Meeting Abstract
The concept of ‘shape’ is something we can intuitively appreciate. However, discretising the shape of morphological features to allow comparative analysis remains difficult. Many techniques, therefore, have been developed to address this challenge. Indeed, the field of geometric morphometrics (GMM) is dedicated to analysing shape change, and provides important insights into the ecology and evolution of life. Yet not all morphological features lend themselves well to GMM techniques, particularly in the absence of clearly homologous landmarks. Here we present a new method (α-shapes) for quantifying shape complexity, using mammalian bacula as a case study. Mammalian bacula (penile bones) are an interesting example, as they possess extreme shape diversity yet contain few distinct landmarks for interspecific GMM. α-shapes involves shrink-wrapping a mesh around a set of 3D points in space (point clouds). These point clouds are representative of the study specimen, and the smaller the α, the tighter the ‘shrink-wrap’ around the points. In this study, microCT scans of specimens are converted into point clouds and α-shapes fitted using increasingly refined meshes (smaller α). The α that produces a mesh with a volume most closely matching the volume calculated directly from microCT are considered ‘optimal’. Values of optimal α are then compared interspecifically as a means of quantifying shape complexity. The α-shapes methodology is a valuable addition to the suite of techniques available to researchers interested in morphology and shape complexity, particularly when traditional GMM analysis are deemed inappropriate.
