Molecules and morphology reveal ‘new’ widespread North American freshwater mussel species (Bivalvia: Unionidae)

Sean M. Keogh, Andrew M Simons

Research output: Contribution to journalArticlepeer-review

13 Scopus citations

Abstract

In the Family Unionidae, the greatest radiation of freshwater mussels, malacologists have been misled by extreme intraspecific shell variation and conversely interspecific conchological stasis or convergence. We characterized the genetic and morphological diversity of two phenotypes of Lampsilis teres from specimens (n = 108) collected across its distribution using geometric and traditional morphometrics and multilocus molecular phylogenetics to test the hypothesis that phenotypes represent separate species. Results from our morphometric and molecular phylogenetic analyses unanimously indicate that L. teres sensu lato is made up of two divergent, widespread species with overlapping distributions. We describe a new species and provide a revised description of L. teres sensu stricto. We use morphometrics and machine-learning classification algorithms to test if shell morphology alone can be used to discriminate between these species. Classification percentages of 97.02% and 93.86% demonstrate that shell morphology is highly informative for species identification. This study highlights our lack of understanding of species diversity of freshwater mussels and the importance of multiple characters and quantitative approaches to species delimitation.

Original languageEnglish (US)
Pages (from-to)182-192
Number of pages11
JournalMolecular Phylogenetics and Evolution
Volume138
DOIs
StatePublished - Sep 2019

Bibliographical note

Funding Information:
We thank Jeff Garner, Bernard Sietman, Mike Davis, Shelby Marr, John Harris, Don Hubbs, Jason Wisniewski, Josh Obermeyer, Carla Atkinson, Michael Buntin, Savannah Reach, Jesse Hollifield and Taylor Fagin for assistance in the field. A special thanks to Kevin Cummings and Rachel Vinsel of Illinois Natural History Survey, Kentaro Inoue and Charles Randklev of Texas A&M Natural Resources Institute, and John Harris of Arkansas State University for specimen loans. The use of museum collections: Bell Museum of Natural History, Illinois Natural History Survey, Smithsonian National Museum of Natural History, and University of Michigan Museum of Zoology greatly improved this study. We thank Lisa & Jeff Garner, Meenu & Rahul Saraf, Stuart McGregor, Emily Olsen & Eric Puls, and Josh Obermeyer for their hospitality during field excursions. Tricia Anderson, Josh Egan, Kory Evans, Peter Hundt, and Keiffer Williams scored shell coloration. This work was funded by the Dayton Wally Wildlife Fellowship , Moos Graduate Research Fellowship in Aquatic Biology ( University of Minnesota ), Joyce Davenport Fellowship , Dayton Research Grant (Bell Museum of Natural History), and the Minnesota Agricultural Experiment Station .

Publisher Copyright:
© 2019 Elsevier Inc.

Keywords

  • Cryptic diversity
  • Machine-learning
  • Morphometrics
  • Species delimitation
  • Unionida

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