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Record W2135589541 · doi:10.1139/x09-127

Factors controlling epiphytic lichen biomass during postfire succession in black spruce boreal forests

2009· article· en· W2135589541 on OpenAlexafffundvenueabout
Catherine Boudreault, Yves Bergeron, Darwyn Coxson

Bibliographic record

VenueCanadian Journal of Forest Research · 2009
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicLichen and fungal ecology
Canadian institutionsUniversité du Québec à MontréalUniversity of Northern British Columbia
FundersFonds Québécois de la Recherche sur la Nature et les TechnologiesUniversité du Québec à Montréal
KeywordsLichenEpiphyteTaigaEcological successionBiomass (ecology)Species richnessEcologyBlack spruceBorealAbundance (ecology)ForestryBiologyEnvironmental scienceGeography

Abstract

fetched live from OpenAlex

Alectorioid lichens are the dominant group of epiphytic lichens in boreal forests. Epiphytic lichen richness and abundance generally increase with stand age and within-stand heterogeneity. The objective of this study was to evaluate the importance of time elapsed since the last fire, stand structure, tree size, tree age, and branch height for epiphytic lichen biomass of the boreal forest of western Quebec. We sampled 12 sites belonging to four forest age classes (from 50 to >200 years). We assessed epiphytic lichen biomass of three species groups ( Bryoria , Evernia , and Usnea ) on 12 trees in each site. Our results showed that biomass of Bryoria and Usnea was higher in intermediate stages (between 101 and 200 years) compared with younger (50–100 years) and older (>200 years) stages. Biomass of the three species groups was greater on larger diameter trees (>16 cm) compared with smaller ones (<16 cm). These results indicate that the protection of postfire stands aged between 101 and 200 year should be prioritized to maintain the functional role of epiphytic lichens in managed landscapes.

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)0.001
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 score0.621
Threshold uncertainty score0.980

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.049
GPT teacher head0.297
Teacher spread0.247 · 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

Citations31
Published2009
Admission routes4
Has abstractyes

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