Quantitative Analysis of Fish Morphology Through Landmark and Outline-based Geometric Morphometrics with Free Software

Abstract

Morphology underpins key biological and evolutionary processes that remain elusive. This is in part due to the limitations in robustly and quantitatively analyzing shapes within and between groups in an unbiased and high-throughput manner. Geometric morphometrics (GM) has emerged as a widely employed technique for studying shape variation in biology and evolution. This study presents a comprehensive workflow for conducting geometric morphometric analysis of fish morphology. The step-by-step manual provides detailed instructions for using popular free software, such as the TPS series, MorphoJ, ImageJ, and R, to carry out generalized Procrustes analysis (GPA), principal component analysis (PCA), discriminant function analysis (DFA), canonical variate analysis (CVA), mean shape analysis, and thin plate spline analysis (TPS). The Momocs package in R is specifically utilized for in-depth analysis of fish outlines. In addition, selected functions from the dplyr package are used to assist in the analysis. The full process of fish outline analysis is covered, including extracting outline coordinates, converting and scaling data, defining landmarks, creating data objects, analyzing outline differences, and visualizing results. In conclusion, the current protocol compiles a detailed method for evaluating fish shape variation based on landmarks and outlines. As the field of GM continues to evolve and related software develops rapidly, the limitations associated with morphological analysis of fish are expected to decrease. Interoperable data formats and analytical methods may facilitate the sharing of morphological data and help resolve related scientific problems. The convenience of this protocol allows for fast and effective morphological analysis. Furthermore, this detailed protocol could be adapted to assess image-based differences across a broader range of species or to analyze morphological data of the same species from different origins.