21-25 July 2025, Cape Town, South Africa
Call for applications - please use this form
Course overview
This course will provide an introduction to the theory and practice of ecological forecasting using a combination of lectures and practical sessions. Participants will be introduced to how to develop, evaluate, improve and communicate ecological forecasts, with an emphasis on practical applications in conservation and resource management. Topics include Bayesian statistics (simple models, hierarchical Bayes, state-space models, etc); fusing multiple data sources; forecast uncertainty propagation & assessment; iterative data assimilation (e.g. Kalman Filter, Ensemble Kalman Filter, Particle Filter); machine learning; decision science; and a range of ecological forecasting applications such as phenology, microbiomes, carbon, infectious disease, and aquatic productivity.
The course will be led by EFI founder Prof Michael Dietze (Boston University), supported by members of the Centre for Statistics in Ecology, the Environment and Conservation (SEEC) at the University of Cape Town, and others.
The course content will be based on previous courses run by the EFI, including the 2022 course. Further details will be shared here in due course.