Pheno + WSG MBaiki

R/find.trait/Mbaiki.R

@@ -17,6 +17,8 @@
 # data-base for Mbaiki species
 # 3. "DensiteBoisSimpleMbaiki.csv" --> An additional file for wood density data
 # 4. "Autour-de-Mbaiki-Releves-par-trait-et-taxon.txt" --> PlanTrait data
+# 5. "getpheno_cofortraits_20140212.csv" --> Phenology
+# 6. "GlobalWoodDensityDatabase.txt" --> Dryad wood density database
 
 library(reshape)
 
@@ -139,17 +141,92 @@ countsup.LeafN # 34
 countsup.SLA # 34
 countsup.WSG # 0
 
+#=============================================================
+# Phenology
+d.pheno <- read.csv2(file="data/raw/Mbaiki/getpheno_cofortraits_20140212.csv",header=TRUE)
+dim(d.pheno)
+names(d.pheno)[8] <- "pheno"
+head(d.pheno)
+head(data.species.3)
+Species.Name.From.List <- function (x) {
+    genus <- x[1]
+    sp <- x[2]
+    lb <- paste(genus,sp,sep=" ")
+    return(lb)
+}
+d.pheno$latin.binomial <- c(unlist(lapply(strsplit(as.character(d.pheno$species),split=" "),Species.Name.From.List)))
+Unique.Paste <- function (x) {
+    r <- paste(unique(x),collapse=" ")
+    return(r)
+}
+Mat.Pheno <- as.data.frame(tapply(as.character(d.pheno$pheno),d.pheno$latin.binomial,Unique.Paste))
+Mat.Pheno$latin.binomial <- row.names(Mat.Pheno)
+row.names(Mat.Pheno) <- NULL
+names(Mat.Pheno) <- c("D_EV","latin.binomial")
+Mat.Pheno$D_EV <- as.character(Mat.Pheno$D_EV)
+str(Mat.Pheno)
+# Set leaf-exchanger to evergreen
+w <- grep("leaf-exchanger",Mat.Pheno$D_EV)
+Mat.Pheno$D_EV[w] <- "EV"
+Mat.Pheno$D_EV[Mat.Pheno$D_EV=="decidue"] <- "D"
+Mat.Pheno$D_EV[Mat.Pheno$D_EV=="sempervirente"] <- "EV"
+Mat.Pheno$D_EV[!(Mat.Pheno$D_EV %in% c("D","EV"))] <- NA
+
+# Merge
+data.species.4 <- merge(data.species.3,Mat.Pheno,
+                        by.x="Species",by.y="latin.binomial",all.x=TRUE)
+
+#=============================================================
+# WSG with Dryad
+
+# Import Dryad
+dryad <- read.table(file="data/raw/Mbaiki/GlobalWoodDensityDatabase.txt",header=TRUE,sep="\t")
+head(dryad)
+names(dryad)
+
+# Mean by species
+dryad.2 <- data.frame(Binomial=as.character(levels(as.factor(dryad$Binomial))),
+                      WSG.dryad.mean=NA,WSG.dryad.sd=NA,WSG.dryad.n=NA)
+dryad.2$WSG.dryad.mean <- as.numeric(tapply(dryad$WSG,dryad$Binomial,mean))
+dryad.2$WSG.dryad.sd <- as.numeric(tapply(dryad$WSG,dryad$Binomial,sd))
+dryad.2$WSG.dryad.n <- as.numeric(tapply(dryad$WSG,dryad$Binomial,length))
+names(dryad.2)
+
+# Merge
+data.species.5 <- merge(data.species.4,dryad.2,by.x="Species",by.y="Binomial",all.x=TRUE)
+
+# Take dryad value if WSG==NA
+names(data.species.5)
+n.case <- sum(is.na(data.species.5$Wood.density.mean) & !is.na(data.species.5$WSG.dryad.mean))
+w <- which(is.na(data.species.5$Wood.density.mean) & !is.na(data.species.5$WSG.dryad.mean))
+data.species.5$Wood.density.mean[w] <- data.species.5$WSG.dryad.mean[w]
+data.species.5$Wood.density.sd[w] <- data.species.5$WSG.dryad.sd[w]
+data.species.5$Wood.density.n[w] <- data.species.5$WSG.dryad.n[w]
+
+# Plots
+hist(data.species.5$Wood.density.mean)
+hist(data.species.5$SLA.mean)
+hist(data.species.5$Leaf.N.mean)
+
+#================
+# Output
+
+# Select the right columns
+names(data.species.5)
+data.species.6 <- data.species.5[,c(1:13,34)]
+names(data.species.6)
+
 # Plots
-hist(data.species.3$Wood.density.mean)
-hist(data.species.3$SLA.mean)
-hist(data.species.3$Leaf.N.mean)
+hist(data.species.6$Wood.density.mean)
+hist(data.species.6$SLA.mean)
+hist(data.species.6$Leaf.N.mean)
 
 #================
 # Output
 
 # Select the right columns
-names(data.species.3)
-data.TRAITS.std <- data.species.3[,c(1:13)]
+names(data.species.6)
+data.TRAITS.std <- data.species.3[,c(1:13,34)]
 names(data.TRAITS.std)
 data.TRAITS.std$Max.height.mean <- NA
 source("R/find.trait/trait-fun.R")