Geometric morphometrics (GM) is an important method of shape analysis and increasingly used in a wide range of scientific disciplines. Presently, a single character comparison system of geometric morphometric data is used in almost all empirical studies, and this approach is sufficient for many scientific problems. However, the estimation of overall similarity among taxa or objects based on multiple characters is crucial in a variety of contexts (e.g. (semi-)automated identification, phenetic relationships, tracing of character evolution, phylogenetic reconstruction). Here we propose a new web-based tool for merging several geometric morphometrics data files from multiple characters into a single data file. Using this approach information from multiple characters can be compared in combination and an overall similarity estimate can be obtained in a convenient and geometrically rigorous manner. To illustrate our method, we provide an example analysis of 25 dung beetle species with seven Procrustes superimposed landmark data files representing the morphological variation of body features: the epipharynx, right mandible, pronotum, elytra, hindwing, and the metendosternite in dorsal and lateral view. All seven files were merged into a single one containing information on 649 landmark locations. The possible applications of such merged data files in different fields of science are discussed.

Geometric morphometrics (GM) is an important method of shape analysis and increasingly used in a wide range of scientific disciplines. Presently, a single character comparison system of geometric morphometric data is used in almost all empirical studies, and this approach is sufficient for many scientific problems. However, the estimation of overall similarity among taxa or objects based on multiple characters is crucial in a variety of contexts (e.g. (semi-)automated identification, phenetic relationships, tracing of character evolution, phylogenetic reconstruction). Here we propose a new web-based tool for merging several geometric morphometrics data files from multiple characters into a single data file. Using this approach information from multiple characters can be compared in combination and an overall similarity estimate can be obtained in a convenient and geometrically rigorous manner. To illustrate our method, we provide an example analysis of 25 dung beetle species with seven Procrustes superimposed landmark data files representing the morphological variation of body features: the epipharynx, right mandible, pronotum, elytra, hindwing, and the metendosternite in dorsal and lateral view. All seven files were merged into a single one containing information on 649 landmark locations. The possible applications of such merged data files in different fields of science are discussed.