Genetic and metal analyses of fragmented populations of<i>Betula papyrifera</i>(Marsh) in a mining reclaimed region: identification of population–diagnostic molecular marker
Bibliographic record
Abstract
White birch (Betula papyrifera) is an open pollinate species that is, dominant in the Northern Ontario after land reclamation. In fact, this species represents 65% of all trees in the region. We hypothesized that the exchange of genetic information between fragmented populations by range-wide paternal introgression is possible in wind-pollinated species such as B. papyrifera. On the other hand, the effects of heavy metal contamination from the mining activities on plant growth and population dynamics are well documented. The main objectives of this study were (1) to assess the level of genetic variation, gene flow, and population sustainability of B. papyrifera after land reclamation; and (2) to determine the level of phytoavailable metals in soil and their accumulation in trees. We found that B. papyrifera is a Ni and Zn accumulator with a translocation factor of 6.4 and 81, respectively, and an indicator of Cu and Pb. The level of polymorphic loci, Shannon index, Nei's genetic diversity, observed number of alleles, and gene flow were determined for the fragmented populations within the targeted region. The percent of polymorphic loci ranged from 28% to 56%; the gene flow was also low with a value of 0.89, and the population differentiation was very high with a value of 0.36. Two population-diagnostic ISSR markers were identified. They were cloned, sequenced, and converted to SCAR markers. Overall, the fragmented populations of B. papyrifera in Northern Ontario are genetically sustainable based on the moderate level of intrapopulation variability.
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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".