Alternative reproductive tactics increase effective population size and decrease inbreeding in wild Atlantic salmon
Bibliographic record
Abstract
While nonanadromous males (stream-resident and/or mature male parr) contribute to reproduction in anadromous salmonids, little is known about their impacts on key population genetic parameters. Here, we evaluated the contribution of Atlantic salmon mature male parr to the effective number of breeders (Nb) using both demographic (variance in reproductive success) and genetic (linkage disequilibrium) methods, the number of alleles, and the relatedness among breeders. We used a recently published pedigree reconstruction of a wild anadromous Atlantic salmon population in which 2548 fry born in 2010 were assigned parentage to 144 anadromous female and 101 anadromous females that returned to the river to spawn in 2009 and to 462 mature male parr. Demographic and genetic methods revealed that mature male parr increased population Nb by 1.79 and 1.85 times, respectively. Moreover, mature male parr boosted the number of alleles found among progenies. Finally, mature male parr were in average less related to anadromous females than were anadromous males, likely because of asynchronous sexual maturation between mature male parr and anadromous fish of a given cohort. By increasing Nb and allelic richness, and by decreasing inbreeding, the reproductive contribution of mature male parr has important evolutionary and conservation implications for declining Atlantic salmon populations.
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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 | 0.000 | 0.000 |
| 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) | 0.001 | 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".