Silviculture alters the genetic structure of an eastern hemlock forest in Maine, USA
Bibliographic record
Abstract
We evaluated the influence of long-term silvicultural selection on the genetic structure of an eastern hemlock (Tsuga canadensis (L.) Carr.) forest at the Penobscot Experimental Forest, in Maine, USA. Plots in this forest received one of the following three treatments: (1) selection cuts in which small and poorly formed trees were preferentially removed in 1957 and 1977; (2) diameter-limit cuts in which trees at least 24 cm in diameter were removed in 1952, 1973, and 1994; or (3) no harvesting (an unmanaged control). Because of an association between the occurrence of rare alleles and tree phenotypes, phenotypically based tree removals were associated with a shift in allelic frequency. Where smaller trees with inferior phenotypes were preferentially removed (selection cut), the number of rare alleles and estimates of future genetic potential were lower than in the control group. Because of the theoretical long-term evolutionary benefit of unique gene forms, the loss of rare alleles could diminish the potential of populations to adapt to and survive ongoing environmental change. In contrast, alleles that were rare in the control group existed at a higher frequency in the diameter-limit cut. However, productivity was low in this stand, where the frequency of characteristically rare alleles was artificially amplified.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".