A Thermo‐Compositional Model of the African Cratonic Lithosphere

Abstract

Cratons are the ancient continental cores, around which continents accrete and grow. They are stable for billions of years, and due to their geologic evolution often provide an abundancy of resources, for example, rare earth elements and diamonds. Cratons are usually underlain by thick continental lithosphere, their so-called "roots", which can reach up to about 250 km into the Earth (e.g., Steinberger & Becker, 2018). With a few exceptions (Kaban et al., 2015), these roots resist mantle convection, and thus deviate mantle flow. Therefore, a better understanding of cratons, their evolution and dynamics may provide further insight to large-scale dynamic and tectonic processes. Cratons appear to be buoyant with respect to the underlying mantle despite the fact that their long-term cooling causes an increase in density. A commonly cited explanation is the iso-pycnic hypothesis (Jordan, 1978) that is based on the counter-balancing effect of chemical buoyancy. The density increase caused by reduced temperatures is balanced by density decrease from depletion in heavy constituents, mostly iron (Fe;Griffin, O'Reilly, Natapov, & Ryan, 2003). Depletion is commonly measured by means of Mg#, the percentage of Magnesium (Mg) in the total amount of Mg and Fe (100*Mg/(Mg + Fe)) in mantle minerals. Mg#s around 89 are common for fertile mantle rocks, while strongly depleted samples exhibit values around 94 (Griffin, O'Reilly,

Africa's Crustal Architecture Inferred From Probabilistic and Perturbational Inversion of Ambient Noise: ADAMA

“…These models are heavily spatially aliased. In particular, the models of the bulk velocity in the crust or it's thickness (Moho depth) have been conducted using several techniques that can be broadly categorized into three categories: (a) passive source seismics with sensitivity to the crust, for example, receiver functions, ambient noise, or SS reflectivity (Globig et al., 2016; Pasyanos & Nyblade, 2007; Rychert & Shearer, 2010; Tugume et al., 2013) (b) regionalized earthquake body wave tomography models with only marginal sensitivity to the crust (Boyce et al., 2021; Celli, Lebedev, Schaeffer, & Gaina, 2020), and (c) joint gravity and seismic models (Finger et al., 2021, 2022; Haas et al., 2021). Our new model is not heavily spatially aliased.…”

“…When other passive source data sets are jointly interpreted, the improved depth resolution of other elastic‐properties like compressional wave speed, Poisson ratio, is possible only when the measurements are made in regions with low‐resolution. In what follows, we review the current state of seismic models of the African crust (Begg et al., 2009; Crosby et al., 2010; Finger et al., 2022; Raveloson et al., 2015). We contrast this with Moho models based on joint inversion with other geophysical methods to obtain thermo‐compositional models of the African lithosphere (Afonso et al., 2022; Globig et al., 2016; Haas et al., 2021; Raveloson et al., 2021).…”

Africa’s Crustal Architecture Inferred from Probabilistic and Perturbational Inversion of Ambient Noise: ADAMA

“…For seismic methods, like receiver functions, that improve sensitivity right underneath the seismic station then depth resolution of crust and mantle discontinuities will only be possible when stations are co-located with regions with high resolution from surface wave studies. In what follows, we review the current state of seismic models of the crust (Begg et al, 2009;Crosby et al, 2010;Raveloson et al, 2015;Finger et al, 2022), we contrast this with Moho models based on joint inversion with other geophysical methods of obtain thermo-compositional models of the African lithosphere (Globig et al, 2016;Raveloson et al, 2021;Haas et al, 2021;Afonso et al, 2022).…”

“…Compared to other regions or the world, Africa is sparsely instrumented and therefore earlier seismic models based on combined active and passive source seismics have required extensive spatial averaging (Mooney, 2010;Fishwick & Bastow, 2011;Stolk et al, 2013;Globig et al, 2016). These are heavily spatially aliased models of the bulk velocity in the crust or it's thickness (Moho depth) and have been conducted using several techniques that can be broadly categorized into three categories: (1) passive source seismics with sensitivity to the crust, e.g., receiver functions, ambient noise, or SS reflectivity (Pasyanos & Nyblade, 2007;Rychert & Shearer, 2010;Tugume et al, 2013;Globig et al, 2016) (2) regionalized earthquake body wave tomography models with only marginal sensitivity to the crust, Boyce et al, 2021), and (3) joint gravity and seismic models (Haas et al, 2021;Finger et al, 2021Finger et al, , 2022. Compared to these techniques, we provide the best resolution on the bulk shear velocity in the crust.…”

Effects of multi-extensional tectonics in a cratonic area: 3D numerical modeling and implications for the Congo Basin

“…In particular, the recent seismic tomography model of Emry et al (2019) and Celli et al (2020) have shown that the Congo Craton is composed of at least three cratonic blocks, 200-250 km thick, with eroded margins. Furthermore, the lithospheric thermal structure, reflected by the surface heat flow values (Lucazeau et al, 2015) and obtained from inversion of this seismic tomography model, taking into account the mantle compositional variations (Finger et al, 2022), indicate typical cratonic temperatures. On the other hand, mantle density variations, induced by the composition, show small depletion in Fe components, which is expressed by the Mg number ( 1 Mg # < 91) (Finger et al, 2022).…”