Urban transportation resilience reflects the ability of the transportation system to maintain its basic functions and structure through its resistance, mitigation, and absorption under extreme conditions, or the ability to restore the original equilibrium or reach a new equilibrium state within a reasonable time and with reasonable cost. Global warming, sea-level rise, and rapid urbanization all increase the risk of compound extreme weather events, presenting challenges for the operation of urban-related infrastructure including transportation infrastructure. In this context, some questions become important. For example, how to measure the strength of urban transportation resilience under extreme weather events (including the impact of different extreme weather event intensities on its strength); how to monitor its spatial and temporal features and evolution trends; and how long will it take for the entire system to restore balance? At present, effective monitoring methods for transportation resilience under the influence of extreme events are lacking, especially the monitoring of the temporal and spatial dynamic changes of transportation resilience under climate change, to answer these questions. Therefore, it is urgently needed to solve the problem of accurately identifying the state of urban transportation resilience under extreme weather events and improving the level of prevention and control of transportation system impact of natural hazard-related disasters. The development of big data mining technology and deep learning methods for spatiotemporal prediction made the construction of spatiotemporal datasets for evaluating and predicting urban transportation resilience possible. Such datasets can reveal the spatiotemporal evolution features, changing trends of urban transportation resilience intensity under the influence of extreme weather events, as well as the mechanism of influence. It indicates the key research areas that should be focused on for transportation resilience under climate warming. This article reviewed and summarized the research on transportation resilience in China and internationally in the past 50 years, analyzed the deficiencies in the existing research based on the relevant research results of transportation resilience in China and globally, and identified the key areas and directions of the research on transportation resilience under climate warming in order to provide new ideas for future research on transportation resilience.

A rare persistent high temperature event occurred in the Yangtze River Basin in summer 2022, which caused serious impacts on the life and production of the provinces in the basin. Scientific analysis of the causes of this high temperature process is of great significance for improving the prediction and early warning of high temperature processes. Based on the NCEP/NCAR reanalysis data and the daily temperature data collected from 699 stations in the Yangtze River Basin, this study examined the atmospheric circulation characteristics and the causes of this high temperature process. The findings indicate that: 1) The high temperature process that occurred in the Yangtze River Basin in 2022 ranked the highest in terms of the area of influence, intensity, duration, and comprehensive strength since 1961. 2) There were mainly two circulation causes that attributed to this high temperature process. The first was the impact of local circulation, that is, the middle and upper layers of the troposphere over the Yangtze River Basin was controlled by the abnormal anticyclonic circulation generated by the equivalent barotropic mechanism. The second was the impact of large-scale circulation, that is, the South Asia High and Western Pacific Subtropical High moved in an opposite direction and overlapped over the Yangtze River Basin. Under the control of high pressure, the sinking movement over the Yangtze River Basin and the solar radiation reaching the ground are obviously strong, which led to strong extreme high temperature. 3) The main reason for the long duration of the abnormal circulation is that with the Rossby wave transmitting energy eastward from Western Europe and the Lake Baikal, the circulation distribution presented a "two grooves and one ridge" model from west to east in the middle and high latitude of Eurasia and a stable "three-wave" model in the middle and high latitudes in the northern hemisphere. Therefore, the energy converged in the subtropical region above the Yangtze River Basin, which helped maintain the intensity of the subtropical high and the occurrence of the abnormal positive height anomalies over the Yangtze River Basin.

Administrative division is the basic supporting unit for a country to carry out local governance. The adjustment of administrative divisions is related to the grassroots social governance system and capacity building, and constitutes a part of the modernization of the national governance system and governance capacity, which has a long-term impact on economic development and regional governance. This article systematically reviewed and analyzed the literature on China's administrative division research in the past 30 years, and summarized the development status of China's administrative division research from the aspects of history, type of models, effectiveness evaluation, influencing factors, and comparison within China and internationally. The research found that the setting of administrative divisions serves the national development strategy, and the research is closely related to national policies. The promulgation and implementation of relevant policies stimulate the research of administrative divisions, and vice versa. The study of administrative division has a strong historical continuity and spans multiple disciplines. Drawing on the useful experience of developed countries, it also has very strong local characteristics. In the process of integration of administrative divisions into national governance system and governance modernization, scientific and practical research on the setting and adjustment of administrative divisions should be strengthened. We should give full play to the advantages of multiple disciplines, strengthen the theoretical and methodological research on the setting and adjustment of administrative divisions, and comprehensively improve the effectiveness of national spatial governance.

One of the basic topics in population geography is how the population distributes and changes on terrain gradients. With the improvement of data accuracy and quality, it is feasible to conduct macroscopic analysis for this question based on kilometer grid cells. This study analyzed the distribution and change characteristics of China's population on the gradients of elevation, ruggedness, and slope from 2000 to 2020, using methods of frequency distribution statistics, based on 1-km grid statistical cells, and using spatial demographic datasets (WorldPop) and digital elevation model datasets (SRTMGL1). The effects of different digital elevation model datasets (including ASTER GDEM and SRTMGL1) and spatial demographic datasets (including WorldPop, LandScan, and GPW) on the results were also compared and the differences between the 1-km grid and 100-meter grid data were further explored with SRTMGL1 and WorldPop. The results show that: 1) The population increasingly tends to be distributed at the lower position of terrain gradients. The half-balance points of the population distribution on elevation, ruggedness, and slope gradients were 95.6 m, 50.7 m, and 3.01° respectively in 2000, and decreased to 77.0 m, 46.8 m, and 2.88° in 2020. 2) Dominant area of population distribution relative to land area has been stably located at a lower position of terrain gradients. The upper boundary of the dominant part of the population over terrain (MU) is stably located at the elevation of 520 m, the ruggedness of 137 m, and the slope of 6.84°, respectively, and the population dominance rate rose from 0.511, 0.248, and 0.217 in 2000 to 0.522, 0.274, and 0.255 in 2020, respectively. 3) Different spatial demographic datasets have no effect on the distribution and change pattern of population on terrain gradients, while DEM datasets have significant effects on the ruggedness gradient and slope gradient distribution of population. There is no difference between 1-km grid and 100-meter grid data for this study, and the 1-km grid dataset is recommended for the study of population distribution at the national scale and above. This study provides a new basic reference for understanding of the relationship between population distribution and terrain in China at the kilometer grid scale.

With the advent of the post-industrial era, a "green turn" has gradually become the basic principle of global urban renewal. However, green initiatives and practices in urban renewal often focus on environmental sustainability, neglecting the green gentrification that can be triggered at the social level. In the context of urban renewal in China, urban greening practices have emerged with many representations similar to the phenomenon of green gentrification, but this has not attracted the attention of scholars in China. This study adopted a qualitative research method to investigate the effects and mechanisms of green gentrification in the context of urban renewal, taking the greening practices of urban agricultural parks as an example. The study found that: 1) In the context of urban renewal, urban greening practices imply a logic of gentrification in action, and the postmodern aesthetic and experiential landscape it creates becomes a place representation of green gentrification. 2) Greening practices oriented to serve the urban elite have triggered landscape segregation and stratification, but under the guarantee of the Chinese land tenure and management system, the indigenous people are not displaced but receive dividends from the recapitalization of the land. 3) The government, village collectives and residents, and developers have formed green growth alliances to meet their political and economic demands for the purposes of urban governance, land rents, and economic interests, respectively, eventually forming a government-led green gentrification operation mechanism. This study empirically analyzed green gentrification, which originated in western societies, in the institutional and social contexts of China, expanding the connotation and explanatory validity of green gentrification in the context of multiple geographies, and providing new theoretical perspectives and practical insights for understanding the change of human-land relationship in the context of urban renewal in China.

The urban life cycle theory was proposed by Hall and Van den Berg and colleagues based on European urban research. According to the changes in the population of the urban core and rings, the urban spatial evolution process is divided into four stages: Urbanization, suburbanization, deurbanization, and reurbanization. The stage alternation and specific stages described by the theory have also been confirmed by subsequent empirical research, and this theory has been widely applied in identifying and studying the stages of urban development. However, this theory has been criticized and questioned as follows: 1) The process of urban development cannot be measured solely from a single population change perspective; 2) There are heterogeneities in urban development under different backgrounds; 3) The division of stages is unreasonable and debatable; and 4) Urban space does not always evolve linearly in a unidirectional order. In this context, many studies have made revisions, supplements, and improvements to this theory, and some new theories have been proposed, but there is still room for breakthroughs and development. Future breakthroughs can be made in the following aspects: 1) Incorporate marginal cities, shrinking cities, gentrification, and new urban phenomena into research of the post crisis and post pandemic period, and consider changes in people's lifestyle and thinking, socioeconomic background, and so on, to expand the applicability of the theory; 2) Refine urban types to identify the diversity of evolution, and conduct comparative research to identify urban life cycle models that are suitable for China; 3) Incorporate population structure and integrate the data of population size, age, and household and socioeconomic characteristics to enhance the depth of urban spatial analysis; and 4) Increase research on the migration of residents and businesses, expand micro-scale perspectives, and integrate multiple urban systems to enhance the comprehensiveness of urban spatial evolution theory.

The upper Jinsha River has seen increased variability of stream runoff under the global warming since 1990 and extreme flood events with a 100-year recurrence period have occurred in recent years with flood peaks double or triple that of its normal annual mean flow, which has led to challenges to the utilization of water resources and reservoir operation in the basin. The upper Jinsha River Basin covers a large area but has few observation stations. Compared to the traditional models, the single objective runoff simulation based on machine learning (ML) model has shown advantages in forecasting floods, but the research on runoff prediction of ML model for large rivers originated in alpine mountains is insufficient. In this study, the long short-term memory (LSTM) neural network model was used to simulate the annual runoff process in the upper Jinsha River and the model was driven by daily precipitation, mean temperature, and snow cover area extracted from the 500 m elevation bands of GPM, ERA5-Land, and MODIS snow cover products. The model was built with the runoff observation data as the objective. An ensemble model driven by daily means of all above parameters of the whole basin was also built and compared with the LSTM model. Both models used data from 2001-2014 for training and 2015-2019 for validation. The results show that the Nash-Sutcliffe efficiency (NSE) of the two models was greater than or equal to 0.80 within 15 days lead-time, the models had similar NSE in adjacent lead-times, and the NSE decreased to about 0.70 for the lead-times of 25 and 30 days, which indicates that the runoff simulation results of the two models are reasonable at the 30 days and shorter lead-times. Better results of runoff simulation were generated by the LSTM model driven by the vertical zonation data for the 1-5 days lead-times as compared to the ensemble model. The advantage of the vertical zonation data-driven model reduced for the 7-13 days lead-time and the simulation results are equivalent for the 15-30 days lead-time. The vertical zonation data-driven model was superior to the ensemble model in simulating flood season runoff. In general, the runoff simulation accuracy of the vertical zonation data-driven model is the highest at the 3 days lead-time, especially for spring and summer floods. We conclude that the developed model driven by the elevation zonation data can provide reliable prediction of floods, which can provide a reference for the operation of the downstream cascade hydropower stations of the middle Jinsha River. However, the improvement of the ML model for extreme spring floods should still be an important direction in future research.

Understanding the employment preferences of the floating population is crucial for formulating relevant employment policies. In this study, based on the China dynamic monitoring survey data for the floating population in 2017, we categorized the employment options into traditional secondary industry, high-tech manufacturing industry, traditional service industry, and modern service industry, and then scrutinized the floating population's employment choices and spatial variations at the prefecture level. We also established a mixed-effects multinomial logistic regression model to investigate individual and regional factors of the employment choice of the floating population. The main findings of the study are as follows: 1) The majority of the floating population have engaged in employment in the traditional service and traditional secondary industry, with only a small fraction opting for high-tech manufacturing and modern service employment. 2) The percentages of the floating population engaged in employment in the traditional secondary industry and high-tech manufacturing industry were significantly higher in the eastern region than in other regions, particularly in the Yangtze River Delta, Pearl River Delta, and Shandong Peninsula. 3) Most city units in the central-west and Northeast regions had a high concentration of floating population employment in the traditional service industry, with some city units showing relatively high employment percentages in the modern service industry. 4) The floating population's employment choices were influenced by both regional and individual factors. Specifically, regional industrial structure and urban population size affected the regional employment structure, while employment competition and human capital levels of the floating population affected their integration into the regional employment structure. Moreover, gender, age, and population registration status of the floating population also affected their employment choice. The research findings can deepen the understanding of the mechanisms behind the employment choice of the floating population in Chinese cities, especially the relationship between the employment choice of the floating population and urban industrial development, providing references and support for the formulation of employment policies on the floating population.

Production of space systematically integrates Marxism and spatial theories into a materialistic system with both dialectical and historical thinking, opening up a new horizon for interpreting and analyzing spatial practice processes. Using the CiteSpace bibliometric method and based on publications in China and in the field of production of space, combined with in-depth reading of typical literature, this study examined the progress of the application of the theory of production of space in the field of urbanization research in China, and summarized the overview, highlights, and shortcomings of research. The results indicate that: 1) The rapid development of urbanization in China and the expansion of the dissemination and influence of the Western theory on the production of space have jointly promoted the relevant research in China, which is characterized by diverse objects, broad themes, flexible perspectives, and a combination of practical interpretation and problematic criticism, focusing on the correspondence between foreign theories and local practices. 2) The generalization of spatial patterns of urbanization and the critique of urbanization effects are the two key points of the application of the production of space theory. The former is to apply production of space to sort out diverse and specific localization practices, while the latter is the revelation of contradictions in specific spatial production practices based on human-centered values. There still exist several shortcomings: 1) The lack of attention to the richness of historical practice and the special focus on the logic of capital have led to the suspicion of economic determinism and relatively neglected other important areas such as everyday life. 2) Insufficient attention to the localization of historical practices and the biased dogmatic appropriation of Western theories has limited the growth of critical theoretical innovation. 3) Insufficient attention has been paid to the need to guide practice, and the value of Marxism for guiding practice is still limited. 4) From the standpoint of historical materialism, the outlook of theory application was proposed in the light of the specific trends and needs of high-quality development of urbanization in China, that is, from productive space analysis to living space concern, from spatial problem analysis to the construction of a Chinese system of theories, and from the interpretation of spatial theory to the guidance of spatial practice.

Pest disasters are serious threats faced by the forest ecosystem of China. This study selected 316 research papers on forest pest disasters with the selection criteria that primary data of the research were completely obtained from ground survey. We compiled the time of occurrence, location, affected area, and intensity of each forest pest disaster (FPD) event. Then, using Meta-analysis on these records, we depicted the spatial and temporal variability of forest pest disasters in China. A total of 962 FPD records were compiled. These records involved 299 counties in China and covered a temporal range from 1985 to 2018. The results showed that there were 242 county-times of serious FPD events during 1985-2018 with an annual mean of 7.1 county-times. From 1985 to 2005, the annual county-time number of serious FPD events increased at 0.4 county-times per year, but the upward trend was replaced by a decline of -0.6 county-times per year from 2005 to 2018. Spatially, there were more FPD events in the Wuyi Mountains in southeast China and the Qilian Mountains in northwest China compared to other regions. The frequency of serious FPD events exhibited a declining trend from the southeastern coast of China to the northwestern inland region. The Wuyi Mountains area was the most serious FPD region of China. Meteorology factors were considered the primary factor that influenced the FPD. The interannual fluctuation of FPD frequency was negatively correlated with winter temperature of the previous year in the southern part of the semi-arid area and the warm temperate semi-humid area; while it is negatively correlated with spring temperature in the north sub-tropic area and the central sub-tropic area in the south.

The once-in-a-century revolution in the automobile manufacturing industry has triggered a "car-making frenzy" in China, subsequently reshaping the spatial landscape of the country's automobile manufacturing industry. This study used comprehensive micro-enterprise databases and employed location quotient indicators to compare the spatial agglomeration characteristics of the Chinese automobile manufacturing industry between 2013 and 2021. It examined the distinctive location traits of both new energy and traditional automobile manufacturing sectors, while also evaluating the co-agglomeration patterns of three pivotal industries—automobile, electronics, and electrical-in Chinese cities. Additionally, the study employed the negative binomial regression method to investigate the factors that influence the site selection of Chinese automobile manufacturing enterprises. The findings of this study are as follows: Chinese automobile manufacturing enterprises tend to concentrate in cities with a solid historical industrial foundation, showcasing a blend of continuity and change in the industrial layout. The location choices of Chinese new energy automobile manufacturing enterprises are both path dependence and path breakthrough. While cities with established prowess in traditional automobile manufacturing still hold potential for developing the new energy automobile sector, cities with weaker traditional automobile manufacturing sectors, such as Shenzhen, have made remarkable strides in the realm of new energy vehicles. In 2021, only 11 cities in China, including Shanghai, Hefei, and Suzhou, achieved the co-agglomeration of the three major manufacturing industries (automobile, electronics, and electrical). Notably, cities with well-developed automobile industries, such as Chongqing, did not gain specialized advantages in the electronics and electrical manufacturing sectors. Factors such as the diversification index of the manufacturing industry, the complexity of manufacturing knowledge, the size of the resident population, and the location quotient of the automobile manufacturing industry contribute to attracting automobile manufacturing enterprises. Traditional automobile manufacturing tends to gravitate towards cities with a concentration of foreign industrial enterprises, which diverges from the agglomeration patterns observed in the electronics manufacturing sector. The impact of location quotient in the electronics and electrical manufacturing industry on the site selection of Chinese new energy vehicle manufacturing enterprises did not demonstrate statistical significance. This study contributes to enriching the theory of industrial location in China and provides valuable insights for automotive manufacturing companies in their site selection process, as well as informing government policies related to industrial layout planning.

With the development of 5G, AI, and the Internet, we have entered the era of video socialization. Based on the Douyin (TikTok) data, this study analyzed the characteristics of the urban network in China with the help of the social network analysis method, and explored the influencing factors by using the optimal parameters-based geographical detector. The results show that: 1) The unbalanced distribution pattern of different types of cities based on local and non-local connections is basically consistent with the long-standing east-west gap, and the city grade based on the Douyin (TikTok) social media platform does not completely follow the traditional city grade system. 2) The overall network showed a triangular pyramid structure, which is very similar to the development pattern of urban agglomerations in the 14th Five-Year Plan. 3) The main influencing factors of urban network centrality in China are the level of economic development and information development, and the secondary influencing factors are the level of logistics development and tourism development. 4) Due to the varied stages of development, different regions showed obvious spatial differences. The southwestern region was more affected by the level of logistics development, the northeastern region was more affected by the level of tourism development, and the northwestern region was more affected by the level of economic development.

Health is an old but ever-present topic for human beings, which is closely related to the geographical environment. The new health geography emphasizes the role of place in influencing individual and public health. Multisensory therapeutic landscape research reveals the interactions between elements of place and health practices at various spatial scales. In the context of deep integration of tourism and health, this study used the theoretical framework of therapeutic landscape in health geography, which advances the traditional methodologies that examine the single dimension of visualscape. Taking Nanjing Purple Mountain National Forest Park as a case, this study explored the elements of multisensory therapeutic landscape and its mechanism of health impact in tourism destinations from the perspective of human-land interaction. The user-generated content that directly reflects tourists' perception was adopted to analyze the components and mechanism of health impact of multisensory therapeutic landscape in Nanjing Purple Mountain National Forest Park. Based on the results of analysis using the grounded theory, the therapeutic landscape in Nanjing Purple Mountain National Forest Park was decomposed into four dimensions of visualscape, soundscape, smellscape, and haptiscape, which have unique attributes and complex relationships. The findings confirmed that the therapeutic landscapes in tourism destinations are multisensory while the visualscape is not always dominant. Furthermore, through the multiple correspondence analysis, the meaning of multisensory therapeutic landscape in Nanjing Purple Mountain National Forest Park were clustered into three themes: nature, tranquility and coordination, revealing the health impact mechanism of place in the continuous dynamic interactions between the destination and the tourist. The concept of multisensory therapeutic landscape indicates the interactions between environmental factors and health practices at various spatial scales, which provides a new perspective to explore the relationship between place and human health. The intersection of health geography and tourism geography will enrich the theories and methods of landscape research, and promote the sustainable development of tourism destinations with multisensory therapeutic landscape.

With the collaborative development of the urban agglomeration of the Yellow River Ji-shaped bend, it is of great scientific value to carry out the study of its spatial patterns. With the development of modern transportation, communication, and information technologies, the pattern of flow space based on dynamic element flow has become a research frontier. This study combined traditional static data and dynamic flow spatial data to examine the hierarchical spatial pattern of the urban agglomeration of the Yellow River Ji-shaped bend. The static data include the calculated comprehensive strength of the cities in the region, and the dynamic data are related to the dynamic flow space of three types of flows, namely population flow, logistics flow, and information flow. These elements were considered to make a comprehensive assessment of the multi-level spatial pattern of the urban agglomeration of the Yellow River Ji-shaped bend. This study found that: 1) There are some differences in the strength of spatial linkages among various types of flows in the region, where information flows are the strongest and there are strong linkages between information flows and other elemental flows. 2) Ordos is the dominant city in the urban agglomeration of the Yellow River Ji-shaped bend, and Yinchuan, Hohhot, Taiyuan, and Wuhai are the secondary dominant cities. Small city clusters centered on these cities have been formed in the region. In the future, the cities in this urban agglomeration should focus on strengthening the overall radiation capacity and spatial linkage strength to promote the rapid, coordinated, and comprehensive development of the urban agglomeration. This will eventually stimulate the urban network development from point to axis, and then to a "surface" in the urban agglomeration of the Yellow River Ji-shaped bend.

Modern new media technology tools represented by Tiktok provide an important means for "New Farmer" to participate in rural cultural tourism and rural revitalization. However, existing research had paid little attention to the spatial distribution characteristics of this group, and there was a lack of reasonable and objective evaluation of the cultural tourism transformation potential of "New Farmer" anchors. Based on the data of Tiktok "New Farmer" anchors on the Chanmama website, this study comprehensively measured the rural cultural tourism transformation potential of "New Farmer" anchors from three aspects: directivity, recognition, and dissemination and used hotspot analysis to analyze the spatial differentiation of the characteristics of "New Farmer" anchors and their cultural tourism transformation potential. It further explored the cultural tourism driving mode of "New Farmer" anchors, revealing the regional differences in their cultural tourism transformation potential from a spatial perspective to provide a reference for better leveraging the cultural tourism driving capabilities of the "New Farmer" anchors. The results show that: 1) "New Farmer" anchors exhibited obvious characteristics of more in the south and fewer in the north, with more males and fewer females. There were significant differences in the spatial pattern of anchor scale and cultural tourism transformation potential, and the cultural tourism transformation potential of Henan and Shandong, was very limited. 2) The southwestern region, especially Sichuan and Chongqing, had prominent advantages in terms of the number and scale of "New Farmer" anchors, live streaming sales, and potential for cultural tourism transformation. 3) Less than 40% of ordinary media users had the potential for cultural tourism transformation. Although the number of "rural guardians" was limited, they brought significant potential for cultural tourism transformation. 4) There were significant regional differences in the advantageous characteristics of rural cultural tourism transformation potential. "New Farmer" anchors in the southwest had strong cultural tourism promotion concepts, and their short videos showed higher degree of direction towards cultural tourism content. The cultural and tourism videos in the southeastern region showed significant advantages in recognition and dissemination, and the content quality of cultural and tourism videos was even better. 5) The "New Farmer" anchors with different identities were different in terms of creative motivation, narrative mode, and narrative content. Their driving mode of cultural tourism could be divided into grassroots cadres-direct driving, rural guardians-indirect driving, and ordinary personal media users-potential driving. In general, Tiktok "New Farmer" anchors, characterized by individual creation, had played a significant role in breaking through the differences in the eastern, central, and western regions of China, and promoted equal development between the central and western regions and the eastern region. However, the significant differences between the south and the north and the limited potential for cultural tourism transformation still need further attention.

Trade connectivity is a crucial component in the implementation of the Belt and Road Initiative (BRI). Based on the BRI trade network database, this study integrated three mesoscale analysis methods, including community detection, core-periphery profile, and disparity filter, to build an analytical framework for exploring trade network connectivity and further investigated the spatiotemporal patterns, topological relationship, and structural evolution of "the Belt and Road" trade network from 2000 to 2020 in two dimensions, including nodes and edges. This study aimed to provide scientific references for a comprehensive and in-depth understanding of "the Belt and Road" trade network connectivity. The results show that: 1) The BRI trade network connections and density continuously increased, and the size distribution in trade volumes showed spatial heterogeneity, gradually forming patterns with an apparent hierarchical structure, unbalanced spatial distribution, and increasingly close trade ties. 2) The BRI trade network included five trade blocs with significant geographical proximity, and geographical distance still played an essential role in the evolution of the international trade division of labor system at the global and regional scales. 3) The core-periphery structures of the BRI trade network are undergoing structural adjustments, with the core and peripheral structures showing apparent differentiation and the core-peripheral polarization effect emerging. 4) The backbone structures of the BRI trade network have been continuously expanded and enriched, showing a trend of convergence to the core countries, forming backbone network patterns with China as the absolute core, radiating outward and linking the whole region while India, Russia, and Turkey have also formed their backbone networks in local regions. From the perspective of network science, examining trade network connectivity is crucial for understanding the trade network structure, optimizing the trade development pattern, and enhancing the trade network resilience in "the Belt and Road" regions.

In the process of rapid urbanization, regional human-environment relationships in rural areas have become increasingly complex, and these areas are facing the challenge of integrating limited resources to realize industrial transformation and development. From the perspective of the factor-structure-function transformation of the rural territorial system, this study elucidated the conceptual connotation and driving force of rural industrial restructuring. On this basis, it classified the typical patterns of rural industrial restructuring according to the development direction of the dominant industries, with a specific focus on Guangxi. The study then proceeded to construct the guarantee mechanism for rural industrial restructuring. The following four main conclusions were reached: 1) Rural industrial restructuring can be comprehended as the process of optimizing spatial layout, extending the industrial chain, and enhancing the industrial system through industrial cultivation, adjustment, upgrading, and transformation. This process is grounded in the integration of the basic factors of industrial development—such as labor, land, and capital—in the context of local development conditions and external market environment. Rural industrial restructuring is characterized by the diversification of subjects and business forms, aiming to achieve both the benign and balanced development of rural industries internally and the value output externally. 2) In the practice of industrial restructuring, external driving forces and endogenous development forces of the rural territorial system interact with each other to jointly promote the coupling and coordination of various factors related to industrial development. 3) Rural industrial restructuring comprises five typical patterns, including the specialization of agricultural production, the industrialization of traditional culture, the tourism-driven development, the agglomeration of manufacturing, and service-oriented commerce and logistics. 4) In terms of policy, emphasis should be placed on guiding the concentration of key factors of production in rural areas by breaking down institutional barriers; building modern rural industrial systems by optimizing the industrial structure and improving the industrial layout; and improving the benefit linkage mechanism by adhering to the principle that the central position of farmers should not be compromised. Through a comprehensive approach, an institutional arrangement can be made for promoting rural industrial restructuring and facilitating the revitalization of rural industries.

The digital economy is a new driving force for China's economic development and an important growth point for expanding domestic demand. This study examined the mechanism of the digital economy affecting household consumption. Based on the panel data of 31 provinces of China from 2011 to 2020 and using the mediation effect model and the spatial Durbin model, this study examined the mechanism and spatial effects of the digital economy on household consumption and conducted an expanded analysis from the temporal and regional dimensions. The results show that: 1) The digital economy can directly promote household consumption. 2) The indirect effect of the digital economy on consumption is to improve the diversification of products on the supply side, increase household income on the demand side, and promote market integration on the market side. 3) While promoting local consumption, the digital economy also has positive spillover effects among provinces with similar economic levels. 4) The results of the expanded analysis show that the role of the digital economy in driving consumption is sustainable over time, which increases with the improvement of the economic level. Meanwhile, the effect is stronger in the central and western regions than in the eastern region, showing the characteristics of benefiting the poor and favoring the less developed regions. These results expanded the research perspectives of digital economy driving consumer consumption, and provide a decision reference for the strategy of boosting consumer demand based on the digital economy.

Improving the carbon sequestration and sink capacity of terrestrial ecosystems is one of the most economical and green ways to achieve the carbon peaking and carbon neutrality goals on schedule. Soil particulate organic carbon (POC) and mineral-associated organic carbon (MAOC), as important soil organic carbon fractions, are the key to understanding changes in the carbon cycle in terrestrial ecosystems. Previous studies have shown that climate warming has changed the carbon cycle of terrestrial ecosystems and affected the input of organic carbon from plants and microorganisms at the same time, but there is no unified conclusion on the response of soil organic carbon components to climate warming and their controlling factors. This article systematically introduced the framework of soil particulate and mineral-associated organic matter. The formation, transformation, and stabilization of the two components were described. The article reviewed current research progresses on the response of soil particulate and mineral-associated organic carbon to climate warming and their influencing factors. On this basis, the shortcomings of existing research and future challenges were discussed, and the key scientific issues that need to be solved urgently at present and future research directions were proposed, in order to provide a theoretical reference for the formulation of soil organic carbon management and solutions to climate change.

The combinations of regional climate factors and climate risk types caused by temperature rise in the backdrop of global warming are complex and diverse. South and Southeast Asia (SSEA) have attracted great attention due to their tropical monsoon climate and related unique characteristics. Exploring the patterns of change in temperature and precipitation in SSEA is of great significance for evaluating their effects on regional human activities and disaster risk such as the occurrence and development of active fires. Based on the 1980-2018 global climate element dataset (Climatologies at High Resolution for the Earth Land Surface Areas (CHELSA) V2.1, 30″×30″), and using statistical methods such as linear fitting and Mann-Kendall test, the spatiotemporal characteristics and evolution trends of temperature and precipitation in SSEA were examined from the aspects of overall trend of change and regional difference characteristics. The main conclusions are that: First, precipitation in SSEA has increased significantly in the past nearly four decades. A mutation of the trend of precipitation was detected in 2005. Second, nearly 2/3 of the SSEA region experienced an increasing trend of precipitation. Although rainfall change intensities in South Asia and Southeast Asia were similar in the rainy season, the amplitude in Southeast Asia was greater in the dry season. Third, SSEA has shown a significant warming trend in the last 40 years, and difference in monthly temperature rise was slight. Fourth, the regions with an increasing trend in temperature accounted for nearly 99.13% of SSEA, and the temperature change in Southeast Asia was more significant than that in South Asia during the rainy season. However, temperature rise in South Asia was more significant in the dry season, while it was the opposite in Southeast Asia. Finally, SSEA showed a notable trend of warming-wetting climate since the 1980s, which was featured by greater significance and intensity of temperature and precipitation changes in Southeast Asia.

Vegetation phenology is a sensitive indicator of climate change, and the effects of different meteorological factors and changes in atmospheric pollutants on peak vegetation growth have not been fully explored. In this study, we used satellite observed normalized difference vegetation index (NDVI) data from 2001 to 2015 to investigate the temporal changes of peak of growing season (POS) and maximum vegetation growth (NDVI_max) in the Beijing-Tianjin-Hebei region by the Theil-Sen slope estimator. We also analyzed the effects of preseason temperature and precipitation on POS and NDVI_max considering the effects of the fine particulate matter (PM_2.5) to investigate the indirect effect of PM_2.5 on POS and NDVI_max in the region, and the direct effects of PM_2.5 on POS and NDVI_max by partial correlation analyses. The results showed that earlier POS and higher NDVI_max occurred in the Yanshan Mountains and Taihang Mountains, POS in the eastern and southern plains were relatively late, and the NDVI_max in Zhangjiakou City, the Yanshan Mountains, and the Taihang Mountains showed a significant increasing trend. Preseason precipitation had a greater impact on POS and NDVI_max (the area where significant correlation was found accounted for 12.9% and 15.2% of the study area), which was similar to the effect of temperature (8.7% and 5.9%, respectively). Under the impact of PM_2.5, the feedbacks of precipitation and temperature were different in different regions and seasons, and the responses of phenology to the changes of precipitation and temperature caused by PM_2.5 also showed spatial heterogeneity. PM_2.5 led to the underestimation of the advancing effect of precipitation on POS in the central and eastern plains and northern Yanshan Mountains, overestimation of the advancing effect of precipitation on POS in the northern Zhangjiakou area, and overestimation of the advancing effect of temperature on POS in the eastern and southern plains and the Bashang areas. Overall, the indirect effect of PM_2.5 on NDVI_max was reducing NDVI_max (P<0.1). In the long run, PM_2.5 would directly advance POS and increase NDVI_max in most areas of the Beijing-Tianjin-Hebei region (P<0.1). Our study revealed the response of peak vegetation growth to climate factors and atmospheric pollutants in the Beijing-Tianjin-Hebei region, which are of great significance for an in-depth understanding of the response and feedback of vegetation growth to changes in the climate and air pollution.