植物生态学报 ›› 2021, Vol. 45 ›› Issue (7): 799-808.DOI: 10.17521/cjpe.2021.0024

• 资料论文 • 上一篇    

中国现代花粉数据集

陈海燕1, 徐德宇1, 廖梦娜1,2, 李凯1,2, 倪健1,2,*(), 曹现勇3, 程波4, 郝秀东5, 孔昭宸6, 李升峰7, 李小强8, 刘光琇9, 刘平妹10, 刘兴起11, 孙湘君12, 唐领余13, 魏海成14, 许清海15, 阎顺16, 羊向东17, 杨振京18, 于革17, 张芸6, 张志勇19, 赵克良8, 郑卓20, Ulrike HERZSCHUH21   

  1. 1浙江师范大学化学与生命科学学院, 浙江金华 321004
    2浙江金华山亚热带森林生态系统野外科学观测研究站, 浙江金华 321004
    3中国科学院青藏高原研究所青藏高原地球系统科学国家重点实验室, 北京 100101
    4华中师范大学城市与环境科学学院, 武汉 430079
    5南宁师范大学北部湾环境演变与资源利用教育部重点实验室, 南宁 530001
    6中国科学院植物研究所, 北京 100093
    7南京大学地理与海洋科学学院, 南京 210023
    8中国科学院古脊椎动物与古人类研究所, 北京 100044
    9中国科学院西北生态环境资源研究院, 兰州 730000
    10 台湾大学地质科学系, 中国台北 10617
    11 首都师范大学资源环境与旅游学院, 北京 100048
    12 同济大学海洋与地球科学学院, 上海 200092
    13 中国科学院南京地质古生物研究所, 南京 210008
    14 中国科学院青海盐湖研究所, 西宁 810008
    15 河北师范大学资源与环境科学学院, 石家庄 050027
    16 中国科学院新疆生态与地理研究所, 乌鲁木齐 830011
    17 中国科学院南京地理与湖泊研究所, 南京 210008
    18 中国地质科学院水文地质与环境地质研究所, 石家庄 050061
    19 中国科学院庐山植物园, 江西九江 332900
    20 中山大学地球科学与工程学院, 广州 510275
    21 Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research, Potsdam 14473, Germany
  • 收稿日期:2021-01-19 接受日期:2021-03-26 出版日期:2021-07-20 发布日期:2021-10-22
  • 通讯作者: 倪健 ORCID:0000-0001-5411-7050
  • 作者简介:* 倪健: ORCID: 0000-0001-5411-7050, nijian@zjnu.edu.cn
  • 基金资助:
    中国科学院战略性先导科技专项(XDA19050103);中国科学院战略性先导科技专项(XDA2009000003);中国科学院战略性先导科技专项(XDB31030104)

A modern pollen dataset of China

CHEN Hai-Yan1, XU De-Yu1, LIAO Meng-Na1,2, LI Kai1,2, NI Jian1,2,*(), CAO Xian-Yong3, CHENG Bo4, HAO Xiu-Dong5, KONG Zhao-Chen6, LI Sheng-Feng7, LI Xiao-Qiang8, LIU Guang-Xiu9, LIU Ping-Mei10, LIU Xing-Qi11, SUN Xiang-Jun12, TANG Ling-Yu13, WEI Hai-Cheng14, XU Qing-Hai15, YAN Shun16, YANG Xiang-Dong17, YANG Zhen-Jing18, YU Ge17, ZHANG Yun6, ZHANG Zhi-Yong19, ZHAO Ke-Liang8, ZHENG Zhuo20, Ulrike HERZSCHUH21   

  1. 1College of Chemistry and Life Sciences, Zhejiang Normal University, Jinhua, Zhejiang 321004, China
    2Jinhua Mountain Observation and Research Station for Subtropical Forest Ecosystems, Jinhua, Zhejiang 321004, China
    3State Key Laboratory of Tibetan Plateau Earth System Science, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China
    4College of Urban and Environmental Sciences, Central China Normal University, Wuhan 430079, China
    5Key Laboratory of Environment Change and Resource Use in Beibu Gulf (Nanning Normal University), Ministry of Education, Nanning 530001, China
    6Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China
    7School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China
    8Institute of Vertebrate Paleontology and Paleoanthropology, Chinese Academy of Sciences, Beijing 100044, China
    9Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
    10 Department of Geosciences, Taiwan University, Taipei 10617, China
    11 College of Resource Environment and Tourism, Capital Normal University, Beijing 100048, China
    12 School of Ocean and Earth Science, Tongji University, Shanghai 200092, China
    13 Nanjing Institute of Geology and Palaeontology, Chinese Academy of Sciences, Nanjing 210008, China
    14 Qinghai Institute of Salt Lakes, Chinese Academy of Sciences, Xining 810008, China
    15 College of Resource and Environmental Sciences, Hebei Normal University, Shijiazhuang 050027, China
    16 Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Ürümqi 830011, China
    17 Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China
    18 Institute of Hydrogeology and Environmental Geology, Chinese Academy of Geological Sciences, Shijiazhuang 050061, China
    19 Lushan Botanical Garden, Chinese Academy of Sciences, Jiujiang, Jiangxi 332900, China
    20 School of Earth Sciences and Engineering, Sun Yat-Sen University, Guangzhou 510275, China
    21 Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research, Potsdam 14473, Germany
  • Received:2021-01-19 Accepted:2021-03-26 Online:2021-07-20 Published:2021-10-22
  • Contact: NI Jian ORCID:0000-0001-5411-7050
  • Supported by:
    Strategic Priority Research Program of the Chinese Academy of Sciences(XDA19050103);Strategic Priority Research Program of the Chinese Academy of Sciences(XDA2009000003);Strategic Priority Research Program of the Chinese Academy of Sciences(XDB31030104)

摘要:

孢粉是重建古植被、古气候的重要基础数据。孢粉数据库对研究样点至区域和全球尺度上的古环境演变规律、古气候变化特征反演和古生物地球化学循环模拟等具有重要意义。该文收集整理了中国1960-2020年间发表和部分未发表的现代花粉数据记录, 包括样品编号、采样位置、采样地经纬度和海拔高度、样品类型、数据来源、数据类型、周边植被信息、参考文献、花粉类群及其含量等信息; 并对数据进行筛选和标准化等处理, 由此整合为中国现代花粉数据集。该数据集由4 497个现代花粉采样点的数据信息组成, 包括660个来自中国第四纪孢粉数据库数据, 1 763个前期整理发表的数据和2 074个近期收集的数据, 涵盖772个花粉类群。样品类型以土壤表层样品(3 332个)为主, 苔藓样品以及湖泊、海洋表层样品等为辅, 广泛分布于全国不同地理区域和植被类型中, 其中以温带荒漠区域(24.91%)和亚热带常绿阔叶林区域(24.02%)最丰富, 其次为温带草原区域(16.14%)和青藏高原高寒植被区域(15.83%)。数据按照来源可分为原始数据(58%)和数值化数据(42%); 按照数据类型可分为原始统计粒数的样点(59%)和以花粉百分比表达的样点(41%)。半个多世纪以来, 科研人员开展了大量的表层现代花粉取样和研究。本数据集虽然仅获取部分记录, 但样点覆盖了我国绝大多数地区, 可有效地用于古植被与古气候重建的现代孢粉与现代植被校验, 并将为中国孢粉数据库的建立与更深入的孢粉研究提供数据支撑。

关键词: 中国, 花粉数据库, 表层花粉, 现代植被

Abstract:

Pollen record is an essential data for reconstructing paleovegetation and paleoclimate. It is important for the studies of paleoenvironmental evolution, characteristics of paleoclimate change and simulation of paleobiogeochemical cycles from site to regional and global scales. In this paper, we collected and sorted out the pollen data records from published and unpublished Chinese literature between 1960 to 2020. The records included sample numbers, sampling locations (latitude, longitude and altitude of sampling sites), sample types, data sources, data types, surrounding vegetation, references, and pollen taxa, their compositions as well. They were filtered and standardized to integrate a pollen dataset of China. This dataset consists of 4 497 modern pollen sampling sites, including 660 published data from the Chinese Quaternary Pollen Database, 1 763 from early published data and 2 074 from recently collected data, belonging to 772 pollen taxa. The samples were mainly from surface soils (3 332 sites), and the rest were from moss plosters, surface sediments from lakes and the ocean. The sampling sites are widely scattered around China representing different geographical regions and vegetation types: 24.91%. in the temperate desert region, 24.02% in the subtropical evergreen broad-leaved forest region, followed by the temperate grassland region (16.14%) and alpine vegetation region of Qingzang Plateau (15.83%). The data can be divided into the raw data (58%) and numerical data (42%) according to their sources, and grain count (59%) and calculated pollen percentage (41%) by data type as well. The database constructed from the samples over China during the past half-century+ period is, though by far from complete, good representation of most of the areas in China, which can be effective in the reconstruction of past vegetation and climates as modern verification.

Key words: China, pollen database, surface pollen, modern vegetation