Title Climatic factors driving vegetation declines in the 2005 and 2010 Amazon droughts
Authors Zhao, Wenqian
Zhao, Xiang
Zhou, Tao
Wu, Donghai
Tang, Bijian
Wei, Hong
Affiliation Beijing Normal Univ, State Key Lab Earth Surface Processes & Resource, Beijing, Peoples R China.
Beijing Normal Univ, Fac Geog Sci, Coll Remote Sensing Sci & Engn, State Key Lab Remote Sensing Sci, Beijing, Peoples R China.
JCGCS, Beijing, Peoples R China.
Shaanxi Jinkong Compass Informat Serv CO LTD, Xian, Peoples R China.
Beijing Engn Res Ctr Global Land Remote Sensing, Beijing, Peoples R China.
Beijing Normal Univ, Minist Educ, Environm Change & Nat Disaster, Beijing, Peoples R China.
Peking Univ, Coll Urban & Environm Sci, Beijing, Peoples R China.
Beijing Normal Univ, State Key Lab Earth Surface Processes & Resource, Beijing, Peoples R China.
Zhao, X (reprint author), Beijing Normal Univ, Fac Geog Sci, Coll Remote Sensing Sci & Engn, State Key Lab Remote Sensing Sci, Beijing, Peoples R China.
Zhao, X (reprint author), JCGCS, Beijing, Peoples R China.
Zhao, X (reprint author), Beijing Engn Res Ctr Global Land Remote Sensing, Beijing, Peoples R China.
Keywords CANOPY STRUCTURE
TIME-SERIES
RAIN-FOREST
VARIABILITY
DYNAMICS
MODIS
WATER
NDVI
SOIL
SEASONALITY
Issue Date 2017
Publisher PLOS ONE
Citation PLOS ONE.2017,12(4).
Abstract Along with global climate change, the occurrence of extreme droughts in recent years has had a serious impact on the Amazon region. Current studies on the driving factors of the 2005 and 2010 Amazon droughts has focused on the influence of precipitation, whereas the impacts of temperature and radiation have received less attention. This study aims to explore the climate-driven factors of Amazonian vegetation decline during the extreme droughts using vegetation index, precipitation, temperature and radiation datasets. First, time-lag effects of Amazonian vegetation responses to precipitation, radiation and temperature were analyzed. Then, a multiple linear regression model was established to estimate the contributions of climatic factors to vegetation greenness, from which the dominant climate- driving factors were determined. Finally, the climate-driven factors of Amazonian vegetation greenness decline during the 2005 and 2010 extreme droughts were explored. The results showed that (i) in the Amazon vegetation greenness responded to precipitation, radiation and temperature, with apparent time lags for most averaging interval periods associated with vegetation index responses of 0-4, 0-9 and 0-6 months, respectively; (ii) on average, the three climatic factors without time lags explained 27.28 +/- 21.73% (mean +/- 1 SD) of vegetation index variation in the Amazon basin, and this value increased by 12.22% and reached 39.50 +/- 27.85% when time lags were considered; (iii) vegetation greenness in this region in non-drought years was primarily affected by precipitation and shortwave radiation, and these two factors altogether accounted for 93.47% of the total explanation; and (iv) in the common epicenter of the two droughts, pixels with a significant variation in precipitation, radiation and temperature accounted for 36.68%, 40.07% and 10.40%, respectively, of all pixels showing a significant decrease in vegetation index in 2005, and 15.69%, 2.01% and 45.25% in 2010, respectively. Overall, vegetation greenness declines during the 2005 and 2010 extreme droughts were adversely influenced by precipitation, radiation and temperature; this study provides evidence of the influence of multiple climatic factors on vegetation during the 2005 and 2010 Amazon droughts.
URI http://hdl.handle.net/20.500.11897/473934
ISSN 1932-6203
DOI 10.1371/journal.pone.0175379
Indexed SCI(E)
Appears in Collections: 城市与环境学院

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