Search Results (129)

Climate change and human activities are widely recognized as major drivers of global biodiversity loss. The Brown Eared Pheasant (Crossoptilon mantchuricum), a ground-dwelling avian species unique to China, is confined to a highly fragmented range and faces persistent long-term threats. To devise robust and site-specific preservation strategies, it is imperative to elucidate the species’ sensitivity to climate change and pinpoint high-priority protection areas. In this study, we integrated field surveys, ensemble species distribution modelling, Marxan systematic conservation planning, and GAP analysis to assess habitat suitability changes under future climate scenarios and identify conservation gaps for the Brown Eared Pheasant. Our results demonstrate that the species’ distribution is primarily driven by annual temperature range, precipitation in the coldest and wettest quarters, and elevation, underscoring its highly restricted climatic niche. Based on current climatic conditions, highly suitable habitats are primarily distributed across specific mountainous regions: Hebei Province (Xiaowutai Mountains), Shanxi Province (the Taihang, Lvliang, and Taiyue mountain systems), Shaanxi Province (Huanglong Mountains), and northwestern Beijing (the Donglingshan area). Simulations conducted across prospective climatic scenarios suggest a continued decline in suitable habitat, which becomes increasingly restricted to higher latitudes and mountainous regions. According to our GAP analysis, current protected area networks fail to encompass 72.27% of the priority conservation zones identified, with significant gaps in the southern Lvliang, Taiyue, and Huanglong Mountains. The outcomes of this research establish a robust empirical foundation with which to inform prospective preservation strategies and habitat stewardship for the Brown Eared Pheasant. Full article

Understanding residents’ and tourists’ public space perceptions and satisfaction was essential for the sustainable planning and tourism development of historic towns. However, limited attention has been paid to the different perceptions between the two groups, as well as the nonlinear relationship between public space perception and satisfaction. Taking Fenghuang Ancient Town as the study area, this study used independent sample t-tests to examine the differences between residents and tourists. The XGBoost-SHAP model was further applied to identify key influencing factors and nonlinear interaction mechanisms affecting satisfaction. The results showed that: (1) residents perceived higher public awareness, space openness, and accessibility, whereas tourists reported higher crowd density and business prosperity; (2) color harmony most strongly influenced residents’ satisfaction, while spatial comfort had the strongest influence on tourists’ satisfaction; (3) color harmony and spatial comfort positively affected satisfaction, whereas space openness (residents) and crowd density (tourists) showed U-shaped relationships; and (4) for residents, the strongest interaction was between color harmony and business prosperity (0.015), while for tourists it was between spatial comfort and color harmony (0.038). These findings provided evidence-based guidance for sustainable public space planning and cultural heritage tourism management, contributing to inclusive governance and the long-term sustainability of historic towns. Full article

Understanding the spatial spillover effects of ecosystem services (ESs) on the water–energy–food (WEF) development level is critical for regional sustainability, yet empirical evidence remains limited. Using prefecture-level units in the Yellow River Basin (YRB), this study investigated the relationship between four ESs, i.e., water yield, carbon storage, food production, and soil conservation, with the WEF development level from 2000 to 2020. A spatial Durbin model and geographically and temporally weighted regression were employed to quantify global spatial spillover effects and local heterogeneity. Results showed that both the WEF development level and ESs improved over the study period. At the basin scale, carbon storage exhibited the strongest positive effects on WEF development, with direct, spillover, and total effects of 0.29, 0.89, and 1.18, respectively. At the regional scale, water yield was positively associated with the WEF development level in northern Shaanxi and Shanxi Provinces but negatively associated in western Inner Mongolia Autonomous Region. Carbon storage maintained weak but consistently positive associations across most regions. Food production showed strong positive associations in eastern Shandong Province but moderate negative associations in southern Shanxi and western Henan Provinces. Soil conservation showed strong positive associations in western Inner Mongolia and parts of Qinghai, whereas strong negative associations occurred in eastern Shandong and Henan provinces. These findings underscore the critical role of carbon storage in supporting coordinated WEF development and emphasize the need to enhance carbon storage and adopt region-specific ecosystem management strategies for sustainable development in the YRB. Full article

Driven by the demand for high-quality housing, fourth-generation residential buildings—known internationally as “Vertical Forest” and in China as “Urban Forest Garden”—have developed rapidly. Initially built in mild southern regions, they have recently expanded to colder northern areas, with over 50 projects underway in provinces such as Shanxi, Hebei, Shaanxi, and Gansu. Several cities have introduced design standards and incentives, and the China Association for Standardization of Engineering Construction has issued the “Design Standards for Urban Forest Garden Housing.” However, in cold regions, where winters are long and cold and summers are short and hot, there is a lack of systematic quantitative research on how balcony design affects building carbon reduction, energy efficiency, and indoor thermal comfort. To address this research gap, this paper poses the following research questions: (1) In fourth-generation residential buildings in cold regions, how do different combinations of balcony orientations affect annual energy consumption and indoor thermal comfort? (2) Which balcony configurations offer the best balance between carbon reduction, energy efficiency, and thermal comfort? Based on statistical analysis of terrace configurations from more than 40 projects, 12 typical configuration models were identified. Using Ladybug and Honeybee tools on the Grasshopper platform, building energy consumption and indoor thermal comfort were simulated. Multi-objective trade-off analysis was performed using the Pareto front method. In this study, indoor thermal comfort was evaluated using the PMV (Predicted Mean Vote) index. PMV is an index proposed by Professor Fanger that comprehensively reflects human thermal sensation, taking into account air temperature, humidity, wind speed, mean radiant temperature, human metabolic rate, and clothing thermal resistance. Its typical range is −3 (cold) to +3 (hot); in this study, the comfort zone was defined as −1 ≤ PMV ≤ 1. Key findings: (1) The southwest + south terrace configuration shows the highest annual energy consumption, exceeding the lowest (northwest + west) by 2.7%, indicating that south-facing terraces are less favorable for carbon reduction. (2) The best thermal comfort is achieved with east, west, and south orientations. Compared to the least comfortable combination (southwest + northwest), the difference in PMV comfort percentage reaches 2.4%. (3) The Pareto front reveals that beyond a certain comfort level, energy consumption increases sharply. The west + south and east + south combinations yield the highest thermal comfort (49.4%) while maintaining relatively low energy consumption (17.98 kWh/m²). Therefore, in cold regions, fourth-generation residential designs should prioritize terrace combinations integrating south-facing and side-facing orientations and avoid pure corner configurations to balance winter solar gain and summer shading. Full article

Mountainous traditional villages are rural heritage settlements shaped by complex environmental and socioeconomic interactions. Rapid urbanization has driven resource outflow and spatial restructuring, intensifying the conservation–development conflict. Existing conservation models relying on standardized criteria neglect village heterogeneity, and current studies insufficiently capture cluster-specific driving mechanisms across spatial scales. Using 153 traditional villages in the Qin–Ba Mountains of southern Shaanxi, this study shifts the analysis from overall spatial pattern identification to the comparison of cluster-specific driving mechanisms. The results indicate (1) traditional villages display an agglomeration pattern of “one primary core, one secondary core, and multiple peripheries,” forming valley corridor and hilly barrier clusters; (2) socioeconomic factors show greater explanatory power than natural factors at the global scale; (3) influencing factors exhibit dual heterogeneity, with intensity and direction varying across space and clusters displaying distinct dominant-factor combinations; and (4) socioeconomic factors may provide enabling conditions for traditional village conservation and adaptive reuse under appropriate governance contexts. Accordingly, valley corridor clusters can follow “conservation through development,” whereas hilly barrier clusters should adopt “development through conservation.” These findings offer empirical support for spatially differentiated governance of mountainous traditional villages. Full article

The new energy vehicle (NEV) industry is a key sector for achieving dual carbon goals and advancing regional green transformation. Its sustainable development depends on the deep coupling of the industrial chain and the innovation chain. Drawing on data from Shaanxi’s NEV industry covering the period 2014–2023, this study employed kernel density estimation (KDE), the entropy weight method, the coupling coordination degree model, and the optimal parameter geographical detector. Specifically, we examine Shaanxi’s national positioning and spatial pattern within the NEV industry, the spatiotemporal evolution of the coupling coordination degree between its industrial and innovation chains, and the key driving factors along with their interaction mechanisms. The results indicate that Shaanxi is situated within the secondary core growth zone of central and western China. Within the province, the industry exhibits a pronounced spatial pattern characterized by single core concentration in Xi’an, contiguous support across the Guanzhong region, and point-like distribution in northern and southern Shaanxi. The dual-chain coupling coordination degree in Shaanxi’s NEV industry has improved steadily, resulting in a four-tier structure comprising core breakthrough, secondary catch-up, weak foundation, and lagging predicament categories. The dominant driving factors are Industrial Agglomeration Degree, Research and Development (R&D) Funding Input, and Resource Utilization Rate. The interaction between Resource Utilization Rate and Integration Degree exerts the strongest effect. Full article

Traditional villages represent vital living heritage in China. We develop a multi-scale eco-coupling framework integrating GIS spatial analysis and 3D laser scanning to analyze the natural and social environment, spatial patterns, and architectural forms across macro–meso–micro levels in traditional villages of southern Shaanxi, and use partial least squares structural equation modeling (PLS-SEM) to test the hypothesized cross-scale pathways. The results show significant spatial clustering, mainly in the water-adjacent low-mountain valleys and under moderate gradients of GDP, population density, and road density. The morphology is classified as clustered, linear, or scatter shaped, while buildings are dominated by courtyard, patio, and single-row layouts with timber structures, rammed earth or stone walls, and double-pitched roofs. After reliability and validity checks, the PLS-SEM confirms significant macro–meso–micro pathways, with the meso scale as a key mediator. Overall, the study reveals that persistence depends on long-term coupling among multi-scale factors, providing theoretical and methodological support for conservation and sustainable development. Full article

Depression is one of the most common mental disorders in modern society, and it has become a serious threat to human health. The limitations of existing antidepressant drugs have prompted people to turn to the multi-target, low-toxic side effects of natural products. This article reviews the conventional nutrients (omega-3 fatty acids, folic acid, and mineral elements) and functional active ingredients (flavonoids, polysaccharides, saponins, and terpenoids) in medicinal and food homologous substances (MFHs). They show antidepressant potential by regulating neurotransmitters, improving hypothalamic–pituitary–adrenal (HPA) axis function, promoting neuroplasticity, inhibiting neuroinflammation, regulating ferroptosis, and interfering with the gut–brain axis. In addition, this paper discusses the application prospects of modern technologies such as microbial fermentation and nano-delivery in improving the bioavailability of MFHs and product development. In summary, MFHs have potential application value in dietary intervention and adjuvant therapies for depression; in the future, randomized controlled clinical trials should be strengthened, and multi-omics technology should be combined to promote the development of precision products so as to provide a new perspective for the development of new antidepressant drugs. Full article

In this study, global spatial autocorrelation, local spatial autocorrelation, Spearman correlation analysis, gray correlation analysis, entropy weight method, and the gravity model were used to analyze the spatiotemporal variation and environment-urban-economy-associated factors of air quality of 31 provinces in China during 2015~2022. From 2015 to 2022, the Air Quality Index (AQI) exhibited a downward trend in 30 out of 31 Chinese provinces, with the exception of Shaanxi Province. Concurrently, the annual average concentrations of PM_2.5, PM₁₀, SO₂, NO₂, and CO declined across the study period. High-high clusters and low-high outliers were observed in northern China, whereas low-low clusters and high-low outliers were distributed in southern China. Twelve provinces (38.7%) showed positive correlation (0.095~0.95), 18 provinces (58.1%) showed negative correlation (−0.76~0.095), and only Anhui showed no correlation between AQI and O₃. The comprehensive AQI quality presented a dual-core model in Sichuan (in the southwest) and Henan (in the central part) of China, while the comprehensive AQI improvement rate presented a single-core model in Jiangsu in the east of China. The gravity models incorporating AQI and GDP revealed that both air quality and economic performance improved over the study period. The spatial pattern of pollution evolved from a multi-core structure to a non-core structure, whereas the pattern of economic growth transitioned from a non-core structure to a dual-core structure, with the Beijing-Tianjin-Hebei region and the Yangtze River Delta emerging as the primary urban agglomerations. Full article

The Shaanxi section of the Qinling Mountains serves as a critical ecological transition zone and security barrier between northern and southern China. Monitoring the dynamics of its vegetation Net Primary Productivity (NPP) is essential for understanding regional carbon cycling and informing ecological management strategies. This study integrates three complementary analytical frameworks: the Mann–Kendall test combined with the Theil–Sen slope for linear trend extrapolation (MK-Theil-Sen), mechanistic simulation (CASA model), and machine learning (random forest). First, we analyzed the spatiotemporal evolution of NPP from 2000 to 2023. Then, based on three CMIP6 scenarios (SSP119, SSP245, SSP585), we projected NPP changes for 2030–2050 and compared results across different models and scenarios. The key findings are as follows: ① From 2000 to 2023, NPP in the Shaanxi section of the Qinling Mountains exhibited a fluctuating upward trend with a cumulative increase of 16.7%. Spatially, it showed a pattern of “higher in the south, lower in the north; higher in the west, lower in the east”. ② Multiple models predict continued NPP growth, though the magnitude remains uncertain. Mechanistic models, incorporating climate stress factors, yield relatively conservative projections. ③ Emission scenarios significantly influence future trends, with low-emission pathways (SSP119) favoring NPP enhancement and extended growing seasons. ④ Different vegetation types exhibit varying responses to scenario changes: broadleaf forests show the highest sensitivity, while grasslands and meadows demonstrate strong climate stability across models, with cultivated vegetation exhibiting intermediate sensitivity. This study provides comprehensive scientific references for regional ecological security assessment and adaptive management through historical analysis and multi-model, multi-scenario projections of NPP in the Shaanxi section of the Qinling Mountains. Full article

The tea lace bug, Stephanitis chinensis, is an important pest in the southwest tea region in China. It has recently emerged in some parts of the tea areas, severely impacting the profitability of spring tea. To clarify the distribution dynamics of S. chinensis under current and future climate change, this study used the MaxEnt model and ArcGIS software to predict the distribution and dominant environmental factors of S. chinensis. The results show that the mean precipitation of the warmest quarter (Bio18), the minimum temperature of the coldest month (Bio6), annual precipitation (Bio12), and the variation coefficient of temperature (Bio4) are the dominant environmental factors affecting S. chinensis distribution. Under the current climatic conditions, the suitable habitats for S. chinensis are mainly distributed in East and South Asia, with only a small distribution in southern Europe, southeastern North America, and coastal areas of southeastern South America; the highly suitable habitats are primarily distributed in China, southern Japan, and southern South Korea. The total suitable area of S. chinensis accounts for approximately 28.58% of China’s land area. The high-suitability regions are primarily concentrated in the Guizhou, Chongqing, Sichuan, Hubei, Hunan, Shaanxi, and Jiangsu provinces. Under future climate conditions, the total suitable area of S. chinensis will increase to varying degrees, primarily expanding northward, with the extension of high-suitability areas mainly concentrated in Hubei, Anhui, and Henan. The migration distance of the geographical distribution center ranges between 32.27 km and 96.13 km, with a primary shift toward the northeast. This study predicts potential suitable areas for the tea lace bug under different climate change scenarios. Specifically, regions at the highest risk, such as the Hubei, Anhui, and Henan provinces, should enhance monitoring and early warning systems and implement timely prevention and control measures to ensure the safe production of tea. Full article

The genus Isaria is a group of abundant and widely distributed entomopathogenic fungi that plays an important role in the history of traditional Chinese medicine. Entomopathogenic fungi with medicinal value were collected from the field, and optimal temperature and growth media compositions were investigated to establish a theoretical foundation for the future development of these strains. A strain of Isaria cateniobliqua, designated ICF, was isolated from soil in the Hualongshan National Nature Reserve in southern Shaanxi. The optimal cultivation temperature and nutrient solution were screened, and the effects of subcultivation on mycelium production, metabolite production, and hydroxyl radical scavenging activity of strain ICF were investigated. The optimal growth temperature for strain ICF was determined to be 21 °C, with the ideal culture medium consisting of glucose and tussah silkworm pupa powder supplemented with KH₂PO₄ and MgSO₄. Mycelium production and cordycepin content peaked in the fourth generation (G4), whereas peak metabolite production and cordycepic acid production occurred in the fifth generation (G5). Polysaccharide content was highest in the first generation (G1), and hydroxyl radical scavenging activity was optimal in G4. Exploring the optimal culture conditions of the strain provides a theoretical basis for its development, utilization, and industrial production for medicinal applications. Full article

Symplocos is an ecologically important genus that plays vital roles in subtropical evergreen broad-leaved mountain forests, including contributing to nutrient cycling, providing shelter and habitats for various organisms, and supporting overall plant diversity across East and Southeast Asia. Many species exhibit high levels of endemism and sensitivity to environmental change. China, with its wide range of ecosystems and climatic zones, is home to 18 endemic Symplocos species. Studies revealed that global warming is driving shifts in species diversity, particularly in mountains. Our study explores the current and projected richness patterns of endemic Symplocos species in China under climate change scenarios, emphasizing the implications for conservation planning. We applied stacked species distribution models (SSDMs), using key bioclimatic and environmental variables to predict current and future habitat suitability for endemic Symplocos species, evaluated model performance through multiple accuracy metrics, and generated ensemble projections to assess richness patterns under climate change scenarios. To assess the spatial configuration and fragmentation patterns of the endemic species richness under current and future climate scenarios, landscape metrics were calculated based on classified richness maps. The produced models demonstrated high accuracy with AUC > 0.9 and TSS > 0.75, highlighting the critical role of bioclimatic variables, particularly precipitation and temperature, in shaping endemic Symplocos distribution. Our analysis identifies the current hotspots of Symplocos endemism along southeastern China, particularly in Zhejiang, Fujian, Jiangxi, Hunan, southern Anhui, and northern Guangdong and Guangxi. These areas are at high risk, with up to 35% of endemic Symplocos species richness predicted to be lost over the next 60 years due to climate change. The study predicts a high decrease in endemic Symplocos species richness, especially in South China (e.g., Fujian, Guangdong, Guizhou, Yunnan, southern Shaanxi), and mid-level decreases in East China (e.g., Heilongjiang, Jilin, eastern Inner Mongolia, Liaoning). Conversely, potential increases in endemic Symplocos species richness are projected in northern and western Xinjiang, western Tibet, and parts of eastern Sichuan, Guangxi, Hunan, Hebei, and Anhui, suggesting these regions may serve as future refugia for endemic Symplocos species. The analysis of the landscape structure and configuration revealed relatively minor but notable variations in the spatial structure of endemic Symplocos richness patterns under current and future climate scenarios. However, under the SSP585 scenario by 2080, the medium richness class showed a more pronounced decrease in aggregation index and increase in number of patches relative to other richness classes, suggesting that higher emissions may drive fragmentation of moderately rich areas, potentially isolating populations of Symplocos. These structural changes suggest a potential reduction in habitat quality and connectivity, posing significant risks to the persistence of endemic Symplocos populations, which underscores the urgent need for targeted smart-climate conservation strategies that prioritize both current hotspots and potential future refugia to enhance the resilience of endemic Symplocos forests and their ecosystems in the face of climate change. Full article

To study the selenium (Se) content and dietary risk in typical Se-rich regions (the soil Se thresholds were as follows: high Se at 0.4–3.0 mg/kg and excessive Se at >3.0 mg/kg), the northern of Langao County, Ankang City, Shaanxi Province was studied. Contents of Se in crops and drinking water were analyzed. The average Se contents in drinking water was 12.32 μg/L in the excessive-Se and 13.50 μg/L in the high-Se areas. Corn, rice, sweet potato, and eggplant exhibited the highest average Se contents in the excessive-Se area, while potato and radish showed the highest levels in the high-Se area. Adults (and children) living in excessive-Se areas had a mean daily Se intake of 598 (305) μg/day, and those in high-Se areas had an intake of 536 (275) μg/day. Although crops were the main dietary source of Se, the contribution of drinking water, particularly for children, should not be overlooked as an additional source of Se intake. The average hazard quotients of adults (children) from excessive-Se and high-Se areas were 1.77 (1.95) and 1.58 (1.76), respectively. Therefore, there are non-carcinogenic health risks for humans in the two regions. Full article

The Qinba Mountains in China span six provinces, characterized by a large population, rugged terrain, steep peaks, deep valleys, and scarce flat land, making large-scale agricultural development challenging. Terraced fields serve as the core cropland type in this region, playing a vital role in preventing soil erosion on sloping farmland and expanding agricultural production space. They also function as a crucial medium for sustaining the ecosystem services of mountainous areas. As a transitional zone between China’s northern and southern climates and a vital ecological barrier, the Qinba Mountains’ terraced ecosystems have undergone significant spatial changes over the past two decades due to compound factors including the Grain-for-Green Program, urban expansion, and population outflow. However, current large-scale, long-term, high-resolution monitoring studies of terraced fields in this region still face technical bottlenecks. On one hand, traditional remote sensing interpretation methods rely on manually designed features, making them ill-suited for the complex scenarios of fragmented, multi-scale distribution, and terrain shadow interference in Qinba terraced fields. On the other hand, the lack of high-resolution historical imagery means that low-resolution data suffers from insufficient accuracy and spatial detail for capturing dynamic changes in terraced fields. This study aims to fill the technical gap in detailed dynamic monitoring of terraced fields in the Qinba Mountains. By creating image tiles from Landsat-8 satellite imagery collected between 2017 and 2020, it employs three deep learning semantic segmentation models—DeepLabV3 based on ResNet-34, U-Net, and PSPNet deep learning semantic segmentation models. Through optimization strategies such as data augmentation and transfer learning, the study achieves 15-m-resolution remote sensing interpretation of terraced field information in the Qinba Mountains from 2000 to 2020. Comparative results revealed DeepLabV3 demonstrated significant advantages in identifying terraced field types: Mean Pixel Accuracy (MPA) reached 79.42%, Intersection over Union (IoU) was 77.26%, F1 score attained 80.98, and Kappa coefficient reached 0.7148—all outperforming U-Net and PSPNet models. The model’s accuracy is not uniform but is instead highly contingent on the topographic context. The model excels in environments that are archetypal for mid-altitudes with moderately steep slopes. Based on it we create a set of tiles integrating multi-source data from RBG and DEM. The fusion model, which incorporates DEM-derived topographic data, demonstrates improvement across these aspects. Dynamic monitoring based on the optimal model indicates that terraced fields in the Qinba Mountains expanded between 2000 and 2020: the total area was 57.834 km² in 2000, and by 2020, this had increased to 63,742 km², representing an approximate growth rate of 8.36%. Sichuan, Gansu, and Shaanxi provinces contributed the majority of this expansion, accounting for 71% of the newly added terraced fields. Over the 20-year period, the center of gravity of terraced fields shifted upward. The area of terraced fields above 500 m in elevation increased, while that below 500 m decreased. Terraced fields surrounding urban areas declined, and mountainous slopes at higher elevations became the primary source of newly constructed terraces. This study not only establishes a technical paradigm for the refined monitoring of terraced field resources in mountainous regions but also provides critical data support and theoretical foundations for implementing sustainable land development in the Qinba Mountains. It holds significant practical value for advancing regional sustainable development. Full article