Conceptual and methodological advances in habitat-selection modeling: guidelines for ecology and evolution

Joseph M. Northrup, Eric Vander Wal, Maegwin Bonar, John Fieberg, Michel P. Laforge, Martin Leclerc, Christina M. Prokopenko, Brian D. Gerber

Research output: Contribution to journalArticlepeer-review

52 Scopus citations


Habitat selection is a fundamental animal behavior that shapes a wide range of ecological processes, including animal movement, nutrient transfer, trophic dynamics and population distribution. Although habitat selection has been a focus of ecological studies for decades, technological, conceptual and methodological advances over the last 20 yr have led to a surge in studies addressing this process. Despite the substantial literature focused on quantifying the habitat-selection patterns of animals, there is a marked lack of guidance on best analytical practices. The conceptual foundations of the most commonly applied modeling frameworks can be confusing even to those well versed in their application. Furthermore, there has yet to be a synthesis of the advances made over the last 20 yr. Therefore, there is a need for both synthesis of the current state of knowledge on habitat selection, and guidance for those seeking to study this process. Here, we provide an approachable overview and synthesis of the literature on habitat-selection analyses (HSAs) conducted using selection functions, which are by far the most applied modeling framework for understanding the habitat-selection process. This review is purposefully non-technical and focused on understanding without heavy mathematical and statistical notation, which can confuse many practitioners. We offer an overview and history of HSAs, describing the tortuous conceptual path to our current understanding. Through this overview, we also aim to address the areas of greatest confusion in the literature. We synthesize the literature outlining the most exciting conceptual advances in the field of habitat-selection modeling, discussing the substantial ecological and evolutionary inference that can be made using contemporary techniques. We aim for this paper to provide clarity for those navigating the complex literature on HSAs while acting as a reference and best practices guide for practitioners.

Original languageEnglish (US)
Article numbere02470
JournalEcological Applications
Issue number1
StatePublished - Jan 2022

Bibliographical note

Funding Information:
The authors wish to thank the many colleagues and mentors that have helped to shape the ideas in this paper through countless discussion on this topic including G. Aarts, M. Boyce, M. Hooten, J. Matthiopoulos, P. McLoughlin, E. Merrill, and G. Wittemyer. M. Leclerc was a Banting postdoctoral fellow 2020–2022 (201909BPF‐431281‐74641) and acknowledges the financial support from FRQNT 2018‐2020 (#255026) and Environment and Climate Change Canada. B. Gerber's contribution to this work was supported by the USDA National Institute of Food and Agriculture, Hatch Formula project 1017848. J. Fieberg received partial support from the Minnesota Agricultural Experimental Station. This work was supported by the Natural Sciences and Engineering Research Council of Canada Discovery Grants to J.M. Northrup and E Vander Wal. J.M. Northrup and E. Vander Wal conceived the idea of the paper, all authors contributed directly to the writing of the paper, J.M. Northrup compiled the sections and all authors contributed to revisions.

Publisher Copyright:
© 2021 The Authors. Ecological Applications published by Wiley Periodicals LLC on behalf of The Ecological Society of America

PubMed: MeSH publication types

  • Journal Article
  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.
  • Review


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