过去50年气候变化下中国潜在植被NPP的脆弱性评价

doi:10.11821/dlxb201605008

Abstract

Abstract:

By using the IBIS, a dynamic vegetation model, this study firstly simulated the NPP dynamics of China's potential vegetation in the past 50 years (1961-2010). Then according to the Fifth Assessment Report by IPCC, this study used the average climate conditions during 1986-2005 as the "standard climate", and took the NPP of the potential vegetation in this climate condition as the evaluation basis. Compared with the evaluation basis, the NPP fluctuation of each year was calculated to judge whether the potential vegetation adapts the climate change or not. Meanwhile, the degree of the inadaptability was evaluated. Finally, the NPP vulnerability of potential vegetation was evaluated by synthesizing the times and degrees of inadaptability to the climate change during the past 50 years. Results showed that: the NPP of the desert ecosystems south of the Tianshan Mountains, and the NPP of grassland ecosystems in northern China and western Tibetan Plateau were more likely to be impacted by the climate change in the study period. The NPP vulnerability of these ecosystems to climate change in the past 50 years was relatively high. The NPP of most of the forest ecosystems was not likely to be influenced by climate change. The NPP vulnerability to climate change of the evergreen broadleaved forests and coniferous forests was lower. Additionally, the NPP of the desert ecosystems north of Tianshan Mountains, and the NPP of the grassland ecosystems in the central and eastern parts of the Tibetan Plateau had lower vulnerability to climate change.

Key words: climate change, potential vegetation, NPP, vulnerability, IBIS, China

Quanzhi YUAN, Shaohong WU, Erfu DAI, Dongsheng ZHAO, Ping REN, Xueru ZHANG. NPP vulnerability of China's potential vegetation to climate change in the past 50 years[J].Acta Geographica Sinica, 2016, 71(5): 797-806.

Figures/Tables 4

Fig. 1

Tab. 1

Fig. 2

Fig. 3

References 34

[1]	IPCC. Climate Change 2014: Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge, United Kingdom and New York, NY, USA: Cambridge University Press, 2014.
[2]	Fang Chuanglin, Wang Yan.A comprehensive assessment of urban vulnerability and its spatial differentiation in China. Journal of Geographical Sciences, 2015, 70(2): 234-247. doi: 10.11821/dlxb201502005
	[方创琳, 王岩. 中国城市脆弱性的综合测度与空间分异特征. 地理学报, 2015, 70(2): 234-247.] doi: 10.11821/dlxb201502005
[3]	Cai Yunlong.Sensitivity and adaptation of chinese agriculture under global climate change. Acta Geographica Sinica, 1996, 51(3): 202-212.
	[蔡运龙. 全球气候变化下中国农业的脆弱性与适应对策. 地理学报, 1996, 51(3): 202-212.]
[4]	Editorial Committee of National Assessment Report of Climate Change. Third National Assessment Report of Climate Change. Beijing: Science Press, 2014.
	[气候变化国家评估报告编写委员会.第三次气候变化国家评估报告. 北京: 科学出版社, 2014.]
[5]	Wu Shaohong, Huang Jikun, Liu Yanhua, et al.Pros and Cons of climate change in China. China Population, Resources and Environment, 2014, 24(1): 7-13.
	[吴绍洪, 黄季焜, 刘燕华, 等. 气候变化对中国的影响利弊. 中国人口.资源与环境, 2014, 24(1): 7-13.]
[6]	Liu Yanhua, Li Xiubin.Fragile Ecological Environment and Sustainable Development. Beijing: The Commercial Press, 2007.
	[刘燕华, 李秀彬. 脆弱生态环境与可持续发展. 北京: 商务印书馆, 2007.]
[7]	Tian Yaping, Chang Hao.Bibliometric analysis of research progress on ecological vulnerability in China. Journal of Geographical Sciences, 2012, 67(11): 1515-1525. doi: 10.11821/xb201211008
	[田亚平, 常昊. 中国生态脆弱性研究进展的文献计量分析. 地理学报, 2012, 67(11): 1515-1525.] doi: 10.11821/xb201211008
[8]	Li Kerang, Chen Yufeng.Analysis of vulnerability of forest in China responded to global climate change. Acta Geographica Sinica, 1996, 51(Suppl.1): 40-49. doi: 10.11821/xb1996s1004
	[李克让, 陈育峰. 全球气候变化影响下中国森林的脆弱性分析. 地理学报, 1996, 51(Suppl.1): 40-49.] doi: 10.11821/xb1996s1004
[9]	Tuxen R.Die heutige potentielle natuerliche Vegetation als Gegenstand der vegetationskartierung. Angewandte Pflanzensoziologie. 1956, 13: 5-42.
[10]	Wu Shaohong, Dai Erfu, Huang Mei, et al.Study on the vulnerability of ecological system in China under the future climate change scenario (B2) in 21st century. Chinese Science Bulletin, 2007, 52(7): 811-817.
	[吴绍洪, 戴尔阜, 黄玫, 等. 21世纪未来气候变化情景(B2)下中国生态系统的脆弱性研究. 科学通报, 2007, 52(7): 811-817.]
[11]	Yu Li, Cao Mingkui, Tao Bo, et al.Quantitative assessment of the vul nerability of terrestrial ecosystems of China to climate change based on potential vegetation. Journal of Plant Ecology, 2008, 32(3): 521-530. doi: 10.3773/j.issn.1005-264x.2008.03.001
	[於琍, 曹明奎, 陶波, 等. 基于潜在植被的中国陆地生态系统对气候变化的脆弱性定量评价. 植物生态学报, 2008, 32(3): 521-530.] doi: 10.3773/j.issn.1005-264x.2008.03.001
[12]	Zhao Dongsheng, Wu Shaohong.Vulnerability of natural ecosystem in China under regional climate scenarios: An analysis based on eco-geographical regions. Acta Geographica Sinica, 2013, 68(5): 602-610. doi: 10.1007/s11442-014-1085-3
	[赵东升, 吴绍洪. 气候变化情景下中国自然生态系统脆弱性研究. 地理学报, 2013, 68(5): 602-610.] doi: 10.1007/s11442-014-1085-3
[13]	Lieth H, Whittaker R H.Primary Productivity of the Biosphere. New York: Springer-Verlag, 1975.
[14]	Ruimy A, Saugier B, Dedieu G.Methodology for the estimation of terrestrial net primary production from remotely sensed data. Journal of Geographical Research, 1994, 99(D3): 5263-5283.
[15]	Li Kerang, Huang Mei, Tao Bo, et al.Process Modeling of China's Terrestrial Ecosystem and Its Response to Global Change. Beijing: China Meteorological Press, 2009.
	[李克让, 黄玫, 陶波, 等. 中国陆地生态系统过程及对全球变化响应与适应的模拟研究. 北京: 气象出版社, 2009.]
[16]	Holdridge L R.Determination of world plant formations from simple climatic data. Nanotechnology, 1947, 105(2727):299-303. pmid: 32844705375867159055910148292223222217800882815900697440743009980
[17]	Prentice I C, Cramer W, Harrison S P, et al.A global biome model based on plant physiology and dominance, soil properties and climate. Journal of Biogeography, 1992, 19(19): 117-134. doi: 10.2307/2845499
[18]	Neilson R P.A Model for predicting continental-scale vegetation distribution and water balance. Ecological Applications, 1995, 5(2): 362-385.
[19]	Parton W J, Scurlock J M O, Ojima D S, et al. observation and modeling of biomass and soil organic matter dynamics for the grassland biome worldwide. Global Biogeochemical Cycles, 1993, 7(4): 785-809. doi: 10.1029/93GB02042
[20]	Woodward F I, Smith T M, Emanuel W R.A global land primary productivity and phytogeography model. Global Biogeochemical Cycles, 1995, 9(4): 471-490. doi: 10.1029/95GB02432
[21]	Foley J A, Prentice I C, Ramankutty N, et al.An integrated biosphere model of land surface processes, terrestrial carbon balance, and vegetation dynamics. Global Biogeochemical Cycles, 1996, 10(4): 603-628. doi: 10.1029/96GB02692
[22]	Kucharik C J, Foley J A, Delire C, et al.Testing the performance of a Dynamic Global Ecosystem Model: Water balance, carbon balance, and vegetation structure. Global Biogeochemical Cycles, 2000, 14(3): 795-825. doi: 10.1029/1999GB001138
[23]	Sitch S, Smith B, Prentice I C, et al.Evaluation of ecosystem dynamics, plant geography, and terrestrial carbon cycling in the LPJ dynamic global vegetation model. Global Change Biology, 2003, 9(2): 161-185. doi: 10.1046/j.1365-2486.2003.00569.x pmid: 1703012
[24]	Yuan Q Z, Zhao D S, Wu S H, et al.Validation of the Integrated Biosphere Simulator in simulating the potential natural vegetation map of China. Ecological Research, 2011, 26(5): 917-929 doi: 10.1007/s11284-011-0845-0
[25]	Yuan Q Z, Wu S H, Zhao D S, et al.Modeling net primary productivity of the terrestrial ecosystem in China from 1961 to 2005. Journal of Geographical Sciences, 2014, 24(1): 3-17 doi: 10.1007/s11442-014-1069-3
[26]	International Geosphere-Biosphere Program-Data and Information System(IGBP-DIS),Global Soil Data Task: Spatial Data base of Soil Properties,Toulouse, France, 1999.
[27]	Hutchinson M F.The application of thin plate splines to continent wide data assimilation, Data Assimilation Systems, BMRC Research Report No. 27. Melbourne: Bureau of Meteorology, 1991.
[28]	Metzger M J. Schroter D. Leemans R, et al.A spatially explicit and quantitative vulnerability assessment of ecosystem service change in Europe. Regional Environmental Change, 2008, 8(3): 91-107. doi: 10.1007/s10113-008-0044-x
[29]	Minnen J G, van Onigkeit J, Alcamo J. Critical climate change as an approach to assess climate change impacts in Europe: Development and application. Environmental Science & Policy, 2002, 5(4): 335-347. doi: 10.1016/S1462-9011(02)00044-8
[30]	Shi Xiaoli.Risk assessment of Chinese Ecosystem under climate change scenarios, [D]. Beijing: Institute of Geographical Sciences and Natural Resource Research Chinese Academy of Sciences, 2009.
	[石晓丽. 气候变化情景下中国生态系统风险评价[D]. 北京: 中国科学院地理科学与资源研究所, 2009.]
[31]	Wu Shaohong, Yin Yunhe, Zhao Huixia, et al.Recognition of ecosystem response to climate change impact. Advances in Climate Change Research, 2005, 1(3): 115-118. doi: 10.3969/j.issn.1673-1719.2005.03.004
	[吴绍洪, 尹云鹤, 赵慧霞等. 生态系统对气候变化适应的辨识. 气候变化研究进展, 2005, 1(3): 115-118.] doi: 10.3969/j.issn.1673-1719.2005.03.004
[32]	Zheng Du, et al.Chinese Eco-geographical Regionalization Research. Beijing: The Commercial Press, 2008.
	[郑度, 等. 中国生态地理区域系统研究. 北京: 商务印书馆, 2008.]
[33]	Ye Duzheng.Prestudy of China’s Global Change. Beijing: China Meteorological Press, 1992.
	[叶笃正,中国的全球变化预研究. 北京: 气象出版社, 1992.]
[34]	Zhao Yuelong.Types Distribution and Comprehensive Improvement of Fragile Ecological Environment in China. Beijing: China Environmental Science Press, 1999.
	[赵跃龙. 中国脆弱生态环境类型分布及其综合整治. 北京: 中国环境科学出版社, 1999.]

植被功能型	气候要素相对敏感度
植被功能型	气温 (℃)	温差 (℃)	降水量 (mm)	相对湿度 (%)	云量 (%)	风速 (m/s)	雨日 (d)
热带常绿阔叶树	5.229	-0.032	0.375	0.682	-0.278	0.011	-0.219
热带雨绿阔叶树	6.818	-0.037	0.361	0.692	-0.277	0.013	-0.216
亚热带常绿阔叶树	-0.684	-0.040	0.174	0.442	-0.141	-0.002	-0.045
温带常绿针叶树	-0.026	-0.081	0.553	1.082	0.184	-0.053	-0.092
温带落叶阔叶树	0.001	-0.086	0.656	0.733	0.186	-0.033	-0.064
北方常绿针叶树	-1.876	-0.062	0.292	0.886	-0.082	-0.040	-0.051
北方落叶阔叶树	-4.010	-0.093	0.654	0.759	0.136	-0.039	-0.069
北方落叶针叶树	-4.311	-0.073	0.356	0.572	0.012	-0.030	-0.040
常绿灌木	-0.480	-0.097	0.371	0.324	-0.764	-0.163	0.120
落叶灌木	-0.485	-0.069	0.212	0.261	-0.686	-0.031	0.176
暖性(C4)草	3.601	-0.020	0.559	0.611	-1.916	-0.049	0.390
冷性(C3)草	-1.590	-0.116	0.348	0.510	-0.022	-0.042	-0.035

NPP vulnerability of China's potential vegetation to climate change in the past 50 years

RichHTML

PDF (PC)

Like

Knowledge

Cited

Abstract

Cite this article

share this article

Figures/Tables 4

References 34

Related Articles 15

Metrics

Comments

[1]	SUN Pingjun, WANG Kewen. Identification and stage division of urban shrinkage in the three provinces of Northeast China [J]. Acta Geographica Sinica, 2021, 76(6): 1366-1379.
[2]	WEI Shimei, PAN Jinghu. Network structure resilience of cities at the prefecture level and above in China [J]. Acta Geographica Sinica, 2021, 76(6): 1394-1407.
[3]	YANG Ren, PAN Yuxin. Spatial patterns, formation mechanism and coping strategies of rural vulnerability in China at the county level [J]. Acta Geographica Sinica, 2021, 76(6): 1438-1454.
[4]	YIN Jiangbin, LI Shangqian, JIANG Lei, CHENG Zhe, HUANG Xiaoyan, LU Gaigai. The spatio-temporal variations and driving factors of non-farm employment growth in contiguous destitute areas of China [J]. Acta Geographica Sinica, 2021, 76(6): 1471-1488.
[5]	HU Pan, CHEN Bo, SHI Peijun. Spatiotemporal patterns and influencing factors of rainstorm-induced flood disasters in China [J]. Acta Geographica Sinica, 2021, 76(5): 1148-1162.
[6]	WANG Keyi, LIU Xiaohong, ZENG Xiaomin, XU Guobao, ZHANG Lingnan, LI Chunyue. Stable nitrogen isotope in tree rings: Progresses, problems and prospects [J]. Acta Geographica Sinica, 2021, 76(5): 1193-1205.
[7]	LIU Zhenhai, WANG Shaoqiang, CHEN Bin. Spatial and temporal variations of frozen ground and its vegetation response in the eastern segment of China-Mongolia-Russia economic corridor from 2000 to 2015 [J]. Acta Geographica Sinica, 2021, 76(5): 1231-1244.
[8]	HUANG Xiaodong, MA Haitao, MIAO Changhong. Connectivity characteristics for city networks in China based on innovative enterprises [J]. Acta Geographica Sinica, 2021, 76(4): 835-852.
[9]	WANG Lucang, LIU Haiyang, LIU Qing. China's city network based on Tencent's migration big data [J]. Acta Geographica Sinica, 2021, 76(4): 853-869.
[10]	XIA Xingsheng, PAN Yaozhong, ZHU Xiufang, ZHANG Jinshui. Monthly calibration and optimization of Ångström-Prescott equation coefficients for agricultural comprehensive area in China [J]. Acta Geographica Sinica, 2021, 76(4): 888-902.
[11]	MA Zuopeng, LI Chenggu, ZHANG Pingyu. Characteristics, mechanism and response of urban shrinkage in the three provinces of Northeast China [J]. Acta Geographica Sinica, 2021, 76(4): 767-780.
[12]	FAN Zemeng. Spatial identification and scenario simulation of ecotone distribution in China [J]. Acta Geographica Sinica, 2021, 76(3): 626-644.
[13]	XU Yu, LI Xiubin, XIN Liangjie. Differentiation of scale-farmland transfer rent and its influencing factors in China [J]. Acta Geographica Sinica, 2021, 76(3): 753-763.
[14]	GU Hengyu, SHEN Tiyan. Spatial evolution characteristics and driving forces of Chinese highly educated talents [J]. Acta Geographica Sinica, 2021, 76(2): 326-340.
[15]	ZHU Shengjun, JIN Wenwan. Local export variety, regional institutions and firm related diversification [J]. Acta Geographica Sinica, 2021, 76(2): 398-414.