Energy-based step selection analysis: modelling the energetic drivers of animal movement and habitat use
Abstract
1. The energetic gains from foraging and costs of movement are expected to be key drivers of animal decision-making, as their balance is a large determinant of body condition and survival. This fundamental perspective is often missing from habitat selection studies, which mainly describe correlations between space use and environmental features, rather than the mechanisms behind these correlations. 2. To address this gap, we present a novel parameterisation of step selection functions (SSFs), that we term the energy selection function (ESF). In this model, the likelihood of an animal selecting a movement step depends directly on the corresponding energetic gains and costs, and we can therefore assess how moving animals choose habitat based on energetic considerations. 3. The ESF retains the mathematical convenience and practicality of other SSFs and can be quickly fitted using standard software. In this paper, we outline a workflow, from data-gathering to statistical analysis, and use a case study of polar bears ( Ursus maritimus ) to demonstrate application of the model. 4. We explain how defining gains and costs at the scale of the movement step allows us to include information about resource distribution, landscape resistance, and movement patterns. We further
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