A synthesis of the coast‐wide decline in survival of West Coast Chinook Salmon (<i>Oncorhynchus tshawytscha,</i>Salmonidae)
Bibliographic record
Abstract
Abstract We collated smolt‐to‐adult return rate (SAR) data for Chinook salmon from all available regions of the Pacific coast of North America to examine the large‐scale patterns of salmon survival. For consistency, our analyses primarily used coded wire tag‐based (CWT) SAR estimates. Survival collapsed over the past half century by roughly a factor of three to ca. 1% for many regions. Within the Columbia River, the SARs of Snake River populations, often singled out as exemplars of poor survival, are unexceptional and in fact higher than estimates reported from many other regions of the west coast lacking dams. Given the seemingly congruent decline in SARs to similar levels, the notion that contemporary survival is driven primarily by broader oceanic factors rather than local factors should be considered. Ambitious Columbia River rebuilding targets may be unachievable because other regions with nearly pristine freshwater conditions, such as SE Alaska and northern BC, also largely fail to reach these levels. Passive integrated transponder (PIT) tag‐based SAR estimates available for Columbia River Basin populations are generally consistent with CWT findings; however, PIT tag‐based SARs are not adjusted for harvest which compromises their intended use because harvest rates are large and variable. More attention is needed on how SARs should be quantified and how rebuilding targets are defined. We call for a systematic review by funding agencies to assess consistency and comparability of the SAR data generated and to further assess the implications of survival falling to similar levels in most regions of the west coast.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".