JOURNAL ARTICLE
Three‐dimensional anatomy of the Tully monster casts doubt on its presumed vertebrate affinities.
Published In: Palaeontology, 2023, v. 66, n. 2. P. 1 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Mikami, Tomoyuki; Ikeda, Takafumi; Muramiya, Yusuke; Hirasawa, Tatsuya; Iwasaki, Wataru; Cherns, Lesley 3 of 3
Abstract
Tullimonstrum gregarium, also known as the Tully monster, is a well‐known phylogenetic enigma, fossils of which have been found only in the Mazon Creek Lagerstätte. The affinities of Tullimonstrum have been debated since its discovery in 1966, because its peculiar morphology with stalked eyes and a proboscis cannot easily be compared with any known animal morphotypes. Recently, the possibility that Tullimonstrum was a vertebrate has attracted much attention, and it has been postulated that Tullimonstrum might fill a gap in the fossil record of early vertebrates, providing important insights into vertebrate evolutionary history. With the hope of resolving this debate, we collected 3D surface data from 153 specimens of Tullimonstrum using a high‐resolution laser 3D scanner and conducted x‐ray micro‐computed tomographic (μCT) analysis of stylets in the proboscis. Our investigation of the resulting comprehensive 3D morphological dataset revealed that structures previously regarded as myomeres, tri‐lobed brain, tectal cartilages and fin rays are not comparable with those of vertebrates. These results raise further doubts about its vertebrate affinities, and suggest that Tullimonstrum may have been either a non‐vertebrate chordate or a protostome. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Palaeontology. 2023/03, Vol. 66, Issue 2, p1
- Document Type:Article
- Subject Area:Earth and Atmospheric Sciences
- Publication Date:2023
- ISSN:0031-0239
- DOI:10.1111/pala.12646
- Accession Number:163336685
- Copyright Statement:Copyright of Palaeontology is the property of Wiley-Blackwell 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.)
Looking to go deeper into this topic? Look for more articles on EBSCOhost.