Collaborative Research: ButterflyNet--an integrative framework for comparative biology

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The world is crawling with insects, many of which play crucial roles as pollinators, prey, mutualists, and critical components of ecosystem health. Despite their significance, insects remain understudied, imposing major limitations on our understanding of the patterns and processes in insect ecology and evolution. Butterflies are the exception, however, thanks to the efforts of centuries of collectors and enthusiasts who have appreciated their beauty and fascinating biology. More is known about their morphology, species distributions, behavior, and larval resources than any other insect group. However, this information needs to be synthesized, placed in an evolutionary context, and made available for research. This project will achieve these two goals by reconstructing the evolutionary history of the approximately 18,800 described species and assembling a database of biological information about each species using field guides, social media, collections, and other sources. All of this information will be made available to the public via a website with the goal of catalyzing synthetic research and comparative studies. In addition to public outreach and education, the members of the research team will train graduate students and postdoctoral researchers in systematics and bioinformatics.This project will produce a set of online tools and databases for comparative studies of butterflies. At the heart of the project is the assembly of a molecular phylogeny incorporating all known butterfly species. A hierarchical approach will be used to reconstruct butterfly relationships. To create a robust backbone phylogeny, approximately 500 loci will be captured from a single exemplar species from within each of the ~1,800 genera using anchored enrichment prior to sequencing. Genetic data from public databases and from our own sequencing efforts will then be collected to include remaining known species and complete the phylogeny. Model-based inference will examine the complexity of speciation, extinction, biogeography, and trait evolution. Existing locality data will be assembled from museum collections, inventories, citizen science monitoring networks, and expert knowledge to model species distributions using the integrative Map of Life framework. Species trait data have already been assembled for some groups and regions, but this project will create a consistent, harmonized trait database while also closing major gaps to create a globally comprehensive compilation of trait data on species life history, interactions, ecology, and distributions. All of these data layers will be made available through the Map of Life online platform, thus delivering community vetted and curated data and tools to catalyze comparative research.