Predicting species distributions for conservation decisions

Authors

  • Antoine Guisan,

    Corresponding author
    1. Department of Ecology and Evolution, University of Lausanne, Lausanne, Switzerland
    2. Institute of Earth Surface Dynamics, University of Lausanne, Lausanne, Switzerland
    3. ARC Centre of Excellence for Environmental Decisions (CEED), School of Biological Sciences, The University of Queensland, St Lucia, Brisbane, Qld, Australia
    4. CSIRO Ecosystem Sciences, Ecosciences Precinct, Dutton Park, Brisbane, Qld, Australia
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  • Reid Tingley,

    1. ARC Centre of Excellence for Environmental Decisions (CEED), School of Botany, The University of Melbourne, Parkville, Vic, Australia
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  • John B. Baumgartner,

    1. ARC Centre of Excellence for Environmental Decisions (CEED), School of Botany, The University of Melbourne, Parkville, Vic, Australia
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  • Ilona Naujokaitis-Lewis,

    1. Ecology & Evolutionary Biology, University of Toronto, Toronto, Canada
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  • Patricia R. Sutcliffe,

    1. ARC Centre of Excellence for Environmental Decisions (CEED), School of Biological Sciences, The University of Queensland, St Lucia, Brisbane, Qld, Australia
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  • Ayesha I. T. Tulloch,

    1. ARC Centre of Excellence for Environmental Decisions (CEED), School of Biological Sciences, The University of Queensland, St Lucia, Brisbane, Qld, Australia
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  • Tracey J. Regan,

    1. ARC Centre of Excellence for Environmental Decisions (CEED), School of Botany, The University of Melbourne, Parkville, Vic, Australia
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  • Lluis Brotons,

    1. Centre de Recerca Ecològica i Aplicacions Forestals (CREAF), Bellaterra, Spain
    2. Centre Tecnològic Forestal de Catalunya (CTFC - CEMFOR), Solsona, Spain
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  • Eve McDonald-Madden,

    1. ARC Centre of Excellence for Environmental Decisions (CEED), School of Biological Sciences, The University of Queensland, St Lucia, Brisbane, Qld, Australia
    2. CSIRO Ecosystem Sciences, Ecosciences Precinct, Dutton Park, Brisbane, Qld, Australia
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  • Chrystal Mantyka-Pringle,

    1. CSIRO Ecosystem Sciences, Ecosciences Precinct, Dutton Park, Brisbane, Qld, Australia
    2. ARC Centre of Excellence for Environmental Decisions (CEED), School of Geography, Planning and Environmental Management, The University of Queensland, St Lucia, Brisbane, Qld, Australia
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  • Tara G. Martin,

    1. ARC Centre of Excellence for Environmental Decisions (CEED), School of Biological Sciences, The University of Queensland, St Lucia, Brisbane, Qld, Australia
    2. CSIRO Ecosystem Sciences, Ecosciences Precinct, Dutton Park, Brisbane, Qld, Australia
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  • Jonathan R. Rhodes,

    1. ARC Centre of Excellence for Environmental Decisions (CEED), School of Geography, Planning and Environmental Management, The University of Queensland, St Lucia, Brisbane, Qld, Australia
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  • Ramona Maggini,

    1. ARC Centre of Excellence for Environmental Decisions (CEED), School of Biological Sciences, The University of Queensland, St Lucia, Brisbane, Qld, Australia
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  • Samantha A. Setterfield,

    1. Research Institute for Environment and Livelihoods, Charles Darwin University, Darwin, NT, Australia
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  • Jane Elith,

    1. School of Botany, The University of Melbourne, Parkville, Vic, Australia
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  • Mark W. Schwartz,

    1. John Muir Institute of the Environment, University of California, Davis, USA
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  • Brendan A. Wintle,

    1. ARC Centre of Excellence for Environmental Decisions (CEED), School of Botany, The University of Melbourne, Parkville, Vic, Australia
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  • Olivier Broennimann,

    1. Department of Ecology and Evolution, University of Lausanne, Lausanne, Switzerland
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  • Mike Austin,

    1. CSIRO Ecosystem Sciences, Canberra, Australia
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  • Simon Ferrier,

    1. CSIRO Ecosystem Sciences, Canberra, Australia
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  • Michael R. Kearney,

    1. Department of Zoology, The University of Melbourne, Parkville, Vic, Australia
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  • Hugh P. Possingham,

    1. ARC Centre of Excellence for Environmental Decisions (CEED), School of Biological Sciences, The University of Queensland, St Lucia, Brisbane, Qld, Australia
    2. Imperial College London, Department of Life Sciences, Silwood Park, Berkshire, England, UK
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  • Yvonne M. Buckley

    1. ARC Centre of Excellence for Environmental Decisions (CEED), School of Biological Sciences, The University of Queensland, St Lucia, Brisbane, Qld, Australia
    2. Zoology Department, School of Natural Sciences, Trinity College, Dublin 2, Ireland
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Abstract

Species distribution models (SDMs) are increasingly proposed to support conservation decision making. However, evidence of SDMs supporting solutions for on-ground conservation problems is still scarce in the scientific literature. Here, we show that successful examples exist but are still largely hidden in the grey literature, and thus less accessible for analysis and learning. Furthermore, the decision framework within which SDMs are used is rarely made explicit. Using case studies from biological invasions, identification of critical habitats, reserve selection and translocation of endangered species, we propose that SDMs may be tailored to suit a range of decision-making contexts when used within a structured and transparent decision-making process. To construct appropriate SDMs to more effectively guide conservation actions, modellers need to better understand the decision process, and decision makers need to provide feedback to modellers regarding the actual use of SDMs to support conservation decisions. This could be facilitated by individuals or institutions playing the role of ‘translators’ between modellers and decision makers. We encourage species distribution modellers to get involved in real decision-making processes that will benefit from their technical input; this strategy has the potential to better bridge theory and practice, and contribute to improve both scientific knowledge and conservation outcomes.

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