I have too many environmental variables to use in a multiple regression analysis. If I use all the variables the models are just too complex. The use of the PCA axes in the regression analysis was impossible to interpret (since there wasn't a clear correlation with environmental variables), so we chose to select a limited number of variables, namely those that had the higher explanation in PCA.
A PCA was used for each set of environmental variables, namely the variables related with the structure of the stream, the evolving vegetation, the climatic, the physical-chemical characteristics of the water from summer period and from winter period, separately. The PCA was performed using the correlation matrix option, using the software PC-ORD, v. 4.21 (McCune & Mefford 1999). For each set of variables, only the variables with coordinates higher than 0.20, for the two first axes, of the PCA, were selected to be used in multiple regression analysis.
I could not find literature that confirms that it's OK to do this, but I think it is not wrong.