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Record W3173925494 · doi:10.5061/dryad.bg79cnp9k

Data from: A shift from phenol to silica-based leaf defenses during long-term soil and ecosystem development

2021· article· en· W3173925494 on OpenAlexaff
Félix de Tombeur, Étienne Laliberté, Hans Lambers, Michel‐Pierre Faucon, Graham Zemunik, Benjamin L. Turner, Jean‐Thomas Cornelis, Grégory Mahy

Bibliographic record

VenueOpen MIND · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSilicon Effects in Agriculture
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsEcosystemTerm (time)Environmental scienceEcologyBiology

Abstract

fetched live from OpenAlex

The resource availability hypothesis predicts that plants adapted to infertile soils have high levels of anti-herbivore leaf defenses. This hypothesis has been mostly explored for secondary metabolites such as phenolics, while it remains underexplored for silica-based defenses. We determined leaf concentrations of total phenols and silicon (Si) in plants growing along the 2-million-year Jurien Bay chronosequence, exhibiting an extreme gradient of soil fertility. We found that nitrogen (N) limitation on young soils led to a greater expression of phenol-based defenses, whereas old, phosphorus (P)-impoverished soils favored silica-based defenses. Both defense types were negatively correlated at the community and individual species level. Our results suggest a tradeoff among these two leaf defense strategies based on the strength and type of nutrient limitation, thereby opening up new perspectives for the resource availability hypothesis and plant defense research. This study also highlights the importance of silica-based defenses under low P supply.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.659
Threshold uncertainty score0.997

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 communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.062
GPT teacher head0.275
Teacher spread0.213 · 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 designBench or experimental
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
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueOpen MINDSame topicSilicon Effects in AgricultureFrench-language works237,207