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Facilitative succession in a boreal bryophyte community driven by changes in available moisture and light

2006· article· en· W4231737601 on OpenAlexaffabout
Nicole J. Fenton, Yves Bergeron

Bibliographic record

VenueJournal of Vegetation Science · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicPeatlands and Wetlands Ecology
Canadian institutionsUniversité du Québec en Abitibi-TémiscamingueUniversité du Québec à Montréal
Fundersnot available
KeywordsBryophyteChronosequenceEcological successionBorealEcologyForest floorEnvironmental scienceTaigaWater tableGeographyEcosystemBiologyGeologyGroundwater

Abstract

fetched live from OpenAlex

Abstract Question: What are the drivers of bryophyte succession in paludifying boreal Picea mariana forests? Location: The Clay‐Belt of Quebec and Ontario, Canada. Methods: The bryophyte community and habitat variables (forest floor thickness, water table, stand density, canopy openness micro‐climate and presence of ericaceous species) were analysed in a chronosequence of 13 stands from 50 to more than 350 years since fire. Results: Across the chronosequence, feathermosses were replaced by shade and desiccation tolerant slower growing hummock Sphagna and then by faster growing hollow Sphagna. These changes were linked with both increasing light availability and the movement of the water table into the forest floor. Conclusions: As water table rise is dependent on forest floor thickness, which is in turn influenced by the presence of Sphagna, this successional sequence represents an example of facilitation. Furthermore, it emphasizes the importance of water table rise in determining stand level, and landscape level variables such as carbon balance.

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)0.001
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 score0.303
Threshold uncertainty score0.603

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.010
GPT teacher head0.248
Teacher spread0.238 · 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

Citations101
Published2006
Admission routes2
Has abstractyes

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