›› 2014, Vol. 24 ›› Issue (2): 249-268.doi: 10.1007/s11442-014-1086-2

• Research Articles • 上一篇    下一篇

Combining LPJ-GUESS and HASM to simulate the spatial distribution of forest vegetation carbon stock in China

ZHAO Mingwei1,2, YUE Tianxiang1, ZHAO Na1,2, SUN Xiaofang3, ZHANG Xingying4   

  1. 1. State Key Laboratory of Resources and Environment Information System, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100010, China;
    2. University of Chinese Academy of Sciences, Beijing 100049, China;
    3. School of Geography and Tourism, Qufu Normal University, Rizhao 276800, Shandong, China;
    4. National Satellite Meteorological Center, China Meteorological Administration, Beijing 100081, China
  • 收稿日期:2013-10-23 修回日期:2013-11-30 出版日期:2014-04-15 发布日期:2014-03-24
  • 通讯作者: Yue Tianxiang, Professor, E-mail:yue@lreis.ac.cn E-mail:yue@lreis.ac.cn
  • 作者简介:Zhao Mingwei, PhD Candidate, specialized in ecological modeling and system simulation. E-mail:zhaomw@ lreis.ac.cn
  • 基金资助:

    National High-tech R&D Program of the Ministry of Science and Technology of the People's Republic of China, No.2013AA122003; National Key Technologies R&D Program of the Ministry of Science and Technology of China, No.2013BACO3B05

Combining LPJ-GUESS and HASM to simulate the spatial distribution of forest vegetation carbon stock in China

ZHAO Mingwei1,2, YUE Tianxiang1, ZHAO Na1,2, SUN Xiaofang3, ZHANG Xingying4   

  1. 1. State Key Laboratory of Resources and Environment Information System, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100010, China;
    2. University of Chinese Academy of Sciences, Beijing 100049, China;
    3. School of Geography and Tourism, Qufu Normal University, Rizhao 276800, Shandong, China;
    4. National Satellite Meteorological Center, China Meteorological Administration, Beijing 100081, China
  • Received:2013-10-23 Revised:2013-11-30 Online:2014-04-15 Published:2014-03-24
  • Contact: Yue Tianxiang, Professor, E-mail:yue@lreis.ac.cn E-mail:yue@lreis.ac.cn
  • About author:Zhao Mingwei, PhD Candidate, specialized in ecological modeling and system simulation. E-mail:zhaomw@ lreis.ac.cn
  • Supported by:

    National High-tech R&D Program of the Ministry of Science and Technology of the People's Republic of China, No.2013AA122003; National Key Technologies R&D Program of the Ministry of Science and Technology of China, No.2013BACO3B05

摘要:

It is very important in accurately estimating the forests' carbon stock and spatial distribution in the regional scale because they possess a great rate in the carbon stock of the terrestrial ecosystem. Yet the current estimation of forest carbon stock in the regional scale mainly depends on the forest inventory data,and the whole process consumes too much labor,money and time. And meanwhile it has many negative influences on the forest carbon storage updating. In order to figure out these problems,this paper,based on High Accuracy Surface Modeling (HASM),proposes a forest vegetation carbon storage simulation method. This new method employs the output of LPJ-GUESS model as initial values of HASM and uses the inventory data as sample points of HASM to simulate the distribution of forest carbon storage in China. This study also adopts the seventh forest resources statistics of China as the data source to generate sample points,and it also works as the simulation accuracy test. The HASM simulation shows that the total forest carbon storage of China is 9.2405 Pg,while the calculated value based on forest resources statistics are 7.8115 Pg. The forest resources statistics is taken based on a forest canopy closure,and the result of HASM is much more suitable to the real forest carbon storage. The simulation result also indicates that the southwestern mountain region and the northeastern forests are the important forest carbon reservoirs in China,and they account for 39.82% and 20.46% of the country's total forest vegetation carbon stock respectively. Compared with the former value (1975-1995),it manifests that the carbon storage of the two regions do increase clearly. The results of this research show that the large-scale reforestation in the last decades in China attains a significant carbon sink.

关键词: forest carbon storage, initial value, sample points, LPJ-GUESS, HASM

Abstract:

It is very important in accurately estimating the forests' carbon stock and spatial distribution in the regional scale because they possess a great rate in the carbon stock of the terrestrial ecosystem. Yet the current estimation of forest carbon stock in the regional scale mainly depends on the forest inventory data,and the whole process consumes too much labor,money and time. And meanwhile it has many negative influences on the forest carbon storage updating. In order to figure out these problems,this paper,based on High Accuracy Surface Modeling (HASM),proposes a forest vegetation carbon storage simulation method. This new method employs the output of LPJ-GUESS model as initial values of HASM and uses the inventory data as sample points of HASM to simulate the distribution of forest carbon storage in China. This study also adopts the seventh forest resources statistics of China as the data source to generate sample points,and it also works as the simulation accuracy test. The HASM simulation shows that the total forest carbon storage of China is 9.2405 Pg,while the calculated value based on forest resources statistics are 7.8115 Pg. The forest resources statistics is taken based on a forest canopy closure,and the result of HASM is much more suitable to the real forest carbon storage. The simulation result also indicates that the southwestern mountain region and the northeastern forests are the important forest carbon reservoirs in China,and they account for 39.82% and 20.46% of the country's total forest vegetation carbon stock respectively. Compared with the former value (1975-1995),it manifests that the carbon storage of the two regions do increase clearly. The results of this research show that the large-scale reforestation in the last decades in China attains a significant carbon sink.

Key words: forest carbon storage, initial value, sample points, LPJ-GUESS, HASM