Modelling in situ activities of enzymes as a tool to explain seasonal variation of soil respiration from agro-ecosystems
Modelling in situ activities of enzymes as a tool to explain seasonal variation of soil respiration from agro-ecosystems
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DOI：
10.1016/j.soilbio.2014.12.001
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发表时间：
2015-02-01
影响因子：
9.7
通讯作者：
Poll, Christian
中科院分区：
文献类型：
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作者：
Ali, Rana S.;Ingwersen, Joachim;Poll, Christian
了解原位酶活性有助于澄清土壤有机碳(SOC)的命运，SOC是预测未来气候的最大不确定性之一。在这里，我们首次使用原位酶活性模型来解释土壤呼吸的季节变化，从而探索了土壤温度和水分对SOM分解的影响。我们测定了德国西南部农业土壤中三种酶(β-葡萄糖苷酶、木聚糖酶和酚氧化酶)的温度敏感性(Q(10))和β-葡萄糖苷酶的湿度敏感性。β-葡萄糖苷酶、木聚糖酶和酚氧化酶的潜在活性以及Q(10)中的β-葡萄糖苷酶和酚氧化酶的活性存在显著的季节变化，而木聚糖酶的活性没有明显的季节变化。我们测量了4种水分水平(12%-32%)下β-葡萄糖苷酶活性的水分敏感性，并拟合了一个饱和函数，反映了在低水分条件下由于限制底物扩散而增加的底物限制。β-葡萄糖苷酶活性的水分响应函数全年保持稳定。酶对温度和湿度的敏感性仍然是C模型中最大的不确定性之一。因此，我们使用响应函数来模拟基于温度和基于温度和湿度的原位酶活性，以表征SOC分解的季节变化。我们发现温度是控制原位酶活性的主要因素。为了证明我们的模拟方法的相关性，我们将模拟的原位酶活性与每周测量的土壤呼吸数据进行了比较。基于温度的原位酶活性很好地解释了土壤呼吸的季节变化，模型效率在0.35到0.78之间。与我们基于酶的方法相比，对现场土壤温度的指数响应函数的拟合对土壤呼吸的解释程度较小。添加土壤水分作为辅助因素仅部分改善了模型的效率。我们的结果证明了这种新方法解释酶相关过程的季节变化的潜力。(C)2014爱思唯尔有限公司。保留所有权利。
Understanding in situ enzyme activities could help clarify the fate of soil organic carbon (SOC), one of the largest uncertainties in predicting future climate. Here, we explored the role of soil temperature and moisture on SOM decomposition by using, for the first time, modelled in situ enzyme activities as a proxy to explain seasonal variation in soil respiration. We measured temperature sensitivities (Q(10)) of three enzymes (beta-glucosidase, xylanase and phenoloxidase) and moisture sensitivity of beta-glucosidase from agricultural soils in southwest Germany. Significant seasonal variation was found in potential activities of beta-glucosidase, xylanase and phenoloxidase and in Q(10) for beta-glucosidase and phenoloxidase activities but not for xylanase. We measured moisture sensitivity of beta-glucosidase activity at four moisture levels (12% -32%), and fitted a saturation function reflecting increasing substrate limitation due to limited substrate diffusion at low water contents. The moisture response function of beta-glucosidase activity remained stable throughout the year. Sensitivity of enzymes to temperature and moisture remains one of the greatest uncertainties in C models. We therefore used the response functions to model temperature-based and temperature and moisture-based in situ enzyme activities to characterize seasonal variation in SOC decomposition. We found temperature to be the main factor controlling in situ enzyme activities. To prove the relevance of our modelling approach, we compared the modelled in situ enzyme activities with soil respiration data measured weekly. Temperature-based in situ enzyme activities explained seasonal variability in soil respiration well, with model efficiencies between 0.35 and 0.78. Fitting an exponential response function to in situ soil temperature explained soil respiration to a lesser extent than our enzyme-based approach. Adding soil moisture as a co-factor improved model efficiencies only partly. Our results demonstrate the potential of this new approach to explain seasonal variation of enzyme related processes. (C) 2014 Elsevier Ltd. All rights reserved.