A document by María Constanza Manassero. Click on the document to view its contents.

The Archean Superior craton was formed by the assemblage of continental and oceanic terranes at ∼2.6 Ga. The craton is surrounded by multiple Proterozoic mobile belts, including the Paleoproterozoic Trans-Hudson Orogen which brought together the Superior and Rae/Hearne cratons at ∼1.9-1.8 Ga. Despite numerous studies on Precambrian lithospheric formation and evolution, the deep thermochemical structure of the Superior craton and its surroundings remains poorly understood. Here we investigate the upper mantle beneath the region from the surface to 400 km depth by jointly inverting Rayleigh wave phase velocity dispersion data, elevation, geoid height and surface heat flow, using a probabilistic inversion to obtain a (pseudo-)3D model of composition, density and temperature. The lithospheric structure is dominated by thick cratonic roots (>300 km) beneath the eastern and western arms of the Superior craton, with a chemically depleted signature (Mg# > 92.5), consistent with independent results from mantle xenoliths. Beneath the surrounding Proterozoic and Phanerozoic orogens, the Mid-continent Rift and Hudson Strait, we observe a relatively thinner lithosphere and more fertile composition, indicating that these regions have undergone lithospheric modification and erosion. Our model supports the hypothesis that the core of the Superior craton is well-preserved and has evaded lithospheric destruction and refertilization. We propose three factors playing a critical role in the craton’s stability: (i) the presence of a mid-lithospheric discontinuity, (ii) the correct isopycnic conditions to sustain a strength contrast between the craton and the surrounding mantle, and (iii) the presence of weaker mobile belts around the craton.

The thermochemical structure of the lithosphere exerts control on melting mechanisms in the mantle as well as the location of volcanism and ore deposits. Imaging the complex interactions between the lithosphere and asthenospheric mantle requires the joint inversion of multiple data sets and their uncertainties. In particular, the combination of seismic velocity and electrical conductivity with data proxies for bulk composition and elusive minor phases is a crucial step towards fully understanding large-scale lithospheric structure and melting. We apply a novel probabilistic approach for joint inversions of 3D magnetotelluric and seismic data to image the lithosphere beneath southeast Australia. Results show a highly heterogeneous lithospheric structure with deep conductivity anomalies that correlate with the location of Cenozoic volcanism. In regions where the conductivities have been at odds with sub-lithospheric temperatures and seismic velocities, we observe that the joint inversion provides conductivity values consistent with other observations. The results reveal a strong relationship between metasomatized regions in the mantle and i) the limits of geological provinces in the crust, which elucidates the subduction-accretion process in the region; ii) distribution of leucitite and basaltic magmatism; iii) independent geochemical data, and iv) a series of lithospheric steps which constitute areas prone to generating small-scale instabilities in the asthenosphere. This scenario suggests that shear-driven upwelling and edge-driven convection are the dominant melting mechanisms in eastern Australia rather than mantle plume activity, as conventionally conceived. Our study offers an integrated lithospheric model for southeastern Australia and provides insights into the feedback mechanism driving surface processes.

Joint probabilistic inversions of magnetotelluric (MT) and seismic data has great potential for imaging the thermochemical structure of the lithosphere as well as mapping fluid/melt pathways and regions of mantle metasomatism. In this contribution we present a novel probabilistic (Bayesian) joint inversion scheme for 3D MT and surface-wave dispersion data particularly designed for large-scale lithospheric studies. The approach makes use of a recently developed strategy for fast solutions of the 3D MT forward problem (Manassero et al., 2020) and combines it with adaptive Markov chain Monte Carlo (MCMC) algorithms and parallel-in-parallel strategies to achieve extremely efficient simulations. To demonstrate the feasibility, benefits and performance of our joint inversion method to image the conductivity, temperature and velocity structures of the lithosphere, we apply it to two numerical examples of increasing complexity. The inversion approach presented here is timely and will be useful in the joint analysis of MT and surface wave data that are being collected in many parts of the world. This approach also opens up new avenues for the study of translithospheric and transcrustal magmatic systems, the detection of metasomatised mantle and the incorporation of MT into multi-observable inversions for the physical state of the Earth’s interior.