To successfully grow, reproduce, and survive, animals must balance energy intake from the environment with their energy expenditure. However, environmental changes, such as those associated with the development of renewable energies, can disrupt this delicate balance and ultimately impact the vital rates of animal populations. To minimize harm and reap the benefits of renewables, predictive methods can be used to anticipate the effects of development on animal populations and mitigate its impact. Agent-based energy budget models offer an approach to predicting animal foraging success and behavior under environmental change. These models allow for the representation of animal energetics and spatially-explicit movement behavior and enable context-dependent decision-making. Because neither the environment nor anthropogenic impacts are uniform in space and time, such modeling efforts must consider the spatiotemporal dynamics of the environment and how individual animals' experiences shape their fitness. In this study, we present an agent-based energy budget model developed for harbor porpoises in the inner Danish waters, which represents animal movements, energetics, population dynamics, and environmental variability in high detail. The developed framework was tested against empirical estimates of population structure and seasonal variations in energetics and found to accurately reproduce observed patterns. As part of a larger project aimed at mitigating the impacts of offshore windfarm development on porpoises, called DEPONS, the model was applied to evaluate the population consequences of disturbance from seismic surveys, often used to survey windfarm sites before their development, and assess the underlying drivers of porpoise vulnerability to disturbance. We found that the largest effects of seismic surveys occurred in late summer and fall, and were linked to reproduction costs, water temperature, and body fat, rather than the number of exposed animals. Our results stress the importance of considering temporal variation in individual energetics and their link to disturbance effects when predicting impacts on populations. As we strive towards a sustainable future and face the challenges posed by climate change, anticipatory methods are needed to offset emissions while safeguarding biodiversity. This framework offers a tool to anticipate and mitigate indirect effects of environmental change, including from renewable development, which can be applied to a range of animal species.
