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Phylogenetic, ecological and intraindividual variability patterns in grass phytolith shape
Kristýna Hošková1,2, Jiří Neustupa1, Petr Pokorný3
1Department of Botany, Faculty of Sciences, Charles University in Prague, Benátská, 2, CZ-128 01 Praha 2, Czech Republic.
Grass silica short cell (GSSC) phytoliths reveal evolutionary history. Geometric morphometrics of 2-D phytolith shapes show phylogenetic patterns, enhancing paleoecology insights.
Area of Science:
- Paleobotany and Evolutionary Biology
- Plant Morphology and Anatomy
Background:
- Grass silica short cell (GSSC) phytoliths are key fossil evidence for grass evolution and paleoecology.
- Quantitative analysis of phytolith shape variation offers new classification opportunities.
- Phylogenetic, ecological, and intraindividual phytolith shape variability patterns require further exploration.
Purpose of the Study:
- To analyze the full range of intraindividual phytolith shape variation in extant grasses.
- To explore phylogenetic patterns in phytolith shape using geometric morphometrics.
- To assess the utility of 2-D phytolith shape analysis for paleoecological reconstruction.
Main Methods:
- Geometric morphometric analysis of 3650 two-dimensional (2-D) phytolith outlines.
- Analysis encompassed 73 grass species, 48 genera, 18 tribes, and eight subfamilies, with a focus on Pooideae.
- Semi-landmarks were used to span phytolith outlines for shape analysis.
Main Results:
- Two-dimensional (2-D) phytolith shape is primarily influenced by deep-time diversification of grass subfamilies.
- Distinct phytolith shape variations were observed in early-diverging Pooideae lineages (Meliceae, Stipeae).
- Significant variation in intraindividual phytolith shape exists across species, creating a notable phylogenetic pattern.
Conclusions:
- Geometric morphometrics successfully revealed phylogenetic patterns in 2-D phytolith shape outlines.
- Phytoliths, analyzed via geometric morphometrics, show strong potential for tracking grass evolutionary history and paleoecology.
- This method is valuable for quantitative paleoecological reconstruction, especially with large phytolith datasets.
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