Flooding has become one of the major abiotic stresses that seriously affects plant growth and development owing to changes in the global precipitation pattern. Mulberry (Morus alba L.) is a desirable tree spePhysocarpus amurensis Maxim andcies with high ecological and economic benefits. To reveal the response and adaptive mechanisms of the photosynthetic functions of mulberry leaves to flooding stress, chlorophyll synthesis, photosynthetic electron transfer and the Calvin cycle were investigated by physiological studies combined with an analysis of the transcriptome. Flooding stress inhibited the synthesis of chlorophyll (Chl) and decreased its content in mulberry leaves. The sensitivity of Chl a to flooding stress was higher than that of Chl b owing to the changes of CHLG (LOC21385082) and CAO (LOC21408165) that encode genes during chlorophyll synthesis. The levels of expression of Chl b reductase NYC (LOC112094996) and NYC (LOC21385774), which are involved in Chl b degradation, were upregulated on the fifteenth day of flooding, which accelerated the transformation of Chl b to Chl a, and upregulated the expression of PPH (LOC21385040) and PAO (LOC21395013). This accelerated the degradation of chlorophyll. Flooding stress significantly inhibited the photosynthetic function of mulberry leaves. A Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of differentially expressed genes under different days of flooding stress indicated significant enrichment in Photosynthesis-antenna proteins (map00196), Photosynthesis (map00195) and Carbon fixation in photosynthetic organisms (map00710). On the fifth day of flooding, 7 and 5 genes that encode antenna proteins were identified on LHCII and LHCI, respectively. They were significantly downregulated, and the degree of downregulation increased as the trees were flooded longer. Therefore, the power of the leaves to capture solar energy and transfer this energy to the reaction center was reduced. The chlorophyll fluorescence parameters and related changes in the expression of genes in the transcriptome indicated that the PSII and PSI of mulberry leaves were damaged, and their activities decreased under flooding stress. On the fifth day of flooding, electron transfer on the PSII acceptor side of mulberry leaves was blocked, and the oxygen-evolving complex (OEC) on the donor side was damaged. On the tenth day of flooding, the thylakoid membranes of mulberry leaves were damaged. Five of the six coding genes that mapped to the OEC were significantly downregulated. Simultaneously, other coding genes located at the PSII reaction center and those located at the PSI reaction center, including Cytb6/f, PC, Fd, FNR and ATP, were also significantly downregulated. In addition, the gas exchange parameters (P_n, G_s, T_r, and C_i) of the leaves decreased after 10 days of flooding stress primarily owing to the stomatal factor. However, on the fifteenth day of flooding, the value for the intracellular concentration of CO₂ was significantly higher than that on the tenth day of flooding. In addition, the differentially expressed genes identified in the Calvin cycle were significantly downregulated, suggesting that in addition to stomatal factors, non-stomatal factors were also important factors that mediated the decrease in the photosynthetic capacity of mulberry leaves. In conclusion, the inhibition of growth of mulberry plants caused by flooding stress was primarily related to the inhibition of chlorophyll synthesis, antenna proteins, photosynthetic electron transfer and the Calvin cycle. The results of this study provide a theoretical basis for the response and mechanism of adaptation of the photosynthetic function of mulberry to flooding stress.

Background: Soil microbial community diversity serves as a highly sensitive indicator for assessing the response of terrestrial ecosystems to various changes, and it holds significant ecological relevance in terms of indicating ecological alterations. At the global scale, vegetation type acts as a major driving force behind the diversity of soil microbial communities, encompassing both bacterial and fungal components. Modifications in vegetation type not only induce transformations in the visual appearance of land, but also influence the soil ecosystem’s material cycle and energy flow, resulting in substantial impacts on the composition and performance of soil microbes. Methods: In order to examine the disparities in the structure and diversity of soil microbial communities across distinct vegetation types, we opted to utilize sample plots representing four specific vegetation types. These included a woodland with the dominant tree species Drypetes perreticulata, a woodland with the dominant tree species Horsfieldia hainanensis, a Zea mays farmland and a Citrus reticulata fields. Through the application of high-throughput sequencing, the 16S V3_V4 region of soil bacteria and the ITS region of fungi were sequenced in this experiment. Subsequently, a comparative analysis was conducted to explore and assess the structure and dissimilarities of soil bacterial and fungal communities of the four vegetation types were analyzed comparatively. Results: Our findings indicated that woodland soil exhibit a higher richness of microbial diversity compared to farmland soils. There were significant differences between woodland and farmland soil microbial community composition. However, all four dominant phyla of soil fungi were Ascomycota across the four vegetation types, but the bacterial dominant phyla were different in the two-farmland soil microbial communities with the highest similarity. Furthermore, we established a significant correlation between the nutrient content of different vegetation types and the relative abundance of soil microorganisms at both phyla and genus levels. This experiment serves as a crucial step towards unraveling the intricate relationships between plants, soil microbes, and soil, as well as understanding the underlying driving mechanism.

The leaf area index (LAI) is a crucial indicator for quantifying forest productivity and community ecological processes. Satellite remote sensing can achieve large-scale LAI monitoring, but it needs to be calibrated and validated according to the in situ measurements on the ground. In this study, we attempted to use different indirect methods to measure LAI in a tropical secondary forest. These methods included the LAI-2200 plant canopy analyzer (LAI-2200), Digital Hemispherical Photography (DHP), Tracing Radiation and Architecture of Canopies (TRAC), and Terrestrial Laser Scanning (TLS) (using single-station and multi-station measurements, respectively). Additionally, we tried to correct the measured LAI by obtaining indicators of woody components and clumping effects. The results showed that the LAI of this forest was large, with estimated values of 5.27 ± 1.16, 3.69 ± 0.74, 5.86 ± 1.09, 4.93 ± 1.33, and 3.87 ± 0.89 for LAI-2200, DHP, TRAC, TLS multi-station, and TLS single-station, respectively. There was a significant correlation between the different methods. LAI-2200 was significantly correlated with all other methods (p < 0.01), with the strongest correlation with DHP (r = 0.684). TRAC was significantly correlated with TLS single-station (p < 0.01, r = 0.283). TLS multi-station was significantly correlated with TLS single-station (p < 0.05, r = 0.266). With the multi-station measurement method, TLS could maximize the compensation for measurement bias due to the shadowing effects. In general, the clumping index of this forest was 0.94 ± 0.05, the woody-to-total area ratio was 3.23 ± 2.22%, and the total correction coefficient was 1.03 ± 0.07. After correction, the LAI estimates for all methods were slightly higher than before, but there was no significant difference among them. Based on the performance assessment of existing ground-based methods, we hope to enhance the inter-calibration between methods to improve their estimation accuracy under complex forest conditions and advance the validation of remote sensing inversion of the LAI. Moreover, this study also provided a practical reference to promote the application of LiDAR technology in tropical forests.

This study investigates how different vegetation types influence the molecular structure and abundance of soil organic carbon (SOC), as well as their influence on microbial metabolic pathways and community composition. Soil samples were collected from four different sites: a woodland dominated by Drypetes perreticulata (DP), a woodland dominated by Horsfieldia hainanensis (HM), a Zea mays L. field (ZL), and a citrus reticulata orchard (CB). The molecular structure of soil organic carbon (SOC) was characterised using Fourier Transform Infrared (FTIR) spectroscopy, identifying aromatic carbon (ArC), polysaccharide carbon (PSC), alkyl carbon (AlkC), amine carbon (AmC), ether carbon (EtC), and olefin carbon (OleC). Our results indicated significant variations across vegetation types: DG exhibited a significantly higher ArC content, while maize fields showed lower PSC levels. To analyse the relationships between different samples, we employed principal component analysis (PCA), which revealed distinct organic carbon structures across vegetation types, with the forests (DG and HM) significantly differing from agricultural sites (ZL and CB). Additionally, the 16S V3_V4 region of soil bacteria was sequenced using high-throughput sequencing. We employed PICRUSt2 to predict microbial metabolic pathways, revealing consistent core metabolic functions across samples but significant variations in secondary metabolism, with HM samples exhibiting the most distinctive metabolic profiles. Redundancy analysis (RDA) further demonstrated that microbial metabolic pathway variation explained 55.66% of organic carbon structure variance. Key microbial taxa exhibited significant associations with specific carbon source types and functional pathways. These findings highlight the pivotal mechanisms by which different vegetation types regulate soil organic carbon structure and composition by driving changes in microbial metabolic traits and community assembly. This study provides a mechanistic basis for understanding the coupling between vegetation, microorganisms, and carbon cycling, offering significant guidance for optimising vegetation restoration strategies, enhancing soil carbon sequestration capacity, and advancing carbon management practices based on microbial regulation.

Natural and planted forests differentially regulate soil quality through vegetation–soil interactions. The effects of four types of planting covers on soil nutrients, enzyme activities, and microbial communities in the Guangxi Camellia nitidissima National Nature Reserve were studied, revealing the multi-dimensional influences of natural (broadleaf, shrubland) and planted forests (bamboo, pine) on soil quality. Surface soils (0–10 cm depth) were characterized for physicochemical properties (pH, TC, TN, NO₃⁻-N, AP), enzyme activities (α-amylase, urease, phosphatase, β-glucosidase), and microbial composition (using 16S rRNA and ITS region sequencing). Mantel tests and PLS–PM modeling were employed to investigate interactions among vegetation, soil variables, and microbes. Natural forests exhibited higher pH, nitrate nitrogen, and enzymatic activities (urease, phosphatase, β-glucosidase) alongside enhanced carbon–nitrogen accumulation and reduced acidification. Planted forests showed elevated available phosphorus and nutrient supply but lower organic matter retention. Microbial communities displayed higher similarity within natural forests, with fungal composition strongly linked to total carbon/nitrogen (p < 0.05). Vegetation type positively influenced bacterial diversity but negatively affected fungal communities. Natural forests maintained critical soil–microbe–plant interactions supporting ecosystem resilience through carbon–nitrogen cycling, while planted forests fostered divergent microbial functionality despite short-term nutrient benefits. These findings underscore natural forests’ unique role in preserving ecological stability and reveal fundamental limitations of artificial systems in mimicking microbially-mediated biogeochemical processes. Conservation policy should prioritize the protection of natural forests while simultaneously integrating microbial community management with vegetation restoration efforts to enhance long-term ecosystem functionality and nutrient cycling efficiency.