Accounting for animal movement in estimation of resource selection functions: sampling and data analysis.

By J. Forester, Hae Kyung Im, Paul J. Rathouz. Ecology, 2009

369 citations recorded by the source corpus.

Subfields: Ecology, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/d7152c41151e196b0bb53deb6656affaa4e74096

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In Ecology

In Nature and Landscape Conservation

Citations in the corpus

Reactive responses of zebras to lion encounters shape their predator–prey space game at large scale (2016, methodology): “…starting location as observed steps, but differed in that length and turning angle were randomly drawn from the empirical distribution of step lengths and turning angles obtained by pooling steps data from all other individuals, as recommended by Fortin et al. (2005) and Forester et al. (2009).”
Fencing solves human‐wildlife conflict locally but shifts problems elsewhere: A case study using functional connectivity modelling of the African elephant (2018, methodology): “Besides habitat variables, we integrated step length as a predictor for excluding possible bias caused by a parametric distribution of step length (Forester et al., 2009).”
Integrated step selection analysis: bridging the gap between resource selection and animal movement (2015, background): “To conclude, our work complements several recent contributions advocating the use of movement covariates within step-selection analysis (Forester et al. 2009; Johnson et al. 2013; Warton & Aarts 2013; Duchesne et al. 2015).”
Animal movement tools (amt): R package for managing tracking data and conducting habitat selection analyses (2018, background): “…to habitat-related covariates, movement-related covariates (functions of distances between points, angular deviations) resulting in likelihood-based estimates of the shape and scale of the underlying analytical distributions (Avgar et al. , 2016; Duchesne et al. , 2015; Forester et al. , 2009).”
Anthropogenic food resources foster the coexistence of distinct life history strategies: year-round sedentary and migratory brown bears (2016, background): “Steps with higher SSF scores w(X) are more likely to be chosen by the animals (Fortin et al., 2005), and β = 0 indicates absence of selection (Forester et al., 2009).”
Correlation and studies of habitat selection: problem, red herring or opportunity? (2010, methodology): “This latter approach will result in biased estimators if the assumed movement model is misspecified, but one can guard against mis-specification by including distance as a predictor in the selection model, especially if the effect of distance is modelled using a flexible approach (e.g. regression sp”
Diel predator activity drives a dynamic landscape of fear (2017, positive): “We used a 1:3 empirical sampling design (Fortin et al. 2005, Forester et al. 2009) where, for each end location of a movement step, three available locations were sampled with replacement from each individual ’ s respective step-length and turning-angle distributions.”
Temperature-mediated habitat use and selection by a heat-sensitive northern ungulate (2012, methodology): “…affects movement of moose at short temporal scales (van Beest et al. 2011), we quantified temperature-mediated RSFs at the scale of an individual’s movement trajectory using a matched casecontrol design (also known as step-selection functions; SSF: Fortin et al. 2005a; Forester et al. 2009).”