Climate reconstructions based on GDGTs and pollen surface datasets from Mongolia and Siberia: Calibrations and applicability to extremely dry and cold environments

• Main Authors: Dugerdil, Lucas, Joannin, Sébastien, Peyron, Odile, Jouffroy-Bapicot, Isabelle, Vannière, Boris, Boldgiv, Bazartseren, Ménot, Guillemette
• Format: Text
• Language: English
• Published: 2020
• Subjects: taiga; Siberia
• Online Access: https://doi.org/10.5194/bg-2019-475; https://www.biogeosciences-discuss.net/bg-2019-475/

Our understanding of climate and vegetation changes throughout the Holocene is hampered by biases in the proxy representativeness in sedimentary archives. Such potential biases are identified by comparing proxies to modern environments. Consequently, it becomes important to conduct multi-proxy studies and robust calibrations. The taiga-steppes of the Mongolian plateau, ranging from the extremely cold-dry Baikal basin to the Gobi desert, are characterized by low annual precipitation and continental annual air temperature as well as livestock grazing. The characterization of the climate system of this area is crucial for the understanding of Holocene Monsoon Oscillations. This study focuses on the calibration of proxy-climate relationships for pollen and glycerol dialkyl glycerol tetraethers (GDGTs) by comparing large published Eurasian calibrations with a set of 53 new surface samples (moss, soil and surface sediments). We show that: (1) preserved pollen assemblages are clearly imprinted on the extremities of the ecosystem range but mitigated and unclear on the ecotones; (2) for both proxies, inferred relationships depend on the geographical range covered by the calibration database as well as on the sample nature; (3) local calibrations, even those derived to the low range of climate parameters encompassed in the study area, better reconstruct climatic parameters than the global ones by reducing the limits for saturation impact, and (4) a bias in climatic reconstructions is induced by the over-parameterization of the models by addition of artificial correlation. We encourage the application of this surface calibration method to consolidate our understanding of the Holocene climate and environment variations.