| Summary: | It is well-known that cranial skeleton traits are most informative in variability studies. A skull is one of the most stable morphological structures, with its traits allowing to define distinctions and estimate both intraspecies and interspecies variability. The aim of this work was the grey southeast Ukraine wolf skull morphological variety features research. We have examined wolf skulls from the scientific collection of forest biology, game management and ichthyology department of the Zaporizhzhya national university. The cranial skeleton variability estimation has been done employing 23 different traits. The most relevant linear bone reference points which form craniometry foundation were chosen. Mesocephalic type wolf skull (CI=53,44%) is massive and high with the extended foreface. The predator facial skull length is typically about 60% of skull length. According to all measured indices, predator males were slightly larger than females. However, significant sexual distinctions were observed for 8 out of 23 investigated traits: postcranial and zygomatic width, rostrum and hard palate width, skull height, length of the upper and lower jaw teeth, length of the molar lower jaw teeth. The range of wolf males variability was 4,90-12,14%, and females – 4,32-13,96%. In males, the following 5traits were most variable: the basic length, mastoid width, width between supraorbital processes, rostrum width, width between the canines. Only the width between the canines was the most variable in females. The range of predator craniometric traits specific variability was 7,46%. The most variable traits were the rostrum width and width between the canines. It is notable that trait variability is higher in females in comparison with males. Males provide major contribution to the general variability of 9 traits (the basic length, facial skull length, mastoid width, interorbital width, width between supraorbital processes, zygomatic width, rostrum width, hard palate width, length of the lower jaw), and females only to 4 traits ...
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