[R-sig-ME] glmer, split-plot design simple question

[chico3 at sapo.pt]

Dear experts,

I have a question concerning the implementation of a mixed model in my  
specific experiment. I have search the archives and found no answer to  
my problem.

I have four luminaires randomly distributed. Two luminaires have light  
on and two luminaires have no light. Below the luminaires I have two  
treatments. Each treatment as four replicates that were randomly  
distributed below the luminaires. Moreover, I have made all the  
possible combinations of presence absence of light and treatments.

I want to check if there is a effect of each treatment and the  
interactions between all the combinations.The response variable is a  
proportion (number of specific specie/total number of species)

Treatment1<-as.factor(“Yes”,”No”)
Treatment2<- as.factor(“Yes”,”No”)
Light<- as.factor(“Yes”,”No”)
Response<-cbind(number_of_specific_species, total_species)

I have made this model,

  model<-glmer(Response ~ Treatmen1*Treatment2 + (1|Light), family=binomial)

However this doesn´t allow to see the effect of light or the  
interaction between light and treatments. Moreover, I don´t know how  
to include overdispersion, since glmer doesn´t allow quasi families  
such as glm.

I know this is a simple question, but I greatly would appreciate some  
clues on how to proceed.