Agricultural policy in England is undergoing the greatest change for 50 years. Under the principle of ‘public money for public goods’, new incentives are emerging to reward farmers for delivering enhancements to ecosystem services. i.e., activities which improve the environment and benefit society and human wellbeing. Timing is opportune. With the phasing out subsidies, rising input costs and volatile markets, farmers are increasingly willing to adapt their practices to secure a sustainable future for their businesses.
While there is enormous potential to harness new public sector programmes (and private funding schemes) to accelerate nature recovery and help maintain farm revenue, the opportunities are difficult for landowners to navigate. Of the few farmers that are generating income from the environment, some employ intermediaries to understand the markets and sell their public goods (carbon capture, water quality improvement) and others are forming co-operative partnerships to position themselves more strongly for negotiation.
In this PhD project, you will identify markets for public goods, scoping opportunities for ‘stacking’ or ‘bundling’ different revenue streams. You will compare existing tools for ecosystem service valuation (e.g. NEVO, InVEST) with your own GIS-derived data. You will quantify uncertainties and examine the utility of modelled outputs for establishing trade-offs and synergies under multiple objectives to land management; for example, how do you maintain food production while maximising carbon storage and achieving biodiversity net gain? You will talk to farmer groups to aggregate solutions and lessen concerns about uncertainties, wasted opportunities or overcommitments. You will pioneer a multi-scale, resilient ‘portfolio’ approach to land management.
This project is at the cutting edge of pragmatic solutions for nature recovery and will position you as an expert in the field. The PhD will prepare you for a future career in research, or with government or non-government land management and conservation agencies.
The start date is October 2023
Entry requirements
We welcome applications from candidates of environmental science and numerical disciplines, including degrees in geography, environmental economics or computing. Previous experience with GIS and scripting languages such as R or Python, would be advantageous. Candidates should have excellent communication and presentation skills and will ideally be highly motivated to apply academic research to real-world problems.
The standard minimum entry requirement is 2:1.
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