model
{
	Tau.noninformative <- 1.0E-2
	P.gamma <- 1.0E-2
	for (i in 1:N.site) {
		Y[i] ~ dpois(mean[i])
		log(mean[i]) <- beta + re[i]
	}
	re[1:N.site] ~ car.normal(Adj[], Weights[], Num[], tau)
	beta ~ dnorm(0, Tau.noninformative)
	tau ~ dgamma(P.gamma, P.gamma)
}