Search Results (1,705)

Przewalski’s gazelle (Procapra przewalskii) is an endangered ungulate endemic to the Qinghai–Tibet Plateau, with a small population size and exposure to multiple ecological pressures. Its gut microbiota may play a crucial role in host environmental adaptation. To investigate the functional divergence of gut microbial communities, we performed high-throughput metagenomic sequencing on 105 wild fecal samples collected from 10 geographic regions around Qinghai Lake. The results revealed significant regional differentiation in key functional modules related to metabolism, antibiotic resistance mechanisms, and virulence-associated pathways. All populations showed enrichment in core metabolic pathways such as carbohydrate and amino acid metabolism, with carbohydrate-active enzymes dominated by glycoside hydrolases (GHs) and glycosyltransferases (GTs), exhibiting overall functional conservation. Although populations shared many antibiotic- and virulence-related reference genetic markers, the marker composition associated with distinct resistance mechanisms and pathogenic processes exhibited clear population-specific patterns, suggesting differential microbial responses to local environmental pressures. Correlation network analysis further identified core taxa (e.g., Arthrobacter and Oscillospiraceae/Bacteroidales lineages) as key genera linking community structure with core metabolic, resistance-related, and virulence-associated marker functions. Overall, the gut microbiota of Przewalski’s gazelle exhibits a complex spatially structured functional differentiation, reflecting host–microbiome co-adaptation under region-specific ecological pressures. These findings provide critical methodological and theoretical support for microecological health assessment and regionally informed conservation management of this endangered species. Full article

PM_2.5 is the primary source of urban atmospheric pollution, as it not only damages the ecological environment but also poses a threat to human health. Taking the Yangtze River Economic Belt as the research object, this study analyzes the spatiotemporal variation characteristics of PM_2.5 concentrations in the region from 2005 to 2020. Furthermore, by combining the Geodetector model with Geographically and Temporally Weighted Regression (GTWR) model, the spatiotemporal heterogeneity of its influencing factors is revealed at three scales: municipal, watershed, and grid. The results show that, from 2005 to 2020, the annual average PM_2.5 concentration in the Yangtze River Economic Belt exhibited an inverted U-shaped trend with 2013 as the inflection point, showing distinct spatial clustering characteristics. Overall, the spatiotemporal variation in annual average PM_2.5 concentration demonstrated a significant downward trend during this period, with slower decline rates in the western region and faster rates in the central and eastern regions. Spatial differentiation of annual average PM_2.5 concentrations within the region was primarily influenced by three factors: PFA, PISA, and PD. NDVI and PWA exerted their effects mainly at large scales, while MAT and SDE primarily acted at small scales. Within the region, NDVI and CVO predominantly suppressed PM_2.5 concentrations, whereas MAT, PFA, PD, and SDE primarily promoted PM_2.5 pollution. The spatial distribution of effects for factors within the same category is broadly consistent across the three scales, though details vary. This study overcomes previous limitations of administrative-scale research, yielding more refined results. It provides new methodologies and insights for future research while offering more precise scientific support for regional PM_2.5 governance. Full article

University students face rising mental health pressures, making restorative environmental perception (REP) in campus forests critical for psychological recovery. While environmental factors are recognized contributors, Socio-Ecological Systems (SES) theory emphasizes that environmental and social processes are interdependent. Within this context, informal social interaction (ISI)—low-effort encounters such as greetings or small talk—represent a key social dimension that may complement environmental restoration by fostering comfort and embedded affordances. However, most studies examine these factors separately, often using coarse measures that overlook heterogeneity in restorative mechanisms. This study investigates how environmental-exposure and social–environmental context dimensions jointly shape REP in campus forests, focusing on distributional patterns beyond average effects. Using a Public Participation Geographic Information Systems (PPGIS) approach, 30 students photographed 1294 tree-dominant scenes on a forest-rich campus. Environmental features were quantified via semantic segmentation, and ISI was rated alongside REP. Quantile regression estimated effects across the REP distribution. Three distributional patterns emerged. First, blue exposure and ISI acted as reliable resources, consistently enhancing REP with distinct profiles. Second, green exposure functioned as a threshold-dependent resource, with mid-quantile attenuation but amplified contributions in highly restorative scenes. Third, anthropogenic and demographic factors created conditional barriers with distribution-specific effects. Findings demonstrate that campus forest restoration operates through differentiated socio-ecological mechanisms rather than uniform pathways, informing strategies for equitable, restoration-optimized management. More broadly, the distributional framework offers transferable insights for urban forests as socio-ecological infrastructures supporting both human well-being and ecological resilience. Full article

The conservation and transmission of cultural heritage are enduring drivers of sustainable development. As a significant form of cultural heritage, temples play a vital role in maintaining urban historical continuity and embodying local culture. This study investigated the landscape roles of temples within the ancient city of Chongqing. Drawing primarily on sources such as the “Chongqing Fuzhi Quantu” (Complete Map of Chongqing Prefecture) from the Qing Dynasty, it identifies 79 temples in historical Chongqing. Employing Historical Geographic Information Systems (HGIS), the study reveals the multi-scale distribution characteristics of these temples and their interaction mechanisms with the urban spatial structure. The findings indicate that: (1) The development of Chongqing’s temples is closely linked to the stratification process of urban historical landscapes, serving as historical markers reflecting urban culture; (2) The distribution of temples in Qing-dynasty Chongqing exhibited significant correlations with the mountain-river environment and topography, forming clusters at key urban nodes while demonstrating spatial differentiation based on their attributes; (3) the landscape roles of temples in the ancient Chongqing city by guiding the urban landscape order, shaping city landmarks, and anchoring collective memories. Through the interrelated interactions across multiscale spaces, they collectively shaped the urban imagery. The study aims to provide practical recommendations for urban heritage conservation, cultural tourism, and sustainable development. Full article

Advancing ecological civilization in the Yellow River Basin requires a nuanced understanding of the spatiotemporal evolution of ecosystem service value (ESV) and its underlying drivers, which are fundamental to regional sustainable development. This study examines the Henan section of the Yellow River Basin, applying the equivalent factor method to estimate ESV in 2020 at three grid scales: 3 km × 3 km, 5 km × 5 km, and 10 km × 10 km. Spatial patterns of land-averaged ESV at each scale are characterized using autocorrelation analysis, while the geodetector model is employed to identify and quantify the influence of driving factors on ESV spatial heterogeneity. The findings reveal that (1) ESV displays both consistent and variable spatial patterns, with higher values in the west and north, lower values in the east and south, and a distinct high-value belt along water bodies; (2) strong spatial positive correlation and aggregation of ESV are observed at all grid scales, though these effects weaken as grid cell size increases; and (3) human activities exert a significant influence on regional ESV, with the interaction of multiple factors providing robust explanatory power for ESV variation, which diminishes with increasing scale. These results offer insights for optimizing ecosystem management and promoting sustainable development in the Yellow River Basin. Full article

Background/Objectives: Houttuynia cordata Thunb., a widely consumed vegetable and traditional food in Asia, possesses significant nutritional value. However, the impact of geographical origin on its nutritional metabolite composition, crucial for food quality and functionality, remains unclear. Methods: Here, we conducted a comprehensive metabolomic analysis of H. cordata cultivated across six major Chinese regions (Yunnan, Guangxi, Guizhou, Sichuan, Chongqing, Hubei) using UPLC-MS/MS. Results and Conclusions: We identified 496 nutritional metabolites, predominantly amino acids and derivatives (53.23%). Key bioactive carbohydrates, maltotriose and maltitol, exhibited distinct geographical accumulation patterns: maltotriose was significantly enriched in Yunnan (YN), while maltitol accumulated predominantly in Sichuan (SC). Integrated transcriptomic analysis linked this variation to the differential expression of starch metabolism genes (GBE1/glgB, α-amylases, β-amylases). Bioinformatic evaluation suggested potential health-related functionalities associated with these metabolites. These findings provide critical insights into the geographical determinants of H. cordata nutritional quality and functional properties. They offer a scientific foundation for optimizing cultivation practices based on regional advantages and developing H. cordata as a region-specific, high-value vegetable and functional food ingredient targeting distinct nutraceutical applications. Full article

The rational utilization of cultivated land resources is central to ensuring both ecological and food security in the Yangtze River Economic Belt (YREB), holding strategic significance for regional sustainable development. Using panel data from 2010 to 2023 for 130 cities in the YREB, this study examines a spatial correlation network (SCN) for non-grain land use (NGLU) and its driving forces via a modified gravity model, social network analysis (SNA), and quadratic assignment procedure regression. The results show the following: (1) The risk of NGLU continues to increase, with the spatial pattern evolving from a “single-peak right deviation” pattern to a “multi-peak coexistence” pattern featuring three-level polarization and gradient transmission, primarily driven by economic potential disparities. (2) The SCN has increased in density, but its pathways are relatively singular. Node functions exhibit significant differentiation, with high-degree nodes forming “control poles”, high-intermediate nodes dominating cross-regional risk transmission, and low-proximity nodes experiencing “protective marginalization”. Node centrality distribution is highly connected with the regional development gradient. (3) The formation of the spatial network is jointly driven by multiple factors. Geographical proximity, economic potential differences, comparative benefit differences, non-agricultural employment differences, and factor mobility all positively contribute to the spillover effect. Conversely, implementing cultivated land protection policies and the regional imbalance in local industrial development path dependence significantly inhibit the non-grain trend. This study further reveals that a synergistic governance system characterized by “axial management, node classification, and edge support” should be recommended to prevent the gradient risk transmission induced by economic disparities, providing a scientific basis for achieving sustainable use of regional cultivated land resources and coordinated governance of food security. Full article

Scientific assessment of sustainable development potential (SDP) and analysis of spatial heterogeneity mechanisms of traditional villages are crucial for promoting the synergy between cultural heritage conservation and rural revitalization strategies. With an emphasis on traditional villages in the Cantonese region, this study develops a thorough evaluation methodology that combines spatial analysis and multi-criteria decision-making. It aims to (1) systematically reveal the spatial differentiation characteristics of sustainable development potential; (2) develop and validate a combined weighting method that effectively integrates both subjective and objective weights; and (3) identify key driving factors and their interaction mechanisms influencing the formation of this potential. To achieve these objectives, the research sequentially conducted the following steps: First, an evaluation indicator system encompassing socioeconomic, cultural, ecological, and infrastructural dimensions was developed. Second, the Analytic Hierarchy Process and the Entropy Weight Method were employed to calculate subjective and objective weights, respectively, followed by integration of these weights using a combined weighting model. Subsequently, the potential assessment results were incorporated into a Geographic Information System, and spatial autocorrelation analysis was applied to identify agglomeration patterns. Finally, the Geographical Detector model was utilized to quantitatively analyze the explanatory power of various influencing factors and their interactions on the spatial heterogeneity of potential. The main findings are as follows: First, the sustainable development potential of traditional Cantonese villages exhibits a significant “core–periphery” spatial structure, forming a high-potential corridor in the Zhongshan–Jiangmen–Foshan border area, while peripheral areas generally display “low–low” agglomeration characteristics. Second, the combined weighting model effectively reconciled 81.0% of case discrepancies, significantly improving assessment consistency (Kappa coefficient above 0.85). Third, we identified economic income (q = 0.661) and ecological baseline (q = 0.616) were identified as key driving factors. Interaction detection revealed that the interaction between economic income and transportation accessibility had the strongest explanatory power (q = 0.742), followed by the synergistic effect between ecological baseline and architectural heritage (q = 0.716), highlighting the characteristic of multi-factor synergistic driving. The quantitative and spatially explicit evaluation framework established in this study not only provides methodological innovation for research on the sustainable development of traditional villages but also offers a scientific basis for formulating regionally differentiated revitalization strategies. The research findings hold significant theoretical and practical importance for achieving a positive interaction between the conservation and development of traditional villages. Full article

The karst ecologically fragile region of northern Guangxi faces dual pressures from wetland shrinkage and landscape functional degradation driven by rapid urbanisation. The mechanisms governing its multi-scale landscape pattern evolution and the dominance of disturbances require urgent clarification. This study integrates land use data from 1980 to 2020, employing ArcGIS 10.8 analysis, Fragstats landscape indices, and optimal parameter geographic detectors to construct a ‘pattern-process-driver’ interpretative framework in northern Guangxi. It quantitatively reveals the evolution characteristics and driving mechanisms of wetland landscape patterns in northern Guangxi, thereby optimising wetland ecological conservation pathways. Results indicate the following: (1) Between 1980 and 2020, total wetland area decreased by 65.58 km², exhibiting a ‘structural substitution’ trend characterised by natural wetland decline and artificial wetland expansion. (2) Wetland landscape patterns exhibited intensified fragmentation and increased structural complexity. (3) Wetland evolution was primarily driven by annual mean temperature, GDP, and annual mean precipitation, reflecting a composite mechanism characterised by climate dominance, economic pressure, and policy failure. Specifically, the increase in temperature is the main reason for the decrease in natural wetlands, while economic growth dominates the expansion of artificial wetlands. This study provides scientific basis for karst wetland ecological restoration and differentiated territorial spatial planning, offering reference for ecological and environmental governance in karst watersheds. Full article

This study proposes and empirically validates a spatiotemporal life cycle assessment (LCA) framework for hydroelectric power generation applied to the Sinop Hydroelectric Power Plant in Brazil. Unlike conventional LCA, which assumes spatial and temporal homogeneity, the framework incorporates annual temporal discretisation and geographically differentiated impacts across all phases of assessment. The methodology combines the Enhanced Structural Path Analysis (ESPA) method with temporal modeling and region-specific inventory data. The results indicate that environmental impacts peak in the fourth year of the ‘Construction and Assembly’ stage, primarily due to the intensive production of concrete and steel. A spatial analysis shows that these impacts extend beyond Brazil, with notable contributions from international supply chains. By identifying temporal and geographical hotspots, the framework offers a refined understanding of impact dynamics and drivers. Uncertainty analysis further demonstrates that temporal discretisation significantly affects impact attribution, with the ‘Construction and Assembly’ stage results varying by up to ±15%, depending on scheduling assumptions. Overall, the study advances the LCA methodology while offering robust empirical evidence to guide sustainable decision-making in Brazil’s power sector and to inform global debates on low-carbon energy transitions. Full article

As a multi-ethnic border region of China, Xinjiang hosts revolutionary cultural tourism resources (RCTRs) that embody historical memory and the spirit of frontier reclamation, while also playing a strategic role in strengthening national identity and maintaining regional stability. Yet, their spatial distribution is highly uneven due to geographical, historical, and socio-economic constraints. This study analyzes 135 representative sites using a dual framework of spatial pattern analysis and driving mechanism quantification. Nearest neighbor index, imbalance index, Lorenz curve, geographic concentration index, kernel density estimation, and hotspot analysis results reveal a clustered “multi-core–peripheral attenuation” pattern with pronounced regional disparities. GIS-based overlay analysis identifies natural thresholds of moderate elevation (834–2865 m) and gentle slopes (0–8.65°), while socio-economic factors such as transportation corridors and population density amplify clustering effects. Geographic Detector results confirm road network density (q = 0.85, p < 0.01) and historical site density (q = 0.79, p < 0.01) as dominant drivers, with interactions between natural and social factors enhancing explanatory power above 0.90. These findings highlight the coupled influence of topographic suitability and socio-economic accessibility. Policy recommendations include optimizing road network layouts, adopting tiered heritage protection, and fostering cross-regional cooperation. The study provides scientific evidence for balanced development and sustainable conservation of RCTRs, contributing to the achievement of sustainable development goals (SDGs) related to cultural heritage, regional equity, and inclusive growth. Full article

Background: Ctenomys is a subterranean rodent genus known for exhibiting the highest levels of chromosome variation, both among species (2n = 10 to 70) and within species. Ctenomys minutus is particularly notable for its extensive chromosomal diversity, comprising the greatest number of described cytotypes within this genus. In contrast, Ctenomys lami presents the highest degree of karyotypic variation within a comparatively restricted geographic range. Both species inhabit the coastal plain of southern Brazil: C. minutus occurs in dunes and sandy fields extending from Laguna (Santa Catarina State) to São José do Norte (Rio Grande do Sul State), whereas C. lami is restricted to the “Coxilha das Lombas” region, which lies parallel to the distribution of C. minutus in Rio Grande do Sul State. Despite their close evolutionary relationship and the absence of external morphological differences, the mechanism underlying their karyotypic divergence remains poorly understood. Methods: In this study, we applied whole-chromosome painting using probes from Ctenomys flamarioni to investigate chromosomal evolution in C. minutus and C. lami. Results: The resulting homology maps revealed a variety of chromosomal rearrangements that differentiate cytotypes both within and between these species. Comparative analyses demonstrated substantial karyotypic divergence from C. flamarioni, although some entire chromosomes and large chromosomal segments remained conserved between C. minutus and C. lami. Our findings underscore the critical role of chromosomal rearrangements in shaping the diversification of Ctenomys. Additionally, we identified shared chromosomal rearrangements in C. minutus and C. lami, which are likely restricted to the torquatus group. Conclusions: These rearrangements provide new insights into the processes driving chromosomal evolution in genus Ctenomys. Full article

The pollen morphological characteristics of 16 pummelos and 4 other citrus germplasms from Vietnam, Thailand, and China were observed using scanning electron microscopy (SEM). Observations included equatorial view, polar view, and exine ornamentation. The results showed that the pollen of all tested materials was monads, prolate, or subprolate. The average polar axis length of the pollen ranged from 29.121 to 37.043 µm, and that of the equatorial axis ranged from 19.861 to 25.911 µm. A t-test revealed that the polar axis of pollen from Chinese pummelo germplasms was significantly longer than that of varieties from Southeast Asia, indicating certain geographical differentiation. The apertures were all colporate type, predominantly with four to five colpi (75% of grains); only four colpi were observed in the remainder (25%). The pollen exine ornamentation of pummelo germplasms was perforated, whereas that of other citrus types was reticulate. Pummelos exhibited a smaller pori diameter (0.264–0.673 µm) and wider distance between pori (0.581–1.118 µm), while other citrus species had larger lumina (1.253–1.684 µm) and narrower muri (0.443–0.664 µm). Principal component analysis (PCA) and cluster analysis were performed based on pollen traits, and two principal component factors were extracted. The pummelo germplasms were divided into two subgroups: sweet pummelo and red pummelo, which demonstrated a correlation among their pollen morphology, flesh color, and flesh flavor. The phenotypic diversity of pollen among different pummelo germplasms may provide a valuable auxiliary reference for the identification and systematic classification of pummelos. Full article

Musaceae represent one of the main crops of economic and food importance worldwide. In Ecuador, the production and export of bananas, plantains, and abaca are fundamental pillars of the national economy. However, the presence of Fusarium oxysporum f. sp. cubense tropical race 4 (Foc TR4) in neighbouring countries increases the risk to production systems. In this study, information was collected through simple random probability sampling, using a semi-structured survey that included sociodemographic information, crop characteristics, phytosanitary problems, agronomic management practices, and biosecurity measures. To differentiate the profile of producers, a Multiple Correspondence Analysis (MCA) was performed, followed by a hierarchical cluster analysis to establish their types. Additionally, a vulnerability index—Iv (low, medium, high, and critical—is proposed, considering variables such as geographic location, cultivar diversity, and producer management. Among the producers surveyed, 83.3% were men and 16.7% were women; 64% identified as Mestizo, 31% as Montubio, and 1.7% as Afro-Ecuadorian. At the time of the interview, only 38.5% used some biosecurity measures on their farms. Multivariate analyses identified six groups of producers with distinct characteristics, including ethnicity, location, crop type, phytosanitary issues, and adoption of biosecurity measures. Iv ranged from −0.60 to 3.20, with an average of 0.59. Producer groups 1 to 3 presented low to medium vulnerability, while groups 4 to 6 exhibited critical levels. These results demonstrate the diversity of production systems and profiles of Musaceae producers in Ecuador, as well as the need to strengthen biosecurity measures and phytosanitary management to reduce vulnerability to threats such as Foc TR4. Full article

Coffee is one of Peru’s most important agricultural commodities, and its productivity is highly influenced by environmental variability. This study aimed to evaluate agro-morphological traits, proximate bean composition, and the phenotypic plasticity index (PPI) of Coffea arabica (Catimor variety) cultivated in three neighboring provinces of Piura: Ayabaca, Huancabamba, and Morropón. Unlike previous studies that broadly compare distant regions, this research focuses on geographically close yet climatically contrasting environments, providing new insight into how microclimatic and edaphic variability shape both morphological and chemical traits. A total of 300 plants were sampled, and 12 morphological descriptors were recorded alongside proximate composition analyses of moisture, crude protein, fiber, ash, fat, and carbohydrates. Multivariate approaches, including cluster analysis, multiple correspondence analysis, and Pearson correlations, were applied to determine groupings and trait associations. Results indicated that 12 morphological variables consistently reflected species-specific descriptors, forming two statistical groups, with Morropón showing the greatest homogeneity. Significant differences (p ≤ 0.05) were observed in the proximate composition of most variables, except for crude fiber and carbohydrates. Morropón beans showed the highest fat and moisture values, while Huancabamba had elevated protein and ash levels. Morphological traits exhibited higher plasticity (PPI = 0.70) compared with proximate traits (PPI = 0.21). These findings reveal that even within short spatial distances, coffee plants exhibit marked phenotypic differentiation driven by local environmental factors, offering a novel, fine-scale perspective on trait variability relevant to breeding and adaptation studies under changing climatic conditions. Full article