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A 'How to' guide for interpreting parameters in habitat-selection analyses.

John Fieberg1, Johannes Signer2, Brian Smith3

  • 1Department of Fisheries, Wildlife, and Conservation Biology, University of Minnesota, St. Paul, MN, USA.

The Journal of Animal Ecology
|February 14, 2021
PubMed
Summary

This study simplifies habitat-selection analysis for wildlife management. It clarifies complex models and provides open-source tools to make animal movement and habitat use research more accessible.

Keywords:
habitat-selection functioninhomogeneous Poisson point processintegrated step-selection analysisintensity functionrelative selection strengthresource-selection functionstep-selection functiontelemetry

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Area of Science:

  • Ecology
  • Wildlife Biology
  • Movement Ecology

Background:

  • Habitat-selection analyses link animal behavior to environmental factors, crucial for wildlife management and conservation.
  • Integrated step-selection analyses model both animal movement and habitat selection but present interpretation challenges.
  • Existing methods for integrated step-selection analyses can be mathematically complex and difficult for users to implement.

Purpose of the Study:

  • To simplify parameter interpretation in habitat-selection and step-selection functions using accessible theoretical frameworks.
  • To provide a practical guide for implementing integrated step-selection analyses with open-source code.
  • To enhance the understandability and accessibility of advanced habitat-selection analyses for researchers and wildlife managers.

Main Methods:

  • Utilizing weighted distribution theory and the inhomogeneous Poisson point process to clarify model parameters.
  • Demonstrating methods with simple, illustrative examples.
  • Developing a 'how to' guide for integrated step-selection analyses using the 'amt' R package.

Main Results:

  • The study successfully demonstrates how weighted distribution theory and Poisson point processes can aid in interpreting habitat-selection model parameters.
  • A clear, step-by-step guide for implementing integrated step-selection analyses using the 'amt' package is provided.
  • Open-source code examples are made available to facilitate practical application.

Conclusions:

  • Habitat-selection analyses, particularly integrated step-selection analyses, can be made more accessible and understandable to a wider audience.
  • The provided methods and tools empower researchers to more effectively model animal movement and habitat selection.
  • Increased accessibility of these analytical techniques will benefit wildlife management and conservation efforts.