diff --git a/R/MP_3c_HCR_ICES_MSY.R b/R/MP_3c_HCR_ICES_MSY.R
index f0acbb1..4e61bd5 100644
--- a/R/MP_3c_HCR_ICES_MSY.R
+++ b/R/MP_3c_HCR_ICES_MSY.R
@@ -43,6 +43,8 @@ IcesHCR <- function(stocks, advice, advice.ctrl, year, stknm,...){
     stk@discards <- computeDiscards(stk)
     
     ageStruct <- ifelse(dim(stk@m)[1] > 1, TRUE, FALSE)
+    
+
 
     if(ageStruct == TRUE){
       if(any(stk@catch[,tail(dimnames(stk@catch)$year,3)]<1e-2)){
@@ -57,7 +59,9 @@ IcesHCR <- function(stocks, advice, advice.ctrl, year, stknm,...){
     
     ref.pts <- advice.ctrl[[stknm]]$ref.pts # matrix[3,it]  rows = Blim, Btrigger, Fmsy
     Cadv <- ifelse(advice.ctrl[[stknm]][['AdvCatch']][year+1] == TRUE, 'catch', 'landings')
-   
+    target <- advice.ctrl[[stknm]]$target # Target when the biomass is above MSY BTrigger, it can be Fupp or Fmsy, or other target in the reference points
+      
+      
     iter     <- dim(stk@m)[6]
     yrsnames <- dimnames(stk@m)[[2]]
     yrsnumbs <- as.numeric(yrsnames)
@@ -186,7 +190,7 @@ IcesHCR <- function(stocks, advice, advice.ctrl, year, stknm,...){
             # Find where the SSB (Age structured) OR Biomass (Aggregated) in relation to reference points.
             b.pos <-  findInterval(b.datyr, ref.pts[c('Blim', 'Btrigger'),i])  # [1]
             
-            Ftg <- ifelse(b.pos == 0, 0, ifelse(b.pos == 1, ref.pts['Fmsy',i]*b.datyr/ref.pts[ 'Btrigger',i], ref.pts['Fmsy',i]))
+            Ftg <- ifelse(b.pos == 0, 0, ifelse(b.pos == 1, ref.pts['Fmsy',i]*b.datyr/ref.pts[ 'Btrigger',i], ref.pts[target,i]))
             
             print(Ftg)
             
diff --git a/R/OM_1b_Population_Growth_Functions_ASPG_DDW.R b/R/OM_1b_Population_Growth_Functions_ASPG_DDW.R
new file mode 100644
index 0000000..209b343
--- /dev/null
+++ b/R/OM_1b_Population_Growth_Functions_ASPG_DDW.R
@@ -0,0 +1,27 @@
+# Age structured population growth with densodependence
+ASPG_DDW <- function(biols, SRs, fleets, year, season, stknm, biols.ctrl,...){
+  
+  # update wt of stknm
+  ddw.model <- biols.ctrl[[stkm]][['DDW.model']]
+  lfd       <- biols.ctrl[[stkm]][['LFD']]
+  a         <- biols.ctrl[[stkm]][['a.lw']]
+  lbins     <- as.numeric(colNames(lfd))
+  
+  B <- quantSums((biols[[stkm]]@wt*biols[[stkm]]@n)[,year-1])[drop=T]
+    
+  condF <- predict(LW_lm, data.frame(biomass = B))
+
+  wy <- a*(lbins)^condF
+  
+  wt <- rowSums(sweep(lfd, 2, wy, "*"))
+  
+  biols[[stkm]]@wt[,year] <- wt
+  
+  # use normal ASPG to project the population
+  
+  res <- ASPG(biols, SRs, fleets, year, season, stknm, biols.ctrl,...)
+  
+  return(res)
+} 
+
+
diff --git a/R/OM_2b_Update_catch.R b/R/OM_2b_Update_catch.R
index d4316f0..d155a01 100644
--- a/R/OM_2b_Update_catch.R
+++ b/R/OM_2b_Update_catch.R
@@ -217,6 +217,8 @@ BioPop.CAA  <- function(fleets, biols, BDs, biols.ctrl, fleets.ctrl, advice, adv
 #-------------------------------------------------------------------------------
 AgePop.CAA <- function(fleets, biols, BDs, biols.ctrl, fleets.ctrl, advice, advice.ctrl, year = 1, season = 1, flnm = 1, stknm = 1,...){
 
+ # if(flnm == 'OT_WHB_-9') browser()
+  
     rho <- fleets.ctrl[['catch.threshold']][stknm,year,, season,drop=T] # [it]
 
     nf    <- length(fleets)
diff --git a/src/FLBEIA.dll b/src/FLBEIA.dll
index d95d1f7..f17fd61 100644
Binary files a/src/FLBEIA.dll and b/src/FLBEIA.dll differ