Contemporary landscape architecture studies have paid close attention to the interactions between public aesthetic preferences and the landscape environment. Scenic beauty has become an important evaluation indicator of landscape quality. The quality of the plant color landscape is an important factor affecting scenic beauty. Exploring the relationship between the composition rules and internal properties of autumn plant color landscapes in urban parks and public aesthetic preferences can provide new ideas for the evaluation and design of plant community color landscapes. Taking 12 parks in Changsha City, Hunan Province, China, as the study area and 85 plant communities as the sample plots, scenic beauty estimation (SBE) was used to evaluate the autumn plant color landscape of urban parks. ColorImpact software was used to extract the color values of each plant community. Fifteen original color element indicators were determined, and the data were statistically analyzed by principal component analysis (PCA), one-way ANOVA, multiple comparison analysis and systematic cluster analysis. Four principal components were extracted to construct the characteristic indices and a comprehensive model of the color landscape quality of autumn plant communities. The four characteristic indices showed significant or extremely significant differences among the five SBE grades. From the overall trend, the SBE grades showed a positive correlation with PC1 (primary and adjunctive color index), PC2 (color structure and property index) and PC3 (autumn-color-leafed index) and a negative correlation with PC4 (intersperse color index). R_PH (ratio of primary hue), R_P (ratio of primary color), R_C (color-leafed index), R_WC (ratio of warm and cool colors), and N_C (number of colors) were the key factors affecting the SBE grade. Overall, R_PH, R_P, R_C, and R_WC positively influenced the SBE values, while N_C negatively influenced the SBE values, and five to seven colors were more moderate. The quality of the color landscape can be improved by creating plant communities with three types of color composition: warm-toned dominant type, warm- and cold-toned contrast type, and multicolor harmonic type. The results provide a reference for the evaluation, design and construction of autumn plant color landscapes in urban parks.

Understanding the influencing effect of meteorological factors and air pollutants in the campus plot and the relationship between them is an important topic in the planning and design of campus green space. The changes of pollutant concentrations and meteorological factors in campus green space have certain patterns and specific influencing factors. In this study, we selected four sample plots in Nanjing Forestry University as the research objects, and collected various environmental parameters of the four plots on July 25, 2022. The results showed that the main influences of meteorological factors are the type of the underlying surface of the site, the degree of plant canopy density and the shade coverage area of the building. These factors mainly have a great influence on the value of temperature and humidity. The comprehensive influencing factors can be concluded that the cooling and humidifying effect of the site is ranked as follows: forest > lawn > asphalt road > concrete Square. The main influencing factors of pollutants are: illumination, wind speed, temperature and relative humidity. Among them, illumination and temperature have a negative correlation with PM_2.5, wind speed and relative humidity have a positive correlation with PM_2.5. Our research shows that the adjustment of campus green space factors can reduce the concentration of pollutants by changing the meteorological factors.

This study employed a combination of ultraviolet spectrophotometry, LC-ESI-MS/MS system, and RNA-sequencing technology; the extracts and isolation of total RNA from the red and yellow leaf strains of red maple (Acer rubrum L.) at different developmental stages were subjected to an intercomparison of the dynamic content of chlorophyll and total anthocyanin, flavonoid metabolite fingerprinting, and gene expression. The metabonomic results indicated that one hundred and ninety-two flavonoids were identified, which could be classified into eight categories in the red maple leaves. Among them, 39% and 19% were flavones and flavonols, respectively. The metabolomic analysis identified 23, 32, 24, 24, 38, and 41 DAMs in the AR1018r vs. AR1031r comparison, the AR1018r vs. AR1119r comparison, the AR1031r vs. AR1119r comparison, the AR1018y vs. AR1031y comparison, the AR1018y vs. AR1119y comparison, and the AR1031y vs. AR1119y comparison, respectively. In total, 6003 and 8888 DEGs were identified in AR1018r vs. AR1031r comparison and in the AR1018y vs. AR1031y comparison, respectively. The GO and KEGG analyses showed that the DEGs were mainly involved in plant hormone signal transduction, flavonoid biosynthesis, and other metabolite metabolic processes. The comprehensive analysis revealed that caffeoyl-CoA 3-O-methyltransferase (Cluster-28704.45358 and Cluster-28704.50421) was up-regulated in the red strain but down-regulated in the yellow strain, while Peonidin 3-O-glucoside chloride and Pelargonidin 3-O-beta-D-glucoside were up-regulated in both the red and yellow strains. By successfully integrating the analyses on the behavior of pigment accumulation, dynamics of flavonoids, and differentially expressed genes with omics tools, the regulation mechanisms underlying leaf coloring in red maple at the transcriptomic and metabolomic levels were demonstrated, and the results provide valuable information for further research on gene function in red maple.