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Herbivore‐induced shifts in carbon and nitrogen allocation in red oak seedlings

2008· article· en· W2104750648 on OpenAlexfundno aff
Christopher J. Frost, Mark D. Hunter

Bibliographic record

VenueNew Phytologist · 2008
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoil Carbon and Nitrogen Dynamics
Canadian institutionsnot available
FundersCanadian Forest ServiceU.S. Forest ServiceNational Science Foundation
KeywordsHerbivoreMicrocosmEcosystemBiologyBotanyAgronomyEcology

Abstract

fetched live from OpenAlex

* A dual-isotope, microcosm experiment was conducted with Quercus rubra (red oak) seedlings to test the hypothesis that foliar herbivory would increase belowground carbon allocation (BCA), carbon (C) rhizodeposition and nitrogen (N) uptake. Plant BCA links soil ecosystems to aboveground processes and can be affected by insect herbivores, though the extent of herbivore influences on BCA is not well understood in woody plants. * Microcosms containing 2-yr-old Q. rubra seedlings and soil collected from the Coweeta Hydrologic Laboratory (NC, USA) were subjected to herbivory or left as undamaged controls. All microcosms were then injected with 15N-glycine and pulsed with 13CO2. * Contrary to our hypothesis, herbivore damage reduced BCA to fine roots by 63% and correspondingly increased allocation of new C to foliage. However, 13C recoveries in soil pools were similar between treatments, suggesting that exudation of C from roots is an actively regulated component of BCA. Herbivore damage also reduced N allocation to fine roots by 39%, apparently in favor of storage in taproot and stem tissues. * Oak seedlings respond to moderate insect herbivore damage with a complex suite of allocation shifts that may simultaneously increase foliar C, maintain C rhizodeposition and N assimilation, and shift N resources to storage.

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 score0.114
Threshold uncertainty score0.993

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 head0.029
GPT teacher head0.233
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

Citations106
Published2008
Admission routes1
Has abstractyes

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