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Biogeographic response of marine plankton to Cenozoic environmental changes

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Abstract

In palaeontological studies, groups with consistent ecological and morphological traits across a clade’s history (functional groups)1 afford different perspectives on biodiversity dynamics than do species and genera2,3, which are evolutionarily ephemeral. Here we analyse Triton, a global dataset of Cenozoic macroperforate planktonic foraminiferal occurrences4, to contextualize changes in latitudinal equitability gradients1, functional diversity, palaeolatitudinal specialization and community equitability. We identify: global morphological communities becoming less specialized preceding the richness increase after the Cretaceous–Palaeogene extinction; ecological specialization during the Early Eocene Climatic Optimum, suggesting inhibitive equatorial temperatures during the peak of the Cenozoic hothouse; increased specialization due to circulation changes across the Eocene–Oligocene transition, preceding the loss of morphological diversity; changes in morphological specialization and richness about 19 million years ago, coeval with pelagic shark extinctions5; delayed onset of changing functional group richness and specialization between hemispheres during the mid-Miocene plankton diversification. The detailed nature of the Triton dataset permits a unique spatiotemporal view of Cenozoic pelagic macroevolution, in which global biogeographic responses of functional communities and richness are decoupled during Cenozoic climate events. The global response of functional groups to similar abiotic selection pressures may depend on the background climatic state (greenhouse or icehouse) to which a group is adapted.

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Fig. 1: Foraminiferal functional groups.
Fig. 2: Cenozoic climate and ecogroup metrics.
Fig. 3: Cenozoic climate and morphogroup metrics.

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Data availability

All data were sourced from the Triton dataset4 (https://doi.org/10.1038/s41597-021-00942-7).

Code availability

The code used to carry out the analyses is available in Zenodo at https://doi.org/10.5281/zenodo.7888565 (ref. 84).

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Acknowledgements

A.S. and W.F.F. were supported by the University of Maryland, A.W. was supported by a postdoctoral fellowship at the University of Texas Institute for Geophysics, and A.J.F. receives funding from NSERC through DGECR-2022-00141 and RGPIN-2022-03305. A.S. additionally acknowledges training and technical support from the COMBINE programme at the University of Maryland, the James S. McDonnell Foundation and the Society of Fellows at Harvard University. We thank the creators of the Triton dataset—I. Fenton, T. Aze, D. Lazarus, J. Renaudie, A. Dunhill, J. Young and E. Saupe—without whom this study would not have been possible, as well as the micropalaeontologists and scientific ocean drilling staff who generated and contributed to the underlying data; and P. Pearson, J. Partin, S. D’Hondt, M. Leckie, E. Sibert and A. Auderset for scientific discussion of the manuscript.

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  1. These authors contributed equally: Anshuman Swain, Adam Woodhouse

Authors and Affiliations

  1. Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA

    Anshuman Swain

  2. Museum of Comparative Zoology, Harvard University, Cambridge, MA, USA

    Anshuman Swain

  3. Department of Paleobiology, National Museum of Natural History, Washington, DC, USA

    Anshuman Swain

  4. Department of Biology, University of Maryland, College Park, MD, USA

    Anshuman Swain & William F. Fagan

  5. University of Texas Institute for Geophysics, University of Texas at Austin, Austin, TX, USA

    Adam Woodhouse & Christopher M. Lowery

  6. School of Earth Sciences, University of Bristol, Bristol, UK

    Adam Woodhouse

  7. School of Earth and Ocean Sciences, University of Victoria, Victoria, British Columbia, Canada

    Andrew J. Fraass

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Contributions

A.S. and A.W. formulated the study, generated the data and carried out the analyses. All authors contributed to the interpretation of data. A.S. and A.W. conceived and plotted the figures. A.S. wrote the code to carry out analyses. All authors contributed to the writing and editing of the manuscript.

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Extended data figures and tables

Extended Data Fig. 1 Sampling completeness over time.

Sample coverage values calculated for occurrences in different palaeolatitudinal bands for each million year slice for species, ecogroups and morphogroups. Note that small sample sizes limit confidence in estimates left of the blue dotted line (≥ 58 Ma). Also see Extended Data Fig. 2.

Extended Data Fig. 2 Spatially-explicit sampling completeness over time.

(A) Logarithmic scaling of total number of samples, (B) Sample coverage of morphogroups, (C) Sample coverage of ecogroups. Note that, as mentioned in Extended Data Fig. 1, the number of samples for ( ≥ 58 Ma) is quite low and therefore must be treated with caution. In (B) and (C), the palaeolatitudinal bands in a given time bin with less than 5 samples have been removed. Note that blue colors equal high values, whereas red colors correspond to low values.

Extended Data Fig. 3 Cenozoic climate and major climatic events, and specialization indices.

(A) Benthic δ18O and δ13C from Westerhold et al.19, PETM = Paleocene-Eocene Thermal Maximum, EECO = Early Eocene Climatic Optimum, MECO = Middle Eocene Climatic Optimum, EOT = Eocene-Oligocene Transition, OMB = Oligocene-Miocene Boundary, MCO = Miocene Climatic Optimum, INHG = Intensification of Northern Hemisphere Glaciation. (B) Morphogroup Paired difference index (MPDI), (C) Ecogroup Paired difference index (EPDI). Note that blue colors equal high ecogroup richness (B) or specialization (C), whereas red colors correspond to low values of each metric.

Extended Data Fig. 4 Shannon diversity of species, morphogroups, and ecogroups during the Cenozoic.

These metrics were calculated using Shannon entropy of count of each species (in A), morphogroup (in B) or ecogroup (in C) using the vegan package in R. Note that blue colors equal high ecogroup richness (B) or specialization (C), whereas red colors correspond to low values of each metric.

Extended Data Fig. 5 Inflection points.

Logistic function fitted to max-min normalized Morphogroup richness in (A) 66-57 Ma (Residual Standard Error (RSE): 0.07666), (C) 39-29 Ma (RSE: 0.04937), (E) 29-20 Ma (RSE: 0.07999) and (G) 24-14 Ma (RSE: 0.03875) and for max-min normalized Morphogroup Specialization Index (MSI)in (B) 66-57 Ma (RSE: 0.2119), (D) 39-29 Ma (RSE: 0.1722), (F) 29-20 Ma (RSE: 0.1036) and (H) 24-14 Ma (RSE: 0.1191) along with a line joining the predicted points from the logistic fit. The red dotted lines represent the point of inflection in each plot. Low values of RSE in these fits denote good fits.

Extended Data Fig. 6 Spatially averaged functional specialization across important time periods.

(A) Average ESI between 56-50 Ma, (B) Average MSI between 34-23 Ma.

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Swain, A., Woodhouse, A., Fagan, W.F. et al. Biogeographic response of marine plankton to Cenozoic environmental changes. Nature (2024). https://doi.org/10.1038/s41586-024-07337-9

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