decostand {vegan}R Documentation

Standardization Methods for Community Ecology

Description

The function provides some popular (and effective) standardization methods for community ecologists.

Usage

decostand(x, method, MARGIN, range.global, logbase = 2, na.rm=FALSE, ...)

wisconsin(x)

Arguments

x Community data, a matrix-like object.
method Standardization method. See Details for available options.
MARGIN Margin, if default is not acceptable. 1 = rows, and 2 = columns of x.
range.global Matrix from which the range is found in method = "range". This allows using same ranges across subsets of data. The dimensions of MARGIN must match with x.
logbase The logarithm base used in method = "log".
na.rm Ignore missing values in row or column standardizations.
... Other arguments to the function (ignored).

Details

The function offers following standardization methods for community data:

Standardization, as contrasted to transformation, means that the entries are transformed relative to other entries.

All methods have a default margin. MARGIN=1 means rows (sites in a normal data set) and MARGIN=2 means columns (species in a normal data set).

Command wisconsin is a shortcut to common Wisconsin double standardization where species (MARGIN=2) are first standardized by maxima (max) and then sites (MARGIN=1) by site totals (tot).

Most standardization methods will give nonsense results with negative data entries that normally should not occur in the community data. If there are empty sites or species (or constant with method = "range"), many standardization will change these into NaN.

Value

Returns the standardized data frame, and adds an attribute "decostand" giving the name of applied standardization "method".

Note

Common transformations can be made with standard R functions.

Author(s)

Jari Oksanen and Etienne Laliberté (method = "log").

References

Anderson, M.J., Ellingsen, K.E. & McArdle, B.H. (2006) Multivariate dispersion as a measure of beta diversity. Ecology Letters 9, 683-693.

Legendre, P. & Gallagher, E.D. (2001) Ecologically meaningful transformations for ordination of species data. Oecologia 129; 271–280.

Oksanen, J. (1983) Ordination of boreal heath-like vegetation with principal component analysis, correspondence analysis and multidimensional scaling. Vegetatio 52; 181–189.

Examples

data(varespec)
sptrans <- decostand(varespec, "max")
apply(sptrans, 2, max)
sptrans <- wisconsin(varespec)

## Chi-square: PCA similar but not identical to CA.
## Use wcmdscale for weighted analysis and identical results.
sptrans <- decostand(varespec, "chi.square")
plot(procrustes(rda(sptrans), cca(varespec)))

[Package vegan version 1.16-32 Index]