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Record W2057890350 · doi:10.2136/sssaj2005.0186

Soil Nutrient Dynamics after Harvesting and Slash Treatments in Boreal Aspen Stands

2006· article· en· W2057890350 on OpenAlexaff
Annie Belleau, Suzanne Brais, David Paré

Bibliographic record

VenueSoil Science Society of America Journal · 2006
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicForest Ecology and Biodiversity Studies
Canadian institutionsNatural Resources CanadaCanadian Forest ServiceUniversité du Québec en Abitibi-Témiscamingue
Fundersnot available
KeywordsSlash (logging)Environmental scienceSlash PineForest floorNutrientAgronomyGrowing seasonTaigaBiologySoil waterBotanyEcologySoil sciencePinus <genus>

Abstract

fetched live from OpenAlex

The effects of harvesting and slash treatments on soil nutrient dynamics were assessed in boreal aspen stands growing on mesic clayey sites. Stem‐only harvested stands were compared with unharvested controls according to a complete block design with three replications. Within harvested areas, four slash treatments (stem‐only harvesting [SOH], whole‐tree harvesting [WHT], wood chip application, and slash burns) were compared. Treatments created a gradient of slash that ranged from 52.3 Mg ha −1 in stem‐only to 13.8 Mg ha −1 in control stands. The amount of slash had no effect on wood decomposition rates but was strongly associated with higher forest floor organic C, Kjeldahl N and base cation concentrations (Ca e and Mg e ), base saturation, pH, and effective cation exchange capacity (CEC) and lower microbial C/N when control stands were compared with stem‐only harvested stands. Slash burn severity was too low to significantly reduce slash loads and induce base cation release but severe enough to reduce forest floor microbial C and N concentrations (−48 and −55%, respectively) for at least one complete growing season. Slash burn also induced increases in forest floor available P (54%) concentration compared with other slash treatments. Chipping reduced forest floor microbial N concentration by 25% and increased microbial C/N by 28% but had no impact on nutrient availability. Differences between WTH and SOH were linked to the abundance of slash. Finally, the results illustrate that whatever the treatment, the amount of slash left on the ground is the main factor found to affect soil microbial community characteristics and soil nutrient 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)0.000
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 score0.013
Threshold uncertainty score0.547

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
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 head0.008
GPT teacher head0.204
Teacher spread0.196 · 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

Citations73
Published2006
Admission routes1
Has abstractyes

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