Search Results (278)

Tropical sandy beaches are dynamic ecosystems where microbial communities play crucial roles in biogeochemical processes and tracking human impact. Despite their importance, these habitats remain underexplored. Here, using amplicon-based sequencing of bacterial (V3-V4 16S rRNA) and fungal (ITS2) markers, we first describe microbial communities inhabiting supralittoral–intertidal sediments of two contrasting sandy beaches in the Tadjoura Gulf (Djibouti Republic): Sagallou-Kalaf (SK, rural, siliceous sand) and Siesta Plage (SP, urban, calcareous sand). Sand samples were collected at low tide along 10 m transects perpendicular to the shoreline. Bacterial communities differed significantly between sites and along the sea-to-land gradient, suggesting an influence from both anthropogenic activity and sediment granulometry. SK was dominated by Escherichia-Shigella, Staphylococcus, and Bifidobacterium, associated with human and agricultural sources. SP showed higher richness, with enriched marine-associated genera such as Hoeflea, Xanthomarina, and Marinobacter, also linked to hydrocarbon degradation. Fungal diversity was less variable, but showed significant shifts along transects. SK communities were dominated by Kluyveromyces and Candida, while SP hosted a broader fungal assemblage, including Pichia, Rhodotorula, and Aureobasidium. The higher richness at SP suggests that calcium-rich sands, possibly due to their buffering capacity and greater moisture retention, offer more favorable conditions for microbial colonization. Full article

As global climate change accelerates, the urban heat island (UHI) phenomenon has become increasingly pronounced, posing significant challenges to urban energy balance, atmospheric processes, and public health. This study used the Weather Research and Forecasting (WRF) model to dynamically downscale two CMIP6 scenarios—moderate forcing (SSP245) and high forcing (SSP585)—focusing on Zhengzhou, a rapidly urbanizing city in central China. High-resolution simulations captured fine-scale intra-urban temperature patterns and analyze the spatial and seasonal variations in UHI intensity in 2030 and 2060. The results demonstrated significant seasonal variations in UHI effects in Zhengzhou for both 2030 and 2060 under SSP245 and SSP585 scenarios, with the most pronounced warming in summer. Notably, under the SSP245 scenario, elevated autumn temperatures in suburban areas reduced the urban–rural temperature gradient, while intensified rural cooling during winter enhanced the UHI effect. These findings underscore the importance of integrating high-resolution climate modeling into urban planning and developing targeted adaptation strategies based on future UHI patterns to address climate challenges. Full article

Pesticide exposure gradients between occupational, para-occupational, and general populations remain poorly characterized in North African agricultural contexts. This study evaluates urinary pesticide levels among farmers, indirectly exposed individuals, and a control group in Morocco’s Fez-Meknes region. A cross-sectional survey measured pesticide concentrations using LC-MS/MS in urine samples collected from 154 adults residing in both rural and urban areas. A questionnaire was used to gather information from participants regarding factors that may elevate the risk of pesticide exposure. The results revealed that farmers exhibited the highest concentrations of pesticides in their urine, including compounds classified as Ia/Ib by the World Health Organization. Indirectly exposed individuals showed moderate levels of contamination, with notable detections such as dichlofluanid (22.13 µg/L), while the control group had residual traces of neonicotinoids, notably imidacloprid (2.05 µg/L). Multivariate analyses revealed several sociodemographic factors significantly associated with increased pesticide exposure. The main risk factors identified included low education, residence in an agricultural area, and the consumption of untreated water (wells/rivers). Conversely, wearing personal protective equipment was associated with reduced urinary concentrations. This study highlights intense occupational exposure among farmers, secondary environmental contamination among residents living near treated areas, and the widespread dispersion of pesticide residues into urban areas. Full article

Urban vegetation shows significant spatial differences due to the combined effects of natural and human factors, yet fine-scale evolutionary patterns and their cross-scale feedback mechanisms remain limited. This study focuses on the Yangtze River Delta (YRD), the top economic area in China. By integrating data from multiple Landsat sensors, we built a high—resolution framework to track vegetation dynamics from 1990 to 2020. It generates annual 30-m Enhanced Vegetation Index (EVI) data and uses a new Vegetation Green—Brown Balance Index (VBI) to measure changes between greening and browning. We combined Mann-Kendall trend analysis with machine—learning based attribution analysis to look into vegetation changes across different city types and urban—rural gradients. Over 30 years, the YRD’s annual EVI increased by 0.015/10 a, with greening areas 3.07 times larger than browning. Spatially, urban centers show strong greening, while peri—urban areas experience remarkable browning. Vegetation changes showed a city-size effect: larger cities had higher browning proportions but stronger urban cores’ greening trends. Cluster analysis finds four main evolution types, showing imbalances in grey—green infrastructure allocation. Vegetation baseline in 1990 is the main factor driving the long-term trend of vegetation greenness, while socioeconomic and climate drivers have different impacts depending on city size and position on the urban—rural continuum. In areas with low urbanization levels, climate factors matter more than human factors. These multi-scale patterns challenge traditional urban greening ideas, highlighting the need for vegetation governance that adapts to specific spatial conditions and city—unique evolution paths. Full article

This study investigates rural settlement patterns and land suitability in Rwanda’s Western Highlands, a mountainous region highly vulnerable to geohazards like landslides and flooding. Its primary aim is to inform sustainable, climate-resilient development planning in this fragile landscape. We employed high-resolution satellite imagery, a Digital Elevation Model (DEM), and comprehensive geospatial datasets to analyze settlement distribution, using Thiessen polygons for influence zones and Kernel Density Estimation (KDE) for spatial clustering. The Analytic Hierarchy Process (AHP) was integrated with the GeoDetector model to objectively weight criteria and analyze settlement pattern drivers, using population density as a proxy for human pressure. The analysis revealed significant spatial heterogeneity in settlement distribution, with both clustered and dispersed forms exhibiting distinct exposure levels to environmental hazards. Natural factors, particularly slope gradient and proximity to rivers, emerged as dominant determinants. Furthermore, significant synergistic interactions were observed between environmental attributes and infrastructure accessibility (roads and urban centers), collectively shaping settlement resilience. This integrative geospatial approach enhances understanding of complex rural settlement dynamics in ecologically sensitive mountainous regions. The empirically grounded insights offer a robust decision-support framework for climate adaptation and disaster risk reduction, contributing to more resilient rural planning strategies in Rwanda and similar Central African highland regions. Full article

Arid and semi-arid regions serve as crucial ecological barriers in China, making the spatiotemporal evolution of their ecological environmental quality (EEQ) scientifically significant. This study developed a Modified Remote Sensing Ecological Index (MRSEI) by innovatively integrating the Comprehensive Salinity Indicator (CSI) into the Remote Sensing Ecological Index (RSEI) and applied it to systematically evaluate the spatiotemporal evolution of EEQ (2014–2023) in Yinchuan City, a typical arid region of northwest China along the upper Yellow River. The study revealed the spatiotemporal evolution patterns through the Theil–Sen (T-S) estimator and Mann–Kendall (M-K) test, and adopted the Light Gradient Boosting Machine (LightGBM) combined with the Shapley Additive Explanation (SHAP) to quantify the contributions of ten natural and anthropogenic driving factors. The results suggest that (1) the MRSEI outperformed the RSEI, showing 0.41% higher entropy and 5.63% greater contrast, better characterizing the arid region’s heterogeneity. (2) The EEQ showed marked spatial heterogeneity. High-quality areas are concentrated in the Helan Mountains and the integrated urban/rural development demonstration zone, while the core functional zone of the provincial capital, the Helan Mountains ecological corridor, and the eastern eco-economic pilot zone showed lower EEQ. (3) A total of 87.92% of the area (7609.23 km²) remained stable with no significant changes. Notably, degraded areas (934.52 km², 10.80%) exceeded improved zones (111.04 km², 1.28%), demonstrating an overall ecological deterioration trend. (4) This study applied LightGBM with SHAP to analyze the driving factors of EEQ. The results demonstrated that Land Use/Land Cover (LULC) was the predominant driver, contributing 41.52%, followed by the Digital Elevation Model (DEM, 18.26%) and Net Primary Productivity (NPP, 12.63%). This study offers a novel framework for arid ecological monitoring, supporting evidence-based conservation and sustainable development in the Yellow River Basin. Full article

As a pivotal node in urban spatial restructuring, the evolution of three-dimensional (3D) compactness in high-speed rail station areas is crucial for sustainable development. However, the existing research predominantly focuses on two-dimensional forms and lacks dynamic analysis and models that are adaptable to complex terrains. This study develops an enhanced 3D gravitational model that integrates satellite imagery and Gaode building data to quantify the spatiotemporal heterogeneity and carry out multidimensional classification of the compactness across 16 stations in the Chengdu-Chongqing urban agglomeration (2015–2025), with driving factors being identified through correlation and regression analyses. The key findings reveal the following: (1) The mean compactness increased by 22.41%, exhibiting nonlinear heterogeneity characterized by high initial values with low growth rates versus low initial values with high growth rates. Spatially, the southern line evolved from a dual-core pattern at the terminals to multigradient development, while the northern line maintained stable growth despite gradient discontinuities. These spatial differentiations resulted from synergistic effects of urban sizes (station hierarchy), terrain features, administrative divisions, and the line affiliation. (2) The built-up land area (under equal study conditions) and vertical development emerged as key drivers, with the building height diversity demonstrating dual spatial effects (enhancing both compactness and aesthetic richness). Complex terrain characteristics were found to promote clustered urban land use and compact efficiency during initial development phases. This study proposes a planning framework that integrates morphology-adaptive zoning control, ecology-responsive compactness principles, and urban–rural integrated settlement patterns, providing quantitative tools for mountainous station development. These findings offer theoretical and practical support for achieving urban sustainability goals and meeting the 3D compactness and transit-oriented development requirements in territorial spatial planning. Full article

As a vital bridge linking human well-being with ecological processes, cultural ecosystem services (CESs) play a pivotal role in understanding the equilibrium of social–ecological systems. However, the spatial supply–demand relationships of CESs remain underexplored in rapidly urbanizing regions. This study establishes an integrated framework by synthesizing multi-source geospatial data, socioeconomic indicators, and the Maximum Entropy (MaxEnt) model to investigate the spatial dynamics of CESs in Taiyuan City. Key findings include the following: (1) A pronounced spatial heterogeneity in CES supply distribution, exhibiting a core-to-periphery diminishing gradient, with inverse correlations observed among different CES categories. (2) Accessibility, topographic features, and fractional vegetation cover emerged as primary drivers of spatial supply differentiation, while climatic factors and elevation exerted non-negligible influences on this Loess Plateau urban system. (3) Four spatial mismatch patterns were identified through the supply–demand analysis: high supply–high demand (38.1%), low supply–low demand (37.2%), low supply–high demand (13.6%), and high supply–low demand (10.9%). The coupling coordination degree of CESs in Taiyuan City indicated moderate coordination, with severe imbalances observed in urban–rural transitional zones. This study reveals nonlinear interactions between natural landscapes and anthropogenic factors in shaping CES spatial distributions, particularly the trade-offs between esthetic value and transportation constraints. By integrating big data and spatial modeling, this research advances CES quantification methodologies and provides actionable insights for optimizing green infrastructure, prioritizing ecological restoration, and balancing urban–rural CES provision. These outcomes address methodological gaps in coupled social–ecological system research while informing practical spatial governance strategies. Full article

Efficient urban land use is essential for sustainable urban growth. However, the efficiency of buildings in carrying urban functions remains poorly understood. A comprehensive approach for measuring urban building use efficiency (UBUE) and marginal effect was developed by quantifying the relationship between building volume and urban function. The intensity of urban function was calculated from nighttime light intensity, population density, and facility density. The UBUE at national and urban scales was assessed for 35 Chinese cities. Three significant findings emerge. First, UBUE shows significant spatial variation at national and urban scales, with a maximum disparity of 4.3 times among the 35 cities and a gradual decline along the urban–rural gradient within urban areas. Second, in cities in the western and northeastern areas, a smaller amount of urban function was generated per unit of newly constructed building volume, indicating that newly increased buildings are less efficient. Third, the scaling exponents of most cities were less than one, suggesting a marginal diminishing effect in the relationship between urban function and building volume. The marginal diminishing effect was more pronounced in economically developed cities. The comprehensive investigation of the relationship between urban function and building volume provides a scientific basis for land development allocation policies and urban growth regulation. Full article

This study investigates the relationship between Green View Index (GVI) and street thermal environment in Hangzhou’s main urban area during summer, quantifying urban greenery’s impact on diurnal/nocturnal thermal conditions to inform urban heat island mitigation strategies. Multi-source data (3D morphological metrics, LCZ classifications, mobile measurements) were integrated with deep learning-derived street-level GVI through image analysis. A random forest-multiple regression hybrid model evaluated spatiotemporal variations and GVI impacts across time, street orientation, and urban-rural gradients. Key findings include: (1) Urban street Ta prediction model: Daytime model: R² = 0.54, RMSE = 0.33 °C; Nighttime model: R² = 0.71, RMSE = 0.42 °C. (2) GVI shows significant inverse association with temperature, A 0.1 unit increase in GVI reduced temperatures by 0.124°C during the day and 0.020 °C at night. (3) Orientation effects: North–south streets exhibit strongest cooling (1.85 °C daytime reduction), followed by east–west; northeast–southwest layouts show negligible impact; (4) Canyon geometry: Low-aspect canyons (H/W < 1) enhance cooling efficiency, while high-aspect canyons (H/W > 2) retain nocturnal heat despite daytime cooling; (5) Urban-rural gradient: Cooling peaks in urban-fringe zones (10–15 km daytime, 15–20 km nighttime), contrasting with persistent nocturnal warmth in urban cores (0–5 km); (6) LCZ variability: Daytime cooling intensity peaks in LCZ3, nighttime in LCZ6. These findings offer scientific evidence and empirical support for urban thermal environment optimization strategies in urban planning and landscape design. We recommend dynamic coupling of street orientation, three-dimensional morphological characteristics, and vegetation configuration parameters to formulate differentiated thermal environment design guidelines, enabling precise alignment between mitigation measures and spatial context-specific features. Full article

Urban green spaces face increasing pressure to reconcile ecological conservation with rising public demand as urbanization accelerates. Yet the spatial coupling of human needs and natural provisioning in the urban–rural fringe remains insufficiently understood. Focusing on the country park cluster in Beijing’s Huitian region, this study develops an integrated assessment framework—combining ecological importance, ecological connectivity potential, construction suitability, and recreational demand—to evaluate nature suitability and pinpoint spatial mismatches in human–nature interactions. Ecological importance is quantified through ecological sensitivity analysis and InVEST-based habitat-quality modeling, while ecological connectivity potential is estimated via normalized least-cost corridor analysis. Construction suitability is derived from the proportion of artificial surfaces and road network density, and recreational demand is measured by population concentration, facility density, and transport accessibility. These metrics are synthesized to map nature-suitability patterns and reveal divergences between human demand and ecological provisioning. The results show a pronounced north–south gradient in ecological importance, with Dongxiaokou Ditch and Dongxiaokou Forest Park emerging as ecological hotspots. Nineteen ecological source patches are identified, with the strongest connectivity in the southern sector of Dongxiaokou Forest Park. Areas of high construction suitability coincide with well-developed infrastructure, whereas recreational demand clusters around Tiantongyuan and Beiqing Road. Natural and artificial elements intertwine to form an ecological core of 870.74 hm², yet 13.29% of the study area exhibits mismatches—particularly residential zones lacking green-space access. Over-development within Dongxiaokou Urban Recreation Park likewise falls short of ecological expectations. The study offers targeted recommendations—ecological protection, facility optimization, green-space enhancement, and the integration of multifunctional green infrastructure—and provides a transferable framework for coordinating human and natural systems in other urban–rural fringe contexts. Full article

Soil has the ability to serve as a universal sink, meaning it may absorb contaminants from the environment. Additionally, plant leaves can also be used as indicators of environmental contamination. In our study, the bioaccumulation factor (BAF) was used to assess metal accumulation in the soil and leaves of the neem tree (Azadirachta indica) in Faisalabad, Pakistan. We analyzed the primary physical and chemical characteristics of the surface layer of soil in urban, suburban, and rural areas along an urbanization gradient. The ICP-OES technique was used to analyze the following elements: Ba, Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb, Sr and Zn. The highest concentration of all elements was found in soil samples from urban areas, with an increasing tendency along with the urbanization gradient. A significant difference was found along the urbanization gradient on the plant leaves except for Cd, Cu, and Zn; a high level of pollution was measured for Ba, Pb, Co, Ni, Cr, and Cd in the urban area. We also calculated the bioaccumulation factor (BAF), but no clear pattern was found. Our findings show that high concentrations in soil do not always turn into higher plant uptake for plants. Our findings suggest that traffic and industrial emissions are likely the main cause of the metals in Faisalabad, because their concentration is higher than their background concentration. Our results also suggest that elemental analysis of soil and plant leaves is an appropriate indicator of environmental contamination. Full article

This study focuses on 67 counties in Guangdong Province, China, and investigates the spatial distribution patterns, regional differentiation characteristics, and functional zoning of rural areas based on the “Production–Living–Ecological” (PLE) functional synergy theoretical framework. Multiple quantitative methods, including the entropy method, spatial concentration degree, and functional identification, were employed. Key findings include: (1) Rural functions in Guangdong exhibit significant heterogeneous evolution. Production functions have generally weakened, showing a spatial pattern of “consolidation in the south and decline in the north”. Ecological functions demonstrate a U-shaped recovery trend, with high-value areas concentrating around the Pearl River Delta urban agglomeration, indicating effective ecological protection policies. Living functions continue to decline due to population mobility and imbalanced public services. (2) Structural transformation of rural function types occurred: Weakly integrated counties decreased (2010–2019), dual function type counties (production–ecological and living–ecological) significantly increased, and ecology-dominant counties predominated, highlighting ecological polarization under policy interventions. (3) Functional evolution is driven by terrain gradients, policy regulation, and industrial relocation. The research provides empirical evidence for optimizing territorial spatial governance and coordinating urban–rural development. Recommendations include promoting dynamic PLE balance through high-standard farmland construction, ecological industrialization cultivation, and cross-regional compensation mechanisms to facilitate rural revitalization and sustainable development. Full article

The built environment has been widely recognized as a critical determinant of physical activity among older adults. However, urban–rural disparities and the non-linear effects of environmental features remain underexplored. Using interpretable machine learning (random forest model) on nationwide representative data from 2526 older adults in the China Health and Retirement Longitudinal Study (CHARLS) database, this study identified both common and distinct risk factors for insufficient moderate-to-vigorous physical activity (MVPA) across diverse urban and rural contexts. The results revealed a location-based gradient in physical activity insufficiency: rural areas < suburban areas < central urban areas. Rural older adults faced greater constraints from safety concerns and transportation accessibility limitations. In comparison, urban older adults would benefit from targeted improvements in built environment quality, particularly elevator accessibility and diverse public activity spaces. Furthermore, non-linear relationships were observed between built environment features and physical activity, elucidating the “density paradox”: while moderate urban compactness promoted active behaviors, excessive density (>24,000 persons/km²), perceived overcrowding, and over-proximity to specific facilities (<1 km) were linked to reduced MVPA. These findings underscore the necessity for differentiated policy interventions in urban and rural settings to address the distinct environmental needs of older adults. Meanwhile, in urban planning, it is crucial that we balance spatial compactness and functional diversity within optimal thresholds for creating sustainable and inclusive built environments. Although a compact design may enhance mobility, equal attention must be paid to preventing spatial disorder from over-densification. Full article

The urban heat island (UHI) effect has emerged in the literature as a major challenge to urban well-being, primarily driven by increasing urbanization. To address this challenge, this study investigates the spatiotemporal pattern of the UHI in the fast-growing city of Kisangani and within its urban–rural gradient from 2000 to 2024 using land surface temperature (LST) data from the MODIS 11A2 V6.1 product. Inferential and descriptive statistics were applied to examine the patterns of UHI and the relationships between the LST, building volume density (BVD), and vegetation density expressed by the Normalized Difference Vegetation Index (NDVI). The results showed that the spatial extent of the moderate UHI gradually increased from 16 km² to 38 km², while the high UHI increased from 9 km² to 19 km². Furthermore, although high UHI values (0.2 < UHI ≤ 0.3) are observed in urban areas and significant differences in UHI variations are detected across urban, peri-urban, and rural zones, the results indicate that the mean UHI in Kisangani’s urban areas remains below 0.2. Therefore, based on average UHI variations, Kisangani’s urban zones exhibit moderate disparities in LST compared to rural areas. Moreover, the LST variations significantly correlate with the building volume and vegetation densities. However, the influence of vegetation density as a predictor of LST gradually decreases while the influence of building volume density increases over time, suggesting the need to implement a synergistic development pathway to manage the interactions between urbanization, landscape change, and ecosystem service provision. This integrated approach may represent a crucial solution for mitigating the UHI effect in regions categorized as high-temperature zones. Full article