Field investigation‐ and dietary metabarcoding‐based screening of arthropods that prey on primary tea pests

Abstract

Predatory natural enemies play key functional roles in biological control. Abundant predatory arthropod species have been recorded in tea plantation ecosystems. However, few studies have comprehensively evaluated the control effect of predatory arthropods on tea pests in the field. We performed a 1‐year field investigation and collected predatory arthropods and pests in the tea canopy. A total of 7931 predatory arthropod individuals were collected, and Coleosoma blandum (Araneae, Theridiidae) was the most abundant species in the studied tea plantation. The population dynamics between C. blandum and four main tea pest species (Aleurocanthus spiniferus, Empoasca onukii, Ectropis grisescens, and Scopula subpunctaria) were established using the individual number of predators and pests in each month. The results showed that C. blandum appeared to co‐occur in the tea canopy with A. spiniferus, Em. onukii, and Ec. grisescens in a longer period. The prey spectrum of C. blandum was further analyzed using DNA metabarcoding. Among prey species, A. spiniferus, Em. onukii, and Ec. grisescens were included, and the relative abundance and positive rates of target DNA fragments of A. spiniferus were greater than that of other two pests. Combined with the high dominance index of C. blandum, co‐occurrence between C. blandum and A. spiniferus in time and space and high positive rate and relative abundance of target DNA fragments of A. spiniferus, C. blandum was identified to prey on A. spiniferus, and C. blandum may be an important predator of A. spiniferus. Thus, C. blandum has potential as a biological control agent of A. spiniferus in an integrated pest management strategy.

Using DNA metabarcoding to assess insect diversity in citrus orchards

“…DNA metabarcoding offers simultaneous identification of multiple species in bulk samples ( Yu et al, 2012 ). Prior studies have used metabarcoding to examine insect biodiversity, pest prevalence ( Piper et al, 2022 ), and to evaluate predator-prey relationships ( Yang et al, 2022 ). For example, ( Huang et al, 2022 ) used metabarcoding to reveal the composition of Diptera communities in a subtropical system, while ( Kirse et al, 2021 ) used this method to analyze seasonal shifts in arthropod diversity in Malaise trap catches.…”