Research interests

Agriculture cover more than 55 million km² of land, making it the largest human-made ecosystem on Earth. It is a major driver of climate change, deforestation, and biodiversity loss—yet it is also one of the sectors most vulnerable to the impacts of climate change. At the same time, the global demand for agricultural commodities for food, feed, fiber, and the expanding bioeconomy is projected to rise significantly in the coming decades. The major challenge for agriculture is to adapt to these changing conditions, increase productivity, and enhance resilience—while minimizing environmental degradation and reducing greenhouse gas emissions.

My research aims to better understand the complex mutual feedbacks between agriculture and the environment across local to global scales, to make agricultural systems more sustainable and resilient.  To this end, I develop a range of modeling approaches—from process-based to empirical and machine learning—with the goal of building a digital twin of the global agricultural system.

My research focuses on the one hand on the modeling of agricultural suitability and the biophysical processes of crop growth and yields under both historical and potential future climate conditions. This includes the consideration of extreme weather events, as well as various agricultural management practices and adaptation strategies. On the other hand, by coupling these bio-physical models with computable general equilibrium (CGE) models, I contribute to the development of integrated assessment models that allow for the spatially explicit simulation of land use change. These approaches account for teleconnections between local consumption and global land-use patterns through international trade. This integration allows for the assessment of trade-offs between climate change adaptation and mitigation, food security, biodiversity conservation, and the achievement of other Sustainable Development Goals (SDGs).

Current and previous positions

Education and key qualifications