| 引用本文: | 刘会基,刘恩峰,于真真,张恩楼,林琪,王荣,沈吉.近百年来洱海沉积物有机碳埋藏时空变化.湖泊科学,2019,31(1):282-292. DOI:10.18307/2019.0126 |
| LIU Huiji,LIU Enfeng,YU Zhenzhen,ZHANG Enlou,LIN Qi,WANG Rong,SHEN Ji.Spatio-temporal patterns of organic carbon burial in the sediment of Lake Erhai in China during the past 100 years. J. Lake Sci.2019,31(1):282-292. DOI:10.18307/2019.0126 |
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| 近百年来洱海沉积物有机碳埋藏时空变化 |
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刘会基1,2, 刘恩峰1,3, 于真真1,2, 张恩楼1, 林琪1,2, 王荣1, 沈吉1
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1.中国科学院南京地理与湖泊研究所湖泊与环境国家重点实验室, 南京 210008;2.中国科学院大学, 北京 100049;3.山东师范大学地理与环境学院, “人地协调与绿色发展”山东省高校协同创新中心, 济南 250358
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| 摘要: |
| 湖泊沉积物有机碳埋藏是陆地碳循环中重要的环节，对全球碳平衡起着重要的作用.洱海是云贵高原第二大淡水湖，目前对洱海生态环境变化、重金属与营养盐污染等已展开了较为深入的研究，但对近百年来沉积物有机碳埋藏时空变化与驱动因素缺乏系统的分析.本文通过对洱海北部湖区典型岩芯（编号EH2012）以及其他湖区13个沉积岩芯中有机碳（OC）含量的分析，结合湖泊生态环境与气候因子变化，研究了近百年来沉积物有机碳埋藏时空变化特征与影响因素.C/N摩尔比值表明洱海沉积物中OC以湖泊内源为主，不同湖区岩芯中OC含量变化趋势基本相似.以EH2012岩芯为例，OC含量历史变化可分为3个阶段：1970年以前，表现出较稳定的低值；1970-2000年，OC含量逐渐增加；2000年以来，OC含量增加更加明显并达到近百年来的最大值.近百年来，EH2012岩芯有机碳累积速率（OCAR）呈逐渐增加趋势，变化范围为7.9~87.2 g/（m2·a），平均OCAR（OCAR）为24.1 g/（m2·a）；OCAR变化与OC含量和区域气温呈显著正相关，全球变暖与营养驱动下的湖泊生产力提高可能是近年来OCAR增加的主要原因之一.基于重金属Cd污染初始时间建立的时标，1982年以来不同湖区OCAR为17.1~44.7 g/（m2·a），采用克里金插值得到的全湖OCAR均值为31.4 g/（m2·a）；不同湖区OCAR与磷累积速率呈显著正相关，指示了湖泊营养水平对有机碳埋藏空间变化的重要影响. |
| 关键词: 洱海 沉积物 有机碳埋藏 时空变化 驱动机制 |
| DOI：10.18307/2019.0126 |
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| 基金项目:国家科技基础性工作专项（2014FY110400）和国家自然科学基金项目（41672354，41271214）联合资助. |
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| Spatio-temporal patterns of organic carbon burial in the sediment of Lake Erhai in China during the past 100 years |
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LIU Huiji1,2, LIU Enfeng1,3, YU Zhenzhen1,2, ZHANG Enlou1, LIN Qi1,2, WANG Rong1, SHEN Ji1
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1.State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, P. R. China;2.University of Chinese Academy of Sciences, Beijing 100049, P. R. China;3.Collaborative Innovation Center of Human-Nature and Green Development in Universities of Shandong, College of Geography and Environment, Shandong Normal University, Ji'nan 250358, P. R. China
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| Abstract: |
| Organic carbon (OC) burial in lake sediments plays important roles in the terrestrial carbon cycle and global carbon balance. Lake Erhai is the second largest freshwater lake in the Yunnan-Guizhou Plateau. There have been many studies on the changes in the lake ecological environment and pollution of trace metals and nutrients, but limited knowledge is available on the spatio-temporal patterns in OC burial in sediment. Based on the analysis of OC content in core EH2012 and other 13 sedimentary cores in Lake Erhai, the characteristics in temporal and spatial variations of OC burial in recent 100 years were studied, and their relationships with the climatic, anthropogenic and ecological factors were discussed. The C/N molar ratio indicated that the sedimentary OC in Lake Erhai were mainly autochthonous in source, and they displayed similar vertical trends in the cores from different lake areas. In core EH2012, for example, the OC content displayed three stages variations. The OC content were low before 1970 AD, followed by a gradual increase between 1970 and 2000 AD, then increased sharply after 2000 AD and reached the maxima in recent years. The organic carbon accumulation rate (OCAR) increased gradually over the past 100 years as shown in core EH2012, and ranged from 7.9 to 87.2 g/(m2·a), with an average value (OCAR) of 24.1 g/(m2·a). The OCAR variations in cores EH2012 were positively correlated with the OC content and regional temperature, suggesting that the enhancing lake primary productivity driven by both nutrients levels and temperature should be one of major factors responsible for rising OCAR. Using the 1982 chronology mark established by initial time of Cd pollution in the cores, the OCAR since 1982 AD showed large diversity in different lake areas, ranging from 17.1 to 44.7 g/(m2·a), and it averaged 31.4 g/(m2·a) for the whole lake based on the Kriging interpolation. The spatial variation in OCAR is positively correlated with the phosphorus accumulation rate, which also suggests the driving mechanism of nutrient levels on the OC burial. |
| Key words: Lake Erhai sediment organic carbon burial spatio-temporal variations driving mechanism |
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