Herrick & Mankin: Early Detection of the Red Palm Weevil by Acoustics 983 ACOUSTICAL DETECTION OF EARLY INSTAR RHYNCHOPHORUS FERRUGINEUS (COLEOPTERA: CURCULIONIDAE) IN CANARY ISLAND DATE PALM, PHOENIX CANARIENSIS (ARECALES: ARECACEAE)

The red palm weevil (RPW), Rhynchophorus ferrugineus (Olivier), recently found in Curaçao and Aruba, has become an economically significant palm tree pest in many tropical and subtropical regions. By the time a palm infested with RPW displays visible damage, larvae have destroyed much of the trunk internal structure, typically resulting in tree mortality. Acoustic technology may enable pest managers to detect and treat early RPW infestations before tree mortality, and to reduce unwanted importation and/or exportation of infested palms. Experiments were conducted in Aruba to determine the detectability of sounds produced by early instars in open, urban environments and in enclosures with ca. 10 dB acoustical shielding. To distinguish RPW signals from background noise, recordings first were analyzed to identify larval sound impulse bursts, trains of 7-199 impulses, 3-30-ms in duration, where impulses within the train were separated by less than 0.25 s. For a burst to be considered a larval sound, it was specified that a majority of its impulses must have spectra that match mean spectra (profiles) of known larval sound impulses more closely than profiles of background noise or known nontargeted sound sources. Based on these analyses, RPW larval bursts were detected in > 80% of palm fronds inoculated with neonates the previous day. There were no significant differences between burst rates in enclosed and open environments, but the shielding provided by the enclosure enabled detection of early instars from greater distances. Thus, there is potential to use acoustic technology to detect early RPW infestation in either minimally shielded or open environments. In addition, because late-instar impulses ranged to higher amplitude and had greater diversity of spectral features than with early instars, it may be possible to identify late-instar infestations based on the amplitudes and the diversity of sound features detected.