Members of the group teach on various bachelor and masters level courses at SDU, but primarily in the following three courses.
Population biology and evolution
Population biology and evolution are the foundations for understanding biological phenomena including biological diversity, population fluctuations and extinctions, and interactions among species. Knowledge of there concepts has practical applications in population and resource management, nature conservation, medicine and epidemiology, animal/plant breeding, etc. I am the course director and a lecturer on an undergraduate course at the University of Southern Denmark that explains the key processes in population biology and evolution at the individual, population, and species levels. It covers the tools for understanding these procesess including simple theoretical and mathematical models. The course is run in the autumn semester. The university’s official page for the course is here.
Introduction to biodemography
Biodemography is the study of demographic characteristics, including patterns of birth and death, and how they interact with environmental drivers in species across the tree of life. I am the course director of a new course at the University of Southern Denmark that covers the basic concepts of biodemography including life-history theory, evolutionary theories of aging, demographic methods for analysis of populations, and data collection. The course survey the demography of taxonomic groups from animals (including humans) to plants and covers how demographic principles are applied in conservation and management. Students will gain the skills to construct and analyse life tables and matrix population models, and to understand and synthesise primary literature from the field. The university’s official page for the course is here.
Planning and evaluation of biological studies
In this Masters-level course at the University of Southern Denmark students learn to formulate biological questions in order to design, analyse, interpret, and present their own studies. Theory, exercises and examples are presented to prepare students for the quantitative analysis of their future projects. The course makes heavy use of the statistical programming language, R, for data manipulation, visualisation, and analysis. The university’s official page for the course is here.