Abstract
The endangered Barton Springs and Austin blind salamanders (Eurycea sosorum and E. waterlooensis, respectively) are micro-endemics to the Barton Springs segment of the Edwards Aquifer and its contributing zone in Central Texas. Although vertically segregated within the aquifer system, both species are known from the same spring outflows and occasionally hybridize. We used geometric morphometrics and model-based clustering applied to a large sample of standardized salamander photographs to evaluate the potential for objective phenotypic assignment to either species, as well as putative hybrids. In addition to characterizing variation in head shape, our analyses inferred sets of clusters corresponding to ontogenetic series in both species but did not infer any distinct hybrid clusters. Eurycea sosorum and E. waterlooensis have distinctive head size to trunk length allometries, which contributed to the effective clustering of species, even at small body sizes. We also observed subtle, but significant, microgeographic variation in E. sosorum, suggesting the possibility of population substructuring, phenotypic plasticity, or undetected hybridization.
Highlights
Model-based clustering methods have been used increasingly in biology for objectively partitioning observations into cohesive groups based on high-dimensional datasets [1,2]
We added to this dataset any additional wild individuals previously identified as E. waterlooensis (n = 22) as well as individuals of E. waterlooensis from the Austin Salamander Conservation Center (n = 24) in order to increase our sample size and to more accurately evaluate the spectrum of phenotypic variation for this species, which represents only about 1% of the salamanders encountered at Barton Springs [15,20]
P-Value η2 for this species based on expert identifications, i.e., clusters corresponding to wild juveniles and mostly
Summary
Model-based clustering methods have been used increasingly in biology for objectively partitioning observations into cohesive groups based on high-dimensional datasets [1,2]. These methods are frequently deployed in studies of gene expression and species delimitation [3,4,5,6,7] but have numerous other applications. We evaluate phenotypic variation in head shape as well as overall accuracy of Bayesian model-based clustering when compared with expert identification for distinguishing among species and hybrids of two endangered salamander species endemic only to the Barton Springs segment and its contributing zone of the Edwards Aquifer in Central Texas.
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