expected.num.species: Expected Number of Species

In sprex: Calculate Species Richness and Extrapolation Metrics

Description

Calculate the expected number of species for a given sample size.

Usage

expected.num.species(m, f, f0.func, ...)

Arguments

m	number of samples.
f	a vector of species frequencies where f[i] is the number of species represented by only i samples.
f0.func	a function that computes the number of unobserved species (f0).
...	other arguments to f0.func.

Value

a vector or matrix (depending on whether m is a scalar or vector, respectively) of the estimated number of species (s.ind) seen in m samples, and the standard deviation (sd.s.ind).

Author(s)

Eric Archer [e-mail]

References

Eqns 4, 5, 9, and 10 in 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)
expected.num.species(60, f = f, f0.func = Chao1)

expected.num.species(c(60, 70, 75), f = f, f0.func = Chao1)

Example output

     s.ind   sd.s.ind          m      s.est         f0      s.obs          n 
 39.438316   3.844294  60.000000 463.311392 351.311392 112.000000 237.000000 
        s.ind sd.s.ind  m    s.est       f0 s.obs   n
[1,] 39.43832 3.844294 60 463.3114 351.3114   112 237
[2,] 44.52766 4.216620 70 463.3114 351.3114   112 237
[3,] 46.98870 4.393692 75 463.3114 351.3114   112 237

sprex documentation built on May 2, 2019, 9:42 a.m.