model
{
	Tau.noninformative <- 1.0E-4
	P.gamma <- 1.0E-4
	for (i in 1:N.sample) {
		Survival[i] ~ dbin(p[i], Number[i])
		logit(p[i]) <- (
			flat
			+ flatGTLS[GTLS[i]]
			+ S1[i] * (bc[1] + bs[1, Species[i]])
			+ W1[i] * (bc[2] + bs[2, Species[i]])
			+ Edge[i] * (
				bc[3] + bs[3, Species[i]]
				+ S1[i] * (bc[4] + bs[4, Species[i]])
				+ W1[i] * (bc[5] + bs[5, Species[i]])
			)
		)
	}
	for (k in 1:N.b) {
		bc[k] ~ dnorm(0, Tau.noninformative) # non-informative
		for (s in 1:N.species) {
			bs[k, s] ~ dnorm(0, tau.bs[k])
		}
		tau.bs[k] ~ dgamma(P.gamma, P.gamma)
	}
	flat ~ dnorm(0, Tau.noninformative) # non-informative
	for (k in 1:N.GTLS) {
		flatGTLS[k] ~ dnorm(0, tau)
	}
	tau ~ dgamma(P.gamma, P.gamma)
}