Contrasting Changes in Vegetation Growth due to Different Climate Forcings over the Last Three Decades in the Selenga-Baikal Basin
Wang, Guan1,2; Wang, Ping1; Wang, Tian-Ye1,2; Zhang, Yi-Chi1; Yu, Jing-Jie1,2; Ma, Ning3; Frolova, Natalia L.4; Liu, Chang-Ming1
刊名REMOTE SENSING
2019-02-02
卷号11期号:4页码:17
关键词climate change vegetation growth NDVI Baikal Lake vegetation response
ISSN号2072-4292
DOI10.3390/rs11040426
通讯作者Wang, Ping(wangping@igsnrr.ac.cn)
英文摘要The Selenga-Baikal Basin, a transboundary river basin between Mongolia and Russia, warmed at nearly twice the global rate and experienced enhanced human activities in recent decades. To understand the vegetation response to climate change, the dynamic spatial-temporal characteristics of the vegetation and the relationships between the vegetation dynamics and climate variability in the Selenga-Baikal Basin were investigated using the Normalized Difference Vegetation Index (NDVI) and gridded temperature and precipitation data for the period of 1982 to 2015. Our results indicated that precipitation played a key role in vegetation growth across regions that presented multiyear mean annual precipitation lower than 350 mm, although its importance became less apparent over regions with precipitation exceeding 350 mm. Because of the overall temperature-limited conditions, temperature had a more substantial impact on vegetation growth than precipitation. Generally, an increasing trend was observed in the growth of forest vegetation, which is heavily dependent on temperature, whereas a decreasing trend was detected for grassland, for which the predominant growth-limiting factor is precipitation. Additionally, human activities, such as urbanization, mining, increased wildfires, illegal logging, and livestock overgrazing are important factors driving vegetation change.
资助项目Science and Technology Basic Resources Investigation Program of China[2017FY101302] ; Science and Technology Basic Resources Investigation Program of China[2017FY101301] ; Strategic Priority Research Program of the Chinese Academy of Sciences[XDA2003020101] ; Key Project of the Chinese Academy of Sciences[ZDRW-ZS-2017-4] ; National Natural Science Foundation of China[41671023] ; National Natural Science Foundation of China[41571029] ; National Natural Science Foundation of China[41801047] ; National Natural Science Foundation of China[41271050] ; NSFC-RFBR Program 2018-2019[41811530084] ; NSFC-RFBR Program 2018-2019[18-55-53025 GammaPhiEH_a]
WOS关键词NET PRIMARY PRODUCTION ; KHARAA RIVER-BASIN ; DESERT STEPPE ; LAKE BAIKAL ; TRENDS ; DYNAMICS ; NDVI ; RUNOFF ; VARIABILITY ; INDEX
WOS研究方向Remote Sensing
语种英语
出版者MDPI
WOS记录号WOS:000460766100056
资助机构Science and Technology Basic Resources Investigation Program of China ; Strategic Priority Research Program of the Chinese Academy of Sciences ; Key Project of the Chinese Academy of Sciences ; National Natural Science Foundation of China ; NSFC-RFBR Program 2018-2019
内容类型期刊论文
源URL[http://ir.igsnrr.ac.cn/handle/311030/49251]  
专题中国科学院地理科学与资源研究所
通讯作者Wang, Ping
作者单位1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Water Cycle & Related Land Surface Proc, Beijing 100101, Peoples R China
2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
3.Chinese Acad Sci, Inst Tibetan Plateau Res, Key Lab Tibetan Environm Changes & Land Surface P, Beijing 100101, Peoples R China
4.Lomonosov Moscow State Univ, Dept Land Hydrol, GSP 1, Moscow 119991, Russia
推荐引用方式
GB/T 7714
Wang, Guan,Wang, Ping,Wang, Tian-Ye,et al. Contrasting Changes in Vegetation Growth due to Different Climate Forcings over the Last Three Decades in the Selenga-Baikal Basin[J]. REMOTE SENSING,2019,11(4):17.
APA Wang, Guan.,Wang, Ping.,Wang, Tian-Ye.,Zhang, Yi-Chi.,Yu, Jing-Jie.,...&Liu, Chang-Ming.(2019).Contrasting Changes in Vegetation Growth due to Different Climate Forcings over the Last Three Decades in the Selenga-Baikal Basin.REMOTE SENSING,11(4),17.
MLA Wang, Guan,et al."Contrasting Changes in Vegetation Growth due to Different Climate Forcings over the Last Three Decades in the Selenga-Baikal Basin".REMOTE SENSING 11.4(2019):17.
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