Articles | Volume 22, issue 20
https://doi.org/10.5194/bg-22-5975-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-22-5975-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Improving marine sediment carbon stock estimates: the role of dry bulk density and predictor adjustments
School of Civil Engineering, University College Dublin, Dublin, Ireland
Markus Diesing
Geological Survey of Norway, P.O. Box 6315, Torgarden, 7491 Trondheim, Norway
Agri-Food and Biosciences Institute Northern Ireland, Fisheries and Aquatic Ecosystems Branch, Newforge Lane, Belfast, BT9 5PX, UK
William Ross Hunter
Agri-Food and Biosciences Institute Northern Ireland, Fisheries and Aquatic Ecosystems Branch, Newforge Lane, Belfast, BT9 5PX, UK
Anthony Grey
School of Chemical Science, Dublin City University, Dublin, Ireland
Brian P. Kelleher
School of Chemical Science, Dublin City University, Dublin, Ireland
Mark Coughlan
School of Earth Sciences, University College Dublin, Dublin, Ireland
SFI Research Centre for Applied Geosciences (iCRAG), O'Brien Centre for Science East, University College Dublin, Dublin, Ireland
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Markus Diesing, Marija Sciberras, Terje Thorsnes, Lilja Bjarnadottir, and Øyvind Moe
EGUsphere, https://doi.org/10.5194/egusphere-2025-2159, https://doi.org/10.5194/egusphere-2025-2159, 2025
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Dragging fishing nets across the seafloor might lead to the release of carbon dioxide, potentially leading to negative consequences such as the ocean turning sour and the planet heating up even more quickly. Protecting areas of the seabed from such human activities could help reduce negative consequences, but which places should be protected? We present a new method to map areas of the seabed offshore Norway which are most at risk and could be considered for protection.
Christian Lønborg, Cátia Carreira, Gwenaël Abril, Susana Agustí, Valentina Amaral, Agneta Andersson, Javier Arístegui, Punyasloke Bhadury, Mariana B. Bif, Alberto V. Borges, Steven Bouillon, Maria Ll. Calleja, Luiz C. Cotovicz Jr., Stefano Cozzi, Maryló Doval, Carlos M. Duarte, Bradley Eyre, Cédric G. Fichot, E. Elena García-Martín, Alexandra Garzon-Garcia, Michele Giani, Rafael Gonçalves-Araujo, Renee Gruber, Dennis A. Hansell, Fuminori Hashihama, Ding He, Johnna M. Holding, William R. Hunter, J. Severino P. Ibánhez, Valeria Ibello, Shan Jiang, Guebuem Kim, Katja Klun, Piotr Kowalczuk, Atsushi Kubo, Choon-Weng Lee, Cláudia B. Lopes, Federica Maggioni, Paolo Magni, Celia Marrase, Patrick Martin, S. Leigh McCallister, Roisin McCallum, Patricia M. Medeiros, Xosé Anxelu G. Morán, Frank E. Muller-Karger, Allison Myers-Pigg, Marit Norli, Joanne M. Oakes, Helena Osterholz, Hyekyung Park, Maria Lund Paulsen, Judith A. Rosentreter, Jeff D. Ross, Digna Rueda-Roa, Chiara Santinelli, Yuan Shen, Eva Teira, Tinkara Tinta, Guenther Uher, Masahide Wakita, Nicholas Ward, Kenta Watanabe, Yu Xin, Youhei Yamashita, Liyang Yang, Jacob Yeo, Huamao Yuan, Qiang Zheng, and Xosé Antón Álvarez-Salgado
Earth Syst. Sci. Data, 16, 1107–1119, https://doi.org/10.5194/essd-16-1107-2024, https://doi.org/10.5194/essd-16-1107-2024, 2024
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In this paper, we present the first edition of a global database compiling previously published and unpublished measurements of dissolved organic matter (DOM) collected in coastal waters (CoastDOM v1). Overall, the CoastDOM v1 dataset will be useful to identify global spatial and temporal patterns and to facilitate reuse in studies aimed at better characterizing local biogeochemical processes and identifying a baseline for modelling future changes in coastal waters.
Amin Shoari Nejad, Andrew C. Parnell, Alice Greene, Peter Thorne, Brian P. Kelleher, Robert J. N. Devoy, and Gerard McCarthy
Ocean Sci., 18, 511–522, https://doi.org/10.5194/os-18-511-2022, https://doi.org/10.5194/os-18-511-2022, 2022
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We have collated multiple sources of tide gauge data for Dublin Port, and subsequently corrected them for bias. We have then shown that these corrected mean sea level measurements agree with nearby tide gauges to a far higher degree than the raw data. A longer-term comparison with Brest and Newlyn also indicates overall agreement. Our final adjusted dataset estimated the rate of sea level rise to be 1.1 mm/yr between 1953 and 2016 and 7 mm/yr between 1997 and 2016 at Dublin Port.
Markus Diesing, Terje Thorsnes, and Lilja Rún Bjarnadóttir
Biogeosciences, 18, 2139–2160, https://doi.org/10.5194/bg-18-2139-2021, https://doi.org/10.5194/bg-18-2139-2021, 2021
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The upper 10 cm of the seafloor of the North Sea and Skagerrak contain 231×106 t of carbon in organic form. The Norwegian Trough, the deepest sedimentary basin in the studied area, stands out as a zone of strong organic carbon accumulation with rates on par with neighbouring fjords. Conversely, large parts of the North Sea are characterised by rapid organic carbon degradation and negligible accumulation. This dual character is likely typical for continental shelf sediments worldwide.
Markus Diesing
Earth Syst. Sci. Data, 12, 3367–3381, https://doi.org/10.5194/essd-12-3367-2020, https://doi.org/10.5194/essd-12-3367-2020, 2020
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A new digital map of the sediment types covering the bottom of the ocean has been created. Direct observations of the seafloor sediments are few and far apart. Therefore, machine learning was used to fill those gaps between observations. This was possible because known relationships between sediment types and the environment in which they form (e.g. water depth, temperature, and salt content) could be exploited. The results are expected to provide important information for marine research.
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Short summary
Marine sediments store carbon and are critical in the global carbon cycle, but data gaps reduce the accuracy of carbon stock estimates. This study improves estimates in the Irish Sea by refining key data inputs. Using machine learning and bias adjustments, the new model suggests previous estimates overestimated carbon stocks by 31.4 %. The findings highlight the need for more accurate sediment measurements to guide environmental policies and better protect carbon storage in marine ecosystems.
Marine sediments store carbon and are critical in the global carbon cycle, but data gaps reduce...
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