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Land Use and Land Cover Affect the Depth Distribution of Soil Carbon: Insights From a Large Database of Soil Profiles
Frontiers in Environmental Science ( IF 4.6 ) Pub Date : 2020-08-25 , DOI: 10.3389/fenvs.2020.00146
Benjamin N. Sulman , Jennifer Harden , Yujie He , Claire Treat , Charles Koven , Umakant Mishra , Jonathan A. O’Donnell , Lucas E. Nave

Soils contain a large and dynamic fraction of global terrestrial carbon stocks. The distribution of soil carbon (SC) with depth varies among ecosystems and land uses and is an important factor in calculating SC stocks and their vulnerabilities. Systematic analysis of SC depth distributions across databases of SC profiles has been challenging due to the heterogeneity of soil profile measurements, which vary in depth sampling. Here, we fit over 40,000 SC depth profiles to an exponential decline relationship with depth to determine SC concentration at the top of the mineral soil, minimum SC concentration at depth, and the characteristic “length” of SC concentration decline with depth. Fitting these parameters allowed profile characteristics to be analyzed across a large and heterogeneous dataset. We then assessed the differences in these depth parameters across soil orders and land cover types and between soil profiles with or without a history of tillage, as represented by the presence of an Ap horizon. We found that historically tilled soils had more gradual decreases of SC with depth (greater e-folding depth or Z∗), deeper SC profiles, lower SC concentrations at the top of the mineral soil, and lower total SC stocks integrated to 30 cm. The large database of profiles allowed these results to be confirmed across different land cover types and spatial areas within the Continental United States, providing robust evidence for systematic impacts of historical tillage on SC stocks and depth distributions.

中文翻译:

土地利用和土地覆盖影响土壤碳的深度分布:来自大型土壤剖面数据库的见解

土壤包含全球陆地碳储量的大部分动态部分。土壤碳 (SC) 随深度的分布因生态系统和土地用途而异,是计算 SC 库及其脆弱性的重要因素。由于土壤剖面测量的异质性,土壤剖面测量的异质性在深度采样中有所不同,因此对 SC 剖面数据库中 SC 深度分布的系统分析一直具有挑战性。在这里,我们将超过 40,000 个 SC 深度剖面拟合成与深度的指数下降关系,以确定矿质土壤顶部的 SC 浓度、深度处的最小 SC 浓度以及 SC 浓度随深度下降的特征“长度”。拟合这些参数允许跨大型异构数据集分析轮廓特征。然后,我们评估了这些深度参数在土壤顺序和土地覆盖类型之间以及在有或没有耕作历史的土壤剖面之间的差异,如 Ap 层的存在所代表的。我们发现,历史上耕作的土壤随着深度(更大的 e 折叠深度或 Z*)、更深的 SC 剖面、矿质土壤顶部的更低 SC 浓度以及整合到 30 cm 的总 SC 储量更低,SC 会逐渐减少。大型剖面数据库允许在美国大陆不同土地覆盖类型和空间区域中确认这些结果,为历史耕作对 SC 种群和深度分布的系统影响提供有力的证据。如Ap视界的存在所代表。我们发现,历史上耕作的土壤随着深度(更大的 e 折叠深度或 Z*)、更深的 SC 剖面、矿质土壤顶部的更低 SC 浓度以及整合到 30 cm 的总 SC 储量更低,SC 会逐渐减少。大型剖面数据库允许在美国大陆不同土地覆盖类型和空间区域中确认这些结果,为历史耕作对 SC 种群和深度分布的系统影响提供有力的证据。如Ap视界的存在所代表。我们发现,历史上耕作的土壤随着深度(更大的 e 折叠深度或 Z*)、更深的 SC 剖面、矿质土壤顶部的更低 SC 浓度以及整合到 30 cm 的总 SC 储量更低,SC 会逐渐减少。大型剖面数据库允许在美国大陆不同土地覆盖类型和空间区域中确认这些结果,为历史耕作对 SC 种群和深度分布的系统影响提供有力的证据。
更新日期:2020-08-25
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