beta.pair.abund {betapart}

Abundance-based pair-wise dissimilarities

Description

Computes 3 distance matrices accounting for the (i) balanced variation in abundances, (ii) abundance gradients, and (iii) total dissimilarity (i.e. the sum of both components).

Usage

beta.pair.abund(x, index.family = "bray")

Arguments

x

data frame, where rows are sites and columns are species. Alternatively x can be a betapart.abund object derived from the betapart.core.abund function

index.family

family of dissimilarity indices, partial match of "bray" or "ruzicka".

Value

The function returns a list with three dissimilarity matrices. For index.family="bray" the three matrices are:

beta.bray.bal

dist object, dissimilarity matrix accounting for the dissimilarity derived from balanced variation in abundance between sites

beta.bray.gra

dist object, dissimilarity matrix accounting for the dissimilarity derived from unidirectional abundance gradients

beta.bray

dist object, dissimilarity matrix accounting for total abundance-based dissimilarity between sites, measured as the Bray-Curtis index

For index.family="ruzicka" the three matrices are:

beta.ruz.bal

dist object, dissimilarity matrix accounting for the dissimilarity derived from balanced variation in abundance between sites

beta.ruz.gra

dist object, dissimilarity matrix accounting for the dissimilarity derived from unidirectional abundance gradients

beta.ruz

dist object, dissimilarity matrix accounting for total abundance-based dissimilarity between sites, measured as the Ruzicka index

Author(s)

Andrés Baselga

References

Baselga, A. 2013. Separating the two components of abundance-based dissimilarity: balanced changes in abundance vs. abundance gradients. Methods in Ecology and Evolution 4: 552–557

Legendre, P. 2014. Interpreting the replacement and richness difference components of beta diversity. Global Ecology and Biogeography, 23: 1324–1334

See Also

beta.multi.abund, beta.sample.abund, betapart.core.abund, beta.pair

Examples

require(vegan)
data(BCI)
BCI.pair<-beta.pair.abund(BCI, index.family="bray")