lizards: Phylogeny and quantitative traits of lizards

lizardsR Documentation

Phylogeny and quantitative traits of lizards

Description

This data set describes the phylogeny of 18 lizards as reported by Bauwens and D\'iaz-Uriarte (1997). It also gives life-history traits corresponding to these 18 species.

Format

lizards is a list containing the 3 following objects :

traits

is a data frame with 18 species and 8 traits.

hprA

is a character string giving the phylogenetic tree (hypothesized phylogenetic relationships based on immunological distances) in Newick format.

hprB

is a character string giving the phylogenetic tree (hypothesized phylogenetic relationships based on morphological characteristics) in Newick format.

Details

Variables of lizards$traits are the following ones : mean.L (mean length (mm)), matur.L (length at maturity (mm)), max.L (maximum length (mm)), hatch.L (hatchling length (mm)), hatch.m (hatchling mass (g)), clutch.S (Clutch size), age.mat (age at maturity (number of months of activity)), clutch.F (clutch frequency).

Note

This dataset replaces the former version in ade4.

References

Bauwens, D., and D\'iaz-Uriarte, R. (1997) Covariation of life-history traits in lacertid lizards: a comparative study. American Naturalist, 149, 91–111.

See a data description at http://pbil.univ-lyon1.fr/R/pdf/pps063.pdf (in French).

Examples



if(require(ape) && require(phylobase)){

## see data
data(lizards)
liz.tr <- read.tree(tex=lizards$hprA) # make a tree
liz <- phylo4d(liz.tr, lizards$traits) # make a phylo4d object
table.phylo4d(liz)

## compute and plot principal components
if(require(ade4)){
liz.pca1 <- dudi.pca(lizards$traits, cent=TRUE,
   scale=TRUE, scannf=FALSE, nf=2) # PCA of traits
myPC <- phylo4d(liz.tr, liz.pca1$li) # store PC in a phylo4d object
varlab <- paste("Principal \ncomponent", 1:2) # make labels for PCs
table.phylo4d(myPC, ratio=.8, var.lab=varlab) # plot the PCs
add.scatter.eig(liz.pca1$eig,2,1,2,posi="topleft", inset=c(0,.15))
title("Phylogeny and the principal components")

## compute a pPCA ##
## remove size effect
temp <- lapply(liz.pca1$tab, function(e) residuals(lm(e~-1+liz.pca1$li[,1])) )
temp <- data.frame(temp)
row.names(temp) <- tipLabels(liz)

## build corresponding phylo4d object
liz.noSize <- phylo4d(liz.tr, temp)
ppca1 <- ppca(liz.noSize, method="Abouheif", scale=FALSE, scannf=FALSE)
plot(ppca1)

}
}



adephylo documentation built on Oct. 6, 2023, 5:07 p.m.