Search Results (1,921)

In China’s national parks, Tianchuang were located on land within boundaries that are excluded from national park administration to reduce governance conflicts. According to existing research on boundary optimization of protected area, Tianchuang are routinely regarded as fixed constraints or contextual backgrounds rather than optimization targets. Based on systematic conservation planning (SCP) theory and integrated models of MaxEnt, InVEST, and Marxan, and taking Tianchuang as dynamically adjustable spatial variables, this study aims to explore the boundary optimization schemes of Tianchuang areas in Wuyishan National Park of China. The main findings are as follows: Firstly, highly suitable habitats for representative species are predominantly concentrated within the north-central region of the park, while Tianchuang patches generate significant edge effects and pose critical disturbances to ecosystem integrity. Secondly, human activity intensity demonstrates marked spatial heterogeneity, indicating distinct variations in socioeconomic impacts and management difficulties among Tianchuang patches. Thirdly, based on irreplaceability, landscape connectivity, and patch fragmentation, three optimization strategies are proposed, namely incorporation, retention, and provisional retention, balancing ecological protection and community development. This study provides a scientific basis for the differentiated management of Tianchuang areas in Wuyishan National Park and offers a practical pathway for the boundary optimization and spatial governance of protected areas in China. Full article

Porcine reproductive and respiratory syndrome (PRRS), caused by PRRSV, causes substantial economic losses in the swine industry. Because viral variability and host genetic complexity limit conventional control, identifying host genetic factors associated with PRRS resistance through genomic approaches is important for disease-resistant breeding. In this study, 699 pigs were immunized with a PRRSV vaccine, 135 were selected for PRRSV infection experiments, and 133 were retained for whole-genome resequencing after two-stage phenotypic screening based on post-immunization and post-infection profiles. Genome-wide selection-signal analysis identified 12 highly differentiated regions (F_st > 0.15), annotated to 11 candidate genes: NFXL1, NIPAL1, CHIC2, LOC100623351, LOC100513671, LOC100513484, CENPC, STAP1, UBA6, GNRHR, and LOC100512727. The original exploratory GWAS identified candidate association signals, including signals annotated to PYGM, NFXL1, KIAA1324L, and FLNC; after PC1/PC2 adjustment, NFXL1 retained exploratory support, and additional exploratory signals were observed. Public PRRSV-related transcriptomic datasets provided additional expression-level evidence, with NIPAL1 and PYGM showing increased expression in PRRSV-infected porcine alveolar macrophages. Functional enrichment and variant-level analyses supported the biological relevance of the prioritized candidate gene set, particularly the chromosome 8 NFXL1 region, where the A-C-G haplotype was more frequent in resistant pigs. These findings provide useful genetic clues for further validation and PRRS resistance breeding. Full article

Traditional species distribution models can identify climatically suitable areas but offer limited guidance for spatially explicit agricultural planning. In this study, we constructed a three-dimensional coupled framework of “suitability prediction–habitat quality filtering–ecological security screening” by integrating BIOMOD2 ensemble modeling, InVEST habitat quality assessment, and ecological security evaluation to identify candidate cultivation zones for Piper nigrum L. in China under climate change. Based on occurrence records and environmental variables, we simulated potential suitable habitats under current and future climate scenarios, identified key climatic drivers, and delineated candidate zones by overlaying habitat quality and ecological security levels. The results show that the current total suitable area for P. nigrum is 87.76 × 10⁴ km², with low-, moderate-, and high-suitability areas accounting for 37.28 × 10⁴ km², 25.12 × 10⁴ km², and 25.36 × 10⁴ km², respectively. Temperature seasonality and winter cold stress were identified as the dominant factors shaping the suitability pattern. Under future climate scenarios, the total suitable area shows an increasing trend, with highly suitable areas expanding toward the coastal regions of South China and the low-latitude hilly zones. After overlaying with habitat quality and ecological security, climatically suitable but ecologically fragile or intensively disturbed areas were effectively excluded, and the current candidate cultivation zones were identified as mainly concentrated in the southern Yunnan–southern Guangxi–Guangdong–Hainan coastal region. This framework enables a transition from identifying climatic suitability to collaborative climate–habitat–ecology screening, providing a scientific basis for sustainable cultivation and germplasm management of P. nigrum, and is transferable to priority cultivation area identification for other tropical cash crops. Full article

The varying sensibilities of diverse proxies to Indian Summer Monsoon (ISM) variables lead to inconsistencies across individual studies. To attain a comprehensive understanding of the ISM driving mechanisms, it is essential to compile multi-proxy paleorecords from diverse monsoon-influenced areas. However, terrestrial ISM records spanning the last 200 ka remain sparse. Here, we performed a magnetic analysis of the PT2 core lacustrine sediments from the Heqing Basin, covering the past 184 ka, to reconstruct ISM variations from millennial to orbital timescales. According to the rock magnetic results, samples displaying strong magnetization are dominated by substantial amounts of magnetite and maghemite, accompanied by a broad grain-size distribution. Conversely, samples with weak magnetization show only limited quantities of fine-grained magnetite. The decrease in magnetic mineral concentration is attributed to the reduction in both coarse and fine-grained particles. Magnetic mineral dissolution intensity (MMDI) which combines magnetic susceptibility and frequency-dependent magnetic susceptibility, is highly sensitive to ISM changes. Consequently, we derived an ISM index from the MMDI and geochemical indicators of the PT2 core lacustrine sediments. This index exhibits pronounced “glacial–interglacial variations”, aligning with other regional ISM indicators from southwestern China and a variety of ISM-related proxies from a broader range of ISM-influenced areas. This suggests that ISM intensity is more sensitive to glacial boundary conditions in high-latitude ice sheets. Full article

Climate variability strongly affects fungal ecology and mycotoxin contamination patterns in maize. This study evaluated the influence of weather conditions during the 2024 growing season on the occurrence and co-occurrence of regulated and emerging mycotoxins in maize from two Southeast European regions: the Autonomous Province of Vojvodina (APV), Serbia, and the Republic of Srpska (RoS), Bosnia and Herzegovina (BIH). A total of 266 maize samples were analysed using an LC-MS/MS method targeting 21 fungal metabolites. The exceptionally hot and dry summer conditions, particularly the severe drought recorded in APV during August, were associated with regional differences in mycotoxin profiles. APV maize showed higher contamination with drought-related mycotoxins, especially aflatoxins, while fumonisins were highly prevalent in both regions. Overall, fumonisins were the dominant regulated mycotoxins (88.0%), followed by aflatoxins (41.4%) and T-2/HT-2 toxins (31.6%), whereas deoxynivalenol and zearalenone occurred less frequently. Emerging metabolites showed high prevalence, particularly alternariol monomethyl ether (86.5%), moniliformin (74.4%), and ergot alkaloids (53.4%). Co-occurrence analysis revealed 189 different combinations, with up to ten mycotoxins detected simultaneously. These findings demonstrate region-specific weather-driven shifts in maize contamination and emphasize the need for multi-mycotoxin monitoring strategies including both regulated and emerging contaminants. Full article

The fascia lata (FL), the deep fascia of the thigh, plays a crucial role in lower-limb biomechanics, force transmission, and surgical applications. This is because of its histological architecture and, more importantly, its integration with the major lower limb muscles. Its regionally variable thickness and multilayered organization enable the formation of extensive attachments to the iliac crest and deep crural fascia, functionally integrating it with the tensor fasciae latae, gluteus maximus, and iliotibial tract. Once a passive envelope surrounding the thigh musculature is considered, it is now understood to be a dynamic collagen-rich structure with both mechanical and biological roles. Understanding the vascularization and innervation patterns of the fascia lata is crucial for both surgical procedures and regenerative medicine, as these features influence the healing potential and graft viability. Close anatomical and functional integration between the FL and tensor fasciae latae (TFL) enhances the biomechanical strength and vascular potential of FL-based grafts, effectively resulting in the structure being a promising resource for advanced reconstructive surgery. This relationship provides not only mechanical reinforcement, but also improved biological viability, making vascularized FL particularly valuable in situations that require durable tissue support. Emerging evidence highlights its potential in managing avascular bone necrosis, where TFL contributes to revascularization and enhances the healing capacity. Although FL has been applied in select lower-extremity reconstructions, its broader reconstructive possibilities remain underexplored. The combination of structural resilience, biological activity, and adaptability underscores FL and TFL as underutilized yet highly promising grafts for modern orthopedic reconstruction. Full article

Geographical traceability of rice is critical for authenticity identification and quality control, yet it poses considerable challenges for tracing origins in adjacent small-scale producing areas. To explore the causes of metabolic differences and geographical traceability potential of rice from adjacent small-scale producing areas, non-targeted metabolomics combined with multivariate statistical analysis was employed to systematically investigate the metabolic profiles of rice from Panjin (PJ), Donggang (DG) and Yingkou (YK) in Liaoning Province. The characteristic metabolic markers for each producing area were screened, and the effects of climatic and soil factors as well as their interactive effects on grain metabolite composition were elucidated. The results showed that the partial least squares-discriminant analysis (PLS-DA) model established based on differential metabolites achieved acceptable discrimination among rice samples from the three regions. With variable importance in projection (VIP) > 2.0 as the screening threshold, the core characteristic markers of each producing area were determined: PJ is LPC 17:2, LPA 18:3, D-(+)-Arabitol, DG is 2′-Deoxyadenosine, LDGTS 18:2, and YK is LPE 17:2; the markers are mainly primary metabolites, including lipids, sugar alcohols and nucleotides. Sunshine duration, air humidity, wind conditions and soil layer temperature were highly correlated climatic drivers responsible for metabolic differentiation, and characteristic metabolic markers from different producing areas exhibited distinct meteorological response patterns. Soil physicochemical properties and mineral elements significantly affected the differential accumulation of metabolites, among which soil Sr element and organic matter exhibited crucial indicative significance for metabolic variation of rice in adjacent regions. Multi-factor interaction analysis verified significant synergistic coupling effects between regional climate and soil environment. Meteorological factors, including sunshine, wind and soil temperature, together with soil chemical factors involving organic matter, pH, Sr, K and Ca, were identified as core driving factors for the spatial differentiation of region-specific rice metabolites. The present study provides theoretical support at the metabolic level for the construction of a small-scale rice geographical traceability system and the mechanism research on the regional quality formation of rice. Full article

Heavy metal contamination in urban street dust is often highly heterogeneous, limiting the effectiveness of conventional geostatistical mapping approaches. In Mexico City, previous studies have reported very low spatial autocorrelation for key elements, making interpolation-based methods unsuitable for representing contamination patterns. This study proposes a multiscale cartographic framework to analyze and visualize heavy metal contamination in street dust from 482 sampling sites using the contamination factor (CF) and pollution load index (PLI) at three levels of spatial analysis: (i) city-scale patterns identified through hierarchical clustering of districts based on median CF values, (ii) district-scale variability assessed through statistical comparisons of PLI distributions, and (iii) site-scale identification of contamination hotspots using observed PLI values. Results revealed five contamination clusters and significant differences in pollution load among districts (Kruskal–Wallis, p < 0.05); PLI values in Xochimilco and Tláhuac are significantly lower than in Cuauhtémoc, Gustavo A. Madero, and Magdalena Contreras. Higher contamination levels were concentrated in northern and central districts, whereas lower levels predominated in the south. Site-scale analysis identified localized hotspots associated with transportation infrastructure, industrial areas, and commercial corridors, reflecting the influence of local emission sources. The results demonstrate that contamination patterns operate simultaneously at city, district, and site scales and cannot be adequately represented through interpolation alone. The proposed framework provides a practical approach for visualizing heterogeneous contamination datasets, supporting environmental decision-making, and may apply to other metropolitan regions characterized by weak spatial autocorrelation and localized pollution processes. Full article

Background/Objective: African swine fever (ASF), caused by African swine fever virus (ASFV), is a highly contagious viral disease affecting domestic pigs and wild boars, causing severe economic losses. Although commercial ASF vaccines have recently been approved in Vietnam, controlling ASF transmission remains challenging. Since injection-based vaccination is impractical for wild boars, oral vaccination is considered essential. This study aimed to evaluate the safety, immunogenicity, protective efficacy, and dose-related outcomes of ASFV-G-ΔI177L/ΔLVR, a live attenuated ASFV vaccine candidate with deletion in the I177L gene and left variable region (LVR), administered orally to convention pigs. Methods: The ASFV-G-ΔI177L/ΔLVR vaccine candidate was orally administered to conventional pigs at three dose levels (10^2.25, 10^5.0, and 10^6.0 TCID₅₀/dose). At 28 days post-vaccination, pigs were challenged intramuscularly with a virulent ASFV field strain at 10^2.0 HAD₅₀/mL and monitored clinically. Protection was assessed by ASFV-specific antibody responses (p32) and survival following challenge. Results: Oral immunization was well tolerated, with no vaccine-associated clinical signs observed before challenge. Following challenge, vaccinated pigs showed different protective outcomes among the tested dose groups, with survival rates of 1/4 (10^2.25 TCID₅₀/dose), 4/4 (10^5.0 TCID₅₀/dose), and 3/4 (10^6.0 TCID₅₀/dose), respectively. Pigs that succumbed to infection showed neither detectable viremia nor ASFV-specific antibodies before challenge, suggesting incomplete vaccine uptake may have resulted in insufficient immune induction rather than an adverse effect associated with vaccination. In contrast, pigs that seroconverted prior to challenge were fully protected and exhibited lower viral loads than the control animals. Conclusions: ASFV-G-ΔI177L/ΔLVR was well tolerated as an oral live attenuated vaccine candidate and induced protective immunity against virulent ASFV challenge under the present experimental conditions. Notably, complete protection was observed in the 10^5.0 TCID₅₀/dose group, supporting the potential of this vaccine candidate for oral immunization strategies against ASF. However, the present data do not allow a definitive conclusion regarding the dose–response relationship, and further studies with larger group sizes and field-relevant models are needed to refine dose selection and practical applicability, particularly for wild boar vaccination. Full article

Urban heat intensification is an increasing concern in rapidly urbanizing arid cities, where extreme climatic conditions intersect with expansive urban growth. This study examines the spatiotemporal dynamics of urban thermal patterns in the Doha metropolitan region, Qatar, by integrating multi-season remote sensing with urban morphological analysis. Seasonal composites of land surface temperature (LST), Urban Heat Island (UHI) intensity, and Normalized Difference Vegetation Index (NDVI) were derived from Landsat 8–9 Collection 2 Level-2 imagery across eight seasons from Spring 2024 to Winter 2026. Urban form was characterized using Local Climate Zones (LCZs) and quantified through class-level landscape metrics, i.e., Largest Patch Index (LPI), Number of Patches (NP), and CLUMPY. The results showed a pronounced seasonal variability, with LST ranging from approximately 12.5 °C in winter to 61.3 °C in summer, and intra-urban UHI exceeding 10 °C during peak conditions. The bare soil/sand, with relative coverage of 52.84% and LPI of 25.45%, and the large low-rise, with relative coverage of 38.60% and LPI of 14.70%, typologies dominate the landscape, forming highly aggregated spatial structures, while vegetation cover remained minimal. Weak negative relationships between NDVI and thermal indicators revealed that vegetation alone had limited explanatory power. In contrast, LCZ-based analysis revealed a better thermal differentiation across urban typologies, with compact forms associated with higher thermal intensities. These findings highlight the dominant role of urban morphology and spatial configuration in shaping thermal patterns and support the need for morphology-sensitive planning strategies in arid urban environments. Full article

Background/Objectives: Internet gaming has become a widespread global activity, raising concerns about the prevalence of Internet Gaming Disorder (IGD). However, existing meta-analyses report highly variable prevalence estimates. This umbrella review aims to clarify the prevalence and variability of IGD by synthesizing evidence from meta-analyses to provide a comprehensive overview of IGD prevalence across populations, age groups, and regions. Methods: Following PRISMA guidelines, systematic searches were carried out across five published literature databases and two supplementary search sources. Title and abstract screening, followed by full-text eligibility assessment, were conducted independently by three authors. The same three authors then performed data extraction and quality assessment for the nine included meta-analyses. Results: After screening, nine eligible meta-analyses were included. The overall median prevalence of IGD was 6.20%, with an interquartile range of 4.25% to 8.30%. Subgroup analyses indicated a higher prevalence among males compared to females. Evidence for age differences between adolescents and adults was limited and should be interpreted cautiously because age groups were inconsistently defined across meta-analyses. Regional comparisons suggested higher prevalence estimates in Asia than in Europe, and gamer profile comparisons suggested higher prevalence estimates in gamers than in the general population, although evidence for these differences was limited and not consistent across meta-analyses. Conclusions: Overall, the findings indicate that IGD affects a sizeable proportion of the population, but prevalence estimates vary depending on demographic and regional characteristics. Greater consistency in diagnostic criteria, assessment tools, and reporting standards is needed to improve the comparability and interpretability of IGD prevalence research. Full article

This study evaluates the spatial variability of hydric stress in the State of Sinaloa, northwestern Mexico, through the integrated analysis of hydroclimatic variables, multispectral remote sensing indicators, and environmental factors. Historical hydroclimatic conditions were analyzed using meteorological records from 1961 to 2020, whereas Landsat 8 imagery acquired on 7 July 2025, was used to evaluate the spatial expression of hydric stress. Reference evapotranspiration (ETo) was estimated using the FAO-56 Penman–Monteith methodology, and hydrological deficit conditions were determined from the relationship between precipitation (P) and ETo. Spectral indicators including land surface temperature ($\overline{T}$_a), the Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), Modified Normalized Difference Water Index (MNDWI), and the NDWI/MNDWI relationship were used to evaluate vegetation response, surface moisture conditions, and thermal anomalies associated with hydric stress. The results revealed persistent conditions where ETo systematically exceeded P, with hydrological deficit values ranging from approximately −1600 mm·year⁻¹ to localized positive values near 50 mm·year⁻¹. The most severe deficits were concentrated within the northwestern and north-central agricultural valleys of Sinaloa. Statistical validation revealed significant negative relationships between hydrological deficit and all evaluated spectral indicators. The strongest association was observed for MNDWI (R² = 0.387), followed by NDWI/MNDWI (R² = 0.277), NDWI (R² = 0.220), and NDVI (R² = 0.134), confirming the sensitivity of vegetation and moisture-related indicators to long-term hydrological stress conditions. Spatial analyses revealed a strong correspondence among low NDVI, negative NDWI and MNDWI responses, elevated $\overline{T}$_a, and regions characterized by high atmospheric evaporative demand. Additional spatial validation integrating land-use and vegetation-cover changes (1993–2011), regional geology, topography, and the distribution of highly productive agricultural valleys demonstrated that the most severe hydrological deficits coincided with areas affected by vegetation-cover loss, agricultural expansion, and intensive land use. Although these datasets correspond to different observation periods, they collectively reflect the cumulative environmental effects associated with persistent hydrological stress across the region. The combined effects of hydrological imbalance, forest-cover reduction, and agricultural intensification have progressively reduced ecosystem resilience and increased environmental vulnerability throughout one of the most productive agricultural regions of northwestern Mexico. These findings provide a scientific basis for water-resource management, territorial planning, ecosystem restoration, and climate-adaptation strategies under increasing water-scarcity conditions. Full article

Drought poses a major threat to ecosystem stability in arid regions. In Xinjiang, China, vegetation dynamics are highly sensitive to hydroclimatic variability, yet the evolution of drought and its ecological impacts remain insufficiently quantified. Using meteorological observations from 86 stations (1962–2021), drought dynamics were characterized using the Standardized Precipitation Evapotranspiration Index (SPEI) combined with run theory, while MODIS products (2001–2021) were used to quantify vegetation phenology and productivity. Results indicate that despite a regional warming–wetting trend, more than 97% of Xinjiang exhibits a significant increase in drought frequency and intensity after 1997, with pronounced spatial heterogeneity concentrated in southern Xinjiang. Vegetation phenology shows a significant shift, with spring onset advancing at a rate of −1.9 days decade⁻¹ and growing season length increasing by +3.8 days decade⁻¹. Vegetation productivity derived from MODIS shows strong spatial variability, with GPP and NPP exhibiting consistent increasing trends, particularly in northern Xinjiang. Multi-scale analysis reveals strong scale dependence in drought–vegetation interactions, where short-term drought (SPEI-3 and SPEI-6) exerts the strongest influence on vegetation dynamics, while long-term drought (SPEI-12) primarily controls ecosystem stability and post-drought recovery. Correlation and extreme-event analyses further indicate that seasonal drought and phenological shifts jointly regulate ecosystem productivity by altering water availability and carbon uptake periods. These results highlight a warming–wetting but drought-intensifying regime in Xinjiang and emphasize the dominant role of seasonal drought in regulating vegetation functioning under climate change. Full article

The Yellow River Basin is a vital ecological security barrier for China, as well as a region rich in cultural and tourism resources. Tourism has emerged as a core industry underpinning both ecological conservation and sustainable, high-quality regional development within the basin. As the tourism industry transitions toward sustainable and high-quality development, tourism efficiency serves not only as a core indicator for measuring the quality of tourism development but also as a critical basis for assessing regional tourism sustainability. Taking 68 Outstanding Tourism Cities in the Yellow River Basin from 2009 to 2023 as research samples, this study employs the Super-Slack-Based Measure (Super-SBM) model to measure tourism efficiency. It depicts the spatiotemporal evolution through trend surface analysis, spatial autocorrelation analysis, hotspot analysis, and standard deviation ellipses and utilizes the Geographically and Temporally Weighted Regression (GTWR) model to identify the determinants of spatiotemporal heterogeneity. Tourism efficiency in the basin’s Outstanding Tourism Cities is generally low but has a variably increasing trend with a pronounced spatial gradient of upstream > midstream > downstream. The efficiency of tourism is highly interdependent spatially and highly clustered, as the regional high and low values are mostly situated up- and downstream, respectively. In general, the center of tourism efficiency has changed to the southwest instead of the northeast. The infrastructure, industrial structure and human capital characterize the efficiency of tourism, but the openness to the external world is the most significant factor, and the impact of these factors also varies sharply in terms of their strength. This study systematically reveals the spatiotemporal evolution patterns and heterogeneous driving mechanisms of tourism efficiency in Outstanding Tourism Cities within the Yellow River Basin. It not only expands the research perspectives and empirical analytical frameworks for sustainable tourism development at the basin scale but also provides a precise decision-making basis for the coordinated advancement of sustainable and high-quality tourism development in the region. Full article

This paper examines the long-run relationship between subjective well-being and digital transformation in the six Gulf Cooperation Council (GCC) countries—Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, and the United Arab Emirates—over the period 2011–2025 using a balanced country-year panel dataset. Subjective well-being is measured by the national average Cantril Ladder score from the Gallup World Poll as reported in the World Happiness Report. Explanatory variables include a binary AI Readiness Period Indicator (AI) distinguishing the pre-AI-readiness phase (2011–2018, AI = 0) from the post-AI-readiness phase (2019–2025, AI = 1), anchored by the Oxford Insights Government AI Readiness Index, Internet penetration from the International Telecommunication Union (ITU), and real GDP per capita. After accounting for cross-sectional dependence and non-stationarity, the analysis employs a panel autoregressive distributed lag (ARDL) framework estimated via the Pooled Mean Group (PMG) approach. The results indicate the existence of a stable long-run cointegrating relationship among the variables. The baseline PMG estimates suggest positive long-run associations between GDP per capita and the AI Readiness Period Indicator with subjective well-being, and a negative association between Internet penetration and well-being in a high-connectivity regional context. Short-run effects are generally weak, while the error-correction term confirms adjustment toward the long-run equilibrium. Robustness checks based on alternative estimators confirm the positive long-run effect of income, while the estimated effects of the AI Readiness Period Indicator and Internet penetration show sensitivity in sign and significance across specifications and should therefore be interpreted as indicative rather than definitive. Overall, the findings suggest that digital transformation is not a homogeneous driver of subjective well-being. Instead, the AI Readiness Period Indicator and Internet penetration operate through distinct mechanisms, with potentially different welfare implications in highly connected rentier-state economies. Full article