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Record W2057812161 · doi:10.1139/x06-070

Postfire dynamics of black spruce coarse woody debris in northern boreal forest of Quebec

2006· article· en· W2057812161 on OpenAlexfundvenueaboutno aff
Yan Boulanger, Luc Sirois

Bibliographic record

VenueCanadian Journal of Forest Research · 2006
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicForest Ecology and Biodiversity Studies
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaFonds Québécois de la Recherche sur la Nature et les Technologies
KeywordsSnagChronosequenceCoarse woody debrisBlack spruceTaigaEnvironmental scienceWater contentNitrogenNitrogen cycleClearcuttingForest floorChemistryAgronomyEcologySoil scienceSoil waterBiologyGeology

Abstract

fetched live from OpenAlex

In this study, postfire coarse woody debris (CWD) dynamics in northern Quebec, Canada, were assessed using a 29-year chronosequence. Postfire woody-debris storage, decomposition rates, and variation of nitrogen and carbon contents of black spruce CWD (Picea mariana (Mill.) BSP) are estimated. The decomposition rate for postfire snags is exceptionally slow (k = 0.00), while the decomposition rate for logs (k = 0.019–0.021) is within previously recorded values for the boreal forest. The low decomposition rate for snags could be related to low moisture content associated with the position of debris and fast bark shedding. Given the low CWD decomposition rates and CWD storage (21.3–66.8 m 3 ·ha –1 ), carbon losses from postfire CWD are relatively low, varying between 35.5 and 128.8 kg·ha –1 ·year –1 at the study sites. The nitrogen content in CWD drops quickly between living trees and snags and increases slightly with time since fire in logs. Nitrogen content is not related to wood density or to moisture content of deadwood. Rapid loss of nitrogen is associated with fast decomposition of subcortical tissues, leaching, and insect comminution. The increase in nitrogen content at the oldest site could result from asymbiotic nitrogen fixation, although a longer time span in the chronosequence would probably have revealed a greater nitrogen gain in increasingly decayed CWD.

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 score0.318
Threshold uncertainty score0.364

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 studies0.0000.001
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 head0.025
GPT teacher head0.242
Teacher spread0.217 · 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

Citations71
Published2006
Admission routes3
Has abstractyes

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