Department of Biology, University of Oregon, Oregon, USA.
Institute of Ecology and Evolution, University of Oregon, Oregon, USA.
Environ Microbiol. 2023 Feb;25(2):268-282. doi: 10.1111/1462-2920.16275. Epub 2022 Nov 20.
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.
由于许多未知的种群动态、生理和反应动力学参数以及物种组成的不确定性,预测微生物代谢率和新兴生物地球化学通量仍然具有挑战性。在这里,我们表明,当种群动态和反应动力学的作用时间尺度比物理混合过程短得多时,可以消除对这些参数的需求。这种情况在混合不良的水柱和沉积物中很常见。在这种“快速反应-传输”(FRT)极限下,预测所需的只是化学边界条件、物理混合过程和反应计量,而不需要了解物种组成、生理学或种群/反应动力学参数。使用跨越 2001-2014 年的时间序列数据以及在永久缺氧的卡里亚科盆地的 180-900 米深度,我们证明 FRT 方法可以准确预测主要电子供体和受体的动态(在所有情况下 Pearson r≥0.9)。因此,该系统中的许多微生物过程在很大程度上受到传输限制,因此无论物种组成、种群动态和动力学如何,都是可以预测的。我们的方法可以为许多微生物群落动态和动力学未知的系统进行预测。我们的发现还揭示了微生物系统中经常观察到的功能和分类学之间脱钩的一种机制。