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Record W1581146042 · doi:10.7202/045097ar

Benthic diatom communities from two salt marshes of the St. Lawrence Estuary (Canada)

2010· article· en· W1581146042 on OpenAlexafffundabout
Michèle A. De Sève, Patrick Poulin, Émilien Pelletier, Karine Lemarchand

Bibliographic record

VenueRevue des sciences de l eau · 2010
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal ecosystems
Canadian institutionsUniversité du Québec à Rimouski
FundersCanada Research Chairs
KeywordsDiatomSalt marshMarshEstuaryBenthic zoneDominance (genetics)OceanographySedimentEcologyDiversity indexEnvironmental scienceGeologyBiologySpecies richnessWetlandGeomorphology

Abstract

fetched live from OpenAlex

Microphytobenthic diatom communities were investigated in the high and low sections of two salt marshes of the Lower St. Lawrence Estuary (eastern Canada): one featuring a sandy low marsh zone (Pointe-aux-Épinettes; PE) and one with a muddy low marsh area (Pointe-au-Père; PP). Based on diatom composition and diversity, bacterial abundance, chlorophyll- a , phaeopigments and geochemical analyses (C org , N tot , granulometry, extracellular polymeric substances), the PP high marsh area appeared to be singular compared to the other sampling sites. Estimated surface biomass ranged from 11 to 71 g C•m -2 in the PE marsh and from 24 to 486 g C•m -2 in the PP marsh. A higher diversity of diatom species was observed in the PP high marsh area with a dominance of epipelic forms, in opposition to the dominant epipsammic forms at the other sites. Statistical analyses showed that diatom density was mainly affected by nutrient availability while the relative abundance of epipelic and epipsammic species was related to sediment grain size. This study provides original data on the composition of benthic diatoms in surface sediments in St. Lawrence saltmarshes during summer time that represent the first step to the determination of the DBI (Diatom biological index) of these northern environments.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.096
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.035
GPT teacher head0.230
Teacher spread0.195 · 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.

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

Citations6
Published2010
Admission routes3
Has abstractyes

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