Diversity investigation by application of DNA barcoding: A case study of lepidopteran insects in Xinjiang wild fruit forests, China.

To investigate the species diversity of lepidopteran insects in Xinjiang wild fruit forests, establish insect community monitoring systems, and determine the local species pool, we test the applicability of DNA barcoding based on cytochrome oxidase subunit I () gene for accurate and rapid identification of insect species. From 2017 to 2019, a total of 212 samples with ambiguous morphological identification were selected for DNA barcoding analysis. Five sequence-based methods for species delimitation (ABGD, BINs, GMYC, jMOTU, and bPTP) were conducted for comparison to traditional morphology-based identification. In total, 2,422 samples were recorded, representing 143 species of 110 genera in 17 families in Lepidoptera. The diversity analysis showed that the richness indices for Noctuidae was the highest (54 species), and for Pterophoridae, Cossidae, Limacodidae, Lasiocampidae, Pieridae, and Lycaenidae were the lowest (all with 1 species). The Shannon-Wiener species diversity index (H') and Pielou's evenness (J') of lepidopteran insects first increased and then decreased across these 3 years, while the Simpson diversity index showed a trend of subtracted then added. For molecular-based identification, 67 lepidopteran species within 61 genera in 14 families were identified through DNA barcoding. Neighbor-joining (NJ) analysis showed that conspecific individuals were clustered together and formed monophyletic groups with a high support value, except for (Denis & Schiffermüller, 1775) (Noctuidae: Hadeninae). Sixty-seven morphospecies were classified into various numbers of MOTUs based on ABGD, BINs, GMYC, jMOTU, and bPTP (70, 96, 2, 71, and 71, respectively). In Xinjiang wild fruit forests, the family with the largest number of species is Noctuidae, followed by Geometridae, Crambidae, and the remaining families. The highest Shannon diversity index is observed for the family Noctuidae. Our results indicate that the distance-based methods (ABGD and jMOTU) and character-based method (bPTP) outperform GMYC. BINs is inclined to overestimate species diversity compared to other methods.