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Spatial pattern of marine oxygenation set by tectonic and ecological drivers over the Phanerozoic

Nature Geoscience volume 16, pages 1020–1026 (2023)Cite this article

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Abstract

Marine redox conditions (that is, oxygen levels) impact a wide array of biogeochemical cycles, but the main controls of marine redox since the start of the Phanerozoic about 538 million years ago are not well established. Here we combine supervised machine learning with shale-hosted trace metal concentrations to reconstruct a near-continuous record of redox conditions in major marine depositional settings. We find synchronously opposite redox changes in upper ocean versus deep shelf and (semi-)restricted basin settings ('redox anticouples', nomen novum) in several multi-million-year intervals, which can be used to track the positions of oxygen-minimum zones and the primary locations of organic burial through time. These changes coincided with biological innovations that altered large-scale oxidant-reductant fluxes (mid-Palaeozoic spread of land plants; Mesozoic plankton revolution) and tectonic upheavals that regulated sea-level elevation (Pangaea amalgamation and break-up). We find that the pre-Devonian deep shelf was buffered at a largely anoxic state probably by dissolved organic matter, switched to a transitional state during the Devonian–Carboniferous interval characterized by the inception of persistent oxygen-minimum zones and subsequently shifted to a redox regime featuring thin oxygen-minimum zones ballasted probably by particulate organic matter. Deep shelf redox changes are correlated with background extinction rates of marine animals, and mass extinctions during major redox transitions generally were more severe.

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Fig. 1: A schematic diagram of shale depositional settings defined in this study.
Fig. 2: Frequencies of depositional settings compared with paleobiotic and I/Ca records.
Fig. 3: Intensity of deep shelf reducing conditions compared with tectonic, sea-level and atmospheric variables.
Fig. 4: Relationship between deep shelf reducing conditions and GERMA.

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Data availability

All data needed to evaluate the conclusions of the manuscript are archived as Supplementary Data Files associated with the online version of this article and also available at figshare (https://doi.org/10.6084/m9.figshare.24139617).

Code availability

Python code for machine learning is archived as supplementary code files associated with the online version of this article and is also available at figshare (https://doi.org/10.6084/m9.figshare.24139617).

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Acknowledgements

This research was supported by the National Natural Science Foundation of China (41888101 to X.W., C.L. and M.Z.; 42293293 to X.W.; 41921002 to M.Z.; 41821001, 41825019, 42130208 to C.L.), the National Key Research and Development Program of China (2022YFF0800100 to M.Z.; 2020YFA0607700 to X.W.) and the 111 Project of China (BP0820004 to C.L.). We gratefully acknowledge J. F. Emmings for constructive comments during review.

Author information

Authors and Affiliations

  1. Key Laboratory of Cenozoic Geology and Environment, Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing, China

    Xiangli Wang

  2. College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing, China

    Xiangli Wang & Maoyan Zhu

  3. State Key Laboratory of Biogeology and Environmental Geology, China University of Geosciences, Wuhan, China

    Thomas J. Algeo

  4. State Key Laboratory of Geological Processes and Mineral Resources, China University of Geosciences, Wuhan, China

    Thomas J. Algeo

  5. Department of Geosciences, University of Cincinnati, Cincinnati, OH, USA

    Thomas J. Algeo

  6. State Key Laboratory of Oil and Gas Reservoir Geology & Exploitation and Institute of Sedimentary Geology, Chengdu University of Technology, Chengdu, China

    Chao Li

  7. Key Laboratory of Deep-time Geography and Environment Reconstruction and Applications of Ministry of Natural Resources, Chengdu University of Technology, Chengdu, China

    Chao Li

  8. International Centre for Sedimentary Geochemistry and Biogeochemistry Research, Chengdu University of Technology, Chengdu, China

    Chao Li

  9. State Key Laboratory of Palaeobiology and Stratigraphy and Centre for Excellence in Life and Paleoenvironment, Nanjing Institute of Geology and Palaeontology, Chinese Academy of Sciences, Nanjing, China

    Maoyan Zhu

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  1. Xiangli Wang
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Contributions

Research design: X.W, C.L. Methodology: X.W. Validation: X.W., T.J.A. Investigation: X.W., T.J.A., C.L., M.Z. Data curation: X.W., T.J.A. Visualization: X.W. Supervision: X.W. Writing, original draft: X.W. Writing, review and editing: X.W., T.J.A., C.L., M.Z.

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Correspondence to Xiangli Wang or Chao Li.

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Nature Geoscience thanks Joseph Emmings and Frantz Ossa Ossa for their contribution to the peer review of this work. Primary Handling Editor(s): James Super, in collaboration with the Nature Geoscience team.

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Extended data

Extended Data Fig. 1 Map of sample locations.

Sample locations.

Extended Data Fig. 2 Paleo-map of reconstructed F′CPOMZ.

Paleogeographic distribution of F′CPOMZ (value represented by the color bar). See definition and calculation of F′CPOMZ in the main text. Reconstruction of tectonic configuration and conversion of coordinates were performed using GPlates PALEOMAP PaleoAtlas35.

Extended Data Fig. 3 Paleo-map of reconstructed F′P-Euxinic.

Paleogeographic distribution of F′P-Euxinic (value represented by the color bar). See definition and calculation of F′P-Euxinic in the main text. Reconstruction of tectonic configuration and conversion of coordinates were performed using GPlates PALEOMAP PaleoAtlas35.

Extended Data Fig. 4 Paleo-map of reconstructed FCPOMZ.

Paleogeographic distribution of FCPOMZ (value represented by the color bar). See definition and calculation of FCPOMZ in the main text. Reconstruction of tectonic configuration and conversion of coordinates were performed using GPlates PALEOMAP PaleoAtlas35.

Extended Data Fig. 5 Paleo-map of reconstructed FP-Euxinic.

Paleogeographic distribution of FP-Euxinic (value represented by the color bar). See definition and calculation of FP-Euxinic in the main text. Reconstruction of tectonic configuration and conversion of coordinates were performed using GPlates.

Extended Data Fig. 6 Paleo-map of reconstructed FBPOMZ.

Paleogeographic distribution of FBPOMZ (value represented by the color bar). See definition and calculation of FBPOMZ in the main text. Reconstruction of tectonic configuration and conversion of coordinates were performed using GPlates PALEOMAP PaleoAtlas35.

Extended Data Fig. 7 Paleo-map of reconstructed FS-Euxinic.

Paleogeographic distribution of FS-Euxinic (value represented by the color bar). See definition and calculation of FS-Euxinic in the main text. Reconstruction of tectonic configuration and conversion of coordinates were performed using GPlates PALEOMAP PaleoAtlas35.

Extended Data Fig. 8 Secular evolution of Fe/Al, Mo/Al, U/Al and V/Al in Phanerozoic shales.

Secular evolution of Fe/Al (wt%/wt%), Mo/Al (ppm/wt%), U/Al (ppm/wt%) and V/Al (ppm/wt%) in Phanerozoic shales. Markers and error bars represent medians and 2SDs of 10,000 bootstrap resampling from spatiotemporally reweighted database (see Materials and Methods). Curves and bands are LOWESS fittings (smoothing factors optimized by 10-fold cross-validation) and prediction intervals (2σ). Raw data are represented by gray dots. Note that y-axes are cropped and thus some raw data fall outside of the graphs.

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Wang, X., Algeo, T.J., Li, C. et al. Spatial pattern of marine oxygenation set by tectonic and ecological drivers over the Phanerozoic. Nat. Geosci. 16, 1020–1026 (2023). https://doi.org/10.1038/s41561-023-01296-y

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