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Record W2038075847 · doi:10.3390/f4041141

White Spruce Plantations on Abandoned Agricultural Land: Are They More Effective as C Sinks than Natural Succession?

2013· article· en· W2038075847 on OpenAlexaffabout
Sylvie Tremblay, Rock Ouimet

Bibliographic record

VenueForests · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicForest Ecology and Biodiversity Studies
Canadian institutionsMinistère des Ressources naturelles et des Forêts (Québec)
Fundersnot available
KeywordsChronosequenceEcological successionVegetation (pathology)LitterEnvironmental scienceForestrySoil carbonAgronomyBiomass (ecology)Plant litterRangelandSoil waterAgroforestryEcologyNutrientGeographyBiologySoil science

Abstract

fetched live from OpenAlex

The objective of this study was to compare organic carbon (C) accumulation in plantations (PL) and natural succession (NS) established on fallow lands along a 50-year chronosequence in the eastern mixed forest subzone of Quebec (Canada). Above- and below-ground woody biomass were estimated from vegetation measurement surveys, and litter and soil (0–50 cm depth) C from samplings. At the year of abandonment, total C content of both PL and NS sites averaged 100 ± 13 Mg C ha−1. Over 50 years, total C content doubled on NS sites and tripled on PL sites (217.9 ± 28.7 vs. 285.7 ± 31.0 Mg ha−1) with respect to fallow land. On NS sites, the new C stocks accumulated entirely in the vegetation. On PL sites, C accumulated mostly in the vegetation and to a lesser extent in the litter, whereas it decreased by a third in the soil. As a result, the net C accumulation rate was 1.7 ± 0.7 Mg ha−1 yr−1 greater on PL sites than on NS sites over 50 years. By the 23rd year, PL sites became greater net C sinks than NS sites in the fallow lands of the study area, even with the loss of soil C.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.007
GPT teacher head0.211
Teacher spread0.204 · 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.

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

Citations26
Published2013
Admission routes2
Has abstractyes

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