An advanced shape-fitting algorithm applied to quadrupedal mammals : improving volumetric mass estimates

Brassey, CA; Gardiner, JD

Abstract

Body mass is a fundamental physical property of an individual
and has enormous bearing upon ecology and physiology.
Generating reliable estimates for body mass is therefore a
necessary step in many palaeontological studies. Whilst early
reconstructions of mass in extinct species relied upon isolated
skeletal elements, volumetric techniques are increasingly
applied to fossils when skeletal completeness allows.We apply
a new ‘alpha shapes’ (α-shapes) algorithm to volumetric mass
estimation in quadrupedal mammals. α-shapes are defined
by: (i) the underlying skeletal structure to which they are
fitted; and (ii) the value α, determining the refinement of fit.
For a given skeleton, a range of α-shapes may be fitted
around the individual, spanning from very coarse to very
fine. We fit α-shapes to three-dimensional models of extant
mammals and calculate volumes, which are regressed against
mass to generate predictive equations. Our optimal model is
characterized by a high correlation coefficient and mean square
error (r2 =0.975, m.s.e.=0.025). When applied to the woolly
mammoth (Mammuthus primigenius) and giant ground sloth
(Megatherium americanum), we reconstruct masses of 3635 and
3706 kg, respectively. We consider α-shapes an improvement
upon previous techniques as resulting volumes are less
sensitive to uncertainties in skeletal reconstructions, and do not
require manual separation of body segments from skeletons.

Citation

Brassey, C., & Gardiner, J. (2015). An advanced shape-fitting algorithm applied to quadrupedal mammals : improving volumetric mass estimates. Royal Society Open Science, 2(8), 150302. https://doi.org/10.1098/rsos.150302

• Journal Article Type: Article
• Acceptance Date: Jul 23, 2015
• Publication Date: Jan 1, 2015
• Deposit Date: Dec 16, 2015
• Publicly Available Date: Apr 5, 2016
• Journal: Royal Society Open Science
• Publisher: The Royal Society
• Volume: 2
• Issue: 8
• Pages: 150302
• DOI: https://doi.org/10.1098/rsos.150302
• Publisher URL: http://dx.doi.org/10.1098/rsos.150302
• Related Public URLs: http://rsos.royalsocietypublishing.org/