Representing Organic Matter Thermodynamics in Biogeochemical Reactions via Substrate-Explicit Modeling

Frontiers in Microbiology
Hyun-Seob SongTimothy D. Scheibe

Abstract

Predictive biogeochemical modeling requires data-model integration that enables explicit representation of the sophisticated roles of microbial processes that transform substrates. Data from high-resolution organic matter (OM) characterization are increasingly available and can serve as a critical resource for this purpose, but their incorporation into biogeochemical models is often prohibited due to an over-simplified description of reaction networks. To fill this gap, we proposed a new concept of biogeochemical modeling-termed substrate-explicit modeling-that enables parameterizing OM-specific oxidative degradation pathways and reaction rates based on the thermodynamic properties of OM pools. Based on previous developments in the literature, we characterized the resulting kinetic models by only two parameters regardless of the complexity of OM profiles, which can greatly facilitate the integration with reactive transport models for ecosystem simulations by alleviating the difficulty in parameter identification. The two parameters include maximal growth rate (μmax) and harvest volume (Vh) (i.e., the volume that a microbe can access for harvesting energy). For every detected organic molecule in a given sample, our approach prov...Continue Reading

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Citations

Jan 10, 2021·Metabolites·Vanessa A Garayburu-CarusoEmily B Graham
Nov 21, 2021·Proceedings of the National Academy of Sciences of the United States of America·Salvatore CalabresePhilippe Van Cappellen

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