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300 results for “bumble bee”
Fire is associated with positive shifts in bumble bee (Bombus vosnesenskii) body size and bee abundance in the Southern Sierra Nevada Mountains
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Bumble bee niche overlap along an elevation gradient: How traits can inform novel competitive pressures under climate change
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Social control of egg-laying in independently nest-founding bumble bee queens
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Data for: Consequences of microsporidian prior exposure for virus infection outcomes and bumble bee host health
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Floral preferences of mountain bumble bees are constrained by functional traits but flexible through elevation and season
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A simulated natural heatwave perturbs bumble bee immunity and resistance to infection
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Whole genome demographic models indicate divergent effective population size histories shape contemporary genetic diversity gradients in a montane bumble bee
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Microbiome assembly and maintenance across the lifespan of bumble bee workers
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High thermal tolerance in high elevation species and laboratory-reared colonies of tropical bumble bees
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Core symbionts, age at inoculation, and diet affect colonization of the bumble bee gut by a common bacterial pathogen
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Data from: Pesticide and pathogen exposure causes idiosyncratic gene expression responses across four diverse North American bumble bee species
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Pollen collection by the western honey bee and common eastern bumble bee foraging in a common landscape and applications for agri-environment schemes
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Biogeographic parallels in thermal tolerance and gene expression variation under temperature stress in a widespread bumble bee
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Data for: Positive impact of postfire environment on bumble bees not explained by habitat variables in a remote forested ecosystem
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Data for: Higher floral richness promotes rarer bee communities across remnant and reconstructed tallgrass prairies, though remnants contain higher abundances of a threatened bumble bee (Bombus Latreille)
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Mean body size predicts colony performance in the common eastern bumble bee (Bombus impatiens)
Prior studies suggest that both the mean and variation of worker size predict the performance of bumble bee colonies. The 'variation hypothesis' posits that colony performance increases with variation of worker body size due to more efficient division of labour within colonies. The 'mean size hypothesis' posits that colony performance increases with mean bumble bee size, as each individual’s efficiency tends to increase with body size. The present study tested these non-mutually exclusive hypotheses by establishing 62 Bombus impatiens Cresson (Hymenoptera, Apidae) nest boxes in 32 semi-natural savanna fragments within large-scale experimental landscapes in South Carolina (U.S.A.). Based on measurements of > 24 000 individuals and on colony growth over ca. 7 weeks, our results support the mean size hypothesis, not the variation hypothesis.
Experimental infection of bumble bees with honey bee associated viruses: no direct fitness costs but potential future threats to novel wild bee hosts
<p>Pathogen spill-over represents an important cause of biodiversity decline. For wild bee species such as bumble bees, many of which are in decline, correlational data point toward viral spill-over from naged honey bees as a potential cause. Yet impacts of honey bee viruses on wild bees are rarely evaluated. Here, in a series of highly controlled laboratory infection assays with well characterised viral inocula, we show that three viral types isolated from honey bees (<i>Deformed wing virus</i> genotype A, <i>Deformed wing virus</i> genotype B and <i>Black queen cell virus</i>) readily replicate within hosts of the bumble bee <i>Bombus terrestris</i>. Impacts of these honey bee-derived viruses – either injected or fed – on the mortality of <i>B. terrestris </i>workers were, however, negligible and likely dependent on host condition. Our results highlight the potential threat of viral spill-over from honey bees to novel wild bee species, though they also underscore the importance of additional studies on this and other non- bee species under field-realistic conditions to evaluate whether pathogen spill-over has a negative impact on wild bee individuals and population fitness.</p>
Local adaptation across a complex bioclimatic landscape in two montane bumble bee species
<p>Understanding evolutionary responses to variation in temperature and precipitation across species ranges is of fundamental interest given ongoing climate change. The importance of temperature and precipitation for multiple aspects of bumble bee (<i>Bombus</i>) biology, combined with large geographic ranges that expose populations to diverse environmental pressures, make these insects well-suited for studying local adaptation. We analyzed genome-wide sequence data from two widespread bumble bees, <i>Bombus vosnesenskii </i>and <i>Bombus vancouverensis</i>, using multiple Environmental Association Analysis methods to investigate climate adaptation across latitude and altitude. The strongest signatures of selection were observed in <i>B. </i><i>vancouverensis</i>, but despite unique responses between species for most loci, we detected several shared responses. Genes relating to neural and neuromuscular function and ion transport are especially evident with respect to temperature variables, while genes relating to cuticle formation, tracheal and respiratory system development, and homeostasis were associated with precipitation variables. Our data thus suggest that adaptive responses for tolerating abiotic variation are likely to be complex, but that several parallels among species can emerge even for these complex traits and landscapes. Results provide the framework for future work into mechanisms of thermal and desiccation tolerance in bumble bees and a set of genomic targets that might be monitored for future conservation efforts.</p>
Data from: Flight of the bumble bee: buzzes predict pollination services
Multiple interacting factors drive recent declines in wild and managed bees, threatening their pollination services. Widespread and intensive monitoring could lead to more effective management of wild and managed bees. However, tracking their dynamic populations is costly. We tested the effectiveness of an inexpensive, noninvasive and passive acoustic survey technique for monitoring bumble bee behavior and pollination services. First, we assessed the relationship between the first harmonic of the flight buzz (characteristic frequency) and pollinator functional traits that influence pollination success using flight cage experiments and a literature search. We analyzed passive acoustic survey data from three locations on Pennsylvania Mountain, Colorado to estimate bumble bee activity. We developed an algorithm based on Computational Auditory Scene Analysis that identified and quantified the number of buzzes recorded in each location. We then compared visual and acoustic estimates of bumble bee activity. Using pollinator exclusion experiments, we tested the power of buzz density to predict pollination services at the landscape scale for two bumble bee pollinated alpine forbs (Trifolium dasyphyllum and T. parryi). We found that the characteristic frequency was correlated with traits known to affect pollination efficacy, explaining 30-52% of variation in body size and tongue length. Buzz density was highly correlated with visual estimates of bumble bee density (r = 0.97), indicating that acoustic signals are predictive of bumble bee activity. Buzz density predicted seed set in two alpine forbs when bumble bees were permitted access to the flowers, but not when they were excluded from visiting. Our results indicate that acoustic signatures of flight can be deciphered to monitor bee activity and pollination services to bumble bee pollinated plants. We propose that applications of this technique could assist scientists and farmers in rapidly detecting and responding to bee population declines.
Data from: Unsupervised machine learning reveals mimicry complexes in bumble bees occur along a perceptual continuum
Müllerian mimicry theory states that frequency dependent selection should favour geographic convergence of harmful species onto a shared colour pattern. As such, mimetic patterns are commonly circumscribed into discrete mimicry complexes each containing a predominant phenotype. Outside a few examples in butterflies, the location of transition zones between mimicry complexes and the factors driving mimicry zones has rarely been examined. To infer the patterns and processes of Müllerian mimicry, we integrate large-scale data on the geographic distribution of colour patterns of social bumble bees across the contiguous United States and use these to quantify colour pattern mimicry using an innovative, unsupervised machine learning approach based on computer vision. Our data suggest that bumble bees exhibit geographically clustered, but sometimes imperfect colour patterns and that mimicry patterns gradually transition spatially, rather than exhibit discrete boundaries. Additionally, examination of colour pattern transition zones of three comimicking, polymorphic species, where active selection is driving phenotype frequencies, revealed their transition zones to differ in location within a broad region of poor mimicry. Potential factors influencing mimicry transition zone dynamics are discussed.
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.