Population dynamics and seasonal incidence of aphids on mustard under changing climate
Bibliographic record
Abstract
Roughly 38% of Canada’s canola-mustard output is lost each year to insect pests, with aphids ranking as the single most damaging group across the semi-arid cropping belt of southern Alberta. This research examined the population dynamics and seasonal incidence of aphid species on mustard (Brassica juncea L.) under the changing climatic conditions of southern Alberta. Field observations were carried out at the Prairie Dryland Agricultural College research farm, Lethbridge, during the growing seasons of 2022-23 and 2023-24. Weekly counts were recorded on ten randomly tagged plants per replication across three cultivars (AC Vulcan, Andante, and Cutlass). Lipaphis erysimi was the dominant species, accounting for 62.4% of total aphid counts, followed by Myzus persicae (18.7%) and Brevicoryne brassicae (11.3%). Peak population coincided with the first fortnight of July in both seasons (67.4 and 74.8 aphids per 10 cm apical shoot, respectively). Multiple regression analysis showed that maximum temperature (r = 0.78) and morning relative humidity (r = −0.45) were the strongest weather correlates. A year-on-year increase of 11.0% in peak aphid density was observed, pointing to a climate-driven intensification of pest pressure that warrants revised threshold-based management calendars.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".