1. A brief introduction to the nutrient tool-kit, getting R Studio to work and checking the data
Martyn Kelly
@Basil0saurus

2. Overview The CIS Guidance Manual explains the theory
Ecological
Regulatory
Chemical
Statistical
CIS Guidance Document 23 explains the EU’s strategy for eutrophication
This workshop focuses on the process of deriving appropriate boundaries

3. Toolkit versions
The most flexible version, but the one where you are most likely to encounter problems
A user-friendly version of the R Studio scripts but slightly less flexible and run from a remote server
The easiest to use, but also the most basic and lacks some of the functionality

4. How to learn more about R

6. Introduction to R: our assumptions
R and R Studio have been installed
The toolkit has been extracted to a folder
The data you want to use is in the correct format (see data template)
This data file is in the same directory as the toolkit.
Now open R Studio …

7. The R Studio interface
The interface: your script opens here. You can edit it and save changes so that you can run them again in the future.
Environment: tells you what data and information has been read into R or derived from calculations you have made.
Other windows: includes all files in the working directory, plots you have produced, add-in packages you are using and help files
The console: when you run a command you will see the outcome here.

8. R basics: the interface
Text appears in black except:
Text that will not be executed is green
type a “#” to tell R that this is the case
(useful for annotating scripts)
Text/numbers that are functions are blue
If text appears in red, you’ve made a mistake or R is sending you a warning
This will appear in the console, not the interface
If it is a mistake, the script will stop working
If it is a warning, the script will continue to run
Some options in R scripts are prefaced by “#”:
data <- read.csv(file = FName, dec=".", header = TRUE) #For "." decimal
#data <- read.csv(file = FName, dec=",",header = TRUE) #For “,” decimal, Central Europe
(Move the “#” to the upper line of script if you use comma decimals)
Everything in R is case sensitive
To execute commands:
Highlight lines in script and press “run”; or,
Ctrl-enter; or,
Press “source” to run entire script (not recommended for this course)

9. R basics: graphics
Graphs appear under the “plots” tab in the bottom right window …
… unless you specify a separate window:
> win.graph(width=8,height=4) > par(mfrow=c(1,2))
Different for Macs:
> quartz(width=8, height=4)

10. Help!
Or type your query directly into Google (answer is often found in stackoverflow.com)

11. Data format Column headings must be exactly as in template
Either cut and paste your values into template
Or edit headings in your data file
Avoid special characters (/,-,%,$ …) and accents in sample IDs

12. Data format
Save your data file in *.csv format

13. Data format

14. More about data EQRs should be uncapped if possible
i.e. not truncated at 1.0
N and P should have few values < detection limit
Both these factors can cause deviations from linearity in biology-pressure relationships

15. Load “required packages”
(p. # in Instruction manual)
You don’t need these packages for this workshop
Double click here

16. Check your data Page 24 in instruction manual
Now load 01_Tkit_check_data.R
See if you can run this script yourself, using the example dataset provided.
First, edit filename (“Fname”) (line 15)
currently: DataTemplate_Example1.csv
Change this to: DataTemplate_Example1_wks.csv