Density-dependent development in pest and domestic Drosophilidae species
Bibliographic record
Abstract
The capacity to lay eggs inside healthy fruits rather than on decaying plant matter differentiates insect fruit pests from domestic species. This niche differentiation has been previously proposed to be an adaptation to avoid competition. We hypothesize that pest species will be more strongly affected by competition. We compare the impact of larvae density on fitness traits between Drosophila pests ( Drosophila suzukii (Matsumura, 1931); Zaprionus indianus Gupta, 1970) and domestic species ( Drosophila immigrans Sturtevant, 1921; Drosophila melanogaster Meigen, 1830). We assessed the effect of crowding on adult emergence and development time. Viability decreased gradually with density for D. immigrans and D. suzukii, while for D. melanogaster and Z. indianus it remained high. Development time increased with density; this was stronger on Z. indianus and D. immigrans than on D. suzukii, which had a moderate increase, and D. melanogaster, which did not change. Contrary to expectations, the distinct patterns observed were not related to each species' domestic or pest lifestyle. In fact, patterns consistent with either scramble or contest type of competition were observed on both pest and domestic species, respectively. These findings challenge prior beliefs regarding competition effects among Drosophila pest species and provide information relevant to integrated pest management.
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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 | 0.000 |
| 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".