Evidence supporting panmixia in Greenland halibut (<i>Reinhardtius hippoglossoides</i>) in the Northwest Atlantic
Bibliographic record
Abstract
Assessment of population structure is critical to the design and implementation of sound management and conservation strategies. However, population structure must be assessed using markers attuned to population genetic processes such as genetic drift and gene flow, which reflect actual levels of reproductive isolation among putative genetic clusters. This is critical for highly exploited, commercial species that form the backbone of regional and local economies. Here, we show extremely low levels of population genetic differentiation among Greenland halibut (Reinhardtius hippoglossoides) collected from throughout the Northwest Atlantic, which cannot be statistically differentiated from panmixia using 12 species-specific polymorphic microsatellite markers. In contrast, some previous studies have demonstrated significant differences among individuals collected from various parts of the species’ range using a variety of both genetic and nongenetic techniques. In accordance with other reports and consistent with the species’ life history, we demonstrate that the most parsimonious explanation reconciling observed patterns is a repeated high degree of local differentiation of new recruits and colonizers originating from a common gene pool. Such a scenario has important conservation implications in terms of devising more appropriate strategies balancing species persistence and replenishment with sustainable resource use.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".