Estimation of Bioenergetics Parameters for Rainbow Trout (Oncorhynchus mykiss) Using Capture-Recapture Data with Comparison to Estimates from a Laboratory-Based Model
Brett T. van Poorten, Carl J. Walters*
Identifiers and Pagination:Year: 2010
First Page: 69
Last Page: 79
Publisher Id: TOFISHSJ-3-69
Article History:Received Date: 20/01/2009
Revision Received Date: 01/06/2009
Acceptance Date: 01/06/2009
Electronic publication date: 3/6/2010
Collection year: 2010
open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: (https://creativecommons.org/licenses/by/4.0/legalcode). This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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.