Dataset for Trans-generational effects on diapause and life-history-traits of an aphid parasitoid
Bibliographic record
Abstract
Dataset for the following article: Transgenerational effects act on a wide range of insects’ life-history traits and can be involved in the control of developmental plasticity, such as diapause expression. Decrease in or total loss of winter diapause expression recently observed in some species could arise from inhibiting maternal effects. In this study, we explored transgenerational effects on diapause expression and traits in one commercial and one Canadian field strain of the aphid parasitoid Aphidius ervi. These strains were reared under short photoperiod (8:16 h LD) and low temperature (14 °C) conditions over two generations. Diapause levels, developmental times, physiological and morphological traits were measured. Diapause levels increased after one generation in the Canadian field but not in the commercial strain. For both strains, the second generation took longer to develop than the first one. Tibia length and wing surface decreased over generations while fat content increased. A crossed-generations experiment focusing on the industrial parasitoid strain showed that offspring from mothers reared at 14 °C took longer to develop, were heavier, taller with wider wings and with more fat reserves than those from mothers reared at 20 °C (8:16 h LD). No effect of the mother rearing conditions was shown on diapause expression. Additionally to direct plasticity of the offspring, results suggest transgenerational plasticity effects on diapause expression, development time, and on the values of life-history traits. We demonstrated that populations showing low diapause levels may recover higher levels through transgenerational plasticity in response to diapause-induction cues, provided that environmental conditions are reaching the induction-thresholds specific to each population. Transgenerational plasticity is thus important to consider when evaluating how insects adapt to changing environments.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.114 | 0.041 |
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".