The pitfalls of ignoring behaviour when quantifying habitat selection

Authors

  • C. L. Roever,

    Corresponding author
    1. Conservation Ecology Research Unit, Department of Zoology and Entomology, University of Pretoria, Hatfield, South Africa
    • Correspondence: Carrie L. Roever. Conservation Ecology Research Unit, Department of Zoology and Entomology, University of Pretoria, Hatfield 0083, South Africa.

      E-mail: mail@carrieroever.com

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    • These authors contributed equally to this work.
  • H. L. Beyer,

    1. ARC Centre of Excellence for Environmental Decisions, Centre for Biodiversity & Conservation Science, University of Queensland, Brisbane, Qld, Australia
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    • These authors contributed equally to this work.
  • M. J. Chase,

    1. Conservation Ecology Research Unit, Department of Zoology and Entomology, University of Pretoria, Hatfield, South Africa
    2. Elephants Without Borders, Kasane, Botswana
    3. San Diego Zoo Institute for Conservation Research, San Diego Zoo Global, Escondido, CA, USA
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  • R. J. van Aarde

    1. Conservation Ecology Research Unit, Department of Zoology and Entomology, University of Pretoria, Hatfield, South Africa
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Abstract

Aim

Habitat selection is a behavioural mechanism by which animals attempt to maximize their inclusive fitness while balancing competing demands, such as finding food and rearing offspring while avoiding predation, in a heterogeneous and changing environment. Different habitat characteristics may be associated with each of these demands, implying that habitat selection varies depending on the behavioural motivations of the animal. Here, we investigate behaviour-specific habitat selection in African elephants and discuss its implications for distribution modelling and conservation.

Location

Northern Botswana, Africa, case study.

Methods

We use Bayesian state-space models to characterize location time series data of elephants into two behavioural states (encamped and exploratory). We then develop habitat selection models for each behavioural state and contrast them to models based on data pooled among behaviours.

Results

Spatial predictions of habitat use were often markedly different among the models. Behaviour-specific and pooled habitat selection models differed in model structure, the magnitude of model coefficients and the form of the selection curve (linear or quadratic). Selection was typically strongest in the behaviour-specific models, although this varied according to behavioural state and habitat covariate.

Main conclusions

Ignoring behavioural states often had important consequences for quantifying habitat selection. Quantifying selection irrespective of behaviour (among all behaviours) can obscure important species–habitat relationships, thereby risking weak or incorrect inferences. Behaviour-specific habitat selection provides greater insight into the process of habitat selection and can improve predictive habitat selection estimates. As some behaviours are more relevant to specific conservation objectives than others, focusing on behaviour-specific selection could improve how habitats are prioritized for conservation or management.

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