β-diversity scaling patterns are consistent across metrics and taxa
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β‐diversity (variation in community composition) is a fundamental component of biodiversity, with implications for macroecology, community ecology and conservation. However, its scaling properties are poorly understood. Here, we systematically assessed the spatial scaling of β‐diversity using 12 empirical large‐scale datasets including different taxonomic groups, by examining two conceptual types of β‐diversity and explicitly considering the turnover and nestedness components. We found highly consistent patterns across datasets. Multiple‐site β‐diversity (i.e. variation across multiple sites) scaling curves were remarkably consistent, with β‐diversity decreasing with sampled area according to a power law. For pairwise dissimilarities, the rates of increase of dissimilarity with geographic distance remained largely constant across scales, while grain size (or scale level) had a stronger effect on overall dissimilarity. In both analyses, turnover was the main contributor to β‐diversity, following total β‐diversity patterns closely, while the nestedness component was largely insensitive to scale changes. Our results highlight the importance of integrating both inter‐ and intraspecific aggregation patterns across spatial scales, which underpin substantial differences in community structure from local to regional scales.
Antão , L H , McGill , B , Magurran , A E , Soares , A & Dornelas , M 2019 , ' β-diversity scaling patterns are consistent across metrics and taxa ' , Ecography , vol. 42 , no. 5 , pp. 1012-1023 . https://doi.org/10.1111/ecog.04117
© 2018 The Authors. Ecography © 2018 Nordic Society Oikos. This work has been made available online in accordance with the publisher's policies. This is the author created accepted version manuscript following peer review and as such may differ slightly from the final published version. The final published version of this work is available at https://doi.org/10.1111/ecog.04117
DescriptionWe thank the University of St Andrews Bioinformatics Unit (Wellcome Trust ISSF grant 105621/Z/14/Z). L.H.A.was supported by Fundação para a Ciência e Tecnologia, Portugal (POPH/FSE SFRH/BD/90469/2012), A.E.M. by the ERC BioTIME (250189) and BioCHANGE (727440), and B.J.M. by USDA Hatch grant to MAFES #1011538 and NSF ABI grant #1660000. The BioTIME database was funded by ERC AdG BioTIME (250189) and ERC PoC BioCHANGE (727440).
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