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Record W4213042654 · doi:10.1139/as-2020-0055

Essential oil content of <i>Rhododendron tomentosum</i> responds strongly to manipulation of ecosystem resources in Arctic Alaska

2022· article· en· W4213042654 on OpenAlexvenueno aff
Tracey A. Baldwin, Steven F. Oberbauer

Bibliographic record

VenueArctic Science · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsnot available
FundersOffice of Polar ProgramsNational Science Foundation
KeywordsEcosystemShadingEssential oilShrubBiologyArcticPhosphorusHuman fertilizationEcologyNutrientBotanyAgronomyChemistry

Abstract

fetched live from OpenAlex

The essential oils of the widely distributed boreal/Arctic dwarf shrub, Rhododendron tomentosum ssp. subarcticum (Harmaja) G.D. Wallace, have important ecological, cultural, medicinal, and commercial roles. To understand the relationship between resource limitation and essential oil content of this species we measured the amount and diversity of terpenes from shoots of plants exposed to a 14-year ecosystem resource manipulation experiment in Arctic Alaska. Treatments tested interactive effects of nitrogen (N) and phosphorus (P) addition, warming and N + P fertilization, and shading and N + P fertilization. The controls and NP fertilization had the highest essential oil content, whereas shading and P addition had less than 20% of the control content. Warming reduced essential oil content to &lt;65% of that of the controls. Essential oil components varied greatly among the treatments, with significant differences in the expression of specific essential oil components. Large changes in plant community composition and ecosystem structure in response to treatments likely played a large role in the response of R. tomentosum. Our data suggest that resource changes in response to climate warming and its secondary effects on light and nutrient availability have the potential to change the profiles of essential oils in R. tomentosum, with important ecological and cultural impacts.

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)0.001
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 score0.108
Threshold uncertainty score0.369

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.247
Teacher spread0.228 · 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

Citations6
Published2022
Admission routes1
Has abstractyes

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