Dynamics of genetic variation in <i>Taxus baccata</i>: local versus regional perspectives
Bibliographic record
Abstract
Increasing loss of habitat tends to reduce biodiversity at the inter- and intra-specific levels. Within species, the remaining diversity is often partitioned so that a great amount of neutral genetic variation is assigned to among-population variation. This implies reduced gene flow as a consequence of population isolation. We tested whether random amplified polymorphic DNA (RAPD) markers indicate population and (or) regional differentiation in Swiss populations of English yew (Taxus baccata L.), a dioecious forest tree species with scattered distribution. Our sampling included three northern Swiss regions, each containing four populations, and a central-Alpine region with two populations. Four RAPD primers, giving rise to 41 scorable marker bands, identified all but two sampled individuals as unique genotypes. Analyses of molecular variance (AMOVA) detected no significant differentiation among the three northern Swiss regions yet a marginally significant differentiation of these regions versus the central-Alpine region. Concordantly, Mantel tests revealed isolation by distance only when considering all 14 populations. We postulate that the inferred level of gene flow, through wind-borne pollen and occasional long-distance seed dispersal, prevents isolation by distance in northern Switzerland, where stands of T. baccata are relatively abundant. This perpetuates a coherent regional network of occurrences of T. baccata, as might be expected in a metapopulation.Key words: genetic variation, isolation by distance, metapopulation, population differentiation, RAPD-PCR, Taxus baccata.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 teacher head, 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".