Cited by 189Remote Sensing and LiDAR ApplicationsPlant Water Relations and Carbon DynamicsForest ecology and management

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Post-drought decline of the Amazon carbon sink.

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Yang, Yan, Saatchi, Sassan S., Xu, Liang, Yu, Yifan, Choi, Sungho, Phillips, Nathan, Kennedy, Robert, Keller, Michael, Knyazikhin, Yuri, Myneni, Ranga B.·2018·Nature Communications

DOI 10.1038/s41467-018-05668-6PMC PMC6085357

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Abstract

Abstract Amazon forests have experienced frequent and severe droughts in the past two decades. However, little is known about the large-scale legacy of droughts on carbon stocks and dynamics of forests. Using systematic sampling of forest structure measured by LiDAR waveforms from 2003 to 2008, here we show a significant loss of carbon over the entire Amazon basin at a rate of 0.3 ± 0.2 (95% CI) PgC yr−1 after the 2005 mega-drought, which continued persistently over the next 3 years (2005–2008). The changes in forest structure, captured by average LiDAR forest height and converted to above ground biomass carbon density, show an average loss of 2.35 ± 1.80 MgC ha−1 a year after (2006) in the epicenter of the drought. With more frequent droughts expected in future, forests of Amazon may lose their role as a robust sink of carbon, leading to a significant positive climate feedback and exacerbating warming trends.

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Fig. 1 Spatial patterns of rainfall and corresponding canopy structure changes in each climatic region. a Drought classification map derived from rainfall data82. b Interannual changes of top canopy structure (RH90) relative to RH90 in 2004 for each climatic region defined in panel a. The abbreviations ED, SD, MD, LD, and ND are regions of extreme drought, severe drought, moderate drought, light drought, and no drought. The purple line in panel a delineates the boundary of Amazon basin area. Non-tropical forests in panel a were colored in gray. The error bars in panel b stand for 95% confidence intervals. Estimations in panel b were derived from the spatial modeling with filled data gaps (SMF) method (see Methods)CC BY · PubMed Central

Fig. 2 GLAS-derived biomass changes in Amazon. a Interannual above ground biomass (AGB) changes of regional means in five climatic regions (see Fig. 1a); b Interannual total carbon changes in North; c Interannual total carbon changes in South; d Interannual total carbon changes over the Amazon basin. The error bars (shaded area) stand for 95% confidence intervals. We combine regions LD and ND to be North, and regions ED, SD, and MD as South. The abbreviations ED, SD, MD, LD, and ND are regions of extreme drought, severe drought, moderate drought, light drought and no drought. All estimations in this figure were derived from the spatial modeling with filled data gaps (SMF) method (see Methods)CC BY · PubMed Central

Fig. 3 Net carbon change and emissions from fire and deforestation. a Classification map showing pixels with intact Amazon forests belonging to South and North, as well as fire and deforestation activities in tropical forests. b Annual contributions of fire and deforestation emissions compared to the net forest carbon change in the North region. c Annual contributions of fire and deforestation emissions compared to the net carbon change in the South region. d Cumulative contributions of net forest carbon change, fire and deforestation emissions in the South relative to the 2004 level. The colormap in panel a was generated using rainfall82, MODIS fire50 and Landsat51 products. Pixels were identified as fire or deforested when at least 1% of these land-use activities were detected during our observational period. In panels b-d, the positive sign indicates carbon emission to the atmosphere, and negative emission refers to carbon sink. The error bars in estimating emissions are at 95% confidence intervalsCC BY · PubMed Central

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Authors: Yang, Y., Saatchi, S. S., Xu, L., Yu, Y., Choi, S., Phillips, N., Kennedy, R., Keller, M., Knyazikhin, Y., & Myneni, R. B.
Affiliations: Boston University (US)
Jet Propulsion Laboratory (US)
Oregon State University (US)
US Forest Service (US)
Corresponding author: Yang, Yan
ORCID: Yang, Yan
Saatchi, Sassan S.
Xu, Liang
Yu, Yifan
Choi, Sungho
Phillips, Nathan
Kennedy, Robert
Keller, Michael
Knyazikhin, Yuri
Myneni, Ranga B.
Venue: Nature Communications
Publisher: Springer Science and Business Media LLC
Published: 2018-08-09
Volume: 9
Issue: 1
Pages: 3172-3172
ISSN: 2041-1723 (ISSN-L)
DOI: 10.1038/s41467-018-05668-6
PMC: PMC6085357
OpenAlex: W2887158854
Cited by: 189
References: 80
Citations by year: 2026: 12 · 2025: 15 · 2024: 29 · 2023: 25 · 2022: 29 · 2021: 39 · 2020: 23 · 2019: 16 · 2018: 1
FWCI: 9.92
Type: journal article
Language: en
Open access: gold
doi.org
Licence: cc-by
creativecommons.org/licenses/by/4.0 (tdm)
creativecommons.org/licenses/by/4.0 (vor)
Locations: Nature Communications (publishedVersion, cc-by)
Europe PMC (PubMed Central) (publishedVersion, other-oa)
PubMed Central (publishedVersion, cc-by)
PubMed (publishedVersion)
OpenBU (Boston University) (publishedVersion, cc-by)
RePEc: Research Papers in Economics (submittedVersion)
DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
Funders: National Science Foundation
National Aeronautics and Space Administration
California Institute of Technology
U.S. Geological Survey
Jet Propulsion Laboratory
Topics: Life Sciences › Agricultural and Biological Sciences › Forestry › Remote Sensing and LiDAR Applications
Physical Sciences › Environmental Science › Global and Planetary Change › Plant Water Relations and Carbon Dynamics
Life Sciences › Agricultural and Biological Sciences › Forestry › Forest ecology and management
Keywords: Amazon drought, forest carbon loss, aboveground biomass, forest structure, climate feedbacks, forest carbon dynamics, Amazon basin

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