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Abstract Modeling insect heat exchange and predicting thermal responses depends on accurate representation of body size and shape. Still, most biophysical models approximate these complex forms using simplified geometric solids, whose relationships to real body forms have not been rigorously tested. Advances in surface modeling of small objects allow us to interrogate these assumptions by capturing the real 3D complexity of insect body forms. We used photogrammetry to construct 3D models of honey bee specimens and empirically measured body volume and surface area. Compared to empirical measurements, we found that traditional, geometric size estimation methods systematically underestimate body surface area and volume. We incorporated these error estimates into published heat budget data and found that these errors propagated non-linearly through the model, shifting the relative dominance of convective and radiative heat loss as temperature increases. These results suggest that body size and surface area assumptions can distort modeled heat transfer, particularly under low temperatures, demonstrating that morphological simplifications can bias physiological inference. This work underscores the utility of empirical 3D morphology for refining biophysical models of insect thermoregulation. 

Abstract Bees are one of the most important pollinators in terrestrial ecosystems, supporting biodiversity and food production. However, global knowledge of their interactions with host plants remains limited. To address this, we describe and refine a subset of the Global Biotic Interactions (GloBI) database focused on bee-plant interactions. We updated taxonomy using current checklists and enhanced the dataset with metadata on geography, endemism, and human uses of plants. The resulting dataset includes 981,982 unique interaction records between 5,537 bee species and 12,699 plant taxa. Despite its scale, the dataset is affected by strong taxonomic and geographic biases. It covers only 26% of described bee species and 4% of flowering plant taxa—primarily those used by humans—and is heavily skewed toward North America and Western Europe. Nevertheless, GloBI represents a valuable resource for incorporating bee-plant interactions into biodiversity and conservation-oriented research and represents a considerable advance in our current knowledge. 

Abstract Dynamic coloration is one of the most striking visual displays in the animal kingdom. While reversible colour changes are well characterized in animal communication, more passive effects of climate on baseline coloration remain poorly understood. Here, we present a novel experimental demonstration of reversible, humidity-induced colour change in bees. In controlled lab experiments, we show that relative humidity affects cuticle colour of the sweat bee Agapostemon subtilior, changing dramatically within 24 h from a deep blue-green at low humidity to a pale, coppery green at high humidity. Older specimens experienced greater magnitude colour shifts, suggesting that cuticular degradation may increase water permeability and amplify moisture effects. To understand whether these effects shape colour variation in the wild, we extracted colour data from a large dataset of crowd-sourced field images. We found that ambient humidity weakly predicts colour variation across A. subtilior’s western range, in a manner consistent with the direction of colour change established in lab experiments. While the structural basis for this colour change is still unknown, these shifts are directionally consistent with moisture-induced swelling of multilayer structures that causes reflection of longer wavelengths, a mechanism described in other insects and cephalopods. Together, these results demonstrate that climate modulates structural coloration in bees, emphasizing the role of abiotic conditions in shaping dynamic visual traits. 

{"Abstract":["Last modified: January 09, 2025\n\nIntroductionThis dataset comprises all bee interactions indexed by Global Biotic Interactions (GloBI; Poelen et al. 2014). It is published quarterly by the Big Bee Project (Seltmann et al. 2021) to summarize all available knowledge about bee interactions from natural history collections, community science observations (i.e., iNaturalist), and the literature. Interactions include flower visitation, parasitic interactions (mite, viral), lecty, and many others.\n\nData DescriptionPlease see the integration process page to better understand how Global Biotic Interactions combines datasets from various sources. The complete interaction dataset for all species can be accessed via https://www.globalbioticinteractions.org/data.\n\nData is filtered for unique records based on the interaction description and source citation. Archives contain full data records and unique filtered records in tab-delimited format.\n\nDataset column name definitions https://api.globalbioticinteractions.org/interactionFields or https://api.globalbioticinteractions.org/interactionFields\n\nDuplicate records occur in the database because more than one provider shares information. This is most frequently occuring in museum specimen data and duplicates can be identified evaluating the institutionCode, collectionCode and catalogNumber fields. The file catalogNumber_counts.tsv groups records by these three fields for this dataset, but does not filter out duplicate records. Additionally, this dataset includes the citation information provided by the data publisher. The provided sourceCitation may not include information about the primary provider (often the natural history collection) the specimen data originates and the catalogNumber should be referenced to understand the original source of the data.\n\nIf you know of a missing dataset, or wish to share your dataset, please contact us!\n\n \n\nMetrics\n\n\n\n\nDate\n\n\nTotal bee records\n\n\n\n07-17-2020\n232,906\n\n\n01-24-2021\n257,738\n\n\n11-17-2021\n226,160\n\n\n06-01-2022\n286,818\n\n\n11-07-2022\n429,308\n\n\n01-18-2024\n842,819\n\n\n07-03-2024\n1,109,057\n\n\n01-09-2025\n1,223,768\n\n\n11-25-2025\n2,480,473\n\n\n\n\n \n\n\n\n\nDate\nAndrenidae\nApidae\nColletidae\nHalictidae\n\n\n07-17-2020\n73,463\n106,222\n20,821\n58,880\n\n\n01-24-2021\n77,824\n120,919\n21,376\n63,945\n\n\n11-17-2021\n25,535\n134,517\n10,568\n43,070\n\n\n06-01-2022\n78,016\n144,827\n20,409\n64,054\n\n\n11-07-2022\n84,172\n171,378\n30,792\n79,155\n\n\n01-18-2024\n166,473\n334,224\n63,847\n171,931\n\n\n07-03-2024\n\n\n289,400\n\n\n\n371,953\n\n\n\n83,337\n\n\n\n190,562\n\n\n\n01-09-2025\n\n\n204,565\n\n\n\n686,195\n\n\n\n70,724\n\n\n\n241,856\n\n\n\n11-25-2025\n\n\n269,191\n\n\n\n1,509,768\n\n\n\n129,763\n\n\n\n386,203\n\n\n\n\n\n \n\n\n\n\nDate\nMegachilidae\nMelittidae\nStenotritidae\n\n\n07-17-2020\n44,449\n2,511\n23\n\n\n01-24-2021\n48,856\n2,624\n18\n\n\n11-17-2021\n37,001\n995\n9\n\n\n06-01-2022\n54,516\n2,994\n18\n\n\n11-07-2022\n61,391\n2,396\n24\n\n\n01-18-2024\n100,814\n5,088\n442\n\n\n07-03-2024\n\n\n162,587\n\n\n\n4,964\n\n438\n\n\n01-09-2025\n\n\n126,113\n\n\n\n5,928\n\n441\n\n\n11-25-2025\n\n\n174,935\n\n\n\n9,764\n\n849\n\n\n\n\n \n\nIncluded files\n\n\n\nfilter_and_count_bee_families.sh - script for separating bee records into family and counting number of records for each family\n\ncitation-count.sh - script for counting citations\n\nfamily_counts.tsv - counts by family\n\nglobi-bees-filtered_file.tsv.gz - list of all bee interaction data indexed on Global Biotic Interactions from GloBI version 2025-Nov-25 produced by [filter_and_count_bee_families.sh].\n\ninteractions.tsv.gz - archive of the full Global Biotic Interaction dataset on November 25, 2025. Downloaded from https://www.globalbioticinteractions.org\n\n\n \n\nInteraction Sources\n\nBelow is a list of sources that contributed to this dataset, along with raw counts of unique interactions and links to the corresponding digital archives and reviews. These datasets are indexed and reviewed by Global Biotic Interactions (GloBI) using automated, reproducible workflows that extract species-interaction records, reconcile taxonomic names against authoritative catalogs, and summarize the findings. Each review produces a versioned digital archive to ensure long-term preservation and to document data provenance. For details, see the Methods section within each linked archive.\n\n\n\n\ncount\nsource\n\n\n276746\n\n\n\n\nhttp://iNaturalist.org is a place where you can record what you see in nature, meet other nature lovers, and learn about the natural world.\n\n\n\n\n266822\n\n\n\n\nReji Chacko, M., Albouy, C., Altermatt, F., Brändle, M., Casanelles Abella, J., Boussange, V., Campell, F., Ellis, W. N., Fopp, F., Gossner, M. M., Ho., H., Joss, A., Kipf, P., Neff, F., Petrović, A., Prié, V., Tomanović, Ž., Zimmerli, N., Pellissier, L. (2024). trophiCH v1 - a food web for Switzerland. EnviDat. https://www.doi.org/10.16904/envidat.467.\n\n\n\n\n258683\n\n\n\n\nUSGS Biodiversity Information Serving Our Nation (BISON) IPT\n\n\n\n\n180849\n\n\n\n\necdysis - a portal for live-managing arthropod occurrence data\n\n\n\n\n113301\n\n\n\n\nDigital Bee Collections Network, 2014 (and updates). Version: 2015-03-18. National Science Foundation grant DBI 0956388; PBI: Phytophagous Insects as a Model Group for Documenting Planetary Biodiversity (Insecta: Heteroptera: Miridae: Orthotylinae, Phylinae). Version: 08 Mar 2016. National Science Foundation grant DBI#0316495; Tri-Trophic Thematic Collection Network, 2014 (and updates). Version: 08 Mar 2016. http://tcn.amnh.org/. National Science Foundation grant(s) EF#1115081, EF#1115103, EF#1115080, EF#1115144, EF#1115191, EF#1115104, EF#1115115\n\n\n\n\n112006\n\n\n\n\nUniversity of Kansas Natural History Museum - Snow Entomological Museum Collection\n\n\n\n\n79134\n\n\n\n\nSymbiota Collections of Arthropods Network (SCAN)\n\n\n\n\n62736\n\n\n\n\nFrost Entomological Museum, Pennsylvania State University\n\n\n\n\n49513\n\n\n\n\nLanuza et al. (2025), EuPPollNet: A European Database of Plant-Pollinator Networks. Global Ecol Biogeogr, 34: e70000. https://doi.org/10.1111/geb.70000\n\n\n\n\n41298\n\n\n\n\nBalfour, N.J., Castellanos, M.C., Goulson, D., Philippides, A. and Johnson, C., 2022. DoPI: The Database of Pollinator Interactions. Ecology, 103, e3801.\n\n\n\n\n28517\n\n\n\n\nPaDIL Bee records from the Pests and Diseases Image Library, http://www.padil.gov.au.\n\n\n\n\n27114\n\n\n\n\nGuzman, Laura Melissa; Kelly, Tyler; Elle, Elizabeth, 2022, "A dataset for pollinator diversity and their interactions with plants in the Pacific NorthWest", https://doi.org/10.5683/SP3/WTEZNH, Borealis, V1\n\n\n\n\n24564\n\n\n\n\nUniversity of Michigan Museum of Zoology Insect Division. Full Database Export 2020-11-20 provided by Erika Tucker and Barry Oconner.\n\n\n\n\n23727\n\n\n\n\nCarril OM, Griswold T, Haefner J, Wilson JS. (2018) Wild bees of Grand Staircase-Escalante National Monument: richness, abundance, and spatio-temporal beta-diversity. PeerJ 6:e5867 https://doi.org/10.7717/peerj.5867\n\n\n\n\n18757\n\n\n\n\nA. Thessen. 2014. Species associations extracted from EOL text data objects via text mining.\n\n\n\n\n18003\n\n\n\n\nPensoft Darwin Core Archives available via Integrated Publication Toolkit\n\n\n\n\n17603\n\n\n\n\nDorey, J.B., Fischer, E.E., Chesshire, P.R. et al. A globally synthesised and flagged bee occurrence dataset and cleaning workflow. Sci Data 10, 747 (2023). https://doi.org/10.1038/s41597-023-02626-w\n\n\n\n\n17088\n\n\n\n\nVandame R, Mérida J, Sagot P, Madrigal González D, Bedolla García B Y, González-Vanegas P A, Cultid-Medina C A, Barrios J M (2023). Potential host plant records recovered from ECOAB wild bee collection, Mexico. Version 1.10. Comisión nacional para el conocimiento y uso de la biodiversidad.\n\n\n\n\n15763\n\n\n\n\nSchwarz, Benjamin et al. (2021). Data from: Temporal scale-dependence of plant-pollinator networks [Dataset]. Dryad. https://doi.org/10.5061/dryad.qz612jmbp\n\n\n\n\n10211\n\n\n\n\nPensoft Darwin Core Archives with associateTaxa columns\n\n\n\n\n9104\n\n\n\n\nAmerican Museum of Natural History Hymenoptera\n\n\n\n\n8678\n\n\n\n\nAubouin, L., Genoud, D., Givord-Coupeau, B. et al. BeeFunc, a comprehensive trait database for French bees. Sci Data 12, 1302 (2025). https://doi.org/10.1038/s41597-025-05626-0\n\n\n\n\n8657\n\n\n\n\nWeb of Life. http://www.web-of-life.es .\n\n\n\n\n6600\n\n\n\n\nUniversity of Michigan Museum of Zoology, Division of Insects\n\n\n\n\n6331\n\n\n\n\nAllen-Perkins, Alfonso, Magrach, Ainhoa, Dainese, Matteo, Garibaldi, Lucas A., Kleijn, David, Rader, Romina, Reilly, James R., et al. 2022. "CropPol: A Dynamic, Open and Global Database on Crop Pollination." Ecology 103(3): e3614. https://doi.org/10.1002/ecy.3614\n\n\n\n\n6290\n\n\n\n\nPurdue Entomological Research Collection\n\n\n\n\n6178\n\n\n\n\nRedhead, J.W.; Coombes, C.F.; Dean, H.J.; Dyer, R.; Oliver, T.H.; Pocock, M.J.O.; Rorke, S.L.; Vanbergen, A.J.; Woodcock, B.A.; Pywell, R.F. (2018). Plant-pollinator interactions database for construction of potential networks. NERC Environmental Information Data Centre. https://doi.org/10.5285/6d8d5cb5-bd54-4da7-903a-15bd4bbd531b\n\n\n\n\n5535\n\n\n\n\n@article{Hale_2024, title={A highly resolved network reveals the role of terrestrial herbivory in structuring aboveground food webs}, volume={379}, ISSN={1471-2970}, url={http://dx.doi.org/10.1098/rstb.2023.0180}, DOI={10.1098/rstb.2023.0180}, number={1909}, journal={Philosophical Transactions of the Royal Society B: Biological Sciences}, publisher={The Royal Society}, author={Hale, Kayla R. S. and Curlis, John David and Auteri, Giorgia G. and Bishop, Sasha and French, Rowan L. K. and Jones, Lance E. and Mills, Kirby L. and Scholtens, Brian G. and Simons, Meagan and Thompson, Cody and Tourville, Jordon and Valdovinos, Fernanda S.}, year={2024}, month=jul }\n\n\n\n\n5531\n\n\n\n\nhttps://mangal.io - the ecological interaction database.\n\n\n\n\n5316\n\n\n\n\nClint Otto, Russ Bryant, and Ned H. Euliss Jr., 2020, The U.S. Geological Survey Pollinator Library Dataset: U.S. Geological Survey. https://doi.org/10.5066/P9DSS3VL\n\n\n\n\n4688\n\n\n\n\nUniversity of Colorado Museum of Natural History Entomology Collection\n\n\n\n\n4680\n\n\n\n\nNational Database Plant Pollinators. Center for Plant Conservation at San Diego Zoo Global. Accessed via https://saveplants.org/national-collection/pollinator-search/ on 2020-06-05.\n\n\n\n\n4284\n\n\n\n\nSeltmann, K., Van Wagner, J., Behm, R., Brown, Z., Tan, E., & Liu, K. (2020). BID: A project to share biotic interaction and ecological trait data about bees (Hymenoptera: Anthophila). UC Santa Barbara: Cheadle Center for Biodiversity and Ecological Restoration. Retrieved from https://escholarship.org/uc/item/1g21k7bf\n\n\n\n\n4169\n\n\n\n\nEardley C, Coetzer W. 2016. Catalogue of Afrotropical Bees.\n\n\n\n\n3709\n\n\n\n\nArizona State University Hasbrouck Insect Collection\n\n\n\n\n3619\n\n\n\n\nMaiorano, L., Montemaggiori, A., Ficetola, G.F., O’Connor, L. & Thuiller, W. (2020), Data from: Tetra-EU 1.0: a species-level trophic meta-web of European tetrapods, Dryad, Dataset, https://doi.org/10.5061/dryad.jm63xsj7b hash://md5/40b3d2de829d5f6d98ab71b0b5aa87fd\n\n\n\n\n3547\n\n\n\n\nMycology Collections Data Portal (MyCoPortal). https://mycoportal.org\n\n\n\n\n3140\n\n\n\n\nUniversity of New Hampshire Donald S. Chandler Entomological Collection\n\n\n\n\n3124\n\n\n\n\nCaraDonna, P.J. 2020. Temporal variation in plant-pollinator interactions, Rocky Mountain Biological Laboratory, CO, USA, 2013 - 2015 ver 1. Environmental Data Initiative. https://doi.org/10.6073/pasta/27dc02fe1655e3896f20326fed5cb95f (Accessed 2021-04-16).\n\n\n\n\n3120\n\n\n\n\nLaManna, JA, Burkle, LA, Belote, RT, Myers, JA. Biotic and abiotic drivers of plant–pollinator community assembly across wildfire gradients. J Ecol. 2020; 00: 1– 14. https://doi.org/10.1111/1365-2745.13530 .\n\n\n\n\n3039\n\n\n\n\nOllerton, J., Trunschke, J. ., Havens, K. ., Landaverde-González, P. ., Keller, A. ., Gilpin, A.-M. ., Rodrigo Rech, A. ., Baronio, G. J. ., Phillips, B. J., Mackin, C. ., Stanley, D. A., Treanore, E. ., Baker, E. ., Rotheray, E. L., Erickson, E. ., Fornoff, F. ., Brearley, F. Q. ., Ballantyne, G. ., Iossa, G. ., Stone, G. N., Bartomeus, I. ., Stockan, J. A., Leguizamón, J., Prendergast, K. ., Rowley, L., Giovanetti, M., de Oliveira Bueno, R., Wesselingh, R. A., Mallinger, R., Edmondson, S., Howard, S. R., Leonhardt, S. D., Rojas-Nossa, S. V., Brett, M., Joaqui, T., Antoniazzi, R., Burton, V. J., Feng, H.-H., Tian, Z.-X., Xu, Q., Zhang, C., Shi, C.-L., Huang, S.-Q., Cole, L. J., Bendifallah, L., Ellis, E. E., Hegland, S. J., Straffon Díaz, S., Lander, T. A. ., Mayr, A. V., Dawson, R. ., Eeraerts, M. ., Armbruster, W. S. ., Walton, B. ., Adjlane, N. ., Falk, S. ., Mata, L. ., Goncalves Geiger, A. ., Carvell, C. ., Wallace, C. ., Ratto, F. ., Barberis, M. ., Kahane, F. ., Connop, S. ., Stip, A. ., Sigrist, M. R. ., Vereecken, N. J. ., Klein, A.-M., Baldock, K. ., & Arnold, S. E. J. . (2022). Pollinator-flower interactions in gardens during the COVID-19 pandemic lockdown of 2020. Journal of Pollination Ecology, 31, 87–96. https://doi.org/10.26786/1920-7603(2022)695\n\n\n\n\n2831\n\n\n\n\nRobert L. Minckley San Bernardino Valley from the year 2000 to 2011.\n\n\n\n\n2778\n\n\n\n\nHarvard University M, Morris P J (2021). Museum of Comparative Zoology, Harvard University. Museum of Comparative Zoology, Harvard University.\n\n\n\n\n2252\n\n\n\n\nGiselle Muschett & Francisco E. Fontúrbel. 2021. A comprehensive catalogue of plant – pollinator interactions for Chile\n\n\n\n\n2068\n\n\n\n\nCohen JM, Sauer EL, Santiago O, Spencer S, Rohr JR. 2020. Divergent impacts of warming weather on wildlife disease risk across climates. Science. doi:10.1126/science.abb1702\n\n\n\n\n2038\n\n\n\n\nSarah E. Miller. 07/06/2017. Information extracted from dataset https://www.idigbio.org/portal/recordsets/db4bb0df-8539-4617-ab5f-eb118aa3126b.\n\n\n\n\n1884\n\n\n\n\nInternational Council for the Exploration of the Sea (ICES). Year of The Stomach Datasets.\n\n\n\n\n1815\n\n\n\n\nhttp://gomexsi.tamucc.edu\n\n\n\n\n1812\n\n\n\n\n@article {Keck2025.01.24.634685, author = {Keck, Fran{\\c c}ois and Broadbent, Henry and Altermatt, Florian},title = {Extracting massive ecological data on state and interactions of species using large language models},year = {2025},doi = {10.1101/2025.01.24.634685},journal = {bioRxiv}}\n\n\n\n\n1766\n\n\n\n\nFricke, E.C., Svenning, J. Accelerating homogenization of the global plant–frugivore meta-network. Nature 585, 74–78 (2020). https://doi.org/10.1038/s41586-020-2640-y\n\n\n\n\n1654\n\n\n\n\nKlompen H, Johnson N (2018). Ohio State Acarology Laboratory (OSAL), Ohio State University. Museum of Biological Diversity, The Ohio State University. Accessed via https://mbd-db.osu.edu/hol/taxon_name/05fbf4bb-f8e1-404e-a27c-759d345aa4d0 on 2023-11-06 hash://sha256/fb23140e60f4889de35ae174b2570cf294012bff4f2c8c419c292af51c98c25f\n\n\n\n\n1619\n\n\n\n\nGrundler MC (2020) SquamataBase: a natural history database and R package for comparative biology of snake feeding habits. Biodiversity Data Journal 8: e49943. https://doi.org/10.3897/BDJ.8.e49943\n\n\n\n\n1510\n\n\n\n\nBrose, U. (2018). GlobAL daTabasE of traits and food Web Architecture (GATEWAy) version 1.0 [Data set]. German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig. https://doi.org/10.25829/IDIV.283-3-756\n\n\n\n\n1502\n\n\n\n\nFlorida State Collection of Arthropods\n\n\n\n\n1431\n\n\n\n\nSarah E Miller. 6/19/2015. Species associations manually extracted from datasets https://www.nceas.ucsb.edu/interactionweb/resources.html.\n\n\n\n\n1351\n\n\n\n\nRubinigg M. 2023 Data on economic dependence of pollination by animals in crops as well as observations of pollinators on plant species, inon economic dependence of pollination by animals in crops as well as observations of pollinators on plant species, in particular crops. EU Pollinator Hub. [2025-08-28] app.pollinatorhub.eu\n\n\n\n\n1091\n\n\n\n\nMagrach, Ainhoa et al. (2017), Data from: Plant-pollinator networks in semi-natural grasslands are resistant to the loss of pollinators during blooming of mass-flowering crops, Dryad, Dataset, https://doi.org/10.5061/dryad.k0q1n\n\n\n\n\n1057\n\n\n\n\nSarah E Miller. 4/18/2016. Species associations from Wardeh, M. et al. Database of host-pathogen and related species interactions, and their global distribution. Sci. Data 2:150049 doi: 10.1038/sdata.2015.49 (2015)\n\n\n\n\n1057\n\n\n\n\nWardeh, M., Risley, C., McIntyre, M. et al. Database of host-pathogen and related species interactions, and their global distribution. Sci Data 2, 150049 (2015). https://doi.org/10.1038/sdata.2015.49\n\n\n\n\n958\n\n\n\n\nSarah E Miller. 5/30/2016. Interations from various papers.\n\n\n\n\n945\n\n\n\n\nUniversity of California Santa Barbara Invertebrate Zoology Collection\n\n\n\n\n873\n\n\n\n\nEd Baker; Ian J. Kitching; George W. Beccaloni; Amoret Whitaker et al. (2016). Dataset: NHM Interactions Bank. Natural History Museum Data Portal (data.nhm.ac.uk). https://doi.org/10.5519/0060767\n\n\n\n\n870\n\n\n\n\nDel Risco, A.A., Montoya, Á.M., García, V. et al. Data synthesis and dynamic visualization converge into a comprehensive biotic interaction network: a case study of the urban and rural areas of Bogotá D.C.. Urban Ecosyst (2021). https://doi.org/10.1007/s11252-021-01133-3\n\n\n\n\n857\n\n\n\n\nThe International Barcode of Life Consortium (2016). International Barcode of Life project (iBOL). Occurrence dataset https://doi.org/10.15468/inygc6\n\n\n\n\n762\n\n\n\n\nOllerton J, Liede-Schumann S, Endress ME, Meve U, Rech AR, Shuttleworth A, Keller HA, Fishbein M, Alvarado-Cárdenas LO, Amorim FW, Bernhardt P, Celep F, Chirango Y, Chiriboga-Arroyo F, Civeyrel L, Cocucci A, Cranmer L, da Silva-Batista IC, de Jager L, Deprá MS, Domingos-Melo A, Dvorsky C, Agostini K, Freitas L, Gaglianone MC, Galetto L, Gilbert M, González-Ramírez I, Gorostiague P, Goyder D, Hachuy-Filho L, Heiduk A, Howard A, Ionta G, Islas-Hernández SC, Johnson SD, Joubert L, Kaiser-Bunbury CN, Kephart S, Kidyoo A, Koptur S, Koschnitzke C, Lamborn E, Livshultz T, Machado IC, Marino S, Mema L, Mochizuki K, Morellato LPC, Mrisha CK, Muiruri EW, Nakahama N, Nascimento VT, Nuttman C, Oliveira PE, Peter CI, Punekar S, Rafferty N, Rapini A, Ren ZX, Rodríguez-Flores CI, Rosero L, Sakai S, Sazima M, Steenhuisen SL, Tan CW, Torres C, Trøjelsgaard K, Ushimaru A, Vieira MF, Wiemer AP, Yamashiro T, Nadia T, Queiroz J, Quirino Z. The diversity and evolution of pollination systems in large plant clades: Apocynaceae as a case study. Ann Bot. 2019 Jan 23;123(2):311-325. doi: 10.1093/aob/mcy127. PMID: 30099492; PMCID: PMC6344220.\n\n\n\n\n760\n\n\n\n\nIllinois Natural History Survey Insect Collection\n\n\n\n\n721\n\n\n\n\nPoelen, J. H. (2024). A biodiversity dataset graph: Biological Associations in TaxonWorks hash://sha256/e4a47c067d6c125da60c9a1b92b5eecdea539cb8666cd3aed99db347ae5b8ed0 hash://md5/686007de79cc2a49ab23fd3debe56e3f [Data set]. Zenodo. https://doi.org/10.5281/zenodo.11151783\n\n\n\n\n711\n\n\n\n\nTexas A&M University Insect Collection\n\n\n\n\n703\n\n\n\n\nNatural History Collections managed by Arctos (https://arctosdb.org) accessed via https://vertnet.org .\n\n\n\n\n688\n\n\n\n\nRusso, Laura; Fitzpatrick, Una; Larkin, Michelle et al. (2022). Database of plant-flower visitor interactions from Ireland [Dataset]. Dryad. https://doi.org/10.5061/dryad.kwh70rz47\n\n\n\n\n634\n\n\n\n\nClassen, Alice; Steffan-Dewenter, Ingolf (2020): Plant-pollinator interactions along an elevational gradient on Mt. Kilimanjaro. PANGAEA, https://doi.org/10.1594/PANGAEA.911390\n\n\n\n\n627\n\n\n\n\nA review of the status of web-based African Plant-Pollinator Interaction data.\n\n\n\n\n607\n\n\n\n\nScott L. Gardner and Gabor R. Racz (2021). University of Nebraska State Museum - Parasitology. Harold W. Manter Laboratory of Parasitology. University of Nebraska State Museum.\n\n\n\n\n590\n\n\n\n\nNational Museum of Natural History, Smithsonian Institution IPT RSS Feed\n\n\n\n\n563\n\n\n\n\nRaymond, B., Marshall, M., Nevitt, G., Gillies, C., van den Hoff, J., Stark, J.S., Losekoot, M., Woehler, E.J., and Constable, A.J. (2011) A Southern Ocean dietary database. Ecology 92(5):1188. Available from http://dx.doi.org/10.1890/10-1907.1 . Data set supplied by Ben Raymond.\n\n\n\n\n555\n\n\n\n\nSarah E Miller. 6/22/2015. Species associations manually extracted from datasets https://www.nceas.ucsb.edu/interactionweb/resources.html.\n\n\n\n\n492\n\n\n\n\nRCPol: Online Pollen Catalogs Network. 2016. https://rcpol.org.br/\n\n\n\n\n480\n\n\n\n\nPinnegar, J.K. (2014). DAPSTOM - An Integrated Database & Portal for Fish Stomach Records. Version 4.7. Centre for Environment, Fisheries & Aquaculture Science, Lowestoft, UK. February 2014, 39pp.\n\n\n\n\n459\n\n\n\n\nPardee, G.L., Ballare, K.M., Neff, J.L., Do, L.Q., Ojeda, D., Bienenstock, E.J., Brosi, B.J., Grubesic, T.H., Miller, J.A., Tong, D. and Jha, S., 2023. Local and Landscape Factors Influence Plant-Pollinator Networks and Bee Foraging Behavior across an Urban Corridor. Land, 12(2), p.362. https://www.mdpi.com/2073-445X/12/2/362\n\n\n\n\n437\n\n\n\n\nThe Albert J. Cook Arthropod Research Collection\n\n\n\n\n409\n\n\n\n\nSarah E Miller. 6/25/2015. Species associations manually extracted from Robertson, C. 1929. Flowers and insects: lists of visitors to four hundred and fifty-three flowers. Carlinville, IL, USA, C. Robertson.\n\n\n\n\n384\n\n\n\n\nBoreux, Virginie; Klein, Alexandra-Maria (2019). Global pollinator database. figshare. Dataset. https://doi.org/10.6084/m9.figshare.9980471.v1\n\n\n\n\n334\n\n\n\n\nFroese, R. and D. Pauly. Editors. 2018. FishBase. World Wide Web electronic publication. www.fishbase.org, version (10/2018).\n\n\n\n\n320\n\n\n\n\nHurlbert, A. H., Olsen, A. M., Sawyer, M. M., and Winner, P. M. 2021. Avian Diet Database. https://doi.org/10.5281/zenodo.5151056\n\n\n\n\n296\n\n\n\n\nGlobal Web Database (http://globalwebdb.com): an online collection of food webs. Accessed via https://www.globalwebdb.com/Service/DownloadArchive on 2017-10-12.\n\n\n\n\n290\n\n\n\n\nCalifornia Academy of Sciences Entomology and Entomology Type Collection\n\n\n\n\n290\n\n\n\n\nSarah E Miller. 06/10/2015. Species associations manually extracted from Chamberlin, W. J. The Buprestidae of North America, Exclusive of Mexico, a Catalogue including Synonomy, Bibliography, Distribution, Type Locality and Hosts of Each Species,. 1926.\n\n\n\n\n274\n\n\n\n\nBENSCH, S., HELLGREN, O. and PÉREZ‐TRIS, J. (2009), MalAvi: a public database of malaria parasites and related haemosporidians in avian hosts based on mitochondrial cytochrome b lineages. Molecular Ecology Resources, 9: 1353-1358. https://doi.org/10.1111/j.1755-0998.2009.02692.x\n\n\n\n\n263\n\n\n\n\nCanterbury Museum. (2025). Canterbury Museum (CMNZ) collection insect specimen-plant flower interactions (0.4) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.15429172\n\n\n\n\n263\n\n\n\n\nFood Webs and Species Interactions in the Biodiversity of UK and Ireland (Online). 2017. Data provided by Malcolm Storey. Also available from http://bioinfo.org.uk.\n\n\n\n\n259\n\n\n\n\nhttp://invertebrates.si.edu/parasites.htm\n\n\n\n\n248\n\n\n\n\nWorldFAIR pilot data from: VisitationData_Luisa_Carvalheiro.\n\n\n\n\n246\n\n\n\n\nEneida L. Hatcher, Sergey A. Zhdanov, Yiming Bao, Olga Blinkova, Eric P. Nawrocki, Yuri Ostapchuck, Alejandro A. Schäffer, J. Rodney Brister, Virus Variation Resource – improved response to emergent viral outbreaks, Nucleic Acids Research, Volume 45, Issue D1, January 2017, Pages D482–D490, https://doi.org/10.1093/nar/gkw1065 .\n\n\n\n\n230\n\n\n\n\nUniversity of Hawaii Insect Museum\n\n\n\n\n211\n\n\n\n\nPalomares, M.L.D. and D. Pauly. Editors. 2018. SeaLifeBase. World Wide Web electronic publication. www.sealifebase.org, version (10/2018).\n\n\n\n\n204\n\n\n\n\n@article{Sabino_2022, doi = {10.1016/j.agee.2022.108012}, url = {https://doi.org/10.1016%2Fj.agee.2022.108012}, year = 2022, month = {sep}, publisher = {Elsevier {BV}}, volume = {335}, pages = {108012}, author = {William Sabino and Luciano Costa and Tamires Andrade and Juliana Teixeira and Gustavo Araújo and André Luís Acosta and Luísa Carvalheiro and Tereza Cristina Giannini}, title = {Status and trends of pollination services in Amazon agroforestry systems}, journal = {Agriculture, Ecosystems & Environment}}\n\n\n\n\n181\n\n\n\n\nBrigham Young University Arthropod Museum\n\n\n\n\n179\n\n\n\n\nStokland, J.; Dahlberg, A.; Meyke, E.; Schigel, D.; Siitonen, J. (2006) The Nordic saproxylic database - a comprehensive overview of the biological diversity in dead wood. 1st European Congress of Conservation Biology - "Diversity for Europe". August 2006, Hungary. Book of Abstracts. Society of Conservation Biology (USA) & Blackwell Publishing (UK) p. 159 .\n\n\n\n\n169\n\n\n\n\nUniversity of Wisconsin Stevens Point, Stephen J. Taft Parasitological Collection\n\n\n\n\n164\n\n\n\n\nStephens, P. R., Pappalardo, P. , Huang, S. , Byers, J. E., Farrell, M. J., Gehman, A. , Ghai, R. R., Haas, S. E., Han, B. , Park, A. W., Schmidt, J. P., Altizer, S. , Ezenwa, V. O. and Nunn, C. L. (2017), Global Mammal Parasite Database version 2.0. Ecology, 98: 1476-1476. doi:10.1002/ecy.1799\n\n\n\n\n162\n\n\n\n\nBrose, U. et al., 2005. Body sizes of consumers and their resources. Ecology, 86(9), pp.2545–2545. Available at: https://doi.org/10.1890/05-0379.\n\n\n\n\n159\n\n\n\n\nCruz, G.L.T., Winck, G.R., D’Andrea, P.S. et al. Integrating databases for spatial analysis of parasite-host associations and the novel Brazilian dataset. Sci Data 10, 757 (2023). https://doi.org/10.1038/s41597-023-02636-8\n\n\n\n\n143\n\n\n\n\nYale University Peabody Museum Collections Data Portal\n\n\n\n\n141\n\n\n\n\nWIRC / University of Wisconsin Madison WIS-IH / Wisconsin Insect Research Collection\n\n\n\n\n134\n\n\n\n\nBartomeus, Ignasi (2013): Plant-Pollinator Network Data. figshare. Dataset. https://doi.org/10.6084/m9.figshare.154863.v1\n\n\n\n\n133\n\n\n\n\nSarah E Miller. 12/13/2016. Species associations manually extracted from Onstad, D.W. EDWIP: Ecological Database of the World's Insect Pathogens. Champaign, Illinois: Illinois Natural History Survey, [23/11/2016]. http://insectweb.inhs.uiuc.edu/Pathogens/EDWIP.\n\n\n\n\n128\n\n\n\n\nLlewelyn, J., Strona, G., Dickman, C.R., Greenville, A.C., Wardle, G.M., Lee, M.S.Y., Doherty, S., Shabani, F., Saltré, F. and Bradshaw, C.J.A. (2023), Predicting predator–prey interactions in terrestrial endotherms using random forest. Ecography e06619. https://doi.org/10.1111/ecog.06619\n\n\n\n\n119\n\n\n\n\nSpecies Interactions of Australia Database (SIAD): Helping us to understand species interactions in Australia and beyond. http://www.discoverlife.org/siad/ .\n\n\n\n\n116\n\n\n\n\nField Museum of Natural History IPT\n\n\n\n\n106\n\n\n\n\nGroom, Q.J., Maarten De Groot, M. & Marčiulynienė, D. (2020) Species interation data manually extracted from literature for species .\n\n\n\n\n106\n\n\n\n\nLintulaakso, K., Tatti, N. and Žliobaitė, I., 2023. Quantifying mammalian diets. Mammalian Biology, 103(1), pp.53-67. https://doi.org/10.1007/s42991-022-00323-6\n\n\n\n\n99\n\n\n\n\nMihara, T., Nishimura, Y., Shimizu, Y., Nishiyama, H., Yoshikawa, G., Uehara, H., Hingamp, P., Goto, S., and Ogata, H.; Linking virus genomes with host taxonomy. Viruses 8, 66 doi:10.3390/v8030066 (2016).\n\n\n\n\n92\n\n\n\n\nSan Diego Natural History Museum\n\n\n\n\n79\n\n\n\n\nCarlson, C.J. et al., 2021. The Global Virome in One Network (VIRION): an atlas of vertebrate-virus associations. Available at: http://dx.doi.org/10.1101/2021.08.06.455442\n\n\n\n\n79\n\n\n\n\nCristina Preda and Quentin Groom. 2014. Species associations manually extracted from literature.\n\n\n\n\n72\n\n\n\n\nFaulwetter S, Markantonatou V, Pavloudi C, Papageorgiou N, Keklikoglou K, Chatzinikolaou E, Pafilis E, Chatzigeorgiou G, Vasileiadou K, Dailianis T, Fanini L, Koulouri P, Arvanitidis C (2014) Polytraits: A database on biological traits of marine polychaetes. Biodiversity Data Journal 2: e1024. doi:10.3897/BDJ.2.e1024 . Available at http://polytraits.lifewatchgreece.eu.\n\n\n\n\n62\n\n\n\n\nUS National Museum of Natural History Ixodes Records\n\n\n\n\n60\n\n\n\n\nAlmeida, F. (2005) Trophic Ecology of Atlantic Cod, off Cape Cod, MA, from F/V Riena Marie NEC-FA2001-1 in the Gulf of Maine from 2001-2004 (NEC-CoopRes project). Biological and Chemical Oceanography Data Management Office (BCO-DMO). (Version final) Version Date 2005-10-01 [if applicable, indicate subset used]. http://lod.bco-dmo.org/id/dataset/3087\n\n\n\n\n54\n\n\n\n\nFarr, David F.; Rossman, Amy Y.; Castlebury, Lisa A. (2021). United States National Fungus Collections Fungus-Host Dataset. Ag Data Commons. https://doi.org/10.15482/USDA.ADC/1524414.\n\n\n\n\n53\n\n\n\n\nSoleto-Casas RC and Simões N (2020). Parasitic and commensal invertebrates of echinoderms from American Tropical And Subtropical Atlantic manually extracted from literature.\n\n\n\n\n48\n\n\n\n\nSemantic Prototypes in Research Ecoinformatics (SPIRE). Data provided by Joel Sachs. See also http://ebiquity.umbc.edu/get/a/publication/297.pdf .\n\n\n\n\n45\n\n\n\n\nOlito, Colin; Fox, Jeremy W. (2015), Data from: Species traits and abundances predict metrics of plant–pollinator network structure, but not pairwise interactions, Dryad, Dataset, https://doi.org/10.5061/dryad.7st32\n\n\n\n\n43\n\n\n\n\nPrice Institute of Parasite Research, School of Biological Sciences, University of Utah\n\n\n\n\n40\n\n\n\n\nSarah E Miller. 9/19/2017. Species associations manually extracted from Benesh, D. P., Lafferty, K. D. and Kuris, A. (2017), A life cycle database for parasitic acanthocephalans, cestodes, and nematodes. Ecology, 98: 882. doi:10.1002/ecy.1680\n\n\n\n\n37\n\n\n\n\nPocock, Michael J. O.; Evans, Darren M.; Memmott, Jane (2012), Data from: The robustness and restoration of a network of ecological networks, Dryad, Dataset, https://doi.org/10.5061/dryad.3s36r118\n\n\n\n\n36\n\n\n\n\nQuentin J. Groom. 2020. Species interactions of species on the List of invasive alien species of Union concern\n\n\n\n\n34\n\n\n\n\nSarah E Miller. 6/20/2015. Species associations manually extracted from datasets https://www.nceas.ucsb.edu/interactionweb/resources.html.\n\n\n\n\n32\n\n\n\n\nBallantyne, Gavin; Baldock, Katherine C. R.; Willmer, Pat G. (2015), Data from: Constructing more informative plant-pollinator networks: visitation and pollen deposition networks in a heathland plant community, Dryad, Dataset, https://doi.org/10.5061/dryad.17pp3\n\n\n\n\n31\n\n\n\n\nShaw, LP, Wang, AD, Dylus, D, et al. The phylogenetic range of bacterial and viral pathogens of vertebrates. Mol Ecol. 2020; 29: 3361– 3379. https://doi.org/10.1111/mec.15463\n\n\n\n\n27\n\n\n\n\nMuseum for Southwestern Biology (MSB) Parasite Collection\n\n\n\n\n27\n\n\n\n\nSarah E Miller. 5/17/2016. Wenzel, Rupert L., and Vernon J. Tipton. Appendix: Classified List of Hosts and Parasites. Chicago, Ill.: Field Museum of Natural History, 1966.\n\n\n\n\n26\n\n\n\n\nSarah E Miller. 9/19/2016. Species associations extracted from Graystock, P., Blane, E.J., McFrederick, Q.S., Goulson, D. and Hughes, W.O., 2016. Do managed bees drive parasite spread and emergence in wild bees?. International Journal for Parasitology: Parasites and Wildlife, 5(1), pp.64-75.\n\n\n\n\n23\n\n\n\n\nAgosti, Donat. 2020. Transcription of Linné, C. von, 1758. Systema naturae per regna tria naturae secundum classes, ordines, genera, species, cum characteribus, differentiis, synonymis, locis. Available at: http://dx.doi.org/10.5962/bhl.title.542 .\n\n\n\n\n23\n\n\n\n\nUdy, Kristy; Reininghaus, Hannah; Scherber, Christoph; Tscharntke, Teja (2020), Data from: Plant-pollinator interactions along an urbanization gradient from cities and villages to farmland landscapes, Dryad, Dataset, https://doi.org/10.5061/dryad.4mw6m906s\n\n\n\n\n20\n\n\n\n\nIPBES. (2016). The assessment report of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services on pollinators, pollination and food production. Table 2.4.3 p88 Zenodo. https://doi.org/10.5281/zenodo.3402857\n\n\n\n\n20\n\n\n\n\nSherman, Aja C.; Geiselman, Cullen; Simons, Nancy B.; Upham, Nathan S.; Poelen, Jorrit H.; Reeder, DeeAnn M.; Bertolino, Sandro; Groom, Quentin; Phelps, Kendra; Agosti, Donat; Willoughby, Anna R. In Preparation. Bat-Co-Roosting Database develop by the Biodiversity-related knowledge hub on COVID-19.\n\n\n\n\n19\n\n\n\n\nSeltzer, Carrie; Wysocki, William; Palacios, Melissa; Eickhoff, Anna; Pilla, Hannah; Aungst, Jordan; Mercer, Aaron; Quicho, Jamie; Voss, Neil; Xu, Man; J. Ndangalasi, Henry; C. Lovett, Jon; J. Cordeiro, Norbert (2015): Plant-animal interactions from Africa. figshare. https://dx.doi.org/10.6084/m9.figshare.1526128\n\n\n\n\n18\n\n\n\n\nJakovos Demetriou and Quentin Groom 2014. Species associations of Sceliphron manually extracted from literature.\n\n\n\n\n17\n\n\n\n\nSpecies Connect. https://speciesconnect.com\n\n\n\n\n16\n\n\n\n\nGeiselman, Cullen K. & Sarah Younger. 2020. Bat Eco-Interactions Database. www.batbase.org\n\n\n\n\n14\n\n\n\n\nFabricia Sousa Paz, Carlos Eduardo Pinto, Rafael Melo de Brito, Vera Lucia Imperatriz-Fonseca, Tereza Cristina Giannini, Edible Fruit Plant Species in the Amazon Forest Rely Mostly on Bees and Beetles as Pollinators, Journal of Economic Entomology, Volume 114, Issue 2, April 2021, Pages 710–722, https://doi.org/10.1093/jee/toaa284\n\n\n\n\n14\n\n\n\n\nScientific Committee on Antarctic Research. (2023). SCAR Southern Ocean Diet and Energetics Database (2023-04-04) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.7796465 hash://md5/e41e29d8fb3c2d731f292ec08798cf6b hash://md5/05abf23c0b9e5f4bc721ff407455af0a hash://sha256/7a344b858ab8d1daeca1da49843e8bf957f1116ff9e10a29176ab5c02cb49bef\n\n\n\n\n12\n\n\n\n\nBernice Pauahi Bishop Museum, J. Linsley Gressitt Center for Research in Entomology\n\n\n\n\n12\n\n\n\n\nGaden S. Robinson; Phillip R. Ackery; Ian Kitching; George W Beccaloni; Luis M. Hernández (2023). HOSTS (from HOSTS - a Database of the World's Lepidopteran Hostplants) [Data set resource]. Natural History Museum. https://data.nhm.ac.uk/dataset/hosts/resource/877f387a-36a3-486c-a0c1-b8d5fb69f85a via Natural History Museum (2023). Data Portal query on 1 resources created at 2023-05-24 11:19:42.032183 PID https://doi.org/10.5519/qd.bsucrxdz\n\n\n\n\n12\n\n\n\n\nGandhi, K. J. K., & Herms, D. A. (2009). North American arthropods at risk due to widespread Fraxinus mortality caused by the Alien Emerald ash borer. Biological Invasions, 12(6), 1839–1846. doi:10.1007/s10530-009-9594-1.\n\n\n\n\n12\n\n\n\n\nMeyer R.S., et al., Beach environmental DNA fills gaps in photographic biomonitoring to track spatiotemporal community turnover across 82 phyla. Environmental DNA, submitted June 3, 2019.\n\n\n\n\n10\n\n\n\n\nConsortium of Small Vertebrate Collections\n\n\n\n\n10\n\n\n\n\nLee, Leshon; Tan, David J. X.; Oboňa, Jozef; Gustafsson, Daniel R.; Ang, Yuchen; Meier, Rudolf (2021). Phoresy Records Appendix.xlsx. figshare. Dataset. https://doi.org/10.6084/m9.figshare.12671711.v1\n\n\n\n\n9\n\n\n\n\nC. Anela Choy, Steven H. D. Haddock, Bruce H. Robison. 2017. Deep pelagic food web structure as revealed by in situ feeding observations. Proc. R. Soc. B 2017 284 20172116; DOI:10.1098/rspb.2017.2116.\n\n\n\n\n8\n\n\n\n\nSarah E Miller. 7/6/2016. Arctos collection.\n\n\n\n\n6\n\n\n\n\nGeiselman, Cullen K. and Tuli I. Defex. 2015. Bat Eco-Interactions Database. www.batplant.org\n\n\n\n\n5\n\n\n\n\nNEON Biorepository Portal at Arizona State University (ASU)\n\n\n\n\n4\n\n\n\n\nSarah E Miller. 4/20/2015. Species associations manually extracted from various papers and articles from site https://repository.si.edu\n\n\n\n\n4\n\n\n\n\nSarah E Miller. 5/28/2015. Arnaud, Paul Henri. A Host-parasite Catalog of North American Tachinidae (Diptera). Washington, D.C.: U.S. Dept. of Agriculture, Science and Education Administration, 1978.\n\n\n\n\n4\n\n\n\n\nSarah E Miller. 7/7/2016. Text gathered from Wirta, H.K., Vesterinen, E.J., Hambäck, P.A., Weingartner, E., Rasmussen, C., Reneerkens, J., Schmidt, N.M., Gilg, O. and Roslin, T., 2015. Exposing the structure of an Arctic food web. Ecology and evolution, 5(17), pp.3842-3856.\n\n\n\n\n4\n\n\n\n\nUniversity of California Santa Barbara Herbarium\n\n\n\n\n3\n\n\n\n\nGippet, J.M.W., Bates, O.K., Moulin, J. et al. The global risk of infectious disease emergence from giant land snail invasion and pet trade. Parasites Vectors 16, 363 (2023). https://doi.org/10.1186/s13071-023-06000-y\n\n\n\n\n3\n\n\n\n\nJorrit H. Poelen. 2017. Species interactions associated with known species interaction datasets.\n\n\n\n\n3\n\n\n\n\nMinisterio del Ambiente, Agua y Transición Ecológica de Ecuador - MAATE.\n\n\n\n\n3\n\n\n\n\nSarah E Miller. 9/15/2016. Species associations extracted from http://parasiticplants.siu.edu/index.html.\n\n\n\n\n3\n\n\n\n\nSarah E Miller. 9/3/2015. Species associations manually extracted from JSTOR.\n\n\n\n\n3\n\n\n\n\nSchriml, L. M., Arze, C., Nadendla, S., Ganapathy, A., Felix, V., Mahurkar, A., … Hall, N. (2009). GeMInA, Genomic Metadata for Infectious Agents, a geospatial surveillance pathogen database. Nucleic Acids Research, 38(Database), D754–D764. doi:10.1093/nar/gkp832\n\n\n\n\n2\n\n\n\n\nCarnegie Invertebrate Zoology Collection\n\n\n\n\n2\n\n\n\n\nF. Gabriel. Muñoz. 2017. Palm-Animal frugivore associations extracted from literature with Biodiversity Observations Miner for SouthEast Asia.\n\n\n\n\n2\n\n\n\n\nFerrer-Paris, José R.; Sánchez-Mercado, Ada Y.; Lozano, Cecilia; Zambrano, Liset; Soto, José; Baettig, Jessica; Leal, María (2014): A compilation of larval host-plant records for six families of butterflies (Lepidoptera: Papilionoidea) from available electronic resources. figshare. http://dx.doi.org/10.6084/m9.figshare.1168861\n\n\n\n\n2\n\n\n\n\nInouye, David (2017). An Access database of records collated from the literature about flies pollinating or at least visiting flowers, updated 2017. https://doi.org/10.13016/M2SZ73 http://hdl.handle.net/1903/19193 hash://sha256/a9ab0a6173d34695c85f5fb8947e196478d1253d9d79b0662921ef4e36639c05\n\n\n\n\n2\n\n\n\n\nPaleo Digitization Working Group. Biological associations extracted from fossil specimens.\n\n\n\n\n2\n\n\n\n\nQuentin J. Groom. 2020. Bat interation data manually extracted from literature.\n\n\n\n\n2\n\n\n\n\nSarah E. Miller. 04/14/2015. Extracted from literature Scott, J.A. 1986.  The Butterflies of North America.  Stanford University Press, Stanford, CA\n\n\n\n\n2\n\n\n\n\nStrona, G., Palomares, M. L. D., Bailly, N., Galli, P., & Lafferty, K. D. (2013). Host range, host ecology, and distribution of more than 11 800 fish parasite species. Ecology, 94(2), 544–544. doi:10.1890/12-1419.1\n\n\n\n\n2\n\n\n\n\nStrong, Justin S., and Shawn J. Leroux. 2014. "Impact of Non-Native Terrestrial Mammals on the Structure of the Terrestrial Mammal Food Web of Newfoundland, Canada." PLOS ONE 9 (8): e106264. https://doi.org/10.1371/journal.pone.0106264\n\n\n\n\n2\n\n\n\n\nThessen AE. 2017. Biotic Interactions in Greenland. GloBI. 10.5281/zenodo.266824\n\n\n\n\n1\n\n\n\n\nBourlat SJ, Koch M, Kirse A, Langen K, Espeland M, Giebner H, Decher J, Ssymank A, Fonseca VG (2023) Metabarcoding dietary analysis in the insectivorous bat Nyctalus leisleri and implications for conservation. Biodiversity Data Journal 11: e111146. https://doi.org/10.3897/BDJ.11.e111146\n\n\n\n\n1\n\n\n\n\nCamargo-Sanabria, A.A., Fernández, J.A., Hernández-Quiroz, N.S., Buitrago-Torres, D.L. and Álvarez-Córdova, F. (2025), Ecological Interactions of Terrestrial Mammals in the Chihuahuan Desert: A Systematic Map. Mam Rev e70001. https://doi.org/10.1111/mam.70001\n\n\n\n\n1\n\n\n\n\nDe Rojas M, Doña J, Dimov I (2020) A comprehensive survey of Rhinonyssid mites (Mesostigmata: Rhinonyssidae) in Northwest Russia: New mite-host associations and prevalence data. Biodiversity Data Journal 8: e49535. https://doi.org/10.3897/BDJ.8.e49535\n\n\n\n\n1\n\n\n\n\nDeans, Andrew (2021). Catalog of Rose Gall, Herb Gall, and Inquiline Gall Wasps (Hymenoptera: Cynipidae) of the United States, Canada, and Mexico\n\n\n\n\n1\n\n\n\n\nGunther KA et al. 2014 Dietary breadth of grizzly bears in the Greater Yellowstone Ecosystem. Ursus 25(1):60-72\n\n\n\n\n1\n\n\n\n\nHiveTracks WorldFAIR Test Data.\n\n\n\n\n1\n\n\n\n\nSarah E Miller. 3/4/2015. Species associations manually extracted from http://onlinelibrary.wiley.com/doi/10.1111/j.1474-919X.2009.00907.x/suppinfo.\n\n\n\n\n1\n\n\n\n\nSarah E Miller. 5/21/2015. Text gathered from http://www.biodiversitylibrary.org/\n\n\n\n\n1\n\n\n\n\nVanderweyen A, Fraiture A, Groom Q, Desmet P, Reyserhove L (2019). Catalogue of the Rust Fungi of Belgium. Botanic Garden Meise.\n\n\n\n\n1\n\n\n\n\nVanderweyen, A., & Fraiture, A. (2009). Catalogue des Uredinales de Belgique, 1re partie, Chaconiaceae, Coleosporiaceae, Cronartiaceae, Melampsoraceae, Phragmidiaceae, Pucciniastraceae, Raveneliaceae et Uropyxidaceae. Lejeunia, Revue de Botanique|Vanderweyen, A., & Fraiture, A. (2009). Catalogue des Uredinales de Belgique, 2ème partie, Pucciniaceae (sauf Puccinia)(suite 2). Lejeunia, Revue de Botanique.|Vanderweyen, A., & Fraiture, A. (2012). CATALOGUE DES UREDINALES DE Belgique 3ème partie Pucciniaceae (genre Puccinia). Lejeunia, Revue de Botanique.\n\n\n\n\n1\n\n\n\n\nZeke Marshall. 2021. Species interactions manually extracted from literature.\n\n\n\n\n\n\n \n\nReferences\n\nPoelen JH, Simons JD, Mungall CJ (2014). Global Biotic Interactions: An open infrastructure to share and analyze species-interaction datasets. Ecological Informatics. https://doi.org/10.1016/j.ecoinf.2014.08.005\n\nSeltmann KC, Allen J, Brown BV, Carper A, Engel MS, Franz N, Gilbert E, Grinter C, Gonzalez VH, Horsley P, Lee S, Maier C, Miko I, Morris P, Oboyski P, Pierce NE, Poelen J, Scott VL, Smith M, Talamas EJ, Tsutsui ND, Tucker E (2021) Announcing Big-Bee: An initiative to promote understanding of bees through image and trait digitization. Biodiversity Information Science and Standards 5: e74037. https://doi.org/10.3897/biss.5.74037\n\nPoelen, JS & Seltmann, KS (2024) Bees Only Please: Bees Only Please: Selecting Hundreds of Thousands of Possible Bee Interactions Using a Laptop, Open Datasets, and Small (but Mighty) Commandline Tools. https://www.globalbioticinteractions.org/2024/06/07/bees-only-please\n\nAscher, J. S. and J. Pickering (2020) Discover Life bee species guide and world checklist (Hymenoptera: Apoidea: Anthophila). http://www.discoverlife.org/mp/20q?guide=Apoidea_species.\n\nAcknowledgements\n\nThis project is supported by the National Science Foundation. Award numbers: DBI:2102006, DBI:2101929, DBI:2101908, DBI:2101876, DBI:2101875, DBI:2101851, DBI:2101345, DBI:2101913, DBI:2101891 and DBI:2101850 "],"Other":["Please cite the resources, natural history collections and publications where the data originated as found in uniq_citations.tsv file above. Also, please cite Poelen et. al (above in References) to cite Global Biotic Interactions."]} 

Abstract Wild bees are widely believed to be in decline, yet most species remain unassessed for IUCN extinction risk. Geographic range size is used in risk assessments under the assumption that species with smaller ranges are more vulnerable to anthropogenic impacts. Narrow diet breadth can also increase vulnerability but is not currently incorporated into assessments.Niche breadth theory predicts a positive association between range size and diet breadth, which could concentrate risk among dietary specialists, but this relationship is not well established for bees and may differ among taxa.Here, we combined pollen‐use data from natural history collections with global occurrence records to test the relationship between diet breadth and range size across bees and among bee families. We assigned diet breadth using three metrics (categorical, numerical and phylogenetic) and estimated range size as the extent of occurrence for 633 species from six families.Across bees, range size increased with diet breadth, and diet specialists tended to occupy smaller ranges. These results suggest that range size and diet breadth jointly contribute to increased vulnerability in bees, indicating that some specialist species may merit conservation prioritisation.Our findings support the integration of trait‐based approaches for assessing extinction risk and highlight the high value of natural history data in identifying patterns of vulnerability among pollinators. 

Abstract An animal’s diet breadth is a central aspect of its life history, yet the factors determining why some species have narrow dietary breadths (specialists) and others have broad dietary breadths (generalists) remain poorly understood. This challenge is pronounced in herbivorous insects due to incomplete host plant data across many taxa and regions. Here, we develop and validate machine learning models to predict pollen diet breadth in bees, using a bee phylogeny and occurrence data for 682 bee species native to the United States, aiming to better understand key drivers. We found that pollen specialist bees made an average of 72.9% of their visits to host plants and could be predicted with high accuracy (mean 94%). Our models predicted generalist bee species, which made up a minority of the species in our dataset, with lower accuracy (mean 70%). The models tested on spatially and phylogenetically blocked data revealed that the most informative predictors of diet breadth are plant phylogenetic diversity, bee species’ geographic range, and regional abundance. Our findings also confirm that range size is predictive of diet breadth and that both male and female specialist bees mostly visit their host plants. Overall, our results suggest we can use visitation data to predict specialist bee species in regions and for taxonomic groups where diet breadth is unknown, though predicting generalists may be more challenging. These methods can thus enhance our understanding of plant-pollinator interactions, leading to improved conservation outcomes and a better understanding of the pollination services bees provide. 

Habitat loss is a primary driver of global biodiversity decline, negatively impacting many species, including native bees. One approach to counteract the consequences of habitat loss is through restoration, which includes the transformation of degraded or damaged habitats to increase biodiversity. In this review, we survey bee habitat restoration literature over the last 14 years to provide insights into how best to promote bee diversity and abundance through the restoration of natural landscapes in North America. We highlight relevant questions and concepts to consider throughout the various stages of habitat restoration projects, categorizing them into pre-, during-, and post-restoration stages. We emphasize the importance of planning species- and site-specific strategies to support bees, including providing floral and non-floral resources and increasing nest site availability. Lastly, we underscore the significance of conducting evaluations and long-term monitoring following restoration efforts. By identifying effective restoration methods, success indicators, and areas for future research, our review presents a comprehensive framework that can guide land managers during this urgent time for bee habitat restoration. 

Abstract Climatic factors are known to shape the expression of social behaviours. Likewise, variation in social behaviour can dictate climate responses. Understanding interactions between climate and sociality is crucial for forecasting vulnerability and resilience to climate change across animal taxa.These interactions are particularly relevant for taxa like bees that exhibit a broad diversity of social states. An emerging body of literature aims to quantify bee responses to environmental change with respect to variation in key functional traits, including sociality. Additionally, decades of research on environmental drivers of social evolution may prove fruitful for predicting shifts in the costs and benefits of social strategies under climate change.In this review, we explore these findings to ask two interconnected questions: (a) how does sociality mediate vulnerability to climate change, and (b) how might climate change impact social organisation in bees? We highlight traits that intersect with bee sociality that may confer resilience to climate change (e.g. extended activity periods, diet breadth, behavioural thermoregulation) and we generate predictions about the impacts of climate change on the expression and distribution of social phenotypes in bees.The social evolutionary consequences of climate change will be complex and heterogeneous, depending on such factors as local climate and plasticity of social traits. Many contexts will see an increase in the frequency of eusocial nesting as warming temperatures accelerate development and expand the temporal window for rearing a worker brood. More broadly, climate‐mediated shifts in the abiotic and biotic selective environments will alter the costs and benefits of social living in different contexts, with cascading impacts at the population, community and ecosystem levels. 

Abstract Global declines in bee populations are threatening the ecosystem services they provide, including pollination. Many bee–plant interactions are understudied, producing an incomplete understanding of resulting ecosystem‐level vulnerabilities. The last decade has generated a wealth of opportunistic data originating from natural history collection records, published ecological datasets, and citizen/community science initiatives in online databases such as Global Biotic Interactions (GloBI). Here, we explore hypotheses related to bee–plant interactions and detection processes using the GloBI database, curated checklists of bee and flowering plant species, and an occupancy model. We hypothesized that larger, social bees would visit a larger number of plant species, while smaller, solitary bees would visit fewer. We also predicted that flowers with open, bowl‐like shapes would attract a greater diversity of bee visitors compared to closed shapes. Further, we hypothesized that both floral and bee traits, such as bright colors and conspicuous patterns, would increase detectability, and that different data collection methods would vary in their ability to capture bee–plant interactions. Lastly, we hypothesized that the interaction network generated by the output of the occupancy model, which accounted for imperfect bee–plant detection, would yield more interactions, thereby increasing measures of evenness and decreasing nestedness and specialization, as compared to the network generated from recorded interaction data. We found that smaller bees exhibited higher probabilities of plant interactions than larger bees, but we did not find evidence that bee sociality influenced the probability of interacting with plants. We found that blue flowers and closed (not‐bowl‐shaped) flowers had higher probabilities of bee‐plant interaction than other flower colors or bowl‐shaped flowers, respectively. We also found that larger bee size, blue flowers, bowl shapes, and community science sources were associated with higher detection probabilities of bee–plant interactions. Lastly, the interaction network generated by the occupancy model output showed higher levels of evenness, nestedness, and connectance than the network generated by the GloBI data. Our study is among the first to utilize occupancy modeling to directly model species' interactions, leverage aggregated, open‐source databases and expert checklists, and highlight the influence of detection and collection biases on our understanding of ecological interactions. 

Last modified: July 3, 2024 IntroductionThis dataset comprises all bee interactions indexed by Global Biotic Interactions (GloBI; Poelen et al. 2014). It is published quarterly by the Big Bee Project (Seltmann et al. 2021) to summarize all available knowledge about bee interactions from natural history collections, community science observations (i.e., iNaturalist), and the literature. Interactions include flower visitation, parasitic interactions (mite, viral), lecty, and many others. Data DescriptionPlease see the [integration process page](https://www.globalbioticinteractions.org/process) to better understand how Global Biotic Interactions combines datasets from various sources. The complete interaction dataset for all species can be accessed via https://www.globalbioticinteractions.org/data. Data is filtered for unique records based on the interaction description and source citation. Archives contain full data records and unique filtered records in tab-delimited format. Dataset column name definitions https://api.globalbioticinteractions.org/interactionFields or https://api.globalbioticinteractions.org/interactionFields Duplicate records occur in the database because more than one provider shares information. This is most frequently occuring in museum specimen data and duplicates can be identified evaluating the institutionCode, collectionCode and catalogNumber fields. The file catalogNumber_counts.tsv groups records by these three fields for this dataset, but does not filter out duplicate records. Additionally, this dataset includes the citation information provided by the data publisher. The provided sourceCitation may not include information about the primary provider (often the natural history collection) the specimen data originates and the catalogNumber should be referenced to understand the original source of the data. Summary statistics about the dataset can be found in the bees-only-review.pdf file. This review of all bee data indexed by Global Biotic Interactions was created using GloBI’s Interaction Data Review Report Framework via repository https://github.com/Big-Bee-Network/select-bee-interactions.sh. Metrics Date Total bee records 07-17-2020 232,906 01-24-2021 257,738 11-17-2021 226,160 06-01-2022 286,818 11-07-2022 429,308 01-18-2024 842,819 07-03-2024 1,109,057   Date Andrenidae Apidae Colletidae Halictidae 07-17-2020 73,463 106,222 20,821 58,880 01-24-2021 77,824 120,919 21,376 63,945 11-17-2021 25,535 134,517 10,568 43,070 06-01-2022 78,016 144,827 20,409 64,054 11-07-2022 84,172 171,378 30,792 79,155 01-18-2024 166,473 334,224 63,847 171,931 07-03-2024 289,400 371,953 83,337 190,562   Date Megachilidae Melittidae Stenotritidae 07-17-2020 44,449 2,511 23 01-24-2021 48,856 2,624 18 11-17-2021 37,001 995 9 06-01-2022 54,516 2,994 18 11-07-2022 61,391 2,396 24 01-18-2024 100,814 5,088 442 07-03-2024 162,587 4,964 438   Included Resources count sourceCitation 219440 Symbiota Collections of Arthropods Network (SCAN) 156437 University of Kansas Natural History Museum 150780 Digital Bee Collections Network, 2014 (and updates). Version: 2015-03-18. National Science Foundation grant DBI#0956388 134657 USGS Biodiversity Information Serving Our Nation (BISON) IPT 126820 http://iNaturalist.org is a place where you can record what you see in nature, meet other nature lovers, and learn about the natural world. 44522 PaDIL Bee records from the Pests and Diseases Image Library, http://www.padil.gov.au. 38658 University of Michigan Museum of Zoology Insect Division. Full Database Export 2020-11-20 provided by Erika Tucker and Barry Oconner. 27711 Carril OM, Griswold T, Haefner J, Wilson JS. (2018) Wild bees of Grand Staircase-Escalante National Monument: richness, abundance, and spatio-temporal beta-diversity. PeerJ 6:e5867 https://doi.org/10.7717/peerj.5867 15506 Seltmann, K., Van Wagner, J., Behm, R., Brown, Z., Tan, E., & Liu, K. (2020). BID: A project to share biotic interaction and ecological trait data about bees (Hymenoptera: Anthophila). UC Santa Barbara: Cheadle Center for Biodiversity and Ecological Restoration. Retrieved from https://escholarship.org/uc/item/1g21k7bf 14666 Web of Life. http://www.web-of-life.es . 14577 Pensoft Darwin Core Archives available via Integrated Publication Toolkit 13447 University of Colorado Museum of Natural History Entomology Collection 13296 https://mangal.io - the ecological interaction database. 10705 National Database Plant Pollinators. Center for Plant Conservation at San Diego Zoo Global. Accessed via https://saveplants.org/national-collection/pollinator-search/ on 2020-06-05. 8529 Ollerton, J., Trunschke, J. ., Havens, K. ., Landaverde-González, P. ., Keller, A. ., Gilpin, A.-M. ., Rodrigo Rech, A. ., Baronio, G. J. ., Phillips, B. J., Mackin, C. ., Stanley, D. A., Treanore, E. ., Baker, E. ., Rotheray, E. L., Erickson, E. ., Fornoff, F. ., Brearley, F. Q. ., Ballantyne, G. ., Iossa, G. ., Stone, G. N., Bartomeus, I. ., Stockan, J. A., Leguizamón, J., Prendergast, K. ., Rowley, L., Giovanetti, M., de Oliveira Bueno, R., Wesselingh, R. A., Mallinger, R., Edmondson, S., Howard, S. R., Leonhardt, S. D., Rojas-Nossa, S. V., Brett, M., Joaqui, T., Antoniazzi, R., Burton, V. J., Feng, H.-H., Tian, Z.-X., Xu, Q., Zhang, C., Shi, C.-L., Huang, S.-Q., Cole, L. J., Bendifallah, L., Ellis, E. E., Hegland, S. J., Straffon Díaz, S., Lander, T. A. ., Mayr, A. V., Dawson, R. ., Eeraerts, M. ., Armbruster, W. S. ., Walton, B. ., Adjlane, N. ., Falk, S. ., Mata, L. ., Goncalves Geiger, A. ., Carvell, C. ., Wallace, C. ., Ratto, F. ., Barberis, M. ., Kahane, F. ., Connop, S. ., Stip, A. ., Sigrist, M. R. ., Vereecken, N. J. ., Klein, A.-M., Baldock, K. ., & Arnold, S. E. J. . (2022). Pollinator-flower interactions in gardens during the COVID-19 pandemic lockdown of 2020. Journal of Pollination Ecology, 31, 87–96. https://doi.org/10.26786/1920-7603(2022)695 8014 Redhead, J.W.; Coombes, C.F.; Dean, H.J.; Dyer, R.; Oliver, T.H.; Pocock, M.J.O.; Rorke, S.L.; Vanbergen, A.J.; Woodcock, B.A.; Pywell, R.F. (2018). Plant-pollinator interactions database for construction of potential networks. NERC Environmental Information Data Centre. https://doi.org/10.5285/6d8d5cb5-bd54-4da7-903a-15bd4bbd531b 7630 CaraDonna, P.J. 2020. Temporal variation in plant-pollinator interactions, Rocky Mountain Biological Laboratory, CO, USA, 2013 - 2015 ver 1. Environmental Data Initiative. https://doi.org/10.6073/pasta/27dc02fe1655e3896f20326fed5cb95f (Accessed 2021-04-16). 6921 Purdue Entomological Research Collection 6911 Arizona State University Hasbrouck Insect Collection 6430 LaManna, JA, Burkle, LA, Belote, RT, Myers, JA. Biotic and abiotic drivers of plant–pollinator community assembly across wildfire gradients. J Ecol. 2020; 00: 1– 14. https://doi.org/10.1111/1365-2745.13530 . 6288 Pensoft Darwin Core Archives with associateTaxa columns 6269 Eardley C, Coetzer W. 2016. Catalogue of Afrotropical Bees. 6114 University of Michigan Museum of Zoology, Division of Insects 5089 Magrach, Ainhoa et al. (2017), Data from: Plant-pollinator networks in semi-natural grasslands are resistant to the loss of pollinators during blooming of mass-flowering crops, Dryad, Dataset, https://doi.org/10.5061/dryad.k0q1n 3860 Giselle Muschett & Francisco E. Fontúrbel. 2021. A comprehensive catalogue of plant – pollinator interactions for Chile 3720 Frost Entomological Museum, Pennsylvania State University 3670 Natural History Collections managed by Arctos (https://arctosdb.org) accessed via https://vertnet.org . 3620 Sarah E Miller. 6/19/2015. Species associations manually extracted from datasets https://www.nceas.ucsb.edu/interactionweb/resources.html. 3581 Robert L. Minckley San Bernardino Valley from the year 2000 to 2011. 3581 University of New Hampshire Collection of Insects and other Arthropods UNHC-UNHC 3581 University of New Hampshire Donald S. Chandler Entomological Collection 2242 Sarah E. Miller. 07/06/2017. Information extracted from dataset https://www.idigbio.org/portal/recordsets/db4bb0df-8539-4617-ab5f-eb118aa3126b. 2223 Bartomeus, Ignasi (2013): Plant-Pollinator Network Data. figshare. Dataset. https://doi.org/10.6084/m9.figshare.154863.v1 2110 Illinois Natural History Survey Insect Collection 2074 Florida State Collection of Arthropods 2035 Ed Baker; Ian J. Kitching; George W. Beccaloni; Amoret Whitaker et al. (2016). Dataset: NHM Interactions Bank. Natural History Museum Data Portal (data.nhm.ac.uk). https://doi.org/10.5519/0060767 1762 Poelen, Jorrit H. (2023). A biodiversity dataset graph: Biological Associations in TaxonWorks hash://sha256/a4d651aac5220487835e6178511886e98b845b2d98cb7c5447fb2b042e0654d2 hash://md5/849edbe55e31e54ea5cdaba0188c5655 (0.2) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.8253729 1681 Harvard University M, Morris P J (2021). Museum of Comparative Zoology, Harvard University. Museum of Comparative Zoology, Harvard University. 1563 Ballantyne, Gavin; Baldock, Katherine C. R.; Willmer, Pat G. (2015), Data from: Constructing more informative plant-pollinator networks: visitation and pollen deposition networks in a heathland plant community, Dryad, Dataset, https://doi.org/10.5061/dryad.17pp3 1365 Sarah E Miller. 5/30/2016. Interations from various papers. 1281 Sarah E Miller. 4/18/2016. Species associations from Wardeh, M. et al. Database of host-pathogen and related species interactions, and their global distribution. Sci. Data 2:150049 doi: 10.1038/sdata.2015.49 (2015) 1102 University of California Santa Barbara Invertebrate Zoology Collection 1086 Cohen JM, Sauer EL, Santiago O, Spencer S, Rohr JR. 2020. Divergent impacts of warming weather on wildlife disease risk across climates. Science. doi:10.1126/science.abb1702 939 Allen Hurlbert. 2017. Avian Diet Database. 918 Texas A&M University Insect Collection 906 Del Risco, A.A., Montoya, Á.M., García, V. et al. Data synthesis and dynamic visualization converge into a comprehensive biotic interaction network: a case study of the urban and rural areas of Bogotá D.C.. Urban Ecosyst (2021). https://doi.org/10.1007/s11252-021-01133-3 872 Cristina Preda and Quentin Groom. 2014. Species associations manually extracted from literature. 754 United States Geological Survey (USGS) Pollinator Library. https://www.npwrc.usgs.gov/pollinator. 752 Sarah E Miller. 6/22/2015. Species associations manually extracted from datasets https://www.nceas.ucsb.edu/interactionweb/resources.html. 750 RCPol: Online Pollen Catalogs Network. 2016. https://rcpol.org.br/ 744 Classen, Alice; Steffan-Dewenter, Ingolf (2020): Plant-pollinator interactions along an elevational gradient on Mt. Kilimanjaro. PANGAEA, https://doi.org/10.1594/PANGAEA.911390 704 Yale University Peabody Museum Collections Data Portal 677 The Albert J. Cook Arthropod Research Collection 541 Udy, Kristy; Reininghaus, Hannah; Scherber, Christoph; Tscharntke, Teja (2020), Data from: Plant-pollinator interactions along an urbanization gradient from cities and villages to farmland landscapes, Dryad, Dataset, https://doi.org/10.5061/dryad.4mw6m906s 524 Pardee, G.L., Ballare, K.M., Neff, J.L., Do, L.Q., Ojeda, D., Bienenstock, E.J., Brosi, B.J., Grubesic, T.H., Miller, J.A., Tong, D. and Jha, S., 2023. Local and Landscape Factors Influence Plant-Pollinator Networks and Bee Foraging Behavior across an Urban Corridor. Land, 12(2), p.362. https://www.mdpi.com/2073-445X/12/2/362 511 Sarah E Miller. 6/25/2015. Species associations manually extracted from Robertson, C. 1929. Flowers and insects: lists of visitors to four hundred and fifty-three flowers. Carlinville, IL, USA, C. Robertson. 511 The International Barcode of Life Consortium (2016). International Barcode of Life project (iBOL). Occurrence dataset https://doi.org/10.15468/inygc6 454 Seltzer, Carrie; Wysocki, William; Palacios, Melissa; Eickhoff, Anna; Pilla, Hannah; Aungst, Jordan; Mercer, Aaron; Quicho, Jamie; Voss, Neil; Xu, Man; J. Ndangalasi, Henry; C. Lovett, Jon; J. Cordeiro, Norbert (2015): Plant-animal interactions from Africa. figshare. https://dx.doi.org/10.6084/m9.figshare.1526128 342 Mycology Collections Data Portal (MyCoPortal). 2020. https://mycoportal.org 292 Global Web Database (http://globalwebdb.com): an online collection of food webs. Accessed via https://www.globalwebdb.com/Service/DownloadArchive on 2017-10-12. 268 University of Wisconsin Stevens Point, Stephen J. Taft Parasitological Collection 241 University of Hawaii Insect Museum 168 Sarah E Miller. 12/13/2016. Species associations manually extracted from Onstad, D.W. EDWIP: Ecological Database of the World's Insect Pathogens. Champaign, Illinois: Illinois Natural History Survey, [23/11/2016]. http://insectweb.inhs.uiuc.edu/Pathogens/EDWIP. 153 California Academy of Sciences Entomology and Entomology Type Collection 127 Olito, Colin; Fox, Jeremy W. (2015), Data from: Species traits and abundances predict metrics of plant–pollinator network structure, but not pairwise interactions, Dryad, Dataset, https://doi.org/10.5061/dryad.7st32 114 Kari Lintulaakso. 2023. MammalBase Diet Database. 106 Brose, U. (2018). GlobAL daTabasE of traits and food Web Architecture (GATEWAy) version 1.0 [Data set]. German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig. https://doi.org/10.25829/IDIV.283-3-756 104 Groom, Q.J., Maarten De Groot, M. & Marčiulynienė, D. (2020) Species interation data manually extracted from literature for species . 96 Eneida L. Hatcher, Sergey A. Zhdanov, Yiming Bao, Olga Blinkova, Eric P. Nawrocki, Yuri Ostapchuck, Alejandro A. Schäffer, J. Rodney Brister, Virus Variation Resource – improved response to emergent viral outbreaks, Nucleic Acids Research, Volume 45, Issue D1, January 2017, Pages D482–D490, https://doi.org/10.1093/nar/gkw1065 . 93 Jakovos Demetriou and Quentin Groom 2014. Species associations of Sceliphron manually extracted from literature. 92 San Diego Natural History Museum 80 Price Institute of Parasite Research, School of Biological Sciences, University of Utah 59 National Museum of Natural History, Smithsonian Institution IPT RSS Feed 56 Poelen, JH (2016). Plant pathogen-host interactions scraped from Common Names of Plant Diseases published by the American Phytopathological Society at http://www.apsnet.org/publications/commonnames/Pages/default.aspx using Samara, a Planteome (http://planteome.org) plant-trait scraper. 50 Florez-Montero, G.L., Muylaert, R.L., Nogueira, M.R., Geiselman, C., Santana, S.E., Stevens, R.D., Tschapka, M., Rodrigues, F.A. and Mello, M.A.R. (2022), NeoBat Interactions: A data set of bat–plant interactions in the Neotropics. Ecology. Accepted Author Manuscript e3640. https://doi.org/10.1002/ecy.3640 50 Ferrer-Paris, José R.; Sánchez-Mercado, Ada Y.; Lozano, Cecilia; Zambrano, Liset; Soto, José; Baettig, Jessica; Leal, María (2014): A compilation of larval host-plant records for six families of butterflies (Lepidoptera: Papilionoidea) from available electronic resources. figshare. http://dx.doi.org/10.6084/m9.figshare.1168861 39 Pocock, Michael J. O.; Evans, Darren M.; Memmott, Jane (2012), Data from: The robustness and restoration of a network of ecological networks, Dryad, Dataset, https://doi.org/10.5061/dryad.3s36r118 37 Sarah E Miller. 9/19/2016. Species associations extracted from Graystock, P., Blane, E.J., McFrederick, Q.S., Goulson, D. and Hughes, W.O., 2016. Do managed bees drive parasite spread and emergence in wild bees?. International Journal for Parasitology: Parasites and Wildlife, 5(1), pp.64-75. 36 Mihara, T., Nishimura, Y., Shimizu, Y., Nishiyama, H., Yoshikawa, G., Uehara, H., Hingamp, P., Goto, S., and Ogata, H.; Linking virus genomes with host taxonomy. Viruses 8, 66 doi:10.3390/v8030066 (2016). 36 Quentin J. Groom. 2020. Species interactions of species on the List of invasive alien species of Union concern 33 IPBES. (2016). The assessment report of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services on pollinators, pollination and food production. Table 2.4.3 p88 Zenodo. https://doi.org/10.5281/zenodo.3402857 30 Brigham Young University Arthropod Museum 24 Geiselman, Cullen K. & Sarah Younger. 2020. Bat Eco-Interactions Database. www.batbase.org 24 Geiselman, Cullen K. and Tuli I. Defex. 2015. Bat Eco-Interactions Database. www.batplant.org 23 Agosti, Donat. 2020. Transcription of Linné, C. von, 1758. Systema naturae per regna tria naturae secundum classes, ordines, genera, species, cum characteribus, differentiis, synonymis, locis. Available at: http://dx.doi.org/10.5962/bhl.title.542 . 21 Species Connect. https://speciesconnect.com 17 http://invertebrates.si.edu/parasites.htm 14 Gandhi, K. J. K., & Herms, D. A. (2009). North American arthropods at risk due to widespread Fraxinus mortality caused by the Alien Emerald ash borer. Biological Invasions, 12(6), 1839–1846. doi:10.1007/s10530-009-9594-1. 12 Food Webs and Species Interactions in the Biodiversity of UK and Ireland (Online). 2017. Data provided by Malcolm Storey. Also available from http://bioinfo.org.uk. 12 Sarah E Miller. 5/28/2015. Arnaud, Paul Henri. A Host-parasite Catalog of North American Tachinidae (Diptera). Washington, D.C.: U.S. Dept. of Agriculture, Science and Education Administration, 1978. 10 University of California Santa Barbara Herbarium 9 Field Museum of Natural History IPT 8 Brose, U. et al., 2005. Body sizes of consumers and their resources. Ecology, 86(9), pp.2545–2545. Available at: http://dx.doi.org/10.1890/05-0379. 8 Strong, Justin S., and Shawn J. Leroux. 2014. "Impact of Non-Native Terrestrial Mammals on the Structure of the Terrestrial Mammal Food Web of Newfoundland, Canada." PLOS ONE 9 (8): e106264. https://doi.org/10.1371/journal.pone.0106264 7 Chen L, Liu B, Wu Z, Jin Q, Yang J, 2017. DRodVir: A resource for exploring the virome diversity in rodents. J Genet Genomics. 44(5):259-264. 5 Froese, R. and D. Pauly. Editors. 2018. FishBase. World Wide Web electronic publication. www.fishbase.org, version (10/2018). 5 Pinnegar, J.K. (2014). DAPSTOM - An Integrated Database & Portal for Fish Stomach Records. Version 4.7. Centre for Environment, Fisheries & Aquaculture Science, Lowestoft, UK. February 2014, 39pp. 4 Aja Sherman, Cullen Geiselman. 2021. Bat Co-Roosting Database 4 Bernice Pauahi Bishop Museum, J. Linsley Gressitt Center for Research in Entomology 4 Mollentze, Nardus, & Streicker, Daniel G. (2019). Viral zoonotic risk is homogenous among taxonomic orders of mammalian and avian reservoir hosts (Version 1.0.0) [Data set]. Zenodo. http://doi.org/10.5281/zenodo.3516613 4 Sarah E Miller. 7/7/2016. Text gathered from Wirta, H.K., Vesterinen, E.J., Hambäck, P.A., Weingartner, E., Rasmussen, C., Reneerkens, J., Schmidt, N.M., Gilg, O. and Roslin, T., 2015. Exposing the structure of an Arctic food web. Ecology and evolution, 5(17), pp.3842-3856. 4 Sarah E Miller. 9/15/2016. Species associations extracted from http://parasiticplants.siu.edu/index.html. 4 Sarah E. Miller. 04/14/2015. Extracted from literature Scott, J.A. 1986.  The Butterflies of North America.  Stanford University Press, Stanford, CA 4 Scott L. Gardner and Gabor R. Racz (2021). University of Nebraska State Museum - Parasitology. Harold W. Manter Laboratory of Parasitology. University of Nebraska State Museum. 2 Deans, Andrew (2021). Catalog of Rose Gall, Herb Gall, and Inquiline Gall Wasps (Hymenoptera: Cynipidae) of the United States, Canada, and Mexico 2 Jorrit H. Poelen. 2017. Species interactions associated with known species interaction datasets. 2 Museum for Southwestern Biology (MSB) Parasite Collection 2 Sarah E Miller. 4/20/2015. Species associations manually extracted from various papers and articles from site https://repository.si.edu 2 Seltmann, Katja C. 2020. Biotic species interactions about ticks manually extracted from literature. 2 Species Interactions of Australia Database (SIAD): Helping us to understand species interactions in Australia and beyond. http://www.discoverlife.org/siad/ . 1 Chen L, Liu B, Yang J, Jin Q, 2014. DBatVir: the database of bat-associated viruses. Database (Oxford). 2014:bau021. doi:10.1093/database/bau021 1 Grundler MC (2020) SquamataBase: a natural history database and R package for comparative biology of snake feeding habits. Biodiversity Data Journal 8: e49943. https://doi.org/10.3897/BDJ.8.e49943 1 Gunther KA et al. 2014 Dietary breadth of grizzly bears in the Greater Yellowstone Ecosystem. Ursus 25(1):60-72 1 Sarah E Miller. 7/6/2016. Arctos collection. Included files bee_data_BID.sh - script for separating bee records into family uniq_citations.tsv - list of unique citations indicating bee interactions Andrenidae_data_unique.tsv - Andrenidae records     Apidae_data_unique.tsv - Apidae records         Colletidae_data_unique.tsv - Colletidae records Halictidae_data_unique.tsv - Halictidae records     Megachilidae_data_unique.tsv - Megachilidae records     Melittidae_data_unique.tsv - Melittidae records Stenotritidae_data_unique.tsv - Stenotritidae records bees-only-interactions.tsv.zip - list of all bee interaction data indexed on Global Biotic Interactions from GloBI version 2024-06-07 produced by https://github.com/Big-Bee-Network/select-bee-interactions.sh bees-only-review.pdf - Review of all bee data indexed by Global Biotic Interactions using GloBI’s Interaction Data Review Report Framework via repository https://github.com/Big-Bee-Network/select-bee-interactions.sh catalogNumber_counts.tsv - counts by catalogNumber in dataset. Duplicate catalog numbers indicate duplicated data shared by multiple data providers. ReferencesGloBI Community. (2024). Global Biotic Interactions: Interpreted Data Products hash://md5/946f7666667d60657dc89d9af8ffb909 hash://sha256/4e83d2daee05a4fa91819d58259ee58ffc5a29ec37aa7e84fd5ffbb2f92aa5b8 (0.7) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.11552565. Poelen JH, Simons JD, Mungall CJ (2014). Global Biotic Interactions: An open infrastructure to share and analyze species-interaction datasets. Ecological Informatics. https://doi.org/10.1016/j.ecoinf.2014.08.005 Seltmann KC, Allen J, Brown BV, Carper A, Engel MS, Franz N, Gilbert E, Grinter C, Gonzalez VH, Horsley P, Lee S, Maier C, Miko I, Morris P, Oboyski P, Pierce NE, Poelen J, Scott VL, Smith M, Talamas EJ, Tsutsui ND, Tucker E (2021) Announcing Big-Bee: An initiative to promote understanding of bees through image and trait digitization. Biodiversity Information Science and Standards 5: e74037. https://doi.org/10.3897/biss.5.74037 Poelen, JS & Seltmann, KS (2024) Bees Only Please: Bees Only Please: Selecting Hundreds of Thousands of Possible Bee Interactions Using a Laptop, Open Datasets, and Small (but Mighty) Commandline Tools. https://www.globalbioticinteractions.org/2024/06/07/bees-only-please Ascher, J. S. and J. Pickering (2020) Discover Life bee species guide and world checklist (Hymenoptera: Apoidea: Anthophila). http://www.discoverlife.org/mp/20q?guide=Apoidea_species. Acknowledgements This project is supported by the National Science Foundation. Award numbers: DBI:2102006, DBI:2101929, DBI:2101908, DBI:2101876, DBI:2101875, DBI:2101851, DBI:2101345, DBI:2101913, DBI:2101891 and DBI:2101850