JOURNAL ARTICLE
When morphology meets molecules: diversity of dart-bearing Hygromia Risso, 1826 land snails (Gastropoda: Hygromiidae).
Published In: Zoological Journal of the Linnean Society, 2025, v. 204, n. 1. P. 1 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Proćków, Małgorzata; Zając-Garlacz, Kamila S; Bertrand, Alain 3 of 3
Abstract
This article focuses on the taxonomic revision and species diversity assessment of the European land snail genus Hygromia using an integrative approach combining shell and genital morphology, including love dart characteristics, with genetic analyses of mitochondrial and nuclear DNA from 205 specimens across 90 European localities. The study confirms the existence of two monophyletic subgenera—Hygromia sensu stricto (s.s.) with the widespread species Hygromia cinctella, and Riedelia, which includes Hygromia limbata sensu stricto and its subspecies H. limbata hylonomia, Hygromia tassyi (synonymous with Hygromia gofasi), and the newly described species Hygromia pyrenaica. Morphological shell characters alone were insufficient for reliable species identification, whereas love dart morphology provided significant taxonomic value. The findings reveal a complex evolutionary history with several narrowly distributed endemic taxa primarily in the Pyrenees region, highlighting the need for further population genetic studies to clarify species boundaries and biogeography within the genus.
Additional Information
- Source:Zoological Journal of the Linnean Society. 2025/05, Vol. 204, Issue 1, p1
- Document Type:Article
- Subject Area:Anatomy and Physiology
- Publication Date:2025
- ISSN:0024-4082
- DOI:10.1093/zoolinnean/zlaf003
- Accession Number:186061303
- 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.