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Record W2029726548 · doi:10.2980/19-3-3488

Fine root seasonal dynamics, plasticity, and mycorrhization in 2 coexisting Mediterranean oaks with contrasting aboveground phenology

2012· article· en· W2029726548 on OpenAlexvenueno aff
Lluís Coll, J. Julio Camarero, Juán Martínez de Aragón

Bibliographic record

VenueEcoscience · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMycorrhizal Fungi and Plant Interactions
Canadian institutionsnot available
Fundersnot available
KeywordsEvergreenBiologyMediterranean climatePhenologyBotanySeasonalityDeciduousGrowing seasonHorticultureEcology

Abstract

fetched live from OpenAlex

To advance understanding of the mechanisms underpinning the coexistence of Mediterranean oak species, we conducted a year-long analysis of the production, architecture, and mycorrhization status of the fine roots of a mixed evergreen (Quercus ilex) and winter deciduous (Quercus faginea) oak stand. We used the ingrowth bag technique to sample the fine roots produced by each species in spring, summer, and winter. For each season, root architecture traits (specific root length, root diameter, root tips) and variables associated to root ectomycorrhizal status were measured in the laboratory. Results showed a marked seasonality in the fine root architecture, including more fine root tips and longer roots per unit of weight formed in spring and summer, revealing a capacity in Mediterranean oak species to modify root architecture in spring and suggesting the possibility of increased resource capture in summer. Fine root ectomycorrhizal status was comparable between species and also showed marked seasonality: we found a high percentage of roots colonized by dead ectomycorrhizas in winter but low ectomycorrhizal colonization rates in summer. Quercus ilex produced greater amounts of fine roots than Q. faginea (particularly during spring), suggesting greater competitive ability in the former species for belowground resources.

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 score0.068
Threshold uncertainty score0.958

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 head0.015
GPT teacher head0.217
Teacher spread0.203 · 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

Citations29
Published2012
Admission routes1
Has abstractyes

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