The role of genus and life span in predicting seed and vegetative trait variation and correlation in Lathyrus, Phaseolus, and Vicia

Abstract

Premise: Annual and perennial life history transitions are abundant among angiosperms, and understanding the phenotypic variation underlying life span shifts is a key endeavor of plant evolutionary biology. Comparative analyses of trait variation and correlation networks among annual and perennial plants is increasingly important as new herbaceous perennial crops are being developed for edible seed. However, it remains unclear how seed to vegetative growth trait relationships correlate with life span.

Methods: To assess the relative roles of genus and life span in predicting phenotypic variation and trait correlations, we measured seed size and shape, germination proportion, and early-life-stage plant height and leaf growth over 3 mo in 29 annual and perennial, herbaceous congeneric species from three legume genera (Lathyrus, Phaseolus, and Vicia).

Results: Genus was the strongest predictor of seed size and shape variation, and life span consistently predicted plant height and leaf number at single time points. Correlation networks revealed that annual species had significant associations between seed traits and vegetative traits, whereas perennials had no significant seed-vegetative associations. Each genus also differed in the extent of integration between seed and vegetative traits, as well as within-vegetative-trait correlation patterns.

Conclusions: Genus and life span were important for predicting aspects of early-life-stage phenotypic variation and trait relationships. Differences in phenotypic correlation may indicate that selection on seed size traits will impact vegetative growth differently depending on life span, which has important implications for nascent perennial breeding programs.

Keywords: Fabaceae; Leguminosae; life history strategy; perennial grain; phenotypic correlation; phenotypic integration; relative growth rate; resource allocation; trade-offs; trait correlation network.