stoch.quasi.ext {popbio} | R Documentation |
Estimate the quasi-extinction probability by simulation for a structured population in an an independently and identically distributed stochastic environment
stoch.quasi.ext(matrices, n0, Nx, tmax = 50, maxruns = 10, nreps = 5000, prob = NULL, sumweight = NULL, verbose=TRUE)
matrices |
a list with two or more projection
matrices, or a matrix with one projection matrix per column,
with elements filled by columns |
n0 |
initial population vector |
Nx |
quasi-extinction threshold |
tmax |
number of time steps or projection intervals |
maxruns |
number of times to simulate cumulative distribution function |
nreps |
number of iterations. |
prob |
a vector of probability weights used by
sample for selecting the projection matrices. |
sumweight |
A vector of ones and zeros used to omit stage classes when checking quasi-extinction threshold. Default is to sum across all stage classes. |
verbose |
Print comment at start of run 1,2,3,etc. |
A matrix with quasi-extinction probabilities for each run by columns
Chris Stubben
converted Matlab code from Box 7.5 in Morris and Doak (2002)
Morris, W. F., and D. F. Doak. 2002. Quantitative conservation biology: Theory and practice of population viability analysis. Sinauer, Sunderland, Massachusetts, USA.
data(hudsonia) n<-c(4264, 3,30,16,25,5) names(n)<-c("seed", "seedlings", "tiny", "small", "medium" , "large") ## exclude seeds using sumweight x<-stoch.quasi.ext(hudsonia, n, Nx=10, nreps=500, sumweight=c(0,1,1,1,1,1)) matplot(x, xlab="Years", ylab="Quasi-extinction probability", type='l', lty=1, col=rainbow(10), las=1, main="Time to reach a quasi-extinction threshold of 10 above-ground individuals")