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popbio (version 1.0.1)

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)

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.

Value

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

source

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

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

Run this code
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))

plot(x[,1], xlab="Years", ylab="Quasi-extinction probability",
type="n", ylim=c(0,max(x)), 
main=paste("Time to reach a quasi-extinction threshold 
of 10 above-ground individuals"))
for(i in 1:dim(x)[2])
  {
    lines(x[,i], col=rainbow(dim(x)[2])[i])
  }

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