diff --git a/merge.data.NSW.R b/merge.data.NSW.R
index 4dc6dc0e8c6f45050c46bf8ed372dc36c90cdbfc..76b800942b2681273d243c2132687390508592b3 100644
--- a/merge.data.NSW.R
+++ b/merge.data.NSW.R
@@ -5,17 +5,16 @@ library(reshape)
 
 ######################### READ DATA read individuals tree data
 data.nswbrc <- read.csv("./data/raw/DataNSW/NSW_data_BRcontrols.csv", header = TRUE, 
-    stringsAsFactors = FALSE, sep = "\t")
+    stringsAsFactors = FALSE)
 data.nswbrc$Date.of.measure <- as.vector(sapply(data.nswbrc$Date.of.measure, function(x) {
     unlist(strsplit(x, "/"))[3]
 }))  ## Extract the years only
 data.nswbrt <- read.csv("./data/raw/DataNSW/NSW_data_BRtreatments.csv", header = TRUE, 
-    stringsAsFactors = FALSE, sep = "\t")
+    stringsAsFactors = FALSE)
 data.nswbrt$Date.of.measure <- as.vector(sapply(data.nswbrt$Date.of.measure, function(x) {
     unlist(strsplit(x, "/"))[3]
 }))  ## Extract the years only
-data.nswbs1 <- read.csv("./data/raw/DataNSW/NSW_data_BS1.csv", header = TRUE, stringsAsFactors = FALSE, 
-    sep = "\t")
+data.nswbs1 <- read.csv("./data/raw/DataNSW/NSW_data_BS1.csv", header = TRUE, stringsAsFactors = FALSE)
 data.nswbs1$Date.of.measure <- as.character(format(as.Date(data.nswbs1$Date.of.measure, 
     format = "%d-%b-%y"), format = "%d/%b/%Y"))
 data.nswbs1$Date.of.measure <- as.vector(sapply(data.nswbs1$Date.of.measure, function(x) {
@@ -24,8 +23,7 @@ data.nswbs1$Date.of.measure <- as.vector(sapply(data.nswbs1$Date.of.measure, fun
 
 ## data.nswbs2 has a different format to the other datasets, so format to match
 ## the above
-data.nswbs2 <- read.csv("./data/raw/DataNSW/NSW_data_BS2.csv", header = TRUE, stringsAsFactors = FALSE, 
-    sep = "\t")
+data.nswbs2 <- read.csv("./data/raw/DataNSW/NSW_data_BS2.csv", header = TRUE, stringsAsFactors = FALSE)
 data.nswbs2$Plot <- apply(data.nswbs2[, 1:2], 1, paste, collapse = "")
 
 data.nswbs2$Subplot <- NULL
@@ -40,8 +38,7 @@ data.nswbs22[["DBH.cm..1988."]] <- data.nswbs22[["DBH.cm..2000."]] <- NULL
 data.nswbs2 <- data.nswbs22[, c(1:5, 8:9, 7, 6)]
 rm(data.nswbs22)
 
-data.nswtnd <- read.csv("./data/raw/DataNSW/NSW_data_TND.csv", header = TRUE, stringsAsFactors = FALSE, 
-    sep = "\t")
+data.nswtnd <- read.csv("./data/raw/DataNSW/NSW_data_TND.csv", header = TRUE, stringsAsFactors = FALSE)
 data.nswtnd$Date.of.measure <- as.character(format(as.Date(data.nswtnd$Date.of.measure, 
     format = "%d-%b-%y"), format = "%d/%b/%Y"))
 data.nswtnd$Date.of.measure <- as.vector(sapply(data.nswtnd$Date.of.measure, function(x) {