JOURNAL ARTICLE
A new specimen of Dacentrurus armatus Owen, 1875 (Ornithischia: Thyreophora) from the Upper Jurassic of Spain and its taxonomic relevance in the European stegosaurian diversity.
Published In: Zoological Journal of the Linnean Society, 2025, v. 203, n. 3. P. 1 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Sánchez-Fenollosa, Sergio; Escaso, Fernando; Cobos, Alberto 3 of 3
Abstract
This article focuses on the taxonomy and anatomical reassessment of European Upper Jurassic stegosaurs, particularly the genus Dacentrurus armatus. Based on a newly described, relatively complete stegosaurian skeleton from the Villar del Arzobispo Formation in Spain and a comprehensive review of European material, the study finds high morphological homogeneity among specimens previously assigned to Dacentrurus armatus and the controversial taxon Miragaia longicollum. Consequently, Miragaia longicollum is proposed as a subjective junior synonym of Dacentrurus armatus, consolidating the European Late Jurassic stegosaurian fauna to two species: Dacentrurus armatus and Stegosaurus stenops. Additionally, the species longispinus from the Morrison Formation (USA) is reaffirmed as belonging to the genus Alcovasaurus, distinct from Dacentrurus. The study provides an updated diagnosis of Dacentrurus armatus based on autapomorphies from the holotype and referred specimens, enhancing understanding of its anatomy and intraspecific variation.
Additional Information
- Source:Zoological Journal of the Linnean Society. 2025/03, Vol. 203, Issue 3, p1
- Document Type:Article
- Subject Area:Earth and Atmospheric Sciences
- Publication Date:2025
- ISSN:0024-4082
- DOI:10.1093/zoolinnean/zlae074
- Accession Number:184296389
- Copyright Statement:Copyright of Zoological Journal of the Linnean Society is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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