Genetic Differentiation of Jack Pine (Pinus banksiana) and Red Pine (P. resinosa) Populations From Metal Contaminated Areas in Northern Ontario (Canada) Using ISSR Markers
Bibliographic record
Abstract
Abstract Metal accumulation in soil and plant tissues has caused severe ecological damage in forest ecosystems in the Sudbury region. The main objective of the present study was to determine the levels of genetic diversity in jack and red pine populations growing in metal contaminated and uncontaminated areas. Newly introduced populations were compared to 40 to 60 old populations. For jack pine, the percentage of polymorphic loci (P %) ranged from 14.6% to 45.8% with a mean of 31.6%. Nei’s gene diversity (h) varied from 0.046 to 0.169 with an average of 0.100, and Shannon’s index (I) ranged from 0.070 to 0.250 with an average of 0.153. The level of genetic variation was much lower in the red pine populations. For this species, the level of polymorphic loci varied from 4.55% to 27.27%. The mean for Nei’s gene diversity and Shannon’s information index, were 0.034 and 0.053, respectively. The highest genetic diversity values were observed in new plantations being developed by the Sudbury reforestation program. Overall, the genetic distance among the Pinus banksiana populations revealed that all the populations analyzed were genetically close to each other. There was no association between metal accumulation and genetic diversity for both species.
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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) | 0.001 | 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) | 0.001 | 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 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".