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Analyzing fluctuating asymmetry with geometric morphometrics: concepts, methods, and applications

Klingenberg CP

Symmetry. 2015;7(2):843-934.

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Abstract

Approximately two decades after the first pioneering analyses, the study of shape asymmetry with the methods of geometric morphometrics has matured and is a burgeoning field. New technology for data collection and new methods and software for analysis are widely available and have led to numerous applications in plants and animals, including humans. This review summarizes the concepts and morphometric methods for studying asymmetry of shape and size. After a summary of mathematical and biological concepts of symmetry and asymmetry, a section follows that explains the methods of geometric morphometrics and how they can be used to analyze asymmetry of biological structures. Geometric morphometric analyses not only tell how much asymmetry there is, but also provide information about the patterns of covariation in the structure under study. Such patterns of covariation in fluctuating asymmetry can provide valuable insight about the developmental basis of morphological integration, and have become important tools for evolutionary developmental biology. The genetic basis of fluctuating asymmetry has been studied from empirical and theoretical viewpoints, but serious challenges remain in this area. There are many promising areas for further research that are only little explored at present.

Bibliographic metadata

Type of resource:
Content type:
Publication status:
Published
Publication type:
Publication form:
Author list:
Published date:
Accepted date:
2015-05-27
Submitted date:
2015-02-19
Journal title:
ISSN:
Publisher:
Volume:
7
Issue:
2
Start page:
843
End page:
934
Total:
91
Pagination:
843-934
Digital Object Identifier:
10.3390/sym7020843
Research data access statement included:
Not applicable
Attached files Open Access licence:
Creative Commons Attribution (CC BY)
Attached files embargo period:
Immediate release
Attached files release date:
8th June, 2015
Access state:
Active

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University researcher(s):
Academic department(s):

Record metadata

Manchester eScholar ID:
uk-ac-man-scw:266026
Created by:
Klingenberg, Christian
Created:
8th June, 2015, 10:36:02
Last modified by:
Klingenberg, Christian
Last modified:
8th June, 2015, 19:41:48

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