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Transfer efficiency of organic carbon in marine sediments

Author

Listed:
  • James A. Bradley

    (Queen Mary University of London
    GFZ German Research Center for Geosciences)

  • Dominik Hülse

    (University of California, Riverside
    Max-Planck-Institute for Meteorology)

  • Douglas E. LaRowe

    (University of Southern California)

  • Sandra Arndt

    (Université Libre de Bruxelles)

Abstract

Quantifying the organic carbon (OC) sink in marine sediments is crucial for assessing how the marine carbon cycle regulates Earth’s climate. However, burial efficiency (BE) – the commonly-used metric reporting the percentage of OC deposited on the seafloor that becomes buried (beyond an arbitrary and often unspecified reference depth) – is loosely defined, misleading, and inconsistent. Here, we use a global diagenetic model to highlight orders-of-magnitude differences in sediment ages at fixed sub-seafloor depths (and vice-versa), and vastly different BE’s depending on sediment depth or age horizons used to calculate BE. We propose using transfer efficiencies (Teff’s) for quantifying sediment OC burial: Teff is numerically equivalent to BE but requires precise specification of spatial or temporal references, and emphasizes that OC degradation continues beyond these horizons. Ultimately, quantifying OC burial with precise sediment-depth and sediment-age-resolved metrics will enable a more consistent and transferable assessment of OC fluxes through the Earth system.

Suggested Citation

  • James A. Bradley & Dominik Hülse & Douglas E. LaRowe & Sandra Arndt, 2022. "Transfer efficiency of organic carbon in marine sediments," Nature Communications, Nature, vol. 13(1), pages 1-8, December.
  • Handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-35112-9
    DOI: 10.1038/s41467-022-35112-9
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    References listed on IDEAS

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    1. Olivier Cartapanis & Daniele Bianchi & Samuel L. Jaccard & Eric D. Galbraith, 2016. "Global pulses of organic carbon burial in deep-sea sediments during glacial maxima," Nature Communications, Nature, vol. 7(1), pages 1-7, April.
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    Cited by:

    1. Shi, Wen & Chen, Ao & Xie, Xiang, 2024. "Generating and validating cluster sampling matrices for model-free factor screening," European Journal of Operational Research, Elsevier, vol. 313(1), pages 241-257.

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