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Lead Supervisor: Dr Adam Pellegrini
Co-Supervisor: Professor David Coomes

Brief Summary

Restoring carbon lost from soils due to agriculture are a lynchpin of society’s plans to hit emission-reduction targets, and will be improved in this project by developing a new-age soil carbon model with unprecedented data on farm-level yields and soils in collaboration with private companies working to implement carbon offset schemes.

Importance of Research 

Finding ways to manage land to promote both carbon storage and provide critical services such as food production is necessary for humans to hit emission reduction targets. One key step is incentivising managers in the private sector to use practices that encourage carbon storage and sequestration, often in the form of paying for carbon offsets. Quantifying the potential to store carbon is challenging, especially in below-ground pools of soil organic matter that dominate many cultivated landscapes (e.g., farms). However, paying farmers to storage carbon has exceptional potential to slow climate change--expected to contribute nearly 30% of the ability of land use management to offset global anthropogenic greenhouse gas emissions. The paucity of data and employment of deprecated models has resulted in skepticism of storage potential estimates. Consequently, improving our estimates is both a pressing and exciting scientific opportunity.

Project Summary

This project will draw on high-resolution and spatially-extensive data from agriculture to both develop, test, and simulate changes in potential soil carbon storage under different management regimes. Critically, the project will develop a new-age soil organic matter model that incorporates several of the conceptual breakthroughs that have been made over the last few years. Moreover, high-resolution farm level yield data will allow for unprecedented data-model comparisons via a collaboration with a private sector company (Granular and Corteva).

What will the successful applicant do

Compile code from other agricultural models and develop an adapted model with a new understanding of soil organic matter dynamics. Integrate both yield data, soil surveys, and remote sensing observations for thousands of samples to validate the model. Use the models to initialise and project future carbon storage under different management regimes and payment schemes to explore mitigation potential in agricultural landscapes.


Lal, Rattan. "Soil carbon sequestration impacts on global climate change and food security." science 304, no. 5677 (2004): 1623-1627.
Jarecki, Marek K., and Rattan Lal. "Crop management for soil carbon sequestration." Critical Reviews in Plant Sciences 22, no. 6 (2003): 471-502.
Lal, Rattan, Michael Griffin, Jay Apt, Lester Lave, and M. Granger Morgan. "Managing soil carbon." (2004): 393-393.