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湖泊沉积物文献信息的网络分析:研究现状和热点
引用本文:王瑞杰,李刚,徐耀阳.湖泊沉积物文献信息的网络分析:研究现状和热点[J].长江流域资源与环境,2019,28(1):192-201.
作者姓名:王瑞杰  李刚  徐耀阳
作者单位:中国科学院城市环境研究所,福建厦门361021;中国科学院大学,北京100049;中国科学院宁波城市环境观测研究站,浙江宁波315800;中国科学院城市环境研究所,福建厦门361021;中国科学院宁波城市环境观测研究站,浙江宁波315800
基金项目:国家重点研发计划;中国科学院率先行动“百人计划”;国家自然科学基金;国家自然科学基金
摘    要:通过对湖泊沉积物研究领域的文献信息的网络分析,对了解目前该领域在全球的研究现状、研究热点及其未来的发展趋势具有重要的意义,也为我国长江下游湖泊群的科学研究和生态保护提供了科学参考。以Web of Science中1931~2016年的文献信息为数据源,以“lake sediment*”作为标题的字段进行信息检索,结合文献计量法,采用词频统计、聚类分析和网络分析方法,评估了湖泊沉积物研究领域的研究现状和发展趋势。结果表明:该领域共检索到相关文献9 126篇,且文献的发表数量随时间变化呈指数增长(R2=0.98,P<0.01);美国发表文献数量最多,共有2 086篇,占总出版文献数的20.5%,中国发表文献的数量为2 086篇,仅次于美国,欧美等发达国家对研究文献量的贡献较大,发展中国家中,中国的贡献较大;研究文献涉及最多的三大学科分别为环境科学与生态、地质学和海洋与淡水生物学,属于这三大学科的文献分别有3 368(22.0%)、2 698(17.6%)、2 099(13.7%)篇;Journal of Paleolimnology、Hydrobiologia和Limnology and Oceanography为该研究领域文献发表较多的期刊,发表文献数量分别为412、366、237篇,分别占总文献数量的4.5%、4.0%、2.6%;从该领域的研究热点和发展趋势上来看,重金属和有机污染物的污染与风险、湖泊沉积物与古气候的研究、湖泊富营养化等研究成为湖泊沉积物研究的热点方向,它们作为关键词出现频率位于前10,未来模型和多元统计运用等方向作为新的关键词出现,且出现频次进入前50,说明这两个方向具有一定的研究价值和发展空间。

关 键 词:湖泊沉积物  聚类分析  网络分析  研究热点  发展趋势

Network Analysis of Literature in Formation of Lake Sediment: Research Status and Hotspot
WANG Rui-jie,LI Gang,XU Yao-yang.Network Analysis of Literature in Formation of Lake Sediment: Research Status and Hotspot[J].Resources and Environment in the Yangtza Basin,2019,28(1):192-201.
Authors:WANG Rui-jie  LI Gang  XU Yao-yang
Institution:(1. Key Laboratory of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences,  Xiamen 361021, China; 2. University of Chinese Academy of Sciences, Beijing 100049, China;  3. Ningbo Urban Environment Observation and Research Station, Chinese Academy of Sciences, Ningbo 315830, China);
Abstract:A network analysis of literatures in the lake sediments research field is not only important for understanding the current research status, research hotspot and future development trend of this field, but also significant for providing us scientific references to investigate and protect ecological environments of the lakes at Yangtze River’s downstream. This paper evaluated the research status and development trend of lake sediments. An effective bibliometric analysis was conducted to analyze the existing literature about “lake sediment” which were published in the the database Web of ScienceTM Core Collection (WOS) 1931 to 2016. And word frequency statistics, cluster analysis and network analysis methods were applied. The results showed that 9 126 related documents were retrieved in this field, and the number of published documents had an exponential growth with time (R2=0.98, P<0.01). The United States had the largest number of articles published, a total of 2 086, accounting for 20.5% of the total number of published articles. There were 2 086 articles published in China, second only to the United States. Developed countries such as Europe and the United States had contributed a great deal to the volume of research literature. Meanwhile, in developing countries, China played an important role in the field of lake sediment. The three subjects with the largest number of research literatures were Environmental Sciences & Ecology, Geology and Marine & Freshwater Biology, with 3 368 (22.0%), 2 698 (17.6%), and 2 099 (13.7%) articles respectively. The top three journals published on lake sediment were Journal of Paleolimnology, Hydrobiologia and Limnology and Oceanography. The number of articles published were 412, 366, and 237, which accounted for 4.5%, 4.0%, and 2.6% of the total articles respectively. From the perspective of research hotspots and development trends in this field, the research hot spots in the study of lake sediments focus on the field of the pollution and risk of heavy metals and organic pollutants, study of lake sediments and paleoclimate, as well as lake eutrophication. Their frequency of occurrence as keywords was in the top 10. In the future, ‘lake sediment model’ and ‘multivariate statistical applications’ appear as new keywords, and frequency appears in the top 50. They had a certain research value and development space.
Keywords:
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