Estimation of Bioenergetics Parameters for Rainbow Trout (Oncorhynchus mykiss) Using Capture-Recapture Data with Comparison to Estimates from a Laboratory-Based Model

Abstract

Bioenergetics models provide estimates of growth and consumption in fish and other animals. These estimates can then be used to infer metabolic and population-level consequences of various natural or human-induced environmental perturbations to fish populations. Most existing models utilize parameter values and functions derived from laboratory experiments on similar, closely related populations or species. However, the use of parameters from other species has long been criticized and recent work suggests that certain metabolic rates can vary substantially between closely related species and geographically separated populations of the same species. We evaluate a new model framework (termed the general bioenergetics model) which estimates bioenergetics parameters from length-increment and length-at-age data taken from the same population being modelled. Estimates of growth and consumption from this general model are compared with the commonly used "Wisconsin" bioenergetics model in terms of model fit and predictions resulting from simulated climate warming. Growth estimates using the general bioenergetics model were slightly higher than that of the Wisconsin model but consumption estimates were similar. Both models made similar predictions about effect of climate warming, although there was a consistent difference between model estimates of growth. The findings of this study add weight to the notion that metabolic information through bioenergetics models can be estimated from the population, although further validation should be conducted.

Estimating Differences in Growth and Metabolism in Two Spatially Segregated Groups of Columbia River White Sturgeon Using a Field-Based Bioenergetics Model

“…n and Q m ). Several authors have cautioned against 'borrowing' parameters from other population or species [33][34][35] because of the possibility of model sensitivity to some parameters [36,37] and because of some parameters showing variation across species or populations [38]. However, sensitivity analysis on analogues of n and Q m in other bioenergetics models have shown model outputs are quite insensitive to these parameters [36,39].…”

How can bioenergetics help us predict changes in fish growth patterns?

“…This is primarily because temperature does not simply affect basal metabolic rate of the population being considered, but includes effects on burst and sustained swimming speeds due to the influence of temperature various enzymes involved in active metabolic processes (Fontoura and Agostinho, 1996). Moreover, temperature also strongly drives patterns of prey availability in all aspects of the ecosystem implying that temperature affects both metabolism and consumption (Kitchell et al, 1977;DeStasio et al, 1996;Ficke et al, 2007;van Poorten and Walters, 2010). Assuming consumption and metabolism scale similarly with temperature implies that temperature only affects K in the VBGF, as assumed by most authors (e.g.…”

Comparison of Bioenergetics Parameters from Two Spring-Fed Riverine Largemouth Bass Populations

“…For this scenario, we fit the general bioenergetics model in a hierarchical fashion, using data from the first year of the study (Trial 1) and then using data from both years (Trial 2), in order to assess model fit with increasing data. In both trials, samples sizes for growth increment and length-at-age data were relatively low compared to other case studies used to fit the general bioenergetics model [30][31][32]. For the second scenario, we attempted to estimate all bioenergetics parameters: H, d, m, n, Q c and Q m .…”

“…Second, the incorporation of growth increment data should allow for more precisely defined seasonality in consumption and growth. Third, the Bayesian parameter estimation allows uncertainty in parameter estimates to be incorporated into management recommendations [30]. Finally, the use of data commonly collected in many population assessments should allow for seamless integration into a framework for testing hypotheses that require estimates of fish consumption rates.…”