DAMOCLES_sim: Simulating DAMOCLES

Description

Simulates DAMOCLES

Usage

DAMOCLES_sim(
  phy,
  gamma_0,
  gamma_td,
  mu,
  sigma,
  psiBranch,
  psiTrait,
  z,
  phi,
  traitOpt,
  br0,
  br_td,
  nTdim,
  root.state,
  root.trait.state,
  plotit = FALSE,
  keepExtinct = FALSE
)

Arguments

phy

phylogeny in phylo format

gamma_0

initial per lineage rate of immigration (gamma)

gamma_td

time dependency in gamma

per lineage rate of local extinction

sigma

probability of local (i.e. in-situ) speciation

psiBranch

phylogenetic distance at which gamma is half gamma_0

psiTrait

trait distance at which gamma is half gamma_0

shape of increase in gamma with increasing trait or phylogenetic distance

phi

rate of decline in gamma with distance from trait optima

traitOpt

trait value at which gamma = gamma_0

br0

Brownian rate parameter

br_td

rate of temporal decline in Brownian rate parameter

nTdim

number of independent trait dimensions

root.state

geographic state of ancestor i.e. present (1) or absent(0)

root.trait.state

trait value of ancestor

plotit

whether to plot the phylogeny and timing of immigration/local extinction events

keepExtinct

whether to retain data for extinct lineages

Value

A list of two tables. The first table contains the following columns: The first column contains the vector of tip labels in the phylogeny The last column contains the presence (1) or absence (0) of the species The second table has dimensions d x N where d is the number of trait dimensions and N is the number of species. It contains the trait values.

References

Pigot, A.L. & R.S. Etienne (2015). A new dynamic null model for phylogenetic community structure. Ecology Letters 18: 153-163.

Examples

Run this code

# NOT RUN {
#create random phylogeny
library(ape)
phy = ape::rcoal(10)
		
#run DAMOCLES		
out = DAMOCLES_sim(
  phy,
  gamma_0 = 1.5,
  gamma_td =0,
  mu = 0,
  sigma = 0,
  psiBranch = 0,
  psiTrait = 0,
  z = 10,
  phi = 0,
  traitOpt = 1,
  br0 = 0.1,
  br_td = -0.1,
  nTdim = 2,
  root.state = 1,
  root.trait.state = 0,
  plotit = FALSE,
  keepExtinct = FALSE
  )

#the output consists of a list		
patable = out[[1]] # the first element is the presence absence table
traits = out[[2]] # this is a matrix of traits values

#show presence/absence on the tree
patable$col = rep("black",dim(patable)[1])
patable$col[which(patable$state == 1)] = "red"
plot(phy,tip.col = patable$col)

# }