James D. Boyko

The paper analyzes global flower color diversity using community science data, finding a latitudinal gradient in color diversity and associations with climate and pollination strategies.

The paper investigates how vegetative and reproductive traits contribute to habitat shifts in Neotropical Myrtaceae, finding vegetative traits act as enablers while reproductive traits show both enabler and adaptive patterns.

The paper introduces HyperMk2, a method to efficiently model the coevolution of multiple binary characters by reducing state space, enabling analysis of larger systems than previous methods.

This paper introduces a method for automatically selecting optimal discrete character models using regularization and simulated annealing, showing improved statistical performance and biological realism.

This paper improves ancestral state reconstruction by introducing joint reconstructions and uncertainty quantification, showing higher accuracy and biological insights in antibiotic resistance evolution.

The paper introduces an R package called mvh for assembling and organizing virtual herbaria from openly available specimen images, achieving a 99% success rate in downloading images.

SegColR automates image segmentation and color extraction using deep learning models, enabling efficient phenotypic data analysis from biodiversity images.

The paper investigates historical causes for the latitudinal polyploidy gradient by analyzing ploidy states and ancestral niches across four plant clades.

The paper uses hidden Markov models to show that trait change rates, not static traits, predict diversification rates in flowering plants.