I'm trying to understand the regression analysis done in a published study.
They use GAM models to predict plant growth, and to test for the most important predictors. They have measured growth of individual plants at 20 different sites, and also have several environmental measures (e.g. temperature, precipitation, soil characteristics) which seem to be measured at the site level.
They say that the environmental variables are included as fixed effects predictors, and site is included as a random effect. I'm confused as surely within a site, all the plant growth measurements have identical environmental measurements associated with them (as these seem to be measured at the site level) - what does this leave to test?
Am I misunderstanding fixed/random effects, or is the methodology poorly explained? Is it still possible to test which of the fixed effects is the strongest predictor if site is included as a random effect?