Influence of temperature on historic and future population fitness of the western spruce budworm, <i>Choristoneura occidentalis</i>
Bibliographic record
Abstract
Climate change affects the geographic range and outbreak behavior of forest insects. Both the range and dynamics of insect populations are linked to physiological responses to abiotic conditions and trophic interactions via their effects on individual fitness. We develop a process-based simulation model of population fitness for the western spruce budworm, Choristoneura occidentalis (Freeman) to examine the effects of temperature on historical range and observed outbreak behavior in the complex topography western North America. Model predictions are consistent with observed changes in the distribution and frequency of this insect’s outbreaks over the past 100 years. These changing patterns are the result of several direct and indirect responses of the insect to temperature. Overwintering survival is negatively affected by warming and determines its southern and lower-elevation limit. Ability to complete its life cycle before killing frosts limits its range to the north and at higher elevations. Interactions affecting synchrony between the insect’s feeding life stages and host foliage development also determines fitness and will increase the area favoring fitness of western spruce budworm in the future, especially in western Canada where host trees extend much farther north than the insect currently does.
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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 | 0.001 |
| 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 | 0.001 | 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".