Variation in the Population Structure of Yukon River Chum and Coho Salmon: Evaluating the Potential Impact of Localized Habitat Degradation
Bibliographic record
Abstract
We used microsatellite and mitochondri-al DNA–restriction fragment length polymorphism (mtDNA–RFLP) analyses to test the hypothesis that chum salmon Oncorhynchus keta and coho salmon O. kisutch in the Yukon River, Alaska, exhibit population structure at differing spatial scales. If the hypothesis is true, then the risk of losing genetic diversity because of habitat degradation from a gold mine near a Yukon River tributary could differ between the two species. For each species, collections were made from two tributaries in both the Innoko and Tanana rivers, which are tributaries to the lower and middle Yukon River. The results revealed a large difference in the degree and spatial distribution of population structure between the two species. For chum salmon, the microsatellite loci (F-statistic (FST) = 0.021) and mtDNA (FST = −0.008) revealed a low degree of interpopulation genetic diversity on a relatively large geographic scale. This large-scale population structure should minimize, although not eliminate, the risk of genetic diversity loss due to localized habitat degradation. For coho salmon, the microsatellites (FST = 0.091) and mtDNA (FST = 0.586) revealed a high degree of interpopulation genetic diversity on a relatively small geographic scale. This small-scale population structure suggests that coho salmon are at a relatively high risk of losing genetic diversity due to localized habitat degradation. Our study underscores the importance of a multispecies approach for evaluating the potential impact of land-use activities on the genetic diversity of Pacific salmon.
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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 | 0.000 | 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".