Using maximum entropy production to describe microbial biogeochemistry over time and space in a meromictic pond
Using maximum entropy production to describe microbial biogeochemistry over time and space in a meromictic pond
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DOI：
10.3389/fenvs.2018.00100
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发表时间：
2018-02
期刊：
影响因子：
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通讯作者：
J. Vallino;J. Huber
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文献类型：
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作者：
J. Vallino;J. Huber
最大熵产生(MEP)猜想假定，具有多个自由度的系统可能会组织起来以最大限度地提高自由能量的耗散率。以前的工作表明，生物系统可以通过利用进化获得和改进的时间策略来最大化自由能量的耗散，并通过合作在空间上击败非生物系统。在这项研究中，我们开发了一个MEP模型来描述在Siders Pond观察到的生物地球化学，Siders Pond是一个磷酸盐受限的分生系统，位于马萨诸塞州法尔茅斯，由于密度驱动的层结支持厌氧光合作用，以及催化O、N、S、Fe和Mn等氧化还原循环的微生物群落，该系统显示出陡峭的化学梯度。MEP模型使用代谢网络来表示微生物的氧化还原反应，其中生物量的分配和反应速率是通过求解随时间最大化熵产生的优化问题和受平流-弥散-反应模型约束的一维垂直剖面来确定的。我们介绍了一种新的光营养建模方法，并显式地表示了好氧光自养、缺氧光自养和厌氧光自养。代谢网络还包括异养菌、硫酸盐还原菌、硫化物氧化菌以及好氧和厌氧牧草的反应。将模型结果与在Siders Pond的一个15米深的站点上收集的8个深度的24小时生物地球化学成分的观测结果进行了比较。在长间隔(3d)上最大化熵产生的结果比短(0.25d)间隔优化产生的结果更类似于现场观测，这支持了随时间最大化熵产生的时间策略的重要性。此外，我们发现，必须在局部最大化熵产生，而不是在全球范围内，因为非生物过程，如水的光吸收，能量势迅速下降。野外观测和模拟结果的结合表明，自然界中的微生物系统可以通过应用在时间和空间上的最大熵产生猜想来准确地描述。
The maximum entropy production (MEP) conjecture posits that systems with many degrees of freedom will likely organize to maximize the rate of free energy dissipation. Previous work indicates that biological systems can outcompete abiotic systems by maximizing free energy dissipation over time by utilizing temporal strategies acquired and refined by evolution, and over space via cooperation. In this study, we develop an MEP model to describe biogeochemistry observed in Siders Pond, a phosphate limited meromictic system located in Falmouth, MA that exhibits steep chemical gradients due to density-driven stratification that supports anaerobic photosynthesis as well as microbial communities that catalyze redox cycles involving O, N, S, Fe and Mn. The MEP model uses a metabolic network to represent microbial redox reactions, where biomass allocation and reaction rates are determined by solving an optimization problem that maximizes entropy production over time and a 1D vertical profile constrained by an advection-dispersion-reaction model. We introduce a new approach for modeling phototrophy and explicitly represent aerobic photoautotrophs, anoxygenic photoheterotrophs and anaerobic photoautotrophs. The metabolic network also includes reactions for heterotrophic bacteria, sulfate reducing bacteria, sulfide oxidizing bacteria and aerobic and anaerobic grazers. Model results were compared to observations of biogeochemical constituents collected over a 24 hour period at 8 depths at a single 15 m deep station in Siders Pond. Maximizing entropy production over long (3 d) intervals produced results more similar to field observations than short (0.25 d) interval optimizations, which support the importance of temporal strategies for maximizing entropy production over time. Furthermore, we found that entropy production must be maximized locally instead of globally where energy potentials are degraded quickly by abiotic processes, such as light absorption by water. This combination of field observations with modeling results show that microbial systems in nature can be accurately described by the maximum entropy production conjecture applied over time and space.