Conservation genetics of Magnolia acuminata, an endangered species in Canada: Can genetic diversity be maintained in fragmented, peripheral populations?
Bibliographic record
Abstract
The genetic diversity of peripheral populations is potentially important to the future adaptive capacity of species, although may be difficult to predict. A large number of species-at-risk in Canada are at the northern edge of their distribution, and many of these live in fragmented habitat. We used nuclear and chloroplast markers to assess patterns of genetic diversity and differentiation within and among populations of Canadian Magnolia acuminata (Cucumber tree), an endangered species in Canada that extends as far north as the fragmented Carolinian forest in southern Ontario. We also compared the genetic composition of Canadian M. acuminata to populations sampled throughout its central distribution in the USA. We found a high proportion of shared microsatellite alleles, plus a single cpDNA haplotype, distributed throughout the entire M. acuminata range. We also found that despite occupying fragmented habitat at their range periphery, Canadian populations showed little reduction in genetic diversity relative to the USA populations, and we attribute this to effective historical dispersal in a long-lived, polyploid species. However, a combination of private alleles, genetic substructuring, and lower levels of genetic diversity in seedlings compared to mature trees, suggests that current levels of gene flow are relatively low among Canadian populations. Therefore, despite high levels of genetic diversity in Canadian M. acuminata, managers should be aware that without intervention, populations will likely become increasingly isolated and experience a reduction in genetic diversity which in turn may threaten their long-term survival in Canada.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".