The upsurge in anthropogenic climate change has accelerated the habitat loss and fragmentation of wild animals and plants. The rare and endangered plants are important biodiversity elements. However, the lack of comprehensive and reliable information on the spatial distribution of these organisms has hampered holistic and efficient conservation management measures. We explored the consequences of climate change on the geographical distribution of Firmiana kwangsiensis (Malvaceae), an endangered species, to provide a reference for conservation, introduction, and cultivation of this species in new ecological zones. Modeling of the potential distribution of F. kwangsiensis under the current and two future climate scenarios in maximum entropy was performed based on 30 occurrence records and 27 environmental variables of the plant. We found that precipitation‐associated and temperature‐associated variables limited the potentially suitable habitats for F. kwangsiensis. Our model predicted 259,504 km² of F. kwangsiensis habitat based on 25 percentile thresholds. However, the high suitable habitat for F. kwangsiensis is only about 41,027 km². F. kwangsiensis is most distributed in Guangxi's protected areas. However, the existing reserves are only 2.7% of the total suitable habitat and 4.2% of the high suitable habitat for the plant, lower than the average protection area in Guangxi (7.2%). This means the current protected areas network is insufficient, underlining the need for alternative conservation mechanisms to protect the plant habitat. Our findings will help identify additional F. kwangsiensis localities and potential habitats and inform the development and implementation of conservation, management, and cultivation practices of such rare tree species.

Evaluating the spatial quality of a living street entails identifying and assessing the outdoor space that influences residents’ leisure and recreation, which may contribute to urban renewal. The application of multi-source data and deep learning technology enables an objective evaluation of large-scale spatial quality as opposed to the traditional questionnaire survey or experts’ subjective evaluation. Based on street view images, points of interest, and road network data, this study developed subjective and objective evaluation indicators for the central city of Hengyang using semantic segmentation and ArcGIS spatial analysis. This study then assigned weights to each indicator and calculated the spatial quality score for living streets. In addition, the subjective evaluations of the street view images were compared to test and verify the validation of the objective evaluation model. Finally, the study analyzed the accessibility within 500 m of the study area using Spatial Syntax and ArcGIS to overlay the low spatial quality score with the highest accessibility to identify the streets with the highest priority in the subsequent urban plan. The results indicate that the spatial quality of living in the west of Hengyang is higher than that in its northeast region. In addition, Xiao Xia Street, Guanghui Street, and Hengqi Road comprised the majority of the areas that required a priority update. Correspondingly, our research is expected to be a useful management tool for identifying urban street space issues and guiding urban renewal.

The urban heat island effect poses significant challenges to urban residents by diminishing thermal comfort and altering outdoor behaviors in hot environments. Although improvements in green space and adjustments to paving materials can alleviate these impacts, their combined effects remain insufficiently studied. This study employed ENVI-met software to simulate nine vegetation-paving material combinations and assess their influence on the thermal environment and thermal comfort of a campus courtyard during summer. Regression analyses were conducted to explore the interactions among these strategies. Air temperature (T _a ), surface temperature (T _s ), relative humidity (RH) and physiological equivalent temperature (PET) were used as key indicators to evaluate the effectiveness of each scenario. Results showed that “trees + lawn” and “trees + shrubs + lawn” were most effective in reducing T _a , T _s and PET, while increasing RH. In contrast, the “lawn + shrubs” configuration demonstrated limited effectiveness. Among the paving materials, high-reflectivity concrete yielded the greatest reductions in T _a and T _s , followed by standard concrete, with asphalt being the least effective. However, high-reflective concrete also led to an increase in PET due to increased radiant heat exposure. These findings provide a valuable foundation for informing microclimate-responsive landscape strategies in campus courtyards under summer conditions.

Exposure to natural landscapes has been shown to affect both physiological and psychological well-being, with the extent of these effects varying across different landscape types. However, the underlying mechanisms remain poorly understood. The association among stress reduction, environments characteristics and individual differences requires further investigation, particularly considering the complexity of landscape attributes and the variability of personal responses. In this study, 98 university students participated in a survey to evaluate the effects of different landscape types on visual preference and fatigue recovery. Physiological data (blood pressure, heart rate), psychological data (Perceived Restorative Scale), and visual preferences were analyzed before and after participants viewed the images of eight representative landscape space types: mountain, field, waterscape, lawn, desert, forest, artificial nature, plant. The results indicated that landscape type significantly influenced both physiological responses and emotional states, as well as participants’ perceived recovery from stress. Among the eight landscape spaces, water features and forests were reported to be the most restorative. Compared to freshmen, juniors exhibited greater improvements in physical and psychological recovery, alongside more positive evaluations of the environments. Notably, the desert landscape elicited varied responses depending on participants’ grade level and gender, suggesting that restoration effects may be modulated by individual characteristics. This may reflect an evolutionary predisposition to prefer natural features that enhance survival. These findings contribute to environmental psychology and provide valuable insights for educational practice and environmental design.

Climate change has accelerated the habitat loss and fragmentation of wildlife. Dye plants of “Fengxiang dyeing” are important indigenous natural resources for traditional printing and dyeing craft in southwest China, is of practical and cultural importance for dozens of ethnic minorities. However, lack of the spatial distribution information of these plants has hampered holistic and efficient conservation management measures. We analyzed the potentially suitable areas of four dye plants (Liquidambar formosana, Strobilanthes cusia, Persicaria tinctoria and Indigofera tinctoria) necessary for “Fengxiang dyeing” based on their geographical distribution sites under different climatic situations using the maximum entropy (MaxEnt) model. The results showed that temperature, precipitation and elevation were the most important factors affecting the suitable geographical areas of the four dye plants. Under the current climate conditions, the overlapping suitable habitat areas of the four plants were mainly in the four southern provinces of China, including Guizhou, Guangxi, Guangdong and Hainan. L. formosana was used as the base plant for combination with the other three plants under the two future climate scenarios (SSP126 and SSP585), and the overlapping suitable habitat areas of the obtained seven combination patterns were considered suitable for potential craft development. Five patterns showed an increase, while two patterns showed a decreasing trend with the increasing carbon emission. The prediction results showed that the overlapping suitable habitat center of the four plants will gradually move to the northeast, indicating that the overlapping suitable habitat area and craft distribution area will be changed. These results provide the basis for understanding the spatial distribution pattern changes of dye plants caused by climate change and establishing measures for protecting and developing printing and dyeing craft.

Cultural ecosystem services (CES) represent fundamental expressions of human-environment interactions. A comprehensive assessment of CES supply and demand offers a robust scientific foundation for optimizing the transformation of ecosystem service values to improve human well-being. This study integrates multi-source datasets and employs Maximum Entropy (MaxEnt) modeling with the ArcGIS platform to analyze the spatial distribution of CES supply and demand in Hunan Province, a typical mountain tourism regions in China. Furthermore, geographical detector methods were used to identify and quantify the driving factors influencing these spatial patterns. The findings reveal that: (1) Both CES supply and demand demonstrate pronounced spatial heterogeneity. High-demand areas are predominantly concentrated around prominent scenic locations, forming a “multi-core, clustered” pattern, whereas high-supply areas are primarily located in urban centers, water systems, and mountainous regions, exhibiting a gradient decline along transportation corridors and river networks. (2) According to the CES supply-demand pattern, Hunan Province can be classified into demand, coordination, and enhancement zones. Coordination zones dominate (45–70%), followed by demand zones (20–30%), while enhancement zones account for the smallest proportion (5–20%). (3) Urbanization intensity and land use emerged as the primary drivers of CES supply-demand alignment, followed by vegetation cover, distance to water bodies, and population density. (4) The explanatory power of two-factor interactions across all eight CES categories surpasses that of any individual factor, highlighting the critical role of synergistic multi-factorial influences in shaping the spatial pattern of CES. This study provides a systematic analysis of the categories and driving factors underlying the spatial alignment between CES supply and demand in Hunan Province. The findings offer a scientific foundation for the preservation of ecological and cultural values and the optimization of spatial patterns in mountain tourist areas, while also serving as a valuable reference for the large-scale quantitative assessment of cultural ecosystem services.