A FOOD WEB ANALYSIS OF THE FISHERY IN

CHEQUAMEGON BAY, LAKE SUPERIOR

by

Jennifer A. Devine

A Thesis

submitted in partial fulfillment of the

requirements of the degree

MASTER OF SCIENCE

IN

NATURAL RESOURCES (FISHERIES)

College of Natural Resources

UNIVERSITY OF WISCONSIN

Stevens Point, Wisconsin

August2002 APPROVED BY THE GRADUATE COMMITTEE OF:

Dr. Michael J. Hansen, Committee Chairman Associate Professor of Fisheries College of Natural Resources

Dr. Tim Assistant Professor of Wildlife College of Natural Resources

r. Christopher Assistant Pr fessor of Biology and Water Resources College of Natural Resources

Stephen T. Schram Lake Superior Fisheries Supervisor Wisconsin Department of Natural Resources

11 ABSTRACT

I modeled prey consumption by coolwater and coldwater predators in

Chequamegon Bay, an important and productive sport fishery on the southwestern shore of Lake Superior, to determine the impact of predators on the fish community and to evaluate current fishery management actions. Coolwater predators included walleye

Stizostedion vitreum, northern pike Esox lucius, and smallmouth bass Micropterus dolomieu. Coldwater predators included lake trout Salvelinus namaycush, splake S. fontinalis x S. namaycush, burbot Lota Iota, lake whitefish Coregonus clupeaformis, and brown trout Salmo trutta. Stomach samples were collected throughout the year over a three-year period using a variety of gears. Temperature was monitored with temperature loggers. Length-weight relationships were estimated for all predator species, and growth in length and weight was estimated using von Bertalanffy models. Total instantaneous mortality was estimated from catch curves, natural mortality was estimated by Pauly's

equation, and fishing mortality was estimated by the difference between total and natural mortality. Abundance of coolwater predators was estimated by mark-recapture, while

abundance of coldwater predators was estimated by relating the catch of stocked lake trout to the catch of other coldwater species in the bay. Prey abundance was estimated by

yearly bottom trawl surveys. Diet changed annually for most predator species, depending

on prey availability, and predator species diets overlapped. Rainbow smelt Osmerus

mordax was the predominant prey of walleye, splake, lake whitefish, and lake trout.

Other fish species, such as ninespine stickleback Pungitius pungitius, sculpins, shiners

and trout perch Percopsis omiscomaycus, were the predominant prey of northern pike,

smallmouth bass, burbot and splake. Lake whitefish consumed the most prey per individual over their lifetime at 1327 pounds of prey, while other predators consumed between 48 and 251 pounds of prey per individual. Walleye consumed 10.3 million pounds of prey, which was 84% of the total prey consumption. Coolwater predators, which are permanent residents in the bay, consumed more prey than coldwater predators, which are only part-time residents in the bay; coolwater predators consumed 90% of the total prey consumption, while coldwater predators consumed only 10%. Simulated management actions resulted in small changes in predator consumption; prey consumption was reduced by only 10% by enacting minimum length limit changes for smallmouth bass and walleye, and eliminating stocking of walleye, brown trout and splake within Chequamegon Bay. Knowledge of forage requirements will be used to assist managers in developing a community based approach to management of the resource.

1V ACKNOWLEDGMENTS

I am indebted to many people for the completion of this thesis. I thank my major advisor, Mike Hansen, who provided much support, direction, and countless tissues. I thank my graduate committee, Dr. Tim Ginnett, Dr. Chris Hartleb, and Steve Schram for their comments and support. A special thanks to Steve Schram for the idea and support for this project. The Wisconsin Sea Grant Program, Wisconsin Department of Natural

Resources and Great Lakes Fishery Commission provided funding for this project. The

Wisconsin Department of Natural Resources, National Biological Service, U.S. Fish and

Wildlife Service, Bad River Natural Resources Department, Mark Ebener and Brian

Linton provided data for this project. I thank Mark Ebener, Chuck Madenjian, and Steve

Hewett for assistance and support. I thank the Lake Superior Technical Committee for allowing me to present my findings for review.

I especially thank Scott Hulse, Scott Sapper, Chris Zunker and Randy from the

Wisconsin Department of Natural Resources, Bayfield Office, for their assistance in data collection, support and infinite patience when working with me. It has been an honor and a pleasure to work with these individuals. I thank my fellow graduate students and friends, Brian Linton, Mark Rogers, Kevin Kapuscinski, Miriam Wyman, Stephanie

Sigmund, Felicia Fawcett, Melissa Goerlitz, Linda Duguid and Nicola Bissett for assistance and putting up with me in times of stress. Finally, I thank my family for support and encouragement.

V TABLE OF CONTENTS

ABSTRACT...... 111

ACKNOWLEDGEMENTS...... V

LIST OF TABLES ...... -...... Vlll

LIST OF FIGURES...... X

LIST OF APPENDICES...... Xll

INTRODUCTION...... 1 Fishery Management...... 3 Food Web Dynamics...... 5 Bioenergetics...... 6

METHODS.~...... 10 Study Site...... 10 Bioenergetics...... 12 Diet...... 16 Energy Density...... 18 Physiological Parameters...... 18 Thermal History...... 19 Maturity...... 19 Growth...... 20 Mortality ...... ~ ...... 21 Abundance...... 23 Prey Abundance ...... ·...... 26

RESULTS ...... 39 Diet ...... 39 Temperature ...... 42 Growth ...... 42 Mortality ...... , ...... 42 Abundance ...... 43 Prey Abundance...... 43 Annual Predator Consumption...... 43 Effect of Management Scenarios on Predator Consumption...... 45

DISCUSSION ...... ·...... 61 Predator Diets...... 61 Temperature...... 64 Prey Abundance...... 65 Consumption Estimates...... 67

VI MANAGEMENT IMPLICATIONS...... 71

REFERENCES...... 73

APPENDICES ...... ; 88

Vll LIST OF TABLES

Table 1. Fishing regulations for coolwater predators in Chequamegon Bay, Lake Superior, 2001...... 27

Table 2. Fishing regulations for coldwater predators in Chequamegon Bay, Lake Superior, 2001. Total bag limit for all trout is five, of which only 3 can be lake trout...... 27

Table 3. Length-weight relationships for prey species in Chequamegon Bay, Lake Superior, 2001.' All lengths are in millimeters. Relationships are log10 unless noted with a#, then relationships are loge. Emerald shiner length-weight relationship was used to estimate spottail shiner and mimic shiner weights, pumpkinseed was used to estimate bluegill and rockbass weights, round whitefish was used to estimate pygmy whitefish weights, and ninespine stickleback was used to estimate brook stickleback weights. Alewives length-weight relationship uses standard length, not total length. All conversions from standard length (SL) to total length (TL) were taken from Becker (1983) or approximated from members of the same family unless otherwise noted. Sample size and R2 values were noted for all species when data was collected from this study...... 28

Table 4. Energy density of the eight diet categories used in bioenergetics modeling of Chequamegon Bay, Lake Superior, 2001. Crustaceans includes only Mysis, Diporeia and Bythotrephes. Energy density is in joules per gram wet weight...... 29

Table 5. Physiological parameter values used in bioenergetics modeling of predatory fish in Chequamegon Bay, Lake Superior, 2001. Values are from Hanson et al. (1997). Lake trout values were used for brown trout and splake, while burbot values were taken from Rudstam et al. (1994). Burbot caloric density was taken from Johnson et al. (1999). Smallmouth bass egestion/excretion was changed from equation #1 to #3...... 30

Table 6. Day and age of spawning, and spawning losses incurred for all seven predator species in Chequamegon Bay, Lake Superior, 2001. Splake were assumed to have no natural reproduction...... 36

Table 7. Parameters used to estimate temperatures for December through April, and temperatures recorded from temperature stations May through November in Chequamegon Bay, Lake Superior, 2000. Temperatures measured at the 18m station were used to model lake trout, lake whitefish and burbot of ages 3+, 9m was used to model brown trout, splake and burbot of ages 1 and 2, and 5m was used to model northern pike. Walleye were modeled with temperatures from the 4m station for June­ October, 9m for December, and the remaining months were modeled with temperatures from 5m. Smallmouth bass of ages 1 and 2 were modeled with temperature from 2m depth for May-October, 5m for November, and 4m for the remainder of the year. Smallmouth bass of ages 3+ were modeled using temperatures from 4m depth May-June, 9m August-September, and 5m the remainder of the year...... 46 Table 8. Parameters from von Bertalanffy models and length-weight regression estimates for predator species in Chequamegon Bay, Lake Superior 1998-2001. Parameters Kand to from the size at age models for northern pike, brown trout and burbot were used to solve for Woo as the weight at age models for these species would not converge. Lake trout values were borrowed from another study (Linton 2002)...... 47

Table 9. Total instantaneous mortality (Z), conditional fishing mortality (Fm), and conditional natural mortality (Mn) rates of predators in Chequamegon Bay, Lake Superior, under the 2001 management regulations. To simulate the elimination of the 20- inch minimum length limit on walleye, fishing and natural mortality from age 9 was used. To simulate the enactement of an 18-inch minimum length limit on smallmouth bass, fishing mortality of0.0268 at age 9, 0.0674 at age 10, 0.0912 at age 11, 0.1144 at age 12, 0.1628 at age 13, and 0.2168 at age 14+ was used...... 48

Table 10. Abundance by age of predators in Chequamegon Bay, Lake Superior, during 2001 ...... 49

Table 11. Total average available prey biomass in Chequamegon Bay, Lake Superior, 1995-1998...... 51

Table 12. Gross conversion efficiency (gig) by age for each of the predator species in Chequamegon Bay, Lake Superior, 2001. Values are expressed as percentages...... 52

Table 13. Total prey consumption by each predator species in Chequamegon Bay, Lake Superior, in 2001...... 54

1V LIST OF FIGURES

Figure 1. Depth contour map of Chequamegon Bay, Lake Superior with major towns and spawning areas noted (figure redrawn from Fishing Hot Spots, Inc.). Depths are in feet.. ······································································································ 37

Figure 2. Number of walleye, brown trout and splake stocked annually in Chequamegon Bay, Lake Superior from 1979 through 2001. Walleye are numbers of fingerlings stocked by the WDNR along the Ashland shoreline and by Bad River Natural Resources Department in the Kakagon River...... 38

Figure 3. Proportion of diet oflake trout by age in Chequamegon Bay, Lake Superior, 1998-2001. Other fish includes small species offish ..... :...... 55

Figure 4. Proportion of diet of brown trout by age in Chequamegon Bay, Lake Superior, 1998-2001. Other fish includes salmonines and coregonines and small species of fish ...... ~...... 55

Figure 5. Proportion of diet of splake by age in Chequamegon Bay, Lake Superior, 1998- 2001. Other fish includes salmonines and coregonines and small species offish...... 56

Figure 6. Proportion of diet of burbot by age in Chequamegon Bay, Lake Superior, 1998- 2001. Other fish includes salmonines and coregonines and small species offish...... 56

Figure 7. Proportion of diet of lake whitefish by age in Chequamegon Bay, Lake Superior, 1998-2001. Other fish includes salmonines and coregonines and small species offish...... 57

Figure 8. Proportion of diet of walleye by age in Chequamegon Bay, Lake Superior, 1998-2001. Other fish includes salmonines and coregonines and small species of fish ...... 57

Figure 9. Proportion of diet of northern pike by age in Chequamegon Bay, Lake Superior, 1998-2001. Other fish includes salmonines and coregonines and small species of fish .. ·····································································································" 58

Figure 10. Proportion of diet of smallmouth bass by age in Chequamegon Bay, Lake Superior, 1998-2001. Other fish includes salmonines and coregonines and sniall species offish ...... -...... 58

Figure 11. Effect of eliminating stocking of splake (black) and brown trout (white) on annual prey consumption by these species in Chequamegon Bay, Lake Superior, 2001.. 59

Figure 12. Effect of simulated management scenarios on walleye annual prey consumption in Chequamegon Bay, Lake Superior, 2001...... 59

V Figure 13. Effect of changing the minimum length limit on smallmouth bass from 22- inches to 18-inches on annual prey consumption in Chequamegon Bay, Lake Superior, 2001...... 60 LIST OF APPENDICES

Appendix A. Lake trout diet information in Chequamegon Bay, Lake Superior, 1998- 2001 ..... ················································ ···································· ...... 88

Appendix B. Brown trout diet information in Chequamegon Bay, Lake Superior, 1998- 2001 ...... 92

Appendix C. Splake diet information in Chequamegon Bay, Lake Superior, 1998-2001 ··············································"···"··············"·································· 95

Appendix D. Burbot diet information in Chequamegon Bay, Lake Superior, 1998-2001 ...... 98

Appendix E. Lake whitefish diet information in Chequamegon Bay, Lake Superior, · 1998-2001 ...... 102

Appendix F. Walleye diet information in Chequamegon Bay, Lake Superior, 1998-2001 ...... 106

Appendix G. Northern pike diet information in Chequamegon Bay, Lake Superior, 1998- 2001 ································································································ 111

Appendix H. Smallmouth bass diet information in Chequamegon Bay, Lake Superior, 1998-2001 ...... 117

Appendix I. Growth, gametic production, P value, and gross conversion efficiency for predators in Chequamegon Bay, Lake Superior, 2001...... 122

Appendix J. Annual predator consumption by age in Chequamegon Bay, Lake Superior in 2001 ...... , ...... ·...... 132

Xl INTRODUCTION

Ecosystems are comprised of communities, populations and individual organisms, with each higher level consisting of elements from the lower level (Evans et al. 1987).

Dynamics at each level are controlled by abiotic and biotic factors interacting within and between levels (Jackson et al. 2001). In lentic systems, fish community structure is determined by abiotic factors, such as lake morphology, temperature and acidity, and biotic factors, such as competition and predator-prey interactions (Colby et al. 1987,

Jackson et al. 2001). Competition and predation usually regulate community composition (Persson and Diehl 1990) and production dynamics (Evans et al.1987).

Competition and predation play important roles in structuring fish communities.

Fish respond to competition with declining individual growth rates, changes in foraging, or habitat shifts (Haas and Schaeffer 1992, Hodgson and Kitchell 1987, Werner 1984).

Predators have the ability to suppress prey populations, thereby creating conditions where resources are limited and predator growth rates are reduced (Haas and Schaeffer 1992, Li et al. 1996a, 1996b). Competition for limited resources causes shifts in foraging as predators switch from feeding on energetically profitable prey that are in short supply to feeding on more numerous, less profitable prey (Hodgson and Kitchell 1987, Rand and

Stewart 1998). Predators often utilize different habitats when competing, which allows for exploration of different food sources (Werner 1984, Jackson et al. 2001 ). Predation may increase species diversity, regulate the size and behavior of the prey community, and promote growth of prey species (He and Kitchell 1990, Jackson et al. 2001). Systems without large piscivores may contain few fish species with stunted populations. 2

Piscivores may promote diversity and regulate the size of the prey community by preventing a few species from dominating the assemblage (Thorpe 1986, Evans et al.

1987, Jackson et al. 2001). Predation may reduce prey density, which can decrease interspecific competition between prey species, and thereby promote growth of prey species (Colby et al. 1987, He and Kitchell 1990). Fish community dynamics are controlled on spatial and temporal scales by the longest-lived species, usually predators, so manipulating predator density is one way to manage community structure. However, factors such as harvest and species introductions disrupt size and niche organization in the community (Evans et al. 1987).

Introducing or removing species can affect the way energy and biomass move through the community by causing shifts in native species abundance and localized extinctions (Evans and Loftus 1987). Predator and prey species may be introduced intentionally to enhance fishing. While the consequences of such actions are usually not foreseen, introductions may negatively affect fish communities (Evans and Loftus 1987).

Native species often compete for resources with introduced species or are affected by predation on eggs and young by introduced species (Stewart et al. 1981, Evans and

Loftus 1987). Several native fish species declined in abundance or became locally extinct when rainbow smelt Osmerus mordax and alewive Alosa psedoharengus were introduced and became abundant in Lake Michigan (Stewart et al. 1981 ). Rainbow smelt, documented in Lake Superior in 1937 (Van Oosten 1937), prey on the larvae and eggs of many species (MacCallum and Selgeby 1987). Rainbow smelt have been pinpointed as the cause of the lake herring Coregonus artedii collapse in Lake Superior (Colby et al.

1987), the impediment to lake herring recovery (MacCallum and Selgeby 1987), the 3 decline of coregonine species in Ontario lakes (Loftus and Hulsman 1986), and the decline of walleye Stizostedion vitreum in Lake Erie (Hartman 1972) and Wisconsin lakes (Colby et al. 1987).

Fishery Management

Interactions in the fish community can determine the success or failure of fishery management actions. Predator-prey interactions are of paramount importance when determining the success of management actions; too much demand on the prey population can cause long-term detrimental effects in the system. Prey populations, once depleted, are slow to recover (De Vries and Stein 1990), therefore, understanding fish community interactions and food web dynamics can lead to more effective management.

Management of fisheries entails controlling mortality by regulating fishing effort or harvest, increasing recruitment by stocking, adding new species, or manipulating habitat (Evans et al.1987, Nielsen 1999). Manipulations applied to enhance single species without consideration of the patterns of fish assemblages may cause unforeseen

C responses in the fish community. Predicting how the system will respond when moderately or lightly disturbed by management actions is difficult (Colby et al. 1987).

Species interactions in the fish community can cause management actions to have unpredictable, and sometimes undesirable effects. For example, raising minimum size limits on a predator species may not cause a noticeable increase in abundance or size of fish. In heavily fished, productive waters, minimum length limits may create a bottleneck

(the size composition shifts to a modal size just below the size limit); interspecific competition may then lead to stunting and reduced recruitment (Noble and Jones 1999, 4

Dunning et al. 1982). Harvest regulations may not have the desired effect on the targeted species if affected by density-dependent growth and mortality rates (Elliot 1984).

· Stocking a predator in a system may not cause an increase in numbers of that predator if stocked at a size where they are eaten by another species. Lake trout

Salvelinus namaycush stocked as fry, fingerlings, or eggs over a spawning reef could be subjected to high levels of predation by burbot Lota Iota (Edsall et al. 1993) and larger lake trout (Negus 1995). Smallmouth bass Micropterus dolomieu are often stocked into systems populated by walleye; however, smallmouth bass has been shown to be an important prey of walleye (Ryder and Kerr 1978). Walleye are stocked in many systems in Wisconsin at a size where they are piscivorous and can cannibalize younger, naturally recruited walleye, thereby suppressing recruitment of the next year class (Li et al. 1996a).

Esocids stocked at a small size may be susceptible to predation by largemouth bass

Micropterus salmoides (Stein et al. 1981) or other predators (Pierce et al. 1995).

Manipulating the habitat, such as through the installation of spawning reefs, may not increase the abundance of predators because the eggs and young are eaten by another species using the reef as habitat. Rehabilitation of lake trout in Lake Michigan may be less effective due to predation on lake trout eggs and young by slimy sculpins Cottus cognatus, which inhabit spawning reefs (Jones et al. 1995, Hudson et al. 1995); Alewife populations in Lake Michigan have been pinpointed as a possible cause for poor recruitment of lake trout, because alewives are known to prey upon lake trout eggs and larvae (Holey et al. 1995). 5

Food Web Dynamics

Traditional management actions aimed at single species may not be effective due to complex dynamics occurring in the system. Successful management, to be productive, must focus on the entire community and account for the dynamics within the community.

Food web dynamics of the Laurentian Great Lakes were altered by shifts in the forage base, intentional and accidental species introductions, declines in native predator and prey populations, predator stocking, spawning habitat destruction and increased commercial fishing pressure (Stewart et al. 1981, MacCallum and Selgeby 1987, Hansen et al. 1990, Ebener 1995, Negus 1995).

Lake Michigan food web dynamics changed dramatically after the introduction of alewives and rainbow smelt. Alewives and rainbow smelt increased in abundance, and caused the decline and extinction of several native fish species and reduced growth rates of other species (Stewart et al. 1981 ). In addition, the composition and size structure of the zooplankton community changed as alewives increased in abundance (Wells 1969).

With the introduction of salmonid predators, alewife abundance decreased while native prey fish abundance increased (Stewart et al. 1981 ). The success of top-down control of alewives by salmonines is attributed to high stocking densities, and because salmonines evolved to prey upon fish with behavior similar to alewives (Scott and Crossman 1973).

Introducing salmonines to control alewife abundance was such a success that the salmon fishery collapsed in the early 1980s when 80% of the chinook salmon Oncorhynchus tshawytscha population died from bacterial kidney disease, induced by stress from overstocking and malnourishment (Ebener 1995). 6

The Lake Superior fish community has changed dramatically since the decline of lake trout and lake herring and the invasion of sea lamprey Petromyzon marinus and rainbow smelt (Lawrie and Rahrer 1972, MacCallum and Selgeby 1987). The decline of native fishes through overexploitation allowed invasive species to become established, which then precipitated the population crash of lake trout and lake herring (Lawrie and

Rahrer 1972). Lake Superior is unique in that nutrient loadings were never excessive, as in the other Great Lakes (Jude and Leach 1999); however, Lake Superior's low productivity may also make it much more sensitive to overstocking and overfishing

(Negus 1995). Salmonid introductions and sea lamprey control assisted in rebuilding predator biomass, but too many predators may now be present. In addition, natural reproduction of many stocked salmonids has resulted in higher abundances than predicted

(MacCallum and Selgeby 1987). Most native fish populations are believed to be reverting to historical abundances (MacCallum and Selgeby 1987); however, introduced species are consuming much of the available prey biomass. Negus (1995) and Ebener

(1995) estimated predator consumption and concluded predatory demand exceeded prey biomass.

Bioenergetics

Knowledge of the trophic linkages between fish species in a community is important for understanding and modeling fish daily ration, growth, prey mortality and competition among predators (Breck 1993). Bioenergetics modeling is used to answer management and research questions concerning predator-prey dynamics and predator consumption, often where cultured or stocked fish are important membe.rs of the fish 7 community (Ney 1990, Hansen et al. 1993). Bioenergetics models can also be used to predict the effect of increased harvest of predators on prey availability (Hartman and

Margraf 1992, Ebener 1995, Negus 1995), examine the efficiency of top-down control of undesirable species (Mayo et al. 1998), describe variation in growth of individual species

(Madenjian and Carpenter 1991 ), and evaluate the roles of predation and competition in structuring fish communities (Stewart et al. 1981 ).

Bioenergetics has been used in Lake Superior to assess predator-prey dynamics and to evaluate stocking levels. Rainbow trout Salmo gairdneri, brown trout Salmo trutta, splake Salvelinus fontinalis x Salvelinus namaycush, lake trout, and coho

Oncorhynchus kisutch, chinook and Atlantic salmon Salmo salar are stocked in Lake

Superior to increase predator stocks (Negus 1995, Lawrie and Rahrer 1972). The total number of predators stocked in U.S. waters of Lake Superior from 1985 to the present

averaged 2.5 million fish annually (Ebener 1995). Lake trout stocking has been reduced recently due to reduced stocked fish survival and increased reproduction; however,

stocking of all other species has been either maintained or increased (Ebener 1995).

Negus (1995) found chinook salmon and lake trout consumed the greatest amount of prey

in Minnesota waters of Lake Superior; however, most predatory impact by chinook

salmon occurred soon after stocking. Negus (1995) concluded that manipulating stocking

levels of chinook salmon would allow for greater control over and restoration of prey

populations than changing lake trout stocking levels. Lake trout and siscowet Salvelinus

namaycush siscowet (a deep water form oflake trout) had the highest prey consumption

rates in U.S. waters of Lake Superior (Ebener 1995). Ebener (1995) found that 8 eliminating stocking of rainbow trout, chinook salmon, and coho salmon did not substantially increase prey fish abundance or biomass.

Bioenergetics modeling has been used to simulate the effects of a catch-and­ release fishing (no harvest) and various slot limit size regulations (limited harvest) on predator consumption rates. Maintaining a catch-and-release fishery resulted in high consumption rates and reduced size of predators (Perry et al.1995). Perry et al. (1995) found that increases in harvest rates and resultant increases in prey abundances could significantly increase growth of largemouth bass, especially of younger year classes.

Luecke et al. (1994) found that implementing a protected slot length limit of24-36 inches on lake trout resulted in the greatest number of trophy fish being harvested, lowest yield and highest consumption demand. Implementing protected slot length limits from 20-30 inches to 28-36 inches all resulted in increased consumption, although the 28-36 inch protected slot length limit exhibited the lowest consumptive demand (Luecke et al. 1994).

My goal was to determine if the abundance of prey fish could adequately sustain food web dynamics within Chequamegon Bay. My first objective was to quantify the impact of predators on the Chequamegon Bay fish community; I used bioenergetics to estimate annual consumption by cool- and coldwater predators. My second objective was to evaluate the effect of current fishery management actions on food web dynamics; I simulated the effect of different management actions on predator consumption. The management actions I simulated include the elimination of stocking of brown trout, splake and walleye within Chequamegon Bay, the elimination of the regulation allowing

anglers to keep one walleye over twenty inches, and the enaction of an eighteen inch minimum length limit on smallmouth bass. I varied fishing mortality rates in the 9 bioenergetics model to simulate different harvest levels of predators under the proposed regulation changes. To simulate the elimination of stocking, I eliminated stocked fish from abundance estimates. 10

METHODS

Study Site

Chequamegon Bay, located on the southwestern shore of Lake Superior, supports a diverse and highly productive recreational (angling) fishery that is of great economic importance to the surrounding communities. A limited tribal commercial (gillnetting) fishery for walleye exists in Chequamegon Bay, and is restricted to the Kakagon River and

Kakagon Sloughs (Rick Huber, Bad River Natural Resources Department, personal communication). Chequamegon Bay is 19 km long and 8 km wide, has a maximum depth of 23 m, an average depth of 8.6 m, and a surface area of 15,390 ha (Ragotzkie 1969). The south end and east side of the bay are less then 5 m deep; however, a deep-water channel that extends along the western side provides a cold water refuge for fish species (Figure 1).

The bay extends from the mouth of the Houghton Point to the tip of Long Island, a sand barrier that protects and separates the bay from the main body of the lake; however, strong winds from the northeast and southwest activate thermal currents between the bay and lake

(Ragotzkie 1969, Hoff and Bronte 1999). The bay stratifies thermally from June to

September with surface waters reaching as high as 23°C in summer; stratification begins much earlier in the bay then in the rest of the lake (Ragotzkie 1966, Ragotzkie 1969). Lake

Superior is highly oligotrophic, therefore, biomass production is low (Lawrie 1978); however, embayments are typically more mesotrophic than the lake (Ragotzkie 1969).

Five to ten percent of the volume of Chequamegon Bay is flushed daily (Ragotzkie 1969).

The fish community of Chequamegon Bay differs from the rest of Lake Superior because it contains both cool and cold-water fish species. The Wisconsin Department of 11

Natural Resources (WDNR) historically supplemented the fishery in the bay by stocking walleye, splake, brown trout, lake trout, chinook salmon, and brook trout Salvelinus fontinalis (Maccallum and Selgeby 1987). Currently, the WDNR stocks only splake, brown trout and walleye in the bay, while the Bad River Natural Resources Department stocks walleye within the Kakagon River (Figure 2).

Angling harvest of smallmouth bass, walleye, and northern pike Esox lucius has been restricted in Chequamegon Bay; lake trout, brown trout and splake harvest are subjected to regulations set for Lake Superior (Tables 1-2). Smallmouth bass

Micropterus dolomieui angling regulations were changed in 1994 after anglers expressed concern that the population was being overfished; the minimum length limit was set high

(;?:22 inches) to virtually close the fishery (S. Schram, WDNR, Bayfield, personal communication). W alieye harvest regulations were changed in 1992 to allow the walleye to recover from overfishing. The primary walleye spawning stock in Chequamegon Bay, supplemented by stocking, is located in Kakagon Sloughs, a tributary to the bay. In addition, walleyes are stocked along the Ashland shoreline to create a second self­ sustaining population; however, determination of the success of recruitment of this stock has been difficult because all populations mix in the bay during the non-spawning season

(S. Schram, WDNR, Bayfield, personal communication). After walleye abundance decreased, yellow perch Perea flavescens became abundant due to a lack of predation.

Yellow perch are now less abundant as a result of increased angling pressure, species introductions, and increased predation (S. Schram, WDNR, Bayfield, personal communication). Northern pike regulations were changed partially in response to a fear 12 of overexploitation and because regulations on northern pike throughout the state were under review.

Bioenergetics

Bioenergetics is a balanced energy equation in which the energy of consumed food is partitioned into growth (somatic and gonadal), total metabolism (respiration, active metabolism [swimming speed] and specific dynamic action [food digestion and assimilation]), and waste losses (egestion and excretion):

Consumption= Growth+ Total metabolism+ Waste

Knowledge of any three of the main components allows for estimation of the fourth by difference. Bioenergetics is often used to estimate consumption, given measurements of growth, because growth estimates are often easer to obtain in the field than accurate estimates of consumption (Hewett and Johnson 1992):

Growth= Consumption- Total metabolism - Waste

Solving the equation for growth is used to assess the effects of limiting factors such as temperature and prey availability on growth (Kitchell et al. 1977, Rice et al.

1983). Bioenergetics models are used to describe the energy budget for an average fish in the population, which is then expanded to the entire population by multiplying single fish dynamics with estimates of cohort survival and population size (Kitchell et al. 1977,

Hansen et al. 1993). 13

Consumption and respiration have an immediate control on growth, rates of which are determined by temperature and fish size (Kitchell et al. 1977). Consumption is the proportion of maximum daily ration, and is estimated from feeding experiments at optimum temperature for a particular fish species (Kitchell et al. 1977, Stewart et al.

1981, Ney 1993). The highest consumption rates are found in larvae and are often difficult to determine. Consumption is estimated using the equation:

where C = specific consumption rate ( g • g-1 • d-1 ), p = proportion of maximum ration

(ranging from Oto 1), T = water temperature,1(7) = water temperature dependence function, and Cmax = maximum specific feeding rate ( g • g-1 • d-1 ), which is an allometric function of weight:

C max =CAxWcB where CA = slope of the allometric function near the origin, CB = exponent of the allometric function, and W = fish weight.

The bioenergetics model is used to estimate relative feeding rate by calculating a p-value, which is the proportion of maximum consumption that is required to achieve observed growth (Ney 1993, Kitchell et al. 1994, Hanson et al. 1997). A p-value of 1.0 is unlikely because of variability in temperature, feeding rates, and prey availability. High p-values may indicate that the Cmax function is incorrect, individuals used to generate parameters in the Cmax function may be smaller, or feeding was at a lower temperature than individuals in the study (S. Hewett, WDNR, Madison, personal communication). P- 14 values can also be used as an indicator of prey fish abundance or success of predation by predators if seasonal water temperature and energy content of predator and prey do not vary with time or cohort (Hartman and Margraf 1992).

Total metabolic costs include respiration, specific dynamic action, and active metabolism. Respiration, the amount of energy used by the fish for routine metabolism, is affected by temperature, fish size, activity, and feeding level (Kitchell et al. 1977,

Hewett and Johnson 1992). Specific dynamic action is the cost of digestion, assimilation, and storage and is assumed to be a proportion of the consumption rate (Kitchell et al.

1977, Job ling 1985). Activity (swimming speed) is a constant, a function of body mass above a species-specific temperature cutoff, or a function of mass and temperature below a cutoff temperature (Hanson et al. 1997). Respiration is estimated by:

R = aW P x J(T)x Activity

where R = specific rate ofrespiration ( g · g-1 • d-1 ), W = fish weight, a= slope of the allometric weight function near the origin, /J= exponent of the allometric weight function, T = water temperature,.f{1) = the water temperature dependence function, and

Activity = the increment for active metabolism. Specific dynamic action is estimated by:

S = SDAx(C-F) where S = energy accounted for by specific dynamic action, SDA = proportion of assimilated energy lost to specific dynamic action (ranging from O to 1), C = specific feeding rate ( g • g-1 • d-1), and F= specific rate of egestion (g • g-1 • d-1 ). Waste products in the form of egestion (fecal waste) and excretion (nitrogenous waste) are 15 estimated by the model as a constant proportion of consumption, or as a function of water temperature, ration and food type (Stewart et al.1981, Ney 1993, Hanson et al. 1997).

Values are expressed as grams of waste per gram of fish per day.

Growth is apportioned into somatic and gonadal growth; gonadal growth occurs during somatic growth and losses occur during spawning. If the time span of the model run includes a spawning date for mature fish, the proportion of body mass lost can be defined over a time period (Hanson et al. 1997). The average proportion of mass lost for both sexes is estimated instead of differentiating between males and females.

The bioenergetics model is fairly reliable when predicting consumption based on measurements of growth (Stewart et al. 1983, Bartell et al. 1986, Rice and Cochran

1984). Kitchell et al. (1977) found that when predicting consumption from growth, the models are robust even when internal parameters are poorly known; errors are constrained by fitting the model to known growth. Internal parameters that have the greatest influence on model predictions when estimating consumption from measurements of growth are the temperature dependence functions of consumption and respiration and the allometric function parameters of consumption and respiration (Rice et al. 1983, Bartell et al. 1986). The parameters of the allometric functions result in small errors in consumption estimates when the model is fit to measured growth; however, errors are much larger when growth is used to predict consumption (Kitchell et al. 1977,

Stewart et al. 1983, Bartell et al. 1986). Errors in internal parameters cause small errors in predictions, whereas small errors in estimates of growth, population size, and diet lead to large errors in predictions (Kitchell et al. 1977, Lyons and Magnuson 1987). 16

The bioenergetics model estimates consumption for a group, or cohort, of similarly sized (aged) fish of the same species experiencing identical environmental conditions (Hanson et al. 1997). While individual fish may vary slightly, estimates represent the average individual. Data requirements for the bioenergetics model to estimate consumption of a cohort include diet, energy density of prey and predator, predator physiological parameters, thermal history of the fish, size or age at sexual maturity, and annual endpoints of growth. The net predatory impact of a population can then be predicted by combining cohorts, which requires estimates of predator mortality rates and abundance. Estimates of prey biomass are necessary to compare predicted consumption with available prey.

Diet

Predators were captured for this study during 1998-2001 using gillnets, fyke nets, trap nets, seining and angling. One to two hour gillnet lifts were used for sampling cool­ and coldwater fish habitats. Sites were selected based on habitat; areas selected included shoals, drop-offs, weed beds, areas with structure, and random sites along the deep-water channel. Nets were 30.5 meters long with mesh sizes ranging from 38-mm to 133-mm stretched-mesh in 13-mm increments, 210/2 monofilament, hung on the 1/2 basis; depths sampled ranged from 1.5m to 17.5 meters. A graded mesh survey was also conducted using nets with meshes ranging from 25-mm to 178-mm stretched-mesh in 13-mm increments, 210/2 monofilament, hung on the ½ basis, which are fished at four fixed locations every two years. Locations spanned the deep-water channel (4.5-21 meters).

Predators were collected along the Ashland shoreline using 4-foot fyke nets with I-inch or 3/8-inch stretch mesh, and 75 foot leads. Fyke nets were lifted every 24 hours. 17

Single-pot trap nets consisting of2-inch stretch mesh in the wings and heart and 1-inch stretch mesh in the pot were fished in water 3-8 meters deep along the Ashland shoreline and on shoals. Trap nets had 200-foot leads of2-inch stretch mesh, while some had the addition of75-feet of 1-inch stretch mesh for a total of275 feet. A 50-foot bag seine with 3/16-inch mesh was used in Kakagon and Sandcut sloughs, near Fish Creek, and

along the Ashland shoreline. A single 100-foot pull was made at each site along the shoreline. Angling samples were collected throughout the bay during the year.

Stomach samples were either processed immediately or contents were frozen and

processed within several months of collection. Prey species were identified to the lowest

practical taxon, usually species for fish and family for invertebrates, and wet weight of the contents was measured to the nearest 0.1 gram. All fish prey were measured to the

nearest 0.1-inch (total, standard or backbone length, as practical). Length was converted

from SL to TL using conversion factors from Becker (1983), Carlander (1977), or was

approximated using conversion factors for species in the same family. Weights of all fish

prey species were estimated from species-specific weight-length equations (Table 3).

Invertebrate prey were either counted or weighed, depending on family.

Prey items were divided into eight categories: rainbow smelt, yellow perch,

coregonines, salmonines, other fish, crayfish, other crustaceans (Diporeia, Mysis and

Bythotrephes), and other invertebrates; percentage of diet by weight for each predator age

class was estimated. All unknown fish were distributed according to the proportion of

identified fish in a predators diet. Because of the lack of adequate diet data over time and

across age classes, diet samples were grouped together if predators did not show a

definite diet shift with age. For young age classes not collected, diet information was 18 taken from the literature. Diet was broken down by simulation day for each of the age groupings, with day 1 set to June 1st because most naturally produced predators would have hatched by this time. Changes in diet were calculated by linear interpolation between simulation dates.

Energy Density

Prey caloric density was obtained from the literature (Table 4). Energy value for other fish was estimated as an average of energy values for the predominant species in this category (ninespine stickleback Pungitius pungitius, trout-perch Percopsis omiscomaycus, slimy sculpin, emerald shiner Notropis atherinoides, and spottail shiner

Notropis hudsonius). Rainbow smelt undergo an ontogenetic change in energy density

(Lantry and Stewart 1993), so I used an average of adult and juvenile rainbow smelt energy content because predators feed upon rainbow smelt of all sizes. Most predator caloric density estimates are included in the bioenergetics model, but burbot energy density was taken from Johnson et al. 1999. Energy density for splake and brown trout were borrowed from lake trout (Hanson et al. 1997).

Physiological Parameters

Predator physiological parameters for consumption, respiration, and egestion­ excretion were taken from Hanson et al. (1997) for all species except burbot (Table 5).

Burbot physiological parameters were taken from Rudstam et al. (1995). Lake trout physiological parameters were used to simulate splake and brown trout. 19

Thermal History

Temperature was recorded every four hours from early May through the end of

November in 2000 with two temperature loggers located at 5 and 9 meters in depth (inner bay deep). Temperature was also measured every two weeks at 4 meters in the inner bay

(inner bay shallow), and at 18 meters in the outer bay (outer bay deep), every meter from early June through November in 2000. Temperature for missing months (December -

April) was estimated by:

Temperature= (a* month)+ (b * month 2 )+ (c * month3 )

This equation creates a sine wave, such as that generated by temperature cycles.

December temperature was first set at 4° Celsius and was then estimated using the generated parameters. Temperature of each predator species was modeled according to the depth the species were captured in Chequamegon Bay.

Maturity

Reproductive losses through spawning are simulated at an age or size when a species is considered sexually mature; spawning losses began when most of the population was considered mature. Proportion of mature fish at a given length was estimated and values over years were averaged. A logistic maturity curve was then estimated numerically:

M-exp(a+bxage)/ - /I+exp(a+bxage) 20 where M = proportion mature at age, and a and b are parameters that shape the curve. If maturity data for a species was insufficient, age at maturity was obtained from the literature or WDNR unpublished data. Spawning losses were taken from the literature for each species; spawning losses are an average of male and female percentage of body weight lost due to spawning (Table 6).

Growth

_ Length was measured on all predators and weight was assessed whenever possible. Bony structures were collected for age estimation (Devries and Frie 1996).

Length-weight relationships were estimated for all species by using linear regression on log10-transformed data:

where Wt = weight, L1 = length, a= intercept, and /3 = slope.

Growth parameters of von Bertalanffy models were estimated numerically for length and weight of individual fish:

where Lt = length at age t, Loc, = asymptotic length for the population, K = rate at which Lt approaches Loc,, t = age and to = age at zero length. 21 where f3 is estimated from the length-weight regression equation and the other parameters are similar to those in the length-age model. Weight at age was used to generate annual endpoints of growth for each predator age class.

Mortality

Total instantaneous mortality was estimated from catch curves for each species.

For all predators except smallmouth bass, catch curves were constructed by multiplying estimated predator abundance with predator catch frequency. Mortality for smallmouth bass was estimated by following the 1987 year-class from 1991 through 1999. For walleye and northern pike, total instantaneous mortality was estimated by creating a catch curve from catch frequency multiplied by estimated population abundance. To estimate burbot mortality, catch frequency ofburbot captured in 1997 and 1999 in WI-I waters by the WDNR were applied to estimated burbot abundance in Chequamegon Bay. Catch curves for the remaining coldwater species were generated by multiplying estimated abundance of that species in the bay by catch frequency.

Linear regression of loge-transformed catch against age was used to estimate instantaneous total mortality (Z):

where Nt is numbers at age t, and No is number at age 0. Annual mortality rates (A) were then estimated from the equation:

A= 1-exp-z 22

For smallmouth bass, instantaneous fishing mortality was estimated from exploitation rates using the equation:

where Z = total instantaneous mortality rate ( estimated from catch curve), A = total annual mortality rate, µ = average exploitation rate (1/M ), R = number of recaptures in recreational and WDNR survey fisheries, and M= number of marked fish from mark­ recapture studies (see below).

For the remaining seven predator species, instantaneous fishing mortality was estimated by difference:

F=Z-M where M = instantaneous natural mortality rate, estimated from Pauly's equation:

log10 M = -0.0066-0.279log10 (L,,,)+ 0.6543log10 (K)+ 0.4634log10 (T)

where L00 and K are parameters from the von Bertalanffy growth model and T is average environmental temperature in Celsius measured in Chequamegon Bay. Lake trout natural and fishing mortality rates were borrowed from Linton (2002). Instantaneous fishing and natural mortality rates were converted into conditional fishing and natural mortality rates for use in the bioenergetics model.

Fishing mortality of predator species not fully vulnerable to the fishery was estimated by the equation: 23

where Fx is instantaneous fishing mortality of ages not fully vulnerable to the fishery, sx is the proportion of each age class vulnerable to the fishery [ranging from 0 (not vulnerable) to I (fully vulnerable)], and Fis fishing mortality. This was done for all predators except lake trout, which were borrowed from Linton (2002).

Abundance

Mature northern pike abundance was estimated by mark-recapture in 2001 using the Chapman modification of the Peterson estimator:

(M+I)* 1C+I) Abundance=--'----'---'-\:_-'--_ I R+I where M = number of marked fish, C = number of fish examined for marks, and R = number ofrecaptures. Four northern pike spawning areas were sampled with fyke nets:

Short Bridge, Washburn, Sandcut, and Kakagon sloughs (Figure I). Each area was sampled 15-19 net-nights except Sandcut, which was sampled 40 net nights. Northern pike were collected using 4-foot fyke nets with I-inch and 3/8-inch stretch mesh, and 75 foot leads. Nets were lifted every 24 hours. Fish were marked by partial removal of a fin and clips differed at each spawning area. Northern pike were recaptured in August using one hour gillnet sets ( described above).

Mature smallmouth bass abundance was estimated by mark-recapture in spring

2001_ during spawning in Sandcut and Kakagon Sloughs using the Chapman modification of the Peterson estimator. Smallmouth bass in Sandcut were captured using a 20-foot AC 24 electrofishing boat. Three boats with two people scooping per boat were used, and the boat was equipped with a 230-volt 3-phase generator operated at 80% duty cycle at 2-4 amperes. One night of sampling was used to mark the population, smallmouth bass were marked by clipping the top lobe of the caudal fin. The entire habitat of Sandcut was not sampled because some areas were too shallow for the boat, while others were too deep for the current to be effective. Smallmouth bass in Kakagon Sloughs were captured by hook and line. Smallmouth bass were marked in three consecutive days and were marked by clipping the bottom lobe of the caudal fin. Smallmouth bass were recaptured in

August of 2001 using one hour gillnet sets (described above).

One population of walleye reproduces in the Kakagon River in Chequamegon

Bay. Walleye are also stocked at two locations, in the Kakagon River and along the

Ashland shoreline. Abundance of the Kakagon Slough spawning walleye population was estimated in 1998 using the Chapman modification of the Peterson estimator. Walleye longer than 16 inches were captured in 4-5-inch stretch mesh monofilament gill nets, and were marked with an orange Floy tag and caudal fin hole punch. Walleye were recaptured with fyke nets. To estimate the number of stocked fingerlings surviving to

2001, WDNR and Bad River Natural Resources Department walleye stocking records

(1980-2001) were used with walleye survival rate.

Abundance of coldwater predators was estimated from the ratio between the catch of stocked lake trout to the catch of other coldwater predators in summer gillnet surveys in the bay:

Abundance= A(SLT)x c(cx(SLT) 25 where A (SLT) = number of lake trout stocked in Chequarnegon Bay during 1980-1995 that survived to 2001, C(CP) = catch of coldwater predator species in gillnet catches, and

C(SLT) = catch of stocked lake trout in gillnet catches. The total number of surviving lake trout stocked in Chequarnegon Bay during 1980-1995, the final year of stocking within the bay, was used where survival of stocked lake trout was found by catch curve analysis of wild and stocked lake trout (described above).

Abundance at age of stocked fish in 2001 was estimated by applying the estimated survival rate to the number of fingerlings stocked, except for brown trout age

2+. Abundance of stocked brown trout age 2+ was estimated by:

where A(NJ = estimated abundance of native brown trout at age t, C(N) = average catch of native brown trout in summer gillnet surveys (1994, 1998 and 2000), and C(S) = - average catch of stocked brown trout in WDNR summer gillnet surveys.

Abundance at age of all predators not fully vulnerable to the fishery was estimated by the equation:

where N,= abundance at age t, No= intercept from the instantaneous total mortality estimate of the population, and Z = instantaneous total mortality rate. Abundance at age for younger fish was found by back calculating from ages used to estimate total 26

instantaneous mortality, while abundance of fish older than those used to estimate

mortality was estimated by forward casting using the same equation.

Prey Abundance

Prey species populations were surveyed in the bay each year during 1995-1998

with bottom trawls (Buckner 1995, Hoff and Bronte 1999). Fish were sampled from mid­

July to early August at 38 fixed stations throughout Chequamegon Bay; one IO-minute

trawl tow was made per station (Hoff and Bronte 1999). A sub sample of each species of

fish was measured, and weights were obtained from length-weight relationships for these

fish. Weight per hectare was estimated by multiplying summed weights of each species

in each year by area swept. Weight per hectare was multiplied by the total area of

Chequamegon Bay (16,660 ha) to estimate the total weight of prey species each year.

Average biomass of each species was determined by averaging total weight during 1995-

1999.

Total prey biomass includes the amount of biomass existing at the time of the

· trawl survey plus the amount of prey produced during the course of the year. Production

was estimated with species-specific production to biomass ratios (P:B), which were

obtained from the literature (Kitchell et al. 2000). Estimated production was added to

total biomass to determine the amount of available prey in Chequamegon Bay over the

course of the year. 27

Table 1. Fishing regulations for coolwater predators in Chequamegon Bay, Lake Superior, 2001. Year SMB Walleye Northern Pike 2001 0bag Sbag 2 bag May 4-June 14 15-inch minimum 26-inch minimum 1 bag, 22-inch minimum 1 over 20" Continuous season June 15-March 1 Continuous season

Table 2. Fishing regulations for coldwater predators in Chequamegon Bay, Lake Superior, 2001. Total bag limit for all trout is five, of which only 3 can be lake trout.. Year Sp lake Lake Trout Brown Trout Lake Whitefish 2001 5 bag 3 bag 5 bag 25 pounds + 1· 15-inch 15-inch minimum, 15-inch more fish mm1mum Only 1 over 25-inches m1mmum No minimum Continuous Dec. 1st - Sept 30th Continuous Continuous season season season 28

Table 3. Length-weight relationships for prey species in Chequamegon Bay, Lake Superior, 2001. All lengths are in millimeters. Relationships are log10 unless noted with a #, then relationships are loge. Emerald shiner length-weight relationship was used to estimate spottail shiner and mimic shiner weights, pumpkinseed was used to estimate bluegill and rockbass weights, round whitefish was used to estimate pygmy whitefish weights, and ninespine stickleback was used to estimate brook stickleback weights. Alewives length-weight relationship uses standard length, not total length. All conversions from standard length (SL) to total length (TL) were taken from Becker (1983) or approximated from members of the same family unless otherwise noted. Sample size and R2 values were noted for all species when data was collected from this ~~- . Species Intercept Slope R n TL to SL Yellow percha -5.0811 3.0755 0.936 86 TL=l.20*SL Ruffea -4.429 2. 794 0.950 57 Pumpkinseedb -4.7724 2.9712 TL=l.26*SL Smelt -5.545 3.119 TL=l.27*SL Alewivesb -3.770 2.51 Ninespine Stickleback* -5.2953 3.0849 TL=l.14*SL Johnny Darteld -12.9211 3.2972 TL=l.20*SL Log Perch#d -11.8963 3.0533 TL=l.18*SL Trout-Perchb -5.0321 3.08 TL=l.24*SL Emerald Shine? -4.71 2.73 TL=l.27*SL Common Shinerb -5.56 3.29 TL=l.25*SL White sucke? -5.051 3.040 TL=l.18*SL b Longnose Suckerb -5.0685 3.0225 TL=l.21 *SL Brown Bullheadb -5.061 3.065 TL=l.20*SL Black Bullhead#d -10.8113 2.9242 TL=l.19*SL Lake Whitefisha -5.5687 3.1878 0.992 146 TL=l.18*SL b Lake Herring* -5.1803 3.0098 TL=l.19*SL b Round Whitefishb -5.276 3.223 TL=l.16*SL b Slimy Sculpinf -5.4947 3.3207 TL=l.19*SL Spoonhead Sculpinb -5.2837 3.1739 TL=l.20*SL *WDNR (unpublished data) a This study b Carlander ( 1977) c USGS, Ashland (unpublished data) a Becker (1983) f Selgeby (1988) 29

Table 4. Energy density of the eight diet categories used in bioenergetics modeling of Chequamegon Bay, Lake Superior, 2001. Crustaceans includes only Mysis, Diporeia and Bythotrephes. Energy density is in joules per gram wet weight. Prey Species Energy Density Citation Smelt Day 1 4054.5 Lantry and Stewart (1993) Day 31 4157.5 Day 61 4600.5 Day 93 4186 Day 122 4012 Day 274 4005.5 Day 365 4054.5 Yellow Perch 5700 Hartman and Margraf (1992) Coregonines 7500 Ebener (1995) Salmonines 5441 Negus (1995) Other fish 4679 Mayo (1997), Hartman and Margraf (1992) Crustaceans 4310 Stewart et al. (1983) Crayfish 3200 Yako et al. (2000) Other Inverts 3200 Ebener 1995, Negus (1995) Table 5. Physiological parameter values used in bioenergetics modeling of predatory fish in Chequamegon Bay, Lake Superior, 2001. Values are from Hanson et al. (1997). Lake trout values were used for brown trout and splake, while burbot values were taken from Rudstam et al. (1994). Burbot caloric density was taken from Johnson et al. (1999). Smallmouth bass egestion/excretion was changed from eguation # 1 to #3. Parameter Lake Trout Brown Trout Splake Whitefish Burbot Salvelinus Salmo trutta Salvelinus Core go nus Lota Iota namaycush namaycushX clupeaformis S. ontalius Consumption Equation 1 1 1 2 2 CA-weight dependent intercept of 0.0589 0.0589 0.0589 1.61 0.099 consumption CB-weight dependent coefficient of -0.307 -0.307 -0.307 -0.32 -0.195 consumption CQ-temperature dependent coefficient 0.1225 0.1225 0.1225 3.53 2.41 of consumption CTO-optimal temperature for * * * 16.8 13.7 l;.) consumption 0 CTM-maximum temperature for * * * 26 21 consumption CTL-temperature for K4 * * * * * CKl-proportion of maximum * * * * * consumption at CQ CK4-proportion of maximum * * * * * consumption at CTL

Respiration Equation set 1 1 1 1 2 RA-respiration intercept 0.00463 0.00463 0.00463 0.0018 0.008 RB-respiration coefficient -0.295 -0.295 -0.295 -0.12 -0.172 RQ-temperature function 0.059 0.059 0.059 0.047 1.88 R TO-swimming speed coefficient for 0.0232 0.0232 0.0232 0.025 21 optimum temperature Parameter Lake Trout Brown Trout S2lake Whitefish Burbot Respiration Cont. RTM-swimming speed coefficient for 0 0 0 0 24 maximum temperature I RTL-cutoff water temperature 11 11 11 0 * RK.1-weight dependent intercept for 1 1 1 7.23 * swimming speed RK.4-weight dependent coefficient for 0.05 0.05 0.05 0.025 * swimming speed ACT-swimming speed intercept 11.7 11.7 11.7 0 1.25 BACT-swimming speed coefficient 0.0405 0.0405 0.0405 0 * SDA-specific dynamic action 0.172 0.172 0.172 0.17 0.2

Egestion/Excretion Equation set 3 3 3 1 1 w FA-fecal loss intercept 0.212 0.212 0.212 0.25 0.17 ..... FB-fecal loss coefficient -0.222 -0.222 -0.222 * * PG-feeding level coefficient for fecal 0.631 0.631 0.631 * * loss DA-urinary loss intercept 0.0314 0.0314 0.0314 0.1 0.09 DB-urinary loss slope 0.58 0.58 0.58 * * DG-feeding level coefficient for urinary -0.299 -0.299 -0.299 * * loss Pinv-proportion of invertebrates 0.10 0.10 0.10 indigestable Pinv-proportion of crayfish indigestable 0.17 0.17 0.17 Pfish-proportion of fish indigestable 0.033 0.033 0.033 Parameter Lake Trout Brown Trout Splake Whitefish Burbot Predator Caloric Density Equation 2 2 2 2 1 Caloric density * * * * 5135 Alphl-intercept of first body-weight 5701 5701 5701 3956 * relationship Betal-coeffecient of first body-weight 3.0809 3.0809 3.0809 59 * relationship Cutoff-weigth at change in body-weight 1472 1472 1472 155 * equation Alpha2-intercept of second body-weight 9092 9092 9092 13060 * relation Beta2-coefficient of second body-weight 0.7786 0.7786 0.7786 0.004186 * relation

w N Table 5 cont. Parameter Walleye Walleye Northern Pike Smallmouth Bass Stizostedion vitreum Stizostedion vitreum Esox lucius Micropterus Adult (Age 2+) Juvenile (Age 1) dolomieui Consumption Equation 2 2 2 2 CA-weight dependent intercept of 0.25 0.45 0.2045 0.25 consumption CB-weight dependent coefficient of -0.27 -0.27 -0.18 -0.31 consumption CQ-temperature dependent coefficient 2.3 2.3 2.59 3.8 of consumption CTO-optimal temperature for 22 25 24 29 consumption CTM-maximum temperature for 28 28 34 36 consumption w CTL-temperature for K4 * * * * w CKl-proportion of maximum * * * * consumption at CQ CK4-proportion of maximum * * * * consumption at CTL

Respiration Equation set 2 2 1 2 RA-respiration intercept 0.0108 0.013827 0.00246 0.009 RB-respiration coefficient -0.2 -0.22 -0.18 -0.21 RQ-temperature function 2.1 2.1 0.055 3.3 R TO-swimming speed coefficient for 27 27 0.122 30 optimum temperature RTM-swimming speed coefficient for 32 32 * 37 maximum temperature RTL-cutoff water temperature * * * * Parameter Walle}'.e Walleie N orthem Pike Smallmouth Bass RK.1-weight dependent intercept for * * 1 * swimming speed RK.4-weight dependent coefficient for * * * * swimming speed ACT-swimming speed intercept 1 3 1 2 BACT-swimming speed coefficient * * * * SDA-specific dynamic action 0.172 0.1 0.14 0.16

Egestion/Excretion Equation set 1 1 1 3 FA-fecal loss intercept 0.158 0.25 0.2 0.104 FB-fecal loss coefficient -0.222 * * -0.222 PG-feeding level coefficient for fecal 0.631 * * 0.631 loss w ~ DA-urinary loss intercept 0.0253 0.05 0.07 0.068 DB-urinary loss slope 0.58 * * 0.58 DG-feeding level coefficient for urinary -0.299 * * -0.299 loss Pinv-proportion of invertebrates 0.1 indigestable Pinv-proportion of crayfish indigestable 0.17 P fish-proportion of fish indigestable 0.33

Predator Caloric Density Equation 1 1 1 1 Caloric density 4186 3349 3600 4186 Alphl-intercept of first body-weight * * * * relationship Betal-coeffecient of first body-weight * * * * relationship Parameter Walleye Walleye Northern Pike Smallmouth Bass Predator Caloric Density Cont. Cutoff-weigth at change in body-weight * * * * equation Alpha2-intercept of second body-weight * * * * relation Beta2-coefficient of second body-weight * * * * relation Table 6. Day and age of spawning, and spawning losses incurred for all seven predator species in Chequamegon Bay, Lake Superior, 2001. Splake were assumed to have no natural reproduction.

Species Model Day Age Spawning loss Source Lake trout 153 October 30 9+ 6.8% Stewart et al. (1983) Brown trout 137 October 16 3+ 18% Hayes et al. (2000) Lake whitefish 163 November 9 6+ 10% Rudstam et al. (1994) Burbot 260 February 13 3+ 11% Rudstam et al. (1995) Smallmouth bass 1 June 1 5+ 11% S. Schram, WDNR, Bayfield office, pers. comm. Walleye 332 April 25 6+ 10% Schram et al. (1992) N orthem pike 332 April 25 4+ 13% Diana and Mackay (1979) 37

67 73 f:; .. _ -( ))'·,~. . ),. ·'/ ·, J\ I (/ 61 ··-'•} A~ ( 'v·1.~ . I (s S 61 ;, ) (_ /24 · ) ~2 . ~- . J I '°' {j•·/"' )2·.--- _/" s J ~~ ;~7 0-/ /

) 27 ) ( ' I . I .J~/ 'i ~ I '\

and Shortbridge

Figure 1. Depth contour map of Chequamegon Bay, Lake Superior with major towns and spawning areas noted (figure redrawn from Fishing Hot Spots, Inc.). Depths are in feet. 38

6

5 ,--...

0 1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 Year

■ Walleye: Kakagon □ Walleye: Ashland Ii Browns lilli!ISplake

Figure 2. Number of walleye, brown trout and splake stocked ann,ually in Chequamegon Bay, Lake Superior from 1979 through 2001. Walleye are numbers of fingerlings stocked by the WDNR along the Ashland shoreline and by Bad River Natural Resources Department in the Kakagon River. 39

RESULTS

Diet

Lake trout of ages 3-7 ate a higher percentage of rainbow smelt than lake trout of age 8 and older, which ate a higher percentage of coregonines (Figure 3). Other fish species eaten by lake trout of ages 3 and older included ninespine stickleback and spottail shiners. Because no lake trout of ages 1 or 2 were collected, diet for these ages was taken from the literature (Negus 1995). Rainbow smelt were the predominant prey item throughout the year for lake trout of ages 3-7, except in June when other species were included in higher proportions in the diet. Diet of lake trout of age 8 and older changed throughout the year. Older lake trout fed mainly on rainbow smelt and coregonines except in winter, when other fish species were eaten in higher proportions, and in spring

(April-March), when predominant prey were coregonines and other fish species. Lake trout diet information is in Appendix A.

Brown trout fed predominantly on smelt and other fish species at all ages (Figure

4). Other fish species eaten included primarily ninespine stickleback and emerald shiners. Diet samples from all ages were combined because few samples were collected over a wide range of dates for all ages. Brown trout fed mainly on rainbow smelt, except in autumn (September-December), when other fish species were predominant prey items.

Brown trout diet information is in Appendix B.

Splake of ages 1-3 fed mainly on rainbow smelt and other fish species (Figure 5).

Other species of fish eaten in high proportions were ninespine stickleback and sculpins.

Because of small sample size of splake age 4 and older, diets of all ages were grouped 40 together. Diet of splake did not change annually. Splake fed predominantly on rainbow smelt throughout the year. Other fish species were eaten in higher proportions during

July to early August, whereas yellow perch were eaten in higher proportions in

November. Splake diet information is in Appendix C.

Burbot sample size was small and information on burbot of ages 1-5 was lacking

(Figure 6), so diets of burbot of ages 1 and 2 were taken from the literature (Fratt 1991 ).

Age 6 and older burbot ate primarily rainbow smelt and sculpins. All samples were combined to represent the diet ofburbot of age 3 and older. Burbot diet changed seasonally. Coregonines and rainbow smelt were predominant prey during spring and summer (March-July), whereas other fish species and coregonines were predominant prey during the rest of the year. Burbot diet information is in Appendix D.

Lake whitefish of ages 1-5 fed only on amphipods, Bythotrephes and other invertebrates, while lake whitefish of ages 6 and older fed predominantly on rainbow smelt (Figure 7). Other invertebrates and fish species eaten in high proportions included fingernail clams (Sphaeriidae ), spottail shiners, and troutperch. Diet of lake whitefish of ages 1-5 ate amphipods in high proportions during the summer, and other invertebrates the rest of the year. Lake whitefish of ages 6 and older ate predominantly rainbow smelt throughout the year, and ate other fish species in higher proportions during September­

October and February-March. Lake whitefish diet information is in Appendix E.

Walleye fed predominantly on rainbow smelt at all ages (Figure 8), whereas other fish species eaten in high proportions were ninespine sticklebacks and shiners. Diet of walleye did not change with age, so diet of all ages of walleyes were combined. Walleye 41

fed predominantly on rainbow smelt throughout the spring and summer, and switched to yellow perch, coregonines, salmonines, and other fish species in autumn and winter.

Walleye diet information is in Appendix F.

Diets of northern pike changed with age (Figure 9). Northern pike of ages 1-2 fed

predominantly on yellow perch, other fish species, and rainbow smelt, northern pike of

age 3 ate mainly other fish species, and northern pike of ages 4 and older ate primarily

coregonines, salmonines and rainbow smelt. Other fish species in high proportions in the

diet of northern pike of all ages were white suckers, trout perch, ruffe, and various

species of shiners. Diet of northern pike of ages 1-2 changed seasonally; rainbow smelt

was the predominant prey during July, yellow perch was the predominant prey during

September, and other fish species were predominant prey during the rest of the year. Age

3 northern pike fed on coregonines in early summer, rainbow smelt during summer (July

through mid-September), and other species of fish during the rest of the year. Northern

pike of ages 4 and older fed mainly on salmonines in early summer and other fish species

during the rest of the year. Rainbow smelt were eaten infrequently, but were the

predominant prey when eaten. Northern pike diet information is in Appendix G.

Smallmouth bass of ages 1-9 fed mainly on yellow perch and other fish species,

while smallmouth bass of age 10 and older fed mainly on rainbow smelt and other fish

species (Figure 10). Smallmouth bass of ages 1-9 ate a higher proportion of crayfish than

older bass. Smallmouth bass of all ages fed on similar species of other fish; however,

smallmouth bass of ages 1-9 fed on more sculpins than older age classes. Diet of all age

groups did not change seasonally, other fish species were the predominant prey

throughout the year. Smallmouth bass diet information is in Appendix H. 42

Temperature

Temperatures at all sites except the deepest site (18 meters) were highest in

August and low~st in January (Table 7). Temperature at the deepest site was highest in

July and October, and lowest in February; temperature in October was similar to temperatures at other stations. Estimated January temperature at the deepest sit~ was not used because the predicted temperature was too low (0.76 degrees C). Instead, temperature linearly increased from December to February.

Growth

Predator species showed a range of growth rates. Northern pike, brown trout and lake trout attained the largest asymptotic lengths and weights (Table 8). Asymptotic length and weight were similar for walleye and lake whitefish, and asymptotic length was similar for splake and burbot. Smallmouth bass attained the lowest asymptotic length, while splake had the lowest asymptotic weight. Size at age, weight at age, gamete production and p-value (proportion of maximum consumption to achieve observed growth) are included in Appendix I.

Mortality

Predator species showed a wide range of total instantaneous mortality rates.

Splake had the highest total instantaneous mortality rate, while lake whitefish had the lowest total instantaneous mortality rate (Table 9). Walleye, burbot and brown trout had similar total instantaneous mortality rates, and northern pike and lake trout had similar rates. Splake had the highest fishing mortality rate, while lake whitefish had the lowest. 43

Burbot and smallmouth bass had zero fishing mortality and similar natural mortality rates.

Abundance

Walleye and northern pike were the most abundant predators at 3. 7 mill.ion and

222,852 individuals of all ages respectively, while lake trout was the least abundant predator at 2,556 individuals of all ages. Estimated abundance at age is given for all species in Table 10. Coolwater predators (smallmouth bass, northern pike and walleye) make up 94% of total predator abundance in Chequamegon Bay, whereas coldwater predators (lake whitefish, lake trout, brown trout, splake and burbot) make up only 6% of total predator abundance.

Prey Abundance

The estimated total available prey biomass ranged from 20.4 to 86.9 million pounds from 1995 to 1998 and averaged 44,457,412 pounds (Table 11). Of the total available prey biomass of all sizes, white sucker was the most abundant prey, and composed 69% of the available prey biomass. Troutperch, yellow perch, lake whitefish, rainbow smelt, round whitefish, walleye and smallmouth bass were the next most abundant species; each species made up between 2 to 5% of the available prey biomass.·

Remaining species each made up less than 1% of the total available biomass.

Annual Predator Consumption

Lake whitefish consumed the most prey per individual over their lifetime, 1317 pounds of prey per predator, whereas other predators each consumed between 48 and 251 44 pounds of prey per predator over their lifetime (Appendix J). Smallmouth bass and splake had the lowest lifetime prey consumption per individual. Lifetime consumption per individual for northern pike, walleye and brown trout were similar, and lake trout and burbot experienced similar lifetime consumption per individual rates.

Predators exhibited a wide range of gross conversion efficiencies (Table 12).

Lake whitefish had the lowest gross conversion efficiency for all ages combined. Lake whitefish also had the lowest gross conversion efficiency at all ages except for splake, which had the lowest gross conversion efficiency at age for ages 8-11. Smallmouth bass had the highest gross conversion efficiency for any given age and all ages combined.

Peak gross conversion for all species occurred at the age of sexual maturation.

Total consumption of prey by all predators in Chequamegon Bay was 12.3 million pounds, of which 96% was fish (11.9 million pounds). Walleye consumed the most prey, approximately 10.3 million pounds per year and accounted for 84% of total predator consumption in Chequamegon Bay. Remaining predators consumed less than one million pounds of prey per predator population. Cool water predators (smallmouth bass, northern pike and walleye) consumed 90% of the total prey consumption, whereas coldwater predators (lake whitefish, lake trout, brown trout, splake, and burbot) consumed only 10% of total prey consumption.

Rainbow smelt were consumed more than any other prey item and were the predominant prey of walleye, splake, lake whitefish, and lake trout (Table 13).

Coolwater predators consumed 96% of all yellow perch consumption; though splake and brown trout also consumed yellow perch (17,178 and 429 pounds per year respectively). 45

Walleye, northern pike, splake, smallmouth bass and brown trout consumed 30% of the total available yellow perch biomass in Chequamegon Bay. Walleye were the primary predator of salmonines in Chequamegon Bay, and consumed 90% of total salmonines consumption.

Effect ofManagement Scenarios on Predator Consumption

Simulated management scenarios resulted in small changes in prey consumption; prey consumption was reduced by 10% by enacting minimum length limit changes on walleye and smallmouth bass, and eliminating stocking of brown trout, splake and walleye. Total prey consumption was reduced by 9.9% by eliminating the stocking of brown trout, splake and walleye within Chequamegon Bay. Eliminating the stocking of brown trout and splake in Chequamegon Bay reduced prey consumption by these species by 978,530 pounds (Figure 11 ). Prey consumption by walleyes was reduced by only 2% by eliminating stocking of walleye within Chequamegon Bay (Figure 12). Walleye prey consumption was reduced by 249,545 pounds (2%) by eliminating stocking and changing regulations to eliminate the 20-inch minimum length limit, while prey consumption by walleyes was reduced by 7,251 pounds (0.06%) by eliminating only the 20-inch minimum length limit. Enacting an 18-inch minimum length limit on smallmouth bass reduced prey consumption by 215 pounds (Figure 13). Table 7. Parameters used to estimate temperatures for December through April, and temperatures recorded from temperature stations May through November in Chequamegon Bay, Lake Superior, 2000. Temperatures measured at the 18m station were used to model lake trout, lake whitefish and burbot of ages 3+, 9m was used to model brown trout, splake and burbot of ages 1 and 2, and 5m was used to model northern pike. Walleye were modeled with temperatures from the 4m station for June-October, 9m for December, and the remaining months were modeled with temperatures from 5m. Smallmouth bass of ages 1 and 2 were modeled with temperature from 2m depth for May­ October, 5m for November, and 4m for the remainder of the year. Smallmouth bass of ages 3+ were modeled using temperatures from 4m depth May-June, 9m August-September, and 5m the remainder of the year. Day 4 Meters 2 Meters 5 Meters 9 Meters 18 Meters a 0.5155 1.0412 0.5951 -0.0901 b 0.6537 0.4742 0.4880 0.5908 C -0.0572 -0.0456 -0.0434 -0.0474 June 1 10.3 10.6 11.3 9.4 7.5 June 30 12.8 13.4 11.9 10.7 8.2

July 16.9 17.3 16.0 13.9 10.8 .j::. August 20.1 20.5 17.9 15.0 9.8 0\ September 14.9 14.9 14.8 14.1 8.4 October 12.6 12.5 11.3 10.8 10.5 November 2.6 2.6 5.0 5.1 3.7 December 1.5 1.9 2.4 2.1 January 1.1 1.5 1.0 February 3.2 3.6 2.8 1.8 March 5.9 6.2 5.0 3.8 April 8.9 8.8 7.4 6.1 May 10.3 10.8 9.4 6.2 Table 8. Parameters from von Bertalanffy models and length-weight regression estimates for predator species in Chequamegon Bay, Lake

Superior 1998-2001. Parameters K and t0 from the size at age models for northern pike, brown trout and burbot were used to solve for

W 00 as the weight at age models for these species would not converge. Lake trout values were borrowed from another study (Linton 2002). Parameter Walleye Northern Smallmouth Lake Brown Splake Lake Burbot Pike Bass Trout Trout Whitefish

L00 (mm) 702.86 1035.04 473.23 833.10 882.62 642.54 737.86 657.50 K 0.1351 0.1586 0.2804 0.149 0.1876 0.3683 0.1311 0.1775 to -1.8454 -1.7494 0.0438 -0.451 -1.3935 -0.9551 -0.8112 -0.2676 R2 0.817 0.691 0.913 0.930 0.677 0.677 0.862 0.584 n 1262 450 1034 273 36 104 169 304

W 00 (g) 3072.17 8588.50 1935.02 5335.20 7692.68 1870.37 3358.67 2322.84 K 0.1566 0.2069 0.1182 0.6054 0.1748 to -2.489 -1.0416 -2.4516 -0.2663 0.4241 .i::...... :i R2 0.693 0.845 0.525 0.620 0.821 n 155 1034 6207 62 121 a 3.1659 3.4347 2.9712 2.9966 2.9724 3.1547 3.1878 3.1122 p -5.4582 -6.4214 -4.7224 -5.0367 -4.8699 -5.442 -5.5687 -5.404 R2 0.960 0.941 0.981 0.918 0.906 0.882 0.992 0.908 n 307 469 315 8301 64 110 146 366 Table 9. Total instantaneous mortality (Z), conditional fishing mortality (Fm), and conditional natural mortality (Mn) rates of predators in Chequamegon Bay, Lake Superior, under the 2001 management regulations. To simulate the elimination of the 20-inch minimum length limit on walleye, fishing and natural mortality from age 9 was used. To simulate the enactement of an 18-inch minimum length limit on smallmouth bass, fishing mortality of0.0268 at age 9, 0.0674 at age 10, 0.0912 at age 11, 0.1144 at age 12, 0.1628 at age 13, and 0.2168 at age 14+ was used. Lake Whitefish Walleye Smallmouth Bass Burbot N orthem Pike Lake Trout Splake Brown Trout z 0.2787 0.6654 0.4276 0.5469 0.8930 0.8655 1.2190 0.5148 Age Fm Mn Fm Mn Fm Mn Fm Mn Fm Mn Fm Mn Fm Mn Fm Mn 1 0 0.1793 0 0.4860 0 0.3479 0 0.4213 0 0.5906 0.0081 0.1986 0.1616 0.6475 0 0.4024 2 0 0.1793 0 0.4860 0 0.3479 0 0.4213 0 0.5906 0.0081 0.1986 0.5241 0.3791 0.1614 0.2874 3 0 0.1793 0 0.4860 0 0.3479 0 0.4213 0 0.5906 0.0081 0.1986 0.5476 0.3468 0.2321 0.2218 4 0 0.1793 0.1277 0.4107 0 0.3479 0 0.4213 0 0.5411 0.0081 0.1986 0.5476 0.3468 0.2321 0.2218 5 0.0326 0.2177 0.2391 0.3244 0 0.3479 0 0.4213 0.2483 0.4553 0.0276 0.2164 0.5476 0.3468 0.2321 0.2218 6 0.0602 0.1947 0.2450 0.3191 0 0.3479 0 0.4213 0.3586 0.3617 0.0533 0.2354 0.5476 0.3468 0.2321 0.2218 7 0.0773 0.1798 0.3280 0.2351 0 0.3479 0 0.4213 0.4323 0.2788 0.0945 0.2723 0.5476 0.3468 0.2321 0.2218 ~ 8 0.0946 0.1642 0.3337 0.2285 0 0.3479 0 0.4213 0.4509 0.2544 0.1741 0.3022 0.5476 0.3468 0.2321 0.2218 9 0.0946 0.1642 0.3542 0.2041 0 0.3479 0 0.4213 0.4863 0.2031 0.2498 0.3154 0.5476 0.3468 0.2321 0.2218 10 0.0946 0.1642 0.3542 0.2041 0 0.3479 0 0.4213 0.4863 0.2031 0.3001 0.3296 0.5476 0.3468 0.2321 0.2218 11 0.0946 0.1642 0.3542 0.2041 0 0.3479 0 0.4213 0.4863 0.2031 0.3265 0.3387 0.5476 0.3468 12 0.0946 0.1642 0.3542 0.2041 0 0.3479 0 0.4213 0.4863 0.2031 0.3570 0.3457 13 0.0946 0.1642 0.1730 0.3 784 0 0.3479 0 0.4213 0.4863 0.2031 0.3488 0.3510 14 0.0946 0.1642 0.1730 0.3784 0 0.3479 0 0.4213 0.4863 0.2031 15+ 0.0946 0.1642 0.1730 0.3 784 0 0.3479 49

Table 10. Abundance by age of predators in Chequamegon Bay, Lake Superior, during 2001. Age Lake Whitefish Walleye Smallmouth Bass Burbot Native Stocked Kakagon .Ashland 1 4070 1770338 6683 27413 6110 3478 2 3080 910029 39636 0 3984 2022 3 2331 467794 0 3439 2598 1175 4 1764 240466 0 0 1694 683 5 1335 123610 0 7178 1104 397 6 1010 63541 0 3285 720 231 7 765 32663 0 0 470 134 8 579 16790 0 885 306 78 9 438 8631 6 246 200 45 10 331 4437 5 128 130 26 11 251 2281 3 80 85 15 12 190 1173 0 0 55 9 13 144 772 2 0 36 5 14 109 508 23 24 3 15 82 334 0 15 2 16 62 220 13 10 1 17 47 145 8 7 18 36 95 3 4 19 27 63 4 2 20 20 41 1 1 21 15 27 22 12 18 23 9 12 24 7 8 25 5 5 26 4 3 27 3 2 28 2 1 29 1 Total 16729 3644007 . 46335 42707 17554 8306 50

Table 10 Continued. Age Splake Northern Pike Lake Trout Brown Trout Stocked Native Stocked Native Stocked 1 93150 131613 1246 0 93 88503 2 22018 53885 524 0 55 23 3 2938 22061 221 0 33 14 4 3083 9032 93 0 20 8 5 173 3698 39 0 12 5 6 194 1514 16 0 7 3 7 0 620 7 167 4 2 8 23 254 3 144 3 1 9 9 104 1 53 2 1 10 3 43 1 27 1 11 1 17 11 12 7 2 13 3 2 14 1 15 Total 121591 222852 2151 406 230 88560 51

Table 11. Total average available prey biomass in Chequamegon Bay, Lake Superior, 1995-1998. Species Average Pounds Bluegill 536 Brook Stickleback 1,299 Brown Bullhead 62,335 Brown Trout 199,479 Burbot 304,231 Chinook Salmon 706 Coho Salmon 23,011 Emerald Shiner 73,111 Johnny Darter 86,797 Lake Herring 24,637 Lake Trout - native 75,111 Lake Trout - stocked 395,673 Lake Whitefish 2,363,473 Logperch 23,861 Longnose Sucker 428,564 Mimic Shiner 21,445 Ninespine Stickleback 276,199 Pygmy Whitefish 3,937 Rainbow Smelt 2,047,715 Rockbass 13,602 Round Whitefish 896,981 Ruffe 21,879 Shorthead Redhorse 280,527 Slimy Sculpin 30,856 Smallmouth Bass 1,444,660 Splake 52,006 Spoonhead Sculpin 19,226 Spottail Shiner 158,628 Troutperch 2,226,518 Walleye 921,331 White Sucker 30,548,744 Yell ow Perch 1,430,336 52

Table 12. Gross conversion efficiency (gig) by age for each of the predator species in Chequamegon Bay, Lake Superior, 2001. Values are expressed as percentages. Age Lake Whitefish Walleye Smallmouth bass Burbot Northern Pike Lake Trout 1 0.74 10.33 22.16 4.43 16.22 13.05 2 3.10 14.23 21.18 7.17 12.64 7.88 3 3.67 13.21 25.15 12.06 12.04 7.65 4 3.61 11.96 23.93 11.89 15.72 7.15 5 3.20 10.64 27.78 11.31 15.02 6.60 6 4.38 14.37 26.45 10.59 14.25 6.06 7 3.90 13.52 25.03 9.85 13.50 5.59 8 3.47 12.73 23.67 9.17 12.80 5.57 9 3.11 12.02 22.40 8.56 12.16 7.33 10 2.80 11.41 21.75 8.03 11.57 7.00 11 2.55 10.86 20.72 7.56 11.07 6.70 12 2.35 10.37 19.89 7.16 10.63 6.42 13 2.18 9.97 19.17 6.82 10.23 6.17 14 2.04 9.60 18.54 6.52 9.90 15 1.92 9.29 18.04 6.28 16 1.83 9.02 17.65 6.07 17 1.75 8.79 17.29 18 1.68 8.59 17.00 19 1.63 8.42 16.78 20 1.58 8.28 16.61 21 1.54 8.15 22 1.51 8.04 23 1.48 7.95 24 1.46 7.87 25 1.44 7.80 26 1.43 7.73 27 1.42 7.69 28 1.40 7.65 29 1.40 All Ages 1.89 9.48 20.21 8.03 12.05 6.73 Note: Calculations are based on year simulations. Length and weights refer to the start of the year. ·oametes shed are included in estimation of gross conversion efficiences. 53

Table 12 continued. Age Splake Brown Trout 1 9.33 12.32 2 12.99 9.63 3 10.66 12.58 4 7.29 12.38 5 4.53 11.99 6 2.65 11.52 7 11.08 8 0.84 10.68 9 0.47 10.30 10 0.26 9.97 11 0.14 All Ages 4.27 11.07 Table 13. Total prey consumption by each predator species in Chequamegon Bay, Lake Superior, in 2001. Species Walleye Northern Splake Brown Lake Smallmouth Burbot Lake Total Pike Trout Whitefish Bass Trout Crustaceans 97 0 2,326 0 20,293 20 2,885 1,893 25,622 Crayfish 229,794 8,794 0 0 0 5,339 73 0 244,000 Other Invertebrates 14,256 17,907 10,919 71,754 49,355 165 429 998 164,786 Rainbow Smelt 6,185,973 182,630 335,212 178,247 70,581 1,628 3,086 6,442 6,957,358 Yellow Perch 240,188 174,512 17,178 429 0 2,612 0 0 434,919 Coregonines 985,832 36,014 1,010 1,288 1,459 0 3,534 353 1,029,137 Salmonines 770,402 28,685 52,229 0 0 0 0 0 851,316 Other Fish 1,911,950 318,627 79,533 229,991 23,630 11,130 8,085 1,763 2,582,946 Total 10,338,492 767,169 498,408 481,710 165,318 20,895 18,093 11,449 12,290,084

Vl .+::,. 55

100% 90% 80% -Q) i5 70% 0 60% -C: 0 50% t 0 40% c...... 0 30% a.. 20% 10% 0% 2 3 4 5 6 7 8 9 10 11 12+ Age

■ Smelt □ Coregonines ~ Other Fish □ Invertebrates

Figure 3. Proportion of diet oflake trout by age in Chequamegon Bay, Lake Superior, 1998-2001. Other fish includes small species of fish.

100% 90% 80% Q) i5- 70% -0 60% C: 0 50% t 0 40% c.. 30% a..e 20% 10% 0% 2 3 4 5 6+ Age

■ Smelt □ Yellow Perch li'ilOther Fish II Crustaceans □ Invertebrates

Figure 4. Proportion of diet of brown trout by age in Chequamegon Bay, Lake Superior, 1998-2001. Other fish includes salmonines and coregonines and small species of fish. 56

100%

90% 80% Q) 0 70% -0 60% C 0 50% t 40% 0a. 0 L.. 30% a.. 20%

10%

0% 2 3 4 5. 6+ Age

■ Smelt □ Yellow Perch li:10ther Fish lllilCrustaceans □ Invertebrates Figure 5. Proportion of diet of splake by age in Chequamegon Bay, Lake Superior, 1998-. 2001. Other fish includes salmonines and coregonines and small species of fish.

100% 90% ..... 80% Q) 0 70% -0 60% C 0 50% t 0 40% a. e 30% a.. 20% 10% 0% 2 3 4 5 6 7 8 9 10 11 12 13 14 15+ Age

■ Smelt □ Yellow Perch ~ Other Fish II Crustaceans □ Invertebrates

Figure 6. Proportion of diet of burbot by age in Chequamegon Bay, Lake Superior, 1998- 2001. Other fish includes salmonines and coregonines and small species of fish. 57

100% ·•· / 90% I 80% -Q) Ii i5 70% I 0 60% - ••• C: 0 50% I [ I t I 0 40% C. L k 0 30% I ... I a.. 20% I

10% 1• I 0% I 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 Age

■ Smelt □ Yellow Perch l:\:10ther Fish liilll Crustaceans D Invertebrates

Figure 7. Proportion of diet of lake whitefish by age in Chequamegon Bay, Lake Superior, 1998-2001. Other fish includes salmonines and coregonines and small species of fish.

100% ... 90% I I 80% -Q) 70% .....0 0 60% C: 0 50% t 0 40% C. 0... 30% a.. 20% 10% 0% 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20+ Age

■ Smelt □ Yellow Perch kl Other Fish II Crustaceans D Invertebrates

Figure 8. Proportion of diet of walleye by age in Chequamegon Bay, Lake Superior, 1998-2001. Other fish includes salmonines and coregonines and small species of fish. 58

100% 90% ..... 80% Q) .....i5 70% 0 60% C: 0 50% :e 40% 0a. e 30% a. 20% 10% 0% 1 2 3 4 5 6 7 8+ Age

■ Smelt D Yellow Perch mOther Fish II Crustaceans □ Invertebrates

Figure 9. Proportion of diet of northern pike by age in Chequamegon Bay, Lake Superior, 1998-2001. Other fish includes salmonines and coregonines and small species of fish.

100% 90% ..... 80% Q) i5 70% 0 60% -C: 0 50% :e 40% a.0 0 30% L.. a. 20% 10% 0% 2 3 4 5 6 7 8 9 10 11 12 13+ Age

■ Smelt D Yellow Perch mOther Fish II Crustaceans D Invertebrates

Figure 10. Proportion of diet of smallmouth bass by age in Chequamegon Bay, Lake Superior, 1998-2001. Other fish includes salmonines and coregonines and small species offish. 59

0.5 'iii' u C a.6 0.4 C .Q ~ 0.3

C .Q ~ 0.2 :::, (/) C 0 o 0.1

a.f

Current management No stocking

Figure 11. Effect of eliminating stocking of splake (black) and brown trout (white) on annual prey consumption by these species in Chequamegon Bay, Lake Superior, 2001.

'iii' 12 u C :::, a.0 10 C g 8 ~ C 6 0 :;::; C. E :::, 4 (/) C 0 (.) 2 >, ...(I) a. 0 Current No 20" minimum No stocking, No stocking, no management length limit current length 20" minimum limits length limit

Figure 12. Effect of simulated management scenarios on walleye annual prey consumption in Chequamegon Bay, Lake Superior, 2001. 60

25 U) "O C: 5 20 Cl.. "O C: t1I g 15 .c !:::- c: f 10 E => "'C: 8 5 >, ~ Cl..

Current management 18" minimum length limit

Figure 13. Effect of changing the minimum length limit on smallmouth bass from 22- inches to 18-inches on annual prey consumption in Chequamegon Bay, Lake Superior, 2001. 61

DISCUSSION

Predator Diets

Diets of lake trout in this study were similar to other recent studies of Lake

Superior (Conner et al. 1993, Ebener 1995, Negus 1995, Gallihat 2000); however, seasonal trends were not similar and may reflect differences in prey availability between

Chequamegon Bay and the rest of Lake Superior. Historically, coregonine species, such as lake herring and deepwater ciscoes, were the preferred prey of lake trout (Dryer et al.

1965). However, with the decline of coregonine populations and the introduction of rainbow smelt into the Great Lakes, lake trout diets shifted to predominantly rffi:nbow smelt (Conner et al. 1993 ). The distributions of coregonines and rainbow smelt overlap in near-shore areas, and Conner et al. (1993) showed lake trout switched to eating progressively more coregonines and less rainbow smelt near-shore. I found that this dietary shift was only apparent with older lake trout in Chequamegon Bay, and was also reflected from older lake trout in western Lake Superior (Ebener 1995, Mason et al.

1998).

My results for brown trout and splake diets are similar to previous studies of brown trout and splake diets in Lake Superior (Ebener 1995, Conner et al. 1993); however, I found that brown trout ate fewer aquatic invertebrates in Chequamegon Bay than in Lake Superior. This may reflect inadequate sampling of brown trout within

Chequamegon Bay; important seasonal diet items may not have been included due to small sample size. Small prey fishes differ in the diet for both species between this study and previous studies (Ebener 1995, Conner et al. 1993); coolwater prey species were 62 included in higher proportions in this study, which is most likely a reflection of habitat and prey availability.

I found that burbot fed on similar prey species in Chequarnegon Bay as in western

Lake Superior, except less arnphipods and more coolwater species were included in burbot diets in Chequarnegon Bay (Bailey 1972, WDNR unpublished data). Mysis were a much more important diet item in the past (Bailey 1972). Seasonal trends differ between more recent studies and Bailey (1972), which indicates that foraging patterns may be changing. Bailey (1972) showed that burbot ate coregonines in large proportions in January and late summer, while more recent data (WDNR unpublished data) and my study show coregonines are one of the main diet items throughout the year. Coregonine populations are increasing in Lake Superior (MacCallurn and Selgeby 1987, S.Schrarn,

WDNR, Bayfield, personal communication), which may account for this difference. In

Green Bay, Lake Michigan, burbot fed on similar species and were shown to have similar seasonal trends as burbot in Chequarnegon Bay, except that burbot in Green Bay ate a larger proportion of alewives (Rudstarn et al. 1995); alewives are much more abundant in

Lake Michigan. In Green Bay, burbot, as in this study, ate a higher proportion of coolwater prey species, which indicates that burbot feed upon coolwater species if encountered.

I found that lake whitefish fed predominantly on rainbow smelt after the age of 6, which has not been documented elsewhere. Hoff et al. (1997) found that lake herring in the Apostle Islands region of Lake Superior preyed on rainbow smelt in winter, which suggests that planktivores are capable of eating fish. Competition or increased energy demands may be the cause of this unusual diet. Abundance of coregonine species is 63 increasing in Lake Superior (Maccallum and Selgeby 1987, S.Schram, WDNR, Bayfield, personal communication) and could be causing increased competition among young age classes. The diet shift may occur to reduce competition for limited prey at a time when lake whitefish energy demands are increasing due to sexual maturation. Lake whitefish become sexually mature at age 6 and may choose to feed on a more energetically profitable prey.

I found that diets of walleye in Chequamegon Bay included more species than was reported for walleye in western Lake Superior and the St. Louis River (Swenson

1977, Mayo 1997). Walleye in western Lake Superior fed exclusively on rainbow smelt, whereas walleye in Chequamegon Bay, although they fed predominantly on rainbow smelt, had a more varied diet, which reflects greater variety of prey species in

Chequamegon Bay. The high proportion of rainbow smelt in the diet of walleye in

Chequamegon Bay most likely reflects availability; rainbow smelt are highly available in

Chequamegon Bay (Heist and Swenson 1983, Buckner 1995). In contrast, walleye in the

St. Louis River did not feed on rainbow smelt in high proportion until after age 11.

Instead, yellow perch was an important prey for St. Louis River walleye, and made up approximately 15% of the diet of ages 2-10 (Mayo 1997). Yellow perch was not an important prey for Chequamegon Bay walleye except for a few age classes; when included, yellow perch made up 15-25% of the diet. Differences in diet between walleye in Chequamegon Bay and the St. Louis River may reflect differences in prey preferences, prey availability or predator-avoidance behavior. Walleye in Chequamegon Bay could be selecting for soft-rayed prey and avoiding spiny-rayed fishes, as has been shown in other studies (Hartman and Margraf 1992, Knight and Vondracek 1992). Rainbow smelt may 64 be more available in Chequamegon Bay; rainbow smelt use Chequamegon Bay as a nursery area (Hoff and Bronte 1999), which results in high densities of young rainbow smelt in the bay throughout the year and high influxes of mature rainbow smelt during the spring to spawn. Swenson (1977) found that walleye utilize pelagic prey during the summer, and rainbow smelt exhibit pelagic behavior when young (Lantry and Stewart

1993) or in turbid water (Heist and Swenson 1993). Yellow perch, unlike rainbow smelt, may have developed more effective predator-avoidance behavior due to co-evolving with walleye as a primary predator.

I found that northern pike and smallmouth bass fed on many of the same species in Chequamegon Bay as Mayo (1997) and Ogle et al. (1996) found in the St. Louis River, except that rainbow smelt was not a major prey of these species in the St. Louis River.

Crayfish was not a predominant prey for smallmouth bass in Chequamegon Bay (12% all ages combined), whereas crayfish are important prey for smallmouth bass in many other waters (Rabeni 1992, Weidel et al. 2000). Mayo (1997) also did not show crayfish as being a main diet item of smallmouth bass in the St. Louis River (17% all years combined). Smallmouth bass in Chequamegon Bay are feeding upon readily available prey that are more energetically profitable and less costly to handle than crayfish.

Temperature

Chequamegon Bay heated faster in the spring than the St. Louis River; however, average water temperatures in the St. Louis River were much higher after April (Mayo

1997). Chequamegon Bay is several degrees cooler than the St. Louis River because of regular mixing with Lake Superior. Warm surface waters are blown out of the bay and replaced with cold water, or warm water is displaced by cold water being forced into the 65 bay (Ragotzkie et al. 1969). Water temperature in Chequamegon Bay cooled faster in autumn than in Lake Superior. Negus (1995) and Ebener (1995) reported mean temperatures ranging from 4.4 to 7.0 C in November in Lake Superior, whereas in

Chequamegon Bay, water temperature was recorded as low as 2.6 C. Chequarnegon Bay showed a rapid decrease in temperature after October, when strong storms would thoroughly mix waters in Chequamegon Bay with deep, cold water from Lake Superior.

In Chequarnegon Bay, average water temperature decreased more quickly, but also warmed more quickly than in Lake Superior. Low temperatures estimated in

Chequamegon Bay for the winter months were similar to those recorded in other studies; however, low temperatures were recorded earlier in Chequarnegon Bay than in Lake

Superior (Ebener 1995, Negus 1995). This temperature pattern is consistent with

Chequarnegon Bay freezing and thawing before the rest of the lake.

Prey Abundance

I found that predator consumption exceeded estimated available prey biomass for some prey species, such as rainbow smelt, perhaps because prey fish biomass was underestimated in Chequamegon Bay. Prey fish underestimates could be attributed to vulnerability or availability of fish to trawls or lack of information on movement of fish in Chequarnegon Bay.

Acoustical surveys indicate bottom trawls greatly underestimate prey biomass due to the distribution of species in the water column, trawl avoidance by fish, and gear inefficiencies (Brandt et al. 1991 ). Lantry and Stewart ( 1993) found that rainbow smelt of ages O and 1 in the Great Lakes were distributed around the thermocline, and were unavailable to summer bottom trawl sampling. Rainbow smelt use Chequamegon Bay as 66 a nursery area (Hoff and Bronte 1999), therefore, most of the rainbow smelt in the summer in the bay are yearlings and are distributed in the water column at the time of trawling. Age O yellow perch are also pelagic, and remain unavailable to bottom trawls until they reach a length of 30 mm and become demersal (Ney and Smith 1975). Other prey species, such as lake herring and lake whitefish, are pelagic and are not susceptible to bottom trawling. Erosion of red-clay sediments reduces water clarity in Chequamegon

Bay after storm events (Ragotzkie et al. 1969), and could potentially affect catchability of species to bottom trawls. Fish species distribution in the water column is affected by water clarity; rainbow smelt are suspended in the water column during the day instead of the bottom during periods of high turbidity (Heist and Swenson 1993). Time of day, size and fish density also affect catchability; trawl net avoidance by fish is greater during the day and increases with fish size (Francis and Williams 1995), and high fish density ahead of the trawl increases fish escapement and avoidance (Godo et al. 1990). Some species are able to outswim entrapment by the net (Suuronen et al. 1997), avoid the oncoming vessel by swimming out of the way (Pitcher et al. 1996), or swim along with the trawl and escape when towing speed is reduced to haul in the net (Misund et al. 1999). Gear inefficiencies include the inability to trawl in depths less than 1.5 meters, which results in some of the most productive habitats in Chequamegon Bay not being sampled.

Movement of prey species into Chequamegon Bay from Lake Superior is poorly understood. Rainbow smelt are known to spawn in Chequamegon Bay (Hoff and Bronte

1999), therefore, large numbers of adult rainbow smelt move into the bay in spring.

However, information on movement of rainbow smelt during the remainder of the year is lacking. In addition, commercial catches indicate that prey species, such as lake herring 67 and other coregonines, move between Chequamegon Bay and Lake Superior (WDNR unpublished information). Temperature and habitat may keep other small prey species from moving out of Chequamegon Bay into Lake Superior. Abundances of prey fish in

Chequamegon Bay may be seen in patterns of prey use by predators and may reflect movement of prey species into the bay.

Consumption Estimates

I found that lake whitefish consumed over five times the biomass of prey per individual over their lifetime than any other predator species in Chequamegon Bay. In addition, after the age of 6, lake whitefish age-specific consumption per individual was exceeded only by brown trout age-specific consumption. High consumption per individual of lake whitefish may partially be explained by how the species was modeled.

Lake whitefish were modeled as living to age 29, longer than aH other predator species in

Chequamegon Bay, because of total annual mortality. Total annual mortality for lake whitefish in Chequamegon Bay was low because a commercial fishery for lake whitefish does not operate in the bay. Lake whitefish in Chequamegon Bay were modeled with a total annual mortality rate of 24%, whereas lake whitefish in the Apostle Islands have a total annual mortality rate of 63% (WDNR unpublished data). Low gross conversion efficiency of lake whitefish may also contribute to high consumption rates. Low conversion efficiency may reflect poor fit of the model to the data or inability to properly digest fish. Other studies have shown that a bioenergetics model for coregonines accurately predicted growth (Helminen et al. 1990, Rudstam et al. 1994); however, these studies did not test predictions of consumption or test the model specifically for lake whitefish. 68

I found that gross conversion efficiencies estimated for all predators except lake whitefish in Chequamegon Bay were within the range for other piscivores (Brett and

Groves 1979). Gross conversion efficiency is an indicator of diet adequacy, ration level, state of health and environmental suitability for a fish (Brett and Groves 1979). High conversion efficiency is equated with fast growth (Stewart et al. 1983, Diana 1995).

Smallmouth bass experienced the fastest growth of all predator species in Chequamegon

Bay and gross conversion efficiency of smallmouth bass was double that of other species.

Walleye gross conversion efficiency was similar to that found elsewhere for walleye of various sizes at varying temperatures (Kelso 1972). Negus (1995) estimated 6.23% total gross conversion efficiency for lake trout in Minnesota waters of Lake Superior, which is comparable to my estimate for lake trout in Chequamegon Bay. Stewart et al. (1983) estimated higher gross conversion efficiency for lake trout in Lake Michigan (12.2%) and

Rudstam et al. (1995) estimated higher GCE for burbot in Green Bay, Lake Michigan

(10. 7%). Higher rates in Lake Michigan could be attributed to differences in seasonal temperatures and productivity between the two systems (Lantry and Stewart 1993).

Gross conversion efficiency for splake of ages 8 and older is under 1 %; this may be due to decreased consumption by older age classes.

I found that all predator populations except burbot and lake whitefish had peak consumption at age 1, the age of maximum abundance. Burbot consumption peaked at age 2 and lake whitefish peaked at age 5. Rudstam et al. (1995) also found burbot consumption peaked at age 2 in Green Bay, Lake Michigan. This may be a result of burbot preying mainly upon small prey fish species, which have a lower energy density than coregonines or rainbow smelt. Peak lake whitefish consumption was most likely 69 related to diet; lake whitefish fed only on invertebrates and may have eaten large amounts of this prey to obtain enough energy.

Consumption by predator species in Chequamegon Bay was reduced very little by enacting the various simulated management scenarios. The walleye population consumed the most prey in Chequamegon Bay. Most walleyes in the bay are naturally produced, therefore, eliminating stocking of walleye reduced consumption by this species by only a small percentage. Eliminating stocking of brown trout and splake eliminated nearly all consumption by these species in the bay; however, brown trout and splake would continue to move into Chequamegon Bay from Lake Superior to feed. At most, a modest decrease in consumption by these species would be expected if stocking were moved out of the bay. Decreasing the minimum length limit of smallmouth bass reduced consumption by only a small amount because smallmouth bass longer than 18 inches are not numerous. Eliminating the daily bag limit of one walleye over 20-inches did not decrease consumption greatly because abundance of large walleye is low.

Predator consumption estimates may be inaccurate because some predator species were not included in the analysis due to small sample size, physiological parameter borrowing, or because of errors in input variables in the bioenergetics model. Species not modeled include coho and chinook salmon, which are known to move through

Chequamegon Bay at certain times of the year; these species have been shown to have higher consumption rates than other salmonines (Stewart et al. 1981, Negus 1995, Ebener

1995). Physiological parameters were lacking for brown trout and splake, and were therefore borrowed from lake trout. Parameter borrowing between species is common in bioenergetics modeling, which can create errors in consumption estimates if energetics 70 differ significantly between species (Ney 1990, 1993, Rudstam et al. 1995). Growth of brown trout and splake were assumed to be similar to lake trout; any errors in consumption estimates due to differences in the allometric functions of consumption and respiration of brown trout and splake are small because errors in internal parameters create small errors in predicted consumption (Kitchell et al. 1977, Stewart et al. 1983,

Bartell et al. 1986). Recent studies have modeled brown trout consumption in Lake

Superior and Lake Michigan as being intermediate between other salmonine species, while the predatory demand of splake was ignored (Stewart et al. 1981, Stewart and

Ibarra 1991, Ebener 1995). Predatory population effects are predicted using estimates of abundance and mortality; therefore, estimates of consumption depend on accurate estimates of abundance and mortality and are highly sensitive to errors in these parameters (Hewett 1989). Errors in mark-recapture abundance estimates of coolwater species were minimized by using multiple gears for marking and recapture (Pierce 1997).

Underestimating abundance of coldwater species during late fall through early spring will not effect consumption estimates greatly because consumption decreases with decreasing water temperatures; consumption is minimal at cold temperatures (Diana 1995).

Estimating mortality from catch curves is precise and accurate as long as mortality does not increase for older age classes (Yan Den A vyle and Hayward 1999). 71

MANAGEMENT IMPLICATIONS

Bioenergetics is an important tool for predicting predatory demand on prey fish populations, and is often used to predict the effect of management actions (Stewart et al.

1981, Luecke et al. 1994, Perry et al. 1995). Prey consumption by smallmouth bass in

Chequamegon Bay under the current management (22-inch minimum length limit) was negligible, so simulating a decrease in the minimum length limit to 18-inches did not greatly decrease prey consumption. Because the existing trophy smallmouth bass fishery is an important recreational resource and brings revenue into the community, I recommend not changing the current regulations on this species. Splake and brown trout are also important in the angling fishery. Angler catches of these species show that brown trout and splake are the species most harvested in Chequamegon Bay, except for lake trout, coho salmon and lake whitefish, (WDNR unpublished data). In addition, splake and brown trout consumption in Chequamegon Bay is minimal, 7.9% of the total consumption. I found that walleye preyed heavily upon salmonines, therefore, stocking of these species, instead of building stocks for angler harvest, may only be achieving supplemental feeding of the walleye population. Because little is known of salmonine movement into Chequamegon Bay, moving stocking outside the bay may not result in a decrease in harvest of these species within the bay. Walleyes consume the greatest amount of prey in Chequamegon Bay; however, manipulating management of this species, through eliminating the 20-inch minimum length Hmit and supplemental stocking, would likely have little effect on overall consumption. Increased harvest, such as increasing the bag limit, may be more effective for reducing consumption by walleye. 72

Although prey fish biomass may have been underestimated for some species, average available prey fish biomass exceeded annual predator consumption, indicating prey may not be limiting predator growth and abundance in Chequamegon Bay. The abundance of prey can sustain food web dynamics in Chequamegon Bay under the current management actions. Accurate estimates of prey abundance are difficult to obtain with bottom trawls. Prey abundance is often underestimated by relying on one gear type.

Hydroacoustics has been effective for determining pelagic prey abundance in Lake

Michigan and Lake Superior (Brandt et al. 1991, Heist and Swenson 1993).

Hydroacoustics, coupled with bottom trawl data, might result in a more accurate estimate of prey abundance in Chequamegon Bay, for use in judging the effect of predator demand on prey populations.

Bioenergetics is fairly accurate for predicting consumption when input data is accurate, therefore, additional data should be collected to obtain a more accurate estimate of current predator demand in Chequamegon Bay and for future bioenergetics modeling.

Predator abundance has the greatest effect on predicted consumption, therefore, accurate estimates of abundance are needed. Natural reproduction by stocked walleye, splake and brown trout was assumed to be negligible in this study, which could have resulted in underestimating abundance of these species in Chequamegon Bay. Walleye are known to spawn along the Ashland shoreline in addition to the Kakagon River (S.Schram, WDNR,

Bayfield, personal communication); however, whether these stocked fish reproduce is unknown. The extent of natural reproduction by stocked species should be determined.

In addition, coldwater predator movement into Chequamegon Bay has a direct effect on abundance. Most predator movement into the bay appears to occur during fall and 73 winter, as suggested from creel data (WDNR unpublished data). Consumption decreases with decreasing water temperature, therefore, increased abundance of coldwater predators in fall and winter may not cause an increase in consumption by these species. The timing of movement of coldwater predators into Chequarnegon Bay should be determined.

Because mortality had a direct effect on abundance, estimates of post-stocking mortality are needed. Estimates of stocked returns on steelhead are approximately 2% (S.Schrarn,

WDNR, Bayfield, personal communication), which suggests that post-stocking mortality could be substantial and abundance of stocked fish, as modeled here, may be too high.

Lastly, diet, growth, mortality and abundance data on other predators, such as rainbow trout, coho and chinook salmon, were missing. These species have been shown to be efficient predators (Stewart et al. 1981, Ebener 1995, Negus 1995), and information on their abundance, growth, diet, mortality and movement into Chequarnegon Bay should be collected. 74

REFERENCES

Bailey, M.M. 1972. Age, growth, reproduction and food of the burbot Lota Iota (Linnaeus), in Southwestern Lake Superior. Transactions of the American Fisheries Society 101: 667-674.

Bartell, S.M., J.E. Breck, R.H. Gardner, and A.L. Brenkert. 1986. Individual parameter perturbation and error analysis of fish bioenergetics models. Canadian Journal of Fisheries and Aquatic Science 43: 160-168.

Becker, G.C. 1983. Fishes of Wisconsin, University of Wisconsin Press, Madison.

Boisclair, D., and W.C. Leggett. 1989. Among-population variability of fish growth: III. Influence of fish community. Canadian Journal of Fisheries and Aquatic Science 46: 1539-1550.

Brandt, S.B., D.M. Mason, E.V. Patrick, R.L. Argyle, L. Wells, P.A. Unger and D.J. Stewart. 1991. Acoustic measures of the abundance and size of pelagic planktivores in Lake Michigan. Canadian Journal of Fisheries and Aquatic Science 48: 894-908.

Breck, J.E. 1993. Foraging theory and piscivorous fish: are forage fish just big zooplankton? Transactions of the American Fisheries Society 122: 902-911.

Brett, J.R., and T.D.D. Groves. 1979. Physiological energetics. Pages 280-344 in W.S. Hoar, D.J. Randall and J.R. Brett, editors. Fish Physiology, Academic Press, New York.

Buckner, E.R. 1995. The summer fish community ofChequamegon Bay, Lake Superior. Masters Thesis. University of Wisconsin-Stevens Point, Stevens Point. 75

Carlander, K.D. 1977. Handbook of freshwater fishery biology. Iowa State University Press, Ames, Iowa.

Colby, P.J., P.A. Ryan, D.H. Schupp and S.L. Serns. 1987. Interactions in north­ temperate lake fish communities. Canadian Journal of Fisheries and Aquatic Science 44: 104-128.

Conner, DJ., C.R. Bronte, J.H. Selgeby, and H.L. Collins. 1993. Food of slamonine predators in Lake Superior, 1981-87. Great Lakes Fishery Commission Technical Report 59.

Devries, D.R., and R.V. Frie. 1996. Determination of age and growth. Pages 483-508 in B.R. Murphy and D.W. Willis, Editors. Fisheries Techniques. American Fisheries Society, Bethesda, Maryland.

De Vries, D.R., and R.A. Stein. 1990. Manipulating shad to enhance sport fisheries in North America: an assessment. North American Journal of Fisheries Management 10: 209-223.

Diana, J.S. 1995. Biology and Ecology of Fishes. Cooper Publishing Group, Carmel, Indiana.

Diana, J.S. 1983. Growth, maturation, and production of northern pike in three Michigan lakes. Transactions of the American Fisheries Society 112: 38-46.

Diana, J.S., and W.C. Mackay. 1979. Timing and magnitude of energy deposition and loss in the body, liver, and gonads of northern pike (Esox lucius). Journal of the Fisheries Research Board of Canada 36: 481-487.

Dryer, W.R., L.F. Erkkila, and C.L. Tetzloff. 1965. Food of lake trout in Lake Superior. Transactions of the American Fisheries Society 94: 169-176. 76

Dunning, D.J., Q. Ross and J. Gladden. 1982. Evaluation of minimum size limits for St. Lawrence River northern pike. North American Journal of Fisheries Management 2: 171-175.

Ebener, M.P. 1995. Bioenergetics of predatory fish in Western U.S. waters of Lake Superior. A report prepared for the Red Cliff Band of Lake Superior Chippewas. Great Lakes Indian Fish & Wildlife Commission, Biological Services Division. Odonah, Wisconsin.

Edsall, T.A., G.W. Kennedy and W.H. Homs. 1993. Distribution, abundance, and resting microhabitat ofburbot on Julian's Reef, Southwestern Lake Michigan. Transactions of the American Fisheries Society 122: 560-574.

Elliot, J.M. 1984. Numerical changes and population regulation in young migratory trout, Sa/mo trutta, in a Lake District stream. Journal of Animal Ecology 53: 327-350.

Evans, D.O., B.A. Henderson, T.R. Marshall, R.T. Oglesby and W.J. Christie. 1987. Concepts and methods of community ecology applied to freshwater fisheries management. Canadian Journal of Fisheries and Aquatic Science 44 (Supplement 2): 448-470.

Evans, D.O., and D.H. Loftus. 1987. Colonization of inland lakes in the Great Lakes region by rainbow smelt, Osmerus mordax: their freshwater niche and effects on indigenous fishes. Canadian Journal of Fisheries and Aquatic Science 44(Suppl. 2): 249-266

Francis, M.P., and M.W. Williams.· 1995_ Diel variation in trawl catch rates of Pagrus auratus (Sparidae). Fisheries Research 24: 301-310. 77

Fratt, T.W. 1991. Trophic ecology ofburbot and lake trout in Green Bay and Lake Michigan with information for burbot on fecundity, gonadosomatic index, sea lamprey marks, and intestinal acanthocephalans. Masters Thesis. University of Wisconsin-Stevens Point, Stevens Point.

Gallinat, M.P. 2000. Food habits oflake trout in management units WI-2 and MI-2 of Lake Superior, 1998-99. Red Cliff Fisheries Depart, Assessment Report 00-2, Bayfield.

Godo, O.R., S.J.Walsh, and A. Engas. 1999. Investigating density-dependent catchability in bottom-trawl surveys. ICES-Journal of Marine Science 56: 292- 298.

Haas, R.C., and J.S. Schaeffer. 1992. Predator-prey and competitive interactions among, walleye, yellow perch, and other forage fishes in Saginaw Bay, Lake Huron. Michigan Department of Natural Resources, Technical Report No. 1984, Ann Arbor.

Hansen, M.J., D. Voisclair, S.B. Brandt, S.W. Hewett, J.F. Kitchell, M.C. Lucas and J.J. Ney. 1993.· Applications ofbioenergetics models to fish ecology and management: where do we go from here? Transactions of the American Fisheries Society 122: 1019-1030.

Hansen, M.J., P.T. Schultz and B.A. Lasee. 1990. Changes in Wisconsin's Lake Michigan salmonid sport fishery, 1969-1985. North American Journal of Fisheries Management 10: 442-457.

Hanson, P.C., T.B. Johnson, D.E. Schindler and J.F. Kitchell. 1997. Fish bioenergetics 3.0. University of Wisconsin, Sea Grant Institure, WISCU-T-97-001, Madison. 78

Hartman, K.J., and F.J. Margraf. 1992. Effects of prey and predator abundances on prey consumption and growth of walleyes in Western Lake Erie. Transactions of the American Fisheries Society 121: 245-260.

Hartman, W. L. 1972. Lake Erie: effects of exploitation, environmental changes and new species on the fishery resources. Journal of the Fisheries Research Board of Canada 29: 899-912.

Hayes, J.W., J.D. Stark, and K.A. Shearer. 2000. Development and test of a whole­ lifetime foraging and bioenergetics growth model for drift-feeding brown trout. Transactions of the American Fisheries Society 129: 315-332.

He, X., and J.F. Kitchell. 1990. Direct and indirect effects of predation on a fish community: A whole-lake experiment. Transactions of the American Fisheries Society 119: 825-835.

Heist, B.G., and W.A. Swenson. 1993. Distribution and abundance ofrainbow smelt in western Lake Superior as determined from acoustic sampling. Journal of Great Lakes Research 9: 343-353.

Helminen, H., J. Sarvala, and S. Hirvonen. 1990. Growth and food consumption of vendace (Coregonus albula (L.)) in Lake Pyhajarvi, SW Finalnd: a bioenergetics modeling analysis. Hydrobiologia 200/201: 511-522.

Hewett, S.W., and B.L. Johnson. 1992. Fish bioenergetics model 2.0. University of Wisconsin, Sea Grant Institute, WIS-SG-92-250, Madison.

Hewett, S.W. 1989. Ecological applications ofbioenergetics models. American Fisheries Society Sympoium 6: 113-120. 79

Hodgson, J.R., and J.F. Kitchell. 1987. Opportunistic foraging by largemouth bass (Micropterus salmoides). The American Midland Naturalist 118: 323-336.

Hoff, M.H., and C.R. Bronte. 1999. Structure and stability of the midsummer fish communities in Chequamegon Bay, Lake Superior, 1973-1996. Transactions of the American Fisheries Society 128: 362-373.

Hoff, M.H., J. Link, and C. Haskell. 1997. Piscivory by Lake Superior lake herring (Coregonus artedii) on rainbow smelt (Osmerus mordax) in winter, 1993-1995. Journal of Great Lakes Research 23: 210-211.

Holey, M.E., R.W. Rybicki, G.W. Eck, E.H. Brown Jr., J.E. Marsden, D.S. Lavis, M.L. Toneys, T.N. Trudeau and R.M. Horrall. 1995. Progress toward lake trout restoration in Lake Michigan. Journal of Great Lakes Research 21 (Supplement 1): 128-151.

Hudson, P.L., J.F. Savino, and C.R. Bronte. 1995. Predator-prey relations and competition for food between Age-0 lake trout and slimy sculpins in the Apostle Island Region of Lake Superior. Journal of Great Lakes Research 21 (Supplement 1): 445-457.

Jackson, D.A., P.R. Peres-Neto and J.D. Olden. 2001. What controls who is where in freshwater fish communities - the roles of biotic, abiotic, and spatial factors. Canadian Journal of Fisheries and Aquatic Science 58: 157-170.

Job ling, M. 1985. Physiological and social constraints on growth of fish with special reference to charr, Salvelinus alpinus L. Aquaculture 44: 83-90.

Johnson, T.B., D.M. Mason, S.T. Schram, and J.F. Kitchell. 1999. Ontogenetic and seasonal patterns in the energy content of piscivorous fishes in Lake Superior. Journal of Great Lakes Research 25: 275-281. 80

Jones, M.L., G.W. Eck, D.O. Evans, M.C. Fabrizio, M.H. Huff, P.L. Hudson, J. Janssen, D. Jude., R. O'Gorman, and J.F. Savino. 1995. Limitations to lake trout (Salvelinus namaycush) rehabilitation in the Great Lakes imposed by biotic interactions occurring at early life stages. Journal of Great Lakes Research 21 (Suppl 1): 505-517.

Jude, D.J., and J.H. Leach. 1999. Great Lakes Fisheries. Pages 623-664 in C.C. Kohler · and W.A. Huberts, (Eds). Inland Fisheries Management in North America. American Fisheries Society, Bethesda, Maryland.

Kitchell, J.F., S.P. Cox, C.J. Harvey, T.B. Johnson, D.M. Mason, K.K. Schoen, K. Aydin, C. Bronte, M. Ebener, M. Hansen, M. Hoff, S. Schram, D. Schreiner, and C.J. Walters. 2000. Sustainability of the Lake Superior fish community: interactions in a food web context. Ecosystems 3: 545-560.

Kitchell, J.F., L.A. Eby, D.E. Schindler and R.A. Wright. 1994. Predator-prey dynamics in an ecosystem context. Journal of Fish Biology 45 (Supplement A): 209-226.

Kitchell, J.F., D.J. Stewart and D. Weininger. 1977. Applications of a bioenergetics model to yellow perch (Percaflavescens) and walleye (Stizostedion vitreum vitreum). Journal of the Fisheries Research Board of Canada 34: 1922-1935.

Kelso, J.R.M. 1972. Conversion, maintenance, and assimilation for walleye, Stizostedion vitreum vitreum, as affected by size, diet, and temperature. Journal of the Fisheries Research Board of Canada 29: 1181-1192.

,Knight, R.L., and B. Vondracek. 1992. Changes in prey fish populations in western Lake Erie, 1969-88, as related to walleye, Stizostedion vitreum, predations. Canadian Journal of Fisheries and Aquatic Science 50: 1289-1298. 81

Lantry, B.F., and D.J. Stewart. 1993. Ecological energetics of rainbow smelt in the Laurentian Great Lakes: an interlake comparison. Transactions of the American Fisheries Society 122" 951-976.

Lawrie, A.H. 1978. The fish community of Lake Superior. Journal of Great Lakes Research 4: 513-549.

Lawrie, A.H., and J .F. Rahrer. 1972. Lake Superior: effects of exploitation and introductions on the salmonid community. Journal of the Fisheries Research Board of Canada 29: 765-776.

Li, J., Y. Cohen, D.H. Schupp and I.R. Adelman. 1996a. Effects of walleye stocking on year-class strength. North American Journal of Fisheries Management 16: 840- 850.

Li, J., Y. Cohen, D.H. Schupp and I.R. Adelman. 1996b. Effects of walleye stocking on population abundance and fish size. North American Journal of Fisheries Management 16: 830-839.

Linton, B. 2002. Statistical catch-at-age models for lake trout in Wisconsin waters of Lake Superior. Masters Thesis. University of Wisconsin - Stevens Point, Stevens Point.

Loftus, D. H., and P. F. Hulsman. 1986. Predation on larval lake whitefish (Coregonus clupeaformis) and lake herring (C. artedii) by adult rainbow smelt (Osmerus mordax,). Canadian Journal of Fisheries and Aquatic Science 43: 812-818.

Luecke, C., T.C. Edwards Jr., M.W. Wengert Jr., S. Brayton and R. Schneidervin. 1994. Simulated changes in lake trout yield, trophies, and forage consumption under various slot limits. North American Journal of Fisheries Management 14: 14-21. 82

Lyons, J., and J.J. Magnuson. 1987. Effects of walleye predation on the population dynamics of small littoral-zone fishes in a Northern Wisconsin lake. Transactions of the American Fisheries Society 116: 29-39.

MacCallum, W.R., and J.H. Selgeby. 1987. Lake Superior revisited 1984. Canadian Journal of Fisheries and Aquatic Science 44: 23-36.

Madenjian, C.P., and S.R. Carpenter. 1991. Individual-based model for growth of young-of-the-year walleye: a piece of the recruitment puzzle. Ecological Applications 1: 268-279.

Mason, D.M., T.B. Johnson, and J.F. Kitchell. 1998. Consequences of prey fish community dynamics on lake trout (Salvelinus namaycush) foraging efficiency in Lake Superior. Canadian Journal of Fisheries and Aquatic Science 55: 1273- 1284.

Mayo, K.R., J.H. Selgeby and M.E. McDonald. 1998. A bioenergetics modeling evaluation of top-down control of ruffe in the St. Louis River, Western Lake Superior. Journal of Great Lakes Research 24: 329-342.

Mayo, K.R. 1997. A bioenergetics modeling approach to top-down control of ruffe (Gymnocephalus cernuus) in the St. Louis River. Masters Thesis. University of Minnesota-Duluth, Duluth.

Misund, O.A., N. Luyeye, J. Coetzee, and D. Boyer. 1999. Trawl sampling of small pelagic fish off Angola: Effects ofavoidance, towing speed, tow duration, and time of day. ICES Journal of Marine Science 56: 275-283.

Negus, M.T. 1995. Bioenergetics modeling as a Salmonine management tool applied to Minnesota waters of Lake Superior. North American Journal of Fisheries Management 15: 60-78. 83

Ney, J.J. 1993. Bioenergetics modeling today: growing pains on the cutting edge. Transactions of the American Fisheries Society 122: 736-748.

Ney, J.J. 1990. Trophic economics in fisheries: assessment of demand-supply relationships between predators and prey. Reviews in Aquatic Sciences 2: 55-81.

Ney, J.J., and L.L. Smith, Jr. 1975. First-year growth of yellow perch, Percaflavescens, in the Red Lakes, Minnesota. Transactions of the American Fisheries Society 104: 718-725.

Nielsen, L.A. 1999. History of inland fisheries management in North America. Pages 3- 28 in C.C. Kohler and W.A. Huberts, (Eds). Inland Fisheries Management in North America. American Fisheries Society, Bethesda, MD.

Noble, R.L. and T.W. Jones. 1999. Managing fisheries with regulations. Pages 455-475 in C.C. Kohler and W.A. Huberts, (Eds). Inland Fisheries Management in North America. American Fisheries Society, Bethesda, MD.

Ogle, D.H., J.G. Selgeby, J.F. Savino, R.M. Newman, and M.G. Henry. 1996. Predation on ruffe by native fishes of the St. Louis River Estuary, Lake Superior, 1989- 1991. North American Journal of Fisheries Management 16: 115-123.

Perry, W.B., W.A. Janowsky and F.J. Margraf. 1995. A bioenergetics simulation of the potential effects of angler harvest on growth of largemouth bass in a catch-and­ release fishery. North American Journal of Fisheries Management 15: 705-712.

Persson, L., and S. Diehl. 1990. Mechanistic individual-based approaches in the population/community ecology of fish. Annalles Zoological Fennici 27: 165- 182. 84

Pierce, R.B. 1997. Variable catchability and bias in population estimates for northern pike. Transactions of the American Fisheries Society 126: 658-664.

Pierce, R.B., C.M. Tomcko and D .H. Schupp. 1995. Exploitation of northern pike in seven small north-central Minnesota lakes. North American Journal of Fisheries Management 15: 601-609.

Pitcher, T.J., O.A. Misund, A. Ferno, B. Totland, and V. Melle. 1996. Adaptive behavior of herring schools in the Norwegian Sea as revealed by high-resolution sonar. ICES-Journal-of-Marine-Science 53: 449-452.

Rabeni, C.F. 1992. Trophic linkage between stream centrarchids and their crayfish prey. Canadian Journal of Fisheries and Aquatic Science 49: 1714-1721.

Ragotzkie, R.A., W.F. Ahmsbrak and A. Synowiec. 1969. Summer thermal structure and circulation of Chequamegon Bay, Lake Superior - a fluctuation system. Proceedings Conference of Great Lakes Research 12: 686-704.

Ragotzkie, R.A. 1966. The Keweenaw current, a regular feature of summer circulation of Lake Superior. University of Wisconsin Department of Meteorology, Technical Report 29, Madison.

Rand, P.S., and D.J. Stewart. 1998. Dynamics of salmonine diets and foraging in Lake Ontario, 1983-1993: a test of a bioenergetic model prediction. Canadian Journal of Fisheries and Aquatic Science 55: 307-317.

Rice, J.A., and P.A. Cochran. 1984. Independent evaluation of a bioenergetics model for largemouth bass. Ecology 65: 732-739. 85

Rice, J. A.; J; E. Breck; S. M. Bartell and J. F. Kitchell. 1983. Evaluating the constraints of temperature, activity and consumption on growth of largemouth bass. Environmental Biology of Fishes 9: 263-275.

Rudstam, L.G., P.E. Peppard, T.W. Fratt, R.E. Bruesewitz, D.W. Coble, F.A. Copes, and J.F. Kitchell. 1995. Prey consumption by the burbot (Lota Iota) population in Green Bay, Lake Michigan, based on a bioenergetics model. Canadian Journal of Fisheries and Aquatic Science 52: 1074-1082.

Rudstam, L.G., F.B. Binkowski, and M.A. Miller. 1994. A bioenergetics model for analysis of food consumption patterns of bloater in Lake Michigan. Transactions of the American Fisheries Society 123: 344-357.

Ryder, R.A., and S.A. Kerr. 1978. The adult walleye in the percid community - a niche definition based on feeding, behavior, and food specificity. Pages 39-51 in R.L. Kendals, Editors. Selected Coolwater Fishes of North America. American Fisheries Society Special Publication 11, Bethesda, Maryland.

Schram, S.T., T.L. Margenau, and W.H. Blust. 1992. Population biology and management of the walleye in Western Lake Superior. Wisconsin Department of Natural Resources, Technical Bulletin No. 177, Madison.

Scott, W.B., and E.J. Crossman. 1973. Freshwater fishes of Canada, Fisheries Research Board of Canada Bulletin 184, Ottawa.

Selgeby, J.H. 1988. Comparative biology of the sculpins of Lake Superior. Journal of Great Lakes Research 14: 44-51.

Stein, R.A., R. F. Carline and R. S. Hayward. 1981. Largemouth bass predation on stocked tiger muskellunge. Transactions of the American Fisheries Society 110: 604-612. 86

Stewart, D.J., J.F. Kitchell and L.B. Crowder. 1981. Forage fishes and their salmonid predators in Lake Michigan. Transactions of the American Fisheries Society 110: 751-765.

Stewart, D.J., D. Weininger, D.V. Rottiers and T.A. Edsall. 1983. An energetics model for lake trout, Salvelinus namaycush: Application to the Lake Michigan population. Canadian Journal of Fisheries and Aquatic Science 40: 681-698.

Suuronen, P., E. Lehtonen, and J. Wallace. 1997. Avoidance and escape behavior by herring encountering midwater trawls. Fisheries Research 29: 13-24.

Swenson, W.A. 1977. Food consumption of walleye (Stizostedion vitreum vitreum) and sauger (S. canadense) in relation to food availability and physical conditions in Lake of the Woods, Minnesota, Shagawa Lake, and Western Lake Superior. Journal of the Fisheries Research Board of Canada 34: 1643-1654.

Thorpe, J.E. 1986. Age at first maturity in Atlantic salmon, Salmo salar: freshwater period influences and conflicts with smolting. Canadian Special Publication of Fisheries and Aquatic Sciences 89: 7-14.

Van Den Avyle, M.J., and R.S. Hayward. 1999. Dynamics of exploited fish populations. Pages 127-163 in C.C. Kohler and W.A. Hubert, editors. Inland Fisheries Management in North America. American Fisheries Society, Bethesda, Maryland.

Van Oosten, J. 193 7. The dispersal of smelt, Osmerus mordax, in the Great Lakes region. Transactions of the American Fisheries Society 66: 160-171.

Wahl, D.H., and R.A. Stein. 1991. Food consumption and growth of three esocides: field tests of a bioenergetic model. Transactions of the American Fisheries Society 120: 230-246. 87

Weidel, B.C., D.C. Josephson, and C.C. Krueger. 2000. Diet and prey selection of naturalized smallmouth bass in an oligotrophic Adirondack lake. Journal of Freshwate Ecology 15: 411-420.

Wells, L. 1969. Effects of alewife predation on zooplankton populations in Lake Michigan. Limnology and Oceanography 14: 556-565.

Werner, E.E. 1984. The mechanisms of species interactions and community organization in fish. Pages 360-382 in D.R. Strong Jr., D. Simberloff, L.G. Abele and A.B. Thistles, Editors. Ecological communities. Princeton University Press, Princeton, New Jersey.

Yako. L.A., M.E. Mather, and F. Juanes. 2000. Assessing the contribution of anadromous herring to largemouth bass growth. Transactions of the American Fisheries Society 129: 77-88. 88

APPENDIX A. Lake trout diet information in Chequamegon Bay, Lake Superior, 1998-2001.

Table A I. Proportion of diet items (wet weight) by age for lake trout in Chequamegon Bay, Lake Superior, 1998-2001. Age Number Number Smelt Yell ow Coregonines Salmonines Other Crustaceans Other of Sam:eles with Food Perch Fish Invertebrates 0 23.0 0 0 0 2.0 52.0 23.0 2 0 52.0 0 0 0 22.0 12.0 15.0 3 18 14 61.1 0 37.5 0 1.4 0 0 4 24 15 90.2 0 3.2 0 6.6 0 0 5 29 20 96.4 0 3.6 0 0 0 0 6 34 24 98.4 0 0 0 0 0 1.6 7 15 6 100.0 0 0 0 0 0 0 8 27 9 65.1 0 34.9 0 0 0 0 9 22 6 45.2 0 49.4 0 5.4 0 0 10 24 9 34.0 0 65.0 0 1.0 0 0 11 13 5 39.9 0 55.4 0 4.7 0 0 12+ 30 10 15.8 0 78.9 0 5.3 0 0.1 Note: Diet of age 1 and 2 lake trout taken from Negus (1995). 89

Table A2. Proportions of diet items by wet weight in the "Other Fish" and "Other Invertebrates" diet category by age for lake trout in Chequamegon Bay, Lake Superior, 1998-2001. Age Plecoptera Mayfly Ninespine Alewife Lamprey Spottail Stickleback Shiner 1 2 3 0.0 0 4.6 0 0 2.0 4 0.0 0 0 0 0 0 5 1.6 0 0 0 0 0 6 0 0 0 0 0 0 7 0 0 0 0 0 0 8 0 0 0.4 0 0 5.1 9 0 0 0 0 1.0 0 10 0 0 0 2.6 0 2.2 11 0 0.1 0 4.0 0 1.3 12+ 0 0 0 0 0 0 90

Table A3. Seasonal proportions (wet weight) of prey items for lake trout of ages 3-7 in Chequamegon Bay, Lake Superior, 1998-2001. Day 1 is June 1st. Values between days between dates were estimated in simulations by linear interpolation. Day Smelt Coregonines Other Fish Invertebrates 1 50.0 0 50.0 0 61 0 0 100.0 0 66 100.0 0 0 0 79 30.7 0 69.3 0 84 100.0 0 0 0 111 100.0 0 0 0 183 100.0 0 0 0 184 0 0 100.0 0 252 100.0 0 0 0 253 100.0 0 0 0 259 100.0 0 0 0 261 100.0 0 0 0 267 100.0 0 0 0 274 100.0 0 0 0 276 0 100.0 0 0 280 100.0 0 0 0 287 100.0 0 0 0 288 100.0 0 0 0 290 100.0 0 0 0 292 100.0 0 0 0 295 100.0 0 0 0 297 98.4 1.6 0 0 320 100.0 0 0 0 365 50.0 0 50.0 0 91

Table A4. Seasonal proportions (wet weight) of prey items for lake trout of ages 8 and older in Chequamegon Bay, Lake Superior, 1998-2001. Day 1 is June 1st. Values between days between dates were estimated in simulations b}:'. linear interpolation. Da}:'. Smelt Coregonines Other Fish Invertebrates 1 100.0 0 0 0 61 100.0 0 0 0 66 84.1 15.9 0 0 84 28.0 72.0 0 0 88 99.9 0 0 0.1 111 98.7 0 1.3 0 122 100.0 0 0.0 0 123 0 100.0 0 0 128 0 99.9 0 0.1 129 100.0 0 0 0 134 0 0 0 100.0 183 19.9 0 80.1 0 184 35.4 0 64.6 0 248 0 100.0 0 0 254 0 0 100.0 0 276 0 100.0 0 0 288 100.0 0 0 0 289 100.0 0 0 0 292 100.0 0 0 0 365 100.0 0 0 0 92

APPENDIXB. Brown trout diet information in Chequamegon Bay, Lake Superior, 1998-2001.

Table Bl. Proportion of diet items by wet weight of brown trout by age in Chequamegon Bay, Lake Sueerior, 1998-200 I. Age Number Number Smelt Yell ow Coregonines Salmonines Other Amphipods Oth~r ofSameies with Food Perch Fish Invertebrates 1 11 5 57.5 0 29.6 0 11.0 0 1.9 2 40 23 57.3 0 0 0 42.2 0 0.5 3 46 16 46.4 0.9 0 0 49.0 0 3.7 4 20 4 96.7 0 0 0 3.3 0 0 5 14 5 63.3 7.3 0 0 29.2 0 0.2 6+ 5 2 0 0 0 0 100 0 0 93

Table B2. Proportions of diet items by wet weight in the "Other Fish" and "Other Invertebrates" diet category of brown trout by age in Chequamegon Bay, Lake Superior. Age Plecoptera Mayfly Caddisfly Leech Ruffe Trout Ninespine Emerald Unknown Perch Stickleback Shiner Minnow l 0 0 0.11 1.79 0 0 0 10.97 0 2 0 0.49 0 0.01 0 0 14.58 26.32 1.31 3 3.58 0.04 0 0 0.48 4.10 34.10 10.01 0.33 4 0 0 0 0 0 0 0.44 0 2.83 5 0 0.17 0.02 0 0 0 29.18 0 0 6 0 0 0 0 0 0 0 100 0 94

Table B3. Seasonal proportions (wet weight) of prey items for brown trout of all ages in Chequamegon Bay, Lake Superior, 1998-2001. Day 1 is June 1st. Values between days between dates were estimated in simulations by linear interpolation. Day Smelt Yellow Perch Coregonines Other Fish Invertebrates 1 0 0 0 86.0 14.0 14 0 0 0 86.0 14.0 16 100 0 0 0 0 61 70.8 0 0 29.2 0 66 100 0 0 0 0 79 0 1.8 5.9 92.3 0 84 100 0 0 0 0 85 99.7 0 0 0 0.3 86 100 0 0 0 0 89 0 0 0 67.6 32.4 92 100 0 0 0 0 97 0 0 0 99.7 0.3 110 0 0 0 100 0 111 0 0 0 100 0 129 0 0 0 100 0 136 0 0 0 0 100 184 0 0 0 100 0 218 72.6 0 0 27.4 0 290 74.1 0 0 0 25.9 295 0 0 0 0 100 307 100 0 0 0 0 365 0 0 0 86.0 14.0 Table Cl. Proportion of diet (wet weight) by age for splake in Chequamegon Bay, Lake Superior, 1998-2001. ►"'Cl "'Cl Age Number Number Smelt Yellow Perch Coregonines Salmonines Other Fish Crustaceans Other ~ of Samples with Food Invertebrates d..... 1 103 67 70.6 0 0 0 29.1 0.04 0.27 ~ n 2 70 28 82.2 0 2.7 0 14.4 0.7 0.03 [/J 3 29 8 46.3 10.1 0 14.2 29.5 0 0 "d 4 15 2 0 0 0 0 100 0 0 - (I)~ 5 5 1 0 0 0 0 100 0 0 c.. -·(I) 6+ 10 3 11.9 0 0 0 15.7 0 72.4 -s· Note: Crustaceans include Diporeia hoyi, Mysis relicta and Bythotrephes only. o' sa -·0::s s· n \0 :::r' Vl (I) ..c s:::

s(I) (JC/ 0::s 0::, ~ ~ r ~ ~ (t) [/J .§ (t) >-t -·0 ~""! ...... \0 \0 00 I N 0 0...... Tabe C2. Proportions of diet items by wet weight in the "Other Fish" and "Other Invertebrates" diet category by age for splake in Chequamegon Bay, Lake Superior, 1998-2001. Age Ninespine Emerald Spottail Johnny Sculpin Trout Amphipods Bythotrephes Unknown Annelids Odonata Mayfly Stickleback Shiner Shiner Darter Perch Invertebrate 1 17.25 5;93 1.14 0 2.96 1.85 0.04 0 0.25 0.01 0 0.02 2 4.49 3.99 0 0.73 0 5.17 0.22 0.45 0.03 0 0 0 3 24.52 0.40 0 0 4.57 0 0 0 0 0 0 0 4 6.25 0 0 0 93.75 0 0 0 0 0 0 0 5 100.00 0 0 0 0 0 0 0 0 0 0 0 6+ 15.72 0 0 0 0 0 0 0 72.38 0 0 0 Table C3. Seasonal proportions (wet weight) of prey items for splake of all ages in Chequamegon Bay, Lake Superior, 1998-2001. Day 1 is June 1st. Values between days between dates were estimated in simulations by linear interpolation. Day Smelt Yellow Perch Coregonines Salmonines Other Fish Crustaceans Other Invertebrates 1 100.0 0 0 0 0 0 0 11 100.0 0 0 0 0 0 0 17 14.1 0 0 0 0 0 85.9 25 100.0 0 0 0 0 0 0 38 100.0 0 0 0 0 0 0 61 61.2 0 0 0 38.4 0.4 0 66 72.1 0 0 0 27.8 0 0.1 79 0.0 0 0 0 99.2 0 0.8 84 82.l 0 2.0 0 15.6 0.3 0 111 96.8 0 0 0 0 3.2 0 129 100.0 0 0 0 0 0 0 '-0 130 0.0 0 0 100.0 0 0 0 -.....) 182 56.4 0 0 0 43.6 0 0 183 0.0 96.2 0 0 3.8 0 0 234 100.0 0 0 0 0 0 0 249 0.0 0 0 0 100.0 0 0 259 69.9 0 0 0 30.1 0 0 287 100.0 0 0 0 0 0 0 288 100.0 0 0 0 0 0 0 290 85.8 0 0 0 14.2 0 0 292 84.2 0 0 0 15.8 0 0 294 100.0 0 0 0 0 0 0 295 0.0 0 0 0 0 0 100.0 298 81.1 0 0 0 18.9 0 0 314 87.1 0 0 0 12.9 0 0 365 100.0 0 0 0 0 0 0 Table DI. Proportion of diet items (wet weight) by age for burbot in Chequamegon Bay, Lake Superior, 1998-2001. -0► Age Number Number Smelt Yellow Perch Coregonines Salmoniries Other Fish Crustaceans Other -0 of Samples with Food Invertebrates ~ u.,_. 1 0 0 0 0 0 0 0 0 >< 2 0 0 0 0 0 0 0 0 t, 3 0 0 0 0 0 0 0 0 t:o i=a- 4 0 0 0 0 0 0 0 0 s. 5 0 0 0 0 0 0 0 0 0...... c'D' 6 3 3 81.2 0 0 0 2.09 16.73 0 s· 7 4 2 18.1 0 0 0 81.94 0 0 o' 3 8 4 4 96.0 o· 0 0 0 3.95 0 Ill..... 9 4 4 80.9 0 0 0 19.13 0 0 ::,o· 10 3 3 99.8 0 0 0 0 0 0.23 s· n ::;" 11 6 4 52.1 0 0 0 47.89 0 0 (I) ..0 l,O 12 2 1 100.0 0 0 0 0 0 0 i= 00 sIll 13 4 3 25.4 0 73.8 0 0.81 0 0 (I) (JO 0 14 3 2 0 0 0 0 100.00 0 0 ::, 15+. 1 10 7.8 0 91.6 0 0.37 0.16 0.03 t:o Ill Note: Crustaceans include Diporeia hoyi, Mysis relicta and crayfish. :< t"'"' Ill ::,;- (I) en i= "'O (I) o·-t ~-t IO- IO 00 I N 0 -0 99

Table D2. Seasonal proportions (wet weight) of prey items for burbot of ages 1-2 in Chequamegon Bay, Lake Superior. Diet taken from Fratt (1991). Day I is June 1st. Day Smelt Coregonines Other Fish Inverts Crayfish Crustaceans I 5.27 1.90 55.27 6.68 0.28 30.61 365 5.27 1.90 55.27 6.68 0.28 30.61 Table D3. Seasonal proportions (wet weight) of prey items for burbot of ages 3+ in Chequamegon Bay burbot, Lake Superior, 1998-2001. Day 1 is June 1st. Values between days between dates were estimated in simulations by linear interpolation. Day Smelt Coregonines Other Fish Invertebrates Crayfish Crustaceans 1 100 0 0 0 0 0 24 96.18 0 0 0 3.82 0 66 13.15 86.54 0 0.04 0.26 0 79 6.18 93.82 0 0 Q.00 0 84 14.92 82.55 1.74 0.03 0.76 0 110 0 0 100 0 0 0 111 28.30 0 71.70 0 0 0 122 0 0 100 0 0 0 128 0 0 100 0 0 0 214 0 46.57 53.43 0 0 0 214 0 46.57 53.43 0 0 0 ...... 253 0 93.13 6.87 0 0 0 ·o0 280 100 0 0 0 0 0 287 100 0 0 0 0 0 290 23.01 0 76.99 0 0 0 356 0 0 0 0 0 100 363 100 0 0 0 0 0 365 100 0 0 0 0 0 Table D4. Proportions of diet items by wet weight in the "Other Fish" and "Other Invertebrates" diet category for burbot of all ages in Chequamegon Bay, Lake Superior 1998-2001. Age Crayfish Amp hi pods Unknown Plecoptera Ninespine Trout Log Sculpin Invertebrates Stickleback Perch Perch 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 5 0 0 0 0 0 0 0 0 6 16.56 0.17 0 0 0 0 0 2.09 7 0 0 0 0 0 0 0 81.94 8 3.95 0 0 0 0 0 0 0 9 0 0 0 0 0 0 19.13 0 10 0 0 0 0.23 0 0 0 0 ...... 0 11 0 0 0 0 0 38.80 0 9.10 ...... 12 0 0 0 0 0 0 0 0 13 0 0 0 0 0 0 0 0.81 14 0 0 0 0 67.77 0 0 32.23 15+ 0.16 0 0.03 0 0.21 0 0 0.16 Table El. Proportion of diet items (wet weight) by age for lake whitefish in Chequamegon Bay, Lake Superior, 1998-2001. >"'O "'O Age Number Number Smelt Yellow Perch Coregonines Salmonines Other Fish Crustaceans Other ~ of Samples with Food Invertebrates xt:, 1 2 2 0 0 0 0 0 100 0 rn 2 19 14 0 0 0 0 0 64.9 35.1 t"'"' ~ 3 4 4 0 0 0 0 0 0.0 100.0 (I) 4 9 8 0 0 0 0 0 27.3 72.7 ~ .....s-: (I) 5 13 6 0 0 0 0 0 0 100 ::ti 6 25 19 83.1 0 0 0 13.3 2.9 19.8 "'::i-' Q.. 7 55 43 82.4 0 0 0 15.2 1.7 32.1 .....~- s· 8 59 46 56.5 0 0 0 40.7 2.4 22.9 o' 9 59 43 74.0 0 0 0 23.4 2.6 0.3 sa 10 36 28 21.9 0 0 0 74.6 3.4 1.2 s· :::i 11 21 16 58.5 0 0 0 27.7 13.4 1.2 s· n 0- 12 11 7 88.4 0 0 0 9.4 2.2 0 ::i-' N (I) 13 7 5 87.9 0 0 0 11.9 0.2 0 .c=

14 6 4 96.6 0 0 0 0 3.4 0 s(I) (TO 0 0 0 0 100 0 0 15 3 3 0 :::i 16 5 3 92.3 0 0 0 7.7 0 0 tti 17 2 2 0 0 15.3 0 84.7 0 0 ~ t"'"' ~ 18 3 2 100 0 0 0 0 0 0 (I) 19 2 0 0 0 0 0 0 0 0 r:n -f5 0 0 0 0 0 0 (I) 20 2 1 100 s·'"I 21 3 0 0 0 0 0 0 0 0 ~'"I ..... \0 22 2 0 0 0 0 0 0 0 0 \0 00 I 23+ 2 1 100 0 0 0 0 0 0 N 0 0 Note: Crustaceans includes only Diporeia hoyi, Mysis relicta, and Bythotrephes species. :-' Table E2. Proportions of diet items by weight in the "Other Fish" and "Other Invertebrates" diet category for lake whitefish in Chequamegon Bay, Lake Superior 1998-2001. Age Sculpin Johnny Emerald Spottail Trout Ninespined Sphaeriidae Chironomids Unknown Plecoptera Snail Fly Mayfly Annelids Darter Shiner Shiner Perch Stickleback Invertebrate 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 9.1 22.0 2.1 0.5 0 1.1 0 0.2 3 0 0 0 0 0 0 100.0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 67.1 0 0 0 5.6 0 0 0 5 0 0 0 0 0 0 100.0 0 0 0 0 0 0 0 6 13.3 0 0 0 0 0 19.8 0 0 0 0 0 0 0 7 0 0 0 14.0 1.1 0 31.8 0.4 0 0 0 0 0 0 8 0 0.4 0 15.8 24.5 0 3.6 0 0 0 0 0 19.2 0.1 9 3.0 0.1 0 20.3 0 0 0 0.3 0 0 0 0 0 0 10 0 0 0 39.4 35.2 0 1.2 0 0 0 0 0 0 0 ..... 0 11 0 0 0 27.7 0 0 0 1.2 0 0 0 0 0 0 w 12 O· 4.6 0 0 0 4.8 0 0 0 0 0 0 0 0 13 0 0 0 0 0 11.9 0 0 0 0 0 0 0 0 14 0 0 0 0 0 0 0 0 0 0 0 0 0 0 15 0 0 0 0 0 0 0 0 0 0 0 0 0 0 16 0 0 0 0 7.7 0 0 0 0 0 0 0 0 0 17 60.4 0 24.3 0 0 0 0 0 0 0 0 0 0 0 18 0 0 0 0 0 0 0 0 0 0 0 0 0 0 19 0 0 0 0 0 0 0 0 0 0 0 0 0 0 20 0 0 0 0 0 0 0 0 0 0 0 0 0 0 21 0 0 0 0 0 0 0 0 0 0 0 0 0 0 22 0 0 0 0 0 0 0 0 0 0 0 0 0 0 23+ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 104

Table E3. Seasonal proportions (wet weight) of prey items for lake whitefish of ages 1-5 in Chequamegon Bay, Lake Superior, 1998-2001. Day 1 is June 1st. Values between days between dates were estimated in simulations by linear interpolation. Day Smelt Yell ow Perch Other fish Crustaceans Other Invertebrates 1 0 0 0 0 100.0 23 0 0 0 0 100.0 66 0 0 0 14.3 85.7 84 0 0 0 66.7 33.3 365 0 0 0 0 100.0 105

Table E4. Seasonal proportions (wet weight) of prey items for lake whitefish of ages 6+ in Chequamegon Bay, Lake Superior, 1998-2001. Day 1 is June 1st. Values between days between dates were estimated in simulations by linear interpolation. Day Smelt Yellow Perch Coregonines Other fish Crustaceans Other Invertebrates 1 91.0 0 0 1.7 2.1 5.2 65 91.4 0 0 3.4 4.2 1.0 83 100.0 0 0 0 0 0 101 0 0 0 0 0 100.0 109 65.2 0 0 34.8 0 0 110 35.0 0 0 65.0 0 0 121 0 0 0 100.0 0 0 122 90.4 0 0 9.6 0 0 127 0 0 0 0 99.5 0.51 128 33.8 0 0 0 66.2 0 135 0 0 0 48.4 0 51.6 182 91.6 0 0 8.4 0 0 183 99.5 0 0 0.5 0 0 263 0 0 20.2 79.8 0 0 301 0 0 0 100.0 0 0 318 100.0 0 0 0 0 0 342 90.5 0 0 0 0 9.5 365 91.0 0 0 1.7 2.1 5.2 Table Fl .. Proportion of diet items (by wet weight) by age for walleye of all ages in Chequamegon Bay, Lake Superior, ""1::1► ""1::1 1998-2001. ~ Age Number Number Smelt Yell ow Perch Coregonines Salmonines Other Fish Crayfish Crustaceans Other t:l -X of Samples with Food Invertebrates "T'J 1 29 15 100 0 0 0 0 0 0 0.02 ~ 2 30 16 83.2 16.8 0 0 0 0 0 0 e. ~ 3 92 40 93.1 0.8 0 5.6 0.47 0 0 0.04 (1) 0. 4 121 58 92.5 0 0.99 0 6.5 0 0 0.03 ;;·..... 5 138 68 99.2 0 0 0 0.79 0 0 0.02 s· ~ 6 136 63 96.5 0 0 0 3.5 0 0 0.08 3 7 141 63 78.0 6.9 0 0 15.l 0 0 0.02 ~o· 8 65 36 90.3 0 0 0 9.4 0.31 0 0.01 ::i 9 52 24 90.0 0 0 0 9.6 0 0 0 s· ::,-n 10 36 15 97.6 0 0 0 2.0 0 0 0.38 (1) ...... 0 0 11 30 16 67.1 0 13.3 0 19.6. 0 0 0.03 c:: O'I

s(1) 12 21 8 61.2 22.9 0 0 15.9 0 0 0.06 (IQ 0 13 25 11 58.6 0 20.7 0 20.6 0 0.01 0.04 ·::i 14 15 8 99.1 0 0 0 0.92 0 0 0 tx:i ~ 15 6 3 100 - 0 0 0 0.0 0 0 0 t""' ::., ~ 16 11 7 99.7 0 0 0 0.28 0 0 0 (1) 17 10 2 97.8 0 0 0 0 0 0 2.2 cr.ic:: '"Ci (1) 18 5 0 0 0 0 0 0 0 0 0 o·'"1 19 3 2 23.7 25.9 17.7 0 32.8 0 0 0 ~'"1 20+ 18 16 53.7 0 44.8 0 1.2 0.29 0 0.01 -\0 \0 00 I N 0 -0 Table F2. Proportions of diet items by weight in the "Other Fish" and "Other Invertebrates" diet categories for walleye of all ages in Chequamegon Bay, Lake Superior, 1998-2001. Age Nine spine Burbot Smallmouth Emerald Spottail Alewife Johnny Bullhead Ruffe Slimey Unknown Mayfly Stickleback Bass Shiner Shiner Darter Sculpin Invertebrate 1 0 0 0 0 0 0 0 0 0 0 0 0.02 2 0 0 0 0 0 0 0 0 0 0 0 0 3 0.47 0 0 0 0 0 0 0 0 0 0.01 0.03 4 0.15 0 5.83 0.50 0 0 0 0 0 0 0 0.03 5 0.20 0 0 0 0.15 0 0 0 0 0.44 0 0.02 6 0.34 0 0 2.99 0.13 0 0 0 0 0 0 0.08 7 0.64 0 0 2.41 0.07 11.95 0 0 0 0 0 0.02 8 1.88 0 0 3.64 1.61 0 0.42 0 0 1.85 0 0.01 9 2.41 O· 0 5.24 0.23 0 0 0 0 1.71 0 0 10 0 0 0 0 2.00 0 0 0 0 0 0.35 0.03 0 11 0.20 15.36 0 0 0.36 0 0 0 0 3.68 0 0.03 ---..} 12 · 8.82 0 0 7.06 0 0 0 0 0 0 0 0.06 13 0 0 0 0 0 0 0 20.61 0 0 0 0.04 14 0.92 0 0 0 0 0 0 0 0 0 0 0 15 0 0 0 0 0 0 0 0 0 0 0 0 16 0.28 0 0 0 0 0 0 0 0 0 0 0 17 0 0 0 0 0 0 0 0 0 0 0 2.23 18 0 0 0 0 0 0 0 0 0 0 0 0 19 0 0 0 0 0 0 0 0 32.80 0 0 0 20+ 0 0 0 0 0.43 0 0 0 0.80 0 0 0.01 Table F3. Seasonal proportions (wet weight) of prey items for walleye of all ages in Chequamegon Bay, Lake Superior, 1998-2001. Day 1 is June 1st. Values between days between dates were estimated in simulations by linear interpolation. Day Smelt Yellow Perch Coregonines Salmonines Other Fish Crayfish Amphipods Other Invertebrates 1 100 0 0 0 0 0 0 0 4 100 0 0 0 0 0 0 0 11 100 0 0 0 0 0 0 0 12 100 0 0 0 0 0 0 0 14 66.4 0 33.4 0 0 0 0 0.2 15 100 0 0 0 0 0 0 0 16 99.8 0 0 0 0 0 0 0.2 17 99.4 0 0 0 0 0 0 0.6 18 96.6 0 0 0 0 0 0 3.4 20 98.8 0 0 0 0 0 0 1.2 21 99.9 0 0 0 0 0 0 0.1 0 22 100 0 0 0 0 0 0 0 -00 23 100 0 0 0 0 0 0 0 24 100 0 0 0 0 0 0 0 28 99.9 0 0 0 0 0 0.1 0 29 100 0 0 0 0 0 0 0 30 98.3 0 0 0 0 1.4 0 0.2 31 99.8 0 0 0 0 0 0 0.2 32 99.7 0 0 0 0 0 0 0.3 79 58.1 0 2.6 0 39.3 0 0 0 84 100 0 0 0 0 0 0 0 85 99.4 0 0 0 0.6 0 0 0 88 76.8 0 0 23.2 0 0 0 0 89 100 0 0 0 0 0 0 0 90 100 0 0 0 0 0 0 0 Table F3 Continued. Day Smelt Yellow Perch Coregonines Salmonines Other Fish Crayfish Amp hi pods Other Invertebrates 91 100 0 0 0 0 0 0 0 92 100 0 0 0 0 0 0 0 93 96.0 4.0 0 0 0 0 0 0 94 93.1 6.9 0 0 0 0 0 0 99 100 0 0 0 0 0 0 0 100 100 0 0 0 0 0 0 0 101 90.0 0 0 0 10.0 0 0 0 102 100 0 0 0 0 0 0 0 103 100 0 0 0 0 0 0 0 105 100 0 0 0 0 0 0 0 106 100 0 0 0 0 0 0 0 110 86.5 0 0 0 13.5 0 0 0 -0 111 79.4 0 0 0 20.6 0 0 0 "° 121 55.4 29.6 0 0 14.9 0 0 0 122 95.7 4.3 0 0 0 0 0 0 123 92.6 0 7.4 0 0 0 0 0 124 82.2 0 0 0 17.8 o. 0 0 127 64.6 0 0 0 35.4 0 0 0 128 68.4 0 0 0 31.6 0 0 0 129 66.1 33.9 0 0 0 0 0 0 130 91.8 0 0 0 8.2 0 0 0 133 0 0 0 0 100 0 0 0 134 0 0 0 0 100 0 0 0 154 0 0 0 0 65.9 33.0 0 I.I 184 4.5 0 0 93.0 2.5 0 0 0 260 0 0 100 0 0 0 0 0 Table F3 Continued. Day Smelt Yellow Perch Coregonines Salmonines Other Fish Crayfish Amphipods Other Invertebrates 283 0 33.9 23.1 0 43.0 0 0 0 288 0 100 0 0 0 0 0 0 292 22.1 0 40.4 0 37.5 0 0 0 353 100 0 0 0 0 0 0 0 356 100 0 0 0 0 0 0 0 362 100 0 0 0 0 0 0 0 365 100 0 0 0 0 0 0 0

...... 0 "'C► Table G 1. Proportion of diet items (by wet weight) by age for northern pike in Chequamegon Bay, Lake Superior, 1998-2001. "'C Age Number Number Smelt Yellow Perch Coregonines Salmonines Other Fish Crayfish Other ~ of Samples with Food Invertebrates u..... >< 1 21 8 22.4 48.8 0 10.7 17.4 0.6 0 a 2 34 26 11.0 24.2 1.0 6.9 56.9 0 0 z 3 47 17 9.0 11.2 2.1 9.9 67.5 0.4 0 0 ::r~ (1) 4 32 14 5.8 9.6 37.1 0 47.6 0 0 3 5 33 11 3.8 25.2 0 43.3 27.6 0 0.04 -0 ~ 6 7 2 100 0 0 0 0 0 0 (1) 0.. 7 10 1 100 0 0 0 0 0 0 .....~- 8+ 8 6 77.8 0 0 0 22.2 0 0 s· o'

8i:.:, .....o· ::3 s· - (J - ::r - (1) ..0 =i:.:,s (1) (JQ 0 ::3 t;Cl ~

ri:.:, :;,;-- (1) r:/1 -0= (1) ~sr""I ..... 1.0 '-0 00 I N 0 .....0 112

Table G2. Proportions of diet items by weight in the "Other Fish" and "Other Invertebrates" diet category by age for northern pike in Chequamegon Bay, Lake Superior, 1998-2001. Age Plecoptera Ninespine Common Smallmouth Trout Rockbass Stickleback Shiner Bass Perch 1 0 1.1 11.6 0 0 0 2 0 1.1 0.8 0 11.8 26.7 3 0 4.2 0 0 0 0 4 0 2.5 0 7.3 14.0 0 5 0.04 0.3 0 0 1.2 12.5 6 0 0 0 0 0 0 7 0 0 0 0 0 0 8+ 0 9.6 0 0 12.5 0 113

Table G2 Continued. Age White Ruffe Log Emerald Sculpin Johnny Spottail Sucker Perch Shiner Darter Shiner 1 0 0 0 4.7 0 0 0 2 1.3 11.1 0 1.4 0.2 0 2.6 3 31.4 23.0 0.3 0 0 0 8.5 4 18.7 0 2.1 1.0 0 0 2.1 5 0 3.5 0 0 9.2 0.2 0.7 6 0 0 0 0 0 0 0 7 0 0 0 0 0 0 0 8+ 0 0 0 0 0 0 0 114

Table G3. Seasonal proportions (wet weight) of prey items for northern pike of ages 1-2 in Chequamegon Bay, Lake Superior, 1998-2001. Day 1 is June 1st. Values between days between dates were estimated in simulations by linear interpolation. Day Smelt Yellow Perch Coregonines Salmonines Other Fish Invertebrates 1 0 0 0 0 100 0 10 0 0 6.56 0 93.44 0 13 0 0 0 0 100 0 16 0 0 0 0 100 0 18 0 80.53 18.36 0 0 1.11 23 0 0 0 0 100 0 30 100 0 0 0 0 0 31 100 0 0 0 0 0 32 100 0 0 0 0 0 79 48.56 0 0 19.25 32.18 0.01 102 0 100 0 0 0 0 120 0 90.72 0 0 9.28 0 122 0 52.08 0 0 47.92 0 128 0 77.46 0 0 22.54 0 183 0 0 0 0 100 0 338 31.85 18.38 0 0 49.76 0 353 14.23 0 81.54 0 4.23 0 356 0 0 0 0 100 0 356 0 0 0 0 100 0 Table G4. Seasonal proportions (wet weight) of prey items for northern pike of age 3 in Chequamegon Bay, Lake Superior, 1998-2001. Day 1 is June 1st. Values between days between dates were estimated in simulations by linear interpolation. Day Smelt Yellow Perch Coregonines Salmonines Other Fish Invertebrates Crayfish 1 0 0 50.00 0 50.00 0 0 11 0 0 0 0 100 0 0 30 100 0 0 0 0 0 0 32 100 0 0 0 0 0 0 52 100 0 0 0 0 0 0 65 0 0 0 0 0 0 100 79 0 0 0 100 0 0 0 84 45.63 0 0 46.75 7.62 0 0 100 100 0 0 0 0 0 0 122 0 0 0 0 100 0 0 ...... 338 0 42.17 0 0 57.83 0 0 ...... 356 0 0 100 0 0 0 0 Vo 365 0 0 50.0 0 50.0 0 0 116

Table G5. Seasonal proportions (wet weight) of prey items for northern pike of ages 4+ in Chequamegon Bay, Lake Superior, 1998-2001. Day 1 is June 1st. Values between days between dates were estimated in simulations by linear interpolation. Day Smelt Yellow Perch Coregonines Salmonines Other Fish Invertebrates I 0 0 0 100 0 0 4 0 0 0 100 0 0 12 0 0 0 0 100 0 15 0 0 0 0 100 0 16 0 0 0 0 100 0 24 0 0 0 0 100 0 32 100 0 0 0 0 0 64 0 0 0 0 0 100 79 0 0 0 0 100 0 83 65.03 0 0 0 34.97 0 88 1.80 0 98.20 0 0 0 110 0 0 0 0 97.11 2.89 123 0 0 0 0 100 0 124 100 0 0 0 0 0 133 0 0 0 0 100 0 182 0 0 0 0 100 0 183 4.76 63.09 0 0 32.14 0 290 57.40 0 42.60 0 0 0 338 53.89 40.45 0 0 5.66 0 356 0 0 0 100 0 0 365 0 0 0 100 0 0 Table Hl. Proportion of diet items (by wet weight) by age for smallmouth bass in Chequamegon Bay, Lake Superior, 1998-2001. Age Number Number Smelt Yellow Perch Coregonines Salmonines Other Fish Crayfish Other of Samples with Food Invertebrates -0► 1 1 0 0 0 0 0 0 0 0 -0 2 24 7 0 81.8 0 0 10.7 7.5 0 ~ 3 15 3 0 81.4 0 0 0 18.6 0 ->< 4 10 4 0 0 0 0 75.7 24.3 0 ;:c 5 47 21 2.5 9.2 0 0 66.8 21.0 0.49 sr/J 6 52 21 0 8.2 0 0 70.5 20.6 0.76 ~ 3 7 36 16 6.4 20.3 0 0 59.3 0 13.5 0.50 ....s::: 8 14 40.2 ::,-- 38 0 0 0 47.6 12.0 0.24 cr- ~ 9 60 26 0 1.7 0 0 82.7 14.5 1.2 V, 0. 10 74 38 16.8 10.3 0 0 54.1 18.3 0.46 ....

s(1) (JCl 0 :::I tJj ~ t""' ~ (1) r/J s::: "O (1) ::I. 0 ~"1 -'-0 '-0 00 I N 0 0 :-' Table H2. Proportions of diet items by weight in the "Other Fish" and "Other Invertebrates" diet category for smallmouth bass in Chequamegon Bay, Lake Superior, 1998-2001. Age Crayfish Amphi pods Caddisfly Mayfly Chironomid Plecoptera Unknown Invertebrate 1 0.00 0 0 0 0 0 0 2 7.50 0 0 0 0 0 0 3 18.64 0 0 0 0 0 0 4 24.32 0 0 0 0 0 0 5 20.98 0.04 0 0.49 0 0 0 6 20.61 0 0 0.76 0 0 0 7 13.48 0 0.01 0.38 0 0 0.11 8 11.98 0 0 0.24 0 0 0 9 14.46 0.05 0 0.86 0 0 0.29 10 18.27 0 0.10 0.16 0 0.20 0 ...... 11 5.68 0.05 0 0.05 0 0 0 00. 12 4.70 0 0 0.04 0 0 0 13 5.33 0 0 0.18 0 0 0 14 0 0 0 0 0 0 0 15 0 0 0 0 0 0 0 16 17.25 0 0 0 0 0 0 Table H2 Continued. Age Ninespine Trout Pumpkinseed Common Johnny Log Emerald Ruffe Sculpin Stickleback Perch Shiner Darter Perch Shiner 1 0 0 0.00 0 0 0 0 0 0 2 0 0 10.66 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 75.68 5 0 0 0 0 0 0 5.44 54.25 7.12 6 0 0 0 0 6.10 0 3.06 61.30 0 7 0 35.01 0 0 1.47 0 1.84 0 21.01 8 0.60 0 0 0 2.50 23.53 3.82 0 17.13 9 30.33 11.57 0 0 0 0 3.81 0 36.95 10 3.35 0 0 10.02 1.70 0 2.39 11.11 25.54 11 1.93 14.09 1.15 0 0 0 1.43 13.26 10.23 ...... 12 0.72 0 0.83 40.09 2.51 5.91 0.96 9.60 1.92 "° 13 0 0 0 0 2.85 0 0 0 0 14 0 0 0 0 100.00 0 0 0 0 15 0 0 0 0 0 0 0 0 1.97 16 0.73 0 0 49.07 0 0 0 0 0 Table H3. Seasonal proportions (wet weight) of prey items for smallmouth bass of ages 1-9 in Chequamegon Bay, Lake

5 Superior, 1998-2001. Day 1 is June 1 \ Values between days between dates were estimated in simulations by linear interpolation. Day Smelt Yellow Perch Other Fish Crayfish Other Invertebrates Crustaceans 1 0 0 0 97.8 2.2 0 6 0 0 0 97.8 2.2 0 17 0 0 60.0 38.5 0.1 1.3 30 0 7.4 90.0 2.5 0 0.2 79 0 0 93.0 7.0 0 0 84 51.2 0 43.7 5.1 0 0 101 0 91.6 0 8.4 0 0 102 0 60.6 39.4 0 0 0 111 0 0 0 100 0 0 123 0 0 98.8 0 1.2 0 -N 128 0 0 28.4 71.6 0 0 0 129 0 43.2 12.l 44.5 0.2 0 130 0 0 0 100 0 0 133 0 0 81.2 17.5 1.3 0 134 0 0 97.5 2.3 0.2 0 136 0 0 96.9 0 3.1 0 152 94.7 0 0 0 5.3 0 154 0 21.5 67.2 9.9 1.4 0 365 0 0 0 97.8 2.2 0 121

Table H4. Seasonal proportions (wet weight) of prey items for smallmouth bass of ages 10+ in Chequarnegon Bay, Lake Superior, 1998-2001. Day 1 is June 1st. Values between days between dates were estimated in simulations by linear interpolation. Day Smelt Yellow Perch Other Fish Crayfish Other Invertebrates Crustaceans 1 0 0 99.6 0 0.2 0.2 6 0 0 99.6 0 0.2 0.2 24 0 0 95.6 4.4 0 0 30 0 0 0 100 0 0 40 0 81.3 0 0 14.9 3.7 79 0 0 78.2 21.8 0 0 84 88.0 0 10.3 1.7 0 0 110 0 0 0 100 0 0 111 0 10.2 88.2 1.7 0 0 122 0 8.0 88.3 3.7 0 0 123 0 0 58.2 41.8 0 0 128 0 68.2 9.2 22.6 0 0 129 0 17.1 67.2 15.6 0.1 0 130 0 0 0 100 0 0 133 0 0 99.6 0 0.4 0 134 0 0 94.2 5.8 0 0 136 0 74.0 9.1 17.0 0 0 152 0 0 63.0 35.8 1.2 0 154 0 0 30.7 66.5 2.8 0 365 0 0 99.6 0 0.2 0.2 n > Table IL Annual growth, gametic production (average of males and females), P, and food conversion efficiency of brown ::r '"t:) 0 '"t:) trout in Chequamegon Bay, Lake Superior, during 2001. Lengths and weight refer to the start of the year. P refers to the -§ ~ proportion of maximum consumption needed to account for observed growth. Conversion efficiencies are given on a s 0 - (JQ X wet-weight basis. § ~ p Age Size Weight Growth Gametes Consumption % Gross Conversion ~..,t::oo • 0 (mm) (g) (g) (g) (g) Efficiency (gig) r< ~ ~?' 1 319 375 375 0 0.508 3041 12.32 0 (JQ 2 416 820 446 0 0.511 4632 9.63 ~s "O 0 3 496 1383 563 397 0.621 7637 12.58 3. §'· 4 562 2008 625 535 0.613 9373 12.38 .Sl "Sl NO oO. 5 617 2650 641 671 0.607 10945 11.99 oC:: .-~ o· 6 662 3274 624 798 0.604 12348 11.52 p 7 700 3860 586 915 0.600 13550 11.08 '"t:) < 8 731 4395 535 1020 0.596 14564 10.68 !::...... c:: N 9 757 4875 479 1113 0.594 15468 10.30 .o N § 10 779 5298 423 1195 0.592 16226 9.97 0. 11 796 5666 368 aCl) Cl) All Ages 11.07 (') 0 ~ 0.., o·Cl) 0= s (') iii" (') '-<= o'.., "O.., 0 0. !:;. ..,0 a·Cl) Table 12. Annual growth, gametic production ( average of males and females), P, and food conversion efficiency of burbot in Chequamegon Bay, Lake Superior, during 2001. Lengths and weight refer to the start of the year. P refers to the proportion of maximum consumption needed to account for observed growth. Conversion efficiencies are given on a wet-weight basis. Age Size Weight Growth Gametes p Consumption % Gross Conversion (mm) (g) (g) (g) (g) Efficiency (gig) 1 132 16 16 0 0.690 358 4.43 2 218 75 59 0 0.634 819 7.17 3 289 180 106 39 0.541 1198 12.06 4 349 324 144 60 0.520 1712 11.89 5 399 492 168 83 0.506 2220 11.31 6 441 671 179 107 0.495 2702 10.59 7 476 852 181 130 0.486 3152 9.85 8 506 1027 175 151 0.480 3551 9.17 ...... N 9 531 1191 164 171 0.475 3907 8.56 w 10 551 1341 150 189 0.471 4220 8.03 11 568 1476 135 204 0.467 4496 7.56 12 583 1597 120 218 0.464 4728 7.16 13 595 1702 106 231 0.462 4932 6.82 14 605 1794 92 241 0.460 5110 6.52 15 614 1874 80 250 0.459 5249 6.28 16 621 1942 68 258 0.458 5377 6.07 17 627 2001 59 All Ages 8.03 Table 13. Annual growth, gametic production (average of males and females), P, and food conversion efficiency of splake in Chequamegon Bay, Lake Superior, during 2001. Lengths and weight refer to the start of the year. Prefers to the proportion of maximum consumption needed to account for observed growth. Conversion efficiencies are given on a wet-weight basis. Age Size Weight Growth p Consumption % Gross Conversion (mm) (g) (g) (g) Efficiency (gig) 1 330 261 261 0.5391 2792 9.33 2 426 743 483 0.4541 3716 12.99 3 493 1169 426 0.3926 3994 10.66 4 539 1460 291 0.3506 3988 7.29 5 571 1638 178 0.3252 3926 4.53 6 593 1741 103 0.3152 3883 2.65 7 608 1799 58 8 619 1831 32 0.2998 3838 0.84 ..... N 9 626 1849 18 0.2969 3819 0.47 .i:,. 10 631 1859 10 0.2959 3818 0.26 11 635 1864 5 0.2949 3810 0.14 12 637 1867 All Ages 4.27 Note: Splake were assumed to have no natural reproduction. Splake were not stocked in 1995. Table 14. Annual growth, gametic production (average of males and females), P, and food conversion efficiency oflake trout in Chequamegon Bay, Lake Superior, during 2001. Lengths and weight refer to the start of the year. Prefers to the proportion of maximum consumption needed to account for observed growth. Conversion efficiencies are given on a wet-weight basis. Age Size Weight Growth Gametes p Consumption % Gross conversion (mm) (g) (g) (g) (g) efficiency (g/g) 1 162 201 201 0 0.608 1543 13.0 2 255 367 165 0 0.596 2097 7.9 3 335 573 207 0 0.577 2704 7.6 4 404 812 239 0 0.578 3338 7.2 5 463 1073 261 0 0.577 3952 6.6 6 515 1347 274 0 0.574 4524 6.1 7 559 1627 280 0 0.564 5006 5.6 8 597 1906 279 0 0.513 5006 5.6 N 9 629 2179 273 168 0.564 6008 7.3 -v-, 10 658 2442 263 186 0.561 6419 7.0 11 682 2694 251 203 0.555 6789 6.7 12 703 2931 237 220 0.551 7116 6.4 13 721 3153 222 235 0.549 7404 6.2 14 736 3359 206 All Ages 6.73 Table 15. Annual growth, gametic production (average of males and females), P, and food conversion efficiency of lake whitefish in Chequamegon Bay, Lake Superior, during 2001. Lengths and weight refer to the start of the year. Prefers to the proportion of maximum consumption needed to account for observed growth. Conversion efficiencies are given on a wet-weight basis. Age Size Weight Growth Gametes p Consumption % Gross Conversion (mm) (g) (g) (g) (g) Efficiency (gig) 1 156 2 2 0 0.146 217 0.74 2 227 33 31 0 0.233 1000 3.10 3 290 124 91 0 0.314 2481 3.67 4 345 277 154 0 0.347 4262 3.61 5 393 481 204 0 0.377 6375 3.20 6 436 719 237 111 0.367 7941 4.38 7 473 972 253 144 0.393 10173 3.90 8 505 1227 256 176 0.416 12417 3.47 -N 9 534 1475 248 207 0.438 14618 3.11 O'I 10 559 1708 233 235 0.457 16721 2.80 11 581 1923 215 262 0.474 18643 2.55 12 600 2117 194 285 0.488 20399 2.35 13 617 2290 173 306 0.501 21977 2.18 14 632 2443 153 324 0.513 23428 2.04 15 645 2576 134 340 0.521 24619 1.92 16 656 2692 116 354 0.530 25746 1.83 17 666 2792 100 366 0.537 26678 1.75 18 675 2878 86 376 0.543 27486 1.68 19 683 2952 74 385 0.549 28245 1.63 20 690 3015 63 393 0.553 28818 1.58 21 696 3068 53 399 0.557 29347 1.54 22 701 3114 45 404 0.560 29775 1.51 Table 15 Continued. Age Size Weight Growth Gametes p Consumption % Gross Conversion (mm) (g) (g) (g) (g) Efficiency (gig) 23 705 3152 38 409 0.563 30169 1.48 24 709 3185 33 413 0.564 30467 1.46 25 713 3212 28 416 0.566 30738 1.44 26. 716 3235 23 419 0.567 30918 1.43 27 719 3255 20 421 0.568 31084 1.42 28 721 3271 17 423 0.570 31306 1.40 29 723 3285 14 425 0.571 31445 1.40 30 725 3297 12 All Ages 1.89

...... N -....J Table 16. Annual growth, gametic production (average of males and females), P, and food conversion efficiency of smallmouth bass in Chequamegon Bay, Lake Superior, during 2001. Lengths and weight refer to the start of the year. P refers to the proportion of maximum consumption needed to account for observed growth. P values over 1 indicate the Cmax function in the bioenergetics model is incorrect because individuals used to generate the parameters may have been smaller than· in this study. Conversion efficiencies are given on a wet-weight basis. Age Size Weight Growth Gametes p Consumption % Gross Conversion (mm) (g) (g) (g) (g) Efficiency (gig) 1 111 86 86 0 1.434 388 22.16 2 200 209 123 0 1.332 582 21.18 3 267 368 159 0 1.488 632 25.15 4 317 544 176 0 1.379 735 23.93 5 355 722 178 79 1.523 926 27.78 6 384 892 170 98 1.469 1013 26.45 7 406 1048 156 115 1.426 1084 25.03 _. 8 422 1187 139 131 1.390 1141 23.67 N 9 435 1309 122 144 1.363 1187 22.40 00 10 444 1414 105 156 1.316 1198 21.75 11 451 1503 89 165 1.301 1230 20.72 12 457 1579 75 174 1.285 1252 19.89 13 461 1642 63 181 1.273 1271 19.17 14 464 1694 52 186 1.266 1288 18.54 15 466 1737 43 191 1.258 1300 18.04 16 468 1773 36 195 1.250 1309 17.65 17 469 1803 30 198 1.246 1318 17.29 18 470 1827 24 201 1.242 1325 17.00 19 471 1847 20 203 1.238 1330 16.78 20 471 1863 16 205 1.234 1332 16.61 21 472 1876 All Ages 20.21 Table 17. Annual growth, gametic production (average of males and females), P, and food conversion efficiency of northern pike in Chequamegon Bay, Lake Superior, during 2001. Lengths and weight refer to the start of the year. Prefers to the proportion of maximum consumption needed to account for observed growth. Conversion efficiencies are given on a wet-weight basis. Age Size Weight Growth Gametes p Consumption % Gross Conversion (mm) (g) (g) (g) (g) Efficiency (gig) 1 366 241 241 0 0.414 1488 16.22 2 464 546 305 0 0.390 2410 12.64 3 548 965 419 0 0.389 3484 12.04 4 619 1471 506 278 0.406 5046 15.72 5 680 2031 560 361 0.397 6218 15.02 6 732 2617 585 445 0.390 7338 14.25 7 777 3203 586 526 0.384 8381 13.50 8 815 3773 569 604 0.379 9334 12.80 ..... N 9 847 4312 540 677 0.375 10197 12.16 \0 10 875 4814 502 743 0.372 10974 11.57 11 898 5274 460 804 0.369 11661 11.07 12 918 5691 416 858 0.367 12257 10.63 13 935 6064 373 906 0.365 12783 10.23 14 950 6396 332 949 0.363 13253 9.90 15 962 6690 294 All Ages 12.05 Table 18. Annual growth, gametic production (average of males and females), P, and food conversion efficiency of walleye in Chequamegon Bay, Lake Superior, during 2001. Lengths and weight refer to the start of the year. Prefers to the proportion of maximum consumption needed to account for observed growth. Conversion efficiencies are given on a wet-weight basis. Age Size Weight Growth Gametes p Consumption % Gross Conversion (mm) (g) (g) (g) (g) Efficiency (gig) 1 155.1 199 199 0 0.522 1922 10.33 2 224.3 353 155 0 0.290 1086 14.23 3 284.8 538 185 0 0.285 1398 13.21 4 337.7 741 203 0 0.281 1697 11.96 5 383.8 951 211 0 0.277 1978 10.64 6 424.1 1161 210 150 0.298 2502 14.37 7 459.4 1364 203 171 0.296 2766 13.52 8 490.1 1555 192 191 0.294 3004 12.73 -I..;,.) 9 517.0 1733 178 209 0.293 3221 12.02 0 10 540.5 1896 163 226 0.292 3403 11.41 11 561.0 2043 147 240 0.291 3566 10.86 12 579.0 2175 132 254 0.291 3716 10.37 13 594.6 2292 117 265 0.290 3835 9.97 14 608.3 2395 104 275 0.289 3945 9.60 15 620.2 2486 91 284 0.289 4039 9.29 16 630.7 2566 80 292 0.288 4120 9.02 17 639.8 2636 70 299 0.288 4188 8.79 18 647.8 2696 60 305 0.288 4254 8.59 19 654.7 2749 52 310 0.287 4302 8.42 20 660.8 2794 45 314 0.287 4341 8.28 21 666.1 2833 39 318 0.287 4383 8.15 22 670.8 2867 34 321 0.287 4420 8.04 Table 18 Continued. Age Size Weight Growth Gametes p Consumption % Gross Conversion (mm) (g) (g) (g) (g) Efficiency (gig) 23 674.8 2896 29 324 0.286 4441 7.95 24 678.4 2921 25 326 0.286 4467 7.87 25 681.5 2943 22 329 0.286 4491 7.80 26 684.2 2961 18 330 0.286 4510 7.73 27 685.8 2977 16 332 0.286 4527 7.69 28 688.6 2991 14 333 0.286 4532 7.65 29 690.4 3003 All Ages 9.48

...... w...... 132

APPENDIX J. Annual predator consumption by age in Chequamegon Bay, Lake Superior in 2001.

Table J1. Walleye consumption in pounds by age class in Chequamegon Bay, Lake Superior in 2001. Age Crustaceans Crayfish Invertebrates Smelt Yell ow Perch Coregonines 1 52 119178 7537 3396487 139230 593466 2 16 41782 2502 1039362 38396 150296 3 11 26576 1616 671574 24256 94270 4 7 16404 1008 419064 14900 57620 5 4 10375 642 267088 9393 36193 6 3 6991 428 176390 6342 24485 7 2 3662 225 92845 3315 12772 8 1 2150 133 54705 1943 7474 9 0 1158 72 29536 1045 4015 10 0 629 39 16081 567 2175 11 0 340 21 8726 307 1176 12 0 176 11 4517 159 607 13 0 120 7 3080 108 413 14 0 85 5 2175 76 291 15 0 54 3 1401 49 187 16 0 39 2 998 35 133 17 0 26 2 666 23 89 18 0 17 1 438 15 58 19 0 12 1 300 10 40 20 0 7 0 190 7 25 21 0 5 0 123 4 16 22 0 3 0 83 3 11 23 0 2 0 55 2 7 24 0 1 0 37 1 5 25 0 1 0 23 1 3 26 0 1 0 14 0 2 27 0 0 0 9 0 1 28 0 0 0 5 0 1 Total 97 229794 14256 6185973 240188 985832 133

Table J1 Continued. Age Salmonines Other Fish Total by Population Total by Individual 1 428173 1031579 5715703 4 2 129972 331054 1733380 2 3 82206 211632 1112140 3 4 50541 131085 690628 4 5 31879 83116 438690 4 6 21548 55688 291874 6 7 11269 29216 153306 6 8 6607 17172 90186 7 9 3554 9254 48634 7 10 1928 5030 26449 8 11 1044 2726 14340 8 12 539 1410 7419 8 13 367 960 5055 8 14 259 678 3568 9 15 167 436 2298 9 16 118 310 1636 9 17 79 207 1092 9 18 52 136 718 9 19 36 93 491 9 20 22 59 311 10 21 15 38 202 10 22 10 26 136 10 23 7 17 91 10 24 4 12 61 10 25 3 7 38 10 26 2 4 23 10 27 1 3 15 10 28 1 1 8 10 Total 770402 1911950 10338492 218 Table J2. Northern pike consumption in pounds by age class in Chequamegon Bay, Lake Superior, in 2001. Age Crayfish Invertebrates Smelt Yellow Perch Coregonines Salmonines Other Fish Total by Population Total by Individual 1 0 33 69318 96876 10368 4906 120369 301869 3 2 0 24 48840 63866 7311 3158 79493 202692 5 3 8794 0 37009 6966 10656 4358 53347 121129 8 4 0 9003 13996 3522 3916 8314 33428 72178 11 5 0 4627 7095 1749 1983 4197 16886 36537 14 6 0 2266 3440 835 961 2029 8165 17695 16 7 0 1070 1613 387 450 949 3821 8291 18 8 0 492 738 175 206 433 1744 3788 21 9 0 222 331 78 92 194 780 1696 22 10 0 99 147 35 41 86 347 755 24 11 0 42 62 14 17 36 146 318 26 12 0 18 27 6 7 16 63 138 27 w 13 0 8 12 3 3 7 28 62 28 -~ 14 0 3 4 1 1 2 10 21 29 Total 8794 17907 182630 174512 36014 28685 318627 767169 253 Table J3. Smallmouth bass consumption in pounds by age class in Chequamegon Bay, Lake Superior, in 2001. Age Crustaceans Crayfish Invertebrates Smelt Yellow Perch Other Fish Total by Population Total by Individual 1 3 1115 31 420 667 2319 4554 1 2 3 1061 29 405 643 2328 4469 1 3 3 846 24 209 331 1728 3141 1 4 2 637 18 157 251 1323 2388 2 5 2 525 15 129 206 1083 1960 2 6 1 374 10 92 147 776 1400 2 7 1 260 7 64 102 543 978 2 8 1 178 5 44 70 373 670 3 9 0 121 3 30 48 254 456 3 10 2 76 8 27 50 137 299 3 11 1 51 5 18 34 92 201 3 12 1 33 4 12 22 61 132 3 -\.;.J 13 1 22 2 8 15 40 88 3 V, 14 0 15 2 5 10 27 60 3 15 0 9 1 3 6 17 38 3 16 0 6 1 2 4 12 25 3 17 0 4 0 2 3 8 18 3 18 0 3 0 1 2 5 10 3 19 0 1 0 0 1 2 5 3 20 0 1 0 0 0 1 3 3 Total 20 5339 165 1628 2612 11130 20895 48 Table J4. Splake consumption in pounds by age class in Chequamegon Bay, Lake Superior, in 2001. Age Crustaceans Invertebrates Smelt Yellow Perch Coregonines Salmonines Other Fish Total by Population Total by Individual 1 1630 7170 233448 12558 640 37577 55558 348581 6 2 529 2787 77059 3584 214 11191 18265 113628 8 3 77 432 11266 492 31 1566 2664 16529 9 4 81 469 11909 506 33 1623 2813 17434 9 5 4 26 661 2 89 156 28 966 9 6 5 29 735 31 2 99 173 1074 9 7 8 0.58 3 86 4 0 12 20 126 8 9 0.23 1 34 1 0.09 4 8 49 8 10 0.08 0.45 11 0.46 0.03 1 3 16 8 0.03 0.15 4 0.15 0.01 0 1 5 8 Total 2326 10919 335212 17178 1010 52229 79533 498408 83 ..... (j.) 0\ Table JS. Brown trout consum12tion in pounds by age class in Chequamegon Bay, Lake Superior, in 2001. Age Invertebrates Smelt Yellow Perch Coregonines Other Fish Total by Population Total by Individual 1 71388 177211 427 1280 228709 479015 7 2 93 245 1 2 307 647 10 3 88 247 1 2 309 647 17 4 64 183 0 1 226 474 21 5 45 130 0 1 160 337 24 6 29 87 0 1 106 224 27 7 19 58 0 0 70 147 30 8 14 41 0 0 50 106 32 9 11 33 0 0 40 84 34 10 4 12 0 0 14 29 36 Total 71754 178247 429 1288 229991 481710 238

v.) --...) Table J6. Lake trout consumption in pounds by age class in Chequamegon Bay, Lake Superior, in 2001. Age Crustaceans Invertebrates Smelt Coregonines Other Fish Total by Population Total by Individual 1 1742 560 1090 0 57 3450 3 2 154 198 1260 0 366 1978 5 3 0 0 760 5 313 1078 6 4 0 0 394 3 164 561 7 5 0 0 195 1 82 279 9 6 0 0 92 1 39 131 10 7 0 0 1100 7 470 1577 11 8 0 134 853 185 151 1324 11 9 0 60 380 82 66 588 13 10 0 32 203 44 35 314 14 11 0 14 88 19 15 135 15 12 0 3 17 4 3 26 16 w 13 0 3 17 4 3 27 16 -00 Total 1896 1003 6449 354 1765 11468 136 Table 17. Burbot consumption in pounds by age class in Chequamegon Bay, Lake Superior, in 2001. A~e Crustaceans Crayfish Invertebrates Smelt Coregonines Other Fish Total by Population Total by Individual 1 834 8 182 143 52 1505 2723 1 2 1131 10 247 194 70 2041 3694 2 3 267 14 0 713 909 1243 3146 3 4 210 12 0 610 763 1023 2619 4 5 153 10 0 468 577 763 1971 5 6 105 7 0 334 409 536 1392 6 7 70 5 0 229 278 362 944 7 8 45 3 0 150 182 235 616 8 9 29 2 0 97 116 150 393 9 10 17 1 0 60 72 92 242 9 11 11 1 0 37 44 56 148 10 12 6 0 0 22 27 34 90 10 ...... (.;..) 13 4 0 0 13 15 20 51 11 \0 14 3 0 0 9 11 13 36 11 15 1 0 0 5 5 7 18 12 16 1 0 0 2 3 4 9 12 Total 2885 73 429 3086 3534 8085 18093 118 Table JS. Lake whitefish consumption in pounds by age class in Chequamegon Bay, Lake Superior, in 2001 Age Crustaceans Invertebrates Smelt Yellow Perch Coregonines Other Fish Total by Population Total by Individual 1 594 1105 0 0 0 1698 0 2 2006 3981 0 0 0 5987 2 3 3680 7622 0 0 0 11302 5 4 4780 9964 0 0 0 14744 9 5 5411 11318 0 0 0 16729 14 6 522 2113 9662 0 207 3303 15807 18 7 509 2053 9407 0 199 3186 15353 22 8 471 1898 8712 0 182 2931 14194 27 9 421 1692 7772 0 161 2602 12647 32 10 364 1463 6727 0 138 2244 10937 37 11 309 1238 5694 0 116 1893 9250 41 12 256 1026 4720 0 96 1566 7663 45 --+:- 13 209 838 3856 0 78 1277 6258 48 0 14 169 676 3113 0 63 1030 5051 52 15 134 535 2462 0 50 813 3993 54 16 106 423 1948 0 39 643 3158 57 17 83 332 1530 0 31 504 2481 59 18 66 262 1208 0 24 398 1958 61 19 51 202 931 0 19 307 1509 62 20 38 153 704 0 14 232 1141 64 21 29 117 538 0 11 177 871 65 22 24 95 436 0 9 144 707 66 23 18 72 332 0 7 109 537 67 24 14 57 261 0 5 86 422 67 25 10 41 188 0 4 62 304 68 26 8 33 151 0 3 50 245 68 Table J8 Continued. Age Crustaceans Invertebrates Smelt Yellow Perch Coregonines Other Fish Total by Population Total by Individual 27 6 25 114 0 2 37 185 69 28 4 17 77 0 2 25 124 69 29 2 8 38 0 1 13 62 69 Total 20293 49355 70581 0 1459 23630 165318 1317

...... j::,.