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Publication Details
AFRICAN RESEARCH NEXUS
SHINING A SPOTLIGHT ON AFRICAN RESEARCH
The exchangeability of shape
BMC Research Notes, Volume 3, Article 266, Year 2010
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Description
Background. Landmark based geometric morphometrics (GM) allows the quantitative comparison of organismal shapes. When applied to systematics, it is able to score shape changes which often are undetectable by traditional morphological studies and even by classical morphometric approaches. It has thus become a fast and low cost candidate to identify cryptic species. Due to inherent mathematical properties, shape variables derived from one set of coordinates cannot be compared with shape variables derived from another set. Raw coordinates which produce these shape variables could be used for data exchange, however they contain measurement error. The latter may represent a significant obstacle when the objective is to distinguish very similar species. Results. We show here that a single user derived dataset produces much less classification error than a multiple one. The question then becomes how to circumvent the lack of exchangeability of shape variables while preserving a single user dataset. A solution to this question could lead to the creation of a relatively fast and inexpensive systematic tool adapted for the recognition of cryptic species. Conclusions. To preserve both exchangeability of shape and a single user derived dataset, our suggestion is to create a free access bank of reference images from which one can produce raw coordinates and use them for comparison with external specimens. Thus, we propose an alternative geometric descriptive system that separates 2-D data gathering and analyzes. © 2010 Dujardin et al; licensee BioMed Central Ltd.
Authors & Co-Authors
Dujardin, Jean Pierre Al
Thailand, Nakhon Pathom
Mahidol University
France, Montpellier
Ird Centre de Montpellier
Kaba, Dramane
Cote D'ivoire
Institut Pierre Richet/insp
Henry, A.
United States, Honolulu
University of Hawaiʻi at Mānoa
Statistics
Citations: 92
Authors: 3
Affiliations: 4
Identifiers
Doi:
10.1186/1756-0500-3-266
Research Areas
Health System And Policy
Study Design
Cross Sectional Study
Study Approach
Quantitative