Bibliographic record
Abstract
Temperate, polar and alpine insects generally do not feed over winter and hence must manage their energy stores to fuel their metabolism over winter and to meet the energetic demands of development and reproduction in the spring. In this Review, we give an overview of the accumulation, use and conservation of fat reserves in overwintering insects and discuss the ways insects modify fats to facilitate their selective consumption or conservation. Many insects are in diapause and have depressed metabolic rates over winter; together with low temperatures, this means that lipid stores are likely to be consumed predominantly in the autumn and spring, when temperatures are higher but insects remain dormant. Although there is ample evidence for a shift towards less-saturated lipids in overwintering insects, switches between the use of carbohydrate and lipid stores during winter have not been well-explored. Insects usually accumulate cryoprotectants over winter, and the resulting increase in haemolymph viscosity is likely to reduce lipid transport. For freeze-tolerant insects (which withstand internal ice), we speculate that impaired oxygen delivery limits lipid oxidation when frozen. Acetylated triacylglycerols remain liquid at low temperatures and interact with water molecules, providing intriguing possibilities for a role in cryoprotection. Similarly, antifreeze glycolipids may play an important role in structuring water and ice during overwintering. We also touch on the uncertain role of non-esterified fatty acids in insect overwintering. In conclusion, lipids are an important component of insect overwintering energetics, but there remain many uncertainties ripe for detailed exploration.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".