Production of multiple flowers in inflorescences allows the reproductive phenotypes of individual plants to include systematic among-flower variation, which could be adaptive. Systematic trait variation within inflorescences could arise from resource competition among flowers, or be a developmentally determined feature of flower position, regardless of resource dynamics. The latter, architectural effect typically manifests as continuous floral variation within inflorescences. For architectural effects to be adaptive, floral trait variation among individuals must covary with reproductive performance and be heritable. However, heritability and phenotypic selection on gradients of variation cannot be estimated readily with traditional statistical approaches. Instead, we advocate and illustrate the application of two functional data analysis techniques with observations of Delphinium glaucum (Ranunculaceae). To demonstrate the parameters-as-data approach we quantify heritability of variation in anthesis rate, as represented by the regression coefficient relating daily anthesis rate to inflorescence age. SNP-based estimates detected significant heritability (h 2 ¼ 0.245) for declining anthesis rate within inflorescences. Functional regression was used to assess phenotypic selection on anthesis rate and a floral trait (lower sepal length). The approach used spline curves that characterize within-inflorescence variation as functional predictors of a plant's fruit set. Selection on anthesis rate varied with inflorescence age and the duration of an individual's anthesis period. Lower sepal length experienced positive selection for basal and distal flowers, but negative selection for central flowers. These results illustrate the utility and power of functional-data analyses for studying architectural effects and specifically demonstrate that these effects are subject to natural selection and hence adaptive.

Ecological interaction and adaptation both depend on phenotypic characteristics. In contrast with the common conception of the 'adult' phenotype, plant bodies develop continuously during their lives. Furthermore, the different units (metamers) that comprise plant bodies are not identical copies, but vary extensively within individuals. These characteristics foster recognition of plant phenotypes as dynamic mosaics. We elaborate this conception based largely on a wide-ranging review of developmental, ecological and evolutionary studies of plant reproduction, and identify its utility in the analysis of plant form, function and diversification. An expanded phenotypic conception is warranted because dynamic mosaic features affect plant performance and evolve. Evidence demonstrates that dynamic mosaic phenotypes enable functional ontogeny, division of labour, resource and mating efficiency. In addition, dynamic mosaic features differ between individuals and experience phenotypic selection. Investigation of the characteristics and roles of dynamic and mosaic features of plant phenotypes benefits from considering within-individual variation as a functionvalued trait that can be analysed with functional data methods. Phenotypic dynamics and within-individual variation arise despite an individual's genetic uniformity, and develop largely by heterogeneous gene expression and associated hormonal control. These characteristics can be heritable, so that dynamic mosaic phenotypes can evolve and diversify by natural selection.