Peng Zhou

Objective: To assess woody plant community functional diversity and its main environmental drivers in the northern Hainan volcanic lava region, a tropical volcanic landscape with marked habitat heterogeneity. Methods: Woody plant communities were surveyed in the field, leaf functional traits were measured, and nonparametric tests, correlation analysis, redundancy analysis (RDA), and structural equation modeling (SEM) were used to evaluate functional-diversity patterns and potential direct and indirect driver pathways. Results: Community-weighted mean values of leaf area (LA), leaf dry matter content (LDMC), chlorophyll a/b ratio (Chl a/Chl b), leaf dry weight (LDW), and leaf tissue density (LTD) were higher in trees than in shrubs ( p < 0.001). Functional richness (FRic), functional dispersion (FDis), and Rao’s quadratic entropy (RaoQ) were also higher in trees ( p < 0.001). Mean annual precipitation (MAP), soil pH, and aggregation index (AI) were the main drivers for the whole community, tree layer, and shrub layer, respectively. SEM suggested that meteorological and environmental factors, anthropogenic-disturbance, and landscape factors may affect functional diversity both directly and indirectly through soil properties. Conclusion: Functional diversity in this volcanic lava ecosystem is shaped by multiple environmental pathways, with soil properties playing an important mediating role. These findings provide evidence for conserving and managing woody plant communities in tropical volcanic landscapes.

Against the backdrop of continuous natural space loss and accelerated urbanization, considerable attention has been directed toward balancing economic development demands with the protection of fragile ecosystems within limited spatial boundaries to achieve regional sustainable development. This study therefore focuses on Chengmai County, a small-scale region prioritizing both green development and ecological conservation. Land-use changes and trends in ecosystem services value (ESV) from 2000 to 2020 were analyzed. An ecological security assessment model was developed, integrating ecosystem services, ecological sensitivity, and landscape connectivity, which enabled the identification of areas with high ecological security value as ecological sources. Ecological corridors and nodes were extracted using the minimum cumulative resistance model and the gravity model, culminating in the construction of Chengmai County’s ecological security pattern through overlay analysis. The main findings are summarized as follows: (1) Construction land expanded rapidly between 2000 and 2020. The ecological sensitivity of Chengmai County displayed a spatial distribution pattern of “high in the south, low in the north,” while ESV exhibited a pattern of “high in the central-south and low in the northeast,” showing an overall increasing trend. (2) The overall ecological security status was relatively favorable. A total of 10 ecological nodes and 45 ecological corridors were identified, including 16 core corridors. (3) Based on these analyses, an ecological security pattern described as “one axis, two belts, and three zones” was established for Chengmai County. This study provides a practical spatial strategy for ecological conservation and sustainable development in Chengmai County and offers a transferable methodological framework for similar coastal regions facing development pressures.

As a typical coastal tourist city, Sanya has experienced large-scale urbanization driven by tourism development, leading to landscape fragmentation, disorderly urban sprawl, and irrational resource utilization. These factors have intensified regional ecological risks and caused the degradation of ecosystem service functions, thereby constraining sustainable urban development. Therefore, establishing urban ecological zoning can identify the dynamic relationship between ecological conditions and urban growth, ease human-land conflicts, and promote high-quality urban development. This study employed the value equivalency method and the landscape ecological risk index method to calculate the ecosystem service value (ESV) and the ecological risk index (ERI) of Sanya City from 2000 to 2020 and to delineate ecological zones. The PLUS model was used to predict the changes in ecological zoning of Sanya City under a natural development scenario in 2030. The results demonstrate the following: (1) The ecological risk in the study area shows a distribution pattern of “high in the south and low in the north,” with low-risk areas being the dominant type, accounting for about 80% of the total area. Over time, the area of high-risk zones has shown an increasing trend, while that of low-risk zones has decreased year by year. (2) The ecosystem service value in the study area shows a distribution pattern of “high in the north and low in the south,” with a decreasing trend over time, with a cumulative reduction of 2.11 × 10⁸ ten thousand yuan from 2000 to 2020. (3) Among the four ecological zones, the ecological protection zone is the dominant type, accounting for about 50%. The increase in the ecological early warning zone is the most significant. In contrast, the ecological optimization and improvement zones show a marked decrease. The prediction results show that by 2030, the ecological early warning and ecological protection zones will increase, while the other zones will decrease. This study adopts a temporal-dynamic approach by constructing a framework that integrates historical evolution with future simulation, providing scientific evidence for building Sanya’s ecological security pattern and spatial governance. It offers practical significance for coordinating regional ecological conservation with urban development.

Recreational resources, fundamental to ecological experiences, are critical in balancing conservation with development. Effective ecotourism planning is especially vital for newly established protected areas such as the Hainan Tropical Rainforest National Park in China’s developing system of natural conservation areas. Targeting Hainan Tropical Rainforest National Park, this study applies nearest neighbor index, kernel density analysis, and exploratory spatial data analysis (ESDA) to study the spatial pattern of 274 recreational resource points. Results indicate a clustered spatial pattern with significant differences in resource density among municipalities. Specifically, 98% of these resources can be reached in 3 h, with an average travel time of 91 min, and cultural resources exhibit greater accessibility than natural resources. Natural resource availability and ethnic culture are major factors of resource distribution and accessibility. This research offers a theoretical basis and practical guidance for optimizing recreational resource allocation and promoting ecotourism in the park, contributing to the ongoing discussion of sustainable tourism development.