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Future ocean hypercapnia driven by anthropogenic amplification of the natural CO2 cycle


High carbon dioxide (CO2) concentrations in sea-water (ocean hypercapnia) can induce neurological, physiological and behavioural deficiencies in marine animals1,2,3,4,5,6,7,8,9,10. Prediction of the onset and evolution of hypercapnia in the ocean requires a good understanding of annual variations in oceanic CO2 concentration, but there is a lack of relevant global observational data. Here we identify global ocean patterns of monthly variability in carbon concentration using observations that allow us to examine the evolution of surface-ocean CO2 levels over the entire annual cycle under increasing atmospheric CO2 concentrations. We predict that the present-day amplitude of the natural oscillations in oceanic CO2 concentration will be amplified by up to tenfold in some regions by 2100, if atmospheric CO2 concentrations continue to rise throughout this century (according to the RCP8.5 scenario of the Intergovernmental Panel on Climate Change)11. The findings from our data are broadly consistent with projections from Earth system climate models12,13,14,15. Our predicted amplification of the annual CO2 cycle displays distinct global patterns that may expose major fisheries in the Southern, Pacific and North Atlantic oceans to hypercapnia many decades earlier than is expected from average atmospheric CO2 concentrations. We suggest that these ocean ‘CO2 hotspots’ evolve as a combination of the strong seasonal dynamics of CO2 concentration and the long-term effective storage of anthropogenic CO2 in the oceans that lowers the buffer capacity in these regions, causing a nonlinear amplification of CO2 concentration over the annual cycle. The onset of ocean hypercapnia (when the partial pressure of CO2 in sea-water exceeds 1,000 micro-atmospheres) is forecast for atmospheric CO2 concentrations that exceed 650 parts per million, with hypercapnia expected in up to half the surface ocean by 2100, assuming a high-emissions scenario (RCP8.5)11. Such extensive ocean hypercapnia has detrimental implications for fisheries during the twenty-first century.

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Figure 1: Future amplification of ocean CO2 levels.
Figure 2: Increasing variability in future CO2 levels.
Figure 3: Example of future CO2 amplification and early-onset hypercapnia.
Figure 4: Global onset of future hypercapnia.


  1. Cripps, I. L., Munday, P. L. & McCormick, M. I. Ocean acidification affects prey detection by a predatory reef fish. PLoS ONE 6, e22736 (2011)

    CAS  ADS  Article  Google Scholar 

  2. Devine, B. M. & Munday, P. L. Habitat preferences of coral-associated fishes are altered by short-term exposure to elevated CO2 . Mar. Biol. 160, 1955–1962 (2013)

    CAS  Article  Google Scholar 

  3. Devine, B. M., Munday, P. L. & Jones, G. P. Homing ability of adult cardinalfish is affected by elevated carbon dioxide. Oecologia 168, 269–276 (2012)

    ADS  Article  Google Scholar 

  4. Dixson, D. L., Munday, P. L. & Jones, G. P. Ocean acidification disrupts the innate ability of fish to detect predator olfactory cues. Ecol. Lett. 13, 68–75 (2010)

    Article  Google Scholar 

  5. Ferrari, M. C. O. et al. Putting prey and predator into the CO2 equation – qualitative and quantitative effects of ocean acidification on predator–prey interactions. Ecol. Lett. 14, 1143–1148 (2011)

    Article  Google Scholar 

  6. Jutfelt, F., De Souza, K. B., Vuylsteke, A. & Sturve, J. Behavioural disturbances in a temperate fish exposed to sustained high-CO2 levels. PLoS ONE 8, e65825 (2013)

    CAS  ADS  Article  Google Scholar 

  7. Munday, P. L. et al. Ocean acidification impairs olfactory discrimination and homing ability of a marine fish. Proc. Natl Acad. Sci. USA 106, 1848–1852 (2009)

    CAS  ADS  Article  Google Scholar 

  8. Nilsson, G. E. et al. Near-future carbon dioxide levels alter fish behaviour by interfering with neurotransmitter function. Nature Clim. Change 2, 201–204 (2012)

    CAS  ADS  Article  Google Scholar 

  9. Spady, B. L., Watson, S. A., Chase, T. J. & Munday, P. L. Projected near-future CO2 levels increase activity and alter defensive behaviours in the tropical squid Idiosepius pygmaeus. Biol. Open 3, 1063–1070 (2014)

    Article  Google Scholar 

  10. Watson, S. A. et al. Marine mollusc predator-escape behaviour altered by near-future carbon dioxide levels. Proc. R. Soc. Lond. B 281, 20132377 (2014)

    Article  Google Scholar 

  11. Meinshausen, M. et al. The RCP greenhouse gas concentrations and their extensions from 1765 to 2300. Clim. Change 109, 213–241 (2011)

    CAS  ADS  Article  Google Scholar 

  12. Aumont, O. & Bopp, L. Globalizing results from ocean in situ iron fertilization studies. Glob. Biogeochem. Cycles 20, GB2017 (2006)

    ADS  Article  Google Scholar 

  13. Dunne, J. P. et al. GFDL’s ESM2 global coupled climate–carbon earth system models. Part II: carbon system formulation and baseline simulation characteristics. J. Clim. 26, 2247–2267 (2013)

    ADS  Article  Google Scholar 

  14. Jones, C. D. et al. The HadGEM2-ES implementation of CMIP5 centennial simulations. Geosci. Model Dev. 4, 543–570 (2011)

    ADS  Article  Google Scholar 

  15. Yang, D. & Saenko, O. A. Ocean heat transport and its projected change in CanESM2. J. Clim. 25, 8148–8163 (2012)

    ADS  Article  Google Scholar 

  16. Sasse, T. P., McNeil, B. I. & Abramowitz, G. A novel method for diagnosing seasonal to inter-annual surface ocean carbon dynamics from bottle data using neural networks. Biogeosciences 10, 4319–4340 (2013)

    ADS  Article  Google Scholar 

  17. Egleston, E. S., Sabine, C. L. & Morel, F. M. M. Revelle revisited: buffer factors that quantify the response of ocean chemistry to changes in DIC and alkalinity. Glob. Biogeochem. Cycles 24, GB1002 (2010)

    ADS  Article  Google Scholar 

  18. Orr, J. C. et al. Anthropogenic ocean acidification over the twenty-first century and its impact on calcifying organisms. Nature 437, 681–686 (2005)

    CAS  ADS  Article  Google Scholar 

  19. Sabine, C. L. et al. The oceanic sink for anthropogenic CO2 . Science 305, 367–371 (2004)

    CAS  ADS  Article  Google Scholar 

  20. Shaw, E. C., McNeil, B. I., Tilbrook, B., Matear, R. & Bates, M. L. Anthropogenic changes to seawater buffer capacity combined with natural reef metabolism induce extreme future coral reef CO2 conditions. Glob. Change Biol. 19, 1632–1641 (2013)

    ADS  Article  Google Scholar 

  21. Byrne, M., Lamare, M., Winter, D., Dworjanyn, S. A. & Uthicke, S. The stunting effect of a high CO2 ocean on calcification and development in sea urchin larvae, a synthesis from the tropics to the poles. Phil. Trans. R. Soc. Lond. B 368, 20120439 (2013)

    Article  Google Scholar 

  22. Fabry, V. J., Seibel, B. A., Feely, R. & Orr, J. C. Impacts of ocean acidification on marine fauna and ecosystem processes. ICES J. Mar. Sci. 65, 414–432 (2008)

    CAS  Article  Google Scholar 

  23. Maas, A. E., Wishner, K. F. & Seibel, B. A. The metabolic response of pteropods to acidification reflects natural CO2-exposure in oxygen minimum zones. Biogeosciences 9, 747–757 (2012)

    CAS  ADS  Article  Google Scholar 

  24. Food and Agriculture Organization of the United Nations. The State of World Fisheries and Aquaculture 2014 9–12 (FAO, 2014)

  25. Volff, J.-N. Genome evolution and biodiversity in teleost fish. Heredity 94, 280–294 (2013)

    Article  Google Scholar 

  26. Ishii, M. et al. Air–sea CO2 flux in the Pacific Ocean for the period 1990–2009. Biogeosciences 11, 709–734 (2014)

    ADS  Article  Google Scholar 

  27. Lenton, A. et al. Sea–air CO2 fluxes in the Southern Ocean for the period 1990–2009. Biogeosciences 10, 4037–4054 (2013)

    ADS  Article  Google Scholar 

  28. Sarma, V. V. S. S. et al. Sea–air CO2 fluxes in the Indian Ocean between 1990 and 2009. Biogeosciences 10, 7035–7052 (2013)

    CAS  ADS  Article  Google Scholar 

  29. Schuster, U. et al. Trends in North Atlantic sea-surface fCO2 from 1990 to 2006. Deep Sea Res. II 56, 620–629 (2009)

    CAS  ADS  Article  Google Scholar 

  30. Shaw, E. C., McNeil, B. I. & Tilbrook, B. Impacts of ocean acidification in naturally variable coral reef flat ecosystems. J. Geophys. Res. Oceans 117, C03038 (2012)

    ADS  Article  Google Scholar 

  31. Taylor, K. E., Stouffer, R. J. & Meehl, G. A. An overview of CMIP5 and the experiment design. Bull. Am. Meteorol. Soc. 93, 485–498 (2012)

    ADS  Article  Google Scholar 

  32. Key, R. M. et al. A global ocean carbon climatology: results from global data analysis project (GLODAP). Glob. Biogeochem. Cycles 18, GB4031 (2004)

    ADS  Article  Google Scholar 

  33. Kohonen, T. Self-organizing Maps 3rd edn (Springer, 2001)

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We thank R. Matear and A. Lenton from the CSIRO for conversations, performing initial model runs and analysis of CMIP5 model output for use here. We acknowledge the World Climate Research Programme’s Working Group on Coupled Modelling, which is responsible for CMIP, and we thank the climate modelling groups (Hadley Centre, IPSL, Can and GFDL) for producing their models and making the output openly accessible. For CMIP, the US Department of Energy’s Program for Climate Model Diagnosis and Intercomparison provides coordinating support, and led the development of software infrastructure in partnership with the Global Organization for Earth System Science Portals. We acknowledge support from the Australian Research Council discovery grant DP110104955.

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Authors and Affiliations



B.I.M. conceived and designed the project, interpreted the results and wrote the paper. T.P.S. helped design the project and carried out all of the numerical and data analysis, and contributed important interpretations, discussions and revisions to the final manuscript.

Corresponding author

Correspondence to Ben I. McNeil.

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The authors declare no competing financial interests.

Extended data figures and tables

Extended Data Figure 1 Ocean Revelle factor.

Distribution of the mean Revelle or ‘buffer’ factor in the surface ocean in 2000, determined from our study.

Source data

Extended Data Figure 2 Quantifying biases in the SOMLO approach.

Bias in concentrations (expressed as a percentage) in 2100 due to using steady-state assumptions in the SOMLO analysis. Positive (negative) values indicate that SOMLO over-estimates (under-estimates) .

Extended Data Figure 3 Future CO2 amplification as predicted by climate models.

ad, CO2 amplification factors by the year 2100 as predicted by four ESMs: HadGEM2-ES (a), IPSL-CM5A-MR (b), CanESM2 (c) and GFDL-ESM2M (d); see Extended Data Table 1 for model details.

Extended Data Figure 4 Comparison of present-day natural CO2 variability as predicted by model and data.

Taylor diagram comparing the ability of ESMs to capture the dynamics and magnitude of the annual cycle of CO2 with our data-based approach. Here, the open circle on the x axis represents the standard deviation in our data-based predictions, while the grey contour lines represent the residual standard error between the ESMs and our data-based predictions.

Extended Data Figure 5 Interannual variability of future CO2 amplification.

CO2 amplification factors within the HadGEM2 model for each year from 2097 to 2100.

Extended Data Figure 6 Nonlinearity of future CO2 distributions between SOMLO and models.

Surface distribution (normalized such that the mean level across the whole surface ocean is shifted to zero) as predicted by SOMLO and two climate models (CanESM2 and HadGEM2-ES), highlighting the change in distribution between 2006 and 2100. The nonlinearity is evidenced by ‘bulging’ in the 2100 distributions for positive , relative to those for negative .

Extended Data Table 1 Main characteristics of the four ESMs used in this study

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McNeil, B., Sasse, T. Future ocean hypercapnia driven by anthropogenic amplification of the natural CO2 cycle. Nature 529, 383–386 (2016).

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