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Record W4412834418 · doi:10.1139/as-2025-0012

Rhizosphere bacteria and fungi are differentially structured by host plants, soil mineralogy, and ectomycorrhizal communities in the Alaskan Tundra

2025· article· en· W4412834418 on OpenAlexvenueno aff
Fernando Montaño-López, Hannah Holland‐Moritz, Caitlin Hicks Pries, Jessica G. Ernakovich

Bibliographic record

VenueArctic Science · 2025
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsnot available
FundersOffice of Polar Programs
KeywordsRhizosphereTundraHost (biology)BiologyBotanyEcologyBacteriaEnvironmental scienceEcosystemPaleontology

Abstract

fetched live from OpenAlex

The rhizosphere contains diverse groups of bacteria and fungi living near plant roots and mycorrhizal hyphae whose composition and function are key drivers of ecosystem and biogeochemical processes. Despite rich literature on rhizosphere communities, no studies have examined the drivers of rhizosphere communities across plants or soil types in the tundra. We collected 513 root samples from 141 individual plants representing six plant species and three mycorrhizal association types across four glacial histories in Northern Alaska. Glacial drifts ranged from 11 000 to 4.5 million years since deglaciation representing a gradient in glacial history and mineralogical weathering. We found that glacial history, a strong proxy for soil mineralogy, explained the most variation in rhizosphere bacterial communities (13.3%) while interactions between glacial history and host plants explained the most variation in fungal rhizosphere communities (11.6%). We found strong correlations between ectomycorrhizal and rhizosphere communities across spatial scales and sites for the shrub Betula nana (30.7%–54.7% correlated), and that ectomycorrhizal composition was most similar among root fragments of the same plant, followed by plants at the same site, and plants at different sites. This work serves to advance the ecological understanding of rhizosphere and ectomycorrhizal communities in response to shrubification.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.162
Threshold uncertainty score0.986

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 studies0.0000.001
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 head0.014
GPT teacher head0.221
Teacher spread0.207 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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