Insect migration is a key ecological process with significant implications for biodiversity, ecosystem functioning, and agriculture. However, the seasonal dynamics of most airborne insect taxa remain poorly understood. Conventional monitoring methods are often constrained by low taxonomic resolution and difficulties in specimen identification. DNA metabarcoding offers a powerful alternative; however, its application to directly sampled airborne insects is limited. To address this gap, this study applied a two-marker metabarcoding framework-cytochrome c oxidase subunit I (COI) and mitochondrial 16S rRNA-to characterize the temporal dynamics of airborne insect communities in a southern port city of South Korea. Monthly collections from April to October 2023 using a 10-m aerial trap revealed diverse taxa, including small-bodied insects, endemic species, and agricultural pests of potential concern. COI outperformed 16S by recovering a broader range of orders and resolving over half of amplicon sequence variants (ASVs) to the species level, compared to less than 20% for 16S, which was largely restricted to Hemiptera despite recovering more ASVs overall. These results highlight the relative superiority of COI for species-level resolution in airborne insect monitoring and demonstrate that 16S rRNA can complement COI by capturing additional diversity. The combined use of COI and 16S rRNA was particularly effective, improving taxonomic coverage and consistently revealing three distinct temporal phases in community composition: early May to early July, late July to early September, and late September to late October. Our findings demonstrate the utility of metabarcoding for the high-resolution monitoring of airborne insect diversity and temporal dynamics. We further highlight the importance of developing regionally enriched DNA reference libraries to maximize species-level assignments and support long-term surveillance of migratory insect populations.
Kim et al. (Mon,) studied this question.