Energy‐based step selection analysis: Modelling the energetic drivers of animal movement and habitat use

The energetic gains from foraging and costs of movement are expected to be key drivers of animaldecision-making, as their balance is a large determinant of body condition and survival. Thisfundamental perspective is often missing from habitat selection studies, which mainly describecorrelations between space use and environmental features, rather than the mechanisms behindthese correlations. To address this gap, we present a novel parameterisation of step selection functions (SSFs), thatwe term the energy selection function (ESF). In this model, the likelihood of an animal selectinga movement step depends directly on the corresponding energetic gains and costs, and we cantherefore assess how moving animals choose habitat based on energetic considerations. The ESF retains the mathematical convenience and practicality of other SSFs and can be quicklyfitted using standard software. In this paper, we outline a workflow, from data-gathering to statis-tical analysis, and use a case study of polar bears (Ursus maritimus) to demonstrate application ofthe model. We explain how defining gains and costs at the scale of the movement step allows us to includeinformation about resource distribution, landscape resistance, and movement patterns. We further demonstrate this process with a case study of polar bears, and show how the parameters can beinterpreted in terms of selection for energetic gains and against energetic costs. The ESF is a flexible framework that combines the energetic consequences of both movement andresource selection, thus incorporating a key mechanism into habitat selection analysis. Further,because it is based on familiar habitat selection models, the ESF is widely applicable to any studysystem where energetic gains and costs can be derived, and has immense potential for methodolog-ical extensions