Centre for Sustainable Aquatic Ecosystems, Harry Butler Institute, Murdoch University, 90 South St., Murdoch, WA 6150, Australia.
College of Science, Health, Engineering and Education, Murdoch University, 90 South Street, Murdoch, WA 6150, Australia.
J Exp Biol. 2021 Apr 1;224(7). doi: 10.1242/jeb.233544. Epub 2021 Apr 15.
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 (ṀO2) 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 ṀO2-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 ṀO2-DBA relationship and incorporate such dependencies into the coefficients 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 evaluated the performance of this coefficient-corrected model against commonly used methods of accounting for mass effects on the ṀO2-DBA relationship and found the lowest error and bias in the coefficient-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.
动态体加速度（DBA）通过动物附着标签进行测量，已成为估计自由生活个体野外代谢率的有力方法。在控制条件下通过呼吸计对耗氧量（ṀO2）与 DBA 进行校准后，可以将预测模型应用于从自由生活个体收集的 DBA 数据。然而，实验室校准通常在相对较窄的动物尺寸范围内进行，如果将预测模型应用于野外不同尺寸的个体，可能会引入偏差。在这里，我们测试了ṀO2-DBA 关系的质量依赖性，以开发一种用于估计生物体大小不同时野外代谢率的实验框架。我们对个体进行了呼吸计实验，这些个体的体重跨度为一个数量级（1.74-17.15kg），并使用两阶段建模过程来评估ṀO2-DBA 关系的种内尺度依赖性，并将这种依赖性纳入到ṀO2 预测模型的系数中。最终的预测模型显示出尺度依赖性；ṀO2-DBA 关系的斜率呈强烈的异速生长（M1.55），而截距项更接近同形生长（M1.08）。通过自举和模拟，我们评估了这种系数校正模型与常用的考虑质量对ṀO2-DBA 关系影响的方法相比的性能，并发现系数校正方法的误差和偏差最小。ṀO2-DBA 关系的强烈尺度依赖性表明，在将使用一个尺寸类别开发的模型应用于不同尺寸的个体时，必须谨慎行事。
