Climate change threatens coastal biodiversity, necessitating proactive conservation for endangered species like the mangrove Acanthus ebracteatus. This study integrated the MaxEnt and OPGD models to simulate its potential suitable habitats under current and three future SSP scenarios (SSP126, SSP245, and SSP585). Based on the MaxEnt model, sea surface salinity (SSS_range), sea surface temperature (SST_max), soil texture (T_silt, T_sand), and annual precipitation (Bio12) were identified as the dominant factors influencing its distribution, with SSS_range emerging as the key constraint. Furthermore, interaction analysis using the OPGD model revealed significant synergistic effects, particularly between salinity and soil properties (q > 0.8), underscoring the importance of multi-factor interactions in ecological niche modeling. Under the three SSP scenarios, the suitable habitat is projected to expand northeastward, accompanied by a poleward shift in the distribution centroid, driven predominantly by warming temperatures and altered rainfall patterns. KDE analysis revealed that existing protected areas do not fully cover regions with high habitat suitability. We propose a stratified conservation strategy that enhances in situ protection in core zones, initiates assisted restoration in potential habitats, and promotes experimental outplanting in future climatically suitable areas. This study provides scientific insights for the conservation and management of Acanthus ebracteatus under global climate change.

As a common practice in urban landscape design, tree planting plays an important role in improving the environment and microclimate. This study aimed to investigate the thermal comfort effects provided by trees on the surrounding environment. Using the common tree species Ficus altissima growing in lower subtropical China, the variation in temperature, humidity, and wind speed due to the tree canopy was summarized, the intensity of transpiration and cooling effects was analyzed, and the regression relationship between the indicators and thermal comfort was investigated using the physiological equivalent temperature (PET). The results revealed that various indications for thermal comfort may be described separately by one-dimensional regression equations, and three viable multiple regression equations could be created using the PET by combining physical, physiological, and microclimatic parameters.