Impact of extreme and fluctuating temperatures on aphid–parasitoid dynamics
Bibliographic record
Abstract
Climate change is predicted to increase the occurrence of extreme temperature events. We constructed a stage‐structured Leslie matrix model with intra‐generational dynamics to explore the impact of extreme and fluctuating temperatures on host–parasitoid dynamics. We varied three temperature parameters to generate a range of temperature regimes that varied in their daily maximum temperatures, the number of warmer‐than‐average days and the autocorrelation of those warmer‐than‐average days. All three temperature parameters influenced host–parasitoid dynamics. Increasing the frequency of warmer than average days and the degree of autocorrelation only exerted significant impacts on host– parasitoid dynamics when daily maximum temperatures were sufficient to produce temperature‐dependent mortality. The effects of increasing autocorrelation of daily temperatures were dependent on the maximum daily temperatures and the frequency of warmer than average days. When daily maximum temperatures were severely warm, but the frequency of those severely warm days was low, increasing autocorrelation increased the probability that the aphids and parasitoids will persist, but when the frequency of severely warm days is increased, increasing autocorrelation decreases the probability that the populations will persist. These temperature phenomena exert significant effects on host–parasitoid dynamics in addition to those effects produced by changes in mean temperatures and warrant further investigation at the community level.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".