#RDA des variables physico-chimiques
spe.chem <- rda(spe.hel~., data=envchem)
 
#Sélection des variables significatives
R2a.all.chem <- RsquareAdj(spe.chem)$adj.r.squared
ordiR2step(rda(spe.hel~1, data=envchem), 
           scope= formula(spe.chem), direction= "forward", R2scope=TRUE, pstep=1000)
names(envchem)
(envchem.pars <- envchem[, c( 4, 6, 7 )])
 
#RDA avec les autres variables significatives
spe.topo <- rda(spe.hel~., data=envtopo)
R2a.all.topo <- RsquareAdj(spe.topo)$adj.r.squared
ordiR2step(rda(spe.hel~1, data=envtopo), 
           scope= formula(spe.topo), direction= "forward", R2scope=TRUE, pstep=1000)
names(envtopo)
envtopo.pars <- envtopo[, c(1,2)]
 
#Varpart
spe.part <- varpart(spe.hel, envchem.pars, envtopo.pars)
windows(title="Variation partitioning - parsimonious subsets")
plot(spe.part, digits=2)
 
#Tests de significativité des fractions
anova.cca(rda(spe.hel, envchem.pars), step=1000) # Test of fractions [a+b]
anova.cca(rda(spe.hel, envtopo.pars), step=1000) # Test of fractions [b+c]
env.pars <- cbind(envchem.pars, envtopo.pars) 
anova.cca(rda(spe.hel, env.pars), step=1000) # Test of fractions [a+b+c]
anova.cca(rda(spe.hel, envchem.pars, envtopo.pars), step=1000) # Test of fraction [a]
anova.cca(rda(spe.hel, envtopo.pars, envchem.pars), step=1000) # Test of fraction [c]