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Record W2921812364 · doi:10.3389/fmicb.2019.00421

Succession of Composition and Function of Soil Bacterial Communities During Key Rice Growth Stages

2019· article· en· W2921812364 on OpenAlexaff
Wenhui Wang, Xue Luo, Chen Yang, Xianfeng Ye, Hui Wang, Zhe Cao, Wei Ran, Zhongli Cui

Bibliographic record

VenueFrontiers in Microbiology · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicMicrobial Community Ecology and Physiology
Canadian institutionsUniversity of Saskatchewan
FundersNational Natural Science Foundation of China
KeywordsEcological successionRipeningBiologyAgronomyStrawMicrobial population biologyManureFertilizerEcologyBotanyBacteria

Abstract

fetched live from OpenAlex

Elucidating the succession of soil microbial communities and microbial functions at key plant growth stages is a major goal of microbial ecology research. In this study, we investigated the succession of soil bacteria during four fertilizer treatments (control, NPK, NPK + pig manure and NPK + straw) and at three crucial rice growth stages (tillering, heading and ripening) in paddy soil from a rice-wheat cropping system over a 10-year period. The results showed that the bacterial community and function composition of the control treatment was significantly different from that of the other treatments with NPK fertilizers, and S1 from others stages (ANOSIM, p < 0.05). The application of pig manure could reduce the effects of applying NPK fertilizers on bacterial communities in heading and ripening stages, but the effects of straw returning is not obvious. Variance partitioning analyses (VPA) suggested that pH, OM, and AK appeared to be key factors responsible for the microbial community changes observed in all the treatments or stages. The correlation results showed the bacterial families different between S1 and other stages such as Micromonosporaceae, Nocardioidaceae, Gaiellaceae and Anaerolineaceae etc., were correlated with bacterial KEGG metabolic pathways. In addition, the topological of the soil bacterial community network with more nodes, links and higher Maximal degree at the heading stage and maintained relatively similar topological structures at the heading and ripening stages. However, the topological of the functional networks at the ripening stage were a small yet complicated co-occurring network with 209 nodes, 789 links, higher Average connectivity (avgK) and Maximal degree. These results suggest an obvious succession of soil bacteria and bacterial function at the key rice growth stages, but the topological of functional network structure of bacteria changes a little in the early and middle stages of rice, while its changes significantly in the ripening stage of rice growth.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.572
Threshold uncertainty score0.835

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)0.0010.000

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 head0.004
GPT teacher head0.183
Teacher spread0.178 · 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

Citations53
Published2019
Admission routes1
Has abstractyes

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