Dear all,
Thanks for the very useful replies. Standardizing explanatory variables
doesn't look like necessary as vegan copes well with non-centred constraints
in original scale (Jari dixit). My response variables are not species
abundances but indices describing the interaction structure of a community.
They are not quite normal, but using Box-Cox transformation here might
affect the results (Nicholas dixit). My response variables are measured in
very different scales though so they need to be standardised if all
variables are to have the same weight in the ordination (Gavin dixit).
I'll run rda in vegan with untransformed explanatory variables and
standardised response variables and see how it goes. Regarding the
non-normality of my response variables, Nicholas suggested (if I understood
correctly) to look for an alternative ordination method that assumes truly
Gaussian (or other distributions) along the principal axis. This would imply
breaking up the analysis (instead of using vegan) and doing it step by step
with ordination and regression functions, but it looks like too complicated
for my poor R (and by the way stats) skills. If you people think this might
would I'll give it a try.

A related question by the way, is it possible in vegan to perform a forward
selection of variables in the context of a redundancy analysis just like
Canoco does?

Thanks again for all the useful and kind replies both on and off the list.

Best wishes,

Mariano

--------------------------

Mariano Devoto
School of Biological Sciences
University of Bristol
Woodland Road


Bristol, UK
BS8 1UG
Tel. +44 (0) 1179545960 (internal 45960)
web: http://agro.uba.ar/~mdevoto <http://agro.uba.ar/%7Emdevoto>

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