Covariates Description.

The calcium accumulation problem (CAP) in cinnamon soil regions of northern China significantly impacts crop yields. Identifying and mitigating CAP is crucial for improving soil quality and agricultural productivity. This study, based on field research in Aohan Banner, Chifeng City, utilizes legacy soil maps to construct a CAP dataset and evaluates the predictive performance of several machine learning models. The influence of topography on CAP is also analyzed. Key findings include: (1) In the study area, CAP predominantly manifests as block formations in dry land. Of the surveyed farmers, 58% report CAP in their cropland, with 84% noting reduced yields, though 76% have not implemented any specific mitigation measures. (2) Evaluation of machine learning models shows that tree-based models (BRT and XGBoost) outperform others in predicting CAP, with BRT demonstrating superior mapping capabilities. (3) Spatial analysis reveals that CAP is more common in the eastern and central regions of Aohan Banner, particularly in terrains such as slopes, ridges, and peaks. Additionally, the cold-to-hot zone ratio increases significantly as terrain transitions from dry to humid. (4) Regression analysis shows a strong negative correlation between terrain variables (e.g., MRVBF and GEO) and the likelihood of CAP. A further analysis indicates that CAP is more likely to occur in areas with higher soil erosion risk. These findings provide valuable insights for identifying CAP in regional soil mapping and for guiding future research in this area.中国北方褐土区域的钙积问题（Calcium Accumulation Problem, CAP）会对作物产量造成显著影响。识别并缓解钙积问题，对于提升土壤质量与农业生产力至关重要。本研究以赤峰市敖汉旗为野外调研区域，依托历史土壤图构建钙积问题数据集，对多种机器学习模型的预测性能开展评估，并分析了地形对钙积问题的影响。主要研究结果如下： (1) 研究区域内，旱地中的钙积问题主要以块状形态分布。受访农户中，58%的农户在其耕地上发现了钙积问题，其中84%的农户反映作物产量下降，但仍有76%的农户未采取任何针对性缓解措施。 (2) 机器学习模型评估结果显示，基于树的模型（BRT与XGBoost）在钙积问题预测任务中的表现优于其他模型，其中BRT的制图能力更为出色。 (3) 空间分析结果表明，敖汉旗东部与中部区域的钙积问题更为频发，尤其是在坡地、脊线与峰地等地形中。此外，随着地形从干旱向湿润过渡，冷热点区域比值显著升高。 (4) 回归分析结果显示，地形变量（如MRVBF与GEO）与钙积问题发生概率之间存在显著负相关关系。进一步分析表明，土壤侵蚀风险更高的区域更易发生钙积问题。 上述研究结果可为区域土壤制图中的钙积问题识别工作提供重要参考，同时可为该领域的后续研究提供指导。