High genetic diversity and low differentiation in North American Margaritifera margaritifera (Bivalvia: Unionida: Margaritiferidae)
Bibliographic record
Abstract
Information on the genetic diversity and population genetic structure of threatened species is important for guiding management decisions. Margaritifera margaritifera (freshwater pearl mussel) occurs across western Russia, north and central Europe, and Atlantic drainages of north-eastern North America (NA). European populations of M. margaritifera are considered endangered, whereas NA populations are thought to be relatively secure. As such, the population genetics of M. margaritifera occurring in European rivers is relatively well studied while that of NA populations is not known. In this study, we investigated the genetic diversity and differentiation of M. margaritifera in Canada and the USA. Genetic diversity indices calculated from nine microsatellite loci were relatively high in the NA population. Analyses of genetic structure indicated that a single panmictic population exists for M. margaritifera in NA. However, there was evidence of substructure in some tributaries of the St. Lawrence River in Québec, Canada. The NA population of M. margaritifera has low genetic differentiation and high diversity, possibly resulting from large population size and high gene flow. Consequently, conservation of this species should focus primarily on maintaining favourable habitat conditions and connectivity for host fish.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".