Advanced Dutch Elm Disease Management in Winnipeg through RPAS-Based Monitoring and Elm Bark Beetle Activity Tracking
Notice bibliographique
Résumé
This study consisted of two projects designed to provide information to improve Dutch elm disease (DED), (Ophiostoma novo-ulmi), management methods in Winnipeg, Manitoba. The objective of the first project was to test whether a remote piloted aircraft system (RPAS) equipped with a multispectral camera can detect DED symptoms in American elm (Ulmus americana) trees. Three neighbourhoods in Winnipeg were surveyed using this technology in 2022 and 2023, and categorical maps of diseased versus healthy trees were generated for each neighbourhood using a variety of vegetation indices and methods of delineating tree canopies in the imagery. Ground disease detection surveys were conducted in conjunction with the aerial surveys to guide and validate these maps. Results for each survey showed that healthy tree canopies had significantly higher mean normalized difference vegetation index (NDVI) values than DED/hazard trees. Other vegetation indices were also tested, but mean NDVI values generated the most accurate classifications. Manually digitized polygons outlining the shape of each tree canopy also generated more accurate classifications than generic circles or rectangles centred on tree coordinates, but overall success of DED detection was still moderately low with manual polygons at 67.3%. The results from this research indicate that the use of RPAS solely to detect DED will require more refinement to increase accuracy levels to be as reliable as ground survey crews. However, the technology is effective at detecting dead elm trees or trees with advanced DED symptoms with 79.5% overall correct classification, and would therefore be a useful tool to assist with current DED management strategies, particularly in less accessible locations. The native elm bark beetle (Hylurgopinus rufipes) is the primary known insect vector of DED spread in Manitoba, while several other elm bark beetle species can also spread the disease elsewhere in North America. One of these species, the banded elm bark beetle (Scolytus schevyrewi) has been reported in rural Manitoba feeding on Siberian elm (Ulmus pumila). The objectives of the second project were to determine the beginning of emergence of summer brood of elm bark beetles in Winnipeg, and to determine if the banded elm bark beetle is present and attracted to American elm trees in Winnipeg. A pilot experiment was carried out from July 13 to September 18, 2023. American elm and Siberian elm logs were collected and left exposed in a Winnipeg neighbourhood. Logs were partially debarked throughout the study period. Beetles found on the surface of logs, boring into them, or inside the logs, along with larvae in galleries, were collected and preserved. Nearly all adult bark beetles collected were identified as banded elm bark beetles, which was unexpected given that banded elm bark beetles were not found to be attracted to American elm in previous studies in rural Manitoba. DNA bar coding technology was used to confirm that larvae and adults collected in elm logs were banded elm bark beetles. These findings suggest that banded elm bark beetles could potentially be a second significant vector of DED in Winnipeg’s urban forest.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».