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.

  • Article
  • Published:

Increased interglacial atmospheric CO2 levels followed the mid-Pleistocene Transition

Nature Geoscience volume 15, pages 307–313 (2022)Cite this article

Subjects

Abstract

Atmospheric CO2 and polar ice volume have been strongly coupled over the past 805,000 years. However, the prior extent of coupling, during times of lower-amplitude ice-volume variability, is unknown because continuous high-resolution CO2 records are lacking. We reconstructed the past 1,460,000 years of atmospheric CO2 (~1,700 year sample resolution) by taking advantage of the unique relationship between CO2 concentration and leaf-wax δ13C resulting from changes in the extent of C3 and C4 vegetation in East India. Notably, reconstructed interglacial CO2 concentrations were lower before the transition to large volume variability during the mid-Pleistocene Transition (900,000 years ago). Prior to the mid-Pleistocene Transition, CO2 exhibited a secular trend similar to that of deep-ocean carbon isotopes. At orbital time scales, phase analysis indicates that the CO2 lead relative to ice volume changed to a lag during the mid-Pleistocene Transition. Combined, these findings suggest that deep-ocean circulation controlled the long-term CO2 trend, and that interaction between CO2, continental ice and deep-ocean circulation was reorganized during the mid-Pleistocene Transition, involving a decrease in carbon storage in the deep Pacific.

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

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Reconstructed CO2 concentration during the last 1.46 Myr.
Fig. 2: δ13CFA, C4/(C3 + C4) plant ratio, CO2 concentration and ice volume.
Fig. 3: Dynamic vegetation model results.
Fig. 4: Phase lead and lag of CO2FA, ice volume and deep-ocean circulation.

Similar content being viewed by others

Data availability

The data are available in supplementary tables and at https://www.ncei.noaa.gov/pub/data/paleo/paleocean/indian_ocean/yamamoto2021/yamamoto2021-u1446.txt. The CMIP5 and PMIP3 datasets are publicly available at https://pcmdi.llnl.gov/mips/cmip5/ and https://pmip3.lsce.ipsl.fr, respectively. CMAP precipitation data are available at http://www.cdc.noaa.gov/. ECMWF ERA‐40 data are available at https://apps.ecmwf.int/datasets/.

References

  1. Barnola, J. M., Raynaud, D., Korotkevich, Y. S. & Lorius, C. Vostok ice core provides 160,000-year record of atmospheric CO2. Nature 329, 408–414 (1987).

    Article  Google Scholar 

  2. Petit, J. R. et al. Climate and atmospheric history of the past 420,000 years from the Vostok ice core. Nature 399, 429–436 (1999).

    Article  Google Scholar 

  3. Lüthi, D. et al. High-resolution carbon dioxide concentration record 650,000–800,000 years before present. Nature 453, 379–382 (2008).

    Article  Google Scholar 

  4. Bereiter, B. et al. Revision of the EPICA Dome C CO2 record from 800 to 600 kyr before present. Geophys. Res. Let. 42, 542–549 (2015).

    Article  Google Scholar 

  5. Foster, G. L. Seawater pH, pCO2 and [CO2−] variations in the Caribbean Sea over the last 130 kyr: a boron isotope and B/Ca study of planktic foraminifera. Earth Planet. Sci. Lett. 271, 254–266 (2008).

    Article  Google Scholar 

  6. Hönisch, B., Hemming, N. G., Archer, D., Siddall, M. & McManus, J. F. Atmospheric carbon dioxide concentration across the mid-Pleistocene Transition. Science 324, 1551–1554 (2009).

    Article  Google Scholar 

  7. Chalk, T. B. et al. Causes of ice age intensification across the mid-Pleistocene Transition. Proc. Natl Acad. Sci. USA 114, 13114–13119 (2017).

    Article  Google Scholar 

  8. Dyez, K. A., Hönisch, B. & Schmidt, G. A. Early Pleistocene obliquity‐scale pCO2 variability at ~1.5 million years ago. Paleoceanogr. Paleoclimatol. 33, 1270–1291 (2018).

    Article  Google Scholar 

  9. Pagani, M., Liu, Z., LaRiviere, J. & Ravelo, A. C. High Earth-system climate sensitivity determined from Pliocene carbon dioxide concentrations. Nat. Geosci. 3, 27–30 (2010).

    Article  Google Scholar 

  10. Da, J., Zhang, Y. G., Li, G., Meng, X. & Ji, J. Low CO2 levels of the entire Pleistocene epoch. Nat. Commun. 10, 4342 (2019).

    Article  Google Scholar 

  11. Cui, Y., Schubert, B. A. & Jahren, A. H. A 23 m.y. record of low atmospheric CO2. Geology 48, 888–892 (2020).

    Article  Google Scholar 

  12. Martínez-Botí, M. A. et al. Boron isotope evidence for oceanic carbon dioxide leakage during the last deglaciation. Nature 518, 219–222 (2015).

    Article  Google Scholar 

  13. Higgins, J. A. et al. Atmospheric composition 1 million years ago from blue ice in the Allan Hills, Antarctica. Proc. Natl Acad. Sci. USA 112, 6887–6891 (2015).

    Article  Google Scholar 

  14. Yan, Y. et al. Two-million-year-old snapshots of atmospheric gases from Antarctic ice. Nature 574, 663–666 (2019).

    Article  Google Scholar 

  15. Pisias, N. G. & Moore, T. C. Jr. The evolution of the Pleistocene climate: a time series approach. Earth Planet. Sci. Lett. 52, 450–458 (1981).

    Article  Google Scholar 

  16. Clark, P. U. et al. The Middle Pleistocene Transition: characteristics, mechanisms, and implications for long-term changes in atmospheric pCO2. Quat. Sci. Rev. 25, 3150–3184 (2006).

    Article  Google Scholar 

  17. Clark, P. U. & Pollard, D. Origin of the Middle Pleistocene Transition by ice sheet erosion of regolith. Paleoceanography 13, 1–9 (1998).

    Article  Google Scholar 

  18. Ganopolski, A. & Calov, R. The role of orbital forcing, carbon dioxide and regolith in 100 kyr glacial cycles. Clim. Past 7, 1415–1425 (2011).

    Article  Google Scholar 

  19. Tabor, C. R. & Poulsen, C. J. Simulating the mid-Pleistocene Transition through regolith removal. Earth Planet. Sci. Lett. 434, 231–240 (2016).

    Article  Google Scholar 

  20. Willeit, M., Ganopolski, A., Calov, R. & Brovkin, V. Mid-Pleistocene Transition in glacial cycles explained by declining CO2 and regolith removal. Sci. Adv. 5, eaav7337 (2019).

    Article  Google Scholar 

  21. Pena, L. D. & Goldstein, S. L. Thermohaline circulation crisis and impacts during the mid-Pleistocene Transition. Science 345, 318–322 (2014).

    Article  Google Scholar 

  22. Raymo, M. E. & Huybers, P. Unlocking the mysteries of the ice ages. Nature 451, 284–285 (2008).

    Article  Google Scholar 

  23. Medina-Elizalde, M. & Lea, D. W. The mid-Pleistocene Transition in the tropical. Pacific. Science 310, 1009–1012 (2005).

    Google Scholar 

  24. Elderfield, H. et al. Evolution of ocean temperature and ice volume through the mid-Pleistocene climate transition. Science 337, 704–708 (2012).

    Article  Google Scholar 

  25. Clemens, S. C. et al. Remote and local drivers of Pleistocene South Asian summer monsoon precipitation: a test for future predictions. Sci. Adv. 7, eabg3848 (2021).

    Article  Google Scholar 

  26. Edwards, E. J. et al. The origins of C4 grasslands: integrating evolutionary and ecosystem science. Science 328, 587–591 (2010).

    Article  Google Scholar 

  27. Cerling, T. E., Ehlenringer, J. R. & Harris, J. M. Carbon dioxide starvation, the development of C4 ecosystem, and mammalian evolution. Philos. Trans. R. Soc. Lond. B 353, 159–171 (1998).

    Article  Google Scholar 

  28. Ainsworth, E. & Long, S. P. What have we learned from 15 years of free-air CO2 enrichment (FACE)? A meta-analytic review of the responses of photosynthesis, canopy properties and plant production to rising CO2. N. Phytol. 165, 351–372 (2005).

    Article  Google Scholar 

  29. Schubert, A. & Jahren, A. H. Global increase in plant carbon isotope fractionation following the Last Glacial Maximum caused by increase in atmospheric pCO2. Geology 43, 435–438 (2015).

    Article  Google Scholar 

  30. Braconnot, P. et al. Evaluation of climate models using palaeoclimatic data. Nat. Clim. Change 2, 417–424 (2012).

    Article  Google Scholar 

  31. Abe-Ouchi, A. et al. Ice-sheet configuration in the CMIP5/PMIP3 Last Glacial Maximum experiments. Geosci. Model Dev. 8, 3621–3637 (2015).

    Article  Google Scholar 

  32. O’ishi, R. & Abe-Ouchi, A. Influence of dynamic vegetation on climate change and terrestrial carbon storage in the Last Glacial Maximum. Clim. Past 9, 1571–1587 (2013).

    Article  Google Scholar 

  33. Rao, V. P., Reddy, N. P. & Rao, C. M. Clay mineral distribution in the shelf sediments off the northern part of the east coast of India. Cont. Shelf Res. 8, 145–151 (1988).

    Article  Google Scholar 

  34. Phillips, S. C. et al. Long-timescale variation in bulk and clay mineral composition of Indian continental margin sediments in the Bay of Bengal, Arabian Sea, and Andaman Sea. Mar. Petrol. Geol. 58, 117–138 (2014).

    Article  Google Scholar 

  35. Hain, M. P., Foster, G. L. & Chalk, T. Robust constraints on past CO2 climate forcing from boron isotope proxy. Paleoceanogr. Paleoclimatol. 33, 1099–1115 (2018).

    Article  Google Scholar 

  36. Zhang, Y. G. et al. Refining the alkenone-pCO2 method I: lessons from the Quaternary glacial cycles. Geochim. Cosmochim. Acta 260, 177–191 (2019).

    Article  Google Scholar 

  37. McClymont, E. L., Sosdian, S. M., Rosell-Melé, A. & Rosenthal, Y. Pleistocene sea surface temperature evolution: early cooling, delayed glacial intensification, and implications for the mid-Pleistocene climate transition. Earth Sci. Rev. 123, 173–193 (2013).

    Article  Google Scholar 

  38. French, K. L. et al. Millennial soil retention of terrestrial organic matter deposited in the Bengal Fan. Sci. Rep. 8, 11997 (2018).

    Article  Google Scholar 

  39. Hein, C. J., Usman, M., Eglinton, T. I., Haghipour, N. & Galy, V. V. Millennial-scale hydroclimate control of tropical soil carbon storage. Nature 581, 63–66 (2020).

    Article  Google Scholar 

  40. Lisiecki, L. E. & Raymo, M. E. A Pliocene–Pleistocene stack of 57 globally distributed benthic δ18O records. Paleoceanography 20, PA1003 (2005).

    Google Scholar 

  41. Hodell, D. A., Venz, K. A., Charles, C. D. & Ninnemann, U. S. Pleistocene vertical carbon isotope and carbonate gradients in the South Atlantic sector of the Southern Ocean. Geochem. Geophys. Geosyst. 4, 1004 (2003).

    Article  Google Scholar 

  42. Lisiecki, L. E. A benthic δ13C-based proxy for atmospheric pCO2 over the last 1.5 Myr. Geophys. Res. Lett. 37, L21708 (2010).

    Article  Google Scholar 

  43. Farmer, J. R. et al. Deep Atlantic Ocean carbon storage and the rise of 100,000-year glacial cycles. Nat. Geosci. 12, 355–360 (2019).

    Article  Google Scholar 

  44. Abe-Ouchi, A. et al. Insolation-driven 100,000-year glacial cycles and hysteresis of ice-sheet volume. Nature 500, 190–193 (2013).

    Article  Google Scholar 

  45. Sexton, P. F. & Barker, S. Onset of ‘Pacific-style’ deep-sea sedimentary carbonate cycles at the mid-Pleistocene Transition. Earth Planet. Sci. Lett. 321, 81–94 (2012).

    Article  Google Scholar 

  46. Chikaraishi, Y., Naraoka, H. & Poulson, S. R. Hydrogen and carbon isotopic fractionations of lipid biosynthesis among terrestrial (C3, C4 and C.A.M.) and aquatic plants. Phytochemistry 65, 1369–1381 (2004).

    Article  Google Scholar 

  47. Chikaraishi, Y., Takano, Y. & Ohkouchi, N. Heterotrophic uptake of soil amino acids by C4 plants: unusual stable isotopic composition of C4 plant lipids may be derived from amino acid uptake. In Book of Abstacts, IMOG 2015 Prague (eds Schwark, L. et al.) A02 (2015).

  48. Sitch, S. et al. Evaluation of ecosystem dynamics, plant geography and terrestrial carbon cycling in the L.P.J. dynamic global vegetation model. Glob. Change Biol. 9, 161–185 (2003).

    Article  Google Scholar 

  49. Paillard, D., Labeyrie, L. & Yiou, P. Macintosh program performs time-series analysis. Eos 77, 379 (1996).

    Article  Google Scholar 

  50. Clemens, S. C., Kuhnt, W., LeVay, L. J. & the Expedition 353 Scientists. Indian monsoon rainfall. In Proc. of the International Ocean Discovery Program Vol. 353 (2016).

  51. Mazumdar, A. et al. Geochemical characterization of the Krishna–Godavari and Mahanadi offshore basin (Bay of Bengal) sediments: a comparative study of provenance. Mar. Petrol. Geol. 60, 18–33 (2015).

    Article  Google Scholar 

  52. Zorzi, C. et al. Indian monsoon variations during three contrasting climate periods: the Holocene, Heinrich Stadial 2 and the last interglacial–glacial transition. Quat. Sci. Rev. 125, 50–60 (2015).

    Article  Google Scholar 

  53. Singh, J. S. & Chaturvedi, R. K. Diversity of ecosystem types in India: a review. Proc. Indian Natn. Sci. Acad. 83, 569–594 (2017).

    Google Scholar 

  54. Sage, R. F. A portrait of the C4 photosynthetic family on the 50th anniversary of its discovery: species number, evolutionary lineages, and Hall of Fame. J. Exp. Bot. 68, e11–e28 (2017).

    Article  Google Scholar 

  55. Gao, L., Guimond, J., Thomas, E. & Huang, Y. Major trends in leaf wax abundance, δ2H and δ13C values along leaf venation in five species of C3 plants: physiological and geochemical implications. Org. Geochem. 78, 144–152 (2015).

    Article  Google Scholar 

  56. Pearson, A., McNichol, A. P., Benitez-Nelson, B. C., Hays, J. M. & Eglinton, T. Origins of lipid biomarkers in Santa Monica Basin surface sediments: a case study using compound-specific Δ14C analysis. Geochim. Cosmochim. Acta 65, 3123–3137 (2001).

    Article  Google Scholar 

  57. Keeling, R. F. et al. Atmospheric evidence for a global secular increase in carbon isotopic discrimination of land photosynthesis. Proc. Natl Acad. Sci. USA 114, 10361–10366 (2017).

    Article  Google Scholar 

  58. Elsig, J. et al. Stable isotope constraints on Holocene carbon cycle changes from an Antarctic ice core. Nature 461, 507–510 (2009).

    Article  Google Scholar 

  59. Lourantou, A. et al. Constraint of the CO2 rise by new atmospheric carbon isotopic measurements during the last deglaciation. Glob. Biogeochem. Cycles 24, GB2015 (2010).

    Article  Google Scholar 

  60. Diefendorf, A. F., Mueller, K. E., Wing, S. L., Koch, P. L. & Freeman, K. H. Global patterns in leaf 13C discrimination and implications for studies of past and future climate. Proc. Natl Acad. Sci. USA 107, 5738–5743 (2010).

    Article  Google Scholar 

  61. Bazin, L. et al. An optimized multi-proxy, multi-site Antarctic ice and gas orbital chronology (AICC2012): 120–800 ka. Clim. Past 9, 1715–1731 (2013).

    Article  Google Scholar 

  62. Uppala, S. M. et al. The ERA‐40 re-analysis. Q. J. R. Meteorol. Soc. 131, 2961–3012 (2005).

    Article  Google Scholar 

  63. Xie, P. & Arkin, P. A. A 17‐year monthly analysis based on gauge observations, satellite estimates, and numerical model outputs. Bull. Am. Meteorol. Soc. 78, 2539–2558 (1997).

    Article  Google Scholar 

  64. O’ishi, R. & Abe-Ouchi, A. Influence of dynamic vegetation on climate change arising from increasing CO2. Clim. Dynam. 33, 645–663 (2009).

    Article  Google Scholar 

  65. Hays, J. D., Imbrie, J. I. & Shackleton, N. J. Variations in the Earth’s orbit: pacemaker of the ice ages. Science 194, 1121–1132 (1976).

    Article  Google Scholar 

  66. Imbrie, J. & Imbrie, J. Z. Modeling the climatic response to orbital variations. Science 207, 943–953 (1980).

    Article  Google Scholar 

  67. Gebregiorgis, D. et al. Southern Hemisphere forcing of South Asian monsoon precipitation over the past ~1 million years. Nat. Commun. 9, 4702 (2018).

    Article  Google Scholar 

  68. Bolton, C. T. et al. A 500,000 year record of Indian summer monsoon dynamics recorded by eastern equatorial Indian Ocean upper water-column structure. Quat. Sci. Rev. 77, 167–180 (2013).

    Article  Google Scholar 

  69. Clemens, S. C. & Prell, W. L. A 350,000 year summer-monsoon multi-proxy stack from the Own Ridge, Northern Arabian Sea. Mar. Geol. 201, 35–51 (2003).

    Article  Google Scholar 

  70. Caley, T. et al. New Arabian Sea records help decipher orbital timing of Indo-Asian monsoon. Earth Planet. Sci. Lett. 308, 433–444 (2011).

    Article  Google Scholar 

  71. Wara, M. W., Ravelo, A. C. & Delaney, M. L. Permanent El Niño-like conditions during the Pliocene warm period. Science 309, 758–761 (2005).

    Article  Google Scholar 

  72. de Garidel-Thoron, T., Rosenthal, Y., Bassinot, F. & Beaufort, L. Stable sea surface temperatures in the western Pacific warm pool over the past 1.75 million years. Nature 433, 293–297 (2005).

    Google Scholar 

  73. McGrath, S. M., Clemens, S. C., Huang, Y. & Yamamoto, M. Greenhouse gas and ice volume drive Pleistocene Indian summer monsoon precipitation isotope variability. Geophys. Res. Lett. 48, e2020GL092249 (2021).

    Article  Google Scholar 

  74. Ansari, A., Noble, J., Deodhar, A. & Kumar, U. S. Atmospheric factors controlling the stable isotopes (δ18O and δ2H) of the Indian summer monsoon precipitation in a drying region of eastern India. J. Hydrol. 584, 124636 (2020).

    Article  Google Scholar 

Download references

Acknowledgements

This research used samples provided by IODP expedition 353. We thank Y. Sazuka, A. Muto and K. Ono for analytical assistance, and Y. Chikaraishi for providing the end-member value of wild C4 plants. M.Y. was funded by JSPS grants JPMXS05R2900001 and 19H05595 and JAMSTEC Exp 353 post-cruise study. S.C.C. was supported by US NSF OCE1634774. A.A.-O. was supported by JSPS grant 17H06104, MEXT grant 17H06323 and JAMSTEC to use the Earth Simulator supercomputer. R.O. was supported by ArCS project JPMXD1300000000 (MEXT, Japan).

Author information

Authors and Affiliations

  1. Faculty of Environmental Earth Science, Hokkaido University, Sapporo, Japan

    Masanobu Yamamoto

  2. Graduate School of Environmental Science, Hokkaido University, Sapporo, Japan

    Masanobu Yamamoto, Osamu Seki & Yuko Tsuchiya

  3. Department of Earth, Environmental and Planetary Sciences, Brown University, Providence, RI, USA

    Steven C. Clemens & Yongsong Huang

  4. Insititute of Low Temperature Science, Hokkaido University, Sapporo, Japan

    Osamu Seki

  5. Atmosphere and Ocean Research Institute, The University of Tokyo, Kashiwa, Japan

    Ryouta O’ishi & Ayako Abe-Ouchi

Authors
  1. Masanobu Yamamoto
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Steven C. Clemens
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Osamu Seki
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Yuko Tsuchiya
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Yongsong Huang
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Ryouta O’ishi
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Ayako Abe-Ouchi
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

M.Y. designed the study. M.Y., O.S., Y.T. and Y.H. generated δ13CFA data. S.C.C. generated foraminifera δ18O data and the age–depth model. M.Y. analysed data. R.O. and A.A.-O. performed model experiments. M.Y. wrote the manuscript with input from others.

Corresponding author

Correspondence to Masanobu Yamamoto.

Ethics declarations

Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Nature Geoscience thanks Julio Sepulveda and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary Handling Editor: James Super, in collaboration with the Nature Geoscience team.

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 Location of IODP Site U1446.

The sediments at Site U1446 were derived mainly from the Mahanadi River (blue) and the adjacent coastal rivers (yellow)33,34,51.

Extended Data Fig. 2 δ13CFA, monsoon indices, and sea surface temperature (SST) at Site U1446 during the last 1.46 Myr.

a, Monsoon indices: normalized values of Indian summer monsoon (ISM) records based on the seawater δ18O (reversed δ18Osw U1446)25 at Site U1446, seawater δ18O of the Andaman Sea (reversed δ18Osw Andaman Sea)67, difference between surface and thermocline foraminifera δ18O (Δδ18O) in the equatorial Indian Ocean68, Indian summer monsoon (I.S.M.) stack of the Arabian Sea69,70. b and e, δ13CFA and U1446 δ18Osw. c and f, δ13CFA and the U1446 TEX86H-based SST25. d, CO2FA and the western Pacific warm pool (WPWP) SST. The SSTs in the WPWP were averaged (Sites ODP Site 80623,71 and MD97-214072). Thick lines indicate the 200-kyr running mean.

Extended Data Fig. 3 Coefficients of determination (r2) between δ13CFA and climate parameters for Site U1446 during the last 805 kyr.

Monsoon proxies A and B respectively correspond to the seawater δ18O (δ18Osw)25, a proxy of salinity in the Bay of Bengal, and long-chain n-fatty acid δD (for the last 640 kyr: δDFA)73, a proxy of tropical convection activity74, at Site U1446, respectively. The r2 value between δ13CFA and the Antarctic ice core CO2 concentration with tuned age4 is highest, indicating that atmospheric CO2 concentration is a major factor determining δ13CFA. The low r2 value between δ13CFA and δ18Osw suggests that the influence of precipitation on δ13CFA is limited. The δDFA has higher coefficients with δ13CFA, ice core CO2 concentration, benthic foraminifera δ18Ob (δ18Ob)25 and SST25. The higher correlation between δ13CFA and δDFA is attributable to the response of the tropical convection activity to CO2-induced global climate.

Extended Data Fig. 4 The differences in annual mean precipitation and surface air temperature in the sediment source area between the LGM and preindustrial periods (LGM – PI).

They were estimated with nine different GCMs30,31,32. The decreases in annual mean precipitation and temperature in the sediment source area (grids of the black border) were 9 ± 23% and 3.4 ± 0.8 °C, respectively.

Extended Data Fig. 5 The areas where C3/C4 vegetation is expected to respond primarily to CO2 changes.

The green grid shows the site where the increase in C4 vegetation due to the decrease in CO2 from 285 to 185 ppm is greater than the increase due to the decrease in precipitation and temperature from the PI level to the LGM level. Vegetation was predicted using LPJ-DGVM under the PI and LGM conditions30,31,32. A very few regions where the increase in C4 vegetation is significant show an empirical response of C3/C4 vegetation to CO2 variation, characterized by hot and seasonally dry (savanna) climates, and could serve as targets for replicating our CO2 reconstruction.

Extended Data Fig. 6 Tuning of records.

a,b, The δ13CFA at Site U1446 and Antarctic ice core CO2 concentrations4 during the last 805 kyr before and after tuning, and c and d, the plots of δ13CFA and Antarctic ice core CO2 concentration4 between 5 and 800 ka before and after tuning. The Antarctic CO2 record4 was tuned to the δ13CFA record.

Extended Data Fig. 7 The effect of tuning.

Power spectra, coherence, and phase difference of the variation in δ13CFA-based CO2 (CO2FA) and Antarctic EPICA CO2 (ref. 4) before and after tuning the EPICA record to the δ13CFA-record in the period between 5 and 800 ka. The horizontal line in the coherence panel indicates the 95% confidence level. Faint lines in the phase difference panel indicate the upper and lower limits of the 80% confidence level. The δ13CFA and EPICA CO2 records showed similar power spectra and high coherences at orbital cycles, implying that the δ13CFA reflects the atmospheric CO2 concentration. The tuning increased coherence in the 41-, 23- and 19-kyr cycles, and reduced the phase lags.

Extended Data Fig. 8 The calibration of δ13CFA to CO2 concentration.

a, Plot of δ13CFA (axis reversed) and the Antarctic ice core CO2 concentration4 in the 5–400 and 400–800 ka periods, b, The slope and intercept of the linear regression equation between δ13CFA and ice core CO2 variations in moving 400-kyr windows, c, The CO2 concentrations estimated from constant δ13CFA values using the calibration equations of the panel b.

Extended Data Fig. 9 Histograms showing the number of samples by CO2 value during two distinct periods of 950 and 1,500 ka.

The values were estimated by the δ13CFA at Site U1446 (CO2FA), blue ice13,14, foraminiferal δ11B (ref. 8), alkenone δ13C (ref. 9), pedogenic carbonate δ13C (ref. 10) and C3 plant δ13C (ref. 11).

Extended Data Fig. 10 Estimates of CO2 in various methods.

CO2 values estimated by the δ13CFA at Site U1446 (CO2FA) with a calibration error of 12 ppm, foraminiferal δ11B (with 1σ interval; ref. 8 data after refs. 5,6,7), alkenone δ13C (with the upper and lower estimates)9, pedogenic carbonate δ13C (ref. 10) and δ13C of C3 plants11 during the past 1.5 Myr.

Supplementary information

Supplementary Table 1

The age constraints for site U1446.

Supplementary Table 2

The δ13CFA and calculated CO2 concentrations (CO2FA) for site U1446.

Supplementary Table 3

The δ13CFA of C3 and C4 plants predicted based on the Suess effect and the empirical relationship between the δ13C of C3 plants and atmospheric CO2 concentration.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Yamamoto, M., Clemens, S.C., Seki, O. et al. Increased interglacial atmospheric CO2 levels followed the mid-Pleistocene Transition. Nat. Geosci. 15, 307–313 (2022). https://doi.org/10.1038/s41561-022-00918-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41561-022-00918-1

This article is cited by

Search

Advanced 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