Underwater but not out of sight: genetic monitoring of effective population size in the endangered North Sea houting (<i>Coregonus oxyrhynchus</i>)
Bibliographic record
Abstract
We analysed 12 microsatellite DNA loci in temporal samples (1980, 1994, and 2002) from the only remaining indigenous population of the North Sea houting (Coregonus oxyrhynchus) in the Vidaa River, Denmark. Using a novel temporal method, we estimated effective population size (Ne) to be 577.4 (90% highest posterior density limits 297.23719.8). The same method was used to estimate Neat the beginning and end of the sampled time interval, and the results were indicative of a relatively stable population. In contrast, tests for recent bottlenecks suggested population declines in the 1980 and 1994 samples, possibly reflecting declines prior to 1980 in the total North Sea houting population. To evaluate the usefulness of the two methods for routine genetic monitoring, we simulated population declines corresponding to reproduction by only 20 or 50 parents in 2002. For both simulated samples, the temporal method provided evidence for a population decline, whereas the test for bottlenecks did not suggest population decline. We conclude that the North Sea houting in the Vidaa River is not immediately threatened by inbreeding or loss of evolutionary potential, and the applied temporal method appears very useful for genetic monitoring of effective population size in endangered, isolated fish populations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".