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      Climatic factors driving vegetation declines in the 2005 and 2010 Amazon droughts

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          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.

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          Most cited references43

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          Climate change, deforestation, and the fate of the Amazon.

          The forest biome of Amazonia is one of Earth's greatest biological treasures and a major component of the Earth system. This century, it faces the dual threats of deforestation and stress from climate change. Here, we summarize some of the latest findings and thinking on these threats, explore the consequences for the forest ecosystem and its human residents, and outline options for the future of Amazonia. We also discuss the implications of new proposals to finance preservation of Amazonian forests.
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            Persistent effects of a severe drought on Amazonian forest canopy.

            Recent Amazonian droughts have drawn attention to the vulnerability of tropical forests to climate perturbations. Satellite and in situ observations have shown an increase in fire occurrence during drought years and tree mortality following severe droughts, but to date there has been no assessment of long-term impacts of these droughts across landscapes in Amazonia. Here, we use satellite microwave observations of rainfall and canopy backscatter to show that more than 70 million hectares of forest in western Amazonia experienced a strong water deficit during the dry season of 2005 and a closely corresponding decline in canopy structure and moisture. Remarkably, and despite the gradual recovery in total rainfall in subsequent years, the decrease in canopy backscatter persisted until the next major drought, in 2010. The decline in backscatter is attributed to changes in structure and water content associated with the forest upper canopy. The persistence of low backscatter supports the slow recovery (>4 y) of forest canopy structure after the severe drought in 2005. The result suggests that the occurrence of droughts in Amazonia at 5-10 y frequency may lead to persistent alteration of the forest canopy.
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              Time-lag effects of global vegetation responses to climate change.

              Climate conditions significantly affect vegetation growth in terrestrial ecosystems. Due to the spatial heterogeneity of ecosystems, the vegetation responses to climate vary considerably with the diverse spatial patterns and the time-lag effects, which are the most important mechanism of climate-vegetation interactive effects. Extensive studies focused on large-scale vegetation-climate interactions use the simultaneous meteorological and vegetation indicators to develop models; however, the time-lag effects are less considered, which tends to increase uncertainty. In this study, we aim to quantitatively determine the time-lag effects of global vegetation responses to different climatic factors using the GIMMS3g NDVI time series and the CRU temperature, precipitation, and solar radiation datasets. First, this study analyzed the time-lag effects of global vegetation responses to different climatic factors. Then, a multiple linear regression model and partial correlation model were established to statistically analyze the roles of different climatic factors on vegetation responses, from which the primary climate-driving factors for different vegetation types were determined. The results showed that (i) both the time-lag effects of the vegetation responses and the major climate-driving factors that significantly affect vegetation growth varied significantly at the global scale, which was related to the diverse vegetation and climate characteristics; (ii) regarding the time-lag effects, the climatic factors explained 64% variation of the global vegetation growth, which was 11% relatively higher than the model ignoring the time-lag effects; (iii) for the area with a significant change trend (for the period 1982-2008) in the global GIMMS3g NDVI (P < 0.05), the primary driving factor was temperature; and (iv) at the regional scale, the variation in vegetation growth was also related to human activities and natural disturbances. Considering the time-lag effects is quite important for better predicting and evaluating the vegetation dynamics under the background of global climate change. © 2015 John Wiley & Sons Ltd.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                20 April 2017
                2017
                : 12
                : 4
                : e0175379
                Affiliations
                [1 ]State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing, China
                [2 ]The State Key Laboratory of Remote Sensing Science, College of Remote Sensing Science and Engineering, Faculty of Geographical Science, Beijing Normal University, Beijing, China
                [3 ]Joint Center for Global Change Studies (JCGCS), Beijing, China
                [4 ]Shaanxi Jinkong Compass Information Service CO. LTD, Xian, China
                [5 ]Beijing Engineering Research Center for Global Land Remote Sensing, Beijing, China
                [6 ]Environmental Change and Natural Disaster, Ministry of Education, Beijing Normal University, Beijing, China
                [7 ]College of Urban and Environmental Sciences, Peking University, Beijing, China
                The Ohio State University, UNITED STATES
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                • Conceptualization: XZ WZ TZ.

                • Data curation: BT.

                • Formal analysis: WZ DW.

                • Funding acquisition: XZ.

                • Investigation: WZ DW.

                • Methodology: XZ WZ TZ.

                • Project administration: XZ.

                • Resources: BT HW.

                • Software: WZ DW.

                • Supervision: XZ.

                • Validation: WZ DW.

                • Visualization: XZ.

                • Writing – original draft: WZ XZ.

                • Writing – review & editing: WZ XZ.

                Article
                PONE-D-16-30013
                10.1371/journal.pone.0175379
                5398491
                28426691
                0efec696-f69d-4946-9b5a-3ab017474934
                © 2017 Zhao et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 27 July 2016
                : 26 March 2017
                Page count
                Figures: 8, Tables: 3, Pages: 19
                Funding
                This study was supported by the National Key Research and Development Program of China (NO. 2016YFA0600103) and Project Supported by State Key Laboratory of Earth Surface Processes and Resource Ecology.
                Categories
                Research Article
                Physical Sciences
                Physics
                Electromagnetic Radiation
                Solar Radiation
                Earth Sciences
                Atmospheric Science
                Meteorology
                Rain
                Ecology and Environmental Sciences
                Drought
                Biology and Life Sciences
                Ecology
                Ecosystems
                Forests
                Rainforests
                Ecology and Environmental Sciences
                Ecology
                Ecosystems
                Forests
                Rainforests
                Ecology and Environmental Sciences
                Terrestrial Environments
                Forests
                Rainforests
                Biology and Life Sciences
                Ecology
                Plant Ecology
                Plant Communities
                Grasslands
                Ecology and Environmental Sciences
                Ecology
                Plant Ecology
                Plant Communities
                Grasslands
                Biology and Life Sciences
                Plant Science
                Plant Ecology
                Plant Communities
                Grasslands
                Ecology and Environmental Sciences
                Terrestrial Environments
                Grasslands
                Earth Sciences
                Atmospheric Science
                Meteorology
                Biology and Life Sciences
                Ecology
                Ecosystems
                Forests
                Ecology and Environmental Sciences
                Ecology
                Ecosystems
                Forests
                Ecology and Environmental Sciences
                Terrestrial Environments
                Forests
                Earth Sciences
                Seasons
                Custom metadata
                The Vegetation index data are downloaded from https://lpdaac.usgs.gov/dataset_discovery/modis/modis_products_table/mod13c2. The CRU climate data are downloaded from http://www.cru.uea.ac.uk/.

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