Abstract
The Amazon is the largest continuous tropical forest in the world and plays a key role in the global carbon cycle. Human-induced disturbances and climate change have impacted the Amazon carbon balance. Here we conduct a comprehensive synthesis of existing state-of-the-art estimates of the contemporary land carbon fluxes in the Amazon using a set of bottom-up methods (i.e., dynamic vegetation models and bookkeeping models) and a top-down inversion (atmospheric inversion model) over the Brazilian Amazon and the whole Biogeographical Amazon domain. Over the whole biogeographical Amazon region bottom-up methodologies suggest a small average carbon sink over 2010-2020, in contrast to a small carbon source simulated by top-down inversion (2010-2018). However, these estimates are not significantly different from one another when accounting for their large individual uncertainties, highlighting remaining knowledge gaps, and the urgent need to reduce such uncertainties. Nevertheless, both methodologies agreed that the Brazilian Amazon has been a net carbon source during recent climate extremes and that the south-eastern Amazon was a net land carbon source over the whole study period (2010-2020). Overall, our results point to increasing human-induced disturbances (deforestation and forest degradation by wildfires) and reduction in the old-growth forest sink during drought.
Original language | English |
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Article number | 46 |
Journal | Communications Earth and Environment |
Volume | 5 |
Issue number | 1 |
DOIs | |
State | Published - Dec 2024 |
Funding
The development of this research has been supported by the Newton Fund through the Met Office Climate Science for Service Partnership Brazil (CSSP Brazil), 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). C.W. is funded via UK National Centre for Earth Observation (NE/R016518/1 and NE/N018079/1). L.S.B is funded by State of Sao Paulo Science Foundation\u2014FAPESP (2018/14006-4, 2020/02656-4). L.G. was funded by CARBAM project (FAPESP 2016/02018-2). ORNL is managed by UT-Battelle, LLC, for the DOE under contract DE-AC05-1008 00OR22725. For the purpose of open access, the author has applied a \u2018Creative Commons Attribution (CC BY) licence to any Author Accepted Manuscript version arising. We thank Ian Harris for advising us on the CRUJRA forcing dataset.