Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
11
datasets available to search
ShareScore release 0.9.0
Dataset results
11 results for “non-native bees”
Harnessing the power of digitized natural history collections to visualize spatiotemporal patterns in native and non-native bee flight phenology
<p>What time of year are bees flying, where are they flying, and how do biogeographical factors, sex, and native status affect flight phenology? Consistent monitoring along with creating spatially and temporally explicit visualizations using large openly available data sets enhance our understanding of trends in flight time phenology and shape our understanding of bee-plant interactions, including shifts in the phenology of bee pollinators.</p> <p>Species occurrence data from digitized collection networks (iNaturalist, Global Biodiversity Information Faculty (GBIF), Integrated Digitized Biocollections (iDigBio), Symbiota Collections of Arthropods Network (SCAN), and UC Santa Barbara Collection Network) are part of an effort to improve our understanding of bees in coastal Santa Barbara County, including the California Channel Islands. New inventory collections combined with historical data from over 11 natural history museums and 2 observation networks are used in an effort to examine patterns and changes in phenology of native and non-native bee species, and create updated species inventories.</p> <p>Synthesizing species observation data from digitized natural history collections makes use of a wealth of existing data and multiplies the analytical power of isolated observations, but it is not without limitations and challenges. By exploring novel techniques to generate clear and accurate visualizations to communicate bee flight time, we present our key initial findings and identify geographic, temporal, and taxonomic gaps, which will lead to further focused inventory projects of coastal Santa Barbara County, improved data quality for phenological analyses, and reusable methods for visualizing insect phenology data across taxa or geography.</p> <p><strong>The attached files include the R code and some of the .csv files used to produce the figures in my poster that was available on demand at the Entomology Society of America 2020 virtual meeting. </strong></p>
Fig. 1 in Use of crape myrtle, Lagerstroemia (Myrtales: Lythraceae), cultivars as a pollen source by native and non-native bees (Hymenoptera: Apidae) in Quincy, Florida
Fig. 1. Cultivar positions in crape myrtle experimental block. Each small circle is 1 crape myrtle. Each quadrat has 4 crape myrtle plants of the same cultivar. Legend for cultivar abbreviations: Apalach = 'Apalachee', Bwhite = 'Byers Wonderful White', Cbeau = 'Carolina Beauty', Natch = 'Natchez', and Tuske = 'Tuskegee'.
Figure 1 in Ecological impact and population status of non-native bees in a Brazilian urban environment
Figure 1 Bipartite network and non-native bees sampled in Curitiba. a) Bipartite network, non-native plant and bees colored, b) Anthidium manicatum, female; c) Distributional range of A. manicatum (SpeciesLink); d) Melipona scutellaris worker on Calliandra brevipes; e) Distributional range of M. scutellaris (SpeciesLink), natural records in green.
Data from: Fitness costs and benefits of a non-native floral resource for subalpine solitary bees
Open the record for dataset details and reuse information.
Fig. 2 in Use of crape myrtle, Lagerstroemia (Myrtales: Lythraceae), cultivars as a pollen source by native and non-native bees (Hymenoptera: Apidae) in Quincy, Florida
Fig. 2. Bahiagrass quadrat positions.
Fig. 3 in Use of crape myrtle, Lagerstroemia (Myrtales: Lythraceae), cultivars as a pollen source by native and non-native bees (Hymenoptera: Apidae) in Quincy, Florida
Fig. 3. Isolines depicting Bombus impatiens aggregations and gaps in bahiagrass on 23 Jul 2010.
Fig. 4 in Use of crape myrtle, Lagerstroemia (Myrtales: Lythraceae), cultivars as a pollen source by native and non-native bees (Hymenoptera: Apidae) in Quincy, Florida
Fig. 4. Isolines depicting Bombus impatiens distributions in crape myrtle on 21 Jul 2010.
Spillover of chalkbrood fungi to native solitary bee species from non-native congeners
<p>Introduced, managed bees such as mason bees (genus <em>Osmia</em>) can confer significant pollination benefits to agricultural systems, but a risk of introducing non-native species into new ecosystems is the co-introduction of pathogens along with them. Pathogen spillover to wild, native bees may then drive native bee species declines.</p> <p>This study examined prevalence of the chalkbrood-causing fungal genus <em>Ascosphaera</em> in the nests of both non-native and native mason bee species. We conducted large-scale trap-nesting and pan-trapping efforts across the Mid-Atlantic United States with community scientists. Using molecular methods, nests were screened for all known <em>Ascosphaera</em> species in which genetic sequences have been published. After finding <em>Ascosphaera</em> species first described in Asia, we compared their local prevalence with the local abundance of mason bees from Asia. Lastly, we compared the prevalence of co-introduced Ascosphaera species across sites with a variety of landcover profiles.</p> <p>Results indicate species originally described in Japan, <em>Ascosphaera naganensis</em> and <em>Ascosphaera fusiformis</em>, are now present in native Virginia mason bees, <em>Osmia lignaria</em> and <em>Osmia georgica</em>, with high prevalence of <em>A. naganensis</em> found in <em>O. georgica</em>.</p> <p>We also found that the declining native mason bee <em>O. georgica</em> experienced higher prevalence of non-native <em>Ascosphaera</em> spp. at sites with larger numbers of non-native <em>O. cornifrons</em> and <em>O. taurus</em>, perhaps indicating greater likelihood of spillover of these <em>Ascosphaera</em> species with greater sources of transmission. Lastly, when the proportion of agricultural landcover surrounding bee nests was high, there was significantly greater prevalence of non-native <em>Ascosphaera</em> in <em>O. georgica</em> compared to more natural landcover types.</p> <p>Synthesis and applications. Through community science programming, we documented species of Japanese chalkbrood fungi inside native mason bee nests in North America. Native mason bees encounter non-native fungi more frequently with increasing abundance of non-native mason bees. Agricultural landscapes may exacerbate spillover of non-native fungi for native mason bees. The use of non-native bee species in agriculture should involve monitoring native bees for pathogens in the surrounding area for detection of spillover and species declines.</p>
Spillover of chalkbrood fungi to native solitary bee species from non-native congeners
Open the record for dataset details and reuse information.
Are native and non-native pollinator friendly plants equally valuable for native wild bee communities?
<p>Bees rely on floral pollen and nectar for food. Therefore, pollinator friendly plantings are often used to enrich habitats in bee conservation efforts. As part of these plantings, non-native plants may provide valuable floral resources, but their effects on native bee communities have not been assessed in direct comparison with native pollinator friendly plantings. In this study, we performed a common garden experiment by seeding mixes of 20 native and 20 non-native pollinator friendly plant species at separate neighboring plots at three sites in Maryland, USA, and recorded flower visitors for two years. A total of 3744 bees (120 species) were collected. Bee abundance and species richness was either similar across plant types (mid-season and for abundance also late season) or lower at native than at non-native plots (early season and for richness also late season). The overall bee community composition differed significantly between native and non-native plots, with 11 and 23 bee species found exclusively at one plot type or the other, respectively. Additionally, some species were more abundant at native plant plots, while others<i> </i>were more abundant at non-natives. Native plants hosted more specialized plant-bee visitation networks than non-native plants. Three species out of the five most abundant bee species were more specialized when foraging on native plants than on non-native plants. Overall, visitation networks were more specialized in the early season than in late seasons. Our findings suggest that non-native plants can benefit native pollinators, but may alter foraging patterns, bee community assemblage, and bee-plant network structures.</p> <p> </p>
Are native and non-native pollinator friendly plants equally valuable for native wild bee communities?
Open the record for dataset details and reuse information.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.