HundredPopMonoecious: Example datasets for a hundred-deme monoecious metapopulation

In MarcoAndrello/MetaPopGen_0.0.8: Simulation of metapopulation genetics

Description

Datasets of survival, fecundity, mutation, dispersal and initial population size for a hundred-deme monoecious metapopulation.

Usage

data(HundredPop)

Format

This dataset contains the objects N1, sigma, phi_F, phi_M, mu, delta, kappa0 and T_max, as in the dataset FourPopMonoecious. The help page of the FourPopMonoecious dataset contains a detailed explanation for each object.

Details

The HundredPopMonoecious dataset has one locus with 2 alleles (therefore, 3 genotypes), 100 demes and 5 age-classes. Initial demes are composed of 1000 individuals per age class, all of the same genotype. Survival and fecundities do not differ among demes, years or genotypes, but change with age. Survival increases from 0.4 at age 1 to 0.6 at ages 3-5. Fecundity is zero from age 1 to age 3, is moderate at age 4 and is maximal at age 5.

Examples

data(HundredPopMonoecious)

# Shows the genotypic composition of demes
colours <- rainbow(3)
barplot(N1[,,1],xlab="Deme",ylab="Number of age-1 individuals",col=colours)
par(xpd=NA)
lg.txt <- c("A1A1", "A1A2", "A2A2")
legend(0.2,1200,lg.txt,fill=colours,ncol=3,bty="n")

# Run the simulation
N <- sim.metapopgen.monoecious(input.type="array",N1=N1, sigma=sigma, phi_F=phi_F, phi_M=phi_M, mu=mu, delta=delta, kappa0=kappa0, T_max=T_max)

# Shows the genotypic composition of demes at the end of the simulation
# Compare with that at the beginning!
colours <- rainbow(3)
barplot(N[,,1,dim(N)[4]],xlab="Deme",ylab="Number of age-1 individuals",col=colours)
lg.txt <- c("A1A1", "A1A2", "A2A2")
legend(0.2,1200,lg.txt,fill=colours,ncol=3,bty="n")

# Temporal evolution of fst. Pairwise comparison for deme 1 vs 2, 1 vs 50 and 1 vs 100
fst <- array(NA,dim=c(3,100))
vdeme <- c(2,50,100)
for (t in 1 : 100) {
for (i in 1 : 3){
deme <- vdeme[i]
fst[i,t] <- fst.pairwise.monoecious(N,1,deme,1,1,t,t)
}
}
plot(c(1:100),fst[1,],type="l",col="blue",xlab="Time",ylab="Pairwise Fst",ylim=c(0,0.4))
matplot(c(1:100),fst[2,],type="l",col="darkgreen",add=T)
matplot(c(1:100),fst[3,],type="l",col="red",add=T)
legend(30,0.4,c("Deme 1 - Deme 2","Deme 1 - Deme 50","Deme 1 - Deme 100"),col=c("blue","darkgreen","red"),lty=1)

MarcoAndrello/MetaPopGen_0.0.8 documentation built on May 25, 2019, 12:23 p.m.