model_ss.jags

    model{
      # Priors
      N.est[1] ~ dunif(0.00001, 10)             # Prior for initial population density (max in dataset:6.6)
      mean.rmax ~ dunif(0.00001, 10)            # Prior for mean rmax
      K ~ dunif(0.00001, 100)                     # prior for carrying capacity
      sigma.proc ~ dunif(0.00001, 50)           # Prior for sd of state process
      sigma2.proc <- pow(sigma.proc, 2)         # Variance = sd^2
      tau.proc <- pow(sigma.proc, -2)           # Tau = sqrt(sd)
      sigma.obs ~ dunif(0.00001, 50)            # Prior for sd of observation process
      sigma2.obs <- pow(sigma.obs, 2)
      tau.obs <- pow(sigma.obs, -2)
      
      # Likelihood
      # State process
      for (t in 1:(T-1)){
      rmax[t] ~ dnorm(mean.rmax, tau.proc)T(0, 10)        # Truncated normal distribution to prevent values < 0
      rd[t] <- rmax[t]*(1-N.est[t]/K)
      N.est[t+1] <- N.est[t]+N.est[t]*rd[t]
      }
      # Observation process
      for (t in 1:T){
      y[t] ~ dnorm(N.est[t], tau.obs)
      }
    }