Table 6 List of abbreviations used in this study

‘spatial logistic regression model’; pure spatial approach for analysing tracking data

‘spatio-temporal point process model’; spatio-temporal approach for analysing tracking data, developed from an Eulerian point of view

‘step selection model’ (also called ‘step selection function /SSF’ or ‘step selection analysis / SSA’); spatio-temporal approach for analysing tracking data, developed from a Lagrangian point of view

‘integrated step selection model’; integrating the SSM approach with a mechanistic movement model

‘minimal convex polygon’; minimal convex polygon containing all tracking points, for estimation of the minimum home rage

‘generalized linear model’; extension of linear regression models for non-normally distributed data

‘generalized additive model’; extension of GLM to describe non-linear (‘additive’) dependencies

‘generalized estimation equation’; estimation method for parameters of a GLM with possible unknown correlation between outcomes

‘generalized linear mixed model’; extension of GLM to describe outcome correlation with random effects

‘least absolute shrinkage and selection operator’; technique for model selection that can especially cope with a high number of possible predictors