812380 Multi-scale modelling and system dynamics in aquatic ecosystems (in Eng.)

Art
Vorlesung und Übung
Semesterstunden
1.5
Vortragende/r (Mitwirkende/r)
Bauer, Andreas , Zitek, Andreas , Sendzimir, Jan , Melcher, Andreas , Kowal, Johannes Luca
Organisation
Hydrobiologie und Gewässermanagement
Angeboten im Semester
Sommersemester 2025
Unterrichts-/ Lehrsprachen
Englisch
Lehrinhalt

This lecture is structured into different modelling applications in theory and praxis given by five scientists from their insights and experience:
(01) Introduction to multi-scale modelling and system analyses (Kowal and Melcher; 1 unit)
(02) Large-scale quantitative models (Kowal; 3 units + 2 exercises)
(03) Cause-effect models, Dynalearn (Zitek; 3 units + 2 exercises)
(04) Multiple lines of evidence assessment (Bauer and Melcher; 3 units + 2 exercises)
(05) Semi-quantitative models, VENDSIM (Sendzimir; 3 units + 2 exercises)
(06) Final discussion and written exam (Melcher, 1 unit)
Inhaltliche Voraussetzungen (erwartete Kenntnisse)

Basics in applied limnology, statistics and data management
Lehrziel

After successful completion of this lecture, participants can:

•Understand the fundamentals of applied ecosystem statistics and modeling at different spatial and time scales;
•Incorporate information of different kinds (quantitative and qualitative) and from different perspectives (natural and social science) in research and decision-making related to managing aquatic ecosystems;
•To understand and identify the principal elements and process features of applied aquatic ecosystems modeling and to structure and hierarchically relate them. The conceptual causal modelling unit follows hereby the concepts of hierarchy theory supported by qualitative reasoning as means for qualitative causal simulations.
•Sharpen their statistical intuition and abstract reasoning as well as their reasoning from numerical data through ecology-based and other research (sociology, adaptive management).
•Demonstrate critical thinking in interpreting and deriving conclusions from environmental and ecological data-sets.
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