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Record W2150929025 · doi:10.1139/x03-274

Range of variability in boreal aspen plant communities after wildfire and clear-cutting

2004· article· en· W2150929025 on OpenAlexfundvenueaboutno aff
Sybille Haeussler, Yves Bergeron

Bibliographic record

VenueCanadian Journal of Forest Research · 2004
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaUniversité du Québec à MontréalMinistry of Natural Resources
KeywordsClearcuttingUnderstoryBasal areaBorealSpecies richnessPlant communityForestryEnvironmental scienceRange (aeronautics)TaigaEcologyBiomass (ecology)BiodiversityGeographyForbVegetation (pathology)CanopyBiologyGrassland

Abstract

fetched live from OpenAlex

Composition, structure, and diversity of vascular and nonvascular plant communities was compared 3 years after wildfire and clear-cutting in mesic trembling aspen (Populus tremuloides Michx.) forests of the southern Canadian boreal forest. We examined mean response to disturbance and variability around the mean across four to five spatial scales. Four 1997 wildfires were located near Timmins, Ontario, and ten 1996–1997 clearcuts were located adjacent to the wildfires. We randomly located plots within mesic, aspen-dominated stands selected to minimize predisturbance environmental differences. Correspondence analysis separated wildfire and clearcut samples based on community composition: wildfires had more aspen suckers, Diervilla lonicera Mill., and pioneering mosses; clearcuts had more under story tall shrubs, forbs, bryophytes, and lichens. Live tree basal area averaged 1.7 m 2 /ha in wildfires and 1.8 m 2 /ha in clearcuts (p = 0.59), and understory community structure (the horizontal and vertical distribution of live and dead plant biomass) was not markedly different. Clearcuts had higher species richness with greater variance than wildfires across all spatial scales tested, but differences in beta and structural diversity varied with spatial scale. Generally, clearcut–wildfire differences were more evident and wildfire variability greater at larger analytical scales, suggesting that plant biodiversity monitoring should emphasize cumulative effects across landscapes and regions.

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)0.006
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 score0.365
Threshold uncertainty score0.531

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.022
GPT teacher head0.262
Teacher spread0.240 · 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

Citations95
Published2004
Admission routes3
Has abstractyes

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