4.6 Article

Transport-limited reactions in microbial systems

Journal

ENVIRONMENTAL MICROBIOLOGY
Volume 25, Issue 2, Pages 268-282

Publisher

WILEY
DOI: 10.1111/1462-2920.16275

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When population dynamics and reaction kinetics operate at much shorter time scales than physical mixing processes, the need for unknown population dynamical, physiological and reaction-kinetic parameters and uncertainties in species composition can be eliminated. In this 'fast-reaction-transport' (FRT) limit, accurate predictions can be made based on chemical boundary conditions, physical mixing processes and reaction stoichiometries without knowledge of species composition, physiology or population/reaction kinetic parameters. Our findings suggest that microbial processes in poorly mixed water columns and sediments are largely transport limited and thus predictable regardless of species composition, population dynamics and kinetics.
Predicting microbial metabolic rates and emergent biogeochemical fluxes remains challenging due to the many unknown population dynamical, physiological and reaction-kinetic parameters and uncertainties in species composition. Here, we show that the need for these parameters can be eliminated when population dynamics and reaction kinetics operate at much shorter time scales than physical mixing processes. Such scenarios are widespread in poorly mixed water columns and sediments. In this 'fast-reaction-transport' (FRT) limit, all that is required for predictions are chemical boundary conditions, the physical mixing processes and reaction stoichiometries, while no knowledge of species composition, physiology or population/reaction kinetic parameters is needed. Using time-series data spanning years 2001-2014 and depths 180-900 m across the permanently anoxic Cariaco Basin, we demonstrate that the FRT approach can accurately predict the dynamics of major electron donors and acceptors (Pearson r >= 0.9 in all cases). Hence, many microbial processes in this system are largely transport limited and thus predictable regardless of species composition, population dynamics and kinetics. Our approach enables predictions for many systems in which microbial community dynamics and kinetics are unknown. Our findings also reveal a mechanism for the frequently observed decoupling between function and taxonomy in microbial systems.

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