Rearing History, Larval Density, and Larval Developmental Stage Affect Volatile- and Light-Mediated Diel Hiding Behavior in Mythimna unipuncta
Bibliographic record
Abstract
Abstract Our previous study has shown that plant volatiles and light jointly influence the diel hiding behavior of Mythimna unipuncta larvae using the third instars of the laboratory colony. Here, we investigated the effect of rearing history, larval density, and developmental stage on the diel hiding behavior of M. unipuncta larvae under controlled laboratory conditions. Third-instar larvae from a newly established, field-derived colony exhibited more frequent hiding behavior in the presence of maize volatiles, regardless of the light regime, whereas third-instar larvae from a long-term laboratory colony (> 5 years) showed no change in response to volatiles. Larval density during the second instar also altered responsiveness; low-density cohorts from the new colony exhibited increased hiding in response to volatiles, whereas high-density cohorts exhibited a decrease. Furthermore, developmental stage also influenced behavior. Second instars from the new colony consistently exhibited increased hiding when exposed to volatiles, regardless of light conditions. In contrast, under light condition, the fifth–sixth instars hid more with volatiles than without. Under dark condition, however, they hid less with volatiles than without. Our results demonstrate that diel hiding behavior in M. unipuncta larvae is shaped not only by immediate environmental cues such as light and plant volatiles but also by larval rearing history, social context (density) and the developmental states. This study provides novel insights into the behavioral adaptations underlying diel activity patterns in herbivorous insects.
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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) | 0.002 | 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".