Soil magnetic susceptibility (MS) is a basic soil physical property that is influenced by environmental factors and processes. Mapping MS is fundamental to exploring its spatial pattern, influencing factors and practical applications. However, the traditional spatial interpolation method is difficult to implement in detailed large-scale mapping. Digital soil mapping (DSM) based on environmental factors provides a more effective method. It has been widely adopted in the prediction of soil physiochemical characteristics, but not yet in MS mapping. This study aimed to explore the spatial pattern of soil MS in an agro-pastoral transitional zone (APTZ) of north China, reveal influencing factors of MS, and extract the significance of DSM of MS and its possible applications. Soil samples were collected from two layers (0–5 and 35–40 cm) in an APTZ. For each sample, χ_lf and χ_fd were measured. The quantile regression forest (QRF) model was used to predict MS and assess uncertainties. The results indicated substantial spatial variation of MS in APTZ. QRF predicted MS with satisfying accuracy (adjusted R² = 0.37–0.64). Influencing factors of MS included parent material, topography, and vegetation. The predominant factors varied with MS attributes, depth, and environment. Soil redistribution further complicated the MS spatial pattern. Water erosion resulted in declining topsoil χ_fd at steep slopes. Topsoil χ_fd of grassland transect showed higher covariate of variation (8.23%) compared with forest (4.83%). Wind brought exogenous particles with low MS and led to a weaker correlation between topsoil χ_lf and χ_fd (p > 0.1) compared with subsoil (p < 0.05). DSM of MS based on environmental factors reveals the undetected influencing factors at a small scale and helps to identify dominant factors in different environments, which provides the possibility of adopting MS in practical works at a large scale.

土壤磁化率（MS）是一种受环境因素和过程影响的基本土壤物理性质。映射 MS 是探索其空间格局、影响因素和实际应用的基础。然而，传统的空间插值方法难以在详细的大尺度映射中实现。基于环境因素的数字土壤测绘（DSM）提供了一种更有效的方法。它已被广泛应用于土壤理化特性的预测，但尚未用于 MS 制图。本研究旨在探索华北农牧交错带（APTZ）土壤MS的空间格局，揭示MS的影响因素，提取MS的DSM意义及其可能的应用。从 APTZ 中的两层（0-5 和 35-40 厘米）收集土壤样品。_测量了lf和 χ _fd。分位数回归森林 (QRF) 模型用于预测 MS 和评估不确定性。结果表明 APTZ 中 MS 的空间变化很大。QRF 以令人满意的准确度预测 MS（调整后的 R ² = 0.37–0.64）。MS的影响因素包括母质、地形和植被。主要因素随 MS 属性、深度和环境而变化。土壤再分布进一步复杂化了 MS 空间格局。水蚀导致陡坡表土 χ _fd下降。表土 χ _fd与森林（4.83%）相比，草地样带的变异协变量（8.23%）更高。风带来了低 MS 的外源颗粒，与底土 (p < 0.05) 相比，导致表层土 χ _lf和 χ _{fd (p > 0.1) 之间的相关性较弱。}基于环境因素的MS DSM在小范围内揭示了未被发现的影响因素，有助于识别不同环境中的主导因素，这为MS在实际工作中大规模采用提供了可能。