Stability of Marine Organic Matter Respiration Stoichiometry

T. Tanioka, K. Matsumoto

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

The amount of oxygen consumed during organic matter remineralization critically depends on how much organic carbon is remineralized per unit dissolved oxygen respired (respiratory quotient, RQ) but the global distribution and the mechanisms that control RQ are not well understood. Here we estimate RQ in the surface ocean by using two independent methods, one using satellite-derived macromolecular composition of phytoplankton and another using objectively gridded nutrient data. Both methods yield mean RQ of ~0.7 with small spatial variability consistent with previous estimates. This pattern is likely to be a result of phytoplankton protein content universally exceeding those of carbohydrates and lipids. At face value, the relative stability of RQ suggests that the remineralization stoichiometry will not affect the ongoing deoxygenation of the world ocean. However, the possibility remains that RQ may increase in the future (e.g., organic matter becoming more carbohydrate-dominated) and thus ameliorate deoxygenation.

Original languageEnglish (US)
Article numbere2019GL085564
JournalGeophysical Research Letters
Volume47
Issue number1
DOIs
StatePublished - Jan 16 2020

Bibliographical note

Funding Information:
This research was supported by a grant from the US National Science Foundation (OCE-1827948). TT acknowledges support from University of Minnesota Doctoral Dissertation Fellowship. KM was supported by a Leverhulme Trust Visiting Professorship and sabbatical support at the University of Oxford. Numerical computation was carried out using resources at the University of Minnesota Supercomputing Institute. We thank Pearce Buchanan for fruitful discussions. Satellite-derived phytoplankton macromolecule data are available from Roy (). Ocean tracer data used to calculate vertical gradients are available from World Ocean Atlas 2013 (https://www.nodc.noaa.gov/OC5/woa13/woa13data.html). Phytoplankton macromolecule data set used in Figure is available from the Macromolecular database (https://doi.org/10.1371/journal.pone.0155977.s001) (Finkel et al.,). Timeseries data of phytoplankton macromolecules used in Figure?S8 are provided in Table?S6 and at the Zenodo repository (https://doi.org/10.5281/zenodo.3588626) (Tanioka & Matsumoto,).

Funding Information:
This research was supported by a grant from the US National Science Foundation OCE‐1827948. TT acknowledges support from University of Minnesota Doctoral Dissertation Fellowship. KM was supported by a Leverhulme Trust Visiting Professorship and sabbatical support at the University of Oxford. Numerical computation was carried out using resources at the University of Minnesota Supercomputing Institute. We thank Pearce Buchanan for fruitful discussions. Satellite‐derived phytoplankton macromolecule data are available from Roy ( ). Ocean tracer data used to calculate vertical gradients are available from World Ocean Atlas 2013 ( https://www.nodc.noaa.gov/OC5/woa13/woa13data.html ). Phytoplankton macromolecule data set used in Figure is available from the Macromolecular database ( https://doi.org/10.1371/journal.pone.0155977.s001 ) (Finkel et al., ). Timeseries data of phytoplankton macromolecules used in Figure S8 are provided in Table S6 and at the Zenodo repository ( https://doi.org/10.5281/zenodo.3588626 ) (Tanioka & Matsumoto, ). ( )

Publisher Copyright:
©2020. American Geophysical Union. All Rights Reserved.

Keywords

  • Redfield ratio
  • elemental stoichiometry
  • marine phytoplankton
  • organic matter respiration
  • oxygen cycle

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