discovery.curve: Discovery Curve

Description

Calculate the components of a species discovery curve.

Usage

discovery.curve(f, f0.func, max.x = sum(f * 1:length(f)), n.pts = 100, ci = 0.95, ...)

Arguments

a vector of species frequencies where f[i] is the number of species represented by only i samples.

f0.func

function to use to calculate f0.

max.x

the maximum number of samples to calculate the curve for. Defaults to the sample size of f.

n.pts

number of points between 0 and max.x to estimate.

size of the confidence interval (0.5:1).

...

other arguments to f0.func.

Value

f.stats: a named vector from f0.func.
s.ind: a matrix of S.ind estimates for each value of m along with the standard deviation of S.ind.
s.ind.ci: a matrix of the upper and lower confidence intervals of S.ind.
ci.poly: a matrix of points describing the ci polygon.
rarefact.line: a matrix of points defining the rarefaction line (<= s.obs).<="" dd="">
extrap.line: a matrix of points defining the extrapolation line (> S.obs).

References

Colwell, R.K., A. Chao, N.J. Gotelli, S.-Y. Lin, C.X. Mao, R.L. Chazdon, and J.T. Longino. 2012. Models and estimators linking individual-based and sample-based rarefaction, extrapolation and comparison of assemblages. Journal of Plant Ecology 5(1):3-21.

Examples

Run this code

data(osa.old.growth)
f <- expand.freqs(osa.old.growth)
d <- discovery.curve(f, f0.func = Chao1, max.x = 1200)
plot(d)