anc.clim {phyloclim} | R Documentation |
This function implements a nonparametric approach to estimate ancestral climatic tolerances proposed by Evans et al. (2009), using ace
from the ape
package.
anc.clim(target, posterior = NULL, pno, n = 100, method = "GLS")
target |
An object of class "phylo" ; a best estimate (e.g., ML estimate) of topology on which to summarize mean estimated climatic tolerances, must be ultrametric.
|
posterior |
An object of class "multiPhylo" containing a sample of ultrametric trees from the posterior distribution of a Bayesian tree search to be used for reconstruction of ancestral climatic tolerances. posterior = NULL (the default) means that reconstruction uses target instead.
|
pno |
A data frame containing predicted niche occupancy (PNO) profiles, produced e.g. with pno . |
n |
An integer: The PNO profile given by pno argument will be resamples n times. |
method |
A character string specifying the method used for estimation. Two choices are possible: "ML" or "GLS" (see ace for details).
|
A list containing three elements:
tree |
An object of class "phylo" , the target tree used in the estimation. |
means |
A vector containing the means of estimated ancestral climatic tolerances. The elements of means are in the same order as node numbers in element tree . |
central.density |
A matrix, which for each of the terminal nodes in tree contains the minimum and the maximum of the 80 percent density interval of climatic tolerances (as sampled from the PNO). |
Christoph Heibl (heibl@lmu.de)
Evans, M. E. K., S. A. Smith, R. S. Flynn, and M. J. Donoghue. 2009. Climate, niche evolution, and diversification of the 'bird-cage evening primroses' (Oenothera, sections Anogra and Kleinia). Am. Nat. 173: 225-240.
# load phylogeny and PNOs of Oxalis sect. Palmatifoliae data(palmatifoliae_tree) data(palmatifoliae_pno) # choose summer precipitation for analysis clim <- palmatifoliae_pno$PrecipitationWarmestQuarter # estimate ancestral tolerances ac <- anc.clim(target = palmatifoliae_tree, pno = clim, n = 100) # visualize results plotAncClim(ac, ylab = "Precipitation of warmest quarter (mm)")