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Record W2788325995 · doi:10.1139/cjss-2017-0115

Short-term changes in spruce foliar nutrients and soil properties in response to wood ash application in the sub-boreal climate zone of British Columbia

2018· article· en· W2788325995 on OpenAlexafffundvenueabout
Karl A. Domes, Trevor de Zeeuw, Hugues B. Massicotte, Ché Elkin, W. B. McGill, Michael J. Jull, Colin E. Chisholm, P. Michael Rutherford

Bibliographic record

VenueCanadian Journal of Soil Science · 2018
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCoal and Its By-products
Canadian institutionsUniversity of Northern British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaMinistry of EnvironmentUniversity of Northern British Columbia
KeywordsWood ashAmendmentNutrientRandomized block designAgronomyEnvironmental scienceChemistrySoil pHSoil waterSoil scienceBiology

Abstract

fetched live from OpenAlex

Utilization of wood ash as a forest soil amendment in British Columbia could have numerous benefits, including potentially increasing tree growth. Two wood-derived bottom ashes (low-carbon gasifier ash and high-carbon boiler ash) were applied at 5000 kg ha −1 (dry weight equivalent) with urea (100 kg N ha −1 ), in a two-way factorial randomized block design across two (18- and 24-yr-old) hybrid spruce (Picea glauca × engelmannii Parry × Engelm.) plantations in interior British Columbia. Changes in spruce foliar nutrients and selected soil properties were evaluated. After one growing season, foliar Ca and S significantly increased in plots treated with ash, and foliar N significantly increased while foliar Mg and P significantly decreased in spruce treated with urea. In LFH horizons, soil pH, exchangeable base cations (Ca, Mg, and K), strong acid-extractable B, and Ca significantly increased (p < 0.05) with ash addition; soil pH was greatest in plots treated with urea plus gasifier ash. No significant treatment effects were observed in underlying mineral soil. We conclude that gasifier and boiler ash derived from clean wood applied at 5000 kg ha −1 are effective soil amendments as expressed within 1 yr by changes in nutrient status of LFH horizons and spruce foliage.

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)0.000
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 score0.542
Threshold uncertainty score0.549

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.015
GPT teacher head0.202
Teacher spread0.187 · 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

Citations15
Published2018
Admission routes4
Has abstractyes

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