Search Results (240)

The development of the Great Wall National Cultural Park has unleashed the potential for integrating cultural and tourism development along the Great Wall. However, ICH along the Great Wall, a key part of its cultural identity, suffers from low recognition and a mismatch between protection and development efforts. This study analyzes provincial-level and above ICH along Hebei’s Great Wall using geospatial tools and the Geographical Detector model to explore distribution patterns and influencing factors, while Geographically Weighted Regression is utilized to reveal spatial heterogeneity. It tests two hypotheses: (H1) ICH shows a clustered pattern; (H2) economic factors have a greater impact than cultural and natural factors. Key findings show: (1) ICH distribution is numerically balanced north–south but spatially uneven, with dense clusters in the south and scattered patterns in the north. (2) ICH and crafts cluster significantly, while dramatic balladry spreads evenly, and other categories are random. (3) Average annual temperature and precipitation have the greatest impact on ICH distribution, with the factors ranked as: natural > cultural > economic. Multidimensional interactions show significant enhancement effects. (4) Influencing factors vary spatially. Population density, transport, temperature, and traditional villages are positively related to ICH. Elevation, precipitation, tourism, and cultural institutions show mixed effects across regions. These insights support targeted ICH conservation and sustainable development in the Great Wall cultural corridor. Full article

Dark skies, a vital natural and cultural resource, have been increasingly threatened by light pollution due to rapid urbanization, leading to ecological degradation and biodiversity loss. As a key strategy for sustainable regional development, dark sky parks (DSPs) not only preserve nocturnal environments but also enhance livability by balancing urban expansion and ecological conservation. This study develops a novel framework for evaluating DSP suitability, integrating ecological and socio-economic dimensions, including the resource base (e.g., nighttime light levels, meteorological conditions, and air quality) and development conditions (e.g., population density, transportation accessibility, and tourism infrastructure). Using the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) as a case study, we employ Delphi expert consultation, GIS spatial analysis, and multi-criteria decision-making to identify optimal DSP locations and prioritize conservation zones. Our key findings reveal the following: (1) spatial heterogeneity in suitability, with high-potential zones being concentrated in the GBA’s northeastern, central–western, and southern regions; (2) ecosystem advantages of forests, wetlands, and high-elevation areas for minimizing light pollution; (3) coastal and island regions as ideal DSP sites due to the low light interference and high ecotourism potential. By bridging environmental assessments and spatial planning, this study provides a replicable model for DSP site selection, offering policymakers actionable insights to integrate dark sky preservation into sustainable urban–regional development strategies. Our results underscore the importance of DSPs in fostering ecological resilience, nighttime tourism, and regional livability, contributing to the broader discourse on sustainable landscape planning in high-urbanization contexts. Full article

This study investigates the heavy metal contamination in urban and peri-urban soils of Thessaloniki, Greece, over a two-year period (2023–2024). A total of 208 composite soil samples were systematically collected from 52 sites representing diverse land uses, including high-traffic roadsides, industrial zones, residential neighborhoods, parks, and mixed-use areas, with sampling conducted both after the wet (winter) and dry (summer) seasons. Soil physicochemical properties (pH, electrical conductivity, texture, organic matter, and calcium carbonate content) were analyzed alongside the concentrations of heavy metals such as Cd, Co, Cr, Cu, Mn, Ni, Pb, and Zn. A pollution assessment employed the Geoaccumulation Index (I_geo), Contamination Factor (Cf), Pollution Load Index (PLI), and Potential Ecological Risk Index (RI), revealing variable contamination levels across the city, with certain hotspots exhibiting a considerable to very high ecological risk. Multivariate statistical analyses (PCA and HCA) identified distinct anthropogenic and geogenic sources of heavy metals. Health risk assessments, based on USEPA models, evaluated non-carcinogenic and carcinogenic risks for both adults and children via ingestion and dermal contact pathways. The results indicate that while most sites present low to moderate health risks, specific locations, particularly near major transport and industrial areas, pose elevated risks, especially for children. The findings underscore the need for targeted monitoring and remediation strategies to mitigate the ecological and human health risks associated with urban soil pollution in Thessaloniki. Full article

This study examines diurnal surface temperature dynamics across major Moroccan cities during the growing season and explores the interaction between urban and vegetated surfaces. We also introduce the Urban Thermal Impact Ratio (UTIR), a novel metric designed to quantify urban thermal comfort as a function of the surface urban heat island (SUHI) intensity. The analysis is based on outputs from a land surface model (LSM) for the year 2010, integrating high-resolution Landsat and MODIS data to characterize land cover and biophysical parameters across twelve land cover types. Our findings reveal moderate urban–vegetation temperature differences in coastal cities like Tangier (1.8 °C) and Rabat (1.0 °C), where winter vegetation remains active. In inland areas, urban morphology plays a more dominant role: Fes, with a 20% impervious surface area (ISA), exhibits a smaller SUHI than Meknes (5% ISA), due to higher urban heating in the latter. The Atlantic desert city of Dakhla shows a distinct pattern, with a nighttime SUHI of 2.1 °C and a daytime urban cooling of −0.7 °C, driven by irrigated parks and lawns enhancing evapotranspiration and shading. At the regional scale, summer UTIR values remain below one in Tangier-Tetouan-Al Hoceima, Rabat-Sale-Kenitra, and Casablanca-Settat, suggesting that urban conditions generally stay within thermal comfort thresholds. In contrast, higher UTIR values in Marrakech-Safi, Beni Mellal-Khénifra, and Guelmim-Oued Noun indicate elevated heat discomfort. At the city scale, the UTIR in Tangier, Rabat, and Casablanca demonstrates a clear diurnal pattern: it emerges around 11:00 a.m., peaks at 1:00 p.m., and fades by 3:00 p.m. This study highlights the critical role of vegetation in regulating urban surface temperatures and modulating urban–rural thermal contrasts. The UTIR provides a practical, scalable indicator of urban heat stress, particularly valuable in data-scarce settings. These findings carry significant implications for climate-resilient urban planning, optimized energy use, and the design of public health early warning systems in the context of climate change. Full article

Cocaine misuse induces microglial activation and neuroinflammation, contributing to neurodegeneration and behavioral impairments. Prior studies have shown that cocaine induces mitochondrial dysfunction, dysregulated mitophagy, and lysosomal impairment in microglia. Here, we investigated the therapeutic potential of N-acetylcysteine (NAC) in mitigating cocaine-induced microglial activation and neuroinflammation. Mouse primary microglial cells (MPMs) were pretreated with NAC (5 mM) for 1 h prior to cocaine exposure (10 µM, 24 h) and analyzed for markers of microglial activation, mitophagy, and lysosomal integrity using Western blot, Seahorse assays, lysosomal pH, and membrane potential measurements. In vivo, C57BL/6N mice received NAC (200 mg/kg, i.p.) 1 h before daily cocaine injections (20 mg/kg, i.p.) for 7 days. Behavioral assays (open field, novel object recognition) and brain biomarker analyses (frontal cortex, hippocampus) were performed. Cocaine exposure elevated CD11b, mitophagy markers (PINK1, PARK, and DLP1), and autophagy proteins (Beclin1, and p62), while impairing mitochondrial and lysosomal functions. NAC pretreatment restored mitochondrial and lysosomal function, reduced reactive oxygen species, and normalized protein expression. In vivo, NAC also alleviated cocaine-induced microglial activation and behavioral deficits. These findings highlight NAC as a promising therapeutic agent to counteract cocaine-mediated neuroinflammation and neurotoxicity. Full article

Understanding the geographic distribution of mammal species is essential for informed conservation planning, maintaining local ecosystem stability, and addressing research gaps, particularly in data-deficient regions. This study investigated the distribution and richness of 20 mammal species within Nyerere National Park (NNP), a large and understudied protected area in Southern Tanzania. We applied species distribution models (SDMs) using presence data collected through ground surveys between 2022 and 2024, combined with environmental variables derived from remote sensing, including land surface temperature, vegetation indices, soil moisture, elevation, and proximity to water sources and human infrastructure. Models were constructed using the Maximum Entropy (MaxEnt) algorithm, and performance was evaluated using the Area Under the Curve (AUC) metric, yielding high accuracy ranging from 0.81 to 0.97. Temperature (32.3%) and vegetation indices (23.4%) emerged as the most influential predictors of species distributions, followed by elevation (21.7%) and proximity to water (14.5%). Species richness, estimated using a stacked SDM approach, was highest in the northern and riparian zones of the park, identifying potential biodiversity hotspots. This study presents the first fine-scale SDMs for mammal species in Nyerere National Park, offering a valuable ecological baseline to support conservation planning and promote sustainable ecotourism development in Tanzania’s southern protected areas. Full article

National parks serve as critical spatial units for conserving ecological baselines, maintaining genetic diversity, and delivering essential ecosystem services. However, accelerating socio-economic development has increasingly intensified the conflict between ecological protection and transportation infrastructure. Ecologically sustainable transportation planning is, therefore, essential to mitigate habitat fragmentation, facilitate species migration, and conserve biodiversity. This study examines the Giant Panda National Park and its buffer zone, focusing on six mammal species: giant panda, Sichuan snub-nosed monkey, leopard cat, forest musk deer, rock squirrel, and Sichuan takin. By integrating Maxent ecological niche modeling with circuit theory, it identified ecological source areas and potential corridors, and employed a two-step screening approach to design species-specific wildlife crossings. In total, 39 vegetated overpasses were proposed to serve all target species; 34 underpasses were integrated using existing bridge and culvert structures to minimize construction costs; and 27 canopy bridges, incorporating suspension cables and elevated pathways, were designed to connect forest canopies for arboreal species. This study established a multi-species and multi-scale conservation framework, providing both theoretical insights and practical strategies for ecologically integrated transportation planning in national parks, contributing to the synergy between biodiversity conservation and sustainable development goals. Full article

This study assesses habitat suitability and identifies conservation priority areas for the endangered Marco Polo sheep throughout Khunjerab National Park (Pakistan) and Tashkurgan Natural Reserve (China). We analyzed species occurrence records against environmental variables (elevation, slope, climate, land cover) using MaxEnt modeling. Model performance was validated through AUC-ROC analysis and response curves, generating spatial predictions of suitable habitats to inform conservation strategies. Spatial predictions were generated to map potential distribution zones, aiding conservation planning for this endangered species. The model’s predictive performance was evaluated using the Area Under the Curve (AUC) of the Receiver Operating Characteristic curve, yielding an AUC of 0.919, indicating strong discriminatory capability. Elevation (43.9%), slope (25.9%), and September precipitation (15.9%) emerged as the most influential environmental predictors, collectively contributing 85.7% to the model. The total percentage contribution and permutation significance values were 98.6% and 77.8%, respectively. Jackknife analysis identified elevation (bio-1), slope (bio-7), hillshade (bio-2), and the maximum July temperature (bio-9) as the most significant factors influencing the distribution of Marco Polo sheep, Conversely, variables such as viewshade (bio-14), land cover (bio-3), and precipitation in August (bio-4) contributed a minimal gain, suggesting that they had little impact on accurately predicting species distribution. The habitat suitability map reveals varying conditions across the study area, with the highest suitability (yellow zones) found in the northern and western regions, particularly along the Wakhan Corridor ridgelines. The southern regions, including Khunjerab Pass, show predominantly low suitability, marked by purple zones, suggesting poor habitat conditions. The eastern region displays moderate to low suitability, with fragmented patches of green and yellow, indicating seasonal habitats. The survival of transboundary Marco Polo sheep remains at risk due to poaching activities and habitat destruction and border fence barriers. This study recommends scientific approaches to habitat restoration together with improved China–Pakistan cooperation in order to establish sustainable migratory patterns for this iconic species. Full article

Traditional park designs no longer meet the diverse needs of young users amid rising visitor numbers and environmental challenges. Exploring the impact of mountain city parks on youth is crucial, yet localised studies on their spatial perceptions in such unique environments are lacking. Landscape design based on spatial perception evaluation offers a promising approach for renewing mountain parks to address these complex needs. Therefore, a pilot study was conducted in Chongqing’s Pipa Mountain and Eling Parks, involving questionnaire surveys and on-site spatial data collection. Using principal component analysis to select the visual and auditory indicators most related to environmental satisfaction in the overall park and various types of gathering spaces, the results showed that the first principal component of the visual environment in the entrance platform and key nodes (r = 0.41, r = 0.45), as well as the first principal component of the auditory environment in the entrance platform, path platform, and elevated points (r = 0.67, r = 0.85, r = 0.68), all showed significant positive correlations with environmental satisfaction (p < 0.01). Moreover, naturalness and aesthetics were identified as the main factors influencing environmental satisfaction. A random forest model analysed nonlinear relationships, ranking spatial factors by importance. Simultaneously, SHAP analysis highlighted the effects of key factors like elevation changes, green view index, colour diversity, and natural elements. Elevation changes were positively correlated with satisfaction at elevated points but showed a negative correlation in the overall park environment and other gathering spaces. This study explored space-perception dynamics in mountain city parks, proposing strategies to improve environmental quality in various gathering spaces and the park. These findings support creating liveable mountainous environments and guide “human-centred health,” quality enhancement, and sustainable development in renewing mountain city parks. Full article

Forest ecosystems serve as pivotal components of the global carbon cycle, with canopy height representing a critical biophysical parameter for quantifying ecosystem functionality, thereby holding substantial implications for forest resource management and carbon sequestration assessments. The precise extraction of ground elevation and vegetation canopy height is essential for advancing topographic and ecological research. The Terrestrial Ecosystem Carbon Inventory Satellite (referred to as TECIS hereafter) offers unprecedented capabilities for the large-scale, high-precision extraction of ground elevation and vegetation canopy height. Using the Northeast China Tiger and Leopard National Park as our study area, we first processed TECIS data to derive topographic and canopy height profiles. Subsequently, the accuracy of TECIS-derived ground and canopy height estimates was validated using onboard light detection and ranging (LiDAR) measurements. Finally, we systematically evaluated the influence of multiple factors on estimation accuracy. Our analysis revealed that TECIS-derived ground and canopy height estimates exhibited mean errors of 0.7 m and −0.35 m, respectively, with corresponding root mean square error (RMSE) values of 3.83 m and 2.70 m. Furthermore, slope gradient, vegetation coverage, and forest composition emerged as the dominant factors influencing canopy height estimation accuracy. These findings provide a scientific basis for optimizing the screening and application of TECIS data in global forest carbon monitoring. Full article

Road crashes impose significant societal costs, and while links between static land use and safety are established, the long-term impacts of dynamic land use conversions remain under-explored. This study addresses this gap by investigating and quantifying how specific land use transitions over a decade influence subsequent road crash frequency in Metropolitan Melbourne. Our objective was to understand which conversion pathways pose the greatest risks or offer safety benefits, informing urban planning and policy. Utilizing extensive observational data covering numerous land use conversions, we employed Negative Binomial models (selected as the best fit over Poisson and quasi-Poisson alternatives) to analyze the association between various transition types and crash occurrences in surrounding areas. The analysis revealed distinct and statistically significant safety outcomes. Major findings indicate that transitions introducing intensified activity and vulnerable road users, such as converting agricultural land or parks to educational facilities (e.g., Agri → Edu, coefficient ≈ +0.10; Park → Edu, ≈+0.12), or intensifying land use in previously less active zones (e.g., Park → Com, ≈+0.07; Trans → Park, ≈+0.10), significantly elevate long-term crash risk, particularly when infrastructure is inadequate. Conversely, conversions creating low-traffic, nature-focused environments (e.g., Water → Park, ≈–0.16) or channeling activity onto well-suited infrastructure (e.g., Trans → Com, ≈–0.12) demonstrated substantial reductions in crash frequency. The critical role of context-specific infrastructure adaptation, highlighted by increased risks in some park conversions (e.g., Com → Park, ≈+0.06), emerged as a key mediator of safety outcomes. These findings underscore the necessity of integrating dynamic, long-term road safety considerations into land use planning, mandating appropriate infrastructure redesign during conversions, and prioritizing interventions for identified high-risk transition scenarios to foster safer and more sustainable urban development. Full article

From 1998 to 2024, we collected field samples at 45 selected lakes in Yellowstone National Park during the months of April through October. We estimated inflows, outflows, and Secchi depths for most lakes. We analyzed the samples for total phosphorous and chlorophyll-a. We used these data to classify the lake trophic states using the Carlson TSI (CTSI), Vollenweider (VW), and Larsen–Mercier (LM) models to assess how trophic states evolved over this 26-year period. This longitudinal dataset is unique because of its extensive 26-year time span gathered from difficult-to-access locations. We found that the data depended on lake size, lake elevation, and the month when data were collected. Most of the lakes exhibit mesotrophic conditions, with variations depending on the trophic state model used. The CTSI distribution shows median values typically between 40 and 55, while the VW and LM index distributions present a somewhat similar pattern but with fewer lakes categorized due to data requirements. We visualized temporal patterns using heatmaps and analyzed trends using the Mann–Kendall test to identify trends and if they were statistically significant. We found only four lakes with statistically significantly increasing trends and two with decreasing trends. Because of the difference in the months when data were collected, the increasing trends in three of the lakes are less certain. We found that, except for four lakes, the trophic states of Yellowstone lakes were maintained or improved over this ~20-year period. Only the trophic state of Nymph Lake clearly deteriorated. The remaining lakes had stable trophic states, with three having weak evidence of worsening conditions. This long-term dataset, which we publish for others’ use, provides an opportunity to better understand eutrophication processes and water quality dynamics in Yellowstone, providing critical information for park management and conservation efforts. Full article

Rapid urbanization in Karachi, Pakistan, has resulted in increased impervious surfaces, leading to significant challenges, such as frequent flooding, urban heat islands, and loss of vegetation. These issues pose challenges to urban resilience, livability, and sustainability, which further demand solutions that incorporate urban greening and effective water management. This research uses remote sensing technologies and Geographic Information Systems (GISs), to analyze current surface treatments and their relationship to Karachi’s blue-green infrastructure. By following this approach, we evaluate flood risk and identify key flood-conditioning factors, including elevation, slope, rainfall distribution, drainage density, and land use/land cover changes. By utilizing the Analytical Hierarchy Process (AHP), we develop a flood risk assessment framework and a comprehensive flood risk map. Additionally, this research proposes an innovative Sponge City (SC) framework that integrates nature-based solutions (NBS) into urban planning, especially advocating for the establishment of green infrastructure, such as green roofs, rain gardens, and vegetated parks, to enhance water retention and drainage capacity. The findings highlight the urgent need for targeted policies and stakeholder engagement strategies to implement sustainable urban greening practices that address flooding and enhance the livability of Karachi. This work not only advances the theoretical understanding of Sponge Cities but also provides practical insights for policymakers, urban planners, and local communities facing similar sustainability challenges. Full article

The value network of the high-tech park constitutes a value co-creation system where multiple entities facilitate knowledge transformation through interaction, thereby achieving collaborative innovation. The reasonable distribution of collaborative innovation benefits among various innovation entities is a critical factor in maintaining the motivation for innovation within the value network. This study examines the co-creation mechanism of the value network in high-tech parks from the perspective of knowledge innovation, with the aim of enhancing the efficiency of knowledge transfer and spillover among entities. Additionally, it seeks to establish a fairer and more rational benefit distribution framework to promote collaborative innovation and ensure the stable operation of the value network. Firstly, we identify the entities involved in value co-creation within the high-tech park. Subsequently, we analyze the roles and interrelationships of these entities within the value co-creation network. We determine the knowledge flow pathways by employing the shortest path method, and innovatively construct an MMPP/M/C queuing model to depict the processes of knowledge transfer and spillover among the entities engaged in value co-creation. We optimize and solve the queuing model using the matrix geometric method, deriving metrics such as the average queue length, average arrival rate, average waiting time, and service intensity under the steady state of the system, and verify the applicability and effectiveness of the model in the application of the high-tech park through empirical data. Finally, by integrating the improved Shapley value method, a benefit distribution model is constructed that incorporates five types of factors: contribution level, resource input, knowledge spillover effect, effort level, and risk undertaking. The rationality and operability of this model are validated through computational examples. Research findings indicate that the optimized queuing model enhances the efficiency of knowledge transfer and spillover among entities, while the refined benefit distribution mechanism effectively compensates entities with high contribution levels, substantial resource inputs, significant knowledge spillover effects, elevated effort levels, and high risk assumption levels. This provides both theoretical support and practical guidance for sustaining the long-term stable operation of the value network. Full article

The aging population has posed significant challenges to the built environment (BE) in urban residential areas, particularly in addressing older adults’ activity and health needs. Understanding how the BE influences older adults’ activity and health is crucial for promoting active and healthy aging. This study explored the interactions among the BE, self-efficacy (SE), activity engagement (AE), and self-rated health (SH) for older adults in urban residential areas. A random sampling technique selected 372 older adults residing in urban residential areas to participate in the questionnaire survey. Spearman correlation and hierarchical regression analysis were used to develop the BE-SE-AE-SH model for older people based on social cognitive theory. Accessibility, land use mix, and street connectivity affect activity engagement by influencing older persons’ walking and self-care abilities. Land use mix discourages walking ability and activity engagement, while esthetics encourages activity engagement. Land use mix, street connectivity, transportation, walking ability, self-care ability, and activity engagement enhance older adults’ self-rated health. Practical recommendations for age-friendly urban residential areas include the following: (1) optimize elevators and footpaths; (2) decentralize small businesses and create multi-use parking; (3) shorten crossings and enhance pavements; (4) add natural and humanistic elements; (5) limit car speed and install traffic signals. Full article