Density Dependence of Egg Recruitment and Moth Dispersal in Spruce Budworms
Bibliographic record
Abstract
Egg recruitment quantifies the relative importance of realized fecundity and migration rates in the population dynamics of highly mobile insects. We develop here a formal context upon which to base the measurement and interpretation of egg recruitment in population dynamics of eastern and western spruce budworms, two geographically separated species that share a very similar ecology. Under most circumstances, per capita egg recruitment rates in these budworms are higher in low-density populations and lower in high-density populations, relative to the regional mean: Low-density populations are nearly always migration sinks for gravid moths, and dense populations nearly always sources. The slope of this relationship, measured on a log scale, is negatively correlated with migration rate, and ranges between 0 and −1. The steeper the slope, the more marked net migration. Using our western spruce budworm observations, we found strong evidence of density-dependent emigration in budworms, so migration is not simply a random perturbation in the lagged, density-dependent stochastic process leading to budworm outbreaks. It is itself statistically and biologically density-dependent. Therefore, moth migration is a synchronizing factor and a spread mechanism that is essential to understanding the development and expansion of spruce budworm outbreaks at regional scales in the boreal forests of North America.
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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 | 0.002 |
| 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".