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Species Distribution Modelling

Get an overview of species distribution modelling techniques, use R for handling, modelling and visualizing geo-datasets, and conjointly develop software for...

Splash Page

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Learning Environment

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


You need to deliver unmarked assignments (“Studienleistung”) during the course and at the end a marked student HTML tutorial work as part of your overall co...

Frequently Asked Questions

Git and GitHub Where can I find the url to my personal GitHub classroom repository? Follow the link to the GitHub classroom provided by the instructor and y...



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 ...

R and RStudio

Start to learn the essentials for working with R and RStudio.

Example: R Markdown with html output

This page shows how a compiled R markdown file looks like (in fact, all code examples in this course were compiled with R markdown). This is a header This ...


A note on individual learning log assignments with GitHub Within this course, you will individually submit your personal solutions for the course assignments...

Assignment: Hello R, Hello GitHub

This assignment introduces you to R, R scripts and R markdown. Your submission will be pushed to your class repository at GitHub. After completion you should...



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 k...

Data Types

Learn how data is measured and organized from an R perspective.

Object Types

Learn how data types are structured within different object types in R.


Learn how to access your data in R objects.

Work Environment

Efficiently set up your project directory structure and get control over your paths to directories and files.



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

Vector Data

Vector data consists of potentially linked points defined by coordinates that can form complex geometries with assigned attributes. Vector data model In a ...

Raster Data

Raster data consists of cells or pixels in a seamless grid system and usually contain only one value per cell or pixel. Raster data model Raster data is co...

Coordinate Reference Systems

An integral part of all spatial data is the coordinate reference system (CRS), which is used to define meaningful distances between data points irrespective ...

Example: Workflow in R

This example provides a schematic workflow for processing vector and raster data in R. Get raster data Firstly, we import some raster data into our working...

Assignment: Spatial Data Processing

This exercise will lead you through some of the most basic and important steps for spatial data processing. Things you need for this worksheet R — the in...



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

Why SDM?

Obviously, there are too many species on Earth to know them all, not to say their distributional ranges. To make things even more complicated, a species doe...

Task: Ecological Concepts

There are some ecological concepts that are needed to interpret and critically evaluate SDM results, which are going to be discussed here. Watch the followi...

SDM workflow

All SDM approaches have a similar generic workflow: The five main steps in the species distribution modelling cycle. Source: Zurell et. al 2020, https...

Assignment: Student tutorials

Get familiar with relevant references for SDM and prepare an HTML tutorial for a particular modelling technique. Things you need for this assignment Refere...



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