6 EC
Semester 1, period 2
5224GLEB6Y
| Owner | Master Biological Sciences |
| Coordinator | W.D. Kissling |
| Part of | Master Biological Sciences, track Ecology and Evolution, Master Biological Sciences, track General Biology, |
Biodiversity contributes to ecosystem functioning and is of fundamental importance for human well-being. Hence, knowledge about the spatial (global) distribution of biodiversity is essential for reporting and managing biodiversity change, and for contributing to the vision that biodiversity is valued, conserved, restored and wisely used. With this course, we want to contribute to educating a new generation of ecologists who are equipped with quantitative skills to address questions in global ecology, biodiversity and conservation science. We particularly focus on two aspects: (1) handling large biodiversity and environmental datasets, and (2) modelling and analyzing species distributions, spatial biodiversity patterns, and animal movement. In the first week, lectures will be given to introduce the different topics, and tutorials in daily computer practica will provide hands-on material and code for ecological data analysis and visualization using the R programming software and ArcGIS as a Geographic Information System (GIS). In weeks 2-4, the students (in groups of 3-4) will then develop their own research project in global ecology and biodiversity by combining ecological and environmental data for a specific research question, and writing this up as a report similar to a draft manuscript for submission to a journal. Additionally, two oral presentations and a final data repository will have to be provided by each student group.
Will be provided during the course via Canvas
R software with various packages
ArcGIS (not compatible with MAC OS)
Powerpoint presentations and other materials will be provided
|
Activity |
Hours |
|
|
Computerpracticum |
20 |
|
|
Hoorcollege |
15 |
|
|
Project |
104 |
|
|
Werkcollege |
16 |
|
|
Self study |
13 |
|
|
Total |
168 |
(6 EC x 28 uur) |
Requirements of the programme concerning attendance (OER-B):
Additional requirements for this course:
Absence needs to be communicated to the course coordinator. Attendance during student presentations and during introduction to research projects is mandatory.
| Item and weight | Details |
|
Final grade | |
|
0.4 (40%) Research project | Mandatory |
|
0.1 (10%) Data repository | Mandatory |
|
0.1 (10%) Oral presentation | Mandatory |
|
0.4 (40%) Written report | Mandatory |
Research project (40%)
- Quality
- Theoretical knowledge
- Technical Skills
- Independence/initiative
- Original contribution
- Working attitude
- Accuracy
- Cooperation with others
Data repository (10%)
- Completeness
- Consistent structure
- Error free
- Good meta data
Oral presentation (10%)
- Contents
- Clarity of presentation
- Discussion
Written report (40%)
- Context
- Scientific Quality
- Use of literature
- Structure and language
- Lay-out
Grades, scores for each assessment criteria, and general assessment comments and feedback will be provided on Canvas for each assessment part (Research project, Data repository, Oral presentation and Written report), and/or communicated via Email.
The 'Regulations governing fraud and plagiarism for UvA students' applies to this course. This will be monitored carefully. Upon suspicion of fraud or plagiarism the Examinations Board of the programme will be informed. For the 'Regulations governing fraud and plagiarism for UvA students' see: www.student.uva.nl
| Weeknummer | Onderwerpen | Studiestof |
| 1 | Lectures on biodiversity, environmental data, data integration, and modelling and statistical analysis; Daily computer practicum with focus on R analysis and coding, introduction to statistical modelling and workflows for data aggregation and cleaning, also data visualization with ArcGIS | |
| 2 | Development of student research projects. Obligatory introduction and allocation to research projects on Monday morning, independent development of research projects during the rest of the week, including specifying the research focus (topic and research question) and compilation and aggregation of necessary data. First data analysis. Regular meetings with supervisors are mandatory. |
|
| 3 | Obligatory data presentation on Monday morning, continuation of student research projects with focus on data analysis and modelling, summarizing key results in figures and tables, starting to write report. Regular meetings with supervisors are mandatory. | |
| 4 | Finalizing data analysis, report writing and preparation of final presentation, final presentation (obligatory), making data repository, submission of written report and data repository. | |
| 5 | ||
| 6 | ||
| 7 | ||
| 8 |
The schedule for this course is published on DataNose.