The present study reports data on the skull bone morphometry of barking and sambar deer. The skulls of adult barking deer (n = 6) and sambar deer (n = 6) of either sex (n = 3 males and n = 3 females) were collected from the Aizawl Zoological Park, Aizawl, Mizoram, India, with official permission from the Government of Mizoram. Anatomically, barking and sambar deer's skulls were elongated, pyramid-like, dolichocephalic and consisted of thirty-two cranial and facial bones. The cranial bones were eleven (three single and four paired), comprising of occipital, sphenoid, ethmoid, frontal, interparietal, parietal and temporal. The facial bones were twenty-one (one single and ten were paired), consisting of the maxilla, premaxilla (incisive), palatine, pterygoid, nasal, lacrimal, zygomatic (malar), vomer, turbinates, mandible and hyoid. In the present study, altogether 41 different measurements were taken morphologically and 6 different indices were applied. The obtained morphometrical parameters were significantly (p < .01, p < .05) higher in males than females of both species. Species wise, all obtained parameters were higher in sambar deer than barking deer. The obtained 41 different skull parameters and 6 indices showed statistically significant differences (p < .01 and p < .05) between both sexes of barking and sambar deer; however, practically these differences were meagre. The present morphometrical study on the skull of both species can help the wildlife professionals and zoo veterinarians determine the sex of these animals and differentiate it from other domestic and wild small ruminants for solving veterolegal cases. This study's findings will also motivate and assist other comparative studies with various domestic and wild small ruminants.
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http://dx.doi.org/10.1111/ahe.12653 | DOI Listing |
Curr Biol
January 2025
Durrell Institute of Conservation and Ecology, University of Kent, Canterbury CT2 7NR, UK.
Conservation initiatives strive for reliable and cost-effective species monitoring. However, resource constraints mean management decisions are overly reliant on data derived from single methodologies, resulting in taxonomic or geographic biases. We introduce a data integration framework to optimize species monitoring in terms of spatial representation, the reliability of biodiversity metrics, and the cost of implementation, focusing on tigers and their principal prey (sambar deer and wild pigs).
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School of Architecture and Urban Planning, Guangzhou University, Guangzhou 510006, China.
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Department of Forest Biology, Faculty of Forestry, Kasetsart University, Chatuchak, Bangkok, Thailand.
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