Fit regressions on species abundance or presence/absence across communities and calculate phylogenetic correlations
sppregs(samp, env, tree=NULL, fam="gaussian")
sppregs.plot(sppreg, rows=c(1,3), cex.mag=1, x.label="phylogenetic correlations",
y.label=c("occurrence correlations w/ env", "occurrence correlations wo/ env",
"change in correlations"))community data matrix, species as columns, communities as rows
environmental data matrix
phylo tree object or a phylogenetic covariance matrix
object from function sppregs
rows = c(1,3) plots in a row; rows = c(3,1) in a column
value for cex in par
x axis labels
y axis labels
the regression error distribution
the residuals from each species regression
the estimated coefficients from each species regression
the standard errors of the coefficients
correlations of pairwise species phylogenetic correlations between: the observed pairwise correlations of species across communities, the residual correlations, and the pairwise differences between the two
the observed pairwise correlations of species across communities
the residual pairwise correlations of species across communities
the phylogenetic pairwise correlations among species
For each species in samp, the function fits regressions of species presence/absence or abundances
on the environmental variables supplied in env; and calculates the (n^2-n)/2 pairwise species correlations
between the residuals of these fits and pairwise species phylogenetic correlations. The residuals can be
thought of as the presence/absence of species across sites/communities after accounting for how species respond
to environmental variation across sites. Each set of coefficients can be tested for phylogenetic signal with, for example,
the function phylosignal.
The function sppregs.plot produces a set of three plots of the correlations of pairwise species phylogenetic correlations versus:
the observed pairwise correlations of species across communities, the residual correlations, and the pairwise differences between (i.e., the
change in species co-occurrence once the environmental variables are taken into account). The significance of these correlations can be tested
via permutation with the function phylostruct.
Helmus M.R., Savage K., Diebel M.W., Maxted J.T. & Ives A.R. (2007) Separating the determinants of phylogenetic community structure. Ecology Letters, 10, 917-925