NIGK15005U Ecological Modelling

Volume 2024/2025

MSc Programme in Environmental Science
MSc Programme in Geography and Geoinformatics
MSc Programme in Geography and Geoinformatics with a minor subject

MSc Programme in Sustainable Forest and Nature Management



The course teaches basic knowledge of ecological modelling, with a focus on processes in ecosystems and their interaction with the environment. It addresses how numerical models of these processes and interactions are constructed, how these models can be used (together with experiments and observations) to understand the dynamics of ecosystems, and how they can be applied to address interactions in ecosystems.

The course focuses on understanding and representing ecosystem processes, and on the design, implementation (programming) and assessment of numerical models to describe these processes. The course has a strong emphasis on hands-on experience in designing and programming models, with computer exercises as the main method to practice this.

Learning Outcome


  • Modelling of biogeochemical processes in soil and vegetation, and the influence of environmental drivers on these
  • Modelling of population dynamics (exponential growth, logistic growth, and agent-based models)
  • Modelling of diffusion and heat transfer in layered systems



  • Description of systems with relational diagrams
  • Numerical integration (understanding of Euler forward integration and basic knowledge of higher-order integration methods)



  • Ability to describe ecosystems and their processes in qualitative and quantitative ways
  • Understanding of the linkage between hypotheses, ecological theory and models, and between models and experiments/​observations.
  • Ability to design a model with state variables and their rates of change, and define systems and system boundaries
  • Understanding of the numerical integration of models
  • Critical assessment of the outcome of models, their sources of uncertainty, and the limitations of model design


Please see Absalon course page

BSc in Geography and Geoinformatics or equivalent is recommended.
The form of teaching is exercises combined with ad hoc lectures. For the teaching plan, please see Absalon.
  • Category
  • Hours
  • Preparation
  • 171
  • Exercises
  • 35
  • Total
  • 206
Continuous feedback during the course of the semester
Feedback by final exam (In addition to the grade)

Oral feedback will be provided on the student's exercises to improve the understanding and implementation of modelling principles in model code.

Feedback will be provided on the final written assignment in the exam.

7,5 ECTS
Type of assessment
Written assignment, during course
Oral examination, 20 minutes, no preparation time
Type of assessment details
The written assignment is prepared during the course and must be handed in prior to the exam week. The oral exam uses the written assignment as its point of departure. It includes the titles listed in the officially approved reading list.
All aids allowed

It is allowed to use Large Language Models (LLM)/Large Multimodal Models (LMM) – e.g . ChatGPT and GPT-4 for the Python programmering

Marking scale
7-point grading scale
Censorship form
No external censorship
Several internal examiners.

Same as the ordinary exam.

The written assignment must be handed in prior to the re-examination week. The oral exam uses the written assignment as its point of departure. It includes the titles listed in the officially approved reading list.

Criteria for exam assesment

Please see learning outcomes.