Economic geographical theories have long posited collaboration as a fundamental mechanism for knowledge recombination and regional innovation. This imperative is intensified by the growing demands of contemporary innovation, where technological advancement increasingly hinges on the integration of multidisciplinary knowledge bases, a process that elevates technological complexity. We contend that the development of such complex technologies inherently demands not only cross-disciplinary collaboration but also a heightened reliance on geographic proximity to facilitate the exchange of tacit knowledge and ensure contextual embeddedness. However, the empirical validity of this theoretical proposition and its underlying evolutionary mechanisms remain underexplored in the Chinese context. Addressing this gap, this paper analyzes the spatial characteristics of knowledge innovation and cooperation in China, drawing on patent data from 2000 to 2017. Our findings reveal that: 1) Collaborative knowledge innovation in China has not only followed a growing trend but has also evolved into a multi-polar spatial distribution over the past decade; 2) A positive correlation exists between technological complexity and cooperation, with increasing complexity fostering local, intra-city collaboration; 3) A city’s established knowledge production capacity exerts a moderating effect on this process, reinforcing path-dependent characteristics in regional industrial development. By foregrounding the Chinese context, this study moves beyond validating existing theories to offer a nuanced empirical extension to innovation and evolutionary economic geography. It illuminates the geographically variegated mechanisms through which knowledge complexity, institutional configurations, and regional assets interact to shape and continually reshape the economic landscape.
Overseas R&D is a crucial means for enterprises to access foreign innovation resources and enhance their innovative capabilities. This paper utilizes Chinese enterprises’ patent application data from the United States Patent and Trademark Office (USPTO) and employs GIS spatial analysis to characterize the spatial distribution of their overseas R&D activities. Furthermore, it applies a panel negative binomial regression model to investigate the determinants of Chinese enterprises’ overseas R&D from a host country perspective, conducting a categorical analysis. The main findings are as follows: 1) Chinese enterprises’ overseas R&D activities exhibit an inverted U-shaped trend. Between 2012 and 2017, the number of overseas inventors associated with Chinese enterprises increased, while after 2018, due to technology restrictions imposed by Western countries such as the United States, this number began to decline. 2) Chinese enterprises’ overseas R&D activities are primarily driven by technology acquisition motives, concentrating and increasingly agglomerating in developed countries in North America and Europe. 3) The analysis of influencing factors reveals that institutional distance and information technology factors significantly impact Chinese enterprises’ overseas R&D activities. A separate analysis distinguishing between the developed and developing host countries shows that overseas R&D in developed countries is more influenced by formal institutional distance, while overseas R&D in developing countries is more significantly affected by informal institutional distance and geographic proximity. This study contributes to the empirical research on overseas R&D by developing countries and provides decision-making support for Chinese enterprises in selecting locations for their overseas R&D activities.
To effectively leverage the positive role of the digital economy in enhancing the resilience of the tourism system is crucial for ensuring the stable and long-term development of the tourism economy and achieving high-quality growth. To this end, the article integrates multi-source data to construct a panel dataset of 285 prefecture-level and above cities in China from 2011 to 2019, analyzes the evolutionary characteristics between the digital economy and tourism industry resilience from the spatial and temporal dimensions, and empirically examines the influence process, regional heterogeneity, and the mechanism of action by using the panel spatial Durbin model. The research finds that: 1) The digital economy and the resilience of the tourism industry as a whole are on an upward trend, and the development gap between cities has narrowed slightly in a converging trend. In terms of spatial distribution, the former shows a “ladder-like” pattern of high in the east and low in the west, while the latter shows a spatial evolution pattern of “central collapse”. 2) Digital economy and tourism industry resilience have strong spatial agglomeration characteristics, while the two show significant positive spatial correlation. 3) The digital economy not only enhances the resilience of the local tourism industry, but also acts on neighboring cities through spatial spillover effects. Heterogeneity analysis shows that the degree of influence of the direct effect is: Northeast > East > West > Central, and high digital economy region > low digital economy region; at the same time, the Central Region shows a negative spillover effect, while the high digital economy region shows a significant positive spillover effect. 4) Mechanism tests indicate that tourism innovation capability and tourism market influence are the two major paths through which the digital economy enables tourism industry resilience. The results of the study can provide a policy basis for effectively promoting the digital transformation of multiple tourism actors at the municipal scale, improving the ability to respond to crisis events, and promoting the sustainable and high-quality development of the tourism industry.
In the era of the knowledge economy, endogenous technological relatedness has increasingly evolved into networked configurations, profoundly reshaping the micro-level transmission mechanisms and output pathways of regional innovation. The spatiotemporal complexity and growth effects of these networks have attracted growing scholarly attention. Drawing on technological correlation theory, this study examines the spatiotemporal evolution and growth effects of the technological correlation network in the Yangtze River Delta (YRD) from 2002 to 2021. Results show that the network has expanded steadily, with deepening technological integration and a marked concentration of globally connected technologies along the Shanghai-Nanjing-Hefei-Hangzhou-Ningbo corridor. Its structural backbone has shifted from single-core dominance to multi-core concurrency, where star-shaped, chain-like, and tree-like patterns coexist, and the rise of hub and backbone technologies has become a key driver of urban innovation. The network also demonstrates strong modularity: the number of communities remains stable, yet their scales diverge and compositions diversify, with core technologies rooted both in origin hubs such as Shanghai, Nanjing, and Hangzhou and in application markets including Changzhou, Nantong, and Huzhou. While the knowledge base of individual technological clusters shows increasing diversification, cities with concentrated innovation resources—such as Nantong, Yancheng, and Jinhua—tend to prioritize specific domains. Patterns of urban network evolution can be categorized as comprehensive innovation, horizontal expansion, vertical specialization, or balanced low-level growth, broadly aligned with economic and administrative hierarchies. Growth effects are heterogeneous: aggregation and chain-like structures yield rising marginal benefits, while modular and global features follow an inverted U-shaped trajectory. These dynamics are further moderated by the scale of universities, enterprises, and individuals, as well as by the broader policy environment.
Understanding how urban innovation spaces are embedded in their unique local “soil” is key to accelerating the development of new quality productive forces. Based on the in-depth analysis of the essence of urban innovation space, this study constructs a theoretical framework of urban innovation space system at the micro level, and empirically analyses it by using exploratory spatial analysis method and optimal parameters-based geographical detector model, with a case study of Lanzhou. The results show that: 1) Lanzhou urban innovation space takes “old city, development zone, new district/city” as the core carrier. Among them, the knowledge-based, incubation-based, and production-based innovation spaces are organized in the modes of “campus+park+urban area”“urban area+campus+park” and “development zone+park+urban area”, respectively. 2) The organization of clusters shows “specialized clusters” with “parks” as innovation carriers and “diversified clusters” with “urban areas” as innovation carriers. There is a certain positive coupling relationship between different types of innovation spaces, and a unidirectional asymmetry of “proximity”. 3) From a general perspective, the differentiation pattern of innovation space in Lanzhou is mainly influenced by land cost, production service, culture and leisure factors. It is also significantly influenced by the interaction between innovation environment factors, such as location history and industrial environment, and innovation service factors, such as transportation and travel and production services. 4) In terms of subtypes, knowledge-based innovation spaces are particularly dependent on location history factors; land cost factors obviously constrain incubation-based innovation spaces; and production-based innovation spaces are more sensitive to factors such as production services, land costs, culture, and leisure. At the same time, each type of innovation space is subject to the comprehensive influence of the interaction and coupling of various factors.
Against the backdrop of climate change, energy transition, and high-quality development, new energy vehicles (NEVs) have become an increasingly vital component of strategic emerging industries. Specifying the spatiotemporal patterns of NEV enterprises within urban agglomerations and identifying the influencing factors are basic scientific issues for facilitating the development of NEV industrial development. This paper depicts the spatiotemporal patterns of NEV enterprises in the Pearl River Delta (PRD) during 2017—2021 and examines the influencing factors through the lens of the dual dynamics of state and market. The findings indicate that: 1) The spatial pattern of NEV enterprises in the PRD has evolved from a “single-core” centered in Shenzhen to a “dual-core” centered in Shenzhen and Guangzhou, with the highest concentration in the boundary areas of Guangzhou-Foshan and Shenzhen-Dongguan. Upstream “raw material” enterprises have dispersed from Shenzhen to Guangzhou, Huizhou, and Zhuhai; midstream “core component” enterprises remain largely concentrated in Shenzhen; downstream “vehicle manufacturing” enterprises are concentrated in Shenzhen and Guangzhou and begin to spread to surrounding areas, with “supporting and aftermarket” enterprises evolving from a dual-core pattern in Shenzhen and Guangzhou to multiple hotspots. 2) Both state and market dynamics influence the spatiotemporal pattern of NEV enterprises in the PRD, with the effects on the distribution of NEV enterprises in the PRD varying across development stages, geographic locations and industry chain segments. In terms of development stages, the influencing factors of enterprise spatial layout shift from the dual drive of government and market to market forces dominance. With respect to geographic locations, the eastern PRD is more sensitive to market dynamics, while the western PRD sees a relatively more prominent role of the government. As for the industrial chain, market forces mainly affect the upstream and midstream, while the downstream and extended segments are under the dual influence of both state and market forces.
Based on the pressure-state-response model, the study constructed a comprehensive analysis framework of carbon neutrality capacity from three dimensions, namely, resource and environmental pressure, carbon neutrality status and response degree, using entropy method and spatial distance model. It explored the carbon neutrality capacity and spatio-temporal differentiation characteristics of cities in the Yangtze River Delta from 2010 to 2020. It also applied the triangle model to classify the types of carbon neutrality of cities and explored their differentiated regulation mechanisms. The results showed that: 1) The evaluation values of the carbon neutrality pressure, state and response subsystems of cities in the Yangtze River Delta have generally shown an upward trend. The dimensions both developed independently and interacted with each other. The pressure was higher in the east and lower in the west. Shanghai and Suzhou were the high pressure centers. The state was opposite, better in the west and south. The response extended from the east-centre to the south and north-east. 2) From 2010 to 2020, the range of carbon neutrality index values changed from 0.32-1.41 to 0.53-1.42. The overall differences of carbon neutrality capacity in cities have been narrowing, and the dynamic evolution characteristics of different cities have great difference. The carbon neutrality capacity of the high-value areas in the west and north regions has significantly decreased, the carbon neutrality capacity of the low-value areas in the centre-east region has significantly improved, and the carbon neutrality capacity of the medium-value areas in the south region has fluctuated up or down. The response level of various cities has increased significantly, but the pressure continues to increase under the effect of rapid socio-economic development, which has hindered the homogeneous growth of cities’ carbon neutrality capability to a certain extent. 3) Based on the percentage combination of the pressure, state and response, 4 types of carbon neutrality regulation paths were established: response-dominant zone, pressure-response zone, state-response zone, and pressure-state-response zone. The results can provide policy reference for formulating differentiated carbon neutrality strategies and promoting the development of urban low-carbon economy.
Based on panel data of grain output and year-end population size from 285 cities during 2000—2022, this study employs spatial analysis, the spatial mismatch index of grain supply and demand, and a two-way fixed effects model to explore the spatiotemporal evolution and influencing factors of China’s grain output and supply-demand relationships. The results show that: 1) The growth rate of grain output has slowed, with a decline in grain output in major sales areas among the three primary grain output and sales zones. The spatial clustering of grain output has intensified, with high-value clusters concentrating in the northeast and Huang-Huai-Hai regions, while low-value clusters are shifting to South China and the middle and lower reaches of the Yangtze River. The spatial distribution center of grain output has shifted northeastward. 2) The per capita grain availability has increased from above the subsistence level to exceeding the food security threshold, while the spatial mismatch between grain output and demand has intensified. Per capita grain availability in major production areas has increased significantly, with an abundant grain supply. In production-consumption balance areas, per capita grain availability has slightly declined, resulting in a relatively tight supply. In major sales areas, per capita grain availability has decreased markedly, leading to a very constrained supply. Cities with abundant grain supply are concentrated in the northern regions, while cities with very limited grain supply are clustered in the southern regions. Cities with relatively abundant or relatively scarce supply are scattered across various areas. Many cities in major production areas and production-consumption balance areas have seen improvements in the grain supply-demand relationship, while many cities in major sales areas have experienced a deterioration in this relationship. 3) There is a significant positive relationship between grain output and factors such as sown area, technological progress, government intervention, climate, and farmland quality. Among these, sown area is the key factor driving grain output growth. In contrast, grain prices, urbanization, and agricultural labor force have a significant negative impact on grain output, with urbanization having the most pronounced negative effect. The findings of this study can provide references for adjusting China’s grain production-consumption divisions, alleviating the grain supply-demand imbalance, and promoting grain production.
Rural public cultural spaces serve as vital arenas for sustaining community identity, transmitting cultural values, and fostering social cohesion in the context of rural revitalization. Against this backdrop, the new endogenous governance model provides an effective framework for activating their internal dynamics and guiding sustainable cultural development. The interaction between internal and external forces facilitates the creation of public cultural assets that benefit all villagers and strengthens the social foundation for collective participation. Nevertheless, limited scholarly attention has been devoted to understanding how external forces can effectively and sustainably stimulate endogenous development in rural cultural contexts, where resource scarcity, uneven participation, and fragmented governance remain common challenges. To address this gap, this study investigates the internal mechanisms and governance effects of fostering new endogenous development in rural public cultural spaces through an in-depth case study of Deng Yun Shuyuan in Heyuan City, Guangdong Province. The findings reveal that: 1) Mobility serves as a key medium in aligning internal and external elements within rural cultural spaces, forming a governance pathway that encompasses resource input-articulation-endogenization, subject injection-articulation-empowerment, system embedding-articulation-generation, and institutional embedding-articulation-generation; 2) Although most mobile elements gradually withdraw over time, the sustained circulation of resources, actors, and ideas—anchored by public welfare organizations—constitutes the core mechanism of new endogenous development in rural libraries. This mechanism not only integrates urban and rural cultural resources but also enhances local participation, nurtures cultural identity, and enables the construction of governance systems tailored to local contexts, thereby ensuring the long-term activation of rural public cultural spaces; 3) Beyond cultural governance, the new endogenous development of rural libraries plays a critical role in advancing rural civilization, strengthening community cohesion, and contributing to the broader goals of constructing ecologically livable, prosperous, and well-governed socialist rural communities while deepening urban-rural integration. Overall, this study offers novel theoretical insights and practical implications for the sustainable governance of rural public cultural spaces, thereby enriching strategies for rural cultural revitalization and providing references for comprehensive rural development in China and beyond. It also underscores the importance of rethinking governance models that balance external support with local agency, ensuring that cultural revitalization efforts remain both context-sensitive and sustainable over time.
In the context of new urbanization centered on human beings, the topic of migrant workers’ citizenship has become a research hotspot. This article focuses on the Pearl River Delta urban agglomeration, where the migrant population is concentrated and urbanization is developing rapidly, based on the 2017 China Mobile Population Dynamic Monitoring Data. First, the entropy method is used to quantify the weights of the citizenship ability indicators and assess the citizenship ability of rural migrant workers in the Pearl River Delta urban agglomerations; second, the causal analysis framework of “survival ability-adaptive ability-potential ability” is constructed, and the evolution of the citizenship ability of rural migrant workers is simulated based on the Bayesian network model in different scenarios. The study found that the citizenship ability of migrant workers gradually extends from low-level living needs to high-level emotional needs. The citizenship ability of rural migrant workers in the Pearl River Delta urban agglomeration exhibits significant spatial disparities. Core areas lead the way, driven by strong economic agglomeration and high employment absorption capacity. Peripheral zones occupy a middle ground, supported by relatively well-developed public services and moderate living costs. In contrast, outer areas lag behind due to structural deficiencies, particularly the lack of adequate public services. The key to enhancing the ability of migrant workers to become citizens lies in breaking down regional institutional barriers, strengthening the effectiveness of citizenship management in the core area, continuing to stimulate the vitality of the population in the periphery area, and pushing forward the construction of public services in the outer area, so as to promote the coordinated and interlinked development of the regions within the Pearl River Delta urban agglomeration, and to push forward the high-quality development of urbanization.
Total factor productivity (TFP) is the core driving force behind the high-quality development of Japan’s beef cattle industry, and it is also a key factor that sustains the industry’s long-term sustainable growth. Using panel data for 9 agricultural regions in Japan from 2004 to 2022, this study applies the Malmquist-Luenberger index to measuring and to decomposing TFP in the beef cattle farming sector. It also employs Geodetector and the Spatial Durbin Model to examine in depth the spatiotemporal evolution of TFP and the factors that shape it. These methods make it possible to trace changes over time, capture spatial correlation, and identify the principal drivers of regional differences. The empirical results indicate the following: 1) From 2004 to 2022, TFP in Japan’s beef cattle farming kept declining on a sustained basis. Over the same period, regional development became increasingly uneven. The Tokai region was the only region that recorded positive TFP growth. All other regions showed a general downward trend during the study period. Taken together, these facts point to persistent weakness in total factor efficiency across most areas of the country. 2) Overall, TFP displays a positive spatial correlation. Regions with higher TFP tend to be adjacent to regions with similarly high levels, and lower TFP regions are often clustered as well. Geodetector analysis further identifies the following as the dominant factors that explain spatial differentiation in TFP: the number of agricultural technology R&D personnel, the intensity of fiscal support, the degree of industrial agglomeration, feed production capacity, and material labor productivity. The observed spatial differentiation is produced by a multi-dimensional, multi-factor mechanism rather than by a single cause. In other words, human capital, public finance, industrial clustering, and resource and productivity conditions act together and reinforce one another to shape the spatial pattern of TFP. 3) Industrial agglomeration, fiscal support intensity, and the number of agricultural technology R&D personnel display significant and positive spatial spillover effects, indicating that coordinated and parallel progress across regions is the necessary choice for promoting the sustained and healthy development of the beef cattle farming sector. This study aims to provide theoretical support and empirical evidence for the sustainable development of Japan’s beef cattle industry, and to offer policy references that can inform practice aimed at improving the quality of economic growth in the beef cattle industries of both China and Japan.
The phenomenon of “internet celebrity city”, a product of the digital economy, illustrates how virtual information flow can transform into actual tourist traffic. This paper uses Harbin’s emergence as an “internet celebrity city” as a case study, applying time series analysis, Granger causality tests, and multi-scale geographically weighted regression (MGWR) models to examine the mechanisms by which tourism information flow drives passenger flow. It also examines their interaction’s spatiotemporal dynamics and influencing factors. The key findings are: 1) Tourism information flow and passenger flow in the preparation, launch, outbreak and sustained four stages of attraction and interaction characteristics of symbiosis, attraction is reflected in the threshold effect and precursor effect, interaction through the feedback to strengthen the formation of a virtuous circle. 2) This interaction displays notable scale effects and spatial heterogeneity, with a significant bidirectional Granger causality observed nationwide, while complex spatial differentiation emerges at the regional level. 3) Consumer potential, information level, and transportation accessibility positively impact tourism passenger flow, while spatial distance negatively impacts passenger flow. This study enhances the theoretical framework of tourism flow dynamics by integrating spatiotemporal scales and spatial heterogeneity analysis. It proposes three strategies: developing dynamic information ecosystems for crisis management; implementing differentiated marketing strategies that leverage regional responsiveness, including cultural campaigns for remote markets; and fostering transportation-information synergy to enhance accessibility through coordinated high-speed rail promotions with social media trends. These findings offer insights for optimizing digital tourism governance and improving destination competitiveness in platform economies.
Quoting the concept of geographical nature, this article analyzes the pattern characteristics of static location and dynamic network competitiveness of 19 ports in the coastal PFTZ, as well as their mismatch state, and scrutinizes the impact of static location factors representing the first and secondary geographical characteristics of ports on their network embedding, particularly focusing on how the impact changed before and after the embedding of Dalian Port. The results show that: 1) There is spatial heterogeneity in the location conditions for FTP construction. The Yangtze River Delta (YRD) and the Pearl River Delta (PRD) forming a “main core & subsidiary core” structure with higher location advantages, while other regions form a single-core structure with dominant oligopoly ports. The pattern of port embedding position and embedding structure level has a certain similarity. 2) The location competitiveness of ports and their network embedding levels are significantly negative mismatched, but to some extent, these two advantages can be transformed into one another. Ports like Suzhou Port, which are in a negative mismatched state, can compensate for the deficiencies in the first or second geographical nature by gaining network benefits. 3) Dalian Port’s location competitiveness and network embedding levels are both in the middle range, and its overall performance is in a negative mismatched state. When embedded in the coastal free trade port system, it can reduce the negative impact of hinterland support and the level of port city economic development on network embedding. Openness to the outside world is an advantageous factor for Dalian Port in embedding into the free trade ports system, while the limited hinterland and distribution capacity lead to its lower attractiveness compared to surrounding ports.
This paper constructs a theoretical framework for the network of hedging actors of neighbouring countries of South China Sea under the human-ocean relations geographical system, aiming to fill the existing research gap in systematically analyzing regional hedging dynamics from a geographical perspective. It then utilizes the relevant model to carefully portray and in-depth analyze the evolution of Vietnam’s China-biased hedging between China and the United States and the key driving factors over the two-decade period from 2001 to 2020, a timeframe marked by significant shifts in global and regional power structures.The conclusions are as follows: 1) Vietnam’s hedging is not a random policy choice but a geo-strategy that arises and develops in a specific geo-environment—shaped by the South China Sea’s unique geography and regional power balance. It is deeply influenced by the relative power differences between countries and the spatial synthesis of relations, and its development and evolution cannot be separated from the influence of the network of hedging actors of neighbouring countries of South China Sea under the human-ocean relations geographical system, as interactions with other regional states further mold its hedging decisions; 2) During the period of Nong Duc Manh, Vietnam initially adopted positive hedging in favor of China, driven by early cooperation needs, but as regional tensions gradually emerged, the negative hedging tended to be strengthened; during the period of Nguyen Phu Trong, the positive hedge has been moving forward with twists and turns amid fluctuating bilateral cooperation projects, while the negative hedge has had its ups and downs, closely tied to changes in regional security incidents; 3) The positive hedges that drive Vietnam’s implementation of bias toward China are “the closeness of diplomatic ties between Vietnam and China”—reflected in high-level exchanges and bilateral agreements—and “the level of development of Vietnamese society’s hard power”, as stronger domestic capacity boosts its confidence in cooperative engagement. Meanwhile, the negative hedges are “Vietnam’s perceived geo-political threat of China” based on its regional security assessments, “Vietnam’s systemic pressures” from internal policy coordination and external alliance expectations, and “South China Sea geopolitical imagery” shaped by media narratives and regional state interactions. These findings not only enrich the academic discussion on regional hedging behaviors but also provide practical references for understanding Vietnam’s foreign policy adjustments in the complex South China Sea context, and help clarify the interplay between geo-factors and state strategic choices in this region, offering insights for promoting stable regional interactions.
Against the backdrop of global warming and the increasing emissions and transboundary transport of aerosols dominated by black carbon, chain disaster events induced by glacier melting on the Qinghai-Tibet Plateau are occurring frequently. Clarifying the variation patterns of black carbon substances on the Qinghai-Tibet Plateau under different climatic backgrounds and intensities of human activities from a historical perspective is of great significance for reasonably coping with disaster risks. This article reviews the black carbon records from different geological archives including lake sediments, aeolian sediments, and ice cores on the Qinghai-Tibet Plateau, and analyzes their spatiotemporal variation characteristics on multiple time scales of glacial-interglacial, the Holocene, historical periods, and recent centuries, and reveals their relationships with climate change and human activities. Results show that: 1) On glacial-interglacial time scale, existing research primarily based on charcoal records, indicates that the wildfire conditions are closely related to regional vegetation types and the wetness and dryness of the climate, but there are few studies on this time scale, and more reliable records are urgently needed to enrich the fire dataset. 2) For the Holocene paleofire history, charcoal records show a general “high-low-high” trend, reflecting the significant impact from regional climate in the early and middle Holocene and from human activities in the late Holocene on the paleofire history. 3) The fire activity intensity on the Qinghai-Tibet Plateau in past 2 000 years has increased to some extent compared with the past, revealing the great role of human activities such as agricultural expansion, war conflicts, and religious sacrifice in environmental evolution. 4) Over the past century, the concentration of black carbon has shown an overall upward trend, reflecting the development of surrounding areas and the growth of pollutant emissions, highlighting the transboundary transport characteristics of air pollution and the profound impact of human activities on the regional environment. Studying the variation characteristics of black carbon on different time scales on the Qinghai-Tibet Plateau and its associations with climate change and human activities can provide scientific references for further assessing the impact of past human activities on the ecological environment of the Qinghai-Tibet Plateau and predicting changes in fires and pollutant transport in region under context of global climate change.
Global climate change has led to frequent occurrence of compound extreme events. Clarifying the temporal and spatial characteristics and their effects on vegetation in ecologically fragile areas of compound events such as dry-wet abrupt alternations can provide scientific basis for safeguarding regional ecological security. By establishing the Long-cycle Drought-Flood Abrupt Alternation Index (LDFAI) and applying the Theil-Sen slope estimation, Mann-Kendall test and Pearson correlation analysis, we reveal the temporal and spatial change characteristics of dry-wet abrupt alternations and NDVI in the upper and middle reaches of the Yellow River from 1982 to 2022, and explore the impacts of these events on vegetation cover. The results indicate that: 1) An dry-wet abrupt alternations occurred in the upper and middle reaches of the Yellow River every 2-3 years on average, and the frequency was higher in the Loess Plateau and the eastern Qinghai-Tibet Plateau. The intensity of these events decreased significantly after 2003. 2) The annual average NDVI of vegetation in the upper and middle reaches of the Yellow River increased at a rate of
Based on long-term meteorological and multi-source remote sensing data, the Standardized Precipitation Evapotranspiration Index (SPEI) and Vegetation Health Index (VHI) were selected to characterize the temporal and spatial characteristics of meteorological and ecological drought, respectively. Using eco-geographical divisions as the analytical framework, we develop a propagation model from meteorological to ecological drought based on Copula functions and conditional probability to reveal the spatial-temporal heterogeneity of propagation probability and triggering thresholds under different environmental settings. Furthermore, the driving mechanism was analyzed based on the XGBoost machine learning algorithm. The results show that: 1) Northeast China exhibited a wetting trend from 1982 to 2024, but the risk of meteorological drought triggering ecological drought still widely exists, with significant differences among ecological-geographical zones. 2) The drought propagation risk in the northern region is significantly lower than that in the southern region, and the propagation probability increases with the intensification of meteorological drought. In region I, the propagation probabilities under different meteorological drought scenarios reach 35.6%, 46.3%, and 52.6%, respectively. Regions II and V exhibit lower response thresholds of ecosystems to meteorological drought than other regions. 3) Multi-factor nonlinear threshold effects are evident: Temperature shows a three-stage threshold effect; Precipitation aggravates propagation when <60 mm but reduces risk within 60-90 mm; Evaporation, NDVI, and Soil Moisture present a saturating “promotion at low levels and inhibition at high levels” response. 4) The geographical detector, which dominates regional differentiation through multi-factor interactions, shows that all regional factor interactions exhibit an enhancement effect. Among them, region I has the strongest hydrothermal coupling effect, with the interaction q-value of Pre and Tem reaching 0.546. The interaction between NDVI and Tem in regions II and V is significant, and the interaction between NDVI and SM in region III is 42% higher than that in the natural state.
In recent years, extreme summer precipitation events have occurred frequently in northeast China, posing a serious threat to the socio-economic development and the safety of people’s lives and property. The accuracy of precipitation data is crucial for disaster prevention, and mitigation, as well as scientific research. Using the daily precipitation data from the national benchmark meteorological station in northeast China (1998—2018) and the hourly precipitation data within Jilin Province, the applicability of CLDAS multi-source fusion precipitation data and CN05.1 grid precipitation data to summer precipitation in northeast China was comprehensively assessed in this study. The results indicate that both CLDAS-Pre and CN05.1 can reasonably reflect the spatial distribution of summer precipitation in northeast China to a certain extent. Compared with CN05.1, CLDAS-Pre has a better correlation with the observed precipitation (>0.8), with smaller mean relative error and root mean square error. Dry and wet deviations are found for summer precipitation over northeast China in CLDAS-Pre and CN05.1, respectively, with this phenomenon most pronounced in August. Both datasets have a higher reproduction of the number of days with light and moderate rainfall, and a lower estimation of the number of days with heavy rainfall. The peak accuracy of CLDAS-Pre hourly precipitation reproduction is roughly between midnight and early morning over the entire region. Overall, CLDAS multi-source fusion precipitation has better applicability in the northeast region. However, the CN05.1 dataset, with its longer sequence, retains significant advantages for applications such as model validation.
Chinese Academy Sciences
Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences
Science Press