南海北部31 ka以来GDGTs组成及其对古温度和季风变化的响应

刘磊; 管红香; 冯俊熙; 许兰芳; 茅晟懿; 刘丽华

doi:10.16562/j.cnki.0256-1492.2020021101

南海北部31 ka以来GDGTs组成及其对古温度和季风变化的响应

1.
中国科学院广州能源研究所，中国科学院天然气水合物研究重点实验室，广州 510640

2.
中国科学院大学，北京 100049

3.
中国地质调查局广州海洋地质调查局，广州 510760

基金项目: 国家自然科学基金项目“南海北部陆坡不同矿物组分冷泉碳酸盐岩”（91958105）；青岛海洋科学与技术国家实验室开放基金“冷泉区双壳和管状蠕虫环境中自生碳酸盐岩的有机地球化学对比研究”（QNLM2016ORP0210）；广州市科技计划项目“南海北部神狐钻探区自生黄铁矿形成机制及其指示意义” (201804010372)

详细信息

作者简介: 刘磊（1993—），男，硕士研究生，主要研究方向为海洋地质，E-mail：sc170130@mail.ustc.edu.cn

通讯作者: 管红香（1981—），女，副研究员，主要研究方向为冷泉碳酸盐岩的地质地球化学特征，E-mail：guanhx@ms.giec.ac.cn

中图分类号: P736.4

收稿日期: 2020-02-11

修回日期: 2020-03-31

刊出日期: 2020-06-25

Composition of glycerol dibiphytanyl glycerol tetraethers (GDGTs) and its responses to paleotemperature and monsoon changes since 31ka in northern South China Sea

1.
Key Lab of Renewable Energy and Gas Hydrate, Guangzhou Institute of Energy Conversion, Chinese Academy of Sciences, Guangzhou 510640, China

2.
University of Chinese Academy of Sciences, Beijing 100049, China

3.
Guangzhou Marine Geological Surveys, Guangzhou 510760, China

More Information

Corresponding author: GUAN Hongxiang, guanhx@ms.giec.ac.cn

Received Date: 11 February 2020

Revised Date: 31 March 2020

Publish Date: 25 June 2020

摘要

摘要:
南海因受到高纬度气候、低纬度大洋以及东亚季风等多种因素的影响而成为研究古温度和季风变化的理想区域。本文通过研究QH-CL11柱状沉积物的GDGTs组成、含量变化特征及其延伸的86个碳原子的四醚指标（TEX^H₈₆），分析南海北部GDGTs来源，并定量计算QH-CL11柱状沉积物记录的海洋表面温度（SST），从而探讨31 ka以来南海北部古温度变化的驱动机制。通过甲烷指数和支链/异戊二烯类指标等，确定isoGDGTs主要来自于奇古菌，适用于古温度重建。TEX^H₈₆温度显示出明显的冰期—间冰期旋回，与南海北部有孔虫和U^K’₃₇ SSTs具有很好的相似性。出现在TEX^H₈₆ SST中的海因里希冷事件（H1-3）和Bølling–Allerød暖期之前的温度大幅度上升事件（14.6 ka）反映了高纬度气候对南海的影响。南海SSTs和北太平洋MD01-2421 U^K’₃₇ SST的差异（ΔSSTs）可以用来反映东亚冬季风强度的变化。ΔSSTs显示东亚冬季风强度在Bølling–Allerød暖期前增加，在新仙女木时期达到最大值，在全新世早期再次下降，然后在全新世中晚期缓慢增加，这与前人对东亚冬季风强度的认识具有很好的一致性。该方法对重建长周期东亚冬季风强度具有重要的指导意义。
- 异戊二烯甘油二烷基甘油四醚类 /
- TEX^H₈₆ /
- 海洋表面温度 /
- 东亚冬季风强度 /
- 南海北部
Abstract:
The South China Sea (SCS), under the control of multiple climate patterns, is an ideal region for studies of paleo-climate and the East Asian monsoon. In this paper, we studied the composition and characteristics of isoGDGTs to further identify their sources and used the outspread TEX^H₈₆ index to reconstruct the sea surface temperature (SST) of the northern SCS for the past 31 ka quantificationally. By calculating the Methane Index and BIT indexes, we found that the isoGDGTs mainly came from Thaumarchaeota, and are suitable for TEX^H₈₆ appliance. TEX^H₈₆ temperatures exhibit distinct glacial–interglacial cycles, and is very similar to the SSTs from foraminifera and U^K'₃₇ in the northern SCS. TEX^H₈₆ SSTs showed a decline trend during the Heinrich events (H1-3) and an abrupt rise at 14.6 kaBP before Bølling–Allerød (BA) warming, suggesting a tight climate teleconnection between the northern SCS and the North Atlantic region in last Deglaciation. The SST differences (ΔSSTs) between the SCS and the core MD01-2421 in the North Pacific was calculated and used to reveal the intensity of East Asian Winter monsoon. ΔSSTs showed that the EAWM intensity firstly increased before the BA warming, reached a maximum in the Younger Dryas period, decreased again in early Holocene and slowly increased in Late and Middle Holocene. The ∆SSTs results coincide with previous findings on the EAWM variations and constitute a feasible means of long-term EAWM intensity reconstruction.

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图 1 南海北部QH-CL11沉积柱及对比站位位置图^[11]

Figure 1.

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图 2 南海北部17940、17954和MD997-2146沉积柱U^K’₃₇数据及MATLAB拟合的平均U^K’_{37 north}温度^{[9, 17]}

Figure 2.

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图 3 QH-CL11柱状沉积物年代模型

Figure 3.

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图 4 QH-CL11中检测到的GDGTs的相对含量。Crenarchaeol' 表示Crenarchaeol异构体

Figure 4.

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图 5 （a）南海北部U^K’_{37 north} SST和（b）QH-CL11 TEX^H₈₆温度，以及（c）U^K’_{37 north} SST与QH-CL11 TEX^H₈₆温度之间的差值（夏季、冬季及年平均SST来自19740站位的有孔虫数据^[16]）

Figure 5.

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图 6 （a）沉积柱QH-CL11的TEX^H₈₆数据和U^K’_{37 north} SST投图；（b）QH-CL11和 MD97-2146平均后的TEX^H₈₆数据（AVETEX^H₈₆）和U^K’_{37 north} SST投图^{[9, 12, 25]}

Figure 6.

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图 7 （a）QH-CL11的沉积速率，（b）QH-CL11的支链/异戊二烯指标BIT，（c）GISP2冰心δ¹⁸O记录^[46]，（d）QH-CL11 TEX^H₈₆ SST

Figure 7.

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图 8 （a）董哥洞δ¹⁸O记录^[2]，（b）湖光岩湖Ti含量记录^[5]，（c）QH-CL11 TEX^H₈₆ SST与MD01-2421 U^K’₃₇ SST的差值^[47]，（d）U^K’_{37 north} SST与MD01-2421 U^K’₃₇ SST的差值^[9,17,47]，（e）MD97-2151 U^K’₃₇ SST与MD01-2421 U^K’₃₇ SST的差值^[47-48]，（f）MD97-2151 U^K’₃₇ SST与QH-CL11 TEX^H₈₆ SST的差值^[48]

Figure 8.

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表 1 文中用到的指标的定义式

Table 1. Initial definitions of the proxies used in this article.

指标定义	合理范围	来源
		[28]
	＞15 ℃	[32]
	＜15 ℃	[32]
	＜0.4	[36]
	＜0.3	[37]
	＜45	[38]
GDGT-0/ Crenarchaeol	＜2	[39]
GDGT-0/ Crenarchaeol	＜0.4	[40]

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表 2 研究区年平均及季节变化海温数据

Table 2. Annual mean and seasonal SST data in the study area

冬季温度/ ℃	春季温度/ ℃	夏季温度/ ℃	秋季温度/ ℃	年平均温度/ ℃
24.3	26.7	29.1	27.5	26.9
注：所有数据都是在0 m水深观测，数据来源于World Ocean Atlas 2013。

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表 3 南海北部QH-CL11沉积柱有孔虫AMS¹⁴C年龄

Table 3. ¹⁴C-AMS ages from core QH-CL11 in the northern South China Sea（SCS）

实验室编号	深度/（cmbsf ^a）	有孔虫种类	¹⁴C测定年龄/aBP	校正后年龄/aBP
526367	2～5	G.ruber + G.sacculifer	200 ±30	0～71
524755	62～65	G.ruber + G.sacculifer	3 450 ±30	3 174～3 426
526368	182～185	G.ruber + G.sacculifer	8 710 ±30	92 43～9 469
524758	242～245	G.ruber + G.sacculifer	11 100 ±30	12 530～12 710
524759	302～305	G.ruber + G.sacculifer	12 650±30	13 950～14 305
524760	362～365	G.ruber + G.sacculifer	13 410±30	15 745～15 306
526370	482～485	G.ruber + G.sacculifer	18 890±60	22 132～22 523
526371	542～545	G.ruber + G.sacculifer	22 500±70	26 045～26 543
526372	602～605	G.ruber + G.sacculifer	24 820±90	28 160～28 715
524765	672～675	G.ruber + G.sacculifer	28 080±120	31 160～31 649
注：^a 海底以下以厘米为单位的深度。

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表 4 文中收集的古温度和古环境数据来源与信息

Table 4. Sources of paleotemperature and paleoenvironment data collected in the paper

名称	纬度（°N）	经度（°E）	数据类型	来源
GISP2冰心	72.970	−38.800	δ¹⁸O [‰ SMOW]	[46]
董哥洞	25.283	108.083	δ¹⁸O [‰ VPDB]	[2]
湖光岩湖	21.250	110.472	Ti [counts·s⁻¹]	[5]
MD01-2421	36.033	141.783	U^K’₃₇	[47]
17940	20.117	117.383	U^K’₃₇	[17]
MD97-2146	20.117	117.385	U^K’₃₇/TEX^H₈₆	[9, 12, 25]
17954	14.797	111.525	U^K’₃₇	[17]
MD97-2151	8.728	109.869	U^K’₃₇	[48]

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表 5 南海北部QH-CL11柱状沉积物中各指标及TEX^H₈₆ SST数据

Table 5. The indices used to evaluate the application of TEX₈₆ and TEX^H₈₆ SST in core QH-CL11

编号	深度/ cmbsf	年龄/ ka	甲烷指数MI	GDGT-0/ Crenarchaeol	GDGT-2/ Crenarchaeol	%GDGT-2	BIT	TEX^H₈₆	TEX^H₈₆ SST/ ℃
190438	1	0.01	0.21	0.44	0.14	39.8	0.026	−0.180	26.3
190439	11	0.44	0.19	0.40	0.12	38.2	0.019	−0.184	26.0
190440	21	0.99	0.19	0.37	0.12	37.8	0.018	−0.192	25.5
190441	31	1.53	0.19	0.39	0.13	38.4	0.024	−0.174	26.7
190442	41	2.08	0.20	0.37	0.13	40.5	0.017	−0.175	26.6
190443	61	3.16	0.19	0.39	0.13	40.8	0.023	−0.178	26.5
190444	71	3.83	0.20	0.40	0.13	39.8	0.029	−0.172	26.9
190445	81	4.54	0.19	0.37	0.12	39.7	0.021	−0.178	26.5
190446	91	5.25	0.19	0.35	0.13	38.9	0.028	−0.174	26.7
190447	101	5.96	0.20	0.39	0.14	39.9	0.029	−0.175	26.6
190448	121	7.38	0.21	0.39	0.14	40.8	0.021	−0.176	26.6
190449	131	7.78	0.18	0.34	0.12	39.4	0.019	−0.165	27.3
190450	141	8.08	0.19	0.33	0.13	41.3	0.017	−0.157	27.8
190451	151	8.39	0.19	0.35	0.13	39.9	0.016	−0.170	26.9
190452	161	8.69	0.19	0.36	0.13	41.0	0.014	−0.171	26.9
190453	181	9.29	0.18	0.36	0.12	40.2	0.017	−0.174	26.7
190454	191	9.76	0.19	0.37	0.13	40.2	0.018	−0.180	26.3
190455	201	10.31	0.19	0.36	0.13	40.8	0.016	−0.175	26.6
190456	211	10.85	0.19	0.38	0.13	40.3	0.016	−0.178	26.4
190457	221	11.40	0.20	0.41	0.13	40.7	0.016	−0.184	26.0
190458	241	12.48	0.20	0.50	0.12	41.4	0.019	−0.209	24.3
190459	251	12.80	0.17	0.41	0.10	38.7	0.016	−0.216	23.8
190460	261	13.05	0.19	0.43	0.12	40.5	0.021	−0.206	24.5
190461	271	13.30	0.19	0.42	0.11	38.7	0.017	−0.209	24.3
190462	281	13.56	0.20	0.45	0.12	39.5	0.015	−0.216	23.8
190463	301	14.06	0.18	0.48	0.11	39.9	0.014	−0.214	24.0
190464	311	14.30	0.21	0.58	0.13	39.9	0.013	−0.234	22.6
190465	321	14.54	0.19	0.54	0.11	39.4	0.015	−0.234	22.6
190466	331	14.77	0.19	0.58	0.10	39.0	0.014	−0.256	21.1
190467	341	15.00	0.19	0.60	0.11	39.8	0.023	−0.243	22.0
190468	361	15.47	0.19	0.59	0.10	39.3	0.021	−0.257	21.0
190469	371	16.09	0.19	0.57	0.10	37.7	0.025	−0.254	21.2
190470	381	16.85	0.18	0.55	0.10	37.6	0.030	−0.267	20.3
190471	391	17.60	0.18	0.57	0.10	36.9	0.027	−0.259	20.9
190472	401	18.36	0.17	0.53	0.09	36.4	0.022	−0.252	21.4
190473	421	19.86	0.19	0.54	0.11	40.3	0.023	−0.231	22.8
190474	431	20.34	0.20	0.54	0.11	39.1	0.023	−0.243	22.0
190475	441	20.72	0.16	0.49	0.08	36.9	0.023	−0.258	20.9
190476	451	21.10	0.18	0.54	0.10	37.9	0.025	−0.252	21.3
190477	461	21.48	0.18	0.56	0.10	39.1	0.022	−0.252	21.4
190478	481	22.24	0.19	0.54	0.10	35.2	0.016	−0.228	23.0
190479	491	22.82	0.20	0.60	0.12	38.7	0.018	−0.247	21.7
190480	501	23.48	0.19	0.53	0.10	38.4	0.021	−0.246	21.7
190481	511	24.14	0.20	0.60	0.12	39.6	0.022	−0.238	22.3
190482	521	24.80	0.18	0.51	0.10	38.2	0.022	−0.235	22.5
190483	541	26.12	0.17	0.51	0.10	36.0	0.024	−0.205	24.6
190484	551	26.55	0.18	0.51	0.10	36.0	0.020	−0.231	22.8
190485	561	26.91	0.19	0.52	0.11	37.8	0.023	−0.241	22.1
190486	571	27.26	0.20	0.52	0.12	40.7	0.022	−0.219	23.6
190487	581	27.62	0.19	0.54	0.11	36.4	0.028	−0.222	23.4
190488	601	28.33	0.18	0.53	0.10	36.2	0.022	−0.238	22.3
190489	611	28.76	0.19	0.52	0.11	38.2	0.019	−0.217	23.7
190490	621	29.19	0.19	0.58	0.10	36.4	0.028	−0.239	22.2
190491	631	29.61	0.19	0.54	0.10	37.4	0.022	−0.249	21.6
190492	641	30.04	0.20	0.58	0.11	38.0	0.029	−0.237	22.4
190493	661	30.88	0.20	0.58	0.11	39.1	0.027	−0.240	22.2
190494	671	31.31	0.19	0.50	0.11	38.3	0.024	−0.212	24.1
190495	681	31.67	0.20	0.57	0.12	40.4	0.024	−0.229	23.0

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南海北部31 ka以来GDGTs组成及其对古温度和季风变化的响应

1. 中国科学院广州能源研究所，中国科学院天然气水合物研究重点实验室，广州 510640 2. 中国科学院大学，北京 100049 3. 中国地质调查局广州海洋地质调查局，广州 510760

作者简介: 刘磊（1993—），男，硕士研究生，主要研究方向为海洋地质，E-mail：sc170130@mail.ustc.edu.cn

通讯作者: 管红香（1981—），女，副研究员，主要研究方向为冷泉碳酸盐岩的地质地球化学特征，E-mail：guanhx@ms.giec.ac.cn

Composition of glycerol dibiphytanyl glycerol tetraethers (GDGTs) and its responses to paleotemperature and monsoon changes since 31ka in northern South China Sea

1. Key Lab of Renewable Energy and Gas Hydrate, Guangzhou Institute of Energy Conversion, Chinese Academy of Sciences, Guangzhou 510640, China 2. University of Chinese Academy of Sciences, Beijing 100049, China 3. Guangzhou Marine Geological Surveys, Guangzhou 510760, China

Corresponding author: GUAN Hongxiang, guanhx@ms.giec.ac.cn

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1.
中国科学院广州能源研究所，中国科学院天然气水合物研究重点实验室，广州 510640

2.
中国科学院大学，北京 100049

3.
中国地质调查局广州海洋地质调查局，广州 510760

1.
Key Lab of Renewable Energy and Gas Hydrate, Guangzhou Institute of Energy Conversion, Chinese Academy of Sciences, Guangzhou 510640, China

2.
University of Chinese Academy of Sciences, Beijing 100049, China

3.
Guangzhou Marine Geological Surveys, Guangzhou 510760, China