An approach for ambrosia beetle (Coleoptera: Curculionidae: Scolytinae) management: can low-cost detectors effectively identify ethanol emissions in flood-stressed trees?

Abstract

Ambrosia beetles (Coleoptera: Curculionidae: Scolytinae) are small fungus-farming beetles that damage stressed nursery trees directly through tunneling and structural weakening, and indirectly by introducing pathogenic fungi. Stressed trees emit ethanol, which is the primary host-locating cue for ambrosia beetles. This study evaluated the efficacy of low-cost ethanol detectors as a solution for the early detection of flood-stressed trees susceptible to ambrosia beetle infestation. Experiments were conducted using 48 native dogwoods (Cornus florida L.) subjected to flooded or non-flooded conditions. The attacks of ambrosia beetles were significantly higher in flooded trees, indicating a clear preference and validating the use of flood stress as a reliable method for susceptibility assessment. Ethanol emitted from these trees was measured using low-cost alcohol saliva test strips and Dräger Pac 8000 personal gas detectors alongside a solid phase microextraction-gas chromatography-mass spectrometry (SPME-GC-MS) for ethanol confirmation. In addition to stem tissue analysis for ethanol detection via SPME-GC-MS, we found that twig and root tissue samples can also be assessed effectively using low-cost detectors such as alcohol strips and Dräger devices. GC-MS, a reliable method for volatile compound identification and quantification, confirmed ethanol as the dominant volatile in flooded trees, with both low-cost detectors correlating positively with SPME-GC-MS results. These detectors could offer a rapid, cost-effective method for identifying trees at risk of ambrosia beetle attack. However, their accuracy can be limited by false positives, as some plant genera emit aromatic volatiles such as eugenol, which may interfere with ethanol detection. More work is needed to optimize these tools for use by nursery growers, consultants, and researchers as an early-warning system and aid in ambrosia beetle management decision-making.