This study establishes a framework to assess greenspace supply-demand disparities related to thermal discomfort from the perspective of population mobility across urban functional zones (UFZs). High-resolution greenspace maps and location-based service (LBS) datasets for Nanjing, China, were combined with Spearman correlation analyses and a four-quadrant model to elucidate associations and matching patterns between greenspace exposure and thermal comfort. The findings indicate that population fluctuations affect the availability of actual greenspace, with correlations to thermal discomfort showing significant temporal variations among different UFZs. During morning workday hours, commercial zones have a significantly higher representation in Quadrant II (82.26%) compared to non-workdays (70.86%), which is characterized by high population density, low greenspace exposure, and pronounced thermal discomfort. In contrast, residential and public service zones maintain consistently high and stable proportions in Quadrant I across all periods. This spatial mismatch is primarily caused by differences in available greenspace quantities and population mobility. Planning adjustments should focus on ensuring sufficient greenspace provision in key areas during peak population mobility periods to mitigate thermal discomfort. Minimizing residents’ staying time in thermally uncomfortable zones, implementing time-specific greenspace access, and strategically increasing greenspace coverage are essential for improving the mismatch between greenspace supply and demand.

Morphology, the study of shapes or forms, when applied to tourism, emphasizes the multifarious spatial practices between morphological elements and tourism activities. However, existing literature on morphology in the context of tourism usually only focuses on a single or a limited number of study areas, overlooking common or even universal patterns across various tourism destinations. To address this gap, we utilize geospatial big data and present a case study on the morphology of 406 “AAAAA”-rated scenic areas in China. A framework based on “points”, “lines”, “planes”, and “solids” was designed to systematically organize and analyze morphological elements across scenic areas. The findings provide valuable insights for tourism planning and development, such as the co-occurrence of dense road networks and fragmented landscapes within scenic areas, as well as the resource- context-influenced (cultural or natural) associations between morphological features and tourism indicators. This research provides valuable strategic guidance for more effective and informed tourism development while acknowledging the trade-offs between generalizability and local specificity.

A low-carbon lifestyle presents new opportunities for sustainable urban development. While previous studies have verified the impact of the built environment and socio- economic status (SES) on low-carbon lifestyles, they have primarily focused on direct effects. At present, there is still a lack of analysis on the interaction effects on low-carbon lifestyles, and limited attention has been given to the peer effect in low-carbon lifestyles, especially in the context of residential differentiation. Therefore, we take Zhengzhou city as the case area and first calculate the low-carbon lifestyle of 1485 families from three dimensions: low-carbon action (A), low-carbon interest (I) and low-carbon opinion (O). We then analyze the direct and interactive impacts of the built environment and SES on low-carbon lifestyles and explore the peer effect. Our findings indicate that families with higher SES have higher levels of low-carbon interest and low-carbon opinion, but relatively low levels of low-carbon action. This suggests an interest-action bias in the low-carbon lifestyles of high-SES families. POI density, road network density and accessibility positively affect low-carbon lifestyles—that is, residents living in areas with well-developed infrastructure and convenient transportation tend to be green in their daily behavior. The peer effect influences low-carbon action, interest, and opinion by 54.6%, 34.9%, and 16%, respectively, indicating that the peer effect is most evident in low-carbon action. That is, the peer effect is more obvious in low-carbon action. In addition, the built environment affects the low-carbon lifestyles of different SES groups. Land-use mix positively increases low-carbon action and low-carbon interest among high-SES groups but reduces low-carbon opinion. Road network density positively affects the low-carbon action of high-SES groups and the low-carbon interest and low-carbon opinion of low-SES groups. This study explores low-carbon lifestyles from a situational perspective, providing a practical basis for policies aimed at accelerating a transition to sustainable living.

This study proposes a framework for the concept of “new quality productive forces” in the ice and snow economy (ISE) as a strategic response to global climate change and the demands of technological and industrial transformation for high-quality development. These new quality productive forces in the ISE have developed alongside the zonal distribution of natural resources, strictly adhere to ecological principles, and integrate value transformation mechanisms specific to ice and snow resources. Their development is projected to generate multiple benefits across ecological, economic, and social dimensions. The new quality productive forces in the ISE are characterized by technology-driven resource development, synergistic integration across the entire ice and snow industry value chain, and a focus on high-quality, green growth. Grounded in geography and economics, the new quality productive forces in the ISE link scientific innovation, the reallocation of productive factors, and industrial upgrading within the context of resource constraints. Furthermore, they expand the growth potential of the ISE by fostering new production relations through digital, intelligent, and green integration, while advancing low-carbon, sustainable development under the guiding principle that “ice and snow landscapes are also mountains of gold and silver.” For China’s ISE, these new quality productive forces emphasize rigorous resource protection, balanced human-environment relationships, a resilient integrated supply chain framework, and an efficient “dual circulation” economic model. Practical strategies include integrating production factors, optimizing spatial resource allocation, fostering industrial synergy, and adapting production relations, all aimed at advancing the sustainable and high-quality development of China’s ISE.

In research on the legendary Xia Dynasty of ancient China, the famous archaeological site of Erlitou and its culture are the most debated topics. A key question is whether this ancient culture is truly related to the Xia Dynasty. This study combines traditional literature (Xia Xiao Zheng), archaeological evidence (on alligators), and climate simulation (of autumn rains) to demonstrate that the ancient Chinese phenological calendar, Xia Xiao Zheng, likely originated in the same region as the Erlitou culture. A logical explanation of these findings is that both Xia Xiao Zheng and the Erlitou culture are indeed closely related to the Xia Dynasty.

Drought significantly constrains vegetation growth and reduces terrestrial carbon sinks. Currently, the spatiotemporal patterns and mechanisms of the differential impacts of soil and meteorological droughts on vegetation productivity remain inadequately understood. In this study, we analyzed soil moisture (SM), vapor pressure deficit (VPD), and gross primary productivity (GPP) to investigate their spatiotemporal patterns and the combined effects on GPP over China. The results revealed that: (1) Soil drought and meteorological drought generally exhibited temporally synchronous trends across China. (2) GPP was predominantly affected by the combined and synchronous effects of both SM and VPD, although their effects displayed directional variability differences in certain regions. (3) SM demonstrated a greater relative importance on GPP than VPD across more than half of the regions in China, whereas deciduous broadleaf forests were the only vegetation type primarily affected by VPD. (4) Under the lag effects, both SM and VPD exhibited bidirectional Granger causality with GPP, with the interaction between VPD and GPP proving more pronounced than that of SM. Our research provides valuable insights into the mechanisms through which SM and VPD influence GPP, contributing to improved predictions vegetation productivity and implementing ecological restoration.

Medicinal plant diversity (MPD) is an indispensable part of global plant diversity, serving as the foundation for human survival by offering remedies and preventive measures against diseases. However, factors such as overexploitation, competition from invasive alien species, and climate change, threaten the habitats of medicinal plants, necessitating a comprehensive understanding of their spatial distribution and suitable habitats. We leveraged a decade of field survey data on medicinal plant distribution in the Yinshan Mountains, combined with spatial analysis, species distribution modeling, and the Carnegie Ames Stanford Approach (CASA) to explore the MPD spatial distribution and suitable habitats. Spatial analysis revealed that the central and eastern parts of Yinshan Mountains were the primary MPD hotspots, with no cold spots evident at various spatial scales. As the spatial scale decreased, previous non-significant regions transformed into hotspots, with instances where large-scale hotspots became insignificant. These findings offer valuable guidance for safeguarding and nurturing MPD across diverse spatial scales. In future climate change scenarios within the shared socioeconomic pathways (SSP), the habitat suitability for MPD in the Yinshan Mountains predominantly remains concentrated in the central and eastern regions. Notably, areas with high net primary productivity (NPP) values and abundant vegetation coverage align closely with MPD habitat suitability areas, potentially contributing to the region’s rich MPD.

Situated in the semi-arid regions of North China, the Nihewan Basin documents the fluvio-lacustrine sequence and Pleistocene archaeological sites, offering an excellent opportunity to investigate human adaptation to environmental change in East Asia, especially in North China. However, paleoenvironmental datasets from Middle Pleistocene archaeological sites are not fully understood. Focusing on the evidence from the 0.63-0.49 Ma-old site of Jijiazhuang (Nihewan Basin, North China), this paper presents the results of various environmental indicators from the site context. Moreover, it explores the links between hominin behavioral adaptations and ecological variability during the extra-long interglacial period in North China. Sedimentological features of the excavated section indicate that the site was formed in the margin of the Nihewan paleolake. Based on well-constructed pollen, sediment grain size, color reflectance, and major geochemical element analyses, five stages of environmental changes were identified during site formation. This study indicates that hominins occupied the site at the early part of Stage 2, when the Nihewan paleolake had a relatively low water level and the climate was temperate, with strong weathering intensity dominated by wooded grassland landscapes. In conclusion, the results suggest that the extra-long duration of interglacial or mild stadial climate events (MISs 15-13) in the Northern Hemisphere may have provided favorable conditions for increased technological innovations and adaptive strategies among Middle Pleistocene hominins in the Nihewan Basin even in North China.

With the rapid advancement of global socio-economy and mounting environmental and ecological risks, China faces challenges in ensuring its food security and sustainable development, which further affects global food trade and security. This study aims to identify the supply‒demand match between cropland supply and food consumption and to evaluate sustainable cropland zoning in multiple scenarios and multidimensional assessments. This study uses ecological, environmental and socioeconomic data to quantify diverse food demand patterns into corresponding cropland demands, further mapping the spatio-temporal characteristics of China’s cropland supply‒demand matches. By utilizing shared socioeconomic pathways (SSPs), this study delineates multiple scenarios to determine the supply‒demand of cropland across different Chinese regions from 2030 to 2050. On the basis of ecological, geographical and socioeconomic datasets, this study constructs a multidimensional and multiscenario framework for sustainable agricultural zoning from 2030 to 2050 and proposes a future sustainable agricultural development strategy for each region in different periods. The results indicate that between 2002 and 2022, there was a significant gap between cropland supply and demand. Moreover, an obvious spatial mismatch is observed between cropland supply and demand across various Chinese regions. From 2030 to 2050, there is a noticeable shift in the spatial distribution of cropland supply and demand, with the supply‒demand match becoming more strained and varying considerably under different development scenarios. With significant differences between different development scenarios, different regions will have to adopt different development strategies at different periods. This study proposes a multiscenario and multidimensional simulation framework for future agricultural sustainable zoning, which aims to provide scientific insights and policy improvements to promote sustainable agricultural development.

Uncovering the evolution process of rural revitalization level (RRL) in China and elucidating the complex driving mechanism hold significant implications for implementing rural revitalization strategy and advancing rural modernization. This study analyzes the spatio-temporal evolution of China’s RRL from 2002 to 2022 and reveals its complex driving mechanism. The results show that China’s RRL steadily increased from 0.1083 to 0.4463, and the provincial RRL exhibited the characteristic of decreasing successively in the eastern region, the central region, and the western region. The overall differences of RRL are shrinking, and intra-group differences contribute almost 1/3 of the overall variation, more than the contribution of inter-group differences. Although the influencing factors show nonlinear characteristics, on the whole, economic level and human capital exhibit positive effects, while relief degree, urbanization, industrialization, and opening degree exhibit negative effects. Farmland resources and investment intensity exhibit the characteristics of positive effect and negative effect equilibrium. At the regional scale, influencing factors exhibit significant spatio-temporal heterogeneity. In the future, to achieve comprehensive rural revitalization, it is vital to implement systemic policy measures, such as enhancing industrial competitiveness, supplementing rural talents, and optimizing the relations between urban and rural areas as well as between industry and agriculture.

Exploring the spatial heterogeneity of ecosystem services (ESs) and their driving factors under various interaction patterns is essential for informing sustainable development policies. Using Northeast China as a case study, this research investigates eight key ESs, including water yield (WY), carbon storage (CS), food provision (FP), habitat quality (HQ), soil conservation (SC), wind-break and sand-fixation (WS), water purification (WP) and aesthetic landscape (AL). The study examines the complexity of ESs from three dimensions: individual ES, ES pairs and ES bundles, and further evaluates their spatial heterogeneity and socio- ecological drivers. The results indicate that the spatial distribution of ESs remained relatively stable from 2000 to 2020. During this period, WY and FP increased significantly, CS and HQ remained relatively unchanged. SC, WS and AL followed an “increase-decrease-increase” trend, and WP exhibited a “decrease-increase” fluctuation. Overall, synergistic relationships among ES Pairs were more prevalent than trade-offs. Notably, CS showed trade-offs with over 70% of the other ESs, while HQ exhibited trade-offs with SC, WS, WP, and AL. The FP-HQ synergy bundle, primarily located in the Greater Hinggan Mountains and eastern regions, emerged as the dominant ES bundle. Ecological factors—such as solar radiation, temperature, slope, DEM, and NDVI—exerted a stronger influence on ES patterns than social factors like GDP and population density. Furthermore, these ecological drivers had a greater impact on individual ESs compared to ES pairs or ES bundles. These findings offer valuable insights for policymakers to understand the complex interrelationships among ESs and to design more effective and regionally tailored management strategies.

Human activities have significantly impacted the land surface temperature (LST), endangering human health; however, the relationship between these two factors has not been adequately quantified. This study comprehensively constructs a Human Activity Intensity (HAI) index and employs the Maximal Information Coefficient, four-quadrant model, and XGBoost- SHAP model to investigate the spatiotemporal relationship and influencing factors of HAI-LST in the Yellow River Basin (YRB) from 2000 to 2020. The results indicated that from 2000 to 2020, as HAI and LST increased, the static HAI-LST relationship in the YRB showed a positive correlation that continued to strengthen. This dynamic relationship exhibited conflicting development, with the proportion of coordinated to conflicting regions shifting from 1:4 to 1:2, indicating a reduction in conflict intensity. Notably, only the degree of conflict in the source area decreased significantly, whereas it intensified in the upper and lower reaches. The key factors influencing the HAI-LST relationship include fractional vegetation cover, slope, precipitation, and evapotranspiration, along with region-specific factors such as PM_2.5, biodiversity, and elevation. Based on these findings, region-specific ecological management strategies have been proposed to mitigate conflict-prone areas and alleviate thermal stress, thereby providing important guidance for promoting harmonious development between humans and nature.

Understanding the characteristics and driving factors behind changes in vegetation ecosystem resilience is crucial for mitigating both current and future impacts of climate change. Despite recent advances in resilience research, significant knowledge gaps remain regarding the drivers of resilience changes. In this study, we investigated the dynamics of ecosystem resilience across China and identified potential driving factors using the kernel normalized difference vegetation index (kNDVI) from 2000 to 2020. Our results indicate that vegetation resilience in China has exhibited an increasing trend over the past two decades, with a notable breakpoint occurring around 2012. We found that precipitation was the dominant driver of changes in ecosystem resilience, accounting for 35.82% of the variation across China, followed by monthly average maximum temperature (Tmax) and vapor pressure deficit (VPD), which explained 28.95% and 28.31% of the variation, respectively. Furthermore, we revealed that daytime and nighttime warming has asymmetric impacts on vegetation resilience, with temperature factors such as Tmin and Tmax becoming more influential, while the importance of precipitation slightly decreases after the resilience change point. Overall, our study highlights the key roles of water availability and temperature in shaping vegetation resilience and underscores the asymmetric effects of daytime and nighttime warming on ecosystem resilience.

Dryland regions face complex interactions between urbanization and ecological changes, where effective coordination is essential for enhancing sustainability and resilience. However, most studies concentrate on the national or provincial scales, with insufficient research on county-level coordination, limiting the ability to provide targeted policies from a precise perspective. This study addresses this gap by analyzing 39 counties within the Hohhot-Baotou-Ordos-Yulin Urban Agglomeration (HBOYUA), a typical dryland urban cluster in China. We use daytime and nighttime remote sensing images to track the spatio-temporal evolution of urbanization and ecological conditions from 1992 to 2023. A novel quantitative framework based on an improved coupling coordination degree (CCD) is proposed to assess their coordination relationship. The results reveal that: (1) Urbanization and ecological quality both exhibited fluctuating upward trends, with spatial heterogeneity increasing for urbanization and decreasing for the eco-environment. Regions with better ecological conditions had higher urbanization levels. (2) The overall coordinated level improved from imbalance (0.36) to low-level coordination (0.55), although its spatial distribution remained uneven, with central urban areas showing higher CCD than surrounding counties. (3) Socioeconomic factors exerted greater effects on CCD than natural factors, with GDP and land surface temperature (LST) playing a significant role in interaction analysis. (4) In western arid regions, urbanization did not necessarily harm ecosystems; instead, ecological conditions improved alongside urbanization. This research offers targeted and valuable references for county and city governments in resource allocation and sustainable development. The proposed methodology is also adaptable for urban resilience studies in other regions.

Rapid urbanization in China has led to spatial antagonism between urban development and farmland protection and ecological security maintenance. Multi-objective spatial collaborative optimization is a powerful method for achieving sustainable regional development. Previous studies on multi-objective spatial optimization do not involve spatial corrections to simulation results based on the natural endowment of space resources. This study proposes an Ecological Security-Food Security-Urban Sustainable Development (ES-FS- USD) spatial optimization framework. This framework combines the non-dominated sorting genetic algorithm II (NSGA-II) and patch-generating land use simulation (PLUS) model with an ecological protection importance evaluation, comprehensive agricultural productivity evaluation, and urban sustainable development potential assessment and optimizes the territorial space in the Yangtze River Delta (YRD) region in 2035. The proposed sustainable development (SD) scenario can effectively reduce the destruction of landscape patterns of various land-use types while considering both ecological and economic benefits. The simulation results were further revised by evaluating the land-use suitability of the YRD region. According to the revised spatial pattern for the YRD in 2035, the farmland area accounts for 43.59% of the total YRD, which is 5.35% less than that in 2010. Forest, grassland, and water area account for 40.46% of the total YRD—an increase of 1.42% compared with the case in 2010. Construction land accounts for 14.72% of the total YRD—an increase of 2.77% compared with the case in 2010. The ES-FS-USD spatial optimization framework ensures that spatial optimization outcomes are aligned with the natural endowments of land resources, thereby promoting the sustainable use of land resources, improving the ability of spatial management, and providing valuable insights for decision makers.

Existing studies have mostly focused on sustainable intensification (SI) in agricultural systems, while neglecting the integrated analysis of SI for the land space utilization system (LSUS). This has resulted in a lack of systematic solutions in balancing sustainable resource utilization and environmental protection. This study reviewed SI’s conceptual framework and evaluation, identified the gaps, and proposed an analytical framework of SI with clear logic and modeling processes for LSUS. Key findings include: (1) Resource competition and ecosystem pressures have highlighted the need to extend traditional agriculture-focused SI to LSUS and establish a clear quantitative evaluation framework for SI; (2) SI for LSUS refers to a system state in which a specific sub-system produces its dominant functions with resource savings, reduced environmental impact, efficient function output, and stable/enhanced function provision, while sub-systems evolve in a coordinated and orderly manner; (3) The assessment framework of SI for LSUS clarifies modeling processes, suggested indicators, methods and scale hierarchy system to help policymakers identify SI priorities across scales, informing strategies to balance agricultural, socioeconomic, and ecosystem goals. This study overcomes the limitations of traditional SI, providing crucial insights for tracking SI performance and identifying barriers in LSUS to enlighten the sustainable land use and management practices.

With the continuous evolution of urban surface types, the impact of the urban heat island effect on the human population has intensified. Investigating the factors influencing urban thermal environments is crucial for providing theoretical support to urban planning and decision-making. In this study, Shenyang was selected to comprehensively analyse multiple factors, including topography, human activity, vegetation and landscape. Moreover, we used the random forest algorithm to explore nonlinear factors influencing land surface temperature (LST) over four years in the study area. The results revealed that from 2005 to 2020, the total areas with sub-high and high-temperature zones in northern Shenyang steadily increased. The area ratio of these zones increased from 20.18% in 2005 to 24.86% in 2020. Additionally, significant and strong correlations were observed between LST and variables such as the enhanced vegetation index (EVI), normalised difference vegetation index (NDVI), population density, proportion of cropland and proportion of impervious land. In 2010, proportion of impervious land exhibited the strongest correlation with LST at the 5 km scale, reaching 0.852 (p<0.01). The 4 km grid scale was identified as the optimal grid size for this study, while the 2 km grid performed the worst. In 2020, NDVI emerged as the most significant factor influencing LST. These findings provide valuable guidance for improving urban planning and developing sustainable strategies.

In drylands, biocrusts play crucial roles in regulating ecosystem functions. The study was conducted in the hilly rangelands of the semi-arid northern Negev of Israel, where we assessed the visual, morphological, spectral, and soil properties of livestock trampling routes and inter-route spaces in northern and southern facing hillslopes. Overall, both hillslope aspects were visually similar, whereas the ground surface of the routes was brighter (74.4% were characterized as having a ‘light’ color) than the inter-route spaces (86.8% were characterized as having a ‘dark’ color). These observations were supported by morphological identification of biocrust composition, which was dominated by cyanobacteria (67%) in the routes, and by mixed cyanobacteria/moss (56%) in the inter-routes. Mean Normalized Difference Vegetation Index (NDVI) was 24% higher in the inter-routes, while the mean Brightness Index (BI) was 12% higher in the routes. At the same time, the mean Crust Index (CI) was identical in the two microhabitats. Soil quality index (SQI), calculated based on the (pedoderm) soil properties of the two microhabitats, was 6% greater in the inter-routes than in the routes. This study suggests that recurrent trampling exacerbates soil compaction and shearing along the routes, thus preventing the successional development of complex biocrust compositions.

Achieving conservation goals in natural habitats requires a balanced approach that integrates both sustainable community development and nature conservation, rather than completely excluding human activities from wilderness areas. However, limited understanding exists regarding locals’ willingness to participate (WTP) in the construction and stewardship of national parks as well as their driving factors behind this willingness. To identify the key drivers that promote locals’ WTP in national parks, we investigated local residents’ participation willingness and embedded an additional structure perceived value (PV) into the Theory of Planned Behavior (TPB) model, analyzing the data by using structural equation modeling. Local communities were slightly willing to participate in Changtang National Park and conservation in general; interestingly, nomads’ willingness was stronger than settlers’. Perceived behavioral control (PBC) exhibited the most significant impact on WTP, with particular emphasis on the livelihood risks associated with grasslands. PV indirectly influenced WTP by affecting attitude (ATT), personal/social norms (PSN), and PBC, while it did not have a direct impact on WTP. For settlers and nomads, different variables influence their varying levels of willingness to engage in park participation. These results deepen our understanding of community willingness to participate and differences in drivers of WTP between settlers and nomads, contributing to relevant knowledge to inform seeking a balance between sustainable community development and nature conservation.

The intricate network of bilateral trade relationships among Pacific Rim countries (PRCs), along with the associated embodied carbon flows plays a pivotal role in shaping global carbon emission patterns and dynamics. This study employs a multi-regional input- output analysis and a symbiotic degree model to explore the symbiotic effects of trade-embodied carbon flows between China and PRCs. We show that between 2009 and 2021, China’s trade-embodied carbon exports to PRCs surged from 214.20 million tons to 614.80 million tons, driven largely by mechanical and electronic equipment. The share of the United States, Japan, and South Korea in China’s total embodied carbon exports to PRCs has declined, whereas Southeast Asian countries have emerged as the primary source of China’s embodied carbon imports. The degree of symbiosis in trade-embodied carbon between China and PRCs shifted from negative to positive, indicating a gradual trend toward positive asymmetric symbiosis. Moreover, China’s role in regional trade-embodied carbon flows has transitioned from passive to active, with its influence particularly pronounced in countries such as Vietnam, Thailand, Japan, South Korea, and Russia.

A comprehensive understanding of vegetation responses to climate extremes is essential for predicting ecological risks. The Tianshan Mountains, the world’s largest arid mountain system, are ecologically vulnerable to climate extremes, yet the spatiotemporal heterogeneity of vegetation responses is not well understood. To address this, we assessed changes in vegetation phenophases using the green-up date (GUD) and the monthly maximum vegetation index (MVI). Their relationship with climate extremes across seasons and geographic units was analyzed using Classification and Regression Tree and Principal Component Analysis. Results indicate that GUD advanced by 0.276 days/year, with MVI increasing in spring and decreasing in summer. On a yearly scale, nighttime heatwaves advanced GUD in all vegetation types at lower altitudes with higher snow cover, whereas daytime heatwaves delayed GUD in grasslands. On a monthly scale, early spring heatwaves generally benefitted vegetation, with positive effects decreasing from forests to grasslands: forests benefitted from March to May, forest-grassland from March to April, and grasslands only in March. By late summer, heatwaves were negatively correlated with MVI across all vegetation types. This study highlights the complex responses of vegetation to climate extremes and underscores the vulnerability of high-altitude, low snow-covered grasslands, which is crucial for guiding restoration efforts.

Studying runoff characteristics and quantifying human activities’ impact on northern Shaanxi, a crucial mineral resource area in China, is crucial to alleviate water resource contradictions. In this study, hydrological element trends were analyzed using the β-z-h three-parameter indication method. The Mann-Kendall, Pettitt, moving T, and Yamamoto methods were used to test the mutation point of hydrological elements. The Budyko framework was used to quantitatively assess the impacts of climate change and multiple human activities on runoff reduction. The results showed that (1): Precipitation (PRE), potential evapotranspiration (E₀), and temperature (TEM) showed increasing trends; runoff in the Huangfuchuan, Gushanchuan, Kuye River, Tuwei River, Wuding River, Qingjian River, and Yanhe River catchments showed decreasing trends (HFC, GSC, KYR, TWR, WDR, QJR, YR); whereas runoff in the Jialu River (JLR) catchment showed a “V-shaped” trend from 1980 to 2020. (2) Runoff was positively correlated with PRE and negatively correlated with E₀ and the subsurface index (n), with the elasticity coefficients of PRE, E₀, and n showing an increasing trend in the change period. (3) Human activities were a key factor in runoff reduction, although the impact of different human activities showed spatial variations. This study provides a scientific foundation for achieving the sustainable development of water resources in mining areas.

Green roofs play a vital role in promoting sustainable urban development and achieving carbon neutrality by enhancing carbon sequestration, oxygen release, and efficiency of land use. Despite these benefits, living roof coverage in China remains limited. To address the challenges in policy formulation, operational monitoring, and the absence of multi-scale retrofit strategies supported by robust assessment methods, this study develops a comprehensive evaluation framework. The framework integrates vector data, building age information, and point-of-interest (POI) data, and applies an optimized Prophet model to classify six major climate zones. This approach facilitates the selection of appropriate plant species and substrates while quantifying the potential for carbon sequestration and oxygen release. An assessment of 90 cities reveals approximately 1.3861 billion square meters of rooftop area suitable for green roof implementation, with an estimated annual carbon sequestration potential of 67.30 million tons and oxygen release of 30.36 million tons. Commercial buildings contribute significantly, comprising 65% of the total suitable area. Climate zones 2 and 3 exhibit the most favorable outcomes. The current study provides a reliable quantitative reference for evaluating the carbon sequestration and oxygen release capacities of green roofs and supports the formulation of effective retrofit policies.

The conversion of subtropical red soils into farmland involves complex transformations of iron oxides. Investigating iron mineralogy can enhance understanding of magnetic minerals in relation to soil formation on farmland in subtropical regions. In this study, we investigated the properties of iron oxide and its environmental implications in the farmland of Meizhou city, Guangdong province. The results showed that farmland soils had higher magnetism than the red soils developed from the same metamorphic rock. The red soils displayed significantly higher concentrations of goethite and hematite than the farmland soils. The dominant factor influencing the magnetic changes in farmland and red soils was the concentration of fine-grained ferromagnetic minerals. Red soil magnetism is an indicator of soil weathering intensity, whereas farmland soil magnetism is closely related to human cultivation activities. In contrast to the red soils, the farmland soils lacked the pronounced transformation of ferromagnetic minerals into hematite and goethite. A vigorous oxidation process catalyzes the transformation of strong magnetic minerals into significant amounts of hematite and goethite, which promotes the reduced magnetism of red soils. The conversion of red soils into farmland soils initially increased the accumulation of ferromagnetic materials due to cultivation processes. However, long-term cultivation led to the gradual loss of fine-grained ferromagnetic minerals, while goethite and lepidocrocite became the dominant magnetic mineral types.

The amplitude of the annual temperature cycle (ATC) is a crucial component of Earth’s climate and profoundly influences its phenology and ecosystem dynamics. However, most previous studies on ATC amplitude have been confined to the post-industrial instrumental period. Although a few studies have reconstructed ATC amplitudes over the past few centuries using proxy data, these efforts have been limited to regional scales, leaving the global profile of ATC amplitude from the pre- to post-industrial periods poorly understood. Here, leveraging rigorous evaluation and screening of monthly mean air temperature data derived from eleven CMIP5/CMIP6 models spanning the last millennium, combined with grid-based weighted averaging, we produced reliable ATC amplitude series for global and hemispheric land areas since 850 CE. Our analysis reveals a significant reduction in ATC amplitude since the 1860s across global and Northern Hemispheric lands, whereas the Southern Hemisphere has been relatively stable. The unprecedented decline in ATC amplitude since the late 19th century stands in stark contrast to the modest increases observed during the Medieval Climate Anomaly (ca. 1000-1300 CE) and the Little Ice Age (ca. 1400-1850 CE). These findings, particularly the distinct shift in ATC amplitude between the pre- and post-industrial periods, provide an early global fingerprint of anthropogenic forcing on climate change.

This study investigates climate- and human-induced hydrological changes in the Zavkhan River-Khyargas Lake Basin, a highly sensitive arid and semi-arid region of Central Asia. Using Mann-Kendall, innovative trend analysis, and Sen’s slope estimation methods, historical climate trends (1980-2100) were analyzed, while land cover changes represented human impacts. Future projections were simulated using the MIROC model with Shared Socioeconomic Pathways (SSPs) and the Tank model. Results show that during the past 40 years, air temperature significantly increased (Z=3.93***), while precipitation (Z=-1.54*) and river flow (Z=-1.73*) both declined. The Khyargas Lake water level dropped markedly (Z= -5.57***). Land cover analysis reveals expanded cropland and impervious areas due to human activity. Under the SSP1.26 scenario, which assumes minimal climate change, air temperature is projected to rise by 2.0℃, precipitation by 21.8 mm, and river discharge by 1.61 m³/s between 2000 and 2100. These findings indicate that both global warming and intensified land use have substantially altered hydrological and climatic processes in the basin, highlighting the vulnerability of western Mongolia’s water resources to combined climatic and anthropogenic influence.

Ecosystems along the eastern margin of the Qinghai-Tibet Plateau (EQTP) are highly fragile and extremely sensitive to climate change and human disturbances. To quantitatively assess climate-induced ecosystem responses, this study proposes a Climate-Induced Productivity Index (CIPI) based on the Super Slack-Based Measure (Super-SBM) model using remote sensing data from 2001 to 2020. The results reveal persistently low CIPI values (0.47-0.53) across major ecosystem types, indicating widespread vulnerability to climatic variability. Among these ecosystems, forests exhibit the highest CIPI (0.55), followed by shrublands (0.54), croplands (0.53), grasslands (0.51), and barelands (0.43). The Theil index analysis further demonstrates significant intra-group disparities, suggesting that extreme climatic events amplify CIPI heterogeneity. Moreover, the dominant environmental drivers differ among ecosystem types: the Palmer Drought Severity Index (PDSI) primarily constrains grassland productivity, solar radiation (SRAD) strongly influences shrub and cropland systems, whereas subsurface factors exert greater control in forested regions. This study provides a quantitative framework for evaluating climate-ecosystem interactions and offers a scientific basis for long-term ecological monitoring and security planning across the EQTP.

A comprehensive understanding of urbanization impacts on landscape dynamics, eco-environmental consequences, and advancements in human habitation is paramount for effectively advancing urbanization-related sustainable development goals. This study predicted the urbanization process within the Hohhot-Baotou-Ordos-Ulanqab (HBOU) region and its projected implications for ecology, human settlement, and energy consumption in 2020-2050 using multi-source data and models under Shared Socioeconomic Pathways (SSPs). The results revealed that the HBOU region’s urban area grew by 624.66 km² between 1990 and 2020. By 2050, it is expected to reach 1793.49±169.30 km², mainly expanding into cropland (58.95%) and natural ecological land (31.79%). Urban greening is projected to enhance, with the highest urban green space (UGS) predicted under SSP1 (32.42%). Under this scenario, the per capita urban area (PCUA) and per capita urban green space area (PCUGA) are projected to reach 172.66 and 55.63 m²/person in 2050, respectively. Furthermore, the ecological and energy utilization impacts are anticipated to decrease by 3.99% to 37.52% relative to alternative scenarios. Our projections suggest that limiting urbanization area in the HBOU region to 1500-1600 km² would significantly enhance the settlement environment and mitigate ecological and energy consumption effects. These results guide urban strategies balancing ecology, energy use, and habitation in arid regions.

Rapid regional population shifts and spatial polarization have heightened pressure on cultivated land—a critical resource demanding urgent attention amid ongoing urban-rural transition. This study selects Jiangsu province, a national leader in both economic and agricultural development, as a case area to construct a multidimensional framework for assessing the recessive morphological characteristics of multifunctional cultivated land use. We examine temporal dynamics, spatial heterogeneity, and propose an integrated zoning strategy based on empirical analysis. The results reveal that: (1) The recessive morphology index shows a consistent upward trend, with structural breaks in 2007 and 2013, and a spatial shift from “higher in the east and lower in the west” to “higher in the south and lower in the north.” (2) Coordination among sub-dimensions of the index has steadily improved. (3) The index is expected to continue rising in the next decade, though at a slower pace. (4) To promote coordinated multidimensional land-use development, we recommend a policy framework that reinforces existing strengths, addresses weaknesses, and adapts zoning schemes to current spatial conditions. This research offers new insights into multifunctional cultivated land systems and underscores their role in enhancing human well-being, securing food supply, and supporting sustainable urban-rural integration.

Landslides pose a formidable natural hazard across the Qinghai-Tibet Plateau (QTP), endangering both ecosystems and human life. Identifying the driving factors behind landslides and accurately assessing susceptibility are key to mitigating disaster risk. This study integrated multi-source historical landslide data with 15 predictive factors and used several machine learning models—Random Forest (RF), Gradient Boosting Regression Trees (GBRT), Extreme Gradient Boosting (XGBoost), and Categorical Boosting (CatBoost)—to generate susceptibility maps. The Shapley additive explanation (SHAP) method was applied to quantify factor importance and explore their nonlinear effects. The results showed that: (1) CatBoost was the best-performing model (CA=0.938, AUC=0.980) in assessing landslide susceptibility, with altitude emerging as the most significant factor, followed by distance to roads and earthquake sites, precipitation, and slope; (2) the SHAP method revealed critical nonlinear thresholds, demonstrating that historical landslides were concentrated at mid-altitudes (1400-4000 m) and decreased markedly above 4000 m, with a parallel reduction in probability beyond 700 m from roads; and (3) landslide-prone areas, comprising 13% of the QTP, were concentrated in the southeastern and northeastern parts of the plateau. By integrating machine learning and SHAP analysis, this study revealed landslide hazard-prone areas and their driving factors, providing insights to support disaster management strategies and sustainable regional planning.