4.2 Article

Cranial variation in Meriones tristrami (Rodentia: Muridae: Gerbillinae) and its morphological comparison with Meriones persicus, Meriones vinogradovi and Meriones libycus: a geometric morphometric study

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WILEY
DOI: 10.1111/jzs.12020

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Jird; morphological variation; Muridae; Rodentia; skull

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Jirds (genus Meriones) comprise a group of rodents, of which the biodiversity is still poorly known. Reason for this is that several species of similar morphologies are known to occur sympatrically. In the north-west of Iran, four such species occur: Meriones tristrami, Meriones persicus, Meriones vinogradovi and Meriones libycus, prone to several issues of taxonomical ambiguity. A proper characterization of morphological distinctiveness between these species, in relation to the variation within species, could provide the required information for species diagnosis and identification. As some cranial characters of M. tristrami, M. persicus and M. vinogradovi are quite similar, demarcations of species-specific phenotypic variation have proven to be difficult. To tackle this problem, this study involves a geometric morphometric analysis of skull shape and size, incorporating a large representative sample of these four species, originating from most parts of their natural distribution range (especially for M. tristrami). It is first tested whether M. tristrami can be distinguished from the other sympatric species, and if so, to what degree the species shows a geoclimatic pattern in its skull shape and size when comparing different populations. The shape and size analyses show that M. libycus can be distinguished because of its largest skull and the relatively largest tympanic bulla, and that M. tristrami can be distinguished from the other species. At an intraspecific level in M. tristrami, the Iranian groups (Qazvin and west Iran) do not differ in shape among them, but do so in skull size. They could, however, be distinguished in skull shape from the non-Iranian populations included (Turkey and Jordan). To what degree this continuous data can now be translated into discrete and diagnostic features, useful for taxonomic purposes, remains to be studied.

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