Dynamic changes in <i>Wolbachia</i> infection over a single generation of <i>Drosophila suzukii</i>, across a wide range of resource availability
Bibliographic record
Abstract
Abstract Wolbachia bacteria are maternally inherited symbionts that commonly infect terrestrial arthropods. Many Wolbachia reach high frequencies in their hosts by manipulating their reproduction, for example by causing reproductive incompatibilities between infected male and uninfected female hosts. However, not all strains manipulate reproduction, and a key unresolved question is how these non‐manipulative Wolbachia persist in their hosts, often at intermediate to high frequencies. One such strain, wSuz, infects the invasive fruit pest Drosophila suzukii, spotted‐wing drosophila. Here, we tested the hypothesis that wSuz infection provides a competitive benefit when resources are limited. Over the course of one season, we established population cages with varying amounts of food in a semi‐field setting and seeded them with a 50:50 mixture of flies with and without Wolbachia. We predicted that Wolbachia‐infected individuals should have higher survival and faster development than their uninfected counterparts when there was little available food. We found that while food availability strongly impacted fly fitness, there was no difference in development times or survival between Wolbachia‐infected and uninfected flies. Interestingly, however, Wolbachia infection frequencies changed dramatically, with infections either increasing or decreasing by as much as 30% in a single generation, suggesting the possibility of unidentified factors shaping Wolbachia infection over the course of the season.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".