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Record W2727714304 · doi:10.3390/f8070235

Distribution and Characterization of Armillaria Complex in Atlantic Forest Ecosystems of Spain

2017· article· en· W2727714304 on OpenAlexaff
Nebai Mesanza, Cheryl L. Patten, Eugenia Iturritxa

Bibliographic record

VenueForests · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMycorrhizal Fungi and Plant Interactions
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsArmillariaBiologyBotanyDeciduousArmillaria melleaForest ecologyEcologyPopulationEcosystem

Abstract

fetched live from OpenAlex

Armillaria root disease is a significant forest health concern in the Atlantic forest ecosystems in Spain. The damage occurs in conifers and hardwoods, causing especially high mortality in young trees in both native forests and plantations. In the present study, the distribution of Armillaria root disease in the forests and plantations of the Basque Country is reported. Armillaria spp. were more frequently isolated from stands with slopes of 20–30% and west orientation, acid soils with high permeability, deciduous hosts, and a rainfall average above 1800 mm. In a large-scale survey, 35% of the stands presented Armillaria structures and showed disease symptoms. Of the isolated Armillaria samples, 60% were identified using molecular methods as A. ostoyae, 24% as A. mellea, 14% as A. gallica, 1% as A. tabescens, and 1% as A. cepistipes. In a small scale sampling, population diversity was defined by somatic compatibility tests and Universally Primed-PCR technique. Finally, the pathogenicity of A. mellea, the species with the broadest host range, was determined on different tree species present in the Atlantic area of Spain in order to determine their resistance levels to Armillaria disease. A significant difference in disease severity was observed among tree species (p < 0.001), with Pinus radiata being the most susceptible tree species and Cryptomeria japonica the most resistant to A. mellea.

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 score0.152
Threshold uncertainty score0.994

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)0.0000.000

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 head0.018
GPT teacher head0.225
Teacher spread0.206 · 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

Citations16
Published2017
Admission routes1
Has abstractyes

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