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Seismic evidence of effects of water on melt transport in the Lau back-arc mantle

Nature volume 518, pages 395–398 (2015)Cite this article

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Abstract

Processes of melt generation and transport beneath back-arc spreading centres are controlled by two endmember mechanisms: decompression melting similar to that at mid-ocean ridges and flux melting resembling that beneath arcs1. The Lau Basin, with an abundance of spreading ridges at different distances from the subduction zone, provides an opportunity to distinguish the effects of these two different melting processes on magma production and crust formation. Here we present constraints on the three-dimensional distribution of partial melt inferred from seismic velocities obtained from Rayleigh wave tomography using land and ocean-bottom seismographs. Low seismic velocities beneath the Central Lau Spreading Centre and the northern Eastern Lau Spreading Centre extend deeper and westwards into the back-arc, suggesting that these spreading centres are fed by melting along upwelling zones from the west, and helping to explain geochemical differences with the Valu Fa Ridge to the south2, which has no distinct deep low-seismic-velocity anomalies. A region of low S-wave velocity, interpreted as resulting from high melt content, is imaged in the mantle wedge beneath the Central Lau Spreading Centre and the northeastern Lau Basin, even where no active spreading centre currently exists. This low-seismic-velocity anomaly becomes weaker with distance southward along the Eastern Lau Spreading Centre and the Valu Fa Ridge, in contrast to the inferred increase in magmatic productivity1. We propose that the anomaly variations result from changes in the efficiency of melt extraction, with the decrease in melt to the south correlating with increased fractional melting and higher water content in the magma. Water released from the slab may greatly reduce the melt viscosity3 or increase grain size4, or both, thereby facilitating melt transport.

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Figure 1: Maps of the study region and mantle velocities.
Figure 2: Cross-sections A–A′, B–B′ and C–C′ showing the azimuthally averaged SV-wave velocity.
Figure 3: Cross-sections D–D′ and E–E′ of azimuthally averaged SV-wave velocity with a schematic model showing the along-strike variations.

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Acknowledgements

We thank P. J. Shore, Y. J. Chen and the captains, crew and science parties of the RVs Roger Revelle and Kilo Moana for data collecting; D. W. Forsyth, Y. Yang, G. G. Euler, D. Heeszel, X. Sun and W. Shen for helping with data processing; N. Harmon, C. Rychert, P. Skemer and B. M. Mahan for discussions; and N. Hu for support. IRIS PASSCAL and OBSIP provided land-based seismic instrumentation and OBSs, respectively. This work was supported by the Ridge 2000 Program under NSF grants OCE-0426408 (D.A.W. and J.A.C.), EAR-0911137 (D.A.W.), OCE-0426369 (S.C.W.), OCE-0430463 (D.K.B.) and OCE-0426428 (R.A.D.).

Author information

Authors and Affiliations

  1. Department of Earth and Planetary Sciences, Washington University, St Louis, 63130, Missouri, USA

    S. Shawn Wei & Douglas A. Wiens

  2. Lamont-Doherty Earth Observatory, Columbia University, Palisades, 10964, New York, USA

    Yang Zha, Terry Plank & Spahr C. Webb

  3. Scripps Institution of Oceanography, University of California, San Diego, La Jolla, California 92093, USA,

    Donna K. Blackman

  4. Department of Geology and Geophysics, University of Hawaii, Honolulu, 96822, Hawaii, USA

    Robert A. Dunn

  5. Department of Geology, Southern Illinois University, Carbondale, 62901, Illinois, USA

    James A. Conder

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Contributions

S.S.W., advised by D.A.W., analysed the seismic data. T.P. downloaded and analysed the geochemical data. S.S.W. and D.A.W. took the lead in writing the manuscript, and all authors discussed the results and edited the manuscript.

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Correspondence to S. Shawn Wei.

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The authors declare no competing financial interests.

Additional information

Raw seismic data are available at the Data Management Center of the Incorporated Research Institutions for Seismology (http://www.iris.edu/dms/nodes/dmc), under network IDs YL, Z1 and XB.

Extended data figures and tables

Extended Data Figure 1 Maps of azimuthally averaged SV-wave velocity at depths of 20, 40, 60, 70, 80 and 100 km.

S-wave velocity of 3.8 km s−1 is contoured. Star illustrates node 364, used in the Monte Carlo inversion (Extended Data Fig. 7). Spreading centres and bathymetry contours are labelled as in Fig. 1c.

Extended Data Figure 2 Seismic stations and earthquakes used in this study.

Red triangles represent island-based stations operated from October 2009 to December 2010. Red and black dots are WHOI (Woods Hole Oceanographic Institution) and LDEO (Lamont-Doherty Earth Observatory) OBSs deployed from November 2009 to November 2010. Open circles mean unrecovered OBSs. Yellow dots and triangles indicate OBSs and island-based stations deployed during September to December 1994, respectively. Spreading centres and bathymetry are labelled as in Fig. 1b. The inset shows the earthquakes (blue dots) used in this study centred at the Lau Basin (red star).

Extended Data Figure 3 Maps of azimuthally isotropic phase velocity at periods of 21, 28, 37, 45 and 60 s inverted with the finest inverting grid.

Spreading centres and bathymetry contours are labelled as in Fig. 1c. Dispersion curves are shown for the CLSC (blue), ELSC (green), VFR (cyan), East Pacific Rise13 (magenta), Mariana back-arc39 (black) and NF89 models14 (red and dark red). The CLSC, ELSC and VFR are represented by nodes shown in Fig. 1d. Error bars indicate the standard deviations of phase velocity.

Extended Data Figure 4 Robustness of the phase-velocity inversion at periods of 37, 50 and 66 s, which are most sensitive to depths of about 50 km (where the velocity is lowest), 70 km (where the inclined LVZ extends away from the trench) and 100 km (the maximum depth to be interpreted), respectively.

Left panels: maps of double standard deviation inverted with the finest grid. Middle panels: resolution test of phase-velocity inversion with the finest inverting grid (regularly spacing black points). Black dots and triangles represent 63 OBSs and 26 land-based seismic stations used in this study, respectively. The black polygon outlines the region in which we display results because within it we achieved a reasonable resolution of phase-velocity inversion at all periods. Spreading centres and bathymetry contours are labelled as in Fig. 1c. Right panels: Rayleigh wave ray-paths (black lines) used in phase-velocity inversion. Seismic stations are labelled as in Fig. 1b.

Extended Data Figure 5 Previous results of ambient-noise tomography.

a, Isotropic phase velocities of Rayleigh waves at the period of 18 s. Black dots indicate the OBSs used in this study, red triangles represent active volcanoes, and black lines mean the spreading centres. b, Azimuthally averaged SV-wave velocity at a depth of 30 km. All ANT results from ref. 15.

Extended Data Figure 6 Two examples of phase velocity measured by the two-station method.

a, Surface waves (black curves) of two earthquakes (red stars) propagated to four OBSs (red dots). b, The earthquake at the Chile trench was recorded by stations N01W and N03W. The difference in epicentral distances is about 171.5 km. The Rayleigh wave at a period of 37 s has a delay time of 47.8 s, suggesting a phase velocity of 3.59 km s−1. c, The earthquake at the Mariana trench was recorded by stations A12W and S01W. The difference in epicentral distances is about 165.1 km. The Rayleigh wave at a period of 37 s has a delay time of 45.0 s, suggesting a phase velocity of 3.67 km s−1.

Extended Data Figure 7 SV-wave-velocity inversion of Monte Carlo algorithm for node 364.

a, Models of SV-wave velocity. b, Forward-calculated dispersion curves. Each grey curve indicates one ‘good’ model whose smoothness and mis-fit are smaller than the criteria. Blue, magenta, black, red and dark red curves represent the model from linearized inversion, the average model, the best model from Monte Carlo inversion and NF89 models of two age categories14, respectively. In a, the model of SV-wave velocity from ref. 35 (green) is shown for reference. In b, the green curve indicates phase velocities inverted by TPWT, with error bars showing the standard deviations.

Extended Data Figure 8 Cross-sections of predicted SV-wave velocity.

Calculations are based on numerical models of temperature and water content23, the extended Burgers model20, and corrections for radial anisotropy14 and effects of water24. The colour scale is the same as in Fig. 2. Although, compared with that beneath the CLSC, the temperature beneath the VFR is lower owing to slab cooling, which potentially increases the seismic velocity, the much higher water content reduces the velocity more significantly and leads to a stronger signal of low velocity in the prediction.

Extended Data Figure 9 Pressures and temperatures of equilibration of Lau Basin glasses with Fo90 mantle.

We used major elements, H2O measurements, constraints and the thermobarometer of ref. 27 to calculate P–T paths for most primitive melts (crystallizing olivine only). Back-arc averages for the VFR and the CLSC–ELSC high-temperature cluster are shown with smaller symbols and error bars of 1 s.d. Fields are given for the FRSC, the MTJ and Tonga Arc Volcano A for comparison. All data are from PetDB43,44,45,46,47,48 and ref. 54. The dry solidus is from ref. 57. Back-arc averages are traced back along wet decompression melting paths, as described in Methods.

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Wei, S., Wiens, D., Zha, Y. et al. Seismic evidence of effects of water on melt transport in the Lau back-arc mantle. Nature 518, 395–398 (2015). https://doi.org/10.1038/nature14113

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