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Record W2969790067 · doi:10.1093/njaf/22.4.229

Plant Community Structure After Wildfire in the Subarctic Forests of Western Labrador

2005· article· en· W2969790067 on OpenAlexaffabout
Neal P. P. Simon, Francis E. Schwab

Bibliographic record

VenueNorthern Journal of Applied Forestry · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsCollege of the North Atlantic
Fundersnot available
KeywordsSubarctic climateDisturbance (geology)Species richnessEcologyGeographyClearcuttingPlant communityLichenForestryBiology

Abstract

fetched live from OpenAlex

Abstract We compared western Labrador (Canada) plant communities on 12 10-ha plots representing five forest ages (2, 18, 40, 80, and 140 years) on subhygric sites and two 140-year-old sites on an atypical, moist, well-drained soil. Species richness was less variable and lower on the 80-year-old sites, and conifers did not dominate a site until 40 to 80 years after a disturbance. Herbs were dominant on 2- and 18-year-old sites, whereas woody shrubs were common across all successional stages. Cladina spp. were most abundant on our 40-year-old sites but were replaced by pleurocarpous mosses on our ≥80-year-old sites. Our results are consistent with others who found a delay in conifer establishment that may have resulted from poor seed beds due to the accumulation of unburned duff and inhibitory chemicals from Cladina spp. If these factors are inhibiting conifer establishment, this may conflict with the objectives of forest managers considering emulating natural disturbance in forest operations.North. J. Appl. For. 22(4):229–235.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.483
Threshold uncertainty score0.971

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.005
GPT teacher head0.199
Teacher spread0.194 · 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 source (direct Gemma or distilled Codex), 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

Citations13
Published2005
Admission routes2
Has abstractyes

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