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土壤过程机理和强迫因子对土壤中有机碳深度分布模拟的影响。

Effects of soil process formalisms and forcing factors on simulated organic carbon depth-distributions in soils.

机构信息

Aix-Marseille Univ, CNRS, IRD, INRA, Coll de France, CEREGE, 13545 Aix en Provence, France; Ghent University, Department of Environment, Coupure Links 653, B-9000, Belgium.

Aix-Marseille Univ, CNRS, IRD, INRA, Coll de France, CEREGE, 13545 Aix en Provence, France.

出版信息

Sci Total Environ. 2019 Feb 20;652:523-537. doi: 10.1016/j.scitotenv.2018.10.236. Epub 2018 Oct 18.

Abstract

Soil organic carbon (OC) sequestration (i.e. the capture and long-term storage of atmospheric CO) is being considered as a possible solution to mitigate climate change, notably through land use change (conversion of cropped land into pasture) and conservation agricultural practices (reduced tillage). Subsoil horizons (from 30 cm to 1 m) contribute to ca. half the total amount of soil OC, and the slow dynamics of deep OC as well as the relationships between the OC depth distribution and changes in land use and tillage practices still need to be modelled. We developed a fully modular, mechanistic OC depth distribution model, named OC-VGEN. This model includes OC dynamics, plant development, transfer of water, gas and heat, mixing by bioturbation and tillage as processes and climate and land use as boundary conditions. OC-VGEN allowed us to test the impact of 1) different numerical representations of root depth distribution, decomposition coefficients and bioturbation; 2) evolution of forcing factors such as land use, agricultural practices and climate on OC depth distribution at the century scale. We used the model to simulate decadal to century time scale experiments in Luvisols with different land uses (pasture and crop) and tillage practices (conventional and reduced) as well as projection scenarios of climate and land use at the horizon of 2100. We showed that, among the different tested formalisms/parametrizations: 1) the sensitivity of the simulated OC depth distribution to the tested numerical representations depended on the considered land use; 2) different numerical representations may accurately fit past soil OC evolution while leading to different OC stock predictions when tested for future forcing conditions (change of land use, tillage practice or climate).

摘要

土壤有机碳(OC)固存(即捕获和长期储存大气 CO)被认为是缓解气候变化的一种可能方法,特别是通过土地利用变化(将耕地转化为牧场)和保护性农业措施(减少耕作)。亚表层(30cm 到 1m)对土壤 OC 的总量贡献约为一半,深层 OC 的缓慢动态以及 OC 深度分布与土地利用和耕作方式变化之间的关系仍需要建模。我们开发了一个完全模块化的、基于机制的 OC 深度分布模型,名为 OC-VGEN。该模型包括 OC 动态、植物发育、水、气体和热的传递、生物扰动和耕作的混合过程以及气候和土地利用作为边界条件。OC-VGEN 使我们能够测试以下因素的影响:1)不同的根深度分布、分解系数和生物扰动的数值表示;2)土地利用、农业措施和气候等强迫因素的演变对 OC 深度分布的影响在世纪尺度上。我们使用该模型模拟了不同土地利用(牧场和作物)和耕作措施(常规耕作和少耕)的卢维斯土壤以及 2100 年气候和土地利用的预测情景的十年到百年时间尺度实验。我们表明,在测试的不同形式/参数化中:1)模拟的 OC 深度分布对测试的数值表示的敏感性取决于所考虑的土地利用;2)不同的数值表示方法可能会准确地拟合过去的土壤 OC 演化,而在测试未来的强迫条件(土地利用、耕作措施或气候的变化)时,可能会导致不同的 OC 储量预测。

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