Severe Inbreeding and Small Effective Number of Breeders in a Formerly Abundant Marine Fish
Bibliographic record
Abstract
In contrast to freshwater fish it is presumed that marine fish are unlikely to spawn with close relatives due to the dilution effect of large breeding populations and their propensity for movement and reproductive mixing. Inbreeding is therefore not typically a focal concern of marine fish management. We measured the effective number of breeders in 6 New York estuaries for winter flounder (Pseudopleuronectes americanus), a formerly abundant fish, using 11 microsatellite markers (6-56 alleles per locus). The effective number of breeders for 1-2 years was remarkably small, with point estimates ranging from 65-289 individuals. Excess homozygosity was detected at 10 loci in all bays (FIS = 0.169-0.283) and individuals exhibited high average internal relatedness (IR; mean = 0.226). These both indicate that inbreeding is very common in all bays, after testing for and ruling out alternative explanations such as technical and sampling artifacts. This study demonstrates that even historically common marine fish can be prone to inbreeding, a factor that should be considered in fisheries management and conservation plans.
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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".