In the context of global change, a central challenge in ecology is to establish the multi-scale evolution and coupling mechanisms of ecosystems. In particular, it is necessary to clarify the structural mismatch between hierarchical levels that arises when ecological networks (ENs) are constructed across varying extents or grains. Using city- and central urban-level examples, we introduced a cross-level ENs spatial mismatch measurement index (SMI) and a scale-effect analysis framework. Five representative cities from the Northeast, Northwest, Central, Southwest, and Southeast China were selected as research areas. A unified approach combining minimum cumulative resistance and XGBoost models enable the preliminary construction of two-level ENs. SMI is then applied to evaluate cross-level mismatches, followed by analysis of extent and grain effects. Mechanisms underlying EN disconnection and potential solution pathways are further examined. The results show that: (1) spatial mismatch indicators (SMI_source, SMI_corridor, SMI_nodes) defined on ecological source areas (ESA), corridor, and strategic nodes, reflect mismatch degrees across EN levels; (2) scale effects reveal decreasing SMI with expanding observation extent in central urban area, fluctuating values with synchronous change in data grain, and increasing values with higher statistical grid density; (3) the largest patch index and landscape division index exert a strong influence on SMI_source, while patch number and Shannon’s diversity index play key roles in SMI_corridor; and (4) variation in landscape composition and configuration heterogeneity across scales provides explanatory power of mismatch phenomenon and scale effects. The study contributes to ecological pattern analysis by offering a quantitative method for multi-scale EN research, with implications for ecological protection and regional landscape planning.
This article examines the role of transnational infrastructure in the production of state power, and advances an understanding of human-nonhuman assemblage as the power agency. Drawing on the assemblage perspective, this paper aims to decipher the shape and materialization of transnational infrastructure through a case study of the China-Laos Railway project. This paper empirically sets up the socio-material process of a transnational multi-actor railway assemblage and its state power dynamics, arguing that it functions as a “strategic coupling” of bilateral interests under the Belt and Road Initiative. Along with the China Railway Machine and a multitude of railway-related agencies and activities, the study identifies non-human agents (land and railway equipment) intertwined in the ongoing assemblage formation and deploying state power as the railway project materializes. In doing so, observations suggest the transnational infrastructure territorialization and reconfiguration of the power assemblage under the BRI could be viewed within a broad, dialectical, and relational perspective. Furthermore, the study illustrates the temporality and spatiality of the transnational railway assemblage during the railway operation phase. Finally, this paper calls for comparing and exploring variegated transnational connectivity infrastructuralism from a grounded, and balanced milieu of human and non-human assemblage perspective.
The Qilian Mountains (QLMs) are a critical ecological security barrier and water conservation region in northwestern China, which support regional climate regulation and ecosystem stability. However, climate change-induced variabilities in vegetation dynamics can threaten these functions. Although vegetation–climate relationships have been widely examined, the sensitivity and ecological risks of QLM vegetation to growing-season drought extremes remain poorly understood. In this study, we applied the Carnegie–Ames–Stanford Approach (CASA) to estimate net primary productivity (NPP) during the main growing season (May–August) across the QLMs from 1990–2022. Spatiotemporal variations in NPP were analyzed using the Mann-Kendall test and Theil-Sen slope estimator. Vegetation sensitivity and ecological risk were quantified using linear regression slopes between NPP and the standardized precipitation evapotranspiration index (SPEI), and temporal changes in sensitivity were assessed using a three-year moving window. Additionally, vegetation resistance and resilience to drought extremes were calculated for different vegetation types. The results showed that both NPP and SPEI in the QLMs exhibited significant upward trends over the study period. Approximately 12.7
Global agricultural expansion into marginal land, coupled with rapid urbanization, leads to cropland redistribution worldwide. This process is especially ubiquitous in China, where fragmented policy frameworks during its early development stage accelerated cropland redistribution. However, the integrated assessment of cropland redistribution, particularly in terms of its impacts, remains understudied. To address this gap, this paper employed the GAEZ and InVEST models to investigate the qualitative and ecological impacts of cropland redistribution in China. The results demonstrated that: (1) From 2000 to 2020, cropland redistribution across provinces exhibited significant spatial homogeneity, with a gross loss of 30.90 Mha partially offset by a gross gain of 24.47 Mha. (2) Most provinces lacked balanced cropland productivity, as the average productivity of cropland gains (2.07×105 t/km2) is much lower than that of cropland losses (2.91×105 t/km2); (3) Cropland redistribution led to a net decline in ecosystem services, despite cropland gains exhibit higher average values in carbon storage, habitat quality, and soil conservation than cropland losses; (4) While cropland redistribution often causes ecological degradation, there are co-benefits observed between cropland quality and ecology in some cases. These variations suggest that ecological degradation owing to cropland redistribution can be mitigated and moderated by other factors. Region-specific policy instruments are, therefore, crucial to maintaining cropland productivity and preventing further ecological degradation.
Ten landscape regions (LSRs) can be distinguished on the Tibetan Plateau (TP) based on distinct climatic and geomorphic characteristics as well as the processes and landforms on the basis of literature review, fieldwork and satellite images. These LSRs are influenced by permafrost, aeolian processes (including loess) and Pleistocene processes. The highest glacier region (LSR 1) and the nivation and the periglacial zones (LSRs 2 and 3) are related to moisture and temperature. At lower altitudes on the eastern margin LSR 4, characterized by moderate processes, dominates while steppe gorges (LSR 6) are widespread in the semiarid northeastern parts. Braided and torrential river systems (LSR 5) dominate the subtropical regions below ∼4000 m in the southern and eastern parts of the TP. Pediments and alluvial fans (LSR 7) and arid to hyperarid LSRs 8–10 are more common in the Qaidam Basin and along the northern margin. Several landforms and sediments provide evidence of the Pleistocene extent of the LSRs. Considering the effects of climate on past and present geomorphological processes in the different altitudinal belts of the TP can support the development of more comprehensive landscape models. This process-based approach links the analyses of both ecozonal systems and human disturbance.
The Yunnan–Vietnam Railway Transportation Corridor serves as the foundation for regional cooperation between China and Vietnam. On the basis of the statistical data and OpenStreetMap, methods such as the coupled coordination degree model were employed in this study to analyze the spatiotemporal characteristics of the coupled coordination degree of the Yunnan–Vietnam Corridor’s transport–economy–society (TES) composite system from 2013 to 2022. The results indicate the following. (1) The transportation corridors are multielement composite systems whose development is the result of a formation mechanism referred to as the “transportation trunk line–transportation network–composite system.” (2) The comprehensive level of development of the Yunnan–Vietnam Corridor has steadily improved, and the transportation subsystem is a significant contributor to this improvement. (3) The degree of coupling coordination of the corridor has shifted from mild imbalance to moderate imbalance, indicating that coordinated development remains far from realized. (4) The coupling coordination of the corridor is divided into three tiers, exhibiting a point-axis development trend and a dumbbell-shaped pattern. In the future, efforts should be made to accelerate the construction of an efficient Yunnan–Vietnam Railway trunk line and transportation network, and optimize the coordination level and pattern of the corridor.
This study investigates microblade technology across the Qinghai-Tibet Plateau and the Loess Plateau since the Last Glacial Maximum, aiming to reconstruct its dispersal routes, ecological adaptations, and connections to climatic and environmental changes. By integrating the MaxEnt ecological niche model, GIS-based spatial analysis, typological studies of lithic artifacts, and least-cost path analysis, we systematically reconstructed the diffusion processes and habitat suitability for microblade-using populations between 24–6 ka BP. The results reveal that (1) microblade technology spread progressively from the Loess Plateau to the northeastern margin and further into the interior of the Qinghai-Tibet Plateau, demonstrating a phased expansion from east to west and from low to high altitudes; (2) the dominant environmental factors influencing distribution shifted over time: the mean temperature of the coldest quarter was the primary limiting factor during 24–18 ka BP and 18–12 ka BP (contributing 69.6
A systematic quantification of the embodied clean energy footprint in global supply chains is essential for optimizing renewable energy utilization and facilitating low-carbon transitions. However, existing research lacks a comprehensive analysis of clean energy flows, particularly with respect to value chain positions and driving mechanisms. This study develops an integrated framework that combines multi-regional input-output (MRIO) models and value chain decomposition to trace the spatiotemporal evolution of the embodied clean energy footprints across 42 major economies from 2006 to 2016, clarify their differentiated positions in global supply chains, and identify key drivers using structural decomposition analysis (SDA). The results indicate that the global embodied clean energy footprints increased by 12.66 million TJ between 2006 and 2016, exhibiting a distinct South-to-North flow pattern from resource-rich developing economies to industrialized developed economies, with the Asia-Pacific region, especially China, emerging as the primary growth pole. Value chain analysis indicates that low and middle-income economies exhibit strong coupling between domestic clean energy use and value added, thereby embedding themselves in medium and low-tier supply chain segments, whereas high-income economies show mechanistic decoupling and diversified pathways, some of which suffer from external dependence and inefficiency. SDA identifies clean energy intensity and changes in domestic and foreign demand as the core drivers, while technology spillovers and policy shifts exert heterogeneous effects. This study reveals value chain fragmentation, technological disparities, and regional imbalances in global clean energy supply chain, thereby providing quantitative evidence to support differentiated green trade and energy transition policies.
For ecotourism destinations, it is critical to balance rapid urban expansion with ecological protection. Focusing on the National Ecotourism Collaborative Zone in southeastern China, this study constructs an integrated analytical framework encompassing “scale-density-morphology” to characterize urban land dynamics. By employing two-step cluster analysis and Geographical Detector models, we identified distinct spatial pattern typologies and quantified the individual and interactive effects of natural, socio-economic, and tourism-specific drivers. Results reveal that urban land expanded dramatically from 4698.85 km2 in 2000 to 10,204.88 km2 in 2023. Concurrently, the number of cities exhibiting high Aggregation Index (AI>75) increased from 4 to 12. The spatial pattern types of the 19 cities can be classified into four categories. Notably, while overall spatial typologies remained relatively stable across cities, the hotspots of urban expansion gradually shifted from tertiary to secondary and primary tourism destinations. Factor detection results show that tourism-related drivers—such as tourism revenue, passenger turnover volume, and tourism resource endowment—exerted growing influence on urban land expansion over time, particularly after 2015. Meanwhile, natural environmental factors increasingly constrained urban form and density. Furthermore, interaction detection shows that the combined effects of natural, socio-economic, and tourism industry factors significantly amplified their individual influences.
Ecological resilience(ER)reflects an ecosystem's capacity to adapt to climate change,natural disturbances,and human-induced stress.This study evaluated ER in the Qinling-Daba Mountains(QDM),China,from 2000 to 2020 using a resistance-robustness-recovery model.Specifically,the PLUS model was employed to assess the impacts of land use change on ER under three scenarios:natural development(NDS),ecological preserva-tion(EPS),and farmland preservation(FPS).Spatial drivers of ER were analyzed using the geographic detector model and multi-scale geographically weighted regression.The results revealed a significant upward trend in ER,with high values in central and southern QDM and low values in urban lowland areas.Regarding the scenarios,ER improved under EPS,plat-eaued under NDS,and declined under FPS.The key drivers were found to be NDVI,slope,DEM,temperature,and nighttime light.ER showed positive correlations with high NDVI and slope and negative correlations with low vegetation and flat terrain.These findings provide deeper insight into ER dynamics and scientific guidance for regional ecological protection,planning,and resilience building in the QDM and similar mountainous ecosystems globally.
Wetland ecosystem services (ES) are influenced in opposite ways by ecological threats and conservation management, yet their combined effects on ES trade-offs and synergies remain largely understudied. To address this, we developed an evaluation indicator system for 1977 Ramsar Sites globally and calculated indices of ES importance (ESI), ecological threat intensity (ETI), and conservation management intensity (CMI) using the extremum value method. Generalized additive models were applied to analyze the nonlinear responses of ES trade-offs and synergies along CMI and ETI gradients. We found that 58.9
Ancient agricultural development has been affected by climate change. The upper Yinghe River draining into the Huaihe River represents an important region for tracing the origins of primitive agriculture in China. To clarify the relationship between primitive agriculture and climate change in this region, optically stimulated luminescence (OSL) dating and physicochemical analyses were performed on a Holocene loess-paleosol PLG profile. The results indicated that paleosol (S0) developed during the mid-Holocene climatic optimum (8500–3100 a BP). The OSL ages of 7220±700 and 6800±400 a were obtained from the lower and middle parts of S0, respectively, and the cultural remains at 70 cm yielded an OSL age of 6890±400 a. These chronological results were consistent with the age of the Peiligang Culture (7800–7300 a BP) during the Neolithic period. In the S0 layer, the fine silt and clay contents and magnetic susceptibility reached their highest values, whereas the higher total organic carbon (TOC) content and lower pH values indicated a warmer and more humid climate. Such favorable hydrothermal conditions promoted weathering and pedogenesis, facilitated S0 formation, and created suitable soil conditions for agricultural development during the Peiligang cultural period. These findings suggest that climate exerted key control on Holocene loess pedogenesis and that Neolithic primitive agriculture was closely associated with the favorable climate and well-developed soils of the mid-Holocene climatic optimum.
Establishing a scientifically sound ecological security pattern (ESP) is essential for maintaining ecological security in arid regions. Although notable progress has been made in the construction of ESP, studies that systematically integrate the trade-offs and synergies between ecosystem services (ESs) supply and demand into the ESP optimization process is still lacking. In arid regions, regional demands for water yield and carbon storage form the core of ecological security, directly influencing ecosystem stability. Thus, we enhanced the evaluation of water yield and carbon storage demands and proposed a novel ESP optimization framework that explicitly incorporates ESs supply-demand trade-offs and synergies. Ecological sources were identified based on both ESs supply and supply-demand trade-offs. Resistance surfaces were optimized using multidimensional factors, and ecological corridors and pinch points were delineated with circuit theory to refine the ESP in the Hexi Corridor. The improved demand evaluation methods for water yield and carbon storage achieved high spatial accuracy. Due to environmental variation and anthropogenic pressures, ESs supply, demand and their interactions showed marked spatial heterogeneity. The ESP optimization framework identified 157 ecological sources, revealed key resistance mechanisms and delineated 196 ecological corridors and 656 pinch points, demonstrating its scientific rigor and spatial validity. An ESP featuring “two belts, three corridors, and four zones” was developed. Targeted optimization strategies were proposed, including source restoration, resistance surface regulation, enhanced corridor connectivity, and multi-scale synergistic restoration. The proposed ESP optimization framework is founded on an intrinsic transmission mechanism linking the regulation of production–living–ecological space demands, the optimization of supply–demand relationships, and the enhancement of ESP. By integrating the restructuring of ESs supply–demand relationships into the ESP optimization process, this framework establishes a targeted optimization pathway for arid regions and promotes a transition in ecological restoration from “passive conservation” to “active regulation”.
Tourism carbon emission efficiency (TCEE) reflects the low-carbon transformation performance of service-oriented regional economies, yet its spatial drivers remain insufficiently understood. Using panel data for 108 prefecture-level cities in the Yangtze River Economic Belt from 2006–2022, this study measures TCEE with a slack-based measure model incorporating undesirable outputs and a Global Malmquist–Luenberger index, and examines the spatial effects of economic restructuring and green technological progress through a spatial Durbin model. The results show that TCEE remains below the efficiency frontier but exhibits a gradual upward trend with pronounced regional disparities. A significant positive spatial dependence indicates that efficiency improvements in one city are associated with those in neighboring cities. Economic structural adjustment—particularly industrial upgrading and energy structure optimization—significantly enhances local TCEE and generates positive spatial spillovers. Urbanization displays a nonlinear relationship with TCEE, characterized by a U-shaped local effect and an inverted U-shaped spillover effect. Green technological progress improves local efficiency, while its spillover effects vary across regions. This study provides empirical evidence that tourism low-carbon transition is jointly shaped by structural transformation and technological progress through spatial interactions. The findings highlight the importance of coordinated regional governance in promoting low-carbon development in large economic belt.
Urbanization has been widely recognized as one of the most important factors af-fecting urban land use,especially in densely populated and ecologically sensitive river basins.Therefore,cities must transition from high-pollution practices to more sustainable land re-source management for socio-economic development.The objective of this study was to fill the knowledge gap regarding the impact of urbanization on urban land green use efficiency(ULGUE)and its regional variations.To achieve this,the Malmquist-Luenberger model and a spatial econometric model were employed to assess ULGUE and examine the spatial corre-lation between urbanization and ULGUE from 2005 to 2022.The analysis was conducted in China's prefecture-level cities in the Yangtze River Economic Belt(YREB)and Yellow River Basin(YRB)regions.The results indicated that the ULGUE of the YREB fluctuated upward,whereas that of the YRB fluctuated downward,with cities along the rivers exhibiting higher efficiency was higher.The spatial distribution characteristics of urbanization rates in the two basins demonstrated that the Heihe-Tengchong Line serves as a dividing line for urbanization levels.In addition,the spatial relationship between urbanization and ULGUE exhibited sig-nificant heterogeneity across different basins and cities of varying sizes.These findings in-form decision-making for sustainable urban development in river basins.
People-oriented new-type urbanization emphasizes the synergistic improvement of level and quality.This study,based on a quantity-quality synergy perspective,constructs a unified theoretical framework integrating these two dimensions.Focusing on the Yangtze River Economic Belt(YREB)from 2000 to 2022,this study comprehensively examines its new-type urbanization using methods including the entropy method,kernel density estimation,and a synergy evolution model,with driving mechanisms revealed by a Geodetector.The results indicate that:(1)Both the urbanization level and quality in the YREB have continu-ously increased,with the level rising from 32.54 to 61.64 and the quality from 43.47 to 67.93.However,the urbanization level remains below the national average and exhibits significant regional disparities.(2)The spatial pattern reveals a hierarchical gradient characterized by"downstream leading,midstream in the middle,and upstream lowest".While central cities demonstrate radiating effects,siphoning effects persist in major southwestern cities,and the northern downstream area lags behind.(3)The synergistic evolution of urbanization level and quality significantly improved,transitioning from a polarized state of"quality lag"and"level imbalance"towards coordinated development.(4)The urbanization development patterns have shifted from extensive to optimal and imbalanced types.The downstream region is dominated by the optimal type,while the midstream and upstream areas primarily exhibit the imbalanced pattern,highlighting a significant potential for level improvement.(5)New-type urbanization in the YREB is driven by the synergistic effects of natural endowment,govern-ment regulation,and market adjustment,forming a tripartite system where"Innovation+"plays a particularly crucial role.This research provides a scientific basis for promoting new-type urbanization construction and high-quality development.
Understanding the spatial network structures and heterogeneous driving factors of urban ecological resilience (UER) is essential for effective regional collaborative governance, yet it is often overlooked in traditional assessments. Focusing on the Yellow River Basin (YRB), this study constructs an evaluation system for UER based on the “Absorption-Resistance-Renewal” framework. Specifically, it explores the network spatial connections and the network spatial structures of UER among cities by combining social network analysis. Subsequently, the spatially constrained hierarchical clustering algorithm is used to integrate complex networks into the zoning system. Furthermore, a comprehensive analysis of the factors affecting UER is conducted using an interpretable machine learning method. The results show that: (1) The UER in the YRB exhibits an inverted U-shaped trend, first increasing and then decreasing. There are significant disparities at both the city and provincial levels, with substantial internal differences and a more scattered distribution in cities of Shanxi and Shaanxi. (2) The classification of UER in the YRB shows a clear change in levels, with 45.76
Grasslands cover 25％of global land,and provide 20％of human dietary protein and store over 30％of terrestrial carbon.There has been a substantial amount of research on the topic of grassland ecosystem services(GES).However,existing reviews primarily focus on the spatiotemporal changes in the quantity of these services,lacking a comprehensive global discussion on service variations,driving factors,and mitigation strategies.This study employs a combined approach of empirical analysis and systematic review to analyze 534 peer-reviewed publications indexed in Web of Science(1997-2023).The study aims to:(1)evaluate current research on GES,(2)identify key drivers of change and their impacts,and(3)suggest practical strategies for sustainable grassland management.The study found that:(1)Research on grassland ecosystem services has surged in the past decades,mostly in regions with large grasslands and strong economies,with over half of studies conducted in China(39.58％)and the U.S.(16.67％).(2)A total of 41 GESs were identified under four broad categories,with regulating services most studied and cultural services least.(3)Most articles focus on causes of changes,while fewer address human well-being and manage-ment.(4)Climate change and human activities are the main drivers,impacting 81.15％and 70.36％of global grasslands,respectively.(5)The affected area is expanding,reaching 2500.67 million ha and 2094.68 million ha in 2018.We discussed potential reasons for the findings,identified research gaps,highlighted future research areas,and addressed current grassland management issues and offered some practical recommendations.Most im-portantly,we propose a novel"Ecosystem Service-based Grassland Management"(ESGM)framework.The framework's innovation lies in its systematic integration of three critical dimensions:(1)grassland ecosystem service assessment,(2)management practices,and(3)human well-being.This integrated approach offers a robust decision-support tool for poli-cymakers operating at various governance levels.
Rapid urbanization threatens eco-environment quality (EEQ), in which the urban landscape pattern (ULP) plays a key role. However, the multi-scale mechanisms behind their spatial nonstationarity and nonlinear interactions remain underexplored. This study constructed an EEQ index, incorporating urban impervious surface and air pollution, based on urban ecosystem elements. Using a novel framework that integrates MGWR with a random forest model interpreted by SHAP, we explored the spatially nonstationary and nonlinear association between ULP and the EEQ index, and further quantified the contributions and thresholds of ULP both globally and locally. The results indicate that: (1) EEQ index in China’s coastal areas (CNCA) averaged 0.64, indicating a generally favorable level, with lower values in urban agglomeration distribution; (2) Urban built-up area percentage (UAP), urban built-up height (UBH), Shape, Contagion, and patch Euclidean Nearest-Neighbor Mean Distance index were the top contributors; (3) UAP and UBH have bidirectional effects on EEQ index in CNCA, reflecting characteristics of the Environmental Kuznets Curve. However, patterns were inconsistent for urban agglomerations within CNCA, indicating significant spatial discrepancies and nonlinear features, and growing inequality among urban agglomerations has heightened the complexity of their thresholds. Overall, prioritizing urban landscapes with order, strong cohesion, and effective connectivity in landscape planning can guide future urban expansion.
Long-term monitoring of vegetation dynamics is essential for assessing ecosystems resilience and responses to climate change.The China Ecosystem Research Network(CERN)is a national long-term observation network that provides an ecological baseline across Chi-na's major ecosystems.This study analyzed vegetation trends and their driving factors from 2000 to 2024 across 34 CERN field stations and their surrounding areas.An intercomparison of multiple NDVI products revealed substantial inconsistencies.MODIS NDVI exhibited su-perior temporal stability and spatial coherence and was therefore selected for long-term analysis.The mean NDVI at CERN stations(0.419)was 37.8％higher than the national av-erage(0.304),and showed significantly faster greening trends(0.022/10 a)compared to suburban(0.013/10 a)and rural(0.017/10 a)areas,reflecting effective vegetation restoration and stable ecosystem management.Vegetation changes at CERN field stations were pre-dominantly governed by climatic rather than anthropogenic factors.Among different ecosys-tem types,air temperature(AT),sunshine duration(SD),and relative humility(RH)were the dominant drivers in farmland,forest,and wetland.For grassland,AT and SD were the main drivers,whereas AT and RH exerted the strongest influence in the desert ecosystem.These findings confirm the representativeness of CERN stations and underscore the predominant role of climatic factors in shaping long-term vegetation trajectories across China's diverse ecosystems.
