Genetic Population Structure of Brook Trout Inhabiting a Large River Watershed
Bibliographic record
Abstract
The genetic population structure of brook trout Salvelinus fontinalis inhabiting the Miramichi River, New Brunswick, a large (14,000-km2) river system composed of three main stems, was assessed using six microsatellite DNA loci. Samples from 12 sites incorporating four temporal replicates were analyzed. An individual-based assignment method without a priori knowledge of geographic origin suggested the presence of five candidate source populations within the 12 sites. Drainage structuring based on the 12 sampling sites did not explain the observed patterns of genetic population structure (analysis of molecular variance: 0.74% of variance explained; not significant). Conversely, the five candidate source populations estimated under the assignment approach significantly explained the genetic population structure observed (3.47% of variance explained; P < 0.001), the level of population fragmentation within sampling sites increasing significantly with proximity to the mouth of the watershed (P = 0.011). These results suggested elevated levels of brook trout dispersal within a large river watershed where geographic distance among sampling sites did not have a significant impact on the genetic population structure. Brook trout populations inhabiting a large river watershed may therefore be more influenced by ecological variables affecting the observed patterns of divergence, such as alternative life history strategies (e.g., anadromy) and habitat selection.
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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 | 0.000 |
| 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".