Soil organic carbon(SOC)is the most important indicators of soil quality and health.Identifying the spatial distribution of SOC and its influencing factors in cropland is crucial to understand the terrestrial carbon c...Soil organic carbon(SOC)is the most important indicators of soil quality and health.Identifying the spatial distribution of SOC and its influencing factors in cropland is crucial to understand the terrestrial carbon cycle and optimize agronomic management.Yunnan Province,characterized by mountainous topography and varied elevation,is one of the highest SOC regions in China.Yet its SOC stock of cropland and influencing factors has not been fully studied due to the lack of adequate soil investigation.In this study,the digital mapping of SOC at 1 km resolution and the estimation of total SOC stock in cropland of Yunnan Province was undertaken using 8637 topsoil(0-20 cm)samples and a series of spatial data through Random Forest(RF)model.It was showed that across the cropland of Yunnan Province,the mean SOC density and total stock were 4.84 kg m^(-2) and 337.5 Mt,respectively.The spatial distribution indicated that relatively high SOC density regions resided in the northwest and northeast parts of Yunnan Province.Elevation(19.5%),temperature(17.3%),rainfall(14.5%),and Topographic wetness index(9.9%)were the most important factors which controlled spatial variability of SOC density.Agronomic practices(e.g.,crop straw treatments,fertilizer management)should be optimized for the sustainable development of crop production with high SOC sequestration capacity in Yunnan Province.展开更多
文摘为了能够快速准确地掌握整个昆明地区土壤水解性氮含量的情况,收集963个不同类型的土壤样品,采用竞争自适应重加权采样(Competitive adaptive reweighted sampling,CARS)变量选择方法筛选波长变量,并建立水解性氮的偏最小二乘法(Partial least squares,PLS)分析模型。结果表明,采用CARS方法优选波长变量后,模型参数有所改善,交互验证标准偏差(Root mean square error of cross validation,RMSECV)由31.63降至25.55,交互验证相关系数(Correlation coefficientof cross validation,Rcv)由0.78提升至0.84,且模型外部验证结果与内部交叉验证结果基本一致。研究结果表明近红外光谱技术结合CARS分法,在大量代表性样品建模下,能够有效建立昆明地区不同土壤类型的水解性氮含量的近红外数学模型,方法可推广应用于土壤其他组分的近红外检测,具有重要的指导意义。
基金funded by the Science and Technology Projects of Yunnan Province,China(2017YN06 and 2018BB019)the Key Research&Development project of Yunnan Province(2018530000241017)the National Natural Science Foundation of China(31671642)。
文摘Soil organic carbon(SOC)is the most important indicators of soil quality and health.Identifying the spatial distribution of SOC and its influencing factors in cropland is crucial to understand the terrestrial carbon cycle and optimize agronomic management.Yunnan Province,characterized by mountainous topography and varied elevation,is one of the highest SOC regions in China.Yet its SOC stock of cropland and influencing factors has not been fully studied due to the lack of adequate soil investigation.In this study,the digital mapping of SOC at 1 km resolution and the estimation of total SOC stock in cropland of Yunnan Province was undertaken using 8637 topsoil(0-20 cm)samples and a series of spatial data through Random Forest(RF)model.It was showed that across the cropland of Yunnan Province,the mean SOC density and total stock were 4.84 kg m^(-2) and 337.5 Mt,respectively.The spatial distribution indicated that relatively high SOC density regions resided in the northwest and northeast parts of Yunnan Province.Elevation(19.5%),temperature(17.3%),rainfall(14.5%),and Topographic wetness index(9.9%)were the most important factors which controlled spatial variability of SOC density.Agronomic practices(e.g.,crop straw treatments,fertilizer management)should be optimized for the sustainable development of crop production with high SOC sequestration capacity in Yunnan Province.
