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

Jonathan Sanderman*, Tomislav Hengl, Greg Fiske, Kylen Solvik, Maria Fernanda Adame, Lisa Benson, Jacob J. Bukoski, Paul Carnell, Miguel Cifuentes-Jara, Daniel Donato, Clare Duncan, Ebrahem M. Eid, Philine Zu Ermgassen, Carolyn J. Ewers Lewis, Peter I. Macreadie, Leah Glass, Selena Gress, Sunny L. Jardine, Trevor G. Jones, Eugéne Ndemem NsomboMd Mizanur Rahman, Christian J. Sanders, Mark Spalding, Emily Landis

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

260 Citations (Scopus)

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 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.

Original languageEnglish
Article number055002
JournalEnvironmental Research Letters
Volume13
Issue number5
DOIs
Publication statusPublished - May 2018

Keywords

  • blue carbon
  • carbon sequestration
  • land use change
  • machine learning

Fingerprint

Dive into the research topics of 'A global map of mangrove forest soil carbon at 30 m spatial resolution'. Together they form a unique fingerprint.

Cite this