Advisor(s) - Committee Chair
Scott Grubbs (Director), Jarrett Johnson, and Keith Philips
Department of Biology
Master of Science
Predicting where rare species may be found is important in addressing and directing conservation efforts. Knowledge of the distribution for many of these taxa is often lacking or unknown altogether. The use of species distributional modeling fills gaps in this knowledge by predicting where a species may be present by taking a correlative approach between presence/pseudoabsences and environmental data. The aim of this study was to describe the distribution of several rare and uncommon aquatic insects using Maximum Entropy (MaxEnt) modeling as human influences within the central Appalachian Mountains are increasing and isolating pockets of biodiversity. Species distribution modeling of 15 central Appalachian stoneflies (Insecta: Plecoptera) resulted in the identification of potentially suitable habitat that was subsequently field-tested with adult collections in Maryland during the emergence period of each target species. This method yielded 29 new collections of seven target species. Locations from these collections of targeted species were used to generate refined models of species distribution following an iterative process. Final models now function as a guide for future collecting events.
Biodiversity | Entomology | Terrestrial and Aquatic Ecology
Hogan, Phillip Nathaniel, "Predictive Distributional Modeling of Rare and Uncommon Stoneflies (Insecta: Plecoptera) of the Central Appalachian Mountains Using Maximum Entropy" (2021). Masters Theses & Specialist Projects. Paper 3522.