Flea beetle (Coleoptera: Chrysomelidae) species in canola (Brassicaceae) on the northern Great Plains of North America
Bibliographic record
Abstract
Abstract Flea beetle (Coleoptera: Chrysomelidae) species and numbers were determined from yellow sticky traps (n=11 180) set out in canola (Brassica Linnaeus, Brassicaceae) fields at 300 site years and 15 ecoregions across the Canadian Prairie provinces in each spring of 2007–2011 and in North Dakota, United States of America in 2010–2011. Peak numbers and relative species abundance varied with year, site, and ecoregion. Phyllotreta striolata (Fabricius) was most common in northern ecoregions, whereas Phyllotreta cruciferae (Goeze) dominated nearer the 49th parallel. The proportion of P. striolata in northern areas increased dramatically compared with surveys in the 1970s. Phyllotreta striolata displaced Psylliodes punctulata Melsheimer as the most common flea beetle in the Peace River Lowlands, displaced P. cruciferae as the most common flea beetle in the Aspen Parkland of central Alberta, Canada, and increased in proportion in central Saskatchewan and much of Manitoba, Canada. Once rare in southern ecoregions, P. striolata was found there in increasing numbers. Temperature was the most consistent weather parameter to predict occurrence of both P. cruciferae and P. striolata. Although P. striolata became more numerous over years in four of seven principal ecoregions, P. cruciferae remained the predominant species on traps with the highest numbers of flea beetles.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".