Curator of Botany and Earth History
Bibliographic record
Abstract
Predicted atmospheric change, mainly climate change, will have profound effects on the biodiversity of Canadian forests. Predictions derived from forest models, responses of spe-cies and ecosystems related to modern ecological characteristics and paleoecological stud-ies suggest large-scale, wide-ranging changes from the biome to physiological levels. Paleoecological analogues in B.C. and other parts of Canada reveal that major changes must be expected in forest composition, range, structure and ecological processes. In B.C., past warmer and drier climates supported a different forest pattern, including forest types with no modern analogue. This produced dramatically different disturbance regimes, specifically more fires, and affected tree growth rates. The relationship of forests with non-forest habitats, especially wetlands and grasslands was different suggesting implications for wildlife biodiversity. British Columbia's Forest Practices Code prescribes guidelines for biodiversity objectives but ignores the issue of atmospheric change. This omission may result from a lack of understanding of the profound potential effects of atmospheric change on forest biodiversity in the next harvest cycle and lack of mechanisms to assess impacts and develop manage-ment strategies for specific sites. An example of a simple paleoecological assessment method involving pollen ratios is proposed.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.283 | 0.188 |
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".