基于森林资源清查数据估算中国森林生物量固碳潜力
作者:
作者单位:

国家林业和草原局调查规划设计院

作者简介:

通讯作者:

中图分类号:

基金项目:

国家自然科学基金项目(31400426,41671045);国家重点研发计划(2016YFA0600104);国家留学基金(201403270013)


Estimation of carbon sequestration potential of forest biomass in China based on National Forest Resources Inventory
Author:
Affiliation:

Academy of Forest Inventory and Planning, National Forestry and Grassland Administration

Fund Project:

  • 摘要
  • |
  • 图/表
  • |
  • 访问统计
  • |
  • 参考文献
  • |
  • 相似文献
  • |
  • 引证文献
  • |
  • 文章评论
    摘要:

    森林是全球陆地生态系统中最大的植被碳库和碳汇,森林固碳被认为是各国抵减工业温室气体排放的重要途径,通过森林资源清查数据编制国家温室气体清单也是大多数国家的选择。但是,由于森林固碳本身的复杂性,未来通过森林固碳能够抵消多少工业碳排放往往并不清楚。如何基于森林资源清查数据估算森林的固碳潜力,仍是一个值得深入研究的领域。通过能够公开获得的森林资源清查数据,分起源(人工林和天然林)、36个树种、5个林龄组建立了国家和省两级森林蓄积量年增长量模型,并以第六次森林资源清查期为起点,估算了基线情景(造林、管理、干扰、气候、采伐等条件不变)下2001-2200年前中国森林生物量变化和中国森林生物量固碳潜力。结果认为,天然林蓄积量年增长量一般低于人工林;多数天然林树种的蓄积量增长过程符合理论上认为的中间高、前后低的逻辑斯蒂曲线形式,即中龄林、近熟林、成熟林年增长量高,幼龄林和过熟林年增长量低;人工林蓄积量增长过程多为前期高、后期低的形式,即幼龄林、中龄林和近熟林年增长量高,成熟林和过熟林年增长量低。基线情景下中国森林碳容量为12.82 Pg C,其中人工林为6.6 Pg C,天然林为6.2 Pg C;相对于2001年碳储量来说,到2200年中国森林生物量固碳潜力为6.52 Pg C。综合已有研究认为,中国森林生物量固碳潜力为6.52-13.57 Pg C。本研究可以用于优化森林生长过程模型,为我国森林管理政策的制定提供参考。

    Abstract:

    Forests are the largest carbon pools and sinks of terrestrial ecosystems worldwide. Forest carbon sequestration is an important method for reducing industrial greenhouse gases (GHG) emissions, and an option for conducting nationally determined contributions (NDCs) in most countries that signed the Paris Agreement, which aims to help humans limit global temperature increases by no more than 2℃ from pre-industry level. Most countries prepare national GHG inventories based on forest resources inventory data, which is considered as the most acceptable method. However, a few countries estimated the carbon sequestration potential of forests to offset the industry GHG emission in the future because of the uncertainty of forest carbon sequestration. Estimation of the carbon sequestration potential of forests based on forest resources inventory requires an improved understanding of forest growth and forestry sustainability. In this study, based on the publicly available National Forest Resources Inventory of China, we established a forest volume increase model for natural and planted forests of 36 forest types and five age groups at the national and provincial levels. We used the biomass expansion factor (BEF) to calculate the annual biomass from volume and estimated the carbon carrying capacity and carbon sequestration potential of China's forest biomass in a baseline scenario (maintaining the current state of afforestation, management, disturbance, climate, harvesting, etc.). The results showed that the annual volume increase in natural forests was lower than that in planted forests. For natural forests, the volume slowly increased initially, then rapidly, and then slowly again. Young and over-mature forests increased slowly, while the middle, pre-mature and mature forests increased rapidly. For planted forests, the volume initially increased rapidly and then then slowly. Young, middle, and pre-mature forests increased rapidly, while mature and over-mature forests increased slowly. The carbon carry capacity of Chinese forests was 12.82 Pg C in the baseline scenario, in which the natural and planted forests showed values of 6.2 Pg C and 6.6 Pg C, respectively. The planted forests will reach a peak in 2085, and the natural forests will continue to absorb carbon after 2140. In 2200, the carbon sequestration potential of China's forest biomass will be 6.52 Pg C compared to the forest carbon stock in 2001. Thus, China's forests can conservative sequestrate of 6.52 Pg C even without any improvement or enhancement in forest management. The carbon sequestration potential is 6.52-13.57 Pg C based on our study and published studies. This study can help to improve forest productivity model and planning of climate change mitigation policies and forest management.

    参考文献
    相似文献
    引证文献
引用本文

刘迎春,高显连,付超,于贵瑞,刘兆英.基于森林资源清查数据估算中国森林生物量固碳潜力.生态学报,2019,39(11):4002~4010

复制
分享
文章指标
  • 点击次数:
  • 下载次数:
  • HTML阅读次数:
  • 引用次数: