ROOM: RSCC, F2
We will illustrate strategies for fitting habitat selection models (resource-selection and step-selection functions, RSFs and SSFs, respectively) to data from multiple tagged individuals, highlighting three recent developments: 1) Integrated Step-Selection Function (iSSFs), a simple framework for simultaneous modeling of animal movement and habitat selection processes using conditional logistic regression. These models allow one to relax the assumption that movement characteristics (i.e. step lengths and turn angles) are independent of habitat features. 2) The amt (animal movement tools) package in R, which provides tools for exploratory analysis of animal location data, functions for data development prior to fitting RSFs or SSFs, and a simple tidyverse workflow for seamless fitting of RSF and SSF models to data from individual animals. 3) Methods for efficient estimation of mixed effect RSFs and SSFs using INLA and glmmTMB.
Organizers: John Fieberg, Tal Avgar, Johannes Signer, Stefanie Muff
Supported by: Biometrics Working Group and Spatial Ecology and Telemetry Working Group