Structural Attributes of Old-Growth and Partially Harvested Northern White-Cedar Stands in Northeastern North America
Bibliographic record
Abstract
Forestry practitioners often need to identify old-growth stands because of their high conservation value. To identify the structural and compositional characteristics potentially unique to old-growth northern white-cedar (Thuja occidentalis L.) stands, we compared 16 old-growth stands and 17 partially harvested stands in Maine, USA and New Brunswick, Canada. Potential old-growth predictors included common structural metrics such as basal area (BA), quadratic mean diameter (QMD), large tree (≥40 cm diameter at breast height) density, and volumes of coarse woody debris (CWD), along with six structural indices. Using generalized linear mixed-models, we identified two significant structural predictors that differentiate old-growth from partially harvested stands when used in combination: Volume of advanced-decay CWD and live tree QMD. None of the structural indices were useful in distinguishing between old-growth and partially harvested stands, nor did the two types differ with respect to tree species composition. Our results demonstrate that two metrics easily derived from standard inventory data—decayed CWD volume and QMD—effectively characterize the old-growth white-cedar stands sampled in this study. Taken together, these results can improve management decision making for white-cedar, particularly in the context of certification, while also shedding light on the effects of past partial harvesting on current forest structure.
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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 | 0.001 |
| 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".