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Variation Partitioning - RDA predicted values from spatial component with absence/presence matrix

amommendes 
Dear list members,

I extracted a matrix of predicted values by the pure spatial model (fraction
C in the variation partitioning approach with environmental and spatial
variables [i.e.,Y ~ environmental + spatial]) from a matrix of species
presence/absence as the following example:

require (vegan)
data(mite)
data(mite.env)
data(mite.pcnm)
mite[mite>0]<-1 # abundance matrix to presence/absence matrix

mod <- rda(mite ~ ., data=cbind(mite.pcnm,mite.env))
modEnv<- rda (mite~.,mite.env)
predFull<- predict(mod)
predEnv<-predict (modEnv)
predSpace<- predFull-predEnv # predicted values (species "occurrence"?) 

I would like to know if it would be correct (or even if make sense)
interpret this matrix of predicted values as predicted species "occurrences"
by pure spatial model.

Thanks in advance,

Amom



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