Falconer Ruth E, Battaia Guillaume, Schmidt Sonja, Baveye Philippe, Chenu Claire, Otten Wilfred
SIMBIOS School of Science, Engineering and Technology, Abertay University, Dundee, United Kingdom.
Bioemco, AgroParisTech, Université Paris-Saclay, Thiverval-Grignon, France.
PLoS One. 2015 May 19;10(5):e0123774. doi: 10.1371/journal.pone.0123774. eCollection 2015.
Soil respiration represents the second largest CO2 flux from terrestrial ecosystems to the atmosphere, and a small rise could significantly contribute to further increase in atmospheric CO2. Unfortunately, the extent of this effect cannot be quantified reliably, and the outcomes of experiments designed to study soil respiration remain notoriously unpredictable. In this context, the mathematical simulations described in this article suggest that assumptions of linearity and presumed irrelevance of micro-scale heterogeneity, commonly made in quantitative models of microbial growth in subsurface environments and used in carbon stock models, do not appear warranted. Results indicate that microbial growth is non-linear and, at given average nutrient concentrations, strongly dependent on the microscale distribution of both nutrients and microbes. These observations have far-reaching consequences, in terms of both experiments and theory. They indicate that traditional, macroscopic soil measurements are inadequate to predict microbial responses, in particular to rising temperature conditions, and that an explicit account is required of microscale heterogeneity. Furthermore, models should evolve beyond traditional, but overly simplistic, assumptions of linearity of microbial responses to bulk nutrient concentrations. The development of a new generation of models along these lines, and in particular incorporating upscaled information about microscale processes, will undoubtedly be challenging, but appears to be key to understanding the extent to which soil carbon mineralization could further accelerate climate change.
土壤呼吸是陆地生态系统向大气输送二氧化碳的第二大通量,其微小增加都可能显著促使大气中二氧化碳进一步增多。遗憾的是,这种效应的程度无法可靠地量化,旨在研究土壤呼吸的实验结果仍然极难预测。在此背景下,本文所述的数学模拟表明,地下环境中微生物生长定量模型以及碳储量模型中常用的线性假设和微尺度异质性无关假设似乎并不合理。结果表明,微生物生长是非线性的,在给定的平均养分浓度下,强烈依赖于养分和微生物的微尺度分布。这些观察结果在实验和理论方面都具有深远影响。它们表明,传统的宏观土壤测量不足以预测微生物反应,尤其是对温度升高的反应,需要明确考虑微尺度异质性。此外,模型应超越传统但过于简单的微生物对总养分浓度反应线性假设。沿着这些思路开发新一代模型,特别是纳入有关微尺度过程的尺度上推信息,无疑具有挑战性,但似乎是理解土壤碳矿化在多大程度上可能进一步加速气候变化的关键。