High-throughput iNaturalist image analysis reveals flower color divergence in Monarda fistulosa

Abstract

Characterizing patterns of trait variation across widespread species is a fundamental goal of natural history. Here we create a pipeline to analyze a large community science dataset and test hypothesized flower color divergence across the range of a widespread wildflower. Monarda fistulosa is a North American perennial that produces showy lavender inflorescences. Although previous literature suggests that the flowers of western M. fistulosa might display a deeper purple color than the eastern varieties, this divergence has not been assessed at scale. We process over 40,000 community science photographs of M. fistulosa to identify flowers and extract color. We demonstrate that the flowers of the montane western variety have lower lightness and higher chroma, corresponding to a deeper violet color, than those of eastern M. fistulosa . Our approach and validation provides a scalable framework for phenotyping community science images and enables analysis of geographic color variation in other widespread species.

Code and data availability

The paper's flower-color phenotyping pipeline has explicit public availability statements: the analysis code and produced datasets are on the authors' GitHub repository, the trained Roboflow segmentation model is publicly hosted, and the source iNaturalist/GBIF observation-image export is archived with a DOI. All are直接