Multivariate determination of Atlantic herring population health in a large marine ecosystem
Bibliographic record
Abstract
Abstract Atlantic herring are among the most harvested marine fish species globally and are of extraordinary ecological and economic importance. Within the Scotian Shelf and Bay of Fundy management zone (NAFO Division 4WX), herring support one of the largest fisheries in Canada, yet the conservation status of the stock is currently unclear. We use field observations, stock assessments, and published studies to evaluate the long-term (1965–2016) status, or health, of 4WX Atlantic herring based on 33 indicators that serve as proxies for the ecological dynamics across the larval, juvenile, and adult stages. Sixteen indicators that showed evidence of significant and synchronous temporal changes were integrated to produce a standardized series of herring population health. This multivariate index exhibited a gradual, long-term decline punctuated by a more rapid decline between 1980 and 2005. Following normalization, future trajectories of herring spawning stock biomass (SSB) over this period were best forecast by the average weight of herring (r2 = 0.63; lag = 6 years) and indicated that SSB would remain low over the next 6 years. Our study suggests that integrating factors related to population health can provide deeper insight in situations where individual series are uncertain and can complement existing assessment approaches.
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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 | 0.001 | 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 | 0.000 | 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".