stoch.quasi.ext: Quasi-extinction threshold
In popbio: Construction and Analysis of Matrix Population Models

Description Usage Arguments Details Value Author(s) References See Also Examples

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

1 2	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.

converted Matlab code from Box 7.5 in Morris and Doak (2002)

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

Chris Stubben

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

stoch.projection

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")