Characterization of Substrate-Borne Vibrational Signals of Euschistus servus (Heteroptera: Pentatomidae)

Abstract

Problem Statement: Stink bugs were not major pests of cotton in the southeastern United States until cotton varieties containing Bacillus thuringiensis (Bt) transgenes came into common use, enabling reductions in insecticide applications against highly destructive lepidopteran pests. To maintain the benefits of reduced insecticide applications, it would be advantageous to detect and target isolated populations of stink bugs before they rise to economically important levels. However, detection methods for these pests are less than optimal, and alternative methods are being investigated. One novel method of detection would be to exploit substrate-borne vibrational signals of these bugs. Approach: To develop an effective vibration detection method, substrate-borne vibrational signals produced by different species commonly occurring in the region must be characterized sufficiently to enable detection of these species in the absence of visual observation. In this research, substrate-borne vibrational signals were recorded from the brown stink bug Euschistus servus. These signals were categorized by dominant frequency, duration, and repetition time using a Gaussian mixture model, revealing an assortment of "songs" in an acoustic repertoire. Results: Females of E. servus emitted two distinct songs while males of E. servus emitted four distinct songs. Results indicated that the repertoire of this species differs from that of other species in the same geographical location (southeastern United States) reported in previous literature. Conclusion/Recommendations: In conclusion, detection of pentatomid pests by their substrate-borne vibrational signals must include the parameters of each unique song of each species of stink bug to be detected, including those of the two female and four male songs of E. servus. The characterization of these songs will allow for the development of a monitoring system in the field using strategically placed accelerometers to detect stink bug vibrational communication and thus provide a density map of the location of these pests.