Pattern-informed energetics: Energy allocation modeling for predicting trait variation and population persistence

Cara A. Gallagher , Viktoriia Radchuk, Melanie Dammhahn, Florian Jeltsch

Energetics drive emergent ecosystem processes, shaping behavior and population dynamics in response to environmental conditions. While energy budget models can be used to effectively link resource dynamics to fitness outcomes, they often lack empirical grounding for energy allocation under resource constraints. Here, we introduce the Pattern-Informed Energetics (PIE) framework, which leverages diverse observations to infer parameters governing energy allocation. Using a rodent case study, we informed and tested PIE against 40 observed patterns, including population dynamics, morphometrics, energetics, and life-history traits, assessing its ability to replicate experimental results and predict responses to climate scenarios. Our findings demonstrate that PIE can predict how environmental change affects traits and population trajectories, offering a robust framework for improving biodiversity forecasting. By linking energy allocation to emergent patterns, PIE strengthens the integration of physiological insights into predictive models, improving our understanding of species' responses to environmental change while accounting for their evolved life histories.