Ecosystem heterogeneity and diversity mitigate Amazon forest resilience to frequent extreme droughts
Open accessAbstract
Summary: The impact of increases in drought frequency on the Amazon forest's composition, structure and functioning remain uncertain. We used a process‐ and individual‐based ecosystem model (ED 2) to quantify the forest's vulnerability to increased drought recurrence. We generated meteorologically realistic, drier‐than‐observed rainfall scenarios for two Amazon forest sites, Paracou (wetter) and Tapajós (drier), to evaluate the impacts of more frequent droughts on forest biomass, structure and composition. The wet site was insensitive to the tested scenarios, whereas at the dry site biomass declined when average rainfall reduction exceeded 15%, due to high mortality of large‐sized evergreen trees. Biomass losses persisted when year‐long drought recurrence was shorter than 2–7 yr, depending upon soil texture and leaf phenology. From the site‐level scenario results, we developed regionally applicable metrics to quantify the Amazon forest's climatological proximity to rainfall regimes likely to cause biomass loss > 20% in 50 yr according to ED 2 predictions. Nearly 25% (1.8 million km 2) of the Amazon forests could experience frequent droughts and biomass loss if mean annual rainfall or interannual variability changed by 2σ. At least 10% of the high‐emission climate projections (CMIP 5/RCP 8.5 models) predict critically dry regimes over 25% of the Amazon forest area by 2100.
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Amazonian forests are heterogeneous in their resilience to disturbances, which may have contributed to buffering large-scale transitions in the past.
“Amazonian forests are heterogeneous in their resilience to disturbances, which may have contributed to buffering large-scale transitions in the past37,61,62.”
From Critical transitions in the Amazon forest system (2024) · cites this paper as [61]
The Regional patterns of vulnerability section describes differences in drought resilience across Amazonian regions, and the Impacts of climate variability section says canopy reorganization can make responses to climate change more gradual. These passages support heterogeneous resilience and a possible buffering mechanism, but they do not establish that it buffered large-scale transitions in the past. (LLM, conf=0.83)
Experimental — accuracy not yet measuredSimulating individual trees can improve the representation of growth and mortality dynamics, which ultimately affect forest dynamics.
“Simulating individual trees can improve the representation of growth and mortality dynamics, which ultimately affect forest dynamics (for example, refs. 61,62,99).”
From Critical transitions in the Amazon forest system (2024) · cites this paper as [61]
The Ecosystem Demography Model, version 2 section describes a size- and age-structured model, and Site-level simulations link size-dependent growth and mortality to changes in forest structure. This supports the importance of representing tree-level differences, but the paper describes structured equations rather than simulations of individual trees and does not show that individual-tree simulation improves the representation of those dynamics. (LLM, conf=0.82)
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Higher functional diversity improves modeling of Amazon forest carbon storage
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Duff burning from wildfires in a moist region: different impacts on PM 2.5 and ozone
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Amazon forest fragmentation and edge effects temporarily favored understory and midstory tree growth
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Degradation and deforestation increase the sensitivity of the Amazon Forest to climate extremes
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Future Drought‐Induced Tree Mortality Risk in Amazon Rainforest
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Application of Big Data Analysis in Cost Control of Marine Fishery Breeding
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Future Hurricanes Will Increase Palm Abundance and Decrease Aboveground Biomass in a Tropical Forest
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Ecological Feedbacks in the Earth System
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Self-citationSanderson, B. M. (2021) · Earth System Dynamics · doi:10.5194/esd-2020-85-ac4
Liu, Y. (2021) · Atmospheric chemistry and physics · doi:10.5194/acp-2021-485-ac1
Liu, Y. (2021) · Atmospheric chemistry and physics · doi:10.5194/acp-2021-485-ac2
(2021) · Atmospheric chemistry and physics · doi:10.5194/acp-2021-485-rc1
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Sanderson, B. M. (2021) · Earth System Dynamics · doi:10.5194/esd-2020-85-ac3
Sanderson, B. M. (2021) · Earth System Dynamics · doi:10.5194/esd-2020-85-ac2
(2021) · Earth System Dynamics · doi:10.5194/esd-2020-85-rc1
(2021) · Earth System Dynamics · doi:10.5194/esd-2020-85-rc2
(2021) · Earth System Dynamics · doi:10.5194/esd-2020-85-rc3
(2021) · Earth System Dynamics · doi:10.5194/esd-2020-85-cc1
- Authors
- Longo, M., Knox, R. G., Levine, N. M., Alves, L. F., Bonal, D., Camargo, P. B., Fitzjarrald, D. R., Hayek, M. N., Restrepo‐Coupe, N., Saleska, S. R., da Silva, R., Stark, S. C., Tapajós, R. P., Wiedemann, K. T., Zhang, K., Wofsy, S. C., & Moorcroft, P. R.
- Affiliations
- Jet Propulsion Laboratory (US)
- Lawrence Berkeley National Laboratory (US)
- University of Southern California (US)
- University of California, Los Angeles (US)
- Ecologie et Ecophysiologie Forestières (FR)
- Centro de Energia Nuclear na Agricultura Universidade de São Paulo Piracicaba SP 13416‐000 Brazil
- University at Albany, State University of New York (US)
- Harvard University (US)
- Climate Change Cluster University of Technology Sydney Sydney NSW 2007 Australia
- University of Arizona (US)
- Universidade Federal do Oeste do Pará Santarém PA 68040‐255 USA
- Michigan State University (US)
- Universidade Federal do Oeste do Pará (BR)
- Hohai University (CN)
- Corresponding author
- Moorcroft, Paul R.
- ORCID
- Venue
- New Phytologist
- Publisher
- Wiley
- Published
- 2018-05-22
- Volume
- 219
- Issue
- 3
- Pages
- 914-931
- ISSN
- 0028-646X (ISSN-L)
- 1469-8137
- OpenAlex
- W2803398890
- Cited by
- 111
- References
- 121
- Citations by year
- 2026: 8 · 2025: 12 · 2024: 9 · 2023: 9 · 2022: 27 · 2021: 20 · 2020: 12 · 2019: 7 · 2018: 7
- FWCI
- 6.73
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- New Phytologist (publishedVersion, cc-by)
- PubMed (publishedVersion)
- OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) (submittedVersion)
- HAL (submittedVersion, cc-by)
- eScholarship (California Digital Library) (submittedVersion)
- NOAA Institutional Repository (submittedVersion, cc-by)
- UTS ePRESS (University of Technology Sydney) (submittedVersion)
- Funders
- Agence Nationale de la Recherche (ANR‐10‐LABX‐0025)
- National Oceanic and Atmospheric Administration
- Conselho Nacional de Desenvolvimento Científico e Tecnológico (200686/2005‐4)
- Fundação de Amparo à Pesquisa do Estado de São Paulo
- National Aeronautics and Space Administration (NNX08AP68A, NNX08AU95H, NNX10AR75G)
- National Science Foundation (0730305)
- Gordon and Betty Moore Foundation (1971, 3413)
- Topics
- Physical Sciences › Environmental Science › Global and Planetary Change › Plant Water Relations and Carbon Dynamics
- Physical Sciences › Environmental Science › Global and Planetary Change › Fire effects on ecosystems
- Physical Sciences › Environmental Science › Nature and Landscape Conservation › Forest ecology and management
- Keywords
- Amazon rainforest, drought frequency, forest resilience, ecosystem heterogeneity, biodiversity, forest biomass loss, tree mortality, evergreen trees, soil texture, leaf phenology, climate change projections, RCP8.5, Paracou, Tapajós, forest structure and composition
- MeSH terms
- Carbon Dioxide, Computer Simulation, Geography, Models, Theoretical, Rain, South America, Plant Transpiration, Biomass, Droughts, Forests
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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