Early instar mortality of a forest pest caterpillar: which mortality sources increase during an outbreak crash?
Bibliographic record
Abstract
Abstract Collapses of insect pest outbreaks are often attributed to delayed density dependence of predation. The forest tent caterpillar, Malacosoma disstria Hübner (Lepidoptera: Lasiocampidae), is an outbreaking pest species defoliating mixed wood boreal forests in eastern Canada. This species presents periodic population dynamics with peaks every 10 years and outbreaks lasting 1–3 years impacting the health of its host tree. We asked about the relative importance of various sources of early‐instar mortality during and after the crash of an outbreak, testing for density dependence. We used a triad set‐up of complete predator exclusion, partial exclusion, and free colonies to distinguish between intrinsic mortality (caused by, e.g., pathogens) and mortality caused by flighted and walking natural enemies, and compared defoliated outbreak sites with control sites. Overall, survival was lowest in the free colonies and increased with partial and complete predator exclusion. Survival was also higher in control than in outbreak sites and higher in the final year of the outbreak than in the following year. We observed no changes in mortality from walking enemies, but an increase in intrinsic mortality and mortality from flighted enemies. in the year following the outbreak. This increase is consistent with density dependence of these mortality sources, but its occurrence in the control sites as well was unexpected. These findings show that mortality from flighted natural enemies and intrinsic source increases after the outbreak, but do not contribute to the population crash. However, they help maintain low endemic levels between outbreaks.
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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 | 0.001 | 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".