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")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".
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)
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
# NOT RUN {
data(ceram.s)
ceram.dist<-beta.pair(ceram.s, index.family="jac")
# }
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