Coastwide Stock Structure of Winter Flounder Using Nuclear DNA Analyses
Bibliographic record
Abstract
Abstract Many Winter Flounder Pseudopleuronectes americanus populations have declined dramatically. In U.S. waters, Winter Flounder are managed as three stocks: Gulf of Maine, southern New England–Mid‐Atlantic Bight, and Georges Bank. Historically, it was believed that the spawning of inshore stocks occurs exclusively within natal estuaries. Based on the supposition of estuary‐specific spawning, we hypothesized that Winter Flounder exhibit greater stock structure than predicted by the three‐stock model and, in fact, that they exhibit genetic differentiation at the level of individual estuaries. We tested this hypothesis by conducting microsatellite DNA analysis at 12 loci and single‐nucleotide polymorphism analysis at 4 loci on young‐of‐the year and adult Winter Flounder collected from 27 estuaries from Newfoundland to Delaware as well as from Georges Bank. We found highly significant coastwide genetic stock structure among Winter Flounder; however, there was little evidence of estuary‐specific structure. Pooled collections from north and south of Cape Cod were genetically distinct, as were many individual collections compared between these two regions. However, there was little genetic heterogeneity among estuarine collections within either of these major geographic regions. The two Canadian collections from the Miramichi River and Newfoundland were genetically distinct from those in the Gulf of Maine. Our collection from Georges Bank was marginally distinct from the inshore collections from north and south of Cape Cod. Overall, our genetic results support the three‐stock model used to manage Winter Flounder in U.S. waters and indicate the presence of at least two genetic stocks in Canadian waters (the Miramichi River in the Gulf of St. Lawrence and Passamaquoddy Bay in the Bay of Fundy). Furthermore, our data suggest that the spawning of Winter Flounder in nearshore coastal waters is more extensive than previously thought or that homing is weaker, contributing to the absence of genetic differentiation among populations from proximal estuaries.
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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 | 0.001 | 0.001 |
| 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".