diff --git a/R/find.trait/NVS.R b/R/find.trait/NVS.R
index 7336f4bfd0049d42452268b3a5fb443d1e292a65..eebacb151d68ac3682419a1b4362e0bace4cd99d 100644
--- a/R/find.trait/NVS.R
+++ b/R/find.trait/NVS.R
@@ -27,7 +27,7 @@ data.trait$SLA.mean <- 1/data.trait$lma.gm2; data.trait$SLA.mean <- data.trait$S
 data.trait$SLA.sd <- NA
 data.trait$Wood.density.mean <- data.trait$wood; data.trait$wood <- NULL
 data.trait$Wood.density.sd <- NA
-data.trait$Max.height.mean <- log10(data.trait$height.m); data.trait$height.m <- NULL
+data.trait$Max.height.mean <- data.trait$height.m; data.trait$height.m <- NULL
 data.trait$Max.height.sd <- NA
 
 ## read traits from TRY
diff --git a/R/format.data/NVS.R b/R/format.data/NVS.R
index 7f09974b0c92b2490375e03c058c5f3e0c0bee63..e9d47dddb94803ae40d45a0b2e8a54cafedccb92 100644
--- a/R/format.data/NVS.R
+++ b/R/format.data/NVS.R
@@ -67,8 +67,8 @@ rm(data.sp, data.sp2)
 # library(RColorBrewer)
 # library(rworldmap)
 # newmap <- getMap(resolution = 'coarse')
-# ## # different resolutions available
-# plot(newmap,xlim=c(166,177),ylim=c(-34,-47))
+# # ## # different resolutions available
+# plot(newmap,xlim=c(166,177),ylim=c(-47,-34))
 # ecoreg <- factor(data.nz$ecocode); levels(ecoreg) <- mycols <- brewer.pal(length(levels(ecoreg)), "Set1")
 # points(data.nz[['Lon']],data.nz[['Lat']],pty='.',cex=.2,col = as.character(ecoreg))
 # legend('bottomleft', col = mycols, legend = names(table(data.nz$ecocode)), pch = rep(19,length(levels(ecoreg)))) 
@@ -87,4 +87,6 @@ vec.abio.var.names <- c("MAT", "MAP")
 vec.basic.var <- c("obs.id","tree.id", "sp", "sp.name","cluster","plot", "ecocode", "D", "G", "dead", 
     "year", "htot", "Lon", "Lat", "perc.dead","weights","census")
 data.tree <- subset(data.nz, select = c(vec.basic.var, vec.abio.var.names))
+
+
 write.csv(data.tree,file="output/formatted/NVS/tree.csv",row.names = FALSE)