Escapement, harvest, and unknown loss of radio-tagged adult salmonids in the Columbia River Snake River hydrosystem
Bibliographic record
Abstract
Accurate estimates of escapement by adult anadromous salmonids are difficult, especially in large, multistock river systems. We used radiotelemetry and a fishery reward program to calculate escapement, harvest, and unaccounted for loss rates for 10 498 adult chinook salmon (Oncorhynchus tshawytscha) and 5324 steelhead (Oncorhynchus mykiss) during six return years in the Columbia River basin. Mean annual escapements to spawning sites, hatcheries, or the upper bounds of the monitored hydrosystem were 73.4% (springsummer chinook salmon), 61.3% (fall chinook salmon), and 62.6% (steelhead). Mean reported harvest rates were 8.7% (springsummer chinook), 22.0% (fall chinook), and 15.1% (steelhead) within the mainstem hydrosystem and 5.9%, 3.4%, and 5.7%, respectively, in lower hydrosystem tributaries. On average, 12%17% of each run had unknown fates in the mainstem hydrosystem. Escapement, harvest, and loss varied significantly between runs and years, within runs between known-origin subbasin stocks, and between interdam river reaches. Multiyear quantitative assessments like this can reduce uncertainty, clarify inter- and intra-annual variability, and help managers better evaluate fisheries, identify conservation priorities, and help protect evolutionarily significant populations.
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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 | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".