Population Biology Week 3

gistfile1.txt

#####################################################
#lambda varies over time
#####################################################

low <- as.data.frame(matrix(ncol=100, nrow=100))

high <- as.data.frame(matrix(ncol=100, nrow=100))

t <- seq(2,101, by=1)
N0 <- 50
high[1,] <- N0
low[1,] <- N0

lamda<-matrix(data=rnorm(n=10000, mean=1.05,sd=.3),nrow=100,ncol=100)
for(i in 1:99){
 high[(i+1),]<-high[i,]*lamda[i,]
}

lamda<-matrix(data=rnorm(n=10000, mean=1.05,sd=.3),nrow=100,ncol=100)
for(i in 1:99){
 low[(i+1),]<-low[i,]*lamda[i,]
}



low$mean <- rowMeans(low)
high$mean <- rowMeans(high)

#generate the arith mean
lambda <- rep(1.05,100)
t <- seq(1,100,by=1)
arith <- N0*(lambda^t)

par(mfcol=c(3,1))

#plot low 
plot(low[,1] ,  type="l")
for(i in 2:10){
  lines(low[,i], type="l")
}

#plot high 
plot(high[,1],type="l")
for(i in 2:10){
  lines(high[,i], type="l")
}

# plot means
plot(arith, col="red", type="l", lwd=3)
lines(high$mean,  col="orange",lwd=3)
lines(low$mean,  col="green", lwd=3)