Spatial and temporal dynamics in canopy dominance of an old-growth central Appalachian forest
Bibliographic record
Abstract
Many old-growth deciduous forests in eastern North America exhibit dynamics that suggest succession from dominance by oaks (Quercus spp.) to dominance by maples (Acer spp.). We examined this phenomenon using 20 years of vegetation data from an old-growth central Appalachian forest. Considering the site as a whole, the importance of Quercus spp. declined and that of Acer spp. increased. In particular, Acer rubrum L. exhibited increasing importance in the overstory canopy on upper slopes, and Quercus spp. exhibited a contraction in spatial distribution, particularly in the midstory (P < 0.05). This narrowing of distribution in Quercus spp. was associated with regeneration being restricted to dry, acidic sites. We also considered successional dynamics within three previously identified ecological communities in the study area: oak, mixed mesophytic, and beech. This analysis indicated that increased A. rubrum importance was limited to the upper-slope oak community. A successional dynamic was not apparent in the mixed mesophytic community, and the beech community was characterized by increasing importance of Tsuga canadensis (L.) Carr. Our results suggest that ecological communities have distinct successional trajectories and that predictions of future dynamics must consider topographic and ecological gradients.
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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 | 0.001 | 0.001 |
| 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".