bray.part: Partitioning pair-wise Bray-Curtis dissimilarities

In betapart: Partitioning Beta Diversity into Turnover and Nestedness Components

Partitioning pair-wise Bray-Curtis dissimilarities

Description

Computes 3 distance matrices accounting for the balanced variation and abundance gradient components of Bray-Curtis dissimilarity, and the sum of both values (i.e. Bray-Curtis dissimilarity)

Usage

bray.part(x)

Arguments

x	data frame of species abundances, where rows are sites and columns are species.

Value

The function returns a list with three dissimilarity matrices.

bray.bal	dist object, dissimilarity matrix accounting for the dissimilarity derived from balanced variation in abundance between sites
bray.gra	dist object, dissimilarity matrix accounting for the dissimilarity derived from unidirectional abundance gradients
bray	dist object, dissimilarity matrix accounting for total abundance-based dissimilarity between sites, measured as the Bray-Curtis 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

See Also

beta.pair

Examples

require(vegan)
data(BCI)
BCI.matrices<-bray.part(BCI)

betapart documentation built on March 31, 2023, 10:29 p.m.