Journal ArticleDOI
Partitioning the turnover and nestedness components of beta diversity
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TLDR
In this paper, a unified framework for the assessment of beta diversity, disentangling the contribution of spatial turnover and nestedness to beta-diversity patterns, is provided, which is crucial for our understanding of central biogeographic, ecological and conservation issues.Abstract:
Aim Beta diversity (variation of the species composition of assemblages) may reflect two different phenomena, spatial species turnover and nestedness of assemblages, which result from two antithetic processes, namely species replacement and species loss, respectively. The aim of this paper is to provide a unified framework for the assessment of beta diversity, disentangling the contribution of spatial turnover and nestedness to beta-diversity patterns.
Innovation I derive an additive partitioning of beta diversity that provides the two separate components of spatial turnover and nestedness underlying the total amount of beta diversity. I propose two families of measures of beta diversity for pairwise and multiple-site situations. Each family comprises one measure accounting for all aspects of beta diversity, which is additively decomposed into two measures accounting for the pure spatial turnover and nestedness components, respectively. Finally, I provide a case study using European longhorn beetles to exemplify the relevance of disentangling spatial turnover and nestedness patterns.
Main conclusion Assigning the different beta-diversity patterns to their respective biological phenomena is essential for analysing the causality of the processes underlying biodiversity. Thus, the differentiation of the spatial turnover and nestedness components of beta diversity is crucial for our understanding of central biogeographic, ecological and conservation issues.read more
Citations
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Journal ArticleDOI
Betapart an R package for the study of beta diversity
Andrés Baselga,C. David L. Orme +1 more
TL;DR: Betapart as mentioned in this paper is an R package for computing total dissimilarity as Sorensen or Jaccard indices, as well as their respective turnover and nestedness components.
Journal ArticleDOI
Beta diversity as the variance of community data: dissimilarity coefficients and partitioning.
TL;DR: The approach links the concept of beta diversity with the analysis of community data by commonly used methods like ordination and anova, and addressed the question of which index to use by coding 16 indices using 14 properties that are necessary for beta assessment, comparability among data sets, sampling issues and ordination.
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How Should Beta-Diversity Inform Biodiversity Conservation?
TL;DR: How beta-diversity is impacted by human activities, including farming, selective logging, urbanization, species invasions, overhunting, and climate change is reviewed.
Journal ArticleDOI
Interpreting the replacement and richness difference components of beta diversity
TL;DR: This paper first reviews the historical development of the formulae for decomposing dissimilarities into replacement, richness difference and nestedness indices, and shows that local contributions of replacement and richness difference to total beta diversity can be computed and mapped.
Journal ArticleDOI
The relationship between species replacement, dissimilarity derived from nestedness, and nestedness
TL;DR: It is shown how Jaccard dissimilarity can be partitioned into meaningful turnover and nestedness components, and extended to multiple-site situations, and the concepts of nestedness and nesteds-resultant Dissimilarity are discussed.
References
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