Exploring movement decisions: can Bayesian movement-state models explain crop consumption behaviour in elephants (Loxodonta africana)?

1. Animal movements towards goals or targets are based upon either maximization of resources or risk avoidance, and the way animals move can reveal information about their motivation for movement. 2. We use Bayesian movement models and hourly GPS-fixes to distinguish animal movements into movement states and analyse the influence of environmental variables on being in and switching to a state. Specifically, we apply our models to understand elephant movement decisions surrounding agricultural fields and crop consumption. As it is unclear what the role of habitat features are on this complex issue, we analyse whether elephants target agricultural crops for consumption, or simply pass through them in search of water. 3. Our Hidden-Markov models divide elephant movements into two states: exploratory movements that are fast and directional, and encamped movements that are slow and meandering. For each elephant, we ran 16 models with each possible combination of habitat features (river, elep...