Streamflow response to clear‐cut logging on British Columbia's Okanagan Plateau
Bibliographic record
Abstract
The Upper Penticton Creek watershed experiment has collected 28 years of streamflow data from 2 small snow‐dominated watersheds on the Okanagan Plateau of British Columbia, where the effects of timber harvesting on streamflow regime are of broad concern. We apply 3 empirical analysis techniques to these data to evaluate changes in streamflow regime following clear‐cut logging of 47% of the 241 Creek watershed, with the adjacent 240 Creek watershed serving as an unlogged control. While logging had only a small effect on annual yield (5% increase), the results of all 3 analysis techniques confirmed a dramatic change in the timing and magnitude of April through June streamflow. A paired watershed analysis showed that during the first 7 years post‐logging, average April and May water yield increased by 29% and 19%, respectively, while June and July water yield decreased by 23% and 17%, respectively. This pattern of change was confirmed by significant increases in standardised April–May monthly total water yield. Changes in the daily flow duration curves for each month also show a 67% increase in daily yields exceeded ≤10% of the time in April and a 15% increase in May. Daily yields exceeded ≤10% of the time decreased by 24% in June and 17% in July. These streamflow shifts increase the risk of channel destabilization and damage to aquatic habitat during the snowmelt season, and water shortages in the Okanagan region early in the irrigation season (June through July).
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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 | 0.000 | 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".