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.
174
datasets available to search
ShareScore release 0.9.0
Dataset results
174 results for “bee diversity”
Bioinformatic pipeline: Genomic diversity landscape of the honey bee gut microbiota
<p>This data-set describes the full bioinformatic pipeline used to analyze 54 metagenomic samples of the honey bee gut microbiota. Each sample was isolated from an individual honey bee, and all samples originate from two colonies of the Engel laboratory at the University of Lausanne, Switzerland. The full raw data-set is available from the sequence-read archive: SRP150166.</p> <p>A publication based on this analysis is currently under review, with the title: "Genomic diversity landscape of the honey bee gut microbiota", and an upload to Biorxiv is also underway.</p> <p>The data-set contains tar-balls for the different main workflows of the analysis. Dowload and unpack to view the contents (tar -zxvf filename.tar.gz). For each workflow, all directories contain README.txt files, describing the contents of the directory. Due to size constraints, some intermediate files have been omitted, and some workflows are demonstrated for a subset of the data. However, the full analysis can be reproduced from the raw data, using the provided scripts.</p> <p>Scripts are included within workflow directories, and are also provided as a separate tar-ball for convenience. All perl-scripts come with documentation, which can be viewed by typing: "perl script_name.pl -h". For R scripts, the usage is indicated as a comment in the top lines of each script. Note that many of the scripts require specific input-files to be present in the run-directory. Their usage is demonstrated within the workflow directories in bash-scripts (*.sh). Commands used for generating plots and some statistics are given within workflow directories in text-files "R.commands" when applicable.</p> <p>Aside from custom code, the pipeline also utilizes various open-source Software packages, which are detailed in the file "software_dependencies.txt". Note, while many of the scripts will run fast on any computer, some steps of the pipeline are computationally demanding, and will require significant computing time, as well as storage space. When scripts are known to be time-consuming, this is indicated in the script help message.</p> <p> </p> <p> </p> <p> </p>
Figure 7 in Diversity and life-history traits of wild bees (Insecta: Hymenoptera) in intensive agricultural landscapes in the Rolling Pampa, Argentina
Figure 7. Mean number of (a) above-ground nesting bee individuals, (b) floral specialist bee individuals, (c) oligolectic bee individuals and (d) oil-collecting bee individuals in cropped area (n = 28 points) and semi-natural area (n = 11 points). ns indicates a non-significant result. Asterisks indicate that means are significantly different (Wilcoxon rank sum test, ** = P <0.01). Bars show SEs.
Figure 2 in Diversity and life-history traits of wild bees (Insecta: Hymenoptera) in intensive agricultural landscapes in the Rolling Pampa, Argentina
Figure 2. Semi-natural area of the study site: (a) semi-natural grassland; (b) the stream 'Arroyo Dulce' and its banks (Photos: Violette Le Féon).
Maintaining habitat diversity at small scales benefits wild bees and pollination services in mountain apple orchards
<p>In 2021, we conducted our study in apple orchards in South Tyrol, an Alpine region in Italy, using pan-traps, direct observations of visitation frequency, and a pollinator exclusion experiment. We investigated the scale-dependent effects of landscape heterogeneity and other parameters on wild bee assemblages and the related pollination service they provide at five spatial scales (radius 100 – 2,000 m).</p>
Data from: Climatic conditions and landscape diversity predict plant-bee interactions and pollen deposition in bee-pollinated plants.
<p>Climate change, landscape homogenization and the decline of beneficial insects threaten pollination services to wild plants and crops. Understanding how pollination potential (i.e. the capacity of ecosystems to support pollination of plants) is affected by climate change and landscape homogenization is fundamental for our ability to predict how such anthropogenic stressors affect plant biodiversity. Models of pollinator potential are improved when based on pairwise plant-pollinator interactions and pollinator´s plant preferences. However, whether the sum of predicted pairwise interactions with a plant within a habitat (a proxy for pollination potential) relates to pollen deposition on flowering plants has not yet been investigated. We sampled plant-bee interactions in 68 Scandinavian plant communities in landscapes of varying land-cover heterogeneity along a latitudinal temperature gradient of 4–8 C°, and estimated pollen deposition as the number of pollen grains on flowers of the bee-pollinated plants <em>Lotus corniculatus</em>, and <em>Vicia cracca</em>. We show that plant-bee interactions, and the pollination potential for these bee-pollinated plants increase with landscape diversity, annual mean temperature, plant abundance, and decrease with distances to sand-dominated soils. Furthermore, the pollen deposition in flowers increased with the predicted pollination potential, which was driven by landscape diversity and plant abundance. Our study illustrates that the pollination potential, and thus pollen deposition, for wild plants can be mapped based on spatial models of plant-bee interactions that incorporate pollinator-specific plant preferences. Maps of pollination potential can be used to guide conservation and restoration planning.</p>
Figure 2 in Generalist ground-nesting bees dominate diversity survey in intensively managed agricultural land
Figure 2. Species richness compared between sampling periods. Dark grey bars: species from the genus Andrena Fabricius (Andrenidae); light grey bars: species from the genera: Halictus Latreille, Lasioglossum Curtis (Halictidae), Osmia Panzer (Megachilidae), and Nomada Scopoli (Apidae); black bars: species from the genus Bombus Latreille (Apidae). Different letters above the dark grey bars indicate a significant statistical difference between sampling periods in total species richness of all sampled genera (F (3, 42) = 20.01, p<0.001).
Figure 1 in Generalist ground-nesting bees dominate diversity survey in intensively managed agricultural land
Figure 1. Total number of bees sampled in this study at the four different sampling periods. Dark grey bars: individuals from the genus Andrena Fabricius (Andrenidae); light grey bars: individuals from the genera: Halictus Latreille, Lasioglossum Curtis (Halictidae), Osmia Panzer (Megachilidae), and Nomada Scopoli (Apidae); black bars: individuals from the genus Bombus Latreille (Apidae). Different letters above the dark grey bars indicate a significant statistical difference between sampling periods in activity-density of individuals from all sampled genera (F (3, 42) = 18.89, p<0.001).
Response of wild bee diversity, abundance and functional traits to vineyard inter-row management intensity and landscape diversity across Europe
<p>Data set used for analyses in the publication "Response of wild bee diversity, abundance and functional traits to vineyard inter-row management intensity and landscape diversity across Europe".</p> <p>First sheet in the Excel-file gives a detailed description of the abbreviations, terms etc. used in the following tables. Please also check the method section in the publication for the detailed description on how data were collected.</p> <p>If you have any questions feel free to contact Sophie Kratschmer via e-mail</p>
Fig. 2a-f in Wild bees (Anthophila) of Porto Santo (Madeira Archipelago) and their habitats: species diversity, distribution patterns and bee-plant network *
Fig. 2a-f: a) Andrena dourada, female; b) Andrena portosanctana, female collecting pollen on Cakile maritima; c) Lasioglossum wollastoni, female in front of nesting site; d) Osmia latreillei iberoafricana, male visiting Cakile maritima; e) Amegilla quadrifasciata maderae, female collecting pollen on Echium portosanctensis, f) Bombus terrestris lusitanicus, worker, collecting pollen on Echium portosanctensis. Photos: A. Kratochwil (a, b, e), A. Schwabe (c, d, f).
Fig. 1 in Wild bees (Anthophila) of Porto Santo (Madeira Archipelago) and their habitats: species diversity, distribution patterns and bee-plant network *
Fig. 1: Aspects from some of our sampling sites and their surroundings in March after an extreme dry winter and a wet winter: Left: March 2012 (November 2011–March 2012, no precipitation); right: March 2017 (October 2016–March 2017, 301 mm precipitation); a, b: sand beach with Vila Baleira in the centre; c, d: Pico Juliana and mainly fallow land; e, f: southern-exposed extensively grazed dry grassland; view from Capela da Graça (in the background right: Pico do Facho with Pinus plantations). Photos: A. Schwabe.
Fig. 1 in Stingless Bee (Hymenoptera: Apidae: Meliponini) Diversity In Dipterocarp Forest Reserves In Peninsular Malaysia
Fig. 1. Locations of the six Virgin Jungle Reserves where stingless bee collections occurred: BFR = Berembun Forest Reserve; GAFR = Gunung Angsi Forest Reserve; GTFR = Gunung Tebu Forest Reserve; KSFR = Kledang Saiong Forest Reserve; SFR = Semangkok Forest Reserve; UGFR = Ulu Gombak Forest Reserve.
Fig. 4 in Stingless Bee (Hymenoptera: Apidae: Meliponini) Diversity In Dipterocarp Forest Reserves In Peninsular Malaysia
Fig. 4. NMDS ordination based on the Jaccard distance metric. Topographic locations where collections occurred are indicated by the shapes of points: ▲ Ridges, ◆ Slopes, and ● Valleys.
Fig. 2 in Stingless Bee (Hymenoptera: Apidae: Meliponini) Diversity In Dipterocarp Forest Reserves In Peninsular Malaysia
Fig. 2. Sampling design for one set of three transects. Three sets of three 300-m sampling transects were established at each Virgin Jungle Reserve. Transects ran parallel to each other with approximately 500 m between them. Nine baiting points were established along each transect.
FIGURES 20–22 in Larval Diversity in the Bee Genus Megachile (Hymenoptera: Apoidea: Megachilidae)
FIGURES 20–22. Diagrams of postdefecating larva of Megachile (Chelostomoides) prosopidis. 20. Entire larva, lateral view. 21, 22. Head, frontal and lateral views, respectively.
FIGURES 15, 16 in Larval Diversity in the Bee Genus Megachile (Hymenoptera: Apoidea: Megachilidae)
FIGURES 15, 16. Diagrams of mature larvae Megachile (Creightonella) atrata, lateral views. 15. Entire postdefecating larva. 16. Posterior part of predefecating larva.
FIGURES 11–14 in Larval Diversity in the Bee Genus Megachile (Hymenoptera: Apoidea: Megachilidae)
FIGURES 11–14. Diagrams of mature larvae of Megachile (Chalicodoma) nigripes. 11, 12. Post- and predefecating larvae, lateral view, respectively. 13, 14. Head, frontal and lateral views, respectively.
FIGURES 1–4 in Larval Diversity in the Bee Genus Megachile (Hymenoptera: Apoidea: Megachilidae)
FIGURES 1–4. Diagrams of mature larvae of mature larvae of Megachile (Eutricharaea) minutissima. 1, 2. Post- and predefecating larvae, lateral view, respectively. Predefecating larva, lateral view. 3, 4. Head, frontal and lateral views, respectively.
Whole genome demographic models indicate divergent effective population size histories shape contemporary genetic diversity gradients in a montane bumble bee
<p>Understanding historical range shifts and population size variation provides important context for interpreting contemporary genetic diversity. Methods to predict changes in species distributions and model changes in effective population size (N<sub>e</sub>) using whole genomes make it feasible to examine how temporal dynamics influence diversity across populations. We investigate N<sub>e</sub> variation and climate-associated range shifts to examine the origins of a previously observed latitudinal heterozygosity gradient in the bumble bee <em>Bombus</em> <em>vancouverensis</em> Cresson (Hymenoptera: Apidae: <em>Bombus</em> Latreille) in western North America. We analyze whole genomes from a latitude-elevation cline using sequentially Markovian coalescent models of N<sub>e</sub> through time to test whether relatively low diversity in southern high-elevation populations is a result of long-term differences in N<sub>e</sub>. We use Maxent models of the species range over the last 130,000 years to evaluate range shifts and stability. N<sub>e</sub> fluctuates with climate across populations, but more genetically diverse northern populations have maintained greater Ne over the late Pleistocene and experienced larger expansions with climatically favorable time periods. Northern populations also experienced larger bottlenecks during the last glacial period which matched the loss of range area near these sites, however, bottlenecks were not sufficient to erode diversity maintained during periods of large N<sub>e</sub>. A genome sampled from an island population indicated a severe postglacial bottleneck, indicating that large recent post-glacial declines are detectable if they have occurred. Genetic diversity was not related to niche stability or glacial-period bottleneck size. Instead, spatial expansions and increased connectivity during favorable climates likely maintain diversity in the north while restriction to high elevations maintains relatively low diversity despite greater stability in southern regions. Results suggest genetic diversity gradients reflect long-term differences in N<sub>e</sub> dynamics and also emphasize the unique effects of isolation on insular habitats for bumble bees. Patterns are discussed in the context of conservation under climate change.</p>
Whole genome demographic models indicate divergent effective population size histories shape contemporary genetic diversity gradients in a montane bumble bee
Open the record for dataset details and reuse information.
Data from: Pesticide and pathogen exposure causes idiosyncratic gene expression responses across four diverse North American bumble bee species
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.