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Effectiveness of biological surrogates for predicting patterns of marine biodiversity: a global meta-analysis

Citation

Mellin, C and Delean, S and Caley, J and Edgar, G and Meekan, M and Pitcher, R and Przeslawski, R and Williams, A and Bradshaw, C, Effectiveness of biological surrogates for predicting patterns of marine biodiversity: a global meta-analysis, PLoS ONE, 6, (6) Article e20141. ISSN 1932-6203 (2011) [Refereed Article]


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Licenced under the Creative Commons Attribution 2.5 Generic (CC BY 2.5) http://creativecommons.org/licenses/by/2.5/

DOI: doi:10.1371/journal.pone.0020141

Abstract

The use of biological surrogates as proxies for biodiversity patterns is gaining popularity, particularly in marine systems where field surveys can be expensive and species richness high. Yet, uncertainty regarding their applicability remains because of inconsistency of definitions, a lack of standard methods for estimating effectiveness, and variable spatial scales considered. We present a Bayesian meta-analysis of the effectiveness of biological surrogates in marine ecosystems. Surrogate effectiveness was defined both as the proportion of surrogacy tests where predictions based on surrogates were better than random (i.e., low probability of making a Type I error; P) and as the predictability of targets using surrogates (R2). A total of 264 published surrogacy tests combined with prior probabilities elicited from eight international experts demonstrated that the habitat, spatial scale, type of surrogate and statistical method used all influenced surrogate effectiveness, at least according to either P or R2. The type of surrogate used (higher-taxa, cross-taxa or subset taxa) was the best predictor of P, with the higher-taxa surrogates outperforming all others. The marine habitat was the best predictor of R2, with particularly low predictability in tropical reefs. Surrogate effectiveness was greatest for higher-taxa surrogates at a <10-km spatial scale, in low-complexity marine habitats such as soft bottoms, and using multivariate-based methods. Comparisons with terrestrial studies in terms of the methods used to study surrogates revealed that marine applications still ignore some problems with several widely used statistical approaches to surrogacy. Our study provides a benchmark for the reliable use of biological surrogates in marine ecosystems, and highlights directions for future development of biological surrogates in predicting biodiversity.

Item Details

Item Type:Refereed Article
Research Division:Biological Sciences
Research Group:Ecology
Research Field:Marine and Estuarine Ecology (incl. Marine Ichthyology)
Objective Division:Environment
Objective Group:Flora, Fauna and Biodiversity
Objective Field:Marine Flora, Fauna and Biodiversity
Author:Edgar, G (Professor Graham Edgar)
ID Code:77846
Year Published:2011
Web of Science® Times Cited:55
Deposited By:Sustainable Marine Research Collaboration
Deposited On:2012-06-01
Last Modified:2017-11-01
Downloads:241 View Download Statistics

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