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dc.contributor.authorO'Connor, Mary I
dc.contributor.authorHolding, Johnna M
dc.contributor.authorKappel, Carrie V
dc.contributor.authorDuarte, Carlos M
dc.contributor.authorBrander, Keith
dc.contributor.authorBrown, Christopher J
dc.contributor.authorBruno, John F
dc.contributor.authorBuckley, Lauren
dc.contributor.authorBurrows, Michael T
dc.contributor.authorHalpern, Benjamin S
dc.contributor.authorKiessling, Wolfgang
dc.contributor.authorMoore, Pippa
dc.contributor.authorPandolfi, John M
dc.contributor.authorParmesan, Camille
dc.contributor.authorPoloczanska, Elvira S
dc.contributor.authorSchoeman, David S
dc.contributor.authorSydeman, William J
dc.contributor.authorRichardson, Anthony J
dc.date.accessioned2018-01-05T04:27:18Z
dc.date.available2018-01-05T04:27:18Z
dc.date.issued2015
dc.identifier.issn1466-822X
dc.identifier.doi10.1111/geb.12218
dc.identifier.urihttp://hdl.handle.net/10072/173587
dc.description.abstractAim 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.
dc.description.peerreviewedYes
dc.languageEnglish
dc.publisherWiley-Blackwell Publishing
dc.relation.ispartofpagefrom64
dc.relation.ispartofpageto76
dc.relation.ispartofjournalGlobal Ecology and Biogeography
dc.relation.ispartofvolume24
dc.subject.fieldofresearchEcological Applications not elsewhere classified
dc.subject.fieldofresearchEcology
dc.subject.fieldofresearchEcological Applications
dc.subject.fieldofresearchPhysical Geography and Environmental Geoscience
dc.subject.fieldofresearchcode050199
dc.subject.fieldofresearchcode0602
dc.subject.fieldofresearchcode0501
dc.subject.fieldofresearchcode0406
dc.titleStrengthening confidence in climate impacts science
dc.typeJournal article
dc.type.descriptionC1 - Articles
dc.type.codeC - Journal Articles
dcterms.licensehttp://creativecommons.org/licenses/by/3.0/
dc.description.versionPublished
gro.rights.copyright© The Author(s) 2014. This is an Open Access article distributed under the terms of the Creative Commons Attribution 3.0 Unported (CC BY 3.0) License (https://creativecommons.org/licenses/by/3.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
gro.hasfulltextFull Text
gro.griffith.authorBrown, Chris J.


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