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Record W2809352680 · doi:10.3390/f9070376

Structural Attributes of Old-Growth and Partially Harvested Northern White-Cedar Stands in Northeastern North America

2018· article· en· W2809352680 on OpenAlexaffabout
Nathan Wesely, Shawn Fraver, Laura S. Kenefic, Aaron R. Weiskittel, Jean‐Claude Ruel, Michael Thompson, Alan S. White

Bibliographic record

VenueForests · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicForest Ecology and Biodiversity Studies
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsSnagBasal areaContext (archaeology)ForestryCoarse woody debrisForest managementDiameter at breast heightOld-growth forestGeographyStand developmentAgroforestryEcologyHabitatBiologyArchaeology

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.623
Threshold uncertainty score0.383

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.017
GPT teacher head0.204
Teacher spread0.187 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations10
Published2018
Admission routes2
Has abstractyes

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