metadataFRANCE and new unique file for France

R/CLIMATE.FRANCE.R

-################################################ LOAD and PROCEED CLIMATIC DATA
-source("./R/FUN.climate.R")
-## Data extracted from C. Piedallu data base with Radition with cloud cover for
-## each plots Piedallu, C, and J Gegout. 2008. “Efficient Assessment of
-## Topographic Solar Radiation to Improve Plant Distribution Models.” Agricultural
-## and Forest Meteorology 148 (11) (October): 1696–1706.
-## doi:10.1016/j.agrformet.2008.06.001.  Temperature and precipitation with
-## temperature corrected by elevation based on Piedallu, C., J. C. Gégout, V.
-## Perez, F. Lebourgeois, and R. Field. 2012. “Soil Water Balance Performs Better
-## Than Climatic Water Variables in Tree Species Distribution Modelling.” Global
-## Ecology and Biogeography.
-## http://onlinelibrary.wiley.com/doi/10.1111/geb.12012/full.
-
-###### LOAD PIDEALLU DATA
-data.CLIM <- read.csv("./data/raw/DataFrance/climate_piedallu/placettesGK_avec_2011.csv", 
-    header = T, sep = "\t", stringsAsFactors = FALSE, dec = ",", na.strings = "")
-print(names(data.CLIM))
-
-data.CLIM$rumkg_500 <- as.numeric(gsub(",", ".", data.CLIM$rumkg_500))
-
-
-######################################### COMPUTE CLIMATIC VARIABLES !!!
-
-### NEED TO COMPUTE DDG5 NEED TO COMPUTE SOIL MAX WATER CONTENT NEED TO COMPUTE PET
-### NEED TO COMPUTE WATER BUDGET
-
-## remove NA lines
-data.CLIM.na <- is.na(data.CLIM[["tmoy6190_1_cor"]])
-data.CLIM2 <- data.CLIM[!data.CLIM.na, ]
-
-### apply function sgdd
-sgdd.vec <- apply(data.CLIM2[, 82:93], MARGIN = 1, FUN = fun.sgdd)
-MeanT.vec <- apply(data.CLIM2[, 82:93], MARGIN = 1, FUN = mean)
-plot(MeanT.vec, sgdd.vec)
-dim(data.CLIM)
-
-################################################# Max Soil Water Content compute based on Piedallu, C., J. C. Gégout, A. Bruand,
-################################################# and I. Seynave. 2011. “Mapping Soil Water Holding Capacity over Large Areas to
-################################################# Predict Potential Production of Forest Stands.” Geoderma 160 (3): 355–366.
-
-### read data texture as in Piedallu et al. 2011
-data.texture <- read.table("./data/raw/DataFrance/climate_piedallu/texture.txt", 
-    header = T)
-### load ecological data
-load(file = "./data/process/ecologie_tot.Rdata")
-head(ecologie_tot)
-
-codeprof <- c(2.5, 10, 20, 30, 40, 50, 60, 70, 80, 92.5)  # code prof en cm
-codecaillou <- c(2.5, 10, 20, 30, 40, 50, 60, 70, 80, 90, 97.5)  ## code percentage en %
-
-# compute swhc
-swhc <- fun.swhc(affroc = ecologie_tot$affroc, cailloux = ecologie_tot$cailloux, 
-    text2 = ecologie_tot$text2, text1 = ecologie_tot$text1, prof2 = ecologie_tot$prof2, 
-    prof1 = ecologie_tot$prof1, codeprof, codecaillou, data.texture)
-swhc[is.na(ecologie_tot$prof2)] <- NA
-
-### add to ecological data based
-ecologie_tot$SWHC <- swhc
-
-
-################################## COMPUTE PET WITH TURC FORMULA unit to convert radneb61_ from J/cm2/month in
-################################## MJ/m2/day /100/30 then to convert in KJ/m2/day as in Nick formula *1000
-
-## RAD and Temperature of the 12 months
-radneb61_1to12 <- 66:77
-tmoy6190_1_cor.1to12 <- 82:93
-
-### apply in parallel
-library(doParallel)
-registerDoParallel(cores = 6)  ## affect automaticaly half of the core detected to the foreach
-getDoParWorkers()  ## here 8 core so 4 core if want to use more registerDoParallel(cores=6)
-
-PET.matrix <- foreach(i = 1:length(data.CLIM$idp), .combine = rbind) %dopar% {
-    fun.PET(i, rad = data.CLIM[, radneb61_1to12], temp = data.CLIM[, tmoy6190_1_cor.1to12])
-}
-
-PET.matrix <- PET.matrix[!data.CLIM.na, ]
-PET.matrix[PET.matrix < 0] <- 0  ## affect zero if negative PET
-
-## plot to check PET computed by me vs PET of Christian par(mfrow=c(3,4)) for (i
-## in 1:12) {plot(PET.matrix[,i],data.CLIM2[,i+48]) ; lines(0:100,0:100)}
-
-colnames(PET.matrix) <- paste("PET.cor.", 1:12, sep = "")
-############## MERGE CLIMATE and PET
-data.CLIM2 <- cbind(data.CLIM2, PET.matrix, sgdd = sgdd.vec)
-
-### MERGE WITH ECOLOGICAL DATA
-ecologie.clim <- merge(ecologie_tot, data.CLIM2, by = "idp", all.x = T)
-dim(ecologie_tot)
-dim(ecologie.clim)
-names(ecologie.clim)
-
-
-ecologie.clim2 <- ecologie.clim[!is.na(ecologie.clim$PET.cor.1) & !is.na(ecologie.clim$SWHC), 
-    ]
-
-########################################################################################### COMPUTE WATER BUDGET
-
-## ### test function
-## fun.WaterBudget(i=16,prcp.m=(ecologie.clim2[,paste('prec6190_',1:12,sep='')]),
-## PET.m=(ecologie.clim2[,paste('PET.cor.',1:12,sep='')]),
-## Ta.m=(ecologie.clim2[,c('tmoy6190_1_cor',paste('tmoy6190_1_cor.',1:11,sep=''))]),
-## SWHC.v=(ecologie.clim2[ ,'SWHC']),n=2)
-
-
-### apply function in parallel
-library(doParallel)
-registerDoParallel(cores = 6)  ## affect automaticaly half of the core detected to the foreach
-getDoParWorkers()  ## here 8 core so 4 core if want to use more registerDoParallel(cores=6)
-
-WBWS.matrix <- foreach(i = 1:length(ecologie.clim2$idp), .combine = rbind) %dopar% 
-    {
-        fun.WaterBudget(i, prcp.m = (ecologie.clim2[, paste("prec6190_", 1:12, sep = "")]), 
-            PET.m = (ecologie.clim2[, paste("PET.cor.", 1:12, sep = "")]), Ta.m = (ecologie.clim2[, 
-                c("tmoy6190_1_cor", paste("tmoy6190_1_cor.", 1:11, sep = ""))]), 
-            SWHC.v = (ecologie.clim2[, "SWHC"]), n = 2)
-    }
-
-### MERGE all and saved
-WBWS.matrix2 <- cbind(idp = ecologie.clim2$idp, WBWS.matrix)
-ecologie.clim.data <- merge(ecologie.clim, WBWS.matrix2, by = "idp", all.x = T)
-
-##### change tplant not good format
-load("./data/process/placette_tot.Rdata")
-ecologie.clim.data$tplant <- placette_tot$tplant
-
-### Compute mean T and annual sum of precip
-
-ecologie.clim.data$MAT <- apply(ecologie.clim.data[, 114:125], MARGIN = 1, FUN = mean)
-ecologie.clim.data$SAP <- apply(ecologie.clim.data[, 69:80], MARGIN = 1, FUN = sum)
-
-
-saveRDS(ecologie.clim.data, file = "./data/process/ecologie.clim.data.rds")
-
-
-
-
-
-
-######################################################### FIGURES OF CLIMATIC DATA
-ecologie.clim.data <- readRDS("./data/process/ecologie.clim.data.rds")
-names(ecologie.clim.data)
-
-### check climatic data
-
-pdf("./figs/sgdd.tmin.map.pdf")
-par(mfrow = c(2, 2))
-plot(ecologie.clim.data$xl93, ecologie.clim.data$yl93, col = rev(heat.colors(10))[cut(ecologie.clim.data$sgdd, 
-    quantile(ecologie.clim.data$sgdd, probs = (0:10)/10, na.rm = T), labels = F)], 
-    cex = 0.2, pty = "s", xlab = NA, ylab = NA, main = "SGDD")
-
-plot(ecologie.clim.data$xl93, ecologie.clim.data$yl93, col = rev(heat.colors(10))[cut(ecologie.clim.data$tmin6190_min_cor, 
-    quantile(ecologie.clim.data$tmin6190_min_cor, probs = (0:10)/10, na.rm = T), 
-    labels = F)], cex = 0.2, pty = "s", xlab = NA, ylab = NA, main = "Tmin")
-plot(ecologie.clim.data$tmin6190_min_cor, ecologie.clim.data$sgdd, cex = 0.2, xlab = "Tmin", 
-    ylab = "SGDD")
-dev.off()
-
-pdf("./figs/Water.map.pdf")
-par(mfrow = c(2, 2), mar = c(1, 1, 1, 1))
-plot(ecologie.clim.data$xl93, ecologie.clim.data$yl93, col = rev(colorRampPalette(c("blue", 
-    "red"))(10))[cut(ecologie.clim.data$WB.y, quantile(ecologie.clim.data$WB.y, probs = (0:10)/10, 
-    na.rm = T), labels = F)], cex = 0.2, pty = "s", xlab = NA, ylab = NA)
-plot(ecologie.clim.data$xl93, ecologie.clim.data$yl93, col = rev(colorRampPalette(c("blue", 
-    "red"))(10))[cut(ecologie.clim.data$WB.s, quantile(ecologie.clim.data$WB.s, probs = (0:10)/10, 
-    na.rm = T), labels = F)], cex = 0.2, pty = "s", xlab = NA, ylab = NA)
-plot(ecologie.clim.data$xl93, ecologie.clim.data$yl93, col = rev(colorRampPalette(c("blue", 
-    "red"))(10))[cut(ecologie.clim.data$WS.y, quantile(ecologie.clim.data$WS.y, probs = (0:10)/10, 
-    na.rm = T), labels = F)], cex = 0.2, pty = "s", xlab = NA, ylab = NA)
-plot(ecologie.clim.data$xl93, ecologie.clim.data$yl93, col = rev(colorRampPalette(c("blue", 
-    "red"))(10))[cut(ecologie.clim.data$WS.s, quantile(ecologie.clim.data$WS.s, probs = (0:10)/10, 
-    na.rm = T), labels = F)], cex = 0.2, pty = "s", xlab = NA, ylab = NA)
-dev.off()
-
-pdf("./figs/Water.var,cor.pdf")
-par(mfrow = c(2, 2))
-plot(ecologie.clim.data[["WB.y"]], ecologie.clim.data[["WS.y"]], xlab = "WB year", 
-    ylab = "ratio AET/D year", cex = 0.2)
-plot(ecologie.clim.data[["WB.s"]], ecologie.clim.data[["WS.s"]], xlab = "WB growing season", 
-    ylab = "ratio AET/D growing season", cex = 0.2)
-plot(ecologie.clim.data[["WB.s"]], ecologie.clim.data[["WB.y"]], xlab = "WB growing season", 
-    ylab = "WB growing year", cex = 0.2)
-plot(ecologie.clim.data[["WS.s"]], ecologie.clim.data[["WS.y"]], xlab = "ratio AET/D growing season", 
-    ylab = "ratio AET/D year", cex = 0.2)
-dev.off()
-pdf("./figs/sgdd.water.cor.pdf")
-plot(ecologie.clim.data[["sgdd"]], ecologie.clim.data[["WS.y"]], xlab = "SGDD", ylab = "ratio AET/D year", 
-    cex = 0.2)
-dev.off()
-
-### DO PCA OF CLIMATIC DATA
-
-data.prc <- prcomp(ecologie.clim.data[apply(is.na(ecologie.clim.data[, c("sgdd", 
-    "tmin6190_min_cor", "WB.s", "WS.s")]), MARGIN = 1, FUN = sum) < 1, c("sgdd", 
-    "tmin6190_min_cor", "WB.s", "WS.s")], na.action = na.omit, scale = T)
-summary(data.prc)
-scores <- data.prc$x
-pdf("./figs/climate.pca.pdf")
-biplot(data.prc, pch = 1, xlabs = rep(".", length(data.prc$x[, 1])), ylabs = c("SGDD", 
-    "Tmin", "WB", "WS"))
-text(150, 180, labels = paste("Var PC1 ", ((summary(data.prc)))$importance[2, 1], 
-    sep = ""))
-text(150, 165, labels = paste("Var PC2 ", ((summary(data.prc)))$importance[2, 2], 
-    sep = ""))
-dev.off()
-
-
-##### FIGS on elevation correction of temperature done by Christian map of diff
-##### between mean altitude of the 1x1km cell and actual elevation of the plots
-pdf("./figs/map.error.alti.pdf")
-plot(data.CLIM$xl2, data.CLIM$yl2, col = "grey", cex = 0.3, xlab = "X", ylab = "Y")
-data.temp <- data.CLIM[data.CLIM$diff..altIFN...mnt50 < (-100) | (data.CLIM$diff..altIFN...mnt50 > 
-    100), ]
-points(data.temp$xl2, data.temp$yl2, col = c("red", "coral3", "coral", "grey", "coral", 
-    "coral3", "red")[cut(data.temp$diff..altIFN...mnt50, breaks = c(-500, -300, -200, 
-    -100, 100, 200, 300, 500), labels = F)], cex = 0.5, pch = 1)
-dev.off()
-
-##### PLOT HIST OF ALL VARIABLES
-pdf("./figs/climatvar.hist.pdf")
-par(mfrow = c(3, 4))
-for (i in 37:48) hist(data.CLIM[, i], xlab = "Monthly Precip (mm)", main = names(data.CLIM)[i])
-
-par(mfrow = c(3, 4))
-for (i in 49:60) hist(data.CLIM[, i], xlab = "PET (mm)", main = names(data.CLIM)[i])
-
-par(mfrow = c(3, 4))
-for (i in 66:77) hist(data.CLIM[, i], xlab = "Radiation (?)", main = names(data.CLIM)[i])
-
-par(mfrow = c(3, 4))
-for (i in 82:93) hist(data.CLIM[, i], xlab = "temperature (C)", main = names(data.CLIM)[i])
-dev.off()
-
-pdf("./figs/xyplot.Tunco.Tcor.pdf")
-par(mfrow = c(3, 4))
-for (i in 1:12) plot(data.CLIM[, (23:34)[i]], data.CLIM[, (82:94)[i]], xlab = "temperature (C) uncorrected", 
-    ylab = "temperature (C) corrected", main = names(data.CLIM)[(23:34)[i]])
-dev.off() 

merge.data.FRANCE.R

 ############################################# MERGE FRENCH DATA
 source("./R/format.function.R")
-## source('./R/READ.DATA.NFI.FRANCE.R') need to be run if no already doen (long
-## ...)  source('./R/CLIMATE.FRANCE.R')
-
-########################################################################### READ DATA (test)
-
-### read individuals tree data
-load("./data/process/arbre.ALIVE.DEAD2.Rdata")
-
-### read climate
-ecologie.clim.data <- readRDS("./data/process/ecologie.clim.data.rds")
-#### merge
-dataIFN.FRANCE.t <- merge(arbre.ALIVE.DEAD2, subset(ecologie.clim.data, select = c("idp", 
-    "SER", "sgdd", "WB.y", "WB.s", "WS.y", "WS.s", "MAT", "SAP")), by = "idp")
-rm(arbre.ALIVE.DEAD2, ecologie.clim.data)
-
-#### load plot data and merge
-load("./data/process/placette_tot.Rdata")
-dataIFN.FRANCE <- merge(dataIFN.FRANCE.t, placette_tot[, names(placette_tot) != "YEAR"], 
-    by = "idp")
-rm(placette_tot, dataIFN.FRANCE.t)
 
+################################ READ DATA (test)
+dataIFN.FRANCE <- read.csv("./data/raw/DataFrance/dataIFN.FRANCE.csv", stringsAsFactors = FALSE)
 ### read IFN species names and clean
-species.clean <- fun.clean.species.tab(read.csv("./data/species.list/species.csv", 
+species.clean <- fun.clean.species.tab(read.csv("./data/raw/DataFrance/species.csv", 
     sep = "\t", stringsAsFactors = FALSE))
 
 ### read TRY data

ms/metadata/France/_file_index.csv

-filename,sep,skip,contents
-2005/arbres_foret_2005.csv,c,0, 
-2005/arbres_morts_foret_2005.csv,c,0, 
-2005/arbres_peupleraie_2005.csv,c,0, 
-2005/documentation_2005-2.csv,c,0, 
-2005/documentation_flore.csv,c,0, 
-2005/ecologie_2005.csv,c,0, 
-2005/flore_2005.csv,c,0, 
-2005/placettes_foret_2005.csv,c,0, 
-2005/placettes_peupleraie_2005.csv,c,0, 
-2006/arbres_foret_2006.csv,c,0, 
-2006/arbres_morts_foret_2006.csv,c,0, 
-2006/arbres_peupleraie_2006.csv,c,0, 
-2006/couverts_foret_2006.csv,c,0, 
-2006/documentation_2006-2.csv,c,0, 
-2006/documentation_flore.csv,c,0, 
-2006/ecologie_2006.csv,c,0, 
-2006/flore_2006.csv,c,0, 
-2006/placettes_foret_2006.csv,c,0, 
-2006/placettes_peupleraie_2006.csv,c,0, 
-2007/arbres_foret_2007.csv,c,0, 
-2007/arbres_morts_foret_2007.csv,c,0, 
-2007/arbres_peupleraie_2007.csv,c,0, 
-2007/couverts_foret_2007.csv,c,0, 
-2007/documentation_2007-2.csv,c,0, 
-2007/documentation_flore.csv,c,0, 
-2007/ecologie_2007.csv,c,0, 
-2007/flore_2007.csv,c,0, 
-2007/placettes_foret_2007.csv,c,0, 
-2007/placettes_peupleraie_2007.csv,c,0, 
-2008/arbres_foret_2008.csv,c,0, 
-2008/arbres_morts_foret_2008.csv,c,0, 
-2008/arbres_morts_peupleraie_2008.csv,c,0, 
-2008/arbres_peupleraie_2008.csv,c,0, 
-2008/couverts_foret_2008.csv,c,0, 
-2008/documentation_2008-2.csv,c,0, 
-2008/documentation_flore.csv,c,0, 
-2008/ecologie_2008.csv,c,0, 
-2008/flore_2008.csv,c,0, 
-2008/placettes_foret_2008.csv,c,0, 
-2008/placettes_peupleraie_2008.csv,c,0, 
-2009/arbres_foret_2009.csv,c,0, 
-2009/arbres_morts_foret_2009.csv,c,0, 
-2009/arbres_morts_peupleraie_2009.csv,c,0, 
-2009/arbres_peupleraie_2009.csv,c,0, 
-2009/couverts_foret_2009.csv,c,0, 
-2009/documentation_2009-2.csv,c,0, 
-2009/documentation_flore.csv,c,0, 
-2009/ecologie_2009.csv,c,0, 
-2009/flore_2009.csv,c,0, 
-2009/placettes_foret_2009.csv,c,0, 
-2009/placettes_peupleraie_2009.csv,c,0, 
-2010/arbres_foret_2010.csv,c,0, 
-2010/arbres_morts_foret_2010.csv,c,0, 
-2010/arbres_morts_peupleraie_2010.csv,c,0, 
-2010/arbres_peupleraie_2010.csv,c,0, 
-2010/couverts_foret_2010.csv,c,0, 
-2010/documentation_2010.csv,c,0, 
-2010/documentation_flore.csv,c,0, 
-2010/ecologie_2010.csv,c,0, 
-2010/flore_2010.csv,c,0, 
-2010/placettes_foret_2010.csv,c,0, 
-2010/placettes_peupleraie_2010.csv,c,0, 
-2011/arbres_foret_2011.csv,c,0, 
-2011/arbres_morts_foret_2011.csv,c,0, 
-2011/arbres_morts_peupleraie_2011.csv,c,0, 
-2011/arbres_peupleraie_2011.csv,c,0, 
-2011/couverts_foret_2011.csv,c,0, 
-2011/documentation_2011.csv,c,0, 
-2011/documentation_flore.csv,c,0, 
-2011/ecologie_2011.csv,c,0, 
-2011/flore_2011.csv,c,0, 
-2011/placettes_foret_2011.csv,c,0, 
-2011/placettes_peupleraie_2011.csv,c,0, 
-altitude/SER_alti_2011.csv,c,0, 
-altitude/SER_alti.csv,c,0, 
-climate_piedallu/placettesGK_avec 2011.csv,c,0, 
-climate_piedallu/placettesGK2.csv,c,0, 
-climate_piedallu/texture.txt,t,0, 
-cycle3/arbres2.txt,t,0, 
-cycle3/data.arbre.tot.txt,t,0, 
-cycle3/speciesnames.txt,t,0, 
+filename	sep	skip	contents
+dataIFN.FRANCE.csv	t	0	data for IFN France with climatic variables
+species.csv	t	0	species code and species Latin name

ms/metadata/France/_site_details.csv

-Item,Details
-contact name,
-contact email,
-contact affiliation,
-dataset name,
-country,
-climate,
-vegetation type,
-minimum tree size,
-field methodology,
-trait information,
-key references,
+Item	Details
+contact name	Georges Kunstler
+contact email	georges.kunstler@gmail.com
+contact affiliation	Irstea, UR Mountain Ecosystems, St-Martin-d'H?res, France & Department of Biological Sciences, Macquarie University, Sydney, NSW 2109, Australia
+dataset name	French National Forest Inventory
+country	France
+climate	The climate of the lowlands varies from Mediterranean through oceanic to continental
+vegetation type	Mediterranean, temperate and mountain forests
+minimum tree size	7.5 cm
+field methodology	Data extracted from http://inventaire-forestier.ign.fr/spip/ . The French National Forest Inventory (http://inventaire-forestier.ign.fr) comprises a network of temporary plots established on a a sample of grid of approximately 1000 x 1000 m (plot randomly located in a square of 450m around the centre of the cell) covering the French national territory with contrasting climatic (collected between 2005 and 2011). The climate of the lowlands varies from Mediterranean through oceanic to continental, but the climate is also strongly affected by the elevation in mountain areas. For each measured tree, stem circumference, species, status (alive or died in the last 5 years), and radial growth over five years were recorded.  The radial growth was determined from two short cores taken at breast height.
+trait information	extracted from TRY
+key references	http://inventaire-forestier.ign.fr/spip/

ms/metadata/France/files/2005_arbres_foret_2005.csv

-use,var,units,description
-0,idp.a.veget.espar.ori.lib.forme.tige.c13.ir5.htot.q1.q2.q3.r.lfsd.v.w,,

ms/metadata/France/files/2005_arbres_morts_foret_2005.csv

-use,var,units,description
-0,idp.a.espar.ori.veget.c0.v.w,,

ms/metadata/France/files/2005_arbres_peupleraie_2005.csv

-use,var,units,description
-0,idp.a.veget.espar.clon.ori.c13.htot.q1.q2.q3.r.lfsd.v.w,,

ms/metadata/France/files/2005_documentation_2005-2.csv

-use,var,units,description
-0,donnee.code.libelle,,

ms/metadata/France/files/2005_documentation_flore.csv

-use,var,units,description
-0,codtax.nomlatin.lib_ref.numnomen,,

ms/metadata/France/files/2005_ecologie_2005.csv

-use,var,units,description
-0,idp.dateeco.obsdate.topo.obstopo.pent2.expo.masque.humus.obspedo.roche.obsroc.affroc.afpla.cailloux.cai40.text2.text1.prof2.prof1.obsprof.pcalc.pcalf.pox.ppseudo.pgley.obshydr.tsol.lign1.lign2.herb.obsveget,,

ms/metadata/France/files/2005_flore_2005.csv

-use,var,units,description
-0,idp.codtax.abond,,

ms/metadata/France/files/2005_placettes_foret_2005.csv

-use,var,units,description
-0,idp.xl93.yl93.dep.csa.uta.tm2.dc.tplant.dist.acces.pentn.portn.esspre.cac.ess_age_1,,

ms/metadata/France/files/2005_placettes_peupleraie_2005.csv

-use,var,units,description
-0,idp.xl93.yl93.dep.csa.uta.dc.dist.portn.cac,,

ms/metadata/France/files/2006_arbres_foret_2006.csv

-use,var,units,description
-0,idp.a.veget.espar.ori.lib.forme.tige.mortb.c13.ir5.htot.q1.q2.q3.r.lfsd.v.w,,

ms/metadata/France/files/2006_arbres_morts_foret_2006.csv

-use,var,units,description
-0,idp.a.espar.ori.veget.c0.v.w,,

ms/metadata/France/files/2006_arbres_peupleraie_2006.csv

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ms/metadata/France/files/2006_couverts_foret_2006.csv

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ms/metadata/France/files/2006_documentation_2006-2.csv

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ms/metadata/France/files/2006_documentation_flore.csv

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