Disjunction between canola distribution and the genetic structure of its recently described pest, the canola flower midge (Contarinia brassicola)
Bibliographic record
Abstract
Population genomics is a useful tool in the integrated pest management toolbox for elucidating population dynamics, demography, and histories of invasion. However, next-generation sequencing approaches can be hampered by low DNA input from small organisms, such as insect pests. Here, we use a restriction-site associated DNA sequencing approach combined with whole-genome amplification to assess genomic population structure of a newly described pest of canola, the diminutive canola flower midge, Contarinia brassicola. We find that whole-genome amplification prior to library preparation caused a reduction in the overall number of loci sequenced and an increase in overall sequencing depth but had no discernable impact on genotyping consistency for population genetic analysis. Clustering analyses recovered little geographic structure across the main canola production region, but differentiated several geographically disparate populations at edges of the agricultural zone. Given a lack of alternative hypotheses for this pattern, we suggest these data support alternative hosts for this species and thus our canola-centric view of this midge as a pest has limited our understanding of its biology. These results speak to the need for increased surveying effort across multiple habitats and other potential hosts within Brassicaceae, to elucidate both our ecological and evolutionary knowledge of this species as well as potential management implications.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.002 | 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".