Genetic diversity and differentiation of core vs. peripheral populations of eastern white cedar, <i>Thuja occidentalis</i> (Cupressaceae)
Bibliographic record
Abstract
PREMISE OF THE STUDY: Geographically peripheral (marginal) populations are expected to have lower genetic diversity and higher genetic differentiation than geographically core (central) populations as a result of supposedly lower effective population size (N(e)) and higher genetic drift, founder effect, fragmentation, and isolation in peripheral than in core populations. Here we address this issue for a long-lived plant species, eastern white cedar (Thuja occidentalis). METHODS: Genetic diversity and population structure of 13 natural populations of eastern white cedar from its Canadian eastern peripheral and core natural ranges in New Brunswick, Nova Scotia, and Prince Edward Island were studied using six nuclear microsatellite DNA markers. KEY RESULTS: The core populations of eastern white cedar had significantly higher allelic diversity (mean A = 8.83, A(r) = 8.13, A(e) = 4.03) and N(e) (428) than the peripheral populations (A = 6.64, A(r) = 6.15, A(e) = 3.12, N(e) = 198). However, expected heterozygosity was similar in the core (H(e) = 0.64) and peripheral (H(e) = 0.60) populations. Genetic differentiation was significantly higher among the peripheral (F(ST) = 0.089) than among the core (F(ST) = 0.032) populations. No genetic differentiation (F(ST)/Φ(RT) = 0.000) was detected between core and peripheral regions. CONCLUSIONS: Peripheral populations have significantly lower N(e) and genetic diversity in terms of allelic diversity (richness) and significantly higher genetic differentiation than the core populations of eastern white cedar in its Canadian eastern range. However, core and peripheral populations have similar levels of expected heterozygosity. Implications for conservation of eastern white cedar genetic resources are discussed.
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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) | 0.000 | 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 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".