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Instability of the African large low-shear-wave-velocity province due to its low intrinsic density

Nature Geoscience volume 15, pages 334–339 (2022)Cite this article

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Abstract

Seismic observations have revealed two seismic anomalies in the lowermost mantle, one beneath Africa and the other beneath the Pacific Ocean, named large low-shear-wave-velocity provinces. These structures are generally considered to be intrinsically dense thermochemical piles that influence mantle and core processes. However, the controls on their morphology, including their relative height difference and their stability, remain unclear. Here we analyse published global shear-wave tomography models, which show that the African anomaly is about 1,000 km greater in height than the Pacific anomaly. With our numerical simulations, we find that the maximum height a thermochemical pile can reach is more controlled by its density and the surrounding mantle viscosity, and less so by its own viscosity and volume. Comparing these findings suggests that the African anomaly has a relatively lower density and thus may be less stable than the Pacific anomaly, implying the two anomalies have different compositions, dynamics and evolution histories.

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Fig. 1: Depth profiles of the lateral average shear-wave velocity anomaly (\(\overline {\mathrm{dV}}_{\rm{s}}\)) at four vertical cross-sectional locations through the LLSVPs.
Fig. 2: The effects of volume and buoyancy number of pile materials and background mantle viscosity on the height of piles.
Fig. 3: Effects of model parameters on the height of piles.
Fig. 4: The height of piles as a function of pile buoyancy number and background mantle viscosity.

Data availability

All seismic tomography models are downloaded from the SubMachine59 website. The seismic data and all other source data about geodynamic modelling results presented in this study are available at https://figshare.com/projects/Yuan_Li_2022_NG/129185. The seismic data include 17 global shear-wave models, including TX20112, GyPSuM-S15, SAW642ANb16, SEMUCB-WM117, SEMum18, SGLOBE-rani19, TX201520, SEISGLOB121, SEISGLOB222, HMSL-S0623, PRI-S0524, SP12RTS-S25, SPani-S26, S20RTS27, S362ANI+M28, S40RTS29 and SAVANI30.

Code availability

The author’s modified 2D Citcom code used in this study is available from https://figshare.com/projects/Yuan_Li_2022_NG/129185. The CitcomCU code is available at https://geodynamics.org/cig/software/citcomcu/.

References

  1. Garnero, E. J., McNamara, A. K. & Shim, S. H. Continent-sized anomalous zones with low seismic velocity at the base of Earth’s mantle. Nat. Geosci. 9, 481–489 (2016).

    Article  Google Scholar 

  2. Grand, S. P. Mantle shear-wave tomography and the fate of subducted slabs. Philos. Trans. R. Soc. A 360, 2475–2491 (2002).

    Article  Google Scholar 

  3. Li, X.-D. & Romanowicz, B. Global mantle shear velocity model developed using nonlinear asymptotic coupling theory. J. Geophys. Res. Solid Earth 101, 22245–22272 (1996).

    Article  Google Scholar 

  4. Ritsema, J., van Heijst, H. J. & Woodhouse, J. H. Global transition zone tomography. J. Geophys. Res. 109, B02302 (2004).

    Google Scholar 

  5. Li, M., Zhong, S. & Olson, P. Linking lowermost mantle structure, core–mantle boundary heat flux and mantle plume formation. Phys. Earth Planet. Inter. 277, 10–29 (2018).

    Article  Google Scholar 

  6. Olson, P. & Amit, H. Magnetic reversal frequency scaling in dynamos with thermochemical convection. Phys. Earth Planet. Inter. 229, 122–133 (2014).

    Article  Google Scholar 

  7. Cottaar, S. & Lekic, V. Morphology of seismically slow lower-mantle structures. Geophys. J. Int. 207, 1122–1136 (2016).

    Article  Google Scholar 

  8. He, Y. & Wen, L. Structural features and shear-velocity structure of the ‘Pacific Anomaly’. J. Geophys. Res. Solid Earth 114, B02309 (2009).

    Google Scholar 

  9. Lekic, V., Cottaar, S., Dziewonski, A. & Romanowicz, B. Cluster analysis of global lower mantle tomography: a new class of structure and implications for chemical heterogeneity. Earth Planet. Sci. Lett. 357–358, 68–77 (2012).

    Article  Google Scholar 

  10. Ni, S. & Helmberger, D. V. Ridge-like lower mantle structure beneath South Africa. J. Geophys. Res. 108, 2094 (2003).

    Article  Google Scholar 

  11. Wang, Y. & Wen, L. Geometry and P and S velocity structure of the ‘African Anomaly’. J. Geophys. Res. Solid Earth 112, B05313 (2007).

    Article  Google Scholar 

  12. Ni, S., Tan, E., Gurnis, M. & Helmberger, D. Sharp sides to the African superplume. Science 296, 1850–1852 (2002).

    Article  Google Scholar 

  13. Rawlinson, N., Fichtner, A., Sambridge, M. & Young, M. K. in Advances in Geophysics, Vol. 55 (ed Dmowska, R.) Ch. 1 (Elsevier, 2014).

  14. Burke, K., Steinberger, B., Torsvik, T. H. & Smethurst, M. A. Plume generation zones at the margins of large low shear velocity provinces on the core–mantle boundary. Earth Planet. Sci. Lett. 265, 49–60 (2008).

    Article  Google Scholar 

  15. Simmons, N. A., Forte, A. M., Boschi, L. & Grand, S. P. GyPSuM: a joint tomographic model of mantle density and seismic wave speeds. J. Geophys. Res. Solid Earth 115, B12310 (2010).

    Article  Google Scholar 

  16. Panning, M. P., Lekić, V. & Romanowicz, B. A. Importance of crustal corrections in the development of a new global model of radial anisotropy. J. Geophys. Res. Solid Earth 115, B12325 (2010).

    Article  Google Scholar 

  17. French, S. W. & Romanowicz, B. A. Whole-mantle radially anisotropic shear velocity structure from spectral-element waveform tomography. Geophys. J. Int. 199, 1303–1327 (2014).

    Article  Google Scholar 

  18. Lekić, V. & Romanowicz, B. Inferring upper-mantle structure by full waveform tomography with the spectral element method. Geophys. J. Int. 185, 799–831 (2011).

    Article  Google Scholar 

  19. Chang, S. J., Ferreira, A. M. G., Ritsema, J., van Heijst, H. J. & Woodhouse, J. H. Joint inversion for global isotropic and radially anisotropic mantle structure including crustal thickness perturbations. J. Geophys. Res. Solid Earth 120, 4278–4300 (2015).

    Article  Google Scholar 

  20. Lu, C. & Grand, S. P. The effect of subducting slabs in global shear wave tomography. Geophys. J. Int. 205, 1074–1085 (2016).

    Article  Google Scholar 

  21. Durand, S., Debayle, E., Ricard, Y. & Lambotte, S. Seismic evidence for a change in the large-scale tomographic pattern across the D′′ layer. Geophys. Res. Lett. 43, 7928–7936 (2016).

    Article  Google Scholar 

  22. Durand, S., Debayle, E., Ricard, Y., Zaroli, C. & Lambotte, S. Confirmation of a change in the global shear velocity pattern at around 1,000 km depth. Geophys. J. Int. 211, 1628–1639 (2017).

    Article  Google Scholar 

  23. Houser, C., Masters, G., Shearer, P. & Laske, G. Shear and compressional velocity models of the mantle from cluster analysis of long-period waveforms. Geophys. J. Int. 174, 195–212 (2008).

    Article  Google Scholar 

  24. Montelli, R., Nolet, G., Dahlen, F. A. & Masters, G. A catalogue of deep mantle plumes: new results from finite-frequency tomography. Geochem. Geophys. Geosyst. 7, Q11007 (2006).

    Article  Google Scholar 

  25. Koelemeijer, P., Ritsema, J., Deuss, A. & van Heijst, H. J. SP12RTS: a degree-12 model of shear- and compressional-wave velocity for Earth’s mantle. Geophys. J. Int. 204, 1024–1039 (2016).

    Article  Google Scholar 

  26. Tesoniero, A., Auer, L., Boschi, L. & Cammarano, F. Hydration of marginal basins and compositional variations within the continental lithospheric mantle inferred from a new global model of shear and compressional velocity. J. Geophys. Res. Solid Earth 120, 7789–7813 (2015).

    Article  Google Scholar 

  27. Ritsema, J., van Heijst, H. J. & Woodhouse, J. H. Complex shear wave velocity structure imaged beneath Africa and Iceland. Science 286, 1925–1931 (1999).

    Article  Google Scholar 

  28. Moulik, P. & Ekström, G. An anisotropic shear velocity model of the Earth’s mantle using normal modes, body waves, surface waves and long-period waveforms. Geophys. J. Int. 199, 1713–1738 (2014).

    Article  Google Scholar 

  29. Ritsema, J., Deuss, A., van Heijst, H. J. & Woodhouse, J. H. S40RTS: a degree-40 shear-velocity model for the mantle from new Rayleigh wave dispersion, teleseismic traveltime and normal-mode splitting function measurements. Geophys. J. Int. 184, 1223–1236 (2011).

    Article  Google Scholar 

  30. Auer, L., Boschi, L., Becker, T. W. & Giardini, D. Savani: a variable resolution whole-mantle model of anisotropic shear velocity variations based on multiple data sets. J. Geophys. Res. Solid Earth 119, 3006–3034 (2014).

    Article  Google Scholar 

  31. Li, M. & Zhong, S. The source location of mantle plumes from 3D spherical models of mantle convection. Earth Planet. Sci. Lett. 478, 47–57 (2017).

    Article  Google Scholar 

  32. Tackley, P. J. in The Core–Mantle Boundary Region Vol. 28 (eds Gurnis, M. et al.) 231–253 (American Geophysical Union, 1998).

  33. McNamara, A. K. & Zhong, S. Thermochemical structures beneath Africa and the Pacific Ocean. Nature 437, 1136–1139 (2005).

    Article  Google Scholar 

  34. Zhang, N., Zhong, S., Leng, W. & Li, Z. X. A model for the evolution of the Earth’s mantle structure since the Early Paleozoic. J. Geophys. Res. Solid Earth 115, B06401 (2010).

    Article  Google Scholar 

  35. Bull, A. L., McNamara, A. K. & Ritsema, J. Synthetic tomography of plume clusters and thermochemical piles. Earth Planet. Sci. Lett. 278, 152–162 (2009).

    Article  Google Scholar 

  36. Davies, D. R. et al. Reconciling dynamic and seismic models of Earth’s lower mantle: the dominant role of thermal heterogeneity. Earth Planet. Sci. Lett. 353–354, 253–269 (2012).

    Article  Google Scholar 

  37. Davaille, A. & Romanowicz, B. Deflating the LLSVPs: bundles of mantle thermochemical plumes rather than thick stagnant “piles”. Tectonics 39, e2020TC006265 (2020).

    Article  Google Scholar 

  38. Hosseini, K. et al. Global mantle structure from multifrequency tomography using P, PP and P-diffracted waves. Geophys. J. Int. 220, 96–141 (2020).

    Article  Google Scholar 

  39. Davaille, A. Simultaneous generation of hotspots and superwells by convection in a heterogeneous planetary mantle. Nature 402, 756–760 (1999).

    Article  Google Scholar 

  40. Davaille, A., Le Bars, M. & Carbonne, C. Thermal convection in a heterogeneous mantle. Convection thermique dans un manteau hétérogène. C. R. Geosci. 335, 141–156 (2003).

    Article  Google Scholar 

  41. Jellinek, A. M. & Manga, M. Links between long-lived hot spots, mantle plumes, D″, and plate tectonics. Rev. Geophys. 42, RG3002 (2004).

    Article  Google Scholar 

  42. Kumagai, I., Davaille, A. & Kurita, K. On the fate of thermally buoyant mantle plumes at density interfaces. Earth Planet. Sci. Lett. 254, 180–193 (2007).

    Article  Google Scholar 

  43. Le Bars, M. & Davaille, A. Whole layer convection in a heterogeneous planetary mantle. J. Geophys. Res. 109, B03403 (2004).

    Google Scholar 

  44. Moresi, L. N. & Solomatov, V. S. Numerical investigation of 2D convection with extremely large viscosity variations. Phys. Fluids 7, 2154–2162 (1995).

    Article  Google Scholar 

  45. Langemeyer, S. M., Lowman, J. P. & Tackley, P. J. The dynamics and impact of compositionally originating provinces in a mantle convection model featuring rheologically obtained plates. Geophys. J. Int. 220, 1700–1716 (2020).

    Article  Google Scholar 

  46. Li, M., McNamara, A. K., Garnero, E. J. & Yu, S. Compositionally-distinct ultra-low velocity zones on Earth’s core–mantle boundary. Nat. Commun. 8, 177 (2017).

    Article  Google Scholar 

  47. Mitrovica, J. X. & Forte, A. M. A new inference of mantle viscosity based upon joint inversion of convection and glacial isostatic adjustment data. Earth Planet. Sci. Lett. 225, 177–189 (2004).

    Article  Google Scholar 

  48. Steinberger, B. & Calderwood, A. R. Models of large-scale viscous flow in the Earth’s mantle with constraints from mineral physics and surface observations. Geophys. J. Int. 167, 1461–1481 (2006).

    Article  Google Scholar 

  49. Davaille, A. & Jaupart, C. Transient high-Rayleigh-number thermal convection with large viscosity variations. J. Fluid Mech. 253, 141–166 (1993).

    Article  Google Scholar 

  50. Le Bars, M. & Davaille, A. Large interface deformation in two-layer thermal convection of miscible viscous fluids. J. Fluid Mech. 499, 75–110 (2004).

    Article  Google Scholar 

  51. Huang, C., Leng, W. & Wu, Z. Iron-spin transition controls structure and stability of LLSVPs in the lower mantle. Earth Planet. Sci. Lett. 423, 173–181 (2015).

    Article  Google Scholar 

  52. Tan, E. & Gurnis, M. Metastable superplumes and mantle compressibility. Geophys. Res. Lett. 32, L20307 (2005).

    Article  Google Scholar 

  53. Simmons, N. A., Forte, A. M. & Grand, S. P. Thermochemical structure and dynamics of the African superplume. Geophys. Res. Lett. 34, L02301 (2007).

    Article  Google Scholar 

  54. Burke, K. & Gunnell, Y. The African Erosion Surface: A Continental-Scale Synthesis of Geomorphology, Tectonics, and Environmental Change Over the Past 180 Million Years (Geological Society of America, 2008).

  55. Doucet, L. S. et al. Distinct formation history for deep-mantle domains reflected in geochemical differences. Nat. Geosci. 13, 511–515 (2020).

    Article  Google Scholar 

  56. Farrell, K. A. O. & Lowman, J. P. Emulating the thermal structure of spherical shell convection in plane-layer geometry mantle convection models. Phys. Earth Planet. Inter. 182, 73–84 (2010).

    Article  Google Scholar 

  57. Tackley, P. J. & King, S. D. Testing the tracer ratio method for modeling active compositional fields in mantle convection simulations. Geochem. Geophys. Geosyst. 4, 8302 (2003).

    Article  Google Scholar 

  58. Zhong, S. Constraints on thermochemical convection of the mantle from plume heat flux, plume excess temperature, and upper mantle temperature. J. Geophys. Res. Solid Earth 111, B04409 (2006).

    Article  Google Scholar 

  59. Hosseini, K. et al. SubMachine: web-based tools for exploring seismic tomography and other models of Earth’s deep interior. Geochem. Geophys. Geosyst. 19, 1464–1483 (2018).

    Article  Google Scholar 

Download references

Acknowledgements

We are grateful to the extensive discussions and comments on the manuscript by E. Garnero. We also thank K. Hosseini for SubMachine datasets and Y. Wang and S. Yu for valuable comments. The numerical models were performed on the Agave cluster at Arizona State University. Both Q.Y. and M.L. are supported by National Science Foundation grant numbers EAR-1849949 and EAR-1855624.

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Authors and Affiliations

  1. School of Earth and Space Exploration, Arizona State University, Tempe, AZ, USA

    Qian Yuan & Mingming Li

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  1. Qian Yuan
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M.L. conceived the project and Q.Y. performed all experiments. Both authors analysed the data and wrote the manuscript.

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Correspondence to Qian Yuan.

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Nature Geoscience thanks Wei Leng, Neala Creasy and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary Handling Editors: Louise Hawkins and Stefan Lachowycz, in collaboration with the Nature Geoscience team.

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Extended data

Extended Data Fig. 1 Cross-section locations through two LLSVPs used for depth profiles of the averaged Vs anomaly.

A1-A10 and B1-B5 are for African LLSVP while C1-C5 and D1-D13 performed for Pacific LLSVP. A4, B4 and C2, D6 are the four cross-sections that were found bear the maximum height for African and Pacific LLSVP, respectively. They are respectively named as AA´, BB´ and CC´, DD´ in the main text. All section data are downloaded from the SubMachine website59. The 17 global S-wave models are TX20112, GyPSuM-S15, SAW642ANb16, SEMUCB-WM117, SEMum18, SGLOBE-rani19, TX201520, SEISGLOB121, SEISGLOB222, HMSL-S0623, PRI-S0524, SP12RTS-S25, SPani-S26, S20RTS27, S362ANI + M28, S40RTS29, SAVANI30. This figure was generated using GMT software version 6.0.0 (https://www.generic-mapping-tools.org/).

Extended Data Fig. 2 Depth profiles of the \(\overline{\mathrm{dV}}_{\rm{s}}\) (gray dashed line) and their gradient (blue lines) at 2 selected vertical cross-section locations through the African LLSVP.

a, c, the gradient of the \(\overline{\mathrm{dV}}_{\rm{s}}\) as a function of depth for African A4 and B4 vertical cross-sections as shown in Extended Data Fig. 1. b, d, similar to panel a and c, but only the negative values of dVs are used when calculating the \(\overline {\mathrm{dV}}_{\rm{s}}\). Below the turning point (yellow filled circle) the gradient is mostly positive (shown by the vertical red dotted lines), while above which the gradient is fluctuating around 0 (shown by the vertical black dotted lines). The gradient is defined by the change of \(\overline{\mathrm{dV}}_{\rm{s}}\) over the change of radius.

Extended Data Fig. 3 Depth profiles of the \(\overline{\mathrm{dV}}_{\rm{s}}\) (gray dashed line) and its gradient (blue line) at 2 selected vertical cross-section locations through the Pacific LLSVP.

a, c, the gradient of the \(\overline{\mathrm{dV}}_{\rm{s}}\) as a function of depth for Pacific C2 and D6 vertical cross-sections as shown in Extended Data Fig. 1. b, d, similar to panel a and c, but only the negative values of dVs are used when calculating the \(\overline{\mathrm{dV}}_{\rm{s}}\). Below the turning point (yellow filled circle) the gradients are mostly positive (shown by the vertical red dotted lines), while above which the gradient is fluctuating around 0 (shown by the vertical black dotted lines). The gradient is defined by the change of \(\overline{\mathrm{dV}}_{\rm{s}}\) over the change of radius.

Extended Data Fig. 4 Depth profiles of the \(\overline{\mathrm{dV}}_{\rm{s}}\) at 15 vertical cross-section locations through the African LLSVP.

a, the horizontally averaged \(\overline{\mathrm{dV}}_{\rm{s}}\) as a function of depth for the 10 vertical cross-sections as shown in Extended Data Fig. 1. b, similar to panel a, but only the negative values of dVs are used when calculating the \(\overline{\mathrm{dV}}_{\rm{s}}\). c, the horizontally averaged \(\overline{\mathrm{dV}}_{\rm{s}}\) as a function of depth for the 5 vertical cross-sections as shown in Extended Data Fig. 1. d, similar to panel c, but only the negative values of dVs are used when calculating the \(\overline{\mathrm{dV}}_{\rm{s}}\). The yellow filled circle marks the turning point we defined as the maximum height in main text.

Extended Data Fig. 5 Depth profiles of the \(\overline{\mathrm{dV}}_{\rm{s}}\) at 18 vertical cross-section locations through the Pacific LLSVP.

a, the horizontally averaged \(\overline{\mathrm{dV}}_{\rm{s}}\) as a function of depth for the 5 vertical cross-sections as shown in Extended Data Fig. 1. b, similar to panel a, but only the negative values of dVs are used when calculating the \(\overline{\mathrm{dV}}_{\rm{s}}\). c, the horizontally averaged \(\overline{\mathrm{dV}}_{\rm{s}}\) as a function of depth for the 13 vertical cross-sections as shown in Extended Data Fig. 1. d, similar to panel c, but only the negative values of dVs are used when calculating the \(\overline{\mathrm{dV}}_{\rm{s}}\). The yellow filled circle marks the turning point we defined as the maximum height in main text.

Extended Data Fig. 6 The effects of model parameters on the height of piles revealed by the field of residual buoyancy (with the horizontal averaged removed).

a, the reference case. From b to f, only one parameter is modified from the reference case, they are respectively the initial volume of pile materials (11%) (b), pile viscosity (30 times higher than the reference run) (c), 25 times higher background mantle viscosity (d), a larger buoyancy number of 1.2 (e), and smaller buoyancy number of 0.6 (f). Green curves show pile edges.

Extended Data Fig. 7 The effects of model parameters on the height of piles revealed by the deviatoric stress.

All cases here from a-f are the same corresponding to that in Extended Data Fig. 6. The green curves show the pile edges.

Extended Data Fig. 8 Pile height as a function of pile buoyancy number and background mantle viscosity for 450 individual models.

Gray crosses indicate the cases that the thermochemical piles are not stable.

Extended Data Fig. 9 The effect of different geometry on pile height.

a and b show the composition and temperature fields respectively for a model of same parameters with the reference case but with aspect ratio of 6. c, Blue solid circles show the height of pile from models with aspect ratio of 1, and orange solid circles show the height of pile from models with aspect ratio of 6. The error bar of each calculation refers to one standard deviation of the maximum heights from different timesteps when the model reached steady state. The composition field in panel a shows pure background mantle materials (Beff = 0), pure pile materials (Beff = 0.8), or a mixture between them (intermediate values).

Extended Data Fig. 10 The setup and height of piles in 3D models.

(a), snapshot of the compositional field in the 3D reference case whose parameters are the same as the 2D reference case. Only the lowermost 1,000 km of the model domain is shown. (b-f), the laterally averaged composition as a function of depth (represented by the height above the CMB) and time for the 3D reference model (b), and other 3D models with 4% more initial pile volume (c), 100 times higher pile viscosity (d), 20 times higher background mantle viscosity (e), and a smaller buoyancy number of 0.5 (f). The black curves show the contours at average composition of 0.05, which are defined as the top of the thermochemical piles. The yellow curve in (b) are the same contour of a higher resolution case, whose parameters are the same to the 3D reference model.

Supplementary information

Supplementary Information

Supplementary Figs. 1–4 and Table 1.

Supplementary Data 1

Physical parameters and results for all cases in this study.

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Yuan, Q., Li, M. Instability of the African large low-shear-wave-velocity province due to its low intrinsic density. Nat. Geosci. 15, 334–339 (2022). https://doi.org/10.1038/s41561-022-00908-3

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