Semester of Graduation

Summer 2025

Degree

Master of Science (MS)

Department

Biological Sciences

Document Type

Thesis

Abstract

Characterizing niche differences in closely related species can provide valuable insights into the extent of ecological divergence between species, and the potential evolutionary processes behind speciation. This study builds the first ecological niche models for the Eurycea dwarf salamander species complex, which includes five species with varying distributions across the southeastern United States. Ecological niche models (ENMs) were built for each species using the machine-learning algorithm, MaxEnt. We used pairwise niche overlap analyses and statistical validation techniques to investigate potential ecological drivers behind species divergence and the degree of niche overlap among the five Eurycea species. We found an overall pattern of niche divergence among this species group, with our results showing significant niche differentiation in eight out of ten pairwise comparisons. Climatic variables, particularly temperature-related metrics, were found to play a significant role in shaping species distributions but contributions varied across species. Our results provide support for the previously suggested adaptive radiation of Eurycea species in the southeast US, highlighting the importance of ecological factors in diversification. Further, our ENM results suggest novel areas for future field investigations and conservation efforts of these species.

Date

5-30-2025

Committee Chair

James Cronin

Available for download on Friday, May 15, 2026

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