Course Units


This course is intended as a blended learning module, although the provided introductions, explanations and examples might be useful for self-study only, too.

01 The very basics

Go through a brute force introduction into R, R Markdown, the RStudio IDE, version management with Git and GitHub’s classroom functionality to get ready for solving the upcoming assignment problems and submitting your solutions.

02 More basics

Learn how data can be measured and represented by different data types before focussing on how these data types are structured in object types in R. Get to know how to access your data stored in different object types by indexing, which will open up the door for working with R.

03 Working with spatial data

Get a brute-force introduction to working with different kinds of spatial data in R.

04 SDM basics

Learn why Species Distribution Modelling (SDM) is necessary, what SDM can be used for, as well as the underlying ecological concepts of SDM.

05 SDM workflow

All SDM approaches have a similar generic workflow as outlined by Zurell et. al 2020:

06 Create your own student tutorial

Get familiar with relevant references for SDM and prepare an HTML tutorial for a particular modelling technique.

Student tutorials

This is going to be a continuously updated collection of sources to obtain various kinds of information on different SDM techniques.