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Asthenospheric low-velocity zone consistent with globally prevalent partial melting

Nature Geoscience volume 16, pages 175–181 (2023)Cite this article

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Abstract

The asthenosphere plays a fundamental role in present-day plate tectonics as its low viscosity controls how convection in the mantle below it is expressed at the Earth’s surface above. The origin of the asthenosphere, including the role of partial melting in reducing its viscosity and facilitating deformation, remains unclear. Here we analysed receiver-function data from globally distributed seismic stations to image the lower reaches of the asthenospheric low-seismic-velocity zone. We present globally widespread evidence for a positive seismic-velocity gradient at depths of ~150 km, which represents the base of a particularly low-velocity zone within the asthenosphere. This boundary is most commonly detected in regions with elevated upper-mantle temperatures and is best modelled as the base of a partially molten layer. The presence of the boundary showed no correlation with radial seismic anisotropy, which represents accumulated mantle strain, indicating that the inferred partial melt has no substantial effect on the large-scale viscosity of the asthenosphere. These results imply the presence of a globally extensive, partially molten zone embedded within the asthenosphere, but that low asthenospheric viscosity is controlled primarily by gradual pressure and temperature variations with depth.

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Fig. 1: Globally distributed receiver functions.
Fig. 2: The relationship between receiver-function phases and asthenospheric VSV.
Fig. 3: Modelling the PVG-150 with partial melt.
Fig. 4: The PVG-150, anisotropy, melt and viscosity.
Fig. 5: Interpretation of the observed PVG-150 and PVG-260 mantle velocity gradients.

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Data availability

Seismograms were downloaded from the IRIS Data Management Center (http://ds.iris.edu/ds/nodes/dmc/). The Sp receiver functions for all stations are available as raw data on the Figshare platform (https://doi.org/10.6084/m9.figshare.21706325). Geochemical data were downloaded from GEOROC (http://georoc.mpch-mainz.gwdg.de/Georoc) and are provided as Supplementary Table 1. Velocity model GLAD-M25 (ref. 22) was obtained from E. Bozdag. Velocity models SEMUCB-WM1 (ref. 21) and SEMUCB-UMQ59 were downloaded from the Berkeley Global Seismology Group (http://seismo.berkeley.edu/wiki_br/Main_Page). Velocity Model SAVANI-US42 was from T. W. Becker’s website (http://www-udc.ig.utexas.edu/external/becker/tdata.html). The attenuation model QRFSI12 (ref. 58) was from C. A. Dalton’s website (http://www.geo.brown.edu/research/Dalton/downloads.html); QsADR17 (ref. 60) was from E. Debayle’s website (http://perso.ens-lyon.fr/eric.debayle/). Other velocity models, including CAM2016 (refs. 2,40), S362ANI + M41 and SGLOBE-rani39 were from the IRIS archive (https://ds.iris.edu/ds/products/emc-earthmodels/).

Code availability

All computer codes used for data processing, analysis and plotting are available on request.

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Acknowledgements

We thank E. Bozdag for providing the global adjoint tomography model GLAD-M25, B. Romanowicz for the attenuation model SEMUCB-UMQ, M. Behn for his global flow model, C. A. Dalton for assistance with Perple_X and discussions about partial melting, Z. Ma for help with CRUST1.0 and S. P. Grand for discussions about paper structure. This work was supported by the US National Science Foundation grant EAR-1829401 received by K.M.F.

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Authors and Affiliations

  1. Department of Earth, Environmental and Planetary Sciences, Brown University, Providence, RI, USA

    Junlin Hua, Karen M. Fischer & Greg Hirth

  2. Department of Geological Sciences, Jackson School of Geosciences, The University of Texas at Austin, Austin, TX, USA

    Junlin Hua & Thorsten W. Becker

  3. Institute for Geophysics, Jackson School of Geosciences, The University of Texas at Austin, Austin, TX, USA

    Thorsten W. Becker

  4. Oden Institute for Computational Engineering and Sciences, The University of Texas at Austin, Austin, TX, USA

    Thorsten W. Becker

  5. Department of Earth and Atmospheric Sciences, Cornell University, Ithaca, NY, USA

    Esteban Gazel

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Contributions

J.H. initiated the project and conducted the data analysis, comparison and modelling in the paper. K.M.F. advised on the seismological aspects and overall conclusions of the paper. T.W.B. advised on the geodynamical modelling and seismology results. E.G. advised on its petrological components. G.H. advised on rheological modelling. Interpretation of the results reflects discussions among the authors. The manuscript was written by J.H. with contributions from K.M.F. and other authors.

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Correspondence to Junlin Hua.

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Nature Geoscience thanks Geeth Manthilake, Mingming Jiang and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary Handling Editor: Louise Hawkins, in collaboration with the Nature Geoscience team.

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Extended data

Extended Data Fig. 1 Probabilities of the PVG-150 phase.

a. Example of estimating the probability of the PVG-150 phase from the Sp receiver function at station SMAI (Antarctic Peninsula) in network AI. The solid line shows the receiver function amplitude. The background shows the heat map for the 3,000 perturbed receiver functions. The dashed line shows one of the perturbed receiver functions, whose maximum amplitude is below the threshold amplitude for picking of 0.006 (dotted line). In this case, no PVG-150 phase is picked, although the original stacked receiver function has an amplitude much higher than the threshold. Among all perturbed receiver functions, 96.9% produce a picked PVG-150 phase. The other dotted line shows zero amplitude. b. Map of the depth of the PVG-150 phase for those with probabilities over 0.8 (Fig. 1a). c. Similar to b but for the maximum amplitude of the PVG-150 phase as defined in Extended Data Fig. 4d. d. Map of the probability of the PVG-150 phase obtained from weighted averaging of the probability at surrounding stations. e. Map of the uncertainty of the PVG-150 phase probability represented by the weighted standard deviation among surrounding stations. f. Stations (triangles) with similar PVG-150 phase probability relative to neighboring stations indicated by W3 (Eq. 4) values over 0.4. These stations have the strongest contributions to the average mantle profiles in Fig. 4a and Extended Data Fig. 8. Black triangles indicate stations with the PVG-150 (probability over 0.8), and white triangles show stations without the PVG-150 (probability below 0.2). Background shows average VSV at 110–130 km depths22, as in Fig. 1a.

Extended Data Fig. 2 The PVG-260 phase.

a. Map similar to Fig. 1a, but in this case PVGs were picked between 230 and 350 km depths, which is the potential depth range for X-discontinuities25. The background VSV22 is at 260 km depth. Hotspots61,62,63, subduction zones64 and the rim of cratons represented by the 180 LAB contour in ref. 2 are also plotted. b. Observed receiver functions, similar to Fig. 2a, but binned by VSV at 260 km depth. The PVG-260 phase is present across a wider range of VSV values than the PVG-150.

Extended Data Fig. 3 Relationships between receiver functions and mantle properties.

a-b. Observed receiver functions binned by average VSV at 110–130 km depths beneath the station, similar to Fig. 2a, but based on different reference velocity models: (a) SEMUCB-WM1 (ref. 21) (b) CAM2016 (ref. 2). c-d. Similar to Fig. 2a, with the same reference model22, but using only the 644 continental stations (c) or only the 74 oceanic stations (d). A station was designated as oceanic if its crustal type in CRUST1.0 (ref. 65) is normal oceanic, oceans 3 Myr and younger, melt affected ocean and oceanic plateaus, or oceanic plateau with continental crust. e. The same as Fig. 2a, but with a less saturated color scale to show the NVG phase better. f-h. Similar to Fig. 2a and panels c and d, respectively, but filtered with a 6–100 s bandpass filter instead of 10–100 s. i-j. Similar to Figs. 2a and 3c, respectively, but with stations close to subducting slabs removed. A station was designated as near a subducting slab if it is located within 1° of any slab depth that is shallower than 250 km based on Slab2 (ref. 66). k-l. Similar to Fig. 2a,b but plotted with respect to the average VP/VS at 110–130 km depths. m. Similar to Fig. 2b, but only with PVG-150 probabilities; Lines are for all stations combined, oceanic stations only, and continental stations only. The dashed lines in a-k mark the maximum (minimum for k) value with a clear PVG-150 phase; in c-i they are placed at the same VSV as in Fig. 2a in j at the same VS of 4.39 km/s as in Fig. 3c and in a, b and k at 4.29 km/s, 4.27 km/s and 1.763. The color bar at the bottom of the figure pertains to all panels except e, whose color bar is on its right side.

Extended Data Fig. 4 Properties of the PVG and NVG (LAB) phases.

a. Amplitude ratios between PVG-150 and LAB phases, and between LAB and Moho phases as a function of average VSV at 110–130 km depths22. The Moho amplitude is defined as the maximum receiver function amplitude above 80 km depth for each VSV, the LAB amplitude is the maximum negative amplitude between 50 and 150 km depths, and the PVG-150 amplitude is the maximum value between 100 and 200 km depths in Fig. 2a. b. The distribution of picked PVG-150 depths. c. The distribution of picked LAB depths. d. The PVG-150 amplitude distribution. e. The LAB amplitude distribution. f. The distribution of LVZ thickness from stations with both PVG and LAB phase picks. Lines show the median values for the distributions. All the distributions are based on non-cratonic stations (defined as having average VSV at 110–130 km depths below 4.46 km/s).

Extended Data Fig. 5 The effects of waveform frequency content.

Synthetic Sp receiver functions for the velocity models in c were filtered by 6–100 s (a) and 10–100 s (b) bandpass filters before deconvolution. Colors correspond to velocity gradients from the LVZ to the underlying asthenosphere over 10 to 50 km depth ranges (as shown in c). Horizontal dotted lines show the center of VS discontinuities. Vertical dashed lines mark zero amplitude for receiver functions. The vertical dotted-dashed lines in a & b show the median NVG and PVG amplitudes (Extended Data Fig. 4) of the observed phases when filtered over 10–100 s. This analysis shows that the 10–100 s filter receiver functions are less sensitive both to changes in the velocity gradient depth range and to small variations in the absolute depth of the velocity gradient. The 10–100 s filter was therefore chosen to measure globally-averaged PVG-150 properties. d) The effect of a range of filters on observed receiver function stacks at a single station (ANM, AK network), whose NVG and PVG amplitudes are close to the median of all stations (dashed lines). Colors correspond to receiver functions filtered over different period ranges. Filters containing shorter periods show greater separation between the LAB NVG and the PVG-150, providing additional evidence that the PVG-150 is not a side-lobe.

Extended Data Fig. 6 Ray parameter dependence of the Sp receiver functions.

a. Observed Sp receiver functions binned as a function of ray parameter. b. Synthetic Sp receiver functions for a mantle with an isotropic LVZ (LVZ VS lower than the underlying mantle). c. Synthetic Sp receiver functions where the LVZ is radially anisotropic with ξ equal to 1.1 but has no P anisotropy, and its VVoigt is the same as the underlying mantle. d. The LVZ contains P anisotropy (\(\varphi ^{ - 1} = {{{\mathrm{V}}}}_{{{{\mathrm{PH}}}}}^2/{{{\mathrm{V}}}}_{{{{\mathrm{PV}}}}}^2\) is 0.96) but no S anisotropy, and its Voigt average for P-wave velocity is the same as the underlying mantle. e. The LVZ contains both S (ξ equal to 1.1) and P anistropy (φ−1 equal to 1.04, the value suggested by PREM27 when ξ is 1.1), and the Voigt average for S-wave and P-wave velocities are the same as the underlying mantle. All anisotropic layers in c-e have an η of 0.9, consistent with PREM27 when ξ is 1.1.

Extended Data Fig. 7 Binned synthetic receiver functions.

a. Predicted receiver functions similar to Fig. 3b, but produced from velocities that are those in Fig. 3a minus the poroelasticity effect of partial melt33. b. Similar to a, but velocities also include the effects of a small amount of melt on diffusion creep viscosity10 which strongly influences anelasticity where melting occurs. c. Similar to Fig. 3b, but with a grain size of 1 mm (10 mm for Fig. 3b). d. Similar to a, but the anelasticity is based on ref. 67 to include pre-melting effects, and the poroelasticity effect is not included. Black dashed lines are the same as in Fig. 3.

Extended Data Fig. 8 Mantle property contrasts between areas with and without the PVG-150 phase.

The first three rows show differences in weighted averaged (Eq. 4) profiles of VVoigt (a), ξ (b), attenuation (c) and radial mantle flow velocity (d) for stations with (red lines) and without (blue lines) the PVG-150 phase. The fourth row (e) shows differences in weighted averaged profiles of VVoigt and ξ for different tectonic settings. Transparent areas show one standard deviation for the averaged profiles. Black dashed lines are reference values from PREM27. For VVoigt and ξ, columns are for velocity models SEMUCB-WM1 (ref. 21), CAM2016 (refs. 2,40), SVANI-US42, GLAD-M25 (ref. 22), S362ANI + M41 and SGLOBE-rani39. For attenuation, columns show models SEMUCB-UMQ59, QsADR17 (ref. 60) and QRFSI12 (ref. 58). For radial mantle flow velocity, the first column contains modeled radial flow velocity based on the approach in ref. 43 and the tomographic model in ref. 68, and the second column shows the modeled velocity from ref. 69. For tectonic settings70,71,72,73,74,75,76,77,78,79,80,81,82,83, we considered oceanic regions, continental regions, and regions excluding subducting slabs; these tectonic groups are defined the same as in Extended Data Fig. 3.

Extended Data Fig. 9 1D modeling of radial anisotropy assuming different effects of partial melt.

First and second rows illustrate the 1D models of mantle Couette (a) and Poiseuille flow (b) (1,450 °C cases). The first column shows the solution for mantle flow velocity, and the second column is the equivalent mantle viscosity. The 3rd to 5th columns show predicted ξ for different points in time: early in strain accumulation; when radial anisotropy has developed to resemble the observed profiles; and when anisotropy has reached its saturation level over a broad depth range. The time intervals of strain accumulation for these three stages are labelled in the bottom right corners. The sixth column shows the product of the fourth column convolved with a Gaussian whose standard deviation is 30 km to mimic the potential for reduced vertical resolution in tomography due to broad surface wave sensitivity kernels. The seventh column shows the radial anisotropy when grain size is 1 mm (10 mm for other columns); here the plate motion for Couette flow is set to 10 cm/yr (with a different x-axis), and the longer deformation times are labeled. Same as in Fig. 4b, blue lines are for the case when the effects of partial melt on viscosity are ignored; red dashed lines show when partial melt effects are only characterized by a moderate exponential term34; and red solid lines are the case when a factor of 5 viscosity increase is introduced across 150 km depth to represent stronger partial melting impacts on viscosity above the PVG-150.

Extended Data Fig. 10 Modelled 3D radial anisotropy with localized asthenospheric viscosity layering.

Model results in this figure are all from ref. 43. The first row shows the relative mantle viscosity at 134 km depth, and in the corresponding second and third columns, low-viscosity bands parallel or perpendicular to the mid-ocean ridges are present at depths between 100 and 150 km. Beneath 150 km depth, the reference viscosity distribution (first column) is assumed. The second and third rows show predicted ξ structures at 100 and 200 km depths for viscosity structures in the first row. At 100 km depth, radial anisotropy is increased in the low viscosity bands, and at 200 km depth, radial anisotropy is decreased beneath the low viscosity bands.

Supplementary information

Supplementary Information

Supplementary Methods 1–4, Discussion 1–4 and Figs. 1–3.

Supplementary Table 1

Information about the samples we used to calculate primary magma equilibration conditions

Supplementary Data 1

Global 10–100 s Sp receiver functions analysed in this study

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Hua, J., Fischer, K.M., Becker, T.W. et al. Asthenospheric low-velocity zone consistent with globally prevalent partial melting. Nat. Geosci. 16, 175–181 (2023). https://doi.org/10.1038/s41561-022-01116-9

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