MétaCan
Menu
Back to cohort
Record W2033567868 · doi:10.3390/f6020416

Stand Dynamics, Humus Type and Water Balance Explain Aspen Long Term Productivity across Canada

2015· article· en· W2033567868 on OpenAlexafffundabout
Kenneth A. Anyomi, François Lorenzetti, Yves Bergeron, Alain Leduc

Bibliographic record

VenueForests · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicForest ecology and management
Canadian institutionsUniversité du Québec en OutaouaisUniversité du Québec en Abitibi-TémiscamingueUniversité du Québec à MontréalNatural Sciences and Engineering Research Council of Canada
FundersMitacs
KeywordsProductivityEnvironmental scienceHumusContext (archaeology)Site indexDeciduousEcologyEcosystemLitterCanopyGeographySoil waterSoil scienceBiology

Abstract

fetched live from OpenAlex

This study examined the relative importance of soil, stand development and climate hypotheses in driving productivity for a species that is widely distributed in North America. Inventory plots, 3548 of such, either dominated by aspen or made up of species mixture of which aspen occurs in dominant canopy position were sampled along a longitudinal gradient from Quebec to British Columbia. Site index (SI), was used as a measure of productivity, and soil, climate and stand attributes were correlated with site index in order to determine their effects on productivity. Results show a decline in productivity with high moisture deficit. Soil humus correlates significantly with SI but does not sufficiently capture differential rates of litter deposition and decomposition effects over the long-term. Consequently, aspen composition, stand ageing, and stand structural changes dominate variability in productivity. Within the context where deciduous cover has being increasing, there are implications for forest productivity.

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 score0.902
Threshold uncertainty score0.928

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 studies0.0000.000
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 head0.009
GPT teacher head0.226
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

Citations8
Published2015
Admission routes3
Has abstractyes

Explore more

Same venueForestsSame topicForest ecology and managementFrench-language works237,207