Critical transitions in the Amazon forest system

Bernardo M. Flores*, Encarni Montoya, Boris Sakschewski, Nathália Nascimento, Arie Staal, Richard A. Betts, Carolina Levis, David M. Lapola, Adriane Esquível-Muelbert, Catarina Jakovac, Carlos A. Nobre, Rafael S. Oliveira, Laura S. Borma, Da Nian, Niklas Boers, Susanna B. Hecht, Hans ter Steege, Julia Arieira, Isabella L. Lucas, Erika BerenguerJosé A. Marengo, Luciana V. Gatti, Caio R. C. Mattos, Marina Hirota*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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Abstract

The possibility that the Amazon forest system could soon reach a tipping point, inducing large-scale collapse, has raised global concern1–3. For 65 million years, Amazonian forests remained relatively resilient to climatic variability. Now, the region is increasingly exposed to unprecedented stress from warming temperatures, extreme droughts, deforestation and fires, even in central and remote parts of the system1. Long existing feedbacks between the forest and environmental conditions are being replaced by novel feedbacks that modify ecosystem resilience, increasing the risk of critical transition. Here we analyse existing evidence for five major drivers of water stress on Amazonian forests, as well as potential critical thresholds of those drivers that, if crossed, could trigger local, regional or even biome-wide forest collapse. By combining spatial information on various disturbances, we estimate that by 2050, 10% to 47% of Amazonian forests will be exposed to compounding disturbances that may trigger unexpected ecosystem transitions and potentially exacerbate regional climate change. Using examples of disturbed forests across the Amazon, we identify the three most plausible ecosystem trajectories, involving different feedbacks and environmental conditions. We discuss how the inherent complexity of the Amazon adds uncertainty about future dynamics, but also reveals opportunities for action. Keeping the Amazon forest resilient in the Anthropocene will depend on a combination of local efforts to end deforestation and degradation and to expand restoration, with global efforts to stop greenhouse gas emissions.
Original languageEnglish
Pages (from-to)555-564
Number of pages10
JournalNature
Volume626
Issue number7999
Early online date14 Feb 2024
DOIs
Publication statusPublished - 15 Feb 2024

Bibliographical note

Acknowledgments:
This work was inspired by the Science Panel for the Amazon (SPA) initiative (https://www.theamazonwewant.org/) that produced the first Amazon Assessment Report (2021). The authors thank C. Smith for providing deforestation rates data used in Extended Data Fig. 5b. B.M.F. and M.H. were supported by Instituto Serrapilheira (Serra-1709-18983) and C.J. (R-2111-40341). A.S. acknowledges funding from the Dutch Research Council (NWO) under the Talent Program Grant VI.Veni.202.170. R.A.B. and D.M.L. were supported by the AmazonFACE programme funded by the UK Foreign, Commonwealth and Development Office (FCDO) and Brazilian Ministry of Science, Technology and Innovation (MCTI). R.A.B. was additionally supported by the Met Office Climate Science for Service Partnership (CSSP) Brazil project funded by the UK Department for Science, Innovation and Technology (DSIT), and D.M.L. was additionally supported by FAPESP (grant no. 2020/08940-6) and CNPq (grant no. 309074/2021-5). C.L. thanks CNPq (proc. 159440/2018-1 and 400369/2021-4) and Brazil LAB (Princeton University) for postdoctoral fellowships. A.E.-M. is supported by the UKRI TreeScapes MEMBRA (NE/V021346/1), the Royal Society (RGS\R1\221115), the ERC TreeMort project (758873) and the CESAB Syntreesys project. R.S.O. received a CNPq productivity scholarship and funding from NERC-FAPESP 2019/07773-1. S.B.H. is supported by the Geneva Graduate Institute research funds, and UCLA’s committee on research. J.A.M. is supported by the National Institute of Science and Technology for Climate Change Phase 2 under CNPq grant 465501/2014-1; FAPESP grants 2014/50848-9, the National Coordination for Higher Education and Training (CAPES) grant 88887.136402-00INCT. L.S.B. received FAPESP grant 2013/50531-0. D.N. and N.B. acknowledge funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 820970. N.B. has received further funding from the Volkswagen foundation, the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement no. 956170, as well as from the German Federal Ministry of Education and Research under grant no. 01LS2001A.

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