Zhejiang Province, as a key ecological region in southeastern China, plays a vital role in ensuring regional ecological security and sustainable development through its soil conservation services (SCS). Based on remote sensing data, this study employed the InVEST model to evaluate the characteristics of SCS in Zhejiang from 2001 to 2020. Long-term trends were identified using Sen’s Slope and the Mann–Kendall test, spatial autocorrelation was assessed through Moran’s I, the contributions of driving factors were quantified using XGBoost combined with SHAP, and spatial heterogeneity was further explored using Geographically Weighted Regression (GWR). The results indicate that: (1) from 2001 to 2020, SCS exhibited a fluctuating trend of “decline followed by recovery,” with significantly higher values in the western mountainous areas than in the eastern coastal and plain regions; approximately 58% of the area remained stable, while 40% experienced degradation; (2) Spatial autocorrelation analysis showed that areas with strong SCS were concentrated in the western mountains, while low-value areas were mainly distributed in the eastern coastal and urban regions; (3) natural factors contributed the most, followed by climatic and human activity factors; and (4) the GWR model outperformed the OLS model in revealing the spatial variation in the effects of natural and anthropogenic drivers. These findings provide valuable scientific references and decision-making support for ecological conservation, watershed management, and sustainable land use in Zhejiang Province.

A series of Ag-loaded and oxygen vacancy (OV)-containing BiOBr_(OV)/BiOI_0.08 (Ag/BiOBr_(OV)/BiOI_0.08) photocatalysts with varying Ag loading levels were synthesized via the solvothermal–photocatalytic reduction method. As confirmed via optical, photoelectrochemical, and 4-chlorophenol photodegradation experiments, a low Ag loading level significantly enhanced the photogenerated charge carrier (PCC) transfer on the BiOBr_(OV)/BiOI_0.08 semiconductor surface and the performance of Ag/BiOBr_(OV)/BiOI_0.08 photocatalysts, which was attributable to the synergism between the effect of OVs and the localized surface plasmon resonance (LSPR) of Ag nanoparticles. Additionally, BiOBr_(OV)/BiOI heterojunctions facilitated efficient visible-light harvesting and PCC separation. As indicated by finite-difference time-domain (FDTD) simulations and density functional theory (DFT) calculations, the electric field intensity in the “hot spots” generated at the interface between the BiOBr_(OV)/BiOI_0.08 semiconductor and Ag nanoparticles increased by more than eight times, and the presence of OVs and Ag atomic clusters introduced impurity energy levels in the semiconductor bandgap, improving PCC separation and Ag/BiOBr_(OV)/BiOI_0.08 photocatalytic efficiency. However, an increase in silver loading renders the composite metallic, suggesting a reduction in its photocatalytic performance. This work provides new insights for designing highly active visible light catalysts and contributes to the development of more efficient plasmonic catalysts.

In the present paper, a series of Ag/BiOBr_0.85I_0.15 composite nanoparticles with different silver loading were prepared by a combined solvothermal and photocatalytic reduction method. The composite samples have been characterized by XRD, XPS, SEM, EDX, TEM, UV-Vis, and N₂ adsorption/desorption techniques. The characterization results showed that BiOBr_0.85I_0.15 composite nanoparticles have a tetragonal phase structure. Silver nanoparticles are uniformly distributed on the BiOBr_0.85I_0.15, which results in surface plasmon resonance absorption, effectively increasing the visible light absorption ability of BiOBr_0.85I_0.15. The photocatalytic activity of the samples was evaluated by photocatalytic degradation of ammonia nitrogen in circulating aquaculture water under simulated sunlight irradiation. The effect of the Ag loading amount on the photocatalytic degradation of ammonia nitrogen was investigated. Silver loading of 1% (molar ratio) can effectively improve the degradation capacity of the catalyst for ammonia nitrogen in water. The recycling experiments show that 1%Ag/BiOBr_0.85I_0.15 has good photocatalytic stability. ESR characterization and oxidation species scavenging experimental results suggest that h⁺, ¹O₂, and ·O_2⁻ are the main oxidizing species in the photocatalytic system.

To achieve a rapid and accurate estimation of the soil organic matter (SOM) content in wetland soil, we focused on surface soil samples from the Xianshan Lake wetland area in Zhejiang Province and proposed a novel method called Marine-Predators-Algorithm-Based Random Forest (MPARF) to establish a fast detection model for the SOM content. This study analyzed 85 soil samples from the study area with the aim of assessing the performance of various combinations of ten differential transformation methods and five regression algorithms in predicting the SOM content. Our research findings demonstrate that the combination of second-order differentiation (SD) and MPARF yields the best results, with the highest R² value (0.92) and the lowest RMSE (1.32 g/kg). Furthermore, we determined that the average SOM content in the study area’s soil is 9.77 g/kg. Additionally, we confirmed that different differential transformation methods contribute to improving the correlation between spectral data and the SOM content, thereby enhancing the development of predictive models. This study provides a robust methodology and foundation for future soil organic matter monitoring in the region.

Soil metal contamination poses potential risks to ecosystem health, yet its vertical distribution and impacts on microbial communities in protected wildlife habitats remain poorly understood. This study investigated the vertical variation (0–80 cm) in seven metals or metalloids (Zn, Cr, Cu, Co, Ni, As, and Pb) and their correlations with soil bacterial communities in the Chinese Changxing Alligator Nature Reserve, Zhejiang Province, China. Soil samples were collected from two functional zones—the Reserved Breeding Zone (FY) and Reintroduction Zone (FG)—at four depth intervals. The results revealed distinct vertical stratification for both soil elements (metals and metalloids) and bacterial communities. Soil element concentrations exhibited depth-dependent variations, with surface layers showing higher accumulation of Zn, Ni, Cu, Cr and Pb, while As was enriched in deeper horizons. Bacterial alpha diversity declined with depth, and community composition shifted markedly: Pseudomonadota and Actinomycetota dominated surface soils, whereas Acidobacteriota and Chloroflexota increased in deeper layers. Network analysis revealed that microbial co-occurrence network complexity decreased with soil depth, indicating greater stability and environmental adaptability of surface soil microbial communities. Pearson correlation and Mantel analyses revealed significant depth-related variation in soil element concentrations (Zn, Co, Ni, Cu, Pb, Cr, and As), and these patterns were closely associated with shifts in soil bacterial community structure. This study provides systematic evidence of vertical differentiation in soil element–microbe interactions within reserve soil profiles, offering a scientific basis for habitat quality assessment, ecological risk warning, and Chinese alligator habitat conservation and management.