Temporally stable, weak genetic structuring in brackish water northern pike (<i>Esox lucius</i>) in the Baltic Sea indicates a contrasting divergence pattern relative to freshwater populations
Bibliographic record
Abstract
Understanding spatiotemporal population genetic patterns is important for conservation management of ecologically and socioeconomically important species. This is particularly so in species-poor environments such as the brackish Baltic Sea. We examined over 600 northern pike (Esox lucius), a coastal predator and treasured sport fish, collected over major parts of the Baltic Sea coastline. We found low genetic divergence among populations, indicating a contrasting genetic structure of brackish water coastal spawners compared with previous reports on anadromous Baltic pike migrating up freshwater streams for spawning. A pattern of genetic isolation by distance either over shortest waterway or primarily along the mainland coast with islands as stepping stones suggested that gene flow is primarily taking place among neighboring populations, possibly with some migration over open water. Temporal data showed a stable genetic structure over a decade. Within a single sampling year, however, spatial divergence was larger during spawning than feeding season, indicating increased mixing of populations during the feeding season. Management should assure connectivity among brackish spawning grounds and large population sizes at identified core areas.
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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 | 0.000 |
| 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".