中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Spatio-Temporal Evolution, Future Trend and Phenology Regularity of Net Primary Productivity of Forests in Northeast China

文献类型:期刊论文

作者Wang, Chunli1,2; Jiang, Qun'ou1,3; Deng, Xiangzheng3; Lv, Kexin1,3; Zhang, Zhonghui4
刊名REMOTE SENSING
出版日期2020-11-01
卷号12期号:21页码:22
关键词Net Primary Productivity (NPP) phenology regularity future trend Northeast China
DOI10.3390/rs12213670
通讯作者Jiang, Qun'ou(jiangqo@bjfu.edu.cn)
英文摘要Net Primary Productivity (NPP) is one of the significant indicators to measure environmental changes; thus, the relevant study of NPP in Northeast China, Asia, is essential to climate changes and ecological sustainable development. Based on the Global Production Efficiency (GLO-PEM) model, this study firstly estimated the NPP in Northeast China, from 2001 to 2019, and then analyzed its spatio-temporal evolution, future changing trend and phenology regularity. Over the years, the NPP of different forests type in Northeast China showed a gradual increasing trend. Compared with other different time stages, the high-value NPP (700-1300 gC center dot m(-2)center dot a(-1)) in Changbai Mountain, from 2017 to 2019, is more widely distributed. For instance, the NPP has an increasing rate of 6.92% compared to the stage of 2011-2015. Additionally, there was a significant advance at the start of the vegetation growth season (SOS), and a lag at the end of the vegetation growth season (EOS), from 2001 to 2019. Thus, the whole growth period of forests in Northeast China became prolonged with the change of phenology. Moreover, analysis on the sustainability of NPP in the future indicates that the reverse direction feature of NPP change will be slightly stronger than the co-directional feature, meaning that about 30.68% of the study area will switch from improvement to degradation. To conclude, these above studies could provide an important reference for the sustainable development of forests in Northeast China.
WOS关键词GROSS PRIMARY PRODUCTION ; CLIMATE-CHANGE ; SPRING PHENOLOGY ; USE EFFICIENCY ; HUMAN APPROPRIATION ; SOLAR-RADIATION ; BIOMASS ; MODEL ; SATELLITE ; MODIS
资助项目Key Project of National Key Research and Development Plan[2017YFC050400103] ; National Science and Technology Projects[2017ZX07101004] ; National Science and Technology Projects[2017ZX07108002] ; Major Research Plan of National Natural Science Foundation of China[41901234] ; Major Research Plan of National Natural Science Foundation of China[51909052] ; Fundamental Research Funds for the Central Universities[2015ZCQSB03] ; Hebei Natural Science Foundation[D2015207002]
WOS研究方向Remote Sensing
语种英语
出版者MDPI
WOS记录号WOS:000589383400001
资助机构Key Project of National Key Research and Development Plan ; National Science and Technology Projects ; Major Research Plan of National Natural Science Foundation of China ; Fundamental Research Funds for the Central Universities ; Hebei Natural Science Foundation
源URL[http://ir.igsnrr.ac.cn/handle/311030/156697]  
专题中国科学院地理科学与资源研究所
通讯作者Jiang, Qun'ou
作者单位1.Beijing Forestry Univ, Sch Soil & Water Conservat, Key Lab Soil & Water Conservat & Desertificat Pre, Beijing 100083, Peoples R China
2.Nanjing Univ, Int Inst Earth Syst Sci, Jiangsu Prov Key Lab Geog Informat Sci & Technol, Nanjing 210023, Peoples R China
3.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China
4.Jilin Prov Acad Forestry Sci, Changchun 130021, Peoples R China
推荐引用方式
GB/T 7714
Wang, Chunli,Jiang, Qun'ou,Deng, Xiangzheng,et al. Spatio-Temporal Evolution, Future Trend and Phenology Regularity of Net Primary Productivity of Forests in Northeast China[J]. REMOTE SENSING,2020,12(21):22.
APA Wang, Chunli,Jiang, Qun'ou,Deng, Xiangzheng,Lv, Kexin,&Zhang, Zhonghui.(2020).Spatio-Temporal Evolution, Future Trend and Phenology Regularity of Net Primary Productivity of Forests in Northeast China.REMOTE SENSING,12(21),22.
MLA Wang, Chunli,et al."Spatio-Temporal Evolution, Future Trend and Phenology Regularity of Net Primary Productivity of Forests in Northeast China".REMOTE SENSING 12.21(2020):22.

入库方式: OAI收割

来源:地理科学与资源研究所

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