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  • A global map of mangrove forest soil carbon at 30 m spatial resolution

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    Author(s)
    Sanderman, Jonathan
    Hengl, Tomislav
    Fiske, Greg
    Solvik, Kylen
    Adame, Maria Fernanda
    Benson, Lisa
    Bukoski, Jacob J
    Carnell, Paul
    Cifuentes-Jara, Miguel
    Donato, Daniel
    Duncan, Clare
    Eid, Ebrahem M
    zu Ermgassen, Philine
    Lewis, Carolyn J Ewers
    Macreadie, Peter I
    Glass, Leah
    Gress, Selena
    Jardine, Sunny L
    Jones, Trevor G
    Nsombo, Eugene Ndemem
    Rahman, Md Mizanur
    Sanders, Christian J
    Spalding, Mark
    Landis, Emily
    Griffith University Author(s)
    Adame Vivanco, Fernanda
    Year published
    2018
    Metadata
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    Abstract
    With the growing recognition that effective action on climate change will require a combination of emissions reductions and carbon sequestration, protecting, enhancing and restoring natural carbon sinks have become political priorities. Mangrove forests are considered some of the most carbon-dense ecosystems in the world with most of the carbon stored in the soil. In order for mangrove forests to be included in climate mitigation efforts, knowledge of the spatial distribution of mangrove soil carbon stocks are critical. Current global estimates do not capture enough of the finer scale variability that would be required to ...
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    With the growing recognition that effective action on climate change will require a combination of emissions reductions and carbon sequestration, protecting, enhancing and restoring natural carbon sinks have become political priorities. Mangrove forests are considered some of the most carbon-dense ecosystems in the world with most of the carbon stored in the soil. In order for mangrove forests to be included in climate mitigation efforts, knowledge of the spatial distribution of mangrove soil carbon stocks are critical. Current global estimates do not capture enough of the finer scale variability that would be required to inform local decisions on siting protection and restoration projects. To close this knowledge gap, we have compiled a large georeferenced database of mangrove soil carbon measurements and developed a novel machine-learning based statistical model of the distribution of carbon density using spatially comprehensive data at a 30 m resolution. This model, which included a prior estimate of soil carbon from the global SoilGrids 250 m model, was able to capture 63% of the vertical and horizontal variability in soil organic carbon density (RMSE of 10.9 kg m−3). Of the local variables, total suspended sediment load and Landsat imagery were the most important variable explaining soil carbon density. Projecting this model across the global mangrove forest distribution for the year 2000 yielded an estimate of 6.4 Pg C for the top meter of soil with an 86–729 Mg C ha−1 range across all pixels. By utilizing remotely-sensed mangrove forest cover change data, loss of soil carbon due to mangrove habitat loss between 2000 and 2015 was 30–122 Tg C with >75% of this loss attributable to Indonesia, Malaysia and Myanmar. The resulting map products from this work are intended to serve nations seeking to include mangrove habitats in payment-for- ecosystem services projects and in designing effective mangrove conservation strategies.
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    Journal Title
    Environmental Research Letters
    Volume
    13
    Issue
    5
    DOI
    https://doi.org/10.1088/1748-9326/aabe1c
    Copyright Statement
    © 2018 The Author(s). Published by IOP Publishing Ltd. Original content from this work may be used under the terms of the Creative Commons Attribution 3.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.
    Subject
    Other environmental sciences not elsewhere classified
    Publication URI
    http://hdl.handle.net/10072/380044
    Collection
    • Journal articles

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