Description and analysis of spatial patterns in geometric morphometric data

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 s...

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Detalles Bibliográficos
Autores principales: González, Paula Natalia, Bonfili, Noelia, Vallejo Azar, Mariana Nahir, Barbeito Andrés, Jimena, Bernal, Valeria, Pérez, Sergio Iván
Formato: Articulo
Lenguaje:Inglés
Publicado: 2019
Materias:
Biología
Pseudolandmarks
Semilandmarks
Intensive sampling
Spatial autocorrelation
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/131377
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-131377
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Biología
Pseudolandmarks
Semilandmarks
Intensive sampling
Spatial autocorrelation
spellingShingle Biología
Pseudolandmarks
Semilandmarks
Intensive sampling
Spatial autocorrelation
González, Paula Natalia
Bonfili, Noelia
Vallejo Azar, Mariana Nahir
Barbeito Andrés, Jimena
Bernal, Valeria
Pérez, Sergio Iván
Description and analysis of spatial patterns in geometric morphometric data
topic_facet Biología
Pseudolandmarks
Semilandmarks
Intensive sampling
Spatial autocorrelation
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.
format Articulo
Articulo
author González, Paula Natalia
Bonfili, Noelia
Vallejo Azar, Mariana Nahir
Barbeito Andrés, Jimena
Bernal, Valeria
Pérez, Sergio Iván
author_facet González, Paula Natalia
Bonfili, Noelia
Vallejo Azar, Mariana Nahir
Barbeito Andrés, Jimena
Bernal, Valeria
Pérez, Sergio Iván
author_sort González, Paula Natalia
title Description and analysis of spatial patterns in geometric morphometric data
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
publishDate 2019
url http://sedici.unlp.edu.ar/handle/10915/131377
work_keys_str_mv AT gonzalezpaulanatalia descriptionandanalysisofspatialpatternsingeometricmorphometricdata
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AT vallejoazarmariananahir descriptionandanalysisofspatialpatternsingeometricmorphometricdata
AT barbeitoandresjimena descriptionandanalysisofspatialpatternsingeometricmorphometricdata
AT bernalvaleria descriptionandanalysisofspatialpatternsingeometricmorphometricdata
AT perezsergioivan descriptionandanalysisofspatialpatternsingeometricmorphometricdata
bdutipo_str Repositorios
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