tree_bd: Phylogenetic uncertainty - net diversification rate
In sensiPhy: Sensitivity Analysis for Comparative Methods

Description Usage Arguments Details Value Author(s) References See Also Examples

Performs estimates of diversification rate evaluating uncertainty in trees topology.

1	tree_bd(phy, n.tree = "all", method = "ms", track = F, ...)

`phy`	A phylogeny (class 'multiPhylo', see ?`ape`).
`n.tree`	Number of times to repeat the analysis with n different trees picked randomly in the multiPhylo file. (If `n.tree` = "all", diversification will be estimated among the set of trees provided in `phy`)
`method`	the method for estimating diversification rate ("ms" or "km") (see Details).
`track`	Print a report tracking function progress (default = TRUE)
`...`	Further arguments to be passed to `phylosig`

This function estimates net diversification rate using bd.ms (Magallon and Sanderson (2000) method) or speciation rate using bd.km (Kendall-Moran method) for n trees, randomly picked from a multiPhylo file.

Output can be visualised using sensi_plot.

The function tree_bd returns a list with the following components:

tree.bd.estimates: Three number, diversification/speciation rate estimate ("Magallon and Sanderson" or "Kendall-Moran") for each run with a different phylogenetic tree.

stats: Main statistics for estimates across trees.CI_low and CI_high are the lower and upper limits of the 95

Gustavo Paterno

Paterno, G. B., Penone, C. Werner, G. D. A. sensiPhy: An r-package for sensitivity analysis in phylogenetic comparative methods. Methods in Ecology and Evolution 2018, 9(6):1461-1467

Magallon S and MJ Sanderson. 2000. Absolute diversification rates in angiosperm clades. Evolution 55:1762-1780.

bd.ms, tree_phylm,sensi_plot

data("primates")
# To estimate diversification rate with Magallon and Sanderson method:
fit <- tree_bd(phy = primates.phy, n.tree = 30, method = "ms")
summary(fit)
sensi_plot(fit)
# To estimate speciation rate Kendall-Moran method
fit <- tree_bd(phy = primates.phy, n.tree = 30, method = "km")
summary(fit)
sensi_plot(fit)