CONFIDENT TAXONOMY: USING BAYESIAN PROBABILITIES TO SUPPORT GENUS AND SPECIES LEVEL IDENTIFICATIONS BASED ON MORPHOLOGICAL TRAITS.
The current biodiversity crisis requires innovative and accessible approaches for documenting diverse organisms. Dragonflies are among the target groups monitored to assess aquatic ecosystem health by parataxonomists involved with water quality monitoring programs. These observations could be facilitated by the collection of exuviae, the last exoskeleton of the nymph stage that is shed when the adult emerges. Exuviae are often more difficult to identify than adult dragonflies and the resources used for identification are more limited. We evaluated 26 morphological features to incorporate into a probabilistic key for continuous data. Dragonfly exuviae were collected in late-May through mid-June from 2015-2017 from nine Wisconsin rivers. A set of 320 specimens were used as training data for the probabilistic key. A second set of 100 specimens will be identified by undergraduate students using traditional taxonomic keys as well as the probabilistic key. Identifications will be confirmed by taxonomic experts and the accuracy of both identification methods will be evaluated using contingency tables. Our results and prototype key support the development of alternative identification tools that are accessible to experts and non-experts and include more continuous data.
Nicole Chapman (Primary Presenter/Author), University of Wisconsin Parkside, firstname.lastname@example.org;
Nora Willkomm (Co-Presenter/Co-Author), University of Minnesota, email@example.com;
Christopher Tyrrell (Co-Presenter/Co-Author), Milwaukee Public Museum, firstname.lastname@example.org;
Jessica Orlofske (Co-Presenter/Co-Author), University of Wisconsin-Parkside, email@example.com;