Abstract
Dynamic body acceleration (DBA), measured through animal-attached tags, has emerged as a powerful method for estimating field metabolic rates of free-ranging individuals. Following respirometry to calibrate Oxygen consumption rate ((M) over dot(O2)) with DBA under controlled conditions, predictive models can be applied to DBA data collected from free-ranging individuals. However, laboratory calibrations are generally performed on a relatively narrow size range of animals, which may introduce biases if predictive models are applied to differently sized individuals in the field. Here, we tested the mass dependence of the (M) over dot(O2)-DBA relationship to develop an experimental framework for the estimation of field metabolic rates when organisms differ in size. We performed respirometry experiments with individuals spanning one order of magnitude in body mass (1.74-17.15 kg) and used a two-stage modelling process to assess the intraspecific scale dependence of the (M) over dot(O2)-DBA relationship and incorporate such dependencies into the coefficients of (M) over dotO(2) predictive models. The final predictive model showed scale dependence; the slope of the (M) over dot(O2)-DBA relationship was strongly allometric (M-1.55), whereas the intercept term scaled closer to isometry (M-1.08). Using bootstrapping and simulations, we evaluated the performance of this coefficient-corrected model against commonly used methods of accounting for mass effects on the (M) over dot(O2)-DBA relationship and found the lowest error and bias in the coefficient-corrected approach. The strong scale dependence of the (M) over dot(O2)-DBA relationship indicates that caution must be exercised when models developed using one size class are applied to individuals of different sizes.