Date of Award
Master of Science - Environmental Sciences
Dr. Daniel Unger
Dr. David Kulhavy
Dr. Christopher Schalk
The Arizona toad (Anaxyrus microscaphus) and Jones’ waxy dogbane (Cycladenia humilis var. jonesii) are habitat specialists with historical ranges in the desert southwest and specifically, Zion National Park (ZION). The machine learning method, MaxEnt, constructed species distribution models (SDMs) in ZION for the two study species at 30 m and 900 m spatial resolutions using climate, topographic, and remotely sensed data. Additionally, 900 m forecasting models were constructed to observe the shifts in suitable habitat for the years 2050 and 2070, based off two representative concentration pathway scenarios. Results indicate promising predictive power for both high resolution models (30m) for C. humilis var. jonesii and A. microscaphus with area under curve (AUC) test analysis of 0.715 and 0.810, respectively. Forecasting models displayed decreasing suitability for A. microscaphus with both climate scenarios applied to the model. However, C. humilis var. jonesii habitat increased with future scenarios applied to the MaxEnt models.
Driver, Sam; Schalk, Chris M.; Unger, Daniel; and Kulhavy, David, "Species Distribution Modeling for Arid Adapted Habitat Specialists in Zion National Park" (2020). Electronic Theses and Dissertations. 354.
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