Dendrochronological reconstruction of arborvitae leafminer (<i>Argyresthia</i> spp.) outbreaks on northern white-cedar (<i>Thuja occidentalis</i>) in Maine, USA
Bibliographic record
Abstract
Although northern white-cedar ( Thuja occidentalis; henceforth cedar) is thought to have few insect pests, arborvitae leafminers (primarily Argyresthia thuiella) have been known to cause leaf necrosis. Yet, historical evidence for leafminer outbreaks is limited. We combined leafminer larval surveys conducted between 1950 and 1992 with tree-ring analyses from eight cedar stands to reconstruct a history of leafminer outbreaks in Maine, USA. Our tree-ring data show distinctive 2- to 3-year growth reductions that we attribute to leafminers. Several such growth reductions correspond to peak leafminer larval abundances, providing evidence that the reductions are reliable indicators of leafminer activity. Outbreak severity within a site was unrelated to cedar abundance. Outbreak periods thus identified (beginning ca. 1919, 1937, 1950, 1962, mid-1970s, but not at all sites) suggest that leafminer damage may have been more prevalent (albeit patchy) than previously thought. This historical information is relevant given current outbreaks in Maine and elsewhere.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| 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".