应用多参数示踪方法研究黄河口湿地沉积有机质来源和分布
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摘要
河口湿地是陆海相互作用的重要地带,由于与周边环境频繁的物质交换,其生态系统中的生物地球化学循环过程复杂多变。作为全球碳循环研究的重要内容之一,河口湿地沉积有机质的生物地球化学过程是湿地研究的重要命题,一直备受关注。湿地沉积有机质来源的示踪,是了解有机质在湿地分布、迁移、降解和转化等行为机制的基础,对于其了解的深入,有助于加强对河口湿地在陆源有机质向外海输送过程中的作用的认识。
黄河口湿地是一个典型的滨海河口湿地,由黄河携带的大量泥沙在河口淤积而成,是中国暖温带保存最完整、最广阔、最年轻的湿地生态系统,是我国及世界上研究河口新生湿地生态系统形成、演化及发展规律的最佳场所之一。本文以黄河口湿地为研究对象,分别于2009年4月和6月采集了不同区域的表层沉积物和柱状沉积物样品,进行了粒度、总有机碳(TOC),总氮(TN)、稳定碳同位素(δ~(13)C)和生物标志物(正构烷烃和四醚膜脂)等参数的分析,在此基础上计算了相关的有机地球化学指标(如C/N比、碳优势指数(CPI)、支链与类异戊二烯四醚指标(BIT)等)用来指示沉积有机质的来源,并建立了基于δ~(13)C和BIT等指标的端元混合模型用来区分不同来源对黄河口湿地沉积有机质的贡献;通过上述多种参数的分析,结合两个采样时间前后水文和环境条件的变化,以及不同采样区域的位置、植被等的差异,探讨不同环境条件对各参数和指标时空分布的影响。
研究结果表明,黄河口湿地沉积物粒度组成主要为粉砂,平均比例为75%。全样分析参数TOC、TN、C/N比和δ~(13)C的含量有比较明显的区域和季节分布特征。C/N比和δ~(13)C值显示,处于黄河口湿地核心恢复区的A区域和处于黄河入海前的最后一个浮桥下方的B区域沉积有机质以陆源输入占优势,处于黄河故道的C区域沉积有机质主要来源于海源,并呈现从近黄河河岸的采样点向远离的方向,陆源输入的影响逐渐降低,而海源输入的影响逐渐升高的特点。2009年4月份与6月份具有明显不同的有机质含量和分布特点。C/N比显示6月份有较强的陆源输入,但是并没有在δ~(13)C上得到证实。基于δ~(13)C的双端元模型计算结果表明A区域陆源有机质的平均贡献率为52%,B和C区域的贡献率分别为44%和34%。
对沉积物中正构烷烃的分析表明,黄河口湿地正构烷烃以高碳数烷烃为主,具有明显的奇碳优势,各指标均显示沉积有机质的陆源高等植物输入优势。与全样分析参数一样,正构烷烃分子指标也有明显的季节和区域变化趋势。2009年4月份的正构烷烃分子指标数值要普遍高于6月份,显示有更高的陆源输入影响,与δ~(13)C所揭示的相一致,并且从近黄河河岸的站位向远离的方向,陆源输入的影响逐渐降低,而海源输入的影响逐渐升高。
黄河口湿地表层沉积物中检测到大量的代表海洋来源的泉古菌醇(Crenarchaeol)和代表陆地土壤有机质来源的支链四醚膜脂,BIT指标显示了明显的区域和季节分布。2009年4月的BIT值要高于6月份,尤其是A区域,指示了土壤对此区域沉积有机质贡献较大;B区域BIT值指示土壤有机质的贡献在中等水平;而C区域BIT值较小,表明沉积有机质来源于土壤的贡献很小。利用包含δ~(13)C、C/N比和BIT指标在内的三端元混合模型计算了海源、陆地植物、土壤对沉积有机质的贡献,结果表明A区域和B区域沉积物中土壤有机质的贡献率较大,平均分别为89%和68%,而C区域是海源贡献的有机质相对较大,贡献率为39%。双端元和三端元混合模型计算得到的陆源和海源贡献率不同,三端元模型得到的陆源贡献率要大于双端元模型,表明双端元模型可能忽略了来自土壤有机质的贡献。
Coastal wetlands are located at the boundary between ocean and land.The biogeochemical process in the coastal wetland is complicated and volatile due to the frequently exchange of materials between the adjacent ecosystems. Being an important part of global carbon cycle, the biogeochemical process of sedimentary organic matters in estuary wetlands is an important proposition in Wetland Research and has been focused on for the recent decades. The source of sedimentary organic matters is essential for understanding their distribution, migration, degradation and transformation. It will help us insight the knowlogement of the role which estuary wetlands in translating the terrestrial organic matter to open sea.
As a typical coastal wetlands, the Yellow River Estuarine Wetland (YREW) is accumulated by massive amount of mud and sand which arise from the Yellow River, is the most integrated, broadest and youngest wetland ecological system in warm temperate zone of China, and is one of the best areas for studying the formation, evolution and development of new coastal wetlands in the world. Surface sediments, six sediment cores were collected from different areas of the YREW in different seasons. Grain size, Total organic carbon (TOC), Total nitrogen (TN) and stable carbon (δ~(13)C) compositions, as well as biomakers (n-alkanes and GDGTs) were measured. C/N ratio, Carbon Preference Index (CPI), four Branched and Isoprenoid ether Index (BIT) which been used to indicate the source of sedimentary organic matters were calculated. Two and three end-member mixing models which were established based onδ~(13)C and BIT respectively, were used to distinguish the contribution of different source to sedimentary organic matters. The influences of environment conditions on the spatial and temporal distribution of indexes were discussed based on the analysis of various parameters, as well as on the combination of hydrological and environmental difference between sample time. The vegetation differences among sample sites were also taken into consideration.
Experimental data indicated that silt was the predominant composition of sediments, and the average percentage was 75%. Spatial and temporal variations of the TOC, TN, C/N ratios andδ~(13)C of sediments were significantly different. C/N ratios andδ~(13)C indicated that the predominate source of sedimentary organic matters was terrestrial in area A (located at the area of core recovery in the YREW) and B (below the pontoon which is the last pontoon before The Yellow River enters the sea), but in area C (near the countryhero) was marine. From near river bank sampling point to the far river bank direction, the influence of terrestrial inputs reduced gradually, but the influence of sea source inputs elevated gradually. The content and distribution of organic matters were significantly different between the month April and June. C/N ratio showed a strong terrestrial inputs in June, but not consistent withδ~(13)C. Quantification of terrestrial OC in surface sediments was calculated by two end-member mixing models based onδ~(13)C, the results showed that terrestrial OC accounts for 52% in area A, and in area B and C accounts for 44% and 34%, respectively.
The predominant composition of n-alkanes was high molecular weight and strong odd-even carbon preference. Similar to bulk chemical parameters, the n-alkane proxies had different area and season variation tendency. The n-alkane proxies in April were higher than in June, 2009, demonstrated that had higher terrestrial inputs in June, which consistented withδ~(13)C. From near river bank sampling point to the far river bank direction, the influence of terrestrial inputs reduced gradually, but the influence of sea source inputs elevated gradually.
GDGTs analysis showed that there were amount of Crenarchaeol (produced by marine planktonic Crenarchaeota) and Branch-GDGTs (derived from presumably anaerobic bacteria) in surface sediments of YREW. The BIT value was higher in April than in June 2009, especially in area A, indicated the proportion of soil organic matter was high in area A, intermediate in area B, and low in area C. Application of three end-member mixing model including C/N ratios,δ~(13)C and BIT, suggested that the proportion of soil organic matter was higher in area A and B, their accounts for 89% and 68%, respectively, while in area C the proportion of marine organic matter was higher which accounts for 39%. The contribution of terrestrial sources calculated from three end-member mixing model was greater than that from two end-member mixing model, indicating that the contribution of soil organic matter may been ignored by two end-member mixing model.
黄河口湿地是一个典型的滨海河口湿地,由黄河携带的大量泥沙在河口淤积而成,是中国暖温带保存最完整、最广阔、最年轻的湿地生态系统,是我国及世界上研究河口新生湿地生态系统形成、演化及发展规律的最佳场所之一。本文以黄河口湿地为研究对象,分别于2009年4月和6月采集了不同区域的表层沉积物和柱状沉积物样品,进行了粒度、总有机碳(TOC),总氮(TN)、稳定碳同位素(δ~(13)C)和生物标志物(正构烷烃和四醚膜脂)等参数的分析,在此基础上计算了相关的有机地球化学指标(如C/N比、碳优势指数(CPI)、支链与类异戊二烯四醚指标(BIT)等)用来指示沉积有机质的来源,并建立了基于δ~(13)C和BIT等指标的端元混合模型用来区分不同来源对黄河口湿地沉积有机质的贡献;通过上述多种参数的分析,结合两个采样时间前后水文和环境条件的变化,以及不同采样区域的位置、植被等的差异,探讨不同环境条件对各参数和指标时空分布的影响。
研究结果表明,黄河口湿地沉积物粒度组成主要为粉砂,平均比例为75%。全样分析参数TOC、TN、C/N比和δ~(13)C的含量有比较明显的区域和季节分布特征。C/N比和δ~(13)C值显示,处于黄河口湿地核心恢复区的A区域和处于黄河入海前的最后一个浮桥下方的B区域沉积有机质以陆源输入占优势,处于黄河故道的C区域沉积有机质主要来源于海源,并呈现从近黄河河岸的采样点向远离的方向,陆源输入的影响逐渐降低,而海源输入的影响逐渐升高的特点。2009年4月份与6月份具有明显不同的有机质含量和分布特点。C/N比显示6月份有较强的陆源输入,但是并没有在δ~(13)C上得到证实。基于δ~(13)C的双端元模型计算结果表明A区域陆源有机质的平均贡献率为52%,B和C区域的贡献率分别为44%和34%。
对沉积物中正构烷烃的分析表明,黄河口湿地正构烷烃以高碳数烷烃为主,具有明显的奇碳优势,各指标均显示沉积有机质的陆源高等植物输入优势。与全样分析参数一样,正构烷烃分子指标也有明显的季节和区域变化趋势。2009年4月份的正构烷烃分子指标数值要普遍高于6月份,显示有更高的陆源输入影响,与δ~(13)C所揭示的相一致,并且从近黄河河岸的站位向远离的方向,陆源输入的影响逐渐降低,而海源输入的影响逐渐升高。
黄河口湿地表层沉积物中检测到大量的代表海洋来源的泉古菌醇(Crenarchaeol)和代表陆地土壤有机质来源的支链四醚膜脂,BIT指标显示了明显的区域和季节分布。2009年4月的BIT值要高于6月份,尤其是A区域,指示了土壤对此区域沉积有机质贡献较大;B区域BIT值指示土壤有机质的贡献在中等水平;而C区域BIT值较小,表明沉积有机质来源于土壤的贡献很小。利用包含δ~(13)C、C/N比和BIT指标在内的三端元混合模型计算了海源、陆地植物、土壤对沉积有机质的贡献,结果表明A区域和B区域沉积物中土壤有机质的贡献率较大,平均分别为89%和68%,而C区域是海源贡献的有机质相对较大,贡献率为39%。双端元和三端元混合模型计算得到的陆源和海源贡献率不同,三端元模型得到的陆源贡献率要大于双端元模型,表明双端元模型可能忽略了来自土壤有机质的贡献。
Coastal wetlands are located at the boundary between ocean and land.The biogeochemical process in the coastal wetland is complicated and volatile due to the frequently exchange of materials between the adjacent ecosystems. Being an important part of global carbon cycle, the biogeochemical process of sedimentary organic matters in estuary wetlands is an important proposition in Wetland Research and has been focused on for the recent decades. The source of sedimentary organic matters is essential for understanding their distribution, migration, degradation and transformation. It will help us insight the knowlogement of the role which estuary wetlands in translating the terrestrial organic matter to open sea.
As a typical coastal wetlands, the Yellow River Estuarine Wetland (YREW) is accumulated by massive amount of mud and sand which arise from the Yellow River, is the most integrated, broadest and youngest wetland ecological system in warm temperate zone of China, and is one of the best areas for studying the formation, evolution and development of new coastal wetlands in the world. Surface sediments, six sediment cores were collected from different areas of the YREW in different seasons. Grain size, Total organic carbon (TOC), Total nitrogen (TN) and stable carbon (δ~(13)C) compositions, as well as biomakers (n-alkanes and GDGTs) were measured. C/N ratio, Carbon Preference Index (CPI), four Branched and Isoprenoid ether Index (BIT) which been used to indicate the source of sedimentary organic matters were calculated. Two and three end-member mixing models which were established based onδ~(13)C and BIT respectively, were used to distinguish the contribution of different source to sedimentary organic matters. The influences of environment conditions on the spatial and temporal distribution of indexes were discussed based on the analysis of various parameters, as well as on the combination of hydrological and environmental difference between sample time. The vegetation differences among sample sites were also taken into consideration.
Experimental data indicated that silt was the predominant composition of sediments, and the average percentage was 75%. Spatial and temporal variations of the TOC, TN, C/N ratios andδ~(13)C of sediments were significantly different. C/N ratios andδ~(13)C indicated that the predominate source of sedimentary organic matters was terrestrial in area A (located at the area of core recovery in the YREW) and B (below the pontoon which is the last pontoon before The Yellow River enters the sea), but in area C (near the countryhero) was marine. From near river bank sampling point to the far river bank direction, the influence of terrestrial inputs reduced gradually, but the influence of sea source inputs elevated gradually. The content and distribution of organic matters were significantly different between the month April and June. C/N ratio showed a strong terrestrial inputs in June, but not consistent withδ~(13)C. Quantification of terrestrial OC in surface sediments was calculated by two end-member mixing models based onδ~(13)C, the results showed that terrestrial OC accounts for 52% in area A, and in area B and C accounts for 44% and 34%, respectively.
The predominant composition of n-alkanes was high molecular weight and strong odd-even carbon preference. Similar to bulk chemical parameters, the n-alkane proxies had different area and season variation tendency. The n-alkane proxies in April were higher than in June, 2009, demonstrated that had higher terrestrial inputs in June, which consistented withδ~(13)C. From near river bank sampling point to the far river bank direction, the influence of terrestrial inputs reduced gradually, but the influence of sea source inputs elevated gradually.
GDGTs analysis showed that there were amount of Crenarchaeol (produced by marine planktonic Crenarchaeota) and Branch-GDGTs (derived from presumably anaerobic bacteria) in surface sediments of YREW. The BIT value was higher in April than in June 2009, especially in area A, indicated the proportion of soil organic matter was high in area A, intermediate in area B, and low in area C. Application of three end-member mixing model including C/N ratios,δ~(13)C and BIT, suggested that the proportion of soil organic matter was higher in area A and B, their accounts for 89% and 68%, respectively, while in area C the proportion of marine organic matter was higher which accounts for 39%. The contribution of terrestrial sources calculated from three end-member mixing model was greater than that from two end-member mixing model, indicating that the contribution of soil organic matter may been ignored by two end-member mixing model.
引文
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