Leaving no zircon unturned: quantifying the impact of handpicking sharply faceted detrital zircon on maximum depositional age analysis

ABSTRACT Using the youngest detrital-zircon date(s) of a sedimentary deposit to constrain its maximum depositional age (MDA) is a widespread and growing application of geochronology. Most MDA studies analyze zircon grains at random, but this strategy can be costly and inefficient in cases where the youngest age group is only a small fraction of the population. We propose that handpicking sharply faceted zircon grains will increase the likelihood of encountering first-cycle zircon that have not undergone significant sedimentary transport, thus producing MDA estimates that are closer to the depositional age. We evaluate this procedure by conducting intra-sample comparisons of randomly selected versus handpicked zircon separates from 30 samples analyzed via laser-ablation–inductively coupled plasma–mass spectrometry (LA–ICP–MS). Our results show that handpicking zircon produces an overall shift towards younger ages in comparison to their randomly analyzed counterparts by an average of ∼ 406 Myr. In randomly analyzed separates, only 1.6% of grains were within 5 Myr of an independent estimate of the MDA, while handpicked separates contained 14.2%, an approximately nine-fold increase. However, handpicking can also lead to selection of older grains if they have been minimally transported, as with one handpicked Mesozoic sample that yielded 81% of ∼ 1.1 Ga zircon interpreted to be derived from a local granitic source. Handpicking is most effective in samples where young, sharply faceted grains are diluted by older, rounded grains, as with one sample that exhibited an ∼ 18-fold increase in the proportion of near-depositional-age zircons relative to its counterpart where grain selection was random. Because handpicking zircon imparts a severe bias on the resulting U–Pb age distribution, we recommend that two separate aliquots be used for quantitative provenance characterization through random analysis and MDA analysis through handpicking.