The quantitative genetics of floral trait variation in Lobelia: potential constraints on adaptive evolution.
Although pollinator-mediated natural selection has been measured on many floral traits and in many species, the extent to which selection is constrained from producing optimal floral phenotypes is less frequently studied. In particular, negative correlations between flower size and flower number are hypothesized to be a major constraint on the evolution of floral displays, yet few empirical studies have documented such a trade-off. To determine the potential for genetic constraints on the adaptive evolution of floral displays, I estimated the quantitative genetic basis of floral trait variation in two populations of Lobelia siphilitica. Restricted maximum likelihood (REML) analyses of greenhouse-grown half-sib families were used to estimate genetic variances and covariances for flower number and six measures of flower size. There was significant genetic variation for all seven floral traits in both populations. Flower number was negatively genetically correlated with four measures of flower size in one population and three measures in the other. When the genetic variance-covariance matrices were combined with field estimates of phenotypic selection gradients, the predicted multivariate evolutionary response was less than or opposite in sign to the selection gradient for flower number and five of six measures of flower size, suggesting genetic constraints on the evolution of these traits. More generally, my results indicate that the adaptive evolution of floral displays can be constrained by trade-offs between flower size and number, as has been assumed by many theoretical models of floral evolution.
Caruso
Christina M
CM
Departments of Biology and Mathematics, Grinnell College, Grinnell, Iowa 50112, USA. carusoc@uoguelph.ca
D000220:Adaptation, Biological; D000704:Analysis of Variance; D035264:Flowers / Q000033:anatomy & histology*; D007484:Iowa; D016013:Likelihood Functions; D029746:Lobelia / Q000033:anatomy & histology / Q000235:genetics*; D008957:Models, Genetic; D012641:Selection, Genetic