Search Results (6,677)

In urban areas, green spaces have become the main refuge for biodiversity, providing essential habitat and resources for urban-adapted species. However, scientific evidence on the fitness consequences of urban green space management for urban populations remains scarce, limiting our ability to design successful conservation and management strategies. Here, we assess the fitness consequences of different levels of management practices in green spaces (i.e., high for areas with continuous intervention such as regular mowing and irrigation, and low for areas with minimal, sporadic maintenance) based on a 19-year long-term monitoring of the Eurasian Tree Sparrow (Passer montanus), a species with high behavioural plasticity in response to human-altered habitats. We formulated a unistate capture–mark–recapture model to estimate age-dependent survival while accounting for uncertainty in recapture probability. Furthermore, by means of GLMMs, we tested if the level of management influences reproductive parameters (i.e., breeding failure, number of eggs, nestlings, fledglings, brood number from the same year, breeding success). We found that high urban green space management caused a decline in adult survival, but we found no effect on juvenile survival. We also found lower breeding failure, a greater number of eggs, and larger brood numbers in the low management areas, but no differences were found in the number of nestlings and fledglings. Consequently, we found no differences in overall breeding success. Our results highlight the reduction in survival in a near-threatened passerine species due to routine green urban space management, in addition to differences in reproductive parameters depending on the degree of green urban space management. Overall, we confirm that the same species show several reproductive strategies with different breeding effort to reach similar breeding success, whatever the human context is. However, birds pay the cost in adult survival, and probably in shortening life span. Therefore, the management of urban green spaces has a negative impact on biodiversity in cities. It is necessary to review the management practices of these urban areas and promote practices that are friendly to biodiversity. Full article

Breeding in bird species inhabiting the temperate climate zone is strongly seasonally regulated. One such species is the common pheasant (Phasianus colchicus), widely maintained in aviary systems and of considerable importance in game management. The aim of this study was to determine seasonal variability in selected morphological traits of male common pheasants and to assess their relationship with vocalisation parameters during the annual cycle. The study was conducted on males kept under aviary conditions. Traits related to reproductive condition were analysed, including testicular mass and facial wattle height, together with mating vocalisations. The results revealed clear seasonal variation in the analysed traits. A gradual increase in body mass and spur length was observed from summer to winter, reflecting the maturation of young males and accumulation of energy reserves before the breeding season. The highest values of reproductive parameters, particularly testicular mass and wattle height, were recorded in spring, indicating peak hormonal activity and full sexual maturity. In June, a marked regression of these traits and a decline in the somatic condition traits were observed, corresponding to the end of the breeding season. Changes in vocal activity followed a similar pattern, suggesting a link between acoustic parameters and seasonal reproductive dynamics. Full article

Protected areas are often treated as internally homogeneous conservation units, yet their communities may be structured either as discrete modules or as continuous gradients shaped by environmental heterogeneity and human disturbance. Using camera-trap data from Liziping Nature Reserve, China, we examined the spatial organization of mammal and galliform bird communities and tested whether species-level environmental responses help explain community structure. From 109 camera-trap sites surveyed between October 2017 and July 2020, we obtained 6688 independent detections and retained 17 species for analysis. We combined β-diversity decomposition, clustering, NMDS ordination, single-species occupancy models, clustering of environmental response coefficients, and Mantel tests. Community variation was dominated by turnover rather than nestedness, and clustering based on co-occurrence and relative activity patterns did not reveal well-separated discrete modules. Instead, NMDS indicated continuous variation along environmental gradients, with elevation and vegetation productivity as the strongest correlates. Occupancy models showed marked species-specific environmental responses, especially to elevation, habitat structure, and human disturbance, and β-based clustering suggested two broad environmental response groups. Although human influences did not affect all species uniformly, some species showed clear sensitivity to recent disturbance and human-modified landscapes. These results indicate that communities in Liziping are better characterized as continuous gradient structures than as discrete modules, and suggest that conservation should emphasize the maintenance of environmental heterogeneity, habitat continuity, connectivity, and differentiated management of human activities within mountain protected areas. Full article

Bird strike events on rotating jet engine fan blades pose significant risks to aviation safety, yet high-fidelity numerical simulations remain computationally expensive, limiting their use in parametric design studies. This study develops a physics-guided machine learning surrogate framework for predicting bird strike response on rotating Ti-6Al-4V fan blades, systematically comparing Lagrangian (gelatin-based, Mooney–Rivlin) and Smoothed Particle Hydrodynamics (SPH, water-like) formulations. A total of 100 explicit dynamic simulations were conducted in ANSYS LS-DYNA (R2) (50 per formulation), varying bird impact velocity and blade angular speed. Random Forest, Support Vector Regression, Polynomial Regression, and XGBoost regression models were trained and evaluated using five-fold cross-validation. Results demonstrate that SPH-based surrogates achieve superior predictive accuracy, with Random Forest yielding R² = 0.9938 for maximum deformation and R² = 0.9962 for total energy dissipation. In contrast, Lagrangian-based stress surrogates exhibited severe performance degradation (R² = 0.24) due to mesh-dependent numerical noise. The trained surrogates achieved computational speed-up factors of 10⁴–10⁵ relative to direct simulation. These findings establish that surrogate model reliability is fundamentally governed by the numerical quality of the training data, providing guidance for integrating machine learning with impact simulation workflows in aero-engine blade design. Full article

Increased demands for protein have led to a search for alternatives to traditional protein sources like soy and animal protein. Black Soldier Fly Larvae can be reared on many feedstocks to produce a high-quality nutrient source for livestock and pets. These insects contain biologically meaningful compounds like antimicrobial peptides, lauric acid, and chitin. This combination of compounds highlights the need to investigate BSFL as a functional ingredient in broilers. This study examined the impact of BSFL inclusion on broiler performance with and without a subclinical Necrotic Enteritis (NE) challenge over two experiments. In both experiments, diets included 0%, 2.5%, or 5.0% BSFL from 0–42 d. During Experiment 2, birds were given a live coccidiosis vaccine at hatch and challenged with C. perfringens at 19, 20, and 21 d. Primary variables include growth performance, lesion scores, and NE-specific mortality. A BSFL inclusion of 2.5% and 5.0% significantly improved feed conversion ratio in both experiments (p < 0.001); 5% BSFL inclusion also significantly improved body weight gain in both experiments (p = 0.014, p = 0.023, respectively). Overall, results indicate that BSFL is an effective and safe feed ingredient option for commercial broiler production, providing biologically relevant improvements in performance with and without disease pressure. Full article

Canola meal, with environmentally friendly attributes, lower cost, and previous studies, is an interesting proteic source to partially replace the soybean meal for poultry nutrition. For that, in this work we aimed to investigate canola meal as a partial replacement of soybean meal in finishing poultry diets (21 to 49 days) on the productive performance, also including the impact on the quality, nutritional attributes and antioxidative status of valuable cuts of meat. Ninety-six 21-day-old chickens were assigned to four experimental diets (24/diet), with increasing doses of canola meal (CM 0, 2.5, 5 and 10%). Daily consumption, weekly live weight and post mortem carcass weight and yield were determined. At 24 h post mortem, pH, color (CIE L, a*, b*) and drip loss were measured in the breast, drumstick and thigh cuts. Fatty acid composition and health lipid indexes were also determined in the fresh cuts. The oxidative status of lipids and proteins, polyphenol and flavonoids content in fresh and in stored (7 days-display at 4–6 °C) in vacuum packaged cuts were determined. Including CM, up to 10%, the feed intake and growth of birds was not affected (p = 0.74 and p = 0.87 respectively). In meat, CM significantly decreased the drip loss (p < 0.05), the pH in breast and thigh (p = 0.01 and p = 0.05 respectively), a lower L and b in thigh and increased PUFAs in more oxidative cuts, with a strong interaction between dose and muscle type. There was no effect on lipid oxidation while carbonyls decrease at a 2.5% dose in fresh and stored cuts but there is an increase with higher ones. Flavonoids raise the maximum deposition in meat at 5% CM. In conclusion, CM can be included in finishing poultry diets, but high doses must to be adequately managed if performance and quality of meat criteria are considered together. Full article

New Guinea, the world’s largest tropical island, supports the planet’s richest insular avifauna. Large areas of New Guinea remain poorly surveyed, however, in part due to the island’s challenging terrain. In hard-to-access areas, like many mountainous parts of New Guinea, automated surveying tools, like camera traps, may be especially helpful to address the survey deficit. Here we present the results of a camera-trap survey of the avifauna of the Cyclops Mountains, a range in New Guinea’s western, Indonesian provinces (Indonesian Papua). To our knowledge, our results represent only the second published survey of birds from Indonesian Papua. We deployed 73 camera traps along an elevation gradient (143–1963 m) of the Cyclops Mountains for 11,869 camera-trap nights, recording 22 bird species from 1696 independent detections. Our species list is, to our knowledge, the first to include observations from the upper northern slopes of the Cyclops Mountains. It documents the first record of Masked Bowerbird (Sericulus aureus) in the range and provides photographic rediscoveries of two ‘lost’ species: Mayr’s Honeyeater (Ptiloprora mayri) and Mayr’s Forest Rail (Rallicula mayri). We also report substantial elevation range extensions for several species, including numerous records of Northern Cassowary (Casuarius unappendiculatus) over 1000 m above its historically known elevation ceiling. These findings provide new insights into species distributions and ecological flexibility in New Guinea’s montane systems, highlighting the potential for previously undocumented biodiversity in under-surveyed regions. Although camera traps detected fewer species than traditional ornithological methods, they were effective in documenting several elusive, ground-dwelling bird species, highlighting their value as a complementary tool for ornithological research in challenging terrain like New Guinea. Finally, we use our data to publish an updated bird species checklist for the Cyclops Mountains. Full article

Salmonella Enteritidis (SE) infections in poultry threaten animal health and food safety. Antibiotic resistance makes alternative treatments necessary. Bamboo polyphenols (BP), recovered from bamboo vinegar—a byproduct of bamboo carbonization—represent a sustainable and eco-friendly candidate for combating avian salmonellosis. We tested BP against SE using laboratory tests and a chick model. BP showed a minimum inhibitory concentration of 1:256 against SE. We infected chicks with 1.8 × 10⁸ CFU per bird. The results indicated that adding 0.2% (v/v) BP to drinking water demonstrated optimal efficacy for prevention. Adding 0.4% (v/v) BP demonstrated optimal efficacy for treatment. Prophylactic BP administration effectively prevented SE-induced mortality and tissue damage. As a therapeutic agent, BP performed comparably to berberine. BP lowered the bacterial load in organs and increased chick survival to 96%. At the transcriptional level, BP administration downregulated the TLR4/MyD88/NF-κB pathway. It also improved antioxidant levels, strengthened the intestinal barrier, and restored healthy gut bacteria. These results indicate that BP could serve as a potential and sustainable feed additive to reduce SE infection in poultry. Full article

Parakeets exhibit many similar traits across species, with only subtle differences in features and coloration used for classification, which complicates detection and identification for birdwatchers, breeders, and researchers. Traditional classification methods rely on observation, while more expensive options involve DNA sampling. We developed a bird classification system that identifies Asiatic parakeets by combining You Only Look Once Version 5 (YOLOv5) for detection with ResNet-50 for the classification of four specific species: Alexandrine, Moustache, Plum-headed, and Indian Ringneck parakeets. Using a Raspberry Pi 4B and a Raspberry Pi Camera housed in a customized enclosure to capture images of the birds, the evaluation indicated an overall accuracy of 95.05% through a multi-class confusion matrix, demonstrating the effectiveness of the system as a reliable tool for avian identification and research. Full article

Background/Objectives: Native to the Indo-Pacific region, edible bird’s nests (EBN; Yan Wo in Chinese) are the solidified saliva of swiftlets (Aerodramus fuciphagus and A. maximus) and have been consumed as a traditional functional food for centuries. However, the bioactive components and underlying mechanisms of EBN remain poorly understood. EBN consists of over 60% protein, much of which is heavily glycosylated, forming complex glycoconjugates that are resistant to enzymatic digestion. This study examines the properties of EBN-derived bioactive peptides and assesses their potential for skin moisturization and anti-inflammation when applied topically. Methods: EBN was double-boiled for an extended period, then digested with gastric enzymes to extract active peptides. Digestion was over 90% efficient, and peptide molecular weights were measured. The enzymatic digest was then fractionated using an activity-guided approach based on assays for skin moisturization and anti-inflammatory properties. Results: A novel bioactive heptapeptide, with the sequence LAGAAHF and designated EBN_P3, was identified and characterized. It attenuated TNF-α-induced inflammatory responses in HaCaT keratinocytes and alleviated dermatitis symptoms in a DNCB-induced C57BL/6 mouse model. Conclusions: EBN-derived peptides with skin moisturizing and anti-inflammatory activities hold significant promise for development into functional ingredients for skincare products. Full article

Fine-grained bird identification is crucial for ecosystem monitoring, species conservation, and habitat assessment. However, in real-world environments, there are challenges such as imbalances in modality quality and interference from background noise. To improve fine-grained audio-visual bird classification under heterogeneous modality conditions, we propose an audio-visual feature fusion framework named CABIF-Net. This framework introduces a confidence-based Top-K mean pooling module to select key frames to optimize the visual representations at the video level. Through a Confidence Calibration module, it dynamically assesses the reliability of the visual and audio modalities and integrates a Bidirectional Inter-modulation Fusion module to achieve controllable cross-modal information interaction. Experiments were conducted on the publicly available SSW60 dataset, characterized by severe noise and imbalance in modality quality, and the self-built Birds21 dataset with balanced modality quality. The experimental results show that the classification accuracies were 85.76% and 96.67%, respectively, outperforming existing unimodal methods and several mainstream fusion strategies. Weight distribution and visualization analyses further indicate that the proposed method can adaptively adjust the modality contributions based on discriminative evidence at the sample level. This study provides an effective framework for fine-grained audio-visual bird species recognition. Full article

Surface anomalies such as dust accumulation and bird droppings on photovoltaic (PV) panels can significantly reduce their energy production and lead to inefficient maintenance decisions. This paper proposes a vision-based deep learning framework for the automatic detection of PV panel surface conditions and validates the detected anomalies using real inverter-level energy production data. Unlike conventional studies focusing solely on detection performance, the proposed approach introduces a unified and physically interpretable framework that directly links image-based anomaly detection with inverter-level energy performance and decision-oriented PV maintenance. An EfficientNetB3-based model is trained using a two-stage transfer learning strategy on a publicly available Kaggle dataset and evaluated using standard classification metrics. The trained model is then deployed and validated at a 1 MW solar power plant located at Karaman, Türkiye. Classification results obtained from field images are systematically linked with inverter-associated hourly energy production measurements. Following panel cleaning and natural rainfall, an approximately 12.5% increase in inverter-level hourly energy production is observed for the analyzed PV group (120 panels, ~270 Wp), corresponding to an increase from 23.2 to 26.1 kWh. In addition, the study introduces an energy–water–sustainability-aware cleaning decision framework tailored for arid and semi-arid regions where water scarcity and deep groundwater extraction present critical constraints. The framework defines a quantitative decision rule in which panel cleaning is performed only when the expected recoverable energy exceeds the energy cost of water extraction and cleaning. Overall, the proposed approach enables accurate surface anomaly detection while supporting sustainability-aware, resource-efficient and data-driven maintenance decisions for PV power plant operation. Full article

This paper proposes a multi-strategy Secretary Bird Optimization Algorithm (MS-SBOA) for solving global optimization problems and 3D wireless sensor network deployment. While preserving the original two-phase search framework of SBOA, the proposed algorithm achieves a dynamic balance between global exploration and local exploitation through the synergistic integration of multiple enhancement strategies, including a hybrid initialization scheme combining Latin hypercube sampling and quasi-opposition-based learning, a success-history-based adaptive parameter learning mechanism, a finance-inspired market-state trading operator, and an elite-guided population regulation strategy. Experimental results on the IEEE CEC2020 and CEC2022 benchmark test suites demonstrate that MS-SBOA significantly outperforms nine comparative algorithms, including VPPSO, IAGWO, and QHSBOA, under both 10-dimensional and 20-dimensional settings. The proposed algorithm exhibits superior optimization accuracy, faster convergence speed, and stronger robustness. Statistical analyses using the Wilcoxon rank-sum test and the Friedman mean rank test further confirm that the observed performance improvements are statistically significant. Moreover, MS-SBOA is applied to three-dimensional wireless sensor network (3D WSN) deployment optimization problems, where the average coverage rates reach 76.22% and 82.32% for 30-node and 50-node deployment scenarios, respectively. The resulting node distributions are more uniform, and the computational efficiency is improved compared with competing algorithms. Full article

Background: The dorsal raphe nucleus (DRN) produces and distributes serotonin, while the hypothalamus (HYP) uses serotonergic signals to regulate physiological processes in chickens. Coconut oil (COCO), rich in medium-chain fatty acids, is rapidly absorbed without re-esterification. Methods: Day-old broilers (Ross 708 male, n = 160) were distributed into two dietary treatments with five replicates of 16 birds each. The birds were fed a corn–soybean meal (SBM) basal diet supplemented with 3% of poultry fat (CON) or coconut oil (COCO). The body-weight gain (BWG), feed intake (FI), and feed conversion ratio (FCR) were recorded over a 3-week period, and the data were subjected to a t-test. Untargeted metabolomic analysis by high-performance liquid chromatography (HPLC-MS) was used to evaluate the influence of the type of dietary fat on metabolite profiles in the DRN, HYP, and plasma of broiler chickens. Principal component analysis (PCA) was used to identify unique metabolites, and ANOVA was used to identify the metabolites that were significantly abundant (p < 0.05). The metabolites were then annotated using the KEGG and HMDB databases. Results: Birds in the COCO treatment gained more weight on average (0.8446 kg/bird) than birds in the CON group (0.8132 kg/bird; p = 0.0496). Five metabolites associated with multiple significant cellular processes, such as brain function, energy metabolism, and neurotransmission, showed similar differential expression patterns, while two metabolic pathways (butanoate metabolism and alanine, aspartate and glutamate metabolism) were identified. Conclusions: The dietary inclusion of COCO improves BWG in poultry and enhances their overall well-being by modulating metabolite profiles, supporting neurotransmission, and enriching the metabolic pathways essential for growth and brain function. Full article

This study investigated the effects of chronic heat stress (HS) on brain injury in broilers and the associated molecular changes. A chronic HS model was established by exposing broilers to 35 °C from 08:00 to 20:00 daily from 21 to 42 days of age, and samples were collected at 28, 35, and 42 days of age. Chronic HS significantly impaired growth performance and was associated with histopathological and ultrastructural alterations in brain tissue. Serum antioxidant enzyme activities and the total antioxidant capacity were significantly reduced, whereas malondialdehyde levels were significantly increased, indicating sustained oxidative stress (OS). Blood–brain barrier (BBB) permeability, assessed by Evans blue extravasation, was significantly higher in HS birds and was accompanied by reduced mRNA expression of the tight junction-related genes ZO-1 and Claudin-5. In addition, chronic HS was associated with increased mRNA expression in genes related to cellular stress, oxidative stress, and inflammation, including key components of the TLR4/MyD88/NF-κB/NLRP3 pathway, as well as decreased expression of IL-4. These findings suggest that chronic HS is associated with enhanced OS, altered neuroinflammatory gene expression, and BBB impairment in the broiler brain. Overall, this study provides evidence that chronic HS is associated with brain injury in broilers and highlights a potential link among OS, inflammation-related transcriptional changes, and BBB dysfunction, thereby offering a basis for further mechanistic and interventional studies. Full article