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751-5102-00L 3 Credits MSC D-USYS

Biogeochemical Modeling of Agroecosystems

Lecturers & Examiners: Prof. Dr. Johan Six, Dr. Marijn Van de Broek, Dr. Moritz Laub
VVZ CR n/a

Last Updated: 2026-06-03 00:13:57

Abstract

This class provides an introduction to biogeochemical modeling in the context of agricultural ecosystems. It covers the general background and principles of modeling agricultural biogeochemistry in a theoretical part (e.g., plant growth and soil C dynamics), while the focus is on learning how to code biogeochemical models in the R software environment.

Objective

The aim of the course is to (i) introduce students to a range of concepts applied in biogeochemical modelling of agroecosystems, with an emphasis on soil biogeochemistry (carbon cycling) and (ii) teach students the basics of coding biogeochemical models in a free and open-source software environment (R). The focus of the course is on hands-on coding. At the end of the course, students will: - Be able to critically evaluate different concepts applied in widely used biogeochemical models in an agricultural context - Be familiar with the basic concepts of programming that are specifically applicable to modelling biogeochemical cycles in an agricultural context - Be able to come up with basic conceptual models to evaluate crop growth and carbon cycling in agricultural soils, given certain constraints and - Be able to write computer codes to convert their conceptual models to numerical models, and evaluate model outcomes.

Content

The class consists of (i) a limited theoretical part, in which students learn the basics of biogeochemical models in an agricultural context and (ii) a more extensive part, in which students learn to program plant growth models and soil biogeochemical models in the R software environment. Throughout the course, the R skills necessary to code biogeochemical models are explained using examples related to soil biogeochemical cycling or crop growth (e.g., different data structures, loops, functions, if/else etc.). Aspect of biogeochemical modeling that are covered include constructing sets of coupled differential equations that form the core of numerical models, solving differential equations analytically and numerically, by writing solvers and using existing solvers, model calibration techniques and using different modelling aspects to code flexible models. These principles are applied to code published and widely-used biogeochemical models to solve research questions. The course encourages the use of large language models as coding aid.

Resources

Literature

The following handbooks serve as the basis for the concepts and skills the students will learn in the course: - Soltani and Sinclair, 2012, Modeling physiology of crop development, growth and yield. - Soetaert and Herman, 2009, A Practical Guide to Ecological Modelling, Springer Netherlands. - Wallach et al., 2018, Working with Dynamic Crop Models, 3rd Edition, Academic Press. - van Oijen, M., 2020, Bayesian Compendium. Springer International Publishing.

General Information

Language
English
Levels
MSC
Frequency
Yearly recurring

Examination

Type
graded semester performance
Digital
The examination takes place on your own device. No installation of SEB required.
Students will take an open-book computer exam halfway through the course using R (counts for 50%; 3 points out of 6). At the end of the semester, students will present the results of a group exercise on biogeochemical models in class. The evaluation consists of a joint grade for the group effort (counts for 33%; 2 points out of 6) and an individual oral assessment, where each student will answer one question regarding their group's topic (counts for 17%; 1 point out of 6).

Course Components

Type Title Time & Place Hours
lecture with exercise Biogeochemical Modeling of Agroecosystems
This course takes place in the meeting room of the LFH-building (LFH B2) on Wednesday 14:15-17:00. This room has 18 seats.
  • Wed 14:00-17:00 (Ex te rn)
3 h weekly

Offered In