300006 UE Species distribution modelling (2020S)
Continuous assessment of course work
Labels
Registration/Deregistration
Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).
- Registration is open from Th 06.02.2020 08:00 to Th 20.02.2020 18:00
- Deregistration possible until Th 30.04.2020 18:00
Details
max. 16 participants
Language: English
Lecturers
Classes (iCal) - next class is marked with N
- Friday 06.03. 15:00 - 16:00 Seminarraum (Fakultätszentrum für Biodiversität) Rennweg EG
- Monday 25.05. 09:00 - 17:00 Seminarraum (Fakultätszentrum für Biodiversität) Rennweg EG
- Tuesday 26.05. 09:00 - 17:00 Seminarraum (Fakultätszentrum für Biodiversität) Rennweg EG
- Wednesday 27.05. 09:00 - 17:00 Seminarraum (Fakultätszentrum für Biodiversität) Rennweg EG
- Thursday 28.05. 09:00 - 17:00 Seminarraum (Fakultätszentrum für Biodiversität) Rennweg EG
- Friday 29.05. 09:00 - 17:00 Seminarraum (Fakultätszentrum für Biodiversität) Rennweg EG
Information
Aims, contents and method of the course
Assessment and permitted materials
Participants will work in groups of two. Each group will have its own 'project' including the full sequence of modelling, projection and analysis work. Evaluation will be based on work during the course and on a final 15-min presentation of the groups' results.
Minimum requirements and assessment criteria
The course requires basic familiarity with R. As there will be groups of two, knowledge of partners may be complementary.
Positive evaluation requires regular presence, active work during the course and doing at least part of the final presentation.
Positive evaluation requires regular presence, active work during the course and doing at least part of the final presentation.
Examination topics
Reading list
Association in the course directory
MEC-6, MBO 7
Last modified: Mo 07.09.2020 15:21
The course will combine introductory lectures with pratical work. Practical work will include all main steps from data preparation, model parameterization & evaluation to projection, mapping and analysis of projection results. All practical work will be done in R.