CaltechAUTHORS
  A Caltech Library Service

Carbon loss from forest degradation exceeds that from deforestation in the Brazilian Amazon

Qin, Yuanwei and Xiao, Xiangming and Wigneron, Jean-Pierre and Ciais, Philippe and Brandt, Martin and Fan, Lei and Li, Xiaojun and Crowell, Sean and Wu, Xiaocui and Doughty, Russell and Zhang, Yao and Liu, Fang and Sitch, Stephen and Moore, Berrien, III (2021) Carbon loss from forest degradation exceeds that from deforestation in the Brazilian Amazon. Nature Climate Change, 11 (5). pp. 442-448. ISSN 1758-678X. https://resolver.caltech.edu/CaltechAUTHORS:20210527-093457171

[img] Image (JPEG) (Extended Data Fig. 1: Monthly multivariate El Niño/Southern Oscillation (ENSO) index and Atlantic Multidecadal Osillation (AMO) index during 2009–2019) - Supplemental Material
See Usage Policy.

108kB
[img] Image (JPEG) (Extended Data Fig. 2: Two-dimension scatter plots and linear regression relationships between L-VOD AGB and MODIS-based forest area fraction in the Brazilian Amazon during 2010–2019) - Supplemental Material
See Usage Policy.

302kB
[img] Image (JPEG) (Extended Data Fig. 3: The spatial distributions of AGB changes in 2015 and 2019) - Supplemental Material
See Usage Policy.

276kB
[img] Image (JPEG) (Extended Data Fig. 4: The relationships between annual average AGB and forest area changes within different initial forest area fraction intervals in 2010) - Supplemental Material
See Usage Policy.

220kB
[img] Image (JPEG) (Extended Data Fig. 5: The annual gross forest area loss estimated by this study, Global Forest Watch (GFW), and PRODES in the Brazilian Amazon during 2010–2019) - Supplemental Material
See Usage Policy.

163kB
[img] Image (JPEG) (Extended Data Fig. 6: Interannual variation of atmospheric CO₂ concentration) - Supplemental Material
See Usage Policy.

105kB
[img] Image (JPEG) (Extended Data Fig. 7: AGB changes over the two periods of 2010–2013 and 2015–2018 along the precipitation and maximum cumulated water deficit (MCWD) in the Brazilian Amazon) - Supplemental Material
See Usage Policy.

163kB
[img] Image (JPEG) (Extended Data Fig. 8: AGB recovery strength in 2017, 2018, and 2019 after 2015/2016 El Nino) - Supplemental Material
See Usage Policy.

258kB
[img] Image (JPEG) (Extended Data Fig. 9: The spatial distribution maps of the average OCO-2 XCO2 in the wet season and dry season at the spatial resolution of 1˚ in the Brazilian Amazon in 2015 and 2016) - Supplemental Material
See Usage Policy.

234kB
[img] Image (JPEG) (Extended Data Fig. 10: AGB anomaly, forest area fraction, (Precipitation (P) – Evapotranspiration (ET)) anomaly, and fire area in the intact forests in the Brazilian Amazon during 2010–2019) - Supplemental Material
See Usage Policy.

146kB
[img] PDF (Supplementary Figs. 1–8 and Tables 1 and 2) - Supplemental Material
See Usage Policy.

2MB
[img] PDF (Reporting Summary) - Supplemental Material
See Usage Policy.

71kB

Use this Persistent URL to link to this item: https://resolver.caltech.edu/CaltechAUTHORS:20210527-093457171

Abstract

Spatial–temporal dynamics of aboveground biomass (AGB) and forest area affect the carbon cycle, climate and biodiversity in the Brazilian Amazon. Here we investigate interannual changes in AGB and forest area by analysing satellite-based annual AGB and forest area datasets. We found that the gross forest area loss was larger in 2019 than in 2015, possibly due to recent loosening of forest protection policies. However, the net AGB loss was three times smaller in 2019 than in 2015. During 2010–2019, the Brazilian Amazon had a cumulative gross loss of 4.45 Pg C against a gross gain of 3.78 Pg C, resulting in a net AGB loss of 0.67 Pg C. Forest degradation (73%) contributed three times more to the gross AGB loss than deforestation (27%), given that the areal extent of degradation exceeds that of deforestation. This indicates that forest degradation has become the largest process driving carbon loss and should become a higher policy priority.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.1038/s41558-021-01026-5DOIArticle
https://rdcu.be/clr0mPublisherFree ReadCube access
http://earthenginepartners.appspot.com/science-2013-global-forestRelated ItemGFW product
http://www.obt.inpe.br/OBT/assuntos/programas/amazonia/prodesRelated ItemPRODES forest product
https://lpdaac.usgs.gov/data/Related ItemMOD14A2, MOD16A2 and MCD64A1 products
https://pmm.nasa.gov/data-access/downloads/trmmRelated ItemTRMM product
https://www.esrl.noaa.gov/psd/Related ItemPAR product
ORCID:
AuthorORCID
Qin, Yuanwei0000-0002-5181-9986
Xiao, Xiangming0000-0003-0956-7428
Wigneron, Jean-Pierre0000-0001-5345-3618
Ciais, Philippe0000-0001-8560-4943
Brandt, Martin0000-0001-9531-1239
Fan, Lei0000-0002-1834-5088
Crowell, Sean0000-0001-8353-3707
Wu, Xiaocui0000-0001-7447-0257
Doughty, Russell0000-0001-5191-2155
Zhang, Yao0000-0002-7468-2409
Sitch, Stephen0000-0003-1821-8561
Additional Information:© 2021 Springer Nature Limited. Received 06 April 2020. Accepted 12 March 2021. Published 29 April 2021. We thank P. Friedlingstein, N. Vuichard, D. Zhu, M. Kautz and B. Poulter for their comments and discussion regarding the early version of this manuscript. Y.Q. and X.X. were supported by the NASA Land Use and Land Cover Change programme (grant no. NNX14AD78G); the Inter-American Institute for Global Change Research (IAI) (grant no. CRN3076), which is supported by the US National Science Foundation (grant no. GEO-1128040); and the NSF EPSCoR project (grant no. IIA-1301789). Y.Q., X.X., S.C., X.W., R.D. and B.M. were supported by NASA’s GeoCarb Mission (GeoCarb Contract no. 80LARC17C0001). J.-P.W. was supported by the SMOS project of the TOSCA Programme from CNES, France (Centre National d’Etudes Spatiales). P.C. and S.S. were supported by the RECCAP2 project, which is part of the ESA Climate Change Initiative (contract no. 4000123002/18/I-NB) and the H2020 European Institute of Innovation and Technology (4C; grant no. 821003). S.S. was supported by the Newton Fund through the Met Office Climate Science for Service Partnership Brazil (CSSP Brazil). M.B. was supported by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement no. 947757 TOFDRY) and a DFF Sapere Aude grant (no. 9064–00049B). L.F. was supported by the National Natural Science Foundation of China (grant nos 41801247 and 41830648) and the Natural Science Foundation of Jiangsu Province (grant no. BK20180806). X.L. was supported by the China Scholarship Council (grant no. 201804910838). F.L. was supported by the Strategic Priority Research Program of the Chinese Academy of Sciences (grant no. XDA20010202). Data availability. The annual evergreen forest maps67 and AGB maps68 are freely available in GeoTIFF format at Figshare. The GFW product is available at http://earthenginepartners.appspot.com/science-2013-global-forest. The PRODES forest product is available at http://www.obt.inpe.br/OBT/assuntos/programas/amazonia/prodes. The MOD14A2, MOD16A2 and MCD64A1 products are available at https://lpdaac.usgs.gov/data/. The TRMM product is available at https://pmm.nasa.gov/data-access/downloads/trmm. The PAR product is from the NCEP/DOE 2 Reanalysis data provided by the NOAA/OAR/ESRL PSD, Boulder, Colorado, USA, from their website at https://www.esrl.noaa.gov/psd/. Code availability. The code for the evergreen forest mapping and spatial correlation analysis are freely available at Figshare69. The other data processing and analyses were done mainly in ArcMap (https://desktop.arcgis.com/en/arcmap/). Author Contributions. X.X. and Y.Q. designed the overall study plan. Y.Q. and X.X. prepared the annual evergreen forest maps. J.-P.W., M.B., L.F. and X.L. prepared the annual L-VOD AGB dataset. S.C. prepared the OCO-2 XCO2 dataset. Y.Q., X.X., X.W., R.D., Y.Z. and F.L. carried out the data processing and analysis. X.X., Y.Q., J.-P.W., P.C., M.B., S.S. and L.F. interpreted the results. Y.Q. and X.X. drafted the manuscript, and all authors contributed to the writing and revision of the manuscript. The authors declare no competing interests. Peer review information. Nature Climate Change thanks Luiz Aragão, Paulo Brando and Fernando Espírito-Santo for their contribution to the peer review of this work.
Funders:
Funding AgencyGrant Number
NASANNX14AD78G
Inter-American Institute for Global Change ResearchCRN3076
NSFICER-1128040
NSFOIA-1301789
NASA80LARC17C0001
Centre National d'Études Spatiales (CNES)UNSPECIFIED
European Space Agency (ESA)4000123002/18/I-NB
European Research Council (ERC)821003
Met Office Climate Science for Service Partnership (CSSP)UNSPECIFIED
European Research Council (ERC)947757
Independent Research Fund Denmark9064-00049
National Natural Science Foundation of China41801247
National Natural Science Foundation of China41830648
Natural Science Foundation of Jiangsu ProvinceBK20180806
China Scholarship Council201804910838
Chinese Academy of SciencesXDA20010202
Subject Keywords:Climate change; Climate-change ecology; Forest ecology; Tropical ecology
Issue or Number:5
Record Number:CaltechAUTHORS:20210527-093457171
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20210527-093457171
Official Citation:Qin, Y., Xiao, X., Wigneron, JP. et al. Carbon loss from forest degradation exceeds that from deforestation in the Brazilian Amazon. Nat. Clim. Chang. 11, 442–448 (2021). https://doi.org/10.1038/s41558-021-01026-5
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:109276
Collection:CaltechAUTHORS
Deposited By: George Porter
Deposited On:27 May 2021 20:43
Last Modified:27 May 2021 20:43

Repository Staff Only: item control page