diff --git a/RunIBCwithoutGUI.R b/RunIBCwithoutGUI.R
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+++ b/RunIBCwithoutGUI.R
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+#####
+# libraries
+#####
+library(foreach)
+library(doParallel)
+library(labeling)s
+#####
+# Notes
+#####
+# -------------- Make sure to compile IBC before running this code ----------- #
+# ----------------- run Model-files/CompileIBC.bat --------------------------- #
+# code is copied/adapted from R-files/SimulationSpecificSettings.R
+#####
+# Load previously saved simulation settings 
+#####
+# You can use the GUI to generate the SimulationSettings.Rdata
+# simply run a very small test script (min. repetitions, min. years, min. grid size) and save the project
+# You then might want to adapt some of the settings manually (e.g. increase repetitions, number of simulated years etc.)
+load("ExampleAnalyses/DoseResponse/HerbicideSettings/SimulationSettings.Rdata") # just as an example for this script
+#####
+# read PFT community file and sensitivity file
+#####
+ModelVersion <- 3
+PFTfileName <- get("IBCcommunity", envir=SaveEnvironment) # txt-file with trait parameters of all species
+PFTHerbEffectFile <- "./HerbFact.txt" # you need this file if you run IBC with manual effects
+AppRateFile <- "./AppRate.txt" # you need this file if you run IBC with dose-response data
+MCruns <- get("IBCrepetition", envir=SaveEnvironment) # nb of repetitions 
+GridSize <- get("IBCgridsize", envir=SaveEnvironment) # area of the grid
+SeedInput <- get("IBCSeedInput", envir=SaveEnvironment) # external seed input
+belowres <- get("IBCbelres", envir=SaveEnvironment) # belowground resources
+abres <- get("IBCabres", envir=SaveEnvironment) # aboveground resources
+abampl <- get("IBCabampl", envir=SaveEnvironment) # seasonal amplitude of aboveground resources
+graz <- get("IBCgraz", envir=SaveEnvironment) # grazing intensity
+tramp <- get("IBCtramp", envir=SaveEnvironment) # trampling intensity
+cut <- get("IBCcut", envir=SaveEnvironment) # cutting/mowing events
+week_start <- get("IBCweekstart", envir=SaveEnvironment)-10 # start of the herbicide application (calendar week); note that IBC only simulate growing period
+HerbDuration <- get("IBCDuration", envir=SaveEnvironment) # hericide duration [years]
+RecovDuration <- get("IBCRecovery", envir=SaveEnvironment) # recovery duration [years]
+InitDuration <- get("IBCInit", envir=SaveEnvironment) # intial years 
+Tmax <- InitDuration + HerbDuration + RecovDuration # years to simulate
+HerbEff <- get("IBCherbeffect", envir=SaveEnvironment) # txt or dose response
+if(HerbEff=="txt-file") EffectModel <- 0
+if(HerbEff=="dose-response") EffectModel <- 2
+Scenarios <- as.numeric(get("IBCScenarios", envir=SaveEnvironment)) # number of rates tested
+nb_data <- as.numeric(get("nb_data", envir=SaveEnvironment)) # number of test species
+
+#####
+# running control
+#####
+scenario <- 0 # for control runs
+# copy community file into Model-folder
+path <- "Model-files/"
+write.table(get("IBCcommunityFile", envir=SaveEnvironment), paste(path,PFTfileName, sep=""), sep="\t", quote=F,row.names=F) # make sure the Model-files folder includes the file of your PFT community 
+
+copy <- file.copy("Input-files/HerbFact.txt",  path) # make sure the Model-files folder includes the HerbFact.txt file 
+copy <- file.copy("Input-files/AppRate.txt",  path) # make sure the Model-files folder includes the AppRate.txt file
+
+# Change directory
+setwd('Model-files')
+# determine the number of cores that can be used (for parallel running)
+no_cores <- max(detectCores()-2,1) # you might want to adapt this and give a specific number of cores (e.g. when using a HPC)
+cl <- makeCluster(no_cores)
+registerDoParallel(cl)
+
+# Start control simulations in parallel with the given settings
+foreach(MC = 1:MCruns)  %dopar%
+  system(paste('./IBCgrassGUI', ModelVersion, GridSize, Tmax, InitDuration, PFTfileName, SeedInput, belowres, abres, abampl, tramp, graz, cut,
+               week_start, HerbDuration, 0, EffectModel, scenario, MC, sep=" "), intern=T)
+stopCluster(cl)
+
+# change directory
+setwd('..')
+
+# remove files before running treatment
+remove <- file.remove(paste("Model-files/", PFTfileName, sep=""))
+remove <- file.remove("Model-files/HerbFact.txt")
+remove <- file.remove("Model-files/AppRate.txt")
+
+#####
+# copy control simulations
+#####
+# create folder
+dir.create("currentSimulation/0", recursive=TRUE) # adapt path if needed
+
+# PFT files
+file_list <- list.files(path = "Model-files/", pattern="Pt__*")
+for (file in file_list){
+  path <- paste("currentSimulation/", unlist(strsplit(file,"_"))[6], sep="")
+  copy <- file.copy(paste("Model-files/" ,file , sep="") ,  path)
+  if (copy==T) file.remove(paste("Model-files/" ,file , sep="") )
+}
+
+# GRD files
+file_list <- list.files(path = "Model-files/", pattern="Grd__*", recursive=TRUE)
+for (file in file_list){
+  path <- paste("currentSimulation/", unlist(strsplit(file,"_"))[6], sep="")
+  copy <- file.copy(paste("Model-files/" ,file , sep="") ,  path)
+  if (copy==T) file.remove(paste("Model-files/" ,file , sep="") )
+}
+
+#####
+# running treatment based on txt file (not in this example)
+#####
+if(HerbEff=="txt-file"){
+  # cluster for parallel processing
+  no_cores <- max(detectCores()-2,1) # you might want to adapt this and give a specific number of cores (e.g. when using a HPC)
+  cl <- makeCluster(no_cores)
+  registerDoParallel(cl)
+  
+  # generate PFTfile with herbicide sensitivities 
+  
+  PFTfile <- get("IBCcommunityFile", envir=SaveEnvironment)
+  PFTsensitivity <- get("PFTSensitivityFile", envir=SaveEnvironment) # here the sensitivity of all PFTs are stored
+  
+  # run treatment simulations
+  foreach(MC = 1:MCruns, .export=c("PFTfile", "PFTsensitivity", "PFTfileName", "EffectModel",
+                                   "ModelVersion", "belowres", "abres", "abampl", "Tmax", "InitDuration", "GridSize", "SeedInput",
+                                   "HerbDuration", "tramp", "graz", "cut", "week_start"))  %dopar%
+    {
+      scenario <- 1 # for treatment simulations
+  
+      # Generate PFTfile for each MC run
+      PFTfile<-merge(PFTfile, PFTsensitivity, by="Species")
+      
+      #make sure, all values are set to 0 (no affect)
+      PFTfile[,25] <- 0
+      
+      # set random values
+      PFTfile[PFTfile$Sensitivity=="random",25] <- c(runif(nrow(PFTfile[PFTfile$Sensitivity=="random",]),  min = 0, max = 1))
+      
+      # set full values
+      PFTfile[PFTfile$Sensitivity=="full",25] <- c(rep(1, nrow(PFTfile[PFTfile$Sensitivity=="full",])))
+      
+      # set high values
+      PFTfile[PFTfile$Sensitivity=="high",25] <- c(runif(nrow(PFTfile[PFTfile$Sensitivity=="high",]),  min = 0.66, max = 1))
+      
+      # set medium values
+      PFTfile[PFTfile$Sensitivity=="medium",25] <- c(runif(nrow(PFTfile[PFTfile$Sensitivity=="medium",]),  min = 0.35, max = 0.65))
+      
+      # set low values
+      PFTfile[PFTfile$Sensitivity=="low",25] <- c(runif(nrow(PFTfile[PFTfile$Sensitivity=="low",]),  min = 0.1, max = 0.35))
+      
+      # copy others (not affected PFTs get 0)
+      PFTfile[PFTfile$Sensitivity=="not affected",25] <- c(rep(0, nrow(PFTfile[PFTfile$Sensitivity=="not affected",])))
+      
+      # remove temp. column and prepare final PFT file for this repetition
+      PFTfile<-PFTfile[,-ncol(PFTfile)]
+      PFTfile <- cbind(PFTfile[,c(2,1)],PFTfile[,-c(1:2)])
+      
+      #save PFT file
+      write.table(PFTfile[,-ncol(PFTfile)], paste(unlist(strsplit(PFTfileName,".txt")), MC, ".txt", sep=""), row.names=F, quote=F, sep="\t")
+      
+      # copy necessary files to Model-files folder
+      path <- "Model-files/"
+      copy <- file.copy(paste(unlist(strsplit(PFTfileName,".txt")), MC, ".txt", sep=""),  path)
+      copy <- file.copy("HerbFact.txt",  path)
+      copy <- file.copy("Input-files/AppRate.txt",  path)
+      
+      # change directory
+      setwd('Model-files')
+      
+      # cmd call for running IBC
+      mycall<-paste('./IBCgrassGUI', ModelVersion, GridSize, Tmax, InitDuration, paste("./",unlist(strsplit(PFTfileName,".txt")), MC, ".txt", sep=""), 
+                    SeedInput, belowres, abres, abampl, tramp, graz, cut, 
+                    week_start, HerbDuration, 1, EffectModel, scenario, MC, sep=" ")
+      
+      # start treatment run
+      system(mycall, intern=TRUE)
+      
+      # change working directory
+      setwd('..')
+      
+      # remove old files
+      remove <- file.remove(paste("Model-files/", unlist(strsplit(PFTfileName,".txt")), MC, ".txt", sep=""))
+      remove <- file.remove("Model-files/HerbFact.txt")
+      remove <- file.remove("Model-files/AppRate.txt")
+    }
+  
+  # stop cluster for parallel processing
+  stopCluster(cl)
+  
+  #####
+  # copy treatment
+  #####
+  # copy files to directory
+  dir.create("currentSimulation/1", recursive=TRUE)
+  file_list <- list.files(path = "Model-files/", pattern="Pt__*")
+  for (file in file_list){
+    path <- "currentSimulation/1"
+    copy <- file.copy(paste("Model-files/" ,file , sep="") ,  path)
+    #  todo make sure that all files were copied!
+    if (copy==T) file.remove(paste("Model-files/" ,file , sep="") )              
+  } 
+  # GRD files
+  file_list <- list.files(path = "Model-files/", pattern="Grd__*")
+  for (file in file_list){
+    path <- "currentSimulation/1"
+    copy <- file.copy(paste("Model-files/" ,file , sep="") ,  path)
+    #  todo make sure that all files were copied!
+    if (copy==T) file.remove(paste("Model-files/" ,file , sep="") )              
+  }
+  
+  # Copy treamtent settings
+  dir.create(paste("currentSimulation/HerbicideSettings", sep=""), recursive=TRUE)
+  file_list <- list.files(pattern=paste(unlist(strsplit(PFTfileName,".txt")),"*",sep=""))
+  file_list <- file_list[file_list!=PFTfileName] #TODO: stimmt das mit der Datei???
+  file_list <- c(file_list, "SimulationSettings.Rdata")
+  copy <- file.copy(file_list ,  paste("currentSimulation/HerbicideSettings", sep=""))
+  #  todo make sure that all files were copied!
+  if (all(copy==T)) file.remove(file_list)
+  copy <- file.copy("HerbFact.txt" ,  paste("currentSimulation/HerbicideSettings", sep=""))
+  if (all(copy==T)) file.remove("HerbFact.txt")
+  copy <- file.copy("PFTsensitivity.txt" ,  paste("currentSimulation/HerbicideSettings", sep=""))
+  if (all(copy==T)) file.remove("PFTsensitivity.txt")
+}
+#####
+# running treatment based on dose responses
+#####
+if(HerbEff=="dose-response"){
+  count <- 0
+  PFTfile <- get("IBCcommunityFile", envir=SaveEnvironment)
+  # Application rate scenarios
+  AppRateScenarios <- data.frame(get("IBCAppRateScenarios", envir=SaveEnvironment))
+  PFTsensitivity <- get("PFTSensitivityFile", envir=SaveEnvironment)
+  # Generate cluster for parallel processing
+  no_cores <- max(detectCores()-2,1) # you might want to adapt this and give a specific number of cores (e.g. when using a HPC)
+  cl <- makeCluster(no_cores)
+  registerDoParallel(cl)
+  
+  # run repetitions for treatment
+  foreach(MC = 1:MCruns, .export=c("PFTfile", "PFTsensitivity", "PFTfileName", "EffectModel",
+                                   "ModelVersion", "belowres", "abres", "abampl", "Tmax", "InitDuration", "GridSize", "SeedInput",
+                                   "week_start", "HerbDuration", "tramp", "graz", "cut", "Scenarios", "nb_data",
+                                   "AppRateScenarios"))  %dopar%
+    {
+      #####
+      # set sensitivities for each treatment repetition
+      #####
+      PFTfile<-merge(PFTfile, PFTsensitivity, by="Species")
+      
+      # make sure, all values are set to 0 (no affect)
+      PFTfile[,28:39] <- 0
+      
+      # assign EC50 and slope values
+      #####
+      # biomass
+      #####
+      if("EC50andslope_Biomass.txt" %in% list.files()){
+        # read the calculated dose responses by the GUI
+#------ you need to prepare these data files manually if you do not use the GUI! ------------#
+        DR<-read.table("EC50andslope_Biomass.txt", sep="\t", header=T)
+        # random DRs
+        # EC50
+        PFTfile[PFTfile$Sensitivity=="random",28] <- c(runif(nrow(PFTfile[PFTfile$Sensitivity=="random",]),  min = max(0,(DR[nb_data+1,2] - DR[nb_data+2,2])), max = max(0,(DR[nb_data+1,2] + DR[nb_data+2,2]))))
+        # slope
+        PFTfile[PFTfile$Sensitivity=="random",29] <- c(runif(nrow(PFTfile[PFTfile$Sensitivity=="random",]), min = max(0,(DR[nb_data+1,3] - DR[nb_data+2,3])), max = max(0,(DR[nb_data+1,3] + DR[nb_data+2,3]))))
+        
+        # existing DR
+        for (i in 1:nb_data){
+          # EC50
+          PFTfile[PFTfile$Sensitivity==paste("dose response based on Spec ", i, sep=""),28] <- c(rep(DR[i,2],nrow(PFTfile[PFTfile$Sensitivity==paste("dose response based on Spec ", i, sep=""),])))
+          # slope
+          PFTfile[PFTfile$Sensitivity==paste("dose response based on Spec ", i, sep=""),29] <- c(rep(DR[i,3],nrow(PFTfile[PFTfile$Sensitivity==paste("dose response based on Spec ", i, sep=""),])))
+        } # end nb of test species
+        
+        # not affected
+        # EC50
+        PFTfile[PFTfile$Sensitivity=="not affected",28] <- c(rep(0, nrow(PFTfile[PFTfile$Sensitivity=="not affected",])))
+        # slope
+        PFTfile[PFTfile$Sensitivity=="not affected",29] <- c(rep(0, nrow(PFTfile[PFTfile$Sensitivity=="not affected",])))
+      } # end if biomass affected
+      #####
+      # seedling biomass
+      #####
+      if("EC50andslope_SeedlingBiomass.txt" %in% list.files()){
+        # read the calculated DR
+#------ you need to prepare these data files manually if you do not use the GUI! ------------#
+        DR<-read.table("EC50andslope_SeedlingBiomass.txt", sep="\t", header=T)
+        # random DRs
+        # EC50
+        PFTfile[PFTfile$Sensitivity=="random",30] <- c(runif(nrow(PFTfile[PFTfile$Sensitivity=="random",]),  min = max(0,(DR[nb_data+1,2] - DR[nb_data+2,2])), max = max(0,(DR[nb_data+1,2] + DR[nb_data+2,2]))))
+        # slope
+        PFTfile[PFTfile$Sensitivity=="random",31] <- c(runif(nrow(PFTfile[PFTfile$Sensitivity=="random",]), min = max(0,(DR[nb_data+1,3] - DR[nb_data+2,3])), max = max(0,(DR[nb_data+1,3] + DR[nb_data+2,3]))))
+        
+        # existing DR
+        for (i in 1:nb_data){
+          # EC50
+          PFTfile[PFTfile$Sensitivity==paste("dose response based on Spec ", i, sep=""),30] <- c(rep(DR[i,2],nrow(PFTfile[PFTfile$Sensitivity==paste("dose response based on Spec ", i, sep=""),])))
+          # slope
+          PFTfile[PFTfile$Sensitivity==paste("dose response based on Spec ", i, sep=""),31] <- c(rep(DR[i,3],nrow(PFTfile[PFTfile$Sensitivity==paste("dose response based on Spec ", i, sep=""),])))
+        } # end nb of test species
+        
+        # not affected
+        # EC50
+        PFTfile[PFTfile$Sensitivity=="not affected",30] <- c(rep(0, nrow(PFTfile[PFTfile$Sensitivity=="not affected",])))
+        # slope
+        PFTfile[PFTfile$Sensitivity=="not affected",31] <- c(rep(0, nrow(PFTfile[PFTfile$Sensitivity=="not affected",])))
+      } # end seedling biomass affected
+      #####
+      # survival
+      #####
+      if("EC50andslope_Survival.txt" %in% list.files()){
+        # read the calculated DR
+#------ you need to prepare these data files manually if you do not use the GUI! ------------#
+        DR<-read.table("EC50andslope_Survival.txt", sep="\t", header=T)
+        # random DRs
+        # EC50
+        PFTfile[PFTfile$Sensitivity=="random",32] <- c(runif(nrow(PFTfile[PFTfile$Sensitivity=="random",]),  min = max(0,(DR[nb_data+1,2] - DR[nb_data+2,2])), max = max(0,(DR[nb_data+1,2] + DR[nb_data+2,2]))))
+        # slope
+        PFTfile[PFTfile$Sensitivity=="random",33] <- c(runif(nrow(PFTfile[PFTfile$Sensitivity=="random",]), min = max(0,(DR[nb_data+1,3] - DR[nb_data+2,3])), max = max(0,(DR[nb_data+1,3] + DR[nb_data+2,3]))))
+        
+        # existing DR
+        for (i in 1:nb_data){
+          # EC50
+          PFTfile[PFTfile$Sensitivity==paste("dose response based on Spec ", i, sep=""),32] <- c(rep(DR[i,2],nrow(PFTfile[PFTfile$Sensitivity==paste("dose response based on Spec ", i, sep=""),])))
+          # slope
+          PFTfile[PFTfile$Sensitivity==paste("dose response based on Spec ", i, sep=""),33] <- c(rep(DR[i,3],nrow(PFTfile[PFTfile$Sensitivity==paste("dose response based on Spec ", i, sep=""),])))
+        } # end nb of test species
+        
+        # not affected
+        # EC50
+        PFTfile[PFTfile$Sensitivity=="not affected",32] <- c(rep(0, nrow(PFTfile[PFTfile$Sensitivity=="not affected",])))
+        # slope
+        PFTfile[PFTfile$Sensitivity=="not affected",33] <- c(rep(0, nrow(PFTfile[PFTfile$Sensitivity=="not affected",])))
+      } # end survival affected
+      #####
+      # establishment
+      #####
+      # read the calculated DR
+#------ you need to prepare these data files manually if you do not use the GUI! ------------#      
+      if("EC50andslope_Establishment.txt" %in% list.files()){
+        # read the calculated DR
+        DR<-read.table("EC50andslope_Establishment.txt", sep="\t", header=T)
+        # random DRs
+        # EC50
+        PFTfile[PFTfile$Sensitivity=="random",34] <- c(runif(nrow(PFTfile[PFTfile$Sensitivity=="random",]),  min = max(0,(DR[nb_data+1,2] - DR[nb_data+2,2])), max = max(0,(DR[nb_data+1,2] + DR[nb_data+2,2]))))
+        # slope
+        PFTfile[PFTfile$Sensitivity=="random",35] <- c(runif(nrow(PFTfile[PFTfile$Sensitivity=="random",]), min = max(0,(DR[nb_data+1,3] - DR[nb_data+2,3])), max = max(0,(DR[nb_data+1,3] + DR[nb_data+2,3]))))
+        
+        # existing DR
+        for (i in 1:nb_data){
+          # EC50
+          PFTfile[PFTfile$Sensitivity==paste("dose response based on Spec ", i, sep=""),34] <- c(rep(DR[i,2],nrow(PFTfile[PFTfile$Sensitivity==paste("dose response based on Spec ", i, sep=""),])))
+          # slope
+          PFTfile[PFTfile$Sensitivity==paste("dose response based on Spec ", i, sep=""),35] <- c(rep(DR[i,3],nrow(PFTfile[PFTfile$Sensitivity==paste("dose response based on Spec ", i, sep=""),])))
+        } # end nb of test species
+        
+        # not affected
+        # EC50
+        PFTfile[PFTfile$Sensitivity=="not affected",34] <- c(rep(0, nrow(PFTfile[PFTfile$Sensitivity=="not affected",])))
+        # slope
+        PFTfile[PFTfile$Sensitivity=="not affected",35] <- c(rep(0, nrow(PFTfile[PFTfile$Sensitivity=="not affected",])))
+      } # end establishment affected
+      #####
+      # seed sterility
+      #####
+      if("EC50andslope_SeedSterility.txt" %in% list.files()){
+        # read the calculated DR
+#------ you need to prepare these data files manually if you do not use the GUI! ------------#      
+        DR<-read.table("EC50andslope_SeedSterility.txt", sep="\t", header=T)
+        # random DRs
+        # EC50
+        PFTfile[PFTfile$Sensitivity=="random",36] <- c(runif(nrow(PFTfile[PFTfile$Sensitivity=="random",]),  min = max(0,(DR[nb_data+1,2] - DR[nb_data+2,2])), max = max(0,(DR[nb_data+1,2] + DR[nb_data+2,2]))))
+        # slope
+        PFTfile[PFTfile$Sensitivity=="random",37] <- c(runif(nrow(PFTfile[PFTfile$Sensitivity=="random",]), min = max(0,(DR[nb_data+1,3] - DR[nb_data+2,3])), max = max(0,(DR[nb_data+1,3] + DR[nb_data+2,3]))))
+        
+        # existing DR
+        for (i in 1:nb_data){
+          # EC50
+          PFTfile[PFTfile$Sensitivity==paste("dose response based on Spec ", i, sep=""),36] <- c(rep(DR[i,2],nrow(PFTfile[PFTfile$Sensitivity==paste("dose response based on Spec ", i, sep=""),])))
+          # slope
+          PFTfile[PFTfile$Sensitivity==paste("dose response based on Spec ", i, sep=""),37] <- c(rep(DR[i,3],nrow(PFTfile[PFTfile$Sensitivity==paste("dose response based on Spec ", i, sep=""),])))
+        } # end nb of test species
+        
+        # not affected
+        # EC50
+        PFTfile[PFTfile$Sensitivity=="not affected",36] <- c(rep(0, nrow(PFTfile[PFTfile$Sensitivity=="not affected",])))
+        # slope
+        PFTfile[PFTfile$Sensitivity=="not affected",37] <- c(rep(0, nrow(PFTfile[PFTfile$Sensitivity=="not affected",])))
+      } # end seed sterility affected
+      #####
+      # seed number
+      #####
+      if("EC50andslope_SeedNumber.txt" %in% list.files()){
+        # read the calculated DR
+#------ you need to prepare these data files manually if you do not use the GUI! ------------#      
+        DR<-read.table("EC50andslope_SeedNumber.txt", sep="\t", header=T)
+        # random DRs
+        # EC50
+        PFTfile[PFTfile$Sensitivity=="random",38] <- c(runif(nrow(PFTfile[PFTfile$Sensitivity=="random",]),  min = max(0,(DR[nb_data+1,2] - DR[nb_data+2,2])), max = max(0,(DR[nb_data+1,2] + DR[nb_data+2,2]))))
+        # slope
+        PFTfile[PFTfile$Sensitivity=="random",39] <- c(runif(nrow(PFTfile[PFTfile$Sensitivity=="random",]), min = max(0,(DR[nb_data+1,3] - DR[nb_data+2,3])), max = max(0,(DR[nb_data+1,3] + DR[nb_data+2,3]))))
+        
+        # existing DR
+        for (i in 1:nb_data){
+          # EC50
+          PFTfile[PFTfile$Sensitivity==paste("dose response based on Spec ", i, sep=""),38] <- c(rep(DR[i,2],nrow(PFTfile[PFTfile$Sensitivity==paste("dose response based on Spec ", i, sep=""),])))
+          # slope
+          PFTfile[PFTfile$Sensitivity==paste("dose response based on Spec ", i, sep=""),39] <- c(rep(DR[i,3],nrow(PFTfile[PFTfile$Sensitivity==paste("dose response based on Spec ", i, sep=""),])))
+        } # end nb of test species
+        
+        # not affected
+        # EC50
+        PFTfile[PFTfile$Sensitivity=="not affected",38] <- c(rep(0, nrow(PFTfile[PFTfile$Sensitivity=="not affected",])))
+        # slope
+        PFTfile[PFTfile$Sensitivity=="not affected",39] <- c(rep(0, nrow(PFTfile[PFTfile$Sensitivity=="not affected",])))
+      } # end seed number affected
+      
+      #####
+      # save the generated PFT file (specific for one treatment repetition)
+      #####
+      PFTfile<-PFTfile[,-ncol(PFTfile)]
+      PFTfile <- cbind(PFTfile[,c(2,1)],PFTfile[,-c(1:2)])
+      
+      #save PFT file
+      write.table(PFTfile[,-ncol(PFTfile)], paste(unlist(strsplit(PFTfileName,".txt")), MC, ".txt", sep=""), row.names=F, quote=F, sep="\t")
+      
+      #####
+      # run simulations per app rate
+      #####
+      path <- "Model-files/"
+      # Copy generated file to Model-files folder
+      copy <- file.copy(paste(unlist(strsplit(PFTfileName,".txt")), MC, ".txt", sep=""),  path)
+      # Copy dummy HerbFact.txt file (needed for c++ code; could probably be improved)
+      copy <- file.copy("Input-files/HerbFact.txt",  path)
+      # Change directory
+      setwd('Model-files')
+      
+      # generate the AppRate.txt files and run simulations
+      
+      for(scenario in 1:Scenarios){ # Scenarios is the number of tested/simulated application rates
+        
+        # split txt file with all AppRates of all Scenarios into the scenario and save as AppRate.txt
+        write.table(AppRateScenarios[,scenario], "AppRate.txt",  col.names=FALSE,  row.names=FALSE, sep="\t")
+        
+        # cmd call for running IBC
+        mycall<-paste('./IBCgrassGUI',ModelVersion, GridSize, Tmax, InitDuration, 
+                      paste("./",unlist(strsplit(PFTfileName,".txt")), MC, ".txt", sep=""), 
+                      SeedInput, belowres, abres, abampl, tramp, graz, cut, 
+                      week_start, HerbDuration, 1, EffectModel, scenario, MC, sep=" ")
+        # start treatment run
+        system(mycall, intern=TRUE)
+        
+        # remove 'old' files before starting new simulation
+        remove <- file.remove("Model-files/AppRate.txt")
+      } # end for apprates
+      
+      # Change directory
+      setwd('..')
+      # remove old files
+      remove <- file.remove(paste("Model-files/", unlist(strsplit(PFTfileName,".txt")), MC, ".txt", sep=""))
+      remove <- file.remove("Model-files/HerbFact.txt")
+      
+    }
+  # stop cluster for parallel processing
+  stopCluster(cl)
+  
+  #####
+  # copy treatment
+  #####
+  
+  # PFT files
+  file_list <- list.files(path = "Model-files/", pattern="Pt__*", recursive=TRUE)
+  for (file in file_list){
+    path <- paste("currentSimulation/", unlist(strsplit(file,"_"))[6], sep="")
+    if(!(unlist(strsplit(file,"_"))[6] %in% list.files("currentSimulation/"))) dir.create(paste("currentSimulation/",unlist(strsplit(file,"_"))[6],sep=""))
+    copy <- file.copy(paste("Model-files/" ,file , sep="") ,  path)
+    #  todo make sure that all files were copied!
+    if (copy==T) file.remove(paste("Model-files/" ,file , sep="") )              
+  }
+  
+  # GRD files
+  file_list <- list.files(path = "Model-files/", pattern="Grd__*", recursive=TRUE)
+  for (file in file_list){
+    path <- paste("currentSimulation/", unlist(strsplit(file,"_"))[6], sep="")
+    if(!(unlist(strsplit(file,"_"))[6] %in% list.files("currentSimulation/"))) dir.create(paste("currentSimulation/",unlist(strsplit(file,"_"))[6],sep=""))
+    copy <- file.copy(paste("Model-files/" ,file , sep="") ,  path)
+    #  todo make sure that all files were copied!
+    if (copy==T) file.remove(paste("Model-files/" ,file , sep="") )              
+  }
+  
+  # Herbicide treatment settings
+  dir.create(paste("currentSimulation/HerbicideSettings", sep=""), recursive=TRUE)
+  # all generated PFT files with sensitivities
+  file_list <- list.files(pattern=paste(unlist(strsplit(PFTfileName,".txt")),"*",sep=""))
+  file_list <- file_list[file_list!=PFTfileName]
+  # file_list <- c(file_list, "SimulationSettings.Rdata", "Example_doseresponse.png", "AppRateScenarios.txt") # these files are only generated by the GUI
+  copy <- file.copy(file_list ,  paste("currentSimulation/HerbicideSettings", sep=""))
+  # remove after copy
+  if (all(copy==T)) file.remove(file_list)
+  
+  # HerbFact file 
+  copy <- file.copy("HerbFact.txt" ,  paste("currentSimulation/HerbicideSettings", sep=""))
+  if (all(copy==T)) file.remove("HerbFact.txt")
+  
+  # PFT sensitivity file
+  copy <- file.copy("PFTsensitivity.txt" ,  paste("currentSimulation/HerbicideSettings", sep=""))
+  if (all(copy==T)) file.remove("PFTsensitivity.txt")
+  
+  # EC50 and slopes
+  file_list <- list.files(pattern="EC50andslope*")
+  copy <- file.copy(file_list ,  paste("currentSimulation/HerbicideSettings", sep=""))
+  if (all(copy==T)) file.remove(file_list)
+  #
+  
+  file_list <- list.files(pattern="*Effects.txt")
+  copy <- file.copy(file_list ,  paste("currentSimulation/HerbicideSettings", sep=""))
+  if (all(copy==T)) file.remove(file_list)
+} # end if dose response based
\ No newline at end of file