Co-desIgning Robust natural Capital LandscapEs (CIRCLE)

Research Translation Fellowship

The UK Government is designing a new Environmental Land Management (ELM) policy for England which will change how our rural landscape looks, and what it does, for centuries to come. It will be the biggest intervention in agricultural policy for more than 50 years, and will see up to £3bn a year of current agricultural subsidies redirected into 'public money for public goods' - paying land managers to provide environmental benefits like clean water and carbon capture.

ELM will be the central policy tool through which the Government intends to deliver its environmental targets, set out in the 25 Year Environment Plan and elsewhere; including net zero Carbon emissions by 2050, creation and restoration of half-a-million hectares of wildlife-rich habitat, and improving water quality and quantity. To do this, part of ELM will incentivise permanent land use change out of agriculture, to woodland, wetland, and saltmarshes; and improving peatland. However whilst the benefits of such changes may take many decades to come about, the decisions on how to make these happen must be taken now.

To make those decisions, Defra must address three key questions: Where should land use change happen? How should it be encouraged? And what are its wider impacts? One important source of information to answer those questions comes from models that can simulate land use changes arising from different policy designs; and predict their impacts on the environment and their benefits to society. Defra's access to, and understanding of, those modelling capabilities is limited. The core purpose of this research translation fellowship is to embed an academic land use modelling expert in Defra's ELM team. They will deliver modelling evidence from the Landscapes Decisions Programme directly into the policy design process.

The reality of land use modelling is that predictions come with uncertainties, arising from model inaccuracy and inherent uncertainty of the future (e.g. climate, food prices). In a programme like ELM, with widespread changes across landscapes, and long-term consequences many decades in the future, understanding these uncertainties is critical to ensure the desired outcomes are delivered. To that end, this fellowship will draw on new methods of uncertainty analysis that are being developed through the ADVANCES (Advancing analysis of natural capital in landscape decisions) project. The fellowship will extend those methods to a suite of land use decision models run by the Land Environment Economics and Policy (LEEP) Institute at the University of Exeter, and apply that model suite to support ELM design.

In collaboration with Defra we will identify patterns of land use change that deliver good outcomes (e.g. carbon capture), and at what level of risk (i.e. uncertainties over those amounts). For example, we can identify combinations of places where the outcomes of land use change are sensitive to uncertainties; and compare those to others that deliver less favourable outcomes, but with more certainty, and hence less risk. Policymakers can then balance outcomes and their risk when deciding where land use change under ELM should go.

The project will also provide Defra with the capacity to simulate policies, and compare their ability to encourage land managers to make the desired land use changes. Working with Defra we will examine policies with different payment types (e.g. up-front payments; annual payments, bonuses), the things that are paid for (e.g. carbon capture, recreation access); and the way prices are set (e.g. fixed prices, auctions).

Finally the fellowship will assess the wider impacts of ELM, including on food security, viability of farm businesses, and national carbon footprints. Taken together this fellowship aims to empower Defra with cutting edge science inputs that will enable the design of a robust ELM policy, and deliver a step-change in the quality of the nation's environment.