1
|
Hatala KG, Gatesy SM, Manafzadeh AR, Lusardi EM, Falkingham PL. Technical note: A volumetric method for measuring the longitudinal arch of human tracks and feet. Am J Biol Anthropol 2024; 183:e24897. [PMID: 38173148 DOI: 10.1002/ajpa.24897] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/08/2023] [Revised: 11/07/2023] [Accepted: 12/18/2023] [Indexed: 01/05/2024]
Abstract
Fossil footprints (i.e., tracks) were believed to document arch anatomical evolution, although our recent work has shown that track arches record foot kinematics instead. Analyses of track arches can thereby inform the evolution of human locomotion, although quantifying this 3-D aspect of track morphology is difficult. Here, we present a volumetric method for measuring the arches of 3-D models of human tracks and feet, using both Autodesk Maya and Blender software. The method involves generation of a 3-D object that represents the space beneath the longitudinal arch, and measurement of that arch object's geometry and spatial orientation. We provide relevant tools and guidance for users to apply this technique to their own data. We present three case studies to demonstrate potential applications. These include, (1) measuring the arches of static and dynamic human feet, (2) comparing the arches of human tracks with the arches of the feet that made them, and (3) direct comparisons of human track and foot arch morphology throughout simulated track formation. The volumetric measurement tool proved robust for measuring 3-D models of human tracks and feet, in static and dynamic contexts. This tool enables researchers to quantitatively compare arches of fossil hominin tracks, in order to derive biomechanical interpretations from them, and/or offers a different approach for quantifying foot morphology in living humans.
Collapse
Affiliation(s)
- Kevin G Hatala
- Department of Biology, Chatham University, Pittsburgh, Pennsylvania, USA
| | - Stephen M Gatesy
- Department of Ecology, Evolution, and Organismal Biology, Brown University, Providence, Rhode Island, USA
| | - Armita R Manafzadeh
- Department of Ecology, Evolution, and Organismal Biology, Brown University, Providence, Rhode Island, USA
- Institute for Biospheric Studies, Yale University, New Haven, Connecticut, USA
- Department of Earth and Planetary Sciences, Yale University, New Haven, Connecticut, USA
- Peabody Museum of Natural History, Yale University, New Haven, Connecticut, USA
| | | | - Peter L Falkingham
- School of Biological and Environmental Sciences, Liverpool John Moores University, Liverpool, UK
| |
Collapse
|
2
|
Lallensack JN, Romilio A, Falkingham PL. A machine learning approach for the discrimination of theropod and ornithischian dinosaur tracks. J R Soc Interface 2022; 19:20220588. [PMID: 36349446 PMCID: PMC9653224 DOI: 10.1098/rsif.2022.0588] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2022] [Accepted: 10/24/2022] [Indexed: 10/17/2023] Open
Abstract
Fossil tracks are important palaeobiological data sources. The quantitative analysis of their shape, however, has been hampered by their high variability and lack of discrete margins and landmarks. We here present the first approach using deep convolutional neural networks (DCNNs) to study fossil tracks, overcoming the limitations of previous statistical approaches. We employ a DCNN to discriminate between theropod and ornithischian dinosaur tracks based on a total of 1372 outline silhouettes. The DCNN consistently outperformed human experts on an independent test set. We also used the DCNN to classify tracks of a large tridactyl trackmaker from Lark Quarry, Australia, the identity of which has been subject to intense debate. The presented approach can only be considered a first step towards the wider application of machine learning in fossil track research, which is not limited to classification problems. Current limitations, such as the subjectivity and information loss inherent in interpretive outlines, may be overcome in the future by training neural networks on three-dimensional models directly, though this will require an increased uptake in digitization among workers in the field.
Collapse
Affiliation(s)
- Jens N. Lallensack
- School of Biological and Environmental Sciences, Liverpool John Moores University, James Parsons Building, Bryon Street, Liverpool L3 3AF, UK
| | - Anthony Romilio
- School of Chemistry and Molecular Biosciences, The University of Queensland, Brisbane 4072, Australia
| | - Peter L. Falkingham
- School of Biological and Environmental Sciences, Liverpool John Moores University, James Parsons Building, Bryon Street, Liverpool L3 3AF, UK
| |
Collapse
|
3
|
Bishop PJ, Clemente CJ, Weems RE, Graham DF, Lamas LP, Hutchinson JR, Rubenson J, Wilson RS, Hocknull SA, Barrett RS, Lloyd DG. Using step width to compare locomotor biomechanics between extinct, non-avian theropod dinosaurs and modern obligate bipeds. J R Soc Interface 2018; 14:rsif.2017.0276. [PMID: 28724627 DOI: 10.1098/rsif.2017.0276] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2017] [Accepted: 06/22/2017] [Indexed: 12/13/2022] Open
Abstract
How extinct, non-avian theropod dinosaurs locomoted is a subject of considerable interest, as is the manner in which it evolved on the line leading to birds. Fossil footprints provide the most direct evidence for answering these questions. In this study, step width-the mediolateral (transverse) distance between successive footfalls-was investigated with respect to speed (stride length) in non-avian theropod trackways of Late Triassic age. Comparable kinematic data were also collected for humans and 11 species of ground-dwelling birds. Permutation tests of the slope on a plot of step width against stride length showed that step width decreased continuously with increasing speed in the extinct theropods (p < 0.001), as well as the five tallest bird species studied (p < 0.01). Humans, by contrast, showed an abrupt decrease in step width at the walk-run transition. In the modern bipeds, these patterns reflect the use of either a discontinuous locomotor repertoire, characterized by distinct gaits (humans), or a continuous locomotor repertoire, where walking smoothly transitions into running (birds). The non-avian theropods are consequently inferred to have had a continuous locomotor repertoire, possibly including grounded running. Thus, features that characterize avian terrestrial locomotion had begun to evolve early in theropod history.
Collapse
Affiliation(s)
- P J Bishop
- Geosciences Program, Queensland Museum, Brisbane, Australia .,School of Allied Health Sciences, Griffith University, Gold Coast, Australia.,Innovations in Health Technology, Menzies Health Institute Queensland, Southport, Queensland, Australia
| | - C J Clemente
- School of Science and Engineering, University of the Sunshine Coast, Maroochydore, Australia.,School of Biological Sciences, University of Queensland, Brisbane, Australia
| | - R E Weems
- Calvert Marine Museum, Solomons, USA.,Paleo Quest, Gainesville, FL, USA
| | - D F Graham
- School of Allied Health Sciences, Griffith University, Gold Coast, Australia.,Innovations in Health Technology, Menzies Health Institute Queensland, Southport, Queensland, Australia
| | - L P Lamas
- Structure and Motion Laboratory, Royal Veterinary College, Hatfield, UK.,Faculdade de Medicina Veterinária, Universidade de Lisboa, Lisbon, Portugal
| | - J R Hutchinson
- Structure and Motion Laboratory, Royal Veterinary College, Hatfield, UK
| | - J Rubenson
- College of Health and Human Development, Pennsylvania State University, University Park, PA, USA.,School of Human Sciences, University of Western Australia, Crawley, Australia
| | - R S Wilson
- School of Biological Sciences, University of Queensland, Brisbane, Australia
| | - S A Hocknull
- Geosciences Program, Queensland Museum, Brisbane, Australia.,School of Allied Health Sciences, Griffith University, Gold Coast, Australia.,Innovations in Health Technology, Menzies Health Institute Queensland, Southport, Queensland, Australia
| | - R S Barrett
- School of Allied Health Sciences, Griffith University, Gold Coast, Australia.,Innovations in Health Technology, Menzies Health Institute Queensland, Southport, Queensland, Australia
| | - D G Lloyd
- School of Allied Health Sciences, Griffith University, Gold Coast, Australia.,Innovations in Health Technology, Menzies Health Institute Queensland, Southport, Queensland, Australia.,School of Human Sciences, University of Western Australia, Crawley, Australia
| |
Collapse
|