Migration effort and wild population size influence the prevalence of hybridization between escaped farmed and wild Atlantic salmon
Bibliographic record
Abstract
Hybridization of escaped farmed Atlantic salmon Salmo salar with wild populations occurs throughout their native range and can threaten wild population stability and persistence. The extent of hybridization is often population-specific and can drive changes in phenotype and genotype. Current understanding of the forces that contribute to the spatial distribution of hybridization is insufficient despite its potential to inform conservation and management efforts. Using a panel of 95 single nucleotide polymorphisms previously validated for identifying parr of farmed, wild, or hybrid descent, we present a novel exploration of inter- and intra-river distribution of hybrids from 33 locations across 9 rivers in southern Newfoundland, Canada. The proportion of hybrids varied significantly across (p < 0.001) and within rivers (p < 0.05 in 4 rivers). Binomial mixed models and logistic regression showed increased proportions of hybrid and feral offspring within smaller rivers (p < 0.0001). Within-river distribution of hybrid parr was strongly associated with the migration effort required to reach spawning sites; the hybrid proportion decreased significantly (p < 0.05) with increased elevation, geographic distance and the presence of obstructions. These observations support previous hypotheses that the distribution of escaped farmed Atlantic salmon can be restricted by migratory challenges, which result in the reduction of hybrid individuals in upstream spawning sites relative to downstream locations. Our research demonstrates that levels of hybridization vary spatially and are associated with landscape features. We suggest that consideration of spatial variation in levels of hybridization will be essential for the evaluation of impacts that escaped farmed salmon impose on wild 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 | 0.001 | 0.002 |
| 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 | 0.001 |
| 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".