Journal article
Strengthening confidence in the climate change impact science
Global Ecology and Biogeography, Vol.24(1), pp.64-76
2015
Abstract
Aim: To assess confidence in conclusions about climate-driven biological change through time, and identify approaches for strengthening confidence scientific conclusions about ecological impacts of climate change. Location: Global. Methods: We outlined a framework for strengthening confidence in inferences drawn from biological climate impact studies through the systematic integration of prior expectations, long-term data and quantitative statistical procedures. We then developed a numerical confidence index (Cindex) and used it to evaluate current practices in 208 studies of marine climate impacts comprising 1735 biological time series. Results: Confidence scores for inferred climate impacts varied widely from 1 to 16 (very low to high confidence). Approximately 35% of analyses were not associated with clearly stated prior expectations and 65% of analyses did not test putative non-climate drivers of biological change. Among the highest-scoring studies, 91% tested prior expectations, 86% formulated expectations for alternative drivers but only 63% statistically tested them. Higher confidence scores observed in studies that did not detect a change or tracked multiple species suggest publication bias favouring impact studies that are consistent with climate change. The number of time series showing climate impacts was a poor predictor of average confidence scores for a given group, reinforcing that vote-counting methodology is not appropriate for determining overall confidence in inferences. Main conclusions: Climate impacts research is expected to attribute biological change to climate change with measurable confidence. Studies with long-term, high-resolution data, appropriate statistics and tests of alternative drivers earn higher Cindex scores, suggesting these should be given greater weight in impact assessments. Together with our proposed framework, the results of our Cindex analysis indicate how the science of detecting and attributing biological impacts to climate change can be strengthened through the use of evidence-based prior expectations and thorough statistical analyses, even when data are limited, maximizing the impact of the diverse and growing climate change ecology literature.
Details
- Title
- Strengthening confidence in the climate change impact science
- Authors
- Mary I O'Connor (Author) - University of British Columbia, CanadaJohnna M Holding (Author) - Instituto Mediterráneo de Estudios Avanzados, SpainCarrie V Kappel (Author) - National Center for Ecological Analysis and Synthesis, United StatesCarlos M Duarte (Author) - University of Western AustraliaKeith Brander (Author) - DTU Aqua, DenmarkChristopher J Brown (Author) - University of QueenslandJohn F Bruno (Author) - University of North Carolina Chapel Hill, United StatesLauren Buckley (Author) - University of North Carolina Chapel Hill, United StatesMichael T Burrows (Author) - Scottish Marine Institute, United KingdomBenjamin S Halpern (Author) - University of California, United StatesWolfgang Kiessling (Author) - Universität Erlangen-Nürnberg, GermanyPippa Moore (Author) - Edith Cowan UniversityJohn M Pandolfi (Author) - University of QueenslandCamille Parmesan (Author) - Plymouth University, United KingdomElvira S Poloczanska (Author) - CSIRO Marine and Atmospheric ResearchDavid S Schoeman (Author) - University of the Sunshine Coast - Faculty of Science, Health, Education and EngineeringWilliam J Sydeman (Author) - Farallon Institute for Advanced Ecosystem Research, United StatesAnthony J Richardson (Author) - University of Queensland
- Publication details
- Global Ecology and Biogeography, Vol.24(1), pp.64-76
- Publisher
- Wiley-Blackwell Publishing Ltd.
- Date published
- 2015
- DOI
- 10.1111/geb.12218
- ISSN
- 1466-822X
- Organisation Unit
- School of Science and Engineering - Legacy; University of the Sunshine Coast, Queensland; School of Science, Technology and Engineering
- Language
- English
- Record Identifier
- 99448650102621
- Output Type
- Journal article
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