Constraining the absolute time and duration of geologic processes is one of the great challenges and goals in Earth sciences. Increasingly, the integration of geochronologic constraints with petrologic information is being qualitatively applied to understanding the timescales of metamorphic, igneous, tectonic, and fluid-related processes. Many rocks and geochronometers preserve relative age constraints such as compositional zoning or cross cutting relationships. This prior information can be formalized in a Bayesian statistical framework to generate a probabilistic posterior chronology. As we show here, these “age-sequence” models can enhance precision on geochronologic dates and rates and insight into tectonic models. Bayesian modeling of complex, concentrically, zoned monazite from the northern Appalachian orogen was used to develop a detailed temperature-time history through the Acadian (∼405–395 Ma) and Neoacadian (∼380–350 Ma) orogenies with significantly reduced uncertainties (40–70 %). Modeling of zoned monazite from a southern Trans-Hudson orogen granulite yielded durations of 0.5+9/-0.4 Ma and 20+5/-8 Ma for biotite-dehydration melting and suprasolidus conditions, respectively. The relatively short intervals of heating and peak conditions are consistent with a back-arc tectonic setting. A complementary approach, Bayesian change point detection, provides a framework to constrain the timing of compositional changes that can be linked with metamorphic reactions. Applying this approach in the northern Appalachian orogen demonstrates contrasting durations of low-Y monazite crystallization (∼10 vs ∼30 myr) in regions with different pressure-temperature histories. Compositionally distinct monazite domains can be linked with garnet stability, which provides a key constraint on tectonic models. Bayesian statistical analysis represent a powerful tool that can be widely applied to refine the absolute time and duration of geologic processes. A more objective and reproducible set of interpretations are produced by this more formal, although not necessarily complex, statistical analysis.
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