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Record W2167669810 · doi:10.1139/b11-036

Natural plant colonization of borrow pits in boreal forest highlands of eastern Canada

2011· article· en· W2167669810 on OpenAlexaffvenueabout
Sandrine Hugron, Roxane Andersen, Monique Poulin, Line Rochefort

Bibliographic record

VenueBotany · 2011
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicLichen and fungal ecology
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsLichenEcological successionColonizationEcologyPlant communityBorealBiologyVascular plantTaigaPioneer speciesGeographyForestrySpecies richness

Abstract

fetched live from OpenAlex

Plant colonization after gravel extraction for road construction is slow and is often considered to be primary succession. The goal of this study was to identify the plant communities that spontaneously colonized borrow pits located in boreal climate zones and to assess how environmental variables influenced this colonization process. It also helped identifying potential combinations of plants to use as well as environmental factors to improve to restore borrow pits. A total of 505 plots were inventoried in 117 borrow pits located in the boreal forest highlands 120 km northeast of Quebec City, Quebec, Canada (Parc national des Grands Jardins). Species cover was visually estimated for different plant communities within each borrow pit where slope and soil characteristics were also evaluated. We used multivariate analyses, including clustering, redundancy, and regression tree analyses. The borrow pits studied were undergoing primary succession processes decades after abandonment. The main pioneer species were bryophytes and lichens. Soil water content and soil physicochemistry had the greatest influence on the natural colonization of borrow pits. We observed that, based on the prevailing conditions, the bryophytes Polytrichum piliferum Hedw. and Niphotrichum canescens (Hedw.) Bednarek-Ochyra & Ochyra, lichens of the genus Stereocaulon , and the lichen Trapeliopsis granulosa (Hoffm.) Lumbsch could potentially act as nurse species and could initiate the restoration of borrow pits located in boreal forests.

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 score0.553
Threshold uncertainty score0.594

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 head0.177
Teacher spread0.163 · 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
Published2011
Admission routes3
Has abstractyes

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