Description du poste
Forests currently absorb roughly a third of human carbon emissions, but this service is not guaranteed. Pest and pathogen outbreaks - already devastating forests from North American bark beetles to European ash dieback - are expected to intensify under climate change, yet we have almost no capacity to predict impacts on future carbon storage. This project asks: how will pest and pathogen outbreaks reshape forest carbon dynamics as the climate changes, and can we build a predictive capability for this risk within a global climate model? The student will develop and test a new capability for simulating pest/pathogen outbreaks within a leading UK land surface model (JULES), linking outbreak dynamics - informed by observational and satellite records of tree mortality and defoliation - to how forests grow, compete and recover. Methods include process-based model development, sensitivity and attribution experiments, and evaluation against satellite disturbance and biomass records across European and North American forests. The student will have significant freedom to choose which pest/pathogen systems, regions and processes to prioritise, shaping their own research direction as understanding develops; supervisors provide a strong technical foundation while actively supporting that independence from year one. Training includes climate/land-surface model development and computational skills (Exeter) and regular visits to the Met Office with our Collaborative partner (Arthur Argles), a leading developer of next-generation vegetation models (JULES-RED), providing hands-on training in ecosystem modelling and operational practice, alongside remote-sensing and data science skills. The close, pre-existing collaboration between Exeter's climate modelling group and the Met Office underpins this partnership, embedding the student in both academic and operational research.