Climatic effects on ice‐jam flooding of the Peace‐Athabasca Delta
Bibliographic record
Abstract
Abstract The Peace‐Athabasca Delta (PAD) in northern Alberta is one of the world's largest inland freshwater deltas, home to large populations of waterfowl, muskrat, beaver, and free‐ranging wood bison. In recent decades, a paucity of ice‐jam flooding in the lower Peace River has resulted in prolonged dry periods and considerable reduction in the area covered by lakes and ponds that provide habitat for aquatic life in the PAD region. Building on previous work that has identified the salient hydro‐climatic factors, the frequency of ice‐jam floods is considered under ‘present’ (1961–1990) and ‘future’ (2070–2099) climatic conditions. The latter are determined using temperature and precipitation output from the Canadian Climate Centre's second‐generation Global Climate Model (CGCM2) for two different greenhouse‐gas/sulphate emission scenarios. The analysis indicates that the ice season is likely to be reduced by 2–4 weeks, while future ice covers would be slightly thinner than they are at present. More importantly, a large part of the Peace River basin is expected to experience frequent and sustained mid‐winter thaws, leading to significant melt and depleted snowpacks in the spring. Using an empirical relationship between ice‐jam flood occurrence and size of the spring snowpack, a severe reduction in the frequency of ice‐jam flooding is predicted under both future‐climate scenarios that were considered. In turn, this trend is likely to accelerate the loss of aquatic habitat in the PAD region. Implications for potential mitigation and adaptation strategies are discussed. Copyright © 2006 Crown in the right of Canada. Published by John Wiley & Sons, Ltd.
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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".