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Soil organic carbon in semiarid alpine regions: the spatial distribution, stock estimation, and environmental controls

机译:半干旱高寒地区的土壤有机碳:空间分布,储量估算和环境控制

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Purpose Soil organic carbon (SOC) in alpine regions is characterized by a strong local heterogeneity, which may contribute to relatively large uncertainties in regional SOC stock estimation. However, the patterns, stock, and environmental controls of SOC in semiarid alpine regions are still less understood. Therefore, the purpose of this study is to comprehensively quantify the stock and controls of SOC in semiarid alpine regions. Materials and methods Soils from 138 study sites across a typical semiarid alpine basin (1755-5051 m, similar to 1 x 10(4) km(2)) are sampled at 0-10, 10-20, 20-40, and 40-60 cm. SOC content, bulk density, soil texture, and soil pH are determined. Both a classical statistical model (i.e., a multiple linear regression, MLR) and a machine learning technique (i.e., a random forest, RF) are applied to estimate the SOC stock at a basin scale. The study further quantifies the environmental controls of SOC based on a general linear model (GLM) coupled with the structural equation modeling (SEM). Results and discussion SOC density varies significantly with topographic factors, with the highest values occurring at an elevation zone of similar to 3400 m. The results show that the SOC is more accurately estimated by the RF compared to the MLR model, with a total stock of 219.33 Tg C and an average density of 21.25 kg C m(-2) at 0-60 cm across the study basin. The GLM approach reveals that the topography is seen to explain about 58.11% of the total variation in SOC density at 0-10 cm, of which the largest two proportions are attributable to the elevation (44.32%) and the aspect factor (11.25%). The SEM approach further indicates that, of the climatic, vegetative, and edaphic factors examined, the mean annual temperature, which is mainly shaped by topography, exerts the most significant control on SOC, mainly through its direct effect, and also, through indirect effect as delivered by vegetation type. Conclusions The results of this study highlight the presence of high stocks of organic carbon in soils of semiarid alpine regions, indicating a fundamental role played by topography in affecting the overall SOC, which is mainly attained through its effects on the mean annual temperature.
机译:目的高寒地区土壤有机碳(SOC)的特征是强烈的局部异质性,这可能导致区域SOC储量估算中存在较大的不确定性。但是,对半干旱高山地区SOC的模式,储量和环境控制仍知之甚少。因此,本研究的目的是全面量化半干旱高寒地区SOC的存量和控制量。材料和方法在一个典型的半干旱高山盆地(1755-5051 m,类似于1 x 10(4)km(2))的138个研究地点的土壤分别以0-10、10-20、20-40和40采样-60厘米确定SOC含量,堆密度,土壤质地和土壤pH。既可以应用经典统计模型(即多元线性回归,MLR),也可以使用机器学习技术(即,随机森林,RF)来估算流域规模的SOC。该研究基于通用线性模型(GLM)和结构方程模型(SEM)进一步量化了SOC的环境控制。结果与讨论SOC密度随地形因素而显着变化,最高值出现在海拔3400 m处。结果表明,与MLR模型相比,RF可以更准确地估计SOC,整个研究盆地的总存量为219.33 Tg C,0-60 cm处的平均密度为21.25 kg C m(-2)。 GLM方法表明,地形可解释0-10 cm SOC密度总变化的约58.11%,其中最大的两个比例可归因于高程(44.32%)和长宽比(11.25%) 。 SEM方法进一步表明,在所考察的气候,植物和水生因子中,主要由地形决定的年平均温度主要通过其直接作用以及间接作用对SOC进行最重要的控制。根据植被类型。结论这项研究的结果突出了半干旱高山地区土壤中有机碳的高储量,表明地形在影响总体SOC中起着根本作用,这主要是通过其对年平均温度的影响来实现的。

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