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Record W2018110275 · doi:10.1139/x02-119

Interactions among <i>Kalmia angustifolia</i>, soil characteristics, and the growth and nutrition of black spruce seedlings in two boreal Newfoundland plantations of contrasting fertility

2002· article· en· W2018110275 on OpenAlexfundvenueaboutno aff
Stephen H Yamasaki, James W. Fyles, Brian Titus

Bibliographic record

VenueCanadian Journal of Forest Research · 2002
Typearticle
Languageen
FieldEnvironmental Science
TopicSeedling growth and survival studies
Canadian institutionsnot available
FundersCanadian Forest Service
KeywordsBlack spruceBorealBiologyHumusPicea abiesCompetition (biology)NutrientSeedlingNutrient cycleBotanyEcologyTaigaSoil water

Abstract

fetched live from OpenAlex

To determine the nature of the negative influence of Kalmia angustifolia L. on black spruce (Picea mariana (Mill.) BSP) seedling growth and foliar nutrient concentrations, the effect of proximity to Kalmia on spruce seedlings was studied on two Kalmia-dominated sites of contrasting soil characteristics in central Newfoundland. Spruce seedlings and the soil at the base of their stems were sampled, and spruce leader length and foliar N and P concentration, as well as various physicochemical soil characteristics, were determined. Path analysis was used to determine the strength of direct and indirect relationships among variables hypothesized to be causally linked. Path diagrams were generated based on current knowledge of nutrient cycling in boreal ecosystems and mechanisms previously hypothesized to account for the influence of Kalmia on black spruce. On the wetter and richer site, proximity to Kalmia was associated with reduced spruce growth and humus extractable NH 4 -N, suggesting nutrient competition. On the drier and poorer site, results were consistent with a direct negative effect of Kalmia on the N nutrition of spruce. On both sites, we also found evidence for a direct effect of Kalmia on spruce growth that is consistent with allelopathic effects on spruce function.

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)0.001
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 score0.369
Threshold uncertainty score0.845

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
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 head0.278
Teacher spread0.249 · 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

Citations47
Published2002
Admission routes3
Has abstractyes

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