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Rapid emergence of subaerial landmasses and onset of a modern hydrologic cycle 2.5 billion years ago

Naturevolume 557pages545548 (2018) | Download Citation


The history of the growth of continental crust is uncertain, and several different models that involve a gradual, decelerating, or stepwise process have been proposed1,2,3,4. Even more uncertain is the timing and the secular trend of the emergence of most landmasses above the sea (subaerial landmasses), with estimates ranging from about one billion to three billion years ago5,6,7. The area of emerged crust influences global climate feedbacks and the supply of nutrients to the oceans8, and therefore connects Earth’s crustal evolution to surface environmental conditions9,10,11. Here we use the triple-oxygen-isotope composition of shales from all continents, spanning 3.7 billion years, to provide constraints on the emergence of continents over time. Our measurements show a stepwise total decrease of 0.08 per mille in the average triple-oxygen-isotope value of shales across the Archaean–Proterozoic boundary. We suggest that our data are best explained by a shift in the nature of water–rock interactions, from near-coastal in the Archaean era to predominantly continental in the Proterozoic, accompanied by a decrease in average surface temperatures. We propose that this shift may have coincided with the onset of a modern hydrological cycle owing to the rapid emergence of continental crust with near-modern average elevation and aerial extent roughly 2.5 billion years ago.

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This work was supported by National Science Foundation (NSF) grant EAR1447337 and by the University of Oregon. N.D. was supported by NSF grant EAR1502591. A.B. was supported by National Sciences and Engineering Research Council (NSERC) Discovery and Accelerator grants. We thank P. Hoffman, S. Mertanen and D. Evans for discussions about Precambrian palaeogeography and environmental changes; K. Johnson for technical help with vacuum lines; and O. Melnik for help with programming.

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Nature thanks C. Hawkesworth and the other anonymous reviewer(s) for their contribution to the peer review of this work.

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  1. Department of Earth Sciences, University of Oregon, Eugene, OR, USA

    • I. N. Bindeman
    • , D. O. Zakharov
    • , J. Palandri
    •  & G. J. Retallack
  2. Department of Earth Sciences, University of Geneva, Geneva, Switzerland

    • N. D. Greber
  3. Origins Laboratory, Department of the Geophysical Sciences and Enrico Fermi Institute, The University of Chicago, Chicago, IL, USA

    • N. Dauphas
  4. Department of Geology, University of Johannesburg, Auckland Park, South Africa

    • A. Hofmann
    •  & A. Bekker
  5. Department of Geology, Pomona College, Claremont, CA, USA

    • J. S. Lackey
  6. Department of Earth Sciences, University of California, Riverside, CA, USA

    • A. Bekker


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I.N.B. conceived the study and wrote the paper; D.O.Z., J.P. and I.N.B. built the purification line and collected the data; N.D.G. and N.D. provided composite shale samples studied previously for titanium isotopes; A.B., A.H. and G.J.R. provided samples; J.S.L. performed major- and trace-element analyses; I.N.B. and N.D. discussed the inversion approach and I.N.B. implemented the model; D.O.Z. contributed to statistical treatment; A.B., N.D., N.D.G. and G.J.R. contributed to discussions on Precambrian environments and crustal evolution. All authors contributed to writing and editing the paper.

Competing interests

The authors declare no competing interests.

Corresponding author

Correspondence to I. N. Bindeman.

Extended data figures and tables

  1. Extended Data Fig. 1 Comparison of isotopic and key elemental ratios of the shales studied here, illustrating the relative constancy of the composition of the exposed crust that is undergoing weathering, and in particular proportion of exposed mafic versus silicic rocks.

    See, for example, refs 1,33. The δ49Ti data are from ref. 8, which used a large dataset that included many of the samples studied here. The elemental data are from Extended Data Table 3 and ref. 14. Variation in the composition of the exposed crust cannot explain the oxygen-isotope trends that we have identified here.

  2. Extended Data Fig. 2 Distribution density plot for the samples studied here.

    Data from Fig. 1.

  3. Extended Data Fig. 3 Calculating the δ′18O and Δ′17O values of the weathering products of shales.

    Solving a system of three unknowns (for example, the temperature of alteration and the values of Δ′17O and δ′18O along the MWL) in three equations (Supplementary Information equations (1), (5) and (6)) follows these steps: the results of Supplementary Information equations (1), (5) and (6) are substituted sequentially into each other until one unknown is left. This results in a function with respect to temperature (T, a single parameter) to solve: y = 0 = 36.323T − 23.33T2 + 0.00264T3 − 1.38 × 107. This is a third-order polynomial equation that has three roots; we solve for roots in a realistic temperature range to obtain the temperature and δ18OW. The concave blue curve originating from a point on the MWL shows isotope fractionation between shale and water with the indicated temperatures of equilibration. The grey curve represents a mixing line between detrital and weathering products of the indicated proportions, computed using the CIA.

  4. Extended Data Fig. 4 Evaluating the sensitivity of reconstructed δ18OW and temperature values to variations in the input parameters.

    We show here the effects of varying the proportion of quartz (Q) in shales (±20%), the CIA (±10 units), and Δ′17O (D170) (±0.01‰), the latter occurring naturally owing to, for instance, silicification.

  5. Extended Data Fig. 5 Calculated temperature, δ18OW and Δ17OW values plotted against age of shales.

    a, δ18OW versus age; b, temperature versus age; c, Δ17OW versus age; d, δ18OW versus temperature. These values are based on the solution of three equations with three input parameters: δ′18Oshale, δ′17Oshale and the proportion of quartz (see Extended Data Fig. 3). Sensitivity analysis is provided in Extended Data Fig. 4. Most measurements yielded solved roots (plus signs within symbols); when equations could not be solved, small variations in the input parameters (Extended Data Table 1) allowed us to find roots. In particular, correcting for secondary silicification (see Extended Data Table 1) by decreasing Δ′17Oshale by 0.01‰ to 0.08‰ along the silicification line allowed us to find roots in all but two cases. Note that the overall calculated δ18OW and temperature ranges agree with modern and recent values for surface, diagenetic, basinal and pore waters measured in drillholes21. Note also that the absolute calculated values for the temperature of water–rock interaction (weathering) and δ18OW depend on the assumed isotopic fractionations in Extended Data Fig. 6; however, given that these values solved within realistic bounds, the fractionations of ref. 19 and the MWL defined in ref. 17 are probably well constrained and calibrated in absolute triple-oxygen-isotope space. The lowest δ18OW and temperature are computed for recent clay samples from Antarctica, and for 2.5–2.2-Gyr-old synglacial Palaeoproterozoic shales, confirming the participation of low-δ18Ow synglacial waters in diagenesis, as proposed previously14. The highest recent temperature and δ18OW values are for Palaeocene–Eocene (55-million-year-old) thermal maximum shales (ref. 34 and Extended Data Table 1). eg, Interquartile range statistics and running averages for the parameters computed in ad.

  6. Extended Data Fig. 6 Quartz/water, illite/water and bulk-shale/water 18O/16O fractionation factors.

    The quartz/water and illite/water 1,000lnα (18O/16O) fractionation factors are based on refs 19,35. The bulk-shale/water 1,000lnα (18O/16O) fractionation factors are based on the assumption that bulk shale comprises 70% illite and 30% quartz (that is, Q = 0.3). The blue line (for quartz/water fractionation) corresponds to Supplementary Information equation (2) and equation (9) in ref. 19. The green line (for illite/water fractionation) is the best-fit second-order polynomial with two fit coefficients based on the equation in ref. 35 that includes three fit coefficients. We used these coefficients to solve equations for bulk-shale/water triple-oxygen-isotope fractionations according to the proportion of quartz (determined through X-ray-diffraction; Extended Data Table 2).

  7. Extended Data Fig. 7 Chemical index of alteration (CIA) plotted against time.

    CIA = Al2O3/(Al2O3 + CaO + Na2O + K2O)mol. Data are taken from this work (triangles), ref. 14 (diamonds), and literature data (circles).

  8. Extended Data Table 1 Triple-oxygen-isotope analyses of the shale samples used here
  9. Extended Data Table 2 Quantitative XRD data for a selection of studied shales
  10. Extended Data Table 3 New XRF analyses of samples studied here

Supplementary information

  1. Supplementary Information

    This file contains Supplementary Methods, Data Availability Statement and Supplementary References.

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