DNA metabarcoding and morphological identification reveal similar richness, taxonomic composition and body size patterns among flying insect communities

Abstract

Tracking insect biodiversity trends and predicting future trajectories is limited by a lack of monitoring data across large spatiotemporal scales. DNA metabarcoding is a time‐ and cost‐efficient method to obtain these data, but has several potential limitations in comparison to traditional morphological approaches. For example, metabarcoding may miss low‐abundance or smaller bodied individuals and is limited to presence/absence information, which may bias estimates of biodiversity and community composition. However, few comparisons of metabarcoding and morphology‐based identification have been made using insects, the by far most diverse animal taxonomic group. Here, we compared terrestrial insect communities identified via morphology versus metabarcoding across four different habitats and three seasons (late spring, mid‐summer and early autumn) during 2019. We compared identified species and community richness, composition and body size, with a focus on key taxonomic groups of bees, true bugs, butterflies and hoverflies. We identified 252 total species, with 54.8% identified by both methods, whereas 21.4% and 19.8% were solely detected with metabarcoding or morphology, respectively. Overall, total community richness, taxonomic composition and community body size were similar between methods. Metabarcoding detection successes declined in low‐abundance and smaller taxa, particularly bees, hoverflies and true bugs; however, species richness of hoverflies and butterflies tended to be higher compared with morphological identification. Our results show that metabarcoding can provide an accurate overview of insect community differences that are comparable to those determined via morphological identification. We recommend that insect monitoring programmes consider incorporating metabarcoding, although future research is needed to overcome some remaining limitations.