Nitrogen dioxide (NO₂) at a high concentration is among the most common and harmful air pollutants. The present study aimed to explore the physiological responses of plants exposed to NO₂. A total of 41 plants were classified into 13 functional groups according to the Angiosperm Phylogeny Group classification system. The plants were exposed to 6 μL/L NO₂ in an open-top glass chamber. The physiological parameters (chlorophyll (Chl) content, peroxidase (POD) activity, and soluble protein and malondialdehyde (MDA) concentrations) and leaf mineral ion contents (nitrogen (N⁺), phosphorus (P⁺), potassium (K⁺), calcium (Ca²⁺), magnesium (Mg²⁺), manganese (Mn²⁺), and zinc (Zn²⁺)) of 41 garden plants were measured. After NO₂ exposure, the plants were subsequently transferred to a natural environment for a 30-d recovery to determine whether they could recover naturally and resume normal growth. The results showed that NO₂ polluted the plants and that NO₂ exposure affected leaf Chl contents in most functional groups. Increases in both POD activity and soluble protein and MDA concentrations as well as changes in mineral ion concentrations could act as signals for inducing defense responses. Furthermore, antioxidant status played an important role in plant protection against NO₂-induced oxidative damage. NO₂ poses a pollution risk to plant systems, and antioxidant status plays an important role in plant protection against NO₂-induced oxidative damage. In conditions of strong air pollution, more evergreen plants may be considered in landscape design, particularly in seasonal regions. The results of this study may provide useful data for the selection of landscaping plants in NO₂ polluted areas.

Bougainvillea L. (Nyctaginaceae) is a South American native woody flowering shrub of high ornamental, economic, and medicinal value which is susceptible to cold damage. We sequenced the complete chloroplast (cp) genome of B. glabra and B. spectabilis, two morphologically similar Bougainvillea species differing in cold resistance. Both genomes showed a typical quadripartite structure consisting of one large single-copy region, one small single-copy region, and two inverted repeat regions. The cp genome size of B. glabra and B. spectabilis was 154,520 and 154,542 bp, respectively, with 131 genes, including 86 protein-coding, 37 transfer RNA, and 8 ribosomal RNA genes. In addition, the genomes contained 270 and 271 simple sequence repeats, respectively, with mononucleotide repeats being the most abundant. Eight highly variable sites (psbN, psbJ, rpoA, rpl22, psaI, trnG-UCC, ndhF, and ycf1) with high nucleotide diversity were identified as potential molecular markers. Phylogenetic analysis revealed a close relationship between B. glabra and B. spectabilis. These findings not only contribute to understanding the mechanism by which the cp genome responds to low-temperature stress in Bougainvillea and elucidating the evolutionary characteristics and phylogenetic relationships among Bougainvillea species, but also provide important evidence for the accurate identification and breeding of superior cold-tolerant Bougainvillea cultivars.

This study investigated the impact of Bacillus subtilis on plant growth and the rhizosphere microbial community in rose cultivation under saline–alkaline stress. Saline–alkaline stress was simulated with varying salt and alkali levels. Bacillus subtilis was introduced, and 16S rRNA high-throughput sequencing was conducted to analyze the root microbial community. Introduction of Bacillus subtilis significantly promoted rose growth and mitigated saline–alkaline stress effects. Gene sequencing revealed increased abundance of microbial genera, such as Tessaracoccus, Intrasporangium, Glutamicibacter, Agrobacterium, Saccharibacteria, Falsochrobactrum, Mesorhizobium, Bacillus, Ensifer, and Ornithinicoccus, under normal and saline–alkaline conditions, while functional changes in colony abundance were observed under different environments through PICRUST2 analysis. Bacillus subtilis demonstrated potential in enhancing rose growth and stress resistance under saline–alkaline conditions, affecting the regulation of the root microbial community. This study provides insights for improving soil conditions and enhancing plant adaptability in saline–alkaline regions.

Climate change, a global biodiversity threat, largely influences the geographical distribution patterns of species. China is abundant in woody landscape plants. However, studies on the differences in the adaptive changes of plants under climate change between northern and southern China are unavailable. Therefore, herein, the MaxEnt model was used to predict changes in the suitable distribution area (SDA) and dominant environmental variables of 29 tree species under two climate change scenarios, the shared socioeconomic pathways (SSPs) 126 and 585, based on 29 woody plant species and 20 environmental variables in northern and southern China to assess the differences in the adaptive changes of plants between the two under climate change. Temperature factors dominated the SDA distribution of both northern and southern plants. Southern plants are often dominated by one climatic factor, whereas northern plants are influenced by a combination of climatic factors. Northern plants are under greater pressure from SDA change than southern plants, and their SDA shrinkage tendency is significantly higher. However, no significant difference was observed between northern and southern plants in SDA expansion, mean SDA elevation, and latitudinal change in the SDA mass center. Future climate change will drive northern and southern plants to migrate to higher latitudes rather than to higher elevations. Therefore, future climate change has varying effects on plant SDAs within China. The climate change intensity will drive northern landscape plants to experience greater SDA-change-related pressure than southern landscape plants. Therefore, northern landscape plants must be heavily monitored and protected.

The rapid socio-economic development and urbanization in China have led to a decline in air quality. Therefore, the spatial and temporal distribution patterns of urban air pollution, as well as its formation mechanisms and influencing factors, have become important areas of research in atmospheric environment studies. This paper focuses on nine monitoring sites in Nanjing, where concentration data for six air pollutants and vegetation index data were collected from 2013 to 2021. The objective of this study is to investigate the changes in air pollutants and vegetation index over time and space, as well as their relationship with each other, and to assess the social and environmental impacts of air pollution. The findings reveal a spatial distribution pattern of air pollution in Nanjing that exhibits significant variability, with pollutant concentrations decreasing from the city center towards the surrounding areas. Notably, the main urban area has lower air quality compared to the peripheral regions. The results obtained from best-fit linear regression models and correlation heatmaps demonstrate a strong correlation (coefficient of determination, R² > 0.5) between the normalized difference vegetation index (NDVI) and pollutants such as SO₂, NO₂, PM_2.5, PM₁₀, and O₃ within a radial distance of 2 km from the air pollutant monitoring sites. These findings indicate that NDVI can be an effective indicator for assessing the distribution and concentrations of air pollutants. Negative correlations between NDVI and socio-economic indicators are observed under relatively consistent natural conditions, including climate and terrain. Therefore, the spatiotemporal distribution patterns of NDVI can provide valuable insights not only into socio-economic growth but also into the levels and locations of air pollution concentrations.