Spatiotemporal Distribution and Uncertainty of Soil C:N Ratios in Global 0-30cm and 30-100cm Soil Layers

We collected 36997 soil C:N data points for the 0-30 cm layer and 31691 data points for the 30-100 cm layer, integrating a total of 24 environmental covariates from five categories closely related to soil C:N, including climate, vegetation, topography, soil properties, and human activities. A zonal direct modeling strategy was employed in conjunction with quantile random forest to develop the predictive models. The 10-fold cross-validation results demonstrated that the model achieved an R² of 0.77 for C:N030 and 0.71 for C:N30100. Based on this model, the spatial distribution and uncertainty of global soil C:N for the 0-30 cm and 30-100 cm layers were mapped at a 1 km resolution. Comparative analysis indicates that the 1 km global soil C:N dataset produced in this study exhibits higher accuracy than existing products.本研究共收集得到0-30厘米土层的土壤碳氮比（soil C:N）数据点36997个，30-100厘米土层数据点31691个，并整合了与土壤碳氮比密切相关的五大类共计24项环境协变量，涵盖气候、植被、地形、土壤属性及人类活动。研究采用分区直接建模策略结合分位数随机森林构建预测模型。10折交叉验证结果显示，模型针对0-30厘米土层土壤碳氮比的决定系数（R²）达0.77，针对30-100厘米土层的决定系数达0.71。基于该模型，本研究以1千米分辨率绘制了全球0-30厘米与30-100厘米土层土壤碳氮比的空间分布及其不确定性图谱。对比分析表明，本研究生成的1千米分辨率全球土壤碳氮比数据集，其精度优于现有同类数据集。