Several native species of Lauraceae (e.g. sassafras) in the southeastern United States are being eradicated by laurel wilt disease. Laurel wilt is caused by a highly invasive and cryptic ambrosia beetle, Xyleborus glabratus, and its fungal symbiont. The symbiont pathogen is spread during colonization of native Lauraceae. Xyleborus glabratus and the pathogen are remarkably effective at colonizing and killing healthy populations of Lauraceae in a brief time period. Control methods have been unable to slow the spread of laurel wilt disease and X. glabratus populations have been spreading into northern latitudes. Presently, cold temperatures may be the only factor limiting establishment of the beetle in interior populations of sassafras. Empirically derived physiological data from this study were combined with climatic, microhabitat, and host data to model the invasive potential/hazard rate of X. glabratus and laurel wilt in sassafras forests of the United States. Sharing this model data will help land managers, forest health specialists, urban foresters, and landowners make informed proactive management decisions regarding laurel wilt disease.

Standoff detection of targets using volatiles is essential when considering substances that are hazardous or dangerous, or for which the presence or location is unknown. For many invasive biological threats, their presence is often not realized until they have begun visibly affecting and spreading through crops or forests. The fungus Raffaelea lauricola is a biothreat vectored by the invasive beetle Xyleborus glabratus, or redbay ambrosia beetle (RAB), whose presence in avocado groves is currently detectable by visual inspection. Once visually identified, the affected trees must be removed and destroyed to protect those remaining trees. However, if the fungus is identified via standoff volatile detection, there is anecdotal evidence that it can be treated with propiconazole and saved from progression to the fatal laurel wilt disease. As a result of the rapid spread of R. lauricola and the quick death of trees, early detection through standoff methods is essential. The only current method of pre-symptomatic identification is canine detection. Canines are sensitive and selective biological detectors that can trace odors to their source, despite the presence of a variety of background odors. The present research evaluated the volatile organic compounds (VOCs) of the laurel wilt disease and R. lauricola using headspace solid phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC-MS). Additionally, a new method for odor collection and presentation to trained detection canines was developed. Knowledge of the disease and standoff volatile detection capabilities are improved using this information.

Laurel wilt disease is a vascular wilt affecting the xylem and water conductivity in trees belonging to the family Lauraceae. The disease was introduced by an invasive species of ambrosia beetle, Xyleborus glabratus. The beetle, together with its newly described fungal symbiont Raffaelea lauricola (pathogenic to host trees), has lead to the devastation and destruction of over 300 million wild redbay trees in southeastern forests. Ambrosia beetles make up a very unique clade of beetle and share a co-evolved obligatory mutualistic relationship with their partner fungi. Rather than consuming host tree material, the beetles excavate galleries or canals within them. These galleries serve two purposes: reproduction and fungal gardening. The beetles house fungal spores within specialized sacs, mycangia, and essentially inoculate host trees with the pathogenic agent. They actively grow and cultivate gardens of the fungus in galleries to serve as their sole food source. Once the fungus reaches the xylem vessels of the host tree, it thrives and leads to the blockage of water flow, both because of fungal accumulation and to the host response of secreting gels, gums and tyloses to occlude vessels in an attempt to quarantine the fungus. This disease spreads rapidly, and as a result, once symptoms become visible to the naked eye, it is already too late to save the tree, and it has likely already spread to adjacent ones. The present study presents the first documented study involving the early detection of disease from deep within a tree through the use of scent-discriminating canines. In addition, the present study has lead to the development of a novel sample collection device enabling the non-destructive sampling of beetle galleries. Finally, a metabolomics approach revealed key biochemical pathway modifications in the disease state, as well as potential clues to disease development.