Methods of ecological modelling

Subject description

The course  is highly methodological oriented where the main focus is on:

– a system approach to understanding ecosystems and application of systems thinking  for definition of the problems,

– fundamental principles of ecological modelling,

– construction of mechanistic models, models from large datasets and qualitative models for decision support.

In the first part of the course, students are introduced to the fundamental principles of systems and systems thinking, which allows them to gain a comprehensive insight into the structure and functioning of the studied system (e.g., ecosystem). The main focus is on the correct definition and proper formulation of the problems and their solutions by application of the ecological modelling methods.

The second part of the course is focused on the concepts of ecological modelling, which are given in the form of steps and rules required to achieve the methodological correctness of building an ecological model.

The last part of the course addresses three basic groups of ecological models: mechanistic prediction models, prediction and classification models constructed from data, and qualitative decision models.

The content of the course consists from the following six sections: 1. Introduction to ecological modelling, 2. A system, 3. Concepts of ecological modelling, 4. Mechanistic models, 5. Models from large datasets and 6. Qualitative  decision support models.

The subject is taught in programs

Objectives and competences

The main of objective of the course is to provide students with knowledge about modern methods of ecological modelling that will enable them to understand the structure and functioning of ecosystems and to make reliable predictions of their behaviour.


Students will acquire methodological skills needed to build a qualitative and quantitative ecological models that will allow them to gain new knowledge about the behaviour of the studied ecosystems (models for explanation), to predict their behaviour (predictive models) and to build models for the management of these systems (decision support models).

Teaching and learning methods

The course consists of lectures, exercises and seminar work. Each part of the lecture is followed by exercises about the application of particular modelling tools (e.g., STELLA, WEKA, DEXi). Students present their results in a seminar work.   

Expected study results

Knowledge and understanding:


Students will be able to apply studied modelling  methods and tools on particular research cases.

Basic sources and literature

Jørgensen, S.E., Bendoricchio, G., 2011. Fundamentals of ecological modelling : applications in environmental management and research . 4th ed.,  Elsevier


Witten H.I., Frank E., Hall M.A., 2011. Data mining : practical machine learning tools and techniques. 3rd. ed.,  Morgan Kaufmann


Bohanec M. 2012. Odločanje in modeli. 1. ponatis. Ljubljana, DMFA


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