popbio (version 2.4.4)

countCDFxt: Count-based extinction probabilities and bootstrap confidence intervals

Description

This function takes parameters derived from population counts and calculates the probability of extinction with bootstrap confidence intervals for a density-independent model, using a diffusion approximation.

Usage

countCDFxt(mu, sig2, nt, Nc, Ne, tq=nt, tmax=50, Nboot=500, plot=TRUE)

Arguments

mu

estimated value of mean mu

sig2

estimated value of sample variance

nt

number of transitions in the data set

Nc

current population size

Ne

quasi-extinction threshold

tq

length of the census (in years), default is number of transitions

tmax

latest time to calculate extinction probability, default 50

Nboot

number of bootstrap samples for calculating confidence intervals for extinction probabilities, default 500)

plot

draw extinction time CDF plot with log-scale on y-axis

Value

The function plots the cumulative probabilities of quasi-extinction through time with 95% confidence intervals. It also returns a data frame with the extinction time CDF for the best parameter estimates (Gbest), and the lower and upper bootstrap confidence limits for extinction probabilites (Glo, Gup).

References

Dennis et al. 1991, Ecological Monographs 61: 115-143.

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

See Also

extCDF

Examples

# NOT RUN {
## plot like Figure 3.8 in Morris and Doak (2002).
data(grizzly)
logN<-log(grizzly$N[-1]/grizzly$N[-39])
countCDFxt(mu=mean(logN), sig2=var(logN), nt=38, tq=38, Nc=99, Ne=20)
# }