Population studies of tree-defoliating insects in Canada: a century in review
Bibliographic record
Abstract
Abstract Our review highlights research during the past century focussed on the population ecology of outbreak-prone insect defoliators in Canadian forests. Based on reports from national and provincial surveys that began in the 1930s, there have been at least 106 insect defoliators reported to outbreak, most of which are native Lepidoptera, Hymenoptera (sawflies), or Coleoptera (in order of frequency from most to least). Studies comparing life-history traits of outbreak versus non-outbreak species to better understand why certain species are more outbreak-prone indicate several traits especially common among outbreak species, including egg clustering and aggregative larval feeding. There have been at least 50 time-series studies examining the spatiotemporal population behaviour of 12 major defoliator species. These studies provide evidence for both regular periodicity and spatial synchrony of outbreaks for most major species. Life-table studies seeking to understand the agents causing populations to fluctuate have been carried out for at least seven outbreak species, with the majority identifying natural enemies (usually parasitoids) as the major driver of outbreak collapse. Our review concludes with several case studies highlighting the impact and historical underpinnings of population studies for major defoliator species and a discussion of potential avenues for future research.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.011 | 0.020 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".