Unique Presentation Identifier:
P58
Program Type
Honors
Faculty Advisor
Chris Kellner and Kyler Hecke
Document Type
Poster
Location
Face-to-face
Start Date
29-4-2025 3:00 PM
Abstract
Species delineation is commonly achieved through genetic analyses, but the utility of morphometrics as an alternative method remains unclear. This study investigates whether morphometric measurements can effectively differentiate species in madtoms (Noturus spp.). A total of 10 morphometric traits were measured from 50 individuals each of three madtom species: the Slender Madtom (Noturus exilis), the Black River Madtom (Noturus maydeni), the Ozark Madtom (Noturus albater), the Ouachita Madtom (Noturus lachneri) and the Freckled Madtom (Noturus nocturnus). Random forest modeling was employed to identify which morphometric variables most accurately distinguish between these species. The findings suggest that morphometric data, when analyzed with advanced modeling techniques, can serve as a viable alternative for species delineation. This research provides valuable insights for future studies on species identification and enhances the utility of morphometrics in natural history collections, potentially reducing reliance on genetic methods in certain contexts.
Recommended Citation
Walden, Harley C., "Can Assessment of Morphometrics Correctly Predict Species in Madtoms?" (2025). ATU Student Research Symposium. 39.
https://orc.library.atu.edu/atu_rs/2025/2025/39
Included in
Can Assessment of Morphometrics Correctly Predict Species in Madtoms?
Face-to-face
Species delineation is commonly achieved through genetic analyses, but the utility of morphometrics as an alternative method remains unclear. This study investigates whether morphometric measurements can effectively differentiate species in madtoms (Noturus spp.). A total of 10 morphometric traits were measured from 50 individuals each of three madtom species: the Slender Madtom (Noturus exilis), the Black River Madtom (Noturus maydeni), the Ozark Madtom (Noturus albater), the Ouachita Madtom (Noturus lachneri) and the Freckled Madtom (Noturus nocturnus). Random forest modeling was employed to identify which morphometric variables most accurately distinguish between these species. The findings suggest that morphometric data, when analyzed with advanced modeling techniques, can serve as a viable alternative for species delineation. This research provides valuable insights for future studies on species identification and enhances the utility of morphometrics in natural history collections, potentially reducing reliance on genetic methods in certain contexts.