Insights into the northward shift of Pacific cod in warming Bering Sea waters from pop-up satellite archival tags
Bibliographic record
Abstract
The summertime distribution of Pacific cod in the Bering Sea shifted dramatically northward into the Northern Bering Sea (NBS) during 2017–2019 in conjunction with unprecedented ocean warming. In 2019, we tagged 38 NBS Pacific cod with pop-up satellite archival tags during summer foraging to characterize seasonal migration to winter spawning locations. Geolocation results for 31 Pacific cod indicate that tagged Pacific cod moved out of the NBS shelf area beginning in November ahead of oncoming winter sea ice. Most tagged fish (77% geolocation probability) moved to traditional spawning areas in the Eastern Bering Sea during the peak spawning period, but some crossed international and internal management boundaries by moving into Russian waters and the Gulf of Alaska (16% and 7% geolocation probability, respectively). Our results demonstrate that Pacific cod are tightly coupled to seasonal environmental changes and suggest that recent northward shifts in summertime distributions are tied to warm-water expansion of foraging habitat. Our findings underscore the need for adaptive management strategies to address the challenges of shifting fish distributions under changing environmental conditions.
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 | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".