Compound-specific radiocarbon analysis as new tool to investigate C-dynamics in sustainable agriculture

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Agriculture intensification is a key source of anthropogenic carbon dioxide, in turn contributing to global warming and climate change. Whilst numerous agricultural practices aim to improve productivity, such as ploughing or use of inorganic fertilizers, they also disrupt natural carbon storage mechanisms. Causing mineralisation of the organic matter to carbon dioxide, then emitted to the atmosphere. Carbon sequestration in agricultural soils represents a vital opportunity to recover soil organic matter and combat anthropogenic carbon dioxide emissions. As such the UK has joined the 4 pour mille initiative which aims to increase carbon storage in agricultural soils by 0.4% per year. To achieve this goal the current amount of carbon stored must be quantified and the mechanisms driving soil organic matter storage must be understood. Recently, the view that compounds possess an intrinsic recalcitrance, due to their molecular properties, has been fundamentally questioned. Instead current research has postulated that biological and physico-chemical stabilisation mechanisms are responsible for long term persistence. However, this stabilisation may vary between biochemical classes and locations. The project will utilise the long term experiments conducted at Rothamstead Research, studying both fresh and archived soils. Highly developed fractionation methods will be used to isolate and quantify characteristic target compounds. These fractions will also be purity checked using high field NMR approach pioneered at the University of Bristol. Additionally, 14C measurements using the University of Bristol radiocarbon accelerator will be used to determine the turnover rates of these target compounds and elucidate how these rates are dependent on the biological or physico-chemical protection mechanisms versus their intrinsic recalcitrance. Selection of these target compounds will be in collaboration with Rothamsted Research, as this mechanistic understanding will contribute to development of the RothC model, as well as informing agricultural management decisions aiming to improve agricultural sustainability.