Biocomplexity in a demersal exploited fish, white hake (<i>Urophycis tenuis</i>): depth-related structure and inadequacy of current management approaches
Bibliographic record
Abstract
Understanding the factors generating patterns of genetic diversity is critical to implementing robust conservation and management strategies for exploited marine species. Yet, often too little is known about population structure to properly tailor management schemes. Here we report evidence of substantial population structure in white hake ( Urophycis tenuis ) in the Northwest Atlantic, perhaps among the highest levels of population structure exhibited by a highly exploited, widely dispersed, long-lived marine fish. We show that depth plays a role in this extensive and temporally stable structure, which does not conform to previously established fisheries management units. Three genetically distinguishable populations were identified, where all straddle several management divisions and two (Southern Gulf of St. Lawrence and Scotian Shelf) overlap in their range, coexisting within a single division. The most highly exploited population in the Southern Gulf of St. Lawrence was also the most isolated and likely the smallest (genetically effective). This work shows that conservation and management priorities must include population structure and stability in establishing effective species recovery strategies.
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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 | 0.000 | 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".