植物生态学报 ›› 2009, Vol. 33 ›› Issue (3): 516-534.DOI: 10.3773/j.issn.1005-264x.2009.03.011

• 研究论文 • 上一篇    下一篇

北京山区3种暖温带森林生态系统未来碳平衡的模拟与分析

刘瑞刚1,2, 李娜1,2, 苏宏新1, 桑卫国1,*()   

  1. 1 中国科学院植物研究所植被与环境变化国家重点实验室,北京 100093
    2 中国科学院研究生院,北京 100049
  • 收稿日期:2008-07-25 接受日期:2009-01-04 出版日期:2009-07-25 发布日期:2009-05-31
  • 通讯作者: 桑卫国
  • 作者简介:*E-mail: swg@ibcas.ac.cn
  • 基金资助:
    国家自然科学基金(30590382);外国专家局、教育部中央民族大学项目(2008-B08044)

SIMULATION AND ANALYSIS ON FUTURE CARBON BALANCE OF THREE DECIDUOUS FORESTS IN BEIJING MOUNTAIN AREA, WARM TEMPERATE ZONE OF CHINA

LIU Rui-Gang1,2, LI Na1,2, SU Hong-Xin1, SANG Wei-Guo1,*()   

  1. 1State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China
    2Graduate University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2008-07-25 Accepted:2009-01-04 Online:2009-07-25 Published:2009-05-31
  • Contact: SANG Wei-Guo

摘要:

使用LPJ-GUESS植被动态模型, 在北京山区研究了未来100a以辽东栎 (Quercus liaotungensis) 为优势种的落叶阔叶林、以白桦 (Betula platyphylla) 为主的阔叶林和油松 (Pinus tabulaeformis) 为优势种的针阔混交林的碳变化, 定量分析了生态系统净初级生产力 (NPP) 、土壤异养呼吸 (Rh) 、净生态系统碳交换 (NEE) 和碳生物量 (Carbon bio-mass) 对两种未来气候情景 (SRES A2和B2) 以及相应大气CO2浓度变化情景的响应特征。结果表明:1) 未来100a两种气候情景下3种森林生态系统的NPP和Rh均增加, 并且A2情景下增加的程度更大;2) 由于3种生态系统树种组成的不同, 未来气候情景下各自NPP和Rh增加的比例不同, 导致三者NEE的变化也相异:100a后辽东栎林由碳汇转变为弱碳源, 白桦林仍保持为碳汇但功能减弱, 油松林成为一个更大的碳汇;3) 3种森林生态系统的碳生物量在未来气候情景下均增大, 21世纪末与20世纪末相比:辽东栎林在A2情景下碳生物量增加的比例为27.6%, 大于B2情景下的19.3%;白桦林和油松林在B2情景下碳生物量增加的比例分别为34.2%和52.2%, 大于A2情景下的30.8%和28.4%。

关键词: 净初级生产力, 土壤异养呼吸, 净生态系统碳交换, 碳循环, 气候变化, LPJ-GUESS模型, 气候情景

Abstract:

Aims Climate change is expected to cause changes of carbon cycling in forest ecosystems, and prediction research suggests there is dramatic spatial heterogeneity and uncertainty in responses of carbon balance of forest ecosystems to climate change. The goals of our research were to predict and analyze impacts of climate change on the carbon cycling of warm temperate forests in Beijing mountain area in the next 100 years and to understand the heterogeneity and uncertainty on the ecosystem scale with LPJ-GUESS model.

Methods The ecosystem model was used to learn how forest ecosystem productivity and carbon bal-ance change in a long-term time scale and to learn about differences of carbon balance among various ecosystems by comparing ecosystem components of carbon balance. The dynamic vegetation model (LPJ-GUESS), used for the first time in China and driven by A2 and B2 greenhouse gas emission sce-narios of the Special Report on Emissions Scenarios (SRES) of IPCC, projected climate change impacts on carbon balance for three typical warm temperate forest ecosystems (oak, birch and Chinese pine forests) in the Dongling Mountain area of Beijing, China.

Important findings Net ecosystem primary productivity (NPP) and heterotrophic respiration (Rh) will increase in the three forests, and the A2 scenario was associated with larger changes in NPP and Rh than the B2 scenario. Because of differences in species composition among the forests, increases in NPP and Rh were different and changes in net ecosystem exchange (NEE) were different among the forests: oakforest switched from a sink to a small source of carbon, birch forest remained as a smaller sink of carbon, and Chinese pine forest became a larger carbon sink over the next 100 years. Also, carbon biomass will generally increase in the forests by 2100. Comparing SRES A2 with B2, there was larger carbon storage in the relative lower emission scenario (B2). Projected differences in carbon balance among these forests in the same area were more dependent on species composition than climate factors (A2 and B2 scenarios) under future climate change.

Key words: NPP, Rh, NEE, carbon flux, carbon balance, LPJ-GUESS model, climate change