Scalable Bayesian inference framework for uncertainty quantification in stochastic models using thousands of processors in parallel at the Swiss Supercomputing Center and ETH Zurich.
We compare invasions in aquatic and terrestrial ecosystems primarily at large (national) spatial scales and among several higher-level taxa (insects, molluscs, crustaceans, all major vertebrate classes, and plants).
Community detection consists of extracting the affinity between agents of a system, which is extracted from quantities such as the frequency of interactions.
We investigate human impacts on the community composition of macroinvertebrates and fish in Swiss rivers with statistical analyses of existing monitoring data, food web analyses, and computer models.
Development of a semi-distributed hydrological model with a “flexible” approach. Testing and comparing of different model structures to combine modeling and experimenting into a learning process.
With continuing population growth, increasing affluence and economic development, and diet change towards more meat consumption, the demand for food will also increase.
