AB-202 Marine Arctic Biology

The course AB-202 run by Janne Søreide at the University Centre in Svalbard provides a solid introduction to Arctic marine ecosystems and covers the entire food web from small protists to marine mammals. The course consists of a a mixture of lectures, seminars, laboratory exercises and fieldwork. The students will get familiar with the most common protists, macroalgae, invertebrates, fish, sea birds and marine mammals living in the Barents Sea – Svalbard region.

The course also practices working with data through:

  • using data from previous years for analysis and discussion for a poster presentation
  • collecting, analysing and discussing data for a cruise report connected to a longer field work

Below, you can find tutorials covering parts of those processes, including tips on how to prepare your datasheets, intro to R-studio, relevant R scripts with explanations and more to come. The tutorial is structured according to the steps you will go through to prepare your poster and many of those are relevant for the report-work as well and is developed by Eike Stübner.



We can perform many methods to visualize and analyze multivarate data. In the tutorial you can find scripts and a short description to 3 of the most commonly used ones: Cluster analysis Multi dimensional scaling (MDS) PCR/RDA In this post, we will look at Principal Component Analysis (PCR) and RDA. […]

5.5 Multivariate analysis – PCA/RDA


Below, you will find some examples of plots and scripts that are relevant for some of your projects. There is also an own section on ggplot in bioSTATS, and at the ggplot web-page.   Example 1: Polar cod contribution to fish community For the plots below you will need the […]

6.3 Example scripts for some plots




[code language=”r”] ##### inspect data #### #inspect summary stats summary(Data_in2) #max, min,median, mean summary(Data_in) #max, min,median, mean range(B_taxa) #max & min values in whole dataset range(Data_in) #you will get an error message: this only works if the dataframe contains only numeric values #The amount of 0s in your dataset can […]

5.1 Example script (Inspect & standardize/transform data)




Introduction on many basics are covered other places in the R-tutorial. I encourage you to look around there if you need help with basic operations.  Still, below I mention some basics that you will need. Creating objects R treats our data as objects. They can be single vectors, matrices, lists […]

4.2 Some basics


[code language=”r”]#set working directory setwd("C:/Users/x/OneDrive/AB202 vår 2019/R") ################ import data and preparations ##### # for data import, make sure that the file path is correct #import from text file (export as text from excel file first, tabulator deliniated)### Data_in<-read.table("C:/Users/x/OneDrive/AB202 vår 2019/R/AB202fish_poster.txt", header=TRUE, sep="\t", dec=",") Data_in<-read.table("C:/Users/x/OneDrive/AB202 vår 2019/R/AB202benthos_poster.txt", header=TRUE, sep="\t", dec=",") […]

3.5 Example script