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Article Dans Une Revue Scientific Data Année : 2023

A dynamic and collaborative database for morphogeometric information of trilobites

Résumé

Modern morphometric-based approaches provide valuable metrics to quantify and understand macroevolutionary and macroecological patterns and processes. Here we describe TriloMorph, an openly accessible database for morpho-geometric information of trilobites, together with a landmark acquisition protocol. In addition to morphological traits, the database contains contextual data on chronostratigraphic age, geographic location, taxonomic information and lithology of landmarked specimens. In this first version, the dataset has broad taxonomic and temporal coverage and comprises more than 55% of all trilobite genera and 85% of families recorded in the Paleobiology Database through the Devonian. We provide a release of geometric morphometric data of 277 specimens linked to published references. Additionally, we established a Github repository for constant input of morphometric data by multiple contributors and present R functions that help with data retrieval and analysis. This is the first attempt of an online, dynamic and collaborative morphometric repository. By bringing this information into a single open database we enhance the possibility of performing global palaeobiological research, providing a major complement to current occurrence-based databases.
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hal-04418979 , version 1 (26-01-2024)

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Fernanda Serra, Diego Balseiro, Claude Monnet, Enrique Randolfe, Arnaud Bignon, et al.. A dynamic and collaborative database for morphogeometric information of trilobites. Scientific Data , 2023, 10 (1), pp.841. ⟨10.1038/s41597-023-02724-9⟩. ⟨hal-04418979⟩
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