gam variable selection

Dear list,

I am studying the influence of several environmental factors (numeric &
dummies) on species densities (= numeric) using the gam()
function with a gaussian link function in the mgcv package. As stated in 
Wood (2006) there is no variable selection algorithm.

Is it an appropriate (iterative) approach to drop the predictor being
least significant (eg. p > 0.05), refit the model, compare the GCV/AIC
score and so forth. Should I first focus on the smoothing functions or 
fixed effects? Or is such a distinction not important at all?

Perhaps someone has more experience with GAMs and can give me a helping
hand? Thanks in advance!

Best
Marco

Marco Helbich
Department of Geography
University of Heidelberg