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

doi:10.1007/s11430-017-9095-1

	A novel procedure for pollen-based quantitative paleoclimate reconstructions and its application in China
	Chen JianHui 1; Lv FeiYa 1; Huang XiaoZhong 1; Birks, H. John B.2,3; Telford, Richard J.2,3; Zhang ShengRui 4; Xu QingHai 4; Zhao Yan 5,6; Wang HaiPeng 1; Zhou AiFeng 1
刊名	SCIENCE CHINA-EARTH SCIENCES
	2017-11-01
卷号	60 期号:11 页码:2059-2066
关键词	Pollen Quantitative reconstructions Statistical significance Marginal areas of the Asian summer monsoon
ISSN号	1674-7313
DOI	10.1007/s11430-017-9095-1
通讯作者	Chen JianHui(jhchen@lzu.edu.cn)
英文摘要	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 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 (P-ann) 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 P-ann 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.
资助项目	National Natural Science Foundation of China[41471162] ; National Natural Science Foundation of China[41571182] ; National Key R&D Program of China[2017YFA0603402]
WOS关键词	ASIAN SUMMER MONSOON ; LAST GLACIAL MAXIMUM ; CLIMATE-CHANGE ; LOESS PLATEAU ; PRECIPITATION CHANGES ; HOLOCENE VEGETATION ; TIBETAN PLATEAU ; NORTHERN CHINA ; LAKE ; MIDHOLOCENE
WOS研究方向	Geology
语种	英语
出版者	SCIENCE PRESS
WOS记录号	WOS:000413691300012
资助机构	National Natural Science Foundation of China ; National Key R&D Program of China
内容类型	期刊论文
源URL	[http://ir.igsnrr.ac.cn/handle/311030/61247]
专题	中国科学院地理科学与资源研究所
通讯作者	Chen JianHui
作者单位	1.Lanzhou Univ, Coll Earth & Environm Sci, Minist Educ, Key Lab West Chinas Environm Syst, Lanzhou 730000, Gansu, Peoples R China 2.Univ Bergen, Dept Biol, N-5020 Bergen, Norway 3.Univ Bergen, Bjerknes Ctr Climate Res, N-5020 Bergen, Norway 4.Hebei Normal Univ, Inst Nihewan Archaeol Res, Shijiazhuang 050024, Hebei, Peoples R China 5.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China 6.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
推荐引用方式 GB/T 7714	Chen JianHui,Lv FeiYa,Huang XiaoZhong,et al. A novel procedure for pollen-based quantitative paleoclimate reconstructions and its application in China[J]. SCIENCE CHINA-EARTH SCIENCES,2017,60(11):2059-2066.
APA	Chen JianHui.,Lv FeiYa.,Huang XiaoZhong.,Birks, H. John B..,Telford, Richard J..,...&Wei GuoYing.(2017).A novel procedure for pollen-based quantitative paleoclimate reconstructions and its application in China.SCIENCE CHINA-EARTH SCIENCES,60(11),2059-2066.
MLA	Chen JianHui,et al."A novel procedure for pollen-based quantitative paleoclimate reconstructions and its application in China".SCIENCE CHINA-EARTH SCIENCES 60.11(2017):2059-2066.