The Ontario Hardwood Forest Health Survey: 1986 – 1998
Bibliographic record
Abstract
In 1986 the Ontario government established a long-term program to monitor hardwood forest health. The program was initiated in response to widespread reports of forest decline in North America and Europe and the implication that air pollution, specifically acidic deposition, was a causal factor. Visual symptoms of branch dieback, leaf colour, and leaf size, have been quantitatively evaluated on about 15 000 trees in 110 plots. This report summarizes the results of the first 12 years (1986 to 1998). Over that time period, relative to the 1986 baseline year, 84% of the plots have improved in condition, 12% have not changed, and 4% have deteriorated. Generally, hardwood forest health in the province appears to be quite good; severe decline is limited and very site-specific, occurring only in selected northern regions on acid-sensitive and/or marginal sites, or in southern areas on very shallow soils. Northern forests growing on coarse-textured shallow soils underlain by precambrian rock are in poorer health relative to southern forests growing on finer-textured, deeper soil over limestone. On soils sensitive to acidic deposition, tree health deteriorated as soil pH and exchangeable aluminum levels increased. Key words: forest health, forest decline, decline index, Ontario, hardwood, air pollution, acid rain
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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 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".