Genetic subpopulation structuring and its implications in a mature eastern white pine stand
Bibliographic record
Abstract
We examined patterns of genetic structuring within a mature eastern white pine (Pinus strobus L.) forest, using geographic information system (GIS)-based data and maps that combined genetic (isozyme analysis of 46 loci) and other tree-specific information (e.g., size, growth, age, and location) for 220 trees in Jericho, Vermont. Interconnections between genotypic information with other tree characteristics revealed several patterns of genetic structuring. Average observed heterozygosity generally increased with tree age-class, and trees with a high number of rare alleles were disproportionally represented in suppressed crown classes. Spatial structuring was also evident: trees within 5 m of one another were highly related, and levels of relatedness generally decreased with increasing distance between trees. In general, a 35-m-radius circle around any tree circumscribed its zone of genetic similarity. Hierarchical cluster analysis indicated the stand consisted of five family groups that exhibited greater genetic similarity within than among clusters. Temporal structuring (a generation gap) was also evident: trees of similar age showed significant positive relatedness, as did trees 3040 years apart. Patterns of genetic structuring likely resulted from the combined influences of natural selection, isolation by distance, and functional generation times. Genetic structuring may also have biological and management implications. Computer-based simulated harvests suggested that the stand could experience genetic alteration when tree removal criteria disrupted existing structural patterns.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".