Soil total phosphorus plays an important role in soil fertility, plant growth, and bioge-ochemical cycles. This study aims to determine the spatial distribution characteristics of soil total phosphorus and identify its main influencing factors in the study area, thereby providing a basis for the scientific management of soil total phosphorus. Here, we conducted a comprehensive analysis by combining classical statistical analysis, ge-ostatistics methods, Pearson correlation analysis, one-way analysis of variance (ANOVA), and structural equation modeling (SEM) to explore the spatial distribution patterns of soil total phosphorus and its influencing factors. The results showed that soil total phosphorus in the study area ranged from 161.00 to 991.00 mg/kg, with an average of 495.71 mg/kg. Spatially, soil total phosphorus exhibited a patchy distribu-tion pattern, with high values primarily concentrated in cultivated areas along rivers and low values mainly located in forested areas in the southeastern and central re-gions. Additionally, the nugget effect of soil total phosphorus was 71.5%, indicating a moderate level of spatial variability. The Pearson correlation analysis revealed that soil total phosphorus content was significantly correlated with multiple factors, including land use types, soil parent material, distance from settlements, slope, and soil pH. Based on these findings, we employed ANOVA to analyze the impacts of various fac-tors. The results indicated that soil total phosphorus content showed significant differences under the influence of different factors. Subsequently, we further explored in depth the action paths through which these factors affect soil total phosphorus us-ing SEM. The SEM results showed that the absolute values of the total effects of the influencing factors on soil total phosphorus, ranked from highest to lowest, were as follows: land use types (0.499) > soil parent material (0.240) > distance from settle-ments (0.178) > slope (0.161) > elevation (0.127) > soil pH (0.114) > normalized differ-ence vegetation index (0.103). These findings provide a scientific foundation for the effective management of soil total phosphorus in similar study areas.

Cropland abandonment is a critical challenge for food security and the sustainable use of land resources, especially in the hilly and mountainous regions of southern China. To characterize the spatiotemporal evolution and associated-factor patterns of cropland abandonment in these regions, this study uses Ji’an City, Jiangxi Province, as a case study and develops an integrated framework for abandonment identification and monitoring, predictive-association analysis, relative risk assessment, and zoning management. Using Landsat remote sensing imagery from 1990 to 2024, crop phenological features, and multisource topographic, soil, climatic, ecological, and socioeconomic data, we identified and evaluated long-term cropland abandonment. The results show that, after incorporating phenological features and temporal filtering, annual land-use classification evaluated with spatially separated testing samples achieved a mean overall accuracy of 95.27% and a mean Kappa coefficient of 0.931, and the overall accuracy of cropland abandonment identification reached 91.58%, with a Kappa coefficient of 0.83. Cropland abandonment in Ji’an City showed an overall accelerating trend, with the abandonment rate exceeding 15% during 2020–2021. Spatially, abandonment was more intensive in the west than in the east and more severe in mountainous areas than in plains. Paddy field abandonment was the dominant form of cropland abandonment across the city, whereas dryland abandonment was more limited in extent but showed stronger interannual fluctuations. The predictive-association analysis indicated that tree cover consistently showed high predictive importance for both paddy fields and drylands. Paddy field predictions were more strongly associated with topographic position, surface roughness, and soil conservation, whereas dryland predictions showed stronger associations with aridity and population density. From 1993 to 2023, the model-estimated relative abandonment risk increased, and high-risk areas expanded from deep mountainous regions to low-hill areas. By coupling relative risk levels with associated-factor patterns, we divided paddy fields and drylands into four management zones: core protection zones, dynamic warning zones, integrated improvement zones, and ecological fallow zones. Differentiated management strategies were then proposed for each zone. This study provides methodological support and decision-making evidence for cropland abandonment monitoring, cropland protection, and differentiated land management in the hilly and mountainous regions of southern China.