discovery.curve: Discovery Curve

In EricArcher/sprex: Species Richness and Extrapolation

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,
  plot = TRUE,
  ...
)

Arguments

f	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.
ci	size of the confidence interval (0.5:1).
plot	plot the curve?
...	other arguments to f0.func.

Value

a list with:

f.stats	a named vector from f0.func.
curve	a data.frame defining the rarefaction and extrapolation curves (specified in the section column), and columns providing the lower (lci) and upper (uci).

Author(s)

Eric Archer [e-mail]

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

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

print(str(d))

EricArcher/sprex documentation built on Sept. 4, 2023, 8:35 a.m.