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Record W2017124903 · doi:10.1139/x03-219

Response of <i>Gaultheria shallon</i> and <i>Epilobium angustifolium</i> to large additions of nitrogen and phosphorus fertilizer

2004· article· en· W2017124903 on OpenAlexvenueno aff
Jennifer Bennett, Brent M Lapthorne, Leandra L Blevins, Cindy E. Prescott

Bibliographic record

VenueCanadian Journal of Forest Research · 2004
Typearticle
Languageen
FieldEnvironmental Science
TopicSeedling growth and survival studies
Canadian institutionsnot available
Fundersnot available
KeywordsTsugaBiomass (ecology)PhosphorusWestern HemlockSeedlingBiologyAgronomyBotanyHuman fertilizationFertilizerHorticultureAnimal scienceChemistry

Abstract

fetched live from OpenAlex

A study was established in coastal British Columbia to determine if repeated nitrogen (N) and phosphorus (P) fertilization negatively influences the reestablishment of salal (Gaultheria shallon Pursh) on cleared and burned cedar–hemlock (Thuja plicata Donn ex D. Don – Tsuga heterophylla (Raf.) Sarg.) forests. Fertilizers were applied for 3 years, and the biomass of ground vegetation and conifer seedling survival and growth were measured. Salal biomass decreased with high levels of N application (1000 kg N/ha), but not when 400 kg P/ha was added with 1000 kg N/ha. The addition of 500 kg N/ha, with or without P, stimulated salal growth. The biomass of fireweed (Epilobium angusti folium L.) increased with the addition of N + P but not with N alone. In the high N and N + P treatments, conifer seedling survival and heights were reduced. These results confirm earlier reports that salal responds negatively to high N applications and that this negative response can be alleviated with simultaneous additions of P. The response of fireweed to N + P, but not to N alone, suggests that the abundance of this species is more indicative of P than N availability.

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)0.002
metaresearch head score (Gemma)0.001
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 score0.072
Threshold uncertainty score0.983

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.026
GPT teacher head0.282
Teacher spread0.256 · 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

Citations18
Published2004
Admission routes1
Has abstractyes

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