Building and Visualising Ordinations of Shape Data in R With Morphospace

Area of Science:

• Evolutionary Biology
• Morphometrics
• Computational Biology

Background:

• Geometric morphometrics simplifies high-dimensional shape data for analysis.
• Current ordination and visualization methods lack a unified approach, limiting biological insight.

Purpose of the Study:

• To introduce "morphospace", an R package for streamlined shape ordination and visualization.
• To enhance the biological relevance of morphometric analyses through integrated tools.

Main Methods:

• The "morphospace" package offers a workflow for filtering nuisance variation, building biologically relevant ordinations, and projecting diverse elements.
• It integrates shape data with non-shape information for advanced visualizations.
• The package facilitates the creation of publication-ready figures and heuristic exploration.

Main Results:

• "morphospace" provides a unified approach to shape ordination and visualization in geometric morphometrics.
• The package enables filtering of nuisance variation and emphasizes different biological signals.
• It allows projection of various elements (shapes, clusters, axes, phylogenies) and integrates non-shape data.

Conclusions:

• The "morphospace" R package facilitates the creation of publication-ready visualizations for geometric morphometrics.
• It enhances the exploration of shape variation patterns and underlying evolutionary processes.
• This tool supports palaeontological and evolutionary research by improving data interpretation.