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Minimal East Antarctic Ice Sheet retreat onto land during the past eight million years

Naturevolume 558pages284–287 (2018)Cite this article

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Abstract

The East Antarctic Ice Sheet (EAIS) is the largest potential contributor to sea-level rise. However, efforts to predict the future evolution of the EAIS are hindered by uncertainty in how it responded to past warm periods, for example, during the Pliocene epoch (5.3 to 2.6 million years ago), when atmospheric carbon dioxide concentrations were last higher than 400 parts per million. Geological evidence indicates that some marine-based portions of the EAIS and the West Antarctic Ice Sheet retreated during parts of the Pliocene1,2, but it remains unclear whether ice grounded above sea level also experienced retreat. This uncertainty persists because global sea-level estimates for the Pliocene have large uncertainties and cannot be used to rule out substantial terrestrial ice loss3, and also because direct geological evidence bearing on past ice retreat on land is lacking. Here we show that land-based sectors of the EAIS that drain into the Ross Sea have been stable throughout the past eight million years. We base this conclusion on the extremely low concentrations of cosmogenic10Be and26Al isotopes found in quartz sand extracted from a land-proximal marine sediment core. This sediment had been eroded from the continent, and its low levels of cosmogenic nuclides indicate that it experienced only minimal exposure to cosmic radiation, suggesting that the sediment source regions were covered in ice. These findings indicate that atmospheric warming during the past eight million years was insufficient to cause widespread or long-lasting meltback of the EAIS margin onto land. We suggest that variations in Antarctic ice volume in response to the range of global temperatures experienced over this period—up to 2–3 degrees Celsius above preindustrial temperatures4, corresponding to future scenarios involving carbon dioxide concentrations of between 400 and 500 parts per million—were instead driven mostly by the retreat of marine ice margins, in agreement with the latest models5,6.

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Fig. 1: Locations of the AND-1B core in the Ross Sea and ice-flow lines to the core site, along with simulated ice-sheet retreat during the Pliocene.
Fig. 2: AND-1B stratigraphy and cosmogenic nuclide samples.
Fig. 3: Cosmogenic nuclide abundances.
Fig. 4: AND-1B10Be record.

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References

  1. Naish, T. et al. Obliquity-paced Pliocene West Antarctic ice sheet oscillations.Nature458, 322–328 (2009).

    Article ADS PubMed CAS  Google Scholar 

  2. Cook, C. P. et al. Dynamic behaviour of the East Antarctic ice sheet during Pliocene warmth.Nat. Geosci.6, 765–769 (2013).

    Article ADS CAS  Google Scholar 

  3. Dutton, A. et al. Sea-level rise due to polar ice-sheet mass loss during past warm periods.Science349, aaa4019 (2015).

    Article PubMed CAS  Google Scholar 

  4. Haywood, A. M., Dowsett, H. J. & Dolan, A. M. Integrating geological archives and climate models for the mid-Pliocene warm period.Nat. Commun.7, 10646 (2016).

    Article ADS PubMed PubMed Central CAS  Google Scholar 

  5. DeConto, R. M. & Pollard, D. Contribution of Antarctica to past and future sea-level rise.Nature531, 591–597 (2016).

    Article ADS PubMed CAS  Google Scholar 

  6. Golledge, N. R. et al. Antarctic climate and ice-sheet configuration during the early Pliocene interglacial at 4.23 Ma.Clim. Past13, 959–975 (2017).

    Article  Google Scholar 

  7. Barrett, P. J. Resolving views on Antarctic Neogene glacial history—the Sirius debate.Earth Env. Sci. Trans. R. Soc. Edinburgh104, 31–53 (2013).

    Article  Google Scholar 

  8. Pollard, D. & DeConto, R. M. Modelling West Antarctic ice sheet growth and collapse through the past five million years.Nature458, 329–332 (2009).

    Article ADS PubMed CAS  Google Scholar 

  9. Scherer, R. P., DeConto, R. M., Pollard, D. & Alley, R. B. Windblown Pliocene diatoms and East Antarctic Ice Sheet retreat.Nat. Commun.7, 12957 (2016).

    Article ADS PubMed PubMed Central CAS  Google Scholar 

  10. Kingslake, J., Ely, J. C., Das, I. & Bell, R. E. Widespread movement of meltwater onto and across Antarctic ice shelves.Nature544, 349–352 (2017).

    Article ADS PubMed CAS  Google Scholar 

  11. Raymo, M., Mitrovica, J. X., O’Leary, M. J., DeConto, R. & Hearty, P. Departures from eustasy in Pliocene sea-level records.Nat. Geosci.4, 328–332 (2011).

    Article ADS CAS  Google Scholar 

  12. Fretwell, P. et al. Bedmap2: improved ice bed, surface and thickness datasets for Antarctica.Cryosphere7, 375–393 (2013).

    Article ADS  Google Scholar 

  13. Bierman, P. R., Shakun, J. D., Corbett, L. B., Zimmerman, S. R. & Rood, D. H. A persistent and dynamic East Greenland Ice Sheet over the past 7.5 million years.Nature540, 256–260 (2016).

    Article ADS PubMed CAS  Google Scholar 

  14. Gosse, J. C. & Phillips, F. M. Terrestrial in situ cosmogenic nuclides: theory and application.Quat. Sci. Rev.20, 1475–1560 (2001).

    Article ADS  Google Scholar 

  15. Talarico, F. M., McKay, R. M., Powell, R. D., Sandroni, S. & Naish, T. Late Cenozoic oscillations of Antarctic ice sheets revealed by provenance of basement clasts and grain detrital modes in ANDRILL core AND-1B.Global Planet. Change96, 23–40 (2012).

    Article ADS  Google Scholar 

  16. Farmer, G. L. & Licht, K. J. Generation and fate of glacial sediments in the central Transantarctic Mountains based on radiogenic isotopes and implications for reconstructing past ice dynamics.Quat. Sci. Rev.150, 98–109 (2016).

    Article ADS  Google Scholar 

  17. Golledge, N. R. & Levy, R. H. Geometry and dynamics of an East Antarctic Ice Sheet outlet glacier, under past and present climates.J. Geophys. Res. Earth Surf.116, F03025 (2011).

    Article ADS  Google Scholar 

  18. Jones, R. S. et al. Cosmogenic nuclides constrain surface fluctuations of an East Antarctic outlet glacier since the Pliocene.Earth Planet. Sci. Lett.480, 75–86 (2017).

    Article ADS CAS  Google Scholar 

  19. Rohling, E. J. et al. Sea-level and deep-sea-temperature variability over the past 5.3 million years.Nature508, 477–482 (2014); corrigendum510, 432 (2014).

    Article ADS PubMed CAS  Google Scholar 

  20. Snyder, C. W. Evolution of global temperature over the past two million years.Nature538, 226–228 (2016).

    Article ADS PubMed CAS  Google Scholar 

  21. Balco, G., Stone, J. O. & Jennings, C. Dating Plio-Pleistocene glacial sediments using the cosmic-ray-produced radionuclides Be-10 and Al-26.Am. J. Sci.305, 1–41 (2005).

    Article ADS CAS  Google Scholar 

  22. Rovey, C. W. & Balco, G. Paleoclimatic interpretations of buried paleosols within the pre-Illinoian till sequence in northern Missouri, USA.Palaeogeogr. Palaeoclim. Palaeoecol.417, 44–56 (2015).

    Article ADS  Google Scholar 

  23. Gasson, E., DeConto, R. M., Pollard, D. & Levy, R. H. Dynamic Antarctic ice sheet during the early to mid-Miocene.Proc. Natl Acad. Sci. USA113, 3459–3464 (2016).

    Article ADS PubMed PubMed Central CAS  Google Scholar 

  24. Winkelmann, R., Levermann, A., Ridgwell, A. & Caldeira, K. Combustion of available fossil fuel resources sufficient to eliminate the Antarctic Ice Sheet.Sci. Adv.1, e1500589 (2015).

    Article ADS PubMed PubMed Central CAS  Google Scholar 

  25. Gulick, S. P. S. et al. Initiation and long-term instability of the East Antarctic Ice Sheet.Nature552, 225–229 (2017).

    Article ADS PubMed CAS  Google Scholar 

  26. Hay, C. et al. The sea-level fingerprints of ice-sheet collapse during interglacial periods.Quat. Sci. Rev.87, 60–69 (2014).

    Article ADS  Google Scholar 

  27. Wilson, G. S. et al. Neogene tectonic and climatic evolution of the Western Ross Sea, Antarctica—chronology of events from the AND-1B drill hole.Global Planet. Change96, 189–203 (2012).

    Article ADS  Google Scholar 

  28. Zachos, J., Pagani, M., Sloan, L., Thomas, E. & Billups, K. Trends, rhythms, and aberrations in global climate 65 Ma to present.Science292, 686–693 (2001).

    Article ADS PubMed CAS  Google Scholar 

  29. Lüthi, D. et al. High-resolution carbon dioxide concentration record 650,000–800,000 years before present.Nature453, 379–382 (2008).

    Article ADS PubMed CAS  Google Scholar 

  30. Foster, G. L., Royer, D. L. & Lunt, D. J. Future climate forcing potentially without precedent in the last 420 million years.Nature Comm. 8, 14845 (2017).

  31. Krissek, L. et al. Sedimentology and stratigraphy of the AND-1B core, ANDRILL McMurdo Ice Shelf Project, Antarctica.Terra Antarctica14, 185–222 (2007).

    Google Scholar 

  32. Corbett, L. B., Bierman, P. R. & Rood, D. H. An approach for optimizing in situ cosmogenic 10Be sample preparation.Quat. Geochronol.33, 24–34 (2016).

    Article  Google Scholar 

  33. Nishiizumi, K. et al. Absolute calibration of10Be AMS standards.Nucl. Instrum. Methods Phys. Res. B258, 403–413 (2007).

    Article ADS CAS  Google Scholar 

  34. Nishiizumi, K. Preparation of26Al AMS standards.Nucl. Instrum. Methods Phys. Res. B223–224, 388–392 (2004).

    Article ADS CAS  Google Scholar 

  35. Nuzzo, R. Statistical errors.Nature506, 150–152 (2014).

    Article ADS PubMed CAS  Google Scholar 

  36. Kruschke, J. K. Bayesian estimation supersedes the t test.J. Exp. Psychol.142, 573–603 (2013).

    Article  Google Scholar 

  37. Kruschke, J. K.Doing Bayesian Data Analysis: A Tutorial with R, JAGS and Stan (Elsevier, London, 2015).

    MATH  Google Scholar 

  38. Gelman, A., Carlin, J. B., Stern, H. S. & Rubin, D. B.Bayesian Data Analysis (Chapman & Hall/CRC, London, 2004).

    MATH  Google Scholar 

  39. Currie, L. A. The measurement of environmental levels of rare gas nuclides and the treatment of very low-level counting data.IEEE Trans. Nucl. Sci.19, 119–126 (1972).

    Article ADS CAS  Google Scholar 

  40. Kruschke, J. K.Informed priors for Bayesian comparison of two groupshttp://doingbayesiandataanalysis.blogspot.com/2015/04/informed-priors-for-bayesian-comparison.html (2015).

  41. R Core Development Team.R: a language and environment for statistical computerhttp://www.R-project.org/ (2016).

  42. Kruschke, J. K. & Meredith, M.BEST: Bayesian estimation supersedes the t-testhttps://cran.r-project.org/web/packages/BEST/index.html (2015).

  43. Plummer, M. JAGS: a program for analysis of Bayesian graphical models using Gibbs sampling. InProc. 3rd Int. Workshop on Distributed Statistical Computing (eds Hornik, K. et al.) (2003).

  44. Plummer, M., Best, N., Cowles, K. & Vines, K. CODA: convergence diagnosis and output analysis for MCMC.R News6, 7–11 (2006).

    Google Scholar 

  45. Gelman, A. & Rubin, D. B. Inference from iterative simulation using multiple sequences.Stat. Sci.7, 457–472 (1992).

    Article MATH  Google Scholar 

  46. Korschinek, G. et al. A new value for the half-life of10Be by heavy-ion elastic recoil detection and liquid scintillation counting.Nucl. Instrum. Methods Phys. Res. B268, 187–191 (2010).

    Article ADS CAS  Google Scholar 

  47. Norris, T. L., Gancarz, A. J., Rokop, D. J. & Thomas, K. W. Half-life of26Al.J. Geophys. Res. Solid Earth88, B331–B333 (1983).

    Article ADS  Google Scholar 

  48. Jamieson, S. S. R., Sugden, D. E. & Hulton, N. R. J. The evolution of the subglacial landscape of Antarctica.Earth Planet. Sci. Lett.293, 1–27 (2010).

    Article ADS CAS  Google Scholar 

  49. Thomson, S. N., Reiners, P. W., Hemming, S. R. & Gehrels, G. E. The contribution of glacial erosion to shaping the hidden landscape of East Antarctica.Nat. Geosci.6, 203–207 (2013).

    Article ADS CAS  Google Scholar 

  50. Wellman, P. & Tingey, R. J. Glaciation, erosion and uplift over part of East Antarctica.Nature291, 142–144 (1981).

    Article ADS  Google Scholar 

  51. Bo, S. et al. The Gamburtsev mountains and the origin and early evolution of the Antarctic Ice Sheet.Nature459, 690–693 (2009).

    Article ADS PubMed CAS  Google Scholar 

  52. Young, D. A. et al. A dynamic early East Antarctic Ice Sheet suggested by ice-covered fjord landscapes.Nature474, 72–75 (2011).

    Article ADS PubMed CAS  Google Scholar 

  53. Heisinger, B. et al. Production of selected cosmogenic radionuclides by muons.Geochim. Cosmochim. Acta66, A558 (2002).

    Google Scholar 

  54. Balco, G., Stone, J. O., Lifton, N. A. & Dunai, T. J. A complete and easily accessible means of calculating surface exposure ages or erosion rates from10Be and26Al measurements.Quat. Geochronol.3, 174–195 (2008).

    Article  Google Scholar 

  55. Golledge, N. R., Levy, R. H., McKay, R. M. & Naish, T. R. East Antarctic ice sheet most vulnerable to Weddell Sea warming.Geophys. Res. Lett.44, 2343–2351 (2017).

    ADS  Google Scholar 

  56. Peltier, W. R. Global glacial isostasy and the surface of the ice-age Earth: the ICE-5G (VM2) model and GRACE.Annu. Rev. Earth Planet. Sci.32, 111–149 (2004).

    Article ADS CAS  Google Scholar 

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Acknowledgements

We thank the Antarctic Research Facility for AND-1B samples, and J. X. Mitrovica for his help in performing the glacial isostatic adjustment modelling. This research was supported by National Science Foundation (NSF) grant ARC-1023191 (to P.R.B. and L.B.C.); Boston College start-up funds (to J.D.S.); Vermont Established Program to Stimulate Competitive Research (EPSCoR) grants EPS-1101317 and NSF OIA 1556770 (to K.U. and D.M.R.); NSF grant EAR-1153689 (to M.W.C.); and the New Zealand Ministry of Business Innovation and Employment contract C05X1001 (to T.N. and N.R.G.). This is Lawrence Livermore National Laboratory project LLNL-JRNL-735619.

Reviewer information

Nature thanks J. Gosse, E. Gasson, J. Willenbring and the other anonymous reviewer(s) for their contribution to the peer review of this work.

Author information

Authors and Affiliations

  1. Department of Earth and Environmental Sciences, Boston College, Chestnut Hill, MA, USA

    Jeremy D. Shakun & Carling C. Hay

  2. Department of Geology and Rubenstein School of the Environment and Natural Resources, University of Vermont, Burlington, VT, USA

    Lee B. Corbett & Paul R. Bierman

  3. Civil and Environmental Engineering, University of Vermont, Burlington, VT, USA

    Kristen Underwood & Donna M. Rizzo

  4. Center for Accelerator Mass Spectrometry, Lawrence Livermore National Laboratory, Livermore, CA, USA

    Susan R. Zimmerman

  5. Department of Earth, Atmospheric, and Planetary Sciences, Purdue University, West Lafayette, IN, USA

    Marc W. Caffee

  6. Department of Physics and Astronomy, Purdue University, West Lafayette, IN, USA

    Marc W. Caffee

  7. Antarctic Research Centre, Victoria University of Wellington, Wellington, New Zealand

    Tim Naish & Nicholas R. Golledge

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Contributions

J.D.S. and P.R.B. conceived the study. L.B.C. performed laboratory work. K.U. and D.M.R. conducted statistical analyses. S.R.Z. and M.W.C. made isotopic measurements. T.N. and N.R.G. contributed to data interpretation. C.C.H. performed glacial isostatic adjustment simulations. All authors contributed to the preparation of the manuscript.

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Correspondence toJeremy D. Shakun.

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Extended data figures and tables

Extended Data Fig. 1 Modelled patterns of erosion.

ad, Simulated erosion potential under the Antarctic Ice Sheet, calculated from modelled driving stress and basal velocity fields for several uniform (atmosphere and ocean) warming scenarios of: 4 °C (a), 8 °C (b), 12 °C (c) and 15 °C (d)55. The location of the AND-1B core is shown by the yellow dot. We note that erosive zones tend to extend towards the continental interior with warming. dT, temperature anomaly from present; dV, ice-volume anomaly from present, in sea-level equivalent (s.l.e.).

Extended Data Fig. 2 Glacial isostatic adjustment following ice retreat.

ad, Antarctic land above sea level (yellow) 0 kyr (a), 5 kyr (b), 10 kyr (c), and 15 kyr (d) after a near-instantaneous (1-kyr) collapse of all marine-based ice-sheet sectors, in two different models of mantle viscosity26. Model 1 is from ref.56, and model 2 (our model) has the following parameters: lithosphere thickness, 96 km; upper-mantle viscosity, 5 × 1020 Pa s−1; and lower-mantle viscosity, 1022 Pa s−1. The location of the AND-1B core is shown by the star.

Extended Data Fig. 3 Nuclide abundances in AND-1B samples versus blank populations.

a,b, Cumulative exceedance probabilities of measured (that is, not blank-corrected)10Be (a) and26Al (b) nuclide abundances in AND-1B samples (blue) and in all blanks run by the same operator in the same low-level fume hood (red), with 1σ uncertainties. These plots display the fraction of measurements that exceed a given nuclide abundance. Note that probabilities are generally higher for the samples than the blanks; in other words, a random draw from the samples is more likely to be above a random draw from the blanks, suggesting that they are separable populations.

Extended Data Fig. 4 AND-1B decay-corrected26Al concentrations.

Shaded intervals surrounding the blue line show 1σ uncertainties, while shaded intervals not surrounding the blue line show the possible range of decay-corrected concentrations in samples that are below the detection limit. The dashed black line simulates the26Al concentration in non-eroding material at 2,000 metres above sea level (m asl) that was originally saturated at 14 Ma and subsequently decayed under cold-based, non-erosive ice. The fact that several AND-1B samples have higher concentrations than those in this extreme scenario (which is the most favourable to having nuclides persist to the present) suggests that the AND-1B nuclides were produced after the expansion of the EAIS in the mid-Miocene.

Extended Data Fig. 5 Modelled concentrations of cosmogenic nuclides for various durations of interglacial exposure and glacial erosion rates.

ad, Simulated10Be (a,b) and26Al (c,d) concentrations in material sourced from sea level and from 2,000 m asl in Antarctica as a function of the fraction of time for which land is exposed, during 40-kyr glacial cycles. (Results are nearly identical if the cycles are instead 100-kyr long.) Erosion rates were assumed to be 0 m per Myr during ice-free conditions, on the basis of geologic evidence for negligible late Cenozoic erosion in ice-free areas of the TAMs9,10. Black arrows next to the scale bars show the range of decay-corrected nuclide concentrations in AND-1B samples. The model was initialized with zero nuclides at 8 Ma (representative of conditions suggested by AND-1B sample H); the model also assumes instantaneous transport of eroded sediment to the ocean with no mixing, and continuous radioactive decay. Concentrations shown are the Pliocene (5 Ma to 3 Ma) average. Comparison of these simulations with AND-1B nuclide concentrations suggests that land exposure in sediment source regions was probably quite limited in duration or extent through the Plio-Pleistocene.

Extended Data Fig. 6 Modelling a mid-Pliocene exposure of bedrock.

ad, Each panel shows actual AND-1B decay-corrected10Be concentrations with 1σ uncertainty (green), as well as simulated10Be concentrations assuming a single 10-kyr (a), 50-kyr (b), 100-kyr (c) and 200-kyr (d) exposure of a bedrock column in the mid-Pliocene. The exposure event was chosen to start at 3.6 Ma and extend for up to 200 kyr in duration on the basis of the presence of a 60-m-thick diatomite unit in the AND-1B core, thought to reflect warm interglacial conditions from 3.6 Ma to 3.4 Ma1. Simulated records are driven by production at sea level (grey) or at 2,000 m asl (black), and are subjected to continuous radioactive decay and continuous erosion at rates of 0 m per Myr (solid lines), 20 m per Myr (dashed lines), and 100 m per Myr (dotted lines). The model assumes that the sediment source was initially devoid of nuclides and that sediments are transported instantaneously to the sea floor. The synthetic time series have been binned to the same resolution as the AND-1B data.

Extended Data Fig. 7 Modelling a mid-Pliocene exposure event with eroded bedrock mixed through a deformable bed.

The figure shows AND-1B decay-corrected10Be concentrations with 1σ uncertainties (green). It also depicts simulated10Be concentrations, assuming a single exposure event from 3.6 Ma to 3.4 Ma and routing of eroded bedrock through a well mixed deformable bed, for various bed thicknesses and erosion rates. Material eroded from the bedrock profile is instantaneously mixed throughout the deformable bed in each time step, and an equal amount of material is removed from the bed, keeping its thickness constant. Sediment mixing in the deformable bed dilutes the surface10Be signal of the exposure event but extends its longevity through time in comparison with the bedrock simulations shown in Extended Data Fig. 6. Simulated records are driven by production at sea level, and subjected to continuous radioactive decay and continuous erosion. The model assumes that the bedrock and deformable bed were initially devoid of nuclides and that sediments eroded from the deformable bed are transported instantaneously to the sea floor. The synthetic time series have been binned to the same resolution as the AND-1B data.

Extended Data Fig. 8 Conceptual diagram showing the outcomes of Bayesian one-groupt-tests and their interpretation.

a, Nuclides are credibly present above background: that is, the sample value is greater than the mean of the blanks (defined at the mode of the posterior distribution), and the region of uncertainty surrounding the sample value fully excludes the 90% credible interval (C.I.) on the posterior distribution of the mean of the blanks. The grey shaded regions give the uncertainty range in the sample nuclide concentration.b, Nuclides are not credibly present above background: the sample value is less than or equal to the blank mean.c, Nuclides are not credibly present above background: although the sample value is greater than the blank mean, the region of uncertainty surrounding the sample value does not fully exclude the 90% C.I.

Extended Data Table 1 Comparison of nuclide abundances in sample populations and procedural blank populations
Extended Data Table 2 Comparison of nuclide abundances in individual samples and procedural blanks

Supplementary information

Supplementary Data

This file contains AND-1B sediment processing data, AND-1B cosmogenic nuclide data and process blank cosmogenic nuclide data.

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Shakun, J.D., Corbett, L.B., Bierman, P.R.et al. Minimal East Antarctic Ice Sheet retreat onto land during the past eight million years.Nature558, 284–287 (2018). https://doi.org/10.1038/s41586-018-0155-6

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