Calculating structural complexity in phylogenies using ancestral ontologies

Area of Science:

• Evolutionary biology
• Phylogenetics
• Morphological complexity

Background:

• Measuring evolutionary complexity is challenging due to diverse concepts.
• Objective measurement of complexity remains elusive in evolutionary biology.

Purpose of the Study:

• To develop a simple, objective measure of evolutionary complexity.
• To incorporate hierarchical anatomical information into complexity assessment.
• To apply this measure to phylogenetic analysis.

Main Methods:

• Developed a node-driven complexity measure using anatomical ontologies.
• Utilized neomorphic and transformational characters for novelties and morphological regions.
• Integrated character scorings with anatomical ontologies to infer node ontologies and complexity scores.
• Applied the method to a dataset of 166 araneomorph spider species and 393 characters using the Spider Ontology (SPD).

Main Results:

• The node-driven approach revealed a complexity distribution skewed towards simplification in spiders.
• Complexity transitions showed no apparent correlation with character branch lengths.
• Node-driven and terminal-driven complexity scores were generally correlated, but transition values showed higher divergence.
• Ontology structure allowed complexity scoring for organ systems and body parts.

Conclusions:

• The developed node-driven method provides a robust measure of evolutionary complexity.
• Spider evolution, based on this measure, exhibits a trend towards simplification.
• The approach offers a way to trace complexity on phylogenetic trees and analyze organ system complexity.