Warming leads to opposite patterns in weight-at-age for young versus old age classes of Bering Sea walleye pollock
Bibliographic record
Abstract
The temperature–size rule predicts that climate warming will lead to faster growth rates for juvenile fishes but lower adult body size. Testing this prediction is central to understanding the effects of climate change on population dynamics. We use fisheries-independent data (1999–2019) to test predictions of age-specific climate effects on body size in eastern Bering Sea walleye pollock ( Gadus chalcogrammus). This stock supports one of the largest food fisheries in the world but is experiencing exceptionally rapid warming. Our results support the predictions that weight-at-age increases with temperature for young age classes (ages 1, 3, and 4) but decreases with temperature for old age classes (ages 7–15). Simultaneous demonstrations of larger juveniles and smaller adults with warming have thus far been rare, but pollock provide a striking example in a fish of exceptional ecological and commercial importance. The age-specific response to temperature was large enough (0.5–1 SD change in log weight-at-age) to have important implications for pollock management, which must estimate current and future weight-at-age to calculate allowable catch, and for the Bering Sea pollock 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 | 0.000 | 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 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".