Conditional CCA and Monte Carlo - Help!

Hi All,
I am using canonical correspondence analysis to compare a community
composition matrix to a matrix of sample spatial relationships and
environmental variables. In order to parse out how much variance is
explained purely by space (S/E) or the environment (E/S) I am using a
conditional (partial) CCA.  I want to test significance via Monte Carlo but
I can not find a way to do this with a conditional CCA.  I have been using
vegan for the CCA and attempting to use ade4 to run a Monte Carlo. However,
these two packages conflict when it comes to CCA.  If I use vegan I can run
a conditional CCA, and if I use ade4 I can do a Monte Carlo - but I can't
figure out how to do a conditional CCA with ade4 OR a Monte Carlo with
vegan.  If anyone has experience with this I would be truly grateful for
your help!  I am fairly new to R, and I have quickly found myself in a place
where "Google-ing" has no longer proven useful.  Below are my scripts and
error messages.

Using Vegan:

vare.cca <- cca(InvertR.csv ~ Space1 + Space2... + Condition(Env1) +
Condition(Env2)..., HabitatSpaceR.csv)
randtest(vare.cca, nrepet = 1000)

Error in randtest.cca(vare.cca, nrepet = 1000) : 
  Object of class dudi expected

Using ade4:

vare.cca <- cca(InvertR.csv ~ Space1 + Space2... + Condition(Env1) +
Condition(Env2)..., HabitatSpaceR.csv)

Error in cca(InvertR.csv ~ Space1 + Space2... + Condition(Env1) +
Condition(Env2)... +  : 
  data.frame expected





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