Constraining the body mass range of Anzu wyliei using volumetric and extant-scaling methods

• Main Authors: Kyle Atkins-Weltman, Eric Snively, Patrick O'Connor
• Format: Article
• Language: English
• Published: University of Alberta Libraries 2021-09-01
• Series: Vertebrate Anatomy, Morphology, Palaeontology
• Subjects: Mass estimation; body density; respiratory pneumaticity; Anzu; Caenagnathidae; Oviraptorosauria
• Online Access: https://journals.library.ualberta.ca/vamp/index.php/VAMP/article/view/29375

The ability to accurately and reliably estimate body mass of extinct taxa is a vital tool for interpreting the physiology and even behavior of long-dead animals. For this reason, paleontologists have developed many possible methods of estimating the body mass of extinct animals, with varying degrees of success. These methods can be divided into two main categories: volumetric mass estimation and extant scaling methods. Each has advantages and disadvantages, which is why, when possible, it is best to perform both, and compare the results to determine what is most plausible within reason. Here we employ volumetric mass estimation (VME) to calculate an approximate body mass for previously described specimens of Anzu wyliei from the Carnegie Museum of Natural History. We also use extant scaling methods to try to obtain a reliable mass estimate for this taxon.  In addition, we present the first digital life restoration and convex hull of the dinosaur Anzu wyliei used for mass estimation purposes. We found that the volumetric mass estimation using our  digital model was 216-280kg, which falls within the range predicted by extant scaling techniques, while the mass estimate using minimum convex hulls was below the predicted range, between 159-199 kg . The VME method for Anzu wyliei strongly affirms the predictive utility of extant-based scaling. However, volumetric mass estimates are likely more precise because the models are based on comprehensive specimen anatomy rather than regressions of a phylogenetically comprehensive but disparate sample.