EFFECT OF SOIL COMPACTION AND ORGANIC MATTER REMOVAL ON GENOTYPIC DIVERSITY, GENETIC STRUCTURE, AND TRAIT EXPRESSIONS IN ASPEN
Bibliographic record
Abstract
Quaking aspen (Populus tremuloides, Michx.) is a fast growing tree which is broadly distributed in North America. It reproduces both clonally through root suckers and sexually through seeds. In order to assess the effect of postharvest treatment on genotypic diversity and structure and on phenotypic trait expressions, we analyzed a total of 323 stems in three control plots and in three treatment plots in Long-Term Soil Productivity study site at Ottawa National Forest with heavy soil compaction and forest floor removal at seven highly variable microsatellite markers and for 25 phenotypic traits. Overall higher spatial aggregation of ramets from the same clonal assemblies and spatial separation of different clonal assemblies was observed in the treatment plots as compared to control plots. Phenotypic and genetic clonal delineation showed a high correspondence in two treatment plots with the most pronounced spatial genetic structure. Phenotypic delineation of clonal colonies was not possible in other plots where clonal colonies were spatially intermixed or occupied a large area. Heavy soil compaction and forest floor removal might have restricted the spread of clonal colonies in treatment plots. While treatment had little effects on genetic and phenotypic separation among plots, very high genetic differentiation was found among most plots with amaximum pairwise RST differentiation of 35.8%. One treatment plot was strongly differentiated phenotypically from all other plots likely as result of micro-environmental variation. Consequently, micro-environmental variation and genetic differences among plots should be considered when treatment effects on phenotypic trait expression are analyzed.
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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 | 0.000 | 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 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".