Wild host fruit–niche diversity of <i>Drosophila suzukii</i> in lowbush blueberry agroecosystems in Saguenay-Lac-Saint-Jean, Québec, Canada
Bibliographic record
Abstract
Abstract Understanding movements of Drosophila suzukii (Diptera: Drosophilidae) into berry fruit crops from wild-fruit hosts in borders of semi-natural agroecosystems, such as lowbush blueberry, is important to determining harvesting time and managing wild-fruit diversity near crops. This study aimed to inventory the wild-fruit hosts associated with lowbush blueberry (Ericaceae) production in Québec, Canada, near the limits of lowbush blueberry’s eastern North American range. We also tested the hypothesis that fruit traits of berry fruit species present in or near lowbush blueberry fields might explain field infestation levels. Flies of both sexes emerged from five wild-fruit species in 2016, to which six more species were added in 2017. The most productive wild-fruit hosts were Cornus canadensis (Cornaceae) and Aralia hispida (Araliaceae) (> 100 emerged flies/100 g of fruit) in 2016, to which Prunus pensylvanica (Rosaceae) and Rubus idaeus (Rosaceae) were added in 2017. Among nine variables considered in statistical modelling (fruit size, sugar content, and reflected colour bands) and taxonomic family (a nominal variable), none could explain field infestation levels over two years. In lab tests comparing fruits of Cornus canadensis, a common weed within fields, and lowbush blueberries, mated D. suzukii females laid twice as many eggs on blueberries, but both species were equally suitable for development.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".