RESEARCH ARTICLE Inbreeding dynamics in reintroduced, age-structured populations of highly fecund species
Bibliographic record
Abstract
Abstract Reintroduction programs aim at reinstalling a self-sustained population into the wild via a period of supplementation with captive-bred individuals. This pro-cedure can rapidly generate inbreeding among offspring because of the mating scheme and this inbreeding might be further enhanced by the reintroduction scenario. First, we used simulations to assess the consequences of breeding designs on mean inbreeding index F among offspring when the genetic diversity of breeders, the number and sex ratios of breeders, and the proportion of successful crosses vary. A high number of breeders, a balanced sex ratio, a high proportion of effective crosses and a genetically diverse source population generally contribute to lower F values. However, moderately high (‡20) numbers of breeders combined with all but the most biased sex ratios produced mean F values near minimal values. The variability in F was negligible in all parameter combinations except for a very small number of breeders (5) and very biased sex ratios ( £ 1M: 19F). We also simulated the long-term inbreeding dynamics in the introduced population under various demographic scenarios. Our main finding was that the annual number of introduced offspring is a decisive factor in establishing long-term F values in the supple-mented population. Low supplementation levels (102) quickly generated an almost completely inbred population whereas high levels ( ‡ 104) produced stable F values close to that of the introduced offspring. Simulations were run based on the life history and specific demographics of the bloater (Coregonus hoyi), whose reintroduction in Lake Ontario is being considered.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.001 | 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".