Life-cycle modeling reveals high recovery potential of at-risk wild Chinook salmon via improved migrant survival
Bibliographic record
Abstract
Chinook salmon ( Oncorhynchus tshawytscha) in the Columbia River basin are threatened by anthropogenic changes to migratory corridors, estuaries, and natal habitats. Streams provide spatially heterogeneous natal habitats essential for salmon spawning and rearing life stages. We fit a statistical state-space model to salmon populations in Idaho's Middle Fork Salmon River (MFSR) to assess spatial variation in natal productivity and population growth. Our model integrated multiple long-term data sets to estimate variation in per-capita smolt production and smolt-to-adult (SAR) survival. Smolt production varied across stream segments, averaging 104.48 female smolts per spawning female, while SARs averaged 0.74%. Chinook salmon population growth rates exceeded replacement in 17% of segments (4 of 23). By increasing SARs to 1.8% (near the lower bound of Columbia River basin recovery targets), we predict that all 23 MFSR segments will yield positive population growth rates at contemporary (very low) spawner densities. Our analysis suggests that for Snake River basin populations within high-quality natal habitats, SAR improvements will elevate salmon population growth rates and enhance restoration of at-risk wild Chinook salmon.
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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 | 0.000 | 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".