Significant progress has been made in the Beautiful China Initiative, where the discipline of geography has leveraged its comprehensive and regional strengths to play a key role. To address the technological needs of this initiative, geographers have organized and undertaken major scientific and technological tasks, such as the "Ecological Civilization Project Towards a Beautiful China". Through continuous innovation across multiple domains—including Major Function Oriented Zoning, territorial space development and protection, comprehensive environmental pollution control, regional joint prevention and control, eco-geographical regionalization, ecological environment restoration and protection zoning, and the evaluation of Beautiful China Initiative's progress and the synergy of ecological civilization construction—geographers have continuously advanced the geographical theories, methods, and research paradigms pertaining to the Initiative. These efforts have provided crucial scientific and technological support for opening the pathway for turning "lucid waters and lush mountains" into "invaluable assets", promoting the integrated protection and restoration of mountain-river-forest-farmland-lake-grassland-desert system, and advancing the prevention and control of environmental pollution, thereby played a prominent role in building a "Modernization Characterized by Harmonious Coexistence between Man and Nature". The Beautiful China Initiative has propelled the geographical study of human-environment interactions into a new era of ecological civilization; it likewise stands as a major national-level practice for achieving Sustainable Development Goals. In the new phase of comprehensively advancing the Beautiful China Initiative and implementing the global sustainable development agenda, geography should focus on addressing resource and environmental pressures and spatial disparities. Specifically, it should: (1) Conduct research on integrated prevention and control of ecological environment risks in key regions; (2) Deepen the understanding of human-environment relationships, and advance research on enhancing resource carrying capacity and promoting efficient resource utilization; (3) Coordinate the Regional Coordinated Development Strategy, Regional Major Strategy, and Major Function Oriented Zoning Strategy to conduct research on the spatial framework supporting the Beautiful China Initiative across all domains; (4) Leverage new technologies such as large-scale Low Earth Orbit satellite constellations and artificial intelligence to enhance ecological and environmental monitoring and assessment capabilities, and to plan the spatial distribution of green, low-carbon, and new quality productive forces; (5) Share the experiences of the Beautiful China Initiative and strengthen green cooperation within the Belt and Road Initiative, thereby contributing to the shared goals of global sustainable development.

The disruptive, leapfrog, and transformative development of artificial intelligence is bringing unprecedented challenges and opportunities to the field of human geography. Against this backdrop, and based on the development history of AI and its application background in the discipline, this paper explores a human-land system framework based on human-machine collaboration. The innovation in the development paradigm of human geography under the shift in AI technology is mainly reflected in the following aspects: the research focus shifts from human-land coordination to virtual interaction; data usage moves from manual collection and translation to intelligent integration; technology application transitions from traditional methods to intelligent tools; and the disciplinary ecology evolves from humanistic characteristics to technological crossovers. At the same time, technological innovation brings new challenges to the development of the discipline, including potential crises in disciplinary identity, difficulties in theoretical innovation, shortcomings in technological application, ethical value risks, intensified cross-disciplinary competition, and reflections on value recognition. Finally, this research proposes that human geography in the age of artificial intelligence should be guided by the goal of building an independent knowledge system for Chinese human geography. It should be rooted in Chinese practice, actively embrace technological advancements while upholding disciplinary values and ethics, promote the "disciplinarization" of artificial intelligence technology, and attempt to build databases and large models for human geography. The aim is to effectively answer the crucial questions of our time: for whom are we educating, what kind of people are we educating, and how are we educating them.

Exploring ecosystem services (ES) is a key approach to understand the relationship between human and ecosystems. General spatial mapping methods for ES are limited to depict the interrelationships and interactions among social and ecological elements, leading to the lack of integrity and systematicity in governance. Integrating social-ecological network analysis methods with ES can enhance the analysis of the driving mechanisms, trade-off and synergic relations, and key factors of social governance. This study systematically reviewed the development of social-ecological network methods, and summarized the advantages and prospects of these methods in ES association research. The three advantages of social-ecological network methods are: (1) the social-ecological correlation network provides a new perspective for analyzing the trade-off relationships between ES and their social feedback mechanisms; (2) the social-ecological spatial network helps to resolve the spatial mismatch problem between governance and ecological connections; (3) multi-level network analysis enhances the effectiveness of assessing adaptive governance. In the future, ES association research should focus on the forecast of ES steady state and redundancy based on trade-offs and social feedback employing dynamic disequilibrium methods, the quantification of cultural ES based on rational values, and the key adaptive governance measure of ES management for ecosystem steady state.

The sustainable development of transboundary basins holds significant strategic importance for achieving global environmental goals and promoting regional peace and cooperation. This study systematically reviews 1201 publications on the sustainable development of transboundary basins from 1973 to 2024 using natural language processing and bibliometric methods. It analyzes the spatiotemporal patterns, thematic focuses, and methodological evolution of research across 310 global transboundary basins. Results show that existing studies predominantly focus on individual basins, lacking systematic global-scale comparisons, with research being highly concentrated in Asia, particularly Southeast Asia. Over time, the research has shown a generally increasing trend, with Chinese scholars playing a leading role in Asian transboundary basin studies. In terms of research themes, governance-related topics dominate, especially transboundary water resource management (SDG 6) and multilateral cooperation mechanisms (SDG 17). However, current quantitative assessments mainly target single basins and individual goals, resulting in limited systemic and integrated analyses. There is an urgent need to develop an operational assessment framework that accounts for spatial heterogeneity and scenario adaptability to effectively support sustainable governance practices in global transboundary basins. The findings highlight the urgency and necessity of advancing systematic assessments and policy coordination for the sustainable development of transboundary basins.

Alluvial meandering rivers exhibit dynamic processes of sinuous migration that imprint diverse planform morphologies on the Earth's surface. This paper reviews recent advances in the understanding of meander planform evolution, with emphasis on four aspects: (1) the evolution patterns of individual bends, (2) the spatiotemporal heterogeneity of migration processes, (3) the relationship between migration rate and curvature, and (4) the mechanisms and characteristics of cutoffs. The review further synthesizes four key themes in meander migration research: the self-organized criticality of planform dynamics, the lag effects between curvature and migration, the mechanisms driving cutoffs, and advances in process-based migration modeling. Finally, we highlight current limitations and propose future directions. These include the establishment of long-term, high-resolution monitoring systems to automatically collect dynamic planform data, the integration of multiple theories of river evolution with field-based hydrosedimentary measurements, and the development of unified multi-scale models within an interdisciplinary analytical framework. Such efforts will provide a stronger scientific basis for applications in engineering, environmental management, ecology, and fluvial geomorphology.

Research on the geomorphological regionalization of the Mongolian Plateau has long been limited by ambiguities in boundary delineation and inconsistencies in indicator systems. This study integrates multisource geospatial data to establish principles for defining the extent of the Mongolian Plateau on the basis of dominant genetic mechanisms and morphological characteristics, and it presents a comprehensive framework for geomorphological regionalization. By combining a bottom-up merging strategy with a top-down subdivision approach, and by employing a hybrid clustering model that couples a self-organizing feature map (SOFM) with Ward's hierarchical method, we systematically delineate the boundaries of the Mongolian Plateau and construct a three-level geomorphological regionalization scheme. Results indicate the following: (1) The total area of the Mongolian Plateau is approximately 2.83 million km², spanning Mongolia, China, and Russia. Its boundaries extend eastward to the western slopes of the Greater Hinggan Mountains, southward to the Qilian Mountains-southern Ordos margin, westward to the Sayan-Altai mountain systems, and northward to the southern edge of the Stanovoy Highlands. (2) The regionalization scheme identifies 3 primary geomorphological regions, 18 secondary subregions, and 66 tertiary units. This framework reveals spatial heterogeneity patterns of landforms, where macroscale structures are governed by tectonic uplift, and microscale differentiation is shaped by climatic processes. This study provides a scientific basis and foundational dataset for ecological security assessment and transboundary resource management across the Mongolian Plateau.

Landslides are among the most destructive geological hazards worldwide, with rainfall acting as the predominant triggering factor. This study presents a spatiotemporal landslide early warning model for South China, using Guangdong province as a representative case study, integrating the CTRL-T (Calculation of Thresholds for Rainfall-induced Landslides-Tool) rainfall event segmentation method with advanced deep learning techniques. Utilizing data from 352 automatic rainfall stations and 804 recorded landslide events from 2018 to 2023, the CTRL-T method identified 50541 rainfall events, of which 296 triggered landslides, resulting in a triggering rate of 0.59%. Three critical rainfall characteristics—antecedent duration (Da), antecedent cumulative rainfall (Ea), and triggering rainfall (Eo)—were extracted to construct a 3-4-4-1 deep neural network ensemble. Key findings include: (1) Landslide events predominantly occurred during April to June (spring), with a triggering rate of 1.68%, while the summer period, despite the highest rainfall frequency, exhibited only a 0.25% triggering rate; (2) Landslide-triggering events had a markedly higher median rainfall (597.5 mm) than non-triggering events (43.2 mm); (3) The optimal warning model, at a 1-hour lag, achieved an ROC AUC of 0.902 and a balanced accuracy of 0.859; (4) Retrospective validation of three typical cases demonstrated that the model achieved an average early warning time of 12 hours with 100% success rate, outperforming I-D threshold methods. The deep learning ensemble effectively captured the complex, nonlinear relationships between rainfall patterns and landslide occurrence, demonstrating robust predictive capability for landslide risk in the subtropical monsoon climate of South China. The adaptive CTRL-T method also proved highly suitable for dynamic rainfall event identification in this region. This research provides a scientific and technical foundation for landslide early warning, with demonstrated operational value and significant potential to enhance disaster risk reduction efforts. Future work should integrate multi-source data—including topography, geology, and soil properties—to further improve model generalizability, physical interpretability, and practical application across diverse geographic and climatic settings, ultimately supporting more resilient disaster management strategies.

Plain river networks are experiencing pronounced structural and functional reorganization under rapid urbanization, yet their multidimensional evolutionary patterns and driving mechanisms remain insufficiently quantified. Taking the Nanxun Plain River Network as a case study, this research systematically examines the spatiotemporal evolution of river-network structure, connectivity, and network properties across the Hangzhou-Jiaxing-Huzhou Plain from the 2006 to the 2024. By integrating SOM-K-medoids clustering with an XGBoost-SHAP framework, we quantitatively reveal the heterogeneity of river-network evolution and its driving mechanisms. The results show that: (1) During the study period, the river-network density declined from 3.71 to 3.66 km/km², indicating a persistent reduction in system complexity and a trend toward spatial homogenization. Connectivity and network properties exhibited an early-stage decline followed by stabilization, with the proportion of polders experiencing decreases reaching 34%-62% in 2015, but dropping to 20%-43% in 2024. (2) Clustering analysis identified five river network types, with the most intense type transitions occurring during 2006-2015, when the dominant type shifted from Type II (31%) to a dual dominance of Type I and Type V (each 28%). During 2015-2024, the type structure became more stable, with Type II and Type V accounting for 31% and 28%, respectively, and high-complexity river network units concentrating from peripheral areas toward the central-southern region. (3) The evolution of structural connectivity and multifractal characteristics was jointly driven by urbanization and river network density, with the contribution of urbanization to structural connectivity increasing continuously to 43.08%, while the influence of river network density on fractal complexity intensified markedly during 2015-2024. Changes in node importance and network transmission capacity were jointly controlled by discharge conditions and river network density, with discharge contributing more than 40% during 2006-2015. This study advances the theoretical understanding of plain river network evolution and provides practical insights for river network optimization and water environment management.

As the primary water recharge area, the Yellow River water conservation area (YRWCA) plays a critical role in the basin's water resources configuration and ecological security. Influenced by climate warming and human activities, the climatic conditions and underlying surface characteristics in this region have undergone significant changes, leading to nonlinear responses in hydrological processes. However, the key driving mechanisms behind changes in mean and extreme runoff states remain unclear. To address this, 31 typical headwater catchments within the YRWCA were selected for this study. Using the XGBoost-SHAP method, the contributions of climatic and underlying surface factors to changes in mean, high, and low flows from 2000 to 2020 were quantified. Furthermore, hierarchical clustering was employed to reveal the dominant driving mechanism types and their spatial differentiation characteristics. The results indicate that: (1) The spatial pattern of runoff in the YRWCA exhibits a distribution that is high in the west and low in the east. While the overall flow trend is increasing, there is a spatial disparity characterized by increases in the west and decreases in the east. (2) Precipitation, potential evapotranspiration, and forest land proportion are the key driving factors for runoff variations. Climatic factors dominate changes in mean and high flows, whereas underlying surface factors play a more critical role in regulating low flows. (3) The driving factors show significant nonlinear impacts and threshold effects on runoff regimes. When precipitation exceeds approximately 660 mm, and vegetation coverage and forestland proportion exceed about 44% and 28%, they exert positive effects on mean/high flows and low flows. (4) Runoff change patterns in the YRWCA are subject to multiple influences, including flow regimes, spatial attributes, climatic background, and human activities. Changes in mean and high flows can be categorized into "precipitation-dominated" and "precipitation-evapotranspiration coupled" types, while low flow changes correspond to "underlying surface-dominated" and "climate-underlying surface synergistic" patterns.

Reclaimed water resources are pivotal in alleviating water scarcity, fostering resource circularity, and bolstering the resilience of urban water systems. As a strategic pathway toward achieving United Nations Sustainable Development Goal (SDG) 6—Clean Water and Sanitation—safe and efficient reuse of treated wastewater has gained significant global prominence. Nevertheless, the spatiotemporal dynamics of reclaimed water in China remain under-explored, and the underlying drivers lack systematic investigation. This study employs a robust methodological framework, integrating Hierarchical Cluster Analysis (HCA), Principal Component Analysis (PCA), and multiple linear OLS regression, to comprehensively examine the temporal evolution and spatial distribution of China's reclaimed water resources. The findings delineate a distinct progression through three developmental phases: (1) an initial phase characterized by inadequate wastewater treatment penetration during the period of extensive industrialization (2002-2008), (2) a rapid expansion phase driven by infrastructure-led growth in treatment rate (2009-2015), and (3) a convergence phase within the current technology-policy era (2016-2023), where reclaimed water volumes have increasingly aligned with wastewater discharge rates. Spatially, the distribution is markedly constrained by the Hu Line, exhibiting a pronounced east-west gradient with higher utilization concentrated in the eastern region. The driving mechanisms of this spatial differentiation have shifted from an early reliance on fiscal investment and natural water endowment to contemporary determinants such as regional economic scale, population density, and industrial upgrading. Notably, rural areas—characterized by dispersed populations and deficient infrastructure—exhibit persistently low recovery rates, highlighting the exigency for decentralized treatment solutions. As China navigates tightening water constraints and shifting demographic trends, the developmental paradigm must transition from quantitative expansion to qualitative optimization. This study provides a quantitative foundation for region-specific strategies and theoretical support for sustainable and equitable water resource allocation within the framework of integrated water resources management.

Understanding plant water-use strategies under varying drought intensities is crucial for guiding ecological restoration on the Loess Plateau. This study conducted intensive biennial sampling (2023-2024) of soil water, precipitation, and xylem water from representative vegetation types. Target species encompassed ecological revegetation trees, economic fruit trees, a typical herbaceous plant and major staple crops. Stable isotope (δ²H and δ¹⁸O) tracing coupled with the Bayesian mixing model (MixSIAR) was utilized to quantify plant water sources, while structural equation modeling (SEM) was employed to identify the drivers of water-use shifts across a drought gradient. Key findings show that: (1) Soil water δ¹⁸O displayed a vertical profile of surface enrichment and deep-layer depletion, exhibiting significant spatial heterogeneity across landforms. Xylem water δ¹⁸O was most stable in the river valley plain (RVP), with tree species showing significantly higher isotopic variance than herbaceous plants. (2) Temporally, plants primarily extracted shallow soil water and precipitation during the wet season, transitioning to mid-to-deep soil water during the dry season. Interannual variability in water uptake was lower in 2023 than in 2024. Specifically, herbaceous plants and crops relied mainly on precipitation and shallow soil water; ecological revegetation trees exhibited strong seasonal plasticity, whereas economic fruit trees consistently exploited mid-layer soil water. (3) Under intensifying drought (moderate to extreme), natural vegetation dynamically adjusted its water-use strategies, displaying high ecohydrological plasticity. In contrast, planted vegetation maintained rigid water uptake patterns, revealing a critical lack of adaptive capacity under severe moisture stress. (4) Precipitation (P), vapor pressure deficit (VPD), and relative humidity (RH) emerged as the dominant environmental drivers controlled these water-use shifts. This study elucidates the divergent ecohydrological response mechanisms of natural versus planted vegetation under varying drought severities, offering a mechanistic basis for adaptive vegetation management and sustainable water resource allocation in the Loess Plateau.

Clarifying the spatio-temporal differentiation patterns of cultivated land protection efficiency and its mechanism of impact on food security is a key scientific issue for optimizing territorial space governance and strengthening the foundation of food security. This study comprehensively employs the Dagum Gini coefficient, spatial conditional Kernel density, and the Dynamic Spatial Durbin Model to examine the spatio-temporal evolution of cultivated land protection efficiency in China from 2005 to 2020 and its spatial effects on food security. The findings reveal that: (1) Temporally, cultivated land protection efficiency in China exhibited a three-phase transition pattern: sharp decline (2005-2007) - stable development (2008-2012) - rapid growth (2013-2020). Spatially, it displayed an unequal pattern: northeastern > western > eastern > central region. (2) Regarding regional disparities, the inter-provincial Gini coefficient of cultivated land protection efficiency showed a trend of "expansion before convergence", with an overall reduction in imbalance. Intra-regional differences followed the hierarchy: eastern > western > central > northeastern region. (3) Cultivated land protection efficiency in China exhibits persistence; it generally converges under both spatial static and dynamic conditions; spatial positive correlation weakens when the efficiency gap between adjacent regions is large. (4) Cultivated land protection efficiency in China exerts significant and robust positive direct effects and spatial spillover effects on food security, with long-term effects consistently stronger than short-term effects. Industrial structure, grain trade, and labor conditions also significantly positively influence food security. The research confirms that spatial factors play a crucial role in the regional disparities, spatio-temporal evolution of cultivated land protection efficiency, and its effects on food security. It is imperative to enhance ecological governance capacity according to local conditions to coordinate the ecological and productive functions of cultivated land.

This study takes 21 prefecture-level cities in Guangdong province as research samples to evaluate multifunctional farmland across production, living, ecological, and cultural dimensions using the CRITIC-entropy weighting method. A spatial correlation matrix is then constructed through the modified gravity model. Furthermore, social network analysis (SNA) and quadratic assignment procedure (QAP) are employed to explore the spatio-temporal characteristics and driving mechanisms of the multifunctional farmland spatial correlation network under new-type urbanization. The results show that: (1) From 2003 to 2023, production and cultural functions declined, living function remained stable, and ecological function experienced a decline-then-increase pattern. Spatially, western Guangdong emerged as a high-value cluster across all functions, northern Guangdong dominated in production and living functions, whereas the Pearl River Delta (PRD) led only in cultural function. (2) The multifunctional farmland spatial correlation network is fully connected and non-hierarchical except for the living function, with efficient transmission paths and small-world characteristics. Nodes exhibit significant role differentiation: northern Guangdong serves as an aggregation hub in production and living networks, while the PRD acts as a distribution center in ecological and cultural networks. Block model analysis reveals strengthened intra-block connections and differentiated inter-block paths. Production, living, and ecological functions shift toward unidirectional transmission, whereas cultural function tends toward bidirectional coordination. (3) Driving factors are classified into four types. Geographical adjacency and R&D personnel gaps exert stable effects on all functions. Temperature, population density, and traffic accessibility disparities show consistent effects on specific functions. Industrial structure and construction land proportion disparities show divergent effects across functions. Fiscal support for agriculture shows phased effects only on living function. This study provides scientific evidence for optimizing spatial layout and network governance of multifunctional farmland under new-type urbanization, thereby facilitating cross-regional coordination in farmland management and utilization.

Urban expansion and habitat quality are two critical and interrelated factors influencing the global urbanization process. Oases serve as the core of inland river basins in arid regions and they are the foundational ecosystems for the emergence and development of oasis cities. Due to the limited, fragmented, and fragile nature of oasis habitats, the impact of oasis city expansion on regional habitat quality is particularly significant. This study focuses on the spatial heterogeneity and interrelationships among mountains, oases, and deserts within inland river basins in arid regions, as well as the spatial interdependence between oases and cities. It classifies different types of oasis cities, constructs an analytical framework to assess the impact of oasis city expansion on various habitat spaces, and comprehensively applies urban expansion models and habitat quality assessment models. A systematic analysis was conducted to explore the spatio-temporal characteristics of urban expansion and habitat quality changes in the Heihe River Basin's oases from 2000 to 2020, aiming to reveal how urban expansion influences habitat quality. The results indicate that: (1) The spatial expansion intensity of oasis cities generally follows the order: Middle Position Oasis City I > Higher Position Oasis City > Lower Position Oasis City > Middle Position Oasis City II, exhibiting significant spatial heterogeneity. All types of oasis cities are primarily characterized by edge expansion, with enclave and infill expansion as secondary patterns, showing a trend of convergence. From the perspectives of population and economic development, Middle Position Oasis City I were the first to enter a phase of rapid expansion, followed by type II cities gradually transitioning into rapid expansion, which then spread to both Lower Position Oasis City and Higher Position Oasis City. Under the siphoning effect of Middle Position Oasis City I, Higher Position Oasis City exhibits signs of contraction. (2) From 2000 to 2020, the overall habitat quality of the basin remained relatively stable; however, habitat degradation within the oasis areas was more pronounced, following the pattern: Middle Position Oasis > Higher Position Oasis > Lower Position Oasis. Around urban centers, a distinct stratified pattern of degradation—severe, moderate, and mild—has emerged, reflecting the influence of urban expansion on oasis habitat quality. (3) The expansion of oasis cities directly causes habitat damage through land occupation and transformation, leading to significant degradation of habitat quality in surrounding areas.

Agricultural regional systems exhibit distinct hierarchical and nested characteristics in factor allocation, functional performance, and evolutionary mechanisms. Achieving sustainable agricultural development hinges critically on understanding the cross-scale interaction mechanisms within the system, beyond the internal laws of individual scales. Grounded in theories of the human-land relationship areal system, agricultural multifunctionality, and land use transition, this study systematically analyzes the theoretical connotations, realization processes, and coupling mechanisms between the transformation of agricultural regional functions and the ecological utilization of cropland within the context of China's agricultural transformation. The research indicates that: (1) The transformation of agricultural regional functions represents a directional, trend-wise shift in functional morphology driven by socio-economic development stages. The direction of functional evolution, determined by societal demand, manifests in three pathways: diversification of functional composition, structural transformation of functional combinations, and trend-wise changes in overall functional intensity. (2) Ecological cropland utilization is a transformative process achieving multi-functional synergy and enhanced system resilience through restructuring cropland use patterns and guiding positive succession in cropland ecological processes. (3) The coupling of these processes operates through an "inducement-transmission-feedback" mechanism. Upgraded societal demands and policy regulations drive the valorization of "ecological" elements, inducing micro-level factor substitution. This change cascades through an "element-structure-function" transmission, reshaping management systems, industrial organization, and spatial patterns to emerge as macro-level functional transformation. Concurrently, the dynamic interplay of positive and negative feedback mechanisms drives the system's evolution toward multi-functional synergy and high resilience. This study offers an integrated perspective on cross-scale interactions within agricultural regional systems, providing theoretical support for promoting agricultural green transformation and precisely implementing rural revitalization strategies.

The frequency and intensity of compound drought-heatwave events (CDHEs) have significantly increased under the backdrop of global climate change. The synergistic effects of CDHEs pose severe threats to terrestrial vegetation ecosystems. This study employs spatiotemporal coupling analysis of multi-source remote sensing vegetation data and meteorological records to systematically characterize vegetation responses to CDHEs in the Yangtze River Basin during the period 1982-2024. We quantify vegetation recovery durations under CDHEs of varying seasons/intensities and identify dominant drivers. Key findings include: (1) Over the past 40 years, vegetation greenness and productivity in the study area have shown a significant upward trend (middle reaches > upper reaches > lower reaches), with the trend of vegetation greening notably accelerating. This is primarily attributed to the increase in atmospheric CO₂ concentration (38%) and climate warming (33%). The 2022 extreme drought suppressed vegetation growth by -1.49% (2022) and -1.52% (2023), with recovery to 2021 levels still unachieved by 2024. (2) CDHEs showed distinct spatial patterns: increasing frequencies in upper and middle reaches versus decreasing in lower reaches. Mild CDHEs promoted subsequent-year vegetation growth, while severe events suppressed it, suggesting moderate disturbance enhances ecosystem resilience. (3) Vegetation recovery followed a "function-over-structure" trajectory, with GPP recovering 24%-36% faster than NDVI. In most regions, vegetation recovered within four seasons. However, recovery took significantly longer when CDHEs occurred around the peak of the growing season. Furthermore, the recovery mechanism presents a dual pattern: soil moisture is the dominant factor (48%-52%) for vegetation recovery under mild CDHEs, while vegetation coverage dominates (57%) under mode-CDHEs, revealing the difference in recovery pathways of "mild CDHEs—moisture-dominated, mode-CDHEs—structure-supported". This study reveals the lag characteristics of vegetation response to CDHEs and the intensity-dependent recovery mechanisms, providing a scientific basis for regional ecological restoration.

In the context of building up strength of agriculture and rural revitalization strategy in China, together with the One-Country-One-Priority-Product initiative of the Food and Agriculture Organization (FAO), cultivating agricultural products with geographical indication is an important lever to promote high-quality agricultural development and prosperity for all. Therefore, exploring their economic effects and underlying mechanisms is of great significance for the sustainable development of characteristic agriculture. Based on the directory of China's national agricultural products of geographical indication from 2008 to 2024 and micro survey data on rural revitalization surveys covering 10 provinial-level regions of China, in this study, spatial analysis and propensity score matching were carried out to analyze the spatio-temporal evolution of geographical indication agricultural products and evaluate their income-increasing effects on village collectives and rural households. The results show that the number of geographical indication agricultural products expanded markedly from 121 in 2008 to 3527 in 2024, representing an approximately 28-fold growth. Spatially, they exhibit a clustering feature of dense in the east and sparse in the west, with pronounced spatial self-selection characteristics. Empirical analysis demonstrates that geographical indication certification has a significant positive net effect on income growth. It can increase the collective economic income of certified villages by an average of 1.4989 million yuan per year (an increase of 42.32%), and promote the per capita disposable income of farmers by an average of 4143.72 yuan per year (an increase of 23.82%). From a mechanism perspective, these products facilitate inclusive income growth via a pathway encompassing element attraction, industry driving and value enhancement. Specifically, brand premium effects attract the agglomeration of policy and capital, promote industrial chain extension and employment creation, and increase land rents, product prices and value-added, thereby contributing to the inclusive income growth of village collectives and rural households. Conclusions of this study can provide empirical support for empowering rural revitalization with geographical indication agricultural products, contributing to the global action of One-Country-One-Priority-Product with Chinese practical cases, and providing decision-making references for the formulation of differentiated development policies for rural industries.

The coordinated development of population, cultivated land, and food production is the key to promoting regional sustainable development. Based on the perspective of sustainable diets, this study systematically analyzes the changes in supply and demand of China's population-cultivated land-food system from 1987 to 2023, and makes regional divisions according to the matching characteristics of supply and demand, and then proposes targeted control measures. The study found that: (1) At the demand side, national grain demand continues to rise, with household food expenditures driving a shift in grain demand from primarily staple food to feed grain. Total cultivated land requirements have increased, approaching existing domestic cultivated resources, as animal-derived foods emerge as the primary driver of cultivated land pressure. The sustained growth in imported virtual cultivated land has intensified dependence on international cultivated resources. (2) At the supply side, the decline in China's total cultivated land area slowed from 1987 to 2023. While cultivated land increased across different regions, the growth patterns varied significantly. Grain production has yet to meet residents' food consumption needs, presenting the challenge of surplus staple food and a shortage of feed grain. Significant disparities exist in grain productivity across different regions. (3) Based on calculations of key indicators such as population carrying capacity, pressure on cultivated land, and grain self-sufficiency rate, China is divided into six major types: high-carrying capacity, high-pressure, high-dependence regions; medium-carrying capacity, medium-pressure, staple food surplus regions; low-carrying capacity, low-pressure, resource-constrained regions; low-carrying capacity, low-pressure, reserve cultivated land regions; low-carrying capacity, low-pressure, ecological conservation regions; and medium-carrying capacity, medium-pressure, structural transformation regions. Differentiated regulatory strategies guided by sustainable dietary principles are proposed. This study provides scientific guidance for formulating farmland conservation and agricultural structural optimization strategies driven by balanced dietary needs, offering a theoretical framework for establishing a new national food security paradigm and achieving sustainable transformation of food systems.

A well-functioning food system is crucial for advancing both environmental sustainability and addressing malnutrition. Dietary optimization has become a research focus in geography, environmental science, and agricultural science. However, existing studies often overlook key factors such as production constraints, regional disparities, away-from-home consumption, and feed grain use, limiting the applicability of their conclusions. Based on China's food production and distribution patterns, this study developed three dietary optimization strategies-environment, health, and preference-to simulate provincial dietary adjustments in urban and rural areas. Results show that under nutritional adequacy, the environmental strategy achieved the greatest impact, reducing food consumption by 30% in urban and 10.2% in rural areas, and lowering environmental footprints by approximately 40% and 37.7%, respectively. Guangdong province exhibited the highest optimization potential, with a reduction of up to 16.5 million tons in food consumption and significant environmental benefits. Further analysis revealed that ignoring away-from-home consumption would lead to an underestimation of food consumption by 18.2% (urban) and 7.9% (rural), and environmental impacts by 22.5% and 10.2%, respectively. Optimizing livestock-based foods significantly increased surpluses of grains, tubers, and legumes. These findings provide scientific evidence for differentiated dietary optimization strategies and contribute to the sustainable transformation of China's food system.

As the distinctive high-altitude agro-pastoral ecotone in China, the Qinghai-Xizang Plateau exhibits unique regional characteristics in resident food consumption. Refined analysis of dietary patterns in such areas is crucial for understanding the coupled human-natural systems in this special region. Based on primary food consumption data in 2021 from 216 rural households in Nyingchi, Xizang, collected through a stratified household survey in 2022, this study employed food consumption and nutrient intake indicators, combined with statistical analysis, to systematically examine the dietary structures, nutrition characteristics and household-level variations among residents in this region. The results demonstrate that (1) The dietary structure of rural households in Nyingchi retained traditional characteristics but exhibited significant imbalances. Per capita annual food consumption reached 511.21 kg, dominated by plant-based foods, with cereals (mainly wheat flour, rice and highland barley) and vegetables being the most consumed categories. Animal-based foods consisted mainly of meat and dairy. (2) Food consumption was highly dependent on local agricultural and pastoral production, forming a transitional dietary pattern between agricultural and pastoral areas. At the regional scale, the self-sufficiency rates of high-consumption items, including cereals, vegetables, meat, and dairy, all exceeded 40%. At the household scale, larger cultivation (or livestock rearing) scales were associated with higher per capita consumption of the corresponding foods. (3) Compared with the Chinese Dietary Guidelines for Plateau Residents (2023), rural residents have exceeded recommended standards for energy, protein and fat by 36.27%, 6.73% and 42.68%, respectively. Cereals were the primary source of energy and protein, while edible oil was the main contributor to fat intake. (4) Significant household-level variations in dietary patterns were observed. Per capita food consumption and nutrient intake decreased with increasing household sizes (P < 0.01), followed a U-shaped trend with rising average age (P < 0.01), and increased with higher off-farm employment and income levels, particularly for non-staple foods. These findings provide scientific evidence and practical guidance for optimizing dietary structure, enhancing nutritional health, and promoting the sustainable development of agri-food systems in analogous regions.