Intensified chemical weathering during Early Triassic revealed by magnesium isotopes
2020
Abstract Marine ecosystem recovery after the latest Permian mass extinction (LPME) was a protracted process during the Early Triassic (∼252-247 Ma) owing to repeated climatic and environmental perturbations. Chemical weathering can supply nutrients to the ocean and may have played an important role in the Early Triassic carbon cycle and biological recovery. However, only limited geochemical records of chemical weathering during the Early Triassic have been presented to date, and the relationship between changes in weathering intensity and the slow recovery of marine ecosystems is effectively unknown. Here, we report magnesium (Mg) isotopic compositions of the siliciclastic components from shallow-marine carbonates in two well-studied Upper Permian-Lower Triassic sections in Iran and South China to track changes in chemical weathering intensity after the LPME. Both sections display a wide range of δ26Mg values (−2.09 ‰ to +1.10 ‰ at Zal, −2.30 ‰ to +0.33 ‰ at Zuodeng). We identified two distinct stages (I and II) in each section based on δ26Mg values and major elemental ratios. Variations of δ26Mg values in Stage I (Changhsingian to mid-Dienerian) are mainly controlled by mineralogical composition that can obscure weathering signals. By contrast, δ26Mg variations in Stage II (upper Dienerian to upper Spathian) are independent of lithology and inferred to reflect control by chemical weathering intensity. The trends in chemical weathering intensity within Stage II correspond to first-order variations in climate and carbon cycling. Marine ecosystem recovery during the Early Triassic may have been linked to recurrent episodes of intense chemical weathering caused by CO2 degassing and climate warming. This study demonstrates the potential utility of the Mg isotopic compositions of the silicate fraction in marine carbonates as a proxy for chemical weathering intensity, laying the groundwork for general applications of this method to deep-time systems.
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