Abundance Trends of Pacific Salmon During a Quarter Century of <scp>ESA</scp> Protection
Bibliographic record
Abstract
ABSTRACT Between 1989 and 2007, 28 Distinct Population Segments (DPS) of Pacific salmon ( Oncorhynchus spp.) spawning in rivers in California and the Pacific Northwest (Oregon, Washington, Idaho) were listed (protected) under the US Endangered Species Act (ESA). In the roughly 25 years since then, considerable efforts have been made to recover these populations, but no DPS has increased sufficiently to be delisted. We evaluated abundance trends of ESA‐listed Pacific salmon DPS, along with DPS that were not ESA‐listed. Our goal was to evaluate whether protected DPS increased in abundance during the period of protection (nominally 1995–2020 in our study), either in absolute terms or relative to the unprotected DPS. A majority of the protected DPS had increasing abundance trends over this time period, and protected populations had higher median trends than non‐protected populations of the same species. Geographically, populations in the Pacific Northwest had higher median trends than those in California. Among species of protected populations, Chinook salmon ( O. tshawytscha ), chum salmon ( O. keta ) and sockeye salmon ( O. nerka ) had higher median trends than coho salmon ( O. kisutch ) and steelhead (anadromous O. mykiss ). For most DPS (listed and unlisted), trends in harvest rates and hatchery releases were relatively stable during the same time period, whereas trends in indicators related to freshwater and marine climate were generally negative for salmon. Our results suggest that salmon recovery actions may have helped to stabilise and increase protected DPS, but most remain far below their recovery goals.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".