Long-term impact of a leaf miner outbreak on the performance of quaking aspen
Bibliographic record
Abstract
The aspen leaf miner, Phyllocnistis populiella Cham., has caused widespread and severe damage to aspen in the boreal forests of western North America for over a decade. We suppressed P. populiella on individual small aspen ramets using insecticide at two sites near Fairbanks, Alaska, annually for 7 years and compared plant performance with controls. Insecticide treatment successfully reduced leaf damage by P. populiella during most years and had little effect on herbivory by externally feeding invertebrates. By the end of the study, control ramets had suffered a reduction in height and girth relative to treated ramets and to the original, pretreatment size. Control ramets produced smaller leaves during some years and, after 7 years, produced fewer total shoots and leaves than ramets sprayed with insecticide. Treatment did not affect mortality, but at the warmer of the two sites, ramets sustaining ambient levels of leaf mining were significantly more likely to die back to basal sprouts than those treated with insecticide. We conclude that a decade of P. populiella outbreak has caused strongly negative effects on aspen development and the production of aboveground tissues.
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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 | 0.000 | 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".