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Exploring uncertainty of Amazon dieback in a perturbed parameter Earth system ensemble.
Chris A Boulton1, Ben B B Booth2, Peter Good2
1Earth System Science, College of Life and Environmental Sciences, University of Exeter, Exeter, UK.
Global Change Biology
|April 28, 2017
Summary
The Amazon rainforest may face significant future forest loss, especially long-term, due to climate change uncertainties. Understanding forest resiliency and climate feedbacks is crucial for predicting its fate.
Area of Science:
- Climate Science
- Ecology
- Environmental Modeling
Background:
- The future of the Amazon rainforest is uncertain due to projected climate change and its inherent resiliency.
- Previous models have not fully integrated land vegetation processes with physical climate feedbacks.
Purpose of the Study:
- To explore the impact of uncertainties in climate and land surface processes on Amazon forest future.
- To analyze both transient and long-term committed forest responses under various emissions scenarios.
Main Methods:
- Utilized a perturbed physics ensemble of the HadCM3C model.
- Investigated changes in forest coverage by the end of the 21st century.
- Adapted a "dry-season resilience" method to predict long-term committed forest response.
Main Results:
- High probability of greater forest loss on longer timescales than by 2100, particularly in mid-range and low emissions scenarios.
- Uncertainty in forest outcomes increases with the strength of emissions scenarios.
- Low optimum temperatures for photosynthesis and high minimum leaf area index are linked to dieback.
Conclusions:
- Reducing uncertainty in both climate change projections and forest resiliency is vital for determining the Amazon's future.
- The study suggests less extreme forest loss than some previous standard model configurations.
- Long-term forest loss is a significant concern, even under lower emissions.
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