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Agricultural soil organic carbon stocks in the north-eastern Iberian Peninsula: Drivers and spatial variability

机译:东北伊比利亚半岛农业土壤有机碳股:司机及空间变异性

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Estimating soil organic carbon (SOC) stocks under agriculture, assessing the importance of their drivers and understanding the spatial distribution of SOC stocks are crucial to predicting possible future SOC stocks scenarios under climate change conditions and to designing appropriate mitigation and adaptation strategies. This study characterized and modelled SOC stocks at two soil depth intervals, topsoil (0-30 an) and subsoil (30-100 cm), based on both legacy and recent data from 7245 agricultural soil profiles and using environmental drivers (climate, agricultural practices and soil properties) for agricultural soils in Catalonia (NE Spain). Generalized Least Square (GLS) and Geographical Weighted Regression (GWR) were used as modelling approaches to: (i) assess the main SOC stock drivers and their effects on SOC stocks; (ii) analyse spatial variability of SOC stocks and their relationships with the main drivers; and (iii) predict and map SOC stocks at the regional scale. While topsoil variation of SOC stocks depended mainly on climate, soil texture and agricultural variables, subsoil SOC stocks changes depended mainly on soil attributes such us soil texture, clay content, soil type or depth to bedrock. The GWR model revealed that the relationship between SOC stocks and drivers varied spatially. Finally, the study was only able to predict and map topsoil SOC stocks at the regional scale, because controlling factors of SOC stocks at the subsoil level were largely unavailable for digital mapping. According to the resulting map, the mean SOC stock value for Catalan agriculture at the topsoil level was 4.88 +/- 0.89 kg/m(2) and the total magnitude of the carbon pool in agricultural soils of Catalonia up to 30 cm reached 47.9 Tg. The present study findings are useful for defining carbon sequestration strategies at the regional scale related with agricultural land use changes and agricultural management practices in a context of climate change. (C) 2019 Elsevier B.V. All rights reserved.
机译:估计农业土壤有机碳(SOC)股,评估其司机的重要性和了解SoC股票的空间分布对于预测气候变化条件下可能的未来SoC股情景以及设计适当的缓解和适应策略至关重要。本研究以两种土壤深度间隔,表土(0-30A)和Substhill(30-100厘米)为特征和建模的SoC股,基于来自7245个农业土壤概况的遗产和最近的数据,并使用环境司机(气候,农业实践加泰罗尼亚农业土壤及土壤特性(NE西班牙)。广义最小二乘(GLS)和地理加权回归(GWR)被用作建模方法:(i)评估主要的SOC股司机及其对SoC股的影响; (ii)分析SoC股的空间变异及其与主要司机的关系; (iii)在区域规模上预测和地图SoC股。虽然SoC股的表土变异主要依赖于气候,土壤质地和农业变量,但底层SoC股票的变化主要依赖于土壤属性,这些土壤纹理,粘土含量,土壤类型或深度上的基岩。 GWR模型透露,SoC股票和司机之间的关系在空间上变化。最后,该研究只能在区域规模上预测和地图表土SOC股,因为在底土水平的SoC股的控制因素很大程度上无法用于数字映射。根据结果​​地图,表土水平的加泰罗尼亚农业的平均SoC股票价值为4.88 +/- 0.89千克/米(2),加泰罗尼亚农业土壤中的碳库总幅度高达30厘米达到47.9吨。目前的研究结果可用于在气候变化背景下定义与农业土地利用变化和农业管理实践有关的区域规模的碳封存策略。 (c)2019 Elsevier B.v.保留所有权利。

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