Plant community attributes 12 to 14 years following precommercial thinning in a young lodgepole pine forest
Bibliographic record
Abstract
We investigated plant community responses (abundance, species diversity, and structural diversity) to a range of precommercial thinning densities in young lodgepole pine (Pinus contorta Dougl. ex Loud. var. latifolia Engelm.) stands 12 to 14 years after thinning, with both unthinned and old-growth stands for comparison. Abundance of understory plants, especially herbs, appeared to increase dramatically in the thinned stands. The moss layer was significantly more abundant in old-growth stands than in the young pine stands. Of a total of 108 species sampled, only three were introduced species, all of which occurred more frequently in the low-density stands than in any of the other stands. Thinning treatments appeared to increase the abundance of late-seral species. Our results suggest that by disrupting canopy closure, thinning decreased the dominance of tall trees and increased the abundance of herbs, shrubs, and trees in the understory height classes. As a result, thinning to low densities significantly increased the structural richness of the tree layer and caused an increase in total structural diversity, which, although only marginally significant (p = 0.06), was likely biologically important. Our results suggest that thinning will enhance the abundance, species diversity, and structural diversity of the plant community 12 to 14 years postthinning.
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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 | 0.000 | 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".