A presence or absence (binary) matrix for each species (columns) in each location or grid cell (rows)
method
The method to use. Options are "pairwise", "topology", and "spanning". Default is "spanning".
type
Phylogenetic measure from those listed in Schweiger et al 2008. Options are "Q", "P", "W", "clade", "species", "J", "F", "AvTD","TTD", "Dd". Default is "clade".
root
Phylogenetic diversity can either be rooted or unrooted. Details in Schweiger et al 2008. Default is FALSE.
average
Phylogenetic diversity can either be averaged or not averaged. Details in Schweiger et al 2008. Default is FALSE.
verbose
Boolean indicating whether to print progress output during calculation. Default is TRUE.
Details
Given a phylogenetic tree and a presence/absence matrix this script calculates phylogenetic diversity of a group of species across a given set of grid cells or locations. The library "ape" is required to read the tree in R. Command is "read.tree" or "read.nexus".
Options of type:
"P" is a normalized mearure of "Q".
"clade" is "PDnode" when root= FALSE, and is "PDroot" ehn root =TRUE.
"species" is "AvPD".
Value
This function returns a list of phylogenetic diversity values for each of the grid cells in the presence/absence matrix
Schweiger, O., S. Klotz, W. Durka and I. Kuhn. 2008. A comparative test of phylogenetic diversity indices. Oecologia, 157, 485-495.
Pio, D.V., O. Broennimann, T.G. Barraclough, G. Reeves, A.G. Rebelo, W. Thuiller, A. Guisan and N. Salamin. 2011. Spatial predictions of phylogenetic diversity in conservation decision making. Conservation Biology, 25, 1229-1239.
Pio, D.V., R. Engler, H.P. Linder, A. Monadjem, F.P.D. Cotterill, P.J. Taylor, M.C. Schoeman, B.W. Price, M.H. Villet, G. Eick, N. Salamin and A. Guisan. 2014. Climate change effects on animal and plant phylogenetic diversity in southern Africa. Global Change Biology, 20, 1538-1549.
Examples
fpath <- system.file("extdata", "ecospat.testTree.tre", package="ecospat")
tree <-read.tree(fpath)
data <- ecospat.testData[9:52]
pd <- ecospat.calculate.pd(tree, data, method = "spanning", type = "species", root = FALSE,
average = FALSE, verbose = TRUE )
plot(pd)