Studying the spatial variation patterns and influencing factors of soil organic matter (SOM) in hilly and basin areas is of great significance for guiding agricultural production practices. This study takes Lanxi City as an example and comprehensively considers soil formation factors such as climate, vegetation, and terrain. Based on the genetic algorithm, 47 environmental variables are combined and optimized to construct a random forest (RF) model and an improved version—a random forest model based on genetic algorithm variable combination optimization (RF-GA). At the same time, the SHAP interpretation method is used to quantitatively analyze the spatial distribution characteristics of the SOM content and further identify the main driving factors. Compared with the ordinary Kriging (OK) and random forest (RF) methods, the random forest model based on genetic algorithm variable combination optimization (RF-GA) demonstrates a significantly improved prediction accuracy (R² = 0.49; RMSE = 3.49 g·kg⁻¹), with an MAE = 3.019 and LCCC = 0.67. Among the three models, the R² of the RF-GA model increases by 87.84% and 56.29%. The model prediction results indicate that the SOM content in the study area ranges from 12.11 to 31.38 g·kg⁻¹, showing spatial distribution characteristics of a higher content in mountainous areas and a lower content in plains. A further SHAP analysis shows that terrain, climate, and biological factors are key environmental factors affecting the spatial differentiation of the SOM, with the channel network base level (CNBL), which contributes 20.68% to the model, and DEM, which has a contribution rate of 5.57%, playing particularly significant roles. By regulating moisture, erosion deposition, vegetation distribution, and microclimate conditions, they significantly affect the spatial distribution of the SOM. In summary, the RF-GA and its interpretable prediction model constructed in this study not only effectively reveal the spatial and driving mechanisms of SOM in hilly and basin areas but also provide a solid theoretical basis and practical guidance for accurate mapping, the formulation of sustainable utilization strategies for soil resources, and ensuring national food security.

Cropland dynamics in ecologically fragile regions are central to balancing food security and ecological integrity in the Yellow River Basin. Ningxia Hui Autonomous Region is used as a case study. An integrated simulation framework is developed by coupling an improved grey prediction model (Improved GM(1,1)) with the CLUMondo spatial model. The analysis addresses four questions: how cropland changed during 2009–2024, which drivers explain cropland suitability and transitions, what spatial resolution is appropriate for implementation, and how cropland patterns differ under alternative development pathways for 2025–2040. Historical cropland change in Ningxia during 2009–2024 is quantified, and spatial patterns for 2025–2040 are projected under three scenarios: business-as-usual (BAU), ecological protection (EP), and rapid urbanization (URE). Cropland change during 2009–2024 shows pronounced phased fluctuations and a stable redistribution pattern described as “southern reduction and northern replenishment, urban decrease and rural increase”. Population growth, economic expansion, and policy regulation jointly drive this spatiotemporal reconfiguration. Land demand forecasting is improved by introducing a metabolism mechanism and residual correction into the grey model, which reduces mid- to long-term divergence. Multi-scale logistic regression tests show the highest AUC at 50 m, with AUC values exceeding 0.8 across land categories, and this resolution is used for model implementation. Model performance is evaluated using AUC, Kappa, and overall accuracy, supporting the applicability of the framework in arid, ecologically fragile regions. Scenario simulations reveal clear divergence in future spatial outcomes. BAU maintains sustained pressure on cropland protection and ecological security. URE increases the risk of encroachment on high-quality cropland in the central–northern irrigated areas due to urban expansion. EP constrains construction land growth and secures strategic ecological spaces, thereby slowing the loss of high-quality cropland while maintaining development capacity. These results provide a transparent basis for scenario-based territorial spatial planning in Ningxia and offer transferable evidence for managing cropland–ecology tradeoffs in arid and semi-arid regions.

With the rapid development of high-speed railway (HSR), many scholars have studied the competition between HSR and aviation or inter-city coach, but few studies have discussed the supply-service relationship within the railway system. This paper explores the competition and cooperation between HSR and conventional railway (CR) at the city-pair level of 39 core cities in China from the temporal perspective. Comprehensive considering the departure time and arrival time between city pairs as the representation of train service quality, we find that the proportion of superior quality service of high-speed train (HST) is far higher than that of conventional train (CT). However, the time slots representing the competition degree show that CR with fewer superior quality trains is easier to be replaced than HSR. The supply-service relationships of the railway system indicate that HSR has become the main transportation mode between core cities, and the CR, as an auxiliary transportation, shows a certain complementary effect in the temporal perspective. Spatially, HSR and CR services are more likely to generate temporal competition on the mainline, but temporal complementarity between city pairs on non-arterial lines. This study can provide inspiration for regional spatial planning by better understanding the operation strategy of railway passenger transport system.