This study constructs a “attribute-relationship” dataset of Chinese semiconductor enterprises and, by drawing on location theory, evolutionary economic geography, and relational economic geography, develops an interpretive framework for the relationships among the central government, local governments, and enterprises. Social network analysis is employed to investigate the evolution of spatial characteristics and the driving mechanisms of China's semiconductor industry. The findings reveal that: (1) China's semiconductor industry is primarily concentrated in metropolitan regions centered around Beijing, the Yangtze River Delta, and the Pearl River Delta. Different regions exhibit relatively distinct functional roles within the semiconductor industry chain. Cities such as Beijing, Shanghai, and Shenzhen serve as “hubs” for the agglomeration and diffusion of semiconductor activities, while their respective regions are deeply embedded in the investment and financing “networks” of the industry. (2) Under the “actor-relationship” interpretive framework, the interactions among the central government, local governments, and semiconductor enterprises, the historical foundations of semiconductor development in specific regions, and the supply-demand dynamics both within and outside the semiconductor industry chain are identified as key factors shaping the spatial structure of China's semiconductor industry. (3) The inter-actor relationships further influence the geographical layout of the semiconductor industry by integrating and intervening in the historical foundations of regional semiconductor development and the market resources related to supply and demand in the industry. Moreover, these relationships manifest in different forms and interaction mechanisms across different historical periods. This research aims to combine spatial analysis of enterprise data with qualitative insights into the semiconductor industry's development, in order to establish a more robust theoretical framework and uncover the specific mechanisms behind the formation of China's semiconductor industry's geographical patterns. The study seeks to provide further insights into the spatial logic of strategic emerging industries in China from an economic geography perspective.
Innovative factors tend to exhibit pronounced geographical clustering. Amidst growing uncertainties in international economic and technological competition and the accelerated transformation of China's domestic economic model, a crucial challenge is to effectively promote the diffusion and transfer of high-quality scientific achievements, thereby achieving high-level technological self-reliance. This paper examines the spatio-temporal evolution of technological diffusion within strategic emerging industries in the Yangtze River Delta. Building on this foundation, and grounded in the Chinese government's strong commitment to innovation-driven development, the study empirically investigates the impact of the G60 Science and Technology Innovation Corridor on regional technology diffusion and its underlying mechanisms. The results show that: (1) The breadth and depth of technology diffusion within the study area continue to expand, following an evolutionary shift from single-centre to multi-centre interactions, with cities along the G60 Innovation Corridor occupying a dominant position. (2) The development of the G60 Innovation Corridor significantly enhances the technological diffusion capacity of cities along its route, particularly in developed cities such as Shanghai and Hangzhou. (3) Mechanism analysis indicates that the corridor primarily promotes regional technological diffusion through three channels: strengthening strategic government guidance, enhancing economic agglomeration (high-tech enterprises and talent), and optimizing the innovation environment (transport infrastructure, financial supply, and openness to external markets). (4) Further analysis reveals that while the corridor facilitates the diffusion of applied and proprietary technologies among enterprises, it does not appear to significantly improve technology transfer from universities and research institutions to enterprises. These findings not only deepen our understanding of how cross-regional collaborative innovation policies, exemplified by the G60 Innovation Corridor, contribute to the high-quality diffusion of scientific and technological achievements, but also provide valuable policy implications for future design.
Cross-border intellectual property deployment has become a key strategic approach for major countries to capture international markets and participate in global competition. This paper constructs a theoretical framework for the locational choice of cross-border IP deployment, integrating methods such as GIS spatial analysis and econometric analysis. Using U.S. digital technology patents as a case study, it systematically depicts the temporal evolution, locational selection patterns, deployment pathways, and influencing factors of cross-border IP deployment. The findings are as follows: (1) The scale of cross-border IP deployment in U.S. digital technologies has shown a fluctuating upward trend. (2) The geographical scope of this deployment has undergone a dynamic process of “contraction-expansion-contraction”. Its key deployment locations have shifted eastward, forming a dual-core spatial structure centered on East Asia and Europe. In several key fields, there has been a trend of concentration toward leading countries. (3) The preferred deployment pathway involves initial filing in the home market, followed by global deployment through mechanisms such as the PCT. (4) Strategic motivations such as market-oriented strategies and home country priorities are the driving forces behind the U.S. cross-border IP deployment in digital technologies. Host country environmental factors, including market size, competitive pressure, and the level of IP protection, have significant effects on attracting U.S. IP deployment. Multidimensional proximity also plays a key role: geographic and linguistic proximity reduce the cost and barriers to cross-border deployment, while economic proximity, representing similar market demand, reflects the necessity of reinforcing IP deployment.
The new round of scientific and technological revolution is accelerating the disappearance of knowledge barriers. Knowledge, technology, and thinking from different fields mutually converge in the strategic emerging industry, thus continuously promoting the generation of radical technological innovation. Taking the biomedical industry as an example, we categorize technological convergence into two related types: similar and complementary, as well as two development dimensions: horizontal and vertical. Based on the patent data of 287 cities at prefecture level and above in China from 2004 to 2018, we portray the spatio-temporal differentiation characteristics of technological convergence, and examine the mechanism of technology convergence on radical technological innovation. The results show that: (1) The level of technological convergence of the biomedical industry in Chinese cities shows an overall upward trend, with obvious regional differences. Cities with high levels of technological convergence are mainly located in the Yangtze River Delta, the Bohai Rim, and the Pearl River Delta. (2) The 19 key cities of the biomedical industry are divided into four tiers of convergence development. Beijing, Shanghai, and Guangzhou show strong convergence strength, while the remaining cities still have different development shortcomings. (3) The innovation effect of technological convergence varies according to convergence types and convergence dimensions. Horizontal and vertical convergence among similar technologies as well as vertical convergence among complementary technologies promote the radical innovation level of the biomedical industry in different degrees, while the effect of horizontal convergence among complementary technologies is not significant. This study provides a more detailed scientific cognition of the spatio-temporal evolution of technological convergence and its innovation effect, which can provide scientific references for the formulation of innovative development policies for strategic emerging industries.
As a core pillar of new energy development, the new energy vehicle industry has become an important part of the national strategies around the world. The article adopts social network analysis, trade contribution ratio, interdependence index and other methods to comprehensively analyze the dynamic evolution of the global new energy vehicle trade network and the evolution of China's position based on the relevant data from 2017 to 2023. The results show that: (1) The global trade network of new energy vehicles has shown the trend of “group-type” and “decentralization”. China's position in the global new energy vehicle trade network has improved significantly, with all its trade network indicators performing strongly and ranking among the top five internationally. (2) In terms of trade contribution, China's role in the global new energy vehicle market is expanding. However, its production capacity remains oriented primarily toward the domestic market. In 2022, China entered the global top five in terms of trade contribution rate for the first time, yet still lagged significantly behind traditional automotive leaders like Germany. (3) In terms of trade relations, China's role in the new energy vehicle sector has evolved from a position of relative disadvantage to one of advantage, with its dominance continuously growing. Based on the conclusions, the following policy recommendations are proposed: first, China should should closely monitor the international NEV market dynamics and make timely, flexible adjustments to its capacity planning and market strategies. Second, China should place strategic emphasis on achieving sci-tech self-reliance and self-strengthening at higher levels. Sustained increases in R&D investment are crucial to securing a sustainable competitive edge for its new energy vehicle industry on the global stage. Third, China should steadily expand institutional opening up, strengthen international exchanges and cooperation, and ensure effective integration with international economic and trade policies.
The great power game and global changes have caused a huge impact on China's industrial chain, with a sharp increase in insecurity factors. China attaches great importance to industrial development and emphasizes the need to enhance the modernization level of industrial chain. At the same time, digital economy is booming, not only demonstrating the power to reshape industrial competitive advantages, but also potentially changing the laws of industrial development. It is of great significance to explore how digital economy affects industrial chain modernization and its impact mechanism. This paper constructs a theoretical analysis framework of digital economy's impact on industrial chain modernization from the dual perspective of supply and demand. Based on the sample data of 238 cities at prefecture level and above in China from 2010 to 2022, this paper explores how digital economy affects industrial chain modernization and its mechanism by using multidimensional fixed effect model, and parallel mediation effect model. The results are as follows: (1) The digital economy significantly facilitates industrial chain modernization. This finding holds after a series of rigorous tests, including using instrumental variables constructed by the lagged explanatory variable and shift-share methods to address endogeneity, and conducting robustness checks by altering variable measurements, estimation methods, sample scope (e.g., excluding municipalities), and data intervals. (2) The test of mediation mechanism shows that the digital economy mainly affects industrial chain modernization through supply and demand channels. Among them, the supply side mainly plays a driving role through human capital and technological innovation. The demand side mainly plays a pulling role through consumer demand. (3) The test of moderation mechanism shows that the impact of digital economy on industrial chain modernization is moderated by data protection scenarios. Among them, data openness, data rule of law construction and data security guarantee all play a positive moderation role. (4) Heterogeneity test shows that digital economy has differential impacts on industrial chain modernization in cities of different regions, sizes, and urban agglomerations. The impact of the digital economy is more pronounced in regions with a more developed economy, a larger city scale, and a stronger urban agglomeration. This study thereby enriches the existing theoretical framework and offers practical insights for policymakers in selecting pathways to achieve industrial chain modernization.
The improvement and organization of county-level size distribution play crucial roles in rural revitalization and urban-rural integration during the later stages of urbanization in China. However, progress in related studies has been hindered by data limitations. Based on the impervious surface data in 2017, this paper analyzed the characteristics and influencing factors of the county-level size distribution of urban-rural settlements in China. The results reveal that: (1) The county-level size distribution of urban-rural settlements generally tends to show characteristics of both primacy and rank-size distribution. While primacy of the county seat is prevalent in most counties, the adjusted R2 of the rank-size rule is generally high and the average Zipf index is slightly bigger than 1, supporting the evidence of rank-size distribution. (2) Physical geographical elements such as elevation and gradient are prerequisites for the growth of urban-rural settlements, shaping the characteristics of urban-rural settlement systems such as the county seat dominance and plains dominance. (3) The closer the county seat location is to the geographic center of the county, the more conducive to the formation of its dominant position, while the more dispersed the distribution of town and village settlements is more conducive to the formation of a balanced size distribution. (4) In counties with higher levels of economic development, the primacy of the county seat diminishes. Instead of a balanced distribution of resources across all town and village settlements, resources tend to cluster in key towns and villages outside the county seat. This pattern fosters the formation of a multi-centered urban-rural settlement system.
Integrating methods such as the entropy method, centroid shift, standard deviation ellipse, Dagum Gini coefficient, spatial autocorrelation, and spatial econometrics, this study examines the spatiotemporal evolution of urban resilience in the Guangdong-Hong Kong-Macao Greater Bay Area from 1997 to 2022 and explores its influencing factors based on the TOE framework. The results show that: (1) Over the past 26 years, the urban resilience of the study area has significantly improved, with significant resilience fluctuations observed in cities such as Macao, Guangzhou, and Dongguan. From a dimensional perspective, infrastructure resilience and economic resilience have grown rapidly, with an average increase of 4.19 times and 3.28 times, respectively. (2) From 2007 to 2012, the spatial resilience of the region shifted from a “single core” (Hong Kong-Macao) to a “dual core” (Hong Kong-Macao-Shenzhen-Guangzhou) pattern, which then strengthened in subsequent years. The center of regional resilience is shifting inland. Concurrently, its spatial distribution exhibits an evolutionary pattern of “agglomeration, diffusion, and re-agglomeration”. The resilience gap between the nine cities in the Pearl River Delta and Hong Kong-Macao region has narrowed by 55.74%, and after 2003, intra-group differences in the nine cities in the Pearl River Delta have become the main source of resilience differences. (3) From the perspective of influencing factors, the construction of new digital infrastructure has a significant positive effect on economic, social, and infrastructure resilience, but has a negative impact on ecological resilience. Scientific investment promotes the improvement of resilience in various dimensions and has a positive spillover effect on the comprehensive resilience of surrounding cities. Financial support is beneficial for economic and social resilience, but it weakens infrastructure resilience and has negative spillover effects on the resilience of surrounding cities. Organizational management contributes to the improvement of economic, infrastructure, and ecological resilience, but fails to significantly enhance social resilience. Foreign investment will have a positive spatial spillover effect on the comprehensive resilience of surrounding cities. Entrepreneurial activity helps enhance urban resilience. This study analyzes the evolutionary characteristics of resilience in the Greater Bay Area from a spatiotemporal perspective and examines the influencing factors, aiming to provide reference for the construction of a “livable, resilient, and smart” world-class bay area and urban agglomeration in this region.
Exploring the economy-society-environment interplay in less developed regions from an environmental justice perspective advances the practical application of environmental-economic geography. This approach is crucial for effectively responding to sustainable development challenges. By introducing the theory of environmental justice, this paper first proposes a heuristic analytical framework and then empirically examines the spatio-temporal relationship between the distribution of polluting enterprises and the sociodemographic characteristics, using the Lanzhou-Xining urban agglomeration as a case study. The results show that: (1) From 2000 to 2020, the study area witnessed a steady increase in the number of polluting enterprises, accompanied by a growing spatial imbalance in their distribution. Driven by a “core-edge” spatial growth model centered on the provincial capitals of Lanzhou and Xining, the geographical spatial pattern of “one belt, two circles and multiple clusters” has gradually emerged. (2) The urban agglomeration is at a development stage characterized by a low level but high rate of urbanisation, while simultaneously facing the increasingly serious social issue of a dual demographic superposition of aging and youthification. As the core components of the urban agglomeration, the Lanzhou-Baiyin and Xining-Haidong metropolitan areas demonstrate a clear trend of growing spatial differentiation between their internal and external zones. (3) Spatially and temporally, the distribution of polluting enterprises exhibited distinct correlations with various sociodemographic characteristics: A consistently strengthening positive correlation with the migrant population share, a positive but steadily weakening one with the elderly population share, a positive yet fluctuating one with the rural population share, and finally, a shift from a negative to a positive correlation with the child population share. (4) Key factors influencing the spatio-temporal differentiation of sociodemographic characteristics near polluting enterprises in less developed regions include housing marketization, social stratification, urban-rural spatial reconfiguration, and environmental regulatory adjustments. The underlying driving mechanism involves the redistribution of spatial interests driven by external capital seeking profit maximization, coupled with governmental neglect of the environmental rights of disadvantaged groups and lack of governance. To achieve high-quality leapfrog development, we recommend a three-pronged approach: deploying technological innovation for pollution control, implementing scientific site selection to ensure distributional justice, and advocating for institutional fairness to guarantee procedural equity.
Amidst the rapid evolution of socioeconomic structures and functional spaces in rural China, the enduring relevance of Central Place Theory in explaining the hierarchy and layout of human settlements now faces new challenges. This paper takes Taihe County in Anhui Province as a case study. It employs LBS (Location Based Services) data to identify the travel connections of residents on weekdays, weekends, and holidays, thereby characterizing and measuring the town-village system through the lenses of employment-residence patterns, facility layout, and kinship relationships. On this basis, integrating the proportion of primary town connections with complex network algorithms such as Louvain community detection, the paper examines the organizational characteristics of the town-village spatial network from three dimensions: nodes, network communities, and spatial hierarchical structures, using Taihe County in China's central plains as a representative case. Our findings indicate that the spatial organization of towns and villages in the central plains has not fully transcended the framework of the traditional Central Place Theory, which is grounded in administrative levels. With the shift in dominant flows from employment-residence to facility layout and then to kinship ties, the network evolves into a flatter structure. This evolution has formed three town-village network modes: “county seat-township-village”“county seat-township-central village-general village”, and “adjacent network”, providing practical insights for the scientific planning of the town-village system in central China.
Rehabilitation services are crucial for the development and social participation of people with disabilities, and the spatial layout of facilities directly affects service equity. However, existing studies lack refined methods to measure the spatial matching level of rehabilitation service supply and demand for different types of disabilities, making it difficult to reveal the mechanisms through which such matching affects the functional recovery of people with disabilities. This study employs the two-step floating catchment area method, incorporating travel probabilities, modes, caregiver costs, transportation expenses, and accessibility needs to construct a monetized travel cost accessibility model to measure the spatial matching level of rehabilitation service supply and demand. Using the central urban area of Tianjin as a case study and data from 129,833 certified people with disabilities in 2022, the study applies ordered logistic regression and propensity score matching to examine the impact of the spatial matching of rehabilitation service supply and demand on the functional recovery of people with visual, hearing, physical, mental, intellectual, and speech disabilities. It also explores the moderating effects of community environmental characteristics. The results indicate that: （1）The spatial distribution of people with disabilities follows a “high-in-the-core, low-in-the-periphery” pattern, driven mainly by population density, the share of elderly residents, and regional socioeconomic development. （2）Supply-demand matching of rehabilitation facilities is concentric and decreasing for visual, hearing, speech, and physical disabilities, whereas mental and intellectual services show a patchy northwest-high / southeast-low pattern. （3）Improved spatial matching significantly enhances functional recovery—most strongly for visual, hearing, and speech disabilities, moderately for physical disabilities, and weakly for mental and intellectual disabilities. （4）Individually, male, older age, early onset of disability, lower education, unmarried status, agricultural household registration, and unemployment are associated with higher disability severity. （5）Community characteristics (higher housing prices, education, healthcare, and commercial service levels) moderate and generally amplify the positive effects of rehabilitation services on functional recovery.
Scientific clarification of the spatiotemporal interaction patterns and digital enhancement paths for the synergistic growth of cultural and tourism efficiency is the key to achieving deep integration and high-quality development of these industries under waves of efficiency change and the digital economy. This paper constructs an index system for the digital economy and the efficiency of the cultural and tourism industry, and builds a theoretical framework for their synergistic growth based on theories of industrial integration, synergy, and technological spillover. Using the super-EBM model, Harken model, exploratory spatiotemporal data analysis, and spatial panel regression models, this study examined the spatiotemporal characteristics of cultural and tourism efficiency synergy across 30 Chinese provincial-level regions (2011-2021). It further explored the impact of the digital economy on this synergy and its dynamic spatial effects. The results revealed that (1) The cultural and tourism industries have entered a phase of synergistic growth characterized by mutual enhancement. Within this synergy, the cultural industry acts as the sequential parameter, playing a dominant role. (2) China's synergistic growth in cultural and tourism efficiency showed an “M”-shaped fluctuating trend after its decline in 2012, forming a regional pattern of “East>Central>West” and revealing significant positive spatial agglomeration. (3) China's cultural and tourism efficiency synergy exhibits significant path dependence and transfer inertia, alongside a weakening trend in spatial integration. The local spatial structure and dependency direction remained relatively stable during both the 2011-2015 and 2016-2021 periods, with greater stability observed in the eastern region compared to the more dynamic central and western regions. (4) The digital economy can significantly promote the synergistic growth of cultural and tourism efficiency, which still holds after the endogeneity and robustness tests; the digital economy has a significant positive spatial effect on the synergistic growth of cultural and tourism efficiency, but over time, this effect presents a dynamic diminishing characteristic. This research provides new theoretical and empirical insights for clarifying the intrinsic mechanisms and evolutionary logic of the cultural and tourism system, as well as for promoting its digital empowerment, quality improvement, and deep integration.
In recent years, the empowerment of digital technologies in rural tourism has become increasingly normalized, yet there is a lack of sorting out and analysis in research related to the digitalization of rural tourism. On the basis of clarifying the conceptual connotation of rural tourism digitalization and adhering to the people-centered development concept, this paper summarizes relevant research issues from four aspects: protection of subjects' rights and interests, practice of digital applications, sustainable development, and innovation in collaborative governance. Moreover, based on the IMOI (Input-Mediator-Output-Input) framework and TOE (Technology-Organization-Environment) theory, it constructs a research framework for rural tourism digitalization from six links—origin, composition, process, mechanism, effect, and goal—and expounds on the dynamic evolution mode and self-feedback cycle mechanism of rural tourism digitalization. Looking ahead, it is necessary to explore the theoretical framework of rural tourism digitalization from an interdisciplinary perspective, investigate rural tourism and digitalization from different angles, and apply the qualitative-to-quantitative comprehensive integration method combined with empirical research, so as to provide a theoretical and practical basis for the digitalization of rural tourism.
nderstanding how different key stakeholders perceive cultural ecosystem services (CES) and the mechanisms behind these perceptions is essential for the inclusive realization of social values and the sustainable management of world natural heritage sites. Taking the Danxiashan as a case study, this study employed social values of ecosystem services model (SolVES) to explore the spatial distribution, trade-off & synergies of ten social values of cultural ecosystem services (CESSVs) and their influencing factors from the perspective of 4 groups of key stakeholders (non-local tourists, local residents, and employees of local government and local tourism enterprises), based on social survey and geospatial data. Results showed: (1) CESSVs exhibited significant clustering in Danxiashan, with the agglomeration effect among stakeholders was listed in the following order: non-local tourists > tourism enterprises employees > local residents > local government employees. The spatial differentiation of CESSVs was as follows: Elder Peak > Yangyuan Stone > Jinjiang Gallery Scenic Area. (2) All stakeholders believed that there were significant synergies among 10 CESSVs in Danxiashan. However, noticeable differences were observed in coupling coordination degree of CESSVs among stakeholders in the order: local government > tourism enterprises > local residents > non-local tourists. (3) CESSVs perception among non-local tourists and local residents was primarily influenced by natural factors, while that for employees of local government and tourism enterprises were more strongly shaped by anthropogenic factors. These findings provide scientific support for the inclusive realization and the synergistic enhancement of CESSVs at Danxiashan, and have general references value for other world natural heritage sites.
Farmland marginalization is widespread in China's mountainous areas, posing challenges to national food security and the stability of mountain ecosystems. However, the degree of marginalization varies among different farmland types. This study focuses on uncultivated farmland as a major form of marginalization. Using data from the Third National Land Survey, we identified the extent and spatial distribution of uncultivated sloping land and terraced land, the two dominant farmland types in mountainous areas. An ordinary least squares (OLS) regression model was then applied to determine the main factors driving farmland uncultivation for each type. Finally, we classified regional patterns of uncultivation and proposed policy recommendations to promote the sustainable use of mountainous farmland. The results indicate that: (1) At the national scale, the uncultivation rates of sloping land and terraced land in 2019 were 7.03% and 6.64%, respectively. (2) Uncultivated farmland showed clear spatial heterogeneity. Uncultivated sloping land was mainly distributed in the Loess Plateau, while uncultivated terraced land was concentrated in both the Loess Plateau and the southern hilly regions. (3) Farmland uncultivation was shaped by multiple interacting factors, but the dominant drivers differed across regions. Based on the leading factors, these regions were categorized into four types: natural endowment dominated, locational condition dominated, input factor dominated, and comparative disadvantage dominated areas. (4) Different regional types require targeted management strategies. Natural endowment dominated areas should promote ecological restoration or specialty agriculture. Locational condition dominated areas should improve infrastructure and production connectivity through land consolidation and high-standard farmland construction. Input factor dominated areas need to strengthen land transfer mechanisms, agricultural service systems, and new business entities. Comparative disadvantage dominated areas should increase subsidies for agricultural inputs, encourage high-value crops such as fruits, flowers, and vegetables, and develop facility-based agriculture where appropriate.
The Loess Plateau is a globally sensitive region to environmental change. In recent decades, ecological restoration has significantly altered regional land surface conditions and water-carbon cycling processes, profoundly impacting water resources and ecosystem patterns. However, whether the increased water consumption induced by ecological restoration is sustainable, and how the water-carbon balance is affected by the dual drivers of climate change and human activities, remain critical scientific questions imperative to clarify. Based on MODIS remote sensing vegetation indices and the Vegetation Interface Processes (VIP) model, this study simulates and examines the spatiotemporal patterns of evapotranspiration (ET), gross primary productivity (GPP), and water use efficiency (WUE) in the northern Shaanxi Loess Plateau since the implementation of the Grain-for-Green Program (2000-2021). The results show that: (1) ET, GPP, and WUE all exhibited significant increasing trends during 2000-2021 (p<0.05), with regional average annual change rates of 5.61 mm/a, 20.76 gC/m²/a, and 0.03 gC/m²/mm/a, respectively. The increase in WUE directly resulted from significantly larger increases in GPP compared to ET. (2) WUE's response to climate change showed marked spatial heterogeneity: A positive correlation with precipitation (P) in the north and negative in the south; predominantly negative correlation with air temperature (Ta) (especially significant in shrub-grasslands of the northern semi-arid zone); and mainly positive correlation with sunshine duration (SD) (notably pronounced in forested areas of the southern semi-humid zone). (3) The relative contributions of climate change and human activities to ET, GPP, and WUE changes were 11.4%/88.2%, -2.2%/101.8%, and -15.0%/115.3%, respectively. Climate change promoted ET but suppressed WUE, while human activities exerted positive effects on all three components, serving as the dominant driver of water-carbon balance evolution over the past two decades. This study demonstrates that ecological restoration drives WUE growth by preferentially enhancing carbon assimilation (GPP increased 2.1 times faster than ET). This finding provides key evidence for clarifying the debate on whether “ecological restoration exacerbates water stress”, offering a scientific basis for optimizing regional ecological restoration strategies to achieve sustainable development.
