Redefining spatial population structure of winter flounder (<i>Pseudopleuronectes americanus</i>): implications for stock assessment and management
Bibliographic record
Abstract
The southern New England – mid-Atlantic (SNE–MA) stock of winter flounder (Pseudopleuronectes americanus) collapsed in the 1990s without discernable recovery to date. Owing to the lack of recovery, consideration of population subcomponents, which are currently ignored in fisheries stock structure definitions, may be necessary for rebuilding. We used the otolith chemistry tracer manganese–calcium ratios (Mn/Ca) to estimate inshore- versus ocean-nursery contributions of 77.3%/22.7% in SNE–MA, 15.7%/84.3% in the Gulf of Maine (GOM), and 60.0%/40.0% in Georges Bank (GB). In addition, we used strontium–calcium ratios (Sr/Ca) to estimate migratory- and resident-contingent membership of nursery-classified fish. Across all stocks, 30.2% of fish were classified as bay residents, 25.2% as bay migrants, 25.8% as ocean residents, and 18.8% as ocean migrants. Finally, model selection indicated that both nursery-specific and contingent-specific growth models were more appropriate than a common model. Nursery-specific models exhibited increasing deviations in length with age. Contingent-specific model reflected moderate differences at the youngest ages but convergence at older ages. These findings are informative for the population structure and migration ecology of winter flounder; however, simulation is required to determine whether partial migration and substock structure are necessary inputs for sustainable fisheries management.
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 | 0.002 | 0.003 |
| 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 | 0.001 |
| 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".