Syrphid diversity in sweet alyssum flower strips in Quebec’s lettuce fields: molecular identification and delimitation of the Sphaerophoria complex
Bibliographic record
Abstract
[1]¿p#1 Lettuce (Lactuca sativa L.; Asteraceae) is an economically significant agricultural product in Canada, with 70% of commercial production in peatlands (Histosols) in southern Quebec. Insecticide application has been the primary method for managing lettuce pests in Quebec however more sustainable strategies are needed to control lettuce pests effectively. In this context, conservation biological control is a highly promising alternative, involving the cultivation of flowering strips within the agricultural ecosystem to attract and support natural enemies. The objective of this study was to evaluate the potential of alyssum (Lobularia maritima (L.) Desv.; Brassicaceae) in attracting syrphids (Diptera: Syrphidae), some of which are voracious predators of lettuce pests during their larval stage. A total of 1,934 specimens of 16 species were collected from annual flowering plants grown in three different lettuce farms in Quebec. The most abundant species was Toxomerus marginatus (Say), accounting for approximately 70% of the specimens. The second and third most abundant were Sphaerophoria philanthus Meigen and Allograpta obliqua (Say), corresponding to nearly 10.3% and 4.6% of the samples, respectively. All other species constituted less than 4% each. A group of 82 female specimens, initially identified as belonging to the Sphaerophoria philanthus/asymmetrica/abbreviata species complex, underwent Cytochrome Oxidase I (COI) DNA sequence-based delimitation analyses, which suggested the presence of three molecular operational taxonomic units (MOTUs). Fourteen of the 16 identified species or MOTU are aphid predators at the larval stage. Our findings suggest that alyssum flowers can successfully attract natural aphid predators in lettuce fields in Quebec. This approach may help mitigate lettuce pest-related problems and decrease the dependence on insecticides in lettuce crops, promoting more sustainable pest management practices.
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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 | 0.002 | 0.001 |
| 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".