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Record W4200402001 · doi:10.1139/cjb-2021-0194

Post-fire peatland vegetation recovery: a case study in open rich fens of the Canadian boreal forest

2021· article· en· W4200402001 on OpenAlexafffundvenueabout
Mélina Guêné‐Nanchen, Marie-Claire LeBlanc, Line Rochefort

Bibliographic record

VenueBotany · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicPeatlands and Wetlands Ecology
Canadian institutionsCenter for Northern Studies
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Sphagnum Peat Moss AssociationAurora Research Institute
KeywordsPeatBryophyteBiologySphagnumBorealVegetation (pathology)BogCarexEcologyEcological successionVascular plantMossTaigaEcosystemBotanySpecies richness

Abstract

fetched live from OpenAlex

Fire plays a major role in the structuring and functioning of boreal ecosystems. As peatlands are important components of boreal forests, the impact of fire upon these wetter ecosystems is increasingly studied, but with the focus on treed peatlands and Sphagnum-dominated bogs so far. Important fires occurring more frequently in the past decade in southern Northwest Territories (Canada) provide the opportunity to assess early post-fire vegetation regeneration in open rich fens (one, two, and five years post-fire) and to better understand early recovery succession. We aimed to (i) evaluate whether and how open rich fens are affected by fire, and (ii) describe short-term vegetation regeneration for both bryophytes and vascular species. A shift was observed between pioneer bryophytes and brown mosses between the second and fifth year post-fire. Vascular plants, especially slow-growing species and the ones reproducing mainly by seeds, recovered partially. The first bryophyte species recovering were pioneer species adapted to colonize burned environments such as Marchantia polymorpha L. or Ceratodon purpureus (Hedw.) Brid. For vascular plant species, the ones previously present and able to regrow rapidly from unburned plant structures (base of tussocks, rhizomes, roots) were represented by species like Betula glandulosa Michx. or Carex aquatilis Wahlenb. The wetter conditions and lower fuel availability of fen depressional biotopes were important factors controlling the resistance and regeneration of species associated with them.

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 score0.252
Threshold uncertainty score0.254

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 head0.014
GPT teacher head0.246
Teacher spread0.232 · 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

Citations12
Published2021
Admission routes4
Has abstractyes

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