Data from: Systematics and evolution of inflorescence structure in the Tradescantia alliance (Commelinaceae)
View DatasetDescription
The Tradescantia alliance (subtribes Tradescantiinae and Thyrsantheminae of tribe Tradescantieae, family Commelinaceae) comprises a group of closely related New World genera exhibiting considerable variation in morphological, life history, and genomic traits. Despite ecological and cytogenetic significance, phylogenetic relationships among genera and species remain uncertain. In particular, variation in inflorescence morphology has confounded classification and taxonomy. The presence of self compatible and incompatible species allowed us to test the hypothesis that self compatible species will have condensed inflorescences. We inferred phylogenetic relationships using two plastid loci (rpL16, trnL-trnF) for 85 taxa in Commelinaceae, with sampling focused in the Tradescantia alliance. Constraint tests supported only subtribe Tradescantiinae, Tripogandra and Tinantia as monophyletic, with Tripogandra nested within Callisia. We estimated ancestral states for both breeding system and inflorescence condensation and tested for a correlation. Inflorescence morphology, an important character for generic identification, is more labile than previously expected, with condensed inflorescences evolving twice with three subsequent reversals. Breeding system evolution is more complex, with many more switches between self compatibility and self incompatibility and more uncertainty in ancestral state estimates. While we did not find a correlation between self compatibility and inflorescence condensation, we propose additional floral and inflorescence characteristics that may have contributed to variation in breeding system.
Citations (1)
- https://doi.org/10.1600/036364414x677991DataCite MDC
Cited on 01 March 2014
Weight: 1.23
Mentions (0)
No mentions found
Metrics Over Time
Publication Details
Subfield
Ecology, Evolution, Behavior and Systematics
Field
Agricultural and Biological Sciences
Domain
Life Sciences
Confidence Score
51%
Source
Scholar Data Model