College of Graduate Studies: Theses & Dissertations

Term of Award

Spring 2026

Degree Name

Master of Science in Biology (M.S.)

Document Type and Release Option

Thesis (open access)

Copyright Statement / License for Reuse

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.

Department

Department of Biology

Committee Chair

Checo Colón-Gaud

Committee Member 1

James Roberts

Committee Member 2

Scott Harrison

Committee Member 3

Zanethia Barnett

Abstract

Crayfish assemblage composition in the southeastern United States is understudied relative to other aquatic taxa, such as aquatic insects and fishes, and the Coastal Plain watersheds of that region are particularly underrepresented in the contemporary literature on this topic. For example, although 38% of the crayfish species in Georgia are considered “species of greatest conservation need,” most of the distributional data used to make these designations are outdated, with some dating back over 50 years. This thesis sought to update our understanding of the contemporary distributions of crayfish species within the Ogeechee River Basin (ORB), a watershed in southeastern Georgia that runs from the Piedmont to the Atlantic Coastal Plain. By incorporating field-collected distributional data with landscape-scale hydrological and geographical data, I then asked which environmental features play the strongest role in explaining assemblage structure. In so doing, I employed a novel approach to defining communities of common profile, which are groups of assemblages with similar probabilities of species occurrences, by using a Bayesian joint species distribution modeling technique, Hierarchical Modeling of Species Communities (HMSC), to account for the landscape predictors as well as the spatial effects of both Euclidean and fluvial distances between sites. Principal component analyses (Hierarchical Clustering on Principal Components (HCPC) and Partitioning Around Medoids (PAM) clustering on the PC axes) were performed on the species occurrence probability data from the HMSC model to identify communities of common profile. The most influential landscape predictors used in the model were wetland cover, total upstream channel length, and watershed sub-basins (HUC8). The same four clusters arose from both clustering analyses: a group of assemblages in the northern portion of the upper Ogeechee sub-basin; in the mainstem of the Ogeechee; in the tributaries of the Lower and Coastal Ogeechee surrounding the mainstem; and encompassing the entire Canoochee sub-basin. Use of novel modeling approaches allowed me to predict species distributions with relatively high accuracy, suggesting that these methods may be useful in other studies of aquatic assemblage structure. Updated distributional data for SGCNs will assist state and federal agencies with conservation planning for those taxa.

Research Data and Supplementary Material

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