Landslides caused by earthquakes bring about dramatic changes in soil erodibility. In order to understand the change characteristics of soil erodibility during a vegetation restoration period after the 5.12 Wenchuan earthquake, a non-landslide area, landslide area, and transition area in Leigu Town, Beichuan County were selected as research areas. Field soil sampling, geostatistics, and spatial interpolation were used to explore the spatiotemporal changes in soil physicochemical properties and soil erodibility during a natural restoration in 2013 (5 years after the earthquake) and in 2022 (14 years after the earthquake). The results showed that the comprehensive soil erodibility index (CSEI) was mainly composed of five soil factors, which were soil pH, soil total nitrogen (TN), mean weight diameter of soil aggregates (MWD), fractal dimension of soil water stable aggregates (D), and soil erodibility (K_epic). The CSEI of the landslide area was slightly lower than that of the non-landslide area. The CSEI was gradually increasing during the process of natural restoration after earthquake. From 2013 to 2022, the increase rates of the CSEI were 6.9%, 10.0%, and 41.5% for the landslide area, non-landslide area, and transition area, respectively. Along attitude segments, the spatial distribution of soil erodibility in 2022 is more uniform than that in 2013. The higher value of CSEI was located in the upper part of research areas. The spatial distribution of the CSEI in 2013 and 2022 appeared as a moderate autocorrelation. The variable ranges of CSEI in 2013 and 2022 were about 20 m. In the early stage of vegetation restoration, soil and water conservation engineering was recommended in the landslide area.

Plantago asiatica L. is an important medicinal and edible plant in China, whose wild resources have declined sharply due to overharvesting. Accurately assessing its potential suitable habitats and identifying the dominant environmental factors are of great scientific significance for germplasm conservation. In this study, we focused on Jiangxi Province and, based on 79 field occurrence records and 29 environmental variables, employed a MaxEnt model optimized using the kuenm package (version 1.1.9) (AUC = 0.806) to simulate the potential distribution of this species under current and three future Shared Socioeconomic Pathway (SSP) scenarios (SSP126, SSP370, and SSP585). The results indicated that static non-climatic factors at the regional scale—specifically, soil clay content (contribution rate: 56.7%)—were the dominant force determining the distribution of Plantago asiatica, with an influence far exceeding that of climatic and topographic factors. Under all future SSP scenarios, its distribution range exhibited notable spatiotemporal conservatism, and the centroid showed no long-distance migration. This study provides a scientific reference for optimizing the conservation framework of Plantago asiatica germplasm resources, identifying priority cultivation areas, and formulating regional adaptive management strategies.

Soil erosion in the purple soil region presents severe challenges with complex driving mechanisms. At the same time, evaluation and prediction of runoff and sediment dynamics are lacking for natural vegetation restoration in bare areas. The Mann–Kendall and Pettitt tests were employed to identify abrupt shift points in runoff and sediment dynamics, utilizing monitoring data from the Suining Soil and Water Conservation Experimental Station over the period from 1984 to 2018. Therefore, the research periods were divided into a baseline period (1984–1992) and an evaluation period (1993–2018). Subsequently, encompassing rainfall, runoff, sediment, topography, soil properties, and vegetation parameters, a Water Erosion Prediction Project (WEPP) model was established to quantify the reduction benefits of runoff and sediment during the period of forest restoration. We found that the calibrated WEPP model demonstrated satisfactory performance based on Nash–Sutcliffe efficiency coefficients (NSE > 0.5) and determination coefficients (R² > 0.5) for runoff and sediment simulations. The WEPP model and double-mass curve analysis method revealed that forest restoration reduced runoff and sediment by more than 80%. It is recommended to implement artificial vegetation restoration before reaching the threshold for natural vegetation restoration to achieve soil and water conservation goals.

Scientifically assessing the spatiotemporal evolution of regional carbon storage is of great significance for achieving the “dual carbon” goals and optimizing territorial spatial patterns. This study integrated the PLUS and InVEST models to systematically reconstruct the spatiotemporal pattern of carbon storage in Hebei Province from 2000 to 2020, simulate its evolution trajectory under different scenarios in 2030, and identify its driving mechanisms using the GeoDetector model. The main findings are as follows: (1) From 2000 to 2020, cropland was the dominant land use type in Hebei Province, and carbon storage exhibited a spatial pattern of “high in the northwest, low in the southeast.” Carbon storage increased from 16.23 × 10⁸ t to 16.31 × 10⁸ t, with a significantly slowed growth rate after 2010. (2) Multi-scenario simulations for 2030 indicate that under the natural development and economic priority scenarios, construction land expands significantly while cropland and grassland continue to decrease. In contrast, carbon storage shows an increasing trend under the ecological protection and cropland protection scenarios. (3) Driving factor analysis reveals that the spatial differentiation of carbon storage is primarily controlled by natural factors such as slope, elevation, and NDVI, while the explanatory power of anthropogenic factors, particularly population density, has significantly increased. The interaction between NDVI and slope exhibits a synergistic enhancement effect. This study elucidates the coupling mechanisms between land use change and carbon storage under different policy orientations, providing a scientific basis for territorial spatial optimization and the formulation of differentiated carbon neutrality pathways in Hebei Province.