data("mite") # Load mite species abundance data
data("mite.env") # Load envdata
# Hellinger transform the community data
mite.spe.hel <- decostand(mite, method = "hellinger")
mite.env <- mite.env[,1:2]
mite.env$SoilCont <- rnorm(70,5,2)
mite.env$SubsDens <- decostand(mite.env$SubsDens, method = "standardize")
mite.env$WatrCont <- decostand(mite.env$WatrCont, method = "standardize")
mite.env$SoilCont <- decostand(mite.env$SoilCont, method = "standardize")
mite.rda <- rda(mite.spe.hel ~ WatrCont + SubsDens + SoilCont, data = mite.env)
I want to compute variable contribution to each of the principal axis in the RDA. I found a similar computation using the factoextra enter link description here package. This computes for PCA like this. How can I do this for the RDA analysis like above?
# Contributions of variables to RDA1
fviz_contrib(mite.rda, choice = "var", axes = 1, top = 10)
# Contributions of variables to RDA2
fviz_contrib(mite.rda, choice = "var", axes = 2, top = 10)
Error in .get_facto_class(X) : An object of class : rdacca can't be handled by factoextra
