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Future carbon emissions from global mangrove forest lossMangroves have among the highest carbon densities of any tropical forest. These ‘blue carbon’ ecosystems can store large amounts of carbon for long periods, and their protection reduces greenhouse gas emissions and supports climate change mitigation. Incorporating mangroves into Nationally Determined Contributions to the Paris Agreement and their valuation on carbon markets requires predicting how the management of different land-uses can prevent future greenhouse gas emissions and increase CO2 sequestration. We integrated comprehensive global datasets for carbon stocks, mangrove distribution, deforestation rates, and land-use change drivers into a predictive model of mangrove carbon emissions. We project emissions and foregone soil carbon sequestration potential under ‘business as usual’ rates of mangrove loss. Emissions from mangrove loss could reach 2391 Tg CO2 eq by the end of the century, or 3392 Tg CO2 eq when considering foregone soil carbon sequestration. The highest emissions were predicted in southeast and south Asia (West Coral Triangle, Sunda Shelf, and the Bay of Bengal) due to conversion to aquaculture or agriculture, followed by the Caribbean (Tropical Northwest Atlantic) due to clearing and erosion, and the Andaman coast (West Myanmar) and north Brazil due to erosion. Together, these six regions accounted for 90% of the total potential CO2 eq future emissions. Mangrove loss has been slowing, and global emissions could be more than halved if reduced loss rates remain in the future. Notably, the location of global emission hotspots was consistent with every dataset used to calculate deforestation rates or with alternative assumptions about carbon storage and emissions. Our results indicate the regions in need of policy actions to address emissions arising from mangrove loss and the drivers that could be managed to prevent them.
Document ID
20220000191
Acquisition Source
Goddard Space Flight Center
Document Type
Reprint (Version printed in journal)
Authors
Maria F. Adame ORCID
(Griffith University Brisbane, Queensland, Australia)
Rod M. Connolly ORCID
(Griffith University Brisbane, Queensland, Australia)
Mischa P. Turschwell ORCID
(Griffith University Brisbane, Queensland, Australia)
Catherine E. Lovelock ORCID
(University of Queensland Brisbane, Queensland, Australia)
Temilola Fatoyinbo ORCID
(Goddard Space Flight Center Greenbelt, Maryland, United States)
David Lagomasino ORCID
(East Carolina University Greenville, North Carolina, United States)
Liza A. Goldberg ORCID
(University of Maryland, College Park College Park, Maryland, United States)
Jordan Holdorf ORCID
(Griffith University Brisbane, Queensland, Australia)
Daniel A. Friess ORCID
(National University of Singapore Singapore, Singapore)
Sigit D. Sasmito ORCID
(Charles Darwin University Darwin, Northern Territory, Australia)
Jonathan Sanderman ORCID
(Woodwell Climate Research Center)
Michael Sievers ORCID
(Griffith University Brisbane, Queensland, Australia)
Christina Buelow ORCID
(Griffith University Brisbane, Queensland, Australia)
J. Boone Kauffman ORCID
(Oregon State University Corvallis, Oregon, United States)
Dale Bryan-Brown ORCID
(Griffith University Brisbane, Queensland, Australia)
Christopher J. Brown ORCID
(Griffith University Brisbane, Queensland, Australia)
Date Acquired
January 19, 2022
Publication Date
February 28, 2021
Publication Information
Publication: Global Change Biology
Publisher: Wiley
Volume: 27
Issue: 12
Issue Publication Date: June 1, 2021
ISSN: 1354-1013
e-ISSN: 1365-2486
Subject Category
Earth Resources And Remote Sensing
Funding Number(s)
WBS: 281945.02.03.08.46
PROJECT: Australian Research Council DP180103124
Distribution Limits
Public
Copyright
Portions of document may include copyright protected material.
Technical Review
External Peer Committee
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