.S. Fish lind Wildlife Service

Uoyd Five Hundred Building, Suite 1692

500N.E. Multnomah Street

Portland, Oregon 97232

REGION 4

Regional Director

U.S. Fish and Wildlife Service

Richard B. Russell Building

75 Spring Street, S.W.

Atlanta, Georgia 30303

,

,

I __r----

6!

,----- L, J_

1

, : ,--- I ,

I

REGION 2

Regional Director

U.S. Fish and Wildlife Service

P.O. Box 1306

Albuquerque, New Mexico 87103

REGION S

Regional Director

U.S. Fish and Wildlife Service

One Gateway Center

Newton Comer, Massachusetts 02158

REGION 7

Regional Director

U.S. Fish and Wildlife Service

10II E. Tudor Road

Anchorage, Alaska 99503

,."

REGION 3

Regional Director

U.S. Fish and Wildlife Service

Federal Building, Fort Snelling

Twin Cities, Minnesota 5SIII

REGION 6

Regional Director

U.S. Fish and Wildlife Service

P.O. Box 25486

Denver Federal Center

Denver, Colorado 80225
DEPARTMENT OF THE INTERIOR

u.s. FISH AND WILDLIFE SERVICE

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