rich: Species richness, their confidence interval and other useful indices

Description

Computes the cumulative and average species richness over a set of samples, the associated bootstrap statistics and other useful indices.

Usage

rich(matrix, verbose = FALSE, nrandom = NULL)

Arguments

matrix

matrix is a typical species-sample matrix. Rows correspond to samples whereas columns stand for species.

verbose

If verbose=FALSE, a simplied output is returned.

nrandom

Number or randomizations if bootstrap estimations are required. Non-null values < 10 are set to 99.

Value

crCumulated richness over sampling units.
mrMean richness over sampling units.
mrsdStandard deviation of the mean richness.
singletonsSpecies with at most one observation.
doubletonsSpecies with at most two observations.
uniquesSpecies encountered in only one sample.
duplicatesSpecies encountered in only two samples.
bootCRA data frame showing the outputs of the bootstrap analyses of the cumulative richness (computed if nrandom != FALSE): cr.obs Observed cumulative richness, equal to cr above. cr.bootMean of the bootstrap values. cr.bcorrMean of the bootstrap values corrected for the bias estimated below. cr.biasBias. cr.seStandard error of the cumulative richness estimated by bootstrap. This is estimated as the standard deviation of the bootstrap values. cr.lbnLower bound of the first order normal approximation confidence interval (see boot.ci {boot}). cr.ubnUpper bound of the first order normal approximation confidence interval (see boot.ci {boot}).
bootMRA data frame showing the outputs of the bootstrap analyses of the mean richness (computed if nrandom != FALSE): mr.obs Observed mean richness, equal to mr above. mr.bootMean of the bootstrap values. mr.bcorrMean of the bootstrap values corrected for the bias estimated below. mr.biasBias. mr.seStandard error of the mean richness estimated by bootstrap. This is estimated as the standard deviation of the bootstrap values. mr.lbnLower bound of the first order normal approximation confidence interval (see boot.ci {boot}). mr.ubnUpper bound of the first order normal approximation confidence interval (see boot.ci {boot}).
nrandomNumber of randomizations used in the bootstrap.
richvecA vector containing the observed richness in each sample or populations. The mean of richvec corresponds to mr (available if verbose == TRUE).
matrixThe data set passed to rich as the matrix argument (available if verbose == TRUE).
matrixbinBinary (presence/absence) transformation of the data set passed to rich as the matrix argument (available if verbose == TRUE).
sumrowA vector of the sum of species for each sample (available if verbose == TRUE).
sumcolA vector of the sum of sample for each species (available if verbose == TRUE).
zeroesNumber of zeroes in the data set (available if verbose == TRUE).

Details

rich computes basic descriptive statistics from typical species by sample data sets.

References

Manly, B.F.J. (1997). Randomization and Monte Carlo methods in biology. Chapman & Hall.

Examples

Run this code

data(ef)
# No bootstrap statistics
rich(matrix=ef)
# Bootstrap estimation based on 499 randomizations
rich(matrix=ef, nrandom=499)

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