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Quantitative approaches in climate change ecology

Lookup NU author(s): Professor Pip MooreORCiD

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This is the final published version of a review published in its final definitive form in 2011. For re-use rights please refer to the publishers terms and conditions.


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. © 2011 Blackwell Publishing Ltd.


Publication metadata

Author(s): Brown CJ, Schoeman DS, Sydeman WJ, Brander K, Buckley LB, Burrows M, Duarte CM, Moore PJ, Pandolfi JM, Poloczanska E, Venables W, Richardson AJ

Publication type: Review

Publication status: Published

Journal: Global Change Biology

Year: 2011

Volume: 17

Issue: 12

Pages: 3697-3713

Print publication date: 01/12/2011

Online publication date: 24/08/2011

ISSN (print): 1354-1013

ISSN (electronic): 1365-2486

URL: https://doi.org/10.1111/j.1365-2486.2011.02531.x

DOI: 10.1111/j.1365-2486.2011.02531.x


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