Rarefaction estimator of species richness

rarefact {sub.sample}

Usage

rarefact(x, ESn = c(25, 50, 100, 150, 200, 250), num.reps = 100, subset = NULL)

Arguments

`x`	a data frame with samples in columns and taxa in rows
`ESn`	a vector of numbers of individuals for which species richness will be calculated
`num.reps`	number of randomizations: see details
`subset`	a vector of (contiguous) row numbers to permit estimate of the number of species of a subset of all species for a specified count of individuals

Details

This function estimates species richness for specified counts of individuals for a matrix of species counts. It also will estimate the richness of a subset of all species. It is useful for rapid calculation of multiple rarefaction curves. It calculates expected species richness by randomly selecting ESn individuals from each sample, and counting the number of taxa. This randomization is conducted num.reps times from which the mean and variance of expected species richness ES is calculated.

Value

`ES`	a data frame of listing mean of ES and variance of ES for each count ESn in each sample
`ES`	as above
`ES.subset`	a dataframe of the same structure as ES, but for the subset of species

Author(s)

Chris Walsh: Chris.Walsh@sci.monash.edu.au.

References

Marchant, R. (1989) A subsampler for samples of benthic invertebrates. Bulletin of the Australian Society for Limnology 12, 49-52.

Examples

#calculate rarefaction curves for a set of macroinvertebrate #counts from 3 samples: calculating both total species richness #and species richness of mayflies and caddisflies (QE and QT) urban <- read.table("urban.txt", header=TRUE) urban <- data.frame(urban[,2:24],row.names = urban[,1]) urban.ES <- rarefact(urban[3:5], subset = c(145:154)) urban.ES

Urban Water Ecology