Quantifying the effect of late bombardment on terrestrial zircons
The first 500 million years of Earth history is thought to be a period of intense planetary bombardment, but the timing and flux of this meteorite bombardment is poorly understood. In particular, on the basis of an inferred lunar impact history, some workers have hypothesized a ~3.9 Ga terminal cataclysm (TC) in which there was marked increase in the impact flux affecting the Moon, the Earth and possibly other terrestrial planets. Minerals that survived this enigmatic period offer a way to test early planetary bombardment models as they may contain telltale micro- to nanoscale shock features. Here, we present results from a numerical modeling calculation that assesses the probability that a zircon residing in the crust would escape shock melting or shock deformation during a TC bombardment event. Even with conservative pressure estimates for zircon shock deformation and intermediate bombardment intensities, we find that only ~6% of ≥4.0 Ga crust would be expected to survive a 3.9 Ga cataclysm without experiencing either complete melting or zircon shock metamorphism. In this study, we couple this modeling with a search for shock effects in the oldest zircons from the Acasta Gneiss Complex, which would have been present in the Earth's crust during a putative 3.9 Ga TC. Spatially correlated electron and NanoSIMS ion microscopy of 4.02 Ga igneous zircons from Acasta reveals no evidence of ancient shock. These data, together with similar results from other Hadean zircon suites, confirm that a post-Hadean TC is unlikely to have occurred. We suggest that the dearth of pre-3.9 Ga terrestrial crust and zircons is instead best explained by endogenic processes related to the mechanisms of early crust formation. Our modeling allows us to evaluate bombardment scenarios from the terrestrial zircon record by applying probabilistic interpretations to zircon shock deformation data. This approach will be valuable for other planetary bodies, allowing broader conclusions to be drawn from geographically limited datasets.