Sources of coaster brook trout (Salvelinus fontinalis) revealed by genomic analysis of brook trout populations along Minnesota’s shoreline with Lake Superior
Bibliographic record
Abstract
Knowledge of population-level relationships and how these relationships pertain to different life history forms is critical to developing effective management plans for native trout, char, and salmon. In the Lake Superior basin, identifying effective restoration strategies for coaster brook trout (Salvelinus fontinalis), a lake-inhabiting form of brook trout, is hampered by limited information on genetic connectivity and source-sink dynamics among brook trout populations. Here, we infer these relationships by surveying 8,178 single nucleotide polymorphisms in 234 brook trout from seven rivers along the Minnesota shoreline with Lake Superior, including from reaches above and below natural waterfalls that prevent upstream movement. We identified well-differentiated above-barrier populations that supply brook trout to below-barrier reaches. We also compared within-river brook trout to 26 coaster brook trout from Lake Superior. We identified at least four source populations for these coaster brook trout, three of which were located within rivers. Additionally, we estimated NE for within-river populations and detected a decline across recent generations, with the most recent estimates approaching critical thresholds. Finally, comparisons with 94 domestic brook trout representing nine hatchery strains revealed a lack of domestic introgression into wild populations, demonstrating the importance of natural reproduction to population persistence. Our results offer novel insights into sources of coaster brook trout and highlight the role of within-river populations in supporting the coaster life history. Management efforts focused on instream restoration may be more important to rehabilitating coaster brook trout than previously thought and are urgently needed given the population-level conservation status reported here.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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".