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A novel procedure for pollen-based quantitative paleoclimate reconstructions and its application in China.
- Source :
- SCIENCE CHINA Earth Sciences; Nov2017, Vol. 60 Issue 11, p2059-2066, 8p
- Publication Year :
- 2017
-
Abstract
- 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 ) 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 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. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 16747313
- Volume :
- 60
- Issue :
- 11
- Database :
- Complementary Index
- Journal :
- SCIENCE CHINA Earth Sciences
- Publication Type :
- Academic Journal
- Accession number :
- 125872486
- Full Text :
- https://doi.org/10.1007/s11430-017-9095-1