A simple energy budget equation is developed to yield a bioenergetics model designed to simulate fish growth. Parameters for the model are estimated from the literature for application to yellow perch (Perca flavescens) and walleye (Stizostedion vitreum vitreum). Simulations are presented that demonstrate model output as functions of body size, activity level, ration level, food quality, and environmental temperature. Sensitivity analyses identify the importance of food consumption, activity, and excretion as biological processes represented in the parameters. On the basis of temperature conditions in selected lakes and specified feeding levels, simulations are presented to quantify the importance of year-to-year variation of temperature in determining growth. In heterothermal systems, temperature selection by percids can have a significant effect on growth. For walleye on fixed rations, annual growth can vary from zero to twofold increments due entirely to differences in summer temperatures. Variations in food quality have lesser effects. Key words: Perca, Stizostedion, bioenergetics model, growth, sensitivity, simulations

An energetics model is implemented for lake trout, Salvelinus namaycush, and applied to the Lake Michigan population. It includes an egestion function allowing any proportional mix of fish and invertebrates in the diet, a growth model accounting for both ontogenetic and seasonal changes in energy-density of predator and prey, a model for typical in situ swimming speed, and reproductive energy losses due to gametes shed. Gross conversion efficiency of energy by lake trout over their life (21.8%) is about twice the efficiency of converting biomass to growth because they store large amounts of high-energy fats. Highest conversion efficiencies are obtained by relatively fast-growing individuals, and over half the annual energy assimilated by older age-classes may be shed as gametes. Sensitivity analysis indicates a general robustness of the model, especially for estimating consumption by fitting a known growth curve. Largest sensitivities were for the intercept and weight dependence coefficients of metabolism. Population biomass and associated predatory impact of a given cohort increase steadily for about 3.5 yr then decline steadily after fishing mortality becomes important in the fourth year in the lake. This slow response time precludes manipulation of lake trout stocking densities as a means to control short-term prey fluctuations. Predation by lake trout on alewife, Alosa pseudoharengus, has been increasing steadily since 1965 to about 8 400 t∙yr−1, and is projected to rise to almost 12 000 t∙yr−1 by 1990.