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Amazonia as a carbon source linked to deforestation and climate change

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Abstract

Amazonia hosts the Earth’s largest tropical forests and has been shown to be an important carbon sink over recent decades1,2,3. This carbon sink seems to be in decline, however, as a result of factors such as deforestation and climate change1,2,3. Here we investigate Amazonia’s carbon budget and the main drivers responsible for its change into a carbon source. We performed 590 aircraft vertical profiling measurements of lower-tropospheric concentrations of carbon dioxide and carbon monoxide at four sites in Amazonia from 2010 to 20184. We find that total carbon emissions are greater in eastern Amazonia than in the western part, mostly as a result of spatial differences in carbon-monoxide-derived fire emissions. Southeastern Amazonia, in particular, acts as a net carbon source (total carbon flux minus fire emissions) to the atmosphere. Over the past 40 years, eastern Amazonia has been subjected to more deforestation, warming and moisture stress than the western part, especially during the dry season, with the southeast experiencing the strongest trends5,6,7,8,9. We explore the effect of climate change and deforestation trends on carbon emissions at our study sites, and find that the intensification of the dry season and an increase in deforestation seem to promote ecosystem stress, increase in fire occurrence, and higher carbon emissions in the eastern Amazon. This is in line with recent studies that indicate an increase in tree mortality and a reduction in photosynthesis as a result of climatic changes across Amazonia1,10.

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Fig. 1: Regions of influence.
Fig. 2: Annual mean VPs.
Fig. 3: Annual carbon fluxes.
Fig. 4: 40-year precipitation and temperature trends.
Fig. 5: Spatial results overview.

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Data availability

The CO2 VP data that support the findings of this study are available from PANGAEA Data Archiving, at https://doi.org/10.1594/PANGAEA.926834Source data are provided with this paper.

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Acknowledgements

We thank S. Denning and E. Mitchard for valuable reviews. This work was funded by many projects supporting the long-term measurements: State of Sao Paulo Science Foundation – FAPESP (16/02018-2, 11/51841-0, 08/58120-3, 18/14006-4, 18/14423-4, 18/18493-7, 19/21789-8, 11/17914-0), UK Environmental Research Council (NERC) AMAZONICA project (NE/F005806/1), NASA grants (11-CMS11-0025, NRMJ1000-17-00431), European Research Council (ERC) under Horizon 2020 (649087), 7FP EU (283080), MCTI/CNPq (2013), CNPq (134878/2009-4, 310130/2017-4, 305054/2016-3, 314416/2020-0). We thank the staff at NOAA/GML who provided advice and technical support for air sampling and measurements in Brazil, and the pilots and technical team at aircraft sites who collected the air samples. We thank J. F. Mueller for providing modelled biogenic CO fluxes.

Author information

Authors and Affiliations

Authors

Contributions

L.V.G., M.G. and J.B.M. conceived the basin-wide measurement programme and approach; L.V.G. wrote the paper; all co-authors participated in scientific meetings to interpret the data, and commented on and reviewed the manuscript; L.G.D., A.H.S., L.S.B., H.L.G.C., G.T., L.M. and L.V.G. contributed to the region-of-influence study; L.V.G., H.L.G.C., E.A., L.S.B., S.M.C. and J.B.M. contributed to the climate data weighted analysis; L.G.D., C.S.C.C., S.M.C. and R.A.L.N. contributed to the greenhouse gas concentration analysis; G.T. provided deforestation analyses; J.B.M. and L.V.G. contributed to the estimation of biogenic CO.

Corresponding author

Correspondence to Luciana V. Gatti.

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The authors declare no competing interests.

Additional information

Peer review information Nature thanks Scott Denning, Edward Mitchard and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data figures and tables

Extended Data Fig. 1 VPs, time series and annual mean CO2 concentrations.

a, Time series of mean VPs of the CO2 mole fractions of the flasks below 1.5 km a.s.l. (red circles) and above 3.8 km a.s.l. (blue circles) for sites SAN, ALF, RBA and TAB_TEF (590 VPs) and the background sites RPB, ASC and CPT. b, Annual mean VPs for the four sites (annual mean per height; see Methods). c, Annual mean ΔVP (see Methods) for each site and year. d, Annual mean differences between mean CO2 mole fractions below 1.5 km a.s.l. and means above 3.8 km a.sl. for each site and year (see Methods). e, Partial column annual means plotted against annual mean fluxes, by site.

Source data

Extended Data Fig. 2 Regions of influence.

a, Mean quarterly regions of influence for the ALF, SAN, RBA, TEF and TAB sites, averaged between 2010 and 2018, calculated using the density of back-trajectories (see Methods). b, Deforestation inside quarterly regions of influence and the Amazon mask (purple line) using data from PRODES32 (see Methods). c, Annual mean regions of influence (trajectory densities) averaged between 2010 and 2018.

Extended Data Fig. 3 Seasonal carbon flux and driver variables.

Average monthly means of potential flux driver variables at sites TAB_TEF, SAN, RBA and ALF in 2010–2018. Grey bands denote the standard deviation of the monthly mean.

Extended Data Fig. 4 Time series of carbon flux and driver variables.

As in Extended Data Fig. 3, but showing the full time series of monthly means from 2010 to 2018 for SAN, ALF, TAB_TEF and RBA. Grey bands as in Extended Data Fig. 3, showing the 2010–2018 standard deviation for each month.

Extended Data Fig. 5 ALF NBE drivers.

a, ALF annual mean NBE (NBE = total C flux − fire C flux, in g C m−2 d−1) from 2010 to 2018. Error bars are uncertainties related to the background, travel time trajectories, emission ratios CO/CO2 and natural CO flux (see Methods). b, Annual mean FCNBE, annual mean temperature and GRACE (equivalent water thickness) satellite soil water storage anomalies.

Extended Data Fig. 6 Amazon carbon fluxes per region.

a, Separation of three regions inside the Amazon Mask (7,256,362 km2, purple line). Region 1: area of combined regions of influence for SAN and ALF; region 2: area of combined region of influence for RBA and TAB (2010–2012) and RBA and TEF (2013–2018), excluding region 1; region 3: the remaining area outside regions 1 and 2 and inside the purple line. b, Annual mean fluxes for regions 1, 2 and 3 (total, blue line; fire, red line; NBE, green line).

Extended Data Fig. 7 Mean temperature and precipitation in Amazonia over the past 40 years.

a, Monthly mean temperature in Amazonia in 1979–2018, calculated using ERA Interim (ECMWF) monthly means (see Methods). Grey points are monthly mean temperatures from 1979 to 2018. Blue and red circles show decadal monthly mean temperatures for 1979–1988 and 2009–2018, respectively. Error bars denote one standard deviation for the decade. b, Blue circles are annual mean temperatures; green circles show mean temperatures for January, February and March; red circles show mean temperatures for August, September and October. c, As in a, but for precipitation calculated using GPCP version 2.3 (see Methods). d, Blue circles are annual total precipitation; green circles are total precipitation for January, February and March; and red circles are total precipitation for August, September and October.

Extended Data Fig. 8 Seasonal temperature and precipitation over the past 40 years.

Monthly precipitation (GPCP v2.3) and monthly mean temperature (ERA-Interim) for TAB, SAN, RBA, ALF and TEF, calculated using spatial weightings from 2010–2018 quarterly regions of influence (Extended Data Fig. 2a) inside the Amazon mask. Symbols are as in Extended Data Fig. 7.

Extended Data Table 1 Analysis of temperature and precipitation data obtained over the past 40 years
Extended Data Table 2 Summary of the main results for ALF, SAN, RBA and TAB_TEF

Supplementary information

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Gatti, L.V., Basso, L.S., Miller, J.B. et al. Amazonia as a carbon source linked to deforestation and climate change. Nature 595, 388–393 (2021). https://doi.org/10.1038/s41586-021-03629-6

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