JOURNAL ARTICLE
Taxonomy and molecular phylogenetic position of new species and new records of Coelosphaeridae (Demospongiae: Poecilosclerida) from the Mexican Pacific.
Published In: Zoological Journal of the Linnean Society, 2023, v. 199, n. 2. P. 511 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Cruz-Barraza, José Antonio; Carballo, José Luis; Aguilar-Camacho, José María 3 of 3
Abstract
This article focuses on the taxonomy, distribution, and molecular phylogenetics of the family Coelosphaeridae (order Poecilosclerida, class Demospongiae) in the Mexican Pacific Ocean. It describes two new species—*Celtodoryx chichiltik* sp. nov. and *Lissodendoryx (Anomodoryx) incrustans* sp. nov.—and provides new regional records and redescriptions of *Lissodendoryx (Waldoschmittia) hawaiiana* and *Lissodendoryx (Lissodendoryx) albemarlensis*. Molecular analyses using mitochondrial cytochrome c oxidase subunit I (COI mtDNA) and nuclear 28S rDNA sequences reveal that Coelosphaeridae, as well as the genera *Lissodendoryx* and *Celtodoryx*, are not monophyletic, indicating complex phylogenetic relationships within Poecilosclerida. The study also confirms a wide Pacific distribution for *L. (W.) hawaiiana* based on genetic similarity between Mexican and Hawaiian specimens. These findings highlight the need for integrative taxonomy combining morphological and molecular data to resolve systematic challenges in this diverse but understudied sponge group.
Additional Information
- Source:Zoological Journal of the Linnean Society. 2023/10, Vol. 199, Issue 2, p511
- Document Type:Article
- Subject Area:Biology
- Publication Date:2023
- ISSN:0024-4082
- DOI:10.1093/zoolinnean/zlad036
- Accession Number:172759116
- 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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