Quantification of bone surface textures: exploring a new method of ontogenetic ageing

Abstract Identification of ontogenetic age classes plays an important role in the fields of zoology, palaeontology and archaeology, where accurate age classifications of (sub)fossil remains are a crucial component for the reconstruction of past life. Textural ageing—the identification of age-related...

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Main Authors: Jimmy de Rooij, Marleen Q. Vintges, Thim Zuidwijk, Carel T. H. Heerkens, Anne S. Schulp
Format: Article
Language:English
Published: SpringerOpen 2023-12-01
Series:Journal of Analytical Science and Technology
Subjects:
Online Access:https://doi.org/10.1186/s40543-023-00413-1
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author Jimmy de Rooij
Marleen Q. Vintges
Thim Zuidwijk
Carel T. H. Heerkens
Anne S. Schulp
author_facet Jimmy de Rooij
Marleen Q. Vintges
Thim Zuidwijk
Carel T. H. Heerkens
Anne S. Schulp
author_sort Jimmy de Rooij
collection DOAJ
description Abstract Identification of ontogenetic age classes plays an important role in the fields of zoology, palaeontology and archaeology, where accurate age classifications of (sub)fossil remains are a crucial component for the reconstruction of past life. Textural ageing—the identification of age-related bone surface textures—provides a size-independent method for age assessment of vertebrate material. However, most of the work so far is limited to qualitative results. While qualitative approaches provide helpful insights on textural ageing patterns, they are heavily subject to observer bias and fall short of quantitative data relevant for detailed statistical analyses and cross-comparisons. Here, we present a pilot study on the application of 3D surface digital microscopy to quantify bone surface textures on the long bones of the grey heron (Ardea cinerea) and the Canada goose (Branta canadensis) using internationally verified roughness parameters. Using a standardised measuring protocol, computed roughness values show a strong correlation with qualitative descriptions of textural patterns. Overall, higher roughness values correspond to increased numbers of grooves and pits and vice versa. Most of the roughness parameters allowed distinguishing between different ontogenetic classes and closely followed the typical sigmoidal animal growth curve. Our results show that bone texture quantification is a feasible approach to identifying ontogenetic age classes.
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spelling doaj.art-6525bd3c9759414ba07ff37e3fc051a62023-12-17T12:20:12ZengSpringerOpenJournal of Analytical Science and Technology2093-33712023-12-011411910.1186/s40543-023-00413-1Quantification of bone surface textures: exploring a new method of ontogenetic ageingJimmy de Rooij0Marleen Q. Vintges1Thim Zuidwijk2Carel T. H. Heerkens3Anne S. Schulp4Faculty of Geosciences, Utrecht UniversityNaturalis Biodiversity CenterDepartment of Imaging Physics, Faculty of Applied Sciences, Delft University of TechnologyDepartment of Imaging Physics, Faculty of Applied Sciences, Delft University of TechnologyFaculty of Geosciences, Utrecht UniversityAbstract Identification of ontogenetic age classes plays an important role in the fields of zoology, palaeontology and archaeology, where accurate age classifications of (sub)fossil remains are a crucial component for the reconstruction of past life. Textural ageing—the identification of age-related bone surface textures—provides a size-independent method for age assessment of vertebrate material. However, most of the work so far is limited to qualitative results. While qualitative approaches provide helpful insights on textural ageing patterns, they are heavily subject to observer bias and fall short of quantitative data relevant for detailed statistical analyses and cross-comparisons. Here, we present a pilot study on the application of 3D surface digital microscopy to quantify bone surface textures on the long bones of the grey heron (Ardea cinerea) and the Canada goose (Branta canadensis) using internationally verified roughness parameters. Using a standardised measuring protocol, computed roughness values show a strong correlation with qualitative descriptions of textural patterns. Overall, higher roughness values correspond to increased numbers of grooves and pits and vice versa. Most of the roughness parameters allowed distinguishing between different ontogenetic classes and closely followed the typical sigmoidal animal growth curve. Our results show that bone texture quantification is a feasible approach to identifying ontogenetic age classes.https://doi.org/10.1186/s40543-023-00413-1RoughnessSurfacesTaphonomyTopographyBoneOntogeny
spellingShingle Jimmy de Rooij
Marleen Q. Vintges
Thim Zuidwijk
Carel T. H. Heerkens
Anne S. Schulp
Quantification of bone surface textures: exploring a new method of ontogenetic ageing
Journal of Analytical Science and Technology
Roughness
Surfaces
Taphonomy
Topography
Bone
Ontogeny
title Quantification of bone surface textures: exploring a new method of ontogenetic ageing
title_full Quantification of bone surface textures: exploring a new method of ontogenetic ageing
title_fullStr Quantification of bone surface textures: exploring a new method of ontogenetic ageing
title_full_unstemmed Quantification of bone surface textures: exploring a new method of ontogenetic ageing
title_short Quantification of bone surface textures: exploring a new method of ontogenetic ageing
title_sort quantification of bone surface textures exploring a new method of ontogenetic ageing
topic Roughness
Surfaces
Taphonomy
Topography
Bone
Ontogeny
url https://doi.org/10.1186/s40543-023-00413-1
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