Repeated freezing induces a trade-off between cryoprotection and egg production in the goldenrod gall fly,<i>Eurosta solidaginis</i>
Bibliographic record
Abstract
Internal ice formation leads to wholesale changes in ionic, osmotic and pH homeostasis, energy metabolism, and mechanical damage, across a small range of temperatures, and is thus an abiotic stressor that acts at a distinct, physiologically-relevant, threshold. Insects that experience repeated freeze-thaw cycles over winter will cross this stressor threshold many times over their lifespan. Here we examine the effect of repeatedly crossing the freezing threshold on short-term physiological parameters (metabolic reserves and cryoprotectant concentration) as well as long-term fitness-related performance (survival and egg production) in the freeze-tolerant goldenrod gall fly Eurosta solidaginis. We exposed overwintering prepupae to a series of low temperatures (-10, -15, or -20 °C) with increasing numbers of freezing events (3, 6, or 10) with differing recovery periods between events (1, 5, or 10 days). Repeated freezing increased sorbitol concentration by about 50% relative to a single freezing episode, and prompted prepupae to modify long chain triacylglycerols to acetylated triacylglycerols. Long-term, repeated freezing did not significantly reduce survival, but did reduce egg production by 9.8% relative to a single freezing event. Exposure temperature did not affect any of these measures, suggesting that threshold crossing events may be more important to fitness than the intensity of stress in E. solidaginis overwintering.
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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".