- Department of Plant Protection Biology, Swedish University of Agricultural Sciences
- SnifferDogs Sweden
Vosvrdova, N.; Johansson, A.; Turcani, M.; Jakus, R.; Tyser, D.; Schlyter, F.; Modlinger, R.
One of the most promising techniques for rapid detection of bark beetle-infested trees is the use of specially trained dogs. Due to the novelty of using dogs in detecting bark beetle-infested trees, evaluation of success or comparison with the traditional approaches is lacking. Spruces were pre-treated with a synthetic pheromone at several tree positions in six experimental forest stands of 4-12 ha. The tree positions were selected based on their arrangement in a random scheme or in patches considered suitable for bark beetle colonisation. Three dogs of different ages, sex, and levels of experience in detecting Ips typographus were compared with three experienced human bark beetle specialists. We used GPS positioning of dog tracks (unleashed), handlers, human experts, and detection points during the search under a blind-test procedure for tracking positions. The potential utility of the search methods was estimated with three aspects: 1) search success: detection of infested trees, 2) search effort: length of route, and 3) search efficiency: trees detected / unit time.Dog-handler pairs were overall more successful in detecting trees attacked by bark beetles than human experts. In particular, the success rate of dogs was higher in plots with random arrangement pre-baited trees and search efficiency was four times higher than that of the human experts.The most efficient time for the use of dogs for detection would be during the spring flight period, when detection of first attacks and small hot spots could potentially prevent the development of larger infestations. The main advantage of using the dog search method is to amplify the time-window from about one week to one month from the detection to prompt removal of the infested trees from the forest.
Detection dog; Forest pest management; Ips typographus; Norway spruce; Green attack
Forest Ecology and Management
2023, Volume: 528, article number: 120626
SLU Plant Protection Network
SLU Forest Damage Center
SDG15 Life on land