[R-sig-eco] Interpretation of RDA triplot where x axis is RDA vector and y axis is PCA vector

[Marko Djurakic]

Dear r-sig-ecology community,

I appreciate if someone can tell me is it meaningful to interpret 
redundancy analysis (RDA) and triplot of RDA where x axis represent RDA 
vector and y axis is PCA vector?

For instance, I performed RDA in vegan where response matrix was 
Hellinger-transformed absolute abundance of several types of chromosomal 
inversions and explanatory matrix consisted of 19 bioclim variables. 
With a full set of bioclim variables model was overfitted and I reduced 
number of explanatory variables using VIF and afterwards (if necessary) 
performed forward selection. In the final model, there was only one 
explanatory variable in the model, thus there is one RDA axis, and 
several PCA axes (unconstrained residual variance). Therefore RDA 
triplot shows RDA vector as x axis and PCA vector on the y axis. Is is 
meaningful to interpret such RDA and its graph?

Kind regards,

Marko