• Open Access

Quantitative approaches in climate change ecology

Authors

  • Christopher J. Brown,

    Corresponding author
    1. Climate Adaptation Flagship, CSIRO Marine and Atmospheric Research, Ecosciences Precinct, Brisbane, QLD, Australia
    • School of Biological Sciences, The University of Queensland, St Lucia, QLD, Australia
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  • David S. Schoeman,

    1. Environmental Science Research Institute, School of Environmental Sciences, University of Ulster, Coleraine, UK
    2. Department of Zoology, Nelson Mandela Metropolitan University, Port Elizabeth, South Africa
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  • William J. Sydeman,

    1. Farallon Institute for Advanced Ecosystem Research, Petaluma, CA, USA
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  • Keith Brander,

    1. National Institute of Aquatic Resources, Technical University of Denmark, Charlottenlund, Denmark
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  • Lauren B. Buckley,

    1. Department of Biology, University of North Carolina, Chapel Hill, NC, USA
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  • Michael Burrows,

    1. Scottish Association for Marine Science, Scottish Marine Institute, Argyll, PA, UK
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  • Carlos M. Duarte,

    1. Department of Global Change Research, IMEDEA (UIB-CSIC), Instituto Mediterráneo de Estudios Avanzados, Esporles, Mallorca, Spain
    2. The UWA Ocean Institute, University of Western Australia, Crawley, WA, Australia
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  • Pippa J. Moore,

    1. Centre for Marine Ecosystems Research, Edith Cowan University, Perth, WA, Australia
    2. Institute of Biological, Environmental and Rural Sciences, Aberystwyth University, Aberystwyth, UK
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  • John M. Pandolfi,

    1. Australian Research Council Centre of Excellence for Coral Reef Studies, School of Biological Sciences, The University of Queensland, St. Lucia, QLD, Australia
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  • Elvira Poloczanska,

    1. Climate Adaptation Flagship, CSIRO Marine and Atmospheric Research, Ecosciences Precinct, Brisbane, QLD, Australia
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  • William Venables,

    1. CSIRO Mathematics, Informatics and Statistics, Ecosciences Precinct, Brisbane, QLD, Australia
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  • Anthony J. Richardson

    1. School of Biological Sciences, The University of Queensland, St Lucia, QLD, Australia
    2. Climate Adaptation Flagship, CSIRO Marine and Atmospheric Research, Ecosciences Precinct, Brisbane, QLD, Australia
    3. Centre for Applications in Natural Resource Mathematics (CARM), School of Mathematics and Physics, University of Queensland, St Lucia, QLD, Australia
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Correspondence: Christopher Brown, tel. + 61 7 3365 8259, fax + 61 7 3365 1655, e-mail: christo.j.brown@gmail.com

Abstract

Contemporary impacts of anthropogenic climate change on ecosystems are increasingly being recognized. Documenting the extent of these impacts requires quantitative tools for analyses of ecological observations to distinguish climate impacts in noisy data and to understand interactions between climate variability and other drivers of change. To assist the development of reliable statistical approaches, we review the marine climate change literature and provide suggestions for quantitative approaches in climate change ecology. We compiled 267 peer-reviewed articles that examined relationships between climate change and marine ecological variables. Of the articles with time series data (n = 186), 75% used statistics to test for a dependency of ecological variables on climate variables. We identified several common weaknesses in statistical approaches, including marginalizing other important non-climate drivers of change, ignoring temporal and spatial autocorrelation, averaging across spatial patterns and not reporting key metrics. We provide a list of issues that need to be addressed to make inferences more defensible, including the consideration of (i) data limitations and the comparability of data sets; (ii) alternative mechanisms for change; (iii) appropriate response variables; (iv) a suitable model for the process under study; (v) temporal autocorrelation; (vi) spatial autocorrelation and patterns; and (vii) the reporting of rates of change. While the focus of our review was marine studies, these suggestions are equally applicable to terrestrial studies. Consideration of these suggestions will help advance global knowledge of climate impacts and understanding of the processes driving ecological change.

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