Holotestoid: a computational model for testing hypotheses about echinoid skeleton form and growth.

Area of Science:

• Paleontology
• Developmental Biology
• Computational Biology

Background:

• Echinoid skeleton (test) morphology is complex.
• Analyzing test patterns requires multifaceted approaches.
• Previous analyses faced challenges with single-method limitations.

Purpose of the Study:

• To present Holotestoid, a novel computational model for echinoid test growth.
• To emulate macrostructural ontogenic processes in test development.
• To explain morphological disparity in echinoid tests.

Main Methods:

• Developed a computational model (Holotestoid) emulating four ontogenic processes: plate growth, addition, interaction, and gapping.
• Used a geometric representation and analogies (bubble interactions, close-packing) to simulate growth.
• Simulated growth zones by adjusting parameters like ambulacral column angle.

Main Results:

• Successfully simulated growth zones for multiple echinoid species (e.g., Arbacia punctulata, Strongylocentrotus franciscanus).
• Quantitatively compared simulated morphology with real specimens, validating the model.
• Demonstrated the model's ability to explain morphological variations by altering key parameters.

Conclusions:

• Holotestoid effectively simulates echinoid test growth and development.
• The model provides a framework for understanding morphological diversity in echinoids.
• This computational approach enhances the analysis of skeletal patterns in marine invertebrates.