- Understanding ecosystem greenhouse gas (GHG) exchange crucial for climate change prediction
- Exploring novel opportunities to reduce GHG emissions from intensive crop production on peat
- Developing new emission factors important for UK GHG flux accounting
- Using Eddy Covariance - a cutting edge technology for ecosystem research
English lowland peat occupies 958 km2 (Natural England 2010) and stores large amounts of carbon. Nearly all fen peatland was drained and cultivated for intensive agriculture. In eastern England, this has led to peat loss rates of ~1cm yr-1 under intensive agriculture (Richardson & Smith 1977), with associated high CO2 emissions. Until recently, most direct measurements of CO2 and other GHG fluxes for UK peatlands came from upland blanket bogs, which have different ecosystem properties from fens. Recent studies by the supervisors as part of DEFRA and NERC projects have, however, highlighted the scale of GHG fluxes for lowland peats, particularly those under agricultural management, with emissions of 7.3 Mt CO2-eq yr-1 under arable, representing the largest land-based source of GHG emissions in the UK (Evans et al. 2016). These studies also indicate that crop type and disturbance are less important than water table in controlling the scale of the GHG flux.
Based partially on existing data, the studentship will evaluate the impact of innovative agricultural management practices on GHG emissions at lowland peat sites in East Anglia. Initial research there has provided the first direct CO2 flux measurements using eddy covariance (EC) of an intensively cultivated lowland peatland in the UK using eddy covariance (Morrison et al. 2013; Cumming et al. in prep). We now wish to build on these baseline data to explore the impact of altered agricultural management that is aimed specifically at reducing GHG emissions The studentship will focus on setting up and running two flux towers at co-located sites in order to explore the relationship between GHG fluxes and land/water management practices and the potential to reduce emissions from agriculture on organic soils. The work will complement an on-going NERC project and have significant impact potential for the UK GHG budget and the UK/European peat horticultural industry.
- What is the impact of past and present land use on GHG emissions in lowland Fens?
- How do agricultural management practices drive GHG emissions in lowland Fens?
- Can implementation of innovative management approaches provide effective measures for GHG emissions mitigation?
The methodology combines well established approaches with considerable scope for the development of new lines of research, outreach and impact to knowledge end users. Trace gas exchange (H2O, CO2, CH4) between the atmosphere and different management systems will be measured using EC. The two sites, with different water tables, are located close together in a high intensity agricultural landscape. Instrumentation comprises infra-red gas analysers, sonic anemometers and a range of meteorological equipment. Raw data will be processed with the EddyPro software from LiCor, with further quality control using the R software with externally-supplied packages but also custom code developed in house. Information about the sites/landscapes will be supplemented with remote sensing and other data. There will be the option of modelling using the project data and JULES, the joint UK land environment simulator. Results will be written up for publication in scientific journals.
Training and Skills
CENTA students are required to complete 45 days training throughout their PhD including a 10 day placement. In the first year, students will be trained as a single cohort on environmental science, research methods and core skills. Throughout the PhD, training will progress from core skills sets to master classes specific to CENTA research themes. Further training will be provided in instrument properties and maintenance, measurement theory and practice and site maintenance. For data processing training will be given on the data processing chain, in particular training on the use of linux systems, EddyPro, and the R software environment.
Year 1: Training in site maintenance, software usage and development, attending workshops on the eddy covariance method. Initial data analysis and evaluation of GHG fluxes. Initial writing and upgrade.
Year 2: Continued station maintenance, workshops, data analysis and evaluation of management and climate impacts on GHG fluxes, conference attendance, preparation of manuscript for journal submission. Continued development of thesis.
Year 3: Continued station maintenance, data analysis, manuscript submission and revision, conference attendance, thesis preparation.
Partners and collaboration (including CASE)
The project will interact with G’s Fresh, one of the UK’s largest vegetable supplies, who own the agricultural land on which the research will take place. There is potential for converting this project into a CASE studentship.
Dr Jörg Kaduk has 15 years experience in eddy covariance measurements and 25 years in carbon cycle and ecosystem modelling with particular focus on ecophysiology, and has supervised 7 PhD students to completion. Prof Susan Page has 30 years experience in research on the ecology of peatlands and has supervised numerous PhD students to completion.
The student will join a vibrant and diverse research students community of the Centre for Landscape and Climate Research (CLCR) and the department of Geography working on different aspects of global change. The project already has a significant number of years of observations from previous NERC and DEFRA projects providing a strong data baseline on which to build.
Department of Geography
University of Leicester
Leicester, LE1 7RH
Jk61@le.ac.uk, 0116 252 3848