A method for quantifying, visualising, and analysing gastropod shell form
- Published
- Accepted
- Subject Areas
- Developmental Biology, Taxonomy, Zoology
- Keywords
- Mollusca, MeshLab, Blender 3D, radar chart, accretionary growth, snails, elliptical fourier analysis outline, 3D morphometrics
- Copyright
- © 2013 Liew et al.
- Licence
- This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
- Cite this article
- 2013. A method for quantifying, visualising, and analysing gastropod shell form. PeerJ PrePrints 1:e157v1 https://doi.org/10.7287/peerj.preprints.157v1
Abstract
Quantitative analysis of organismal form is an important component for almost every branch of biology. Although generally considered an easily-measurable structure, the quantification of gastropod shell form is still a challenge because shells lack homologous structures and have a spiral form that is difficult to capture with linear measurements. In view of this, we adopt the idea of theoretical modelling of shell form, in which the shell form is the product of aperture ontogeny profiles in terms of aperture growth trajectory that is quantified as curvature and torsion, and of aperture form that is represented by size and shape. We develop a workflow for the analysis of shell forms based on the aperture ontogeny profile, starting from the procedure of data preparation (retopologising the shell model), via data acquisition (calculation of aperture growth trajectory, aperture form and ontogeny axis), and data presentation (qualitative comparison between shell forms) and ending with data analysis (quantitative comparison between shell forms). We evaluate our methods on representative shells of the genus Opisthostoma, which exhibit great variability in shell form. The outcome suggests that our method is more robust, reproducible, and versatile than the conventional traditional and geometric morphometric approaches for the analysis of shell form. Finally, we propose several potential applications of our methods in functional morphology, theoretical modelling, taxonomy, and evolutionary biology.
Supplemental Information
Supplementary Information (http://dx.doi.org/10.6084/m9.figshare.877061)
File S1– A python script for procedures 5 and 6 – Aperture form and growth trajectory analysis on retopologised 3D shell mesh in Blender.
File S2– A python script to convert normalised elliptical Fourier coefficients to polygon mesh in Blender.
File S3 – An R script for data analysis as described in procedures 7 and 8.
File S4 – PLY ASCII mesh 3D model of Opisthostoma laidlawi Sykes 1902.
File S5 – PLY ASCII mesh 3D model of Opisthostoma crassipupa van Benthem Jutting, 1952.
File S6 – PLY ASCII mesh 3D model of Opisthostoma christae Maassen 2001.
File S7 – PLY ASCII mesh 3D model of Opisthostoma vermiculum Clements and Vermeulen, 2008.
File S8 – PLY ASCII mesh 3D model of Opisthostoma laidlawi that was reduced in size by one-half and with slight modification of the last aperture size.
File S9 – PLY ASCII mesh 3D model of Opisthostoma christae that was reshaped into an elongated form by reducing the model size (linear dimension) by one-half along the x and y axes, and by doubling the size along the z axis.
File S10 – PLY ASCII mesh 3D model of Opisthostoma christae that was reshaped into a depressed form by doubling the model size along the x and y axes, and by reducing the size by one-half along the z axis.
File S11 – PLY ASCII mesh 3D model of Opisthostoma vermiculum that consists of one Opisthostoma vermiculum original 3D model of which the aperture was connected to a second enlarged Opisthostoma vermiculum.
File S12 – A Blender file consisting of raw data of 8 shells of procedures 1 – 4. (FILE SIZE WAS TOO LARGE FOR PEERJ, PLEASE FIND THIS FILE IN FIGSHARE)