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Record W2733369329 · doi:10.3390/agriculture7070057

Grasslands and Croplands Have Different Microbial Biomass Carbon Levels per Unit of Soil Organic Carbon

2017· article· en· W2733369329 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAgriculture · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoil Carbon and Nitrogen Dynamics
Canadian institutionsBrandon University
Fundersnot available
KeywordsGrasslandSoil carbonBiomass (ecology)Environmental scienceSoil waterAgronomyTotal organic carbonSoil scienceEcologyBiology

Abstract

fetched live from OpenAlex

Primarily using cropped systems, previous studies have reported a positive linear relationship between microbial biomass carbon (MBC) and soil organic carbon (SOC). We conducted a meta-analysis to explore this relationship separately for grasslands and croplands using available literature. Studies were limited to those using fumigation–extraction for MBC for field samples. Trials were noted separately where records were distinct in space or time. Grasslands were naturally occurring, restored, or seeded. Cropping systems were typical of the temperate zone. MBC had a positive linear response to increasing SOC that was significant in both grasslands (p < 0.001; r2 = 0.76) and croplands (p < 0.001; r2 = 0.48). However, MBC increased 2.5-fold more steeply per unit of increasing SOC for grassland soils, as compared to the corresponding response in cropland soils. Expressing MBC as a proportion of SOC across the regression overall, slopes corresponded to 2.7% for grasslands and 1.1% for croplands. The slope of the linear relationship for grasslands was significantly (p = 0.0013) steeper than for croplands. The difference between the two systems is possibly caused by a greater proportion of SOC in grasslands being active rather than passive, relative to that in croplands, with that active fraction promoting the formation of MBC.

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.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.684
Threshold uncertainty score0.999

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 head0.016
GPT teacher head0.210
Teacher spread0.194 · 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