geomorph: anrpackage for the collection and analysis of geometric morphometric shape data

Abstract

Summary1. 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.

Brain shape convergence in the adaptive radiation of New World monkeys

“…S6). To digitize the surface semilandmarks, a mesh of 268 roughly equidistant points was generated automatically on one specimen and then projected onto every other endocast, using the landmarks and curve semilandmarks as reference points for alignment and a thin-plate spline interpolation (36), as implemented in the geomorph package for R (37). To remove nonshape variation, a generalized Procrustes analysis (GPA) was performed.…”

Go big or go fish: morphological specializations in carnivorous bats

“…We used TPSDIG2 (v. 2.22; [37]) to digitize landmarks and sliding semi-landmarks in ventral and lateral views of the cranium, and lateral view of the mandible (electronic supplementary material, table S1). We used GEOMORPH (v. 2.15.3; [38]) to conduct geometric morphometric analyses of shape variation and allometry on each of these datasets. For each species and view, we performed Procrustes superimpositions to obtain landmark coordinates and centroid sizes across specimens.…”

Genome of the Tasmanian tiger provides insights into the evolution and demography of an extinct marsupial carnivore

“…All other analyses were performed using MorphoJ v1.06d 55 , except for K mult and ANOVA, which were estimated in the geomorph package of R 70 , and convergence measures C 1 -C 3 calculated in the R package convevol 23 . For all tests, statistical significance (α = 0.05) was determined by a random permutation procedure of 10,000 iterations, except in convevol, which was run for 1,000 iterations.…”