The Yellow River Basin (YRB) is a vital ecological zone in China owing to its sensitive and fragile environment. Under the long-term influence of climate changes and artificial factors, the relationship between precipitation, vegetation, and surface water in the YRB has changed drastically, ultimately affecting the water resources and environmental management. Therefore, we applied multivariate statistical analysis to investigate the precipitation, normalized difference vegetation index (NDVI), and surface water changes in the YRB from 2000 to 2021. Furthermore, we attempted to clarify the ecological effects of precipitation by explaining the relationship between precipitation and vegetation in terms of the time-lag relationship using the Integrated Multi-satellite Retrievals for Global Precipitation Measurement algorithm, Moderate Resolution Imaging Spectroradiometer, and hydrological databases. Precipitation, vegetation, and area of surface water in the YRB showed increasing trends from 2000-2021 (e.g., 7.215 mm/yr, 0.004 NDVI/yr, and 0.932 km²/yr, respectively). The water level in the upper reaches of the YRB showed a downward trend, whereas that in the middle and lower reaches exhibited an upward trend. Changes in precipitation had a positive effect on vegetation and surface water in the YRB, with correlation coefficients of 0.63 and 0.51, respectively. The responses of NDVI and surface water elevation to precipitation were heterogeneous and delayed, with the majority showing a lag time of approximately ≤ 16 days. Moreover, the lag times of Longyangxia Lake and Ngoring-Co Lake were 0 and 8 days, respectively. We showed that precipitation variability can effectively explain vegetation improvement and increases in surface water elevation, while providing a proven scenario for predicting the surface water and vegetation productivity under the influence of climate change.

Population exposure is a dominant representation of rainstorm hazard risks. However, the refined precipitation data in temporal resolution and the comparison of exposure to different rainstorm events remain relatively unexplored. Hourly precipitation data from 165 meteorological stations w used to investigate the spatiotemporal evolution of population exposure to different rainstorm scenarios in the prefecture-level cities for different periods and age groups. The Geographical Detector was adopted to quantitatively analyze the influencing factors and contribution rates to changes in population exposure during each period. The results revealed that population exposure to persistent rainstorms and abrupt rainstorms was low in the center and high in the surrounding areas, and the high exposure value decreased significantly in the 2010s. Additionally, as the duration of rainstorm events increased, the center of the high-value area of population exposure shifted southward. The distribution of population exposure was closely related to the age structure, demonstrating strong consistency with the distribution of different age groups. Except for abrupt rainstorms, the contribution rates of the average land GDP and urbanization rate to the exposure of all rainstorm scenarios increased significantly. This implies that the main factors influencing population exposure have shifted from meteorological to socioeconomic factors.

Significant spatiotemporal variation in human livelihood patterns and its relationship to trans-Eurasian exchange and climate change in north China during the late Neolithic and Bronze Age, has been intensively studied in recent years, but the comprehensive influence of natural and social factors on this variation is not well understood. Therefore, we analyze archaeobotanical, zooarchaeological and carbon isotopic data from late Neolithic and Bronze Age sites in agricultural, pastoral, and agro-pastoral regions of north China. Our results demonstrate human subsistence strategies transformed at different speeds in these three geographic areas after wheat, barley, and sheep, goats, and cattle were introduced into north China. Introduced crops and livestock dominated human livelihoods in pastoral regions and became important subsistence in areas above ~1500 m a.s.l. in agro-pastoral regions after ~3600 BP. In agricultural regions, indigenous millet crops were the most important subsistence throughout 6000- 2200 BP, but wheat use increased significantly around 2700 BP. Our study suggests that the introduction of new crops and herbivorous livestock related to the prehistoric trans-Eurasian exchange, and their adaptive advantage in high-cold environments might have rapidly facilitated human adaptability and social development in pastoral regions and northwest margin of agro-pastoral regions during the Bronze Age.

In recent years, cropland development in high-slope regions in China has alleviated the contradiction between total cropland balance and insufficient development space. However, this change in cropland slope brings risks to sustainable resource utilization. This study explored the slope characteristics of cropland in China from 1990 to 2020 and assessed the gained cropland stability. The results showed that (1) From 1990 to 2020, the lost cropland area was greater than the gained area, and the distribution showed an uphill trend. (2) The areas with a significant upslope change in cropland were mainly concentrated in the southern plain, containing the central grain-producing regions at its core and other well-developed eastern coastal areas. (3) The areas with distinct downslope cropland changes were mainly concentrated in the upper reaches of the Yangtze and Yellow rivers and the ecologically fragile areas of Inner Mongolia and the Loess Plateau. (4) The gained cropland stability was unsatisfactory; about one-third of the gained cropland was unstable, which had the highest abandonment rate within 5 years, and the gained cropland stability decreased with the slope. In addition, this study explored cropland conversion types at different slopes in different regions and discussed the reasons for slope cropland changes and gained cropland instability in different regions. Finally, optimization policies were proposed to protect and control newly gained cropland.

Different types of urban construction land are different in terms of driving factors for their expansion. Most existing studies on driving forces for urban construction land expansion have considered the construction urban land as a whole and have not examined and compared the differentiated driving forces for different types of construction land expansion. This study explored the differentiated driving mechanisms for two types of urban construction land expansion by selecting key driving factors and using spatial econometric regression and geographical detector models. The results show that there are significant differences in the driving forces for expansion between the two types of urban construction land. The driving factors of urban land expansion do not necessarily affect industrial parks. And the factors acting on expansion of both types are different in influence degree. For urban expansion, economic density growth, the value-added growth of tertiary industries, and proximity to urban centers have a negative effect. However, urbanization levels and value-added growth of secondary industries have a positive effect. The explanatory power of these factors is arranged in the following descending order: value-added growth of tertiary industries, value-added change of secondary industries, urban population growth, economic density growth, and proximity to urban centers; road network density has no significant effect. For industrial parks expansion, the value-added growth of secondary industries and road network density has a positive effect, while economic density growth has a negative effect. The explanatory power is arranged in the following descending order: value-added growth of secondary industries, road network density, and economic density growth. The findings can help implement differentiated and refined urban land use management policies.

Cultivated land plays a pivotal role in ensuring national food security, particularly in populous nations like China, where substantial investments are made to develop cultivated land as a counterbalance to construction-occupied areas. Consequently, long-term, effective monitoring of the utilization of newly cultivated land becomes imperative. This study introduces a comprehensive monitoring framework, designed for refined scales, that leverages remote sensing data. The framework focuses on the sustainable utilization of newly cultivated land, emphasizing utilization sustainability, productivity stability, and landscape integration. Its effectiveness was validated through a case study in Guangdong province, China. The results revealed satisfactory utilization sustainability and improved productivity stability of newly cultivated land in Guangdong, though landscape integration showed sub-optimal results. Furthermore, the comprehensive evaluation categorized the newly cultivated land into three levels and eight types. The study recommends enhancing the site selection process for newly cultivated land and improving the long-term monitoring, as well as incentive and constraint mechanisms, for their utilization. This study can provide a scientific reference to bolster the implementation of cultivated land protection policies, thereby contributing significantly to high-quality economic and social development.

This research aimed to understand supply and demand in the global nickel market from a product chain perspective. Accordingly, we established an extensive time-series database for the nickel trade network and employed network analysis methods to explore the dynamics and shifts in the global nickel trade network. The results are as follows: first, refined nickel and nickel semis dominated global nickel trade; second, the interaction between different nickel product networks profoundly affected the global nickel supply chain; third, the global nickel trade network consisted of core-periphery structures exhibiting different degrees of spatial heterogeneity; and fourth, the most connected global backbone structure was in nickel semis, followed by refined nickel, nickel ore, and nickel scrap. Together, trade in these four products constituted an overall network topology characterized by complex forms, a clear hierarchy, and uneven development. We conclude the paper by making several recommendations to secure global nickel supply chains and promote nickel circular economy.

Based on the data of listed companies in the core industry chain of China's new energy vehicles in 2015 and 2021, this paper constructs their industrial network from the perspective of the value chain, and uses methods such as social network and negative binomial regression model to study the characteristics, evolution, differences, and formation mechanisms of different value chain networks. The results show that: (1) R&D-oriented, production-oriented, and service-oriented networks share several common features: These networks are simultaneously expanding in scale and transitioning towards more efficient “small world” network; The degree distribution in these networks follows a power-law distribution, indicating a scale-free network structure; There is a decrease in the power-law exponent of network’s degree distribution, indicating an increase in network heterogeneity. Furthermore, there is a significant positive correlation between the degrees of nodes in networks with diverse value chains, suggesting that the same node holds a similar level of significance across different networks. (2) The number of power-prestige, power and prestige nodes increases in the networks of all value chain segments, except in the service-oriented network, where there are no power nodes. In each value chain network, these nodes have different agglomeration directions: In R&D-oriented network, the nodes tend to cluster around headquarters and high-level cities. In contrast, service-oriented network shows a concentration of nodes in municipalities, sub-provincial and provincial capitals. Similarly, production-oriented network demonstrates a clustering of nodes in traditional production bases. (3) Different value-added segments of industry form different types of agglomeration in pursuit of different factor endowments and agglomeration effect, and form the spatial structure of the strongest connection industrial network with different characteristics. The R&D-oriented networks have always been an integrated and closely connected multiple core-periphery structure community with the influence of social, technological and geographical proximities; Transformation of service-oriented network from an integrated and closely connected multiple core-periphery structure community to a multiple core-semi-periphery-periphery structure community with the influence of social, geographical and institutional proximities; Transformation of production-oriented network from the partially integrated and localized core-periphery structure community to the more decentralized multiple independent core-periphery structure community with the influence of the social, institutional of administrative boundaries and geographical proximities.

Commuting is an important part of primary school students’ travel behavior, which has been concerned for a long time. We found that the commute-mode choice behavior of primary school students in the context of regional segmentation shows strong characteristics in space, but has not yet been considered in traditional research. To fill this gap, this study summarizes the commute-mode choices of primary school students with different characteristics based on the Beijing School Commute Survey. And the geographically weighted regression (GWR) model is built to analyze the zonal heterogeneity of the impact of personal characteristics, family factors and school factors on the primary school students’ commute- mode choices from a low-carbon perspective. The results demonstrate that the possibility of primary school students choosing low-carbon commuting modes is positively correlated with the grade, commuting time, commuting escort type and housing category, but is inversely related with the commuting distance and the distance from the school to the city center. The coefficient estimates of explanatory variables vary across regions. Finally, we put forward policy suggestions regarding promoting the low-carbon commuting structure, such as developing the urban slow traffic system, which serve as a reference for policymakers.