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Soil carbon in the world’s tidal marshes

Tania L. Maxwell Orcid Logo, Mark D. Spalding Orcid Logo, Daniel A. Friess, Nicholas J. Murray Orcid Logo, Kerrylee Rogers Orcid Logo, Andre S. Rovai Orcid Logo, Lindsey S. Smart, Lukas Weilguny Orcid Logo, Maria Fernanda Adame Orcid Logo, Janine B. Adams Orcid Logo, William E. N. Austin, Margareth S. Copertino, Grace M. Cott, Micheli Duarte de Paula Costa Orcid Logo, James R. Holmquist Orcid Logo, Cai Ladd Orcid Logo, Catherine E. Lovelock Orcid Logo, Marvin Ludwig Orcid Logo, Monica M. Moritsch, Alejandro Navarro, Jacqueline L. Raw Orcid Logo, Ana-Carolina Ruiz-Fernández Orcid Logo, Oscar Serrano, Craig Smeaton Orcid Logo, Marijn Van de Broek, Lisamarie Windham-Myers, Emily Landis, Thomas A. Worthington Orcid Logo

Nature Communications, Volume: 15, Start page: 10265

Swansea University Author: Cai Ladd Orcid Logo

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Abstract

Tidal marshes are threatened coastal ecosystems known for their capacity to store large amounts of carbon in their water-logged soils. Accurate quantification and mapping of global tidal marshes soil organic carbon (SOC) stocks is of considerable value to conservation efforts. Here, we used training...

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Published in: Nature Communications
ISSN: 2041-1723
Published: Springer Nature 2024
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URI: https://cronfa.swan.ac.uk/Record/cronfa68361
Abstract: Tidal marshes are threatened coastal ecosystems known for their capacity to store large amounts of carbon in their water-logged soils. Accurate quantification and mapping of global tidal marshes soil organic carbon (SOC) stocks is of considerable value to conservation efforts. Here, we used training data from 3710 unique locations, landscape-level environmental drivers and a global tidal marsh extent map to produce a global, spatially explicit map of SOC storage in tidal marshes at 30 m resolution. Here we show the total global SOC stock to 1 m to be 1.44 Pg C, with a third of this value stored in the United States of America. On average, SOC in tidal marshes’ 0–30 and 30–100 cm soil layers are estimated at 83.1 Mg C ha−1 (average predicted error 44.8 Mg C ha−1) and 185.3 Mg C ha−1 (average predicted error 105.7 Mg C ha−1), respectively.
College: Faculty of Science and Engineering
Funders: We thank Daniele Baisero, Thomas Ball, and Alison Eyres for methodological help. This project benefited from funding from the Bezos Earth Fund and other donors supporting the Nature Conservancy (T.A.W., E.L., and M.D.S.). LH Pérez-Bernal provided assistance in the geochemical analysis of sediment cores from Mexico. This work was performed using resources provided by the Cambridge Service for Data-Driven Discovery (CSD3) operated by the University of Cambridge Research Computing Service (www.csd3.cam.ac.uk), provided by Dell EMC and Intel using Tier-2 funding from the Engineering and Physical Sciences Research Council (capital grant EP/T022159/1), and DiRAC funding from the Science and Technology Facilities Council (www.dirac.ac.uk). Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.
Start Page: 10265