Background: DNA metabarcoding is rapidly emerging as a cost-effective approach for large-scale biodiversity assessment and pest monitoring. The current study employed metabarcoding to assess insect diversity in citrus orchards in Ganzhou City, Jiangxi, China in both 2018 and 2019. Insects were sampled using Malaise traps deployed in three citrus orchards producing a total of 43 pooled monthly samples.
Methods: The Malaise trap samples were sequenced following DNA metabarcoding workflow. Generated sequences were curated and analyzed using two cloud databases and analytical platforms, the barcode of life data system (BOLD) and multiplex barcode research and visualization environment (mBRAVE).
Results: These platforms assigned the sequences to 2,141 barcode index numbers (BINs), a species proxy. Most (63%) of the BINs were shared among the three sampling sites while BIN sharing between any two sites did not exceed 71%. Shannon diversity index (H') showed a similar pattern of BIN assortment at the three sampling sites. Beta diversity analysis by Jaccard similarity coefficient (J) and Bray-Curtis distance matrix (BC) revealed a high level of BIN similarity among the three sites (J = 0.67-0.68; BC = 0.19-0.20). Comparison of BIN records against all those on BOLD made it possible to identify 40% of the BINs to a species, 57% to a genus, 97% to a family and 99% to an order. BINs which received a species match on BOLD were placed in one of four categories based on this assignment: pest, parasitoid, predator, or pollinator. As this study provides the first baseline data on insect biodiversity in Chinese citrus plantations, it is a valuable resource for research in a broad range of areas such as pest management and monitoring beneficial insects in citrus gardens.
Keywords: Beneficial species; Biodiversity; Biological control; Citrus pests; DNA metabarcoding.
© 2023 Liu et al.