D<b>ecreased fire frequency and increased water levels affect riparian forest dynamics in southwestern boreal Quebec, Canada</b>
Bibliographic record
Abstract
The relative importance of fire and flooding on the population dynamics of eastern white-cedar ( Thuja occidentalis L.) and black ash ( Fraxinus nigra Marsh.) was evaluated in eight old-growth riparian stands of southwestern boreal Quebec, Canada. Rising water levels and decreasing fire frequency since the end of the Little Ice Age (ca. 1850) were expected to have favoured an inland migration of the riparian forest fringe, with the flood-tolerant black ash colonizing the lower parts of the shore terraces and eastern white-cedar the upper parts. Black ash was found to be restricted to the riparian zone (<200 cm elevation), whereas eastern white-cedar trees did not occur below 100 cm above lake level. Gaps of postfire eastern white-cedar recruitment were noted in stands exposed to riparian disturbances, whereas relatively continuous recruitment occurred at protected sites. Black ash, more tolerant to flooding and ice push, invaded the shore terrace sites left vacant by eastern white-cedar. The riparian forest fringe surrounding Lake Duparquet is currently migrating upland and this trend is expected to continue as water levels continue to increase and fire frequency continues to decrease during the 21st century.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".