Physiological determinants of biogeography: the importance of metabolic depression to heat tolerance.

A quantitative understanding of physiological thermal responses is vital for forecasting species distributional shifts in response to climate change. Many studies have focused on metabolic rate as a global metric for analyzing the sublethal effects of changing environments on physiology. Thermal Performance Curves (TPCs) have been suggested as a viable analytical framework, but standard TPCs may not fully capture physiological responses, due in part to failure to consider the process of metabolic depression. We derived a model based on the non-linear regression of biological temperature-dependent rate processes and built a heart rate dataset for 26 species of intertidal molluscs distributed from 33°S to ~40°N. We then calculated physiological thermal performance limits with continuous heating using T1/2H , the temperature at which heart rate is decreased to 50% of the maximal rate, as a more realistic measure of upper thermal limits. Results indicate that heat-induced metabolic depression of cardiac performance is a common adaptive response that allows tolerance of harsh environments. Furthermore, our model accounted for the high inter-individual variability in the shape of cardiac TPCs. We then used these TPCs to calculate physiological thermal safety margins (pTSM), the difference between the maximal operative temperature (95th percentile of field temperatures) and T1/2H of each individual. Using pTSMs, we developed a physiological species distribution model (pSDM) to forecast future geographic distributions. pSDM results indicate that climate-induced species range shifts are potentially less severe than predicted by a simple correlative SDM. Species with metabolic depression below the optimum temperature will be more thermal resistant at their warm trailing edges. High intraspecific variability further suggests that models based on species-level vulnerability to environmental change may be problematic. This multi-scale, mechanistic understanding that incorporates metabolic depression and inter-individual variability in thermal response enables better predictions about the relationship between thermal stress and species distributions.