Description and analysis of spatial patterns in geometric morphometric data
- Autores
- González, Paula Natalia; Bonfili, Noelia; Vallejo Azar, Mariana Nahir; Barbeito Andrés, Jimena; Bernal, Valeria; Pérez, Sergio Iván
- Año de publicación
- 2019
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- The development of techniques for the acquisition of high-resolution 3D images, such as computed tomography and magnetic resonance imaging, has opened new avenues to the study of complex morphologies. Detailed descriptions of internal and external traits can be now obtained, allowing the intensive sampling of surface points. In this paper, we introduce a morphometric and statistical framework, grounded on Procrustes and Procrustes-like techniques as well as standard spatial statistics, to explicitly describe and incorporate the spatial pattern of these surface points into the analyses. We exemplified this approach by analyzing ontogenetic changes in a sample of human brain endocasts and inter-specific differences between primate skulls. An intensive sampling of points on 3D surfaces was performed by automatic techniques and the morphometric variation among specimens was measured by the residuals obtained after the alignment of points. Our results showed that shape changes in both examples are spatially structured. Different results were attained by using methods that incorporate or not the spatial structure in the evaluation of the effect of specific biological factors on shape variation. Particularly, these analyses indicated that the effect of biological factors acting at local scales can be confounded with more systemic factors (by example, the effect of the diet on the facial skeleton) if the spatial structure is not taken into account. Overall, our results suggest that the intensive description of shape differences among structures using densely sampled points on 3D surfaces combined with spatial statistical methods can be used to explore problems not widely addressed in morphological studies.
Facultad de Ciencias Naturales y Museo - Materia
-
Biología
Pseudolandmarks
Semilandmarks
Intensive sampling
Spatial autocorrelation - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- http://creativecommons.org/licenses/by-nc-sa/4.0/
- Repositorio
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/131377
Ver los metadatos del registro completo
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Description and analysis of spatial patterns in geometric morphometric dataGonzález, Paula NataliaBonfili, NoeliaVallejo Azar, Mariana NahirBarbeito Andrés, JimenaBernal, ValeriaPérez, Sergio IvánBiologíaPseudolandmarksSemilandmarksIntensive samplingSpatial autocorrelationThe development of techniques for the acquisition of high-resolution 3D images, such as computed tomography and magnetic resonance imaging, has opened new avenues to the study of complex morphologies. Detailed descriptions of internal and external traits can be now obtained, allowing the intensive sampling of surface points. In this paper, we introduce a morphometric and statistical framework, grounded on Procrustes and Procrustes-like techniques as well as standard spatial statistics, to explicitly describe and incorporate the spatial pattern of these surface points into the analyses. We exemplified this approach by analyzing ontogenetic changes in a sample of human brain endocasts and inter-specific differences between primate skulls. An intensive sampling of points on 3D surfaces was performed by automatic techniques and the morphometric variation among specimens was measured by the residuals obtained after the alignment of points. Our results showed that shape changes in both examples are spatially structured. Different results were attained by using methods that incorporate or not the spatial structure in the evaluation of the effect of specific biological factors on shape variation. Particularly, these analyses indicated that the effect of biological factors acting at local scales can be confounded with more systemic factors (by example, the effect of the diet on the facial skeleton) if the spatial structure is not taken into account. Overall, our results suggest that the intensive description of shape differences among structures using densely sampled points on 3D surfaces combined with spatial statistical methods can be used to explore problems not widely addressed in morphological studies.Facultad de Ciencias Naturales y Museo2019info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArticulohttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdf260-270http://sedici.unlp.edu.ar/handle/10915/131377enginfo:eu-repo/semantics/altIdentifier/issn/0071-3260info:eu-repo/semantics/altIdentifier/issn/1934-2845info:eu-repo/semantics/altIdentifier/doi/10.1007/s11692-019-09479-5info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T11:31:47Zoai:sedici.unlp.edu.ar:10915/131377Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 11:31:47.456SEDICI (UNLP) - Universidad Nacional de La Platafalse |
dc.title.none.fl_str_mv |
Description and analysis of spatial patterns in geometric morphometric data |
title |
Description and analysis of spatial patterns in geometric morphometric data |
spellingShingle |
Description and analysis of spatial patterns in geometric morphometric data González, Paula Natalia Biología Pseudolandmarks Semilandmarks Intensive sampling Spatial autocorrelation |
title_short |
Description and analysis of spatial patterns in geometric morphometric data |
title_full |
Description and analysis of spatial patterns in geometric morphometric data |
title_fullStr |
Description and analysis of spatial patterns in geometric morphometric data |
title_full_unstemmed |
Description and analysis of spatial patterns in geometric morphometric data |
title_sort |
Description and analysis of spatial patterns in geometric morphometric data |
dc.creator.none.fl_str_mv |
González, Paula Natalia Bonfili, Noelia Vallejo Azar, Mariana Nahir Barbeito Andrés, Jimena Bernal, Valeria Pérez, Sergio Iván |
author |
González, Paula Natalia |
author_facet |
González, Paula Natalia Bonfili, Noelia Vallejo Azar, Mariana Nahir Barbeito Andrés, Jimena Bernal, Valeria Pérez, Sergio Iván |
author_role |
author |
author2 |
Bonfili, Noelia Vallejo Azar, Mariana Nahir Barbeito Andrés, Jimena Bernal, Valeria Pérez, Sergio Iván |
author2_role |
author author author author author |
dc.subject.none.fl_str_mv |
Biología Pseudolandmarks Semilandmarks Intensive sampling Spatial autocorrelation |
topic |
Biología Pseudolandmarks Semilandmarks Intensive sampling Spatial autocorrelation |
dc.description.none.fl_txt_mv |
The development of techniques for the acquisition of high-resolution 3D images, such as computed tomography and magnetic resonance imaging, has opened new avenues to the study of complex morphologies. Detailed descriptions of internal and external traits can be now obtained, allowing the intensive sampling of surface points. In this paper, we introduce a morphometric and statistical framework, grounded on Procrustes and Procrustes-like techniques as well as standard spatial statistics, to explicitly describe and incorporate the spatial pattern of these surface points into the analyses. We exemplified this approach by analyzing ontogenetic changes in a sample of human brain endocasts and inter-specific differences between primate skulls. An intensive sampling of points on 3D surfaces was performed by automatic techniques and the morphometric variation among specimens was measured by the residuals obtained after the alignment of points. Our results showed that shape changes in both examples are spatially structured. Different results were attained by using methods that incorporate or not the spatial structure in the evaluation of the effect of specific biological factors on shape variation. Particularly, these analyses indicated that the effect of biological factors acting at local scales can be confounded with more systemic factors (by example, the effect of the diet on the facial skeleton) if the spatial structure is not taken into account. Overall, our results suggest that the intensive description of shape differences among structures using densely sampled points on 3D surfaces combined with spatial statistical methods can be used to explore problems not widely addressed in morphological studies. Facultad de Ciencias Naturales y Museo |
description |
The development of techniques for the acquisition of high-resolution 3D images, such as computed tomography and magnetic resonance imaging, has opened new avenues to the study of complex morphologies. Detailed descriptions of internal and external traits can be now obtained, allowing the intensive sampling of surface points. In this paper, we introduce a morphometric and statistical framework, grounded on Procrustes and Procrustes-like techniques as well as standard spatial statistics, to explicitly describe and incorporate the spatial pattern of these surface points into the analyses. We exemplified this approach by analyzing ontogenetic changes in a sample of human brain endocasts and inter-specific differences between primate skulls. An intensive sampling of points on 3D surfaces was performed by automatic techniques and the morphometric variation among specimens was measured by the residuals obtained after the alignment of points. Our results showed that shape changes in both examples are spatially structured. Different results were attained by using methods that incorporate or not the spatial structure in the evaluation of the effect of specific biological factors on shape variation. Particularly, these analyses indicated that the effect of biological factors acting at local scales can be confounded with more systemic factors (by example, the effect of the diet on the facial skeleton) if the spatial structure is not taken into account. Overall, our results suggest that the intensive description of shape differences among structures using densely sampled points on 3D surfaces combined with spatial statistical methods can be used to explore problems not widely addressed in morphological studies. |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019 |
dc.type.none.fl_str_mv |
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http://sedici.unlp.edu.ar/handle/10915/131377 |
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http://sedici.unlp.edu.ar/handle/10915/131377 |
dc.language.none.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
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openAccess |
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http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) |
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