基于HASM的中国森林植被碳储量空间分布模拟

doi:10.11821/dlxb201309005

地理学报 ›› 2013, Vol. 68 ›› Issue (9): 1212-1224.doi: 10.11821/dlxb201309005

基于HASM的中国森林植被碳储量空间分布模拟

赵明伟^1,2, 岳天祥¹, 赵娜^1,2, 孙晓芳³

1. 中国科学院地理科学与资源研究所资源环境信息系统国家重点实验室, 北京 100101;
2. 中国科学院大学, 北京 100049;
3. 曲阜师范大学地理与旅游学院, 日照 276800

收稿日期:2013-05-20 修回日期:2013-06-21 出版日期:2013-09-05 发布日期:2013-09-05
作者简介:赵明伟(1986- ), 博士研究生, 研究方向为资源环境与生态系统模拟。E-mail: zhaomw@lreis.ac.cn
基金资助:
国家高技术研究发展计划项目(2013AA122003);国家科技支撑计划(2013BACO3B05)

Spatial distribution of forest vegetation carbon stock in China based on HASM

ZHAO Mingwei^1,2, YUE Tianxiang¹, ZHAO Na^1,2, SUN Xiaofang³

1. State Key Laboratory of Resources and Environment Information System, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China;
2. University of Chinese Academy of Sciences, Beijing 100049, China;
3. School of Geography and Tourism, Qufu Normal University, Rizhao 276800, Shandong, China

Received:2013-05-20 Revised:2013-06-21 Online:2013-09-05 Published:2013-09-05
Contact: 岳天祥(1963- ), 博士, 研究员, 中国地理学会会员(S110007693M), 研究方向为资源环境地学模型与系统模拟。E-mail: yue@lreis.ac.cn
Supported by:
Foundation 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 the People's Republic of China, No. 2013BACO3B05

摘要/Abstract

摘要： 当前区域尺度上森林碳储量估算主要依据森林资源清查数据,整个过程不仅消耗大量人力、物力,而且十分耗时,严重影响了森林碳储量估算的时效性。针对这一问题,本文提出了基于HASM的森林植被碳储量模拟方法,该方法以全球植被动态模型LPJ-Guess 输出的植被碳储量为驱动场,以森林清查样地数据为精度控制点,模拟生成中国陆地森林碳储量分布情况。研究以第7 次中国森林资源清查数据作为精度控制点数据源,同时作为本文模拟方法的精度验证。结果表明,中国森林碳储量为9.2405 Pg,考虑到森林资源清查是基于一定的郁闭度进行的,因此HASM模拟的结果与根据森林资源清查结果计算得出的7.8115 Pg 相比更符合实际情况,西南山区和东北林区是中国森林最主要的碳库,其碳储量分别占中国森林植被碳储量的39.82%和20.46%。同时与之前(1975-1995 年) 相比具有较大幅度的增长,表明近几十年来中国坚持大规模植树造林的碳汇效果显著。同时也表明基于HASM的森林植被碳储量空间分布模拟方法是有效的,模拟结果合理且精度较高,表明该方法在全球尺度上森林植被碳储量模拟及其它生态系统中碳储量模拟中具有应用潜力。

关键词: 驱动场, 精度控制条件, HASM, LPJ-Guess, 森林碳储量

Abstract: As the forests are the main carbon stock reservoir of the terrestrial ecosystem, it is of great importance to estimate its carbon stock and spatial distribution accurately in regional scale. However, the current estimation of forest carbon stock in regional scale primarily depends on the forest inventory data, and the whole process of it consumes labor, money and time, and influences the update of the forest carbon storage at the same time. With the purpose of solving these problems, this paper puts forward a forest vegetation carbon storage simulation method based on HASM. This new method takes 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. The research takes the 7th forest resources statistics of China as the data source to produce sample points, and it also serves as the simulation accuracy test. The HASM simulation makes it clear that the total forest carbon storage of China is 9.2405 Pg, and the calculated value based on forest resources statistics is 7.8115 Pg. As regards that the forest resources statistics is taken based on a forest canopy closure, the result of HASM is much more suitable to the real forest carbon storage. The simulation result also demonstrates that the southwestern mountainous and the northeastern forests are the dominating forest carbon reservoirs in China, and they account for 39.82% and 20.46% respectively. Compared with the former value (1975-1995), the carbon storage of the two regions did increase apparently. The results of this research indicate that the large reforestation in the last decades in China attains a significant carbon sink.

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

赵明伟, 岳天祥, 赵娜, 孙晓芳. 基于HASM的中国森林植被碳储量空间分布模拟[J]. 地理学报, 2013, 68(9): 1212-1224.

ZHAO Mingwei, YUE Tianxiang, ZHAO Na, SUN Xiaofang. Spatial distribution of forest vegetation carbon stock in China based on HASM[J]. Acta Geographica Sinica, 2013, 68(9): 1212-1224.

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基于HASM的中国森林植被碳储量空间分布模拟

Spatial distribution of forest vegetation carbon stock in China based on HASM

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