Morpho-Functional Analysis Using Procrustes Superimposition by Static Reference
Morpho-Functional Analysis Using Procrustes Superimposition by Static Reference
复制标题
通过静态参考使用 Procrustes 叠加进行形态泛函分析
DOI:
10.1007/s11692-018-9456-9
复制
发表时间:
2018
影响因子:
2.5
通讯作者:
Nyakatura
中科院分区:
文献类型:
--
作者:
Mielke;Nyakatura
In conventional geometric morphometric analyses of limb long bones, differences in the evolutionary capacity of articular surfaces and non-articular structures often remain unrecognised. It can be shown that areas of high spatial variance dominate shape data, which is problematic for the functional interpretation of limb long bone shape. We herein introduce Procrustes superimposition by static reference (PSSR), a novel analysis strategy that aims to facilitate morpho-functional inference. This procedure exploits the spatial constraint of some reference structures (in our case, articular surfaces) for the superimposition of other subareas (e.g. muscle attachment sites) in relation to that static reference. PSSR allows for the transformation of raw scan data, enabling researchers to extract geometric models of two- and three-dimensional substructures that cannot effectively be integrated with landmarks. As we demonstrate by a simple model analysis for one muscle attachment site, this procedure can yield measures of direct functional relevance. Multivariate analysis of an extensive set of subareas indicates how this type of data relates to conventional shape coordinates. The shape evolution of xenarthran humeri, which has previously been subject to a detailed study (Milne et al., J Zool 278(1):48–56, 2009), serves as a test case. The concept of a variance-based separation of landmark subsets expands mathematical methods by incorporating knowledge about evolutionary constraints. PSSR could therefore find application far beyond the intuitive case study of long bone shape.
登录
查看更多内容
DOI:
10.1007/s00114-015-1280-9
发表时间:
2015
期刊:
The Science of Nature
影响因子:
--
作者:
Anne‐Claire Fabre;M. Salesa;R. Cornette;M. Antón;J. Morales;S. Peigné
通讯作者:
S. Peigné
DOI:
--
发表时间:
2004
期刊:
影响因子:
--
作者:
C. Klingenberg;M. Pigliucci;K. Preston
通讯作者:
K. Preston
影响因子:
1.9
作者:
Fabre, Anne-Claire;Cornette, Raphael;Goswami, Anjali
通讯作者:
Goswami, Anjali
影响因子:
2.7
作者:
Michael H. Albert;Huiling Le;C. Small
通讯作者:
C. Small
影响因子:
10.7
作者:
Gibb GC;Condamine FL;Kuch M;Enk J;Moraes-Barros N;Superina M;Poinar HN;Delsuc F
通讯作者:
Delsuc F