analyzing binomial data with spatially correlated errors

Dear R users,

I want to explain binomial data by a serie of fixed effects. My problem is 
that my binomial data  are spatially correlated. Naively, I thought I could 
found something similar to gls to analyze such data. After some reading, I 
decided that lmer is probably to tool I need. The model I want to fit would 
look like

lmer ( cbind(n.success,n.failure) ~ (x1 + x2 + ... + xn)^2 , family=binomial, 
correlation=corExp(1,form=~longitude+latitude))

This doesn't work because lmer says it needs a random effect in the model. 
And, apart from the spatial random effect that I want to capture by computing 
the correlation matrix, I have no other random effect.

There must be something I do not understand here... I can't get why gls can do 
this on gaussian data but lmer can't on binomial ones.

Any help or thought on this would be welcome !

Jean-Baptiste Ferdy
Institut des Sciences de l'?volution de Montpellier
CNRS UMR 5554
Universit? Montpellier 2
34 095 Montpellier cedex 05
tel. +33 (0)4 67 14 42 27
fax ?+33 (0)4 67 14 36 22