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Sediment subduction in Hadean revealed by machine learning.
- Source :
- Proceedings of the National Academy of Sciences of the United States of America; 7/23/2024, Vol. 121 Issue 30, p1-9, 9p
- Publication Year :
- 2024
-
Abstract
- Due to the scarcity of rock samples, the Hadean Era predating 4 billion years ago (Ga) poses challenges in understanding geological processes like subaerial weathering and plate tectonics that are critical for the evolution of life. The Jack Hills zircon from Western Australia, the primary Hadean samples available, offer valuable insights into magma sources and tectonic genesis through trace element signatures. However, a consensus on these signatures has not been reached. To address this, we developed a machine learning classifier capable of deciphering the geochemical fingerprints of zircon. This allowed us to identify the oldest detrital zircon originating from sedimentary-derived "S-type" granites. Our results indicate the presence of S-type granites as early as 4.24 Ga, persisting throughout the Hadean into the Archean. Examining global detrital zircon across Earth's history reveals consistent supercontinent-like cycles from the present back to the Hadean. These findings suggest that a significant amount of Hadean continental crust was exposed, weathered into sediments, and incorporated into the magma sources of Jack Hills zircon. Only the early operation of both subaerial weathering and plate subduction can account for the prevalence of S-type granites we observe. Additionally, the periodic evolution of S-type granite proportions implies that subduction-driven tectonic cycles were active during the Hadean, at least around 4.2 Ga. The evidence thus points toward an early Earth resembling the modern Earth in terms of active tectonics and habitable surface conditions. This suggests the potential for life to originate in environments like warm ponds rather than extreme hydrothermal settings. [ABSTRACT FROM AUTHOR]
- Subjects :
- CHEMICAL fingerprinting
PLATE tectonics
HADEAN
CONTINENTAL crust
MACHINE learning
Subjects
Details
- Language :
- English
- ISSN :
- 00278424
- Volume :
- 121
- Issue :
- 30
- Database :
- Complementary Index
- Journal :
- Proceedings of the National Academy of Sciences of the United States of America
- Publication Type :
- Academic Journal
- Accession number :
- 178890233
- Full Text :
- https://doi.org/10.1073/pnas.2405160121