A Case Study: Looking at the Effects of Fragmentation on Genetic Structure in Different Life History Stages of Old-Growth Mountain Hemlock (Tsuga mertensiana)
Bibliographic record
Abstract
We examined fine-scale genetic structure of mountain hemlock (Tsuga mertensiana) in an old-growth stand and an adjacent seedling population, with the goal of detecting the effects of fragmentation. Three hundred and six old-growth trees and 195 naturally regenerating seedlings were genotyped at 5 microsatellite loci. Genetic diversity was similar across old-growth life stages and within the clear-cut seedlings. Significant inbreeding was found in the adult class (30+ cm diameter at breast height) of old-growth seedlings and in the adjacent natural regeneration. Relatedness was significantly associated with physical distance for both the oldest age class and for regenerating seedlings in the adjacent clear-cut, whereas intermediate classes showed no such association. As intermediate classes show no isolation by distance, the associations that arise probably occur from single cohort regeneration that clearly has taken place in the clear-cut, and possibly when the oldest old-growth trees were established. Parentage analysis suggested that large-scale fragmentation, such as this clear-cut, allowed for increased long-distance seed dispersal. We conclude that long-lived tree populations can consist of a cohort mosaic, reflecting the effects of fragmentation, and resulting in a complex, age-dependent, local population structure with high levels of genetic diversity.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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 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".