run.popgensim: Run a time-forward popgen simulation

In PopGenReport: A Simple Framework to Analyse Population and Landscape Genetic Data

Run a time-forward popgen simulation

Description

performs a time-forward, agent-based and spatiallly explicit genetic population simulation

Usage

run.popgensim(
  simpops,
  steps,
  cost.mat,
  n.offspring,
  n.ind,
  mig.rate,
  disp.max,
  disp.rate,
  n.allels,
  mut.rate,
  n.cov = 3,
  rec = "none",
  emi.table = NULL
)

Arguments

simpops	pops object (a list of pop)
steps	the number of steps (generations)
cost.mat	a cost matrix (e.g. calculated via costDistance)
n.offspring	number of offsprings per female
n.ind	number of individuals
mig.rate	migration rate
disp.max	dispersal distance of disp.rate individuals
disp.rate	percentage of individuals achieving disp.max
n.allels	number of maximal alleles at a loci
mut.rate	mutation rate
n.cov	number of covariates (defaults to 3)
rec	switch if emigration matrix should be recorded, either "none" or "emi"
emi.table	a emigration matrix, if provide a fixed number of migration events will take place otherwise based on disp.max, mig.rate and disp.rate,

Details

A pops object created via init.popgensim is used as input. The function simulates time forward individual-based spatially explicit population dynamics. Subpopulations are linked by dispersal that can be specified via a pairwise distance matrix between subpopulations [cost.mat]. Distances are converted to a probability. Currenlty the function used is the p2p function, where dispersal is modeled using an exponential function, that can be specified via disp.max and disp.rate. disp.max specifies the maximal distance that are achieved by the proportion of disp.rate individuals in a subpopulation. The number of dispersers per generation is set to round(mig.rate * n.ind). A simple mutation rate can be specified (the probability of a mutation per loci) using mut.rate. The maximal allowed number of alleles per loci need to be specified. Currently the mutation model is a simple Kmax-allele model [n.alleles]. As before n.cov is the number if covariates in the data.frame (currenlty fixed to n.cov=3). To track emigration events between subpopulations (be aware output is then a list instead of a simple pops object) rec can be set to "emi", which provides a matrix that shows the actual emigrations between subpopulations during the simulation. Emigration can also be determistic (instead of using disp.max and disp.rate) to a specified number of dispersal events per subpopulations. Over each generation events are occuring in that order: 1. dispersal, 2. reproduction, 3. mutation. For convinience the simulation can be run a specified number of generations [steps]. In case extra dynamics need to be modelled (e.g. one population is increased in number be a managment action or population are affected by environmental factors) simulations can also run only in single time steps [steps=1]. See example.

Value

an updated pops object after steps time steps or a list that includes the pops object and the emigration matrix [rec="emi"].

See Also

init.popgensim

Examples

library(raster)
set.seed(1)
locs <- cbind(x=round(runif(5,5,45)), y=round(runif(5,5,45)) )
cm <- as.matrix(dist(locs))
pops <- init.popgensim(n.pops = 5, n.ind=20, sex.ratio = 0.25, n.loci = 5, n.allels = 10, n.cov = 3)
#run pops
pops <- run.popgensim(pops, steps = 200, cost.mat= cm, n.offspring = 2, n.ind = 20,
mig.rate = 0.125, disp.max = 30, disp.rate =0.1, n.allels = 10, mut.rate = 0)
#convert to genind object
pops.gi <-pops2genind(pops)
#calculate pairwise fsts using pairwise.fstb
fsts <- pairwise.fstb(pops.gi)
#plot
plot(locs, xlim=c(0,50), ylim=c(0,50), pch=16,cex=4, col="darkgrey")
for (i in 1:4)
for (ii in (i+1):5)
lines(c(locs[i,1], locs[ii,1]), c(locs[i,2], locs[ii,2]), lwd=fsts[i,ii]*30, col="darkgreen")
text(locs+0.5, labels=1:5, col="white", font=2)

PopGenReport documentation built on Oct. 11, 2023, 9:07 a.m.