Flowers occupy color‐space extremes: an anthocyanin‐derived theoretical floral color‐space approach Journal Article uri icon

Overview

abstract

  • Abstract; ; Premise; Floral color is a stunning, complex trait that has long served as a model for connecting genetics, development, evolution, and ecology. Nevertheless, few mechanistic models relate flower color to the pigments that produce variation, nor has there been much exploration into theoretically possible flower color variation. Here we explored these topics using an anthocyanin‐derived theoretical color‐space approach.; ; ; Methods; ; We characterized flower color, floral anthocyanin concentrations, evolutionary history, and biogeography for 51 species of neotropical; Ruellia; to compare extant color diversity to an anthocyanin‐derived theoretical color space and analyzed potential drivers of variation. To build the color space, we utilized reflectance spectrometry, HPLC, double‐digest restriction‐site‐associated next‐generation sequencing, and an extensive data set of; Ruellia; occurrences.; ; ; ; Results; ; An anthocyanin floral color model predicted a significant portion of the observed variation in reflectance spectra. Flowers spanned most of the theoretically possible color space, but with phenotypes clustered at the extreme edges of the space. Species of; Ruellia; exhibited less biochemical constraint than other well‐studied lineages, commonly producing three or more types of anthocyanins (39%), but still showed evidence of constraint. Shared evolutionary history and biogeographical overlap were not strong predictors of color disparity between species pairs.; ; ; ; Conclusions; ; Anthocyanins were primary predictors of flower color in; Ruellia; , but a significant portion of variation remained unexplained by our model, implicating additional mechanisms (e.g., co‐pigmentation and pH) underlying flower color. Modeling color space provided a powerful framework for quantifying evolutionary constraints, offering insights into the mechanisms shaping phenotypic diversity.; ;

publication date

  • January 15, 2026

Date in CU Experts

  • January 16, 2026 10:50 AM

Full Author List

  • Watts JL; Medina N; Kiel C; Luján M; Smith SD; Manzitto‐Tripp EA

author count

  • 6

Other Profiles

International Standard Serial Number (ISSN)

  • 0002-9122

Electronic International Standard Serial Number (EISSN)

  • 1537-2197

Additional Document Info

number

  • e70149