Using Mitochondrial and Nuclear Sequence Data for Disentangling Population Structure in Complex Pest Species: A Case Study with Dermanyssus gallinae
Bibliographic record
Abstract
Among global changes induced by human activities, association of breakdown of geographical barriers and impoverishered biodiversity of agroecosystems may have a strong evolutionary impact on pest species. As a consequence of trade networks' expansion, secondary contacts between incipient species, if hybrid incompatibility is not yet reached, may result in hybrid swarms, even more when empty niches are available as usual in crop fields and farms. By providing important sources of genetic novelty for organisms to adapt in changing environments, hybridization may be strongly involved in the emergence of invasive populations. Because national and international trade networks offered multiple hybridization opportunities during the previous and current centuries, population structure of many pest species is expected to be the most intricate and its inference often blurred when using fast-evolving markers. Here we show that mito-nuclear sequence datasets may be the most helpful in disentangling successive layers of admixture in the composition of pest populations. As a model we used D. gallinae s. l., a mesostigmatid mite complex of two species primarily parasitizing birds, namely D. gallinae L1 and D. gallinae s. str. The latter is a pest species, considered invading layer farms in Brazil. The structure of the pest as represented by isolates from both wild and domestic birds, from European (with a focus on France), Australian and Brazilian farms, revealed past hybridization events and very recent contact between deeply divergent lineages. The role of wild birds in the dissemination of mites appears to be null in European and Australian farms, but not in Brazilian ones. In French farms, some recent secondary contact is obviously consecutive to trade flows. Scenarios of populations' history were established, showing five different combinations of more or less dramatic bottlenecks and founder events, nearly interspecific hybridizations and recent population mixing within D. gallinae s. str.
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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 | 0.001 | 0.003 |
| 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 | 0.001 |
| 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".