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Record W2900035379 · doi:10.1139/cjb-2018-0072

Anthropogenic and soil environmental drivers of arbuscular mycorrhizal community composition differ between grassland ecosystems

2018· article· en· W2900035379 on OpenAlexvenueno aff
Alice G. Tipton, Elizabeth L. Middleton, William G. Spollen, Candace Galen

Bibliographic record

VenueBotany · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMycorrhizal Fungi and Plant Interactions
Canadian institutionsnot available
Fundersnot available
KeywordsCalcareousBedrockGrasslandAgronomyEcosystemPlant communityEcologyEcological successionBiologyAgroforestryBotany

Abstract

fetched live from OpenAlex

Interactions between arbuscular mycorrhizal fungi (AMF) and plants are sensitive to a myriad of underlying factors, including soil chemistry and land-use disturbances. Here we address how two grassland ecosystems (Ozark glades vs. tallgrass prairies) in south-central USA have been impacted by legacy effects from land-use disturbances (e.g., fire suppression in glades and tillage, fertilizer, row cropping, and grazing in prairies) and geological substrate (acidic versus calcareous bedrock). We surveyed AMF on the roots of two native generalist host species [Ruellia humilis Nutt. and Schizachyrium scoparium (Michx.) Nash] as well as plants randomly selected from the plant community. Glades on calcareous bedrock had a higher pH than those on acidic bedrock, and AMF communities on all three root sample types varied between acidic and calcareous bedrock locations. In prairies, both bedrock types had a similar soil pH, and AMF communities on all three root sample types varied across remnant and disturbed prairies. Shifts in AMF composition across land-use history included shifts in dominant AMF genera, and some unique rare AMF taxa were restricted to only calcareous glades or remnant prairies. Our findings suggest that reseeding prairie plant communities on cultivated lands does not restore AMF communities. Restoration projects need to address the soil environment and community.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.434
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 head0.011
GPT teacher head0.203
Teacher spread0.192 · 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

Citations20
Published2018
Admission routes1
Has abstractyes

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