Global Ecology and Biodiversity

Course manual 2021/2022

Course content

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 handling large biodiversity and environmental datasets, modelling of spatial biodiversity patterns and species distributions, introducing a set of remote sensing products, and applying tools for spatial ecological data analysis. The students will develop their own research project in global ecology and biodiversity and combine ecological and environmental data using R, Microsoft Excel/Access, Geographic Information Systems (GIS) and other quantitative tools. The statistical modelling and prediction of species potential distributions and biodiversity in geographic space is of particular focus.

Study materials

Practical training material

• Will be provided during the course

Software

• R software with various packages

• ArcGIS

• Micrososft Excel and Access

• Other tools

Other

• Powerpoint presentations and other materials will be provided

Objectives

• Design a research project in global ecology
• Find, handle and aggregate important global datasets for exploring environmental conditions, species distributions and biodiversity patterns
• Implement statistical models (e.g. species distribution models, multi-variate regressions)
• Quantify the effect of environmental variables on species distributions, species richness and functional traits
• Download, clean and quality check species occurrence records from GBIF

Teaching methods

• Lecture
• Laptop seminar
• Computer lab session/practical training
• Presentation/symposium
• Self-study
• Working independently on e.g. a project or thesis
• Supervision/feedback meeting

Learning activities

Attendance

Requirements of the programme concerning attendance (OER-B):

1. Attendance during practical components exercises is mandatory.

Additional requirements for this course:

Absence needs to be communicated to the course coordinator.

Assessment

Research project (40%)
- Quality
- Theoretical knowledge
- Technical Skills
- Independence/initiative
- Original contribution
- Working attitude
- Accuracy
- Cooperation with others

Data management & curation (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

Fraud and plagiarism

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

Course structure

Timetable

The schedule for this course is published on DataNose.

Contact information

Coordinator

• W.D. Kissling

Staff

• S. Shinneman MSc