Computes 3 distance matrices accounting for the (i) turnover (replacement), (ii) nestedness-resultant component, and (iii) total dissimilarity (i.e. the sum of both components).
beta.pair(x, index.family = "sorensen")The function returns a list with three dissimilarity matrices.
For index.family="sorensen" the three matrices are:
dist object, dissimilarity matrix accounting for spatial turnover (replacement), measured as Simpson pair-wise dissimilarity
dist object, dissimilarity matrix accounting for nestedness-resultant dissimilarity, measured as the nestedness-fraction of Sorensen pair-wise dissimilarity
dist object, dissimilarity matrix accounting for total dissimilarity, measured as Sorensen pair-wise dissimilarity (a monotonic transformation of beta diversity)
For index.family="jaccard" the three matrices are:
dist dissimilarity matrix accounting for spatial turnover, measured as the turnover-fraction of Jaccard pair-wise dissimilarity
dist object, dissimilarity matrix accounting for nestedness-resultant dissimilarity, measured as the nestedness-fraction of Jaccard pair-wise dissimilarity
dist object, dissimilarity matrix accounting for beta diversity, measured as Jaccard pair-wise dissimilarity (a monotonic transformation of beta diversity)
data frame, where rows are sites and columns are species. Alternatively x can be a betapart object derived from the betapart.core function
family of dissimilarity indices, partial match of "sorensen" or "jaccard".
Andrés Baselga and David Orme
Baselga, A. 2010. Partitioning the turnover and nestedness components of beta diversity. Global Ecology and Biogeography 19:134-143
Baselga, A. 2012. The relationship between species replacement, dissimilarity derived from nestedness, and nestedness. Global Ecology and Biogeography 21, 1223-1232
beta.pair.abund, codebeta.multi, beta.sample, betapart.core, beta.temp
data(ceram.s)
ceram.dist<-beta.pair(ceram.s, index.family="jac")
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