Global anthropogenic impacts have incited devastating effects on both human and wildlife populations. Emerging infectious diseases (EID) are one consequence of these impacts. One particular EID, chytridiomycosis, is a threat to global amphibian populations, causing massive die-offs and several species extinctions. While predictive modeling has helped the general understanding of where the aquatic pathogen causing chytridiomycosis, Batrachochytrium dendrobatidis (Bd), could spread to, most models are on continental or countrywide scales. This coarse-scale modeling makes local management and conservation planning for imperiled amphibians difficult. In addition, modeling efforts can vary depending on location and species, making it necessary to test the predictive abilities of multiple models. This research performed three Species Distribution Models (SDMs) – a generalized linear model (GLM), a generalized additive model (GAM), and a maximum entropy model (MaxEnt) – for the Bd fungus in west-central Colorado, an area of management interest for the endangered boreal toad (Anaxyrus boreas boreas). The discriminative abilities for all three models were high according to each SDM’s AUC value (GLM AUC = 0.767; GAM AUC = 0.840; MaxEnt AUC = 0.742). The predicted variables underlying each of these models were similar to previous Bd modeling efforts, and discrepancies among the three models were minimal. In contrast, similarities in the different SDM’s predictive results suggested testable hypotheses to better understand Bd distribution and create more informative SDMs. This research is the first step towards spatial modeling on finer spatial scales that can be used for a specific management purpose.
Year manuscript completed
Year degree awarded
Chytridiomycosis, Bd, Species Distribution Modeling, Amphibians, Boreal Toad
Master of Science
Jesse D. Jones College of Science, Engineering and Technology
Howard H Whiteman
Robin Q Zhang
Kate S He
Joe N Caudell
Torres, Melanie L., "A Presence-Only Species Distribution Model Comparison Predicting the Distribution of the Amphibian Chytrid Fungus (Batrachochytrium dendrobatidis)" (2017). Murray State Theses and Dissertations. 49.