Three‐Dimensional Correlated Random Walks for Animal Movement and Habitat Selection

ABSTRACT

Animal movement and habitat selection underpin important ecological phenomena, from individual behaviour to population‐level distributions. Despite navigating three‐dimensional space, animals' movement is typically measured and analysed on a two‐dimensional plane, which limits our understanding of species that swim or fly. Therefore, we propose a step selection function (SSF) capable of quantifying animal movement and habitat selection in three dimensions. We formulate a very general family of three‐dimensional correlated random walks, aimed at capturing unique features of three‐dimensional data. Using Antarctic petrel data, we illustrate how these SSFs can be used to assess selection for vertically‐stratified habitat, account for barriers (e.g., the ground or ocean surface), and model attraction to any number of directional targets. Our modelling framework provides a solid foundation for three‐dimensional analyses, which will be crucial to answer ecological questions that would otherwise be ignored in two dimensions.