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Estimating Utilization Distributions From Fitted Step-Selectionfunctions, Johannes Signer, John Fieberg, Tal Avgar
Estimating Utilization Distributions From Fitted Step-Selectionfunctions, Johannes Signer, John Fieberg, Tal Avgar
Wildland Resources Faculty Publications
Habitat-selection analyses are often used to link environmental covariates, measured within some spatial domain of assumed availability, to animal location data that are assumed to be independent. Step-selection functions (SSFs) relax this independence assumption, by using a conditional model that explicitly acknowledges the spatiotemporal dynamics of the availability domain and hence the temporal dependence among successive locations. However, it is not clear how to produce an SSF-based map of the expected utilization distribution. Here, we used SSFs to analyze virtual animal movement data generated at a fine spatiotemporal scale and then rarefied to emulate realistic telemetry data. We then compared …
Integrated Step Selection Analysis: Bridgingthe Gap Between Resource Selection And Animal Movement, Tal Avgar, Jonathan R. Potts, Mark A. Lewis, Mark S. Boyce
Integrated Step Selection Analysis: Bridgingthe Gap Between Resource Selection And Animal Movement, Tal Avgar, Jonathan R. Potts, Mark A. Lewis, Mark S. Boyce
Wildland Resources Faculty Publications
A resource selection function is a model of the likelihood that an available spatial unit will be used by an animal, given its resource value. But how do we appropriately define availability? Step selection analysis deals with this problem at the scale of the observed positional data, by matching each ‘used step’ (connecting two consecutive observed positions of the animal) with a set of ‘available steps’ randomly sampled from a distribution of observed steps or their characteristics. Here we present a simple extension to this approach, termed integrated step selection analysis (iSSA), which relaxes the implicit assumption that observed movement …