stoch.quasi.ext: Calculate quasi-extinction threshold

Description

Estimate the quasi-extinction probability by simulation for a structured population in an an independently and identically distributed stochastic environment

Usage

stoch.quasi.ext(matrices, n0, Nx, tmax = 50, maxruns = 10, nreps = 5000, 
                         prob = NULL, sumweight = NULL, verbose=TRUE)

Arguments

matrices

a list with two or more projection matrices, or a matrix with one projection matrix per column, with elements filled by columns

initial population vector

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.

Value

A matrix with quasi-extinction probabilities for each run by columns

References

Morris, W. F., and D. F. Doak. 2002. Quantitative conservation biology: Theory and practice of population viability analysis. Sinauer, Sunderland, Massachusetts, USA.

Examples

Run this code

# NOT RUN {
data(hudsonia)
n <- c(4264, 3,30,16,25,5)
names(n)<-c("seed",  "seedlings", "tiny", "small", "medium" , "large")
## exclude seeds using sumweight.  Using 100 nreps for speed
x <- stoch.quasi.ext(hudsonia, n, Nx=10, nreps=100, 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")
# }