Paleomass for R-bracketing body volume of marine vertebrates with 3D models.
Body mass estimation
Body silhouette
Marine vertebrate
R
Software
Superellipse
Journal
PeerJ
ISSN: 2167-8359
Titre abrégé: PeerJ
Pays: United States
ID NLM: 101603425
Informations de publication
Date de publication:
2023
2023
Historique:
received:
23
06
2023
accepted:
03
08
2023
medline:
31
8
2023
pubmed:
29
8
2023
entrez:
29
8
2023
Statut:
epublish
Résumé
Body mass is arguably the most important characteristic of an organism, yet it is often not available in biological samples that have been skeletonized, liquid-preserved, or fossilized. The lack of information is especially problematic for fossil species, for which individuals with body mass information are not available anywhere. Multiple methods are available for estimating the body mass of fossil terrestrial vertebrates but those for their marine counterparts are limited. Paleomass is a software tool for estimating the body mass of marine vertebrates from their orthogonal silhouettes through bracketing. It generates a set of two 3D models from these silhouettes, assuming superelliptical body cross-sections with different exponent values. By setting the exponents appropriately, it is possible to bracket the true volume of the animal between those of the two models. The original version phased out together with the language platform it used. A new version is reported here as an open-source package based on the R scripting language. It inherits the underlying principles of the original version but has been completely rewritten with a new architecture. For example, it first produces 3D mesh models of the animal and then measures their volumes and areas with the VCG library, unlike the original version that did not produce a 3D model but instead computed the volume and area segment by segment using parametric equations. The new version also exports 3D models in polygon meshes, allowing later tests by other software. Other improvements include the use of NACA foil sections for hydrofoils such as flippers, and optional interpolation with local regression. The software has a high accuracy, with the mean absolute errors of 1.33% when the silhouettes of the animals are known.
Identifiants
pubmed: 37641602
doi: 10.7717/peerj.15957
pii: 15957
pmc: PMC10460563
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
e15957Informations de copyright
© 2023 Motani.
Déclaration de conflit d'intérêts
The author declares that they have no competing interests.
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