Seven decades of growth and environmental response in a <i>Sebastes norvegicus</i> otolith biochronology from the Barents Sea
Bibliographic record
Abstract
Abstract Warming trends in the Arctic are affecting the structure and functioning of marine ecosystems with implications for fisheries productivity. Long-term biological records are necessary to establish baseline ranges of variability and responses to environmental change, yet time series that span multiple decades are scarce. To address these issues in the Barents Sea, we combined crossdating techniques from the field of dendrochronology and linear mixed-effect modeling to develop a 67-y biochronology spanning 1952–2019 from the otolith growth-increment widths of golden redfish, Sebastes norvegicus. We compared annual growth anomalies to ocean temperatures and lower-trophic indicators, finding that growth was positively correlated to winter (Jan–Mar) bottom and surface temperatures, but did not relate to available indicators of primary productivity or Calanus spp. abundance. Additionally, females grew more rapidly than males, and fish farther to the east grew more rapidly relative to those captured to the west. Strongly positive correlations (r > 0.6) between mean population growth and gridded sea surface temperatures spanned nearly 10 degrees of latitude and twenty-five degrees of longitude, including nursery grounds in the Norwegian Sea. The study demonstrates how the dating controls of crossdating can be combined with the variance-partitioning strengths of mixed-modeling approaches to reveal climate sensitivities in long-lived fish. Furthermore, it reveals a positive effect of ocean temperature on annual growth, which may be due to the effects of warmer winters.
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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 | 0.000 |
| 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".