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Record W2463358298 · doi:10.1639/0747-9859-33.2.70

Variation in Lichen Species Assemblages and Secondary Metabolites Surrounding<i>Stereocaulon</i>Species in the Boreal Forest of Northwestern Manitoba

2016· article· en· W2463358298 on OpenAlexafffundabout
Jennifer Doering, Chris Deduke, Michele D. Piercey‐Normore

Bibliographic record

VenueEvansia · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicLichen and fungal ecology
Canadian institutionsUniversity of Manitoba
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsLichenSpecies richnessThallusSecondary metaboliteBotanyCladoniaEcologyTaigaBiologyQuadratBorealShrub

Abstract

fetched live from OpenAlex

Lichen assemblages and their secondary metabolites may be influenced by the broader habitat. More specifically, the function of the thallus structure within a species may influence the production of some secondary metabolites. The objectives of this study were to examine thallus variation in secondary metabolites for one genus, Stereocaulon, and to compare the diversity of lichen assemblages and their secondary metabolite distributions in the boreal forest of northwestern Manitoba. Five sites in each of three study regions were selected (Sherridon, North Star, and Athapap), around the presence of a Stereocaulon thallus. All ground lichen species were collected from five quadrats within each site totaling 75 quadrats. Lichen species were identified and thin-layer chromatography was performed to identify secondary metabolites. A total of 59 ground lichen species and 20 secondary metabolites were identified. This study showed that norstictic acid and constictic acid were absent from the pseudopodetia but present in the apothecia and phyllocladia of Stereocaulon tomentosum only. It also showed that species richness was different between one region (Athapap) and the other two regions (North Star and Sherridon). North Star and Sherridon had the highest species richness and number of metabolites and Athapap had the lowest.

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 score0.260
Threshold uncertainty score0.751

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 head0.020
GPT teacher head0.213
Teacher spread0.193 · 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

Citations5
Published2016
Admission routes3
Has abstractyes

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