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Record W2041752994 · doi:10.1139/b06-131

Proglacial succession of biological soil crusts and vascular plants: biotic interactions in the High Arctic

2006· article· en· W2041752994 on OpenAlexafffundvenueabout
Katie Breen, Esther Lévesque

Bibliographic record

VenueCanadian Journal of Botany · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicPolar Research and Ecology
Canadian institutionsUniversité du Québec à Trois-Rivières
FundersNetworks of Centres of Excellence of CanadaNatural Sciences and Engineering Research Council of Canada
KeywordsVascular plantChronosequenceVegetation (pathology)Ecological successionPrimary successionBiological soil crustPlant communityEcologyGeologyLichenSpecies richnessBiology

Abstract

fetched live from OpenAlex

To evaluate the hypothesis that biological soil crusts facilitate the establishment and maintenance of vascular plants during succession, we studied the distribution patterns of crusts and vascular plants along a High Arctic glacier foreland and compared the success of plants growing in and out of crusted substrate. Multivariate analyses determined that distance from the glacier and crust cover were the most important variables, explaining 11% and 9% of the variance in the vegetation data, respectively. Surfaces colonized by biological soil crusts generally supported higher plant densities and showed positive associations with the most dominant, long-lived plant species such as Saxifraga oppositifolia L., Salix arctica Pall., and Dryas integrifolia Vahl. Crusts facilitate plant establishment and growth in early and midsuccession but may compete for available resources further along the chronosequence. This study recognizes subtle direct influences of crust on vegetation density but also draws attention to a much larger overall positive effect on community structure. Succession on this foreland proceeds via a “directional-replacement” model and supports a well-developed community of biological soil crusts and vascular plants with greater species richness, cover, and density compared with other glacier foreland vegetation communities previously investigated on Ellesmere Island, Nunavut.

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 score0.312
Threshold uncertainty score0.956

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)0.0010.000

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 head0.014
GPT teacher head0.237
Teacher spread0.223 · 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

Citations82
Published2006
Admission routes4
Has abstractyes

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