2020
DOI: 10.31223/x5ps3p
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A global Bayesian temperature calibration for lacustrine brGDGTs

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Cited by 18 publications
(61 citation statements)
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“…4). We also apply the global Bayesian calibration for lacustrine brGDGTs, known as BayMBT, using the baymbt_predict() MATLAB function (Martinez-Sosa et al, 2021). Following the approach of Martinez-Sosa et al (2021), we estimated the prior value for our dataset by calculating a mean temperature using the Russell et al (2018)…”
Section: Gdgt Analysismentioning
confidence: 99%
See 1 more Smart Citation
“…4). We also apply the global Bayesian calibration for lacustrine brGDGTs, known as BayMBT, using the baymbt_predict() MATLAB function (Martinez-Sosa et al, 2021). Following the approach of Martinez-Sosa et al (2021), we estimated the prior value for our dataset by calculating a mean temperature using the Russell et al (2018)…”
Section: Gdgt Analysismentioning
confidence: 99%
“…S2, S3). There are currently several lacustrine MBTʹ5ME calibrations that can be applied to reconstruct past temperature (Dang et al, 2018;Russell et al, 2018;Zhao et al, 2020;Martinez-Sosa et al, 2021). The calibration of Dang et al (2018) is based on alkaline lakes, and so is inappropriate to apply at Lake El'gygytgyn, which has a pH of ~6 (Cremer et al, 2005).…”
Section: Interpretation Of the Brgdgt Recordmentioning
confidence: 99%
“…Based on the branched GDGT concentrations, distributions, and isomerization, we conclude that the BayMBT calibration recently produced by Martinez-Sosa et al (2021) provides the most reliable paleotemperature reconstruction from the GDGTs.…”
Section: Brgdgtsmentioning
confidence: 84%
“…Figure S4 shows the raw MBT'5ME data, along with the three lakes-based calibrations discussed in the main text (Martinez-Sosa et al, 2021;Russell et al, 2018;Zhao et al, 2021). As can be seen, the temporal structure of the reconstructions is identical, as all three are based on the MBT'5ME index.…”
Section: Brgdgtsmentioning
confidence: 99%
“…Since the methodological advances that allowed for the separation of 5-and 6-methyl isomers (De Jonge et al, 2014a) and the development of new calibrations, both modern (Hanna et al, 2016;Dang et al, 2018;Cao et al, 2020) and paleo (Super et al, 2018;Thomas et al, 2018;Crump et al, 2019;Harning et al, 2020) studies have continued to support a warm-season bias. Additionally, a recent Bayesian calibration found the mean temperature of Months Above Freezing (MAF) to be the only mode to significantly correlate with brGDGT distributions in a global lake sediment dataset (Martínez-Sosa et al, 2020). However, this warm-season bias has yet to be tested thoroughly in the regions in which it is most pronounced -namely, those with low MAT and high seasonality.…”
Section: Introductionmentioning
confidence: 99%