#Biplot of the PCA on the environmental variables (scaling 2)
windows()
plot(env.pca)
windows()
plot(env.pca, scaling=2, type="none", # scaling 2 = correlation biplot : 
                                      # distances among abjects in the biplot DO NOT approximate their Euclidean distances
                                      # but angles among descriptor vectors reflect their correlation
     xlab = c("PC1 (%)", round((env.pca$CA$eig[1]/sum(env.pca$CA$eig))*100,2)),
     ylab = c("PC2 (%)", round((env.pca$CA$eig[2]/sum(env.pca$CA$eig))*100,2)),
     xlim = c(-1,1), ylim=c(-1,1))
points(scores(env.pca, display="sites", choices=c(1,2), scaling=2), 
       pch=21, col="black", bg="darkgreen", cex=1.2) 
text(scores(env.pca, display="species", choices=c(1), scaling=2),
     scores(env.pca, display="species", choices=c(2), scaling=2),
     labels=rownames(scores(env.pca, display="species", scaling=2)),
     col="red", cex=0.8)