Giant taxon-character matrices: the future of morphological systematics

Area of Science:

• Systematics and evolutionary biology.
• Phylogenetic analysis using morphological data.

Background:

• The study addresses the debate surrounding the use of large morphological (phenomic) datasets in phylogenetics.
• It critiques the practice of simply eliminating "problematic" characters, as proposed by Simões et al. ()
• This approach risks discarding valuable phylogenetic information.

Discussion:

• Morphological datasets are essential for robust phylogenetic inference.
• The elimination of characters, rather than their careful recoding, is a flawed methodology.
• Best practices for morphological data collection are necessary to advance systematics.

Key Insights:

• Large morphological datasets are indispensable for accurate phylogenetic reconstruction.
• Recoding "problematic" characters is vital for maximizing phylogenetic signal.
• Adopting standardized data collection protocols is crucial for the field.

Outlook:

• Further research into character recoding algorithms and best practices is recommended.
• The integration of large phenomic datasets will continue to shape phylogenetic studies.
• Promoting rigorous morphological data collection will enhance the reliability of evolutionary trees.