Abstract The Amazon biome is being pushed by unsustainable economic drivers towards an ecological tipping point where restoration to its previous state may no longer be possible. This degradation is the result of self-reinforcing interactions between deforestation, climate change and fire. We assess the economic, natural capital and ecosystem services impacts and trade-offs of scenarios representing movement towards an Amazon tipping point and strategies to avert one using the Integrated Economic-Environmental Modeling (IEEM) Platform linked with spatial land use-land cover change and ecosystem services modeling (IEEM + ESM). Our approach provides the first approximation of the economic, natural capital and ecosystem services impacts of a tipping point, and evidence to build the economic case for strategies to avert it. For the five Amazon focal countries, namely, Brazil, Peru, Colombia, Bolivia and Ecuador, we find that a tipping point would create economic losses of US$256.6 billion in cumulative gross domestic product by 2050. Policies that would contribute to averting a tipping point, including strongly reducing deforestation, investing in intensifying agriculture in cleared lands, climate-adapted agriculture and improving fire management, would generate approximately US$339.3 billion in additional wealth and a return on investment of US$29.5 billion. Quantifying the costs, benefits and trade-offs of policies to avert a tipping point in a transparent and replicable manner can support the design of regional development strategies for the Amazon biome, build the business case for action and catalyze global cooperation and financing to enable policy implementation.
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Adaptive mitigation strategies hedge against extreme climate futures
The United Nations Framework Convention on Climate Change agreed to “strengthen the global response to the threat of climate change, in the context of sustainable development and efforts to eradicate poverty” (UNFCCC 2015). Designing a global mitigation strategy to support this goal poses formidable challenges. For one, there are trade-offs between the economic costs and the environmental benefits of averting climate impacts. Furthermore, the coupled human-Earth systems are subject to deep and dynamic uncertainties. Previous economic analyses typically addressed either the former, introducing multiple objectives, or the latter, making mitigation actions responsive to new information. This paper aims at bridging these two separate strands of literature. We demonstrate how information feedback from observed global temperature changes can jointly improve the economic and environmental performance of mitigation strategies. We focus on strategies that maximize discounted expected utility while also minimizing warming above 2 °C, damage costs, and mitigation costs. Expanding on the Dynamic Integrated Climate-Economy (DICE) model and previous multi-objective efforts, we implement closed-loop control strategies, map the emerging trade-offs and quantify the value of the temperature information feedback under both well-characterized and deep climate uncertainties. Adaptive strategies strongly reduce high regrets, guarding against mitigation overspending for less sensitive climate futures, and excessive warming for more sensitive ones.
more » « less- NSF-PAR ID:
- 10388415
- Publisher / Repository:
- Springer Science + Business Media
- Date Published:
- Journal Name:
- Climatic Change
- Volume:
- 166
- Issue:
- 3-4
- ISSN:
- 0165-0009
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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