Phanerozoic thermochronology record of Afro-Arabia through space and time.

IF 5.8 2区综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES Scientific Data Pub Date : 2025-03-17 DOI:10.1038/s41597-025-04767-6

Samuel C Boone, Malcolm McMillan, Maria-Laura Balestrieri, Barry Kohn, Andrew Gleadow, Abaz Alimanovic, Graham Hutchinson, Wayne Noble, Vhairi Mackintosh, Christian Seiler, Dave Belton, Danielle Majer-Kielbaska, Daniel F Stockli, Joachim Jacobs, Edgardo J Pujols, Matthias Daßinnes, Benjamin Emmel, Fabian Kohlmann, Romain Beucher

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Abstract

Low-temperature thermochronology has been widely used in eastern Africa and Arabia (Afro-Arabia) to investigate the long-term thermal evolution of the crust in response to Phanerozoic tectonism. Yet, utilisation of this invaluable thermochronology record to inform numerical investigations into the long-term tectonothermal, geodynamic and landscape evolution of the region has been limited by the dispersion of these data across numerous disparate case studies. Here, we present a relational database of apatite (1787), zircon (68) and titanite fission-track (97) analyses, and apatite (1,945), zircon (3310), and titanite (U-Th)/He (83) ages, including 465 new fission-track and 2,583 new single-grain (U-Th)/He analyses from the region. Where available, all detailed data needed for performing thermal history modelling are presented. Also included are 668 digitised thermochronology-derived thermal history simulations. Collectively, this comprehensive database records the Phanerozoic thermal evolution of Afro-Arabia through space and time. The machine-readable database is made publicly available through the EarthBank platform, enabling 4D (3D through time) geospatial data interrogation.

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来源期刊

Scientific Data Social Sciences-Education

CiteScore

11.20

自引率

4.10%

发文量

689

审稿时长

16 weeks

期刊介绍： Scientific Data is an open-access journal focused on data, publishing descriptions of research datasets and articles on data sharing across natural sciences, medicine, engineering, and social sciences. Its goal is to enhance the sharing and reuse of scientific data, encourage broader data sharing, and acknowledge those who share their data. The journal primarily publishes Data Descriptors, which offer detailed descriptions of research datasets, including data collection methods and technical analyses validating data quality. These descriptors aim to facilitate data reuse rather than testing hypotheses or presenting new interpretations, methods, or in-depth analyses.