{"Abstract":["Stomach contents of fishes (1977-1981) and stable isotopes of fishes, invertebrates, and basal resources (1994) were collected from spikerush marsh, sawgrass ridge, and alligator pond habitats in Shark River Slough, Everglades National Park, Florida, USA. These data were used to quantify diet, trophic niche area, trophic position, basal resource use and how these metrics vary among size classes, seasons, and habitats. Data collection is complete. These data support Flood et al. (2023). Associated R code will be made available through Peter Flood's GitHub: https://github.com/pjflood/historic_everglades_aquatic_food_web. \n References:\n Flood, Peter J., William F. Loftus, and Joel C. Trexler. "Fishes in a seasonally pulsed wetland show spatiotemporal shifts in diet and trophic niche but not shifts in trophic position." Food Webs 34 (2023): e00265. https://doi.org/10.1016/j.fooweb.2022.e00265"]}
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Stable isotope values of consumers, producers, and organic matter in the Shark River Slough and Taylor Slough, Everglades National Park (FCE LTER), Florida, USA, 2019 – ongoing
{"Abstract":["Wetland food webs have often been characterized as detrital-based ‘brown’ energy pyramids, whereas the relative role of autotrophic (‘green’) vs. microbial (‘brown’) energy sources falls along a continuum set by physical drivers, as well as autochthonous and allochthonous inputs (Moore et al. 2004; Evans-White & Halvorson 2017) that change with ecosystem development (Schmitz et al. 2006). In the Florida Coastal Everglades (FCE), metabolic imbalances, including the collapse of calcareous periphyton mats, begin with a loss of foundation species primary production and legacy organic matter (Gaiser et al. 2006). This process likely enhances heterotrophic microbial productivity (Schulte 2016) and the supply of detrital energy to consumers by changing bioavailable and recalcitrant carbon supplies (Baggett et al. 2013). A shift from complex periphyton communities to transient planktonic communities under elevated P exposure reduces habitat structure and animal refuges but increases ‘green’ energy supplies and edibility (Trexler et al. 2015; Naja et al. 2017). Multiple sites (n=9) within the FCE were selected to document changes in coastal food webs as a result of eutrophication and increasing hydrologic variability. The project began in 2019 and is currently ongoing.\n \n References:\n Baggett, L. P., Heck, K. L., Frankovich, T. A., Armitage, A. R., & Fourqurean, J. W. (2013). Stoichiometry, growth, and fecundity responses to nutrient enrichment by invertebrate grazers in sub-tropical turtle grass (Thalassia testudinum) meadows. Marine biology, 160, 169-180.\n Evans-White, M. A., and H. M. Halvorson. 2017. Comparing the Ecological Stoichiometry in Green and Brown Food Webs – A Review and Meta-analysis of Freshwater Food Webs. Frontiers in Microbiology 8:1184. \n Gaiser, E. E., Childers, D. L., Jones, R. D., Richards, J. H., Scinto, L. J., & Trexler, J. C. (2006). Periphyton responses to eutrophication in the Florida Everglades: cross‐system patterns of structural and compositional change. Limnology and Oceanography, 51(1part2), 617-630.\n Moore, J. C., E. L. Berlow, D. C. Coleman, P. C. Ruiter, Q. Dong, A. Hastings, N. C. Johnson, K. S. McCann, K. Melville, P. J. Morin, K. Nadelhoffer, A. D. Rosemond, D. M. Post, J. L. Sabo, K. M. Scow, M. J. Vanni, and D. H. Wall. 2004. Detritus, trophic dynamics and biodiversity: Detritus, trophic dynamics and biodiversity. Ecology Letters 7:584–600. \n Naja, M., Childers, D. L., & Gaiser, E. E. (2017). Water quality implications of hydrologic restoration alternatives in the Florida Everglades, United States. Restoration Ecology, 25, S48-S58.\n Schmitz, O. J., Kalies, E. L., & Booth, M. G. (2006). Alternative dynamic regimes and trophic control of plant succession. Ecosystems, 9, 659-672.\n Schulte, Nicholas O., "Controls on Benthic Microbial Community Structure and Assembly in a Karstic Coastal Wetland" (2016). FIU Electronic Theses and Dissertations. 2447. 10.25148/etd.FIDC000233\n Trexler, J. C., Gaiser, E. E., Kominoski, J. S., & Sanchez, J. (2015). The role of periphyton mats in consumer community structure and function in calcareous wetlands: lessons from the Everglades. Microbiology of the everglades ecosystem, 155-179."]}
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- PAR ID:
- 10643722
- Publisher / Repository:
- Environmental Data Initiative
- Date Published:
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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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:2101850more » « less
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ESCHER (Exploration of Saline Cryospheric Habitats with Europa Relevance) is a NASA funded PSTAR (Planetary Science and Technology from Analog Research) program with the general geophysical goals of characterizing the subglacial environment of Devon Ice Cap in Nunavut, Canada as a potential planetary analog. The project seeks to gather additional evidence for unique chemistry in the subglacial hydrological system and to further the technical development of the scientific instrumentation. ESCHER represents the first field deployment of a multi-polarization radar system on an A-Star 350 B2 helicopter platform. This is the sixth polar deployment of this helicopter geophysical system, and the first in the arctic. The previous helicopter-based systems expeditions were KRT1, KRT2, ASE2, ASE3, ASE4. Similar results for ASE3 are described in Pierce et al, 2023, and Pierce et al, 2024. The science goals include characterizing the subglacial environment from the summit of Devon Ice Cap to Sverdrup Glacier’s marine termination. The study area includes three linked geographical regions: i) The summit area where Rutishauser et al. (2020), presented further evidence for the existence of fluid at the base of Devon Ice Cap; ii) the shoulder region of the ice cap, just upstream of the ice flow that enters the outlet valleys of Fox and Sverdrup Glaciers. This region includes the hypothesized distributed hydrological system that transitions into channelized geometry, and iii) The Sverdrup/Fox valley glaciers, tidewater terminus, and locations of subglacial discharge. The study region also includes the upper catchment of the Crocker Bay Glaciers and some of the western land terminating flanks of the ice cap. All data in this collection is derived from a multipolarization version of the Helicopter Radar (HERA) system (Lindzey et al., 2017, 2022). Included in this dataset are the Level 2 time registered geophysical observables for the specific lines mentioned in Pierce et al., (2024); ice thickness, partial bed reflectivity, surface reflectivity, bed and surface elevation derived both from incoherent processing (IR2HI2) and focused processing (IRFOC2; Peters et al., 2007); no multipolarization processing is included here. Also included is specularity content (IRSPC2; Schroeder et al., 2014, Young et al, 2016). Data consists of ASCII tab delimited tables, with header describing the columns and key metadata on a per transect basis. Images showing simple maps of values are also included. The following transects are included: DEV3/PER0a/Y79a DEV3/PER0a/Y80a DEV3/PER0a/Y81a DEV3/PER0a/Y82a DEV3/PER0a/Y83a DEV3/PER0a/Y84a DEV3/PER0a/Y85a DEV3/PER0a/Y86a DEV3/PER0a/Y87a References: Pierce, C., 2024, Advanced Analysis of the Sub-Glacial Environment Using Radar Echo Sounding Simulations, Ph. D. Thesis, Montana State University Pierce, C., Gerekos, C., Skidmore, M., Beem, L., Blankenship, D., Lee, W. S., Adams, E., Lee, C.-K., and Stutz, J., 2024, Characterizing sub-glacial hydrology using radar simulations, The Cryosphere, 18, 4, 1495--1515, 10.5194/tc-18-1495-2024 Pierce, C., Skidmore, M., Beem, L., Blankenship, D., Adams, E., and Gerekos, C., 2024, Exploring canyons beneath Devon Ice Cap for sub-glacial drainage using radar and thermodynamic modeling, Journal Of Glaciology, 1--18, 10.1017/jog.2024.49 Lindzey, L., Quartini, E., Buhl, D., Blankenship, D., Richter, T., Greenbaum, J., and Young, D., 2017, KRT1/LGV1 Season Field Report, 237 10.26153/tsw/11620 Lindzey, L. E., Beem, L. H., Young, D. A., Quartini, E., Blankenship, D. D., Lee, C.-K., Lee, W. S., Lee, J. I., and Lee, J., 2020, Aerogeophysical characterization of an active subglacial lake system in the David Glacier catchment, Antarctica, The Cryosphere, 14, 7, 2217--2233, 10.5194/tc-14-2217-2020 Peters, M. E., Blankenship, D. D., Carter, S. P., Young, D. A., Kempf, S. D., and Holt, J. W., 2007, Along-track Focusing of Airborne Radar Sounding Data From West Antarctica for Improving Basal Reflection Analysis and Layer Detection, IEEE Transactions On Geoscience And Remote Sensing, 45, 9, 2725-2736, 10.1109/TGRS.2007.897416Rutishauser, A., Blankenship, D. D., Young, D. A., Wolfenbarger, N. S., Beem, L. H., Skidmore, M. L., Dubnick, A., and Criscitiello, A. S., 2022, Radar sounding survey over Devon Ice Cap indicates the potential for a diverse hypersaline subglacial hydrological environment, The Cryosphere, 16, 379-395, https://doi.org/10.5194/tc-16-379-2022 Schroeder, D. M., Blankenship, D. D., Raney, R. K., and Grima, C., 2015, Estimating subglacial water geometry using radar bed echo specularity: application to Thwaites Glacier, West Antarctica, IEEE Geoscience And Remote Sensing Letters, 12, 3, 443-447, 10.1109/LGRS.2014.2337878 Young, D. A., Schroeder, D. M., Blankenship, D. D., Kempf, S. D., and Quartini, E., 2016, The distribution of basal water between Antarctic subglacial lakes from radar sounding, Philosophical Transactions Of The Royal Society A, 374, 20140297, 1-21, 10.1098/rsta.2014.0297more » « less
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As the climate warms and dry periods become more extreme, shallow groundwater discharge is generally becoming a less reliable source of streamflow while deep groundwater discharge remains a more resilient source. The implications of shifts in the relative balance of shallow and deep groundwater discharge sources are profound in gaining streams. These different sources exert critical controls on stream temperature and water quality as influenced by legacy groundwater contaminant transport. Groundwater discharge flux rates over time were used for the inference of source groundwater characteristics to prominent riverbank groundwater discharge faces along the mainstem Farmington River, CT USA. To estimate groundwater discharge rates, we deployed sediment temperature loggers (iButton #DS1922L, Maxim Integrated, Inc., San Jose, CA, USA) in vertical profilers installed directly into mapped preferential groundwater discharge points across extensive riverbank discharge face features.Temperature data contained in this release were collected from June 24 to November 5, 2020, at 40 distinct discharge point riverbank locations, similar to those described by Barclay et al. (2022) and Briggs et al. (2022). Saturated sediment thermal conductivity and heat capacity were measured in-situ with a TEMPOS Thermal Property Analyzer (TEMPOS, Meter Group, Inc., Pullman, WA, USA) at multiple points across each riverbank discharge face to aid in estimating groundwater discharge flux rates. Barclay, J. R., Briggs, M. A., Moore, E. M., Starn, J. J., Hanson, A. E. H., & Helton, A. M. (2022). Where groundwater seeps: Evaluating modeled groundwater discharge patterns with thermal infrared surveys at the river-network scale. Advances in Water Resources, 160. https://doi.org/10.1016/j.advwatres.2021.104108 Briggs, M. A., Jackson, K. E., Liu, F., Moore, E. M., Bisson, A., & Helton, A. M. (2022). Exploring Local Riverbank Sediment Controls on the Occurrence of Preferential Groundwater Discharge Points. Water, 14(1). https://doi.org/10.3390/w14010011more » « less
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