Back

Green Lacewing Chrysoperla rufilabris (Neuroptera: Chrysopidae) is a potential biological agent for controlling crapemyrtle bark scale (Hemiptera: Eriococcidae)

Wu, B.; Xie, R.; Gu, M.; Qin, H.

2022-04-18 ecology
10.1101/2022.04.18.488594 bioRxiv
Show abstract

Crapemyrtle bark scale (CMBS; Acanthococcus lagerstroemiae), an invasive sap-sucking hemipteran, has spread across 16 U.S. states. Infestation of CMBS negatively impacts the flowering of crapemyrtles and reduces the aesthetic quality of ornamental plants. The widespread use of soil-applied neonicotinoid insecticides to repress the CMBS infestation could threaten important beneficial insects; therefore, using natural enemies to control CMBS is greatly needed. This study evaluated larval green lacewing (Chrysoperla rufilabris) as a biocontrol agent of CMBS. Predatory behavior of the larval C. rufilabris upon CMBS was documented under a stereomicroscope using infested crapemyrtle samples collected from different locations in College Station. Predation potential of C. rufilabris upon CMBS eggs and foraging performance using Y-maze assay were both investigated in laboratory conditions. Results confirmed that larval C. rufilabris preyed on CMBS nymphs, eggs, and adult females. The evaluation of predation potential results showed that the number of CMBS eggs consumed in 24 hours by 3rd instar C. rufilabris (176.4 {+/-}6.9) was significantly higher than by 2nd instar (151.5{+/-}6.6) and by 1st instar (11.8{+/-}1.3). The foraging performance results showed that larval C. rufilabris could target CMBS under dark, indicating that some cues associated with olfactory response were likely involved when preying on CMBS. This study is the first report that validated C. rufilabris as a natural predator of CMBS and its potential as a biological agent to control CMBS. Future investigation about the olfactory response of larval C. rufilabris to CMBS would benefit the development of environmental-friendly strategies to control CMBS spread.

Matching journals

The top 2 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.