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Thermodynamic theory explains the temperature optima of soil microbial processes and high Q(10) values at low temperatures

机译:热力学理论解释了土壤微生物过程的最佳温度和低温下的高Q(10)值

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Our current understanding of the temperature response of biological processes in soil is based on the Arrhenius equation. This predicts an exponential increase in rate as temperature rises, whereas in the laboratory and in the field, there is always a clearly identifiable temperature optimum for all microbial processes. In the laboratory, this has been explained by denaturation of enzymes at higher temperatures, and in the field, the availability of substrates and water is often cited as critical factors. Recently, we have shown that temperature optima for enzymes and microbial growth occur in the absence of denaturation and that this is a consequence of the unusual heat capacity changes associated with enzymes. We have called this macromolecular rate theory - MMRT (Hobbs etal., , ACS Chem. Biol. 8:2388). Here, we apply MMRT to a wide range of literature data on the response of soil microbial processes to temperature with a focus on respiration but also including different soil enzyme activities, nitrogen and methane cycling. Our theory agrees closely with a wide range of experimental data and predicts temperature optima for these microbial processes. MMRT also predicted high relative temperature sensitivity (as assessed by Q(10) calculations) at low temperatures and that Q(10) declined as temperature increases in agreement with data synthesis from the literature. Declining Q(10) and temperature optima in soils are coherently explained by MMRT which is based on thermodynamics and heat capacity changes for enzyme-catalysed rates. MMRT also provides a new perspective, and makes new predictions, regarding the absolute temperature sensitivity of ecosystems - a fundamental component of models for climate change.
机译:我们目前对土壤中生物过程的温度响应的了解基于Arrhenius方程。这可以预测温度随温度的升高呈指数增长,而在实验室和现场,对于所有微生物过程,总有一个明显可识别的最佳温度。在实验室中,这是通过高温下酶的变性来解释的,并且在现场,经常提到底物和水的可用性是关键因素。最近,我们已经表明,在没有变性的情况下会发生酶和微生物生长的最佳温度,这是与酶相关的异常热容变化的结果。我们将这种大分子速率理论称为MMRT(Hobbs et al。,ACS Chem。Biol。8:2388)。在这里,我们将MMRT应用到有关土壤微生物过程对温度的响应的大量文献数据中,重点是呼吸作用,还包括不同的土壤酶活性,氮和甲烷循环。我们的理论与广泛的实验数据非常吻合,并预测了这些微生物过程的最佳温度。 MMRT还预测了在低温下较高的相对温度敏感性(通过Q(10)计算评估),并且随着温度的升高Q(10)下降,这与文献中的数据综合相符。 MMRT一致地解释了土壤中Q(10)的下降和温度的最优值,MMRT基于热力学和热容量随酶催化速率的变化而变化。 MMRT还就生态系统的绝对温度敏感性(气候变化模型的基本组成部分)提供了新的视角并做出了新的预测。

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