Adaptive advantages of dietary mixing different‐aged foliage within conifers for a generalist defoliator
Bibliographic record
Abstract
Abstract Few herbivores are well adapted to feeding on all foliage age classes available and most have evolved traits that are attuned to the characteristics of either developing or mature foliage; however, recent evidence has shown a number of insect herbivores that may mix different‐aged foliage as a means of enhancing fitness. We carried out a series of laboratory and field experiments to investigate whether larvae of Asian gypsy moth [ L. umbrosa (Butler) = L. dispar hokkaidoensis Goldschmidt] ( Lepidoptera : Lymantriidae) engage in and benefit from foliage‐age dietary mixing in common conifer species that naturally occur in its native range of Hokkaido, Japan. In a laboratory experiment, early instar larvae were observed on both developing and mature foliage when both age classes were available; however, larval survival and weight were highest on hosts with developing foliage available (larch, fir, and pine), whereas all larvae died on spruce where only mature foliage was available. In contrast, laboratory and field experiments indicated that late‐instar larvae often consumed both developing and mature foliage on all conifer species studied, although there was general preference bias towards mature foliage. Field bioassays indicated that late‐instar larvae provided both foliage age classes (a ‘mixed’ diet) had similar performance to those provided only developing or mature foliage. Results of this study indicate that larvae obtain limited performance benefits from mixing different foliage age‐classes into their diet, other than perhaps the benefits accrued from having a broader resource pool available on a single host tree.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".