Inverse regional responses to climate change and fishing intensity by the recreational rockfish (<i>Sebastes</i> spp.) fishery in California
Bibliographic record
Abstract
The interactive effects of ocean climate and fishing pressure on nearshore rockfishes (Sebastes spp.) were examined using historical commercial passenger fishing vessel catch records from California. Principal component analysis was used to characterize the dominant patterns in catch per unit effort (CPUE) over time (19571999) and space (10′ latitude × 10′ longitude blocks). Ocean climate explained 60% of the variation in CPUE and revealed opposite responses in northern and southern California. In warm El Niño years, CPUE was 4.2 times higher in the north and 1.8 times lower in the south. CPUE responded similarly to low-frequency climate shifts by increasing in the north and decreasing in the south after 19761977. Four geographic regions responded as discrete units to environmental forcing and fishing intensity: North, Central, South, and Channel Islands. Over time, annual fish landings declined sharply in the South, with fishing effort remaining stationary and high relative to that in the other regions. In the North, landings and fishing effort remained tightly coupled, with effort an order of magnitude lower than in the South. These findings support a management strategy for nearshore rockfishes in California based on regional responses to ocean climate and fishing intensity.
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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 | 0.001 | 0.001 |
| 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".