Can we avert an Amazon tipping point? The economic and environmental costs

Onil Banerjee; Martin Cicowiez; Marcia N. Macedo; Žiga Malek; Peter H. Verburg; Sean Goodwin; Renato Vargas; Ludmila Rattis; Kenneth J. Bagstad; Paulo M. Brando; Michael T. Coe; Christopher Neill; Octavio Damiani Marti; Josué Ávila Murillo

doi:10.1088/1748-9326/aca3b8

Can we avert an Amazon tipping point? The economic and environmental costs

Onil Banerjee^*
, Martin Cicowiez
, Marcia N. Macedo
, Žiga Malek
, Peter H. Verburg
, Sean Goodwin
, Renato Vargas
, Ludmila Rattis
, Kenneth J. Bagstad
, Paulo M. Brando
, Michael T. Coe
, Christopher Neill
, Octavio Damiani Marti
, Josué Ávila Murillo

^*Corresponding author for this work

Environmental Geography

Research output: Contribution to Journal › Article › Academic › peer-review

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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.

Original language	English
Article number	125005
Pages (from-to)	1-12
Number of pages	12
Journal	Environmental Research Letters
Volume	17
Issue number	12
Early online date	2 Dec 2022
DOIs	https://doi.org/10.1088/1748-9326/aca3b8
Publication status	Published - Dec 2022

Bibliographical note

Funding Information:
This study was commissioned by the UK’s HM Treasury to inform the Dasgupta Review on the Economics of Biodiversity. The study was funded by the UK’s Department for Environment, Food & Rural Affairs and the Inter-American Development Bank. Support for Onil Banerjee’s time was provided by the Inter-American Development Bank until March 2022 and by RMGEO Consultants Inc. thereafter. Support for Bagstad’s time was provided by the USGS Land Change Science Program. Modeling of deforestation-climate feedbacks and analysis of regional climate risks for agricultural productivity, drought, and fire were supported by grants from the NSF (INFEWS #1739724), CNPq (Nexus-Cerrado #441463/2017-7; PELD-Tang #441703/2016-0PELD), and the Gordon and Betty Moore Foundation (#5482, #9957). The authors thank Robert Marks, Emily McKenzie, Felix Nugee and the Dasgupta Review Team for their constructive review of an early version of this study. The authors thank the Inter-American Development Bank’s Allen Blackman, Gregory Watson, Annette Kilmer, Eirivelthon Lima, Carlos Salazar, Santiago Bucaram, Marisol Inurritegui, Pedro Martel, Fabiano Bastos, Jose Luiz Rossi and Aloisio de Melo for their valuable comments. Thanks also to Judson Ferreira Valentim, Mariane Crespolini dos Santos and Sergio De Zen for sharing their insights. The authors thank GLASSNET for providing a platform for engaging with GLASSNET scholars to enrich the study and identify linkages with related work from global to local scales.

Publisher Copyright:
© 2022 The Author(s). Published by IOP Publishing Ltd.

Funding

This study was commissioned by the UK’s HM Treasury to inform the Dasgupta Review on the Economics of Biodiversity. The study was funded by the UK’s Department for Environment, Food & Rural Affairs and the Inter-American Development Bank. Support for Onil Banerjee’s time was provided by the Inter-American Development Bank until March 2022 and by RMGEO Consultants Inc. thereafter. Support for Bagstad’s time was provided by the USGS Land Change Science Program. Modeling of deforestation-climate feedbacks and analysis of regional climate risks for agricultural productivity, drought, and fire were supported by grants from the NSF (INFEWS #1739724), CNPq (Nexus-Cerrado #441463/2017-7; PELD-Tang #441703/2016-0PELD), and the Gordon and Betty Moore Foundation (#5482, #9957). The authors thank Robert Marks, Emily McKenzie, Felix Nugee and the Dasgupta Review Team for their constructive review of an early version of this study. The authors thank the Inter-American Development Bank’s Allen Blackman, Gregory Watson, Annette Kilmer, Eirivelthon Lima, Carlos Salazar, Santiago Bucaram, Marisol Inurritegui, Pedro Martel, Fabiano Bastos, Jose Luiz Rossi and Aloisio de Melo for their valuable comments. Thanks also to Judson Ferreira Valentim, Mariane Crespolini dos Santos and Sergio De Zen for sharing their insights. The authors thank GLASSNET for providing a platform for engaging with GLASSNET scholars to enrich the study and identify linkages with related work from global to local scales.

Funders	Funder number
INFEWS	1739724
RMGEO Consultants Inc.
National Science Foundation
U.S. Geological Survey
Gordon and Betty Moore Foundation	5482, 9957
Gordon and Betty Moore Foundation
Inter-American Development Bank
Department for Environment, Food and Rural Affairs, UK Government
Conselho Nacional de Desenvolvimento Científico e Tecnológico	441703/2016-0PELD, 441463/2017-7
Conselho Nacional de Desenvolvimento Científico e Tecnológico

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 13 Climate Action
SDG 15 Life on Land

Keywords

Amazon tipping point
climate change
computable general equilibrium model
ecosystem services
integrated economic-environmental modeling
land use land cover change
natural capital

Access to Document

10.1088/1748-9326/aca3b8Licence: CC BY

Banerjee+et+al_2022_Environ._Res._Lett._10.1088_1748-9326_aca3b8Accepted author manuscript, 905 KBLicence: CC BY

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Cite this

Banerjee, O., Cicowiez, M., Macedo, M. N., Malek, Ž., Verburg, P. H., Goodwin, S., Vargas, R., Rattis, L., Bagstad, K. J., Brando, P. M., Coe, M. T., Neill, C., Marti, O. D., & Murillo, J. Á. (2022). Can we avert an Amazon tipping point? The economic and environmental costs. Environmental Research Letters, 17(12), 1-12. Article 125005. https://doi.org/10.1088/1748-9326/aca3b8

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title = "Can we avert an Amazon tipping point? The economic and environmental costs",

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.",

keywords = "Amazon tipping point, climate change, computable general equilibrium model, ecosystem services, integrated economic-environmental modeling, land use land cover change, natural capital",

author = "Onil Banerjee and Martin Cicowiez and Macedo, \{Marcia N.\} and {\v Z}iga Malek and Verburg, \{Peter H.\} and Sean Goodwin and Renato Vargas and Ludmila Rattis and Bagstad, \{Kenneth J.\} and Brando, \{Paulo M.\} and Coe, \{Michael T.\} and Christopher Neill and Marti, \{Octavio Damiani\} and Murillo, \{Josu{\'e} {\'A}vila\}",

note = "Funding Information: This study was commissioned by the UK{\textquoteright}s HM Treasury to inform the Dasgupta Review on the Economics of Biodiversity. The study was funded by the UK{\textquoteright}s Department for Environment, Food \& Rural Affairs and the Inter-American Development Bank. Support for Onil Banerjee{\textquoteright}s time was provided by the Inter-American Development Bank until March 2022 and by RMGEO Consultants Inc. thereafter. Support for Bagstad{\textquoteright}s time was provided by the USGS Land Change Science Program. Modeling of deforestation-climate feedbacks and analysis of regional climate risks for agricultural productivity, drought, and fire were supported by grants from the NSF (INFEWS \#1739724), CNPq (Nexus-Cerrado \#441463/2017-7; PELD-Tang \#441703/2016-0PELD), and the Gordon and Betty Moore Foundation (\#5482, \#9957). The authors thank Robert Marks, Emily McKenzie, Felix Nugee and the Dasgupta Review Team for their constructive review of an early version of this study. The authors thank the Inter-American Development Bank{\textquoteright}s Allen Blackman, Gregory Watson, Annette Kilmer, Eirivelthon Lima, Carlos Salazar, Santiago Bucaram, Marisol Inurritegui, Pedro Martel, Fabiano Bastos, Jose Luiz Rossi and Aloisio de Melo for their valuable comments. Thanks also to Judson Ferreira Valentim, Mariane Crespolini dos Santos and Sergio De Zen for sharing their insights. The authors thank GLASSNET for providing a platform for engaging with GLASSNET scholars to enrich the study and identify linkages with related work from global to local scales. Publisher Copyright: {\textcopyright} 2022 The Author(s). Published by IOP Publishing Ltd.",

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AU - Verburg, Peter H.

AU - Goodwin, Sean

AU - Vargas, Renato

AU - Rattis, Ludmila

AU - Bagstad, Kenneth J.

AU - Brando, Paulo M.

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N2 - 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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KW - computable general equilibrium model

KW - ecosystem services

KW - integrated economic-environmental modeling

KW - land use land cover change

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ER -

Can we avert an Amazon tipping point? The economic and environmental costs

Abstract

Bibliographical note

Funding

UN SDGs

Keywords

Access to Document

Persistent URL (handle)

Other files and links

Fingerprint

An Amazon Tipping Point: The Economic and Environmental Fallout

Land use modeling for the Integrated economic-environmental modeling + Ecosystem Services Modeling Platform

Cite this

Can we avert an Amazon tipping point? The economic and environmental costs

Abstract

Bibliographical note

Funding

UN SDGs

Keywords

Access to Document

Persistent URL (handle)

Other files and links

Fingerprint

Research output

An Amazon Tipping Point: The Economic and Environmental Fallout

Activities

Land use modeling for the Integrated economic-environmental modeling + Ecosystem Services Modeling Platform

Cite this