A Phylogenetic Regression Model for Studying Trait Evolution on Network

A phylogenetic regression model that incorporates the network structure allowing reticulation event to study trait evolution is proposed. The parameter estimation achieved through maximum likelihood approach, where an algorithm developed by taking a in eNewick format as input build up variance–covariance matrix. applied common sunflower, Helianthus annuus, investigating its traits used respond drought conditions. Results show our provides acceptable estimates of parameters, most analyzed were found have significant correlation with tolerance.