Spatiotemporal surveillance of Varroa destructor in Ontario, Canada
Bibliographic record
Abstract
There has been continued concern regarding the sustained levels of overwinter colony losses experienced by beekeepers in Canada. Although not entirely attributable to one single cause, these losses have been repeatedly linked to the parasitic mite, Varroa destructor, and thus a concerted effort towards their control has been ongoing. Many jurisdictions in North America have adopted an integrated pest management (IPM) approach to Varroa control, with the primary aim of maintaining mite levels below critical thresholds, above which there is a decreased likelihood for colony survival. Developing and optimizing IPM strategies is reliant on a comprehensive understanding of the biology, risk-factors, and distribution of the pest across the population to efficiently allocate resources and target interventions. Until now, the distribution of Varroa in Ontario has not been presented in the literature. The purpose of this thesis is to enhance the current state of Varroa surveillance across the province of Ontario by providing missing population-level context of the distribution of honey bee colonies and mites across space and time. Through geospatial interpolation of registered honey bee colonies, a province-wide population distribution map is presented, essential for standardizing future epidemiological studies, and permitting further insight into the implications of population density on colony health. Using spatial scan statistics and geostatistical modelling, a continuous depiction of the distribution of Varroa mite infestation intensities is developed and several regions of substantially increased risk are highlighted. Through time series analyses, a repeating seasonal pattern of provincial Varroa mite levels is described and evidence is presented to suggest an association between mite counts and weather variables at a 7-week lag interval. As a culminating project for this thesis, a practical information dashboard is developed for all members of the beekeeping community, to disseminate the key findings of these presented works, and enable, potentially, the future collection and analysis of improved quantities of data through citizen science. The results presented in this thesis offer valuable information for guiding future research and policy decisions regarding V. destructor in Ontario, while simultaneously demonstrating the methods available for the assessment of diseases in honey bees or other animal species.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".