Response of trembling aspen to partial cutting and subsequent forest tent caterpillar defoliation in a boreal mixedwood stand in northeastern Ontario, Canada
Bibliographic record
Abstract
The growth response and mortality of trembling aspen ( Populus tremuloides Michx.) were monitored 1, 3, 5, and 11 years after partially harvesting an aspen-dominated mature mixedwood stand in northeastern Ontario. Both diameter and height of aspen trees responded positively to harvesting. However, 3 years after harvest, the growth rates of residual aspen were severely suppressed by 3 years of moderate to severe defoliation by forest tent caterpillar ( Malacosoma disstria Hbn.). The diameter growth of surviving trees almost recovered, but due to continuous crown dieback in the 6 years after defoliation ceased, height growth did not. Over the 11 years after harvest, 70% of residual aspen died, with 80% of that mortality occurring in the 6 years after defoliation. Trees in the lower canopy and in the partial cut had higher mortality rates than those in the upper canopy and in the uncut control. Increased mortality at the individual tree level was generally associated with greater foliage loss. Aspen growth and mortality were associated with defoliation levels, particularly for trees in partial cut treatments. Partial cutting and crown class strongly influenced the response of aspen trees to insect defoliation and should be considered when selecting residual trees during harvesting.
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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 | 0.001 | 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".