In the face of global changes as i.e. the climate change there is a need to better understand and predict the stability behavior of ecosystem functioning. However, the immense number of not yet fully characterized organisms and the highly complex networks among them prevents the prediction of the functional response directly from determining the taxonomic composition of communities. On the other hand, studies that have reduced community information down to simple diversity patterns obtained contrasting results concerning the correlation of community diversity parameters and functional parameters as system stability. Recent studies suggest that the reduction of complexity of communities down to intermediate levels, as i.e. characterizing the community by its composition of specialists and generalists or quantifying the redundancy of present traits may be a promising tool to predict and understand its stability response to disturbances.

Microbial communities are main drivers of carbon and nutrient cycling on earth and because of their enormous population sizes within small sample volumes and short generation times they can be used as ideal systems for ecological studies.

The aim of the proposed study is to use metagenomic and metatranscriptomic data of aquatic microbial communities to delineate and understand mechanisms that enable functional stability of these communities.

For this purpose both, data from natural environments as well as data from experimentally manipulated systems will be used. The option to simultaneously assign taxonomic and functional data to metagenomic/metatranscriptomic reads will hereby enable to extract information that i.e. informs about the dominance of generalists or redundant traits in the community. Meta-omic data will further provide an insight into the mechanisms that enable stability of the microbial functional response and thereby support the understanding of functional stability behavior on the community level.