Amplified fragment length polymorphism analysis reveals high genetic variation in the Ouachita Mountain endemic <i>Carex latebracteata</i> (Cyperaceae)
Bibliographic record
Abstract
Species with limited geographic ranges are often of conservation concern because they may possess low levels of genetic variability and thus have a reduced ability to respond to stochastic events. As a consequence, an important conservation strategy is to maximize a species’ adaptive potential by preserving natural levels of genetic variation. With this goal in mind, we assessed genetic variation within and among six populations of the Ouachita Mountain endemic Carex latebracteata Waterfall using 653 amplified fragment length polymorphism (AFLP) loci. Indices of genetic variation [% polymorphic loci, expected heterozygosity (HE), population differentiation (ΦPT)] were most consistent with an outcrossing or mixed mating system despite an inflorescence morphology that seems conducive to self-pollination. An analysis of molecular variance (AMOVA) showed that >80% of the variation occurred within populations, suggesting high levels of gene flow. The close geographic proximity of most populations, which are often adjacent to streams, may facilitate long-distance seed dispersal and help to maintain high intra-population genetic variation. Conservation strategies focused on maintaining the ecological integrity of rivers and streams, and the provision of naturally vegetated buffers would likely assist in the conservation of this and other Ouachita Mountain endemics.
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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".