model {
# Priors
log(lambda) <- loglam
loglam ~ dunif(-10, 10)
p0 ~ dunif(-10, 10)
p1 ~ dunif(-10, 10)

for(k in 1:nG){
u[k] ~ dnorm(0, tau)
}
tau <- pow(sigma, -2)
sigma ~ dunif(0, 5)
# State equation
for (i in 1:R) {
N[i] ~ dpois(lambda)
# Loop over sites
# Observation equation
for (t in 1:T) {
# Loop over surveys
y[i,t] ~ dbin(p[i,t], N[i])
p[i,t] <- 1 / (1 + exp( -1 * (p0 + p1 * x[i] + u[gID[i,t]])))
}
}
# Derived quantities
totalN <- sum(N[])
# Population size over all R sites
logsigma <- log(sigma)
}