Geochemical and geophysical constrains on the dynamic topography of the Southern African Plateau

Alan G. Jones*, Juan Carlos Afonso, Javier Fullea

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    18 Citations (Scopus)


    The deep mantle African Superswell is considered to contribute to the topographic uplift of the Southern African Plateau, but dynamic support estimates vary wildly depending on the approach and data used. One reason for these large disparities is that the role of lithospheric structure, key in modulating deep dynamic contributions to elevation, is commonly ignored or oversimplified in convection studies. We use multiple high-quality geophysical data coupled with xenolith-based geochemical constraints to compute the isostatic lithospheric contribution to the elevation of the Plateau, facilitating isolation of the current dynamic component from the total observed elevation. We employ a multiobservable stochastic algorithm to invert geoid anomaly, surface-wave dispersion data, magnetotelluric data, and surface heat flow to predict elevation in a fully thermodynamically and internally-consistent manner. We find that a compositionally layered 230 ± 7 km thick lithosphere is required to simultaneously fit all four data types, in agreement with abundant independent xenolith evidence. Our stochastic modeling indicates a lithospheric contribution to elevation of the order of 670 m, which implies dynamic support arising from the convecting sublithospheric mantle of ∼650 m. Our results have important implications for the understanding of lithospheric-deep mantle feedback mechanisms and for calibrating dynamic topography estimates from global convection studies.

    Original languageEnglish
    Pages (from-to)3556-3575
    Number of pages20
    JournalGeochemistry, Geophysics, Geosystems
    Issue number10
    Publication statusPublished - 1 Oct 2017


    • dynamic topography
    • geochemical-geophysical inversion
    • lithosphere
    • thermochemical modeling


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