Search Results (685)

The process of urbanization has intensified the urban heat environment, with the degradation of thermal conditions closely linked to the morphological characteristics of different functional zones. This study delineated urban functional areas using a multivariate dataset and investigated the seasonal and threshold effects of landscape and architectural features on land surface temperature (LST) through boosted regression tree (BRT) modeling and Spearman correlation analysis. The key findings are as follows: (1) LST exhibits significant seasonal variation, with the strongest urban heat island effect occurring in summer, particularly within industry, business, and public service zones; residence zones experience the greatest temperature fluctuations, with a seasonal difference of 24.71 °C between spring and summer and a peak temperature of 50.18 °C in summer. (2) Fractional vegetation cover (FVC) consistently demonstrates the most pronounced cooling effect across all zones and seasons. Landscape indicators generally dominate the regulation of LST, with their relative contribution exceeding 45% in green land zones. (3) Population density (PD) exerts a significant, seasonally dependent dual effect on LST, where strategic population distribution can effectively mitigate extreme heat events. (4) Mean building height (MBH) plays a vital role in temperature regulation, showing a marked cooling influence particularly in residence and business zones. Both the perimeter-to-area ratio (LSI) and frontal area index (FAI) exhibit distinct seasonal variations in their impacts on LST. (5) This study establishes specific indicator thresholds to optimize thermal comfort across five functional zones; for instance, FVC should exceed 13% in spring and 31.6% in summer in residence zones to enhance comfort, while maintaining MBH above 24 m further aids temperature regulation. These findings offer a scientific foundation for mitigating urban heat waves and advancing sustainable urban development. Full article

Elaeocarpus sylvestris (Lour.) Poir. var. ellipticus (Thunb.) H.Hara, an evergreen tree species native to Jeju Island, South Korea, has experienced a progressive decline associated with phytoplasma infection. This study aimed to evaluate the efficacy of oxytetracycline-based tree injection for suppressing phytoplasma and improving tree vitality. Two formulations—oxytetracycline hydrochloride (4.3%) and oxytetracycline calcium alkyltrimethyl ammonium (17%)—were administered to 40 infected individuals across two sites using a gravity-fed injection system. Treatment efficacy was evaluated based on chlorophyll content as an indicator of physiological recovery, while phytoplasma presence was assessed by PCR at 150 days after injection. The oxytetracycline hydrochloride group showed the highest suppression, with a 70% phytoplasma non-detection rate as determined by PCR analysis. Treated trees exhibited significantly higher chlorophyll content compared to untreated infected controls. These findings suggest that minimally invasive tree injection using oxytetracycline can provide temporary suppression of phytoplasma and support physiological recovery in E. sylvestris. Full article

Background: Salmonella is a bacterium that causes foodborne infections. This study characterized two strains isolated from cheese and beef in Brazil using whole-genome sequencing (WGS). Objectives: We evaluated their antimicrobial resistance profiles, virulence factors, plasmid content, serotypes and phylogenetic relationships. Methods: DNA was extracted and sequenced on the NovaSeq 6000 platform; the pangenome was assembled using the Roary tool; and the phylogenetic tree was constructed via IQ-TREE. Results and Discussion: For contextualization and comparison, 3493 Salmonella genomes of Brazilian origin from NCBI were analyzed. In our isolates, both strains carried the aac(6′)-Iaa_1 gene, while only Schwarzengrund harbored the qnrB19_1 gene and the Col440I_1 plasmid. Cerro presented the islands SPI-1, SPI-2, SPI-3, SPI-4, SPI-5 and SPI-9, while Schwarzengrund also possessed SPI-13 and SPI-14. Upon comparison with other Brazilian genomes, we observed that Cerro and Schwarzengrund represented only 0.40% and 2.03% of the national database, respectively. Furthermore, they revealed that Schwarzengrund presented higher levels of antimicrobial resistance, a finding supported by the higher frequency of plasmids in this serovar. Furthermore, national data corroborated our findings that SPI-13 and SPI-14 were absent in Cerro. A virulence analysis revealed distinct profiles: the cdtB and pltABC genes were present in the Schwarzengrund isolates, while the sseK and tldE1 family genes were exclusive to Cerro. The results indicated that the sequenced strains have pathogenic potential but exhibit low levels of antimicrobial resistance compared to national data. The greater diversity of SPIs in Schwarzengrund explains their prevalence and higher virulence potential. Conclusions: Finally, the serovars exhibit distinct virulence profiles, which results in different clinical outcomes. Full article

The koala (Phascolarctos cinereus) is recognised as threatened across two thirds of its distribution and identified as particularly susceptible to climate change. The aim of this study was to assess the spatio-temporal variation in microclimate across koala home ranges and determine any tendency for koalas to exploit this variability. Temperature data loggers were set out in a grid pattern across the study site on St Bees Island, Queensland. Resident koalas were collared with GPS units recording location at night or during the day. Our results revealed that temperature variation across the landscape was greatest on the hottest days (~10 °C). During the day, koalas were found in areas of the landscape that recorded lower daytime temperatures, and during the night, they were found in areas that recorded the highest daytime temperatures. We postulate that koalas avoided the hottest areas of their range during summer days and were more likely to use cooler non-fodder trees but utilised them at night because these areas corresponded with the location of fodder trees. From our results, we suggest that the microclimate of non-fodder trees both (a) explains their selection by koalas during the day and (b) highlights their importance to koala persistence, in addition to the known fodder species. Full article

Amman’s rapid population growth and sprawling urbanization have resulted in car-centric, fragmented neighborhoods that lack social cohesion and are vulnerable to the impacts of climate change. This study reframes walkability as a climate adaptation strategy, demonstrating how pedestrian-oriented spatial planning can reduce vehicle emissions, mitigate urban heat island effects, and enhance the resilience of green infrastructure in peri-urban contexts. Using Deir Ghbar, a rapidly developing marginal area on Amman’s western edge, as a case study, we combine objective walkability metrics (street connectivity and residential and retail density) with GIS-based spatial regression analysis to examine relationships with residents’ sense of community. Employing a quantitative, correlational research design, we assess walkability using a composite objective walkability index, calculated from the land-use mix, street connectivity, retail density, and residential density. Our results reveal that higher residential density and improved street connectivity significantly strengthen social cohesion, whereas low-density zones reinforce spatial and socioeconomic disparities. Furthermore, the findings highlight the potential of targeted green infrastructure interventions, such as continuous street tree canopies and permeable pavements, to enhance pedestrian comfort and urban ecological functions. By visualizing spatial patterns and correlating built-environment attributes with community outcomes, this research provides actionable insights for policymakers and urban planners. These strategies contribute directly to several Sustainable Development Goals (SDGs), particularly SDG 11 (Sustainable Cities and Communities) and SDG 13 (Climate Action), by fostering more inclusive, connected, and climate-resilient neighborhoods. Deir Ghbar emerges as a model for scalable, GIS-driven spatial planning in rural and marginal peri-urban areas throughout Jordan and similar regions facing accelerated urban transitions. By correlating walkability metrics with community outcomes, this study operationalizes SDGs 11 and 13, offering a replicable framework for climate-resilient urban planning in arid regions. Full article

The diffusion effect of river cooling is critical for mitigating the urban heat island effect in riverside areas and for establishing an urban cooling network. River cooling effect diffusion is influenced by the two-dimensional (2D) and three-dimensional (3D) urban morphology of surrounding areas. However, the characteristics of 2D/3D urban morphology that facilitate efficient river cooling effect diffusion remain unclear. This study establishes a technical framework to analyze river cooling effect diffusion resistance (RCDR) across different urban morphologies, using the Huangpu River waterside area in Shanghai as a case study. Seven urban morphology indicators, derived from both 2D and 3D dimensions, were developed to characterize the river cooling effect diffusion resistance. The relative contributions and marginal effects were analyzed using the Boosted Regression Tree (BRT) model. The study found that (1) river cooling effect diffusion was heterogeneous, with four typical patterns; (2) the Landscape Shape Index (LSI) and Blue-green Space Ratio (BGR) significantly impacted cooling effect diffusion; and (3) optimal cooling effect diffusion occurred when the blue-green space occupancy ratio exceeded 20% and building density ranged from 0.1 to 0.3. This study’s technical framework offers a new perspective on river cooling effect diffusion and heat island mitigation in riverside spaces, with significant practical value and potential for broader application. Full article

Due to the potential role of Auchenorrhyncha in the transmission of the bacterium Xylella fastidiosa in a wide variety of cultivations, during recent years in Europe, many studies have focused on species composition, abundance and seasonal appearance of Auchenorrhyncha. However, females and nymphs are difficult to identify, as species-level identification relies primarily on male genitalia morphology. Sampling was conducted over four years in olive fields in Lesvos Island, in the Northeast Aegean, Greece, using sweep nets and Malaise traps. Both adults and nymphs were collected, with males identified to species level, while females and nymphs were separated on different morphotypes. Representatives from each morphotype and identified adults were sequenced using the mitochondrial cytochrome oxidase subunit I (COI) gene. Using a classical morphological approach, 58 species were identified to species level, and using DNA barcoding, nymph morphotypes and females were successfully identified within the families Cicadellidae, Aphrophoridae, Delphacidae and Issidae. A phylogenetic tree was generated, clustering nymphs together with the corresponding adults. Our results demonstrate the utility of combining morphological and molecular methods for accurate species identification and highlight the importance of enriching online databases with additional species records. Full article

Accurate short-term forecasting of photovoltaic power generation is vital for the operational stability of isolated energy systems, especially in regions with increasing renewable energy penetration. This study presents a novel AI-based forecasting framework applied to the island of Cyprus. Using machine learning methods, particularly regression trees, the proposed approach evaluates the impact of key environmental variables on PV performance, with an emphasis on atmospheric dust transport and air composition variability. A distinguishing feature of this work is the integration of cross-continental dust events and diverse atmospheric parameters into a structured forecasting model. A new clustering methodology is introduced to classify these inputs and analyze their correlation with PV output, enabling improved feature selection for model training. Importantly, all input parameters are sourced from publicly accessible, internet-based platforms, facilitating wide reproducibility and operational application. The obtained results demonstrate that incorporating dust deposition and air composition features significantly enhances forecasting accuracy, particularly during severe dust episodes. This research not only fills a notable gap in the PV forecasting literature but also provides a scalable model for other dust-prone regions transitioning to high levels of solar energy integration. Full article

Rubber Tree (Hevea brasiliensis) phenology critically influences tropical plantation productivity and carbon cycling, yet topography and climate impacts remain unclear. By integrating multi-sensor remote sensing (2001–2020) and Google Earth Engine, this study analyzed spatiotemporal dynamics in Hainan Island, China. Results reveal that both the start (SOS occurred between early and late March: day of year, DOY 60–81) and end (EOS occurred late January to early February: DOY 392–406, counted from the previous year) of the growing season exhibit progressive delays from the southeast to northwest, yielding a 10–11 month growing season length (LOS). Significantly, LOS extended by 4.9 days per decade (p < 0.01), despite no significant trends in SOS advancement (−1.1 days per decade) or EOS delay (+3.7 days per decade). Topographic modulation was evident: the SOS was delayed by 0.27 days per 100 m elevation rise (p < 0.01), while the EOS was delayed by 0.07 days per 1° slope increase (p < 0.01). Climatically, a 100 mm precipitation increase advanced SOS/EOS by approximately 1.0 day (p < 0.05), preseasonally, a 1 °C February temperature rise advanced the SOS and EOS by 0.49 and 0.53 days, respectively, and a 100 mm January precipitation increase accelerated EOS by 2.7 days (p < 0.01). These findings advance our mechanistic understanding of rubber phenological responses to climate and topographic gradients, providing actionable insights for sustainable plantation management and tropical forest ecosystem adaptation under changing climatic conditions. Full article

Ponderosa pine (Pinus ponderosa Lawson & C. Lawson) forests in the western United States have experienced reduced fire frequency since Euro-American settlement, usually because of successful fire suppression policies and even without such human impacts at remote sites in the Great Basin and Mojave Deserts. In an effort to improve our understanding of long-term environmental dynamics in sky-island ecosystems, we developed tree-ring chronologies from ponderosa pines located in the Sheep Mountain Range of southern Nevada, inside the Desert National Wildlife Refuge (DNWR). After comparing those dendrochronological records with other ones available for the south-central Great Basin, we analyzed their climatic response using station-recorded monthly precipitation and air temperature data from 1950 to 2024. The main climatic signal was December through May total precipitation, which was then reconstructed at annual resolution over the past five centuries, from 1490 to 2011 CE. The mean episode duration was 2.6 years, and the maximum drought duration was 11 years (1924–1934; the “Dust Bowl” period), while the longest episode, 19 years (1905–1923), is known throughout North America as the “early 1900s pluvial”. By quantifying multi-annual dry and wet episodes, the period since DNWR establishment was placed in a long-term dendroclimatic framework, allowing us to estimate the potential drought resilience of its unique, tree-dominated environments. Full article

Due to rising temperatures, energy use, and thermal discomfort, urban heat islands (UHIs) pose a serious environmental threat to urban sustainability. This systematic review synthesizes peer-reviewed literature on various forms of green infrastructure and their mechanisms for mitigating UHI effects, and the function of urban green spaces (UGSs) in reducing the impact of UHI. In connection with urban parks, green roofs, street trees, vertical greenery systems, and community gardens, important mechanisms, including shade, evapotranspiration, albedo change, and ventilation, are investigated. This study emphasizes how well these strategies work to lower city temperatures, enhance air quality, and encourage thermal comfort. For instance, the findings show that green areas, including parks, green roofs, and street trees, can lower air and surface temperatures by as much as 5 °C. However, the efficiency of cooling varies depending on plant density and spatial distribution. While green roofs and vertical greenery systems offer localized cooling in high-density urban settings, urban forests and green corridors offer thermal benefits on a larger scale. To maximize their cooling capacity and improve urban resilience to climate change, the assessment emphasizes the necessity of integrating UGS solutions into urban planning. To improve the implementation and efficacy of green spaces, future research should concentrate on policy frameworks and cutting-edge technology such as remote sensing. Full article

Urban blue–green space (UBGS) plays a critical role in mitigating the urban heat island (UHI) effect and reducing land surface temperatures (LSTs). However, existing research has not sufficiently explored the optimization of UBGS spatial configurations or their interactions with urban morphology. This study takes New York City as a case and systematically investigates small-scale urban cooling strategies by integrating multiple factors, including adjustments to the blue–green ratio, spatial layouts, vegetation composition, building density, building height, and layout typologies. We utilize multi-source geographic data, including LiDAR derived land cover, OpenStreetMap data, and building footprint data, together with LST data retrieved from Landsat imagery, to develop a prediction model based on generative adversarial networks (GANs). This model can rapidly generate visual LST predictions under various configuration scenarios. This study employs a combination of qualitative and quantitative metrics to evaluate the performance of different model stages, selecting the most accurate model as the final experimental framework. Furthermore, the experimental design strictly controls the study area and pixel allocation, combining manual and automated methods to ensure the comparability of different ratio configurations. The main findings indicate that a blue–green ratio of 3:7 maximizes cooling efficiency; a shrub-to-tree coverage ratio of 2:8 performs best, with tree-dominated configurations outperforming shrub-dominated ones; concentrated linear layouts achieve up to a 10.01% cooling effect; and taller buildings exhibit significantly stronger UBGS cooling performance, with super-tall areas achieving cooling effects approximately 31 percentage points higher than low-rise areas. Courtyard layouts enhance airflow and synergistic cooling effects, whereas compact designs limit the cooling potential of UBGS. This study proposes an innovative application of GANs to address a key research gap in the quantitative optimization of UBGS configurations and provides a methodological reference for sustainable microclimate planning at the neighborhood scale. Full article

Leaf litter traits among tree species exert a direct influence on spatiotemporal nutrient turnover and an indirect influence by shifting the decomposition dynamics of leaf litter mixtures including other sympatric species. Cycas micronesica and Serianthes nelsonii are two Mariana Island tree species that are endangered, and developing a greater understanding of the influence of these trees on biogeochemistry may improve information-based conservation decisions. The objectives of this study were to quantify the influence of mixing the leaf litter of these species with 12 sympatric forest plants to determine the additive and nonadditive influences on decomposition. The C. micronesica litter was collectively antagonistic when litter mixtures were incubated in a mesocosm study and a field litterbag study, and the response was similar among the included species. The S. nelsonii litter was collectively synergistic among the same mixed species, and the response was dissimilar among the included species. The contributions of these two threatened tree species to spatiotemporal diversity in biogeochemistry are dissimilar and considerable. These findings indicate that species recovery efforts for these two species are of paramount importance for maintaining Mariana Island ecological integrity and native biodiversity by sustaining their contributions to ecosystem services. Full article

Wildfires are integral to many forest ecosystems, yet their ecological effects are often influenced by historical land use and management. In this study, we assess the short-term impacts of fire and management on Castanea sativa Mill. stands in the fayal-brezal zone of northern Tenerife (Canary Islands), where traditional agroforestry systems have been widely abandoned. We established 12 transects across four stands: managed-burned, managed-unburned, oldfield-burned, and oldfield-unburned. We analyzed forest structure, understory species richness and composition, and soil nutrient content one year after a large wildfire. Forest structure has primarily been determined by management history, with oldfield plots showing greater tree density, basal area, and basal sprouting. Fire has had a limited effect on tree mortality, affecting ~10% of individuals on average. Understory species richness was significantly higher in managed plots, particularly those affected by fire, suggesting a positive interaction between disturbance and management. Species composition differed significantly among treatments, with Indicator Species Analysis identifying distinct taxa associated with each condition. Fire in oldfield plots led to increased compositional similarity with managed stands, indicating fire’s potential homogenizing effect. Principal Component Analysis of soil nutrients did not reveal clear treatment-related patterns, which was probably due to microenvironmental variability and the short post-fire interval. Overall, our results highlight the dominant role of land-use legacy in structuring these forests, with fire acting as a secondary but influential driver, revealing significant changes in species composition as well as in species richness. These findings have direct relevance for conservation and restoration strategies as well as for maintenance in these stands of Castanea sativa. They should also encourage managers of these protected areas, where land abandonment and fire are increasingly shaping forest dynamics. Full article

As important urban green spaces, rivers enhance cooling island effects significantly by leveraging environmental factors. This study selected Suzhou River in Shanghai as the subject to explore how to improve blue–green–gray infrastructure to optimize the river cooling island effect on the riparian zone for outdoor activities in summer. A total of 77 samples, including 36 control groups and 41 experimental groups, were categorized into 12 types of blue–green–gray infrastructure composite features. ENVI-met was used to simulate summer thermal comfort, while redundancy analysis and boosted regression trees were used to identify significant factors and thresholds influencing the river’s cooling island effect. The results showed that for Suzhou River, the green–blue–green–gray–green composition most effectively optimizes the river cooling island effect. It is recommended to select construction sites where the river width is 55 m and the percentage of green infrastructure exceeds 40% and keep the distance between green infrastructure and the water body to within 3 m. Additionally, limiting gray infrastructure to less than 10%, with an average building height of 37 m and a building undulation of 25 m, is recommended to achieve the optimal cooling effect. This study finally proposes optimization strategies to maximize the cooling island effect of urban rivers, offering insights for the development of climate-adaptive urban riparian zones. Full article