Forecasting organismal responses to environmental change using biophysical models

A core challenge of our time is to predict how organisms will respond to global environmental change. Yet most of our current predictive tools are correlative (statistical) methods that largely overlook the mechanisms underlying organism-environment interactions and thus have a limited capacity to extrapolate responses to unprecedented environmental scenarios. An emerging area of research is committed to developing mechanistic models to capture these interactions – a multidisciplinary endeavor integrating disparate fields such as thermodynamics, physiology, and evolutionary biology. A starting point towards achieving this integration has been to develop biophysical models describing energy and mass exchange between an organism and its (micro)environment to derive metrics of physiological performance and fitness. Biophysical models combine -through physical first principles - information about the environment and functional traits that govern organism-microenvironment interactions. I will walk through examples of applications including three main approaches: (1) Predicting the fundamental niche (i.e., deriving performance as a function of the environment); (2) Predicting optimal phenotypes (i.e., performance as a function of phenotypic traits); and (3) Predicting patterns of trait variation across environments (i.e., performance in response to both environment and phenotype). Biophysical models are contributing to the transformation of ecology into a predictive science; they nonetheless face methodological and conceptual barriers that need to be overcome with further theoretical and empirical development.