The UK is overhauling how it manages its land—farms, forests, wetlands, and urban green spaces—by building a new decision-making framework that integrates social science, economics, ecology, and mathematics. This matters because current land-use decisions are often made in isolation, by different groups with conflicting priorities: farmers, developers, conservationists, and government agencies. The post-Brexit regulatory environment demands a more coordinated approach, especially to meet Defra’s 25-year environment plan, which targets cleaner air and water, thriving biodiversity, reduced environmental hazards, and climate change adaptation. If successful, the Programme Coordination Team will produce practical decision-making tools that allow land users—from parliament to private landowners—to plan together. This could reshape how the UK balances food production, housing, nature recovery, and carbon storage on the same landscapes. The team includes senior academics and “champions for change” who will break down institutional silos and connect researchers with policymakers and businesses. The project is applied and policy-focused, not fundamental science. Its primary output is a coordinated research community and a set of usable tools, not new theoretical knowledge.
View original technical description
The Strategic Priority Fund (SPF) programme 'Landscape Decisions: towards a new framework for using land assets' is delivering a new framework for land management decisions. It draws on social science, economics, natural science, mathematics and modelling, in order to provide solutions to delivering a 'Green Brexit' that enables the United Kingdom to achieve Defra's ambitious 25-year environment plan: clean air by reducing air pollution, clean and plentiful water under conditions of a changing climate, thriving plants and wildlife by protecting and enhancing biodiversity, reducing the risks of harm from environmental hazards, using resources from nature more sustainably and efficiently, enhancing the beauty, heritage and engagement with our natural landscapes, mitigating and adapting our landscapes to climate change, minimising waste, managing exposure to chemicals and enhancing biosecurity. The Programme Coordination Team will bring together new knowledge from many academic subjects to provide a cohesive programme that will deliver against the research questions articulated for the SPF Landscape decisions into and a new set of decision-making tools. The PCT combines specialist expertise at senior academic level in natural sciences, landscape research, social geography, and mathematics, pure and applied to ecology and ecological complexity. Beyond the discipline specific expertise, the team also includes champions for change, who are senior members of the university, able to navigate the complex, political and institutional landscapes, able to break down the silos and work cross boundaries. We have identified three champions who will be playing a pivotal role in ensuring the delivery of our impact strategy in the areas of policy, academia-business interactions and interdisciplinarity. By fostering interdisciplinarity, establishing a new research community from the diverse research base and with a strong and innovative communication plan we will promote these new tools to landscape decision makers in parliament, government agencies and the private sector. The new tools and knowledge will allow different land users to plan their landscape decisions in a much more coordinated way. This will lead to a better quality of the environment in the United Kingdom under a post-EU regulatory framework. To achieve this vision, the Programme Coordination Team will organise a series of community workshops and other events to bring together experts from different fields with land managers and decision makers. It will coordinate the main work packages in the Programme and ensure that the new knowledge from these is put together into practical solutions.
Plain English summaries and category classifications on this site are generated by AI and may not perfectly reflect the original research.
Is something wrong? Let us know