Improvement of Bioenergetics Model Predictions for Fish Undergoing Compensatory Growth

Abstract

A previous evaluation of a bioenergetics model applied to juvenile hybrid sunfish (F1 hybrid of female green sunfish Lepomis cyanellus × male bluegill L. macrochirus) undergoing compensatory growth (CG) indicated that the model substantially overestimated growth and underestimated cumulative consumption. This result suggested that fish bioenergetics models might not adequately account for physiological shifts that occur during CG. However, we demonstrate that application of a recently developed procedure for correcting consumption‐ and growth‐rate‐dependent systematic errors common among bioenergetics models negates much of the predictive error that had been attributed to the physiological complexities of CG. Correction equations for estimating the model‐relative growth rate error (predicted less observed; g · g−1 · d−1) from the observed mean daily consumption rate (g · g−1 · d−1) and the consumption rate error (predicted less observed; g · g−1 · d−1) from the observed relative growth rate (g · g−1 · d−1) were derived by applying linear regression analysis to data from individual hybrid sunfish not undergoing CG. These independently generated correction equations significantly improved model predictions of growth and cumulative consumption for three groups of fish undergoing CG at one temperature near their growth optimum. The findings indicate that the high consumption and growth rates characteristic of fish undergoing CG merely amplify the consumption‐ and growth‐rate‐dependent errors inherent in bioenergetics models and that model predictions for fish undergoing CG can be significantly improved through application of the correction procedure.

Improvement of an Esocid Bioenergetics Model for Juvenile Fish

“…The corrective equation we developed significantly reduced model bias and improved the accuracy of consumption estimates. A similar approach was used to improve estimates of cumulative consumption for white crappie (Bajer et al 2004b) and juvenile hybrid sunfish (green sunfish Lepomis cyanellus 3 bluegill L. macrochirus) undergoing compensatory growth (Whitledge et al 2006).…”

“…In recent studies, consumption-dependent error has been shown to be widespread among bioenergetics models (Madenjian and O'Connor 1999;Bajer et al 2004a, b;Whitledge et al 2006). For age-0 tiger muskellunge, feeding rate and water temperature are known to strongly affect the accuracy of bioenergetics predictions (Chipps et al 2000b).…”

Using a bioenergetic model to assess growth reduction from catch‐and‐release fishing and hooking injury in rainbow trout, Oncorhynchus mykiss

“…Compensatory growth by trout was not included in the model. The ability of fish to exhibit an accelerated growth rate to compensate for food deprivation or shortage has been noted widely in captive fish from controlled studies (Abbott & Dill 1989; Whitledge, Hayward, Noltie & Wang 1998; Ali, Nicieza & Wootton 2003; Whitledge, Bajer & Hayward 2006), but information is lacking for wild fish inhabiting streams with limited and seasonal food resources. In addition to the duration of food deprivation influencing weight gain of rainbow trout, past nutritional history, energy content of the diet and whether fish are fed at or below satiation has also been found to influence weight gain and feeding intensity (Jobling & Koskela 1996; Boujard, Burel, Médale, Haylor & Moisan 2000; Ali et al.…”

A Bioenergetics Model for Zander: Construction, Validation, and Evaluation of Uncertainty Caused by Multiple Input Parameters

“…Boisclair and Leggett (1989) demonstrated that ACT varied greatly among yellow perch populations, and Post (1990) suggested the use of an ACT of 4 for juvenile yellow perch. In summary, many bioenergetics models have been able to estimate C or G with an ACT from 1 to 2 or by using functions based on swimming speed determined in the laboratory (Stewart et al 1983;Karjalainen et al 1997;Whitledge and Hayward 1997;Madenjian and O'Connor 1999;Madenjian et al 2000;Pääkkönen et al 2003;Whitledge et al 2003Whitledge et al , 2006Chipps and Wahl 2004) or in the field (Worishka and Mehner 1998;Madenjian et al 2000;Pääkkönen et al 2003;Stevens et al 2006). In contrast, Trudel and Rasmussen (2006) suggested that ACT varies widely between populations and that the use of a constant ACT for different lakes is not reliable.…”