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J Morphol ; 279(3): 361-374, 2018 03.
Article in English | MEDLINE | ID: mdl-29178202

ABSTRACT

The bony cranial structures of even-toed hoofed mammals are important for understanding ecology and behavior of ruminants. Horns, the cranial appendages of the family Bovidae, are covered in a layer of keratin that is often not preserved in the fossil record; however, this keratin sheath is intimately involved in the processes that influence horn shape evolution. To understand the relationship between these two components of horns, we quantified both core and sheath shape for four extant species using three-dimensional geometric morphometric analyses in separate, core- and sheath-specific morphospaces as well as a combined morphospace. We assessed correlations between the horn and sheath morphospaces using two-block partial least squares regression, a Mantel test of pairwise distances between species, and Procrustes ANOVA. We measured disparity in the combined morphospace as Procrustes distances between mean shapes of cores and sheaths within and between species and as Procrustes variance. We also tested whether core and sheath shapes could be discriminated by taxon with a canonical variate analysis. Results show that horn core and sheath morphospaces are strongly correlated. The differences in shape between a species' core and sheath were statistically significant, but not as great as those between the cores and sheaths of different species when close relatives were not considered, and core and sheath Procrustes variances are not significantly different within species. Cores and sheath shapes were highly identifiable and were assigned to the correct clade 93% of the time in the canonical variate analysis. Based on these tests, horn cores are distinguishable in geometric morphometric analyses, extending the possibility of using geometric morphometrics to study the ecology and evolution of bovid horns to the fossil record.


Subject(s)
Cattle/anatomy & histology , Horns/anatomy & histology , Imaging, Three-Dimensional , Analysis of Variance , Anatomic Landmarks , Animals , Female , Male , Principal Component Analysis , Species Specificity
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