The relationship between long-term foliar decline assessments and annual growth of sugar maple in Ontario, Canada.
Bibliographic record
Abstract
This thesis presents an investigation of the relationship between visual signs of foliar decline, as represented by a long-term observational index, and annual radial growth of sugar maple (Acer saccharum Marsh.) in unmanaged forests in Ontario, Canada. Dendrochronological records from 24 sites across central and southern Ontario were examined for signs of declining growth, with associated visual decline assessments from 1990-2011 examined for predictive or reactive evidence of observed growth patterns. Foliar decline was found to be moderately predictive of future growth decline, showing correlations 2-3 years in advance of radial growth declines in 46% of plots. In contrast, 25% of sites also showed 2 or more years of correlation between increasing foliar damage and increased growth, although the mechanism responsible for this is unclear. Climate models showed that variation in radial growth was significantly correlated to climate in most study sites. When the effects of climate on growth were removed, the foliar decline / radial growth relationship changed and generally became less predictive. The relationship of growth patterns, foliar condition and site conditions showed no clear pattern across all study sites, suggesting site-specific interactions play an important role in growth dynamics. Overall, sugar maple populations in Ontario show declining growth over the past several decades, although rates of decline vary. The analyses conducted in this study suggest visual assessments of foliar health may be most useful as a predictive management tool once a baseline sensitivity of each plot to foliar condition has been established.
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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 | 0.001 |
| 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 | 0.001 | 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".