Development of Comprehensive Theoretical Morphospaces for Canine Cranial Morphology

Throughout the evolution of the family Canidae, there is a continuous belief that canines have an exceptional olfactory system which allows them to have a heightened sense of smell. Because of this olfactory sophistication, canines have become prevalent as detection animals in the military, homeland security, law enforcement, forensics, and civilian applications. However, while the trait is highly regarded, the exact role of nasal morphology is understudied. We aim to investigate the influences of nasal cavity and internal structure morphology in odor detection. However, nasal structure is a sophisticated morphological target and requires innovative solutions to capture the key variables in the system and isolate the effects when single parameters are altered. To develop this method, we will employ three Computerized Tomography (CT) scans; a Golden Retriever (Mesocephalic), Chihuahua (Mesocephalic), and English Bulldog (Brachiocephalic). From these we create 3D models of these skulls within SlicerMorph to retrieve morphometric parameters for incorporation into a Principal Components Analysis (PCA). We then use the subsequent morphospace in tandem with Blender to build out theoretical morphotypes that can be used to measure how varying parameters individually influences functional outcomes. The value of this method\u27s development study is the creation of a procedural workflow to populate a theoretical morphospace. Using canid skulls as a case study, the development of this workflow can lead to possible automation allowing for quick and efficient creation of large theoretical morphology data sets to examine structure-function interactions at high resolution. In the future, we will expand our data set with CT scans from the LA County Natural History Museum and integrate them into computational fluid dynamics analyses to assess shape-olfaction interactions