Description Usage Arguments Value Author(s) References Examples
View source: R/get_PD_sample.R
Computes the proportion of conserved phylogenetic diversity as a function of the proportion of conserved species, in trees simulated by the model
1 2 | get_PD_sample(epsilon, beta, alpha, N, sampl.frac, ntree, equal.ab,
eta, lengths = "yule", b = 1, d = 0)
|
epsilon |
Minimum size of unsampled splits (see appendix 1) |
beta |
Imbalance index |
alpha |
Clade age-richness index |
N |
Initial tip number |
sampl.frac |
Vector of tips fractions for which we want to compute the conserved PD |
ntree |
Number of simulated trees |
equal.ab |
If set to TRUE, all species have the same probability to go extinct first (default to TRUE) |
eta |
Clade abundance-richness index (if equal.ab == FALSE) |
lengths |
Model used to simulate node depths (can be "yule" (the default) or "kingman") |
b |
Birth rate (if lengths == "yule") |
d |
Death rate (if lengths == "yule") |
A table of size length(sample.fract)*ntree. The element in ligne i and column j is the remaining Phylogenetic Diversity fraction for the j^th tree in wich a fraction sample.frac[i] has been sampled.
Odile Maliet, Fanny Gascuel & Amaury Lambert
Maliet O., Gascuel F., Lambert A. (2018) Ranked tree shapes, non-random extinctions and the loss of phylogenetic diversity, bioRxiv 224295, doi: https://doi.org/10.1101/224295
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | set.seed(813)
sampl.frac=seq(0,1,by=0.05)
PD = get_PD_sample(epsilon=0.01,beta=0,alpha=0,N=50,
sampl.frac=sampl.frac,ntree=10,equal.ab=FALSE,
eta=0.5,lengths="yule",b=1,d=0)
probs = c(0.1, 0.9, 0.5)
PD_stats = as.vector(t(sapply(1:nrow(PD), function(i){quantile(PD[i,], probs)})))
par(mgp=c(2.2, 0.8, 0))
par(mar=c(4, 4, 1, 1))
plot(1, type="n", xlab="Fraction of extinct species, p",
ylab="PD loss", ylim=c(0,1), xlim=c(0,1))
points(c(0,1),c(0,1),t="l",col=grey(0),lty=3)
# plot 95% confidence intervals (grey area)
polygon(c(1-sampl.frac, rev(1-sampl.frac)), c(1-PD_stats[(1:length(sampl.frac))],
rev(1-PD_stats[((length(sampl.frac)+1):(2*length(sampl.frac)))])),
border=NA, col=grey(0.7))
# plot median value (black line)
points(1-sampl.frac, 1-PD_stats[((2*length(sampl.frac)+1):(3*length(sampl.frac)))],t="l")
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