Variable Introgression from Supplemental Stocking in Southern Ontario Populations of Lake Trout
Bibliographic record
Abstract
Abstract An unintended consequence of fish stocking is genetic homogenization from interbreeding between indigenous populations and genetically distinct hatchery strains. Lake trout populations in southern Ontario have been extensively supplemented with hatchery strains originating from Great Lakes sources, but evaluation of introgressive admixture has been challenging without data or samples that precede historical stocking events. We used complementary genetic markers (mitochondrial PCR‐RFLP and 12 microsatellite DNA loci) to resolve native and introgressed (hatchery descendent) genetic profiles for lake trout from four unstocked lakes and eight stocked lakes using samples from an introduced population (i.e., established by introduction of stocked fish) and source hatchery strains for comparison. We predicted that some inland populations would retain a composite native genetic profile similar to profiles of populations in unstocked lakes and that introduced and introgressed populations would resemble hatchery sources. Allele frequency‐based methods and Bayesian individual assignment techniques gave largely congruent results for inferred population ancestries. Four of the eight supplemented populations included in this analysis exhibited genetic profiles consistent with native ancestry, indicating limited introgressive admixture. The remaining supplemented populations, however, showed evidence of introgression and homogenization with genetically distinct stocked fish. Recorded stocking history alone was not indicative of admixture in these populations, which suggests that other genetic, ecological, or anthropogenic factors facilitated reproduction between native and stocked fish.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".