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Record W2019215876 · doi:10.1111/nph.13226

Host identity is a dominant driver of mycorrhizal fungal community composition during ecosystem development

2014· article· en· W2019215876 on OpenAlexaff
Laura B. Martínez‐García, Sarah J. Richardson, Jason M. Tylianakis, Duane A. Peltzer, Ian A. Dickie

Bibliographic record

VenueNew Phytologist · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMycorrhizal Fungi and Plant Interactions
Canadian institutionsAlgoma University
Fundersnot available
KeywordsChronosequenceEcosystemBiologyEcological successionEcologyHost (biology)Plant community

Abstract

fetched live from OpenAlex

Little is known about the response of arbuscular mycorrhizal fungal communities to ecosystem development. We use a long-term soil chronosequence that includes ecosystem progression and retrogression to quantify the importance of host plant identity as a factor driving fungal community composition during ecosystem development. We identified arbuscular mycorrhizal fungi and plant species from 50 individual roots from each of 10 sites spanning 5-120 000 yr of ecosystem age using terminal restriction fragment length polymorphism (T-RFLP), Sanger sequencing and pyrosequencing. Arbuscular mycorrhizal fungal communities were highly structured by ecosystem age. There was strong niche differentiation, with different groups of operational taxonomic units (OTUs) being characteristic of early succession, ecosystem progression and ecosystem retrogression. Fungal alpha diversity decreased with ecosystem age, whereas beta diversity was high at early stages and lower in subsequent stages. A total of 39% of the variance in fungal communities was explained by host plant and site age, 29% of which was attributed to host and the interaction between host and site (24% and 5%, respectively). The strong response of arbuscular mycorrhizal fungi to ecosystem development appears to be largely driven by plant host identity, supporting the concept that plant and fungal communities are tightly coupled rather than independently responding to habitat.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.416
Threshold uncertainty score1.000

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)0.0010.000

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 head0.017
GPT teacher head0.226
Teacher spread0.210 · 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

Citations226
Published2014
Admission routes1
Has abstractyes

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