Genetic diversity, admixture, and hatchery influence in Brook Trout (<i>Salvelinus fontinalis</i>) throughout western New York State
Bibliographic record
Abstract
Abstract Although Brook Trout are distributed across most of eastern North America, population numbers have declined in many regions due to habitat loss, climate change, and competition with non‐native species. In New York State, Brook Trout habitat has been substantially reduced, with many areas showing complete extirpation of Brook Trout populations, predominantly in the western portion of the state. Small, fragmented populations are at risk of genetic diversity loss, inbreeding depression, and reduced fitness, leading to a greater potential for local extirpation. Genetic monitoring is a practical tool that can facilitate further conservation‐decision making regarding small populations. In this study, we used 12 microsatellite loci to examine 3,436 sampled Brook Trout, representing 75 sites from the Allegheny, Erie/Niagara, Genesee, Oswego, Lake Ontario, and Susquehanna drainage basins throughout western New York State. Three Brook Trout hatchery strains were also genetically characterized to evaluate the degree of hatchery introgression between wild populations and hatchery strains stocked in the region. Overall, estimates of genetic diversity varied widely: Allelic richness ranged from 2.23 to 7.485, and expected heterozygosity ranged from 0.402 to 0.766. As observed for Brook Trout in other regions, we found a high degree of genetic differentiation among populations, with all comparisons except one showing significant F ST values. Hatchery introgression was found to be minimal, with estimates ranging from 1.96% to 3.10% of wild individuals exhibiting membership proportions to a hatchery strain cluster exceeding 10% ( q ≥ 0.10). Results from this investigation can be used to prioritize management efforts for Brook Trout in western New York State and act as a baseline to monitor future population trends.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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 teacher head, 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".