Deciphering Hatchery Stock Influences on Wild Populations of Vermont Lake Trout
Bibliographic record
Abstract
Abstract To better understand the influence of hatchery practices on wild populations of Lake Trout Salvelinus namaycush, we used a landscape genetic approach to tease apart the population genetic patterns expected due to natural processes versus hatchery stocking, i.e., human‐mediated gene flow. In several lakes across our study area in Vermont, the presence of exogenous mitochondrial DNA haplotypes supported our human‐mediated gene flow hypothesis. Microsatellite DNA analyses showed introgression of hatchery genotypes into the wild populations. Nonetheless, clustering patterns within river drainages and signatures of isolation by distance were consistent with natural postglacial colonization. We conclude that though the genetic makeup of Vermont Lake Trout populations has been influenced by stocking, a lack of genetic bottlenecks and concordance with landscape processes suggests that much of the indigenous genetic diversity remains intact. We were able to attribute departures from expectations based on natural genetic patterns to hatchery introgression in specific lakes. To preserve the adaptive potential of local populations that have persisted since the last ice age, we suggest areas for which hatchery supplementation could be minimized. Received June 16, 2014; accepted September 12, 2014
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".