Amazonian forest-savanna bistability and human impact
- Submitting institution
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University of Bristol
- Unit of assessment
- 12 - Engineering
- Output identifier
- 197132248
- Type
- D - Journal article
- DOI
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10.1038/ncomms15519
- Title of journal
- Nature Communications
- Article number
- 15519
- First page
- -
- Volume
- 8
- Issue
- -
- ISSN
- 2041-1723
- Open access status
- Compliant
- Month of publication
- May
- Year of publication
- 2017
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
2
- Research group(s)
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N - Applied Nonlinear Mathematics
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- New data analysis and analytical insight shows Amazon is much more robust than previously thought. High profile and popular accounts showed local bistability so that removed forest would permanently remain savanna. Here it's shown that distance to human influence is confounding factor in data, whose removal shows there is sharp forest/savanna transition. Explained by mathematical model and concept of Maxwell point in energy landscape. Result of complexity science interdisciplinary PhD. Resulted in popular children's publication, a PLOS One followup, House's work with IPCC and Postdoc for Wuyts on natural tipping points at Exeter. Importance for understanding climate resilience.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -