Data from: Genome-wide investigation of the multiple origins hypothesis for deep-spawning kokanee salmon (Oncorhynchus nerka) across its pan-Pacific distribution
Bibliographic record
Abstract
Abstract Salmonids have emerged as important study systems for investigating molecular processes underlying parallel evolution given their tremendous life history variation. Kokanee, the resident form of anadromous sockeye salmon (Oncorhynchus nerka), have evolved multiple times across the species’ pan-Pacific distribution, exhibiting multiple reproductive ecotypes including those that spawn in streams, on lake-shores, and at lake depths >50 meters. The latter has only been detected in five locations in Japan and British Columbia, Canada. Here, we investigated the multiple origins hypothesis for deep-spawning kokanee, using 9,721 SNPs distributed across the genome analyzed for the vast majority of known populations in Japan (Saiko Lake) and Canada (Anderson, Seton, East Barrière Lakes) relative to stream-spawning populations in both regions. We detected 397 outlier loci, none of which were robustly identified in paired-ecotype comparisons in Japan and Canada independently. Bayesian clustering and principal components analyses based on neutral loci revealed six distinct clusters, largely associated with geography or translocation history, rather than ecotype. Moreover, a high level of divergence between Canadian and Japanese populations, and between deep- and stream-spawning populations regionally, suggest the deep-spawning ecotype independently evolved on the two continents. On a finer level, Japanese kokanee populations exhibited low estimates of heterozygosity, significant levels of inbreeding, and reduced effective population sizes relative to Canadian populations, likely associated with transplantation history. Along with preliminary evidence for hybridization between deep-spawning and stream-spawning ecotypes in Saiko Lake, these findings should be considered within the context of on-going kokanee fisheries management in Japan.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".