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Geo-Marine Letters

, Volume 37, Issue 4, pp 333–344 | Cite as

Lunar recession encoded in tidal rhythmites: a selective overview with examples from Argentina

  • Vanina L. López de AzarevichEmail author
  • Miguel B. Azarevich
Review

Abstract

The study of tides from the sedimentary record of tidal rhythmites, applying fast Fourier transform analysis, contributes to the understanding of the surficial evolution of our highly dynamic planet, and of the astronomical cycles that influenced the ancient tidal systems. This overview of lunar retreat rates, which includes examples from Argentina, displays a generalized pattern of nonlinear, progressively extended lunar cycles up to the present day. The lunar retreat calculated at different stages of the Earth’s history identifies three time spans of extremely high recession rates, amounting to almost twice that of the present day: Archean–Paleoproterozoic (6.93 cm/year), Neoproterozoic I–Ediacaran (7.01 cm/year) and Ediacaran–early Cambrian (6.48 cm/year). Older comparable recession rates are difficult to recognize because of the lack of tidal rhythmic sequences. The maximum lunar retreat rate is registered after the Copernican meteor bombardment event on the Moon at ~900 Ma, and the time span coincides with the continental dispersal of Rodinia. Every acceleration of the lunar retreat rate coincides with two main processes: (1) meteorite impacts on the Earth or Moon, and (2) reconfiguration of landmasses accompanied by earthquakes that generated changes in the rotational axis of the Earth, inundation surfaces, and glaciation/deglaciation processes. The simultaneous occurrence of such processes makes it difficult to distinguish the causes and effects of each individual process, but its conjunction would have promoted the destabilization of the Earth–Moon system in terms of moment of inertia that was transferred to the Moon rotation.

Keywords

Cambrian Lunar Surface Rodinia Band Iron Formation Lunar Cycle 
These 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.

Notes

Acknowledgements

This study was funded by the research project no. 2037 of the Consejo de Investigaciones de la Universidad Nacional de Salta (CIUNSa), with academic support from CEGA-INSUGEO-CONICET. The guest editor R.A. Scasso, as well as A.J. van Loon, an anonymous reviewer and the journal editors are thanked for their insightful comments and suggestions.

Compliance with ethical standards

Conflict of interest

The authors declare that there is no conflict of interest with third parties.

Supplementary material

367_2017_500_MOESM1_ESM.docx (26 kb)
ESM Table 1 (DOCX 26 kb)

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Copyright information

© Springer-Verlag Berlin Heidelberg 2017

Authors and Affiliations

  1. 1.Centro de Estudios Geológicos Andinos (CEGA), Instituto Superior de Correlación Geológica (INSUGEO), Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET)Universidad Nacional de SaltaSaltaArgentina
  2. 2.Centro de Estudios Geológicos Andinos (CEGA), Instituto Superior de Correlación Geológica (INSUGEO), Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET)SaltaArgentina

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