Simultaneous identification and correction of systematic error in bioenergetics models: demonstration with a white crappie (Pomoxis annularis) model

Abstract

Recent evidence indicates that important systematic error exists in many fish bioenergetics models (BEMs). An approach for identifying and correcting this error is demonstrated with a white crappie (Pomoxis annularis) BEM. Model-predicted trajectories of growth and cumulative consumption for 39 individual white crappie obtained from six 60-day laboratory experiments diverged from observed values by up to 42.5% and 227%, respectively, indicating systematic error in the BEM. To evaluate correlates of the systematic error, model prediction errors were regressed against three major input/output variables of BEMs that were covered by the laboratory experiments: fish body weight (80–341 g), temperature (23–30 °C), and consumption level (0.5%–6.2% daily). Consumption level explained >80% of the prediction error for growth and consumption. Two multiple regression equations containing body weight, temperature, and consumption variables were developed to estimate growth prediction error (R2 = 0.96) and consumption prediction error (R2 = 0.86), and incorporated into the white crappie BEM to correct its predictions. Cross-validation indicated that growth and consumption prediction error was reduced 2- to 4-fold by correction. Given recent evidence of widespread systematic error and increasing application rates of BEMs, the efficient error-identification and -correction approach described appears broadly applicable and timely.