Format: ORAL

Morgan R. Gostel1, M. Andotiana Andriamanohera1, Higor Antonio-Domingues2, Ana R. G. Simes2, Isabel Larridon2, Benoit Loeuille2

1 Botanical Research Institute of Texas, Fort Worth, Texas, USA 2 Royal Botanic Gardens, Kew, Richmond, UK

The ironweed tribe, Vernonieae, is one of the most species rich in the daisy family (Compositae) and has a complicated taxonomic history that has led to it being referred to by a number of pejoratives, including the evil tribe. A key challenge for taxonomists who work with this tribe was the recognition of a large and poorly defined core genus, Vernonia, which included more than 1,000 species worldwide. In 1999, the genus was re-circumscribed to comprise just 20 species from the Americas and as a result, the necessary reclassification of more than 1,000 species in Vernonia sensu lato was initiated. In the last two decades, significant systematic efforts have resulted in the reclassification of many Vernonieae taxa in the Western Hemisphere. However, comparably little progress has been made toward taxonomic revision of the genus in the Eastern Hemisphere, where ca. 700 species are recognized from West Africa to Southeast Asia and the Pacific islands. Throughout the range of this tribe in the Eastern Hemisphere, there are currently 13 subtribes and 67 genera, but approximately 150 species in this tribe remain in Vernonia and await reclassification. Furthermore, recent studies suggest few of the subtribes currently recognized are monophyletic. We present results of phylogenomic analyses using a combined marker set including Angiosperms353 and Compositae-1061 as well as a greatly expanded sampling of species in this tribe from the Eastern Hemisphere to test the monophyly of subtribes and genera. We also explore morphological character variation in the tribe to understand patterns of evolution and help to support sub-tribal identification of taxa in the field and collections. Lastly, we present a plan to curate and rapidly share taxonomic data using the Global Compositae Database.