Root Exudate Driven Perturbations of Iron Oxide-Organic Matter Assemblages: Impact on Phase Transformations and Carbon Fractionation

With support from the Environmental Chemical Sciences (ECS) program in the Division of Chemistry, Professors R. Lee Penn and Rene Boiteau at the University of Minnesota investigate the stability of organic matter (OM) and minerals in soils and sediments. Results will elucidate and improve predictions of OM accumulation and degradation. Assemblages of iron oxide minerals and organic matter, hereafter referred to as Fe-OM, are major regulators of global carbon and nutrient cycles, with OM often protected by minerals through complex and interconnected chemical processes. Using model compounds and whole root exudates, the team will examine how plant exudates transform Fe-OM and impact the distribution of OM within the solid and liquid phases and at their interfaces as minerals change over time. Findings will elucidate mechanisms of OM stabilization and disruption that can shed light on how plant and microbial processes affect OM stability, potentially leading to new strategies for increasing soil carbon and supporting sustainable land use. The project will also develop open-source machine learning algorithms to predict how organic molecules react with minerals in soil, with applications to understanding the fate of various chemicals, including pollutants. This project aims to test the hypothesis that plant exudate molecules that act as both reductants and chelates may be particularly effective at promoting the release of Fe and OM from Fe-OM, and that certain Fe-OM materials resist transformation. It combines experiments using varied model organic compounds and root exudates and synthesized Fe minerals with a broad suite of experiments and analyses. The three primary aims are (1) quantify the distribution and fractionation of organic matter during Fe(II) catalyzed iron oxide transformations; (2) identify which exudate model compounds and whole root exudate molecules disrupt Fe-OM, releasing dissolved OM and Fe(II) and promoting phase transformations, and understand the relevant modes of action; and (3) characterize the impact of chemical gradients on OM redistribution upon introduction of Fe(II), model exudates, and whole root exudate using flow-through reactors to better mimic field conditions. The three tasks will focus on progressively narrower Fe-OM materials and exudate chemistries that exhibit the greatest differences in reactivity to ultimately reveal mechanisms and determine which Fe-OM are most susceptible and resistant to those processes. The resulting large data set relating organic molecule structural characteristics to their distribution within the solid and liquid phases and at their interfaces will be leveraged to develop a predictive machine learning model. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.