An introduction to statistical models used to characterize species-habitat associations with animal movement data.
| Title: | An introduction to statistical models used to characterize species-habitat associations with animal movement data. |
|---|---|
| Authors: | Florko KRN; Institute for the Oceans and Fisheries, University of British Columbia, 2202 Main Mall, Vancouver, BC, V6T 1Z4, Canada. katieflorko@gmail.com.; Togunov RR; Department of Zoology, University of British Columbia, Vancouver, BC, Canada.; Department of Mathematical Sciences, Norwegian University of Science and Technology, Trondheim, Norway.; Centre for Biodiversity Dynamics, Norwegian University of Science and Technology, Trondheim, Norway.; Gryba R; Institute for the Oceans and Fisheries, University of British Columbia, 2202 Main Mall, Vancouver, BC, V6T 1Z4, Canada.; Department of Statistics, University of British Columbia, Vancouver, BC, Canada.; Department of Geography, University of British Columbia, Vancouver, BC, Canada.; Sidrow E; Department of Statistics, University of British Columbia, Vancouver, BC, Canada.; Ferguson SH; Fisheries and Oceans Canada, Freshwater Institute, Winnipeg, MB, Canada.; Department of Biological Sciences, University of Manitoba, Winnipeg, MB, Canada.; Yurkowski DJ; Fisheries and Oceans Canada, Freshwater Institute, Winnipeg, MB, Canada.; Department of Biological Sciences, University of Manitoba, Winnipeg, MB, Canada.; Auger-Méthé M; Institute for the Oceans and Fisheries, University of British Columbia, 2202 Main Mall, Vancouver, BC, V6T 1Z4, Canada.; Department of Statistics, University of British Columbia, Vancouver, BC, Canada. |
| Source: | Movement ecology [Mov Ecol] 2025 Apr 17; Vol. 13 (1), pp. 27. Date of Electronic Publication: 2025 Apr 17. |
| Publication Type: | Journal Article; Review |
| Language: | English |
| Journal Info: | Publisher: BioMed Central Country of Publication: England NLM ID: 101635009 Publication Model: Electronic Cited Medium: Print ISSN: 2051-3933 (Print) Linking ISSN: 20513933 NLM ISO Abbreviation: Mov Ecol Subsets: PubMed not MEDLINE |
| Imprint Name(s): | Original Publication: London : BioMed Central, 2013- |
| Abstract: | Understanding species-habitat associations is fundamental to ecological sciences and for species conservation. Consequently, various statistical approaches have been designed to infer species-habitat associations. Due to their conceptual and mathematical differences, these methods can yield contrasting results. In this paper, we describe and compare commonly used statistical models that relate animal movement data to environmental data. Specifically, we examined selection functions which include resource selection function (RSF) and step-selection function (SSF), as well as hidden Markov models (HMMs) and related methods such as state-space models. We demonstrate differences in assumptions while highlighting advantages and limitations of each method. Additionally, we provide guidance on selecting the most appropriate statistical method based on the scale of the data and intended inference. To illustrate the varying ecological insights derived from each statistical model, we apply them to the movement track of a single ringed seal (Pusa hispida) in a case study. Through our case study, we demonstrate that each model yields varying ecological insights. For example, while the selection coefficient values from RSFs appear to show a stronger positive relationship with prey diversity than those of the SSFs, when we accounted for the autocorrelation in the data none of these relationships with prey diversity were statistically significant. Furthermore, the HMM reveals variable associations with prey diversity across different behaviors, for example, a positive relationship between prey diversity and a slow-movement behaviour. Notably, the three models identified different "important" areas. This case study highlights the critical significance of selecting the appropriate model as an essential step in the process of identifying species-habitat relationships and specific areas of importance. Our comprehensive review provides the foundational information required for making informed decisions when choosing the most suitable statistical methods to address specific questions, such as identifying expansive corridors or protected zones, understanding movement patterns, or studying behaviours. In addition, this study informs researchers with the necessary tools to apply these methods effectively.; (© 2025. The Author(s).) |
| Competing Interests: | Declarations. Ethics approval and consent to participate: All applicable institutional and/or national guidelines for the care and use of animals were followed. Animal handling was approved by the Freshwater Institute Animal Care Committee (FWI-ACC-2012) and Fisheries and Oceans Canada's Licenses to Fish for Scientific Purposes (S-05/06–09/13–1006-NU). Consent for publication: Not applicable. Competing interests: The authors declare no competing interests. |
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| Contributed Indexing: | Keywords: Animal movement; Biologging; Habitat selection; Hidden Markov models; Integrated step-selection functions; Movement ecology; Poisson point process models; Resource selection functions; Ringed seal (Pusa hispida); Step-selection functions; Telemetry |
| Entry Date(s): | Date Created: 20250417 Latest Revision: 20250419 |
| Update Code: | 20260130 |
| PubMed Central ID: | PMC12004767 |
| DOI: | 10.1186/s40462-025-00549-2 |
| PMID: | 40247418 |
| Database: | MEDLINE |
Journal Article; Review