Impact of biogeochemical processess on mineral weathering and transformation

Abstract

Determining how microorganisms directly and indirectly affect elemental speciation is critical for developing more predictive assessments of numerous biogeochemical cycles. This dissertation aims to constrain microbe-mineral interactions of two model systems, the weathering of chromium (Cr)-containing solids and the reverse weathering of silicon (Si)-containing solids (e.g. biogenic silica). The first model system, the bioweathering of Cr-containing solids, was chosen due to the lack of information regarding redox-independent weathering of solid phase Cr by environmentally relevant organic molecules. In this study, microbially mediated weathering of Cr-containing minerals was discovered to occur via both ligand complexation and increased solid solubility. This redox-independent process also introduced a range of Cr isotope signatures that were within the range of previously observed Cr isotope signatures in rock records linked to Cr redox cycling. The choice of the second model system, the reverse weathering of Si-containing solids, was motivated by current knowledge gaps regarding the global Si cycle. This dissertation presents characterization of the composition of organic matter produced by diatoms as well as the transformation of diatom-derived biogenic silica during early diagenesis. Nutrient regime was found to influence the amount and composition of dissolved organic matter produced by a model diatom species, which provides insights into the composition and bioavailability of dissolved organic matter under forecasted shifts to different nutrient regimes in certain ocean regions. Furthermore, the transformation of biogenic silica into aluminosilicate mineral phases was found to occur within a relatively short time frame and strongly controlled by the presence and concentration of aluminum and iron. Overall, the results of this dissertation demonstrate further advances in addressing current gaps regarding microbe-mineral interactions in the two model systems.