Evidence of density- and size-dependent mortality in hatchery-reared juvenile white sturgeon (Acipenser transmontanus) in the Kootenai River
Bibliographic record
Abstract
We evaluated effects of stocking level and size-at-release on survival rates of hatchery-reared juvenile white sturgeon ( Acipenser transmontanus ) in the Kootenai River using Cormack–Jolly–Seber and related models implemented in Program MARK. A total of 119 768 marked and unmarked hatchery juveniles were released from 1992 to 2006, of which 2938 passive integrated transponder (PIT)-tagged fish were subsequently recaptured. Annual survival rates of marked groups ranged from 0.01 to 0.84 (mean = 0.45) during the first year at large, from 0.48 to 1.0 (mean = 0.84) in the second year, and averaged 1.0 during all subsequent years. First year survival rates declined substantially in recent years, particularly for small fish (<25 cm fork length). Approximately 59% of the variation in first year survival was explained by a negative relationship with estimated juvenile abundance (linear regression, P < 0.01). Length-at-release of individuals explained a substantial proportion of the within-year variation in survival during the first year at large. Our results provide strong evidence of density- and size-dependent mortality in hatchery-reared juvenile white sturgeon in the Kootenai River. Management actions that prioritize the release of fewer, larger-sized fish will likely improve first year survival rates and subsequent recruitment to the spawning-age population.
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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 | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".