TY - JOUR
T1 - BayMBT
T2 - A Bayesian calibration model for branched glycerol dialkyl glycerol tetraethers in soils and peats
AU - Dearing Crampton-Flood, Emily
AU - Tierney, Jessica E.
AU - Peterse, Francien
AU - Kirkels, Frédérique M.S.A.
AU - Sinninghe Damsté, Jaap S.
N1 - Funding Information:
The work was supported by funding from the Netherlands Earth System Science Center ( NESSC ) through a gravitation grant (NWO 024.002.001) from the Dutch Ministry for Education, Culture and Science to JSSD and co-PIs. JET was supported by National Science Foundation grant EAR-1603674. FP acknowledges funding from ETH Fellowship FEL-36 11-1 (New Zealand soil), NWO Veni grant 863.13.016 (Indian soils), and KNAW China Exchange Program grant 530-6CDP17 (Chinese soils). We would like to thank Sebastian Breitenbach (Ruhr-University Bochum) for soil collection in Siberia. Thanks to Tian Ma and Jingjing Guo ( Institute of Botany, Chinese Academy of Sciences ) for help with extractions of the Chinese soils. We would also like to thank the associate editor and the contribution of three anonymous reviewers whose comments greatly improved the manuscript.
Funding Information:
The work was supported by funding from the Netherlands Earth System Science Center (NESSC) through a gravitation grant (NWO 024.002.001) from the Dutch Ministry for Education, Culture and Science to JSSD and co-PIs. JET was supported by National Science Foundation grant EAR-1603674. FP acknowledges funding from ETH Fellowship FEL-36 11-1 (New Zealand soil), NWO Veni grant 863.13.016 (Indian soils), and KNAW China Exchange Program grant 530-6CDP17 (Chinese soils). We would like to thank Sebastian Breitenbach (Ruhr-University Bochum) for soil collection in Siberia. Thanks to Tian Ma and Jingjing Guo (Institute of Botany, Chinese Academy of Sciences) for help with extractions of the Chinese soils. We would also like to thank the associate editor and the contribution of three anonymous reviewers whose comments greatly improved the manuscript.
Publisher Copyright:
© 2019 The Author(s)
PY - 2020/1/1
Y1 - 2020/1/1
N2 - Accurate temperature records for the deep geological past are a vital component of paleoclimate research. Distributional changes of branched glycerol dialkyl glycerol tetraether (brGDGT) lipids in geological archives including paleosoils are a promising indicators to infer past continental air temperatures. However, the ‘orphan’ status of the brGDGTs, the potential effect of temperature-independent parameters on their relative distribution, and the uneven geographical distribution of the soils used for calibration contribute to the high uncertainty of brGDGT-based transfer functions (root mean squared error, RMSE: ±5 °C). Here, we expand the soil dataset from the previous calibration(s) with new and published soil data. We use Bayesian statistics to calibrate the relationship of the 5-methyl brGDGTs (MBT′5Me) and mean annual air temperature (MAAT). The addition of soils from warm (>28 °C) environments from India substantially increases the upper limit of the Bayesian calibration (BayMBT) from 25 to 29 °C, aiding in the generation of temperature records for past greenhouse climates, such as the Eocene. The BayMBT model also effectively minimizes the structured MAAT residuals prevalent in previous calibrations, therefore giving the opportunity to explore confounding factors on the calibration. We formulate a set of alternative calibration models to test the effect of specific environmental parameters and show that soils at mid-latitudes with temperature seasonalities >20 °C are not well described by the BayMBT model. We find that the MBT′5Me index is best correlated to the average temperature of all months >0 °C, called the BayMBT0 model. This finding supports the hypothesis that brGDGT production ceases or slows down in the winter months. However, a persistent feature of the BayMBT model and previous calibrations is the significant scatter at mid-latitudes, which is speculatively linked with a possible increase in diversity of microbial brGDGT-producing communities in these locations.
AB - Accurate temperature records for the deep geological past are a vital component of paleoclimate research. Distributional changes of branched glycerol dialkyl glycerol tetraether (brGDGT) lipids in geological archives including paleosoils are a promising indicators to infer past continental air temperatures. However, the ‘orphan’ status of the brGDGTs, the potential effect of temperature-independent parameters on their relative distribution, and the uneven geographical distribution of the soils used for calibration contribute to the high uncertainty of brGDGT-based transfer functions (root mean squared error, RMSE: ±5 °C). Here, we expand the soil dataset from the previous calibration(s) with new and published soil data. We use Bayesian statistics to calibrate the relationship of the 5-methyl brGDGTs (MBT′5Me) and mean annual air temperature (MAAT). The addition of soils from warm (>28 °C) environments from India substantially increases the upper limit of the Bayesian calibration (BayMBT) from 25 to 29 °C, aiding in the generation of temperature records for past greenhouse climates, such as the Eocene. The BayMBT model also effectively minimizes the structured MAAT residuals prevalent in previous calibrations, therefore giving the opportunity to explore confounding factors on the calibration. We formulate a set of alternative calibration models to test the effect of specific environmental parameters and show that soils at mid-latitudes with temperature seasonalities >20 °C are not well described by the BayMBT model. We find that the MBT′5Me index is best correlated to the average temperature of all months >0 °C, called the BayMBT0 model. This finding supports the hypothesis that brGDGT production ceases or slows down in the winter months. However, a persistent feature of the BayMBT model and previous calibrations is the significant scatter at mid-latitudes, which is speculatively linked with a possible increase in diversity of microbial brGDGT-producing communities in these locations.
KW - Bayesian statistics
KW - Paleothermometry
KW - brGDGTs
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U2 - 10.1016/j.gca.2019.09.043
DO - 10.1016/j.gca.2019.09.043
M3 - Article
AN - SCOPUS:85073551731
VL - 268
SP - 142
EP - 159
JO - Geochmica et Cosmochimica Acta
JF - Geochmica et Cosmochimica Acta
SN - 0016-7037
ER -