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Branched Glycerol Dialkyl Glycerol Tetraethers (brGDGTs) from Lake Fazilman, Uzbekistan

Dugerdil, LucasEast China Normal UniversityMénot, GuillemetteÉcole Normale Supérieure de LyonPeyron, OdileUniversité de MontpellierEgamberdieva, DilfuzaCentral Asian UniversityJouffroy-Bapicot, IsabelleUniversité Bourgogne Franche-ComtéVannière, BorisUniversité Bourgogne Franche-ComtéAlimov, JakhongirNational University of UzbekistanLuneau, EliseDeutsches Archäologisches InstitutLhuillier, JohannaLumière University Lyon 2Joannin, SébastienUniversité de Montpellier
ABI

Аннотация

This data table contains the concentration of the major branched Glycerol Dialkyl Glycerol Tetraethers (brGDGTs) of a 227 cm-long core core from Lake Fazilman (Fazilman kul, 40.550406 N, 66.589361 E; 1637 m a.s.l.), collected in July 2021 with a 50 cm Russian corer. Mainly, each sample of one cm³ of sediment, after a 24 hours lyophilization and weighing, was crushed. The total lipid content (TLC) was twice extracted from the sediment with a DCM:MeOH (3:1) solvent extraction catalysed by microwave at 70 °C and under pressure. Then, to separate GDGTs from other lipids, the TLC was filtered on SPE cartridges and concentrated in vials. External C46 GDGTs were added as internal standard in order to estimate the Fazilman GDGTs absolute concentration (Huguet et al., 2006). GDGTs were injected in hexane:iso-propanol (99.8:0.2) solvent for a high performance liquid chromatography mass spectrometry (HPLC-APCI-MS, Agilent 1200) analysis in LGLTPE-ENS de Lyon laboratory. Then each compound was manually integrated using the m/z ratio and relative abundances in order to identify brGDGTs 5-, 6- (De Jonge et al., 2014) and 7-methyls (Ding et al., 2016). Following De Jonge et al. (2014), the Roman numerals represent different GDGT structures. The different 5-, 6- and 7- isomers are given. The data are in fractional abundances. The sample depth is given in centimeters and the age in year calibrated BP (age-depth model performed with BACON and the IntCal20 calibration curve based on 15 radiocarbon dating; Blaauw et al., 2011; Reimer et al., 2020). The data table also contains the climate reconstructions obtains from ensemble modelling based on several linear calibration and Boosted Regression Trees (BRT) machine learning models. For more details on the statistical method, please refer to Dugerdil et al. (in review). The climate parameters correspond to Mean Annual Air Temperature (MAAT, °C), Aridity Index (AI, no unit), Mean Average temperature of months above Freezing (MAF, °C) and the Mean Precipitation of the Colder Quarter (MPCOQ, mm.yr-1).

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