Hysteresis of tropical forests in the 21st century
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Tropical forests modify the conditions they depend on through feedbacks at different spatial scales. These feedbacks shape the hysteresis (history-dependence) of tropical forests, thus controlling their resilience to deforestation and response to climate change. Here, we determine the emergent hysteresis from local-scale tipping points and regional-scale forest-rainfall feedbacks across the tropics under the recent climate and a severe climate-change scenario. By integrating remote sensing, a global hydrological model, and detailed atmospheric moisture tracking simulations, we find that forest-rainfall feedback expands the geographic range of possible forest distributions, especially in the Amazon. The Amazon forest could partially recover from complete deforestation, but may lose that resilience later this century. The Congo forest currently lacks resilience, but is predicted to gain it under climate change, whereas forests in Australasia are resilient under both current and future climates. Our results show how tropical forests shape their own distributions and create the climatic conditions that enable them.
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Satellite observations of tree cover distributions across tropical South America suggest a critical threshold between 1,000 and 1,250 mm of annual rainfall.
“Satellite observations of tree cover distributions across tropical South America suggest a critical threshold between 1,000 and 1,250 mm of annual rainfall78,79.”
From Critical transitions in the Amazon forest system (2024) · cites this paper as [78]
The Results (‘Stability of tropical forests’; page unavailable) use forest-cover distributions to identify a rainfall-dependent change in South America, with bistability beginning at 1,250 mm per year. The paper does not place the threshold between 1,000 and 1,250 mm per year; it reports a bistable range of 1,250–2,050 mm per year. (LLM, conf=0.85)
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Self-citation
- Authors
- Staal, A., Fetzer, I., Wang-Erlandsson, L., Bosmans, J. H. C., Dekker, S. C., van Nes, E. H., Rockström, J., & Tuinenburg, O. A.
- Affiliations
- Stockholm Resilience Centre (SE)
- Radboud University Nijmegen (NL)
- Utrecht University (NL)
- Corresponding author
- Staal, Arie
- ORCID
- Venue
- Nature Communications
- Published
- 2020-10-05
- Volume
- 11
- Issue
- 1
- Pages
- 4978-4978
- ISSN
- 2041-1723 (ISSN-L)
- PMC
- PMC7536390
- OpenAlex
- W3089791600
- Cited by
- 200
- References
- 6
- Citations by year
- 2026: 26 · 2025: 27 · 2024: 37 · 2023: 39 · 2022: 41 · 2021: 30
- FWCI
- 10.22
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Nature Communications (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Socio-Environmental Systems Modeling (acceptedVersion, other-oa)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Radboud Repository (Radboud University) (submittedVersion)
- Radboud Repository (Radboud University) (submittedVersion, other-oa)
- Utrecht University Repository (Utrecht University) (submittedVersion, other-oa)
- Data Archiving and Networked Services (DANS) (submittedVersion, cc-by)
- Funders
- Svenska Forskningsrådet Formas (2019-01220, 2018-02345)
- Nederlandse Organisatie voor Wetenschappelijk Onderzoek (0.16.veni.171.019)
- Vetenskapsrådet (2018-)
- Stockholms Universitet
- H2020 European Research Council (743080)
- Topics
- Physical Sciences › Environmental Science › Global and Planetary Change › Ecosystem dynamics and resilience
- Physical Sciences › Environmental Science › Global and Planetary Change › Climate variability and models
- Physical Sciences › Environmental Science › Global and Planetary Change › Conservation, Biodiversity, and Resource Management
- Keywords
- tropical forests, hysteresis, tipping points, climate change impacts, Amazon rainforest, forest distribution, global hydrological models, history dependence
- MeSH terms
- Africa, Asia, Southeastern, Australia, Conservation of Natural Resources, Feedback, Rain, South America, Tropical Climate, Ecosystem, Climate Change, Forests
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