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dc.contributor.authorSmith, Jansen
dc.contributor.authorRillo, Marina C.
dc.contributor.authorKocsis, Ádám T.
dc.contributor.authorDornelas, Maria
dc.contributor.authorFastovich, David
dc.contributor.authorHuang, Huai-Hsuan M.
dc.contributor.authorJonkers, Lukas
dc.contributor.authorKiessling, Wolfgang
dc.contributor.authorLi, Qijian
dc.contributor.authorLiow, Lee Hsiang
dc.contributor.authorMargulis-Ohnuma, Miranda
dc.contributor.authorMeyers, Stephen
dc.contributor.authorNa, Lin
dc.contributor.authorPenny, Amelia M.
dc.contributor.authorPippenger, Kate
dc.contributor.authorRenaudie, Johan
dc.contributor.authorSaupe, Erin E.
dc.contributor.authorSteinbauer, Manuel J.
dc.contributor.authorSugawara, Mauro
dc.contributor.authorTomašovỳch, Adam
dc.contributor.authorWilliams, John W.
dc.contributor.authorYasuhara, Moriaki
dc.contributor.authorFinnegan, Seth
dc.contributor.authorHull, Pincelli M.
dc.date.accessioned2023-07-26T09:30:08Z
dc.date.available2023-07-26T09:30:08Z
dc.date.issued2023-10-01
dc.identifier291185292
dc.identifier89c7dfac-5539-435b-93f0-d96ca68bd061
dc.identifier85165696672
dc.identifier.citationSmith , J , Rillo , M C , Kocsis , Á T , Dornelas , M , Fastovich , D , Huang , H-H M , Jonkers , L , Kiessling , W , Li , Q , Liow , L H , Margulis-Ohnuma , M , Meyers , S , Na , L , Penny , A M , Pippenger , K , Renaudie , J , Saupe , E E , Steinbauer , M J , Sugawara , M , Tomašovỳch , A , Williams , J W , Yasuhara , M , Finnegan , S & Hull , P M 2023 , ' BioDeepTime : a database of biodiversity time series for modern and fossil assemblages ' , Global Ecology and Biogeography , vol. 32 , no. 10 , pp. 1680-1689 . https://doi.org/10.1111/geb.13735en
dc.identifier.issn1466-822X
dc.identifier.otherRIS: urn:2749FC563AE09C41A06A59F1B42FF4E4
dc.identifier.otherORCID: /0000-0002-4392-8090/work/139552595
dc.identifier.urihttps://hdl.handle.net/10023/28028
dc.descriptionFunding: The authors thank the Paleosynthesis Project and the Volkswagen Stiftung for funding that supported this project (Az 96 796). M.C.R. acknowledges the German Research Foundation (DFG) for funding through the Cluster of Excellence ‘The Ocean Floor – Earth's Uncharted Interface’ (EXC 2077, grant no. 390741603). E.E.S. acknowledges funding from Leverhulme Trust grant RPG-201170, the Leverhulme Prize and the National Science Research Council grant NE/V011405/1. Q.J.L. and L.N. acknowledge support from the Youth Innovation Promotion Association (2019310) and the Chinese Academy of Sciences (CAS-WX2021SF-0205). A.M.P. acknowledges funding from the Leverhulme Trust through research grant RPG-2019-402. M.D. acknowledges funding from Leverhulme Trust through the Leverhulme Centre for Anthropocene Biodiversity (RC-2018-021) and a research grant (RPG-2019-402), and the European Union (ERC coralINT, 101044975). L. H. L. acknowledges funding from the European Research Council (macroevolution.abc ERC grant no. 724324). K.H.P acknowledges funding from the National Science Foundation Graduate Research Fellowship Program (DGE-2139841). H.H.M.H. acknowledges support from Peter Buck Postdoc Fellowship, Smithsonian Institution. A.T. acknowledges funding from the Slovak Research and Development Agency (APVV 22-0523) and the Slovak Scientific Grant Agency (VEGA 02/0106/23).en
dc.description.abstractMotivation We have little understanding of how communities respond to varying magnitudes and rates of environmental perturbations across temporal scales. BioDeepTime harmonizes assemblage time series of presence and abundance data to help facilitate investigations of community dynamics across timescales and the response of communities to natural and anthropogenic stressors. BioDeepTime includes time series of terrestrial and aquatic assemblages of varying spatial and temporal grain and extent from the present-day to millions of years ago. Main Types of Variables Included BioDeepTime currently contains 7,437,847 taxon records from 10,062 assemblage time series, each with a minimum of 10 time steps. Age constraints, sampling method, environment and taxonomic scope are provided for each time series. Spatial Location and Grain The database includes 8752 unique sampling locations from freshwater, marine and terrestrial ecosystems. Spatial grain represented by individual samples varies from quadrats on the order of several cm2 to grid cells of ~100 km2. Time Period and Grain BioDeepTime in aggregate currently spans the last 451 million years, with the 10,062 modern and fossil assemblage time series ranging in extent from years to millions of years. The median extent of modern time series is 18.7 years and for fossil series is 54,872 years. Temporal grain, the time encompassed by individual samples, ranges from days to tens of thousands of years. Major Taxa and Level of Measurement The database contains information on 28,777 unique taxa with 4,769,789 records at the species level and another 271,218 records known to the genus level, including time series of benthic and planktonic foraminifera, coccolithophores, diatoms, ostracods, plants (pollen), radiolarians and other invertebrates and vertebrates. There are to date 7012 modern and 3050 fossil time series in BioDeepTime. Software Format SQLite, Comma-separated values.
dc.format.extent10
dc.format.extent2026378
dc.language.isoeng
dc.relation.ispartofGlobal Ecology and Biogeographyen
dc.subjectDeep-timeen
dc.subjectGlobalen
dc.subjectPalaeobiologyen
dc.subjectSpecies richnessen
dc.subjectTemporalen
dc.subjectTimescaleen
dc.subjectTurnoveren
dc.subjectDASen
dc.subjectSDG 14 - Life Below Wateren
dc.subjectSDG 15 - Life on Landen
dc.subjectMCCen
dc.titleBioDeepTime : a database of biodiversity time series for modern and fossil assemblagesen
dc.typeJournal articleen
dc.contributor.sponsorThe Leverhulme Trusten
dc.contributor.sponsorThe Leverhulme Trusten
dc.contributor.institutionUniversity of St Andrews. School of Biologyen
dc.contributor.institutionUniversity of St Andrews. Centre for Biological Diversityen
dc.contributor.institutionUniversity of St Andrews. Fish Behaviour and Biodiversity Research Groupen
dc.contributor.institutionUniversity of St Andrews. Marine Alliance for Science & Technology Scotlanden
dc.identifier.doihttps://doi.org/10.1111/geb.13735
dc.description.statusPeer revieweden
dc.identifier.grantnumberORPG-8061en
dc.identifier.grantnumberen


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