Model 1

model {

	for (i in 1:N) {
		lns[i] ~ dnorm(mu[i], tau[group[i]])
		mu[i] <- alpha[group[i],1] + alpha[group[i],2] * mtetemp[i]
	}
	
	
	for (i in 1:Ngroups) {
		alpha[i, 1:2] ~ dmnorm(beta[1:2],taubeta[1:2,1:2])
		tau[i] ~ dgamma(0.001, 0.001)
		sigma[i] <- pow(tau[i], -0.5)
	}

	taubeta[1:2,1:2] ~ dwish(Q[1:2,1:2],2)
	for (j in 1:2) {
      beta[j] ~ dnorm(0, 0.001)
      }
	for (i in 1:2) {
      for(j in 1:2) {
      Q[i,j] <- equals(i,j)
      }
      }
}


Model 2

model {

	for (i in 1:N) {
		lns[i] ~ dnorm(mu[i], tau[group[i]])
		mu[i] <- alpha[group[i],1] + alpha[group[i],2] * temp[i]
	}

	
	for (i in 1:Ngroups) {
		alpha[i, 1:2] ~ dmnorm(beta[1:2], taubeta[1:2,1:2])
      tau[j] ~ dgamma(0.001, 0.001)
      sigma[j] <- pow(tau[j], -0.5)
	}

      for (i in 1:N) {		
      temp[i] ~ dnorm(mtetemp[i], tautemp) 
      }

	taubeta[1:2,1:2] ~ dwish(Q[1:2,1:2],2)
	for (j in 1:2) {
      beta[j] ~ dnorm(0, 0.001)
      }
	for (i in 1:2) {
      for(j in 1:2) { 
      Q[i,j] <- equals(i,j)
      }
      }
	sigmatemp ~ dnorm(0, 0.5) I(0,)
	tautemp <- pow(sigmatemp, -2)
}


Model 3

model {

	for (i in 1:N) {
		lns[i] ~ dnorm(mu[i], tau[group[i]])
		mu[i] <- alpha[group[i],1] + alpha[group[i],2] * mtetemp[i]
	}
	
	for (j in 1:Ngroups) {
		tau[j] ~ dgamma(0.001, 0.001)
		sigma[j] <- pow(tau[j], -0.5)
		alpha[j, 1:2] ~ dmnorm(beta[j, 1:2],taubeta[1:2,1:2])
		for (k in 1:2) {
			beta[j, k] <- gamma[1, k]  + gamma[2,k]*log(latmean[j]) + 
      gamma[3, k]*log(latrange[j])
		}
	}
	
	for (j in 1:3) {
      for(k in 1:2) {
      gamma[j,k] ~ dnorm(0, 0.001)
      }
      }
	
	taubeta[1:2,1:2] ~ dwish(Q[1:2,1:2],2)
	for (i in 1:2) {
      for(j in 1:2) {
      Q[i,j] <- equals(i,j)
		}
	}
}