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Record W2140272910 · doi:10.1139/x10-054

Litter degradation rate and β-glucosidase activity increase with fungal diversity

2010· article· en· W2140272910 on OpenAlexvenueno aff
David LeBauer

Bibliographic record

VenueCanadian Journal of Forest Research · 2010
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicForest Ecology and Biodiversity Studies
Canadian institutionsnot available
FundersNational Science Foundation
KeywordsLitterPolyphenol oxidaseBiodiversityLigninBotanyBiologyOxidative enzymeDecompositionEcosystemCelluloseChemistryEcologyEnzymeBiochemistryPeroxidase

Abstract

fetched live from OpenAlex

Declining biodiversity is a critical component of global change owing to its influence on ecosystem functioning. Decomposition rate frequently increases with fungal species number, but the responses of extracellular enzymes to fungal species number have not been tested. To test the effect of biodiversity on decomposition and enzyme activities, quaking aspen ( Populus tremuloides Michx.) litter was inoculated with mixtures of one, two, four, or eight fungi from a pool of 16 fungi that had been isolated from a boreal forest in Alaska. Total CO2 release and the activities of β-glucosidase, which targets cellulose, and polyphenol oxidase, which targets lignin and other recalcitrant phenolic compounds, were observed across the range of species numbers in the mixtures. Total CO2 release and β-glucosidase activity increased with number of species but were only weakly correlated with each other; polyphenol oxidase activity had no correlation with number of species or CO2 release. The results indicate that, over 4 months, decomposition of labile carbon is positively correlated with number of species.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.039
GPT teacher head0.243
Teacher spread0.203 · 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 source (direct Gemma or distilled Codex), 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

Citations31
Published2010
Admission routes1
Has abstractyes

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