701-1677-00L Quantitative Vegetation Dynamics: Models from Tree to Globe
| Semester | Autumn Semester 2021 |
| Lecturers | H. Lischke, U. Hiltner, B. Rohner |
| Periodicity | yearly recurring course |
| Language of instruction | English |
| Abstract | This course provides hands-on experience with models of vegetation dynamics across temporal and spatial scales. The underlying principles, assets and trade-offs of the different approaches are introduced, and students work in a number of small projects with these models to gain first-hand experience. |
| Learning objective | Students will - be able to understand, assess and evaluate the fundamental properties of dynamic systems using vegetation models as case studies - obtain an overview of dynamic modelling techniques from the individual plant to the global level - understand the basic assumptions of the various model types, which dictate the skill and limitations of the respective model - be able to work with such model types on their own - appreciate the methodological basis for impact assessments of future climate change and other environmental changes on ecosystems. |
| Content | Models of individuals - Deriving single-plant models from inventory measurements - Plant models based on 'first principles' Models at the stand scale - Simple approaches: matrix models - Competition for light and other resources as central mechanisms - Individual-based stand models: distance-dependent and distance-independent - Theoretical models Models at the landscape scale - Simple approaches: cellular automata - Dispersal and disturbances (windthrow, fire, bark beetles) as key mechanisms - Landscape models Global models - Sacrificing local detail to attain global coverage: processes and entities - Dynamic Global Vegetation Models (DGVMs) - DGVMs as components of Earth System Models |
| Lecture notes | Handouts will be available in the course and for download |
| Literature | Will be indicated at the beginning of the course |
| Prerequisites / Notice | - Basic training in modelling and systems analysis - Basic knowledge of programming, ideally in R - Good knowledge of general ecology, vegetation dynamics, and forest systems |