<i>Populus tremuloides</i> stands continue to deteriorate after drought-incited sudden aspen decline
Bibliographic record
Abstract
Reports of forest damage have increased with the frequency of climatic extremes, but longer term impacts of such events on population dynamics of forest trees are generally unknown. Incited by the turn-of-the-century drought, sudden aspen decline (SAD) damaged 535 000 ha of Populus tremuloides Michx. in the Southern Rockies ecoregion of western North America. Although spread of the disease stopped in about 2009, most of the affected stands continued to deteriorate. Remeasurement of plots in southwestern Colorado showed that, since the peak of the epidemic, live basal area in sick plots decreased by an additional 28% to only 38% of that in healthy plots. Sick plots had much more recent damage than healthy plots, with almost three times as much recently dead basal area, over twice the density of recently dead trees, and almost four times as much recent crown loss. The important contributing agents in SAD were still active in sick stands in 2013. Density of small regeneration showed opposite trends, increasing in healthy plots and decreasing in sick plots. Timely regeneration treatments may be needed in some such stands to facilitate recovery. In addition to acute damage from climatic extremes, long-term decline diseases like SAD will likely be a common signature of forest damage from climate change.
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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 | 0.001 | 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".