#Read matrix of species per traits:
trait<-read.table("matrixtraits.txt",header=TRUE,sep="\t",dec=",")
traitdata<-trait[,-1]
rownames(traitdata)<-trait[,1]

#Read matrix of abundance per species in 12 plots or communities: 
abund<-read.table("matrixabundtraits.txt",header=TRUE,sep="\t",dec=",")
abundata<-abund[,-1]
rownames(abundata)<-abund[,1]
library(FD)

#Height:
traitdata1<-traitdata[-c(52,53,59),]
abundata1<-abundata[,-c(52,53,59)]
functindicesheight<-dbFD(traitdata1["Height"],abundata1)
write.table(functindicesheight$RaoQ,file="Raoheight.txt",sep="\t")
write.table(functindicesheight$CWM,file="CWMheight.txt",sep="\t")

#LDMC
traitdata1<-traitdata[-c(8,13,14,26,27,31,36,43,45,52,53,57,59,60,62,65,73,78,80,86:87,89,93,105:106,108,113,118,125),]
abundata1<-abundata[,-c(8,13,14,26,27,31,36,43,45,52,53,57,59,60,62,65,73,78,80,86:87,89,93,105:106,108,113,118,125)]
functindicesLDMC<-dbFD(traitdata1["LDMC"],abundata1)
write.table(functindicesLDMC$RaoQ,file="RaoLDMC.txt",sep="\t")
write.table(functindicesLDMC$CWM,file="CWMLDMC.txt",sep="\t")

#SLA
traitdata1<-traitdata[-c(8,13,31,36,43,45,52,53,57,59,60,62,73,86:87,89,93,105:106,108,125),]
abundata1<-abundata[,-c(8,13,31,36,43,45,52,53,57,59,60,62,73,86:87,89,93,105:106,108,125)]
functindicesSLA<-dbFD(traitdata1["SLA"],abundata1)
write.table(functindicesSLA$RaoQ,file="RaoSLA.txt",sep="\t")
write.table(functindicesSLA$CWM,file="CWMSLA.txt",sep="\t")

#LA
traitdata1<-traitdata[-c(52,53,59),]
abundata1<-abundata[,-c(52,53,59)]
functindicesLA<-dbFD(traitdata1["LA"],abundata1)
write.table(functindicesLA$RaoQ,file="RaoLA.txt",sep="\t")
write.table(functindicesLA$CWM,file="CWMLA.txt",sep="\t")

#SM:
traitdata1<-traitdata[-c(3,13,18,31,45,52,53,59,62,74,79,87,89,93,105,106,108,117,119),]
abundata1<-abundata[,-c(3,13,18,31,45,52,53,59,62,74,79,87,89,93,105,106,108,117,119)]
functindicesSM<-dbFD(traitdata1["SM"],abundata1)
write.table(functindicesSM$RaoQ,file="RaoSM.txt",sep="\t")
write.table(functindicesSM$CWM,file="CWMSbien.txt",sep="\t")