Using synthetic semiochemicals to train canines to detect bark beetle–infested trees

The dog detection allows timely removal by sanitation logging of first beetle-attacked trees before offspring emergence, preventing local beetle increases. Detection dogs rapidly learned responding to synthetic bark beetle pheromone components, with known chemical titres, allowing search training during winter in laboratory and field. Dogs trained on synthetics detected naturally attacked trees in summer at a distance of > 100 m.

Context An early detection of first beetle-attacked trees would allow timely sanitation felling before offspring emergence, curbing local beetle increase.
Aims We tested if detection dogs, trained off-season on synthetic pheromone components from Ips typographus, could locate naturally bark beetle–infested spruce trees.
Methods Indoor training allowed dogs to discriminate between the infestation odours (target) and natural odours (non-target) from the forest. Odour stimuli were shown by chemical analysis to be bioactive at extremely low-levels released (< 10−4 ng/15 min) in the laboratory.
Results Detection dogs, trained to recognise four different synthetic pheromone compounds in the wintertime, were able to detect naturally infested spruce trees unknown to humans the following summer. The dog-handler pairs were able to detect an infested spruce tree from the first hours of beetle attack until several weeks after first attack, long before discolouration of the crown. Trained sniffer dogs detected infested spruce trees out to ≥ 100 m, as measured by GPS-collar tracks.
Conclusion Dog-handler pairs appear to be more efficient than humans alone in timely detecting bark beetle infestations due to the canine’s ability to cover a greater area and detect by olfaction infestations from a far longer distance than can humans.

Keywords
Ips typographus, Gas chromatography–mass spectrometry extracted ion chromatograms, Detection dog, Sanitation logging, Forest protection, Norway spruce

Open-access publication
Johansson, A., Birgersson, G. & Schlyter, F. Annals of Forest Science (2019) 76: 58. https://doi.org/10.1007/s13595-019-0841-z

Data availability
The datasets generated and/or analysed during the current study are available in the Zenodo repository (Johansson et al. 2019) at https://doi.org/10.5281/zenodo.2605357.