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Eocene to Oligocene terrestrial Southern Hemisphere cooling caused by declining pCO2

Nature Geoscience volume 14, pages 659–664 (2021)Cite this article

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Abstract

The greenhouse-to-icehouse climate transition from the Eocene into the Oligocene is well documented by sea surface temperature records from the southwest Pacific and Antarctic margin, which show evidence of pronounced long-term cooling. However, identification of a driving mechanism depends on a better understanding of whether this cooling was also present in terrestrial settings. Here, we present a semi-continuous terrestrial temperature record spanning from the middle Eocene to the early Oligocene (~41–33 million years ago), using bacterial molecular fossils (biomarkers) preserved in a sequence of southeast Australian lignites. Our results show that mean annual temperatures in southeast Australia gradually declined from ~27 °C (±4.7 °C) during the middle Eocene to ~22–24 °C (±4.7 °C) during the late Eocene, followed by a ~2.4 °C-step cooling across the Eocene/Oligocene boundary. This trend is comparable to other temperature records in the Southern Hemisphere, suggesting a common driving mechanism, likely \(p{{\rm{CO}}_{2}}\). We corroborate these results with a suite of climate model simulations demonstrating that only simulations including a decline in \(p{{\rm{CO}}_{2}}\) lead to a cooling in southeast Australia consistent with our proxy record. Our data form an important benchmark for testing climate model performance, sea–land interaction and climatic forcings at the onset of a major Antarctic glaciation.

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Fig. 1: Middle Eocene to early Oligocene temperatures.
Fig. 2: Terrestrial temperatures versus SSTs.
Fig. 3: Comparison with climate model simulations.

Data availability

All of the lignite data supporting the findings of this study and the compilation of previously published SST records used in Fig. 2 and Extended Data Fig. 3 are available in Supplementary Data 1. All data are available via PANGAEA at https://doi.org/10.1594/PANGAEA.933176 and the model simulation data are available via the freely accessible Bristol Research Initiative for the Dynamic Global Environment server at https://www.paleo.bristol.ac.uk/ummodel/scripts/papers/, as is the standard protocol at the University of Bristol.

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Acknowledgements

We thank NERC (reference: CC010) and NEIF (www.isotopesuk.org) for funding and maintenance of the instrumentation used for this work. We thank S. Blackbird at the University of Liverpool for technical assistance with the TOC analyses. This research was carried out with funding from the European Research Council under the European Union’s Seventh Framework Programme (FP/2007-2013) and European Research Council Grant Agreement number 340923 “The greenhouse earth system” T-GRES (awarded to R.D.P.). Further funding was provided by the Royal Society as part of a Tata University Research Fellowship to B.D.A.N. and the associated enhancement award that funded V.L. Climate model simulations were carried out using the computational facilities of the Advanced Computing Research Centre, University of Bristol, and were supported by NERC (grant number NE/L002434/1).

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Authors and Affiliations

  1. Organic Geochemistry Unit, School of Chemistry, School of Earth Sciences, University of Bristol, Bristol, UK

    Vittoria Lauretano, Richard D. Pancost & B. David A. Naafs

  2. Cabot Institute for the Environment, University of Bristol, Bristol, UK

    Vittoria Lauretano, Alan T. Kennedy-Asser, Paul J. Valdes, Daniel J. Lunt, Richard D. Pancost & B. David A. Naafs

  3. Bristol Research Initiative for the Dynamic Global Environment, School of Geographical Sciences, University of Bristol, Bristol, UK

    Alan T. Kennedy-Asser, Paul J. Valdes & Daniel J. Lunt

  4. School of Earth Sciences, The University of Melbourne, Melbourne, Victoria, Australia

    Vera A. Korasidis & Malcolm W. Wallace

  5. Department of Paleobiology, Smithsonian Institution, Washington, DC, USA

    Vera A. Korasidis

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  1. Vittoria Lauretano
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Contributions

B.D.A.N. and V.L. designed the project. V.L. performed all of the biomarker analyses. A.T.K.-A. and D.J.L. performed the HadCM3BL model simulations. P.J.V. performed the supplementary simulations (Extended Data Fig. 6). V.A.K. and M.W.W. provided the samples, as well as palynological and stratigraphic information. V.L. wrote the manuscript with contributions from all authors.

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Correspondence to Vittoria Lauretano or B. David A. Naafs.

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The authors declare no competing interests.

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

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Extended data

Extended Data Fig. 1 TOC% content.

Total Organic Carbon (TOC) wt.% content vs MAATpeat. Only samples with >30 wt.% were interpreted for MAATpeat analyses.

Extended Data Fig. 2 Nonmetric multidimensional scaling (NMDS).

Nonmetric multidimensional scaling (NMDS) by species relative abundance matrix29. Samples are coded by coal seam and age as indicated in the key.

Extended Data Fig. 3 Comparison with available terrestrial EOT geochemical proxy records.

Compilation of terrestrial temperature quantitative proxy records across the Eocene/Oligocene23,24,25,43,45,56,57,58,59,60,61,62 depicting the degree of cooling for each proxy record and time span at each location. Full circles represent land-based records, while empty circles indicate records of terrestrial temperature change derived from marine sediment cores. (Map from Ocean Data View, https://odv.awi.de/).

Extended Data Fig. 4 Modelled Mean annual air temperature (MAAT).

a, Modelled mean annual air temperature (MAAT) for each of the 8 simulations used in this analysis (black dots and error bars) compared to the South Australia lignite record (coloured dots and error bars). Model error is taken as the maximum and minimum values from the 3 × 3 grid cell box surrounding the proxy location. Annual mean temperatures display a cold bias both before and after the EOT (see text). b, Maps showing the MAAT for each simulation over the South Australia region.

Extended Data Fig. 5 Model spin-up.

Spin-up trends showing the mean annual air temperature for the South Australia region with a 50-year running climatology. Gaps in time series show where simulations were continued or extended.

Extended Data Fig. 6 Tasman Seaway.

Modelled mean annual temperature change in response to a deepening Tasman Seaway (from 100 to 1,500 m depth). Note: these simulations used an alternate model configuration and spin-up procedure and are therefore for illustrative purposes only.

Extended Data Table 1 Climate model simulations.

Model simulation details.

Extended Data Table 2 Climate model boundary conditions.

Boundary conditions of pairs of model simulations used to recreate changes across the EOT. Boundary conditions that remain the same before and after the EOT are shaded in grey.

Supplementary information

Supplementary Information

Supplementary discussion and references.

Supplementary Data 1

Supplementary Tables 1–3.

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Lauretano, V., Kennedy-Asser, A.T., Korasidis, V.A. et al. Eocene to Oligocene terrestrial Southern Hemisphere cooling caused by declining pCO2. Nat. Geosci. 14, 659–664 (2021). https://doi.org/10.1038/s41561-021-00788-z

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