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Placing an upper limit on cryptic marine sulphur cycling

Nature volume 513, pages 530–533 (2014)Cite this article

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Abstract

A quantitative understanding of sources and sinks of fixed nitrogen in low-oxygen waters is required to explain the role of oxygen-minimum zones (OMZs) in controlling the fixed nitrogen inventory of the global ocean. Apparent imbalances in geochemical nitrogen budgets1 have spurred numerous studies to measure the contributions of heterotrophic and autotrophic N2-producing metabolisms (denitrification and anaerobic ammonia oxidation, respectively)2,3. Recently, ‘cryptic’ sulphur cycling was proposed as a partial solution to the fundamental biogeochemical problem of closing marine fixed-nitrogen budgets in intensely oxygen-deficient regions4. The degree to which the cryptic sulphur cycle can fuel a loss of fixed nitrogen in the modern ocean requires the quantification of sulphur recycling in OMZ settings. Here we provide a new constraint for OMZ sulphate reduction based on isotopic profiles of oxygen (18O/16O) and sulphur (33S/32S, 34S/32S) in seawater sulphate through oxygenated open-ocean and OMZ-bearing water columns. When coupled with observations and models of sulphate isotope dynamics and data-constrained model estimates of OMZ water-mass residence time, we find that previous estimates for sulphur-driven remineralization and loss of fixed nitrogen from the oceans are near the upper limit for what is possible given in situ sulphate isotope data.

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Figure 1: Establishing the isotopic composition of seawater sulphate.
Figure 2: Pore-water δ18O profiles.
Figure 3: Model predictions for the maximum allowable rate of sulphate reduction.

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Acknowledgements

We thank the Johnston laboratory, B. Chang, S. Wankel, D. Canfield and J. Granger for discussions and comments; D. Capone and M. Prokopenko for sample collection (all supported by National Science Foundation (NSF) Division of Ocean Sciences); and G. Henderson, W. Homoky and GEOTRACES. Funding was provided by Harvard University (D.T.J., A.M.), the Agouron Institute (D.T.J., B.C.G.) and the NSF EAR-I/F (D.T.J., E.B.) and NSF/OCE grant nos 1140404 (K.L.C.) and 0850905 (A.N.K.).

Author information

Authors and Affiliations

  1. Department of Earth and Planetary Sciences, Harvard University, Cambridge, 02138, Massachusetts, USA

    D. T. Johnston, A. Masterson & E. Beirne

  2. Department of Geosciences, Virginia Tech University, Blacksburg, 24061, Virginia, USA

    B. C. Gill

  3. Department of Environmental Earth System Science, Stanford University, Stanford, 94305, California, USA

    K. L. Casciotti

  4. Department of Earth, Ocean and Atmospheric Sciences, Florida State University, Tallahassee, 32306, Florida, USA

    A. N. Knapp

  5. Department of Earth Sciences, University of Southern California, Los Angeles, 90089, California, USA

    W. Berelson

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Contributions

D.T.J. and B.C.G. developed the project. W.B. and K.L.C. provided samples with the help of W. Homoky and G. Henderson (GEOTRACES). B.C.G., A.M. and E.B. performed the analyses. K.C. and A.N. performed nitrogen measurements with assistance from M. Forbes. D.T.J. and A.M. performed all modelling. All authors contributed to the writing of the manuscript.

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Correspondence to D. T. Johnston.

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Extended data figures and tables

Extended Data Figure 1 Test of whether changes in sulphate concentrations (although small) are related to salinity (here in practical salinity units).

A significant but weak correlation exists (P = 0.0075): see the text for discussion.

Extended Data Figure 2 Plot of sulphate concentrations against isotopic composition of sulphate.

The lack of a correlation is consistent with no overall heterogeneity in the ocean, especially as a function of sulphate reduction or sulphide oxidation, which would impart the characteristic 18O effect.

Extended Data Figure 3 Series of figures demonstrating the severity of oxygen deficiency at stations 11 and 25.

This is reflected both in nutrient budgets, tracked with N*, and in isotopes (in δ15N). Data are presented for both stations 11 and 25.

Extended Data Figure 4 Rank order box-and-whisker presentation of δ18Osulphate data for the ten water columns studied.

Data are discussed in the text. At the far right is a representation of all the data. Whiskers are 95% confidence intervals around a given median value (black bars at the centre of the boxes).

Extended Data Figure 5 Replotting of Fig. 3 with two different choices for δ18Os.c..

One estimate is based on s.e.m.; the other is based on the uncertainty over the entire global data set.

Extended Data Figure 6 Isotopic predictions for sulphate cycling as a function of water mass transit time.

The contour key shows various residence times of water within oxygen-deficient waters.

Extended Data Figure 7 The link between nitrogen and sulphur.

a, Prediction for sulphate reduction rates for a cryptic sulphur cycle containing 1 mmol m−2 d−1 sulphate reduction. b, Prediction for nitrate consumption rate. All biogeochemistry is arbitrarily distributed over a path length of 200 m. Units were chosen to be directly comparable to those in Table 1 of ref. 4.

Extended Data Table 1 Site locations
Full size table
Extended Data Table 2 Sulphur and oxygen isotope standards
Full size table

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Johnston, D., Gill, B., Masterson, A. et al. Placing an upper limit on cryptic marine sulphur cycling. Nature 513, 530–533 (2014). https://doi.org/10.1038/nature13698

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