diff --git a/DEM2POINT.R b/DEM2POINT.R
index 6aaca5320f826f5dfd8544918f3b7bcc61881220..041a51426738d27f2e54529ab256fd455eb7f119 100644
--- a/DEM2POINT.R
+++ b/DEM2POINT.R
@@ -1,110 +1,117 @@
-# 1. PREPARATION #-------------------------------------
-# DO ONLY ONCE
-
-# package to load many pckgs (to show how2install pckg)
-install.packages("pacman") # install from web to PC
-library(pacman) # load(attach) from PC's library folder
-
-pacman::p_load(raster, maptools, sp, dismo, rasterVis, rgdal)
-# notice: when '#' the line is "neutral = Not run"
-
-# set path to DEM-raster
-rasterpath<-"C:/Users/CHORO_04/Onedrive/PRACTICALS/AREALKUNDE/SDM"
-# set path to species dots shapefile
-
-# 2. GET THE DATA #-----------------------------------------
-# DEM raster
-setwd(rasterpath)
-elev <- raster("CHELSA-DEM.tif") #from the defined path
-
-# Create Study area "SWA"
-ext <- extent(elev) # get extent of DEM raster
-SWA <- as(ext, 'SpatialPolygons')#convert ext to a SpatialPolygon
-proj4string(SWA) <- CRS("+init=epsg:4326") #define KBS WGS84=4326
-
-# Species occurrences
-setwd("C:/Users/CHORO_04/OneDrive/AREALKUNDE/PRACTICALS/SPEC01")
-# the resp. path to species dots
-# you only need to change *THIS PATH* and *ELEVATION* range for
-# all next species
-
-dots <- maptools::readShapePoints("DOTS.shp")
-proj4string(dots) <- CRS("+init=epsg:4326") #define KBS WGS84=4326
-
-# 3. OUT GBIF DOTS #----------------------------------
-SWA_DOTS <- dots[SWA,] # select 341 which 'in SWA'
-# = like the 'select by location' step in QGIS
-
-# jetzt die selektieren, die "CTS-SWA..." sind
-
-# Vorher: Replacing NA's with "None" for all SWA_DOTS
-# muss aber leider vorher als level hinzugefuegt werden
-# get levels and add "None"
-levels <- levels(SWA_DOTS@data$datasetNam)
-levels[length(levels) + 1] <- "None"
-# refactor datasetNam to include "None" as level
-# and replace NA with "None"
-SWA_DOTS@data$datasetNam <- factor(SWA_DOTS@data$datasetNam,
- levels = levels)
-SWA_DOTS@data$datasetNam[is.na(SWA_DOTS@data$datasetNam)] <- "None"
-
-# jetzt endlich unsere 91 CTS auswaehlen
-CTS_DOTS<-SWA_DOTS[(SWA_DOTS@data$datasetNam == "CTS-SWA-9-1"),]
-
-# 4. EXTRACT DEM #------------------------------------------
-
-# define circles with a radius of 15 km around SWA_DOTS
-# with "dismo::" I make sure the "circles" function works
-# by calling it directly from dismo-package
-BUFF <- dismo::circles(CTS_DOTS,d=15000,lonlat=T)
-
-# everybody: draw 10000 random points within BUFF circles
-SAMPLE <- spsample(BUFF@polygons, 10000, type='random')
-# das dauert am laengsten/takes the longest time
-
-# extract DEM values at point positions
-ElevDots<-extract(elev,SAMPLE,df=T) # "point sampling tool"
-hist(ElevDots$CHELSA.DEM) # to see the data
-
-# 5. SUBSET BY DEM #--------------------------
-
-# In CTS-SWA: "Pergularia tomentosa is a light requiring species
-# occurring in open places, insolated, and on dry sandy or
-# gravelly-sandy-clayey soils, frequently together with Artemisia
-# and various semishrublets (suffrutex). In vertical distribution
-# it has been found in depressions around the Dead Sea, more or
-# less at -250 m and usually it does not grow beyond 900-1200 m
-# elevation. The most elevated localities have been found in
-# Pakistan at 1330 m and in Afghanistan at 1 500-1600 m."
-# -> In this case I choose -250 to 1250m and neglect the outliers.
-
-# Join the (spatial)SAMPLE and ElevDots data (both n = 10000)
-SAMPLEDOTS <- SpatialPointsDataFrame(SAMPLE, ElevDots)
-summary(SAMPLEDOTS)
-# Subsetting an SPDF in R is easy.
-# You can do it just like a normal dataframe.
-# remember "CHELSA.DEM" is the elevation
-SMPLDTS<-SAMPLEDOTS[(SAMPLEDOTS@data$CHELSA.DEM > -250),]
-SMPLDT <-SMPLDTS[(SMPLDTS@data$CHELSA.DEM < 1250),]
-hist(SMPLDT@data$CHELSA.DEM,
- col="red",
- add=T) # to control
-
-# 6. PLOT THE DATA #-----------------------------------------
-plot(SWA)
-plot(elev, add=T)
-plot(SWA, add=T)
-plot(dots,col="black",pch=20,cex=0.5,add=T)
-plot(CTS_DOTS, col="red",pch=16,cex=0.5,add=T)
-plot(BUFF, cex=5, add=T) #enlarged by 5
-plot(SMPLDT, col="blue", pch=16,cex=0.1,add=T)
-
-# 7. PLOT 3D FOR FUN #--------------------------------------
-require(rasterVis)
-plot3D(elev,
- maxpixels=1e6,
- zfac=0.1,
- drape=NULL,
- col=terrain.colors)
-
-
+## Install of additional packages
+## pkgs are will only be downloaded, if they aren't installed yet
+
+# pacman is currently only available for R 3.5 and higher, which isn't available for Linux LTS distros
+#if(!require(pacman)) {
+# install.packages("pacman")
+# library(pacman)
+#}
+
+pkgNeeded <- c("base", "raster", "maptools", "sp", "dismo", "rasterVis", "rgdal")
+isInstalled <- sapply(pkgNeeded, require, character.only = TRUE)
+print(isInstalled)
+
+
+pacman::p_load("raster", "maptools", "sp", "dismo", "rasterVis", "rgdal")
+# notice: when '#' the line is "neutral = Not run"
+
+# set path to DEM-raster
+rasterpath<-"C:/Users/CHORO_04/Onedrive/PRACTICALS/AREALKUNDE/SDM"
+# set path to species dots shapefile
+
+# 2. GET THE DATA #-----------------------------------------
+# DEM raster
+setwd(rasterpath)
+elev <- raster("CHELSA-DEM.tif") #from the defined path
+
+# Create Study area "SWA"
+ext <- extent(elev) # get extent of DEM raster
+SWA <- as(ext, 'SpatialPolygons')#convert ext to a SpatialPolygon
+proj4string(SWA) <- CRS("+init=epsg:4326") #define KBS WGS84=4326
+
+# Species occurrences
+setwd("C:/Users/CHORO_04/OneDrive/AREALKUNDE/PRACTICALS/SPEC01")
+# the resp. path to species dots
+# you only need to change *THIS PATH* and *ELEVATION* range for
+# all next species
+
+dots <- maptools::readShapePoints("DOTS.shp")
+proj4string(dots) <- CRS("+init=epsg:4326") #define KBS WGS84=4326
+
+# 3. OUT GBIF DOTS #----------------------------------
+SWA_DOTS <- dots[SWA,] # select 341 which 'in SWA'
+# = like the 'select by location' step in QGIS
+
+# jetzt die selektieren, die "CTS-SWA..." sind
+
+# Vorher: Replacing NA's with "None" for all SWA_DOTS
+# muss aber leider vorher als level hinzugefuegt werden
+# get levels and add "None"
+levels <- levels(SWA_DOTS@data$datasetNam)
+levels[length(levels) + 1] <- "None"
+# refactor datasetNam to include "None" as level
+# and replace NA with "None"
+SWA_DOTS@data$datasetNam <- factor(SWA_DOTS@data$datasetNam,
+ levels = levels)
+SWA_DOTS@data$datasetNam[is.na(SWA_DOTS@data$datasetNam)] <- "None"
+
+# jetzt endlich unsere 91 CTS auswaehlen
+CTS_DOTS<-SWA_DOTS[(SWA_DOTS@data$datasetNam == "CTS-SWA-9-1"),]
+
+# 4. EXTRACT DEM #------------------------------------------
+
+# define circles with a radius of 15 km around SWA_DOTS
+# with "dismo::" I make sure the "circles" function works
+# by calling it directly from dismo-package
+BUFF <- dismo::circles(CTS_DOTS,d=15000,lonlat=T)
+
+# everybody: draw 10000 random points within BUFF circles
+SAMPLE <- spsample(BUFF@polygons, 10000, type='random')
+# das dauert am laengsten/takes the longest time
+
+# extract DEM values at point positions
+ElevDots<-extract(elev,SAMPLE,df=T) # "point sampling tool"
+hist(ElevDots$CHELSA.DEM) # to see the data
+
+# 5. SUBSET BY DEM #--------------------------
+
+# In CTS-SWA: "Pergularia tomentosa is a light requiring species
+# occurring in open places, insolated, and on dry sandy or
+# gravelly-sandy-clayey soils, frequently together with Artemisia
+# and various semishrublets (suffrutex). In vertical distribution
+# it has been found in depressions around the Dead Sea, more or
+# less at -250 m and usually it does not grow beyond 900-1200 m
+# elevation. The most elevated localities have been found in
+# Pakistan at 1330 m and in Afghanistan at 1 500-1600 m."
+# -> In this case I choose -250 to 1250m and neglect the outliers.
+
+# Join the (spatial)SAMPLE and ElevDots data (both n = 10000)
+SAMPLEDOTS <- SpatialPointsDataFrame(SAMPLE, ElevDots)
+summary(SAMPLEDOTS)
+# Subsetting an SPDF in R is easy.
+# You can do it just like a normal dataframe.
+# remember "CHELSA.DEM" is the elevation
+SMPLDTS<-SAMPLEDOTS[(SAMPLEDOTS@data$CHELSA.DEM > -250),]
+SMPLDT <-SMPLDTS[(SMPLDTS@data$CHELSA.DEM < 1250),]
+hist(SMPLDT@data$CHELSA.DEM,
+ col="red",
+ add=T) # to control
+
+# 6. PLOT THE DATA #-----------------------------------------
+plot(SWA)
+plot(elev, add=T)
+plot(SWA, add=T)
+plot(dots,col="black",pch=20,cex=0.5,add=T)
+plot(CTS_DOTS, col="red",pch=16,cex=0.5,add=T)
+plot(BUFF, cex=5, add=T) #enlarged by 5
+plot(SMPLDT, col="blue", pch=16,cex=0.1,add=T)
+
+# 7. PLOT 3D FOR FUN #--------------------------------------
+require(rasterVis)
+plot3D(elev,
+ maxpixels=1e6,
+ zfac=0.1,
+ drape=NULL,
+ col=terrain.colors)
+
+