Defining the window of opportunity for feeding initiation by second-instar spruce budworm larvae
Bibliographic record
Abstract
Establishing feeding sites is critical for the survival of neonate Lepidoptera larvae. Rapid foliar quality changes during leaf expansion create a narrow window of opportunity for establishment of early-spring feeders. We examined the effect of phenological synchrony between black spruce (Picea mariana (Mill.) Britton, Sterns & Poggenb.) and balsam fir (Abies balsamea (L.) Mill.) budbreak and spruce budworm (Choristoneura fumiferana (Clemens)) emergence on the feeding behaviour of young larvae and on overall larval growth and survival under laboratory conditions. We correlated these variables with bud development and foliar toughness during the growing season. Our results show that early-emerging second-instar larvae were unable to feed on either black spruce or balsam fir buds; budworm on balsam fir mined old foliage and exhibited good survival and performance, but those on black spruce remained on the foliar surface and suffered high mortality and low growth. In the second later-emerging cohort, bud feeding gradually increased on black spruce whereas it was already the predominant behaviour on balsam fir, and no differences in performance were observed between host species. Thus, black spruce budbreak constitutes a strict window of opportunity, since larvae are often unable to mine the old foliage. Our results suggest that mechanical toughness could be the obstacle preventing young larvae from mining old black spruce needles. Our findings confirm the importance of second-instar ecology in spruce budworm, suggesting that, if climate warming eventually results in an improvement in phenological synchrony between spruce budworm and black spruce, larval survival may increase.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".