Insect Immunity Varies Idiosyncratically During Overwintering
Bibliographic record
Abstract
Overwintering insects face multiple stressors, including pathogen and parasite pressures that shift with seasons. However, we know little of how the insect immune system fluctuates with season, particularly in the overwintering period. To understand how immune activity changes across autumn, winter, and spring, we tracked immune activity of three temperate insects that overwinter as larvae: a weevil (Curculio sp., Coleoptera), gallfly (Eurosta solidaginis, Diptera), and larvae of the lepidopteran Pyrrharctia isabella. We measured baseline circulating hemocyte numbers, phenoloxidase activity, and humoral antimicrobial activity, as well as survival of fungal infection and melanization response at 12°C and 25°C to capture any potential plasticity in thermal performance. In Curculio sp. and E. solidaginis, hemocyte concentrations remained unchanged across seasons and antimicrobial activity against Gram-positive bacteria was lowest in autumn; however, Curculio sp. were less likely to survive fungal infection in autumn, whereas E. solidaginis were less likely to survive infection during the winter. Furthermore, hemocyte concentrations and antimicrobial activity decreased in P. isabella overwintering beneath snow cover. Overall, seasonal changes in activity were largely species dependent, thus it may be difficult to create generalizable predictions about the effects of a changing climate on seasonal immune activity in insects. However, we suggest that the relationship between the response to multiple stressors (e.g., cold and pathogens) drives changes in immune activity, and that understanding the physiology underlying these relationships will inform our predictions of the effects of environmental change on insect overwintering success.
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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".