Abstract
Abstract. Chronological uncertainty is a hallmark of the paleoenvironmental sciences and geosciences. While many tools have been made available to researchers to quantify age uncertainties suitable for various settings and assumptions, disparate tools and output formats often discourage integrative approaches. In addition, associated tasks like propagating age-model uncertainties to subsequent analyses, and visualizing the results, have received comparatively little attention in the literature and available software. Here, we describe geoChronR, an open-source R package to facilitate these tasks. geoChronR is built around an emerging data standard (Linked PaleoData, or LiPD) and offers access to four popular age-modeling techniques (Bacon, BChron, OxCal, BAM). The output of these models is used to conduct ensemble data analysis, quantifying the impact of chronological uncertainties on common analyses like correlation, regression, principal component, and spectral analyses by repeating the analysis across a large collection of plausible age models. We present five real-world use cases to illustrate how geoChronR may be used to facilitate these tasks, visualize the results in intuitive ways, and store the results for further analysis, promoting transparency and reusability.
Highlights
1.1 BackgroundQuantifying chronological uncertainties, and how they influence the understanding of past changes in Earth systems, is a unique and fundamental challenge of the paleoenvironmental sciences and geosciences
1. improving analytical techniques that allow for more precise age determination on smaller and context-specific samples (e.g., Eggins et al, 2005; Santos et al, 2010; Zander et al, 2020); 2. refining our understanding of how past changes in the Earth system impact chronostratigraphy, for example, improvements to the radiocarbon calibration curve (Reimer et al, 2011, 2013, 2020) and advances in our understanding of spatial variability in cosmogenic production rates used in exposure dating (Balco et al, 2009; Masarik and Beer, 2009; Charreau et al, 2019); and
GeoChronR provides an accessible, open-source, and extensible software package of industry-standard and cutting-edge tools that provides users with a single environment to create, analyze, and visualize time-uncertain data. geoChronR is designed around emerging standards that connect users to growing libraries of standardized datasets formatted in the Linked PaleoData (LiPD) format (McKay and Emile-Geay, 2016), including thousands of datasets archived at the World Data Service for Paleoclimatology (WDS-Paleo) and lipdverse.org, those at the LinkedEarth wiki, and Neotoma (Williams et al, 2018) via the neotoma2lipd package (McKay, 2020)
Summary
Quantifying chronological uncertainties, and how they influence the understanding of past changes in Earth systems, is a unique and fundamental challenge of the paleoenvironmental sciences and geosciences. The need for better solutions to both characterize uncertainty, and to explicitly evaluate how age uncertainty impacts the interpretation of records of past climate, ecology or landscapes, has been long recognized (e.g., Noren et al, 2013; National Academies of Sciences, Engineering, and Medicine, 2020, and reference therein). In response to this need, the paleoenvironmental sciences and geoscientific communities have made substantial advances toward improving geochronological accuracy by. Extracting the relevant data from commonly used agemodeling algorithms, creating time-uncertain ensembles, reformatting those data for analysis in available tools typically requires the development of extensive custom codes. Exit surveys were conducted to gather feedback and to suggest improvements and extensions, which were integrated into subsequent versions of the software
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