Nearly 70% of UK land area and 50% of European Union (EU) land is used for agriculture. These landscapes have been shaped by centuries of large-scale human impacts through traditional or intensive land-use systems. Today’s agricultural landscapes, ‘representing the combined work of nature and man’ (as defined by UNESCO’s World Heritage Committee) are valued for their ecological, social and historic functions (Plieninger et al., 2013), (Hartel et al., 2014). However, the public goods provided by these agro-ecosystems and their related natural resources – including food, bioenergy, clean water, biodiversity, carbon storage and sequestration – are threatened by unsustainable land-use intensification, abandonment, and climate change. At the same time, climate action has ramped up across the world (albeit slowed down by the covid-19 outbreak) and the UK has committed to reaching Net Zero carbon emissions by 2050, including in the agricultural sector, which accounts for about 10% of the UK’s GHG emissions. Furthermore, following UK Brexit, the agricultural policy, and particularly the incentives, regulations and subsidies farmers get from public funding are dramatically changing. Thus, understanding the environmental impacts of farmers’ actions, in particular on carbon sequestration and subsequent storage in agricultural soils is of paramount importance.
Figure: Typical agricultural landscapes are controlled by individual farmers and provide many public goods including biodiversity, flood protection and carbon sequestration. These may depend on how farmers manage their land e.g. conventional versus minimal tillage, or are provided by field margins, hedgerows and other semi-natural elements. We lack evidence on the effect and proximate drivers controlling the GHG balance of the abovementioned interventions and their potential to sequester and store carbon.
This is an exciting and innovative project with the potential to make a big contribution to the agricultural sector and their ability to achieve ‘net-zero’ greenhouse gas (GHG) emissions by 2050. The project aim is to improve the evidence base on the impact of different agricultural practices (e.g. tillage, cover crops etc.) and semi-natural landscape features (e.g. hedgerows) on a range of ecological and environmental outcomes, including greenhouse gas (GHG) balance and carbon sequestration, soil health, biodiversity and water quality. Specifically, depending on research interests, the studentship would address a combination of the following:
- Quantitative meta-analysis/rapid-evidence review of the impact of regenerative agricultural practices / landscape features on GHG fluxes, soil carbon, soil structure as well as crop, farm profit margins, birds/insects populations and water quality.
- Building on system-mapping exercise done by iCASP Soil Carbon project, develop dynamic system modelling, Bayesian model or Fuzzy Cognitive Models to capture the inter-connectivity between drivers and multiple impacts of regenerative practices
- Improve and adapt existing protocols to cover the range of relevant measures and indicators related to soil carbon, soil health, farm economics, biodiversity and water quality and trial them in the University of Leeds Research farm.
The PhD student will benefit from joining the Horizon 2020 BESTMAP (bestmap.eu) project activities coordinated by Prof. Ziv. BESTMAP is a 4 year programme dedicated to improving policy impact assessment models for post-2020 Common Agricultural Policy (CAP). They will also be involved in recently started Horizon 2020 ClieNFarm (Climate Neutral FARMing) project and BBSRC funded “Transformations to Regenerative Food Systems” project.
Fit to NERC Science
This project is aligned with the NERC terrestrial research area, in particular research areas on soil science, ecosystem-scale process and land use.
Potential for high impact outcome
Post-Brexit, there is an opportunity to shape the future Environmental Land Management Schemes (ELMS) which will replace the current subsidies programme and set new regulations for agricultural farming. Better evidence linking practices farmers may adopt and impacts on carbon/GHG, as well co-benefits and tradeoffs on biodiversity, water and economics, would help shape that new policy to help both farmers and the environment, making the research timely and likely to produce several high impact outputs. Via Leeds’ Global Food and Environment Institute and the iCASP project, the results of this PhD will be presented to DEFRA, Natural England, National Farmers Union, Yorkshire Agricultural Society farmers network and other stakeholders.
The student will work under the supervision of Prof. Guy Ziv within the Ecology and Global Change research cluster in the School of Geography and Prof. Pippa Chapman in the River Basins cluster in the School of Geography. The project provides a high-level of training in (i) rapid-evidence review/meta-analysis and data analysis; (ii) modelling and statistics and (iii) soil sampling and lab analysis. The student will be supported throughout the studentship by a comprehensive PGR skills training programme that follows the VITAE Research Development Framework and focuses on knowledge and intellectual abilities; data analysis; paper writing; personal effectiveness; research governance and organisation; and engagement, influence and impact. Training needs will be assessed at the beginning of the project and at key stages throughout the project and the student will be encouraged to participate in the numerous training and development course that are run within the university to support PGR students, including statistics training (e.g. R), academic writing skills, grant writing etc (http://www.emeskillstraining.leeds.ac.uk/). Supervision will involve regular meetings between all supervisors and further support of a research support group.
The student should have a keen interest in agriculture and its environmental impacts with a strong background in a physical geography, earth sciences, plant sciences, environmental sciences or related discipline. Strong analytical/statistical/modelling skills are desirable but not essential, as full training will be provided during the PhD.
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