The influence of temperature on Pacific hake co‐occurrence with euphausiids in the <scp>California Current Ecosystem</scp>
Bibliographic record
Abstract
Abstract Understanding the influence of ocean conditions on predator–prey relationships can provide insight for ecosystem‐based fisheries management. Pacific hake ( Merluccius productus ) are abundant and commercially important groundfish in the California Current Ecosystem (CCE) that consume euphausiids (krill) as a major prey item. We used data from the biennial joint U.S.‐Canada Integrated Ecosystem & Acoustic Trawl Survey for Pacific hake (2007–2019, n = 8 surveys) to quantify co‐occurrence of age 2+ hake with krill in relation to bottom depth, continental shelf break location, surface chlorophyll‐a, and 100‐m temperature. Vertical distributions of hake varied among years and were not correlated to krill depth. Hake hotspots occurred primarily off the Oregon coast and near Cape Mendocino, while most krill hotspots occurred in the northern CCE. The probability of co‐occurrence was greatest during cool ocean conditions (100‐m temperature 1°C below average), averaging 41.0% and extending throughout most of the CCE. During warm ocean conditions (100‐m temperature 1°C above average), predicted co‐occurrence averaged 17.0% and was concentrated near Cape Mendocino. These results indicate that hake‐krill co‐occurrence is a function of predator and prey spatial distributions and overall krill abundance. Furthermore, temperature influences hake‐krill co‐occurrence and may explain some of the variation in hake growth and recruitment to the fishery.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".