AI-enhanced decision support systems for treescapes in the UK
COLLABORATORS: Daniel Williamson (CEMPS, Turing Fellow), Brett Day (Business School), Ian Bateman (Business School), Deyu Ming and Serge Guillas (UCL,Turing)
IDSAI Research Fellow: Dr Bertrand Nortier
Description: The 2019 Climate Change Act amendment requires the UK to achieve net zero greenhouse gas (GHG) emissions by 2050. Crucial to any strategy for meeting this target is the widespread planting of trees, removing GHG from the atmosphere. Design of “treescaping” policies must address two challenges: (i) A variety of factors (such as reliance upon private-sector uptake of incentives) introduce uncertainty regarding the level of GHG removed by tree planting; (ii) Alongside carbon sequestration, tree planting affects a wide array of other ecosystem services including biodiversity, flood, recreation, fire risk, food production and so on.
For each element of (i) and (ii) different research communities have models for their piece of the process. All models are interconnected and can be computationally intensive. To provide policy support, the project aims to run this network of models, propagating their uncertainties over a continuum of policies, in order to present decision makers (DM) with a subspace of policies that are consistent with their stated targets for CO2 sequestration and illustrate trade-offs with costs and other ecosystem services. DM may have an ill-formed prior understanding regarding the trade-offs they might accept across impacts, so rather than using a multi-objective optimisation, the vision is to deliver a mapping of the whole policy space for DMs to explore in real time, offering the potential for radical improvements in policy.
