Spatial distribution of genetic diversity in populations of Hagenia abyssinica (Bruce) J.F. Gmel from Ethiopia
Bibliographic record
Abstract
Genetic variation among 596 individuals from 22 natural and 3 planted populations of Hagenia abyssinica (Rosaceae) sampled from the montane forests of Ethiopia was investigated at amplified fragment length polymorphism (AFLP) loci. We observed 106 unequivocally scorable AFLP markers out of which 91.5 percent were polymorphic. Populations harbored varying genetic diversities (He = 0.139-0.362), and showed low but significant genetic differentiation among them (FST = 0.077). Significant differentiation was observed even though previous paleoecological studies indicated that Hagenia abyssinica recolonized Ethiopia only after the Last Glacial Maximum, and our earlier analyses of maternally inherited chloroplast DNA revealed low mixing of recolonizing lineages through seeds and rare long distance seed dispersal. Genetic diversity did not decrease along recolonization routes, confirming effective gene flow, most likely through pollen, among populations. The observed variation at putatively neutral AFLPs does not reflect clinal variation patterns. As expected, population differentiation is lower at anonymous, mostly biparentally inherited, AFLPs than at maternally inherited chloroplast haplotypes. Despite presumably efficient seed and pollen dispersal of H. abyssinica by wind, a significant non-random fine-scale spatial genetic structure was observed up to 80 m in some populations. Due to significant pair-wise differentiation observed between populations, as many populations as possible should be considered for conservation, tree improvement and forestation programs.
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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 | 0.001 |
| 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".