Search Results (1,901)

Existing studies have mainly focused on either intangible cultural heritage (ICH) or traditional villages separately, while limited attention has been paid to their coupled spatial relationship and influencing mechanisms at the provincial scale. To address this gap, this study investigates the spatial characteristics and influencing factors of 869 national and provincial intangible cultural heritage (ICH) items and 777 traditional villages in Yunnan Province using Geographic Information Systems (GISs) and geographic detector methods. The results indicate significant differences in their spatial distribution patterns: ICH exhibits a “multi-core clustering” structure, whereas traditional villages present a “dual-core clustering with multiple dispersed patches” pattern. The study further reveals a spatial mismatch as well as a significant positive spatial correlation between ICH and traditional villages. Natural environmental conditions and historical-cultural factors jointly shape their spatial differentiation, while socio-economic factors such as urbanization exert a stronger influence on ICH distribution, and demographic and economic conditions more strongly affect traditional villages. This study contributes to the literature by integrating cultural landscape theory with GIS-based spatial analysis to reveal the spatial interaction mechanisms between ICH and traditional villages in Yunnan Province. The findings provide theoretical support and practical implications for cultural heritage conservation, rural revitalization, and territorial spatial planning in ethnically diverse border regions. Full article

Background/Objectives: Vitamin D deficiency is a global health concern, yet circulating 25-hydroxyvitamin D (25OHD) concentrations vary substantially across geographical regions and ancestral groups. Genetic predisposition may contribute to these differences. This systematic review aimed to synthesize evidence from genome-wide association studies (GWAS) on genetic variation associated with circulating 25OHD across populations from different ancestral backgrounds and to evaluate linkage disequilibrium (LD) between reported variants. Methods: A systematic review was conducted according to PRISMA 2020 guidelines. PubMed and the GWAS Catalog were searched to identify genome-wide association studies (GWAS) on circulating 25-hydroxyvitamin D (25OHD) concentrations. Studies were screened against predefined eligibility criteria, and data were extracted using a standardized framework. Methodological quality was assessed using a standardized tool, and study power adequacy was assessed formally. Genome-wide significant SNPs were extracted, and unique variants between studies were grouped by ancestry. Among these, dbSNP-indexed variants were grouped into genomic cluster windows and evaluated for LD structure. Results: Fifteen GWAS were included. Across these studies, 349 genome-wide significant SNP associations were identified, corresponding to 294 unique variants, of which 283 were indexed in dbSNP and retained for genomic and LD analyses. Variant discovery was dominated by large-scale European-ancestry studies, although African, Middle Eastern, East Asian, Hispanic/Latino, South Asian, and trans-ethnic studies also contributed signals. Some evidence of ancestry-specific variation was apparent, yet not conclusive due to lower study power in non-European cohorts. Variant aggregation was strongest at biologically relevant vitamin D loci, including GC, CYP2R1, DHCR7/NADSYN1, and FLG. Fifteen variants were replicated in at least two independent cohorts. LD-based clustering identified several high LD groups comprising variants identified across studies, with the strongest LD appearing between variants within established vitamin D-related loci, particularly GC, CYP2R1, DHCR7/NADSYN1, and FLG. Conclusions: Circulating 25OHD appears to be influenced by shared core loci involved in vitamin D metabolism, across ancestries. Although some evidence of ancestry-specific variation was identified, findings should be interpreted with caution, in light of the predominance of European-ancestry GWAS and scarcity of sufficiently powered GWAS for other ancestral populations. Larger GWAS in non-European populations are essential for improving ancestry-specific variant discovery and interpretation. Full article

Introduction: Freshwater habitats underpin global biodiversity and provide an array of essential ecosystem services to humans. However, threat hotspots like the Iberian Peninsula combine severe anthropogenic impacts (habitat degradation, climate change, and biological invasions, among others) with a high number of endemic range-restricted freshwater species. Despite the urgency, current conservation actions fall short of providing adequate protection. The irreplaceability index has been proposed as a useful assessment tool to focus limited efforts on areas that provide the highest benefit for threatened species. However, the transboundary nature of many rivers in the Iberian Peninsula can be a source of inefficiencies in protection if prioritisation efforts are conducted at a national rather than a peninsular scale. Objective: The aim of this study is to identify priority conservation basins for threatened native freshwater fish in the Iberian Peninsula and to evaluate the impact of national versus transboundary management strategies on the spatial protection afforded to these species. Methodology: The irreplaceability index was calculated for each basin by integrating basin richness, species rarity and their IUCN Red List conservation status. First, we modelled the species’ probability of presence using field observations recorded since 2000. Rarity was then calculated as the ratio between the modelled probability and the total number of basins within the species’ theoretical natural distribution. We then weighted each species’ rarity by its IUCN Red List conservation status, with higher weights to threatened species. We then calculated the basin irreplaceability index as the sum across all the species present in the basin of their conservation status-weighted rarity and ranked them according to this index. We replicated this approach considering Spain and Portugal independently, and both countries as one conservation planning unit. Results and Conclusions: The most irreplaceable basins were those harbouring a high density of threatened, narrow-range endemics. The priorities in each country differ depending on whether management strategies adopt a national or a broader geographical approach. Therefore, effective conservation requires transboundary planification to safeguard the shared biodiversity across countries. Full article

In UAV-based remote sensing, accurate and efficient image mosaicing is crucial for achieving real-time monitoring. Traditional cloud-centric processing paradigms, however, face core scientific challenges such as high latency, bandwidth bottlenecks, and limited autonomy, making them inadequate for dynamic, real-time scenarios. To address these issues, this paper proposes an edge-computing-enabled UAV image mosaicing system. The system consists of a UAV remote sensing platform and an edge computing terminal, with the core being our novel B-SIFT-ILS algorithm. The algorithm first uses geographic coordinates for unified registration, constructs a Gaussian scale space for multi-resolution representation, and then precisely locates extrema in the Difference of Gaussian (DoG) space using a 3D quadratic function. A BANSAC algorithm is subsequently employed to refine feature points and extract stable SIFT features, and finally, Iterative Least Squares (ILS) are used to achieve seamless mosaicing. Experimental results demonstrate that, compared with classical RANSAC, the proposed method achieves superior feature sampling accuracy (rotation: 0.879, translation: 0.877) and lower latency. The ILS-based smoothing stage effectively eliminates noise and ghosting without introducing gradient reversal, performing comparably to deep learning methods while significantly outperforming direct averaging and Gaussian approaches. On the NVIDIA Jetson Orin NX edge terminal, a single processing instance requires only 1124 ms, highlighting its strong potential for real-time, low-latency, and autonomous mosaicing tasks. Future research will focus on extending the approach to non-planar terrains and implementing adaptive parameter tuning for the BANSAC algorithm. Full article

With the growing focus on people-centered urban development sustainability in megacities, urban amenities have emerged as an important factor consistently associated with residential differentiation and restructuring. Understanding how it relates to the structure of social space is essential to advancing spatial equity. The study developed an analytical framework that integrates functional characteristics and supply patterns and applied Multi-scale Geographically Weighted Regression (MGWR) to examine how amenities shaped socio-spatial differentiation within Beijing’s Fifth Ring Road from 2015 to 2025. The results indicate that socio-spatial differentiation showed a rise followed by a decline across the three time points examined, yet its spatial pattern maintained a stable agglomeration characteristic of “high in the core area and low in the peripheral areas.” Significant differences exist in the roles of amenities across different attributes and scales. Market-driven factors, represented by amenity density and amenity diversity, typically exert their influence over larger spatial scales and are generally associated with spatial mixing and provide baseline opportunities for potential social interaction. Attributes such as amenity publicness and amenity uniqueness, which are more influenced by institutional and capital factors, primarily operate at local scales. While they are often associated with exclusionary effects in traditional core areas, they are also consistent with a certain degree of spatial integration in some revitalized districts. This study offers a more nuanced explanation for understanding the socio-spatial restructuring of megacities in transition and provides empirical evidence for advancing more equitable and sustainable urban governance. Full article

Pavement damages along the Qinghai–Xizang Highway (QXH) in permafrost regions are jointly controlled by geographical and engineering factors, leading to higher damage rates than in non-permafrost regions. However, the overall development trend of these damages and the spatial–temporal patterns have not been systematically quantified. To analyze the spatial distribution of different pavement damages, reveal the spatial–temporal associations, and analyze the spatial heterogeneity of the driving factors, three field surveys were conducted in 2014, 2019 and 2024, with records of seven major pavement damages. Statistical analyses were used to examine the relationships among single and co-occurring damages. Then, a novel geographical model, combining a graph convolutional network with multi-scale geographically weighted regression (GCN-MGWR), was further developed to treat the QXH as a linear geographic unit and to assess the spatial heterogeneity and relative contribution of different influencing factors. The results show that the mean pavement damage ratios in permafrost regions during the three surveys are 4.21%, 6.82%, and 4.74%, respectively, with crack-type damages (transverse, longitudinal, and block cracking) exhibiting the highest occurrence rates. The three strongest pairs of correlations are transverse and longitudinal cracking (0.584), transverse and block cracking (0.570), and waving and rutting (0.622). The primary factors influencing crack-type damages are embankment thickness, mean annual ground surface temperature (MAGST), elevation and existing damages. Transverse and longitudinal cracking show a pronounced increase with rising MAGST, and embankment thickness below 1 m or above 4 m significantly contribute to the development of both crack types (SHAP > 0.5). Overall, the evolution of crack-type damages has shifted from being primarily controlled by geographical factors to being controlled by the combined influence of engineering and geographical factors during 2014–2024. The factor contributions identified by the GCN-MGWR model provide quantitative support for the regional adaptive design and specific maintenance of roadway in permafrost regions. Full article

Connected vehicle platforms enable large-scale collection of vehicle dynamics data from production fleets, creating opportunities for passive roadway monitoring using onboard sensing systems. While existing vibration-based approaches primarily focus on pavement roughness estimation, the ability of fused onboard signals to capture defect-level characteristics remains insufficiently explored. This study investigates whether Road Surface Monitoring (RSM) signals, developed by Honda as an integrated OEM sensing approach, contain distinguishable patterns associated with specific road surface defects. A framework is developed to analyze, detect, and classify defect-related vibration signatures using these fused signals. The approach introduces the Defect Consistency Index (DCI), which measured a 29% average difference between pothole and patching signal signatures within the dataset. A threshold-based Defect Identification Algorithm (DIA) was then applied to detect defective segments, achieving 89% detection accuracy. A machine learning pipeline using shape-based features was subsequently used to classify potholes and patching, achieving up to 90% classification accuracy on the evaluated dataset. The framework was evaluated using real-world RSM data collected from a single instrumented vehicle within a limited geographic region. The results indicate that fused vibration signals contain recurring defect-related patterns that may support defect-level analysis using compact, non-visual measurements. These findings indicate the potential of connected vehicle vibration sensing for scalable roadway monitoring while highlighting the need for broader validation across vehicles, environments, and defect conditions. Full article

Background/Objectives: No study has investigated the effect of the catechol-O-methyltransferase (COMT) Val158Met rs4680 polymorphism in cognitive and executive performance in migraine. The current study investigated the potential influence of the Val158Met rs4680 polymorphism in cognitive performance/executive function in women with migraine. Methods: One hundred and forty women with migraine (70 chronic and 70 episodic) and 70 healthy controls completed the following neurocognitive tests (D2 Attention test and Rey–Osterrieth Complex Figure) and executive functions (subtest “Digits D/R/I” of the Wechsler Adult Intelligence Scale WAIS-IV battery for, the 5-Digit test, the Symbol Search for and the Zoo Test) for evaluating selective attention, visual perception, working memory, mental inhibition, processing speed and planning/decision making, respectively. Thus, three genotypes (Val/Val, Val/Met, and Met/Met) of the Val158Met polymorphism were identified by polymerase chain reaction. The effect of group and Val158Met genotype in neurocognitive tests and executive functions was evaluated with multivariate analysis of covariance (MANCOVA). Results: The MANCOVA revealed a significant Val158Met polymorphism* group interaction on neurocognitive performance (Wilk’s λ = 0.393, F [76,688] = 2.425, p < 0.001, n2p = 0.208, 1 − β = 0.999), not influenced by age (Wilk’s λ = 0.920, F [19,174] = 0.743, p = 0.734, n2p = 0.035, 1 − β = 0.120), educational level (Wilk’s λ = 0.875, F [19,174] = 1.024, p = 0.440, n2p = 0.047, 1 − β = 0.190) and prophylactic medication (Wilk’s λ = 0.855, F [19,174]= 1.000, p = 0.467, n2p= 0.145, 1 − β = 0.686). Post hoc analyses revealed that women with chronic migraine with the Met/Met genotype exhibited domain-specific better performance (i.e., higher selective attention, visuospatial memory) and executive functioning (i.e., working memory, planning/decision making) than those women with chronic migraine carrying Val/Val or Val/Met genotypes. Conclusions: We found an association of the Met/Met genotype with neurocognitive performance/executive functioning, particularly in women with chronic migraine since women with chronic migraine carrying the Met/Met genotype showed domain-specific better cognitive performance/executive functioning than those with the Val allele. Future studies including large sample sizes from different geographic locations are needed to better generalizability and validity of the current results. Full article

Despite geographical proximity and broadly similar agro -climatic conditions, China and Vietnam show sharply divergent coffee export performance, with Vietnam ranking as the world’s second largest exporter, while China’s exports remain modest. This study compares the determinants of their bilateral coffee exports over 2001 to 2022, using a gravity model estimated by Poisson pseudo maximum likelihood with partner and year fixed effects, a specification that retains zero trade flows and absorbs global price and demand shocks. Once these common shocks and fixed bilateral factors are controlled, trading-partner demand characteristics such as GDP, population, and urbanization are not robust determinants of exports for either country. The most consistent determinant is domestic production, which is positively associated with exports for both nations and helps explain their divergent export scale. Domestic consumption cannot be separated cleanly from production, so it is not interpreted as crowding out exports. On the policy dimension, Vietnam’s WTO accession shows a positive association with exports while China’s Belt and Road participation shows none, but these are institutionally different forms of integration and are read as associations, rather than causal effects. The findings carry implications for sustainable development, linking producer competitiveness to livelihoods under Goal 1, growth and decent work under Goal 8, and the balance between domestic and export use of production under Goal 12. Full article

Soil wind erosion (SWE) remains a significant challenge to improving ecological environmental quality and achieving sustainable socioeconomic development in drylands of northern China. An in-depth understanding of the spatio-temporal variations and underlying mechanisms of regional SWE is a prerequisite for the scientific prevention and mitigation of erosion-related hazards. However, in regions with high variability in intra-annual climate, quantitative studies on the spatial heterogeneity and intra-annual variability of drivers of SWE are scarce. This knowledge gap poses challenges for policymakers in developing effective landscape management strategies that are spatially and temporally specific. Here, the dynamics of SWE in the Xilingol typical steppe of China were simulated using the Revised Wind Erosion Equation (RWEQ) at seasonal and annual scales during 2000–2020. Stepwise regression and geographically weighted regression (GWR) were employed to examine the spatial heterogeneity in the relationships between SWE and environmental variables. The results revealed that RWEQ simulations were significantly correlated with the frequency of dust storm events at the seasonal scale (R² = 0.807, p < 0.01). SWE in spring accounted for approximately two-thirds of the annual total, indicating that spring was the critical period for SWE control. High SWE intensity was concentrated in sandy soil regions, with the Otindag Sandy Land and Gahai Elesu Sandy Land being identified as priority areas for desertification prevention and control. Over the study period, SWE exhibited an overall decreasing trend at both seasonal and annual scales, suggesting an enhancement in the ecosystem’s capacity for windbreak and sand stabilization. The stepwise regression results indicated that climatic factors generally had greater explanatory power than topographic and landscape pattern variables. Wind speed showed the strongest association with SWE across different time scales, whereas the relationships of normalized difference vegetation index (NDVI) and precipitation with SWE exhibited clear seasonal dependence. The GWR results further revealed pronounced spatial heterogeneity and seasonal variability in both the direction and magnitude of the associations between SWE and climatic and landscape pattern variables. These findings provide scientific support for identifying priority areas for desertification prevention and for developing spatio-temporally targeted landscape management strategies in dryland sandy regions. Full article

Phytoplankton communities in the proposed water source area of the Western Route of the South-to-North Water Diversion Project showed multi-level responses across monitoring-period groups and diversion areas. Based on 64 valid samples, total biomass ranged from 0.027 to 5.659 mg L⁻¹ and showed no consistent differences between monitoring-period groups or diversion areas, indicating site- and sampling-period-scale patchiness. Among the dominant biomass-contributing taxa, most were diatom taxa, and the relative contributions of the top ten dominant taxa and Other taxa were reorganized among monitoring-period–area combinations. NMDS, PERMANOVA, and PERMDISP showed that monitoring period was significantly associated with community structure, whereas diversion-area effects were not significant. dbRDA indicated significant environmental–spatial constraints on community composition, with an adjusted explanatory power of 28.2%; T, NH₄⁺–N, TN, NO₃⁻–N, EC, pH, DO, and DTN were significant predictors. VPA showed stronger pure environmental than pure spatial effects, while DDR and EDR revealed significant geographic and environmental distance relationships. Taxonomic Bray–Curtis null models suggested a predominance of stochastic-like taxonomic turnover signatures, with stronger deterministic-like deviations in the upper-line diversion area. GAM identified NH₄⁺–N, DO, and EC as significant biomass predictors. These findings support integrating biomass, community composition, measured physicochemical variables, and taxonomic assembly signatures into sustainability-oriented phytoplankton monitoring for high-elevation riverine water source areas, thereby providing ecological evidence for sustainable water source protection and adaptive management. Full article

Land-use change is a major driver of ecosystem service reconfiguration, yet the character and intensity of resulting trade-offs remain highly variable across studies. This review synthesizes English-language research retrieved primarily from the Web of Science Core Collection and supplemented by Scopus and Google Scholar, with particular attention to the multi-scale characteristics of trade-offs, the analytical consequences of different assessment approaches, and their relevance for sustainability governance. The reviewed literature reveals several recurrent patterns. Intensive land conversion commonly produces short-term gains in provisioning or construction-related benefits while reducing regulating and supporting services. Trade-offs are strongly scale dependent, reflecting differences in ecological processes, land-use decisions, and governance units rather than analytical sensitivity alone. The landscape configuration further shapes ecosystem service interactions in ways that cannot be inferred from land-use area alone. However, evidence on restoration co-benefits, spatial-optimization gains, and governance claims based on scenario results remains context-dependent. These findings should be interpreted as conditional support for comparing land-use options, identifying potential trade-off displacement, and clarifying planning constraints, rather than as proof that restoration or optimization will automatically improve governance outcomes. The current evidence base is geographically uneven and strongly concentrated in Chinese case studies, which enriches planning-oriented research but limits straightforward generalization across institutional and environmental settings. Further progress may depend on stronger cross-scale and dynamic analysis, closer integration of the ecosystem service supply, demand, and flow, and more explicit treatment of uncertainty. More importantly, the value of future research will lie not simply in producing additional maps or indicators, but in establishing a clearer correspondence between the type of evidence generated and the governance decisions it is expected to inform. Full article

Tourism destinations increasingly serve both domestic and international visitors whose geographic behaviors may differ substantially, yet most analytical frameworks treat visitor distributions as spatially homogeneous. Few studies compare how domestic and international tourists cluster spatially within the same destination. Those differences matter enormously for destinations where visitor segments follow distinct geographic patterns. We analyzed 1547 bilingual TripAdvisor reviews from Chanthaburi Province, Thailand (2014–2023), combining Random Forest classification (83.26% accuracy for Thai, 96.45% for English) with Incremental Spatial Autocorrelation (ISA), Global Moran’s I, and Getis-Ord Gi* hotspot analysis. International visitors clustered more intensely overall (I = 0.253 vs. 0.213), but domestic visitors spread across all six tourism areas including agrotourism, while international visitors were concentrated in heritage, coastal recreation, and nature-temple zones with agrotourism absent. Both segments clustered strongly at cultural heritage sites and at beach destinations, contradicting the common assumption that coastal areas primarily serve international visitors, while agrotourism clustered exclusively among domestic visitors despite active policy promotion. These patterns reflect differential information access rather than attraction quality. The zone-level framework is transferable to secondary heritage destinations across Southeast Asia, where platform-based monitoring offers a practical alternative to large-scale visitor surveys. Full article

Cities in climatic transition zones face coupled radiative and evaporative stresses, and their carbon emission mechanisms differ significantly from those in humid regions. Taking Xi’an, a typical megacity in the transition zone, as a case study, this research utilises a 500 m × 500 m grid to integrate multi-source data for carbon emission accounting. By applying spatial autocorrelation and the Multi-scale Geographically Weighted Regression (MGWR) model, this study examines the spatial heterogeneity of carbon emissions and the mechanisms through which urban planning influences them. The results indicate that carbon emissions in Xi’an exhibit a “core–periphery” agglomeration pattern, with commercial land use exhibiting the highest emission intensity. Carbon emissions and land surface temperature are spatially coupled, consistent with a hypothesised positive feedback loop of the “dry heat island” effect. Morphological factors exhibit spatial non-stationarity: floor area ratio is positively associated with emissions in the old city centre, whereas mutual shading among super-high-rise buildings in the High-Tech Zone coincides with a weaker effect. Building density shows a positive association only where ventilation is limited. Land use mix and blue–green spaces show non-linear negative associations with emissions, with higher marginal benefits in arid–hot environments. This study proposes carbon reduction strategies for the renewal of old urban areas, business cores, and new ecological districts, providing empirical evidence and decision-making references for low-carbon spatial planning in cities within the climatic transition zone. Full article

Rapid urbanization, climate change, and uneven regional development have increasingly intensified spatial heterogeneity in food security. As one of China’s major commercial grain-producing areas, the Main Grain-Producing Region in the Middle Reaches of the Yangtze River (MGPR-MRYR) plays a critical role in ensuring national food security. However, existing studies have paid limited attention to spatial heterogeneity and driving mechanisms at the urban agglomeration scale. Taking the Wuhan (WUA), Changsha–Zhuzhou–Xiangtan (CZXUA), and Poyang Lake (PYLUA) urban agglomerations as analytical units, this study constructs a multidimensional food security evaluation framework covering supply security, production resource security, and circulation–consumption security. Based on panel data from 2013 to 2023, the entropy weight method, kernel density estimation (KDE), Theil index decomposition, spatial autocorrelation analysis, and the optimal-parameter geographical detector (OPGD) model were employed. Food security levels in the MGPR-MRYR exhibited an overall upward trend, particularly after 2020, although significant spatial heterogeneity persisted among urban agglomerations. A spatial pattern of “higher in the west than east, and inland over lakeside” emerged, with significant positive clustering gradually expanding westward. Intra-agglomeration disparities—especially within the WUA—contributed more to regional inequality than inter-agglomeration differences. Agricultural machinery power and rural population remained the dominant driving factors, while the influence of urbanization and annual precipitation increased over time. All factor interactions showed enhancement effects, indicating that food security is shaped by the synergistic interplay of natural, socioeconomic, and agricultural production factors. This study reveals the transition of driving mechanisms from traditional factor dependence to multi-factor system synergy. These findings suggest that food security governance in rapidly urbanizing grain-producing regions should shift from uniform policies to differentiated, synergy-oriented strategies tailored to each urban agglomeration’s development stage and resource constraints. Full article