Is it time to rethink the use of hatcheries to produce Pacific salmon in the Strait of Georgia?
Bibliographic record
Abstract
All Pacific salmon hatcheries produce salmon, but the original hypothesis in the 1970s was that hatchery-produced salmon would fill unused ocean production capacity and the Canadian commercial catch of about 70,000 MT would double to about 140,000 MT by 2005. In 2019 and 2020 the averaged total Canadian commercial Pacific salmon catch for these two years was 5,237 MT. The science is clear that there was not unused ocean carrying capacity and the original hypothesis that more juveniles needed to be added to the ocean to produce more salmon can be rejected. It is the capacity of the ocean in recent years that was regulating abundance and not a shortage of smolts or fry. We found in a recent 9-year study that a 51% reduction in hatchery released coho salmon into the Strait of Georgia did not reduce the number juvenile hatchery coho salmon in the fall of the first ocean year showing that the trend in the percent of hatchery and wild juveniles after four months in the ocean did not change over the 9-years. One explanation is that the hatchery-reared coho salmon had adapted to climate related changes in the Strait of Georgia ecosystem at a critical survival time in the first months in the ocean, perhaps even better than wild salmon. Our example is for coho salmon but it is possible that the example extends to other species of salmon. The message is that, 1- we need to understand better the mechanisms that regulate coho salmon in the ocean and 2 – we need to rethink how we use hatcheries.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".