The susceptibility of an urban ash canopy to the emerald ash borer - a temporal and spatial analysis from Winnipeg, Manitoba, Canada
Bibliographic record
Abstract
The invasive emerald ash borer (Agrilus planipennis Fairmaire; Coleoptera: Buprestidae) was first detected in Winnipeg, Manitoba in 2017 and has the potential to become a serious threat to the city's extensive ash (Fraxinus spp.) canopy. The objectives of this thesis were to predict A. planipennis emergence and peak activity patterns in Winnipeg; and to determine the potential susceptibility of neighbourhoods to infestation. To predict adult emergence and peak activity of A. planipennis, we used local weather station data to calculate the number of degree-days accumulated in each year for the 1970–2019 period using three different degree-day accumulation models. The estimated mean emergence dates for the 50-year period were June 14 ± 8.5 days (double sine model), June 14 ± 8.5 days (single sine model), and June 19 ± 9.1 days (standard model). The peak activity dates were July 16 ± 8.8 days (double sine model), July 17 ± 8.7 days (single sine model), and July 21 ± 9.4 days (standard model). To determine the potential susceptibility of neighbourhoods, ash density (trees/ha) maps, Moran plots, and correlograms were developed to model how A. planipennis might spread throughout Winnipeg and the potential corridors that may facilitate beetle movement. This study found that private green ash trees along riverbanks may be of most concern to city managers as these trees have significant potential to influence how EAB disperses throughout Winnipeg. The management of private green ash (Fraxinus pensylvanica Marsh.) trees along riverbanks will be a major variable in how successful A. planipennis dispersal is throughout the city. The results from this study will provide managers with information regarding the predicted temporal and spatial behavior of A. planipennis in Winnipeg allowing for improved timing of control measures and monitoring.
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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 | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".