Xiaoying Ping

Ecosystem service flows (ESF) serve as a crucial bridge connecting the supply of ecosystem services to human demand. However, there are still deficiencies in the framework research on driving mechanisms and practical applications. In this research, we took the freshwater yield ecosystem service in the Henan section of the Yellow River Basin as a case study. We developed a comprehensive framework focusing on "supply-demand quantification-attribute evaluation-driving analysis-pattern optimization" utilizing methods such as network model, random forest, and Bayesian belief network. The key findings are as follows: (1) There was a spatial mismatch between the freshwater yield ecosystem service supply and demand, with demand exceeding supply in the study area. (2) Three flow directions and 35 sub-boundaries were identified throughout the flow process, with flow quantity ranging from 0 to 188×106 m3. (3) Evapotranspiration and human activities were the primary factors affecting the changes in supply-demand, with the contribution of 0.47 and 0.14, respectively. (4) Key optimization areas included Southern Luoyang, Central and Southern Sanmenxia, and Central Jiyuan. The comprehensive framework developed in this study analyzes ecosystem service supply and demand from four dimensions, enhancing the organization and depth of "flow" research. Furthermore, the framework demonstrates strong practical applicability, specifically in addressing the supply-demand imbalance of ecosystem services, providing robust support for water resource management and government decision-making in the Henan section of the Yellow River through effective water resource optimization.

Vegetation exerts a significant cooling effect, particularly during the hot summer; however, the spatial scale effects and gender difference among occupants’ subjective thermal comfort remain elusive. Developing a comprehensive model to elucidate the multidimensional relationship between green spaces and thermal experience holds paramount importance. Taking Longzi River Park in Zhengzhou city as a case study, this research examined the influence of vegetation on thermal experience by using structural equation modeling (SEM) from perspectives of fitting scale and gender disparities. It was found that (1) The vegetation environment not only influences thermal sensation, comfort and demand independently, but also influences the pathway between them. These influence paths constitute a complex causal network, functioning as a framework of “sensation → comfort → demand” and its influencing factors. (2) There exists a scaling effect in the pathway framework, which conforms to a threshold of 10 m for the inner radius and 30 m for the outer radius. The goodness of SEM model fit declines with the increase in either the inner radius or the outer radius, or both. (3) Differences in genders are exhibited for the pathway framework, with the vegetation exerting a stronger influence on female sensation and comfort, as well as male demand. The pathway from sensation to comfort to demand is more pronounced in male populations. The research findings contribute to the development of improved and sustainable vegetation distribution in urban parks.

Urban morphology has been empirically demonstrated to be self-organized and can be quantified by fractal dimension. However, the spatial variation rule of fractal features at the sub-zone scale has yet to be uncovered, as well as the relationship between fractal dimension values and road network or land-use patterns. In this study, the urban area is partitioned into 158 grid units, with subsequent calculations conducted to determine the fractal dimensions (using 2D box-counting and 3D voxel-counting methods), road network characteristics, and land-use patterns within each individual unit. The pattern of how architectures fill into the 2D or 3D embedding space at the grid level is revealed. Moreover, the spatial relationship between the road network, land-use, and their impacts on the local architectural layout is elucidated by employing MGWR, a model that incorporates the principles of fitting localized spatial regression. The results are as follows: (1) urban morphology follows fractal laws at a sub-zone scale, both in a 2D plane and 3D volume; (2) the filling degree of architecture is high in the urban center but low in the periphery areas; (3) the selected variables fit well with the regression models; (4) there is spatial heterogeneity regarding the influence of each factor. The research findings provide valuable insights into the theoretical relationship between urban morphology and the composite structure of road networks and land use. This facilitates identifying crucial areas and priority directions for urban renewal construction, as well as optimizing architectural design to improve efficiency and functionality.