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Lookup NU author(s): Professor Pip MooreORCiD
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0).
© 2014 The Authors. 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.
Author(s): O'Connor MI, Holding JM, Kappel CV, Duarte CM, Brander K, Brown CJ, Bruno JF, Buckley L, Burrows MT, Halpern BS, Kiessling W, Moore P, Pandolfi JM, Parmesan C, Poloczanska ES, Schoeman DS, Sydeman WJ, Richardson AJ
Publication type: Article
Publication status: Published
Journal: Global Ecology and Biogeography
Year: 2015
Volume: 24
Issue: 1
Pages: 64-76
Print publication date: 01/01/2015
Online publication date: 08/09/2014
Acceptance date: 01/01/1900
Date deposited: 29/12/2020
ISSN (print): 1466-822X
ISSN (electronic): 1466-8238
Publisher: Wiley
URL: https://doi.org/10.1111/geb.12218
DOI: 10.1111/geb.12218
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