Genetic Population Structure among Source Populations for Coaster Brook Trout in Nipigon Bay, Lake Superior
Bibliographic record
Abstract
Abstract Populations of coaster brook trout Salvelinus fontinalis, a potadromous ecotype endemic to Lake Superior, have declined precipitously over the past 150 years. This study quantified the relatedness and genetic structure of remnant coaster and river‐resident brook trout within Nipigon Bay using microsatellite DNA markers. Individual assignment tests confirmed that coaster brook trout are a life history variant of brook trout derived from populations in tributary habitats, rather than a genetically distinct subspecies or evolutionarily significant unit. Furthermore, coasters appear to act as vectors for gene flow among riverine populations, providing genetic connectivity among allopatric tributaries. Molecular data indicated substantial gene flow among several below‐barrier populations, whereas other tributaries contained separate, largely discrete populations. Isolated above‐barrier populations showed the greatest interpopulation differentiation, with limited downstream gene flow observed within tributaries. The relative contributions of the sampled tributary populations to the coasters in Nipigon Bay were highly variable among rivers, indicating that management of source river populations will be critical for the effective conservation and restoration of coaster brook trout within Lake Superior.
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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 | 0.000 |
| 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".