A novel procedure for pollen-based quantitative paleoclimate reconstructions and its application in China  

作　　者：CHEN JianHui LV FeiYa HUANG XiaoZhong H.John B.BIRKS Richard J.TELFORD ZHANG ShengRui XU QingHai ZHAO Yan WANG HaiPeng ZHOU AiFeng HUANG Wei LIU JianBao WEI GuoYing 

机构地区：[1]Key Laboratory of West China's Environmental System(Ministry of Education),College of Earth and Environmental Sciences,Lanzhou University,Lanzhou 730000,China [2]Department of Biology and Bjerknes Centre for Climate Research,University of Bergen,N-5020 Bergen,Norway [3]Institute of Nihewan Archaeology Research,Hebei Normal University,Shijiazhuang 050024,China [4]Institute of Geographic Science and Natural Resources Research,Chinese Academy of Sciences,Beijing 100101,China [5]University of Chinese Academy of Sciences,Beijing 100049,China

出　　处：《Science China Earth Sciences》2017年第11期2059-2066,共8页中国科学（地球科学英文版）

基　　金：supported by the National Natural Science Foundation of China(Grant Nos.41471162&41571182);the National Key R&D Program of China(Grant No.2017YFA0603402)

摘　　要：Traditionally, the evaluation of pollen-based quantitative paleoclimate reconstructions focuses on the ability of calibration sets to infer present climatic conditions and/or the similarity between fossil and modem assemblages. Objective criteria for choosing the most appropriate climate parameter（s） to be reconstructed at a specific site are thus lacking. Using a novel approach for testing the statistical significance of a quantitative reconstruction using random environmental data, in combination with the advantageous large environmental gradients, abundant vegetation types and comprehensive modem pollen databases in China, we describe a new procedure for pollen-based quantitative paleoclimatic reconstructions. First, the most significant environmental variable controlling the fossil pollen assemblage changes is identified. Second, a calibration set to infer changes in this targeted variable is built up, by limiting the modem ranges of other environmental variables. Finally, the pollen-based quantitative reconstruction is obtained and its statistical significance assessed. This novel procedure was used to reconstruct the mean annual precipitation （Pann） from Gonghai Lake in the Lvliang Mountains, and Tianchi Lake in the Liupan Mountains, on the eastern and western fringe of the Chinese Loess Plateau, respectively. Both Pann. reconstructions are statistically significant （p〈0.001）, and a sound and stable correlation relationship exists in their common period, showing a rapid precipitation decrease since 3300 cal yr BP. Thus, we propose that this procedure has great potential for reducing the uncertainties associated with pollen-based quantitative paleoclimatic reconstructions in China.Traditionally, the evaluation of pollen-based quantitative paleoclimate reconstructions focuses on the ability of calibration sets to infer present climatic conditions and/or the similarity between fossil and modern assemblages. Objective criteria for choosing the most appropriate climate parameter(s) to be reconstructed at a specific site are thus lacking. Using a novel approach for testing the statistical significance of a quantitative reconstruction using random environmental data, in combination with the advantageous large environmental gradients, abundant vegetation types and comprehensive modern pollen databases in China, we describe a new procedure for pollen-based quantitative paleoclimatic reconstructions. First, the most significant environmental variable controlling the fossil pollen assemblage changes is identified. Second, a calibration set to infer changes in this targeted variable is built up, by limiting the modern ranges of other environmental variables. Finally, the pollen-based quantitative reconstruction is obtained and its statistical significance assessed. This novel procedure was used to reconstruct the mean annual precipitation(Pann) from Gonghai Lake in the Lvliang Mountains, and Tianchi Lake in the Liupan Mountains, on the eastern and western fringe of the Chinese Loess Plateau, respectively. Both Pann reconstructions are statistically significant(p<0.001), and a sound and stable correlation relationship exists in their common period, showing a rapid precipitation decrease since 3300 cal yr BP. Thus, we propose that this procedure has great potential for reducing the uncertainties associated with pollen-based quantitative paleoclimatic reconstructions in China.

关 键 词：POLLEN Quantitative reconstructions Statistical significance Marginal areas of the Asian summer monsoon 

分 类 号：P532[天文地球—古生物学与地层学] Q914[天文地球—地质学]