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dc.contributor.authorCarlton, Joshua Stuart
dc.date.accessioned2014-03-03T23:07:40Z
dc.date.available2014-03-03T23:07:40Z
dc.date.issued2004-12
dc.identifier.othercarlton_joshua_s_200412_ms
dc.identifier.urihttp://purl.galileo.usg.edu/uga_etd/carlton_joshua_s_200412_ms
dc.identifier.urihttp://hdl.handle.net/10724/22074
dc.description.abstractRobust redhorse, Moxostoma robustum, is a recently rediscovered, imperiled species of sucker (Catostomidae) that inhabits several rivers in the Atlantic Slope drainage and is subject to intense conservation efforts. Its spawning period frequently overlaps that of a sympatric congener, the notchlip redhorse (M. collapsum), making identifying the larvae of the species difficult. I measured various morphometrics, meristics, and developmental characteristics on lab-reared larvae of each species, fit a classification tree model to the data, and used the model to create a key discriminating between the species. The model had a leave-one-out, cross-validation expected error rate of 4.7%. The key formed from the model is highly accurate for fishes from 10–20 mm total length: three independent verifiers used the key to identify fishes with a 95% accuracy rate. This key is one of a few that distinguishes between sympatric Moxostoma larvae and is the first to identify larval robust redhorse.
dc.languageeng
dc.publisheruga
dc.rightspublic
dc.subjectRobust redhorse
dc.subjectMoxostoma robustum
dc.subjectNotchlip redhorse
dc.subjectMoxostoma collapsum
dc.subjectTaxonomic key
dc.subjectOconee River
dc.subjectCatostomidae
dc.subjectLarval fishes
dc.subjectCATDAT
dc.subjectClassification trees
dc.subjectRobust Redhorse Conservation Committee
dc.titleIdentification of larval Moxostoma (Catostomidae) in the Oconee River, Georgia
dc.typeThesis
dc.description.degreeMS
dc.description.departmentForest Resources
dc.description.majorForest Resources
dc.description.advisorCecil A. Jennings
dc.description.committeeCecil A. Jennings
dc.description.committeeJames Peterson
dc.description.committeeByron Freeman


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