Larval nutrition affects life history traits in a capital breeding moth
Bibliographic record
Abstract
Fitness depends not only on resource uptake but also on the allocation of these resources to various life history functions. This study explores the life-history consequences of larval diet in terms not only of larval performance but also of adult body composition and reproductive traits in the forest tent caterpillar (Malacosoma disstria Hübner). Caterpillars were reared on their preferred tree host, trembling aspen (Populus tremuloides), or on one of three artificial foods: high protein:low carbohydrate, equal protein-to-carbohydrate ratio or low protein:high carbohydrate. Survivorship, larval development rate and adult body size were lowest on the carbohydrate-biased diet and similar on the protein-biased and equal-ratio diets. Fecundity increased with body size but did not otherwise differ between diets. Moths reared on the carbohydrate-biased diet allocated a lower proportion of their mass to the ovaries and more to somatic growth whereas those on equal-ratio and protein-biased diets allocated more to reproductive tissue and less to somatic tissue. These differences in allocation to reproduction arose from differences in the size of eggs, an index of offspring quality. No differences were found in lipid and protein content of female ovaries, accessory glands or somatic tissue, or of the whole body of male moths. The findings show that physiological processes regulate the composition of the different components of the adult body. Diet effects occur as differences in overall body size and in relative allocation to these components. Although lepidopterans can, to a large extent, compensate post-ingestively for nutritionally deficient diets, investment in reproduction vs somatic growth depends on the nutrients available.
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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".