model {

	# likelihood
	for (i in 1:n) {
		y[i] ~ dpois(lambda[i])
		log(lambda[i]) <- alpha + beta1*elev[i] + beta2*elev2[i] + W[i]
		muW[i] <- 0
    }

	# Spatial exponential
	W[1:n] ~ spatial.exp(muW[], xcoord[], ycoord[], tauSp, phi, 1)

	# Priors for the fixed effects
	alpha ~ dnorm(0, 0.01)
	beta1 ~ dnorm(0, 0.04)
	beta2 ~ dnorm(0, 0.04)

  # Priors for the spatial random effect
	tauSp <- pow(sdSp, -2)
	sdSp ~ dt(0,1,2)I(0,)  #dunif(0, 5) #
	phi ~  dunif(0.01, 5)#dt(0,1,1)I(0,) 

}