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SCIENCE DRIVER

Ineractions Between Microbes and Minerals Control the Emergent Temperature Response of SOM Decomposition Carbon Cycle Feedback Uncertainties J.Y. Tang and W.J. Riley. RESULTS. SCIENCE DRIVER. Results reject a static Q 10 Predict a highly variable CUE under realistic temperature variability.

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SCIENCE DRIVER

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  1. Ineractions Between Microbes and Minerals Control the Emergent Temperature Response of SOM Decomposition Carbon Cycle Feedback Uncertainties J.Y. Tang and W.J. Riley RESULTS SCIENCE DRIVER • Results reject a static Q10 • Predict a highly variable CUE under realistic temperature variability • Field and laboratory experiments have found Q10 and ΔEact vary spatiotemporally, making predicted carbon-climate feedbacks very uncertain • We developed a thermodynamically based decomposition model to explore interactions between temperature, microbial biogeochemistry, microbial community dynamics, and mineral surface sorptive reactions (submitted Nature Geoscience) METHODS • T temporal variability leads to different SOM predictions through impacts on the emergent CUE • We applied the “equal-carbon” method (to be argued faulty) and found asymmetric T sensitivities and differences between “recalcitrant” and “labile” SOM • SOC and mineral surfaces compete for extracellular enzymes • DOC competes with extracellular enzymes for mineral surfaces • Mineral surfaces compete with microbes for DOC • Thermal adaptation and community shifts affect respiration rates under 4 K warming scenario • Including diurnal cycle removed community shift • Assumed Langmuir isotherm • Applied Equilibrium Chemistry Approximation (ECA) kinetics (Tang and Riley 2013) for competition • Model prognoses CUE using the dynamic energy budget (DEB) theory • Thermodynamically consistent treatment of structural maintenance, structural growth, and extracellular enzyme production in metabolism • Includes an internal reserve pool • Parameterized the temperature dependencies of (1) enzymatic SOC degradation, (2) microbial DOC uptake, (3) microbial reserve pool turnover, (4) mineral surface sorption reactions, (5) microbial maintenance, (6) microbial cell growth, and (7) enzyme production CONCLUSIONS • Many parameters used in BGC models are dynamic emergent system responses resulting from abiotic factors, microbial physiology, microbial community structure, and enzymes • Therefore, models that have statically parameterized these emergent responses are mechanistically incorrect and likely inaccurately predicting long-term soil organic matter dynamics.

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