Investigation of Fishing and Climate Effects on the Community Size Spectra of Eastern Bering Sea Fish
Bibliographic record
Abstract
Abstract The eastern Bering Sea (EBS) is a highly productive subarctic marine ecosystem that is exposed to considerable climate variability and is noted for conservative management of its fishery resources. The community size spectrum (CSS; relationship between animal abundance and size) of fish captured in EBS shelf bottom trawl surveys was examined for evidence of change over time and fishing and climate effects. The slope (indicative of fish size) and height (indicative of ecosystem productivity, or essentially fish abundance) of the CSS can change due to changes in fishing intensity and climate variability. Linear trends were not observed in EBS groundfish size or abundance during 1982–2006. The abundance of large‐sized fish increased in 2001–2006 relative to 1982–2000. Observed changes in CSS height partially corroborated evidence for decreased productivity of the main fishery target species since the late 1990s, which may have been due to changes in relative species composition. In addition, abundance and size composition of nontarget fish decreased during 1982–2006, possibly related to changes in water temperature. In contrast, however, the size and productivity of fish that were primarily bycatch species increased during 1982–2006. Unlike in other ecosystems, changes in CSS slopes and heights for the EBS were not related to exploitation rates. Changes in the abundance of fish in areas that were normally occupied by cold bottom water (northwest inner and middle shelf) may have been related to the effects of temperature on fish distribution.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".