No abstract

We develop a model for somatic growth in fishes that explicitly allows for the energy demand imposed by reproduction. We show that the von Bertalanffy (VB) equation provides a good description of somatic growth after maturity, but not before. We show that the parameters of the VB equation are simple functions of age at maturity and reproductive investment. We use this model to show how the energy demands for both growth and reproduction trade off to determine optimal life-history traits. Assuming that both age at maturity and reproductive investment adapt to variations in adult mortality to maximize lifetime offspring production, our model predicts that: (i) the optimal age of maturity is inversely related to adult mortality rate; (ii) the optimal reproductive effort is approximately equal to adult mortality rate. These predictions are consistent with observed variations in the life-history traits of a large sample of iteroparous freshwater fishes.

Life history characteristics of 54 Ontario lake trout (Salvelinus namaycush) populations vary with differences in lake area (range 25-450 000 ha) and total dissolved solids (TDS) (range 15-180 mg·L-1). Populations from large lakes exhibit greater maximum sizes, greater ages and sizes at first maturity, lower natural mortality rates, and lower sustainable yields. Populations from high-TDS lakes exhibit higher growth rates in early life, lower ages at first maturity, larger sizes at first maturity, and higher natural mortality rates. Angler catchability increases significantly at low population densities. With these relationships included in an age-structured population model, we found that the fishing mortality rate at maximum equilibrium yield ranges from 0.12·year-1 for a 100-ha, low-TDS lake to 0.37·year-1 for a 10 000-ha, high-TDS lake; the fishing effort level at maximum equilibrium yield ranges from 6.6 angler-h·ha-1· year-1 for a 100-ha, low-TDS lake to 4.0 angler-h·ha-1·year-1 for a 10 000-ha, high-TDS lake. Populations from small, low-TDS lakes are more sensitive to overexploitation than populations from large, high-TDS lakes. Easily measured, environmental correlates of life history characters may be common among fish species and are useful in developing exploitation guidelines for populations that are not well studied.

We used a coupled social-ecological model to study the landscape-scale patterns emerging from a mobile population of anglers exploiting a spatially structured walleye (Sander vitreus) fishery. We systematically examined how variations in angler behaviors (i.e., relative importance of walleye catch rate in guiding fishing site choices), harvesting efficiency (as implied by varying degrees of inverse density-dependent catchability of walleye), and angler population size affected the depletion of walleye stocks across 157 lakes located near Thunder Bay (Ontario, Canada). Walleye production biology was calibrated using lake-specific morphometric and edaphic features, and angler fishing site choices were modeled using an empirically grounded multi-attribute utility function. We found support for the hypothesis of sequential collapses of walleye stocks across the landscape in inverse proportionality of travel cost from the urban residence of anglers. This pattern was less pronounced when the regional angler population was low, density-dependent catchability was absent or low, and angler choices of lakes in the landscape were strongly determined by catch rather than non-catch-related attributes. Thus, our study revealed a systematic pattern of high catch importance reducing overfishing potential at low and aggravating overfishing potential at high angler population sizes. The analyses also suggested that density-dependent catchability might have more serious consequences for regional overfishing states than variations in angler behavior. We found little support for the hypotheses of systematic overexploitation of the most productive walleye stocks and homogenized catch-related qualities among lakes sharing similar access costs to anglers. Therefore, one should not expect anglers to systematically exploit the most productive fisheries or to equalize catch rates among lakes through their mobility and other behaviors. This study underscores that understanding landscape overfishing dynamics involves a careful appreciation of angler population size and how it interacts with the attributes that drive angler behaviors and depensatory mechanisms such as inverse density-dependent catchability. Only when all of these ingredients are considered and understood can one derive reasonably predictable patterns of overfishing in the landscape. These patterns range from self-regulating systems with low levels of regional fishing pressure to sequential collapse of walleye fisheries from the origin of angling effort.

Food web structure is paramount in regulating a variety of ecologic patterns and processes, although food web studies are limited by poor empirical descriptions of inherently complex systems. In this study, stable isotope ratios (δN and δC) were used to quantify trophic relationships and food chain length (measured as a continuous variable) in 14 Ontario and Quebec lakes. All lakes contained lake trout as the top predator, although lakes differed in the presumed number of trophic levels leading to this species. The presumed number of trophic levels was correlated with food chain length and explained 40% of the among-lake variation. Food chain length was most closely related to fish species richness ([Formula: see text]) and lake area ([Formula: see text]). However, the two largest study lakes had shorter food chains than lakes of intermediate size and species richness, producing hump-shaped relationships with food chain length. Lake productivity was not a powerful predictor of food chain length ([Formula: see text]), and we argue that productive space (productivity multiplied by area) is a more accurate measure of available energy. This study addresses the need for improved food web descriptions that incorporate information about energy flow and the relative importance of trophic pathways.