stoch.quasi.ext: Quasi-extinction threshold

In popbio: Construction and Analysis of Matrix Population Models

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
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.

Details

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

Value

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

Author(s)

Chris Stubben

References

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

See Also

stoch.projection

Examples

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, las=1,
 main="Time to reach a quasi-extinction threshold
of 10 above-ground individuals")

popbio documentation built on May 29, 2024, 4:35 a.m.