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Record W2902840019 · doi:10.1098/rstb.2018.0018

Are fungal strains from salinized streams adapted to salt-rich conditions?

2018· article· en· W2902840019 on OpenAlexaff
Ana Lúcia Gonçalves, Adriana Lelis Carvalho, Feli× Bärlocher, Cristina Canhoto

Bibliographic record

VenuePhilosophical Transactions of the Royal Society B Biological Sciences · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicFreshwater macroinvertebrate diversity and ecology
Canadian institutionsMount Allison University
FundersAgence Nationale de la Recherche
KeywordsBiologySoil salinitySalinityMicrocosmConidiumPlant litterBiomass (ecology)BiodiversitySTREAMSEcologyBotanyNutrient

Abstract

fetched live from OpenAlex

Anthropogenic salinization of freshwater is a global problem with largely unknown consequences for stream functions. We compared the effects of salt addition (6 g l −1 NaCl) in microcosms on leaf mass loss and microbial parameters in single- and multispecies assemblages of fungal strains ( Heliscus lugdunensis , HELU; Tetracladium marchalianum , TEMA; Flagellospora curta , FLCU) isolated from a reference (R) or salinized (S) stream. Fungal growth and interactions were also assessed. Salinization inhibited leaf decomposition and fungal biomass, but no differences were observed between species, strains or species combinations. Sporulation rates in monocultures were not affected by added salt, but differed among species (FLCU > HELU > TEMA), with S strains releasing more conidia. Fungal assemblages did not differ significantly in total conidia production (either between strains or medium salt concentration). HELU was the dominant species, which also had highest growth and most pronounced antagonistic behaviour. Fungal species, irrespective of origin, largely maintained their function in salinized streams. Strains from salt-contaminated streams did not trade-off conidial production for vegetative growth at high salt levels. The expected reduction of fungal diversity and potential changes in nutritional litter quality owing to salinization may impact leaf incorporation into secondary production in streams. This article is part of the theme issue ‘Salt in freshwaters: causes, ecological consequences and future prospects’.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.054
GPT teacher head0.259
Teacher spread0.205 · 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 source (direct Gemma or distilled Codex), 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

Citations28
Published2018
Admission routes1
Has abstractyes

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