Abstract
More than a third of mid-ocean ridges have a spreading rate of less than 20 millimetres a year1. The lack of deep imaging data means that factors controlling melting and mantle upwelling2,3, the depth to the lithosphere–asthenosphere boundary (LAB)4,5, crustal thickness6,7,8,9 and hydrothermal venting are not well understood for ultraslow-spreading ridges10,11. Modern electromagnetic data have greatly improved our understanding of fast-spreading ridges12,13, but have not been available for the ultraslow-spreading ridges. Here we present a detailed 120-kilometre-deep electromagnetic joint inversion model for the ultraslow-spreading Mohns Ridge, combining controlled source electromagnetic and magnetotelluric data. Inversion images show mantle upwelling focused along a narrow, oblique and strongly asymmetric zone coinciding with asymmetric surface uplift. Although the upwelling pattern shows several of the characteristics of a dynamic system3,12,13,14, it probably reflects passive upwelling controlled by slow and asymmetric plate movements instead. Upwelling asthenosphere and melt can be traced to the inferred depth of the Mohorovičić discontinuity and are enveloped by the resistivity (100 ohm metres) contour denoted the electrical LAB (eLAB). The eLAB may represent a rheological boundary defined by a minimum melt content. We also find that neither the melt-suppression model7 nor the inhibited-migration model15, which explain the correlation between spreading rate and crustal thickness6,16,17,18,19, can explain the thin crust below the ridge. A model in which crustal thickness is directly controlled by the melt-producing rock volumes created by the separating plates is more likely. Active melt emplacement into oceanic crust about three kilometres thick culminates in an inferred crustal magma chamber draped by fluid convection cells emanating at the Loki’s Castle hydrothermal black smoker field. Fluid convection extends for long lateral distances, exploiting high porosity at mid-crustal levels. The magnitude and long-lived nature of such plumbing systems could promote venting at ultraslow-spreading ridges.
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Code availability
MARE2DEM20 is a parallel adaptive finite element code for two-dimensional forward and inverse modelling for electromagnetic geophysics and was used for data modelling and inversion in this project. MARE2DEM is available for download at http://mare2dem.ucsd.edu/. The CSEM and MT processing software used in this study are available from EMGS ASA http://www.emgs.com/, but restrictions apply to the availability of the software, which were used under special agreement for the current study, and so they are not publicly available. The software is, however, available from the corresponding author upon reasonable request and with permission of EMGS ASA.
Data availability
The data that support the findings of this study are available from NTNU, but restrictions apply to the availability of these data, which were used under special agreement for the current study. All relevant data are, however, available from the corresponding author upon reasonable request and with the permission of NTNU.
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Acknowledgements
We thank the Faculty of Engineering, Department of Geoscience and Petroleum, NTNU Oceans, the ROSE consortium (with financial support from Norwegian Research Council, grant number 228400) and the Geophysics group at the Norwegian University of Science and Technology (NTNU) for funding the survey. We thank EMGS ASA for collecting excellent data in a very challenging environment.
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Nature thanks Steven Constable and Rob Evans for their contribution to the peer review of this work.
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S.E.J. developed the project, analysed the data and wrote the manuscript. H.E.F.A. analysed the data and wrote the manuscript together with S.E.J. Data were processed and the Methods section was prepared by M.P. and R.M. All authors took part in data analyses, discussed the results and commented on the manuscript.
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Extended data figures and tables
Extended Data Fig. 1 Bathymetry and electromagnetic acquisition geometry.
Water depth (black), receiver positions with names (yellow triangles) and the CSEM source track (red) for the acquired two-dimensional line at Loki’s Castle.
Extended Data Fig. 2 CSEM data examples.
Measured CSEM data (dots) and synthetic data for the resulting model from CSEM data inversion (lines) for two selected receivers at line positions (−3 km and +25 km). The electric-field magnitude (top) and phase data (bottom) are displayed for the frequencies 0.5 Hz (blue), 1.0 Hz (green) and 2.0 Hz (red). The total root-mean-square error for the resulting resistivity model is 1.13.
Extended Data Fig. 3 Inverted and measured MT data.
MT (transverse magnetic mode) data (circles) and synthetic data (solid lines) for the inversion result are shown for all MT stations used. The total root-mean-square misfit is 1.4. ρa is apparent resistivity.
Extended Data Fig. 4 Anisotropic resistivity model from two-dimensional CSEM data inversion.
Image of the horizontal resistivity ρh (top) and the vertical resistivity ρv (bottom). The resulting model has a root-mean-square misfit of 1.13. The locations of the electromagnetic receivers are shown as white circles.
Extended Data Fig. 5 Anisotropic resistivity model from simultaneous joint inversion of CSEM and MT (transverse magnetic mode) data.
The three components of the resistivity tensor—ρx, ρy and ρz—show strong similarities owing to strong anisotropy regularization. CSEM receiver positions are plotted as circles, and receivers with MT used in the joint inversion are plotted as triangles. The model fits the data with a root-mean-square misfit of 1.4.
Extended Data Fig. 6 Temperature, conductivity and melt content versus depth beneath the Mohns Ridge.
a, Temperature versus depth for the 3 Myr west profile. TMAX, calculated by inverting measured conductivities to TSEO3 (Fig. 3a), is shown as grey circles. The resulting geotherm (heavy black line) is consistent with adiabatic upwelling combined with a 3 Myr halfspace cooling model. Dry solidi for lherzolite39,40 and harzburgite41 are shown for reference. b, Temperature versus depth for the axial profile with adiabatic upwelling to the depth of the eMoho combined with a near-linear cooling trend towards 320 °C at the seabed (Loki’s Castle). TMAX, calculated by inverting measured conductivities to TSEO3 (Fig. 3a), is shown as orange circles. c, Temperature versus depth for the 4 Myr east profile. TMAX, calculated by inverting measured conductivities to TSEO3 (Fig. 3a), is shown as blue circles. The resulting geotherm (heavy black line) reflects adiabatic upwelling to eLAB depth combined with a gradual cooling towards 4 Myr halfspace model temperatures about 15 km below the seabed. d, Resistivity versus depth and calculated melt content42 for the 3 Myr west profile. Calculated resistivity versus depth for dry DMM (SEO3), basalt + 1 wt% H2O and gabbro are shown for reference. e, Resistivity versus depth and calculated melt content42 for the axial profile. Calculated resistivity versus depth profiles for dry DMM (SEO3), basalt + 1 wt% H2O and gabbro are shown for reference. f, Resistivity versus depth and calculated melt content42 for the 4 Myr east profile. Calculated resistivity versus depth profiles for dry DMM (SEO3), basalt + 1 wt% H2O and gabbro are shown for reference.
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Johansen, S.E., Panzner, M., Mittet, R. et al. Deep electrical imaging of the ultraslow-spreading Mohns Ridge. Nature 567, 379–383 (2019). https://doi.org/10.1038/s41586-019-1010-0
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DOI: https://doi.org/10.1038/s41586-019-1010-0
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