Watersheds constitute highly coupled nature-society complex systems where the coordination of human-water relationships is fundamental to sustainability. Under dual pressures from global change and intensive anthropogenic activities, traditional single-factor governance approaches have proven inadequate for addressing systemic risks in watershed systems. Grounded in systems science theory, this study developed a comprehensive theoretical framework for green watersheds centered on human-water harmony, proposing an innovative “Four Waters, Four Dimensions” model that emphasizes the synergistic development of water resources, water environment, water ecology, and water economy. This holistic approach acknowledges the interdependence of these elements and their collective role in promoting watershed sustainability, transcending traditional sectoral silos by simultaneously addressing resource availability, environmental quality, ecological integrity, and economic viability. To operationalize this framework, a systematic methodology encompassing ‘System Analysis-Comprehensive Assessment-Spatial Governance’ was established. The system analysis component identified key elements of the coupled human-water system, including driving forces in the socioeconomic subsystem and supporting capacities in water subsystems, employed the DPSIR (Drivers-Pressures-State-Impact-Response) framework to analyze coupling mechanisms and feedback processes, and established a comprehensive simulation platform through multi-module integration to support coordinated development analysis. The comprehensive assessment module followed the progressive logic of ‘indicator species persistence-ecosystem functionality-environmental improvement-socioeconomic development’, constructing a multi-tiered evaluation framework based on ecological integrity that integrates multi-dimensional indicators to assess coordination among the four water dimensions. The spatial governance component utilized GIS-based fuzzy C-means clustering analysis to delineate management units with similar characteristics, establishing differentiated regulatory thresholds and implementing place-based “one strategy per unit” approaches that balance ecological protection with economic development needs. Three representative implementation models tailored to diverse regional contexts were proposed. The urban-intensive model, designed for highly urbanized regions, prioritizes pollution-economy decoupling through green industrial transformation, rainwater resource utilization, and ecological space restoration. The agriculture-dominated model, targeting major agricultural production areas, emphasizes source control through precision agriculture, water-saving irrigation technologies, and non-point source pollution management. The ecologically-fragile model, applicable to environmentally vulnerable regions, focuses on ecological restoration, vegetation recovery, and ecosystem service value realization. Each model incorporates quantifiable performance indicators and explicitly integrates carbon neutrality objectives, addressing both synergies and trade-offs among emission reduction, water conservation, and pollution control measures. This research provides comprehensive theoretical foundations and actionable practical pathways for transcending traditional watershed management bottlenecks, advancing both high-level environmental protection and high-quality regional development, and achieving sustainable human-water coexistence in the context of global environmental change.
The intensification of climate change and human activities has exposed the world to highly complex ecological risks. Identifying ecological security patterns based on ecological security early warning constitutes the theoretical foundation and practical support for ecological risk management. Taking the Poyang Lake Basin as the study area, this paper conducts an ecological security early warning assessment using a CNN-LSTM model. By integrating the early warning results with the MSPA method and circuit theory, a basin-scale ecological security pattern was constructed, and targeted protection measures were proposed for the identified ecological restoration areas. The results indicate that: 1) The CNN-LSTM model demonstrates strong predictive capability and high accuracy in ecological security early warning assessment. The ecological security early warning in the study area exhibits a spatial pattern of high in the surrounding areas and low in the central region. 2) Ecological source area 26
Urban street walkability is key to healthy cities and sustainable development, as it is closely linked to residents’ daily activities. Existing research lacks a comprehensive quantitative framework integrating microscale visual perception and macroscale land use, making it challenging to accurately assess walkability on a large scale. This study develops a novel framework for evaluating walkability and spatial equity at the street-level. The framework incorporates multiple walkability dimensions including visual perception, network connectivity, function accessibility, and terrain suitability by integrating street view imagery, street network data, POI data, and terrain data. Using spatial analysis methods such as semantic segmentation, space syntax and topographical analysis, this study reveals the spatial pattern and regional differences in street walkability, and evaluates the spatial equity of walkability with location quotient and Gini coefficient. The results show that: 1) Street walkability of the Chongqing downtown area exhibits a core-periphery spatial pattern, decreasing gradually from the urban center outwards. High walkability is concentrated in central commercial and riverfront zones, while low walkability appears in peripheral and mountainous areas. 2) Streets in the central area are primarily function-topography dominated, highlighting the crucial contribution of service provision and natural terrain to walkability levels. 3) While street walkability presents significant regional differences, the differences in walkability among demographic groups are relatively small from a vertical perspective. Across subgroups defined by gender and age, the disparities remain small. Regression analysis further confirms that the analytical framework integrating visual perception and land use is effective for fine-scale walkability assessment in complex terrains. This empirical study on Chongqing, a city with distinct mountainous characteristics, provides differentiated and practical guidance for optimizing walking environments and fostering more equitable urban planning.
Research on the relationship between spatial structure and environment at the megaregional scale overlooks industrial pollution emissions as a key indicator and rarely examines the exit of pollution firms and scale effect of environmental governance. Taking 19 megaregions in China as the sample, which account for more than 85% of the nation’s GDP and 75% of population, this study examines the impact of regional spatial structure on regional industrial pollution emissions from 2003 to 2021. The megaregional spatial structure is measured by the Herfindahl-Hirschman Index (HHI) and with urban population data, while industrial pollution emission is indexed by industrial dust emissions. The control variables in the baseline model include megaregional economic development, population size, industrial structure, the level of openness, and government intervention. Four robustness checks were conducted using 3 approaches: replacing industrial dust with sulfur dioxide (SO2), substituting the spatial structure measurement with the coefficient of variation and the share of primate city population in the megaregion, and replacing population data with nighttime light data. The mechanism test uses data on the exit of polluting enterprises in megaregions. The heterogeneity analysis examines the differential effects of megaregional spatial structure under various socio-economic conditions by introducing the interaction terms. The study reveals that: 1) Megaregions with monocentric spatial structure exhibit a significant reduction effect on industrial dust emissions. The relationship demonstrates robustness after the robustness checks. 2) Mechanism tests indicate that monocentric megaregions tend to have larger population sizes in their primate cities, which promote the exit of polluting enterprises due to the stricter environmental regulation, as well as enhance the scale effect of environmental governance. 3) The reduction effect of monocentric spatial structure on industrial dust emissions is more pronounced in megaregions with weaker government intervention, lower levels of openness and economic development, and higher industrial agglomeration. For megaregions that possess these socioeconomic attributes, enhancing regional monocentricity represents a feasible spatial strategy for achieving the goal of industrial pollution reduction. These findings provide insights into the performance evaluation of megaregional spatial structure and offer implications for regional spatial planning.
This paper employs the entropy method and the Super-SBM model to construct an evaluation system framework for China’s synergistic governance efficiency of pollution reduction and carbon mitigation based on undesirable outputs, measures the co-governance efficiency of pollution reduction and carbon mitigation in 30 provinces (municipalities, districts) of China from 2011 to 2021, and uses the Dagum Gini coefficient and kernel density estimation to analyze its spatiotemporal dynamic evolution patterns. Additionally, the modified gravity model and social network analysis are utilized to explore the spatial correlation and spillover effects of co-governance efficiency. The research findings indicate that: 1) From 2011 to 2021, the efficiency of China’s synergistic governance of pollution reduction and carbon abatement increased steadily from 0.531 to 0.995. In terms of spatial differences: Western region > eastern region > central region, and eastern & central regions > central & western regions > eastern & western regions. 2) The overall efficiency of synergistic governance of pollution reduction and carbon mitigation experienced a trend of double peaks-single peak-double peaks, with the polarization phenomenon remaining prominent. The polarization trend in the eastern region has weakened, but the absolute differences in the western and central regions have increased, showing a clear polarization phenomenon. 3) There is a significant spatial proximity effect, particularly prominent in the Beijing-Tianjin-Hebei region, the Yangtze River Delta, and the Pearl River Delta. The overall network characteristics reveal a weakening spatial correlation in inter-regional environmental governance, with the network tending to become more loosely connected. Individual network characteristics indicate that the distances between the studied regions have decreased, and the spatial connectivity and synergistic effects among individuals in pollution control have increasingly strengthened, highlighting the central and bridging roles of the research units. 4) The spatial correlation of collaborative governance efficiency for pollution reduction and carbon emission reduction exhibits the characteristics of “plate agglomeration, functional differentiation, and centripetal transmission”. Regional heterogeneity and differences in industrial layout are the core factors shaping this pattern. In the future, it is necessary to optimize the network structure through targeted policies to enhance the overallity and effectiveness of collaborative governance.
The low-carbon city pilot (LCCP) policy has become an important driver of China’s low-carbon transition and green urban development. As a major pillar of the national economy and a key source of energy consumption and carbon emissions, the manufacturing sector is directly influenced by the LCCP policy. Meanwhile, increasingly active intercity investment has made manufacturing investment networks an important carrier for depicting regional industrial linkages and resource allocation patterns. Therefore, investigating the impact of the LCCP policy on manufacturing investment networks is of great significance for understanding industrial spatial restructuring under environmental regulation. Based on panel data for prefecture-level and above cities in China, this paper adopts the dual perspectives of outward and inward investment to examine the impact of the LCCP policy on manufacturing investment networks. Network analysis is employed to characterize the spatio-temporal evolution of manufacturing investment networks in pilot and non-pilot cities from 2013 to 2022, and a difference-in-differences (DID) model is further used to identify the policy effects. The results show that: 1) During the study period, the manufacturing investment network of pilot cities exhibited stronger investment linkages and a trend toward multi-core expansion, whereas the network of non-pilot cities was characterized by localized leaps, forming a hierarchical structure dominated by pilot cities and participated in by non-pilot cities. 2) The LCCP policy significantly promotes the expansion of manufacturing investment networks by simultaneously increasing outward and inward investment in pilot cities. The positive effects are concentrated in the central and western regions, while no significant effects are observed in the eastern region. Further analysis reveals that this regional heterogeneity is mainly reflected in the coexistence of outward relocation of pollution-intensive industries and inward inflows of green investment, indicating that the policy strengthens environmental constraints while facilitating the agglomeration of capital toward greener industries. 3) The investment-promoting effect of the LCCP policy is jointly constrained by urban agglomeration boundaries and spatial proximity. Specifically, the policy exerts weaker effects on cross-urban-agglomeration investment and long-distance investment, indicating that its investment-promoting effect is concentrated among geographically proximate cities.
The Yangtze River Delta is a strategic pilot zone for regional coordinated development in China, aiming to promote regional development by building a closer and more balanced networked spatial pattern. However, existing research mostly focuses on the structural characteristics of urban networks, with few studies addressing whether the effects generated by urban networks, which is network externalities, will increase as the network structure becomes increasingly perfect. This paper constructs the urban network of the Yangtze River Delta based on the data of enterprises equity investments among cities from 2000 to 2021, measures the network structure and network externalities over the years, and finds that the networked spatial pattern strategy has generally promoted regional development. In terms of structure, it is manifested as the network structure basically evolving as planned. In terms of effect, it is manifested that the vast majority of cities have promoted their own development by accessing the network. However, as the connections among cities in the Yangtze River Delta become increasingly close and balanced, network externalities do not continuously increase but rather first increase and then decrease. Only 59.4% of cities have network externalities that evolve in the same direction as the network hierarchy, while 36.8% of cities have network externalities that weaken as the network hierarchy improves. Finally, this paper offers 3 planning implications: The Yangtze River Delta region should continue to adhere to the strategy orientation of a networked spatial pattern, regional planning should respect the objective laws of the evolution of network externalities, and the focus should still be on expanding the local scale.
Taking Beijing as a case study, this study investigates how small towns in megacity suburbs develop through the interplay between hierarchical competitiveness and network connectivity. It aims to identify differentiated patterns of hierarchical-network synergy among suburban small towns and to reveal the driving mechanisms that shape their roles within both urban hierarchies and inter-town networks. This study develops a two-dimensional analytical framework that integrates hierarchical competitiveness and network connectivity. Based on corporate investment and financing linkage data, an inter-town investment network is constructed for 150 small towns in Beijing’s suburban areas. The results show that suburban small towns in Beijing exhibit both hierarchical differentiation and networked connectivity. Hierarchical competitiveness presents a top-heavy pyramid structure and is mainly concentrated in plain areas near the central city, whereas network connectivity shows a relatively more balanced structure and an east-west spatial differentiation. Four types of hierarchical-network synergy patterns are identified: dual-high synergy towns, including 44 towns with both strong hierarchical competitiveness and network connectivity; network-led towns, including 41 towns with relatively weak hierarchical status but strong network embeddedness; hierarchy-led towns, including only 2 towns with strong hierarchical competitiveness but limited network connectivity; and dual-low towns, including 63 towns with weak performance in both dimensions. The driving mechanisms vary across these types: dual-high towns are mainly supported by industrial development and public service provision; network-led towns are driven by economic strength and industrial development; hierarchy-led towns are associated with economic and public service factors but lack sufficient network activation; and dual-low towns are constrained primarily by weak economic foundations and transport-location disadvantages. This study demonstrates that the hierarchical-network framework provides a more nuanced interpretation of their differentiated regional roles, revealing how some towns consolidate development through dual advantages, while others gain new opportunities through network embeddedness despite limited hierarchical status. The findings contribute to a relational understanding of small-town development and offer empirical evidence for formulating differentiated policies, enhancing town-level vitality, and promoting more coordinated regional development in megacity suburbs.
Geopolitics has long been a classical and important topic in geographical studies. Since the 20th century, major shifts in the global geopolitical landscape have profoundly influenced world peace and development. The introduction of quantitative methods provides new perspectives, data resources, and analytical tools for understanding complex geopolitical phenomena. From an interdisciplinary perspective, this paper conducts a systematic review of quantitative geopolitical studies published between 1992 and 2025. Based on 3 core scientific questions of descriptive measurement, empirical quantification and simulation forecasting, this paper examines the evolution of data sources and methodological approaches, compares the main differences between international and Chinese research, and proposes future research directions. The review finds that international studies tend to focus on the geographical disruptions of capital logic and economic order, embedding geopolitical issues within broader frameworks of economic operation, spatial organization and risk transmission. Significant progress has been made in geopolitical risk measurement, the assessment of economic spillover effects, and geopolitical crisis forecasting. By contrast, Chinese studies are more strongly oriented toward national security and are deeply influenced by realist geopolitical thought. They place greater emphasis on the macro-level description of national strength, spatial patterns, and their interactions, and have developed particular advantages in measuring geopolitical environments and identifying spatial differentiation patterns. However, Chinese quantitative geopolitical research remains relatively weak in the construction of multilingual event databases, the analysis of dynamic mechanisms, and the prediction of geopolitical crises. In view of the strengths and limitations of existing research, this paper proposes 3 future development paths. First, natural language processing should be further employed to improve the real-time, autonomous, and open monitoring of geopolitical situations. Second, time-series analysis and causal inference methods should be strengthened to reveal the multi-actor and multi-scale dynamic mechanisms through which geopolitical events generate impacts. Third, nonlinear optimization and coupled-system models should be applied to building probabilistic early-warning and response simulation frameworks for geopolitical crises. This paper aims to refine the theoretical system of geopolitics through quantitative approaches and to provide methodological support for geography-based strategic studies.
Refugee issue is one of the major non-traditional security problems affecting regional security and global governance. The emergence of the refugee issue and the migration of refugees are significantly influenced by the geographical environment. Based on the refugee flow data of the Middle East and North Africa released by the United Nations High Commissioner for Refugees (UNHCR), the historical process and geographical routes of refugee migration are analyzed first. Then, from the two main subjects of the country of origin and the country of asylum, and integrating the two factors of geographical selection and geographical intervention, a gravity model of refugee migration is constructed from three research perspectives: time period analysis, spatial heterogeneity analysis, and spatio-temporal variable analysis. Furthermore, explore the driving mechanism of non-refugee migration in central northeast China. The research findings show that: 1) The geographical routes of refugee migration exhibit dynamic transformation characteristics. The geographical routes shift from the “neighboring country priority” route oriented towards “security protection” to the “extraterritorial migration” route oriented towards “development opportunities”. During this process, “gateway transit” is often experienced. 2) Refugee migration is jointly influenced by geographical selection factors and geographical intervention factors. At different stages of migration and among different regions they move into, the driving factors show significant differences and changes. 3) Path dependence and spatial clustering effects significantly promote the targeted migration of refugees. The migration of the host country and its neighboring countries in the previous stage will all facilitate the migration of refugees in the next round. Clarifying the geographical selection and geographical intervention of non-refugee migration in central northeast China is of great theoretical and practical significance for understanding the migration patterns of refugees, a special type of international migration, and exploring the influence of regional geographical environment and policies on refugee migration.
Based on enterprise data from 286 prefecture-level cities in China, a spatial synergy effect measurement model for the logistics and manufacturing industries from a sprawl perspective is developed along 3 dimensions: intensity, direction, and form. Hotspot analysis and time series clustering techniques are employed to identify the characteristics of spatial sprawl for these 2 industries from 2008 to 2022. Additionally, the spatial synergy effects between the logistics and manufacturing industries, as well as their evolutionary patterns, are analyzed. The results reveal several key findings: 1) Cities with sprawling logistics enterprises account for 67.48%-72.03% of Chinese cities, while those with sprawling manufacturing enterprises account for 73.78%-75.87%, centrifugal diffusion is the dominant type of spatial sprawl. 2) From the perspective of sprawl, the spatial coordination of the 2 industries exhibits pronounced heterogeneity and evident stage-by-stage shifts. High-level agglomerations have shifted from the eastern region such as Jiangsu and Zhejiang to the central regions such as Hubei and Henan, while low-level agglomerations have shifted from localized areas in Southwestern and Northwestern China toward North China. Moreover, the spatial pattern has moved from an initial “west-weak/east-strong” configuration toward an east-west balance, while the north-south gradient has changed from “strong in the middle, and weak at both ends” to “strong in the south, and weak in the north”. 3) The spatial synergy evolution patterns of the 2 industries can be categorized into 3 distinct types: coordination-disorder-coordination, disorder-coordination-disorder and disorder-coordination, involving 96, 61, and 129 cities respectively. Their spatial migration path follows a three-stage trajectory from the west to the southeast and then to the northeast, characterized by an initially weak overall coordination pattern with weakly coordinated areas concentrated in central-western China, subsequent improvement in central-western China during the middle stage, and enhanced coordination nationwide in the later stage, with the principal spatial disparity shifting from an east-west pattern to a north-south pattern.
The wine industry, as a representative sector combining both cultural attributes and consumption-oriented characteristics, serves as a crucial vehicle for promoting high-quality regional economic development and meeting the growing needs for a better life. However, in recent years, China’s wine industry has fallen into a dilemma of simultaneous declines in both output and consumption. Existing studies have predominantly focused on the supply side, while insufficient attention has been paid to the spatial mechanisms of demand. This paper argues that inadequate market demand constitutes the core constraint underlying the current downturn, primarily due to the absence of the “home market effect” and the “price index effect,” which together result in weak consumption performance and limited market expansion. To address this issue, this study builds upon the theoretical framework of New Economic Geography and integrates an agent-based modeling (ABM) approach to dynamically simulate the evolution of China’s wine industry under multiple counterfactual scenarios. By incorporating both supply-side and demand-side interactions into a unified analytical framework, the paper aims to uncover the endogenous mechanisms shaping industrial spatial dynamics and market outcomes, as well as their policy implications under different development paths. The results yield 3 main findings. First, the relaxation of cost constraints can fundamentally reshape spatial equilibrium. A reduction in production costs enhances the competitiveness of domestic wine by amplifying both the price index effect and the home market effect, thereby expanding market size and improving the relative position of domestic producers. Second, spatial product differentiation strategies play a critical role in fostering competitive advantages. By increasing product heterogeneity, domestic wine producers can attract more consumers, which in turn leads to a rise in the number of firms and an expansion of market share. Third, the coordinated interaction between demand and supply across space is essential for breaking the current impasse. When domestic wine gains a cost advantage, the expansion of demand significantly strengthens the home market effect, effectively reversing the import-dominated market structure. Meanwhile, the price index effect facilitates a mutually beneficial outcome for both producers and consumers and promotes a more balanced spatial distribution of production and consumption. These findings suggest that the development of the wine industry in China should not rely solely on supply-side improvements, but must also place greater emphasis on demand-side cultivation. In particular, fostering a wine-oriented lifestyle and enhancing consumer engagement are critical to unlocking market potential and sustaining long-term growth. By integrating New Economic Geography with computational experimental methods, this study constructs a comprehensive analytical framework that jointly considers supply and demand dynamics. It not only contributes to the theoretical understanding of spatial economic processes in cultural consumption industries, but also provides methodological insights and policy implications for promoting the high-quality development of regionally distinctive industries.
The three provinces of northeastern China are typical representatives of the general trend of population change in China. Studying how to respond to provincial population shrinkage and enhance urban economic resilience in these provinces holds general and forward-looking value for promoting high-quality regional economic development. Taking 34 cities in the three provinces of northeast China from 2005 to 2023 as the research object, this paper employs the coupling coordination degree model and the panel vector autoregression model to analyze the mutual feedback effects between population shrinkage at the provincial and city levels and individual urban economic resilience. The results show that: 1) During the study period, the mutual promotion between population and urban economic resilience in the three northeastern provinces was limited, with most cities being in a state of circular imbalance. 2) In terms of spatial evolution, the high-value areas of coupling coordination between population and urban economic resilience in the three northeastern provinces have gradually evolved into a cluster-belt spatial pattern with Harbin-Changchun-Shenyang-Dalian as the key nodes, while the peripheral cities of these key nodes have improved slowly, falling into a locked state. 3) A benign interaction between urban economic resilience and populations at both the city and provincial levels has yet to be established in the three northeastern provinces. Accompanying their respective sluggish development, these systems have become trapped in a cyclical path of mutual inhibition, overall exhibiting the characteristic that populations at both the provincial and city levels constitute an inhibitory mutual feedback with individual urban economic resilience.
County-level units are the basic units for regulating population flow in the process of urban-rural integrated development. Promoting county-level population flow is an important entry point for supporting the full revitalization of northeast China with high-quality population development. Based on the data of the 5th, 6th and 7th National Population Census, this article reveals the characteristics of county-level population flow from the perspective of spatial-temporal evolution, and explores the key driving factors of county-level population flow based on the Geographically Weighted Regression (GWR) model. The results show that: 1) County-level population flow has become more active in northeast China, with a marked increase in population flow rates. The ranking of floating population has changed significantly, and the population attraction centers in the counties are undergoing adjustment and transformation. The adjustment of county-level floating population rank-size distribution is mainly caused by the rank adjustment of intra-provincial population flow, while the rank-size distributions of inter-provincial population flow remain relatively stable. The floating population in northeast China is relatively evenly distributed across counties, with no dominant floating population concentration counties emerging. The growth rate of the floating population is lower than that of the permanent population, and counties with a larger permanent resident population exhibit weaker external attractiveness and external connectivity. 2) Population flow rates are relatively high in coastal and border regions in northeast China, border counties are hotspots of county-level population flow, with intra-provincial floating population concentrated in border counties and inter-provincial floating population concentrated in the central and southern regions of Liaoning. 3) County-level population flow in northeast China is the result of the interplay between economic, social, environmental, and location factors. Economic factors are the core drivers of county-level population flow in the northeast China. Social factors, environmental and location factors have continuing impacts on population flow. Resource dependence exerts a more pronounced restraining effect on intra-provincial population flow, while resource depletion intensifies population outflow from counties. Resource dependence inhibits population inflow in resource-based counties, and the phenomenon of the resource curse exists in resource-based counties.
Amid China’s rapid urbanization, migrants’ “spatial dislocation” dilemma highlights the disconnection between physical relocation and psychological belonging. Existing studies predominantly explain migrant well-being through structural perspectives such as social capital and policy systems, while neglecting dynamic interactions with natural environments. This study introduces biophilic theory to propose biophilic practices encompassing materiality (nature contact), emotionality (nature experience/connection), and agency (nature participation). Focusing on Nanjing’s urban core, we investigate how biophilic practices influence migrant well-being through the tripartite mediation pathway of emotional regulation, symbolic reproduction, and social integration. Empirical analysis uses questionnaire data from 49 communities in Nanjing’s main urban districts (October 2023—January 2024). Multiple regression models examine differential effects of biophilic practices and their components (nature contact, experience, connection, participation) on hedonic and eudaimonic well-being, with causal stepwise regression and Bootstrap methods testing mediation by nostalgia, place attachment, and social interaction. Key findings show: 1) Biophilic practices significantly enhance both hedonic and eudaimonic well-being; 2) Regarding dimensions, emotional aspects (nature experience/connection) contribute most to well-being and form its core pathway. Material aspects (nature contact) mainly promote short-term emotional improvement, significantly affecting only hedonic well-being. Agentic aspects (nature participation) primarily drive self-growth, promoting only eudaimonic well-being; 3) Triadic mediation effects exist: nostalgia mediates the positive impacts of nature experience and connection on both hedonic and eudaimonic well-being; place attachment mediates the effects of nature contact and connection on hedonic well-being; social interaction demonstrates the strongest mediation, operating across nature contact, experience, and connection dimensions for both well-being types, confirming social integration as the core mechanism generating migrant well-being. This research deepens understanding of migrant well-being mechanisms through emotion-nature perspectives, expands the conceptual scope of biophilic practices in nature-wellbeing studies, and provides an operational measurement framework for interdisciplinary research. Findings offer insights for urban natural space planning and migrant well-being policies.
As the world’s only“Double-Olympics City”, the spatial allocation and sustainable use of its sports tourism resources are core pillars supporting the high-quality development of the local sports industry and meeting residents’ health needs. Taking 16 administrative districts of Beijing as research units, this study draws on point-of-interest (POI) data of sports tourism resources and sports event data, and comprehensively adopts multiple spatial statistical methods including average nearest neighbor analysis, kernel density estimation, bivariate spatial autocorrelation, and multi-scale buffer analysis to systematically explore the spatial coupling characteristics, mismatch mechanisms and sustainable development paths of tangible and intangible sports tourism resources under the dual-Olympic effect. The main findings are as follows: 1) Sports tourism resources present a highly significant spatial agglomeration pattern, forming a core-periphery structure of “one core (Olympic Central Area), one belt (Chaoyang-Haidian-Fengtai), and multiple poles in outer suburbs”; there is a remarkable gap in resource distribution between the core area and outer suburbs, with a prominent spatial Matthew effect. 2) Resource types show clear differentiation: man-made facility resources and cultural event resources are highly concentrated in the core area; natural landform-dependent resources are relatively evenly distributed under the constraints of geographical background conditions; ice and snow resources present a dual-core mode of “ice facilities in urban areas and snow facilities in suburbs”. 3) The spatial coupling of tangible and intangible sports tourism resources is imbalanced; sports events rely heavily on core Olympic heritage venues, resulting in a polarized pattern where core venues are overloaded while peripheral facilities remain idle, and there is no significant spatial linkage effect between the 2 types of resources. 4) There is a spatial mismatch between resource supply and demand: insufficient sports facilities near residents’ living areas coexists with over-utilized facilities in the core area, and inadequate transportation and supporting services in outer suburbs further intensify this imbalance. Accordingly, this paper proposes sustainable utilization paths from four dimensions of spatial optimization, heritage revitalization, industrial integration and regional coordination, so as to provide a scientific basis for optimizing the spatial layout of Beijing’s sports tourism resources and promoting the value transformation of Olympic heritage.
The climate environment in southwest China (primarily including Yunnan, Guizhou, Sichuan, and Chongqing) is complex, and frequent droughts in recent years have significantly impacted the sustainable socioeconomic development of the region. Current research conclusions regarding the spatiotemporal characteristics of droughts in southwest China remain divergent or even contradictory, and the relationship between drought characteristics and large-scale climatic processes in this region is still insufficiently clear. To understand the drought characteristics in this region and provide a scientific basis for drought prediction and prevention, this study, based on meteorological data from 382 stations in southwest China (Yunnan, Sichuan, Guizhou, and Chongqing), evaluates the applicability of 4 drought indices—the Meteorological Drought Composite Index (MCI), Standardized Precipitation Evapotranspiration Index (SPEI), Standardized Precipitation Index (SPI), and Relative Moisture Index (MI)—in the study area. It reveals the spatiotemporal evolution characteristics of droughts and their relationship with large-scale climatic processes. The results show that: 1) All 4 indices can effectively reflect drought information. MCI demonstrates the strongest representation of comprehensive drought signals (with a loading of 0.996 on the first principal component), while SPI shows the highest correlation with drought-affected crop areas (Pearson correlation coefficient of −0.729). 2) Spatially, high-frequency drought areas identified by MCI and MI are concentrated in the western Sichuan Plateau and the transition zone from the Sichuan Basin to the Qinghai-Xizang Plateau. High-risk areas identified by SPEI are distributed in a patchy pattern across high-altitude cold regions and dry-hot valleys. High-risk areas identified by SPI are mainly located in the eastern Sichuan Basin and the Yunnan-Guizhou border region. Temporally, the interannual fluctuations of the drought station ratio are within a range of ±10, and the consistency rate of dry/wet condition judgments among the indices is 62.86%. Mutation test results indicate that MCI, SPI, and MI experienced a mutation in 1990, while SPEI experienced a mutation in 2004. Wavelet analysis results show that all indices exhibit periodicities of 5 years and 10-15 years, but no significant dominant period is identified. 3) Drought indices show negative correlations with water vapor flux divergence over a large area (station proportion >87%), with the most significant negative correlations north of a line roughly from southern Sichuan to western Guizhou, and weaker correlations to the south. The Arctic Oscillation (AO) is identified as the primary climatic oscillation signal influencing drought in the study area, while the influences of the Multivariate ENSO Index (MEI), Western Pacific Index (WPI), and Pacific-North American Index (PNA) on the interannual variation of drought in the study area are relatively weak.
Understanding the trade-off/synergy relationships among watershed ecosystem services and their driving mechanisms is crucial for enhancing human well-being and achieving regional sustainable development. Water yield and soil conservation play pivotal roles in maintaining ecosystem stability. Accelerated urbanization has significantly altered land-use patterns in the Pearl River Basin, profoundly affecting water yield and soil conservation. Taking the Pearl River Basin as the study area, this research quantified water yield and soil conservation using the InVEST model, examined the trade-off/synergy relationships between these services through Pearson correlation analysis, and identified the main driving factors of the spatial heterogeneity in trade-off intensity using the optimal parameters-based geographical detector (OPGD). The main findings are as follows: 1) From 2000 to 2020, the multi-year average water yield and soil conservation in the basin were 1076.73 mm and 182.23 t/hm2, respectively, both showing an initial increase followed by a decline. 2) The water yield-soil conservation relationship in the Pearl River Basin was dominated by synergistic effects (39.58%), with forestland accounting for the highest proportion (78.74%) in strong synergy areas, while water bodies accounted for the largest share (88.67%) in strong trade-off regions. 3) Single-factor detection revealed that precipitation (q=0.592) and elevation (q=0.155) were the primary driving factors of the spatial heterogeneity in trade-off intensity; interaction detection further indicated that the interaction between precipitation and the Normalized Difference Vegetation Index (NDVI) exhibited the strongest explanatory power (q=0.657). These findings provide decision-making support for optimizing ecosystem service benefits and promoting integrated soil erosion management in the Pearl River Basin.
Desert margins are highly sensitive to environmental changes and human activities. This study focuses on an isolated dune field on the southern margin of the Hobq Desert, intersected by ephemeral drainages including the Mubulag, Baerdong, and Burgastai Khundi. Using high resolution satellite images acquired in 2007, 2009, 2013, 2017, and 2021, alongside multi-temporal 2017 seasonal data, this study quantitatively investigates the spatiotemporal variations in dune pattern parameters across six distinct zones using 55 quadrats based on a dune pattern analysis approach. Fractional vegetation cover (FVC) dynamics were further extracted via Google Earth Engine (GEE) to evaluate landscape changes and drive mechanism processes during the 14 year period. The results indicate significant landscape transformations and a persistent trend toward desertification reversal. The regional average FVC rose from 0.42 in 2007 to 0.47 in 2021, representing a 12% total increase, with high value clusters expanding along rivers, highways, and southeastern zones. This vegetation recovery, coupled with massive ecological engineering, led to a substantial reduction in barchan dune (chains) and an expansion of parabolic dunes and nebkhas. Notably, artificial shrublands expanded 5.8 fold from 2007 to 2013. By 2021, the continuous barchan chains in the eastern sector had completely transitioned into fixed or semi fixed parabolic dunes. The crestline length and dune height show a decreasing trend, whereas dune spacing and dune defect density exhibit an increasing trend. Dune orientation shifted counterclockwise from NE-SW to NNE-SSW, which is consistent with the change in resultant drift direction (from 171.73°to 149.48°), confirming the dominant control of wind regime dynamics on dune orientation. Climatic and anthropogenic forces collaboratively drove these morphodynamic shifts. A distinct meteorological shift occurred after 2011: average annual precipitation increased from 256.41 mm (2000—2011) to 341.83 mm (2012—2021), while annual wind speed dropped from 4.46 m/s to 4.28 m/s, causing the sand driving wind to rotate from WNW to W. This wind reduction and sand source immobilization by vegetation reduced the dune migration rate from 6.74 m/a to 2.74 m/a. On a seasonal scale in 2017, crestline length fluctuated from a minimum in April to a maximum in June, and orientation temporarily shifted toward NNE-SSW and N-S in summer before returning to NE-SW in winter. Crucially, local environmental barriers disrupted the downwind self organization of the dune field, exacerbating spatial heterogeneity. The Mubulag Khundi bisected the terrain, acting as a sand source supplier for its downwind impact zone. Meanwhile, the Baerdong Khundi exhibited intricate aeolian-fluvial interactions. In conclusion, dune pattern evolution on the southern margin of the Hobq Desert is a coupled response to climatic wet-warming and intensive ecological restoration, providing critical parameters for modeling dryland landscape evolution and optimizing desertification control policies.
Identifying key ecological restoration areas that can effectively enhance ecological network connectivity remains a major challenge in regional ecological planning and restoration practice. However, the lack of comparative and quantitative analysis of restoration strategies for key areas, along with insufficient justification for the grading, classification, and sequencing, has restricted the accuracy and effectiveness of ecological restoration. Taking the northern ecological barrier area of Guangzhou, as a case study, this study developed an integrated framework for identifying key ecological restoration areas from the perspective of basin ecological network optimization. Ecological sources were comprehensively identified by coupling the synergies of dominant ecosystem services and landscape connectivity. Circuit theory was applied to extract ecological corridors, ecological pinch points, and ecological barrier points. Then, three scenarios were constructed to evaluate the effects of increasing ecological sources and ecological corridors and to compare the impacts of ecological pinch point degradation and ecological barrier point removal on network connectivity. The results identified 67 core ecological sources with a total area of 1 522.51 km2, which were mainly distributed at the junctions of administrative boundaries among different districts. A total of 125 ecological corridors were extracted, including 50 important ecological corridors. In addition, 32 ecological pinch points and 48 ecological barrier points were identified, including 18 major ecological barrier points and 30 minor ecological barrier points. Scenario simulations showed that the addition of seven potential ecological sources and 18 ecological corridors significantly increased all network connectivity metrics. Moreover, 21.08 km2 of moderately and severely degraded vegetation were identified within ecological sources and require urgent ecological restoration. Comparisons among different restoration scenarios revealed that key ecological pinch points and the major ecological barrier points overlapping with these locations had the greatest influence on network connectivity. Therefore, these areas should be prioritized in ecological restoration practices. Subsequently, restoration and management efforts should be gradually extended to ecological pinch points characterized by protection enhancement and maintenance management in order to further improve the integrity of the ecological network.This study provides an effective framework for identifying key ecological restoration areas by integrating ecosystem service function synergies, landscape connectivity, and scenario simulation. The findings provide a scientific basis for identifying restoration priorities and optimizing ecological restoration planning and contribute to the improvement of ecological network connectivity.
