Potential effects of stock enhancement with hatchery-reared seed on genetic diversity and effective population size
Bibliographic record
Abstract
The present study investigated the genetic efficiency of enhancing populations of wild scallops using hatchery-produced seed scallops. Scallops from the Isle of Man (IOM), Irish Sea, and from a scallop hatchery were genotyped using 15 microsatellite markers. Hatchery scallops had equivalent heterozygosity to wild scallops, but rare alleles were likely to be lost in hatchery scallops as represented by lower allelic richness. The effective number of breeders (Nb) of the hatchery scallops was estimated at 32.4 (95% CI: 24.4–44.9). The confidence intervals for the estimates of Nbfor the IOM included infinity. When Nbbecomes large the genetic signal is weak compared with the sampling noise; therefore, while we can be confident that the Nbof IOM scallops is larger than that of the hatchery, the precise difference is uncertain. Simulations showed it is possible, in some scenarios, that stock enhancement with hatchery seed can lead to an increase in the wild population's effective size; however, in the majority of scenarios a decrease in the effective size of the wild population is more likely. A precautionary approach to stock enhancement with hatchery seed is advised.
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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 | 0.003 | 0.006 |
| 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".