In order to make sense of the data, we often use mathematical models. As for every scientific problem we try to use the most appropriate mathematical description, we develop and use a large variety of mathematical models. Here you will find a small selection of our modelling work. The tools we developed to efficiently solve these models can be found on our scientific computing section.
- The first model example is ‘good old’ OMEXDIA, one of the first vertically resolved biogeochemical models of the sediment. The mix of very slow and very fast processes in sediment environments often makes it quite a challenge to efficiently solve such models, but our R-packages make R especially suitable for this type of modelling. As you play with this model, bear in mind that the model comprises 600 nonlinear equations. So, each time you alter the value of a parameter, a quite substantial mathematical problem is solved.
- The next model application is a very simple one that describes how a tracer, injected as labeled glucose, propagates through a food web. Such simple models are efficient tools to quantify how much a certain organism relies on a particular food source (here bacteria).
- The dynamic energy budget (DEB) application models how an organism allocates its resources in structural and reserve tissues.
- A special type of models are our foodweb models. As food web flows among biological groups are difficult or even impossible to measure, we use whatever information we have to quantify these flows. Very often we lack temporal information, so we then use linear techniques to solve these models.