The Alan Turing Institute is building a national network of AI and digital twin technologies to tackle the UK’s biodiversity loss and climate change. Digital twins are virtual replicas of real-world systems—such as farms, cities, or weather patterns—that allow researchers to test interventions before deploying them in the physical world. The problem is that current environmental monitoring and prediction tools are fragmented, slow, and unable to handle the complexity of interconnected ecosystems and climate systems. This programme aims to close that gap by unifying expertise from six national labs, including the Met Office and the British Antarctic Survey, around four long-term missions: automating biodiversity tracking, localising climate predictions, optimising natural resource use, and designing net-zero cities. If successful, the work could transform how the UK manages its natural environment—making infrastructure like water grids and energy networks more resilient, enabling real-time adjustments to farming practices, and giving policymakers reliable simulations to test sustainability policies. The programme will also produce a five-year national roadmap, ensuring the tools developed are adopted beyond the research community.
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The Alan Turing Institute (Turing), in collaboration with national labs, will lead a nationwide effort to develop and launch novel methods in AI and digital twinning technologies that improve the UK's effectiveness in addressing environment and sustainability (E&S) concerns. Turing has identified four long-term E&S missions: 1) automate biodiversity monitoring to enable nature recovery; 2) deliver localised environmental predictions to mitigate the impacts of climate change; 3) optimise infrastructure for sustainable use of natural resources; and 4) model interventions to achieve sustainable cities and regions for a net zero world. The proposed programme will bring together a diverse group of UK leaders and experts in AI, environment, sustainability and policy to refine these missions, develop an ambitious national 5-year roadmap and undertake transformative environmental research and innovation to avert climate and biodiversity catastrophe. Such complex challenges necessitate a blend of advanced analytical skills working in conjunction with environmental scientists across various sub-disciplines. Here, AI and data science act as the binding agent that unifies these diverse teams, and Turing serves as the central hub for UK-wide inclusive activities, leveraging its past ASG seeded research activities with partners. Specifically, this will involve collaboration with national laboratories to establish and augment our collective understanding, which will include: British Antarctic Survey (BAS), UK Centre for Ecology & Hydrology (UK CEH), Centre for Environment, Fisheries and Aquaculture Science (Cefas), National Oceanography Centre (NOC), UK Met Office, and Rothamsted Research. The work is separated into the following workstreams (WS): WS1: E&S Mission Scoping with UK research and practitioner communities - WS1.1: Deep stakeholder mapping and engagement to develop, refine and launch the E&S Missions. - WS1.2: Capacity-building to support E&S delivery - WS1.3: Nurturing a national community of research and best practice WS2: Scaling-up game-changing environmental research from the Turing's AI for Science and Government programme - WS2.1: Intelligent fusion of sensor data bridging global and local scales - WS2.2: Digital Twins of Controlled Environment Agriculture - WS2.3: Automated shape analysis and tracking within imagery - WS2.4: Reproducible environmental pipelines for digital twins - WS2.5: Foster an open international environmental data science community WS3: Establishing physics informed data-driven national capability in weather prediction
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