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Distinct slab interfaces imaged within the mantle transition zone


Oceanic lithosphere descends into Earth’s mantle at subduction zones and drives material exchange between Earth’s surface and its deep interior. The subduction process creates chemical and thermal heterogeneities in the mantle, with the strongest gradients located at the interfaces between subducted slabs and the surrounding mantle. Seismic imaging of slab interfaces is key to understanding slab compositional layering, deep-water cycling and melting, yet the existence of slab interfaces below 200 km remains unconfirmed. Here, we observe two sharp and slightly dipping seismic discontinuities within the mantle transition zone beneath the western Pacific subduction zone that coincide spatially with the upper and lower bounds of the high-velocity slab. Based on a multi-frequency receiver function waveform modelling, we found the upper discontinuity to be consistent with the Mohorovičić discontinuity of the subducted oceanic lithosphere in the mantle transition zone. The lower discontinuity could be caused by partial melting of sub-slab asthenosphere under hydrous conditions in the seaward portion of the slab. Our observations show distinct slab–mantle boundaries at depths between 410 and 660 km, deeper than previously observed, suggesting a compositionally layered slab and high water contents beneath the slab.

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Fig. 1: Map of the subduction region in northeast China.
Fig. 2: Slab interfaces imaged at MTZ depths are consistent with slab geometry inferred from seismicity and full-waveform tomography images.
Fig. 3: Velocity perturbations across phases X1 and X2 inferred from multi-frequency waveform modelling are large, around 4–6%.
Fig. 4: Observations show that the slab interfaces can persist to MTZ depths.

Data availability

Seismic data from CSN were provided by the Data Management Center of China National Seismic Network at Institute of Geophysics, China Earthquake Administration (,, registration is required to download the data, in Chinese). The NECESSArray data were downloaded through the Incorporated Research Institutions for Seismology ( Waveforms of the NECsaids data are deposited in the Seismic Array Laboratory, Institute of Geology and Geophysics, Chinese Academy of Sciences (, and can be downloaded via The Seismic Array Laboratory will make the NECsaids Array data publicly available from October 2021 (three years after the completion of the NECsaids project). In addition, the raw multi-frequency (with Gaussian low-pass filters of 0.5, 0.75, 1.0 or 1.5) receiver function waveform data (2.7Gb) obtained in this study can be downloaded either from (World Data System for Geophysics; or from

Code availability

The RF CCP stacking code was downloaded from The other codes used in this paper are available upon request from the corresponding authors.


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We thank L. Chen, H. Kawakatsu, T.-R. A. Song, S. P. Grand, J. Yang and J. Hu for numerous discussions during this work. We thank all the people who installed and service the NECsaids array. We also thank V. Lambert and P. Adamek for linguistic suggestions. This study was supported by the Strategic Priority Research Program (B) of the Chinese Academy of Sciences (grant number XDB18000000) and the National Natural Science Foundation of China (grant numbers 91958209, 41974057, 41130316 and 41630209). J.B. was supported by the National Science Foundation’s Collaborative Study of Earth’s Deep Interior (EAR-1161046 and EAR-2009935).

Author information




X.W. and Q-F.C. designed the research. X.W. conducted the seismic analysis. X.W., Q-F.C., F.N., J.B. and L.L. contributed to the interpretation of seismic observations. X.W. wrote the manuscript, and all co-authors discussed the results and commented on the manuscript.

Corresponding authors

Correspondence to Qi-Fu Chen or Fenglin Niu.

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The authors declare no competing interests.

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Peer review information Primary Handling Editors: Stefan Lachowycz; Melissa Plail.

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Extended data

Extended Data Fig. 1 Seismic stations and earthquakes used in this study.

a, Study region and locations of broadband seismic stations (triangles) used in this study. The thick red lines give the location of the profiles shown in Fig. 2 in the main text. The black lines (numbered from 1 to 10) give the location of the profiles shown in Extended Data Figs. 2 and 3, to demonstrate the non-uniqueness of the phases X1 and X2. Black dashed curves show the Wadati-Benioff zone obtained from the distribution of intermediate/deep earthquakes. The red symbols indicate the Cenozoic active volcanoes in this region. b, Spatial distribution of earthquakes used in receiver function study, colored by their back azimuth. c, Histogram shows the number of receiver functions from different back azimuth.

Extended Data Fig. 2 Comparison of CCP stacking images and the tomography studies.

Receiver function common conversion point stacking images along the five profiles (1-5) shown in Extended Data Fig. 1. For comparison, the corresponding full-waveform tomographic images from Tao et al.4 are shown. The subducting Pacific slab is highlighted by positive velocity anomaly contours.

Extended Data Fig. 3 Comparison of CCP stacking images and the tomography studies.

Same as Extended Data Fig. 2, but for five profiles (6-10) shown in Extended Data Fig. 1.

Extended Data Fig. 4 Cross-correlation analyze of the phases X1 and X2 and the slab-related fast-velocity anomaly contours in tomographic studies.

We use the Pearson correlation coefficient (CC) to qualify the correlation between phases X1 ac, and X2 df, and the velocity contours. Our study suggests that the existence of the phases X1/X2 is best correlated with velocity contour of 1%, while the depth of the phases X1/X2 is best correlated with the velocity of 3%.

Extended Data Fig. 5 Multi-frequency receiver function waveform modeling.

a, The 1D velocity model set up in Receiver Function synthetic tests. b, Sensitivity to the velocity contrast. c, Sensitivity to the transition thickness. d, Sensitivity to the Gaussian filter parameter (frequency).

Extended Data Fig. 6 Multi-frequency receiver function waveform modeling results for both the synthetic data and observation.

af, Diagrams show the variation of the amplitude of the Pds phase with transition thickness, velocity perturbation and Gaussian filter parameter. Black heavy line indicates the amplitude of the 410-km discontinuity in IASP91 model49 for reference. ei, The frequency dependent amplitude of the Pds phases in real data, along with the uncertainties estimated by a bootstrapping method.

Extended Data Fig. 7 Sensitivity test for the multi-frequency receiver function waveform modeling.

a, and b, Examples show the multi-frequency Receiver Function (RF) waveforms sensitivity to the thickness and shear-wave speed. c, The RF waveforms are more sensitive to the relative velocity change along the depth, rather than the absolutely velocity value.

Extended Data Fig. 8 Estimated topography of wadsleyite-ringwoodite phase transition based on thermal anomalies from tomography models.

a, S-velocity model of FWEA18-S4, NECESS-S41 along the profile A shown in the main text. b, The estimated temperature anomaly using a temperature-velocity relationship29 of dVs/T=−3.1×10−4 km s−1K−1. The thick red line shows the estimated temperature at 520 km depth. The thin gray lines show the estimated temperature profiles over a 100 km depth interval around 520 km to accompany the resolution of tomographic studies. c, Estimated topography of wadsleyite-ringwoodite phase transition using a Clapeyron slope of 2 MPa/K23. The purple lines show the estimation, while the thick black line shows the observation. d, Similar as (c), but for a Clapeyron slope of 4 MPa/K23. Note that even though the velocity anomalies in regions A and B are very similar in magnitude, the depths of observed phase X1 have a large difference.

Extended Data Fig. 9 Comparison of different models for interpreting the observed Phase X2.

Schematic cartoons show different models/interpretations (left column), while the limitations of each model are shown in the right column29,32,35,58,59.

Extended Data Fig. 10 Comparison of a variety of tomography models along a same profile.

P-velocity model of FWEA18-P4, GAP_P42, MIT-0860 and S-velocity model of FWEA18-S4, NECESS-S41. The general features, such as the high velocity anomaly interpreted as the subducting Pacific slab and the low velocity sub-slab anomalies, can be observed in all these models. However, the distribution and amplitude of these anomalies are different from each other. The FWEA18 is expected to have higher spatial resolution than the others in the northwest Pacific region, due to the dense seismic data coverage and the usage of full-waveform inversion algorithm4. Therefore, we use the FWEA18 model to conduct 3D velocity correction in our RF analysis.

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Wang, X., Chen, QF., Niu, F. et al. Distinct slab interfaces imaged within the mantle transition zone. Nat. Geosci. 13, 822–827 (2020).

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