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New coupled model used inversely for reconstructing past terrestrial carbon storage from pollen data: validation of model using modern data

Authors

  • HAIBIN WU,

    1. State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an 710075, China,
    2. CEREGE, UMR 6635, CNRS/Aix-Marseille Université, BP 80, 13545 Aix-en-Provence Cedex 4, France,
    3. Institut des Sciences de l'Environnement, Département des Sciences Biologiques, Université du Québec à Montréal, Montréal H3C 3P8, Canada,
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  • JOËL GUIOT,

    1. CEREGE, UMR 6635, CNRS/Aix-Marseille Université, BP 80, 13545 Aix-en-Provence Cedex 4, France,
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  • CHANGHUI PENG,

    1. Institut des Sciences de l'Environnement, Département des Sciences Biologiques, Université du Québec à Montréal, Montréal H3C 3P8, Canada,
    2. Ecology Research Section, Central-South University of Forestry and Technology, Changsha, Hunan 410004, China,
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  • ZHENGTANG GUO

    1. Institute of Geology and Geophysics, Chinese Academy of Sciences, PO Box 9825, Beijing 100029, China
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Changhui Peng, Institut des Sciences de l'environnement, Université du Québec à Montréal, Case postale 8888, succ Centre-Ville, Montréal (QC), Canada H3C 3P8. tel. +1 514 987 3000, ext. 1056, fax +1 514 987 4718, e-mail: peng.changhui@uqam.ca

Abstract

The knowledge of potential impacts of climate change on terrestrial vegetation is crucial to understand long-term global carbon cycle development. Discrepancy in data has long existed between past carbon storage reconstructions since the Last Glacial Maximum by way of pollen, carbon isotopes, and general circulation model (GCM) analysis. This may be due to the fact that these methods do not synthetically take into account significant differences in climate distribution between modern and past conditions, as well as the effects of atmospheric CO2 concentrations on vegetation. In this study, a new method to estimate past biospheric carbon stocks is reported, utilizing a new integrated ecosystem model (PCM) built on a physiological process vegetation model (BIOME4) coupled with a process-based biospheric carbon model (DEMETER). The PCM was constrained to fit pollen data to obtain realistic estimates. It was estimated that the probability distribution of climatic parameters, as simulated by BIOME4 in an inverse process, was compatible with pollen data while DEMETER successfully simulated carbon storage values with corresponding outputs of BIOME4. The carbon model was validated with present-day observations of vegetation biomes and soil carbon, and the inversion scheme was tested against 1491 surface pollen spectra sample sites procured in Africa and Eurasia. Results show that this method can successfully simulate biomes and related climates at most selected pollen sites, providing a coefficient of determination (R) of 0.83–0.97 between the observed and reconstructed climates, while also showing a consensus with an R-value of 0.90–0.96 between the simulated biome average terrestrial carbon variables and the available observations. The results demonstrate the reliability and feasibility of the climate reconstruction method and its potential efficiency in reconstructing past terrestrial carbon storage.

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