Mangrove forests store high densities of organic carbon, which, when coupled with high rates of deforestation, means that mangroves have the potential to contribute substantially to carbon emissions. Consequently, mangroves are strong candidates for inclusion in nationally determined contributions (NDCs) to the United Nations Framework Convention on Climate Change (UNFCCC), and payments for ecosystem services (PES) programmes that financially incentivize the conservation of forested carbon stocks. This study quantifies annual mangrove carbon stocks from 2000 to 2012 at the global, national and sub-national levels, and global carbon emissions resulting from deforestation over the same time period. Globally, mangroves stored 4.19 Pg of carbon in 2012, with Indonesia, Brazil, Malaysia and Papua New Guinea accounting for more than 50% of the global stock. 2.96 Pg of the global carbon stock is contained within the soil and 1.23 Pg in the living biomass. Two percent of global mangrove carbon was lost between 2000 and 2012, equivalent to a maximum potential of 316,996,250 t of CO2 emissions.
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IPCC. Climate Change 2014: Impacts, Adaptation and Vulnerability: Regional Aspects (Cambridge Univ. Press, Cambridge, UK, 2014).
Donato, D. C. et al. Mangroves among the most carbon-rich forests in the tropics. Nat. Geosci. 4, 293–297 (2011).
Hamilton, S. E. Assessing the role of commercial aquaculture in displacing mangrove forest. Bull. Mar. Sci. 89, 585–601 (2013).
Hamilton, S. E. & Casey, D. Creation of a high spatio-temporal resolution global database of continuous mangrove forest cover for the 21st century (CGMFC-21). Glob. Ecol. Biogeogr. 25, 729–738 (2016).
van Bochove, J.-W., Sullivan, E. & Nakamura, T. The Importance of Mangroves to People: A Call to Action (UNEP World Conservation Monitoring Centre, Cambridge, UK, 2014).
Richards, D. R. & Friess, D. A. Rates and drivers of mangrove deforestation in Southeast Asia, 2000–2012. Proc. Natl Acad. Sci. USA 113, 344–349 (2016).
Hamilton, S. E. & Lovette, J. Ecuador’s mangrove forest carbon stocks: a spatiotemporal analysis of living carbon holdings and their depletion since the advent of commercial aquaculture. PLoS One 10, e0118880 (2015).
Lovelock, C. E. et al. The vulnerability of Indo-Pacific mangrove forests to sea-level rise. Nature 526, 559–563 (2015).
Pendleton, L. et al. Estimating global 'blue carbon' emissions from conversion and degradation of vegetated coastal ecosystems. PLoS One 7, e43542 (2012).
Murdiyarso, D. et al. The potential of Indonesian mangrove forests for global climate change mitigation. Nat. Clim. Change 5, 1089–1092 (2015).
UNFCCC. Adoption of the Paris Agreement, Proposal by the President, Draft decision -/CP.21, report no. FCCC/CP/2015/L.9/Rev.1 (United Nations, Paris, France, 2015).
Hiraishi, T. et al. 2013 Supplement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories: Wetlands (IPCC, Geneva, Switzerland, 2014).
Wunder, S. Revisiting the concept of payments for environmental services. Ecol. Econ. 117, 234–243 (2015).
Mcleod, E. et al. A blueprint for blue carbon: toward an improved understanding of the role of vegetated coastal habitats in sequestering CO2. Front. Ecol. Environ. 9, 552–560 (2011).
Sutton-Grier, A. E. & Moore, A. Leveraging carbon services of coastal ecosystems for habitat protection and restoration. Coast. Manag. 44, 259–277 (2016).
Thompson, B. S., Clubbe, C. P., Primavera, J. H., Curnick, D. & Koldewey, H. J. Locally assessing the economic viability of blue carbon: a case study from Panay Island, the Philippines. Ecosyst. Serv. 8, 128–140 (2014).
Friess, D. A. & Webb, E. L. Variability in mangrove change estimates and implications for the assessment of ecosystem service provision. Glob. Ecol. Biogeogr. 23, 715–725 (2014).
Harris, N. L. et al. Baseline map of carbon emissions from deforestation in tropical regions. Science 336, 1573–1576 (2012).
Donato, D. C. Perspective and parsimony in forest carbon management. Carbon Manag. 3, 227–230 (2012).
IPCC. The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (Cambridge Univ. Press, New York, USA, 2013).
Siikamäki, J., Sanchirico, J. N. & Jardine, S. L. Global economic potential for reducing carbon dioxide emissions from mangrove loss. Proc. Natl Acad. Sci. 109, 14369–14374 (2012).
Lovelock, C. E., Fourqurean, J. W. & Morris, J. T. CO2 emissions from coastal wetland transitions to other land uses: tidal marshes, mangrove forests, and seagrass beds. Front. Mar. Sci 4, https://doi.org/10.3389/fmars.2017.00143 (2017).
Datta, D., Chattopadhyay, R. & Guha, P. Community based mangrove management: a review on status and sustainability. J. Environ. Manag. 107, 84–95 (2012).
US EPA. Energy and the Environment: Greenhouse Gas Equivalencies Calculator https://www.epa.gov/energy/greenhouse-gas-equivalencies-calculator (2016).
Breithaupt, J. L., Smoak, J. M., Smith, T. J., Sanders, C. J. & Hoare, A. Organic carbon burial rates in mangrove sediments: strengthening the global budget. Glob. Biogeochem. Cycles 26, GB3011 (2012).
Chmura, G. L., Anisfeld, S. C., Cahoon, D. R. & Lynch, J. C. Global carbon sequestration in tidal, saline wetland soils. Glob. Biogeochem. Cycles 17, 1111 (2003).
Jardine, S. L. & Siikamäki, J. V. A global predictive model of carbon in mangrove soils. Environ. Res. Lett. 9, 104013 (2014).
Atwood, T. B. et al. Global patterns in mangrove soil carbon stocks and losses. Nat. Clim. Change 7, 523–528 (2017).
Tong, L.-I., Chang, C.-W., Jin, S.-E. & Saminathan, R. Quantifying uncertainty of emission estimates in National Greenhouse Gas Inventories using bootstrap confidence intervals. Atmos. Environ. 56, 80–87 (2012).
IPCC. 2006 IPCC Guidelines for National Greenhouse Gas Inventories (IPCC, New York, USA, 2006).
Harris, N. Global Forest Watch Climate: Summary of Methods and Data (2016); http://climate.globalforestwatch.org/downloads/about/technical-note/wri15_TECH_GFW-Climate-v3.pdf
Angelsen, A. Moving Ahead with REDD: Issues, Options and Implications (Center for International Forestry Research, Bogor, Indonesia, 2008).
Friess, D. A. et al. Policy challenges and approaches for the conservation of mangrove forests in Southeast Asia. Conserv. Biol. 30, 933–949 (2016).
Huettner, M., Leemans, R., Kok, K. & Ebeling, J. A comparison of baseline methodologies for ‘Reducing Emissions from Deforestation and Degradation’. Carbon Balance Manag. 4, 4 (2009).
Sloan, S. & Pelletier, J. How accurately may we project tropical forest-cover change? A validation of a forward-looking baseline for REDD. Glob. Environ. Change 22, 440–453 (2012).
Hansen, M. C. et al. High-resolution global maps of 21st-century forest cover change. Science 342, 850–853 (2013).
Giri, C. et al. Status and distribution of mangrove forests of the world using Earth observation satellite data. Glob. Ecol. Biogeogr. 20, 154–159 (2011).
Olson, D. M. et al. Terrestrial ecoregions of the world: a new map of life on Earth. BioScience 51, 933–938 (2001).
Twilley, R. R., Chen, R. H. & Hargis, T. Carbon sinks in mangroves and their implications to carbon budget of tropical coastal ecosystems. Water Air Soil Pollut. 64, 265–288 (1992).
Hutchison, J., Manica, A., Swetnam, R., Balmford, A. & Spalding, M. Predicting global patterns in mangrove forest biomass. Conserv. Lett. 7, 233–240 (2014).
Hamilton, S. E., Lovette, J. P., Borbor-Cordova, M. J. & Millones, M. The carbon holdings of northern Ecuador’s mangrove forests. Ann. Am. Assoc. Geogr. 107, 54–71 (2017).
Saenger, P. & Snedaker, S. C. Pantropical trends in mangrove aboveground biomass and annual litterfall. Oecologia 96, 293–299 (1993).
Hijmans, R. J., Cameron, S. E., Parra, J. L., Jones, P. G. & Jarvis, A. Very high resolution interpolated climate surfaces for global land areas. Int. J. Climatol. 25, 1965–1978 (2005).
Kauffman, J. B. & Donato, D. Protocols for the Measurement, Monitoring and Reporting of Structure, Biomass and Carbon Stocks in Mangrove Forests (Center for International Forestry Research, Bogor, Indonesia, 2012).
Komiyama, A., Sasitorn, P. & Shogo, K. Common allometric equations for estimating the tree weight of mangroves. J. Trop. Ecol. 21, 471–477 (2005).
Komiyama, A., Ong, J. E. & Poungparn, S. Allometry, biomass, and productivity of mangrove forests: a review. Aquat. Bot. 89, 128–137 (2008).
Kauffman, J. B., Heider, C., Cole, T. G., Dwire, K. A. & Donato, D. C. Ecosystem carbon stocks of Micronesian mangrove forests. Wetlands 31, 343–352 (2011).
Alongi, D. M. Carbon sequestration in mangrove forests. Carbon Manag. 3, 313–322 (2012).
Caruana, R. & Niculescu-Mizil, A. An empirical comparison of supervised learning algorithms. Proc. 23rd Int. Conf. Machine Learning 161–168 (2006).
This study benefited from access to some pre-existing remote sensing and modelling data sets, particularly the Global Forest Cover data set from the University of Maryland.
The authors declare no competing interests.
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Supplementary Figures 1–2, Error and Uncertainty Analysis, Supplementary Discussion, Supplementary Tables 3–5 and Supplementary References
Extends Table 1 in the manuscript to all 105 mangrove-holding level one administrative units globally
Extends Table 2 in the manuscript to all 752 mangrove-holding level one administrative units globally
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Hamilton, S.E., Friess, D.A. Global carbon stocks and potential emissions due to mangrove deforestation from 2000 to 2012. Nature Clim Change 8, 240–244 (2018). https://doi.org/10.1038/s41558-018-0090-4
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