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Solving the Sample Size Problem for Resource Selection Analysis
  • +22
  • Garrett Street,
  • Jonathan Potts,
  • Luca Börger,
  • James Beasley,
  • Stevew Demarais,
  • John Fryxell,
  • Philip McLoughlin,
  • Kevin Monteith,
  • Christina Prokopenko,
  • Milton Ribeiro,
  • Arthur Rodgers,
  • Bronson Strickland,
  • Floris van Beest,
  • David Bernasconi,
  • Larissa Beumer,
  • Guha Dharmarajan,
  • Samantha Dwinnel,
  • David Keiter,
  • Alexine Keuroghlian,
  • Levi Newediuk,
  • Júlia Oshima,
  • Olin Rhodes,
  • Peter Schlichting,
  • Neils Schmidt,
  • Eric Vander Wal
Garrett Street
Mississippi State University

Corresponding Author:gms246@msstate.edu

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Jonathan Potts
University of Sheffield
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Luca Börger
Swansea University
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James Beasley
University of Georgia
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Stevew Demarais
Mississippi State University
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John Fryxell
University of Guelph
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Philip McLoughlin
University of Saskatchewan
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Kevin Monteith
University of Wyoming
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Christina Prokopenko
Memorial University of Newfoundland
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Milton Ribeiro
Universidade Estadual Paulista
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Arthur Rodgers
Ontario Ministry of Natural Resources and Forestry
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Bronson Strickland
Mississippi State University
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Floris van Beest
Aarhus Universitet
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David Bernasconi
University of Georgia
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Larissa Beumer
Aarhus Universitet
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Guha Dharmarajan
University of Georgia
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Samantha Dwinnel
University of Wyoming
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David Keiter
University of Nebraska-Lincoln
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Alexine Keuroghlian
IUCN
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Levi Newediuk
Memorial University of Newfoundland
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Júlia Oshima
Universidade Estadual Paulista Julio de Mesquita Filho Departamento de Ecologia Campus de Rio Claro
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Olin Rhodes
University of Georgia
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Peter Schlichting
Arizona State University
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Neils Schmidt
Aarhus Universitet
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Eric Vander Wal
Memorial University of Newfoundland
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Abstract

Resource selection analysis (RSA) is a cornerstone approach for understanding animal distributions, yet there exists no rigorous quantification of sample sizes required to obtain reliable results. We provide closed-form mathematical expressions for both the number of animals and relocations per animal required for parameterising RSA to a given degree of precision. Required sample sizes depend on just two quantities: habitat selection strength and an index of landscape complexity, which we define rigorously. We validate our solutions using 5,678,623 GPS locations from 511 animals from 10 species (omnivores, carnivores, and herbivores from boreal, temperate, and tropical forests, montane woodlands, swamps, and tundra). Our results contradict conventional wisdom by showing that environmental effects on distributions can often be estimated with fewer animals and relocations than assumed, with far-reaching implications for ecologists, conservationists, and natural resource managers.