Abstract

Early Archean (>3.0 Ga) sedimentary rocks are present in high-grade metamorphic terranes and greenstone belts in southern Africa and Western Australia. The viability and quality of basin analysis in these terranes improves with decreasing metamorphic grade and degree of structural complexity. Depending on the state of preservation of the rocks, it is possible to reconstruct some or all of: stratigraphy, source-area composition and age, sediment dispersal patterns and depositional environments, and basin configuration and tectonic setting.Pre-greenstone (>3.6 Ga) gneisses in the high-grade Limpopo Province and Western Gneiss Terrain are envisaged as remnants of cratonic nucleii. These gneisses represent basement to cover rocks that are exclusively of sedimentary origin and accumulated between ca. 3.6 and 3.2 Ga. Limpopo cover rocks are devoid of primary sedimentary structures and consist of quartzite with detrital zircons (original quartz arenite), marble (limestone), metapelite (mudstone) and aluminous gneiss (possible wacke). This quartz arenite-carbonate association implies a stable tectonic setting and the best analogs may be younger cratonic-shelf deposits. Metapelites in the Limpopo Province have a complex rare earth element (REE) geochemistry indicating a mixed provenance that included differentiated continental crust. A thick sequence (ca. 2.5 km) of conglomerate and crossbedded aluminous gneiss (wacke) in the Western Gneiss Terrain is interpreted as an alluvial deposit and possibly accumulated in a rift setting. Rare earth element geochemistry of metapelites indicates that differentiated continental crust consisting of K-granites was the dominant component of the source terrain.Predominantly mafic and ultramafic volcanism in the Barberton and Pilbara greenstone belts took place between 3.5 and 3.3 Ga in an oceanic environment distant from any continental influence. Intercalated sedimentary deposits indicate that volcanism took place at relatively shallow-water depths. The volcanic sequences are overlain by predominantly siliciclastic sedimentary intervals. In the Barberton greenstone belt, the distribution of facies, in conjunction with paleocurrent, pétrographie, geochemical, and geochronological data indicate that the Fig Tree and overlying Moodies Groups (ca. 5 km thick) were derived by progressive unroofing of a southerly source terrain consisting of the older volcanic rocks with intercalated sedimentary deposits, and a 3.5 to 3.3 Ga gneiss complex. Sedimentation took place initially in a submarine-fan setting. Basin shoaling is indicated by the upward transition into braided-alluvial and shallow-marine sediments. The stratigraphic evolution of the Fig Tree and Moodies Groups is similar to that of Phanerozoic foreland or foredeep basins.In the Pilbara Block the lower Gorge Creek Group is compositionally similar to the Moodies Group and was derived from a comparable provenance; the tectonic setting of the basin is unclear. The upper Gorge Creek Group unconformably overlies the lower subdivision and contains abundant quartzite clasts recycled from it. This ca. 3 km-thick stratigraphie sequence is exclusively of continental origin; depositional environments include alluvial fans, braided rivers, floodplains, and lakes. Stratigraphie and sedimentological evidence indicates that basin development was controlled by marginal strike-slip faulting.Available age constraints indicate that sedimentary rocks in the high-grade terranes and greenstone belts developed contemporaneously. Cover rocks in the high-grade terranes accumulated on thick continental crust and reflect a stable cratonic setting. In contrast, volcanic intervals in the greenstone belts are considered to have developed in an oceanic setting, whereas the overlying siliciclastic intervals reflect active tectonic settings associated with crustal shortening.KeywordsDetrital ZirconGreenstone BeltCover RockQuartz AreniteLimpopo ProvinceThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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