rate.estimate: Calculate net diversification rate with confindence limits, and test diversities

Description

rate.estimate Uses Magellon and Sanderson method to calculate net diversification rate for a clade given extant diversity and age. Associated functions crown.p and stem.p also calculate the probability of obtaining a clade with at least k species given a net diversification rate (r), extinction fraction (e), and time interval. Associated functions stem.limits and crown.limits generate confidence limits on extant diversity given a net diversification rate (r), extinction fraction (e), and time interval.

Usage

rate.estimate(time=0, n=0, phy=NULL, epsilon = 0, missing = 0, crown=TRUE, kendall.moran=FALSE)
crown.p(time, r, epsilon, n)
stem.p(time, r, epsilon, n)
crown.limits(r, epsilon, time, prob=c(0.025, 0.975))
stem.limits(r, epsilon, time, prob=c(0.025, 0.975))

Arguments

time

Time interval; can be a vector

Number of extant species

phy

Phylogenetic tree; can be supplied instead of time and n. If you're using a tree then crown is automatically true.

epsilon

Extinction rate as a fraction of speciation rate

missing

Number of taxa missing from tree

crown

If true, time is treated as crown age; otherwise, stem age

kendall.moran

If true, calculates Kendall-Moran estimate of speciation rate; requires a complete phylogenetic tree

Net diversification rate, birth - death

prob

Range of probabilities for calculating confidence region

Value

rate.estimate: Returns net diversification rate r = lambda - mu, and confidence interval crown.p and stem.p: Returns the probability of obtaining a clade as big as, or bigger than, size n, given time, r, and epsilon stem.limits and crown.limits: Return confidence intervals for clade size given time, r, and epsilon

References

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

Examples

Run this code

data(geospiza)
attach(geospiza)

# Assuming no extinction
rate.estimate(phy=geospiza.tree, missing=1)

# Assuming high extinction
rate.estimate(phy=geospiza.tree, epsilon=0.9, missing=1)