Geometric Morphometrics for Biologists: A Primer
Geometric Morphometrics for Biologists is an introductory textbook for a course on geometric morphometrics, written for graduate students and upper division undergraduates, covering both theory of shape analysis and methods of multivariate analysis. It is designed for students with minimal math background; taking them from the process of data collection through basic and more advanced statistical analyses. Many examples are given, beginning with simple although realistic case-studies, through examples of complex analyses requiring several different kinds of methods. The book also includes URL's for free software and step-by-step instructions for using the software.
* Accessible, student-tested introduction to sophisticated methods of biological shape analysis
* Detailed instructions for conducting analyses with freely available, easy to use software
* Numerous illustrations; including graphical presentations of important theoretical concepts and demonstrations of alternative approaches to presenting results
* Many realistic examples, both simple and complex, from on-going research
* Comprehensive glossary of technical terms
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allometric coefficients allometry analysis analyze angle axes axis baseline bending energy biological blocks Bookstein bootstrap sets calculated categorical variable caudal peduncle centroid Chapter compute confidence interval configurations of landmarks correlation covariance cranial data set deformation degrees of freedom denticulata describe developmental digitizing dimensions disparity displacements distribution eigenvalues eigenvectors elongatus Equation error estimate example Figure function geometric morphometrics gouldingi groups heterochrony hypersphere independent variable Kendall’s shape space length linear MANOVA manueli mathematical mean measurements morphogenesis morphology multivariate null hypothesis ontogenetic ontogeny options p-value partial Procrustes distance partial warp scores permutation permutation test piranha plot points postcranial pre-shape space principal components principal components analysis Procrustes superimposition reference regression relative rotation sample scale semilandmarks shape change shape coordinates shape differences shape variables skull species specimens squared three-dimensional triangles two-dimensional Type I error uniform components values variance variation vectors