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

Arguments

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

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.

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

Run this code

# NOT RUN {
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)
# }

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