The effect of warmer winters on the demography of an outbreak insect is hidden by intraspecific competition
Bibliographic record
Abstract
Abstract Warmer climates are predicted to increase bark beetle outbreak frequency, severity, and range. Even in favorable climates, however, outbreaks can decelerate due to resource limitation, which necessitates the inclusion of competition for limited resources in analyses of climatic effects on populations. We evaluated several hypotheses of how climate impacts mountain pine beetle reproduction using an extensive 9‐year dataset, in which nearly 10,000 trees were sampled across a region of approximately 90,000 km 2 , that was recently invaded by the mountain pine beetle in Alberta, Canada. Our analysis supports the hypothesis of a positive effect of warmer winter temperatures on mountain pine beetle overwinter survival and provides evidence that the increasing trend in minimum winter temperatures over time in North America is an important driver of increased mountain pine beetle reproduction across the region. Although we demonstrate a consistent effect of warmer minimum winter temperatures on mountain pine beetle reproductive rates that is evident at the landscape and regional scales, this effect is overwhelmed by the effect of competition for resources within trees at the site level. Our results suggest that detection of the effects of a warming climate on bark beetle populations at small spatial scales may be difficult without accounting for negative density dependence due to competition for resources.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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 teacher head, 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".