The role of legumes in achieving net zero: reducing nitrogen losses and improving soil health

Scottish Government has pledged to meet a net-zero target for GHG emissions in Scotland by 2045 and the UK government by 2050. However, current agricultural practices result in high nitrogen (N) losses through nitrate leaching and emissions of the greenhouse gas (GHG) nitrous oxide (N2O). Improved agricultural practices can prevent soil health depletion and excess synthetic N fertiliser application. Implementing legumes into the crop system to capture and utilise biological forms of N provides a nature-based solution contributing to net zero targets. Diverse plant species mixtures that include N-fixing legumes (e.g. red clover, black medic, lucerne) are currently being used in organic agriculture but further development in conventional agriculture is needed, particularly understanding N cycling and soil GHG release in diverse species mixtures vs. monocultures. Evidence-based studies which directly measure N transfer-processes across contrasting agricultural systems (cover crops, grass/legume mixtures, intercropping, herbal leys) are needed to better understand plant-soil interactions and their ability to be manipulated for optimising N use efficiency and reducing GHG emissions whilst maintaining crop productivity.
An experimental programme will be developed to investigate grass-legume species diversity, composition and intercropping effects on N fixation, N pools, N uptake and ecological responses, such as soil health status and plant productivity. Implications for residue quality and incorporation will also be studied in terms of net-gains and losses for the following crop and wider legacy effects. The project will develop grass/legume management guidance for optimal N use efficiency utilizing existing experimental field sites linked with current mob grazing, carbon sequestration potential, GHG monitoring and future RESAS research activities. The student will be trained in a range of analytical techniques (e.g. continuous flow analysis, gas chromatography, isotope ratio mass spectrometry, genetic techniques/analyses) to explore N pools, GHG emissions and soil microbial community diversity. These would provide detailed information about plant-soil N interactions which is vital for development of relationships that will be incorporated into dynamic deterministic models to improve the predictions of N cycling.
Collectively supervisors on this project have extensive PhD supervision experience (at lead and co-supervisor levels on a range of interdisciplinary topics). The lead supervisor is responsible for identifying training needs through active communication with the student and awareness of the student's background and relevant experience. To ensure excellent training of the selected PhD student, the student's progress and training needs are monitored throughout the PhD programme.