The primary rationale for the use of phylogenetically based statistical methods is that phylogenetic signal, the tendency for related species to resemble each other, is ubiquitous. Whether this assertion is true for a given trait in a given lineage is an empirical question, but general tools for detecting and quantifying phylogenetic signal are inadequately developed. We present new methods for continuous-valued characters that can be implemented with either phylogenetically independent contrasts or generalized least-squares models. First, a simple randomization procedure allows one to test the null hypothesis of no pattern of similarity among relatives. The test demonstrates correct Type I error rate at a nominal α = 0.05 and good power (0.8) for simulated datasets with 20 or more species. Second, we derive a descriptive statistic, K, which allows valid comparisons of the amount of phylogenetic signal across traits and trees. Third, we provide two biologically motivated branch-length transformat...

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Testing for phylogenetic signal in comparative data: behavioral traits are more labile.

Increasingly, data on shape are analysed in combination with molecular genetic or ecological information, so that tools for geometric morphometric analysis are required. Morphometric studies most often use the arrangements of morphological landmarks as the data source and extract shape information from them by Procrustes superimposition. The MorphoJ software combines this approach with a wide range of methods for shape analysis in different biological contexts. The program offers an integrated and user-friendly environment for standard multivariate analyses such as principal components, discriminant analysis and multivariate regression as well as specialized applications including phylogenetics, quantitative genetics and analyses of modularity in shape data. MorphoJ is written in Java and versions for the Windows, Macintosh and Unix/Linux platforms are freely available from http://www.flywings.org.uk/MorphoJ_page.htm.

Morphoj: an integrated software package for geometric morphometrics

The first edition of "Geometric Morphometrics for Biologists" has been the primary resource for teaching modern geometric methods of shape analysis to biologists who have a stronger background in biology than in multivariate statistics and matrix algebra. These geometric methods are appealing to biologists who approach the study of shape from a variety of perspectives, from clinical to evolutionary, because they incorporate the geometry of organisms throughout the data analysis. The second edition of this book retains the emphasis on accessible explanations, and the copious illustrations and examples of the first, updating the treatment of both theory and practice. The second edition represents the current state-of-the-art and adds new examples and summarizes recent literature, as well as provides an overview of new software and step-by-step guidance through details of carrying out the analyses. This title contains updated coverage of methods, especially for sampling complex curves and 3D forms and a new chapter on applications of geometric morphometrics to forensics. It offers a reorganization of chapters to streamline learning basic concepts. It presents detailed instructions for conducting analyses with freely available, easy to use software. It provides numerous illustrations, including graphical presentations of important theoretical concepts and demonstrations of alternative approaches to presenting results.

Geometric morphometrics for biologists: a primer

The analysis of shape is a fundamental part of much biological research. As the field of statistics developed, so have the sophistication of the analysis of these types of data. This lead to multivariate morphometrics in which suites of measurements were analyzed together using canonical variates analysis, principal components analysis, and related methods. In the 1980s, a fundamental change began in the nature of the data gathered and analyzed. This change focused on the coordinates of landmarks and the geometric information about their relative positions. As a by-product of such an approach, results of multivariate analyses could be visualized as configurations of landmarks back in the original space of the organism rather than only as statistical scatter plots. This new approach, called “geometric morphometrics”, had benefits that lead Rohlf and Marcus (1993) to proclaim a “revolution” in morphometrics. In this paper, we briefly update the discussion in that paper and summarize the advances in the ten years since the paper by Rohlf and Marcus. We also speculate on future directions in morphometric analysis.

Geometric morphometrics: Ten years of progress following the ‘revolution’

Summary 1. Many ecological and evolutionary studies seek to explain patterns of shape variation and its covariation with other variables. Geometric morphometrics is often used for this purpose, where a set of shape variables are obtained from landmark coordinates following a Procrustes superimposition. 2. We introduce geomorph: a software package for performing geometric morphometric shape analysis in the R statistical computing environment. 3. Geomorph provides routines for all stages of landmark-based geometric morphometric analyses in two and three-dimensions. It is an open source package to read, manipulate, and digitize landmark data, generate shape variables via Procrustes analysis for points, curves and surfaces, perform statistical analyses of shape variation and covariation, and to provide graphical depictions of shapes and patterns of shape variation. An important contribution of geomorph is the ability to perform Procrustes superimposition on landmark points, as well as semilandmarks from curves and surfaces. 4. A wide range of statistical methods germane to testing ecological and evolutionary hypotheses of shape variation are provided. These include standard multivariate methods such as principal components analysis, and approaches for multivariate regression and group comparison. Methods for more specialized analyses, such as for assessing shape allometry, comparing shape trajectories, examining morphological integration, and for assessing phylogenetic signal, are also included. 5. Several functions are provided to graphically visualize results, including routines for examining variation in shape space, visualizing allometric trajectories, comparing specific shapes to one another and for plotting phylogenetic changes in morphospace. 6. Finally, geomorph participates to make available advanced geometric morphometric analyses through the R statistical computing platform.

https://besjournals.onlinelibrary.wiley.com/doi/epdf/10.1111/2041-210X.12035

geomorph: an r package for the collection and analysis of geometric morphometric shape data

http://www.pdfsdocuments.com/geometric-morphometrics-for-biologists.pdf

Geometric Morphometrics for Biologists

In the mammalian auditory system, sensory cell loss resulting from aging, ototoxic drugs, infections, overstimulation and other causes is irreversible and leads to permanent sensorineural hearing loss. To restore hearing, it is necessary to generate new functional hair cells. One potential way to regenerate hair cells is to induce a phenotypic transdifferentiation of nonsensory cells that remain in the deaf cochlea. Here we report that Atoh1, a gene also known as Math1 encoding a basic helix-loop-helix transcription factor and key regulator of hair cell development, induces regeneration of hair cells and substantially improves hearing thresholds in the mature deaf inner ear after delivery to nonsensory cells through adenovectors. This is the first demonstration of cellular and functional repair in the organ of Corti of a mature deaf mammal. The data suggest a new therapeutic approach based on expressing crucial developmental genes for cellular and functional restoration in the damaged auditory epithelium and other sensory systems.

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Auditory hair cell replacement and hearing improvement by Atoh1 gene therapy in deaf mammals

It has been claimed that quantified features are inappropriate for phylogenetic anal- ysis. We consider that claim to be true under most conditions for characters discovered by com- monly used morphometric methods, including outline-based and conventional multivariate meth- ods. The most important reason these characters are unsuitable is that one of the tests of homol- ogy, the test of similarity, may be difficult to apply to them. This test is not even possible if the methods for comparing forms, such as outline-based techniques, do not ensure that the characters are located in the same part of the anatomy. Conventional methods, including principal compo- nents analysis, have no explicit basis for localizing characters. In addition, unless the transfor- mation between forms is homogeneous, conventional methods cannot dissect transformations re- gion by region to discover characters. However, one morphometric method, the thin-plate spline decomposed by its partial warps (TPS), finds characters that can be subjected to the same tests of homology (conjunction, similarity, and congruence) that we would apply to all other characters. Among available methods, TPS is unique in being able to locate the center and spatial extent of regional differences in shape and ensures that the same regions are compared among forms. We provide an example using the teleost fishes piranhas, in which tests of homology are applied to a synapomorphy found by the method. (Morphometrics; homology; synapomorphy; thin-plate spline; character analysis; piranha; Pygocentrus; Pygopristis; Serrasalmus.) Shape similarities among organisms Because much of our argument depends have long been recognized as having sys- on our meaning of homology, we begin tematic value. Whether shave features in with a brief foray into semantics. Follow- quantitative form can be a source of infor- ing a discussion of the definition of ho- mation about phylogenetic relationships is mology, we examine several morphometric more controversial. This doubt is reflected methods and judge their potential for in the literature, particularly in the claims yielding characters appropriate for phylo- that quantitative shape features cannot be genetic analyses. subjected to the same tests of homology that other characters must pass (Pimentel HOMOLOGY and Riggins, 1987). This position strikes di- Patterson (1982), like Rieppel (1980), dis- rectly at the use of morphometrics as a tinguished between taxic homology, a fea- class of tools for phylogenetic analysis. ture of a monophyletic group, and trans- Herein, we argue that ,at least one morpho- formational homology. The evidence of metric method is both suitable and useful taxic homologies is synapomorphies that in phylogenetic analysis because charac- have passed three tests: conjunction, simi- ters found by it can be treated in the same larity, and congruence. Systematists who way as can characters from any other use the term "synapomorphy" for shared source. However, we also contend that derived states, whether or not shown to be many methods currently in use are indeed congruent, qualify this definition by re- inappropriate because they cannot gener- stricting it to "corroborated synapomor- ate results meeting the criteria applied to phies." Systematists who use terms such as phylogenetic characters. "putative synapomorphy" to refer to the coded characters prior to testing their con-

Morphometrics, homology, and phylogenetics: quantified characters as synapomorphies

Summary Several models explain how a complex integrated system like the rodent mandible can arise from multiple developmental modules. The models propose various integrating mechanisms, including epigenetic effects of muscles on bones. We test five for their ability to predict correlations found in the individual (symmetric) and fluctuating asymmetric (FA) components of shape variation. We also use exploratory methods to discern patterns unanticipated by any model. Two models fit observed correlation matrices from both components: (1) parts originating in same mesenchymal condensation are integrated, (2) parts developmentally dependent on the same muscle form an integrated complex as do those dependent on teeth. Another fits the correlations observed in FA: each muscle insertion site is an integrated unit. However, no model fits well, and none predicts the complex structure found in the exploratory analyses, best described as a reticulated network. Furthermore, no model predicts the correlation between proximal parts of the condyloid and coronoid, which can exceed the correlations between proximal and distal parts of the same process. Additionally, no model predicts the correlation between molar alveolus and ramus and/or angular process, one of the highest correlations found in the FA component. That correlation contradicts the basic premise of all five developmental models, yet it should be anticipated from the epigenetic effects of mastication, possibly the primary morphogenetic process integrating the jaw coupling forces generated by muscle contraction with those experienced at teeth.

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Donald L. Swiderski

Papers

Geometric morphometrics for biologists: a primer

Geometric Morphometrics for Biologists

Auditory hair cell replacement and hearing improvement by Atoh1 gene therapy in deaf mammals

Morphometrics, homology, and phylogenetics: quantified characters as synapomorphies

Modularity of the rodent mandible: integrating bones, muscles, and teeth.