Elaborations of the mass‐balance equation that partitions energy of consumed food into its various physiological fates have flourished in the past 15 years. These bioenergetics models have been converted to powerful simulation tools and used in fisheries science, most often for predicting consumption by predators or for projecting fish growth as a function of temperature and prey availability. New uses of bioenergetics models are proliferating and range from predictions of larval survival to analysis of ecosystem function. Companion technologies such as hydroacoustics and physiological telemetry promise to further broaden the spectrum of potential applications. However, the data demands and uncertain accuracy of multiparameter models may constrain their ability to address routine fish management questions. Field measures of consumption or growth failed to corroborate bioenergetics estimates consistently (differences of at least 50%) in four of six published tests. Poor agreement could be due to inaccuracies in field measures, bioenergetics estimates, or both. Errors in bioenergetics estimates will accrue when input values for internal parameters and external variables are deficient; problems can result from unknown activity costs, extrapolation of weight‐dependent power functions, unjustified borrowing of physiological values from other species, and use of nonrepresentative field data. Remediation of these deficiencies will require a major concerted research effort and extensive field corroboration. Simpler individual and production‐based models show promise for predicting long‐term consumption or growth but also require substantiation of input parameters and more corroboration. In the interim, I suggest that bioenergetics models will remain better suited for making relative comparisons than for making precise quantitative predictions.

Papers and panel discussions given during a 1992 symposium on bioenergetics models are summarized. Bioenergetics models have been applied to a variety of research and management questions relating to fish stocks, populations, food webs, and ecosystems. Applications include estimates of the intensity and dynamics of predator–prey interactions, nutrient cycling within aquatic food webs of varying trophic structure, and food requirements of single animals, whole populations, and communities of fishes. As tools in food web and ecosystem applications, bioenergetics models have been used to compare forage consumption by salmonid predators across the Laurentian Great Lakes for single populations and whole communities, and to estimate the growth potential of pelagic predators in Chesapeake Bay and Lake Ontario. Some critics say that bioenergetics models lack sufficient detail to produce reliable results in such field applications, whereas others say that the models are too complex to be useful tools for fishery managers. Nevertheless, bioenergetics models have achieved notable predictive successes. Improved estimates are needed for model parameters such as metabolic costs of activity, and more complete studies are needed of the bioenergetics of larval and juvenile fishes. Future research on bioenergetics should include laboratory and field measurements of key model parameters such as weight‐dependent maximum consumption, respiration and activity, and thermal habitats actually occupied by fish. Future applications of bioenergetics models to fish populations also depend on accurate estimates of population sizes and survival rates.

To explain the limited stocking success of fingerling striped bass Morone saxatilis in Smith Mountain Lake, Virginia, we examined the relationship between size‐selective winter survival and length‐dependent patterns in growth, food habits, prey fish availability, and lipid energy reserves during the first year of life in two successive years from 1994 to 1996. Length distributions of striped bass were unimodal at the time of stocking, and growth remained positive for all fish during both growing seasons. By the fall of both years, a bimodal length distribution had developed within the age‐0 cohort, which then consisted of small‐mode (<150 mm) and large‐mode (>180 mm) fish. The differential growth was attributed to size‐dependent differences in prey consumption and diet quality. Small‐mode striped bass maintained a mixed diet of invertebrates and small cyprinids, whereas fish in the larger mode were strictly piscivorous, consuming only age‐0 alewives Alosa pseudoharengus. The disparity in food habits, which was probably influenced by the limited availability of alewife prey to smaller striped bass, resulted in size‐dependent differences in physiological condition, as larger juveniles amassed twice the lipid index levels as smaller fish by winter. By spring of both years, the bimodal length distribution had become unimodal and comprised almost entirely large‐mode striped bass. In addition, large‐mode fish had retained approximately 80% of their fall lipid stores, whereas surviving small‐mode individuals had retained only 40% of fall lipids. These results suggest that depletion of lipid energy, possibly coupled with other size‐dependent stressors, may explain the greater winter mortality of small fish. Stocking fingerling striped bass in Smith Mountain Lake at a larger size and earlier in the growing season should result in a greater proportion of stocked fish successfully switching to age‐0 alewife prey, thereby improving first‐year growth, winter survival, and recruitment to age 1.

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Wild brook trout Savelinus fontinalis in the Hazel River, Shenandoah National Park, Virginia, were marked with individually labeled visible implant tags, fin‐clipped, and recaptured at intervals over the following year. Tags remained legible over the entire period. Overall tag retention was 65%. Tag retention rates were only about 50% for brook trout 130—160 mm in total length (TL) but rose to 100% for brook trout 200 mm TL or greater. The magnitude of decline in the recapture percentage for brook trout that retained tags is consistent with reported mortality rates for southern Appalachian brook trout populations. Total length and condition of tagged and untagged adult brook trout did not differ significantly in August, October, and May collections.