Broadscale Population Structure and Hatchery Introgression of Midwestern Brook Trout
Bibliographic record
Abstract
Abstract Brook Trout Salvelinus fontinalis have faced significant declines throughout their native range and have been stocked in Midwestern waters since the late 1800s to offset such losses. Several studies have investigated the genetic effects of these stockings, but these efforts have been confined to relatively small spatial scales. In this study, we compiled 8,454 Brook Trout microsatellite genotypes from 188 wild Midwestern populations and 26 hatchery strains to provide novel insights of broadscale population structure, regional patterns of genetic diversity, and estimates of hatchery introgression for inland Wisconsin populations. Our results indicate high levels of differentiation among our study populations, a lack of hydrological population structuring, lower estimates of genetic diversity in the Driftless Area, and that hatchery introgression has been largely confined to regions of inland Wisconsin that have been heavily affected by anthropogenic disturbances (i.e., the Driftless Area). We also provide evidence that populations may be able to purge hatchery‐derived alleles, discuss possible mechanisms behind this phenomenon, and consider their relevance to accurate estimation of hatchery introgression. Collectively, these results summarize the genetic effects of over a century of anthropogenic disturbance on native Brook Trout populations and emphasize the importance of integrating historical data into contemporary genetic research of intensively managed species.
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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 | 0.001 | 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".