Cold tolerance and winter survival of seasonally‐acclimatised second‐instar larvae of the spruce budworm, <i>Choristoneura fumiferana</i>
Bibliographic record
Abstract
Abstract Field‐acclimatised spruce budworm larvae, Choristoneura fumiferana , supercool to as low as −41.6°C in winter months. Yet the extent to which they can withstand exposures to temperatures slightly above their supercooling point has never been investigated. In both January and February 2018, we tested various combinations of sub‐zero temperatures (−37 to −42°C) and exposure durations (0.75–12 h) to estimate the combinations of temperature and exposure durations required to kill half the population (LTT 50 ). At −37 or −38°C, the estimated emergence probability was about 0.80 at all exposure durations. In contrast, the LTT 50 was reached after 11.4 h at −39°C, 9.4 h at −40°C, and 3 h at −41°C. A temperature of −42°C was fatal to most larvae. During the winters of 2017, 2018 and 2019, survival experiments were conducted at three latitudes (46–48°N) in Québec. Regardless of the year or latitude, none of the daily minimum temperatures recorded in January or February were cold enough to reach the LTT 50 . However, the sudden drops in temperature that occurred after the winter thaw of March and in early December 2018 were likely responsible for the low proportions of emerged larvae observed. Hence, despite the high capacity of spruce budworm larvae to withstand very low sub‐zero temperatures in winter months, they remain highly vulnerable to cold spells during their early diapause or post‐diapause development. Such climatic disturbances deserve more attention, as they may increase under climate change.
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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".