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The radiation of angiosperms is marked by a phenomenal diversity of floral size, shape, color, scent, and reward.1,2,3,4 The multi-dimensional response to selection to optimize pollination has generated correlated suites of these floral traits across distantly related species, known as “pollination syndromes.”5,6,7,8,9 The ability to test the broad utility of pollination syndromes and expand upon the generalities of these syndromes is constrained by limited trait data, creating a need for new approaches that can integrate vast, unstructured records from community-science platforms. Here, we compile the largest North American flower color dataset to date, using GPT-4 with Vision to classify color in over 11,000 species across more than 1.6 million iNaturalist observations. We discover that red- and orange-flowering species (classic “hummingbird pollination” colors) bloom later in eastern North America compared with other colors, corresponding to the arrival of migratory hummingbirds. Our findings reveal how seasonal flowering phenology, in addition to floral color and morphology, can contribute to the hummingbird pollination syndrome in regions where these pollinators are migratory. Our results highlight phenology as an underappreciated dimension of pollination syndromes and underscore the utility of integrating artificial intelligence with community-science data. The potential breadth of analysis offered by community-science datasets, combined with emerging data extraction techniques, could accelerate discoveries about the evolutionary and ecological drivers of biological diversity. 

Combinations of correlated floral traits have arisen repeatedly across angiosperms through convergent evolution in response to pollinator selection to optimize reproduction. While some plant groups exhibit very distinct combinations of traits adapted to specific pollinators (so-called pollination syndromes), others do not. Determining how floral traits diverge across clades and whether floral traits show predictable correlations in diverse groups of flowering plants is key to determining the extent to which pollinator-mediated selection drives diversification. The North AmericanSilenesectionPhysolychnisis an ideal group to investigate patterns of floral evolution because it is characterized by the evolution of novel red floral color, extensive floral morphological variation, polyploidy, and exposure to a novel group of pollinators (hummingbirds). We test for correlated patterns of trait evolution that would be consistent with convergent responses to selection in the key floral traits of color and morphology. We also consider both the role of phylogenic distance and geographic overlap in explaining patterns of floral trait variation. Inconsistent with phenotypically divergent pollination syndromes, we find very little clustering of North AmericanSileneinto distinct floral morphospace. We also find little evidence that phylogenetic history or geographic overlap explains patterns of floral diversity in this group. White- and pink-flowering species show extensive phenotypic diversity but are entirely overlapping in morphological variation. However, red-flowering species have much less phenotypic disparity and cluster tightly in floral morphospace. We find that red-flowering species have evolved floral traits that align with a traditional hummingbird syndrome, but that these trait values overlap with several white and pink species as well. Our findings support the hypothesis that convergent evolution does not always proceed through comparative phenotypic divergence, but possibly through sorting of standing ancestral variation.