Patterns and consequences of dispersal for Arctic Char (Pisces: Salvelinus alpinus) from the Canadian Arctic
Bibliographic record
Abstract
Dispersal can have a multitude of ecological and evolutionary consequences that can be either positive or negative for population fitness and persistence. In this thesis, I describe patterns of dispersal in Arctic Char (Salvelinus alpinus), and I explored some of its consequences. I first examined the consequences of post-glacial dispersal for the distribution of genetic variation across the Canadian range of the species. MtDNA sequences and microsatellite markers provided evidence that the populations of Arctic Char currently inhabiting the Arctic Archipelago probably recolonized from a small glacial refugium, most likely located in ice-free areas of the Archipelago itself. I also presented evidence that two glacial lineages of Char (an Arctic lineage and an Atlantic lineage) probably hybridized post-glacially in the eastern Arctic. Finally, the importance of contemporary dispersal in redistributing genetic variation was illustrated by the fact that anadromous populations have greater within-population genetic diversity, and are less genetically differentiated, than landlocked populations. Second, I used a genetic assignment approach to study patterns of dispersal among populations distributed around Cumberland Sound, Nunavut. Estimates of dispersal rates varied extensively depending on the analysis method used, but all were relatively high compared to other salmonid species. I also found evidence that overwintering individuals have a greater propensity to disperse to non-natal habitats than individuals destined to spawn that year. The consequences of this behaviour for local adaptation among populations was examined using a population genetic model parameterized with estimates of gene flow obtained from microsatellite data. Third, I tested alternative hypotheses for the co-existence of sympatric migratory ecotypes in three lakes of southeast Baffin Island. Microsatellite data showed that the resident and anadromous components of the population are not genetically differentiated, suggesting that migratory behavior is not a genetically fixed trait. Together, the three parts of my thesis provide a general understanding of the patterns and consequences of dispersal for Arctic Char. Since dispersal will be crucial for the response of Arctic Char to environmental change, I conclude by discussing how my work can serve as a foundation for future work on the role of dispersal in adaptation to a changing Arctic.
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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 | 0.002 | 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".