Data from: The faces of Bacidia schweinitzii: molecular and morphological data reveal three new species including a widespread sorediate morph
Lendemer, James C., 1 Institute of Systematic Botany, The New York Botanical Garden, Bronx, NY 10458-5126, U.S.A.
Harris, Richard C., 1 Institute of Systematic Botany, The New York Botanical Garden, Bronx, NY 10458-5126, U.S.A.
Ladd, Douglas, 2 The Nature Conservancy, 2800 S. Brentwood Blvd., St. Louis, MO 63144, U.S.A.
Published May 10, 2017 on Dryad.
Cite this dataset
Lendemer, James C.; Harris, Richard C.; Ladd, Douglas (2017). Data from: The faces of Bacidia schweinitzii: molecular and morphological data reveal three new species including a widespread sorediate morph [Dataset]. Dryad. https://doi.org/10.5061/dryad.k94h8
Bacidia schweinitzii is a common crustose lichen that is widespread in eastern North America. It is comprised of three distinct morphotypes differing in apothecial pigmentation. Here we show that molecular data from the mtSSU region affirms the distinctiveness of these morphotypes, prompting the recognition of three species: B. schweinitzii s.str., B. ekmaniana sp. nov. and B. purpurans sp. nov. We also show that a common sorediate crustose lichen, sympatric with B. schweinitzii, represents a monophyletic lineage whose relationship with B. schweinitzii s.str. could not be resolved with certainty using analyses of ITS and mtSSU sequence data. We recognize this sorediate lineage as a distinct species, B. sorediata sp. nov. All four taxa are described, illustrated and mapped.
This is a compressed zip folder that contains the input files and alignments for molecular phylogenetic analyses performed for the study. These include:1) alignment of nrITS (NEXUS); 2) alignment of nrITS used for distance metrics (NEXUS); 3, alignments of mtSSU used in maximum likelihood (ML; PHYLIP) and Bayesian inference (BI; NEXUS); and 4) alignments of mtSSU+nrITS (standard in NEXUSA format with excluded regions) used in partitioned ML (PHYLIP, together with partition input file for RAxML) and partitioned BI (NEXUS).