forward selection RDA after controlling for constraints

Hello all,

I would like to run this by everyone and maybe get some hints as to what R functions I could use for this.  Ok, so I have macroinvertebrate assemblage data from across the SE.  I would like to control for geographic distance (lat/long), Watershed area, and year before submitting these data to an RDA with the rest of the environmental data using a variable selection technique.

Does it make sense to detrend the data using a mlm on hellinger transfomed abundances with the above env variables as regressors and then submit the residuals to rda with the rest of the env variables I am interested in?

Stephen,

If you happen to use vegan functions for forward selection, please note that they all (should) take a scope argument that can (should) be a list of lower and upper scopes. Put your controlled variables (distance???, watershed area, year) in the lower scope and these plus other candidate variables in the upper scope, and there you go. I have used "should", because I have rarely used these functions myself, and I'm not sure if lower scope really is implemented in all, but is *should* be: file a bug report if this fails. 

I have no idea how to have distance RDA. Well, I have ideas, but none that I have are very good.

Using separate mlm and modelling residuals will not work quite correctly, because that ignores correlations between groups of variables. Vegan functions do not ignore those.

Cheers, Jari Oksanen

Jari Oksanen, Dept Biology, Univ Oulu, 90014 Finland
jari.oksanen at oulu.fi, Ph. +358 400 408593, http://cc.oulu.fi/~jarioksa