地球科学进展 ›› 2023, Vol. 38 ›› Issue (9): 967 -977. doi: 10.11867/j.issn.1001-8166.2023.057

生态系统对全球变化的响应 上一篇    下一篇

GDGTs温度指标在青藏高原湖泊的应用潜力分析——以昆仑山黑海为例
程昕( ), 王小雨( ), 曹怀仁, 张成君   
  1. 兰州大学 地质科学与矿产资源学院,甘肃 兰州 730030
  • 收稿日期:2023-03-01 修回日期:2023-06-30 出版日期:2023-09-10
  • 通讯作者: 王小雨 E-mail:xincheng_c@yeah.net;wangxiaoyu@lzu.edu.cn
  • 基金资助:
    国家自然科学基金项目(41501209);甘肃省科技计划项目(21JR7RA502)

Application Potential Analysis of GDGTs Temperature Index in Lakes on the Qinghai-Tibet Plateau: The Case of Heihai Lake on Kunlun Mountain

Xin CHENG( ), Xiaoyu WANG( ), Huairen CAO, Chengjun ZHANG   

  1. Faculty of Geological Sciences and Mineral Resources, Lanzhou University, Lanzhou 730030, China
  • Received:2023-03-01 Revised:2023-06-30 Online:2023-09-10 Published:2023-09-25
  • Contact: Xiaoyu WANG E-mail:xincheng_c@yeah.net;wangxiaoyu@lzu.edu.cn
  • About author:CHENG Xin, Master student, research area includes organic geochemistry. E-mail: xincheng_c@yeah.net
  • Supported by:
    the National Natural Science Foundation of China(41501209);The Science and Technology Plan of Gansu Province(21JR7RA502)

古温度的定量重建已成为理解地球气候系统演化的关键性环节,然而目前可靠的陆地温度重建指标仍然较少。来源于微生物细胞膜的甘油二烷基甘油四醚膜类脂(GDGTs)及其相关指标(甲基化/环化指标MBT/CBT和四醚指标TEX86)在湖泊古温度的定量重建中具有一定的潜力,但由于湖泊系统的复杂性及高原气候的特殊性等问题,使得相关指标在青藏高原湖泊的应用受到影响。因此,对目标湖泊开展详细的现代过程分析,考察GDGTs温度指标的应用潜力尤为重要。以位于藏北高原的黑海作为研究对象,采集表层沉积物、流域土壤以及入湖河流沉积物共24个样品。分析了黑海沉积系统中GDGTs的来源,探讨了GDGTs及其相关指标对环境因子的响应,考察了MBT/CBT指标及温度转换函数在高原湖泊温度重建中的适用性。结果表明:黑海中存在部分内源性GDGTs;水体深度对GDGTs的组成与分布影响较显著,电导率与总有机碳的影响较弱;MBT/CBT指标在高海拔和寒冷地区的湖泊古温度重建中有一定的局限性,应该结合区域特点、气候类型及母源微生物对特殊环境的生态响应等,建立更加适用于高原湖泊的温度指标及校正方程。

Quantitative reconstruction of paleotemperature has become a critical link in understanding the evolution of the Earth’s climate system. However, only few reliable continental temperature reconstruction indicators are available. Glycerol Dialkyl Glycerol Tetraether membrane lipids (GDGTs) are derived from microbial cell membranes. The MBT/CBT and TEX86 indices related to GDGTs have been applied to the quantitative paleotemperature reconstruction of lake systems. However, because of the complexity of the lake systems and the particularity of the plateau climate, the application of relevant indicators in lakes on the Qinghai-Tibet Plateau is affected. Therefore, it is vital to conduct detailed modern process analyses of the target lakes and investigate the potential applications of these indices. In this study, 24 samples of soil, lake, and river surface sediments were collected from Heihai Lake on the northern Tibetan Plateau. The sources of GDGTs in the Heihai Lake sedimentary system were analyzed. The responses of the GDGTs and their related indicators to environmental factors were discussed. The applicability of the MBT/CBT index and temperature conversion function to the temperature reconstruction of plateau lakes was investigated. Results show that there are some endogenous GDGT compounds present in Heihai Lake, and that water depth has a significant effect on the composition and distribution of GDGTs. Conductivity and TOC have weak effects on GDGTs, and the MBT/CBT index has some limitations in reconstructing lake temperature in high-altitude and cold regions. Therefore, more suitable temperature indicators and correction equations for plateau lakes need to be established by combining the regional characteristics, climate types, and ecological responses of microorganisms to special environments.

中图分类号: 

图1 黑海地理位置和采样点位置图
Fig. 1 Locations of Heihai Lake and the sampling sites
表1 采样点的环境因子和 GDGTs相关指标信息
Table 1 Environmental factors and relative proxies of GDGTs on sampling site
样品 编号 海拔/m 经度(E) 纬度(N) 深度/m

电导率/

(ms/cm)

TOC/% TEX86 35 MBT 9 MBT'5ME 36 CBT 9 GDGT-0/Cren
LS1 4 446 93°17'20.1" 35°57'47.8'' 0.30 0.70 2.00 0.687 0.134 0.138 0.253 1.472
LS2 4 444 93°17'24.2" 35°57'49.4'' 0.40 0.62 1.19 0.529 0.166 0.168 0.257 4.077
LS3 4 448 93°17'22.8" 35°57'49.3'' 0.40 0.60 0.84 0.379 0.146 0.150 0.421 2.396
LS4 4 447 93°17'20.0" 35°57'48.3'' 0.70 0.88 2.05 0.360 0.137 0.143 0.439 1.635
LS5 4 447 93°17'19.8" 35°57'48.1'' 0.70 0.59 1.09 0.665 0.122 0.127 0.273 1.258
LS6 4 444 93°17'00.4" 35°57'45.4'' 1.30 0.73 0.93 0.697 0.120 0.126 0.265 18.549
LS7 4 446 93°16'58.0" 35°57'45.8'' 1.30 0.72 0.93 0.676 0.127 0.131 0.289 29.375
LS8 4 447 93°16'56.1" 35°57'45.1'' 1.00 0.70 0.99 0.701 0.119 0.124 0.285 22.717
LS9 4 442 93°17'22.9" 35°58'18.7'' 1.60 0.67 2.54 0.588 0.127 0.132 0.246 0.763
LS10 4 437 93°17'11.5" 35°58'18.3'' 2.00 0.74 2.05 0.593 0.141 0.146 0.195 0.722
LS11 4 445 93°17'28.6" 35°58'29.6" 2.00 0.69 4.18 0.558 0.151 0.156 0.267 0.801
LS12 4 433 93°17'29.7'' 35°58'53.7'' 3.10 0.70 6.26 0.581 0.153 0.159 0.201 2.735
LS13 4 447 93°17'26.7'' 36°00'08.9" 1.40 0.60 1.45 0.573 0.152 0.157 0.178 0.616
LS14 4 447 93°17'23.3'' 36°00'06.9" 1.20 0.61 1.87 0.535 0.163 0.163 0.345 1.059
RS15 4 441 93°14'40.4'' 35°58'29.9'' 1.23 0.598 0.182 0.187 0.273 1.272
RS16 4 438 93°14'39.0'' 35°58'31.2'' 0.79 0.600 0.185 0.189 0.194 1.384
RS17 4 436 93°14'10.8'' 35°58'28.4'' 0.79 0.628 0.213 0.218 0.115 1.310
RS18 4 437 93°14'14.0'' 35°57'46.8'' 0.67 0.250 0.230 0.241 0.160 1.450
RS19 4 447 93°14'29.4'' 35°57'27.6'' 0.71 0.467 0.269 0.282 0.064 0.580
S20 4 469 93°14'38.1'' 35°56'43.3'' 0.92 0.578 0.070 0.071 0.826 0.829
S21 4 460 93°14'03.8'' 35°56'58.0'' 0.96 0.505 0.020 0.020 1.440 1.045
S22 4 465 93°14'02.9'' 35°56'46.6'' 0.93 0.564 0.028 0.028 1.057 0.943
S23 4 478 93°13'56.3'' 35°56'32.3'' 0.89 0.581 0.006 0.007 1.173 1.472
S24 4 478 93°13'55.1'' 35°56'31.7'' 0.95 0.000 0.008 0.008 1.357 2.734
图2 湖泊、河流表层沉积物及流域土壤中GDGTs的分布特征
Fig. 2 The GDGTs distribution in surface sediments of lakesriver and surface soils sediments characteristics
图3 brGDGTsa)和isoGDGTsb)在3种样品中的相对含量
Fig. 3 The relative content of brGDGTsaand isoGDGTsbin three types of samples
图4 黑海表层沉积物样品的环境参数与基于GDGTs各指标以及GDGTs分布之间的关系
(a)主成分分析;(b)冗余分析
Fig. 4 The relationship between environmental variables of Heihai lake surface sediment samples and GDGTs-based indicators and GDGTs distribution
(a) Principal component analysis biplot; (b) Redundancy analysis triplot
表2 基于主成分分析和冗余分析分析环境因子对于 GDGTs的相关性
Table 2 Correlation of environmental factors on GDGTs based on PCA and RDA analysis
表3 基于 brGDGTs建立的温度重建方程
Table 3 Reconstruction equation of temperature based on brGDGTs
图5 利用经验方程重建温度与实际年均温度对比
红色区域:多年夏季月平均气温(16.2~18.5 ℃);黄色区域:多年春季月平均气温(1.2~12.3 ℃);蓝色区域:多年冬季月平均气温
Fig. 5 Reconstruct the comparison between the temperature and the actual average temperature by using the empirical equation
(-4.2 ~12.3 ℃) Red area: indicating the average summer temperature (16.2~18.5 ℃) in each month for many years); Yellow area: indicates the average temperature (1.2~12.3 ℃) in spring in each month of many years; Blue area: indicates the average temperature (-4.2~12.3 ℃) of each month in winter for many years
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