The transpiration-to-evapotranspiration ratio (T/ET) is a crucial indicator of the carbon-water cycle and energy balance. Despite the marked seasonality of warming and greening patterns, the differential responses of T/ET to environmental changes across the seasons remain unclear. To address this, we employed a model-data fusion method, integrating the Priestley-Taylor Jet Propulsion Lab model with observational datasets, to analyze the seasonal trends of T/ET in China’s terrestrial ecosystems from 1981 to 2021. The results showed that T/ET significantly increased in spring, summer, and autumn, with growth rates of 0.0018 a^-1 (p<0.01), 0.0024 a^-1 (p<0.01), and 0.0013 a^-1 (p<0.01), respectively, whereas the winter trends remained statistically insignificant throughout the study period. Leaf area index dynamics were identified as the primary driver of the increase in T/ET during summer, accounting for 79% of the trend. By contrast, climate change was the main contributor to the rising T/ET trends in spring and autumn, accounting for 72% and 77% of the T/ET increase, respectively. Additionally, warming is pivotal for climate-driven changes in T/ET trends. This study elucidated seasonal variations in T/ET responses to environmental factors, offering critical insights for the sustainable management of ecosystems and accurate prediction of future environmental change impacts.

The application of ecosystem services (ES) theories in land consolidation is a confusing issue that has long plagued scholars and government officials. As the upgraded version of traditional land consolidation, comprehensive land consolidation (CLC) emphasizes ecological benefits, but it does not achieve the expected effect during the pilot phase. This study first proposed a theoretical analysis framework based on ES knowledge to answer the three key questions of why, where, and how to implement CLC better. Taking mountainous counties as the study area, we found that ES trade-offs/synergies, bundles, and drivers were significantly affected by scale effects. ES knowledge can play a crucial role in designing multi-scale CLC strategies regarding the objective, zoning, intensity, and mode. Specifically, mitigating the significant trade-offs between recreational opportunities, food production, and other ES is the top priority of CLC. Land consolidation zoning based on the ES bundles analysis is more rational and can provide the scientific premise for designing locally adapted CLC measures. Land consolidation can be classified into high-intensity direct intervention and low-intensity indirect intervention modes, based on the major drivers of ES. These findings help narrow the gap between ES and CLC practices.

Ecosystem services in urban agglomerations are the environmental conditions under which human survival and development are sustained. Quantitative assessment of ecosystem services and complex interactions can contribute positively to the achievement of the Sustainable Development Goals (SDGs) for urban agglomerations. However, studies on the future contribution of multi-scenario ecosystem services to the SDGS are lacking. We propose novel integrated modeling framework that integrates the CLUES, InVEST, SOM, and GWR approaches to address the complex relationship between ecosystem services over a long “past-present-future” time series. We construct a novel ecosystem service bundle-based approach for measuring urban agglomerations progress towards achieving ecologically relevant sustainable development goals at multiple scales. In the future scenario, the water yield (WY), habitat quality (HQ), and soil conservation (SC) show similar spatial patterns, with comparable spatial grids, while carbon stock (CS) remains predominantly unchanged and the ecological protection scenario (EPS) improves more significantly. The high-synergy regions are mainly distributed in bundle 4, and most of the trade-off regions appear in bundles 1 and 2. Over the last 30 years, all but the water-related SDGs are declining in bundle 1 of the two urban agglomerations, which are 15% higher in the Guangxi Beibu Gulf (GBG) than in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA). From 2020 to 2035, the three scenarios demonstrate that the optimization of the SDGs progresses most effectively under the future ecological protection scenario (EPS). In particular, bundles 3 and 4 are significantly improved. This critical new knowledge can be used in sustainable ecosystem management and decision-making in urban agglomerations.

Regular quantitative assessments of regional ecological environment quality (EEQ) and driving force analyses are highly important for environmental protection and sustainable development. Northern China is a typical climate-sensitive and ecologically vulnerable area, however, the changes in EEQ in this region and their underlying causes remain unclear. Traditional evaluations of EEQ rely primarily on the remote sensing ecological index (RSEI), which lacks assessments of indicators such as greenness (NDVI), humidity (WET), heat (LST), and dryness (NDBSI). To address these issues, this study employs the principal component analysis method and the Google Earth Engine to construct an RSEI suitable for long-term and large-scale applications and analyzes the spatio-temporal variations in the RSEI, NDVI, WET, NDBSI, and LST. Additionally, geographical detectors are utilized to analyze the driving factors affecting EEQ. The results indicate the following. (1) The RSEI shows a fluctuating upward trend, with an average value of 0.4566, indicating a gradual improvement in EEQ. The EEQ exhibited significant spatial heterogeneity, with a pattern of lower values in the west and higher values in the east. (2) The NDVI and WET exhibit fluctuating increasing trends, indicating improvements in both indices. The NDBSI shows a fluctuating decreasing trend, whereas the LST presents a fluctuating increasing trend, suggesting an improvement in the NDBSI and a slight deterioration in the LST. NDVI and WET demonstrate a spatial pattern characterized by low values in the west and high values in the east. NDBSI and LST demonstrate a spatial pattern characterized by low values in the east and high values in the west. (3) Land use types and precipitation are the primary driving factors influencing the spatial differentiation of the EEQ. The explanatory power of these driving factors significantly increases under their interactions, particularly the interaction between land use types and other driving factors. This study fills the gap in existing EEQ evaluations that analyze only the RSEI without considering the NDVI, WET, NDBSI, and LST. The findings provide new insights for EEQ assessments and serve as a scientific reference for environmental protection and sustainable development.

The agro-pastoral ecotone in northern China (APENC) is an ecologically fragile region with a variable climate and unbalanced socioeconomic development. Identifying the spatial range and transitional dynamics of the APENC is crucial for understanding the delicate balance between regional ecology, the economy, and society. The human-Earth system provides a comprehensive research framework in which human activities and the natural environment are viewed as interdependent and dynamically interactive. Guided by the principles of human-Earth system science, in this study, the boundaries of the APENC are identified by integrating core parameters, including water, land, climate, ecology, and human factors. Raster-based spatial data analysis is employed to examine the spatial and temporal evolution of the APENC from 1990 to 2020. The APENC extends from northeast to southwest along the central axis of northern China, displaying trends of contraction and fragmentation over time, with its centre of gravity shifting closer to the Hu Huanyong Line. The peripheral areas exhibit heightened sensitivity to environmental and ecological changes, highlighting the region’s vulnerability to external pressures. In this study, management strategies grounded in sustainable development principles are proposed, a framework for integrating ecological changes with socioeconomic strategies is established, and actionable guidance for policy- makers to promote sustainable development in this fragile and dynamic region is provided.

Cropland suitability analysis is a vital tool for ensuring food security and sustainable agriculture, coordinating ecological space with human activity space on the Qinghai-Tibet Plateau (QTP). However, there are few studies on complete and accurate cropland suitability assessments on the QTP, let alone on identifying key potential areas for cropland development. We used a novel assessment model to generate a 30-m cropland suitability map for the QTP. The identification of areas with cropland development potential and the evaluation of potentially available cropland were further integrated into a unified analytical framework. We found that only 10.18% of the study area is suitable for large-scale and permanent cropland. Moreover, approximately 72.75% of the existing cropland was found to be distributed in suitable or marginally suitable areas. Considering the trade-offs related to irrigation water supply convenience, approximately 1.07% of the study area was identified as having high potential for cropland development. Four key potential areas were further identified: the Shannan Valley, the Nyingchi Valley, the Zanda Valley, and the Gonghe Basin. These areas boast abundant potentially available cropland resources and ecological resettlement capacities, which leads us to recommend strategic priorities for comprehensive land consolidation and water development. This study has practical significance for optimizing land resource allocation and guiding decision-making related to ecological migration on the QTP.

Research on urban health constitutes an important issue in the field of health geography and also a strong propeller of the Healthy China Initiative. As the main form that realizes new-type urbanization, urban agglomerations should become the primal sites for the construction of a “Healthy China”. The evaluation of healthy cities’ development in urban agglomerations has both theoretical and practical values. Based on the concept of urban health and its evaluation models, this paper developed an evaluation framework for healthy cities that involved multiple data sources. With 19 urban agglomerations in China as the research subjects, we used CRITIC weighting and geographical detectors to examine the geographies of healthy cities and their influencing factors in 2010 and 2020. The results were fourfold. Firstly, the urban health level of China significantly increased from 2010 to 2020, and the comprehensive health index developed towards a positive skewed distribution, along with a shift from “low in the hinterland - high in the coastal areas” to a “multipolar” pattern led by the coastal and southwest urban agglomerations. Secondly, among various dimensions of urban health, the healthy environment index became improved with narrowed regional differences; while the health services index was still polarized; health collaboration was upgraded with a strengthened intercity health network; the healthy population index slightly declined and converged to the middle. Thirdly, urban health in China has initially demonstrated the characteristics of a H-H pattern in the Yangtze River Delta and Chengdu- Chongqing regions, as well as L-L clusters in the northern urban agglomerations, the narrowed regional differences, and increasing coordination within each urban agglomeration. Fourthly, the geographical detector found that economy, urbanization and the human capital were significant external factors that affected urban health development. The explanatory power of technological innovation and opening to the outside world were also increasing. The development of healthy cities is yet to be transformed into regional health integration.

In recent years, the uncontrollable risks of urban production-living-ecological (PLE) space have increased sharply, making resilience enhancement essential for sustainable urban development. Based on the social-ecological system (SES) theory, this study constructs an assessment framework for urban PLE space resilience by analyzing its inherent characteristics. The central urban area of Ganzhou city is taken as a case study to evaluate urban PLE space resilience and diagnose its obstacles. The results are as follows: The PLE space resilience in the central urban area of Ganzhou exhibits gradations and substantial spatial differentiation. The ecological space resilience in the study area was the highest, followed by that of production space, while living space resilience was the lowest. The primary factors influencing PLE space resilience are concentrated in the dimensions of robustness and adaptability. In particular, the robustness of the PLE space is relatively low. Based on these results, targeted spatial resilience governance strategies for the PLE space have been proposed. These strategies serve as theoretical and technical references for the study area. By adopting the PLE space perspective, this paper enriches resilience research and provide theoretical support for sustainable urban development.

The uneven distribution of medical resources has led to increasingly frequent patient mobility; however, the interaction between this phenomenon and the healthcare supply-demand relationship remains underexplored. The present study constructed the 2023 Cross-City Patient Mobility Network in China using one million patient mobility data records obtained from online healthcare platforms. We applied urban network analysis to uncover mobility patterns and used the coupling coordination degree model to assess healthcare supply-demand relationships before and after patient mobility. Explainable machine learning further revealed the impact of supply-demand coupling on patient mobility. The results indicated the following: Patient mobility followed administrative boundaries, although megacities serve areas beyond provincial borders; The scale of healthcare supply and demand displayed a multi-centric spatial pattern with a general decline from east to west, and these characteristics of demand distribution were further solidified by patient mobility; Cities with low supply-demand coupling and undersupply experienced patient outflows, while cities with high coupling and oversupply attracted them. In turn, patient mobility helped balance healthcare supply and demand, optimising the coupling relationship across cities. Thus, this research not only provides a methodological reference for understanding the interaction between patient mobility and healthcare systems but also offers empirical insights for public health policy.

Understanding the evolutionary trends and driving factors behind extreme hourly precipitation (EHP) in typical urban agglomerations is crucial for predicting and preventing rapid floods. We collected hourly precipitation datasets from 31 observation stations in the Central Yunnan Urban Agglomeration (CYA) spanning from 2004 to 2020. Urban and rural observations were dynamically classified based on impervious surface fraction. Linear (Granger) and nonlinear causal methods(convergent cross-mapping and Liang-Kleeman information flow) were used to identify the causal impact mechanisms of large-scale circulation, environment and urbanization on EHP. Moreover, geo-detector further reveals the spatial influence of these factors and their interactions on EHP. Our findings revealed that EHP mainly occurred in the afternoon and at midnight. Also, the frequency and intensity of EHP in the CYA significantly (p≤0.05) increased from 2004 to 2020, especially in urban areas. The increasing rate in urban areas was higher than that in rural areas. However, the duration of EHP/hourly total precipitation exhibited a significant/nonsignificant decreasing trend with no significant difference between urban and rural areas. Causality tests and geo-detector indicated that EHP was impacted by natural variability and urbanization. Large-scale circulation indices such as the Pacific Decadal Oscillation, El Niño-Southern Oscillation, and Indian Ocean Dipole nonlinearly influenced EHP. Additionally, urban landscape layout, vegetation, and population variation may strengthen EHP by changing environmental factors such as temperature and relative humidity. Interactions exist between these factors and influence EHP, although large-scale circulation remains the dominant influence. With global climate warming and rapid urbanization in the CYA, the frequency and intensity of EHP may further amplify in the future.

Understanding the local ecological security status and its underlying drivers can be used as an effective reference for balancing ecosystem development with societal needs. This study assesses the ecological security of the Loess Plateau (LP) by integrating ecosystem health and ecosystem services, explores the varying impacts of ecosystem structure, quality, and services on ecological security index (ESI), and identifies the key driving factors of ESI using the Geodetector model. The results show that: (1) the average ESI indicates a relatively safe ecological status in LP with a significant increase in ESI observed in 50.21% of the region, largely due to the ecological restoration programs. (2) Natural factors predominantly influence ESI, although human factors play a significant role in the earthy-rocky mountain region and plateau wind-sand region. (3) The interactions between driving factors have a much greater impact on ESI than any single factor, with the interactions between precipitation and human factors being the most influential combination. This study provides a novel perspective on assessing ecological security in LP. We recommend that future ecological restoration efforts should consider the varying roles of ecosystem structure, quality, and services in ESI while tailoring strategies to the primary driving factors based on local conditions.

Rural development is an important part of national development in China. However, the lack of rural development degree (RDD) changes and divergence analyses limited our understanding for how to promote rural development in different regions. Therefore, this work introduced a rural development assessment index and equal weighting system, consisting of five dimensions and 25 indicators, to investigate provincial RDD and changes in 2015 and 2021. The results showed that national RDD increased from 0.403±0.066 in 2015 to 0.486±0.054 in 2021 and the scores for each of the five dimensions also improved. China’s rural areas had a good development foundation, but rural industrial prosperity and wealthy lifestyle were lagging. Targeted rural development policies promoted provincial-level increases in these dimensions. The RDD top-ranked provinces were mainly in eastern China. Most of the bottom-ranked provinces were in central and western China. The top-ranked provinces usually had three or four strong dimensions that supported regional rural development. However, weak performances in all dimensions were usually observed in the bottom-ranked provinces, which limited RDD improvements. The bottom-ranked provinces are encouraged to improve their ecological livability, effective governance, and wealthy lifestyle.

Regional development strategies that align with urban characteristics and the scientific allocation of construction land indicators can effectively guide the high-quality coordinated development of urban agglomerations. However, the issue of whether urbanization matches the development strategy has always lacked an in-depth response in geography. Moreover, along with the urbanization process, the land limitation for agricultural and ecological spaces becomes increasingly strict, and the availability of construction land indicators is increasingly constrained. The construction land allocation is thus critical for the distribution of regional resources and the development goals of urban agglomeration. Based on the principles of development geography and the core-periphery theory, this study comprehensively considered three subsystems of urbanization (population, economy, and land) and the spatial link intensity among cities within a certain region to analyze the impacts of “siphon” and “radiation” effects on regional development, and assessed whether China’s two major regional urbanization strategies aligned the comprehensive development characteristics. Furthermore, the quantitative construction land allocation in Beijing-Tianjin-Hebei (BTH) and Yangtze River Delta (YRD) urban agglomerations was completed. The results showed that the urban comprehensive level index (UCL) in core cities (Beijing and Tianjin) and peripheral cities differed significantly in BTH, demonstrating a clear core-periphery structure. Along with urbanization, the “siphon” effect in BTH was weakening. Beijing’s urban primacy decreased and the growth rate of UCL decreased from 53.89% in the first five years to 18.37% in the last five years during the study period (2020-2019). In contrast, the “radiation” effect in YRD was more obvious, exhibiting a development pattern driven by multiple growth poles. Temporally, the BTH indicated a coordinated development trend, while the integration level of YRD continued to strengthen. Compared to the top-down construction land allocated by the government, the results of quantitative allocation in this study reduced volatility. This study confirms the scientific basis of the coordinated development for BTH and the integrated regional development strategy for YRD from the perspective of development geography. It also provides a practical reference for the construction land allocation.

The Taihang Mountains in North China are an important carbon-water ecosystem service supply area. Understanding the coupling effect and influencing mechanisms of mountain carbon sequestration as well as water conservation is essential for regional ecological restoration and sustainable development. In this study, we utilized models such as the coupled coordination degree model, the random forest and Geodetector to analyze the spatio-temporal changes as well as driving factors of carbon sequestration-water conservation coupling coordination in the Taihang Mountains. The results show that: (1) From 1990 to 2020, the carbon sequestration and water conservation capacity of the Taihang Mountains exhibited a spatial pattern with higher values in the southeast and central regions, while lower values in the northwest region. (2) The average coupling coordination degree from 1990 to 2020 was 0.23, which was overall low, with a fluctuating decreasing-rising-decreasing trend over time. The coupling coordination degree exhibited a pattern that is high in the middle and low in the periphery, with a fluctuating distribution that initially decreases and then increases with the increasing altitude. The overall trend of coupling coordination is degradation, with concentrated degradation in the northwest mountainous regions. (3) Precipitation and soil texture were identified as the main driving factors influencing coupling coordination, with the interaction between precipitation and soil sand content showing the strongest explanatory power, while that among topography, vegetation and human activities had relatively low explanatory power. Therefore, enhanced protection and the continuous monitoring of vegetation and soil environments in the Taihang Mountains are essential, with particular emphasis on ecological restoration in areas experiencing a persistent degradation of carbon-water coupling. This study can provide assistance in monitoring and managing carbon sink and water resources in the mountains, meanwhile mitigating potential adverse impacts on human well-being.

This paper selects sampling sections for the mainstream and tributaries of the middle and lower reaches of the Yellow River, collects river water and sediment samples during the flood season for pollen analysis, and uses methods such as Geodetector to explore the distribution characteristics and influencing factors of pollen. The results show significant variations in vegetation composition across different watersheds, leading to notable differences in both the percentage and concentration of pollen types. Pollen concentration in river water is generally higher in the mainstream compared to tributaries, while sediment pollen percentage and concentration are typically lower in the mainstream than in tributaries. The concentration of suspended solids is the most significant factor affecting pollen concentration in the Yellow River, with this effect being particularly prominent outside the Shanxi-Shaanxi Gorge. Abundant coarse sand and rapid flow velocities are likely responsible for the high suspended solids concentration and lower pollen concentration observed in the mainstream of the Shanxi-Shaanxi Gorge. In sediments, clay content is the primary factor influencing pollen concentration, and its interaction with silt and flow velocity has a more prominent influence on pollen concentration. At the Yellow River section below the Shanxi-Shaanxi Gorge, sediment pollen and clay concentrations significantly increase. The changes in pollen concentration in the river water before and after the reservoir are consistent with the suspended solids concentration, while the changes in sediment pollen concentration are consistent with the clay content. Notably, pollen concentrations in sediments decrease more significantly after passing through a reservoir compared to changes observed in river water samples. Overall, there is a strong correlation between river pollen and topsoil pollen, which can provide a reliable reflection of the broader vegetation landscape of the watershed. The findings can provide support for paleoenvironmental reconstruction using pollen from alluvial sediments or lakes with river inflows.

A macro-tidal tropical estuary with high fluvial discharge is characterized by both fragility and remarkable dynamism. This study utilizes the Salween River Delta (SRD) as a case example to examine the interplay between morphology and vegetation under similar tidal conditions. Our analysis of correlations and inferences revealed several significant trends in the SRD: (1) an overall expansion of land area and intertidal vegetation, with the most pronounced changes occurring in the eastern sector; (2) the predominance of river discharge influencing the southwestern and northern sectors, contrasted with the primary impact of storm surges in the eastern sector; and (3) three distinct causal relationships among estuarine morphology, vegetation, storm surges, and river discharge: a direct model where river discharge shapes estuarine morphology, a progressive model in which river discharge affects vegetation distribution, subsequently influencing estuarine morphology, and a hybrid model where storm surges directly impact vegetation and indirectly modify its distribution through changes in estuarine morphology. The stability of sediment supply and the role of intertidal vegetation are crucial for the continuous seaward advance, providing a vital foundation for the protection and development of estuarine deltas.

Population growth leads to increased utilization of water resources. One of these resources is groundwater, which has steadily declined each year. The depletion of these resources brings about various environmental challenges. The present study aimed to explore the relationship between groundwater fluctuations and land subsidence in the Malayer Plain, Iran, focusing on quantifying subsidence resulting from groundwater extraction. Using Sentinel-1 satellite data (2014-2019) and monthly piezometric measurements (1996-2018), the analysis revealed an average deformation velocity of -6.3 cm yr^-1, with accumulated subsidence of -32 cm over the 2014-2019 period. The maximum subsidence rate reached 10.3 cm yr^-1 in areas of intensive agricultural activity. A wavelet-PCA spatiotemporal analysis of groundwater fluctuations identified critical multi-scale patterns strongly correlated with subsidence trends. Regression analysis between subsidence rates and groundwater fluctuations at various wavelet decomposition levels explained 75% of the variance (R² = 0.75), indicating that intermediate-scale groundwater declines were the primary drivers of subsidence. Furthermore, land use analysis using Landsat data (1999-2021) revealed a 6230-ha increase in irrigated farmland, contributing to heightened groundwater extraction and subsidence rates. These findings highlight the critical need for sustainable groundwater management to mitigate the risks of continued subsidence in the region.

The Hengduan Mountains region (HMR) is one of the most densely distributed and severe flash flood disaster-prone areas in southwest China. It is also a key area for major engineering projects and beautiful countryside construction in Southwest China. However, previous studies have not systematically summarized the development characteristics and formation modes of flash flood disasters in the HMR, which limits the development of theoretical and technical system for flood control. In this study, we focused on the physical processes of flash flood disasters in the HMR, including generation, movement, and disaster formation, and clarified the dominant disaster-inducing conditions (multiple humid monsoon circulation, high potential energy and high heterogenous underlying surface) and disaster development characteristics (high spatio-temporal heterogeneity, highly concentrated energy, chain and cascading effects, and clustered occurrence) of flash floods in the HMR. Based on the entire processes of flash flood disasters, three major formation modes have been summarized: the runoff generation mode of vegetation-hydrology-soil coupling dominated by high hydraulic gradient in mountainous areas, strong flow-sediment coupling movement, and serious disaster losses due to high exposure of disaster bearing objects. Finally, based on the issues in previous research, four future research challenges for flash flood disaster in the HMR were proposed. Our study provides insights into disaster prevention and reduction research, including fundamental theoretical system, precise risk assessment of regional disasters, and accurate early warning and forecasting of flash floods.

Urban environments offer a wealth of opportunities for residents to respite from their hectic life. Outdoor running or jogging becomes increasingly popular of an option. Impacts of urban environments on outdoor running, despite some initial studies, remain underexplored. This study aims to establish an analytical framework that can holistically assess the urban environment on the healthy vitality of running. The proposed framework is applied to two modern Chinese cities, i.e., Guangzhou and Shenzhen. We construct three interpretable random forest models to explore the non-linear relationship between environmental variables and running intensity (RI) through analyzing the runners’ trajectories and integrating with multi-source urban big data (e.g., street view imagery, remote sensing, and socio-economic data) across the built, natural, and social dimensions, The findings uncover that road density has the greatest impact on RI, and social variables (e.g., population density and housing price) and natural variables (e.g., slope and humidity) all make notable impact on outdoor running. Despite these findings, the impact of environmental variables likely change across different regions due to disparate regional construction and micro-environments, and those specific impacts as well as optimal thresholds also alter. Therefore, construction of healthy cities should take the whole urban environment into account and adapt to local conditions. This study provides a comprehensive evaluation on the influencing variables of healthy vitality and guides sustainable urban planning for creating running-friendly cities.

While algorithms have been created for land usage in urban settings, there have been few investigations into the extraction of urban footprint (UF). To address this research gap, the study employs several widely used image classification method classified into three categories to evaluate their segmentation capabilities for extracting UF across eight cities. The results indicate that pixel-based methods only excel in clear urban environments, and their overall accuracy is not consistently high. RF and SVM perform well but lack stability in object-based UF extraction, influenced by feature selection and classifier performance. Deep learning enhances feature extraction but requires powerful computing and faces challenges with complex urban layouts. SAM excels in medium-sized urban areas but falters in intricate layouts. Integrating traditional and deep learning methods optimizes UF extraction, balancing accuracy and processing efficiency. Future research should focus on adapting algorithms for diverse urban landscapes to enhance UF extraction accuracy and applicability.

China is the world’s largest carbon dioxide (CO₂) emitter and a major trading country. Both anthropogenic and natural factors play a critical role in its carbon budget. However, previous studies mostly focus on evaluating anthropogenic emissions or the natural carbon cycle separately, and few included trade-related (import and export) CO₂ emissions and its contribution on global warming. Using the CarbonTracker CT2019 assimilation dataset and China trade emissions from the Global Carbon Project, we found that the change trend of global CO₂ flux had obvious spatial heterogeneity, which is mainly affected by anthropogenic CO₂ flux. From 2000 to 2018, carbon emissions from fossil fuels in the world and in China all showed an obvious increasing trend, but the magnitude of the increase tended to slow down. In 2018, the radiative forcing (RF) caused by China’s import and export trade was ‒0.0038 W m^‒2, and the RF caused by natural carbon budget was ‒0.0027 W m^‒2, offsetting 1.54% and 1.13% of the RF caused by fossil fuels that year, respectively. From 2000 to 2018, the contribution of China’s carbon emission from fossil fuels to global RF was 11.32%. Considering China’s import and export trade, the contribution of anthropogenic CO₂ emission to global RF decreased to 9.50%. Furthermore, taking into account the offset of carbon sink from China’s terrestrial ecosystems, the net contribution of China to global RF decreased to 7.63%. This study demonstrates that China’s terrestrial ecosystem and import and export trade are all mitigating China’s impact on global anthropogenic warming, and also confirms that during the research process on climate change, comprehensively considering the carbon budget from anthropogenic and natural carbon budgets is necessary to systematically understand the impacts of regional or national carbon budgets on global warming.

Carbon fluxes are essential indicators assessing vegetation carbon cycle functions. However, the extent and mechanisms by which climate change and human activities influence the spatiotemporal dynamics of carbon fluxes in arid oasis and non-oasis area remains unclear. Here, we assessed and predicted the future effects of climate change and human activities on carbon fluxes in the Hexi Corridor. The results showed that the annual average gross primary productivity (GPP), net ecosystem productivity (NEP), and ecosystem respiration (Reco) in the Hexi Corridor oasis increased by 263.91 g C·m^-2·yr^-1, 118.45 g C·m^-2·yr^-1 and 122.46 g C·m^-2·yr^-1, respectively, due to the expansion of the oasis area by 3424.84 km² caused by human activities from 2000 to 2022. Both oasis and non-oasis arid ecosystems in the Hexi Corridor acted as carbon sinks. Compared to the non-oasis area, the carbon fluxes contributions of oasis area increased, ranging from 10.21% to 13.99% for GPP, 8.50% to 11.68% for NEP, and 13.34% to 17.13% for Reco. The contribution of the carbon flux from the oasis expansion area to the total carbon flux change in the Hexi Corridor was 30.96% (7.09 Tg C yr^-1) for GPP, 29.57% (3.39 Tg C yr^-1) for NEP and 32.40% (3.58 Tg C yr^-1) for Reco. The changes in carbon fluxes in the oasis area were mainly attributed to human activities (oasis expansion) and temperature, whereas non-oasis area was mainly due to climate factors. Moreover, the future increasing trends were observed for GPP (64.99%), NEP (66.29%) and Reco (82.08%) in the Hexi Corridor. This study provides new insights into the regulatory mechanisms of carbon cycle in the arid oasis and non-oasis area.

Accurate spatio-temporal land cover information in agricultural irrigation districts is crucial for effective agricultural management and crop production. Therefore, a spectral- phenological-based land cover classification (SPLC) method combined with a fusion model (flexible spatiotemporal data fusion, FSDAF) (abbreviated as SPLC-F) was proposed to map multi-year land cover and crop type (LC-CT) distribution in agricultural irrigated areas with complex landscapes and cropping system, using time series optical images (Landsat and MODIS). The SPLC-F method was well validated and applied in a super-large irrigated area (Hetao) of the upper Yellow River Basin (YRB). Results showed that the SPLC-F method had a satisfactory performance in producing long-term LC-CT maps in Hetao, without the requirement of field sampling. Then, the spatio-temporal variation and the driving factors of the cropping systems were further analyzed with the aid of detailed household surveys and statistics. We clarified that irrigation and salinity conditions were the main factors that had impacts on crop spatial distribution in the upper YRB. Investment costs, market demand, and crop price are the main driving factors in determining the temporal variations in cropping distribution. Overall, this study provided essential multi-year LC-CT maps for sustainable management of agriculture, eco-environments, and food security in the upper YRB.

Changes in production-living-ecological spaces (PLES) profoundly affect the global carbon cycle, further challenging socio-ecological system sustainability. However, the impacts of PLES changes on carbon balance have been insufficiently discussed under a spatial heterogeneity perspective, resulting in an inadequate understanding of green development. This paper quantified the dynamics of PLES using the transfer matrix method and assessed the carbon balance computed by the ecological support coefficient of carbon emissions (ESC) in Shandong province from 2000 to 2020. The impacts of PLES changes on ESC were further investigated using a geographically weighted regression model. On this basis, carbon balance zones were delineated through cluster analysis. The results indicated that both production and ecological spaces decreased while the living space increased during 2000-2020. Carbon emissions increased and its sequestration decreased. As a result, ESC initially increased and then decreased, exhibiting apparent spatial clustering. The impact of different PLES transfer changes on ESC varies across county sites, with production→living space having the most significant impact on regional ESC and ecology→living space having the most negligible impact. Finally, six types of carbon balance zones were established to reduce carbon emissions. The findings are expected to support policy implementations for reducing carbon emissions and optimizing territorial development through low-carbon land use.

This study explores the impact of intergenerational differences on farmers’ terrace abandonment in response to increasing intergenerational differentiation among rural households and the practical issue of terrace abandonment. Logit and Tobit models are employed to conduct empirical analysis and it is found that terrace abandonment increases sequentially among the new, middle, and old generations, confirming that intergenerational differences significantly influence whether farmers abandon terraces and the terrace abandonment scale. Village characteristics and government subsidies significantly influence farmers’ terrace abandonment. An increase in the number of migrant workers in the village increases terrace abandonment among new and middle generation farmers, whereas an increase in the distance from the village to the county significantly increases terrace abandonment among old generation farmers. An increase in the village’s total population significantly reduces terrace abandonment among new generation farmers. An increase in government subsidies significantly reduces terrace abandonment among middle and old generation farmers. The impact of intergenerational differences on terrace abandonment is more pronounced in low-altitude areas. To reduce terrace abandonment, it is necessary to promote terrace transfer, develop characteristic agriculture, improve terrace farming subsidies, and propose targeted strategies for the different generations of farmers.

Social networks are vital for building the livelihood resilience of rural households. However, the impact of social networks on rural household livelihood resilience remains empirically underexplored, and most existing studies do not disaggregate social networks into different dimensions, which limits the understanding of specific mechanisms. Based on 895 household samples collected in China’s Dabie Mountains and structural equation modeling, this paper explored the pathway to enhance livelihood resilience through social networks by disaggregating it into five dimensions: network size, interaction intensity, social cohesion, social support, and social learning. The results indicate that: (1) Livelihood assets, adaptive capacity and safety nets significantly contribute to livelihood resilience, whereas sensitivity negatively affects it. Accessibility to basic services has no significant relationship with livelihood resilience in the study area. (2) Social networks and their five dimensions positively impact livelihood resilience, with network support having the greatest impact. Therefore, both the government and rural households should recognize and enhance the role of social networks in improving livelihood resilience under frequent disturbances. These findings have valuable implications for mitigating the risks of poverty recurrence and contributing to rural revitalization.

Agriculture, significantly impacted by climate change and climate variability, serves as the primary livelihood for smallholder farmers in South Asia. This study aims to examine and evaluate the factors influencing smallholder farmers’ adaptive capacity (AC) in addressing these risks through surveys from 633 households across Nepal, India, and Bangladesh. The findings reveal that AC is influenced by various indicators categorized under eight principal factors. The first three factors, which explain about one-third of the variance in each country, include distinct significant indicators for each nation: in Nepal, these indicators are landholding size, skill-development training, knowledge of improved seed varieties, number of income sources, access to markets, and access to financial institutions; in India, they encompass access to agricultural-input information, knowledge of seed varieties, access to markets, access to crop insurance, changing the sowing/harvesting times of crops, and access to financial services; in Bangladesh, the key factors are access to financial institutions, community cooperation, changing the sowing/harvesting times of crops, knowledge of improved seed varieties, and access to agricultural-input information. Notably, indicators such as trust in weather information, changing sowing/harvesting times of crops, and crop insurance were identified as important determinants of AC, which have been overlooked in previous studies.

The perfection of the cross-border regional innovation system of the Pearl River Delta (PRD) and Hong Kong remarkably underpins the construction of the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) towards an international technological innovation hub. This paper focuses on the relational characteristics of the usage of technological innovation functions and elements, including labor force, technology, and producer services from Hong Kong by high-technology firms in the PRD, and probes into the influencing factors by integrating the objective perspective on the impact of firm-level socioeconomic attributes and subjective perspective on the open interpretations on the reasons by using or not using technological innovation functions and elements from Hong Kong by various stakeholders in high-technology domains in the PRD. Key research findings are fourfold. First, Hong Kong’s technological innovation functions primarily ride on its institutional advantages under the “One Country, Two Systems” framework to empower high-technology firms in the PRD by expanding their international market, international business operation, and financing, but cross-border investment and entrepreneurship has retrieved to a relatively marginalized position. The degree of supply-demand relations of producer services is the highest, followed by labor force and technology. Second, Hong Kong-invested, large-sized, and long-standing high-technology firms in the PRD are more inclined to use technological innovation elements from Hong Kong, while domestic, small-and-medium-sized, and start-up high-technology firms in the PRD are in turn, gradually unhooked from the supply of technological innovation elements from Hong Kong. Third, Hong Kong enjoys both advantages and disadvantages in supplying labor forces, technologies, and producer services to high-technology firms in the PRD, with advantages in competitiveness, international linkages and visions, and disadvantages in high cost, lack of more profound mutual understanding between Hong Kong and the PRD, and the imperfect cooperation mechanisms. Fourth, interactions among the transitioning role of Hong Kong in the macro-level global and national economic development landscape, meso-level cross-border regional specificities under the “One Country, Two Systems” framework, and micro-level heterogeneous practices and capabilities of firms influence the usage of technological innovation functions and elements from Hong Kong by high-technology firms in the PRD.

Globalization has resulted in a notable rise in the flow of high-skilled talent from emerging countries to developed nations. Current research on transnational talent flow mainly focuses on the destination countries, with less attention given to the perspective of the sending countries, particularly lacking a dynamic discussion on its impact on technological evolution in the origin countries. Based on the OECD REGPAT database, this paper aims to explore how talent groups migrating to developed countries facilitate the return of knowledge and technology to emerging countries and achieve breakthroughs in their technological evolution paths, while further discussing the potential mechanisms involved. The findings of this paper are as follows: (1) The technological development of emerging countries is a path-dependent process, where countries often branch into new technologies related to their preexisting knowledge base. Consequently, knowledge feedback from high-skilled talents increases the likelihood of sending countries developing unrelated technologies. (2) The mobility of talents across borders fosters more international collaborations and citations for patents that are unrelated to the local knowledge base, thus enriching the technological paths of sending countries. (3) The mobility of high-skilled talents primarily affects complex technologies, which have significant economic effects that encourage imitation by other countries. However, the effect on novel technologies is less significant due to their strong geographical stickiness. In general, this paper addresses the gaps in existing research on talent outflow and the technological evolution of origin countries, providing empirical evidence for the positive role of transnational talent mobility in the technological catch-up of emerging nations. Besides, it offers recommendations for talent export, import, and innovation policy formulation in these countries.

An appropriate spatial structure of a power battery supply network is crucial for the specialization and scale development of key components in new energy vehicles, accelerating the transformation and upgrade of the industry. This paper investigates the cooperative relationships among supply chain enterprises from the perspective of complex networks. Employing methodologies such as the gravity model and Moran’s I analysis, it explores the spatial structural characteristics and correlation patterns of the power battery supply network in China and discusses the influencing factors using the quadratic assignment procedure, revealing the mechanisms behind the differences in the spatial distributions of the power battery supply network. The results indicate that the distribution of power battery enterprises is densely concentrated in the eastern and southern regions, whereas the western region has a sparse distribution. The spatial supply network consists of a four-tier linkage system, encompassing 135 prefecture-level cities, with Chongqing, Shanghai, Nanjing, and other cities particularly prominent. Overall, the degree of agglomeration is low, with coastal cities dominating the landscape and inland cities serving as complementary regions. Most areas are characterized as insignificant or low-high regions, and the regional linkage effect of core cities is not pronounced. There is a notable lack of significance and high spatial heterogeneity. Four types of factors—spatial factors, market factors, agglomeration economies, and innovation levels—jointly influence and shape the spatial structure of the power battery supply network.