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Using Phylogenetic and Coalescent Methods to Understand the Species Diversity in the Cladia aggregata Complex (Ascomycota, Lecanorales)

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Title
Using Phylogenetic and Coalescent Methods to Understand the Species Diversity in the Cladia aggregata Complex (Ascomycota, Lecanorales)
Published in
PLOS ONE, December 2012
DOI 10.1371/journal.pone.0052245
Pubmed ID
Authors

Sittiporn Parnmen, Achariya Rangsiruji, Pachara Mongkolsuk, Kansri Boonpragob, Aparna Nutakki, H. Thorsten Lumbsch

Abstract

The Cladia aggregata complex is one of the phenotypically most variable groups in lichenized fungi, making species determination difficult and resulting in different classifications accepting between one to eight species. Multi-locus DNA sequence data provide an avenue to test species delimitation scenarios using genealogical and coalescent methods, employing gene and species trees. Here we tested species delimitation in the complex using molecular data of four loci (nuITS and IGS rDNA, protein-coding GAPDH and Mcm-7), including 474 newly generated sequences. Using a combination of ML and Bayesian gene tree topologies, species tree inferences, coalescent-based species delimitation, and examination of phenotypic variation we assessed the circumscription of lineages. We propose that results from our analyses support a 12 species delimitation scenario, suggesting that there is a high level of species diversity in the complex. Morphological and chemical characters often do not characterize lineages but show some degree of plasticity within at least some of the clades. However, clades can often be characterized by a combination of several phenotypical characters. In contrast to the amount of homoplasy in the morphological characters, the data set exhibits some geographical patterns with putative species having distribution patterns, such as austral, Australasian or being endemic to Australia, New Zealand or Tasmania.

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Geographical breakdown

Country Count As %
Germany 2 3%
Malaysia 1 1%
Netherlands 1 1%
Italy 1 1%
Iceland 1 1%
United States 1 1%
Unknown 71 91%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 16 21%
Researcher 16 21%
Student > Master 9 12%
Professor 8 10%
Professor > Associate Professor 4 5%
Other 11 14%
Unknown 14 18%
Readers by discipline Count As %
Agricultural and Biological Sciences 43 55%
Biochemistry, Genetics and Molecular Biology 9 12%
Environmental Science 4 5%
Pharmacology, Toxicology and Pharmaceutical Science 1 1%
Business, Management and Accounting 1 1%
Other 3 4%
Unknown 17 22%