Ecological modelling, based on field data, has become an indispensable tool in ecological research. It consists of a number of steps: analysing data, proposing plausible mechanistic models and mechanistic explanations for observed phenomena, and selecting models based on maximum likelihood or an information criterion. This course presents a conceptual framework for ecological modelling: covering elementary growth models and probability distributions needed to mathematically model processes. The models are confronted with the data, using state of the art statistical methods. The course presents techniques for dynamic simulation, model fitting, parameter estimation, and model selection based on maximum likelihood and information theory. While the theory has emerged from the field of ecology, it has shown to be widely applicable in the life sciences. The course is taught with R as the programming language because it is freeware and it allows flexibility in handling and modelling data.
The conceptual framework is taught from the book “Ecological Models and Data in R” by Ben Bolker, Princeton University Press, 2008. Examples are drawn from the field of (agro-)ecology. The course consists of theory lectures, hands-on practical sessions and a case study to synthesize the acquired skills and knowledge. The case study is presented and discussed on the last day of the course.
After completing the course, the participant
Day 1: Dynamic simulation in R
Day 2: Stochastic simulation
Day 3: Fitting an ecological model with maximum likelihood
Day 4: Parameter optimization and model selection
Day 5: Case studies
Day 6: Case study presentations
Target Group | The course is aimed at PhD candidates and other academics. |
Group Size | Min. 20, max. 30 participants |
Course duration | 6 days |
Language of instruction | English |
Frequency of recurrence | Once every two years |
Number of credits | 1.8 ECTS |
Lecturers | Dr.ir. Bob Douma (Centre for Crops System Analysis, Wageningen University & Research), Dr. Lia Hemerik (Biometris, Wageningen University & Research) and Dr.ir. Wopke van der Werf (Centre for Crops Systems Analysis, Wageningen University & Research) |
Prior knowledge | Basic knowledge of R (e.g. installing packages, reading data-files, linear regression), and basic knowledge on statistics (e.g. linear regression, anova). |
Location | Wageningen University Campus |
Options for accommodation | Accommodation is not included in the fee of the course, but there are several possibilities in Wageningen. For information on B&B's and hotels in Wageningen please visit proefwageningen.nl. Another option is Short Stay Wageningen. Furthermore Airbnb offers several rooms in the area. Finally, there is also a very active public Facebook group called “Wageningen Student Plaza”, where rooms are often offered for short-term sublets, but where one could also easily post a request for renting a room for a week in Wageningen. Finally, note that besides the restaurants in Wageningen, there are also options to have dinner at Wageningen Campus. |
Claudius van de Vijver (PE&RC)
Phone: +31 (0) 317 485116
Email: claudius.vandevijver@wur.nl
At this moment, this course is not scheduled yet. However, if you register your interest in this activity below, we will inform you as soon as the course is scheduled and registration of participation is opened.