globalchange  > 过去全球变化的重建
DOI: 10.1016/j.quascirev.2014.06.005
Scopus记录号: 2-s2.0-84903792539
论文题名:
Human influence as a potential source of bias in pollen-based quantitative climate reconstructions
作者: Li J.; Zhao Y.; Xu Q.; Zheng Z.; Lu H.; Luo Y.; Li Y.; Li C.; Seppä H.
刊名: Quaternary Science Reviews
ISSN: 2773791
出版年: 2014
卷: 99
起始页码: 112
结束页码: 121
语种: 英语
英文关键词: Bias ; Calibration models ; Central China ; Climate reconstructions ; Human influence index ; Pollen
Scopus关键词: Calibration ; Charcoal ; Climate change ; Lakes ; Repair ; Vegetation ; Bias ; Calibration model ; Central chinas ; Climate reconstruction ; Human influences ; Pollen ; Climate models ; anthropogenic effect ; calibration ; charcoal ; error analysis ; index method ; paleoclimate ; paleotemperature ; pollen ; precipitation (climatology) ; Quaternary ; reconstruction ; China
英文摘要: Human influence on vegetation is a potential confounding factor in pollen-based quantitative climate reconstructions. Here, we examine this issue in China, a region with intensive and long-lasting human influence. We employ modern datasets for human influence index (HII), climate and pollen over continental China to develop quantitative calibration models for HII and two key climate variables (annual precipitation, PANN; annual mean temperature, TANN). We assess the effect of HII on modern pollen assemblages and individual pollen taxa by comparison with climate variables by using constrained ordination methods and boosted regression trees and apply the calibration models to a pollen record spanning the last 6200 years from Lake Tianchi in central China. The results show that HII has smaller influence on the modern pollen data than PANN and TANN, except for in east-central China where the relationship between pollen data and HII is both statistically and ecologically significant. The reconstructed HII from Lake Tianchi remains relatively stable at 6200-2900cal.yrBP, rises gradually at 2900-1100cal.yrBP, and increases abruptly 1100 years ago. These HII trends are roughly concordant with Holocene charcoal and historical population records. The climate reconstructions change in tune with the HII, with an abrupt decline of PANN and a rise of TANN after 1100cal.yrBP. Other palaeoclimatic data contradict the reconstructed patterns of PANN and TANN during the last millennium, suggesting that the climate reconstructions over the last 11 centuries are seriously biased due to the marked increase of human influence. Such a bias likely exists in other pollen-based climate reconstructions from other regions with strong and long-lasting human influence on vegetation. © 2014 Elsevier Ltd.
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/60192
Appears in Collections:过去全球变化的重建

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作者单位: Department of Geosciences and Geography, University of Helsinki, Gustaf Hällströmin katu 2a, P.O. Box 64, Helsinki 00014, Finland; Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Datun Road, Beijing 100101, China; Institute of Nihewan Archaeology Research, Hebei Normal University, East Road of Southern 2nd Ring, Shijiazhuang 050024, China; College of Resources and Environment Science, Hebei Key Laboratory of Environmental Change and Ecological Construction, Hebei Normal University, East Road of Southern 2nd Ring, Shijiazhuang 050024, China; MOE Key Laboratory of Western China's Environmental System, Lanzhou University, Southern Tianshui Road, Lanzhou 730000, China; Department of Earth Sciences, Sun Yat-sen University, Xingang Xi Road, Guangzhou 510275, China; Key Laboratory of Cenozoic Geology and Environment, Institute of Geology and Geophysics, Chinese Academy of Sciences, Beitucheng Western Road, Beijing 100029, China; Institute of Botany, Chinese Academy of Sciences, Xiangshan Nanxincun, Beijing 100093, China; State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, East Beijing Road, Nanjing 210008, China

Recommended Citation:
Li J.,Zhao Y.,Xu Q.,et al. Human influence as a potential source of bias in pollen-based quantitative climate reconstructions[J]. Quaternary Science Reviews,2014-01-01,99
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