北京市农田土壤有机碳密度空间变异及影响因素
X825; 探明区域农田土壤有机碳密度(soil organic carbon density,SOCD)空间分布特征及其影响因素对增加农田土壤碳汇、实现"双碳"目标具有重要意义.该研究以北京市为研究区,基于2022年采样实测的0～60 cm各层SOCD数据,采用3D概念模型、Mantel test、地理加权回归、地理探测器模型开展SOCD空间变异分析,探究不同因素对SOCD的影响程度及各因素间交互后的作用力.结果表明:1)研究区SOCD在空间上呈自表层向深层逐渐降低的趋势,其中0～15cm 土层的SOCD显著高于30～60 cm(P＜0.05),0～60 cm 土层的有机...
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| Published in | 农业工程学报 Vol. 40; no. 9; pp. 119 - 127 |
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| Main Authors | , , , , , |
| Format | Journal Article |
| Language | Chinese |
| Published |
安徽理工大学地球与环境学院,淮南 232001%北京市密云区土肥工作站,北京 101500%北京市耕地建设保护中心,北京 100020
01.05.2024
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1002-6819 |
| DOI | 10.11975/j.issn.1002-6819.202312032 |
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| Abstract | X825; 探明区域农田土壤有机碳密度(soil organic carbon density,SOCD)空间分布特征及其影响因素对增加农田土壤碳汇、实现"双碳"目标具有重要意义.该研究以北京市为研究区,基于2022年采样实测的0～60 cm各层SOCD数据,采用3D概念模型、Mantel test、地理加权回归、地理探测器模型开展SOCD空间变异分析,探究不同因素对SOCD的影响程度及各因素间交互后的作用力.结果表明:1)研究区SOCD在空间上呈自表层向深层逐渐降低的趋势,其中0～15cm 土层的SOCD显著高于30～60 cm(P＜0.05),0～60 cm 土层的有机碳储量约为10.80 Tg.2)土壤含水率、土壤亚类、地形部位分别对0～15、15～60、45～60 cm 土层的SOCD产生了显著影响(P＜0.05);土壤亚类、土壤母质、土壤质地、地形部位与SOCD的空间关联性较强,关联程度自表层向下逐渐增大.3)各重要因子交互后对研究区SOCD的解释能力呈双因子增强或非线性增强的关系,土壤亚类与其他各因子交互后对SOCD的解释能力提升最为突出.今后研究区内开展土壤有机碳空间变异等相关研究时应尽可能综合考虑多因素间的交互作用,其中土壤亚类(土壤类型)可作为重点指标.研究结果可为优化农田资源空间结构,制定农田固碳增汇措施提供科学参考. |
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| AbstractList | X825; 探明区域农田土壤有机碳密度(soil organic carbon density,SOCD)空间分布特征及其影响因素对增加农田土壤碳汇、实现"双碳"目标具有重要意义.该研究以北京市为研究区,基于2022年采样实测的0～60 cm各层SOCD数据,采用3D概念模型、Mantel test、地理加权回归、地理探测器模型开展SOCD空间变异分析,探究不同因素对SOCD的影响程度及各因素间交互后的作用力.结果表明:1)研究区SOCD在空间上呈自表层向深层逐渐降低的趋势,其中0～15cm 土层的SOCD显著高于30～60 cm(P＜0.05),0～60 cm 土层的有机碳储量约为10.80 Tg.2)土壤含水率、土壤亚类、地形部位分别对0～15、15～60、45～60 cm 土层的SOCD产生了显著影响(P＜0.05);土壤亚类、土壤母质、土壤质地、地形部位与SOCD的空间关联性较强,关联程度自表层向下逐渐增大.3)各重要因子交互后对研究区SOCD的解释能力呈双因子增强或非线性增强的关系,土壤亚类与其他各因子交互后对SOCD的解释能力提升最为突出.今后研究区内开展土壤有机碳空间变异等相关研究时应尽可能综合考虑多因素间的交互作用,其中土壤亚类(土壤类型)可作为重点指标.研究结果可为优化农田资源空间结构,制定农田固碳增汇措施提供科学参考. |
| Abstract_FL | This study aims to explore the spatial variability of soil organic carbon density(SOCD)and influencing factors in the carbon sink of farmland soils.Taking Beijing as the study area,the SOCD data was measured for each layer from 0 to 60 cm sampled in the field from June to October 2022.A conceptual model was established using 3D GMS.Then the SOCD was simulated to determine the spatial variability in three dimensions.According to the dummy variable models,the mantel test,the geographical weighted regression,and the GeoDetector models were used to explore the importance of different factors on the SOCD and the interactive contribution among the factors on both quantitative and spatial scales.The results showed that:1)The SOCD shared a spatial trend of decreasing from the surface to the deeper layers,with the SOCD significantly higher(P＜0.05)in the 0-15 cm soil depth than in the 30-60 cm soil layer.The variability of SOCD was more substantial in the deeper soil layers.The soil organic carbon stock in 0-60 cm was 10.80 Tg.2)The spatial and scale effects were found in the intensity of different factors on the SOCD.The soil subclass,soil parent material,soil texture,soil water content,and topographic site were the significant influencing factors on the variation of SOCD in the study area.Among them,the soil water content,soil subclass,and topographic site were dominated(P＜0.05)SOCD at the soil depths of 0-15,15-60,and 45-60 cm,respectively.Soil subclass,soil parent material,soil texture,and topographic site were spatially strongly associated with the SOCD.The intensity of their association gradually increased from the surface layer to the deeper layer.The disturbance by human activities gradually decreased in the soil below the surface layer.The factors that caused the variation of SOCD were shifted to the natural factors.3)The expression of SOCD showed a two-way or non-linear enhancement after the interaction of the significant factors.The soil subclass showed the most prominent enhancement to explain SOCD after interacting with each other factor.Among them,there was the strongest explanatory power for the SOCD at 0-30 cm soil depth after interaction with soil water content,with 0.724(0-15 cm)and 0.789(15-30 cm),respectively.The explanatory power of SOCD was the strongest at 30-60 cm soil depth after interaction with soil parent material,with 0.649(30-45 cm)and 0.784(45-60 cm),respectively.The interaction of multiple factors should be considered for the spatial variability of soil organic carbon and driving factors.Among them,soil subclasses(soil types)can be incorporated as a priority reference indicator,indicating the differences and the soil-forming parent material,texture configuration,and moisture condition of the environment.The finding can also provide the scientific references to optimize the spatial structure of farmland resources,in order to realize the carbon sequestration and sink enhancement in farmland. |
| Author | 袁胜君 王维瑞 夏沙沙 孔晨晨 张世文 胡睿鑫 |
| AuthorAffiliation | 安徽理工大学地球与环境学院,淮南 232001%北京市密云区土肥工作站,北京 101500%北京市耕地建设保护中心,北京 100020 |
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| Author_FL | HU Ruixin WANG Weirui KONG Chenchen YUAN Shengjun ZHANG Shiwen XIA Shasha |
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| DocumentTitle_FL | Spatial variation and influencing factors of soil organic carbon density in Beijing farmland of China |
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| Keywords | three-dimensional space simulation space-related 土壤有机碳 影响因素 interaction 交互效应 soil organic carbon 三维空间模拟 空间相关 农田 farmland influencing factor |
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| Publisher | 安徽理工大学地球与环境学院,淮南 232001%北京市密云区土肥工作站,北京 101500%北京市耕地建设保护中心,北京 100020 |
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| Title | 北京市农田土壤有机碳密度空间变异及影响因素 |
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