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.

Sensitivity of Holocene East Antarctic productivity to subdecadal variability set by sea ice

Abstract

Antarctic sea-ice extent, primary productivity and ocean circulation represent interconnected systems that form important components of the global carbon cycle. Subdecadal to centennial-scale variability can influence the characteristics and interactions of these systems, but observational records are too short to evaluate the impacts of this variability over longer timescales. Here, we use a 170-m-long sediment core collected from Integrated Ocean Drilling Program Site U1357B, offshore Adélie Land, East Antarctica to disentangle the impacts of sea ice and subdecadal climate variability on phytoplankton bloom frequency over the last ~11,400 years. We apply X-ray computed tomography, Ice Proxy for the Southern Ocean with 25 carbon atoms, diatom, physical property and geochemical analyses to the core, which contains an annually resolved, continuously laminated archive of phytoplankton bloom events. Bloom events occurred annually to biennially through most of the Holocene, but became less frequent (~2–7 years) at ~4.5 ka when coastal sea ice intensified. We propose that coastal sea-ice intensification subdued annual sea-ice break-out, causing an increased sensitivity of sea-ice dynamics to subdecadal climate modes, leading to a subdecadal frequency of bloom events. Our data suggest that projected loss of coastal sea ice will impact the influence of subdecadal variability on Antarctic margin primary productivity, altering food webs and carbon-cycling processes at seasonal timescales.

Your institute does not have access to this article

Access options

Buy article

Get time limited or full article access on ReadCube.

$32.00

All prices are NET prices.

Fig. 1: Area of study and example bloom event after sea-ice break-out.
Fig. 2: Simplified sediment deposition model for U1357B.
Fig. 3: Holocene proxy records in Adélie Land.
Fig. 4: EHA of greyscale data and XRF Si/Ti productivity proxies.

Data availability

The raw greyscale data, light laminae depths, light laminae sand percent, XRF silicon, XRF titanium and HBI diene data for IODP Site U1357B are available at https://doi.org/10.1594/PANGAEA.933380.

References

  1. Arrigo, K. R., van Dijken, G. & Long, M. Coastal Southern Ocean: a strong anthropogenic CO2 sink. Geophys. Res. Lett. 35, L21602 (2008).

    Article  Google Scholar 

  2. Rintoul, S. R. On the origin and influence of Adélie Land bottom water. Antarct. Res. Ser. 75, 151–171 (1998).

    Google Scholar 

  3. Moore, J. K. & Abbott, M. R. Phytoplankton chlorophyll distributions and primary production in the Southern Ocean. J. Geophys. Res. Ocean. 105, 28709–28722 (2000).

    Article  Google Scholar 

  4. Arrigo, K. R. & van Dijken, G. L. Phytoplankton dynamics within 37 Antarctic coastal polynya systems. J. Geophys. Res. C. 108, 1–18 (2003).

    Google Scholar 

  5. Comiso, J. C., McClain, C. R., Sullivan, C. W., Ryan, J. P. & Leonard, C. L. Coastal zone color scanner pigment concentrations in the Southern Ocean and relationships to geophysical surface features. J. Geophys. Res. 98, 2419–2451 (1993).

    Article  Google Scholar 

  6. Smith, W. O. & Nelson, D. M. Importance of ice edge phytoplankton production in the Southern Ocean. Bioscience 36, 251–257 (1986).

    Article  Google Scholar 

  7. Rigual-Hernández, A. S., Trull, T. W., Bray, S. G., Closset, I. & Armand, L. K. Seasonal dynamics in diatom and particulate export fluxes to the deep sea in the Australian sector of the southern Antarctic Zone. J. Mar. Syst. 142, 62–74 (2015).

    Article  Google Scholar 

  8. Yuan, X. ENSO-related impacts on Antarctic sea ice: a synthesis of phenomenon and mechanisms. Antarct. Sci. 16, 415–425 (2004).

    Article  Google Scholar 

  9. Nuncio, M. & Yuan, X. The influence of the Indian Ocean dipole on Antarctic sea ice. J. Clim. 28, 2682–2690 (2015).

    Article  Google Scholar 

  10. L’Heureux, M. L. & Thompson, D. W. J. Observed relationships between the El Niño Southern Oscillation and the extratropical zonal-mean circulation. J. Clim. 19, 276–287 (2006).

    Article  Google Scholar 

  11. Stammerjohn, S. E., Martinson, D. G., Smith, R. C., Yuan, X. & Rind, D. Trends in Antarctic annual sea ice retreat and advance and their relation to El Niño–Southern Oscillation and Southern Annular Mode variability. J. Geophys. Res. 113, C03S90 (2008).

    Article  Google Scholar 

  12. Fogt, R. L., Bromwich, D. H. & Hines, K. M. Understanding the SAM influence on the South Pacific ENSO teleconnection. Clim. Dyn. 36, 1555–1576 (2011).

    Article  Google Scholar 

  13. Saba, G. K. et al. Winter and spring controls on the summer food web of the coastal West Antarctic Peninsula. Nat. Commun. 5, 1–8 (2014).

    Google Scholar 

  14. Arrigo, K. R. & Van Dijken, G. L. Annual changes in sea-ice, chlorophyll a, and primary production in the Ross Sea, Antarctica. Deep. Res. Part II Top. Stud. Oceanogr. 51, 117–138 (2004).

    Article  Google Scholar 

  15. Venables, H. J., Clarke, A. & Meredith, M. P. Wintertime controls on summer stratification and productivity at the western Antarctic Peninsula. Limnol. Oceanogr. 58, 1035–1047 (2013).

    Article  Google Scholar 

  16. Mayewski, P. A. et al. State of the antarctic and southern ocean climate system. Rev. Geophys. 47, 1–38 (2009).

    Article  Google Scholar 

  17. Escutia, C., Brinkhuis, H., Klaus, A. & Expedition 318 Scientists. Site U1357. In Proc. IODP Vol. 318 (IODP, 2011).

  18. Shevenell, A. E., Ingalls, A. E., Domack, E. W. & Kelly, C. Holocene Southern Ocean surface temperature variability west of the Antarctic Peninsula. Nature 470, 250–254 (2011).

    Article  Google Scholar 

  19. Pike, J., Swann, G. E. A., Leng, M. J. & Snelling, A. M. Glacial discharge along the west Antarctic Peninsula during the Holocene. Nat. Geosci. 6, 199–202 (2013).

    Article  Google Scholar 

  20. Whitworth, T. et al. in Ocean, Ice, and Atmosphere: Interactions at the Antarctic Continental Margin (eds. Jacobs, S. S. & Weiss, R. F.) 75, 1–27 (American Geophysical Union, 1998).

  21. Ashley, K. E. et al. Mid-Holocene Antarctic sea-ice increase driven by marine ice sheet retreat. Clim. Past 17, 1–19 (2021).

    Article  Google Scholar 

  22. Dunbar, R. B., Anderson, J. B., Domack, E. W. & Jacobs, S. S. in Oceanology of the Antarctic Continental Shelf (ed. Jacobs, S. S.) 309–312 (American Geophysical Union, 1985).

  23. Massom, R. A. et al. Change and variability in East Antarctic sea ice seasonality, 1979/80–2009/10. PLoS ONE 8, e64756 (2013).

    Article  Google Scholar 

  24. Denis, D. et al. Seasonal and subseasonal climate changes recorded in laminated diatom ooze sediments, Adélie Land, East Antarctica. Holocene 16, 1137–1147 (2006).

    Article  Google Scholar 

  25. Maddison, E. J., Pike, J. & Dunbar, R. B. Seasonally laminated diatom-rich sediments from Dumont d’Urville Trough, East Antarctic Margin: Late-Holocene Neoglacial sea-ice conditions. Holocene 22, 857–875 (2012).

    Article  Google Scholar 

  26. Denis, D. et al. Holocene productivity changes off Adélie Land (East Antarctica). Paleoceanography 24, PA3207 (2009).

    Article  Google Scholar 

  27. Crosta, X., Debret, M., Denis, D., Courty, M. A. & Ther, O. Holocene long-and short-term climate changes off Adélie Land, East Antarctica. Geochem. Geophys. Geosyst. 8, 1–15 (2007).

    Article  Google Scholar 

  28. Belt, S. T. et al. Source identification and distribution reveals the potential of the geochemical Antarctic sea ice proxy IPSO25. Nat. Commun. 7, 12655 (2016).

    Article  Google Scholar 

  29. Crosta, X., Denis, D. & Ther, O. Sea ice seasonality during the Holocene, Adélie Land, East Antarctica. Mar. Micropaleontol. 66, 222–232 (2008).

    Article  Google Scholar 

  30. Moy, C. M., Seltzer, G. O., Rodbell, D. T. & Anderson, D. M. Variability of El Niño/Southern Oscillation activity at millennial timescales during the Holocene epoch. Nature 420, 162–165 (2002).

    Article  Google Scholar 

  31. Carré, M. et al. Holocene history of ENSO variance and asymmetry in the eastern tropical Pacific. Science 345, 1045–1047 (2014).

    Article  Google Scholar 

  32. Cobb, K. M. et al. Highly variable El Niño–Southern Oscillation throughout the Holocene. Science 339, 67–70 (2013).

    Article  Google Scholar 

  33. Karamperidou, C., Di Nezio, P. N., Timmermann, A., Jin, F.-F. & Cobb, K. M. The response of ENSO flavors to mid-Holocene climate: implications for proxy interpretation. Paleoceanography 30, 527–547 (2017).

    Article  Google Scholar 

  34. Abram, N. J. et al. Evolution of the Southern Annular Mode during the past millennium. Nat. Clim. Change 4, 564–569 (2014).

    Article  Google Scholar 

  35. Abram, N. J. et al. Palaeoclimate perspectives on the Indian Ocean Dipole. Quat. Sci. Rev. 237, 106302 (2020).

    Article  Google Scholar 

  36. Mackintosh, A. N. et al. Retreat history of the East Antarctic Ice Sheet since the Last Glacial Maximum. Quat. Sci. Rev. 100, 10–30 (2014).

    Article  Google Scholar 

  37. Leventer, A. et al. Marine sediment record from the East Antarctic margin reveals dynamics of ice sheet recession. GSA Today 16, 4–10 (2006).

    Article  Google Scholar 

  38. Gerringa, L. J. A. et al. Iron from melting glaciers fuels the phytoplankton blooms in Amundsen Sea (Southern Ocean): iron biogeochemistry. Deep Sea Res. II 71–76, 16–31 (2012).

    Article  Google Scholar 

  39. Moreau, S. et al. Sea ice meltwater and circumpolar deep water drive contrasting productivity in three Antarctic polynyas. J. Geophys. Res. Ocean. 124, 2943–2968 (2019).

    Article  Google Scholar 

  40. Massom, R. A. et al. Effects of regional fast-ice and iceberg distributions on the behaviour of the Mertz Glacier polynya, East Antarctica. Ann. Glaciol. 33, 391–398 (2001).

    Article  Google Scholar 

  41. Etourneau, J. et al. Holocene climate variations in the western Antarctic Peninsula: evidence for sea ice extent predominantly controlled by changes in insolation and ENSO variability. Clim. Past 9, 1431–1446 (2013).

    Article  Google Scholar 

  42. Schneider, D. P. et al. Observed Antarctic interannual climate variability and tropical linkages. J. Clim. 25, 4048–4066 (2012).

    Article  Google Scholar 

  43. Ciasto, L. M. et al. Teleconnections between tropical Pacific SST anomalies and extratropical Southern Hemisphere climate. J. Clim. 28, 56–65 (2015).

    Article  Google Scholar 

  44. Marshall, G. J. & Thompson, D. W. J. The signatures of large-scale patterns of atmospheric variability in Antarctic surface temperatures. J. Geophys. Res. Atmos. 121, 3276–3289 (2016).

    Article  Google Scholar 

  45. IPCC Special Report on the Ocean and Cryosphere in a Changing Climate (eds Weyer, N. M. et al.) (IPCC, 2019).

  46. Mouginot, J., Scheuchl, B. & Rignot, E. MEaSUREs Antarctic boundaries for IPY 2007–2009 from Satellite Radar, Version 2. [68°S, 65°S; 148°E, 138°E] (NASA National Snow and Ice Data Center, 2017).

  47. Fretwell, P. et al. Bedmap2: improved ice bed, surface and thickness datasets for Antarctica. Cryosphere 7, 375–393 (2013).

    Article  Google Scholar 

  48. Beaman, R. J., O’Brien, P. E., Post, A. L. & De Santis, L. A new high-resolution bathymetry model for the Terre Adélie and George V continental margin, East Antarctica. Antarct. Sci. 23, 95–103 (2011).

    Article  Google Scholar 

  49. NASA Ocean Biology Processing Group. MODIS-Aqua Level 2 Ocean Color Data Version R2018.0 NASA Ocean Biology DAAC (2017); https://doi.org/10.5067/AQUA/MODIS/L2/OC/2018

  50. Hu, C., Lee, Z. & Franz, B. Chlorophyll a algorithms for oligotrophic oceans: a novel approach based on three-band reflectance difference. J. Geophys. Res. 117, C01011 (2012).

    Google Scholar 

  51. Yamane, M. et al. Compound-specific 14C dating of IODP expedition 318 core U1357A obtained off the Wilkes Land coast, Antarctica. Radiocarbon 56, 1009–1017 (2014).

    Article  Google Scholar 

  52. Blaauw, M. & Christen, J. A. Flexible paleoclimate age-depth models using an autoregressive gamma process. Bayesian Anal. 6, 457–474 (2011).

    Article  Google Scholar 

  53. Canuel, E. A. & Martens, C. S. Reactivity of recently deposited organic matter: degradation of lipid compounds near the sediment-water interface. Geochim. Cosmochim. Acta 60, 1793–1806 (1996).

    Article  Google Scholar 

  54. Ohkouchi, N., Kawamura, K. & Taira, A. Fluctuations of terrestrial and marine biomarkers in the western tropical Pacific during the last 23,300 years. Paleoceanography 12, 623–630 (1997).

    Article  Google Scholar 

  55. Yokoyama, Y. et al. Widespread collapse of the Ross Ice Shelf during the late Holocene. Proc. Natl Acad. Sci. USA 113, 2354–2359 (2016).

    Article  Google Scholar 

  56. Prothro, L. O. et al. Timing and pathways of East Antarctic Ice Sheet retreat. Quat. Sci. Rev. 230, 106166 (2020).

    Article  Google Scholar 

  57. Yamane, M. et al. Small- to ultra-small-scale radiocarbon measurements using newly installed single-stage AMS at the University of Tokyo. Nucl. Instrum. Methods Phys. Res. B 455, 238–243 (2019).

    Article  Google Scholar 

  58. Berkman, P. A. & Forman, S. L. Pre-bomb radiocarbon and the reservoir correction for calcareous marine species in the Southern Ocean. Geophys. Res. Lett. 23, 363–366 (1996).

    Article  Google Scholar 

  59. Denis, D. et al. Holocene glacier and deep water dynamics, Adélie Land region, East Antarctica. Quat. Sci. Rev. 28, 1291–1303 (2009).

    Article  Google Scholar 

  60. Mortlock, R. A. & Froelich, P. N. A simple method for the rapid determination of biogenic opal in pelagic marine sediments. Deep Sea Res. A. 36, 1415–1426 (1989).

    Article  Google Scholar 

  61. St-Onge, G. & Long, B. F. CAT-scan analysis of sedimentary sequences: an ultrahigh-resolution paleoclimatic tool. Eng. Geol. 103, 127–133 (2009).

    Article  Google Scholar 

  62. Boespflug, X., Long, B. F. N. & Occhietti, S. CAT-scan in marine stratigraphy: a quantitative approach. Mar. Geol. 122, 281–301 (1995).

    Article  Google Scholar 

  63. Horos Project (Horos, 2017).

  64. Schindelin, J. et al. Fiji: an open-source platform for biological-image analysis. Nat. Methods 9, 676–682 (2012).

    Article  Google Scholar 

  65. Belt, S. T. et al. A novel chemical fossil of palaeo sea ice: IP25. Org. Geochem. 38, 16–27 (2007).

    Article  Google Scholar 

  66. Massé, G. et al. Highly branched isoprenoids as proxies for variable sea ice conditions in the Southern Ocean. Antarct. Sci. 23, 487–498 (2011).

    Article  Google Scholar 

  67. Jensen, S., Renberg, L. & Reutergårdh, L. Residue analysis of sediment and sewage sludge for organochlorines in the presence of elemental sulfur. Anal. Chem. 49, 316–318 (1977).

    Article  Google Scholar 

  68. Riis, V. & Babel, W. Removal of sulfur interfering in the analysis of organochlorines by GC-ECD. Analyst 124, 1771–1773 (1999).

    Article  Google Scholar 

  69. Johns, L. et al. Identification of a C25 highly branched isoprenoid (HBI) diene in Antarctic sediments, Antarctic sea-ice diatoms and cultured diatoms. Org. Geochem. 30, 1471–1475 (1999).

    Article  Google Scholar 

  70. Meyers, S. Astrochron: An R Package for Astrochronology (CRAN, 2014).

  71. Ragueneau, O. et al. A review of the Si cycle in the modern ocean: recent progress and missing gaps in the application of biogenic opal as a paleoproductivity proxy. Glob. Planet. Change 26, 317–365 (2000).

    Article  Google Scholar 

  72. Iwasaki, S., Takahashi, K., Ogawa, Y., Uehara, S. & Vogt, C. Alkaline leaching characteristics of biogenic opal in Eocene sediments from the central Arctic Ocean: a case study in the ACEX cores. J. Oceanogr. 70, 241–249 (2014).

    Article  Google Scholar 

  73. Brown, E. T. in Micro-XRF Studies of Sediment Cores. Developments in Paleoenvironmental Research (eds. Croudace, I. W. & Rothwell, R. G.) 267–277 (Springer, 2015).

  74. Jimenez-Espejo, F. J. et al. Changes in detrital input, ventilation and productivity in the central Okhotsk Sea during the marine isotope stage 5e, penultimate interglacial period. J. Asian Earth Sci. 156, 189–200 (2018).

    Article  Google Scholar 

  75. Rothwell, R. G. & Croudace, I. W. in Micro-XRF Studies of Sediment Cores. Developments in Paleoenvironmental Research (eds. Croudace, I. W. & Rothwell, R. G.) 25–102 (Springer, 2015).

  76. Agnihotri, R., Altabet, M. A., Herbert, T. D. & Tierney, J. E. Subdecadally resolved paleoceanography of the Peru margin during the last two millennia. Geochem. Geophys. Geosyst. 9, Q05013 (2008).

    Article  Google Scholar 

  77. Dickson, A. J., Leng, M. J., Maslin, M. A. & Röhl, U. Oceanic, atmospheric and ice-sheet forcing of South East Atlantic Ocean productivity and South African monsoon intensity during MIS-12 to 10. Quat. Sci. Rev. 29, 3936–3947 (2010).

    Article  Google Scholar 

  78. Martin-Puertas, C., Brauer, A., Dulski, P. & Brademann, B. Testing climate-proxy stationarity throughout the Holocene: an example from the varved sediments of Lake Meerfelder Maar (Germany). Quat. Sci. Rev. 58, 56–65 (2012).

    Article  Google Scholar 

  79. Melles, M. et al. 2.8 Million years of arctic climate change from Lake El’gygytgyn, NE Russia. Science 337, 315–320 (2012).

    Article  Google Scholar 

  80. Killick, R., Fearnhead, P. & Eckley, I. A. Optimal detection of changepoints with a linear computational cost. J. Am. Stat. Assoc. 107, 1590–1598 (2012).

    Article  Google Scholar 

  81. Lavielle, M. Using penalized contrasts for the change-point problem. Signal Process. 85, 1501–1510 (2005).

    Article  Google Scholar 

Download references

Acknowledgements

This research used samples and data provided by IODP expedition 318, sponsored by the US National Science Foundation (NSF) and participating countries under the management of the Consortium for Ocean Leadership, including the Australian and New Zealand International Ocean Discovery Program Consortium. Funding was provided by Royal Society Te Apārangi Marsden Fund (18-VUW-089 to R.M.M. and 15-VUW-131 to N.A.N.B.) and the New Zealand Ministry of Business, Innovation and Employment through the Antarctic Science Platform (ANTA1801). Funding was also provided by the New Zealand Ministry of Business, Innovation and Employment Strategic Science Investment Fund (SSIF) through GNS Science (grant 540GCT32). We acknowledge funding from the Dumont d’Urville NZ-France Science and Technology Programme, MARICE project (Marine and Ice core reconstruction of East Antarctic sea ice variability over the past 2,000 years) (project nos. 45455NF and 19-VUW-047-DDU Catalyst Fund, RSNZ). J.E. and X.C. acknowledge funding by the ERC StG ICEPROXY (203441), the ANR CLIMICE and the FP7 Past4Future (243908) projects. F.J.J.-E. was funded by project 201830I092 (Spanish Research Council). C.E. and F.J.J.-E acknowledge funding by the Spanish Ministry of Science and Innovation (grant CTM2017-89711-C2-1-P), co-funded by the European Union through FEDER funds. C.R.R. was funded by a University of Otago research grant and a L’Oréal-UNESCO For Women in Science Australia and New Zealand Fellowship. The Natural Environment Research Council funded K.E.A. (CENTA PhD; NE/L002493/1) and J.B. (standard grant Ne/I00646X/1). Y.Y. was funded by the Japan Society for Promotion of Science (JSPS) grant no. JP20H00193. S.F.P. was supported by National Science Foundation grant OPP-0732796. R.B.D. was supported by National Science Foundation grants PLR-1644118 and OCE-1129101. The authors acknowledge the Norwegian Polar Institute’s Quantarctica package, and the use of imagery from the NASA Worldview application (https://worldview.earthdata.nasa.gov/), part of the NASA Earth Observing System Data and Information System.

Author information

Authors and Affiliations

Authors

Contributions

K.M.J., R.M.M. and N.A.N.B designed the study and wrote the paper with input from all authors. K.M.J., R.M.M. and H.J.H. analysed the X-ray CT data. R.M.M. and A.A. conducted the grain size analyses. J.E. produced the HBI data. F.J.J.-E. produced the XRF geochemical data. C.R.R. conducted the opal (%BSi) measurements. M.Y. and Y.Y. analysed and provided the compound-specific 14C ages. R.B.D. and C.E. were lead proponents of the ancillary IODP expedition 318 proposal to core IODP Site 1357. All authors contributed to the interpretations of data and finalization of the manuscript.

Corresponding author

Correspondence to Katelyn M. Johnson.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Peer review information Nature Geoscience thanks Kaarina Weckström and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary Handling Editor(s): James Super.

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

Extended data

Extended Data Fig. 1 Corrected and calibrated radiocarbon age models for U1357B and MD03-2601.

Age Model for U1357B (blue symbols show calibrated and corrected ages, and blue line of calculated Bayesian age-depth curve, using BACON R package; dotted lines are 2 sigma uncertainty) and MD03-2601 (red symbols and lines as for U1357B) show that sediment advection is a regional signal as sedimentation rates covary. Compound specific ages from U1357A are shown in green with 2 sigma uncertainties. U1357B is a longer core with 87 14C dates, leading to a much higher resolution age model. U1357B also includes the last 1,000 years, which is lacking in MD03-2601.

Extended Data Fig. 2 Grain size analysis of light laminae.

Light laminae in three intervals (Interval 1: ~4.5 to present; Interval 2: ~8-4.5 ka; Interval 3: ~11.4-8 ka;) have a dominant silt-fine sand mode and are less than 125 µm. Sand percent provides a measure of this coarse silt to fine sand mode and is used as a proxy to capture the upper values of relative current strength.

Extended Data Fig. 3 Correlations of Adélie Drift Proxies.

(a,b) Overlay plot and correlation between laminae counts (frequency of biological blooms) and biogenic mass accumulation rates (advection of biological material by wind driven current strength). (c,d) Overlay plot and correlation between sand percent (grain size proxy for wind driven current strength) and biogenic mass accumulation rates (advection of biological material by wind driven current strength). (d,e) Overlay plot and correlation between sand percent (grain size proxy for wind driven current strength) and laminae counts (frequency of biological blooms).

Extended Data Fig. 4 Image Analysis example.

From left to right: Line-scan core photo, CT image, raw greyscale curve with light laminae picks in orange, and XRF titanium data. The CT image visually enhances the laminations, and provides a sub-mm resolved greyscale curve that better captures the rapid shifts in sedimentation. Frequencies from the manually picked laminae (Fig. 3d) match those extracted from the greyscale curve (Fig. 4).

Extended Data Fig. 5 Greyscale data in relation sedimentological changes at the site.

Greyscale data compared to various sedimentological proxies of the core. (a) GRA Bulk Density (b) Natural Gamma Radiation (NGR) (c) XRF peak area of silicon (d) XRF peak area of titanium (e) XRF peak area of silicon/titanium ratio used to indicate long-term changes in biological productivity (f) Greyscale curve from the CT images. XRF, GRA Bulk Density, and Greyscale interpolated to 5 cm. Black curves indicate a robust LOESS smoothing using 2% of the data points for all data sets. GRA Bulk Density and NGR data from ref. 17.

Extended Data Fig. 6 Holocene Mean Changepoints.

Calculation of shifts in the mean of various Holocene records using statistical changepoint analysis. This method identifies the point at which the mean of a timeseries changes most significantly by finding the point at which the total residual error from the mean of each section is minimized (ref. 80,81). Shifts in Adélie Land proxies (a-d) occur between ~4.3 and ~4.7 ka.

Extended Data Fig. 7 IBRD in U1357B.

Section 19H5 (169.98-170.67 m) from U1357B is the only portion of core with substantial IBRD. The top of this section is dated to ~11.365ka.

Supplementary information

Supplementary information

Supplementary Figs. 1 and 2, and Table 1.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Johnson, K.M., McKay, R.M., Etourneau, J. et al. Sensitivity of Holocene East Antarctic productivity to subdecadal variability set by sea ice. Nat. Geosci. 14, 762–768 (2021). https://doi.org/10.1038/s41561-021-00816-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41561-021-00816-y

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