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Published: 2016-08-09

Progress on the phylogeny of caddisflies (Trichoptera)

University of California, Department of Entomology and Nematology; Briggs Hall, Room 367, Davis, CA 95616-5270, U.S.A.
BioArch, Environment Building, Department of Biology, University of York, YO10 5DD, York, UNITED KINGDOM.
Beijing Advanced Innovation Center for Food Nutrition and Human Health, and the College of Food Science and Nutritional Engineering, China Agricultural University, Beijing, CHINA
Smithsonian Institution, Office of Research Information Services, Office of the CIO, Washington D.C., U.S.A. 20013-7012
Div. Vertebrate Zoology: Herpetology, American Museum of Natural History, Central Park West at 79th Street, New York NY 10024-5010 U.S.A.
University of Minnesota, Department of Entomology, 1980 Folwell Ave., St. Paul, MN 55108, U.S.A.
Annulipalpia Integripalpia Brevitentoria Plenitentoria Phylogeny


We present our current phylogenetic hypothesis on the phylogeny of Trichoptera, generated from an analysis of over 7000 nucleotides from 18S and 28S rRNA, EF-1α, COI, and CAD. We corroborate our earlier hypotheses, with results that include a monophyletic Annulipalpia, Integripalpia, Brevitentoria, and Plenitentoria. Monophyly of Psychomyioidea, Pseudoneureclipsidae, and Grumichellinae were confirmed. The "Spicipalpian" families were again found to be paraphyletic, and most closely related to Integripalpia. Ptilocolepidae was not found to be monophyletic, but support for its paraphyly was so weak that we interpret our results as unresolved. We interpret our measures of branch support, and present a collapsed phylogeny that more conservatively represents our current hypothesis. We discuss how these data can eventually be merged into other sources of data, such as COI barcode data and transcriptomes, and suggest that a single huge analysis of all data, with all taxa, is unnecessary if analyses can be phylogenetically subdivided into many separate parts, using transcriptome data to fix the deepest nodes, and allowing faster evolving data to be more appropriately targeted to nodes closer to the tips of the tree.


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