Abstract
Radiocarbon dates from megafaunal remains provide insights into climatic and anthropogenic factors shaping past ecosystems. Chronologies have advanced through rigorous chemical purification (pretreatment) of fossil vertebrate collagen for accelerator mass spectrometry (AMS) radiocarbon dating. We present MEGA14C, a comprehensive dataset of late Quaternary AMS radiocarbon dates for Holarctic large-bodied mammals, based on collagen purified by ultrafiltration (92% of records), XAD-2 purification (7%) and hydroxyproline isolation (1%). MEGA14C includes 11,715 dates spanning 8 orders, 23 families, 78 genera, 133 species and 18 subspecies, 27% from extinct taxa, and dominated by Equus, Bos, Mammuthus, Rangifer, Bison, Ursus, Cervus, Canis, Coelodonta and Sus. Where available, geolocation, genetic and isotopic data are provided. Pretreatment is critical for accurate and reproducible radiocarbon measurements, yet 44% of published dates lack this information. We addressed this gap through over 10,000 personal communications (out of >100,000 emails) with researchers and AMS laboratories among the parties involved in fossil dating. This unique dataset supports (pre)historical research and provides a foundation for future expansion and/or integration into a global radiocarbon repository.
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Data availability
The dataset is available at https://doi.org/10.6084/m9.figshare.27826200.
Code availability
The R scripts developed for manipulating the MEGA14C dataset [Usage Notes/Calibrating 14C dates in MEGA14C] are available on figshare123. R is a programming language in a free software environment distributed under the terms of the GNU General Public License (www.R-project.org/Licenses).
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Acknowledgements
Research funded through Australian Research Council’s Discovery Project DP170104665 and the University of New South Wales (UNSW), Australia. Publication fees funded by School of Biological Sciences/University of Adelaide, Australia. Publication fees were shared by Heriot-Watt University (CST), University of California - Irvine (JRS), and Department of Biogeography and Global Change - Museo Nacional de Ciencias Naturales - Spanish National Research Council (SHP). We are extremely grateful to the hundreds of authors who shared methodological information associated with the 14C dates included in MEGA14C when contacted about their published research. Each contribution has been invaluable and is cited as a personal communication within the dataset. We particularly acknowledge (given the very high volume of communications) Ronny Friedrich, Tomasz Goslar, Irka Hajdas, Emma Henderson, Gregory Hodgins, Marie Kanstrup, Adrian Lister, Greg McDonald (who also provided comments on a preliminary draft), Melanie Mucke, Adam Nadachowski, Paula Reimer, and Chris Widga (who also peer-reviewed the submitted manuscript for Scientific Data).
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S.H.P. conceived the idea, reviewed the literature, collated and curated the data, communicated with researchers, curators, technicians and AMS facilities, built the dataset, and wrote the first draft of the manuscript and the R scripts. T.W.S. contributed archival data from 1988 to present, contacts for researchers and institutions, discussion and details on 14C protein chemistry and edited preliminary and final drafts of the manuscript. J.R.S. contributed sample processing details for Lawrence Livermore National Laboratory, Livermore (to 2001; CAMS) and University of California, Irvine (2001 to present; UCIAMS), contacts for researchers and institutions and chemical discussions. K.J.M. advised on selection and formatting of dataset metadata fields and categories, provided feedback on early iterations of the dataset design, participated in discussions about megafauna chronologies, revised the R script manual and contributed to the writing of the manuscript. C.S.T. contributed funding for the project, gave advice on the dataset and contributed to the writing.
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Herrando-Pérez, S., Mitchell, K.J., Southon, J.R. et al. A dataset of radiocarbon dates from Holarctic mammal collagen purified with high-quality chemistry. Sci Data (2026). https://doi.org/10.1038/s41597-026-06562-3
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DOI: https://doi.org/10.1038/s41597-026-06562-3


