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Bayesian integration of astrochronology and radioisotope geochronology

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Abstract. Relating stratigraphic position to numerical time using age–depth models plays an important role in determining the rate and timing of geologic and environmental change throughout Earth history. Astrochronology uses the geologic record of astronomically derived oscillations in the rock record to measure the passage of time and has proven to be a valuable technique for developing age–depth models with high stratigraphic and temporal resolution. However, in the absence of anchoring dates, many astrochronologies float in numerical time. Anchoring these chronologies relies on radioisotope geochronology (e.g., U–Pb, 40Ar/39Ar), which produces high-precision (<±1 %), stratigraphically distributed point estimates of age. In this study, we present a new R package, astroBayes, for a Bayesian inversion of astrochronology and radioisotopic geochronology to derive age–depth models. Integrating both data types allows reduction in uncertainties related to interpolation between dated horizons and the resolution of subtle changes in sedimentation rate, especially when compared to existing Bayesian models that use a stochastic random walk to approximate sedimentation variability. The astroBayes inversion also incorporates prior information about sedimentation rate, superposition, and the presence or absence of major hiatuses. The resulting age–depth models preserve both the spatial resolution of floating astrochronologies and the accuracy as well as precision of modern radioisotopic geochronology. We test the astroBayes method using two synthetic datasets designed to mimic real-world stratigraphic sections. Model uncertainties are predominantly controlled by the precision of the radioisotopic dates and are relatively constant with depth while being significantly reduced relative to “dates-only” random walk models. Since the resulting age–depth models leverage both astrochronology and radioisotopic geochronology in a single statistical framework they can resolve ambiguities between the two chronometers. Finally, we present a case study of the Bridge Creek Limestone Member of the Greenhorn Formation where we refine the age of the Cenomanian–Turonian boundary, showing the strength of this approach when applied to deep-time chronostratigraphic questions.
Title: Bayesian integration of astrochronology and radioisotope geochronology
Description:
Abstract.
Relating stratigraphic position to numerical time using age–depth models plays an important role in determining the rate and timing of geologic and environmental change throughout Earth history.
Astrochronology uses the geologic record of astronomically derived oscillations in the rock record to measure the passage of time and has proven to be a valuable technique for developing age–depth models with high stratigraphic and temporal resolution.
However, in the absence of anchoring dates, many astrochronologies float in numerical time.
Anchoring these chronologies relies on radioisotope geochronology (e.
g.
, U–Pb, 40Ar/39Ar), which produces high-precision (<±1 %), stratigraphically distributed point estimates of age.
In this study, we present a new R package, astroBayes, for a Bayesian inversion of astrochronology and radioisotopic geochronology to derive age–depth models.
Integrating both data types allows reduction in uncertainties related to interpolation between dated horizons and the resolution of subtle changes in sedimentation rate, especially when compared to existing Bayesian models that use a stochastic random walk to approximate sedimentation variability.
The astroBayes inversion also incorporates prior information about sedimentation rate, superposition, and the presence or absence of major hiatuses.
The resulting age–depth models preserve both the spatial resolution of floating astrochronologies and the accuracy as well as precision of modern radioisotopic geochronology.
We test the astroBayes method using two synthetic datasets designed to mimic real-world stratigraphic sections.
Model uncertainties are predominantly controlled by the precision of the radioisotopic dates and are relatively constant with depth while being significantly reduced relative to “dates-only” random walk models.
Since the resulting age–depth models leverage both astrochronology and radioisotopic geochronology in a single statistical framework they can resolve ambiguities between the two chronometers.
Finally, we present a case study of the Bridge Creek Limestone Member of the Greenhorn Formation where we refine the age of the Cenomanian–Turonian boundary, showing the strength of this approach when applied to deep-time chronostratigraphic questions.

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