Late Holocene brGDGTs-based quantitative paleotemperature reconstruction from lacustrine sediments on the western Tibetan Plateau

doi:10.1007/s11707-022-1082-2

2023, Vol. 17

Issue (4) : 997-1011 https://doi.org/10.1007/s11707-022-1082-2

Late Holocene brGDGTs-based quantitative paleotemperature reconstruction from lacustrine sediments on the western Tibetan Plateau

Xiumei LI¹, Sutao LIU¹, Juzhi HOU²(

), Zhe SUN³, Mingda WANG⁴, Xiaohuan HOU², Minghua LIU¹(

), Junhui YAN¹, Lifang ZHANG¹

¹. Henan Key Laboratory for Synergistic Prevention of Water and Soil Environmental Pollution, School of Geographic Sciences, Xinyang Normal University, Xinyang 464000, China
². Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China
³. Institute of Geography and Resources Science, Sichuan Normal University, Chengdu 610066, China
⁴. School of Geography, Liaoning Normal University, Dalian 116029, China

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Abstract

We present a quantitative mean annual air temperature (MAAT) record spanning the past 4700 years based on the analysis of branched glycerol dialkyl glycerol tetraethers (brGDGTs) from a sediment core from Xiada Co, an alpine lake on the western Tibetan Plateau (TP). The record indicates a relatively stable and warm MAAT until 2200 cal yr BP; subsequently, the MAAT decreased by ~4.4°C at ~2100 cal yr BP and maintained a cooling trend until the present day, with centennial-scale oscillations centered at ~800 cal yr BP, ~600 cal yr BP, and ~190–170 cal yr BP. MAAT decreased abruptly at ~500–300 cal yr BP and reached its minimum for the past 4700 years. We assessed the representativeness of our record by comparing it with 15 published paleotemperature records from the TP spanning the past ~5000 years. The results show divergent temperature variations, including a gradual cooling trend, a warming trend, and no clear trend. We suggest that these discrepancies could be caused by factors such as the seasonality of the temperature proxies, the length of the freezing season of the lakes, the choice of proxy-temperature calibrations, and chronological errors. Our results highlight the need for more high-quality paleotemperature reconstructions with unambiguous climatic significance, clear seasonality, site-specific calibration, and robust dating, to better understand the processes, trends, and mechanisms of Holocene temperature changes on the TP.

Keywords Tibetan Plateau lake sediments branched GDGTs paleotemperature

Corresponding Author(s): Juzhi HOU,Minghua LIU

Online First Date: 08 January 2024 Issue Date: 06 February 2024

Cite this article:

Xiumei LI,Sutao LIU,Juzhi HOU, et al. Late Holocene brGDGTs-based quantitative paleotemperature reconstruction from lacustrine sediments on the western Tibetan Plateau[J]. Front. Earth Sci., 2023, 17(4): 997-1011.

URL:

https://academic.hep.com.cn/fesci/EN/10.1007/s11707-022-1082-2
https://academic.hep.com.cn/fesci/EN/Y2023/V17/I4/997

Fig.1 (a) Map showing the sites referenced in the text: Lugu Lake (1), Chongce ice core (2), Tengchongqinghai Lake (3), Xiada Co (4), Hehai Lake (5), Tiancai Lake (6), Guozha Co (7), Bangong Co (8), Hongyuan Peat (9), Aweng Co (10), Guliya ice core (11), Ngamring Co (12), Cuoqia Lake (13), Qinghai Lake (14), Lingge Co (15), Red circles indicate temperature records showing a long-term warming trend, blue circles indicate temperature records showing a long-term cooling trend, and black circles indicate temperature records with no clear trend. (b) Drainage basin of Xiada Co. The sampling site is represented by a red star at the depocenter at 19 m water depth.

Fig.2 Age-depth model for core XDC2014-1 adopted from Li et al. (2019). The ages of the upper 10 cm were determined by ²¹⁰Pb and ¹³⁷Cs dating (Fig. 2(a)), and those of the lower part by AMS ¹⁴C dating (Fig. 2(b)).

Fig.3 (a) Comparison of the fractional abundance of brGDGTs in core XDC2014-1 for Xiada Co (black, this study) with that in soils (purple, Ding et al., 2015) and lake surface sediments (red, Liang et al., 2022) from the Tibetan Plateau. (b) Comparison of the fractional abundances of tetramethylated, pentamethylated, and hexamethylated brGDGTs in the sediments from Xiada Co with lake surface sediments (Liang et al., 2022) and soils (Ding et al., 2015) from the Tibetan Plateau, and globally distributed soils (Naafs et al., 2017).

Tab.1 Formulas used to calculate the brGDGTs indices and calibrations

Fig.4 Comparison of MAAT records for Xiada Co reconstructed using different calibrations: (a) MAAT based on Tibetan Lakes proposed by Liang et al. (2022), which is adopted in this study; (b) MAAT based on Tibetan Lakes proposed by Wang et al. (2016); (c) MAAT based on Tibetan soil proposed by Ding et al.(2015); (d) MAAT based on Tibetan Lakes proposed by Günther et al. (2014); (e) MAAT based on global soils proposed by De Jonge et al. (2014); (f) MAAT based on global soils proposed by Peterse et al. (2012); (g) MAAT based on global soils proposed by Weijers et al. (2007).

Fig.5 Comparison of brGDGTs-based MAAT at Xiada Co (a) with brGDGTs-based MAAT reconstruction for Tengchongqinghai Lake (Zhao et al., 2021) (b); brGDGTs-based MAAT reconstruction for Lugu Lake (Zhao et al., 2021) (c); global temperature reconstructions (Marcott et al., 2013) (d); MAAT reconstructed by a synthesis of fossil pollen records from the TP (Chen et al., 2020) (e); brGDGTs-based temperature reconstruction for Chongce ice core (Pang et al., 2020) (f); brGDGTs-based ice-free-season temperature (from March to October, T_M-O) reconstruction for Cuoqia Lake (Zhang et al., 2022) (g); brGDGTs-based MAAT reconstruction for Ngamring Co (Sun et al., 2022) (h); brGDGTs-based MAAT reconstruction for Aweng Co (Li et al., 2017) (i); brGDGTs-based MAAT reconstruction from the alpine Sahara sand peatland in the southern Altai Mountains (Wu et al., 2020) (j); δ¹⁸O record of the Guliya ice cap (Thompson et al., 1997) (k); brGDGTs-based MAAT reconstruction for Bangong Co (Wang et al., 2021) (l); brGDGTs-based MAAT reconstruction for the Hongyuan peatland (Yan et al., 2021) (m).

Fig.6 Comparison of brGDGTs-based MAAT at Xiada Co (a) with summer temperature reconstructed by a synthesis of fossil pollen records from the TP (Chen et al., 2020) (b); summer temperature inferred from subfossil chironomid assemblages from Heihai Lake (Chang et al., 2017) (c); δ¹⁸O record of Guozha Co (Li et al., 2021b) (d); probability density plot of moraine ages on the TP (Chen et al., 2020) (e); alkenone-based summer temperature for Qinghai Lake (Hou et al., 2016) (f); summer temperature inferred from subfossil chironomid assemblages from Tiancai Lake (Zhang et al., 2017) (g).

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