Search Results (403)

We conducted a mark–release–recapture study of the ringlet butterfly, Erebia pronoe glottis, in the Pyrenees to study population density, flight activity, dispersal, and nectar plant preferences. We found differences between both sexes in population density (males: 48/ha; females: 23/ha), sex ratio (2.1), and behaviour (75.4 vs. 20.5% flying). Both sexes used a wide range of nectar plants (Asteraceae, 40.6%; Apiaceae, 34.4%; Caprifoliaceae, 18.8%). However, local abundance appeared to be limited by the availability of nectar plants. Compared to a population of an extensively used pasture in the Alps, a significant increase in flight activity, but not in range, was observed. Movement patterns showed the establishment of home ranges, which significantly limited the dispersal potential, being low for both sexes (mean fight distances-males: 101 m ± 73 SD; females: 68 m ± 80 SD). A sedentary taxon such as E. pronoe glottis does not seem to be able to avoid the pressure of resource shortage by dispersal. As a late-flying pollinator, Erebia pronoe competes seasonally for scarce resources. These are further reduced by grazing pressure and are exploited by honey bees as a superior competitor, resulting in low habitat quality and, consequently, in comparatively low abundance of E. pronoe glottis. Full article

Traditional algorithms such as Dijkstra and APF rely on complete environmental information for path planning, which results in numerous constraints during modeling. This not only increases the complexity of the algorithms but also reduces the efficiency and reliability of the planning. Swarm intelligence algorithms possess strong data processing and search capabilities, enabling them to efficiently solve path planning problems in different environments and generate approximately optimal paths. However, swarm intelligence algorithms suffer from issues like premature convergence and a tendency to fall into local optima during the search process. Thus, an improved Artificial Bee Colony-Beetle Antennae Search (IABCBAS) algorithm is proposed. Firstly, Tent chaos and non-uniform variation are introduced into the bee algorithm to enhance population diversity and spatial searchability. Secondly, the stochastic reverse learning mechanism and greedy strategy are incorporated into the beetle antennae search algorithm to improve direction-finding ability and the capacity to escape local optima, respectively. Finally, the weights of the two algorithms are adaptively adjusted to balance global search and local refinement. Results of experiments using nine benchmark functions and four comparative algorithms show that the improved algorithm exhibits superior path point search performance and high stability in both high- and low-dimensional environments, as well as in unimodal and multimodal environments. Ablation experiment results indicate that the optimization strategies introduced in the algorithm effectively improve convergence accuracy and speed during path planning. Results of the path planning experiments show that compared with the comparison algorithms, the average path planning distance of the improved algorithm is reduced by 23.83% in the 2D multi-obstacle environment, and the average planning time is shortened by 27.97% in the 3D surface environment. The improvement in path planning efficiency makes this algorithm of certain value in engineering applications. Full article

The Jilong Valley, situated in Rikaze, Xizang, China, is characterized by its complex topography and variable climatic conditions, providing a suitable habitat for Apis cerana Fabricius, 1793. To facilitate the conservation of germplasm resources and maintain genetic diversity, it is imperative to elucidate the population structure and lineage differentiation of A. cerana within this ecologically distinct region. In this study, we collected A. cerana specimens from 12 geographically disparate locations across various altitudinal gradients within the Jilong Valley, and also integrated publicly available sequencing data of A. cerana from various regions across mainland Asia. In total, our analysis encompassed sequencing data from 296 individuals. Population structure analyses based on SNP data revealed that A. cerana in Jilong represents a genetically distinct population that differs markedly from other regional A. cerana populations in terms of genetic lineage, although its subspecies identity remains to be confirmed. Through screening based on F_ST values, we identified SNP loci that contribute significantly to distinguishing between Jilong and non-Jilong A. cerana. Using these loci, the convolutional neural network model TraceNet was trained, which demonstrated specific recognition capabilities for Jilong versus non-Jilong A. cerana. This further confirmed the universality and efficiency of TraceNet in identifying honey bee lineages. These findings contribute valuable insights for the identification and conservation of A. cerana germplasm resources in specific geographical regions. Full article

The morphological diversity of Moroccan honey bees (Apis mellifera) was investigated using geometric morphometrics to assess wing venation patterns among three populations representing three climatic zones: desert, semiarid, and Mediterranean. A total of 193 honey bee samples were analyzed and compared to historical reference samples from the Morphometric Bee Data Bank in Oberursel, representing the three subspecies: A. m. intermissa, A. m. sahariensis, and A. m. major. Principal component analysis and linear discriminant analysis revealed significant, yet overlapping morphological differences among the climatic groups. Spatial modeling showed a significant southwest–northeast clinal gradient in wing morphology. Almost all samples were assigned to the African evolutionary lineage, except one, suggesting a dominant African genetic background. Interestingly, all three populations showed greater morphological affinity to A. m. intermissa than to A. m. sahariensis, which could indicate introgression or limitations in the current reference dataset. These discrepancies highlight the necessity of revising subspecies boundaries using updated morphometric and genomic approaches. These findings improve our understanding of honey bee biodiversity in Morocco and provide valuable information for conservation and breeding programs. Full article

This paper presents a hybrid indoor localization framework combining time difference of arrival (TDoA) measurements with a swarm intelligence optimization technique. To address the nonlinear optimization challenges in three-dimensional (3D) indoor localization via TDoA measurements, we systematically evaluate the artificial bee colony (ABC) algorithm and chimpanzee optimization algorithm (ChOA). Through comprehensive Monte Carlo simulations in a cubic 3D environment with eight beacons, our comparative analysis reveals that the ChOA achieves superior localization accuracy while maintaining computational efficiency. Building upon the ChOA framework, we introduce a multi-beacon fusion strategy incorporating a local outlier factor-based linear weighting mechanism to enhance robustness against measurement noise and improve localization accuracy. This approach integrates spatial density estimation with geometrically consistent weighting of distributed beacons, effectively filtering measurement outliers through adaptive sensor fusion. The experimental results show that the proposed algorithm exhibits excellent convergence performance under the condition of a low population size. Its anti-interference capability against Gaussian white noise is significantly improved compared with the baseline algorithms, and its anti-interference performance against multipath noise is consistent with that of the baseline algorithms. However, in terms of dealing with UWB device failures, the performance of the algorithm is slightly inferior. Meanwhile, the algorithm has relatively good time-lag performance and target-tracking performance. The study provides theoretical insights and practical guidelines for deploying reliable localization systems in complex indoor environments. Full article

The European honey bee (Apis mellifera) significantly contributes to Australian agriculture, especially in honey production and the pollination of key crops. However, managed bee populations are declining due to pathogens, agrochemicals, poor forage, climate change, and habitat loss. Major threats include bacteria, fungi, mites, and pests. With the increasing demand for pollination and the movement of bee colonies, monitoring these threats is essential. It has been demonstrated that honey constitutes an easily accessible source of environmental DNA. Environmental DNA in honey comes from all organisms that either directly or indirectly aid in its production and those within the hive environments. In this study, we extracted eDNA from 135 honey samples and tested for the presence of DNA for seven key honey bee pathogens and pests—Paenibacillus larvae, Melissococcus plutonius (bacterial pathogens), Nosema apis, Nosema ceranae (microsporidian fungi), Ascosphaera apis (fungal pathogen), Aethina tumida, and Galleria mellonella (arthropod pests) by using end-point singleplex and multiplex PCR assays. N. ceranae emerged as the most prevalent pathogen, present in 57% of the samples. This was followed by the pests A. tumida (40%) and G. mellonella (37%), and the pathogens P. larvae (21%), N. apis (19%), and M. plutonius (18%). A. apis was detected in a smaller proportion of the samples, with a prevalence of 5%. Additionally, 19% of the samples tested negative for all pathogens and pests analysed. The data outlines essential information about the prevalence of significant arthropod, fungal, and bacterial pathogens and pests affecting honey bees in Australia, which is crucial for protecting the nation’s beekeeping industry. Full article

Honey bees (Apis mellifera ligustica) are essential pollinators in both ecosystems and agricultural production. However, their populations are declining due to various factors, including pesticide exposure. Despite their importance, the reproductive castes, particularly drones, remain understudied in terms of pesticide effects. To investigate the effects of azoxystrobin and picoxystrobin on honey bee drones, the drones were exposed to different concentrations of azoxystrobin and picoxystrobin for 14 days; the drone survival, body weight, nutrient content, reproductive organs, and sperm concentration were assessed. Results showed that exposure to both fungicides caused a significant reduction in drone survival rates, with survival rates decreasing progressively as the duration of exposure increased. Compared to the control group, the body weights of drones in all treatment groups were significantly lower on days 7 and 14. Nutrient analysis revealed that low concentrations of azoxystrobin and picoxystrobin increased protein levels, while free fatty acid content decreased significantly in all treatment groups. No significant changes were observed in the total carbohydrate content. Morphological examination of reproductive organs showed that the lengths of the mucus glands and seminal vesicles in drones were significantly shorter in the treatment groups compared to the control group. Furthermore, exposure to azoxystrobin and picoxystrobin resulted in a significant decline in sperm concentration in the drones. These findings indicate that azoxystrobin and picoxystrobin have adverse effects on the health and reproductive capacity of honey bee drones. The present study highlights the need to reassess the risks posed by these fungicides to pollinators, particularly given the critical role of drones in maintaining the genetic diversity and resilience of honey bee colonies. Further research is warranted to elucidate the underlying mechanisms of these effects and explore potential mitigation strategies. Full article

Effective control of the parasitic mite Varroa destructor in honey bee (Apis mellifera) colonies relies on integrated pest management (IPM) strategies to prevent mite populations from reaching economic injury levels. Formulations of oxalic acid combined with glycerin may provide a viable summer treatment option in continental Northern climates. This study evaluated the efficacy of oxalic acid and glycerin strips compared to oxalic acid dribble and 65% formic acid when applied in mid-August. Mite levels and colony health parameters were assessed, and honey samples from oxalic acid-treated colonies were analyzed for residue levels. Results showed that the oxalic acid and glycerin strips had a moderate acaricidal efficacy (55.8 ± 3.2%), which was significantly higher than those of 65% formic acid (42.6 ± 3.2%) and oxalic acid dribble (39.5 ± 4.3%), which did not differ between them, suggesting potential for summer mite control. No significant adverse effects on cluster size, worker mortality, queen status, or colony survival were observed. Oxalic acid and glycerin increased the proportion of spotty brood patterns at early timepoints after treatment, but recovery was noted after 45 days of starting the treatment. Similar effects on brood were observed with 65% formic acid 14 days after starting the treatment, with recovery by 28 and 45 days after starting the treatment. No significant differences in oxalic acid residues in honey from the control and treatment colonies were found. Oxalic acid and glycerin strips might help control varroa mite populations, delaying their exponential growth and helping reduce economic losses for beekeepers, but this treatment should be considered as part of an IPM strategy and not a stand-alone method for V. destructor control. Full article

Honey bees (Apis mellifera) are major pollinators, playing a critical role in global food production, biodiversity, and ecosystem stability. However, their populations are increasingly threatened by multiple interacting stressors, including pesticide exposure. Among these, agricultural insecticides and anti-Varroa acaricides such as dinotefuran and amitraz can persist in hive matrices, resulting in chronic and combined exposure. This study investigates the low lethal (LC₁₀ and LC₃₀) effects of these compounds, individually and in combination, on honey bee survival, immune function, oxidative stress responses, detoxification pathways, and hypopharyngeal gland morphology. Both pesticides negatively affected honey bee health at low lethal concentrations, with dinotefuran showing higher toxicity. Exposure led to the reduced survival, suppression of vitellogenin expression, and dysregulation of genes related to antioxidant defense, immunity, and detoxification. Additionally, high concentrations of dinotefuran and its combination with amitraz impaired hypopharyngeal gland morphology. Notably, co-exposure resulted in synergistic toxic effects, exacerbating physiological damage beyond individual treatments. These findings emphasize the potential risks of combined exposure to agricultural and beekeeping pesticides. A more comprehensive risk assessment and stricter regulations are urgently needed. Full article

The wild tomato (Solanum sisymbriifolium) is a globally distributed shrubby weed with both negative and positive impacts, including its invasive properties and the potential for pharmaceutical and traditional medicinal uses. Despite its ecological significance, the plant’s reproductive biology and pollination ecology remain poorly understood. This study aimed to investigate the floral biology, pollination ecology, and plant reproduction of the weed species. Some flower traits, such as flowering intensity, flower display size, and pollen and ovule production, peaked during spring, summer, and the monsoon, while flower longevity and stigmatic receptivity were the longest in winter. The plant species was self-compatible (ISI = 0.02), heavily depended on pollinators (IDP = 0.72), and experienced minimal pollination limitation (D = 0.10) under open-pollination conditions. Flower visitors’ traits (e.g., abundance, diversity, and richness) were higher in the spring, summer, and the monsoon, and these were lower in winter. The vital pollination service was provided by Amegilla zonata, Ceratina binghami, Lasioglossum cavernifrons, Nomia (Curvinomia) strigata, Tetragonula pagdeni, Xylocopa aestuans, Xylocopa amethystina, Xylocopa fenestrata, and Xylocopa latipes. Reproductive success, as indicated by fruit and seed set, varied seasonally, being higher during the spring–monsoon period and lower in winter. These findings support effective management of this weed species and help conserve the associated bee populations. Full article

Background/Objectives: The objectives of this study were to identify the genetic effects involved in the expression of individual honeybee grooming behavior in response to Varroa destructor and to determine if there is an association between the expression of this behavior and the infestation levels of Varroa in the honeybee colonies. Methods: The study was conducted in a population of 112 colonies composed of six segregating genetic groups that were derived from two honeybee lines that were selected for high and low individual honeybee grooming behavior. The individual honeybee grooming behavior of 3974 workers from the 112 colonies was measured by the time it takes a bee to respond in performing grooming behavior after a mite was placed on her body. The population growth of Varroa in the colonies was measured over a period of six months. Results: Differences between the genetic groups were found in the expression of individual honeybee grooming behavior (p < 0.01). The distribution of means of the genetic groups fits a genetic additive and dominance effects model for the expression of individual honeybee grooming behavior (r² = 0.95; p < 0.01). Differences between the genetic groups were found in the colony population growth of Varroa over a period of six months (p < 0.01). A positive correlation was found between the mean individual honeybee grooming behavior of the colonies and the Varroa level of infestation in the colonies (r = 0.57; p < 0.01). Conclusions: The results indicate that additive and dominance genetic effects are associated with honeybee individual grooming behavior and that this trait has an effect on the levels of Varroa infestation in the colonies. Full article

Wildfires are increasing in extent and severity under anthropogenic climate change, with potential adverse impacts on native pollinators like wild bees. In 2019/2020, wildfires burned swathes of the Australian bushland. Whilst herbaceous angiosperms may flower in the post-fire environment, providing sustenance to native bees, pre-made holes created by wood-boring beetles that obligate cavity-nesting “renter” bees may take a longer time to recover. This may prevent native bees from colonising new areas or reduce the populations that have survived. To date, trap-nests, also known as bee hotels, have never been used as a tool to assist in providing nesting resources in post-fire environments. The project “Bee hotels to boost bees after bushfires” supported the recovery of native bee populations by installing artificial nesting substrates (bee hotels) in areas of high biodiversity value that were impacted by the 2019/2020 bushfires. This was achieved through monitoring of 1000 bee hotels (500 bamboo and 500 wooden) and visual surveys at five burnt sites and three control sites (nearby burnt sites without bee hotels) by a native bee ecologist from September–March 2021/2022. The bee hotel uptake was low initially, but by March, all hotels were occupied. Over 800 nests were created by bees in the bee hotels installed for this project and significantly more bees were observed in sites with bee hotels compared to control sites. Across sites, there was a significant negative association between honeybee density and nest occupancy, suggesting honeybees may be exerting competitive pressure on native bees in post-fire habitats. In conclusion, bee hotels, if designed correctly, can aid in boosting cavity-nesting bee populations following fires. Full article

Varroa destructor, an ectoparasitic mite of honey bees, is a major contributor to global colony declines. To manage infestations, beekeepers frequently apply both synthetic and organic miticides—sometimes in combination. While much attention has been given to foragers’ pesticide exposure, nurse bees are also at risk due to direct miticide contact and prolonged exposure to residuals in hive matrices. Despite this, little is known about the effects of sequential miticide applications on nurse bees. In this study, we evaluated the toxicities of single and pairwise consecutive applications of three synthetic miticides (fluvalinate, coumaphos, and amitraz) and two organic miticides (formic acid and oxalic acid) at field-realistic concentrations. Miticides were topically applied to nurse bees with 24 h between consecutive treatments. Synthetic miticides caused minimal mortality, while both organic miticides—especially formic acid—significantly reduced survivorship. Consecutive treatments generally produced mortality rates comparable to that of the corresponding organic miticide alone, indicating that observed toxicities were primarily driven by the organic agents. Notably, the fluvalinate–formic acid combination induced no significant adverse effects. These findings highlight the need for caution when using miticides in combination and support the development of safer application strategies to protect vulnerable in-hive bee populations.. Full article

Phospholipase A₂ (PLA₂) is a prevalent molecule in the honeybee venom. Its importance is reflected by the number of scientists focused on studying it from various points of view. This review summarises a significant amount of data concerning this fascinating substance. Firstly, the origin and occurrence of PLA₂, with similarities and differences among species or populations of bees are highlighted. Next, its synthesis, post-translational processing and structural features are described, followed by the PLA₂ availability. In a larger section, the multiple effects of honeybee venom PLA₂ are detailed, starting with the main ability as an enzyme to interact with biological membranes and to hydrolyse the sn-2 ester bond in 1,2-diacyl-sn-3-phosphoglycerides; the docking process, the substrate binding and the catalytic steps are analysed too. Then, the pro-/anti-inflammatory effect and allergenic property, the anticoagulant effect and the involvement of PLA₂ in apoptosis are revised. Selected antiviral, antibiotic and antitumoral effects of PLA₂, as well as its use in immunotherapy are mentioned as beneficial applications. Additionally, the mechanisms of toxicity of PLA₂ are presented in detail. Finally, a number of anti-PLA₂ compounds are enumerated. In each section, the features of the honeybee venom molecule are discussed in relation to PLA₂s from other species. Full article

Optimizing vehicle placement in unmarked parking areas is essential for maximizing space efficiency, particularly in irregular and high-demand urban environments. This study investigates the optimal allocation of additional vehicles in spaces left unoccupied around parked cars by comparing seven heuristic optimization algorithms: Particle Swarm Optimization, Artificial Bee Colony, Gray Wolf Optimizer, Harris Hawks Optimizer, Phasor Particle Swarm Optimization, Multi-Population Based Differential Evolution, and the Colony-Based Search Algorithm. The experiments were conducted in two different parking areas, one designed for parallel parking and the other for perpendicular parking, under three scenarios allowing different levels of cars’ rotational flexibility. The results indicate that MDE consistently outperforms other methods in both speed and robustness, achieving the highest vehicle capacity. These findings provide a foundation for smart parking systems, enabling real-time optimization, reduced congestion, and improved urban mobility. Full article