Rivers worldwide are increasingly threatend by multiple anthropogenic stressors such as drought, salinization or alteration of hydromorphology. But so far, we lack a generic understanding of how these ecosystems respond to stressors, and how they recover after stressor release. The knowledge gap is particularly severe for microorganisms in river sediments. These microscopic forms of life are responsible for the largest part of organic carbon turnover and are thus crucial for the functioning of river ecosystems. We seek to understand the fundamental mechanisms that determine how microbial communities respond to stressor increase and release. We do this by studying the functioning and composition of sediment microbial communities in controlled lab microcosms and outdoor mesocosms.

Environmental impacts can change the composition of the native microbial community. But even in the absence of environmental impacts, the native microbial community is highly diverse and variable in space and time. That is why we are so far still lacking indicator microorganisms that allow us to assess whether a specific habitat is in a good (natural) - or bad (disturbed)- ecological condition. We tackle this problem for groundwater ecosystems, in which microorganisms are the dominant form of life. We work on developing a microbial index for ecological quality assessment of groundwater by combining microbial community analysis with activity measurements and abiotic parameter values. The microbial index is initially developed for a specific contamination gradient at one groundwater site and is then extended to other sites to make it more generally applicable.

Good water quality is essential for the health of aquatic animals in captivity. We study how aquarium water gets contaminated with microbial pathogens, how these pathogens may survive and thrive, and how they can be removed effectively. Pathogen survival is fundamentally different for environmental pathogens for which aquarium water represents a natural reservoir, and for obligate pathogens, which are adapted to the environment on or within the animal host. We study how factors like pathogen loading rate (excretion of feces), environmental parameters (e.g. temperature, substrate concentrations), and biotic interactions affect pathogen survival using time-series of microbial community composition and pathogen density. This allows us to evaluate microbial water quality and infection risk, and to relate them to manageable factors, e.g the performance of the water filtration system.

Microbial communities are highly complex systems because they consist of many different species and because they are highly variable. The fast development of many molecular and sequencing methods of the last decade has enabled us to describe their composition in the minutest details. But if we want to be able to predict and manage microbial communities, we need a generic understanding that goes beyond the mere description of their composition. We therefore develop ecological concepts that aim at explaining the generic structure of microbial communities, working them out using computer simulations. We test our hypotheses by confronting our theory with empirical data.