As an important part of farmland, the slope farmland is widely distributed in the central and western plateau mountain region in China. It is necessary to scientifically evaluate the slope farmland quality (SFQ) and analyze the spatial structure characteristics of SFQ to ensure reasonable utilization and partition protection of slope farmland resources. This paper takes the typical plateau mountain region—Yunnan Province in China—as an example and systematically identifies the leading factors of SFQ. The sloping integrated fertility index (SIFI) is adopted to reflect the SFQ. The evaluation system is built to quantitatively evaluate the SFQ and the spatial structure characteristics of SFQ were analyzed by a geostatistical model, autocorrelation analysis and spatial cold–hot spot analysis. The results show that the SFQ indexes in Yunnan Province are between 0.36 and 0.81, with a mean of 0.59. The SFQ grade is based on sixth-class, fifth-class, seventh-class and fourth-class land. The SFQ indexes present a normal spatial distribution, and the Gaussian model fits well with the semi-variance function of the spatial distribution of SFQ indexes. Furthermore, the spatial distribution of SFQ indexes is moderately autocorrelated. The structural factors play a major role in the spatial heterogeneity of SFQ indexes, but the influence of random factors should not be ignored. The spatial distribution of SFQ grades has a significant spatial aggregation characteristic, and the types of local indicators of spatial association (LISA) are based on high–high (HH) aggregation and low–low (LL) aggregation. The cold spot and hot spot distributions of SFQ grades display the significant spatial difference. The hot spot area is mainly distributed in Central Yunnan and the Southern Fringe, while the cold spot area mainly distributes in the Northeastern Yunnan, Northwestern Yunnan and Southwestern Yunnan. This study could provide a scientific basis for SFQ management and ecological environment protection in the plateau mountain region.

Tillage practices significantly influence soil nutrient retention, soil structure, and stability. However, the impact of tillage practices on soil stability and erosion resistance through the perturbation approach of soil structure remains unclear. This study aimed to establish universal principles across slope surface and soil profile scales. We evaluated the effects of various tillage practices, including conventional tillage (CT), soil compaction (CM), subsoil tillage (ST), no tillage (NT), and subsoil tillage and soil compaction (SCM) on soil stability and erosion resistance in China’s red soil hilly region. Soil stability, erosion resistance, and other soil properties were quantified using field surveys and laboratory experiments. We discovered significant variations in soil aggregate stability (SAS), wet aggregate stability (WAS), soil mechanical stability (SMS), and soil erodibility (SE) among the five tillage methods. The K factor’s average value indicated that the 0–40 cm soil layer was more erodible for CT (0.472) than for other methods, with NT (0.26) being the least erodible. NT (0.43) was the most effective treatment for reducing SE, while SCM (0.41) enhanced soil fertility, controlled SE, and mitigated machinery-induced soil compaction risks. CM (0.38) maintained soil stability without improving the soil nutrient storage, while ST (0.33) improved the soil stability such as alleviating the soil hardening caused by CM. The results provide reference parameter values for selecting appropriate tillage methods to decrease soil degradation and erosion while enhancing the soil productivity in a red soil hilly region.

Soil erosion is the key factor leading to the degradation of tillage-layer quality, which directly threatens regional food and ecological security. To study the characteristics of soil structure, water retention capacity, and nutrient changes in the tillage layer of purple soil sloping farmland under different erosion conditions, a shovel soil erosion test was performed to distinguish the factors that hinder the tillage-layer quality of sloping farmland under different erosion degrees. The degradation of soil structure showed that with the intensification of erosion, soil bulk density, soil capillary porosity, and sand content displayed an overall increasing trend; the soil water retention degradation was expressed by the average increase in the soil water holding capacity and the average decrease in the infiltration rate; soil nutrient degradation was derived from the average decrease in soil nutrient content. At the initial stage of erosion, the soil nutrient degradation was extremely sensitive to soil erosion, which was the limiting factor of the tillage layer; when the erosion reached stage E-15 (erosion 15 cm), the soil nutrients, soil permeability, and soil capillary porosity became the limiting factors; for E-20 (erosion 20 cm), the limiting factors added an index on the basis of stage E-15, namely, soil total porosity. When soil erosion continued for 53 years, the tillage-layer quality index was lower than the threshold value (0.46). Reconstructing soil profile of the tillage layer is an effective way to break the limitations of the barrier factors and improve the tillage-layer quality.

Quantitative evaluations of the cultivated-layer quality (CLQ)of sloping farmland are important for the effectively improving and rationally utilizing of the cultivated layers. Using a red soil watershed as the research object, we quantitatively analysed the relationship among factors influencing the CLQ using structural equation modeling based on the DPSIR framework (A framework for describing the interactions between society and environment developed by the European Environmental Agency) to describe the CLQ evolution process. We identified the key indicators of the driving factors (D) during cultivated-layer degradation and critical environmental pressure (P) to construct a reasonable cultivatedlayer (RCL) by principal component analysis (PCA). We defined the main CLQ diagnostic indicator set to assess the CLQ by factor analysis and analysed the reasonable measures to improve the CLQ. The results show quantified direct or reverse effects among D, P, state performance (S), problem impacts (I) and response strategy (R). The contribution rates of D and P were affected by the comprehensive effects of natural and human factors or human factors along. The CLQ diagnostic indicator set included 7 soil indicators and sub-soiling is the main adjusted measure for cultivated-layer recovery. These results could provide important technological paths for objectively understanding the causes drivers of the degradation and improving the CLQ for red soil sloping farmland.