Dryas iulia (Lepidoptera, Nymphalidae) larval preference and performance on four sympatric Passiflora hosts
Bibliographic record
Abstract
Host plant quality is determinant for herbivorous insects performance and survival. While on larval stages, insects select their host plants based on factors such as leaf nitrogen and water content, digestibility, and defences. Of great interest is the coevolutionary relationship between the Heliconiini insects and the Passiflora plants. In this study we experimentally evaluated Dryas iulia (Nymphalidae) larval preference to four sympatric Passiflora (Passifloraceae) and subsequently, the larval performance on the two most consumed species. We tested the hypothesis that D. iulia larvae prefer the Passiflora species with higher nutritional quality and lower defence, which supports the greatest larval performance. Dryas iulia larvae preferred P. misera (60.5% leaf consumption) over P. pohlii (28.9%), P. suberosa (15.5%), and P. edulis (not consumed). Passiflora misera presented the highest N concentration, third in water content, second in tector trichomes, and no glandular trichomes (only P. suberosa did). Nitrogen best explained D. iulia larvae leaf consumption; which further explains the greatest larval performance in P. misera than in P. suberosa: i.e. higher survival (23.1%), conversion efficiency of ingested food (32.8%), relative growth rate (14.8%), heavier pupae (15.2%), and lower relative consumption rate (13.8%). This study creates the opportunity to further investigate the Heliconiini-Passiflora system and showed that D. iulia larvae can assess and choose the host plant (even among sympatric species) that supports the greatest performance.
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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".