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Volume 30 Issue 1

Jan.  2013

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Article >  ADVANCES IN ATMOSPHERIC SCIENCES  > 2013 >  30(1): 116-124

Evaluating the Tree Population Density and Its Impacts in CLM-DGVM

  • 1.

    International Center for Climate and Environment Sciences, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, University of Chinese Academy of Sciences, Beijing 100049;International Center for Climate and Environment Sciences, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029;International Center for Climate and Environment Sciences, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, University of Chinese Academy of Sciences, Beijing 100049


doi: 10.1007/s00376-012-1271-0

  • Vegetation population dynamics play an essential role in shaping the structure and function of terrestrial ecosystems. However, large uncertainties remain in the parameterizations of population dynamics in current Dynamic Global Vegetation Models (DGVMs). In this study, the global distribution and probability density functions of tree population densities in the revised Community Land Model-Dynamic Global Vegetation Model (CLM-DGVM) were evaluated, and the impacts of population densities on ecosystem characteristics were investigated. The results showed that the model predicted unrealistically high population density with small individual size of tree PFTs (Plant Functional Types) in boreal forests, as well as peripheral areas of tropical and temperate forests. Such biases then led to the underestimation of forest carbon storage and incorrect carbon allocation among plant leaves, stems and root pools, and hence predicted shorter time scales for the building/recovering of mature forests. These results imply that further improvements in the parameterizations of population dynamics in the model are needed in order for the model to correctly represent the response of ecosystems to climate change.
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    [2] SONG Xiang and ZENG Xiaodong*, , 2014: Investigation of Uncertainties of Establishment Schemes in Dynamic Global Vegetation Models, ADVANCES IN ATMOSPHERIC SCIENCES, 31, 85-94.  doi: 10.1007/s00376-013-3031-1
    [3] ZENG Xiaodong, 2010: Evaluating the Dependence of Vegetation on Climate in an Improved Dynamic Global Vegetation Model, ADVANCES IN ATMOSPHERIC SCIENCES, 27, 977-991.  doi: 10.1007/s00376-009-9186-0
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    • Manuscript History

    Manuscript received: 10 January 2013
    Manuscript revised: 10 January 2013
    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

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    Evaluating the Tree Population Density and Its Impacts in CLM-DGVM

    • 1. International Center for Climate and Environment Sciences, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, University of Chinese Academy of Sciences, Beijing 100049;International Center for Climate and Environment Sciences, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029;International Center for Climate and Environment Sciences, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, University of Chinese Academy of Sciences, Beijing 100049
    • Manuscript received: 2013-01-10
    • Manuscript revised: 2013-01-10

    Abstract: Vegetation population dynamics play an essential role in shaping the structure and function of terrestrial ecosystems. However, large uncertainties remain in the parameterizations of population dynamics in current Dynamic Global Vegetation Models (DGVMs). In this study, the global distribution and probability density functions of tree population densities in the revised Community Land Model-Dynamic Global Vegetation Model (CLM-DGVM) were evaluated, and the impacts of population densities on ecosystem characteristics were investigated. The results showed that the model predicted unrealistically high population density with small individual size of tree PFTs (Plant Functional Types) in boreal forests, as well as peripheral areas of tropical and temperate forests. Such biases then led to the underestimation of forest carbon storage and incorrect carbon allocation among plant leaves, stems and root pools, and hence predicted shorter time scales for the building/recovering of mature forests. These results imply that further improvements in the parameterizations of population dynamics in the model are needed in order for the model to correctly represent the response of ecosystems to climate change.

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