Analysing planktonic foraminiferal growth in three dimensions with foram3D: an R package for automated trait measurements from CT scans
Analysing planktonic foraminiferal growth in three dimensions with foram3D: an R package for automated trait measurements from CT scans
Foraminifera are one of the few taxa that preserve their entire ontogeny in their fossilised remains. Revealing this ontogeny through micro-computed tomography (CT) of fossil planktonic foraminifera has greatly improved our understanding of their life history and allows accurate quantification of total shell volume, growth rates and developmental constraints throughout an individual's life. Studies using CT scans currently mainly focus on chamber size, but the wealth of three-dimensional data generated by CT scans has the potential to reconstruct complete growth trajectories. Here we present an open-source R package to analyse growth in three-dimensional space. Using only the centroid xyz coordinates of every chamber, the functions determine the growth sequence and check that chambers are in the correct order. Once the order of growth has been verified, the functions calculate distances and angles between subsequent chambers, determine the total number of whorls and the number of chambers in the final whorl at the time each chamber was built, and, for the first time, quantify trochospirality. The applications of this package will enable repeatable analysis of large data sets and quantification of key taxonomic traits and ultimately provide new insights into the effects of ontogeny on evolution.
149-164
Brombacher, Anieke
2a4bbb84-4743-4a36-973b-4ad2bf743154
Searle-Barnes, Alex
27cd9e5f-9a76-4d3d-8c88-0d3d0b1fad63
Zhang, Wenshu
cfa69116-bc11-4ca4-8444-07037f4aeab9
Ezard, Thomas
a143a893-07d0-4673-a2dd-cea2cd7e1374
1 November 2022
Brombacher, Anieke
2a4bbb84-4743-4a36-973b-4ad2bf743154
Searle-Barnes, Alex
27cd9e5f-9a76-4d3d-8c88-0d3d0b1fad63
Zhang, Wenshu
cfa69116-bc11-4ca4-8444-07037f4aeab9
Ezard, Thomas
a143a893-07d0-4673-a2dd-cea2cd7e1374
Brombacher, Anieke, Searle-Barnes, Alex, Zhang, Wenshu and Ezard, Thomas
(2022)
Analysing planktonic foraminiferal growth in three dimensions with foram3D: an R package for automated trait measurements from CT scans.
Journal of Micropalaeontology, 41 (2), .
(doi:10.5194/jm-41-149-2022).
Abstract
Foraminifera are one of the few taxa that preserve their entire ontogeny in their fossilised remains. Revealing this ontogeny through micro-computed tomography (CT) of fossil planktonic foraminifera has greatly improved our understanding of their life history and allows accurate quantification of total shell volume, growth rates and developmental constraints throughout an individual's life. Studies using CT scans currently mainly focus on chamber size, but the wealth of three-dimensional data generated by CT scans has the potential to reconstruct complete growth trajectories. Here we present an open-source R package to analyse growth in three-dimensional space. Using only the centroid xyz coordinates of every chamber, the functions determine the growth sequence and check that chambers are in the correct order. Once the order of growth has been verified, the functions calculate distances and angles between subsequent chambers, determine the total number of whorls and the number of chambers in the final whorl at the time each chamber was built, and, for the first time, quantify trochospirality. The applications of this package will enable repeatable analysis of large data sets and quantification of key taxonomic traits and ultimately provide new insights into the effects of ontogeny on evolution.
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jm-41-149-2022
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Accepted/In Press date: 30 September 2022
Published date: 1 November 2022
Additional Information:
Funding Information:
This research has been supported by the Natural Environment Research Council (grant nos. NE/J018163/1 and NE/P019269/1).
Publisher Copyright:
Copyright © 2022 Anieke Brombacher et al.
Identifiers
Local EPrints ID: 472181
URI: http://eprints.soton.ac.uk/id/eprint/472181
ISSN: 0262-821X
PURE UUID: 5a52408a-f6ba-4442-9ba4-d1c0e53fe48d
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Date deposited: 28 Nov 2022 18:20
Last modified: 13 Jul 2024 01:54
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Author:
Wenshu Zhang
Author:
Thomas Ezard
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