Long-term spatial and structural dynamics in Acadian mixedwood stands managed under various silvicultural systems
Bibliographic record
Abstract
Using inventory data from a long-term silviculture experiment in east-central Maine, spatial models were developed to analyze 28 years (1974–2002) of stand structural dynamics. Differences in spatial pattern, species mingling, height differentiation, and relative stand complexity index (rSCI) were compared among five treatments: commercial clear-cutting, fixed diameter-limit, 5 year single-tree selection, three-stage shelterwood (both with and without precommercial thinning), and unharvested natural areas. Regardless of treatment, regeneration events (whether induced by natural breakup of the overstory or by harvesting) increased aggregation in spatial pattern and reduced species mingling, more so in the commercial clearcut and fixed diameter-limit treatments where hardwood densities were highest. Regular spatial patterns were rare. Height differentiation values for individual trees and stand-level mean rSCI were generally highest in untreated natural areas and 5 year selection treatments, intermediate in commercial clearcut and fixed diameter-limit treatments, and lowest in three-stage shelterwood treatments. After a brief adjustment period, precommercial thinning in a shelterwood treated stand generally increased species mingling, height differentiation, and rSCI. Two untreated natural areas exhibited divergent pathways of structural development. Dynamics in uneven-aged selection treatments more closely resembled that of the untreated natural areas than did the shelterwood, commercial clearcut, or fixed diameter-limit treatments.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 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".