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Walleye and Sauger Life History



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Walleye and Sauger Life History
Mi c h a e l a. Bo z e k , Do M i n i c a. Ba c c a n t e , a n D ni g e l P. le s t e r
Chapter 7
The life history of an organism is the series of chronological events that it experiences in
order to survive, grow, mature, reproduce, and recruit to perpetuate the species. The genetic
characteristics of each individual and of the population as a whole helps determine whether
and how an organism responds to conditions in its environment to maximize its reproductive
success (i.e., fitness). More specifically, a combination of the morphological and physiologi-
cal traits allows organisms to respond to environmental conditions and dictates how it reacts
to environmental stochasticity and competition, predation, and prey. These environmental
conditions and ecological processes continually influence the genetic composition of a spe-
cies, and on the other hand, also provide the template with which it can interact with them.
In this chapter, life history events are chronicled as life stages, each having its own set of
challenges and benefits that walleye and sauger must face to be successful in their respective
environments. We first review the life history of walleye in detail and then synthesize our cur-
rent understanding on how this species demonstrates its ecological and evolutionary success
through its life history adaptations and approaches. We then briefly review the life history of
sauger and compare and contrast it to the major life history events of walleye.
Walleye and sauger are members of the family Percidae, which includes the darters,
freshwater perches, and zander (Sloss et al. 2004; see Chapters 2 and 3). They are found
in freshwater rivers systems and lakes throughout North America having their distribution
influenced by glacial events and further extended through stocking (see Chapter 4).Walleyes
have successfully adapted to habitats in a wide array of aquatic systems across North America
(see Chapter 5). They exist in rivers and lakes varying in geography, geology, and land use
across a wide latitudinal range, which greatly affects growing season and thus life history
strategies. The walleye has been described as a coolwater species but are found along a wide
environmental continuum reaching their maximum abundance in cool mesotrophic environ-
ments where summer maximum temperatures and oxygen concentrations are optimized for
the species (Niemuth et al. 1959; Kitchell et al. 1977). Hokanson (1977) suggested that wa-
ter temperatures must decline to at least 10°C for successful gonadal maturation in walleye
(see Chapter 6), which may impose distributional limits in southern latitudes. Kitchell et al.
(1977) believed that walleye optimized environmental conditions along a thermal continuum
that falls between warmer centrarchid-dominated systems and colder salmonid-dominated
2 Chapter 7
systems. Initially, walleye may have been a riverine species that colonized lakes through river
systems created by glacial meltwaters, but their current distribution indicates that they are
equally adapted to both lotic and lentic environments. This generalized habitation has been
facilitated by their unique adaptation of scotopic vision, enabling walleyes to forage effec-
tively in a dim-light environment. This scotopic vision allows efficient foraging after dark
and in environments that have high turbidity, which can apply to many warmwater riverine
environments in particular. Where water clarity is higher, scotopic vision allows efficient noc-
turnal foraging and, thus, results in a temporal niche that separates the walleye from other top
Across their geographic range, the localized distribution and abundance of walleyes is
affected by the fish community. In large lakes, walleyes can coexist with other top preda-
tors such as northern pike, muskellunge, lake trout, and smallmouth bass without intense
competition (Johnson et al. 1977; Marshall and Ryan 1987; Schupp 1992). In smaller lakes,
however, walleyes may not normally coexist at high densities with northern pike, smallmouth
bass, and other centrarchids (Johnson et al. 1977; Nate et al. 2003; Fayram et al. 2005). More
intense ecological interactions may be the reason for this distribution limitation. Kitchell et
al. (1977) believed that lakes smaller than 100 ha reduced the likelihood that walleyes could
persist with other top predators although they can persist in lakes as small as 30 ha (Wisconsin
Department of Natural Resources, Spillerberg Lake, unpublished data). Fayram et al. (2005)
found that in the presence of largemouth bass, walleyes have reduced standing stocks or may
be precluded from these systems altogether. In 15 Illinois reservoirs, survival of stocked lar-
val walleyes was negatively related to juvenile centrarchid densities (Hoxmeier et al. 2006),
which the authors attributed to predation.
In a geographic sense, walleye is the most successful freshwater top predator in North
America; its native distribution spans a latitudinal range that exceeds that of other top preda-
tors (e.g., lake trout, northern pike, burbot, muskellunge, smallmouth bass, largemouth bass)
and has a climatic gradient of approximately 4,000 annual growing degree-days greater than
5°C (Figure 7.1). The success of walleye is due partly to its preference for cooler water (see
Chapters 5 and 6). Across a broad latitudinal range, optimal growth conditions for coolwater
species exist at some point during the annual cycle. In contrast, optimal growth conditions
for warmwater or coldwater species exist over a smaller latitudinal range. The other factor
contributing to the broad success of walleye is the plasticity of its life history. As we demon-
strate in this chapter, life history traits such as growth, mortality rate, age and size at maturity,
and fecundity may vary widely among walleye populations. Much of this variation can be
explained by environmental factors that influence growth.
This chapter has four main goals: (1) describe the events that shape walleye life history;
(2) describe the variation that exists in walleye life history; (3) identify the major environ-
mental factors that account for this variation; and (4) apply life history theory to explain this
variation. We begin by providing an overview of the walleye life cycle, identifying key stages
and documenting variation in the duration of each stage. Details of each life stage (spawning,
egg, young of the year [i.e., age 0], juvenile, adult) are presented in section 7.2. For each life
stage, we summarize empirical findings about environmental factors that contribute to varia-
tion in traits. Our presentation of empirical findings builds on previous data syntheses (Colby
et al. 1979; Carlander 1997) by incorporating more recent data available in the literature and
in government databases (i.e., Ontario and Québec). Specific sources of data are identified in
the captions of figures.
Walleye and Sauger Life History
Figure 7.1. Growing Degree Days (GDD, °C) in North America and the native distributions of
walleye and sauger. Geographic distribution is based on maps in Scott and Crossman (1973).
The GDD data are based on New et al. (1999) and available at:
maps.php?datasetid = 31&includerelatedlinks = 1&dataset = 31.
4 Chapter 7
Subsequent sections take a more holistic view of the walleye life history variation and
offer an explanation that is based on natural selection. Because selection favors individuals
that maximize their fitness, the patterns we observe are expected to be optimal solutions to
environmental constraints. We focus on the lifetime growth pattern of walleye and show how
this pattern is shaped by reproductive traits and influenced by environmental factors affecting
growth potential and mortality rate. In a final section, we provide a brief synopsis of sauger
life history, of which much less is known, and contrast its life history with that of walleye.
7.2.1 Overview
The walleye is a relatively successful and plastic species having adapted to a wide ar-
ray of coolwater habitats in rivers and lakes over a large geographic area of North America
(Figure 7.2). Walleyes spawn in spring, just after ice-out in northern latitudes of their range,
and require minimum temperatures in winter to allow them to complete gamete maturation,
which limits their southern distribution. No parental care is provided and first-year survival
is low (generally <1%). Eggs hatch in 10–27 d (inversely related to water temperature; see
Chapter 13) and year-classes are inversely correlated to variation in spring water incubation
temperatures although causality is not well understood. Larvae quickly become free swim-
ming, and young walleyes go through ontogenetic shifts in diet as they increase in size (see
Chapter 8). As adults, they are primarily piscivorous although in some systems and, season-
ally, macroinvertebrates may constitute a substantial portion of their diet. Diet is variable and
depends upon prey availability in the system where they are located. Growth differs between
sexes. Size at maturity is not related to climate whereas age at maturity and longevity are
related to climate. Age at maturity ranges from 2 years in the south to 11 years in the north
and longevity ranges from 30 years in north to 5 years in south.
7.2.2 Spawning
In northern latitudes, walleyes spawn in the spring and may begin spawning under the ice.
In lakes, long-wave radiation warms water along the bottom in shallow areas or warmer water
from tributary streams starts to mix with lake water. Increasing temperature acts as a stimulus
to initiate spawning movements and migrations and spawning behavior (Eschmeyer 1950;
Rawson 1957; Preigel 1970). Timing varies with latitude, from late January in the extreme
south to June in the far north, and is influenced by both photoperiod and temperature (Scott
and Crossman 1973; Becker 1983; Malison and Held 1996). Photoperiod regulates the annual
egg and sperm maturation development cycle, whereas temperature induces actual spawning
activity. Water temperature during spawning typically ranges from about 5–7°C in the north
and 8–10°C in the south. In Savanne Lake, Ontario (48°N), annual trap netting on spawning
grounds from 1972 to 1994 produced the highest catches around 6°C that declined sharply
as temperature rose to 10°C (Colby and Baccante 1996). In fact, spawning runs into Oneida
Lake, New York, tributaries do not commence in years when tributary stream temperatures are
lower than lake temperatures (Forney 1967). And at the southern extreme of their range, wall-
eyes may not spawn if water temperatures do not cool sufficiently (Prentice and Clark 1978).
Walleye and Sauger Life History
In these cases, populations can only be sustained through stocking (Colby et al. 1979). While
spawning temperatures vary, they may only be plastic within a given time period of seasonal
maturation brought about by oogenesis, which is timed to photoperiod. In Lake la Ronge, Sas-
katchewan, walleye spawning runs begin at higher temperatures (7.2–11.1°C) in years when
spawning occurs early (April 30–May 7) whereas they spawned at colder temperatures (3.3–7
.2°C) in years when spawning was delayed by cold weather (May 17–21) (Rawson 1957; Ho-
kanson 1977). Similarly, in Lake Winnebago, Wisconsin, walleye spawning runs start sooner
in warmer tributary marshes (2.2–15.6°C) than in the larger colder lake (4–11.1°C) (Preigel
1970; see Chapter 5 for additional details on spawning temperature variation).
Walleye is categorized as a broadcast, simple lithophilous spawner (McElman 1983).
In lakes, walleyes typically spawn along shorelines in shallow offshore reefs, on point bars,
by islands, and on mid-lake reefs (Eschmeyer 1950; Raabe 2006). In rivers walleyes usually
spawn in rapids and riffles, where there is adequate flow and oxygen for egg development
(Walburg 1972; Stevens 1990). Walleyes may also spawn in less traditional, “unexpected”
habitats. For example, walleyes have been known to spawn in marshes on sedges and grass-
es in the Wolf River, Wisconsin (Preigel 1970; Minor 1980). They are generally nocturnal
spawners, although they spawn in daytime, particularly near peak spawning periods or when
light levels are low (Eschmeyer 1950; Ellis and Giles 1965). Because walleyes have highly
Figure 7.2. Graphical representation of variations in growth, maturation, and longevity of
walleye across its geographical range. Once walleye reach maturity, females grow larger than
males, as shown by the dotted line trajectory. Egg stage, maturity, and longevity are repre-
sented by the letters E, M, and L, respectively.
6 Chapter 7
reflective eyes, they are easily spotted on spawning shoals during the night using a strong
beam of light. Typically, males become ripe at cooler temperatures and arrive at the spawning
grounds before females and remain there longer after the females have left (Ellis and Giles
1965; Becker 1983). Consequently, the sex ratio on spawning grounds generally favors males.
Spawning behavior varies in systems but the pattern is generally representative. According
to Ellis and Giles (1965), males approach females, sometimes with alternating erected and
flattened dorsal fin, and push females from their side. This behavior, coupled with increasing
darting motion, attracts other fish. As the group grows, females release their eggs in bouts,
sometimes up to three times per minute. Males then release milt over the area where eggs are
7.2.3 Eggs
Walleyes are highly fecund and their eggs are small, averaging approximately 2 mm (1.3–
2.1 mm) in diameter (Smith 1941; Colby et al. 1979). Eggs are fertilized as they are deposited
onto spawning substrates and remain adhesive from 1 to 5 h or more. The adhesive properties
of the egg chorion may enhance fertilization of the eggs by keeping them closer to sperm
that is emitted from the males externally. Distance of the eggs from spawning males affects
fertilization; in laboratory studies, increasing depth of initially deposited eggs (i.e., depth of
layers of eggs that are clumped) relative to milt decreases egg fertilization. Eggs stacked 10
mm deep had a fertilization rate (i.e., percentage of eggs fertilized) of 65%, whereas eggs
stacked 7 mm had fertilization rates of 77% and eggs stacked 4 mm had fertilization rates of
86% (Moore 2003).
Once fertilized, water hardens the external membrane of the eggs, which eventually results
in the loss of adhesiveness; the length of time eggs remain adhesive is variable. In Lake Win-
nebago, eggs were adhesive for 1–2 h, but in hatchery investigations adhesiveness can last up
to 5 h while eggs are being stirred and some eggs may adhere to each other for up to 4 d (Krise
et al. 1986). Once walleye eggs lose their adhesiveness they can fall into interstitial spaces of
coarser substrate matrices or they can be carried from the spawning site by water currents and
deposited elsewhere. Fertilized eggs remain hyaline, translucent, and have a fairly firm and ro-
bust chorion during incubation. In contrast, unfertilized eggs or dead embryos develop a white
speck, eventually turning opaque and often developing a fungus (Saprolegnia spp.) initially
on the chorion before spreading (Eschmeyer 1950; Johnson 1961; Preigel 1970). Saprolegnia
kills the eggs by disrupting physiological processes of the developing embryo. As hatching
approaches, walleye embryos develop black eyes and the chorion begins to soften and deterio-
rate. Movement by active embryos eventually breach the chorion releasing the larval walleye
where they initially settle to the bottom or get carried away by currents.
The distribution of eggs within spawning areas is clearly heterogeneous. Raabe (2006)
mapped individual spawning locations (i.e., spawning pairs) across a shoreline spawning reef
in Big Crooked Lake, Wisconsin. He found individual egg patches (per individual spawning
bout) located in nearshore areas (generally <0.5 m depth) and few egg patches were found far-
ther than 5 m from shore despite similar physical habitat conditions other than slight increases
in depth. Williamson (2008) found the distribution of walleye eggs was discontinuous later-
ally both within reefs and among reefs despite sites exhibiting the same habitat conditions.
It is likely that these walleye spawning habitats were not saturated and without territoriality,
habitat selection reflects an ideal-free distribution (Fretwell 1972). Egg densities also vary
Walleye and Sauger Life History
across systems as a function of availability of suitable spawning habitat and adult population
size. Egg densities in lake spawning habitats averaged 1,545 eggs/m2 in Lake Winnebigosh-
ish, Minnesota (Johnson 1961) and ranged from 145 to 277 eggs/m2 on Sunken Chicken Reef
in Lake Erie (Fitzsimons et al. 1995). Egg densities were as high as 6,241 eggs/m2 in Ontario
streams (Corbett and Powles 1986). In contrast, degraded habitats may have low densities
unable to sustain natural recruitment as occurs in Saginaw Bay, Lake Huron, on historical
spawning sites (Fielder 2002). Walleye egg densities in these degraded, in-lake reef habitats
in Saginaw Bay were as low as 1 egg/m2 (Fielder 2002) and artificial reef habitat projects
(i.e., “restoration” or “enhancement” projects) often see no egg deposition (Neuswanger and
Bozek 2004; Williamson 2008).
The substrate matrix at the spawning site and other proximal substrates may play an im-
portant role in successful hatching. In lakes, Johnson (1961), Raabe (2006), and Williamson
(2008) found that walleyes used and selected spawning sites very close to shore in shallow
water over cobble and gravel substrates. In Lake Winnebigoshish, Johnson (1961) found that
hatching success was higher on coarser substrates compared with finer substrates; walleye
eggs incubating on muck and detritus substrates had the poorest survival (0.6–4.5%), fol-
lowed by sand (2.7–13.2%) and gravel–rubble (17.5–34.3%). Similar findings have been cor-
roborated by Eschmeyer (1950), Preigel (1970), and Busch et al. (1975). Nate et al. (2003)
found that the relative abundance of sand and silt in littoral zones of Wisconsin lakes was
inversely related to walleye standing stocks. In years when water levels recede in lakes and
coarser shoreline substrates are exposed, walleyes may spawn on less-favorable, smaller-sized
substrates that accumulate offshore. Weak year-classes were observed under these conditions
in Lake Winnibigoshish (Johnson 1961) and in Rainy Lake, Ontario–Minnesota (Chevalier
1977). While a majority of walleyes reportedly spawn over coarser substrates, some indeed
spawn over smaller substrates such as sand on shallow flats despite widespread availability
of coarser substrates as they do in Big Crooked Lake, Wisconsin, although survival was not
assessed (Raabe 2006). Walleyes, however, can successfully spawn on other substrates. In the
Wolf River, Wisconsin, walleyes spawn on flooded marsh vegetation where water flow con-
tinues to oxygenate eggs and they consistently produce large year-classes (Preigel 1970), and
Niemuth et al. (1972) found walleyes spawning on root masses along lake shores of Tumas
Lake, Wisconsin.
The presumed benefit of larger rock substrates, such as gravel and cobble that have lower
embeddedness, is that they provide interstitial spaces for eggs to settle into after they lose
their adhesiveness, thus protecting them from siltation, entrainment and transport currents,
abrasion, and predation. During transport, eggs can be abraded, which may increase the rate
of bacterial and fungal infections that can kill incubating eggs (Oseid 1977). Because walleye
eggs are located in shallow lake water where wave energy is highest, they can be transported
from spawning sites and then deposited laterally, offshore, or even onshore. In particular,
large storms create wave energy that readily transports eggs away from spawning areas. For
instance, Raabe (2006) found in lakes that water velocities produced from nearshore wind-
wave energy were high enough to move walleye eggs in a spawning area 19% of the time
while eggs were incubating there. At that same site, velocities were high enough to entrain
and move heavier sand particles 5.5% of the time while eggs were incubating, potentially
abrading or burying them. As a result, walleye eggs have been found incubating away from
spawning sites in Big Crooked Lake on sand flats adjacent to spawning areas where no spawn-
ing actually occurred, but where wave action transported them to that location (Raabe 2006).
8 Chapter 7
Johnson (1961) observed walleye eggs stranded along the shores of Lake Winnebigoshish af-
ter spring storms. Roseman et al. (2001) found that the number of walleye eggs removed from
spawning sites was dependent on the quality of spawning sites and intensity of wind-wave
energy in Lake Erie; sites with greater interstitial spaces retained more eggs during storms.
Roseman et al. (2001) observed the loss of 80% of walleye eggs from spawning reefs after a
gale-force storm; under those conditions, more eggs were removed from shallow portions of
the reef than from deeper portions. In rivers, larger substrates may be even more important.
Walleyes spawn at velocities between 0.4 and 1.0 m/s, although caution should be applied to
data from faster velocities as measurements may not all be nose (i.e., fish position) velocities
(Paragamian 1989; Stevens 1990; Liaw 1991; Ichthyological Associates 1996; VanderKooy
and Peterson 1998). Even higher velocities have been reported for walleye spawning (see
Kerr et al. 1997). At these consistent higher velocities in lotic environments, interstitial spaces
undoubtedly protect eggs by reducing abrasion and preventing their transport to suboptimal
incubation locations.
While severe wave action is often detrimental to egg survival, slight water movement
across spawning sites is desirable because it oxygenates eggs while preventing sedimenta-
tion (Daykin 1965; Oseid and Smith 1976). In assessing embryonic anatomy and physiology
of walleye, McElman (1983) observed that the temporary embryonic respiratory system is
geared to high levels of dissolved oxygen in water. Kitchell et al. (1977) believed that river-
and lake-analogous features of slight water movement allowed walleyes to be successful in
reproducing in both environments. In many lakes and rivers, this is achieved by spawning
on larger, coarse-grained substrates primarily of gravel and cobble where some water move-
ment occurs within the matrix. Also in lakes, walleyes spawn in shallow water (<1.0 m and
primarily <0.5 m deep) very close to shore or on submerged shoals where water movement is
common (Eschmeyer 1950; Johnson 1961; Raabe 2006). In rivers, walleyes spawn in riffles
where water moves across incubating eggs. In some rivers such as the Wolf River system in
Wisconsin, walleyes spawn on submerged cattail beds that create “mats” (Preigel 1970) in
which sheet-flow water moves across and through the beds providing oxygen for the develop-
ing embryos.
Larger substrates for egg incubation may also reduce access by predators. Predation on
walleye eggs in aquatic systems is common, although population-level effects have not yet
been substantiated to the point of showing that it negatively affects recruitment thus far, but
it is possible. Interstitial spaces in coarser substrates, such as gravel and cobble, afford some
protection to walleye eggs from predators. White sucker, a common sympatric species in
walleye-inhabited lakes and rivers, are often seen in walleye spawning areas but do not appear
to target walleye eggs for predation (Preigel 1970; Wolfert et al. 1975; Corbett and Powles
1986). In many systems, white suckers begin to spawn in proximal areas as walleye spawning
ends, so their presence may merely be coincidental. Corbett and Powles (1986) found yellow
perch and spottail shiners preyed on walleye eggs but did not assess effects on overall wall-
eye recruitment. Wolfert et al. (1975) found that yellow perch, spottail shiners, stonecat, and
white suckers preyed upon walleye eggs in Lake Michigan although yellow perch were the
predominant predators. Roseman et al. (1996) found that 86% of white perch contained wall-
eye eggs in their stomachs in Lake Erie. Both Wolfert et al. (1975) and Roseman et al. (1996)
felt that predation might only be a problem in years with low temperatures and slow warming
rates where eggs would be exposed to predation for extended periods and when white perch
spawning would overlap to a greater extent with walleye spawning. In those years, spent white
Walleye and Sauger Life History
perch in spawning areas would increase predation rates on walleye eggs as they begin to feed
after spawning.
Walleye typically exhibit high egg mortality. Eggs are broadcast over substrates without
any site preparation or parental care (e.g., egg fanning, protection from predation) as occurs
in centrarchids and other fishes. Egg survival estimates from fertilization through hatching
in Lake Goegebic, Michigan, ranged from 25% to 50% (Eschmeyer 1950). Johnson (1961)
estimated egg survival ranged from 0.6% to 35.7% among sites in Lake Winnibigoshish, Min-
nesota, and Engel et al. (2000) reported artificially fertilized egg survival rates in incubation
chambers held in situ in Escanaba Lake, Wisconsin, ranged from 19% to 62%. In Oneida
Lake, Forney (1976, 1977) estimated 99% mortality occurred before walleye reached 10 mm
and believed most mortality occurred during the egg stage. Egg survival rates in Lake Erie
have ranged from 7% to 43% (Roseman et al. 1996).
Interannual variation in larval production (Johnston et al. 1995) may be due in part to the
quality and quantity of eggs produced in any given year, which are related by the size and size
structure of the spawning population (Johnston 1997). Hatching success of eggs is positively
related to female age and negatively related to female length adjusted for age (Johnston 1997;
Johnston et al. 2007). Some research suggests that most mortality in walleye eggs is evident
within the first several days after spawning; eggs at this time are either unfertilized, not vi-
able, or very sensitive to environmental perturbation (Fox 1993; Holtze and Hutchinson 1989;
Heidinger et al. 1997). For example, Heidinger et al. (1997) found that 83% of walleye egg
mortality occurs within 6 h of fertilization. Latif et al. (1999) found that 80% of the mortality
in walleye eggs incubating at 10°C occurred at 50–100 h after fertilization (21–42 thermal
units [TU = number of days postfertilization × temperature, °C]).
Environmental effects on eggs during incubation are believed to greatly influence mortal-
ity and thus year-class strength in walleyes, although understanding factors directly causing
stock–recruitment relations in natural systems needs more research. Survival of walleye eggs
in natural systems is initially the result of a combination of suitable incubation temperatures
and well-oxygenated water. The influence of temperature and oxygen, as well as other factors,
including pH, aluminum ion, and fine sediment, have been studied under laboratory condi-
tions and observed in nature, but effects of temperature and oxygen predominate. Cooler wa-
ter temperature negatively affects egg development rates, thus increasing the amount of time
eggs are subject to other sources of egg mortality such as predation, spread of fungus, wave
action and abrasion, and transport to unsuitable substrates. However, while water temperature
fluctuations influence year-class strength, there does not appear to be a direct physiological
basis for direct mortality on eggs from temperature fluctuations under natural conditions. In
fact Koonce et al. (1977) concluded that only under extreme climatic conditions in Lake Erie
could lethality be directly attributed to temperature. Engel et al. (2000) found no relation be-
tween in situ hatching success and water temperatures in Escanaba Lake from 1985 to 1992.
Extended water temperatures below 6°C or above 19°C, however, can be lethal to developing
walleye embryos (Smith and Koenst 1975; Schneider et al. 2002). Latif et al. (1999) found
that 80% of the mortality in walleye eggs incubated at 10°C occurred at 50–100 h posthatch
(21–42 TU) when germinal layers of cells are transformed into various body organs; it is at
this time that walleye eggs might be most susceptible to sources of mortality.
The reasons for a lack of temperature fluctuation-associated mortality are twofold. First,
walleye eggs are resilient to most water temperature fluctuations they may encounter in na-
ture during spring spawning and incubation periods. Moreover, because walleyes spawn near
10 Chapter 7
ice-out in northern latitudes, the species clearly has evolved to allow eggs to survive at low
water temperatures. In the laboratory, Allbaugh and Manz (1964) found development and
survival of embryos to the eyed stage was unaffected by temperature fluctuations as high as
21°C. Schneider et al. (2002) found no increase in mortality occurring to the eyed stage when
eggs were subjected to either a 20°C temperature fluctuation in12 h or when eggs were then
returned to 10.5°C in 8 h. In the same study, percent hatching success was also not affected
by temperature swings of nearly 14°C. Second, the latent heat of water (energy resistance to
temperature change) is too high to allow temperatures to fluctuate to the degree they would
need to in order to kill incubating eggs in spawning areas. For instance, Raabe (2006) found
that variation in temperatures along a depth profile of a walleye spawning area (0–2 m deep)
in a northern Wisconsin lake were usually less than 2°C in any 24-h period and in 2 years no
temperatures in these shallow spawning areas ever dropped more than 4°C across the entire
spawning season; thus, no temperatures at any depth ever approached lethal conditions.
Temperature does influence fertilization and embryonic development rates. Koenst and
Smith (1976) found that optimum fertilization rates occurred at 6–12°C in laboratory studies,
which corresponds to the temperatures often observed at spawning sites in nature (Niemuth et
al. 1959; Preigel 1970; Hokanson 1977). On the other hand, optimum incubation temperatures
for eggs ranged from 9–15°C with peak hatching occurring at 15°C (Koenst and Smith 1976;
Engel et al. 2000). In both laboratory and field studies, egg development rates increase with
increasing water temperature (Johnson 1961; Preigel 1970; Koenst and Smith 1976). Colby
et al. (1979) reported on work by W. L. Hartman (unpublished data) using data from four dif-
ferent studies to correlate progress to 50% hatching based on average incubation temperature.
The resulting equation: y = –5.481 + 1.062x, where y is 100/d to the mid-hatch time and x is
the average incubation temperature in °C, describes this relationship. In Savanne Lake, On-
tario, using Hartman’s equation and measuring water temperatures on the spawning grounds
from 1972 to 1991, we estimated the number of days to 50% hatching ranged from 10 to 26
d, with a mean of 18 d (authors’ unpublished results). Incubation to swim-up periods have
been reported to range from 10 to 27 d under natural conditions (Niemuth et al. 1959; Johnson
1961; Preigel 1970; Engel et al. 2000) and from 5 to 30 d in laboratory settings (Hurley 1972;
Koenst and Smith 1976; McElman and Balon 1979).
Standardized approaches to predict hatching times incorporate thermal units (TU), which
are the sum of the mean daily water temperatures above 0°C from fertilization through hatch-
ing (see Chapter 13). McElman and Balon (1979) found that at 15°C, walleye embryo eye
pigmentation was observed at 76 TU and hatching at 135 TU (approximately 9 d). At lower
and more variable water temperatures (7.8–11.1°C), Hurley (1972) observed hatching from
257 to 265 TU. Jones et al. (2003) developed an equation for describing the percent of daily
embryonic development as follows: y = 0.0479T2 – 0.2385T + 2.499 based on work by Smith
and Koenst (1975) where y is the predicted percent of development per day towards hatching
and T is the mean daily water temperature in °C; values of y are summed for each day and
when y reaches 100, hatching occurs.
Other characteristics of incubation sites can reduce or inhibit successful hatching of wall-
eyes. Oxygen concentrations above 5–6 mg/L are optimal for walleye egg incubation and
survival (Oseid and Smith 1971; see Chapter 6) although Colby and Smith (1967) reported
successful, albeit reduced, hatching occurred at levels less than 3 mg/L. Auer and Auer (1990)
believed that low dissolved oxygen, along with elevated ammonia nitrogen and hydrogen sul-
fide at the sediment–water interface in the Fox River, Wisconsin, precluded successful incuba-
Walleye and Sauger Life History
tion and hatching. Locations with surficial sediment chemical oxygen demand (COD) greater
than 40 mg O2/g dry weight were not deemed suitable for walleye egg incubation. Ammonia
(NH3) concentrations greater than 29 µg/L are deemed chronically unsuitable for walleye
reproduction (USEPA 1976, 1987). Presumably, areas that have gravel–cobble substrates and
moving water and are generally selected for spawning, reduce the occurrence of these adverse
microhabitat conditions
Recent studies indicate that hatching success in walleye depends partly on the number of
eggs produced (i.e., density-dependent survival) as well as maternal factors affecting the qual-
ity of eggs. Evidence of density-dependent survival was provided by Johnston et al. (1995)
who showed variation in hatching success was related to annual variation in egg production.
Maternal influences on egg and larval survival have been demonstrated in laboratory studies
(reviewed by Venturelli et al. 2010b). Both maternal age or size (Johnston 1997; Johnston et
al. 2007) and egg quality (e.g., egg size, lipid content; Moodie et al. 1989; Czesny and Dab-
rowski 1998; Johnston et al. 2007) have positive effects on the survival of eggs and larvae. Egg
size has cascading effects because it is positively related to larval size (Moodie et al. 1989;
Johnston 1997; Johnston et al. 2007), which, in turn, increases survival through negative ef-
fects on cannibalism, deformities, and starvation (Moodie et al. 1989; Johnston and Mathias
1993, 1996). Johnston (1997) found that hatching success in the laboratory was positively
related to female age and negatively related to female length adjusted for age. In field studies,
Craig et al. (1995) reported higher survival of walleye eggs from females that were older and
smaller at age. Pond experiments (Venturelli et al. 2010b) have shown a positive effect of egg
size on larval survival after 2 months.
These findings imply that the size and age structure of the spawning population have com-
plex effects on offspring survival. Recent research highlights the value of older fish in contrib-
uting differentially to recruitment of fish in general (Kamler 2005; Venturelli et al. 2009) and
of walleyes in particular (Johnston 1997; Johnston et al. 2007; Venturelli et al. 2010b). Hansen
et al. (1998) found that the abundance of walleyes age 5 and older were the most descriptive in
estimating recruitment success in Escanaba Lake. Similarly, Venturelli et al. (2010b) found that
the maximum recruitment rate of walleyes in western Lake Erie approximately doubled when
the abundance of female walleyes age 5 and older increased from 7% to 21%. These studies
underscore the value of older females to recruitment processes. Research by Casselman et al.
(2006) also suggests that there is considerable variation in the quality of male walleye sperm.
This variation in sperm quality can affect fertilization rates, although its relation to age is not
known. In their laboratory studies, male walleyes with the fastest swimming sperm had fertil-
ization rates 40% greater than males with the slowest swimming sperm.
7.2.4 Age 0 (Hatch to Age 1) Habitat Selection and Feeding
At hatching larvae are 6–9 mm total length (TL) at the caudal fin fold (Preigel 1970; see
Chapter 13). Because walleyes hatch without a full complement of fins and fin rays (McElman
1983), they are still technically considered embryos (McElman and Balon 1979; McElman
1983) until they develop further. Fin ray ossification begins at 10 mm TL and is complete by
18 mm (Nelson 1968a). Scale development begins at 24 mm and is complete by 45 mm (Pre-
igel 1964). Adult coloration is developed at about 35 mm (Nelson 1968a).
12 Chapter 7
Age-0 walleyes are ineffective swimmers and can only withstand low water velocities
(Walburg 1971). Immediately after hatching, larvae are not free swimming but rather lay on
the bottom occasionally moving into the water column. Generally embryos remain sedentary
for only a short time (<1 d), making irregular and uncontrolled movements at first but then
quickly learning to swim (Becker 1983). Without air in their swim (gas) bladder initially,
they are negatively buoyant at first, with their negative buoyancy contributing to their initial
sporadic and erratic movements.
Because larvae are not free swimming immediately after hatching, they are subject to
water currents caused either by wind–wave interactions in lakes or hydraulic current pat-
terns in streams. The interaction between the strategy of drifting larvae in water currents and
their successful transport to suitable nursery areas underlies the successful coupling of two
sequential life stage habitat interactions. Raabe (2006) found that water velocities along a
shoreline spawning shoal in Big Crooked Lake exceeded levels that could induce transport
of eggs up to 19% of the egg incubation period and probably are of a magnitude to influence
the movements of free-swimming larvae. Jones et al. (2003) found a decrease in survival of
drifting age-0 walleyes with increasing drift distance to nursery habitats. In Lake Erie, water
currents carry age-0 walleyes to rearing habitats (Nepszy et al. 1991), and Roseman et al.
(2005) found that currents in Lake Erie concentrate zooplankton along with larval walleyes,
making these areas good foraging localities. Clearly water currents influence the fate of very
young walleyes. High discharge events such as flooding in rivers can also trigger downstream
movement of age-0 walleyes (Harvey 1987), although the ecological consequences of these
events are not clear.
Walleye embryos hatch with limited yolk and, as a result, need to start feeding soon
after hatching; in fact feeding begins before their yolk sacs are completely absorbed (Engel
et al. 2000). Initial diet items include small zooplankton such as rotifers, copepods, nauplii,
small cladocerans, Chaoborus spp., and chironomids (Mathias and Li 1982; Engel et al. 2000;
Galarowicz et al. 2006; Hoxmeier et al. 2006; see Chapter 8). Prey density probably affects
growth and survival of age-0 walleyes as food limitations can result in cannabilism and star-
vation in some systems (Chevalier 1973; Jonas and Wahl 1998). In Lake Erie, pelagic larval
walleyes show high spatial overlap with ichthyoplankton density (Roseman et al. 2005). For
postswim-up age-0 walleyes, the timing of initial spring phytoplankton blooms and the result-
ing production of zooplankton that feed on the phytoplankton may be crucial to walleyes at
this stage If phytoplankton growth is delayed, in turn reducing zooplankton density until after
larvae emerge, young walleyes may starve. The extent to which that occurs in natural systems
is unknown.
Once free swimming, walleyes are believed to move out into open water in some systems
to begin openly feeding, primarily on zooplankton (Eschmeyer 1950; Faber 1967; Morsell
1970; Mathias and Li 1982). In Escanaba Lake, age-0 walleyes shifted their habitat use in
late June (at 35 mm TL) from pelagic to littoral zone habitats (Engel et al. 2000). Initially
in spring, sampling near the water surface with tow nets produced greater catches of age-0
walleyes than did deeper tows; after mid-June, walleyes made night movements near shore
where they could be captured by seining at night. In contrast, in Big Clear Lake, Ontario,
age-0 walleyes initially used areas of high macrophyte abundance in waters from 2 to 5 m
deep (mid-June to mid-July), later shifting to areas of low cover complexity (mid-July to late
August) (Pratt and Fox 2001). Those authors believed the shift in habitat choice may have
been related to attempts to avoid predation by adult walleyes. However, some studies suggest
Walleye and Sauger Life History
that when young walleyes inhabit macrophyte beds, they may also be inhabited by largemouth
bass where they may get preyed upon; the inverse relations in abundances of walleyes and lar-
gemouth bass provide some circumstantial evidence of this possibility (Fayram et al. 2005).
Quist and Guy (2004) found that larval walleyes 5–7 d old (initial swim-up) did not respond
to simulated predator attacks whereas larval saugeyes (walleye × sauger hybrids) did; but at
12–14 d they both showed avoidance behavioral responses. In rivers, recently hatched wall-
eyes migrate downstream with stream currents and increase their drift rates during periods of
low light (i.e., cloudy nights or small moon stages). In northern Ontario, age-0 walleyes ap-
pear to orient more to prey items than specific habitat types (Leis and Fox 1996).
Walleye clearly undergo ontogentic shifts in diet and at each life stage consume the most
profitable diet items available (Galarowicz et al. 2006; see Chapter 8). During their first year
of life, walleye feeding switches from zooplankton to benthic invertebrates and then to fish
(Forney 1966; Colby et al. 1979; Mathias and Li 1982; Fox 1989; Fox et al. 1992; Madon
and Culver 1993; Chapter 8). Target prey size increases as walleye grow; gape width limits
prey size (Preigel 1970; Hokanson 1977; Serns 1982; Engel et al. 2000). Bremigan and Stein
(1994) clearly articulated the necessary link between gape width, available zooplankton size,
and recruitment dynamics in fish. The onset of piscivory in walleyes typically occurs between
50 and 80 mm (Smith and Moyle 1945; Smith and Pycha 1960; Walker and Applegate 1976),
but has been observed in postlarval walleyes (Li and Mathias 1982) and age-0+ walleyes as
small as 30 mm (Maloney and Johnson 1957) and as large as 100 mm (Li and Ayles 1981a,
1981b; Kolar et al. 2003). Smith and Pycha (1960) found walleyes shifting to larger prey than
zooplankton at 60 mm TL. In Escanaba Lake, some walleyes consumed prey fish within 2
weeks of hatching, although it was a minor part of their diet (Engel et al. 2000). Similar diet
shifts are observed in zander (pikeperch), a close relative of walleye in European waters. For
example, Van Densen et al. (1996) reported that zander in a lake in The Netherlands fed exclu-
sively on zooplankton until they reached a length of 40 mm, at which point they began feeding
on macroinvertebrates and fish; zanders larger than 70 mm fed exclusively on fish.
Graeb et al. (2005) conducted laboratory experiments to compare the ontogeny of pis-
civory in walleye (a specialist piscivore) and yellow perch (a dietary generalist). Walleyes of
all size classes (20–80 mm) exhibited piscivorous behavior, whereas yellow perch showed
negative to neutral selection for fish prey and slower growth than did walleyes when feeding
on fish. Walleyes foraged more efficiently than yellow perch on all prey types, in part because
gape widths of walleyes increased more quickly with body size. Galarowicz et al. (2006)
examined diet shifts in age-0 walleyes (20–150 mm) through experiments in which zooplank-
ton, benthic invertebrates, and fish were made available at different density combinations.
Consumption of each prey type changed with walleye size and prey densities. Small walleyes
(20 mm) selected zooplankton and fish, whereas larger walleyes (40–100 mm) selected ben-
thic invertebrates and fish. Walleyes larger than 100 mm selected only fish. This study also
revealed that walleye growth can be sustained on benthic invertebrates if they are abundant,
but not on zooplankton; walleyes larger than 40 mm actually lose weight when feeding ex-
clusively on zooplankton. (See Chapter 8 for additional discussion of diets and ontogenic diet
Ontogenetic diet shifts in walleye are accompanied by changes in retinal structure that en-
hance scotopic (dim light) vision and affect habitat selection (Ali and Anctil 1977; Braekevelt
et al. 1989; Vandenbyllaardt et al. 1991). The tapetum lucidum, a light-reflecting layer of the
retina that increases retinal sensitivity (Craig 1987), is present when fish are 37 mm long and
14 Chapter 7
fully developed when walleyes are 140 mm long. Aggregation of photoreceptor cells to form
macroreceptors, which are believed to increase acuity in dim light, begins when walleyes are
approximately 60 mm long. Before the development of the tapetum lucidum, walleye are
positively phototactic at ambient daytime illumination levels and frequent the limnetic zone,
feeding mainly on zooplankton (Houde and Forney 1970). At this stage, walleyes may be at-
tracted to surface waters at night by the use of an artificial light (Regier et al. 1969). Labora-
tory studies have shown that the phototactic response shifts from positive to negative when
walleyes are 32–40 mm long (Bulkowski and Meade 1983). In nature, walleyes 25–30 mm
long frequent the littoral zone and are sometimes found in shallow sheltered bays, but wall-
eyes gradually move from littoral shoals into deeper water as summer progresses (Raney and
Lachner 1942). This habitat shift, which is correlated with the development of scotopic vision,
indicates a continuing adaptation to progressively decreasing light intensities (Ryder and Kerr
1978). Early development of scotopic vision permits young walleyes to exploit dimly lit en-
vironments not used by other predators, thereby enabling relatively rapid growth during their
first year of life. First-year Growth
The optimum temperature given by Smith and Koenst (1975) for growth of small wall-
eyes (65–87 mm) is 22°C; however, there is some disagreement with respect to a precise
value and an optimum range around this value may be more appropriate depending on other
environmental conditions (see Chapters 6 and 13). First-year growth of walleyes is highly
variable among populations, but much of this variation can be explained by thermal differ-
ences (Figure 7.3). This effect was first reported by Colby and Nepszy (1981) who used an
agricultural index of thermal energy to explain latitudinal variation in first year growth of
walleye. This index, mean growing degree-days above 5°C (GDD), uses daily measures of
maximum air temperature to calculate the cumulative degrees above 5°C during an annual
cycle. Colby and Nepszy (1981) showed that mean TL at first annulus increased with GDD,
ranging from approximately 100 mm at GDD = 1200°C (northern Ontario) to 240 mm at
GDD = 4000°C (southern United States). As illustrated in Figure 7.3, first-year growth is ap-
proximately the same for both sexes (Figure 7.3A) and 72% of among-population variation in
growth is explained by GDD (Figure 7.3B). Residual variation is expected due to differences
in food availability and, thus, consumption rates among populations. Because food consump-
tion combines multiplicatively with temperature in determining growth rate (e.g., Kitchell et
al. 1977) residuals are expected to increase with GDD, as illustrated in Figure 7.3B. First-year Survival
Data from a few well-studied walleye populations imply that average survival from egg to
age 1 is in the order of 0.01% (Baccante and Colby 1996). The vast majority of eggs depos-
ited each year do not contribute to the age 1+ walleye population because many eggs are not
fertilized, fail to hatch, or age-0 fish die as a result of predation, starvation, or disease. Fall
surveys of age-0 walleye abundance are often conducted on intensively managed lakes be-
cause they provide an index of year-class strength that forecasts harvest potential. For instance
Serns (1982, 1983) found that electrofishing catch per unit effort (CPUE) was related to the
density of young walleyes in northern Wisconsin lakes. Johnson (1999) was able to signifi-
Walleye and Sauger Life History
050100 150 200 250300 350400
Female length at age 1 (mm)
Male length at age 1 (mm)
Growing Degree Days (
Total length at age 1 (mm)
Figure 7.3. First-year growth of walleye. Total length at age 1 is mean back-calculated length
at first annulus. Points are estimates for 38 populations reported in Colby et al. (1979) or
Carlander (1997) for which sex-specific data were available. In panel (A), male estimates are
plotted against female estimates to demonstrate that first-year growth does not differ among
sexes. In panel (B), mean length at age (i.e., average of male and female estimates) is plotted
against GDD, demonstrating that first-year growth increases with GDD: mean length = 25.6
+ 0.066 GDD (r2 = 0.72). GDD values for each population were supplied by Yingming Zhao,
Ontario Ministry of Natural Resources (see Zhao et al. 2008), based on interpolation of the
IPCC 1961–1990 climate normals for North America.
16 Chapter 7
cantly establish that fall age-0 walleye abundances forecasted future years-classes in northern
Wisconsin lakes. These studies also indicate high annual variability in fall abundance of age-0
walleyes. Because annual variability in egg production (based on estimates of spawner abun-
dance and fecundity) is low relative to variability in the fall abundance of age-0 walleyes, it is
usually assumed that variability in year-class strength is mainly due to variability in survival
during the first year.
First-year survival is expected to be highly variable because a large number of abiotic and
biotic factors influence young walleye survival. Abiotic factors associated with walleye re-
cruitment include water temperature, wind, and water level characteristics (Eschmeyer 1950;
Johnson 1961; Hokanson 1977). Biotic factors include competition, cannibalism, and inter-
and intraspecific predation. Probably the most important abiotic factor is water temperature.
Its importance was first noted by Forney (1976) who found that spring warming influenced
year-class strength in Oneida Lake. More recent studies have shown that spring temperatures
influences year-class strength in Lake Erie (Madenjian et al. 1996) and in Escanaba Lake
(Hansen et al. 1998). Moreover, year-class strength in walleyes appears to be a regional phe-
nomenon (Beard et al. 2003); for lakes within a geographic region, variation in year-class
strength was correlated among lakes, suggesting a common environmental determinant such
as temperature.
Temperature affects many processes that influence survival during the first year of life.
Spring water temperatures alter the timing of spawning and the duration of egg incuba-
tion (Busch et al. 1975), which in turn affects the length of time that eggs are exposed to a
variety of environmental stressors. Temperature conditions during the spring and summer
affect growth and, consequently, vulnerability to predation. It is not surprising, therefore,
that first-year growth is sometimes correlated with year-class strength. For zander, Buijse
and Houthuijzen (1992) observed that year-class strength in Lake Ijssel, The Netherlands,
varied 300-fold over the period 1966–1989 and both mean length and year-class strength
in November were highly correlated with mean summer temperature, and thus, with each
other. In contrast, Madenjian et al. (1996) observed in Lake Erie that first-year growth was
poorly correlated with recruitment. The major determinant of recruitment was abundance of
an important prey species (gizzard shad) during the fall before spawning. This result implies
that adequate lipid reserves during the winter are needed to support egg production in the
following spring. It suggests that recruitment variability is not due solely to variation in first-
year survival; variation in egg production may also play a role. More direct evidence was
provided by Henderson and Nepszy (1994) who observed variation in year-class strength in
Lake Erie was associated with energetic condition of the spawning stock (see also Henderson
and Morgan 2002).
A potential side effect of slow growth in age-0 walleyes is size-dependent winter mortal-
ity. While common in other species (Shuter et al. 1980; Post and Evans 1989; Bernard and
Fox 1997), the effect of body size on winter mortality is somewhat equivocal for walleye.
Copeland and Carline (1998) found no relation between lipid storage and overwinter survival
of walleyes in hatchery ponds. Pratt and Fox (2002) did not detect an effect on overwinter
survival, but found body weight and lipid concentrations were lower in ponds where predators
were present, suggesting that there may be energetic costs associated with avoiding preda-
tion. Pratt and Fox (2002) believed that overwinter survival was enhanced in walleyes due
to a combination of (1) larger size in the fall relative to other north temperate fishes and (2)
continued feeding during winter months (see also Kelso 1972).
Walleye and Sauger Life History
Biotic factors also affect age-0 survival and recruitment in walleye. Competition with
other species for shared food resources may constrain growth rate, prolonging the period of
high vulnerability to predation. While they are small, walleyes are potential prey for many
cohabitant fishes including yellow perch, smallmouth bass, rainbow smelt, sauger, bullhead,
burbot, northern pike, and others (Colby et al. 1979). In some lakes, cannibalism has also been
identified as an important source of predation (e.g., Forney 1980). The importance of biotic
factors relative to abiotic factors is hard to quantify, but some recent work has indicated that
biotic interactions can have an overriding influence on walleye recruitment (Quist et al. 2003a,
2004). Quist et al. (2003a) proposed a biotic–abiotic confining hypothesis (BACH) to explain
the role of abiotic and biotic mechanisms on walleye recruitment. This study examined the
impact of white crappies on walleye recruitment in Kansas reservoirs. During years with low
white crappie abundance, walleye recruitment was highly variable and probably confined
by abiotic factors. However, when white crappie abundance surpassed a threshold, walleye
abundance was always low. In Wisconsin lakes, Fayram et al. (2005) found the abundance of
largemouth bass was negatively related to the abundance of walleyes in Wisconsin lakes.
These studies suggest that predation can have an overriding influence on first-year sur-
vival and, thus, walleye recruitment. Quist et al. (2003a) point out that an important theory
regarding the native distribution of percids in North America states that interactions with
centrarchids restricted their success in southern latitudes (Collette et al. 1977). Several stud-
ies demonstrate that walleye recruitment is generally poor when centrarchids are a dominant
member of the fish community (Schiavone 1985; Santucci and Wahl 1993). In the Kawartha
Lakes, Ontario, where walleyes were previously dominant, increasing water temperature and
clarity in recent years has favored centrarchids and dramatic declines in walleye abundance
have occurred (Robillard and Fox 2006). Mechanisms driving the decline in walleyes have
not been identified, but it seems likely that centrarchid predation on young walleyes may be
an important factor.
7.2.5 Juvenile (Age 1 to Maturation) Habitat Selection and Feeding
The juvenile life stage in walleye is a period of relatively rapid growth, whose duration
varies inversely with growth rate. Minimum size of maturity is approximately 300 mm TL
in males and somewhat larger in females. In the south, where growth is more rapid, this size
threshold may be attained within 2 years, but in some northern lakes where growth is slow, the
juvenile life stage may exceed 10 years (Venturelli et al. 2010a).
Habitat selection of yearling and subadult walleyes appears to match that of adults (Ryder
1977). Preferred water temperature is in the range of 20–24°C (Coutant 1977; Wismer and
Christie 1987) and based on other published studies, Christie and Regier (1988) concluded
that optimum temperature for walleye growth is 18–22°C. Preferred light intensity was esti-
mated as 8–68 lx by Lester et al. (2004a), based on observations reported by Scherer (1971)
and Ryder (1977). Suitable dissolved oxygen concentration has been reported as greater than
3 mg/L although increased opercular venting can occur at 6 mg/L (Petit 1973) (see also Chap-
ters 5 and 6).
The importance of light to walleye behavior was first investigated by Ryder (1977). Div-
ing observations in Ontario lakes indicated that yearling, subadult, and adult walleyes often
18 Chapter 7
swam together in small to medium size schools (i.e., 3–150 fish) and that these three age
categories reacted almost uniformly in movements and feeding behavior under various light
intensities. Because of their high sensitivity to light, walleyes were often observed to be rest-
ing during daytime illumination, partially concealed in the interstices of boulder shoals or in
cover of dense aquatic vegetation, sunken logs, or other debris on lake substrates. Daytime
transects conducted in waters of different transparency indicated that walleyes were less ac-
tive in clear waters. Angling experiments demonstrated that CPUE increased during the eve-
ning as surface illumination levels declined, suggesting that walleyes are more likely to search
for food at twilight or night than on sunny days.
Ryder’s (1977) observations about the importance of light are supported by other studies.
Ultrasonic tracking (Kelso 1976, 1978) verified that walleyes are relatively inactive during
the day and increase their activity at dusk, when they typically initiate feeding. Gillnetting
studies (Carlander and Cleary 1949) demonstrated that walleyes are more vulnerable to cap-
ture at night and that the greatest periods of mobility are dawn and dusk. The effect of light
on walleye behavior is well known to most ardent anglers (Ryder 1977); walleyes in waters
of low transparency are more inclined to be captured throughout daylight than those in clear
lakes. Also, abrupt daytime decreases in subsurface light intensity (e.g., due to storm clouds
and increased wave action) are often associated with increased catch rates.
The other abiotic factor of key importance to walleye is temperature. Temperature affects
metabolic rate, feeding activity, food conversion efficiency, and consequently, growth of wall-
eye (Kitchell et al. 1977; see Chapter 6). Because maximum growth efficiency of walleye ap-
pears to occur in temperatures of 18–22°C, it is not surprising that walleye reside primarily in
the epilimnion. In clear deep lakes, optimal light conditions during the day exist in deep water
below the thermocline, but walleyes are seldom observed in deep hypolimnetic water. Instead,
they are more likely to be found resting in the epilimnion, using bottom cover to avoid high
light intensity (Ryder 1977).
It is widely acknowledged that walleyes have an affinity for the bottom. Their scotopic
vision provides walleyes with the ability to detect prey in darker conditions than most other
visual predators. This visual advantage is important considering that walleyes do not have
other sensory organs, such as the lateral line, as well developed as in other percids (Disler
and Smirnov 1977). Kerr et al. (1997) reported that preferred substrates are generally thought
to be clean hard materials with abundant cover in the form of boulders, rooted submerged
vegetation, trees, and logs (Holt et al. 1977; Schlagenhaft and Murphy 1985; Johnson et al.
1988; Paragamian 1989). Optimal vegetative cover (percentage of the bottom covered with
aquatic vegetation) is believed to be in the order of 25–45% (McMahon et al. 1984) although
the quantitative basis for this level was unclear.
The combined role of light and temperature in determining suitable walleye habitat in
lakes was explored in a thermal–optical habitat model developed by Lester et al. (2004a).
They showed that suitable habitat, defined as benthic area that offered optimal temperature
and light conditions, was an important determinant of walleye production in Ontario lakes.
Thermal–optical habitat area, combined with a nutrient index (total dissolved solids, TDS),
accounted for 70% of the observed variation in sustained yield of walleyes from angling and
commercial fisheries.
Juvenile walleyes, like adults, are largely piscivorous, opportunistic, and selective, feed-
ing on a large variety of fish species, whereas younger walleyes feed on zooplankton and
benthic invertebrates (Colby et al. 1979; Schneider et al. 1991; Galarowicz et al. 2006; see
Walleye and Sauger Life History
Chapter 8). Prey availability also plays a role in the diet of juvenile walleyes. Lyons (1987)
found that juvenile walleyes selected for darters and against cyprinids in the littoral zone
of Sparking Lake, Wisconsin. However, when age-0 yellow perch became abundant, yellow
perch became more important in their diet. In contrast, Lyons (1987) also found that juvenile
walleyes preferred bluntnose minnow to age-0 yellow perch in laboratory trials suggesting
that availability of prey in Sparkling Lake may be a function of both overall abundance and
movement (i.e., location) relative to locations of walleyes.
Colby et al. (1979) provided many references that list the diverse prey fish that walleyes
feed on. Walleyes have a well-developed set of sharp teeth, which aids them in the capture
and retention of prey fish. R. A. Ryder (Ontario Ministry of Natural Resources, personal com-
munication) has observed walleyes to capture a prey fish from the side, and then move it into
a position where the head of the prey is pointing into the mouth. Any movements by the prey
will then result in forward motion into the walleye’s mouth, and it also ensures that dorsal
spines, such as in yellow perch, collapse to facilitate ingestion. Given a choice, it appears that
walleyes will select soft-rayed fish instead of rigid-rayed ones. Schneider at al. (1991) report
that in Lake Michigan, walleyes were feeding mostly on soft-rayed alewives, white sucker,
and rainbow smelt, avoiding common rigid-rayed species, such as yellow perch, and brown
bullhead. Knight et al. (1984), in a study of walleyes in Lake Erie, found that spiny-rayed fish
were the least important prey, contributing from 0% to 40% to the walleye’s diet. Cisco (i.e.,
lake herring) is an important food item for walleyes in coolwater fish communities (Ryder and
Kerr 1978; Kaufman et al. 2006). Sexual Determination
Sexual determination in juvenile walleyes relies on internal examination of gonads. Es-
chmeyer (1950) provided a detailed description of the development of gonads in the walleye.
A distinguishing feature of the ovary is the anterior end, which is broadly rounded or comes
to a blunt point. Ovaries in small 70-mm female walleyes show very little obvious develop-
ment other than heavy pigmentation throughout their length. As the fish grows to around 130
mm these melanophores are distributed along a narrow band on each side of the ovary. This
pigmentation is usually restricted to a few scattered melanophores anterior and dorsal along
the ovaries. Testes are distinguishable from ovaries in immature fish by the lack of the blunt
anterior end. Testes are more gradually elongated at the anterior end. Testes in small 70-mm
male walleyes are smaller than female ovaries of the same size fish. They are fine threads with
virtually no pigmentation (Colby et al. 1979). Juvenile Growth Rate
During the juvenile life stage, male and female walleyes usually grow at the same rate.
Differences in growth rate typically do not appear until after maturation, when females sus-
tain higher growth rates. Some studies have reported that females were larger than males by
the end of the first year, but this early divergence seems to appear more in the south and in
reservoirs where growth tends to average faster (Carlander 1997). Our compilation of the
published walleye data indicates that differences in mean length at age do not appear until TL
exceeds 350 mm (Figure 7.4), which coincides with the average size of maturity for males
(see section
20 Chapter 7
Latitudinal differences exist in seasonal growth patterns and annual growth rate. At north-
ern extremes, water temperature rarely exceeds 22°C and optimum conditions exist for only a
short period during the summer. Consequently, most of the annual growth in northern popula-
tions occurs from mid-June to August (Forney 1966; Kelso and Ward 1972; Carlander 1997;
Swenson 1977). In contrast, summer water temperatures typically exceed 22°C in southern
latitudes and most of the annual growth occurs during late summer and autumn (Carlander
1997). For Kansas reservoirs, where temperatures often exceed 26°C throughout the summer,
80% of growth is achieved between August and October (Quist et al. 2002). The latter study
also found that mean summer air temperature explained 59–77% of the variation in growth of
age-2 and age-3 walleyes, reductions in growth being evident when air temperature exceeded
25°C. Studies have shown that walleye reduce their feeding activity and seek thermal refugia
when water temperature exceeds 22°C (Ager 1977; Kelso 1972; Hokanson 1977; Williams
1997; Kocovsky and Carline 2001).
In general, annual growth rate increases from north to south (Carlander 1997). Colby et
al. (1979) reported data that indicate five-fold differences in growth between southern and
northern populations. Colby and Nepszy (1981) proposed that these differences were largely
0100 200300 400500 600700 800
Female length at age (mm)
Male length at age (mm)
Figure 7.4. Comparison of mean length at age in males and females. Each point is an age
specific estimate from one population. Dashed line is line of equality; solid curved line is the
LOWESS fit. The two lines deviate when TL is greater than 350 mm. Graph includes data
from 484 walleye populations (402 in Ontario, 52 in Québec, and 30 in USA). Data sources are
Colby et al. (1979), Carlander (1997), Morgan et al. (2003), and Venturelli et al. (2010a).
Walleye and Sauger Life History
due to variation in annual input of thermal energy, which they measured using GDD. More
recent synoptic reviews of walleye growth differences over a broad latitudinal range are pro-
vided by Quist et al. (2003b) and Zhao et al. (2008). Both studies confirm the previously re-
ported relationship between walleye growth rates and GDD. Quist et al. (2003b) highlighted
the additional importance of food availability in determining growth rates, while Zhao et al.
(2008) suggested that life history traits are also linked to ancestral linkages from different
glacial refugia.
7.2.6 Adults Determination of Sexual Maturity
Determination of sexual maturity in walleye is usually made by visual inspection of fish.
One method is to look for the expression of sexual products (milt, eggs) when fish are cap-
tured during the spring spawning season. Alternatively, maturity can be assessed in the fall
by internal examination of the ovaries or testes. Duffy et al. (2000) provided a good textual
description and photo documentation of the various maturity stages of walleye based on go-
nad conditions during the fall. However, being mature does not necessarily ensure that an in-
dividual will spawn. Henderson and Nepszy (1994) warned that some mature female walleyes
with eggs may not spawn if their condition is poor. Age and Size of Maturity
Walleye are iteroparous, reproducing multiple times during their life span. Because onset
of sexual maturation varies among individuals within a population, maturation of a popula-
tion is usually characterized by the age (or size) when 50% of the population is mature. Colby
et al. (1979) reported walleyes maturing as early as 2 years in Texas and as late as 8 years in
northern Ontario. More recent work has revealed larger variation. In Ontario, walleye matu-
ration ranges from 3 to 11 years in females and 2–9 years in males (Morgan et al. 2003). In
some slow growth populations of northern Québec, walleyes may take as long as 12–15 years
to reach maturity (Venturelli et al. 2010a).
A negative correlation between age of maturity and GDD was first noted by Colby and
Nepszy (1981). A functional relationship was subsequently described by Baccante and Colby
(1996) and has been supported by more recent studies (Gangl and Pereira 2003; Sullivan
2003; Venturelli et al. 2010a). This negative relationship is demonstrated in Figure 7.5A,
which is a compilation of published data. Many studies did not distinguish between sexes, but
Venturelli et al. (2010a) described sex-specific relationships based on maturity data from On-
tario and Québec (shown in Figure 7.5A). These results indicate that males typically mature
1–2 years earlier than do females (Figure 7.5B).
Whereas there is strong support for a relation between GDD and age at maturity, there is
no indication that GDD affects size at maturity (Venturelli et al. 2010a). Our data compilation
indicates that, on average, males mature at about 350 mm and females at about 450 mm (Fig-
ure 7.6A). There is, however, substantial variation among populations in size of maturity (i.e.,
262–444 mm in males and 331–562 mm in females for our data set). Male size at maturity is
smaller than, but correlated with, female size of maturity (Figure 7.6B). On average, males
mature at a total length that is approximately 80% of female length at maturity.
22 Chapter 7
0246810 12 14 16
Female age at 50% mature (years)
Male age at 50% mature (years)
Figure 7.5. In panel (A), age at 50% mature of females and males (from the same populations)
are plotted against GDD. The graph also includes data from studies where sex was not speci-
fied. The thin dotted line is the relationship developed by Baccante and Colby (1996) based on
combined sex data (Tm = 3,185/GDD0.871). Thick lines are sex-specific relationships developed
by Venturelli et al. (2010a): females (solid line, Tm_female = 36,666/GDD1.18) and males (dashed
line, Tm_male = 61,846/GDD1.31). In panel (B), age at maturity is compared among sexes. Major
axis regression (solid line) implies Tm_male = 1.06·Tm_female – 2.6 (n = 55, r2 = 0.82). Sex-specific es-
timates are from Venturelli et al. (2010a) and are based on populations where at least 100 fish
of each sex were sampled. Other data (sex not specified) are from Baccante and Colby (1996),
Gangl and Pereira (2003), and Sullivan (2003).
Walleye and Sauger Life History
01000 2000 3000 4000
Growing Degree Days (
Length at 50% mature (mm)
Sex not specified
100 200300 400 500600 700
Female length at 50% mature (mm)
Male length at 50% mature (mm)
Figure 7.6. In panel (A), length at 50% mature of females and males (from the same popula-
tions) are plotted against GDD. The graph also includes data from studies where sex was not
specified. Regression analysis indicates that length at maturity is not related to GDD. Hori-
zontal lines are means for each group: 451 mm for females (thick solid), 348 mm for males
(thick dashed), and 431 mm for sex not specified (thin dotted). In panel (B), length at maturity
is compared among sexes. Major axis regression (solid line) implies Lm_male = 0.83·Lm_female – 23.0
(n = 59, r2 = 0.27). Data sources are listed in the caption of Figure 7.5.
24 Chapter 7 Longevity and Mortality Rate
Some studies have reported sexual differences in longevity suggesting that females live
longer than males (Carlander 1997), but large-scale analyses do not indicate consistent dif-
ferences in longevity. Morgan et al. (2003) estimated mortality rate (a correlate of longevity)
in 296 Ontario walleye populations and reported mean annual mortality was almost identical
among sexes (28% in females and 30% in males). Rennie et al. (2008) examined maximum
age for a subset of these Ontario populations (where sample size was large) and found no
significant difference among sexes. Our compilation of walleye data, which spans a broader
latitudinal gradient, supports these findings (Figure 7.7).
Walleye longevity, like age at maturity, is inversely related to GDD. Colby and Nepszy
(1981) reported that maximum age of walleyes at the northern limit of its range is five times
higher (around 20 years) than at the southern extreme (3–4 years). More recent observations
indicate that maximum age exceeds 30 years in some northern populations (Venturelli et al.
2010a). Our compilation of data from populations spanning 1000–5000 GDD indicates a
range of 4–32 years (Figure 7.8A).
Because longevity is inversely proportional to mortality rate, these results indicate that
mortality rate increases with GDD. We applied Hoenig’s (1983) empirical formula to esti-
mate annual instantaneous mortality rate (Z) from maximum age (Tmax) as follows: Z = 4.22/
0.982). As illustrated in Figure 7.8B, linear regression implies that, on average, mortality
rate increases from approximately 0.15 at 1000 GDD to 0.60 at 3000 GDD. However, for any
given value of GDD, mortality estimates are highly variable. This variability is partially due to
variation in sample size, because maximum age increases with the number of fish examined,
but it may also reflect variation in exploitation rate. To describe the relationship between natu-
ral mortality rate and GDD, we assumed that the lowest mortality values at each level of GDD
represent lightly exploited populations. This approximation suggests that natural mortality
rate increases from approximately 0.13/year at 1000 GDD to 0.39/year at 3000 GDD.
Estimates of natural mortality are rare for walleye populations because walleyes, by vir-
tue of their excellent taste, are a popular target for recreational and commercial harvest. One
exception is the Pymatuning Sanctuary in Pennsylvania, a 530-ha impoundment on the Upper
Shenango River that has been closed to fishing since it was created in 1933 (Kocovsky and
Carline 2001). Estimates of mortality rate in this unexploited population, which ranged from
0.39 to 0.53/year, are slightly higher than our estimate of natural mortality for this climate
zone (GDD = 2327, Z = 0.30). Nevertheless, because natural mortality rate of this mid-latitude
population exceeds total mortality estimates for many populations in colder climates, these
results are consistent with the hypothesis that natural mortality increases with GDD. Maximum Body Size
Walleyes exhibit indeterminate growth, implying that they continue to grow after matura-
tion. Most studies that have examined sexual dimorphism report that females grow larger than
males. Based on a von Bertalanffy growth model, Quist et al. (2003b) estimated that mean
asymptotic length was 496 mm for males and 652 mm for females, implying a ratio of 0.76.
We compiled maximum body size data from the published literature. We used mean length
of the oldest cohort in each sex. Maximum body size is not related to GDD (Figure 7.9A).
Maximum length of females is usually larger than males (Figures 7.9B). On average, male
Walleye and Sauger Life History
maximum length is approximately 80% of females. Frequency of Spawning
The available data suggest that frequency of spawning is annual in most walleye popula-
tions. However, there are indications of physiological limitations at northern and southern
extremes. Walleyes in some northern populations may not spawn every year, because of short
growing seasons (Scott and Crossman 1973). Walleye populations at the southern extreme
have failed to reproduce in years when temperatures where high during time of maturation
(Colby and Nepszy 1981). Hokanson (1977) reported that a minimum winter temperature of
10°C is near the upper limit for gonadal maturation in walleye, which may limit successful
reproduction in southern latitudes, such as Texas (Prentice and Clark 1978; although see Laar-
man 1978). This constraint may dictate the southern limit of self-sustaining walleye popula-
tions. Fecundity, Egg Size and Gonadosomatic Index
Walleyes produce large numbers of eggs compared with many other freshwater fish spe-
cies (Scott and Crossman 1973; Becker 1983). Moreover, fecundity clearly increases as a
function of age but the specific relation varies with geographic location (Figure 7.10), which
may be related to differences in productivity across these systems.
Because fecundity increases roughly proportional to body weight, fecundity of a popu-
0510 15 20 25 30
Female maximum age (years)
Male maximum age (years)
Figure 7.7. Comparison of maximum age in males and females. Dotted line is the line of
equality. Major axis regression (solid line) implies Tmax_male = 1.13 · Tmax_female3.15 (n = 107, r2
= 0.61). Data sources are Colby et al. (1979), Carlander (1997), Kocovsky and Carline (2001),
Morgan et al. (2003), and Venturelli et al. (2010a).
26 Chapter 7
0500 10001500 2000 2500300035004000
Growing Degree Days (oC)
Maximum age (years)
01000 2000 3000 4000
Growing Degree Days (
Mortality rate (Z, /year)
Figure 7.8. In panel (A), the observed maximum ages of walleye from 135 populations are
plotted against GDD. In panel (B), estimates of mortality rate based on maximum age (see
text for details) are plotted against GDD. The solid line is the least-squares regression: Z =
0.000201·GDD – 0.02493. The dotted line is a putative minimum estimate of natural mortality
(see text for details): M = 0.13·GDD. Data sources are listed in the caption of Figure 7.7.
Walleye and Sauger Life History
010002000 3000 4000
Growing Degree Days (
Maximum total length (mm)
0200 400600 800 1000
Female maximum total length (mm)
Male maximum total length (mm)
Figure 7.9. In panel (A), the maximum length of females and males (from the same popula-
tions) are plotted against GDD. Maximum length was measured as mean length of fish in the
oldest cohort. Maximum length does not vary systematically with GDD. Horizontal lines are
means for each group: 669 mm for females (solid), 539 mm for males (dashed). In panel (B),
maximum length is compared among sexes. Major axis regression (solid line) implies Lmax_male
= 0.694·Lmax_female + 75.4 (n = 107, r2 = 0.21). Data sources are Colby et al. (1979), Carlander
(1997), Kocovsky and Carline (2001), Morgan et al. (2003), and Venturelli et al. (2010a).
28 Chapter 7
lation is usually characterized by its relative fecundity (number of eggs per body weight).
Examples shown in Figure 7.11A demonstrate that this relationship may vary widely among
populations. Baccante and Colby (1996) showed that relative fecundity increases with GDD,
ranging from approximately 40,000 eggs/kg in northern waters (GDD, ~1200) to 80,000 eggs/
kg in mid-latitude waters (GDD, ~2500). Insufficient fecundity data were available to exam-
ine this trend further south. An enlarged data set, which includes many more observations
from Ontario (Lester et al. 2000; Morgan et al. 2003), indicates that fecundity of some north-
ern populations may be as low as 20,000 eggs/kg (Figure 7.11B). The relationship implied
by this enlarged data set, however, is virtually identical to that described by Baccante and
Colby (1996). The data demonstrate that, while there is a significant positive effect of GDD
on relative fecundity, high variability exists within climatic zones. For example, fecundity of
populations living at the northern fringe (i.e., GDD = 1100–1300) ranges from 20,000–60,000
Because egg size may vary, fecundity (i.e., egg number) is not sufficient to describe the
reproductive investment of a female fish. A better measure is the gonadosomatic index (GSI),
which is the weight of the gonads relative to somatic weight (i.e., body weight excluding
the gonads) and which varies considerably during maturation leading up to spawning (see
Chapter 6). Eschmeyer (1950) used this index to describe the seasonal development of the
reproductive organs in Lake Gogebic, Michigan, and measure the final investment at time
of spawning. In this lake, female GSI was 4.7% in October and 16.3% just before spawning.
Similar values have been reported for Lake Erie (Henderson et al. 1996) and Minnesota lakes
Figure 7.10. Relationship between fecundity and age for selected walleye populations distrib-
uted across a range of energy input. Figure is redrawn from Baccante and Reid (1988) with
the addition of GDD and fecundity data for Charlie Lake, British Columbia. Growing Degree
Days above 5°C are also shown. Symbols on the curves represent total lengths of sh: • = 40
cm, = 45 cm, = 50 cm, = 55 cm, = 60 cm.
Walleye and Sauger Life History
Fish weight (kg)
Number of eggs
1000 1400 1800 22002600 3000
Growing Degree Days (
Relative fecundity (eggs/kg)
Figure 7.11. In panel (A), the relationship between fecundity and fish weight is contrasted for
two walleye populations in Ontario. Regression through the origin implies relative fecundity
is 85,100 eggs/kg on Rice Lake and 20,900 eggs/kg on Wabigoon Lake. In panel (B), estimates
of relative fecundity for 100 water bodies are plotted against GDD. The dotted line is the rela-
tionship developed by Baccante and Colby (1996) based on a smaller data set: relative fecun-
dity = 24.7·GDD + 14514. The solid line is the least squares fit for the entire data set: relative
fecundity = 25·GDD + 11884 (n = 100, r2 = 0.029). Data sources are Baccante and Colby (1996),
Lester et al. (2000), and Morgan et al. (2003)
30 Chapter 7
(Malison and Held 1996; Figure 6.1 in Chapter 6). Higher GSI values were reported in the
Muskegon River, Michigan, (24.1%) and in Saginaw Bay, Lake Huron (27.8%) (Colby et al.
1979). In some cases, reporting of GSI applies a conversion factor to correct for energy den-
sity differences between eggs and somatic tissue. For example, Shuter et al. (2005) reported
a mean walleye GSI of 24% (range, 9–44%) for 18 inland lakes in Ontario after applying a
conversion factor of 1.41 (from Henderson and Nepszy 1994). This expression of GSI more
accurately describes the energetic investment. Without this correction factor, these results
imply the mean GSI = 17% (range, 6–31%).
Male GSI has also been measured in some populations and is always much less than
female GSI (e.g., Eschmeyer 1950; Malison and Held 1996). Male GSI is not a useful index
of reproductive investment because the energetic cost of sperm production is very small com-
pared with the female cost of egg production; a small allocation of energy to sperm production
is sufficient to produce an abundant supply of sperm. Spawning Migration
Walleyes show fidelity to spawning areas and this homing behavior dictates the move-
ment pattern of adults (Crowe 1962; Olson and Scidmore 1962; Regier et al. 1969; Olson et
al. 1978; Colby et al. 1979; Jennings et al. 1996). The distance that walleyes travel to get to
their spawning grounds and subsequently disperse to feeding areas varies among populations.
Walleyes, although not recognized as strong swimmers compared with other species, such as
salmonids, are also capable of moving long distances. Colby et al. (1979) cite various studies
that report movements ranging from 50 to nearly 300 km. Colby et al. (1979) also cite studies
that report minimal movement between spawning grounds and feeding areas (e.g., <20 km),
despite the potential for much larger movement.
Walleye spawning can generally be classified into three life history spawning typologies:
(1) lake-resident, (2) river-resident, and (3) lake-resident, river-run spawning although there
are many variations of these strategies. In Lake Goegebic, walleyes move inshore to spawn
along wind-swept shorelines (Eschmeyer 1950) as they do in many lakes (Niemuth et al.
1959; Johnson 1961; Raabe 2006). In rivers, such as the Wisconsin River, walleyes move into
large riffles to spawn (Stevens 1990); river spawning is common (Preigel 1970; Scott and
Crossman 1973; Nelson and Walburg 1977; Hartley and Kelso 1991). In the Laurentian Great
Lakes, major tributaries play an important role in providing spawning habitat for walleyes
(Hayes and Petrusso 1998). In Lake Erie, walleyes consist of different stocks moving either
into tributary streams or onto mid-lake reefs to spawn (Stepien 1995; Stepien and Faber 1998;
Roseman et al. 2001) as they do in many lakes of all sizes having tributary streams (Geiling
et al. 1996). Onshore spawning movement in lake systems is probably guided by thermal
conditions that optimize gamete viability and hatching success (Rawson 1957; Forney 1967;
Preigel 1970). There is evidence that distinct walleye stocks utilize different spawning areas
in larger systems (Preigel 1970; Spangler et at. 1977a; Jennings et al. 1996). Spangler et al.
(1977a), reviewing walleyes in Lake Huron, and Jennings et al. (1996), working in a southern
U.S. reservoir, both found walleye movements occur among distinct spawning populations
in the same waterbody. Spawning migratory behavior is system-specific and further inves-
tigations are required to discern under what environmental conditions walleyes will migrate
versus being resident. Schupp and Macins (1977) found that walleyes did not migrate far in
Lake of the Woods, Ontario–Minnesota, whereas Ferguson and Derksen (1971) found that
Walleye and Sauger Life History
walleyes migrate great distances across Lake Huron to spawn. Long migrations may be an
important life history component when suitable spawning habitats are distant from foraging
areas in larger systems.
Large water bodies, such as the Great Lakes, have diverse habitats, such as relatively
shallow and warm bays separated by vast expanses of deep and cold water that can act as
ecological barriers to the movements of walleye. However, strong homing instinct can result
in remarkable movements. For example, adult walleyes captured and tagged at the mouth of
the Current River, near Thunder Bay, Ontario, were released at the north end of Black Bay, a
distance of about 150 km. These two locations are separated by large expanses of deep and
cold water in Lake Superior; however, within 8 months of their release, 18.2% of the walleyes
were recaptured at the source location (Colby and Nepszy 1981).
A study of walleye movements in the Petitot River, British Columbia, furthers our under-
standing of the scope of seasonal walleye movements (Anderson et al. 2009). The 300-km-
long Petitot River flows from Bistcho Lake, Alberta, through northeastern British Columbia
into the Liard River. It appears that walleyes in the Petitot River maintain a primarily fluvial
life history, using the main stem almost exclusively during spawning and winter periods.
However, during the summer, many walleyes migrate as far as 30 km to tributary streams and
then return to the main stem in the fall. Individual fish movements were sometimes substan-
tial and rapid. One individual traveled more than 160 km during a 15-d period in late May.
Another fish traveled 187 km downstream over a 14-d period in mid-July and then returned to
within 2 km of its original location during the following 7 d.
These long migrations are indicative of strong homing behavior in adult walleyes. Olson
et al. (1978) suggested that homing is influenced by adult-learned behavior, strengthened
through repeated annual movements. Because walleye is a schooling species, the existence of
older fish that may guide the spawning migration of younger cohorts is an important consid-
eration in management.
7.3.1 Examples
Examples of lifetime growth patterns in several well-sampled walleye populations are
shown in Figure 7.12. Mean length at age of males and females is shown, separated into im-
mature and mature age groups based on estimates of age at 50% maturity. These examples
demonstrate some features of walleye growth that seem to have wide applicability: (1) both
sexes follow the same growth trajectory before maturation; (2) prematuration growth in length
is approximately linear; (3) males usually mature earlier and, thus, smaller than females; (4)
maturation is usually associated with an abrupt change in growth rate; (5) males usually attain
a smaller maximum body size than females.
The von Bertalanffy (VB) growth equation has been widely used to describe and contrast
lifetime growth patterns in walleye populations (e.g., Quist et al. 2003b; Sass et al. 2004).
Although this model provides a decent approximation of lifetime growth, its value in un-
derstanding life history processes has been questioned. On theoretical grounds, it has been
argued that a single somatic growth equation cannot cleanly account for the change in energy
allocation that occurs with sexual maturity (Nikolskii 1969; Charnov 1993; Day and Taylor
32 Chapter 7
Age (years)
Mean tota l leng th (mm)
0510 15 20 25 30
Age (years)
Mean total length (mm)
0510 15 20 25 30
Wakami Lake
GDD = 1503
Rice Lake
GDD = 2036
Lake Erie (West)
GDD = 2564
Lac Regnault
GDD = 1077
Age (years)
Mean total length (mm)
0510 15 20 25 30
Age (years)
Mean total length (mm)
0510 15 20 25 30
Figure 7.12. Lifetime growth patterns of four walleye populations. In each case, mean length
at age is plotted against age for males (triangles) and females (circles). Maturity status for
each age is indicated using open (immature) and closed (mature) symbols. The growth trajec-
tory of immature fish is indicated by a dashed line. Solid (curved) lines describe the growth
trajectory of mature females, estimated using the biphasic growth model (see text). Examples
represent populations from different climatic zone, arranged in order from cold to warm:
(panel A) Lac Regnault, Québec, GDD = 1077°C; (panel B) Wakami Lake, Ontario, GDD =
1503°C; (panel C) Rice Lake, Ontario, GDD = 2038°C; (panel D) Lake Erie (west); GDD =
2564°C. Data sources are walleye survey databases from Québec (A) and Ontario (B and C)
and from Carlander (1997) (D).
1997; Charnov et al. 2001). For example, the abrupt changes in walleye growth at maturation
cannot be accurately described by the VB growth curve. Furthermore, the structure of the
VB model cannot account for sexual differences in lifetime growth pattern; separate fitting
of the model to males and females cannot generate results that imply identical growth before
7.3.2 Biphasic Growth model
An alternative growth model, which accounts for effects of reproduction and has been ap-
plied to walleye, is the biphasic growth model (Lester et al. 2004b; Shuter et al. 2005; Quince
et al. 2008a, 2008b). The model predicts a rapid, approximately linear, juvenile growth phase,
Walleye and Sauger Life History
followed by a gradual reduction in growth rate after sexual maturation. Because the model
assumes the annual investment in reproduction by a typical female (g = gonad weight/somatic
weight) is constant throughout her reproductive lifetime, it predicts an adult growth pattern
that is described by a Von Bertalanffy growth function (see Lester et al. 2004b). The param-
eters of this function (L, k, to) depend on prematuration growth rate (h), reproductive invest-
ment (g), age of maturity (T), and a time parameter (t1) that captures the influence of prey size
spectrum on early growth. Given a prematuration growth pattern described as:
Lt = h(t t1)
Adult growth is described by the Von Bertalanffy function:
Lt = L(1 – ek(tt0)
where L = 3h/g, k = loge(1 + g/3) and to = T + loge(1 – g(Tt1)/3)/loge(1 + g/3).
The model has been labeled as ‘biphasic’ because it implies that accurate description
of the lifetime growth pattern requires two functions that separately describe prematuration
and postmaturation growth phases. Examples in Figure 7.12 demonstrate that the shapes of
walleye growth curves are consistent with this model. Growth is rapid and approximately lin-
ear before maturation; changes in growth pattern are associated with age of maturation; and
growth is asymptotic during the adult phase. Shuter et al. (2005) showed this model success-
fully describes growth patterns seen in walleye, as well as other species.
Additional support of this model is revealed by interpretation of its parameters. Prema-
turation growth rate (h) estimates the growth that would occur if all surplus energy was al-
located to somatic growth. Departure from this expected trajectory indicates investment in
reproduction, which can be estimated from growth curves as g = 3 h/L. Because egg produc-
tion dominates reproductive costs of females, the g value estimated from the female growth
curve should reflect the female GSI. For several species, Shuter et al. (2005) found a good
match between direct measures of GSI and indirect estimates based on the biphasic model.
For walleyes, GSI ranged from 0.09 to 0.44 (mean = 0.24) and indirect estimates (g) based on
growth curves ranged from 0.14 to 0.35 (mean = 0.22). In this comparison, direct estimates of
GSI were corrected for the higher energy content of eggs relative to soma, using a correction
factor of 1.41. This correction factor was needed because the GSI parameter (g) in the bipha-
sic model measures reproductive investment in energetic units.
7.3.3 Optimal Life History Traits
Life history theory attempts to explain variation in life history traits based on the principle
of natural selection. Because selection favors individuals that maximize their fitness, the pat-
terns we observe are expected to be optimal solutions to environmental constraints. Under this
assumption, the biphasic growth model makes explicit predictions (Lester et al. 2004b) about
relationships among mortality rate (Z), reproductive investment (g), and age at maturity (T)
according to these relationships:
g 1.18·(1 – eZ ) and T 1.95/(eZ – 1) + t1
34 Chapter 7
These equations imply that reproductive investment increases and age at maturity de-
creases as mortality rate increases. This model also predicts effects of the prey environment
on body size. If the scope for growth declines with body size due to a truncated size spectrum
of the prey field (i.e., t1 < 0), age of maturity is expected to decrease. Consequently, fish will
mature at a smaller size and attain a smaller maximum body size. Support for these model
predictions is provided in a study by Shuter et al. (2005) that examined life history variation
in Ontario lakes for four species including walleye.
Beverton (1987) applied life history theory to account for the observation by Colby and
Nepszy (1981) that reduced walleye longevity in warmer climates is compensated by earlier
maturation. This observation is consistent with predictions of the biphasic growth model:
mortality rate increases (Figure 7.8) and age of maturity decreases (Figure 7.5) with GDD. In
addition, the biphasic model offers an explanation for the observation that relative fecundity
increases with GDD (Figure 7.11B); assuming a constant egg size, higher relative fecundity
implies higher reproductive investment, which is expected in warmer climates due to the
higher mortality rate.
7.3.4 Sexual Dimorphism
It is widely recognized that sexual dimorphism exists in walleyes (Eschmeyer 1950; Hile
1954; Carlander and Whitney 1961; Colby et al. 1979; Carlander 1997; Henderson et al.
2003; Quist et al. 2003b; Sass et al. 2004), but it is not entirely clear why. The onset of sexual
dimorphism is related to maturation (Figures 7.4 and 7.12). After maturation annual growth
increments in males are usually smaller than in females and males attain a smaller maximum
body size (Figure 7.9). Given assumptions in the biphasic growth model, slower postmatu-
ration growth in males suggests that reproductive costs are higher than in females. But this
explanation seems unlikely because the energetic cost of sperm production is much less than
egg production. Henderson et al. (2003) proposed that the lower cost of gamete production
in males may be offset by higher activity costs associated with mating. Because males ar-
rive early and stay late on spawning shoals, they forego more feeding opportunities than do
females. In addition, males may expend more energy in the spawning act because they must
compete with other males to access females. While behavioral costs associated with mating
may be higher in males, it seems unlikely that energy expenses during this short period of the
year exceed the cost of egg production incurred by females.
An alternative hypothesis is that adult males consume less food than females. Reduced
food consumption by adult males has been reported for walleye (Henderson et al. 2003) and
yellow perch (Rennie et al. 2008), a close relative of walleye. Assuming that energetic costs of
reproduction are higher for females, males would outgrow females if they consumed the same
amount of food. Evolutionary benefits of growth-limiting behavior in males exist because
male size does not limit the supply of sperm, as opposed to females where body size limits
egg production. Male reproductive success is dependent on fertilizing eggs from the greatest
number of females that appear briefly on spawning shoals. If small agile males have a greater
chance of mating, then high adult growth would not be beneficial; optimal male body size
would depend on the size of female spawners. For walleye, the observed body length ratio is
approximately 0.78 (Rennie et al. 2008). This ratio describes the average relative length of
males to females, when walleyes become mature and also at the end of their lives.
Walleye and Sauger Life History
Temperature and food availability are the primary determinants of fish growth and devel-
opment (Paloheimo and Dickie 1966; Fry 1971; Kitchell et al. 1977). Recently, Neuheimer
and Taggart (2007) showed that GDD, an index of ambient thermal energy, can account for
much of the variation in growth among species and populations of fish. The value of this index
in predicting walleye growth was recognized almost 30 years ago (Colby and Nepszy 1981)
and has been confirmed in more recent studies (e.g., Venturelli et al. 2010a).
Lifetime growth patterns of male and female walleyes living in different climatic zones
are contrasted in Figure 7.13. These results are based on growth data from 432 walleye popu-
lations spanning a GDD range of 1000–4630°C. We divided populations into three climatic
zones: (1) northern extreme (<1500°C), (2) mid-latitude (1500–2500°C), and (3) southern ex-
treme (>2500°C). We averaged mean length at age across populations to describe the average
growth of males and females in each zone. Growth trajectories demonstrate clearly that wall-
eyes grow more slowly and live longer in colder zones than in warmer ones. For example, in
the southern zone (GDD > 2500°C) walleyes reach a total length of 350 mm in approximately
2 years and maximum age is in the order of 10 years. In contrast, walleyes in the north (GDD
< 1500°C) need approximately 5 years to reach 350 mm and may live as long as 30 years.
These differences largely disappear when age is expressed in terms of thermal units in-
stead of calendar years (Figure 7.14). Thermal units are measured as cumulative GDD (i.e.,
age times mean annual GDD of the waterbody). The growth curves for different climatic
zones are practically identical when plotted in this manner. On average, walleyes reach a
length of 350 mm when they have experienced a cumulative GDD of 6000°C, and longev-
ity is in the order of 30000°C GDD. These results imply that when the temporal unit of rate
processes is corrected for temperature differences (using cumulative GDD instead of years),
average growth and mortality rates are the same across a broad climatic gradient. This stan-
dardization is a powerful tool for exploring the effect of food availability on walleye growth
(see Venturelli et al. 2010b). The climate-corrected growth curves also demonstrate that body
Age (yr)
Mean total length (mm)
GDD < 1500
GDD = 1500 to 2500
GDD > 2500
Age (yr)
Mean total length (mm)
GDD < 1500
GDD = 1500 to 2500
GDD > 2500
Figure 7.13. Effect of climate on growth and development of walleye. The average mean
length at age of males (panel A) and females (panel B) is shown for populations in three cli-
matic zones: GDD <1500°C, GDD = 1500–2500°C, and GDD >2500°C. The number of walleye
populations in each zone are 101 (GDD <1500°C), 319 (1500–2500°C), and 11 (GDD >2500°C).
Data sources are Carlander (1997) and walleye survey databases from Ontario and Québec.
36 Chapter 7
size and sexual dimorphism are not affected by climate. On average, walleyes attain the
same maximum size in different climatic zones and there is a consistent difference between
During its lifetime, a walleye undergoes a series of ontogenetic diet shifts, moving suc-
cessively from smaller to larger prey items as it grows (see Chapter 8). Age-0 walleyes ini-
tially feed on zooplankton, switch to benthos, and then become piscivorous. The onset of
piscivory occurs in the first year of life when length is between 50 and 80 mm TL (Smith and
Moyle 1945; Smith and Pycha 1960: Walker and Applegate 1976). Walleye are capable of
consuming fish that are half their length (Campbell 1998). Parsons (1971) observed that the
average prey : predator length ratio for Lake Erie declines from 0.44 for 60-mm walleyes to
0.28 for 400-mm walleyes. A similar length ratio trend is evident in Figure 2 of Kaufman et
al. (2009) for inland lakes of Ontario. Although walleyes are opportunistic feeders and will
feed on small items when they are readily available, the availability of optimally sized prey
seems to be an important determinant of growth and maximum body size (e.g., Henderson et
al. 2004; Kaufman et al. 2009).
Age x mean GDD x 10
Mean total length (mm)
0510 15 20 25 30 35
Sex = Male, GDD < 1500
Sex = Male, GDD = 1500 to 2500
Sex = Male, GDD > 2500
Sex = Female, GDD < 1500
Sex = Female, GDD = 1500 to 2500
Sex = Female, GDD > 2500
Figure 7.14. Effect of climate on growth and development of walleye. Average mean length
at thermal age is shown for populations in three climatic zones: GDD <1500°C, GDD = 1500–
2500°C, and GDD >2500°C, where thermal age is measured as age in years times mean GDD.
Mean length at maturity (solid line: females; dashed line: males) is also shown. Number of
walleye populations and data sources are as in Figure 7.13.
Walleye and Sauger Life History
Prey size has been shown to be a critical factor affecting growth efficiency in fish (Palo-
heimo and Dickie 1966; Ryder and Kerr 1978; Pazzia et al. 2002; Sherwood et al. 2002). If a
predator lives in a community where a broad range of prey sizes is available, the transition to
larger prey species occurs smoothly as the predator grows and potential growth rate remains
constant. If the prey field is truncated such that the availability of prey of suitable size does
not keep pace with increases in predator size, then potential growth rate will decline owing
to the increased foraging costs associated with capturing smaller prey. This decline in growth
potential is expected to have implications on size of maturity and maximum body size. Life
history theory predicts that optimal size of maturity and maximum size are smaller when the
prey field is truncated (e.g., Lester et al. 2004b).
In Ontario, ciscoes provide an important energy-rich large prey item for walleyes (Ryder
and Kerr 1978; Colby et al. 1987; Henderson et al. 2004; Kaufman et al. 2006, 2009). In Lac
des Milles Lacs, Ontario, an increase in walleye growth rate coincided with a diet switch from
yellow perch and sticklebacks to coregonids (primarily cisco) (Colby et al. 1987). Hender-
son et al. (2004) found that walleyes had higher growth efficiencies, lower ingestion rates,
and lower activity levels in lakes where ciscoes were available. Kaufman et al. (2006, 2009)
reported similar findings, but also noted that females attained a larger asymptotic size when
ciscoes were available as prey. Stomach content analysis revealed that walleyes larger than
175 mm TL consumed ciscoes, but ciscoes were more important to larger walleyes. In lakes
without ciscoes, where walleyes fed on yellow perch and benthic invertebrates, the frequency
of perch in the diet increased with walleye size. In lakes with ciscoes, mean prey size was
larger because walleyes switched from smaller perch to larger ciscoes as they grew.
In lakes where forage fish are absent or scarce, walleyes may feed on invertebrates dur-
ing their whole ontogeny (see references in Colby et al. 1979). Given the importance of prey
size in supporting growth, one expects that walleyes in these lakes will be smaller. Growth
studies of walleyes that rely primarily on nonfish prey throughout their ontogeny are scarce.
Paradis et al. (2006) conducted a field study designed to compare growth of piscivorous and
nonpiscivorous walleyes in 10 small (surface area, 25–142 ha) headwater lakes in Québec.
Those investigators found that piscivorous males had slightly higher growth than nonpisci-
vores, but females exhibited no difference. Because assignment of trophic specialization of
each fish was based on stomach contents from one midsummer sampling event, it is question-
able whether this study correctly separated piscivorous and nonpiscivorous fish. It is possible
that all fish fed on a combination of fish and benthic invertebrates and the sampling method
merely identified their most recent meal.
The headwater lakes studied by Paradis et al. (2006) are noteworthy because the maxi-
mum size of walleyes was relatively small (approximately 450 mm TL for both sexes). In
contrast, our growth summary of North American lakes yielded overall means of 701 mm for
females and 568 mm for males. These headwater lakes are also remarkable for their high de-
gree of benthivory. Only 16% of walleyes had stomach contents that were exclusively fish and
the percentage mass of fish in stomachs was not related to walleye size. Given this high degree
of benthivory, we speculate that small body size was due to the lack (or low abundance) of
large prey needed to sustain growth of larger walleyes. Ciscoes were not present in any lakes.
Yellow perch were present but not abundant, perhaps due to the presence of northern pike,
another top predator.
To our knowledge, the only documentation of a walleye population that feeds exclusively
on invertebrates throughout their adult life is in Charlie Lake, British Columbia (Figure 7.15)
38 Chapter 7
(Baccante and Down 2003). Growth is similar to what Paradis et al. (2006) observed for
small headwater lakes in Québec. Female walleyes typically mature at age 5 when they reach
a length of 350 mm. Growth is very slow after maturation and, despite living upwards of 15
years, total length never exceeds 450 mm.
Perhaps the most poignant example of the effect of prey size on walleye size comes from
U.S. reservoirs where prey fish have been introduced to enhance walleye growth. For example,
rainbow smelt were introduced into the Horsetooth Reservoir, Colorado, in 1983 to increase
prey availability for walleyes (Johnson and Goettl 1999). Before the introduction, very few
large (i.e., > 450 mm) walleye were caught in surveys. The introduction was initially highly
successful. Rainbow smelt increased in numbers and walleye diet switched from mostly mac-
roinvertebrates to smelt, resulting in a 50% increase in growth rate and much larger catches
of large walleyes. Although this experiment demonstrated that prey size can have a dramatic
effect on walleye size, the benefits of the rainbow smelt introduction were short lived because
cascading effects subsequently resulted in a walleye recruitment failure (Mercado-Silva et al.
In summary, theoretical and empirical studies indicate that the prey size spectrum is an
important determinant of body size in walleyes. Our understanding of this effect is hampered
because many studies that report on walleye growth fail to provide details about the food en-
vironment. Nevertheless, it seems safe to conclude that large body size in walleyes is attained
only when there is an abundance of large prey items (see Chapter 8 for additional discussion
of feeding and bioenergetics).
Age (years)
Mean total length (mm)
0510 15 20 25 30
Figure 7.15. Example of lifetime growth pattern for a nonpiscivorous walleye population
(Charlie Lake, British Columbia). Mean length at age is plotted against age for males (trian-
gles) and females (circles). Maturity status of each age-group is indicate by open (immature)
and closed (mature) symbols. The dashed line describes the growth trajectory of immature
fish. Data source is D. A. Baccante (unpublished).
Walleye and Sauger Life History
Our description of walleye life history has focused on population differences and the ex-
tent to which traits of a population can be predicted by environmental variables (e.g., climate,
size spectrum of the prey). Life history traits, however, are not population constants. Within a
population they are expected to vary over time, partly because environmental variables fluctu-
ate, but especially because most life history traits are density-dependent. Because growth rate
depends on the per capita availability of food, changes in walleye abundance are expected to
affect growth rates and have cascading effects on other life history traits.
Processes such as growth, mortality, and reproduction are density-dependent if their rates
change depending on the number of individuals in a population (see Chapter 9 for additional
discussion of relationships between recruitment, growth, and mortality). Density-dependent
processes are said to be compensatory when rate changes promote a numerical increase in
the population at low densities (Rose et al. 1999). Compensatory density-dependence permits
populations to persist under conditions of increased mortality and is the basis of concepts such
as surplus production and sustainable harvest. Without compensation, any increase in mortal-
ity would result in population decline and eventual extinction. Thus, compensatory density-
dependence must exist for naturally stable populations to persist under harvesting.
Our understanding of density-dependent processes in walleye is limited because within-
population variation in abundance is needed to measure this effect. As Carlander (1997) points
out, it is not absolute density of the fish which has such a dominant effect on growth, but it is
the population density in relation to carrying capacity. Walleye population density is highly
variable among lakes (Baccante and Colby 1996; Nate et al. 2003; Sass et al. 2004). Based on
data from 85 lakes, Baccante and Colby (1996) reported a median adult density of 14.8 fish/
ha and a maximum density that exceeded 100 fish/ha. Sass et al. (2004) examined growth in
254 Wisconsin walleye populations—where adult density ranged from 1 to 36 fish/ha—and
found weak evidence of density-dependent growth among populations. In contrast, there was
strong evidence of density-dependent growth within populations. In a subsequent paper, Sass
and Kitchell (2005) showed that among-population comparisons revealed stronger evidence
of density-dependent growth when abiotic factors, potentially accounting for variation in car-
rying capacity, were included in the analysis.
Compensatory changes in walleye growth, age of maturation, or fecundity have been
reported in case studies where dramatic changes in walleye abundance have occurred. Table
7.1 provides a summary of reported compensatory changes in walleye. The degree of com-
pensation is expected to depend on the magnitude of change in abundance, but this relation-
ship cannot be determined from these studies because precise measures of walleye density
are usually lacking. The potential magnitude of compensation is demonstrated by the results
of an extreme removal experiment on Henderson Lake, a small (area = 150 ha) unexploited
lake in Ontario (Reid and Momot 1985). Aggressive harvesting reduced adult walleye density
approximately 10-fold (from 22 fish/ha to less than 2 fish/ha) and resulted in increased prema-
turation growth, earlier maturity, and increased relative fecundity. Over a 5-year period, size
at age 4 increased from 350 to 425 mm, age at maturity decreased from 4.6 to 3.2 years, and
fecundity of 500-mm fish increased from 55,000–82,000 eggs per fish. The magnitude of this
within-lake variation in life history traits is similar to that observed among populations living
in similar climatic zones (Figures 7.3B, 7.5A, and 7.11B). It suggests that when one controls
for climate, among-population variation in life history traits may reflect the degree of density-
40 Chapter 7
Publication Study site Methods Results
Dobie (1956) Rearing pond Variation in growth given six-fold • TL at 60 d increased from 40 to 75 mm (+88%)
in density of ngerlings as density declined
Carlander and Clear Lake Variation in growth from 1935–1957 • Length at age 3 inversely related to year-class
Whitney (1961) strength
Anthony and Lake Nipissing Compared growth during periods of high • Length at age 3 increased from 240 to 310 mm
Jorgensen (1977) (1967–1976) and low (1936) walleye (+ 29%)
Spangler et al. Lake Erie Compared growth and maturation during • Length at age 2 increased from 180 to 370 mm
(1977b) periods of high (1927–1933) and low (+100%)
(1964–1966) walleye abundance • Female age at maturity decreased from 4–5 to 3
years (−30%)
• Male age at maturity decreased from 3–4 to 2
years (−42%)
Muth and Wolfert Lake Erie Examined changes in growth and • Standing stock increased three-fold (from 1976
(1986) maturation when abundance increased to 1983)
following closure of the shery in 1970 • Length of age-0 sh in fall decreased from 240
(due to mercury contamination) mm in 1961 to 190 mm in 1983 (−21%)
• Percent of age-2 females mature declined from
80% in early 1970s to 7% in 1983
Shuter and Koonce Lake Erie Examined changes in growth and • Length at age 4 increased from 350 to 500 mm
(1977) maturation over a period (1947–1963) as abundance declined; +42%
when a large decrease in walleye • Decrease in age at maturity
abundance occurred; • Moderate increase in length at maturity
Index of abundance declined from 120
to 10 sh per trap-net lift
Table 7.1. Evidence of density-dependent variation in walleye growth, maturation, and fecundity.
Walleye and Sauger Life History
Publication Study site Methods Results
Kempinger and Escanaba Lake Examined changes in growth over a • Age-specic length increments were negatively
Carline (1977) period (1955–1969) when walleye related to walleye biomass (although not
density uctuated signicant)
• Figure 2 in reference suggests annual length
increment at age 4 increased from 25 to 60 mm
as biomass declined from 30 to 5 kg/ha
Reid and Momot Henderson Lake Experimental harvesting reduced adult • Length at age 4 increased from 350 to 425 mm
(1985) walleye abundance approximately (+21%)
10-fold (22 to 2 sh/ha) • Age at maturity decreased from 4.6 to 3.2 years
• Fecundity at 500 mm TL increased from 55,000
to 82,000 eggs per sh (+50%)
Baccante and Reid Savanne Lake Experimental harvesting reduced walleye • Fecundity at 500 mm TL increased from
(1998) abundance 25%; compared fecundity 47,800 to 59,900 eggs per sh (+25%)
before and after reduction
Fox and Flowers Rearing ponds Examined growth during 6 weeks after • Length at 6 weeks increased from 41.3 to 48.9
(1990) stocking larval walleye; three-fold mm (+18%); weight increased from 470 to 788
variation in larval density g (+68%)
Muth and Ickes Lake Erie Fecundity compared in periods of low • Mean egg production of the dominant spawner
(1993) (1966) and high (1990–1991) age group ( 4 to 8 years) was 25% lower when
abundance abundance was high
Doire et al. (2002,
cited in Simoneau et Five small lakes Compared growth before and after • Growth rate increased 30% in some lakes
al. 2005) of mid-northern intensive experimental shing
Table 7.1. Continued.
42 Chapter 7
Publication Study site Methods Results
Schueller et al. Big Crooked Lake Examined growth, maturation and • Length at age 3 increased from 305 to 370 mm
(2005) fecundity over a period (1997–2003) (+21%)
of declining walleye abundance; • Female age at maturity declined from 4.9 to 3.9
Adult abundance declined from 17 to years (−20%)
7 sh/ha • Variation in fecundity was not related to density
Venturelli et al. Eight lakes in Ontario Compared pre-maturation growth rate • Pre-maturation growth rate was, on average,
(2009) during periods of high and low 1.3-fold higher when abundance was low
abundance • For a population where GDD = 2200, this
change implies length at age 3 increases from
330 to 419 mm (+26%)
Table 7.1. Continued.
Walleye and Sauger Life History
dependent compensation that can exist. It is not recommended, however, that this optimistic
view of compensation be adopted for managing fisheries. A precautionary approach could
be adopted, for example, by assuming that 50% of variation among populations predicts the
potential magnitude of density-dependent compensation.
Parasites in walleye and sauger are virtually universal; they are found in most populations
and nearly all individuals have some parasites (Colby et al. 1979; see Table 6.4 in Chapter 6).
However, very little is known about negative effects that parasites and disease have on wall-
eyes and saugers particularly when it comes to understanding the influence they have on the
life history strategies and population dynamics discussed thus far. Undoubtedly, heaver para-
site loads or incidences of disease would probably reduce overall fitness affecting growth, age
at maturity, and mortality among other life history traits, and warrants further study. Diseases
are discussed in more depth in Chapters 6 and 13.
Like walleye, the sauger is a member of the family Percidae; similarities and differences
in their life history traits are summarized in Table 7.2. The distribution of sauger in North
America, like walleye, is widespread primarily in northern latitudes. While both species co-
occur across much of their ranges, saugers are more limited in distribution, both geographi-
cally and environmentally. They are found primarily in larger, more turbid or stained rivers
or large shallow lakes (Davidoff 1978; Rawson and Scholl 1978; Hesse 1994; Vallazza et al.
1994; Pegg et al. 1997); rivers are believed to be their evolutionary origin (Balon et al. 1977).
Saugers range across Canada from southern and mid-latitudes of Alberta, Saskatchewan,
Manitoba, through Ontario to nearly James Bay, and east across Québec to the St. Lawrence
River. Their range extends south into the United States through New England along the west
side of the Appalachian Mountains south to the Ohio River systems, west to Arkansas and
Tennessee, and northwest to Montana and Wyoming in the Missouri River system (Scott and
Crossman 1973; see Chapter 4). Although both species are extensively managed, the distribu-
tion of sauger has not been artificially expanded nearly to the degree that has occurred with
walleye, although stocking can be common locally (Lynch et al. 1982; Flamming and Willis
1993; Summers et al. 1994; White and Schell 1995) and their abundance across their native
range appears to be in decline (Pegg et al. 1997; Bellgraph et al. 2008). Recent declines of
sauger distribution and abundance have raised concerns. Jaeger et al. (2005) felt that the
highly migratory nature of saugers, high site fidelity, and a wide array of habitats and turbidi-
ties needed for successful execution of its complete life cycle make it sensitive to habitat frag-
mentation by dams. Sauger populations are believed to be in decline in some portions of their
range, but particularly in large rivers where impoundments have altered access to traditional
spawning areas and have reduced suspended sediment loads (Bellgraph et al. 2008). In Norris
Reservoir, Tennessee, saugers do not spawn in the impoundment proper, but rather in tributary
streams (Fitz and Holbrook 1978).
Where walleyes and saugers exist sympatrically, hybridization and backcrossing occur,
and hybrid progeny are referred to as saugeyes (see Chapter 3 for additional details). Hybrids
44 Chapter 7
Life history characteristic Walleye Sauger References
Season March to June, depending on Starts at the tail end of walleye Derback (1947); Eschmeyer
latitude. spawning. (1950); Preigel (1970); Scott
In the north, immediately after and Crossman (1973)
Temperature Normally 6.7 to 8.9°C Begins at temperatures 3.9– Carufel (1963); Scott and
Documented from 5.6 to 14.4°C. Optimal 7.7°C Crossman (1973); Colby et. al.
11.1°C. Optimal = 10.3°C Follows walleye spawning. (1979); Hasnain et al. (2010)
Habitat Shorelines and shallow Same as walleye. Cobb (1923); Eschmeyer
offshore reefs in lakes. (1950); Crowe (1962); Preigel
Spawning Rapids and rifes in rivers (1964, 1969); Walburg (1972);
Primary substrates are gravel Colby et al. (1979); Stevens
and cobble, but may be mixed (1990); Jeffrey and Edds
with sand and boulders. (1999); Jaeger et al. (2005);
Site delity for return Raabe (2006); Bellgraph
spawners. et al. (2008)
Mating Nocturnal Same as walleye. Ellis and Giles (1965);
Polygamous McElman (1983)
Broadcast eggs
No parental care
Egg diameter 1.3–2.1 mm 1.0–1.9 mm Smith (1941); Carufel (1963);
Smaller than walleye Nelson (1968a); Colby et al.
(1979); Graeb et al. (2007)
Fertilization 3–100% Colby et al. (1979)
Table 7.2. Comparison of life history characteristics between walleye and sauger.
Walleye and Sauger Life History
Life history characteristic Walleye Sauger References
Incubation Decreases with increasing Decreases with increasing Nelson (1968a,1968b);
temperature temperature Walburg (1972)
14 d at 12.8°C 9 d at 12.8°C, 21 d at 8.7°C
Temperature 9–15°C 4.5–12.8°C Scott and Crossman (1973);
allowing greatest Colby et al. (1979)
hatching success
Optimal 13.5°C 12.2°C Hasnain et al. 2010
Length at hatch 6.0–8.6 mm 4.5–6.2 mm Scott and Crossman (1973);
Colby et al. (1979)
Length at yolk 10 mm Nelson (1968a)
sac absorption
Scale development 24–45 mm TL Becker (1983)
Development of 37–140 mm TL Ali and Anctil (1977); Collette
tapetum lucidum Developed only in the ventral More uniformly distributed in et al. (1977); Bulkowski and
region of the retina. the retina. Meade (1983); Braekevelt et
Age 0 Adapted for dimmer light than al. (1989); Vandenbyllaardt
walleye. et al. (1991)
Response to light Shifts from positive to Similar to walleye but sauger Scott and Crossman (1973);
negative when 32–40mm TL have higher negative Ali and Anticil (1977);
Coincides with development phototropism than walleye. Hackney and Holbrook (1978);
of the tapetum lucidum. Bulkowski and Meade (1983);
Amadio et al. (2005)
Table 7.2. Continued.
46 Chapter 7
Life history characteristic Walleye Sauger References
Ontogenetic diet Initially feeds on zooplankton, Diet similar to walleye. Smith and Moyle (1945);
Age 0 shifts (onset of then benthos and then sh. Piscivorous when 70–110 mm Smith and Pycha (1960);
piscivory) Onset of piscivory is typically TL. Nelson (1968b); Walker and
at 50–80mm TL. Appelgate (1976); Mathias and
Li (1982); Frey (2003);
Galarowicz et al. (2006)
Length at age 1 76–375 mm 74–244 mm Colby et al. (1979); Carlander
(1997, Table 8-6)
Diurnal feeding Primarily nocturnal, but more Same as walleye. Rawson and Scholl (1978);
pattern daytime foraging when When sympatric with walleye, Wahl and Nielsen (1985);
turbidity is high. sauger forage more Lyons (1987); Graeb et al.
demersally. (2007)
Prey-predator Average 44% when 60 mm TL Parsons (1971); Swenson
length-ratio Average 28% when 400 mm TL (1977); Galarowicz et al.
Juvenile “walleye larger than 40 mm (2006)
(age 1 to actually lose weight when
maturation) forced to feed exclusively on
plankton” (Galarowicz et al. 2006)
Diet System-specic. Consumes a Same as walleye. Mathias and Li (1982); Wahl
wide array of sh species. and Nielsen (1985); Lyons
Also consume larger (1987); Frey (2003);
invertebrates when they are Galarowicz et al. (2006);
readily available. Kaufman et al. (2009)
Table 7.2. Continued.
Walleye and Sauger Life History
Life history characteristic Walleye Sauger References
Final temperature 19.6°C 22.5°C Hasnain et al. (2010)
Optimal growth 22.0°C 22.1°C Hasnain et al. (2010)
Length at 50% Female: 330–560 mm Male: 250–450 mm Preigel (1969, sauger); this
maturity Female: 284 mm Male: 249 mm chapter (walleye)
Age at 50% Female: 4–14 years Combined sex: 2–8 years Carufel (1963, sauger); Vasey
maturity Male: 2–13 years (1967); Walburg (1972);
Increases south to north. Increases south to north. Carlander (1997); this chapter
Adult (walleye)
Longevity 3–30 years 2–13 years Carlander (1997, Table 8-6,
Increases south to north. Increases south to north sauger); this chapter (walleye)
Sexual dimorphism Begins at maturity Mature females may be Hassler (1957); Carlander
Females larger than males slightly larger than males (1997); Quist et al. (2003)
at maturity
Females attain a larger
maximum length
Mean TL at Female: 44–830 mm Combined sex: 0.11–0.55 Carlander (1997, sauger); this
maximum age (mean = 670 mm) chapter (walleye)
Male: 383–700 mm
(mean = 540 mm)
Table 7.2. Continued.
48 Chapter 7
Life history characteristic Walleye Sauger References
Von Bertalanffy Combined sex: 443–1,020 mm Quist et al. (2003, walleye);
growth parameter (L) (mean = 733 mm) Sass et al. (2004, walleye)
Von Bertalanffy Combined sex: 0.07–0.59 Combined sex: 0.11–0.55 Braaten and Guy (2002,
Adult growth parameter (mean = 0.20) (for latitudes 42° to 48° N) sauger); Quist et al. (2003,
(k, per year) Increases with growing walleye); Sass et al. 2004,
Absolute fecundity 10,000–400,000 10,000–209,000 Carlander (1997, sauger);
(no. eggs/female) Increases with body size. Increases with body size. this chapter (walleye)
Relative fecundity 18,000–85,000 33,000–106,000 Carlander (1997, sauger); this
(no. eggs/kg) chapter (walleye)
Table 7.2. Continued.
Walleye and Sauger Life History
and their backcrosses are fertile and are difficult to discriminate from either parental spe-
cies morphologically (Clayton et al. 1973; Billington et al. 1997; Fiss et al. 1997). Saugeyes
occur both naturally (Billington et al. 1997) or are produced purposefully in hatcheries and
stocked (Heidinger and Brooks 1998) (see Chapters 12 and 13). Natural hybridization occurs
as saugers spawn at the tail end of walleye spawning in similar habitats; alteration of native
habitats may increase hybridization rates (Billington et al. 1997). In the Illinois River, Illinois,
spawning by walleyes and saugers overlap considerably and hybridization may be facilitated
by high turbidity levels (140 Jackson Turbidity Units), which may reduce visual recognition
of potential conspecific mates (Mills et al. 1966; Heidinger and Brooks 1998). Saugeyes ex-
hibit hybrid vigor, growing faster than either parental species, and they are more tolerant than
walleyes of warm, eutrophic reservoir conditions (Lynch et al. 1982; Malison et al. 1990; Fiss
et al. 1997). However, stocking saugeyes into systems where walleyes and saugers are native
or already established can be a problem. In systems where saugeyes become established, vi-
able walleye populations may become difficult to maintain or establish although causality for
walleye declines is unclear (Fiss et al. 1997), and where stocked, saugeyes can backcross with
either parental stock and produce viable offspring (White and Schell 1995; Fiss et al. 1997).
Environmental features associated with sauger populations help explain distributional
patterns. In general, saugers prefer warm deep pools and runs with low water current veloci-
ties and high turbidity (Crance 1988; Vallazza et al. 1994; Gangl et al. 2000). In the Wind
River, Wyoming, sauger were most abundant in river reaches where pools and runs were more
than 1 m deep, daily summer water temperatures exceeded 20°C, and alkalinity exceeded 130
mg/l (Amadio et al. 2006). Summer thermal preferences of adult saugers are 20–28°C (Dendy
1948; see Chapter 6) and thermal bioenergetic constraints may limit their northern distribu-
tion (Braaten and Guy 2002). Ryder et al. (1964) identified that the northern distribution of
sauger appears to correspond to the 15.6°C isotherm. Walleyes and saugers have a somewhat
similar physiological thermal optima (mean of tolerance, preference, metabolic rate, perfor-
mance, circulation, and growth) of approximately 22°C (e.g., see Chapter 6), although saugers
favor lower temperatures for spawning (optimal spawning temperature: walleye = 10.3°C,
sauger = 7.7°C; Hokanson 1977; Hasnain et al. 2010). Interestingly, optimum egg develop-
ment temperatures are more similar than spawning temperatures with eggs developing opti-
mally at 13.5°C for walleye and 12.2°C for sauger (Hasnain et al. 2010). Dendy (1948) found
saugers occurred at deeper depths and therefore cooler water than did walleyes (18.6–19.2°C
for saugers versus 20.6–23.2°C for walleyes) in Tennessee reservoirs. Swenson and Smith
(1976) found similar thermal trends in Lake of the Woods, Minnesota. Amadio et al. (2005)
determined that the upstream distributional boundaries of saugers in four western rivers cor-
responded to low summer temperatures, higher channel slopes, and water diversion dams that
limited upstream distribution. The highest sauger biomass was associated with river reaches
where pool and run depths were greater than 1.0 m, the mean daily summer water tempera-
tures were over 20°C, and alkalinity was greater than 130 mg/L. In the southeastern United
States, important sauger fisheries were developed when reservoirs impounded their formerly
riverine habitats; sauger fisheries primarily occur in low-gradient main-stem reservoirs (e.g.,
Cumberland and Tennessee river reservoirs) whereas walleyes more commonly typify up-
land tributary reservoirs (Hackney and Holbrook 1978). In Tennessee River impoundments,
saugers are relatively abundant at elevations below 250 m above sea level while walleyes are
sporadic below 300 m below sea level but are more common at higher elevations (Hackney
and Holbrook 1978). This trend appears to correspond to lower elevation main-stem reser-
50 Chapter 7
voirs being warm, shallow, and turbid and having large inflowing rivers in them where saugers
are more common, versus cooler, deeper, clearer, higher elevation systems that lack large
tributary streams where walleye are more common.
In natural systems, saugers and walleyes appear to partition habitat relative to turbid-
ity and temperature, but in altered systems they may overlap more, at least temporarily as
populations adjust (Bellgraph et al. 2008). Saugers exhibit less environmental plasticity than
do walleyes, but can be sympatric over a wide geographic distribution where environmental
conditions are suitable for both species. Saugers also have scotopic vision similar to walleye
because of the presence of the tapetum lucidum, and they prefer habitats with low light condi-
tions (Moore 1944; Ali and Anctil 1968, 1977). However, saugers are even more negatively
phototaxic than walleyes; walleyes have more retinal epithelial pigment and less reflecting
material than saugers from similar localities, which correlate to differences in habitat selec-
tion and behavior. As a result, saugers prefer darker, more turbid water than do walleyes (Ali
and Anctil 1968, 1977). In fact saugers not only have more reflecting material in their eyes,
they have it more evenly distributed within the retina making them adapted to more turbid
systems, particularly where clay minerals may remain in suspension. As a result, saugers
prefer large turbid lakes such as Lake Winnebago, Wisconsin, Lakes Manitoba and Winnipeg,
Manitoba, and larger turbid rivers such as the Yellowstone and Missouri rivers and lower sec-
tions of their respective tributaries (Hesse 1994).
Saugers are the most migratory of all percids and will migrate hundreds of kilometers to
spawn (Scott and Crossman 1973; Collette et al. 1977; Bellgraph et al. 2008; Kuhn et al. 2008).
In spring, mature adults usually move upstream and spawn in main river channels, tributary
streams, or along lake shorelines, although in the Yellowstone River, there is a downstream
spawning migration (Jaeger et al. 2005). In the middle Missouri River, saugers migrate up to
260 km with similar length migrations occurring in the lower Yellowstone River (<300 km)
(Jaeger et al. 2005; Bellgraph et al. 2008). In Watts Bar Reservoir, Tennessee, saugers migrate
160 km from the lower reaches of the reservoir upriver to the upstream dam for spawning
(Minton and McLean 1982). Graeb et al. (2009) found that saugers shifted habitat selection
from historical remnant river reaches that had been altered by Fort Randall Dam in the Mis-
souri River to occupy new lower river delta habitats where physical conditions were more like
the historical predam state. These new habitats were warmer, more turbid, and actively mean-
dering, thereby providing suitable habitat. Impoundments not only limit the migratory nature
of saugers, but the reduction in sediment load and the concomitant reduction in turbidity has
reduced the length of suitable habitat for saugers throughout western river systems.
Growth of saugers is highly variable across its range, and depends on temperature and
food diversity and abundance. Saugers do not grow as large as walleyes, but can have faster
seasonal growth rates, and maximum growth and food consumption can occur later in the
season than in walleyes. In a study of feeding ecology of saugers in the Ohio River, Wahl
and Nielsen (1985) found fastest growth for saugers occurred during October and November,
compared with August and September for walleyes in Lake of the Woods, Minnesota (Sw-
enson and Smith 1973). Higher growth and food consumption of saugers in the Ohio River
continued into winter. This is thought to be due to different temperature patterns and increased
availability of gizzard shad. This same seasonal growth pattern was observed by Minton and
McLean (1982) for saugers in Watts Bar Reservoir. However, Minton and McLean (1982) also
pointed out that this increased winter growth pattern observed in some sauger populations,
does not occur in all populations, and is highly dependent on prey abundance and composi-
Walleye and Sauger Life History
tion. In Norris Reservoir, Tennessee, Fitz and Holbrook (1978) found that sauger growth rates
were faster than in northern populations.
Saugers vary among systems in their degree of sexual dimorphism. Female saugers are
either similar in size to males or can be larger than males, although in these systems the dif-
ferences are not as large as is seen in walleyes (Carlander 1950; Hassler 1957; Quist et al.
2003b). Length at age between male and female saugers in Garrison Reservoir, North Dakota,
is nearly equal for ages 1 and 2, and by age 5, there is less than 3 cm difference (Carufel
1963). In Lake of the Woods, age-5 and age-6 male and female saugers differ less than 2 cm
(standard length, SL) (Carlander 1950). Age at maturity ranges from 2 to 8 years depending
upon latitude (climate and prey); in Lewis and Clark Lake, South Dakota, saugers mature in
3–4 years (Walburg 1972).
Fecundity of saugers in Garrison Reservoir, North Dakota, increased with size and age,
ranging from 6,500–17,000 eggs/kg (Carufel 1963). In that study, age-3 saugers produced
13,000 eggs whereas age-7 fish produced 101,000 eggs. Simon (1946) reported 50,000
eggs for a 1.4-kg sauger from Wyoming. Fecundity of age-2 Lake Erie saugers ranged from
58,000–77,400 eggs (Rawson and Scholl 1978). Gamete maturation in walleye and sauger
occurs at temperatures below 12°C, which may limit their southern distribution, although the
presence of centrachids may also play a role as well (Collette et al. 1977). A summer gonadal
refractory period ensures an annual reproductive cycle in walleye and sauger (Collette et al.
1977). Saugers spawn at approximately the same temperature as do walleyes: e.g., 3.9–11.7°C
in North Dakota (Carufel 1963), 14.4°C in Tennessee (see Hokanson 1977), 7.2–8.3°C in a
Kansas reservoir (Jeffrey and Edds 1999), 6.1°C (Nelson 1968b), 2.0–15.6°C (Preigel 1969;
Hokanson 1977). In sympatry, sauger typically spawn at the tail end of walleye spawning.
Like walleyes, saugers are broadcast spawners and provide no parental care to eggs or
young. Similarly, eggs are only adhesive briefly although accounts vary as to the degree of
adhesion and duration of adhesiveness. Spawning by saugers generally occurs over coarse
substrates (i.e., gravel and larger-sized substrates) in main-stem and tributary river channels
and tailwaters below reservoirs (Bellgraph et al. 2008). In rivers, saugers spawn in habitats
that create optimal combinations of water velocities and rock substrates. In Lake Winnebago,
Wisconsin, saugers spawn along rocky shorelines (Preigel 1969). In western rivers, saugers
use meanders along natural bedrock outcrops during the spawning season (Nelson 1968b;
St. John 1990; Hesse 1994; Jeffrey and Edds 1999). Staging or spawning of saugers in bluff
pools (i.e., pools hydraulically constrained by bedrock outcrops) and artificially created rip-
rap pools may occur because they combine suitable substrates and velocities for spawning,
but also have secondary currents that may offer velocity refuge for staging fish (Bellgraph et
al. 2008). In Lake Erie, saugers spawn along shale bedrock ridges and sand–gravel substrates
in the Sandusky River, and cobble–boulder riffles in the Maumee River (Rawson and Scholl
1978). In the Yellowstone River, saugers show site fidelity with respect to spawning areas
(Jaeger et al. 2005).
Sauger eggs are similar in size to walleye eggs. Diameter of sauger eggs from Garrison
Reservoir, North Dakota, ranged from 1.0 to 1.8 mm (Carufel 1963). Eggs in Missouri River
reservoirs ranged in diameter from 1.3 to 1.5 mm with their caloric density (cal/g dry weight)
varying from 2,600–3,400; caloric content increased with increasing TL of females (Graeb
et al. 2007). Sauger eggs have been collected in drift samples below spawning sites on the
Missouri River (Nelson 1968b); 68% of eggs collected with suction pumps at depths between
0.6 and 4.0 m in the Missouri River were viable immediately after spawning (Nelson 1968b).
52 Chapter 7
Female saugers of intermediate age (age 4–6) and large sizes (460–520 mm TL) in Missouri
River reservoirs had the highest quality eggs based on size and caloric content (Graeb et al.
2007). Eschmeyer and Smith (1943) reported saugers did not spawn at temperatures below
10°C and eggs were deformed when low temperatures persisted.
Sauger hatching occurred in 21 d at 8.7°C in Lewis and Clark Lake, South Dakota (Wal-
burg 1972). Nelson (1968b) also found hatching occurred in 21 d at 8.3°C and 9–14 d at
12.8°C (Nelson 1968a). At hatching, larvae range in size from 4.5 to 6.2 mm TL and remain
sedentary on the bottom for approximately 7–9 d until their yolk is absorbed. Hatchery-reared
sauger ranged from 4.62 to 5.09 mm TL at hatching (Nelson et al. 1965). Colder water tem-
peratures increase losses as larval development is reduced thus subjecting larvae to planktonic
drifting for longer periods of time (Walburg 1972). Larvae (4.8–7.46 mm TL) in the Missouri
River drifted downstream after hatching (Nelson 1968b) and arrived downstream in the res-
ervoir approximately 1 week after initiating drifting. Considerable numbers of larval saugers
are lost through dams on the Missouri River while they are drifting downstream. Shorter
water-residence times in the reservoir increase water velocities sufficiently high enough to
carry drifting larvae through the lake proper and to the dams (Walburg 1972).
Sauger year-classes fluctuate widely in southern U.S. reservoirs and appear to be a rela-
tively synchronous, region-wide phenomenon (i.e., years of high and low abundance occur
across systems) although specific factors responsible for year-class strength is not well studied
(Hackney and Holbrook 1978). Adult year-class strength was inversely related to water level
fluctuations over the spawning grounds during egg incubation in Missouri River reservoirs
(Nelson 1968b). Fluctuating water levels eliminated viable eggs presumably due to stranding
(Nelson 1968b). Benson (1973) found 10-fold increases in young sauger abundance in years
after high diel water fluctuations from hydropower operations were reduced. Pitlo (2002)
found that year-classes of both saugers and walleyes (fall age 0) were correlated with spring
water temperatures (April 15–May 5) in pool 13 of the upper Mississippi River. Walburg
(1972) found 80% of the variation in sauger year-class strength in Lewis and Clark Lake was
explained by water level fluctuation, reservoir exchange rate, and water temperature.
As with walleye, the diet of sauger is a function of ontogeny and prey availability (see
Chapter 8). Larvae begin feeding on zooplankton (e.g., Cyclops spp.) before the yolk sac is
completely absorbed and then shift to larger zooplankton with increasing size (e.g., Diap-
tomus spp., Daphnia spp.); distinct selectivity of zooplankton occurs (Nelson 1968b). As
saugers grow, they become piscivorous. Adult saugers in the Ohio River consumed gizzard
shad, emerald shiner, and other fishes, with prey consumption averaging 1.1% of their body
weight per day (Wahl and Nielsen 1985). They fed on smaller fish at warmer temperatures and
larger fish at cooler temperatures seasonally. Depending on the system, saugers may feed on
the same prey items as walleyes suggesting potential diet overlap and resource competition,
but saugers and walleyes may partition space (saugers occurring at deeper depths and in some
systems forage on different prey species) thus reducing competition. In lakes where saugers
are sympatric with walleyes and yellow perch, the proportion of the community consisting
of walleyes and yellow perch is reduced (Clady 1978). In the middle Missouri River, diet
overlap between walleyes and saugers was substantial during spring and summer (Bellgraph
et al. 2008); both preyed upon emerald shiners and stonecats in spring, and stonecats, emerald
shiners, macroinvertebrates, and mottled sculpins. In Lake of the Woods, saugers selected
primarily benthic trout-perch throughout summer but increased yellow perch in their diet in
July and August; their consumption rates increased with increasing wave activity (Swenson
Walleye and Sauger Life History
1977). Walleyes in the same system foraged more on yellow perch, rainbow smelt, and Not-
ropis spp. over the same time period. This diet difference suggests that resource partitioning
can and does occur at times between these species, although the phenomenon is not universal
across systems.
Walleye and sauger have successfully colonized a wide array of habitats across northern
latitudes of North America. These species occur sympatrically and allopatrically; where sym-
patric, they may hybridize and backcross, particularly in altered environments. Walleyes ex-
hibit a variety of life history strategies across a wide geographic and climatic region of North
America, exhibiting considerable plasticity in habitat use, growth patterns, survival, and re-
cruitment rates. Their success in a variety of different environmental conditions in lakes and
rivers underscores a complex, yet flexibly adaptive organism suited to colonize and persist
in these habitats. While closely related, saugers exhibit a somewhat less flexible life history
strategy, and even hybridize and backcross with walleye under certain conditions. Life history
strategies within a system vary with abiotic and biotic factors which influence growth, matu-
ration, reproduction, recruitment, and survival. These factors vary across the geographic dis-
tribution of both species, which is strongly influenced by climate (i.e., growing degree-days).
Management of these species that recognizes the differences in life history variation that has
been successful locally will most likely have the most successful long-term outcomes.
Dominic Baccante acknowledges his friend Peter Colby for the many good memories,
fun, and productive times at the Walleye Research Unit in Thunder Bay, Ontario. Also ap-
preciated is the help of Jessica Baccante, Heather Hopkins, and Roxanne Smith, all with the
British Columbia Ministry of Environment, for helping with all aspects of literature search,
maintaining a reprint library, and proof-reading. Serena Baccante drew the walleye sketches
used in Figure 7.2. We thank R. Ryder, J. Deacon, and W. Wawrzyn for their contributions
to fisheries and aquatic resources and the incredible professional mentorship they provided
throughout their lives to so many. C. Jacobson provided support and inspiration. We gratefully
acknowledge the Ontario Ministry of Natural Resources and the Ministère des Ressources
Naturelles du Québec for providing access to walleye survey databases and Trevor Middel for
producing the map in Figure 7.1. We thank R. Klumb, P. Brown, B. Sloss, B. Jackson, and A.
Musch who all reviewed earlier drafts of the chapter.
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