Effect of humidity and temperature on hatching success, time to hatch, and lifespan of the first-instar larvae of the hemlock looper (Lepidoptera: Geometridae)
Bibliographic record
Abstract
Abstract Climate change affects not only temperatures but also rainfall patterns, which can either accentuate or mitigate the effects of warming on water stress in terrestrial insects. Water stress is more likely to affect eggs and larvae due to their small size. Hemlock looper (Lepidoptera: Geometridae) overwinters as eggs, and first-instar larvae must move to settle on host trees in the spring. Their survival depends both on their energy and water reserves that remain after overwintering and on the abiotic conditions present each spring. The effects of humidity (40, 60, and 80%) on the hatching success, time to hatch, and lifespan of unfed first-instar hemlock looper larvae were assessed at two temperatures, at 10 °C and at 22 °C. Lower humidity levels reduced hatching success and increased time to hatch, suggesting that humidity modulates development. On the other hand, higher temperatures reduced hatching success and time to hatch. The survival probability of unfed first-instar larvae was not influenced by ambient humidity but was longer for larvae from eggs reared at high humidity and 10 °C, suggesting that the physiological state of larvae at the time of hatching influences their survival. The ecological significance of these results and how they can influence our management tools are discussed.
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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".