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.
Basin-scale glacier surface mass balance (SMB) reconstruction is a bottleneck for glacier research. In this study, the performances of the enhanced temperature-index model (ETI) and simplified energy-balance model (SEB) for simulating glacial SMB in the Laohugou (LHG) Basin 1980–2020 were compared using the observed and reanalysis datasets. (1) The ETI exhibited more stable and better simulations at the basin scale, which was mainly attributed to the physical structural differences between the two models. (2) In the last 40 years, the annual and cumulative SMB have been −0.39±0.29, −16.020±3.97 m w.e., respectively. After 1990, the rate of glacier ablation approximately tripled that of the 1980s. From 2011 to 2020, a more rapid loss occurred, with a rate of −0.56 m w.e. yr−1. (3) The SMB showed the highest sensitivity to temperature. The sensitivity of the SEB to downward shortwave radiation (SW↓) was approximately triple that of the ETI. Additionally, a significant negative correlation was found between the westerlies-monsoon synergy index and the annual SMB (R=−0.44, p<0.05). These findings present a basic method of SMB simulation at basin scales, where glacier changes are more significantly influenced by temperature.
The distinctive “flat-top and steep-slope” morphology of the Loess Yuan presents significant challenges for traditional slope unit delineation. Conventional methods often mis-segment tableland surfaces, produce jagged unit boundaries, and lack geomorphic rationality. To address these limitations, we developed a novel, high-precision extraction method tailored to this complex terrain. We propose TerrainNet-based Slope Unit Delineation (TSUD), a deep learning approach that integrates multi-source data, including remote sensing imagery, Digital Elevation Models (DEMs), and the topographic position index (TPI). By leveraging TerrainNet, TSUD adaptively captures complex topographic features and specifically optimizes the transitional boundaries between flat tablelands and steep escarpments. Experimental validation in Longfang town, a representative Loess Yuan area in Shaanxi province, demonstrates TSUD’s superiority over traditional techniques. Quantitatively, the method achieves an F1-score of 0.831 and a Mean Intersection over Union (mloU) of 0.711. Qualitatively, TSUD resolves chaotic segmentation in flat regions and eliminates fragmented boundaries along steep slopes. Field investigations confirm that these results align closely with actual landforms, yielding a realistic representation of gully systems and transition zones. This study provides the first systematic optimization of slope unit delineation for Loess Yuan landforms in Northwest China. The proposed “data-driven plus geomorphic constraints” paradigm demonstrates the applicability of deep learning in terrains with coexisting gentle and abrupt morphological transitions, establishing a robust technical foundation for regional landslide susceptibility assessments.
The comprehensive pattern of the natural environment constitutes a complex system shaped by interactions among multiple natural elements, including geology, terrain, climate, hydrology, soil, and biodiversity. The regional structure that embodies this complexity is defined as the comprehensive natural terrestrial system. Consequently, this system provides an integrated perspective for understanding the overall characteristics of the natural environment and resources. Pakistan, with agriculture as its core economic sector, has a natural environment that is inherently linked to its topographic and climatic conditions. Its geographical environmental conditions are similar to those of China. Through analysis of Pakistan’s geological, geomorphological, climatological, hydrological, and vegetation conditions, we adopted the methodology of China’s comprehensive natural regionalization to establish a comprehensive natural terrestrial system scheme for Pakistan. Hierarchically, this scheme is divided into 3 major regions, 5 temperature zones, 8 humidity areas, and 23 natural regions. The scheme reveals the diversity of Pakistan’s natural environment and its three-dimensional geographical zonality characteristics. Furthermore, this study analyzes the ecological advantages, constraints, and resource development potential of each regional unit and proposes targeted strategies for ecological conservation and socioeconomic development. The scheme provides a scientific basis for the sustainable socioeconomic development of Pakistan.
Identifying threshold discharges that govern erosion-deposition transition is crucial for predicting the morphological evolution of point bars.In this study,a comprehensive framework for quantifying threshold discharges via two-dimensional depth-averaged hy-dro-morphodynamic modelling(TDHM)is proposed.When applied to the Sanyiqiao point bar in the lower Yangtze River as a case study,the TDHM framework demonstrated high predic-tive reliability,with root-mean-square error values for the tidal level and flow velocity of 0.072 m and 0.169 m/s,respectively,alongside volumetric change errors ranging from 11％-19％.The results revealed two distinct threshold discharges,namely,one triggering the transition from stability to erosion(20,000-25,000 m3/s)and the other facilitating a shift from net erosion to net deposition(40,000-45,000 m3/s).This dual-threshold behaviour is driven by the non-monotonic response of the bar surface hydrodynamics to increasing discharge.Channel regulation projects and sediment supply influence these thresholds more notably than tribu-tary inflows do.Recent erosion of the point bar could be attributed to the synergistic effect of the 12.5-m deep-water channel project and a reduced sediment supply.The proposed TDHM framework provides a robust predictive tool for estimating morphological adjustments under future environmental changes,thereby supporting proactive river management and naviga-tional safety.
Socio-ecological systems (SESs) are commonly interpreted through a hydrosocial trade-off framework, where ecological restoration competes with socio-economic development under water constraints. Ecological water diversion (Wd) has been implemented to alleviate this trade-off by reallocating water to support ecological recovery and potential socio-economic gains. However, the underlying coupling pathways remain poorly quantified. Using long-term observations (1980–2022), we quantified coupled socio-ecological responses to Wd in two representative regulated basins in northern China: the Heihe River Basin (HRB) and the Baiyangdian Lake Basin (BLB). Results showed both NDVI and water surface area (Wa) increased significantly after Wd since 2000. In the BLB, NDVI increased by 4.4–4.6
This study investigated the spatial and temporal patterns of ablation, debris-cover characteristics, and crevasse distribution on Baishui River Glacier No. 1 based on using multi-year in situ observations (2019–2022). The results reveal a strong elevation–dependent ablation gradient, with annual ablation rates decreasing from 3.8–5.4 m w.e. at 4550–4600 m asl to 1.1–2.1 m w.e. above 4750 m asl, following a gradient of −1.53 m w.e. (100 m)−1. Ablation along the central flowline was 21
When debris flows occur in medium to large gullies,they can cause significant damage.Accurately assessing their disaster risk is key to disaster prevention and reduction.Due to the difficulty that Convolutional Neural Networks(CNNs)face in capturing long-range dependencies,which hampers the extraction of global features for medium to large gully-type debris flow,this paper proposes a Convolutional Transformer Net(CTNet)that combines CNNs and Vision Transformer(ViT).First,positional encoding is added at the start to en-hance the model's spatial awareness,and the network is widened along with the use of grouped convolutions to improve feature extraction capabilities.Next,the partitioned image is linearly projected into a sequence and fed into the ViT Block,where the multi-head self-attention mechanism captures dependencies across different subspaces.Finally,CTNet classifies the gullies into high-risk and low-risk categories based on the risk score vector.In experiments on the Nujiang Gully dataset,CTNet significantly improved the recognition per-formance for medium to large gullies,achieving an accuracy of 88.97％and a precision of 90.85％,which notably outperforms other comparison models.Therefore,CTNet effectively overcomes the limitations of CNNs in global modeling and provides a new paradigm for high-precision disaster-risk gully identification.
Against the backdrop of global warming,the risk of river and lake flood disasters along plateau railways is increasing.The Qinghai-Xizang Railway is the world's longest railway traversing a plateau region.A comprehensive hazard assessment of river and lake flood disasters along the route was conducted after identifying hazard points within a 50-km buffer zone of the railway.The main findings were as follows.(1)The hazard levels for river density,potential flood points of rivers,lake breaching,and waterlogging,in the"relatively high"to"high"classes,accounted for 35.64％,24.84％,10.88％,and 18.18％of the study area,respectively.(2)The comprehensive hazard due to river flood disasters along the rail-way was mainly distributed in the Nachitai-Lhasa section.High hazards due to lake breach-ing and waterlogging were concentrated in the Nachitai-Anduo section.(3)In terms of the comprehensive hazard of river and lake flood disasters,sections with"relatively high"to"high"hazard levels accounted for 22.18％of the total area."High"hazard areas were con-centrated in the Nachitai-Anduo section.With the intensification of global warming,flood risks along high-altitude railway lines are expected to escalate substantially.In particular,the risks arising from upstream or distant glacial lake outburst floods,river capture,and lake expansion should not be underestimated.
Urbanization in China has rapidly reshaped the quality of human settlement; however, most studies have overlooked its continuous spatiotemporal evolutionary characteristics. This study develops a hierarchical framework integrating TOPSIS, spatial autocorrelation, Theil index decomposition, and time series analysis to quantify comprehensive and subsystem-level quality of urban human settlement (QUHS) for 264 Chinese cities from 2002 to 2021. This framework captures spatial heterogeneity, temporal trends, and variations across residential environments, public services, socioeconomic development, and the natural environment, offering a more nuanced understanding than conventional cross-sectional approaches. The results indicate a steady improvement in QUHS nationwide, with pronounced spatial clustering and belt-like regional patterns: cities in the eastern and southern regions advanced more rapidly, whereas those in the northwestern and northeastern regions lagged. Although regional disparities decreased overall, considerable intra-regional differences persisted, highlighting their role in shaping spatial inequality. Based on these findings, initiatives such as ecological civilization promotion, digital economic development, infrastructure upgrades, and regional integration could contribute to improving QUHS; however, persistent intercity differences emphasize the need for regionally tailored and locally adaptive policy measures. By revealing the dynamic evolution and spatial heterogeneity of QUHS, this study enhances understanding of urban sustainability and provides evidence-based insights for planning and policymaking in rapidly urbanizing contexts.
The timing and pattern of abrupt climatic events during the last glacial termination, particularly the Bølling-Allerød (B-A) Interstadial, are critical for understanding rapid climate transitions under global warming. Well-preserved glacial landforms on the Tibetan Plateau (TP) provide valuable insights into past climate change, yet glacier responses to the B-A Interstadial remain poorly constrained due to limited chronological data. Here, we report ten new 10Be surface exposure ages from glacially polished bedrock along the main ice-flow path in the Lahaku Valley, Haizishan Plateau (HZSP), southeastern TP. The results cluster tightly between 15.1±0.9 ka and 13.7±0.9 ka, with a mean of 14.3±0.5 ka, indicating a rapid deglaciation at the onset of the B-A Interstadial. These ages, combined with published 10Be ages in the HZSP, provide robust evidence for B-A deglaciation on the TP. Furthermore, this rapid deglaciation aligns with similar events observed across the Northern Hemisphere, pointing to a common hemispheric-scale climatic forcing. Comparative analysis of glacial and climatic records indicates that the primary driver was likely abrupt warming, linked to ocean-atmosphere processes associated with a reinvigorated Atlantic Meridional Overturning Circulation.
