Description Usage Arguments Value Author(s) References See Also Examples
Computes 3 distance matrices accounting for the spatial turnover and nestedness components of functional beta diversity, and the sum of both values. Functional dissimilarities are based on volume of convex hulls intersections in a multidimensional functional space.
1 | functional.beta.pair(x, traits, index.family="sorensen")
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x |
data frame, where rows are sites and columns are species. Alternatively |
traits |
if |
index.family |
family of dissimilarity indices, partial match of |
The function returns a list with three functional dissimilarity matrices.
For index.family="sorensen"
the three matrices are:
funct.beta.sim |
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funct.beta.sne |
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funct.beta.sor |
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For index.family="jaccard"
the three matrices are:
funct.beta.jtu |
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funct.beta.jne |
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funct.beta.jac |
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Sébastien Villéger, Andrés Baselga and David Orme
Villéger S., Novack-Gottshal P. & Mouillot D. 2011. The multidimensionality of the niche reveals functional diversity changes in benthic marine biotas across geological time. Ecology Letters. 14, 561–568
Baselga, A. 2012. The relationship between species replacement, dissimilarity derived from nestedness, and nestedness. Global Ecology and Biogeography 21, 1223-1232
Villéger, S. Grenouillet, G., Brosse, S. 2013. Decomposing functional beta-diversity reveals that low functional beta-diversity is driven by low functional turnover in European fish assemblages. Global Ecology and Biogeography, 22: 671-681
functional.beta.multi
, functional.betapart.core
, beta.pair
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | ##### 4 communities in a 2D functional space (convex hulls are rectangles)
traits.test<-cbind( c(1,1,1,2,2,3,3,4,4,5,5) , c(1,2,4,1,2,3,5,1,4,3,5) )
dimnames(traits.test)<-list(paste("sp",1:11,sep="") , c("Trait 1","Trait 2") )
comm.test<-matrix(0,4,11,dimnames=list( c("A","B","C","D") , paste("sp",1:11,sep="") ) )
comm.test["A",c(1,2,4,5)]<-1
comm.test["B",c(1,3,8,9)]<-1
comm.test["C",c(6,7,10,11)]<-1
comm.test["D",c(2,4,7,9)]<-1
plot(5,5,xlim=c(0,6), ylim=c(0,6), type="n", xlab="Trait 1",ylab="Trait 2")
points(traits.test[,1],traits.test[,2], pch=21,cex=1.5,bg="black")
rect(1,1,4,4, col="#458B0050", border="#458B00") ; text(2.5,2.5,"B",col="#458B00",cex=1.5)
polygon(c(2,1,3,4), c(1,2,5,4), col="#DA70D650", border="#DA70D6") ;
text(2.5,3,"D",col="#DA70D6",cex=1.5)
rect(1,1,2,2, col="#FF000050" , border="#FF0000") ; text(1.5,1.5,"A",col="#FF0000",cex=1.5)
rect(3,3,5,5, col="#1E90FF50", border="#1E90FF") ; text(4,4.2,"C",col="#1E90FF",cex=1.5)
test.pair<-functional.beta.pair(x=comm.test, traits=traits.test, index.family = "jaccard" )
lapply(test.pair,round,2)
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