Our research group applies quantitative models to understand, explain, and predict patterns and processes in ecology. These models combine empirical observations with statistical or mechanistic representations of environmental relationships to simulate how species, communities, or ecosystems respond under changing conditions and anthropogenic pressure. Formalizing ecological theory and data into equations or capturing patterns with algorithms allows our research group to go beyond the limits of direct experimental observations by using scenario analysis at large spatial and temporal scales under land-use change or climate change scenarios (e.g. IPCC scenarios).

A wide range of modeling approaches is applied depending on the research question. Our research group mostly applies Species distribution models (SDMs), a critical and widely applied tool in ecology and conservation biology that links species occurrences to environmental variables – such as climate data, land use, or topography. The resulting correlative models allow us to delineate current geographic ranges and project potential distributional shifts of a species under land use or land cover change, climatic conditions, or other global change drivers. Among the ongoing research activities that are associated with SDMs are:

• Assessment of climate and land use change impact on species groups, for instance, on Swiss terrestrial insect assemblages under future scenarios up until 2060;
• Projection of pollination services alongside crop suitability at global scales to assess whether co-occurrence persists under environmental change; and 
• Development of SDM-based approaches to capture crop species' environmental niche to develop next-generation agro-ecological suitability assessment.