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Record W4368376976 · doi:10.7717/peerj.15239

Dynamics of bacterial and archaeal communities during horse bedding and green waste composting

2023· article· en· W4368376976 on OpenAlexafffund
Vanessa Grenier, Emmanuel González, Nicholas J. B. Brereton, Frédéric E. Pitre

Bibliographic record

VenuePeerJ · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicComposting and Vermicomposting Techniques
Canadian institutionsEspace pour la vieMcGill UniversityMcGill Genome CentreUniversité de Montréal
FundersFonds de recherche du Québec – Nature et technologiesNatural Sciences and Engineering Research Council of CanadaMitacs
KeywordsCompostGreen wasteOrganic matterLitterAbundance (ecology)Microbial population biologyRelative species abundanceBiodegradable wasteBiologyChemistryAgronomyEcologyBacteria

Abstract

fetched live from OpenAlex

Organic waste decomposition can make up substantial amounts of municipal greenhouse emissions during decomposition. Composting has the potential to reduce these emissions as well as generate sustainable fertilizer. However, our understanding of how complex microbial communities change to drive the chemical and biological processes of composting is still limited. To investigate the microbiota associated with organic waste decomposition, initial composting feedstock (Litter), three composting windrows of 1.5 months (Young phase), 3 months (Middle phase) and 12 months (Aged phase) old, and 24-month-old mature Compost were sampled to assess physicochemical properties, plant cell wall composition and the microbial community using 16S rRNA gene amplification. A total of 2,612 Exact Sequence Variants (ESVs) included 517 annotated as putative species and 694 as genera which together captured 57.7% of the 3,133,873 sequences, with the most abundant species being Thermobifida fusca , Thermomonospora chromogena and Thermobifida bifida . Compost properties changed rapidly over time alongside the diversity of the compost community, which increased as composting progressed, and multivariate analysis indicated significant variation in community composition between each time-point. The abundance of bacteria in the feedstock is strongly correlated with the presence of organic matter and the abundance of plant cell wall components. Temperature and pH are the most strongly correlated parameters with bacterial abundance in the thermophilic and cooling phases/mature compost respectively. Differential abundance analysis revealed 810 ESVs annotated as species significantly varied in relative abundance between Litter and Young phase, 653 between the Young and Middle phases, 1182 between Middle and Aged phases and 663 between Aged phase and mature Compost. These changes indicated that structural carbohydrates and lignin degrading species were abundant at the beginning of the thermophilic phase, especially members of the Firmicute and Actinobacteria phyla. A high diversity of species capable of putative ammonification and denitrification were consistently found throughout the composting phases, whereas a limited number of nitrifying bacteria were identified and were significantly enriched within the later mesophilic composting phases. High microbial community resolution also revealed unexpected species which could be beneficial for agricultural soils enriched with mature compost or for the deployment of environmental and plant biotechnologies. Understanding the dynamics of these microbial communities could lead to improved waste management strategies and the development of input-specific composting protocols to optimize carbon and nitrogen transformation and promote a diverse and functional microflora in mature compost.

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 score0.838
Threshold uncertainty score0.342

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 head0.028
GPT teacher head0.240
Teacher spread0.212 · 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

Citations2
Published2023
Admission routes2
Has abstractyes

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