The Time of Origin and Genetic Diversity of Three Isolated Kokanee Populations in Southwest Alaska
Bibliographic record
Abstract
Abstract We examined the time of origin and genetic diversity of native kokanee, the nonanadromous ecotype of Sockeye Salmon Oncorhynchus nerka, from three isolated lakes in the Katmai National Park and Preserve in southwest Alaska. These kokanee evolved independently from Sockeye Salmon when migration barriers arose, blocking ocean access. We used information about the relative age of each barrier to hypothesize the relative time of origin for kokanee in each lake. In addition, we used data from 13 microsatellite loci to test our time of origin hypotheses and assess genetic diversity of kokanee from these three lakes and proximate Sockeye Salmon populations. Coalescent‐based estimates of the time of origin for kokanee in Jo‐Jo Lake (170 years before present [ybp]) and Devil's Cove Lake (6,583 ybp) were consistent with the relative age of barriers isolating each lake. However, data from Dakavak Lake (1,379 ybp) suggested that the barrier was older than hypothesized. Indices of intrapopulation diversity were lower for kokanee than for Sockeye Salmon. Estimates for kokanee population divergence (RST; the FST analog for microsatellites) among the three lakes were consistent with time of origin estimates. Furthermore, the most recently isolated kokanee (Jo‐Jo Lake population) were most closely related to neighboring Sockeye Salmon. Only the kokanee from Jo‐Jo Lake exhibited a relatively low historical effective population size (Ne ≈ 107) and evidence of a genetic bottleneck. Taken together, the results of this study show that although rare, kokanee in Alaska are not ephemeral and can persist in isolation for hundreds of generations despite the colder temperatures and shorter growing season, that are thought to limit their sustainability in Alaska.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".