Search Results (491)

Leptospirosis is a globally significant zoonosis affecting animal health, productivity, and the environment. While typically associated with tropical climates, its persistence in semi-arid regions such as La Laguna, Mexico—characterized by low humidity, high temperatures, and limited water sources—remains poorly understood. Although these adverse environmental conditions theoretically limit the survival of Leptospira, high livestock density and synanthropic reservoirs (e.g., rodents) may compensate, facilitating transmission. In this cross-sectional study, blood sera from 445 dairy cows (28 herds: 12 intensive [MI], 16 semi-intensive [MSI] systems) were analyzed via microscopic agglutination testing (MAT) against 10 pathogenic serovars. Urine samples were cultured for active Leptospira detection. Risk factors were assessed through epidemiological surveys and multivariable analysis. This study revealed an overall apparent seroprevalence of 27.0% (95% CI: 22.8–31.1), with significantly higher rates in MSI (54.1%) versus MI (12.2%) herds (p < 0.001) and an estimated true seroprevalence of 56.3% (95% CI: 50.2–62.1) in MSI and 13.1% (95% CI: 8.5–18.7) in MI herds (p < 0.001). The Sejroe serogroup was isolated from urine in both systems, confirming active circulation. In MI herds, rodent presence (OR: 3.6; 95% CI: 1.6–7.9) was identified as a risk factor for Leptospira seropositivity, while first-trimester abortions (OR:10.1; 95% CI: 4.2–24.2) were significantly associated with infection. In MSI herds, risk factors associated with Leptospira seropositivity included co-occurrence with hens (OR: 2.8; 95% CI: 1.5–5.3) and natural breeding (OR: 2.0; 95% CI: 1.1–3.9), whereas mastitis/agalactiae (OR: 2.8; 95% CI: 1.5–5.2) represented a clinical outcome associated with seropositivity. Despite semi-arid conditions, Leptospira maintains transmission in La Laguna, particularly in semi-intensive systems. The coexistence of adapted (Sejroe) and incidental serogroups underscores the need for targeted interventions, such as rodent control in MI systems and poultry management in MSI systems, to mitigate both zoonotic and economic impacts. Full article

Similarly to conventional field crops, weeds often pose significant problems in the cultivation of medicinal plants. To date, no comprehensive documentation exists regarding weed infestation levels in these crops in Serbia. The objective of this study was to provide a valuable foundation for developing effective, site-specific weed management strategies in medicinal crop production. Weeds in five medicinal crops (lemon balm, fennel, peppermint, ribwort plantain, German chamomile), were surveyed based on the agro-phytosociological method between 2019 and 2024, and across 59 plots. A total of 109 weed species were recorded, belonging to 29 families and 88 genera. Among them, 75 were annuals and 34 perennials, including 93 broadleaved species, 10 grasses, and one parasitic species. All surveyed plots were heavily infested with perennial weeds such as Elymus repens, Cirsium arvense, Convolvulus arvensis, Lepidium draba, Rumex crispus, Sorghum halepense, Taraxacum officinale, etc. Also, several annual species were found in high abundance and frequency, including Amaranthus retroflexus, Chenopodium album, Galium aparine, Lactuca serriola, Lamium amplexicaule, L. purpureum, Papaver rhoeas, Stellaria media, Veronica hederifolia, V. persica, etc. The most important ecological factors influencing the composition of weed vegetation in investigated medicinal crops were temperature and light for fennel and peppermint plots, soil reaction for lemon balm and ribwort plantain plots, and nutrient content for German chamomile plots. A perspective for exploitation of these results is the development of effective weed control programs tailored to this specific cropping system. Weed control strategies should consider such information, targeting the control of the most frequent, abundant, and dominant species existing in a crops or locality. Full article

Cultivated land quality is a key factor in ensuring sustainable agricultural development. Exploring differences in cultivated land quality under distinct cropping systems is essential for developing targeted improvement strategies. This study takes place in Shenyang City—located in the typical black soil region of Northeast China—as a case area to construct a cultivated land quality evaluation system comprising 13 indicators, including organic matter, effective soil layer thickness, and texture configuration. A minimum data set (MDS) was separately extracted for paddy and upland fields using principal component analysis (PCA) to conduct a comprehensive evaluation of cultivated land quality. Additionally, an obstacle degree model was employed to identify the limiting factors and quantify their impact. The results indicated the following. (1) Both MDSs consisted of seven indicators, among which five were common: ≥10 °C accumulated temperature, available phosphorus, arable layer thickness, irrigation capacity, and organic matter. Parent material and effective soil layer thickness were unique to paddy fields, while landform type and soil texture were unique to upland fields. (2) The cultivated land quality index (CQI) values at the sampling point level showed no significant difference between paddy (0.603) and upland (0.608) fields. However, their spatial distributions diverged significantly; paddy fields were dominated by high-grade land (Grades I and II) clustered in southern areas, whereas uplands were primarily of medium quality (Grades III and IV), with broader spatial coverage. (3) Major constraint factors for paddy fields were effective soil layer thickness (21.07%) and arable layer thickness (22.29%). For upland fields, the dominant constraints were arable layer thickness (27.57%), organic matter (25.40%), and ≥10 °C accumulated temperature (23.28%). Available phosphorus and ≥10 °C accumulated temperature were identified as shared constraint factors affecting quality classification in both systems. In summary, cultivated land quality under different cropping systems is influenced by distinct limiting factors. The construction of cropping-system-specific MDSs effectively improves the efficiency and accuracy of cultivated land quality assessment, offering theoretical and methodological support for land resource management in the black soil regions of China. Full article

Heatwaves intensified by climate change increasingly threaten urban populations, especially the elderly. However, most existing studies have concentrated on short-term or single-scale analyses, lacking a comprehensive understanding of how land cover changes and urbanization affect the vulnerability of the elderly to extreme heat. This study aims to investigate the spatiotemporal distribution patterns of heat-related health risks among the elderly in Nanchang City and to identify their key driving factors within the context of rapid urbanization. This study employs Crichton’s risk triangle framework to the heat-related health risks for the elderly in Nanchang, China, from 2002 to 2020 by integrating meteorological records, land surface temperature, land cover data, and socioeconomic indicators. The model captures the spatiotemporal dynamics of heat hazards, exposure, and vulnerability and identifies the key drivers shaping these patterns. The results show that the heat health risk index has increased significantly over time, with notably higher levels in the urban core compared to those in suburban areas. A 1% rise in impervious surface area corresponds to a 0.31–1.19 increase in the risk index, while a 1% increase in green space leads to a 0.21–1.39 reduction. Vulnerability is particularly high in economically disadvantaged, medically under-served peripheral zones. These findings highlight the need to optimize the spatial distribution of urban green space and control the expansion of impervious surfaces to mitigate urban heat risks. In high-vulnerability areas, improving infrastructure, expanding medical resources, and establishing targeted heat health monitoring and early warning systems are essential to protecting elderly populations. Overall, this study provides a comprehensive framework for assessing urban heat health risks and offers actionable insights into enhancing climate resilience and health risk management in rapidly urbanizing regions. Full article

Climate change poses a major threat to forests, impacting the distribution and viability of key species. Quercus pyrenaica Willd., a marcescent oak endemic to the Iberian Peninsula (Portugal and Spain) and southwestern France and a structural species in submediterranean forests, is particularly susceptible to shifts in temperature and precipitation patterns. Aiming to assess its potential loss of suitable area under future climate scenarios, we developed high-resolution spatial distribution models to project the future habitat suitability of Q. pyrenaica under two climate change scenarios (SSP3-7.0 and SSP5-8.5) for the periods 2070 and 2100. Our model, which has an excellent predictive performance (AUC of 0.971 and a TSS of 0.834), indicates a predominantly northward shift in the potential distribution of the species, accompanied by substantial habitat loss in southern and lowland regions. Long-term potential suitable area may shrink to 42% of that currently available. This, combined with the limited natural dispersal capacity of the species, highlights the urgency of targeted management and conservation strategies. These results offer critical insights to inform conservation strategies and forest management under ongoing climate change. Full article

Thermal camouflage technologies manipulate heat fluxes to conceal objects from thermographic detection, offering potential solutions for thermal management in high-power-density electronics. Most reported approaches are aimed at scenarios where the target is not a heat source; however, any target with a non-zero temperature emits thermal radiation described by the Stefan–Boltzmann law since the thermal radiation of an object is proportional to the fourth power of its temperature (T⁴). To address this issue, this study proposes a thermal camouflage device that considers the influence of radiative thermal transfer from the target. The underlying principle involves maintaining synchronous heat transfer separately along both the device and background surfaces. Numerical simulation confirms the feasibility of this proposed thermal camouflage strategy. Moreover, by altering some parameters related to the target such as geometry, location, temperature, and surface emissivity, excellent performance can be achieved using this device. This work advances thermal management strategies for high-power electronics and infrared-sensitive systems, with applications in infrared stealth, thermal diagnostics, and energy-efficient heat dissipation. Full article

This study aims to characterize the emissions of ammonia (NH₃) and methane (CH₄) from naturally ventilated dairy barns located in cold regions during the winter season, thereby providing a scientific basis for optimizing dairy barn environmental management. The target barn was selected at a commercial dairy farm in Ulanchab, Inner Mongolia, China. Environmental factors, including temperature, humidity, wind speed, and concentrations of NH₃, CH₄, and CO₂, were monitored both inside and outside the barn. The ventilation rate and emission rate were calculated using the CO₂ mass balance method. Additionally, NH₃ and CH₄ emission prediction models were developed using the adaptive neural fuzzy inference system (ANFIS). Correlation analyses were conducted to clarify the intrinsic links between environmental factors and NH₃ and CH₄ emissions, as well as the degree of influence of each factor on gas emissions. The ANFIS model with a Gaussian membership function (gaussmf) achieved the highest performance in predicting NH₃ emissions (R² = 0.9270), while the model with a trapezoidal membership function (trapmf) was most accurate for CH₄ emissions (R² = 0.8977). The improved ANFIS model outperformed common models, such as multilayer perceptron (MLP) and radial basis function (RBF). This study revealed the significant effects of environmental factors on NH₃ and CH₄ emissions from dairy barns in cold regions and provided reliable data support and intelligent prediction methods for realizing the precise control of gas emissions. Full article

The preservation and protection of historic urban centers in climate-sensitive coastal areas contributes to the promotion of culture as a driver and enabler of achieving temporal and spatial sustainability, as it is recognized that urban heritage is an integral part of the urban landscape, culture, and economy. The aim of this study was to enhance the resilience and protection of cultural heritage and historic urban centers (HUCs) in the coastal area of Kaštela, Croatia, by providing recommendations and action guidelines in response to climate change impacts, including rising temperatures, sea levels, storms, droughts, and flooding. Preserving HUCs is essential to maintain their cultural values, original structures, and appearance. Many ancient coastal Roman HUCs lie partially or entirely below mean sea level, while low-lying medieval castles, urban areas, and modern developments are increasingly at risk. Based on vulnerability assessments, targeted mitigation and adaptation measures were proposed to address HUC vulnerability sources. The Historical Urban Landscape Approach tool was used to transition and manage HUCs, linking past, present, and future hazard contexts to enable rational, comprehensive, and sustainable solutions. The effective protection of HUCs requires a deeper understanding of the evolution of urban development, climate dynamics, and the natural environments, including both tangible and intangible urban heritage elements. The “hazard-specific” vulnerability assessment framework, which incorporates hazard-relevant indicators of sensitivity and adaptive capacity, was a practical tool for risk reduction. This method relies on analyzing the historical performance and physical characteristics of the system, without necessitating additional simulations of transformation processes. Full article

Background/Objectives: Out-of-hospital cardiac arrest (OHCA) is associated with high mortality, and outcomes may be influenced by underlying conditions such as cancer, hypertension (HTN), and diabetes mellitus (DM). This study aimed to evaluate whether HTN and DM modify the effects of post-resuscitation treatments—specifically targeted temperature management (TTM) and percutaneous coronary intervention (PCI)—on survival and neurological recovery in OHCA patients with a history of cancer. Methods: This retrospective cohort study analyzed data from the Korean national OHCA registry between January 2018 and December 2021. Adults aged ≥18 years with presumed cardiac-origin OHCA and a documented history of cancer—defined as any prior cancer diagnosis recorded in medical records regardless of remission status—were included. Multivariable logistic regression was used to examine associations between treatment and outcomes, and interaction effects were assessed using adjusted p-values to account for multiple testing. Results: Among the 124,916 EMS-assessed OHCA cases, 4115 patients met the inclusion criteria. TTM and PCI were both statistically associated with good neurological recovery (TTM: adjusted odds ratio [aOR], 1.69; 95% confidence interval [CI], 1.12–2.55; p < 0.05; PCI: aOR, 11.35; 95% CI, 7.98–16.14; p < 0.05). In interaction analyses, the benefit of TTM and PCI for achieving good neurological recovery was attenuated in patients with diabetes mellitus (DM; TTM: aOR, 0.59; 95% CI, 0.23–1.49; PCI: aOR, 4.94; 95% CI, 2.69–9.06) and hypertension (HTN; TTM: aOR, 0.94; 95% CI, 0.49–1.82; PCI: aOR, 7.47; 95% CI, 4.48–12.44), with adjusted p-values < 0.05 for all interactions. Conclusions: In OHCA patients with a history of cancer, TTM and PCI are associated with improved survival and neurological outcomes. However, the presence of comorbidities such as HTN and DM may attenuate these benefits. These findings support the need for individualized post-resuscitation care strategies that account for comorbid conditions. Full article

Understanding the biodiversity of aquatic communities and the underlying mechanisms that shape biodiversity patterns and community dynamics is crucial for the effective conservation and management of freshwater ecosystems. However, traditional survey methods often fail to comprehensively capture species diversity, particularly for low-abundance taxa. Moreover, studies integrating both metazoan and fish communities at fine spatial scales remain limited. To address these gaps, we employed a multi-marker eDNA metabarcoding approach, targeting both the 12S and 18S rRNA gene regions, to comprehensively investigate the composition of metazoan and fish communities in the Yujiang River. A total of 12 metazoan orders were detected, encompassing 15 families, 21 genera, and 19 species. For the fish community, 32 species were identified, belonging to 25 genera, 10 families, and 7 orders. Among these, Adula falcatoides and Coptodon zillii were identified as the most prevalent and abundant metazoan and fish species, respectively. Notably, the most prevalent fish species, C. zillii and Oreochromis niloticus, are both recognized as invasive species. The Bray–Curtis distance of metazoa (average: 0.464) was significantly lower than that of fish communities (average: 0.797), suggesting higher community heterogeneity among fish assemblages. Beta-diversity decomposition indicated that variations in the metazoan and fish communities were predominantly driven by species replacement (turnover) (65.4% and 70.9% for metazoa and fish, respectively) rather than nestedness. Mantel tests further revealed that species turnover in metazoan communities was most strongly influenced by water temperature, while fish community turnover was primarily affected by water transparency, likely reflecting the physiological sensitivity of metazoans to thermal gradients and the dependence of fish on visual cues for foraging and habitat selection. In addition, a co-occurrence network of metazoan and fish species was constructed, highlighting potential predator-prey interactions between native species and Corbicula fluminea, which emerged as a potential keystone species. Overall, this study demonstrates the utility of multi-marker eDNA metabarcoding in characterizing aquatic community structures and provides new insights into the spatial dynamics and species interactions within river ecosystems. Full article

Desertification presents a significant ecological challenge in arid and semi-arid regions, posing a severe threat to regional ecological security and sustainable development. This study introduces an integrated framework for desertification vulnerability assessment, combining the MEDALUS model with the XGBoost algorithm, to evaluate desertification dynamics across the Mongolian Plateau from 2000 to 2020 and project future trends under four Shared Socioeconomic Pathways (SSPs) for 2030. The findings are as follows: (1) Between 2000 and 2020, desertification vulnerability was most pronounced in the southern and western regions of the plateau, with lower vulnerability observed in the northern and eastern areas. High-vulnerability zones expanded over time, highlighting the need for targeted and prioritized management efforts. (2) Climate factors—particularly temperature, wind speed, and precipitation—emerged as the dominant drivers of desertification, followed by soil characteristics and vegetation (NDVI). The influence of human activities on desertification became increasingly significant, stressing the need for improved land management and sustainable practices. (3) Future risks show that desertification vulnerability in the Mongolian Plateau will intensify under high-emission scenarios (SSP3-7.0, SSP5-8.5), with significant expansion of high vulnerability areas. Lower-emission scenarios (SSP1-2.6, SSP2-4.5) may reduce some impacts, but high vulnerability will persist, highlighting the need for urgent climate mitigation and adaptation efforts. Full article

Wind erosion poses a major threat to ecosystem stability and land productivity in arid and semi-arid regions. Accurate identification of its spatiotemporal dynamics and underlying driving mechanisms is a critical prerequisite for effective risk forecasting and targeted erosion control. This study applied the Revised Wind Erosion Equation (RWEQ) model to assess the spatial distribution, interannual variation, and seasonal dynamics of the Soil Wind Erosion Modulus (SWEM) across Inner Mongolia from 1990 to 2022. The GeoDetector model was further employed to quantify dominant drivers, key interactions, and high-risk zones via factor, interaction, and risk detection. The results showed that the average SWEM across the study period was 35.65 t·ha⁻¹·yr⁻¹ and showed a decreasing trend over time. However, localised increases were observed in the Horqin and Hulun Buir sandy lands and central grasslands. Wind erosion was most intense in spring (17.64 t·ha⁻¹·yr⁻¹) and weakest in summer (5.57 t·ha⁻¹·yr⁻¹). Gale days, NDVI, precipitation, and wind speed were identified as dominant drivers. Interaction detection revealed non-linear synergies between gale days and temperature (q = 0.40) and wind speed and temperature (q = 0.36), alongside a two-factor interaction between NDVI and precipitation (q = 0.19). Risk detection indicated that areas with gale days > 58, wind speed > 3.01 m/s, NDVI < 0.2, precipitation of 30.17–135.59 mm, and temperatures of 3.01–4.23 °C are highly erosion-prone. Management should prioritise these sensitive and intensifying areas by implementing site-specific strategies to enhance ecosystem resilience. Full article

Fungal melanin plays a vital role in the survival, reproduction, infection, and environmental adaptation of plant pathogenic fungi. To develop innovative strategies for managing plant fungal diseases, comprehensive investigations into melanin are imperative. Such research is fundamental to elucidating the mechanistic basis of fungal pathogenesis and holds promise for the design of targeted interventions against melanin-mediated virulence determinants. This review systematically elaborates on the classification of fungal melanin in plant pathogens, provides a detailed analysis of the biosynthetic processes of 3,4-dihydroxyphenylalanine (DOPA) and 1,8-dihydroxynaphthalene melanin (DHN melanins), and reveals the catalytic functions and regulatory mechanisms of key enzymes within these pathways. Melanin modulates fungal virulence by influencing appressorial integrity and turgor pressure formation, thereby participating in the host infection process and the formation of overwintering sclerotia. Melanin provides stress resistance by protecting against extreme environmental factors, including UV radiation and high temperatures. It also has the capacity to absorb heavy metals, which increases pathogen survival under adverse conditions. Furthermore, the review also explores the mechanisms of action of melanin inhibitors that target plant pathogenic fungi, providing a theoretical foundation for developing efficient and environmentally friendly antifungal medications. The complex biosynthesis pathways and diverse biological functions of fungal melanin highlight its significant theoretical and practical importance for elucidating pathogenic mechanisms and formulating scientific control strategies. Full article

Heortia vitessoides Moore (Lepidoptera: Pyralidae), the dominant outbreak defoliator of Aquilaria sinensis (Myrtales: Thymelaeaceae, the agarwood-producing tree), poses a severe threat to the sustainable development of the agarwood industry. Current research has preliminarily revealed its biological traits and gene functions. However, significant gaps persist in integrating climate adaptation mechanisms, control technologies, and host interaction networks across disciplines. This review systematically synthesizes the multidimensional mechanisms underlying H. vitessoides outbreaks through the logical framework of “Fundamental Biology of Outbreaks—Environmental Drivers—Control Strategies—Molecular Regulation—Host Defense.” First, we integrate the biological characteristics of H. vitessoides with its climatic response patterns, elucidating the ecological pathways through which temperature and humidity drive population outbreaks by regulating development duration and host resource availability. Subsequently, we assess the efficacy and limitations of existing control techniques (e.g., pheromone trapping, Beauveria bassiana application), highlighting the critical bottleneck of insufficient mechanistic understanding at the molecular level. Building on this, we delve into the molecular adaptation mechanisms of H. vitessoides. Specifically, detoxification genes (e.g., HvGSTs1) and temperature stress-responsive genes (e.g., HvCAT, HvGP) synergistically enhance stress tolerance, while chemosensory genes mediate mating and host location behaviors. Concurrently, we reveal the host defense strategy of A. sinensis, involving activation of secondary metabolite defenses via the jasmonic acid signaling pathway and emission of volatile organic compounds that attract natural enemies—an “induced resistance–natural enemy collaboration” mechanism. Finally, we propose future research directions: deep integration of gene editing to validate key targets, multi-omics analysis to decipher the host–pest–natural enemy interaction network, and development of climate–gene–population dynamics models. These approaches aim to achieve precision control by bridging molecular mechanisms with environmental regulation. This review not only provides innovative pathways for managing H. vitessoides but also establishes a paradigm for cross-scale research on pests affecting high-value economic forests. Full article

Efficient management of groundwater resources is essential for environmental sustainability. This study introduces the development and application of a digital twin (DT) for confined aquifers to optimise water extraction and ensure long-term sustainability. A resilience-based control model was implemented to manage the Morroa Aquifer (Colombia). This model integrated historical, hydrogeological, and climatic data acquired from in-situ sensors and satellite remote sensing. Several heuristic methods were employed to optimise the parameters of the objective function, which focused on managing water extraction in aquifer wells: grid search, genetic algorithms (GA), and particle swarm optimisation (PSO). The results indicated that the PSO algorithm yielded the lowest root mean square error (RMSE), achieving an optimal extraction rate of 8.3 l/s to maintain a target dynamic water level of 58.5 m. Furthermore, the model demonstrated the unsustainability of current extraction rates, even under high-rainfall conditions, highlighting the necessity for revising existing water extraction strategies to safeguard aquifer sustainability. To showcase its practical functionality, a DT prototype was deployed in a well within the Morroa piezometric network (Sucre, Colombia). This prototype utilised an ESP32 microcontroller and various sensors (DS18B20, SKU-SEN0161, SKU-DFR0300, SEN0237-A) to monitor water level, pH, dissolved oxygen, and temperature. The implementation of this DT proved to be a crucial tool for the efficient management of water resources. The proposed methodology provided key information to support decision-making by environmental management entities, thereby optimising monitoring and control processes. Full article