Forecasting like a climate scientist – predicting biodiversity change in the Anthropocene

Biodiversity and ecosystems are degrading worldwide in response to multiple anthropogenic pressures. Yet, our ability to anticipate these changes remains limited. Current approaches are largely retrospective, making it difficult to evaluate future risks or the consequences of different actions. In contrast, climate science has long relied on coordinated modelling to understand mechanisms, attribute change to drivers, and inform policy. In this talk, I explore how biodiversity science can move toward a more predictive and integrative framework. I highlight how forward-looking models can help uncover transient dynamics, improve attribution of biodiversity change to interacting drivers such as climate and land use, and reveal trade-offs among conservation goals. I also discuss how feedbacks between ecological and socio-economic systems shape future trajectories, and why these remain challenging to capture. Advancing our predictive understanding will require more coordinated modelling efforts, including model intercomparisons and integrated scenarios across sectors. Strengthening this predictive foundation will be key to supporting decision-making under the Global Biodiversity Framework and navigating biodiversity change in a rapidly changing world.

Zurell lab website

About the speaker: My research focuses on understanding how species and communities respond to environmental change across spatial and temporal scales, from individual movement and population dynamics to regional and global distribution patterns. I have worked across different taxa, including birds, plants and mammals, and in a range of ecological systems and regions. In my team, we develop and apply a broad range of biodiversity models, from correlative and statistical approaches to mechanistic and individual-based models, often combining ecological processes such as dispersal and demography with large-scale biodiversity and environmental data to improve predictability and support conservation decision-making.