Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Changing carbon-to-nitrogen ratios of organic-matter export under ocean acidification

Abstract

Ocean acidification (OA) will affect marine biotas from the organism to the ecosystem level. Yet, the consequences for the biological carbon pump and thereby the oceanic sink for atmospheric CO2 are still unclear. Here we show that OA considerably alters the C/N ratio of organic-matter export (C/Nexport), a key factor determining efficiency of the biological pump. By synthesizing sediment-trap data from in situ mesocosm studies in different marine biomes, we find distinct but highly variable impacts of OA on C/Nexport, reaching up to a 20% increase/decrease under partial pressure of CO2 (\(p_{{\rm{CO}}_{2}}\)) conditions projected for 2100. These changes are driven by \(p_{{\rm{CO}}_{2}}\) effects on a variety of plankton taxa and corresponding shifts in food-web structure. Notably, our findings suggest a pivotal role of heterotrophic processes in controlling the response of C/Nexport to OA, thus contradicting the paradigm of primary producers as the principal driver of biogeochemical responses to ocean change.

This is a preview of subscription content, access via your institution

Relevant articles

Open Access articles citing this article.

Access options

Buy article

Get time limited or full article access on ReadCube.

$32.00

All prices are NET prices.

Fig. 1: Mesocosm experiment locations and design.
Fig. 2: Impact of simulated OA on C/N ratios of sinking particulate matter in the different in situ mesocosm studies.
Fig. 3: The role of plankton communities in shaping OA impacts on the C/N ratio of organic-matter export.
Fig. 4: Change in C/N of sinking particles and its response to OA.

Data availability

The raw data of the mesocosm studies are archived in the World Data Centre MARE/PANGAEA (www.pangaea.de) and can be found using the keyword ‘KOSMOS’. In addition, the data supporting the findings of this study are available from the corresponding author upon reasonable request.

References

  1. Kwon, E. Y., Primeau, F. & Sarmiento, J. L. The impact of remineralization depth on the air–sea carbon balance. Nat. Geosci. 2, 630–635 (2009).

    Article  CAS  Google Scholar 

  2. Volk, T. & Hoffert, M. I. in The Carbon Cycle and Atmospheric CO2: Natural Variations Archean to Present Vol. 32 (eds Sundquist, E. T. & Broeker, W. S.) 99–110 (American Geophysical Union, 1985).

  3. Passow, U. & Carlson, C. A. The biological pump in a high CO2 world. Mar. Ecol. Prog. Ser. 470, 249–271 (2012).

    Article  CAS  Google Scholar 

  4. Martiny, A. C. et al. Strong latitudinal patterns in the elemental ratios of marine plankton and organic matter. Nat. Geosci. 6, 279–283 (2013).

    Article  CAS  Google Scholar 

  5. DeVries, T. New directions for ocean nutrients. Nat. Geosci. 11, 15–16 (2018).

    Article  CAS  Google Scholar 

  6. Redfield, A. in James Johnstone Memorial Volume (ed. Daniel, R. J.) 177–192 (University Press of Liverpool, 1934).

  7. Kroeker, K. J., Kordas, R. L., Crim, R. N. & Singh, G. G. Meta-analysis reveals negative yet variable effects of ocean acidification on marine organisms. Ecol. Lett. 13, 1419–1434 (2010).

    Article  Google Scholar 

  8. Riebesell, U. & Tortell, P. D. in Ocean Acidification (eds Gattuso, J. P. & Hansson, L.) 99–121 (Oxford Univ. Press, 2011).

  9. Boyd, P. W. & Newton, P. P. Does planktonic community structure determine downward particulate organic carbon flux in different oceanic provinces? Deep Sea Res. I 46, 63–91 (1999).

    Article  CAS  Google Scholar 

  10. Stange, P. et al. Ocean acidification-induced restructuring of the plankton food web can influence the degradation of sinking particles. Front. Mar. Sci. https://doi.org/10.3389/fmars.2018.00140 (2018).

  11. Engel, A. et al. Impact of CO2 enrichment on organic matter dynamics during nutrient induced coastal phytoplankton blooms. J. Plankton Res. 36, 641–657 (2014).

    Article  CAS  Google Scholar 

  12. Riebesell, U. et al. Technical note: a mobile sea-going mesocosm system—new opportunities for ocean change research. Biogeosciences 10, 1835–1847 (2013).

    Article  Google Scholar 

  13. Sswat, M. et al. Food web changes under ocean acidification promote herring larvae survival. Nat. Ecol. Evol. https://doi.org/10.1038/s41559-018-0514-6 (2018).

  14. Riebesell, U. et al. Enhanced biological carbon consumption in a high CO2 ocean. Nature 450, 545–548 (2007).

    Article  CAS  Google Scholar 

  15. Finkel, Z. V. et al. Phytoplankton in a changing world: cell size and elemental stoichiometry. J. Plankton Res. 32, 119–137 (2010).

    Article  CAS  Google Scholar 

  16. van de Waal, D. B., Verschoor, A. M., Verspagen, J. M. H., van Donk, E. & Huisman, J. Climate-driven changes in the ecological stoichiometry of aquatic ecosystems. Front. Ecol. Environ. 8, 145–152 (2010).

    Article  Google Scholar 

  17. Tagliabue, A., Bopp, L. & Gehlen, M. The response of marine carbon and nutrient cycles to ocean acidification: large uncertainties related to phytoplankton physiological assumptions. Glob. Biogeochem. Cycle https://doi.org/10.1029/2010gb003929 (2011).

  18. Thomas, H., Ittekkot, V., Osterroht, C. & Schneider, B. Preferential recycling of nutrients—the ocean’s way to increase new production and to pass nutrient limitation? Limnol. Oceanogr. 44, 1999–2004 (1999).

    Article  CAS  Google Scholar 

  19. Schneider, B., Schlitzer, R., Fischer, G. & Nothig, E. M. Depth-dependent elemental compositions of particulate organic matter (POM) in the ocean. Glob. Biogeochem. Cycle https://doi.org/10.1029/2002gb001871 (2003).

  20. Cripps, G., Flynn, K. J. & Lindeque, P. K. Ocean acidification affects the phyto-zoo plankton trophic transfer efficiency. PLoS ONE https://doi.org/10.1371/journal.pone.0151739 (2016).

  21. Thor, P. & Oliva, E. O. Ocean acidification elicits different energetic responses in an Arctic and a boreal population of the copepod Pseudocalanus acuspes. Mar. Biol. 162, 799–807 (2015).

    Article  CAS  Google Scholar 

  22. Endres, S., Galgani, L., Riebesell, U., Schulz, K. G. & Engel, A. Stimulated bacterial growth under elevated \(p_{{\rm{CO}}_{2}}\): results from an off-shore mesocosm study. PLoS ONE 9, e99228 (2014).

    Article  Google Scholar 

  23. Piontek, J. et al. Response of bacterioplankton activity in an Arctic fjord system to elevated \(p_{{\rm{CO}}_{2}}\): results from a mesocosm perturbation study. Biogeosciences 10, 297–314 (2013).

    Article  Google Scholar 

  24. Bopp, L. et al. Multiple stressors of ocean ecosystems in the 21st century: projections with CMIP5 models. Biogeosciences 10, 6225–6245 (2013).

    Article  Google Scholar 

  25. Taucher, J. & Oschlies, A. Can we predict the direction of marine primary production change under global warming? Geophys. Res. Lett. https://doi.org/10.1029/2010gl045934 (2011).

  26. Schneider, B., Engel, A. & Schlitzer, R. Effects of depth- and CO2-dependent C:N ratios of particulate organic matter (POM) on the marine carbon cycle. Glob. Biogeochem. Cycle https://doi.org/10.1029/2003gb002184 (2004).

  27. Oschlies, A., Schulz, K. G., Riebesell, U. & Schmittner, A. Simulated 21st century’s increase in oceanic suboxia by CO2-enhanced biotic carbon export. Glob. Biogeochem. Cycle https://doi.org/10.1029/2007gb003147 (2008).

  28. Broecker, W. S. & Henderson, G. M. The sequence of events surrounding Termination II and their implications for the cause of glacial–interglacial CO2 changes. Paleoceanography 13, 352–364 (1998).

    Article  Google Scholar 

  29. Broecker, W. S. Ocean chemistry during glacial time. Geochim. Cosmochim. Acta 46, 1689–1705 (1982).

    Article  CAS  Google Scholar 

  30. Boxhammer, T., Bach, L. T., Czerny, J. & Riebesell, U. Technical note: sampling and processing of mesocosm sediment trap material for quantitative biogeochemical analysis. Biogeosciences 13, 2849–2858 (2016).

    Article  Google Scholar 

  31. Sharp, J. H. Improved analysis for “particulate” organic carbon and nitrogen from seawater. Limnol. Oceanogr. 19, 984–989 (1974).

    Article  CAS  Google Scholar 

  32. IPCC Climate Change 2013: The Physical Science Basis (eds Stocker, T. F. et al.) (Cambridge Univ. Press, 2013).

  33. Hedges, L. V., Gurevitch, J. & Curtis, P. S. The meta-analysis of response ratios in experimental ecology. Ecology 80, 1150–1156 (1999).

    Article  Google Scholar 

  34. Schartau, M., Landry, M. R. & Armstrong, R. A. Density estimation of plankton size spectra: a reanalysis of IronEx II data. J. Plankton Res. 32, 1167–1184 (2010).

    Article  Google Scholar 

  35. Mackey, M. D., Mackey, D. J., Higgins, H. W. & Wright, S. W. CHEMTAX—a program for estimating class abundances from chemical markers: application to HPLC measurements of phytoplankton. Mar. Ecol. Prog. Ser. 144, 265–283 (1996).

    Article  CAS  Google Scholar 

  36. Utermöhl, V. H. Neue Wege in der quantitativen Erfassung des Planktons. (Mit besondere Beriicksichtigung des Ultraplanktons). Verh. Internat. Verein. Theor. Angew. Limnol. 5, 567–595 (1931).

    Google Scholar 

  37. Bach, L. T., Riebesell, U. & Schulz, K. G. Distinguishing between the effects of ocean acidification and ocean carbonation in the coccolithophore Emiliania huxleyi. Limnol. Oceanogr. 56, 2040–2050 (2011).

    Article  CAS  Google Scholar 

  38. Stange et al. Quantifying the time lag between organic matter production and export in the surface ocean: implications for estimates of export efficiency. Geophys. Res. Lett. 44, 268–276 (2017).

    Article  CAS  Google Scholar 

Download references

Acknowledgements

This study was supported by the German Federal Ministry of Science and Education (BMBF) in the framework of the projects BIOACID III (Biological Impacts of Ocean Acidification, FKZ 03F0728) and SOPRAN III (Surface Ocean Processes in the ANthropocene, FKZ 03F0662). Funding for the different mesocosm studies was also provided by the European Project on Ocean Acidification (EPOCA, grant no. 211384) from the European Community’s Seventh Framework Programme (FP7/2007–2013), the EU project MESOAQUA (grant no. 228224), as well as BIOACID II (FKZ 03F06550) and SOPRAN II (03F0611). Furthermore, we thank all participating scientists and technicians for their huge effort in realizing the different studies. We also thank the staff of the marine biological stations in the different study locations for providing logistics, technical assistance and support at all times. We also thank the captains and crews of R/V Viking Explorer, M/V Esperanza of Greenpeace, R/V Håkon Mosby (2011609), R/V Alkor (AL376, AL394, AL397, AL406, AL420), R/V Heincke (HE360), R/V Poseidon (POS463) and R/V Hesperides (29HE20140924) for support during transport, deployment and recovery of the mesocosm facilities.

Author information

Authors and Affiliations

Authors

Contributions

J.T., L.T.B. and M.S. conceived and designed the meta-analysis. J.T., T.B., P.S., L.T.B., A.J.P. and U.R. coordinated and implemented the mesocosm experiments, including data acquisition. J.T. was responsible for data analysis, data processing and visualization. J.T. wrote the manuscript, with editing by all co-authors.

Corresponding author

Correspondence to Jan Taucher.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 Impact of elevated CO2 concentrations on cumulative probability distributions of C:Nexport.

Shown are ambient conditions (blue) and ocean acidification (red) with shaded areas denoting standard deviation. Data used for analysis is identical with that in Fig. 2, but computed as cumulative values, thereby depicting the visual representation of a Kolmogorov-Smirnov test. Non-overlapping probability distributions indicate statistically significant differences in C:N between ambient and OA conditions. Note different scaling of x-axes due to large variations in baseline C:N among study regions.

Supplementary information

Supplementary Information

Supplementary Tables 1–4, and Figs. 1 and 2.

Reporting Summary

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Taucher, J., Boxhammer, T., Bach, L.T. et al. Changing carbon-to-nitrogen ratios of organic-matter export under ocean acidification. Nat. Clim. Chang. 11, 52–57 (2021). https://doi.org/10.1038/s41558-020-00915-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41558-020-00915-5

This article is cited by

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing