Habitat-selection analyses allow researchers to link animals to their environment via habitat-selection or step-selection functions, and are commonly used to address questions related to wildlife management and conservation efforts. Habitat-selection analyses that incorporate movement characteristics, referred to as integrated step-selection analyses, are particularly appealing because they allow modelling of both movement and habitat-selection processes. Despite their popularity, many users struggle with interpreting parameters in habitat-selection and step-selection functions. Integrated step-selection analyses also require several additional steps to translate model parameters into a full-fledged movement model, and the mathematics supporting this approach can be challenging for many to understand. Using simple examples, we demonstrate how weighted distribution theory and the inhomogeneous Poisson point process can facilitate parameter interpretation in habitat-selection analyses. Furthermore, we provide a ‘how to’ guide illustrating the steps required to implement integrated step-selection analyses using the amt package By providing clear examples with open-source code, we hope to make habitat-selection analyses more understandable and accessible to end users.
Bibliographical noteFunding Information:
We thank J.R. Potts, three anonymous reviewers and the Associate Editor for helpful comments that improved the manuscript. J.F. received partial salary support from the Minnesota Agricultural Experimental Station. T.A. received partial salary support from the Utah Agricultural Experimental Station.
© 2021 The Authors. Journal of Animal Ecology published by John Wiley & Sons Ltd on behalf of British Ecological Society
- habitat-selection function
- inhomogeneous Poisson point process
- integrated step-selection analysis
- intensity function
- relative selection strength
- resource-selection function
- step-selection function