Articles | Volume 5, issue 1
https://doi.org/10.5194/gchron-5-109-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gchron-5-109-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Short communication/technical note
| 
10 Mar 2023
Short communication/technical note |
| 10 Mar 2023
| 10 Mar 2023
Technical note: colab_zirc_dims: a Google Colab-compatible toolset for automated and semi-automated measurement of mineral grains in laser ablation–inductively coupled plasma–mass spectrometry images using deep learning models
Michael C. Sitar
CORRESPONDING AUTHOR
Department of Geosciences, Colorado State University, Fort Collins,
CO 80523, USA
Ryan J. Leary
Department of Earth and Environmental Science, New Mexico Institute of
Mining and Technology, Socorro, NM 87801, USA
Related subject area
Geochronological data analysis/statistics/modelling
Technical note: RA138 calcite U–Pb LA-ICP-MS primary reference material
Revising chronological uncertainties in marine archives using global anthropogenic signals: a case study on the oceanic 13C Suess effect
The daughter–parent plot: a tool for analyzing thermochronological data
Errorchrons and anchored isochrons in IsoplotR
Short communication: Resolving the discrepancy between U–Pb age estimates for the “Likhall” bed, a key level in the Ordovician timescale
Navigating the complexity of detrital rutile provenance: methodological insights from the Neotethys Orogen in Anatolia
Solving crustal heat transfer for thermochronology using physics-informed neural networks
An optimization tool for identifying Multiple Diffusion Domain Model parameters
Minimizing the effects of Pb loss in detrital and igneous U–Pb zircon geochronology by CA-LA-ICP-MS
Modeling apparent Pb loss in zircon U–Pb geochronology
Calibration methods for laser ablation Rb–Sr geochronology: comparisons and recommendation based on NIST glass and natural reference materials
Short communication: The Wasserstein distance as a dissimilarity metric for comparing detrital age spectra and other geological distributions
ChronoLorica: introduction of a soil–landscape evolution model combined with geochronometers
Calculation of uncertainty in the (U–Th) ∕ He system
Bayesian age–depth modelling applied to varve and radiometric dating to optimize the transfer of an existing high-resolution chronology to a new composite sediment profile from Holzmaar (West Eifel Volcanic Field, Germany)
Short communication: age2exhume – a MATLAB/Python script to calculate steady-state vertical exhumation rates from thermochronometric ages and application to the Himalaya
U and Th content in magnetite and Al spinel obtained by wet chemistry and laser ablation methods: implication for (U–Th) ∕ He thermochronometer
In situ LA-ICPMS U–Pb dating of sulfates: applicability of carbonate reference materials as matrix-matched standards
An algorithm for U–Pb geochronology by secondary ion mass spectrometry
Technical note: Rapid phase identification of apatite and zircon grains for geochronology using X-ray micro-computed tomography
Simulating sedimentary burial cycles – Part 2: Elemental-based multikinetic apatite fission-track interpretation and modelling techniques illustrated using examples from northern Yukon
sandbox – creating and analysing synthetic sediment sections with R
Improving age–depth relationships by using the LANDO (“Linked age and depth modeling”) model ensemble
How many grains are needed for quantifying catchment erosion from tracer thermochronology?
Short communication: Inverse isochron regression for Re–Os, K–Ca and other chronometers
Technical note: Analytical protocols and performance for apatite and zircon (U–Th) ∕ He analysis on quadrupole and magnetic sector mass spectrometer systems between 2007 and 2020
Simulating sedimentary burial cycles – Part 1: Investigating the role of apatite fission track annealing kinetics using synthetic data
The closure temperature(s) of zircon Raman dating
On the treatment of discordant detrital zircon U–Pb data
An evaluation of Deccan Traps eruption rates using geochronologic data
geoChronR – an R package to model, analyze, and visualize age-uncertain data
Development of a multi-method chronology spanning the Last Glacial Interval from Orakei maar lake, Auckland, New Zealand
Robust isochron calculation
Resolving the timescales of magmatic and hydrothermal processes associated with porphyry deposit formation using zircon U–Pb petrochronology
Seasonal deposition processes and chronology of a varved Holocene lake sediment record from Chatyr Kol lake (Kyrgyz Republic)
Unifying the U–Pb and Th–Pb methods: joint isochron regression and common Pb correction
Exploring the advantages and limitations of in situ U–Pb carbonate geochronology using speleothems
Marcel Guillong, Elias Samankassou, Inigo A. Müller, Dawid Szymanowski, Nathan Looser, Lorenzo Tavazzani, Óscar Merino-Tomé, Juan R. Bahamonde, Yannick Buret, and Maria Ovtcharova
Geochronology, 6, 465–474, https://doi.org/10.5194/gchron-6-465-2024, https://doi.org/10.5194/gchron-6-465-2024, 2024
Short summary
Short summary
RA138 is a new reference material for U–Pb dating of carbonate samples via laser ablation inductively coupled plasma mass spectrometry. RA138 exhibits variable U–Pb ratios and consistent U content, resulting in a precise isochron with low uncertainty. Isotope dilution thermal ionization mass spectrometry analyses fix a reference age of 321.99 ± 0.65 Ma. This research advances our ability to date carbonate samples accurately, providing insights into geological processes and historical timelines.
Nil Irvalı, Ulysses S. Ninnemann, Are Olsen, Neil L. Rose, David J. R. Thornalley, Tor L. Mjell, and François Counillon
Geochronology, 6, 449–463, https://doi.org/10.5194/gchron-6-449-2024, https://doi.org/10.5194/gchron-6-449-2024, 2024
Short summary
Short summary
Marine sediments are excellent archives for reconstructing past changes in climate and ocean circulation. Yet, dating uncertainties, particularly during the 20th century, pose major challenges. Here we propose a novel chronostratigraphic approach that uses anthropogenic signals, such as the oceanic 13C Suess effect and spheroidal carbonaceous fly-ash particles, to reduce age model uncertainties in high-resolution marine archives over the 20th century.
Birk Härtel and Eva Enkelmann
Geochronology, 6, 429–448, https://doi.org/10.5194/gchron-6-429-2024, https://doi.org/10.5194/gchron-6-429-2024, 2024
Short summary
Short summary
We present a new data analysis workflow for thermochronological data based on plots of radiogenic daughter vs. radioactive parent concentration. The daughter–parent relationship helps to identify the sources of age variation. Our workflow classifies the daughter–parent relationship and provides further suggestions, e.g., if a dataset can be described by a sample age and which type of sample age to report. We also introduce Incaplot, which is software for creating daughter–parent plots.
Pieter Vermeesch
Geochronology, 6, 397–407, https://doi.org/10.5194/gchron-6-397-2024, https://doi.org/10.5194/gchron-6-397-2024, 2024
Short summary
Short summary
The age of some geological materials can be estimated from the ratio of certain radiogenic "daughter" isotopes to their radioactive "parent". However, in many cases, the age estimation process is complicated by the presence of an inherited component of non-radiogenic daughter isotopes. This paper presents an improved algorithm to estimate the radiogenic and non-radiogenic components, either separately or jointly.
André Navin Paul, Anders Lindskog, and Urs Schaltegger
Geochronology, 6, 325–335, https://doi.org/10.5194/gchron-6-325-2024, https://doi.org/10.5194/gchron-6-325-2024, 2024
Short summary
Short summary
The “Likhall” bed helps to constrain the timing of increased meteorite bombardment of the Earth during the Ordovician period. It is important to understand the timing of this meteorite bombardment when attempting to correlate it with biodiversity changes during the Ordovician period. Calibrating a good age for the “Likhall” bed is, however, challenging and benefited in this study from advances in sample preparation.
Megan A. Mueller, Alexis Licht, Andreas Möller, Cailey B. Condit, Julie C. Fosdick, Faruk Ocakoğlu, and Clay Campbell
Geochronology, 6, 265–290, https://doi.org/10.5194/gchron-6-265-2024, https://doi.org/10.5194/gchron-6-265-2024, 2024
Short summary
Short summary
Sedimentary provenance refers to the study of the origin of sedimentary rocks, tracing where sediment particles originated. Common sedimentary provenance techniques struggle to track mafic igneous and metamorphic rock sources and rutile forms in these rock types. We use rutile form ancient sedimentary rocks in Türkiye to present new recommendations and workflows for integrating rutile U–Pb ages and chemical composition into an accurate sedimentary provenance reconstruction.
Ruohong Jiao, Shengze Cai, and Jean Braun
Geochronology, 6, 227–245, https://doi.org/10.5194/gchron-6-227-2024, https://doi.org/10.5194/gchron-6-227-2024, 2024
Short summary
Short summary
We demonstrate a machine learning method to estimate the temperature changes in the Earth's crust over time. The method respects physical laws and conditions imposed by users. By using observed rock cooling ages as constraints, the method can be used to estimate the tectonic and landscape evolution of the Earth. We show the applications of the method using a synthetic rock uplift model in 1D and an evolution model of a real mountain range in 3D.
Andrew L. Gorin, Joshua M. Gorin, Marie Bergelin, and David L. Shuster
Geochronology Discuss., https://doi.org/10.5194/gchron-2024-11, https://doi.org/10.5194/gchron-2024-11, 2024
Preprint under review for GChron
Short summary
Short summary
The Multiple Diffusion Domain (MDD) model quantifies the temperature dependence of noble gas diffusivity in minerals. However, current methods for tuning MDD parameters can yield biased results, leading to underestimates of sample temperatures through geologic time. Our "MDD Tool Kit" software optimizes all MDD parameters simultaneously, overcoming these biases. We then apply this software to a previously published 40Ar/39Ar dataset (Wong, 2023) to showcase its efficacy.
Erin E. Donaghy, Michael P. Eddy, Federico Moreno, and Mauricio Ibañez-Mejia
Geochronology, 6, 89–106, https://doi.org/10.5194/gchron-6-89-2024, https://doi.org/10.5194/gchron-6-89-2024, 2024
Short summary
Short summary
Chemical abrasion (CA) is a technique that reduces or eliminates the effects of Pb loss in zircon U–Pb geochronology. However, CA has yet to be applied to large-n detrital zircon (DZ) analyses. We show that CA does not negatively impact or systematically bias U–Pb dates, improves the resolution of age populations defined by 206Pb/238U dates, and increases the percentage of concordant analyses in age populations defined by 207Pb/206Pb dates.
Glenn R. Sharman and Matthew A. Malkowski
Geochronology, 6, 37–51, https://doi.org/10.5194/gchron-6-37-2024, https://doi.org/10.5194/gchron-6-37-2024, 2024
Short summary
Short summary
The mineral zircon is widely used to determine the age of rocks based on the radioactive decay of U to Pb, but the measured U–Pb date can be too young if the zircon loses Pb. We present a method for estimating the distribution of apparent Pb loss by mathematical convolution. Applying this approach to 10 samples illustrates contrasting patterns of apparent Pb loss. This study highlights the importance of quantifying Pb loss to better understand its potential effects on zircon U–Pb dates.
Stijn Glorie, Sarah E. Gilbert, Martin Hand, and Jarred C. Lloyd
Geochronology, 6, 21–36, https://doi.org/10.5194/gchron-6-21-2024, https://doi.org/10.5194/gchron-6-21-2024, 2024
Short summary
Short summary
Radiometric dating methods, involving laser ablation as the sample introduction, require robust calibrations to reference materials with similar ablation properties to the analysed samples. In the case of the rubidium–strontium dating method, calibrations are often conducted to nano powder with different ablation characteristics than the crystalline minerals. We describe the limitations of this approach and recommend an alternative calibration method involving natural minerals.
Alex Lipp and Pieter Vermeesch
Geochronology, 5, 263–270, https://doi.org/10.5194/gchron-5-263-2023, https://doi.org/10.5194/gchron-5-263-2023, 2023
Short summary
Short summary
We propose using the Wasserstein-2 distance (W2) as an alternative to the widely used Kolmogorov–Smirnov (KS) statistic for analysing distributional data in geochronology. W2 measures the horizontal distance between observations, while KS measures vertical differences in cumulative distributions. Using case studies, we find that W2 is preferable in scenarios where the absolute age differences in observations provide important geological information. W2 has been added to the R package IsoplotR.
W. Marijn van der Meij, Arnaud J. A. M. Temme, Steven A. Binnie, and Tony Reimann
Geochronology, 5, 241–261, https://doi.org/10.5194/gchron-5-241-2023, https://doi.org/10.5194/gchron-5-241-2023, 2023
Short summary
Short summary
We present our model ChronoLorica. We coupled the original Lorica model, which simulates soil and landscape evolution, with a geochronological module that traces cosmogenic nuclide inventories and particle ages through simulations. These properties are often measured in the field to determine rates of landscape change. The coupling enables calibration of the model and the study of how soil, landscapes and geochronometers change under complex boundary conditions such as intensive land management.
Peter E. Martin, James R. Metcalf, and Rebecca M. Flowers
Geochronology, 5, 91–107, https://doi.org/10.5194/gchron-5-91-2023, https://doi.org/10.5194/gchron-5-91-2023, 2023
Short summary
Short summary
There is currently no standardized method of performing uncertainty propagation in the (U–Th) / He system, causing data interpretation difficulties. We present two methods of uncertainty propagation and describe free, open-source software (HeCalc) to apply them. Compilation of real data using only analytical uncertainty as well as 2 % and 5 % uncertainties in FT yields respective median relative date uncertainties of 2.9 %, 3.3 %, and 5.0 % for apatites and 1.7 %, 3.3 %, and 5.0 % for zircons.
Stella Birlo, Wojciech Tylmann, and Bernd Zolitschka
Geochronology, 5, 65–90, https://doi.org/10.5194/gchron-5-65-2023, https://doi.org/10.5194/gchron-5-65-2023, 2023
Short summary
Short summary
Sediment cores from the volcanic lake Holzmaar provide a very precise chronology based on tree-ring-like annual laminations or varves. We statistically combine this varve chronology with radiometric dating and tested three different methods to upgrade the age–depth model. However, only one of the three methods tested improved the dating accuracy considerably. With this work, an overview of different age integration methods is discussed and made available for increased future demands.
Peter van der Beek and Taylor F. Schildgen
Geochronology, 5, 35–49, https://doi.org/10.5194/gchron-5-35-2023, https://doi.org/10.5194/gchron-5-35-2023, 2023
Short summary
Short summary
Thermochronometric data can provide unique insights into the patterns of rock exhumation and the driving mechanisms of landscape evolution. Several well-established thermal models allow for a detailed exploration of how cooling rates evolved in a limited area or along a transect, but more regional analyses have been challenging. We present age2exhume, a thermal model that can be used to rapidly provide a synoptic overview of exhumation rates from large regional thermochronologic datasets.
Marianna Corre, Arnaud Agranier, Martine Lanson, Cécile Gautheron, Fabrice Brunet, and Stéphane Schwartz
Geochronology, 4, 665–681, https://doi.org/10.5194/gchron-4-665-2022, https://doi.org/10.5194/gchron-4-665-2022, 2022
Short summary
Short summary
This study is focused on the accurate measurement of U and Th by wet chemistry and laser ablation methods to improve (U–Th)/He dating of magnetite and spinel. The low U–Th content and the lack of specific U–Th standards significantly limit the accuracy of (U–Th)/He dating. Obtained U–Th results on natural and synthetic magnetite and aluminous spinel samples analyzed by wet chemistry methods and LA-ICP-MS sampling have important implications for the (U–Th)/He method and dates interpretation.
Aratz Beranoaguirre, Iuliana Vasiliev, and Axel Gerdes
Geochronology, 4, 601–616, https://doi.org/10.5194/gchron-4-601-2022, https://doi.org/10.5194/gchron-4-601-2022, 2022
Short summary
Short summary
U–Pb dating by the in situ laser ablation mass spectrometry (LA-ICPMS) technique requires reference materials of the same nature as the samples to be analysed. Here, we have explored the suitability of using carbonate materials as a reference for sulfates, since there is no sulfate reference material. The results we obtained are satisfactory, and thus, from now on, the sulfates can also be analysed.
Pieter Vermeesch
Geochronology, 4, 561–576, https://doi.org/10.5194/gchron-4-561-2022, https://doi.org/10.5194/gchron-4-561-2022, 2022
Short summary
Short summary
Secondary ion mass spectrometry (SIMS) is the oldest and most sensitive analytical technique for in situ U–Pb geochronology. This paper introduces a new algorithm for SIMS data reduction that treats data as
compositional data, which means that the relative abundances of 204Pb, 206Pb, 207Pb, and 238Pb are processed within a tetrahedral data space or
simplex. The new method is implemented in an eponymous computer programme that is compatible with the two dominant types of SIMS instruments.
Emily H. G. Cooperdock, Florian Hofmann, Ryley M. C. Tibbetts, Anahi Carrera, Aya Takase, and Aaron J. Celestian
Geochronology, 4, 501–515, https://doi.org/10.5194/gchron-4-501-2022, https://doi.org/10.5194/gchron-4-501-2022, 2022
Short summary
Short summary
Apatite and zircon are the most widely used minerals for dating rocks, but they can be difficult to identify in some crushed rock samples. Incorrect mineral identification results in wasted analytical resources and inaccurate data. We show how X-ray computed tomography can be used to efficiently and accurately distinguish apatite from zircon based on density variations, and provide non-destructive 3D grain-specific size, shape, and inclusion information for improved data quality.
Dale R. Issler, Kalin T. McDannell, Paul B. O'Sullivan, and Larry S. Lane
Geochronology, 4, 373–397, https://doi.org/10.5194/gchron-4-373-2022, https://doi.org/10.5194/gchron-4-373-2022, 2022
Short summary
Short summary
Phanerozoic sedimentary rocks of northern Canada have compositionally heterogeneous detrital apatite with high age dispersion caused by differential thermal annealing. Discrete apatite fission track kinetic populations with variable annealing temperatures are defined using elemental data but are poorly resolved using conventional parameters. Inverse thermal modelling of samples from northern Yukon reveals a record of multiple heating–cooling cycles consistent with geological constraints.
Michael Dietze, Sebastian Kreutzer, Margret C. Fuchs, and Sascha Meszner
Geochronology, 4, 323–338, https://doi.org/10.5194/gchron-4-323-2022, https://doi.org/10.5194/gchron-4-323-2022, 2022
Short summary
Short summary
The R package sandbox is a collection of functions that allow the creation, sampling and analysis of fully virtual sediment sections, like having a virtual twin of real-world deposits. This article introduces the concept, features, and workflows required to use sandbox. It shows how a real-world sediment section can be mapped into the model and subsequently addresses a series of theoretical and practical questions, exploiting the flexibility of the model framework.
Gregor Pfalz, Bernhard Diekmann, Johann-Christoph Freytag, Liudmila Syrykh, Dmitry A. Subetto, and Boris K. Biskaborn
Geochronology, 4, 269–295, https://doi.org/10.5194/gchron-4-269-2022, https://doi.org/10.5194/gchron-4-269-2022, 2022
Short summary
Short summary
We use age–depth modeling systems to understand the relationship between age and depth in lake sediment cores. However, depending on which modeling system we use, the model results may vary. We provide a tool to link different modeling systems in an interactive computational environment and make their results comparable. We demonstrate the power of our tool by highlighting three case studies in which we test our application for single-sediment cores and a collection of multiple sediment cores.
Andrea Madella, Christoph Glotzbach, and Todd A. Ehlers
Geochronology, 4, 177–190, https://doi.org/10.5194/gchron-4-177-2022, https://doi.org/10.5194/gchron-4-177-2022, 2022
Short summary
Short summary
Cooling ages date the time at which minerals cross a certain isotherm on the way up to Earth's surface. Such ages can be measured from bedrock material and river sand. If spatial variations in bedrock ages are known in a river catchment, the spatial distribution of erosion can be inferred from the distribution of the ages measured from the river sand grains. Here we develop a new tool to help such analyses, with particular emphasis on quantifying uncertainties due to sample size.
Yang Li and Pieter Vermeesch
Geochronology, 3, 415–420, https://doi.org/10.5194/gchron-3-415-2021, https://doi.org/10.5194/gchron-3-415-2021, 2021
Short summary
Short summary
A conventional isochron is a straight-line fit to two sets of isotopic ratios, D/d and P/d, where P is the radioactive parent, D is the radiogenic daughter, and d is a second isotope of the daughter element. The slope of this line is proportional to the age of the system. An inverse isochron is a linear fit through d/D and P/D. The horizontal intercept of this line is inversely proportional to the age. The latter approach is preferred when d<D, which is the case in Re–Os and K–Ca geochronology.
Cécile Gautheron, Rosella Pinna-Jamme, Alexis Derycke, Floriane Ahadi, Caroline Sanchez, Frédéric Haurine, Gael Monvoisin, Damien Barbosa, Guillaume Delpech, Joseph Maltese, Philippe Sarda, and Laurent Tassan-Got
Geochronology, 3, 351–370, https://doi.org/10.5194/gchron-3-351-2021, https://doi.org/10.5194/gchron-3-351-2021, 2021
Short summary
Short summary
Apatite and zircon (U–Th) / He thermochronology is now a mainstream tool to reconstruct Earth's evolution through the history of cooling and exhumation over the first dozen kilometers. The geological implications of these data rely on the precision of measurements of He, U, Th, and Sm contents in crystals. This technical note documents the methods for He thermochronology developed at the GEOPS laboratory, Paris-Saclay University, that allow (U–Th) / He data to be obtained with precision.
Kalin T. McDannell and Dale R. Issler
Geochronology, 3, 321–335, https://doi.org/10.5194/gchron-3-321-2021, https://doi.org/10.5194/gchron-3-321-2021, 2021
Short summary
Short summary
We generated a synthetic dataset applying published kinetic models and distinct annealing kinetics for the apatite fission track and (U–Th)/He methods using a predetermined thermal history. We then tested how well the true thermal history could be recovered under different data interpretation schemes and geologic constraint assumptions using the Bayesian QTQt software. Our results demonstrate that multikinetic data increase time–temperature resolution and can constrain complex thermal histories.
Birk Härtel, Raymond Jonckheere, Bastian Wauschkuhn, and Lothar Ratschbacher
Geochronology, 3, 259–272, https://doi.org/10.5194/gchron-3-259-2021, https://doi.org/10.5194/gchron-3-259-2021, 2021
Short summary
Short summary
We carried out thermal annealing experiments between 500 and 1000 °C to determine the closure temperature of radiation-damage annealing in zircon (ZrSiO4). Our results show that the different Raman bands of zircon respond differently to annealing. The repair is highest for the external rotation Raman band near 356.6 cm−1. The closure temperature estimates range from 250 to 370 °C for different bands. The differences in closure temperatures offer the prospect of multi-T zircon Raman dating.
Pieter Vermeesch
Geochronology, 3, 247–257, https://doi.org/10.5194/gchron-3-247-2021, https://doi.org/10.5194/gchron-3-247-2021, 2021
Short summary
Short summary
This paper shows that the current practice of filtering discordant U–Pb data based on the relative difference between the 206Pb/238U and 207Pb/206Pb ages is just one of several possible approaches to the problem and demonstrably not the best one. An alternative approach is to define discordance in terms of isotopic composition, as a log ratio distance between the measurement and the concordia line. Application to real data indicates that this reduces the positive bias of filtered age spectra.
Blair Schoene, Michael P. Eddy, C. Brenhin Keller, and Kyle M. Samperton
Geochronology, 3, 181–198, https://doi.org/10.5194/gchron-3-181-2021, https://doi.org/10.5194/gchron-3-181-2021, 2021
Short summary
Short summary
We compare two published U–Pb and 40Ar / 39Ar geochronologic datasets to produce eruption rate models for the Deccan Traps large igneous province. Applying the same approach to each dataset, the resulting models agree well, but the higher-precision U–Pb dataset results in a more detailed eruption model than the lower-precision 40Ar / 39Ar data. We explore sources of geologic uncertainty and reiterate the importance of systematic uncertainties in comparing U–Pb and 40Ar / 39Ar datasets.
Nicholas P. McKay, Julien Emile-Geay, and Deborah Khider
Geochronology, 3, 149–169, https://doi.org/10.5194/gchron-3-149-2021, https://doi.org/10.5194/gchron-3-149-2021, 2021
Short summary
Short summary
This paper describes geoChronR, an R package that streamlines the process of quantifying age uncertainties, propagating uncertainties through several common analyses, and visualizing the results. In addition to describing the structure and underlying theory of the package, we present five real-world use cases that illustrate common workflows in geoChronR. geoChronR is built on the Linked PaleoData framework, is open and extensible, and we welcome feedback and contributions from the community.
Leonie Peti, Kathryn E. Fitzsimmons, Jenni L. Hopkins, Andreas Nilsson, Toshiyuki Fujioka, David Fink, Charles Mifsud, Marcus Christl, Raimund Muscheler, and Paul C. Augustinus
Geochronology, 2, 367–410, https://doi.org/10.5194/gchron-2-367-2020, https://doi.org/10.5194/gchron-2-367-2020, 2020
Short summary
Short summary
Orakei Basin – a former maar lake in Auckland, New Zealand – provides an outstanding sediment record over the last ca. 130 000 years, but an age model is required to allow the reconstruction of climate change and volcanic eruptions contained in the sequence. To construct a relationship between depth in the sediment core and age of deposition, we combined tephrochronology, radiocarbon dating, luminescence dating, and the relative intensity of the paleomagnetic field in a Bayesian age–depth model.
Roger Powell, Eleanor C. R. Green, Estephany Marillo Sialer, and Jon Woodhead
Geochronology, 2, 325–342, https://doi.org/10.5194/gchron-2-325-2020, https://doi.org/10.5194/gchron-2-325-2020, 2020
Short summary
Short summary
The standard approach to isochron calculation assumes that the distribution of uncertainties on the data arising from isotopic analysis is strictly Gaussian. This excludes datasets that have more scatter, even though many appear to have age significance. Our new approach requires only that the central part of the uncertainty distribution of the data defines a "spine" in the trend of the data. A robust statistics approach is used to locate the spine, and an implementation in Python is given.
Simon J. E. Large, Jörn-Frederik Wotzlaw, Marcel Guillong, Albrecht von Quadt, and Christoph A. Heinrich
Geochronology, 2, 209–230, https://doi.org/10.5194/gchron-2-209-2020, https://doi.org/10.5194/gchron-2-209-2020, 2020
Short summary
Short summary
The integration of zircon geochemistry and U–Pb geochronology (petrochronology) allows us to improve our understanding of magmatic processes. Here we could reconstruct the ~300 kyr evolution of the magma reservoir that sourced the magmas, fluids and metals to form the Batu Hijau porphyry Cu–Au deposit. The application of in situ LA-ICP-MS and high-precision CA–ID–TIMS geochronology to the same zircons further allowed an assessment of the strengths and limitations of the different techniques.
Julia Kalanke, Jens Mingram, Stefan Lauterbach, Ryskul Usubaliev, Rik Tjallingii, and Achim Brauer
Geochronology, 2, 133–154, https://doi.org/10.5194/gchron-2-133-2020, https://doi.org/10.5194/gchron-2-133-2020, 2020
Short summary
Short summary
Our study presents the first seasonally laminated (varved) sediment record covering almost the entire Holocene in high mountainous arid Central Asia. The established floating varve chronology is confirmed by two terrestrial radiocarbon dates, whereby aquatic radiocarbon dates reveal decreasing reservoir ages up core. Changes in seasonal deposition characteristics are attributed to changes in runoff and precipitation and/or to evaporative summer conditions.
Pieter Vermeesch
Geochronology, 2, 119–131, https://doi.org/10.5194/gchron-2-119-2020, https://doi.org/10.5194/gchron-2-119-2020, 2020
Short summary
Short summary
The U–Pb method is one of the most powerful and versatile methods in the geochronological toolbox. With two isotopes of uranium decaying to two different isotopes of lead, the U–Pb method offers an internal quality control that is absent from most other geochronological techniques. U-bearing minerals often contain significant amounts of Th, which decays to a third Pb isotope. This paper presents an algorithm to jointly process all three chronometers at once.
Jon Woodhead and Joseph Petrus
Geochronology, 1, 69–84, https://doi.org/10.5194/gchron-1-69-2019, https://doi.org/10.5194/gchron-1-69-2019, 2019
Short summary
Short summary
Recently developed methods for in situ U–Pb age determination in carbonates have found widespread application, but the benefits and limitations of the method over bulk analysis approaches have yet to be fully explored. Here we use speleothems – cave carbonates such as stalagmites and flowstones – to investigate the utility of these in situ dating methodologies for challenging matrices with low U and Pb contents and predominantly late Cenozoic ages.
Cited articles
Abadi, M., Agarwal, A., Barham, P., Brevdo, E., Chen, Z., Citro, C., Corrado, G. S., Davis, A., Dean, J., Devin, M., Ghemawat, S., Goodfellow, I., Harp, A., Irving, G., Isard, M., Jozefowicz, R., Jia, Y., Kaiser, L., Kudlur, M., Levenberg, J., Mané, D., Schuster, M., Monga, R., Moore, S., Murray, D., Olah, C., Shlens, J., Steiner, B., Sutskever, I., Talwar, K., Tucker, P., Vanhoucke, V., Vasudevan, V., Viégas, F., Vinyals, O., Warden, P., Wattenberg, M., Wicke, M., Yu, Y., and Zheng, X.: TensorFlow, Large-scale machine learning on heterogeneous systems, Zenodo [code], https://doi.org/10.5281/zenodo.4724125, 2015.
Alzubaidi, L., Zhang, J., Humaidi, A. J., Al-Dujaili, A., Duan, Y.,
Al-Shamma, O., Santamaría, J., Fadhel, M. A., Al-Amidie, M., and
Farhan, L.: Review of deep learning: concepts, CNN architectures,
challenges, applications, future directions, J. Big Data, 8, 53,
https://doi.org/10.1186/s40537-021-00444-8, 2021.
Augustsson, C., Voigt, T., Bernhart, K., Kreißler, M., Gaupp, R.,
Gärtner, A., Hofmann, M., and Linnemann, U.: Zircon size-age sorting and
source-area effect: The German Triassic Buntsandstein Group, Sediment.
Geol., 375, 218–231, https://doi.org/10.1016/j.sedgeo.2017.11.004, 2018.
Bradski, G.: The OpenCV Library, Dr. Dobb's Journal of Software Tools, 25, 120–125, 2000.
Bukharev, A., Budennyy, S., Lokhanova, O., Belozerov, B., and Zhukovskaya,
E.: The Task of Instance Segmentation of Mineral Grains in Digital Images of
Rock Samples (Thin Sections), in: 2018 International Conference on
Artificial Intelligence Applications and Innovations (IC-AIAI), 2018
International Conference on Artificial Intelligence Applications and
Innovations (IC-AIAI), IC-AIAI 2018, Nicosia, Cyprus, 31 October–2 November 2018,
18–23, https://doi.org/10.1109/IC-AIAI.2018.8674449,
2018.
Cantine, M. D., Setera, J. B., Vantongeren, J. A., Mwinde, C., and Bergmann,
K. D.: Grain size and transport biases in an Ediacaran detrital zircon
record, J. Sediment. Res., 91, 913–928,
https://doi.org/10.2110/jsr.2020.153, 2021.
Cooperdock, E. H. G., Ketcham, R. A., and Stockli, D. F.: Resolving the
effects of 2-D versus 3-D grain measurements on apatite (U–Th)
Dutta, A. and Zisserman, A.: The VIA Annotation Software for Images, Audio
and Video, Proc. 27th ACM Int. Conf. Multimed., Nice, France, 21–25 October 2019, 2276–2279,
https://doi.org/10.1145/3343031.3350535, 2019.
Filippo, M. P., da Fonseca Martins Gomes, O., da Costa, G. A. O. P., and
Mota, G. L. A.: Deep learning semantic segmentation of opaque and non-opaque
minerals from epoxy resin in reflected light microscopy images, Miner.
Eng., 170, 107007, https://doi.org/10.1016/j.mineng.2021.107007,
2021.
Finzel, E. S.: Detrital zircon microtextures and U-PB geochronology of Upper
Jurassic to Paleocene strata in the distal North American Cordillera
foreland basin, Tectonics, 36, 1295–1316,
https://doi.org/10.1002/2017TC004549, 2017.
Harris, C. R., Millman, K. J., van der Walt, S. J., Gommers, R., Virtanen,
P., Cournapeau, D., Wieser, E., Taylor, J., Berg, S., Smith, N. J., Kern,
R., Picus, M., Hoyer, S., van Kerkwijk, M. H., Brett, M., Haldane, A.,
Fernández del Río, J., Wiebe, M., Peterson, P.,
Gérard-Marchant, P., Sheppard, K., Reddy, T., Weckesser, W., Abbasi, H.,
Gohlke, C., and Oliphant, T. E.: Array programming with NumPy, Nature, 585,
357–362, https://doi.org/10.1038/s41586-020-2649-2, 2020.
He, K., Zhang, X., Ren, S., and Sun, J.: Deep Residual Learning for Image
Recognition, arXiv [cs], https://doi.org/10.48550/arXiv.1512.03385, 2015.
He, K., Gkioxari, G., Dollár, P., and Girshick, R.: Mask R-CNN, arXiv [cs], https://doi.org/10.48550/arXiv.1703.06870, 2018.
Hunter, J.D.: Matplotlib: A 2D Graphics Environment, Comput. Sci. Eng., 9,
90–95, https://doi.org/10.1109/MCSE.2007.55, 2007.
Ibañez-Mejia, M., Pullen, A., Pepper, M., Urbani, F., Ghoshal, G., and
Ibañez-Mejia, J. C.: Use and abuse of detrital zircon U-Pb
geochronology – A case from the Río Orinoco delta, eastern Venezuela,
Geology, 46, 1019–1022, https://doi.org/10.1130/G45596.1, 2018.
Jiang, F., Li, N., and Zhou, L.: Grain segmentation of sandstone images
based on convolutional neural networks and weighted fuzzy clustering, IET
Image Process., 14, 3499–3507, https://doi.org/10.1049/iet-ipr.2019.1761,
2020.
Kluyver, T., Ragan-Kelley, B., Pérez, F., Granger, B., Bussonnier, M.,
Frederic, J., Kelley, K., Hamrick, J., Grout, J., Corlay, S., Ivanov, P.,
Avila, D., Abdalla, S., and Willing, C.: Jupyter Notebooks – a publishing
format for reproducible computational workflows, in: Positioning and Power
in Academic Publishing, Players, Agents and Agendas, Göttingen, Germany, 7–9 June 2016, 87–90, https://doi.org/10.3233/978-1-61499-649-1-87, 2016.
Latif, G., Bouchard, K., Maitre, J., Back, A., and Bédard, L. P.:
Deep-Learning-Based Automatic Mineral Grain Segmentation and Recognition,
Minerals, 12, 455, https://doi.org/10.3390/min12040455, 2022.
Lawrence, R. L., Cox, R., Mapes, R. W., and Coleman, D. S.: Hydrodynamic
fractionation of zircon age populations, GSA Bull., 123, 295–305,
https://doi.org/10.1130/B30151.1, 2011.
Leary, R. J., Smith, M. E., and Umhoefer, P.: Grain-Size Control on Detrital
Zircon Cycloprovenance in the Late Paleozoic Paradox and Eagle Basins, USA,
J. Geophys. Res.-Sol. Ea., 125, e2019JB019226,
https://doi.org/10.1029/2019JB019226, 2020a.
Leary, R. J., Umhoefer, P., Smith, M. E., Smith, T. M., Saylor, J. E.,
Riggs, N., Burr, G., Lodes, E., Foley, D., Licht, A., Mueller, M. A., and
Baird, C.: Provenance of Pennsylvanian–Permian sedimentary rocks associated
with the Ancestral Rocky Mountains orogeny in southwestern Laurentia:
Implications for continental-scale Laurentian sediment transport systems,
Lithosphere, 12, 88–121, https://doi.org/10.1130/L1115.1, 2020b.
Leary, R. J., Smith, M. E., and Umhoefer, P.: Mixed eolian–longshore
sediment transport in the late Paleozoic Arizona shelf and Pedregosa basin,
USA: A case study in grain-size analysis of detrital-zircon datasets, J.
Sediment. Res., 92, 676–694, https://doi.org/10.2110/jsr.2021.101, 2022.
Lee, Y. and Park, J.: CenterMask: Real-Time Anchor-Free Instance
Segmentation, arXiv [cs], https://doi.org/10.48550/ARXIV.1911.06667, 2020.
Lee, Y., Hwang, J., Lee, S., Bae, Y., and Park, J.: An Energy and
GPU-Computation Efficient Backbone Network for Real-Time Object Detection,
arXiv [cs], https://doi.org/10.48550/ARXIV.1904.09730, 2019.
Lin, T.-Y., Dollár, P., Girshick, R., He, K., Hariharan, B., and
Belongie, S.: Feature Pyramid Networks for Object Detection, arXiv [cs],
https://doi.org/10.48550/arXiv.1612.03144, 2016.
Liu, Z., Lin, Y., Cao, Y., Hu, H., Wei, Y., Zhang, Z., Lin, S., and Guo, B.:
Swin Transformer: Hierarchical Vision Transformer using Shifted Windows, arXiv [cs],
https://doi.org/10.48550/ARXIV.2103.14030, 2021.
McKinney, W.: Data Structures for Statistical Computing in Python, in:
Proceedings of the 9th Python in Science Conference, 9th Python in Science Conference, Austin, USA, 28 June–3 July 2019, 56–61, https://doi.org/10.25080/Majora-92bf1922-00a, 2010.
Muhlbauer, J. G., Fedo, C. M., and Farmer, G. L.: Influence of textural
parameters on detrital-zircon age spectra with application to provenance and
paleogeography during the Ediacaran–Terreneuvian of southwestern Laurentia,
GSA Bull., 129, 1585–1601, https://doi.org/10.1130/B31611.1, 2017.
Murray, A., Kemenade, H. van, wiredfool, Clark (Alex), J. A., Karpinsky, A., Baranovič, O., Gohlke, C., Dufresne, J., DWesl, Schmidt, D., Kopachev, K., Houghton, A., Mani, S., Landey, S., vashek, Ware, J., Piolie, Douglas, J., T, S., Caro, D., Martinez, U., Kossouho, S., Lahd, R., Lee, A., Brown, E. W., Tonnhofer, O., Bonfill, M., and Base, M.: python-pillow/Pillow: 9.4.0, Zenodo [code], https://doi.org/10.5281/zenodo.7498081, 2023.
Nachtergaele, S. and De Grave, J.: AI-Track-tive: open-source software for
automated recognition and counting of surface semi-tracks using computer
vision (artificial intelligence), Geochronology, 3, 383–394,
https://doi.org/10.5194/gchron-3-383-2021, 2021.
Otsu, N.: A Threshold Selection Method from Gray-Level Histograms, IEEE
Trans. Syst. Man Cybern., 9, 62–66,
https://doi.org/10.1109/TSMC.1979.4310076, 1979.
Paszke, A., Gross, S., Massa, F., Lerer, A., Bradbury, J., Chanan, G.,
Killeen, T., Lin, Z., Gimelshein, N., Antiga, L., Desmaison, A., Köpf,
A., Yang, E., DeVito, Z., Raison, M., Tejani, A., Chilamkurthy, S., Steiner,
B., Fang, L., Bai, J., and Chintala, S.: PyTorch: An Imperative Style, High-Performance Deep Learning Library, in: Proceedings of the 33rd International Conference on Neural Information Processing Systems, NeurIPS 2019, Vancouver, Canada, 8–14 December 2019, 8024–8025, https://doi.org/10.48550/ARXIV.1912.01703, 2019.
Pérez, F. and Granger, B. E.: IPython: a System for Interactive
Scientific Computing, Comput. Sci. Eng., 9, 21–29,
https://doi.org/10.1109/MCSE.2007.53, 2007.
PyPI (Python Package Index): https://pypi.org/, last access: 13 April 2022.
Resentini, A., AndÒ, S., and Garzanti, E.: Quantifying Roundness of
Detrital Minerals By Image Analysis: Sediment Transport, Shape Effects, and
Provenance Implications, J. Sediment. Res., 88, 276–289,
https://doi.org/10.2110/jsr.2018.12, 2018.
Scharf, T., Kirkland, C. L., Daggitt, M. L., Barham, M., and Puzyrev, V.:
AnalyZr: A Python application for zircon grain image segmentation and shape
analysis, Comput. Geosci., 162, 105057,
https://doi.org/10.1016/j.cageo.2022.105057, 2022.
Schindelin, J., Arganda-Carreras, I., Frise, E., Kaynig, V., Longair, M.,
Pietzsch, T., Preibisch, S., Rueden, C., Saalfeld, S., Schmid, B., Tinevez,
J.-Y., White, D. J., Hartenstein, V., Eliceiri, K., Tomancak, P., and
Cardona, A.: Fiji: an open-source platform for biological-image analysis,
Nat. Method., 9, 676–682, https://doi.org/10.1038/nmeth.2019, 2012.
Sitar, M. C.: colab_zirc_dims Video Tutorial & Demo v1.0.10, Youtube [video supplement], https://www.youtube.com/watch?v=ZdO6B-dvHm0 (last access: 28 February 2023), 2022a.
Sitar, M. C.: MCSitar/colab_zirc_dims:
v1.0.10, Zenodo [code], https://doi.org/10.5281/zenodo.7425633, 2022b.
Sitar, M. C. and Leary, R. J.: colab_zirc_dims: full results, datasets, and replication code repository, Zenodo [code and data set],
https://doi.org/10.5281/zenodo.7434851, 2022.
Soloy, A., Turki, I., Fournier, M., Costa, S., Peuziat, B., and Lecoq, N.: A
Deep Learning-Based Method for Quantifying and Mapping the Grain Size on
Pebble Beaches, Remote Sens., 12, 3659, https://doi.org/10.3390/rs12213659,
2020.
Sundell, K., Gehrels, G. E., Quinn, D. P., Pecha, M., Giesler, D., Pepper,
M., George, S., and White, A.: Agecalcml: An Open-Source Matlab-Based Data
Reduction Platform for La-Icp-Ms Geochronology and Geochemistry Data from
the Arizona Laserchron Center, GSA 2020 Connects Online, 358944,
https://doi.org/10.1130/abs/2020AM-358944, 2020.
Teledyne Photon Machines: Chromium 2.4, https://www.teledynecetac.com/support/software, last access: 28 February 2023.
van der Walt, S., Schönberger, J. L., Nunez-Iglesias, J., Boulogne, F., Warner, J. D., Yager, N., Gouillart, E., Yu, T., and the scikit-image contributors: scikit-image: Image processing in Python, PeerJ, 2, e453,
https://doi.org/10.7717/peerj.453, 2014.
Van Rossum, G.: The Python Language Reference, https://docs.python.org/3.8/reference/, last access: 28 February 2023.
Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A.
N., Kaiser, L., and Polosukhin, I.: Attention Is All You Need, in: Advances in Neural Information Processing Systems, NeurIPS 2017, Long Beach, USA, 4–9 December 2017, 7181,
https://doi.org/10.48550/arXiv.1706.03762, 2017.
Wu, Y., Kirillov, A., Massa, F., Lo, W.-Y., and Girshick, R.: Detectron2, https://github.com/facebookresearch/detectron2 (last access: 28 February 2023), 2019.
Ye, H., Yang, Y., and L3str4nge: SwinT_detectron2: v1.2, Zenodo [code], https://doi.org/10.5281/ZENODO.6468976, 2021.
Short summary
We developed code to automatically and semi-automatically measure dimensions of detrital mineral grains in reflected-light images saved at laser ablation–inductively coupled plasma–mass spectrometry facilities that use Chromium targeting software. Our code uses trained deep learning models to segment grain images with greater accuracy than is achievable using other segmentation techniques. We implement our code in Jupyter notebooks which can also be run online via Google Colab.
We developed code to automatically and semi-automatically measure dimensions of detrital mineral...
