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Frontiers of Earth Science

ISSN 2095-0195

ISSN 2095-0209(Online)

CN 11-5982/P

邮发代号 80-963

2019 Impact Factor: 1.62

Frontiers of Earth Science  2023, Vol. 17 Issue (4): 1012-1025   https://doi.org/10.1007/s11707-023-1094-6
  本期目录
Holocene temperature variation recorded by branched glycerol dialkyl glycerol tetraethers in a loess-paleosol sequence from the north-eastern Tibetan Plateau
Tianxiao WANG1, Duo WU1(), Tao WANG1, Lin CHEN1, Shilong GUO1, Youmo LI1, Chenbin ZHANG2
1. Key Laboratory of Western China’s Environmental Systems (Ministry of Education), College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, China
2. Alpine Paleoecology and Human Adaptation Group (ALPHA), Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China
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Abstract

Reconstructing Holocene temperature evolution is important for understanding present temperature variations and for predicting future climate change, in the context of global warming. The evolution of Holocene global temperature remains disputed, due to differences between proxy reconstructions and model simulations, a discrepancy known as the ῾Holocene temperature conundrum᾽. More reliable and quantitative terrestrial temperature records are needed to resolve the spatial heterogeneity of existing records. In this study, based on the analysis of branched glycerol dialkyl glycerol tetraethers (brGDGTs) from a loess-paleosol sequence from the Ganjia Basin in the north-eastern Tibetan Plateau (NETP), we quantitatively reconstructed the mean annual air temperature (MAAT) over the past 12 ka. The MAAT reconstruction shows that the temperature remained low during the early Holocene (12−8 ka), followed by a rapid warming at around 8 ka. From 8 to 4 ka, the MAAT record reached its highest level, followed by a cooling trend from the late Holocene (4−0 ka). The variability of the reconstructed MAAT is consistent with trends of annual temperature records from the Tibetan Plateau (TP) during the Holocene. We attribute the relatively low temperatures during the early Holocene to the existence of ice sheets at high-latitude regions in the Northern Hemisphere and the weaker annual mean insolation at 35°N. During the mid to late Holocene, the long-term cooling trend in the annual temperature record was primarily driven by declining summer insolation. This study provides key geological evidence for clarifying Holocene temperature change in the TP.

Key wordsHolocene    Ganjia Basin    loess    temperature variation    BrGDGTs
收稿日期: 2023-05-12      出版日期: 2024-02-06
Corresponding Author(s): Duo WU   
 引用本文:   
. [J]. Frontiers of Earth Science, 2023, 17(4): 1012-1025.
Tianxiao WANG, Duo WU, Tao WANG, Lin CHEN, Shilong GUO, Youmo LI, Chenbin ZHANG. Holocene temperature variation recorded by branched glycerol dialkyl glycerol tetraethers in a loess-paleosol sequence from the north-eastern Tibetan Plateau. Front. Earth Sci., 2023, 17(4): 1012-1025.
 链接本文:  
https://academic.hep.com.cn/fesci/CN/10.1007/s11707-023-1094-6
https://academic.hep.com.cn/fesci/CN/Y2023/V17/I4/1012
Proxy Calculation Referencesx Equation No.
CBT −log[(Ib + IIb + IIb')/(Ia + IIa + IIa')] Weijers et al. (2007) (1)
MBT' (Ia + Ib + Ic)/(Ia + Ib + Ic + IIa + IIa′ + IIb + IIb′ + IIc + IIc′ + IIIa + IIIa′) Peterse et al. (2012) (2)
MBT'5ME (Ia + Ib + Ic)/(Ia + Ib + Ic + IIa + IIb + IIc + IIIa) De Jonge et al. (2014) (3)
MBT5/6 (Ia + Ib + Ic + IIa′)/(Ia + Ib + Ic + IIa + IIb + IIc + IIIa + IIIa′) Ding et al. (2015) (4)
IR6ME (IIa' + IIb' + IIc' + IIIa' + IIIb' + IIIc')/(IIa' + IIb + IIb' + IIc + IIc' + IIIa + IIIa' + IIIb + IIIb' + IIIc + IIIc') Dang et al. (2016) (5)
CI (Ia)/(Ia + IIa + IIIa) De Jonge et al. (2019) (6)
Tab.1  
Material Calculation References Equation No.
Global soils data set MAAT = 0.81−5.67 × CBT + 31.0 × MBT' (n = 176, R2 = 0.59, RMSE = 5.0°C) Peterse et al. (2012) (7)
Global soils data set MAAT = 31.45 × MBT'5ME−8.57 (n = 222, R2 = 0.66, RMSE = 4.8°C) De Jonge et al. (2014) (8)
TP soils data set MAAT = 28.36 × MBT'5ME−10.82 (n = 27, R2 = 0.65, RMSE = 1.8°C) Ding et al. (2015) (9)
TP soils data set MAAT = 39.51 × MBT5/6−20.14 (n = 27, R2 = 0.82, RMSE = 1.3°C) Ding et al. (2015) (10)
China soils data set MAAT = 42.6 × MBT'5ME−21.0 (n = 149, R2 = 0.75, RMSE = 4.3°C) Wang et al. (2020) (11)
Tab.2  
Fig.1  
Fig.2  
Age/ka IR6ME CI Concentration/(ng·g−1) MBT′5ME MBT' MBT5/6 CBT
0.12 0.81 0.30 41.33 0.38 0.11 0.56 0.32
0.91 0.77 0.26 29.77 0.37 0.12 0.63 −0.01
1.80 0.77 0.31 40.01 0.41 0.14 0.67 −0.01
2.85 0.73 0.32 18.90 0.41 0.16 0.65 −0.12
3.75 0.73 0.30 1.91 0.40 0.16 0.56 −0.07
4.67 0.73 0.38 8.11 0.45 0.19 0.63 −0.04
6.57 0.74 0.40 9.43 0.47 0.19 0.66 −0.02
7.44 0.72 0.35 9.53 0.44 0.18 0.60 −0.01
8.36 0.65 0.20 0.08 0.28 0.18 0.38 −0.06
9.39 0.67 0.22 11.73 0.28 0.12 0.47 −0.12
10.30 0.69 0.21 13.12 0.28 0.11 0.50 −0.15
11.23 0.69 0.19 10.87 0.26 0.11 0.50 −0.08
12.15 0.73 0.22 13.17 0.29 0.11 0.48 −0.09
13.02 0.77 0.22 4.06 0.35 0.12 0.44 −0.22
14.04 0.78 0.22 2.45 0.34 0.11 0.42 −0.28
14.94 0.77 0.20 2.97 0.31 0.10 0.38 −0.26
Tab.3  
Fig.3  
Fig.4  
Fig.5  
Fig.6  
Fig.7  
Temperature/°C MAAT (7) MAAT (8) MAAT (9) MAAT (10) MAAT (11)
Modern value 3.44 3.22 3.49 −0.18 −5.02
Maximum 6.80 6.32 6.55 2.61 −0.83
Minimum 2.29 −0.28 −4.91 −3.35 −9.78
Amplitude value 4.51 6.60 11.46 5.96 8.95
Tab.4  
Fig.8  
Fig.9  
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