Abstract

Paleopedology and geochemical analysis of Upper Jurassic deposits in the Stanleyville Group of Central Africa indicate harsh Late Jurassic paleoclimates in the interior of Gondwana. Subsurface samples collected from the Samba borehole near the center of the Congo Basin show only weak morphological evidence of pedogenesis, but are characterized by an abundance of shrink-swell (vertic) features and rare calcium carbonate nodules, indicating seasonal variations in moisture availability and net soil moisture deficiency, respectively. X-ray diffraction analysis of paleosol matrix material reveals the presence of analcime and the clay mineral palygorskite, strong indicators of hot, arid climatic conditions. The δ 18O and δD values of clay minerals from paleosol profiles range from + 22.3‰ to + 25.4‰ and − 44.4‰ to − 39.6‰ SMOW, respectively, and correspond to crystallization temperatures between 25 °C and 40 °C. These crystallization temperatures compare favorably with austral summer surface temperature estimates for Central Africa that result from Late Jurassic global circulation models. Calculations of soil CO 2 production using the δ 13C values of pedogenic carbonates and plant-derived organic matter produce lower CO 2 production estimates for the Stanleyville Group relative to the roughly contemporary Morrison Formation of the western U.S. These low soil CO 2 production estimates provide further support for arid Late Jurassic climate conditions in the Congo Basin. The paleoclimatic conditions inferred here from the Stanleyville Group are similar to those reconstructed from other Upper Jurassic African continental localities between 5°S and 20°S paleolatitude. However, penecontemporaneous terrestrial coastal sites within this latitudinal belt of Gondwana retain evidence of generally wetter conditions, suggesting that those regions may have received more rainfall than the continental interior. The paleoclimatic setting reconstructed here from geologic indicators and geochemical proxies suggests that general circulation models accurately predict unique paleoenvironmental conditions that lack modern analogs.

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