中国草地生态管理的土壤碳汇模拟研究——基于IPCC清单方法

doi:10.12006/j.issn.1673-1719.2022.255

气候变化研究进展 ›› 2023, Vol. 19 ›› Issue (3): 371-380.doi: 10.12006/j.issn.1673-1719.2022.255

中国草地生态管理的土壤碳汇模拟研究——基于IPCC清单方法

胡国铮¹^,², 干珠扎布¹^,³, 李铭杰¹^,², 余沛东¹^,², 高清竹¹^,³()

1 中国农业科学院农业环境与可持续发展研究所，北京 100081
2 国家农业环境数据中心，北京 100081
3 中国农业科学院农业农村碳达峰碳中和研究中心，北京 100081

收稿日期:2022-11-08 修回日期:2023-01-05 出版日期:2023-05-30 发布日期:2023-04-28
通讯作者: 高清竹，男，研究员，gaoqingzhu@caas.cn
作者简介:胡国铮，男，副研究员
基金资助:
第二次青藏高原综合考察研究(2019QZKK0307);国家自然科学基金项目(31800383);中国农业科学院基本科研业务费专项(Y2022LM16)

Study on the simulation of soil carbon sink in grassland ecological management in China — based on IPCC inventory method

HU Guo-Zheng¹^,², HASBAGAN Ganjurjav¹^,³, LI Ming-Jie¹^,², YU Pei-Dong¹^,², GAO Qing-Zhu¹^,³()

1 Institute of Environment and Sustainable Development for Agriculture, Chinese Academy of Agricultural Sciences, Beijing 100081, China
2 National Data Center of Agricultural Environment, Beijing 100081, China
3 Research Center of Emission Peak and Carbon Neutralization in Agriculture and Rural Affairs, Chinese Academy of Agricultural Sciences, Beijing 100081, China

Received:2022-11-08 Revised:2023-01-05 Online:2023-05-30 Published:2023-04-28

摘要/Abstract

摘要：

草地是中国重要的生态系统碳库，中国为治理草地退化和荒漠化实施了多项草地生态保护建设项目。为了探讨生态系统管理对碳汇的影响，文中基于中国草地生态管理活动水平，设定4个草地生态管理的未来情景，采用IPCC国家温室气体清单指南方法，估算和模拟了中国2001—2030年草地土壤碳汇。结果表明：2001—2010年中国草地土壤碳汇平均为-0.54亿t CO₂ eq/a，2011—2017年显著提升为平均-1.00亿t CO₂ eq/a;未来不同草地生态管理情景下中国草地土壤碳汇在-0.42亿t CO₂ eq/a~-2.00亿t CO₂ eq/a，2018—2030年草地土壤累积碳汇量为-5.46亿~-26.01亿t CO₂ eq。本研究为中国未来草地生态管理政策的制定提供参考。

关键词: 草地生态管理, 土壤碳汇, IPCC清单方法, 模拟

Abstract:

Grassland is an important ecosystem carbon pool in China. Several grassland ecological protection projects have been implemented to control grassland degradation and desertification in China. To reveal the impact of ecological management on ecosystem carbon sequestration, four future scenarios of grassland ecological management were set based on the current intensity of grassland ecological managements. Grassland soil carbon sequestration was estimated in China from 2001 to 2030 by using the IPCC Method for National Greenhouse Gas Inventories. The results showed that the mean grassland carbon sequestration was -0.54×10⁸ t CO₂ eq/a from 2001 to 2010 in China. The grassland soil carbon sequestration significantly increased to -1.00×10⁸ t CO₂ eq/a on average during 2011-2017. Under different grassland ecological management scenarios, the grassland soil carbon sequestration is -0.42×10⁸ to -2.00×10⁸ t CO₂ eq/a in China. And grassland soil will sequestrate -5.46×10⁸ to -26.01×10⁸ t CO₂ eq accumulatively from 2018 to 2030. This study provides reference for the formulation of future grassland ecological management policies.

Key words: Grassland ecological management, Soil carbon sequestration, IPCC inventory, Simulation

胡国铮, 干珠扎布, 李铭杰, 余沛东, 高清竹. 中国草地生态管理的土壤碳汇模拟研究——基于IPCC清单方法[J]. 气候变化研究进展, 2023, 19(3): 371-380.

HU Guo-Zheng, HASBAGAN Ganjurjav, LI Ming-Jie, YU Pei-Dong, GAO Qing-Zhu. Study on the simulation of soil carbon sink in grassland ecological management in China — based on IPCC inventory method[J]. Climate Change Research, 2023, 19(3): 371-380.

图/表 9

表1 2000—2015年中国草地生态工程

Table 1 Grassland ecological projects in China from 2000 to 2015

表2 草地生态管理和草地退化土壤碳变化因子

Table 2 Emission factors of grassland ecological managements and degradation

表3 各草地类型土壤有机质、容重、面积比例和退化比例

Table 3 Soil organic matter, buck density, area ratio and degradation ratio of each grassland type

图1 我国各草地生态管理面积注：橘色阴影为线性模型的信度范围，情景一的不确定性范围为滑动平均值的信度范围，模拟值和其他情景的不确定性为线性模型的预测范围。

Fig. 1 Grassland ecological management area of China. (Orange area represents the confident range. The uncertainty of scenario 1 is the confident range of moving average. The uncertainty of simulation and other scenarios are the predictive range of linear models)

表4 本研究的草地碳汇与其他研究结果对比

Table 4 Grassland carbon sequestration comparation between this study and other studies

图2 2001—2017年我国草地每5年碳汇量

Fig. 2 Grassland carbon sequestration of China in every 5 years during 2001-2017

图3 2001—2030年我国草地碳汇动态

Fig. 3 Grassland carbon sequestration dynamics of China from 2001 to 2030

图4 世界各国“仍为草地的草地”温室气体排放量注：除中国为2014年数据外，其他国家为2019年数据。

Fig. 4 Greenhouse gas (GHG) emission of “grassland remaining grassland” of each country

图5 1990—2019年世界主要经济体“仍为草地的草地”温室气体排放量

Fig. 5 GHG emission of “grassland remaining grassland” of world major economies from 1990 to 2019

参考文献 40

[1]	王国胜, 孙涛, 昝国盛, 等. 陆地生态系统碳汇在实现“双碳”目标中的作用和建议[J]. 中国地质调查, 2021, 8 (4): 13-19.
	Wang G S, Sun T, Zan G S, et al. Roles and suggestions of terrestrial ecosystem carbon sink in achieving carbon emission peak and carbon neutrality in China[J]. Geological Survey of China, 2021, 8 (4): 13-19 (in Chinese)
[2]	国家信息通报. 中华人民共和国气候变化第二次两年更新报告[R]. 北京: 国家信息中心, 2018.
	National Communication. The people’s Republic of China second biennial update report on climate change[R]. Beijing: State Information Center, 2018 (in Chinese)
[3]	张雅欣, 罗荟霖, 王灿. 碳中和行动的国际趋势分析[J]. 气候变化研究进展, 2021, 17 (1): 88-97.
	Zhang Y X, Luo H L, Wang C. Progress and trends of global carbon neutrality pledges[J]. Climate Change Research, 2021, 17 (1): 88-97 (in Chinese)
[4]	方精云. 碳中和的生态学透视[J]. 植物生态学报, 2021, 45 (11): 1-4.
	Fang J Y. Ecological perspectives of carbon neutrality[J]. Chinese Journal of Plant Ecology, 2021, 45 (11): 1-4 (in Chinese) doi: 10.17521/cjpe.2020.0246 URL
[5]	Tang X L, Zhao X, Bai Y F, et al. Carbon pools in China’s terrestrial ecosystems: new estimates based on an intensive field survey[J]. Proceedings of the National Academy of Sciences of the United States of America, 2018, 115 (16): 4021-4026
[6]	韩俊. 中国草原生态问题调查[M]. 上海: 上海远东出版社, 2011.
	Han J. Survey on ecological issues of China’s grassland[M]. Shanghai: Shanghai Far East Publishers, 2011 (in Chinese)
[7]	Xie Z B, Zhu J G, Liu G, et al. Soil organic carbon stocks in China and changes from 1980s to 2000s[J]. Global Change Biology, 2007, 13 (9): 1989-2007 doi: 10.1111/gcb.2007.13.issue-9 URL
[8]	Ren Y J, Lyu Y H, Fu B J. Quantifying the impacts of grassland restoration on biodiversity and ecosystem services in China: a Meta-analysis[J]. Ecological Engineering, 2016, 95: 542-550 doi: 10.1016/j.ecoleng.2016.06.082 URL
[9]	Lu F, Hu H F, Sun W J, et al. Effects of national ecological restoration projects on carbon sequestration in China from 2001 to 2010[J]. Proceedings of the National Academy of Sciences of the United States of America, 2018, 115 (16): 4039-4044 doi: 10.1073/pnas.1700294115 pmid: 29666317
[10]	朴世龙, 何悦, 王旭辉, 等. 中国陆地生态系统碳汇估算: 方法、进展、展望[J]. 中国科学: 地球科学, 2022, 52 (6): 1010-1020.
	Piao S L, He Y, Wang X H, et al. Estimation of China’s terrestrial ecosystem carbon sink: methods, progress and prospects[J]. Science China Earth Sciences, 2022, 52 (6): 1010-1020 (in Chinese)
[11]	蔡博峰, 朱松丽, 于胜民, 等. 《IPCC 2006年国家温室气体清单指南2019修订版》解读[J]. 环境工程, 2019, 37 (8): 1-11.
	Cai B F, Zhu S L, Yu S M, et al. The interpretation of 2019 refinement to the 2006 IPCC guidelines for national greenhouse gas inventory[J]. Environmental Engineering, 2019, 37 (8): 1-11 (in Chinese)
[12]	IPCC. 2019 refinement to the 2006 IPCC guidelines for national greenhouse gas inventories[M]. Cambridge: Cambridge University Press, 2019
[13]	罗文蓉, 胡国铮, 高清竹. 草地生态管理下内蒙古草地土壤有机碳库动态研究[J]. 生态与农村环境学报, 2020, 36 (12): 1588-1597.
	Luo W R, Hu G Z, Gao Q Z. Dynamic study on soil organic carbon reservoir in Inner Mongolia grassland under grassland ecological management[J]. Journal of Ecology and Rural Environment, 2020, 36 (12): 1588-1597 (in Chinese)
[14]	石锋, 李玉娥, 高清竹, 等. 管理措施对我国草地土壤有机碳的影响[J]. 草业科学, 2009, 26 (3): 9-15.
	Shi F, Li Y E, Gao Q Z, et al. Effects of managements on soil organic carbon of grassland in China[J]. Pratacultural Science, 2009, 26 (3): 9-15 (in Chinese)
[15]	戴尔阜, 黄宇, 赵东升. 草地土壤固碳潜力研究进展[J]. 生态学报, 2015, 35 (12): 3908-3918.
	Dai E F, Huang Y, Zhao D S. Review on soil carbon sequestration potential in grassland ecosystems[J]. Acta Ecologica Sinica, 2015, 35 (12): 3908-3918 (in Chinese)
[16]	中华人民共和国农业部畜牧兽医司, 全国畜牧兽医总站. 中国草地资源[M]. 北京: 中国科学技术出版社, 1996.
	Department of Animal Husbandry and Veterinary Medicine, Ministry of Agriculture of the People’s Republic of China, National Animal Husbandry and Veterinary Station. Rangeland resources of China[M]. Beijing: China Science and Technology Press, 1996 (in Chinese)
[17]	Cao X J, Gao Q Z, Hasbagan G, et al. Influence of climatic factors on variation in the Normalised Difference Vegetation Index in Mongolian Plateau grasslands[J]. The Rangeland Journal, 2018, 40 (2): 91-100 doi: 10.1071/RJ16073 URL
[18]	曹旭娟, 干珠扎布, 胡国铮, 等. 基于NDVI3g数据反演的青藏高原草地退化特征[J]. 中国农业气象, 2019, 40 (2): 86-95.
	Cao X J, Hasbagan G, Hu G Z, et al. Characteristics of grassland degradation in the Qinghai Tibetan Plateau, based on NDVI3g Data[J]. Chinese Journal of Agrometeorology, 2019, 40 (2): 86-95 (in Chinese)
[19]	全国畜牧总站. 中国草业统计2001—2005[M]. 北京: 中国农业出版社, 2017.
	National Animal Husbandry and Veterinary Station. China grassland statistics 2001-2005[M]. Beijing: China Agriculture Press, 2017 (in Chinese)
[20]	全国畜牧总站. 中国草业统计2006—2010[M]. 北京: 中国农业出版社, 2018.
	National Animal Husbandry and Veterinary Station. China grassland statistics 2006-2010[M]. Beijing: China Agriculture Press, 2018 (in Chinese)
[21]	全国畜牧总站. 中国草业统计2011—2015[M]. 北京: 中国农业出版社, 2019.
	National Animal Husbandry and Veterinary Station. China grassland statistics 2011-2015[M]. Beijing: China Agriculture Press, 2019 (in Chinese)
[22]	全国畜牧总站. 中国草业统计2016[M]. 北京: 中国农业出版社, 2017.
	National Animal Husbandry and Veterinary Station. China grassland statistics 2016 [M]. Beijing: China Agriculture Press, 2017 (in Chinese)
[23]	全国畜牧总站. 中国草业统计2017[M]. 北京: 中国农业出版社, 2018.
	National Animal Husbandry and Veterinary Station. China grassland statistics 2017 [M]. Beijing: China Agriculture Press, 2018 (in Chinese)
[24]	Tian H Q, Melillo J, Lu C Q, et al. China’s terrestrial carbon balance: contributions from multiple global change factors[J]. Global Biogeochemical Cycles, 2011, 25 (1): GB1007
[25]	Fang J Y, Guo Z D, Piao S L, et al. Terrestrial vegetation carbon sinks in China, 1981-2000 [J]. Science in China (Series D: Earth Sciences), 2007, 9: 1341-1350
[26]	Piao S L, Fang J Y, Ciais P, et al. The carbon balance of terrestrial ecosystems in China[J]. Nature, 2009, 458 (7241): 1009-1013 doi: 10.1038/nature07944 URL
[27]	Jiang F, Wang H W, Chen J M, et al. Nested atmospheric inversion for the terrestrial carbon sources and sinks in China[J]. Biogeosciences, 2013, 10 (8): 5311-5324 doi: 10.5194/bg-10-5311-2013 URL
[28]	国家信息通报. 中华人民共和国气候变化第三次国家信息通报[R]. 北京: 国家信息中心, 2018.
	National Communication. The People’s Republic of China third national communication on climate change[R]. Beijing: State Information Center, 2018 (in Chinese)
[29]	国家信息通报. 中华人民共和国气候变化初始国家信息通报[R]. 北京: 国家信息中心, 2004.
	National Communication. The People’s Republic of China initial national communication on climate change[R]. Beijing: State Information Center, 2004 (in Chinese)
[30]	国家信息通报. 中华人民共和国气候变化第一次两年更新报告[R]. 北京: 国家信息中心, 2017.
	National Communication. The People’s Republic of China first biennial update report on climate change[R]. Beijing: State Information Center, 2017 (in Chinese)
[31]	国家信息通报. 中华人民共和国气候变化第二次国家信息通报[R]. 北京: 国家信息中心, 2012.
	National Communication. The People’s Republic of China second national communication on climate change[R]. Beijing: State Information Center, 2012 (in Chinese)
[32]	Song J, Wan S Q, Peng S S, et al. The carbon sequestration potential of China’s grasslands[J]. Ecosphere, 2018, 9 (10): 02452
[33]	方精云, 景海春, 张文浩, 等. 论草牧业的理论体系及其实践[J]. 科学通报, 2018, 63 (17): 1619-1631.
	Fang J Y, Jing H C, Zhang W H, et al. The concept of “Grass-based Livestock Husbandry” and its practice in Hulun Buir, Inner Mongolia[J]. Chinese Science Bulletin, 2018, 63 (17): 1619-1631 (in Chinese)
[34]	Yang Y, Tilman D, Furey G, et al. Soil carbon sequestration accelerated by restoration of grassland biodiversity[J]. Nature Communications, 2019, 10 (1): 718 doi: 10.1038/s41467-019-08636-w URL pmid: 30755614
[35]	张乾, 李金升, 赵天赐, 等. 生物炭对土壤的影响及在草地生态系统中应用的研究进展[J]. 草地学报, 2019, 27 (2): 279-284. doi: 10.11733/j.issn.1007-0435.2019.02.001
	Zhang Q, Li J S, Zhao T C, et al. Research progress on the effect of Biochar on soil and its application in grassland ecosystem[J]. Acta Agrestia Sinica, 2019, 27 (2): 279-284 (in Chinese)
[36]	Gong H, Li Y, Li S. Effects of interaction between Biochar and nutrients on soil organic carbon sequestration in soda saline-alkalized grassland: a review[J]. Global Ecology and Conservation, 2021, 26: e01449 doi: 10.1016/j.gecco.2020.e01449 URL
[37]	Deng L, Shangguan Z P, Wu G L, et al. Effects of grazing exclusion on carbon sequestration in China’s grassland[J]. Earth-Science Reviews, 2017, 173: 84-95 doi: 10.1016/j.earscirev.2017.08.008 URL
[38]	Smith P, Soussana J R, Angers D, et al. How to measure, report and verify soil carbon change to realise the potential of soil carbon sequestration for atmospheric greenhouse gas removal[J]. Global Change Biology, 2019, 26 (1): 14815
[39]	Tiemeyer B, Freibauer A, Borraz E A, et al. A new methodology for organic soils in national greenhouse gas inventories: data synthesis, derivation and application[J]. Ecological Indicators, 2020, 109 (C): 105838
[40]	王穗子, 刘帅, 樊江文, 等. 碳交易市场现状及草地碳汇潜力研究[J]. 草业学报, 2018, 27 (6): 177-187. doi: 10.11686/cyxb2017276
	Wang S Z, Liu S, Fan J W, et al. Research on the current situation of carbon trading markets and the potential of grassland carbon sinks[J]. Acta Prataculturae Sinica, 2018, 27 (6): 177-187 (in Chinese)

中国草地生态管理的土壤碳汇模拟研究——基于IPCC清单方法

Study on the simulation of soil carbon sink in grassland ecological management in China — based on IPCC inventory method

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