title: Identifying species of moths (Lepidoptera) from Baihua Mountain, Beijing, China, using DNA barcodes.
abstract: DNA barcoding has become a promising means for the identification of organisms of all life-history stages. Currently, distance-based and tree-based methods are most widely used to define species boundaries and uncover cryptic species. However, there is no universal threshold of genetic distance values that can be used to distinguish taxonomic groups. Alternatively, DNA barcoding can deploy a "character-based" method, whereby species are identified through the discrete nucleotide substitutions. Our research focuses on the delimitation of moth species using DNA-barcoding methods. We analyzed 393 Lepidopteran specimens belonging to 80 morphologically recognized species with a standard cytochrome c oxidase subunit I (COI) sequencing approach, and deployed tree-based, distance-based, and diagnostic character-based methods to identify the taxa. The tree-based method divided the 393 specimens into 79 taxa (species), and the distance-based method divided them into 84 taxa (species). Although the diagnostic character-based method found only 39 so-identifiable species in the 80 species, with a reduction in sample size the accuracy rate substantially improved. For example, in the Arctiidae subset, all 12 species had diagnostics characteristics. Compared with traditional morphological method, molecular taxonomy performed well. All three methods enable the rapid delimitation of species, although they have different characteristics and different strengths. The tree-based and distance-based methods can be used for accurate species identification and biodiversity studies in large data sets, while the character-based method performs well in small data sets and can also be used as the foundation of species-specific biochips.
authors.affiliation: College of Life Sciences, Capital Normal University Beijing, 100048, China.
authors.forename: Xiao F
authors.initials: XF
authors.lastname: Liu
authors.affiliation: College of Life Sciences, Capital Normal University Beijing, 100048, China.
authors.forename: Cong H
authors.initials: CH
authors.lastname: Yang
authors.affiliation: School of Forestry, Experiment Center, Northeast Forestry University Haerbin, 150040, China.
authors.forename: Hui L
authors.initials: HL
authors.lastname: Han
authors.affiliation: Wealth from Oceans Flagship, CSIRO Marine and Atmospheric Research GPO Box 1538, Hobart, Tasmania, 7001, Australia.
authors.forename: Robert D
authors.initials: RD
authors.lastname: Ward
authors.affiliation: College of Life Sciences, Capital Normal University Beijing, 100048, China.
authors.forename: Ai-Bing
authors.initials: AB
authors.lastname: Zhang
keywords: Bayesian; DNA barcode; Lepidoptera; cytochrome c oxidase subunit I; diagnostic character; genetic distance; maximum likelihood; moths; neighbor joining