str(mite.env)
(mite.subs=mite.env[,c(1,2,3)]) #Premier jeu de données 
(mite.other=mite.env[,c(4,5)]) #Deuxième jeu de données 
 
#RDA sur mite.subs
rda.mite.subs <- rda(mite.spe.hel~., data=mite.subs)
R2a.all.chem <- RsquareAdj(rda.mite.subs)$adj.r.squared
 
#Sélection progressive pour mite.subs
ordiR2step(rda(mite.spe.hel~1, data=mite.subs), 
           scope= formula(rda.mite.subs), direction= "forward", R2scope=TRUE, pstep=1000)
names(mite.subs)
(mite.subs.pars <- mite.subs[, c(2, 3)])
 
#RDA sur mite.other
rda.mite.other <- rda(mite.spe.hel~., data=mite.other)
R2a.all.chem <- RsquareAdj(rda.mite.other)$adj.r.squared
 
#Sélection progressive sur mite.other
ordiR2step(rda(mite.spe.hel~1, data=mite.other), 
           scope= formula(rda.mite.other), direction= "forward", R2scope=TRUE, pstep=1000)
names(mite.other)
(mite.other.pars <- mite.other[, c(1,2)])
 
#Partitionnement de la variation
(mite.spe.part <- varpart(mite.spe.hel, ~WatrCont+Substrate, ~Shrub+Topo,
                          data=mite.env))
windows(title="Variation partitioning - parsimonious subsets")
plot(mite.spe.part, digits=2)
 
# Test de significativité des fractions
anova.cca(rda(mite.spe.hel~ WatrCont+Substrate, data=mite.env), step=1000) # Test of fractions [a+b]
anova.cca(rda(mite.spe.hel~Shrub+Topo, data=mite.env), step=1000) # Test of fractions [b+c]
(env.pars <- cbind(mite.env[,c(2,3,4,5)])) 
anova.cca(rda(mite.spe.hel~ WatrCont+Substrate+Shrub+Topo, data=env.pars), step=1000) # Test of fractions [a+b+c]
anova.cca(rda(mite.spe.hel~WatrCont+Substrate + Condition(Shrub+Topo), data=env.pars), step=1000) # Test of fraction [a]
anova.cca(rda(mite.spe.hel~Shrub+Topo+ Condition(WatrCont+Substrate ), data=env.pars), step=1000) # Test of fraction [c]