A Mechanistic Approach for Modeling Temperature‐Dependent Consumer‐Resource Dynamics

TLDR

Understanding how communities respond to environmental change is essential for conservation, yet existing models are too simplistic to capture this response. The study aims to improve community dynamics models by incorporating temperature dependence. They incorporate the Boltzmann factor into a bioenergetic consumer‑resource framework. The model predicts that warming does not cause extinctions but can destabilize systems, reduces resource biomass, and alters consumer biomass depending on proximity to extinction, with consumer biomass generally more sensitive, aligning with observations and advancing global‑change testing.

Abstract

Paramount to our ability to manage and protect biological communities from impending changes in the environment is an understanding of how communities will respond. General mathematical models of community dynamics are often too simplistic to accurately describe this response, partly to retain mathematical tractability and partly for the lack of biologically pleasing functions representing the model/environment interface. We address these problems of tractability and plausibility in community/environment models by incorporating the Boltzmann factor (temperature dependence) in a bioenergetic consumer-resource framework. Our analysis leads to three predictions for the response of consumer-resource systems to increasing mean temperature (warming). First, mathematical extinctions do not occur with warming; however, stable systems may transition into an unstable (cycling) state. Second, there is a decrease in the biomass density of resources with warming. The biomass density of consumers may increase or decrease depending on their proximity to the feasibility (extinction) boundary. Third, consumer biomass density is more sensitive to warming than resource biomass density (with some exceptions). These predictions are in line with many current observations and experiments. The model presented and analyzed here provides an advancement in the testing framework for global change scenarios and hypotheses of latitudinal and elevational species distributions.