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Fig. 5 | BMC Biology

Fig. 5

From: Machine-learning strategies for testing patterns of morphological variation in small samples: sexual dimorphism in gray wolf (Canis lupus) crania

Fig. 5

Lateral view shape models reconstructed at the extreme ends of the distribution of EFA outline data projected onto the single canonical variate eigenvector (CV-1, see Fig. 4). Note that the shape distinctions between characteristic male and female morphologies are larger than they were for the dorso-ventral view analytic result (see Fig. 3) and, to some extent, involve obviously artifactual aspects of the morphology (e.g., the excessively worn canine and incisor teeth characteristic of females). It is exceedingly doubtful that sex-based discriminations of this nature could be made reliably by eye. Nonetheless, these results also capture distinctions between male and female cranial shapes that may represent more biologically important aspects of sex-based cranial shape variation (e.g., structure of the nasal opening, aspects of the occipital condyle and pterygoid flange lateral outlines)

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