Computing Rates and Distributions of Rock Recovery in Subduction Zones

Bodies of rock that are detached (recovered) from subducting oceanic plates, and exhumed to Earth's surface, become invaluable records of the mechanical and chemical processing of rock along subduction interfaces. Exposures of interface rocks with high-pressure (HP) mineral assemblages provide insights into the nature of rock recovery, yet various inconsistencies arise when directly comparing the rock record with numerical simulations of subduction. Constraining recovery rates and depths from the rock record presents a major challenge because small sample sizes of HP rocks reduce statistical power. As an alternative approach, this study implements a classification algorithm to identify rock recovery in numerical simulations of oceanic-continental convergence. Over one million markers are classified from 64 simulations representing a large range of subduction zones. Recovery pressures (depths) correlate strongly with convergence velocity and moderately with oceanic plate age, while slab-top thermal gradients correlate strongly with oceanic plate age and upper-plate thickness. Recovery rates strongly correlate with upper-plate thickness, yet show no correlation with convergence velocity or oceanic plate age. Likewise, pressure-temperature (PT) distributions of recovered markers vary among numerical experiments and generally show deviations from the rock record that cannot be explained by petrologic uncertainties alone. For example, a significant gap in marker recovery is found near 2 GPa and 550 degrees C, coinciding with the highest frequencies of exhumed HP rocks. Explanations for such a gap in marker recovery include numerical modeling uncertainties, selective sampling of exhumed HP rocks, or natural geodynamic factors not accounted for in numerical experiments.

Automated summary

Bodies of rock recovered from subducting oceanic plates at Earth's surface provide valuable records of rock processing along subduction interfaces, but comparing the rock record with numerical simulations of subduction reveals inconsistencies. This study uses a classification algorithm to identify rock recovery in numerical simulations and finds correlations between recovery pressures, convergence velocity, and plate age. The results also suggest discrepancies between the recovered markers and the rock record, possibly due to modeling uncertainties or sampling biases.