Temporal and Spatial Variations in Microclimate Influence the Larval Foraging Behaviors and Performance of a Conifer-Feeding Sawfly
Bibliographic record
Abstract
Herbivorous insects are often exposed to broad temporal and spatial variations in microclimate conditions within their host plants and have adapted a variety of behaviors, such as avoidance or basking, to either offset or benefit from such variation. Field experiments were carried out to investigate the influence of daily and intratree variations in microclimate on the behaviors (feeding, resting, dispersal, and hiding) and associated performance of late-instar larvae of the yellowheaded spruce sawfly, Pikonema alaskensis (Rohwer) (Hymenoptera: Tenthredinidae) within crowns of 1.25-1.5 m tall black spruce (Picea mariana [Miller] Britton Sterns Poggenburg); late instars feed on developing shoots of young spruce and are often exposed to microclimatic extremes with unknown effects on performance. Larvae fed diurnally from just after dawn (0800 h) until dusk (2000 h) and rested throughout the night, with brief periods of dispersal occurring in the morning and evening. Neither larval behavior nor abiotic conditions differed significantly between the upper and lower crowns of trees. Temperature, humidity, and solar insolation all explained >90% of variation in feeding; however, sunrise and sunset were the most likely cues influencing diurnal behavior. Most larvae (94%) fed on the bottom, shaded side of shoots, and field experiments indicated that this behavior is adaptive with respect to microclimate, probably reducing hygrothermal stress. Thus, behavioral adaptations by P. alaskensis to daily and within-shoot microclimatic variation may reduce the risk of hygrothermal stress during dispersal or feeding, while still allowing larvae to feed on the preferred and highly nutritious upper crown foliage of young spruce.
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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".