sim.convergence.geo: Simulation of trait data under the model of convergent...
In hmorlon/PANDA: Phylogenetic ANalyses of DiversificAtion

sim.convergence.geo

R Documentation

Simulation of trait data under the model of convergent character displacement described in Drury et al. 2017

Description

Simulates the evolution of a continuous character that evolves depending on pairwise similarity in another, OU-evolving trait (e.g., a trait that covaries with resource use). sig2 and z0 are shared between two traits, max and alpha are for focal trait, OU parameters for non-focal trait

Usage


sim.convergence.geo(phylo,pars, Nsegments=2500, plot=FALSE, geo.object)

Arguments

`phylo`	an object of type 'phylo' (see ape documentation)
`pars`	A matrix with a number of rows corresponding to the desired number of simulations, columns containing values for `sig2` in `[,1]`, `m` in `[,2]`, `alpha` in `[,3]`, `root.value` in `[,4]`, `psi` of the OU model for the non-focal, resource use trait in `[,5]`, and `theta` in the OU model for the non-focal resource use trait in `[,6]`
`Nsegments`	the minimum number of time steps to simulate
`plot`	if `TRUE`, returns two plots: the top plot is focal trait undergoing convergence, the bottom plot is non-focal trait evolving under BM or OU
`geo.object`	geography object created using CreateGeoObject

Details

Adjusting Nsegments will impact the length of time the simulations take. The length of each segment (max(nodeHeights(phylo))/Nsegments) should be much smaller than the smallest branch (min(phylo$edge.length)).

Value

A list of two matrices with the simulated values for each lineage (one simulation per row; columns correspond to species) for trait1 (focul trait undergoing convergence) and non.focal (resource-use trait that determines strength of convergence in trait1)

Author(s)

J.P. Drury jonathan.p.drury@gmail.com

References

Drury, J., Grether, G., Garland Jr., T., and Morlon, H. 2017. A review of phylogenetic methods for assessing the influence of interspecific interactions on phenotypic evolution. Systematic Biology

Examples



data(Anolis.data)
phylo<-Anolis.data$phylo
geo.object<-Anolis.data$geography.object

#simulate with the OU process present and absent
pars<-expand.grid(0.05,-0.1,1,0,c(2,0),0)
sim.convergence.geo(phylo,pars,Nsegments=2500, plot=FALSE, geo.object)

hmorlon/PANDA documentation built on March 8, 2024, 8:36 p.m.