THE INFLUENCE OF HISTORY AND CONTEMPORARY STREAM HYDROLOGY ON THE EVOLUTION OF GENETIC DIVERSITY WITHIN SPECIES: AN EXAMINATION OF MICROSATELLITE DNA VARIATION IN BULL TROUT, SALVELINUS CONFLUENTUS (PISCES: SALMONIDAE)
Bibliographic record
Abstract
Abstract An understanding of the relative roles of historical and contemporary factors in structuring genetic variation is a fundamental, but understudied aspect of geographic variation. We examined geographic variation in microsatellite DNA allele frequencies in bull trout (Salvelinus confluentus, Salmonidae) to test hypotheses concerning the relative roles of postglacial dispersal (historical) and current landscape features (contemporary) in structuring genetic variability and population differentiation. Bull trout exhibit relatively low intrapopulation microsatellite variation (average of 1.9 alleles per locus, average He= 0.24), but high levels of interpopulation divergence (FST= 0.39). We found evidence of historical influences on microsatellite variation in the form of a decrease in the number of alleles and heterozygosities in populations on the periphery of the range relative to populations closer to putative glacial refugia. In addition, one region of British Columbia that was colonized later during deglaciation and by more indirect watershed connections showed less developed and more variable patterns of isolation by distance than a similar region colonized earlier and more directly from refugia. Current spatial and drainage interconnectedness among sites and the presence of migration barriers (falls and cascades) within individual streams were found to be important contemporary factors influencing historical patterns of genetic variability and interpopulation divergence. Our work illustrates the limited utility of equilibrium models to delineate population structure and patterns of genetic diversity in recently founded populations or those inhabiting highly heterogeneous environments, and it highlights the need for approaches incorporating a landscape context for population divergence. Substantial microsatellite DNA divergence among bull trout populations may also signal divergence in traits important to population persistence in specific environments.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 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".