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Title:Using a multi-dimensional approach to determine the conservation and taxonomic statuses of two rare crayfishes in northern Arkansas
Author(s):Quebedeaux, Kathleen B.
Advisor(s):Taylor, Christopher A; Larson, Eric R
Contributor(s):Tan, Milton
Department / Program:Natural Res & Env Sci
Discipline:Natural Res & Env Sciences
Degree Granting Institution:University of Illinois at Urbana-Champaign
cryptic diversity
Abstract:Crayfish are chronically understudied, despite playing important roles in our freshwater ecosystems. The goal of this study was to deepen our understanding of Cambarus causeyi, the Boston Mountain Crayfish, and Cambarus hubbsi, Hubbs’ Crayfish, so they can be more effectively conserved and managed. Cambarus causeyi and C. hubbsi are classified as Species of Greatest Conservation Need in Arkansas, and they are both endemic to Ozarks of North America. The relatively small range and rarity of these species makes them vulnerable to extinction, and both have knowledge gaps that need to be addressed to facilitate conservation. For C. hubbsi we searched for potential cryptic diversity by analyzing both genetic and morphological characteristics. We sequenced two mitochondrial gene regions from individuals across its range and conducted Bayesian and maximum parsimony analyses on these data. Additionally, we recorded a suite of morphological measurements in order to conduct a principal coordinates analysis on the morphology of the species. We identified three unique evolutionarily significant units (ESUs) in need of separate conservation attention. However, our morphological analysis had conflicting results, and only showed one of the recovered clades to be unique. Further genetic data should be analyzed in the future to fill in knowledge gaps from our study and determine the cause of the mismatch between our molecular and morphological results. In the second component of this study, we utilized species distribution modeling (SDM) using the program MaxEnt and fine scale habitat modeling to analyze the distribution and habitat preferences of C. causeyi. Our SDM found average annual precipitation was by far the most important predictor of C. causeyi relative abundance. We collected habitat data from across C. causeyi’s known range, and we used our fine scale-data to ground-truth our SDM. We detected C. causeyi at only nine of 51 sites, potentially due to sampling outside of the peak of the reproductive season. We ran our fine-scale analysis by modeling zero-inflated Poisson generalized linear models and selecting with AICc. Our best model included proportion of sand in the soil and the presence of a competing burrower as explanatory variables. The interpolated MaxEnt output was found to be a poor predictor of finding C. causeyi in our fine-scale analysis potentially because it did not account for biotic interactions and lacked accurate soil data. Additionally, we found C. causeyi to still be vulnerable to a variety of threats such as climate change, interspecific competition, low local abundances, and relatively small range continue to pose a threat to conservation of this narrow endemic.
Issue Date:2021-07-23
Rights Information:Copyright 2021 Kathleen Quebedeaux
Date Available in IDEALS:2022-01-12
Date Deposited:2021-08

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