This dataset contains the digitized treatments in Plazi based on the original journal article Molina-Acevedo, Isabel C., Fernández-Rodríguez, Vanessa, Idris, Izwandy (2022): Morphometric approach to supports distinction among three species of Paucibranchia Molina-Acevedo, 2018 (Annelida: Eunicidae). Zootaxa 5155 (3): 347-370, DOI: 10.11646/zootaxa.5155.3.3
Abstract
In this study, we performed a morphometric approach of 23 quantitative features of Paucibranchia bellii (Audouin & Milne-Edwards, 1833), P. disjuncta (Hartman, 1961), and P. carrerai Molina-Acevedo, 2018 in order to evaluate their importance in interspecific discrimination. We found that eight of the 23 features measured were correlated with the organism’s size, in particular, branchiae, parapodia, and chaetae. The features that were not size-dependent presented a low range of variation related to the maxillary apparatus (as the maxillary formula) or the prostomial appendages and could be used as taxonomically informative characters. The multivariate analysis selected six characteristics that best contributed to the three species’ discrimination. At least four of these features were related to the start of the branchiae and subacicular hooks, the maximum number of chaetigers with branchiae, and the maximum number of branchial filaments, all of them considered size-dependent. However, two other features, teeth in maxilla III and the length of the opening cavity in the maxillary apparatus, were not size-dependent. The results allowed us to demonstrate that both sized- and non-sized depending on characters are helpful and necessary to improve species discrimination within the genus Paucibranchia. Finally, we provide a detailed analysis of the ontogenetic changes of P. carrerai with additional material found on the east coast of Peninsular Malaysia.
Molina-Acevedo I C, Fernández-Rodríguez V, Idris I, plazi (2022). Morphometric approach to supports distinction among three species of Paucibranchia Molina-Acevedo, 2018 (Annelida: Eunicidae). Plazi.org taxonomic treatments database. Checklist dataset https://doi.org/10.15468/tks9ck accessed via GBIF.org on 2026-06-14.
