Search Results (339)

Various nature-based solutions (NbS)—such as constructed wetlands, drainage ditches, and vegetated buffer strips—have recently demonstrated strong potential for mitigating pollutant transport in open channels and river systems. Numerical modeling is a widely adopted and effective approach for assessing the performance of these interventions. This study presents the first development of a two-dimensional (2D) meshless advection–diffusion model based on an Eulerian smoothed particle hydrodynamics (SPH) framework, specifically designed to simulate passive pollutant transport in open channel flows. The proposed model marks a pioneering application of the ESPH technique to environmental pollutant transport problems. It couples the 2D depth-averaged shallow water equations with an advection–diffusion equation to represent both fluid motion and pollutant concentration dynamics. A uniform particle arrangement ensures that each fluid particle interacts symmetrically with eight neighboring particles for flux computation. To represent the pollutant transport process, the dispersion coefficient is defined as the sum of molecular and turbulent diffusion components. The turbulent diffusion coefficient is calculated using a prescribed turbulent Schmidt number and the eddy viscosity obtained from a Smagorinsky-type mixing-length turbulence model. Three analytical case studies, including one-dimensional transcritical open channel flow, 2D isotropic and anisotropic diffusion in still water, and advection–diffusion in a 2D uniform flow, are employed to verify the model’s accuracy and convergence. The model demonstrates first-order convergence, with relative root mean square errors (RRMSEs) of approximately 0.2% for water depth and velocity, and 0.1–0.5% for concentration. Additionally, the model is applied to a laboratory experiment involving 2D pollutant dispersion in a 90° junction channel. The simulated results show good agreement with measured velocity and concentration distributions. These findings indicate that the developed model is a reliable and effective tool for evaluating the performance of NbS in mitigating pollutant transport in open channels and river systems. Full article

Accurate phenological information on sugarcane is crucial for guiding precise cultivation management and enhancing sugar production. Remote sensing offers an efficient approach for large-scale phenology retrieval, but most studies have primarily focused on staple crops. The methods for retrieving the sugarcane phenology—the germination, tillering, elongation, and maturity stages—remain underexplored. This study addresses the challenge of accurately monitoring the sugarcane phenology in complex terrains by proposing an optimized strategy integrating spatiotemporal fusion data. Ground-based validation showed that the change detection method based on the Double-Logistic curve significantly outperformed the threshold-based approach, with the highest accuracy for the elongation and maturity stages achieved at the maximum slope points of the ascending and descending phases, respectively. For the germination and tillering stages with low canopy cover, a novel time-windowed change detection method was introduced, using the first local maximum of the third derivative curve (denoted as Point A) to establish a temporal buffer. The optimal retrieval models were identified as 25 days before and 20 days after Point A for germination and tillering, respectively. Among the six commonly used vegetation indices, the NDVI (normalized difference vegetation index) performed the best across all the phenological stages. Spatiotemporal fusion using the ESTARFM (Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model) significantly improved the monitoring accuracy in heterogeneous agricultural landscapes, reducing the RMSE (root-mean-squared error) by 21–46%, with retrieval errors decreasing from 18.25 to 12.97 days for germination, from 8.19 to 4.41 days for tillering, from 19.17 to 10.78 days for elongation, and from 19.02 to 15.04 days for maturity, highlighting its superior accuracy. The findings provide a reliable technical solution for precision sugarcane management in heterogeneous landscapes. Full article

This paper examines how artificial intelligence (AI) can be strategically deployed to enhance urban planning and environmental livability in Riyadh by generating data-driven, people-centric design interventions. Unlike previous studies that concentrate primarily on visualization, this research proposes an integrative appraisal framework that combines AI-generated design with site-specific environmental data and native vegetation typologies. This study was conducted across key jurisdictional areas including the Northern Ring Road, King Abdullah Road, Al Rabwa, Al-Malaz, Al-Suwaidi, Al-Batha, and King Fahd Road. Using AI tools, urban scenarios were developed to incorporate expanded pedestrian pathways (up to 3.5 m), dedicated bicycle lanes (up to 3.0 m), and ecologically adaptive green buffer zones featuring native drought-resistant species such as Date Palm, Acacia, and Sidr. The quantitative analysis of post-intervention outcomes revealed surface temperature reductions of 3.2–4.5 °C and significant improvements in urban esthetics, walkability, and perceived safety—measured on a five-point Likert scale with 80–100% increases in user satisfaction. Species selection was validated for ecological adaptability, minimal maintenance needs, and compatibility with Riyadh’s sandy soils. This study directly supports the Kingdom of Saudi Arabia’s Vision 2030 by demonstrating how emerging technologies like AI can drive smart, sustainable urban transformation. It aligns with Vision 2030’s urban development goals under the Quality-of-Life Program and environmental sustainability pillar, promoting healthier, more connected cities with elevated livability standards. The research not only delivers practical design recommendations for planners seeking to embed sustainability and digital innovation in Saudi urbanism but also addresses real-world constraints such as budgetary limitations and infrastructure integration. Full article

In recent decades, the Brazilian Cerrado has faced rapid land conversion, resulting in the loss of approximately half of its original vegetation cover. Most existing conservation units within the biome are increasingly threatened by the expansion of land use around their boundaries. The establishment of buffer zones with land use regulations may protect biodiversity within these protected areas. In this study, we evaluated and ranked the 10 km buffer zones of 15 national parks (NPs) located in the Cerrado biome, identifying their priority for biodiversity conservation and sustainable land use interventions. The analysis considered the following data: land use and land cover change from 2012 to 2020, extent of natural vegetation fragments, presence or absence of state and municipal conservation units within the buffer zones, and drainage density. Two multicriteria analysis methods, the analytic hierarchy process and the weighted linear combination, were applied to classify the buffer zones into five levels of threat: very high, high, moderate, low, and very low. Among the 15 buffer zones analyzed, 11 were classified as having high to very high priority for conservation actions. The buffer zones surrounding the Serra da Bodoquena, Emas, Canastra, and Brasília NPs were ranked as having very high priority. Between 2012 and 2020, the most severe reductions in ecological connectivity were observed in the buffer zones of Grande Sertão Veredas (44.5%), Nascentes do Rio Parnaíba (40.4%), and Serra das Confusões (36.7%). Given the relatively high proportion of natural vegetation in the buffer zones located in the northern Cerrado, we recommend prioritizing conservation efforts in this region. In contrast, in the southern portion of the biome, where land occupation is more intense, strategies should focus on promoting environmentally sustainable land use practices. 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

Ningxia has emerged as a strategic hub for China’s photovoltaic (PV) industry by leveraging abundant solar energy resources and geoclimatic advantages. This study analyzed the spatiotemporal expansion trends and microclimatic impacts of PV installations (2015–2024) using Gaofen-1 (GF-1) and Landsat8 satellite imagery with deep learning algorithms and multidimensional environmental metrics. Among semantic segmentation models, DeepLabV3+ had the best performance in PV extraction, and the Mean Intersection over Union, precision, and F1-score were 91.97%, 89.02%, 89.2%, and 89.11%, respectively, with accuracies close to 100% after manual correction. Subsequent land surface temperature inversion and spatial buffer analysis quantified the thermal environmental effects of PV installation. Localized cooling patterns may be influenced by albedo and vegetation dynamics, though further validation is needed. The total PV site area in Ningxia expanded from 59.62 km² to 410.06 km² between 2015 and 2024. Yinchuan and Wuzhong cities were primary growth hubs; Yinchuan alone added 99.98 km² (2022–2023) through localized policy incentives. PV installations induced significant daytime cooling effects within 0–100 m buffers, reducing ambient temperatures by 0.19–1.35 °C on average. The most pronounced cooling occurred in western desert regions during winter (maximum temperature differential = 1.97 °C). Agricultural zones in central Ningxia exhibited weaker thermal modulation due to coupled vegetation–PV interactions. Policy-driven land use optimization was the dominant catalyst for PV proliferation. This study validates “remote sensing + deep learning” framework efficacy in renewable energy monitoring and provides empirical insights into eco-environmental impacts under “PV + ecological restoration” paradigms, offering critical data support for energy–ecology synergy planning in arid regions. Full article

The clean-label movement has markedly increased consumer demand for meat products free from synthetic additives, such as sodium nitrite, ascorbate, and phosphate. This review summarizes strategies to replace these additives with natural alternatives while preserving the functional and quality properties of traditionally cured meats. Nitrite replacement commonly employs nitrate-rich vegetables, alongside nitrate-reducing starter cultures or pre-converted nitrite powders for adequate nitric oxide production and meat pigment stabilization. Ascorbate substitutes include vitamin C-rich materials and polyphenol-based antioxidants from green tea and rosemary, supporting nitrite reduction and contributing to meat pigment and oxidative stability. To compensate for phosphate functions, natural substitutes such as hydrocolloids, dietary fibers, protein isolates, and calcium powders from eggshells or oyster shells have shown partial success in restoring water-holding capacity, pH buffering, and textural integrity. In addition, non-thermal processing technologies, such as high-pressure processing, ultrasound, and cold plasma are explored as complementary strategies to enhance the efficacy of natural ingredients and support industrial scalability. However, challenges persist regarding ingredient variability, dose-dependent effects, and consistency in functional performance. Future research should focus on synergistic ingredient combinations, formulation standardization, and scalable application in industrial production to ensure the production of high-quality clean-label meat products. Full article

We investigated the combined effects of climate and land-use change on plant diversity in northwestern Greece, a region representative of broader European trends in land abandonment. We based our study on comprehensive field data on plants’ distribution and modelling of land-use changes based on socio-economic trends. We build distribution models for 358 taxa based on current (2015) and future (2055) conditions according to the combinations of three climate and three land-use change scenarios. We compared species distribution changes between current and future conditions for each scenario, and we investigated species trends concerning their ecological indicator values and strategies. Additionally, by analyzing the distribution changes in aggregated differential taxa representing the various plant communities in the study area, we identified patterns of distribution shifts at the community level. Our results indicated more pronounced differences between land-use scenarios than between climate ones, which was attributed to the local scale of the study area, its climatic and physiographic characteristics, and its complex land-use legacy. Both climate and land-use changes drastically reduced the distribution of some species, with species distribution loss exceeding 80% under certain combinations of socioeconomic and climate change scenarios. Species ecological indicator values and strategies showed a buffering effect of forest microclimate against climate change, which, however, may favor only species of forest communities. At the community level, land-use change had again a stronger impact than climate change, with consistent patterns within major vegetation types (forests and open habitats) but contrasting trends between them. Our results highlight the need for appropriate conservation plans to counteract the negative impacts of land abandonment and to take advantage of its positive impacts. Full article

Blue–green infrastructure is widely recognized for mitigating the urban heat island effect. However, most existing ENVI-met 5.6.1 studies focus on average thermal conditions and overlook fine-scale spatial gradients. This study investigates the urban park in Luoyang City by integrating high-resolution 3D ENVI-met simulations, multi-source data, and field measurements to quantify thermal gradients between park interiors and surrounding built-up areas. A midline cut-off approach was applied to extract horizontal and vertical thermal profiles. The results show that (1) temperature and physiological equivalent temperature (PET) differences are most pronounced at park edges and transition zones, where vegetation and water bodies serve as natural cooling buffers; (2) urban form indicators, especially the building coverage and open space ratio, significantly impact wind speed and the PET, with greenery improving thermal comfort via shading and evapotranspiration, while impervious surfaces intensify heat stress; (3) the park exhibits a distinct cold island effect, with the average PET in the core area up to 12.3 °C lower than in adjacent built-up zones. The effective cooling distance, which is identified through buffer-based zonal statistics, rapidly attenuates within approximately 200 m from the park boundary. These findings offer a novel spatial perspective on thermal regulation mechanisms of urban landscapes and provide quantitative evidence to guide the design of climate-resilient green infrastructure. Full article

The common leopard (Panthera pardus) in Azad Jammu and Kashmir (AJ and K), Pakistan, is increasingly threatened by habitat fragmentation and climate change. This study employs a dual-model approach, integrating Maximum Entropy (MaxEnt) and Random Forest algorithms with multi-source remote sensing data to evaluate leopard habitat suitability. Our analysis identifies land cover (LC), fractional vegetation cover (FVC), elevation, temperature seasonality (bio4), and distance to roads (Dist_road) as the most influential habitat predictors. Leopards exhibit a strong preference for mixed forests at elevations between 1000 and 3000 m, with a suitability index of 0.83. The study identifies several unsuitable conditions including: road proximity (<0.08 km), low elevation zones (<1000 m), areas with high temperature seasonality (bio4 > 8 °C), and non-forested land cover types. MaxEnt demonstrated superior habitat prediction accuracy over Random Forest (AUC = 0.912 vs. 0.827). The results highlight a distinct north-to-south suitability gradient, with optimal habitats concentrated in the northern districts (Muzaffarabad, Hattian, Neelum, Bagh, Haveli, Poonch, Sudhnutti) and declining suitability in human-dominated southern areas. Based on these findings, this study underscores the urgency of targeted conservation efforts in the northern districts of AJ and K, where optimal leopard habitats are identified. The findings emphasize the need for habitat connectivity and protection measures to mitigate the impacts of habitat fragmentation and climate change. Future conservation strategies should prioritize the preservation of mixed forests and the establishment of buffer zones around roads to ensure the long-term survival of the common leopard in this region. Full article

Mangrove forests, vital coastal ecosystems that provide critical biodiversity habitats and carbon sequestration services, face increasing heavy metal pollution that threatens their ecological functions through bioaccumulation and toxicity to marine organisms. However, existing studies lack dynamic insights into temporal and spatial variations of heavy metals in mangrove sediments. This study systematically analyzed two mangrove reserves in Hainan Island, China (Hainan Dongzhaigang National Nature Reserve [DZG] and Hainan Qinglan Provincial Nature Reserve [QL]), by collecting sediment samples in 2014 and 2022, analyzing metals (Cr, Cu, Zn, As, Cd, and Pb) via ICP-MS, and applying the geo-accumulation index, potential ecological risk index, Markov transition matrix, and statistical analyses. Results showed that DZG exhibited rising Cu and Zn levels but declining Cr, As, Cd, and Pb, with Cd showing the most significant decrease (66.83%). In contrast, QL saw only a 42.7% reduction in Cd, while other heavy metals increased. Spatial heterogeneity linked higher concentrations to anthropogenic hotspots, DZG’s southeast (industrial/aquaculture inputs), and QL’s northwest (urban/industrial discharges). Although ecological risks were generally low, Cd in QL reached a moderate risk level (E_Cd = 46.44, 40 ≤ E_i < 80). The large-scale pond-to-mangrove conversion significantly increased vegetation cover, which enhanced sedimentation rates and exerted a “dilution effect” on sediment heavy metals. These findings underscore anthropogenic activities as the dominant driver of heavy metal contamination. We recommend (1) stringent wastewater control near QL, (2) enhanced shipping regulation, and (3) the establishment of mangrove buffers in heavy metal accumulation zones to improve ecological status. Full article

The Soil and Water Assessment Tool (SWAT) was utilized to analyze the spatiotemporal distribution patterns of composite non-point source pollution in the Yapu Port Basin, China, and to quantify the pollutant load contributions from various sources. Scenario-based simulations were designed to assess the effectiveness of different mitigation strategies, focusing on both agricultural and urban non-point source pollution control. The watershed was divided into 39 sub-watersheds and 106 hydrologic response units (HRUs). Model calibration and validation were conducted using the observed data on runoff, total phosphorus (TP), and total nitrogen (TN). The results demonstrate good model performance, with coefficients of determination (R²) ≥ 0.85 and Nash–Sutcliffe efficiencies (NSEs) ≥ 0.84, indicating its applicability to the study area. Temporally, pollutant loads exhibited a positive correlation with precipitation, with peak values observed during the annual flood season. Spatially, pollution intensity increased from upstream to downstream, with the western region of the watershed showing higher loss intensity. Pollution was predominantly concentrated in the downstream region. Based on the composite source analysis, a series of management measures were designed targeting both agricultural and urban non-point source pollution. Among individual measures, fertilizer reduction in agricultural fields and the establishment of vegetative buffer strips demonstrated the highest effectiveness. Combined management strategies significantly enhanced pollution control, with average TN and TP load reductions of 22.18% and 22.70%, respectively. The most effective scenario combined fertilizer reduction, improved urban stormwater utilization, vegetative buffer strips, and grassed swales in both farmland and orchards, resulting in TN and TP reductions of 67.2% and 56.2%, respectively. Full article

Floating aquatic vegetation and algal blooms are increasing with global warming, potentially reducing UVB exposure and, consequently, vitamin D (vit-D) synthesis in freshwater turtles. Vit-D mediates calcium metabolism and overall health, yet the effects of floating aquatic vegetation on vit-D levels remain unclear, as is whether turtles actively avoid habitats with abundant floating vegetation. Here, we address these questions by quantifying vit-D₃ levels in the blood of adult female painted turtles (Chrysemys picta) exposed to high-vegetation (darker/colder) or clear-water (lighter/warmer) treatments for one month outdoors and one month indoors at a single temperature during late summer and early fall. The observed circulating vit-D₃ levels resembled those reported for other freshwater turtles, declined over time in both treatments, and were marginally lower under high vegetation after 60 days compared to clear water. However, this difference disappeared after correcting for lymph contamination and multiple comparisons, suggesting that perhaps adult females are robust to the effect of floating vegetation, but whether they were buffered by vit-D₃ stores in lipids is unclear. Additionally, in subsequent years, females were exposed to habitat choice experiments and exhibited a strong preference for high floating vegetation over clear water, both as a group (outdoors) and individually (outdoors, and indoors at 21 °C and 26 °C), consistent with known benefits conferred by floating vegetation (food, predator avoidance). While no ill effects of high vegetation nor behavioral avoidance were detected here, longer experiments at different seasons on both sexes and varying ages are warranted before concluding whether painted turtles are truly resilient in their vit-D levels or if, instead, a tradeoff exists between the known benefits of floating vegetation and potential [yet unidentified] detrimental effects (lower dissolved oxygen or vit-D) when vegetation is overgrown for extended periods. Full article

Drought significantly reduces global agricultural productivity and destabilizes ecosystems. As the primary grain-producing region and a key ecological buffer zone in China, Northeast China is experiencing intensifying drought stress. However, the regional-scale characteristics of refined drought and the impact mechanisms on different types of vegetation in the Northeast are rarely investigated. In this study, we analyzed the spatial and temporal characteristics of drought over 30-, 60-, 90-, 180-, 270-, and 360-day time scales in Northeast China using the Standardized Precipitation Index (SPI) based on high-precision daily precipitation data simulated by CLM3.5 from 2008 to 2023. Additionally, we used the MODIS Normalized Difference Vegetation Index (NDVI) to elucidate the response of vegetation to drought across different land use types. The results showed that SPI-30 was the most sensitive for drought detection, and there was a clear trend of drought aggravation in the northern part of the Northeast region. The strongest correlation between vegetation and drought was found in September. A significant lag in the response of vegetation to drought was observed in May, June, July, and August, with the best correlation observed at a one-month lag. In addition, the degree of response to drought varies among different types of vegetation. Grasslands are the most sensitive to drought, while woodlands and wetlands have a weaker response. This study provides a reference for assessing the dynamics of refined climates at different spatial and temporal scales and offers actionable insights for ecosystem management in climate-sensitive agricultural regions. Full article

The wildland–urban interface (WUI) has been a global phenomenon, yet parameter threshold determination remains a persistent challenge in this field. In China, a significant research gap exists in the development of WUI mapping methodology. This study proposes a novel mapping approach that delineates the WUI by integrating both vegetation and building environment perspectives. GaoFen 1 Panchromatic Multi-spectral Sensor (GF1-PMS) imagery was leveraged as the data source. Building location was extracted using object-oriented and hierarchical classification techniques, and the pixel dichotomy method was employed to estimate fractional vegetation coverage (FVC). Building location and FVC were used as input for the WUI mapping. In this methodology, the threshold of FVC was determined by incorporating the remote sensing characteristics of the WUI types, whereas the buffer range of vegetation was refined through sensitivity analysis. The proposed method demonstrated high applicability in Anning City, achieving an overall accuracy of 88.56%. The total WUI area amounted to 49,578.05 ha, accounting for 38.08% of Anning City’s entire area. Spatially, the intermix WUI was predominantly distributed in the Taiping sub-district of Anning City, while the interface WUI was mainly concentrated in the Bajie sub-district of Anning City. MODIS fire spots from 2003 to 2022 were primarily clustered in the Qinglong sub-district, Wenquan sub-district, and Caopu sub-district of Anning City. Our findings indicated a spatial overlap between the WUI and fire-prone areas in Anning City. This study presents an effective methodology for threshold determination and WUI mapping, making up for the scarcity of mapping methodologies in China. Moreover, our approach offers valuable insights for a wise decision in fire risk. Full article