ade4: wca.rlq – R documentation

Become an expert in R — Interactive courses, Cheat Sheets, certificates and more!

wca.rlq

Within-Class RLQ analysis

Description

Performs a particular RLQ analysis where a partition of sites (rows of R) is taken into account. The within-class RLQ analysis search for linear combinations of traits and environmental variables of maximal covariance.

Usage

## S3 method for class 'rlq'
wca(x, fac, scannf = TRUE, nf = 2, ...)
## S3 method for class 'witrlq'
plot(x, xax = 1, yax = 2, ...)
## S3 method for class 'witrlq'
print(x, ...)

Arguments

`x`	an object of class rlq (created by the `rlq` function) for the `wca.rlq` function. An object of class `witrlq` for the `print` and `plot` functions
`fac`	a factor partitioning the rows of R
`scannf`	a logical value indicating whether the eigenvalues bar plot should be displayed
`nf`	if scannf FALSE, an integer indicating the number of kept axes
`xax`	the column number for the x-axis
`yax`	the column number for the y-axis
`...`	further arguments passed to or from other methods

Value

The wca.rlq function returns an object of class 'betrlq' (sub-class of 'dudi'). See the outputs of the print function for more details.

Author(s)

Stéphane Dray stephane.dray@univ-lyon1.fr

References

Wesuls, D., Oldeland, J. and Dray, S. (2012) Disentangling plant trait responses to livestock grazing from spatio-temporal variation: the partial RLQ approach. Journal of Vegetation Science, 23, 98–113.

Examples

data(piosphere)
afcL <- dudi.coa(log(piosphere$veg + 1), scannf = FALSE)
acpR <- dudi.pca(piosphere$env, scannf = FALSE, row.w = afcL$lw)
acpQ <- dudi.hillsmith(piosphere$traits, scannf = FALSE, row.w = afcL$cw)
rlq1 <- rlq(acpR, afcL, acpQ, scannf = FALSE)

wrlq1 <- wca(rlq1, fac = piosphere$habitat, scannf = FALSE)
wrlq1
plot(wrlq1)

ade4

Analysis of Ecological Data: Exploratory and Euclidean Methods in Environmental Sciences

v1.7-16

GPL (>= 2)

Authors

Stéphane Dray <stephane.dray@univ-lyon1.fr>, Anne-Béatrice Dufour <anne-beatrice.dufour@univ-lyon1.fr>, and Jean Thioulouse <jean.thioulouse@univ-lyon1.fr>, with contributions from Thibaut Jombart, Sandrine Pavoine, Jean R. Lobry, Sébastien Ollier, Daniel Borcard, Pierre Legendre, Stéphanie Bougeard and Aurélie Siberchicot. Based on earlier work by Daniel Chessel.

Initial release