Spatial synchrony of the two‐year cycle budworm outbreaks in central British Columbia, Canada
Bibliographic record
Abstract
Outbreaks of forest defoliating insects are usually synchronized over a large spatial scale. Observed records of past outbreaks are usually short and incomplete, therefore long proxy data are useful for better understanding of the spatial synchrony. In this study, we developed tree‐ring proxy records of two‐year cycle spruce budworm ( Choristoneura biennis Freeman) outbreaks in central British Columbia, Canada, and examined the spatial patterns of past outbreaks. This budworm is a major defoliating insect of the interior spruce ( Picea engelmannii Parry× P. glauca Moench) and subalpine fir ( Abies lasiocarpa [Hook.] Nutt.) forests in the Prince George Region of British Columbia. Four outbreaks occurred in relatively close synchrony over the entire region in the period 1880–1999, however, the initiation year, the intensity and extent of outbreaks varied spatially and from one outbreak to another. In some instances, the occurrence of outbreaks was restricted to only one area. The general synchrony of outbreaks suggested that a large‐scale extrinsic factor, such as weather, was at play. However, the imperfect synchrony of outbreaks suggested that local stand characteristics, such as canopy structure, composition of tree species and host plant quality, probably played a major role in preconditioning outbreaks. Dispersal might play a role in synchronizing outbreaks, but the extent to which it contributed to the synchrony was limited in this mountainous region.
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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 | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".