Quantitative approaches in climate change ecology |
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| Authors: | Christopher J Brown David S Schoeman William J Sydeman Keith Brander Lauren B Buckley Michael Burrows Carlos M Duarte Pippa J Moore John M Pandolfi Elvira Poloczanska William Venables Anthony J Richardson |
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| Institution: | 1. School of Biological Sciences, The University of Queensland, , St Lucia, QLD, 4072 Australia;2. Climate Adaptation Flagship, CSIRO Marine and Atmospheric Research, Ecosciences Precinct, , Brisbane, QLD, 4001 Australia;3. Environmental Science Research Institute, School of Environmental Sciences, University of Ulster, , Coleraine, BT52 1SA UK;4. Department of Zoology, Nelson Mandela Metropolitan University, , Port Elizabeth, 6031 South Africa;5. Farallon Institute for Advanced Ecosystem Research, , Petaluma, CA, 94952 USA;6. National Institute of Aquatic Resources, Technical University of Denmark, , DK‐2920 Charlottenlund, Denmark;7. Department of Biology, University of North Carolina, , Chapel Hill, NC, 27566 USA;8. Scottish Association for Marine Science, Scottish Marine Institute, , Argyll, PA, 37 1QA UK;9. Department of Global Change Research, IMEDEA (UIB‐CSIC), Instituto Mediterráneo de Estudios Avanzados, , 07190 Esporles, Mallorca, Spain;10. The UWA Ocean Institute, University of Western Australia, , Crawley, WA, 6009 Australia;11. Centre for Marine Ecosystems Research, Edith Cowan University, , Perth, WA, 6027 Australia;12. Institute of Biological, Environmental and Rural Sciences, Aberystwyth University, , Aberystwyth, SY23 3DA UK;13. Australian Research Council Centre of Excellence for Coral Reef Studies, School of Biological Sciences, The University of Queensland, , St. Lucia, QLD, 4072 Australia;14. CSIRO Mathematics, Informatics and Statistics, Ecosciences Precinct, , Brisbane, QLD, 4001 Australia;15. Centre for Applications in Natural Resource Mathematics (CARM), School of Mathematics and Physics, University of Queensland, , St Lucia, QLD, 4072 Australia |
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| 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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