Mitogen-activated protein kinases (MAPKs) are crucial regulators in coping with abiotic and biotic stresses, including drought, salinity, fungi, and pathogens. However, little is known about the characteristics, evolution process, and functional divergence of the MAPK gene family in Rosaceae plants. A total of 97 MAPK members were identified in six Rosaceae species, including 12 genes in Fragaria vesca, 22 genes in Malus domestica, 23 genes in Pyrus bretschneideri, 12 genes in Prunus mume, 14 genes in Prunus persica, and 14 genes in Rosa chinensis. All MAPK members of six Rosaceae plants were categorized into four clusters by the phylogenetic relationship analysis. Collinearity analysis discovered that both segmental duplication and tandem duplication contributed to the expansion of MAPK family genes in Rosaceae plants. And the analysis of motifs and gene structures indicated that the evolution of the MAPK gene family was highly conserved among phylogenetic clusters in Rosaceae species. In addition, the d_N/d_S rates of MAPK paralogous gene pairs were below one, suggesting the MAPK gene family in Rosaceae was driven by purifying selective pressure. Furthermore, functional divergence analysis discovered that 14 amino acid residues were detected as potentially key sites for functional divergence of MAPK family genes between different cluster pairs, specifically Type I functional divergence. The analysis of functional distance indicated that cluster C retained more of the original functional features, while cluster B exhibited functional specialization. Moreover, the expression profiles revealed that PmMAPK8, PmMAPK9, and PmMAPK10 were both highly expressed under drought stress and low temperature conditions. This study aims to comprehensively analyze the evolutionary process and functional analyses of the MAPK gene family in Rosaceae plants, which will lay the foundation for future studies into MAPK genes of Rosaceae in response to drought and cold stress.

Amid accelerating climate change, intensifying urban heat island effects, and rising public demand for livable, walkable streets, there is an urgent practical need for interpretable and actionable evidence on streetscape quality. Yet, research on streetscape quality has often relied on single data sources and linear models, limiting insight into multidimensional perception; evidence from temperate monsoon cities remains scarce. Using Tianjin’s main urban area as a case study, we integrate street-view imagery with remote sensing imagery to characterize satellite-derived environmental indicators at the point scale and examine the following five perceptual outcomes: comfort, aesthetics, perceived greenness, summer heat perception, and willingness to linger. We develop a three-step interpretable assessment, as follows: Elastic Net logistic regression to establish directional and magnitude baselines; Generalized Additive Models with a logistic link to recover nonlinear patterns and threshold bands with Benjamini–Hochberg false discovery rate control and binned probability calibration; and Shapley additive explanations to provide parallel validation and global and local explanations. The results show that the Green View Index is consistently and positively associated with all five outcomes, whereas Spatial Balance is negative across the observed range. Sky View Factor and the Building Visibility Index display heterogeneous forms, including monotonic, U-shaped, and inverted-U patterns across outcomes; Normalized Difference Vegetation Index and Land Surface Temperature are likewise predominantly nonlinear with peak sensitivity in the midrange. In total, 54 of 55 smoothing terms remain significant after Benjamini–Hochberg false discovery rate correction. The summer heat perception outcome is highly imbalanced: 94.2% of samples are labeled positive. Overall calibration is good. On a standardized scale, we delineate optimal and risk intervals for key indicators and demonstrate the complementary explanatory value of street-view imagery and remote sensing imagery for people-centered perceptions. In Tianjin, a temperate monsoon megacity, the framework provides reproducible, actionable, design-relevant evidence to inform streetscape optimization and offers a template that can be adapted to other cities, subject to local calibration.

Under the background of global climate change and China’s “carbon peak and carbon neutrality” strategy, it is of great significance to assess the carbon sink benefits of urban park plant communities. This study took 20 plant community plots of 20 m × 20 m (400 m²) in Tientsin Water Park as the research object. Carbon sequestration capacity was characterized by carbon stock (CS) and annual carbon sequestration (ACS), and six community structure indicators were quantified: Vegetation Coverage (VC), Canopy Density (CD), Three-Dimensional Green Volume (3DGV), Tree-to-Shrub Ratio (TSR), Vertical Complexity (CV), and Number of Individuals (N). Spearman correlation analysis, principal component analysis, and regression analysis were adopted, and K-means clustering was introduced to identify vegetation structure–function groups, thereby exploring the statistical correlations between these structural characteristic indicators and carbon sink capacity indicators (CS and ACS). The results showed that (1) VC, CD, and 3DGV were significantly positively correlated with CS, suggesting that these factors may be more conducive to long-term carbon pool accumulation; (2) N was significantly positively correlated with ACS, and a nonlinear decreasing trend was observed in the current observation data; (3) the influence of TSR and CV on carbon storage and sequestration also showed a nonlinear correlation. Based on the above correlation findings, the community combinations with higher carbon sink performance in this case were screened out. And suggestions for low-carbon configuration of plant communities, centered on optimizing canopy structure, configuring high-carbon-sequestration tree species, and regulating reasonable density, were proposed, which can be used as a reference for forming hypotheses in subsequent confirmatory studies.