Merge branch 'SpawnerRunAnalysis' of gitlab-ssh.irstea.fr:SimAquaLife/GR3D...

Merge branch 'SpawnerRunAnalysis' of gitlab-ssh.irstea.fr:SimAquaLife/GR3D into exploration_GR3D_process

exploration/GR3D_Rdescription/GR3Dmetapopulation.R

+
+#=============================================================================================================
+# metapopulation identification
+# =============================================================================================================
+computeAutochtonousRate = function(data){
+  data %>% filter(migrationBasin == originBasin) %>% 
+    select(-originBasin) %>% 
+    inner_join(data %>% group_by(year, migrationBasin) %>% 
+                 summarise(totalRun = sum(effective), .groups = 'drop'), by = c('migrationBasin', 'year')) %>% 
+    mutate(autochtonousRate = effective / totalRun) %>% 
+    select(year, migrationBasin, autochtonousRate)
+}
+
+computeHomingRate = function(data){
+  data %>% filter(migrationBasin == originBasin) %>% 
+    select(-migrationBasin) %>% 
+    inner_join(data %>% group_by(year, originBasin) %>% 
+                 summarise(production = sum(effective), .groups = 'drop'), by = c('originBasin', 'year')) %>% 
+    mutate(homingRate = effective / production) %>% 
+    select(year, originBasin, homingRate)
+}
+
+# comparison between autochtonous rate and homing rate
+# computeAutochtonousRate(exchangesData) %>% 
+#   inner_join(computeHomingRate(data = exchangesData), by =  c('migrationBasin' = 'originBasin', 'year'))
+
+
+
+identyMetapopulation = function(exchangesData, threshold = .95, verbose = FALSE) {
+  # exchangesData {year, migrationBasin, originBasin)}
+  
+  exchangesDataUpdated = exchangesData
+  
+  # initialise the connection table between basin and metapopulation
+  metapopulation = exchangesDataUpdated %>% 
+    distinct(year, basin = migrationBasin) %>% 
+    mutate(metapop = basin)
+  
+  iteration = 1
+  
+  # find the basin with the minimum autochtonous rate for the first time,
+  basinWithMinAutochtonousRate = computeAutochtonousRate(data = exchangesDataUpdated) %>%
+    group_by(year) %>%
+    slice(which.min(autochtonousRate))
+  
+  # loop while autochtonousRate is still < 0.95
+  
+  while (basinWithMinAutochtonousRate$autochtonousRate < threshold ) {
+    #  while (iteration <= 4 ) {
+    if (verbose) cat(iteration, ": ", basinWithMinAutochtonousRate$autochtonousRate, '\n' )
+    
+    # basinWithMinAutochtonousRate will be merged with origin basin sending the maximum number of fish in this basin
+    metapopsToBeMerged <-   exchangesDataUpdated %>% 
+      inner_join(basinWithMinAutochtonousRate %>% select(-autochtonousRate), 
+                 by = c('year', 'migrationBasin' )) %>%
+      filter(migrationBasin != originBasin) %>% # to avoid self merging
+      group_by(year) %>% 
+      slice(which.max(effective)) %>% 
+      ungroup() %>% 
+      select(year, migrationBasin, originBasin)
+    
+    # update the connection table between basin and metapopulation by merging metapopulation
+    for (i in 1:nrow(metapopsToBeMerged)) {
+      mergedName = paste0("M", iteration, '_',i)
+      metapopsToBeMerged_i <- metapopsToBeMerged %>% slice(i) 
+      if (verbose) cat("\t", metapopsToBeMerged_i$migrationBasin, ' + ', metapopsToBeMerged_i$originBasin, ' = ', mergedName, "\n")
+      
+      metapopulation <- metapopulation %>% 
+        mutate(metapop = if_else(year == metapopsToBeMerged_i$year &
+                                   metapop %in%  (metapopsToBeMerged_i %>% select(ends_with("Basin")) %>% unlist(use.names = FALSE)), 
+                                 mergedName,
+                                 metapop)) 
+    }
+    # sum by migration and origin basins according to updated metapopulations
+    # computed with initial exchangesData
+    exchangesDataUpdated <- exchangesData %>% 
+      #sum up on migration basins
+      inner_join(metapopulation, 
+                 by = c('year', 'migrationBasin' = 'basin')) %>% 
+      group_by(year, metapop, originBasin) %>% 
+      summarise(effective = sum(effective), .groups = 'drop') %>% 
+      rename(migrationBasin = metapop) %>% 
+      # sum on origine basins
+      inner_join(metapopulation, 
+                 by = c('year', 'originBasin' = 'basin')) %>% 
+      group_by(year, metapop, migrationBasin) %>% 
+      summarise(effective = sum(effective), .groups = 'drop') %>% 
+      rename(originBasin = metapop)
+    
+    # minimum of autochtonous rate
+    basinWithMinAutochtonousRate = computeAutochtonousRate(data = exchangesDataUpdated) %>%
+      group_by(year) %>%
+      slice(which.min(autochtonousRate))
+    
+    iteration = iteration + 1
+  }
+  return(list(metapopulation = metapopulation, exchangesData = exchangesDataUpdated))
+}
+
+
+

exploration/GR3D_Rdescription/thermalRanges.R

+library(tidyverse)
+
+#TODO extract from xml
+
+thermalRange = tibble(process = "Grow", Tmin = 1.7, Topt = 4.5, Tmax = 27.9, type = "Rosso") %>% 
+  bind_rows(tibble(process = "SurvivalSpawnerInRiv", Tmin = 5.4, Topt = 16.7, Tmax = 27.5, type = "Rosso") ) %>% 
+  bind_rows(tibble(process = "Reproduction", Tmin = 5.1, Topt = 13.5, Tmax = 24.5, type = "Rosso") ) %>% 
+  bind_rows(tibble(process = "SurviveAfterReproduction", Tmin = -Inf, Topt = 19.58 - log(19)/0.58, Tmax = 19.58 + log(19)/0.58, type = "logit") )
+
+
+thermalRange %>% mutate(numero = row_number(),
+                        process = factor(process, 
+                                         levels = c("Grow","SurvivalSpawnerInRiv", "SurviveAfterReproduction", "Reproduction" ))) %>% 
+  ggplot() +
+  geom_segment(aes(x = Tmin, y = process, xend = Tmax, yend = process)) +
+  geom_point(aes(x = Topt, y = process)) 
+

exploration/NEA_sensitivity_analysis/extractNumeroProcess.R

 library(tidyverse)
+library(XML)
 #source("../GR3D_Rdescription/GR3D_NEA_XML_parameters.R")
 
 setwd("~/Documents/workspace/GR3D/exploration/NEA_sensitivity_analysis")

exploration/NEA_sensitivity_analysis/metapopulationIdentification.R

-library(tidyverse)
-
-computeAutochtonousRate = function(data){
-  data %>% filter(migrationBasin == originBasin) %>% 
-    select(-originBasin) %>% 
-    inner_join(data %>% group_by(year, migrationBasin) %>% 
-                 summarise(totalRun = sum(effective), .groups = 'drop'), by = c('migrationBasin', 'year')) %>% 
-    mutate(autochtonousRate = effective / totalRun) %>% 
-    select(year, migrationBasin, autochtonousRate)
-}
-
-computeHomingRate = function(data){
-  data %>% filter(migrationBasin == originBasin) %>% 
-    select(-migrationBasin) %>% 
-    inner_join(data %>% group_by(year, originBasin) %>% 
-                 summarise(production = sum(effective), .groups = 'drop'), by = c('originBasin', 'year')) %>% 
-    mutate(homingRate = effective / production) %>% 
-    select(year, originBasin, homingRate)
-}
-
-# comparison between autochtonous rate and homing rate
-# computeAutochtonousRate(exchangesData) %>% 
-#   inner_join(computeHomingRate(data = exchangesData), by =  c('migrationBasin' = 'originBasin', 'year'))
-
-
-
-identyMetapopulation = function(exchangesData, threshold = .95, verbose = FALSE) {
-  exchangesDataUpdated = exchangesData
-  
-  # initialise the connection table between basin and metapopulation
-  metapopulation = exchangesDataUpdated %>% 
-    distinct(year, basin = migrationBasin) %>% 
-    mutate(metapop = basin)
-  
-  iteration = 1
-  
-  # find the basin with the minimum autochtonous rate for the first time,
-  basinWithMinAutochtonousRate = computeAutochtonousRate(data = exchangesDataUpdated) %>%
-    group_by(year) %>%
-    slice(which.min(autochtonousRate))
-  
-  # loop while autochtonousRate is still < 0.95
-  
-  while (basinWithMinAutochtonousRate$autochtonousRate < threshold ) {
-    #  while (iteration <= 4 ) {
-    if (verbose) cat(iteration, ": ", basinWithMinAutochtonousRate$autochtonousRate, '\n' )
-    
-    # basinWithMinAutochtonousRate will be merged with origin basin sending the maximum number of fish in this basin
-    metapopsToBeMerged <-   exchangesDataUpdated %>% 
-      inner_join(basinWithMinAutochtonousRate %>% select(-autochtonousRate), 
-                 by = c('year', 'migrationBasin' )) %>%
-      filter(migrationBasin != originBasin) %>% # to avoid self merging
-      group_by(year) %>% 
-      slice(which.max(effective)) %>% 
-      ungroup() %>% 
-      select(year, migrationBasin, originBasin)
-    
-    # update the connection table between basin and metapopulation by merging metapopulation
-    for (i in 1:nrow(metapopsToBeMerged)) {
-      mergedName = paste0("M", iteration, '_',i)
-      metapopsToBeMerged_i <- metapopsToBeMerged %>% slice(i) 
-      if (verbose) cat("\t", metapopsToBeMerged_i$migrationBasin, ' + ', metapopsToBeMerged_i$originBasin, ' = ', mergedName, "\n")
-      
-      metapopulation <- metapopulation %>% 
-        mutate(metapop = if_else(year == metapopsToBeMerged_i$year &
-                                   metapop %in%  (metapopsToBeMerged_i %>% select(ends_with("Basin")) %>% unlist(use.names = FALSE)), 
-                                 mergedName,
-                                 metapop)) 
-    }
-    # sum by migration and origin basins according to updated metapopulations
-    # computed with initial exchangesData
-    exchangesDataUpdated <- exchangesData %>% 
-      #sum up on migration basins
-      inner_join(metapopulation, 
-                 by = c('year', 'migrationBasin' = 'basin')) %>% 
-      group_by(year, metapop, originBasin) %>% 
-      summarise(effective = sum(effective), .groups = 'drop') %>% 
-      rename(migrationBasin = metapop) %>% 
-      # sum on origine basins
-      inner_join(metapopulation, 
-                 by = c('year', 'originBasin' = 'basin')) %>% 
-      group_by(year, metapop, migrationBasin) %>% 
-      summarise(effective = sum(effective), .groups = 'drop') %>% 
-      rename(originBasin = metapop)
-    
-    # minimum of autochtonous rate
-    basinWithMinAutochtonousRate = computeAutochtonousRate(data = exchangesDataUpdated) %>%
-      group_by(year) %>%
-      slice(which.min(autochtonousRate))
-    
-    iteration = iteration + 1
-  }
-  return(list(metapopulation = metapopulation, exchangesData = exchangesDataUpdated))
-}
+require(tidyverse)
 
+source(GR3Dmetapopulation)
 # upload data =====
 # longer table of effective of different origin basins in each migration basin 
 exchangesData <- read_csv("../../data/output/northeastamerica/effectiveFluxes_1-observed.csv")
 
+
 exchangesData %>% group_by(year, basin = originBasin) %>% 
   summarise(production = sum(effective), .groups = 'drop') %>% 
   inner_join(exchangesData %>% group_by(year, basin = migrationBasin) %>% 

exploration/NEA_sensitivity_analysis/tryFromJava.R

@@ -3,15 +3,16 @@ library(rJava) # see J4R
 #library(yaml)
 library(tidyverse)
 library(jdx)
+library(tictoc)
 
-rm(list = ls())
 
+rm(list = ls())
 
 ## to have the same working directory as GR3D
 #setwd("~/Documents/workspace/GR3D/exploration/NEA_sensitivity_analysis")
 setwd("../..")
 
-
+source("exploration/GR3D_Rdescription/GR3Dmetapopulation.R")
 # ====================================== LOCAL FUNCTIONS =====================================
 convertFromSALtoR = function(java_out){
   require(jdx)
@@ -22,8 +23,8 @@ convertFromSALtoR = function(java_out){
   R_out = lapply(seq(2, length(java_out)), FUN = function(i){convertToR(java_out[[i]])}) %>% 
     unlist() %>% 
     matrix(nrow = length(java_out) - 1, byrow = TRUE, dimnames = list(NULL, headers) ) %>%
-    data.frame() %>% 
-    suppressMessages(type_convert()) 
+    as_tibble() %>% 
+    type_convert()
   
   return(R_out)
 }
@@ -41,7 +42,7 @@ exploreEasyRun = function(){
   # 1. northernmost populated basin_id   
   # 2. centroid latitude
   out_range = .jcall("analysis.EasyRun","[[Ljava/lang/String;","getValuesFromAquanismGroupProcess","processes.processesEachStep.10.exportToR")
-  range = convertFromSALtoR(out_range)
+  range = suppressMessages(convertFromSALtoR(out_range))
   
   # 3. log-likelihood ----
   #       the proportion of reproductions leading to a recruitment > 50 over the 1920-1950 period was used 
@@ -55,66 +56,79 @@ exploreEasyRun = function(){
   #     then in R: annual slope of the linear regression
   #     and average over the period
   # 5. mean age of female and age
-  #     annual mean age in each basin, 
-  #     then in R: average per year,
-  #     and average over the period (1920 and 1950)
+  #     annual mean age over the period (1920 and 1950) in each basin, 
+  #     and average over basin
   out_spawners_features = .jcall("analysis.EasyRun","[[Ljava/lang/String;","getValuesFromAquanismGroupProcess","processes.processesEachStep.9.exportToR")
-  spawners_features = convertFromSALtoR(out_spawners_features)
+  spawners_features =suppressMessages (convertFromSALtoR(out_spawners_features))
   
-  ## ICI coder pente de la droite moyenne des ages
+  slopePrimiparous =  lm(pct_primiparous~latitude, data = spawners_features)$coeff[2]
+  meanAgeFemale = mean(spawners_features$mean_age_female, na.rm = TRUE)
+  meanAgeMale = mean(spawners_features$mean_age_male, na.rm = TRUE)
   
   # ------------------------------------------------------------ #
   # 5. number of metapopulation based on the exchange matrix ----
   #     mean annual exchange matrix between 1920 and 1950
   out_exchanges = .jcall("analysis.EasyRun","[[Ljava/lang/String;","getValuesFromAquanismGroupProcess","processes.processesEachStep.16.exportToR")
-  exchanges = convertFromSALtoR(out_exchanges)
+  exchanges = suppressMessages(convertFromSALtoR(out_exchanges))
+  
+  # keep only basin with a totalRun  (sum over migrationBasin) >0
+  selectedBasin <- exchanges %>% group_by(basin = migrationBasin) %>% 
+    summarise(totalRun = sum(effective), .groups = 'drop') %>% 
+    filter(totalRun > 0) %>% select(basin)
   
-  ## ICI  lancer metapopulationIdentification
+  metapopulations <- exchanges %>% inner_join(selectedBasin, by=c('migrationBasin' = 'basin')) %>%
+    inner_join(selectedBasin, by=c('natalBasin' = 'basin')) %>% 
+    mutate(year =0) %>% rename(originBasin = natalBasin) %>% 
+    identyMetapopulation(., threshold = .95, verbose = FALSE)
   
+  nbMetapopulation = metapopulations$metapopulation %>% 
+    distinct(metapop) %>% 
+    summarise(n = n()) %>% 
+    unlist(use.names = FALSE)
   
-  return(list(northern_basin_id = range$northern_basin_id, 
-              effective_centroid_latitude = range$effective_centroid_latitude,
-              logL = logL,
-              spawners_features = spawners_features,
-              exchanges = exchanges))
+  return(tibble(northern_basin_id = range$northern_basin_id, 
+                effective_centroid_latitude = range$effective_centroid_latitude,
+                logL = logL,
+                slopePrimiparous = slopePrimiparous,
+                meanAgeFemale = meanAgeFemale,
+                meanAgeMale = meanAgeMale, 
+                nbMetapopulation = nbMetapopulation))
 }
 
 
 
 # GR3D arguments -----------------------------------------
-jarfile = "target/GR3D-3.2-SNAPSHOT.jar"
-simDuration = 150
-simBegin = 1
-timeStepDuration = 1
-
-seed = 1
-#'-q',
-arguments = c('-simDuration', simDuration, '-simBegin',simBegin,
-              '-timeStepDuration', timeStepDuration, 
-              '-RNGStatusIndex', format(seed,scientific = FALSE),
-              '-groups',"data/input/northeastamerica/fishRIOBasin_Sapidissima_Rjava.xml",
-              '-env',"data/input/northeastamerica/RIOBNneaBasins_Rjava.xml",
-              '-observers',"data/input/northeastamerica/RIO_obs_empty.xml")
-
-
-
+#' jarfile = "target/GR3D-3.2-SNAPSHOT.jar"
+#' simDuration = 150
+#' simBegin = 1
+#' timeStepDuration = 1
+#' 
+#' seed = 1
+#' #'-q',
+#' arguments = c('-simDuration', simDuration, '-simBegin',simBegin,
+#'               '-timeStepDuration', timeStepDuration, 
+#'               '-RNGStatusIndex', format(seed,scientific = FALSE),
+#'               '-groups',"data/input/northeastamerica/fishRIOBasin_Sapidissima_Rjava.xml",
+#'               '-env',"data/input/northeastamerica/RIOBNneaBasins_Rjava.xml",
+#'               '-observers',"data/input/northeastamerica/RIO_obs_empty.xml")
 
 
 # -----------------------------------------------------
 #  initializes the Java Virtual Machine -------------------------------------
+jarfile = "target/GR3D-3.2-SNAPSHOT.jar"
 .jinit(NULL, force.init = TRUE)
 .jinit(classpath = jarfile, force.init = TRUE)
 .jclassPath()
 
 #  modification of xlm parameters -----------------------
-parametersNamesANG = c("processes.processesEachStep.11.Soffset") 
-thetasANG = c(-1)
-
-parametersNamesENV = c("simulationName")
-thetasENV = c("Allee")
+# parametersNamesANG = c("processes.processesEachStep.11.Soffset") 
+# thetasANG = c(-1)
+# 
+# parametersNamesENV = c("simulationName")
+# thetasENV = c("Allee")
 
 # run the GR3D with updated parameter values in processes --------------------------------------------
-runEasyRun(arguments, parametersNamesANG,thetasANG, parametersNamesENV, thetasENV )
+# runEasyRun(arguments, parametersNamesANG,thetasANG, parametersNamesENV, thetasENV )
 
 # .jcall("analysis.EasyRun", "V", "runSimulation", arguments, 
 #        .jarray(parametersNamesANG), .jarray(thetasANG),
@@ -122,42 +136,60 @@ runEasyRun(arguments, parametersNamesANG,thetasANG, parametersNamesENV, thetasEN
 
 
 # call GR3D method to get model outputs ----------------------------------------------
-res1 = exploreEasyRun()
-res1$spawners_features
 
 
-#
-listeSimulation <- list(list(replicat = 1, 
-                             parametersNamesANG = c("processes.processesEachStep.11.Soffset"), 
-                             thetasANG = c(-1),
-                             parametersNamesENV = c("simulationName"), 
-                             thetasENV = c("Allee")),
-                        list(replicat = 1, 
-                             parametersNamesANG = c("processes.processesEachStep.11.Soffset"), 
-                             thetasANG = c(0),
-                             parametersNamesENV = c("simulationName"), 
-                             thetasENV = c("no Allee")))
-
-for (i in 1:length(listeSimulation)) {
-  arguments = c('-simDuration', simDuration, '-simBegin',simBegin,
-                '-timeStepDuration', timeStepDuration, 
-                '-RNGStatusIndex', format(listeSimulation[[i]]$replicat,scientific = FALSE), 
+runSimulation = function(simulationParameter) {
+  arguments = c('-simDuration', 600, '-simBegin',2,
+                '-timeStepDuration', 1, 
+                '-RNGStatusIndex', format(simulationParameter$replicat,scientific = FALSE), 
                 '-groups',"data/input/northeastamerica/fishRIOBasin_Sapidissima_Rjava.xml",
                 '-env',"data/input/northeastamerica/RIOBNneaBasins_Rjava.xml",
                 '-observers',"data/input/northeastamerica/RIO_obs_empty.xml")
   
-  parametersNamesANG = listeSimulation[[i]]$parametersNamesANG
-  thetasANG = listeSimulation[[i]]$thetasANG
-  parametersNamesENV = listeSimulation[[i]]$parametersNamesENV
-  thetasENV = listeSimulation[[i]]$thetasENV
-  
   runEasyRun(arguments, 
-             parametersNamesANG,
-             thetasANG, 
-             parametersNamesENV , 
-             thetasENV )
-  res1 = exploreEasyRun()
-  cat(res1$effective_centroid_latitude, "\n")
+             parametersNamesANG = simulationParameter$parametersNamesANG,
+             thetasANG = simulationParameter$thetasANG, 
+             parametersNamesENV = simulationParameter$parametersNamesENV, 
+             thetasENV = simulationParameter$thetasENV )
+  
+  #tic()
+  result = exploreEasyRun()
+  #toc()
+  return(result)
 }
 
-toto = listeSimulation[[i]]$parametersNamesANG
+
+#============================
+listeSimulation <- list(list(replicat = 1, 
+                             parametersNamesANG = c("processes.processesEachStep.11.Soffset",
+                                                    "processes.processesEachStep.6.pHomingAfterEquil"), 
+                             thetasANG = c(-1, 0.97),
+                             parametersNamesENV = c("simulationName"), 
+                             thetasENV = c("Allee_highHoming")),
+                        
+                        list(replicat = 1, 
+                             parametersNamesANG = c("processes.processesEachStep.11.Soffset",
+                                                    "processes.processesEachStep.6.pHomingAfterEquil"), 
+                             thetasANG = c(-1, 0.75),
+                             parametersNamesENV = c("simulationName"), 
+                             thetasENV = c("Allee_lowHoming")),
+                        
+                        list(replicat = 1, 
+                             parametersNamesANG = c("processes.processesEachStep.11.Soffset",
+                                                    "processes.processesEachStep.6.pHomingAfterEquil"), 
+                             thetasANG = c(0, 0.97),
+                             parametersNamesENV = c("simulationName"), 
+                             thetasENV = c("noAllee_highHoming")),
+                        
+                        list(replicat = 1, 
+                             parametersNamesANG = c("processes.processesEachStep.11.Soffset",
+                                                    "processes.processesEachStep.6.pHomingAfterEquil"), 
+                             thetasANG = c(0, 0.75),
+                             parametersNamesENV = c("simulationName"), 
+                             thetasENV = c("noAllee_lowHoming"))
+                        )
+tic()
+resSimulation = lapply(listeSimulation, runSimulation)
+toc()
+
+save(listeSimulation, resSimulation, file = 'simulation.Rdata')

src/main/java/analysis/AnalyseFishDistribution.java

@@ -254,40 +254,34 @@ public class AnalyseFishDistribution extends AquaNismsGroupProcess<DiadromousFis
 		// initialise the distribution range
 		double southernEdge = northernLimit;
 		double northernEdge = southernLimit;
-		int southernId = -1;
-		int northernId = -1;
-		String southernName = "";
-		String northernName = "";
-		// String southernName = "";
-		// String northernName = "";
+
+		RiverBasin northernBasin = null;
+		RiverBasin southernBasin = null;
+
 		// initialise for centroid
 		TreeMapForCentile latitudeEffective = new TreeMapForCentile();
 		TreeMapForCentile latitudePresence = new TreeMapForCentile();
 
-		String[][] export = new String[2][6];
-
 		for (RiverBasin riverBasin : riverBasins) {
 			double meanLastRecruitment = riverBasin.getLastRecruitments().getMean();
 			if (meanLastRecruitment >= minimumRecruitsForPopulatedBasin) {
 				// the river basin is considered populated
 
-				// NOTE : recruiit number is calulated after thermal tolerance impact
+				// CHECK : recruiit number is calulated after thermal tolerance impact
 				// (which is intreaged in the stock-recruitment relationship)
 
 				// southern edge
 				if (riverBasin.getLatitude() < southernEdge) {
 					// the basin is the new southern edge
 					southernEdge = riverBasin.getLatitude();
-					southernId = riverBasin.getBasin_id();
-					southernName = riverBasin.getName();
+					southernBasin = riverBasin;
 				}
 
 				// northern edge
 				if (riverBasin.getLatitude() > northernEdge) {
 					// the basin is the new northern edge
 					northernEdge = riverBasin.getLatitude();
-					northernId = riverBasin.getBasin_id();
-					northernName = riverBasin.getName();
+					northernBasin = riverBasin;
 				}
 
 				// for distribution centroide computation
@@ -297,29 +291,41 @@ public class AnalyseFishDistribution extends AquaNismsGroupProcess<DiadromousFis
 			}
 		}
 
-		// if the universe is empty (none of basins is populated)
-		if (southernEdge == northernLimit & northernEdge == southernLimit) {
-			southernEdge = (northernLimit + southernLimit) / 2.;
-			northernEdge = southernEdge;
-		}
-
 		// distribution centroids computation
 		double basinCentroid = latitudePresence.calculateMedian();
 		double effectiveCentroid = latitudeEffective.calculateMedian();
 
+		// export
+		String[][] export = new String[2][8];
 		export[0][0] = "southern_basin_id";
 		export[0][1] = "southern_basin_name";
-		export[0][2] = "northern_basin_id";
-		export[0][3] = "northern_basin_name";
-		export[0][4] = "basin_centroid_latitude";
-		export[0][5] = "effective_centroid_latitude";
-
-		export[1][0] = String.valueOf(southernId);
-		export[1][1] = southernName;
-		export[1][2] = String.valueOf(northernId);
-		export[1][3] = northernName;
-		export[1][4] = String.valueOf(basinCentroid);
-		export[1][5] = String.valueOf(effectiveCentroid);
+		export[0][2] = "southern_latitude";
+		export[0][3] = "northern_basin_id";
+		export[0][4] = "northern_basin_name";
+		export[0][5] = "northern_latitude";
+		export[0][6] = "basin_centroid_latitude";
+		export[0][7] = "effective_centroid_latitude";
+
+		if (southernBasin != null & northernBasin != null) {
+			export[1][0] = String.valueOf(southernBasin.getBasin_id());
+			export[1][1] = southernBasin.getName();
+			export[1][2] = String.valueOf(southernBasin.getLatitude());
+			export[1][3] = String.valueOf(northernBasin.getBasin_id());
+			export[1][4] = northernBasin.getName();
+			export[1][5] = String.valueOf(northernBasin.getLatitude());