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Record W4285732884 · doi:10.3390/plants11141860

The Effect of Frankia and Hebeloma crustiliniforme on Alnus alnobetula subsp. Crispa Growing in Saline Soil

2022· article· en· W4285732884 on OpenAlexaffabout
Haoran Chen, Sylvie Renault, John Markham

Bibliographic record

VenuePlants · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicLegume Nitrogen Fixing Symbiosis
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsFrankiaNitrogen fixationActinorhizal plantBiologySymbiosisBotanyRoot noduleEctomycorrhizaeBiomass (ecology)HorticultureAgronomyMycorrhiza

Abstract

fetched live from OpenAlex

The mining of the oil sands region of Canada’s boreal forest creates disturbed land with elevated levels of salts. Understanding how native plants respond to salt stress is critical in reclaiming these lands. The native species, Alnus alnobetula subsp. crispa forms nitrogen-fixing nodules with Frankia, and ectomycorrhizae with a number of fungal species. These relationships may make the plant particularly well suited for restoring disturbed land. We inoculated A. alnobetula subsp. crispa with Frankia and Hebeloma crustiliniforme and exposed the plants to 0, 50, or 100 mM NaCl for seven weeks. Frankia-inoculated plants had increased biomass regardless of salt exposure, even though salt exposure reduced nitrogen fixation and reduced the efficiency of nitrogen-fixing nodules. The nitrogen-fixing symbiosis also decreased leaf stress and increased root phosphatase levels. This suggests that N-fixing plants not only have increased nitrogen nutrition but also have increased access to soil phosphorus. Mycorrhizae did not affect plant growth but did reduce nodule numbers and nodule efficiency. These results suggest that the nitrogen-fixing trait is more critical than mycorrhizae. While salt stress inhibits nitrogen-fixing symbiosis, plants still benefit from nitrogen fixation when exposed to salt.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.305
Threshold uncertainty score0.220

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 studies0.0000.000
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 head0.007
GPT teacher head0.204
Teacher spread0.197 · 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

Citations6
Published2022
Admission routes2
Has abstractyes

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