Some like it hot: the effects of climate change on reproduction, immune function and disease resistance in the cricket<i>Gryllus texensis</i>
Bibliographic record
Abstract
In many parts of the world, climate change is increasing the frequency and severity of heat waves. How do heat waves impact short-lived poikilotherms such as insects? In the cricket, Gryllus texensis, 6 days of elevated temperatures (i.e. 7°C above the average field temperature and 5°C above their preferred temperature) resulted in increased egg laying, faster egg development and greater mass gain. The increased temperature also increased activity of phenoloxidase and lysozyme-like enzymes, two immune-related enzymes, and enhanced resistance to the Gram-negative bacterium Serratia marcescens. When given a sublethal S. marcescens infection, G. texensis maintained increased reproductive output at the elevated temperature (33°C). These data suggest that heat waves could result in more numerous, disease resistant, crickets. However, resistance to the Gram-positive bacterium, Bacillus cereus was lower at temperatures above or below the average field temperature (26°C). A sublethal infection with B. cereus reduced egg laying at all temperatures and suppressed the increase in egg laying induced by higher temperatures. These results suggest that for some species-pathogen interactions, increased temperatures can induce trade-offs between reproduction and disease resistance. This result may partly explain why G. texensis prefers temperatures lower than those that produce maximal reproductive output and enhanced immune function.
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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".