Distinguishing vegetation types from satellite images has long been a goal of remote sensing, and the combination of multi-source and multi-temporal remote sensing images for vegetation classification is currently a hot topic in the field. In species-rich mountainous environments, this study selected four remote sensing images from different seasons (two aerial images, one WorldView-2 image, and one UAV image) and proposed a vegetation classification method integrating hierarchical extraction and object-oriented approaches for 11 vegetation types. This method innovatively combines the Random Forest algorithm with a decision tree model, constructing a hierarchical strategy based on multi-temporal feature combinations to progressively address the challenge of distinguishing vegetation types with similar spectral characteristics. Compared to traditional single-temporal classification methods, our approach significantly enhances classification accuracy through multi-temporal feature fusion and comparative experimental validation, offering a novel technical framework for fine-grained vegetation classification under complex land cover conditions. To validate the effectiveness of multi-temporal features, we additionally performed Random Forest classifications on the four individual remote sensing images. The results indicate that (1) for single-temporal images classification, the best classification performance was achieved with autumn images, reaching an overall classification accuracy of 72.36%, while spring images had the worst performance, with an accuracy of only 58.79%; (2) the overall classification accuracy based on multi-temporal features reached 89.10%, which is an improvement of 16.74% compared to the best single-temporal classification (autumn). Notably, the producer accuracy for species such as Quercus acutissima Carr., Tea plantations, Camellia sinensis (L.) Kuntze, Pinus taeda L., Phyllostachys spectabilis C.D.Chu et C.S.Chao, Pinus thunbergii Parl., and Castanea mollissima Blume all exceeded 90%, indicating a relatively ideal classification outcome.

Anthocyanins, crucial water-soluble pigments in plants, determine coloration in floral and fruit tissues, while fulfilling essential physiological roles in terms of plant growth, development, and stress adaptation. The biosynthesis of anthocyanins is transcriptionally regulated by WRKY factors, one of the largest plant-specific transcription factor families. Euscaphis japonica is an East Asian species, prized for its exceptionally persistent butterfly-shaped fruits that undergo pericarp dehiscence, overturning, and a color transition to scarlet red. This species represents an ideal system for studying anthocyanin regulation. However, the mechanisms by which WRKY transcription factors orchestrate anthocyanin accumulation during this process remain unknown. In this study, we identified 87 WRKY genes (EjaWRKYs) from the E. japonica genome. Phylogenetic analysis was used to classify these genes into three primary groups, with five subgroups, revealing conserved gene structures and motif compositions, supported by collinearity and comparative synteny analyses. Crucially, ten EjaWRKYs exhibited peak expression during the mature fruit stages, showing positive correlations with key anthocyanin biosynthesis genes. Functional validation through the use of transient transactivation assays in Nicotiana benthamiana confirmed that the five selected EjaWRKYs bind W-box elements and strongly activate reporter gene expression. Our results reveal EjaWRKYs’ regulation of anthocyanin accumulation in E. japonica fruit, provide the first comprehensive WRKY family characterization of this species, and establish a foundation for manipulating ornamental traits in horticultural breeding.

Urban wetlands play a crucial role in maintaining ecological balance, carbon sequestration, and water purification. Sediments are key carriers for wetlands to store elements such as carbon, nitrogen, and phosphorus in the aquatic environment. This study analyzed different sediment layers of seven wetlands in Yangzhou, aiming to explore the relationship between physicochemical factors and microbial communities in wetland sediments, as well as to predict the functions of microbial communities. Functional prediction of microbial communities was conducted based on amplicon sequencing analysis, and the neutral community model was used to determine the formation and evolution process of microbial communities. The results showed that in three wetlands, namely Zhuyu Bay (ZYW), Luyang Lake (LYH), and Runyang Wetland (RYSD), the contents of carbon components (total carbon, total soluble carbon, microbial biomass carbon) in the 0–20 cm sediment layer were higher, while the carbon component contents in Baoying Lake (BYH) showed the opposite trend. Among them, the contents of total nitrogen, alkali-hydrolyzable nitrogen, total phosphorus, available phosphorus, total potassium, and available potassium in the 0–20 cm sediment layer of Runyang Wetland (RYSD) were significantly the highest. This indicates that in Runyang Wetland (RYSD), the 0–20 cm layer has more abundant carbon components and mineral nutrients compared to the 20–40 cm layer. Among the seven wetlands, it was found that the content of total potassium was all greater than 10 g/kg, which was much higher than the contents of total phosphorus and total nitrogen. Analysis of microbial communities revealed that the dominant archaeal phyla were Thaumarchaeota and Euryarchaeota, and the dominant bacterial phyla were Proteobacteria and Acidobacteria. The distribution of functional genes was mainly concentrated in Zhuyu Bay (ZYW) and Luyang Lake (LYH). Zhuyu Bay Wetland (ZYW) had potential advantages in light utilization function, and Luyang Lake (LYH) had potential advantages in carbon and nitrogen cycle functions. The assembly process of the archaeal community was mainly affected by stochastic processes, while the bacterial community was mainly affected by deterministic processes. However, water content, total phosphorus, and available potassium all had strong correlations with both archaeal and bacterial communities. The research results preliminarily reveal the connections between the physicochemical properties of sediments, microbial communities, and their potential functions in Yangzhou urban wetlands, providing an important scientific basis for the protection and management of wetland ecosystems.

Human trampling in urban forest parks has received increasing attention, yet its effects on microbial community assembly remain elusive. This study investigated how trampling influences soil physicochemical properties and microbial communities in Zhuyuwan Scenic Area. Neutral and null community models were used to analyze the effects of trampling on microbial assembly processes. Trampling altered both soil physicochemical properties and microbial diversity. Fungal richness differed significantly between control and light-trampling plots. Soil bulk density (SD) was strongly negatively correlated with other soil physical properties, which were positively intercorrelated. Model analyses showed that light trampling strengthened stochastic processes in bacterial community assembly, whereas heavy trampling reduced this effect. Increasing trampling intensity intensified the influence of stochastic processes on fungal community assembly. Bacterial communities were mainly shaped by heterogeneous selection, while fungal communities were primarily governed by dispersal limitation. These results enhance understanding of how trampling disturbance influences microbial community assembly and provide a theoretical basis for the ecological management and restoration of urban forest parks.

Soil respiration is an indispensable component of soil ecosystems and plays a crucial role in the soil carbon cycle. Understanding the factors that influence soil respiration is of great significance for forestry management. This study monitored six forest types in the Zhuyu Bay Forest of Yangzhou City, Jiangsu Province, China, to investigate the seasonal dynamics of soil respiration across different forest patterns. The key factors influencing soil respiration were identified using a combination of the Random Forest model and the partial least squares path model. The results showed that soil respiration exhibits obvious seasonal variations, as the average soil respiration of the six forest stands peaks at 208.91 mg/m²·h in summer and reaches the lowest point at 46.49 mg/m²·h in winter. Soil respiration primarily is regulated by physicochemical properties. In addition, microbial biomass carbon, microbial biomass nitrogen, sucrase, and dissolved organic carbon were identified as important factors affecting soil respiration, with importance values of 8.13, 7.49, 5.89, and 4.86, respectively. These findings contribute to a more comprehensive understanding of the complex mechanisms underlying the soil carbon cycle and provide a scientific basis for optimizing forest management practices, thus enhancing carbon sequestration and promoting the sustainable development of forest ecosystems.

The soil microbial community in coastal wetlands plays a crucial role in biogeochemical cycling. In this study, Spartina alterniflora soil (HB), found near the sea; Spartina alterniflora soil (ZY), found near land; and Phragmites australis soil (KA), found in coastal wetlands, were selected to study the microbial community structure and major environmental influencing factors. The results showed that environmental factors had a significant difference in the three soils. Compared with the ZY and KA sites, the soil at the HB site had the highest value of salinity (14.1 g/kg) and the lowest value of total organic carbon (TOC) (2.9 g/kg) in summer. At the KA site, the values of soil temperature, soil humidity (SH), TOC, and NH₄⁺ were higher than those at HB and ZY sites, while the values of EC (159.8 μS/cm in summer) and salinity (4.4 g/kg) were the lowest. Furthermore, the microbial community structure had significant differences at the three sites. Pseudomonas and Bacteroidota dominated at the HB site, while Chloroflexota and Gemmatimonades were more abundant at the ZY and KA sites. Microbial alpha diversity analysis indicated that the microbial community diversity of Phragmites australis soil was the most uniform, and the microbial species richness in the soil of Spartina alterniflora near the sea was the highest. Salinity, TOC, and SH might be the key environmental factors that affect the structure and diversity of microbial communities in soils. High-salt environments may promote the enrichment of salt-tolerant microbial communities, while high TOC and suitable soil humidity may enhance the uniformity of microbial communities.