Microsatellite DNA analysis of genetic effects of harvesting in old‐growth eastern white pine (<i>Pinus strobus</i>) in Ontario, Canada
Bibliographic record
Abstract
Microsatellite DNA markers from 13 simple sequence repeat (SSR) loci were used to compare genetic diversity between preharvest pristine and postharvest residual gene pools of two adjacent virgin, old-growth ( approximately 250 years) stands of eastern white pine (Pinus strobus L.) in Ontario. There was concurrence in genetic diversity changes in the postharvest gene pools of the two stands. The total and mean numbers of alleles detected in each stand were reduced by approximately 26% after tree density reductions of approximately 75%. Approximately 18 and 21% of the low-frequency (0. 25 > P > or = 0.01) alleles and 76 and 92% of the rare (P < 0.01) alleles were lost from residual stands A and B, respectively, after harvesting. Multilocus gametic diversity was reduced by 38 and 85% and genotype additivity by approximately 50% in the residual stands after harvesting. Latent genetic potential of each stand was reduced by approximately 40%. Although heterozygosity was reduced (1-5%) in the postharvest residual stands, the reductions were not substantial and not comparable to those using other genetic diversity measures. The reductions in genetic diversity measures were slightly higher than those theoretically expected in postbottleneck populations according to drift theory. In the absence of substantial gene migration that could ameliorate the genetic losses, the ability of the postharvest white pine gene pools to adapt to changing environmental and disease conditions may have been compromised. The microsatellite DNA results for genetic effects of harvesting in old-growth eastern white pine stands were similar to those that we reported earlier from allozyme analysis (Buchert et al. 1997). The results indicate that silvicultural practices should ensure that the gene pools of remaining pristine old-growth stands are reconstituted in the regenerating stands.
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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".