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Record W2586311117 · doi:10.1111/nph.14465

Evolutionary asymmetry in the arbuscular mycorrhizal symbiosis: conservatism in fungal morphology does not predict host plant growth

2017· article· en· W2586311117 on OpenAlexafffund
Alexander Koch, Pedro M. Antunes, Hafiz Maherali, Miranda M. Hart, John N. Klironomos

Bibliographic record

VenueNew Phytologist · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMycorrhizal Fungi and Plant Interactions
Canadian institutionsUniversity of GuelphAlgoma UniversityOkanagan University CollegeUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
KeywordsBiologyObligateSymbiosisBotanyHost (biology)Morphology (biology)Arbuscular mycorrhizalCoevolutionEcologyZoologyBacteria

Abstract

fetched live from OpenAlex

Although arbuscular mycorrhizal (AM) fungi are obligate symbionts that can influence plant growth, the magnitude and direction of these effects are highly variable within fungal genera and even among isolates within species, as well as among plant taxa. To determine whether variability in AM fungal morphology and growth is correlated with AM fungal effects on plant growth, we established a common garden experiment with 56 AM fungal isolates comprising 17 genera and six families growing with three plant host species. Arbuscular mycorrhizal fungal morphology and growth was highly conserved among isolates of the same species and among species within a family. By contrast, plant growth response to fungal inoculation was highly variable, with the majority of variation occurring among different isolates of the same AM fungal species. Our findings show that host performance cannot be predicted from AM fungal morphology and growth traits. Divergent effects on plant growth among isolates within an AM fungal species may be caused by coevolution between co-occurring fungal and plant populations.

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)0.001
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 score0.025
Threshold uncertainty score0.983

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0010.000
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 head0.019
GPT teacher head0.229
Teacher spread0.211 · 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

Citations160
Published2017
Admission routes2
Has abstractyes

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