An exploratory study of “large‐n” detrital zircon geochronology of the Book Cliffs, UT via rapid (3 s/analysis) U–Pb dating

Abstract

Detrital zircon (DZ) U–Pb geochronology has improved the way geologists approach questions of sediment provenance and stratigraphic age. However, there is debate about what constitutes an appropriate sample size (i.e., the number of dates in a DZ sample, n), which depends on project objectives, sample complexity, and, critically, analytical budget. Additionally, there is ongoing concern about bias introduced by zircon grain size. We tested a recently developed rapid (3 s/analysis) data acquisition method by multicollector laser ablation‐inductively coupled plasma‐mass spectrometry (LA‐ICP‐MS) that incorporates an automated selection routine and calculates two‐dimensional grain geometry from polished sample surfaces. Eleven samples were analysed from below and above the Late Cretaceous (Campanian) basal Castlegate unconformity of the Book Cliffs, Utah, in a down‐depositional‐dip transect including Price, Horse, Tusher, and Thompson canyons. 12,448 new concordant dates were generated during two measurement sessions. Results are consistent with recent studies suggesting there is no major provenance change and little time (1–2 Myr) represented across the unconformity. Grain size and sample size both exert a strong control on sample dissimilarity. Age distributions constructed from subsamples of large grains are systematically less similar to whole samples; age distributions composed of small grains are overall more similar to whole samples. As such, North American sediment sources that produce large grains such as the Grenville and Yavapi‐Mazatzal belts can bias age distributions if only large grains are analysed. A sample size of n = 100 is inadequate for characterizing age distributions as complex as those of the Book Cliffs, whereas a sample size of n = 300 provides good characterization. Sample size of n ≈ 1000 or more is unnecessary unless project objectives include scanning for subordinate age groups, such as when identifying the youngest grains for calculating a maximum depositional age (MDA). Dates used in MDA calculations acquired with rapid acquisition are best re‐analysed with longer LA‐ICP‐MS acquisition methods or isotope dilution thermal ionization mass spectrometry for increased accuracy and precision. We include new MATLAB code and open‐source software programs, DZpick and DZmda, for automated spot picking and calculating MDAs.

Recently Identified Mesoproterozoic Strata in South‐Central Idaho Document Late‐Stage Rifting of the Nuna Supercontinent in Western Laurentia

“…MDA calculations are reported for existing methods using DZmda (Sundell et al, 2024;Tables S5 and S6 in Supporting Information S2) including youngest single grain, graphical peak, and grain cluster at 1σ or 2σ (Dickinson & Gehrels, 2009;YSG, YPP, YGC1s, and YGC2s, respectively), weighted mean of the three youngest grains that overlap in uncertainty (Y3Zo), τ method (Barbeau et al, 2009;TAU), youngest statistical population (Coutts et al, 2019;YSP), Gaussian fit to the youngest PDP mode (e.g., Saylor et al, 2023;YGF), and maximum likelihood age (Vermeesch, 2021;MLA). MLA was calculated using IsoplotR (Vermeesch, 2021), with uncertainties reported as 95% confidence intervals within the minimum finite mixture model; both 3parameter and 4-parameter results are reported (Table S5 in Supporting Information S2).…”