4.8 Article

Thermodynamic theory explains the temperature optima of soil microbial processes and high Q10 values at low temperatures

期刊

GLOBAL CHANGE BIOLOGY
卷 20, 期 11, 页码 3578-3586

出版社

WILEY
DOI: 10.1111/gcb.12596

关键词

macromolecular rate theory; MMRT; Q10; respiration; soil; temperature optimum; temperature sensitivity

资金

  1. Landcare Research (Ecosystems Services) [C09X0705]
  2. University of Waikato
  3. New Zealand Agricultural Greenhouse Gas Research Centre

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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.

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