WRS Masters Defense

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Assessing the Effectiveness of Geometric Morphometric Analysis in the Identification of Sphaeriidae (Bivalvia: Veneroida)

Abstract: Sphaeriidae are small freshwater bivalves commonly found throughout North America in a wide range of aquatic habitats. Sphaeriids play an important role in aquatic ecosystems. However, sphaeriids are poorly studied due to the difficulty in traditional identification using dichotomous keys. The inability to correctly identify sphaeriids leaves them largely undocumented and unmonitored, causing inaccuracies in biological and ecological studies. Geometric morphometric analysis (GMA), which measures morphological shapes using anatomical landmarks, has been shown to separate cryptic species of freshwater mussels (Unionidae). The goal of this study was to determine whether GMA could separate and identify two similar species of sphaeriids. This was done by: 1) testing GMA’s ability to separate the two sphaeriid species; 2) determining if specimen age influenced the GMA accuracy; and 3)comparing the GMA identifications to traditional and genomic identification methods. This study used 279 specimens from 45 locations across the Great Lakes region. Specimens were separated into age groups (adults and juvenile) and identified using keys; 138 specimens were selected for genomic identification. Each specimen’s shell was photographed using a microscope camera for GMA to place anatomical landmarks to capture shell shape. The GMA method visually showed the differences between the two species’ shell shapes with a thin-plate spline image. The differences were pronounced in adults but also present in juveniles, and were similar to those described in keys. The GMA identifications were compared to traditional and genomic identifications. The GMA identifications had high percent agreement with the traditional and genomic methods for adults (87.3% and 86.6%). The percent agreement for juveniles was lower for both traditional (60.4%) and genomic (50%) identifications. Traditional and genomic identifications were in near perfect agreement for all age groups (>95%). This study demonstrated that GMA can discriminate between two sphaeriid species that have similar shell morphology. The GMA method could be improved by incorporating computer programs that automate data acquisition, refining details about GMA shell shape data for sphaeriids, and/or the incorporation of 3D scanning to allow the full shape of the clams to be used.