Multi-scale assessment of temperature sensitivity of soil carbon — implications for global warming mitigation

Summary:
Soil organic carbon (SOC) sequestration – removing carbon from the atmosphere and storing it in soil organic matter – is considered a key global warming mitigation strategy 1. SOC is also an indicator of soil quality and resilience, and there is currently much interest in better understanding the links between land degradation and climate change 2. Increased SOC levels also improve both soil moisture retention and drainage; thereby improving agricultural resilience to extreme weather including floods and droughts.
Although SOC plays an important role in environmental policy, there is much uncertainty about how a changing climate will affect SOC dynamics, due to complex interactions between climate, soil and vegetation. Process-based models have been applied to understand the spatial and temporal variability in SOC dynamics. However, most ecosystem-scale biogeochemical models represent SOC dynamics with first-order transfers between conceptual pools defined by turnover time, limiting their capacity to incorporate recent advances in scientific understanding of SOC dynamics, and their sensitivity to temperature 3. A key area of uncertainty is the impact that a warmer climate will have on SOC decomposition and stabilization, and potential feedback effects to global warming. The Microbial Efficiency-Matrix Stabilization (MEMS) model is a recently-developed framework based on functionally-defined and measurable litter and soil pools, and represents a new understanding of SOC formation and persistence 4. The biophysical characterization of each pool and process in the MEMS model enables applying a specific temperature sensitivity to each of them following current understanding. The focus of this PhD fellowship will be to improve the representation of the temperature sensitivity of the MEMS model and then apply it to forecast SOC stock changes at the site and regional scales considering current climate and climate change scenarios.
Objectives:
1. Synthetize the current understanding and data on temperature sensitivity of: litter and SOC decomposition, microbial C use efficiency and turnover; organo-mineral sorption-desorption;
2. Incorporate this understanding into the MEMS model, parameterizing it with literature values;
3. Optimize and validate the revised MEMS model with data from long term temperature manipulation studies; and
4. Use the model to simulate the effect of future warming on SOC dynamics at different temporal and spatial scales.

Potential for high impact outcome
The project will enable relevant advancements to be made in understanding the connection between temperature and soil C dynamics in agricultural land. This research has potential applications in identifying sustainable agricultural practices that can reduce the environmental impact of food production while maintaining or increasing yields. It will also contribute to adaptation strategies for climate change, by modelling the impact of future climate scenarios on carbon cycling processes. Finally, it can help improve the understanding of the global carbon cycle through potential applications of the research outcomes in the improvement of Earth System Models.
Training
The student will work under the supervision of Dr Marcelo Galdos and Professor Pippa Chapman from the Faculty of Environment, University of Leeds, and also interact with Professor Francesca Cotrufo from the Faculty of Soil and Crop Sciences, Colorado State University. The successful candidate will develop a range of research skills, including modelling, field sampling, chemical analysis, statistical analysis and data interpretation, academic writing skills and giving presentations. Training will be provided in field/laboratory health and safety procedures and the use of field and analytical equipment. In addition, the candidate will develop their understanding of soil processes and fluxes related to the cycling and storage of carbon in the soil, and soil modelling. 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 NERC DTP and the University of Leeds to support PGR students, including statistics training (e.g. R, SPSS), academic writing skills, grant writing etc (www.emeskillstraining.leeds.ac.uk). Supervision will involve regular meetings between all supervisors and further support of a research support group.
Student profile:
The student should have a keen interest in soil processes and environmental issues with a strong background in one or more of plant sciences, earth sciences, soil science, environmental sciences or related disciplines. Strong analytical/statistical/fieldwork skills are desirable but not essential, as full training will be provided during the PhD.