Growth and dieback of aspen forests in northwestern Alberta, Canada, in relation to climate and insects
Bibliographic record
Abstract
Trembling aspen (Populus tremuloides Michx.) is the most important deciduous tree in the Canadian boreal forest, with >1000 Tg of carbon stored in the aboveground biomass of this species. Since the early 1990s, aspen dieback has been noted over parts of the southern boreal forest and aspen parkland in western Canada. In this study, tree-ring analysis and forest health assessments were conducted in 18 aspen stands near Grande Prairie, Alta., to examine causes of reduced growth and dieback. Defoliation histories were reconstructed based on light-colored ("white") tree rings and records of past insect outbreaks. The results indicated that several factors contributed to the observed dieback. Defoliation by forest tent caterpillar (Malacosoma disstria Hbn.) and drought in the 1960s and 1980s led to reduced growth and predisposed some stands to secondary damage by wood-boring insects and fungal pathogens. Thawfreeze events during a period (19841993) of unusually light snow cover in late winter may have also contributed to the observed dieback. Under global change, the severity of these stressors may increase, which would pose a serious concern for the future health, productivity, and carbon sequestration of aspen forests in the 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".