| Kommentar |
Educational and qualification objectives: The participants will get introduced to concepts, models and methods of spatial and quantitative biodiversity research. Based on a broad range of contemporary international literature, they will learn about observed and expected biodiversity response to global change, with a focus on climate change and land-use change, as well as current methodological challenges and developments in biodiversity modelling. The course will thus equip students with the theoretical background and practical tools to address pressing societal challenges related to biodiversity change and conservation. Methodological focus will be on species distribution and macroecological modelling approaches, paired with elements from functional diversity analyses. The students will learn to conceptualise quantitative impact assessments, to develop their own computing and analyses codes, and provide practical recommendations based on their modelling results. They will apply the gained theoretical and methodological knowledge to case studies and solve a practical problem related to climate change, land use change and biodiversity conservation.
Prerequisites for participation in the module or specific courses within the module: Modules 1, 2, 3 and 4. Knowledge in statistics (OLS regression, test statistics), basic knowledge in geographic information systems, basic knowledge in R.
|
Type of course
|
Time of attendance, workload in hours
|
ECTS credits (LP) and requirements for their issuance
|
Topics, contents
|
|
SE (seminar)
|
2 SWS[1]
120 hours
25 hours attendance,
95 hours pre-and post-processing of the course
|
4 LP, participation, presentation (ca. 20 min)
|
- Introduction to ecological niche concepts, spatial ecology, macroecology, and biodiversity theory
- Study of international literature about global change impacts on biodiversity and different drivers of biodiversity change; own analysis of single papers
- Global biodiversity observation networks and information facilities
- Policy-relevant tools and methodologies, international guidelines and platforms
- Environmental impact assessment and planning
- Introduction to advanced statistical methods: generalised linear models (GLM), generalised additive models (GAM), classification and regression trees (CART), cluster analyses
|
|
PC SE (computer seminar with R)
|
2 SWS
120 hours
25 hours attendance,
95 hours pre- and post-processing of the course
|
4 LP, participation, exercises, project work
|
The participants deepen the topics and methods acquired in the SE through practical application to case studies. They will advance their programming skills in the statistical environment R.
- Advanced statistical methods (GLM, GAM, CART)
- Model testing and evaluation
- Basic programming elements (loops, functions, vectorisation, advanced scripting)
- GIS functionality in R
- Simple dispersal and demographic modelling
- Functional and phylogenetic analyses, cluster analyses
- Interpretation and discussion of modelling results
|
|
Module exam
|
60 hours
term paper (10 pages/ ca. 15,000-20,000 ZoL oM[2])
|
2 LP, pass
|
Students will choose from a set of different projects and solve a series of applied questions independently in R, using the techniques taught in class. The term paper will be written in form of a scientific article on the topic of the project work and handed in together with relevant R code.
|
[1] SWS = Semesterwochenstunden (hours of attendance per semester week)
[2] „ZoL oM“ = Zeichen ohne Leerzeichen und ohne Materialanhang (characters without space and without appendix) |
