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Synergistic effects of diffusion and microbial physiology reproduce the Birch effect in a micro-scale model

机译:扩散和微生物生理学的协同效应在微观模型中再现了桦木效应

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Large rainfall events following drought cause pulses of CO2 flux that are higher than models predict. This phenomenon, named the "Birch effect" after its discoverer, has been observed for decades, and will influence carbon-climate feedbacks as drying-rewetting (DRW) cycles become more common under intensified climates. Yet, the many interacting factors that determine how soil DRW cycles affect C balance have been difficult to separate empirically. Here we use a spatially explicit biogeochemical-microbial model to examine the mechanisms underlying CO2 dynamics under DRW. We independently model physiological activity and diffusion based on how they vary with (constant) moisture levels in nature, and subject the model to DRW to test the importance of different mechanisms in models with one or two microbial functional groups (cheaters and producers). Our model reproduces respiration patterns similar to empirical observations of the Birch effect when we include mechanisms that link water content to microbial growth and to diffusion rate, whereas inclusion of either mechanism alone produces significantly lower pulses upon rewetting. Diffusion limitation under drought increases substrate availability under rewetting, a process mediated by biogeochemical hotspots and continued enzyme activity under drought. At the same time, high microbial growth under rewetting is needed to replenish enzyme pools and to sustain the biomass required to generate respiration pulses under repeated DRW. Inclusion of cheaters in the model dampens the size of the rewetting pulse and the cumulative amount of CO2 release, as cheaters outcompete producers and reduce overall biomass. Our results provide several novel hypotheses regarding the microbial, biogeochemical, and spatial processes that mediate the Birch effect, which will contribute to a better mechanistic understanding of this important deviation from model predictions. (C) 2015 Elsevier Ltd. All rights reserved.
机译:干旱后发生的大降雨事件导致CO2通量脉冲高于模型预测。这种现象以其发现者的名字命名为“桦木效应”,已经观测了数十年,随着强度增加气候下的干湿重湿(DRW)循环变得越来越普遍,它将影响碳气候反馈。但是,决定土壤DRW循环如何影响C平衡的许多相互作用因素很难凭经验进行分离。在这里,我们使用空间明确的生物地球化学-微生物模型来研究DRW下CO2动力学的潜在机制。我们基于生理活动和扩散随自然中(恒定)水分含量的变化而独立地建模,然后对该模型进行DRW检验,以测试具有一个或两个微生物功能组(加热器和生产者)的模型中不同机制的重要性。当我们包含将水含量与微生物生长和扩散速率相关联的机制时,我们的模型再现的呼吸模式类似于对桦木效应的经验观察结果,而单独包含这两种机制都会在重新润湿时产生明显更低的脉冲。干旱条件下的扩散限制增加了再湿润下的底物利用率,这是由生物地球化学热点和干旱下持续的酶活性介导的。同时,在重复润湿下需要大量的微生物在重新润湿下生长以补充酶库并维持产生呼吸脉冲所需的生物量。在模型中包含作弊者可减少重新润湿脉冲的大小和二氧化碳释放的累积量,因为作弊者胜过生产者,并减少了整体生物量。我们的研究结果提供了关于介导桦木效应的微生物,生物地球化学和空间过程的几种新颖假设,这将有助于更好地从模型预测中更好地理解这一重要偏差。 (C)2015 Elsevier Ltd.保留所有权利。

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