Fine‐Scale Population Genetic Structure and Dispersal of Juvenile Steelhead in the Bulkley‐Morice River, British Columbia
Bibliographic record
Abstract
Abstract A knowledge of fine‐scale population genetic structure and patterns of dispersal is an essential component of any action to conserve genetic diversity and maintain population viability. We genotyped 417 juvenile steelhead Oncorhynchus mykiss from the main stem and tributaries of the Bulkley–Morice River, British Columbia, at 10 microsatellite loci to assess fine‐scale population structure and the patterns and magnitude of juvenile dispersal and mixing. We detected significant genetic structuring among juvenile steelhead from seven tributaries of the Bulkley–Morice River (pairwise FST: 0.008–0.156) and found significant isolation by distance among the tributary populations (R2 = 0.198, P = 0.038). These results reflect the homing behavior of spawning adults as well as the temporal stability of those populations. Genotype assignment of tributary‐caught juveniles showed that rates of juvenile dispersal varied among tributaries. The assignment of juveniles sampled from the main stem of the river to source tributary populations suggested that long‐distance movement in juvenile steelhead is common and that juveniles are well mixed in the main stem. Dispersal and fine‐scale genetic structure in pristine steelhead populations are more complex than previously thought. Therefore, actions to conserve Bulkley–Morice River steelhead must strive to maintain the genetic diversity of tributary populations.
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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 | 0.000 |
| 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".