## Code adapted from Robin Wyatt

model{


##------ SAMPLING MODEL -----------------------
  ##  Population size at surveyed sites

 ## FIRST TRY ------------

## If I try to do this below, BUGS  is unable to set the initial values.

#  for(i in 1:num.survey.sites)
#    {
#      sden[i] <-  d[sample.siteids[i]]
#      x.n[i] <- sden[i] * lengths[sample.siteids[i]] * widths[sample.siteids[i]]
#       n[i, 1] ~ dpois(x.n[i])
#
#     for(j in 1:num.survey.site.removals[i] )
#         {
#         n[i, j + 1] <- n[i, j] - catches.at.survey.site[i, j]
#           catches.at.survey.site[i, j] ~ dbin(p[i], n[i, j])
#         }
#    }


 ## SECOND TRY ------------

 ## If I try to do this below, BUGS complains saying that I have used
 ## an undefined node "nn"

  for(i in 1:num.survey.sites)
    {
      x.n[i] <- d[sample.siteids[i]] * lengths[sample.siteids[i]] * widths[sample.siteids[i]]

      n[i] ~ dpois(x.n[i])
    }

 ##  After first re-seining
  for(i in 1:num.survey.sites)
    {
      nn[i,2] <- n[i] - catches.at.survey.site[i, 2]
      catches.at.survey.site[i, 2] ~ dbin(p[i], n[i])
    }

  ##  After all subsequent re-seinings
  for(i in 1:num.survey.sites)
    {
     for(j in 3:num.survey.site.removals[i] )
      {
        nn[i,j+1] <- nn[i,j] - catches.at.survey.site[i, j]
       catches.at.survey.site[i, j] ~ dbin(p[i], nn[i, j])
      }
    }





  ##------ DENSITY MODEL ------------------------
  ##  Expected densities and pop sizes at all sites.

  for(s in 1:total.sites)
    {
       u[s] <- mu.d
       logden[s] ~ dnorm(u[s], tau.d)
       log(d[s]) <- logden[s]

      x.ipop[s] <-  d[s] *  lengths[s] * widths[s]
      ipop[s] ~ dpois(x.ipop[s])
    }

  ##  Hyperpriors for density

  mu.d ~ dnorm(0,1.0E-6)
  tau.d ~ dgamma(1.0E-3, 1.0E-3)
  sigma.d <- pow(tau.d, -0.5)



##-------CAPTURE PROBABILITY MODEL -----------------------

  ## Expected capture probability
  for(i in 1:num.survey.sites )
    {
      z[i] <- mu.p
      p.prime[i] ~ dnorm(z[i], tau.p)I(-3,3)
      logit(p[i]) <- p.prime[i]
    }

  ##  Hyperpriors for capture probability

  mu.p ~ dnorm(0,1.0E-6)
  tau.p ~ dgamma(1.0E-3, 1.0E-3)

  sigma.p <- pow(tau.p, -0.5)



## -------  OVERALL SUMMARIES


  ##  Reach and river totals
  for(r in 1:num.reaches)
    {
      for (t in 1:total.sites)
        {
          temppop[r, t] <- equals(r, reachid[t]) * ipop[t]
        }
      rpop[r] <- sum(temppop[r, ])
    }

  tpop <- sum(rpop[])


  ##  Stream order totals
  for(i in 1:numorders)
    {
      for (t in 1:total.sites)
        {
          temp[i, t] <- equals(i, orders[t]) * ipop[t]
        }
      opop[i] <- sum(temp[i, ])
    }
}



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