The total suitability of water yield and carbon sequestration under multi-scenario simulations in the Weihe watershed, China
Zeng, Li1,2; Li, Jing1; Qin, Keyu3,4; Liu, Jingya3,4; Zhou, Zixiang5; Zhang, Yumeng1
刊名ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
2020-04-20
页码15
关键词Ecosystem services Bayesian belief network Scenario Land use Suitability priority area
ISSN号0944-1344
DOI10.1007/s11356-020-08205-5
通讯作者Li, Jing(lijing@snnu.edu.cn)
英文摘要Global climate change and national policies play an important role in regional ecosystem services, both of which should be fully considered when exploring their effective use and management. Bayesian belief network (BBN) is often used in complicated system modelling. Using a BBN to construct a network framework of ecosystem services under climate and policy scenarios for exploring the total suitability distribution of ecosystem services is of great significance. In this study, we develop BBN for the total suitability of water yield and carbon sequestration based on hydro-biogeochemical process. And then we predict the probabilities of the total suitability in 2050 through the BBN under multi-scenario simulations accounting for climate change, birth control and carbon tax policies. Finally, total suitability priority regions are mapped, which are synergy development, water yield suitability, carbon sequestration suitability and non-suitability, respectively. Our results indicate forest, cropland, urban area, and grassland have the largest areas under the representative concentration pathway (RCP) 2.6, RCP 4.5, RCP 6.0 and RCP 8.5, respectively. The abolition of the one-child policy has led to a significant expansion of urban areas, and the implementation of the carbon tax policy has greatly increased forest areas. Additionally, temperature, Normalized Vegetation Index (NDVI), precipitation and land use are the key driving factors that influence suitability. The suitable priority regions of different alternatives help policy makers consider ecological protection priorities while addressing management options.
资助项目National Natural Science Foundation of China[41771198] ; National Natural Science Foundation of China[41771576] ; NSFCNRF Scientific Cooperation Program[41811540400] ; Natural Science Basic Research Plan in Shaanxi Province of China[2018JM4010] ; Fundamental Research Funds for the Central Universities, Shaanxi Normal University[GK201901009]
WOS关键词BAYESIAN BELIEF NETWORK ; ECOSYSTEM SERVICES ; TRADE-OFFS ; SPATIOTEMPORAL FEATURES ; LOESS PLATEAU ; LAND ; DYNAMICS ; CYCLES ; FLUXES ; FLOWS
WOS研究方向Environmental Sciences & Ecology
语种英语
出版者SPRINGER HEIDELBERG
WOS记录号WOS:000527523900003
资助机构National Natural Science Foundation of China ; NSFCNRF Scientific Cooperation Program ; Natural Science Basic Research Plan in Shaanxi Province of China ; Fundamental Research Funds for the Central Universities, Shaanxi Normal University
内容类型期刊论文
源URL[http://ir.igsnrr.ac.cn/handle/311030/159876]  
专题中国科学院地理科学与资源研究所
通讯作者Li, Jing
作者单位1.Shaanxi Normal Univ, Sch Geog & Tourism, Xian 710119, Peoples R China
2.Sun Yat Sen Univ, Guangdong Prov Key Lab Urbanizat & Geosimulat, Sch Geog & Planning, Guangzhou 510275, Peoples R China
3.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China
4.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
5.Xian Univ Sci & Technol, Coll Geomat, Xian 710119, Peoples R China
推荐引用方式
GB/T 7714
Zeng, Li,Li, Jing,Qin, Keyu,et al. The total suitability of water yield and carbon sequestration under multi-scenario simulations in the Weihe watershed, China[J]. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH,2020:15.
APA Zeng, Li,Li, Jing,Qin, Keyu,Liu, Jingya,Zhou, Zixiang,&Zhang, Yumeng.(2020).The total suitability of water yield and carbon sequestration under multi-scenario simulations in the Weihe watershed, China.ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH,15.
MLA Zeng, Li,et al."The total suitability of water yield and carbon sequestration under multi-scenario simulations in the Weihe watershed, China".ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH (2020):15.
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