Search Results (1,019)

Wildlife health surveillance is a vital element of disease prevention, biodiversity conservation, and public health protection, especially as most emerging infectious diseases originate from wildlife. In Slovenia, long-term passive surveillance based on necropsy data has yielded valuable insights into wildlife mortality patterns over the past three decades, despite inherent limitations such as carcass detectability, reporting bias, scavenging, and decomposition. Ongoing cooperation among governmental institutions, veterinary services, hunters, and wildlife management organisations has enabled the effective operation of this system, although passive surveillance remains subject to spatial, temporal, and species-specific biases. Necropsy data show that infectious diseases, particularly parasitic infections, are the main causes of mortality in key species such as roe deer and chamois, reflecting both their population abundance and targeted monitoring. In contrast, carcasses of species such as wild boar, red deer, small mammals, and birds are underrepresented due to ecological factors, biosecurity constraints, or low detectability. Overall, while passive wildlife surveillance does not provide representative population-level mortality estimates, it remains a reliable tool for identifying the presence or absence of significant diseases and for understanding broad mortality patterns when interpreted in the context of known methodological and ecological limitations. Full article

Human activities and climate change are influencing the survival and distribution of species, threatening the current distribution pattern of biodiversity and potentially leading to the “sixth mass extinction.” The forest musk deer (Moschus berezovskii) is among the most numerous and widely distributed musk deer species in China. However, its habitat is severely threatened by human activities and climate change. Due to the lack of field surveys and research data, it is difficult to assess the threats posed by human activities and climate change effectively. In this study, we integrate the new records of forest musk deer with climate and human activity data, and apply the MaxEnt species distribution model to evaluate the impact of human activities and climate change on the forest musk deer under current conditions and future scenarios (SSP1-2.6 and SSP5-8.5 for the 2030s, 2050s, and 2070s). Our results showed that the forest musk deer prefer areas with high vegetation cover (NDVI > 0.7), low GDP, and low levels of human activity disturbance. The areas of high-suitability habitats are 90.10 × 10⁴ km², 72.85 × 10⁴ km², and 30.43 × 10⁴ km², respectively. The optimal climatic conditions are an annual precipitation (BIO12) of 750–1500 mm and a seasonal temperature variation (BIO4) of 500–600. Their occurrence probability is highest at elevations between 1500 and 3000 m. Under the current climate conditions, the area of high-suitability habitats is estimated at 5.54 × 10⁴ km², primarily distributed across central–northern Sichuan, northwestern Guangxi, and southern Gansu. Under the future climate scenarios, low and medium-suitability habitats are projected to shrink to varying degrees, whereas the high-suitability area is expected to expand, particularly under the SSP5-8.5-2030s scenario where it is projected to increase by 2.88 × 10⁴ km². The centroid of suitable habitat is projected to shift toward higher-elevation areas in northwestern China, with regional hotspots emerging in southwestern regions such as central–northern Sichuan and northwestern Guangxi. These elevational and distributional shifts highlight the vulnerability of current habitats and the importance of adaptive conservation strategies to strengthen species protection, including continuously advancing forest protection programs, mitigating the impact of human activities in high-altitude areas, and strengthening the protection of key areas in the southwestern region. Full article

This study examines the dynamics of aridity in Mexico in relation to El Niño–Southern Oscillation (ENSO) phases (El Niño, La Niña and neutral conditions) between 1999 and 2024. The aim is to identify ecosystems that are exposed to emerging aridification. Aridity was estimated using the Lang index at a resolution of 1 km across nearly two million grid cells. Aridity intensity and long-term trends were calculated and analysed by ENSO phase to identify areas of double exposure. Over 60% of Mexico is classified as arid or semi-arid. During El Niño, up to 100% of the central and southern regions exhibit increased aridity, affecting an area of 290,852 km² (14.7%), where both the intensity and the trend are high. Although La Niña typically brings wetter conditions, 150,022 km² (7.6%) still exhibit increasing aridity. Areas exposed to aridity under both ENSO phases cover 16,224 km² (0.8%), particularly affecting cloud forests, secondary vegetation and agricultural landscapes. This suggests a process of persistent aridification. The average arid area was 64% ± 7.51% during El Niño, 67% ± 1.44% during La Niña and 64% ± 8.14% during neutral years, indicating substantial variability beyond phase dependence. These findings reveal a complex, non-linear ENSO influence and suggest chronic hydroclimatic stress in some regions. Understanding which ecosystems experience recurrent aridity is crucial for effective water management, biodiversity conservation, and climate adaptation planning. Full article

Peatlands cover approximately 10% (640,000 ha) of Latvia’s territory, of which about 51,000 ha is officially classified as degraded due to peat extraction and related activities. This study assesses the current status of peat extraction site recultivation in Latvia and evaluates future after-use requirements under contrasting policy pathways using a review of scientific literature, project reports, national statistics, and updated peat extraction licence records. A simple allocation model was applied to estimate recultivation trajectories for the nationally defined degraded peatland area under two scenarios: (i) a licence-expiry baseline scenario and (ii) an accelerated immediate-stop-peat-mining scenario. The results show that full recultivation would require average annual efforts of approximately 1500 ha yr⁻¹ under the baseline scenario and around 2000 ha yr⁻¹ under the accelerated scenario. Although European Union-funded projects and corporate initiatives have demonstrated the potential of rewetting, paludiculture, and renewable energy integration, only a limited number of sites have been officially recognised as fully recultivated or restored. Because ecological recovery of peatland functions may take decades, administrative closure alone does not guarantee climate or biodiversity benefits. A phased recultivation strategy linked to licence expiry and prioritising degraded and self-regenerating sites emerges as the most pragmatic pathway for Latvia, balancing European Union climate objectives, institutional capacity, and socio-economic constraints. Full article

Oil spills represent a severe environmental hazard, threatening marine and coastal ecosystems, biodiversity, and socio-economic stability. Timely and accurate detection of such incidents is critical for mitigating their ecological and economic consequences. Conventional detection techniques, including manual inspection and satellite-based observation, remain limited by high operational costs, temporal delays, and restricted spatial coverage. To overcome these limitations, this study introduces a comprehensive computer vision framework that addresses two core challenges: (i) the construction of a large-scale, high-quality synthetic oil spill dataset through mask extraction and seamless blending of oil spill regions with diverse oceanic backgrounds, and (ii) the development of a fine-tuned YOLOv11m-seg detection model trained on this enriched dataset. To further enhance the realism and spatial distinctiveness of oil spill textures, the Line Integral Convolution (LIC) is applied to estimate and visualize ocean surface flow patterns, generating coherent streamline textures that simulate the natural diffusion and transport of oil in water. The model exhibited strong generalization and precision, achieving a training accuracy exceeding IoU@0.50-0.95 to 85% over 50 epochs. Evaluation metrics confirmed its reliability, with an F1 score of 94%, precision of 94%, and recall (mAP@0.50) of 94%. These results demonstrate that the developed approach not only enhances dataset diversity but also substantially improves the accuracy and representativeness of real-time oil spill detection in marine environments. Full article

Previously, the role of decreased biodiversity of gut microbiota in polycystic ovary syndrome (PCOS) was demonstrated, but the objective criteria for assessing the representation of microorganisms associated with hyperandrogenemia (HA) were limited. A total of 175 premenopausal women (26 women with PCOS and HA and 149 women without HA, including 19 healthy controls) were recruited during the Eastern Siberia PCOS Epidemiology and Phenotype (ESPEP) Study (2016–2019). Methods included a questionnaire survey, clinical examination, pelvic U/S, blood and feces sampling. Gut microbiome was analyzed by high-throughput sequencing of the V1–V3 of the variable regions of the 16S rRNA gene (Illumina MiSeq, San Diego, CA, USA). Amplicon libraries of 16S rDNA were processed using the QIIME2 bioinformatics pipeline. All data were analyzed using R 3.6.3. The gut microbiocenosis in women with HA was characterized by a higher representation of Lactobacillus and a lower prevalence of the Clostridia class. For Faecalibacterium, Christensenellaceae_R-7_group, and [Eubacterium] eligens group the cut-off values of their relative presence, associated with HA, were estimated as: ≤0.043%, ≤0.039%, and ≤0.02%, respectively. Conclusions: Women with PCOS-associated HA demonstrate a lower prevalence, predominantly, of Clostridia class gut microorganisms, compared with those without any forms of HA. The study presents the quantitative criteria for assessing the representation of gut microorganisms, negatively associated with hyperandrogenic phenotypes of PCOS. The threshold values proposed may be useful to justify the administration of probiotics in PCOS patients with HA. Full article

Oyamel forest, Abies religiosa (Kunth) Schltdl. et Cham., is a high-mountain ecosystem that contains abundant biodiversity, contributes to supporting traditional medicine, and represents a reservoir of medicinal plants. Despite this medicinal relevance, the potential of the flora of the Mexican Oyamel forest from Santuario del Agua Presa Corral de Piedra (SAPCP), Mexico, has been scarcely studied. This review focused on identifying the flora of the SAPCP which has been reported as medicinal resource in the literature through the recovery of ethnomedicinal uses and their proven pharmacological effects. In addition, phytochemical reports of the SAPCP medicinal flora and their pharmacological activities were integrated and analyzed to estimate their medicinal potential. The results showed that the SAPCP forest represents an important source of medicinal plants, with 39% of the total species reporting at least one ethnomedicinal use belonging to different taxonomic families, but mainly included Asteraceae, Lamiaceae, Rosaceae, and Solanaceae. The most commonly observed ethnomedicinal uses among all the species were against inflammation, infections, diarrhea, and diabetes, while antioxidant, antidiabetic, and anti-inflammatory effects were predominantly proven as pharmacological effects. The phytochemical results revealed a great diversity of secondary metabolites, although flavonoids, phenolic acids, and triterpenes were observed in a major number of species, many of which have been proven to exert anti-inflammatory, antidiabetic, and antibacterial effects through several action mechanisms. In conclusion, these results highlight the importance of sustainable management and the conservation of forest species, as they provide a reservoir of medicinal species that produce bioactive metabolites. Full article

The Balkan Peninsula is a biodiversity hotspot where topographic and habitat heterogeneity have shaped genetic differentiation. Polyploidization significantly contributes to diversification within plant lineages, including the allopolyploid complex of the Austrian speedwell, which comprises diploid, tetraploid and hexaploid lineages. We sampled 751 individuals from 50 populations belonging to this complex across the Balkan Peninsula and Central Europe. Diversity patterns were investigated through microsatellite markers (SSRs), plastid DNA sequences, ploidy estimations, morphological data and climatic niche differentiation analysis. Five lineages were detected within the complex according to nuclear DNA data. The plastid DNA haplotypes form two main groups that overall match those detected by SSR data and could suggest that the hexaploid lineage resulted from two different allopolyploid events. The hexaploid shows higher nuclear genetic diversity and morphological variation than its lower-ploidy relatives, which might allow the species to respond to a wider range of environmental conditions and be responsible for its success (i.e., a broader geographic range and ecological niche). Style length is a crucial character to distinguish diploids from polyploids, which may affect pollination biology within the complex. Full article

The Tibetan Plateau (TP) experienced significant climatic transitions and tectonic uplift during the Middle Miocene. Little is known about plant diversity changes and their relationship with climatic and tectonic processes in spite of extensive reconstructions of vegetation change over this period. Based on palynological assemblages spanning ~15–12 Ma from the Lunpola Basin, we quantitatively reconstruct the evolution of plant diversity around the Middle Miocene Climatic Transition (MMCT) in the central TP. Plant taxa richness and evenness of three groups of tree, shrub and herb, and pteridophyte are estimated using Hill numbers methods. Three distinct diversity phases are identified. From ~15 to 14.2 Ma, plant richness gradually increased while evenness decreased, possibly due to the development of vertical vegetation zones driven by the uplift of the central TP. From ~14.2 to 13.8 Ma, richness dropped sharply in response to rapid climatic deterioration in the MMCT. From ~13.8 to 12 Ma, both richness and evenness increased under fluctuations, associated with paleo-lake shrinkage and expansion of lakeside wetlands caused by persistent plateau uplift and climatic aridification. Long-term changes in plant diversity within the Lunpola Basin were influenced by global climate changes, the uplift of central TP, and regional hydrological dynamics during the Middle Miocene. Our findings provide paleoecological insights into the coevolution of TP growth, climate change, hydrological process, and biodiversity of alpine ecosystem. Full article

Air quality improvement represents a critical challenge for the European Union, with particulate matter (PM) being the most harmful pollutant in urban areas. Urban Green Infrastructures (UGIs) provide essential ecosystem services that mitigate air pollution, notably through PM₁₀ removal via deposition on leaf surfaces, reducing health risks associated with poor air quality. This study quantifies the PM₁₀ removal supplied by urban forests in the Bydgoszcz–Toruń area (Poland) using a spatially explicit modeling framework. Remotely sensed Leaf Area Index, vegetation cover, and PM₁₀ concentration data were integrated within a GIS environment, with all analyses conducted on a seasonal basis to capture temporal variability in vegetation phenology and pollutant levels. Resulting maps of mean seasonal PM₁₀ removal efficiency (kg/ha) reveal distinct functional group patterns: deciduous broadleaves reach peak efficiency in summer, whereas conifers provide a more consistent year-round contribution, resulting in the highest annual removal. Monetary valuation was performed using externality costs from the European Environmental Agency. Overall, urban forests remove 3360.40 Mg of PM₁₀ annually, corresponding to an estimated value of 255.69 M€. Integrating biophysical and economic perspectives supports urban planning and highlights UGIs as nature-based solutions to enhance air quality, protect public health and promote ecosystem biodiversity and resilience. Full article

Honey bees are very important to the ecological environment and human society, contributing significantly to biodiversity and global food security, with an estimated annual impact of $15 billion in crop pollination in the USA. Over 62% of honey bee colony decline has been observed between June 2024 and February 2025. This study investigates bee stress level monitoring due to external disturbances like mechanical vibrations by measuring internal air temperature, relative humidity, and CO₂ gas concentration levels of beehives. A new wireless sensor board for real-time monitoring of honey bee colonies was designed, built, and validated. The board incorporates NDIR-based SCD30 and SCD41 sensors for CO₂, temperature, and humidity monitoring, integrated with a custom-designed two-layer printed circuit board and a Particle Argon^TM microprocessor for Wi-Fi communication. The developed board was tested and validated with live beehives in summer and winter of 2024 and 2025. The experimental study results showed the adequacy of the built sensor board. Bee colony responses on the applied stimuli (knocks) show that bees responded with a temperature increase of over 5 °C, CO₂ concentration increase by 3000 to over 10,000 ppm, and, at the same time, relative humidity drop by about 10% inside beehives. Full article

Freshwater ecosystems play an important role in human survival, ecosystem functioning, and biodiversity conservation, yet industrialisation and urbanisation dump over 80% of untreated sewage into them. This inadequate wastewater management leads to enteric pathogens like Escherichia coli, Salmonella, Shigella, Campylobacter, Vibrio cholerae, Pseudomonas aeruginosa, and Legionella pneumophila that are responsible for a wide range of waterborne human diseases globally with extensive morbidity and mortality. The World Health Organization (WHO) estimates that at least 2 billion individuals drink water contaminated with pathogens, resulting in illnesses like cholera, dysentery, and diarrhoea, and approximately 50,000 diarrheal deaths annually. Classical epidemiology approaches are the basis for determining disease burden in public health, but they are limited in their capacity to predict future health risks. Quantitative microbial risk assessment (QMRA) addresses this by estimating the potential health risks of any exposure to microbial pathogens in any environment using four key elements, which include the identification of the microbial hazards, human exposure to the hazard through diverse activities, dose–response relationships, and the estimated risk of the infection. This review summarises information on freshwater pathogens, their occurrence, sources and health implications. The methodological approaches of QMRA in freshwater systems are reviewed with examples drawn from recreational activities, drinking water, and wastewater-impacted environments. Global QMRA studies indicate a wide range of infection risk estimates, reflecting differences in water sources, pathogens, and exposure conditions. Thus, QMRA is known to be a valuable public health tool for freshwater ecosystems, linking microbial contamination dynamics to health risk estimates that support proactive management and policy-relevant decision-making. Full article

The province of Pastaza is a biodiversity hotspot in the Amazon but lacks up-to-date inventories of its herpetofauna. This study aimed to provide an updated characterization of the richness, composition and conservation status of amphibians and reptiles in different habitats. Between 2013 and 2018, standardized sampling was carried out using quadrats (8 × 8 m) and transects (100 × 20 m), as well as pitfall traps and daytime and night-time visual censuses. A total of 900 h of effort was distributed across six habitats. Coverage estimators, species accumulation curves, range abundance curves, and alpha diversity indices (Shannon, Simpson, and Chao-1) were used for data analysis, as well as similarity indices (Jaccard). A total of 75 species were recorded (51 anurans, eight lizards, 14 snakes and two salamanders), displaying habitat-dependent dominance patterns led by Dendropsophus sarayacuensis and Scinax ruber. Diversity is considered high according to the Chao-1 (19.63–60.53), Shannon–Weaver (2.402–3.223), and Simpson (0.861–0.947) indices, showing interannual variation with a temporary decrease in year 5 and an increase in year 6. The presence of species at risk (VU, n = 26 spp. and EN, n = 2) and high temporal variability highlight the need for continuous monitoring and conservation strategies tailored to specific habitats. Full article

Recent genomic phylogenies have generated new robust classifications of actinopterygian fishes, making possible greater nomenclatural stability, but genus-level classifications of groups like the diverse catfish subfamily Trichomycterinae are still unclear, containing ill-defined paraphyletic taxa. The focus of the present study is the Trichomycterus Lineage (TL), a clade with great morphological diversity, containing about 170 species widely distributed in South America, occurring in the most important biodiversity hotspots of the world, such as the Atlantic Forest, Cerrado, and the Tropical Andes. Most species are small, but at least one reaches about 400 mm of total length, being used as food and depicted in pre-Hispanic Andean ceramics. Based on a comparative morphological analysis, mainly using osteological characters, supported by concordant genomic phylogenies, a new classification at the genus level is here provided. Many morphological features delimiting TL genera seem to be related to ecological adaptations. Nine genera are here recognised of which five are new. Recognition of the new genera will allow easier descriptions of new species and consequently better biodiversity estimates. Full article

In August 2023, a large forest fire burned more than 60% of the Dadia–Lefkimi–Soufli Forest National Park in northeastern Greece, following another large fire in 2022. To quantify the effects of these fires on local herpetofauna, we analyzed community composition, abundance, and diversity before and after the 2023 event. Standardized visual encounter surveys were conducted across 29 sites between 2015 and 2024, spanning burned and unburned areas. Species richness, abundance, and diversity metrics, together with Bray–Curtis community dissimilarities, were compared across sampling periods and fire-severity classes. Amphibian assemblages showed high postfire persistence, with 82% of regional species still detected and no significant changes in diversity indices, likely reflecting the buffering role of perennial streams and other hydrologically stable refugia. In contrast, reptile communities showed clear compositional shifts and experienced severe declines: overall reptile species richness decreased to 30% of prefire levels and diversity indices dropped significantly. Tortoises (i.e., Testudo graeca, T. hermanni) declined by nearly 90% relative to prefire estimates, indicating high vulnerability of low-mobility, long-lived species. Snakes were not detected in any burned sites, whereas only a few small-bodied lizards and the freshwater turtle Mauremys rivulata persisted locally. These findings demonstrate that extreme, landscape-scale fires can restructure reptile communities in Mediterranean forests, particularly where long-term habitat change and drought had already reduced population resilience. The study underscores the need for targeted postfire restoration, conservation planning for slow-dispersing taxa, and long-term biodiversity monitoring under increasingly frequent fire regimes. Full article