betapart.core.abund: Core calculations of betapart for abundance-based...

In betapart: Partitioning Beta Diversity into Turnover and Nestedness Components

Core calculations of betapart for abundance-based dissimilarity measures

Description

Computes the basic quantities needed for computing the abundance-based multiple-site dissimilarity measures and pairwise dissimilarity matrices.

Usage

betapart.core.abund(x)

Arguments

x	data frame, where rows are sites and columns are species

Value

The function returns an object of class betapart.abund with the following elements:

multiple.shared.abund	the multiple-site intersection component in terms of abundances (AM)
pair.shared.abund	a matrix containing the agreement in abundance between pairs of sites (A)
min.not.shared.abund	a matrix containing the minimum disagreement in abundance between pairs of sites: min(B,C)
max.not.shared.abund	a matrix containing the maximum disagreement in abundance between pairs of sites between pairs of sites: max(B,C)
pair.not.shared.abund	a matrix containing the total disagreement in abundance between pairs of sites: B+C

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

Baselga, A. 2017. Partitioning abundance-based multiple-site dissimilarity into components: balanced variation in abundance and abundance gradients. Methods in Ecology and Evolution, 8: 799-808

See Also

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

Examples

require(vegan)
data(BCI)
core.BCI<-betapart.core.abund(BCI)
pair.BCI<-beta.pair.abund(core.BCI)
multi.BCI<-beta.multi.abund(core.BCI)

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