Estimating utilization distributions from fitted step-selection functions

Johannes Signer, John Fieberg, Tal Avgar

Research output: Contribution to journalArticlepeer-review

75 Scopus citations


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 two different approaches for generating maps from the estimated regression coefficients. First, we considered a na€ive approach that used the coefficients as if they were obtained by fitting an unconditional model. Second, we explored a simulation-based approach, where maps were generated using stochastic simulations of the parameterized step-selection process. We found that the simulation-based approach always outperformed the na€ive mapping approach and that the latter overestimated home-range size and underestimated local space-use variability. Differences between the approaches were greatest for complex landscapes and high sampling rates, suggesting that the simulation-based approach, despite its added complexity, is likely to offer significant advantages when applying SSFs to real data.

Original languageEnglish (US)
Article numbere01771
Issue number4
StatePublished - Apr 2017

Bibliographical note

Publisher Copyright:
© 2017 Signer et al.


  • Habitat selection
  • Home range
  • Integrated step-selection analysis
  • Integrated step-selection function
  • Mechanistic home range
  • Movement ecology
  • Resource-selection function
  • Step-selection analysis
  • Step-selection function
  • Utilization distribution


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