Geochemical investigation of the co-evolution of life and environment in the Neoproterozoic Era

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Virginia Tech


The co-evolution of life and the environment stands as a cornerstone in Earth's 4.5-billion-year history. Environmental fluctuations have wielded substantial influence over biological evolution, while life forms have, in turn, reshaped Earth's surface and climate. This dissertation centers on a critical period in Earth's history—the Neoproterozoic Era—when profound environmental shifts potentially catalyzed pivotal eukaryotic evolutionary events. By delving deeper into Neoproterozoic paleoenvironments, I aim at a clearer understanding of life-environment co-evolution in this crucial era. The first chapter focuses on an important juncture—the transition from prokaryote to eukaryote dominance in marine ecosystems during the Tonian Period (1000 Ma to 720 Ma). To assess whether the availability of nitrate, an important macro-nutrient, played a critical role in this evolutionary event, nitrogen isotope compositions (δ15N) of marine carbonates from the early Tonian (ca. 1000 Ma to ca. 800 Ma) Huaibei Group in North China were measured. The data indicate nitrate limitation in early Neoproterozoic oceans. Further, a compilation of Proterozoic sedimentary δ15N data, together with box model simulations, suggest a ~50% increase in marine nitrate availability at ~800 Ma. Limited nitrate availability in early Neoproterozoic oceans may have delayed the ecological rise of eukaryotes until ~800 Ma when increased nitrate supply, together with other environmental and ecological factors, may have contributed to the transition from prokaryote-dominant to eukaryote-dominant marine ecosystems. Recognizing the spatial and temporal variations in Neoproterozoic oceanic environments, the second chapter lays the groundwork for a robust stratigraphic framework for the early Tonian Period. Employing the dynamic time warping algorithm, I constructed a global stratigraphic framework for the early Tonian Period using δ13Ccarb data from the North China, São Francisco, and Congo cratons. This exercise confirms the generally narrow range of δ13Ccarb fluctuations in the early Tonian, but also confirms the presence of a negative δ13Ccarb excursion of notable magnitude (~9 ‰) at ca. 920 Ma in multiple records, suggesting that it was global in scope. This negative excursion, known as the Majiatun excursion, is likely the oldest negative excursion in the Neoproterozoic Era and marks the onset of the dynamic Neoproterozoic carbon cycle. Shifting focus to the late Neoproterozoic, the third chapter delves into the origins of Neoproterozoic superheavy pyrite, whose bulk-sample δ34S values are greater than those of contemporaneous seawater sulfate and whose origins remain controversial. Two supervised machine learning algorithms were trained on a large LA-ICP-MS pyrite trace element database to distinguish pyrite of different origins. The analysis validates that two models built on the co-behavior of 12 trace elements (Co, Ni, Cu, Zn, As, Mo, Ag, Sb, Te, Au, Tl, and Pb) can be used to accurately predict pyrite origins. This novel approach was then used to identify the origins of pyrite from two Neoproterozoic sedimentary successions in South China. The first set of samples contains isotopically superheavy pyrite from the Cryogenian Tiesi'ao and Datangpo formations. The second set of samples contains pyritic rims from the Ediacaran Doushantuo Formation; these pyrite rims are associated with fossiliferous chert nodules and do not have superheavy sulfur isotopes. For the superheavy pyrite, the models consistently show high confidence levels in identifying its genesis type, and three out of four samples were inferred to be of sedimentary origins. For the pyritic nodule rims, the models suggest that early diagenetic pyrite was subsequently altered by hydrothermal fluids and therefore shows mixed signals. The third chapter highlights the importance of pyrite trace elements in deciphering and distinguishing the origins of pyrite in sedimentary strata.



Neoproterozoic, Nitrogen Isotope, Iron Speciation, Redox, Tonian, Nitrate, Eukaryotes, Carbon Isotope, North China Craton, Chemostratigraphy, Sulfur Isotope, Pyrite, Trace Element, LA-ICP-MS, Machine Learning, Random Forest, XGBoost