Advanced Dutch Elm Disease Management in Winnipeg through RPAS-Based Monitoring and Elm Bark Beetle Activity Tracking
Bibliographic record
Abstract
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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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".