Subpolar gyre and temperature drive boreal fish abundance in Greenland waters
Bibliographic record
Abstract
Abstract As result of ocean warming, marine boreal species have shifted their distribution poleward, with increases in abundance at higher latitudes, and declines in abundance at lower latitudes. A key to predict future changes in fish communities is to understand how fish stocks respond to climate variability. Scattered field observations in the first half of the 20th century suggested that boreal fish may coherently invade Greenland waters when temperatures rise, but this hypothesis has remained untested. Therefore, we studied how local temperature variability and the dynamics of the subpolar gyre, a large‐scale driver of oceanic conditions in the North Atlantic, affect abundance of boreal fishes in a region that sharply defines their lower thermal boundary. We analysed information from demersal trawl surveys from 1981 to 2017, for species distributed from shallow shelf to depths of 1,500 m, collected at over 10,000 stations along ~3,000 km of Greenland. Our results show that local temperature and variability of Labrador and Irminger Sea water in the subpolar gyre region drive interdecadal variability of boreal fish abundance in Greenland waters. Although temperature fluctuations were higher in shallow than deep regions, fish abundance changed as quickly in great depths as in shallow depths. This link between physics and biology provides an opportunity for prediction of future trends, which is of utility in Greenland, where fisheries constitute more than 90% of the national export value.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 teacher head, 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".