Worldwide, most ecosystem services have declined. However, the theoretical and analytical frameworks for the ecological risk assessment of ecosystem services are still lacking. Here a framework for the risk assessment of ecosystem services was developed based on the formation, changes, risk, and management of ecosystem services. The framework was tested in Ganzi, the upstream area of the Yangtze River Basin, for the regional ecological warning of ecosystem services. Ecosystem services in the form of soil retention and sandstorm prevention and ecological risks including soil and wind erosion were modelled. The results showed that with the increase in area and quality of natural vegetation (forest and grassland), the soil retention service and sandstorm prevention service increased by 66.92% and 8.59% between 2000 and 2015, respectively. Correspondingly, the ecological risk of soil erosion decreased by 8.8%, and wind erosion remained stable. Despite the negative impacts from agricultural development on sandstorm prevention, the increase in vegetation and improvement in ecological quality led to a decrease in the ecological risks of soil erosion and sandstorm erosion by improvement of ecosystem services. This research provides a new perspective for ecological risk assessment, as well as direct management information on ecological risks, by incorporating ecosystem services.

In the context of global urbanization, traditional villages have garnered increasing scholarly interest due to their role in preserving rich ethnic cultures and their potential contributions to cultural heritage. Existing literature has predominantly attributed the spatial heterogeneity of traditional villages to natural, environmental, and economic factors. However, cultural elements, which are equally crucial to the inheritance and continuation of traditional villages, are rather deficient in current research. By establishing a tripartite framework encompassing “natural environment—space economy—social culture” elements, this article first employs relevant geographic spatial analysis to examine the overall distribution patterns of Chinese traditional villages. Subsequently, it utilizes the Optimal Parameter-based GeoDetector model to assess the maximum impact of single factors and interactions among factors on the spatial heterogeneity of Chinese traditional villages. The paper then integrates spatial production theory to reveal the mechanisms underlying the interactions among these tripartite elements. The research findings indicate that cultural factors exert the most substantial influence on the spatial distribution of traditional Chinese villages, in contrast to previous research records that suggested natural elements had the greatest impact. Additionally, population and genealogy emerge as the two most critical factors, with their interaction having the most significant effect on the spatial pattern of Chinese traditional villages (q = 0.82663). Finally, we put forward regional-level recommendations for the preservation of traditional villages. Overall, our work can not only provide valuable insights for global research on traditional villages in developing countries based on traditional agriculture but also offer recommendations for the preservation of traditional villages in China.

Context: Traffic network construction is an essential method for enhancing the effectiveness of economic activities, but it can have various negative impacts on rare wildlife. In China, the rate of road construction has increased by over 300% during the past decade; however, the resulting fragmentation of rare habitats at a national scale remains uncertain. Aims: This study mainly aimed to evaluate the impacts of road and railway networks on the fragmentation of habitats of endangered species in China. Another aim is to identify the key areas and road sections where improvements to habitat connectivity and integrity are urgently required. Methods: We documented habitat information for 21 indicator species on the basis of two comprehensive datasets and over 120 previous studies. We combined this information to simulate the habitats of all these species by integrating a conceptual model and expert knowledge. We calculated the rates of change on the basis of three geometric habitat patterns for each species in traffic-clearing scenarios and road- and railway-overlay scenarios. An optimal algorithm, the core-area zonation cell-removal rule, was used to identify rare habitats affected by severe traffic stress. Key results: According to our analysis, we ranked the road density in the habitats of all species as a straightforward evaluation of transportation stress. Among the different species considered, snow leopard (Panthera uncia), Cabot’s tragopan (Tragopan caboti) and Przewalski’s gazelle (Procapra przewalskii) appeared to be affected most severely by road-induced fragmentation. In addition, we classified five patterns of habitat fragmentation among species to facilitate wildlife management. On the basis of the trade-off between road density and conservation value per unit, we identified 17 unit sets as key traffic-affected areas, including 40 highways, 62 national roads and 51 railway sections. Conclusions: Our results suggested that assessing the distributions of several key species can be effective in evaluating the impacts of roads on rare-wildlife habitats in China. Our results also indicated that the habitats of narrowly distributed species, such as Chinese alligator and Sichuan partridge, have high traffic densities, but core habitat degradation is even more serious for the habitats of species with higher intrinsic mobility or greater area requirements. Finally, we suggest that future conservation programs and restoration efforts should concentrate on roads or railway sections in the key areas that we identified. Implications: In the present study, we obtained spatially explicit findings related to the maintenance of rare wildlife in a region where wildlife-protection information is lacking. Our site-selection results can be used to allocate highly limited conservation resources in a more efficient and effective manner, to facilitate wildlife protection in this region.

The preservation and advancement of Traditional Villages are intricately linked to the perpetuation of cultural heritage. However, existing research on the spatial disparities among Traditional Villages has yet to consider the impact of cultural factors. Moreover, the geographical similarities shared by Traditional Villages have not been thoroughly examined. Therefore, this study takes the Yellow River Basin and the Yangtze River Basin, both pivotal in the genesis of Chinese culture, as case studies. We employ an Optimal Parameter-based GeoDetector alongside the Spatially Constrained Multivariate Clustering method to delve into the factors influencing the spatial differentiation and geographical similarities of Traditional Villages within these two significant river basins. Subsequently, we offer recommendations for fostering the sustainable preservation and development of Traditional Villages in these regions. The results indicate that the Rural Residents Per Capita Disposable Income has the greatest impact on the spatial differentiation of Traditional Villages in the Yellow River Basin, while the Density of National Intangible Cultural Heritage Inheritors has the most significant influence in the Yangtze River Basin. The interaction effects of the driving factors are more powerful, with a q-value of 0.9544 for the interplay between the Density of National Cultural Protection Units and the Tourism Income in the Yellow River Basin and a value of 0.9099 for the interaction between the Density of National Intangible Cultural Heritage Inheritors and the Transportation in the Yangtze River Basin. Regarding geographical similarity, the Traditional Villages in the Yellow River Basin are divided into three major clusters, while those in the Yangtze River Basin are divided into two.

The conservation and sustainable development of traditional villages have raised global attention in the context of rapid urbanization and modernization. Taking 703 traditional villages in Hunan Province as an example, this study first constructed a Traditional Village Human Settlement Suitability (TVHSS) evaluation system based on the Pressure-State-Response (PSR) model. Then, the entropy weighting method was used to assess the spatiotemporal evolution of TVHSS from 2005 to 2020, while the Geographically Weighted Regression (GWR) model was employed to analyze the influencing factors. The results indicate that the overall TVHSS score increased from 0.521 to 0.776 from 2005 to 2020, with a spatial distribution characterized by lower suitability in the northwest and higher suitability in the southeast. During this period, the pressure subsystem experienced an increase, peaking at 0.058 in 2015 before declining to 0.055 in 2020. Meanwhile, the state subsystem remained relatively stable, with scores slightly decreasing from 0.040 in 2005 to 0.033 in 2020. In contrast, the response subsystem showed a continuous upward trend, rising from 0.430 in 2005 to 0.688 in 2020. The distance to educational institutions, degree of relief, distance to water, and distance on intangible cultural heritage sites have the highest effects on TVHSS. These findings provide a scientific basis for the conservation and sustainable development of traditional villages and offer a replicable analytical framework for similar contexts globally. By addressing the complex interactions between environmental, social, and economic factors, this study contributes to the global discourse on rural sustainability, offering insights that can inform policy-making and guide the preservation of cultural heritage in the face of modernization pressures.

With the intensification of aging, the imbalance between the supply and demand of elderly care services has become increasingly prominent. Taking Changsha as a case study, this research constructs an accessibility evaluation system based on the 15-min life circle theory, utilizing multi-source data. Spatial weighting characteristics of elderly care facility locations were analyzed through machine learning algorithms, and service coverage disparities between urban districts and suburban towns were assessed under 5-, 10-, and 15-min walking thresholds. Street view semantic segmentation technology was employed to extract street environmental elements in central urban areas, and a multiple regression model was established to elucidate the impact mechanisms of the built environment on walking accessibility. Key findings include: (1) Significant urban-rural service disparities exist, with 91.4% of urban core facilities offering seven service categories within 15-min walking catchments compared to 26.86% in township areas, demonstrating suburban infrastructure’s heavy reliance on administrative resource allocation. (2) Street environmental factors exhibit significant correlations with walking accessibility scores. At the 15-min walking threshold, building space ratio and transportation infrastructure coverage positively influenced walking convenience, while sky view ratio showed a negative correlation. (3) A random forest-based location prediction framework identified multiple service gaps in existing facilities. Suburban service deficiencies (e.g., 59.8% medical facility coverage within walkable catchments) emerge as critical equity barriers, prompting recommendations for integrated “micro-clinic + smart pharmacy” networks and prioritized mixed-use zoning in new urban planning. This research advances a data-driven framework for reconciling urbanization-aging conflicts, offering practical insights for developing nations in creating age-friendly urban environments.