Improvements in vegetation coverage are driven by both resource endowment conditions and policy behaviors. To accurately reflect the vegetation restoration effect after ecological policies, this study used the potential realization model to calculate the potential realization degree of vegetation restoration on the Loess Plateau and to assess the vegetation restoration effect after the Grain for Green Program from 2000 to 2020. Then, the influencing factors were explored using the spatial Dubin model. The results reveal that (1) the EVI value of the Loess Plateau in northern Shaanxi increased from below 0.25 at the beginning of the study to approximately 0.35 by the end, indicating that the green territory of the Loess Plateau gradually expanded to the northwest over the study period, and that the east and west of the Loess Plateau are key areas of vegetation cover for further improvement; (2) compared to the traditional EVI indicator, the potential realization degree can more accurately evaluate the vegetation restoration effect driven by ecological policies; (3) policy intensity is positively correlated with the growth rate of the vegetation restoration potential realization degree by 0.183 and significant at 1% level, making it the primary factor influencing the effect of vegetation restoration. Additionally, annual average precipitation and annual sunshine percentage have significant spatial positive contributions to the improvement of vegetation restoration on the Loess Plateau. The study’s findings are expected to contribute to the development of a scientific basis for adjusting the vegetation restoration policy on the Loess Plateau and enhancing ecological restoration efforts.

Quantification of soil water-physical properties and their spatial variation is important to better predict soil structure and functioning, as well as associated spatial patterns in the vegetation. The provision of site-specific soil data further facilitates the implementation of enhanced land use and management practices. Using geostatistical methods, this study quantified the spatial distribution of soil bulk density (SBD), soil moisture (SM), capillary water-holding capacity (CWHC), capillary porosity (CP), non-capillary porosity (NCP), and total porosity (TP) in southern subtropical forests located at the Tropical Forest Research Center in Pingxiang City, China. A topographic map (scale = 1:10,000) was used to create a grid of l km squares across the study area. At the intersections of the grid squares, the described soil water-physical properties were measured. By calculating the coefficient of variation for each soil water-physical property, all measured soil water-physical properties were found to show moderate spatial heterogeneity. Exponential, gaussian, spherical, and linear models were used to fit the semivariograms of the measured soil water-physical properties. Across all soil water-physical properties, the range A₀ variable (i.e., the separation distance between the semivariance and the sill value) measured between 3419 m and 14,156 m. The nugget-to-sill ratio ranged from 9 to 41%, indicating variations in the level of spatial autocorrelation among the soil water-physical properties. Many of the soil water-physical properties were strongly correlated (as assessed using Pearson correlation coefficients). Spatial distribution maps of the soil water-physical properties created via ordinary kriging (OK) showed that most water-physical properties had clumped (aggregated) distributions. SBD showed the opposite spatial pattern to SM and CWHC. Meanwhile, CP and TP showed similar distributions.

Understanding the effects of landscape greening pest control modes (LGPCMs) on carbon storage and soil physicochemical properties is crucial for promoting the sustainable development of urban landscape greening. Climate change and green development have led to increased landscape pest occurrences. However, the impacts of different LGPCMs on carbon storage and soil properties remain unclear. We examined six typical LGPCMs employed in Beijing, China: chemical control (HXFZ), enclosure (WH), light trapping (DGYS), biological agent application (SWYJ), natural enemy release (SFTD), and trap hanging (XGYBQ). Field surveys and laboratory experiments were conducted to analyze their effects on carbon storage and soil physicochemical properties, and their interrelationships. The main results were as follows: (1) Different LGPCMs significantly affected carbon storage in the tree and soil layers (p < 0.05), but not in the shrub and herb layers (p > 0.05). Carbon storage composition across all modes followed the following order: tree layer (64.19%–93.52%) > soil layer > shrub layer > herb layer. HXFZ exhibited the highest tree layer carbon storage (95.82 t/hm²) but the lowest soil layer carbon storage (6.48 t/hm²), while DGYS performed best in the soil, herb, and shrub layers. (2) LGPCMs significantly influenced soil bulk density (SBD), clay (SC), silt particle (SSP), sand (SS), pH, organic carbon (OC), total nitrogen (TN), and heavy metal content (lead (Pb), cadmium (Cd), mercury (Hg)). WH had the highest TN (1.37 g/kg), TP (0.84 g/kg), SC (10.71%) and SSP (42.14%); HXFZ had the highest Cd (8.98 mg/kg), but lowest OC and Pb. DGYS had the highest OC and Hg, and the lowest Cd, SC, and TP. Under different LGPCMs, the heavy metal content in soil ranked as follows: Pb > Cd > Hg. (3) There were significant differences in the relationship between carbon storage and soil physicochemical properties under different LGPCMs. A significant positive correlation was observed between the soil layer carbon storage, TN, and OC, while significant negative correlations were noted between SS and SC as well as SSP. Under SFTD, the tree layer carbon storage showed a negative correlation with Cd, while under DGYS, it correlated negatively with pH and Hg. In summary, While HXFZ increased the short-term tree layer carbon storage, it reduced carbon storage in the other layers and damaged soil structure. Conversely, WH and DGYS better supported carbon sequestration and soil protection, offering more sustainable control strategies. We recommend developing integrated pest management focusing on green control methods, optimizing tree species selection, and enhancing plant and soil conservation management. These research results can provide scientific guidance for collaborative implementation of pest control and carbon sequestration in sustainable landscaping.