Accounting for body mass effects in the estimation of field metabolic rates from body acceleration

Life history, reproduction, and survival are fundamentally linked to energy expenditure and acquisition. Dynamic Body Acceleration (DBA), measured through animal-attached data-loggers or transmitters, has emerged as a powerful method for estimating field metabolic rates of free-ranging individuals. After using respirometry to calibrate oxygen consumption rate (ṀO2) with DBA in captive settings, predictive models can be applied to DBA data collected from free-ranging individuals. However, laboratory calibrations are generally performed on a narrow size range of animals, which may introduce biases when predictive models are applied to differently sized individuals in the field. Here, we tested the influence of scale effects on the ability of a single predictive model to predict ṀO2 over a range of body sizes. We performed respirometry experiments with individuals spanning one order of magnitude in body mass (1.74–17.15 kg) and used a two-step modelling process to assess the intra-specific scale dependence of the ṀO2-DBA relationship and incorporate such dependencies into the covariates of ṀO2 predictive models. The final predictive model showed scale dependence; the slope of the ṀO2-DBA relationship was strongly allometric (M1.55), whereas the intercept term scaled closer to isometry (M1.08). Using bootstrapping and simulations, we tested the performance of this covariate-corrected model against commonly used methods of accounting for mass effects on the ṀO2-DBA relationship and found lowest error and bias in the covariate−corrected approach. The strong scale dependence of the ṀO2-DBA relationship indicates that caution must be exercised when models developed using one size class are applied to individuals of different sizes.