betapart (version 1.6)

phylo.beta.pair: Pair-wise phylogenetic dissimilarities

Description

Computes 3 distance matrices accounting for the phylogenetic turnover and nestedness components of phylogenetic beta diversity, and the sum of both values. Phylogenetic dissimilarities are based on Faith's phylogenetic diversity.

Usage

phylo.beta.pair(x, tree, index.family="sorensen")

Value

The function returns a list with three phylogenetic dissimilarity matrices.

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

phylo.beta.sim

dist object, dissimilarity matrix accounting for phylogenetic turnover, measured as Simpson derived pair-wise phylogenetic dissimilarity

phylo.beta.sne

dist object, dissimilarity matrix accounting for nestedness-resultant phylogenetic dissimilarity, measured as the nestedness-fraction of Sorensen derived pair-wise phylogenetic dissimilarity

phylo.beta.sor

dist object, dissimilarity matrix accounting for phylogenetic beta diversity, measured as Sorensen derived pair-wise phylogenetic dissimilarity

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

phylo.beta.jtu

dist object, dissimilarity matrix accounting for phylogenetic turnover, measured as the turnover-fraction of Jaccard derived pair-wise phylogenetic dissimilarity

phylo.beta.jne

dist object, dissimilarity matrix accounting for nestedness-resultant phylogenetic dissimilarity, measured as the nestedness-fraction of Jaccard derived pair-wise phylogenetic dissimilarity

phylo.beta.jac

dist object, dissimilarity matrix accounting for phylogenetic beta diversity, measured as Jaccard derived pair-wise phylogenetic dissimilarity

Arguments

x

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

tree

a phylogenetic tree of class phylo with tips names identic to species names from the community matrix.

index.family

family of dissimilarity indices, partial match of "sorensen" or "jaccard".

Author

Julien De Bortoli ([e-mail]), Fabien Leprieur([e-mail]), Andrés Baselga and David Orme

Details

The Sorensen dissimilarity index allows computing the PhyloSor index (Bryant et al. 2008) whereas the Jaccard dissimilarity index allows computing the UniFrac index (Lozupone & Knight 2005).

References

Baselga A. (2012) The relationship between species replacement, dissimilarity derived from nestedness, and nestedness. Global Ecology and Biogeography 21, 1223-1232

Bryant JA, Lamanna C, Morlon H, Kerkhoff AJ, Enquist BJ, et al. (2008) Microbes on mountainsides: Contrasting elevational patterns of bacterial and plant diversity. Proceedings of the National Academy of Sciences of the United States of America 105: 11505-11511.

Faith DP, Lozupone CA, Nipperess D, Knight R (2009) The Cladistic Basis for the Phylogenetic Diversity (PD) Measure Links Evolutionary Features to Environmental Gradients and Supports Broad Applications of Microbial Ecology's "Phylogenetic Beta Diversity" Framework. Int J Mol Sci 10: 4723-4741. doi: 10.3390/ijms10114723.

Leprieur F, Albouy C, De Bortoli J, Cowman PF, Bellwood DR, et al. (2012) Quantifying Phylogenetic Beta Diversity: Distinguishing between "True" Turnover of Lineages and Phylogenetic Diversity Gradients. PLoS ONE 7(8): e42760. doi:10.1371/journal.pone.0042760

Lozupone C, Knight R (2005) UniFrac: a new phylogenetic method for comparing microbial communities. Applied and Environmental Microbiology 71: 8228-8235.

See Also

phylo.betapart.core, beta.pair

Examples

# toy tree for 6 species (sp1 to sp6)
require(ape)
toy.tree<-read.tree(text="(((sp1:1,sp2:1):5,(sp3:3,sp4:3):3):2,(sp5:7,sp6:7):1);")
plot(toy.tree)

# toy community table with 6 assemblages (A to F) with 6 species (sp1 to sp6)
toy.comm<-matrix(nrow=6, ncol=6)
rownames(toy.comm)<-c("A","B","C","D","E","F")
colnames(toy.comm)<-c("sp1","sp2","sp3","sp4","sp5","sp6")
toy.comm[1,]<-c(1,1,1,0,0,0)
toy.comm[2,]<-c(0,1,1,1,0,0)
toy.comm[3,]<-c(0,0,1,1,1,0)
toy.comm[4,]<-c(0,0,1,1,1,1)
toy.comm[5,]<-c(0,0,0,1,1,1)
toy.comm[6,]<-c(1,0,0,1,1,1)


toy.phylobetapair<-phylo.beta.pair(toy.comm, toy.tree, index.family="sor")
toy.betapair<-beta.pair(toy.comm, index.family="sor")
plot(toy.betapair$beta.sim,toy.phylobetapair$phylo.beta.sim)
plot(toy.betapair$beta.sne,toy.phylobetapair$phylo.beta.sne)