At the Group of Agro-ecological Modeling (AEcoMod), we study how ecosystems – and biodiversity in particular – respond to changes in land use and landscape structure, with a focus on agricultural landscapes. Our goal is to identify pathways that balance agricultural production with biodiversity conservation – for people and nature. We are particularly interested in how emerging agricultural technologies can support sustainable agriculture and agrobiodiversity conservation, while also critically assessing their challenges and potential risks. In our research, we combine ecological modeling with digital monitoring approaches for agrobiodiversity – including passive acoustic sensors, drones, and satellite remote sensing – alongside classical fieldwork.  By integrating these data and applying methods from artificial intelligence, spatial and probabilistic modeling, and causal inference, we identify the key patterns and drivers of biodiversity and its change across scales. As an interdisciplinary and collaborative team, we work at the interface of science, policy, and practice. We believe that great ideas grow best in an open, supportive, and enjoyable working environment.