JOURNAL ARTICLE

Myology of the masticatory apparatus of herbivorous mammals and a novel classification for a better understanding of herbivore diversity.

  • Published In: Zoological Journal of the Linnean Society, 2023, v. 198, n. 4. P. 1106 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Ercoli, Marcos D; Álvarez, Alicia; Warburton, Natalie M; Janis, Christine M; Potapova, Elena G; Herring, Susan W; Cassini, Guillermo H; Tarquini, Juliana; Kuznetsov, Alexander 3 of 3

Abstract

This article focuses on the classification and evolutionary interpretation of masticatory muscle configurations in herbivorous mammals, based on a comprehensive quantitative analysis of muscle mass proportions and topography across 104 extant species (including rodents, ungulates, diprotodonts, and others) and four extinct taxa. The study identifies 15 distinct myological morphotypes through principal components and cluster analyses, revealing two main evolutionary pathways of herbivorous masticatory specialization that do not align with the traditional dichotomy of 'ungulate-grinding' versus 'rodent-gnawing' types. Rodents exhibit exceptional myological diversity, necessitating subdivision beyond previous classifications, while some extinct herbivores and extant taxa like wombats show convergences bridging rodent-like and ungulate-like morphotypes. The authors propose this refined morphotype scheme as a useful framework for selecting extant models in paleobiological reconstructions and for understanding the functional evolution of mammalian herbivory.

Additional Information

  • Source:Zoological Journal of the Linnean Society. 2023/08, Vol. 198, Issue 4, p1106
  • Document Type:Article
  • Subject Area:Biology
  • Publication Date:2023
  • ISSN:0024-4082
  • DOI:10.1093/zoolinnean/zlac102
  • Accession Number:169699919
  • 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.)

Looking to go deeper into this topic? Look for more articles on EBSCOhost.