Stocking for rehabilitation of burbot in the Kootenai River, Idaho, USA and British Columbia, Canada
Bibliographic record
Abstract
The burbot Lota lota is widespread globally, but the population in the Kootenai River, Idaho and British Columbia, Canada is at risk of extirpation because of habitat changes caused by operation of Libby Dam in Montana, 100 km upstream of the border with Idaho. We developed an age-structured simulation model to estimate the number of age-0 burbot (fall fingerlings) to stock annually to rebuild the population in the Kootenai River. We found with the estimated annual survival of about 38% that 110 000–900 000 age-0 burbot per year will need to be stocked to rebuild the burbot population in the Kootenai River in 25 years, depending on the rehabilitation goal, either 5500 age-4 burbot and older as an interim goal or 17 000 age-4 and older burbot as an ultimate goal (longer than 250 mm). If survival is higher at 61% then the stocking numbers could range from 12 000 to 35 000 age-0 fingerlings per year. After stocked burbot in the population reach age 4, discharge from Libby Dam must be regulated to provide suitable temperatures and flows during the burbot pre-spawning and spawning periods, to enable the population to reproduce and return to self-sustaining status. Our findings will serve as an example for similar efforts to restore depleted burbot populations elsewhere in the world.
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".