{"refrec":{"BRefID":306725,"RR":"<b>Chevalier, M.</b> (2019). Enabling possibilities to quantify past climate from fossil assemblages at a global scale. <i>Global Planet. Change 175</i>: 27-35. <a href=\"https://dx.doi.org/10.1016/j.gloplacha.2019.01.016\" target=\"_blank\">https://dx.doi.org/10.1016/j.gloplacha.2019.01.016</a>","BEntID":299051,"PublicFlag":1,"CheckedFlag":0,"wosflag":1,"vabbflag":1,"RefStringPartII":". <i>Global Planet. Change 175</i>: 27-35. <a href=\"https://dx.doi.org/10.1016/j.gloplacha.2019.01.016\" target=\"_blank\">https://dx.doi.org/10.1016/j.gloplacha.2019.01.016</a>","DocTypID":8,"DocType":"Journal article","MarineFlag":0,"FreshFlag":0,"BrackishFlag":0,"TerrestrialFlag":0,"Authorstring":"Chevalier, M.","OrigTitleTranslFlag":0,"Authorstringtrunc":"Chevalier, M.","Englishabstract":"The field of quantitative palaeoclimatology has made significant progress in the past decades. However, this progress has been spatially heterogeneous and strong discrepancies – both in terms of quality and density – exist between Europe and North America and the rest of the world. The need to balance this distribution of quantified records has never been stronger, and improving our understanding of past global climate is urgent in order to better evaluate and employ the predictions of climate models. In this paper, it is argued that this gap can be reduced by applying the climate reconstruction method CREST (Climate REconstruction SofTware) calibrated using the open-access GBIF (Global Biodiversity Information Facility) database, which contains hundreds of thousands modern distributions of numerous bio-indicator proxies (e.g. pollen, chironomids, foraminifers, etc.). Using the taxonomical diversity of the GBIF database, CREST can be used to reconstruct various climate and/or environmental parameters from assemblage variety of different records. Independent from the usual reconstruction techniques using surface samples for calibration, the CREST/GBIF framework can also be used as an independent tool that can be easily and efficiently applied (1) to complete the global coverage of climate reconstructions, as exemplified with a precipitation reconstruction from Lake Van, Turkey, (2) to revisit existing data sets to obtain new quantitative reconstructions, and (3) to evaluate and/or refine reconstructions based on other methods. The application of this tool promises to foster advances in our understanding of the past climate variability of the Earth system at a global scale.","AbstractOtherLang":null,"BibLvlCode":"AS","StandardTitle":"Enabling possibilities to quantify past climate from fossil assemblages at a global scale","OrigTitleLangCode":"en","OrigTitleLangCodeExtended":"eng","OrigTitleLangID":15,"DateLastModified":{"date":"2026-05-14 01:32:46.643082","timezone_type":1,"timezone":"+02:00"},"UserAccessRight":null,"UserAccID":null,"AuthorKeywords":"CREST method; GBIF database; Modern distributions; Probability density functions; Palaeoclimate quantification","OtherDescriptors":null,"Notes":null,"AnaPub":2019,"MonPub":null,"DateUpdate":"2019-03-06","DateCreate":"2019-03-06","SecASFANote":null,"ConfID":null,"PeerRev":1,"VlizCoreFlag":1,"WoScode":"WOS:000463982700003","VABBcode":null,"OpenAcc":0,"DOI":"10.1016/j.gloplacha.2019.01.016"},"refs":null,"anarec":{"AnaID":306725,"PubliDate":2019,"Pagination":"27-35","XtraPublOfAnaID":null,"ISBN":null,"Volume":"175","Issue":null,"BRefMon":null,"BRefMonRR":null,"BRefXtra":null,"BRefXtraRR":null,"SerBRefID":42934,"SerRR":"Global and Planetary Change. 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