Interaction of foliage and larval age influences preference and performance of a geometrid caterpillar
Bibliographic record
Abstract
Abstract In two recent studies it was reported that feeding on foliage of multiple age classes can improve insect fitness, but it was not determined whether the increase in fitness was due to larvae obtaining a more balanced diet (the balanced-diet hypothesis) or to a difference in the nutritional requirements between young and old larvae (the ontogenetic hypothesis). To test these two hypotheses, we examined the foraging behaviour and performance of young (second or third to fourth instar) and old (third or fourth to fifth instar) larvae of the pale-winged gray moth, Iridopsis ephyraria (Walker) (Lepidoptera: Geometridae), on different-aged foliage of eastern hemlock, Tsuga canadensis (L.) Carrière (Pinaceae), during an outbreak in southwestern Nova Scotia. Defoliation attributed to I. ephyraria was highest on current-year foliage and gradually declined with foliage age. Young larvae were only observed feeding on current-year shoots but old larvae fed on foliage of all ages. When forced to feed on foliage of specific ages in manipulative field studies, survival rates of young and old larvae were highest on current-year and old (≥1 year old) foliage, respectively. However, both young and old larvae had higher survival rates when provided with access to foliage of all age classes than when they were forced to feed on only young or old foliage. Thus, this study supports both the balanced-diet and ontogenetic hypotheses.
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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".