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Record W2053592632 · doi:10.1080/1943815x.2012.702673

Relationships between methane emissions and soil microorganisms in a double-rice field in southern subtropical China

2012· article· en· W2053592632 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

VenueJournal of Integrative Environmental Sciences · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoil Carbon and Nitrogen Dynamics
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsMethanePaddy fieldEnvironmental scienceTillageStrawConventional tillageAgronomyAnaerobic digestionChemistryBiology

Abstract

fetched live from OpenAlex

Methane is produced in anaerobic environments by obligate anaerobic microorganisms through the decomposition of organic matters. To investigate the regression relationships between methane emissions and soil microbes in a double-rice paddy under various field practices, a two-year study was conducted to investigate the seasonal variation of methane emissions and the total activities of soil microbes (TASM) as well as the populations of methanogens (PMET) using the static closed-chamber-GC (gas chromatography) and the most probable number methods. Seven management practices were included in this study to look at the average effect of field treatments on methane emissions and TASM as well as PMET, viz. CWS (conventional tillage + without straw residues + urea), NWS (no tillage + without straw residues + urea), SCU (conventional tillage + without straw residues + controlled-release urea), HN (high stubbles + no tillage + urea), HC (high stubbles + conventional tillage + urea), SN (straw cover + no tillage + urea) and SNF (straw cover + no tillage + urea + continuous flooding). The daily average values of methane emissions and TASM as well as PMET from seven treatments were used for the analysis. Regression analysis was conducted using the R statistical software. Different field practices have significant effect on methane flux and TASM and PMET and similar seasonal variations of methane flux and TASM as well as PMET were found during the rice-growing seasons. Pronounced positive correlations between methane flux and TASM, and PMET were observed. Such relationships can be well described by the exponential or quadratic polynomial models, respectively. Regression analysis indicated that PMET could explain individually at least 97% of variance of methane flux (R2 = 0.97, P < 0.001), while the fitting precision of multiple nonlinear regression model for methane flux with two predictors of TASM and PMET was slightly higher than the univariate regression analysis (R2 = 0.98, P < 0.001). However, as we know, methane emissions from paddy soils are affected by many factors, of which TASM and PMET are the most direct influential variants. In order to reasonably reveal the interactions between methane emissions and environmental factors, the multivariate nonlinear regression analysis should be carried out based on data derived from the extensive field experiments rather than few laboratory trials.

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)0.001
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 score0.092
Threshold uncertainty score0.174

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.027
GPT teacher head0.245
Teacher spread0.218 · 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